Wigginton, K. R. | Search bioRxiv

bioRxiv2025

Novel Machine Learning-based Approach to Identify Viral Biomarkers of Human Respiratory Emissions from Oral and Nasal Metagenomes

Humans spend approximately 90% of their lives in built environments, making virus transmission indoors a key determinant of health. Environmental sampling of respiratory viral pathogens is often challenging because of frequent non-detect measurements. Non-detect measurements do not differentiate between samples containing low or no pathogens from samples that simply lack respiratory expulsions altogether. This ambiguity can be resolved by scanning samples for a biomarker of human respiratory emissions. To do so, reliable biomarkers for environmental monitoring need to be identified. Ideal biomarkers are prevalent across individuals, abundant, and unique to the human respiratory tract. Here, we present a new machine learning-based approach to query for suitable biomarker candidates from publicly available metagenomes and apply it to identify viral biomarkers of healthy oral and nasal microbiomes. Twelve viral biomarker candidates were selected from 1,232 curated viral operational taxonomic units. The viral biomarker candidates had as much as 63% prevalence across respiratory metagenomes and prevalence was further increased to 77-81% by combining two or three biomarkers. Quantitative PCR confirmed that these viral biomarkers were prevalent and abundant in nasal swabs and saliva samples. Notably, top candidate biomarkers remained stable and detectable through multiple lab purification steps, increasing confidence in their viral origins and demonstrating their suitability for environmental monitoring. These findings demonstrate that existing metagenomes can be used to identify effective biomarker candidates for environmental sampling. IMPORTANCEDeveloping non-pharmaceutical interventions to reduce virus transmission indoors relies on robust environmental monitoring methods. Monitoring viral pathogens is challenging because of frequent non-detect measurements that introduce uncertainty. For instance, a non-detect measurement could indicate either the absence of the pathogen or simply the lack of human respiratory activity and thus exposure. To aid in distinguishing these scenarios, this study identifies viruses from the human respiratory tract using publicly available sequencing data that can be incorporated into environmental monitoring as biomarkers of human respiratory activity. These viral biomarkers will improve indoor monitoring to help enact interventions to mitigate virus transmission. Furthermore, our approach to identify biomarkers from existing metagenomes can be adapted for future biomarker identification in any system.

microbiology↗

bioRxiv2020

Comparison of ultrafiltration and iron chloride flocculation in the preparation of aquatic viromes from contrasting sample types

Viral metagenomes (viromes) are a valuable untargeted tool for studying viral diversity and the central roles viruses play in host disease, ecology, and evolution. Establishing effective methods to concentrate and purify viral genomes prior to sequencing is essential for high quality viromes. Using virus spike-and-recovery experiments, we stepwise compared two common approaches for virus concentration, ultrafiltration and iron chloride flocculation, across diverse matrices: wastewater influent, wastewater secondary effluent, river water, and seawater. Viral DNA was purified by removing cellular DNA via chloroform cell lysis, filtration, and enzymatic degradation of extra-viral DNA. We found that viral genomes were concentrated 1-2 orders of magnitude more with ultrafiltration than iron chloride flocculation for all matrices and resulted in higher quality DNA suitable for amplification-free and long-read sequencing. Given its widespread use and utility as an inexpensive field method for virome sampling, we nonetheless sought to optimize iron flocculation. We found viruses were best concentrated in seawater with 5-fold higher iron concentrations than the standard used, inhibition of DNase activity reduced purification effectiveness, and five-fold more iron was needed to flocculate viruses from freshwater than seawater--critical knowledge for those seeking to apply this broadly used method to freshwater virome samples. Overall, our results demonstrated that ultrafiltration and purification performed better than iron chloride flocculation and purification in the tested matrices. Given that the method performance depended on the solids content and salinity of the samples, we suggest spike-and-recovery experiments be applied when concentrating and purifying sample types that diverge from those tested here. ImportanceViruses in diverse habitats numerically dominate microbial community members and are consequential for host fate and responsible for disease outbreaks. Metagenomics has provided novel insights into their presence, diversity, and ecosystem impacts. Yet the approach is hindered by the challenge that, despite their numbers, viral genomes comprise a minor portion of total community DNA in a sample. To comprehensively describe a viral community with metagenomics, viral genomes must be effectively concentrated and purified to capture low abundance and rare viruses amidst the overwhelming presence of cellular genomic DNA. We evaluated two commonly applied methods for concentrating and purifying viral DNA, ultrafiltration and iron chloride flocculation, across four aquatic sample types that differ in their solids content and salinity. Our findings demonstrated the importance of sample characteristics for method effectivity and provided performance measures for a variety of matrices. These findings contribute a more comprehensive understanding of the impacts of virome sample preparation across diverse matrices and are thus important for guiding future virome studies, given the wide range of habitats in which viruses are studied.

microbiology↗