Biology subjects

Kinsella, C. M.

Publications and source records attributed to Kinsella, C. M..

4 recordsLinked to original sources

bioRxiv2025

Disinfecting eukaryotic reference genomes to improve taxonomic inference from ancient environmental metagenomic data

Ancient environmental DNA is increasingly essential for reconstructing past ecosystems, particularly when palaeontological and archaeological tissue remains are absent. Detecting ancient plant and animal DNA in environmental samples often relies on using extensive eukaryotic reference genome databases for profiling shotgun metagenomics data. However, microbial contamination in these references can introduce substantial biases in taxonomic assignments, especially given the typical low abundance of plant and animal DNA in such samples. In this study, we present a method for identifying bacterial and archaeal-like sequences in eukaryotic genomes and apply it to nearly 3,000 reference genomes from NCBI RefSeq and GenBank (vertebrates, invertebrates, plants) as well as the 1,323 PhyloNorway plant genome assemblies from herbarium material from northern high-latitude regions. Our analysis reveals microbial-like sequences in many eukaryotic reference genomes, which are most pronounced in the PhyloNorway dataset. We provide a detailed map of the microbial-like regions, including genomic coordinates and taxonomic annotations. This resource enables the masking of microbial-like regions during profiling analyses, thereby improving the reliability of ancient environmental metagenomic datasets for downstream analyses.

genomics↗

bioRxiv2020

Enhanced virus detection and metagenomic sequencing in patients with meningitis and encephalitis

Meningitis and encephalitis are leading causes of central nervous system (CNS) disease and often result in severe neurological compromise or death. Traditional diagnostic workflows largely rely on pathogen-specific diagnostic tests, sometimes over days to weeks. Metagenomic next-generation sequencing (mNGS) is a high-throughput platform that profiles all nucleic acid in a sample. We prospectively enrolled 68 patients from New England with known or suspected CNS infection and performed mNGS from both RNA and DNA to identify potential pathogens. Using a computational metagenomic classification pipeline based on KrakenUniq and BLAST, we detected pathogen nucleic acid in cerebrospinal fluid (CSF) from 22 subjects. This included some pathogens traditionally diagnosed by serology or not typically identified in CSF, including three transmitted by Ixodes scapularis ticks (Powassan virus, Borrelia burgdorferi, Anaplasma phagocytophilum). Among 24 subjects with no clinical diagnosis, we detected enterovirus in two subjects and Epstein Barr virus in one subject. We also evaluated two methods to enhance detection of viral nucleic acid, hybrid capture and methylated DNA depletion. Hybrid capture nearly universally increased viral read recovery. Although results for methylated DNA depletion were mixed, it allowed detection of varicella zoster virus DNA in two samples that were negative by standard mNGS. Overall, mNGS is a promising approach that can test for multiple pathogens simultaneously, with similar efficacy to pathogen-specific tests, and can uncover geographically relevant infectious CNS disease, such as tick-borne infections in New England. With further laboratory and computational enhancements, mNGS may become a mainstay of workup for encephalitis and meningitis. ImportanceMeningitis and encephalitis are leading global causes of central nervous system (CNS) disability and mortality. Current diagnostic workflows remain inefficient, requiring costly pathogen-specific assays and sometimes invasive surgical procedures. Despite intensive diagnostic efforts, 40-60% of people with meningitis or encephalitis have no clear cause of their CNS disease identified. As diagnostic uncertainty often leads to costly inappropriate therapies, the need for novel pathogen detection methods is paramount. Metagenomic next-generation sequencing (mNGS) offers the unique opportunity to circumvent these challenges using unbiased laboratory and computational methods. Here, we performed comprehensive mNGS from 68 patients with suspected CNS infection, and define enhanced methods to improve the detection of CNS pathogens, including those not traditionally identified in the CNS by nucleic acid detection. Overall, our work helps elucidate how mNGS can become a mainstay in the diagnostic toolkit for CNS infections.

neuroscience↗

bioRxiv2020

Intestinal transkingdom analysis on the impact of antibiotic perturbation in health and critical illness

Bacterial microbiota play a critical role in mediating local and systemic immunity, and shifts in these microbial communities have been linked to impaired outcomes in critical illness. Emerging data indicate that other intestinal organisms, including bacteriophages, viruses of eukaryotes, fungi, and protozoa, are closely interlinked with the bacterial microbiota and their host, yet their collective role during antibiotic perturbation and critical illness remains to be elucidated. Here, multi-omics factor analysis (MOFA), a novel computational strategy to systematically integrate viral, fungal and bacterial sequence data, we describe the functional impact of exposure to broad-spectrum antibiotics in healthy volunteers and critically ill patients. We observe that a loss of the anaerobic intestinal environment is directly correlated with an overgrowth of aerobic pathobionts and their corresponding bacteriophages, as well as an absolute enrichment of opportunistic yeasts capable of causing invasive disease. These findings further illustrate the complexity of transkingdom interactions within the intestinal environment, and show that modulation of the bacterial component of the microbiome has implications extending beyond this kingdom alone.

microbiology↗

bioRxiv2018

Programmed DNA elimination of germline development genes in songbirds

Genomes can vary within individual organisms. Programmed DNA elimination leads to dramatic changes in genome organisation during the germline-soma differentiation of ciliates1, lampreys2, nematodes3,4, and various other eukaryotes5. A particularly remarkable example of tissue-specific genome differentiation is the germline-restricted chromosome (GRC) in the zebra finch which is consistently absent from somatic cells6. Although the zebra finch is an important animal model system7, molecular evidence from its large GRC (>150 megabases) is limited to a short intergenic region8 and a single mRNA9. Here, we combined cytogenetic, genomic, transcriptomic, and proteomic evidence to resolve the evolutionary origin and functional significance of the GRC. First, by generating tissue-specific de-novo linked-read genome assemblies and re-sequencing two additional germline and soma samples, we found that the GRC contains at least 115 genes which are paralogous to single-copy genes on 18 autosomes and the Z chromosome. We detected an amplification of [≥]38 GRC-linked genes into high copy numbers (up to 308 copies) but, surprisingly, no enrichment of transposable elements on the GRC. Second, transcriptome and proteome data provided evidence for functional expression of GRC genes at the RNA and protein levels in testes and ovaries. Interestingly, the GRC is enriched for genes with highly expressed orthologs in chicken gonads and gene ontologies involved in female gonad development. Third, we detected evolutionary strata of GRC-linked genes. Developmental genes such as bicc1 and trim71 have resided on the GRC for tens of millions of years, whereas dozens have become GRC-linked very recently. The GRC is thus likely widespread in songbirds (half of all bird species) and its rapid evolution may have contributed to their diversification. Together, our results demonstrate a highly dynamic evolutionary history of the songbird GRC leading to dramatic germline-soma genome differences as a novel mechanism to minimise genetic conflict between germline and soma.

evolutionary biology↗