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At least 19 recordsLinked to original sources
PubMed1992

Arg276 of GseA, a Chlamydia trachomatis Kdo transferase, is required for the synthesis of the chlamydial genus-specific epitope in Escherichia coli.

GseA is an enzyme from Chlamydia trachomatis that can catalyse the addition of three 3-deoxy-D-manno-octulosonic acid (Kdo) residues onto lipid A precursors. GseA is similar, and in a few stretches identical, in its amino acid sequence to KdtA, an Escherichia coli Kdo transferase. In this study we altered an amino acid of GseA in a region that is identical between GseA and KdtA to test its importance in the structure or catalytic activity of GseA. We found that when Arg276 was changed to Lys, Ile or Ser, GseA activity was lost, suggesting an enzymatic role for this amino acid residue.

Amino Acid Sequence↗
PubMed2004

PCR-based identification of Staphylococcus epidermidis targeting gseA encoding the glutamic-acid-specific protease.

The frequency of the gseA gene encoding a glutamic acid-specific serine protease, GluSE, of Staphylococcus epidermidis was investigated. DNA hybridization analysis demonstrated that gseA existed exclusively in S. epidermidis but not in other bacteria examined. A single step PCR assay with a set of designed primers yielded amplification of gseA from all 69 clinical isolates of S. epidermidis taken from patients and healthy adults, whereas production of GluSE was observed in 74% (51/69) of the isolates. Furthermore, none of the 46 clinical isolates of other species of coagulase-negative staphylococci and 45 clinical isolates of Staphylococcus aureus showed amplification, except a Staphylococcus capitis strain. However, this strain was positive for a S. epidermidis-specific DNA region and the DNA sequence of the 16S rRNA gene showed 99% identity with that of S. epidermidis. Therefore, these results indicated that the present PCR assay for gseA was ubiquitous and highly specific for detection of S. epidermidis.

Bacterial Proteins↗
PubMed1994

Nucleotide sequence variations within the lipopolysaccharide biosynthesis gene gseA (Kdo transferase) among the Chlamydia trachomatis serovars.

The gene gseA, involved in the expression of the genus-specific epitope of chlamydial lipopolysaccharide (LPS), was analyzed by temperature gradient gel electrophoresis (TGGE) to visualize nucleotide sequence variations among the 15 serovars of Chlamydia trachomatis. Sequence analysis showed that the TGGE melting-profile patterns were able to detect single nucleotide variations within gseA and allowed the arrangement of the serovars in groups of both identical nucleotide sequences and sequences containing identical sites of nucleotide substitutions. Compared to serovar L2, four types of patterns were obtained: (i) serotypes A and Ba; (ii) B and C (causing endemic trachoma); (iii) D through K (causing sexually transmitted oculo-genital infections); (iv) L1 through L3 (the causative agents of lymphogranuloma venereum). A total of 58 isolated of C. trachomatis of genital or conjunctival origin were tested by this method in comparison to reference strains. Forty-eight isolates (13 of type E, 16 of type F, nine of type G, and ten of type K) yielded the same melting profile as the corresponding type strain, independent of whether they were isolated from genital or ocular infections. However, ten B serotype strains of genital origin behaved in TGGE like a typical genital strain and not a trachoma strain. Thus, although gseA was found to be highly conserved among C. trachomatis, the obtained TGGE profiles of the tested strains tended to correlate with their specific site of infection.

Amino Acid Sequence↗
PubMed1995

The structures of oligosaccharide bisphosphates isolated from the lipopolysaccharide of a recombinant Escherichia coli strain expressing the gene gseA [3-deoxy-D-manno-octulopyranosonic acid (Kdo) transferase] of Chlamydia psittaci 6BC.

The lipopolysaccharide from the recombinant strain Escherichia coli F515-140 containing the cloned gene gseA [3-deoxy-D-manno-octulopyranosonic acid (Kdo) transferase] from Chlamydia psittaci 6BC was isolated and sequentially de-O-acylated and de-N-acylated. The products were separated by high-performance anion-exchange chromatography into three fractions, two of which contained a single compound. Their structures were elucidated by high-field NMR spectroscopy as alpha-Kdo-(2-->4)-alpha-Kdo-(2-->6)-beta-D-GlcN-(1-->6)-alpha-D-GlcN 1,4'-P2 (compound 1) (tetrasaccharide bisphosphate) [Holst, O., Broer, W., Thomas-Oates, J. E., Mamat, U. & Brade, H. (1993) Eur. J. Biochem. 214, 703-710] and alpha-Kdo-(2-->4)-[alpha-Kdo-(2-->8)-]-alpha-Kdo-(2-->4)-alpha-Kdo- (2-->6)-beta-D-GlcN-(1-->6)-alpha-D-GlcN 1,4'-P2 (compound 4) (hexasaccharide bisphosphate). The third fraction comprised two pentasaccharide bisphosphates, which could be separated by affinity chromatography using an immobilized monoclonal antibody specific for the trisaccharide alpha-Kdo-(2-->8)-alpha-Kdo-(2-->4)-alpha-Kdo. The bound fraction was identified as alpha-Kdo-(2-->8)-alpha-Kdo-(2-->4)-alpha-Kdo-(2-->6)-beta-D- GlcN-(1-->6)-alpha-D-GlcN 1,4'-P2 (compound 2) [Holst, O., Broer, W., Thomas-Oates, J. E., Mamat, U. & Brade, H. (1993) Eur. J. Biochem. 214, 703-710], whereas the unbound fraction was identified as alpha-Kdo-(2-->4)-alpha-Kdo-(2-->4)-alpha-Kdo-(2-->6)-beta-D-GlcN-(1-->6 )- alpha-D-GlcN 1,4'-P2 (compound 3). This novel Kdo tetrasaccharide extends our knowledge on multifunctional Kdo transferases.

Carbohydrate Sequence↗
PubMed2005

PAGE: parametric analysis of gene set enrichment.

BACKGROUND: Gene set enrichment analysis (GSEA) is a microarray data analysis method that uses predefined gene sets and ranks of genes to identify significant biological changes in microarray data sets. GSEA is especially useful when gene expression changes in a given microarray data set is minimal or moderate. RESULTS: We developed a modified gene set enrichment analysis method based on a parametric statistical analysis model. Compared with GSEA, the parametric analysis of gene set enrichment (PAGE) detected a larger number of significantly altered gene sets and their p-values were lower than the corresponding p-values calculated by GSEA. Because PAGE uses normal distribution for statistical inference, it requires less computation than GSEA, which needs repeated computation of the permutated data set. PAGE was able to detect significantly changed gene sets from microarray data irrespective of different Affymetrix probe level analysis methods or different microarray platforms. Comparison of two aged muscle microarray data sets at gene set level using PAGE revealed common biological themes better than comparison at individual gene level. CONCLUSION: PAGE was statistically more sensitive and required much less computational effort than GSEA, it could identify significantly changed biological themes from microarray data irrespective of analysis methods or microarray platforms, and it was useful in comparison of multiple microarray data sets. We offer PAGE as a useful microarray analysis method.

Computational Biology↗
PubMed2024

Assessment of Gene Set Enrichment Analysis using curated RNA-seq-based benchmarks.

Pathway enrichment analysis is a ubiquitous computational biology method to interpret a list of genes (typically derived from the association of large-scale omics data with phenotypes of interest) in terms of higher-level, predefined gene sets that share biological function, chromosomal location, or other common features. Among many tools developed so far, Gene Set Enrichment Analysis (GSEA) stands out as one of the pioneering and most widely used methods. Although originally developed for microarray data, GSEA is nowadays extensively utilized for RNA-seq data analysis. Here, we quantitatively assessed the performance of a variety of GSEA modalities and provide guidance in the practical use of GSEA in RNA-seq experiments. We leveraged harmonized RNA-seq datasets available from The Cancer Genome Atlas (TCGA) in combination with large, curated pathway collections from the Molecular Signatures Database to obtain cancer-type-specific target pathway lists across multiple cancer types. We carried out a detailed analysis of GSEA performance using both gene-set and phenotype permutations combined with four different choices for the Kolmogorov-Smirnov enrichment statistic. Based on our benchmarks, we conclude that the classic/unweighted gene-set permutation approach offered comparable or better sensitivity-vs-specificity tradeoffs across cancer types compared with other, more complex and computationally intensive permutation methods. Finally, we analyzed other large cohorts for thyroid cancer and hepatocellular carcinoma. We utilized a new consensus metric, the Enrichment Evidence Score (EES), which showed a remarkable agreement between pathways identified in TCGA and those from other sources, despite differences in cancer etiology. This finding suggests an EES-based strategy to identify a core set of pathways that may be complemented by an expanded set of pathways for downstream exploratory analysis. This work fills the existing gap in current guidelines and benchmarks for the use of GSEA with RNA-seq data and provides a framework to enable detailed benchmarking of other RNA-seq-based pathway analysis tools.

Humans↗
PubMed2005

Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.

Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.

Cell Line, Tumor↗
PubMed2006

Extensions to gene set enrichment.

MOTIVATION: Gene Set Enrichment Analysis (GSEA) has been developed recently to capture changes in the expression of pre-defined sets of genes. We propose number of extensions to GSEA, including the use of different statistics to describe the association between genes and phenotypes of interest. We make use of dimension reduction procedures, such as principle component analysis, to identify gene sets with correlated expression. We also address issues that arise when gene sets overlap. RESULTS: Our proposals extend the range of applicability of GSEA and allow for adjustments based on other covariates. We have provided a well-defined procedure to address interpretation issues that can raise when gene sets have substantial overlap. We have shown how standard dimension reduction methods, such as PCA, can be used to help further interpret GSEA. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Algorithms↗
PubMed1993

The genus-specific lipopolysaccharide epitope of Chlamydia is assembled in C. psittaci and C. trachomatis by glycosyltransferases of low homology.

Chlamydiae possess a genus-specific epitope that is located on the lipopolysaccharide (LPS) and is composed of a 3-deoxy-D-manno-octulosonic acid (Kdo) trisaccharide of the sequence alpha Kdo-(2-->8)--alpha Kdo-(2-->4)-alpha Kdo. In Chlamydia trachomatis, this trisaccharide is biosynthetically generated through the action of a multi-functional Kdo-transferase encoded by the gene gseA. gseA of Chlamydia psittaci 6BC was cloned and expressed in a rough mutant (Re chemotype) of Escherichia coli (strain F515) that contains an LPS with only two alpha 2-->4-linked Kdo residues. Recombinant strains were able to add the immunodominant Kdo residue in alpha 2-->8-linkage to the parental LPS, as determined by SDS-PAGE and Western blot analysis using a monoclonal antibody against the genus-specific epitope. The DNA sequence of gseA was determined and aligned to that published recently for C. trachomatis serovar L2. Most surprisingly, the two deduced amino acid sequences shared only an overall homology of 67%. Thus, gseA exhibits species specificity at the DNA level, whereas its gene product results in the synthesis of a carbohydrate antigen with genus specificity.

Amino Acid Sequence↗
PubMed1992

A novel 3-deoxy-D-manno-octulosonic acid transferase from Chlamydia trachomatis required for expression of the genus-specific epitope.

DNA cloned from Chlamydia trachomatis is able to direct the formation of the genus-specific lipopolysaccharide epitope of chlamydiae in enteric Gram-negative bacteria. We now demonstrate that a single C. trachomatis gene (gseA) is sufficient to impart this trait to Escherichia coli. The deduced amino acid sequence of gseA shows 23% identity (66% similarity) to kdtA, an E. coli gene that codes for a bifunctional enzyme catalyzing the addition of two 3-deoxy-D-manno-octulosonic acid (Kdo) residues to lipid A precursors (Clementz, T., and Raetz, C. R. H. (1991) J. Biol. Chem. 266, 9687-9696). Extracts of E. coli expressing gseA transfer at least one additional Kdo unit from CMP-Kdo to precursors already bearing the two Kdo residues attached by the kdtA gene product. Introduction of gseA into an E. coli mutant with a thermolabile kdtA gene product endows cell extracts with the ability to transfer not only the third but also the first two Kdos to lipid A precursors, demonstrating that the C. trachomatis enzyme is at least trifunctional. Given the similarities of these two Kdo transferases and the essentiality of Kdo in Gram-negative bacteria, lipopolysaccharide biosynthesis may be a target for development of novel drugs effective against chlamydiae.

Amino Acid Sequence↗
PubMed2002

Characterization and molecular cloning of a glutamyl endopeptidase from Staphylococcus epidermidis.

A novel extracellular endopeptidase, designated GluSE, was purified from Staphylococcus epidermidis ATCC 14990 cultured by the dialysis membrane technique, and the structural gene (gseA) was cloned. GluSE was a 27kDa, glutamic acid-specific protease, and the optimal pH was 8.0. The proteolytic activity was specifically inhibited with diisopropyl fluorophosphate, indicating that it is a serine protease. The gseA encoded a single polypeptide of 282 amino acids with a deduced molecular weight of 30,809, in which the first 19 N-terminal amino acids completely matched the deduced sequence starting at Val-67, suggesting that GluSE is synthesized with a propeptide. The amino acid sequence of GluSE exhibited 50.5% identity to Staphylococcus aureus V8-protease (GluV8). Although GluSE lacks a C-terminal 12 repeats of the PBN/PBZ tripeptide of GluV8, a catalytic triad of His-117, Asp-159 and Ser-235 was conserved in GluSE. Southern hybridization analysis revealed that gseA exists as a single copy on the chromosomal DNA. The finding that production of GluSE was obviously observed in the adherent culture conditions of the dialysis membrane technique, but not in the planktonic culture conditions, strongly suggests that GluSE could be involved in an important etiologic process in S.epidermidis infection leading to multiple tissue damages.

Amino Acid Sequence↗
PubMed1995

Inhibition of lipopolysaccharide biosynthesis and cell growth following inactivation of the kdtA gene in Escherichia coli.

The enzyme 3-deoxy-D-manno-octulosonic acid (Kdo) transferase is encoded by the kdtA gene in Escherichia coli. The enzyme is a single polypeptide that catalyzes the transfer of two Kdo residues to a tetraacyldisaccharide-1,4'-bisphosphate precursor of lipid A, designated lipid IVA (Belunis, C.J., and Raetz, C.R.H. (1992) J. Biol. Chem. 267, 9988-9997). To determine if Kdo transfer to lipid IVA is required for growth, we constructed a strain of E. coli with a chromosomal kdtA::kan insertion mutation. In mutants carrying the kdtA::kan allele on the chromosome, cell growth and Kdo transferase activity were dependent upon a copy of the intact kdtA gene on a plasmid. When the kdtA-bearing plasmid was itself temperature sensitive for replication, the growth of these strains was inhibited after several hours at 44 degrees C, and Kdo transferase activity in extracts became undetectable. Concomitantly, the cells accumulated massive amounts of lipid IVA, the precursor of (Kdo)2-lipid IVA. The kdtA::kan mutation could also be complemented by hybrid plasmids bearing the gseA gene of Chlamydia trachomatis. gseA specifies a distinct Kdo transferase that adds three Kdo moieties to lipid IVA. Lipopolysaccharide from E. coli kdtA::kan constructs complemented by gseA reacts strongly with antibodies directed against the genus-specific epitope of Chlamydia, whereas lipopolysaccharide from parental E. coli K-12 does not. Our studies prove that Kdo attachment during lipid A biosynthesis is essential for cell growth and accounts for the conditional lethality associated with mutations in Kdo biosynthesis.

Carbohydrate Conformation↗
PubMed2024

Polycystic ovarian syndrome (PCOS) and recurrent spontaneous abortion (RSA) are associated with the PI3K-AKT pathway activation.

AIMS: We aimed to elucidate the mechanism leading to polycystic ovarian syndrome (PCOS) and recurrent spontaneous abortion (RSA). BACKGROUND: PCOS is an endocrine disorder. Patients with RSA also have a high incidence rate of PCOS, implying that PCOS and RSA may share the same pathological mechanism. OBJECTIVE: The single-cell RNA-seq datasets of PCOS (GSE168404 and GSE193123) and RSA GSE113790 and GSE178535) were downloaded from the Gene Expression Omnibus (GEO) database. METHODS: Datasets of PSCO and RSA patients were retrieved from the Gene Expression Omnibus (GEO) database. The "WGCNA" package was used to determine the module eigengenes associated with the PCOS and RSA phenotypes and the gene functions were analyzed using the "DAVID" database. The GSEA analysis was performed in "clusterProfiler" package, and key genes in the activated pathways were identified using the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Real-time quantitative PCR (RT-qPCR) was conducted to determine the mRNA level. Cell viability and apoptosis were measured by cell counting kit-8 (CCK-8) and flow cytometry, respectively. RESULTS: The modules related to PCOS and RSA were sectioned by weighted gene co-expression network analysis (WGCNA) and positive correlation modules of PCOS and RSA were all enriched in angiogenesis and Wnt pathways. The GSEA further revealed that these biological processes of angiogenesis, Wnt and regulation of cell cycle were significantly positively correlated with the PCOS and RSA phenotypes. The intersection of the positive correlation modules of PCOS and RSA contained 80 key genes, which were mainly enriched in kinase-related signal pathways and were significant high-expressed in the disease samples. Subsequently, visualization of these genes including PDGFC, GHR, PRLR and ITGA3 showed that these genes were associated with the PI3K-AKT signal pathway. Moreover, the experimental results showed that PRLR had a higher expression in KGN cells, and that knocking PRLR down suppressed cell viability and promoted apoptosis of KGN cells. CONCLUSION: This study revealed the common pathological mechanisms between PCOS and RSA and explored the role of the PI3K-AKT signaling pathway in the two diseases, providing a new direction for the clinical treatment of PCOS and RSA.

Humans↗
PubMed2023

MYH16 upregulation is associated with lung adenocarcinoma aggressiveness and immune infiltration.

Myosin heavy chain 16 (MYH16) may significantly affect cell cycle progression. Nevertheless, there is a lack of evidence about the clinical relevance of MYH16 upregulation in pan cancers, including lung adenocarcinoma (LUAD). MYH16 expression patterns were evaluated in various bioinformatics databases using The Cancer Genome Atlas data set. Clinical and pathological factor data were employed to risk-stratify patients. The Kaplan-Meier plotter approach was used to estimate survival rates. Tumor immune infiltration was explored via the TIMER tool, and gene set enrichment analysis (GSEA) was used to identify the pathways involved in MYH16 upregulation. The results showed that MYH16 was abnormally upregulated in pan cancers, including LUAD. MYH16 expression induction in LUAD was found to be related to the tumor stage. Furthermore, MYH16 upregulation was correlated with LUAD development and worse overall survival, particularly in women. Notably, MYH16 overexpression in LUAD tissues corresponded to the amount of immune infiltration in the tumor. Additionally, univariate Cox hazard regression analysis revealed that MYH16 may be an independent prognostic indicator for LUAD. Furthermore, a nomogram was constructed according to MYH16 expression and clinical characteristics. BMP6 expression deficiency may be a key factor contributing to MYH16 upregulation in LUAD. Finally, GSEA demonstrated that MYH16 might mediate meiosis and gene silencing through RNA signaling pathways. This study, for the first time, showed that MYH16 upregulation in LUAD is associated with various risk factors, increased cancer aggressiveness, enhanced infiltration of tumor immune cells, and reduced survival rates.

Female↗
PubMed2026

Exploring shared biomarkers and their mechanisms in thyroid cancer and systemic lupus erythematosus via bioinformatics analysis.

BACKGROUND: Systemic lupus erythematosus (SLE), an autoimmune disorder, is linked to a heightened risk of multiple malignancies, including thyroid cancer. Thyroid cancer is the most prevalent malignancy of the endocrine system, and its autoimmune-related pathological features render it an optimal subject for investigating the mechanisms of their comorbidity. The molecular mechanisms underlying this comorbidity are still ambiguous. The accurate diagnosis and treatment of thyroid cancer urgently necessitate innovative molecular targets that extend beyond conventional pathological characteristics. This study seeks to employ integrated bioinformatics approaches to elucidate potential shared molecular mechanisms and immunological features between thyroid cancer and systemic lupus erythematosus (SLE), aiming to enhance understanding of their comorbidity and identify novel intervention targets. METHODS: This study initially acquired gene expression data for TC and SLE from the GEO database and subsequently screened and identified differentially expressed genes (DEGs) shared by both diseases. Subsequently, we conducted Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome functional enrichment analyses on these 46 shared differentially expressed genes (DEGs) and further assessed the activation status of pertinent pathways using Gene Set Enrichment Analysis (GSEA). Subsequently, we employed CIBERSORTx to examine immune infiltration patterns and developed protein-protein interaction networks utilising the STRING database. We identified hub genes utilising the MCODE and cytoHubba plugins and visualised the findings with Cytoscape software. We additionally assessed the diagnostic efficacy of these core hub genes in an independent dataset utilising ROC curves and investigated their prognostic relevance in thyroid cancer through Kaplan-Meier survival analysis and multivariate Cox proportional hazards regression. Ultimately, we employed the Network Analyst platform to forecast transcription factor-gene and miRNA-gene regulatory networks and identified potential targeted therapeutic compounds utilising the DSigDB database. RESULTS: This study identified 46 differentially expressed genes (DEGs) commonly linked to thyroid cancer and systemic lupus erythematosus (SLE), which were significantly enriched in signalling pathways associated with immune-inflammatory activation, type I interferon responses, and complement pathway activation. Moreover, GSEA findings validated that immune-inflammatory and autoimmune-related pathways are markedly activated in both conditions. Twelve hub genes were discerned through protein-protein interaction networks. Analysis of immune infiltration indicated that thyroid cancer and systemic lupus erythematosus exhibit a shared characteristic of innate immune dysregulation, marked by the infiltration of myeloid cells (neutrophils, M0/M2 macrophages). Receiver operating characteristic (ROC) curve analysis identified six significant core hub genes with substantial diagnostic value: C1QB, LCN2, C1QC, LTF, VSIG4, and C3AR1. Univariate survival analysis indicated that elevated expression of C1QC and C3AR1 significantly enhances overall survival in thyroid cancer patients; however, multivariate COX regression analysis revealed that their independent prognostic significance necessitates further validation. This study predicted the interaction networks of transcription factors and miRNAs regulating key genes, with LCN2 demonstrating the highest connectivity to miRNAs, and identified candidate therapeutic compounds linked to it. CONCLUSION: This study employed bioinformatics analysis to identify critical shared hub genes and molecular pathways connecting thyroid cancer and systemic lupus erythematosus, offering novel insights into their shared pathogenesis and the advancement of targeted biomarkers and therapeutic strategies.

Bioinformatics analysis↗
PubMed2026

Comparative transcriptomic analysis of the gills and hepatopancreas of freshwater-cultured Litopenaeus vannamei under chronic nitrite stress.

To investigate the differences in molecular responses between the gills and hepatopancreas of freshwater-cultured Litopenaeus vannamei under chronic nitrite stress, a 30-day chronic stress experiment was conducted with a control group and a stress group. Transcriptomic analysis of the gills and hepatopancreas was performed using Illumina sequencing; differentially expressed genes (DEGs) were identified, and GO, KEGG, GSEA, PPI, and RT-qPCR validation were carried out. The results showed that 196 DEGs (161 up-regulated and 35 down-regulated) were identified in the gills, and 287 DEGs (199 up-regulated and 88 down-regulated) in the hepatopancreas, with only 18 DEGs shared between the two tissues. DEGs in the gills were enriched in oxidoreductase activity, glycerophospholipid metabolism, and tyrosine metabolism; DEGs in the hepatopancreas were enriched in lipid transporter activity, phagosome, ECM-receptor interaction, and riboflavin metabolism. GSEA revealed significant suppression of the mTOR pathway in the gills and the Polycomb complex pathway in the hepatopancreas. PPI network analysis identified hub genes P5CS and eEF2 in the gills, and PER, TUBB1, SHMT, and TUBB4B in the hepatopancreas. RT-qPCR validation was consistent with the RNA-seq results (R2 = 0.764). This study indicates that, under chronic nitrite stress, the gill response is centered on redox regulation and inhibition of growth metabolism, whereas the hepatopancreas response primarily involves lipid transport, cytoskeletal remodeling, and phagosome activation. The two tissues synergistically adapt through fundamental biosynthetic and motor protein pathways. This research provides molecular evidence for deciphering the nitrite tolerance mechanisms in freshwater-cultured shrimp.

Animals↗
PubMed2026

Differential Proteomic Profiling of Responders and Non-responders to Direct-Acting Antivirals Treatment in Chronic Hepatitis C Virus Infection.

Hepatitis C Virus (HCV), particularly genotype 3 (GT-3), is highly prevalent in India and is associated with faster progression to cirrhosis, hepatocellular carcinoma, and higher treatment failure rates. Although Direct-Acting Antivirals (DAAs) have revolutionized HCV therapy, 5-10% of patients fail to achieve sustained virological response (SVR). This proteomic study aimed to identify changes in the proteomic profile before and after treatment of both responders and non-responders to HCV treatment. Paired plasma samples from HCV GT-3 infected patients were collected before and 12 weeks after initiating DAAs treatment, along with healthy controls. Quantitative proteomic analysis was performed on the paired samples. Differentially expressed proteins (DEPs) were identified and subjected to functional analysis including gene set enrichment analysis (GSEA) and protein-protein interaction (PPI) network analysis. GSEA revealed enrichment in extracellular matrix organization and innate immune pathways. Expression patterns of candidate proteins selected based on fold change and false discovery rate (FDR) criteria were further evaluated in an independent cohort. Western blot confirmed key expression trends of candidate proteins. Proteins linked to extracellular matrix remodeling and angiogenesis showed differential expression patterns. Successful validation of these candidate proteins in large independent cohorts holds potential to predict therapeutic outcomes.

Humans↗