Biology subjects

Hall, M.

Publications and source records attributed to Hall, M..

At least 55 records · Page 3Linked to original sources

bioRxiv2021

Neutrophil and natural killer cell imbalances prevent muscle stem cell mediated regeneration following murine volumetric muscle loss

Volumetric muscle loss (VML) overwhelms the innate regenerative capacity of mammalian skeletal muscle (SkM), leading to numerous disabilities and reduced quality of life. Immune cells are critical responders to muscle injury and guide tissue resident stem cell and progenitor mediated myogenic repair. However, how immune cell infiltration and inter-cellular communication networks with muscle stem cells are altered following VML and drive pathological outcomes remains underexplored. Herein, we contrast the cellular and molecular mechanisms of VML injuries that result in fibrotic degeneration or regeneration of SkM. Following degenerative VML injuries, we observe heightened infiltration of natural killer (NK) cells as well as persistence of neutrophils beyond two weeks post injury. Functional validation of NK cells revealed an antagonistic role on neutrophil accumulation in part via inducing apoptosis and CCR1 mediated chemotaxis. The persistent infiltration of neutrophils in degenerative VML injuries was found to contribute to impairments in muscle stem cell regenerative function, which was also attenuated by transforming growth factor beta 1 (TGF{beta}1). Blocking TGF{beta} signaling reduced neutrophil accumulation and fibrosis, as well as improved muscle specific force. Collectively, these results enhance our understanding of immune cell-stem cell crosstalk that drives regenerative dysfunction and provide further insight into possible avenues for fibrotic therapy exploration. SINGLE SENTENCE SUMMARYComparison of muscle injuries resulting in regeneration or fibrosis reveals inter-cellular communication between neutrophils and natural killer cells impacts muscle stem cell mediated repair.

cell biology↗

bioRxiv2021

A Novel Membrane Protein in the Rhodobacter sphaeroides LH1-RC Photocomplex

We present a cryo-EM structure of the monomeric light-harvesting-reaction center (LH1-RC) core complex from photosynthetic purple bacterium Rhodobacter (Rba.) sphaeroides at 2.9 [A] resolution. The LH1 complex forms a C-shaped structure composed of 14 {beta}-polypeptides around the RC with a large ring opening. From the cryo-EM density map, a previously unrecognized integral membrane protein, referred to as protein-U, was identified. Protein-U has a U-shaped conformation near the LH1-ring opening and was annotated as a hypothetical protein in the Rba. sphaeroides genome. Deletion of protein-U resulted in a mutant strain that expressed a much-reduced amount of the dimeric LH1-RC, indicating an important role for protein-U in dimerization of the LH1-RC complex. PufX was located opposite protein-U on the LH1-ring opening, and both its position and conformation differed from that of previous reports of dimeric LH1-RC structures obtained at low-resolution. Twenty-six molecules of the carotenoid spheroidene arranged in two distinct configurations were resolved in the Rba. sphaeroides LH1 and were positioned within the complex to block its pores. Our findings offer a new view of the core photocomplex of Rba. sphaeroides and the connections between structure and function in bacterial photocomplexes in general.

biochemistry↗

bioRxiv2021

A hybrid in silico approach reveals novel inhibitors of multiple SARS-CoV-2 variants

The National Center for Advancing Translational Sciences (NCATS) has been actively generating SARS-CoV-2 high-throughput screening data and disseminates it through the OpenData Portal (https://opendata.ncats.nih.gov/covid19/). Here, we provide a hybrid approach that utilizes NCATS screening data from the SARS-CoV-2 cytophatic effect reduction assay to build predictive models, using both machine learning and pharmacophore-based modeling. Optimized models were used to perform two iterative rounds of virtual screening to predict small molecules active against SARS-CoV-2. Experimental testing with live virus provided 100 (~16% of predicted hits) active compounds (Efficacy > 30%, IC50 [≤] 15 M). Systematic clustering analysis of active compounds revealed three promising chemotypes which have not been previously identified as inhibitors of SARS-CoV-2 infection. Further analysis identified allosteric binders to host receptor angiotensin-converting enzyme 2, which were able to inhibit the entry of pseudoparticles bearing spike protein of wild type SARS-CoV-2 as well as South African B.1.351 and UK B.1.1.7 variants.

cell biology↗

bioRxiv2021

Cryo-EM Structure of the Photosynthetic LH1-RC Complex from Rhodospirillum rubrum

We present a cryo-EM structure of the light-harvesting-reaction center (LH1-RC) core complex from purple phototrophic bacterium Rhodospirillum (Rsp.) rubrum at 2.76 [A] resolution. The LH1 complex forms a closed, slightly elliptical ring structure with 16 {beta}-polypeptides surrounding the RC. Our biochemical analysis detected rhodoquinone (RQ) molecules in the purified LH1-RC, and the cryo-EM density map specifically positions RQ at the QA site in the RC. The geranylgeraniol sidechains of bacteriochlorophyll (BChl) aG coordinated by LH1 {beta}-polypeptides exhibit a highly homologous tail-up conformation that allows for interactions with the bacteriochlorin rings of nearby LH1 -associated BChls aG. The structure also revealed key protein-protein interactions in both N- and C-terminal regions of the LH1 {beta}-polypeptides, mainly within a face-to-face structural subunit. Our findings enable to evaluate past experimental and computational results obtained with this widely used organism and provide crucial information for more detailed exploration of light-energy conversion, quinone transport, and structure-function relationships in pigment-protein complexes.

biochemistry↗

bioRxiv2021

High-resolution model of Arabidopsis Photosystem II reveals the structural consequences of digitonin-extraction

In higher plants, the photosynthetic process is performed and regulated by Photosystem II (PSII). Arabidopsis thaliana was the first higher plant with a fully sequenced genome, conferring it the status of a model organism; nonetheless, a high-resolution structure of its Photosystem II is missing. We present the first Cryo-EM high-resolution structure of Arabidopsis PSII supercomplex with average resolution of 2.79 [A], an important model for future PSII studies. The digitonin extracted PSII complexes demonstrate the importance of: the LHG2630-lipid-headgroup in the trimerization of the light-harvesting complex II; the stabilization of the PsbJ subunit and the CP43-loop E by DGD520-lipid; the choice of detergent for the integrity of membrane protein complexes. Furthermore, our data shows at the anticipated Mn4CaO5-site a single metal ion density as a reminiscent early stage of Photosystem II photoactivation.

plant biology↗

bioRxiv2020

Non-covalent TMPRSS2 inhibitors identified from virtual screening

The SARS-CoV-2 pandemic has prompted researchers to pivot their efforts to finding antiviral compounds and vaccines. In this study, we focused on the human host cell transmembrane protease serine 2 (TMPRSS2), which plays an important role in the viral life cycle by cleaving the spike protein to initiate membrane fusion. TMPRSS2 is an attractive target and has received attention for the development of drugs against SARS and MERS. Starting with comparative structural modeling and binding model analysis, we developed an efficient pharmacophore-based approach and applied a large-scale in silico database screening for small molecule inhibitors against TMPRSS2. The hits were evaluated in the TMPRSS2 biochemical assay and the SARS-CoV-2 pseudotyped particle (PP) entry assay. A number of novel inhibitors were identified, providing starting points for further development of drug candidates for the treatment of COVID-19.

bioinformatics↗

bioRxiv2020

Drug Repurposing Screen for Compounds Inhibiting the Cytopathic Effect of SARS-CoV-2

Drug repurposing is a rapid approach to identifying therapeutics for the treatment of emerging infectious diseases such as COVID-19. To address the urgent need for treatment options, we carried out a quantitative high-throughput screen using a SARS-CoV-2 cytopathic assay with a compound collection of 8,810 approved and investigational drugs, mechanism-based bioactive compounds, and natural products. Three hundred and nineteen compounds with anti-SARS-CoV-2 activities were identified and confirmed, including 91 approved drug and 49 investigational drugs. Among these confirmed compounds, the anti-SARS-CoV-2 activities of 230 compounds, including 38 approved drugs, have not been previously reported. Chlorprothixene, methotrimeprazine, and piperacetazine were the three most potent FDA approved drugs with anti-SARS-CoV-2 activities. These three compounds have not been previously reported to have anti-SARS-CoV-2 activities, although their antiviral activities against SARS-CoV and Ebola virus have been reported. These results demonstrate that this comprehensive data set of drug repurposing screen for SARS-CoV-2 is useful for drug repurposing efforts including design of new drug combinations for clinical trials.

microbiology↗

bioRxiv2020

Massive-scale biological activity-based modeling identifies novel antiviral leads against SARS-CoV-2

The recent global pandemic caused by the new coronavirus SARS-CoV-2 presents an urgent need for new therapeutic candidates. While the importance of traditional in silico approaches such as QSAR in such efforts in unquestionable, these models fundamentally rely on structural similarity to infer biological activity and are thus prone to becoming trapped in the very nearby chemical spaces of already known ligands. For novel and unprecedented threats such as COVID-19 much faster and efficient paradigms must be devised to accelerate the identification of new chemical classes for rapid drug development. Here we report the development of a new biological activity-based modeling (BABM) approach that builds on the hypothesis that compounds with similar activity patterns tend to share similar targets or mechanisms of action. In BABM, compound activity profiles established on massive scale across multiple assays are used as signatures to predict compound activity in a new assay or against a new target. We first trained and validated this approach by identifying new antiviral lead candidates for Zika and Ebola based on data from ~0.5 million compounds screened against ~2,000 assays. BABM models were then applied to predict ~300 compounds not previously reported to have activity for SARS-CoV-2, which were then tested in a live virus assay with high (>30%) hit rates. The most potent compounds showed antiviral activities in the nanomolar range. These potent confirmed compounds have the potential to be further developed in novel chemical space into new anti-SARS-CoV-2 therapies. These results demonstrate unprecedented ability using BABM to predict novel structures as chemical leads significantly beyond traditional methods, and its application in rapid drug discovery response in a global public health crisis.

cell biology↗

bioRxiv2020

Discovery of Synergistic and Antagonistic Drug Combinations against SARS-CoV-2 In Vitro

COVID-19 is undoubtedly the most impactful viral disease of the current century, afflicting millions worldwide. As yet, there is not an approved vaccine, as well as limited options from existing drugs for treating this disease. We hypothesized that combining drugs with independent mechanisms of action could result in synergy against SARS-CoV-2. Using in silico approaches, we prioritized 73 combinations of 32 drugs with potential activity against SARS-CoV-2 and then tested them in vitro. Overall, we identified 16 synergistic and 8 antagonistic combinations, 4 of which were both synergistic and antagonistic in a dose-dependent manner. Among the 16 synergistic cases, combinations of nitazoxanide with three other compounds (remdesivir, amodiaquine and umifenovir) were the most notable, all exhibiting significant synergy against SARS-CoV-2. The combination of nitazoxanide, an FDA-approved drug, and remdesivir, FDA emergency use authorization for the treatment of COVID-19, demonstrate a strong synergistic interaction. Notably, the combination of remdesivir and hydroxychloroquine demonstrated strong antagonism. Overall, our results emphasize the importance of both drug repurposing and preclinical testing of drug combinations for potential therapeutic use against SARS-CoV-2 infections.

microbiology↗

bioRxiv2020

Alternative polyadenylation is a determinant of oncogenic Ras function

Alternative polyadenylation of pre-mRNA has been recently shown to play important roles in development and cancer. Activating mutations in the Ras oncogene are common drivers of many human cancers but the mechanisms by which they cooperate with alternative polyadenylation are not known. By exploiting the genetics of C. elegans, we identified cfim-1/CFIm25, a subunit of the alternative polyadenylation machine, as a key determinant of hyperactive Ras function. Ablation of cfim-1 increased penetrance of multivulva phenotype in let-60/Ras gain-of-function (gf) mutant through shortening of transcripts at the 3 untranslated region, including p21 activated kinase pak-1/PAK1 and multidrug transporter mrp-5/ABCC1. Depletion of CFIm25 in human KRAS-driven cancer cells resulted in a similar shortening of 3 untranslated regions in the PAK1 and ABCC1 transcripts, which caused an epithelial-to-mesenchymal transition and increased cell migration. Exploiting the mechanisms by which alternative polyadenylation affects activated oncogene output could offer novel approaches for the treatment of Ras-driven tumors.

cancer biology↗

bioRxiv2020

Amino acid quality modifies the quantitative availability of protein for reproduction in Drosophila melanogaster

Diet composition, especially the relative abundance of key macronutrients, is well known to affect animal wellbeing by changing reproductive output, metabolism and length of life. However, less attention has been paid to the ways the quality of these nutrients modify these macronutrient interactions. Nutritional Geometry can be used to model the effects of multiple dietary components on life-history traits and to compare these responses when diet quality is varied. Previous studies have shown that dietary protein quality can be increased for egg production in Drosophila melanogaster by matching the dietary amino acid proportions to the balance of amino acids used by the sum of proteins in the flys in silico translated exome. Here, we show that dietary protein quality dramatically alters the effect of protein quantity on female reproduction across a broad range of diets varying in both protein and carbohydrate concentrations. These data show that when sources of ingredients vary, their relative value to the consumer can vastly differ and yield very different physiological outcomes. Such variations could be particularly important for meta analyses that look to draw generalisable conclusions from diverse studies.

physiology↗

bioRxiv2020

Identification of key proteins involved in stickleback environmental adaption with system-level analysis

Using abundance measurements of 1,490 proteins from four separate populations of three-spined sticklebacks, we implemented a system-level approach to correlate proteome dynamics with environmental salinity and temperature and the fishs population and morphotype. We identified sets of robust and accurate fingerprints that predict environmental salinity, temperature, morphotype and the population sample origin, observing that proteins with specific functions are enriched in these fingerprints. Highly apparent functions represented in all fingerprints include ion transport, proteostasis, growth, and immunity, suggesting that these functions are most diversified in populations inhabiting different environments. Applying a differential network approach, we analyzed the network of protein interactions that differs between populations. Looking at specific population combinations of differential interaction, we identify sets of connected proteins. We find that these sets and their corresponding enriched functions reflect key processes that have diverged between the four populations. Moreover, the extent of divergence, i.e. the number of enriched functions that differ between populations, is highest when all three environmental parameters are different between two populations. Key nodes in the differential interaction network signify functions that are also inherent in the fingerprints, most prominently proteostasis-related functions. However, the differential interaction network also reveals additional functions that have diverged between populations, notably cytoskeletal organization and morphogenesis. Having such a large proteomic dataset, the strength of these analyses is that the results are purely data-driven, not based on previous findings and hypotheses about adaptation. With such an unbiased approach applied on a large proteomic dataset, we find the strongest signals given by the data, making it possible to develop more discriminatory and complex biomarkers for specific contexts of interest.

systems biology↗

bioRxiv2020

Freshwater monitoring by nanopore sequencing

While traditional microbiological freshwater tests focus on the detection of specific bacterial indicator species, including pathogens, direct tracing of all aquatic DNA through metagenomics poses a profound alternative. Yet, in situ metagenomic water surveys face substantial challenges in cost and logistics. Here we present a simple, fast, cost-effective and remotely accessible freshwater diagnostics workflow centred around the portable nanopore sequencing technology. Using defined compositions and spatiotemporal microbiota from surface water of an example river in Cambridge (UK), we provide optimised experimental and bioinformatics guidelines, including a benchmark with twelve taxonomic classification tools for nanopore sequences. We find that nanopore metagenomics can depict the hydrological core microbiome and fine temporal gradients in line with complementary physicochemical measurements. In a public health context, these data feature relevant sewage signals and pathogen maps at species level resolution. We anticipate that this framework will gather momentum for new environmental monitoring initiatives using portable devices.

microbiology↗

bioRxiv2019

Bee visitation and fruit quality in berries under protected cropping vary along the length of polytunnels

Wild and managed bees provide effective crop pollination services worldwide. Protected cropping conditions are thought to alter the ambient environmental conditions in which pollinators forage for flowers, yet few studies have compared conditions at the edges and centre of growing tunnels. We measured environmental variables (temperature, relative humidity, wind speed, white light and UV light) and surveyed the activity of managed honeybees Apis mellifera, wild stingless bees Tetragonula carbonaria and sweat bees Homalictus urbanus along the length of 32 multiple open-ended polyethylene growing tunnels. These were spaced across 12 blocks at two commercial berry farms, in Coffs Harbour, New South Wales and Walkamin, North Queensland, Australia. Berry yield, fresh weight and other quality metrics were recorded at discrete increments along the length of the tunnels. We found a higher abundance and greater number of flower visits by stingless bees and honeybees at the end of tunnels, and less frequent visits to flowers toward the middle of tunnels. The centre of tunnels experienced higher temperatures and reduced wind speed. In raspberry, fruit shape was improved with greater pollinator abundance and was susceptible to higher temperatures. In blueberry, per plant yield and mean berry weight were positively associated with pollinator abundance and were lower at the centre of tunnels than at the edge. Fruit quality (crumbliness) in raspberries was improved with a greater number of visits by sweat bees, who were not as susceptible to climatic conditions within tunnels. Understanding bee foraging behaviour and changes to yield under protected cropping conditions is critical to inform the appropriate design of polytunnels and aid pollinator management within them.

ecology↗

bioRxiv2019

The evolution and phylodynamics of serotype A and SAT2 foot-and-mouth disease viruses in endemic regions of Africa

Foot-and-mouth disease (FMD) is a major livestock disease with direct clinical impacts as well as indirect trade implications. Control through vaccination and stamping-out has successfully reduced or eradicated the disease from Europe and large parts of South America. However, sub-Saharan Africa remains endemically affected with 5/7 serotypes currently known to be circulating across the continent. This has significant implications both locally for livestock production and poverty reduction but also globally as it represents a major reservoir of viruses, which could spark new epidemics in disease free countries or vaccination zones. This paper describes the phylodynamics of serotypes A and SAT2 in Africa including recent isolates from Cameroon in Central Africa. We estimated the most recent common ancestor for serotype A was an East African virus from the 1930s compared to SAT2 which has a much older common ancestor from the early 1700s. Detailed analysis of the different clades shows clearly that different clades are evolving and diffusing across the landscape at different rates with both serotypes having a particularly recent clade that is evolving and spreading more rapidly than other clades within their serotype. However, the lack of detailed sequence data available for Africa seriously limits our understanding of FMD epidemiology across the continent. A comprehensive view of the evolutionary history and dynamics of FMD viruses is essential to understand many basic epidemiological aspects of FMD in Africa such as the scale of persistence and the role of wildlife and thus the opportunities and scale at which vaccination and other controls could be applied. Finally we ask endemic countries to join the OIE/FAO supported regional networks and take advantage of new cheap technologies being rolled out to collect isolates and submit them to the World Reference Laboratory.

epidemiology↗

bioRxiv2018

Genomic signatures of evolutionary rescue in bats surviving white-nose syndrome

Rapid evolution of advantageous traits following abrupt environmental change can help populations grow and avoid extinction through evolutionary rescue. Here, we provide the first genetic evidence for rapid evolution in bat populations affected by white-nose syndrome (WNS). By comparing genetic samples from before and after little brown bat populations were decimated by WNS, we identified signatures of soft selection on standing genetic variation. This selection occurred at multiple loci in genes linked to hibernation behavior rather than immune function, suggesting that differences in hibernation strategy have allowed these bats to survive infection with WNS. Through these findings, we suggest that evolutionary rescue can be a conservationrelevant process even in slowly reproducing taxa threatened with extinction.

evolutionary biology↗

bioRxiv2018

Pollinator size and its consequences: Predictive allometry for pollinating insects

O_LIBody size is an integral functional trait that underlies pollination-related ecological processes, yet it is often impractical to measure directly. Allometric scaling laws have been used to overcome this problem. However, most existing models rely upon small sample sizes, geographically restricted sampling and have limited applicability for non-bee taxa. Predictive allometric models that consider biogeography, phylogenetic relatedness and intraspecific variation are urgently required to ensure greater accuracy.\nC_LIO_LIHere, we measured body size, as dry weight, and intertegular distance (ITD) of 391 bee species (4035 specimens) and 103 hoverfly species (399 specimens) across four biogeographic regions: Australia, Europe, North America and South America. We updated existing models within a Bayesian mixed-model framework to test the power of ITD to predict interspecific variation in pollinator dry weight in interaction with different co-variates: phylogeny or taxonomy, sexual dimorphism and biogeographic region. In addition, we used ordinary least squares (OLS) regression to assess intraspecific dry weight - ITD relationships for 10 bee and five hoverfly species.\nC_LIO_LIIncluding co-variates led to more robust interspecific body size predictions for both bees (Bayesian R2: 0.946; {Delta}R2 0.047) and hoverflies (Bayesian R2: 0.821; {Delta}R2 0.058) relative to models with ITD alone. In contrast, at the intraspecific level, our results demonstrate that ITD is an inconsistent predictor of body size for bees (R2: 0.02 - 0.66) and hoverflies (R2: -0.11 - 0.44).\nC_LIO_LITherefore, predictive allometry is more suitable for interspecific comparative analyses than assessing intraspecific variation. Collectively, these models form the basis of the dynamic R package, pollimetry, which provides a comprehensive resource for allometric research concerning insect pollinators worldwide.\nC_LI

ecology↗

bioRxiv2018

A comprehensive genomics solution for HIV surveillance and clinical monitoring in a global health setting

High-throughput viral genetic sequencing is needed to monitor the spread of drug resistance, direct optimal antiretroviral regimes, and to identify transmission dynamics in generalised HIV epidemics. Public health efforts to sequence HIV genomes at scale face three major technical challenges: (i) minimising assay cost and protocol complexity, (ii) maximising sensitivity, and (iii) recovering accurate and unbiased sequences of both the genome consensus and the within-host viral diversity. Here we present a novel, high-throughput, virus-enriched sequencing method and computational pipeline tailored specifically to HIV (veSEQ-HIV), which addresses all three technical challenges, and can be used directly on leftover blood drawn for routine CD4 testing. We demonstrate its performance on 1,620 plasma samples collected from consenting individuals attending 10 large urban clinics in Zambia, partners of HPTN 071 (PopART). We show that veSEQ-HIV consistently recovers complete HIV genomes from the majority of samples of different subtypes, and is also quantitative: the number of HIV reads per sample obtained by veSEQ-HIV estimates viral load without the need for additional testing. Both quantitativity and sensitivity were assessed on a subset of 126 samples with clinically measured viral loads, and with standardized quantification controls (VL 100 - 5,000,000 RNA copies/ml). Complete HIV genomes were recovered from 93% (85/91) of samples when viral load was over 1,000 copies per ml. The quantitative nature of the assay implies that variant frequencies estimated with veSEQ-HIV are representative of true variant frequencies in the sample. Detection of minority variants can be exploited for epidemiological analysis of transmission and drug resistance, and we show how the information contained in individual reads of a veSEQ-HIV sample can be used to detect linkage between multiple mutations associated with resistance to antiretroviral therapy. Less than 2% of reads obtained by veSEQ-HIV were identified as in silico contamination events using updates to the phyloscanner software (phyloscanner clean) that we show to be 95% sensitive and 99% specific at decontaminating NGS data. The cost of the assay -- approximately 45 USD per sample -- compares favourably with existing VL and HIV genotyping tests, and provides the additional value of viral load quantification and inference of drug resistance with a single test. veSEQ-HIV is well suited to large public health efforts and is being applied to all [~]9000 samples collected for the HPTN 071-2 (PopART Phylogenetics) study.

genomics↗