prpR, ntrA, and ihf functions are required for expression of the prpBCDE operon, encoding enzymes that catabolize propionate in Salmonella enterica serovar typhimurium LT2

2-Methylcitrate cycle: a well-regulated controller of Bacillus sporulation

Bacillus thuringiensis is the most widely used eco-friendly biopesticide, containing two primary determinants of biocontrol, endospore and insecticidal crystal proteins (ICPs). The 2-methylcitrate cycle is a widespread carbon metabolic pathway playing a crucial role in channelling propionyl-CoA, but with poorly understood metabolic regulatory mechanisms. Here, we dissect the transcriptional regulation of the 2-methylcitrate cycle operon prpCDB and report its unprecedented role in controlling the sporulation process of B. thuringiensis. We found that the transcriptional activity of the prp operon encoding the three critical enzymes PrpC, PrpD, and PrpB in the 2-methylcitrate cycle was negatively regulated by the two global transcription factors CcpA and AbrB, while positively regulated by the LysR family regulator CcpC, which jointly account for the fact that the 2-methylcitrate cycle is specifically and highly active in the stationary phase of growth. We also found that the prpD mutant accumulated 2-methylcitrate, the intermediate metabolite of the 2-methylcitrate cycle, which delayed and inhibited sporulation at the early stage. Thus, our results not only revealed sophisticated transcriptional regulatory mechanisms for the metabolic 2-methylcitrate cycle but also identified 2-methylcitrate as a novel regulator of sporulation in B. thuringiensis.

The Nitrogen Regulator GlnR Directly Controls Transcription of the prpDBC Operon Involved in Methylcitrate Cycle in Mycobacterium smegmatis

Mycobacterium tuberculosis utilizes fatty acids of the host as the carbon source. Metabolism of odd-chain fatty acids by Mycobacterium tuberculosis produces propionyl coenzyme A (propionyl-CoA). The methylcitrate cycle is essential for mycobacteria to utilize the propionyl-CoA to persist and grow on these fatty acids. In M. smegmatis, methylcitrate synthase, methylcitrate dehydratase, and methylisocitrate lyase involved in the methylcitrate cycle are encoded by prpC, prpD, and prpB, respectively, in operon prpDBC In this study, we found that the nitrogen regulator GlnR directly binds to the promoter region of the prpDBC operon and inhibits its transcription. The binding motif of GlnR was identified by bioinformatic analysis and validated using DNase I footprinting and electrophoretic mobility shift assays. The GlnR-binding motif is separated by a 164-bp sequence from the binding site of PrpR, a pathway-specific transcriptional activator of methylcitrate cycle, but the binding affinity of GlnR to prpDBC is much stronger than that of PrpR. Deletion of glnR resulted in faster growth in propionate or cholesterol medium compared with the wild-type strain. The ΔglnR mutant strain also showed a higher survival rate in macrophages. These results illustrated that the nitrogen regulator GlnR regulates the methylcitrate cycle through direct repression of the transcription of the prpDBC operon. This finding not only suggests an unprecedented link between nitrogen metabolism and the methylcitrate pathway but also reveals a potential target for controlling the growth of pathogenic mycobacteria.IMPORTANCE The success of mycobacteria survival in macrophage depends on its ability to assimilate fatty acids and cholesterol from the host. The cholesterol and fatty acids are catabolized via β-oxidation to generate propionyl coenzyme A (propionyl-CoA), which is then primarily metabolized via the methylcitrate cycle. Here, we found a typical GlnR binding box in the prp operon, and the affinity is much stronger than that of PrpR, a transcriptional activator of methylcitrate cycle. Furthermore, GlnR repressed the transcription of the prp operon. Deletion of glnR significantly enhanced the growth of Mycobacterium tuberculosis in propionate or cholesterol medium, as well as viability in macrophages. These findings provide new insights into the regulatory mechanisms underlying the cross talk of nitrogen and carbon metabolisms in mycobacteria.

Integration Host Factor Is Essential for Biofilm Formation, Extracellular Enzyme, Zeamine Production, and Virulence in Dickeya zeae

Dickeya zeae is a globally important pathogenic bacterium that infects many crops, including rice, maize, potato, and banana. Bacterial foot rot of rice caused by D. zeae is one of the most important bacterial diseases of rice in China and some Southeast Asian countries. To investigate the functions of integration host factor (IHF) in D. zeae, we generated knockout mutants of ihfA and ihfB. Phenotypic assays showed that both the ΔihfA and ΔihfB strains had greatly reduced mobility, biofilm formation, extracellular protease, and pectinase activities, and toxin production compared with the wild-type strain. In addition, the mutants did not inhibit the germination of rice seeds, failed to cause soft rot in potatoes and a hypersensitive response in tobacco, and were avirulent in rice. Quantitative reverse-transcription polymerase chain reaction analysis demonstrated that IHF positively regulates the expression of zmsA, hrpN/Y, pelA/B/C, pehX, celZ, prtG, fliC, and DGC (diguanylate cyclase). Electrophoretic mobility shift assays further confirmed that IhfA binds to the promoter region of the DGC gene and may alter the levels of a second bacterial messenger, c-di-GMP, to regulate the pathogenicity or other physiological functions of D. zeae. In summary, IHF is an important integrated regulator of pathogenicity in D. zeae.

GlnR-Mediated Regulation of Short-Chain Fatty Acid Assimilation in Mycobacterium smegmatis

Assimilation of short-chain fatty acids (SCFAs) plays an important role in the survival and lipid biosynthesis of Mycobacteria. However, regulation of this process has not been thoroughly described. In the present work, we demonstrate that GlnR as a well-known nitrogen-sensing regulator transcriptionally modulates the AMP-forming propionyl-CoA synthetase (MsPrpE), and acetyl-CoA synthetases (MsAcs) is associated with SCFAs assimilation in Mycobacterium smegmatis, a model Mycobacterium. GlnR can directly activate the expression of MsprpE and Msacs by binding to their promoter regions based upon sensed nitrogen starvation in the host. Moreover, GlnR can activate the expression of lysine acetyltransferase encoding Mspat, which significantly decreases the activity of MsPrpE and MsAcs through increased acylation. Next, growth curves and resazurin assay show that GlnR can further regulate the growth of M. smegmatis on different SCFAs to control the viability. These results demonstrate that GlnR-mediated regulation of SCFA assimilation in response to the change of nitrogen signal serves to control the survival of M. smegmatis. These findings provide insights into the survival and nutrient utilization mechanisms of Mycobacteria in their host, which may enable new strategies in drug discovery for the control of tuberculosis.

Novel DNA Binding and Regulatory Activities for σ54 (RpoN) in Salmonella enterica Serovar Typhimurium 14028s

The variable sigma (σ) subunit of the bacterial RNA polymerase (RNAP) holoenzyme, which is responsible for promoter specificity and open complex formation, plays a strategic role in the response to environmental changes. Salmonella enterica serovar Typhimurium utilizes the housekeeping σ⁷⁰ and five alternative sigma factors, including σ⁵⁴ The σ⁵⁴-RNAP differs from other σ-RNAP holoenzymes in that it forms a stable closed complex with the promoter and requires ATP hydrolysis by an activated cognate bacterial enhancer binding protein (bEBP) to transition to an open complex and initiate transcription. In S. Typhimurium, σ⁵⁴-dependent promoters normally respond to one of 13 different bEBPs, each of which is activated under a specific growth condition. Here, we utilized a constitutively active, promiscuous bEBP to perform a genome-wide identification of σ⁵⁴-RNAP DNA binding sites and the transcriptome of the σ⁵⁴ regulon of S. Typhimurium. The position and context of many of the identified σ⁵⁴ RNAP DNA binding sites suggest regulatory roles for σ⁵⁴-RNAP that connect the σ⁵⁴ regulon to regulons of other σ factors to provide a dynamic response to rapidly changing environmental conditions.IMPORTANCE The alternative sigma factor σ⁵⁴ (RpoN) is required for expression of genes involved in processes with significance in agriculture, bioenergy production, bioremediation, and host-microbe interactions. The characterization of the σ⁵⁴ regulon of the versatile pathogen S. Typhimurium has expanded our understanding of the scope of the σ⁵⁴ regulon and how it links to other σ regulons within the complex regulatory network for gene expression in bacteria.

Differences in gut microbial composition correlate with regional brain volumes in irritable bowel syndrome

BACKGROUND

Preclinical and clinical evidence supports the concept of bidirectional brain-gut microbiome interactions. We aimed to determine if subgroups of irritable bowel syndrome (IBS) subjects can be identified based on differences in gut microbial composition, and if there are correlations between gut microbial measures and structural brain signatures in IBS.

METHODS

Behavioral measures, stool samples, and structural brain images were collected from 29 adult IBS and 23 healthy control subjects (HCs). 16S ribosomal RNA (rRNA) gene sequencing was used to profile stool microbial communities, and various multivariate analysis approaches were used to quantitate microbial composition, abundance, and diversity. The metagenomic content of samples was inferred from 16S rRNA gene sequence data using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt). T1-weighted brain images were acquired on a Siemens Allegra 3T scanner, and morphological measures were computed for 165 brain regions.

RESULTS

Using unweighted Unifrac distances with hierarchical clustering on microbial data, samples were clustered into two IBS subgroups within the IBS population (IBS1 (n = 13) and HC-like IBS (n = 16)) and HCs (n = 23) (AUROC = 0.96, sensitivity 0.95, specificity 0.67). A Random Forest classifier provided further support for the differentiation of IBS1 and HC groups. Microbes belonging to the genera Faecalibacterium, Blautia, and Bacteroides contributed to this subclassification. Clinical features distinguishing the groups included a history of early life trauma and duration of symptoms (greater in IBS1), but not self-reported bowel habits, anxiety, depression, or medication use. Gut microbial composition correlated with structural measures of brain regions including sensory- and salience-related regions, and with a history of early life trauma.

CONCLUSIONS

The results confirm previous reports of gut microbiome-based IBS subgroups and identify for the first time brain structural alterations associated with these subgroups. They provide preliminary evidence for the involvement of specific microbes and their predicted metabolites in these correlations.

Tunable recombinant protein expression in E. coli: promoter systems and genetic constraints

Tuning of transcription is a promising strategy to overcome challenges associated with a non-suitable expression rate like outgrowth of segregants, inclusion body formation, metabolic burden and inefficient translocation. By adjusting the expression rate-even on line-to purposeful levels higher product titres and more cost-efficient production processes can be achieved by enabling culture long-term stability and constant product quality. Some tunable systems are registered for patents or already commercially available. Within this contribution, we discuss the induction mechanisms of various Escherichia coli inherent promoter systems with respect to their tunability and review studies using these systems for expression tuning. According to the current level of knowledge, some promoter systems were successfully used for expression tuning, and in some cases, analytical evidence on single-cell level is still pending. However, only a few studies using tunable strains apply a suitable process control strategy. So far, expression tuning has only gathered little attention, but we anticipate that expression tuning harbours great potential for enabling and optimizing the production of a broad spectrum of products in E. coli.

Modulating Salmonella Typhimurium's Response to a Changing Environment through Bacterial Enhancer-Binding Proteins and the RpoN Regulon

Transcription sigma factors direct the selective binding of RNA polymerase holoenzyme (Eσ) to specific promoters. Two families of sigma factors determine promoter specificity, the σ(70) (RpoD) family and the σ(54) (RpoN) family. In transcription controlled by σ(54), the Eσ(54)-promoter closed complex requires ATP hydrolysis by an associated bacterial enhancer-binding protein (bEBP) for the transition to open complex and transcription initiation. Given the wide host range of Salmonella enterica serovar Typhimurium, it is an excellent model system for investigating the roles of RpoN and its bEBPs in modulating the lifestyle of bacteria. The genome of S. Typhimurium encodes 13 known or predicted bEBPs, each responding to a unique intracellular or extracellular signal. While the regulons of most alternative sigma factors respond to a specific environmental or developmental signal, the RpoN regulon is very diverse, controlling genes for response to nitrogen limitation, nitric oxide stress, availability of alternative carbon sources, phage shock/envelope stress, toxic levels of zinc, nucleic acid damage, and other stressors. This review explores how bEBPs respond to environmental changes encountered by S. Typhimurium during transmission/infection and influence adaptation through control of transcription of different components of the S. Typhimurium RpoN regulon.

Acs is essential for propionate utilization in Escherichia coli

Bacteria like Escherichia coli can use propionate as sole carbon and energy source. All pathways for degradation of propionate start with propionyl-CoA. However, pathways of propionyl-CoA synthesis from propionate and their regulation mechanisms have not been carefully examined in E. coli. In this study, roles of the acetyl-CoA synthetase encoding gene acs and the NAD(+)-dependent protein deacetylase encoding gene cobB on propionate utilization in E. coli were investigated. Results from biochemical analysis showed that, reversible acetylation also modulates the propionyl-CoA synthetase activity of Acs. Subsequent genetic analysis revealed that, deletion of acs in E. coli results in blockage of propionate utilization, suggesting that acs is essential for propionate utilization in E. coli. Besides, deletion of cobB in E. coli also results in growth defect, but only under lower concentrations of propionate (5mM and 10mM propionate), suggesting the existence of other propionyl-CoA synthesis pathways. In combination with previous observations, our data implies that, for propionate utilization in E. coli, a primary amount of propionyl-CoA seems to be required, which is synthesized by Acs.

Use of a promiscuous, constitutively-active bacterial enhancer-binding protein to define the σ⁵⁴ (RpoN) regulon of Salmonella Typhimurium LT2

Background

Sigma54, or RpoN, is an alternative σ factor found widely in eubacteria. A significant complication in analysis of the global σ⁵⁴ regulon in a bacterium is that the σ⁵⁴ RNA polymerase holoenzyme requires interaction with an active bacterial enhancer-binding protein (bEBP) to initiate transcription at a σ⁵⁴-dependent promoter. Many bacteria possess multiple bEBPs, which are activated by diverse environmental stimuli. In this work, we assess the ability of a promiscuous, constitutively-active bEBP—the AAA+ ATPase domain of DctD from Sinorhizobium meliloti—to activate transcription from all σ⁵⁴-dependent promoters for the characterization of the σ⁵⁴ regulon of Salmonella Typhimurium LT2.

Results

The AAA+ ATPase domain of DctD was able to drive transcription from nearly all previously characterized or predicted σ⁵⁴-dependent promoters in Salmonella under a single condition. These promoters are controlled by a variety of native activators and, under the condition tested, are not transcribed in the absence of the DctD AAA+ ATPase domain. We also identified a novel σ⁵⁴-dependent promoter upstream of STM2939, a homolog of the cas1 component of a CRISPR system. ChIP-chip analysis revealed at least 70 σ⁵⁴ binding sites in the chromosome, of which 58% are located within coding sequences. Promoter-lacZ fusions with selected intragenic σ⁵⁴ binding sites suggest that many of these sites are capable of functioning as σ⁵⁴-dependent promoters.

Conclusion

Since the DctD AAA+ ATPase domain proved effective in activating transcription from the diverse σ⁵⁴-dependent promoters of the S. Typhimurium LT2 σ⁵⁴ regulon under a single growth condition, this approach is likely to be valuable for examining σ⁵⁴ regulons in other bacterial species. The S. Typhimurium σ⁵⁴ regulon included a high number of intragenic σ⁵⁴ binding sites/promoters, suggesting that σ⁵⁴ may have multiple regulatory roles beyond the initiation of transcription at the start of an operon.

Salmonella enterica serovar typhimurium colonizing the lumen of the chicken intestine grows slowly and upregulates a unique set of virulence and metabolism genes

The pattern of global gene expression in Salmonella enterica serovar Typhimurium bacteria harvested from the chicken intestinal lumen (cecum) was compared with that of a late-log-phase LB broth culture using a whole-genome microarray. Levels of transcription, translation, and cell division in vivo were lower than those in vitro. S. Typhimurium appeared to be using carbon sources, such as propionate, 1,2-propanediol, and ethanolamine, in addition to melibiose and ascorbate, the latter possibly transformed to d-xylulose. Amino acid starvation appeared to be a factor during colonization. Bacteria in the lumen were non- or weakly motile and nonchemotactic but showed upregulation of a number of fimbrial and Salmonella pathogenicity island 3 (SPI-3) and 5 genes, suggesting a close physical association with the host during colonization. S. Typhimurium bacteria harvested from the cecal mucosa showed an expression profile similar to that of bacteria from the intestinal lumen, except that levels of transcription, translation, and cell division were higher and glucose may also have been used as a carbon source.

An automated phenotype-driven approach (GeneForce) for refining metabolic and regulatory models

Integrated constraint-based metabolic and regulatory models can accurately predict cellular growth phenotypes arising from genetic and environmental perturbations. Challenges in constructing such models involve the limited availability of information about transcription factor—gene target interactions and computational methods to quickly refine models based on additional datasets. In this study, we developed an algorithm, GeneForce, to identify incorrect regulatory rules and gene-protein-reaction associations in integrated metabolic and regulatory models. We applied the algorithm to refine integrated models of Escherichia coli and Salmonella typhimurium, and experimentally validated some of the algorithm's suggested refinements. The adjusted E. coli model showed improved accuracy (∼80.0%) for predicting growth phenotypes for 50,557 cases (knockout mutants tested for growth in different environmental conditions). In addition to identifying needed model corrections, the algorithm was used to identify native E. coli genes that, if over-expressed, would allow E. coli to grow in new environments. We envision that this approach will enable the rapid development and assessment of genome-scale metabolic and regulatory network models for less characterized organisms, as such models can be constructed from genome annotations and cis-regulatory network predictions.

Computational models of biological networks are useful for explaining experimental observations and predicting phenotypic behaviors. The construction of genome-scale metabolic and regulatory models is still a labor-intensive process, even with the availability of genome sequences and high-throughput datasets. Since our knowledge about biological systems is incomplete, these models are iteratively refined and validated as we discover new connections in biological networks, and eliminate inconsistencies between model predictions and experimental observations. To enable researchers to quickly determine what causes discrepancies between observed phenotypes and model predictions, we developed a new approach (GeneForce) that automatically corrects integrated metabolic and transcriptional regulatory network models. To illustrate the utility of the approach, we applied the developed method to well-curated models of E. coli metabolism and regulation. We found that the approach significantly improved the accuracy of phenotype predictions and suggested changes needed to the metabolic and/or regulatory models. We also used the approach to identify rescue non-growth phenotypes and to evaluate the conservation of transcriptional regulatory interactions between E. coli and S. typhimurium. The developed approach helps reconcile discrepancies between model predictions and experimental data by hypothesizing required network changes, and helps facilitate the development of new genome-scale models.

Regulatory and metabolic rewiring during laboratory evolution of ethanol tolerance in E. coli

We have designed an experimental/computational framework for studying complex phenotypes in bacteria.

Our framework relies on whole-genome fitness profiling coupled with a module-level analysis to discover pathways that directly affect fitness.

As a proof-of-principle, we studied ethanol tolerance in Escherichia coli and we identified key pathways that contribute to this phenotype.

We then validated our findings through genetic manipulations, gene-expression profiling, metabolite-level measurements, and stable-isotope labeling.

Elucidating the genetic basis of complex phenotypes remains a fundamental challenge in biology. We have developed a systematic framework for comprehensive genetic analysis of microbial phenotypes. Our approach combines the power of fitness profiling (Girgis et al, 2007; Amini et al, 2009) with the sensitivity of module-level analysis (Goodarzi et al, 2009a) to identify key genetic modules that directly affect a phenotype under study. We applied our technology to ethanol tolerance, a complex phenotype with broad industrial relevance. Ethanol affects a variety of cellular components and pathways, including but not limited to membrane integrity (Dombek and Ingram, 1984), enzyme activities (Millar et al, 1982), and proton flux (D'Amore et al, 1990). Given the diversity of targets, the emergence of ethanol tolerance requires modifications to multiple pathway (D'Amore and Stewart, 1987).

To reveal the genetic basis of ethanol tolerance in Escherichia coli, we used two high-coverage mutant libraries (a transposon library and an overexpression library) to assess the fitness consequences of single-locus perturbations. Each cell in our transposon library contains a random transposon insertion in its genome (Girgis et al, 2007); whereas the cells in the overexpression library carry 1–3 kb genomic fragments cloned into a cloning vector (Amini et al, 2009). We grew these libraries under mild (4% v/v) and harsh (5.5% v/v) ethanol concentrations. On growth, the abundance of each transposon insertion or overexpression mutant changes as a function of its fitness, a process that can be monitored through parallel genetic footprinting and microarray hybridization (Figure 1A). This results in a global fitness profile, where the contribution of each genetic locus to ethanol tolerance can be quantified in parallel. However, in the context of ethanol tolerance and other complex phenotypes, single-locus perturbations typically result in modest changes in fitness. Although these small differences can be amplified through multiple rounds of selection, the number of generations is limited as spontaneous beneficial mutations emerge in the population and cause strong biases in the resulting fitness profiles. To boost our analytical power without introducing these biases in the data, we used a module-level computational method to discover the pathways and components that are strongly associated with the data as opposed to focusing on the genes individually (Goodarzi et al, 2009a). Genes function in the context of pathways and modules and module-level analyses increase statistical power through combining information from multiple genes functioning as part of a given pathway (Subramanian et al, 2005).

The module-level analysis of the fitness scores from both libraries revealed a diverse set of pathways that have a direct function in ethanol tolerance. Some of these pathways, including heat-shock stress response and osmoregulation, are known modifiers of ethanol tolerance; whereas others such as acid-stress response and fimbrial structures are novel pathways. Among our findings was the important function of three regulatory proteins: FNR, ArcA, and CafA. Knocking out FNR/ArcA that upregulates aerobic respiration proteins and TCA cycle components results in a marked increase in ethanol tolerance. Similarly, knocking out CafA, a post-transcriptional regulator of alcohol dehydrogenase, is beneficial for tolerance. Given these observations, we hypothesized that selection for ethanol tolerance can result in higher ethanol degradation.

As a large fraction of discovered pathways belonged to central metabolism, we used metabolomics to evaluate our findings. To directly assess the metabolic consequences of adaptation to ethanol, we evolved ethanol-tolerant strains in minimal media plus glucose for ∼30 and 160 generations. We then compared the steady-state level of metabolites in these strains to that of the wild type (Figure 1B). In agreement with our fitness profiling results, we observed a significant increase in TCA cycle metabolites in one of our ethanol-tolerant strains. Higher concentrations of TCA cycle components along with a high free coenzyme A (CoA) to acetyl-coenzyme A (acetyl-CoA) ratio hinted at the capacity of this strain to metabolize ethanol. To test this hypothesis, we performed stable-isotope labeling on our ethanol-tolerant strain versus wild type. After growth on labeled ethanol, we measured the fraction of metabolites that were labeled at each timepoint (Figure 1B). Our results confirmed that the ethanol-tolerant strain has the capacity to consume ethanol through its conversion into acetyl-CoA and further assimilation in the TCA cycle.

By using a variety of systems-level approaches, we have been able to genetically dissect ethanol tolerance in E. coli. We have shown that fitness profiling, in combination with module-level analysis tools, can serve as a powerful approach for revealing the genetic basis of complex phenotypes. The fact that laboratory evolution ended up using the very modules that we discovered, highlights the biological and adaptive relevance of the proposed framework.

Understanding the genetic basis of adaptation is a central problem in biology. However, revealing the underlying molecular mechanisms has been challenging as changes in fitness may result from perturbations to many pathways, any of which may contribute relatively little. We have developed a combined experimental/computational framework to address this problem and used it to understand the genetic basis of ethanol tolerance in Escherichia coli. We used fitness profiling to measure the consequences of single-locus perturbations in the context of ethanol exposure. A module-level computational analysis was then used to reveal the organization of the contributing loci into cellular processes and regulatory pathways (e.g. osmoregulation and cell-wall biogenesis) whose modifications significantly affect ethanol tolerance. Strikingly, we discovered that a dominant component of adaptation involves metabolic rewiring that boosts intracellular ethanol degradation and assimilation. Through phenotypic and metabolomic analysis of laboratory-evolved ethanol-tolerant strains, we investigated naturally accessible pathways of ethanol tolerance. Remarkably, these laboratory-evolved strains, by and large, follow the same adaptive paths as inferred from our coarse-grained search of the fitness landscape.

Participation of regulator AscG of the beta-glucoside utilization operon in regulation of the propionate catabolism operon

The asc operon of Escherichia coli is one of the cryptic genetic systems for beta-D-galactoside utilization as a carbon source. The ascFB genes for beta-D-galactoside transport and catabolism are repressed by the AscG regulator. After genomic SELEX screening, AscG was found to recognize and bind the consensus palindromic sequence TGAAACC-GGTTTCA. AscG binding was detected at two sites upstream of the ascFB promoter and at three sites upstream of the prpBC operon for propionate catabolism. In an ascG-disrupted mutant, transcription of ascFB was enhanced, in agreement with the repressor model of AscG. This repression was indicated to be due to interference of binding of cyclic AMP-CRP to the CRP box, which overlaps with the AscG-binding site 1, as well as binding of RNA polymerase to the promoter. Under conditions of steady-state E. coli growth in a rich medium, the intracellular level of AscG stayed constant at a level supposedly leading to tight repression of the ascFB operon. The level of prpR, encoding the activator of prpBCDE, was also increased in the absence of AscG, indicating the involvement of AscG in repression of prpR. Taken together, these data suggest a metabolic link through interplay between the asc and prp operons.

Transcription modulation of Salmonella enterica serovar Typhimurium promoters by sub-MIC levels of rifampin

Promoter-lux fusions that showed rifampin-modulated transcription were identified from a Salmonella enterica serovar Typhimurium 14028 reporter library. The transformation of a subset of fusions into mutants that lacked one of six global regulatory proteins or were rifampin resistant showed that transcription modulation was independent of the global regulators, promoter specific, and dependent on the interaction of rifampin with RNA polymerase.

The integration host factor (IHF) integrates stationary-phase and virulence gene expression in Salmonella enterica serovar Typhimurium

The integration host factor (IHF) is a DNA-binding and -bending protein with roles in local DNA structural organization and transcriptional regulation in Gram-negative bacteria. This heterodimeric protein is composed of the two highly homologous subunits IHFalpha and IHFbeta. DNA microarray analysis was used to define the regulon of genes subject to IHF control in Salmonella enterica serovar Typhimurium (S. Typhimurium). The transcription profile of the wild type was compared with those of mutants deficient in IHFalpha, IHFbeta, or both IHFalpha and IHFbeta. Our data reveal a new connection between IHF and the expression of genes required by the bacterium to undergo the physiological changes associated with the transition from exponential growth to stationary phase. When a mutant lacking IHF entered stationary phase, it displayed downregulated expression of classic stationary-phase genes in the absence of any concomitant change in expression of the RpoS sigma factor. Purified IHF was found to bind to the regulatory regions of stationary-phase genes indicating an auxiliary and direct role for IHF in RpoS-dependent gene activation. Loss of IHF also had a profound influence on expression of the major virulence genes and epithelial cell invasion, indicating a role in co-ordinating regulation of the pathogenic traits with adaptation to stationary phase. Although the three mutants showed considerable overlaps in the genes affected by the ihf lesions, the observed patterns were not identical, showing that S. Typhimurium has not one but three overlapping IHF regulons.

Propionate-regulated high-yield protein production inEscherichia coli

A new expression system containing the Salmonella enterica prpBCDE promoter (P(prpB)) responsible for expression of the propionate catabolic genes (prp BCDE) and prpR encoding the positive regulator of this promoter has been developed and tested. The main features of the expression system compared to those based on the bacteriophage T7 promoter are low background expression and high induced expression in Escherichia coli strains BL21, BL21(DE3), MG1655, and W3110. In addition, propionate is an inexpensive, simple-to-use, nontoxic inducer that is attractive for large-scale protein production. Hence, this new system is highly complementary to the widely used T7 promoter-driven expression systems.

A propionate-inducible expression system for enteric bacteria

A series of new expression vectors (pPro) have been constructed for the regulated expression of genes in Escherichia coli. The pPro vectors contain the prpBCDE promoter (P(prpB)) responsible for expression of the propionate catabolic genes (prpBCDE) and prpR encoding the positive regulator of this promoter. The efficiency and regulatory properties of the prpR-P(prpB) system were measured by placing the gene encoding the green fluorescent protein (gfp) under the control of the inducible P(prpB) of E. coli. This system provides homogenous expression in individual cells, highly regulatable expression over a wide range of propionate concentrations, and strong expression (maximal 1,500-fold induction) at high propionate concentrations. Since the prpBCDE promoter has CAP-dependent activation, the prpR-P(prpB) system exhibited negligible basal expression by addition of glucose to the medium.

Occurrence and expression of tricarboxylate synthases in Ralstonia eutropha

2-Methylcitrate synthase (2-MCS1) and citrate synthase (CS) of Ralstonia eutropha strain H16 were separated by affinity chromatography and analyzed for their substrate specificities. 2-MCS1 used not only the primary substrate propionyl-CoA but also acetyl-CoA and, at a low rate, even butyryl-CoA and valeryl-CoA for condensation with oxaloacetate. The KM values for propionyl-CoA and acetyl-CoA were 0.061 or 0.35 mM, respectively. This enzyme is therefore a competitor for acetyl-CoA during biosynthesis of poly(3-hydroxybutyrate) (PHB) and has to be taken into account if metabolic fluxes are calculated for PHB biosynthesis. In contrast, CS could not use propionyl-CoA as a substrate. The gene-encoding CS (cisY) of R. eutropha was cloned and encodes for a protein consisting of 433 amino acids with a calculated molecular weight of 48,600 Da; it is not truncated in the N-terminal region. Furthermore, a gene encoding a second functionally active 2-methylcitrate synthase (2-MCS2, prpC2) was identified in the genome of R. eutropha. The latter was localized in a gene cluster with genes for an NAD(H)-dependent malate dehydrogenase and a putative citrate lyase. RT-PCR analysis of R. eutropha growing on different carbon sources revealed the transcription of prpC2. In addition, cells of recombinant Escherichia coli strains harboring prpC2 of R. eutropha exhibited high 2-MCS activity of 0.544 U mg-1. A prpC2 knockout mutant of R. eutropha exhibited an identical phenotype as the wild type if grown on different media. 2-MCS2 seems to be dispensable, and a function could not be revealed for this enzyme.

Catabolite repression of the propionate catabolic genes in Escherichia coli and Salmonella enterica: evidence for involvement of the cyclic AMP receptor protein

Previous studies with Salmonella enterica serovar Typhimurium LT2 demonstrated that transcriptional activation of the prpBCDE operon requires the function of transcription factor PrpR, sigma-54, and IHF. In this study, we found that transcription from the prpBCDE and prpR promoters was down-regulated by the addition of glucose or glycerol, indicating that these genes may be regulated by the cyclic AMP (cAMP)-cAMP receptor protein (CRP) complex. Targeted mutagenesis of a putative CRP-binding site in the promoter region between prpR and prpBCDE suggested that these genes are under the control of CRP. Furthermore, cells with defects in cya or crp exhibited reduced transcriptional activation of prpR and prpBCDE in Escherichia coli. These results demonstrate that propionate metabolism is subject to catabolite repression by the global transcriptional regulator CRP and that this regulation is effected through control of both the regulator gene prpR and the prpBCDE operon itself. The unique properties of the regulation of these two divergent promoters may have important implications for mechanisms of CRP-dependent catabolite repression acting in conjunction with a member of the sigma-54 family of transcriptional activators.

2-Methylcitrate-dependent activation of the propionate catabolic operon (prpBCDE) of Salmonella enterica by the PrpR protein

The function of the PrpR protein of Salmonella enterica serovar Typhimurium LT2 was studied in vitro and in vivo. The PrpR protein is a sensor of 2-methylcitrate (2-MC), an intermediate of the 2-methylcitric acid cycle used by this bacterium to convert propionate to pyruvate. PrpR was unresponsive to citrate (a close structural analogue of 2-MC) and to propionate, suggesting that 2-MC, not propionate, is the metabolite that signals the presence of propionate in the environment to S. enterica. prpR alleles encoding mutant proteins with various levels of 2-MC-independent activity were isolated. All lesions causing constitutive PrpR activity were mapped to the N-terminal domain of the protein. Removal of the entire sensing domain resulted in a protein (PrpR(c)) with the highest 2-MC-independent activity. Residue A162 is critical to 2-MC sensing, since the mutant PrpR protein PrpR(A162T) was as active as the PrpR(c) protein in the absence of 2-MC. DNA footprinting studies identified the site in the region between prpR and the prpBCDE operon to which the PrpR protein binds. Analysis of the binding-site sequence revealed two sites with dyad symmetry. Results from DNase I footprinting assays suggested that the PrpR protein may have higher affinity for the site proximal to the P(prpBCDE) promoter.

Role of integration host factor in the transcriptional activation of flagellar gene expression in Caulobacter crescentus

In the Caulobacter crescentus predivisional cell, class III and IV flagellar genes, encoding the extracytoplasmic components of the flagellum, are transcribed in the nascent swarmer compartment. This asymmetric expression pattern is attributable to the compartmentalized activity of the sigma54-dependent transcriptional activator FlbD. Additionally, these temporally transcribed flagellar promoters possess a consensus sequence for the DNA-binding protein integration host factor (IHF), located between the upstream FlbD binding site and the promoter sequences. Here, we deleted the C. crescentus gene encoding the beta-subunit of the IHF, ihfB (himD), and examined the effect on flagellar gene expression. The DeltaihfB strain exhibited a mild defect in cell morphology and impaired motility. Using flagellar promoter reporter fusions, we observed that expression levels of a subset of class III flagellar promoters were decreased by the loss of IHF. However, one of these promoters, fliK-lacZ, exhibited a wild-type cell cycle-regulated pattern of expression in the absence of IHF. Thus, IHF is required for maximal transcription of several late flagellar genes. The DeltaihfB strain was found to express significantly reduced amounts of the class IV flagellin, FljL, as a consequence of reduced transcriptional activity. Our results indicate that the motility defect exhibited by the DeltaihfB strain is most likely attributable to its failure to accumulate the class IV-encoded 27-kDa flagellin subunit, FljL.

Making connections between novel transcription factors and their DNA motifs

The key components of a transcriptional regulatory network are the connections between trans-acting transcription factors and cis-acting DNA-binding sites. In spite of several decades of intense research, only a fraction of the estimated approximately 300 transcription factors in Escherichia coli have been linked to some of their binding sites in the genome. In this paper, we present a computational method to connect novel transcription factors and DNA motifs in E. coli. Our method uses three types of mutually independent information, two of which are gleaned by comparative analysis of multiple genomes and the third one derived from similarities of transcription-factor-DNA-binding-site interactions. The different types of information are combined to calculate the probability of a given transcription-factor-DNA-motif pair being a true pair. Tested on a study set of transcription factors and their DNA motifs, our method has a prediction accuracy of 59% for the top predictions and 85% for the top three predictions. When applied to 99 novel transcription factors and 70 novel DNA motifs, our method predicted 64 transcription-factor-DNA-motif pairs. Supporting evidence for some of the predicted pairs is presented. Functional annotations are made for 23 novel transcription factors based on the predicted transcription-factor-DNA-motif connections.

The difficult interpretation of transcriptome data: the case of the GATC regulatory network

Genomic analyses on part of Escherichia coli's chromosome had suggested the existence of a GATC regulated network. This has recently been confirmed through a transcriptome analysis. Two hypotheses about the molecular control mechanism have been proposed-(i) the GATC network regulation is caused by the presence of GATC clusters within the coding sequences; the regulation is the direct consequence of the clusters' hemi-methylation and therefore their elevated melting temperature, (ii) the regulation is caused by the presence of GATCs in the non-coding 500 bp upstream regions of the affected genes; it is the consequence of an interaction with a regulatory protein like Fnr or CAP. An analysis of the transcriptome data has not allowed us to decide between the two hypotheses. We have therefore taken a classic genomic approach, analyzing the statistical distribution of GATC along the chromosome, using a realistic model of the chromosome as theoretical reference. We observe no particular distribution of GATC in the non-coding upstream regions; however, we confirm the presence of GATC clusters within the genes. In order to verify that the particular distribution observed in E. coli is not a statistical artefact, but has a physiological role, we have carried out the same analysis on Salmonella, making the hypothesis that the genes containing a GATC clusters should be largely the same in the two bacteria. This has been indeed observed, showing that the genes containing a GATC cluster are part of a regulation network. The present is a case study, which demonstrates that the analysis of transcriptome data does not always permit to identify the primary cause of a phenomenon observed; on the other hand, a classic genomic approach linked with a comparative study of related genomes may allow this identification.

Propionyl coenzyme A is a common intermediate in the 1,2-propanediol and propionate catabolic pathways needed for expression of the prpBCDE operon during growth of Salmonella enterica on 1,2-propanediol

The studies reported here identify propionyl coenzyme A (propionyl-CoA) as the common intermediate in the 1,2-propanediol and propionate catabolic pathways of Salmonella enterica serovar Typhimurium LT2. Growth on 1,2-propanediol as a carbon and energy source led to the formation and excretion of propionate, whose activation to propionyl-CoA relied on the activities of the propionate kinase (PduW)/phosphotransacetylase (Pta) enzyme system and the CobB sirtuin-controlled acetyl-CoA and propionyl-CoA (Acs, PrpE) synthetases. The different affinities of these systems for propionate ensure sufficient synthesis of propionyl-CoA to support wild-type growth of S. enterica under low or high concentrations of propionate in the environment. These redundant systems of propionyl-CoA synthesis are needed because the prpE gene encoding the propionyl-CoA synthetase enzyme is part of the prpBCDE operon under the control of the PrpR regulatory protein, which needs 2-methylcitrate as a coactivator. Because the synthesis of 2-methylcitrate by PrpC (i.e., the 2-methylcitrate synthase enzyme) requires propionyl-CoA as a substrate, the level of propionyl-CoA needs to be raised by the Acs or PduW-Pta system before 2-methylcitrate can be synthesized and prpBCDE transcription can be activated.

DNA microarray analyses of the long-term adaptive response of Escherichia coli to acetate and propionate

In its natural environment, Escherichia coli is exposed to short-chain fatty acids, such as acetic acid or propionic acid, which can be utilized as carbon sources but which inhibit growth at higher concentrations. DNA microarray experiments revealed expression changes during exponential growth on complex medium due to the presence of sodium acetate or sodium propionate at a neutral external pH. The adaptive responses to acetate and propionate were similar and involved genes in three categories. First, the RNA levels for chemotaxis and flagellum genes increased. Accordingly, the expression of chromosomal fliC'-'lacZ and flhDC'-'lacZ fusions and swimming motility increased after adaptation to acetate or propionate. Second, the expression of many genes that are involved in the uptake and utilization of carbon sources decreased, indicating some kind of catabolite repression by acetate and propionate. Third, the expression of some genes of the general stress response increased, but the increases were more pronounced after short-term exposure for this response than for the adaptive response. Adaptation to propionate but not to acetate involved increased expression of threonine and isoleucine biosynthetic genes. The gene expression changes after adaptation to acetate or propionate were not caused solely by uncoupling or osmotic effects but represented specific characteristics of the long-term response of E. coli to either compound.

Metabolic engineering of a novel propionate-independent pathway for the production of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) in recombinant Salmonella enterica serovar typhimurium

A pathway was metabolically engineered to produce poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV), a biodegradable thermoplastic with proven commercial applications, from a single, unrelated carbon source. An expression system was developed in which a prpC strain of Salmonella enterica serovar Typhimurium, with a mutation in the ability to metabolize propionyl coenzyme A (propionyl-CoA), served as the host for a plasmid harboring the Acinetobacter polyhydroxyalkanoate synthesis operon (phaBCA) and a second plasmid with the Escherichia coli sbm and ygfG genes under an independent promoter. The sbm and ygfG genes encode a novel (2R)-methylmalonyl-CoA mutase and a (2R)-methylmalonyl-CoA decarboxylase, respectively, which convert succinyl-CoA, derived from the tricarboxylic acid cycle, to propionyl-CoA, an essential precursor of 3-hydroxyvalerate (HV). The S. enterica system accumulated PHBV with significant HV incorporation when the organism was grown aerobically with glycerol as the sole carbon source. It was possible to vary the average HV fraction in the copolymer by adjusting the arabinose or cyanocobalamin (precursor of coenzyme B12) concentration in the medium.

Identification of two prpDBC gene clusters in Corynebacterium glutamicum and their involvement in propionate degradation via the 2-methylcitrate cycle

Genome sequencing revealed that the Corynebacterium glutamicum genome contained, besides gltA, two additional citrate synthase homologous genes (prpC) located in two different prpDBC gene clusters, which were designated prpD1B1C1 and prpD2B2C2. The coding regions of the two gene clusters as well as the predicted gene products showed sequence identities of about 70 to 80%. Significant sequence similarities were found also to the prpBCDE operons of Escherichia coli and Salmonella enterica, which are known to encode enzymes of the propionate-degrading 2-methylcitrate pathway. Homologous and heterologous overexpression of the C. glutamicum prpC1 and prpC2 genes revealed that their gene products were active as citrate synthases and 2-methylcitrate synthases. Growth tests showed that C. glutamicum used propionate as a single or partial carbon source, although the beginning of the exponential growth phase was strongly delayed by propionate for up to 7 days. Compared to growth on acetate, the specific 2-methylcitrate synthase activity increased about 50-fold when propionate was provided as the sole carbon source, suggesting that in C. glutamicum the oxidation of propionate to pyruvate occurred via the 2-methylcitrate pathway. Additionally, two-dimensional gel electrophoresis experiments combined with mass spectrometry showed strong induction of the expression of the C. glutamicum prpD2B2C2 genes by propionate as an additional carbon source. Mutational analyses revealed that only the prpD2B2C2 genes were essential for the growth of C. glutamicum on propionate as a sole carbon source, while the function of the prpD1B1C1 genes remains obscure.

Identification of the 2-methylcitrate pathway involved in the catabolism of propionate in the polyhydroxyalkanoate-producing strain Burkholderia sacchari IPT101(T) and analysis of a mutant accumulating a copolyester with higher 3-hydroxyvalerate content

Burkholderia sacchari IPT101(T) induced the formation of 2-methylcitrate synthase and 2-methylisocitrate lyase when it was cultivated in the presence of propionic acid. The prp locus of B. sacchari IPT101(T) is required for utilization of propionic acid as a sole carbon source and is relevant for incorporation of 3-hydroxyvalerate (3HV) into copolyesters, and it was cloned and sequenced. Five genes (prpR, prpB, prpC, acnM, and ORF5) exhibited identity to genes located in the prp loci of other gram-negative bacteria. prpC encodes a 2-methylcitrate synthase with a calculated molecular mass of 42,691 Da. prpB encodes a 2-methylisocitrate lyase. The levels of PrpC and PrpB activity were much lower in propionate-negative mutant IPT189 obtained from IPT101(T) and were heterologously expressed in Escherichia coli. The acnM gene (ORF4) and ORF5, which are required for conversion of 2-methylcitric acid to 2-methylisocitric acid in Ralstonia eutropha HF39, are also located in the prp locus. The translational product of ORF1 (prpR) had a calculated molecular mass of 70,598 Da and is a putative regulator of the prp cluster. Three additional open reading frames (ORF6, ORF7, and ORF8) whose functions are not known were located adjacent to ORF5 in the prp locus of B. sacchari, and these open reading frames have not been found in any other prp operon yet. In summary, the organization of the prp genes of B. sacchari is similar but not identical to the organization of these genes in other bacteria investigated recently. In addition, this study provided a rationale for the previously shown increased molar contents of 3HV in copolyesters accumulated by a B. sacchari mutant since it was revealed in this study that the mutant is defective in prpC.

Metabolic engineering of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) composition in recombinant Salmonella enterica serovar typhimurium

A recombinant strain of Salmonella enterica serovar Typhimurium (mutant in propionate-activation activity) was metabolically engineered to control the composition of poly(3-hydroxybutyrate-co-3-hydroxy- valerate) (PHBV), a polyhydroxyalkanoate copolymer with commercially desirable properties. A gene (prpE) encoding propionyl-CoA synthetase was placed under the control of the IPTG-inducible taclacUV5 promoter (P(taclacUV5)) while the polyhydroxyalkanoate synthesis operon (phaBCA) from Acinetobacter sp. RA3849 was coexpressed under the control of the arabinose-inducible araBAD promoter (P(BAD)). S. enterica, harboring both constructs, was grown in medium containing a fixed substrate concentration and the composition of the copolymer was varied between 2 mol% and 25 mol% 3-hydroxyvalerate by controlling the IPTG level in the medium. This "dial-a-composition" system should find application in cases where the substrate concentration of a feedstream for PHBV bioplastic production is not adjustable.

Metabolic context and possible physiological themes of sigma(54)-dependent genes in Escherichia coli

Sigma(54) has several features that distinguish it from other sigma factors in Escherichia coli: it is not homologous to other sigma subunits, sigma(54)-dependent expression absolutely requires an activator, and the activator binding sites can be far from the transcription start site. A rationale for these properties has not been readily apparent, in part because of an inability to assign a common physiological function for sigma(54)-dependent genes. Surveys of sigma(54)-dependent genes from a variety of organisms suggest that the products of these genes are often involved in nitrogen assimilation; however, many are not. Such broad surveys inevitably remove the sigma(54)-dependent genes from a potentially coherent metabolic context. To address this concern, we consider the function and metabolic context of sigma(54)-dependent genes primarily from a single organism, Escherichia coli, in which a reasonably complete list of sigma(54)-dependent genes has been identified by computer analysis combined with a DNA microarray analysis of nitrogen limitation-induced genes. E. coli appears to have approximately 30 sigma(54)-dependent operons, and about half are involved in nitrogen assimilation and metabolism. A possible physiological relationship between sigma(54)-dependent genes may be based on the fact that nitrogen assimilation consumes energy and intermediates of central metabolism. The products of the sigma(54)-dependent genes that are not involved in nitrogen metabolism may prevent depletion of metabolites and energy resources in certain environments or partially neutralize adverse conditions. Such a relationship may limit the number of physiological themes of sigma(54)-dependent genes within a single organism and may partially account for the unique features of sigma(54) and sigma(54)-dependent gene expression.

The methylcitric acid pathway in Ralstonia eutropha: new genes identified involved in propionate metabolism

From Ralstonia eutropha HF39 null-allele mutants were created by Tn5 mutagenesis and by homologous recombination which were impaired in growth on propionic acid and levulinic acid. From the molecular, physiological and enzymic analysis of these mutants it was concluded that in this bacterium propionic acid is metabolized via the methylcitric acid pathway. The genes encoding enzymes of this pathway are organized in a cluster in the order prpR, prpB, prpC, acnM, ORF5 and prpD, with prpR transcribed divergently from the other genes. (i) prpC encodes a 2-methylcitric acid synthase (42720 Da) as shown by the measurement of the respective enzyme activity, complementation of a prpC mutant of Salmonella enterica serovar Typhimurium and high sequence similarity. (ii) For the translational product of acnM the function of a 2-methyl-cis-aconitic acid hydratase (94726 Da) is proposed. This protein and also the ORF5 translational product are essential for growth on propionic acid, as revealed by the propionic-acid-negative phenotype of Tn5-insertion mutants, and are required for the conversion of 2-methylcitric acid into 2-methylisocitric acid as shown by the accumulation of the latter, which could be purified as its calcium salt from the supernatants of these mutants. In contrast, inactivation of prpD did not block the ability of the cell to use propionic acid as carbon and energy source, as shown by the propionic acid phenotype of a null-allele mutant. It is therefore unlikely that prpD from R. eutropha encodes a 2-methyl-cis-aconitic acid dehydratase as proposed recently for the homologous prpD gene from S. enterica. (iii) The translational product of prpB encodes 2-methylisocitric acid lyase (32314 Da) as revealed by measurement of the respective enzyme activity and by demonstrating accumulation of methylisocitric acid in the supernatant of a prpB null-allele mutant. (iv) The expression of prpC and probably also of the other enzymes is regulated and is induced during cultivation on propionic acid or levulinic acid. The putative translational product of prpR (70895 Da) exhibited high similarities to PrpR of Escherichia coli and S. enterica, and might represent a transcriptional activator of the sigma-54 family involved in the regulation of the other prp genes. Since the prp locus of R. eutropha was very different from those of E. coli and S. enterica, an extensive comparison of prp loci available from databases and literature was done, revealing two different classes of prp loci.