Gene Expression Patterns Research Articles

Evaluation of Toll-like Receptor 4 (TLR4) Involvement in Human Atrial Fibrillation: A Computational Study.

In the present study, we have explored the involvement of Toll-like Receptor 4 (TLR4) in atrial fibrillation (AF), by using a meta-analysis of publicly available human transcriptomic data. The meta-analysis revealed 565 upregulated and 267 downregulated differentially expressed genes associated with AF. Pathway enrichment analysis highlighted a significant overrepresentation in immune-related pathways for the upregulated genes. A significant overlap between AF differentially expressed genes and TLR4-modulated genes was also identified, suggesting the potential role of TLR4 in AF-related transcriptional changes. Additionally, the analysis of other Toll-like receptors (TLRs) revealed a significant association with TLR2 and TLR3 in AF-related gene expression patterns. The examination of MYD88 and TICAM1, genes associated with TLR4 signalling pathways, indicated a significant yet nonspecific enrichment of AF differentially expressed genes. In summary, this study offers novel insights into the molecular aspects of AF, suggesting a pathophysiological role of TLR4 and other TLRs. By targeting these specific receptors, new treatments might be designed to better manage AF, offering hope for improved outcomes in affected patients.

Swim training induces distinct osseous gene expression patterns in anosteocytic and osteocytic teleost fish

The traditional understanding of bone mechanosensation implicates osteocytes, canaliculi, and the lacunocanalicular network in biomechanical adaptation. However, recent findings challenge this notion, as shown in advanced teleost fish where anosteocytic bone lacking osteocytes are nevertheless responsive to mechanical load. To investigate specific molecular mechanisms involved in bone mechanoadaptation in osteocytic and anosteocytic fish bone, we conducted a 5-min single swim-training experiment with zebrafish and ricefish, respectively. Through RNASeq analysis of fish spines, analyzed at various time points following swim training, we uncovered distinct gene expression patterns in osteocytic and anosteocytic fish bones. Notably, osteocytic fish bone exhibited an early response to mechanical load, contrasting to a delayed response observed in anosteocytic fish bones, both within 8 h following stimulation. We identified an increase in osteoblast differentiation in anosteocytic bone following training, while chordoblast activity was delayed. This temporal response suggests a time-dependent adaptation in anosteocytic bone, indicating the presence of intricate feedback networks within bone that lacks osteocytes.

Deciphering the dual roles of PHD finger proteins from oncogenic drivers to tumor suppressors.

PHD (plant homeodomain) finger proteins emerge as central epigenetic readers and modulators in cancer biology, orchestrating a broad spectrum of cellular processes pivotal to oncogenesis and tumor suppression. This review delineates the dualistic roles of PHD fingers in cancer, highlighting their involvement in chromatin remodeling, gene expression regulation, and interactions with cellular signaling networks. PHD fingers' ability to interpret specific histone modifications underscores their influence on gene expression patterns, impacting crucial cancer-related processes such as cell proliferation, DNA repair, and apoptosis. The review delves into the oncogenic potential of certain PHD finger proteins, exemplified by PHF1 and PHF8, which promote tumor progression through epigenetic dysregulation and modulation of signaling pathways like Wnt and TGFβ. Conversely, it discusses the tumor-suppressive functions of PHD finger proteins, such as PHF2 and members of the ING family, which uphold genomic stability and inhibit tumor growth through their interactions with chromatin and transcriptional regulators. Additionally, the review explores the therapeutic potential of targeting PHD finger proteins in cancer treatment, considering their pivotal roles in regulating cancer stem cells and influencing the immune response to cancer therapy. Through a comprehensive synthesis of current insights, this review underscores the complex but promising landscape of PHD finger proteins in cancer biology, advocating for further research to unlock novel therapeutic avenues that leverage their unique cellular roles.

Unveiling the dynamics of embryogenesis and immune genes expression pattern in the amur common carp (Cyprinus carpio haematopterus)

Amur common carp (Cyprinus carpio haematopterus), is a commercially important fish species that has been genetically improved over the years through selective breeding. Despite its significance in aquaculture, limited knowledge exists regarding its embryogenesis and immune genes associated with its early stages of life. This article represents a detailed study of the embryogenesis and innate immune gene expression analysis of the Amur common carp during its ontogenic developments. The entire embryonic developmental process of ∼44 h could be divided into eight periods, beginning with the formation of the zygote, followed by cleavage, morula, blastula, segmentation, pharyngula, and hatching. The segmentation period, which lasted for ∼ 6 h, exhibited the most significant changes, such as muscle contraction, rudimentary heart formation, increased somites number, and the initiation of blood circulation throughout the yolk. The expression of immune-related genes, namely toll-like receptor (TLR)4, nucleotide-binding oligomerization domain (NOD)1, NOD2 and interleukin (IL)-8 showed stage-specific patterns with varying levels of expression across the developmental stages. The TLR4 gene exhibited the highest expression during the neurella stage, while NOD1 and NOD2 peaked during hatching and IL-8 reached its maximum level during the gastrula stage. This is the first report of the innate immune gene expression during the embryogenesis of Amur common carp.

Pathway-based analyses of gene expression profiles at low doses of ionizing radiation.

Radiation exposure poses a significant threat to human health. Emerging research indicates that even low-dose radiation once believed to be safe, may have harmful effects. This perception has spurred a growing interest in investigating the potential risks associated with low-dose radiation exposure across various scenarios. To comprehensively explore the health consequences of low-dose radiation, our study employs a robust statistical framework that examines whether specific groups of genes, belonging to known pathways, exhibit coordinated expression patterns that align with the radiation levels. Notably, our findings reveal the existence of intricate yet consistent signatures that reflect the molecular response to radiation exposure, distinguishing between low-dose and high-dose radiation. Moreover, we leverage a pathway-constrained variational autoencoder to capture the nonlinear interactions within gene expression data. By comparing these two analytical approaches, our study aims to gain valuable insights into the impact of low-dose radiation on gene expression patterns, identify pathways that are differentially affected, and harness the potential of machine learning to uncover hidden activity within biological networks. This comparative analysis contributes to a deeper understanding of the molecular consequences of low-dose radiation exposure.

Single-cell and spatial transcriptomic investigation reveals the spatiotemporal specificity of the beta-defensin gene family during mouse sperm maturation

Low sperm motility is a significant contributor to male infertility. beta-defensins have been implicated in host defence and the acquisition of sperm motility; however, the regulatory mechanisms governing their gene expression patterns and functions remain poorly understood. In this study, we performed single-cell RNA and spatial transcriptome sequencing to investigate the cellular composition of testicular and epididymal tissues and examined their gene expression characteristics. In the epididymis, we found that epididymal epithelial cells display a region specificity of gene expression in different epididymal segments, including the beta-defensin family genes. In particular, Defb15, Defb18, Defb20, Defb25 and Defb48 are specific to the caput; Defb22, Defb23 and Defb26 to the corpus; Defb2 and Defb9 to the cauda of the epididymis. To confirm this, we performed mRNA fluorescence in situ hybridisation (FISH) targeting certain exon region of beta-defensin genes, and found some of their expression matched the sequencing results and displayed a close connection with epididimosome marker gene Cd63. In addition, we paid attention to the Sertoli cells and Leydig cells in the testis, along with fibroblasts and smooth muscle cells in the epididymis, by demonstrating their gene expression profile and spatial information. Our study provides a single-cell and spatial landscape for analysing the gene expression characteristics of testicular and epididymal environments and has important implications for the study of spermatogenesis and sperm maturation.

Genome-Wide Identification and Characterization of the GRAS Gene Family in Lettuce Revealed That Silencing LsGRAS13 Delayed Bolting.

Lettuce is susceptible to high-temperature stress during cultivation, leading to bolting and affecting yield. Plant-specific transcription factors, known as GRAS proteins, play a crucial role in regulating plant growth, development, and abiotic stress responses. In this study, the entire lettuce LsGRAS gene family was identified. The results show that 59 LsGRAS genes are unevenly distributed across the nine chromosomes. Additionally, all LsGRAS proteins showed 100% nuclear localization based on the predicted subcellular localization and were phylogenetically classified into nine conserved subfamilies. To investigate the expression profiles of these genes in lettuce, we analyzed the transcription levels of all 59 LsGRAS genes in the publicly available RNA-seq data under the high-temperature treatment conducted in the presence of exogenous melatonin. The findings indicate that the transcript levels of the LsGRAS13 gene were higher on days 6, 9, 15, 18, and 27 under the high-temperature (35/30 °C) treatment with melatonin than on the same treatment days without melatonin. The functional studies demonstrate that silencing LsGRAS13 accelerated bolting in lettuce. Furthermore, the paraffin sectioning results showed that flower bud differentiation in LsGRAS13-silenced plants occurred significantly faster than in control plants. In this study, the LsGRAS genes were annotated and analyzed, and the expression pattern of the LsGRAS gene following melatonin treatment under high-temperature conditions was explored. This exploration provides valuable information and identifies candidate genes associated with the response mechanism of lettuce plants high-temperature stress.

Deciphering infected cell types, hub gene networks and cell-cell communication in infectious bronchitis virus via single-cell RNA sequencing.

Infectious bronchitis virus (IBV) is a coronavirus that infects chickens, which exhibits a broad tropism for epithelial cells, infecting the tracheal mucosal epithelium, intestinal mucosal epithelium, and renal tubular epithelial cells. Utilizing single-cell RNA sequencing (scRNA-seq), we systematically examined cells in renal, bursal, and tracheal tissues following IBV infection and identified tissue-specific molecular markers expressed in distinct cell types. We evaluated the expression of viral RNA in diverse cellular populations and subsequently ascertained that distal tubules and collecting ducts within the kidney, bursal mucosal epithelial cells, and follicle-associated epithelial cells exhibit susceptibility to IBV infection through immunofluorescence. Furthermore, our findings revealed an upregulation in the transcription of proinflammatory cytokines IL18 and IL1B in renal macrophages as well as increased expression of apoptosis-related gene STAT in distal tubules and collecting duct cells upon IBV infection leading to renal damage. Cell-to-cell communication unveiled potential interactions between diverse cell types, as well as upregulated signaling pathways and key sender-receiver cell populations after IBV infection. Integrating single-cell data from all tissues, we applied weighted gene co-expression network analysis (WGCNA) to identify gene modules that are specifically expressed in different cell populations. Based on the WGCNA results, we identified seven immune-related gene modules and determined the differential expression pattern of module genes, as well as the hub genes within these modules. Our comprehensive data provides valuable insights into the pathogenesis of IBV as well as avian antiviral immunology.

Genomic identification and expression analysis of acid invertase (AINV) gene family in Dendrobium officinale Kimura et Migo

BackgroundDendrobium officinale Kimura et Migo, a renowned traditional Chinese orchid herb esteemed for its significant horticultural and medicinal value, thrives in adverse habitats and contends with various abiotic or biotic stresses. Acid invertases (AINV) are widely considered enzymes involved in regulating sucrose metabolism and have been revealed to participate in plant responses to environmental stress. Although members of AINV gene family have been identified and characterized in multiple plant genomes, detailed information regarding this gene family and its expression patterns remains unknown in D. officinale, despite their significance in polysaccharide biosynthesis.ResultsThis study systematically analyzed the D. officinale genome and identified four DoAINV genes, which were classified into two subfamilies based on subcellular prediction and phylogenetic analysis. Comparison of gene structures and conserved motifs in DoAINV genes indicated a high-level conservation during their evolution history. The conserved amino acids and domains of DoAINV proteins were identified as pivotal for their functional roles. Additionally, cis-elements associated with responses to abiotic and biotic stress were found to be the most prevalent motif in all DoAINV genes, indicating their responsiveness to stress. Furthermore, bioinformatics analysis of transcriptome data, validated by quantitative real-time reverse transcription PCR (qRT-PCR), revealed distinct organ-specific expression patterns of DoAINV genes across various tissues and in response to abiotic stress. Examination of soluble sugar content and interaction networks provided insights into stress release and sucrose metabolism.ConclusionsDoAINV genes are implicated in various activities including growth and development, stress response, and polysaccharide biosynthesis. These findings provide valuable insights into the AINV gene amily of D. officinale and will aid in further elucidating the functions of DoAINV genes.

Molecular characterization, expression analysis and function identification of Pf_IL-12p35, Pf_IL-23p19 and Pf_IL-12p40 genes in yellow catfish (Pelteobagrus fulvidraco)

The interleukin-12 (IL-12) family is a class of heterodimeric cytokines that play crucial roles in pro-inflammatory and pro-stimulatory responses. Although some IL-12 and IL-23 paralogues have been found in fish, their functional activity in fish remains poorly understood. In this study, Pf_IL-12p35a/b, Pf_IL-23p19 and Pf_IL-12p40a/b/c genes were cloned from yellow catfish (Pelteobagrus fulvidraco), four α-helices were found in Pf_IL-12p35a/b and Pf_IL-23p19. The transcripts of these six genes were relatively high in mucus and immune tissues of healthy individuals, and in gill leukocytes. Following Edwardsiella ictaluri infection, Pf_IL-12p35a/b and Pf_IL-23p19 mRNAs were induced in brain and kidney (or head kidney), Pf_IL-12p40a mRNA was induced in gill, and Pf_IL-12p40b/c mRNAs were induced in brain and liver (or skin). The mRNA expression of these genes in PBLs was induced by phytohaemagglutinin (PHA) and polyinosinic-polycytidylic acid (poly I:C), while lipopolysaccharides (LPS) induced the mRNA expression of Pf_IL-12p35a and Pf_IL-12p40b/c in PBLs. After stimulation with recombinant (r) Pf_IL-12 and rPf_IL-23 subunit proteins, either alone or in combination, mRNA expression patterns of genes related to T helper cell development exhibited distinct differences. The results suggest that Pf_IL-12 and Pf_IL-23 subunits may play important roles in regulating immune responses to pathogens and T helper cell development.

Natural variations of heterosis-related allele-specific expression genes in promoter regions lead to allele-specific expression in maize

BackgroundHeterosis has successfully enhanced maize productivity and quality. Although significant progress has been made in delineating the genetic basis of heterosis, the molecular mechanisms underlying its genetic components remain less explored. Allele-specific expression (ASE), the imbalanced expression between two parental alleles in hybrids, is increasingly being recognized as a factor contributing to heterosis. ASE is a complex process regulated by both epigenetic and genetic variations in response to developmental and environmental conditions.ResultsIn this study, we explored the differential characteristics of ASE by analyzing the transcriptome data of two maize hybrids and their parents under four light conditions. On the basis of allele expression patterns in different hybrids under various conditions, ASE genes were divided into three categories: bias-consistent genes involved in basal metabolic processes in a functionally complementary manner, bias-reversal genes adapting to the light environment, and bias-specific genes maintaining cell homeostasis. We observed that 758 ASE genes (ASEGs) were significantly overlapped with heterosis quantitative trait loci (QTLs), and high-frequency variations in the promoter regions of heterosis-related ASEGs were identified between parents. In addition, 10 heterosis-related ASEGs participating in yield heterosis were selected during domestication.ConclusionsThe comprehensive analysis of ASEGs offers a distinctive perspective on how light quality influences gene expression patterns and gene-environment interactions, with implications for the identification of heterosis-related ASEGs to enhance maize yield.

Stellae-123 gene expression signature improved risk stratification in Taiwanese acute myeloid leukemia patients

The European Leukemia Net recommendations provide valuable guidance in treatment decisions of patients with acute myeloid leukemia (AML). However, the genetic complexity and heterogeneity of AML are not fully covered, notwithstanding that gene expression analysis is crucial in the risk stratification of AML. The Stellae-123 score, an AI-based model that captures gene expression patterns, has demonstrated robust survival predictions in AML patients across four western-population cohorts. This study aims to evaluate the applicability of Stellae-123 in a Taiwanese cohort. The Stellae-123 model was applied to 304 de novo AML patients diagnosed and treated at the National Taiwan University Hospital. We find that the pretrained (BeatAML-based) model achieved c-indexes of 0.631 and 0.632 for the prediction of overall survival (OS) and relapse-free survival (RFS), respectively. Model retraining within our cohort further improve the cross-validated c-indexes to 0.667 and 0.667 for OS and RFS prediction, respectively. Multivariable analysis identify both pretrained and retrained models as independent prognostic biomarkers. We further show that incorporating age, Stellae-123, and ELN classification remarkably improves risk stratification, revealing c-indices of 0.73 and 0.728 for OS and RFS, respectively. In summary, the Stellae-123 gene expression signature is a valuable prognostic tool for AML patients and model retraining can improve the accuracy and applicability of the model in different populations.

Clocking out and letting go to unleash green biotech applications in a photosynthetic host

Cyanobacteria are photosynthetic bacteria whose gene expression patterns are globally regulated by their circadian (daily) clocks. Due to their ability to use sunlight as their energy source, they are also attractive hosts for "green" production of pharmaceuticals, renewable fuels, and chemicals. However, despite the application of traditional genetic tools such as the identification of strong promoters to enhance the expression of heterologous genes, cyanobacteria have lagged behind other microorganisms such as Escherichia coli and yeast as economically efficient cell factories. The previous approaches have ignored large-scale constraints within cyanobacterial metabolic networks on transcription, predominantly the pervasive control of gene expression by the circadian (daily) clock. Here, we show that reprogramming gene expression by releasing circadian repressor elements in the transcriptional regulatory pathways coupled with inactivation of the central oscillating mechanism enables a dramatic enhancement of expression in cyanobacteria of heterologous genes encoding both catalytically active enzymes and polypeptides of biomedical significance.

A Dose-Response Study on Functional and Transcriptomic Effects of FSH on Ex Vivo Mouse Folliculogenesis.

Follicle-stimulating hormone (FSH) binds to its membrane receptor (FSHR) in granulosa cells to activate various signal transduction pathways and drive the gonadotropin-dependent phase of folliculogenesis. Both FSH insufficiency (due to genetic or nongenetic factors) and FSH excess (as encountered with ovarian stimulation in assisted reproductive technology [ART]) can cause poor female reproductive outcomes, but the underlying molecular mechanisms remain elusive. Herein, we conducted single-follicle and single-oocyte RNA sequencing analysis along with other approaches in an ex vivo mouse folliculogenesis and oogenesis system to investigate the effects of different concentrations of FSH on key follicular events. Our study revealed that a minimum FSH threshold is required for follicle maturation into the high estradiol-secreting preovulatory stage, and such threshold is moderately variable among individual follicles between 5 and 10 mIU/mL. FSH at 5, 10, 20, and 30 mIU/mL induced distinct expression patterns of follicle maturation-related genes, follicular transcriptomics, and follicular cAMP levels. RNA sequencing analysis identified FSH-stimulated activation of G proteins and downstream canonical and novel signaling pathways that may critically regulate follicle maturation, including the cAMP/PKA/CREB, PI3K/AKT/FOXO1, and glycolysis pathways. High FSH at 20 and 30 mIU/mL resulted in noncanonical FSH responses, including premature luteinization, high production of androgen and proinflammatory factors, and reduced expression of energy metabolism-related genes in oocytes. Together, this study improves our understanding of gonadotropin-dependent folliculogenesis and provides crucial insights into how high doses of FSH used in ART may impact follicular health, oocyte quality, pregnancy outcome, and systemic health.

The role of claudins in renal transepithelial transport and kidney disease.

25 years after the discovery of claudins as the central constituents of tight junctions, the "hunter-gatherer phase" of claudin research is coming to an end. Deficiency in individual claudins as a cause of rare hereditary diseases is well documented. However, knowledge about the involvement of renal claudins in common kidney diseases and strategies to utilize claudins or their regulators for intervention are still scarce. The present review summarizes novel approaches to address these questions. Publicly accessible omics data provide new insights not only into general claudin expression patterns along the nephron, but also into sex-specific differences in claudin expression and into claudin dysregulation in renal injury. Computational association studies identify claudin variants as risk factors for kidney disease such as nephrolithiasis or loss of filtration capacity. The establishment of innovative cell culture and organoid models contributes to a better understanding of junctional and extra-junctional functions of individual claudins. The current studies lay the foundation for the identification of upstream regulators of renal claudin expression and thus for the development of new concepts for the treatment of kidney disease.

Characterizing dysregulations via cell-cell communications in Alzheimer’s brains using single-cell transcriptomes

BackgroundAlzheimer’s disease (AD) is a devastating neurodegenerative disorder affecting 44 million people worldwide, leading to cognitive decline, memory loss, and significant impairment in daily functioning. The recent single-cell sequencing technology has revolutionized genetic and genomic resolution by enabling scientists to explore the diversity of gene expression patterns at the finest resolution. Most existing studies have solely focused on molecular perturbations within each cell, but cells live in microenvironments rather than in isolated entities. Here, we leveraged the large-scale and publicly available single-nucleus RNA sequencing in the human prefrontal cortex to investigate cell-to-cell communication in healthy brains and their perturbations in AD. We uniformly processed the snRNA-seq with strict QCs and labeled canonical cell types consistent with the definitions from the BRAIN Initiative Cell Census Network. From ligand and receptor gene expression, we built a high-confidence cell-to-cell communication network to investigate signaling differences between AD and healthy brains.ResultsSpecifically, we first performed broad communication pattern analyses to highlight that biologically related cell types in normal brains rely on largely overlapping signaling networks and that the AD brain exhibits the irregular inter-mixing of cell types and signaling pathways. Secondly, we performed a more focused cell-type-centric analysis and found that excitatory neurons in AD have significantly increased their communications to inhibitory neurons, while inhibitory neurons and other non-neuronal cells globally decreased theirs to all cells. Then, we delved deeper with a signaling-centric view, showing that canonical signaling pathways CSF, TGFβ, and CX3C are significantly dysregulated in their signaling to the cell type microglia/PVM and from endothelial to neuronal cells for the WNT pathway. Finally, after extracting 23 known AD risk genes, our intracellular communication analysis revealed a strong connection of extracellular ligand genes APP, APOE, and PSEN1 to intracellular AD risk genes TREM2, ABCA1, and APP in the communication from astrocytes and microglia to neurons.ConclusionsIn summary, with the novel advances in single-cell sequencing technologies, we show that cellular signaling is regulated in a cell-type-specific manner and that improper regulation of extracellular signaling genes is linked to intracellular risk genes, giving the mechanistic intra- and inter-cellular picture of AD.

3D clustering of gene expression data from systemic autoinflammatory diseases using self-organizing maps (Clust3D)

Background and objectiveSystemic autoinflammatory diseases (SAIDs) are characterized by widespread inflammation, but for most of them there is a lack of specific biomarkers for accurate diagnosis. Although a number of machine learning algorithms have been used to analyze SAID datasets, aiding in the discovery of novel biomarkers, there is a growing recognition of the importance of SAID timeseries clustering, as it can capture the temporal dynamics of gene expression patterns. MethodologyThis paper proposes a novel clustering methodology to efficiently associate three-dimensional data. The algorithm utilizes competitive learning to create a self-organizing neural network and adjust neuron positions in time-dependent and high dimensional feature space in order to assign them as clustering centers. The quantitative evaluation of the clustering was based on well-known clustering indices. Furthermore, a differential expression analysis and classification pipeline was employed to assess the capability of the proposed methodology to extract more accurate pathway-specific genes from its clusters. For that, a comparative analysis was also conducted against a heuristic timeseries clustering method. ResultsThe proposed methodology achieved better overall clustering indices scores and classification metrics using genes derived from its clusters. Notable cases include a threefold increase in the Calinski-Harabasz clustering index, a twofold improvement in the Davies–Bouldin clustering index and a ∼60% increase in the classification specificity score. ConclusionA novel clustering methodology was developed and applied on several gene expression timeseries datasets from systemic autoinflammatory diseases, and its ability to efficiently produce well separated clusters compared to existing heuristic methods was demonstrated.

Expression of a unique M. tuberculosis DNA MTase Rv1509 in M. smegmatis alters the gene expression pattern and enhances virulence.

Mycobacterium tuberculosis (M. tb) genome encompasses 4,173 genes, about a quarter of which remain uncharacterized and hypothetical. Considering the current limitations associated with the diagnosis and treatment of tuberculosis, it is imperative to comprehend the pathomechanism of the disease and host-pathogen interactions to identify new drug targets for intervention strategies. Using in-silico comparative genome analysis, we identified one of the M. tb genes, Rv1509, as a signature protein exclusively present in M. tb. To explore the role of Rv1509, a likely methyl transferase, we constructed a knock-in Mycobacterium smegmatis (M. smegmatis) constitutively expressing Rv1509 (Ms_Rv1509). The Ms_Rv1509 led to differential expression of many transcriptional regulator genes as assessed by RNA-seq analysis. Further, in-vitro and in-vivo studies demonstrated an enhanced survival of Ms_Rv1509 inside the host macrophages. Ms_Rv1509 also promoted phagolysosomal escape inside macrophages to boost bacterial replication and dissemination. In-vivo infection studies revealed that Ms_Rv1509 survives better than BCG and causes pathological manifestations in the pancreas after intraperitoneal infection. Long-time survival of Ms_Rv1509 resulted in lymphocyte migration, increased T regulatory cells, giant cell formation, and likely granuloma formation in the pancreas, pointing toward the role of Rv1509 in M. tb pathogenesis.

Investigating gene signatures associated with immunity in colon adenocarcinoma to predict the immunotherapy effectiveness using NFM and WGCNA algorithms.

Colon adenocarcinoma (COAD), a frequently encountered and highly lethal malignancy of the digestive system, has been the focus of intensive research regarding its prognosis. The intricate immune microenvironment plays a pivotal role in the pathological progression of COAD; nevertheless, the underlying molecular mechanisms remain incompletely understood. This study aims to explore the immune gene expression patterns in COAD, construct a robust prognostic model, and delve into the molecular mechanisms and potential therapeutic targets for COAD liver metastasis, thereby providing critical support for individualized treatment strategies and prognostic evaluation. Initially, we curated a comprehensive dataset by screening 2600 immune-related genes (IRGs) from the ImmPort and InnateDB databases, successfully obtaining a rich data resource. Subsequently, the COAD patient cohort was classified using the non-negative matrix factorization (NMF) algorithm, enabling accurate categorization. Continuing on, utilizing the weighted gene co-expression network analysis (WGCNA) method, we analyzed the top 5000 genes with the smallest p-values among the differentially expressed genes (DEGs) between immune subtypes. Through this rigorous screening process, we identified the gene modules with the strongest correlation to the COAD subpopulation, and the intersection of genes in these modules with DEGs (COAD vs COAD vs Normal colon tissue) is referred to as Differentially Expressed Immune Genes Associated with COAD (DEIGRC). Employing diverse bioinformatics methodologies, we successfully developed a prognostic model (DPM) consisting of six genes derived from the DEIGRC, which was further validated across multiple independent datasets. Not only does this predictive model accurately forecast the prognosis of COAD patients, but it also provides valuable insights for formulating personalized treatment regimens. Within the constructed DPM, we observed a downregulation of CALB2 expression levels in COAD tissues, whereas NOXA1, KDF1, LARS2, GSR, and TIMP1 exhibited upregulated expression levels. These genes likely play indispensable roles in the initiation and progression of COAD and thus represent potential therapeutic targets for patient management. Furthermore, our investigation into the molecular mechanisms and therapeutic targets for COAD liver metastasis revealed associations with relevant processes such as fat digestion and absorption, cancer gene protein polysaccharides, and nitrogen metabolism. Consequently, genes including CAV1, ANXA1, CPS1, EDNRA, and GC emerge as promising candidates as therapeutic targets for COAD liver metastasis, thereby providing crucial insights for future clinical practices and drug development. In summary, this study uncovers the immune gene expression patterns in COAD, establishes a robust prognostic model, and elucidates the molecular mechanisms and potential therapeutic targets for COAD liver metastasis, thereby possessing significant theoretical and clinical implications. These findings are anticipated to offer substantial support for both the treatment and prognosis management of COAD patients.

Combined transcriptomics and proteomics unveil the impact of vitamin C in modulating specific protein abundance in the mouse liver

BackgroundVitamin C (ascorbate) is a water-soluble antioxidant and an important cofactor for various biosynthetic and regulatory enzymes. Mice can synthesize vitamin C thanks to the key enzyme gulonolactone oxidase (Gulo) unlike humans. In the current investigation, we used Gulo−/− mice, which cannot synthesize their own ascorbate to determine the impact of this vitamin on both the transcriptomics and proteomics profiles in the whole liver. The study included Gulo−/− mouse groups treated with either sub-optimal or optimal ascorbate concentrations in drinking water. Liver tissues of females and males were collected at the age of four months and divided for transcriptomics and proteomics analysis. Immunoblotting, quantitative RT-PCR, and polysome profiling experiments were also conducted to complement our combined omics studies.ResultsPrincipal component analyses revealed distinctive differences in the mRNA and protein profiles as a function of sex between all the mouse cohorts. Despite such sexual dimorphism, Spearman analyses of transcriptomics data from females and males revealed correlations of hepatic ascorbate levels with transcripts encoding a wide array of biological processes involved in glucose and lipid metabolisms as well as in the acute-phase immune response. Moreover, integration of the proteomics data showed that ascorbate modulates the abundance of various enzymes involved in lipid, xenobiotic, organic acid, acetyl-CoA, and steroid metabolism mainly at the transcriptional level, especially in females. However, several proteins of the mitochondrial complex III significantly correlated with ascorbate concentrations in both males and females unlike their corresponding transcripts. Finally, poly(ribo)some profiling did not reveal significant enrichment difference for these mitochondrial complex III mRNAs between Gulo−/− mice treated with sub-optimal and optimal ascorbate levels.ConclusionsThus, the abundance of several subunits of the mitochondrial complex III are regulated by ascorbate at the post-transcriptional levels. Our extensive omics analyses provide a novel resource of altered gene expression patterns at the transcriptional and post-transcriptional levels under ascorbate deficiency.