Gut microbiota development and dynamics in a Bangladeshi infant cohort during early life.

Code to perform analyses on the 16S rRNA data of the Bangladeshi infant gut microbiota project (Files to be uploaded soon!)

For questions please contact Maria Ioanna Papadaki (papadaki.mg@gmail.com)

This repository contains the analysis scripts for our study on infant gut microbiota development in a Bangladeshi infant population (BBGUT cohort) and how it compares to a Belgian infant cohort (BABEL cohort) during early life. The STORMS checklist for this study is also provided. Each script is organized to guide you through the downstream analysis and visualization of results. All main figures and supplementary data can be reproduced with the following scripts:

1_BBGUT_DEVELOPMENT

1_BBGUT_healthygutprofile_AUG25.R

Function: Exploration of the healthy gut microbiota development in Bangladeshi infants:

1. DMM
2. GMMs
3. Alpha diversity
4. Composition
5. Covid-19

Data generated:

• Figure 1a,1b,1c,1e
• Figure 4a,b
• Supplementary Figure 5a
• Supplementary Figure 6
• Supplementary Figure 12
• Supplementary Table 1
• Supplementary Table 9

2_BBGUT_alpha_div_timebinsAUG25.R

Function: Alpha diversity and Supplementary figures (BBGUT cohort)

Data generated:

• Supplementary Figure 5b
• Supplementary Figure 10

ASV_saturation_plotAUG25.R

Function: ASV saturation plot with increasing sample size (# infants)

Data generated:

• Supplementary Figure 1a,b

Alpha_gmm_lmm.R

Function: Alpha diversity across GMMs (observed, shannon) LMM model

Data generated:

• Supplementary Table 2

Alpha_continuous_model.R

Function: Alpha diversity over time (observed, shannon) LMM model

Data generated:

• Supplementary Table 2

covidmonthpairs_comparison_lmm.R

Function: Normalized 2-month bacterial abundance changes across periods (P-P, P-L, L-L)

Data generated:

• Supplementary Table 8

2_BBGUTVSBABEL

1_BBGUTvsBABEL_Y1_dmm_diversity_AUG25.R

Function: BBGUT – BABEL cohort comparison

1. DMM (for BABEL, for BBGUT use DMM results from full dataset)
2. Alpha diversity (comparison)
3. Beta diversity (comparison)

Data generated:

• Figure 2c
• Supplementary Table 3

1_BBGUTvsBABEL_compdifferences_AUG25.R

Function: BBGUT – BABEL comparison

1. Prevalence changes of common bacterial genera over time
2. Alpha diversity (comparison)

Data generated:

• Figure 2a
• Supplementary Table 4

2_BBGUTvsBABEL_order_of_appearance_Y1_AUG25.R

Function: BBGUT – BABEL comparison

1. Top15 most abundant genera per cohort during year 1
2. Order of Appearance of most abundant genera (y1)
3. Rank (order of appearance) correlations between the two cohorts (y1)
4. Bacterial prevalence correlations between the two cohorts
5. Differential abundances

Data generated:

• Figure 2b, d
• Supplementary Figure 7a, b
• Supplementary Figure 8a, b

3_BBGUT_EXTERNALFACTORS

1_BBGUT_PCoA_dbRDA_AUG25.R

Function: PCoA, dbRDA analysis in BBGUT cohort

1. genus level PCoA analysis for the 3 GMM stages
2. Distance-based Redundancy Analysis on for metadata covariates
3. PcoA infant and maternal samples

Data generated:

• Figure 1a
• Figure 3a
• Supplementary Table 5

2_BBGUT_genus_dbRDA_AUG25.R

Function: Finding covariates that explain the variation of the most abundant bacterial genera dbRDA analysis in BBGUT cohort

Data generated:

• Figure 3b
• Supplementary Table 6

3_BBGUT_Setbacks_AUG25.R

Function: Maturation setbacks in the BBGUT cohort

1. Setbacks in BBGUT cohorts (all changes)
2. Calculate maturation score
3. Setback association to disease events

Data generated:

• Figure 3c
• Figure 3d
• Figure 4c
• Supplementary Figure 9a, b
• Supplementary Table 7

4_SEGATELLA

1_BBGUT_Segatella_AUG25.R

Function: Exploring Segatella in the BBGUT cohort

1. Segatella prevalence across GMM stages and health groups
2. HSA threshold calculation
3. Monthly proportion of HSA in adhoc disease and HTP samples
4. HSA metadata
5. Heatmap for samples with HSA spikes per child over time

Data generated:

• Figure 5 a, b, c
• Supplementary Figure 4a, b
• Supplementary Figure 13a, b
• Supplementary Table 10

2_BBGUT_Segatella_Supplementaryfigure14.R

Function: Segatella ASV abundance across health groups

Data generated:

• Supplementary Figure 14

DATA

Folder containing the data for running all scripts of the main analysis

DATA_PREPROCESSING

Scripts used to create the final ASV table using the pre-processed raw data

1_BBGUT_rdp_annotation.R

Function: OTU Annotation with RDP taxonomy (rdp set 19)

2_BBGUT_decontamination.R

Function: Decontamination using decontam R package

3_BBGUT_final_phyloseq.R

Function: Create final phyloseq object