Actin Cytoskeleton: Profilin Gives Cells an Edge

Nutrient-driven dedifferentiation of enteroendocrine cells promotes adaptive intestinal growth in Drosophila

Post-developmental organ resizing improves organismal fitness under constantly changing nutrient environments. Although stem cell abundance is a fundamental determinant of adaptive resizing, our understanding of its underlying mechanisms remains primarily limited to the regulation of stem cell division. Here, we demonstrate that nutrient fluctuation induces dedifferentiation in the Drosophila adult midgut to drive adaptive intestinal growth. From lineage tracing and single-cell RNA sequencing, we identify a subpopulation of enteroendocrine (EE) cells that convert into functional intestinal stem cells (ISCs) in response to dietary glucose and amino acids by activating the JAK-STAT pathway. Genetic ablation of EE-derived ISCs severely impairs ISC expansion and midgut growth despite the retention of resident ISCs, and in silico modeling further indicates that EE dedifferentiation enables an efficient increase in the midgut cell number while maintaining epithelial cell composition. Our findings identify a physiologically induced dedifferentiation that ensures ISC expansion during adaptive organ growth in concert with nutrient conditions.

Involvement of lncRNAs in cancer cells migration, invasion and metastasis: cytoskeleton and ECM crosstalk

Cancer is the main cause of death worldwide and metastasis is a major cause of poor prognosis and cancer-associated mortality. Metastatic conversion of cancer cells is a multiplex process, including EMT through cytoskeleton remodeling and interaction with TME. Tens of thousands of putative lncRNAs have been identified, but the biological functions of most are still to be identified. However, lncRNAs have already emerged as key regulators of gene expression at transcriptional and post-transcriptional level to control gene expression in a spatio-temporal fashion. LncRNA-dependent mechanisms can control cell fates during development and their perturbed expression is associated with the onset and progression of many diseases including cancer. LncRNAs have been involved in each step of cancer cells metastasis through different modes of action. The investigation of lncRNAs different roles in cancer metastasis could possibly lead to the identification of new biomarkers and innovative cancer therapeutic options.

Systematic Identification of the Optimal Housekeeping Genes for Accurate Transcriptomic and Proteomic Profiling of Tissues following Complex Traumatic Injury

Trauma triggers critical molecular and cellular signaling cascades that drive biological outcomes and recovery. Variations in the gene expression of common endogenous reference housekeeping genes (HKGs) used in data normalization differ between tissue types and pathological states. Systematically, we investigated the gene stability of nine HKGs (Actb, B2m, Gapdh, Hprt1, Pgk1, Rplp0, Rplp2, Tbp, and Tfrc) from tissues prone to remote organ dysfunction (lung, liver, kidney, and muscle) following extremity trauma. Computational algorithms (geNorm, Normfinder, ΔCt, BestKeeper, RefFinder) were applied to estimate the expression stability of each HKG or combinations of them, within and between tissues, under both steady-state and systemic inflammatory conditions. Rplp2 was ranked as the most suitable in the healthy and injured lung, kidney, and skeletal muscle, whereas Rplp2 and either Hprt1 or Pgk1 were the most suitable in the healthy and injured liver, respectively. However, the geometric mean of the three most stable genes was deemed the most stable internal reference control. Actb and Tbp were the least stable in normal tissues, whereas Gapdh and Tbp were the least stable across all tissues post-trauma. Ct values correlated poorly with the translation from mRNA to protein. Our results provide a valuable resource for the accurate normalization of gene expression in trauma-related experiments.

The risk of pancreatic adenocarcinoma following SARS-CoV family infection

COVID 19 disease has become a global catastrophe over the past year that has claimed the lives of over two million people around the world. Despite the introduction of vaccines against the disease, there is still a long way to completely eradicate it. There are concerns about the complications following infection with SARS-CoV-2. This research aimed to evaluate the possible correlation between infection with SARS-CoV viruses and cancer in an in-silico study model. To do this, the relevent dataset was selected from GEO database. Identification of differentially expressed genes among defined groups including SARS-CoV, SARS-dORF6, SARS-BatSRBD, and H1N1 were screened where the |Log FC| ≥ 1and p < 0.05 were considered statistically significant. Later, the pathway enrichment analysis and gene ontology (GO) were used by Enrichr and Shiny GO databases. Evaluation with STRING online was applied to predict the functional interactions of proteins, followed by Cytoscape analysis to identify the master genes. Finally, analysis with GEPIA2 server was carried out to reveal the possible correlation between candidate genes and cancer development. The results showed that the main molecular function of up- and down-regulated genes was "double-stranded RNA binding" and actin-binding, respectively. STRING and Cytoscape analysis presented four genes, PTEN, CREB1, CASP3, and SMAD3 as the key genes involved in cancer development. According to TCGA database results, these four genes were up-regulated notably in pancreatic adenocarcinoma. Our findings suggest that pancreatic adenocarcinoma is the most probably malignancy happening after infection with SARS-CoV family.