Biology subjects

Hu, Y.

Publications and source records attributed to Hu, Y..

At least 577 records · Page 32Linked to original sources

bioRxiv2020

Single-cell RNA sequencing deconvolutes the in vivo heterogeneity of human bone marrow-derived mesenchymal stem cells

Bone marrow-derived mesenchymal stem cells (BM-MSCs) are multipotent stromal cells, which have a critical role in the maintenance of skeletal tissues such as bone, cartilage, and the fat found in bone marrow. In addition to providing microenvironmental support for hematopoietic processes, BM-MSCs can differentiate into various mesodermal lineages including osteoblast/osteocyte, chondrocyte, and adipocyte cells that are crucial for bone metabolism. While BM-MSCs have high cell-to-cell heterogeneity in gene expression, the cell subtypes that contribute to this heterogeneity in vivo in humans have not been characterized. To investigate the transcriptional diversity of BM-MSCs, we applied single-cell RNA sequencing (scRNA-seq) on freshly isolated CD271+ BM-derived mononuclear cells (BM-MNCs) from two human subjects. We successfully identified LEPRhiCD45low BM-MSCs within the CD271+ BM-MNC population, and further codified the BM-MSCs into distinct subpopulations corresponding to the osteogenic, chondrogenic, and adipogenic differentiation trajectories, as well as terminal-stage quiescent cells. Biological functional annotations of transcriptomes suggest that osteoblast precursors may induce angiogenesis coupled with osteogenesis, and chondrocyte precursors may have the potential to differentiate into myocytes. We discovered transcripts for several cluster of differentiation (CD) markers that were highly expressed (e.g., CD167b, CD91, CD130 and CD118) or absent (e.g., CD74, CD217, CD148 and CD68) in BM-MSCs and could be novel markers for human BM-MSC purification. This study is the first systematic in vivo dissection of human BM-MSCs cell subtypes at the single-cell resolution, revealing insight into the extent of their cellular heterogeneity and bone homeostasis.

cell biology↗

bioRxiv2020

Interpersonal brain synchronization with instructor compensates for learner's sleep deprivation in interactive learning

Recent advances shifted the focus on single-brain functioning toward two-brain communication during learning interactions, following the demonstration that interpersonal brain synchronization (IBS) can track instructor-learner information exchange. Here, we investigated (i) whether sleep deprivation (SD) that potentially impacts both social interactions and learning abilities modulates IBS, and (ii) conversely whether and to what extent IBS might compensate for SD-related learning deficits. Instructors (always with regular sleep, RS) were asked to teach numerical reasoning strategies to learners (either SD or RS), during which the activity of both brains was simultaneously recorded using functional near-infrared spectroscopy (fNIRS). SD learners initially performed below their baseline level, worse than RS learners, but learning improvement was comparable between RS and SD conditions after learning with the instructor. IBS within the instructor-learner dyads was higher in the SD (vs. RS) condition in the left inferior frontal cortex. In addition, clustered IBS (estimated by nonnegative matrix factorization) was correlated with performance improvement. Finally, Granger Causality analyses revealed biased causality with higher instructor-to-learner than learner-to-instructor directionality in brain signal processing. Together, these results indicate that SD-related learning deficits can to some extent be compensated via interactions with an instructor, as reflected by increased IBS and preserved learning ability. It suggests an essential role of the instructor in driving synchrony between teaching and SD learning brains during interactions.

neuroscience↗

bioRxiv2020

Bayesian genome scale modelling identifies thermal determinants of yeast metabolism

The molecular basis of how temperature affects cell metabolism has been a long-standing question in biology, where the main obstacles are the lack of high-quality data and methods to associate temperature effects on the function of individual proteins as well as to combine them at a systems level. Here we develop and apply a Bayesian modeling approach to resolve the temperature effects in genome scale metabolic models (GEM). The approach minimizes uncertainties in enzymatic thermal parameters and greatly improves the predictive strength of the GEMs. The resulting temperature constrained yeast GEM uncovered enzymes that limit growth at superoptimal temperatures, and squalene epoxidase (ERG1) was predicted to be the most rate limiting. By replacing this single key enzyme with an ortholog from a thermotolerant yeast strain, we obtained a thermotolerant strain that outgrew the wild type, demonstrating the critical role of sterol metabolism in yeast thermosensitivity. Therefore, apart from identifying thermal determinants of cell metabolism and enabling the design of thermotolerant strains, our Bayesian GEM approach facilitates modelling of complex biological systems in the absence of high-quality data and therefore shows promise for becoming a standard tool for genome scale modeling.

systems biology↗

bioRxiv2020

Site-specific covalent labeling of large RNAs with nanoparticles empowered by expanded genetic alphabet transcription

Conjugation of RNAs with nanoparticles is of significant importance for its numerous applications in biology and medicine, which however remains challenging, especially for large ones. So far, the majority of RNA labeling rely on solid-phase chemical synthesis, which is generally limited to RNAs smaller than 100 nts. We here present an efficient and generally applicable labeling strategy for site-specific covalent conjugation of large RNAs with gold nanoparticle (AuNP) empowered by expanded genetic alphabet transcription. We synthesize an amine-derivatized TPT3 (TPT3A), which are site-specifically incorporated into a 97-nt 3SL RNA and a 719-nt mini genomic RNA (DENV-mini) from Dengue virus serotype 2 (DENV2) by standard in vitro transcription with expanded genetic alphabet containing the A-T, G-C natural base pairs and the TPT3-NaM unnatural base pair. TPT3 modification cause minimal structural perturbations to the RNAs by small angle X-ray scattering. The purified TPT3A-modified RNAs are covalently conjugated with mono-Sulfo-NHS-Nanogold nanoparticles via the highly selective amine-NHS ester reaction and purified under non-denaturing conditions. We demonstrate the application of the AuNP-RNA conjugates in large RNA structural biology by an emerging molecular ruler, X-ray scattering interferometry (XSI). The inter-nanoparticle distance distributions in the 3SL and DENV-mini RNAs derived from XSI measurements support the hypothetical model of flavivirus genome circularization, thus validate the applicability of this novel labeling strategy. The presented strategy overcomes the size constraints in conventional RNA labeling strategies, and is expected to have wide applications in large RNA structural biology and RNA nanotechnology. Significance StatementWe present a site-specific labeling strategy for large RNAs by T7 transcription with expanded genetic alphabet containing TPT3-NaM unnatural base pair. The applicability of this labeling strategy is validated by X-ray scattering interferometry measurements on a 97-nt and a 719-nt RNAs. This strategy can be applicable to natural RNAs or artificial RNA nanostructures with sizes from tens up to thousands of nucleotides, or covalent conjugation of RNAs with other metal nanoparticles. The usage of a far upstream forward primer during PCR enables easy purification of RNA from DNA templates, the non-denaturing conditions for conjugation reactions and purification avoids potential large RNA misfolding. This labeling strategy expands our capability to site-specifically conjugate RNA with nanoparticles for many applications.

biophysics↗

bioRxiv2020

CytoTalk: De novo construction of signal transduction networks using single-cell RNA-Seq data

Single-cell technology has opened the door for studying signal transduction in a complex tissue at unprecedented resolution. However, there is a lack of analytical methods for de novo construction of signal transduction pathways using single-cell omics data. Here we present CytoTalk, a computational method for de novo constructing cell type-specific signal transduction networks using single-cell RNA-Seq data. CytoTalk first constructs intracellular and intercellular gene-gene interaction networks using an information-theoretic measure between two cell types. Candidate signal transduction pathways in the integrated network are identified using the prize-collecting Steiner forest algorithm. We applied CytoTalk to a single-cell RNA-Seq data set on mouse visual cortex and evaluated predictions using high-throughput spatial transcriptomics data generated from the same tissue. Compared to published methods, genes in our inferred signaling pathways have significantly higher spatial expression correlation only in cells that are spatially closer to each other, suggesting improved accuracy of CytoTalk. Furthermore, using single-cell RNA-Seq data with receptor gene perturbation, we found that predicted pathways are enriched for differentially expressed genes between the receptor knockout and wild type cells, further validating the accuracy of CytoTalk. In summary, CytoTalk enables de novo construction of signal transduction pathways and facilitates comparative analysis of these pathways across tissues and conditions.

bioinformatics↗

bioRxiv2020

DeeReCT-APA: Prediction of Alternative Polyadenylation Site Usage Through Deep Learning

Alternative polyadenylation (APA) is a crucial step in post-transcriptional regulation. Previous bioinformatic works have mainly focused on the recognition of polyadenylation sites (PAS) in a given genomic sequence, which is a binary classification problem. Recently, computational methods for predicting the usage level of alternative PAS in a same gene have been proposed. However, all of them cast the problem as a non-quantitative pairwise comparison task and do not take the competition among multiple PAS into account. To address this, here we propose a deep learning architecture, DeeReCT-APA, to quantitatively predict the usage of all alternative PAS of a given gene. To accommodate different genes with potentially different numbers of PAS, DeeReCT-APA treats the problem as a regression task with a variable-length target. Based on a CNN-LSTM architecture, DeeReCT-APA extracts sequence features with CNN layers, uses bidirectional LSTM to explicitly model the interactions among competing PAS, and outputs percentage scores representing the usage levels of all PAS of a gene. In addition to the fact that only our method can predict quantitatively the usage of all the PAS within a gene, we show that our method consistently outperforms other existing methods on three different tasks for which they are trained: pairwise comparison task, highest usage prediction task and ranking task. Finally, we demonstrate that our method can be used to predict the effect of genetic variations on APA patterns and shed light on future mechanistic understanding in APA regulation. Our code and data are available at https://github.com/lzx325/DeeReCT-APA-repo.

bioinformatics↗

bioRxiv2020

The Coxiella burnetii QpH1 plasmid is a virulence factor for colonizing bone marrow-derived murine macrophages

Coxiella burnetii carries a large conserved plasmid or plasmid-like chromosomally integrated sequence of unknown function. Here we report the curing of QpH1 plasmid from C. burnetii Nine Mile phase II, the characterization of QpH1-deficient C. burnetii in in vitro and in vivo infection models, and the characterization of plasmid biology. A shuttle vector pQGK, which is composed of the CBUA0036-0039a region (predicted for QpH1 maintenance), an E. coli plasmid ori, eGFP and kanamycin resistance genes was constructed. The pQGK vector can be stably transformed into Nine Mile II and maintained at a similar low copy like QpH1. Importantly, transformation with pQGK cured the endogenous QpH1 due to plasmid incompatibility. Compared to a Nine Mile II transformant of a RSF1010-based vector, the pQGK transformant shows an identical one-step growth curve in axenic media, a similar growth curve in Buffalo green monkey kidney cells, an evident growth defect in macrophage-like THP-1 cells, and dramatically reduced ability of colonizing bone marrow-derived murine macrophages. In the SCID mouse infection model, the pQGK transformants caused a lesser extent of splenomegaly. Moreover, the plasmid biology was investigated by mutagenesis. We found CBUA0037-0039 are essential for plasmid maintenance, and CBUA0037-0038 account for plasmid compatibility. Taken together, our data suggest that QpH1 encodes factor(s) essential for colonizing murine macrophages, and to a lesser extent for colonizing human macrophages. This study highlights a critical role of QpH1 for C. burnetii persistence in rodents, and expands the toolkit for genetic studies in C. burnetii. Author summaryIt is postulated that C. burnetii recently evolved from an inherited symbiont of ticks by the acquisition of novel virulence factors. All C. burnetii isolates carry a large plasmid or have a chromosomally integrated plasmid-like sequence. The plasmid is a candidate virulence factor that contributes to C. burnetii evolution. Here we describe the construction of novel shuttle vectors that allow to make plasmid-deficient C. burnetii mutants. With this plasmid-curing approach, we characterized the role of the QpH1 plasmid in in vitro and in vivo C. burnetii infection models. We found that the plasmid plays a critical role for C. burnetii growth in macrophages, especially in murine macrophages, but not in axenic media and BGMK cells. Our work highlights an essential role of the plasmid for the acquisition of colonizing capability in rodents by C. burnetii. This study represents a major step toward unravelling the mystery of the C. burnetii cryptic plasmids.

microbiology↗

bioRxiv2020

Elucidating Direct Kinase Targets of Compound Danshen Dropping Pills Employing Archived Data and Prediction Models

The research on the direct target of traditional Chinese medicine (TCM) is the key to study the mechanism and material basis of TCM, but there is still no effective technical methods at present. For Compound Danshen dropping pills (CDDP), there is no report about its direct targets. In this study, the direct targets of CDDP were studied for the first time, especially focusing on the protein kinase family, which plays causal roles in a variety of human disease. Firstly, the literature database of CDDP was constructed by literature retrieval, and the important components contained in CDDP were extracted. Secondly, the potential direct targets of important components was obtained through querying public database and predicted by Multi-voting SEA algorithm. Then, the KinomeX system was used to predict and to filter the potential kinase targets of CDDP. Finally, the experimental verification was carried out. In total, 30 active kinase targets was obtained at 25 g/ml concentration of CDDP, and 9 dose-dependent targets were obtained at 250 g/ml concentration of CDDP. This is an efficient and accurate strategy by integrating the targets recorded in several public databases and the targets calculated by two in silico modelling approaches predict potential direct targets of TCM, which can lay an important foundation for the study of the mechanism and material basis of them, promoting the modernization of TCM.

pharmacology and toxicology↗

bioRxiv2020

O-GlcNAcylation of SAMHD1 Indicating a Link between Metabolic Reprogramming and Anti-HBV Immunity

Viruses hijack the host cell machinery to promote viral replication; however, the mechanism by which metabolic reprogramming regulates innate antiviral immunity in the host remains elusive. Herein, we found that Hepatitis B virus (HBV) infection upregulates glucose transporter 1expression, promotes hexosamine biosynthesis pathway (HBP) activity, and enhances O-linked {beta}-N-acetylglucosamine (O-GlcNAc) modification of downstream proteins. HBP-mediated O-GlcNAcylation positively regulates host antiviral response against HBV in vitro and in vivo. Mechanistically, O-GlcNAc transferase (OGT)-mediated O-GlcNAcylation of sterile alpha motif and histidine/aspartic acid domain-containing protein 1 (SAMHD1) on Ser93 stabilizes SAMHD1 and enhances its antiviral activity. In addition, O-GlcNAcylation of SAMHD1 promoted its antiviral activity against human immunodeficiency virus-1 in vitro. In conclusion, the results of our study reveal a link between HBP, O-GlcNAc modification, and innate antiviral immunity by targeting SAMHD1. Therefore, the results of this study demonstrate a strategy for the potential treatment of HBV infection by modulating HBP activity.

microbiology↗

bioRxiv2020

X-chromosome dosage compensation dynamics in human early embryos

In mammals, female cells are obliged to inactivate one of two X chromosomes to achieve dosage parity with the single X chromosome in male cells, and it is also thought that the single active X chromosome is increased 2-fold to achieve dosage balance with two sets of autosomes (X:A ratio = 1, or Ohnos hypothesis). However, the ontogeny of X-chromosome inactivation and augmentation of the single active X remains unclear during human embryogenesis. Here, we perform single-cell RNA-seq analysis to examine the timing of X:A balancing and X-inactivation (XCI) in pre- and peri-implantation human embryos up to fourteen days in culture. We find that X-chromosome gene expression in both male and female preimplantation embryos is approximately balanced with autosomes (X:A ratio = 1) after embryonic genome activation (EGA) and persists through fourteen days in vitro. Cross-species analysis of preimplantation embryo also show balanced X:A ratio within the first few days of development. By single-cell mRNA SNP profiling, we find XCI beginning in day 6-7 blastocyst embryos, but does not affect X:A dosage balance. XCI is most evident in trophoectoderm (TE) cells, but can also be observed in a small number of inner cell mass (ICM)-derived cells including primitive endoderm (PE) and epiblast (EPI) cells. Analysis between individual XaXa and XaXi sister cells from the same embryo reveals random XCI and persistently balanced X:A ratio, including sister cells transitioning between XaXa and XaXi states. We therefore conclude that the male X-chromosome undergoes X chromosome augmentation prior to the simultaneous X-chromosome inactivation and augmentation in females. Together, our data demonstrate an evolutionally conserved model of X chromosome dosage compensation in humans and other mammalian species.

developmental biology↗

bioRxiv2020

Integrated analysis of gene correlation reveals disordered relationship between metabolism and immunity in tumor microenvironment

BackgroundMetabolism reprogramming and immune evasion are the most fundamental hallmarks for cancer survival. The complex interactions between metabolism and immune systems in tumors and their microenvironment is complicated. Researching on the correlation changes between metabolic and immune related-genes in normal and tumor tissues would help to reveal these complex interactions. MethodsIn this study, the mRNA profiles across 11 cancer types was obtained from The Cancer Genome Atlas (TCGA). Then, the spearmans correlation coefficient was calculated between metabolic and immune related-genes for each sample group. ResultsOur results showed that the number of correlated gene pairs was reduced significantly in tumor tissues compared with those of normal tissue, especially in KIRC, KIRP and STAD. Functional enrichment analysis for the universal (the pairs appeared in more than 2 cancer types) and specific (the pairs only in one specific cancer type) gene pairs across cancer types revealed top pathways which appeared in tumor and normal samples, such as phosphatidylinositol signaling system and inositol phosphate metabolism. Thereinto, the pairs in normal tissues missing in tumors may indicate they are important factors affecting immune system, such as, DGKs and PIP4ks. The correlation analysis between immune checkpoint and metabolism genes also showed a reduced correlation in tumor and had the tissue specificity, such as, FUT8 was strongly correlated with PDCD1 in the HC of STAD and they had a weaker correlation in other normal tissues and tumor types. ConclusionsOur study provides a novel strategy for investigating interaction of tumor immune and metabolism in microenvironment and offers some key points for exploring new targets including metabolic targets and immunomodulator of immune checkpoints.

bioinformatics↗

bioRxiv2020

Implications of error-prone long-read whole-genome shotgun sequencing on characterizing reference microbiomes

Long-read sequencing techniques, such as the Oxford Nanopore Technology, can generate reads that are tens of kilobases in length, and are therefore particularly relevant for microbiome studies. However, due to the higher per-base error rates than typical short-read sequencing, the application of long-read sequencing on microbiomes remains largely unexplored. Here we deeply sequenced two human microbiota mock community samples (HM-276D and HM-277D) from the Human Microbiome Project. We showed that assembly programs consistently achieved high accuracy (~99%) and completeness (~99%) for bacterial strains with adequate coverage. We also found that long-read sequencing provides accurate estimates of species-level abundance (R=0.94 for 20 bacteria with abundance ranging from 0.005% to 64%). Our results demonstrate the feasibility to characterize complete microbial genomes and populations from error-prone Nanopore sequencing data, but also highlight necessary bioinformatics improvements for future metagenomics tool development.

genomics↗

bioRxiv2020

Somatic cell-derived BMPs induce male germ cell meiosis initiation during embryonic stage via regulating Dazl expression

Germ cell fate is believed to be determined by the signaling from sexually differentiated somatic cell. However, the molecular mechanism remains elusive. In this study, ectopic initiation of meiosis in male germ cells was observed during embryonic stage by over-activating CTNNB1 in Sertoli cells. Somatic cell transcriptome and single germ cell RNA-seq analysis indicated that TGF-{beta} signaling was activated after CTNNB1 over-activation. In vitro and in vivo experiments confirmed somatic cell-derived BMPs played crucial roles in germ cell meiosis initiation. Further studies revealed that Dazl was significantly increased in germ cells of CTNNB1 over-activated testes and induced by BMP signaling. DNMT3a and DNA methylation was also reduced in germ cells of CTNNB1 over-activated testes and increased by BMP signaling inhibitor treatment. Taken together, this study demonstrates that germ cell fate could be reprogrammed after sex determination. BMP signaling pathway is involved in germ cell meiosis initiation via up-regulating Dazl expression.

developmental biology↗

bioRxiv2020

Knowledge guided multi-level network inference

Constantly decreasing costs of high-throughput profiling on many molecular levels generate vast amounts of so-called multi-omics data. Studying one biomedical question on two or more omic levels provides deeper insights into underlying molecular processes or disease pathophysiology. For the majority of multi-omics data projects, the data analysis is performed level-wise, followed by a combined interpretation of results. Few exceptions exist, for example the pairwise integration for quantitative trait analysis. However, the full potential of integrated data analysis is not leveraged yet, presumably due to the complexity of the data and the lacking toolsets. Here we propose a versatile approach, to perform a multi-level integrated analysis: The Knowledge guIded Multi-Omics Network inference approach, KiMONo. KiMONo performs network inference using statistical modeling on top of a powerful knowledge-guided strategy exploiting prior information from biological sources. Within the resulting network, nodes represent features of all input types and edges refer to associations between them, e.g. underlying a disease. Our method infers the network by combining sparse grouped-LASSO regression with a genomic position-confined Biogrid protein-protein interaction prior. In a comprehensive evaluation, we demonstrate that our method is robust to noise and still performs on low-sample size data. Applied to the five-level data set of the publicly available Pan-cancer collection, KiMONO integrated mutation, epigenetics, transcriptomics, proteomics and clinical information, detecting cancer specific omic features. Moreover, we analysed a four-level data set from a major depressive disorder cohort, including genetic, epigenetic, transcriptional and clinical data. Here we demonstrated KiMONos analytical power to identify expression quantitative trait methylation sites and loci and show its advantage to state-of-the-art methods. Our results show the general applicability to the full spectrum multi-omics data and demonstrating that KiMONo is a powerful approach towards leveraging the full potential of data sets. The method is freely available as an R package (https://github.com/cellmapslab/kimono).

systems biology↗

bioRxiv2020

Anethole dithiolethione improves liver fatty acid metabolism in hamster fed high-fat diets

"Lipotoxicity" induced by excessive accumulation of free fatty acids (FFAs) in the liver, especially saturated FAs and their toxic metabolites, is closely related to metabolic diseases such as nonalcoholic fatty liver disease (NAFLD). Hydrogen sulfide (H2S), a novel gaseous signaling molecule, has been reported to have lipid-lowering effects, but its effect on FAs metabolism remains unclear. The purpose of this study was to investigate the effect and mechanisms of anethole dithiolethione (ADT, a sustained-release H2S donor) on hepatic FAs metabolism. ADT was administered daily for 4 weeks in male Syrian golden hamsters fed a high fat diet (HFD), and FAs profiles of liver tissues were analyzed using GC-MS. The results showed that in HFD-fed hamsters, ADT treatment significantly reduced the accumulation of saturated and monounsaturated fatty acids (C16:0, C18:0, C16:1, and C18:1n9), while increased the content of n-6 and n-3 series polyunsaturated fatty acids (C20:3n6, C20:4n6, and C22:6n3). Mechanistically, ADT obviously inhibited the overexpression of ACC1, FAS and SCD1, and up-regulated the levels of FATPs, L-FABP, CPT1, FADS1 and FADS2. Notably, ADT evidently induced Mitofusin1 to facilitate mitochondrial fusion and optimize {beta}-oxidation. These findings suggest that ADT plays a beneficial role by regulating the synthesis, desaturation, {beta}-oxidation, uptake, binding/isolation, and transport of FAs. In conclusion, ADT is effective in improving liver FAs metabolic disorders and liver injuries caused by HFD.

pharmacology and toxicology↗

bioRxiv2020

Microbial redox activity mediated anaerobic pyrite oxidation under circumneutral conditions

In modern Earth, anaerobic pyrite oxidation under circumneutral conditions also has great impact on the fate of nitrate in aquifers and sediments, as well as the transportation of toxic metals. However, the mechanism of how microbes mediated this process is still being debated. Electrochemical analysis on pyrite cubic electrode showed that, its oxidation threshold under anaerobic circumneutral conditions (ca. 200 mV) was much lower than that at aerobic acidic conditions (ca. 650 mV), implying possible direct pyrite oxidation by high redox potential cellular components. Sole substrate (pyrite) microbial enrichment cultures with EDTA addition showed higher oxidation rate (0.092 d-1) than that of EDTA-free cultures (0.019 d-1), suggesting that ligands producing pathway was much preferred by microbes than maintaining acidic micro-environments. This hypothesis was supported by amplicon and metagenomic sequencing data, which demonstrated discrepant bacteria involving iron-sulfur oxidation and metabolic potentials in cultures with/without EDTA addition. A concept model was proposed based on experimental data considering different reaction stages and microbial communities. The results shed lights on the potential interactions between microbes and pyrite, which may serve as a model for explaining subsurface pyrite oxidation and optimizing anaerobic pyrite oxidation-based pollutant removal processes. TOC art O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=99 SRC="FIGDIR/small/952168v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@14c7a01org.highwire.dtl.DTLVardef@1de10bdorg.highwire.dtl.DTLVardef@1ceb4dorg.highwire.dtl.DTLVardef@9c27fc_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2020

Global Dynamic Molecular Profiles of Stomatal Lineage Cell Development by Single-Cell RNA Sequencing

The regulation of stomatal lineage cell development has been extensively investigated. However a comprehensive characterization of this biological process based on single-cell transcriptome analysis has not yet been reported. Here, we performed RNA-seq on over 12,844 individual cells from the cotyledons of five-day-old Arabidopsis seedlings. We identified 11 cell clusters corresponding mostly to cells at specific stomatal developmental stages with a series of new marker genes. Comparative analysis of genes with the highest variable expression in these cell clusters revealed three transcriptional networks that regulate the development of mesophyll and guard cells, as well as the differentiation from protodermal to guard mother cells. We investigated the developmental dynamics of marker genes via pseudo-time analysis which revealed potential interactions between them. The identification of several novel marker genes suggests new regulatory mechanisms during development of stomatal cell lineage.

plant biology↗

bioRxiv2020

Molecular taxonomy of human ocular outflow tissues defined by single cell transcriptomics

The conventional outflow pathway is a complex tissue responsible for maintaining intraocular pressure (IOP) homeostasis. The coordinated effort of multiple cells with differing responsibilities ensure healthy outflow function and IOP maintenance. Dysfunction of one or more resident cell type results in ocular hypertension and risk for glaucoma, a leading cause of blindness. In this study, single cell RNA sequencing was performed to generate a comprehensive cell atlas of human conventional outflow tissues. We obtained 17757 genes expression profiles from 8758 cells from eight eyes of four donors representing the outflow cell transcriptome. Upon clustering analysis, 12 distinct cell types were identified, and region-specific expression of candidate genes were mapped in human tissues. Significantly, we identified two distinct expression patterns (myofibroblast and fibroblast) from cells located in the trabecular meshwork (TM), the primary structural component of the conventional outflow pathway. We also located neuron and macrophage signatures in the TM. The second primary component structure, Schlemms canal displayed a unique combination of lymphatic/blood vascular gene expression. Other expression clusters corresponded to cells from neighboring tissues, predominantly in the ciliary muscle/scleral spur, which together correspond to the uveoscleral outflow path. Importantly, the utility of our atlas was demonstrated by mapping glaucoma-relevant genes to outflow cell clusters. Our study provides a comprehensive molecular and cellular classification of conventional and unconventional outflow pathway structures responsible for IOP homeostasis. Significance statementOcular hypertension is the primary, and only modifiable risk factor for glaucoma, the leading cause of irreversible blindness. Intraocular pressure is regulated homeostatically by resistance to aqueous humor outflow through an architecturally complex tissue, the conventional/trabecular pathway. In this study, we generated a comprehensive cell atlas of the human trabecular meshwork and neighboring tissues using single cell, RNA sequencing. We identified 12 distinct cell types, and mapped region-specific expression of candidate genes. The utility of our atlas was demonstrated by mapping glaucoma-relevant genes to conventional outflow cell clusters. Our study provides a comprehensive molecular and cellular classification of tissue structures responsible for intraocular pressure homeostasis in health, and dysregulation in disease.

cell biology↗