Biology subjects

James, R.

Publications and source records attributed to James, R..

26 records · Page 2Linked to original sources

bioRxiv2020

Drug Screening with Zebrafish Visual Behavior Identifies Carvedilol as a Potential Treatment for Retinitis Pigmentosa

Retinitis Pigmentosa (RP) is an incurable inherited retinal degeneration affecting approximately 1 in 4,000 individuals globally. The goal of this work was to identify drugs that can help patients suffering from the disease. To accomplish this, we screened drugs on a zebrafish RP model. This model expresses a truncated human rhodopsin transgene (Tg(rho:Hsa.RH1_Q344X)) causing significant rod degeneration by 7 days post-fertilization (dpf). Consequently, the larvae displayed a deficit in visual motor response (VMR) under scotopic condition. The diminished VMR was leveraged to screen an ENZO SCREEN-WELL(R) REDOX library since oxidative stress is postulated to play a role in RP progression. Our screening identified a beta-blocker, carvedilol, that ameliorated the deficient VMR of the RP larvae and increased their rod number. Carvedilol can act directly on rods as it affected the adrenergic pathway in a rod-like human Y79 cell line. Since carvedilol is an FDA-approved drug, our findings suggest that carvedilol can potentially be repurposed to treat RP patients. Summary StatementThis paper presents the utilization of zebrafish visual behavior, a novel paradigm to screen and identify drugs to treat retinitis pigmentosa, an incurable retinal-degenerative disease.

neuroscience↗

bioRxiv2020

Neuroinflammation in the normal appearing white matter of multiple sclerosis brain causes abnormalities at the node of Ranvier

Changes to the structure of nodes of Ranvier in the normal-appearing white matter (NAWM) of MS brains are associated with chronic inflammation. We show that the paranodal domains in MS NAWM are longer on average than control, with Kv1.2 channels dislocated into the paranode. These pathological features are reproduced in a model of chronic meningeal inflammation generated by the injection of lentiviral vectors for the lymphotoxin- (LT) and interferon-{gamma} (IFN{gamma}) genes. We show that tumour necrosis factor (TNF), IFN{gamma} and glutamate can provoke paranodal elongation in cerebellar slice cultures, which could be reversed by an NMDA blocker. When these changes were inserted into a computational model to simulate axonal conduction, a rapid decrease in velocity was observed, reaching conduction failure in small diameter axons. We suggest that glial cells activated by proinflammatory cytokines can produce high levels of glutamate, which triggers paranodal pathology, contributing to axonal damage and conduction deficits.

neuroscience↗

bioRxiv2020

Low-coverage sequencing cost-effectively detects known and novel variation in underrepresented populations

BackgroundGenetic studies of biomedical phenotypes in underrepresented populations identify disproportionate numbers of novel associations. However, current genomics infrastructure--including most genotyping arrays and sequenced reference panels--best serves populations of European descent. A critical step for facilitating genetic studies in underrepresented populations is to ensure that genetic technologies accurately capture variation in all populations. Here, we quantify the accuracy of low-coverage sequencing in diverse African populations. ResultsWe sequenced the whole genomes of 91 individuals to high-coverage ([≥]20X) from the Neuropsychiatric Genetics of African Population-Psychosis (NeuroGAP-Psychosis) study, in which participants were recruited from Ethiopia, Kenya, South Africa, and Uganda. We empirically tested two data generation strategies, GWAS arrays versus low-coverage sequencing, by calculating the concordance of imputed variants from these technologies with those from deep whole genome sequencing data. We show that low-coverage sequencing at a depth of [≥]4X captures variants of all frequencies more accurately than all commonly used GWAS arrays investigated and at a comparable cost. Lower depths of sequencing (0.5-1X) performed comparable to commonly used low-density GWAS arrays. Low-coverage sequencing is also sensitive to novel variation, with 4X sequencing detecting 45% of singletons and 95% of common variants identified in high-coverage African whole genomes. ConclusionThese results indicate that low-coverage sequencing approaches surmount the problems induced by the ascertainment of common genotyping arrays, including those that capture variation most common in Europeans and Africans. Low-coverage sequencing effectively identifies novel variation (particularly in underrepresented populations), and presents opportunities to enhance variant discovery at a similar cost to traditional approaches.

genomics↗

bioRxiv2019

Environmental reservoirs of Mycobacterium bovis and Mycobacterium tuberculosis in the Ruaha region, Tanzania

This study was designed to investigate the prevalence of members of the Mycobacterium tuberculosis complex (MTBC) in the environment of pastoralists and villagers in the Iringa district, adjacent to the Ruaha National Park in Tanzania. Utilising specific qPCR assays, both Mycobacterium bovis and Mycobacterium tuberculosis were detected in cattle faeces, boma soil, water and household dust. M. bovis was also found in goat faeces and goat boma soil. This is the first report of faecal shedding of M. bovis in goats and the first molecular survey of faecal shedding in cattle. The prevalence of both bacterial species varied by village, area, season and sample type. Geographical and temporal correlations across sample types were suggestive of cross species transmission. This non-invasive test has previously been rigorously validated for screening other mammals; in this study it has successfully been applied to detect M. bovis and M. tuberculosis in livestock faeces and the environment.

microbiology↗

bioRxiv2018

Rapid statistical methods for inferring intra- and inter-hospital transmission of nosocomial pathogens from whole genome sequence data

Whole genome sequence (WGS) data for bacterial pathogens can provide evidence as to the source of nosocomial infection, and more specifically the ability to distinguish between intra- and inter-hospital transmission. This is currently achieved either through using SNP thresholds, which can lack statistical robustness, or by constructing phylogenetic trees, which can be computationally expensive and difficult to interpret. Here we compare two alternative statistical approaches using 1022 genomes of methicillin resistant Staphylococcus aureus (MRSA) clone ST22. In 71% of cases both methods predict the same hospital origin, which is also supported by the ML tree. Robust assignments are divided approximately equally between intra-hospital transmission and inter-hospital transmission. Our approaches are rapid and produce intuitive output that could inform on immediate infection control priorities, as well as providing long-term data on inter-hospital transmission networks. We discuss the strengths and weakness of our methods, and the generalisability of this approach.\n\nOne Sentence SummaryWe present rapid statistical methods for distinguishing intra- versus inter-hospital transmission of bacterial pathogens using whole genome sequence data; these methods do not require the use of SNP thresholds or the generation and interpretation of phylogenetic trees.

epidemiology↗

bioRxiv2018

Structural Basis of Broad Ebolavirus Neutralization by a Human Survivor Antibody

The structural features that govern broad-spectrum activity of broadly neutralizing, anti-ebolavirus antibodies (Abs) are currently unknown. Here we describe the first structure of a broadly neutralizing human Ab, ADI-15946, in complex with cleaved Ebola virus glycoprotein (EBOV GPCL). We find that ADI-15946 employs structural mimicry of a conserved interaction between the GP core and the glycan cap {beta}17-{beta}18 loop to inhibit infection. Both endosomal proteolysis of EBOV GP and binding of monoclonal Ab (mAb) FVM09 displace this loop, increase exposure of ADI-15946s conserved epitope and potentiate neutralization. Our work also illuminated the determinants of ADI-15946s reduced activity against Sudan virus (SUDV), and enabled rational, structure-guided engineering to enhance binding and neutralization against SUDV while retaining the parental breadth of activity.\n\nOne Sentence SummaryThe first crystal structure of a broadly active antibody against surface glycoproteins of ebolaviruses identifies a highly conserved epitope beneath the glycan cap and highlights the molecular requirements for broad ebolavirus neutralization.

immunology↗

bioRxiv2017

Extinction models of robustness for weighted ecological networks

O_LIAnalysis of ecological networks is a valuable approach to understanding the vulnerability of systems to environmental change. The tolerance of ecological networks to co-extinctions, resulting from sequences of primary extinctions, is a widely-used tool for modelling network robustness. Previously, these extinction models have been developed for and applied mostly to binary networks and recently used to predict cascades of co-extinctions in plant-pollinator networks. There is a need for robustness models that can make the most of the weighted data available and most importantly there is a need to understand how the structure of a network affects its robustness.\nC_LIO_LIHere, we developed a framework of extinction models for bipartite ecological networks (specifically plant-pollinator networks). In previous models co-extinctions occurred when nodes lost all their links, but by relaxing this rule (according to a set threshold) our models can be applied to binary and weighted networks, and can permit structurally correlated extinctions, i.e. the potential for avalanches of extinctions. We tested how the average and the range of robustness values is impacted by network structure and the impact of structurally-correlated extinctions sampling non-uniformly from the distribution of random extinction sequences.\nC_LIO_LIWe found that the way that structurally-correlated extinctions are modelled impacts the results; our two ecologically-plausible models produce opposing effects which shows the importance of understanding the model. We found that when applying the models to networks with weighted interactions, the effects are amplified and the variation in robustness increases. Variation in robustness is a key feature of these extinction models and is driven by the structural heterogeneity (i.e. the skewness of the degree distribution) of nodes (specifically, plant nodes) in the network.\nC_LIO_LIOur new framework of models enables us to calculate robustness with weighted, as well as binary, bipartite networks, and to make direct comparisons between models and between networks. This allows us to differentiate effects of the model and of the data (network structure) which is vital for those making ecological inferences from robustness models. The models can be applied to mutualistic and antagonistic networks, and can be extended to food webs.\nC_LI

ecology↗

bioRxiv2017

Genetic Identification Of A Common Collagen Disease In Puerto Ricans Via Identity-By-Descent Mapping In A Health System

Achieving confidence in the causality of a disease locus is a complex task that often requires supporting data from both statistical genetics and clinical genomics. Here we describe a combined approach to identify and characterize a genetic disorder that leverages distantly related patients in a health system and population-scale mapping. We utilize genomic data to uncover components of distant pedigrees, in the absence of recorded pedigree information, in the multi-ethnic BioMe biobank in New York City. By linking to medical records, we discover a locus associated with genetic relatedness that also underlies extreme short stature. We link the gene, COL27A1, with a little-known genetic disease, previously thought to be rare and recessive. We demonstrate that disease manifests in both heterozygotes and homozygotes, indicating a common collagen disorder impacting up to 2% of individuals of Puerto Rican ancestry, leading to a better understanding of the continuum of complex and Mendelian disease.

genomics↗