mRNA levels of tricarboxylic acid cycle genes in Streptomyces coelicolor M145 cultured on glucose.

BACKGROUND: Streptomyces strains degrade many complex organic compounds and produce secondary metabolites. In aerobic organisms such as Streptomyces species, the tricarboxylic acid (TCA) cycle represents an indispensable central carbon metabolic pathway for energy generation and metabolic intermediary replenishment. Although various precursors for antibiotic biosynthesis are derived from this cycle, relatively few studies have focused on determining how a single carbon source can impact this metabolic pathway at different growth phases. In this study, we identified chromosomal genes involved in the TCA cycle in Streptomyces coelicolor and determined their mRNA levels. METHODS AND RESULTS: We searched the genes involved in the TCA cycle in S. coelicolor through bioinformatic analysis. Growth, glucose concentration quantification and RNA isolation were made from cultures of S. coelicolor grown on minimal medium with glucose along 72 h. mRNA levels of all identified genes were obtained by RT-qPCR. Five enzymes encoded by a single gene each were found, while for the rest at least two genes were found. The results showed that all the genes corresponding to the TCA enzymes were transcribed at very different levels and some of them displayed growth-phase dependent expression. CONCLUSION: All TCA cycle-associated genes, including paralog genes, were differentially transcribed in S. coelicolor grown in minimal medium with glucose as carbon source. Some of them, such as succinyl-CoA synthetase and succinate dehydrogenase, have low mRNA levels, which could limit the carbon flux through the TCA cycle. Our findings suggest that the genetic expansion of TCA cycle genes could confer to S. coelicolor the ability to adapt to diverse nutritional conditions and metabolic changes through different paralog genes expression.

miRNA and mRNA Expression Profiles Associated with Lymph Node Metastasis and Prognosis in Penile Carcinoma.

Penile cancer (PeC) is a rare disease, and no prognostic biomarkers have been adopted in clinical practice yet. The objective of the present study was to identify differentially expressed miRNAs (DEmiRs) and genes (DEGs) as potential biomarkers for lymph node metastasis and other prognostic factors in PeC. Tumor samples were prospectively obtained from 24 patients with squamous cell carcinoma of the penis. miRNA microarray analysis was performed comparing tumors from patients with inguinal lymph node metastatic and localized disease, and the results were validated by qRT-PCR. Eighty-three gene expression levels were also compared between groups through qRT-PCR. Moreover, DEmiRs and DEGs expression levels were correlated with clinicopathological variables, cancer-specific (CSS), and overall survival (OS). TAC software, TM4 MeV 4.9 software, SPSS v.25.0, and R software v.4.0.2 were used for statistical analyses. We identified 21 DEmiRs in microarray analysis, and seven were selected for validation. miR-744-5p and miR-421 were overexpressed in tissue samples of metastatic patients, and high expression of miR-421 was also associated with lower OS. We found seven DEGs (CCND1, EGFR, ENTPD5, HOXA10, IGF1R, MYC, and SNAI2) related to metastatic disease. A significant association was found between increased MMP1 expression and tumor size, grade, pathological T stage, and perineural invasion. Other genes were also associated with clinicopathological variables, CSS and OS. Finally, we found changes in mRNA-miRNA regulation that contribute to understanding the mechanisms involved in tumor progression. Therefore, we identified miRNA and mRNA expression profiles as potential biomarkers associated with lymph node metastasis and prognosis in PeC, in addition to disruption in mRNA-miRNA regulation during disease progression.

Identification of best housekeeping genes for the normalization of RT-qPCR in human cell lines.

The identification of the best reference gene is a critical step to evaluate the relative change in mRNA expression of a target gene by RT-qPCR. In this work, we evaluated nineteen genes of different functional classes using Real Time Human Reference Gene Panel (Roche Applied Sciences), to identify the internal housekeeping genes (HKGs) most suitable for gene expression normalization data in human cell lines. Normal cell lines CCD-19LU (lung fibroblast), HEK-293 (epithelial cell of embryonic kidney), WI-26 VA4 (lung fibroblast), and human cancer cells, BT-549 (breast cancer), Hs 578T (breast cancer), MACL-1 (breast cancer), HeLa (cervical carcinoma), U-87 MG (glioblastoma/astrocytoma), RKO-AS45-1 (colorectal carcinoma), and TOV-21G (ovarian adenocarcinoma) were cultivated according to manufacturer's protocol. Twelve candidate reference genes were commonly expressed in five cell lines (CCD-19Lu, HEK-293, RKO-AS45-1, TOV-21G, and U-87 MG). To verify the expression stability, we used the RefFinder web tool, which integrates data from the computational programs Normfinder, BestKeeper, geNorm, and the comparative Delta-Ct method. The ACTB was the most stable reference gene to the CCD-19Lu and HEK-293 cells. The best combination of HKGs for the RKO-AS45-1 and TOV-21G cell lines were B2M/GAPDH and PBGD/B2M, respectively. For the U-87 MG cells, GAPDH and IPO8 were the most suitable HKGs. Thus, our findings showed that it is crucial to use the right HKGs to precise normalize gene expression levels in cancer studies, once a suitable HKG for one cell type cannot be to the other.