Bacteriophages and Auxiliary Metabolic Genes of the Chesapeake and Delaware Bays

🧠 Background & Motivation

Viruses are key regulators of microbial community structure and ecosystem function in marine environments. Beyond their role in host mortality, many bacteriophages encode auxiliary metabolic genes (AMGs)—genes that overlap with host metabolic pathways and can reprogram host metabolism to enhance viral replication. Through this process, viruses influence carbon cycling, nutrient turnover, and energy flow, ultimately contributing to ecosystem homeostasis.

In estuarine systems such as the Chesapeake and Delaware Bays, microbial communities experience strong seasonal and anthropogenic variability. The acquisition and expression of AMGs may provide a mechanism by which viral populations support microbial adaptation to environmental fluctuations and climate-driven stressors.

In this project, I integrated metagenomic, metatranscriptomic, and viral fraction datasets from seasonal sampling campaigns to characterize viral diversity, activity, and metabolic potential. In addition to assembled viruses from whole-community datasets, this work leverages an independent, published viral fraction dataset from the Delaware Bay, enabling direct comparison between cell-associated and free viral communities from the same ecosystem.

🎯 Research Questions & Objectives

• What is the taxonomic composition of DNA and RNA viruses in the Chesapeake and Delaware Bays?
• How does viral diversity inferred from metagenomes and metatranscriptomes compare to that from viral fraction datasets?
• Which auxiliary metabolic genes (AMGs) are encoded by estuarine viruses, and which metabolic pathways do they target?
• Are AMGs actively expressed, and do expression patterns vary seasonally or between bays?
• Can viral host associations be inferred using genome-based and gene-sharing approaches?
• How do estuarine viral communities compare with existing coastal and marine virome datasets?

👨‍🔬 My Role

• Designed the comparative viromics framework integrating MG, MT, and viral fraction data
• Identified and curated viral contigs from metagenomes and metatranscriptomes
• Performed viral taxonomy assignment and vOTU clustering
• Annotated and classified auxiliary metabolic genes (AMGs)
• Quantified viral and AMG abundance and transcriptional activity
• Conducted host prediction and gene-sharing network analyses
• Led comparative analyses with previously published estuarine virome datasets

🧩 Challenges & Solutions

Challenge 1: Distinguishing viral contigs from cellular sequences in complex metagenomic assemblies
Solution: Applied multiple viral detection tools and quality filters, followed by manual curation and validation against viral reference databases.

Challenge 2: Identifying true AMGs while avoiding false positives from host contamination
Solution: Used AMG-specific annotation frameworks with metabolic context checks, flanking gene inspection, and pathway-level validation.

Challenge 3: Integrating whole-community metagenomes with independently generated viral fraction datasets
Solution: Standardized vOTU clustering, taxonomy, and functional annotation pipelines across datasets to enable direct cross-study comparisons.

Challenge 4: Linking viruses to potential microbial hosts in the absence of cultured references
Solution: Combined gene-sharing networks, sequence similarity, and taxonomy-informed inference to predict virus–host associations.

🛠 Methods & Tools

*Data & Sequencing

• Shotgun metagenomics
• Metatranscriptomics
• Viral fraction metagenomes (Delaware Bay, published dataset)
• Read mapping for viral abundance and expression
• Comparative viromics across datasets

*Virome Analysis & Annotation

*Viral Identification & Quality Control

• VirSorter2
• VITAP
• CheckV

*Taxonomy & Classification

• geNomad
• vConTACT2

*AMG Detection & Functional Annotation

• DRAM-v
• VIBRANT
• eggNOG-mapper

*Host Prediction & Networks

• Gene-sharing networks
• Similarity-based host inference

*Mapping & Quantification

• Bowtie2
• SAMtools

*Languages & Workflow

• Python
• Bash
• R
• Snakemake
• SLURM (HPC scheduling)

📄 Publications

• *Manuscript in preparation

🎤 Conferences & Abstracts

• Bacteriophages and Auxiliary Metabolic Gene interactions in microbial adaptation in the Chesapeake and Delaware Bays
  Barbara J. Campbell, Kasey Kiser, Sam Stuckert, Jojy John
  ASM Microbe 2025, Los Angeles, USA

🧑‍🔬 Collaborators / References

Dr. Barbara J. Campbell
Dean’s Distinguished Professor
Department of Biological Sciences, Clemson University
Email: bcampb7@clemson.edu