Transcription of glpT of Escherichia coli K12 is regulated by anaerobiosis and fnr

In silico Design for Systems-Based Metabolic Engineering for the Bioconversion of Valuable Compounds From Industrial By-Products

Selecting appropriate metabolic engineering targets to build efficient cell factories maximizing the bioconversion of industrial by-products to valuable compounds taking into account time restrictions is a significant challenge in industrial biotechnology. Microbial metabolism engineering following a rational design has been widely studied. However, it is a cost-, time-, and laborious-intensive process because of the cell network complexity; thus, it is important to use tools that allow predicting gene deletions. An in silico experiment was performed to model and understand the metabolic engineering effects on the cell factory considering a second complexity level by transcriptomics data integration. In this study, a systems-based metabolic engineering target prediction was used to increase glycerol bioconversion to succinic acid based on Escherichia coli. Transcriptomics analysis suggests insights on how to increase cell glycerol utilization to further design efficient cell factories. Three E. coli models were used: a core model, a second model based on the integration of transcriptomics data obtained from growth in an optimized culture media, and a third one obtained after integration of transcriptomics data from adaptive laboratory evolution (ALE) experiments. A total of 2,402 strains were obtained with fumarase and pyruvate dehydrogenase being frequently predicted for all the models, suggesting these reactions as essential to increase succinic acid production. Finally, based on using flux balance analysis (FBA) results for all the mutants predicted, a machine learning method was developed to predict new mutants as well as to propose optimal metabolic engineering targets and mutants based on the measurement of the importance of each knockout's (feature's) contribution. Glycerol has become an interesting carbon source for industrial processes due to biodiesel business growth since it has shown promising results in terms of biomass/substrate yields. The combination of transcriptome, systems metabolic modeling, and machine learning analyses revealed the versatility of computational models to predict key metabolic engineering targets in a less cost-, time-, and laborious-intensive process. These data provide a platform to improve the prediction of metabolic engineering targets to design efficient cell factories. Our results may also work as a guide and platform for the selection/engineering of microorganisms for the production of interesting chemical compounds.

A trigger enzyme in Mycoplasma pneumoniae: impact of the glycerophosphodiesterase GlpQ on virulence and gene expression

Mycoplasma pneumoniae is a causative agent of atypical pneumonia. The formation of hydrogen peroxide, a product of glycerol metabolism, is essential for host cell cytotoxicity. Phosphatidylcholine is the major carbon source available on lung epithelia, and its utilization requires the cleavage of deacylated phospholipids to glycerol-3-phosphate and choline. M. pneumoniae possesses two potential glycerophosphodiesterases, MPN420 (GlpQ) and MPN566. In this work, the function of these proteins was analyzed by biochemical, genetic, and physiological studies. The results indicate that only GlpQ is an active glycerophosphodiesterase. MPN566 has no enzymatic activity as glycerophosphodiesterase and the inactivation of the gene did not result in any detectable phenotype. Inactivation of the glpQ gene resulted in reduced growth in medium with glucose as the carbon source, in loss of hydrogen peroxide production when phosphatidylcholine was present, and in a complete loss of cytotoxicity towards HeLa cells. All these phenotypes were reverted upon complementation of the mutant. Moreover, the glpQ mutant strain exhibited a reduced gliding velocity. A comparison of the proteomes of the wild type strain and the glpQ mutant revealed that this enzyme is also implicated in the control of gene expression. Several proteins were present in higher or lower amounts in the mutant. This apparent regulation by GlpQ is exerted at the level of transcription as determined by mRNA slot blot analyses. All genes subject to GlpQ-dependent control have a conserved potential cis-acting element upstream of the coding region. This element overlaps the promoter in the case of the genes that are repressed in a GlpQ-dependent manner and it is located upstream of the promoter for GlpQ-activated genes. We may suggest that GlpQ acts as a trigger enzyme that measures the availability of its product glycerol-3-phosphate and uses this information to differentially control gene expression.

Mycoplasma pneumoniae serves as a model organism for bacteria with very small genomes that are nonetheless independently viable. These bacteria infect the human lung and cause an atypical pneumonia. The major virulence determinant of M. pneumoniae is hydrogen peroxide that is generated during the utilization of glycerol-3-phosphate, which might be derived from free glycerol or from the degradation of phospholipids. Indeed, lecithin is the by far most abundant carbon source on lung epithelia. In this study, we made use of the recent availability of methods to isolate mutants of M. pneumoniae and characterized the enzyme that generates glycerol-3-phosphate from deacylated lecithin (glycerophosphocholine). This enzyme, called GlpQ, is essential for the formation of hydrogen peroxide when the bacteria are incubated with glycerophosphocholine. Moreover, M. pneumoniae is unable to cause any detectable damage to the host cells in the absence of GlpQ. This underlines the important role of phospholipid metabolism for the virulence of M. pneumoniae. We observed that GlpQ in addition to its enzymatic activity is also involved in the control of expression of several genes, among them the glycerol transporter. Thus, GlpQ is central to the normal physiology and to pathogenicity of the minimal pathogen M. pneumoniae.

Salmonella enterica highly expressed genes are disease specific

During in vitro broth culture, bacterial gene expression is typically dominated by highly expressed factors involved in protein biosynthesis, maturation, and folding, but it is unclear if this also applies to conditions in natural environments. Here, we used a promoter trap strategy with an unstable green fluorescent protein reporter that can be detected in infected mouse tissues to identify 21 Salmonella enterica promoters with high levels of activity in a mouse enteritis model. We then measured the activities of these and 31 previously identified Salmonella promoters in both the enteritis and a murine typhoid fever model. Surprisingly, the data reveal that instead of protein biosynthesis genes, disease-specific genes such as Salmonella pathogenicity island 1 (SPI-1)-associated genes and genes involved in anaerobic respiration (enteritis) or SPI-2-associated genes and genes of the PhoP regulon (typhoid fever), respectively, dominate Salmonella in vivo gene expression. The overall functional profile of highly expressed genes suggests a marked shift in major transcriptional activities to nutrient utilization during enteritis or to fighting against the host during typhoid fever. The large proportion of known and novel essential virulence factors among the identified genes suggests that high expression levels during infection may correlate with functional relevance.

Isoprenoid biosynthesis as a target for antibacterial and antiparasitic drugs: phosphonohydroxamic acids as inhibitors of deoxyxylulose phosphate reducto-isomerase

Isoprenoid biosynthesis via the methylerythritol phosphate pathway is a target against pathogenic bacteria and the malaria parasite Plasmodium falciparum. 4-(Hydroxyamino)-4-oxobutylphosphonic acid and 4-[hydroxy(methyl)amino]-4-oxobutyl phosphonic acid, two novel inhibitors of DXR (1-deoxy-D-xylulose 5-phosphate reducto-isomerase), the second enzyme of the pathway, have been synthesized and compared with fosmidomycin, the best known inhibitor of this enzyme. The latter phosphonohydroxamic acid showed a high inhibitory activity towards DXR, much like fosmidomycin, as well as significant antibacterial activity against Escherichia coli in tests on Petri dishes.

Stress-inducible gene of Salmonella typhimurium identified by arbitrarily primed PCR of RNA

Fingerprinting of RNA by arbitrarily primed PCR (RAP) can be used to identify conditionally expressed genes in prokaryotes. Differential gene expression in Salmonella typhimurium LT2 in response to peroxide treatment was examined as a system in which to demonstrate this strategy. This treatment models the induction of bacterial protective proteins that may occur when mammalian phagocytes use peroxide to fight S. typhimurium infection. To identify genes inducible by hydrogen peroxide stress, total RNA from peroxide-treated and untreated bacterial cultures were RAP fingerprinted with six different arbitrarily selected primers. A 435-base RAP product that was differentially amplified by RAP using the reverse sequencing primer was cloned and sequenced. Northern blot analysis confirmed that the RNA corresponding to this clone, RSP435, was induced when bacteria were treated with hydrogen peroxide. The RNA was not induced in an oxyR1 mutant that constitutively expressed a subset of hydrogen peroxide-inducible genes. Using pulsed-field gel electrophoresis and dot blot hybridization to an array of induced Mud-P22 integrations, the gene corresponding to RSP435 was mapped to two places, one between 19 and 21.5 min and one between 56 and 57 min. Thus, two similar or identical stress-inducible genes were found in different parts of the genome. Identification, cloning, and mapping of the conditionally expressed RSP435 cDNA were performed entirely by physical means, demonstrating that the strategy should complement genetic methods for many prokaryotic or archaebacterial systems and should be applicable to organisms in which genetic methods are difficult to perform or have not yet been developed.