Biology subjects

Hughes, L. D.

Publications and source records attributed to Hughes, L. D..

6 recordsLinked to original sources

bioRxiv2022

Developing a standardized but extendable framework to increase the findability of infectious disease datasets

Biomedical datasets are increasing in size, stored in many repositories, and face challenges in FAIRness (findability, accessibility, interoperability, reusability). As a Consortium of infectious disease researchers from 15 Centers, we aim to adopt open science practices to promote transparency, encourage reproducibility, and accelerate research advances through data reuse. To improve FAIRness of our datasets and computational tools, we evaluated metadata standards across established biomedical data repositories. The vast majority do not adhere to a single standard, such as Schema.org, which is widely-adopted by generalist repositories. Consequently, datasets in these repositories are not findable in aggregation projects like Google Dataset Search. We alleviated this gap by creating a reusable metadata schema based on Schema.org and catalogued nearly 400 datasets and computational tools we collected. The approach is easily reusable to create schemas interoperable with community standards, but customized to a particular context. Our approach enabled data discovery, increased the reusability of datasets from a large research consortium, and accelerated research. Lastly, we discuss ongoing challenges with FAIRness beyond discoverability.

bioinformatics↗

bioRxiv2022

Tissue-specific modifier alleles determine Mertk loss-of-function traits

Knockout (KO) mouse models play critical roles in elucidating biological processes behind disease-associated or disease-resistant traits. As a consequence of gene KO, mice display certain phenotypes. Based on insight into the molecular role of said gene in a biological process, it is inferred that the particular biological process causally underlies the trait. This approach has been crucial towards understanding the basis of pathological and/or advantageous traits associated with Mertk KO. MERTK is a receptor tyrosine kinase with a critical role in phagocytosis of apoptotic cells or cellular debris. Therefore, early-onset, severe retinal degeneration was described to be a direct consequence of failed phagocytosis of photoreceptor outer segments by retinal pigment epithelia. Similarly, enhanced anti-tumor immunity was inferred to result from the failure of macrophages to dispose cancer cell corpses, resulting in a pro-inflammatory tumor microenvironment. Here we report that the loss of Mertk alone is not sufficient for retinal degeneration. This trait only manifests when the function of the paralog Tyro3 is concomitantly lost. Additionally, the dramatic resistance against two syngeneic mouse tumor models observed in Mertk KO cannot, at least entirely, be ascribed to the loss of Mertk. The widely used Mertk KO carries multiple coincidental changes in its genome that affect the expression of a number of genes, including Tyro3. Nonetheless, neither Tyro3, nor macrophage phagocytosis by alternate genetic redundancy, accounts for the absence of anti-tumor immunity in two independent Mertk KOs. Collectively, our results indicate that context-dependent epistasis of independent modifier alleles determine Mertk KO traits.

immunology↗

bioRxiv2022

Outbreak.info: A standardized, searchable platform to discover and explore COVID-19 resources and data

To combat the ongoing COVID-19 pandemic, scientists have been conducting research at breakneck speeds, producing over 52,000 peer-reviewed articles within the first year. To address the challenge in tracking the vast amount of new research located in separate repositories, we developed outbreak.info Research Library, a standardized, searchable interface of COVID-19 and SARS-CoV-2 resources. Unifying metadata from sixteen repositories, we assembled a collection of over 350,000 publications, clinical trials, datasets, protocols, and other resources as of October 2022. We used a rigorous schema to enforce consistency across different sources and resource types and linked related resources. Researchers can quickly search the latest research across data repositories, regardless of resource type or repository location, via a search interface, public API, and R package. Finally, we discuss the challenges inherent in combining metadata from scattered and heterogeneous resources and provide recommendations to streamline this process to aid scientific research.

bioinformatics↗

bioRxiv2021

Predicting the evolution of Lassa Virus endemic area and population at risk over the next decades

Lassa fever is listed among the diseases that pose the greatest risks to public health by the World Health Organization. This severe viral hemorrhagic fever is caused by Lassa virus, a zoonotic pathogen that repeatedly spills over to humans from its rodent reservoirs. It is currently not known how climate change, transformations in land use, and human population growth could affect the endemic area of this virus, currently limited to parts of West Africa. By exploring the environmental data associated with virus occurrence, we show how temperature, precipitation and the presence of pastures determine ecological suitability for virus circulation. We project that regions in Central and East Africa will likely become suitable for Lassa virus over the next decades and estimate that the total population living in areas suitable for Lassa virus may grow from about 100 million to 700 million by 2070. By analysing geotagged viral genomes, we find that in the event of Lassa virus being introduced into a new suitable region, its spread might remain spatially limited over the first decades. Our results highlight how the endemic area of Lassa virus may expand well beyond West Africa in the next decades due to human impact on the environment, putting hundreds of million more people at risk of infection.

microbiology↗

bioRxiv2021

Schema Playground: A tool for authoring, extending, and using metadata schemas to improve FAIRness of biomedical data

BackgroundBiomedical researchers are strongly encouraged to make their research outputs more Findable, Accessible, Interoperable, and Reusable (FAIR). While many biomedical research outputs are more readily accessible through open data efforts, finding relevant outputs remains a significant challenge. Schema.org is a metadata vocabulary standardization project that enables web content creators to make their content more FAIR. Leveraging schema.org could benefit biomedical research resource providers, but it can be challenging to apply schema.org standards to biomedical research outputs. We created an online browser-based tool that empowers researchers and repository developers to utilize schema.org or other biomedical schema projects. ResultsOur browser-based tool includes features which can help address many of the barriers towards schema.org-compliance such as: The ability to easily browse for relevant schema.org classes, the ability to extend and customize a class to be more suitable for biomedical research outputs, the ability to create data validation to ensure adherence of a research output to a customized class, and the ability to register a custom class to our schema registry enabling others to search and re-use it. We demonstrate the use of our tool with the creation of the Outbreak.info schema--a large multi-class schema for harmonizing various COVID-19 related resources. ConclusionsWe have created a browser-based tool to empower biomedical research resource providers to leverage schema.org classes to make their research outputs more FAIR.

bioinformatics↗

bioRxiv2017

Transcriptional profiling reveals extraordinary diversity among skeletal muscle tissues

Skeletal muscle comprises a family of diverse tissues with highly specialized morphology, function, and metabolism. Many acquired diseases - including HIV, COPD, cancer cachexia, critical illness myopathy, and sepsis - affect specific muscles while sparing others. Even monogenic muscular dystrophies tend to selectively affect certain muscle groups, despite their causative genetic mutations being present in all tissues. These observations suggest that factors intrinsic to muscle tissues influence their susceptibility to various disease mechanisms. Nevertheless, most studies have not addressed transcriptional diversity among skeletal muscles. Here we use RNA sequencing (RNA-seq) to profile global mRNA expression in a wide array of skeletal, smooth, and cardiac muscle tissues from mice and rats. Our data set, MuscleDB, reveals extensive transcriptional diversity, with greater than 50% of transcripts differentially expressed among skeletal muscle tissues. This diversity is only partly explained by fiber type composition and developmental history, suggesting that specialized transcriptional profiles establish the functional identity of muscle tissues. We find conservation in the transcriptional profiles across species as well as between males and females, indicating that these data may be useful in predicting gene expression in related species. Notably, thousands of differentially expressed genes in skeletal muscle are associated with human disease, and hundreds of these genes encode targets of drugs on the market today. We detect mRNA expression of hundreds of putative myokines that may underlie the endocrine functions of skeletal muscle. In addition to demonstrating the intrinsic diversity of skeletal muscles, these data provide a resource for generating testable hypotheses regarding the mechanisms that establish differential disease susceptibility in muscle.\n\nSignificance StatementSkeletal muscles are a diverse family of tissues with a common contractile function but divergent morphology, development, and metabolism. One need only reflect on the different functions of limb muscles and the diaphragm to realize the highly specialized nature of these tissues. Nevertheless, every study of global gene expression has analyzed at most one representative skeletal muscle. Here we measure gene expression from 11 different skeletal muscles in mice and rats. We show that there is no such thing as a representative skeletal muscle, as gene expression profiles vary widely among the tissues analyzed. These data are an important resource for pharmacologists, tissue engineers, and investigators studying the mechanisms of cellular specialization.

systems biology↗