Biology subjects

Williams, C.

Publications and source records attributed to Williams, C..

108 records · Page 6Linked to original sources

bioRxiv2019

A highly multiplexed melt-curve assay for detecting the most prevalent carbapenemase, ESBL and AmpC genes

Resistance to third generation cephalosporins and carbapenems in Gram-negative bacteria is chiefly mediated by beta-lactamases including ESBL, AmpC and carbapenemase enzymes. Routine phenotypic detection methods do not provide timely results, and there is a lack of comprehensive molecular panels covering all important markers. An ESBL/carbapenemase HRM assay (SHV, TEM, CTX-M ESBLs, and NDM, IMP, KPC, VIM and OXA-48-like carbapenemases) and an AmpC HRM assay (16S rDNA control, FOX, MOX, ACC, EBC, CIT and DHA) were designed, and evaluated on 111 Gram-negative isolates with mixed resistance patterns. The sensitivity for carbapenemase, ESBL and AmpC genes was 96.7% (95%CI:82.8-99.9%), 93.6% (95%CI:85.7-97.9%) and 93.8% (95%CI:82.8-98.7%), respectively with a specificity of 100% (95%CI:95.6-100%), 93.9% (95%CI:79.8-99.3%) and 93.7% (95%CI:84.5-98.2%). The HRM assays enable the simultaneous detection of the fourteen most important ESBL, carbapenemase and AmpC genes and could be used as a molecular surveillance tool or to hasten detection of AMR for treatment management.

microbiology↗

bioRxiv2019

Modeling cross-regulatory influences on monolignol transcripts and proteins under single and combinatorial gene knockdowns in Populus trichocarpa

Accurate manipulation of metabolites in the monolignol biosynthetic pathway is a key step for controlling lignin content, structure, and other wood properties important to the bioenergy and biomaterial industries. A crucial component of this strategy is predicting how single and combinatorial knockdowns of monolignol specific gene transcripts influence the abundance of monolignol proteins, which are the driving mechanisms of monolignol biosynthesis. Computational models have been developed to estimate protein abundances from transcript perturbations of monolignol specific genes. The accuracy of these models, however, is hindered by the inability to capture indirect regulatory influences on other pathway genes. Here, we examine the manifestation of these indirect influences collectively on transgenic transcript and protein abundances, identifying putative indirect regulatory influences that occur when one or more specific monolignol pathway genes are perturbed. We created a computational model using sparse maximum likelihood to estimate the resulting monolignol transcript and protein abundances in transgenic Populus trichocarpa based on desired single or combinatorial knockdowns of specific monolignol genes. Using in-silico simulations of this model and root mean square error, we show that our model more accurately estimates transcript and protein abundances in differentiating xylem tissue when individual and families of monolignol genes were perturbed. This approach provides a useful computational tool for exploring the cascaded impact of single and combinatorial modifications of monolignol specific genes on lignin and other wood properties. Additionally, these results can be used to guide future experiments to elucidate the mechanisms responsible for the indirect influences.\n\nAuthor summaryEngineering trees to have desirable lignin and wood traits is of significant interest to the bioenergy and biomaterial industries. Genetically modifying the expression of the genes that drive the monolignol biosynthetic pathway is a useful method for obtaining new traits. Modifying the expression of one gene affects not only the abundance of its encoded protein, but can also indirectly impact the amount of other transcripts and proteins. These proteins drive the monolignol biosynthetic pathway. Having an accurate representation of their abundances is key to understanding how lignin and wood traits are altered. We developed a computational model to estimate how the abundance of monolignol transcripts and proteins are changed when one or more monolignol genes are knocked down. Specifying only the abundances of the targeted genes as input, our model estimates how the levels of the other, untargeted, transcripts and proteins are altered. Our model captures indirect regulatory influences at the transcript and protein levels observed in experimental data. The model is an important addition to current models of lignin biosynthesis. By incorporating our approach into the existing models, we expect to improve our ability to explore how new combinations of gene knockdowns impact lignin and many other wood properties.

systems biology↗

bioRxiv2019

Overcoming Immunological Resistance Enhances the Efficacy of a Novel anti-tMUC1 CAR T Cell Treatment Against Pancreatic Ductal Adenocarcinoma

Chimeric antigen receptor engineered T cells (CAR T cells) have shown remarkable success in treating hematologic cancers. However, this efficacy has yet to translate to treatment in solid tumors. Pancreatic ductal adenocarcinoma (PDA) is a fatal malignancy with poor prognosis. Treatment options are limited and commonly associated with severe side effects. We have developed and characterized a second generation CAR engineered T cell using the light and heavy chain sequence derived from a novel monoclonal antibody, TAB004, that specifically binds the tumor associated antigen, tMUC1. tMUC1 is overexpressed in varying levels on ~85% of all human PDA. We present data showing that the TAB004 derived CAR T cells (tMUC1-CAR T cells) specifically bind to tMUC1 on PDA cells and is cytotoxic against the majority of the PDA cell lines. The tMUC1-CAR T cells do not bind or kill normal epithelial cells. We further demonstrate that the tMUC1-CAR T cells control the growth of orthotopic pancreatic tumors in vivo. PDAs are generally cold tumors with resistance to many standard treatment modalities, thus, it was not surprising that some of the PDA cell lines were refractory to CAR T cell treatment. qPCR analysis of several genes known to be associated with immune resistance revealed overexpression of indoleamine 2, 3-dioxygenases-1 (IDO1), Cyclooxygenase 1 and 2 (COX1 and COX2), Adenosine deaminases acting on RNA (ADAR1) and galectin-9 (Gal-9). We treated resistant PDA cells with a combination of CAR T cells and biological inhibitors of IDO1, COX1/2, ADAR1, and Gal-9. Results showed a significant enhancement of CAR T cell cytotoxicity against PDA cells when inhibiting IDO1, COX1/2, and Gal-9 but not ADAR1 or COX2. Overcoming CAR T cell resistance in PDA is a significant advancement in the field and may lead to future combination therapies that are less toxic but more efficient against this deadly disease.

cancer biology↗

bioRxiv2019

Predicting the effects of SNPs on transcription factor binding affinity

GWAS have revealed that 88% of disease associated SNPs reside in noncoding regions. However, noncoding SNPs remain understudied, partly because they are challenging to prioritize for experimental validation. To address this deficiency, we developed the SNP effect matrix pipeline (SEMpl). SEMpl estimates transcription factor binding affinity by observing differences in ChIP-seq signal intensity for SNPs within functional transcription factor binding sites genome-wide. By cataloging the effects of every possible mutation within the transcription factor binding site motif, SEMpl can predict the consequences of SNPs to transcription factor binding. This knowledge can be used to identify potential disease-causing regulatory loci.

bioinformatics↗

bioRxiv2019

Metformin rescues muscle function in BAG3 myofibrillar myopathy models

Dominant de novo mutations in the co-chaperone BAG3 cause a severe form of myofibrillar myopathy, exhibiting progressive muscle weakness, muscle structural failure, and protein aggregation.\n\nTo identify therapies we generated two zebrafish models, one conditionally expressing BAG3P209L and one with a nonsense mutation in bag3. Whilst transgenic BAG3P209L expressing fish display protein aggregation, modelling the early phase of the disease, bag3-/- fish demonstrate impaired autophagic activity, exercise dependent fibre disintegration, and reduced swimming activity, consistent with later stages.\n\nWe confirmed the presence of impaired autophagy in patient samples and screened autophagy promoting compounds for their effectiveness at removing protein aggregates, identifying nine including Metformin. Further evaluation demonstrated Metformin is not only able to remove the protein aggregates in zebrafish and human myoblasts but is also able to rescue the fibre disintegration and swimming deficit observed in the bag3-/- fish. Therefore, repurposing Metformin provides a promising therapy for BAG3 myopathy.

genetics↗

bioRxiv2018

Non-uniform genetic effect sizes of variants associated with refractive error suggests gene-gene or gene-environment interactions are pervasive

Refractive error is a complex ocular trait controlled by genetic and environmental factors. Genome-wide association studies (GWAS) have identified approximately 150 genetic variants associated with refractive error. Among the known environmental factors, education, near-work and time spent outdoors have been demonstrated to have the strongest associations. Currently, the extent of gene-environment or gene-gene interactions in myopia is unknown. Here we show that the majority of genetic variants associated with refractive error show evidence of effect size heterogeneity, which is a hallmark feature of genetic interactions. Using conditional quantile regression, we observed that 88% of genetic variants associated with refractive error have at least nominally-significant non-uniform, non-linear profiles across the refractive error distribution. SNP effects tend to be strongest at the phenotype extremes and have weaker effects in emmetropes. A parsimonious explanation for these findings is that gene-environment or gene-gene interactions in refractive error are pervasive.\n\nAuthor summaryThe prevalence of myopia (nearsightedness) in the United States and East Asia has almost doubled in the past 30 years. Such a rapid rise in prevalence cannot be explained by genetics, which implies that environmental (lifestyle) risk factors play a major role. Nevertheless, diverse approaches have suggested that genetics is also important, and indeed approximately 150 distinct genetic risk loci for myopia have been discovered to date. One attractive explanation for the evidence implicating both genes and environment in myopia is gene-environment (GxE) interaction (a difference in genetic effect in individuals exposed to a high vs. low level of an environmental risk factor). Past studies aiming to discover GxE interactions in myopia have met with limited success, perhaps because information on lifestyle exposures during childhood has rarely been available. Here we used an agnostic approach that does not require information about specific lifestyle exposures in order to detect signatures of GxE interaction. We found compelling evidence for widespread genetic interactions in myopia, with 88% of 150 known myopia genetic susceptibility loci showing an interaction signature. These findings suggest that GxE interactions in myopia are pervasive.

genetics↗

bioRxiv2018

Comprehensive assessment of multiple biases in small RNA sequencing reveals significant differences in the performance of widely used methods

High-throughput sequencing offers advantages over other quantification methods for microRNA (miRNA), yet numerous biases make reliable quantification challenging. Previous evaluations of the biases associated with small RNA sequencing have focused on adapter ligation bias with limited evaluation of reverse transcription or amplification biases. Furthermore, evaluations of the accuracy of quantifications of isomiRs (miRNA isoforms) or the influence of starting amount on performance have been very limited and no study has yet evaluated differences in the quantification of isomiRs of altered length. In addition, no studies have yet compared the consistency of results derived from multiple moderate starting inputs. We therefore evaluated quantifications of miRNA and isomiRs using four library preparation kits, with various starting amounts, as well as quantifications following removal of duplicate reads using unique molecular identifiers (UMIs) to mitigate reverse transcription and amplification biases. All methods resulted in false isomiR detection; however, the adapter-free method tested was especially prone to false isomiR detection. We demonstrate that using UMIs improves accuracy and we provide a guide for input amounts to improve consistency. Our data show differences and limitations of current methods, thus raising concerns about the validity of quantification of miRNA and isomiRs across studies. We advocate for the use of UMIs to improve accuracy and reliability of miRNA quantifications.

genomics↗

bioRxiv2018

Growth Factor Independent 1 is a tumor suppressor gene in colorectal cancer

Colorectal cancer (CRC) is the third most common cancer and the third leading cause of cancer death in the United States, causing about 50,000 deaths each year. Growth Factor-Independent 1 (GFI1) is a critical zinc finger transcriptional repressor responsible for controlling secretory cell differentiation in the small intestine and colon. GFI1 plays a significant role in the development of human malignancies, including leukemia, lung cancer and prostate cancer. However, the role of GFI1 in CRC progression is largely unknown. Our results demonstrate that RNA and protein expression of GFI1 are reduced in advanced stages of non-mucinous CRC. Subcutaneous tumor models demonstrated that the re-expression of GFI1 in 4 different human CRC cell lines inhibits tumor growth by 25-60%. To further investigate the role of Gfi1 in de novo colorectal tumorigenesis, we developed transgenic mice harboring a deletion of Gfi1 in the distal intestine driven by the CDX2cre (Gfi1F/F; CDX2cre/+) and crossed them with ApcMin/+ mice (ApcMin/+; Gfi1F/F; CDX2cre/+). Loss of Gfi1 significantly increased the total number of colorectal adenomas compared to littermate controls with an APC mutation alone. Furthermore, we found that compound (ApcMin/+; Gfi1F/F; CDX2cre/+) mice develop both adenomas as well as carcinoid-like tumors expressing the neuroendocrine marker chromogranin A, a feature that has not been previously described in APC-mutant tumors in mice. Collectively, these results demonstrate that Gfi1 deficiency promotes colorectal tumorigenesis, and suggest that loss of Gfi1 may promote formation of carcinoid cancers of the large intestines.\n\nSignificanceThese findings reveal that GFI1 functions as a tumor suppressor gene in colorectal tumorigenesis.

cancer biology↗

bioRxiv2018

xMD-miRNA-seq to generate near in vivo miRNA expression estimates in colon epithelial cells

Accurate, RNA-seq based, microRNA (miRNA) expression estimates from primary cells have recently been described. However, this in vitro data is mainly obtained from cell culture, which is known to alter cell maturity/differentiation status, significantly changing miRNA levels. What is needed is a robust method to obtain in vivo miRNA expression values directly from cells. We introduce expression microdissection miRNA small RNA sequencing (xMD-miRNA-seq), a method to isolate cells directly from formalin fixed paraffin-embedded (FFPE) tissues. xMD-miRNA-seq is a low-cost, high-throughput, immunohistochemistry-based method to capture any cell type of interest. As a proof-of-concept, we isolated colon epithelial cells from two specimens and performed low-input small RNA-seq. We generated up to 600,000 miRNA reads from the samples. Isolated epithelial cells, had abundant epithelial-enriched miRNA expression (miR-192; miR-194; miR-200b; miR-200c; miR-215; miR-375) and overall similar miRNA expression patterns to other epithelial cell populations (colonic enteroids and flow-isolated colon epithelium). xMD-derived epithelial cells were generally not contaminated by other adjacent cells of the colon as noted by t-SNE analysis. xMD-miRNA-seq allows for simple, economical, and efficient identification of cell-specific miRNA expression estimates. Further development will enhance rapid identification of cell-specific miRNA expression estimates in health and disease for nearly any cell type using archival FFPE material.

molecular biology↗

bioRxiv2018

BDNF-TrkB signaling in oxytocin neurons contributes to maternal behavior

Brain-derived neurotrophic factor (Bdnf) transcription is controlled by several promoters, which drive expression of multiple transcripts encoding an identical protein. We previously reported that BDNF derived from promoters I and II is highly expressed in hypothalamus and is critical for regulating aggression in male mice. Here we report that BDNF loss from these promoters causes reduced sexual receptivity and impaired maternal care in female mice, which is concomitant with decreased oxytocin (Oxt) expression during development. We identify a novel link between BDNF signaling, oxytocin, and maternal behavior by demonstrating that ablation of TrkB selectively in OXT neurons partially recapitulates maternal care impairments observed in BDNF-deficient females. Using translating ribosome affinity purification and RNA-sequencing we define a molecular profile for OXT neurons and delineate how BDNF signaling impacts gene pathways critical for structural and functional plasticity. Our findings highlight BDNF as a modulator of sexually-dimorphic hypothalamic circuits that govern female-typical behaviors.

neuroscience↗

bioRxiv2018

CityNet - Deep Learning Tools for Urban Ecoacoustic Assessment

O_LICities support unique and valuable ecological communities, but understanding urban wildlife is limited due to the difficulties of assessing biodiversity. Ecoacoustic surveying is a useful way of assessing habitats, where biotic sound measured from audio recordings is used as a proxy for biodiversity. However, existing algorithms for measuring biotic sound have been shown to be biased by non-biotic sounds in recordings, typical of urban environments.\nC_LIO_LIWe develop CityNet, a deep learning system using convolutional neural networks (CNNs), to measure audible biotic (CityBioNet) and anthropogenic (CityAnthroNet) acoustic activity in cities. The CNNs were trained on a large dataset of annotated audio recordings collected across Greater London, UK. Using a held-out test dataset, we compare the precision and recall of CityBioNet and CityAnthroNet separately to the best available alternative algorithms: four acoustic indices (AIs): Acoustic Complexity Index, Acoustic Diversity Index, Bioacoustic Index, and Normalised Difference Soundscape Index, and a state-of-the-art bird call detection CNN (bulbul). We also compare the effect of non-biotic sounds on the predictions of CityBioNet and bulbul. Finally we apply CityNet to describe acoustic patterns of the urban soundscape in two sites along an urbanisation gradient.\nC_LIO_LICityBioNet was the best performing algorithm for measuring biotic activity in terms of precision and recall, followed by bulbul, while the AIs performed worst. CityAnthroNet outperformed the Normalised Difference Soundscape Index, but by a smaller margin than CityBioNet achieved against the competing algorithms. The CityBioNet predictions were impacted by mechanical sounds, whereas air traffic and wind sounds influenced the bulbul predictions. Across an urbanisation gradient, we show that CityNet produced realistic daily patterns of biotic and anthropogenic acoustic activity from real-world urban audio data.\nC_LIO_LIUsing CityNet, it is possible to automatically measure biotic and anthropogenic acoustic activity in cities from audio recordings. If embedded within an autonomous sensing system, CityNet could produce environmental data for cites at large-scales and facilitate investigation of the impacts of anthropogenic activities on wildlife. The algorithms, code and pre-trained models are made freely available in combination with two expert-annotated urban audio datasets to facilitate automated environmental surveillance in cities.\nC_LI

ecology↗

bioRxiv2017

The effect of Wnt signaling on the localization, molecular size and activity of the beta-catenin destruction complex in vivo

Wnt signaling provides a paradigm for cell-cell signals that regulate embryonic development and stem cell homeostasis and are inappropriately activated in cancers. Our current outline of Wnt signaling focuses around several key players. The tumor suppressors APC and Axin form the core of the multiprotein destruction complex, which targets the Wnt-effector beta-catenin for phosphorylation, ubiquitination and destruction. However, mechanisms underlying destruction complex function and those by which Wnt signaling inactivates it remain much less clear. Based on work in cultured cells, we hypothesize the destruction complex is a supermolecular entity that self-assembles by Axin and APC polymerization, and that regulating complex assembly and dynamics underlie function. We took these insights into the Drosophila embryonic epidermis, a premier model of Wnt signaling. Combining biochemistry, genetic tools to manipulate Axin and APC2 levels, advanced imaging and molecule counting, we defined destruction complex assembly, stoichiometry, and localization in vivo, and its downregulation in response to Wnt signaling. Our findings challenge and revise current models of destruction complex function. Endogenous Axin and APC2 proteins accumulate at roughly similar levels, countering the accepted dogma that Axin accumulates at much lower levels. By expressing Axin:GFP at near endogenous levels we found Axin assembles into large cytoplasmic complexes containing tens to hundreds of Axin proteins. Wnt signals trigger complex recruitment to the membrane, while diffuse cytoplasmic Axin levels increase, suggesting slowed assembly. Manipulating Axin or APC2 levels had no effect on destruction complex activity when Wnt signals were absent, but, surprisingly, had opposite effects on the destruction complex when Wnt signals were present. Elevating Axin made the complex resistant to inactivation, while elevating APC2 levels enhanced inactivation. Our data suggest both absolute levels and the ratio of these two core components affect destruction complex function, supporting models in which competition among Axin partners determines destruction complex activity.\n\nAuthor SummaryCell-cell communication is critical for cells to choose fates during embryonic development and often goes wrong in diseases like cancer. The Wnt cell signaling pathway provides a superb example. Mutations in negative regulators like the proteins APC and Axin take the brakes off cell proliferation and thus contribute to colon cancer. We study how APC, Axin and their protein partners keep cell signaling off, and how cell-to-cell Wnt signals reverse this. We use the fruit fly embryo, combining biochemical, and genetic tools with advanced microscopy. We found that APC2 and Axin proteins are present in cells in similar numbers, challenging the previous dogma. We further find that the ability of Wnt signaling to turn off this negative regulatory machine is influenced both by the levels of Axin and APC2 and by the ratio of their protein levels. We also visualize the active destruction complex in the animal, and count the number of Axin proteins in this complex. Finally, we find that Wnt signals have two effects on the destruction complex--recruiting it to the cells plasma membrane and reducing its ability to assemble. Based on this, we propose a new model for how this important signaling pathway is regulated.\n\nAbbreviations

developmental biology↗

bioRxiv2017

A dual sgRNA approach for functional genomics in Arabidopsis thaliana

Reverse genetics uses loss-of-function alleles to interrogate gene function. The advent of CRISPR/Cas9-based gene editing now allows to generate knock-out alleles for any gene and entire gene families. Even in the model plant Arabidopsis thaliana, gene editing is welcomed as T-DNA insertion lines do not always generate null alleles. Here, we show efficient generation of heritable mutations in Arabidopsis using CRISPR/Cas9 with a workload similar to generating overexpression lines. We obtain Cas9 null-segregants with bi-allelic mutations in the T2 generation. Out of seven new mutant alleles we report here, one allele for GRXS17, the ortholog of human GRX3/PICOT, did not phenocopy previously characterized nulls. Notwithstanding, the mutation caused a frameshift and triggered nonsense-mediated decay. We demonstrate that our workflow is also compatible with a dual sgRNA approach in which a gene is targeted by two sgRNAs simultaneously. This paired nuclease method can result in a more reliable loss-of-function alleles that lack a large essential part of the gene. The ease in the CRISPR/Cas9 workflow should help in the eventual generation of true null alleles of every gene in the Arabidopsis genome, which will advance both basic and applied plant research.\n\nOne-sentence summaryWe present a dual sgRNA approach to delete Arabidopsis gene 34 fragments in order to obtain reliable functional knock-outs.

plant biology↗

bioRxiv2017

The Impact of Education on Myopia: A bidirectional Mendelian randomisation analysis in UK Biobank

Myopia, or short-sightedness, is one of the leading causes of visual disability in the World. The prevalence of myopia has risen steadily over recent decades, reaching epidemic levels in Southeast Asia. Observational studies have reported associations between educational attainment and myopia. Whether education causes myopia, myopic children are more intelligent, or another factor, like higher socioeconomic status, causes both is unclear since observational studies are prone to confounding and randomised trials of education are unethical. Using bidirectional Mendelian Randomisation, a form of instrumental variable (IV) analysis free from confounding, we show that every additional year in education leads to an increase in myopic refractive error, but that myopia does not lead to higher educational attainment. Our results suggest that current educational methods contribute to the global burden of myopia, and argue that educational policies and practices should take account of this to reduce future visual disability in the population.

epidemiology↗

bioRxiv2017

Mineral analysis of complete dog and cat foods in the UK and compliance with European guidelines

The mineral content of complete pet food is regulated to ensure health of the companion animal population. A comprehensive analysis of adherence to these regulatory guidelines has not been conducted. We measured mineral composition of a range of complete wet (n=97) and dry (n=80) canine and feline pet food sold in the UK to assess compliance with EU guidelines. While a majority of foods complied with [≥]8 of 11 guidelines (99% and 83% for dry and wet food, respectively), many failed to provide nutritional minimum (e.g. Cu, 20 % of wet food) or exceeded nutritional maximum (e.g. Se, 76% of wet food). Only 6% (6/97) of wet and 39% (34/80) of dry food were fully compliant. Some foods (20-30% of all analysed) had mineral imbalances such as not having the recommended balance of Ca:P (between 1:1 to 2:1). Foods with high fish content had high levels of undesirable metal elements such as arsenic. The study highlights broad non-compliance of a range of popular pet foods sold in the UK with EU guidelines (95% and 61% of wet and dry foods, respectively). If fed exclusively and over an extended period, a number of these pet foods could impact the general health of companion animals.

zoology↗

bioRxiv2017

Privacy-preserving generative deep neural networks support clinical data sharing

BackgroundData sharing accelerates scientific progress but sharing individual level data while preserving patient privacy presents a barrier.\n\nMethods and ResultsUsing pairs of deep neural networks, we generated simulated, synthetic \"participants\" that closely resemble participants of the SPRINT trial. We showed that such paired networks can be trained with differential privacy, a formal privacy framework that limits the likelihood that queries of the synthetic participants data could identify a real a participant in the trial. Machine-learning predictors built on the synthetic population generalize to the original dataset. This finding suggests that the synthetic data can be shared with others, enabling them to perform hypothesis-generating analyses as though they had the original trial data.\n\nConclusionsDeep neural networks that generate synthetic participants facilitate secondary analyses and reproducible investigation of clinical datasets by enhancing data sharing while preserving participant privacy.

bioinformatics↗

bioRxiv2017

An Inference Approach Combines Spatial And Temporal Gene Expression Data To Predict Gene Regulatory Networks In Arabidopsis Stem Cells

Identifying the transcription factors (TFs) and associated networks involved in stem cell regulation is key for understanding the initiation and growth of plant tissues and organs. Although many TFs have been shown to have a role in the Arabidopsis root stem cells, a comprehensive view of the transcriptional signature of the stem cells is lacking. In this work, we used spatial and temporal transcriptomic data to predict interactions among the genes involved in stem cell regulation. For this, we transcriptionally profiled several stem cell populations and developed a gene regulatory network (GRN) inference algorithm that combines clustering with Dynamic Bayesian Network (DBN) inference. We leveraged the topology of our networks to infer potential key regulators. The results presented in this work show that our combination of molecular biology approaches, computational biology and mathematical modeling was key to identify candidate factors that function in the stem cells. Specifically, through experimental validation and mathematical modeling, we identified PERIANTHIA (PAN) as an important molecular regulator of quiescent center (QC) function.

plant biology↗

bioRxiv2017

Phosphatidylserine Exposure after Vascular Injury-Platelet or Endothelial

BackgroundPlatelets membranes are considered the paramount site for the assembly of tenase and prothrombinase complex and are key players in localising coagulation to wound sites. However, the endothelium is also known to express phosphatidylserine (PS) and support the binding of recombinant FVa/FXa even beyond the site of injury. It thus remains unclear, what cell type play the preeminent role in the cellular control of coagulation after vascular injury.\n\nApproachTo address this question, we utilised a model of haemostasis (full thickness 1mm excisional skin wounds) as well as tissues after injury in laser and ferric chloride models of thrombosis. Damage to the endothelium was assessed by the combined methods of picrosirius red staining, immunofluorescence and electron microscopy. Using multiphoton microscopy, we then compared the spatial distribution of PS on platelets and the endothelium.\n\nResultsPlatelets and detectable PS significantly co-localised compared with similar analysis of endothelial cell and exposed PS on wounded carotids arteries which was not significant. Point injury by laser induced restricted damage of the endothelium which was associated with limited platelets recruitment. In consistence with platelets response after FeCl3 injury, platelets exposed most of the PS detected at the wound edge where skin vessels were transected in our haemostasis model (Correlation Coeff. 0.78 +/- 0.12 vs 0.35 +/- 0.23).\n\nConclusionsWe surmised that data from the different models support a paradigm of graded haemostatic response to vascular injury, in which full platelets response is limited to wound sites exposing the sub-endothelial matrix.

physiology↗