Identification of potential microRNAs regulating metabolic plasticity and cellular phenotypes in glioblastoma.

MicroRNAs (miRNAs) play important role in regulating cellular metabolism, and are currently being explored in cancer. As metabolic reprogramming in cancer is a major mediator of phenotypic plasticity, understanding miRNA-regulated metabolism will provide opportunities to identify miRNA targets that can regulate oncogenic phenotypes by taking control of cellular metabolism. In the present work, we studied the effect of differentially expressed miRNAs on metabolism, and associated oncogenic phenotypes in glioblastoma (GBM) using patient-derived data. Networks of differentially expressed miRNAs and metabolic genes were created and analyzed to identify important miRNAs that regulate major metabolism in GBM. Graph network-based approaches like network diffusion, backbone extraction, and different centrality measures were used to analyze these networks for identification of potential miRNA targets. Important metabolic processes and cellular phenotypes were annotated to trace the functional responses associated with these miRNA-regulated metabolic genes and associated phenotype networks. miRNA-regulated metabolic gene subnetworks of cellular phenotypes were extracted, and important miRNAs regulating these phenotypes were identified. The most important outcome of the study is the target miRNA combinations predicted for five different oncogenic phenotypes that can be tested experimentally for miRNA-based therapeutic design in GBM. Strategies implemented in the study can be used to generate testable hypotheses in other cancer types as well, and design context-specific miRNA-based therapy for individual patient. Their usability can be further extended to other gene regulatory networks in cancer and other genetic diseases.

Spatio-temporal metabolokinetics and therapeutic effect of CD106+ mesenchymal stem/stromal cells upon mice with acute lung injury.

Longitudinal investigations have revealed the unique attributes of mesenchymal stem/stromal cells (MSCs) in regenerative medicine. However, the spatio-temporal metabolokinetics and efficacy of MSCs with vascular cell adhesion molecule 1 (also known as CD106) expression in phenotypes and therapeutic effect upon acute lung injury (ALI) mice are largely obscure. For the purpose, we took advantage of the "3IL"-based strategy and Lentivirus-mediated green fluorescent protein (GFP) delivery for the generation of the CD106+ subset (denote as CD106+ -MSCs) from umbilical cord-derived MSCs (denote as NT-MSCs). Therewith, the cellular phenotypes of CD106+ -MSCs including immunophenotypes, multilineage differentiation potential towards adipocytes and osteoblasts were confirmed by flow cytometry and qRT-PCR assay. Meanwhile, multifaceted characteristics of transcriptomic features were analyzed by utilizing the RNA-SEQ and bioinformatics. Furthermore, to compare the therapeutic effects and spatio-temporal dynamics of CD106+ -MSCs, we conducted in vivo fluorescent tracer, hematoxylin and eosin staining, blood smear, blood routine and cytokine detection in mice. Herein, we generated CD106+ -MSCs with GFP expression and confirmed the conservative property of phenotypes. Compared to NT-MSCs with minimal CD106 expression, CD106+ -MSCs manifested consistent distribution and metabolokinetics in vivo but with preferable ameliorative effect upon the pathological appearance and proinflammatory cytokine secretion in ALI mice. Collectively, our data indicated the preferable therapeutic effects of CD106+ -MSCs upon ALI mice, which would benefit the further exploration of the CD106+ subset for pulmonary diseases and investigational new drug application purposes.

In vitro study of the effects of DC electric fields on cell activities and gene expression in human choriocarcinoma cells.

Physiological electric fields (EFs), as one of the environmental cues influencing both normal and tumor cells, have profound effects on tumor cell malignancy potential. The cellular responses to EFs by choriocarcinoma cells and their underlying mechanisms are unknown. In this study, the migration/motility, cell cycle progression and proliferation of choriocarcinoma cells in electric field culture showed that choriocarcinoma cells migrated cathodally in an applied EF, and EF stimulation influenced cell cycle progression through G2/M arrest and therefore induced a reduction in cellular proliferation. The transcriptome of choriocarcinoma cells subjected to EF stimulation (150 mV/mm) was analyzed using RNA sequencing (RNA-Seq), and the results were verified by reverse transcription quantitative polymerase chain reaction. A Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that ErbB and HIF-1 signaling pathways that are involved in cell migration/motility, cell cycle progression and proliferation were significantly altered in cells treated with an EF of 150 mV/mm compared with control cells, and in addition, the downstream pathways of these signaling pathways such as AKT and P42/P44 MAPK (ERK1/2) showed primary activation by Western blotting. This study's results suggest that an applied EF is an effective cue in regulating cellular phenotypes of choriocarcinoma cells and that transcriptional analysis contributes to the understanding of the mechanism of EF-guided cell functions.

Schizandrin A inhibits cellular phenotypes of breast cancer cells by repressing miR-155.

AIMS: Schizandrin A (SchA) is a type of lignan with biological properties against oxidation, inflammation, and cancer. Here, we aimed to sustain the bioactive properties of SchA in proliferative and motional phenotypes of MDA-MB-231 cells and their molecular mechanism. METHODS: MDA-MB-231 cells were exposed to SchA. At 24 h after SchA treatment, the viability and proliferation were measured using CCK-8 and BrdU incorporation methods, respectively. Propidium iodide/Annexin V-FITC staining was carried out for detecting apoptotic cells. Migration and invasion were detected by 24-Transwell assay. Proteins expression was evaluated by Western blotting. MDA-MB-231 cells were transfected with microRNA (miR)-155 mimic, and miR-155 was detected by qRT-PCR. RESULTS: SchA weakens the viability of MDA-MB-231 cells in a dose-relative way (0-40 µM). Furthermore, 30 µM SchA significantly suppresses proliferation, enhances apoptosis, and inhibits migration and invasion. SchA strikingly decreases miR-155. Exogenous miR-155 counteracts the inhibitory effects that SchA confers on proliferative and motional activities. Finally, SchA was observed to blunt PI3K/AKT and Wnt/ß-catenin while miR-155 mimic reverses the effects. CONCLUSION: Taken together, SchA downregulates miR-155 and results in the suppression of proliferation and motility in breast cancer cells. Our findings proposed that SchA might be used as an underlying therapeutic agent.

Large-scale image-based screening and profiling of cellular phenotypes.

Cellular phenotypes are observable characteristics of cells resulting from the interactions of intrinsic and extrinsic chemical or biochemical factors. Image-based phenotypic screens under large numbers of basal or perturbed conditions can be used to study the influences of these factors on cellular phenotypes. Hundreds to thousands of phenotypic descriptors can also be quantified from the images of cells under each of these experimental conditions. Therefore, huge amounts of data can be generated, and the analysis of these data has become a major bottleneck in large-scale phenotypic screens. Here, we review current experimental and computational methods for large-scale image-based phenotypic screens. Our focus is on phenotypic profiling, a computational procedure for constructing quantitative and compact representations of cellular phenotypes based on the images collected in these screens. © 2016 International Society for Advancement of Cytometry.

Biological and Epidemiological Consequences of MTBC Diversity.

Tuberculosis is caused by different groups of bacteria belonging to the Mycobacterium tuberculosis complex (MTBC). The combined action of human factors, environmental conditions and bacterial virulence determine the extent and form of human disease. MTBC virulence is a composite of different clinical phenotypes such as transmission rate and disease severity among others. Clinical phenotypes are also influenced by cellular and immunological phenotypes. MTBC phenotypes are determined by the genotype, therefore finding genotypes responsible for clinical phenotypes would allow discovering MTBC virulence factors. Different MTBC strains display different cellular and clinical phenotypes. Strains from Lineage 5 and Lineage 6 are metabolically different, grow slower, and are less virulent. Also, at least certain groups of Lineage 2 and Lineage 4 strains are more virulent in terms of disease severity and human-to-human transmission. Because phenotypic differences are ultimately caused by genotypic differences, different genomic loci have been related to various cellular and clinical phenotypes. However, defining the impact of specific bacterial genomic loci on virulence when other bacterial determinants, human and environmental factors are also impacting the phenotype would contribute to a better knowledge of tuberculosis virulence and ultimately benefit tuberculosis control.

Heterogeneity in Lowe Syndrome: Mutations Affecting the Phosphatase Domain of OCRL1 Differ in Impact on Enzymatic Activity and Severity of Cellular Phenotypes.

Lowe Syndrome (LS) is a condition due to mutations in the OCRL1 gene, characterized by congenital cataracts, intellectual disability, and kidney malfunction. Unfortunately, patients succumb to renal failure after adolescence. This study is centered in investigating the biochemical and phenotypic impact of patient's OCRL1 variants (OCRL1VAR). Specifically, we tested the hypothesis that some OCRL1VAR are stabilized in a non-functional conformation by focusing on missense mutations affecting the phosphatase domain, but not changing residues involved in binding/catalysis. The pathogenic and conformational characteristics of the selected variants were evaluated in silico and our results revealed some OCRL1VAR to be benign, while others are pathogenic. Then we proceeded to monitor the enzymatic activity and function in kidney cells of the different OCRL1VAR. Based on their enzymatic activity and presence/absence of phenotypes, the variants segregated into two categories that also correlated with the severity of the condition they induce. Overall, these two groups mapped to opposite sides of the phosphatase domain. In summary, our findings highlight that not every mutation affecting the catalytic domain impairs OCRL1's enzymatic activity. Importantly, data support the inactive-conformation hypothesis. Finally, our results contribute to establishing the molecular and structural basis for the observed heterogeneity in severity/symptomatology displayed by patients.

Transcriptomic forecasting with neural ordinary differential equations.

Single-cell transcriptomics technologies can uncover changes in the molecular states that underlie cellular phenotypes. However, understanding the dynamic cellular processes requires extending from inferring trajectories from snapshots of cellular states to estimating temporal changes in cellular gene expression. To address this challenge, we have developed a neural ordinary differential-equation-based method, RNAForecaster, for predicting gene expression states in single cells for multiple future time steps in an embedding-independent manner. We demonstrate that RNAForecaster can accurately predict future expression states in simulated single-cell transcriptomic data with cellular tracking over time. We then show that by using metabolic labeling single-cell RNA sequencing (scRNA-seq) data from constitutively dividing cells, RNAForecaster accurately recapitulates many of the expected changes in gene expression during progression through the cell cycle over a 3-day period. Thus, RNAForecaster enables short-term estimation of future expression states in biological systems from high-throughput datasets with temporal information.

Discovering cellular programs of intrinsic and extrinsic drivers of metabolic traits using LipocyteProfiler.

A primary obstacle in translating genetic associations with disease into therapeutic strategies is elucidating the cellular programs affected by genetic risk variants and effector genes. Here, we introduce LipocyteProfiler, a cardiometabolic-disease-oriented high-content image-based profiling tool that enables evaluation of thousands of morphological and cellular profiles that can be systematically linked to genes and genetic variants relevant to cardiometabolic disease. We show that LipocyteProfiler allows surveillance of diverse cellular programs by generating rich context- and process-specific cellular profiles across hepatocyte and adipocyte cell-state transitions. We use LipocyteProfiler to identify known and novel cellular mechanisms altered by polygenic risk of metabolic disease, including insulin resistance, fat distribution, and the polygenic contribution to lipodystrophy. LipocyteProfiler paves the way for large-scale forward and reverse deep phenotypic profiling in lipocytes and provides a framework for the unbiased identification of causal relationships between genetic variants and cellular programs relevant to human disease.

Characterizing the Metabolic and Immune Landscape of Non-small Cell Lung Cancer Reveals Prognostic Biomarkers Through Omics Data Integration.

Non-small cell lung cancer (NSCLC) is one of the most common malignancies worldwide. The development of high-throughput single-cell RNA-sequencing (RNA-seq) technology and the advent of multi-omics have provided a solid basis for a systematic understanding of the heterogeneity in cancers. Although numerous studies have revealed the molecular features of NSCLC, it is important to identify and validate the molecular biomarkers related to specific NSCLC phenotypes at single-cell resolution. In this study, we analyzed and validated single-cell RNA-seq data by integrating multi-level omics data to identify key metabolic features and prognostic biomarkers in NSCLC. High-throughput single-cell RNA-seq data, including 4887 cellular gene expression profiles from NSCLC tissues, were analyzed. After pre-processing, the cells were clustered into 12 clusters using the t-SNE clustering algorithm, and the cell types were defined according to the marker genes. Malignant epithelial cells exhibit individual differences in molecular features and intra-tissue metabolic heterogeneity. We found that oxidative phosphorylation (OXPHOS) and glycolytic pathway activity are major contributors to intra-tissue metabolic heterogeneity of malignant epithelial cells and T cells. Furthermore, we constructed T-cell differentiation trajectories and identified several key genes that regulate the cellular phenotype. By screening for genes associated with T-cell differentiation using the Lasso algorithm and Cox risk regression, we identified four prognostic marker genes for NSCLC. In summary, our study revealed metabolic features and prognostic markers of NSCLC at single-cell resolution, which provides novel findings on molecular biomarkers and signatures of cancers.

Mesenchymal Stem Cell Functionalization for Enhanced Therapeutic Applications.

IMPACT STATEMENT: Culture expansion of MSCs has detrimental effects on various cell characteristics and attributes (e.g., phenotypic changes and senescence), which, in addition to inherent interdonor variability, negatively impact the standardization and reproducibility of their therapeutic potential. The identification of innate distinct functional MSC subpopulations, as well as the description of ex vivo protocols aimed at maintaining phenotypes and enhancing specific functions have the potential to overcome these limitations. The incorporation of those approaches into cell-based therapy would significantly impact the field, as more reproducible clinical outcomes may be achieved.

Knockdown of long non-coding RNA SNHG5 inhibits malignant cellular phenotypes of glioma via Wnt/CTNNB1 signaling pathway.

Objective: Human brain glioma is the most malignant primary intracranial tumor, which has poor prognosis and high mortality. Long noncoding RNAs are considered to take part in cellular phenotypes and are emerging as diagnostic and prognostic biomarkers of glioma. This study will research the effects of Small Nucleolar RNA Host Gene 5 (SNHG5) gene on malignant cellular phenotypes in glioma and explore the possible mechanisms. Materials and Methods: The expression level of SNHG5 was examined using quantitative Real-time PCR in glioma tissues and cell lines. Loss-of-function experiments of SNHG5 together with Enhanced Cell Counting Kit-8, flow cytometry and cell invasion assay were used to investigate the effects of SNHG5 on malignant cellular phenotypes of glioma cells. Finally, luciferase assay and western blotting were applied to determine the activity of WNT/CTNNB1 signaling pathway. Results: SNHG5 gene was high-expressed in glioma tissues and cell lines. Knockdown of SNHG5 gene depressed cell proliferation and invasiveness as well as promoted the apoptosis of U251 and U87 cells. In addition, online database analysis showed SNHG5 was closely related to Wnt/CTNNB1 signaling pathway. Knockdown of SNHG5 inactivated Wnt/CTNNB1 signaling pathway, and the activating of Wnt/CTNNB1 signaling pathway partly restored the influences of SNHG5 knockdown on malignant cellular phenotypes of U251 and U87 cells. Conclusion: SNHG5 gene was high-expressed in glioma, knockdown of SNHG5 inhibits malignant cellular phenotypes of glioma via Wnt/CTNNB1 signaling pathway.

TALENs-Assisted Multiplex Editing for Accelerated Genome Evolution To Improve Yeast Phenotypes.

Genome editing is an important tool for building novel genotypes with a desired phenotype. However, the fundamental challenge is to rapidly generate desired alterations on a genome-wide scale. Here, we report TALENs (transcription activator-like effector nucleases)-assisted multiplex editing (TAME), based on the interaction of designed TALENs with the DNA sequences between the critical TATA and GC boxes, for generating multiple targeted genomic modifications. Through iterative cycles of TAME to induce abundant semirational indels coupled with efficient screening using a reporter, the targeted fluorescent trait can be continuously and rapidly improved by accumulating multiplex beneficial genetic modifications in the evolving yeast genome. To further evaluate its efficiency, we also demonstrate the application of TAME for significantly improving ethanol tolerance of yeast in a short amount of time. Therefore, TAME is a broadly generalizable platform for accelerated genome evolution to rapidly improve yeast phenotypes.

The role of EMMPRIN expression in ovarian epithelial carcinomas.

PURPOSE: Extracellular matrix metalloproteinase inducer (EMMPRIN) was reported to involve in the invasion and metastasis of malignancies by regulating the expression of vascular endothelial growth factor (VEGF) and matrix metalloproteinases (MMPs) in stromal and cancer cells. The study aimed to clarify the role of EMMPRIN expression in tumorigenesis and progression of ovarian epithelial carcinomas. METHODS: EMMPRIN siRNA were transfected into ovarian carcinoma cells with the phenotypes and their related molecules examined. EMMPRIN expression was determined in ovarian normal tissue, benign and borderline tumors, and epithelial carcinomas by real-time PCR, western blot, and immunohistochemistry. RESULTS: EMMPRIN siRNA treatment resulted in a lower growth, G 1 arrest, apoptotic induction, decreased migration, and invasion. The transfectants showed reduced expression of Wnt5a, Akt, p70s6k, Bcl-xL, survivin, VEGF, and MMP-9 than mock and control cells at both mRNA and protein levels. According to real-time PCR and western blot, EMMPRIN mRNA or protein level was higher in ovarian borderline tumor and carcinoma than normal ovary and benign tumors (P<0.05), and positively correlated with dedifferentiation and FIGO staging (P<0.05). Immunohistochemically, EMMPRIN expression was positively correlated with FIGO staging, dedifferentiation, Ki-67 expression, the lower cumulative and relapse-free survival rate (P<0.05). CONCLUSIONS: Upregulated expression of EMMPRIN protein and mRNA might be involved in the pathogenesis, differentiation, and progression of ovarian carcinomas, possibly by modulating cellular events, such as proliferation, cell cycle, apoptosis, migration, and invasion.