scholarly journals Epinephrine affects gene expression levels and has a complex effect on biofilm formation in micrococcus luteus strain C01 isolated from human skin

Biofilm ◽  
2021 ◽  
pp. 100058
Author(s):  
A.V. Gannesen ◽  
M.I. Schelkunov ◽  
O.V. Geras'kina ◽  
N.E. Makarova ◽  
M.V. Sukhacheva ◽  
...  
Keyword(s):  
Gene Expression ◽  
Human Skin ◽  
Biofilm Formation ◽  
Micrococcus Luteus ◽  
Complex Effect ◽  
Expression Levels ◽  
Gene Expression Levels

scholarly journals Robust Biofilm-Forming Ionizing Radiation Resistant Bacillus subtilis isolated from Ramsar-Iran, Emphasis on Molecular Genetic profiling Analysis

2020 ◽  
Author(s):  
dhuha saeed ali ◽  
reza vazifehmand(Former Corresponding Author) ◽  
Yaya Rukayadi ◽  
Son Radu ◽  
Mirsasan Mirpour ◽  
...  
Keyword(s):  
Gene Expression ◽  
Bacillus Subtilis ◽  
Ionizing Radiation ◽  
Biofilm Formation ◽  
Genetic Variations ◽  
Negative Control ◽  
Expression Levels ◽  
Significant Difference ◽  
Radiation Resistant ◽  
Gene Expression Levels

Abstract Background The production of structurally complex multicellular communities or biofilms is a mode of growth that is believed to require and involves a differential gene expression as compared to their planktonic counterpart. There is a poor knowledge of biofilm formation and its molecular signaling function in a radiation resistance bacteria. Therefore, the aim of the present study was to investigate the genetic variations and gene expression levels of some critical genes involved in the biofilm formation and matrix production in an ionizing-radiation-resistant B. subtilis (RAM-04) isolated from Abe-Siah hot spring, Ramsar- Iran. Bacillus subtilis DSM-10 a non-ionizing-radiation-resistant and standard strain model considered as a negative control. Results Quantification of biofilms performed using crystal violet assay and Scanning Electron Microscopy that the results presented a significant difference of a high level of the biofilm formation in terms of quantity and structure by Bacillus subtilis (RAM-04) as compared to Bacillus subtilis DSM-10. At the Molecular level, a total of 13 genes including ( tapA ) yqxM-sipW-tasA (operon), sinR , sinI , ccpA , epsA-O , spoOB , spoOA , slrA , slrR , ymcA and abrB were selected to study the genetic variations and gene expression levels using direct sequencing method and quantitative PCR technique. Primary analysis revealed genetic variations in ( tapA ) yqxM-sipW-tasA (operon), sinR , sinI , epsA-O , and slrR in B. subtilis (RAM-04) as compared to the negative control. The result of gene expression revealed a significant difference between test and control bacteria. ( tapA ) yqxM-sipW-tasA operon was significantly over expressed ( p = 0.000 with expression folding of 13, 11, 8 respectively) and the expression level of ccpA and slrR were significantly down ( p = 0.000 with expression folding of 0.2 and 0.3 respectively). Conclusions These results support the hypothesis that the induction of biofilm formation is performed by ( tapA ) yqxM-sipW-tasA operon signaling pathway, which in turn indicate that this operon has a positive role in biofilm formation in ionizing-radiation-resistant B. subtilis (RAM-04) under natural radiation environment.

scholarly journals A Sparse and Low-Rank Regression Model for Identifying the Relationships Between DNA Methylation and Gene Expression Levels in Gastric Cancer and the Prediction of Prognosis

Genes ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 854
Author(s):  
Yishu Wang ◽  
Lingyun Xu ◽  
Dongmei Ai
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Dna Methylation ◽  
Regression Model ◽  
The Cancer Genome Atlas ◽  
Low Rank ◽  
Expression Levels ◽  
Rank Regression ◽  
Prediction Of Prognosis ◽  
Gene Expression Levels

DNA methylation is an important regulator of gene expression that can influence tumor heterogeneity and shows weak and varying expression levels among different genes. Gastric cancer (GC) is a highly heterogeneous cancer of the digestive system with a high mortality rate worldwide. The heterogeneous subtypes of GC lead to different prognoses. In this study, we explored the relationships between DNA methylation and gene expression levels by introducing a sparse low-rank regression model based on a GC dataset with 375 tumor samples and 32 normal samples from The Cancer Genome Atlas database. Differences in the DNA methylation levels and sites were found to be associated with differences in the expressed genes related to GC development. Overall, 29 methylation-driven genes were found to be related to the GC subtypes, and in the prognostic model, we explored five prognoses related to the methylation sites. Finally, based on a low-rank matrix, seven subgroups were identified with different methylation statuses. These specific classifications based on DNA methylation levels may help to account for heterogeneity and aid in personalized treatments.

scholarly journals High heterogeneity undermines generalization of differential expression results in RNA-Seq analysis

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Weitong Cui ◽  
Huaru Xue ◽  
Lei Wei ◽  
Jinghua Jin ◽  
Xuewen Tian ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Small Sample ◽  
Differentially Expressed ◽  
Cancer Type ◽  
Rna Seq ◽  
Sample Sizes ◽  
Large Sample ◽  
Expression Levels ◽  
Gene Expression Levels

Abstract Background RNA sequencing (RNA-Seq) has been widely applied in oncology for monitoring transcriptome changes. However, the emerging problem that high variation of gene expression levels caused by tumor heterogeneity may affect the reproducibility of differential expression (DE) results has rarely been studied. Here, we investigated the reproducibility of DE results for any given number of biological replicates between 3 and 24 and explored why a great many differentially expressed genes (DEGs) were not reproducible. Results Our findings demonstrate that poor reproducibility of DE results exists not only for small sample sizes, but also for relatively large sample sizes. Quite a few of the DEGs detected are specific to the samples in use, rather than genuinely differentially expressed under different conditions. Poor reproducibility of DE results is mainly caused by high variation of gene expression levels for the same gene in different samples. Even though biological variation may account for much of the high variation of gene expression levels, the effect of outlier count data also needs to be treated seriously, as outlier data severely interfere with DE analysis. Conclusions High heterogeneity exists not only in tumor tissue samples of each cancer type studied, but also in normal samples. High heterogeneity leads to poor reproducibility of DEGs, undermining generalization of differential expression results. Therefore, it is necessary to use large sample sizes (at least 10 if possible) in RNA-Seq experimental designs to reduce the impact of biological variability and DE results should be interpreted cautiously unless soundly validated.

scholarly journals Genome-Wide Expression and Alternative Splicing in Domesticated Sunflowers (Helianthus annuus L.) under Flooding Stress

Agronomy ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 92
Author(s):  
Joon Seon Lee ◽  
Lexuan Gao ◽  
Laura Melissa Guzman ◽  
Loren H. Rieseberg
Keyword(s):  
Gene Expression ◽  
Alternative Splicing ◽  
Mixed Model ◽  
Agricultural Land ◽  
Alcohol Fermentation ◽  
Expression Levels ◽  
Flooding Stress ◽  
Genome Wide ◽  
And Control ◽  
Gene Expression Levels

Approximately 10% of agricultural land is subject to periodic flooding, which reduces the growth, survivorship, and yield of most crops, reinforcing the need to understand and enhance flooding resistance in our crops. Here, we generated RNA-Seq data from leaf and root tissue of domesticated sunflower to explore differences in gene expression and alternative splicing (AS) between a resistant and susceptible cultivar under both flooding and control conditions and at three time points. Using a combination of mixed model and gene co-expression analyses, we were able to separate general responses of sunflower to flooding stress from those that contribute to the greater tolerance of the resistant line. Both cultivars responded to flooding stress by upregulating expression levels of known submergence responsive genes, such as alcohol dehydrogenases, and slowing metabolism-related activities. Differential AS reinforced expression differences, with reduced AS frequencies typically observed for genes with upregulated expression. Significant differences were found between the genotypes, including earlier and stronger upregulation of the alcohol fermentation pathway and a more rapid return to pre-flooding gene expression levels in the resistant genotype. Our results show how changes in the timing of gene expression following both the induction of flooding and release from flooding stress contribute to increased flooding tolerance.

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