Biology subjects

Zhang, S.

Publications and source records attributed to Zhang, S..

At least 613 records · Page 34Linked to original sources

bioRxiv2023

Guild-Level Gut Microbial Alterations Associate with Non-hepatitis Virus related Hepatocellular Carcinoma

The gut microbiota of hepatocellular carcinoma (HCC) is different from that of cohort without HCC. However, the relationship between non-hepatitis virus related HCC and gut microbial alterations remains elusive. In this work, we studied the gut microbial data in Sequence Read Archive (SRA) database from 58 healthy controls (HC), 31 patients with nonalcoholic fatty liver disease (NAFLD), 206 patients with hepatitis B viruses, 35 patients with HBV related HCC (B-HCC), and 22 patients with non-HBV or non-HCV related HCC (NBNC-HCC). Depend on guild-based analysis, 27 gut bacterial co-abundance groups (CAGs) were established. By studying these CAGs, we found the gut microbial overall structure and composition differed among patients with NBNC-HCC, B-HCC, other liver diseases, and healthy cohort, such as members from Lachnospiraceae, Veillonellaceae, and Prevotella. The network calculated by these CAGs in patients with HCC showed less interactions than that in healthy cohort. The specific CAGs showed correlated to the development of HCC. In addition, gut bacterial dysbiosis index, which was calculated by significantly altered CAGs in patients with NBNC-HCC compared with healthy cohort, showed potential diagnostic power of NBNC-HCC. Therefore, this study shows a new way toward understanding the role of the gut microbiome in patients with non-hepatitis virus related HCC. IMPORTANCEGut microbiome may play an important role in the pathogenesis and development of hepatocellular carcinoma. However, the relationship between non-hepatitis virus related hepatocellular carcinoma and gut microbiome should be further understood. In the current work, we found the alterations of gut microbial structure, composition, and network robustness in these patients by guild-based data analysis. Specific gut bacteria in these patients were related to clinical parameters, such as blood biochemical indexes. More importantly, gut bacterial bio-markers, which can discriminate these patients and cohort without this disease, were showed in this study. Thus, our study suggests that these guild-level gut bacteria may contribute to the development of non-hepatitis virus related hepatocellular carcinoma. This provides a new direction for future studies, which aims to show the importance of the gut microbiome in hepatocellular carcinoma.

microbiology↗

bioRxiv2023

Germline-targeting SOSIP trimer immunization elicits precursor CD4 binding-site targeting broadly neutralizing antibodies in infant macaques.

A vaccine that can achieve protective immunity prior to sexual debut is critical to prevent the estimated 410,000 new HIV infections that occur yearly in adolescents. As children living with HIV can make broadly neutralizing antibody (bnAb) responses in plasma at a faster rate than adults, early childhood is an opportune window for implementation of a multi-dose HIV immunization strategy to elicit protective immunity prior to adolescence. Therefore, the goal of our study was to assess the ability of a B cell lineage-designed HIV envelope SOSIP to induce bnAbs in early life. Infant rhesus macaques (RMs) received either BG505 SOSIP or the germline-targeting BG505 GT1.1 SOSIP (n=5/group) with the 3M-052-SE adjuvant at 0, 6, and 12 weeks of age. All infant RMs were then boosted with the BG505 SOSIP at weeks 26, 52 and 78, mimicking a pediatric immunization schedule of multiple vaccine boosts within the first two years of life. Both immunization strategies induced durable, high magnitude binding antibodies and plasma autologous virus neutralization that primarily targeted the CD4-binding site (CD4bs) or C3/465 epitope. Notably, three BG505 GT1.1-immunized infants exhibited a plasma HIV neutralization signature reflective of VRC01-like CD4bs bnAb precursor development and heterologous virus neutralization. Finally, infant RMs developed precursor bnAb responses at a similar frequency to that of adult RMs receiving a similar immunization strategy. Thus, a multi-dose immunization regimen with bnAb lineage designed SOSIPs is a promising strategy for inducing protective HIV bnAb responses in childhood prior to adolescence when sexual HIV exposure risk begins.

immunology↗

bioRxiv2023

MYC amplifies mitotic perturbations elicited by LXY18 to enable synthetic lethality

The MYC oncoprotein represents an intriguing target for cancer treatment, but its therapeutic potential has been hindered by the absence of specific pharmacological inhibitors. In this study, we demonstrate that the phenoxy quinoline compound LXY18 selectively targets and eliminates cells overexpressing MYC, leaving non-transformed cells unharmed. This synthetic lethality arises from an acute induction of multipolarity, resulting in a persistent arrest in early mitosis followed by cell death in mitosis or after mitotic slippage. Distinctively, LXY18s action contrasts with other antimitotic compounds, as they either fail to induce mitotic arrest or elicit mitotic arrest irrespective of MYC abundance. Furthermore, the MYC abundance in a panel of 98 tumor cell lines correlates with their sensitivity to LXY18. Collectively, our findings uncover LXY18 as an MYC- enabled mitotic blocker and open a new avenue to selectively target MYC-overexpressing tumor cells without affecting normal cells.

cancer biology↗

bioRxiv2023

Machine Learning Based Identification and Characterization of Mast Cells in Eosinophilic Esophagitis

BackgroundEosinophilic esophagitis (EoE) is diagnosed and monitored using esophageal eosinophil levels; however, EoE also exhibits a marked, understudied esophageal mastocytosis. ObjectiveUsing machine learning, we localized and characterized esophageal mast cells to decipher their potential role in disease pathology. MethodsEsophageal biopsy samples (EoE, control) were stained for mast cells by anti-tryptase and imaged using immunofluorescence; high-resolution whole tissue images were digitally assembled. Machine learning software was trained to identify, enumerate, and characterize mast cells, designated Mast Cell-Artificial Intelligence (MC-AI). ResultsMC-AI enumerated cell counts with high accuracy. During active EoE, epithelial mast cells increased and lamina propria (LP) mast cells decreased. In controls and EoE remission patients, papillae had the highest mast cell density and negatively correlated with epithelial mast cell density. Mast cell density in the epithelium and papillae correlated with the degree of epithelial eosinophilic inflammation, basal zone hyperplasia, and LP fibrosis. MC-AI detected greater mast cell degranulation in the epithelium, papillae, and LP in EoE patients compared with control individuals. Mast cells were localized further from the basement membrane in active EoE than EoE remission and controls individuals but were closer than eosinophils to the basement membrane in active EoE. ConclusionUsing MC-AI, we identified a distinct population of homeostatic esophageal papillae mast cells; during active EoE, this population decreases, undergoes degranulation, negatively correlates with epithelial mast cell levels, and significantly correlates with distinct histologic features. Overall, MC-AI provides a means to understand the potential involvement of mast cells in EoE and other disorders. Clinical ImplicationWe have developed a methodology for identifying, enumerating, and characterizing mast cells using artificial intelligence; this has been applied to decipher eosinophilic esophagitis and provides a platform approach for other diseases. Capsule SummaryA machine learning protocol for identifying mast cells, designated Mast Cell-Artificial Intelligence, readily identified spatially distinct and dynamic populations of mast cells in EoE, providing a platform to better understand this cell type in EoE and other diseases.

immunology↗

bioRxiv2023

DrugMap: A quantitative pan-cancer analysis of cysteine ligandability

Cysteine-focused chemical proteomic platforms have accelerated the clinical development of covalent inhibitors of a wide-range of targets in cancer. However, how different oncogenic contexts influence cysteine targeting remains unknown. To address this question, we have developed DrugMap, an atlas of cysteine ligandability compiled across 416 cancer cell lines. We unexpectedly find that cysteine ligandability varies across cancer cell lines, and we attribute this to differences in cellular redox states, protein conformational changes, and genetic mutations. Leveraging these findings, we identify actionable cysteines in NF{kappa}B1 and SOX10 and develop corresponding covalent ligands that block the activity of these transcription factors. We demonstrate that the NF{kappa}B1 probe blocks DNA binding, whereas the SOX10 ligand increases SOX10-SOX10 interactions and disrupts melanoma transcriptional signaling. Our findings reveal heterogeneity in cysteine ligandability across cancers, pinpoint cell-intrinsic features driving cysteine targeting, and illustrate the use of covalent probes to disrupt oncogenic transcription factor activity.

systems biology↗

bioRxiv2023

Yes1-mediated Cul9 phosphorylation promotes the metabolic reprogramming in gastric cancer

Although Cul9 has been implicated in human carcinogenesis, its upstream regulators and roles remain unknown. Herein, we indicate that the Cul9 promoter is hypermethylated in GCs. Bioinformatics, mass spectrometry, and unbiased-kinase screen identify the tyrosine kinase Yes1 as a key regulator of Cul9. Yes1 phosphorylates Cul9 at Y1505, promoting its selective autophagy. Patient-associated mutation of Yes1 or helicobacter pylori infection induces Cul9-Y1505 phosphorylation which switches Cul9 from a tumor-suppressor to an oncogene, as evidenced by the fact that Cul9-Y1505D knockin mice are more susceptible to gastric tumorigenesis than wild-type counterparts. Metabolic profiling and ATAC sequencing reveal that Cul9-Y1505D mutant promotes pyrimidine and purine synthesis pathways in GC. DNA-demethylating drug decitabine or HG78 compound upregulates Cul9 expression and limits GC cell proliferation in a Yes1-dependent manner. The Yes1 inhibitor CH6953755 or Leflunomide and Mycophenolate mofetil (MMF) also impair the malignancy of GC with Cul9 dysregulation. Cul9 in turn binds Yes1 and disrupts Yes1 stability, establishing a feedback circuit. Collectively, our project reveals an unrecognized role of the Yes1-Cul9 loop in GC, suggesting potential therapeutic targets.

cancer biology↗

bioRxiv2023

Genome dilution by cell growth drives starvation-like proteome remodeling in mammalian and yeast cells

Cell size is tightly controlled in healthy tissues and single-celled organisms, but it remains unclear how size influences cell physiology. Increasing cell size was recently shown to remodel the proteomes of cultured human cells, demonstrating that large and small cells of the same type can be biochemically different. Here, we corroborate these results in mouse hepatocytes and extend our analysis using yeast. We find that size-dependent proteome changes are highly conserved and mostly independent of metabolic state. As eukaryotic cells grow larger, the dilution of the genome elicits a starvation-like proteome phenotype, suggesting that growth in large cells is limited by the genome in a manner analogous to a limiting nutrient. We also find that this phenomenon explains many proteomic changes ascribed to yeast aging. Overall, our data suggest that genome concentration is a universal determinant of proteome content in growing cells.

cell biology↗

bioRxiv2023

Competing adaptations maintain non-adaptive variation in a wild cricket population

How emerging adaptive variants interact is an important factor in the evolution of wild populations. However, the opportunity to empirically study this interaction is rare. We recently documented the emergence of an adaptive phenotype curly-wing in Hawaiian populations of field crickets (Teleogryllus oceanicus). Curly-wing inhibits males ability to sing, protecting them from eavesdropping parasitoid flies (Ormia ochracea). Surprisingly, curly-wing co-occurs with similarly protective silent flatwing phenotypes in multiple populations, in which neither phenotype has spread to fixation. These two phenotypes are frequently co-expressed, but since either phenotype sufficiently reduces song amplitude to evade the fly, co-expression confers no additional fitness benefit. Numerous negative fitness consequences are known to accompany flatwing, and we find that curly-wing, too, incurs fitness costs via reduced male courtship success and reduced female longevity. We show through crosses, genomic and mRNA sequencing that curly-wing expression is associated with variation on a single autosome. In parallel analyses of flatwing, our results reinforce previous findings of X-linked single-locus inheritance, with the phenotype likely arising through down-regulation of doublesex. By combining insights about the genetic architecture of these alternative phenotypes with simulations and field observations, we show that the co-occurrence of these two adaptations impedes either from fixing, despite extreme fitness benefits. Interestingly, both flatwing and curly-wing are statistically associated with nearby inversions, which are also retained as polymorphisms. This co-occurrence of similar adaptive forms in the same populations might be more common than generally considered, and could be an important force inhibiting adaptive evolution in wild populations.

evolutionary biology↗

bioRxiv2023

Detecting significantly recurrent genomic connections from simple and complex rearrangements in the cancer genome

The detection of somatic genetic alterations that recur across cancer genomes more than expected by chance has been a major goal of cancer genomics, as these alterations are enriched for "driver" events that promote cancer. Multiple methods have been developed to detect driver point mutations and copy-number variants, but methods to detect driver rearrangements have largely not been pursued. Unlike point mutations and copy-number alterations, which can be assigned to a single genomic locus, rearrangements connect two distant genomic loci, and possibly more in the case of complex or clustered events. Here, we explore genomic features that predict the rate at which any pair of loci will be connected by rearrangements and describe two methods to detect rearrangements that recur more often than this background rate. The first, SVSig-2D, detects pairs of loci that are directly connected by a single rearrangement; the second, SVSig-2Dc also detects loci that are recurrently connected indirectly through two or more rearrangements. When applied to a pan-cancer dataset of over 2,500 cancers, these methods identified 80 significantly recurrent simple rearrangements and 29 complex rearrangements, including both known and novel events. Intriguingly, though both recurrent simple and complex rearrangements tended to be tissue-specific, this was less true for the complex events. The detection of recurrent rearrangements with methods such as these will be an essential component of cancer genomics in the whole-genome sequencing era.

genomics↗

bioRxiv2023

MTGCL: Multi-Task Graph Contrastive Learning for Identifying Cancer Driver Genes from Multi-omics Data

Cancer is a complex disease that typically arises from the accumulation of mutations in driver genes. Identification of cancer driver genes is crucial for understanding the molecular mechanisms of cancer, and developing the targeted therapeutic approaches. With the development of high-throughput biological technology, a large amount of genomic data and protein interaction network data have been generated, which provides abundant data resources for identifying cancer driver genes through computational methods. Given the ability of graph neural networks to effectively integrate graph structure topology information and node features information, some graph neural network-based methods have been developed for identifying cancer driver genes. However, these methods suffer from the sparse supervised signals, and also neglect a large amount of unlabeled node information, thereby affecting their ability to identify cancer driver genes. To tackle these issues, in this work we propose a novel Multi-Task Graph Contrastive Learning framework (called MTGCL) to identify cancer driver genes. By using self-supervised graph contrastive learning to fully utilize the unlabeled node information, MTGCL designs an auxiliary task module to enhance the performance of the main task of driver gene identification. MTGCL simultaneously trains the auxiliary task and main task, and shares the graph convolutional encoder weights, so that the main task enhances the discriminative ability of the auxiliary task via supervised learning, whereas the auxiliary task exploits the unlabeled node information to refine the node representation learning of the main task. The experimental results on pan-cancer and some specific cancers demonstrate the effectiveness of MTGCL in identifying the cancer driver genes. In addition, integrating multi-omics features extracted from multiple cancer-related databases can greatly enhance the performance of identifying cancer driver genes, especially, somatic mutation features can effectively improve the performance of identifying specific cancer driver genes. The source code and data are available at https://github.com/NWPU-903PR/MTGCL. Author SummaryIdentifying cancer driver genes that causally contribute to cancer initiation and progression is essential for comprehending the molecular mechanisms of cancer and developing the targeted therapeutic strategies. However, wet-lab experiments are time-consuming and labor-intensive. The advent of high-throughput multi-omics technology provides an opportunity for identifying the cancer driver genes through data-driven computing approaches. Nevertheless, effectively integrating these omics data to identify cancer driver genes poses significant challenges. Existing computational methods exhibit certain limitations. For instance, conventional approaches (e.g., gene mutation frequency-based methods, network-based methods) often focus on a single omics data, while existing deep learning-based methods have not fully utilized the abundant unlabeled node information, so that their identification accuracy is not high enough. Thus, by fully utilizing multidimensional genomics data and molecular interaction networks, we propose a multi-task learning framework (called MTGCL) to identify cancer driver genes. MTGCL synergistically combines graph convolutional neural networks with graph contrastive learning. The experimental results validate the power of MTGCL for identifying cancer driver genes.

bioinformatics↗

bioRxiv2023

Analysis the molecular similarity of least common amino acid sites in ACE2 receptor to predict the potential susceptible species for SARS-CoV-2

This research offers a bioinformatics approach to forecasting both domestic and wild animals likelihood of being susceptible to SARS-CoV-2 infection. Genomic sequencing can resolve phylogenetic relationships between the virus and the susceptible host. The genome sequence of SARS-CoV-2 is highly interactive with the specific sequence region of the ACE2 receptor of the host species. We further evaluate this concept to identify the most important SARS-CoV-2 binding amino acid sites in the ACE2 receptor sequence through the common similarity of the last common amino acid sites (LCAS) in known susceptible host species. Therefore, the SARS-CoV-2 viral genomic interacting key amino acid region in the ACE2 receptor sequence of known susceptible human host was summarized and compared with other reported known SARS-CoV-2 susceptible host species. We identified the 10 most significant amino acid sites for interaction with SARS-CoV-2 infection from the ACE2 receptor sequence region based on the LCAS similarity pattern in known sensitive SARS-CoV-2 hosts. The most significant 10 LCAS were further compared with ACE2 receptor sequences of unknown species to evaluate the similarity of the last common amino acid pattern (LCAP). We predicted the probability of SARS-CoV-2 infection risk in unknown species through the LCAS similarity pattern. This method can be used as a screening tool to assess the risk of SARS-CoV-2 infection in domestic and wild animals to prevent outbreaks of infection. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=98 SRC="FIGDIR/small/562198v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@1c77e4corg.highwire.dtl.DTLVardef@34cf43org.highwire.dtl.DTLVardef@113734forg.highwire.dtl.DTLVardef@1f763c8_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2023

Double-strand break repair-associated intragenic deletions and tandem duplications suggest the architecture of the repair replication fork

Double-strand break (DSB) repair is associated with a 1000-fold increase in mutations compared to normal replication of the same sequences. In budding yeast, repair of an HO endonuclease-induced DSB at the MAT locus can be repaired by using a homologous, heterochromatic HMR::Kl-URA3 donor harboring a transcriptionally silenced URA3 gene, resulting in a MAT::URA3 (Ura+) repair product where URA3 is expressed. Repair-associated ura3- mutations can be selected by resistance to 5-fluoroorotic acid (FOA). Using this system, we find that a major class of mutations are -1 deletions, almost always in homonucleotide runs, but there are few +1 insertions. In contrast, +1 and -1 insertions in homonucleotide runs are nearly equal among spontaneous mutations. Approximately 10% of repair-associated mutations are interchromosomal template switches (ICTS), even though the K. lactis URA3 sequence embedded in HMR is only 72% identical with S. cerevisiae ura3-52 sequences on a different chromosome. ICTS events begin and end in regions of short microhomology, averaging 7 bp. Long microhomologies are favored, but some ICTS junctions are as short as 2 bp. Both repair-associated intragenic deletions (IDs) and tandem duplications (TDs) are recovered, with junctions sharing short stretches of, on average, 6 bp of microhomology. Intragenic deletions are more than 5 times more frequent than TDs. IDs have a mean length of 60 bp, but, surprisingly there are almost no deletions shorter than 25 bp. In contrast, TDs average only 12 bp. The usage of microhomologies among intragenic deletions is not strongly influenced by the degree of adjacent homeology. Together, these data provide a picture of the structure of the repair replication fork. We suggest that IDs and TDs occur within the migrating D-loop in which DNA polymerase {delta} copies the template, where the 3 end of a partly copied new DNA strand can dissociate and anneal with a single-stranded region of microhomology that lies either in front or behind the 3 end, within the open structure of a migrating D-loop. Our data suggest that [~]100 bp ahead of the polymerase is "open," but that part of the repair replication apparatus remains bound in the 25 bp ahead of the newly copied DNA, preventing annealing. In contrast, the template region behind the polymerase appears to be rapidly reannealed, limiting template switching to a very short region.

genetics↗

bioRxiv2023

A sequence context-based germline filter for structural variant calling from tumor samples without paired normal

Although several recent studies have characterized structural variants (SVs) in germline and cancer genomes, the features of SVs in these different contexts have not been directly compared. We examined similarities and differences between 2 million germline and 115 thousand tumor SVs from a cohort of 963 patients from The Cancer Genome Atlas (TCGA). We found significant differences in features related to their genomic sequences and localization that suggest differences between SV-generating processes and selective pressures. For example, we found that transposon-mediated processes shape germline much more than somatic SVs, while somatic SVs more frequently show features characteristic of chromoanagenesis. These differences were extensive enough to enable us to develop a classifier-"the great GaTSV"-that accurately distinguishes between germline and cancer SVs in tumor samples that lack a matched normal sample.

bioinformatics↗

bioRxiv2023

G protein subunit Gγ13-mediated signaling pathway is critical to the inflammation resolution and functional recovery of severely injured lungs

Tuft cells are a group of rare epithelial cells that can detect pathogenic microbes and parasites. Many of these cells express signaling proteins initially found in taste buds. It is, however, not well understood how these taste signaling proteins contribute to the response to the invading pathogens or to the recovery of injured tissues. In this study, we conditionally nullified the signaling G protein subunit G{gamma}13 and found that the number of ectopic tuft cells in the injured lung was reduced following the infection of the influenza virus H1N1. Furthermore, the infected mutant mice exhibited significantly larger areas of lung injury, increased macrophage infiltration, severer pulmonary epithelial leakage, augmented pyroptosis and cell death, greater bodyweight loss, slower recovery, worsened fibrosis and increased fatality. Our data demonstrate that the G{gamma}13-mediated signal transduction pathway is critical to tuft cells-mediated inflammation resolution and functional repair of the damaged lungs.To our best knowledge, it is the first report indicating subtype-specific contributions of tuft cells to the resolution and recovery.

immunology↗

bioRxiv2023

Innate immune memory after brain injury drives inflammatory cardiac dysfunction

The enormous medical burden of stroke is not only due to the brain injury itself and the acute systemic effects, but is largely determined by chronic comorbidities that develop secondarily after stroke. We hypothesized that the high rate of comorbidity developing after a stroke might have a shared immunological cause, however, the chronic effects of brain injury on systemic immunity have so far been barely investigated. Here, we identified myeloid innate immune memory as a cause of remote organ dysfunction after stroke. Using single-cell sequencing, we identified persistent pro-inflammatory transcriptomic changes in resident monocytes/macrophages in multiple organs one month after experimental ischemic brain injury, which was particularly abundant in the heart and associated with the development of cardiac fibrosis and diastolic dysfunction. A similar phenotype was seen in myocardial autopsy samples from stroke versus control patients. We observed chronic functional changes in myeloid hematopoiesis driven by post-stroke IL-1{beta}-mediated epigenetic changes. These alterations could be transplanted to naive recipient mice and were sufficient to induce cardiac dysfunction. By effectively blocking the trafficking of pro-inflammatory monocytes from the bone marrow to the heart using a dual CCR2/5 inhibitor, we successfully prevented post-stroke cardiac dysfunction. This approach holds promising potential as a novel immune-targeted secondary prevention therapy. We anticipate that the epigenetic immune reprogramming mechanisms detailed here for the brain-heart axis could be generalized to provide a novel framework for explaining the development of various comorbidities after acute tissue injury in remote organs.

immunology↗

bioRxiv2023

A resource for probing influences of perinatal factors on neurodevelopment in 3-10-years-old Chinese children

Adverse perinatal factors can disrupt the normal development of the brain, with potential long-term impacts on childrens overall development. Currently, the neuropathological mechanisms by which these factors lead to various neurodevelopmental disorders (NDDs) remain largely unknown. An open resource that integrate perinatal factors with brain and mental health development is essential for investigating NDD-related aetiology. In this Data Descriptor, we introduce a multicentre database containing information on perinatal factors that influence childrens brain-mind development, namely, periCBD, that combines neuroimaging and behavioural phenotypes with perinatal factors associated with a high incidence of NDDs at county/region/central district hospitals. PeriCBD was designed to establish a platform for the investigation of individual differences in brain-mind development among children aged 3-10 years are associated with perinatal factors. Ultimately, our goal was to develop an early prediction and screening model for NDDs that leverages normative data to facilitate NDD aetiology research. Herein, we provide a systematic overview of the data acquisition/cleaning/quality control/sharing, processes of periCBD and present preliminary brain-mind associations.

neuroscience↗

bioRxiv2023

Inhibition of the macrophage demethylase LSD1 reverses Leishmania amazonensis-induced transcriptomic changes and causes a decrease in parasite load

Intracellular pathogens exploit host cell functions to favor their own survival. In recent years, the subversion of epigenetic regulation has emerged as a key microbial strategy to modify host cell gene expression and evade antimicrobial immune responses. Using the protozoan parasite Leishmania as a model system, we have recently demonstrated that infection causes histone H3 hypomethylation, which is associated with the establishment of an anti-inflammatory phenotype, suggesting that host cell demethylases may play a role in the intracellular survival of these parasites. In this study, we combined pharmacological inhibition with RNA sequencing and quantitative immune-precipitation analysis to investigate the role of the macrophage lysine demethylase LSD1 (KDM1a) in Leishmania intracellular infection in vitro. Treatment of infected macrophages with validated, LSD1-specific inhibitors resulted in a significant reduction in parasite burden. We confirmed the impact of these inhibitors on LSD1 activity within macrophage nuclear extracts using an in vitro demethylase assay and established their LSD1 target engagement in situ by cellular thermal shift assay. RNA-seq analysis of infected and inhibitor-treated macrophages linked parasite killing to a partial reversion of infection-dependent expression changes, restoring the macrophage anti-microbial response and limiting cholesterol biosynthesis. While we ruled out any impact of Leishmania on LSD1 expression or localization, we uncovered significant alterations in LSD1 complex formation within infected macrophages, involving unique interactions with host cell regulatory proteins such as Rcor-1. Our study sheds important new light on the epigenetic mechanisms of macrophage immuno-metabolic subversion by intracellular Leishmania and identifies LSD1 as a potential candidate for host-directed, anti-leishmanial therapy.

cell biology↗

bioRxiv2023

Integrative Transcriptomic Analysis of Anterior and Posterior IOP-Controlling Tissues in Glaucoma Reveals Enrichment of MHC-II Pathway and T-Cell Infiltration Signatures

BackgroundGlaucoma is a multifactorial neurodegenerative disease indicating by abnormalities in the whole eye, apart from optic neuropathy, and is often associated with abnormal intraocular pressure (IOP). However, the underlying pathological mechanisms of glaucoma and the management of IOP remain largely unaddressed. Emerging evidence suggests the involvement of immune changes in glaucoma. Therefore, characterizations of immune alternations by molecular profiling of IOP-controlling tissues from both anterior and posterior eye segments including trabecular meshwork (TM) and choroid may provide insights to the disease mechanism. MethodsBulk TM microarray data (GSE138125 and GSE27276) from primary open-angle glaucoma (POAG) and choroid single-cell transcriptome data (GSE203499) from glaucoma were downloaded from Gene Expression Omnibus (GEO) database. The two qualified TM datasets were integrated. Analyses of differential expression genes (DEGs), functional and pathway annotations, immune infiltration, and disease-related modules were performed using the POAG bulk data. Similarly, DEGs and pathway annotations, single-cell trajectory and switch gene analysis, and cell-cell communications were conducted using the choroid single-cell RNA-sequencing data. Finally, integrated analyses from the two studies were conducted to determine the glaucomatous changes between anterior and posterior IOP-controlling eye tissues. ResultsA total of 102 DEGs between POAG and healthy tissues were identified from the TM data. Gene set enrichment analysis revealed five glaucoma-enriched pathways: ATP generation and metabolism, cornification and keratinization, metabolism of reactive oxygen species (ROS), humoral immune response, and platelet aggregation. Significant immune infiltrations were observed in POAG tissue, including total T cells (excluding CD8+ T cells), NK cells, monocytic lineage, endothelial cells, and fibroblasts. Furthermore, the POAG enriched pathways are primarily from T-cell infiltrations. On the other hand, fourteen distinct cell clusters were identified from the choroid single-cell data. The most evident findings were fibrosis, represented by extracellular matrix (ECM), the actin-binding pathways enrichment in pericyte-fibroblast transition, reduction in light sensitivity of melanocytes, and complex immune changes among all cell types in the pathological conditions compared to control. Taken together, an integrated analyses between the TM microarray and choroid single-cell data result in 111 significantly dysregulated genes in the disease state. These key genes participated in immune and inflammatory reactions (DUSP1, ADM, CD74, CEBPD, HLA-DPA1, ZNF331), served as potential biomarkers for neurodegenerative and autoimmune diseases (such as NR4A2), or regulated membrane integrity, vasculature calcification, ECM interactions, and cell morphology (PTP4A1, MGP, and RASD1). Overall, our integrated data analyses might provide insight to the understanding of the disease mechanism. ConclusionBy integrating bulk microarray data from TM and single-cell transcriptome data from the choroid, we systematically evaluated the glaucomatous transcriptomic changes between the anterior and posterior IOP-controlling tissue from ocular. Results indicated there was a significantly enrichment of genes belonging to the MHC-II pathway and T-cell infiltration in the disease state, opening new avenues for biomarkers discovery and therapeutic interventions to glaucoma.

bioinformatics↗