Biology subjects

Murray, N.

Publications and source records attributed to Murray, N..

5 recordsLinked to original sources

bioRxiv2022

The Colon Mucosal Sialylglycome Is Redox-Regulated by the Golgi Enzyme QSOX1

Mucus shields the intestinal epithelium from pathogens and provides a supportive environment for commensal bacteria. Mucus is composed of enormous, heavily glycosylated proteins called mucins, which become disulfide crosslinked in a multi-step biosynthetic pathway culminating in the Golgi apparatus and secretory granules of goblet cells. We observed that knockout mice lacking the Golgi-localized disulfide catalyst QSOX1 produced poorly protective colon mucus, were hypersensitive to induced colitis, and had an altered microbiome. The initial hypothesis arising from these observations was that QSOX1 catalyzes disulfide crosslinking of mucins. Contrary to this hypothesis, the disulfide-mediated polymerization of mucins and related glycoproteins proceeded normally without QSOX1. Instead, we found that QSOX1 forms regulatory disulfides in Golgi glycosyltransferases and thereby promotes effective sialylation of the colon glycome. Our findings reveal that enzymatic control of Golgi redox state impacts glycan elaboration in goblet cells, and that this pathway is crucial for maintaining mucosal function.

cell biology↗

bioRxiv2020

Reef Cover: a coral reef classification for global habitat mapping from biophysical remote sensing.

Coral reef management and conservation stand to benefit from improved high-resolution global mapping. Yet classifications employed in large-scale reef mapping to date are typically poorly defined, not shared or region-specific. Here we present Reef Cover, a new coral reef geomorphic zone classification, developed to support global-scale coral reef habitat mapping in a transparent and version-based framework. We developed scalable classes by focusing on attributes that can be observed remotely, but whose membership rules also reflect knowledge of reef formation, growth and functioning. Bridging the divide between earth observation data and geo-ecological knowledge of reefs, Reef Cover maximises the trade-off between applicability at global scales, and relevance and accuracy at local scales. We use the Caroline and Mariana Island chains in the Pacific as a case study to demonstrate use of the classification scheme and its scientific and conservation applications. The primary application of Reef Cover is the Allen Coral Atlas global coral reef mapping project, but the system will support bespoke reef mapping conducted at a variety of spatial scales.

systems biology↗

bioRxiv2020

Bacterial dormancy: a subpopulation of viable but non-culturable cells demonstrates better fitness for revival

The viable but non culturable (VBNC) state is a condition in which bacterial cells are viable and metabolically active, but resistant to cultivation using a routine growth medium. We investigated the ability of V. parahaemolyticus to form VBNC cells, and to subsequently become resuscitated. The ability to control VBNC cell formation in the laboratory allowed us to selectively isolate VBNC cells using fluorescence activated cell sorting, and to differentiate subpopulations based on their metabolic activity, cell shape and the ability to cause disease in Galleria mellonella. Our results showed that two key subpopulations (P1 and P2) of V. parahaemolyticus VBNC cells exist and can remain dormant in the VBNC state for long periods. The two subpopulations displayed different abilities for revival under favourable conditions. Proteomic analysis of these subpopulations (at two different time points: 12 days (T12) and 50 days (T50) post VBNC) has also revealed that the proteome of P2 was more similar to that of the starting microcosm culture (T0) than the proteome of P1. The proteins that were significantly up and down regulated between the different VBNC populations were determined and significantly regulated proteins were assigned into 23 functional groups, the majority being included in metabolism functional categories. A lactate dehydrogenase (lldD) protein was significantly upregulated in all subpopulations of VBNC cells and is responsible for converting lactate to pyruvate. Deletion of the lactate dehydrogenase (RIMD2210633:{Delta}lldD) gene causes the cells to enter the VBNC state significantly faster than the wild-type, and exogenously adding lactate to VBNC cells aided resuscitation and extended the resuscitation window. Addition of pyruvate to the RIMD2210633:{Delta}lldD strain restored the wild-type VBNC formation profile. This study suggests that lactate dehydrogenase plays a putative key role in regulating the VBNC state.

microbiology↗

bioRxiv2020

Only 40% of the world's forests are in good health

Many global environmental agendas, including halting biodiversity loss, reversing land degradation, and limiting climate change, depend upon retaining forests with high ecological integrity, yet the scale and degree of forest modification remains poorly quantified and mapped. By integrating data on observed and inferred human pressures and an index of lost connectivity, we generate the first globally-consistent, continuous index of forest condition as determined by degree of anthropogenic modification. Globally, only 17.4 million km2 of forest (40.5%) have high landscape level integrity (mostly found in Canada, Russia, the Amazon, Central Africa and New Guinea) and only 27% of this area is found in nationally-designated protected areas. Of the forest in protected areas, only 56% has high landscape level integrity. Ambitious policies that prioritize the retention of forest integrity, especially in the most intact areas, are now urgently needed alongside current efforts aimed at halting deforestation and restoring the integrity of forests globally.

ecology↗

bioRxiv2019

aer2vec: Distributed Representations of Adverse Event Reporting System Data as a Means to Identify Drug/Side-Effect Associations

Adverse event report (AER) data are a key source of signal for post marketing drug surveillance. The standard methodology to analyze AER data applies disproportionality metrics, which estimate the strength of drug/side-effect associations from discrete counts of their occurrence at report level. However, in other domains, improvements in predictive modeling accuracy have been obtained through representation learning, where discrete features are replaced by distributed representations learned from unlabeled data. This paper describes aer2vec, a novel representational approach for AER data in which concept embeddings emerge from neural networks trained to predict drug/side-effect co-occurrence. Trained models are evaluated for their utility in identifying drug/side-effect relationships, with improvements over disproportionality metrics in most cases. In addition, we evaluate the utility of an otherwise-untapped resource in the Food and Drug Administration (FDA) AER system - reporter designations of suspected causality - and find that incorporating this information enhances performance of all models evaluated.

bioinformatics↗