Metabolite secretion in microorganisms: the theory of metabolic overflow put to the test.

INTRODUCTION: Microbial cells secrete many metabolites during growth, including important intermediates of the central carbon metabolism. This has not been taken into account by researchers when modeling microbial metabolism for metabolic engineering and systems biology studies. MATERIALS AND METHODS: The uptake of metabolites by microorganisms is well studied, but our knowledge of how and why they secrete different intracellular compounds is poor. The secretion of metabolites by microbial cells has traditionally been regarded as a consequence of intracellular metabolic overflow. CONCLUSIONS: Here, we provide evidence based on time-series metabolomics data that microbial cells eliminate some metabolites in response to environmental cues, independent of metabolic overflow. Moreover, we review the different mechanisms of metabolite secretion and explore how this knowledge can benefit metabolic modeling and engineering.

Challenges in integrating Escherichia coli molecular biology data.

One key challenge in Systems Biology is to provide mechanisms to collect and integrate the necessary data to be able to meet multiple analysis requirements. Typically, biological contents are scattered over multiple data sources and there is no easy way of comparing heterogeneous data contents. This work discusses ongoing standardisation and interoperability efforts and exposes integration challenges for the model organism Escherichia coli K-12. The goal is to analyse the major obstacles faced by integration processes, suggest ways to systematically identify them, and whenever possible, propose solutions or means to assist manual curation. Integration of gene, protein and compound data was evaluated by performing comparisons over EcoCyc, KEGG, BRENDA, ChEBI, Entrez Gene and UniProt contents. Cross-links, a number of standard nomenclatures and name information supported the comparisons. Except for the gene integration scenario, in no other scenario an element of integration performed well enough to support the process by itself. Indeed, both the integration of enzyme and compound records imply considerable curation. Results evidenced that, even for a well-studied model organism, source contents are still far from being as standardized as it would be desired and metadata varies considerably from source to source. Before designing any data integration pipeline, researchers should decide on the sources that best fit the purpose of analysis and be aware of existing conflicts/inconsistencies to be able to intervene in their resolution. Moreover, they should be aware of the limits of automatic integration such that they can define the extent of necessary manual curation for each application.

Semantic annotation of biological concepts interplaying microbial cellular responses.

BACKGROUND: Automated extraction systems have become a time saving necessity in Systems Biology. Considerable human effort is needed to model, analyse and simulate biological networks. Thus, one of the challenges posed to Biomedical Text Mining tools is that of learning to recognise a wide variety of biological concepts with different functional roles to assist in these processes. RESULTS: Here, we present a novel corpus concerning the integrated cellular responses to nutrient starvation in the model-organism Escherichia coli. Our corpus is a unique resource in that it annotates biomedical concepts that play a functional role in expression, regulation and metabolism. Namely, it includes annotations for genetic information carriers (genes and DNA, RNA molecules), proteins (transcription factors, enzymes and transporters), small metabolites, physiological states and laboratory techniques. The corpus consists of 130 full-text papers with a total of 59043 annotations for 3649 different biomedical concepts; the two dominant classes are genes (highest number of unique concepts) and compounds (most frequently annotated concepts), whereas other important cellular concepts such as proteins account for no more than 10% of the annotated concepts. CONCLUSIONS: To the best of our knowledge, a corpus that details such a wide range of biological concepts has never been presented to the text mining community. The inter-annotator agreement statistics provide evidence of the importance of a consolidated background when dealing with such complex descriptions, the ambiguities naturally arising from the terminology and their impact for modelling purposes.Availability is granted for the full-text corpora of 130 freely accessible documents, the annotation scheme and the annotation guidelines. Also, we include a corpus of 340 abstracts.

@Note: a workbench for biomedical text mining.

Biomedical Text Mining (BioTM) is providing valuable approaches to the automated curation of scientific literature. However, most efforts have addressed the benchmarking of new algorithms rather than user operational needs. Bridging the gap between BioTM researchers and biologists' needs is crucial to solve real-world problems and promote further research. We present @Note, a platform for BioTM that aims at the effective translation of the advances between three distinct classes of users: biologists, text miners and software developers. Its main functional contributions are the ability to process abstracts and full-texts; an information retrieval module enabling PubMed search and journal crawling; a pre-processing module with PDF-to-text conversion, tokenisation and stopword removal; a semantic annotation schema; a lexicon-based annotator; a user-friendly annotation view that allows to correct annotations and a Text Mining Module supporting dataset preparation and algorithm evaluation. @Note improves the interoperability, modularity and flexibility when integrating in-home and open-source third-party components. Its component-based architecture allows the rapid development of new applications, emphasizing the principles of transparency and simplicity of use. Although it is still on-going, it has already allowed the development of applications that are currently being used.

Reconstruction of a genome-scale metabolic model for Actinobacillus succinogenes 130Z.

BACKGROUND: Actinobacillus succinogenes is a promising bacterial catalyst for the bioproduction of succinic acid from low-cost raw materials. In this work, a genome-scale metabolic model was reconstructed and used to assess the metabolic capabilities of this microorganism under producing conditions. RESULTS: The model, iBP722, was reconstructed based on the functional reannotation of the complete genome sequence of A. succinogenes 130Z and manual inspection of metabolic pathways, covering 1072 enzymatic reactions associated with 722 metabolic genes that involve 713 metabolites. The highly curated model was effective in capturing the growth of A. succinogenes on various carbon sources, as well as the SA production under various growth conditions with fair agreement between experimental and predicted data. Calculated flux distributions under different conditions show that a number of metabolic pathways are affected by the activity of some metabolic enzymes at key nodes in metabolism, including the transport mechanism of carbon sources and the ability to fix carbon dioxide. CONCLUSIONS: The established genome-scale metabolic model can be used for model-driven strain design and medium alteration to improve succinic acid yields.

A Comparative Proteome Analysis of Escherichia coli ΔrelA Mutant Cells.

The bacterial RelA-dependent stringent response exerts a strong influence over various processes. In this work, the impact of the relA gene mutation in Escherichia coli cells was evaluated by a quantitative proteomics analysis, employing stable-isotope labeling and high-resolution mass spectrometry. Chemostat cultures of E. coli W3110 and ΔrelA mutant strains were performed at two dilution rates (0.1 and 0.2 h-1) to assess the influence of the relA gene mutation in steady-state protein levels. A total of 121 proteins showed significant alterations in their abundance when comparing the proteome of mutant to wild-type cells. The relA gene mutation induced changes on key cellular processes, including the amino acids and nucleotide biosynthesis, the lipid metabolism, transport activities, transcription and translation processes, and responses to stress. Furthermore, some of those changes were more pronounced under specific growth conditions, as the most significant differences in protein ratios were observed at one of the dilution rates. An effect of the relA gene mutation in the acetate overflow was also observed, which confers interesting characteristics to this mutant strain that could be useful in the production of recombinant proteins. Overall, these results provide a valuable insight into the E. coli stringent response under defined steady-state conditions, suggesting that this stress response might influence multiple metabolic processes like the acetate overflow or the catabolite repression.

Yeast metabolomics: sample preparation for a GC/MS-based analysis.

Metabolome sample preparation is one of the key factors in metabolomics analyses. The quality of the metabolome data will depend on the suitability of the experimental procedures to the cellular system (e.g., yeast cells) and the analytical performance. Here, we summarize a protocol for metabolome analysis of yeast cells using gas chromatography-mass spectrometry (GC-MS). First, the main phases of a metabolomics analysis are identified: sample preparation, metabolite extraction, and analysis. We also provide an overview on different methods used to quench samples and extract intracellular metabolites from yeast cells. This protocol provides a detailed description of a GC-MS-based analysis of yeast metabolome, in particular for metabolites containing amino and/or carboxyl groups, which represent most of the compounds participating in the central carbon metabolism.

Metabolic responses to recombinant bioprocesses in Escherichia coli.

Escherichia coli has been widely used for the production of recombinant proteins. However, the unbalances between host metabolism and recombinant biosynthesis continue to hamper the efficiency of these recombinant bioprocesses. The additional drainage of biosynthetic precursors toward recombinant processes burdens severely the metabolism of cells that, ultimately, elicits a series of stress responses, reducing biomass growth and recombinant protein production. Several strategies to overcome these metabolic limitations have been implemented; however, in most cases, improvements in recombinant protein expression were achieved at the expense of biomass growth arrest, which significantly hampers the efficiency of recombinant bioprocesses. With the advent of high throughput techniques and modelling approaches that provide a system-level understanding of the cellular systems, it is now expected that new advances in recombinant bioprocesses are achieved. By providing means to deal with these systems, our understanding on the metabolic behaviour of recombinant cells will advance and can be further explored to the design of suitable hosts and more efficient and cost-effective bioprocesses. Here, we review the major metabolic responses associated with recombinant processes and the engineering strategies relevant to overcome these stresses. Moreover, the advantages of applying systems levels engineering strategies to enhance recombinant protein production in E. coli cells are discussed and future perspectives on the advances of mathematical modelling approaches to study these systems are exposed.

Influence of the RelA Activity on E. coli Metabolism by Metabolite Profiling of Glucose-Limited Chemostat Cultures.

Metabolite profiling of E. coli W3110 and the isogenic DrelA mutant cells was used to characterize the RelA-dependent stringent control of metabolism under different growth conditions. Metabolic profiles were obtained by gas chromatography-mass spectrometry (GC-MS) analysis and revealed significant differences between E. coli strains grown at different conditions. Major differences between the two strains were assessed in the levels of amino acids and fatty acids and their precursor metabolites, especially when growing at the lower dilution rates, demonstrating differences in their metabolic behavior. Despite the fatty acid biosynthesis being the most affected due to the lack of the RelA activity, other metabolic pathways involving succinate, lactate and threonine were also affected. Overall, metabolite profiles indicate that under nutrient-limiting conditions the RelA-dependent stringent response may be elicited and promotes key changes in the E. coli metabolism.

Stringent response of Escherichia coli: revisiting the bibliome using literature mining.

BACKGROUND: Understanding the mechanisms responsible for cellular responses depends on the systematic collection and analysis of information on the main biological concepts involved. Indeed, the identification of biologically relevant concepts in free text, namely genes, tRNAs, mRNAs, gene products and small molecules, is crucial to capture the structure and functioning of different responses. RESULTS: In this work, we review literature reports on the study of the stringent response in Escherichia coli. Rather than undertaking the development of a highly specialised literature mining approach, we investigate the suitability of concept recognition and statistical analysis of concept occurrence as means to highlight the concepts that are most likely to be biologically engaged during this response. The co-occurrence analysis of core concepts in this stringent response, i.e. the (p)ppGpp nucleotides with gene products was also inspected and suggest that besides the enzymes RelA and SpoT that control the basal levels of (p)ppGpp nucleotides, many other proteins have a key role in this response. Functional enrichment analysis revealed that basic cellular processes such as metabolism, transcriptional and translational regulation are central, but other stress-associated responses might be elicited during the stringent response. In addition, the identification of less annotated concepts revealed that some (p)ppGpp-induced functional activities are still overlooked in most reviews. CONCLUSIONS: In this paper we applied a literature mining approach that offers a more comprehensive analysis of the stringent response in E. coli. The compilation of relevant biological entities to this stress response and the assessment of their functional roles provided a more systematic understanding of this cellular response. Overlooked regulatory entities, such as transcriptional regulators, were found to play a role in this stress response. Moreover, the involvement of other stress-associated concepts demonstrates the complexity of this cellular response.

Metabolic footprint analysis of recombinant Escherichia coli strains during fed-batch fermentations.

Metabolic footprinting has become a valuable analytical approach for the characterization of phenotypes and the distinction of specific metabolic states resulting from environmental and/or genetic alterations. The metabolic impact of heterologous protein production in Escherichia coli cells is of particular interest, since there are numerous cellular stresses triggered during this process that limit the overall productivity, e.g. the stringent response. Because the knowledge on the metabolic responses in recombinant bioprocesses is still scarce, metabolic footprinting can provide relevant information on the intrinsic metabolic adjustments. Thus, the metabolic footprints generated by E. coli W3110 and the ΔrelA mutant strain during recombinant fed-batch fermentations at different experimental conditions were measured and interpreted. The IPTG-induction of the heterologous protein expression resulted in the rapid accumulation of inhibitors of the glyoxylate shunt in the culture broth, suggesting the clearance of this anaplerotic route to replenish the TCA intermediaries withdrawn for the additional formation of the heterologous protein. Nutritional shifts were also critical in the recombinant cellular metabolism, indicating that cells employ diverse strategies to counteract imbalances in the cellular metabolism, including the secretion of certain metabolites that are, most likely, used as a metabolic relief to survival processes.

A study of the short and long-term regulation of E. coli metabolic pathways.

The present study addresses the regulatory network of Escherichia coli and offers a global view of the short- and long-term regulation of its metabolic pathways. The regulatory mechanisms responsible for key metabolic activities and the structure behind such mechanisms are detailed. Most metabolic functions are dependent on the activity of transcriptional regulators over gene expression--the so-called long-term regulation. However, enzymatic regulation--the so-called short-term regulation--often overlays transcriptional regulation and even, in particular metabolic pathways, enzymatic regulation may prevail. As such, understanding the balance between these two types of regulation is necessary to be able to predict and control cell responses, specifically cell responses to the various environmental stresses.

Assessment of physiological conditions in E. coli fermentations by epifluorescent microscopy and image analysis.

The development of monitoring methods for assessing the physiological state of microorganisms during recombinant fermentation processes has been encouraged by the need to evaluate the influence of processing conditions in recombinant protein production. In this work, a technique based on microscopy and image analysis was developed that allows the simultaneous quantification of parameters associated with viability and fluorescent protein production in recombinant Escherichia coli fermentations. Images obtained from light microscopy with phase contrast are used to assess the total number of cells in a given sample and, from epifluorescence microscopy, both protein producing and injured cells are evaluated using two different fluorochromes: propidium iodide and enhanced yellow fluorescent protein. This technique revealed the existence of different cell populations in the recombinant E. coli fermentation broth that were evaluated along four batch fermentations, complementing information obtained with standard techniques to study the effects of the temperature and induction time in recombinant protein production processes.

A dimensão ambiental dos currículos escolares / The environental dimension of school curricula

O artigo parte de pressupostos e condições fundamentais para a inserção da dimensão ambiental nos currículos da educação escolar nos âmbitos de seus objetivos, conteúdos programáticos, procedimentos de ensino e avaliação da aprendizagem(AU)