Viral tag and grow: a scalable approach to capture and characterize infectious virus-host pairs.
Ho Bin JangLauren ChittickYueh-Fen LiOlivier ZablockiCourtney M SandersonAlfonso CarrilloGer van den EnghMatthew B SullivanPublished in: ISME communications (2022)
Viral metagenomics (viromics) has reshaped our understanding of DNA viral diversity, ecology, and evolution across Earth's ecosystems. However, viromics now needs approaches to link newly discovered viruses to their host cells and characterize them at scale. This study adapts one such method, sequencing-enabled viral tagging (VT), to establish "Viral Tag and Grow" (VT + Grow) to rapidly capture and characterize viruses that infect a cultivated target bacterium, Pseudoalteromonas. First, baseline cytometric and microscopy data improved understanding of how infection conditions and host physiology impact populations in VT flow cytograms. Next, we extensively evaluated "and grow" capability to assess where VT signals reflect adsorption alone or wholly successful infections that lead to lysis. Third, we applied VT + Grow to a clonal virus stock, which, coupled to traditional plaque assays, revealed significant variability in burst size-findings that hint at a viral "individuality" parallel to the microbial phenotypic heterogeneity literature. Finally, we established a live protocol for public comment and improvement via protocols.io to maximally empower the research community. Together these efforts provide a robust foundation for VT researchers, and establish VT + Grow as a promising scalable technology to capture and characterize viruses from mixed community source samples that infect cultivable bacteria.
Keyphrases
- sars cov
- mental health
- healthcare
- single cell
- randomized controlled trial
- systematic review
- induced apoptosis
- climate change
- emergency department
- coronary artery disease
- high throughput
- microbial community
- machine learning
- mass spectrometry
- oxidative stress
- cell proliferation
- cell death
- optical coherence tomography
- high speed
- circulating tumor
- signaling pathway
- deep learning
- cell cycle arrest
- endoplasmic reticulum stress