0 - Prep

Data for this project is from the COPSAC₂₀₁₀ cohort of 711 children / mother pairs. In this project we include vaginal samples (week 24 and week 36), airway samples (1 week, 1 month, and 3 months), and fecal samples (1 week, 1 month, and 1 year) for all mother-child dyads which include a week 36 vaginal sample (665 mothers and 651 children). We describe the vaginal microbiome development from mid pregnancy (week 24) to late pregnancy (week 36), and the transfer to the airways and gut of the children in the first year of life. A special focus is on the differences between transfer to vaginal and sectio born children. All tables created as part of this analysis can also be found in the Source data 1 file Supplementary_results_tables.xlsx

0.1 - Load libraries

0.2 Download main data

COPSACbirthmicrobiome_ASV.RData contains the phyloseq object that is used for all subsequent analysis and with this the whole analysis can be easily replicated

0.3 Download precalculated data

To reduce the computational requirements during this analysis, we have precalculated the most computer intensive parts and if these are downloaded the calculations can be skipped. This means that you can either run this code chunk or all following code chunks which are currently set not to be evaluated.

0.4 - Overview of samples, read counts and observed richness

Phyloseq object used:

## phyloseq-class experiment-level object
## otu_table()   OTU Table:         [ 15514 taxa and 4756 samples ]
## sample_data() Sample Data:       [ 4756 samples by 4 sample variables ]
## tax_table()   Taxonomy Table:    [ 15514 taxa by 10 taxonomic ranks ]
## phy_tree()    Phylogenetic Tree: [ 15514 tips and 15356 internal nodes ]

Sample count per time and type
Time	Samples
Vaginal
Week_24	657
Week_36	665
Fecal
One_week	533
One_month	575
One_year	580
Airway
One_week	526
One_month	606
Three_months	614

ASVs observed per compartment
Compartment	ASVs
Vaginal	3287
Fecal	6818
Airways	7500

Histogram of sequencing depth of study samples by type and time point

Summary stats for compartment
	Count					Observed Richness
Type	Median	Mean	SD	Q25	Q75	Median	Mean	SD	Min	Max	Q25	Q75
Vaginal	50121.0	53875.3	23442.5	38329.8	64631.5	20	25.0	18.8	2	167	12	32
Fecal	50014.5	55171.8	38967.9	30132.2	75199.0	37	45.2	27.3	6	298	26	60
Airway	51232.0	54496.2	35433.9	29259.2	73810.5	26	28.8	15.6	1	231	19	36

Summary stats for compartment/time point
		Count					Observed Richness
Type	Time	Median	Mean	SD	Q25	Q75	Median	Mean	SD	Min	Max	Q25	Q75
Vaginal	Week_24	49918.0	53074.2	23023.6	37689.0	63701.0	20	25.3	17.9	2	125	13	32.0
Vaginal	Week_36	50341.0	54666.7	23840.0	38704.0	65933.0	19	24.7	19.7	2	167	11	31.0
Fecal	One_week	53540.0	59559.5	44625.8	23051.0	91744.0	29	32.1	19.1	8	298	22	37.0
Fecal	One_month	51612.0	57232.7	41400.8	33938.5	75985.5	29	31.9	15.0	6	175	22	39.0
Fecal	One_year	47810.0	49096.4	28920.9	31266.0	63858.5	67	70.5	25.3	12	175	54	84.2
Airway	One_week	45304.5	51252.8	35794.3	23772.5	72282.2	20	22.6	13.3	2	231	16	26.0
Airway	One_month	58918.0	60030.7	35014.2	40285.5	77725.5	27	29.1	16.2	3	226	20	35.0
Airway	Three_months	46566.0	51812.3	34933.3	27468.2	70207.2	33	34.0	14.9	1	114	24	44.0

1 - Vaginal microbiome

1.1 - Data prep

vag_taxglm.RData contains phyloseq objects with vaginal samples at phylum, genus and ASV level for both read counts and relative abundances, as well as a rarefied (2000 reads/sample) at ASV level. OrdinationRes.RData contains weighted UniFrac distances and jensen-Shannon divergence, as well as NMDS ordinations of both

1.2 - Observed vaginal ASV’s:

The distribution of the vaginal reads are here summarized on phylum, genus and individual ASV level.

Count of phyla, genera, and ASV in vaginal samples
Included	Phylum	Genus	ASV
All	28	463	3287
> 0.01%	16	193	958
> 0.1%	10	94	420
> 1%	8	41	173

Average abundance according to phylum
Kingdom	Phylum	taxprc
Bacteria	Firmicutes	85.2
Bacteria	Actinobacteria	12.0
Bacteria	Proteobacteria	1.5
Bacteria	Bacteroidetes	0.8
Bacteria	Fusobacteria	0.2
Bacteria	Tenericutes	0.1

Average abundance according to genus
Kingdom	Phylum	Class	Order	Family	Genus	taxprc
Bacteria	Firmicutes	Bacilli	Lactobacillales	Lactobacillaceae	Lactobacillus	81.1
Bacteria	Actinobacteria	Actinobacteria	Bifidobacteriales	Bifidobacteriaceae	Gardnerella	9.0
Bacteria	Actinobacteria	Actinobacteria	Bifidobacteriales	Bifidobacteriaceae	Bifidobacterium	1.4
Bacteria	Actinobacteria	Coriobacteriia	Coriobacteriales	Atopobiaceae	Atopobium	1.3
Bacteria	Proteobacteria	Gammaproteobacteria	Enterobacteriales	Enterobacteriaceae	Escherichia_Shigella	1.2
Bacteria	Firmicutes	Negativicutes	Selenomonadales	Veillonellaceae	Megasphaera	0.9

Average abundance according to ASV
Kingdom	Phylum	Class	Order	Family	Genus	Species	name	taxprc
Bacteria	Firmicutes	Bacilli	Lactobacillales	Lactobacillaceae	Lactobacillus	Genus_Lactobacillus	Genus_Lactobacillus_323	31.5
Bacteria	Firmicutes	Bacilli	Lactobacillales	Lactobacillaceae	Lactobacillus	Genus_Lactobacillus	Genus_Lactobacillus_139	29.5
Bacteria	Firmicutes	Bacilli	Lactobacillales	Lactobacillaceae	Lactobacillus	Lactobacillus_gasseri	Lactobacillus_gasseri_37	10.4
Bacteria	Actinobacteria	Actinobacteria	Bifidobacteriales	Bifidobacteriaceae	Gardnerella	Genus_Gardnerella	Genus_Gardnerella_40	4.6
Bacteria	Firmicutes	Bacilli	Lactobacillales	Lactobacillaceae	Lactobacillus	Genus_Lactobacillus	Genus_Lactobacillus_268	4.5
Bacteria	Actinobacteria	Actinobacteria	Bifidobacteriales	Bifidobacteriaceae	Gardnerella	Genus_Gardnerella	Genus_Gardnerella_20	3.8

1.3 - Community State Types

The vaginal microbiome is not a smooth continoum, but a set of very well defined clusters, here refered to as Community State Types (CST), and a few less well defined clusters. These are identified by clustering of all the samples based on Jensen Shannon Divergence as beta diversity measure. Partitioning around medoids clustering is then performed for a range of possible clusters and the optimal number defined based on various cluster statistics.

1.3.1 - Define Community State Types

1.3.1.1 - Find optimal number of clusters

Barplots of clustering statistics for 3-9 clusters

Based on the Pearson version of Hubert’s gamma coefficient (pearsongamma), average silhouette width (avg.silwidth) and the Calinski and Harabasz index (ch) 5 or 6 clusters is optimal. Considering the Dunn2 index we consider 6 clusters to be optimal. These are refered to as community state types I to V, with IV being split into IV-a and IV-b.

1.3.1.2 - Create CSTs

The ASVs for the top ASVs in each CST are written to BlastData.xlsx, Blast results and identified species for each ASV have then been added to this file externally.

phyX_cst.RData contains the updated phyloseq objects for all samples (phyX), vaginal samples (vagX), and rarefied vaginal samples (vagX.r)

1.3.2 - CST composition and stability

1.3.2.1 - Prepare data

CommunityStateTypes.RData contains the necessary data regarding dominant taxa and alpha diversity of the CSTs

1.3.2.2 - Describe CST composition and stability

Observed richness and shannon diversity index (SDI) for each CST
		Observed Richness		Shannon Diversity index
CST	Samples (n)	Mean	SD	Mean	SD
CST_I	479	13.44	10.68	0.48	0.47
CST_II	172	18.31	15.68	0.90	0.61
CST_III	446	12.37	9.85	0.55	0.52
CST_IV_a	86	22.21	15.79	1.30	0.71
CST_IV_b	68	19.82	14.53	1.23	0.59
CST_V	71	14.32	11.44	0.89	0.47

Anova statistical test of alpha diversity by CST
Overall differences in observed richness between CSTs

## Analysis of Variance Table
## 
## Response: Observed
##             Df Sum Sq Mean Sq F value    Pr(>F)    
## CST          5  12075 2414.94  17.245 < 2.2e-16 ***
## Residuals 1316 184286  140.04                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Multiple comparison of differences in observed richness between all pairs of CSTs

##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = Observed ~ CST, data = cst.alpha)
## 
## $CST
##                         diff         lwr        upr     p adj
## CST_II-CST_I       4.8734524   1.8713975  7.8755074 0.0000581
## CST_III-CST_I     -1.0727880  -3.2950528  1.1494767 0.7405034
## CST_IV_a-CST_I     8.7688013   4.8136112 12.7239914 0.0000000
## CST_IV_b-CST_I     6.3830284   2.0064816 10.7595751 0.0004797
## CST_V-CST_I        0.8834426  -3.4113731  5.1782584 0.9919023
## CST_III-CST_II    -5.9462405  -8.9774971 -2.9149838 0.0000004
## CST_IV_a-CST_II    3.8953488  -0.5648737  8.3555714 0.1269766
## CST_IV_b-CST_II    1.5095759  -3.3282146  6.3473665 0.9488339
## CST_V-CST_II      -3.9900098  -8.7539891  0.7739694 0.1603017
## CST_IV_a-CST_III   9.8415893   5.8641892 13.8189894 0.0000000
## CST_IV_b-CST_III   7.4558164   3.0591877 11.8524452 0.0000215
## CST_V-CST_III      1.9562307  -2.3590474  6.2715088 0.7885822
## CST_IV_b-CST_IV_a -2.3857729  -7.8662302  3.0946844 0.8158579
## CST_V-CST_IV_a    -7.8853587 -13.3007712 -2.4699461 0.0004936
## CST_V-CST_IV_b    -5.4995857 -11.2299719  0.2308004 0.0684618

Overall differences in Shannon diversity index between CSTs

## Analysis of Variance Table
## 
## Response: Shannon
##             Df Sum Sq Mean Sq F value    Pr(>F)    
## CST          5  92.71 18.5411   66.18 < 2.2e-16 ***
## Residuals 1316 368.69  0.2802                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Multiple comparison of differences in Shannon diversity index between all pairs of CSTs

##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = Shannon ~ CST, data = cst.alpha)
## 
## $CST
##                          diff         lwr        upr     p adj
## CST_II-CST_I       0.42730580  0.29302794  0.5615836 0.0000000
## CST_III-CST_I      0.07762367 -0.02177523  0.1770226 0.2251923
## CST_IV_a-CST_I     0.82552360  0.64861330  1.0024339 0.0000000
## CST_IV_b-CST_I     0.75856486  0.56280786  0.9543219 0.0000000
## CST_V-CST_I        0.40995745  0.21785616  0.6020587 0.0000000
## CST_III-CST_II    -0.34968213 -0.48526613 -0.2140981 0.0000000
## CST_IV_a-CST_II    0.39821780  0.19871809  0.5977175 0.0000002
## CST_IV_b-CST_II    0.33125907  0.11487125  0.5476469 0.0001950
## CST_V-CST_II      -0.01734834 -0.23043468  0.1957380 0.9999077
## CST_IV_a-CST_III   0.74789993  0.56999621  0.9258037 0.0000000
## CST_IV_b-CST_III   0.68094120  0.48428595  0.8775964 0.0000000
## CST_V-CST_III      0.33233379  0.13931724  0.5253503 0.0000149
## CST_IV_b-CST_IV_a -0.06695873 -0.31209217  0.1781747 0.9709838
## CST_V-CST_IV_a    -0.41556614 -0.65779021 -0.1733421 0.0000162
## CST_V-CST_IV_b    -0.34860741 -0.60491982 -0.0922950 0.0015199

Top five Phylums / Genus / ASVs for each CST
	Phylum		Genus		ASV
Rank	Phylum	Abundance (%)	Genus	Abundance (%)	ASV	Abundance (%)
CST I
1	Firmicutes	94.95	Lactobacillus	91.94	Genus_Lactobacillus_323	84.35
2	Actinobacteria	3.32	Bifidobacterium	1.84	Genus_Lactobacillus_139	2.60
3	Proteobacteria	1.25	Enterococcus	1.11	Genus_Bifidobacterium_60	1.54
4	Bacteroidetes	0.27	Escherichia_Shigella	1.02	Genus_Enterococcus_34	1.15
5	Tenericutes	0.12	Gardnerella	0.96	Genus_Escherichia_Shigella_101	0.85
CST II
1	Firmicutes	84.91	Lactobacillus	80.21	Lactobacillus_gasseri_37	70.65
2	Actinobacteria	11.54	Gardnerella	6.85	Genus_Gardnerella_40	4.04
3	Proteobacteria	1.94	Bifidobacterium	2.69	Genus_Gardnerella_20	2.49
4	Bacteroidetes	1.31	Escherichia_Shigella	1.60	Genus_Bifidobacterium_60	2.44
5	Epsilonbacteraeota	0.17	Atopobium	1.36	Lactobacillus_gasseri_47	2.24
CST III
1	Firmicutes	92.34	Lactobacillus	89.23	Genus_Lactobacillus_139	81.17
2	Actinobacteria	5.03	Gardnerella	3.67	Genus_Lactobacillus_268	2.55
3	Proteobacteria	1.69	Escherichia_Shigella	1.20	Genus_Lactobacillus_323	2.03
4	Bacteroidetes	0.48	Megasphaera	0.93	Genus_Gardnerella_20	1.55
5	Fusobacteria	0.34	Bifidobacterium	0.85	Genus_Gardnerella_40	1.53
CST IV a
1	Actinobacteria	62.40	Gardnerella	58.26	Genus_Gardnerella_40	51.17
2	Firmicutes	32.20	Lactobacillus	19.53	Genus_Gardnerella_20	6.17
3	Bacteroidetes	2.84	Megasphaera	5.52	Genus_Megasphaera_22	5.33
4	Fusobacteria	0.88	Atopobium	3.57	Genus_Lactobacillus_139	4.82
5	Proteobacteria	0.82	Prevotella	2.54	Lactobacillus_gasseri_37	3.96
CST IV b
1	Actinobacteria	61.31	Gardnerella	46.75	Genus_Gardnerella_20	45.28
2	Firmicutes	32.48	Lactobacillus	24.44	Genus_Atopobium_36	12.89
3	Proteobacteria	2.76	Atopobium	12.64	Lactobacillus_gasseri_37	12.84
4	Bacteroidetes	2.42	Escherichia_Shigella	2.55	Genus_Lactobacillus_323	2.64
5	Fusobacteria	0.59	Prevotella	2.26	Genus_Escherichia_Shigella_101	2.59
CST V
1	Firmicutes	89.33	Lactobacillus	87.62	Genus_Lactobacillus_268	60.76
2	Actinobacteria	7.93	Gardnerella	6.09	Genus_Lactobacillus_139	20.64
3	Proteobacteria	1.41	Atopobium	1.62	Genus_Gardnerella_20	2.69
4	Bacteroidetes	1.00	Prevotella	0.95	Genus_Gardnerella_7	2.01
5	Epsilonbacteraeota	0.20	Escherichia_Shigella	0.89	Genus_Lactobacillus_265	1.71

Figure 1: Vaginal community state type (CST). (A) Boxplot of top Amplicon sequence variant (ASV) abundance for each CST (including two most abundant ASVs from each CST), (B) boxplot of observed richness by CST, (c) boxplot of Shannon diversity index by CST, and (D) alluvial plot showing the CST at weeks 24–36 for each woman. All plots are colored by the CST.

1.3.2.3 - Stability between w24 and w36 (Permutational)

In order to test the stability between time points, a permutation procedure is used. Here, the distance based on individual women from week 24 to week 36 are compared with random assignments of pairs.

1.3.2.3.1 - Perform permutation calculations

Stability_w24_to_w36_permresults.RData contains the permutation results for CST stability

1.3.2.3.2 - CST stability results

overall stability of CSTs from week 24 to week 36
Women	In same (%)	Changed (%)
657	562 (85.5)	95 (14.5)

CST dependent stability from week 24 to week 36
CST	Time point (week)	Women	In same (%)
CST_I	24	239	221 (92.5)
CST_I	36	237	221 (93.2)
CST_II	24	86	70 (81.4)
CST_II	36	84	70 (83.3)
CST_III	24	213	194 (91.1)
CST_III	36	232	194 (83.6)
CST_IV_a	24	45	30 (66.7)
CST_IV_a	36	41	30 (73.2)
CST_IV_b	24	35	21 (60.0)
CST_IV_b	36	31	21 (67.7)
CST_V	24	39	26 (66.7)
CST_V	36	32	26 (81.2)

Pearson’s Chi-squared test of CST stability

## 
##  Pearson's Chi-squared test
## 
## data:  df.cst.24$w36 by df.cst.24$CST 
## X-squared = 58.4038, df = 5, p-value = 2.596e-11
## alternative hypothesis: true difference in probabilities is not equal to 0 
## sample estimates:
##    proba in group CST_I   proba in group CST_II  proba in group CST_III 
##               0.9246862               0.8139535               0.9107981 
## proba in group CST_IV_a proba in group CST_IV_b    proba in group CST_V 
##               0.6666667               0.6000000               0.6666667 
## 
##         Pairwise comparisons using Pearson's Chi-squared tests with Yates' continuity correction
## 
##              CST_I  CST_II   CST_III CST_IV_a CST_IV_b
## CST_II   1.617e-02       -         -        -        -
## CST_III  7.758e-01 0.05140         -        -        -
## CST_IV_a 1.293e-05 0.14324 9.690e-05        -        -
## CST_IV_b 1.699e-06 0.04716 1.293e-05   0.7758        -
## CST_V    2.903e-05 0.15598 1.968e-04   1.0000   0.7758
## 
## P value adjustment method: fdr

Distance from week 24 to week 36 samples within pairs (internal) and to randomly paired women (external, # permutations = 2500)
		Median distance
Distance metric	pairs	internal	external	Ratio^*	p-value
jsd	657	0.03090	0.63491	20.54648	4e-04
wuf	657	0.00258	0.00974	3.77142	4e-04
^* external / internal distance

Stability between week 24 and week 36 dependent on week 24 CST
CST	Samples (n)	Median distance
Jensen-Shannon divergence
CST_I	239	0.0232
CST_II	86	0.0639
CST_III	213	0.0220
CST_IV_a	45	0.0763
CST_IV_b	35	0.0927
CST_V	39	0.0680
Weighted UniFrac distances
CST_I	239	0.0016
CST_II	86	0.0160
CST_III	213	0.0014
CST_IV_a	45	0.0057
CST_IV_b	35	0.0095
CST_V	39	0.0039

Barplot of median Jensen-Shannon divergence (jsd) and Weighted UniFrac distance between each woman’s vaginal samples by CSTs

Inference (kruskal walis) for differences in stability between week 24 and week 36 dependent on week 24 CST
Distance metric	Rank sum statistic	p-value	degrees of freedom
jsd	49.6	1.66e-09	5
wuf	143	4.02e-29	5

The statistics indicate that stability depends on CST.

1.4 Beta diversity of vaginal

Here PCoA plots show the distirbution of the samples based on CST and beta diversity metric. Clearly, some of the CST are more well defined than others. E.g. CST_IV_b and CST_IV_c are all over the place. This is further confirmed by the statistical analysis of the betadispertion wich clearly show that CST IVa and CST IVb are significantly more dispersed than the other CSTs, with CST I and CST II being the tightest clusters

1.4.1 - NMDS plot of vaginal samples

Figure 1-figure supplement 1: Non-metric multidimenionsal scaling plot based on Jensen–Shannon divergence; samples colored by community state type (CST), and gray lines connect samples from the individual women

1.4.2 - Statistical test of beta diversity

Betadisper test differences in dispersion of each cluster
Overall differences between CSTs

## Analysis of Variance Table
## 
## Response: Distances
##             Df  Sum Sq Mean Sq F value    Pr(>F)    
## Groups       5  3.3709 0.67418  43.072 < 2.2e-16 ***
## Residuals 1316 20.5984 0.01565                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Multiple comparison of differences between all pairs of CSTs

##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = distances ~ group, data = df)
## 
## $group
##                          diff          lwr          upr     p adj
## CST_II-CST_I       0.06275195  0.031013266  0.094490639 0.0000003
## CST_III-CST_I      0.01589486 -0.007599637  0.039389352 0.3836737
## CST_IV_a-CST_I     0.14997156  0.108156027  0.191787100 0.0000000
## CST_IV_b-CST_I     0.16691971  0.120649452  0.213189960 0.0000000
## CST_V-CST_I        0.08410557  0.038699403  0.129511738 0.0000022
## CST_III-CST_II    -0.04685709 -0.078904511 -0.014809679 0.0004588
## CST_IV_a-CST_II    0.08721961  0.040064710  0.134374512 0.0000023
## CST_IV_b-CST_II    0.10416775  0.053021083  0.155314425 0.0000001
## CST_V-CST_II       0.02135362 -0.029012696  0.071719933 0.8321304
## CST_IV_a-CST_III   0.13407671  0.092026358  0.176127054 0.0000000
## CST_IV_b-CST_III   0.15102485  0.104542281  0.197507416 0.0000000
## CST_V-CST_III      0.06821071  0.022588211  0.113833216 0.0003058
## CST_IV_b-CST_IV_a  0.01694814 -0.040993007  0.074889293 0.9610337
## CST_V-CST_IV_a    -0.06586599 -0.123119468 -0.008612516 0.0134341
## CST_V-CST_IV_b    -0.08281414 -0.143397613 -0.022230657 0.0014063

Boxplot of betadispertion per CST

PERMANOVA of Time point using Jensen-Shannon divergence

## 
## Call:
## adonis(formula = vag.jsd ~ Time, data = df) 
## 
## Permutation: free
## Number of permutations: 999
## 
## Terms added sequentially (first to last)
## 
##             Df SumsOfSqs  MeanSqs F.Model      R2 Pr(>F)
## Time         1     0.046 0.046152 0.30907 0.00023  0.868
## Residuals 1320   197.113 0.149328         0.99977       
## Total     1321   197.159                  1.00000

PERMANOVA of CST using Jensen-Shannon divergence

## 
## Call:
## adonis(formula = vag.jsd ~ CST, data = df) 
## 
## Permutation: free
## Number of permutations: 999
## 
## Terms added sequentially (first to last)
## 
##             Df SumsOfSqs MeanSqs F.Model      R2 Pr(>F)    
## CST          5   158.310  31.662  1072.5 0.80296  0.001 ***
## Residuals 1316    38.849   0.030         0.19704           
## Total     1321   197.159                 1.00000           
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

2 - Infant Samples

2.1 - Delivery mode

Summary of delivery mode
	Children
Delivery	n	%
Vaginal	519	79.8
In labor CS	68	10.5
Scheduled CS	63	9.7

2.2 - Airway microbiome

2.2.1 - Subset airway samples

air_taxglm.RData contains phyloseq objects with airway samples at phylum, genus and ASV level for both read counts and relative abundances, as well as a rarefied (2000 reads/sample) at ASV level.

2.2.2 - Dominant airway taxa and overall richness

2.2.2.1 - tables

The distribution of the airway reads are here summarized on phylum, genus and individual ASV level.

Abundance of phyla, genera, and ASV in airway samples
Included	Phylum	Genus	ASV
All	35	828	7500
> 0.01%	13	107	288
> 0.1%	8	37	58
> 1%	4	10	13

Average abundance according to phylum
Kingdom	Phylum	Abundance (%)
Bacteria	Firmicutes	60.8
Bacteria	Proteobacteria	30.4
Bacteria	Actinobacteria	5.5
Bacteria	Bacteroidetes	1.7
Bacteria	Fusobacteria	0.7
Bacteria	Cyanobacteria	0.3

Average abundance according to genus
Kingdom	Phylum	Class	Order	Family	Genus	Abundance (%)
Bacteria	Firmicutes	Bacilli	Bacillales	Staphylococcaceae	Staphylococcus	25.6
Bacteria	Firmicutes	Bacilli	Lactobacillales	Streptococcaceae	Streptococcus	25.6
Bacteria	Proteobacteria	Gammaproteobacteria	Pseudomonadales	Moraxellaceae	Moraxella	14.8
Bacteria	Proteobacteria	Gammaproteobacteria	Pasteurellales	Pasteurellaceae	Haemophilus	6.0
Bacteria	Actinobacteria	Actinobacteria	Corynebacteriales	Corynebacteriaceae	Corynebacterium	4.1
Bacteria	Firmicutes	Bacilli	Bacillales	Bacillales_family_XI	Gemella	3.2

Average abundance according to ASV
Kingdom	Phylum	Class	Order	Family	Genus	Species	ASV	Abundance (%)
Bacteria	Firmicutes	Bacilli	Bacillales	Staphylococcaceae	Staphylococcus	Genus_Staphylococcus	Genus_Staphylococcus_205	24.2
Bacteria	Firmicutes	Bacilli	Lactobacillales	Streptococcaceae	Streptococcus	Genus_Streptococcus	Genus_Streptococcus_177	18.4
Bacteria	Proteobacteria	Gammaproteobacteria	Pseudomonadales	Moraxellaceae	Moraxella	Genus_Moraxella	Genus_Moraxella_95	13.7
Bacteria	Proteobacteria	Gammaproteobacteria	Pasteurellales	Pasteurellaceae	Haemophilus	Genus_Haemophilus	Genus_Haemophilus_69	3.5
Bacteria	Firmicutes	Bacilli	Lactobacillales	Streptococcaceae	Streptococcus	Streptococcus_pneumoniae	Streptococcus_pneumoniae_98	3.4
Bacteria	Firmicutes	Bacilli	Bacillales	Bacillales_family_XI	Gemella	Genus_Gemella	Genus_Gemella_53	3.1

2.2.2.2 - Plot

Figure 2A: Boxplot of top genera with mean abundance of 5% at least one time point. Abundance is plotted on a log10 scale, and all abundances below 0.1% have been set to 0.1% in the plot.

2.2.3 - Airway alpha diversity

For this part we use the rarefied samples (2000 reads/sample)

Summary of alpha diversity by time
		Observed Richness		Shannon Diversity index
Time	Samples (n)	Mean	SD	Mean	SD
One_week	526	16.580	9.532	1.114	0.635
One_month	606	20.467	11.292	1.326	0.612
Three_months	614	25.125	11.103	1.518	0.630

Summary of alpha diversity by time and delivery
		Observed Richness		Shannon Diversity index
Delivery mode	Samples (n)	Mean	SD	Mean	SD
One_week
In labor CS	50	15.740	5.830	1.002	0.644
Scheduled CS	52	15.462	6.314	1.110	0.668
Vaginal	424	16.816	10.185	1.128	0.629
One_month
In labor CS	64	20.703	8.883	1.446	0.698
Scheduled CS	62	17.855	7.149	1.289	0.568
Vaginal	480	20.773	11.966	1.315	0.605
Three_months
In labor CS	65	25.677	11.741	1.560	0.663
Scheduled CS	60	22.750	10.388	1.462	0.653
Vaginal	489	25.344	11.088	1.519	0.624

Outliers not plotted in Figure 2B (Observed richness > 100)
Child	Time point	Delivery	Mother’s CST (week 36)	Observed richness
dyad464	One_month	Vaginal	CST_I	126
dyad342	One_month	Vaginal	CST_I	153
dyad408	One_week	Vaginal	CST_III	145

Figure 2 B-C: Boxplot of alpha diversity, (B) observed richness, and (C) Shannon diversity index, by delivery mode.

Anova statistical test of alpha diversity by Time and Delivery
Overall differences in observed richness

## Analysis of Variance Table
## 
## Response: Observed
##             Df Sum Sq Mean Sq F value  Pr(>F)    
## Time         2  20891 10445.5 91.1252 < 2e-16 ***
## DELIVERY     2    846   423.0  3.6903 0.02516 *  
## Residuals 1741 199568   114.6                    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Multiple comparison of differences in observed richness

##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = Observed ~ Time + DELIVERY, data = df.adiv)
## 
## $Time
##                            diff      lwr       upr p adj
## One_month-One_week     3.887149 2.390517  5.383780     0
## Three_months-One_week  8.545559 7.053465 10.037653     0
## Three_months-One_month 4.658410 3.220340  6.096481     0
## 
## $DELIVERY
##                                diff        lwr       upr     p adj
## Scheduled CS-In labor CS -2.1341848 -4.8078501 0.5394805 0.1470299
## Vaginal-In labor CS       0.2037826 -1.7903087 2.1978739 0.9688195
## Vaginal-Scheduled CS      2.3379674  0.3186474 4.3572874 0.0183126

Overall differences in shannon diversity index

## Analysis of Variance Table
## 
## Response: Shannon
##             Df Sum Sq Mean Sq F value Pr(>F)    
## Time         2  46.25 23.1232 59.1001 <2e-16 ***
## DELIVERY     2   0.33  0.1652  0.4222 0.6557    
## Residuals 1741 681.18  0.3913                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Multiple comparison of differences in shannon diversity index

##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = Shannon ~ Time + DELIVERY, data = df.adiv)
## 
## $Time
##                             diff       lwr       upr p adj
## One_month-One_week     0.2118842 0.1244465 0.2993219 0e+00
## Three_months-One_week  0.4039750 0.3168024 0.4911476 0e+00
## Three_months-One_month 0.1920908 0.1080744 0.2761072 3e-07
## 
## $DELIVERY
##                                 diff         lwr        upr     p adj
## Scheduled CS-In labor CS -0.06077442 -0.21697796 0.09542912 0.6323593
## Vaginal-In labor CS      -0.02598445 -0.14248524 0.09051634 0.8600079
## Vaginal-Scheduled CS      0.03478997 -0.08318476 0.15276469 0.7683547

Alpha diversity does not differ dependent on mothers vaginal CST at week 36

## Analysis of Variance Table
## 
## Response: Observed
##             Df Sum Sq Mean Sq F value Pr(>F)    
## Time         2  20891 10445.5 90.9177 <2e-16 ***
## CST_w36      5    735   147.0  1.2799 0.2698    
## Residuals 1738 199679   114.9                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

## Analysis of Variance Table
## 
## Response: Shannon
##             Df Sum Sq Mean Sq F value Pr(>F)    
## Time         2  46.25 23.1232 59.1229 <2e-16 ***
## CST_w36      5   1.77  0.3533  0.9033 0.4779    
## Residuals 1738 679.74  0.3911                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

2.2.4 - Airway beta diversity

2.2.4.1 - Preparation

Calculation of Weighted UniFrac distances and NMDS ordination for airway samples

air_OrdinationRes.RData contains weighted UniFrac distances and NMDS ordination of the airway samples

2.2.4.2 - Plots and statistics

Figure 2D-E: Non-metric multidimensional scaling plots based on weighted UniFrac distances. Samples from the same individual are connected by gray lines. All plots are colored by time point.

PERMANOVA of Time using weighted Unifrac distances

## 
## Call:
## adonis(formula = air.WUnifrac ~ Time, data = df.plot, strata = df.plot$dyadnb) 
## 
## Blocks:  strata 
## Permutation: free
## Number of permutations: 999
## 
## Terms added sequentially (first to last)
## 
##             Df SumsOfSqs   MeanSqs F.Model      R2 Pr(>F)    
## Time         2   0.01549 0.0077448  11.701 0.01325  0.001 ***
## Residuals 1743   1.15367 0.0006619         0.98675           
## Total     1745   1.16916                   1.00000           
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

PERMANOVA of mothers CST at week 36 using weighted Unifrac distances

## 
## Call:
## adonis(formula = air.WUnifrac ~ CST_w36, data = df.plot, strata = df.plot$dyadnb) 
## 
## Blocks:  strata 
## Permutation: free
## Number of permutations: 999
## 
## Terms added sequentially (first to last)
## 
##             Df SumsOfSqs    MeanSqs F.Model      R2 Pr(>F)
## CST_w36      5   0.00465 0.00093031  1.3901 0.00398      1
## Residuals 1740   1.16451 0.00066926         0.99602       
## Total     1745   1.16916                    1.00000

## 
## Call:
## adonis(formula = air.WUnifrac ~ Time * CST_w36, data = df.plot,      strata = df.plot$dyadnb) 
## 
## Blocks:  strata 
## Permutation: free
## Number of permutations: 999
## 
## Terms added sequentially (first to last)
## 
##                Df SumsOfSqs   MeanSqs F.Model      R2 Pr(>F)    
## Time            2   0.01549 0.0077448 11.6933 0.01325  0.001 ***
## CST_w36         5   0.00454 0.0009089  1.3722 0.00389  0.926    
## Time:CST_w36   10   0.00463 0.0004630  0.6990 0.00396  0.862    
## Residuals    1728   1.14450 0.0006623         0.97890           
## Total        1745   1.16916                   1.00000           
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

PERMANOVA of Delivery using weighted Unifrac distances

## 
## Call:
## adonis(formula = air.WUnifrac ~ DELIVERY, data = df.plot, strata = df.plot$dyadnb) 
## 
## Blocks:  strata 
## Permutation: free
## Number of permutations: 999
## 
## Terms added sequentially (first to last)
## 
##             Df SumsOfSqs    MeanSqs F.Model      R2 Pr(>F)
## DELIVERY     2   0.00287 0.00143643  2.1467 0.00246      1
## Residuals 1743   1.16629 0.00066913         0.99754       
## Total     1745   1.16916                    1.00000

## 
## Call:
## adonis(formula = air.WUnifrac ~ Time * DELIVERY, data = df.plot,      strata = df.plot$dyadnb) 
## 
## Blocks:  strata 
## Permutation: free
## Number of permutations: 999
## 
## Terms added sequentially (first to last)
## 
##                 Df SumsOfSqs   MeanSqs F.Model      R2 Pr(>F)    
## Time             2   0.01549 0.0077448 11.7102 0.01325  0.001 ***
## DELIVERY         2   0.00278 0.0013891  2.1004 0.00238  0.960    
## Time:DELIVERY    4   0.00210 0.0005242  0.7926 0.00179  0.444    
## Residuals     1737   1.14879 0.0006614         0.98258           
## Total         1745   1.16916                   1.00000           
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

2.2.5 - Create figure 2 illustrating airway microbiomes

Figure 2: Airway microbiome. (A) Boxplot of top genera with mean abundance of 5% at least one time point. Abundance is plotted on a log10 scale, and all abundances below 0.1% have been set to 0.1% in the plot. (B–C) Boxplot of alpha diversity, (B) observed richness, and (C) Shannon diversity index, by delivery mode. Three samples with observed richness above 100 were excluded from the plot. (D–E) Non-metric multidimensional scaling plots based on weighted UniFrac distances. Samples from the same individual are connected by gray lines. All plots are colored by time point.

## png 
##   2

2.3 - Fecal microbiome

2.3.1 - Subset fecal samples

fec_taxglm.RData contains phyloseq objects with fecal samples at phylum, genus and ASV level for both read counts and relative abundances, as well as a rarefied (2000 reads/sample) at ASV level.

2.3.2 - Dominant fecal taxa and overall richness

2.3.2.1 - tables

The distribution of the fecal reads are here summarized on phylum, genus and individual ASV level.

Count of phyla, genera, and ASV in fecal samples
Included	Phylum	Genus	ASV
All	33	707	6818
> 0.01%	8	105	306
> 0.1%	5	44	87
> 1%	5	14	22

Average abundance according to phylum
Kingdom	Phylum	Abundance (%)
Bacteria	Bacteroidetes	34.4
Bacteria	Proteobacteria	26.4
Bacteria	Firmicutes	21.4
Bacteria	Actinobacteria	16.2
Bacteria	Verrucomicrobia	1.4
Bacteria	Fusobacteria	0.1

Average abundance according to genus
Kingdom	Phylum	Class	Order	Family	Genus	Abundance (%)
Bacteria	Bacteroidetes	Bacteroidia	Bacteroidales	Bacteroidaceae	Bacteroides	29.2
Bacteria	Actinobacteria	Actinobacteria	Bifidobacteriales	Bifidobacteriaceae	Bifidobacterium	15.6
Bacteria	Proteobacteria	Gammaproteobacteria	Enterobacteriales	Enterobacteriaceae	Escherichia_Shigella	14.1
Bacteria	Proteobacteria	Gammaproteobacteria	Enterobacteriales	Enterobacteriaceae	Family_Enterobacteriaceae	9.2
Bacteria	Firmicutes	Negativicutes	Selenomonadales	Veillonellaceae	Veillonella	3.3
Bacteria	Firmicutes	Clostridia	Clostridiales	Clostridiaceae_1	Clostridium_ss_1	3.0

Average abundance according to ASV
Kingdom	Phylum	Class	Order	Family	Genus	Species	ASV	Abundance (%)
Bacteria	Proteobacteria	Gammaproteobacteria	Enterobacteriales	Enterobacteriaceae	Escherichia_Shigella	Genus_Escherichia_Shigella	Genus_Escherichia_Shigella_101	13.2
Bacteria	Actinobacteria	Actinobacteria	Bifidobacteriales	Bifidobacteriaceae	Bifidobacterium	Genus_Bifidobacterium	Genus_Bifidobacterium_60	10.0
Bacteria	Bacteroidetes	Bacteroidia	Bacteroidales	Bacteroidaceae	Bacteroides	Bacteroides_fragilis	Bacteroides_fragilis_22	6.6
Bacteria	Bacteroidetes	Bacteroidia	Bacteroidales	Bacteroidaceae	Bacteroides	Genus_Bacteroides	Genus_Bacteroides_293	6.3
Bacteria	Bacteroidetes	Bacteroidia	Bacteroidales	Bacteroidaceae	Bacteroides	Genus_Bacteroides	Genus_Bacteroides_260	5.1
Bacteria	Proteobacteria	Gammaproteobacteria	Enterobacteriales	Enterobacteriaceae	Family_Enterobacteriaceae	Family_Enterobacteriaceae	Family_Enterobacteriaceae_63	4.6

2.3.2.2 - Plot

Figure 3A: Fecal sample composition. Boxplot of top genera with mean abundance of 4% at least one time point. Abundance is plotted on a log10 scale, and all abundances below 0.1% have been set to 0.1% in the plot.

2.3.3 - Fecal alpha diversity

For this part we use the rarefied samples (2000 reads/sample)

Summary of alpha diversity by time
		Observed Richness		Shannon Diversity index
Time	Samples (n)	Mean	SD	Mean	SD
One_week	533	23.206	14.263	1.515	0.614
One_month	575	22.101	9.367	1.400	0.541
One_year	580	53.150	18.538	2.327	0.597

Summary of alpha diversity by time and delivery
		Observed Richness		Shannon Diversity index
Delivery mode	Samples (n)	Mean	SD	Mean	SD
One_week
In labor CS	56	23.482	11.557	1.473	0.658
Scheduled CS	51	25.725	32.563	1.563	0.773
Vaginal	426	22.869	10.570	1.515	0.588
One_month
In labor CS	64	21.672	8.142	1.301	0.470
Scheduled CS	50	21.540	9.008	1.399	0.596
Vaginal	461	22.221	9.576	1.414	0.543
One_year
In labor CS	60	49.883	18.762	2.271	0.666
Scheduled CS	54	53.130	18.763	2.329	0.611
Vaginal	466	53.573	18.482	2.335	0.587

Outlier not plotted in Figure 3B (Observed richness > 150)
Child	Time point	Delivery	Mother’s CST (week 36)	Observed richness
dyad734	One_week	Scheduled CS	CST_II	246

Figure 3 B-C: Boxplot of alpha diversity, (B) observed richness, and (C) Shannon diversity index, by delivery mode. One sample with observed richness of >150 was excluded from the plot.

Anova statistical test of alpha diversity by Time and Delivery
Overall differences in observed richness

## [1] "Statistical test of alpha diversity by Time and Delivery method"

## Analysis of Variance Table
## 
## Response: Observed
##             Df Sum Sq Mean Sq  F value Pr(>F)    
## Time         2 354897  177448 835.9279 <2e-16 ***
## DELIVERY     2    313     156   0.7369 0.4788    
## Residuals 1683 357263     212                    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Multiple comparison of differences in observed richness

##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = Observed ~ Time + DELIVERY, data = df.adiv)
## 
## $Time
##                         diff       lwr        upr     p adj
## One_month-One_week -1.105509 -3.160507  0.9494882 0.4170142
## One_year-One_week  29.943621 27.892889 31.9943532 0.0000000
## One_year-One_month 31.049130 29.037806 33.0604545 0.0000000
## 
## $DELIVERY
##                               diff       lwr      upr     p adj
## Scheduled CS-In labor CS  1.796473 -1.948591 5.541538 0.4985965
## Vaginal-In labor CS       1.235954 -1.475642 3.947549 0.5333632
## Vaginal-Scheduled CS     -0.560520 -3.458697 2.337657 0.8927733

Overall differences in shannon diversity index

## Analysis of Variance Table
## 
## Response: Shannon
##             Df Sum Sq Mean Sq  F value Pr(>F)    
## Time         2 293.27 146.636 429.8028 <2e-16 ***
## DELIVERY     2   0.92   0.462   1.3549 0.2583    
## Residuals 1683 574.19   0.341                    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Multiple comparison of differences in shannon diversity index

##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = Shannon ~ Time + DELIVERY, data = df.adiv)
## 
## $Time
##                          diff        lwr         upr     p adj
## One_month-One_week -0.1149787 -0.1973632 -0.03259411 0.0031055
## One_year-One_week   0.8125265  0.7303130  0.89474009 0.0000000
## One_year-One_month  0.9275052  0.8468715  1.00813890 0.0000000
## 
## $DELIVERY
##                                  diff         lwr       upr     p adj
## Scheduled CS-In labor CS  0.083511039 -0.06662806 0.2336501 0.3926698
## Vaginal-In labor CS       0.074407660 -0.03429982 0.1831151 0.2434904
## Vaginal-Scheduled CS     -0.009103379 -0.12529088 0.1070841 0.9815499

Alpha diversity does not differ dependent on mothers vaginal CST at week 36

## Analysis of Variance Table
## 
## Response: Observed
##             Df Sum Sq Mean Sq  F value Pr(>F)    
## Time         2 354897  177448 836.2606 <2e-16 ***
## CST_w36      5   1092     218   1.0288 0.3989    
## Residuals 1680 356484     212                    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

## Analysis of Variance Table
## 
## Response: Shannon
##             Df Sum Sq Mean Sq  F value Pr(>F)    
## Time         2 293.27 146.636 429.0059 <2e-16 ***
## CST_w36      5   0.88   0.177   0.5169 0.7637    
## Residuals 1680 574.23   0.342                    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

2.3.4 - Fecal beta diversity

2.3.4.1 - Preparation

Calculation of Weighted UniFrac distances and NMDS ordination for fecal samples

fec_OrdinationRes.RData contains weighted UniFrac distances and NMDS ordination of the fecal samples

2.3.4.2 - Plots and statistics

Figure 3D-E: Non-metric multi-dimensional scaling plot based on weighted UniFrac distances. Samples from the same individual are connected by gray lines.

PERMANOVA of Time using weighted Unifrac distances

## 
## Call:
## adonis(formula = fec.WUnifrac ~ Time, data = df.plot, strata = df.plot$dyadnb) 
## 
## Blocks:  strata 
## Permutation: free
## Number of permutations: 999
## 
## Terms added sequentially (first to last)
## 
##             Df SumsOfSqs   MeanSqs F.Model      R2 Pr(>F)    
## Time         2   0.05639 0.0281953  30.617 0.03507  0.001 ***
## Residuals 1685   1.55172 0.0009209         0.96493           
## Total     1687   1.60811                   1.00000           
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

PERMANOVA of mothers CST at week 36 using weighted Unifrac distances

## 
## Call:
## adonis(formula = fec.WUnifrac ~ CST_w36, data = df.plot, strata = df.plot$dyadnb) 
## 
## Blocks:  strata 
## Permutation: free
## Number of permutations: 999
## 
## Terms added sequentially (first to last)
## 
##             Df SumsOfSqs    MeanSqs F.Model      R2 Pr(>F)
## CST_w36      5   0.01092 0.00218339  2.2993 0.00679      1
## Residuals 1682   1.59720 0.00094958         0.99321       
## Total     1687   1.60811                    1.00000

## 
## Call:
## adonis(formula = fec.WUnifrac ~ Time * CST_w36, data = df.plot,      strata = df.plot$dyadnb) 
## 
## Blocks:  strata 
## Permutation: free
## Number of permutations: 999
## 
## Terms added sequentially (first to last)
## 
##                Df SumsOfSqs   MeanSqs F.Model      R2 Pr(>F)    
## Time            2   0.05639 0.0281953 30.7926 0.03507  0.001 ***
## CST_w36         5   0.01162 0.0023244  2.5386 0.00723  0.001 ***
## Time:CST_w36   10   0.01096 0.0010964  1.1974 0.00682  0.546    
## Residuals    1670   1.52914 0.0009157         0.95089           
## Total        1687   1.60811                   1.00000           
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

PERMANOVA of Delivery using weighted Unifrac distances

## 
## Call:
## adonis(formula = fec.WUnifrac ~ DELIVERY, data = df.plot, strata = df.plot$dyadnb) 
## 
## Blocks:  strata 
## Permutation: free
## Number of permutations: 999
## 
## Terms added sequentially (first to last)
## 
##             Df SumsOfSqs   MeanSqs F.Model      R2 Pr(>F)
## DELIVERY     2   0.00703 0.0035144  3.6986 0.00437      1
## Residuals 1685   1.60108 0.0009502         0.99563       
## Total     1687   1.60811                   1.00000

## 
## Call:
## adonis(formula = fec.WUnifrac ~ Time * DELIVERY, data = df.plot,      strata = df.plot$dyadnb) 
## 
## Blocks:  strata 
## Permutation: free
## Number of permutations: 999
## 
## Terms added sequentially (first to last)
## 
##                 Df SumsOfSqs   MeanSqs F.Model      R2 Pr(>F)    
## Time             2   0.05639 0.0281953 30.9488 0.03507  0.001 ***
## DELIVERY         2   0.00698 0.0034906  3.8315 0.00434  0.001 ***
## Time:DELIVERY    4   0.01512 0.0037808  4.1500 0.00940  0.001 ***
## Residuals     1679   1.52962 0.0009110         0.95119           
## Total         1687   1.60811                   1.00000           
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

2.3.5 - Create figure 3 illustrating fecal microbiomes

Figure 3: Fecal microbiome. (A) Boxplot of top genera with mean abundance of 4% at least one time point. Abundance is plotted on a log10 scale, and all abundances below 0.1% have been set to 0.1% in the plot. (B–C) Boxplot of alpha diversity, (B) observed richness, and (C) Shannon diversity index, by delivery mode. One sample with observed richness of >150 was excluded from the plot. (D–E) Non-metric multi-dimensional scaling plot based on weighted UniFrac distances. Samples from the same individual are connected by gray lines. All plots are colored by time point.

## png 
##   2

3 - Transfer

3.1 - Preparation

3.1.1 - Calculation of ALL individual ASV models

This is the foundation of all further analysis of transfer from mother to infant Output of this section in ‘./ORresults.RData’

ORresults.RData contains all calculated odds ratios for transfer across delivery mode, infant sample type and time point

3.1.2 - Permutational inference calculation

A permutation test between c-sectio and vaginal birth are conducted for all combinations.

3.1.2.1 - Calculations

weighted_permutation_results_onesided.RData contains the permutations results for the transfer odds

3.1.2.2 - Format output

STATtot.RData contains the formated transfer results as well as supporting tables and lists

3.1.2.3 - Overview of testable ASVs

Table 1 - testable ASV’s

Table1: Individual transfer models, coverage of testable ASVs and strongest results
			Relative abundance^*		Minimum p-value^†		ASVs with p-value below cutoff^†
Time	Type	ASVs(n)	Mother	Child	crude	adjusted	crude < 0.01	crude < 0.05	adjusted < 0.05	adjusted < 0.1
Cesarean sectio
7	Airways	104	30.994	36.451	0.058	0.990	0	0	0	0
7	Fecal	160	31.606	73.259	0.000	0.008	3	5	1	1
30	Airways	131	56.383	84.976	0.008	0.347	3	6	0	0
30	Fecal	181	60.471	83.228	0.008	0.991	1	4	0	0
90	Airways	152	56.791	84.419	0.033	0.992	0	3	0	0
300	Fecal	161	61.669	59.292	0.018	0.991	0	2	0	0
Vaginal delivery
7	Airways	293	63.970	45.965	0.002	0.691	3	13	0	0
7	Fecal	354	65.154	90.692	0.000	0.012	12	28	2	4
30	Airways	342	63.859	90.155	0.000	0.001	8	14	1	2
30	Fecal	395	65.809	92.392	0.002	0.312	11	28	0	0
90	Airways	364	62.224	87.668	0.001	0.260	3	9	0	0
300	Fecal	404	64.182	84.451	0.003	0.457	7	17	0	0
^* Mean relative abundance of the testable ASVs in mother or child
^† Crude p-values are the direct output of each transfer model, adjusted p-values have been FDR adjusted

Descriptives on testable Amplicon sequence variant (ASV) in terms of numbers of ASVs, vaginal, fecal, and airway total coverage, number of tests reaching nominal, and false discovery rate-corrected significance.
			Relative abundance^*		Minimum p-value^†		ASVs with p-value below cutoff^†
Time	Type	ASVs(n)	Mother	Child	crude	adjusted	crude < 0.01	crude < 0.05	adjusted < 0.05	adjusted < 0.1
In labor cesarean sectio
7	Airways	65	20.616	16.849	0.171	0.980	0	0	0	0
7	Fecal	105	21.214	63.576	0.001	0.068	1	2	0	1
30	Airways	81	50.822	59.373	0.005	0.374	1	4	0	0
30	Fecal	121	55.910	75.822	0.016	0.984	0	3	0	0
90	Airways	105	50.661	85.466	0.052	0.985	0	0	0	0
300	Fecal	100	58.004	50.603	0.017	0.983	0	4	0	0
Scheduled cesarean sectio
7	Airways	58	30.109	36.183	0.038	0.981	0	1	0	0
7	Fecal	89	28.119	58.184	0.020	0.873	0	3	0	0
30	Airways	75	23.747	81.034	0.016	0.984	0	2	0	0
30	Fecal	107	30.836	46.935	0.037	0.980	0	1	0	0
90	Airways	87	28.459	76.014	0.033	0.983	0	1	0	0
300	Fecal	91	35.645	33.860	0.054	0.981	0	0	0	0
^* Mean relative abundance of the testable ASVs in mother or child
^† Crude p-values are the direct output of each transfer model, adjusted p-values have been FDR adjusted

3.1.2.4 - ASVs with significant transfer odds

Transfer models that were significant after FDR correction
			Counts^*				Taxonomy
Time	Type	Delivery	0/0	1/0	0/1	1/1	Phylum	Class	Order	Family	Genus	Species	ASV
7	Fecal	CS	102	2	0	3	Proteobacteria	Gammaproteobacteria	Enterobacteriales	Enterobacteriaceae	Escherichia_Shigella	Genus_Escherichia_Shigella	Genus_Escherichia_Shigella_145
7	Fecal	Vaginal	423	1	0	2	Proteobacteria	Gammaproteobacteria	Cardiobacteriales	Wohlfahrtiimonadaceae	Koukoulia	Genus_Koukoulia	Genus_Koukoulia_3
7	Fecal	Vaginal	265	144	3	14	Bacteroidetes	Bacteroidia	Bacteroidales	Prevotellaceae	Prevotella	Genus_Prevotella	Genus_Prevotella_20
30	Airways	Vaginal	284	149	14	33	Tenericutes	Mollicutes	Mycoplasmatales	Mycoplasmataceae	Ureaplasma	Genus_Ureaplasma	Genus_Ureaplasma_8
^* Count of pairs in which the ASV is not found (0/0), found only in the mother (1/0), only in the child (0/1), or in both mother and child (1/1)

All transfer models for above mentioned ASVs
			Counts^*				P-values^†
Time	Type	Delivery	0/0	1/0	0/1	1/1	crude	adjusted
Genus_Escherichia_Shigella_145
7	Airways	CS	96	5	1	0	0.95098	0.99020
7	Fecal	CS	102	2	0	3	0.00005	0.00806
30	Airways	CS	121	4	0	1	0.03968	0.86640
30	Fecal	CS	104	3	5	2	0.02977	0.99123
90	Airways	CS	120	4	1	0	0.96800	0.99200
300	Fecal	CS	107	3	3	1	0.13483	0.99123
7	Airways	In labor CS	47	2	1	0	0.96000	0.98000
7	Fecal	In labor CS	54	0	0	2	0.00065	0.06818
30	Airways	In labor CS	62	1	0	1	0.03125	0.84375
30	Fecal	In labor CS	61	1	1	1	0.06200	0.98437
300	Fecal	In labor CS	57	1	1	1	0.06610	0.98333
7	Fecal	Scheduled CS	48	2	0	1	0.05882	0.98039
30	Fecal	Scheduled CS	43	2	4	1	0.27602	0.98000
90	Airways	Scheduled CS	56	3	1	0	0.95000	0.98333
300	Fecal	Scheduled CS	50	2	2	0	0.92662	0.98148
7	Airways	Vaginal	409	14	0	1	0.03538	0.79735
7	Fecal	Vaginal	397	18	10	1	0.39831	0.99765
30	Fecal	Vaginal	427	18	14	2	0.14909	0.99783
300	Fecal	Vaginal	443	21	2	0	0.91181	0.99785
Genus_Koukoulia_3
7	Fecal	CS	105	1	1	0	0.99065	0.99065
30	Airways	CS	123	1	2	0	0.98413	0.99206
30	Airways	Scheduled CS	60	1	1	0	0.98387	0.98387
7	Fecal	Vaginal	423	1	0	2	0.00003	0.01173
30	Airways	Vaginal	473	3	4	0	0.97516	0.99792
Genus_Prevotella_20
7	Fecal	CS	58	47	1	1	0.69829	0.99065
30	Fecal	CS	62	46	3	3	0.51872	0.99123
90	Airways	CS	68	54	2	1	0.59029	0.99200
300	Fecal	CS	58	50	4	2	0.42658	0.99123
7	Fecal	In labor CS	31	23	1	1	0.67792	0.98214
30	Fecal	In labor CS	36	26	1	1	0.66964	0.98437
90	Airways	In labor CS	36	27	1	1	0.67981	0.98462
300	Fecal	In labor CS	31	25	3	1	0.41416	0.98333
30	Fecal	Scheduled CS	26	20	2	2	0.59815	0.98000
90	Airways	Scheduled CS	32	27	1	0	0.55000	0.98333
300	Fecal	Scheduled CS	27	25	1	1	0.73585	0.98148
7	Airways	Vaginal	268	155	1	0	0.63443	0.99764
7	Fecal	Vaginal	265	144	3	14	0.00013	0.02353
30	Airways	Vaginal	300	175	2	3	0.26749	0.99792
30	Fecal	Vaginal	268	151	27	15	0.55546	0.99783
90	Airways	Vaginal	313	172	2	2	0.44748	0.99796
300	Fecal	Vaginal	282	163	13	8	0.53032	0.99785
Genus_Ureaplasma_8
7	Airways	CS	65	35	0	2	0.12930	0.99020
30	Airways	CS	78	44	0	4	0.01944	0.63667
90	Airways	CS	79	42	1	3	0.13251	0.99200
7	Airways	In labor CS	28	20	0	2	0.18857	0.98000
30	Airways	In labor CS	34	27	0	3	0.09745	0.98437
90	Airways	In labor CS	34	28	1	2	0.44151	0.98462
30	Airways	Scheduled CS	44	17	0	1	0.29032	0.98387
90	Airways	Scheduled CS	45	14	0	1	0.25000	0.98333
7	Airways	Vaginal	269	154	1	0	0.63679	0.99764
30	Airways	Vaginal	284	149	14	33	0.00000	0.00081
30	Fecal	Vaginal	290	169	0	2	0.13708	0.99783
90	Airways	Vaginal	296	161	11	21	0.00071	0.25976
Note:
Transfer models which were significant after FDR are highlighted in bold
^* Count of pairs in which the ASV is not found (0/0), found only in the mother (1/0), only in the child (0/1), or in both mother and child (1/1)
^† Crude p-values are the direct output of each transfer model, adjusted p-values have been FDR adjusted

3.1.3 - Plot ASV transfer odds

The odds for transfer between mother (week 36) and child. Top panel shows the OR (x-axis) and the strength (p-value). Lower panel shows OR (y-axis) versus the population wide vaginal abundance (x-axis). This shows, that 1) there is trend of transfer from more ASVs being positive (OR>1) than negative, more signal in fecal, and that those which obtain the strongest transfer results are those which are in low population-wide vaginal abundance.

3.1.3.1 - Figure 4-figure supplement 1 - vaginal delivery

Figure 4-figure supplement 1: The odds for transfer between mother (week 36) and child for children delivered vaginally. Top panel shows the odds ratio (OR) (x-axis) and the strength (p-value). Lower panel shows OR (y-axis) versus the population-wide vaginal abundance (x-axis).

3.1.3.2 - Figure 4-figure supplement 2 - sectio delivery

Figure 4-figure supplement 2: The odds for transfer between mother (week 36) and child for children delivered by cesarean section (CS). Top panel shows the OR (x-axis) and the strength (p-value). Lower panel shows OR (y-axis) versus the population-wide vaginal abundance (x-axis).

3.1.3.3 - Figure 4-figure supplement 3 - In labor sectio delivery

Figure 4-figure supplement 3: The odds for transfer between mother (week 36) and child for children delivered by in labor CS. Top panel shows the OR (x-axis) and the strength (p-value). Lower panel shows OR (y-axis) versus the population-wide vaginal abundance (x-axis).

3.1.3.4 - Figure 4-figure supplement 4 - Scheduled sectio delivery

Figure 4-figure supplement 4: The odds for transfer between mother (week 36) and child for children delivered by scheduled CS. Top panel shows the OR (x-axis) and the strength (p-value). Lower panel shows OR (y-axis) versus the population-wide vaginal abundance (x-axis).

3.1.3.5 - Figure 4-figure supplement statistics

Inference for relation between odds for tranfers and population maternal abundance^*
Delivery	Time (days)	log10(abundance)^†	SE^‡	p-value
Airways
CS	7	0.2101	0.1135	0.0669
CS	30	0.0193	0.0950	0.8391
CS	90	-0.1157	0.0815	0.1580
In labor CS	7	0.4703	0.1387	0.0012
In labor CS	30	-0.2729	0.1453	0.0640
In labor CS	90	-0.1132	0.1123	0.3157
Scheduled CS	7	-0.2807	0.1431	0.0549
Scheduled CS	30	0.1851	0.1256	0.1448
Scheduled CS	90	0.1479	0.1310	0.2620
Vaginal	7	-0.0114	0.0559	0.8385
Vaginal	30	0.0686	0.0481	0.1543
Vaginal	90	-0.0279	0.0553	0.6142
Fecal
CS	7	0.0120	0.0813	0.8832
CS	30	-0.0535	0.0722	0.4595
CS	300	-0.2048	0.0834	0.0151
In labor CS	7	0.1879	0.1319	0.1575
In labor CS	30	-0.1311	0.1018	0.2003
In labor CS	300	-0.1030	0.1296	0.4287
Scheduled CS	7	-0.1708	0.1080	0.1174
Scheduled CS	30	-0.0570	0.1189	0.6329
Scheduled CS	300	-0.0015	0.1258	0.9903
Vaginal	7	-0.1048	0.0525	0.0466
Vaginal	30	-0.1862	0.0466	0.0001
Vaginal	300	-0.1565	0.0513	0.0024
^* Linear models of maternal abundance (log10 transformed) and WTR, significant models are highlighted in bold
^† Log10 transformed relative maternal abundance
^‡ Standard error

3.2 - Weighted Odds Ratio

In order to make a commen measure for the tranfer signal, a weigthed transfer ratio (WTR) for each compartment and delivery mode. WTR were defined as WP/WN, where WP = sum(-log(OR) x log(p_value)) for ASV with OR>1 and WN = sum(-log(OR) x log(p_value)) for ASV with OR<1. WTR should be around 1 in case of no tranfer, and larger when present, but due to the high sparsity, the null distribution is not always centered around 1. To calculate the significance of any WTR, the dyads are scrampled to construct a null distribution for the ratio and then compared to the model ratio to calculate a p value.

3.2.1 - OVERALL ratio between positive and negative odds

3.2.1.1 - WTR Calculation

RatioStats_onesided.RData contains the formatted output of this section.

3.2.1.2 - WTR tables and figures

Weigthed Transfer Odds as function of delivery mode, compartment and age
		Models^*			Permutation stats^†
Delivery	Time (days)	≥1	<1	Weigthed ratio	p-value	SE	Null distribution	WTR^‡
Airways
CS	7	23	81	1.210	0.539	0.516	1.253	0.966
CS	30	32	99	2.084	0.084	0.479	1.217	1.712
CS	90	29	123	1.262	0.529	0.463	1.293	0.976
Vaginal	7	47	246	2.287	0.034	0.425	1.172	1.951
Vaginal	30	65	277	3.442	0.000	0.358	1.161	2.964
Vaginal	90	55	309	1.603	0.094	0.322	1.076	1.490
Fecal
CS	7	41	119	2.626	0.014	0.419	1.191	2.204
CS	30	37	144	0.927	0.778	0.408	1.206	0.768
CS	300	41	120	1.638	0.216	0.408	1.258	1.302
Vaginal	7	86	268	4.867	0.000	0.329	1.020	4.771
Vaginal	30	94	301	4.489	0.000	0.308	0.977	4.595
Vaginal	300	101	303	2.508	0.005	0.328	1.106	2.268
Note:
WTR with p-value < 0.05 are highlighted in bold
^* Count of models included with OR ≥1 or <1
^† Based on 1000 permutations of the model we calculated the p-value (sum(permutation ratio> weighted ratio)/1000), the standard error of log transformed permutation ratios, and the null distribution (mean permutation ratio)
^‡ Reported in the study and calculated as weighted ratio/null distribution

Figure 4: Weighted transfer ratios from vaginal week 36 to the fecal and airway compartments in first year of life stratified on mode of delivery (blue: vaginal birth, red: cesarean section). A ratio above one indicates enrichment of microbial transfer. Error bars reflect standard errors.

Inference for the difference in weigted ratios between sectio- and vaginal born children
		Permutational WTR_VAG/WTR_CS^*
Time (days)	model WTR_VAG/WTR_CS	median	mean	p-value
Airways
7	1.89	1.29	1.49	0.21
30	1.65	1.40	1.59	0.36
90	1.27	1.06	1.19	0.35
Fecal
7	1.85	1.52	1.63	0.31
30	4.84	1.42	1.62	0.01
300	1.53	1.15	1.30	0.27
Note:
Significantly different WTR_VAG and WTR_CS (p-value < 0.05) are highlighted in bold
^* Based on 1000 permutations of the model, showing median and mean value as well as the p-value (sum(permutation ratio> weighted ratio)/1000)

3.2.2 - WTR at order level

3.2.2.1 - Comparing vaginal to sectio delivery

3.2.2.1.1 - Calculations

OrderRatioSTATs.RData contains the WTR at order level for vaginal and CS deliveries

3.2.2.1.2 - Output

Number of ASVs for each taxonomic partitioning based on Order across all models
Order	min	max	total	median
Clostridiales	5	144	647	40.5
Lactobacillales	21	49	392	31.0
Bacteroidales	7	58	345	25.5
Selenomonadales	5	31	206	14.5
Betaproteobacteriales	6	24	154	11.5
Pseudomonadales	5	23	145	9.5
Corynebacteriales	2	22	140	11.0
Bifidobacteriales	5	12	103	8.0
Enterobacteriales	5	15	103	8.5
Bacillales	4	17	98	6.5

WTR and statistics for testable orders
			Models^*			Permutation stats^†
Time (days)	Type	Delivery	≥1	<1	Weigthed ratio	p-value	SE	Null distribution	WTR^‡
Bacillales
7	Airways	CS	2	5	2.498	0.151	3.351	0.645	3.872
7	Airways	Vaginal	1	16	3.096	0.258	3.761	0.398	7.770
7	Fecal	CS	1	5	0.099	0.422	4.232	0.099	1.000
7	Fecal	Vaginal	1	9	0.013	0.697	4.207	0.986	0.013
30	Airways	CS	2	4	5.414	0.059	2.701	4.540	1.193
30	Airways	Vaginal	1	13	0.892	0.559	2.902	1.238	0.721
30	Fecal	CS	1	5	0.525	0.470	4.204	0.525	1.000
30	Fecal	Vaginal	1	4	0.034	0.756	3.639	0.384	0.089
90	Airways	CS	2	5	1.474	0.377	2.836	1.474	1.000
90	Airways	Vaginal	1	11	3.866	0.213	3.191	0.633	6.106
300	Fecal	CS	1	3	0.699	0.291	4.797	0.215	3.247
300	Fecal	Vaginal	1	3	0.279	0.508	3.810	0.298	0.936
Bacteroidales
7	Airways	CS	1	6	4.305	0.159	5.387	0.001	5146.933
7	Airways	Vaginal	2	14	1.971	0.324	3.630	1.143	1.724
7	Fecal	CS	5	11	1.943	0.421	1.940	1.561	1.245
7	Fecal	Vaginal	11	37	3.141	0.048	0.904	0.978	3.212
30	Airways	CS	1	9	0.752	0.469	3.884	0.752	1.000
30	Airways	Vaginal	8	21	10.037	0.006	1.887	0.965	10.400
30	Fecal	CS	4	21	0.771	0.782	1.422	1.576	0.489
30	Fecal	Vaginal	16	31	8.112	0.000	0.886	0.779	10.415
90	Airways	CS	2	11	2.586	0.229	2.769	0.822	3.144
90	Airways	Vaginal	5	45	0.247	0.881	1.177	0.920	0.268
300	Fecal	CS	3	23	0.406	0.935	0.857	1.337	0.304
300	Fecal	Vaginal	17	41	2.445	0.056	0.661	0.965	2.534
Betaproteobacteriales
7	Airways	CS	1	7	0.014	0.902	2.925	0.971	0.014
7	Airways	Vaginal	3	18	0.456	0.623	2.583	1.004	0.454
7	Fecal	CS	1	7	0.178	0.439	4.577	0.178	1.000
7	Fecal	Vaginal	3	13	12.047	0.015	3.149	0.566	21.299
30	Airways	CS	1	6	0.003	0.813	3.645	0.564	0.005
30	Airways	Vaginal	3	18	0.710	0.543	2.623	0.860	0.825
30	Fecal	CS	0	6	0.000	0.644	4.694	0.278	0.002
30	Fecal	Vaginal	3	11	6.114	0.042	3.090	0.385	15.891
90	Airways	CS	1	9	0.005	0.873	3.126	0.721	0.007
90	Airways	Vaginal	4	20	0.916	0.415	2.126	0.623	1.470
300	Fecal	CS	0	6	0.000	0.620	4.773	0.406	0.001
300	Fecal	Vaginal	3	10	5.949	0.048	2.746	0.604	9.856
Bifidobacteriales
7	Airways	CS	3	2	5.738	0.145	3.188	1.087	5.280
7	Airways	Vaginal	2	7	6.283	0.142	3.301	0.595	10.553
7	Fecal	CS	2	4	0.524	0.647	2.441	0.887	0.591
7	Fecal	Vaginal	7	5	7.699	0.052	1.659	0.928	8.299
30	Airways	CS	1	6	0.462	0.550	4.337	0.842	0.549
30	Airways	Vaginal	4	7	5.236	0.081	2.856	0.854	6.128
30	Fecal	CS	4	4	0.782	0.575	1.632	0.994	0.787
30	Fecal	Vaginal	6	6	2.479	0.186	1.598	0.729	3.399
90	Airways	CS	2	4	2.379	0.245	3.448	0.835	2.847
90	Airways	Vaginal	3	5	3.439	0.170	3.225	0.707	4.862
300	Fecal	CS	3	5	0.927	0.550	1.858	1.056	0.878
300	Fecal	Vaginal	5	6	0.437	0.668	1.711	0.951	0.460
Clostridiales
7	Airways	CS	1	4	0.129	0.604	3.557	0.703	0.183
7	Airways	Vaginal	5	31	4.257	0.125	2.426	1.447	2.943
7	Fecal	CS	6	32	1.881	0.224	1.196	0.941	1.999
7	Fecal	Vaginal	14	79	1.304	0.325	0.744	0.979	1.332
30	Airways	CS	3	14	2.374	0.265	3.108	0.858	2.767
30	Airways	Vaginal	9	38	4.584	0.058	1.696	1.345	3.408
30	Fecal	CS	4	36	0.437	0.826	0.964	1.098	0.398
30	Fecal	Vaginal	14	95	0.600	0.831	0.592	1.099	0.546
90	Airways	CS	4	15	3.305	0.176	2.436	1.373	2.406
90	Airways	Vaginal	4	54	1.284	0.444	1.017	1.158	1.109
300	Fecal	CS	18	23	5.893	0.000	0.735	1.239	4.756
300	Fecal	Vaginal	41	103	3.690	0.013	0.559	1.192	3.097
Corynebacteriales
7	Airways	CS	2	7	3.371	0.243	3.384	0.900	3.744
7	Airways	Vaginal	4	17	4.323	0.086	2.521	0.739	5.851
7	Fecal	CS	2	6	0.725	0.538	3.450	0.833	0.870
7	Fecal	Vaginal	3	8	4.288	0.102	2.526	0.563	7.616
30	Airways	CS	2	9	0.741	0.543	3.527	1.467	0.505
30	Airways	Vaginal	3	19	0.857	0.451	1.975	0.709	1.210
30	Fecal	CS	3	3	4.250	0.110	3.239	0.492	8.645
30	Fecal	Vaginal	4	8	1.652	0.295	2.620	0.600	2.755
90	Airways	CS	1	11	0.112	0.764	3.766	1.480	0.076
90	Airways	Vaginal	2	19	1.800	0.365	2.753	0.997	1.806
300	Fecal	CS	0	2	0.002	0.263	5.803	0.002	1.000
300	Fecal	Vaginal	2	3	2.716	0.213	4.757	0.333	8.153
Enterobacteriales
7	Airways	CS	1	4	1.515	0.339	4.247	0.268	5.644
7	Airways	Vaginal	4	6	5.423	0.101	3.506	0.477	11.363
7	Fecal	CS	2	5	12.677	0.061	3.332	1.001	12.669
7	Fecal	Vaginal	6	9	20.863	0.002	2.318	0.615	33.947
30	Airways	CS	2	3	14.357	0.056	4.188	0.430	33.381
30	Airways	Vaginal	4	4	38.543	0.007	3.222	0.345	111.880
30	Fecal	CS	1	9	0.325	0.661	3.523	0.825	0.394
30	Fecal	Vaginal	7	4	37.443	0.002	2.557	0.616	60.780
90	Airways	CS	2	4	3.857	0.198	3.817	0.495	7.784
90	Airways	Vaginal	2	7	13.791	0.018	3.332	0.368	37.454
300	Fecal	CS	4	3	7.967	0.105	2.969	0.771	10.334
300	Fecal	Vaginal	5	5	14.351	0.020	2.474	0.874	16.422
Lactobacillales
7	Airways	CS	1	20	0.003	0.998	1.305	1.421	0.002
7	Airways	Vaginal	7	38	2.038	0.260	0.924	1.195	1.705
7	Fecal	CS	8	16	4.863	0.039	0.985	0.994	4.892
7	Fecal	Vaginal	18	24	14.754	0.000	0.730	1.059	13.933
30	Airways	CS	11	13	4.006	0.051	0.945	0.967	4.141
30	Airways	Vaginal	14	35	9.293	0.003	0.866	1.363	6.819
30	Fecal	CS	6	20	1.771	0.348	1.040	1.203	1.472
30	Fecal	Vaginal	18	26	18.944	0.000	0.826	1.086	17.448
90	Airways	CS	4	19	0.491	0.802	1.097	1.160	0.423
90	Airways	Vaginal	10	26	7.564	0.021	1.104	1.560	4.850
300	Fecal	CS	6	16	0.577	0.746	1.174	1.197	0.482
300	Fecal	Vaginal	6	30	1.642	0.407	0.959	1.329	1.236
Pseudomonadales
7	Airways	CS	2	5	3.702	0.241	3.966	1.335	2.772
7	Airways	Vaginal	4	19	1.432	0.213	2.055	0.518	2.763
7	Fecal	CS	1	5	0.404	0.558	4.124	0.608	0.664
7	Fecal	Vaginal	3	11	0.888	0.416	3.054	0.680	1.306
30	Airways	CS	1	7	1.692	0.354	4.376	1.692	1.000
30	Airways	Vaginal	4	18	2.366	0.095	1.755	0.537	4.408
30	Fecal	CS	1	5	0.261	0.511	4.286	0.573	0.456
30	Fecal	Vaginal	0	12	0.000	0.957	2.916	0.476	0.001
90	Airways	CS	0	9	0.000	0.862	3.119	1.282	0.000
90	Airways	Vaginal	4	19	0.115	0.860	1.627	0.584	0.197
300	Fecal	CS	0	5	0.000	0.897	4.408	0.292	0.002
300	Fecal	Vaginal	0	10	0.000	0.996	4.111	0.372	0.001
Selenomonadales
7	Airways	CS	2	3	2.247	0.478	4.141	1.954	1.150
7	Airways	Vaginal	4	11	5.295	0.059	2.387	0.747	7.087
7	Fecal	CS	7	5	6.460	0.027	1.769	1.046	6.177
7	Fecal	Vaginal	11	14	19.712	0.000	1.284	0.788	25.020
30	Airways	CS	1	5	0.250	0.409	4.468	0.250	1.000
30	Airways	Vaginal	3	18	0.801	0.502	1.697	0.807	0.992
30	Fecal	CS	5	9	1.002	0.460	1.861	0.912	1.099
30	Fecal	Vaginal	6	24	2.662	0.105	1.362	0.713	3.733
90	Airways	CS	1	9	0.599	0.682	3.127	1.095	0.547
90	Airways	Vaginal	4	20	0.406	0.661	1.355	0.642	0.633
300	Fecal	CS	2	11	0.342	0.772	1.828	0.859	0.398
300	Fecal	Vaginal	7	24	3.416	0.084	1.282	0.926	3.691
Note:
WTR with p-value < 0.05 are highlighted in bold
^* Count of models included with OR ≥1 or <1, and the model weighted ratio
^† Based on 1000 permutations of the model we calculated the p-value (sum(permutation ratio> weighted ratio)/1000), the standard error of log transformed permutation ratios, and the null distribution (mean permutation ratio)
^‡ Reported in the study and calculated as weighted ratio/null distribution. For plots this value is truncated so values lower than 0.625 are plotted as 0.625 and values higher than 16 are plotted as 16.

Figure 5: Weighted transfer ratios (WTRs) from vaginal week 36 to the fecal and airway compartments in the first year of life according to the mode of delivery (blue: vaginal birth, red: cesarean section) partitioned for the 10 most represented taxonomic classes at order level with upper left (Clostridiales) being the most represented order followed by Lactobacillales and so forth. Dashed lines represent analysis on less than 15 ASVs on average. Error bars reflect standard errors. WTR is truncated so values lower than 0.625 are plotted as 0.625 and values higher than 16 are plotted as 16.

3.2.2.2 - Comparing vaginal to scheduled and in labor sectio delivery

3.2.2.2.1 - Calculations

OrderRatioSTATs_split.RData contains the WTR at order level when sectio is split into scheduled and in labor sectio

3.2.2.2.2 - Output

Number of ASVs for each taxonomic partitioning based on Order across all models
Order	min	max	total	median
Bacteroidales	2	58	353	13.0
Betaproteobacteriales	3	24	173	6.5
Clostridiales	2	144	670	24.0
Enterobacteriales	2	15	112	5.0
Lactobacillales	11	49	431	16.5
Selenomonadales	3	31	219	9.0

WTR and statistics for testable orders
			Models^*			Permutation stats^†
Time (days)	Type	Delivery	≥1	<1	Weigthed ratio	p-value	SE	Null distribution	WTR^‡
Bacteroidales
7	Airways	In labor CS	1	3	9.357	0.030	5.588	0.001	8329.962
7	Airways	Scheduled CS	0	3	0.002	0.214	5.532	0.002	1.000
7	Airways	Vaginal	2	14	1.971	0.324	3.630	1.143	1.724
7	Fecal	In labor CS	4	10	1.208	0.545	1.888	1.343	0.899
7	Fecal	Scheduled CS	1	1	2.577	0.616	5.120	5.678	0.454
7	Fecal	Vaginal	11	37	3.141	0.048	0.904	0.978	3.212
30	Airways	In labor CS	1	7	0.626	0.458	3.955	0.626	1.000
30	Airways	Scheduled CS	0	5	0.002	0.257	5.661	0.002	1.000
30	Airways	Vaginal	8	21	10.037	0.006	1.887	0.965	10.400
30	Fecal	In labor CS	5	11	2.659	0.250	1.757	1.351	1.968
30	Fecal	Scheduled CS	1	9	0.011	0.852	3.260	1.468	0.008
30	Fecal	Vaginal	16	31	8.112	0.000	0.886	0.779	10.415
90	Airways	In labor CS	3	7	4.385	0.224	3.088	1.297	3.382
90	Airways	Scheduled CS	1	4	1.085	0.538	4.783	2.164	0.501
90	Airways	Vaginal	5	45	0.247	0.881	1.177	0.920	0.268
300	Fecal	In labor CS	3	9	0.301	0.923	1.140	1.179	0.255
300	Fecal	Scheduled CS	2	14	0.742	0.718	1.580	1.201	0.618
300	Fecal	Vaginal	17	41	2.445	0.056	0.661	0.965	2.534
Betaproteobacteriales
7	Airways	In labor CS	1	5	0.014	0.772	3.739	0.804	0.018
7	Airways	Scheduled CS	1	4	0.027	0.731	3.443	1.710	0.016
7	Airways	Vaginal	3	18	0.456	0.623	2.583	1.004	0.454
7	Fecal	In labor CS	0	7	0.001	0.629	4.791	0.484	0.001
7	Fecal	Scheduled CS	1	2	4.014	0.121	4.762	0.066	60.803
7	Fecal	Vaginal	3	13	12.047	0.015	3.149	0.566	21.299
30	Airways	In labor CS	1	5	0.282	0.462	3.699	0.282	1.000
30	Airways	Scheduled CS	0	5	0.001	0.735	4.262	2.470	0.000
30	Airways	Vaginal	3	18	0.710	0.543	2.623	0.860	0.825
30	Fecal	In labor CS	0	5	0.001	0.396	5.455	0.001	1.000
30	Fecal	Scheduled CS	0	3	0.001	0.514	5.211	1.046	0.001
30	Fecal	Vaginal	3	11	6.114	0.042	3.090	0.385	15.891
90	Airways	In labor CS	0	8	0.001	0.811	3.786	1.648	0.000
90	Airways	Scheduled CS	1	6	0.040	0.786	3.125	1.419	0.028
90	Airways	Vaginal	4	20	0.916	0.415	2.126	0.623	1.470
300	Fecal	In labor CS	0	5	0.001	0.326	5.597	0.001	1.000
300	Fecal	Scheduled CS	0	4	0.001	0.491	5.257	0.001	1.000
300	Fecal	Vaginal	3	10	5.949	0.048	2.746	0.604	9.856
Clostridiales
7	Airways	In labor CS	0	4	0.001	0.619	4.840	1.935	0.000
7	Airways	Scheduled CS	1	1	0.775	0.455	5.662	0.775	1.000
7	Airways	Vaginal	5	31	4.257	0.125	2.426	1.447	2.943
7	Fecal	In labor CS	4	14	0.691	0.646	2.051	1.111	0.622
7	Fecal	Scheduled CS	4	22	2.688	0.237	1.435	1.264	2.126
7	Fecal	Vaginal	14	79	1.304	0.325	0.744	0.979	1.332
30	Airways	In labor CS	2	4	3.628	0.232	3.969	0.822	4.411
30	Airways	Scheduled CS	1	10	0.437	0.341	5.110	0.437	1.000
30	Airways	Vaginal	9	38	4.584	0.058	1.696	1.345	3.408
30	Fecal	In labor CS	4	20	1.145	0.485	1.756	1.108	1.033
30	Fecal	Scheduled CS	2	24	0.448	0.822	1.676	1.370	0.327
30	Fecal	Vaginal	14	95	0.600	0.831	0.592	1.099	0.546
90	Airways	In labor CS	1	11	1.301	0.573	3.520	1.520	0.856
90	Airways	Scheduled CS	3	8	3.155	0.253	3.892	1.220	2.585
90	Airways	Vaginal	4	54	1.284	0.444	1.017	1.158	1.109
300	Fecal	In labor CS	12	12	8.456	0.009	1.129	1.172	7.217
300	Fecal	Scheduled CS	9	10	2.613	0.156	0.943	1.192	2.192
300	Fecal	Vaginal	41	103	3.690	0.013	0.559	1.192	3.097
Enterobacteriales
7	Airways	In labor CS	2	3	2.297	0.260	4.174	0.589	3.898
7	Airways	Scheduled CS	0	2	0.001	0.824	4.530	0.068	0.021
7	Airways	Vaginal	4	6	5.423	0.101	3.506	0.477	11.363
7	Fecal	In labor CS	3	4	19.758	0.035	2.669	1.542	12.811
7	Fecal	Scheduled CS	1	2	2.329	0.593	4.076	3.192	0.730
7	Fecal	Vaginal	6	9	20.863	0.002	2.318	0.615	33.947
30	Airways	In labor CS	3	1	15.075	0.066	3.925	0.678	22.243
30	Airways	Scheduled CS	0	2	0.002	0.748	4.945	0.157	0.012
30	Airways	Vaginal	4	4	38.543	0.007	3.222	0.345	111.880
30	Fecal	In labor CS	1	4	0.631	0.545	3.952	0.707	0.893
30	Fecal	Scheduled CS	1	3	0.150	0.831	3.651	1.008	0.149
30	Fecal	Vaginal	7	4	37.443	0.002	2.557	0.616	60.780
90	Airways	In labor CS	1	3	6.447	0.078	4.410	0.278	23.176
90	Airways	Scheduled CS	1	3	1.074	0.356	4.665	0.119	9.026
90	Airways	Vaginal	2	7	13.791	0.018	3.332	0.368	37.454
300	Fecal	In labor CS	4	2	11.455	0.070	3.063	0.703	16.301
300	Fecal	Scheduled CS	1	2	2.856	0.258	5.063	2.856	1.000
300	Fecal	Vaginal	5	5	14.351	0.020	2.474	0.874	16.422
Lactobacillales
7	Airways	In labor CS	1	12	0.177	0.915	1.634	1.029	0.172
7	Airways	Scheduled CS	1	10	0.008	0.987	1.459	1.174	0.007
7	Airways	Vaginal	7	38	2.038	0.260	0.924	1.195	1.705
7	Fecal	In labor CS	8	10	4.576	0.077	1.131	1.202	3.806
7	Fecal	Scheduled CS	5	10	2.432	0.214	1.368	0.946	2.571
7	Fecal	Vaginal	18	24	14.754	0.000	0.730	1.059	13.933
30	Airways	In labor CS	9	8	4.883	0.027	0.948	0.859	5.684
30	Airways	Scheduled CS	4	9	1.945	0.286	1.542	0.947	2.053
30	Airways	Vaginal	14	35	9.293	0.003	0.866	1.363	6.819
30	Fecal	In labor CS	8	12	2.597	0.182	1.177	1.023	2.540
30	Fecal	Scheduled CS	4	12	0.919	0.632	1.435	1.310	0.701
30	Fecal	Vaginal	18	26	18.944	0.000	0.826	1.086	17.448
90	Airways	In labor CS	5	11	0.466	0.786	0.917	0.959	0.486
90	Airways	Scheduled CS	3	9	1.749	0.386	1.682	1.252	1.396
90	Airways	Vaginal	10	26	7.564	0.021	1.104	1.560	4.850
300	Fecal	In labor CS	5	9	2.256	0.361	1.727	1.431	1.577
300	Fecal	Scheduled CS	4	10	1.536	0.395	1.499	1.261	1.218
300	Fecal	Vaginal	6	30	1.642	0.407	0.959	1.329	1.236
Selenomonadales
7	Airways	In labor CS	0	3	0.001	0.775	4.408	0.846	0.001
7	Airways	Scheduled CS	2	1	45.411	0.004	4.540	0.322	140.939
7	Airways	Vaginal	4	11	5.295	0.059	2.387	0.747	7.087
7	Fecal	In labor CS	5	1	110.383	0.001	3.184	1.297	85.119
7	Fecal	Scheduled CS	3	3	3.372	0.194	2.869	0.917	3.677
7	Fecal	Vaginal	11	14	19.712	0.000	1.284	0.788	25.020
30	Airways	In labor CS	1	2	1.046	0.220	5.156	0.002	418.577
30	Airways	Scheduled CS	1	3	0.207	0.361	4.290	0.207	1.000
30	Airways	Vaginal	3	18	0.801	0.502	1.697	0.807	0.992
30	Fecal	In labor CS	5	4	4.816	0.098	2.122	1.059	4.547
30	Fecal	Scheduled CS	2	8	0.919	0.581	2.373	1.238	0.743
30	Fecal	Vaginal	6	24	2.662	0.105	1.362	0.713	3.733
90	Airways	In labor CS	1	5	0.681	0.685	3.388	1.518	0.448
90	Airways	Scheduled CS	0	5	0.002	0.574	4.678	0.265	0.006
90	Airways	Vaginal	4	20	0.406	0.661	1.355	0.642	0.633
300	Fecal	In labor CS	3	6	1.142	0.472	2.718	1.080	1.058
300	Fecal	Scheduled CS	0	9	0.000	0.918	2.699	1.029	0.000
300	Fecal	Vaginal	7	24	3.416	0.084	1.282	0.926	3.691
Note:
WTR with p-value < 0.05 are highlighted in bold
^* Count of models included with OR ≥1 or <1, and the model weighted ratio
^† Based on 1000 permutations of the model we calculated the p-value (sum(permutation ratio> weighted ratio)/1000), the standard error of log transformed permutation ratios, and the null distribution (mean permutation ratio)
^‡ Reported in the study and calculated as weighted ratio/null distribution. For plots this value is truncated to be between 0.625 and 16

Figure 5-figure supplement 1: Weighted transfer ratios (WTRs) from vaginal week 36 to the fecal and airway compartments in the first year of life according to the mode of delivery (blue: vaginal birth, red: in labor CS, green: scheduled CS) partitioned for the 10 most represented taxonomic classes at order level with upper left (Clostridiales) being the most represented family followed by Lactobacillales and so forth. Dashed lines represent analysis on less than 15 ASVs on average. Error bars reflect standard errors. WTR is truncated so values lower than 0.625 are plotted as 0.625 and values higher than 16 are plotted as 16.

3.3 - Transfer of mothers dominant ASV

In this analysis, the vaginal dominating ASV in each mother is looked for in the corresponding child. This analysis is ASV unspecific I.e. just the dominating one we look for.

3.3.1 - Calculations

Winnerstats.RData contains the result for transfer of mothers dominant ASVs

3.3.2 - Output

Transfer of mosthers most dominating ASVs. The frequency of the ASV in the child is shown on the y-axis, color indicate delivery mode, x-axis the domination rank (1 = most dominating, 2 = second,…), label refers to p-values towards H0 of no transfer.

Plot data
			Samples^*
Time	Delivery	Rank	Child	Mother	shared (%)	p-value
Airways
7	Sectio	1	9	102	8.824	0.526
7	Sectio	2	9	102	8.824	0.132
7	Sectio	3	7	102	6.863	0.302
7	Sectio	4	4	102	3.922	0.841
7	Vaginal	1	56	424	13.208	0.003
7	Vaginal	2	24	424	5.660	0.867
30	Sectio	1	10	126	7.937	0.493
30	Sectio	2	9	126	7.143	0.336
30	Sectio	3	9	126	7.143	0.313
30	Sectio	4	5	126	3.968	0.839
30	Vaginal	1	57	480	11.875	0.003
30	Vaginal	2	42	480	8.750	0.012
90	Sectio	1	9	125	7.200	0.678
90	Sectio	2	6	125	4.800	0.800
90	Sectio	3	8	125	6.400	0.406
90	Sectio	4	7	125	5.600	0.337
90	Vaginal	1	52	489	10.634	0.075
90	Vaginal	2	35	489	7.157	0.160
Fecal
7	Sectio	1	17	107	15.888	0.174
7	Sectio	2	10	107	9.346	0.561
7	Sectio	3	12	107	11.215	0.202
7	Sectio	4	11	107	10.280	0.240
7	Sectio	5	13	107	12.150	0.126
7	Vaginal	1	81	426	19.014	0.000
7	Vaginal	2	62	426	14.554	0.015
30	Sectio	1	18	114	15.789	0.646
30	Sectio	2	17	114	14.912	0.323
30	Sectio	3	11	114	9.649	0.482
30	Sectio	4	14	114	12.281	0.291
30	Vaginal	1	85	461	18.438	0.604
30	Vaginal	2	79	461	17.137	0.006
300	Sectio	1	15	114	13.158	0.967
300	Sectio	2	14	114	12.281	0.171
300	Sectio	3	9	114	7.895	0.373
300	Sectio	4	7	114	6.140	0.734
300	Vaginal	1	91	466	19.528	0.327
300	Vaginal	2	52	466	11.159	0.828
^* Count of samples where that rank ASV is present and the percentage of pairs where it is shared

Ranking of ASVs. I.e. which ASVs are dominating at which rank and in how many mothers does it have that rank
ASV	Samples (n)
Rank 1
Genus_Lactobacillus_139	227
Genus_Lactobacillus_323	224
Lactobacillus_gasseri_37	76
Genus_Gardnerella_40	30
Genus_Gardnerella_20	22
Genus_Lactobacillus_268	22
Rank 2
Genus_Lactobacillus_139	93
Genus_Lactobacillus_268	82
Genus_Lactobacillus_323	70
Lactobacillus_gasseri_37	59
Genus_Gardnerella_40	47
Genus_Gardnerella_20	44
Genus_Megasphaera_22	17
Genus_Bifidobacterium_60	15
Lactobacillus_reuteri_33	15
Rank 3
Genus_Lactobacillus_139	86
Genus_Lactobacillus_323	73
Lactobacillus_gasseri_37	47
Genus_Gardnerella_20	41
Genus_Gardnerella_40	37
Genus_Lactobacillus_268	36
Lactobacillus_reuteri_33	35
Genus_Megasphaera_22	24
Genus_Atopobium_36	17
Rank 4
Genus_Lactobacillus_323	70
Lactobacillus_gasseri_37	60
Genus_Lactobacillus_139	48
Genus_Gardnerella_40	45
Genus_Lactobacillus_268	40
Genus_Gardnerella_20	36
Lactobacillus_reuteri_33	32
Genus_Ureaplasma_8	19
Genus_Megasphaera_22	15

3.4 - Phylogenetic tree with transfer odds

Results on the tree of life Here, we have the individual results shown on the phylogenetic tree

Phylogenetic tree with transfer odds

Modelling transfer of vaginal microbiota from mother to infant (in early life)