Dataset Information

High-resolution genome-wide expression analysis of single myofibers using SMART-Seq.

ABSTRACT: Skeletal muscle is a heterogeneous tissue. Individual myofibers that make up muscle tissue exhibit variation in their metabolic and contractile properties. Although biochemical and histological assays are available to study myofiber heterogeneity, efficient methods to analyze the whole transcriptome of individual myofibers are lacking. Here, we report on a single-myofiber RNA-sequencing (smfRNA-Seq) approach to analyze the whole transcriptome of individual myofibers by combining single-fiber isolation with Switching Mechanism at 5' end of RNA Template (SMART) technology. Using smfRNA-Seq, we first determined the genes that are expressed in the whole muscle, including in nonmyogenic cells. We also analyzed the differences in the transcriptome of myofibers from young and old mice to validate the effectiveness of this new method. Our results suggest that aging leads to significant changes in the expression of metabolic genes, such as Nos1, and structural genes, such as Myl1, in myofibers. We conclude that smfRNA-Seq is a powerful tool to study developmental, disease-related, and age-related changes in the gene expression profile of skeletal muscle.

SUBMITTER: Blackburn DM

PROVIDER: S-EPMC6937554 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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High-resolution genome-wide expression analysis of single myofibers using SMART-Seq.

Blackburn Darren M DM Lazure Felicia F Corchado Aldo H AH Perkins Theodore J TJ Najafabadi Hamed S HS Soleimani Vahab D VD

The Journal of biological chemistry 20191121 52

Skeletal muscle is a heterogeneous tissue. Individual myofibers that make up muscle tissue exhibit variation in their metabolic and contractile properties. Although biochemical and histological assays are available to study myofiber heterogeneity, efficient methods to analyze the whole transcriptome of individual myofibers are lacking. Here, we report on a single-myofiber RNA-sequencing (smfRNA-Seq) approach to analyze the whole transcriptome of individual myofibers by combining single-fiber iso ...[more]

PMID: 31753917

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Project description:To persist in their dynamic human host environments, fungal pathogens must sense and adapt by modulating their gene expression to fulfill their cellular needs. Understanding transcriptional regulation on a global scale would uncover cellular processes linked to persistence and virulence mechanisms that could be targeted for antifungal therapeutics. Infections associated with the yeast Candida albicans, a highly prevalent fungal pathogen, and the multiresistant related species Candida auris are becoming a serious public health threat. To define the set of a gene regulated by a transcriptional regulator in C. albicans, chromatin immunoprecipitation (ChIP)-based techniques, including ChIP with microarray technology (ChIP-chip) or ChIP-DNA sequencing (ChIP-seq), have been widely used. Here, we describe a new set of PCR-based micrococcal nuclease (MNase)-tagging plasmids for C. albicans and other Candida spp. to determine the genome-wide location of any transcriptional regulator of interest using chromatin endogenous cleavage (ChEC) coupled to high-throughput sequencing (ChEC-seq). The ChEC procedure does not require protein-DNA cross-linking or sonication, thus avoiding artifacts related to epitope masking or the hyper-ChIPable euchromatic phenomenon. In a proof-of-concept application of ChEC-seq, we provided a high-resolution binding map of the SWI/SNF chromatin remodeling complex, a master regulator of fungal fitness in C. albicans, in addition to the transcription factor Nsi1 that is an ortholog of the DNA-binding protein Reb1 for which genome-wide occupancy was previously established in Saccharomyces cerevisiae The ChEC-seq procedure described here will allow a high-resolution genomic location definition which will enable a better understanding of transcriptional regulatory circuits that govern fungal fitness and drug resistance in these medically important fungi.IMPORTANCE Systemic fungal infections caused by Candida albicans and the "superbug" Candida auris are becoming a serious public health threat. The ability of these yeasts to cause disease is linked to their faculty to modulate the expression of genes that mediate their escape from the immune surveillance and their persistence in the different unfavorable niches within the host. Comprehensive knowledge on gene expression control of fungal fitness is consequently an interesting framework for the identification of essential infection processes that could be hindered by chemicals as potential therapeutics. Here, we expanded the use of ChEC-seq, a technique that was initially developed in the yeast model Saccharomyces cerevisiae to identify genes that are modulated by a transcriptional regulator, in pathogenic yeasts from the genus Candida This robust technique will allow a better characterization of key gene expression regulators and their contribution to virulence and antifungal resistance in these pathogenic yeasts.

Project description:BACKGROUND: Clostridium beijerinckii is a prominent solvent-producing microbe that has great potential for biofuel and chemical industries. Although transcriptional analysis is essential to understand gene functions and regulation and thus elucidate proper strategies for further strain improvement, limited information is available on the genome-wide transcriptional analysis for C. beijerinckii. RESULTS: The genome-wide transcriptional dynamics of C. beijerinckii NCIMB 8052 over a batch fermentation process was investigated using high-throughput RNA-Seq technology. The gene expression profiles indicated that the glycolysis genes were highly expressed throughout the fermentation, with comparatively more active expression during acidogenesis phase. The expression of acid formation genes was down-regulated at the onset of solvent formation, in accordance with the metabolic pathway shift from acidogenesis to solventogenesis. The acetone formation gene (adc), as a part of the sol operon, exhibited highly-coordinated expression with the other sol genes. Out of the > 20 genes encoding alcohol dehydrogenase in C. beijerinckii, Cbei_1722 and Cbei_2181 were highly up-regulated at the onset of solventogenesis, corresponding to their key roles in primary alcohol production. Most sporulation genes in C. beijerinckii 8052 demonstrated similar temporal expression patterns to those observed in B. subtilis and C. acetobutylicum, while sporulation sigma factor genes sigE and sigG exhibited accelerated and stronger expression in C. beijerinckii 8052, which is consistent with the more rapid forespore and endspore development in this strain. Global expression patterns for specific gene functional classes were examined using self-organizing map analysis. The genes associated with specific functional classes demonstrated global expression profiles corresponding to the cell physiological variation and metabolic pathway switch. CONCLUSIONS: The results from this work provided insights for further C. beijerinckii strain improvement employing system biology-based strategies and metabolic engineering approaches.

Dataset Information

High-resolution genome-wide expression analysis of single myofibers using SMART-Seq.

Publications

High-resolution genome-wide expression analysis of single myofibers using SMART-Seq.

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