Additional file 1 of The gut microbiota is associated with the small intestinal paracellular permeability and the development of the immune system in healthy children during the first two years of life
Creators: name: Kaczmarczyk, Mariusz
name: Löber, Ulrike
name: Adamek, Karolina
name: Węgrzyn, Dagmara
name: Skonieczna-Żydecka, Karolina
name: Malinowski, Damian
name: Łoniewski, Igor
name: Markó, Lajos
name: Ulas, Thomas
name: Forslund, Sofia K.
name: Łoniewska, Beata
Publisher: name: figshare
Year: 2021
Subjects: subject: Medicine
subject: Microbiology
subject: FOS: Biological sciences
subject: FOS: Biological sciences
subject: Cell Biology
subject: Genetics
subject: Physiology
subject: Biotechnology
subject: 39999 Chemical Sciences not elsewhere classified
subject: FOS: Chemical sciences
subject: FOS: Chemical sciences
subject: Ecology
subject: Science Policy
subject: Immunology
subject: FOS: Clinical medicine
subject: FOS: Clinical medicine
subject: 69999 Biological Sciences not elsewhere classified
subject: Inorganic Chemistry

description: Additional file 1: Figure S1. Sample selection and availability (PMU cohort). From 100 healthy, full-term newborns during the period from March 2015 to April 2016, 18 mother + child pairs were initially selected with the highest number of samples available. Since only in two cases the delivery was natural and neither the mother nor the child was treated with antibiotics, it was decided to supplement this cohort with six pairs of mother + child who were not given antibiotics and the delivery was natural. Out of the 24 newborns that were selected in this way, three newborns (F19, F22, F24) were excluded due to inadequate number of samples. Twenty-one newborns (101 samples in total, green tiles) were included, in whom at least four longitudinal stool samples were available. Figure S2. Study flow chart, including zonulin and calprotectin (PMU cohort). The number of samples for downstream analyses might differ due to results out of determination limits (zonulin 800 ng/mL and calprotectin 2100 ug/mL), technical problems (small volume of collected stool specimen, inadequate amount of DNA, sequencing depth), participant attrition. Figure S3. Stool calprotectin level by time in the HMS cohort. Likelihood ratio test, df = 3, P = 2.56e−10, adjusted for mode of delivery Notched boxplot with variable widths proportional to the square-roots of the number of observations in the groups; FDR adjusted p-values 0.05, the same common slope coefficient β (coef.) across all time points and one p-value (P2–P3) were shown. Coefficients and Q values were averaged over 128 Monte Carlo instances of the Dirichlet distribution, followed by center-log transform of each instance. Figure S9. Taxon change versus calprotectin change (PMU cohort). Linear mixed effects models were used to test for an association between the taxon abundance change and calprotectin change accounting for ten time point pairs (P2-P3, P3-P4, etc.) from the same subject, adjusted for mode of delivery and breastfeeding time. Two models were considered: without interaction (w/o int.) and with interaction between time point pair and taxon change (w/ int.). If the interaction term was significant—Q (w/ int.) 0.05, the same common slope coefficient β (coef.) across all time points and one p-value (P2-P3) were shown. Coefficients and Q values were averaged over 128 Monte Carlo instances of the Dirichlet distribution, followed by center-log transform of each instance. Figure S10. Taxon change versus calprotectin change (HMS cohort). Linear mixed effects models were used to test for an association between the taxon abundance change and calprotectin change accounting for six time point pairs (P2–P3, P3–P4, etc.) from the same subject, adjusted for mode of delivery. Two models were considered: without interaction (w/o int.) and with interaction between time point pair and taxon change (w/ int.). If the interaction term was significant—Q (w/ int.) 0.05, the same common slope coefficient β (coef.) across all time points and one p-value (P2-P3) were shown. Coefficients and Q values were averaged over 128 Monte Carlo instances of the Dirichlet distribution, followed by center-log transform of each instance. Figure S11. Pathway change vs calprotectin change (HMS cohort). Linear mixed effects models were used to test for an association between the pathway abundance change and calprotectin change accounting for six time point pairs (P2–P3, P3–P4, etc.) from the same subject, adjusted for mode of delivery. Two models were considered: without interaction (w/o int.) and with interaction between time point pair and taxon change (w/ int.). If the interaction term was significant—Q (w/int.) 0.05, the same common slope coefficient β (coef.) across all time points and one p-value (P2-P3) were shown. Coefficients and Q values were averaged over 128 Monte Carlo instances of the Dirichlet distribution, followed by center-log transform of each instance. Figure S12. Relationship between (changes in) gut abundance of inferred MetaCyc pathways and (changes in) calprotectin levels (HMS cohort). A—common slope model illustrating relationships between CENTFERM-PWY change (centered log-ratio transformed) and calprotectin change (rank transformed), B—common slope model illustrating relationships between PWY-6590 change (centered log-ratio transformed) and calprotectin change (rank transformed); Likelihood ratio test (LRT) p- and Q-values were computed based on 128 Monte Carlo instances of the Dirichlet distribution, followed by center-log transform of each instance, the plots were based on the first Monte Carlo instance. Table S1. Repeated measures correlation of zonulin and calprotectin with microorganisms and predicted MetaCyc pathways (PMU cohort). Table S2. Repeated measures correlation of calprotectin with bacteria and MetaCyc pathway abundance in the PMU and HMS cohorts. Table S3. Pathway change vs Zonulin change (PMU cohort). Table S4. Pathway change vs Calprotectin change (PMU cohort).