Search bioRxivSearch

Biology subjects

Alexander, T. W.

Publications and source records attributed to Alexander, T. W..

2 recordsLinked to original sources

Assessment of metagenomic sequencing and qPCR for detection of influenza D virus in bovine respiratory tract samples

High throughput sequencing is currently revolutionizing the genomics field and providing new approaches to the detection and characterization of microorganisms. The objective of this study was to assess the detection of influenza D virus (IDV) in bovine respiratory tract samples using two sequencing platforms (MiSeq and Nanopore (GridION)), and species-specific qPCR. An IDV-specific qPCR was performed on 232 samples (116 nasal swabs and 116 tracheal washes) that had been previously subject to virome sequencing using MiSeq. Nanopore sequencing was performed on 19 samples positive for IDV by either MiSeq or qPCR. Nanopore sequence data was analyzed by two bioinformatics methods: Whats In My Pot (WIMP, on the EPI2ME platform), and an in-house developed analysis pipeline. The agreement of IDV detection between qPCR and MiSeq was 82.3%, between qPCR and Nanopore was 57.9% (in-house) and 84.2% (WIMP), and between MiSeq and Nanopore was 89.5% (in-house) and 73.7% (WIMP). IDV was detected by MiSeq in 14 of 17 IDV qPCR-positive samples with Cq (cycle quantification) values below 31, despite multiplexing 50 samples for sequencing. When qPCR was regarded as the gold standard, the sensitivity and specificity of MiSeq sequence detection were 28.3% and 98.9%, respectively. We conclude that both MiSeq and Nanopore sequencing are capable of detecting IDV in clinical specimens with a range of Cq values. Sensitivity may be further improved by optimizing sequence data analysis, improving virus enrichment, or reducing the degree of multiplexing.

microbiology

Quantifying fluorescent glycan uptake to elucidate strain-level variability in foraging behaviors of rumen bacteria

Gut microbiomes have vast catabolic potential and are essential to host health and nutrition. An in-depth understanding of the metabolic pathways in these ecosystems will enable us to design treatments (i.e. prebiotics) that influence microbiome structure and enhance host physiology. Currently, the investigation of metabolic pathways relies on inferences derived from metagenomics or in vitro cultivations, however, novel approaches targeting specific cell physiologies can illuminate the functional potential encoded within microbial (meta)genomes to accurately assess metabolic abilities. Here, we present a multi-faceted study using complimentary next-generation physiology and omics approaches to characterize the microbial adaptation to a prebiotic in the rumen ecosystem. Using fluorescently labeled polysaccharides, we identified bacteria that actively metabolize a glycan prebiotic in the rumen microbiome ex vivo. Subsequently, we characterized strain-level variability in carbohydrate utilization systems and predict metabolic strategies of isolated bovine-adapted strains of Bacteroides thetaiotaomicron using comparative whole genome sequencing, RNA-Seq, and carbohydrate-active enzyme fingerprinting.

microbiology