Biology subjects

Chen, V.

Publications and source records attributed to Chen, V..

25 records · Page 2Linked to original sources

bioRxiv2020

RecT recombinase expression enables efficient gene editing in Enterococcus

Enterococcus faecium is a ubiquitous Gram-positive bacterium that has been recovered from the environment, food, and microbiota of mammals. Commensal strains of E. faecium can confer beneficial effects on host physiology and immunity, but antibiotic usage has afforded antibiotic-resistant and pathogenic isolates from livestock and humans. However, the dissection of E. faecium functions and mechanisms has been restricted by inefficient gene editing methods. To address these limitations, here we report the expression of E. faecium RecT recombinase significantly improves the efficiency of recombineering technologies in both commensal and antibiotic-resistant strains of E. faecium and other Enterococcus species such as E. durans and E. hirae. Notably, the expression of RecT in combination with clustered regularly interspaced palindromic repeat (CRISPR)-Cas9 and guide RNAs (gRNAs) enabled highly efficient scar-less single-stranded DNA recombineering to generate specific gene editing mutants in E. faecium. Moreover, we demonstrate that E. faecium RecT expression facilitated chromosomal insertions of double-stranded DNA templates encoding antibiotic selectable markers to generate gene deletion mutants. As further proof-of-principle, we use CRISPR-Cas9 mediated recombineering to knock out both sortase A genes in E. faecium for downstream functional characterization. The general RecT-mediated recombineering methods described here should significantly enhance genetic studies of E. faecium and other closely related species for functional and mechanistic studies. ImportanceEnterococcus faecium is widely recognized as an emerging public health threat with the rise of drug resistance and nosocomial infections. Nevertheless, commensal Enterococcus strains possess beneficial health functions in mammals to upregulate host immunity and prevent microbial infections. This functional dichotomy of Enterococcus species and strains highlights the need for in-depth studies to discover and characterize the genetic components underlining its diverse activities. However, current genetic engineering methods in E. faecium still require passive homologous recombination from plasmid DNA. This involves the successful cloning of multiple homologous fragments into a plasmid, introducing the plasmid into E. faecium, and screening for double-crossover events that can collectively take up to multiple weeks to perform. To alleviate these challenges, we show that RecT recombinase enables rapid and efficient integration of mutagenic DNA templates to generate substitutions, deletions, and insertions in genomic DNA of E. faecium. These improved recombineering methods should facilitate functional and mechanistic studies of Enterococcus.

microbiology↗

bioRxiv2020

Membrane Orientation and Oligomerization of the Melanocortin Receptor Accessory Protein 2

The melanocortin receptor accessory protein 2 (MRAP2) plays a pivotal role in the regulation of several G-protein coupled receptors (GPCR) that are essential for energy balance and food intake. MRAP2 loss-of-function results in obesity in mammals. MRAP2 and its homolog MRAP1 have an unusual membrane topology and are the only known eukaryotic proteins that thread into the membrane in both orientations. In this study, we demonstrate that the conserved polybasic motif that dictates the membrane topology and dimerization of MRAP1 does not control the membrane orientation and dimerization of MRAP2. We also show that MRAP2 dimerizes through its transmembrane domain and can form higher order oligomers that arrange MRAP2 monomers in a parallel orientation. Investigating the molecular details of MRAP2 structure is essential for understanding the mechanism by which it regulates GPCRs and will aid in elucidating the pathways involved in metabolic dysfunction.

biochemistry↗

bioRxiv2020

Massively parallel functional testing of MSH2 missense variants conferring Lynch Syndrome risk

The lack of functional evidence for the majority of missense variants limits their clinical interpretability, and poses a key barrier to the broad utility of carrier screening. In Lynch Syndrome (LS), one of the most highly prevalent cancer syndromes, nearly 90% of clinically observed missense variants are deemed "variants of uncertain significance" (VUS). To systematically resolve their functional status, we performed a massively parallel screen in human cells to identify loss-of-function missense variants in the key DNA mismatch repair factor MSH2. The resulting functional effect map is substantially complete, covering 94% of the 17,746 possible variants, and is highly concordant (96%) with existing functional data and expert clinicians interpretations. The large majority (89%) of missense variants were functionally neutral, perhaps unexpectedly in light of its evolutionary conservation. These data provide ready-to-use functional evidence to resolve the [~]1,300 extant missense VUSs in MSH2, and may facilitate the prospective classification of newly discovered variants in the clinic.

genetics↗

bioRxiv2020

A Comprehensive Multi-Center Cross-platform Benchmarking Study of Single-cell RNA Sequencing Using Reference Samples

Single-cell RNA sequencing (scRNA-seq) has become a very powerful technology for biomedical research and is becoming much more affordable as methods continue to evolve, but it is unknown how reproducible different platforms are using different bioinformatics pipelines, particularly the recently developed scRNA-seq batch correction algorithms. We carried out a comprehensive multi-center cross-platform comparison on different scRNA-seq platforms using standard reference samples. We compared six pre-processing pipelines, seven bioinformatics normalization procedures, and seven batch effect correction methods including CCA, MNN, Scanorama, BBKNN, Harmony, limma and ComBat to evaluate the performance and reproducibility of 20 scRNA-seq data sets derived from four different platforms and centers. We benchmarked scRNA-seq performance across different platforms and testing sites using global gene expression profiles as well as some cell-type specific marker genes. We showed that there were large batch effects; and the reproducibility of scRNA-seq across platforms was dictated both by the expression level of genes selected and the batch correction methods used. We found that CCA, MNN, and BBKNN all corrected the batch variations fairly well for the scRNA-seq data derived from biologically similar samples across platforms/sites. However, for the scRNA-seq data derived from or consisting of biologically distinct samples, limma and ComBat failed to correct batch effects, whereas CCA over-corrected the batch effect and misclassified the cell types and samples. In contrast, MNN, Harmony and BBKNN separated biologically different samples/cell types into correspondingly distinct dimensional subspaces; however, consistent with this algorithms logic, MNN required that the samples evaluated each contain a shared portion of highly similar cells. In summary, we found a great cross-platform consistency in separating two distinct samples when an appropriate batch correction method was used. We hope this large cross-platform/site scRNA-seq data set will provide a valuable resource, and that our findings will offer useful advice for the single-cell sequencing community.

genomics↗

bioRxiv2019

SWI/SNF component BAF250a coordinates OCT4 and WNT signaling pathway to control cardiac lineage differentiation

Dissecting epigenetic mechanisms controlling early cardiac differentiation will provide insights into heart regeneration and heart disease treatment. SWI/SNF complexes remodel nucleosomes to regulate gene expression and play a key role in organogenesis. Here we reported a unique function of BAF250a in regulating the physical interaction of OCT4 and {beta}-CATENIN during cardiac lineage differentiation from human ESCs. BAF250a deletion greatly reduced the physical interaction between OCT4 and {beta}-CATENIN but did not alter the expression of {beta}-CATENIN and OCT4 in the mesodermal progenitor cells. BAF250a ablation led to decreased recruitment of OCT4 and {beta}-CATENIN at promoters of key mesodermal lineage genes, such as MESP1 and EOMES. Subsequently, the expression of lineage specific genes was down-regulated whereas the expression of pluripotent genes was up-regulated. In parallel, BAF250a ablation also altered recruitments of OCT4 and {beta}-CATENIN to the promoter of CCND2 and CCND3, two key genes for S phase entry during cell cycle. Consequently, BAF250a deletion led to prolonged S phase in Mesp1+ cardiac progenitor cells, which in turn inhibited efficient differentiation of Mesp1+ to Isl1+ cells. Furthermore, BAF250a deletion abolished the interaction of OCT4 and BRG1 in mesoderm, suggesting that BAF250a is the key component in SWI/SNF complex that determines the interaction of Oct4/{beta}-catenin in mesoderm. In contrast, we found that BAF250a did not regulate the OCT4/{beta}-CATENIN interaction during neuroectoderm differentiation. Altogether, our results suggest that BAF250a specifically controls proper cardiac mesoderm differentiation by reorganizing the binding of OCT4/{beta}-CATENIN and regulates both key lineage differentiation genes and cell cycle genes coincided in response to WNT/{beta}-CATENIN signal.\n\nHighlightsBAF250a is required for hESC cardiac differentiation\n\nBAF250a is required for the assembly of Brg1/OCT4/{beta}-CATENIN complex and the recruitment of OCT4/{beta}-CATENIN to cardiac genes\n\nBAF250a is dispensable for the interaction of OCT4/{beta}-CATENIN interaction in neuroectoderm differentiation\n\nBAF250a interacts with OCT4/{beta}-CATENIN to promote cardiac differentiation by regulating cell cycle.

developmental biology↗

bioRxiv2018

Weakly supervised classification of rare aortic valve malformations using unlabeled cardiac MRI sequences

Biomedical repositories such as the UK Biobank provide increasing access to prospectively collected cardiac imaging, however these data are unlabeled which creates barriers to their use in supervised machine learning. We develop a weakly supervised deep learning model for classification of aortic valve malformations using up to 4,000 unlabeled cardiac MRI sequences. Instead of requiring highly curated training data, weak supervision relies on noisy heuristics defined by domain experts to programmatically generate large-scale, imperfect training labels. For aortic valve classification, models trained with imperfect labels substantially outperform a supervised model trained on hand-labeled MRIs. In an orthogonal validation experiment using health outcomes data, our model identifies individuals with a 1.8-fold increase in risk of a major adverse cardiac event. This work formalizes a learning baseline for aortic valve classification and outlines a general strategy for using weak supervision to train machine learning models using unlabeled medical images at scale.

bioinformatics↗

bioRxiv2018

Systematic Discovery of the Functional Impact of Somatic Genome Alterations in Individual Tumors through Tumor-specific Causal Inference

We report a tumor-specific causal inference (TCI) framework, which discovers causative somatic genome alterations (SGAs) through inferring causal relationships between SGAs and molecular phenotypes (e.g., transcriptomic, proteomic, or metabolomic changes) within an individual tumor. We applied the TCI algorithm to tumors from The Cancer Genome Atlas (TCGA) and identified those SGAs that causally regulate the differentially expressed genes (DEGs) within each tumor. Overall, TCI identified 634 SGAs that cause cancer-related DEGs in a significant number of tumors, including most of the previously known drivers and many novel candidate cancer drivers. The inferred causal relationships are statistically robust and biologically sensible, and multiple lines of experimental evidence support the predicted functional impact of both well-known and novel candidate drivers. By identifying major candidate drivers and revealing their functional impact in a tumor, TCI shed light on disease mechanisms of each tumor, providing useful information for advancing cancer biology and precision oncology.\n\nSignificance statementsCancer is mainly caused by SGAs. Precision oncology involves identifying and targeting tumor-specific aberrations resulting from causative SGAs. TCI is a novel computational framework for discovering the causative SGAs and their impact on oncogenic processes, thus revealing tumor-specific disease mechanisms. This information can be used to guide precision oncology.

cancer biology↗