A Network Framework for Tracking Resistome-Mobilome Colocalization Across Fecal Microbiota Transplantation Cohorts

RMOBI is a temporal network framework designed for tracking colocalization patterns between antimicrobial resistance genes (ARGs) and mobile genetic elements (MGEs) across donor and recipient gut microbiomes before and after Fecal Microbiota Transplantation (FMT). The framework integrates all publicly available FMT associated longitudinal shotgun metagenomic datasets from the NCBI Sequence Read Archive (SRA) to model ARG–MGE colocalizations and their temporal transitions, enabling users to examine how resistome–mobilome dynamics evolve across treatment phases. Through an interactive interface, users can filter the network by disease type, MGE group, patient stage (donor, pre-FMT, post-FMT) and by ARG or MGE to perform disease specific comparisons. RMOBI is free and open to all users without registration or login requirements

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Data

The study data set comprised 263 fecal metagenomes from sequenced human clinical microbiome samples collected in 13 published fecal microbiota transplantation (FMT) studies, representing 60 patients and 52 donors distributed in three disease specific in silico cohorts. The first cohort included individuals with primary enteric disease, most commonly recurrent Clostridioides difficile infection (rCDI; patients = 34). The second cohort consisted of patients with primary enteric disease associated with multi drug resistant bacterial (MDRB; patients = 14) and third cohort represented a non-enteric condition, melanoma (Melanoma; patients = 12), in which FMT was administered as adjuvant therapy to enhance the chemotherapeutic response. Together, these cohorts provide a diverse clinical context in which FMT has been applied, enabling comparative analysis of resistome-mobilome dynamics across distinct disease backgrounds These datasets provide paired donor, pre-FMT, and post-FMT samples, enabling tracking of AMR dynamics.

Input

As the input data file we provide a CSV file, where each row represents a unique ARG–MGE colocalization event observed in a patient sample. The file must contain the following columns:

Input File Structure


  Patient ID, Disease type, AMR ID, MGE ID, Donor, PreFMT, PostFMT(timepoints)

Patient ID: Unique patient identifier.
Disease type: Melanoma, MDRB, or rCDI.
AMR ID: Classification of the antimicrobial resistance gene.
MGE ID: The mobile genetic element associated with the AMR gene.
Donor: 1 if the colocalization is present in the donor sample; 0 if absent.
PreFMT: 1 if the colocalization is present before FMT; 0 if absent.
PostFMT: 1 if the colocalization is present in any post-FMT timepoint; 0 if absent.

Downloads

We have released the source code of the tool and data under the GNU GPLv3 license. Everything listed on this website can be found in our github repository (https://github.com/SlizovskiyLab/RMOBI).

Output

RMOBI produces structured outputs that summarize how antimicrobial resistance genes (ARGs) and mobile genetic elements (MGEs) colocalize and change across donor, pre-FMT, and post-FMT samples. The results include:

Disease specific summaries

CSV files report each ARG–MGE colocalization and the number of patients in which it appears across the Melanoma, MDRB, and rCDI cohorts, along with phase-specific presence (Donor / Pre / Post).

MGE group summaries

Colocalizations are organized by MGE family (e.g., plasmid, prophage, ICE), enabling identification of high-mobility MGEs and major ARG carriers.

Temporal dynamics

Each ARG–MGE pair is classified as Persist, Emerge, Disappear, or Transfer, indicating how interactions change across FMT treatment phases.

Interactive network visualization

All outputs can be visualized through an interactive D3.js network interface, allowing users to explore ARG–MGE relationships with filtering by disease group, MGE type, and timepoint.

Output Directory Structure


  ├── Disease_Type
  │   ├── Melanoma.csv
  │   ├── MDRB.csv
  │   └── RCDI.csv
  ├── MGE_Group
  │   ├── Colicin_plasmid.csv
  │   ├── Plasmid.csv
  │   ├── ICE.csv
  │   ├── Replicon.csv
  │   ├── Likely IS_TE.csv
  │   ├── Virus.csv
  │   └── Prophage.csv
  ├── Temporal_Dynamics
  │   ├── Disappear.csv
  │   ├── Emerge.csv
  │   ├── Persist.csv
  │   └── Transfer.csv
  └── Top_Entities
      ├── Top_args.csv
      ├── Top_mges.csv
      └── Top_colocalizations.csv