Biology subjects

Luo, M.

Publications and source records attributed to Luo, M..

125 records · Page 7Linked to original sources

bioRxiv2019

ImmuCellAI: a unique method for comprehensive T-cell subsets abundance prediction and its application in cancer immunotherapy

The distribution and abundance of immune cells, particularly T-cell subsets, play pivotal roles in cancer immunology and therapy. There are many T-cell subsets with specific function, however current methods are limited in estimating them, thus, a method for predicting comprehensive T-cell subsets is urgently needed in cancer immunology research. Here we introduce Immune Cell Abundance Identifier (ImmuCellAI), a novel gene set signature-based method, for precisely estimating the abundance of 24 immune cell types including 18 T-cell subsets, from gene expression data. Performance evaluation on both our sequencing data with flow cytometry results and public expression data indicated that ImmuCellAI can estimate immune cells with superior accuracy than other methods especially on many T-cell subsets. Application of ImmuCellAI to immunotherapy datasets revealed that the abundance of dendritic cells (DC), cytotoxic T, and gamma delta T cells was significantly higher both in comparisons of on-treatment vs. pre-treatment and responders vs. non-responders. Meanwhile, we built an ImmuCellAI result-based model for predicting the immunotherapy response with high accuracy (AUC 0.80~0.91). These results demonstrated the powerful and unique function of ImmuCellAI in tumor immune infiltration estimation and immunotherapy response prediction. The ImmuCellAI online server is freely available at http://bioinfo.life.hust.edu.cn/web/ImmuCellAI/.

bioinformatics↗

bioRxiv2019

CCLA: an accurate method and web server for cancer cell line authentication using gene expression profiles

Cancer cell lines (CCLs) as important model systems play critical roles in cancer researches. The misidentification and contamination of CCLs are serious problems, leading to unreliable results and waste of resources. Current methods for CCL authentication are mainly based on the CCL-specific genetic polymorphisms, whereas no method is available for CCL authentication using gene expression profiles. Here, we developed a novel method and homonymic web server (CCLA, Cancer Cell Line Authentication, http://bioinfo.life.hust.edu.cn/web/CCLA/) to authenticate 1,291 human CCLs of 28 tissues using gene expression profiles. CCLA curated CCL-specific gene signatures and employed machine learning methods to measure overall similarities and distances between the query sample and each reference CCL. CCLA showed an excellent speed advantage and high accuracy with a top 1 accuracy of 96.58% or 92.15% (top 3 accuracy of 100% or 95.11%) for microarray or RNA-Seq validation data (719 samples, 461 CCLs), respectively. To the best of our knowledge, CCLA is the first approach to authenticate CCLs based on gene expression. Users can freely and conveniently authenticate CCLs using gene expression profiles or NCBI GEO accession on CCLA website.

bioinformatics↗

bioRxiv2019

A novel vaccine targeting the viral protease cleavage sites protects Mauritian cynomolgus macaques against vaginal SIVmac251 infection

After over three decades of research, an effective anti-HIV vaccine remains elusive. Unconventional and novel vaccine strategies are needed. Here, we report that a vaccine focusing the immune response on the sequences surrounding the 12 viral protease cleavage sites (PCSs) provides greater than 80% protection of Mauritian cynomolgus macaques (MCMs) against repeated intravaginal SIVmac251 challenges. The PCS-specific T cell responses are correlated with vaccine efficacy. The PCS vaccine does not induce immune activation and inflammation known to be associated with increased susceptibility to HIV infection. Machine learning analyses revealed that the immune environment generated by the PCS vaccine predicts vaccine efficacy. Our study demonstrates for the first time that a novel vaccine which targets viral maturation, but lacks full Env and Gag proteins as immunogens, can prevent intravaginal infection in a highly stringent NHP/SIV challenge model. Targeting HIV maturation thus offers a novel approach to developing an effective HIV vaccine. One Sentence SummaryThe anti-PCS T cell responses and the immune environment induced by the novel PCS vaccine are key correlates of vaccine efficacy

microbiology↗

bioRxiv2019

Individualized ctDNA Fingerprints to Monitor Treatment Response and Recurrence in Multiple Cancer Types

Circulating tumor DNA (ctDNA) panels hold high promise of accurately predicting the therapeutic response of tumors while being minimally invasive and cost-efficient. However, their use has been limited to a small number of tumor types and patients. Here, we developed individualized ctDNA fingerprints suitable for most patients with multiple cancer types. The panels were designed based on individual whole-exome sequencing data in 521 Chinese patients and targeting high clonal population clusters of somatic mutations. Together, these patients represent 12 types of cancers and seven different treatments. The customized ctDNA panels have a median somatic mutation number of 19, most of which are patient-specific rather than cancer hotspot mutations; 66.8% of the patients were ctDNA-positive. We further evaluated the ctDNA content fraction (CCF) of the mutations, and analyzed the association between the change of ctDNA concentration and therapeutic response. We followed up 106 patients for clinical evaluation, demonstrating a significant correlation of changes in ctDNA with clinical outcomes, with a consistency rate of 93.4%. In particular, the median CCF increased by 204.6% in patients with progressive disease, decreased by 82.5% in patients with remission, and was relatively stable in patients with stable disease. Overall, 85% of the patients with a ctDNA-positive status experienced metastasis or relapse long before imaging detection, except for two patients who developed recurrence and metastasis almost simultaneously. The average lead time between the first ctDNA-positive finding and radiological diagnosis was 76 days in three patients that changed from a ctDNA-negative to -positive status. Our individualized ctDNA analysis can effectively monitor the treatment response, metastasis, and recurrence in multiple cancer types in patients with multiple treatment options, therefore offering great clinical applicability for improving personalized treatment in cancer.\n\nOne Sentence SummaryctDNA fingerprint panels were customized to predict the treatment response for multiple cancer types from individual whole-exome sequencing data.

cancer biology↗

bioRxiv2019

Serotonin Neurons in the Dorsal and Medial Raphe Nuclei: from Single-Cell Transcriptomes to Whole-Brain Projections

Serotonin neurons of the dorsal and medial raphe nuclei (DR and MR) collectively innervate the entire forebrain and midbrain, modulating diverse physiology and behavior. To gain a fundamental understanding of their molecular heterogeneity, we used plate-based single-cell RNA-sequencing to generate a comprehensive dataset comprising eleven transcriptomically distinct serotonin neuron clusters. Systematic in situ hybridization mapped specific clusters to the principal DR, caudal DR, or MR. These transcriptomic clusters differentially express a rich repertoire of neuropeptides, receptors, ion channels, and transcription factors. We generated novel intersectional viral-genetic tools to access specific subpopulations. Whole-brain axonal projection mapping revealed that DR serotonin neurons co-expressing vesicular glutamate transporter-3 preferentially innervate the cortex, whereas those co-expressing thyrotropin-releasing hormone innervate subcortical regions in particular the hypothalamus. Reconstruction of 50 individual DR serotonin neurons revealed segregated axonal projection patterns at the single-cell level. Together, these results provide a molecular foundation of the heterogenous serotonin neuronal phenotypes.

neuroscience↗

bioRxiv2019

A Chemical Probe of CARM1 Alters Epigenetic Plasticity against Breast Cancer Cell Invasion

CARM1 is a cancer-relevant protein arginine methyltransferase that regulates many aspects of transcription. Its pharmacological inhibition is a promising anti-cancer strategy. Here SKI-73 is presented as a CARM1 chemical probe with pro-drug properties. SKI-73 can rapidly penetrate cell membranes and then be processed into active inhibitors, which are retained intracellularly with 10-fold enrichment for days. These compounds were characterized for their potency, selectivity, modes of action, and on-target engagement. SKI-73 recapitulates the effect of CARM1 knockout against breast cancer cell invasion. Single-cell RNA-seq analysis revealed that the SKI-73-associated reduction of invasiveness act via altering epigenetic plasticity and suppressing the invasion-prone subpopulation. Interestingly, SKI-73 and CARM1 knockout alter the epigenetic plasticity with remarkable difference, arguing distinct modes of action between the small-molecule and genetic perturbation. We therefore discovered a CARM1-addiction mechanism of cancer metastasis and developed a chemical probe to target this process.

biochemistry↗

bioRxiv2019

Systematic and comprehensive benchmarking of an exome sequencing based germline copy-number variant detection pipeline in a clinical setting

PurposeDetecting germline copy-number variants (CNVs) from exome sequencing (ES) is not a standard practice in clinical settings owing to several reasons concerning performance. We comprehensively characterized an ES-based CNV pipeline and developed frameworks for minimizing false-positives and assess the reproducibility.\n\nMethodsWe used a cohort of 387 individuals with both clinical chromosomal microarray (CMA) and ES data available to estimate the initial performance by comparing CNVs from both platforms. A modification of the default workflow was performed to reduce the number of false positives and the reproducibility of the CNVs was assessed using an iterative variant calling process.\n\nResultsThe default pipeline was 93% sensitive with a high false-discovery rate of 44%. The modified workflow had a higher sensitivity of 96% while reducing the total number of CNVs identified and improving the false-discovery rate to 11.4%. With the modified workflow, we demonstrated a 100% validation rate for the CNVs identified in the STRC, a challenging gene to ascertain by short-read NGS. The exome-based pipeline was 100% sensitive for clinically-relevant, rare variants (including single exon deletions), and was reproducible.\n\nConclusionWe demonstrate with our modified workflow and the benchmarking data that an exome-based CNV detection pipeline can be reliably used to detect clinically-relevant CNVs.

bioinformatics↗

bioRxiv2019

Reduced chromatin accessibility underlies gene expression differences in homologous chromosome arms of hexaploid wheat and diploid Aegilops tauschii

Polyploidy has been centrally important in driving the evolution of plants, and leads to alterations in gene expression that are thought to underlie the emergence of new traits. Despite the common occurrence of these global patterns of altered gene expression in polyploids, the mechanisms involved are not well understood. Using a precise framework of highly conserved syntenic genes on hexaploid wheat chromosome 3DL and its progenitor 3L chromosome arm of diploid Aegilops tauschii, we show that 70% of these genes exhibited proportionally reduced gene expression, in which expression in the hexaploid context of the 3DL genes was approximately 40% of the levels observed in diploid Ae. tauschii. Many genes showing elevated expression during later stages of grain development in wheat compared to Ae. tauschii. Gene sequence and methylation differences accounted for only a few cases of differences in gene expression. In contrast, large scale patterns of reduced chromatin accessibility of genes in the hexaploid chromosome arm compared to its diploid progenitor were correlated with observed overall reduction in gene expression and differential gene expression. Therefore, that an overall reduction in accessible chromatin underlies the major differences in gene expression that results from polyploidization.

genomics↗

bioRxiv2019

Compressive Stress Enhances Invasive Phenotype of Cancer Cells via Piezo1 Activation

Uncontrolled growth in solid tumor generates compressive stress that drives cancer cells into invasive phenotypes, but little is known about how such stress affects the invasion and matrix degradation of cancer cells and the underlying mechanisms. Here we show that compressive stress enhanced invasion, matrix degradation, and invadopodia formation of breast cancer cells. We further identified Piezo1 channels as the putative mechanosensitive cellular components that transmit the compression to induce calcium influx, which in turn triggers activation of RhoA, Src, FAK, and ERK signaling, as well as MMP-9 expression. Interestingly, for the first time we observed invadopodia with matrix degradation ability on the apical side of the cells, similar to those commonly observed at the cells ventral side. Furthermore, we demonstrate that Piezo1 and caveolae were both involved in mediating the compressive stress-induced cancer cell invasive phenotype as Piezo1 and caveolae were often colocalized, and reduction of Cav-1 expression or disruption of caveolae with methyl-{beta}-cyclodextrin led to not only reduced Piezo1 expression but also attenuation of the invasive phenotypes promoted by compressive stress. Taken together, our data indicate that mechanical compressive stress activates Piezo1 channels to mediate enhanced cancer cell invasion and matrix degradation that may be a critical mechanotransduction pathway during, and potentially a novel therapeutic target for, breast cancer metastasis

cell biology↗

bioRxiv2018

Consensus interpretation of the Met34Thr and Val37Ile variants in GJB2 by the ClinGen Hearing Loss Expert Panel

PURPOSEPathogenic variants in GJB2 are the most common cause of autosomal recessive sensorineural hearing loss. The classification of c.101T>C/p.Met34Thr and c.109G>A/p.Val37Ile in GJB2 are controversial. Therefore, an expert consensus is required for the interpretation of these two variants.\n\nMETHODSThe ClinGen Hearing Loss Expert Panel (HL-EP) collected published data and shared unpublished information from participating laboratories regarding the two variants. Functional, computational, allelic, and segregation data were also obtained.\n\nRESULTSThe panel reviewed the synthesized information, and classified the Met34Thr and Val37Ile variants according to professional variant interpretation guidelines. We found that Met34Thr and Val37Ile are significantly overrepresented in hearing loss patients, compared to the general population. Met34Thr or Val37Ile homozygotes or compound heterozygotes typically manifest mild to moderate hearing loss. Several other types of evidence also support pathogenic roles for those two variants.\n\nCONCLUSIONResolving controversies in variant classification requires coordinated effort among a panel of international multi-institutional experts to share data, standardize classification rules, review evidence, and reach a consensus. The ClinGen HL-EP concluded that Met34Thr and Val37Ile variants in GJB2 are pathogenic for autosomal recessive nonsyndromic hearing loss with variable expressivity and age-dependent penetrance.

genetics↗

bioRxiv2018

The algae community in taxon Haptophyceae at the early bloom stage of Phaeocystis globosa in Northern Beibu Gulf in winter

Phaeocystis globosa (Order Phaeocystales, family Phaeocystaceae) caused significant impact on aquaculture farming, global climate change and industry. Since the year 2010, intensive red tides of P. globosa began to appear in Beibu Gulf, where previously free of harmful algal blooms, and posed great threats to the cooling systems of a nuclear power plant in 2014 and 2015. In order to discover the bloom mechanism, the community structure of marine microalgae, with a focus on Haptophyceae taxa, in winter in the northern Beibu Gulf near the Qinzhou Bay, Sanniang Bay (SNB) and Dafenjiang River Estuary (DRE), were explored via 18S ribosomal DNA analysis of the V4 region using the Illumina-Based Sequencing platform. The correlation between the relative abundance of five kinds of Haptophyceae algae and environmental factors of seawater were analyzed. The most abundant Haptophyceae-related OTU in terms of number of reads was identified as Phaeocystis and Chrysochromulina. The abundance for other Haptophyceae class was relatively low, such as Haptolina, Prymnesium and Isochrysis. Phaeocystis was present in all samples sites except S6, S11, S12, S14 and S15, and particularly abundant at S8, nearly 29 times more than the second most abundant site. Most notably, the results showed that Phaeocystis displayed highly positive linear correlation with the concentration of NO3--N (Pearson r=0.856, p<0.01). Linear regression analysis indicated that Phaeocystis was significantly linearly related to the NO3--N (R2=0.732; Y=-0.005 + 0.410*X, Y is the relative abundance of P.globosa, X is the concentration of NO3--N; F=38.227, P<0.05) and NO3--N has a significant positive effect on P.globosa (regression coefficient is 0.410, P=0.000). Moreover, the relative abundance of Phaeocystis was significant related to temperature of sea water (Pearson r=-0.882, p<0.01). Water temperature can explain the 77.8% change reason for the P.globosa (R2=0.778), and has a significant effect on P. globosa (Y=0.169-0.009*X, F=49.031, P<0.05), and the regression coefficient is -0.009 (P=0.000) which indicated a significant negative impact relationship between them. Our high throughput sequencing (HTS) based research illustrated how the P. globosa bloom generated and its relationship with NO3--N and temperature of sea water in northern Beibu Gulf for the first time, and bringing hope for solving this big problem.

ecology↗

bioRxiv2018

The Dynamic Conformational Landscapes of the Protein Methyltransferase SETD8

Elucidating conformational heterogeneity of proteins is essential for understanding protein functions and developing exogenous ligands for chemical perturbation. While structural biology methods can provide atomic details of static protein structures, these approaches cannot in general resolve less populated, functionally relevant conformations and uncover conformational kinetics. Here we demonstrate a new paradigm for illuminating dynamic conformational landscapes of target proteins. SETD8 (Pr-SET7/SET8/KMT5A) is a biologically relevant protein lysine methyltransferase for in vivo monomethylation of histone H4 lysine 20 and nonhistone targets. Utilizing covalent chemical inhibitors and depleting native ligands to trap hidden high-energy conformational states, we obtained diverse novel X-ray structures of SETD8. These structures were used to seed massively distributed molecular simulations that generated six milliseconds of trajectory data of SETD8 in the presence or absence of its cofactor. We used an automated machine learning approach to reveal slow conformational motions and thus distinct conformational states of SETD8, and validated the resulting dynamic conformational landscapes with multiple biophysical methods. The resulting models provide unprecedented mechanistic insight into how protein dynamics plays a role in SAM binding and thus catalysis, and how this function can be modulated by diverse cancer-associated mutants. These findings set up the foundation for revealing enzymatic mechanisms and developing inhibitors in the context of conformational landscapes of target proteins.

biophysics↗

bioRxiv2018

Three-dimensional tissue stiffness mapping in the mouse embryo supports durotaxis during early limb bud morphogenesis

Numerous biophysical hypotheses invoke tissue stiffness as a key parameter for shaping tissue during development and for influencing cell behaviours during disease progression. However, currently available methods are insufficient to test hypotheses that concern the physical properties of bulk tissues. Here we introduce, validate and apply a new 3D magnetic device that generates a uniform magnetic field gradient within a space that is sufficient to accommodate a vertebrate, organ-stage embryo under live conditions. The device allows for rapid, nontoxic measurement of the spatial variation of absolute elastic modulus and viscosity deep within mesenchymal tissues and within epithelia. By applying the device to map the spatiotemporal variation of viscoelastic properties within the early mouse limb bud, we identified an anteriorly biased mesodermal stiffness gradient along which cells move collectively to shape the early bud. Tissue stiffness corresponds to the nascent expression domain of fibronectin that is Wnt5a-dependent. The findings challenge the notion that Wnt5a regulates cell movements by chemotaxis, and raises the possibility that Wnt5a modifies the tissue microenvironment to promote durotaxis in vivo. Importantly, the ability to precisely measure tissue stiffness in 3D has the potential to instigate and refine mechanisms of development and disease progression.

developmental biology↗

bioRxiv2018

tmap: topological analysis of population-scale microbiome data

Population-scale microbiome study poses specific challenges in data analysis, from enterotype analysis, identification of driver species, to microbiome-wide association of host covariates. Application of advanced data mining techniques to high-dimensional complex dataset is expected to meet the rapid advancement in large scale and integrative microbiome research. Here, we present tmap, a topological data analysis framework for population-scale microbiome study. This framework can capture complex shape of large scale microbiome data into a compressive network representation. We also develop network-based statistical analysis for driver species identification and microbiome-wide association analysis. tmap can be used for exploring variations in a population-scale microbiome landscape to study host-microbiome association.\n\nAvailability and implementationtmap is available at GitHub (https://github.com/GPZ-Bioinfo/tmap), accompanied with online documentation and tutorial (http://tmap.readthedocs.io).\n\nContacthttp://hk.zhou@siat.ac.cn

bioinformatics↗

bioRxiv2018

Dynamic plant height QTL revealed in maize through remote sensing phenotyping using a high-throughput unmanned aerial vehicle (UAV)

Plant height is the key factor for plant architecture, biomass and yield in maize (Zea mays). In this study, plant height was investigated using unmanned aerial vehicle high-throughput phenotypic platforms (UAV-HTPPs) for maize diversity inbred lines at four important growth stages. Using an automated pipeline, we extracted accurate plant heights. We found that in temperate regions, from sowing to the jointing period, the growth rate for temperate maize was faster than tropical maize. However, from jointing to flowering stage, tropical maize maintained a vigorous growth state, and finally resulted in a taller plant than temperate lines. Genome-wide association study for temperate, tropical and both groups identified a total of 238 quantitative trait locus (QTLs) for the 16 plant height related traits over four growth periods. And, we found that plant height at different stages were controlled by different genes, for example, PIN1 controlled plant height at the early stage and PIN11 at the flowering stages. In this study, the plant height data collected by the UAV-HTTPs were credible and the genetic mapping power is high, indicating that the application of this UAV-HTTPs into the study of plant height will have great prospects.\n\nHighlightWe used UAV-based sensing platform to investigate plant height over 4 growth stages for different maize populations, and detected numbers of reliable QTLs using GWAS.

genetics↗

bioRxiv2018

A genetically-encoded fluorescent acetylcholine indicator

Acetylcholine (ACh) regulates a diverse array of physiological processes throughout the body, yet cholinergic transmission in the majority of tissues/organs remains poorly understood due primarily to the limitations of available ACh-monitoring techniques. We developed a family of G-protein-coupled receptor activation-based ACh sensors (GACh) with sensitivity, specificity, signal-to-noise ratio, kinetics and photostability suitable for monitoring ACh signals in vitro and in vivo. GACh sensors were validated with transfection, viral and/or transgenic expression in a dozen types of neuronal and non-neuronal cells prepared from several animal species. In all preparations, GACh sensors selectively responded to exogenous and/or endogenous ACh with robust fluorescence signals that were captured by epifluorescent, confocal and/or two-photon microscopy. Moreover, analysis of endogenous ACh release revealed firing pattern-dependent release and restricted volume transmission, resolving two long-standing questions about central cholinergic transmission. Thus, GACh sensors provide a user-friendly, broadly applicable toolbox for monitoring cholinergic transmission underlying diverse biological processes.

neuroscience↗

bioRxiv2018

A Chemical Biology Toolbox for the Study of Protein Methyltransferases and Epigenetic Signaling

Protein methyltransferases (PMTs) comprise a major class of epigenetic regulatory enzymes with therapeutic relevance. Here we present a collection of chemical probes and associated reagents and data to elucidate the function of human and murine PMTs in cellular studies. Our collection provides inhibitors and antagonists that together modulate most of the key regulatory methylation marks on histones H3 and H4, providing an important resource for modulating cellular epigenomes. We describe a comprehensive and comparative characterization of the probe collection with respect to their potency, selectivity, and mode of inhibition. We demonstrate the utility of this collection in CD4+ T cell differentiation assays revealing the remarkable potential of individual probes to alter multiple T cell subpopulations with important implications for T cell-mediated processes such as inflammation and immuno-oncology. In particular, we demonstrate a role for DOT1L in limiting Th1 cell differentiation and maintaining lineage integrity.

biochemistry↗