Comparative transcriptomics revealed the mechanism of Stenotrophomonas rhizophila JC1 response and biosorption to Pb2.

Nowadays, there is limited research focusing on the biosorption of Pb2+ through microbial process, particularly at the level of gene expression. To overcome this knowledge gap, we studied the adsorption capacity of Stenotrophomonas rhizophila JC1 to Pb2+, and investigated the physiological mechanism by means of SEM, EDS, FTIR, membrane permeability detection, and investigated the molecular mechanism through comparative transcriptomics. The results showed that after 16 h of cultivation, the biosorption capacity of JC1 for 100 mg/L of Pb2+ reached at 79.8%. The main mechanism of JC1 adsorb Pb2+ is via intracellular accumulation, accounting for more than 90% of the total adsorption. At the physiological level, Pb2+ can precipitate with anion functional groups (e.g., -OH, -NH) on the bacterial cell wall or undergo replacement reaction with cell component elements (e.g., Si, Ca) to adsorb Pb2+ outside of the cell wall, thus accomplishing extracellular adsorption of Pb2+ by strains. Furthermore, the cell membrane acts as a "switch" that inhibits the entry of metal ions into the cell from the plasma membrane. At the molecular level, the gene pbt specificity is responsible for the adsorption of Pb2+ by JC1. In addition, phosphate permease is a major member of the ABC transporter family involved in Pb2+, and czcA/cusA or Co2+/Mg2+ efflux protein plays an important role in the efflux of Pb2+ in JC1. Further, cellular macromolecule biosynthesis, inorganic cation transmembrane transport, citrate cycle (TCA) and carbon metabolism pathways all play crucial roles in the response of strain JC1 to Pb2+ stress.

Prognostic significance of CHCHD2P9 and ZNF204P in breast cancer: exploring their expression patterns and associations with malignancy-related genes.

BACKGROUND: Non-coding RNAs (ncRNAs) have a crucial impact on diverse cellular processes, influencing the progression of breast cancer (BC). The objective of this study was to identify novel ncRNAs in BC with potential effects on patient survival and disease progression. METHODS: We utilized the cancer genome atlas data to identify ncRNAs associated with BC pathogenesis. We explored the association between these ncRNA expressions and survival rates. A risk model was developed using candidate ncRNA expression and beta coefficients obtained from a multivariate Cox regression analysis. Co-expression networks were constructed to determine potential relationships between these ncRNAs and molecular pathways. For validation, we employed BC samples and the RT-qPCR method. RESULTS: Our findings revealed a noteworthy increase in the expression of AC093850.2 and CHCHD2P9 in BC, which was correlated with a poor prognosis. In contrast, ADAMTS9-AS1 and ZNF204P displayed significant downregulation and were associated with a favorable prognosis. The risk model, incorporating these four ncRNAs, robustly predicted patient survival. The co-expression network showed an effective association between levels of AC093850.2, CHCHD2P9, ADAMTS9-AS1, and ZNF204P and genes involved in pathways like metastasis, angiogenesis, metabolism, and DNA repair. The RT-qPCR results verified notable alterations in the expression of CHCHD2P9 and ZNF204P in BC samples. Pan-cancer analyses revealed alterations in the expression of these two ncRNAs across various cancer types. CONCLUSION: This study presents a groundbreaking discovery, highlighting the substantial dysregulation of CHCHD2P9 and ZNF204P in BC and other cancers, with implications for patient survival.

Bayesian genome-wide TWAS with reference transcriptomic data of brain and blood tissues identified 141 risk genes for Alzheimer's disease dementia.

BACKGROUND: Transcriptome-wide association study (TWAS) is an influential tool for identifying genes associated with complex diseases whose genetic effects are likely mediated through transcriptome. TWAS utilizes reference genetic and transcriptomic data to estimate effect sizes of genetic variants on gene expression (i.e., effect sizes of a broad sense of expression quantitative trait loci, eQTL). These estimated effect sizes are employed as variant weights in gene-based association tests, facilitating the mapping of risk genes with genome-wide association study (GWAS) data. However, most existing TWAS of Alzheimer's disease (AD) dementia are limited to studying only cis-eQTL proximal to the test gene. To overcome this limitation, we applied the Bayesian Genome-wide TWAS (BGW-TWAS) method to leveraging both cis- and trans- eQTL of brain and blood tissues, in order to enhance mapping risk genes for AD dementia. METHODS: We first applied BGW-TWAS to the Genotype-Tissue Expression (GTEx) V8 dataset to estimate cis- and trans- eQTL effect sizes of the prefrontal cortex, cortex, and whole blood tissues. Estimated eQTL effect sizes were integrated with the summary data of the most recent GWAS of AD dementia to obtain BGW-TWAS (i.e., gene-based association test) p-values of AD dementia per gene per tissue type. Then we used the aggregated Cauchy association test to combine TWAS p-values across three tissues to obtain omnibus TWAS p-values per gene. RESULTS: We identified 85 significant genes in prefrontal cortex, 82 in cortex, and 76 in whole blood that were significantly associated with AD dementia. By combining BGW-TWAS p-values across these three tissues, we obtained 141 significant risk genes including 34 genes primarily due to trans-eQTL and 35 mapped risk genes in GWAS Catalog. With these 141 significant risk genes, we detected functional clusters comprised of both known mapped GWAS risk genes of AD in GWAS Catalog and our identified TWAS risk genes by protein-protein interaction network analysis, as well as several enriched phenotypes related to AD. CONCLUSION: We applied BGW-TWAS and aggregated Cauchy test methods to integrate both cis- and trans- eQTL data of brain and blood tissues with GWAS summary data, identifying 141 TWAS risk genes of AD dementia. These identified risk genes provide novel insights into the underlying biological mechanisms of AD dementia and potential gene targets for therapeutics development.

Joint effects of CD8A and ICOS in Long QT Syndrome (LQTS) and Beckwith-Wiedemann Syndrome (BWS).

BACKGROUND: Long QT Syndrome (LQTS) and Beckwith-Wiedemann Syndrome (BWS) are complex disorders with unclear origins, underscoring the need for in-depth molecular investigations into their mechanisms. The main aim of this study is to identify the shared key genes between LQTS and BWS, shedding light on potential common molecular pathways underlying these syndromes. METHODS: The LQTS and BWS datasets are available for download from the GEO database. Differential expression genes (DEGs) were identified. Weighted gene co-expression network analysis (WGCNA) was used to detect significant modules and central genes. Gene enrichment analysis was performed. CIBERSORT was used for immune cell infiltration analysis. The predictive protein interaction (PPI) network of core genes was constructed using STRING, and miRNAs regulating central genes were screened using TargetScan. RESULTS: Five hundred DEGs associated with Long QT Syndrome and Beckwith-Wiedemann Syndrome were identified. GSEA analysis revealed enrichment in pathways such as T cell receptor signaling, MAPK signaling, and adrenergic signaling in cardiac myocytes. Immune cell infiltration indicated higher levels of memory B cells and naive CD4 T cells. Four core genes (CD8A, ICOS, CTLA4, LCK) were identified, with CD8A and ICOS showing low expression in the syndromes and high expression in normal samples, suggesting potential inverse regulatory roles. CONCLUSION: The expression of CD8A and ICOS is low in long QT syndrome and Beckwith-Wiedemann syndrome, indicating their potential as key genes in the pathogenesis of these syndromes. The identification of shared key genes between LQTS and BWS provides insights into common molecular mechanisms underlying these disorders, potentially facilitating the development of targeted therapeutic strategies.

Machine learning-based identification of a cell death-related signature associated with prognosis and immune infiltration in glioma.

Accumulating evidence suggests that a wide variety of cell deaths are deeply involved in cancer immunity. However, their roles in glioma have not been explored. We employed a logistic regression model with the shrinkage regularization operator (LASSO) Cox combined with seven machine learning algorithms to analyse the patterns of cell death (including cuproptosis, ferroptosis, pyroptosis, apoptosis and necrosis) in The Cancer Genome Atlas (TCGA) cohort. The performance of the nomogram was assessed through the use of receiver operating characteristic (ROC) curves and calibration curves. Cell-type identification was estimated by using the cell-type identification by estimating relative subsets of known RNA transcripts (CIBERSORT) and single sample gene set enrichment analysis methods. Hub genes associated with the prognostic model were screened through machine learning techniques. The expression pattern and clinical significance of MYD88 were investigated via immunohistochemistry (IHC). The cell death score represents an independent prognostic factor for poor outcomes in glioma patients and has a distinctly superior accuracy to that of 10 published signatures. The nomogram performed well in predicting outcomes according to time-dependent ROC and calibration plots. In addition, a high-risk score was significantly related to high expression of immune checkpoint molecules and dense infiltration of protumor cells, these findings were associated with a cell death-based prognostic model. Upregulated MYD88 expression was associated with malignant phenotypes and undesirable prognoses according to the IHC. Furthermore, high MYD88 expression was associated with poor clinical outcomes and was positively related to CD163, PD-L1 and vimentin expression in the in-horse cohort. The cell death score provides a precise stratification and immune status for glioma. MYD88 was found to be an outstanding representative that might play an important role in glioma.

Differential expression of circRNAs during osteogenic/odontogenic differentiation of stem cells from apical papilla promoted by blue light-emitting diode.

BACKGROUND: Circular RNA (circRNA) is a key player in regulating the multidirectional differentiation of stem cells. Previous research by our group found that the blue light-emitting diode (LED) had a promoting effect on the osteogenic/odontogenic differentiation of human stem cells from apical papilla (SCAPs). This research aimed to investigate the differential expression of circRNAs during the osteogenic/odontogenic differentiation of SCAPs regulated by blue LED. MATERIALS AND METHODS: SCAPs were divided into the irradiation group (4 J/cm2) and the control group (0 J/cm2), and cultivated in an osteogenic/odontogenic environment. The differentially expressed circRNAs during osteogenic/odontogenic differentiation of SCAPs promoted by blue LED were detected by high-throughput sequencing, and preliminarily verified by qRT-PCR. Functional prediction of these circRNAs was performed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) and the circRNA-miRNA-mRNA networks were also constructed. RESULTS: It showed 301 circRNAs were differentially expressed. GO and KEGG analyses suggested that these circRNAs were associated with some signaling pathways related to osteogenic/odontogenic differentiation. And the circRNA-miRNA-mRNA networks were also successfully constructed. CONCLUSION: CircRNAs were involved in the osteogenic/odontogenic differentiation of SCAPs promoted by blue LED. In this biological process, circRNA-miRNA-mRNA networks served an important purpose, and circRNAs regulated this process through certain signaling pathways.

Stemness related lncRNAs signature for the prognosis and tumor immune microenvironment of ccRCC patients.

Long non-coding RNAs (lncRNAs) and cancer stem cells (CSCs) are crucial for the growth, migration, recurrence, and medication resistance of tumors. However, the impact of lncRNAs related to stemness on the outcome and tumor immune microenvironment (TIME) in clear cell renal cell carcinoma (ccRCC) is still unclear. In this study, we aimed to predict the outcome and TIME of ccRCC by constructing a stem related lncRNAs (SRlncRNAs) signature. We firstly downloaded ccRCC patients' clinical data and RNA sequencing data from UCSC and TCGA databases, and abtained the differentially expressed lncRNAs highly correlated with stem index in ccRCC through gene expression differential analysis and Pearson correlation analysis. Then, we selected suitable SRlncRNAs for constructing a prognostic signature of ccRCC patients by LASSO Cox regression. Further, we used nomogram and Kaplan Meier curves to evaluate the SRlncRNA signature for the prognose in ccRCC. At last, we used ssGSEA and GSVA to evaluate the correlation between the SRlncRNAs signature and TIME in ccRCC. Finally, We obtained a signtaure based on six SRlncRNAs, which are correlated with TIME and can effectively predict the ccRCC patients' prognosis. The SRlncRNAs signature may be a noval prognostic indicator in ccRCC.

Investigating molecular markers linked to acute myocardial infarction and cuproptosis: bioinformatics analysis and validation in the AMI mice model.

Cuproptosis-related key genes play a significant role in the pathological processes of acute myocardial infarction (AMI). However, a complete understanding of the molecular mechanisms behind this participation remains elusive. This study was designed to identify genes and immune cells critical to AMI pathogenesis. Based on the GSE48060 dataset (31 AMI patients and 21 healthy persons, GPL570-55999), we identified genes associated with dysregulated cuproptosis and the activation of immune responses between normal subjects and patients with a first myocardial attack. Two molecular clusters associated with cuproptosis were defined in patients with AMI. Immune infiltration analysis showed that there was significant immunity heterogeneity among different clusters. Multiple immune responses were closely associated with Cluster2-specific differentially expressed genes (DEGs). The generalized linear model machine model presented the best discriminative performance with relatively lower residual and root mean square error, and a higher area under the curve (AUC = 0.870). A final two-gene-based generalized linear model was constructed, exhibiting satisfactory performance in two external validation datasets (AUC = 0.719, GSE66360 and AUC = 0.856, GSE123342). Column graph, calibration curve, and decision curve analyses also proved the accuracy of AMI prediction. We also constructed a mouse C57BL/6 model of AMI (3 h, 48 h, and 1 week) and used qRT-PCR and immunofluorescence to detect the expression changes of CBLB and ZNF302. In this study, we present a systematic analysis of the complex relationship between cuproptosis and a first AMI attack, and provide new insights into the diagnosis and treatment of AMI.

Gene expression and immune infiltration analysis comparing lesioned and preserved subchondral bone in osteoarthritis.

Background: Osteoarthritis (OA) is a degenerative disease requiring additional research. This study compared gene expression and immune infiltration between lesioned and preserved subchondral bone. The results were validated using multiple tissue datasets and experiments. Methods: Differentially expressed genes (DEGs) between the lesioned and preserved tibial plateaus of OA patients were identified in the GSE51588 dataset. Moreover, functional annotation and protein-protein interaction (PPI) network analyses were performed on the lesioned and preserved sides to explore potential therapeutic targets in OA subchondral bones. In addition, multiple tissues were used to screen coexpressed genes, and the expression levels of identified candidate DEGs in OA were measured by quantitative real-time polymerase chain reaction. Finally, an immune infiltration analysis was conducted. Results: A total of 1,010 DEGs were identified, 423 upregulated and 587 downregulated. The biological process (BP) terms enriched in the upregulated genes included "skeletal system development", "sister chromatid cohesion", and "ossification". Pathways were enriched in "Wnt signaling pathway" and "proteoglycans in cancer". The BP terms enriched in the downregulated genes included "inflammatory response", "xenobiotic metabolic process", and "positive regulation of inflammatory response". The enriched pathways included "neuroactive ligand-receptor interaction" and "AMP-activated protein kinase signaling". JUN, tumor necrosis factor α, and interleukin-1ß were the hub genes in the PPI network. Collagen XI A1 and leucine-rich repeat-containing 15 were screened from multiple datasets and experimentally validated. Immune infiltration analyses showed fewer infiltrating adipocytes and endothelial cells in the lesioned versus preserved samples. Conclusion: Our findings provide valuable information for future studies on the pathogenic mechanism of OA and potential therapeutic and diagnostic targets.

Genome-wide identification and expression analysis of the WRKY gene family in Rhododendron henanense subsp. lingbaoense.

Background: This work explored the characteristics of the WRKY transcription factor family in Rhododendron henanense subsp. lingbaoense (Rhl) and the expression patterns of these genes under abiotic stress by conducting bioinformatics and expression analyses. Methods: RhlWRKY genes were identified from a gene library of Rhl. Various aspects of these genes were analyzed, including genetic structures, conserved sequences, physicochemical properties, cis-acting elements, and chromosomal location. RNA-seq was employed to analyze gene expression in five different tissues of Rhl: roots, stems, leaves, flowers, and hypocotyls. Additionally, qRT-PCR was used to detect changes in the expression of five RhlWRKY genes under abiotic stress. Result: A total of 65 RhlWRKY genes were identified and categorized into three subfamilies based on their structural characteristics: Groups I, II, and III. Group II was further divided into five subtribes, with shared similar genetic structures and conserved motifs among members of the same subtribe. The physicochemical properties of these proteins varied, but the proteins are generally predicted to be hydrophilic. Most proteins are predicted to be in the cell nucleus, and distributed across 12 chromosomes. A total of 84 cis-acting elements were discovered, with many related to responses to biotic stress. Among the identified RhlWRKY genes, there were eight tandem duplicates and 97 segmental duplicates. The majority of duplicate gene pairs exhibited Ka/Ks values <1, indicating purification under environmental pressure. GO annotation analysis indicated that WRKY genes regulate biological processes and participate in a variety of molecular functions. Transcriptome data revealed varying expression levels of 66.15% of WRKY family genes in all five tissue types (roots, stems, leaves, flowers, and hypocotyls). Five RhlWRKY genes were selected for further characterization and there were changes in expression levels for these genes in response to various stresses. Conclusion: The analysis identified 65 RhlWRKY genes, among which the expression of WRKY_42 and WRKY_17 were mainly modulated by the drought and MeJA, and WRKY_19 was regulated by the low-temperature and high-salinity conditions. This insight into the potential functions of certain genes contributes to understanding the growth regulatory capabilities of Rhl.

Transcriptomics to evaluate the influence mechanisms of ethanol on the ester production of Wickerhamomyces anomalus with the induction of lactic acid.

Wickerhamomyces anomalus is one of the most important ester-producing strains in Chinese baijiu brewing. Ethanol and lactic acid are the main metabolites produced during baijiu brewing, but their synergistic influence on the growth and ester production of W. anomalus is unclear. Therefore, in this paper, based on the contents of ethanol and lactic acid during Te-flavor baijiu brewing, the effects of different ethanol concentrations (3, 6, and 9% (v/v)) combined with 1% lactic acid on the growth and ester production of W. anomalus NCUF307.1 were studied and their influence mechanisms were analyzed by transcriptomics. The results showed that the growth of W. anomalus NCUF307.1 under the induction of lactic acid was inhibited by ethanol. Although self-repair mechanism of W. anomalus NCUF307.1 induced by lactic acid was initiated at all concentrations of ethanol, resulting in significant up-regulation of genes related to the Genetic Information Processing pathway, such as cell cycle-yeast, meiosis-yeast, DNA replication and other pathways. However, the accumulation of reactive oxygen species and the inhibition of pathways associated with carbohydrate and amino acid metabolism may be the main reason for the inhibition of growth in W. anomalus NCUF307.1. In addition, 3% and 6% ethanol combined with 1% lactic acid could promote the ester production of W. anomalus NCUF307.1, which may be related to the up-regulation of EAT1, ADH5 and TGL5 genes, while the inhibition in 9% ethanol may be related to down-regulation of ATF2, EAT1, ADH2, ADH5, and TGL3 genes.

Comparative physiological and transcriptomic analysis of sono-biochemical control over post-acidification of Lactobacillus delbrueckii subsp. bulgaricus.

Thermosonication (UT) prestress treatments combining with varied fermentation patterns has been revealed as an effective method to regulate post-acidification as exerted by Lactobacillus delbrueckii subsp. bulgaricus (L. delbrueckii), but sono-biochemical controlling mechanisms remain elusive. This study employed physiological and transcriptomic analysis to explore the response mechanism of L. delbrueckii to UT-induced microstress (600 W, 33 kHz, 10 min). UT stress-induced inhibition of acidification of L. delbrueckii during (post)-fermentation was first confirmed, relying on the UT process parameters such as stress exposure duration and UT power. The significantly enhanced membrane permeability in cells treated by 600 W for 10 min than the microbes stressed by 420 W for 20 min suggested the higher dependence of UT-derived stresses on the treatment durations, relative to the ultrasonic powers. In addition, ultrasonication treatment-induced changes in cell membrane integrity enhanced and/or disrupted permeability of L. delbrueckii, resulting in an imbalance in intracellular conditions associated with corresponding alterations in metabolic behaviors and fermentation efficiencies. UT-prestressed inoculum exhibited a 21.46% decrease in the membrane potential during the lag phase compared to untreated samples, with an intracellular pH of 5.68 ± 0.12, attributed to the lower activities of H+-ATPase and lactate dehydrogenase due to UT stress pretreatments. Comparative transcriptomic analysis revealed that UT prestress influenced the genes related to glycolysis, pyruvate metabolism, fatty acid synthesis, and ABC transport. The genes encoding 3-oxoacyl-[acyl-carrier-protein] reductases I, II, and III, CoA carboxylase, lactate dehydrogenase, pyruvate oxidase, glucose-6-phosphate isomerase, and glycerol-3-phosphate dehydrogenase were downregulated, thus identifying the relevance of the UT microstresses-downregulated absorption and utilization of carbohydrates with the attenuated fatty acid production and energy metabolisms. These findings could contribute to provide a better understanding of the inactivated effects on the post-acidification of L. delbrueckii by ultrasonic pretreatments, thus providing theoretical basis for the targeted optimization of acidification inhibition efficiencies for yogurt products during chilled preservation processes.

Co-expression analysis reveals distinct alliances around two carbon fixation pathways in hydrothermal vent symbionts.

Most autotrophic organisms possess a single carbon fixation pathway. The chemoautotrophic symbionts of the hydrothermal vent tubeworm Riftia pachyptila, however, possess two functional pathways: the Calvin-Benson-Bassham (CBB) and the reductive tricarboxylic acid (rTCA) cycles. How these two pathways are coordinated is unknown. Here we measured net carbon fixation rates, transcriptional/metabolic responses and transcriptional co-expression patterns of Riftia pachyptila endosymbionts by incubating tubeworms collected from the East Pacific Rise at environmental pressures, temperature and geochemistry. Results showed that rTCA and CBB transcriptional patterns varied in response to different geochemical regimes and that each pathway is allied to specific metabolic processes; the rTCA is allied to hydrogenases and dissimilatory nitrate reduction, whereas the CBB is allied to sulfide oxidation and assimilatory nitrate reduction, suggesting distinctive yet complementary roles in metabolic function. Furthermore, our network analysis implicates the rTCA and a group 1e hydrogenase as key players in the physiological response to limitation of sulfide and oxygen. Net carbon fixation rates were also exemplary, and accordingly, we propose that co-activity of CBB and rTCA may be an adaptation for maintaining high carbon fixation rates, conferring a fitness advantage in dynamic vent environments.

Transcriptome responses of Arabidopsis to necrotrophic fungus Alternaria brassicae reveal pathways and candidate genes associated with resistance.

Alternaria leaf blight (ALB), caused by a necrotrophic fungus Alternaria brassicae is a serious disease of oleiferous Brassicas resulting in significant yield losses worldwide. No robust resistance against A. brassicae has been identified in the Brassicas. Natural accessions of Arabidopsis show a spectrum of responses to A. brassicae ranging from high susceptibility to complete resistance. To understand the molecular mechanisms of resistance/ susceptibility, we analysed the comparative changes in the transcriptome profile of Arabidopsis accessions with contrasting responses- at different time points post-infection. Differential gene expression, GO enrichment, pathway enrichment, and weighted gene co-expression network analysis (WGCNA) revealed reprogramming of phenylpropanoid biosynthetic pathway involving lignin, hydroxycinnamic acids, scopoletin, anthocyanin genes to be highly associated with resistance against A. brassicae. T-DNA insertion mutants deficient in the biosynthesis of coumarin scopoletin exhibited enhanced susceptibility to A. brassicae. The supplementation of scopoletin to medium or exogenous application resulted in a significant reduction in the A. brassicae growth. Our study provides new insights into the transcriptome dynamics in A. brassicae-challenged Arabidopsis and demonstrates the involvement of coumarins in plant immunity against the Brassica pathogen A. brassicae.

De novo transcriptome assembly of the oak processionary moth Thaumetopoea processionea.

OBJECTIVES: The oak processionary moth (OPM) (Thaumetopoea processionea) is a species of moth (order: Lepidoptera) native to parts of central Europe. However, in recent years, it has become an invasive species in various countries, particularly in the United Kingdom and the Netherlands. The larvae of the OPM are covered with urticating barbed hairs (setae) causing irritating and allergic reactions at the three last larval stages (L3-L5). The aim of our study was to generate a de novo transcriptomic assembly for OPM larvae by including one non-allergenic stage (L2) and two allergenic stages (L4 and L5). A transcriptomic assembly will help identify potential allergenic peptides produced by OPM larvae, providing valuable information for developing novel therapeutic strategies and allergic immunodiagnostic assays. DATA: Transcriptomes of three larval stages of the OPM were de novo assembled and annotated using Trinity and Trinotate, respectively. A total of 145,251 transcripts from 99,868 genes were identified. Bench-marking universal single-copy orthologues analysis indicated high completeness of the assembly. About 19,600 genes are differentially expressed between the non-allergenic and allergenic larval stages. The data provided here contribute to the characterization of OPM, which is both an invasive species and a health hazard.

Dysregulated RNA editing of EIF2AK2 in polycystic ovary syndrome: clinical relevance and functional implications.

BACKGROUND: Polycystic ovary syndrome (PCOS) is a prevalent endocrine disorder affecting women of reproductive ages. Our previous study has implicated a possible link between RNA editing and PCOS, yet the actual role of RNA editing, its association with clinical features, and the underlying mechanisms remain unclear. METHODS: Ten RNA-Seq datasets containing 269 samples of multiple tissue types, including granulosa cells, T helper cells, placenta, oocyte, endometrial stromal cells, endometrium, and adipose tissues, were retrieved from public databases. Peripheral blood samples were collected from twelve PCOS and ten controls and subjected to RNA-Seq. Transcriptome-wide RNA-Seq data analysis was conducted to identify differential RNA editing (DRE) between PCOS and controls. The functional significance of DRE was evaluated by luciferase reporter assays and overexpression in human HEK293T cells. Dehydroepiandrosterone and lipopolysaccharide were used to stimulate human KGN granulosa cells to evaluate gene expression. RESULTS: RNA editing dysregulations across multiple tissues were found to be associated with PCOS in public datasets. Peripheral blood transcriptome analysis revealed 798 DRE events associated with PCOS. Through weighted gene co-expression network analysis, our results revealed a set of hub DRE events in PCOS blood. A DRE event in the eukaryotic translation initiation factor 2-alpha kinase 2 (EIF2AK2:chr2:37,100,559) was associated with PCOS clinical features such as luteinizing hormone (LH) and the ratio of LH over follicle-stimulating hormone. Luciferase assays, overexpression, and knockout of RNA editing enzyme adenosine deaminase RNA specific (ADAR) showed that the ADAR-mediated editing cis-regulated EIF2AK2 expression. EIAF2AK2 showed a higher expression after dehydroepiandrosterone and lipopolysaccharide stimulation, triggering changes in the downstrean MAPK pathway. CONCLUSIONS: Our study presented the first evidence of cross-tissue RNA editing dysregulation in PCOS and its clinical associations. The dysregulation of RNA editing mediated by ADAR and the disrupted target EIF2AK2 may contribute to PCOS development via the MPAK pathway, underlining such epigenetic mechanisms in the disease.

CACIMAR: cross-species analysis of cell identities, markers, regulations, and interactions using single-cell RNA sequencing data.

Transcriptomic analysis across species is increasingly used to reveal conserved gene regulations which implicate crucial regulators. Cross-species analysis of single-cell RNA sequencing (scRNA-seq) data provides new opportunities to identify the cellular and molecular conservations, especially for cell types and cell type-specific gene regulations. However, few methods have been developed to analyze cross-species scRNA-seq data to uncover both molecular and cellular conservations. Here, we built a tool called CACIMAR, which can perform cross-species analysis of cell identities, markers, regulations, and interactions using scRNA-seq profiles. Based on the weighted sum models of the conserved features, we developed different conservation scores to measure the conservation of cell types, regulatory networks, and intercellular interactions. Using publicly available scRNA-seq data on retinal regeneration in mice, zebrafish, and chick, we demonstrated four main functions of CACIMAR. First, CACIMAR allows to identify conserved cell types even in evolutionarily distant species. Second, the tool facilitates the identification of evolutionarily conserved or species-specific marker genes. Third, CACIMAR enables the identification of conserved intracellular regulations, including cell type-specific regulatory subnetworks and regulators. Lastly, CACIMAR provides a unique feature for identifying conserved intercellular interactions. Overall, CACIMAR facilitates the identification of evolutionarily conserved cell types, marker genes, intracellular regulations, and intercellular interactions, providing insights into the cellular and molecular mechanisms of species evolution.

Single-cell transcriptome analysis of cavernous tissues reveals the key roles of pericytes in diabetic erectile dysfunction.

Erectile dysfunction (ED) affects a significant proportion of men aged 40-70 and is caused by cavernous tissue dysfunction. Presently, the most common treatment for ED is phosphodiesterase 5 inhibitors; however, this is less effective in patients with severe vascular disease such as diabetic ED. Therefore, there is a need for development of new treatment, which requires a better understanding of the cavernous microenvironment and cell-cell communications under diabetic condition. Pericytes are vital in penile erection; however, their dysfunction due to diabetes remains unclear. In this study, we performed single-cell RNA sequencing to understand the cellular landscape of cavernous tissues and cell type-specific transcriptional changes in diabetic ED. We found a decreased expression of genes associated with collagen or extracellular matrix organization and angiogenesis in diabetic fibroblasts, chondrocytes, myofibroblasts, valve-related lymphatic endothelial cells, and pericytes. Moreover, the newly identified pericyte-specific marker, Limb Bud-Heart (Lbh), in mouse and human cavernous tissues, clearly distinguishing pericytes from smooth muscle cells. Cell-cell interaction analysis revealed that pericytes are involved in angiogenesis, adhesion, and migration by communicating with other cell types in the corpus cavernosum; however, these interactions were highly reduced under diabetic conditions. Lbh expression is low in diabetic pericytes, and overexpression of LBH prevents erectile function by regulating neurovascular regeneration. Furthermore, the LBH-interacting proteins (Crystallin Alpha B and Vimentin) were identified in mouse cavernous pericytes through LC-MS/MS analysis, indicating that their interactions were critical for maintaining pericyte function. Thus, our study reveals novel targets and insights into the pathogenesis of ED in patients with diabetes.

Identification of novel biomarkers to distinguish clear cell and non-clear cell renal cell carcinoma using bioinformatics and machine learning.

Renal cell carcinoma (RCC), accounting for 90% of all kidney cancer, is categorized into clear cell RCC (ccRCC) and non-clear cell RCC (non-ccRCC) for treatment based on the current NCCN Guidelines. Thus, the classification will be associated with therapeutic implications. This study aims to identify novel biomarkers to differentiate ccRCC from non-ccRCC using bioinformatics and machine learning. The gene expression profiles of ccRCC and non-ccRCC subtypes (including papillary RCC (pRCC) and chromophobe RCC (chRCC)), were obtained from TCGA. Differential expression genes (DEGs) were identified, and specific DEGs for ccRCC and non-ccRCC were explored using a Venn diagram. Gene Ontology and pathway enrichment analysis were performed using DAVID. The top ten expressed genes in ccRCC were then selected for machine learning analysis. Feature selection was operated to identify a minimum highly effective gene set for constructing a predictive model. The expression of best-performing gene set was validated on tissue samples from RCC patients using immunohistochemistry techniques. Subsequently, machine learning models for diagnosing RCC were developed using H-scores. There were 910, 415, and 835 genes significantly specific for DEGs in ccRCC, pRCC, and chRCC, respectively. Specific DEGs in ccRCC enriched in PD-1 signaling, immune system, and cytokine signaling in the immune system, whereas TCA cycle and respiratory, signaling by insulin receptor, and metabolism were enriched in chRCC. Feature selection based on Decision Tree Classifier revealed that the model with two genes, including NDUFA4L2 and DAT, had an accuracy of 98.89%. Supervised classification models based on H-score of NDUFA4L2, and DAT revealed that Decision Tree models showed the best performance with 82% accuracy and 0.9 AUC. NDUFA4L2 expression was associated with lymphovascular invasion, pathologic stage and pT stage in ccRCC. Using integrated bioinformatics and machine learning analysis, NDUFA4L2 and DAT were identified as novel biomarkers to differential diagnosis ccRCC from non-ccRCC.

Integrated single cell analysis reveals co-evolution of malignant B cells and tumor micro-environment in transformed follicular lymphoma.

Histological transformation of follicular lymphoma (FL) to aggressive forms is associated with poor outcome. Phenotypic consequences of this evolution and its impact on the tumor microenvironment (TME) remain unknown. We perform single-cell whole genome sequencing (scWGS) and transcriptome sequencing (scWTS) of 11 paired pre/post-transformation patient samples and scWTS of additional samples from patients without transformation. Our analysis reveals evolutionary dynamics of transformation at single-cell resolution, highlighting a shifting TME landscape, with an emerging immune-cell exhaustion signature, co-evolving with the shifting malignant B phenotype in a regulatory ecosystem. Integration of scWGS and scWTS identifies malignant cell pathways upregulated during clonal tumor evolution. Using multi-color immunofluorescence, we transfer these findings to a TME-based transformation biomarker, subsequently validated in two independent pretreatment cohorts. Taken together, our results provide a comprehensive view of the combined genomic and phenotypic evolution of malignant cells during transformation and shifting crosstalk between malignant cells and the TME.