Control analysis as a tool to understand the formation of the las operon in Lactococcus lactis

Trade-offs between the instantaneous growth rate and long-term fitness: Consequences for microbial physiology and predictive computational models

Microbial systems biology has made enormous advances in relating microbial physiology to the underlying biochemistry and molecular biology. By meticulously studying model microorganisms, in particular Escherichia coli and Saccharomyces cerevisiae, increasingly comprehensive computational models predict metabolic fluxes, protein expression, and growth. The modeling rationale is that cells are constrained by a limited pool of resources that they allocate optimally to maximize fitness. As a consequence, the expression of particular proteins is at the expense of others, causing trade-offs between cellular objectives such as instantaneous growth, stress tolerance, and capacity to adapt to new environments. While current computational models are remarkably predictive for E. coli and S. cerevisiae when grown in laboratory environments, this may not hold for other growth conditions and other microorganisms. In this contribution, we therefore discuss the relationship between the instantaneous growth rate, limited resources, and long-term fitness. We discuss uses and limitations of current computational models, in particular for rapidly changing and adverse environments, and propose to classify microbial growth strategies based on Grimes's CSR framework.

Intelligent host engineering for metabolic flux optimisation in biotechnology

Optimising the function of a protein of length N amino acids by directed evolution involves navigating a 'search space' of possible sequences of some 20N. Optimising the expression levels of P proteins that materially affect host performance, each of which might also take 20 (logarithmically spaced) values, implies a similar search space of 20P. In this combinatorial sense, then, the problems of directed protein evolution and of host engineering are broadly equivalent. In practice, however, they have different means for avoiding the inevitable difficulties of implementation. The spare capacity exhibited in metabolic networks implies that host engineering may admit substantial increases in flux to targets of interest. Thus, we rehearse the relevant issues for those wishing to understand and exploit those modern genome-wide host engineering tools and thinking that have been designed and developed to optimise fluxes towards desirable products in biotechnological processes, with a focus on microbial systems. The aim throughput is 'making such biology predictable'. Strategies have been aimed at both transcription and translation, especially for regulatory processes that can affect multiple targets. However, because there is a limit on how much protein a cell can produce, increasing kcat in selected targets may be a better strategy than increasing protein expression levels for optimal host engineering.

Searching for principles of microbial physiology

Why do evolutionarily distinct microorganisms display similar physiological behaviours? Why are transitions from high-ATP yield to low(er)-ATP yield metabolisms so widespread across species? Why is fast growth generally accompanied with low stress tolerance? Do these regularities occur because most microbial species are subject to the same selective pressures and physicochemical constraints? If so, a broadly-applicable theory might be developed that predicts common microbiological behaviours. Microbial systems biologists have been working out the contours of this theory for the last two decades, guided by experimental data. At its foundations lie basic principles from evolutionary biology, enzyme biochemistry, metabolism, cell composition and steady-state growth. The theory makes predictions about fitness costs and benefits of protein expression, physicochemical constraints on cell growth and characteristics of optimal metabolisms that maximise growth rate. Comparisons of the theory with experimental data indicates that microorganisms often aim for maximisation of growth rate, also in the presence of stresses; they often express optimal metabolisms and metabolic proteins at optimal concentrations. This review explains the current status of the theory for microbiologists; its roots, predictions, experimental evidence and future directions.

Identification of Key Metabolites in Poly-γ-Glutamic Acid Production by Tuning γ-PGA Synthetase Expression

Poly-γ-glutamic acid (γ-PGA) production is commonly achieved using glycerol, citrate, and L-glutamic acid as substrates. The constitutive expression of the γ-PGA synthetase enabled γ-PGA production with Bacillus subtilis from glucose only. The precursors for γ-PGA synthesis, D- and L-glutamate, are ubiquitous metabolites. Hence, the metabolic flux toward γ-PGA directly depends on the concentration and activity of the synthetase and thereby on its expression. To identify pathway bottlenecks and important metabolites that are highly correlated with γ-PGA production from glucose, we engineered B. subtilis strains with varying γ-PGA synthesis rates. To alter the rate of γ-PGA synthesis, the expression level was controlled by two approaches: (1) Using promoter variants from the constitutive promoter P veg and (2) Varying induction strength of the xylose inducible promoter P xyl . The variation in the metabolism caused by γ-PGA production was investigated using metabolome analysis. The xylose-induction strategy revealed that the γ-PGA production rate increased the total fluxes through metabolism indicating a driven by demand adaption of the metabolism. Metabolic bottlenecks during γ-PGA from glucose were identified by generation of a model that correlates γ-PGA production rate with intracellular metabolite levels. The generated model indicates the correlation of certain metabolites such as phosphoenolpyruvate with γ-PGA production. The identified metabolites are targets for strain improvement to achieve high level γ-PGA production from glucose.

Systems Biology - A Guide for Understanding and Developing Improved Strains of Lactic Acid Bacteria

Lactic Acid Bacteria (LAB) are extensively employed in the production of various fermented foods, due to their safe status, ability to affect texture and flavor and finally due to the beneficial effect they have on shelf-life. More recently, LAB have also gained interest as production hosts for various useful compounds, particularly compounds with sensitive applications, such as food ingredients and therapeutics. As for all industrial microorganisms, it is important to have a good understanding of the physiology and metabolism of LAB in order to fully exploit their potential, and for this purpose, many systems biology approaches are available. Systems metabolic engineering, an approach that combines optimization of metabolic enzymes/pathways at the systems level, synthetic biology as well as in silico model simulation, has been used to build microbial cell factories for production of biofuels, food ingredients and biochemicals. When developing LAB for use in foods, genetic engineering is in general not an accepted approach. An alternative is to screen mutant libraries for candidates with desirable traits using high-throughput screening technologies or to use adaptive laboratory evolution to select for mutants with special properties. In both cases, by using omics data and data-driven technologies to scrutinize these, it is possible to find the underlying cause for the desired attributes of such mutants. This review aims to describe how systems biology tools can be used for obtaining both engineered as well as non-engineered LAB with novel and desired properties.

Maintaining maximal metabolic flux by gene expression control

One of the marvels of biology is the phenotypic plasticity of microorganisms. It allows them to maintain high growth rates across conditions. Studies suggest that cells can express metabolic enzymes at tuned concentrations through adjustment of gene expression. The associated transcription factors are often regulated by intracellular metabolites. Here we study metabolite-mediated regulation of metabolic-gene expression that maximises metabolic fluxes across conditions. We developed an adaptive control theory, qORAC (for ‘Specific Flux (q) Optimization by Robust Adaptive Control’), and illustrate it with several examples of metabolic pathways. The key feature of the theory is that it does not require knowledge of the regulatory network, only of the metabolic part. We derive that maximal metabolic flux can be maintained in the face of varying N environmental parameters only if the number of transcription-factor binding metabolites is at least equal to N. The controlling circuits appear to require simple biochemical kinetics. We conclude that microorganisms likely can achieve maximal rates in metabolic pathways, in the face of environmental changes.

To attain high growth rates, microorganisms need to sustain high activities of metabolic reactions. Since the catalysing enzymes are in finite supply, cells need to carefully tune their concentrations. When conditions change, cells need to adjust those concentrations. How cells maintain high metabolism rates across conditions by way of gene regulatory mechanisms and whether they can maximise metabolic activity is far from clear. Here we present a general theory that solves this metabolic control problem, which we have called qORAC for specific flux (q) Optimisation by Robust Adaptive Control. It considers that external changes are sensed by internal “sensor” metabolites that bind to transcription factors in order to regulate enzyme-synthesis rates. We show that such a combined system of metabolism and its gene network can self-optimise its metabolic activity across conditions. We present the mathematical conditions for the required adaptive control for robust system-steering to optimal states across conditions. We provide explicit examples of such self-optimising coupled metabolism and gene network systems. We prove that a cell can be robust to changes in K parameters, e.g. external conditions, if at least K internal metabolite concentrations act transcription-factor binding sensors. We find that the optimal relation of the enzyme synthesis rates of self-optimising systems and the concentration of the sensor metabolites can generally be implemented by basic biochemistry. Our results indicate how cells are able to maintain maximal reaction rates, even in changing conditions.

Engineering the glycolytic pathway: A potential approach for improvement of biocatalyst performance

The glycolytic pathway is a main driving force in the fermentation process as it produces energy, cell component precursors, and fermentation products. Given its importance, the glycolytic pathway can be considered as an attractive target for the metabolic engineering of industrial microorganisms. However, many attempts to enhance glycolytic flux, by overexpressing homologous or heterologous genes encoding glycolytic enzymes, have been unsuccessful. In contrast, significant enhancement in glycolytic flux has been observed in studies with bacteria, specifically, Corynebacterium glutamicum. Although there has been a recent increase in the number of successful applications of this technology, little is known about the mechanisms leading to the enhancement of glycolytic flux. To explore the rational applications of glycolytic pathway engineering in biocatalyst development, this review summarizes recent successful studies as well as past attempts.

Physiological and transcriptional responses and cross protection of Lactobacillus plantarum ZDY2013 under acid stress

Acid tolerance responses (ATR) in Lactobacillus plantarum ZDY2013 were investigated at physiological and molecular levels. A comparison of composition of cell membrane fatty acids (CMFA) between acid-challenged and unchallenged cells showed that acid adaptation evoked a significantly higher percentage of saturated fatty acids and cyclopropane fatty acids in acid-challenged than in unchallenged cells. In addition, reverse transcription-quantitative PCR analysis in acid-adapted cells at different pH values (ranging from 3.0 to 4.0) indicated that several genes were differently regulated, including those related to proton pumps, amino acid metabolism, sugar metabolism, and class I and class III stress response pathways. Expression of genes involved in fatty acid synthesis and production of alkali was significantly upregulated. Upon exposure to pH 4.5 for 2 h, a higher survival rate (higher viable cell count) of Lactobacillus plantarum ZDY2013 was achieved following an additional challenge to 40 mM hydrogen peroxide for 60 min, but no difference in survival rate of cells was found with further challenge to heat, ethanol, or salt. Therefore, we concluded that the physiological and metabolic changes of acid-treated cells of Lactobacillus plantarum ZDY2013 help the cells resist damage caused by acid, and further initiated global response signals to bring the whole cell into a state of defense to other stress factors, especially hydrogen peroxide.

Monte-Carlo modeling of the central carbon metabolism of Lactococcus lactis: insights into metabolic regulation

Metabolic pathways are complex dynamic systems whose response to perturbations and environmental challenges are governed by multiple interdependencies between enzyme properties, reactions rates, and substrate levels. Understanding the dynamics arising from such a network can be greatly enhanced by the construction of a computational model that embodies the properties of the respective system. Such models aim to incorporate mechanistic details of cellular interactions to mimic the temporal behavior of the biochemical reaction system and usually require substantial knowledge of kinetic parameters to allow meaningful conclusions. Several approaches have been suggested to overcome the severe data requirements of kinetic modeling, including the use of approximative kinetics and Monte-Carlo sampling of reaction parameters. In this work, we employ a probabilistic approach to study the response of a complex metabolic system, the central metabolism of the lactic acid bacterium Lactococcus lactis, subject to perturbations and brief periods of starvation. Supplementing existing methodologies, we show that it is possible to acquire a detailed understanding of the control properties of a corresponding metabolic pathway model that is directly based on experimental observations. In particular, we delineate the role of enzymatic regulation to maintain metabolic stability and metabolic recovery after periods of starvation. It is shown that the feedforward activation of the pyruvate kinase by fructose-1,6-bisphosphate qualitatively alters the bifurcation structure of the corresponding pathway model, indicating a crucial role of enzymatic regulation to prevent metabolic collapse for low external concentrations of glucose. We argue that similar probabilistic methodologies will help our understanding of dynamic properties of small-, medium- and large-scale metabolic networks models.

NAD-dependent lactate dehydrogenase catalyses the first step in respiratory utilization of lactate by Lactococcus lactis

Lactococcus lactis can undergo respiration when hemin is added to an aerobic culture. The most distinctive feature of lactococcal respiration is that lactate could be consumed in the stationary phase concomitantly with the rapid accumulation of diacetyl and acetoin. However, the enzyme responsible for lactate utilization in this process has not yet been identified. As genes for fermentative NAD-dependent l-lactate dehydrogenase (l-nLDH) and potential electron transport chain (ETC)-related NAD-independent l-LDH (l-iLDH) exist in L. lactis, the activities of these enzymes were measured in this study using crude cell extracts prepared from respiratory and fermentation cultures. Further studies were conducted with purified preparations of recombinant LDH homologous proteins. The results showed that l-iLDH activity was hardly detected in both crude cell extracts and purified l-iLDH homologous protein while l-nLDH activity was very significant. This suggested that l-iLDHs were inactive in lactate utilization. The results of kinetic analyses and the effects of activator, inhibitor, substrate and product concentrations on the reaction equilibrium showed that l-nLDH was much more prone to catalyze the pyruvate reduction reaction but could reverse its role provided that the concentrations of NADH and pyruvate were extremely low while NAD and lactate were abundant. Metabolite analysis in respiratory culture revealed that the cellular status in the stationary phase was beneficial for l-nLDH to catalyze lactate oxidation. The factors accounting for the respiration- and stationary phase-dependent lactate utilization in L. lactis are discussed here.

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LutABC proteins do not participate in lactate oxidation in Lactococcus lactis

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Lactococcus lactis has very low NAD-independent lactate dehydrogenase activity

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Fructose-1,6-bisphosphate-dependent lactate dehydrogenase can work in reverse in vivo

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Metabolite concentrations in the stationary phase are favorable for lactate oxidation

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Respiratory metabolism is the basis for continual lactate oxidation in Lactococcus

Optimality principles in the regulation of metabolic networks

One of the challenging tasks in systems biology is to understand how molecular networks give rise to emergent functionality and whether universal design principles apply to molecular networks. To achieve this, the biophysical, evolutionary and physiological constraints that act on those networks need to be identified in addition to the characterisation of the molecular components and interactions. Then, the cellular "task" of the network-its function-should be identified. A network contributes to organismal fitness through its function. The premise is that the same functions are often implemented in different organisms by the same type of network; hence, the concept of design principles. In biology, due to the strong forces of selective pressure and natural selection, network functions can often be understood as the outcome of fitness optimisation. The hypothesis of fitness optimisation to understand the design of a network has proven to be a powerful strategy. Here, we outline the use of several optimisation principles applied to biological networks, with an emphasis on metabolic regulatory networks. We discuss the different objective functions and constraints that are considered and the kind of understanding that they provide.

Tunable promoters in synthetic and systems biology

Synthetic and systems biologists need standardized, modular and orthogonal tools yielding predictable functions in vivo. In systems biology such tools are needed to quantitatively analyze the behavior of biological systems while the efficient engineering of artificial gene networks is central in synthetic biology. A number of tools exist to manipulate the steps in between gene sequence and functional protein in living cells, but out of these the most straight-forward approach is to alter the gene expression level by manipulating the promoter sequence. Some of the promoter tuning tools available for accomplishing such altered gene expression levels are discussed here along with examples of their use, and ideas for new tools are described. The road ahead looks very promising for synthetic and systems biologists as tools to achieve just about anything in terms of tuning and timing multiple gene expression levels using libraries of synthetic promoters now exist.

Systems biology of lactic acid bacteria: a critical review

Understanding the properties of a system as emerging from the interaction of well described parts is the most important goal of Systems Biology. Although in the practice of Lactic Acid Bacteria (LAB) physiology we most often think of the parts as the proteins and metabolites, a wider interpretation of what a part is can be useful. For example, different strains or species can be the parts of a community, or we could study only the chemical reactions as the parts of metabolism (and forgetting about the enzymes that catalyze them), as is done in flux balance analysis. As long as we have some understanding of the properties of these parts, we can investigate whether their interaction leads to novel or unanticipated behaviour of the system that they constitute.

There has been a tendency in the Systems Biology community to think that the collection and integration of data should continue ad infinitum, or that we will otherwise not be able to understand the systems that we study in their details. However, it may sometimes be useful to take a step back and consider whether the knowledge that we already have may not explain the system behaviour that we find so intriguing. Reasoning about systems can be difficult, and may require the application of mathematical techniques. The reward is sometimes the realization of unexpected conclusions, or in the worst case, that we still do not know enough details of the parts, or of the interactions between them.

We will discuss a number of cases, with a focus on LAB-related work, where a typical systems approach has brought new knowledge or perspective, often counterintuitive, and clashing with conclusions from simpler approaches. Also novel types of testable hypotheses may be generated by the systems approach, which we will illustrate. Finally we will give an outlook on the fields of research where the systems approach may point the way for the near future.

Switch between life history strategies due to changes in glycolytic enzyme gene dosage in Saccharomyces cerevisiae

Adaptation is the process whereby a population or species becomes better fitted to its habitat through modifications of various life history traits which can be positively or negatively correlated. The molecular factors underlying these covariations remain to be elucidated. Using Saccharomyces cerevisiae as a model system, we have investigated the effects on life history traits of varying the dosage of genes involved in the transformation of resources into energy. Changing gene dosage for each of three glycolytic enzyme genes (hexokinase 2, phosphoglucose isomerase, and fructose-1,6-bisphosphate aldolase) resulted in variation in enzyme activities, glucose consumption rate, and life history traits (growth rate, carrying capacity, and cell size). However, the range of effects depended on which enzyme was expressed differently. Most interestingly, these changes revealed a genetic trade-off between carrying capacity and cell size, supporting the discovery of two extreme life history strategies already described in yeast populations: the "ants," which have lower glycolytic gene dosage, take up glucose slowly, and have a small cell size but reach a high carrying capacity, and the "grasshoppers," which have higher glycolytic gene dosage, consume glucose more rapidly, and allocate it to a larger cell size but reach a lower carrying capacity. These results demonstrate antagonist pleiotropy for glycolytic genes and show that altered dosage of a single gene drives a switch between two life history strategies in yeast.

Functional analysis of the role of CggR (central glycolytic gene regulator) in Lactobacillus plantarum by transcriptome analysis

The level of the central glycolytic gene regulator (CggR) was engineered in Lactobacillus plantarum NC8 and WCFS1 by overexpression and in‐frame mutation of the cggR gene in order to evaluate its regulatory role on the glycolytic gap operon and the glycolytic flux. The repressor role of CggR on the gap operon was indicated through identification of a putative CggR operator and transcriptome analysis, which coincided with decreased growth rate and glycolytic flux when cggR was overexpressed in NC8 and WCFS1. The mutation of cggR did not affect regulation of the gap operon, indicating a more prominent regulatory role of CggR on the gap operon under other conditions than tested (e.g. fermentation of other sugars than glucose or ribose) and when the level of the putative effector molecule FBP is reduced. Interestingly, the mutation of cggR had several effects in NC8, i.e. increased growth rate and glycolytic flux and regulation of genes with functions associated with glycerol and pyruvate metabolism; however, no effects were observed in WCFS1. The affected genes in NC8 are presumably regulated by CcpA, since putative CRE sites were identified in their upstream regions. The interconnection with CggR and CcpA‐mediated control on growth and metabolism needs to be further elucidated.

Perspectives on synthetic promoters for biocatalysis and biotransformation

Acting on the transcriptional level, synthetic promoters have been useful tools for controlling gene expression and have applications in many fields. Here, we discuss synthetic promoters and libraries in regard to current and future applications in the field of biocatalysis or biotransformation. We also focus on synthetic promoter design principles and distinguish between prokaryotic and eukaryotic destinations. The natural toolboxes available for tuneable gene expression and the regulation of enzyme function are limited and primarily host specific. Synthetic biology offers generally applicable concepts and quick implementation. Smart alternatives to transcriptional regulation enrich the engineer's tool box for optimizing industrial enzyme production and host-cell physiology for whole-cell processes. Industrially applicable, tuneable enzyme cascades and artificial circuits for iterative up- and down-regulation will soon be achieved.

Systemic properties of metabolic networks lead to an epistasis-based model for heterosis

The genetic and molecular approaches to heterosis usually do not rely on any model of the genotype-phenotype relationship. From the generalization of Kacser and Burns' biochemical model for dominance and epistasis to networks with several variable enzymes, we hypothesized that metabolic heterosis could be observed because the response of the flux towards enzyme activities and/or concentrations follows a multi-dimensional hyperbolic-like relationship. To corroborate this, we used the values of systemic parameters accounting for the kinetic behaviour of four enzymes of the upstream part of glycolysis, and simulated genetic variability by varying in silico enzyme concentrations. Then we "crossed" virtual parents to get 1,000 hybrids, and showed that best-parent heterosis was frequently observed. The decomposition of the flux value into genetic effects, with the help of a novel multilocus epistasis index, revealed that antagonistic additive-by-additive epistasis effects play the major role in this framework of the genotype-phenotype relationship. This result is consistent with various observations in quantitative and evolutionary genetics, and provides a model unifying the genetic effects underlying heterosis.

The Ser/Thr/Tyr phosphoproteome of Lactococcus lactis IL1403 reveals multiply phosphorylated proteins

Recent phosphoproteomics studies of several bacterial species have firmly established protein phosphorylation on Ser/Thr/Tyr residues as a PTM in bacteria. In particular, our recent reports on the Ser/Thr/Tyr phosphoproteomes of bacterial model organisms Bacillus subtilis and Escherichia coli detected over 100 phosphorylation events in each of the bacterial species. Here we extend our analyses to Lactococcus lactis, a lactic acid bacterium widely employed by the food industry, in which protein phosphorylation at Ser/Thr/Tyr residues was barely studied at all. Despite the lack of almost any prior evidence of Ser/Thr/Tyr protein phosphorylation in L. lactis, we identified a phosphoproteome of a size comparable to that of E. coli and B. subtilis, with 73 phosphorylation sites distributed over 63 different proteins. The presence of several multiply phosphorylated proteins, as well as over-representation of phosphothreonines seems to be the distinguishing features of the L. lactis phosphoproteome. Evolutionary comparison and the conservation of phosphorylation sites in different bacterial organisms indicate that a majority of the detected phosphorylation sites are species-specific, and therefore have probably co-evolved with the adaptation of the bacterial species to their present-day ecological niches.

Metabolic control analysis: a tool for designing strategies to manipulate metabolic pathways

The traditional experimental approaches used for changing the flux or the concentration of a particular metabolite of a metabolic pathway have been mostly based on the inhibition or over-expression of the presumed rate-limiting step. However, the attempts to manipulate a metabolic pathway by following such approach have proved to be unsuccessful. Metabolic Control Analysis (MCA) establishes how to determine, quantitatively, the degree of control that a given enzyme exerts on flux and on the concentration of metabolites, thus substituting the intuitive, qualitative concept of rate limiting step. Moreover, MCA helps to understand (i) the underlying mechanisms by which a given enzyme exerts high or low control and (ii) why the control of the pathway is shared by several pathway enzymes and transporters. By applying MCA it is possible to identify the steps that should be modified to achieve a successful alteration of flux or metabolite concentration in pathways of biotechnological (e.g., large scale metabolite production) or clinical relevance (e.g., drug therapy). The different MCA experimental approaches developed for the determination of the flux-control distribution in several pathways are described. Full understanding of the pathway properties when is working under a variety of conditions can help to attain a successful manipulation of flux and metabolite concentration.

Co-factor engineering in lactobacilli: effects of uncoupled ATPase activity on metabolic fluxes in Lactobacillus (L.) plantarum and L. sakei

The hydrolytic F(1)-part of the F(1)F(0)-ATPase was over-expressed in Lactobacillus (L.) plantarum NC8 and L. sakei Lb790x during fermentation of glucose or ribose, in order to study how changes in the intracellular levels of ATP and ADP affect the metabolic fluxes. The uncoupled ATPase activity resulted in a decrease in intracellular energy level (ATP/ADP ratio), biomass yield and growth rate. Interestingly, the glycolytic and ribolytic flux increased in L. plantarum with uncoupled ATPase activity compared to the reference strain by up to 20% and 50%, respectively. The ATP demand was estimated to have approximately 80% control on both the glycolytic and ribolytic flux in L. plantarum under these conditions. In contrast, the glycolytic and ribolytic flux decreased in L. sakei with uncoupled ATPase activity.

The lactate dehydrogenases encoded by the ldh and ldhB genes in Lactococcus lactis exhibit distinct regulation and catalytic properties - comparative modeling to probe the molecular basis

Lactococcus lactis FI9078, a construct carrying a disruption of the ldh gene, converted approximately 90% of glucose into lactic acid, like the parental strain MG1363. This unexpected lactate dehydrogenase activity was purified, and ldhB was identified as the gene encoding this protein. The activation of ldhB was explained by the insertion of an IS905-like element that created a hybrid promoter in the intergenic region upstream of ldhB. The biochemical and kinetic properties of this alternative lactate dehydrogenase (LDHB) were compared to those of the ldh-encoded enzyme (LDH), purified from the parental strain. In contrast to LDH, the affinity of LDHB for NADH and the activation constant for fructose 1,6-bisphosphate were strongly dependent on pH. The activation constant increased 700-fold, whereas the K(m) for NADH increased more than 10-fold, in the pH range 5.5-7.2. The two enzymes also exhibited different pH profiles for maximal activity. Moreover, inorganic phosphate acted as a strong activator of LDHB. The impact of replacing LDH by LDHB on the physiology of L. lactis was assessed by monitoring the evolution of the pools of glycolytic intermediates and cofactors during the metabolism of glucose by in vivo NMR. Structural analysis by comparative modeling of the two proteins showed that LDH has a slightly larger negative charge than LDHB and a greater concentration of positive charges at the interface between monomers. The calculated pH titration curves of the catalytic histidine residues explain why LDH maintains its activity at low pH as compared to LDHB, the histidines in LDH showing larger pH titration ranges.

The las enzymes control pyruvate metabolism in Lactococcus lactis during growth on maltose

The fermentation pattern of Lactococcus lactis with altered activities of the las enzymes was examined on maltose. The wild type converted 65% of the maltose to mixed acids. An increase in phosphofructokinase or lactate dehydrogenase expression shifted the fermentation towards homolactic fermentation, and with a high level of expression of the las operon the fermentation was homolactic.

The serine/threonine/tyrosine phosphoproteome of the model bacterium Bacillus subtilis

Protein phosphorylation on serine, threonine, and tyrosine (Ser/Thr/Tyr) is well established as a key regulatory posttranslational modification in eukaryotes, but little is known about its extent and function in prokaryotes. Although protein kinases and phosphatases have been predicted and identified in a variety of bacterial species, classical biochemical approaches have so far revealed only a few substrate proteins and even fewer phosphorylation sites. Bacillus subtilis is a model Gram-positive bacterium in which two-dimensional electrophoresis-based studies suggest that the Ser/Thr/Tyr phosphorylation should be present on more than a hundred proteins. However, so far only 16 phosphorylation sites on eight of its proteins have been determined, mostly in in vitro studies. Here we performed a global, gel-free, and site-specific analysis of the B. subtilis phosphoproteome using high accuracy mass spectrometry in combination with biochemical enrichment of phosphopeptides from digested cell lysates. We identified 103 unique phosphopeptides from 78 B. subtilis proteins and determined 78 phosphorylation sites: 54 on serine, 16 on threonine, and eight on tyrosine. Detected phosphoproteins are involved in a wide variety of metabolic processes but are enriched in carbohydrate metabolism. We report phosphorylation sites on almost all glycolytic and tricarboxylic acid cycle enzymes, several kinases, and members of the phosphoenolpyruvate-dependent phosphotransferase system. This significantly enlarged number of bacterial proteins known to be phosphorylated on Ser/Thr/Tyr residues strongly supports the emerging view that protein phosphorylation is a general and fundamental regulatory process, not restricted only to eukaryotes, and opens the way for its detailed functional analysis in bacteria.

Synthetic promoter libraries--tuning of gene expression

The study of gene function often requires changing the expression of a gene and evaluating the consequences. In principle, the expression of any given gene can be modulated in a quasi-continuum of discrete expression levels but the traditional approaches are usually limited to two extremes: gene knockout and strong overexpression. However, applications such as metabolic optimization and control analysis necessitate a continuous set of expression levels with only slight increments in strength to cover a specific window around the wild-type expression level of the studied gene; this requirement can be met by using promoter libraries. This approach generally consists of inserting a library of promoters in front of the gene to be studied, whereby the individual promoters might deviate either in their spacer sequences or bear slight deviations from the consensus sequence of a vegetative promoter. Here, we describe the two different methods for obtaining promoter libraries and compare their applicability.

Tunable promoters in systems biology

The construction of synthetic promoter libraries has represented a major breakthrough in systems biology, enabling the subtle tuning of enzyme activities. A number of tools are now available that allow the modulation of gene expression and the detection of changes in expression patterns. But, how does one choose the correct promoter and what are the appropriate methods for reading promoter strength? Furthermore, how fine should the tuning of gene expression be for some specific applications and how can the simultaneous and individual tuning of multiple genes be achieved? Some recent studies have helped us to find answers to many of these questions.

The glycolytic genes pfk and pyk from Lactobacillus casei are induced by sugars transported by the phosphoenolpyruvate:sugar phosphotransferase system and repressed by CcpA

In Lactobacillus casei BL23, phosphofructokinase activity was higher in cells utilizing sugars transported by the phosphoenolpyruvate:sugar phosphotransferase system (PTS). The phosphofructokinase gene (pfk) was cloned from L. casei and shown to be clustered with the gene encoding pyruvate kinase (pyk). pfk and pyk genes are cotranscribed and induced upon growth on sugars transported by the PTS. Contrarily to the model proposed for Lactococcus lactis, where the global catabolite regulator protein (CcpA) is involved in PTS-induced transcription of pfk and pyk, a ccpA mutation resulted in a slight increase in pfk-pyk expression in L. casei. This weak regulation was evidenced by CcpA binding to a region of the pfk-pyk promoter which contained two cre sequences significantly deviated from the consensus. The PTS induction of pfk-pyk seems to be counteracted by the CcpA-mediated repression. Our results suggest that the need to accommodate the levels of pfk-pyk mRNA to the availability of sugars is fulfilled in L. casei by a PTS/CcpA-mediated signal transduction different from L. lactis.