Current Biotechnology - Current Issue

Foot-and-mouth disease (FMD) is a serious viral disease in cattle, causing an estimated economic loss of 6.5-21 billion USD. It is usually controlled through vaccination. The gene-gene association mechanisms underlying the response to FMD vaccination are currently poorly understood and remain significant interest to researchers. Further, little amount of bioinformatic work has been carried out to understand FMD vaccination response in cattle at the molecular level using publicly available gene expression data. Therefore, this study aims to identify key gene markers, gene networks, and hub genes associated with FMD vaccination response in cattle using gene selection and network biology methods.

In this study, computational tools, including gene selection and network biology techniques, were used to understand the FMD vaccination response in cattle using publicly available large gene expression data. Initially, five different gene selection methods were employed to select informative genes from the high-dimensional gene expression data. Then, gene co-expression network analysis was carried out to construct gene-gene association networks and identify various gene modules. Next, hub genes, housekeeping hub genes, and unique hub genes were identified in the constructed networks through our earlier developed DHGA approach.

We identified 666 unique genes commonly selected by the gene selection methods that were informative to the vaccination condition. Two gene co-expression networks under vaccination and non-vaccination conditions were constructed, which revealed the association among the selected genes. Further, the selected genes were grouped into 10 and 13 gene modules under the vaccinated and non-vaccinated conditions, respectively. In the gene networks, we identified 193 and 94 genes as hubs for vaccinated and non-vaccinated conditions, respectively. The detected hub genes were classified into housekeeping hubs (49), unique hubs to vaccinated (144), and unique hubs to non-vaccinated conditions (45) based on their connection strengths. The enrichment analysis of gene modules, genes, and various hub genes indicated that functions, including protein binding, catalytic activity, transcription regulation, and transporter activity, were predominantly activated in response to vaccination.

These identified genes and their key roles can act as potential biomarkers for maximizing FMD vaccination response in cattle. The findings of this study may provide new inputs and hypotheses for future immunological studies.

Staphylococcus haemolyticus is an opportunistic human pathogenic bacterium that constitutes the major part of human skin microflora. This bacterium has shown resistance to most antibiotics. Moreover, it spreads widely in hospitals and causes various infections in human beings. This bacterium has been reported in infected humans, animals, and some insects; however, this is the first report on Staphylococcus haemolyticus being found in scarabaeids in the world. The gut microbiota of white grubs helps in the digestion and assimilation of food, such as cellulose, hemicellulose, and pectin degradation by producing various enzymes.

This study aimed to isolate and identify the cellulose-degrading bacteria from the gut of the most notorious polyphagous white grub,  Brahmina coriacea  and estimated their cellulolytic index for utilization in future studies for decomposing of organic matter and in biofuel production in industries.

In this study, we isolated 11 cellulolytic bacteria from the gut of B. coriacea (Hope) grubs, which were collected from different locations in the north-western Himalayas.

S. haemolyticus was only reported from the grubs of Nauni, Solan region of Himachal Pradesh, India, and identified by using 16S rRNA gene sequencing analysis. S. haemolyticus was able to degrade the cellulose in Carboxy Methyl cellulose (CMC) media.

This bacterium can be used in industries, such as the management of agro-waste, pulp and paper, and biofuel production.

Pancreatic cancer is the sixth leading cause of death with a limited validated biomarker. Finding and validating diagnostic/prognostic markers can be improved by combining both forms of data in a multi-omics approach, which can offer a more comprehensive outcome.

GEO datasets were utilized to identify differentially expressed aquaporins in pancreatic cancer and validated through TCGA-PAAD data. Protein Data Commons (PDC) was used to analyse differentially expressed proteins in PAAD. Functional enrichment analysis and immune cell infiltration analysis were conducted through SRplot and TIMER database, respectively. Survival association was studied using Cox proportional regression and Kaplan-Meier analysis.

A significant downregulation of AQP1, AQP8, AQP11, AQP12A and AQP12B expression and upregulation of AQP5, AQP6 and AQP9 expression were observed in PAAD (p-value = 0.0001). This analysis revealed that overexpression of AQP6 was significantly associated with the poor outcome of the PAAD patients (HR=1.8399, p=0.037). Additionally, we found that alcohol history and low expression of AQP1 and AQP9 were associated with low survival among the PAAD patients and these aquaporins were strongly correlated with immune infiltrates.

Our research underscores the important role of aquaporins, especially AQP6, in pancreatic adenocarcinoma prognosis. The correlation of AQP1 and AQP9 with immune cell infiltration and patient survival indicates their promise as immuno-oncological markers. These results validate the use of aquaporins as diagnostic and prognostic targets in PAAD treatment.

Our results suggested that AQP6 might be a novel prognostic marker in PAAD patients. Additionally, AQP12A and AQP12B may act as distinctive diagnostic markers to detect pancreatic adenocarcinoma.