<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Archiving and Interchange DTD with MathML3 v1.3 20210610//EN"  "JATS-archivearticle1-3-mathml3.dtd"><article xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" dtd-version="1.3"><front><journal-meta><journal-id journal-id-type="nlm-ta">elife</journal-id><journal-id journal-id-type="publisher-id">eLife</journal-id><journal-title-group><journal-title>eLife</journal-title></journal-title-group><issn publication-format="electronic" pub-type="epub">2050-084X</issn><publisher><publisher-name>eLife Sciences Publications, Ltd</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">101388</article-id><article-id pub-id-type="doi">10.7554/eLife.101388</article-id><article-id pub-id-type="doi" specific-use="version">10.7554/eLife.101388.3</article-id><article-version article-version-type="publication-state">version of record</article-version><article-categories><subj-group subj-group-type="display-channel"><subject>Research Article</subject></subj-group><subj-group subj-group-type="heading"><subject>Microbiology and Infectious Disease</subject></subj-group></article-categories><title-group><article-title>Quantification of <italic>Salmonella enterica</italic> serovar Typhimurium population dynamics in murine infection using a highly diverse barcoded library</article-title></title-group><contrib-group><contrib contrib-type="author" equal-contrib="yes"><name><surname>Hotinger</surname><given-names>Julia A</given-names></name><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="fn" rid="equal-contrib1">†</xref><xref ref-type="fn" rid="con1"/><xref ref-type="fn" rid="conf1"/></contrib><contrib contrib-type="author" equal-contrib="yes"><name><surname>Campbell</surname><given-names>Ian W</given-names></name><contrib-id authenticated="true" contrib-id-type="orcid">https://orcid.org/0000-0003-3019-2560</contrib-id><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="fn" rid="equal-contrib1">†</xref><xref ref-type="other" rid="fund2"/><xref ref-type="other" rid="fund4"/><xref ref-type="fn" rid="con2"/><xref ref-type="fn" rid="conf1"/></contrib><contrib contrib-type="author"><name><surname>Hullahalli</surname><given-names>Karthik</given-names></name><contrib-id authenticated="true" contrib-id-type="orcid">https://orcid.org/0000-0003-3064-2090</contrib-id><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="other" rid="fund3"/><xref ref-type="fn" rid="con3"/><xref ref-type="fn" rid="conf1"/></contrib><contrib contrib-type="author"><name><surname>Osaki</surname><given-names>Akina</given-names></name><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="fn" rid="con4"/><xref ref-type="fn" rid="conf1"/></contrib><contrib contrib-type="author" corresp="yes"><name><surname>Waldor</surname><given-names>Matthew K</given-names></name><contrib-id authenticated="true" contrib-id-type="orcid">https://orcid.org/0000-0003-1843-7000</contrib-id><email>mwaldor@research.bwh.harvard.edu</email><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="aff" rid="aff3">3</xref><xref ref-type="other" rid="fund1"/><xref ref-type="fn" rid="con5"/><xref ref-type="fn" rid="conf1"/></contrib><aff id="aff1"><label>1</label><institution-wrap><institution-id institution-id-type="ror">https://ror.org/04b6nzv94</institution-id><institution>Division of Infectious Diseases, Brigham &amp; Women's Hospital</institution></institution-wrap><addr-line><named-content content-type="city">Boston</named-content></addr-line><country>United States</country></aff><aff id="aff2"><label>2</label><institution>Department of Microbiology, Harvard Medical School</institution><addr-line><named-content content-type="city">Boston</named-content></addr-line><country>United States</country></aff><aff id="aff3"><label>3</label><institution-wrap><institution-id institution-id-type="ror">https://ror.org/006w34k90</institution-id><institution>Howard Hughes Medical Institute</institution></institution-wrap><addr-line><named-content content-type="city">Boston</named-content></addr-line><country>United States</country></aff></contrib-group><contrib-group content-type="section"><contrib contrib-type="editor"><name><surname>Kana</surname><given-names>Bavesh D</given-names></name><role>Reviewing Editor</role><aff><institution-wrap><institution-id institution-id-type="ror">https://ror.org/03rp50x72</institution-id><institution>University of the Witwatersrand</institution></institution-wrap><country>South Africa</country></aff></contrib><contrib contrib-type="senior_editor"><name><surname>Kana</surname><given-names>Bavesh D</given-names></name><role>Senior Editor</role><aff><institution-wrap><institution-id institution-id-type="ror">https://ror.org/03rp50x72</institution-id><institution>University of the Witwatersrand</institution></institution-wrap><country>South Africa</country></aff></contrib></contrib-group><author-notes><fn fn-type="con" id="equal-contrib1"><label>†</label><p>These authors contributed equally to this work</p></fn></author-notes><pub-date publication-format="electronic" date-type="publication"><day>13</day><month>02</month><year>2025</year></pub-date><volume>13</volume><elocation-id>RP101388</elocation-id><history><date date-type="sent-for-review" iso-8601-date="2024-08-09"><day>09</day><month>08</month><year>2024</year></date></history><pub-history><event><event-desc>This manuscript was published as a preprint.</event-desc><date date-type="preprint" iso-8601-date="2024-06-29"><day>29</day><month>06</month><year>2024</year></date><self-uri content-type="preprint" xlink:href="https://doi.org/10.1101/2024.06.28.601246"/></event><event><event-desc>This manuscript was published as a reviewed preprint.</event-desc><date date-type="reviewed-preprint" iso-8601-date="2024-10-10"><day>10</day><month>10</month><year>2024</year></date><self-uri content-type="reviewed-preprint" xlink:href="https://doi.org/10.7554/eLife.101388.1"/></event><event><event-desc>The reviewed preprint was revised.</event-desc><date date-type="reviewed-preprint" iso-8601-date="2025-02-03"><day>03</day><month>02</month><year>2025</year></date><self-uri content-type="reviewed-preprint" xlink:href="https://doi.org/10.7554/eLife.101388.2"/></event></pub-history><permissions><copyright-statement>© 2024, Hotinger, Campbell et al</copyright-statement><copyright-year>2024</copyright-year><copyright-holder>Hotinger, Campbell et al</copyright-holder><ali:free_to_read/><license xlink:href="http://creativecommons.org/licenses/by/4.0/"><ali:license_ref>http://creativecommons.org/licenses/by/4.0/</ali:license_ref><license-p>This article is distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License</ext-link>, which permits unrestricted use and redistribution provided that the original author and source are credited.</license-p></license></permissions><self-uri content-type="pdf" xlink:href="elife-101388-v1.pdf"/><self-uri content-type="figures-pdf" xlink:href="elife-101388-figures-v1.pdf"/><abstract><p>Murine models are often used to study the pathogenicity and dissemination of the enteric pathogen <italic>Salmonella enterica</italic> serovar Typhimurium. Here, we quantified <italic>S</italic>. Typhimurium population dynamics in mice using the STAMPR analytic pipeline and a highly diverse <italic>S</italic>. Typhimurium barcoded library containing ~55,000 unique strains distinguishable by genomic barcodes by enumerating <italic>S</italic>. Typhimurium founding populations and deciphering routes of spread in mice. We found that a severe bottleneck allowed only one in a million cells from an oral inoculum to establish a niche in the intestine. Furthermore, we observed compartmentalization of pathogen populations throughout the intestine, with few barcodes shared between intestinal segments and feces. This severe bottleneck widened and compartmentalization was reduced after streptomycin treatment, suggesting the microbiota plays a key role in restricting the pathogen’s colonization and movement within the intestine. Additionally, there was minimal sharing between the intestine and extraintestinal organ populations, indicating dissemination to extraintestinal sites occurs rapidly, before substantial pathogen expansion in the intestine. Bypassing the intestinal bottleneck by inoculating mice via intravenous or intraperitoneal injection revealed that <italic>Salmonella</italic> re-enters the intestine after establishing niches in extraintestinal sites by at least two distinct pathways. One pathway results in a diverse intestinal population. The other re-seeding pathway is through the bile, where the pathogen is often clonal, leading to clonal intestinal populations and correlates with gallbladder pathology. Together, these findings deepen our understanding of <italic>Salmonella</italic> population dynamics.</p></abstract><kwd-group kwd-group-type="author-keywords"><kwd><italic>Salmonella enterica</italic> serovar Typhimurium</kwd><kwd>infectious disease</kwd><kwd>microbial population dynamics</kwd><kwd>barcode lineage tracing</kwd><kwd>population bottleneck</kwd><kwd>disseminated bacterial infection</kwd></kwd-group><kwd-group kwd-group-type="research-organism"><title>Research organism</title><kwd>Mouse</kwd><kwd>Other</kwd></kwd-group><funding-group><award-group id="fund1"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100000060</institution-id><institution>National Institute of Allergy and Infectious Diseases</institution></institution-wrap></funding-source><award-id>R01 AI042347</award-id><principal-award-recipient><name><surname>Waldor</surname><given-names>Matthew K</given-names></name></principal-award-recipient></award-group><award-group id="fund2"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100000062</institution-id><institution>National Institute of Diabetes and Digestive and Kidney Diseases</institution></institution-wrap></funding-source><award-id>P30 DK034854</award-id><principal-award-recipient><name><surname>Campbell</surname><given-names>Ian W</given-names></name></principal-award-recipient></award-group><award-group id="fund3"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100000060</institution-id><institution>National Institute of Allergy and Infectious Diseases</institution></institution-wrap></funding-source><award-id>F31 AI156949</award-id><principal-award-recipient><name><surname>Hullahalli</surname><given-names>Karthik</given-names></name></principal-award-recipient></award-group><award-group id="fund4"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100000062</institution-id><institution>National Institute of Diabetes and Digestive and Kidney Diseases</institution></institution-wrap></funding-source><award-id>T32 DK007477-37</award-id><principal-award-recipient><name><surname>Campbell</surname><given-names>Ian W</given-names></name></principal-award-recipient></award-group><funding-statement>The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.</funding-statement></funding-group><custom-meta-group><custom-meta specific-use="meta-only"><meta-name>Author impact statement</meta-name><meta-value>Microbial lineage tracing during murine systemic infection with <italic>Salmonella</italic> uncovered the bottlenecks that restrict colonization and the hidden routes of interorgan dissemination that drive heterogeneity in infection outcomes.</meta-value></custom-meta><custom-meta specific-use="meta-only"><meta-name>publishing-route</meta-name><meta-value>prc</meta-value></custom-meta></custom-meta-group></article-meta></front><body><sec id="s1" sec-type="intro"><title>Introduction</title><p><italic>Salmonella enterica</italic> is a foodborne pathogen that causes hundreds of millions of infections and over 150,000 deaths worldwide each year (<xref ref-type="bibr" rid="bib28">Lamichhane et al., 2024</xref>). Its over 2000 serovars are divided into human-restricted typhoidal serovars (i.e. Typhi) that cause typhoid fever, a disseminated bacterial infection, and non-typhoidal serovars (e.g. Typhimurium) that are typically limited to intestinal disease in humans. There is, however, a growing number of extraintestinal infections caused by non-typhoidal serovars (<xref ref-type="bibr" rid="bib42">Worley, 2023</xref>).</p><p><italic>Salmonella</italic> is an extremely versatile pathogen capable of replicating both outside of and within host cells in a variety of animal hosts (<xref ref-type="bibr" rid="bib35">Ruby et al., 2012</xref>; <xref ref-type="bibr" rid="bib9">Coombes et al., 2005</xref>; <xref ref-type="bibr" rid="bib18">Higginson et al., 2016</xref>). <italic>Salmonella</italic> has two primary pathogenicity islands (SPI-1 and SPI-2), which facilitate infection in humans and are required for colonization and disease in mice (<xref ref-type="bibr" rid="bib15">Fierer et al., 2012</xref>; <xref ref-type="bibr" rid="bib29">Li, 2022</xref>; <xref ref-type="bibr" rid="bib46">Zhang et al., 2018</xref>), one of the most commonly used model hosts for studying <italic>Salmonella</italic> pathogenesis (<xref ref-type="bibr" rid="bib43">Xu and Hsu, 1992</xref>). In C57BL/6 J mice, <italic>Salmonella enterica</italic> serovar Typhimurium (<italic>S</italic>. Typhimurium) causes a disseminated infection. This murine model has helped to reveal that the pathogen employs numerous virulence factors to drive multiple interconnected mechanisms for escaping from the intestine to reach systemic organs.</p><p>Identifying changes in the frequency of genomic barcodes in otherwise identical bacteria throughout infection is a powerful tool for monitoring pathogen population dynamics in experimental models of infection. However, previous studies using barcoded <italic>Salmonella</italic> to study population dynamics during dissemination were limited in their resolution because they used a small number of barcodes (&lt;30 unique barcodes; <xref ref-type="bibr" rid="bib25">Kaiser et al., 2013</xref>; <xref ref-type="bibr" rid="bib26">Kaiser et al., 2014</xref>; <xref ref-type="bibr" rid="bib13">Dybowski et al., 2015</xref>; <xref ref-type="bibr" rid="bib27">Lam and Monack, 2014</xref>; <xref ref-type="bibr" rid="bib17">Grant et al., 2008</xref>; <xref ref-type="bibr" rid="bib14">Dybowski et al., 2017</xref>), hampering their capacity to measure bottlenecks, the host barriers to infection. These advances notwithstanding, we lack a granular understanding of <italic>Salmonella</italic> population dynamics in murine hosts that can be provided by evaluating the quantity, diversity, and similarity of barcoded <italic>Salmonella</italic> populations across many organs.</p><p>Inspired by previous work, we created an <italic>S</italic>. Typhimurium library containing over 55,000 unique barcodes and used the STAMPR (Sequence Tag-based Analysis of Microbial Populations in R) analytical framework (<xref ref-type="bibr" rid="bib22">Hullahalli et al., 2021</xref>; <xref ref-type="bibr" rid="bib1">Abel et al., 2015</xref>) to quantify the host bottlenecks restricting <italic>Salmonella</italic> colonization and dissemination. STAMPR enables the calculation of the size of the founding population, which represents the number of bacterial cells from the inoculum that survive the bottleneck and give rise to the observed population. In addition, the STAMPR analysis pipeline can determine the relative similarity of bacterial populations at different sites within the same animal by comparing the frequency and identity of barcodes. The quantification of both founding populations and similarity between populations can reveal new insights into host bottlenecks to infection and unexpected patterns of bacterial spread within the host (<xref ref-type="bibr" rid="bib22">Hullahalli et al., 2021</xref>; <xref ref-type="bibr" rid="bib1">Abel et al., 2015</xref>; <xref ref-type="bibr" rid="bib20">Holmes et al., 2025</xref>; <xref ref-type="bibr" rid="bib45">Zhang et al., 2017</xref>; <xref ref-type="bibr" rid="bib8">Chevée et al., 2024</xref>; <xref ref-type="bibr" rid="bib2">Bachta et al., 2020</xref>; <xref ref-type="bibr" rid="bib7">Campbell et al., 2023</xref>).</p><p>Here, oral administration of the <italic>S</italic>. Typhimurium barcoded library revealed that a tight bottleneck restricts <italic>S</italic>. Typhimurium intestinal colonization. Furthermore, we observed compartmentalized subpopulations within the intestine that did not intermix or contribute to the pathogen population shed in the feces. Disrupting the microbiota prior to inoculation by pretreating mice with streptomycin significantly relaxed the severe intestinal colonization bottleneck and increased sharing between intestinal and fecal bacterial populations, demonstrating the importance of the microbiome in protecting against infection and indicating the microbiome has a role in restricting the movement of <italic>S</italic>. Typhimurium within the intestine. Comparing intestinal <italic>S</italic>. Typhimurium populations to disseminated populations in other tissues, we discovered that <italic>S</italic>. Typhimurium dissemination occurs without the need to establish a replicative niche in the intestine, consistent with a previously presented hypothesis (<xref ref-type="bibr" rid="bib41">Watson and Holden, 2010</xref>). Bypassing the intestine by administering <italic>S</italic>. Typhimurium by intravenous (IV) or intraperitoneal (IP) injection nearly eliminated the bottleneck to colonizing extraintestinal sites, suggesting the primary bottleneck to colonizing these sites occurs within or while exiting the intestine. Furthermore, comparisons of the <italic>S</italic>. Typhimurium populations in the bile and intestine following IV and IP inoculation revealed that bile from the gallbladder is one source of bacteria for intestinal re-seeding, a phenomenon observed in humans with recurrent infections (<xref ref-type="bibr" rid="bib10">Crawford et al., 2010</xref>; <xref ref-type="bibr" rid="bib36">Shrout, 2012</xref>). These observations provide a strong foundation for further work defining the mechanisms and dynamics of <italic>Salmonella</italic> spread during infection.</p></sec><sec id="s2" sec-type="results"><title>Results</title><sec id="s2-1"><title>Streptomycin treatment widens the bottleneck impeding <italic>Salmonella</italic> intestinal colonization</title><p>Streptomycin pretreatment is often used to sensitize mice to <italic>S</italic>. Typhimurium orogastric infection. This antibiotic reduces the microbiota and is thought to heighten the pathogen burden and consistency of intestinal colonization (<xref ref-type="bibr" rid="bib5">Bohnhoff et al., 1954</xref>). We orogastrically administered 10<sup>8</sup> colony-forming units (CFU) of a barcoded <italic>S</italic>. Typhimurium library into 8-week-old untreated and streptomycin-treated C57BL/6 J mice to investigate how streptomycin pretreatment modifies <italic>S</italic>. Typhimurium population dynamics. We monitored common markers of disease and colitis during infection (<xref ref-type="fig" rid="fig1s1">Figure 1—figure supplement 1</xref>). Consistent with previous reports (<xref ref-type="bibr" rid="bib5">Bohnhoff et al., 1954</xref>; <xref ref-type="bibr" rid="bib38">Stecher et al., 2006</xref>; <xref ref-type="bibr" rid="bib3">Barthel et al., 2003</xref>), the streptomycin-treated animals lost weight more rapidly than animals that were not streptomycin-treated and were sacrificed on day 4 post-inoculation (dpi), after they had lost &gt;20% of their body weight (<xref ref-type="fig" rid="fig1">Figure 1A</xref>). Fecal shedding of <italic>S</italic>. Typhimurium gradually increased in untreated mice. In contrast, animals pretreated with streptomycin rapidly and uniformly began shedding <italic>S</italic>. Typhimurium, with fecal burdens higher than the inoculum by 24 hr post-inoculation and sustained throughout the experiment (<xref ref-type="fig" rid="fig1">Figure 1B</xref>).</p><fig-group><fig id="fig1" position="float"><label>Figure 1.</label><caption><title><italic>S.</italic> Typhimurium burden following orogastric inoculation of untreated or streptomycin-treated mice.</title><p>(<bold>A</bold>) Percentage of initial weight over time; means and standard deviations are shown. (<bold>B</bold>) Bacterial fecal burden. Box and whisker plots represent max-to-min and interquartile ranges. (<bold>C</bold>) Bacterial burden in organs and fluids. Open circles indicate when the whole gallbladder was used instead of bile. Box and whisker plots represent max-to-min and interquartile ranges. Untreated n=16 (8 males and 8 females), streptomycin (SM) pretreated n=5 (female) unless otherwise noted. Sex-disaggregated data in <xref ref-type="fig" rid="fig3s2">Figure 3—figure supplement 2</xref>. Mann-Whitney tests were used for statistical analyses. Values with p&lt;0.1 shown. Abbreviations: Adipose, left perigonadal adipose tissue; MLN, mesenteric lymph node; PP, Peyer’s patches; SI, small intestine; wash, peritoneal wash.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-101388-fig1-v1.tif"/></fig><fig id="fig1s1" position="float" specific-use="child-fig"><label>Figure 1—figure supplement 1.</label><caption><title>Weight of cecum (<bold>A</bold>) and colon (<bold>B</bold>) after different infection schemes.</title><p>Mann-Whitney tests were used for statistical analyses.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-101388-fig1-figsupp1-v1.tif"/></fig></fig-group><p>We measured <italic>S</italic>. Typhimurium burden in 12 organs/fluids at 4 (+SM) or 5 (untreated/-SM) days post-inoculation, while they were at the peak of disease. Organs/tissues were classified into three groups based on the pathogen burden and differences between the streptomycin-treated and untreated animals (<xref ref-type="fig" rid="fig1">Figure 1Ci–iii</xref>). The gastrointestinal (GI) tract organs, including the proximal and distal small intestine (SI), cecum, colon, and Peyer’s patches (PP), are presumed to be the initial site of infection after orogastric inoculation and generally had 100–10,000-fold higher burden in streptomycin-treated animals (<xref ref-type="fig" rid="fig1">Figure 1Ci</xref>); also, there was much more variation in pathogen burdens within the GI tracts of untreated animals. In contrast, in the extraintestinal immune-rich organs, such as the mesenteric lymph node (MLN), spleen, and liver, the <italic>S</italic>. Typhimurium burdens and variation in burden were similar in the two groups (<xref ref-type="fig" rid="fig1">Figure 1Cii</xref>). In the remaining organs and fluids, including the bile, pancreas, perigonadal adipose tissue (‘adipose’), and peritoneal wash (‘wash’), bacterial burdens were generally lower than in other tissues, except for bile, and the burdens in treated and untreated animals were similar. Together, these observations reveal that although streptomycin treatment markedly elevates the <italic>S</italic>. Typhimurium burden in the GI tract, it does not appear to significantly alter the pathogen burden at sites beyond the intestine.</p><p>Counting the number of <italic>S</italic>. Typhimurium cells within an organ does not directly measure the bottleneck, the bacterial population encountered in establishing its niche because bacterial replication obscures the effects of bottlenecks (i.e. the observed population is the net outcome of a bottleneck followed by replication and migration from other sites). To directly measure the bottleneck impeding intestinal colonization, the experiments described above were carried out with genomically barcoded <italic>S</italic>. Typhimurium. We introduced neutral tags into our <italic>S</italic>. Typhimurium population by integrating short ~25 base pair sequences (barcodes) into the genome on a Tn7 transposon, resulting in a library of ~55,000 strains that are isogenic except for their barcodes (<xref ref-type="bibr" rid="bib22">Hullahalli et al., 2021</xref>; <xref ref-type="bibr" rid="bib1">Abel et al., 2015</xref>). These barcodes can be detected by amplicon sequencing and changes in the abundance and frequencies of barcodes in the library allow us to determine the number of unique cells from the inoculum that gave rise to the observed population, referred to as the ‘founding population’ or ‘founders’. The number of founders is estimated using the STAMPR analytical pipeline by a metric called Ns, which employs a multinomial resampling strategy to determine the sampling depth required to observe a specific number of barcodes given the distribution of barcodes in the inoculum (<xref ref-type="bibr" rid="bib22">Hullahalli et al., 2021</xref>). The size of the founding population in an organ and its barcode diversity reflects the bottleneck experienced by the inoculum, with tighter bottlenecks resulting in fewer unique barcodes than wider bottlenecks (<xref ref-type="fig" rid="fig2">Figure 2A</xref>). Before performing animal experiments, we determined the resolution of STAMPR analysis with our library by creating experimental bottlenecks in a culture of the <italic>S</italic>. Typhimurium library by plating serial dilutions and found that our calculations accurately predicted the number of colony-forming units (which can be considered the true size of the founding population) up to ~700,000 CFU (<xref ref-type="fig" rid="fig2s1">Figure 2—figure supplement 1</xref>).</p><fig-group><fig id="fig2" position="float"><label>Figure 2.</label><caption><title>The bottleneck to <italic>S</italic>. Typhimurium intestinal colonization in orogastrically inoculated mice is widened after streptomycin treatment.</title><p>(<bold>A</bold>) Schematic depicting the effect of a tight versus wide bottleneck on a diverse inoculum and the STAMPR analytical methods used to calculate the founding population (FP) and compare populations at separate sites of infection using genetic distance (GD) analysis. (<bold>B</bold>) Founding populations (Ns) of intestinal samples. Truncated violin plot with all points shown. (<bold>C</bold>) CFU per founder (CFU/Ns) in intestinal tissues. Bars are geometric means and geometric standard deviations. (<bold>D</bold>) Heatmaps of average genetic distance comparisons throughout the GI tract in untreated (left) and streptomycin-treated (right) mice. (<bold>E</bold>) Comparison of genetic distance of GI tract to fecal samples. Mann-Whitney tests were used for statistical analyses. Values with p&lt;0.1 shown. Abbreviations: PP, Peyer’s patches; SI, small intestine; SM, streptomycin.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-101388-fig2-v1.tif"/></fig><fig id="fig2s1" position="float" specific-use="child-fig"><label>Figure 2—figure supplement 1.</label><caption><title><italic>S.</italic> Typhimurium barcoded library diversity and standard curve.</title><p>(<bold>A</bold>) Barcodes in <italic>S</italic> Typhimurium library were mapped to the barcodes in the donor library (pSM1) and the frequency of barcodes in the <italic>S</italic>. Typhimurium library were distributed relatively evenly. (<bold>B</bold>) Calibration curve indicating the library has an Ns resolution limit of ~7 × 10<sup>5</sup>. (<bold>C</bold>) Growth of barcoded STAMP library in LB supplemented with SM is not different than the parent strain (SL1344). Significance was tested with Mann-Whitney test and growth curves were performed 5 times. Curves displayed with 50% opacity.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-101388-fig2-figsupp1-v1.tif"/></fig><fig id="fig2s2" position="float" specific-use="child-fig"><label>Figure 2—figure supplement 2.</label><caption><title>Barcodes from different regions of the intestine and Peyer’s patches from a single animal are largely distinct.</title><p>(<bold>A</bold>) Barcode frequencies of different regions of the intestine and (<bold>B</bold>) individual Peyer’s patches (PP) of an untreated mouse after orogastric gavage of <italic>S</italic>. Typhimurium. “Remaining PP” sample contains the PP from the animal not taken for individual analysis. Frequencies of barcodes are displayed as heatmaps (each box represents a barcode and darker colors represent increased frequency within the sample) and sorted by abundance in each sample sequentially.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-101388-fig2-figsupp2-v1.tif"/></fig></fig-group><p>There was considerable variation in <italic>S</italic>. Typhimurium founding population (Ns) sizes in untreated animals (<xref ref-type="fig" rid="fig2">Figure 2B</xref>), reflecting inter-animal variation in the bottleneck to intestinal colonization, which likely accounts for the variable timing and quantity of fecal shedding observed in this model (<xref ref-type="fig" rid="fig1">Figure 1B</xref>). In most parts of the intestine of untreated mice, there were only ~10<sup>2</sup> unique founders (<xref ref-type="fig" rid="fig2">Figure 2B</xref>), suggesting that at this dose (10<sup>8</sup> CFU) there is a severe intestinal colonization bottleneck that reduces the inoculum population by about ~10<sup>6</sup>-fold. Streptomycin treatment widened this bottleneck considerably, increasing the founding population by 10–100-fold in all regions of the intestine (<xref ref-type="fig" rid="fig2">Figure 2B</xref>). This increased founding population following streptomycin treatment demonstrates that streptomycin clearance of the microbiota and its downstream consequences, such as inflammation (<xref ref-type="bibr" rid="bib5">Bohnhoff et al., 1954</xref>), removes some of the barriers to <italic>S</italic>. Typhimurium establishing a replicative niche in the intestine.</p><p>Streptomycin treatment increased both the total <italic>S</italic>. Typhimurium burden (<xref ref-type="fig" rid="fig1">Figure 1Ci</xref>) and the number of founders (<xref ref-type="fig" rid="fig2">Figure 2B</xref>) in the intestine. Replication of founders generally accounts for the majority of the burden in most tissues. The average net expansion of the population can be measured by dividing bacterial burden by the founding population (CFU/Ns). This calculation revealed that there is generally more net expansion in streptomycin-treated versus untreated animals (<xref ref-type="fig" rid="fig2">Figure 2C</xref>); that is, the increase in CFU following streptomycin treatment is caused by both increased number of founders and increased net replication. These observations suggest that streptomycin treatment not only widens the bottleneck impeding <italic>S</italic>. Typhimurium colonization (increased founders) but also creates a more permissive niche for pathogen population expansion.</p></sec><sec id="s2-2"><title>Streptomycin treatment decreases compartmentalization of <italic>S</italic>. Typhimurium populations within the intestine</title><p>The STAMPR analytical pipeline enables comparison of barcoded bacterial populations sampled from different sites within the same animal. The similarity in the frequency of barcodes between organs is quantified with a metric of genetic distance (<xref ref-type="fig" rid="fig2">Figure 2A</xref>; <xref ref-type="bibr" rid="bib1">Abel et al., 2015</xref>). Organs containing barcodes with indistinguishable proportions have a genetic distance (GD) of zero, while those that do not share barcodes have a genetic distance of nearly one (see Materials and methods). We compared the similarity of barcode frequencies in samples from different intestinal regions. Except for the cecum and colon, in untreated animals the <italic>S</italic>. Typhimurium populations in different regions of the intestine were dissimilar (Avg. GD ranged from 0.369 to 0.729, 2D left); that is, there is little sharing between populations in the intestine. These data suggest that there are separate bottlenecks in different regions of the intestine that cause stochastic differences in the identity of the founders. Interestingly, when these founders replicate, they do not mix, remaining compartmentalized with little sharing between populations throughout the intestinal tract (i.e. barcodes found in one region are not in other regions; <xref ref-type="fig" rid="fig2s2">Figure 2—figure supplement 2</xref>). This was surprising as the luminal contents, an environment presumably conducive to bacterial movement, were not removed from these samples. Further supporting this compartmentalized population hypothesis is the lack of barcode overlap between individual Peyer’s patches taken from the proximal, medial, and distal small intestine of an individual mouse (<xref ref-type="fig" rid="fig2s2">Figure 2—figure supplement 2</xref>). Streptomycin treatment increased the similarity in <italic>S</italic>. Typhimurium populations derived from different parts of the intestine (Avg. GD ranged from 0.157 to 0.407, <xref ref-type="fig" rid="fig2">Figure 2D</xref> right), suggesting that reduction of the microbiota through streptomycin pretreatment increases the mixing of the populations between the intestinal compartments.</p><p><italic>S</italic>. Typhimurium is primarily transmitted through the feces. We attempted to identify the origin from within the intestinal tract of fecal <italic>S</italic>. Typhimurium through genetic distance comparisons of fecal samples to different regions of the intestine. Unexpectedly, in approximately half of the untreated animals, the fecal barcodes were highly dissimilar from the barcodes present in all regions of the intestine (GD &gt;0.75; <xref ref-type="fig" rid="fig2">Figure 2E</xref>), indicating that the majority of the <italic>S</italic>. Typhimurium population at intestinal sites are not being shed into the feces. In contrast, mice treated with streptomycin had similar populations in intestinal and fecal samples (Avg. GD = 0.299 ± 0.06; <xref ref-type="fig" rid="fig2">Figure 2D</xref>), reflecting an increase in sharing between these populations. Thus, STAMPR-based analysis of the high-density barcoded <italic>S</italic>. Typhimurium library enabled quantitative assessments of intestinal bottlenecks and revealed that streptomycin treatment markedly alters the compartmentalization of <italic>S</italic>. Typhimurium replication in the intestine and the source of the pathogen shed in the feces.</p></sec><sec id="s2-3"><title><italic>S</italic>. Typhimurium disseminates out of the intestine before establishing an intestinal replicative niche</title><p>In mice, <italic>S</italic>. Typhimurium routinely spreads out of the intestine to colonize extraintestinal organs. In the intestine, streptomycin treatment increased <italic>S</italic>. Typhimurium burdens by 100–10,000-fold relative to untreated animals. In contrast, streptomycin treatment did not markedly increase the burden of <italic>S</italic>. Typhimurium in systemic organs (<xref ref-type="fig" rid="fig1">Figure 1Cii–iii</xref>). Nevertheless, barcode analysis revealed that streptomycin treatment increased the size of the founding population in extraintestinal organs by ~10-fold (<xref ref-type="fig" rid="fig3">Figure 3A</xref>), suggesting that the net bottleneck to dissemination is relaxed by streptomycin treatment, likely contributing to the more rapid disease progression observed in streptomycin-treated animals (<xref ref-type="fig" rid="fig1">Figure 1A</xref>). However, since the founding population is calculated based on the abundance of barcodes in an organ sample at sacrifice, it is difficult to discern if streptomycin treatment modifies the net bottleneck to dissemination by relaxing the individual bottlenecks to reaching the intestine, colonizing the intestine, disseminating from the intestine, and/or establishing a niche in extraintestinal organs.</p><fig-group><fig id="fig3" position="float"><label>Figure 3.</label><caption><title><italic>S.</italic> Typhimurium disseminates from the intestine before substantial replication.</title><p>(<bold>A</bold>) Founding populations and (<bold>C</bold>) genetic distance from the liver after orogastric inoculation (Gavage) of <italic>S</italic>. Typhimurium with (+SM) or without (-SM) streptomycin pretreatment. (<bold>B</bold>) Scheme depicting proposed dissemination patterns during infection. (<bold>D–F</bold>) Organ CFUs (<bold>D</bold>), founding populations (<bold>E</bold>), and genetic distance from the liver (<bold>F</bold>) after inoculation via drinking (+SM, Drinking) are not statistically different from orogastric gavage (+SM, Gavage). Data for +SM, gavage mice repeated from <xref ref-type="fig" rid="fig1">Figures 1</xref>—<xref ref-type="fig" rid="fig3">3</xref>. (<bold>G–H</bold>) Organ CFUs (<bold>G</bold>) and founding populations (<bold>H</bold>) in untreated mice at 5 or 120 hr after inoculation. 120 hr data repeated from <xref ref-type="fig" rid="fig1">Figures 1</xref>—<xref ref-type="fig" rid="fig3">3</xref>. +SM, Drinking n=5, untreated 5 hr n=5. Mann-Whitney tests were used for statistical analyses. Values with p&lt;0.1 shown. Abbreviations: GD, genetic distance; GI, gastrointestinal; MLN, mesenteric lymph node; PP, Peyer’s patches; SI, small intestine.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-101388-fig3-v1.tif"/></fig><fig id="fig3s1" position="float" specific-use="child-fig"><label>Figure 3—figure supplement 1.</label><caption><title><italic>S.</italic> Typhimurium disseminates to the MLN and spleen prior to substantial replication in the intestine.</title><p>Genetic distance from the MLN (<bold>A</bold>) and spleen (<bold>B</bold>) after orogastric inoculation of <italic>S</italic>. Typhimurium with (+SM) or without (-SM) streptomycin pretreatment. -SM n=16 (8 males and 8 females),+SM n=5 (female). Mann-Whitney tests were used for statistical analyses. Values with p&lt;0.1 shown. Abbreviations: GI, gastrointestinal; MLN, mesenteric lymph node; PP, Peyer’s patches; SI, small intestine.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-101388-fig3-figsupp1-v1.tif"/></fig><fig id="fig3s2" position="float" specific-use="child-fig"><label>Figure 3—figure supplement 2.</label><caption><title>Sex-disaggregated data in mice inoculated through orogastric gavage.</title><p>(<bold>A</bold>) Percentage of initial weight over time; means and standard deviations shown. (<bold>B</bold>) Bacterial burden in feces. (<bold>C</bold>) Bacterial burden in organs and fluids, open circles indicate when the whole gallbladder was taken instead of bile. (<bold>D</bold>) Founding populations (Ns) in organs and fluids. Geometric means and geometric standard deviations are used unless otherwise noted. -SM female n=8, -SM male n=8.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-101388-fig3-figsupp2-v1.tif"/></fig><fig id="fig3s3" position="float" specific-use="child-fig"><label>Figure 3—figure supplement 3.</label><caption><title>Extended data for streptomycin pretreated mice inoculated through orogastric gavage and drinking.</title><p>(<bold>A</bold>) Percentage of initial weight over time; means and standard deviations shown. (<bold>B</bold>) Bacterial burden in feces. (<bold>C</bold>) Bacterial burden in organs and fluids, open circles indicate when the whole gallbladder was taken instead of bile. (<bold>D</bold>) Founding populations (Ns) in organs and fluids. Geometric means and geometric standard deviations are used unless otherwise noted. +SM, Gavage female n=5, and +SM, Drinking female n=5. Mann-Whitney tests were used for statistical analyses. Values with p&lt;0.1 shown.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-101388-fig3-figsupp3-v1.tif"/></fig></fig-group><p>To gain further insight into when <italic>S</italic>. Typhimurium disseminates to extraintestinal sites, we compared the similarity of barcodes found in <italic>S</italic>. Typhimurium isolated from the liver to those in the intestine. The similarity between the initial site of infection (in this case the intestine) and secondary sites differentiates whether the secondary population arose soon after inoculation, before the population experienced the profound intestinal bottleneck (‘early’ in <xref ref-type="fig" rid="fig3">Figure 3B</xref>), or at a later point, after the initial bottlenecks and subsequent replication (‘late’ in <xref ref-type="fig" rid="fig3">Figure 3B</xref>; <xref ref-type="bibr" rid="bib20">Holmes et al., 2025</xref>). We expect that early spread would yield dissimilar barcode frequencies between intestinal and extraintestinal sites, whereas, with late spread, there would be greater barcode similarity in the two populations. Genetic distance comparison of liver samples to other sites revealed that, regardless of streptomycin treatment, there was very little sharing of barcodes between the intestine and extraintestinal sites (Avg. GD &gt;0.75, <xref ref-type="fig" rid="fig3">Figure 3C</xref>). Furthermore, the MLN and spleen populations also lacked similarity with the intestine (<xref ref-type="fig" rid="fig3s1">Figure 3—figure supplement 1</xref>). These analyses strongly support the idea that <italic>S</italic>. Typhimurium disseminates to extraintestinal organs relatively early following inoculation, before it establishes a replicative niche in the intestine.</p><p>It is possible that orogastric gavage can cause trauma to the esophagus that may result in the introduction of bacteria to the bloodstream during inoculation (<xref ref-type="bibr" rid="bib30">Nilsson et al., 2019</xref>), potentially giving rise to the independent populations observed in the intestine and extraintestinal sites (‘direct’ in <xref ref-type="fig" rid="fig3">Figure 3B</xref>). To exclude the possibility that we unintentionally introduced the pathogen into circulation through orogastric gavage, streptomycin-treated mice were administered water containing 10<sup>8</sup> CFU of the <italic>S</italic>. Typhimurium barcoded library in their oral cavity and allowed to drink (+SM, drinking). These animals showed highly similar weight loss and fecal shedding patterns as observed in streptomycin-treated mice orogastrically gavaged (+SM, Gavage) with the same dose of <italic>S</italic>. Typhimurium (<xref ref-type="fig" rid="fig3s3">Figure 3—figure supplement 3</xref>). Furthermore, the bacterial burdens in the intestine and extraintestinal organs were indistinguishable regardless of the method of oral inoculation (<xref ref-type="fig" rid="fig3">Figure 3D</xref>).</p><p>Drinking and orogastric gavage also yielded very similar founding population sizes in all organs (<xref ref-type="fig" rid="fig3">Figure 3E</xref>). The similarity in number of founders suggests that the two inoculums experienced indistinguishable bottlenecks, an unlikely event if orogastric gavage led to routine bloodstream inoculation. Moreover, changing oral administration from orogastric gavage to drinking did not impact the lack of similarity between <italic>S</italic>. Typhimurium barcodes present in liver samples and other organs (<xref ref-type="fig" rid="fig3">Figure 3F</xref>). Together, these observations provide strong support for the idea that that orogastric gavage did not routinely lead to tissue damage that enables <italic>S</italic>. Typhimurium entry into the bloodstream. Instead, these data buttress the idea that <italic>S</italic>. Typhimurium disseminates from the intestine to extraintestinal organs early in the infection, sometime after oral inoculation and prior to significant intestinal replication.</p><p>To confirm our hypothesis that <italic>S</italic>. Typhimurium disseminates from the intestine to extraintestinal organs early in the infection, we sacrificed untreated mice 5 hr after orogastric inoculation with ~10<sup>8</sup> S. Typhimurium. Even at this early timepoint,~100 <italic>S</italic>. Typhimurium CFU were found in liver samples (<xref ref-type="fig" rid="fig3">Figure 3G</xref>), indicating that the pathogen transits out of the intestine to the liver within 5 hr. At this point, there were also ~100 founders present in the liver samples, suggesting that little, if any, replication had occurred (~1 CFU per founder). Notably, the number of liver founders at 5 hr was similar to the number of founders observed at 5 days (120 hr, <xref ref-type="fig" rid="fig3">Figure 3H</xref>), consistent with the idea that dissemination of <italic>S</italic>. Typhimurium from the intestine to the liver establishes the pathogen population that subsequently undergoes considerable replication. Furthermore, the barcodes present in liver samples were not present in any other samples. Together, these data suggest the initial rapid dissemination from the intestine seeds the majority of clones in the liver that are observed at later time points. In contrast to the liver, there were more founders present in samples from the intestine (particularly in the colon) at 5 hr versus 120 hr (<xref ref-type="fig" rid="fig3">Figure 3H</xref>). These data likely indicate that many of the founders observed in the intestine at 5 hr are shed in the feces prior to establishing a replicative niche, and demonstrates that the forces restricting the <italic>S</italic>. Typhimurium population in the intestine act over a period of &gt;5 hr.</p></sec><sec id="s2-4"><title>The primary bottleneck to <italic>S</italic>. Typhimurium extraintestinal infection occurs within or while the pathogen exits the intestine</title><p>The net bottleneck to <italic>S</italic>. Typhimurium spreading to extraintestinal organs following oral inoculation is a combination of individual bottlenecks, including barriers the pathogen encounters within the GI tract, escaping from the intestine, traveling to extraintestinal organs, and establishing a niche at extraintestinal sites. The proportional contribution of each of these bottlenecks is unknown. It is possible that they play equal roles or that one constitutes the majority of the net bottleneck. To further probe how the size of the founding population in extraintestinal organs is impacted by the bottlenecks <italic>S</italic>. Typhimurium experiences within or while exiting the intestine, we bypassed the intestinal bottleneck by administering the barcoded <italic>S</italic>. Typhimurium library intraperitoneally (IP) and intravenously (IV; <xref ref-type="fig" rid="fig4">Figure 4A</xref>), routes that have been used to model the pathogen’s interactions with the immune system in extraintestinal infections (<xref ref-type="bibr" rid="bib42">Worley, 2023</xref>; <xref ref-type="bibr" rid="bib17">Grant et al., 2008</xref>). Lower doses of 10<sup>4</sup> (IP) and 10<sup>3</sup> (IV) CFU were used to avoid rapid death (<xref ref-type="bibr" rid="bib43">Xu and Hsu, 1992</xref>). In addition, infections via orogastric gavage were performed at a dose of 10<sup>4</sup> CFU both with and without streptomycin pretreatment to facilitate direct comparison between inoculation routes (<xref ref-type="fig" rid="fig4">Figure 4A</xref>).</p><fig-group><fig id="fig4" position="float"><label>Figure 4.</label><caption><title><italic>S.</italic> Typhimurium population dynamics following different routes of inoculation.</title><p>(<bold>A</bold>) Infections were performed via 3 routes: orogastric gavage with (Oral +SM) or without (Oral -SM) streptomycin pretreatment, intraperitoneal injection (IP), and intravenous injection (IV). (<bold>B–C</bold>) Bacterial burden (<bold>B</bold>) and founding populations (<bold>C</bold>) in immune-rich extraintestinal organs. (<bold>D–E</bold>) Bacterial burden (<bold>D</bold>) and founding population (<bold>E</bold>) in extraintestinal samples. (<bold>F</bold>) Heatmaps of average genetic distance between extraintestinal organs after IP (top) and IV (bottom) inoculation. Box and whisker plots represent max-to-min and interquartile ranges. Truncated violin plots with all points displayed. Oral -SM n=5, Oral +SM n=4, IP n=16 (8 male, 8 female), IV n=16 (8 male, 8 female). Sex-disaggregated data in <xref ref-type="fig" rid="fig4s1">Figure 4—figure supplement 1</xref>. Mann-Whitney tests were used for statistical analyses. Values with p&lt;0.1 shown. Abbreviations: MLN, mesenteric lymph node.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-101388-fig4-v1.tif"/></fig><fig id="fig4s1" position="float" specific-use="child-fig"><label>Figure 4—figure supplement 1.</label><caption><title>Sex-disaggregated data in mice after inoculation with 10<sup>3</sup>–10<sup>4</sup> CFU <italic>S</italic>.Typhimurium through different routes.</title><p>(<bold>A</bold>) Percentage of initial weight over time; means and standard deviations shown. (<bold>B</bold>) Sex-disaggregated bacterial burden in feces. (<bold>C</bold>) Bacterial burden in organs and fluids. (<bold>D</bold>) Founding populations (Ns) in organs and fluids. Geometric means and geometric standard deviations are used unless otherwise noted. Oral -SM female n=5, Oral +SM n=5, IP male n=8, IP female n=8, IV male n=8, and IV female n=8. Statistical analysis is a Mann-Whitney test. Values with p&lt;0.1 are shown.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-101388-fig4-figsupp1-v1.tif"/></fig><fig id="fig4s2" position="float" specific-use="child-fig"><label>Figure 4—figure supplement 2.</label><caption><title>Pathology observed in mouse adipose tissue.</title><p>(<bold>A</bold>) Images of uninfected adipose. (<bold>B</bold>) Images of white spots on mesenteric (top left), upper mesenteric (top right), perigonadal (bottom left) and perirenal (bottom right) adipose in mice. Yellow circles outline areas with pathology. Blue arrows point to focal lesions. Abbreviations: IV, intravenous; IP, intraperitoneal.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-101388-fig4-figsupp2-v1.tif"/></fig></fig-group><p>Without streptomycin treatment at this lower dose, orogastric gavage (Oral -SM) did not lead to extraintestinal infection. Furthermore, there was no detectable <italic>S</italic>. Typhimurium (and consequently zero founders) in all the organs sampled (<xref ref-type="fig" rid="fig4">Figure 4B–C</xref>), consistent with a bottleneck that completely eliminated the 10<sup>4</sup> cells in the inoculum either before <italic>S</italic>. Typhimurium escaped from the intestine or after spread from the intestine but prior to establishing a niche at extraintestinal sites. Moreover, these untreated mice did not exhibit any signs of disease, including diarrhea, lethargy, or weight loss (<xref ref-type="fig" rid="fig4s1">Figure 4—figure supplement 1</xref>). Thus, the net bottleneck to extraintestinal dissemination following orogastric inoculation results in less than 1 founder after inoculation of 10<sup>4</sup> CFU.</p><p>The pathogen burden and number of founders in immune-rich organs were highly similar following IV and IP inoculation (<xref ref-type="fig" rid="fig4">Figure 4B–C</xref>). Furthermore, the numbers of founders in these organs were similar to the size of the inoculum, suggesting that <italic>S</italic>. Typhimurium does not experience a significant bottleneck when colonizing immune-rich organs following IV and IP inoculation. In streptomycin-treated animals given 10<sup>4</sup> CFU by orogastric gavage, the pathogen burden and number of founders observed in immune-rich organs were ~10-fold lower than after IP and IV inoculation. These observations suggest that the net bottleneck that <italic>S</italic>. Typhimurium experiences while spreading from oral inoculation to extraintestinal immune-rich organs is tighter than the net bottleneck following either IV or IP inoculation. This additional ~10-fold constriction of the net bottleneck is likely contributed by the additional bottlenecks encountered by the pathogen in its route from oral inoculation to arrival in systemic organs, including escaping from the intestine.</p><p>Remarkably, even though most animals had a high <italic>S</italic>. Typhimurium burden in bile extracted from the gallbladder (<xref ref-type="fig" rid="fig4">Figure 4D</xref>), the number of founders was generally very low. Of animals with pathogen in the bile, more than half after all inoculation routes contained only a single founder (<xref ref-type="fig" rid="fig4">Figure 4E</xref>). The high frequency of clonality in the bile indicates the presence of a very tight bottleneck to colonization of the gallbladder. The factors that impede <italic>S</italic>. Typhimurium colonization of the gallbladder and bile are not clear, but once a single or a few bacterial cells take hold, they can replicate to yield a very high burden, with on average ~3 × 10<sup>6</sup> (IP) and ~9 × 10<sup>4</sup> (IV) CFU. Collectively, these observations support the hypothesis that the most restrictive bottleneck to <italic>S</italic>. Typhimurium dissemination occurs within or while the pathogen exits the intestine. However, spread to other organs, such as the gallbladder, are impeded by additional bottlenecks.</p></sec><sec id="s2-5"><title>Route of inoculation affects <italic>S</italic>. Typhimurium replication within and sharing among extraintestinal tissues</title><p>After IV and IP injection of <italic>S</italic>. Typhimurium there were similar burdens (<xref ref-type="fig" rid="fig4">Figure 4B</xref>) and founding population sizes (<xref ref-type="fig" rid="fig4">Figure 4C</xref>) in immune-rich organs. However, these routes yielded divergent outcomes at other sites. In the pancreas, perigonadal adipose tissue, and peritoneal washes, <italic>S</italic>. Typhimurium burdens were 100–1000-fold greater following IP versus IV inoculation (<xref ref-type="fig" rid="fig4">Figure 4D</xref>). Furthermore, at these sites, there was a trend toward more founders after IP inoculation (<xref ref-type="fig" rid="fig4">Figure 4E</xref>), although this trend may be explained by the 10-fold higher IP dose. Along with the increased pathogen burden, white lesions were also observed in the adipose tissue of many IP-inoculated and some IV-inoculated mice (<xref ref-type="fig" rid="fig4s2">Figure 4—figure supplement 2</xref>). We speculate that the increased <italic>S</italic>. Typhimurium burden may originate from replication in the lesions. Exclusively after IP inoculation, there was a considerably higher pathogen burden in these three extraintestinal samples (pancreas, perigonadal adipose, and peritoneal wash) than either the size of the inoculum or founding population, suggesting an increase in localized replication in the peritoneal cavity, the site of inoculation, and adjacent tissue.</p><p>Barcode comparisons revealed that there was a consistently high level of sharing between the spleen and liver after IP and IV inoculation of <italic>S</italic>. Typhimurium (Avg. GD &lt;0.25, <xref ref-type="fig" rid="fig4">Figure 4F</xref>), indicating the spleen and liver are within the same compartment. Previous studies suggest sharing between the liver and spleen is initially minimal but increases over time (<xref ref-type="bibr" rid="bib27">Lam and Monack, 2014</xref>; <xref ref-type="bibr" rid="bib17">Grant et al., 2008</xref>), consistent with early dissemination followed by sharing within the compartment as the infection progresses. After IP inoculation, however, the other extraintestinal sites were dissimilar to the liver/spleen compartment and each other, suggesting they represent separate compartments (GD &gt;0.5, <xref ref-type="fig" rid="fig4">Figure 4F</xref>, top). In contrast, following IV inoculation there was greater similarity (Avg. GD &lt;0.5, <xref ref-type="fig" rid="fig4">Figure 4F</xref>, bottom) between the <italic>S</italic>. Typhimurium populations in the liver/spleen compartment and those from the pancreas and adipose tissue (<xref ref-type="fig" rid="fig4">Figure 4F</xref>, more dark blue squares in the IV versus IP). Thus, these analyses of barcoded bacteria unveil how the route of inoculation can result in divergent population dynamics.</p></sec><sec id="s2-6"><title><italic>S</italic>. Typhimurium can re-seed the intestine through the bile</title><p>Orogastric gavage of 10<sup>4</sup> S. Typhimurium in streptomycin-treated animals resulted in high-level shedding (10<sup>10</sup> CFU/g) by 1 day after inoculation, likely reflecting a rapid blooming of the <italic>S</italic>. Typhimurium population in the intestine. In marked contrast, <italic>S</italic>. Typhimurium shedding was not observed until 4 days after IV or IP pathogen inoculation; at this point, fecal shedding was detected in 8/16 and 11/16 animals inoculated IP or IV, respectively (<xref ref-type="fig" rid="fig5">Figure 5A</xref>). In addition, the <italic>S</italic>. Typhimurium burden in intestinal samples was generally higher in streptomycin-treated animals inoculated by the orogastric route versus untreated animals receiving an IV or IP inoculum (<xref ref-type="fig" rid="fig5">Figure 5B</xref>). The presence of <italic>S</italic>. Typhimurium in the intestine and fecal shedding after systemic inoculation indicates that there are route(s) for <italic>S</italic>. Typhimurium to spread back into the intestine from extraintestinal organs. However, the absence of shedding in some animals and the marked delay in shedding after IP and IV relative to orogastric inoculation suggests that the <italic>S</italic>. Typhimurium population encounters substantial bottleneck(s) on the route(s) from extraintestinal sites back to the intestine.</p><fig id="fig5" position="float"><label>Figure 5.</label><caption><title><italic>S.</italic> Typhimurium population dynamics after IV and IP inoculation differ compared to those after oral gavage.</title><p>(<bold>A</bold>) Fecal shedding after orogastric gavage with (Oral +SM) or without (Oral -SM) streptomycin pretreatment, intraperitoneal injection (IP), and intravenous injection (IV) with <italic>S</italic>. Typhimurium. (<bold>B</bold>) Bacterial burdens in the intestine. Box and whisker plots represent max-to-min and interquartile ranges. (<bold>C</bold>) Founding population of GI organs. (<bold>D</bold>) Genetic distance comparison of colon samples of IV and IP animals to other sites disaggregated by number of colon founders. Means and standard deviations displayed. Mann-Whitney tests were used for statistical analyses. Values with p&lt;0.1 shown. Abbreviations: MLN, mesenteric lymph node; PP, Peyer’s patches; SI, small intestine.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-101388-fig5-v1.tif"/></fig><p>Notably, the number of founders in intestinal samples from animals inoculated IP or IV had a bimodal distribution (<xref ref-type="fig" rid="fig5">Figure 5C</xref>). In some animals, IV and IP inoculation resulted in very few or even only a single founder in intestinal samples (‘clonal’ group, n=9), indicating that the population that re-seeded the intestine had been affected by a severely restrictive bottleneck (<xref ref-type="fig" rid="fig5">Figure 5C</xref>). The remaining animals in the IV and IP groups with colon colonization (n=22) had a much larger number of founders, approaching the number observed in the immune-rich samples (<xref ref-type="fig" rid="fig4">Figure 4C</xref>), suggestive of a highly permissive bottleneck. Together, these data strongly suggest that there are at least two routes by which extraintestinal <italic>S</italic>. Typhimurium can return to the intestine; one route has little, if any, bottleneck and gives rise to a diverse population in the intestine and the other route includes a very tight bottleneck and often results in a clonal intestinal population.</p><p>Comparisons of the genetic distances showed that the IV and IP groups with clonal intestinal populations had the same clone (barcode) throughout their respective GI tracts (clonal colons GD = 0, <xref ref-type="fig" rid="fig5">Figure 5D</xref>). In contrast, colons with diverse populations had less similarity to other regions of the intestine. Comparisons of the barcode similarity of clonal colon samples to extraintestinal samples provided insight into the likely extraintestinal source of the intestinal clone. 7 of the 9 animals with clonal populations in the colon had bile samples with genetic distances of zero, indicating the presence of the same clone and strongly suggesting that the bile clone seeded the intestine through the common bile duct. However, even though most bile samples containing <italic>S</italic>. Typhimurium from IP/IV inoculated mice were clonal (14/26) or pauciclonal (5/26 with Ns = 2–10), most intestinal samples were not clonal, indicating that bile is often not the dominant extraintestinal site that seeds the intestine. Furthermore, clonal bile did not necessarily give rise to a dominant intestinal clone (<xref ref-type="fig" rid="fig6">Figure 6A</xref>, animals 1 and 2). Interestingly, the bottleneck that characterizes the more permissive route to seeding the intestine from extraintestinal sites was even more permissive than the bottleneck that the pathogen experiences following orogastric inoculation (i.e. Ns values for the permissive IP and IV groups were generally greater than those for the orogastric group, <xref ref-type="fig" rid="fig5">Figure 5C</xref>). We speculate that the re-seeding route leading to the diverse <italic>S</italic>. Typhimurium population in the intestine represents a reversal of known mechanisms the pathogen employs to escape from the intestine (<xref ref-type="bibr" rid="bib37">Silva-García et al., 2019</xref>).</p><fig-group><fig id="fig6" position="float"><label>Figure 6.</label><caption><title>Bile re-seeding the intestine is correlated with gallbladder pathology.</title><p>(<bold>A</bold>) Barcode frequency of clonal and diverse colons and bile in mice after IV inoculation. Asterisks indicate visible pathology in the bile. (<bold>B</bold>) Gross anatomy and (<bold>C</bold>) H&amp;E-stained sections of normal, dark, cloudy, and hardened bile after <italic>S</italic>. Typhimurium infection. Red arrows indicate the luminal side of the gallbladder. (<bold>D</bold>) CFU in bile after all infection routes disaggregated by bile phenotype. Box and whisker plots represent max-to-min and interquartile ranges. (<bold>E</bold>) FRD of bile barcodes also found in colon samples. Bars are means with standard deviations. (<bold>F</bold>) Fecal shedding correlates with bile burden when hardened or cloudy bile is present. Line of best fit displayed. Mann-Whitney tests were used for statistical analyses. Values with p&lt;0.1 shown.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-101388-fig6-v1.tif"/></fig><fig id="fig6s1" position="float" specific-use="child-fig"><label>Figure 6—figure supplement 1.</label><caption><title>Bile pathology correlates with the bile re-seeding pathway.</title><p>(<bold>A</bold>) Percentage of observed biliary pathology. (<bold>B</bold>) Founding population of bile disaggregated by biliary pathology. Abbreviations: IV, intravenous; IP, intraperitoneal; SM, streptomycin; SI, small intestine.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-101388-fig6-figsupp1-v1.tif"/></fig></fig-group></sec><sec id="s2-7"><title><italic>S</italic>. Typhimurium re-seeding the intestine through the bile correlates with gallbladder pathology</title><p>Unexpectedly, we observed that animals with clonal colon populations often had clonal bile populations as well as visible biliary pathology, such as darkening, cloudiness, or hardening (<xref ref-type="fig" rid="fig6">Figure 6A–B</xref>). We noticed that animals with diverse colon populations often had gallbladders and bile lacking any visible pathology, regardless of the bile’s clonality. This led us to further analyze the association of gallbladder/bile pathology with the bile-driven intestinal re-seeding pathway. Overall, there was a small chance for any gallbladder/bile phenotype in all the infection schemes we tested, but there was a lower rate of bile colonization in untreated orogastrically gavaged animals (n=2; <xref ref-type="fig" rid="fig6s1">Figure 6—figure supplement 1</xref>).</p><p>Analysis of aggregated data from all infection routes and doses showed that increased pathogen burden in bile correlated with cloudy or hardened biliary pathology (<xref ref-type="fig" rid="fig6">Figure 6D</xref>), but not darkened bile. Additionally, loss of biliary epithelial cells and marked cellular infiltrates were observed in cloudy and hardened bile samples (<xref ref-type="fig" rid="fig6">Figure 6C</xref>). Thus, cloudy and hardened biliary pathology either enables the growth of <italic>S</italic>. Typhimurium in the bile or, more likely, is the result of <italic>S</italic>. Typhimurium growth in the bile. Estimates of the fraction of barcodes that contribute to similarity between the bile and colon (FRD, see Materials and methods) revealed that a greater fraction of bile barcodes was shared with the colon in animals with cloudy and hardened bile samples compared to bile samples without pathology (<xref ref-type="fig" rid="fig6">Figure 6D</xref>). Collectively, these observations show that hardened or cloudy biliary pathology reflects robust <italic>S</italic>. Typhimurium replication in the gallbladder and is correlated with seeding of the intestine. Indeed, fecal shedding correlates with bile burden in animals with hardened or cloudy biliary pathology, but not with animals whose bile was darkened or lacked pathology (<xref ref-type="fig" rid="fig6">Figure 6F</xref>). Thus, STAMPR-based analyses uncovered an unexpected link between gallbladder pathology and bile-related intestinal re-seeding.</p></sec></sec><sec id="s3" sec-type="discussion"><title>Discussion</title><p><italic>S</italic>. Typhimurium is often used to model typhoidal disease in mice because it is highly adept at dissemination from the intestine, with a toolbox of diverse mechanisms to reach and replicate in extraintestinal organs. Previous studies of <italic>Salmonella</italic> population dynamics have been limited in resolution and focused on sites highly colonized by the pathogen, such as the cecum, feces, MLN, spleen, and liver (<xref ref-type="bibr" rid="bib25">Kaiser et al., 2013</xref>; <xref ref-type="bibr" rid="bib26">Kaiser et al., 2014</xref>; <xref ref-type="bibr" rid="bib13">Dybowski et al., 2015</xref>; <xref ref-type="bibr" rid="bib27">Lam and Monack, 2014</xref>; <xref ref-type="bibr" rid="bib17">Grant et al., 2008</xref>). We built upon these studies using a highly diverse library of barcoded bacteria containing over 55,000 unique tags, empowering us to quantify the size of the founding populations (<xref ref-type="bibr" rid="bib1">Abel et al., 2015</xref>) and increasing the resolution of our genetic distance calculations (<xref ref-type="bibr" rid="bib14">Dybowski et al., 2017</xref>). Additionally, we sampled a larger range of organs to evaluate the different patterns of dissemination and population compartmentalization after multiple inoculation routes and doses. With this complex barcoded library and the STAMPR analytical framework, we were able to observe the compartmentalization of the <italic>Salmonella</italic> population in the intestine, that dissemination out of the intestine occurs rapidly, and at least two distinct pathways re-seed the intestine.</p><p>Previous studies have used a limited number of unique barcodes (&lt;30) to quantify <italic>Salmonella</italic> population dynamics in mice. Here, we employ a library that is over 1000-fold more diverse than previously used. Although low diversity libraries can be used to measure bottlenecks and dissemination, higher diversity libraries are advantageous for several reasons. High diversity libraries increase the upper limit of founding population measurements. For example, a library containing only 10 barcodes has a resolution limit of ~200 founders, meaning it would be unable to distinguish between organs with founding populations larger than 200 (e.g. 1000 and 10,000), because both organs would likely contain all 10 barcodes. In contrast, a library with 10,000 barcodes can be used to distinguish between a bottleneck resulting in Ns = 1000 and Ns = 10,000, since these bottlenecks result in a different number of barcodes in output samples. Furthermore, high diversity libraries reduce the likelihood that two tissue samples share the same barcode(s) due to random chance, enabling more accurate quantification of bacterial dissemination. For example, our analysis distinguishing subpopulations of Peyer’s patches (<xref ref-type="fig" rid="fig2s2">Figure 2—figure supplement 2</xref>) would not have been possible with &lt;100 barcodes.</p><p>By evaluating the identity and frequency of barcoded <italic>S</italic>. Typhimurium populations at sites throughout the intestine, we observed the presence of separate compartments along the intestinal tract containing unique subpopulations after orogastric gavage of the pathogen. Streptomycin pretreatment reduced the compartmentalization of <italic>Salmonella</italic> populations in the intestine and correlated with increased barcode sharing between the intestine and shed bacteria. We propose two non-mutually exclusive mechanisms that could account for these observations: (1) an expansion of the replicative niche that produces fecal bacteria (e.g. increased luminal replication) and/or (2) increased escape of <italic>S</italic>. Typhimurium from niches that normally do not contribute to the fecal population (e.g. intracellular tissue-associated bacteria). Since streptomycin treatment has been shown to increase the CFU in the lumen of the intestine and increase fecal shedding with minimal effect on the number of bacteria able to invade the intestinal epithelium (<xref ref-type="bibr" rid="bib3">Barthel et al., 2003</xref>), the former idea seems more likely to be the major contributor.</p><p>In addition to finding distinct populations within the intestine, we also observed that the populations in extraintestinal organs were different from the populations in the intestine. The lack of similarity between intestinal and extraintestinal populations provides additional support for the idea that <italic>Salmonella</italic> disseminates from the intestine prior to substantial replication. Early dissemination is also supported by our discovery that the number of founders in the liver does not increase from 5 hr to 5 days post-inoculation, whereas the founding population in the intestine constricts during this period.</p><p>Among the extraintestinal organs, the liver and spleen often shared similar populations regardless of inoculation route. However, the route of inoculation influenced the sharing between <italic>S</italic>. Typhimurium populations from different organs. The IV and IP routes of inoculation yielded distinct patterns of sharing between the perigonadal adipose tissues, pancreas, and peritoneal wash. These two routes of inoculation are often considered interchangeable because they result in overall similar colonization and disease progression, but we found they lead to divergent patterns of pathogen population sharing between organs. This discovery illustrates the potency of our approach to unveil the impacts of infection route on pathogen spread.</p><p>Although our analyses cannot unequivocally prove the mechanisms <italic>S</italic>. Typhimurium employs to reach extraintestinal sites, evidence of known mechanisms are present in the STAMPR data. For example, the <italic>S</italic>. Typhimurium populations in the liver and MLN of untreated mice were somewhat similar (Avg. GD = 0.556 ± 0.139, <xref ref-type="fig" rid="fig3">Figure 3C</xref>), suggesting the lymphatic system, a well-characterized method of dissemination (<xref ref-type="bibr" rid="bib29">Li, 2022</xref>; <xref ref-type="bibr" rid="bib25">Kaiser et al., 2013</xref>; <xref ref-type="bibr" rid="bib6">Bravo-Blas et al., 2019</xref>), was at least one of the mechanisms used to reach the liver. Interestingly, streptomycin-treatment caused a ~10-fold increase in founders in the liver and spleen (<xref ref-type="fig" rid="fig3">Figure 3A</xref>), indicating a relaxed net bottleneck to dissemination. Concurrently, in streptomycin treated animals, the <italic>S</italic>. Typhimurium population in the liver became more dissimilar from the populations in the MLN (Avg. GD = 0.760 ± 0.056, <xref ref-type="fig" rid="fig3">Figure 3C</xref>), suggesting that the increase in founders reaching disseminated organs did not correlate with replication of these clones in the lymphatic system. Streptomycin treatment is known to increase intestinal inflammation, immune cell infiltration, and permeability of the intestinal epithelium (<xref ref-type="bibr" rid="bib34">Ray et al., 2022</xref>; <xref ref-type="bibr" rid="bib39">Strati et al., 2021</xref>; <xref ref-type="bibr" rid="bib4">Bazett et al., 2016</xref>), and the pathogen may take advantage of these indirect effects of streptomycin treatment to disseminate more efficiently, resulting in increased founders at extraintestinal sites (<xref ref-type="bibr" rid="bib42">Worley, 2023</xref>; <xref ref-type="bibr" rid="bib29">Li, 2022</xref>; <xref ref-type="bibr" rid="bib41">Watson and Holden, 2010</xref>; <xref ref-type="bibr" rid="bib16">Gogoi et al., 2019</xref>).</p><p>As an enteric pathogen spread through the feces, the most expedient method for <italic>Salmonella</italic> propagation and transmission would be for the pathogen to enter the intestine, replicate within the intestine, and be shed into the feces. However, as we have observed, the microbiota creates a significant bottleneck, constricting the inoculum ~10<sup>6</sup>-fold (<xref ref-type="fig" rid="fig2">Figure 2B</xref>), and preventing the majority of the intestinal population from shedding into the feces (<xref ref-type="fig" rid="fig2">Figure 2E</xref>). We propose that dissemination into extraintestinal organs, where <italic>Salmonella</italic> can replicate without competition with the microbiome, is an evolutionary boon for the pathogen. However, it creates a new challenge to bacterial transmission – re-entering the intestine to be shed in the feces. Using IP and IV inoculation, we were able to identify at least two routes by which <italic>Salmonella</italic> re-seeds the intestine. First, diverse populations can re-seed the intestine presumably by reversing known mechanisms of exit from the intestine (e.g. <italic>Salmonella</italic> infiltration through damaged intestinal epithelium outside of or within immune cells <xref ref-type="bibr" rid="bib29">Li, 2022</xref>). Second, a highly bottlenecked population can re-enter the intestine through the common bile duct.</p><p>The bile re-seeding pathway was correlated with cloudy or hardened biliary pathology, increased clonality in the colon, and very high bile pathogen burden. Previous studies have also observed that increased intestinal clonality in <italic>Salmonella</italic> populations at the peak of infection is correlated with increased shedding in a different strain of mice (<xref ref-type="bibr" rid="bib27">Lam and Monack, 2014</xref>), potentially due to bile re-seeding. It is tempting to speculate that the extremely high pathogen burden in the gallbladder in these mice accounts for both the gallbladder/bile pathology as well as the predilection for the bile clone to become dominant in the intestine. However, it is also possible that <italic>S</italic>. Typhimurium derived from a diseased biliary system has an enhanced capacity to become dominant in the intestine. Indeed, <italic>Salmonella</italic> has been previously shown to adapt to growth in bile through regulation of quorum sensing and virulence genes (<xref ref-type="bibr" rid="bib44">Yang et al., 2023</xref>; <xref ref-type="bibr" rid="bib40">Tsai et al., 2020</xref>; <xref ref-type="bibr" rid="bib24">Johnson et al., 2018</xref>). Notably, in experimental <italic>Listeria monocytogenes</italic> (<xref ref-type="bibr" rid="bib45">Zhang et al., 2017</xref>; <xref ref-type="bibr" rid="bib8">Chevée et al., 2024</xref>) and <italic>Psuedomonas auerginosa</italic> (<xref ref-type="bibr" rid="bib2">Bachta et al., 2020</xref>) infections in mice, clonal pathogen populations that replicate to a high burden in bile are also observed and routinely become the dominant clone in the intestine and feces. However, for all three pathogens, the mechanisms that underlie the highly restrictive gallbladder bottleneck remain unknown.</p><p>Long-term murine infections with <italic>Salmonella</italic> result in bile duct inflammation (<xref ref-type="bibr" rid="bib33">Pragasam et al., 2023</xref>; <xref ref-type="bibr" rid="bib12">Dowling, 2000</xref>), but to our knowledge no evidence of biliary inflammation after acute infection has been reported. <italic>Salmonella</italic> is also known to colonize gallbladder epithelia or the surface of gallstones in humans, often the source of pathogen in persistent <italic>Salmonella</italic> infections, and gallstone colonization has been shown to increase the risk of gallbladder cancer (<xref ref-type="bibr" rid="bib10">Crawford et al., 2010</xref>; <xref ref-type="bibr" rid="bib36">Shrout, 2012</xref>; <xref ref-type="bibr" rid="bib40">Tsai et al., 2020</xref>; <xref ref-type="bibr" rid="bib33">Pragasam et al., 2023</xref>). Of note, both <italic>Salmonella</italic> infection and gallstone formation in humans have increased risk in adult females in comparison to males (<xref ref-type="bibr" rid="bib32">Peer et al., 2021</xref>; <xref ref-type="bibr" rid="bib31">Novacek, 2006</xref>; <xref ref-type="bibr" rid="bib11">Dias et al., 2022</xref>). In our experiments, we observed a moderate increase in <italic>Salmonella</italic> disease markers, such as diarrhea, weight loss, and fecal shedding, in female mice in comparison to males (<xref ref-type="fig" rid="fig3s2">Figure 3—figure supplement 2</xref>; <xref ref-type="fig" rid="fig4s1">Figure 4—figure supplement 1</xref>). Moreover, 9/10 mice with hardened bile were female, suggesting a strong correlation of this phenotype with sex and point to a sex bias in the murine model as well.</p><p>The use of highly complex barcoded libraries sharpens analytic resolution to the point where pathogen spread within each individual animal is easily distinguishable and can uncover unexpected and potentially significant insights into pathogen population dynamics during infection. For example, we observed up to 1000-fold variation in the number of <italic>S</italic>. Typhimurium founders in much of the intestine in orogastrically gavaged untreated animals (<xref ref-type="fig" rid="fig2">Figure 2B</xref>), even though the mice were genetically identical, came from the same vendor, and often littermates. This variation was present between mice but not within mice, with individual mice having consistent founders (either high or low) throughout the GI tract. Investigating the mechanisms accounting for this dramatic inter-animal variation is possible with our approach and is of interest because such marked differences in bottlenecks can determine whether pathogen exposure leads to infection. In conclusion, the use of the STAMPR framework coupled with our highly diverse barcoded <italic>S</italic>. Typhimurium library has deepened our understanding of <italic>Salmonella</italic>’s highly interconnected and multidirectional dissemination cycle.</p></sec><sec id="s4" sec-type="materials|methods"><title>Materials and methods</title><table-wrap id="keyresource" position="anchor"><label>Key resources table</label><table frame="hsides" rules="groups"><thead><tr><th align="left" valign="bottom">Reagent type (species) or resource</th><th align="left" valign="bottom">Designation</th><th align="left" valign="bottom">Source or reference</th><th align="left" valign="bottom">Identifiers</th><th align="left" valign="bottom">Additional information</th></tr></thead><tbody><tr><td align="left" valign="bottom">Strain, strain background (<italic>Mus musculus</italic>)</td><td align="left" valign="bottom">C57BL/6 J</td><td align="left" valign="bottom">Jackson laboratory</td><td align="left" valign="bottom">Strain #:000664<break/>RRID:<ext-link ext-link-type="uri" xlink:href="https://identifiers.org/RRID:IMSR_JAX:000664">IMSR_JAX:000664</ext-link><break/></td><td align="left" valign="bottom">Mice</td></tr><tr><td align="left" valign="bottom">Strain, strain background (<italic>Salmonella enterica</italic> serovar Typhimurium)</td><td align="left" valign="bottom">SL1344</td><td align="left" valign="bottom"><xref ref-type="bibr" rid="bib19">Hoiseth and Stocker, 1981</xref></td><td align="left" valign="bottom">NCBI:txid216597</td><td align="left" valign="bottom">Bacterial strains</td></tr><tr><td align="left" valign="bottom">Software, algorithm</td><td align="left" valign="bottom">STAMPR scripts</td><td align="left" valign="bottom"><xref ref-type="bibr" rid="bib22">Hullahalli et al., 2021</xref>; <xref ref-type="bibr" rid="bib23">Hullahalli, 2024</xref></td><td align="left" valign="bottom"><ext-link ext-link-type="uri" xlink:href="https://github.com/hullahalli/stampr_rtisan">https://github.com/hullahalli/stampr_rtisan</ext-link></td><td align="left" valign="bottom">STAMP sample processing</td></tr></tbody></table></table-wrap><sec id="s4-1"><title>Mice</title><p>8-week-old female and male C57BL/6 J mice were purchased from Jackson laboratory. Mice were acclimatized in the biosafety level 2 (BSL2) facility at the Brigham and Women’s Hospital for at least 72 hr before use. The facility is temperature (68–75⁰F) and humidity (50%) controlled with 12  hr light/dark cycles. All experiments involving mice were performed according to protocols reviewed and approved by the Brigham and Women’s Hospital Institutional Animal Care and Use Committee (protocol 2016N000416) and in compliance with the Guide for the Care and Use of Laboratory Animals.</p></sec><sec id="s4-2"><title>Bacterial strains</title><p>A streptomycin-resistant strain of <italic>Salmonella enterica</italic> serovar Typhimurium SL1344 was used to create the barcoded library used here. Unless otherwise noted, <italic>S</italic>. Typhimurium was grown at 37 °C in LB broth or solid agar. As needed, media was supplemented with streptomycin (SM, 200 µg/ml) and/or kanamycin (KM, 50 µg/ml).</p></sec><sec id="s4-3"><title>STAMP library generation</title><p>The barcoded library was created using the pSM1 plasmid donor library, which contains &gt;70,000 barcodes, and helper pJMP1339, which contains the Tn7 transposon and conjugation/replication machinery, as described (<xref ref-type="bibr" rid="bib22">Hullahalli et al., 2021</xref>; <xref ref-type="bibr" rid="bib1">Abel et al., 2015</xref>; <xref ref-type="bibr" rid="bib20">Holmes et al., 2025</xref>; <xref ref-type="bibr" rid="bib45">Zhang et al., 2017</xref>; <xref ref-type="bibr" rid="bib8">Chevée et al., 2024</xref>; <xref ref-type="bibr" rid="bib2">Bachta et al., 2020</xref>; <xref ref-type="bibr" rid="bib7">Campbell et al., 2023</xref>). <italic>S</italic>. Typhimurium was heat shocked for 4 hr at 42 °C. A triparental conjugation was then used to introduce the pSM1 library into <italic>S</italic>. Typhimurium and transconjugants were selected for as SM- and KM-resistant colonies. Transconjugant colonies were pooled in PBS +20% glycerol and stored in aliquots at –80 °C. Illumina sequencing indicated the library contains ~55,000 unique barcodes with even distribution (<xref ref-type="fig" rid="fig2s1">Figure 2—figure supplement 1</xref>). The growth of the library in LB supplemented with SM was not significantly different than the parent strain (<xref ref-type="fig" rid="fig2s1">Figure 2—figure supplement 1</xref>). The resolution limit of STAMPR analysis with our library was ~700,000 founders; this was demonstrated through creation of a standard curve, comparing the true founding population (CFU following plating of a serially diluted culture) versus the calculated founding population (<xref ref-type="fig" rid="fig2s1">Figure 2—figure supplement 1</xref>).</p></sec><sec id="s4-4"><title>Mouse infection</title><p>The barcoded <italic>S</italic>. Typhimurium library was prepared by resuspending a frozen aliquot in LB and expanding for 3–5 hr at 37 °C with shaking unless otherwise noted. OD<sub>600</sub> was used to estimate the size of bacterial population in the culture before use. Following growth, bacteria were pelleted and resuspended in 1 x sterile PBS to the appropriate concentration (orogastric gavage 10<sup>9</sup> or 10<sup>5</sup> CFU/ml; oral via drinking 5x10<sup>9</sup> CFU/ml; IP 10<sup>5</sup> CFU/ml; IV 10<sup>4</sup> CFU/ml) and stored at room temperature prior to inoculation.</p><p>Streptomycin sulfate (100 μl of 200 mg/ml, United States Pharmacopeia grade) was given by orogastric gavage 24 hr before gavage with bacteria. Mice were deprived of food for 2–4 hr before orogastric gavage and given light sedation with isoflurane inhalation immediately prior to gavage. 100 μl inocula were gavaged into the stomach using a 1 ml syringe and sterile 18 G, 1.5-inch, 2 mm ball, flexible feeding needles (Braintree Scientific). Before oral inoculation via drinking, mice were deprived of food for 8 hr. 20 μl inocula were pipetted into the mouth of scruffed mice, who were then observed to ensure consumption. For IP infections, mice were restrained by a scruff, then a 1 ml syringe with a sterile 27 G, 1-inch needle was inserted into the lower right quadrant of the animal’s abdomen at a –45 degree angle, and 100 μl inoculum was injected. Before IV inoculation, mice were placed into small containers on a heating pad to help promote tail vein dilation and restrained with a Broome-style restrainer (Plas Labs). 100 μl inocula were injected into the lateral tail vein using a sterile 27 G needle.</p><p>Bacterial counts were enumerated for all inoculums using serial dilutions on LB agar supplemented with SM. Mice were monitored daily for signs of infection including weight loss, fecal shedding, and diarrhea. Mice with weight loss of &lt;5%, indicative of lack of disease, were excluded from further analysis (orogastric gavage -SM after 10<sup>8</sup> CFU n=2, IP n=3).</p></sec><sec id="s4-5"><title>Necropsy</title><p>At the peak of the disease (4- or 5 days post-inoculation), at 5 hr post-inoculation, or as needed per the humane endpoint in our animal protocol, mice were sacrificed by isoflurane overdose followed by cervical dislocation. Peritoneal washes were obtained by injecting 5 ml sterile PBS into the peritoneal cavity of the animal with a 27 G needle and clamping the hole shut before gently massaging the abdomen for ~30 s before aspirating the wash from the peritoneal cavity. When possible, bile was obtained from the gallbladder with a 31 G short-needle insulin syringe (Sol-M, VWR) and aspirated into 90 μl sterile PBS. The gallbladder was then removed before harvesting the liver and other organs. If bile was not obtainable, the whole gallbladder was placed into a 1.5 ml tube containing 1 ml sterile PBS and 2x3.3 mm stainless steel balls and processed. All other organs (perigonadal adipose tissue, cecum, colon, distal third and proximal third of the small intestine, Peyer’s patches, mesenteric lymph nodes, pancreas, liver, and spleen) were removed and individually placed into 1.5 ml tubes containing 1 ml sterile PBS (5 ml tube and 4 ml PBS for liver) and 2x3.3 mm stainless steel balls and then homogenized using a bead beater (Biospec Products). CFU of all organs was enumerated by serial dilution plating on LB agar containing SM. The remaining sample homogenate was plated on large LB agar plates containing SM for processing before sequencing to enumerate barcode frequency.</p></sec><sec id="s4-6"><title>Histology</title><p>The tissue samples were fixed in 4% paraformaldehyde in PBS and dehydrated in 20% sucrose in PBS. The dehydrated tissue was then embedded in OCT compound and sectioned to 10 µm. The sectioned slides were stained with hematoxylin and eosin (Abcam, #ab245880), washed with distilled water, and captured using Olympus Slideview VS200 (Rodent Histopathology Core, Dana-Farber/Harvard Cancer Center).</p></sec><sec id="s4-7"><title>STAMP sample processing</title><p>Samples were prepared for sequencing as described (<xref ref-type="bibr" rid="bib22">Hullahalli et al., 2021</xref>; <xref ref-type="bibr" rid="bib1">Abel et al., 2015</xref>; <xref ref-type="bibr" rid="bib20">Holmes et al., 2025</xref>; <xref ref-type="bibr" rid="bib45">Zhang et al., 2017</xref>; <xref ref-type="bibr" rid="bib8">Chevée et al., 2024</xref>; <xref ref-type="bibr" rid="bib2">Bachta et al., 2020</xref>; <xref ref-type="bibr" rid="bib7">Campbell et al., 2023</xref>). Briefly, bacteria from large (150 mm x 15 mm) plates were resuspended in PBS +20% glycerol and stored at –80 °C. The frozen suspensions were diluted in water and boiled at 95 °C for 15 min to obtain genomic DNA. An Eppendorf epMotion 5075 liquid handling robot was used to multiplex primer composition for sample preparation before PCR amplification (primers listed in <xref ref-type="table" rid="table1">Table 1</xref>). OneTaq HS Quick-Load (New England Biolabs) was used to amplify the genomic barcodes by PCR for 25 cycles. The presence of amplicons was confirmed by agarose gel electrophoresis. Samples were pooled and purified using a Qiagen DNA cleanup kit. Then DNA concentrations were checked with a Qubit fluorimeter and sequenced with an Illumina NextSeq 1000/2000. FASTQ files were generated by Illumina’s proprietary pipeline in BaseSpace with DRAGEN BCL Conver v3.10.4. Sequencing reads were then demultiplexed, mapped to the donor barcode library pSM1, and trimmed in R (version 4.3.0) using custom scripts to obtain counts for each barcode (Barcode counts are listed in Source data file 1). The founding population (Ns) was determined through comparison to the frequencies of barcodes in the undiluted library using the STAMPR pipeline (<xref ref-type="bibr" rid="bib22">Hullahalli et al., 2021</xref>). Cavalli-Sforza chord distance (2√2/π=0.9) was used to compare the genetic distance of samples from the same animal. FRD was calculated between sample A and sample B as FRD<sub>A-B</sub> = <inline-formula><mml:math id="inf1"><mml:mstyle displaystyle="true" scriptlevel="0"><mml:mrow><mml:mfrac><mml:mrow><mml:mi>l</mml:mi><mml:mi>n</mml:mi><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>R</mml:mi><mml:msub><mml:mi>D</mml:mi><mml:mrow><mml:mi>A</mml:mi><mml:mo>−</mml:mo><mml:mi>B</mml:mi></mml:mrow></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mrow><mml:mi>l</mml:mi><mml:mi>n</mml:mi><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>n</mml:mi><mml:mi>u</mml:mi><mml:mi>m</mml:mi><mml:mi>b</mml:mi><mml:mi>e</mml:mi><mml:mi>r</mml:mi><mml:mspace width="thinmathspace"/><mml:mi>o</mml:mi><mml:mi>f</mml:mi><mml:mspace width="thinmathspace"/><mml:mi>u</mml:mi><mml:mi>n</mml:mi><mml:mi>i</mml:mi><mml:mi>q</mml:mi><mml:mi>u</mml:mi><mml:mi>e</mml:mi><mml:mspace width="thinmathspace"/><mml:mi>b</mml:mi><mml:mi>a</mml:mi><mml:mi>r</mml:mi><mml:mi>c</mml:mi><mml:mi>o</mml:mi><mml:mi>d</mml:mi><mml:mi>e</mml:mi><mml:mi>s</mml:mi><mml:mspace width="thinmathspace"/><mml:mi>i</mml:mi><mml:mi>n</mml:mi><mml:mspace width="thinmathspace"/><mml:mi>s</mml:mi><mml:mi>a</mml:mi><mml:mi>m</mml:mi><mml:mi>p</mml:mi><mml:mi>l</mml:mi><mml:mi>e</mml:mi><mml:mspace width="thinmathspace"/><mml:mi>B</mml:mi></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mfrac></mml:mrow></mml:mstyle></mml:math></inline-formula>. RD<sub>A-B</sub> is a measure for the number of shared barcodes that contribute to genetic similarity (defined as GD &lt;0.8) between two samples, described extensively in <xref ref-type="bibr" rid="bib21">Hubbard et al., 2019</xref>.</p><table-wrap id="table1" position="float"><label>Table 1.</label><caption><title>Primer sequences for PCR.</title></caption><table frame="hsides" rules="groups"><thead><tr><th align="left" valign="bottom">Name</th><th align="left" valign="bottom">Sequence</th></tr></thead><tbody><tr><td align="left" valign="bottom" colspan="2">Forward Primers</td></tr><tr><td align="left" valign="bottom">var21</td><td align="left" valign="bottom"><named-content content-type="sequence">AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTCCGATCTAATGATGGGTTAAAAAGGATCGATCC</named-content></td></tr><tr><td align="left" valign="bottom">var22</td><td align="left" valign="bottom"><named-content content-type="sequence">AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTCCGATCTATGCGATGGGTTAAAAAGGATCGATCC</named-content></td></tr><tr><td align="left" valign="bottom">var23</td><td align="left" valign="bottom"><named-content content-type="sequence">AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTCCGATCTTGCACGATGGGTTAAAAAGGATCGATCC</named-content></td></tr><tr><td align="left" valign="bottom">var24</td><td align="left" valign="bottom"><named-content content-type="sequence">AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTCCGATCTTCATTCGATGGGTTAAAAAGGATCGATCC</named-content></td></tr><tr><td align="left" valign="bottom">var25</td><td align="left" valign="bottom"><named-content content-type="sequence">AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTCCGATCTGAATCGAGATGGGTTAAAAAGGATCGATCC</named-content></td></tr><tr><td align="left" valign="bottom">var26</td><td align="left" valign="bottom"><named-content content-type="sequence">AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTCCGATCTGTCAACTTGATGGGTTAAAAAGGATCGATCC</named-content></td></tr><tr><td align="left" valign="bottom">var27</td><td align="left" valign="bottom"><named-content content-type="sequence">AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTCCGATCTCGGCGTGGCGATGGGTTAAAAAGGATCGATCC</named-content></td></tr><tr><td align="left" valign="bottom">var28</td><td align="left" valign="bottom"><named-content content-type="sequence">AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTCCGATCTCC</named-content><break/><named-content content-type="sequence">TGTACCTTGATGGGTTAAAAAGGATCGATCC</named-content></td></tr><tr><td align="left" valign="bottom" colspan="2">Reverse Primers</td></tr><tr><td align="left" valign="bottom">AD001</td><td align="left" valign="bottom"><named-content content-type="sequence">CAAGCAGAAGACGGCATACGAGATCGT</named-content><break/><named-content content-type="sequence">GATGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCAGATCCTTGGCGGCAAGAAA</named-content></td></tr><tr><td align="left" valign="bottom">AD002</td><td align="left" valign="bottom"><named-content content-type="sequence">CAAGCAGAAGACGGCATACGAGATACATCGGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCAGATCCTTGGCGGCAAGAAA</named-content></td></tr><tr><td align="left" valign="bottom">AD003</td><td align="left" valign="bottom"><named-content content-type="sequence">CAAGCAGAAGACGGCATACGAGATGCCTAAGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCAGATCCTTGGCGGCAAGAAA</named-content></td></tr><tr><td align="left" valign="bottom">AD004</td><td align="left" valign="bottom"><named-content content-type="sequence">CAAGCAGAAGACGGCATACGAGATTGGTCAGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCAGATCCTTGGCGGCAAGAAA</named-content></td></tr><tr><td align="left" valign="bottom">AD005</td><td align="left" valign="bottom"><named-content content-type="sequence">CAAGCAGAAGACGGCATACGAGATCACTGTGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCAGATCCTTGGCGGCAAGAAA</named-content></td></tr><tr><td align="left" valign="bottom">AD006</td><td align="left" valign="bottom"><named-content content-type="sequence">CAAGCAGAAGACGGCATACGAGATATTGGCGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCAGATCCTTGGCGGCAAGAAA</named-content></td></tr><tr><td align="left" valign="bottom">AD007</td><td align="left" valign="bottom"><named-content content-type="sequence">CAAGCAGAAGACGGCATACGAGATGATCTGGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCAGATCCTTGGCGGCAAGAAA</named-content></td></tr><tr><td align="left" valign="bottom">AD008</td><td align="left" valign="bottom"><named-content content-type="sequence">CAAGCAGAAGACGGCATACGAGATTCAAGTGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCAGATCCTTGGCGGCAAGAAA</named-content></td></tr><tr><td align="left" valign="bottom">AD009</td><td align="left" valign="bottom"><named-content content-type="sequence">CAAGCAGAAGACGGCATACGAGATCTGATCGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCAGATCCTTGGCGGCAAGAAA</named-content></td></tr><tr><td align="left" valign="bottom">AD010</td><td align="left" valign="bottom"><named-content content-type="sequence">CAAGCAGAAGACGGCATACGAGATAAGCTAGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCAGATCCTTGGCGGCAAGAAA</named-content></td></tr><tr><td align="left" valign="bottom">AD011</td><td align="left" valign="bottom"><named-content content-type="sequence">CAAGCAGAAGACGGCATACGAGATGTAGCCGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCAGATCCTTGGCGGCAAGAAA</named-content></td></tr><tr><td align="left" valign="bottom">AD012</td><td align="left" valign="bottom"><named-content content-type="sequence">CAAGCAGAAGACGGCATACGAGATTACAAGGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCAGATCCTTGGCGGCAAGAAA</named-content></td></tr><tr><td align="left" valign="bottom">AD013</td><td align="left" valign="bottom"><named-content content-type="sequence">CAAGCAGAAGACGGCATACGAGATTTGACTGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCAGATCCTTGGCGGCAAGAAA</named-content></td></tr><tr><td align="left" valign="bottom">AD014</td><td align="left" valign="bottom"><named-content content-type="sequence">CAAGCAGAAGACGGCATACGAGATGGAACTGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCAGATCCTTGGCGGCAAGAAA</named-content></td></tr><tr><td align="left" valign="bottom">AD015</td><td align="left" valign="bottom"><named-content content-type="sequence">CAAGCAGAAGACGGCATACGAGATTGACATGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCAGATCCTTGGCGGCAAGAAA</named-content></td></tr><tr><td align="left" valign="bottom">AD016</td><td align="left" valign="bottom"><named-content content-type="sequence">CAAGCAGAAGACGGCATACGAGATGGACGGGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCAGATCCTTGGCGGCAAGAAA</named-content></td></tr><tr><td align="left" valign="bottom">AD018</td><td align="left" valign="bottom"><named-content content-type="sequence">CAAGCAGAAGACGGCATACGAGATGCGGACGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCAGATCCTTGGCGGCAAGAAA</named-content></td></tr><tr><td align="left" valign="bottom">AD019</td><td align="left" valign="bottom"><named-content content-type="sequence">CAAGCAGAAGACGGCATACGAGATTTTCACGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCAGATCCTTGGCGGCAAGAAA</named-content></td></tr><tr><td align="left" valign="bottom">AD020</td><td align="left" valign="bottom"><named-content content-type="sequence">CAAGCAGAAGACGGCATACGAGATGGCCACGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCAGATCCTTGGCGGCAAGAAA</named-content></td></tr><tr><td align="left" valign="bottom">AD021</td><td align="left" valign="bottom"><named-content content-type="sequence">CAAGCAGAAGACGGCATACGAGATCGAAACGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCAGATCCTTGGCGGCAAGAAA</named-content></td></tr><tr><td align="left" valign="bottom">AD022</td><td align="left" valign="bottom"><named-content content-type="sequence">CAAGCAGAAGACGGCATACGAGATCGTACGGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCAGATCCTTGGCGGCAAGAAA</named-content></td></tr><tr><td align="left" valign="bottom">AD023</td><td align="left" valign="bottom"><named-content content-type="sequence">CAAGCAGAAGACGGCATACGAGATCCACTCGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCAGATCCTTGGCGGCAAGAAA</named-content></td></tr><tr><td align="left" valign="bottom">AD025</td><td align="left" valign="bottom"><named-content content-type="sequence">CAAGCAGAAGACGGCATACGAGATATCAGTGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCAGATCCTTGGCGGCAAGAAA</named-content></td></tr><tr><td align="left" valign="bottom">AD027</td><td align="left" valign="bottom"><named-content content-type="sequence">CAAGCAGAAGACGGCATACGAGATAGGAATGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCAGATCCTTGGCGGCAAGAAA</named-content></td></tr></tbody></table></table-wrap></sec><sec id="s4-8"><title>Statistical analysis</title><p>Statistical analyses were performed using GraphPad Prism version 10.1.2. Information regarding the number of samples and statistical tests are described in the figure legends. Geometric means, geometric standard deviations, and non-parametric tests were used for analyzing bacterial burden and founding population data. Means, standard deviations, and non-parametric tests were used for comparisons of animal weights, genetic distances, and barcode identity. As our lower limit of detection was near 1, we substituted null values with a value between 0.1 and 0.8 for graphical representation.</p></sec></sec></body><back><sec sec-type="additional-information" id="s5"><title>Additional information</title><fn-group content-type="competing-interest"><title>Competing interests</title><fn fn-type="COI-statement" id="conf1"><p>No competing interests declared</p></fn></fn-group><fn-group content-type="author-contribution"><title>Author contributions</title><fn fn-type="con" id="con1"><p>Conceptualization, Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing – original draft, Writing – review and editing</p></fn><fn fn-type="con" id="con2"><p>Conceptualization, Data curation, Visualization, Methodology, Writing – original draft, Writing – review and editing</p></fn><fn fn-type="con" id="con3"><p>Conceptualization, Software, Formal analysis, Methodology</p></fn><fn fn-type="con" id="con4"><p>Conceptualization, Formal analysis, Investigation</p></fn><fn fn-type="con" id="con5"><p>Conceptualization, Supervision, Funding acquisition, Writing – original draft, Writing – review and editing</p></fn></fn-group><fn-group content-type="ethics-information"><title>Ethics</title><fn fn-type="other"><p>All experiments involving mice were performed according to protocols reviewed and approved by the Brigham and Women's Hospital Institutional Animal Care and Use Committee (protocol 2016N000416) and in compliance with the Guide for the Care and Use of Laboratory Animals.</p></fn></fn-group></sec><sec sec-type="supplementary-material" id="s6"><title>Additional files</title><supplementary-material id="mdar"><label>MDAR checklist</label><media xlink:href="elife-101388-mdarchecklist1-v1.pdf" mimetype="application" mime-subtype="pdf"/></supplementary-material><supplementary-material id="sdata1"><label>Source data 1.</label><caption><title>Barcode counts for all samples in the manuscript (separate file).</title></caption><media xlink:href="elife-101388-data1-v1.csv" mimetype="application" mime-subtype="octet-stream"/></supplementary-material></sec><sec sec-type="data-availability" id="s7"><title>Data availability</title><p>STAMPR scripts are available in <ext-link ext-link-type="uri" xlink:href="https://github.com/hullahalli/stampr_rtisan">Github</ext-link> (copy archived at <xref ref-type="bibr" rid="bib23">Hullahalli, 2024</xref>). Dataset S1 contains the barcode counts used for STAMPR analysis. Requests for further information, resources, or reagents will be fulfilled by the Lead Contact, Matthew K. Waldor (mwaldor@research.bwh.harvard.edu).</p></sec><ack id="ack"><title>Acknowledgements</title><p>The authors would like to thank the Waldor lab for their insight and helpful conversations.</p><p>This work was funded by the Howard Hughes Medical Institute (MKW), grants from the National Institutes of Health R01 AI042347 (MKW), P30 DK034854 (IWC), and fellowships from the National Institutes of Health T32 DK007477-37 (IWC), F31 AI156949 (KH).</p><p>We thank Dana-Farber/Harvard Cancer Center in Boston, MA, for the use of the Rodent Histopathology Core, which provided microscopy services. Dana-Farber/Harvard Cancer Center is supported in part by a NCI Cancer Center Support Grant # NIH 5 P30 CA06516.</p><p>This article is subject to HHMI’s Open Access to Publications policy. HHMI lab heads have previously granted a nonexclusive CC BY 4.0 license to the public and a sublicensable license to HHMI in their research articles. Pursuant to those licenses, the author-accepted manuscript of this article can be made freely available under a CC BY 4.0 license immediately upon publication.</p></ack><ref-list><title>References</title><ref id="bib1"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Abel</surname><given-names>S</given-names></name><name><surname>Abel zur Wiesch</surname><given-names>P</given-names></name><name><surname>Chang</surname><given-names>H-H</given-names></name><name><surname>Davis</surname><given-names>BM</given-names></name><name><surname>Lipsitch</surname><given-names>M</given-names></name><name><surname>Waldor</surname><given-names>MK</given-names></name></person-group><year iso-8601-date="2015">2015</year><article-title>Sequence tag-based analysis of microbial population dynamics</article-title><source>Nature Methods</source><volume>12</volume><fpage>223</fpage><lpage>226</lpage><pub-id pub-id-type="doi">10.1038/nmeth.3253</pub-id><pub-id pub-id-type="pmid">25599549</pub-id></element-citation></ref><ref id="bib2"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Bachta</surname><given-names>KER</given-names></name><name><surname>Allen</surname><given-names>JP</given-names></name><name><surname>Cheung</surname><given-names>BH</given-names></name><name><surname>Chiu</surname><given-names>CH</given-names></name><name><surname>Hauser</surname><given-names>AR</given-names></name></person-group><year iso-8601-date="2020">2020</year><article-title>Systemic infection facilitates transmission of <italic>Pseudomonas aeruginosa</italic> in mice</article-title><source>Nature Communications</source><volume>11</volume><elocation-id>543</elocation-id><pub-id pub-id-type="doi">10.1038/s41467-020-14363-4</pub-id><pub-id pub-id-type="pmid">31992714</pub-id></element-citation></ref><ref id="bib3"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Barthel</surname><given-names>M</given-names></name><name><surname>Hapfelmeier</surname><given-names>S</given-names></name><name><surname>Quintanilla-Martínez</surname><given-names>L</given-names></name><name><surname>Kremer</surname><given-names>M</given-names></name><name><surname>Rohde</surname><given-names>M</given-names></name><name><surname>Hogardt</surname><given-names>M</given-names></name><name><surname>Pfeffer</surname><given-names>K</given-names></name><name><surname>Rüssmann</surname><given-names>H</given-names></name><name><surname>Hardt</surname><given-names>W-D</given-names></name></person-group><year iso-8601-date="2003">2003</year><article-title>Pretreatment of mice with streptomycin provides a <italic>Salmonella enterica</italic> serovar Typhimurium colitis model that allows analysis of both pathogen and host</article-title><source>Infection and Immunity</source><volume>71</volume><fpage>2839</fpage><lpage>2858</lpage><pub-id pub-id-type="doi">10.1128/IAI.71.5.2839-2858.2003</pub-id><pub-id pub-id-type="pmid">12704158</pub-id></element-citation></ref><ref id="bib4"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Bazett</surname><given-names>M</given-names></name><name><surname>Bergeron</surname><given-names>ME</given-names></name><name><surname>Haston</surname><given-names>CK</given-names></name></person-group><year iso-8601-date="2016">2016</year><article-title>Streptomycin treatment alters the intestinal microbiome, pulmonary T cell profile and airway hyperresponsiveness in a cystic fibrosis mouse model</article-title><source>Scientific Reports</source><volume>6</volume><elocation-id>19189</elocation-id><pub-id pub-id-type="doi">10.1038/srep19189</pub-id><pub-id pub-id-type="pmid">26754178</pub-id></element-citation></ref><ref id="bib5"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Bohnhoff</surname><given-names>M</given-names></name><name><surname>Drake</surname><given-names>BL</given-names></name><name><surname>Miller</surname><given-names>CP</given-names></name></person-group><year iso-8601-date="1954">1954</year><article-title>Effect of streptomycin on susceptibility of intestinal tract to experimental <italic>Salmonella</italic> infection</article-title><source>Experimental Biology and Medicine</source><volume>86</volume><fpage>132</fpage><lpage>137</lpage><pub-id pub-id-type="doi">10.3181/00379727-86-21030</pub-id></element-citation></ref><ref id="bib6"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Bravo-Blas</surname><given-names>A</given-names></name><name><surname>Utriainen</surname><given-names>L</given-names></name><name><surname>Clay</surname><given-names>SL</given-names></name><name><surname>Kästele</surname><given-names>V</given-names></name><name><surname>Cerovic</surname><given-names>V</given-names></name><name><surname>Cunningham</surname><given-names>AF</given-names></name><name><surname>Henderson</surname><given-names>IR</given-names></name><name><surname>Wall</surname><given-names>DM</given-names></name><name><surname>Milling</surname><given-names>SWF</given-names></name></person-group><year iso-8601-date="2019">2019</year><article-title><italic>Salmonella enterica</italic> serovar typhimurium travels to mesenteric lymph nodes both with host cells and autonomously</article-title><source>Journal of Immunology</source><volume>202</volume><fpage>260</fpage><lpage>267</lpage><pub-id pub-id-type="doi">10.4049/jimmunol.1701254</pub-id><pub-id pub-id-type="pmid">30487173</pub-id></element-citation></ref><ref id="bib7"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Campbell</surname><given-names>IW</given-names></name><name><surname>Hullahalli</surname><given-names>K</given-names></name><name><surname>Turner</surname><given-names>JR</given-names></name><name><surname>Waldor</surname><given-names>MK</given-names></name></person-group><year iso-8601-date="2023">2023</year><article-title>Quantitative dose-response analysis untangles host bottlenecks to enteric infection</article-title><source>Nature Communications</source><volume>14</volume><elocation-id>456</elocation-id><pub-id pub-id-type="doi">10.1038/s41467-023-36162-3</pub-id><pub-id pub-id-type="pmid">36709326</pub-id></element-citation></ref><ref id="bib8"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Chevée</surname><given-names>V</given-names></name><name><surname>Hullahalli</surname><given-names>K</given-names></name><name><surname>Dailey</surname><given-names>KG</given-names></name><name><surname>Güereca</surname><given-names>L</given-names></name><name><surname>Zhang</surname><given-names>C</given-names></name><name><surname>Waldor</surname><given-names>MK</given-names></name><name><surname>Portnoy</surname><given-names>DA</given-names></name></person-group><year iso-8601-date="2024">2024</year><article-title>Temporal and spatial dynamics of <italic>Listeria monocytogenes</italic> central nervous system infection in mice</article-title><source>PNAS</source><volume>121</volume><elocation-id>e2320311121</elocation-id><pub-id pub-id-type="doi">10.1073/pnas.2320311121</pub-id><pub-id pub-id-type="pmid">38635627</pub-id></element-citation></ref><ref id="bib9"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Coombes</surname><given-names>BK</given-names></name><name><surname>Coburn</surname><given-names>BA</given-names></name><name><surname>Potter</surname><given-names>AA</given-names></name><name><surname>Gomis</surname><given-names>S</given-names></name><name><surname>Mirakhur</surname><given-names>K</given-names></name><name><surname>Li</surname><given-names>Y</given-names></name><name><surname>Finlay</surname><given-names>BB</given-names></name></person-group><year iso-8601-date="2005">2005</year><article-title>Analysis of the contribution of <italic>Salmonella</italic> pathogenicity islands 1 and 2 to enteric disease progression using a novel bovine ileal loop model and a murine model of infectious enterocolitis</article-title><source>Infection and Immunity</source><volume>73</volume><fpage>7161</fpage><lpage>7169</lpage><pub-id pub-id-type="doi">10.1128/IAI.73.11.7161-7169.2005</pub-id><pub-id pub-id-type="pmid">16239510</pub-id></element-citation></ref><ref id="bib10"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Crawford</surname><given-names>RW</given-names></name><name><surname>Rosales-Reyes</surname><given-names>R</given-names></name><name><surname>Ramírez-Aguilar</surname><given-names>Mdle</given-names></name><name><surname>Chapa-Azuela</surname><given-names>O</given-names></name><name><surname>Alpuche-Aranda</surname><given-names>C</given-names></name><name><surname>Gunn</surname><given-names>JS</given-names></name></person-group><year iso-8601-date="2010">2010</year><article-title>Gallstones play a significant role in <italic>Salmonella</italic> spp. gallbladder colonization and carriage</article-title><source>PNAS</source><volume>107</volume><fpage>4353</fpage><lpage>4358</lpage><pub-id pub-id-type="doi">10.1073/pnas.1000862107</pub-id><pub-id pub-id-type="pmid">20176950</pub-id></element-citation></ref><ref id="bib11"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Dias</surname><given-names>SP</given-names></name><name><surname>Brouwer</surname><given-names>MC</given-names></name><name><surname>van de Beek</surname><given-names>D</given-names></name></person-group><year iso-8601-date="2022">2022</year><article-title>Sex and gender differences in bacterial infections</article-title><source>Infection and Immunity</source><volume>90</volume><elocation-id>e0028322</elocation-id><pub-id pub-id-type="doi">10.1128/iai.00283-22</pub-id><pub-id pub-id-type="pmid">36121220</pub-id></element-citation></ref><ref id="bib12"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Dowling</surname><given-names>RH</given-names></name></person-group><year iso-8601-date="2000">2000</year><article-title>Review: pathogenesis of gallstones</article-title><source>Alimentary Pharmacology &amp; Therapeutics</source><volume>14 Suppl 2</volume><fpage>39</fpage><lpage>47</lpage><pub-id pub-id-type="doi">10.1046/j.1365-2036.2000.014s2039.x</pub-id><pub-id pub-id-type="pmid">10903002</pub-id></element-citation></ref><ref id="bib13"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Dybowski</surname><given-names>R</given-names></name><name><surname>Restif</surname><given-names>O</given-names></name><name><surname>Goupy</surname><given-names>A</given-names></name><name><surname>Maskell</surname><given-names>DJ</given-names></name><name><surname>Mastroeni</surname><given-names>P</given-names></name><name><surname>Grant</surname><given-names>AJ</given-names></name></person-group><year iso-8601-date="2015">2015</year><article-title>Single passage in mouse organs enhances the survival and spread of <italic>Salmonella enterica</italic></article-title><source>Journal of the Royal Society, Interface</source><volume>12</volume><elocation-id>20150702</elocation-id><pub-id pub-id-type="doi">10.1098/rsif.2015.0702</pub-id><pub-id pub-id-type="pmid">26701880</pub-id></element-citation></ref><ref id="bib14"><element-citation publication-type="preprint"><person-group person-group-type="author"><name><surname>Dybowski</surname><given-names>R</given-names></name><name><surname>Restif</surname><given-names>O</given-names></name><name><surname>Price</surname><given-names>DJ</given-names></name><name><surname>Mastroeni</surname><given-names>P</given-names></name></person-group><year iso-8601-date="2017">2017</year><article-title>Inferring Within-Host Bottleneck Size: A Bayesian Approach</article-title><source>bioRxiv</source><pub-id pub-id-type="doi">10.1101/116194</pub-id></element-citation></ref><ref id="bib15"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Fierer</surname><given-names>J</given-names></name><name><surname>Okamoto</surname><given-names>S</given-names></name><name><surname>Banerjee</surname><given-names>A</given-names></name><name><surname>Guiney</surname><given-names>DG</given-names></name></person-group><year iso-8601-date="2012">2012</year><article-title>Diarrhea and colitis in mice require the <italic>Salmonella</italic> pathogenicity island 2-encoded secretion function but not SifA or Spv effectors</article-title><source>Infection and Immunity</source><volume>80</volume><fpage>3360</fpage><lpage>3370</lpage><pub-id pub-id-type="doi">10.1128/IAI.00404-12</pub-id><pub-id pub-id-type="pmid">22778101</pub-id></element-citation></ref><ref id="bib16"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Gogoi</surname><given-names>M</given-names></name><name><surname>Shreenivas</surname><given-names>MM</given-names></name><name><surname>Chakravortty</surname><given-names>D</given-names></name></person-group><year iso-8601-date="2019">2019</year><article-title>Hoodwinking the big-eater to prosper: The <italic>Salmonella</italic>-macrophage paradigm</article-title><source>Journal of Innate Immunity</source><volume>11</volume><fpage>289</fpage><lpage>299</lpage><pub-id pub-id-type="doi">10.1159/000490953</pub-id><pub-id pub-id-type="pmid">30041182</pub-id></element-citation></ref><ref id="bib17"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Grant</surname><given-names>AJ</given-names></name><name><surname>Restif</surname><given-names>O</given-names></name><name><surname>McKinley</surname><given-names>TJ</given-names></name><name><surname>Sheppard</surname><given-names>M</given-names></name><name><surname>Maskell</surname><given-names>DJ</given-names></name><name><surname>Mastroeni</surname><given-names>P</given-names></name></person-group><year iso-8601-date="2008">2008</year><article-title>Modelling within-host spatiotemporal dynamics of invasive bacterial disease</article-title><source>PLOS Biology</source><volume>6</volume><elocation-id>e74</elocation-id><pub-id pub-id-type="doi">10.1371/journal.pbio.0060074</pub-id><pub-id pub-id-type="pmid">18399718</pub-id></element-citation></ref><ref id="bib18"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Higginson</surname><given-names>EE</given-names></name><name><surname>Simon</surname><given-names>R</given-names></name><name><surname>Tennant</surname><given-names>SM</given-names></name></person-group><year iso-8601-date="2016">2016</year><article-title>Animal models for salmonellosis: applications in vaccine research</article-title><source>Clinical and Vaccine Immunology</source><volume>23</volume><fpage>746</fpage><lpage>756</lpage><pub-id pub-id-type="doi">10.1128/CVI.00258-16</pub-id><pub-id pub-id-type="pmid">27413068</pub-id></element-citation></ref><ref id="bib19"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Hoiseth</surname><given-names>SK</given-names></name><name><surname>Stocker</surname><given-names>BA</given-names></name></person-group><year iso-8601-date="1981">1981</year><article-title>Aromatic-dependent <italic>Salmonella</italic> typhimurium are non-virulent and effective as live vaccines</article-title><source>Nature</source><volume>291</volume><fpage>238</fpage><lpage>239</lpage><pub-id pub-id-type="doi">10.1038/291238a0</pub-id><pub-id pub-id-type="pmid">7015147</pub-id></element-citation></ref><ref id="bib20"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Holmes</surname><given-names>CL</given-names></name><name><surname>Dailey</surname><given-names>KG</given-names></name><name><surname>Hullahalli</surname><given-names>K</given-names></name><name><surname>Wilcox</surname><given-names>AE</given-names></name><name><surname>Mason</surname><given-names>S</given-names></name><name><surname>Moricz</surname><given-names>BS</given-names></name><name><surname>Unverdorben</surname><given-names>LV</given-names></name><name><surname>Balazs</surname><given-names>GI</given-names></name><name><surname>Waldor</surname><given-names>MK</given-names></name><name><surname>Bachman</surname><given-names>MA</given-names></name></person-group><year iso-8601-date="2025">2025</year><article-title>Patterns of Klebsiella pneumoniae bacteremic dissemination from the lung</article-title><source>Nature Communications</source><volume>16</volume><elocation-id>785</elocation-id><pub-id pub-id-type="doi">10.1038/s41467-025-56095-3</pub-id><pub-id pub-id-type="pmid">39824859</pub-id></element-citation></ref><ref id="bib21"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Hubbard</surname><given-names>TP</given-names></name><name><surname>D’Gama</surname><given-names>JD</given-names></name><name><surname>Billings</surname><given-names>G</given-names></name><name><surname>Davis</surname><given-names>BM</given-names></name><name><surname>Waldor</surname><given-names>MK</given-names></name></person-group><year iso-8601-date="2019">2019</year><article-title>Unsupervised learning approach for comparing multiple transposon insertion sequencing studies</article-title><source>mSphere</source><volume>4</volume><elocation-id>e00031-19</elocation-id><pub-id pub-id-type="doi">10.1128/mSphere.00031-19</pub-id><pub-id pub-id-type="pmid">30787116</pub-id></element-citation></ref><ref id="bib22"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Hullahalli</surname><given-names>K</given-names></name><name><surname>Pritchard</surname><given-names>JR</given-names></name><name><surname>Waldor</surname><given-names>MK</given-names></name></person-group><year iso-8601-date="2021">2021</year><article-title>Refined quantification of infection bottlenecks and pathogen dissemination with STAMPR</article-title><source>mSystems</source><volume>6</volume><elocation-id>e0088721</elocation-id><pub-id pub-id-type="doi">10.1128/mSystems.00887-21</pub-id><pub-id pub-id-type="pmid">34402636</pub-id></element-citation></ref><ref id="bib23"><element-citation publication-type="software"><person-group person-group-type="author"><name><surname>Hullahalli</surname><given-names>K</given-names></name></person-group><year iso-8601-date="2024">2024</year><data-title>Stampr_rtisan</data-title><version designator="swh:1:rev:651ef1a35e5c553d49131acc069bffe305114cef">swh:1:rev:651ef1a35e5c553d49131acc069bffe305114cef</version><source>Software Heritage</source><ext-link ext-link-type="uri" xlink:href="https://archive.softwareheritage.org/swh:1:dir:0caab2ebe5d750304b6f008d39f3cb48531e1d44;origin=https://github.com/hullahalli/stampr_rtisan;visit=swh:1:snp:9724ec638671d8fbef4cfac7c1bce17a6a4be5ed;anchor=swh:1:rev:651ef1a35e5c553d49131acc069bffe305114cef">https://archive.softwareheritage.org/swh:1:dir:0caab2ebe5d750304b6f008d39f3cb48531e1d44;origin=https://github.com/hullahalli/stampr_rtisan;visit=swh:1:snp:9724ec638671d8fbef4cfac7c1bce17a6a4be5ed;anchor=swh:1:rev:651ef1a35e5c553d49131acc069bffe305114cef</ext-link></element-citation></ref><ref id="bib24"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Johnson</surname><given-names>R</given-names></name><name><surname>Ravenhall</surname><given-names>M</given-names></name><name><surname>Pickard</surname><given-names>D</given-names></name><name><surname>Dougan</surname><given-names>G</given-names></name><name><surname>Byrne</surname><given-names>A</given-names></name><name><surname>Frankel</surname><given-names>G</given-names></name></person-group><year iso-8601-date="2018">2018</year><article-title>Comparison of <italic>Salmonella enterica</italic> serovars typhi and typhimurium reveals typhoidal serovar-specific responses to bile</article-title><source>Infection and Immunity</source><volume>86</volume><elocation-id>e00490-17</elocation-id><pub-id pub-id-type="doi">10.1128/IAI.00490-17</pub-id><pub-id pub-id-type="pmid">29229736</pub-id></element-citation></ref><ref id="bib25"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Kaiser</surname><given-names>P</given-names></name><name><surname>Slack</surname><given-names>E</given-names></name><name><surname>Grant</surname><given-names>AJ</given-names></name><name><surname>Hardt</surname><given-names>WD</given-names></name><name><surname>Regoes</surname><given-names>RR</given-names></name></person-group><year iso-8601-date="2013">2013</year><article-title>Lymph node colonization dynamics after oral <italic>Salmonella</italic> Typhimurium infection in mice</article-title><source>PLOS Pathogens</source><volume>9</volume><elocation-id>e1003532</elocation-id><pub-id pub-id-type="doi">10.1371/journal.ppat.1003532</pub-id><pub-id pub-id-type="pmid">24068916</pub-id></element-citation></ref><ref id="bib26"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Kaiser</surname><given-names>P</given-names></name><name><surname>Regoes</surname><given-names>RR</given-names></name><name><surname>Dolowschiak</surname><given-names>T</given-names></name><name><surname>Wotzka</surname><given-names>SY</given-names></name><name><surname>Lengefeld</surname><given-names>J</given-names></name><name><surname>Slack</surname><given-names>E</given-names></name><name><surname>Grant</surname><given-names>AJ</given-names></name><name><surname>Ackermann</surname><given-names>M</given-names></name><name><surname>Hardt</surname><given-names>W-D</given-names></name></person-group><year iso-8601-date="2014">2014</year><article-title>Cecum lymph node dendritic cells harbor slow-growing bacteria phenotypically tolerant to antibiotic treatment</article-title><source>PLOS Biology</source><volume>12</volume><elocation-id>e1001793</elocation-id><pub-id pub-id-type="doi">10.1371/journal.pbio.1001793</pub-id><pub-id pub-id-type="pmid">24558351</pub-id></element-citation></ref><ref id="bib27"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Lam</surname><given-names>LH</given-names></name><name><surname>Monack</surname><given-names>DM</given-names></name></person-group><year iso-8601-date="2014">2014</year><article-title>Intraspecies competition for niches in the distal gut dictate transmission during persistent <italic>Salmonella</italic> infection</article-title><source>PLOS Pathogens</source><volume>10</volume><elocation-id>e1004527</elocation-id><pub-id pub-id-type="doi">10.1371/journal.ppat.1004527</pub-id><pub-id pub-id-type="pmid">25474319</pub-id></element-citation></ref><ref id="bib28"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Lamichhane</surname><given-names>B</given-names></name><name><surname>Mawad</surname><given-names>AMM</given-names></name><name><surname>Saleh</surname><given-names>M</given-names></name><name><surname>Kelley</surname><given-names>WG</given-names></name><name><surname>Harrington</surname><given-names>PJ</given-names></name><name><surname>Lovestad</surname><given-names>CW</given-names></name><name><surname>Amezcua</surname><given-names>J</given-names></name><name><surname>Sarhan</surname><given-names>MM</given-names></name><name><surname>El Zowalaty</surname><given-names>ME</given-names></name><name><surname>Ramadan</surname><given-names>H</given-names></name><name><surname>Morgan</surname><given-names>M</given-names></name><name><surname>Helmy</surname><given-names>YA</given-names></name></person-group><year iso-8601-date="2024">2024</year><article-title>Salmonellosis: an overview of epidemiology, pathogenesis, and innovative approaches to mitigate the antimicrobial resistant infections</article-title><source>Antibiotics</source><volume>13</volume><elocation-id>76</elocation-id><pub-id pub-id-type="doi">10.3390/antibiotics13010076</pub-id><pub-id pub-id-type="pmid">38247636</pub-id></element-citation></ref><ref id="bib29"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Li</surname><given-names>Q</given-names></name></person-group><year iso-8601-date="2022">2022</year><article-title>Mechanisms for the Invasion and Dissemination of <italic>Salmonella</italic></article-title><source>The Canadian Journal of Infectious Diseases &amp; Medical Microbiology = Journal Canadien Des Maladies Infectieuses et de La Microbiologie Medicale</source><volume>2022</volume><elocation-id>2655801</elocation-id><pub-id pub-id-type="doi">10.1155/2022/2655801</pub-id><pub-id pub-id-type="pmid">35722038</pub-id></element-citation></ref><ref id="bib30"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Nilsson</surname><given-names>OR</given-names></name><name><surname>Kari</surname><given-names>L</given-names></name><name><surname>Steele-Mortimer</surname><given-names>O</given-names></name></person-group><year iso-8601-date="2019">2019</year><article-title>Foodborne infection of mice with <italic>Salmonella</italic> Typhimurium</article-title><source>PLOS ONE</source><volume>14</volume><elocation-id>e0215190</elocation-id><pub-id pub-id-type="doi">10.1371/journal.pone.0215190</pub-id><pub-id pub-id-type="pmid">31393874</pub-id></element-citation></ref><ref id="bib31"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Novacek</surname><given-names>G</given-names></name></person-group><year iso-8601-date="2006">2006</year><article-title>Gender and gallstone disease</article-title><source>Wiener Medizinische Wochenschrift (1946)</source><volume>156</volume><fpage>527</fpage><lpage>533</lpage><pub-id pub-id-type="doi">10.1007/s10354-006-0346-x</pub-id><pub-id pub-id-type="pmid">17103289</pub-id></element-citation></ref><ref id="bib32"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Peer</surname><given-names>V</given-names></name><name><surname>Schwartz</surname><given-names>N</given-names></name><name><surname>Green</surname><given-names>MS</given-names></name></person-group><year iso-8601-date="2021">2021</year><article-title>Sex Differences in Salmonellosis Incidence Rates-An Eight-Country National Data-Pooled Analysis</article-title><source>Journal of Clinical Medicine</source><volume>10</volume><elocation-id>5767</elocation-id><pub-id pub-id-type="doi">10.3390/jcm10245767</pub-id><pub-id pub-id-type="pmid">34945061</pub-id></element-citation></ref><ref id="bib33"><element-citation publication-type="book"><person-group person-group-type="author"><name><surname>Pragasam</surname><given-names>AK</given-names></name><name><surname>Maurya</surname><given-names>S</given-names></name><name><surname>Jain</surname><given-names>K</given-names></name><name><surname>Pal</surname><given-names>S</given-names></name><name><surname>Raja</surname><given-names>C</given-names></name><name><surname>Kumar</surname><given-names>S</given-names></name><name><surname>Purohit</surname><given-names>A</given-names></name><name><surname>Pradhan</surname><given-names>D</given-names></name><name><surname>Kajal</surname><given-names>K</given-names></name><name><surname>Talukdar</surname><given-names>D</given-names></name><name><surname>Singh</surname><given-names>AN</given-names></name><name><surname>Verma</surname><given-names>J</given-names></name><name><surname>Jana</surname><given-names>P</given-names></name><name><surname>Rawat</surname><given-names>S</given-names></name><name><surname>Kshetrapal</surname><given-names>P</given-names></name><name><surname>Krishna</surname><given-names>A</given-names></name><name><surname>Kumar</surname><given-names>S</given-names></name><name><surname>Bansal</surname><given-names>VK</given-names></name><name><surname>Yadav</surname><given-names>R</given-names></name><name><surname>Das</surname><given-names>B</given-names></name><name><surname>Srikanth</surname><given-names>CV</given-names></name><name><surname>Garg</surname><given-names>P</given-names></name></person-group><year iso-8601-date="2023">2023</year><source>Chronic Salmonella Infection Contributes to Gallbladder Carcinogenesis</source><publisher-name>SSRN</publisher-name><pub-id pub-id-type="doi">10.2139/ssrn.4540291</pub-id></element-citation></ref><ref id="bib34"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Ray</surname><given-names>N</given-names></name><name><surname>Jeong</surname><given-names>H</given-names></name><name><surname>Kwon</surname><given-names>D</given-names></name><name><surname>Kim</surname><given-names>J</given-names></name><name><surname>Moon</surname><given-names>Y</given-names></name></person-group><year iso-8601-date="2022">2022</year><article-title>Antibiotic exposure aggravates <italic>Bacteroides</italic>-Linked uremic toxicity in the gut-kidney axis</article-title><source>Frontiers in Immunology</source><volume>13</volume><elocation-id>737536</elocation-id><pub-id pub-id-type="doi">10.3389/fimmu.2022.737536</pub-id><pub-id pub-id-type="pmid">35401522</pub-id></element-citation></ref><ref id="bib35"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Ruby</surname><given-names>T</given-names></name><name><surname>McLaughlin</surname><given-names>L</given-names></name><name><surname>Gopinath</surname><given-names>S</given-names></name><name><surname>Monack</surname><given-names>D</given-names></name></person-group><year iso-8601-date="2012">2012</year><article-title><italic>Salmonella</italic>’s long-term relationship with its host</article-title><source>FEMS Microbiology Reviews</source><volume>36</volume><fpage>600</fpage><lpage>615</lpage><pub-id pub-id-type="doi">10.1111/j.1574-6976.2012.00332.x</pub-id><pub-id pub-id-type="pmid">22335190</pub-id></element-citation></ref><ref id="bib36"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Shrout</surname><given-names>JD</given-names></name></person-group><year iso-8601-date="2012">2012</year><article-title>The gall of some bacteria: strange behavior by <italic>Salmonella</italic></article-title><source>Science Translational Medicine</source><volume>4</volume><elocation-id>4012</elocation-id><pub-id pub-id-type="doi">10.1126/scitranslmed.3004012</pub-id></element-citation></ref><ref id="bib37"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Silva-García</surname><given-names>O</given-names></name><name><surname>Valdez-Alarcón</surname><given-names>JJ</given-names></name><name><surname>Baizabal-Aguirre</surname><given-names>VM</given-names></name></person-group><year iso-8601-date="2019">2019</year><article-title>Wnt/β-catenin signaling as a molecular target by pathogenic bacteria</article-title><source>Frontiers in Immunology</source><volume>10</volume><elocation-id>2135</elocation-id><pub-id pub-id-type="doi">10.3389/fimmu.2019.02135</pub-id><pub-id pub-id-type="pmid">31611869</pub-id></element-citation></ref><ref id="bib38"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Stecher</surname><given-names>B</given-names></name><name><surname>Paesold</surname><given-names>G</given-names></name><name><surname>Barthel</surname><given-names>M</given-names></name><name><surname>Kremer</surname><given-names>M</given-names></name><name><surname>Jantsch</surname><given-names>J</given-names></name><name><surname>Stallmach</surname><given-names>T</given-names></name><name><surname>Heikenwalder</surname><given-names>M</given-names></name><name><surname>Hardt</surname><given-names>W-D</given-names></name></person-group><year iso-8601-date="2006">2006</year><article-title>Chronic <italic>Salmonella enterica</italic> serovar Typhimurium-induced colitis and cholangitis in streptomycin-pretreated Nramp1+/+ mice</article-title><source>Infection and Immunity</source><volume>74</volume><fpage>5047</fpage><lpage>5057</lpage><pub-id pub-id-type="doi">10.1128/IAI.00072-06</pub-id><pub-id pub-id-type="pmid">16926396</pub-id></element-citation></ref><ref id="bib39"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Strati</surname><given-names>F</given-names></name><name><surname>Pujolassos</surname><given-names>M</given-names></name><name><surname>Burrello</surname><given-names>C</given-names></name><name><surname>Giuffrè</surname><given-names>MR</given-names></name><name><surname>Lattanzi</surname><given-names>G</given-names></name><name><surname>Caprioli</surname><given-names>F</given-names></name><name><surname>Troisi</surname><given-names>J</given-names></name><name><surname>Facciotti</surname><given-names>F</given-names></name></person-group><year iso-8601-date="2021">2021</year><article-title>Antibiotic-associated dysbiosis affects the ability of the gut microbiota to control intestinal inflammation upon fecal microbiota transplantation in experimental colitis models</article-title><source>Microbiome</source><volume>9</volume><elocation-id>991</elocation-id><pub-id pub-id-type="doi">10.1186/s40168-020-00991-x</pub-id><pub-id pub-id-type="pmid">33549144</pub-id></element-citation></ref><ref id="bib40"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Tsai</surname><given-names>MH</given-names></name><name><surname>Liang</surname><given-names>YH</given-names></name><name><surname>Chen</surname><given-names>CL</given-names></name><name><surname>Chiu</surname><given-names>CH</given-names></name></person-group><year iso-8601-date="2020">2020</year><article-title>Characterization of <italic>Salmonella</italic> resistance to bile during biofilm formation</article-title><source>Journal of Microbiology, Immunology, and Infection = Wei Mian Yu Gan Ran Za Zhi</source><volume>53</volume><fpage>518</fpage><lpage>524</lpage><pub-id pub-id-type="doi">10.1016/j.jmii.2019.06.003</pub-id><pub-id pub-id-type="pmid">31288972</pub-id></element-citation></ref><ref id="bib41"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Watson</surname><given-names>KG</given-names></name><name><surname>Holden</surname><given-names>DW</given-names></name></person-group><year iso-8601-date="2010">2010</year><article-title>Dynamics of growth and dissemination of <italic>Salmonella</italic> in vivo</article-title><source>Cellular Microbiology</source><volume>12</volume><fpage>1389</fpage><lpage>1397</lpage><pub-id pub-id-type="doi">10.1111/j.1462-5822.2010.01511.x</pub-id><pub-id pub-id-type="pmid">20731667</pub-id></element-citation></ref><ref id="bib42"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Worley</surname><given-names>MJ</given-names></name></person-group><year iso-8601-date="2023">2023</year><article-title><italic>Salmonella</italic> Bloodstream Infections</article-title><source>Tropical Medicine and Infectious Disease</source><volume>8</volume><elocation-id>10487</elocation-id><pub-id pub-id-type="doi">10.3390/tropicalmed8110487</pub-id></element-citation></ref><ref id="bib43"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Xu</surname><given-names>HR</given-names></name><name><surname>Hsu</surname><given-names>HS</given-names></name></person-group><year iso-8601-date="1992">1992</year><article-title>Dissemination and proliferation of <italic>Salmonella</italic> typhimurium in genetically resistant and susceptible mice</article-title><source>Journal of Medical Microbiology</source><volume>36</volume><fpage>377</fpage><lpage>381</lpage><pub-id pub-id-type="doi">10.1099/00222615-36-6-377</pub-id><pub-id pub-id-type="pmid">1613775</pub-id></element-citation></ref><ref id="bib44"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Yang</surname><given-names>X</given-names></name><name><surname>Stein</surname><given-names>KR</given-names></name><name><surname>Hang</surname><given-names>HC</given-names></name></person-group><year iso-8601-date="2023">2023</year><article-title>Anti-infective bile acids bind and inactivate a <italic>Salmonella</italic> virulence regulator</article-title><source>Nature Chemical Biology</source><volume>19</volume><fpage>91</fpage><lpage>100</lpage><pub-id pub-id-type="doi">10.1038/s41589-022-01122-3</pub-id><pub-id pub-id-type="pmid">36175659</pub-id></element-citation></ref><ref id="bib45"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Zhang</surname><given-names>T</given-names></name><name><surname>Abel</surname><given-names>S</given-names></name><name><surname>Abel Zur Wiesch</surname><given-names>P</given-names></name><name><surname>Sasabe</surname><given-names>J</given-names></name><name><surname>Davis</surname><given-names>BM</given-names></name><name><surname>Higgins</surname><given-names>DE</given-names></name><name><surname>Waldor</surname><given-names>MK</given-names></name></person-group><year iso-8601-date="2017">2017</year><article-title>Deciphering the landscape of host barriers to <italic>Listeria monocytogenes</italic> infection</article-title><source>PNAS</source><volume>114</volume><fpage>6334</fpage><lpage>6339</lpage><pub-id pub-id-type="doi">10.1073/pnas.1702077114</pub-id><pub-id pub-id-type="pmid">28559314</pub-id></element-citation></ref><ref id="bib46"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Zhang</surname><given-names>K</given-names></name><name><surname>Riba</surname><given-names>A</given-names></name><name><surname>Nietschke</surname><given-names>M</given-names></name><name><surname>Torow</surname><given-names>N</given-names></name><name><surname>Repnik</surname><given-names>U</given-names></name><name><surname>Pütz</surname><given-names>A</given-names></name><name><surname>Fulde</surname><given-names>M</given-names></name><name><surname>Dupont</surname><given-names>A</given-names></name><name><surname>Hensel</surname><given-names>M</given-names></name><name><surname>Hornef</surname><given-names>M</given-names></name></person-group><year iso-8601-date="2018">2018</year><article-title>Minimal SPI1-T3SS effector requirement for <italic>Salmonella</italic> enterocyte invasion and intracellular proliferation in vivo</article-title><source>PLOS Pathogens</source><volume>14</volume><elocation-id>e1006925</elocation-id><pub-id pub-id-type="doi">10.1371/journal.ppat.1006925</pub-id><pub-id pub-id-type="pmid">29522566</pub-id></element-citation></ref></ref-list></back><sub-article article-type="editor-report" id="sa0"><front-stub><article-id pub-id-type="doi">10.7554/eLife.101388.3.sa0</article-id><title-group><article-title>eLife Assessment</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Kana</surname><given-names>Bavesh D</given-names></name><role specific-use="editor">Reviewing Editor</role><aff><institution>University of the Witwatersrand</institution><country>South Africa</country></aff></contrib></contrib-group><kwd-group kwd-group-type="evidence-strength"><kwd>Compelling</kwd></kwd-group><kwd-group kwd-group-type="claim-importance"><kwd>Important</kwd></kwd-group></front-stub><body><p>This <bold>important</bold> study reports a detailed quantification of the population dynamics of <italic>Salmonella enterica</italic> serovar Typhimurium in mice. Bacterial burden and founding population sizes across various organs were quantified, revealing pathways of dissemination and reseeding of the gastrointestinal tract from systemic organs. Using various techniques, including genetic distance measurements, the authors present <bold>compelling</bold> evidence to support their conclusions, thus presenting new knowledge that will be of broad interest to scientists focusing on infectious diseases.</p></body></sub-article><sub-article article-type="referee-report" id="sa1"><front-stub><article-id pub-id-type="doi">10.7554/eLife.101388.3.sa1</article-id><title-group><article-title>Reviewer #1 (Public review):</article-title></title-group><contrib-group><contrib contrib-type="author"><anonymous/><role specific-use="referee">Reviewer</role></contrib></contrib-group></front-stub><body><p>Hotinger et al. explore the population dynamics of <italic>Salmonella enterica</italic> serovar Typhimurium in mice using genetically tagged bacteria. In addition to physiological observations, pathology assessments, and CFU measurements, the study emphasizes quantifying host bottleneck sizes that limit <italic>Salmonella</italic> colonization and dissemination. The authors also investigate the genetic distances between bacterial populations at various infection sites within the host.</p><p>Initially, the study confirms that pretreatment with the antibiotic streptomycin before inoculation via orogastric gavage increases the bacterial burden in the gastrointestinal (GI) tract, leading to more severe symptoms and heightened fecal shedding of bacteria. This pretreatment also significantly reduces between-animal variation in bacterial burden and fecal shedding. The authors then calculate founding population sizes across different organs, discovering a severe bottleneck in the intestine, with founding populations reduced by approximately 10^6-fold compared to the inoculum size. Streptomycin pretreatment increases the founding population size and bacterial replication in the GI tract. Moreover, by calculating genetic distances between populations, the authors demonstrate that, in untreated mice, <italic>Salmonella</italic> populations within the GI tract are genetically dissimilar, suggesting limited exchange between colonization sites. In contrast, streptomycin pretreatment reduces genetic distances, indicating increased exchange.</p><p>In extraintestinal organs, the bacterial burden is generally not substantially increased by streptomycin pretreatment, with significant differences observed only in the mesenteric lymph nodes and bile. However, the founding population sizes in these organs are increased. By comparing genetic distances between organs, the authors provide evidence that subpopulations colonizing extraintestinal organs diverge early after infection from those in the GI tract. This hypothesis is further tested by measuring bacterial burden and founding population sizes in the liver and GI tract at 5 and 120 hours post-infection. Additionally, they compare orogastric gavage infection with the less injurious method of infection via drinking, finding similar results for CFUs, founding populations, and genetic distances. These results argue against injuries during gavage as a route of direct infection.</p><p>To bypass bottlenecks associated with the GI tract, the authors compare intravenous (IV) and intraperitoneal (IP) routes of infection. They find approximately a 10-fold increase in bacterial burden and founding population size in immune-rich organs with IV/IP routes compared to orogastric gavage in streptomycin-pretreated animals. This difference is interpreted as a result of &quot;extra steps required to reach systemic organs.&quot;</p><p>While IP and IV routes yield similar results in immune-rich organs, IP infections lead to higher bacterial burdens in nearby sites, such as the pancreas, adipose tissue, and intraperitoneal wash, as well as somewhat increased founding population sizes. The authors correlate these findings with the presence of white lesions in adipose tissue. Genetic distance comparisons reveal that, apart from the spleen and liver, IP infections lead to genetically distinct populations in infected organs, whereas IV infections generally result in higher genetic similarity.</p><p>Finally, the authors investigate GI tract reseeding, identifying two distinct routes. They observe that the GI tracts of IP/IV-infected mice are colonized either by a clonal or a diversely tagged bacterial population. In clonally reseeded animals, the genetic distance within the GI tract is very low (often zero) compared to the bile population, which is predominantly clonal or pauciclonal. These animals also display pathological signs, such as cloudy/hardened bile and increased bacterial burden, leading the authors to conclude that the GI tract was reseeded by bacteria from the gallbladder bile. In contrast, animals reseeded by more complex bacterial populations show that bile contributes only a minor fraction of the tags. Given the large founding population size in these animals' GI tracts, which is larger than in orogastrically infected animals, the authors suggest a highly permissive second reseeding route, largely independent of bile. They speculate that this route may involve a reversal of known mechanisms that the pathogen uses to escape from the intestine.</p><p>The manuscript presents a substantial body of work that offers a meticulously detailed understanding of the population dynamics of S. Typhimurium in mice. It quantifies the processes shaping the within-host dynamics of this pathogen and provides new insights into its spread, including previously unrecognized dissemination routes. The methodology is appropriate and carefully executed, and the manuscript is well-written, clearly presented, and concise. The authors' conclusions are well-supported by experimental results and thoroughly discussed. This work underscores the power of using highly diverse barcoded pathogens to uncover the within-host population dynamics of infections and will likely inspire further investigations into the molecular mechanisms underlying the bottlenecks and dissemination routes described here.</p></body></sub-article><sub-article article-type="referee-report" id="sa2"><front-stub><article-id pub-id-type="doi">10.7554/eLife.101388.3.sa2</article-id><title-group><article-title>Reviewer #2 (Public review):</article-title></title-group><contrib-group><contrib contrib-type="author"><anonymous/><role specific-use="referee">Reviewer</role></contrib></contrib-group></front-stub><body><p>In this paper, Hotinger et. al. propose an improved barcoded library system, called STAMPR, to study <italic>Salmonella</italic> population dynamics during infection. Using this system, the authors demonstrate significant diversity in the colonization of different <italic>Salmonella</italic> clones (defined by the presence of different barcodes) not only across different organs (liver, spleen, adipose tissues, pancreas and gall bladder) but also within different compartments of the same gastrointestinal tissue. Additionally, this system revealed that microbiota competition is the major bottleneck in <italic>Salmonella</italic> intestinal colonization, which can be mitigated by streptomycin treatment. However, this has been demonstrated previously in numerous publications. They also show that there was minimal sharing between populations found in the intestine and those in the other organs. Upon IV and IP infection to bypass the intestinal bottleneck, they were able to demonstrate, using this library, that <italic>Salmonella</italic> can renter the intestine through two possible routes. One route is essentially the reverse path used to escape the gut, leading to a diverse intestinal population; while the other, through the bile, typically results in a clonal population.</p><p>Comments on latest version:</p><p>The authors have addressed my concerns.</p></body></sub-article><sub-article article-type="author-comment" id="sa3"><front-stub><article-id pub-id-type="doi">10.7554/eLife.101388.3.sa3</article-id><title-group><article-title>Author response</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Hotinger</surname><given-names>Julia A</given-names></name><role specific-use="author">Author</role><aff><institution>Division of Infectious Diseases, Brigham &amp; Women's Hospital</institution><addr-line><named-content content-type="city">Boston</named-content></addr-line><country>United States</country></aff></contrib><contrib contrib-type="author"><name><surname>Campbell</surname><given-names>Ian W</given-names></name><role specific-use="author">Author</role><aff><institution>Division of Infectious Diseases, Brigham &amp; Women's Hospital</institution><addr-line><named-content content-type="city">Boston</named-content></addr-line><country>United States</country></aff></contrib><contrib contrib-type="author"><name><surname>Hullahalli</surname><given-names>Karthik</given-names></name><role specific-use="author">Author</role><aff><institution>Harvard Medical School</institution><addr-line><named-content content-type="city">Boston</named-content></addr-line><country>United States</country></aff></contrib><contrib contrib-type="author"><name><surname>Osaki</surname><given-names>Akina</given-names></name><role specific-use="author">Author</role><aff><institution>Division of Infectious Diseases, Brigham &amp; Women's Hospital</institution><addr-line><named-content content-type="city">Boston</named-content></addr-line><country>United States</country></aff></contrib><contrib contrib-type="author"><name><surname>Waldor</surname><given-names>Matthew K</given-names></name><role specific-use="author">Author</role><aff><institution>Howard Hughes Medical Institute</institution><addr-line><named-content content-type="city">Boston</named-content></addr-line><country>United States</country></aff></contrib></contrib-group></front-stub><body><p>The following is the authors’ response to the original reviews.</p><disp-quote content-type="editor-comment"><p><bold>Public Reviews:</bold></p><p><bold>Reviewer #1 (Public review):</bold></p><p>Hotinger et al. explore the population dynamics of <italic>Salmonella enterica</italic> serovar Typhimurium in mice using genetically tagged bacteria. In addition to physiological observations, pathology assessments, and CFU measurements, the study emphasizes quantifying host bottleneck sizes that limit <italic>Salmonella</italic> colonization and dissemination. The authors also investigate the genetic distances between bacterial populations at various infection sites within the host.</p><p>Initially, the study confirms that pretreatment with the antibiotic streptomycin before inoculation via orogastric gavage increases the bacterial burden in the gastrointestinal (GI) tract, leading to more severe symptoms and heightened fecal shedding of bacteria. This pretreatment also significantly reduces between-animal variation in bacterial burden and fecal shedding. The authors then calculate founding population sizes across different organs, discovering a severe bottleneck in the intestine, with founding populations reduced by approximately 10^6-fold compared to the inoculum size. Streptomycin pretreatment increases the founding population size and bacterial replication in the GI tract. Moreover, by calculating genetic distances between populations, the authors demonstrate that, in untreated mice, <italic>Salmonella</italic> populations within the GI tract are genetically dissimilar, suggesting limited exchange between colonization sites. In contrast, streptomycin pretreatment reduces genetic distances, indicating increased exchange.</p><p>In extraintestinal organs, the bacterial burden is generally not substantially increased by streptomycin pretreatment, with significant differences observed only in the mesenteric lymph nodes and bile. However, the founding population sizes in these organs are increased. By comparing genetic distances between organs, the authors provide evidence that subpopulations colonizing extraintestinal organs diverge early after infection from those in the GI tract. This hypothesis is further tested by measuring bacterial burden and founding population sizes in the liver and GI tract at 5 and 120 hours post-infection. Additionally, they compare orogastric gavage infection with the less injurious method of infection via drinking, finding similar results for CFUs, founding populations, and genetic distances. These results argue against injuries during gavage as a route of direct infection.</p><p>To bypass bottlenecks associated with the GI tract, the authors compare intravenous (IV) and intraperitoneal (IP) routes of infection. They find approximately a 10-fold increase in bacterial burden and founding population size in immune-rich organs with IV/IP routes compared to orogastric gavage in streptomycin-pretreated animals. This difference is interpreted as a result of &quot;extra steps required to reach systemic organs.&quot;</p><p>While IP and IV routes yield similar results in immune-rich organs, IP infections lead to higher bacterial burdens in nearby sites, such as the pancreas, adipose tissue, and intraperitoneal wash, as well as somewhat increased founding population sizes. The authors correlate these findings with the presence of white lesions in adipose tissue. Genetic distance comparisons reveal that, apart from the spleen and liver, IP infections lead to genetically distinct populations in infected organs, whereas IV infections generally result in higher genetic similarity.</p><p>Finally, the authors investigate GI tract reseeding, identifying two distinct routes. They observe that the GI tracts of IP/IV-infected mice are colonized either by a clonal or a diversely tagged bacterial population. In clonally reseeded animals, the genetic distance within the GI tract is very low (often zero) compared to the bile population, which is predominantly clonal or pauciclonal. These animals also display pathological signs, such as cloudy/hardened bile and increased bacterial burden, leading the authors to conclude that the GI tract was reseeded by bacteria from the gallbladder bile. In contrast, animals reseeded by more complex bacterial populations show that bile contributes only a minor fraction of the tags. Given the large founding population size in these animals' GI tracts, which is larger than in orogastrically infected animals, the authors suggest a highly permissive second reseeding route, largely independent of bile. They speculate that this route may involve a reversal of known mechanisms that the pathogen uses to escape from the intestine.</p><p>The manuscript presents a substantial body of work that offers a meticulously detailed understanding of the population dynamics of S. Typhimurium in mice. It quantifies the processes shaping the within-host dynamics of this pathogen and provides new insights into its spread, including previously unrecognized dissemination routes. The methodology is appropriate and carefully executed, and the manuscript is well-written, clearly presented, and concise. The authors' conclusions are well-supported by experimental results and thoroughly discussed. This work underscores the power of using highly diverse barcoded pathogens to uncover the within-host population dynamics of infections and will likely inspire further investigations into the molecular mechanisms underlying the bottlenecks and dissemination routes described here.</p><p>Major point:</p><p>Substantial conclusions in the manuscript rely on genetic distance measurements using the Cavalli-Sforza chord distance. However, it is unclear whether these genetic distance measurements are independent of the founding population size. I would anticipate that in populations with larger founding population sizes, where the relative tag frequencies are closer to those in the inoculum, the genetic distances would appear smaller compared to populations with smaller founding sizes independent of their actual relatedness. This potential dependency could have implications for the interpretation of findings, such as those in Figures 2B and 2D, where antibiotic-pretreated animals consistently exhibit higher founding population sizes and smaller genetic distances compared to untreated animals.</p></disp-quote><p>Thank you for raising this important point regarding reliance on cord distances for gauging genetic distance in barcoded populations. The reviewer is correct that samples with more founders will be more similar to the inoculum and thus inherently more similar to other samples that also have more founders. However, creation of libraries containing very large numbers of unique barcodes can often circumvent this issue. In this case, the effect size of chance-based similarity is not large enough to change the interpretation of the data in Figures 2B and 2D. In our case, the library has ~6x10<sup>4</sup> barcodes, and the founding populations in Figure 2B are ~10<sup>3</sup>. Randomly resampling to create two populations of 10<sup>3</sup> cells from an initial population with 6x10<sup>4</sup> barcodes is expected to yield largely distinct populations with very little similarity. Thus, the similarity between streptomycin-treated populations in Figure 2D is likely the result of biology rather than chance.</p><disp-quote content-type="editor-comment"><p><bold>Reviewer #2 (Public review):</bold></p><p>In this paper, Hotinger et. al. propose an improved barcoded library system, called STAMPR, to study <italic>Salmonella</italic> population dynamics during infection. Using this system, the authors demonstrate significant diversity in the colonization of different <italic>Salmonella</italic> clones (defined by the presence of different barcodes) not only across different organs (liver, spleen, adipose tissues, pancreas, and gall bladder) but also within different compartments of the same gastrointestinal tissue. Additionally, this system revealed that microbiota competition is the major bottleneck in <italic>Salmonella</italic> intestinal colonization, which can be mitigated by streptomycin treatment. However, this has been demonstrated previously in numerous publications. They also show that there was minimal sharing between populations found in the intestine and those in the other organs. Upon IV and IP infection to bypass the intestinal bottleneck, they were able to demonstrate, using this library, that Salmonella can renter the intestine through two possible routes. One route is essentially the reverse path used to escape the gut, leading to a diverse intestinal population; while the other, through the bile, typically results in a clonal population. Although the authors showed that the STAMPR pipeline improved the ability to identify founder populations and their diversity within the same animal during infections, some of the conclusions appear speculative and not fully supported.</p><p>(1) It's particularly interesting how the authors, using this system, demonstrate the dominant role of the microbiota bottleneck in <italic>Salmonella</italic> colonization and how it is widened by antibiotic treatment (Figure 1). Additionally, the ability to track <italic>Salmonella</italic> reseeding of the gut from other organs starting with IV and IP injections of the pathogen provides a new tool to study population dynamics (Figure 5). However, I don't think it is possible to argue that the proximal and distal small intestine, Peyer's patches (PPs), cecum, colon, and feces have different founder populations for reasons other than stochastic variations. All the barcoded <italic>Salmonella</italic> clones have the same fitness and the fact that some are found or expanded in one region of the gastrointestinal tract rather than another likely results from random chance - such as being forced in a specific region of the gut for physical or spatial reasons-and subsequent expansion, rather than any inherent biological cause. For example, some bacteria may randomly adhere to the mucus, some may swim toward the epithelial layer, while others remain in the lumen; all will proliferate in those respective sites. In this way, different founder populations arise based on random localization during movement through the gastrointestinal tract, which is an observation, but it doesn't significantly contribute to understanding pathogen colonization dynamics or pathogenesis. Therefore, I would suggest placing less emphasis on describing these differences or better discussing this aspect, especially in the context of the gastrointestinal tract.</p></disp-quote><p>Thank you for helping us identify this area for further clarification. We agree with the reviewer’s interpretation that seeding of proximal and distal small intestine, Peyer's patches (PPs), cecum, colon, and feces with different founder populations is likely caused by stochastic variations, consistent with separate stochastic bottlenecks to establishing these separate niches. To clarify this point we have modified the text in the results section, “Streptomycin treatment decreases compartmentalization of <italic>S</italic>. Typhimurium populations within the intestine”.</p><p>Change to text:</p><p>“Except for the cecum and colon, in untreated animals the <italic>S</italic>. Typhimurium populations in different regions of the intestine were dissimilar (Avg. GD ranged from 0.369 to 0.729, 2D left); i.e., there is little sharing between populations in the intestine. These data suggest that there are separate bottlenecks in different regions of the intestine that cause stochastic differences in the identity of the founders. Interestingly, when these founders replicate, they do not mix, remaining compartmentalized with little sharing between populations throughout the intestinal tract (i.e., barcodes found in one region are not in other regions, Figure S3). This was surprising as the luminal contents, an environment presumably conducive to bacterial movement, were not removed from these samples.”</p><p>In this section we are interested in the underlying biology that occurs after the initial bottleneck to preserve this compartmentalization during outgrowth of the intestinal population. In other words, what prevents these separate populations from merging (e.g., what prevents the bacteria replicating in the proximal small intestine from traveling through the intestine and establishing a niche in the distal small intestine)? While we do not explore the mechanisms of compartmentalization, we observe that it is disrupted by streptomycin pretreatment, suggesting a microbiota-dependent biological cause.</p><disp-quote content-type="editor-comment"><p>(2) I do think that STAMPR is useful for studying the dynamics of pathogen spread to organs where <italic>Salmonella</italic> likely resides intracellularly (Figure 3). The observation that the liver is colonized by an early intestinal population, which continues to proliferate at a steady rate throughout the infection, is very interesting and may be due to the unique nature of the organ compared to the mucosal environment. What is the biological relevance during infection? Do the authors observe the same pattern (Figures 3C and G) when normalizing the population data for the spleen and mesenteric lymph nodes (mLN)? If not, what do the authors think is driving this different distribution?</p></disp-quote><p>Thank you for raising this interesting point. These data indicate that the liver is seeded from the intestine early during infection. The timing and source of dissemination have relevance for understanding how host and pathogen variables control the spread of bacteria to systemic sites. For example, our conclusion (early dissemination) indicates that the immune state of a host at the time of exposure to a pathogen, and for a short period thereafter, are what primarily influence the process of dissemination, not the later response to an active infection.</p><p>We observe that the liver and mucosal environments within the intestine have similar colonization behaviors. Both niches are seeded early during infection, followed by steady pathogen proliferation and compartmentalization that apparently inhibits further seeding. This results in the identity of barcodes in the liver population remaining distinct from the intestinal populations, and the intestinal populations remaining distinct from each other.</p><p>We observe a similar pattern to the liver in the spleen and MLN (the barcodes in the spleen and MLN are dissimilar to the population in the intestine). To clarify this point, we have modified the text (below) and added this analysis as a supplemental figure (S4).</p><p>Change to text:</p><p>Genetic distance comparison of liver samples to other sites revealed that, regardless of streptomycin treatment, there was very little sharing of barcodes between the intestine and extraintestinal sites (Avg. GD &gt;0.75, Figure 3C). Furthermore, the MLN and spleen populations also lacked similarity with the intestine (Figure S4). These analyses strongly support the idea that S. Typhimurium disseminates to extraintestinal organs relatively early following inoculation, before it establishes a replicative niche in the intestine.</p><disp-quote content-type="editor-comment"><p>(3) Figure 6: Could the bile pathology be due to increased general bacterial translocation rather than <italic>Salmonella</italic> colonization specifically? Did the authors check for the presence of other bacteria (potentially also proliferating) in the bile? Do the authors know whether Salmonella's metabolic activity in the bile could be responsible for gallbladder pathology?</p></disp-quote><p>The reviewer raises interesting points for future work. We did not check whether other bacterial species are translocating during <italic>S</italic>. Typhimurium infection. The relevance of <italic>Salmonella</italic>’s metabolic activity is also very interesting, and we hope these questions will be answered by future studies.</p><disp-quote content-type="editor-comment"><p><bold>Recommendations for the authors:</bold></p><p><bold>Reviewer #1 (Recommendations for the authors):</bold></p><p>Minor points:</p><p>(1) P. 9/10 &quot;... the marked delay in shedding after IP and IV relative to orogastric inoculation suggest that the S. Typhimurium population encounters substantial bottleneck(s) on the route(s) from extraintestinal sites back to the intestine.&quot;: Can you conclude that from the data? It could also be possible that there is a biological mechanism (other than chance events) that delays the re-entry to the intestine.</p></disp-quote><p>We propose that the delay in shedding indicates additional obstacles that bacteria face when re-entering the intestine, and that there are likely biological mechanisms that cause this delay. However, these unknown mechanisms effectively act as additional bottlenecks by causing a stochastic loss of population diversity.</p><disp-quote content-type="editor-comment"><p>(2) P. 11 &quot;...both organs would likely contain all 10 barcodes. In contrast, a library with 10,000 barcodes can be used to distinguish between a bottleneck resulting in Ns = 1,000 and Ns = 10,000, since these bottlenecks result in a different number of barcodes in output samples. Furthermore, high diversity libraries reduce the likelihood that two tissue samples share the same barcode(s) due to random chance, enabling more accurate quantification of bacterial dissemination.&quot;: I agree with the general analysis, but I find it misleading to talk about the presence of barcodes when the analyses in this manuscript are based on the much more powerful comparison of relative abundance of individual tags instead of their presence or absence.</p></disp-quote><p>The reviewer raises an excellent point, and the distinction between relative abundance versus presence/absence is discussed extensively in the original STAMPR manuscript. Although relative abundance is powerful, the primary metric used in this study (Ns) is calculated principally from the number of barcodes, corrected (via simulations) for the probability of observing the same barcode across distinct founders. Although this correction procedure does rely on barcode abundance, the primary driver of founding population quantification is the number of barcodes.</p><disp-quote content-type="editor-comment"><p>(3) P.14 &quot;the library in LB supplemented with SM was not significantly different than the parent strain&quot; and Figure 2C: How was significance tested? How many times were the growth curves recorded? On my print-out, the red color has different shades for different growth curves.</p></disp-quote><p>Significance was tested with a Mann-Whitney and growth curves were performed 5 times. Growth curves are displayed with 50% opacity, and as a result multiple curves directly on top of each other appear darker. The legend to S2 has been modified accordingly.</p><disp-quote content-type="editor-comment"><p>(4) P.16: close bracket in the equation for FRD calculation.</p></disp-quote><p>Done</p><disp-quote content-type="editor-comment"><p>(5) Figure 2C &quot;Average CFU per founder&quot;: I found the wording confusing at first as I thought you divided the average bacterial burden per organ by Ns, instead of averaging the CFU/Ns calculated for each mouse.</p></disp-quote><p>The wording has been clarified.</p><disp-quote content-type="editor-comment"><p>(6) Figure 3B: It would be helpful to include expected genetic distances in the schematic as it is difficult to infer the genetic distance when only two of three, respectively, different &quot;barcode colors&quot; are used. While I find the explanation in the main text intuitive, a graphical representation would have helped me.</p></disp-quote><p>Thank you for the suggestion. Unfortunately, using colors to represent barcodes is imperfect and limits the diversity that can be depicted. We have modified Figure 3B to further clarify.</p><disp-quote content-type="editor-comment"><p>(7) Figure 3C: Why do you compare the genetic distance to the liver, when you discuss the genetic distance of the intestinal population? Is it not possible that the intestinal populations are similar to the extraintestinal organs except the liver?</p></disp-quote><p>For clarity, we chose to highlight exclusively the liver. However, we observed a similar pattern to the liver in other extraintestinal organs. To clarify the generalizability of this point we have added a supplemental figure with comparisons to MLN and Spleen (Supplemental figure S4) as well as further text.</p><disp-quote content-type="editor-comment"><p>(8) Figure 3C &amp; S5A: I found &quot;+SM&quot; and &quot;+SM, Drinking&quot; confusing and would have preferred &quot;+SM, Gavage&quot; and &quot;+SM, Drinking&quot; for clarity.</p></disp-quote><p>Done, thank you for the suggestion.</p><disp-quote content-type="editor-comment"><p>(9) Figure 3G&amp;H: I find it worthy of discussion that the bacterial burden increases over time, while the founding population decreases. Does that not indicate that replication only occurs at specific sites leading to the amplification of only a few barcodes and thereby a larger change of the relative barcode abundance compared to the inoculum?</p></disp-quote><p>From 5h to 120h the size of the founding population decreases in multiple intestinal sites. This likely indicates that the impact of the initial bottleneck is still ongoing at 5h, although further temporal analysis would be required to define the exact timing of the bottleneck. Notably, the passage time through the mouse intestine is ~5h. Many of the founders observed at 5h could be a population that will never establish a replicative niche, and failing to colonize be shed in the feces, bottlenecking the population between 5h and 120h. To clarify this point we have added the following text:</p><p>Section “S. Typhimurium disseminates out of the intestine before establishing an intestinal replicative niche”.</p><p>“In contrast to the liver, there were more founders present in samples from the intestine (particularly in the colon) at 5 hours versus 120 hours (Figure 3H). These data likely indicate that many of the founders observed in the intestine at 5 hours are shed in the feces prior to establishing a replicative niche, and demonstrates that the forces restricting the S. Typhimurium population in the intestine act over a period of &gt; 5 hours.”</p><disp-quote content-type="editor-comment"><p>(10) Figure S2A: I do not understand this figure. Why are there more than 70.000 tags listed? I was under the impression the barcode library in S. Typhimurium had 55.000 tags while only the plasmid pSM1 had more than 70.000 (but the plasmid should not be relevant here). Why are there distinct lines at approximately 10^-5 and a bit lower? I would have expected continuously distributed barcode frequencies.</p></disp-quote><p>During barcode analysis, each library is mapped to the total barcode list in the barcode donor pSM1, which contains ~70,000 barcodes. This enables consistent analysis across different bacterial libraries. The designation “barcode number” refers to the barcode number in pSM1, meaning many of the barcodes in the <italic>Salmonella</italic> library are at zero reads. This graph type was chosen to show there was no bias toward a particular barcode, however there is significant overlap of the points, making individual barcode frequencies difficult to see. We have changed the x-axis to state “pSM1 Barcode Number” and clarified in the figure legend.</p><p>Since the y-axes on these graphs is on a log10 scale, the lines represent barcodes with 1 read, 2 reads, 3 reads, etc. As the number of reads per barcode increases linearly, the space between them decreases on logarithmic axes.</p><disp-quote content-type="editor-comment"><p>(11) There are a few typos in the figure legends of the supplementary material. For example Figure S2: S. Typhimurium not italicized, ~7x105 no superscript. Fig. S4&amp;5 &quot;, Open circles&quot; is &quot;O&quot; is capitalized.</p></disp-quote><p>Typos have been corrected.</p></body></sub-article></article>