Biology subjects

Yang, J.

Publications and source records attributed to Yang, J..

At least 649 records · Page 36Linked to original sources

bioRxiv2022

Bright and sensitive red voltage indicators for imaging action potentials in brain slices and pancreatic islets

As fast developing tools for observing cellular membrane potential, red-emitting genetically encoded voltage indicators (GEVIs) reduce auto-fluorescence background, allow multiplexed recordings, and enable all-optical electrophysiology, but have been limited by either insensitivity or dimness. Here, we report a pair of red GEVIs, Cepheid1b/s, with improved sensitivity, brightness, and photostability. Cepheid1 indicators faithfully report cellular excitability in pancreatic islets and neural activity in acute brain slices.

neuroscience↗

bioRxiv2022

Comparative genomic analysis between Leonurus japonicus and Leonurus sibiricus

Leonurus japonicus Houtt. is an important medicinal plant in East Asia and is now widely recognized for its role in treating cerebral apoplexy and lowering blood lipids. Here, we report two sets of chromosome-level genome sequences for leonurine-producing Leonurus japonicus and for its closely related species leonurine-free Leonurus sibiricus, where 99.78% of 518.19 Mb of L. japonicus was assembled into ten pseudochromosomes with a contig N50 of 17.62 Mb and 99.33% of 472.29 Mb of L. sibiricus was assembled into nine pseudochromosomes with a contig N50 of 13.29 MB. The reference genomes of Leonurus will accelerate the decoding of novel bioactive molecules in medicinal plants, especially in the Lamiaceae family.

plant biology↗

bioRxiv2022

Node-degree aware edge sampling mitigates inflated classification performance in biomedical graph representation learning

Graph representation learning is a family of related approaches that learn low-dimensional vector representations of nodes and other graph elements called embeddings. Embeddings approximate characteristics of the graph and can be used for a variety of machine-learning tasks such as novel edge prediction. For many biomedical applications, partial knowledge exists about positive edges that represent relationships between pairs of entities, but little to no knowledge is available about negative edges that represent the explicit lack of a relationship between two nodes. For this reason, classification procedures are forced to assume that the vast majority of unlabeled edges are negative. Existing approaches to sampling negative edges for training and evaluating classifiers do so by uniformly sampling pairs of nodes. We show here that this sampling strategy typically leads to sets of positive and negative edges with imbalanced edge degree distributions. Using representative homogeneous and heterogeneous biomedical knowledge graphs, we show that this strategy artificially inflates measured classification performance. We present a degree-aware node sampling approach for sampling negative edge examples that mitigates this effect and is simple to implement.

bioinformatics↗

bioRxiv2022

Monkeypox virus quadrivalent mRNA vaccine induces antibody responses and cellular immunity and protects mice against Vaccinia virus

There is an urgent need for efficient and safe vaccines against the monkeypox virus (MPXV) in response to the rapidly spreading monkeypox epidemic. In the age of COVID-19, mRNA vaccines have been highly successful and emerged as platforms enabling rapid development and large-scale preparation. Here, we have developed two MPXV quadrivalent mRNA vaccines, named mRNA-A-LNP and mRNA-B-LNP, based on two IMVs (A29L and M1R) and two EEVs (A35R and B6R). By administering mRNA-A-LNP and mRNA-B-LNP intramuscularly twice, mice have induced MPXV-specific IgG antibodies and potent Vaccinia virus (VACV)-specific neutralizing antibodies. Additionally, it elicited durable MPXV-specific killer memory T-cell immunity as well as memory B-cell immunity in mice. Furthermore, the passive transfer of sera from mRNA-A-LNP and mRNA-B-LNP-immunized mice protected nude mice against the VACV challenge. In addition, two doses of mRNA-A-LNP and mRNA-B-LNP were also protective against the VACV challenge in mice. Overall, our results demonstrated that mRNA-A-LNP and mRNA-B-LNP appear to be safe and effective vaccine candidates against monkeypox epidemics, as well as against outbreaks caused by other orthopoxviruses, including the smallpox virus.

immunology↗

bioRxiv2022

Age and Sex-Dependent Differences in Human Cardiac Matrix-Bound Exosomes Modulate Fibrosis through Synergistic miRNA Effects

Aging is a risk factor for cardiovascular disease, the leading cause of death worldwide. Cardiac fibrosis is a harmful result of repeated myocardial infarction that increases risk of morbidity and future injury. Interestingly, rates of cardiac fibrosis are different between young and aged individuals, as well as men and women. Here, for the first time, we identify and isolate matrix-bound extracellular vesicles from the left ventricles (LVs) of young or aged men and women. These LV vesicles (LVVs) show differences in morphology and content between these four cohorts. LVVs effects on fibrosis were also investigated in vitro, and it was shown that aged male LVVs were pro-fibrotic, while other LVVs were anti-fibrotic. miRNAs identified from these LVVs could partially recapitulate these effects together, but not individually, and confer other benefits. These data suggest that synergistic effects of matrix-resident exosomal miRNAs may influence the differential clinical response to MI.

bioengineering↗

bioRxiv2022

Evaluation of antibody kinetics and durability in health subjects vaccinated with inactivated COVID-19 vaccine (CoronaVac): A cross-sectional and cohort study in Zhejiang, China

BackgroundAlthough inactivated COVID-19 vaccines are proven to be safe and effective in the general population, the dynamic response and duration of antibodies after vaccination in the real world should be further assessed. MethodsWe enrolled 1067 volunteers who had been vaccinated with one or two doses of CoronaVac in Zhejiang Province, China. Another 90 healthy adults without previous vaccinations were recruited and vaccinated with three doses of CoronaVac, 28 days and 6 months apart. Serum samples were collected from multiple timepoints and analyzed for specific IgM/IgG and neutralizing antibodies (NAbs) for immunogenicity evaluation. Antibody responses to the Delta and Omicron variants were measured by pseudovirus-based neutralization tests. ResultsOur results revealed that binding antibody IgM peaked 14-28 days after one dose of CoronaVac, while IgG and NAbs peaked approximately 1 month after the second dose then declined slightly over time. Antibody responses had waned by month 6 after vaccination and became undetectable in the majority of individuals at 12 months. Levels of NAbs to live SARS-CoV-2 were correlated with anti-SARS-CoV-2 IgG and NAbs to pseudovirus, but not IgM. Homologous booster around 6 months after primary vaccination activated anamnestic immunity and raised NAbs 25.5-fold. The NAb inhibition rate subsequently rose to 36.0% for Delta (p=0.03) and 4.3% for Omicron (p=0.004), and the response rate for Omicron rose from 7.9% (7/89) to 17.8% (16/90). ConclusionsTwo doses of CoronaVac vaccine resulted in limited protection over a short duration. The homologous booster slightly increased antibody responses to the Delta and Omicron variants; therefore, the optimization of booster procedures is vital. FundingKey Research and Development Program of Zhejiang Province; Key Program of Health Commission of Zhejiang Province/ Science Foundation of National Health Commission; Major Program of Zhejiang Municipal Natural Science Foundation.

immunology↗

bioRxiv2022

Quartet metabolite reference materials for assessing inter-laboratory reliability and data integration of metabolomic profiling

Various laboratory-developed metabolomic methods lead to big challenges in inter-laboratory comparability and effective integration of diverse datasets. As part of the Quartet Project, we established a publicly available suite of four metabolite reference materials derived from B-lymphoblastoid cell lines from a family quartet of parents and monozygotic twin daughters. We generated comprehensive LC-MS based metabolomic data from the Quartet reference materials using targeted and untargeted strategies in different laboratories. High variabilities in the qualitative and quantitative metabolomic measurements were observed across laboratories. Moreover, the Quartet multi-sample-based quality metrics were developed for objectively assessing the reliability of metabolomic profiling in detecting intrinsic biological differences among difference groups of samples. Importantly, the ratio-based metabolomic profiling, by scaling the absolute values of a study sample relative to those of a universal reference sample, enables data integration in long-term measurements across difference laboratories or platforms. Thus, we constructed the ratio-based high-confidence reference datasets between two reference samples, providing "ground truth" for inter-laboratory proficiency test, which enables objective assessment of various metabolomic methods. Our study provided the community with rich resources and best practice for objective assessment of inter-laboratory measurements and data integration, ensuring reliable large-scale and longitudinal metabolomic profiling.

systems biology↗

bioRxiv2022

IL-6 suppresses vaccine responses in neonatal mice by enhancing IL-2 activity on T follicular helper cells

The inability of neonates to develop CD4+CXCR5+PD-1+ T follicular helper (TFH) cells contributes to their weak vaccine responses. In adult mice, IL-6 promotes TFH-cell expansion by suppressing the expression of IL-2R{beta} on TFH cells. Here, we found a totally opposite role for IL-6 in neonatal mice TFH response. Whereas co-injection of neonatal mice with IL-6 and a conjugate polysaccharide vaccine suppressed TFH response by increasing the production of IL-2 and expression of IL-2R and IL-2R{beta} on TFH cells, immunization of IL-6 knock-out neonatal mice led to improved antibody responses accompanied by expanded TFH cells as well as lower levels of IL-2 and IL-2 receptors on TFH cells. Moreover, CpG containing vaccine improved TFH response in neonates while suppressing the expression of IL-2 receptors on TFH cells, suggesting that CpG protects TFH cells by inhibiting IL-2 activity. These findings unveil age specific differences in IL-6 mediated vaccine responses and highlight the need to consider age related immunobiological attributes in designing vaccines.

immunology↗

bioRxiv2022

Vascular endothelial growth factor A contributes to the increasing of mammalian respiratory epithelial permeability induced by Pasteurella multocida infection

Infections with Pasteurella multocida can cause significant zoonotic respiratory problems in both humans and animals. In vivo tests in mouse infection models were used to investigate the mechanisms of respiratory epithelial barrier dysfunction during respiratory bacterial infection with these pathogens. Results revealed that P. multocida infection significantly increased epithelial permeability and increased expression of vascular endothelial growth factor A (VEGFA) and endothelial nitric oxide synthase (eNOS) in murine tracheae and lungs. In murine lung epithelial cell (MLE-12) models, P. multocida infection decreased the expression of tight junctions (ZO-1) and adherens junctions ({beta}-catenin, E-cadherin), but induced the activation of the hypoxia-inducible factor-1 (HIF-1) and VEGFA signaling. When expression of HIF-1 is suppressed, the induction of VEGFA and ZO-1expression by P. multocida infection is decreased. We also found that intervention of HIF-1 and VEGFA signaling affected infection outcomes caused by respiratory bacteria in mouse models. Most importantly, we demonstrated that P. multocida infection increased permeability of human respiratory epithelial cells and this process was associated with the activation of the HIF-1 and VEGFA signaling and likely contributes to the pathogenesis of P. multocida in humans. ImportanceMammalian respiratory epithelium forms the first line of defense against infections with Pasteurella multocida, an important zoonotic respiratory pathogen. In this study, we found P. multocida infection increased respiratory epithelial permeability and promoted the induction of the hypoxia-HIF-1-VEGFA axis in both mouse and murine cell models. Similar findings were also demonstrated in human respiratory epithelial cells. The results from this study gain important knowledge about the pathogenesis of P. multocida causing infections in both animals and humans.

microbiology↗

bioRxiv2022

Carryover effects of tire wear particle leachate threats reproduction across multiple generations

Toxic additives leached from tire wear particle (TWP) have been linked to some collective death events of fish, also impose impacts on zooplankton as secondary consumer in aquatic food web. In addition to direct impacts of TWP leachate at the current generation, potential delayed carryover from past exposure across multi-generational lineage may augment impacts on individual reproduction, then population maintenance. We investigated the carryover effects from persistent exposure and past TWP leachate exposure along generation passaging on the individual reproduction of rotifer, Brachionus calyciflorus, a typical zooplankton. For rotifer treated with TWP leachate across continuous 7 generations, their offspring were divided into parental exposure or no exposure in each generation. And rotifer transferred into no exposure were maintained for 3 generations to eliminate indirect exposure through their parental germ. The similar response of reproduction, via carryover effects from parental exposure, also emerged in offspring without exposure. Persistent exposure across multiple generations additively impaired individual reproduction performance by transferring from its hermetic effects in original generation, even caused final population collapse. TWP leachate could impose cascading toxicity on population persistence of zooplankton via carryover and cumulative effects on reproduction for long term, which must be considered in risk assessment and management policy to alleviate the effects of TWP.

ecology↗

bioRxiv2022

Flux estimation analysis systematically characterizes the metabolic shifts of the central metabolism pathway in human cancer.

Glucose and glutamine are major carbon and energy sources that promote the fast proliferation of cancer cells. Metabolic shifs observed on cell line or mouse models may not reflect the general metabolic shifts in real human cancer tissue. In this study, we conducted a computational characterization of the flux distribution and variations of the central energy metabolism and key branches in a pan-cancer analysis, including glycolytic pathway, production of lactate, TCA cycle, nucleic acids synthesis, glutaminolysis, glutaminate, glutamine and glutathione metabolism, amino acids synthesis, in 11 cancer subtypes and 9 matched adjacent normal tissue types, by using TCGA tissue transcriptomics data. Our analysis confirms the increased influx in glucose uptake and glycolysis and decreased upper part of TCA cycle, i.e., Warbug effect in the analyzed cancer types. However, consistently increased lactate production and second half of TCA cycle were only seen in certain cancer types. More interestingly, we did not see cancer tissues have highly shifted glutaminolysis compared to their adjacent normal controls. A systems biology model of metabolic shifts in through cancer and tissue types is further developed and analyzed. We observed that (1) normal tissues have distinct metabolic phenotypes, (2) cancer types have drastically different metabolic shifts compared to their adjacent normal controls, and (3) the different shifts happened to tissue specific metabolic phenotypes result in a converged metabolic phenotype through cancer types and cancer progression. This study strongly suggests the possibility to have a unified framework for studies of cancer-inducing stressors, adaptive metabolic reprogramming, and cancerous behaviors.

bioinformatics↗

bioRxiv2022

A Common Resequencing-Based Genetic Marker Dataset for Global Maize Diversity

Maize (Zea mays ssp. mays) populations exhibit vast amounts of genetic and phenotypic diversity. As sequencing costs have declined, an increasing number of projects have sought to measure genetic differences between and within maize populations using whole genome resequencing strategies, identifying millions of segregating single-nucleotide polymorphisms (SNPs) and insertions/deletions (InDels). Unlike older genotyping strategies like microarrays and genotyping by sequencing, resequencing should, in principle, frequently identify and score common genetic variants. However, in practice, different projects frequently employ different analytical pipelines, often employ different reference genome assemblies, and consistently filter for minor allele frequency within the study population. This constrains the potential to reuse and remix data on genetic diversity generated from different projects to address new biological questions in new ways. Here we employ resequencing data from 1,276 previously published maize samples and 239 newly resequenced maize samples to generate a single unified marker set of [~]366 million segregating variants and [~]46 million high confidence variants scored across crop wild relatives, landraces as well as tropical and temperate lines from different breeding eras. We demonstrate that the new variant set provides increased power to identify known causal flowering time genes using previously published trait datasets, as well as the potential to track changes in the frequency of functionally distinct alleles across the global distribution of modern maize.

plant biology↗

bioRxiv2022

Ratio-based quantitative multiomics profiling using universal reference materials empowers data integration

Multiomics profiling is a powerful tool to characterize the same samples with complementary features orchestrating the genome, epigenome, transcriptome, proteome, and metabolome. However, the lack of ground truth hampers the objective assessment of and subsequent choice from a plethora of measurement and computational methods aiming to integrate diverse and often enigmatically incomparable omics datasets. Here we establish and characterize the first suites of publicly available multiomics reference materials of matched DNA, RNA, proteins, and metabolites derived from immortalized cell lines from a family quartet of parents and monozygotic twin daughters, providing built-in truth defined by family relationship and the central dogma. We demonstrate that the "ratio"-based omics profiling data, i.e., by scaling the absolute feature values of a study sample relative to those of a concurrently measured universal reference sample, were inherently much more reproducible and comparable across batches, labs, platforms, and omics types, thus empower the horizontal (within-omics) and vertical (cross-omics) data integration in multiomics studies. Our study identifies "absolute" feature quantitation as the root cause of irreproducibility in multiomics measurement and data integration, and urges a paradigm shift from "absolute" to "ratio"-based multiomics profiling with universal reference materials.

systems biology↗

bioRxiv2022

Dissecting the genetic architecture of sunflower head diameter using genome-wide association study

Sunflower (Helianthus annuus L.) plays an essential role in meeting the edible oil demand worldwide. Sunflower seed yield can be decomposed into several yield component traits, one of which is the head diameter. In 2019, 2020, and 2022, we evaluated the head diameter phenotypic variation on a set of diverse sunflower accessions (N=342) in replicated field trials. By combining three years of field data, the broad sense heritability (H2) of the head diameter trait was estimated to be 0.88. Then, a subset of N=274 accessions was genotyped by using the tunable genotyping-by-sequencing (tGBS) method, resulting in 226,779 high-quality SNPs. With these SNPs and the head diameter phenotype, the genome-wide association study (GWAS) was conducted using two statistical approaches: 1) the mixed linear model (MLM) and 2) the fixed and random model circulating probability unification (farmCPU). The MLM and farmCPU GWAS approaches identified 106 and 8 significant SNPs that were placed close to 53 and 21 genes, respectively. Two significant peaks were identified in MLM, with a strong signal on chromosome 10 and a less strong signal on chromosome 16. The farmCPU method detected the same signals on chromosomes 10 and 16 and several additional significant signals on other chromosomes. The head diameter associated genetic loci and the underlying candidate genes can be leveraged for further functional validation and serve as a basis for sunflower oil yield improvement.

genomics↗

bioRxiv2022

Accurate de novo prediction of RNA 3D structure with transformer network

RNA 3D structure prediction remains challenging though after years of efforts. Inspired by the recent breakthrough in protein structure prediction, we developed trRosettaRNA, a novel deep learning-based approach to de novo prediction of RNA 3D structure. Like trRosetta, the trRosettaRNA pipeline comprises two major steps: 1D and 2D geometries prediction by a transformer network; and full-atom 3D structure folding by energy minimization with constraints from the predicted geometries. We benchmarked trRosettaRNA on two independent datasets. The results show that trRosettaRNA outperforms other conventional methods by a large margin. For example, on 25 targets from the RNA-Puzzles experiments, the mean RMSD of the models predicted by trRosettaRNA is 5.5 [A], compared with 10.5 [A] from the state-of-the-art human group (i.e., Das). Further comparisons with two recently released deep learning-based methods (i.e., DeepFoldRNA and RoseTTAFoldNA) show that all three methods have similar accuracy. However, trRosettaRNA yields more accurate and physically more realistic side-chain atoms than DeepFoldRNA and RoseTTAFoldNA. Finally, we apply trRosettaRNA to predict the structures for the Rfam families that do not have known structures. Analysis shows that for 263 families, the predicted structure models are estimated to be accurate with RMSD < 4 [A]. The trRosettaRNA server and the package are available at: https://yanglab.nankai.edu.cn/trRosettaRNA/.

bioinformatics↗

bioRxiv2022

Correcting batch effects in large-scale multiomic studies using a reference-material-based ratio method

Batch effects are notorious technical variations that are common in multiomic data and may result in misleading outcomes. With the era of big data, tackling batch effects in multiomic integration is urgently needed. As part of the Quartet Project for quality control and data integration of multiomic profiling, we comprehensively assess the performances of seven batch-effect correction algorithms (BECAs) for mitigating the negative impact of batch effects in multiomic datasets, including transcriptomics, proteomics, and metabolomics. Performances are evaluated based on accuracy of identifying differentially expressed features, robustness of predictive models, and the ability of accurately clustering cross-batch samples into their biological sample groups. Ratio-based method is more effective and widely applicable than others, especially in cases when batch effects are highly confounded with biological factors of interests. We further provide practical guidelines for the implementation of ratio-based method using universal reference materials profiled with study samples. Our findings show the promise for eliminating batch effects and enhancing data integration in increasingly large-scale, cross-batch multiomic studies.

systems biology↗

bioRxiv2022

High bacillary burden and the ESX-1 type VII secretion system promote MHC class I presentation to CD8 T-cells during Mycobacterium tuberculosis infection

Mycobacterium tuberculosis (Mtb) subverts host defenses to persist in macrophages despite immune pressure. CD4 T-cells can recognize macrophages infected with a single bacillus in vitro. Under identical conditions, CD8 T-cells inefficiently recognize infected macrophages and fail to restrict Mtb growth, although they can inhibit Mtb growth during high burden intracellular infection. We show that high intracellular Mtb numbers cause macrophage death, leading other macrophages to scavenge cellular debris and cross-present the TB10.4 antigen to CD8 T-cells. Presentation by infected macrophages requires Mtb to have a functional ESX-1 type VII secretion system. These data indicate that phagosomal membrane damage and cell death promote class I MHC presentation of the immunodominant antigen TB10.4 by macrophages. Although this mode of antigen-presentation stimulates cytokine production that we presume would be host beneficial; killing of uninfected cells could worsen immunopathology. We suggest that shifting the focus of CD8 T-cell recognition to uninfected macrophages would limit the interaction of CD8 T-cells with infected macrophages and impair CD8 T-cell mediated resolution of tuberculosis.

immunology↗

bioRxiv2022

Field dependent deep learning enables high-throughput whole-cell 3D super-resolution imaging

Single-molecule localization microscopy (SMLM) in a typical wide-field setup has been widely used for investigating sub-cellular structures with super resolution. However, field-dependent aberrations restrict the field of view (FOV) to only few tens of micrometers. Here, we present a deep learning method for precise localization of spatially variant point emitters (FD-DeepLoc) over a large FOV covering the full chip of a modern sCMOS camera. Using a graphic processing unit (GPU) based vectorial PSF fitter, we can fast and accurately model the spatially variant point spread function (PSF) of a high numerical aperture (NA) objective in the entire FOV. Combined with deformable mirror based optimal PSF engineering, we demonstrate high-accuracy 3D SMLM over a volume of ~180 x 180 x 5 m3, allowing us to image mitochondria and nuclear pore complex in the entire cells in a single imaging cycle without hardware scanning - a 100-fold increase in throughput compared to the state-of-the-art.

biophysics↗