scholarly journals Identification of driver genes and biological signaling for alcoholic myopathy

Author(s):  
Jing Li ◽  
Letian Wang ◽  
Hanming Gu

Abstract Long-term alcohol consumption contributes to muscle weakness and atrophy. However, the mechanism and biological functions are still not clear. In this study, we aim to identify the significantly changed genes and potential signaling pathways in the gastrocnemius and plantaris muscle from C57BL/6Hsd mice by analyzing RNA sequence. The GSE183665 dataset was created by using the Illumina NovaSeq 6000 (Mus musculus). The KEGG and GO analyses showed that "cell migration", "cell adhesion", and "apoptosis" are major biological processes in the skeletal muscles. Moreover, we identified a number of genes including POSTN, GNAI2, MMP2, ELN, CCND1, CXCL12, COL6A1, COL6A2, SFRP2, and FSTL1 by using the PPI network and Reactome map. Thus, our study may shed light on the development of drugs on alcohol myopathy.

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 1969
Author(s):  
Dongmin Jung ◽  
Xijin Ge

Interactions between proteins occur in many, if not most, biological processes. This fact has motivated the development of a variety of experimental methods for the identification of protein-protein interaction (PPI) networks. Leveraging PPI data available STRING database, we use network-based statistical learning methods to infer the putative functions of proteins from the known functions of neighboring proteins on a PPI network. This package identifies such proteins often involved in the same or similar biological functions. The package is freely available at the Bioconductor web site (http://bioconductor.org/packages/PPInfer/).


F1000Research ◽  
2018 ◽  
Vol 6 ◽  
pp. 1969 ◽  
Author(s):  
Dongmin Jung ◽  
Xijin Ge

Interactions between proteins occur in many, if not most, biological processes. This fact has motivated the development of a variety of experimental methods for the identification of protein-protein interaction (PPI) networks. Leveraging PPI data available in the STRING database, we use a network-based statistical learning methods to infer the putative functions of proteins from the known functions of neighboring proteins on a PPI network. This package identifies such proteins often involved in the same or similar biological functions. The package is freely available at the Bioconductor web site (http://bioconductor.org/packages/PPInfer/).


2020 ◽  
Author(s):  
Zhenkun Yang ◽  
Bo Zhang ◽  
Zhenhao Zhang ◽  
Jingjing Wang ◽  
Yaling Hu ◽  
...  

Abstract Background: Glioblastoma is an aggressive primary tumour with the lowest survival time among brain tumours. Tumour-infiltrating immune cells (TIICs) are involved in tumour progression and determine the prognosis, while the association of immune cell infiltration with glioblastoma is rarely unknown. This study aimed to screen survival-related (SR) genes and major biological processes through bioinformatic analysis and to identify the relationship between SR genes and TIICs.Methods:SR genes were screened by comparing the long-term (>36 months) and short-term (<12 months) survivors in the database GSE53733. Gene set enrichment analysis (GSEA) was applied to compare the differences in biological processes between long-term survivors and short-term survivors. The SR genes were identified using the limma package of R. Gene Ontology (GO) analysis was conducted through Metascape. The protein-protein interaction (PPI) network of the SR genes was established through the Search Tool for the Retrieval of Interacting Genes (STRING) website and further analysed by the Molecular Complex Detection (MCODE) algorithm. UALCAN and GlioVis were employed to analyse the expression levels and prognostic value of hub genes. The correlation of hub genes with immune cell filtration was estimated by the Tumor Immune Estimation Resource (TIMER). The gene-drug interaction network was constructed using the Comparative Toxicogenomics Database (CTD).Results: The functions of the detected genes were mainly enriched in epithelial mesenchymal transition (EMT) and oxidative phosphorylation. Of the detected genes, a total of 220 SR genes were identified, including 78 upregulated genes and 142 downregulated genes in long-term survivors. The upregulated genes were mainly related to neuron projection morphogenesis, extracellular matrix, and cation channel activity. The downregulated genes were mainly related to extracellular matrix organization and angiogenesis. The PPI network for SR genes was constructed with 65 edges and 195 nodes, and two significant modules were selected. The results indicated that COL1A2, COL6A2, COL8A1, and COL8A2 were hub SR genes. In addition, they were correlated with immune cell infiltration, especially dendritic cell infiltration.Conclusions: These results revealed that collagens accounted for the progression and prognosis of glioblastoma. In addition, DC infiltration is a risk factor for glioblastoma patients. The expression of collagen protein COL6A2 was significantly correlated with the DC infiltration level and poor prognosis. Further, potential drugs that affect the function of COL6A2 could improve the outcomes of glioblastoma.


F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 1969 ◽  
Author(s):  
Dongmin Jung ◽  
Xijin Ge

Interactions between proteins occur in many, if not most, biological processes. This fact has motivated the development of a variety of experimental methods for the identification of protein-protein interaction (PPI) networks. Leveraging PPI data available STRING database, we use network-based statistical learning methods to infer the putative functions of proteins from the known functions of neighboring proteins on a PPI network. This package identifies such proteins often involved in the same or similar biological functions. The package is freely available at the Bioconductor web site (http://bioconductor.org/packages/PPInfer/).


2021 ◽  
Author(s):  
Jing Li ◽  
Wei Wang ◽  
Hanming Gu

REV-ERB is an orphan nuclear receptor that is widely expressed in the brain and inhibits transcriptional activities. A variety of genes affect the activity and expression of REV-ERB. In this study, our objective is to identify significant signaling pathways and biological processes in the knockout of the REV-ERB mouse brain. The GSE152919 dataset was originally created by using the Illumina HiSeq 4000 (Mus musculus). The KEGG and GO analyses suggested that biological processes "PPAR signaling", "Hippo signaling", and "Hypertrophic cardiomyopathy (HCM)" are mostly affected in the knockout of REV-ERB. Furthermore, we identified a number of genes according to the PPI network including NPAS2, CRY2, BMAL1, and CRY1 which were involved in the lack of REV-ERB in the brain. Therefore, our study provides further insights into the study of circadian clocks.


2019 ◽  
Author(s):  
Xiyan Li ◽  
Michael P. Snyder

AbstractHeavy isotopes are discriminated by biological systems due to kinetic isotopic effects at the biochemical/metabolic levels. How these heavy isotopes are enriched or depleted over a long term is unclear, but artificial manipulation of heavy isotope content in various organisms has produced significant impacts on biological functions, suggesting the origin may arise with intrinsic mechanisms for a functional outcome. Our previous study has revealed an age-associated decline in metabolite heavy isotope content (HIC) in the budding yeast, which could be reversed in part by supplementing heavy water, and consequently, also increased yeast lifespans. In the current study, we report a similar age-dependent decline in HIC from three types of mouse tissues: brain, heart, and skeletal muscles. Furthermore, individual tissues exhibited different patterns of HIC change over age, which appeared to match their development and maturation timelines. These results have demonstrated that age-dependent decline in HIC also exists in mammals, which is likely a traceable feature of development and perhaps aging. Thus, we believe that reversing the decline in HIC could have the potential to extend the healthspan of humans.


2020 ◽  
Vol 26 ◽  
Author(s):  
Pengmian Feng ◽  
Lijing Feng ◽  
Chaohui Tang

Background and Purpose: N 6 -methyladenosine (m6A) plays critical roles in a broad set of biological processes. Knowledge about the precise location of m6A site in the transcriptome is vital for deciphering its biological functions. Although experimental techniques have made substantial contributions to identify m6A, they are still labor intensive and time consuming. As good complements to experimental methods, in the past few years, a series of computational approaches have been proposed to identify m6A sites. Methods: In order to facilitate researchers to select appropriate methods for identifying m6A sites, it is necessary to give a comprehensive review and comparison on existing methods. Results: Since researches on m6A in Saccharomyces cerevisiae are relatively clear, in this review, we summarized recent progresses on computational prediction of m6A sites in S. cerevisiae and assessed the performance of existing computational methods. Finally, future directions of computationally identifying m6A sites were presented. Conclusion: Taken together, we anticipate that this review will provide important guides for computational analysis of m 6A modifications.


2021 ◽  
pp. 002224372110092
Author(s):  
Zhenling Jiang ◽  
Dennis J. Zhang ◽  
Tat Chan

This paper studies how receiving a bonus changes the consumers’ demand for auto loans and the risk of future delinquency. Unlike traditional consumer products, auto loans have a long-term impact on consumers’ financial state because of the monthly payment obligation. Using a large consumer panel data set of credit and employment information, the authors find that receiving a bonus increases auto loan demand by 21 percent. These loans, however, are associated with higher risk, as the delinquency rate increases by 18.5 −31.4 percent depending on different measures. In contrast, an increase in consumers’ base salary will increase the demand for auto loans but not the delinquency. By comparing consumers with bonuses with those without bonuses, the authors find that bonus payments lead to both demand expansion and demand shifting on auto loans. The empirical findings help shed light on how consumers make financial decisions and have important implications for financial institutions on when demand for auto loans and the associated risk arise.


2021 ◽  
Vol 9 (3) ◽  
pp. 501
Author(s):  
Zhimin Zhang ◽  
Qinghui Deng ◽  
Lingling Wan ◽  
Xiuyun Cao ◽  
Yiyong Zhou ◽  
...  

Aquaculture is among the most important and fastest growing agriculture sectors worldwide; however, it generates environmental impacts by introducing nutrient accumulations in ponds, which are possibly different and further result in complex biological processes in the sediments based on diverse farming practices. In this study, we investigated the effects of long-term farming practices of representative aquatic animals dominated by grass carp (GC, Ctenopharyngodon idella) or Chinese mitten crab (CMC, Eriocheir sinensis) on the bacterial community and enzyme activity of sediments from more than 15 years of aquaculture ponds, and the differences associated with sediment properties were explored in the two farming practices. Compared to CMC ponds, GC ponds had lower contents of TC, TN, and TP in sediments, and similar trends for sediment pH and moisture content. Sediment bacterial communities were significantly different between GC and CMC ponds, with higher bacterial richness and diversity in GC ponds. The bacterial communities among the pond sediments were closely associated with sediment pH, TC, and TN. Additionally, the results showed profoundly lower activities of β-1,4-glucosidase, leucine aminopeptidase, and phosphatase in the sediments of GC ponds than CMC ponds. Pearson’s correlation analysis further revealed strong positive correlations between the hydrolytic enzyme activities and nutrient concentrations among the aquaculture ponds, indicating microbial enzyme regulation response to sediment nutrient dynamics. Our study herein reveals that farming practices of fish and crab differently affect bacterial communities and enzymatic activities in pond sediments, suggesting nutrient-driven sediment biological processes in aquaculture ponds for different farming practices.


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