Biology subjects

Li, R.

Publications and source records attributed to Li, R..

At least 397 records · Page 22Linked to original sources

bioRxiv2021

GMQN: A reference-based method for correcting batch effects as well as probes bias in HumanMethylation BeadChip

Illumina HumanMethylation BeadChip is one of the most cost-effective ways to quantify DNA methylation levels at the single-base level across the human genome, which makes it a routine platform for epigenome-wide association studies. It has accumulated tens of thousands of DNA methylation array samples in public databases, thus provide great support for data integration and further analysis. However, majority of public DNA methylation data are deposited as processed data without background probes which are widely used in data normalization. Here we present Gaussian mixture quantile normalization (GMQN), a reference based method for correcting batch effects as well as probes bias in HumanMethylation BeadChip. Availability and implementation: https://github.com/MengweiLi-project/gmqn.

bioinformatics↗

bioRxiv2021

Endothelial integration of mechanosensory signals by the spectrin cytoskeleton

Physiological blood flow induces the secretion of vasoactive compounds, notably NO, and promotes endothelial cell elongation and reorientation parallel to the direction of applied shear. How shear is sensed and relayed to intracellular effectors is incompletely understood. We demonstrate that an apical spectrin network is essential to convey the force imposed by shear to endothelial mechanosensors. By anchoring CD44, spectrin modulates the cell surface density of hyaluronan, which senses and translates shear into changes in plasma membrane tension. Spectrins also regulate the stability of apical caveolae, where the mechanosensitive Piezo1 channels are thought to reside. Accordingly, shear-induced Piezo1 activation and the associated calcium influx were absent in spectrin-deficient cells. As a result, cell realignment and flow-induced eNOS stimulation were similarly dependent on spectrin. We concluded that the apical spectrin network is not only required for shear sensing, but transmits and distributes the resulting tensile forces to mechanosensors that elicit protective and vasoactive responses.

cell biology↗

bioRxiv2021

A novel multifunctional role for Hsp70 in binding post-translational modifications on clients

Hsp70 interactions are critical for cellular viability and the response to stress. Previous attempts to characterize Hsp70 interactions have been limited by their transient nature and inability of current technologies to distinguish direct vs bridged interactions. We report the novel use of cross-linking mass spectrometry (XL-MS) to comprehensively characterize the budding yeast Hsp70 protein interactome. Using this approach, we have gained fundamental new insights into Hsp70 function, including definitive evidence of Hsp70 self-association as well as multi-point interaction with its client proteins. In addition to identifying a novel set of direct Hsp70 interactors which can be used to probe chaperone function in cells, we have also identified a suite of PTM-associated Hsp70 interactions. The majority of these PTMs have not been previously reported and appear to be critical in the regulation of client protein function. These data indicate that one of the mechanisms by which PTMs contribute to protein function is by facilitating interaction with chaperones. Taken together, we propose that XL-MS analysis of chaperone complexes may be used as a unique way to identify biologically-important PTMs on client proteins. O_LIIn vivo confirmation of Hsp70 dimerization C_LIO_LIComprehensive direct interactome of Hsp70 C_LIO_LIMulti-domain interactions between Hsp70 and client proteins C_LIO_LIIdentification of novel biologically-important client protein PTMs C_LI

molecular biology↗

bioRxiv2021

Time Evolution of the Stroke Symptom-Herb Networks Based on TCM Prescriptions

Traditional Chinese Medicine (TCM) has its origins in distant antiquity and has piled up over a long time with much knowledge about diseases, especially stroke. Different combinations of symptom variables yield different combinations of herbs to form a myriad of prescriptions, and they have undergone repeated confirmation and are worthy objects of excavation and analysis. Herbal studies on stroke have developed from genomics to transcriptomics, proteomics and metabolomics, yet more thought is needed on putting time in a wider perspective of the symptoms and herbs for stroke in Chinese medicine. Due to this, we studied the dynamic structure of TCM prescriptions on stroke, using over 270 TCM prescription books containing 2231 prescriptions related to stroke recorded from 341 to 2000 CE. We labeled the functions of the prescriptions with the symptoms based on subject terms in MESH Neurologic Manifestations, then standardized the herbs in the prescriptions, and finally connected the co-occurring symptoms and herbs in the prescriptions to build an undirected complex network. The Stroke Symptom-Herb Networks (SSHNs) can be seen from its network characteristics that it is not a random network and has small-world characteristics. It has experienced two peaks in its nearly 1700-year history, during the Song dynasty, the Ming and Qing dynasties. From 600 years onwards, the core herb cluster has been initially formed. The comparison of sub-network similarities allowed us to identify several symptoms with similar herb clusters. We divided the community based on modularity, and by analyzing the community evolution, we found a more fixed historical evolutionary trend with Hemiplegia and Sialorrhea nodes and their associated symptom and herb nodes. In the time series analysis, we found many symptom-herb combinations that were consistently closely related to historic time depends on assessing the similarity between the symptoms and the herbs. The complex network provides a distinctive perspective for understanding the symptom-herb relationships embedded in TCM prescriptions in remote antiquity.

scientific communication and education↗

bioRxiv2021

Cellulose synthase-like D (CSLD) proteins move in the plasma membrane and their targeting to cell tips, but not cell plates, depends on the actin cytoskeleton

Cellulose Synthase-Like D (CSLD) proteins are implicated in cell wall remodeling during tip growth and cell division in plants, and are known to generate {beta}-1,4-glucan. It is unknown whether they form complexes and move in the plasma membrane like members of the Cellulose Synthase (CESA) family. We used the genetically tractable moss Physcomitrium patens, which has a filamentous protonemal stage that undergoes both tip growth and cell division and is amenable to high resolution live cell imaging, to investigate CSLD function and intracellular trafficking. CSLD2 and CSLD6 are highly expressed in gametophores and are redundantly required for gametophore cellular patterning. Live cell imaging revealed that CSLD6 is also expressed in protonemata where it moves in the plasma membrane and localizes to cell plates and cell tips. Notably, delivery to the apical plasma membrane, but not the cell plate, depends on actin. By comparing the behavior of endogenously tagged CSLD6 and CESA10, we discovered that CSLD6 movements in the plasma membrane were significantly faster, shorter in duration and less linear than CESA10 movements and were insensitive to the cellulose synthesis inhibitor isoxaben. These data suggest that CSLD6 and CESA10 function within different structures and may thus produce structurally distinct cellulose microfibrils.

plant biology↗

bioRxiv2021

Distinct stage-specific transcriptional states of B cells in human tonsillar tissue.

B cells within secondary lymphoid tissues encompass a diverse range of activation states and multiple maturation processes that reflect antigen recognition and transition through the germinal center (GC) reaction, in which mature B cells differentiate into memory and antibody-secreting cells (ASCs). Here, using single-cell RNA-seq, we identify distinct activation and maturation profiles of B cells within and outside the GC reaction in human secondary lymphoid tissue. In particular, we identify a distinct, previously uncharacterized CCL4/CCL3 chemokine-expressing B-cell population with an expression pattern consistent with BCR/CD40 activation. Furthermore, we present a computational method leveraging regulatory network inference and pseudotemporal modeling to identify upstream transcription factor modulation along the GC to ASC maturation axis. Our dataset provides valuable insight into the diverse functional profiles and maturation processes that B cells undergo within secondary lymphoid tissues and will be a useful resource on which to base further studies into the B-cell immune compartment. HighlightsO_LIscRNA-seq of human tonsillar B cells identifies distinct activation and maturation phenotypes. C_LIO_LIIdentification of a chemokine-expressing B-cell population in the human tonsil with a BCR and CD40 co-stimulatory gene signature. C_LIO_LITranscription factor regulatory network analysis identifies MYC and REL as predicted regulators of chemokine expression in the chemokine-expressing B-cell population. C_LIO_LITrajectory inference with gene and regulatory network modeling implicates novel transcription factors in the GC-to-ASC transition. C_LI

immunology↗

bioRxiv2021

Screening of cell-virus, cell-cell, gene-gene interactions among kingdoms of life at single cell resolution

The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) issued a significant and urgent threat to global health. The exact animal origin of SARS-CoV-2 remains obscure and understanding its host range is vital for preventing interspecies transmission. Previously, we have assessed the target cell profiles of SARS-CoV-2 in pets, livestock, poultry and wild animals. Herein, we expand this investigation to a wider range of animal species and viruses to provide a comprehensive source for large-scale screening of potential virus hosts. Single cell atlas for several mammalian species (alpaca, hamster, hedgehog, chinchilla etc.), as well as comparative atlas for lung, brain and peripheral blood mononuclear cells (PBMC) for various lineages of animals were constructed, from which we systemically analyzed the virus entry factors for 113 viruses over 20 species from mammalians, birds, reptiles, amphibians and invertebrates. Conserved cellular connectomes and regulomes were also identified, revealing the fundamental cell-cell and gene-gene cross-talks between these species. Overall, our study could help identify the potential host range and tissue tropism of SARS-CoV-2 and a diverse set of viruses and reveal the host-virus co-evolution footprints.

cell biology↗

bioRxiv2021

An ultrapotent neutralizing bispecific antibody with broad spectrum against SARS-CoV-2 variants

In spite of the successful development of effective countermeasures against Covid-19, variants have and will continue to emerge that could compromise the efficacy of currently approved neutralizing antibodies and vaccines. Consequently, novel and more efficacious agents are urgently needed. We have developed a bispecific antibody, 2022, consisting of two antibodies, 2F8 and VHH18. 2F8 was isolated from our proprietary fully synthetic human IDEAL (Intelligently Designed and Engineered Antibody Library)-VH/VL library and VHH18 is a single domain antibody isolated from IDEAL-nanobody library. 2022 was constructed by attaching VHH18 to the C-terminal of Fc of 2F8. 2022 binds two non-overlapping epitopes simultaneously on the RBD of the SARS-CoV-2 spike protein and blocks the binding of RBD to human angiotensin-converting enzyme 2 (ACE2). 2022 potently neutralizes SARS-CoV-2 and all of the variants tested in both pseudovirus and live virus assays, including variants carrying mutations known to resist neutralizing antibodies approved under EUA and that reduce the protection efficiency of current effective vaccines. The half-maximum inhibitory concentration (IC50) of 2022 is 270 pM, 30 pM, 20 pM, and 1 pM, for wild-type, alpha, beta, and delta pseudovirus, respectively. In the live virus assay, 2022 has an IC50 of 26.4 pM, 13.3 pM, and 88.6 pM, for wild-type, beta, and delta live virus, respectively. In a mouse model of SARS-CoV-2, 2022 showed strong prophylactic and therapeutic effects. A single administration of 2022 intranasal (i.n.) or intraperitoneal (i.p.) 24 hours before virus challenge completely protected all mice from bodyweight loss, as compared with up to 20% loss of bodyweight in placebo treated mice. In addition, the lung viral titers were undetectable (FRNT assay) in all mice treated with 2022 either prophylactically or therapeutically, as compared with around 1x105 pfu/g lung tissue in placebo treated mice. In summary, bispecific antibody 2022 showed potent binding and neutralizing activity across a variety of SARS-CoV-2 variants and could be an attractive weapon to combat the ongoing waves of the COVID-19 pandemic propagated mainly by variants, especially, the much more contagious delta variant.

microbiology↗

bioRxiv2021

Protection of human ACE2 transgenic Syrian hamsters from SARS CoV-2 variants by human polyclonal IgG from hyper-immunized transchromosomic bovines

Pandemic SARS CoV-2 has been undergoing rapid evolution during spread throughout the world resulting in the emergence of many Spike protein variants, some of which appear to either evade antibody neutralization, transmit more efficiently, or potentially exhibit increased virulence. This raises significant concerns regarding the long-term efficacy of protection elicited after primary infection and/or from vaccines derived from single virus Spike (S) genotypes, as well as the efficacy of anti-S monoclonal antibody based therapeutics. Here, we used fully human polyclonal human IgG (SAB-185), derived from hyperimmunization of transchromosomic bovines with DNA plasmids encoding the SARS-CoV-2 Wa-1 strain S protein or purified ectodomain of S protein, to examine the neutralizing capacity of SAB-185 in vitro and the protective efficacy of passive SAB-185 antibody (Ab) transfer in vivo. The Ab preparation was tested for neutralization against five variant SARS-CoV-2 strains: Munich (Spike D614G), UK (B.1.1.7), Brazil (P.1) and SA (B.1.3.5) variants, and a variant isolated from a chronically infected immunocompromised patient (Spike {Delta}144-146). For the in vivo studies, we used a new human ACE2 (hACE2) transgenic Syrian hamster model that exhibits lethality after SARS-Cov-2 challenge and the Munich, UK, SA and {Delta}144-146 variants. SAB-185 neutralized each of the SARS-CoV-2 strains equivalently on Vero E6 cells, however, a control convalescent human serum sample was less effective at neutralizing the SA variant. In the hamster model, prophylactic SAB-185 treatment protected the hamsters from fatal disease and minimized clinical signs of infection. These results suggest that SAB-185 may be an effective treatment for patients infected with SARS CoV-2 variants.

microbiology↗

bioRxiv2021

CUT&Tag-BS: an efficient and low-cost method for simultaneous profiling of histone modification and DNA methylation

It remains a challenge to decipher the complex relationship between DNA methylation, histone modification, and the underlying DNA sequence with limited input material. Here, we developed an efficient, low-input, and low-cost method for simultaneous profiling of genomic localization of histone modification and methylation status of the underlying DNA at single-base resolution from the same cells in a single experiment by integrating CUT&Tag with tagmentation-based bisulfite sequencing (CUT&Tag-BS). We demonstrated the validity of our method for both active and repressive histone modifications using 250,000 mouse ESCs. CUT&Tag-BS shows similar enrichment patterns of histone modification to those observed in non-bisulfite-treated control; it further reveals that H3K4me1-marked regions are mostly CpG-poor, lack methylation concordance, and exhibit prevalent DNA methylation heterogeneity among the cells. We anticipate that CUT&Tag-BS will be widely applied to directly address the genomic relationship between DNA methylation and histone modification, especially in low-input scenarios with precious biological samples.

genomics↗

bioRxiv2021

An oligosaccharide analog exhibited antifungal activity by misleading cell wall organization via targeting PHR transglucosidases

The fungal cell wall is an ideal target for the design of antifungal drugs. In this study we used an analog of cell wall polymer, a highly deacetylated long-chain chitosan oligosaccharide (HCOS), to test its effect against pathogenic Candida strains. Results showed that HCOS was successfully incorporated into the dynamic cell wall organization process and exhibited an apparent antifungal activity against both plankton and mature fungal biofilm, by impairing the cell wall integrity. Unexpectedly, mechanistic studies suggested that HCOS exerts its activity by interfering with family members of PHR {beta}-(1,3)-glucanosyl transferases and affecting the connection and assembly of cell wall polysaccharides. Furthermore, HCOS showed great synergistic activity with different fungicides against Candida cells, especially those in biofilm. These findings indicated HCOS has a great potential as an antifungal drug or drug synergist and proposed a novel antifungal strategy with structure-specific oligosaccharides mimicking cell wall polysaccharide fragments. IMPORTANCEFungal infections have always been a puzzle in clinical medicine. Only a few antifungal drugs are available for medical usage and the widespread use of antifungal drugs increased the incidence of drug resistance. It is an urgent need for the development of novel treatment strategies against fungal infections. In this study, we proposed a novel strategy targeting to fungal cell wall against C. albicans. To our knowledge, it is the first study to show a cell wall polysaccharide fragment analog integrate into and interfere with the fungal cell wall, indicating a novel antifungal strategy using structure-specific oligosaccharides mimicking cell wall polysaccharide fragments.

microbiology↗

bioRxiv2021

A cell-sorting-based nano-scale pipeline for cell-type-specific proteomics in plants

Multicellular organisms such as plants contain different cell types with specialized functions. Analyzing the characteristics of each cell type reveals specific cell functions and enhances understanding of organization and function at the organismal level. Here we report a highly-sensitive and efficient cell type-specific multiomics pipeline, combining simplified flow cytometry-based cell sorting for fluorescent protoplasts and optimized nanoscale proteomics and metabolomics methods, which allow in-depth analysis of the proteomes and metabolomes of a particular cell type. Using this method, we quantitatively compared the proteomes and metabolomes of guard cells and mesophyll cells and revealed that the enrichment of signal transduction-related proteins enables guard cells to respond rapidly to various environmental stimuli. We uncovered a guard cell-specific kinase cascade whereby RAF15 and OST1 mediate ABA-induced stomatal closure. This pipeline can be applied to various cell types in plant or non-plant systems to learn how cells function in highly organized multicellular organisms.

plant biology↗

bioRxiv2021

Comprehensive evaluation of machine learning models and gene expression signatures for prostate cancer prognosis using large population cohorts

Overtreatment remains the pervasive problem in prostate cancer (PCa) management due to the highly variable and often indolent course. Molecular signatures derived from gene expression profiling have played critical roles in PCa treatment decision-making. Many gene expression signatures have been developed to improve the risk stratification of PCa and some of them have already been translationally applied to clinical practice, however, no comprehensive evaluation was performed to compare the performances of the signatures. In this study, we conducted a systematic and unbiased evaluation of 15 machine learning (ML) algorithms and 30 published PCa gene expression-based prognostic signatures leveraging 10 transcriptomics datasets with 1,558 primary PCa patients from public data repositories. The results revealed that survival analysis models outperformed binary classification models for risk assessment, and the performances of the survival analysis methods - Cox model regularized with ridge penalty (Cox-Ridge) and partial least squares regression for Cox model (Cox-PLS) - were generally more robust than the other methods. Based on the Cox-Ridge algorithm, a few top prognostic signatures that have comparable or even better performances than the commercial panels have been identified. The findings from the study will greatly facilitate the identification of existing prognostic signatures that are promising for further validations in prospective studies and promote the development of robust prognostic models to guide clinical decision-making. Moreover, the study provided a valuable data resource from large primary PCa cohorts, which can be used to develop, validate, and evaluate novel statistical methodologies and molecular signatures to improve PCa management.

bioinformatics↗

bioRxiv2021

PCaDB - a comprehensive and interactive database for transcriptomes from prostate cancer population cohorts

Prostate cancer (PCa) is a heterogeneous disease with highly variable clinical outcomes which presents enormous challenges in the clinical management. A vast amount of transcriptomics data from large PCa cohorts have been generated, providing extraordinary opportunities for the molecular characterization of the PCa disease and the development of diagnostic and prognostic signatures. The lack of an inclusive collection and harmonization of the scattered public datasets constrains the extensive use of the valuable resources. In this study, we present a user-friendly database, PCaDB, for a comprehensive and interactive analysis and visualization of gene expression profiles from 77 transcriptomics datasets with 9,068 patient samples. PCaDB also includes a single-cell RNA-sequencing (scRNAseq) dataset for normal human prostates and 30 published PCa prognostic signatures. The comprehensive data resources and advanced analytical methods equipped in PCaDB would greatly facilitate data mining to understand the heterogeneity of PCa and to develop machine learning models for accurate PCa diagnosis and prognosis to assist on clinical decision-making. PCaDB is publicly available at http://bioinfo.jialab-ucr.org/PCaDB/.

bioinformatics↗

bioRxiv2021

High-throughput variant detection using a color-mixing strategy in real-time PCR reactions

Many diseases are related to multiple genetic alterations along a single gene. Probing for highly multiple (>10) variants in a single qPCR tube is not possible due to a limited number of fluorescence channels and one variant per channel, so many more tubes are needed. Here, we experimentally validate our novel color-mixing strategy that uses fluorescence combinations as digital color codes to probe multiple variants simultaneously. The color-mixing strategy relies on a simple intra-tube assay that can probe for 15 variants as part of an inter-tube assay that can probe for an exponentially increased number of variants. The color-mixing strategy is achieved using multiplex double-stranded toehold probes modified with fluorophores and quenchers; the probes are designed to be quenched or luminous after binding to wildtype or variant templates. We used the color-mixing strategy to probe for 21 pathogenic mutations in thalassemia and to distinguish between heterozygous and homozygous variants in 6 tubes, with a specificity of 99% and a sensitivity of 94%. To support tuberculosis diagnosis, we used the same strategy to simultaneously probe in Mycobacterium tuberculosis for rifampicin-resistance mutations occurring within one 81-bp region and one 48-bp region in rpoB gene, plus five isoniazid-resistance mutations in inhA and katG genes.

genetics↗

bioRxiv2021

ASER: Animal Sex Reversal database

Sex reversal, representing extraordinary sexual plasticity during the life cycle, not only triggers reproduction in animals but also affects reproductive and endocrine system-related diseases and cancers in humans. Sex reversal has been broadly reported in animals, however, an integrated resource hub of sex reversal information is still lacking. Here, we constructed a comprehensive database named ASER by integrating sex reversal-related data of 18 species from Teleostei to Mammals. We systematically collected 40,018 published papers and mined the Sex Reversal-associated Genes (SRGs), including their regulatory networks, from 1,611 core papers. We annotated homologous genes and computed conservation scores for whole genomes across the 18 species. Furthermore, we collected 206 available RNA-seq data and investigated the expression dynamics of SRGs during sex reversal or sex determination processes. In addition, we manually annotated 551 ISH images of SRGs from the literature and described their spatial expression in the gonads. Collectively, ASER provides a unique and integrated resource for researchers to query and reuse organized data to explore the mechanisms and applications of SRGs in animal breeding and human health. The ASER database is publicly available at http://aser.ihb.ac.cn/.

zoology↗

bioRxiv2021

Mechanical stress in pancreatic cancer: Signaling pathway adaptation activates cytoskeletal remodeling and enhances cell migration

New treatments for patients with advanced or metastatic pancreatic cancers are urgently needed due to their resistance to all current therapies. Current studies focus on alternative treatment approaches that target or normalize the abnormal microenvironment of pancreatic tumors, which among others, is responsible for elevated mechanical stress in the tumor interior. Nevertheless, the underlying mechanisms by which mechanical stress regulates pancreatic cancer metastatic potential remain elusive. Herein, we used a large-scale proteomic assay to profile mechanical stress-induced signaling cascades that drive the motility of pancreatic cancer cells. Proteomic analysis, together with selective protein inhibition and siRNA treatments, revealed that mechanical stress enhances cell migration through activation of the p38 MAPK/HSP27 and JNK/c-Jun signaling axes, and activation of the actin cytoskeleton remodelers: Rac1, cdc42, and Myosin II. Our results highlight targeting aberrant signaling in cancer cells that are adapted to the mechanical tumor microenvironment as a novel approach to effectively limit pancreatic cancer cell migration.

cancer biology↗

bioRxiv2021

scSVAS: CNV clonal visualization online platform for large scale single-cell genomics

The recent advance of single-cell copy number variation analysis plays an essential role in addressing intra-tumor heterogeneity, identifying tumor subgroups, and restoring tumor evolving trajectories at single-cell scale. Pleasant visualization of copy number analysis results boosts productive scientific exploration, validation, and sharing. Several single-cell analysis figures have the effectiveness of visualizations for understanding single-cell genomics in published articles and software packages. However, they almost lack real-time interaction, and it is hard to reproduce them. Moreover, existing tools are time-consuming and memory-intensive when they reach large-scale single-cell throughputs. We present an online visualization platform, scSVAS, for real-time interactive single-cell genomics data visualization. scSVAS is specifically designed for large-scale single-cell analysis. Compared with other tools, scSVAS manifests the most comprehensive functionalities. After uploading the specified input files, scSVAS deploys the online interactive visualization automatically. Users may make scientific discoveries, share interactive visualization, and download high-quality publication-ready figures. scSVAS provides versatile utilities for managing, investigating, sharing, and publishing single-cell copy number variation profiles. We envision this online platform will expedite the biological understanding of cancer clonal evolution in single-cell resolution. All visualizations are publicly hosted at https://sc.deepomics.org.

bioinformatics↗