RNA-Seq analysis of Bacillus methanolicus MGA3 grown with and without 5-aminovalerate to investigate the transcriptional response of Bacillus methanolicus to 5-aminovalerate.
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB43112 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR5296750_1.fastq.gz | Fastqsanger.gz | |||
| ERR5296750_2.fastq.gz | Fastqsanger.gz | |||
| ERR5296751_1.fastq.gz | Fastqsanger.gz | |||
| ERR5296751_2.fastq.gz | Fastqsanger.gz | |||
| ERR5296752_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 12 |
Similar Datasets
Project description:Bacillus methanolicus MGA3, which has a low tolerance for 5-aminovalerate. To investigate the transcriptional response of Bacillus methanolicus to 5-aminovalerate transcriptomic analysis by differential RNA-Seq in the presence and absence of 5AVA was perfromed. In detail: B. methanolicus cultures were grown in MVcM or MVcMY media containing 200 mM methanol supplemented with and without 50 mM 5AVA, respectively. Cells were harvested in the mid log phase at an OD600 of 0.6 and isolation of total RNA isolation was performed individually for each cultivation condition. Isolated RNA samples from B. methanolicus MGA3 were used in biological triplicates for the cDNA library preparation prior to sequencing. Ribo-Zero rRNA Removal Kit (Bacteria) from Illumina (San Diego, CA, USA) was used to remove the ribosomal RNA molecules from the isolated total RNA. Removal of rRNA was checked by Agilent RNA Pico 6000 kit on Agilent 2100 Bioanalyzer (Agilent Technologies, Böblingen, Germany). RNA was free of detectable rRNA. Preparation of cDNA libraries were performed according to the manufacturer’s instructions of TruSeq stranded mRNA Kit (Illumina, San Diego, USA). Subsequently, each cDNA library was sequenced on a HiSeq1500 (2 x 75nt PE rapid v2) Sequencer system (Illumina, San Diego, USA).
2021-02-25 | E-MTAB-10101 | biostudies-arrayexpress
Project description:Bacillus methanolicus MGA3 Genome sequencing
| PRJNA49595 | ENA
Project description:Bacillus methanolicus MGA3 Genome sequencing
| PRJNA246479 | ENA
Project description:Bacillus methanolicus MGA3 Genome sequencing
| PRJNA165041 | ENA
Project description:Bacillus methanolicus is a Gram-positive, thermophilic, methanol-utilizing bacterium. As a facultative methylotroph, B. methanolicus is also known to utilize d-mannitol, d-glucose and, as recently discovered, sugar alcohol d-arabitol. While metabolic pathways for utilization of methanol, mannitol and glucose are known, catabolism of arabitol has not yet been characterized in B. methanolicus. In this work we present the elucidation of this hitherto uncharted pathway. In order to confirm our predictions regarding genes coding for arabitol utilization, we performed differential gene expression analysis of B. methanolicus MGA3 cells grown on arabitol as compared to mannitol via transcriptome sequencing (RNA-seq). We identified a gene cluster comprising eight genes that was up-regulated during growth with arabitol as a sole carbon source. The RNA-seq results were subsequently confirmed via qRT-PCR experiments. The transcriptional organization of the gene cluster identified via RNA-seq was analyzed and it was shown that the arabitol utilization genes are co-transcribed in an operon that spans from BMMGA3_RS07325 to BMMGA3_RS07365.
2019-07-06 | GSE133849 | GEO
Project description:Background: Bacillus methanolicus MGA3 is a thermophilic, facultative ribulose monophosphate (RuMP) cycle methylotroph. Methylotrophy in this organism depends on the endogenous plasmid pBM19 although all ribulose monophosphate cycle enzymes are also encoded on the chromosome. Together with its ability to produce high yields of amino acids, the relevance of this microorganism as a promising and valuable candidate for future biotechnological applications is evident. The B. methanolicus MGA3 genome consists of a 3,337,035 nucleotides (nt) circular chromosome, the 19,174 nt plasmid pBM19 and the 68,999 nt plasmid pBM69. 3,218 protein-coding regions were annotated on the chromosome, 22 on pBM19 and 82 on pBM69. In the present study, the RNA-seq approach was used to comprehensively investigate the transcriptome of B. methanolicus MGA3 in order to improve the genome annotation, identify novel transcripts, analyze conserved sequence motifs involved in gene expression and reveal operon structures. For this aim, two different cDNA library preparation methods were applied: one which allows characterization of the whole transcriptome and another which includes enrichment of primary transcript 5’‑ends. Results: Analysis of the primary transcriptome data enabled the detection of 2,167 putative transcription start sites (TSSs) which were categorized into 1,642 TSSs located in the upstream region (5’ UTR) of known protein-coding genes and 525 TSSs of novel antisense, intragenic, or intergenic transcripts. The first step of the analysis was the correction of 14 wrongly annotated translation start sites (TLSs) on the basis of the primary transcriptome data. Further investigation of the identified 5’ UTRs resulted in the detailed characterization of their length distribution and the detection of 75 hitherto unknown cis regulatory RNA elements. In addition to this, the exact TSSs positions were utilized to define conserved sequence motifs for translation start sites, ribosome binding sites and promoters in B. methanolicus MGA3. Based on the whole transcriptome data set, novel transcripts, operon structures and mRNA abundances were determined. The analysis of the operon structures revealed that almost half of the genes are transcribed monocistronically (940), whereas 1,164 genes are organized in 381 operons. Several of the genes related to methylotrophy had highly abundant transcripts. Conclusion: The extensive insights into the transcriptional landscape of B. methanolicus MGA3, gained in this study, represent a valuable foundation for further comparative quantitative transcriptome analyses and possibly also for the development of molecular biology tools which at present are very limited for this organism.
2014-12-24 | GSE64469 | GEO
Project description:Here, we established for the first time a proteomic analysis of B. methanolicus MGA3, and we used this approach to compare cells grown on methanol and mannitol at 50°C as well as cells grown on methanol at 37°C and 50°C. Bacillus methanolicus MGA3 is a facultative methylotroph of industrial relevance that is able to grow on methanol as its sole source of carbon and energy. The Gram-positive bacterium possesses a soluble NAD-dependent methanol dehydrogenase and assimilates formaldehyde via the ribulose monophosphate (RuMP) cycle. We used label-free quantitative proteomics to generate reference proteome data for this bacterium and compared the proteome of B. methanolicus MGA3 on two different carbon sources (methanol and mannitol) as well as two different growth temperatures (50°C and 37°C). From a total of approximately 1,200 different detected proteins, approximately 1,000 of these were used for quantification. While the levels of 213 proteins were significantly different at the two growth temperatures tested, the levels of 109 proteins changed significantly when cells were grown on different carbon sources. The carbon source strongly affected the expression of enzymes related to carbon metabolism, and in particular, both dissimilatory and assimilatory RuMP cycle enzyme levels were elevated during growth on methanol compared to mannitol. Our data also indicate that B. methanolicus has a functional TCA cycle that is differentially regulated on mannitol and methanol. Other proteins presumed to be involved in growth on methanol were constitutively expressed under the different growth conditions. Protein Identification: Raw data of gel slices with equal molecular weight were loaded together into the software package Progenesis LCMS Version. 4.1 (www.nonlinear.com), a software tool developed for label-free quantification of LC–MS data. Data was analyzed according to Progenesis LCMS analysis in Weisser et al., In brief, for data loading, the option "High Mass Accuracy Instrument" was selected. LC–MS data were normalized and aligned according to manufacturer’s specifications. In the aligning step manual seeding of "three to five" vectors along the retention time gradient was performed followed by automatic alignment. For the identification of peptide features in the corresponding mass spectrometry files, Mascot generic files (.mgf file format) are generated with Progenesis LCMS (using up to five tandem mass spectra for each feature with the top 200 fragment ion peaks ,charge deconvolution and de-isotopting activated). Mgf files were searched by Mascot 2.3 search engine against an amino acid database containing 20,399 entries including 3,418 MGA3 annotated proteins (downloaded from Uniprot on August 2013), 6,651 yeast proteins, 261 known mass spectrometry contaminants as forward entries and from all forward entries except the contaminats, a reverse decoy sequence. Parameters for precursor tolerance and fragment ion tolerance were set to ± 10 ppm and ± 0.6 Da, respectively. Mascot results were loaded into Scaffold v4.05, using the options for protein clustering and high mass accuracy PeptideProphet scoring.
2014-01-28 | PXD000637 | Pride
Project description:Background: Bacillus methanolicus MGA3 is a thermophilic, facultative ribulose monophosphate (RuMP) cycle methylotroph. Methylotrophy in this organism depends on the endogenous plasmid pBM19 although all ribulose monophosphate cycle enzymes are also encoded on the chromosome. Together with its ability to produce high yields of amino acids, the relevance of this microorganism as a promising and valuable candidate for future biotechnological applications is evident. The B.M-BM- methanolicus MGA3 genome consists of a 3,337,035 nucleotides (nt) circular chromosome, the 19,174M-BM- nt plasmid pBM19 and the 68,999M-BM- nt plasmid pBM69. 3,218 protein-coding regions were annotated on the chromosome, 22 on pBM19 and 82 on pBM69. In the present study, the RNA-seq approach was used to comprehensively investigate the transcriptome of B.M-BM- methanolicus MGA3 in order to improve the genome annotation, identify novel transcripts, analyze conserved sequence motifs involved in gene expression and reveal operon structures. For this aim, two different cDNA library preparation methods were applied: one which allows characterization of the whole transcriptome and another which includes enrichment of primary transcript 5M-bM-^@M-^YM-bM-^@M-^Qends. Results: Analysis of the primary transcriptome data enabled the detection of 2,167 putative transcription start sites (TSSs) which were categorized into 1,642 TSSs located in the upstream region (5M-bM-^@M-^Y UTR) of known protein-coding genes and 525 TSSs of novel antisense, intragenic, or intergenic transcripts. The first step of the analysis was the correction of 14 wrongly annotated translation start sites (TLSs) on the basis of the primary transcriptome data. Further investigation of the identified 5M-bM-^@M-^Y UTRs resulted in the detailed characterization of their length distribution and the detection of 75 hitherto unknown cis regulatory RNA elements. In addition to this, the exact TSSs positions were utilized to define conserved sequence motifs for translation start sites, ribosome binding sites and promoters in B. methanolicus MGA3. Based on the whole transcriptome data set, novel transcripts, operon structures and mRNA abundances were determined. The analysis of the operon structures revealed that almost half of the genes are transcribed monocistronically (940), whereas 1,164 genes are organized in 381 operons. Several of the genes related to methylotrophy had highly abundant transcripts. Conclusion: The extensive insights into the transcriptional landscape of B. methanolicus MGA3, gained in this study, represent a valuable foundation for further comparative quantitative transcriptome analyses and possibly also for the development of molecular biology tools which at present are very limited for this organism. Pooled samples from 16 different cultivation conditions are analysed in whole transcriptome and 5'end enriched transcriptome protocols.
2014-12-24 | E-GEOD-64469 | biostudies-arrayexpress
Project description:Here, we established for the first time a proteomic analysis of B. methanolicus MGA3, and we used this approach to compare cells grown on methanol and mannitol at 50°C as well as cells grown on methanol at 37°C and 50°C. Bacillus methanolicus MGA3 is a facultative methylotroph of industrial relevance that is able to grow on methanol as its sole source of carbon and energy. The Gram-positive bacterium possesses a soluble NAD-dependent methanol dehydrogenase and assimilates formaldehyde via the ribulose monophosphate (RuMP) cycle. We used label-free quantitative proteomics to generate reference proteome data for this bacterium and compared the proteome of B. methanolicus MGA3 on two different carbon sources (methanol and mannitol) as well as two different growth temperatures (50°C and 37°C). From a total of approximately 1,200 different detected proteins, approximately 1,000 of these were used for quantification. While the levels of 213 proteins were significantly different at the two growth temperatures tested, the levels of 109 proteins changed significantly when cells were grown on different carbon sources. The carbon source strongly affected the expression of enzymes related to carbon metabolism, and in particular, both dissimilatory and assimilatory RuMP cycle enzyme levels were elevated during growth on methanol compared to mannitol. Our data also indicate that B. methanolicus has a functional TCA cycle that is differentially regulated on mannitol and methanol. Other proteins presumed to be involved in growth on methanol were constitutively expressed under the different growth conditions. Protein Identification: Raw data of gel slices with equal molecular weight were loaded together into the software package Progenesis LCMS Version. 4.1 (www.nonlinear.com), a software tool developed for label-free quantification of LC–MS data. Data was analyzed according to Progenesis LCMS analysis in Weisser et al., In brief, for data loading, the option "High Mass Accuracy Instrument" was selected. LC–MS data were normalized and aligned according to manufacturer’s specifications. In the aligning step manual seeding of "three to five" vectors along the retention time gradient was performed followed by automatic alignment. For the identification of peptide features in the corresponding mass spectrometry files, Mascot generic files (.mgf file format) are generated with Progenesis LCMS (using up to five tandem mass spectra for each feature with the top 200 fragment ion peaks ,charge deconvolution and de-isotopting activated). Mgf files were searched by Mascot 2.3 search engine against an amino acid database containing 20,399 entries including 3,418 MGA3 annotated proteins (downloaded from Uniprot on August 2013), 6,651 yeast proteins, 261 known mass spectrometry contaminants as forward entries and from all forward entries except the contaminats, a reverse decoy sequence. Parameters for precursor tolerance and fragment ion tolerance were set to ± 10 ppm and ± 0.6 Da, respectively. Mascot results were loaded into Scaffold v4.05, using the options for protein clustering and high mass accuracy PeptideProphet scoring.
2014-01-28 | PXD000638 | Pride
Project description:A total gene expression approach was applied to study the methylotrophic nature of B. methanolicus by comparing the gene expression in bacteria grown methylotropic compared to non-methylotrophic. Genes of interest with different gene expression were quantified in the same RNA samples by real-time PCR, confirming the results found in the microarray experiment. Genes of special interest that are expressed higher when grown methylotrophic, were the RuMP pathway genes located on the pBM19. Bacillus methanolicus was grown in minimal media with either methanol or mannitol as carbon source. The experiment was preformed in triplicate, with bacterial cultures grown on 3 different days.
2012-05-22 | E-GEOD-35298 | biostudies-arrayexpress