Bioinformatics Methods Research Articles

Multi-omics profiling combined with molecular docking reveals immune-inflammatory proteins as potential drug targets in colorectal cancer

Colorectal cancer is globally ranked as the third most common malignant tumor. Its development involves a complex biological process driven by various genetic and epigenetic alterations. To elucidate the biological significance of the extensive omics data, we conducted comparative multi-omics studies on colorectal cancer patients at different clinical stages. Bioinformatics methods were applied to analyze multi-omics datasets and explore the molecular landscape. Drug prediction and molecular docking also were conducted to assess potential therapeutic interventions. In vitro experiments were used to validate the inhibitory effect on the migration and proliferation of cell lines. The results indicate up-regulated proteins involved in immune-inflammatory related pathways, while biomarkers related to muscular contraction and cell adhesion are significantly down-regulated. Drug prediction, coupled with in vitro experiments, suggests that AZ-628 may act as a potential drug to inhibit the proliferation and migration of CRC cell lines HCT-116 and HT-29 by regulating the aforementioned key biological pathways or proteins. Complementing these findings, metabolomics analysis unveiled a down-regulation of key carbon metabolism pathways, alongside an up-regulation in amino acid metabolism, particularly proline metabolism. This metabolic shift may reflect an adaptive response in cancer cells, favoring specific amino acids to support their growth. Together, these integrated results provide valuable insights into the intricate landscape of tumor development, highlighting the crossroads of immune regulation, cellular structure, and metabolic reprogramming in the tumorigenic process and providing valuable insights into cancer pathology.

Up-regulated DSG2 promotes tumor growth and reduces immune infiltration in cervical cancer

BackgroundDesmoglein-2 (DSG2) has been reported to play pivotal roles in various diseases. However, its roles in cervical cancer (CC) remain insufficiently elucidated. Here, we aimed to comprehensively explore the functional mechanisms of DSG2 in CC using bioinformatics and experimental methods. MethodsSeveral online databases, including Gene Expression Profiling Interactive Analysis (GEPIA), ONCOMINE, LinkedOmics, MetaScape, Human protein atlas (HPA), OMICS and single-cell RNA sequencing (scRNA-seq) data were used to explore the expression, prognosis, gene mutations, and potential signaling pathway of DSG2 in CC. Quantitative real-time PCR (qRT-PCR) and western blotting were used to measure DSG2 expression in collected samples. Experimental assays were conducted to verify the effects of dysregulated DSG2 on cervical cell lines in vitro. ResultsBioinformatic analyses revealed that DSG2 was significantly up-regulated in CC compared to normal cervical tissues at both mRNA and protein levels. Elevated DSG2 levels were also associated with poor prognosis and clinical parameters (e.g., cancer stages, tumor grade, nodal metastasis status, etc.). DSG2 expression was predominantly observed in epithelial cells, increasing with disease progression on a single-cell resolution. Additionally, up-regulation of DSG2 significantly enhanced tumor purity by reducing the infiltration of immune cells (e.g., B cells, T cells, NK cells, etc.). Over-expression of DSG2 was further validated in collected CC samples at both mRNA and protein levels. Knockdown of DSG2 markedly reduced the proliferation and invasion of CC cell lines in vitro. ConclusionsIn summary, elevated levels of DSG2 were significantly associated with poor prognosis and diminished immune infiltration in CC. Thus, DSG2 may serve as a potential therapeutic and diagnostic biomarker for CC.

Pan-cancer exploration of PNO1: A prospective prognostic biomarker with ties to immune infiltration

The partner of NOB1 homolog (PNO1) is an RNA-binding protein that participates in ribosome biogenesis and protein modification. The functions of this molecule are largely unknown in cancers, particularly breast cancer. We employed bioinformatics methods to probe the putative oncogenic functions of PNO1 based on expression profiles and clinical data from the cancer genome atlas (TCGA), genotype-tissue expression project (GTEx), human protein atlas (HPA), cancer cell line encyclopedia (CCLE), UALCAN, drug sensitivity in cancer (GDSC) and UCSC XENA databases. Our analyses revealed that PNO1 was overexpressed in 31 malignancies, which excluded kidney chromophobe (KICH) and acute myeloid leukemia (LAML). Prognostic assessments have demonstrated that high PNO1 expression was significantly correlated with poor overall and disease-specific survival in various cancers. The promoter methylation level of PNO1 is significantly decreased in breast invasive carcinoma (BRCA), head and neck squamous cell carcinoma (HNSC), kidney renal papillary cell carcinoma (KIRP), prostate adenocarcinoma (PRAD), thyroid carcinoma (THCA) and uterine corpus endometrial carcinoma (UCEC). Furthermore, inhibition of PNO1 decreased the viability, migration and invasion of breast cancer cells, and these results were confirmed by mouse xenograft models of breast cancer. In addition, we discovered that tumor microenvironment (TME), immune infiltration, and chemotherapy sensitivity were influenced by PNO1 expression. Concordantly, our analyses revealed a significant positive correlation between PNO1 and programmed cell death ligand 1 (PD-L1) expression across breast carcinoma samples. In conclusion, these findings indicate that PNO1 could act as a promising prognostic biomarker and adjunct diagnostic indicator, because it affects tumor growth and invasion. Our study offers valuable new perspectives on the oncogenic role of PNO1 in various types of cancers.

Molecular characterization of cassava zinc finger-homeodomain (ZF-HD) transcription factors reveals their role in disease resistance

The production of cassava (Manihot esculenta Crantz) is constantly threatened by cassava bacterial blight (CBB), caused by Xanthomonas phaseoli pv. manihotis (Xpm). Zinc finger-homeodomain (ZF-HD) belongs to a family of homozygous heterotypic cassette genes widely implicated in various developmental and physiological processes in plants. Despite their importance, a comprehensive analysis of ZF-HD genes, particularly those involved in disease resistance, has not been performed for cassava. In the present study, we utilized bioinformatics methods to identify 21 ZF-HD genes distributed across 11 chromosomes of cassava genome, with the majority exhibiting gene structure without introns. Phylogenetic analysis categorized these genes into two major groups (MIF and ZHD) with five subgroups. We observed fourteen pairs of duplicated genes, suggesting that segmental duplication has likely facilitated the expansion of the cassava ZF-HD gene family. Comparative orthologous analyses between cassava and other plant species shed light on the evolutionary trajectory of this gene family. Promoter analyses revealed multiple hormone- and stress-related elements, indicative of a functional role in stress responses. Expression profiling through RNA-seq and quantitative real-time PCR (qRT-PCR) demonstrated that certain cassava ZF-HD genes are up-regulated in response to Xpm infection, suggesting their involvement in defense mechanisms. Notably, MeZHD7 gene was identified via virus induced gene silencing (VIGS) as potentially crucial in conferring resistance against CBB. Results from subcellular localization experiments indicated that MeZHD7 was localized in the nucleus. The Luciferase reporter assay demonstrated an interaction between MeZHD7 and MeMIF5. These findings may lay the foundation for further cloning and functional analyses of cassava ZF-HD genes, particularly those associated with pathogen resistance.

ORY-1001 inhibits glioblastoma cell growth by downregulating the Notch/HES1 pathway via suppressing lysine-specific demethylase 1 expression

To explore the inhibitory effect ORY-1001, a lysine-specific histone demethylase 1 (LSD1) inhibitor, on growth of glioblastoma (GBM) and the underlying mechanism. We analyzed LSD1 expressions in GBM and normal brain tissues based on data from TCGA and HPA databases. Female BALB/c mouse models bearing xenografts derived from U87 cells or cells with lentivirus-mediated LSD1 silencing or Notch overexpression were treated with saline or 400 µg/kg ORY-1001 by gavage every 7 days, and GBM formation and survival time of the mice were recorded. The effect of ORY-1001 on GBM cell viability was assessed, and its effect on LSD1 expression was analyzed with Western blotting. The genes and pathways associated with LSD1 were analyzed using bioinformatics methods. Western blotting and qRT-PCR were used to detect Notch/HES1 pathway expression after LSD1 silencing and ORY-1001 treatment. The impact of ORY-1001 on viability of U87 cells with Notch1 silencing or overexpression was assessed, and the regulatory effects of ORY-1001 on Notch/HES1 pathway were analyzed using chromatin immunoprecipitation assay. A high expression of LSD1 in GBM was negatively correlated with patient survival (P < 0.001). ORY-1001 and LSD1 silencing obviously reduced tumor burden and prolonged the survival time of GBM-bearing mice. ORY-1001 treatment significantly inhibited the viability and dose-dependently decreased LSD1 expression in GBM cells, and such inhibitory effect of ORY-1001 was attenuated by LSD1 silencing. The Notch pathway enriched the differential genes related to LSD1, and Notch/HES1 pathway expression was significantly down-regulated after LSD1 silencing and ORY-1001 treatment. Notch1 overexpression significantly attenuated the anti-tumor effect of ORY-1001 on GBM. Mechanistically, ORY-1001 disrupted the interaction between LSD1 and the Notch pathway target genes including Notch3, HES1 and CR2. ORY-1001 down-regulates the Notch/HES1 pathway by inhibiting LSD1 expression to suppress the growth of GBM in mice.

Identification of key metabolism-related genes and pathways in spontaneous preterm birth: combining bioinformatic analysis and machine learning.

Spontaneous preterm birth (sPTB) is a global disease that is a leading cause of death in neonates and children younger than 5 years of age. However, the etiology of sPTB remains poorly understood. Recent evidence has shown a strong association between metabolic disorders and sPTB. To determine the metabolic alterations in sPTB patients, we used various bioinformatics methods to analyze the abnormal changes in metabolic pathways in the preterm placenta via existing datasets. In this study, we integrated two datasets (GSE203507 and GSE174415) from the NCBI GEO database for the following analysis. We utilized the "Deseq2" R package and WGCNA for differentially expressed genes (DEGs) analysis; the identified DEGs were subsequently compared with metabolism-related genes. To identify the altered metabolism-related pathways and hub genes in sPTB patients, we performed multiple functional enrichment analysis and applied three machine learning algorithms, LASSO, SVM-RFE, and RF, with the hub genes that were verified by immunohistochemistry. Additionally, we conducted single-sample gene set enrichment analysis to assess immune infiltration in the placenta. We identified 228 sPTB-related DEGs that were enriched in pathways such as arachidonic acid and glutathione metabolism. A total of 3 metabolism-related hub genes, namely, ANPEP, CKMT1B, and PLA2G4A, were identified and validated in external datasets and experiments. A nomogram model was developed and evaluated with 3 hub genes; the model could reliably distinguish sPTB patients and term labor patients with an area under the curve (AUC) > 0.75 for both the training and validation sets. Immune infiltration analysis revealed immune dysregulation in sPTB patients. Three potential hub genes that influence the occurrence of sPTB through shadow participation in placental metabolism were identified; these results provide a new perspective for the development and targeting of treatments for sPTB.

MiR-450a-2-3p targets ERK(1/2) to ameliorate ISO-induced cardiac fibrosis in mice

ObjectiveCardiac fibrosis is an important contributor to atrial fibrillation (AF). Our aim was to identify biomarkers for AF using bioinformatics methods and explore the regulatory mechanism of miR-450a-2-3p in cardiac fibrosis in mice.MethodsTwo datasets, GSE115574 and GSE79768, were obtained from the Gene Expression Omnibus (GEO) database and subsequently merged for further analysis. Differential gene expression analysis was performed to identify differentially expressed genes (DEGs) and miR-450a-2-3p-related differentially expressed genes (MRDEGs). To investigate the underlying mechanism of cardiac fibrosis, a mouse model was established by treating mice with isoproterenol (ISO) and the miR-450a-2-3p agomir.ResultsA total of 127 DEGs and 31 MRDEGs were identified and subjected to Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to determine the functions and pathways involved in AF. In the animal model, histological analysis using HE and Masson staining, as well as quantification of the collagen volume fraction (CVF), was performed. The increased expression of α-smooth muscle actin (α-SMA), collagen type I (COL1), collagen type III (COL3), and extracellular signal-regulated kinase 1/2 (ERK(1/2)) at both the transcriptional and translational levels indicated the significant development of myocardial fibrosis in mice induced with isoproterenol (ISO). In addition, the cross-sectional area of cardiomyocytes and the expression of atrial natriuretic peptide (NPPA) and brain natriuretic peptide (NPPB) were increased in the ISO group compared with the control group. However, after overexpression of the miR-450a-2-3p agomir through caudal vein injection, there was a notable improvement in cardiac morphology in the treated group. The expression levels of α-SMA, COL1, COL3, ERK(1/2), NPPA, and NPPB were also significantly decreased.ConclusionOur study reveals the mechanistic connection between ISO-induced myocardial fibrosis and the miR-450a-2-3p/ERK(1/2) signaling pathway, highlighting its role in the development of cardiac fibrosis. Modulating miR-450a-2-3p expression and inhibiting ERK(1/2) activation are promising approaches for therapeutic intervention in patients with AF.

Decomposing a San Francisco estuary microbiome using long-read metagenomics reveals species- and strain-level dominance from picoeukaryotes to viruses.

Ocean and estuarine microbiomes play critical roles in global element cycling and ecosystem function. Despite the importance of these microbial communities, many species still have not been cultured in the lab. Environmental sequencing is the primary way the function and population dynamics of these communities can be studied. Long-read sequencing provides an avenue to overcome limitations of short-read technologies to obtain complete microbial genomes but comes with its own technical challenges, such as needed sequencing depth and obtaining high-quality DNA. We present here new sampling and bioinformatics methods to attempt decomposing an estuarine microbiome into its constituent genomes. Our results suggest there are only a few strains that comprise most of the species abundances from viruses to picoeukaryotes, and to fully decompose a metagenome of this diversity requires 1 Tbp of long-read sequencing. We anticipate that as long-read sequencing technologies continue to improve, less sequencing will be needed.

Identification of an autophagy- and macropinocytosis-related prognostic signature for the prediction of prognosis and therapeutic response in gastric cancer.

Traditional liquid biopsy markers show a low rate of positivity and accurate in gastric cancer. With the rapid advancement of sequencing technology, scientists have identified promising research avenues in this field. Autophagy and macropinocytosis utilize diverse pathways and mechanisms to supply resources and fuel for tumor growth. Nonetheless, their potential interplay introduces an untapped avenue for the discovery of novel tumor biomarkers. To develop an innovative prognostic signature based on autophagy- and micropinocytosis-related genes, with the aim to predict the outcome and therapeutic response of gastric cancer patients. Additionally, to validate the prognostic impact of this signature, and elucidate the role of representative molecules in gastric cancer. To construct and validate a prognostic signature for gastric cancer, bioinformatics methods such as COX regression, LASSO regression, survival analysis, ROC curve, and nomogram were utilized based on the sequencing and clinical data of gastric cancer patients retrieved from the TCGA and GEO databases. GSEA functional enrichment analyses were employed to predict the biological functions. Meanwhile, qRT-PCR and Western blot experiments were utilized to quantify the mRNA and protein expression levels. Furthermore, the EdU assay and colony formation assay were utilized to examine the cell proliferation ability while the Transwell assays were conducted to assess the migration and invasion abilities of gastric cancer cells. Through consistency clustering and univariate COX analyses, potential prognostic genes involved in both autophagy and macropinocytosis were identified. Based on these genes, a 9-gene signature was constructed, which demonstrated high accuracy in predicting gastric cancer patients' survival period, immunotherapeutic response, and chemotherapy drug tolerance. Furthermore, qRT-PCR analyses of gastric cancer tissue samples showed that the representative genes of this signature were aberrantly overexpressed in gastric cancer, with MATN3, as the most notable molecule, exhibiting significant carcinogenic effects on cancer cells by actively regulating their proliferation, migration, and invasion abilities. Our newly created prognostic signature possesses significant potential as a biomarker for gastric cancer, while MATN3 is identified as an oncogenic factor in gastric cancer. This brings to light new perspectives, which can contribute to enhancing the diagnosis and treatment of gastric cancer.

Prognosis and metabolism with a Golgi apparatus-related genes-based formula in breast cancer.

The Golgi apparatus (GA), an organelle that processes, sorts, and transports proteins synthesized by the endoplasmic reticulum, is also involved in many cellular processes associated with cancer, such as angiogenesis, the innate immune response, and tumor invasion and migration. We aimed to construct a breast cancer (BC) prognosis prediction model based on GA-related genetic information to evaluate the prognosis of patients with BC more accurately than existing models and to stratify patients for clinical therapy. In this study, The Cancer Genome Atlas-breast invasive carcinoma was used as the training cohort, and the Molecular Taxonomy of Breast Cancer International Consortium cohort was used as the validation cohort. Using bioinformatics methods, we constructed a GA-related gene risk score (GRS). The GRS was used to divide BC patients into a high-GRS group and a low-GRS group, and functional analysis, survival analysis, mutation analysis, immune landscape analysis, and metabolic analysis were performed to compare the 2 groups. Finally, a nomogram was constructed for clinical application. The genes in the GRS model were mainly related to the glucose metabolism pathway, and the main mutations in the 2 groups of patients were mutations in TP53 and CHD1. The mutation rate in the high-GRS group was greater than that in the low-GRS group. The high GRS group had higher tumor immune activity glycolysis; the pentose phosphate pathway tended to be the dominant metabolic pathways in this group, while fatty acid oxidation and glutamine catabolism tended to be dominant in the low-GRS group. GA-related genes were used to construct a prediction model for BC patients and had high accuracy in predicting prognosis. The mutations associated with the GRS are mainly TP53 and CDH1. Interestingly, the GRS is correlated with glucose metabolism in terms of gene expression and functional enrichment. In summary, the role of GRS-related genes in glucose metabolism is worthy of further study.

MicroRNA-124-3p targets Sp1 transcription factor to regulate glioma progression in rats

Gliomas are the most prevalent malignancies of the central nervous system (CNS). Downregulation of microRNA‑124 (miR‑124) has been identified in glioma; however, its biological functions in glioma are not yet fully understood. Specificity protein 1 (SP1) is a type of transcription factor that is involved in cancer progression. In this study, we examined the targeting of Sp1 mRNA by miR-124-3p in a rat glioma model. After confirming and selecting the binding of Sp1 to miR-124 with the help of bioinformatics methods, adult male Wistar rats were used to induce glioma by microinjection of 1 × 106 C6 cells into the striatum area of brain. The rats were divided into 3 groups; intact, sham and glioma groups. The presence of glioma was confirmed 21 days after implantation through histological analysis. The expression levels of miR-124 and SP1 genes in the experimental groups were examined using quantitative real-time polymerase chain reaction (qRT-PCR). Our data showed that the expression of miR-124 was significantly downregulated in glioma group compared to the sham and intact group, while the expression of SP1 was significantly upregulated. We found that the expression levels of miR-124 and Sp1 were decreased and increased in C6 cell line compared to the normal brain tissue cell line, respectively. The results indicated that Sp1 was identified as a direct target of miR‑124 through luciferase reporter assays. In summary, this study demonstrated for the first time that miR-124 expression is downregulated and Sp1 expression is upregulated in an animal model of glioma, which, in turn, may be involved in the development of glioma brain cancer.

Exploration of the shared diagnostic genes and mechanisms between periodontitis and primary Sjögren’s syndrome by integrated comprehensive bioinformatics analysis and machine learning

BackgroundAccumulating evidence has showed a bidirectional link between periodontitis (PD) and primary Sjögren’s syndrome (pSS), but the mechanisms of their occurrence remain unclear. Hence, this study aimed to investigate the shared diagnostic genes and potential mechanisms between PD and pSS using bioinformatics methods. MethodsGene expression data for PD and pSS were acquired from the Gene Expression Omnibus (GEO) database. Differential expression genes (DEGs) analysis and weighted gene co-expression network analysis (WGCNA) were utilized to search common genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were conducted to explore biological functions. Three machine learning algorithms (least absolute shrinkage and selection operator (LASSO), support vector machine recursive feature elimination (SVM-RFE), and random forest (RF)) were used to further identify shared diagnostic genes, and these genes were assessed via receiver operating characteristic (ROC) curves in discovery and validation datasets. CIBERSORT was employed for immune cell infiltration analysis. Transcription factors (TFs)-genes and miRNAs-genes regulatory networks were conducted by NetworkAnalyst. Finally, relevant drug targets were predicted by DSigDB. ResultsBased on DEGs, 173 overlapping genes were obtained and primarily enriched in immune- and inflammation-related pathways. WGCNA revealed 34 common disease-related genes, which were enriched in similar biological pathways. Intersecting the DEGs with WGCNA results yielded 22 candidate genes. Moreover, three machine learning algorithms identified three shared genes (CSF2RB, CXCR4, and LYN) between PD and pSS, and these genes demonstrated good diagnostic performance (AUC>0.85) in both discovery and validation datasets. The immune cell infiltration analysis showed significant dysregulation in several immune cell populations. Regulatory network analysis highlighted that WRNIP1 and has-mir-155-5p might be pivotal co-regulators of the three shared gene expressions. Finally, the top 10 potential gene-targeted drugs were screened. ConclusionCSF2RB, CXCR4, and LYN may serve as potential biomarkers for the concurrent diagnosis of PD and pSS. Additionally, we identified common molecular mechanisms, TFs, miRNAs, and candidate drugs between PD and pSS, which may provide novel insights and targets for future research on the pathogenesis, diagnosis, and therapy of both diseases.

Ketogenic diet reshapes cancer metabolism through lysine β-hydroxybutyrylation.

Lysine β-hydroxybutyrylation (Kbhb) is a post-translational modification induced by the ketogenic diet (KD), a diet showing therapeutic effects on multiple human diseases. Little is known how cellular processes are regulated by Kbhb. Here we show that protein Kbhb is strongly affected by the KD through a multi-omics analysis of mouse livers. Using a small training dataset with known functions, we developed a bioinformatics method for the prediction of functionally important lysine modification sites (pFunK), which revealed functionally relevant Kbhb sites on various proteins, including aldolase B (ALDOB) Lys108. KD consumption or β-hydroxybutyrate supplementation in hepatocellular carcinoma cells increases ALDOB Lys108bhb and inhibits the enzymatic activity of ALDOB. A Kbhb-mimicking mutation (p.Lys108Gln) attenuates ALDOB activity and its binding to substrate fructose-1,6-bisphosphate, inhibits mammalian target of rapamycin signalling and glycolysis, and markedly suppresses cancer cell proliferation. Our study reveals a critical role of Kbhb in regulating cancer cell metabolism and provides a generally applicable algorithm for predicting functionally important lysine modification sites.

LBFextract: Unveiling transcription factor dynamics from liquid biopsy data

MotivationThe analysis of circulating cell-free DNA (cfDNA) holds immense promise as a non-invasive diagnostic tool across various human conditions. However, extracting biological insights from cfDNA fragments entails navigating complex and diverse bioinformatics methods, encompassing not only DNA sequence variation, but also epigenetic characteristics like nucleosome footprints, fragment length, and methylation patterns. ResultsWe introduce Liquid Biopsy Feature extract (LBFextract), a comprehensive package designed to streamline feature extraction from cfDNA sequencing data, with the aim of enhancing the reproducibility and comparability of liquid biopsy studies. LBFextract facilitates the integration of preprocessing and postprocessing steps through alignment fragment tags and a hook mechanism. It incorporates various methods, including coverage-based and fragment length-based approaches, alongside two novel feature extraction methods: an entropy-based method to infer TF activity from fragmentomics data and a technique to amplify signals from nucleosome dyads. Additionally, it implements a method to extract condition-specific differentially active TFs based on these features for biomarker discovery. We demonstrate the use of LBFextract for the subtype classification of advanced prostate cancer patients using coverage signals at transcription factor binding sites from cfDNA. We show that LBFextract can generate robust and interpretable features that can discriminate between different clinical groups. LBFextract is a versatile and user-friendly package that can facilitate the analysis and interpretation of liquid biopsy data. Data and Code Availability and ImplementationLBFextract is freely accessible at https://github.com/Isy89/LBF. It is implemented in Python and compatible with Linux and Mac operating systems. Code and data to reproduce these analyses have been uploaded to 10.5281/zenodo.10964406.

Paternal Mitochondrial DNA Leakage in Natural Populations of Large-Scale Loach, Paramisgurnus dabryanus.

Animal mitochondrial DNA is usually considered to comply with strict maternal inheritance, and only one mitochondrial DNA haplotype exists in an individual. However, mitochondrial heteroplasmy, the occurrence of more than one mitochondrial haplotype, has recently been reported in some animals, such as mice, mussels, and birds. This study conducted extensive field surveys to obtain representative samples to investigate the existence of paternal inheritance of mitochondrial DNA (mtDNA) in natural fish populations. Evidence of paternal mitochondrial DNA leakage of P. dabryanus was discovered using high-throughput sequencing and bioinformatics methods. Two distinct mitochondrial haplotypes (16,569 bp for haplotype I and 16,646 bp for haplotype II) were observed, differing by 18.83% in nucleotide sequence. Phylogenetic analysis suggests divergence between these haplotypes and potential interspecific hybridization with M. anguillicaudatus, leading to paternal leakage. In natural populations of P. dabryanus along the Yangtze River, both haplotypes are present, with Type I being dominant (75% copy number). Expression analysis shows that Type I has higher expression levels of ND3 and ND6 genes compared to Type II, suggesting Type I's primary role. This discovery of a species with two mitochondrial types provides a model for studying paternal leakage heterogeneity and insights into mitochondrial genome evolution and inheritance.

Construction of a panoramic mRNA map of adult noncystic fibrosis bronchiectasis and a preliminary study of the underlying molecular mechanisms

BackgroundThe pathogenesis of noncystic fibrosis bronchiectasis in adults is complex, and the relevant molecular mechanisms remain unclear. In this study, we constructed a panoramic map of bronchiectasis mRNA, explored the potential molecular mechanisms, and identified potential therapeutic targets, thus providing a new clinical perspective for the preventive management of bronchiectasis and its acute exacerbation.MethodsThe mRNA profiles of peripheral blood and bronchiectasis tissues were obtained through transcriptome sequencing and public databases, and bioinformatics methods were used to screen for differentially expressed genes (DEGs). The DEGs were then subjected to biological function and pathway analyses. Some DEGs were validated using a real-time quantitative polymerase chain reaction (RT-qPCR) in peripheral blood. Spearman’s correlation analysis was used to analyse the correlation between DEGs and clinical indicators.ResultsBased on transcriptome sequencing and public databases, the mRNA profile of bronchiectasis was determined. DEGs were obtained from the peripheral blood sequencing dataset (985 DEGs), tissue sequencing dataset (2919 DEGs), and GSE97258 dataset (1083 DEGs). Bioinformatics analysis showed that upregulated DEGs had enriched neutrophil-related pathways, and downregulated DEGs had enriched ribosome-related pathways. RT-qPCR testing confirmed the upregulated expression of VCAN, SESTD1, SLC12A1, CD177, IFI44L, SIGLEC1, and RSAD2 in bronchiectasis. These genes were related to many clinical parameters, such as neutrophils, C-reactive protein, and procalcitonin (P < 0.05).ConclusionsTranscriptomic methods were used to construct a panoramic map of bronchiectasis mRNA expression. The findings showed that neutrophil activation, chronic inflammation, immune regulation, impaired ribosomal function, oxidative phosphorylation, and energy metabolism disorders are important factors in the development of bronchiectasis. VCAN, SESTD1, SLC12A1, CD177, IFI44L, SIGLEC1, and RSAD2 may play important roles in the pathogenesis of bronchiectasis and are potential therapeutic targets.

Identification of NAC Transcription Factors in Suaeda glauca and Their Responses to Salt Stress.

NAC (NAM/ATAF1/2/CUC2) transcription factors regulate plant growth and development and stress responses. Because NAC transcription factors are known to play important roles in the regulation of salt tolerance in many plants, we aimed to explore their roles in the halophyte Suaeda glauca. Based on transcriptome sequencing data, we identified 25 NAC transcription factor gene family members. In a phylogenetic tree analysis with Arabidopsis thaliana NAC transcription factors, the SgNACs were divided into 10 groups. The physicochemical properties and conserved domains of the putative proteins, as well as the transcript profiles of their encoding genes, were determined for the 25 SgNAC genes using bioinformatic methods. Most of the S. glauca NAC genes were upregulated to some extent after 24 h of salt stress, suggesting that they play an important role in regulating the salt tolerance of S. glauca. These findings lay the foundation for further research on the functions and mechanisms of the NAC gene family in S. glauca.

Evolutionary Fate of the Opine Synthesis Genes in the Arachis L. Genomes.

Naturally transgenic plants are plants that have undergone Agrobacterium-mediated transformation under natural conditions without human involvement. Among Arachis hypogaea L., A. duranensis Krapov. & W.C. Greg, A. ipaensis Krapov. & W.C. Greg, A. monticola Krapov. & Rigoni, and A. stenosperma Krapov. & W.C. Greg are known to contain sequences derived from the T-DNA of "Agrobacterium". In the present study, using molecular genetics and bioinformatic methods, we characterized natural transgenes in 18 new species from six sections of the genus Arachis. We found that small fragments of genes for enzymes of the agropine synthesis pathway were preserved only in some of the studied samples and were lost in the majority of the species during evolution. At the same time, genes, similar to cucumopine synthases (cus-like), remained intact in almost all of the investigated species. In cultivated peanuts, they are expressed in a tissue-specific manner. We demonstrated the intraspecific variability of the structure and expression of the cus-like gene in cultivated peanuts. The described diversity of gene sequences horizontally transferred from Agrobacterium to plants helps to shed light on the phylogeny of species of the genus Arachis and track possible hybridization events. Data on the ability of certain species to hybridize are useful for planning breeding schemes aimed at transferring valuable traits from wild species into cultivated peanuts.

Hub genes identification and validation of ferroptosis in SARS-CoV-2 induced ARDS: perspective from transcriptome analysis.

Acute Respiratory Distress Syndrome (ARDS) poses a significant health challenge due to its high incidence and mortality rates. The emergence of SARS-CoV-2 has added complexity, with evidence suggesting a correlation between COVID-19 induced ARDS and post-COVID symptoms. Understanding the underlying mechanisms of ARDS in COVID-19 patients is crucial for effective clinical treatment. To investigate the potential role of ferroptosis in SARS-CoV-2 induced ARDS, we conducted a comprehensive analysis using bioinformatics methods. Datasets from the Gene Expression Omnibus (GEO) were utilized, focusing on COVID-19 patients with varying ARDS severity. We employed weighted gene co-expression network analysis (WGCNA), differential gene expression analysis, and single-cell sequencing to identify key genes associated with ferroptosis in ARDS. Hub genes were validated using additional GEO datasets and cell experiment. The analysis discerned 916 differentially expressed genes in moderate/severe ARDS patients compared to non-critical individuals. Weighted Gene Co-expression Network Analysis (WGCNA) unveiled two modules that exhibited a positive correlation with ARDS, subsequently leading to the identification of 15 hub genes associated with ferroptosis. Among the noteworthy hub genes were MTF1, SAT1, and TXN. Protein-protein interaction analysis, and pathway analysis further elucidated their roles. Immune infiltrating analysis highlighted associations between hub genes and immune cells. Validation in additional datasets confirmed the upregulation of MTF1, SAT1, and TXN in SARS-CoV-2-induced ARDS. This was also demonstrated by qRT-PCR results in the BEAS-2B cells vitro model, suggesting their potential as diagnostic indicators. This study identifies MTF1, SAT1, and TXN as hub genes associated with ferroptosis in SARS-CoV-2-induced ARDS. These findings provide novel insights into the molecular mechanisms underlying ARDS in COVID-19 patients and offer potential targets for immune therapy and targeted treatment. Further experimental validation is warranted to solidify these findings and explore therapeutic interventions for ARDS in the context of COVID-19.

Visualizing scRNA-Seq Data at Population Scale with GloScope.

Increasingly, scRNA-Seq studies explore cell populations across different samples and the effect of sample heterogeneity on organism's phenotype. However, relatively few bioinformatic methods have been developed which adequately address the variation between samples for such population-level analyses. We propose a framework for representing the entire single-cell profile of a sample, which we call a GloScope representation. We implement GloScope on scRNA-Seq datasets from study designs ranging from 12 to over 300 samples and demonstrate how GloScope allows researchers to perform essential bioinformatic tasks at the sample-level, in particular visualization and quality control assessment.