METHODS: Thirty-three cell death-associated genes were selected from a literature review. The "DESeq2" R package was used to identify differentially expressed cell death-associated genes between normal prostate tissue (GTEx) and prostate cancer tissue (TCGA) samples. Biological functional enrichment analysis of differentially expressed cell death genes was performed using R statistical software packages, such as "clusterProfiler," "org.Hs.eg.db," "enrichplot," "ggplot2," and "GOplot." Univariate Cox and LASSO Cox regression analyses were conducted to identify prognostic genes associated with the immune microenvironment using the "survival" package. Finally, a predictive model was established based on Gleason score, T stage, and cell death-associated genes.odel was established based on Gleason score, T stage, and cell death-associated genes.
RESULTS: Seventeen differentially expressed genes related to pyroptosis were screened out. Based on these differentially expressed genes, biological function enrichment analysis showed that they were related to pyroptosis of prostate cells. Based on univariate Cox and (LASSO) Cox regression analysis, four pyroptosis-related genes (CASP3, PLCG1, GSDMB, GPX4) were determined to be related to the prognosis of prostate cancer, and the immune correlation analysis of the four pyroptosis-related genes was performed. The expression of CASP3, PLCG1 and GSDMB was positively correlated with the proportion of immune cells, and the expression of GPX4 was negatively correlated with the proportion of immune cells. A predictive nomogram was established by combining Gleason score, T and pyroptosis genes. The nomogram was accompanied by a calibration curve and used to predict 1 -, 2 -, and 5-year survival in PAAD patients.
CONCLUSION: Cell death-associated genes (CASP3, PLCG1, GSDMB, GPX4) play crucial roles in modulating the immune microenvironment and can be used to predict the prognosis of prostate cancer.
RESULTS: The study described the transcriptomes of salivary glands from three swiftlet species (28 samples) generated by RNASeq. A total of 14,835 annotated genes and 428 unmapped genes were cataloged. The current study investigated the genes and pathways that are associated with the development of salivary gland and EBN composition. Differential expression and pathway enrichment analysis indicated that the expression of CREB3L2 and several signaling pathways involved in salivary gland development, namely, the EGFR, BMP, and MAPK signaling pathways, were up-regulated in swiftlets producing white EBN (Aerodramus fuciphagus) and black EBN (Aerodramus maximus) compared with non-EBN-producing swiftlets (Apus affinis). Furthermore, MGAT, an essential gene for the biosynthesis of N-acetylneuraminic acid (sialic acid), was highly expressed in both white- and black-nest swiftlets compared to non-EBN-producing swiftlets. Interspecies comparison between Aerodramus fuciphagus and Aerodramus maximus indicated that the genes involved in N-acetylneuraminic and fatty acid synthesis were up-regulated in Aerodramus fuciphagus, while alanine and aspartate synthesis pathways were up-regulated in Aerodramus maximus. Furthermore, gender-based analysis revealed that N-glycan trimming pathway was significantly up-regulated in male Aerodramus fuciphagus from its natural habitat (cave) compared to their female counterpart.
CONCLUSIONS: Transcriptomic analysis of salivary glands of different swiftlet species reveal differential expressions of candidate genes that are involved in salivary gland development and in the biosynthesis of various bioactive compounds found in EBN.
RESULTS: Planktonic S. Typhi cells were cultured using standard nutrient broth whereas biofilm cells were cultured in a stressful environment using high shearing-force and bile to mimic the gallbladder. Sequencing libraries were prepared from S. Typhi planktonic cells and mature biofilm cells using the Illumina HiSeq 2500 platform, and the transcriptome data obtained were processed using Cufflinks bioinformatics suite of programs to investigate differential gene expression between the two phenotypes. A total of 35 up-regulated and 29 down-regulated genes were identified. The identities of the differentially expressed genes were confirmed using NCBI BLAST and their functions were analyzed. The results showed that the genes associated with metabolic processes and biofilm regulations were down-regulated while those associated with the membrane matrix and antibiotic resistance were highly up-regulated.
CONCLUSIONS: It is proposed that the biofilm phenotype of S. Typhi allows the bacteria to increase production of the membrane matrix in order to serve as a physical shield and to adhere to surfaces, and enter an energy conservation state in response to the stressful environment. Conversely, the planktonic phenotype allows the bacteria to produce flagella and increase metabolic activity to enable the bacteria to migrate and form new colonies of infection. This data provide a basis for further studies to uncover the mechanism of biofilm formation in S. Typhi and to discover novel genes or pathways associated with the development of the typhoid carrier state.
MATERIALS AND METHODS: The different primer sets were developed using bioinformatics software DNASTAR. The E. coli cells were used for recombinant protein expression.
RESULTS: The NiV 'G' region primers were designed and amplified for 1 kb fragment and cloned. The NiV 'G' fragments were sub-cloned in pET-28(+) B and pGEX-5x-1. Recombinant protein thus obtained in soluble form in both the cases was essayed using western blot. The result showed the protein expression yield was more in pET-28(+) B with low stability and vice versa for pGEX-5x-1.
CONCLUSION: The antibodies raised from the protein can be used as diagnostic reagent for detection of NiV. Thus, a new diagnostic technique can be industrialized.