Additional file 1 of Interplay between the gut microbiome and typhoid fever: insights from endemic countries and a controlled human infection model

Additional file 1. Fig. S1: Age distribution of participants in the healthy control, acute typhoid, and presumptive carrier groups, broken down by study site. Statistical annotations are the p-values resulting from Wilcoxon rank sum tests. Fig. S2: Sex split of the different participant groups across the different sites. Fig. S3: Alpha diversity for acute typhoid fever patients and healthy household contacts for each endemic country study site. Fig. S4: Bar chart showing the prevalence of eight common phyla in acute typhoid patients and healthy household contacts, for each study site. Fig. S5: Prevalence of Prevotella copri clade A across age brackets in Malawi, Bangladesh, and Nepal. Fig. S6: Prevalence of Clostridium SGB6179 across age brackets in Malawi, Bangladesh, and Nepal. Fig. S7: Prevalence of GGB4266_SGB5809 across age brackets in Malawi, Bangladesh, and Nepal. Fig. S8: Prevalence of Haemophilus parainfluenzae across age brackets in Malawi, Bangladesh, and Nepal. Fig. S9: Alpha diversity of acute typhoid patients, high Vi-titre participants, and household contacts from Malawi and Nepal. Statistical annotations are the p-values resulting from Wilcoxon rank sum tests. A single asterisk indicates a p-value < 0.01, triple asterisk indicates a p-value < 0.0001. Fig. S10: Beta diversity of acute typhoid fever, high Vi-titre participants, and household contacts from Malawi and Nepal. Fig. S11: Prevalence of B. obeum, H. parainfluenzae, and R. gnavus across three participant groups (household contacts, typhoid cases, and high Vi-titre) in Malawi. Fig. S12: Heatmap of top 400 taxa from Nepalese participants – household contacts, acute typhoid cases and high-Vi titre participants. Fig. 13: The abundance of species only described as species genome bins in the metaphlan database from Malawian and Nepalese household contacts, acute typhoid, and high-Vi titre participants. Fig. S14: Comparison of A) the number of AMR gene and B) the number of AMR gene classes identified in participants from all three sites who did and did not report antibiotic usage prior to sampling. Fig. S15: Beta-diversity plot of 26 CHIM participants challenged with S. Typhi or S. Paratyphi, coloured by whether they were diagnosed with typhoid/paratyphoid fever following pathogen exposure. Fig. S16: Comparison of prevalence of A) succinate2priopionate and B) rnf MGCs between people who were susceptible (disease) and non-susceptible (no_disease) to challenge with S. Typhi