Biology subjects

Patrick, E.

Publications and source records attributed to Patrick, E..

43 records · Page 3Linked to original sources

bioRxiv2019

Investigating the role of exudates in recruiting Streptomyces bacteria to the Arabidopsis thaliana root microbiome

Streptomyces bacteria are ubiquitous in soils and are well-known for producing secondary metabolites, including antimicrobials. Increasingly, they are being isolated from plant roots and several studies have shown they are specifically recruited to the rhizosphere and the endosphere of the model plant Arabidopsis thaliana. Here we test the hypothesis that Streptomyces bacteria have a beneficial effect on A. thaliana growth and could potentially be used as plant probiotics. To do this, we selectively isolated streptomycetes from surface washed A. thaliana roots and generated high quality genome sequences for five strains which we named L2, M2, M3, N1 and N2. Re-infection of A. thaliana plants with L2, M2 and M3 significantly increased plant biomass individually and in combination whereas N1 and N2 had a negative effect on plant growth, likely due to their production of polyene natural products which can bind to phytosterols and reduce plant growth. N2 exhibits broad spectrum antimicrobial activity and makes filipin-like polyenes, including 14-hydroxyisochainin which inhibits the Take-all fungus, Gaeumannomyces graminis var. tritici. N2 antifungal activity as a whole was upregulated ~2-fold in response to indole-3-acetic acid (IAA) suggesting a possible role during competition in the rhizosphere. Furthermore, coating wheat seeds with N2 spores protected wheat seedlings against Take-all disease. We conclude that at least some soil dwelling streptomycetes confer growth promoting benefits on A. thaliana while others might be exploited to protect crops against disease. ImportanceIt is vital that we reduce our reliance on agrochemicals and there is increasing interest in using bacterial strains to promote plant growth and protect against disease. Our study follows up reports that Arabidopsis thaliana specifically recruits Streptomyces bacteria to its roots. In particular, we test the hypothesis that these bacteria can offer benefits to their A. thaliana hosts and that strains isolated from these plants might be used as probiotics. We isolated Streptomyces strains from surface washed A. thaliana roots and genome sequenced five phylogenetically distinct strains. Genome mining and bioassays indicated that all five strains have plant growth promoting properties, including production of IAA, siderophores and ACC deaminase activity. Three strains significantly increased A. thaliana growth in vitro and when applied in combination in soil. Another produces potent filipin-like antifungal metabolites and we used it as a seed coating to protect germinating wheat seeds against the fungal pathogen Gaeumannomyces graminis var. tritici (wheat Take-all fungus). We conclude that introducing an optimal combination of Streptomyces strains into the root microbiome can provide significant benefits to plants.

microbiology↗

bioRxiv2018

DCARS: Differential correlation across ranked samples

Genes act as a system and not in isolation. Thus, it is important to consider coordinated changes of gene expression rather than single genes when investigating biological phenomena such as the aetiology of cancer. We have developed an approach for quantifying how changes in the association between pairs of genes may inform patient prognosis called Differential Correlation across Ranked Samples (DCARS). Modelling gene correlation across a continuous sample ranking does not require the classification of patients into good or poor prognosis groups and can identify differences in gene correlation across early, mid or late stages of survival outcome. When we evaluated DCARS against the typical Fisher Z-transformation test for differential correlation, as well as a typical approach testing for interaction within a linear model, on real TCGA data, DCARS significantly ranked gene pairs containing known cancer genes more highly across a number of cancers. Similar results are found with our simulation study. DCARS was applied to 13 cancers datasets in TCGA, revealing a number of distinct relationships for which survival ranking was found to be associated with a change in correlation between genes. Furthermore, we demonstrated that DCARS can be used in conjunction with network analysis techniques to extract biological meaning from multilayered and complex data.\n\nAvailability: https://github.com/shazanfar/DCARS.

bioinformatics↗

bioRxiv2017

A cortical immune network map identifies a subset of human microglia involved in Tau pathology

Microglial dysfunction has been proposed as one of the many cellular mechanisms that can contribute to the development of Alzheimer's disease (AD). Here, using a transcriptional network map of the human frontal cortex, we identify five gene modules of co-expressed genes related to microglia and assess their role in the neuropathologic features of AD in 541 subjects from two cohort studies of brain aging. Two of these transcriptional programs - modules 113 and 114 - relate to the accumulation of {beta}-amyloid, while module 5 relates to tau pathology. These modules are also detectable in the human brain's epigenome, where we replicate these associations. In terms of tau, we propose that module 5, a marker of activated microglia, may lead to tau accumulation and subsequent cognitive decline. We validate our model further by showing that VASP, a representative module 5 gene, encodes a protein that is upregulated in activated microglia in AD.

neuroscience↗

bioRxiv2017

Housekeeping genes, revisited at the single-cell level

BackgroundSingle-cell RNA-seq (scRNA-seq) profiling has revealed remarkable variation in transcription, suggesting that expression of many genes at the single-cell level are intrinsically stochastic and noisy. Yet, on cell population level, a subset of genes traditionally referred to as housekeeping genes (HKGs) are found to be stably expressed in different cell and tissue types. It is therefore critical to question whether stably expressed genes (SEGs) can be identified on the single-cell level, and if so, how their expression stability can be assessed? We have developed a computational framework for ranking expression stability of genes in single cells. Here we evaluate the proposed framework and characterize SEGs derived from two scRNA-seq datasets that profile early human and mouse development.\n\nResultsHere, we show that gene expression stability indices derived from the early human and mouse development scRNA-seq datasets are highly reproducible and conserved across species. We demonstrate that SEGs identified from single cells based on their stability indices are considerably more stable than HKGs defined previously from cell populations across 10 diverse biological systems. Our analyses indicate that SEGs are inherently more stable at the single-cell level and their characteristics reminiscent of HKGs, suggesting their potential role in sustaining essential functions in individual cells.\n\nConclusionsSEGs identified in this study have immediate utility both for understanding variation/stability of single-cell transcriptomes and for practical applications including scRNA-seq data normalization, the proposed framework can be applied to identify genes with stable expression in other scRNA-seq datasets.

bioinformatics↗

bioRxiv2017

A molecular network of the aging brain implicates INPPL1 and PLXNB1 in Alzheimer’s disease

The fact that only symptomatic therapies of small effect are available for Alzheimers disease (AD) today highlights the need for new therapeutic targets with which to prevent a major contributor to aging-related cognitive decline. Here, we report the construction and validation of a molecular network of the aging human frontal cortex. Using RNA sequence data from 478 individuals, we first identify the role of modules of coexpressed genes, and then confirm them in independent AD datasets. Then, we prioritize influential genes in AD-related modules and test our predictions in human model systems. We functionally validate two putative regulator genes in human astrocytes: INPPL1 and PLXNB1, whose activity in AD may be related to semaphorin signalling and type II diabetes, which have both been implicated in AD. This arc of network identification followed by statistical and experimental validation provides specific new targets for therapeutic development and illustrates a network approach to a complex disease.\n\nOne sentence summaryMolecular network analysis of RNA sequencing data from the aging human cortex identifies new Alzheimers and cognitive decline genes.

systems biology↗

bioRxiv2017

Brain xQTL Map: Integrating The Genetic Architecture Of The Human Brain Transcriptome And Epigenome

We perform quantitative trait locus (xQTL) analyses on a multi-omic dataset, comprising RNA sequence, DNA methylation, and histone acetylation ChIP sequence data from the dorsolateral prefrontal cortex of 411 older adult individuals. We identify SNPs that are significantly associated with gene expression, DNA methylation, and histone modification levels. Many SNPs influence more than one type of molecular feature, and epigenetic features are shown to mediate eQTLs in a number of (9%) such loci. We illustrate the utility of our new resource, xQTL Serve, in prioritizing the cell type most affected by an xQTL and in enhancing genome wide association studies (GWAS) as we report 18 additional CNS disease susceptibility loci after re-analyzing published studies.

bioinformatics↗

bioRxiv2016

Dissecting the role of non-coding RNAs in the accumulation of amyloid and tau neuropathologies in Alzheimer’s disease

BackgroundGiven multiple studies of brain microRNA (miRNA) in relation to Alzheimers disease (AD) with few consistent results and the heterogeneity of this disease, the objective of this study was to explore their mechanism by evaluating their relation to different elements of Alzheimers disease pathology, confounding factors and mRNA expression data from the same subjects in the same brain region.\n\nResultsWe report analyses of expression profiling of miRNA (n=700 subjects) and lincRNA (n=540 subjects) from the dorsolateral prefrontal cortex of individuals participating in two longitudinal cohort studies of aging. Evaluating well-established (miR-132, miR-129), we confirm their association with pathologic AD in our dataset, and then characterize their in disease role in terms of neuritic {beta}-amyloid plaques and neurofibrillary tangle pathology. Additionally, we identify one new miRNA (miR-99) and four lincRNA that are associated with these traits. Many other previously reported associations of microRNA with AD are associated with the confounders quantified in our longitudinal cohort. Finally, by performing analyses integrating both miRNA and RNA sequence data from the same individuals (525 samples), we characterize the impact of AD associated miRNA on human brain expression: we show that the effects of miR-132 and miR-129-5b converge on certain genes such as EP300 and find a role for miR200 and its target genes in AD using an integrated miRNA/mRNA analysis.\n\nConclusionsOverall, miRNAs play a modest role in human AD, but we observe robust evidence that a small number of miRNAs are responsible for specific alterations in the cortical transcriptome that are associated with AD.

neuroscience↗