Biology subjects

Parts, L.

Publications and source records attributed to Parts, L..

28 records · Page 2Linked to original sources

bioRxiv2020

Gene dosage screens in yeast reveal core signalling pathways controlling heat adaptation

Heat stress causes proteins to unfold and lose their function, jeopardizing essential cellular processes. To protect against heat and proteotoxic stress, cells mount a dedicated stress-protective programme, the so-called heat shock response (HSR). Our understanding of the mechanisms that regulate the HSR and their contributions to heat resistance and growth is incomplete. Here we employ CRISPRi/a to down- or upregulate protein kinases and transcription factors in S. cerevisiae. We measure gene functions by quantifying perturbation effects on HSR activity, thermotolerance, and cellular fitness at 23, 30 and 38{degrees}C. The integration of these phenotypes allowed us to identify core signalling pathways of heat adaptation and reveal novel functions for the high osmolarity glycerol, unfolded protein response and protein kinase A pathways in adjusting both thermotolerance and chaperone expression. We further provide evidence for unknown cross-talk of the HSR with the cell cycle-dependent kinase Cdc28, the primary regulator of cell cycle progression. Finally, we show that CRISPRi efficiency is temperature-dependent and that different phenotypes vary in their sensitivity to knock-down. In summary, our study quantifies regulatory gene functions in different aspects of heat adaptation and advances our understanding of how eukaryotic cells counteract proteotoxic and other heat-caused damage.

genetics↗

bioRxiv2020

Genomic epidemiology and evolution of Escherichia coli in wild animals

Escherichia coli is a common bacterial species in the gastrointestinal tracts of warm-blooded animals and humans. Pathogenic and antimicrobial resistance in E. coli may emerge via host switching from animal reservoirs. Despite its potential clinical importance, knowledge of the population structure of commensal E. coli within wild hosts and the epidemiological links between E. coli in non-human hosts and E. coli in humans is still scarce. In this study, we analysed the whole genome sequencing data of a collection of 119 commensal E. coli recovered from the guts of 68 mammal and bird species in Mexico and Venezuela in the 1990s. We observed low concordance between the population structures of E. coli colonizing wild animals and the phylogeny, taxonomy and ecological and physiological attributes of the host species, with distantly related E. coli often colonizing the same or similar host species and distantly related host species often hosting closely related E. coli. We found no evidence for recent transmission of E. coli genomes from wild animals to either domesticated animals or humans. However, multiple livestock- and human-related virulence factor genes were present in E. coli of wild animals, including virulence factors characteristic for Shiga toxin-producing E. coli (STEC) and atypical enteropathogenic E. coli (aEPEC), where several isolates from wild hosts harboured the locus of enterocyte effacement (LEE) pathogenicity island. Moreover, E. coli in wild animal hosts often harboured known antibiotic resistance determinants, including against ciprofloxacin, aminoglycosides, tetracyclines and beta-lactams, with some determinants present in multiple, distantly related E. coli lineages colonizing very different host animals. We conclude that although the genome pools of E. coli colonizing wild animal and human gut are well separated, they share virulence and antibiotic resistance genes and E. coli underscoring that wild animals could serve as reservoirs for E. coli pathogenicity in human and livestock infections. ImportanceEscherichia coli is a clinically importance bacterial species implicated in human and livestock associated infections worldwide. The bacterium is known to reside in the guts of humans, livestock and wild animals. Although wild animals are recognized to serve as potential reservoirs for pathogenic E. coli strains, the knowledge of the population structure of E. coli in wild hosts is still scarce. In this study we used the fine resolution of whole genome sequencing to provide novel insights into the evolution of E. coli genomes within a broad range of wild animal species (including mammals and birds), the co-evolution of E. coli strains with their hosts and the genetics of pathogenicity of E. coli strains in wild hosts. Our results provide evidence for the clinical importance of wild animals as reservoirs for pathogenic strains and necessitate the inclusion of non-human hosts in the surveillance programs for E. coli infections.

microbiology↗

bioRxiv2019

Minimized double guide RNA libraries enable scale-limited CRISPR/Cas9 screens

Genetic screens based on CRISPR/Cas technology are a powerful tool for understanding cellular phenotypes. However, the coverage and replicate requirements result in large experiment sizes, which are limiting when samples are scarce, or the protocols are expensive and laborious. Here, we present an approach to reduce the scale of genome-wide perturbation screens up to fivefold without sacrificing performance. To do so, we deliver two randomly paired gRNAs into each cell, and rely on recent advances in gRNA design, as well as availability of gRNA effect measurements, to reduce the number of gRNAs per gene. We designed a human genome-wide library that has effective size of 30,000 constructs, yet targets each gene with three gRNAs. Our minimized double guide RNA library gives similar results to a standard single gRNA one, but using substantially fewer cells. We demonstrate that genome-wide screens can be optimized in a demanding model of induced pluripotent stem cells, reducing reagent cost 70% per replicate compared to conventional approach, while retaining high performance. The screen design and the reduction in scale it provides will enable functional genomics experiments across many possible combinations of environments and genetic backgrounds, as well as in hard to obtain and culture primary cells.

genetics↗

bioRxiv2019

Minimal genome-wide human CRISPR-Cas9 library

CRISPR guide-RNA libraries have been iteratively optimised to provide increasingly efficient reagents, although their large size is a barrier for many applications. We designed an optimised minimal genome-wide human CRISPR-Cas9 library (MinLibCas9), by mining existing large-scale gene loss-of-function datasets, resulting in a greater than 42% reduction in size compared to other libraries while preserving assay sensitivity and specificity. MinLibCas9 increases the dynamic range of CRISPR-Cas9 loss-of-function screens and extends their application to complex models and assays.

genomics↗

bioRxiv2019

Segmenting nuclei in brightfield images with neural networks

Identifying nuclei is a standard first step to analysing cells in microscopy images. The traditional approach relies on signal from a DNA stain, or fluorescent transgene expression localised to the nucleus. However, imaging techniques that do not use fluorescence can also carry useful information. Here, we demonstrate that it is possible to accurately segment nuclei directly from brightfield images using deep learning. We confirmed that three convolutional neural network architectures can be adapted for this task, with U-Net achieving the best overall performance, Mask R-CNN providing an additional benefit of instance segmentation, and DeepCell proving too slow for practical application. We found that accurate segmentation is possible using as few as 16 training images and that models trained on images from similar cell lines can extrapolate well. Acquiring data from multiple focal planes further helps distinguish nuclei in the samples. Overall, our work liberates a fluorescence channel reserved for nuclear staining, thus providing more information from the specimen, and reducing reagents and time required for preparing imaging experiments.

bioinformatics↗

bioRxiv2019

Agreement between two large pan-cancer CRISPR-Cas9 gene dependency datasets

Genome-scale CRISPR-Cas9 viability screens performed in cancer cell lines provide a systematic approach to identify cancer dependencies and new therapeutic targets. As multiple large-scale screens become available, a formal assessment of the reproducibility of these experiments becomes necessary. We analyzed data from recently published pan-cancer CRISPR-Cas9 screens performed at the Broad and Sanger institutes. Despite significant differences in experimental protocols and reagents, we found that the screen results are highly concordant across multiple metrics with both common and specific dependencies jointly identified across the two studies. Furthermore, robust biomarkers of gene dependency found in one dataset are recovered in the other. Through further analysis and replication experiments at each institute, we found that batch effects are driven principally by two key experimental parameters: the reagent library and the assay length. These results indicate that the Broad and Sanger CRISPR-Cas9 viability screens yield robust and reproducible findings.

cancer biology↗

bioRxiv2018

Mutations generated by repair of Cas9-induced double strand breaks are predictable from surrounding sequence

The exact DNA mutation produced by cellular repair of a CRISPR/Cas9-generated double strand break determines its phenotypic effect. It is known that the mutational outcomes are not random, and depend on DNA sequence at the targeted location. Here, we present a systematic study of this link. We created a high throughput assay to directly measure the edits generated by over 40,000 guide RNAs, and applied it in a range of genetic backgrounds and for alternative CRISPR/Cas9 reagents. In total, we gathered data for over 1,000,000,000 mutational outcomes in synthetic constructs, which mirror those at endogenous loci. The majority of reproducible mutations are insertions of a single base, short deletions, or long microhomology-mediated deletions. gRNAs have a cell-line dependent preference for particular outcomes, especially favouring single base insertions and microhomology-mediated deletions. We uncover sequence determinants of the produced mutations at individual loci, and use these to derive a predictor of Cas9 editing outcomes with accuracy close to the theoretical maximum. This improved understanding of sequence repair allows better design of editing experiments, and may lead to future therapeutic applications.

cell biology↗

bioRxiv2018

Precise prediction of antibiotic resistance in Escherichia coli from full genome sequences

The emergence of microbial antibiotic resistance is a global health threat. In clinical settings, the key to controlling spread of resistant strains is accurate and rapid detection. As traditional culture-based methods are time consuming, genetic approaches have recently been developed for this task. The diagnosis is typically made by measuring a few known determinants previously identified from whole genome sequencing, and thus is restricted to existing information on biological mechanisms. To overcome this limitation, we employed machine learning models to predict resistance to 11 compounds across four classes of antibiotics from existing and novel whole genome sequences of 1936 E. coli strains. We considered a range of methods, and examined population structure, isolation year, gene content, and polymorphism information as predictors. Gradient boosted decision trees consistently outperformed alternative models with an average F1 score of 0.88 on held-out data (range 0.66-0.96). While the best models most frequently employed all inputs, an average F1 score of 0.73 could be obtained using population structure information alone. Single nucleotide variation data were less useful, and failed to improve prediction for ten out of 11 antibiotics. These results demonstrate that antibiotic resistance in E. coli can be accurately predicted from whole genome sequences without a priori knowledge of mechanisms, and that both genomic and epidemiological data are informative. This paves way to integrating machine learning approaches into diagnostic tools in the clinic.\n\nSummaryOne of the major health threats of 21st century is emergence of antibiotic resistance. To manage its economic impact, efforts are made to develop novel diagnostic tools that rapidly detect resistant strains in clinical settings. In our study, we employed a range machine learning tools to predict antibiotic resistance from whole genome sequencing data for E. coli. We used the presence or absence of genes, population structure and isolation year of isolates as predictors, and could attain average precision of 0.93 and recall of 0.83, without prior knowledge about the causal mechanisms. These results demonstrate the potential application of machine learning methods as a diagnostic tool in healthcare settings.

bioinformatics↗

bioRxiv2018

JACKS: joint analysis of CRISPR/Cas9 knock-out screens

Genome-wide CRISPR/Cas9 knockout screens are revolutionizing mammalian functional genomics. Their range of applications remains limited by signal variability from different guide RNAs targeting the same gene, which confounds analysis, and dictates large experiment sizes. To address this problem, we report JACKS, a Bayesian method that jointly analyses screens performed with the same guide RNA library. Modeling the variable guide efficacies greatly improves hit identification, and allows a 2.5-fold reduction in required cell numbers without sacrificing performance compared to current analysis standards.

genomics↗

bioRxiv2017

Binding of the integrated stress response inhibitor, ISRIB, reveals a regulatory site in the nucleotide exchange factor, eIF2B

The Integrated Stress Response (ISR) is a conserved eukaryotic translational and transcriptional program implicated in mammalian metabolism, memory and immunity. The ISR is mediated by stress-induced phosphorylation of translation initiation factor 2 (eIF2) that attenuates the guanine nucleotide exchange factor eIF2B. A chemical inhibitor of the ISR, ISRIB, a bis-O-arylglycolamide, reverses the attenuation of eIF2B by phosphorylated eIF2, protecting mice from neurodegeneration and traumatic brain injury. We report on a cryo-electron microscopy-based structure of ISRIB-bound human eIF2B revealing an ISRIB-binding pocket at the interface between the {beta} and {delta} regulatory subunits. CRISPR/Cas9 mutagenesis of residues lining this pocket altered the hierarchical cellular response to ISRIB congeners in vivo and ISRIB-binding in vitro, thus providing chemogenetic support for the functional relevance of ISRIB binding at a distance from known eIF2-eIF2B interaction sites. Our findings point to a hitherto unexpected allosteric site in the eIF2B decamer exploited by ISRIB to regulate translation.

molecular biology↗