Methanosarcina spelaei strain:MC-15
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA300715 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| Other | ||||
| SRR2886879_1.fastq.gz | Fastqsanger.gz | |||
| SRR2886879_2.fastq.gz | Fastqsanger.gz |
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Project description:Trans-encoded sRNA154 is exclusively expressed under nitrogen (N)-deficiency in Methanosarcina mazei strain Gö1. The respective deletion strain showed a significant growth defect under N-limitation, pointing towards a regulatory role of sRNA154 in the N-metabolism. Aiming to elucidate this regulatory function we characterized sRNA154 by biochemical and genetic approaches. 24 homologs of sRNA154 were identified in recently reported draft genomes of Methanosarcina strains, demonstrating high conservation in sequence and predicted secondary structure with two highly conserved single stranded loop regions. In silico target prediction uncovered multiple potential interactions of both conserved loops with mRNA targets 5´untranslated region and coding sequence) encoding key components of the N-metabolism. In line with the computational prediction transcriptome studies of the sRNA154 deletion mutant by an RNA-seq approach uncovered nrpA-mRNA as a potential target, encoding the transcriptional activator of the nitrogen fixation (nif)-operon. Further evidence obtained by electromobility shift-, stability- and complementation assays, strongly argues for a stabilizing effect of sRNA154 on nrpA-mRNA by binding with both loops. Studying the further predicted N-related targets showing lower transcript levels in the absence of sRNA154, demonstrated that nifH transcript levels are most likely indirectly affected by sRNA154 due to enhanced stability of the nrpA transcripts. Besides, translation of glnA2-mRNA, encoding glutamine synthetase, appears to be affected by sRNA154 masking the ribosome binding site (RBS), whereas glnA1-mRNA appears to be stabilized by sRNA154. Overall, we propose that sRNA154 has a crucial role in N-metabolism in M. mazei and allows a feed forward regulation of nif-gene expression by stabilizing nrpA mRNA.
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Project description:Benedict2011 - Genome-scale metoblic network
of Methanosarcina acetivorans (iMB745)
This model is described in the article:
Genome-scale metabolic
reconstruction and hypothesis testing in the methanogenic
archaeon Methanosarcina acetivorans C2A.
Benedict MN, Gonnerman MC, Metcalf
WW, Price ND.
J. Bacteriol. 2012 Feb; 194(4):
855-865
Abstract:
Methanosarcina acetivorans strain C2A is a marine
methanogenic archaeon notable for its substrate utilization,
genetic tractability, and novel energy conservation mechanisms.
To help probe the phenotypic implications of this organism's
unique metabolism, we have constructed and manually curated a
genome-scale metabolic model of M. acetivorans, iMB745, which
accounts for 745 of the 4,540 predicted protein-coding genes
(16%) in the M. acetivorans genome. The reconstruction effort
has identified key knowledge gaps and differences in peripheral
and central metabolism between methanogenic species. Using flux
balance analysis, the model quantitatively predicts wild-type
phenotypes and is 96% accurate in knockout lethality
predictions compared to currently available experimental data.
The model was used to probe the mechanisms and energetics of
by-product formation and growth on carbon monoxide, as well as
the nature of the reaction catalyzed by the soluble
heterodisulfide reductase HdrABC in M. acetivorans. The
genome-scale model provides quantitative and qualitative
hypotheses that can be used to help iteratively guide
additional experiments to further the state of knowledge about
methanogenesis.
This model is hosted on
BioModels Database
and identified by:
MODEL1507180040.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2024-10-15 | MODEL1507180040 | BioModels
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