Biology subjects

White, R.

Publications and source records attributed to White, R..

32 records · Page 2Linked to original sources

bioRxiv2021

Electrical activity between skin cells regulates melanoma initiation

Oncogenes can only initiate tumors in certain cellular contexts, which is referred to as oncogenic competence. In melanoma, whether cells in the microenvironment can endow such competence remains unclear. Using a combination of zebrafish transgenesis coupled with human tissues, we demonstrate that GABAergic signaling between keratinocytes and melanocytes promotes melanoma initiation by BRAFV600E. GABA is synthesized in melanoma cells, which then acts on GABA-A receptors on keratinocytes. Electron microscopy demonstrates synapse-like structures between keratinocytes and melanoma cells, and multi-electrode array analysis shows that GABA acts to inhibit electrical activity in melanoma/keratinocyte co-cultures. Genetic and pharmacologic perturbation of GABA synthesis abrogates melanoma initiation in vivo. These data suggest that electrical activity across the skin microenvironment determines the ability of oncogenes to initiate melanoma.

cancer biology↗

bioRxiv2021

Multi-environment QTL analysis delineates a major locus associated with homoeologous exchanges for water-use efficiency and seed yield in allopolyploid Brassica napus

O_LICanola varieties exhibit discernible variation in drought avoidance and drought escape traits, suggesting its adaptation to water-deficit environments. However, the underlying mechanisms are poorly understood. C_LIO_LIA doubled haploid (DH) population was analysed to identify QTL associated with water use efficiency (WUE) related traits. Based on the resequenced parental genome data, we developed sequence-capture based markers for fine mapping. mRNA-Seq was performed to determine the expression of candidate genes underlying QTL for carbon isotope discrimination ({Delta}13C). C_LIO_LIQTL contributing to main and QTL x Environment interaction effects for {Delta}13C and for agronomic WUE were identified. One multi-trait QTL for {Delta}13C, days to flower, plant height and seed yield was identified on chromosome A09, in the vicinity of ERECTA. Interestingly, this QTL region was overlapped with a homoeologous exchange event (HE), suggesting its association with the major QTL. Transcriptome analysis revealed several differentially expressed genes between parental lines, including in HE regions. C_LIO_LIThis study provides insights into the complexity of WUE related genes in the context of canola adaptation to water-deficit conditions. Our results suggest that alleles for high {Delta}13C contribute positively to canola yield. Genetic and genomic resources developed herein could be utilised to make genetic gains for improving canola WUE. C_LI

plant biology↗

bioRxiv2020

Digging roots is easier with AI

The scale of root quantification in research is often limited by the time required for sampling, measurement and processing samples. Recent developments in Convolutional Neural Networks (CNN) have made faster and more accurate plant image analysis possible which may significantly reduce the time required for root measurement, but challenges remain in making these methods accessible to researchers without an in-depth knowledge of Machine Learning. We analyzed root images acquired from three destructive root samplings using the RootPainter CNN-software that features an interface for corrective annotation for easier use. Root scans with and without non-root debris were used to test if training a model, i.e., learning from labeled examples, can effectively exclude the debris by comparing the end-results with measurements from clean images. Root images acquired from soil profile walls and the cross-section of soil cores were also used for training and the derived measurements were compared with manual measurements. After 200 minutes of training on each dataset, significant relationships between manual measurements and RootPainter-derived data were noted for monolith (R2=0.99), profile wall (R2=0.76) and core-break (R2=0.57). The rooting density derived from images with debris was not significantly different from that derived from clean images after processing with RootPainter. Rooting density was also successfully calculated from both profile wall and soil core images, and in each case the gradient of root density with depth was not significantly different from manual counts. Our results demonstrate that the proposed approach using CNN can lead to substantial reductions in root sample processing workloads, increasing the potential scale of future root investigations.

plant biology↗

bioRxiv2020

An in vivo reporter for tracking lipid droplet dynamics in transparent zebrafish

Lipid droplets are lipid storage organelles found in nearly all cell types from adipocytes to cancer cells. Although increasingly implicated in disease, current methods to study lipid droplets require fixation or static imaging which limits investigation of their rapid in vivo dynamics. To address this, we created a lipid droplet transgenic reporter in whole animals and cell culture by fusing tdTOMATO to Perilipin-2 (PLIN2), a lipid droplet structural protein. Expression of this transgene in transparent casper zebrafish enabled in vivo imaging of adipose depots responsive to nutrient deprivation and high-fat diet. Using this system, we tested novel regulators of lipolysis, revealing an unexpected role for nitric oxide in modulating adipocyte lipid droplets. Similarly, we expressed the PLIN2-tdTOMATO transgene in melanoma cells and found that the nitric oxide pathway also regulated lipid droplets in cancer. This model offers a tractable imaging platform to study lipid droplets across cell types and disease contexts.

cell biology↗

bioRxiv2020

Cell state diversity promotes metastasis through heterotypic cluster formation in melanoma

In melanoma, transcriptional profiling has revealed multiple co-existing cell states, including proliferative versus invasive sub-populations that have been posited to represent a "go or grow" tradeoff. Both of these populations are maintained in tumors, but how they physically interact to promote metastasis is unknown. We demonstrate that these subpopulations form spatially structured heterotypic clusters that cooperate in the seeding of metastasis. We unexpectedly found that INV cells were tightly adherent to each other, and formed clusters with a rim of PRO cells. Intravital imaging demonstrated cooperation between these populations, in which the INV cells facilitated the spread of less metastatic PRO cells. We identified the TFAP2 neural crest transcription factor as a master regulator of both clustering and the PRO/INV states. Our data suggest a framework for the co-existence of these two divergent cell populations, in which differing cell states form heterotypic clusters that promote metastasis via cell-cell cooperation.

cancer biology↗

bioRxiv2020

Development of caecaloids to study host-pathogen interactions: new insights into immunoregulatory functions of Trichuris muris extracellular vesicles in the caecum

The caecum, an intestinal appendage in the junction of the small and large intestines, displays a unique epithelium that serves as an exclusive niche for a range of pathogens including whipworms (Trichuris spp). While protocols to grow organoids from small intestine (enteroids) and colon (colonoids) exist, the conditions to culture organoids from the caecum have yet to be described. Here, we report methods to grow, differentiate and characterise mouse adult stem cell-derived caecal organoids, termed caecaloids. We compare the cellular composition of caecaloids to that of enteroids identifying differences in intestinal epithelial cell (IEC) populations that mimic those found in the caecum and small intestine. The remarkable similarity in the IECs composition and spatial conformation of caecaloids and their tissue of origin enables their use as an in vitro model to study host interactions with important caecal pathogens. Thus, exploiting this system we investigated the responses of caecal IECs to extracellular vesicles (EVs) secreted/excreted by the intracellular helminth Trichuris muris. Our findings reveal novel immunoregulatory effects of whipworm EVs on the caecal epithelium, including the downregulation of responses to nucleic acid recognition and type-I interferon (IFN) signalling.

immunology↗

bioRxiv2020

Unveiling Crucivirus Diversity by Mining Metagenomic Data

The discovery of cruciviruses revealed the most explicit example of a common protein homologue between DNA and RNA viruses to date. Cruciviruses are a novel group of circular Rep-encoding ssDNA (CRESS-DNA) viruses that encode capsid proteins (CPs) that are most closely related to those encoded by RNA viruses in the family Tombusviridae. The apparent chimeric nature of the two core proteins encoded by crucivirus genomes suggests horizontal gene transfer of CP genes between DNA and RNA viruses. Here, we identified and characterized 451 new crucivirus genomes and ten CP-encoding circular genetic elements through de novo assembly and mining of metagenomic data. These genomes are highly diverse, as demonstrated by sequence comparisons and phylogenetic analysis of subsets of the protein sequences they encode. Most of the variation is reflected in the replication associated protein (Rep) sequences, and much of the sequence diversity appears to be due to recombination. Our results suggest that recombination tends to occur more frequently among groups of cruciviruses with relatively similar capsid proteins, and that the exchange of Rep protein domains between cruciviruses is rarer than gene exchange. Altogether, we provide a comprehensive and descriptive characterization of cruciviruses. IMPORTANCEViruses are the most abundant biological entities on Earth. In addition to their impact on animal and plant health, viruses have important roles in ecosystem dynamics as well as in the evolution of the biosphere. Circular Rep-encoding single-stranded (CRESS) DNA viruses are ubiquitous in nature, many are agriculturally important, and are viruses that appear to have multiple origins from prokaryotic plasmids. CRESS-DNA viruses such as the cruciviruses, have homologues of capsid proteins (CPs) encoded by RNA viruses. The genetic structure of cruciviruses attests to the transfer of capsid genes between disparate groups of viruses. However, the evolutionary history of cruciviruses is still unclear. By collecting and analyzing cruciviral sequence data, we provide a deeper insight into the evolutionary intricacies of cruciviruses. Our results reveal an unexpected diversity of this virus group, with frequent recombination as an important determinant of variability.

evolutionary biology↗

bioRxiv2019

Manumycin Polyketides Act as Molecular Glues Between UBR7 and P53 to Impair Breast Cancer Pathogenicity

Molecular glues are an intriguing therapeutic modality that harness small-molecules to induce interactions between proteins that typically do not interact, thus enabling the creation of novel protein functions not naturally encoded in biology. While molecular glues such as thalidomide and rapamycin have catalyzed drug discovery efforts, such molecules are rare and have often been discovered fortuitously, thus limiting their potential as a general strategy for therapeutic intervention of disease. Historically, natural products have proven to be important sources of molecular glues and we postulated that natural products bearing multiple electrophilic sites may be an unexplored source of such molecules, potentially through multi-covalent attachment. Using activity-based protein profiling (ABPP)-based chemoproteomic platforms, we show that members of the manumycin family of polyketides, which bear multiple potentially reactive sites, target C374 of the putative E3 ligase UBR7 in breast cancer cells to impair breast cancer pathogenicity through engaging in molecular glue interactions with the neo-substrate tumor-suppressor TP53, leading to the activation of p53 transcriptional activity and cell death. Our results reveal a previously undiscovered anti-cancer mechanism of this natural product family and highlight the potential for combining chemoproteomics and multi-covalent natural products for the discovery and characterization of new molecular glues.

biochemistry↗

bioRxiv2019

Structure and functional analysis of the Legionella chitinase ChiA reveals a novel mechanism of metal-dependent mucin degradation

Chitinases are important enzymes that contribute to the generation of carbon and nitrogen from chitin, a long chain polymer of N-acetylglucosamine that is abundant in insects, fungi, invertebrates and fish. Although mammals do not produce chitin, chitinases have been identified in bacteria that are key virulence factors in severe respiratory, gastrointestinal and urinary diseases. However, it is unclear how these enzymes are able to carry out this dual function. Legionella pneumophila is the causative agent of Legionnaires disease, an often-fatal pneumonia and its chitinase ChiA is essential for the survival of L. pneumophila in the lung. Here we report the first atomic resolution insight into the pathogenic mechanism of a bacterial chitinase. We derive an experimental model of intact ChiA and show how its N-terminal region targets ChiA to the bacterial surface after its secretion. We provide the first evidence that L. pneumophila can bind mucins on its surface but this is not dependent on chiA. This demonstrates that additional peripheral mucin binding proteins are also expressed in L. pneumophila. Finally, we show that the ChiA C-terminal chitinase domain has novel metal-dependent peptidase activity against mammalian mucins. These findings suggest that ChiA facilitates bacterial penetration of the alveolar mucosa and ChiA may be a promising target for vaccine development.

microbiology↗

bioRxiv2019

A New Mathematical Model for Tumor Growth, Reduction and Metastasis, Validation with Zebrafish Melanoma and Potential Implications for Dormancy and Recurrence

The genetic and environmental heterogeneity associated with tumors makes cancer treatment and recovery a difficult and unpredictable process. Patients with initially similar disease can experience vastly different outcomes including sustained recovery, refractory disease or, remarkably, recurrence years after treatment. Mathematical models informed with animal and human data provide tools for theoretical and clinical understanding of cancer progression and of the causes of highly variant disease outcomes. This work postulates a population balance model to describe how populations of a large ensemble of tumors of different sizes evolve in time. Each tumor can grow or reduce in size and metastasize. Gender-segregated, immune-competent and immune-suppressed translucent zebrafish (Casper variant) were inoculated with a transgenic melanoma cell line expressing human BRAF V600E and GFP and observed for tumor progression and metastasis. The model describes both these fish data sets, full histograms of population number vs size at multiple times for both immune states, and a human hepatocellular carcinoma data set also consisting of multiple time histograms very well with a minimum of cancer-specific parameters. The only zebrafish parameter to show strong gender-dependence was the host-dependent tumor reduction (immunity) parameter. This result significantly predicts that men should have far worse outcomes than females, yet similar metastasis rates, which are both indeed the case in human melanomas. Moreover the dynamic growth - reduction interplay, for certain relationships between these processes parameters in the model provides a potential mechanism for apparent cancer dormancy and recurrence. Although fish melanoma parameters are not in this range, the model guides future work to try to access it.

cancer biology↗

bioRxiv2018

Professional medical writing support and the quality, ethics and timeliness of clinical trial reporting: a systematic review

BackgroundMany authors choose to work with professional medical writers when reporting the results of clinical trials. We conducted a systematic review to examine the relationship between professional medical writing support (PMWS) and the quality, ethics and timeliness of publications reporting clinical trials.\n\nMethodsUsing terms related to medical writer and observational study, we searched MEDLINE and Embase (no date limits), as well as abstracts and posters from meetings of the International Society for Medical Publication Professionals (ISMPP; 2014-2017). We also hand-searched the journals Medical Writing and The Write Stuff (2014-2017), and the bibliographies of studies identified in the electronic searches. We screened the results to identify studies that compared the quality, ethics and timeliness of clinical trial publications written with and without declared PMWS.\n\nResultsOur searches identified 97 potentially relevant studies, of which 89 were excluded during screening and full paper review. The remaining eight studies compared 849 publications with PMWS with 2073 articles developed without such support. In these eight studies, PMWS was shown to be associated with: increased adherence to Consolidated Standards of Reporting Trials (CONSORT) guidelines (in 3/3 studies in which this was assessed); publication in journals with an impact factor (one study); a higher quality of written English (one study); and a lower likelihood of reporting non-pre-specified outcomes (one study). PMWS was not associated with increased adherence to CONSORT for Abstracts guidelines (one study) or with the impact of published articles (mean number of citations per year, mean number of article views per year and Altmetric score; one study). In studies that assessed timeliness of publication, PMWS was associated with a reduced time from last patient visit in clinical trials to primary publication (one study), whereas time from submission to acceptance showed inconsistent results (two studies).\n\nConclusionsThis systematic review of eight observational studies suggests that PMWS increases the overall quality of reporting of clinical trials and may improve the timeliness of publication.

scientific communication and education↗

bioRxiv2018

Chromatin Accessibility Plays a Key Role in Selective Targeting of Hox Proteins

Hox protein transcription factors specify segmental diversity along the anterior-posterior body axis in metazoans. Understanding the basis of Hox function has long faced the problem that, while the different members of the Hox family show clear functional specificity in vivo, they all show very similar binding specificity in vitro. Based on in vitro studies, cofactors may increase Hox binding selectivity however a satisfactory understanding of in vivo Hox target selectivity is still lacking.\n\nWe have carried out a systematic analysis of the in vivo genomic binding profiles of all eight Drosophila Hox proteins using transient transfection in Kc167 cells to examine Hox protein targeting. We find that Hox proteins show considerable binding selectivity in vivo in the absence of the canonical Hox cofactors Extradenticle and Homothorax. Hox binding selectivity is strongly associated with chromatin accessibility; binding sites in less accessible chromatin show the highest selectivity and the different Hox proteins exhibit different propensities to bind less accessible chromatin. High Hox binding selectivity is also associated with high affinity binding regions, leading to a model where Hox proteins derive binding selectivity through an affinity-based competition with nucleosomes. Provision of the Extradenticle/Homothorax cofactors generally leads to an increase in the number of Hox binding regions and promotes the binding to regions in less accessible chromatin, however the provision of these cofactors has little effect on the overall selectivity of Hox targeting.\n\nThese studies indicate that chromatin accessibility plays a key role in Hox selectivity and we propose that relative chromatin accessibility provides a basis for subtle differences in binding specificity and affinity to generate significantly different sets of genomic targets for different Hox proteins. We suggest that this mechanism may also be relevant to other transcription factor families.

genomics↗

bioRxiv2018

Partial correlation analysis of transcriptomes helps detangle the growth and defense network in spruce

O_LIIn plants, there can be a trade-off between resource allocations to growth versus defense. Here, we use partial correlation analysis of gene expression to make inferences about the nature of this interaction.\nC_LIO_LIWe studied segregating progenies of Interior spruce subject to weevil attack. In a controlled experiment, we measured pre-attack plant growth and post-attack damage with several morphological measures, and profiled transcriptomes of 188 progeny.\nC_LIO_LIWe used partial correlations of individual transcripts (ESTs) with pairs of growth/defense traits to identify important nodes and edges in the inferred underlying gene network, e.g., those pairs of growth/defense traits with high mutual correlation with a single EST transcript. We give a method to identify such ESTs.\nC_LIO_LIA terpenoid ABC transporter gene showed strongest correlations (P=0.019); its transcript represented a hub within the compact 166-member gene-gene interaction network (P=0.004) of the negative genetic correlations between growth and subsequent pest attack. A small 21-member interaction network (P=0.004) represented the uncovered positive correlations.\nC_LIO_LIOur study demonstrates partial correlation analysis identifies important gene networks underlying growth and susceptibility to the weevil in spruce. In particular, we found transcripts that strongly modify the trade-off between growth and defense, and allow identification of networks more central to the trade-off.\nC_LI

plant biology↗

bioRxiv2017

Improving the Generation and Selection of Virtual Populations in Quantitative Systems Pharmacology Models

Quantitative systems pharmacology (QSP) models aim to describe mechanistically the pathophysiology of disease and predict the effects of therapies on that disease. For most drug development applications, it is important to predict not only the mean response to an intervention but also the distribution of responses, due to inter-patient variability. Given the necessary complexity of QSP models, and the sparsity of relevant human data, the parameters of QSP models are often not well determined. One approach to overcome these limitations is to develop alternative virtual patients (VPs) and virtual populations (Vpops), which allow for the exploration of parametric uncertainty and reproduce inter-patient variability in response to perturbation. Here we evaluated approaches to improve the efficiency of generating Vpops. We aimed to generate Vpops without sacrificing diversity of the VPs pathophysiologies and phenotypes. To do this, we built upon a previously published approach (Allen, Rieger et al. 2016) by (a) incorporating alternative optimization algorithms (genetic algorithm and Metropolis-Hastings) or alternatively (b) augmenting the optimized objective function. Each method improved the baseline algorithm by requiring significantly fewer plausible patients (precursors to VPs) to create a reasonable Vpop. #ddct #qsp

pharmacology and toxicology↗