Biology subjects

Cao, Y.

Publications and source records attributed to Cao, Y..

At least 343 records · Page 19Linked to original sources

bioRxiv2020

Single-cell analysis of upper airway cells reveals host-viral dynamics in influenza infected adults

Influenza virus infections are major causes of morbidity and mortality. Research using cultured cells, bulk tissue, and animal models cannot fully capture human disease dynamics. Many aspects of virus-host interactions in a natural setting remain unclear, including the specific cell types that are infected and how they and neighboring bystander cells contribute to the overall antiviral response. To address these questions, we performed single-cell RNA sequencing (scRNA-Seq) on cells from freshly collected nasal washes from healthy human donors and donors diagnosed with acute influenza during the 2017-18 season. We describe a previously uncharacterized goblet cell population, specific to infected individuals, with high expression of MHC class II genes. Furthermore, leveraging scRNA-Seq reads, we obtained deep viral genome coverage and developed a model to rigorously identify infected cells that detected influenza infection in all epithelial cell types and even some immune cells. Our data revealed that each donor was infected by a unique influenza variant and that each variant was separated by at least one unique non-synonymous difference. Our results demonstrate the power of massively-parallel scRNA-Seq to study viral variation, as well as host and viral transcriptional activity during human infection.

genomics↗

bioRxiv2020

Identification of 38 novel loci for systemic lupus erythematosus and genetic heterogeneity that may underly population disparities in this disease

Systemic lupus erythematosus (SLE), a worldwide autoimmune disease with high heritability, shows differences in prevalence, severity and age of onset among different ancestral groups. Previous genetic studies have focused more on European populations, which appear to be the least affected. Consequently, the genetic variations that underly the commonalities, differences and treatment options in SLE among ancestral groups have not been well elucidated. To address this, we undertook a genome-wide association study, increasing the sample size of Chinese populations to the level of existing European studies. Thirty-eight novel SLE-associated loci and incomplete sharing of genetic architecture were identified. Nine disease loci showed clear ancestral group heterogeneity and implicated antibody production as a potential mechanism for differences in disease manifestation. Polygenic risk scores performed significantly better when trained on matched ancestral data sets. These analyses help to reveal the genetic bases for disparities in SLE among ancestral groups.

genetics↗

bioRxiv2020

KMT2D Links TGF-β Signalling to Non-Canonical Activin Pathway and Regulates Pancreatic Cancer Cell Plasticity

Although KMT2D, also known as MLL2, is known to play an essential role in development, differentiation, and tumor suppression, its role in pancreatic cancer development is not well understood. Here, we discovered a novel signaling axis mediated by KMT2D, which links TGF-{beta} to the activin A pathway. We found that TGF-{beta} upregulates a microRNA, miR-147b, which in turn leads to post-transcriptional silencing of KMT2D. Loss of KMT2D induces the expression and secretion of activin A, which activates a non-canonical p38 MAPK-mediated pathway to modulate cancer cell plasticity, promote a mesenchymal phenotype, and enhance tumor invasion and metastasis in mice. We observed a decreased KMT2D expression in human primary and metastatic pancreatic cancer. Furthermore, inhibition or knockdown of activin A reversed the pro-tumoral role of KMT2D. These findings reveal a tumor-suppressive role of KMT2D and identify miR-147b and activin A as novel therapeutic targets in pancreatic cancer.

cancer biology↗

bioRxiv2020

Genome-wide targets identification by CRISPRi-Omics for high-titer production of free fatty acids in Escherichia coli

To construct a superior microbial cell factory for chemical synthesis, a major challenge is to fully exploit cell potential via identifying and engineering beneficial gene targets in the sophisticated metabolic networks. Here, we develop an approach that integrates CRISPR interference (CRISPRi) to readily modulate genes expression and omics analyses to identify potential targets in multiple cellular processes, enabling systematical discovery of beneficial chromosomal gene targets that can be engineered to optimize free fatty acids (FFAs) production in Escherichia coli. We identify 56 beneficial genes via synergistic CRISPRi-Omics strategy, including 46 novel targets functioning in cell structure and division, and signaling transduction that efficiently facilitate FFAs production. Upon repressing ihfA and overexpressing aidB and tesA in E. coli, the recombinant strain LihfA-OaidB results in a FFAs titer of 21.6 g L-1 in fed-batch fermentation, which, to our best knowledge, is the maximum FFAs titer by the recombinant E. coli reported to date.

biochemistry↗

bioRxiv2020

Novel hemorrhage models of cerebral cavernous malformations

Cerebral cavernous malformations (CCMs) are ectatic capillary-venous malformations that develop in approximately 0.5% of the population. Patients with CCMs may develop headaches, focal neurologic deficits, seizures, and hemorrhages. While symptomatic CCMs, depending upon the anatomic location, can be surgically removed, there is currently no pharmaceutical therapy to treat CCMs. Several mouse models have been developed to better understand CCM pathogenesis and test therapeutics. The most common mouse models induce a large CCM burden that is anatomically restricted to the cerebellum and contributes to lethality in the early days of life. These inducible models thus have a relatively short period for drug administration. We developed an inducible CCM3 mouse model that develops CCMs after weaning and provides a longer period for potential therapeutic intervention. Using this new model, three recently proposed CCM therapies - fasudil, tempol, vitamin D3, and a combination of the three drugs failed to substantially reduce CCM formation when treatment was administered for five weeks, from postnatal day 21 (P21) to P56. We next restricted Ccm3 deletion to the brain vasculature and provided greater time (121 days) for CCMs to develop chronic hemorrhage, recapitulating the human lesions. We also developed the first model of acute CCM hemorrhage by injecting mice harboring CCMs with lipopolysaccharide. These efficient models will enable future drug studies to more precisely target clinically relevant features of CCM disease: CCM formation, chronic hemorrhage, and acute hemorrhage.

genetics↗

bioRxiv2020

Suppression of canonical TGF-β signaling enables GATA4 to interact with H3K27me3 demethylase JMJD3 to promote cardiomyogenesis

Direct reprogramming of fibroblasts into cardiomyocytes (CMs) represents a promising strategy to regenerate CMs lost after ischemic heart injury. Overexpression of GATA4, HAND2, MEF2C, TBX5, miR-1, and miR-133 (GHMT2m) along with transforming growth factor beta (TGF-{beta}) inhibition efficiently promotes reprogramming. However, the mechanisms by which TGF-{beta} blockade promotes cardiac reprogramming remain unknown. Here, we identify interactions between the histone H3 lysine 27 trimethylation (H3K27me3) - demethylase JMJD3, the SWI/SNF remodeling complex subunit BRG1, and cardiac transcription factors. Furthermore, canonical TGF-{beta} signaling regulates the interaction between GATA4 and JMJD3. TGF-{beta} activation impairs the ability of GATA4 to bind target genes and prevents demethylation of H3K27 at cardiac gene promoters during cardiac reprogramming. Finally, a mutation in GATA4 (V267M) exhibits reduced binding to JMJD3 and impaired cardiomyogenesis. Thus, we have identified an epigenetic mechanism wherein canonical TGF-{beta} pathway activation impairs cardiac gene programming by interfering with GATA4-JMJD3 interactions.

cell biology↗

bioRxiv2020

Maturation of human induced pluripotent stem cell-derived cardiomyocytes for modeling hypertrophic cardiomyopathy

RationaleHuman induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs) are a powerful platform for biomedical research. However, they are immature, which is a barrier to modeling adult-onset cardiovascular disease. ObjectiveWe sought to develop a simple method which could drive cultured hiPSC-CMs towards maturity across a number of phenotypes. Methods and resultsCells were cultured in fatty acid-based media and plated on micropatterned surfaces to promote alignment and elongation. These cells display many characteristics of adult human cardiomyocytes, including elongated cell morphology, enhanced maturity of sarcomeric structures, metabolic behavior, and increased myofibril contractile force. Most notably, hiPSC-CMs cultured under optimal maturity-inducing conditions recapitulate the pathological hypertrophy caused by either a pro-hypertrophic agent or genetic mutations. ConclusionsThe more mature hiPSC-CMs produced by the methods described here will serve as a useful in vitro platform for characterizing cardiovascular disease.

cell biology↗

bioRxiv2019

Detection of genome-wide low-frequency mutations with Paired-End and Complementary Consensus Sequencing (PECC-Seq) revealed end-repair derived artifacts as residual errors

To improve the accuracy and the cost-efficiency of next-generation sequencing in ultralow-frequency mutation detection, we developed the Paired-End and Complementary Consensus Sequencing (PECC-Seq), a PCR-free duplex consensus sequencing approach. PECC-Seq employed shear points as endogenous barcodes to identify consensus sequences from the overlap in the shortened, complementary DNA strands-derived paired-end reads for sequencing error correction. With the high accuracy of PECC-Seq, we identified the characteristic base substitution errors introduced by the end-repair process of mechanical fragmentation-based library preparations, which were prominent at the terminal 6 bp of the library fragments in the 5-NpCpA-3 or 5-NpCpT-3 trinucleotide context. As demonstrated at the human genome scale (TK6 cells), after removing these potential end-repair artifacts from the terminal 6 bp, PECC-Seq could reduce the sequencing error frequency to mid-10-7 with a relatively low sequencing depth. For TA base pairs, the background error rate could be suppressed to mid-10-8. In mutagen-treated TK6, slight increases in mutagen treatment-related mutant frequencies could be detected, indicating the potential of PECC-Seq in detecting genome-wide ultra-rare mutations. In addition, our finding on the patterns of end-repair artifacts may provide new insights in further reducing technical errors not only for PECC-Seq, but also for other next-generation sequencing techniques.

genomics↗

bioRxiv2019

SCSA: a cell type annotation tool for single-cell RNA-seq data

Currently most methods take manual strategies to annotate cell types after clustering the single-cell RNA sequencing (scRNA-seq) data. Such methods are labor-intensive and heavily rely on user expertise, which may lead to inconsistent results. We present SCSA, an automatic tool to annotate cell types from scRNA-seq data, based on a score annotation model combining differentially expressed genes (DEGs) and confidence levels of cell markers from both known and user-defined information. Evaluation on real scRNA-seq datasets from different sources with other methods shows that SCSA is able to assign the cells into the correct types at a fully automated mode with a desirable precision.

bioinformatics↗

bioRxiv2019

Niacin Stimulates Mammary Gland Development in Pubertal Mice through Activation of the AKT/mTOR and ERK1/2 Signaling Pathways

Previous studies have shown the effects of vitamins on the development of the mammary gland. However, the role of niacin in this process has not been reported. Therefore, the aim of this study was to investigate the effects of niacin on mammary gland development in pubertal mice and to use a mouse mammary epithelial cell line to study the underlying mechanism. The results showed that niacin could activate the AKT/mTOR and ERK signaling pathways by the Gi protein-coupled receptor and increase phosphorylation of 4EBP1 to promote the synthesis of cell proliferation markers, leading to the dissociation of the Rb-E2F1 complex in mMECs. In addition, 0.5% niacin promoted mammary duct development, increased the expression of cyclin D1/D3 and PCNA, and activated Akt/mTOR and ERK1/2 in the mammary glands of pubertal mice. These results strongly suggest that niacin stimulates mammary gland development in pubertal mice through the Akt/mTOR and ERK1/2 signaling pathways and that the Gi protein-coupled receptor is essential for this function.

developmental biology↗

bioRxiv2019

Energy-based Graph Convolutional Networks for Scoring Protein Docking Models

Structural information about protein-protein interactions, often missing at the interactome scale, is important for mechanistic understanding of cells and rational discovery of therapeutics. Protein docking provides a computational alternative to predict such information. However, ranking near-native docked models high among a large number of candidates, often known as the scoring problem, remains a critical challenge. Moreover, estimating model quality, also known as the quality assessment problem, is rarely addressed in protein docking. In this study the two challenging problems in protein docking are regarded as relative and absolute scoring, respectively, and addressed in one physics-inspired deep learning framework. We represent proteins and encounter complexes as intra- and inter-molecular residue contact graphs with atom-resolution node and edge features. And we propose a novel graph convolutional kernel that pool interacting nodes features through edge features so that generalized interaction energies can be learned directly from graph data. The resulting energy-based graph convolutional networks (EGCN) with multi-head attention are trained to predict intra- and inter-molecular energies, binding affinities, and quality measures (interface RMSD) for encounter complexes. Compared to a state-of-the-art scoring function for model ranking, EGCN has significantly improved ranking for a CAPRI test set involving homology docking; and is comparable for Score_set, a CAPRI benchmark set generated by diverse community-wide docking protocols not known to training data. For Score_set quality assessment, EGCN shows about 27% improvement to our previous efforts. Directly learning from structure data in graph representation, EGCN represents the first successful development of graph convolutional networks for protein docking.

bioinformatics↗

bioRxiv2019

Abnormal nitration and S-sulfhydration of Sp1-CSE-H2S pathway contribute to the progress of HHcy

Sp1 (Specificity protein 1)-CSE (cystathionine-{gamma}-lyase)-H2S (hydrogen sulfide) pathway plays an important role in homocysteine-metabolism, whose disorder can result in hyperhomocysteinemia. The deficiency of plasma H2S in patients and animal models with hyperhomocysteinemia has been reported but it is unclear whether this deficiency plays a role in the progress of hyperhomocysteinemia. Furthermore, it remains unknown whether the post-translational modification of Sp1 or CSE mediated by hyperhomocysteinemia itself can in turn affect the development of hyperhomocysteinemia. By both in vivo and in vitro studies, we conducted immunoprecipitation and maleimide assays to detect the post-translational modification of Sp1-CSE-H2S pathway and revealed four major findings: (1) the accumulation of homocysteine augmented the nitration of CSE, thus blunted its bio-activity and caused H2S deficiency. (2) H2S deficiency lowered the S-sulfhydration of Sp1 and inhibited its transcriptional activity, resulted in lower expression of CSE. CSE deficiency decreased the H2S level further, which in turn lowered the S-sulfhydration level of CSE. (3) CSE was S-sulfhydrated at Cys84, Cys109, Cys172, Cys229, Cys252, Cys307 and Cys310 under physiological conditions, mutation of Cys84, Cys109, Cys229, Cys252 and Cys307 decreased its S-sulfhydration level and bio-activity. (4) H2S deficiency could trap hyperhomocysteinemia into a progressive vicious circle and trigger a rapid increase of homocysteine, while blocking nitration or restoring S-sulfhydration could break this circle. In conclusion, this study reveals a novel mechanism involved in the disorder of homocysteine-metabolism, which may provide a candidate therapeutic strategy for hyperhomocysteinemia.

pathology↗

bioRxiv2019

Yersinia canariae sp. nov., isolated from a human yersiniosis case

A Gram-negative rod from the Yersinia genus was isolated from a clinical case of yersiniosis in the United Kingdom. Long read sequencing data from an Oxford Nanopore Technology (ONT) MinION in conjunction with Illumina HiSeq reads were used to generate a finished quality genome of this strain. Overall Genome Related Index (OGRI) of the strain was used to determine that it was a novel species within Yersinia, despite biochemical similarities to Yersinia enterocolitica. The 16S ribosomal RNA gene accessions are MN434982-MN434987 and the accession number for the complete and closed chromosome is CP043727. The type strain is CFS3336T (=NCTC 14382T/ =LMG Accession under process).

microbiology↗

bioRxiv2019

scClassify: hierarchical classification of cells

Cell type identification is a key computational challenge in single-cell RNA-sequencing (scRNA-seq) data. To capitalize on the large collections of well-annotated scRNA-seq datasets, we present scClassify, a hierarchical classification framework based on ensemble learning. scClassify can identify cells from published scRNA-seq datasets more accurately and more finely than in the original publications. We also estimate the cell number needed for accurate classification anywhere in a cell type hierarchy.

bioinformatics↗

bioRxiv2019

De Novo Protein Design for Novel Folds using Guided Conditional Wasserstein Generative Adversarial Networks (gcWGAN)

MotivationFacing data quickly accumulating on protein sequence and structure, this study is addressing the following question: to what extent could current data alone reveal deep insights into the sequence-structure relationship, such that new sequences can be designed accordingly for novel structure folds?\n\nResultsWe have developed novel deep generative models, constructed low-dimensional and generalizable representation of fold space, exploited sequence data with and without paired structures, and developed ultra-fast fold predictor as an oracle providing feedback. The resulting semi-supervised gcWGAN is assessed with the oracle over 100 novel folds not in the training set and found to generate more yields and cover 3.6 times more target folds compared to a competing data-driven method (cVAE). Assessed with structure predictor over representative novel folds (including one not even part of basis folds), gcWGAN designs are found to have comparable or better fold accuracy yet much more sequence diversity and novelty than cVAE. gcWGAN explores uncharted sequence space to design proteins by learning from current sequence-structure data. The ultra fast data-driven model can be a powerful addition to principle-driven design methods through generating seed designs or tailoring sequence space.\n\nAvailabilityData and source codes will be available upon request.\n\nContactyshen@tamu.edu\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2019

ADNP promotes neural differentiation by modulating Wnt/β-catenin signaling

ADNP (Activity Dependent Neuroprotective Protein) is proposed as a neuroprotective protein whose aberrant expression has been frequently linked to neural developmental disorders, including the Helsmoortel-Van der Aa syndrome. However, its role in neural development and pathology remains unclear. Using mESC (mouse embryonic stem cell) directional neural differentiation as a model, we show that ADNP is required for ESC neural induction and neuronal differentiation by maintaining Wnt signaling. Mechanistically, ADNP functions to maintain the proper protein levels of {beta}-Catenin through binding to its armadillo domain which prevents its association with key components of the degradation complex: Axin and APC. Loss of ADNP promotes the formation of the degradation complex and hyperphosphorylation of {beta}-Catenin by GSK3{beta} and subsequent degradation via ubiquitin-proteasome pathway, resulting in down-regulation of key neuroectoderm developmental genes. We further show that ADNP plays key role in cerebellar neuron formation. Finally, adnp gene disruption in zebrafish embryos recapitulates key features of the mouse phenotype, including the reduced Wnt signaling, defective embryonic cerebral neuron formation and the massive neuron death. Thus, our work provides important insights into the role of ADNP in neural development and the pathology of the Helsmoortel-Van der Aa syndrome caused by ADNP gene mutation.

developmental biology↗

bioRxiv2019

A Hybrid Stochastic Model of the Budding Yeast Cell Cycle

The growth and division of eukaryotic cells are regulated by complex, multi-scale networks. In this process, the mechanism controlling cell cycle progression has to be robust against inherent noise in the system. In this paper, a hybrid stochastic model is developed to study the effects of noise on the control mechanism of the budding yeast cell cycle. The modeling approach leverages, in a single multi-scale model, the advantages of two regimes: 1) the computational efficiency of a deterministic approach, and 2) the accuracy of stochastic simulations. Our results show that this hybrid stochastic model achieves high computational efficiency while generating simulation results that match very well with published experimental measurements.

systems biology↗

bioRxiv2019

Prenatal Diagnosis of Fetuses with Increased Nuchal Translucency by Genome Sequencing Analysis

BackgroundIncreased Nuchal Translucency (NT) is an important biomarker associated with increased risk of fetal structural anomalies. It is known to be contributed by a wide range of genetic etiologies from single nucleotide variants to those affecting millions of base-pairs. Currently, prenatal diagnosis is routinely performed by karyotyping and chromosomal microarray analysis (CMA), however, both of them have limited resolution. The diversity of the genetic etiologies warrants an integrated assay such as genome sequencing (GS) for comprehensive detection of genomic variants. Herein, we aim to evaluate the feasibility of applying GS in prenatal diagnosis for the fetuses with increased NT.\n\nMethodsWe retrospectively applied GS (>30-fold) for fetuses with increased NT ([≥]3.5-mm), who underwent routine prenatal diagnosis. Detection of single-nucleotide variants, copy-number variants and structural rearrangements was performed simultaneously and the results were integrated for interpretation in accordance with the guidelines of the American College of Medical Genetics and Genomics. Pathogenic or likely pathogenic (P/LP) variants were selected for validation and parental confirmation, when available.\n\nResultsOverall, 50 fetuses were enrolled, including 34 cases with isolated increased NT and 16 cases with other fetal structural malformations. Routine CMA and karyotyping reported eight P/LP CNVs, yielding a diagnostic rate of 16.0% (8/50). In comparison, GS provided a 2-fold increase in diagnostic yield (32.0%, 16/50), including one mosaic turner syndrome, eight cases with microdeletions/microduplications and seven cases with P/LP point mutations. Moreover, GS identified two cryptic insertions and two inversions. Follow-up study further demonstrated the potential pathogenicity of an apparently balanced insertion which disrupted an OMIM autosomal dominant disease-causing gene at the inserted site.\n\nConclusionsOur study demonstrates that applying GS in fetuses with increased NT can comprehensively detect and delineate the various genomic variants that are causative to the diseases. Importantly, prenatal diagnosis by GS doubled the diagnostic yield compared with routine protocols. Given a comparable turn-around-time and less DNA required, our study provides strong evidence to facilitate GS in prenatal diagnosis, particularly in fetuses with increased NT.

genomics↗