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Related Experiment Video

Updated: Feb 24, 2026

Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples
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Enhanced multi-omic viral profiling from microbial community sequencing with BAQLaVa.

Jordan S L Jensen1,2,3, Sagun Maharjan2,3, Philipp C Münch2,4,5,6

  • 1Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA.

Biorxiv : the Preprint Server for Biology
|February 23, 2026
PubMed
Summary
This summary is machine-generated.

A new algorithm, BAQLaVa, enables high-resolution viral profiling from metagenomic data. This tool enhances understanding of viral communities and their role in inflammatory bowel diseases (IBD).

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Area of Science:

  • Microbiology
  • Virology
  • Bioinformatics

Background:

  • Viruses are essential but often undetected components of microbial ecosystems.
  • Current technologies face limitations in experimental and analytical viral detection.
  • Understanding viral communities is crucial for human health and disease research.

Purpose of the Study:

  • To develop a novel algorithm, BAQLaVa, for high-resolution viral profiling.
  • To improve the detection and analysis of viral species in complex biological samples.
  • To investigate viral community dynamics in inflammatory bowel diseases (IBD).

Main Methods:

  • Developed BAQLaVa algorithm for viral genome bin (VGB) profiling using reference-based alignment.
  • Utilized nucleotide markers and proteome sets for enhanced viral detection.
  • Applied BAQLaVa to metagenome (MGX) and metatranscriptome (MTX) samples from the HMP2 IBDMDB cohort.

Main Results:

  • BAQLaVa achieved >90% species-level recall and precision, outperforming existing methods.
  • Identified reduced virome diversity correlating with bacterial diversity during IBD inflammation.
  • Discovered enrichment of specific viruses in IBD, associated with anti-defense systems and lysogeny regulation.
  • Inferred phage-host relationships using scalable co-occurrence and covariation signals.

Conclusions:

  • BAQLaVa offers a scalable framework for sensitive and specific viral profiling from MGX and MTX data.
  • The algorithm facilitates virome epidemiology and systematic analysis of virus-host interactions.
  • Findings reveal novel viral perturbations and dynamics associated with IBD.