Biology subjects

Liang, S.

Publications and source records attributed to Liang, S..

At least 109 records · Page 6Linked to original sources

bioRxiv2022

Proteomic Dynamics of Breast Cancers Identifies Potential Therapeutic Protein Targets

Treatment and relevant targets for breast cancer (BC) remain limited, especially for triple-negative BC (TNBC). We quantified the proteomes of 76 human BC cell lines using data independent acquisition (DIA) based proteomics, identifying 6091 proteins. We then established a 24-protein panel distinguishing TNBC from other BC types. Integrating prior multi-omics datasets with the present proteomic results to predict the sensitivity of 90 drugs, we found that proteomics data improved drug sensitivity predictions. The sensitivity of the 90 drugs was mainly associated with cell cytoskeleton, signal transduction and mitochondrial function. We next profiled the proteome changes of nine cell lines (five TNBC cell lines, four non-TNBC cell lines) perturbated by EGFR/AKT/mTOR inhibitors. In the TNBC cell lines, metabolism pathways were dysregulated after EGFR/mTOR inhibitors treatment, while RNA modification and cell cycle pathways were dysregulated after AKT inhibitor treatment. Our study presents a systematic multi-omics and in-depth analysis of the proteome of BC cells. This work aims to aid in prioritization of potential therapeutic targets for TNBC as well as to provide insight into adaptive drug resistance in TNBC.

systems biology↗

bioRxiv2022

Characterizing transition cells in developmental processes from scRNA-seq data

Multi-cellular organism development involves orchestrated gene regulations of different cell types and cell states. Single-cell RNA-Seq, enable simultaneous observation of cells in various states, making it possible to study the underlying molecular mechanisms. However, most of the analytical methods do not make full use of the dynamics captured. Here, we model single-cell RNA-seq data obtained from a developmental process as a function of gene regulatory network using stochastic differential equations (SDEs). Based on dynamical systems theory, we showed that pair-wise gene expression correlation coefficients can accurately infer cell state transitions and validated it using mouse muscle cell regeneration scRNA-seq data. We then applied our analytical framework to the PDAC (Pancreatic ductal adenocarcinoma) mouse model scRNA-seq data. Through transition cells found in the pancreatic preinvasive lesions scRNA-seq data, we can better explain the heterogeneity and predict distinct cell fate even at early tumorigenesis stage. This suggests that the biomarkers identified by transition cells can be potentially used for diagnosis, prognosis and therapeutics of diseases.

bioinformatics↗

bioRxiv2022

Multi-omics analyses of drug repurposing reveal Acebutolol and Amiloride for osteoporosis treatment

Osteoporosis is a metabolic bone disease that occurs during aging, characterized by low bone mineral density (BMD) and a high risk of trauma fracture. While current pharmacological interventions provide symptomatic benefits, they are unsatisfactory and have major side effects. In this study, we used multi-omics data and drug similarity to construct osteoporosis driver signaling networks (ODSN) and drug functional networks (DFN), respectively. By integrating ODSN and DFN with treatment transcriptional responses, we observed 8 drugs that demonstrated strong targeting effects on ODSN. Mendelian Randomization analysis determines the causal effect on BMD using cis-eQTLs of the drug targets and BMD GWAS data. The findings suggested Acebutolol and Amiloride may increase BMD, while Acenocoumarol, Aminocaproic acid and Armodafinil may enhance bone loss. Zebrafish experiments experimentally showed Acebutolol hydrochloride and Amiloride hydrochloride had significant protective effects on osteoporosis in zebrafish embryos induced by Dexamethasone. Also, Acenocoumarol reduced bone mineralization compared with the control group. The findings suggest that the hypertension drugs Acebutolol and Amiloride warrant further investigation in functional mechanistic experiments to evaluate their effectiveness for osteoporosis treatments.

systems biology↗

bioRxiv2022

Gene mutations and molecular evolution of the chikungunya virus E1 and E2 from 2014 to 2019

Chikungunya virus (CHIKV), a mosquito-borne Alphavirus, is the etiological agent of chikungunya fever. To investigate the prevalence and genetic characteristics of CHIKV in China, we performed a molecular epidemiological study during the 2014-2019 period. Phylogenetic analysis of CHIKV in the 2014-2019 shows that it is currently clustered geographically, which means that CHIKVs local adaptability is gradually strengthening. Focusing on CHIKV adaptive mutation E1-A226V is not obvious in our study. The CHIKV E1 amino acid non-synonymous mutation results revealed the common mutation site M343I. Most mutation sites belong to the American epidemic strains, and the mutation rate is 2.8%. In 31 sequences, 19 non-synonymous mutations were found in CHIKV E1 (total mutation rate 20/499 = 4%), and 37 non-synonymous mutations in CHIKV E2 (total mutation rate 30/425 = 7%). It is worth noting that the mutation of CHIKV E2 has changed more than that of CHIKV E1 between 2014 and 2019. CHIKV E2 screened out common mutation sites, and the results showed that there are five common mutation sites, namely S119G, L182M, G206D, S300N, and A345T. Eighty-three percent of the CHIKV E2 receptor binding domain mutations in the American strains, namely T3I and N6H, may cause immune escape. We constructed a new luciferase immunosorbent assay using CHIKV E2 antigen and mutant E2 antigen to test the serum of the CHIKV infected patients, and the detected samples and dilution ratios were different. The T3I, N6H, S119G, L182M, G206D, S300N, and A345T mutations in CHIKV E2 could explain these differences between patients. IMPORTANCECHIKV originated in Africa more than 500 years ago, with a common lineage dividing into two distinct branches called West Africa (West African, WA) and East/Central/South Africa (East/Central/South African, ECSA). Moreover, the E1-A226V mutation enhanced the replication and transmission capacity of CHIKV in Aedes albopictus. However, it should be noted that E1-A226V does not explain the CHIKV epidemic that has occurred in the Americas in recent years. We analyzed CHIKV samples in the 2014-2019, and the results showed that the mutation of CHIKV E1 protein occurred was not mainly concentrated in E1-A226V, but concentrated in M343I. This also means that CHIKV constantly mutates in the natural environment and is formed under natural conditions. Analysis of the common mutation sites of CHIKV E2 showed that there were seven common mutation sites S119G/L182M/ G206D /S300N/A345T, and the new mutation of CHIKV E2 may affect serological antibody detection.

evolutionary biology↗

bioRxiv2022

Staphylococcus aureus nt5 gene contributes to bacterial infection ability to form kidney abscess

Staphylococcus aureus (S. aureus) is a commonly conditional infection pathogen, in which several key virulence genes are responsible for bacterial infection ability. The S. aureus nt5 gene, encoding 5-nucleotidase, mediates bacterial nucleic acid pathway, yet it is nearly unknown of nt5 function for staphylococcal infection ability. Herein we have constructed S. aureus mutant with the gene nt5C166T silence (S. aureus {Delta}nt5) by a CRISPR RNA-guided base editing system to investigate bacterial infection ability in vitro and in vivo. As expected, several nt5-related genes are disturbed in S. aureus {Delta}nt5, in which gene transcription level of py is decreased compared with the wild-type S. aureus. Bacterial gene nt5 is downregulated and py/adk are upregulated when S. aureus is exposed to antibiotics daptomycin, which indicates nt5-mediated nucleic acid pathway is interfered upon with daptomycin treatment. Furthermore, the mutant {Delta}nt5 displays about a 40-fold reduction of bacterial loading in mouse kidney on a mouse sepsis model, and the infection ability of {Delta}nt5 is reduced than the wild-type bacteria. The gene nt5 contributes to S. aureus-infected abscess formation in mouse kidney, and the silence of nt5 gene promotes phagocytosis of S. aureus by mouse and human immunocytes. In general, our findings reveal nt5 silence impedes bacterial loading in kidney to form abscess but enhances S. aureus to be phagocytosed by host cell immune system in vitro and in vivo, which indicates that nt5 gene plays an important role in bacterial infection and immune evasion.

immunology↗

bioRxiv2022

CMTR1 is recruited to transcription start sites and promotes ribosomal protein and histone gene expression in embryonic stem cells

CMTR1 (cap methyltransferase 1) catalyses methylation of the first transcribed nucleotide of RNAPII transcripts (N1 2-O-Me), creating part of the mammalian RNA cap structure. In addition to marking RNA as self, N1 2-O-Me has ill-defined roles in RNA expression and translation. Here we investigated the gene specificity of CMTR1 and its impact on RNA expression in embryonic stem cells. Using chromatin immunoprecipitation, CMTR1 was found to bind to transcription start sites (TSS) correlating with RNAPII levels, predominantly binding at histone genes and ribosomal protein (RP) genes. Repression of CMTR1 expression resulted in repression of RNAPII binding at the TSS and repression of RNA expression, particularly of histone and RP genes. In correlation with regulation of histones and RP genes, CMTR1 repression resulted in repression of translation and induction of DNA replication stress and damage. Indicating a direct role for CMTR1 in transcription, addition of recombinant CMTR1 to purified nuclei increased transcription of the histone and RP genes. CMTR1 was found to be upregulated during neural differentiation and there was an enhanced requirement for CMTR1 for gene expression and proliferation during this process. We highlight the distinct roles of the cap methyltransferases RNMT and CMTR1 in target gene expression and differentiation.

cell biology↗

bioRxiv2021

Construction of a potent pan-vaccine based on the evolutionary tendency of SARS-CoV-2 spike protein.

SARS-CoV-2 continued to spread globally along with different variants. Here, we systemically analyzed viral infectivity and immune-resistance of SARS-CoV-2 variants to explore the underlying rationale of viral mutagenesis. We found that the Beta variant harbors both high infectivity and strong immune resistance, while the Delta variant is the most infectious with only a mild immune-escape ability. Remarkably, the Omicron variant is even more immune-resistant than the Beta variant, but its infectivity increases only in Vero E6 cells implying a probable preference for the endocytic pathway. A comprehensive analysis revealed that SARS-CoV-2 spike protein evolved into distinct evolutionary paths of either high infectivity plus low immune resistance or low infectivity plus high immune resistance, resulting in a narrow spectrum of the current single-strain vaccine. In light of these findings and the phylogenetic analysis of 2674 SARS-CoV-2 S-protein sequences, we generated a consensus antigen (S6) taking the most frequent mutations as a pan-vaccine against heterogeneous variants. As compared to the ancestry SWT vaccine with significantly declined neutralizations to emerging variants, the S6 vaccine elicits broadly neutralizing antibodies and full protections to a wide range of variants. Our work highlights the importance and feasibility of a universal vaccine strategy to fight against antigen drift of SARS-CoV-2.

microbiology↗

bioRxiv2021

Increased Brain Volumetric Measurement Precision from Multi-Site 3D T1-weighted 3T Magnetic Resonance Imaging by Correcting Geometric Distortions

Magnetic resonance imaging (MRI) scanner-specific geometric distortions may contribute to scanner induced variability and decrease volumetric measurement precision for multi-site studies. The purpose of this study was to determine whether geometric distortion correction increases the precision of brain volumetric measurements in a multi-site multi-scanner study. Geometric distortion variation was quantified over a one-year period at 10 sites using the distortion fields estimated from monthly 3D T1-weighted MRI geometrical phantom scans. The variability of volume and distance measurements were quantified using synthetic volumes and a standard quantitative MRI (qMRI) phantom. The effects of geometric distortion corrections on MRI derived volumetric measurements of the human brain were assessed in two subjects scanned on each of the 10 MRI scanners and in 150 subjects with cerebrovascaular disease (CVD) acquired across imaging sites. Geometric distortions were found to vary substantially between different MRI scanners but were relatively stable on each scanner over a one-year interval. Geometric distortions varied spatially, increasing in severity with distance from the magnet isocenter. In measurements made with the qMRI phantom, the geometric distortion correction decreased the standard deviation of volumetric assessments by 35% and distance measurements by 42%. The average coefficient of variance decreased by 16% in gray matter and white matter volume estimates in the two subjects scanned on the 10 MRI scanners. Geometric distortion correction using an up-to-date correction field is recommended to increase precision in volumetric measurements made from MRI images.

bioengineering↗

bioRxiv2021

Reference genomes of 545 silkworms enable high-throughput exploring genotype-phenotype relationships

The silkworm Bombyx mori is a domestic insect for silk production and a lepidopteran model. The currently available genomes limit a full understanding of its genetic and phenotypic diversity. Here we assembled long-read genomes of 545 domestic and wild silkworms and constructed a high-resolution pan-genome dataset. We found that the silkworm population harbors extremely variable genomes containing 7,308 new gene families, 4,260 (22%) core gene families, and 3,432,266 non-redundant SVs. We deciphered a series of causal genes and variants associated with domestication, breeding, and ecological adaptation traits, and experimentally validated two of those genes using CRISPR-Cas9 or RNA interference. This unprecedented large-scale genomic resource allows for high-throughput screening of interesting traits for functional genomic research and breeding improvement of silkworms and may serve as a guideline for traits decoding in other species.

genomics↗

bioRxiv2021

Bmmp influences wing shape by regulating anterior-posterior and proximal-distal axis development

Insect wings are subject to strong selective pressure, resulting in the evolution of remarkably diverse wing shapes that largely determine flight capacity. However, the genetic basis and regulatory mechanisms underlying wing shape development are not well understood. The silkworm Bombyx mori micropterous (mp) mutant exhibits shortened wing length and enlarged vein spacings, albeit without changes in total wing area. Thus, the mp mutant comprises a valuable genetic resource for studying wing shape development. In this study, we used molecular mapping to identify the gene responsible for the mp phenotype and designated it Bmmp. Phenotype-causing mutations were identified as indels and single nucleotide polymorphisms in non-coding regions. These mutations resulted in decreased Bmmp mRNA levels and changes in transcript isoform composition. Bmmp null mutants were generated by CRISPR/Cas9 and exhibited significantly smaller wings. By examining the expression of genes critical to wing development in wildtype and Bmmp null mutants, we found that Bmmp exerts its function by coordinately modulating anterior-posterior and proximal-distal axis development. We also studied a Drosophila mp mutant and found that Bmmp is functionally conserved in Drosophila. The Drosophila mp mutant strain exhibits curly wings of reduced size and a complete loss of flight capacity. Our results increase our understanding of the mechanisms underpinning insect wing development and reveal potential targets for pest control.

genetics↗

bioRxiv2021

Stratified Test Accurately Identifies Differentially Expressed Genes Under Batch Effects in Single-Cell Data

Analyzing single-cell sequencing data from large cohorts is challenging. Discrepancies across experiments and differences among participants often lead to omissions and false discoveries in differentially expressed genes. We find that the Van Elteren test, a stratified version of the widely used Wilcoxon rank-sum test, elegantly mitigates the problem. We also modified the common language effect size to supplement this test, further improving its utility. On both simulated and real patient data we show the ability of Van Elteren test to control for false positives and false negatives. A comprehensive assessment using receiver operating characteristic (ROC) curve shows that Van Elteren test achieves higher sensitivity and specificity on simulated datasets, compared with nine state-of-the-art differential expression analysis methods. The effect size also estimates the differences between cell types more accurately.

bioinformatics↗

bioRxiv2021

CBX4 regulates long-form thymic stromal lymphopoietin-mediated airway inflammation through SUMOylation in HDM-induced asthma

RationaleThymic stromal lymphopoietin (TSLP) is present in two distinct isoforms, short-form (sfTSLP) and long-form (lfTSLP). lfTSLP promotes inflammation while sfTSLP inhibits inflammation in allergic asthma. However, little is known about the regulation of lfTSLP and sfTSLP during allergic attack in asthma airway epithelium. Methods and ResultsHere, we report that SUMOylation was enhanced in HDM-induced allergic asthma airway epithelium. Inhibition of SUMOylation significantly alleviated airway Th2 inflammation and lfTSLP expression. Mechanistically, CBX4, a SUMOylation E3 ligase, enhanced lfTSLP, but not sfTSLP, mRNA translation through the RNA binding protein, MEX-3B. MEX-3B promoted lfTSLP translation through binding of its KH domains to the lfTSLP mRNA. Furthermore, CBX4 regulated MEX-3B transcription in HBE through enhancing SUMOylation levels of the transcription factor, TFII-I. ConclusionWe demonstrate an important mechanism whereby CBX4 promotes MEX-3B transcription through enhancing TFII-I SUMOylation, and MEX-3B enhances the expression of lfTSLP through binding to the lfTSLP mRNA and promoting its translation. Our findings uncover a novel target of CBX4 for therapeutic agents to lfTSLP-mediated asthma.

molecular biology↗

bioRxiv2021

The landscape of transcriptional and translational changes over 22 years of bacterial adaptation

Organisms can adapt to an environment by taking multiple mutational paths. This redundancy at the genetic level, where many mutations have similar phenotypic and fitness effects, can make untangling the molecular mechanisms of complex adaptations difficult. Here we use the E. coli long-term evolution experiment (LTEE) as a model to address this challenge. To bridge the gap between disparate genomic changes and parallel fitness gains, we characterize the landscape of transcriptional and translational changes across 11 replicate populations evolving in parallel for 50,000 generations. By quantifying absolute changes in mRNA abundances, we show that not only do all evolved lines have more mRNAs but that this increase in mRNA abundance scales with cell size. We also find that despite few shared mutations at the genetic level, clones from replicate populations in the LTEE are remarkably similar to each other in their gene expression patterns at both the transcriptional and translational levels. Furthermore, we show that the bulk of the expression changes are due to changes at the transcriptional level with very few translational changes. Finally, we show how mutations in transcriptional regulators lead to consistent and parallel changes in the expression levels of downstream genes, thereby linking genomic changes to parallel fitness gains in the LTEE. These results deepen our understanding of the molecular mechanisms underlying complex adaptations and provide insights into the repeatability of evolution.

evolutionary biology↗

bioRxiv2020

Improved prime editors enable pathogenic allele correction and cancer modelling in adult mice

Prime editors (PEs) mediate genome modification without utilizing double-stranded DNA breaks or exogenous donor DNA as a template. PEs facilitate nucleotide substitutions or local insertions or deletions within the genome based on the template sequence encoded within the prime editing guide RNA (pegRNA). However, the efficacy of prime editing in adult mice has not been established. Here we report an NLS-optimized SpCas9-based prime editor that improves genome editing efficiency in both fluorescent reporter cells and at endogenous loci in cultured cell lines. Using this genome modification system, we could also seed tumor formation through somatic cell editing in the adult mouse. Finally, we successfully utilize dual adeno-associated virus (AAVs) for the delivery of a split-intein prime editor and demonstrate that this system enables the correction of a pathogenic mutation in the mouse liver. Our findings further establish the broad potential of this genome editing technology for the directed installation of sequence modifications in vivo, with important implications for disease modeling and correction.

bioengineering↗

bioRxiv2020

Unbiased integration of single cell multi-omics data

Acquiring accurate single-cell multiomics profiles often requires performing unbiased in silico integration of data matrices generated by different single-cell technologies from the same biological sample. However, both the rows and the columns can represent different entities in different data matrices, making such integration a computational challenge that has only been solved approximately by existing approaches. Here, we present bindSC, a single-cell data integration tool that realizes simultaneous alignment of the rows and the columns between data matrices without making approximations. Using datasets produced by multiomics technologies as gold standard, we show that bindSC generates accurate multimodal co-embeddings that are substantially more accurate than those generated by existing approaches. Particularly, bindSC effectively integrated single cell RNA sequencing (scRNA-seq) and single cell chromatin accessibility sequencing (scATAC-seq) data towards discovering key regulatory elements in cancer cell-lines and mouse cells. It achieved accurate integration of both common and rare cell types (<0.25% abundance) in a novel mouse retina cell atlas generated using the 10x Genomics Multiome ATAC+RNA kit. Further, it achieves unbiased integration of scRNA-seq and 10x Visium spatial transcriptomics data derived from mouse brain cortex samples. Lastly, it demonstrated efficacy in delineating immune cell types via integrating single-cell RNA and protein data. Thus, bindSC, available at https://github.com/KChen-lab/bindSC, can be applied in a broad variety of context to accelerate discovery of complex cellular and biological identities and associated molecular underpinnings in diseases and developing organisms.

bioinformatics↗

bioRxiv2020

Single-Cell Manifold Preserving Feature Selection (SCMER)

1AO_SCPLOWBSTRACTC_SCPLOWA key challenge in studying organisms and diseases is to detect rare molecular programs and rare cell populations (RCPs) that drive development, differentiation, and transformation. Molecular features such as genes and proteins defining RCPs are often unknown and difficult to detect from unenriched single-cell data, using conventional dimensionality reduction and clustering-based approaches. Here, we propose a novel unsupervised approach, named SCMER, which performs UMAP style dimensionality reduction via selecting a compact set of molecular features with definitive meanings. We applied SCMER in the context of hematopoiesis, lymphogenesis, tumorigenesis, and drug resistance and response. We found that SCMER can identify non-redundant features that sensitively delineate both common cell lineages and rare cellular states ignored by current approaches. SCMER can be widely used for discovering novel molecular features in a high dimensional dataset, designing targeted, cost-effective assays for clinical applications, and facilitating multi-modality integration.

bioinformatics↗

bioRxiv2020

Co-infection of influenza A virus enhances SARS-CoV-2 infectivity

The upcoming flu season in the northern hemisphere merging with the current COVID-19 pandemic raises a potentially severe threat to public health. Through experimental co-infection of IAV with either pseudotyped or SARS-CoV-2 live virus, we found that IAV pre-infection significantly promoted the infectivity of SARS-CoV-2 in a broad range of cell types. Remarkably, increased SARS-CoV-2 viral load and more severe lung damage were observed in mice co-infected with IAV in vivo. Moreover, such enhancement of SARS-CoV-2 infectivity was not seen with several other viruses probably due to a unique IAV segment as an inducer to elevate ACE2 expression. This study illustrates that IAV has a special nature to aggravate SARS-CoV-2 infection, and prevention of IAV is of great significance during the COVID-19 pandemic.

microbiology↗

bioRxiv2020

A 3D Structural Interactome to Explore the Impact of Evolutionary Divergence, Population Variation, and Small-molecule Drugs on SARS-CoV-2-Human Protein-Protein Interactions

The recent COVID-19 pandemic has sparked a global public health crisis. Vital to the development of informed treatments for this disease is a comprehensive understanding of the molecular interactions involved in disease pathology. One lens through which we can better understand this pathology is through the network of protein-protein interactions between its viral agent, SARS-CoV-2, and its human host. For instance, increased infectivity of SARS-CoV-2 compared to SARS-CoV can be explained by rapid evolution along the interface between the Spike protein and its human receptor (ACE2) leading to increased binding affinity. Sequence divergences that modulate other protein-protein interactions may further explain differences in transmission and virulence in this novel coronavirus. To facilitate these comparisons, we combined homology-based structural modeling with the ECLAIR pipeline for interface prediction at residue resolution, and molecular docking with PyRosetta. This enabled us to compile a novel 3D structural interactome meta-analysis for the published interactome network between SARS-CoV-2 and human. This resource includes docked structures for all interactions with protein structures, enrichment analysis of variation along interfaces, predicted {Delta}{Delta}G between SARS-CoV and SARS-CoV-2 variants for each interaction, predicted impact of natural human population variation on binding affinity, and a further prioritized set of drug repurposing candidates predicted to overlap with protein interfaces{dagger}. All predictions are available online{dagger} for easy access and are continually updated when new interactions are published. {dagger}Some sections of this pre-print have been redacted to comply with current bioRxiv policy restricting the dissemination of purely in silico results predicting potential therapies for SARS-CoV-2 that have not undergone thorough peer-review. The results section titled "Prioritization of Candidate Inhibitors of SARS-CoV-2-Human Interactions Through Binding Site Comparison," Figure 4, Supplemental Table 9, and all links to our web resource have been removed. Blank headers left in place to preserve structure and item numbering. Our full manuscript will be published in an appropriate journal following peer-review.

systems biology↗