Transcriptome Complexity in a Genome-Reduced Bacterium

Güell, Marc; Noort, Vera van; Yus, Eva; Chen, Wei‐Hua; Leigh-Bell, Justine; Michalodimitrakis, Konstantinos; Yamada, Takuji; Arumugam, Manimozhiyan; Doerks, Tobias; Kühner, Sebastian; Rode, Michaela; Suyama, Mikita; Schmidt, Steffen; Gavin, Anne‐Claude; Bork, Peer; Serrano, Luís

doi:10.1126/science.1176951

Cited by 380 publications

(433 citation statements)

References 33 publications

Supporting

Mentioning

410

Contrasting

Order By: Relevance

“…However, this simplicity has been challenged by the widespread use of high-resolution transcriptome mapping technologies [1,2]. Identification of overlapping genomic elements revealed modular operon organization that allows for conditional co-modulation of genes in bacteria and archaea [3,4]. Abundant transcript signals established pervasive transcription as a general phenomenon, expanding our knowledge on the universe of non-coding RNAs [5].…”

Section: Introductionmentioning

confidence: 99%

Internal RNAs overlapping coding sequences can drive the production of alternative proteins in archaea

et al. 2018

View full text Add to dashboard Cite

Prokaryotic genomes show a high level of information compaction often with different molecules transcribed from the same locus. Although antisense RNAs have been relatively well studied, RNAs in the same strand, internal RNAs (intraRNAs), are still poorly understood. The question of how common is the translation of overlapping reading frames remains open. We address this question in the model archaeon Halobacterium salinarum. In the present work we used differential RNA-seq (dRNA-seq) in H. salinarum NRC-1 to locate intraRNA signals in subsets of internal transcription start sites (iTSS) and establish the open reading frames associated to them (intraORFs). Using C-terminally flagged proteins, we experimentally observed isoforms accurately predicted by intraRNA translation for kef1, acs3 and orc4 genes. We also recovered from the literature and mass spectrometry databases several instances of protein isoforms consistent with intraRNA translation such as the gas vesicle protein gene gvpC1. We found evidence for intraRNAs in horizontally transferred genes such as the chaperone dnaK and the aerobic respiration related cydA in both H. salinarum and Escherichia coli. Also, intraRNA translation evidence in H. salinarum, E. coli and yeast of a universal elongation factor (aEF-2, fusA and eEF-2) suggests that this is an ancient phenomenon present in all domains of life.

show abstract

Section: Introductionmentioning

confidence: 99%

Internal RNAs overlapping coding sequences can drive the production of alternative proteins in archaea

et al. 2018

View full text Add to dashboard Cite

show abstract

“…Our results provide insight into: (1) sequence characteristics, such as the uniqueness and vast diversity, of microbial community transcriptomes in the open ocean ecosystem; (2) specific metabolic processes that characterize each of the four habitats investigated; (3) highly expressed gene families, and their putative taxonomic breakdown; and (4) population variability and physiological signals from abundant taxa of the microbial assemblages, inferred via reference genome-centric analyses. Given the great complexity found in the transcriptome of even small genomes (Guell et al, 2009), it must be assumed that we are at present just scratching the surface of the dynamic, complex transcriptional network orchestrated by microbemicrobe and microbe-environment interactions. Future metagenomic and metatranscriptomic surveys at more highly resolved spatial and temporal dimensions will help to provide a more comprehensive picture of microbial functional diversity in natural settings.…”

Section: Discussionmentioning

confidence: 99%

Integrated metatranscriptomic and metagenomic analyses of stratified microbial assemblages in the open ocean

et al. 2010

View full text Add to dashboard Cite

As part of an ongoing survey of microbial community gene expression in the ocean, we sequenced and compared B38 Mbp of community transcriptomes and B157 Mbp of community genomes from four bacterioplankton samples, along a defined depth profile at Station ALOHA in North Pacific subtropical gyre (NPSG). Taxonomic analysis suggested that the samples were dominated by three taxa: Prochlorales, Consistiales and Cenarchaeales, which comprised 36-69% and 29-63% of the annotated sequences in the four DNA and four cDNA libraries, respectively. The relative abundance of these taxonomic groups was sometimes very different in the DNA and cDNA libraries, suggesting differential relative transcriptional activities per cell. For example, the 125 m sample genomic library was dominated by Pelagibacter (B36% of sequence reads), which contributed fewer sequences to the community transcriptome (B11%). Functional characterization of highly expressed genes suggested taxon-specific contributions to specific biogeochemical processes. Examples included Roseobacter relatives involved in aerobic anoxygenic phototrophy at 75 m, and an unexpected contribution of low abundance Crenarchaea to ammonia oxidation at 125 m. Read recruitment using reference microbial genomes indicated depth-specific partitioning of coexisting microbial populations, highlighted by a transcriptionally active high-light-like Prochlorococcus population in the bottom of the photic zone. Additionally, nutrient-uptake genes dominated Pelagibacter transcripts, with apparent enrichment for certain transporter types (for example, the C4-dicarboxylate transport system) over others (for example, phosphate transporters). In total, the data support the utility of coupled DNA and cDNA analyses for describing taxonomic and functional attributes of microbial communities in their natural habitats.

show abstract

“…Recently, the complexity of transcription unit architecture was investigated by several groups (42)(43)(44). The presence of these transcriptional units results in a more complicated model of gene expression, compared with the classical operon model.…”

Section: Assessment Of the Prediction Accuracy Of Fba With Grouping Rmentioning

confidence: 99%

Prediction of metabolic fluxes by incorporating genomic context and flux-converging pattern analyses

Park

Kim

Lee

2010

Proc. Natl. Acad. Sci. U.S.A.

View full text Add to dashboard Cite

Flux balance analysis (FBA) of a genome-scale metabolic model allows calculation of intracellular fluxes by optimizing an objective function, such as maximization of cell growth, under given constraints, and has found numerous applications in the field of systems biology and biotechnology. Due to the underdetermined nature of the system, however, it has limitations such as inaccurate prediction of fluxes and existence of multiple solutions for an optimal objective value. Here, we report a strategy for accurate prediction of metabolic fluxes by FBA combined with systematic and conditionindependent constraints that restrict the achievable flux ranges of grouped reactions by genomic context and flux-converging pattern analyses. Analyses of three types of genomic contexts, conserved genomic neighborhood, gene fusion events, and co-occurrence of genes across multiple organisms, were performed to suggest a group of fluxes that are likely on or off simultaneously. The flux ranges of these grouped reactions were constrained by flux-converging pattern analysis. FBA of the Escherichia coli genome-scale metabolic model was carried out under several different genotypic (pykF, zwf, ppc, and sucA mutants) and environmental (altered carbon source) conditions by applying these constraints, which resulted in flux values that were in good agreement with the experimentally measured 13 C-based fluxes. Thus, this strategy will be useful for accurately predicting the intracellular fluxes of large metabolic networks when their experimental determination is difficult.Escherichia coli | flux balance analysis | grouping reaction constraints | 13 C-based flux | genome-scale metabolic model T he accumulation of omics data, including genome, transcriptome, proteome, metabolome, and fluxome, provides an opportunity to understand cellular physiology and characteristics at multiple levels (1, 2). Among them, the fluxome profiling allows quantification of metabolic fluxes, which collectively represent the cellular metabolic characteristics. For successful metabolic engineering, it is important to understand and predict the changes of metabolic fluxes after modifying interesting genes, pathways, and regulatory circuits. On the basis of systems-level understanding of cellular status through fluxome profiling, rational and systematic development of an improved strain becomes possible (3-6).One of the popular methods that has been used to examine cellular metabolic fluxes and predict their changes in perturbed conditions is flux balance analysis (FBA) (7-12). To calculate the optimal flux distribution in the multidimensional flux solution space of metabolic network, FBA optimizes an objective function, such as maximizing cell growth rate, under pseudosteady state with mass balance and other constraints (13). Given the fact that the information used to reconstruct the metabolic networks is incomplete, multiple equivalent solutions can be computed for the states of these networks (14). One method that has been presented to overcome the problem of mul...

show abstract

Transcriptome Complexity in a Genome-Reduced Bacterium

Cited by 380 publications

References 33 publications

Internal RNAs overlapping coding sequences can drive the production of alternative proteins in archaea

Internal RNAs overlapping coding sequences can drive the production of alternative proteins in archaea

Integrated metatranscriptomic and metagenomic analyses of stratified microbial assemblages in the open ocean

Prediction of metabolic fluxes by incorporating genomic context and flux-converging pattern analyses

Contact Info

Product

Resources

About