Bicarbonate Reclamation Research Articles

Proteomics analysis reveals the differential protein expression of female and male adult Toxocara canis using Orbitrap Astral analyzer.

Toxocara canis, the most prevalent helminth in dogs and other canines, is one of the socioeconomically important zoonotic parasites, particularly affecting pediatric and adolescent populations in impoverished communities. However, limited information is available regarding the proteomes of female and male adult T. canis. To address this knowledge gap, we performed a comprehensive proteomic analysis to identify the proteins with differential abundance (PDAs) and gender-specifically expressed proteins between the two sexes adult T. canis. The comparative proteomic analysis was carried out by the Orbitrap mass spectrometry (MS) with asymmetric track lossless (Astral) analyzer. The difference analysis was conducted using t-test and the proteins verification was achieved through parallel reaction monitoring (PRM). The potential biological functions of identified adult T. canis proteins and PDAs were predicted by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. The domain, transcription factor and subcellular localization of the identified proteins and PDAs were analyzed by InterPro, AnimalTFDB 4.0 and Cell-mPLOC 2.0 databases, respectively. A total of 8565 somatic proteins of adult T. canis were identified. Compared to male adult, 682 up-regulated PDAs and 844 down-regulated PDAs were identified in female adult with P-values < 0.05 and |log2FC|> 1, including 139 proteins exclusively expressed in female and 272 proteins exclusively expressed in male. The GO annotation analysis using all PDAs revealed that the main biological processes, cellular components and molecular functions corresponded to aminoglycan metabolic process, extracellular region and protein tyrosine phosphatase activity, respectively. The KEGG analysis using all PDAs showed that the pathways were mainly associated with adipocytokine signaling pathway, proximal tubule bicarbonate reclamation and PPAR signaling pathway. This study reveals the differential protein expression between female and male adult T. canis, providing valuable resource for developing the novel intervention strategies against T. canis infection in humans and animals, especially from the perspective of sexual development and reproduction.

Biomarker Identification for Preterm Birth Susceptibility: Vaginal Microbiome Meta-Analysis Using Systems Biology and Machine Learning Approaches.

The vaginal microbiome has a substantial role in the occurrence of preterm birth (PTB), which contributes substantially to neonatal mortality worldwide. However, current bioinformatics approaches mostly concentrate on the taxonomic classification and functional profiling of the microbiome, limiting their abilities to elucidate the complex factors that contribute to PTB. A total of 3757 vaginal microbiome 16S rRNA samples were obtained from five publicly available datasets. The sampleswere divided into two categories based on pregnancy outcome: preterm birth (PTB) (N = 966) and term birth (N = 2791). Additionally, the samples were further categorized based on the participants' race and trimester. The 16S rRNA reads were subjected to taxonomic classification and functional profiling using the Parallel-META 3 software in Ubuntu environment. The obtained abundances were analyzed using an integrated systems biology and machine learning approach to determine the key microbes, pathways, and genes that contribute to PTB. The resulting features were further subjected tostatistical analysis to identify the top nine features with the greatest effect sizes. We identified nine significant features, namely Shuttleworthia, Megasphaera, Sneathia, proximal tubule bicarbonate reclamation pathway, systemic lupus erythematosus pathway, transcription machinery pathway, lepA gene, pepX gene, and rpoD gene. Their abundance variations were observed through the trimesters. Vaginal infections caused by Shuttleworthia, Megasphaera, and Sneathia and altered small metabolite biosynthesis pathways such as lipopolysaccharide folate and retinal may increase the susceptibility to PTB. The identified organisms, genes, pathways, and their networks may be specifically targeted for thetreatment of bacterial infections that increasePTB risk.

Genomic Fabrics of the Excretory System's Functional Pathways Remodeled in Clear Cell Renal Cell Carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most frequent form of kidney cancer. Metastatic stages of ccRCC reduce the five-year survival rate to 15%. In this report, we analyze the ccRCC-induced remodeling of the five KEGG-constructed excretory functional pathways in a surgically removed right kidney and its metastasis in the chest wall from the perspective of the Genomic Fabric Paradigm (GFP). The GFP characterizes every single gene in each region by these independent variables: the average expression level (AVE), relative expression variability (REV), and expression correlation (COR) with each other gene. While the traditional approach is limited to only AVE analysis, the novel REV analysis identifies the genes whose correct expression level is critical for cell survival and proliferation. The COR analysis determines the real gene networks responsible for functional pathways. The analyses covered the pathways for aldosterone-regulated sodium reabsorption, collecting duct acid secretion, endocrine and other factor-regulated sodium reabsorption, proximal tubule bicarbonate reclamation, and vasopressin-regulated water reabsorption. The present study confirms the conclusion of our previously published articles on prostate and kidney cancers that even equally graded cancer nodules from the same tumor have different transcriptomic topologies. Therefore, the personalization of anti-cancer therapy should go beyond the individual, to his/her major cancer nodules.

Replacing dietary sodium selenite with biogenic selenium nanoparticles improves the growth performance and gut health of early-weaned piglets

Selenium nanoparticles (SeNPs) are proposed as a safer and more effective selenium delivery system than sodium selenite (Na2SeO3). Here, we investigated the effects of replacing dietary Na2SeO3 with SeNPs synthesized by Lactobacillus casei ATCC 393 on the growth performance and gut health of early-weaned piglets. Seventy-two piglets (Duroc × Landrace × Large Yorkshire) weaned at 21 d of age were divided into the control group (basal diet containing 0.3 mg Se/kg from Na2SeO3) and SeNPs group (basal diet containing 0.3 mg Se/kg from SeNPs) during a 14-d feeding period. The results revealed that SeNPs supplementation increased the average daily gain (P = 0.022) and average daily feed intake (P = 0.033), reduced (P = 0.056) the diarrhea incidence, and improved (P = 0.013) the feed conversion ratio compared with Na2SeO3. Additionally, SeNPs increased jejunal microvilli height (P = 0.006) and alleviated the intestinal barrier dysfunction by upregulating (P < 0.05) the expression levels of mucin 2 and tight junction proteins, increasing (P < 0.05) Se availability, and maintaining mitochondrial structure and function, thereby improving antioxidant capacity and immunity. Furthermore, metabolomics showed that SeNPs can regulate lipid metabolism and participate in the synthesis, secretion and action of parathyroid hormone, proximal tubule bicarbonate reclamation and tricarboxylic acid cycle. Moreover, SeNPs increased (P < 0.05) the abundance of Holdemanella and the levels of acetate and propionate. Correlation analysis suggested that Holdemanella was closely associated with the regulatory effects of SeNPs on early-weaned piglets through participating in lipid metabolism. Overall, replacing dietary Na2SeO3 with biogenic SeNPs could be a potential nutritional intervention strategy to prevent early-weaning syndrome in piglets.

Transcriptional Modulation Reveals Physiological Responses to Temperature Adaptation in Acrossocheilus fasciatus.

In order to explore the molecular regulatory mechanism of temperature acclimation under long-term temperature stress in Acrossocheilus fasciatus, this study used high-throughput sequencing technology to analyze 60 days of breeding under five temperature conditions (12 °C, 16 °C, 20 °C, 24 °C, 28 °C). Compared with 20 °C, 9202, 4959 differentially expressed genes (DEGs) were discovered in low-temperature groups (12 °C, 16 °C), whereas 133 and 878 DEGs were discovered in high-temperature groups (24 °C, 28 °C), respectively. The KEGG functional enrichment analysis revealed that DEGs were primarily enriched in tight junction, PI3 K-Akt signaling pathway and protein digestion and absorption in low-temperature groups, and mainly enriched in proximal tubule bicarbonate reclamation, protein digestion and absorption, and HIF-1 signaling pathway in high-temperature groups. The viability of transcriptome sequencing-based screening of DEGs for temperature adaptation in A. fasciatus was shown by the selection of eight DEGs for further validation by quantitative real-time PCR (qRT-PCR), the findings of which were consistent with the RNA-seq data. According to the findings, protein digestion and absorption were primarily regulated by temperature variations, physiological stress was a significant regulator in regulation under high-temperature stress, and the immune system was a significant regulator in regulation under low-temperature stress. The transcriptional patterns of A. fasciatus under temperature stress are revealed in this study. This knowledge is crucial for understanding how A. fasciatus adapts to temperature and can help us better comprehend the environmental difficulties that A. fasciatus adaptation faces.

Elucidating environmental factors and their combined effects on CKDu in Sri Lanka using zebrafish

Chronic kidney disease with uncertain etiology (CKDu) in Sri Lanka has attracted much attention as a global health issue. However, how environmental factors in local drinking water induce kidney damage in organisms is still elusive. We investigated multiple environmental factors including water hardness and fluoride (HF), heavy metals (HM), microcystin-LR (MC-LR), and their combined exposure (HFMM) to elucidate their toxic effects on CKDu risk in zebrafish. Acute exposure affected renal development and inhibited the fluorescence of Na, K-ATPase alpha1A4:GFP zebrafish kidney. Chronic exposure influenced the body weight of both genders of adult fish and induced kidney damage by histopathological analyses. Furthermore, the exposure significantly disturbed differential expression genes (DEGs), diversity and richness of gut microbiota, and critical metabolites related to renal functions. The transcriptomic analysis revealed that kidney-related DEGs were linked with renal cell carcinoma, proximal tubule bicarbonate reclamation, calcium signaling pathway, and HIF-1 signaling pathway. The significantly disrupted intestinal microbiota was closely related to the environmental factors and H&E score, which demonstrated the mechanisms of kidney risks. Notably, the Spearman correlation analysis indicated that the changed bacteria such as Pseudomonas, Paracoccus, and ZOR0006, etc were significantly connected to the DEGs and metabolites. Therefore, the assessment of multiple environmental factors provided new insights on “bio-markers” as potential therapies of the target signaling pathways, metabolites, and gut bacteria to monitor or protect residents from CKDu.

Alterations in gut microbiota and urine metabolomics in infants with yin-deficiency constitution aged 0–2 years

BackgroundBased on the constitution theroy, infants are classified into balanced constitution (BC) and unbalanced constitution. Yin-deficiency constitution (YINDC) is a common type of unbalanced constitutions in Chinese infants. An infant's gut microbiota directly affects the child's health and has long-term effects on the maturation of the immune and endocrine systems throughout life. However, the gut microbiota of infants with YINDC remains unknown. Herein, we aimed to evaluate the intestinal flora profiles and urinary metabolites in infant with YINDC, find biomarkers to identify YINDC, and promote our understanding of infant constitution classification. MethodsConstitutional Medicine Questionnaires were used to assess the infants’ constitution types. 47 infants with 21 cases of YINDC and 26 cases of BC were included, and a cross-sectional sampling of stool and urine was conducted. Fecal microbiota was characterized using 16S rRNA sequencing, and urinary metabolomics was profiled using UPLC-Q-TOF/MS method. YINDC markers with high accuracy were identified using receiver operating characteristic (ROC) analysis. ResultsThe diversity and composition of intestinal flora and urinary metabolites differed significantly between the YINDC and BC groups. A total of 13 obviously different genera and 55 altered metabolites were identified. Stool microbiome shifts were associated with urine metabolite changes. A combined marker comprising two genera may have a high potential to identify YINDC with an AUC of 0.845. ConclusionsInfants with YINDC had a unique gut microbiota and metabolomic profile resulting in a constitutional microclassification. The altered gut microbiome in YINDC may account for the higher risk of cardiovascular diseases. Metabolomic analysis of urine showed that metabolic pathways, including histidine metabolism, proximal tubule bicarbonate reclamation, arginine biosynthesis, and steroid hormone biosynthesis, were altered in infants with YINDC. Additionally, the combined bacterial biomarker had the ability to identify YINDC. Identifying YINDC in infancy and intervening at an early stage is crucial for preventing cardiovascular diseases.

Combined Intake of Fish Oil and D-Fagomine Prevents High-Fat High-Sucrose Diet-Induced Prediabetes by Modulating Lipotoxicity and Protein Carbonylation in the Kidney.

Obesity has been recognized as a major risk factor for chronic kidney disease, insulin resistance being an early common metabolic feature in patients suffering from this syndrome. This study aims to investigate the mechanism underlying the induction of kidney dysfunction and the concomitant onset of insulin resistance by long-term high-fat and sucrose diet feeding in Sprague Dawley rats. To achieve this goal, our study analyzed renal carbonylated protein patterns, ectopic lipid accumulation and fatty acid profiles and correlated them with biometrical and biochemical measurements and other body redox status parameters. Rats fed the obesogenic diet developed a prediabetic state and incipient kidney dysfunction manifested in increased plasma urea concentration and superior levels of renal fat deposition and protein carbonylation. An obesogenic diet increased renal fat by preferentially promoting the accumulation of saturated fat, arachidonic, and docosahexaenoic fatty acids while decreasing oleic acid. Renal lipotoxicity was accompanied by selectively higher carbonylation of proteins involved in the blood pH regulation, i.e., bicarbonate reclamation and synthesis, amino acid, and glucose metabolisms, directly related to the onset of insulin resistance. This study also tested the combination of antioxidant properties of fish oil with the anti-diabetic properties of buckwheat D-Fagomine to counteract diet-induced renal alterations. Results demonstrated that bioactive compounds combined attenuated lipotoxicity, induced more favorable lipid profiles and counteracted the excessive carbonylation of proteins associated with pH regulation in the kidneys, resulting in an inhibition of the progression of the prediabetes state and kidney disease.

Differential renal proteomics analysis in a novel rat model of iodinated contrast-induced acute kidney injury

Contrast-induced acute kidney injury (CI-AKI), which occurs after the use of iodinated contrast media, has become the third leading cause of hospital-acquired acute kidney injury (AKI). It is associated with prolonged hospitalization and increased risks of end-stage renal disease and mortality. The pathogenesis of CI-AKI is unclear and effective treatments are lacking. By comparing different post-nephrectomy times and dehydration times, we constructed a new, short-course CI-AKI model using dehydration for 24 h two weeks after unilateral nephrectomy. We found that the low-osmolality contrast media iohexol caused more severe renal function decline, renal morphological damage, and mitochondrial ultrastructural alterations compared to the iso-osmolality contrast media iodixanol. The shotgun proteomics based on Tandem Mass Tag (TMT) was used to conduct proteomics research on renal tissue in the new CI-AKI model, and 604 distinct proteins were identified, mainly involving complement and coagulation cascade, COVID-19, PPAR signalling pathway, mineral absorption, cholesterol metabolism, ferroptosis, staphylococcus aureus infection, systemic lupus erythematosus, folate biosynthesis, and proximal tubule bicarbonate reclamation. Then, using parallel reaction monitoring (PRM), we validate 16 candidate proteins, of which five were novel candidates (Serpina1, Apoa1, F2, Plg, Hrg) previously unrelated to AKI and associated with an acute response as well as fibrinolysis. The pathway analysis and 16 candidate proteins may help to discover new mechanisms in the pathogenesis of CI-AKI, allowing for early diagnosis and outcome prediction.

Identification of potential biomarkers for colorectal cancer by clinical database analysis and Kaplan-Meier curves analysis.

This study aimed to explore critical genes as potential biomarkers for the diagnosis and prognosis of colorectal cancer (CRC) for clinical utility. To identify and screen candidate genes involved in CRC carcinogenesis and disease progression, we downloaded microarray datasets GSE89076, GSE73360, and GSE32323 from the GEO database identified differentially expressed genes (DEGs), and performed a functional enrichment analysis. A protein-protein interaction network was constructed, and correlated module analysis was performed using STRING and Cytoscape. The Kaplan-Meier survival curve shows the survival of the hub genes. The expression of cyclin-dependent kinase (CDK1), cyclin B1 (CCNB1), and PCNA in tissues and changes in tumor grade were analyzed. A total of 329 DEGs were identified, including 264 upregulated and 65 downregulated genes. The functions and pathways of DEGs include the mitotic cell cycle, poly(A) RNA binding replication, ATP binding, DNA replication, ribosome biogenesis in eukaryotes, and RNA transport. Forty-seven Hub genes were identified, and biological process analysis showed that these genes were mainly enriched in cell cycle and DNA replication. Patients with mutations in CDK1, PCNA, and CCNB1 had poorer survival rates. CDK1, PCNA, and CCNB1 were significantly overexpressed in the tumor tissues. The expression of CDK1 and CCNB1 gradually decreased with increasing tumor grade. CDK1, CCNB1, and PCNA can be used as potential markers for the diagnosis and prognosis of CRC. These genes are overexpressed in colon cancer tissues and are associated with low survival rates in CRC patients.

The Gut Microbiota Modulates Gene Expression in the Kidney

Gut microbiota are a diverse array of commensal bacteria in the intestinal lumen, and shifts in the composition of gut microbes can influence host health. We have previously established a link between the gut microbiota and host kidney function by showing that gut microbial metabolites can activate G protein‐coupled receptors in the kidney. Although host‐microbiome interactions have been studied at the signaling level, the influence of gut microbes on gene expression at the transcriptional level is unclear. Evidence demonstrates that gut microbiota alters gene transcription in the colon (J. Allen, Genome Medicine, 2019); however, it is entirely unknown whether gut microbiota influences host gene expression at distal sites, such as the kidney. To address this question for the first time, we utilized an unbiased RNA sequencing (RNASeq) approach to compare gene expression in the kidneys of male and female mice which were either germ‐free (GF; without gut microbes) or conventionalized (Conv; with gut microbes). All mice were born on a C57Bl/6 background and housed in the Johns Hopkins GF facility. At four weeks of age, a subset of mice (n=5 males, n=5 females) were conventionalized via oral gavage using a fecal slurry of mixed stool from age‐matched specific‐pathogen free (SPF) mice (n=3 males, n=3 females); whereas an additional cohort of mice (n=5 males, n=5 females) were maintained as GF. Eight weeks after conventionalization both GF and Conv mice were sacrificed, whole kidneys were processed for RNASeq, and fecal pellets from Conv mice were collected for 16S rRNA sequencing. For RNASeq analysis, differentially expressed genes (DEGs) were defined as having a log2fold change ≥ ± 0.5 and base mean ≥ 15 (the average of the normalized count values, dividing by size factors, taken over all samples). We identified a clear effect of the gut microbiota on renal gene expression: 578 DEGs between GF and Conv males, and 340 DEGs between GF and Conv females. Only 73 of these DEGs were common to both males and females. These data demonstrate that the gut microbiota not only impacts gene expression in the kidney, but does so in a sex‐specific manner. In addition, 16S rRNA sequencing showed no differences in bacterial colonization between male and female Conv mice, establishing that the renal transcriptomic differences are not a consequence of differing gut microbes; rather, the same microbes have differential effects in males and females, presumably through differences in either signals (i.e., microbial metabolites), or differences in host responses. Furthermore, DAVID pathway analysis revealed that DEGs are involved in pathways including aldosterone synthesis and secretion, mineral absorption, proximal tubule bicarbonate reclamation, and vasopressin‐regulated water reabsorption. In sum, we demonstrate that the gut microbiota influences kidney gene expression in a sex‐specific manner, and that these transcriptional changes are poised to impact kidney physiology and regulation. We are now working to identify physiologically relevant signals from the microbiome and/or host that mediate these sex‐specific differences, and to determine how they influence renal function.

The Regulatory Role of Neuropeptide Gene Glucagon in Colorectal Cancer: A Comprehensive Bioinformatic Analysis

Background Colorectal cancer is highly prevalent and causes high global mortality, and glucagon axis has been implicated in colon cancer. The present study is aimed at investigating the regulating mechanisms of glucagon involvement in colorectal cancer. Methods Publicly available data from the TCGA database was utilized to explore the expression pattern and regulating role of glucagon (GCG) in colorectal cancer (COADREAD) including colon adenocarcinomas (COAD) and rectum adenocarcinomas (READ). Statistical analyses were performed using the R software packages and public web servers. The expression pattern and prognostic significance of GCG gene in pan-cancer and TCGA-COADREAD data were investigated by performing unpaired and paired sample analyses. The association of GCG expression with clinical characteristics was investigated using logistic regression analysis. Univariate cox regression analysis was performed to test the prognostic value of GCG expression for overall survival in COADREAD patients. GCG-significantly correlated genes were obtained. Biological functions and signaling pathways were identified by performing functional enrichment analysis and Gene Set Enrichment Analysis (GSEA). Additionally, the potential involvement of GCG in tumor immunity was researched by investigating the correlation between GCG expression and 24 tumor infiltrating immune cells. Results GCG was found to be significantly downregulated in COADREAD tumor samples compared with healthy control samples. GCG gene was shown to be associated with the prognostic outcomes of COADREAD, whereby its upregulation predicted improved survival outcomes. Functional enrichment analysis showed that the top 100 positively and top 100 negatively GCG-correlated genes were mainly enriched in three signaling pathways including ribosome, nitrogen metabolism, and proximal tubule bicarbonate reclamation. The GSEA showed that GCG-significantly correlated genes were mainly enriched in cell cycle-related pathways (reactome cell cycle, reactome cell cycle mitotic, reactome cell cycle checkpoints, reactome M phase, Reactome G2 M DNA damage checkpoint, and Reactome G2 M checkpoints), neuropeptide ligand receptor interaction, RHO GTPases signaling, WNT signaling, RUNX1 signaling, NOTCH signaling, ESR signaling, HCMV infection, and oxidative stress-related signaling. GCG was positively correlated with Th17 cells, pDC, macrophages, TFH cells, iDC, Tem, B cells, dendritic cells, neutrophils, mast cells, and eosinophils and was negatively associated with NK cells. Conclusions GCG dysregulation with high prognostic value in COADREAD was noted. Several tumor progression-related pathways and tumor immune-modulatory cells were linked to GCG expression in COADREAD. Therefore, GCG may be regarded as a potential therapeutic target for treating colorectal cancer.

Identification of target genes and prognostic evaluation for colorectal cancer using integrated bioinformatics analysis

The underlying molecular mechanisms of colorectal cancer (CRC) has attracted great attention from the scholarly community. The aim of our study is to identify pivotal genes related to the pathogenesis and prognosis of CRC. We integrated five microarray datasets from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were analyzed with the limma package. DAVID and OmicShare tools were used for Gene Ontology (GO) and KEGG enrichment analysis. The protein–protein interaction (PPI) network of DEGs was constructed. The prognostic analysis of hub genes was performed through Kaplan Meier-plotter. Finally, potential drugs were predicted in the CMap database. Through five microarray datasets, a total of 90 DEGs were detected including 54 up-regulated and 36 down-regulated genes. Biological process analysis showed DEGs were mainly enriched in positive regulation of neutrophil chemotaxis, chemokine-mediated signaling pathway, and bicarbonate transport. Signaling pathway analysis indicated that DEGs played a vital in proximal tubule bicarbonate reclamation, cell cycle and progesterone-mediated oocyte maturation. The GEPIA database confirmed that overexpression levels of hub genes were significantly associated with better survival of patients. Finally, the 20 most significant small molecules were obtained based on the CMap database. Our study has identified novel candidate biomarkers, pathways, and kinases associated with CRC prognosis.

UBE2C affects breast cancer proliferation through the AKT/mTOR signaling pathway.

Background:Ubiquitin-conjugating enzyme E2C (UBE2C) has been shown to be associated with the occurrence of various cancers and involved in many tumorigenic processes. This study aimed to investigate the specific molecular mechanism through which UBE2C affects breast cancer (BC) proliferation.Methods:BC-related datasets were screened according to filter criteria in the Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database. Then differentially expressed genes (DEGs) were identified using Venn diagram analysis. By using DEGs, we conducted the following analyses including Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), protein–protein interaction (PPI), and survival analysis, and then validated the function of the hub gene UBE2C using quantitative reverse transcription-polymerase chain reaction (RT-qPCR), cell counting kit-8 (CCK-8) assay, transwell assay, and Western blot assay.Results:In total, 151 DEGs were identified from the GEO and TCGA databases. The results of GO analysis demonstrated that the DEGs were significantly enriched with mitotic nuclear division, lipid droplet, and organic acid-binding. KEGG analysis showed that the peroxisome proliferators-activated receptor (PPAR) signaling pathway, regulation of lipolysis in adipocytes, and proximal tubule bicarbonate reclamation were significantly enriched in the signal transduction pathway category. The top three hub genes that resulted from the PPI network were FOXM1, UBE2C, and CDKN3. The results of survival analysis showed a close relationship between UBE2C and BC. The results of CCK-8 and transwell assays suggested that the proliferation and invasion of UBE2C knockdown cells were significantly inhibited (P < 0.050). The results of Western blot assay showed that the level of phosphorylated phosphatase and tensin homology deleted on chromosome 10 (p-PTEN) was obviously increased (P < 0.050), whereas the levels of phosphorylated protein kinase B (p-AKT), phosphorylated mammalian target of rapamycin (p-mTOR), and hypoxia-inducible factor-1 alpha (HIF-1α) were dramatically decreased (P < 0.050) in the UBE2C knockdown cell.Conclusion:UBE2C can promote BC proliferation by activating the AKT/mTOR signaling pathway.

ITRAQ-based proteome analysis of porcine group A rotavirus-infected porcine IPEC-J2 intestinal epithelial cells

Porcine rotavirus (PoRV), particularly group A, is one of the most important swine pathogens, causing substantial economic losses in the animal husbandry industry. To improve understanding of host responses to PoRV infection, we applied isobaric tags for relative and absolute quantification (iTRAQ) labeling coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to quantitatively identify the differentially expressed proteins in PoRV-infected IPEC-J2 cells and confirmed the differentially accumulated proteins (DAPs) expression differences by performing RT-qPCR and Western blot analysis. Herein, in PoRV- and mock-infected IPEC-J2 cells, relative quantitative data were identified for 4724 proteins, 223 of which were DAPs (125 up-accumulated and 98 down-accumulated). Bioinformatics analyses further revealed that a majority of the DAPs are involved in numerous crucial biological processes and signaling pathways, such as metabolic process, immune system process, amino acid metabolism, energy metabolism, immune system, MHC class I peptide loading complex, Hippo signaling pathway, Th1 and Th2 cell differentiation, antigen processing and presentation, and tubule bicarbonate reclamation. The cellular localization prediction analysis indicated that these DAPs may be located in the Golgi apparatus, nucleus, peroxisomal, cytoplasm, mitochondria, extracellular, plasma membrane, and endoplasmic reticulum (ER). Expression levels of three up-accumulated (VAMP4, IKBKE, and TJP3) or two down-accumulated (SOD3 and DHX9) DAPs upon PoRV infection, were further validated by RT-qPCR and Western blot analysis. Collectively, this work is the first time to investigate the protein profile of PoRV-infected IPEC-J2 cells using quantitative proteomics; these findings provide valuable information to better understand the mechanisms underlying the host responses to PoRV infection in piglets. SignificanceThe proteomics analysis of this study uncovered the target associated with PoRV-induced innate immune response or cellular damage, and provided relevant insights into the molecular functions, biological processes, and signaling pathway in these targets. Out of these 223 DAPs, the expression levels of three up-accumulated (VAMP4, IKBKE, and TJP3) and two down-accumulated (SOD3 and DHX9) DAPs upon PoRV infection, have been further validated using RT-qPCR and Western blot analysis. These outcomes could uncover how PoRV manipulated the cellular machinery, which could further our understanding of PoRV pathogenesis in piglets.

Identification of gene biomarkers and immune cell infiltration characteristics in rectal cancer.

Compared with colon cancer, the increase of morbidity is more significant for rectal cancer. The current study set out to identify novel and critical biomarkers or features that may be used as promising targets for early diagnosis and treatment monitoring of rectal cancer. Microarray datasets of rectal cancer with a minimum sample size of 30 and RNA-sequencing datasets of rectal adenocarcinoma (READ) were downloaded from the Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database. The method of robust rank aggregation was utilized to integrate differentially expressed genes (DEGs). The protein-protein interaction (PPI) network of the DEGs was structured using the STRING platform, and hub genes were identified using the Cytoscape plugin cytoHubba and an UpSet diagram. R software was employed to perform functional enrichment analysis. Receiver operating characteristic (ROC) curves based on the GEO data and Kaplan-Meier curves based on the TCGA data were drawn to assess the diagnostic and prognostic values of the hub genes. Immune cell infiltration analysis was conducted with CIBERSORT, and the diagnostic value and correlations between prognostic genes and infiltrated immune cells were analyzed by principal component analysis (PCA), ROC curves, and correlation scatter plots. A total of 137 robust DEGs were obtained by integrating datasets in GEO. Twenty-four hub genes, including CHGA, TTR, SAA1, SPP1, MMP1, TGFBI, COL1A1, and PCK1, were identified as a diagnostic gene biomarker group for rectal cancer, and SAA1, SPP1, and SI were identified as potential novel prognostic biomarkers. Functionally, the hub genes were mainly involved in the rectal cancer related interleukin (IL)-17 and proximal tubule bicarbonate reclamation pathways. Twelve sensitive infiltrated immune cells were identified, and were correlated with prognostic genes. The integrated gene biomarker group combined with immune cell infiltration can effectively indicate rectal cancer.

A novel genomic model for predicting the likelihood of delayed graft function in DCD kidney transplantation.

BackgroundThe high incidence of delayed graft function (DGF) following kidney transplantation with donation after cardiac death allografts (DCD-KT) poses great challenges to transplant clinicians. This study aimed to explore the DGF-related biomarkers and establish a genomic model for DGF prediction specific to DCD KT.MethodsBy data mining a public dataset (GSE43974), the key DGF-related genes in DCD kidney biopsies taken after short-time reperfusion (45–60 min) were identified by differential expression analysis and a LASSO-penalized logistic regression model. Their coefficients for modeling were calculated by multivariate logistic regression. Receiver operating characteristic curves and a nomogram were generated to evaluate its predictive ability for DGF occurrence. Gene set enrichment analysis (GSEA) was performed to explore biological pathways underlying DGF in DCD KT.ResultsFive key DGF-related genes (CHST3, GOLPH3, ZBED5, AKR1C4, and ERRFI1) were first identified, all of which displayed good discrimination for DGF occurrence after DCD KT (all P<0.05). A five-mRNA-based risk score was further established and showed excellent predictive ability (AUC =0.9708, P<0.0001), which was obviously higher than that of the five genes alone. Eight DGF-related biological pathways in DCD kidneys, such as “arachidonic acid metabolism”, “lysosome”, “proximal tubule bicarbonate reclamation”, “glutathione metabolism”, were identified by GSEA (all P<0.05). Moreover, a convenient and visual nomogram based on the genomic risk score was also constructed and displayed high accuracy for DGF prediction specific to DCD KT.ConclusionsThe novel genomic model may effectively predict the likelihood of DGF immediately after DCD KT or even prior to transplantation in the context of normothermic machine perfusion in the future.

Predictive Biomarker Panel in Proliferative Lupus Nephritis- Two-Dimensional Shotgun Proteomics.

Introduction Lupus nephritis (LN) is one of the most serious complications of systemic lupus erythematous (SLE). With no specific clinical or laboratory manifestation to predict response to treatment, this study was aimed to provide a panel of predictive biomarkers of response before initiation of treatment. Methods Liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis was performed on plasma and urine samples of 11 patients with biopsy proven proliferative LN at the time of biopsy. Unsupervised principal component analysis (PCA), orthogonal projection to latent structures discriminant analysis (OPLS-DA), gene ontology annotation and protein mapping were performed on 326 proteins in plasma and 1381 proteins in urine samples. Results Samples of eight patients achieved complete remission and three reached partial remission were analyzed. The mean 24-hour protein excretion was 3259 mg/day and the mean eGFR was 87.73 cc/min. OPLS-DA analysis of plasma samples showed a clear discrimination for complete and partial remission patients. Twenty plasma proteins and ten urine proteins with the highest fold changes and AUCs were selected as candidate biomarkers (IGHV1-18, PI16, IGHD, C3, FCER2, EPS8L2, CTTN, BLVRB). This plasma and urine biomarker panel is involved in oxidative stress, acute inflammation, reduction in regulatory T cells, complement pathway consumption, and proximal tubule bicarbonate reclamation. Conclusion Our suggested panel of plasma and urine biomarkers can precisely discriminate patients with possibility of complete response to treatment. It seems that the higher indices of inflammation will associate with better chance of achieving complete remission.

Infertility network and hub genes for nonobstructive azoospermia utilizing integrative analysis.

Non-obstructive azoospermia (NOA) is the most severe form of male infertility owing to the absence of sperm during ejaculation as a result of failed spermatogenesis. The molecular mechanisms of NOA have not been well studied. Here, we revealed the dysregulated differentially expressed genes in NOA and related signaling pathways or biological processes. Cluster features of biological processes include spermatogenesis, fertilization, cilium movement, penetration of zona pellucida, sperm chromatin condensation, and being significantly enriched metabolic pathways in proximal tubule bicarbonate reclamation, aldosterone synthesis and secretion, glycolysis and glycogenesis pathways in NOA using Gene Ontology analysis and pathway enrichment analysis. The NOA gene co-expression network was constructed by weighted gene co-expression network analysis to identify the hub genes (CHD5 and SPTBN2). In addition, we used another Gene Expression Omnibus dataset (GSE45887) to validate these hub genes. Furthermore, we used the Seurat package to classify testicular tissue cells from NOA patients and to characterize the differential expression of hub genes in different cell types from different adult males based on the scRNA-seq dataset (GSE106487). These results provide new insights into the pathogenesis of NOA. Of particular note, CHD5 and SPTBN2 may be potential biomarkers for the diagnosis and treatment of NOA.

Integrated Analysis of Gene Expression and Metabolite Data Reveals Candidate Molecular Markers in Colorectal Carcinoma.

Background: This study investigated potential gene targets and metabolite markers associated with colorectal carcinoma (CRC). Materials & Methods: Gene expression data (GSE110224) related with CRC were obtained from Gene Expression Omnibus, including 17 tumor tissues and 17 normal colon ones. The gene differential analysis, functional analysis, protein-protein interaction (PPI) analysis, and metabolite network construction were performed to identify key genes related to CRC. Moreover, an external dataset was used to validate genes of interest in CRC, and corresponding survival analysis was also conducted. Results: The authors extracted 197 differentially expressed genes (75 upregulated and 122 downregulated genes). Moreover, upregulated genes were closely associated with rheumatoid arthritis and amoebiasis pathways. The downregulated genes were mainly related to bile secretion and proximal tubule bicarbonate reclamation pathway. Combined with PPI network and metabolite prediction, the overlapped nine genes (CXCL1, CXCL8, CXCL10, HDS1782, IL18, PCK1, PTGS2, SERPINB2, TMP1) were found to be critical in CRC. Similar gene expression profiles of nine critical genes were validated by an external dataset, except for SERPINB2. In addition, the expressions of TIMP1, IL1B, and PTGS2 were closely related with prognosis. Finally, the metabolite network analysis revealed that there were close associations between prostaglandin E2 and three pathways (rheumatoid arthritis, amoebiasis, and leishmaniasis). Conclusion: CXCL1/CXCL8/IL1B/PTGS2-prostaglandin E2 axes were the potential signatures involved in CRC progression, which could provide new insights to understand the molecular mechanisms of CRC.