Kaspar Valgepea

Systems biology approach reveals that overflow metabolism of acetate in Escherichia coli is triggered by carbon catabolite repression of acetyl-CoA synthetase

BackgroundThe biotechnology industry has extensively exploited Escherichia coli for producing recombinant proteins, biofuels etc. However, high growth rate aerobic E. coli cultivations are accompanied by acetate excretion i.e. overflow metabolism which is harmful as it inhibits growth, diverts valuable carbon from biomass formation and is detrimental for target product synthesis. Although overflow metabolism has been studied for decades, its regulation mechanisms still remain unclear.ResultsIn the current work, growth rate dependent acetate overflow metabolism of E. coli was continuously monitored using advanced continuous cultivation methods (A-stat and D-stat). The first step in acetate overflow switch (at μ = 0.27 ± 0.02 h-1) is the repression of acetyl-CoA synthethase (Acs) activity triggered by carbon catabolite repression resulting in decreased assimilation of acetate produced by phosphotransacetylase (Pta), and disruption of the PTA-ACS node. This was indicated by acetate synthesis pathways PTA-ACKA and POXB component expression down-regulation before the overflow switch at μ = 0.27 ± 0.02 h-1 with concurrent 5-fold stronger repression of acetate-consuming Acs. This in turn suggests insufficient Acs activity for consuming all the acetate produced by Pta, leading to disruption of the acetate cycling process in PTA-ACS node where constant acetyl phosphate or acetate regeneration is essential for E. coli chemotaxis, proteolysis, pathogenesis etc. regulation. In addition, two-substrate A-stat and D-stat experiments showed that acetate consumption capability of E. coli decreased drastically, just as Acs expression, before the start of overflow metabolism. The second step in overflow switch is the sharp decline in cAMP production at μ = 0.45 h-1 leading to total Acs inhibition and fast accumulation of acetate.ConclusionThis study is an example of how a systems biology approach allowed to propose a new regulation mechanism for overflow metabolism in E. coli shown by proteomic, transcriptomic and metabolomic levels coupled to two-phase acetate accumulation: acetate overflow metabolism in E. coli is triggered by Acs down-regulation resulting in decreased assimilation of acetic acid produced by Pta, and disruption of the PTA-ACS node.

Comparison and applications of label-free absolute proteome quantification methods on Escherichia coli.

Three different label-free proteome quantification methods--APEX, emPAI and iBAQ--were evaluated to measure proteome-wide protein concentrations in the cell. All the methods were applied to a sample from Escherichia coli chemostat culture. A Pearson squared correlation of approximately 0.6 among the three quantification methods was demonstrated. Importantly, the sum of quantified proteins by iBAQ and emPAI corresponded with the Lowry total protein quantification, demonstrating applicability of label-free methods for an accurate calculation of protein concentrations at the proteome level. The iBAQ method showed the best correlation between biological replicates, a normal distribution among all protein abundances, and the lowest variation among ribosomal protein abundances, which are expected to have equal amounts. Absolute quantitative proteome data enabled us to evaluate metabolic cost for protein synthesis and apparent catalytic activities of enzymes by integration with flux analysis. All the methods demonstrated similar ATP costs for protein synthesis for different cellular processes and that costs for expressing biomass synthesis related proteins were higher than those for energy generation. Importantly, catalytic activities of energy metabolism enzymes were an order or two higher than those of monomer synthesis. Interestingly, a staircase-like protein expression was demonstrated for most of the transcription units.

Specific growth rate dependent transcriptome profiling of Escherichia coli K12 MG1655 in accelerostat cultures

Specific growth rate dependent gene expression changes of Escherichia coli K12 MG1655 were studied by microarray and real-time PCR analyses. The bacteria were cultivated on glucose limited minimal medium using the accelerostat method (A-stat) where starting from steady state conditions (chemostat culture) dilution rate is constantly increased. At specific growth rate (mu) 0.47h(-1), E. coli had focused its metabolism to glucose utilization by down-regulation of alternative substrate transporters expression compared to mu=0.3h(-1). It was found that acetic acid accumulation began at mu=0.34+/-0.01h(-1) and two acetate synthesis pathways - phosphotransacetylase-acetate kinase (pta-ackA) and pyruvate oxidase (poxB) - contributed to the synthesis at the beginning of overflow metabolism, i.e. onset of acetate excretion. On the other hand, poxB, pta and ackA expression patterns suggest that pyruvate oxidase may be the only enzyme synthesizing acetate at mu=0.47h(-1). Loss of glucose and acetate co-utilization represented by down-regulation of acs-yjcH-actP operon between specific growth rates 0.3-0.42h(-1) and acetic acid accumulation from mu=0.34+/-0.01h(-1) allows one to surmise that the acetate utilization operon expression might play an important role in overflow metabolism.

Decrease of energy spilling in Escherichia coli continuous cultures with rising specific growth rate and carbon wasting

BackgroundGrowth substrates, aerobic/anaerobic conditions, specific growth rate (μ) etc. strongly influence Escherichia coli cell physiology in terms of cell size, biomass composition, gene and protein expression. To understand the regulation behind these different phenotype properties, it is useful to know carbon flux patterns in the metabolic network which are generally calculated by metabolic flux analysis (MFA). However, rarely is biomass composition determined and carbon balance carefully measured in the same experiments which could possibly lead to distorted MFA results and questionable conclusions. Therefore, we carried out both detailed carbon balance and biomass composition analysis in the same experiments for more accurate quantitative analysis of metabolism and MFA.ResultsWe applied advanced continuous cultivation methods (A-stat and D-stat) to continuously monitor E. coli K-12 MG1655 flux and energy metabolism dynamic responses to change of μ and glucose-acetate co-utilisation. Surprisingly, a 36% reduction of ATP spilling was detected with increasing μ and carbon wasting to non-CO2 by-products under constant biomass yield. The apparent discrepancy between constant biomass yield and decline of ATP spilling could be explained by the rise of carbon wasting from 3 to 11% in the carbon balance which was revealed by the discovered novel excretion profile of E. coli pyrimidine pathway intermediates carbamoyl-phosphate, dihydroorotate and orotate. We found that carbon wasting patterns are dependent not only on μ, but also on glucose-acetate co-utilisation capability. Accumulation of these compounds was coupled to the two-phase acetate accumulation profile. Acetate overflow was observed in parallel with the reduction of TCA cycle and glycolysis fluxes, and induction of pentose phosphate pathway.ConclusionsIt can be concluded that acetate metabolism is one of the major regulating factors of central carbon metabolism. More importantly, our model calculations with actual biomass composition and detailed carbon balance analysis in steady state conditions with -omics data comparison demonstrate the importance of a comprehensive systems biology approach for more advanced understanding of metabolism and carbon re-routing mechanisms potentially leading to more successful metabolic engineering.

Stock culture heterogeneity rather than new mutational variation complicates short-term cell physiology studies of Escherichia coli K-12 MG1655 in continuous culture

Nutrient-limited continuous cultures in chemostats have been used to study microbial cell physiology for over 60 years. Genome instability and genetic heterogeneity are possible uncontrolled factors in continuous cultivation experiments. We investigated these issues by using high-throughput (HT) DNA sequencing to characterize samples from different phases of a glucose-limited accelerostat (A-stat) experiment with Escherichia coli K-12 MG1655 and a duration regularly used in cell physiology studies (20 generations of continuous cultivation). Seven consensus mutations from the reference sequence and five subpopulations characterized by different mutations were detected in the HT-sequenced samples. This genetic heterogeneity was confirmed to result from the stock culture by Sanger sequencing. All the subpopulations in which allele frequencies increased (betA, cspG/cspH, glyA) during the experiment were also present at the end of replicate A-stats, indicating that no new subpopulations emerged during our experiments. The fact that ~31 % of the cells in our initial cultures obtained directly from a culture stock centre were mutants raises concerns that even if cultivations are started from single colonies, there is a significant chance of picking a mutant clone with an altered phenotype. Our results show that current HT DNA sequencing technology allows accurate subpopulation analysis and demonstrates that a glucose-limited E. coli K-12 MG1655 A-stat experiment with a duration of tens of generations is suitable for studying cell physiology and collecting quantitative data for metabolic modelling without interference from new mutations.

Advanced continuous cultivation methods for systems microbiology.

Increasing the throughput of systems biology-based experimental characterization of in silico-designed strains has great potential for accelerating the development of cell factories. For this, analysis of metabolism in the steady state is essential as only this enables the unequivocal definition of the physiological state of cells, which is needed for the complete description and in silico reconstruction of their phenotypes. In this review, we show that for a systems microbiology approach, high-resolution characterization of metabolism in the steady state--growth space analysis (GSA)--can be achieved by using advanced continuous cultivation methods termed changestats. In changestats, an environmental parameter is continuously changed at a constant rate within one experiment whilst maintaining cells in the physiological steady state similar to chemostats. This increases the resolution and throughput of GSA compared with chemostats, and, moreover, enables following of the dynamics of metabolism and detection of metabolic switch-points and optimal growth conditions. We also describe the concept, challenge and necessary criteria of the systematic analysis of steady-state metabolism. Finally, we propose that such systematic characterization of the steady-state growth space of cells using changestats has value not only for fundamental studies of metabolism, but also for systems biology-based metabolic engineering of cell factories.

Lean-proteome strains - next step in metabolic engineering.

Rapid development of high-throughput -omics (e.g., proteomics) and genetic engineering technologies together with an array of new metabolic modeling tools during this century has led to the emergence of new fields of biological research termed systems biology and synthetic biology. The successful exploitation of these developments is evidenced by the creation of increasing number of genetically engineered recombinant cells with superior characteristics (Jantama et al., 2008; Becker et al., 2011) or totally novel functions (Nakamura and Whited, 2003; Yim et al., 2011; Paddon et al., 2013) for diverse sectors such as chemicals and healthcare (Huang et al., 2012; Lee et al., 2012; Sun and Alper, 2014). However, there exists a significant gap in bioprocess performance between studies of the literature and the requirements for an industrially feasible bioprocess for chemical production (Van Dien, 2013). Overall bioprocess performance [productivity (gram/liter/hour), titer (gram/liter) etc.] has to be increased further for successful industrial-scale commercialization to drive the shift from fossil fuel to bioprocess-based chemical production and cost-effective production of novel drugs (Van Dien, 2013). Hence, there is great need for novel approaches addressing these key challenges in chemical and healthcare sectors.

Integrating gene and protein expression data with genome-scale metabolic networks to infer functional pathways

BackgroundThe study of cellular metabolism in the context of high-throughput -omics data has allowed us to decipher novel mechanisms of importance in biotechnology and health. To continue with this progress, it is essential to efficiently integrate experimental data into metabolic modeling.ResultsWe present here an in-silico framework to infer relevant metabolic pathways for a particular phenotype under study based on its gene/protein expression data. This framework is based on the Carbon Flux Path (CFP) approach, a mixed-integer linear program that expands classical path finding techniques by considering additional biophysical constraints. In particular, the objective function of the CFP approach is amended to account for gene/protein expression data and influence obtained paths. This approach is termed integrative Carbon Flux Path (iCFP). We show that gene/protein expression data also influences the stoichiometric balancing of CFPs, which provides a more accurate picture of active metabolic pathways. This is illustrated in both a theoretical and real scenario. Finally, we apply this approach to find novel pathways relevant in the regulation of acetate overflow metabolism in Escherichia coli. As a result, several targets which could be relevant for better understanding of the phenomenon leading to impaired acetate overflow are proposed.ConclusionsA novel mathematical framework that determines functional pathways based on gene/protein expression data is presented and validated. We show that our approach is able to provide new insights into complex biological scenarios such as acetate overflow in Escherichia coli.