Biology subjects

Zhou, J.

Publications and source records attributed to Zhou, J..

At least 307 records · Page 17Linked to original sources

bioRxiv2023

An Artificial Intelligence-Assisted Digital Microfluidic System for Multistate Droplet Control

AbstractDigital microfluidics (DMF) is a versatile technique for parallel and field-programmable control of individual droplets. Given the high freedom in droplet manipulation, it is essential to establish self-adaptive and intelligent control methods for DMF systems with informed of the transient state of droplets and their interactions. However, most related studies focus on the localization and shape recognition of droplets. Here, we develop an AI-assisted DMF framework named "DropAI" for multistate droplet control based on droplet morphology. Semantic segmentation model is integrated into our custom-designed DMF system to recognize the droplet states and their interactions for feedback control with a state machine. The proposed model has a strong generalization ability and can recognize droplets of different colors and shapes with an error rate of less than 0.63%. It enables control of droplets without user intervene. The proposed system will inspire the development of semantic-driven DMF systems which can interface with artificial general intelligence (AGl) models for fully automatic control.

bioengineering↗

bioRxiv2023

Study on genetic differentiation of Schistosome japonicum intermediate hosts Oncomelania hupensis robertsoni in hilly regions of China: using the complete mitochondrial genome

ObjectiveOncomelania hupensis robertsoni is the only intermediate host of Schistosoma japonicum in western China, its genetic differentiation directly impacts the susceptibility of Schistosoma japonicum. This study aimed to sequence the complete mitochondrial genome of Oncomelania hupensis robertsoni Yunnan strain and analyze the genetic differentiation of Oncomelania hupensis robertsoni in hilly regions of China. MethodsSamples were from 14 administrative villages in Yunnan Province of China, with 30 Oncomelania hupensis per village, and the complete mitochondrial genome was sequenced. Additional, we retrieved 14 other region Oncomelania hupensis of complete mitochondrial sequences from GenBank, and a comprehensive analysis of the genetic differentiation of Oncomelania hupensis robertsoni was conducted by constructing phylogenetic trees, calculating genetic distances, and analyzing homogeneity. ResultsA total of 26 complete mitochondrial sequences were determined. The length of genome ranged from 15,181 to 15,187 bp, and the base composition of the genome was A+T (67.5%) and G+C content (32.5%). This genome encoded 37 genes, including 13 protein-coding genes, 2 rRNA genes, 22 tRNA genes and a non-coding region rich in A+T. Using the Philippines genotypes as outgroup, the phylogenetic trees and homology analysis confirmed the existence of two distinct phylogroups, Oncomelania hupensis robertsoni and the remaining 9 provincial genotypes. Oncomelania hupensis robertsoni is subdivided into Oncomelania hupensis robertsoni Yunnan strain and Sichuan strain, with a genetic distance of 0.0834. Oncomelania hupensis robertsoni Yunnan strain is subdivided into two subbranches, "Yunnan North" and "Yunnan South", with a genetic distance of 0.0216, and the samples exhibited over 97% homology. ConclusionOncomelania hupensis robertsoni Yunnan strain exhibits a higher level of genetic homology and clear north-south differentiation, the distribution characteristics were closely associated with watershed distribution. This work reported the first mitochondrial genome of Oncomelania hupensis robertsoni Yunnan strain, which could be used as an important reference genome for Oncomelania hupensis, and also provide a theoretical basis for explaining the distribution pattern of Oncomelania hupensis robertsoni and control of schistosomiasis. Author SummaryOncomelania hupensis (O. hupensis) is the only intermediate host of Schistosoma japonicum (S. japonicum), O. hupensis residing in different geographical regions display morphological differences and genetic variations, along with varying susceptibility to S. japonicum. In this study, we sequenced 26 complete mitochondrial genome of O. hupensis robertsoni Yunnan strain (O. h. r. Yunnan strain), the length of genome ranged from 15,181 to 15,187 bp, and the base composition of the genome was A+T (67.5%) and G+C content (32.5%). This genome encoded 37 genes, including 13 protein-coding genes, 2 rRNA genes, 22 tRNA genes and a non-coding region rich in A+T. Additional, we retrieved 14 other region O. hupensis of complete mitochondrial sequences from GenBank. The phylogenetic trees and homology analysis confirmed that O. hupensis robertsoni is subdivided into Yunnan strain and Sichuan strain, and O. h. r. Yunnan strain is subdivided into two subbranches, "Yunnan North" and "Yunnan South", the samples exhibited over 97% homology. This work reported the first mitochondrial genome of O. h. r. Yunnan strain, which could be used as an important reference genome for O. hupensis, and also provide a molecular biology-based theoretical foundation for understanding the genetic differentiation of O. hupensis.

genomics↗

bioRxiv2023

Stereo-anomaly is found more frequently in tasks that require discrimination between depths

AO_SCPLOWBSTRACTC_SCPLOWWithin the population of humans with otherwise normal vision, there exists some proportion whose ability to perceive depth from binocular disparity is poor or absent. The prevalence of this "stereoanomaly" has been investigated in previous studies, some finding the proportion to be as small as 2%, others finding it to be as great as 30%. In this study, we set out to investigate the possible reason for the wide range of results found in these studies. We used a digital stereoacuity measurement tool that could measure performance in tasks requiring either the detection of disparity or the discrimination of the sign of disparity. The stimulus design was otherwise similar between the two tasks. In a cohort of 228 participants, we found that 98% were able to consistently perform the detection task. In contrast, only 69% consistently performed the discrimination task. The 31% of participants who had difficulty with the discrimination task could further be divided into 17% who were consistently unable to perform the task (seeming to behave at chance), and 14% who showed some ability to perform the task. We propose that the greater prevalence of stereo-anomaly is revealed when tasks require the judgement of the direction of disparity.

neuroscience↗

bioRxiv2023

Inhalation Delivered RNA Aptamer for Therapeutics against SARS-CoV2

The continual emergence and re-emergence of infectious diseases has led to a pressing need for the development of swift and targeted therapeutic interventions. SARS-CoV-2, the causative agent of COVID-19, is a prime example of such a rapidly spreading virus[1]. The global crisis caused by this virus has propelled researchers to explore and adopt novel techniques in the hopes of effectively combating its spread[2]. One such innovative approach is the use of aptamers--single-stranded RNA molecules that can bind targets with high specificity.

molecular biology↗

bioRxiv2023

Integrative analysis of the methylome and transcriptome of tomato fruit (Solanum lycopersicum L.) induced by postharvest handling

Tomato fruit ripening is triggered by the demethylation of key genes, which alters their transcriptional levels thereby initiating and propagating a cascade of physiological events. What is unknown, is how these processes are altered when fruit are ripened using postharvest practices to extend shelf-life, as these practices often reduce fruit quality. To address this, postharvest handling-induced changes in the fruit DNA methylome and transcriptome, and how they correlated with ripening speed, and ripening indicators such as ethylene, ABA, and carotenoids, were assessed. This study comprehensively connected changes in physiological events with dynamic molecular changes. Ripening fruit that reached Turning (T) after storage under dark at 20{degrees}C, 12.5{degrees}C, or 5{degrees}C chilling (followed by 20{degrees}C rewarming), were compared to fresh-harvest fruit FHT. Fruit stored at 12.5{degrees}C, had the biggest epigenetic marks and alterations in gene expression, exceeding changes induced by postharvest chilling. Fruit physiological and chronological age were uncoupled at 12.5{degrees}C, as the time-to-ripening was longest. Fruit ripening at 12.5{degrees}C was not climacteric; there was no respiratory or ethylene burst, rather, fruit were high in ABA. Clear differentiation between postharvest-ripened and FHT was evident in the methylome and transcriptome. Higher expression of photosynthetic genes and chlorophyll levels in FHT fruit, pointing to light as influencing the molecular changes in fruit ripening. Finally, correlative analyses of the -omics data putatively identified genes regulated by DNA methylation. Collectively these data improve our interpretation of how tomato fruit ripening patterns are altered by postharvest practices, and long-term are expected to help improve fruit quality.

plant biology↗

bioRxiv2023

Respiration and growth of Paracoccus denitrificans R-1 with nitrous oxide as an electron acceptor

In the nitrogen biogeochemical cycle, the reduction of nitrous oxide (N2O) to N2 by N2O reductase, which is encoded by nos gene cluster, is the only biological pathway for N2O consumption. However, the capability and mechanisms of microbial N2O reduction are poorly understood. In this study, we investigated the ability to obtain energy for growth of Paracoccus denitrificans R-1 by coupling the oxidation of various electron donors to N2O reduction. This strain has strong N2O reduction capability, and the average N2O reduction rate was 5.10{+/-}0.11x10-9 mol{middle dot}h-1{middle dot}cell-1 under anaerobic condition at 30 using acetate as the electron donor in a defined medium. This reduction was accompanied by the stoichiometric consumption of acetate over time when N2O served as the sole electron acceptor and the reduction can yield energy to support microbial growth, suggesting that microbial N2O reduction is an electron transport process. Cu2+, silver nanoparticles, O2, and acidic conditions can strongly inhibit the reduction, whereas NO3- or NH4+ can promote it. Genomic analysis showed that the gene cluster encoding N2O reductase of P. denitrificans R-1 was composed of nosR, nosZ, nosD, nosF, nosY, and nosL, and nosZ, which was identified as clade I. The respiratory inhibitors test indicated that the pathway of electron transport for N2O reduction was different from that of the traditional electron transport chain for aerobic respiration. These findings suggest that modular N2O reduction by P. denitrificans R-1 is linked to the electron transport chain and energy conservation, and that dissimilatory N2O reduction is a form of microbial anaerobic respiration. IMPOETANCEIn the nitrogen biogeochemical cycle, the reduction of N2O to N2 by N2O reductase, which is encoded by nos genes, is the only biological pathway for N2O consumption. However, the capacity and mechanisms of microbial N2O reduction are poorly understood. We investigated the ability to obtain energy for growth of Paracoccus denitrificans R-1 by coupling the oxidation of various electron donors to N2O reduction. Our study showed that the nosZ type I bacterium, P. denitrificans R-1, can respire N2O as the sole electron donor. Thus, the modular N2O reduction process of clade I denitrifiers not only can consume N2O produced by themselves but can also consume the external N2O generated from non-denitrification biological or abiotic pathways under suitable conditions, which is critical for controlling the release of N2O from ecosystems into the atmosphere.

microbiology↗

bioRxiv2023

A peptide-centric local stability assay to unveil protein targets of diverse ligands

While tremendous progress has been made in chemical proteomics for identifying protein-ligand interactions, it remains challenging for proteome-wide identification of ligand-binding regions without modifying the ligands. Here, we discovered that "disruptive trypsinization" amplifies the readout of ligand-induced protein local stability shifts, and explored this notion in developing "peptide-centric local stability assay" (PELSA), a modification-free approach which achieves unprecedented sensitivity in proteome-wide target identification and binding-region determination. We demonstrate the versatility of PELSA by investigating the interactions across various biological contexts including drug-target interactions, metabolism, epitope mapping, metal proteomics, and post-translational modification recognition. A PELSA study of the oncometabolite R2HG revealed functional insights about its targets and pathogenic processes in both cancer and immune cells. Thus, beyond offering users unprecedented sensitivity for characterizing diverse target-ligand interactions, PELSA supports informative screening and hypothesis generation studies throughout life science.

biochemistry↗

bioRxiv2023

Epigenome erosion in Alzheimer's disease brain cells and induced neurons

Late-onset Alzheimers disease (LOAD) is typically sporadic, correlated only to advanced age, and has no clear genetic risk factors. The sporadic nature of LOAD presents a challenge to understanding its pathogenesis and mechanisms. Here, we comprehensively investigated the epigenome of LOAD primary entorhinal cortex brain tissues via single-cell multi-omics technologies, simultaneously capturing DNA methylation and 3D chromatin conformation. We identified AD-specific DNA methylation signatures and found they interact with bivalent promoters of AD differentially expressed genes. In addition, we discovered global chromosomal epigenome erosion of 3D genome structure within and across brain cell types. Furthermore, to evaluate whether these age- and disease-dependent molecular signatures could be detected in the in vitro cellular models, we derived induced neurons (iNs) converted directly from AD patients fibroblasts and found a set of conserved methylation signatures and shared molecular processes. We developed a machine-learning algorithm to identify robust and consistent methylation signatures of LOAD in vivo primary brain tissues and in vitro fibroblast-derived iNs. The results recapitulate the age- and disease-related epigenetic features in iNs and highlight the power of epigenome and chromatin conformation for identifying molecular mechanisms of neuronal aging and generating biomarkers for LOAD. HIGHLIGHTO_LIAD-specific DNA methylation signatures are identified in entorhinal cortex brain cell types C_LIO_LIThe AD differentially expressed genes linked with differentially methylated regions via loop interactions are enriched in a bivalent chromatin state C_LIO_LIChromosomal epigenome erosion of 3D genome structures occurs in LOAD brain cell types. C_LIO_LIShared and reliable methylation signatures are observed in both in vitro cellular iN models and primary brain tissues. C_LIO_LIMachine learning models identify robust and reliable methylation loci as AD biomarkers across cell types. C_LI

genomics↗

bioRxiv2023

Scaling the fitness effects of mutations with respect to differentially adapted Arabidopsis thaliana accessions under natural conditions

Mutations are the ultimate source of genetic variation for natural selection to act upon. A major question in evolutionary biology is the extent to which new mutations can generate genetic variation under natural conditions to permit adaptive evolution over ecological time scales. Here we collected fitness data for chemically induced (ethylmethane sulfonate, EMS) mutant lines descended from two Arabidopsis thaliana ecotypes that show differential adaptation to the local environment of our common garden plot. Using a novel nonparametric Bayesian statistical approach, we found that both ecotypes accumulated substantial proportions of beneficial mutations. The poorly adapted ecotype showed higher variance in the fitness effect of mutations than the well-adapted ecotype. Furthermore, we predict that it takes less than 4000 generations for the fitness space of the two ecotypes to overlap through mutation accumulation, and that a single founder, through mutation accumulation, is able to achieve the species-wide genetic variation in less than 10,000 generations. Our results provide evidence for relatively rapid local adaptation of Arabidopsis thaliana in natural conditions through new mutations, as well as the utility of nonparametric Bayesian method for modeling the distribution of fitness effects for field-collected data.

evolutionary biology↗

bioRxiv2023

BioKG: a comprehensive, high-quality biomedical knowledge graph for AI-powered, data-driven biomedical research

To address the rapid growth of scientific publications and data in biomedical research, knowledge graphs (KGs) have become a critical tool for integrating large volumes of heterogeneous data to enable efficient information retrieval and automated knowledge discovery (AKD). However, transforming unstructured scientific literature into KGs remains a significant challenge, with previous methods unable to achieve human-level accuracy. In this study, we utilized an information extraction pipeline that won first place in the LitCoin NLP Challenge (2022) to construct a large-scale KG named iKraph using all PubMed abstracts. The extracted information matches human expert annotations and significantly exceeds the content of manually curated public databases. To enhance the KGs comprehensiveness, we integrated relation data from 40 public databases and relation information inferred from high-throughput genomics data. This KG facilitates rigorous performance evaluation of AKD, which was infeasible in previous studies. We designed an interpretable, probabilistic-based inference method to identify indirect causal relations and applied it to real-time COVID-19 drug repurposing from March 2020 to May 2023. Our method identified 600-1400 candidate drugs per month, with one-third of those discovered in the first two months later supported by clinical trials or PubMed publications. These outcomes are very challenging to attain through alternative approaches that lack a thorough understanding of the existing literature. A cloud-based platform (https://biokde.insilicom.com) was developed for academic users to access this rich structured data and associated tools.

bioinformatics↗

bioRxiv2023

Integrating large-scale meta-GWAS and PigGTEx resources to decipher the genetic basis of complex traits in pig.

Understanding the molecular and cellular mechanisms that underlie complex traits in pigs is crucial for enhancing their genetic improvement program and unleashing their substantial potentials in human biomedicine research. Here, we conducted a meta-GWAS analysis for 232 complex traits with 28.3 million imputed whole-genome sequence variants in 70,328 individuals from 14 pig breeds. We identified a total of 6,878 genomic regions associated with 139 complex traits. By integrating with the Pig Genotype-Tissue Expression (PigGTEx) resource, we systemically explored the biological context and regulatory circuits through which these trait-associated variants act and finally prioritized 16,664 variant-gene-tissue-trait circuits. For instance, rs344053754 regulates the expression of UGT2B31 in the liver by affecting the activity of regulatory elements and ultimately influences litter weight at weaning. Furthermore, we investigated the conservation of genetic and regulatory mechanisms underlying 136 human traits and 232 pig traits. Overall, our multi-breed meta-GWAS in pigs provides invaluable resources and novel insights for understanding the regulatory and evolutionary mechanisms of complex traits in both pigs and humans.

genetics↗

bioRxiv2023

Development of properly-polarized trophoblast stem cell-derived organoids to model early human pregnancy

The development of human trophoblast stem cells (hTSC) and stem cell-derived trophoblast organoids has enabled investigation of placental physiology and disease and early maternal-fetal interactions during a stage of human pregnancy that previously had been severely restricted. A key shortcoming in existing trophoblast organoid methodologies is the non-physiologic position of the syncytiotrophoblast (STB) within the inner portion of the organoid, which neither recapitulates placental villous morphology in vivo nor allows for facile modeling of STB exposure to the endometrium or the contents of the intervillous space. Here we have successfully established properly-polarized human trophoblast stem cell (hTSC)-sourced organoids with STB forming on the surface of the organoid. These organoids can also be induced to give rise to the extravillous trophoblast (EVT) lineage with HLA-G+ migratory cells that invade into an extracellular matrix-based hydrogel. Compared to previous hTSC organoid methods, organoids created by this method more closely mimic the architecture of the developing human placenta and provide a novel platform to study normal and abnormal human placental development and to model exposures to pharmaceuticals, pathogens and environmental insults. MotivationHuman placental organoids have been generated to mimic physiological cell-cell interactions. However, those published models derived from human trophoblast stem cells (hTSCs) or placental villi display a non-physiologic "inside-out" morphology. In vivo, the placental villi have an outer layer of syncytialized cells that are in direct contact with maternal blood, acting as a conduit for gas and nutrient exchange, and an inner layer of progenitor, single cytotrophoblast cells that fuse to create the syncytiotrophoblast layer. Existing "inside-out" models put the cytotrophoblast cells in contact with culture media and substrate, making physiologic interactions between syncytiotrophoblast and other cells/tissues and normal and pathogenic exposures coming from maternal blood difficult to model. The goal of this study was to develop an hTSC-derived 3-D human trophoblast organoid model that positions the syncytiotrophoblast layer on the outside of the multicellular organoid. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=69 SRC="FIGDIR/small/560327v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@7f1e7forg.highwire.dtl.DTLVardef@1ab41d9org.highwire.dtl.DTLVardef@7046d5org.highwire.dtl.DTLVardef@13a7542_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

bioRxiv2023

An autophagy adaptor TRIAD3A promotes tau fibrillation by phase separation

Multiple neurodegenerative diseases are characterized by aberrant proteinaceous accumulations of tau. Here, we report an RBR-type E3 ligase TRIAD3A functions as a novel autophagy adaptor for tau. TRIAD3A(RNF216) is an essential gene with mutations causing ageprogressive neurodegeneration. Our studies reveal that TRIAD3A E3 ligase catalyzes a novel mixed K11/K63 polyubiquitin chain and self assembles into liquid-liquid phase separated (LLPS) droplets. Tau is ubiquitinated and accumulates within TRIAD3A LLPS droplets and via LC3 interacting regions targets tau for autophagic degradation. Unexpectedly, tau sequestered within TRIAD3A droplets rapidly converts to amyloid aggregates without the transitional liquid phase of tau. In vivo studies reveal TRIAD3A decreases the accumulation of phosphorylated tau in a tauopathy mouse model, and disease-associated mutation of TRIAD3A increases accumulation of phosphorylated tau, exacerbates gliosis, and increases pathological tau spreading. In human Alzheimers disease brain, TRIAD3A colocalizes with tau amyloid in multiple histological forms suggesting a role in tau homeostasis. TRIAD3A is the first autophagic adaptor that utilizes E3-ligase and LLPS as a mechanism to capture cargo and appears especially relevant to neurodegenerative diseases.

neuroscience↗

bioRxiv2023

GeneCompass: Deciphering Universal Gene Regulatory Mechanisms with Knowledge-Informed Cross-Species Foundation Model

Deciphering the universal gene regulatory mechanisms in diverse organisms holds great potential to advance our knowledge of fundamental life process and facilitate research on clinical applications. However, the traditional research paradigm primarily focuses on individual model organisms, resulting in limited collection and integration of complex features on various cell types across species. Recent breakthroughs in single-cell sequencing and advancements in deep learning techniques present an unprecedented opportunity to tackle this challenge. In this study, we developed GeneCompass, the first knowledge-informed, cross-species foundation model pre-trained on an extensive dataset of over 120 million single-cell transcriptomes from human and mouse. During pre-training, GeneCompass effectively integrates four types of biological prior knowledge to enhance the understanding of gene regulatory mechanisms in a self-supervised manner. Fine-tuning towards multiple downstream tasks, GeneCompass outperforms competing state-of-the-art models in multiple tasks on single species and unlocks new realms of cross-species biological investigation. Overall, GeneCompass marks a milestone in advancing knowledge of universal gene regulatory mechanisms and accelerating the discovery of key cell fate regulators and candidate targets for drug development.

bioinformatics↗

bioRxiv2023

Targeting EIF4A triggers an interferon response to synergize with chemotherapy and suppress triple-negative breast cancer

Protein synthesis is frequently dysregulated in cancer and selective inhibition of mRNA translation represents an attractive cancer therapy. Here, we show that therapeutically targeting the RNA helicase eIF4A by Zotatifin, the first-in-class eIF4A inhibitor, exerts pleiotropic effects on both tumor cells and the tumor immune microenvironment in a diverse cohort of syngeneic triple-negative breast cancer (TNBC) mouse models. Zotatifin not only suppresses tumor cell proliferation but also directly repolarizes macrophages towards an M1-like phenotype and inhibits neutrophil infiltration, which sensitizes tumors to immune checkpoint blockade. Mechanistic studies revealed that Zotatifin reprograms the tumor translational landscape, inhibits the translation of Sox4 and Fgfr1, and induces an interferon response uniformly across models. The induction of an interferon response is partially due to the inhibition of Sox4 translation by Zotatifin. A similar induction of interferon-stimulated genes was observed in breast cancer patient biopsies following Zotatifin treatment. Surprisingly, Zotatifin significantly synergizes with carboplatin to trigger DNA damage and an even heightened interferon response resulting in T cell-dependent tumor suppression. These studies identified a vulnerability of eIF4A in TNBC, potential pharmacodynamic biomarkers for Zotatifin, and provide a rationale for new combination regimens comprising Zotatifin and chemotherapy or immunotherapy as treatments for TNBC. One Sentence SummaryTargeting EIF4A sensitizes TNBC to immune therapy and chemotherapy by suppressing Sox4, inducing an interferon response, and reprograming the tumor immune microenvironment.

cancer biology↗

bioRxiv2023

Cell context-specific Synthetic lethality Prediction and Mechanism Analysis

Synthetic lethality (SL) holds significant promise as a targeted cancer therapy by selectively eliminating tumor cells while sparing normal cells. However, the discovery of SL gene pairs has encountered tremendous challenges, including high costs and low efficiency of experimental methods. Current computational approaches only provide limited insights because of overlooking the crucial aspects of cellular context dependency and mechanistic understanding of SL pairs. To overcome these challenges, we have developed SLWise, a deep-learning model capable of predicting SL interactions in diverse cellular backgrounds. We evaluated SLWise using a real world ground truth standard. The evaluation demonstrated that SLWise outperformed benchmark models in SL prediction. Additionally, we proposed a novel analysis scheme called SLAD-CE (Synthetic Lethal Associated Gene Detection and Cell Damage Evaluation) for the identification of abnormal essential genes induced by SL gene pairs and tracking the extent of cell damage. Leveraging the cell-line-specific input feature L1000 and employing Gene Set Enrichment Analysis (GSEA), SLAD-CE provides valuable insights into the underlying mechanisms of SLWise-predicted gene pairs. The combined utilization of SLWise and SLAD-CE offers an approach for predicting and analyzing SL interactions in specific cellular contexts. Our findings highlight the potential of SLWise and SLAD-CE in advancing SL-based therapies by improving prediction accuracy and enhancing mechanistic understanding, ultimately contributing to the development of effective precision treatments for cancer.

cancer biology↗

bioRxiv2023

Combining Bulk and Single-Cell RNA Sequencing Data to Identify RNA methylation and Autophagy-Related Signatures in Patients with Chronic Obstructive Pulmonary Disease

BackgroundChronic Obstructive Pulmonary Disease (COPD) is a heterogeneous lung condition associated with RNA methylation and autophagy. However, the specific autophagy-related genes and RNA methylation regulators involved in COPD development remain unknown. MethodsWe analyzed COPD and non-COPD patients datasets obtained from the Gene Expression Omnibus database, including Tissue Sequencing Transcriptome (bulk-seq) and single-cell sequencing (scRNA-seq) data. Differentially expressed genes (DEGs) were identified through differential genetic analysis using non-COPD bulk-seq data as the control group and COPD samples were used as the experimental group. Animal experiments were conducted to validate the expression of key genes. COPD model mice were exposed to smoke for four months, and lung function and histopathological changes were assessed. The mRNA and protein expression levels of FTO, IGF2BP2, DDIT3, DNAJB1, and YTHDF3 were measured using RT-qPCR and Western blotting, respectively. ResultsWe identified FTO, IGF2BP2, and YTHDF3 as key methylation genes, along with autophagy hub genes DDIT3 and DNAJB1. Animal experiments showed significantly increased mRNA and protein levels of FTO, YTHDF3 and DNAJB1 and significantly decreased levels of IGF2BP2 in lung tissue of COPD mice compared to the control group. ConclusionOur findings suggest that DDIT3 and DNAJB1 as autophagy hub genes, along with FTO, IGF2BP2 and YTHDF3 as RNA methylation genes, may play crucial roles in the development of COPD. These findings, supported by bulk-seq and scRNA-seq data, contribute novel genetic evidence for understanding the epigenetics of COPD.

cell biology↗

bioRxiv2023

Dual lineage origins of neocortical astrocytes

Astrocytes represent one of the most abundant cell types in the central nervous system, and play an essential role in nearly all aspects of brain functions1. Recent studies have challenged the notion that cortical astrocytes are a uniform population, and have highlighted their diverse characteristics at the morphological, molecular, and functional levels2-5. However, how this diversity originates and establishes during cortical development, remains largely unknown. Using single-cell RNA sequencing, we identified five distinct astrocyte subtypes displaying unique spatial patterns in the mouse neocortex, and discovered essential regulators for their formation. Furthermore, we used TrackerSeq6, a method that integrates heritable DNA barcodes into the genome of electroporated progenitors, to track clonally related astrocytes, and identified two distinct lineages that give rise to the five astrocyte subtypes. The first lineage derives from Emx1+ multipotent progenitors that first generate neurons and then switch to produce cortical astrocytes. The second lineage stems from a fate-restricted progenitor population that exclusively gives rise to a specific subset of cortical astrocytes, marked by Olig2. The knockout of this gene in cortical progenitors is sufficient to promote a fate switch between the two lineages. These findings offer novel insights into the cellular mechanisms underlying astrocyte diversity, highlighting the presence of multiple progenitor subtypes, responsible for generating distinct subtypes of astrocytes.

neuroscience↗