Biology subjects

McCarthy, F.

Publications and source records attributed to McCarthy, F..

4 recordsLinked to original sources

bioRxiv2021

mTOR controls neurotoxic lysosome exocytosis in inflammatory reactive astrocytes

Astrocytes respond and contribute to neuroinflammation by adopting inflammatory reactive states. Although recent efforts have characterized the gene expression signatures associated with these reactive states, the cell biology underlying inflammatory reactive astrocyte phenotypes remains under-explored. Here, we used CRISPR-based screening in human iPSC-derived astrocytes to identify mTOR activation a driver of cytokine-induced endolysosomal system remodeling, manifesting as alkalinization of endolysosomal compartments, decreased autophagic flux, and increased exocytosis of certain endolysosomal cargos. Through endolysosomal proteomics, we identified and focused on one such cargo - IL-32, a disease-associated pro-inflammatory cytokine not present in rodents, whose secretion mechanism is not well understood. We found that IL-32 was partially secreted in extracellular vesicles likely to be exosomes. Furthermore, we found that IL-32 was involved in the polarization of inflammatory reactive astrocyte states, was upregulated in astrocytes in multiple sclerosis lesions, and preferentially co-localized with astrocytes in hypoxic-ischemic encephalopathy. We believe that our results advance our understanding of cell biological pathways underlying inflammatory reactive astrocyte phenotypes and identify potential therapeutic targets.

cell biology↗

bioRxiv2021

Workflows for rapid functional annotation of diverse arthropod genomes

Genome sequencing of a diverse array of arthropod genomes is already underway and these genomes will be used to study human health, agriculture, biodiversity and ecology. These new genomes are intended to serve as community resources and provide the foundational information that is required to apply omics technologies to a more diverse set of species. However, biologists require genome annotation to use these genomes and derive a better understanding of complex biological systems. Genome annotation incorporates two related but distinct processes: demarcating genes and other elements present in genome sequences (structural annotation); and associating function with genetic elements (functional annotation). While there are well established and freely available workflows for structural annotation of gene identification in newly assembled genomes, workflows for providing the functional annotation required to support functional genomics studies are less well understood. Genome-scale functional annotation is required for functional modeling (enrichment, networks, etc.) and a first-pass genome-wide functional annotation effort can rapidly identify under-represented gene sets for focused community annotation efforts. We present an open source, open access and containerized pipeline for genome-scale functional annotation of insect proteomes and apply it to a diverse range of arthropod species. We show that the performance of the predictions is consistent across a set of arthropod genomes with varying assembly and annotation quality.Complete instructions for running each component of the functional annotation pipeline on the command line, a high performance computing cluster and the CyVerse Discovery Environment can be found at the readthedocs site (https://agbase-docs.readthedocs.io/en/latest/agbase/workflow.html). Simple summaryGenomic technologies are accumulating information about genes at a faster rate than ever before, and sequencing initiatives like the Earth Biogenome Project, i5k and Ag100Pest are expected to increase this rate of acquisition. However, if genomic sequencing is to be used for improvement of human health, agriculture and our understanding of biological systems, it is necessary to identify genes and understand how they contribute to biological outcomes. While there are several well-established workflows for assembling genomic sequences and identifying genes, understanding gene function is essential to create actionable knowledge. Moreover this functional annotation process must be easily accessible and provide information at a genomic scale to keep up with new sequence data. We report a well defined workflow for rapid functional annotation of whole proteomes to produce Gene Ontology and pathways information. We test this workflow on a diverse set of arthropod genomes and compare it to common arthropod reference genomes. The workflow we described is freely and publicly available via a web interface on CyVerse or as biocontainers that can be deployed scalably on local computing systems.

bioinformatics↗

bioRxiv2021

Crowdsourcing biocuration: the Community Assessment of Community Annotation with Ontologies (CACAO)

Experimental data about known gene functions curated from the primary literature have enormous value for research scientists in understanding biology. Using the Gene Ontology (GO), manual curation by experts has provided an important resource for studying gene function, especially within model organisms. Unprecedented expansion of the scientific literature and validation of the predicted proteins have increased both data value and the challenges of keeping pace. Capturing literature-based functional annotations is limited by the ability of biocurators to handle the massive and rapidly growing scientific literature. Within the community-oriented wiki framework for GO annotation called the Gene Ontology Normal Usage Tracking System (GONUTS), we describe an approach to expand biocuration through crowdsourcing with undergraduates. This multiplies the number of high-quality annotations in international databases, enriches our coverage of the literature on normal gene function, and pushes the field in new directions. From an intercollegiate competition judged by experienced biocurators, Community Assessment of Community Annotation with Ontologies (CACAO), we have contributed nearly 5000 literature-based annotations. Many of those annotations are to organisms not currently well-represented within GO. Over a ten-year history, our community contributors have spurred changes to the ontology not traditionally covered by professional biocurators. The CACAO principle of relying on community members to participate in and shape the future of biocuration in GO is a powerful and scalable model used to promote the scientific enterprise. It also provides undergraduate students with a unique and enriching introduction to critical reading of primary literature and acquisition of marketable skills. Significance StatementThe primary scientific literature catalogs the results from publicly funded scientific research about gene function in human-readable format. Information captured from those studies in a widely adopted, machine-readable standard format comes in the form of Gene Ontology annotations about gene functions from all domains of life. Manual annotations based on inferences directly from the scientific literature, including the evidence used to make such inferences, represents the best return on investment by improving data accessibility across the biological sciences. To supplement professional curation, our CACAO project enabled annotation of the scientific literature by community annotators, in this case undergraduates, which resulted in contribution of thousands of validated entries to public resources. These annotations are now being used by scientists worldwide.

bioinformatics↗

bioRxiv2021

OpenCell: proteome-scale endogenous tagging enables the cartography of human cellular organization

Elucidating the wiring diagram of the human cell is a central goal of the post-genomic era. We combined genome engineering, confocal live-cell imaging, mass spectrometry and data science to systematically map the localization and interactions of human proteins. Our approach provides a data-driven description of the molecular and spatial networks that organize the proteome. Unsupervised clustering of these networks delineates functional communities that facilitate biological discovery, and uncovers that RNA-binding proteins form a specific sub-group defined by unique interaction and localization properties. Furthermore, we discover that remarkably precise functional information can be derived from protein localization patterns, which often contain enough information to identify molecular interactions. Paired with a fully interactive website opencell.czbiohub.org, we provide a resource for the quantitative cartography of human cellular organization.

cell biology↗