Article Figures & Data
Figures
- FIG 1
General pipeline for mapping microbe-medicine correlations. (a) Schematic overview of the data integration and processing steps. (b) Schematic depiction of the matching algorithm and score distribution. Through the similarity score calculated by the compound’s structure and gene expression profiles, a total of 1,193,324 microbe-drug pairs are presented in MetaMed. (c) A cartoon summary of the methods and integrated databases in MetaMed.
- FIG 2
Global landscape of the entity relationships in MetaMed. (a) Precision-score curve for MetaMed predictions. The precision-score plot shows the precision above a certain MetaMed score justified by KEGG annotations. The x axis corresponds to 1 − MetaMed score. The y axis corresponds to the precision of metabolite-drug pair predictions above a certain score. (b) Biclustering results of the microbes and drugs predicted by the similarity score (cutoff = 0.6). Microbes are labeled by phylum, and single-letter codes for each drug follow the anatomic therapeutic classification system. Therapeutic classes include the following: H, systemic hormonal preparations, excluding sex hormones and insulins; V, various; B, blood and blood-forming organs; P, antiparasitic products; M, musculoskeletal system; L, antineoplastic and immunomodulating agents; G, genitourinary system and sex hormones; R, respiratory system; A, alimentary tract and metabolism; D, dermatologicals; J, anti-infectives for systemic use; S, sensory organs; N, nervous system; C, cardiovascular system. (c) Circular layout of the predicted connections between microbes and drugs (all connections with a similarity score of ≥0.6). Line widths correspond to the number of interactions. The diagram is organized by sorting the microbes clockwise (drugs counterclockwise) in order of decreasing number of connections. Single-letter codes for each drug follow the anatomic therapeutic classification system. (d) Subnetwork showing the microbe hubs and islands (rectangular nodes in the center and periphery, respectively) and their predicted interactions with drug subsets (circles). Each rectangular node represents a single microbe in the phylum (e.g., the upper center node labeled as Actinobacteria actually represents the microbe Streptomyces lusitanus, and the lower center node labeled as Ascomycota actually represents the microbe Aspergillus fumigatus).
- FIG 3
Validation of the MetaMed prediction results. (a) Most of the microbe-drug pairs can be validated by DrugBank or published literature. The first bar indicates that 60 pairs have a similarity of 1.0. The second bar indicates that 96 pairs have a similarity of <1.0. (b) Validation results of the effect of B. coagulans on IBS. The x axis corresponds to treatment weeks. The y axis corresponds to the mean abdominal pain scores and mean bloating scores. (c) Validation results of the effect of B. coagulans on IBS. The x axis corresponds to treatment weeks. The y axis corresponds to the mean bloating scores.
- FIG 4
Validation of the MetaMed prediction of E. coli treating human T2D by MWAS. (a) E. coli at the genus level was significantly increased in the metformin group. The x axis corresponds to different microbes in the family, and “other” means that they cannot be identified at the family level. The y axis corresponds to the metagenomic read count. The P value of Enterobacteriaceae between read counts by taking the metformin group (red box plots) and read counts by taking the placebo group (blue box plots) is labeled at the top of the two box plots. (b) Most of the microbes in Enterobacteriaceae are E. coli. “Other” means the abundance is lower than 0.1%.
Tables
- TABLE 1
Summary of selected connections between microbes and drugs
TEXT S1
Supplemental methods. Download Text S1, PDF file, 0.2 MB.
Copyright © 2019 Zhao et al.
This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.
TABLE S1
List of microbe hubs and islands and their predicted interactions with drug subsets. The predicted connections above a similarity threshold (0.6) are presented to cluster the drugs and microbes by therapeutic class and microbe phylum. Microbe hubs are those microbes identified with the highest interaction number for drug types. Microbe islands are those microbes identified with the lowest interaction number for drug types. Download Table S1, XLSX file, 0.01 MB.
Copyright © 2019 Zhao et al.
This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.
TABLE S2
Predictions of microbe-drug linkages above the similarity score (0.9) and their validations by published literature. Novel identifications of microbes generating secondary metabolites similar to the corresponding drugs are marked gray. Download Table S2, XLSX file, 0.02 MB.
Copyright © 2019 Zhao et al.
This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.
TABLE S3
Predictions of microbes with disease treatment effects above the score 0.9 and their validations by published literature. Novel identifications of microbes with similar therapeutic indications as those of the corresponding drugs are marked gray. Download Table S3, XLSX file, 0.03 MB.
Copyright © 2019 Zhao et al.
This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.
TABLE S4
Predictions of microbes with side effects above the score 0.9 and their validations by published literature. Download Table S4, XLSX file, 0.07 MB.
Copyright © 2019 Zhao et al.
This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.
TABLE S5
Predictions of microbes with effects on immune transition based on the identified microbe-drug linkages above the similarity score 0.9 and their validations by published literature. Download Table S5, XLSX file, 0.06 MB.
Copyright © 2019 Zhao et al.
This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.
