Pig Burn Wound Microbiome

Metagenomic bioinformatics workflow for a pig burn-wound infection model.

Overview

A metagenomic bioinformatics project processing sequencing data from a pig burn-wound model to characterize the wound-associated microbial community and its dynamics over time.

Scientific or practical problem

Understanding how microbial communities colonize and change during burn-wound healing (or infection) can inform wound-care research. This requires a reproducible pipeline for turning raw shotgun metagenomic reads into genome bins and taxonomic/functional profiles.

My role

Bioinformatics analysis support, focused on the computational pipeline: raw-read processing, host-DNA depletion, assembly, genome binning, and taxonomic classification.

Dataset or data type

Shotgun metagenomic sequencing from a pig (animal model) burn-wound study. (Specific sample sizes and collaborator-owned results are not disclosed here.)

Methods and technologies

• Raw-read quality control and host depletion
• Metagenomic assembly
• Genome binning and bin refinement
• CheckM2 completeness/contamination evaluation
• GTDB-Tk taxonomic classification
• Nextflow workflows executed via Slurm and Apptainer

Workflow diagram

flowchart LR
  A[Raw reads] --> B[Host depletion & QC]
  B --> C[Metagenomic assembly]
  C --> D[Genome binning]
  D --> E[Bin refinement + CheckM2]
  E --> F[GTDB-Tk taxonomy]
  F --> G[Downstream microbiome analysis]

Major results or outputs

A reusable, containerized Nextflow workflow for metagenomic assembly-to-taxonomy processing, applicable beyond this specific study.

Challenges and decisions

Host-DNA depletion and bin refinement thresholds required careful tuning given the animal-model sample composition; workflow steps were containerized specifically to make the pipeline portable to other HPC environments.

Publications

Not yet published.

Code and documentation

Internal/collaborator project; not publicly released at this time.

Collaborators

Collaborative project with a research group studying wound-healing models; specific collaborator identities and unpublished results are withheld.

Current status

Ongoing.

Limitations or confidentiality note

This description is intentionally generalized. No unpublished results, sample-level data, or collaborator-identifying details are shown, per data-sharing agreements.