Additional file 1 of Enterotypes of the human gut mycobiome
Creators: name: Lai, Senying
name: Yan, Yan
name: Pu, Yanni
name: Lin, Shuchun
name: Qiu, Jian-Ge
name: Jiang, Bing-Hua
name: Keller, Marisa Isabell
name: Wang, Mingyu
name: Bork, Peer
name: Chen, Wei-Hua
name: Zheng, Yan
name: Zhao, Xing-Ming
Publisher: name: figshare
Year: 2024
Subjects: subject: Microbiology
subject: FOS: Biological sciences
subject: Genetics
subject: Physiology
subject: Environmental Sciences not elsewhere classified
subject: Ecology
subject: Biological Sciences not elsewhere classified
subject: Cancer
subject: Computational Biology

description: Additional file 1: Figure S1. Composition and diversity of the human gut mycobiome across studies and geographic sites. a, The distribution of four highly abundant fungal taxa across three continents. b, The distribution of the number of total reads per sample across study populations. c, Cumulative curves of the number of detected genera according to the number of sequenced samples for different amplicon targets. d, The distribution of fungal Shannon diversity across study continents. e, Comparison of the Shannon diversity (left) and Bray-Curtis pairwise dissimilarities (right) of bacteriome (16S) and mycobiome (ITS) at genus level. f, The correlation between fungal Bray-Curtis distance (FBCD) and bacterial Bray-Curtis distance (BBCD), where the Bray-Curtis distance is calculated between two samples. The shaded gray region represents 95% confidence intervals of the linear regression. In boxplots, boxes span from the first to the third quantiles and black horizontal lines represent the median, with whiskers extending 1.5 times the interquartile range (IQR). p values of two-sided Mann-Whitney U-test are shown. Figure S2. Cumulative curves of the number of detected genera (fungal richness) according to the number of sequenced reads from different study populations. Figure S3. Principal Coordinate Analysis (PCoA) plot of fungal community composition based on Bray-Curtis dissimilarity index. Each point represents a sample and is colored by their dataset (a), continent (b) and Phenotype (c). Figure S4. Composition of the human mycobiome across continents with the removal of the dataset of Limon (2019). a, Genus-level gut mycobiome composition across the three continents (North America, Europe, and Asia). b, The distribution of four highly abundant fungal taxa across three continents. c, The composition of fungal enterotypes across continents in ITS1- and ITS2-combined datasets, respectively. To avoid the bias introduced by the dataset of Limon (2019) from North America (the dataset is missing the Sacc_type enterotype), we re-examined the mycobiome composition across different continents after removing the dataset of the Limon (2019). Figure S5. The robustness of fungal enterotype clustering. a, The optimal clustering number calculated within each distance-matrix determined by Silhouette score. b, The optimal cluster number under varying sampling sizes as determined by Silhouette score for ITS- and ITS2-sequencing datasets, respectively. c, The effect of removing samples from the datasets on the overall clustering behavior for ITS1- and ITS2-sequencing datasets, respectively. We repeated 100 times with different random samples removed in each iteration. The re-clustering results indicated that the enterotypes generally clustered stably with various sample size and less than 10% of samples were wrongly categorized even when half of the samples were removed. d, Hierarchical clustering on the combined ITS1 and ITS2 datasets. e, Clustering results of fungal enterotypes on ITS1 and ITS2- combined datasets visualized by Principal coordinate analysis based on Family and Order levels. The adjusted rand index (ARI) values measuring the similarity between the enterotype clustering results at the family- or order-level against that at the genus-level are shown. e, The optimal clustering number determined by Silhouette score at different taxonomic levels. Partitioning around medoid (PAM) clustering was employed based on the between-sample Bray Curtis distance. Figure S6. Characteristics of fungal enterotypes. a, Abundance of the main contributors of each fungal enterotype within ITS1- (top) and ITS2-combined datasets (bottom). b, The distribution of fungal diversity across fungal enterotypes within ITS1- (top) and ITS2-combined datasets (bottom) as measured by common alpha-diversity indices. c, The distribution of functional richness across fungal enterotypes within the CHGM cohort. In boxplots, boxes span from the first to the third quantiles and black horizontal lines represent the median, with whiskers extending 1.5 times the interquartile range (IQR). p values of two-sided Mann-Whitney U-test are shown. Figure S7. The distribution of the unclassified Ascomycota phylum (Ascomycota.sp) and the unclassified Saccharomycetales order (Saccharomycetales.sp) in ITS1 and ITS2 sequencing datasets. In boxplots, boxes span from the first to the third quantiles and black horizontal lines represent the median, with whiskers extending 1.5 times the interquartile range (IQR). p values of two-sided Mann-Whitney U-test are shown. Figure S8. Robust classification of fungal enterotypes across datasets. a-c, The 5-fold cross-validation results of four-enterotype classifier on ITS1-sequencing dataset (a), ITS2-sequencing dataset (b) and ITS1- and ITS2-combined datasets (c), separately. d-e, The cross-dataset validation performance of four-enterotype classifier between ITS1 and ITS2-sequencing datasets. “Without drivers” refers to excluding the driver genera Candida, Saccharomyces, Aspergillus, Saccharomycetales.sp, and Ascomycota.sp when training the classifiers. “Average” refers to the micro-averaging ROC curve. Figure S9. Bacterial enterotype clustering results for the CHGM metagenomics dataset. a-b, The optimal clustering number calculated within each distance-matrix determined by Silhouette score (a) and CH-index (b). c, Abundance of the main contributors of each bacterial enterotype within each bacterial enterotype. Figure S10. The inter-kingdom interactions between bacterial and fungal communities. a, The correlations between fungal enterotypes and bacterial enterotypes in cohorts with paired 16S sequencing data. The color reflects the O/E ratio (the ratio of observed count to expected count), and asterisks represent the statistical significance of Fisher’s exact test for each pair of comparison: *p &lt; 0.05, **p &lt; 0.01. b, The distribution of Bacteroides and Prevotella across four fungal enterotypes. In boxplots, boxes span from the first to the third quantiles and black horizontal lines represent the median, with whiskers extending 1.5 times the interquartile range (IQR). p values of two-sided Mann-Whitney U-test are shown. Figure S11. The impacts of host phenotypes on the human gut mycobiome. a, Enterotype clustering results on randomly down-sampled datasets (sampled by age group) with 50 repetitions. The left panel shows the optimal cluster number calculated within each distance-matric using Silhouette score for each, and the inner panel of which shows the adjusted rand score (ARI) compared to the original enterotype clusters for each repetition. The right panel shows the distribution of age across re-clustered enterotypes on down-sampled datasets. b, The relationship between Shannon diversity index and age for each fungal enterotype with shaded region representing 95% confidence intervals of the linear regression. c, The correlation between gut aging index (GAI) and Eastern Cooperative Oncology Group (ECOG) score with shaded region representing 95% confidence intervals of the linear regression. d, The distribution of GAI across bacterial enterotypes (E1_bac, E2_bac, E3_bac and E4_bac). e, The distribution of gut aging index (GAI) between non-healthy (Case) and healthy (Control) subjects. f, The distribution of BMI values across fungal enterotypes. g, The distribution of Shannon diversity of the human gut mycobiome between non-healthy (Case) and healthy (Control) subjects. h, The distribution of bacterial Shannon diversity between non-healthy (AD) and healthy (Control) subjects in the CHGM cohort from China. AUD: alcohol use disorder; T2D: type 2 diabetes; CDI: clostridium difficile infection; IBS: irritable bowel syndrome; COVID-19: coronavirus disease 2019; AD: Alzheimer’s disease. In boxplots, boxes span from the first to the third quantiles and black horizontal lines represent the median, with whiskers extending 1.5 times the interquartile range (IQR). p values of two-sided Mann-Whitney U-test are shown. Figure S12. Enterotype clustering results on healthy individuals a., Clustering results of fungal enterotypes on ITS1- and ITS2-sequencing healthy datasets and visualized by principal coordinate analysis (PCoA). b., The optimal cluster number under varying sampling sizes as determined by Silhouette score for ITS1- and ITS2-sequencing healthy datasets, respectively. c., The effect of removing samples from the healthy datasets on the overall clustering behavior for ITS1- and ITS2-sequencing healthy datasets. We repeated 100 times with different random samples removed in each iteration. The re-clustering results indicated that the enterotypes generally clustered stably with various sample size and less than 10% of samples were wrongly categorized even when half of the samples were removed. Supplementary Table S1. Statistic summary of study populations. Supplementary Table S2. The effect size of different factors on fungal community using permutational MANOVA. Supplementary Table S3. Associations between gut fungal and bacterial alpha diversity indices, where Spearman’s coefficient and corresponded p-values were shown in table. Results of Vitali et al (2021) are not shown given its small sample size to calculate correlation. Supplementary Table S4. The effect size of metadata variables in human gut mycobiome variation within each cohort measured by “envfit” function within the R package “vegan” (*p &lt; 0.05, **p &lt; 0.01, ***p &lt; 0.001). Supplementary Table S5. 21 age-associated fungal genera (p-value &lt; 0.05). The p-values of association between these genera and fungal enterotype are also shown. The p-values are determined by the multiple linear regression with adjusted for gender and study. Supplementary Table S6. 31 fungal enterotype-associated metabolic pathways. The p-values are determined by the Wilcoxon-Rank Sum test, and the Benjamini-Hochberg false discovery rate (adjusted p) is employed to correct for multiple testing. Log(FC) denotes the log-transformed fold change of the pathway within respective fungal enterotype relative to other three enterotypes. Supplementary note. The robustness of fungal enterotype clustering results.