Biology subjects

Zheng, H.

Publications and source records attributed to Zheng, H..

At least 163 records · Page 9Linked to original sources

bioRxiv2022

A Cre-Driver Rat Model for Anatomical and Functional Analysis of Glucagon (Gcg)-Expressing Cells in the Brain and Periphery

ObjectiveThe glucagon gene (Gcg) encodes preproglucagon, which is cleaved to form glucagon-like peptide 1 (GLP1) and other mature signaling molecules implicated in metabolic functions. To date there are no transgenic rat models available for precise manipulation of GLP1-expressing cells in the brain and periphery. MethodsTo visualize and manipulate Gcg-expressing cells in rats, CRISPR/Cas9 was used to express iCre under control of the Gcg promoter. Gcg-Cre rats were bred with tdTomato reporter rats to tag Gcg-expressing cells. Cre-dependent AAVs and RNAscope in situ hybridization were used to evaluate the specificity of iCre expression by GLP1 neurons in the caudal nucleus of the solitary tract (cNTS) and intermediate reticular nucleus (IRt), and by intestinal and pancreatic secretory cells. Food intake was assessed in heterozygous (Het) Gcg-Cre rats after chemogenetic stimulation of cNTS GLP1 neurons expressing an excitatory DREADD. ResultsWhile genotype has minimal effect on body weight or composition in chow-fed Gcg-Cre rats, homozygous (Homo) rats have lower plasma glucose levels. In neonatal and adult Gcg-Cre/tdTom rats, reporter-labeled cells are present in the cNTS and IRt, and in additional brain regions (e.g., basolateral amygdala, piriform cortex) that lack detectable Gcg mRNA in adults but display transient developmental or persistently low Gcg expression. Compared to wildtype (WT) rats, hindbrain Gcg mRNA and GLP1 protein in brain and plasma are markedly reduced in Homo Gcg-Cre rats. Chemogenetic stimulation of cNTS GLP1 neurons reduced overnight chow intake in males but not females, the effect in males was blocked by antagonism of central GLP1 receptors, and hypophagia was enhanced when combined with a subthreshold dose of cholecystokinin-8 to stimulate gastrointestinal vagal afferents. ConclusionsGcg-Cre rats are a novel and valuable experimental tool for analyzing the development, anatomy, and function of Gcg-expressing cells in the brain and periphery. In addition, Homo Gcg-Cre rats are a unique model for assessing the role of Gcg-encoded proteins in glucose homeostasis and energy metabolism. HighlightsO_LIA transgenic Gcg-Cre rat model expresses iCre under control of the Gcg promoter C_LIO_LIiCre is expressed by GLP1-positive cells in the hindbrain, pancreas, and intestine C_LIO_LIAdditional brain regions display transient and/or very low levels of Gcg expression C_LIO_LI+/+ Gcg-Cre rats display a marked knockdown of Gcg mRNA and GLP1 protein C_LIO_LIChemogenetic activation of Gcg neurons suppresses food intake in +/- Gcg-Cre rats C_LI

neuroscience↗

bioRxiv2022

Memory CD4 T cell subset organization in the female reproductive tract is regulated via the menstrual cycle through CCR5 signaling

Despite their importance for immunity against sexually transmitted infections (STIs), the composition of the female reproductive tract (FRT) memory CD4 T cell population in response to changes in the local tissue environment during the menstrual cycle remains poorly defined. Here we show that across humans, non-human primates (NHP), and mice, FRT CD4 T cells comprise distinct subsets corresponding to migratory memory (TMM) and resident memory (TRM) cells. TMM display tissue-itinerant trafficking characteristics, restricted FRT tissue distribution, with distinct transcriptional properties and effector responses to infection. CD4 T cell subset fluctuations synchronized with cycle-driven proinflammatory changes within the local tissue environment and oral administration of a CCR5 antagonist inhibited cycle phase-specific migratory T cell surveillance. This study provides novel insights into the dynamic nature of FRT memory CD4 T cells and identifies the menstrual cycle as a key regulator of memory T cell defense at the site of STI exposure. SummaryThe menstrual cycle regulates memory T cell surveillance.

immunology↗

bioRxiv2022

Multiomics reveal that silk fibroin and sericin differentially potentiate the paracrine functions of mesenchymal stem cells and enhance tissue regeneration

Silk fibroin (SF) and sericin (SS), the two major proteins of silk, are attractive biomaterials that show great potential in regenerative medicine. However, their biochemical interactions with stem cells were not fully understood. Here, we employed multiomics to obtain a global view of the triggered cellular processes and pathways of MSCs by SF and SS. Integrated RNA-seq and proteomics revealed that SF and SS strongly enhanced the paracrine activity of MSCs through differentially activating integrin and glycolytic pathways, rather than directly regulating stem cell fate to initiate multiple but distinct biological processes in MSCs. Those specific paracrine signals of MSCs stimulated by SF and SS effectively promoted skin wound healing by influencing the behaviors of multiple resident cells in skin wound microenvironments. This study provides comprehensive and reliable insights into the cellular interactions with SF and SS, enabling future development of silk-based therapeutics for tissue engineering and stem cell therapy.

bioengineering↗

bioRxiv2022

Magnesium and the magnesium transporter UEX regulate sleep via Ca2+-dependent CREB signaling and a CNK-ERK pathway

Magnesium and its related preparations are already in medical use and have recognized therapeutic effects on sleep disorders. However, its underlying molecular mechanisms remain unclear. Here, using Drosophila as a model, we found that RNAi-mediated knockdown of Uex, the homologous gene of magnesium transporters of the Cyclin M family (CNNM) causes increased daily total sleep. Ectopic-expression of CNNM1 can rescue the sleep phenotype in Uex knockdown flies. UEX exhibits rhythmic oscillations in the brain and affects the efflux of cellular Mg2+. Knockdown of Uex in the nervous system influences Ca2+-mediated CREB signaling and neuroplasticity. Additionally, Uex physically interacts with CNK, the upstream regulator of ERK pathway. Similar effects on sleep are observed with knockdown of Cnk in flies. We propose that the UEX regulates sleep through its downstream Ca2+-dependent CREB signaling and a CNK-ERK pathway. Our findings may provide new insight into mechanisms of magnesium and magnesium transporter related sleep disorder.

genetics↗

bioRxiv2022

Molecular characters and phylogenetic analysis of Clostridium perfringens from different regions in China, from 2013 to 2021

Clostridium perfringens (C. perfringens) is a significant foodborne pathogen and a common cause of intestinal diseases in both animals and humans. Altogether, 186 isolates were obtained from humans (n = 147), animals (n = 25), and food (n = 14), comprising 174 type A strains (93.55%), 11 type F strains (5.91%), and one type D strain (0.54%); and were analyzed by multilocus sequence typing (MLST) and antimicrobial susceptibility testing. Additionally, some specific ST complexes were analyzed by cgMLST and cgSNP to investigate genetic relatedness. MLST indicated the most prevalent STs of C. perfringens of human and animal origin were as follows: ST221 (5/147), ST62 (4/147), ST408 (4/147), and ST493 (4/147) were predominant in humans, while ST479 (5/25) was the major type in animals. Within the same ST complex, genetically unrelated relationships or potential clustering/transmission events were further recognized by cgMLST and cgSNP, illustrating that these two methods are valuable in defining outbreaks and transmission events. All tested isolates were susceptible to vancomycin and meropenem. The rates of resistance to metronidazole, penicillin, cefoxitin, moxifloxacin, and clindamycin were low (metronidazole: 1.08%; penicillin: 9.68%; cefoxitin: 0.54%; moxifloxacin: 6.45%; and chloramphenicol: 3.76%). Interestingly, 49.66% of human origin were clindamycin-resistant, and 18.2% were penicillin-insensitive. Importantly, the portion of MDR isolates was significantly lower than in previous reports. The study provides an overview of the epidemiological characteristics of C. perfringens with different origins and hosts in China. C. perfringens demonstrated remarkable genetic diversity and distinct molecular features compared to antibiotic-resistance profiles from other studies. IMPORTANCEC. perfringens is one of the most common bacterial causes of foodborne illness globally, responsible for several food-poisoning outbreaks each year. This study provides an overview of C. perfringens isolates from different hosts and regions in China according to MLST, antibiotic-resistance characters, cgMLST, and cgSNP analyses, showing high genetic diversity and identifying potential clustering and transmission events. The antimicrobial profile in this study was distinct from that of a previous report with a much lower MDR rate, indicating that C. perfringens in China needs further investigation.

molecular biology↗

bioRxiv2022

Predicting Dementia Severity by Merging Anatomical and Diffusion MRI with Deep 3D Convolutional Neural Networks

Machine learning methods have been used for over a decade for staging and subtyping a variety of brain diseases, offering fast and objective methods to classify neurodegenerative diseases such as Alzheimers disease (AD). Deep learning models based on convolutional neural networks (CNNs) have also been used to infer dementia severity and predict future clinical decline. Most CNN-based deep learning models use T1-weighted brain MRI scans to identify predictive features for these tasks. In contrast, we examine the added value of diffusion-weighted MRI (dMRI) - a variant of MRI, sensitive to microstructural tissue properties - as an additional input in CNN-based models of dementia severity. dMRI is sensitive to microstructural brain abnormalities not evident on standard anatomical MRI. By training CNNs on combined anatomical and diffusion MRI, we hypothesize that we could boost performance when predicting widely-used clinical assessments of dementia severity, such as individuals scores on the ADAS11, ADAS13, and MMSE (mini-mental state exam) clinical scales. For benchmarking, we evaluate CNNs that use T1-weighted MRI and dMRI to estimate "brain age" - the task of predicting a persons chronological age from their neuroimaging data. To assess which dMRI-derived maps were most beneficial, we computed DWI-derived diffusion tensor imaging (DTI) maps of mean and radial diffusivity (MD/RD), axial diffusivity (AD) and fractional anisotropy (FA) for 1198 elderly subjects (age: 74.35 +/- 7.74 yrs.; 600 F/598 M, with a distribution of 636 CN/421 MCI/141 AD) from the Alzheimers Disease Neuroimaging Initiative (ADNI). We tested both 2D Slice CNN and 3D CNN neural network models for the above predictive tasks. Our results suggest that for at least some deep learning architectures, diffusion-weighted MRI may enhance performance for several AD-relevant deep learning tasks relative to using T1-weighted images alone.

neuroscience↗

bioRxiv2022

Single-cell Atlas of Human Fetal Cerebellum Decoding Medulloblastoma Origin and Oncogenesis

Medulloblastoma (MB) is the most common malignant childhood brain tumor1,2, yet the origin of the most aggressive subgroup-3 form remains elusive, impeding development of effective targeted treatments. Previous analyses of mouse cerebella3,4 or human counterparts from frozen tissue nuclei5 have not fully defined the compositional heterogeneity of MBs. Here, we undertook an unprecedented single-cell profiling of freshly-isolated human fetal cerebella to establish a reference map delineating hierarchical cellular states in MBs. We identified a unique transitional cerebellar progenitor connecting neural stem cells to neuronal lineages in developing fetal cerebella. Intersectional analysis revealed that the transitional progenitors were enriched in aggressive MB subgroups, including group-3 and metastatic tumors. Single-cell multi-omics revealed underlying regulatory networks in the transitional progenitor populations, including transcriptional determinants HNRNPH1 and SOX11, which are correlated with clinical prognosis in group-3 MBs. Genomic and Hi-C profiling identified de novo long-range chromatin-loops juxtaposing HNRNPH1/SOX11-targeted super-enhancers to cis-regulatory elements of MYC, an oncogenic driver for group-3 MBs. Targeting the transitional progenitor regulators inhibited MYC expression and MYC-driven group-3 MB growth. Our integrated single-cell atlases of human fetal cerebella and MBs reveal potential cell populations predisposed to transformation and regulatory circuitries underlying tumor cell states and oncogenesis, highlighting hitherto unrecognized transitional progenitor intermediates predictive of disease prognosis and potential therapeutic vulnerabilities.

cancer biology↗

bioRxiv2022

Outer membrane utilisomes mediate oligosaccharide uptake in gut Bacteroidetes

Bacteroidetes are abundant members of the human microbiota, with species occupying the distal gut capable of utilising a myriad of diet- and host-derived glycans. Transport of glycans across the outer membrane (OM) of these bacteria is mediated by SusCD protein complexes, comprising a membrane-embedded barrel and a lipoprotein lid, that are thought to operate via a pedal-bin mechanism in which the lids open and close to facilitate substrate binding. However, additional cell surface-exposed lipoproteins, namely surface glycan binding proteins and glycoside hydrolases, play critical roles in the capture and processing of large glycan chains into transport-competent substrates. Despite constituting a crucial mechanism of nutrient acquisition by our colonic microbiota, the interactions between these components in the OM are poorly understood. Here we show that for the levan and dextran utilisation systems of Bacteroides thetaiotaomicron, the additional OM components assemble on the core SusCD transporter, forming stable glycan utilising machines which we term utilisomes. Single particle electron cryogenic electron microscopy (cryo-EM) structures in the absence and presence of substrate reveal concerted conformational changes that rationalise the role of each component for efficient nutrient capture, as well as providing a direct demonstration of the pedal bin mechanism of substrate capture in the intact utilisome.

microbiology↗

bioRxiv2022

High-throughput nanopore sequencing of Treponema pallidum tandem repeat genes arp and tp0470 reveals clade-specific patterns and recapitulates global whole genome phylogeny

Sequencing of most Treponema pallidum (T. pallidum) genomes excludes repeat regions in tp0470 and the tp0433 gene, encoding the acidic repeat protein (arp). As a first step to understanding the evolution and function of these genes and the proteins they encode, we developed a protocol to nanopore sequence tp0470 and arp genes from 212 clinical samples collected from ten countries on six continents. Both tp0470 and arp repeat structures recapitulate the whole genome phylogeny, with subclade-specific patterns emerging. The number of tp0470 repeats is on average appears to be higher in Nichols-like clade strains than in SS14-like clade strains. Consistent with previous studies, we found that 14-repeat arp sequences predominate across both major clades, but the combination and order of repeat type varies among subclades, with many arp sequence variants limited to a single subclade. Although strains that were closely related by whole genome sequencing frequently had the same arp repeat length, this was not always the case. Structural modelling of TP0470 suggested that the eight residue repeats form an extended -helix, predicted to be periplasmic. Modeling of the ARP revealed a C-terminal sporulation-related repeat (SPOR) domain, predicted to bind denuded peptidoglycan, with repeat regions possibly incorporated into a highly charged {beta}- sheet. Outside of the repeats, all TP0470 and ARP amino acid sequences were identical. Together, our data, along with functional considerations, suggests that both TP0470 and ARP proteins may be involved in T. pallidum cell envelope remodeling and homeostasis, with their highly plastic repeat regions playing as-yet-undetermined roles.

microbiology↗

bioRxiv2022

Potent Bacterial Vaccines Require FcγRIIB-mediated Pathogen Capture by Liver Sinusoidal Endothelium

Certain vaccines are more effective than others against microbial infections, but the molecular mechanisms separating the two types of vaccines are largely undefined. Here, by comparing two vaccines of Streptococcus pneumoniae with identical antigens but different efficacies (pneumococcal conjugate vaccine - PCV13 and pneumococcal polysaccharide vaccine - PPV23), we reveal that superior vaccine protection against blood-borne bacteria is primarily achieved by activating pathogen capture of the sinusoidal endothelial cells (ECs) in the liver. Consistent with its superior protection in humans, PCV13 confers a more potent protection than PPV23 against pneumococcal infection in mice. In vivo real-time imaging and genetic mutagenesis revealed that PCV13 activates both liver ECs and resident macrophages Kupffer cells (KCs) to capture IgG-coated bacteria via IgG Fc gamma receptor (Fc{gamma}R). In particular, the Fc{gamma}RIIB-mediated capture by ECs is responsible for PCV13-induced superior protection. In contrast, PPV23 only activates KCs (but not ECs) to achieve a less effective pathogen capture and protection through complement receptor-mediated recognition of IgM- and C3-coated bacteria. These liver-based vaccine protection mechanisms are also found with the vaccines of Neisseria meningitidis and Klebsiella pneumoniae, another two important invasive human pathogens. Our findings have uncovered a novel EC- and Fc{gamma}RIIB-mediated mechanism in the liver for more efficacious vaccine protection. These findings can serve as in vivo functional readouts to evaluate vaccine efficacy and guide the future vaccine development. One Sentence SummaryVaccine efficacy is defined by Fc{gamma}RIIB-mediated capture of antibody-coated bacteria via liver sinusoidal endothelial cells.

immunology↗

bioRxiv2022

Vitamin C is an efficient natural product for prevention of SARS-CoV-2 infection by targeting ACE2 in both cell and in vivo mouse models

ACE2 is a major receptor for cell entry of SARS-CoV-2. Despite advances in targeting ACE2 to inhibit SARS-CoV-2s binding, how to efficiently and flexibly control ACE2 levels for prevention of SARS-CoV-2 infection has not been explored. Here, we revealed Vitamin C (VitC) administration as an effective strategy to prevent SARS-CoV-2 infection. VitC reduced ACE2 protein levels in a dose-dependent manner, while partial reduction of ACE2 can greatly restrict SARS-CoV-2 infection. Further studies uncovered that USP50 is a crucial regulator of ACE2 protein levels, and VitC blocks the USP50-ACE2 interaction, thus promoting K48-linked polyubiquitination at Lys788 and degradation of ACE2, without disrupting ACE2 transcriptional expression. Importantly, VitC administration reduced host ACE2 and largely blocked SARS-CoV-2 infection in mice. This study identified an in vivo ACE2 balance controlled by both USP50 and an essential nutrient VitC, and revealed a critical role and application of VitC in daily protection from SARS-CoV-2 infection. HighlightsO_LIVitC reduces ACE2 protein levels in a dose-dependent manner C_LIO_LIVitC and USP50 regulate K48-linked ubiquitination at Lys788 of ACE2 C_LIO_LIVitC blocks the interaction between USP50 and ACE2 C_LIO_LIVitC administration lowers host ACE2 and prevents SARS-CoV-2 infection in vivo C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=151 SRC="FIGDIR/small/499651v1_ufig1.gif" ALT="Figure 1"> View larger version (60K): org.highwire.dtl.DTLVardef@196682borg.highwire.dtl.DTLVardef@190f14dorg.highwire.dtl.DTLVardef@d22b59org.highwire.dtl.DTLVardef@1c0faa_HPS_FORMAT_FIGEXP M_FIG C_FIG The deubiquitinase USP50 controls ACE2 protein stability and levels, while Vitamin C blocks the USP50-ACE2 interaction and therefore results in ACE2 degradation, offering a flexible and efficient approach to protection of the host from SARS-CoV-2 infection.

microbiology↗

bioRxiv2022

The specificity of different-distance connections in human structural connectomes

Brain structural connectomes underpin complex cognitive processes. To date, abundant organizational features have been distilled by network-based tools, including hubs, modules, and small-worldness. However, these features are often devoid of spatial characteristics which directly shape connection formation. By considering the spatial embedding of brain networks, we reveal the connection specificity, that is, the similarity of similar-distance connections and the dissimilarity of different-distance connections. It is induced by the whole-brain connection length distribution, allowing areas to send and receive diverse signals through different-distance connections. Based on it, areas functional repertoires are associated with their connection length profiles, and meanwhile, length dispersion and clustering coefficients can be integrated into a hierarchy whose age-related degeneration may be related to cognitive decline. These results construct a putative bridge between brain spatial, topological, and functional features, expanding our understanding of how different architectures complement and reinforce each other to achieve complicated brain functions.

neuroscience↗

bioRxiv2022

Enhanced brain structure-function tethering in transmodal cortex revealed by high-frequency eigenmodes

The brains structural connectome supports signal propagation between neuronal elements, shaping diverse coactivation patterns that can be captured as functional connectivity. While the link between structure and function remains an ongoing challenge, the prevailing hypothesis is that the structure-function relationship may itself be gradually decoupled along a macroscale functional gradient spanning unimodal to transmodal regions. However, this hypothesis is strongly constrained by the underlying models which may neglect requisite signaling mechanisms. Here, we transform the structural connectome into a set of orthogonal eigenmodes governing frequency-specific diffusion patterns and show that regional structure-function relationships vary markedly under different signaling mechanisms. Specifically, low-frequency eigenmodes, which are considered sufficient to capture the essence of the functional network, contribute little to functional connectivity reconstruction in transmodal regions, resulting in structurefunction decoupling along the unimodal-transmodal gradient. In contrast, high-frequency eigenmodes, which are usually on the periphery of attention due to their association with noisy and random dynamical patterns, contribute significantly to functional connectivity prediction in transmodal regions, inducing gradually convergent structure-function relationships from unimodal to transmodal regions. Although the information in high-frequency eigenmodes is weak and scattered, it effectively enhances the structure-function correspondence by 35% in unimodal regions and 56% in transmodal regions. Altogether, our findings suggest that the structure-function divergence in transmodal areas may not be an intrinsic property of brain organization, but can be narrowed through multiplexed and regionally specialized signaling mechanisms.

neuroscience↗

bioRxiv2022

Prediction of HLA genotypes from single-cell transcriptome data

The human leukocyte antigen (HLA) locus plays a central role in adaptive immune function and has significant clinical implications for tissue transplant compatibility and allelic disease associations. Studies using bulk-cell RNA sequencing have demonstrated that HLA transcription may be regulated in an allele-specific manner and single-cell RNA sequencing (scRNA-seq) has the potential to better characterize these expression patterns. However, quantification of allele-specific expression (ASE) for HLA loci requires sample-specific reference genotyping due to extensive polymorphism. While genotype prediction from bulk RNA sequencing is well described, the feasibility of predicting HLA genotypes directly from single-cell data is unknown. Here we evaluate and expand upon several computational HLA genotyping tools by comparing predictions from human single-cell data to gold-standard, molecular genotyping. The highest 2-field accuracy averaged across all loci was 76% by arcasHLA and increased to 86% using a composite model of multiple genotyping tools. We also developed a highly accurate model (AUC 0.93) for predicting HLA-DRB345 copy number in order to improve genotyping accuracy of the HLA-DRB locus. Genotyping accuracy improved with read depth and was reproducible at repeat sampling. Using a metanalytic approach, we also show that HLA genotypes from PHLAT and OptiType can generate ASE ratios that are highly correlated (R2 = 0.8 and 0.94, respectively) with those derived from gold-standard genotyping. Highlights- Benchmarking of HLA genotype prediction accuracy from 5- and 3-based single-cell RNA-seq data compared to molecular HLA genotyping - Quantification of transcript coverage by 5- and 3-based single cell sequencing methods - Accurate prediction of complex HLA-DRB345 copy numbers using supervised learning - Balancing accuracy and performance through composite HLA genotyping - Meta-analytic approach to summarizing allele-specific expression of HLA genotypes at single-cell level

bioinformatics↗

bioRxiv2022

A therapeutically targetable NOTCH1-SIRT1-KAT7 axis in T-cell Leukemia

T-cell Acute Lymphoblastic Leukemia (T-ALL) is a NOTCH1-driven disease in need of novel therapies. Here, we identify a NOTCH1-SIRT1-KAT7 link as a therapeutic vulnerability in T-ALL, in which SIRT1 is overexpressed downstream of a novel NOTCH1-bound enhancer. SIRT1 loss impairs leukemia generation, while SIRT1 overexpression accelerates leukemia and confers resistance to NOTCH1 inhibition in a deacetylase-dependent manner. Moreover, secondary SIRT1 loss extends survival and synergizes with NOTCH1 inhibition. Global acetyl-proteomics upon SIRT1 loss uncovered hyperacetylation of KAT7 and BRD1, subunits of a histone acetyltransferase complex targeting H4K12. Metabolic and gene expression profiling revealed a metabolic crisis together with a transcriptional signature resembling KAT7 deletion. Consistently, SIRT1 loss resulted in reduced H4K12ac, and overexpression of a non-acetylatable KAT7 mutant partly rescued SIRT1 loss-induced proliferation defects. The newly unveiled NOTCH1-SIRT1-KAT7 axis uncovers novel therapeutic targets in T-ALL and reveals a circular feedback mechanism balancing deacetylase/acetyltransferase activation with potentially broad relevance in cancer. Statement of significanceWe identified a novel axis in T-ALL whereby NOTCH1 activates SIRT1 through an enhancer region, and SIRT1 deacetylates and activates KAT7. Targeting SIRT1 shows antileukemic effects, partly mediated by KAT7 inactivation. Our results identify novel therapeutic targets and uncover a rheostat mechanism between deacetylase/acetyltransferase activities with potentially broader cancer relevance.

cancer biology↗

bioRxiv2022

INSISTC: Incorporating Network Structure Information for Single-Cell Type Classification

MotivationUncovering gene regulatory mechanisms in individual cells can provide insight into cell heterogeneity and function. Recent accumulated single-cell RNA sequencing data have made it possible to analyze gene regulation at single-cell resolution. On the other hand, understanding cell-type-specific gene regulation can also assist in more accurate cell type and state identification. Computational approaches utilizing gene regulatory relationships for single-cell type classification are under development. Methods pioneering in integrating gene regulatory mechanism discovery with cell-type classification encounter challenges such as how to accurately determine gene regulatory relation-ships and how to incorporate gene regulatory network structure into consideration. ResultsWe developed a computational method to incorporate gene regulatory network structure information for single-cell type classification (INSISTC). INSISTC is capable of identifying cell-type-specific gene regulatory mechanisms while performing single cell type classification. Tested on three mouse scRNA-Seq datasets, including thousands of single-cell samples, INSISTC demonstrated its accuracy in cell type classification and its potential for providing insight into molecular mechanisms specific to individual cells. In comparison with the alternative methods, INSISTC demonstrated its complementary performance for gene regulation interpretation. Availabilityhttps://hulab.ucf.edu/research/projects/INSISTC/ Contacthaihu@cs.ucf.edu or xiaoman@mail.ucf.edu Supplementary informationSupplementary data are available at xxxxxx online.

bioinformatics↗

bioRxiv2022

Evolutionarily conserved effects of Notch signaling drive intestinal graft-versus-host disease in mice and non-human primates

Notch signaling promotes T-cell pathogenicity and graft-versus-host disease (GVHD) after allogeneic hematopoietic cell transplantation (allo-HCT) in mice, with a dominant role for the Delta-like ligand DLL4. To assess if Notchs effects are evolutionarily conserved and identify key mechanisms, we studied antibody-mediated DLL4 blockade in a non-human primate model similar to human allo-HCT. Short-term DLL4 blockade improved post-transplant survival with striking, durable protection from gastrointestinal GVHD, out of proportion to other disease sites. Unlike prior immunosuppressive strategies, anti-DLL4 interfered with a T-cell transcriptional program associated with intestinal infiltration. In cross-species investigations, Notch inhibition decreased surface abundance of the gut-homing integrin a4b7 in conventional T-cells via b1 competition for a4 binding, while preserving a4b7 in regulatory T-cells. Thereby, DLL4/Notch blockade decreased effector T-cell infiltration into the gut, with increased regulatory to conventional T-cell ratios early after allo-HCT. Our results identify a conserved, biologically unique and targetable role of DLL4/Notch signaling in GVHD. One Sentence SummaryNotch signaling promotes pathogenic effector T cell infiltration of the intestine during acute graft-versus-host disease.

immunology↗

bioRxiv2022

A Systematic Evaluation of the Computational Tools for Ligand-receptor-based Cell-Cell Interaction Inference

Cell-cell interactions (CCIs) are essential for multicellular organisms to coordinate biological processes and functions. Many molecules and signaling processes can mediate CCIs. One classical type of CCI mediator is the interaction between secreted ligands and cell surface receptors, i.e., ligand-receptor (LR) interaction. With the recent development of single-cell technologies, a large amount of single-cell RNA Sequencing (scRNA-Seq) data has become widely available. This data availability motivated the single-cell-resolution study of CCIs, particularly LR-based CCIs. Dozens of computational methods and tools have been developed to predict CCIs by identifying LR-based CCIs. Many of these tools have been theoretically reviewed. However, there is little study on current LR-based CCI prediction tools regarding their performance and running results on public scRNA-Seq datasets. In this work, to fill this gap, we tested and compared nine of the most recent computational tools for LR-based CCI prediction. We used fifteen mouse scRNA-Seq samples that correspond to nearly 100K single cells under different experimental conditions for testing and comparison. Besides briefing the methodology used in these nine tools, we summarized the similarities and differences of these tools in terms of both LR prediction and CCI inference between cell types. We provided insight into using these tools to make meaningful discoveries in understanding cell communications.

bioinformatics↗