ABSTRACT
Colorectal cancer (CRC) is a heterogeneous disease that requires new diagnostic and prognostic markers. Integrated bioinformatics approach to identify novel therapeutic targets associated with CRC. Using GEO2R identified DEGs in CRC, and Funrich software facilitated the visualization of DEGs through Venn diagrams. From a total of 114 enhanced DEGs, potential hub genes were further filtered based on their nodal strength and edges using STRING database. To gain insights into the functional roles of these hub genes, gene ontology and pathway enrichment were conducted thorough g: profiler web server. Subsequently, overall survival plots from GEPIA and oncogenic predictive functions like mRNA expressions for stages and nodal metastasis were employed to identify hub genes in CRC patient samples. Additionally, the cBioPortal and HPA databases also revealed genetic alterations and expression levels in these hub genes in CRC patients, further supporting their involvement in colorectal cancer. Gene expression by RT-PCR shows upregulation of hub genes in HT-29 cells. Finally, our integrated bioinformatic analysis revealed that ABCE1, AURKA, HSPD1, PHKA1, CDK4, and YWHAE as hub genes with potential oncogenic roles in CRC. These genes hold promise as diagnostic and prognostic markers for colorectal tumorigenesis, providing insights into targeted therapies for improved patient outcomes.
ABSTRACT
Staphylococcus species are a major pathogen responsible for nosocomial infections and foodborne illnesses. We applied a laser-based BARDOT (bacterial rapid detection using optical scattering technology) for rapid colony screening and detection of Staphylococcus on an agar plate and differentiate these from non-Staphylococcus spp. Among the six growth media tested, phenol red mannitol agar (PRMA) was found most suitable for building the Staphylococcus species scatter image libraries. Scatter image library for Staphylococcus species gave a high positive predictive value (PPV 87.5-100%) when tested against known laboratory strains of Staphylococcus spp., while the PPV against non-Staphylococcus spp. was 0-38%. A total of nine naturally contaminated bovine raw milk and ready-to-eat chicken salad samples were tested, and BARDOT detected Staphylococcus including Staphylococcus aureus with 80-100% PPV. Forty-five BARDOT-identified bacterial isolates from naturally contaminated foods were further confirmed by tuf and nuc gene-specific PCR and 16S rRNA gene sequence. This label-free, non-invasive on-plate colony screening technology can be adopted by the food industries, biotechnology companies, and public health laboratories for Staphylococcus species detection including S. aureus from various samples for food safety and public health management. Graphical abstract.
