The EcoCyc Database

Insights into antibiotic resistance promoted by quinolone exposure

Quinolone-induced antibiotic resistance (QIAR) refers to the phenomenon by which bacteria exposed to sublethal levels of quinolones acquire resistance to non-quinolone antibiotics. We have explored this in Escherichia coli MG1655 using a variety of compounds and bacteria carrying a quinolone-resistance mutation in gyrase, mutations affecting the SOS response, and mutations in error-prone polymerases. The nature of the antibiotic-resistance mutations was determined by whole-genome sequencing. Exposure to low levels of most quinolones tested led to mutations conferring resistance to chloramphenicol, ampicillin, kanamycin, and tetracycline. The mutations included point mutations and deletions and could mostly be correlated with the resistance phenotype. QIAR depended upon DNA gyrase and involved the SOS response but was not dependent on error-prone polymerases. Only moxifloxacin, among the quinolones tested, did not display a significant QIAR effect. We speculate that the lack of QIAR with moxifloxacin may be attributable to it acting via a different mechanism. In addition to the concerns about antimicrobial resistance to quinolones and other compounds, QIAR presents an additional challenge in relation to the usage of quinolone antibacterials.

Protecting the Achilles heel: three FolE_I-type GTP-cyclohydrolases needed for full growth of metal-resistant Cupriavidus metallidurans under a variety of conditions

In Cupriavidus metallidurans and other bacteria, biosynthesis of the essential biochemical cofactor tetrahydrofolate (THF) initiates from guanosine triphosphate (GTP). This step is catalyzed by FolE_I-type GTP cyclohydrolases, which are either zinc-dependent FolE_IA-type or metal-promiscuous FolE_IB-type enzymes. As THF is also essential for GTP biosynthesis, GTP and THF synthesis form a cooperative cycle, which may be influenced by the cellular homeostasis of zinc and other metal cations. Metal-resistant C. metallidurans harbors one FolE_IA-type and two FolE_IB-type enzymes. All three proteins were produced in Escherichia coli. FolE_IA was indeed zinc dependent and the two FolE_IB enzymes metal-promiscuous GTP cyclohydrolases in vitro, the latter, for example, functioning with iron, manganese, or cobalt. Single and double mutants of C. metallidurans with deletions in the folE_I genes were constructed to analyze the contribution of the individual FolE_I-type enzymes under various conditions. FolE_IA was required in the presence of cadmium, hydrogen peroxide, metal chelators, and under general metal starvation conditions. FolE_IB1 was important when zinc uptake was impaired in cells without the zinc importer ZupT (ZIP family) and in the presence of trimethoprim, an inhibitor of THF biosynthesis. FolE_IB2 was needed under conditions of low zinc and cobalt but high magnesium availability. Together, these data demonstrate that C. metallidurans requires all three enzymes to allow efficient growth under a variety of conditions.IMPORTANCETetrahydrofolate (THF) is an important cofactor in microbial biochemistry. This "Achilles heel" of metabolism has been exploited by anti-metabolites and antibiotics such as sulfonamide and trimethoprim. Since THF is essential for the synthesis of guanosine triphosphate (GTP) and THF biosynthesis starts from GTP, synthesis of both compounds forms a cooperative cycle. The first step of THF synthesis by GTP cyclohydrolases (FolEs) is metal dependent and catalyzed by zinc- or metal-promiscuous enzymes, so that the cooperative THF and GTP synthesis cycle may be influenced by the homeostasis of several metal cations, especially that of zinc. The metal-resistant bacterium C. metallidurans needs three FolEs to grow in environments with both high and low zinc and cadmium content. Consequently, bacterial metal homeostasis is required to guarantee THF biosynthesis.

Bacterial acetate metabolism and its influence on human epithelia

Short-chain fatty acids are known modulators of host-microbe interactions and can affect human health, inflammation, and outcomes of microbial infections. Acetate is the most abundant but least well-studied of these modulators, with most studies focusing on propionate and butyrate, which are considered to be more potent. In this mini-review, we summarize current knowledge of acetate as an important anti-inflammatory modulator of interactions between hosts and microorganisms. This includes a summary of the pathways by which acetate is metabolized by bacteria and human cells, the functions of acetate in bacterial cells, and the impact that microbially derived acetate has on human immune function.

Escherichia coli K-12 Transcriptomics for Assessing the Mechanism of Action of High-Power Ultrasound

An investigation into the mechanisms of action on bacteria involving exposure to stress factors was conducted in this study. The effects of ultrasound on Escherichia coli K-12 MG1655 and its isogenic mutant, ∆gadW, under high power ultrasound treatments (26 kHz) were screened and identified by analysing their transcriptome differences between primary and secondary sequential treatments using RNA-Seq. This also helped to assess any developed protection for cells between different generations. According to our results, 1825 genes of all tested conditions were expressed, playing different roles in the cell. The expression of these genes is associated with DNA damage, cell membrane integrity, and also metabolic effects. The studied strains also showed different differential expressed genes (DEGs), with some genes being directly responsible for defence mechanisms, while others play an indirect effect due to cell damage. A gradual decrease in the expression of the genes, as we moved from just one cycle of ultrasound treatment to sequential treatment, was evident from a heat map analysis of the results. Overall, E. coli K-12 builds a self-protection mechanism by increasing the expression of genes involved in the respiration for increased growth, and production of flagellum and pili. It can be concluded that high power ultrasound is a technology that triggers several different defence mechanisms which directly link to E. coli.

Analyzing the Systems Biology Effects of COVID-19 mRNA Vaccines to Assess Their Safety and Putative Side Effects

COVID-19 vaccines have been instrumental tools in reducing the impact of SARS-CoV-2 infections around the world by preventing 80% to 90% of hospitalizations and deaths from reinfection, in addition to preventing 40% to 65% of symptomatic illnesses. However, the simultaneous large-scale vaccination of the global population will indubitably unveil heterogeneity in immune responses as well as in the propensity to developing post-vaccine adverse events, especially in vulnerable individuals. Herein, we applied a systems biology workflow, integrating vaccine transcriptional signatures with chemogenomics, to study the pharmacological effects of mRNA vaccines. First, we derived transcriptional signatures and predicted their biological effects using pathway enrichment and network approaches. Second, we queried the Connectivity Map (CMap) to prioritize adverse events hypotheses. Finally, we accepted higher-confidence hypotheses that have been predicted by independent approaches. Our results reveal that the mRNA-based BNT162b2 vaccine affects immune response pathways related to interferon and cytokine signaling, which should lead to vaccine success, but may also result in some adverse events. Our results emphasize the effects of BNT162b2 on calcium homeostasis, which could be contributing to some frequently encountered adverse events related to mRNA vaccines. Notably, cardiac side effects were signaled in the CMap query results. In summary, our approach has identified mechanisms underlying both the expected protective effects of vaccination as well as possible post-vaccine adverse effects. Our study illustrates the power of systems biology approaches in improving our understanding of the comprehensive biological response to vaccination against COVID-19.

Escherichia coli cell factories with altered chromosomal replication scenarios exhibit accelerated growth and rapid biomass production

Background

Generally, bacteria have a circular genome with a single replication origin for each replicon, whereas archaea and eukaryotes can have multiple replication origins in a single chromosome. In Escherichia coli, bidirectional DNA replication is initiated at the origin of replication (oriC) and arrested by the 10 termination sites (terA–J).

Results

We constructed E. coli derivatives with additional or ectopic replication origins, which demonstrate the relationship between DNA replication and cell physiology. The cultures of E. coli derivatives with multiple replication origins contained an increased fraction of replicating chromosomes and the cells varied in size. Without the original oriC, E. coli derivatives with double ectopic replication origins manifested impaired growth irrespective of growth conditions and enhanced cell size, and exhibited excessive and asynchronous replication initiation. The generation time of an E. coli strain with three replication origins decreased in a minimal medium supplemented with glucose as the sole carbon source. As well as cell growth, the introduction of additional replication origins promoted increased biomass production.

Conclusions

Balanced cell growth and physiological stability of E. coli under rapid growth condition are affected by changes in the position and number of replication origins. Additionally, we show that, for the first time to our knowledge, the introduction of replication initiation sites to the chromosome promotes cell growth and increases protein production.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-022-01851-z.

Dynamic landscape of protein occupancy across the Escherichia coli chromosome

Free-living bacteria adapt to environmental change by reprogramming gene expression through precise interactions of hundreds of DNA-binding proteins. A predictive understanding of bacterial physiology requires us to globally monitor all such protein-DNA interactions across a range of environmental and genetic perturbations. Here, we show that such global observations are possible using an optimized version of in vivo protein occupancy display technology (in vivo protein occupancy display-high resolution, IPOD-HR) and present a pilot application to Escherichia coli. We observe that the E. coli protein-DNA interactome organizes into 2 distinct prototypic features: (1) highly dynamic condition-dependent transcription factor (TF) occupancy; and (2) robust kilobase scale occupancy by nucleoid factors, forming silencing domains analogous to eukaryotic heterochromatin. We show that occupancy dynamics across a range of conditions can rapidly reveal the global transcriptional regulatory organization of a bacterium. Beyond discovery of previously hidden regulatory logic, we show that these observations can be utilized to computationally determine sequence specificity models for the majority of active TFs. Our study demonstrates that global observations of protein occupancy combined with statistical inference can rapidly and systematically reveal the transcriptional regulatory and structural features of a bacterial genome. This capacity is particularly crucial for non-model bacteria that are not amenable to routine genetic manipulation.

Antibiotic tolerance, persistence, and resistance of the evolved minimal cell, Mycoplasma mycoides JCVI-Syn3B

Antibiotic resistance is a growing problem, but bacteria can evade antibiotic treatment via tolerance and persistence. Antibiotic persisters are a small subpopulation of bacteria that tolerate antibiotics due to a physiologically dormant state. Hence, persistence is considered a major contributor to the evolution of antibiotic-resistant and relapsing infections. Here, we used the synthetically developed minimal cell Mycoplasma mycoides JCVI-Syn3B to examine essential mechanisms of antibiotic survival. The minimal cell contains only 473 genes, and most genes are essential. Its reduced complexity helps to reveal hidden phenomenon and fundamental biological principles can be explored because of less redundancy and feedback between systems compared to natural cells. We found that Syn3B evolves antibiotic resistance to different types of antibiotics expeditiously. The minimal cell also tolerates and persists against multiple antibiotics. It contains a few already identified persister-related genes, although lacking many systems previously linked to persistence (e.g. toxin-antitoxin systems, ribosome hibernation genes).

Behind the shield of Czc: ZntR controls expression of the gene for the zinc-exporting P-type ATPase ZntA in Cupriavidus metallidurans

In the metallophilic beta-proteobacterium Cupriavidus metallidurans, the plasmid-encoded Czc metal homeostasis system adjusts the periplasmic zinc, cobalt and cadmium concentration, which influences subsequent uptake of these metals into the cytoplasm. Behind this shield, the P_IB2-type APTase ZntA is responsible for removal of surplus cytoplasmic zinc ions, thereby providing a second level of defense against toxic zinc concentrations. ZntA is the counterpart to the Zur-regulated zinc uptake system ZupT and other import systems; however, the regulator of zntA expression was unknown. The chromid-encoded zntA gene is adjacent to the genes czcI₂C₂B₂', which are located on the complementary DNA strand and transcribed from a common promoter region. These genes encode homologs of plasmid pMOL30-encoded Czc components. Candidates for possible regulators of zntA were identified and subsequently tested: CzcI, CzcI₂, and the MerR-type gene products of the locus tags Rmet_2302, Rmet_0102, Rmet_3456. This led to the identification of Rmet_3456 as ZntR, the main regulator of zntA expression. Moreover, both CzcIs decreased Czc-mediated metal resistance, possibly to avoid "over-excretion" of periplasmic zinc ions, which could result in zinc starvation due to diminished zinc uptake into the cytoplasm. Rmet_2302 was identified as CadR, the regulator of the cadA gene for an important cadmium-exporting P_IB2-type ATPase, which provides another system for removal of cytoplasmic zinc and cadmium. Rmet_0102 was not involved in regulation of the metal resistance systems examined here. Thus, ZntR forms a complex regulatory network with CadR, Zur and the CzcIs. Moreover, these discriminating regulatory proteins assign the efflux systems to their particular function.ImportanceZinc is an essential metal for numerous organisms from humans to bacteria. The transportome of zinc uptake and efflux systems controls the overall cellular composition and zinc content in a double feed-back loop. Zinc starvation mediates, via the Zur regulator, an up-regulation of the zinc import capacity via the ZIP-type zinc importer ZupT and an amplification of zinc storage capacity, which together raise the cellular zinc content again. On the other hand, an increasing zinc content leads to ZntR-mediated up-regulation of the zinc efflux system ZntA, which decreases the zinc content. Together, the Zur regulon components and ZntR/ZntA balance the cellular zinc content under both high external zinc concentrations and zinc starvation conditions.

Best practices on the differential expression analysis of multi-species RNA-seq

Advances in transcriptome sequencing allow for simultaneous interrogation of differentially expressed genes from multiple species originating from a single RNA sample, termed dual or multi-species transcriptomics. Compared to single-species differential expression analysis, the design of multi-species differential expression experiments must account for the relative abundances of each organism of interest within the sample, often requiring enrichment methods and yielding differences in total read counts across samples. The analysis of multi-species transcriptomics datasets requires modifications to the alignment, quantification, and downstream analysis steps compared to the single-species analysis pipelines. We describe best practices for multi-species transcriptomics and differential gene expression.

Systems-Level Chemical Biology to Accelerate Antibiotic Drug Discovery

Drug-resistant bacterial infections pose an imminent and growing threat to public health. The discovery and development of new antibiotics of novel chemical class and mode of action that are unsusceptible to existing resistance mechanisms is imperative for tackling this threat. Modern industrial drug discovery, however, has failed to provide new drugs of this description, as it is dependent largely on a reductionist genes-to-drugs research paradigm. We posit that the lack of success in new antibiotic drug discovery is due in part to a lack of understanding of the bacterial cell system as whole. A fundamental understanding of the architecture and function of bacterial systems has been elusive but is of critical importance to design strategies to tackle drug-resistant bacterial pathogens.Increasingly, systems-level approaches are rewriting our understanding of the cell, defining a dense network of redundant and interacting components that resist perturbations of all kinds, including by antibiotics. Understanding the network properties of bacterial cells requires integrative, systematic, and genome-scale approaches. These methods strive to understand how the phenotypic behavior of bacteria emerges from the many interactions of individual molecular components that constitute the system. With the ability to examine genomic, transcriptomic, proteomic, and metabolomic consequences of, for example, genetic or chemical perturbations, researchers are increasingly moving away from one-gene-at-a-time studies to consider the system-wide response of the cell. Such measurements are demonstrating promise as quantitative tools, powerful discovery engines, and robust hypothesis generators with great value to antibiotic drug discovery.In this Account, we describe our thinking and findings using systems-level studies aimed at understanding bacterial physiology broadly and in uncovering new antibacterial chemical matter of novel mechanism. We share our systems-level toolkit and detail recent technological developments that have enabled unprecedented acquisition of genome-wide interaction data. We focus on three types of interactions: gene-gene, chemical-gene, and chemical-chemical. We provide examples of their use in understanding cell networks and how these insights might be harnessed for new antibiotic discovery. By example, we show the application of these principles in mapping genetic networks that underpin phenotypes of interest, characterizing genes of unknown function, validating small-molecule screening platforms, uncovering novel chemical probes and antibacterial leads, and delineating the mode of action of antibacterial chemicals. We also discuss the importance of computation to these approaches and its probable dominance as a tool for systems approaches in the future. In all, we advocate for the use of systems-based approaches as discovery engines in antibacterial research, both as powerful tools and to stimulate innovation.

Antibiotic tolerance is associated with a broad and complex transcriptional response in E. coli

Antibiotic treatment kills a large portion of a population, while a small, tolerant subpopulation survives. Tolerant bacteria disrupt antibiotic efficacy and increase the likelihood that a population gains antibiotic resistance, a growing health concern. We examined how E. coli transcriptional networks changed in response to lethal ampicillin concentrations. We are the first to apply transcriptional regulatory network (TRN) analysis to antibiotic tolerance by leveraging existing knowledge and our transcriptional data. TRN analysis shows that gene expression changes specific to ampicillin treatment are likely caused by specific sigma and transcription factors typically regulated by proteolysis. These results demonstrate that to survive lethal concentration of ampicillin specific regulatory proteins change activity and cause a coordinated transcriptional response that leverages multiple gene systems.

Mutant Strains of Escherichia coli and Methicillin-Resistant Staphylococcus aureus Obtained by Laboratory Selection To Survive on Metallic Copper Surfaces

Artificial laboratory evolution was used to produce mutant strains of Escherichia coli and methicillin-resistant Staphylococcus aureus (MRSA) able to survive on antimicrobial metallic copper surfaces. These mutants were 12- and 60-fold less susceptible to the copper-mediated contact killing process than their respective parent strains. Growth levels of the mutant and its parent in complex growth medium were similar. Tolerance to copper ions of the mutants was unchanged. The mutant phenotype remained stable over about 250 generations under nonstress conditions. The mutants and their respective parental strains accumulated copper released from the metallic surfaces to similar extents. Nevertheless, only the parental strains succumbed to copper stress when challenged on metallic copper surfaces, suffering complete destruction of the cell structure. Whole-genome sequencing and global transcriptome analysis were used to decipher the genetic alterations in the mutant strains; however, these results did not explain the copper-tolerance phenotypes on the systemic level. Instead, the mutants shared features with those of stressed bacterial subpopulations entering the early or "shallow" persister state. In contrast to the canonical persister state, however, the ability to survive on solid copper surfaces was adopted by the majority of the mutant strain population. This indicated that application of solid copper surfaces in hospitals and elsewhere has to be accompanied by strict cleaning regimens to keep the copper surfaces active and prevent evolution of tolerant mutant strains.IMPORTANCE Microbes are rapidly killed on solid copper surfaces by contact killing. Copper surfaces thus have an important role to play in preventing the spread of nosocomial infections. Bacteria adapt to challenging natural and clinical environments through evolutionary processes, for instance, by acquisition of beneficial spontaneous mutations. We wish to address the question of whether mutants can be selected that have evolved to survive contact killing on solid copper surfaces. We isolated such mutants from Escherichia coli and methicillin-resistant Staphylococcus aureus (MRSA) by artificial laboratory evolution. The ability to survive on solid copper surfaces was a stable phenotype of the mutant population and not restricted to a small subpopulation. As a consequence, standard operation procedures with strict hygienic measures are extremely important to prevent the emergence and spread of copper-surface-tolerant persister-like bacterial strains if copper surfaces are to be sustainably used to limit the spread of pathogenic bacteria, e.g., to curb nosocomial infections.

A brief note on the properties of linear pathways

Linear metabolic pathways are the simplest network architecture we find in metabolism and are a good starting point to gain insight into the operating principles of metabolic control. Linear pathways possess some well-known properties, such as a bias of flux control towards the first few steps of the pathway as well as the lack of flux control at reactions close to equilibrium. In both cases, a rationale for these behaviors is given in terms of how elasticities transmit changes through a pathway. A discussion is given on the fundamental role that two reaction step sections play in a linear pathway when transmitting changes. For a pathway with irreversible steps, the deconstruction is straight forward and includes a product of local response coefficients that cascade along the pathway. When reversibility is included, the picture became more complex but a relationship in terms of the local response coefficients if derived that includes the reverse response coefficients and highlights the interplay between the forward and backward transmission of changes during a perturbation.

SlyA Transcriptional Regulator Is Not Directly Affected by ppGpp Levels

The SlyA transcriptional regulator controls the expression of genes involved in virulence and production of surface components in S. Typhimurium and E. coli. Its mode of action is mainly explained by its antagonism with the H-NS repressor for the same DNA binding regions. Interestingly, it has been reported that the alarmone ppGpp promotes SlyA dimerization and DNA binding at the promoter of pagC, enhancing the expression of this gene in Salmonella. A recurring problem in the field of stringent response has been to find a way of following ppGpp levels in vivo in real time. We thought that SlyA, as a ppGpp responsive ligand, was a perfect candidate for the development of a specific ppGpp biosensor. Therefore, we decided to characterize in depth this SlyA control by ppGpp. However, using various genes whose expression is activated by SlyA, as reporters, we showed that ppGpp does not affect SlyA regulation in vivo. In addition, modulating ppGpp levels did not affect SlyA dimerization in vivo, and did not impact its binding to DNA in vitro. We finally showed that ppGpp is required for the expression of hlyE in E. coli, a gene also activated by SlyA, and propose that both regulators are independently required for hlyE expression. The initial report of ppGpp action on SlyA might be explained by a similar action of SlyA and ppGpp on pagC expression, and the complexity of promoters controlled by several global regulators, such as the promoters of pagC in Salmonella or hlyE in E. coli.

Simultaneous cross-evaluation of heterogeneous E. coli datasets via mechanistic simulation

The extensive heterogeneity of biological data poses challenges to analysis and interpretation. Construction of a large-scale mechanistic model of Escherichia coli enabled us to integrate and cross-evaluate a massive, heterogeneous dataset based on measurements reported by various groups over decades. We identified inconsistencies with functional consequences across the data, including that the total output of the ribosomes and RNA polymerases described by data are not sufficient for a cell to reproduce measured doubling times, that measured metabolic parameters are neither fully compatible with each other nor with overall growth, and that essential proteins are absent during the cell cycle-and the cell is robust to this absence. Finally, considering these data as a whole leads to successful predictions of new experimental outcomes, in this case protein half-lives.

Metabolic engineering for glycoglycerolipids production in E. coli: Tuning phosphatidic acid and UDP-glucose pathways

Glycolipids are target molecules in biotechnology and biomedicine as biosurfactants, biomaterials and bioactive molecules. An engineered E. coli strain for the production of glycoglycerolipids (GGL) used the MG517 glycolipid synthase from M. genitalium for glucosyl transfer from UDPGlc to diacylglycerol acceptor (Mora-Buyé et al., 2012). The intracellular diacylglycerol pool proved to be the limiting factor for GGL production. Here we designed different metabolic engineering strategies to enhance the availability of precursor substrates for the glycolipid synthase by modulating fatty acids, acyl donor and phosphatidic acid biosynthesis. Knockouts of tesA, fadE and fabR genes involved in fatty acids degradation, overexpression of the transcriptional regulator FadR, the acyltransferases PlsB and C, and the pyrophosphatase Cdh for phosphatidic acid biosynthesis, as well as the phosphatase PgpB for conversion to diacylglycerol were explored with the aim of improving GGL titers. Among the different engineered strains, the ΔtesA strain co-expressing MG517 and a fusion PlsCxPgpB protein was the best producer, with a 350% increase of GGL titer compared to the parental strain expressing MG517 alone. Attempts to boost UDPGlc availability by overexpressing the uridyltransferase GalU or knocking out the UDP-sugar diphosphatase encoding gene ushA did not further improve GGL titers. Most of the strains produced GGL containing a variable number of glucosyl units from mono-to tetra-saccharides. Interestingly, the strains co-expressing Cdh showed a shift in the GGL profile towards the diglucosylated lipid (up to 80% of total GGLs) whereas the strains with a fadR knockout presented a higher amount of unsaturated acyl chains. In all cases, GGL production altered the lipidic composition of the E. coli membrane, observing that GGL replace phosphatidylethanolamine to maintain the overall membrane charge balance.

Attractor Concepts to Evaluate the Transcriptome-wide Dynamics Guiding Anaerobic to Aerobic State Transition in Escherichia coli

For any dynamical system, like living organisms, an attractor state is a set of variables or mechanisms that converge towards a stable system behavior despite a wide variety of initial conditions. Here, using multi-dimensional statistics, we investigate the global gene expression attractor mechanisms shaping anaerobic to aerobic state transition (AAT) of Escherichia coli in a bioreactor at early times. Out of 3,389 RNA-Seq expression changes over time, we identified 100 sharply changing genes that are key for guiding 1700 genes into the AAT attractor basin. Collectively, these genes were named as attractor genes constituting of 6 dynamic clusters. Apart from the expected anaerobic (glycolysis), aerobic (TCA cycle) and fermentation (succinate pathways) processes, sulphur metabolism, ribosome assembly and amino acid transport mechanisms together with 332 uncharacterised genes are also key for AAT. Overall, our work highlights the importance of multi-dimensional statistical analyses for revealing novel processes shaping AAT.

Drosophila-associated bacteria differentially shape the nutritional requirements of their host during juvenile growth

The interplay between nutrition and the microbial communities colonizing the gastrointestinal tract (i.e., gut microbiota) determines juvenile growth trajectory. Nutritional deficiencies trigger developmental delays, and an immature gut microbiota is a hallmark of pathologies related to childhood undernutrition. However, how host-associated bacteria modulate the impact of nutrition on juvenile growth remains elusive. Here, using gnotobiotic Drosophila melanogaster larvae independently associated with Acetobacter pomorum^WJL (Ap^WJL) and Lactobacillus plantarum^NC8 (Lp^NC8), 2 model Drosophila-associated bacteria, we performed a large-scale, systematic nutritional screen based on larval growth in 40 different and precisely controlled nutritional environments. We combined these results with genome-based metabolic network reconstruction to define the biosynthetic capacities of Drosophila germ-free (GF) larvae and its 2 bacterial partners. We first established that Ap^WJL and Lp^NC8 differentially fulfill the nutritional requirements of the ex-GF larvae and parsed such difference down to individual amino acids, vitamins, other micronutrients, and trace metals. We found that Drosophila-associated bacteria not only fortify the host’s diet with essential nutrients but, in specific instances, functionally compensate for host auxotrophies by either providing a metabolic intermediate or nutrient derivative to the host or by uptaking, concentrating, and delivering contaminant traces of micronutrients. Our systematic work reveals that beyond the molecular dialogue engaged between the host and its bacterial partners, Drosophila and its associated bacteria establish an integrated nutritional network relying on nutrient provision and utilization.

A study of gnotobiotic fruit flies shows that the animal is involved in an integrated nutritional network with its facultative commensal bacteria, centered around the utilization and sharing of nutrients.

Valine-Induced Isoleucine Starvation in Escherichia coli K-12 Studied by Spike-In Normalized RNA Sequencing

Escherichia coli cells respond to a period of famine by globally reorganizing their gene expression. The changes are known as the stringent response, which is orchestrated by the alarmone ppGpp that binds directly to RNA polymerase. The resulting changes in gene expression are particularly well studied in the case of amino acid starvation. We used deep RNA sequencing in combination with spike-in cells to measure global changes in the transcriptome after valine-induced isoleucine starvation of a standard E. coli K12 strain. Owing to the whole-cell spike-in method that eliminates variations in RNA extraction efficiency between samples, we show that ribosomal RNA levels are reduced during isoleucine starvation and we quantify how the change in cellular RNA content affects estimates of gene regulation. Specifically, we show that standard data normalization relying on sample sequencing depth underestimates the number of down-regulated genes in the stringent response and overestimates the number of up-regulated genes by approximately 40%. The whole-cell spike-in method also made it possible to quantify how rapidly the pool of total messenger RNA (mRNA) decreases upon amino acid starvation. A principal component analysis showed that the first two components together described 69% of the variability of the data, underlining that large and highly coordinated regulons are at play in the stringent response. The induction of starvation by sudden addition of high valine concentrations provoked prominent regulatory responses outside of the expected ppGpp, RpoS, and Lrp regulons. This underlines the notion that with the high resolution possible in deep RNA sequencing analysis, any different starvation method (e.g., nitrogen-deprivation, removal of an amino acid from an auxotroph strain, or valine addition to E. coli K12 strains) will produce measurable variations in the stress response produced by the cells to cope with the specific treatment.

Proteolytic Queues at ClpXP Increase Antibiotic Tolerance

Antibiotic tolerance is a widespread phenomenon that renders antibiotic treatments less effective and facilitates antibiotic resistance. Here we explore the role of proteases in antibiotic tolerance, short-term population survival of antibiotics, using queueing theory (i.e., the study of waiting lines), computational models, and a synthetic biology approach. Proteases are key cellular components that degrade proteins and play an important role in a multidrug tolerant subpopulation of cells, called persisters. We found that queueing at the protease ClpXP increases antibiotic tolerance ∼80 and ∼60 fold in an E. coli population treated with ampicillin and ciprofloxacin, respectively. There does not appear to be an effect on antibiotic persistence, which we distinguish from tolerance based on population decay. These results demonstrate that proteolytic queueing is a practical method to probe proteolytic activity in bacterial tolerance and related genes, while limiting the unintended consequences frequently caused by gene knockout and overexpression.

Genome-Based Metabolic Reconstruction Unravels the Key Role of B12 in Methionine Auxotrophy of an Ortho-Phenylphenol-Degrading Sphingomonas haloaromaticamans

Auxotrophy to amino acids and vitamins is a common feature in the bacterial world shaping microbial communities through cross-feeding relations. The amino acid auxotrophy of pollutant-degrading bacteria could hamper their bioremediation potential, however, the underlying mechanisms of auxotrophy remain unexplored. We employed genome sequence-based metabolic reconstruction to identify potential mechanisms driving the amino acid auxotrophy of a Sphingomonas haloaromaticamans strain degrading the fungicide ortho-phenylphenol (OPP) and provided further verification for the identified mechanisms via in vitro bacterial assays. The analysis identified potential gaps in the biosynthesis of isoleucine, phenylalanine and tyrosine, while methionine biosynthesis was potentially effective, relying though in the presence of B12. Supplementation of the bacterium with the four amino acids in all possible combinations rescued its degrading capacity only with methionine. Genome sequence-based metabolic reconstruction and analysis suggested that the bacterium was incapable of de novo biosynthesis of B12 (missing genes for the construction of the corrin ring) but carried a complete salvage pathway for corrinoids uptake from the environment, transmembrane transportation and biosynthesis of B12. In line with this the bacterium maintained its degrading capacity and growth when supplied with environmentally relevant B12 concentrations (i.e., 0.1 ng ml^–1). Using genome-based metabolic reconstruction and in vitro testing we unraveled the mechanism driving the auxotrophy of a pesticide-degrading S. haloaromaticamans. Further studies will investigate the corrinoids preferences of S. haloaromaticamans for optimum growth and OPP degradation.

Manganese Is Required for the Rapid Recovery of DNA Synthesis following Oxidative Challenge in Escherichia coli

Divalent metals such as iron and manganese play an important role in the cellular response to oxidative challenges and are required as cofactors by many enzymes. However, how these metals affect replication after oxidative challenge is not known. Here, we show that replication in Escherichia coli is inhibited following a challenge with hydrogen peroxide and requires manganese for the rapid recovery of DNA synthesis. We show that the manganese-dependent recovery of DNA synthesis occurs independent of lesion repair, modestly improves cell survival, and is associated with elevated rates of mutagenesis. The Mn-dependent mutagenesis involves both replicative and translesion polymerases and requires prior disruption by H₂O₂ to occur. Taking these findings together, we propose that replication in E. coli is likely to utilize an iron-dependent enzyme(s) that becomes oxidized and inactivated during oxidative challenges. The data suggest that manganese remetallates these or alternative enzymes to allow genomic DNA replication to resume, although with reduced fidelity.IMPORTANCE Iron and manganese play important roles in how cell's cope with oxygen stress. However, how these metals affect the ability of cells to replicate after oxidative challenges is not known. Here, we show that replication in Escherichia coli is inhibited following a challenge with hydrogen peroxide and requires manganese for the rapid recovery of DNA synthesis. The manganese-dependent recovery of DNA synthesis occurs independently of lesion repair and modestly improves survival, but it also increases the mutation rate in cells. The results imply that replication in E. coli is likely to utilize an iron-dependent enzyme(s) that becomes oxidized and inactivated during oxidative challenges. We propose that manganese remetallates these or alternative enzymes to allow genomic DNA replication to resume, although with reduced fidelity.

The MACADAM database: a MetAboliC pAthways DAtabase for Microbial taxonomic groups for mining potential metabolic capacities of archaeal and bacterial taxonomic groups

Progress in genome sequencing and bioinformatics opens up new possibilities, including that of correlating genome annotations with functional information such as metabolic pathways. Thanks to the development of functional annotation databases, scientists are able to link genome annotations with functional annotations. We present MetAboliC pAthways DAtabase for Microbial taxonomic groups (MACADAM) here, a user-friendly database that makes it possible to find presence/absence/completeness statistics for metabolic pathways at a given microbial taxonomic position. For each prokaryotic 'RefSeq complete genome', MACADAM builds a pathway genome database (PGDB) using Pathway Tools software based on MetaCyc data that includes metabolic pathways as well as associated metabolites, reactions and enzymes. To ensure the highest quality of the genome functional annotation data, MACADAM also contains MicroCyc, a manually curated collection of PGDBs; Functional Annotation of Prokaryotic Taxa (FAPROTAX), a manually curated functional annotation database; and the IJSEM phenotypic database. The MACADAM database contains 13 509 PGDBs (13 195 bacterial and 314 archaeal), 1260 unique metabolic pathways, completed with 82 functional annotations from FAPROTAX and 16 from the IJSEM phenotypic database. MACADAM contains a total of 7921 metabolites, 592 enzymatic reactions, 2134 EC numbers and 7440 enzymes. MACADAM can be queried at any rank of the NCBI taxonomy (from phyla to species). It provides the possibility to explore functional information completed with metabolites, enzymes, enzymatic reactions and EC numbers. MACADAM returns a tabulated file containing a list of pathways with two scores (pathway score and pathway frequency score) that are present in the queried taxa. The file also contains the names of the organisms in which the pathways are found and the metabolic hierarchy associated with the pathways. Finally, MACADAM can be downloaded as a single file and queried with SQLite or python command lines or explored through a web interface.

The MACADAM database: a MetAboliC pAthways DAtabase for Microbial taxonomic groups for mining potential metabolic capacities of archaeal and bacterial taxonomic groups

Progress in genome sequencing and bioinformatics opens up new possibilities, including that of correlating genome annotations with functional information such as metabolic pathways. Thanks to the development of functional annotation databases, scientists are able to link genome annotations with functional annotations. We present MetAboliC pAthways DAtabase for Microbial taxonomic groups (MACADAM) here, a user-friendly database that makes it possible to find presence/absence/completeness statistics for metabolic pathways at a given microbial taxonomic position. For each prokaryotic 'RefSeq complete genome', MACADAM builds a pathway genome database (PGDB) using Pathway Tools software based on MetaCyc data that includes metabolic pathways as well as associated metabolites, reactions and enzymes. To ensure the highest quality of the genome functional annotation data, MACADAM also contains MicroCyc, a manually curated collection of PGDBs; Functional Annotation of Prokaryotic Taxa (FAPROTAX), a manually curated functional annotation database; and the IJSEM phenotypic database. The MACADAM database contains 13 509 PGDBs (13 195 bacterial and 314 archaeal), 1260 unique metabolic pathways, completed with 82 functional annotations from FAPROTAX and 16 from the IJSEM phenotypic database. MACADAM contains a total of 7921 metabolites, 592 enzymatic reactions, 2134 EC numbers and 7440 enzymes. MACADAM can be queried at any rank of the NCBI taxonomy (from phyla to species). It provides the possibility to explore functional information completed with metabolites, enzymes, enzymatic reactions and EC numbers. MACADAM returns a tabulated file containing a list of pathways with two scores (pathway score and pathway frequency score) that are present in the queried taxa. The file also contains the names of the organisms in which the pathways are found and the metabolic hierarchy associated with the pathways. Finally, MACADAM can be downloaded as a single file and queried with SQLite or python command lines or explored through a web interface.

Redox-Sensing Iron-Sulfur Cluster Regulators

SIGNIFICANCE

Iron-sulfur cluster proteins carry out multiple functions, including as regulators of gene transcription/translation in response to environmental stimuli. In all known cases, the cluster acts as the sensory module, where the inherent reactivity/fragility of iron-sulfur clusters with small/redox-active molecules is exploited to effect conformational changes that modulate binding to DNA regulatory sequences. This promotes an often substantial reprogramming of the cellular proteome that enables the organism or cell to adapt to, or counteract, its changing circumstances. Recent Advances: Significant progress has been made recently in the structural and mechanistic characterization of iron-sulfur cluster regulators and, in particular, the O₂ and NO sensor FNR, the NO sensor NsrR, and WhiB-like proteins of Actinobacteria. These are the main focus of this review.

CRITICAL ISSUES

Striking examples of how the local environment controls the cluster sensitivity and reactivity are now emerging, but the basis for this is not yet fully understood for any regulatory family.

FUTURE DIRECTIONS

Characterization of iron-sulfur cluster regulators has long been hampered by a lack of high-resolution structural data. Although this still presents a major future challenge, recent advances now provide a firm foundation for detailed understanding of how a signal is transduced to effect gene regulation. This requires the identification of often unstable intermediate species, which are difficult to detect and may be hard to distinguish using traditional techniques. Novel approaches will be required to solve these problems.

Repurposing type III polyketide synthase as a malonyl-CoA biosensor for metabolic engineering in bacteria

Malonyl-CoA is an important central metabolite for the production of diverse valuable chemicals including natural products, but its intracellular availability is often limited due to the competition with essential cellular metabolism. Several malonyl-CoA biosensors have been developed for high-throughput screening of targets increasing the malonyl-CoA pool. However, they are limited for use only in Escherichia coli and Saccharomyces cerevisiae and require multiple signal transduction steps. Here we report development of a colorimetric malonyl-CoA biosensor applicable in three industrially important bacteria: E. coli, Pseudomonas putida, and Corynebacterium glutamicum RppA, a type III polyketide synthase producing red-colored flaviolin, was repurposed as a malonyl-CoA biosensor in E. coli Strains with enhanced malonyl-CoA accumulation were identifiable by the colorimetric screening of cells showing increased red color. Other type III polyketide synthases could also be repurposed as malonyl-CoA biosensors. For target screening, a 1,858 synthetic small regulatory RNA library was constructed and applied to find 14 knockdown gene targets that generally enhanced malonyl-CoA level in E. coli These knockdown targets were applied to produce two polyketide (6-methylsalicylic acid and aloesone) and two phenylpropanoid (resveratrol and naringenin) compounds. Knocking down these genes alone or in combination, and also in multiple different E. coli strains for two polyketide cases, allowed rapid development of engineered strains capable of enhanced production of 6-methylsalicylic acid, aloesone, resveratrol, and naringenin to 440.3, 30.9, 51.8, and 103.8 mg/L, respectively. The malonyl-CoA biosensor developed here is a simple tool generally applicable to metabolic engineering of microorganisms to achieve enhanced production of malonyl-CoA-derived chemicals.

The Pseudomonas aeruginosa Complement of Lactate Dehydrogenases Enables Use of d- and l-Lactate and Metabolic Cross-Feeding

Lactate is thought to serve as a carbon and energy source during chronic infections. Sites of bacterial colonization can contain two enantiomers of lactate: the l-form, generally produced by the host, and the d-form, which is usually produced by bacteria, including the pulmonary pathogen Pseudomonas aeruginosa. Here, we characterize P. aeruginosa’s set of four enzymes that it can use to interconvert pyruvate and lactate, the functions of which depend on the availability of oxygen and specific enantiomers of lactate. We also show that anaerobic pyruvate fermentation triggers production of the aerobic d-lactate dehydrogenase in both liquid cultures and biofilms, thereby enabling metabolic cross-feeding of lactate over time and space between subpopulations of cells. These metabolic pathways might contribute to P. aeruginosa growth and survival in the lung.

Pseudomonas aeruginosa is the most common cause of chronic, biofilm-based lung infections in patients with cystic fibrosis (CF). Sputum from patients with CF has been shown to contain oxic and hypoxic subzones as well as millimolar concentrations of lactate. Here, we describe the physiological roles and expression patterns of P. aeruginosa lactate dehydrogenases in the contexts of different growth regimes. P. aeruginosa produces four enzymes annotated as lactate dehydrogenases, three of which are known to contribute to anaerobic or aerobic metabolism in liquid cultures. These three are LdhA, which reduces pyruvate to d-lactate during anaerobic survival, and LldE and LldD, which oxidize d-lactate and l-lactate, respectively, during aerobic growth. We demonstrate that the fourth enzyme, LldA, performs redundant l-lactate oxidation during growth in aerobic cultures in both a defined MOPS (morpholinepropanesulfonic acid)-based medium and synthetic CF sputum media. However, LldA differs from LldD in that its expression is induced specifically by the l-enantiomer of lactate. We also show that the P. aeruginosa lactate dehydrogenases perform functions in colony biofilms that are similar to their functions in liquid cultures. Finally, we provide evidence that the enzymes LdhA and LldE have the potential to support metabolic cross-feeding in biofilms, where LdhA can catalyze the production of d-lactate in the anaerobic zone, which is then used as a substrate in the aerobic zone. Together, these observations further our understanding of the metabolic pathways that can contribute to P. aeruginosa growth and survival during CF lung infection.

Influence of Glucose Availability and CRP Acetylation on the Genome-Wide Transcriptional Response of Escherichia coli: Assessment by an Optimized Factorial Microarray Analysis

Background: While in eukaryotes acetylation/deacetylation regulation exerts multiple pleiotropic effects, in Escherichia coli it seems to be more limited and less known. Hence, we aimed to progress in the characterization of this regulation by dealing with three convergent aspects: the effector enzymes involved, the master regulator CRP, and the dependence on glucose availability.

Methods: The transcriptional response of E. coli BW25113 was analyzed across 14 relevant scenarios. These conditions arise when the wild type and four isogenic mutants (defective in deacetylase CobB, defective in N(ε)-lysine acetyl transferase PatZ, Q- and R-type mutants of protein CRP) are studied under three levels of glucose availability (glucose-limited chemostat and glucose-excess or glucose-exhausted in batch culture). The Q-type emulates a permanent stage of CRP^acetylated, whereas the R-type emulates a permanent stage of CRP^deacetylated. The data were analyzed by an optimized factorial microarray method (Q-GDEMAR).

Results: (a) By analyzing one mutant against the other, we were able to unravel the true genes that participate in the interaction between ΔcobB/ΔpatZ mutations and glucose availability; (b) Increasing stages of glucose limitation appear to be associated with the up-regulation of specific sets of target genes rather than with the loss of genes present when glucose is in excess; (c) Both CRP^deacetylated and CRP^acetylated produce extensive changes in specific subsets of genes, but their number and identity depend on the glucose availability; (d) In other sub-sets of genes, the transcriptional effect of CRP seems to be independent of its acetylation or deacetylation; (e) Some specific ontology functions can be associated with each of the different sets of genes detected herein.

Conclusions: CRP cannot be thought of only as an effector of catabolite repression, because it acts along all the glucose conditions tested (excess, limited, and exhausted), exerting both positive and negative effects through different sets of genes. Acetylation of CRP does not seem to be a binary form of regulation, as there is not a univocal relationship between its activation/inhibitory effect and its acetylation/deacetylation stage. All the combinatorial possibilities are observed. During the exponential growth phase, CRP also exerts a very significant transcriptional effect, mainly on flagellar assembly and chemotaxis (FDR = 7.2 × 10⁻⁴⁴).

Data integration and predictive modeling methods for multi-omics datasets

We provide an overview of opportunities and challenges in multi-omics predictive analytics with particular emphasis on data integration and machine learning methods.

Modulation of Global Transcriptional Regulatory Networks as a Strategy for Increasing Kanamycin Resistance of the Translational Elongation Factor-G Mutants in Escherichia coli

Evolve and resequence experiments have provided us a tool to understand bacterial adaptation to antibiotics. In our previous work, we used short-term evolution to isolate mutants resistant to the ribosome targeting antibiotic kanamycin, and reported that Escherichia coli develops low cost resistance to kanamycin via different point mutations in the translation Elongation Factor-G (EF-G). Furthermore, we had shown that the resistance of EF-G mutants could be increased by second site mutations in the genes rpoD/cpxA/topA/cyaA Mutations in three of these genes had been discovered in earlier screens for aminoglycoside resistance. In this work, we expand our understanding of these second site mutations, the goal being to understand how these mutations affect the activities of the mutated gene products to confer resistance. We show that the mutation in cpxA most likely results in an active Cpx stress response. Further evolution of an EF-G mutant in a higher concentration of kanamycin than what was used in our previous experiments identified the cpxA locus as a primary target for a significant increase in resistance. The mutation in cyaA results in a loss of catalytic activity and probably results in resistance via altered CRP function. Despite a reduction in cAMP levels, the CyaA^N600Y mutant has a transcriptome indicative of increased CRP activity, pointing to an unknown role for CyaA and / or cAMP in gene expression. From the transcriptomes of double and single mutants, we describe the epistasis between the mutation in EF-G and these second site mutations. We show that the large scale transcriptomic changes in the topoisomerase I (FusA^A608E-TopA^S180L) mutant likely result from increased negative supercoiling in the cell. Finally, genes with known roles in aminoglycoside resistance were present among the misregulated genes in the mutants.

Mathematical modelling of microbes: metabolism, gene expression and growth

The growth of microorganisms involves the conversion of nutrients in the environment into biomass, mostly proteins and other macromolecules. This conversion is accomplished by networks of biochemical reactions cutting across cellular functions, such as metabolism, gene expression, transport and signalling. Mathematical modelling is a powerful tool for gaining an understanding of the functioning of this large and complex system and the role played by individual constituents and mechanisms. This requires models of microbial growth that provide an integrated view of the reaction networks and bridge the scale from individual reactions to the growth of a population. In this review, we derive a general framework for the kinetic modelling of microbial growth from basic hypotheses about the underlying reaction systems. Moreover, we show that several families of approximate models presented in the literature, notably flux balance models and coarse-grained whole-cell models, can be derived with the help of additional simplifying hypotheses. This perspective clearly brings out how apparently quite different modelling approaches are related on a deeper level, and suggests directions for further research.

Natural RNA Polymerase Aptamers Regulate Transcription in E. coli

In search for RNA signals that modulate transcription via direct interaction with RNA polymerase (RNAP), we deep sequenced an E. coli genomic library enriched for RNAP-binding RNAs. Many natural RNAP-binding aptamers, termed RAPs, were mapped to the genome. Over 60% of E. coli genes carry RAPs in their mRNA. Combining in vitro and in vivo approaches, we characterized a subset of inhibitory RAPs (iRAPs) that promote Rho-dependent transcription termination. A representative iRAP within the coding region of the essential gene, nadD, greatly reduces its transcriptional output in stationary phase and under oxidative stress, demonstrating that iRAPs control gene expression in response to changing environment. The mechanism of iRAPs involves active uncoupling of transcription and translation, making nascent RNA accessible to Rho. iRAPs encoded in the antisense strand also promote gene expression by reducing transcriptional interference. In essence, our work uncovers a broad class of cis-acting RNA signals that globally control bacterial transcription.

Mechanisms for Differential Protein Production in Toxin-Antitoxin Systems

Toxin-antitoxin (TA) systems are key regulators of bacterial persistence, a multidrug-tolerant state found in bacterial species that is a major contributing factor to the growing human health crisis of antibiotic resistance. Type II TA systems consist of two proteins, a toxin and an antitoxin; the toxin is neutralized when they form a complex. The ratio of antitoxin to toxin is significantly greater than 1.0 in the susceptible population (non-persister state), but this ratio is expected to become smaller during persistence. Analysis of multiple datasets (RNA-seq, ribosome profiling) and results from translation initiation rate calculators reveal multiple mechanisms that ensure a high antitoxin-to-toxin ratio in the non-persister state. The regulation mechanisms include both translational and transcriptional regulation. We classified E. coli type II TA systems into four distinct classes based on the mechanism of differential protein production between toxin and antitoxin. We find that the most common regulation mechanism is translational regulation. This classification scheme further refines our understanding of one of the fundamental mechanisms underlying bacterial persistence, especially regarding maintenance of the antitoxin-to-toxin ratio.

Revealing genome-scale transcriptional regulatory landscape of OmpR highlights its expanded regulatory roles under osmotic stress in Escherichia coli K-12 MG1655

A transcription factor (TF), OmpR, plays a critical role in transcriptional regulation of the osmotic stress response in bacteria. Here, we reveal a genome-scale OmpR regulon in Escherichia coli K-12 MG1655. Integrative data analysis reveals that a total of 37 genes in 24 transcription units (TUs) belong to OmpR regulon. Among them, 26 genes show more than two-fold changes in expression level in an OmpR knock-out strain. Specifically, we find that: 1) OmpR regulates mostly membrane-located gene products involved in diverse fundamental biological processes, such as narU (encoding nitrate/nitrite transporter), ompX (encoding outer membrane protein X), and nuoN (encoding NADH:ubiquinone oxidoreductase); 2) by investigating co-regulation of entire sets of genes regulated by other stress-response TFs, stresses are surprisingly independently regulated among each other; and, 3) a detailed investigation of the physiological roles of the newly discovered OmpR regulon genes reveals that activation of narU represents a novel strategy to significantly improve osmotic stress tolerance of E. coli. Thus, the genome-scale approach to elucidating regulons comprehensively identifies regulated genes and leads to fundamental discoveries related to stress responses.

The EcoCyc database: reflecting new knowledge about Escherichia coli K-12

EcoCyc (EcoCyc.org) is a freely accessible, comprehensive database that collects and summarizes experimental data for Escherichia coli K-12, the best-studied bacterial model organism. New experimental discoveries about gene products, their function and regulation, new metabolic pathways, enzymes and cofactors are regularly added to EcoCyc. New SmartTable tools allow users to browse collections of related EcoCyc content. SmartTables can also serve as repositories for user- or curator-generated lists. EcoCyc now supports running and modifying E. coli metabolic models directly on the EcoCyc website.

Computing and Applying Atomic Regulons to Understand Gene Expression and Regulation

Understanding gene function and regulation is essential for the interpretation, prediction, and ultimate design of cell responses to changes in the environment. An important step toward meeting the challenge of understanding gene function and regulation is the identification of sets of genes that are always co-expressed. These gene sets, Atomic Regulons (ARs), represent fundamental units of function within a cell and could be used to associate genes of unknown function with cellular processes and to enable rational genetic engineering of cellular systems. Here, we describe an approach for inferring ARs that leverages large-scale expression data sets, gene context, and functional relationships among genes. We computed ARs for Escherichia coli based on 907 gene expression experiments and compared our results with gene clusters produced by two prevalent data-driven methods: Hierarchical clustering and k-means clustering. We compared ARs and purely data-driven gene clusters to the curated set of regulatory interactions for E. coli found in RegulonDB, showing that ARs are more consistent with gold standard regulons than are data-driven gene clusters. We further examined the consistency of ARs and data-driven gene clusters in the context of gene interactions predicted by Context Likelihood of Relatedness (CLR) analysis, finding that the ARs show better agreement with CLR predicted interactions. We determined the impact of increasing amounts of expression data on AR construction and find that while more data improve ARs, it is not necessary to use the full set of gene expression experiments available for E. coli to produce high quality ARs. In order to explore the conservation of co-regulated gene sets across different organisms, we computed ARs for Shewanella oneidensis, Pseudomonas aeruginosa, Thermus thermophilus, and Staphylococcus aureus, each of which represents increasing degrees of phylogenetic distance from E. coli. Comparison of the organism-specific ARs showed that the consistency of AR gene membership correlates with phylogenetic distance, but there is clear variability in the regulatory networks of closely related organisms. As large scale expression data sets become increasingly common for model and non-model organisms, comparative analyses of atomic regulons will provide valuable insights into fundamental regulatory modules used across the bacterial domain.

Multi-omics integration accurately predicts cellular state in unexplored conditions for Escherichia coli

A significant obstacle in training predictive cell models is the lack of integrated data sources. We develop semi-supervised normalization pipelines and perform experimental characterization (growth, transcriptional, proteome) to create Ecomics, a consistent, quality-controlled multi-omics compendium for Escherichia coli with cohesive meta-data information. We then use this resource to train a multi-scale model that integrates four omics layers to predict genome-wide concentrations and growth dynamics. The genetic and environmental ontology reconstructed from the omics data is substantially different and complementary to the genetic and chemical ontologies. The integration of different layers confers an incremental increase in the prediction performance, as does the information about the known gene regulatory and protein-protein interactions. The predictive performance of the model ranges from 0.54 to 0.87 for the various omics layers, which far exceeds various baselines. This work provides an integrative framework of omics-driven predictive modelling that is broadly applicable to guide biological discovery.

Multi-omics data integration is a great challenge. Here, the authors compile a database of E. coli proteomics, transcriptomics, metabolomics and fluxomics data to train models of recurrent neural network and constrained regression, enabling prediction of bacterial responses to perturbations.

Comparative genomics and evolution of transcriptional regulons in Proteobacteria

Comparative genomics approaches are broadly used for analysis of transcriptional regulation in bacterial genomes. In this work, we identified binding sites and reconstructed regulons for 33 orthologous groups of transcription factors (TFs) in 196 reference genomes from 21 taxonomic groups of Proteobacteria. Overall, we predict over 10 600 TF binding sites and identified more than 15 600 target genes for 1896 TFs constituting the studied orthologous groups of regulators. These include a set of orthologues for 21 metabolism-associated TFs from Escherichia coli and/or Shewanella that are conserved in five or more taxonomic groups and several additional TFs that represent non-orthologous substitutions of the metabolic regulators in some lineages of Proteobacteria. By comparing gene contents of the reconstructed regulons, we identified the core, taxonomy-specific and genome-specific TF regulon members and classified them by their metabolic functions. Detailed analysis of ArgR, TyrR, TrpR, HutC, HypR and other amino-acid-specific regulons demonstrated remarkable differences in regulatory strategies used by various lineages of Proteobacteria. The obtained genomic collection of in silico reconstructed TF regulons contains a large number of new regulatory interactions that await future experimental validation. The collection provides a framework for future evolutionary studies of transcriptional regulatory networks in Bacteria. It can be also used for functional annotation of putative metabolic transporters and enzymes that are abundant in the reconstructed regulons.

Analysis tools for the interplay between genome layout and regulation

BACKGROUND

Genome layout and gene regulation appear to be interdependent. Understanding this interdependence is key to exploring the dynamic nature of chromosome conformation and to engineering functional genomes. Evidence for non-random genome layout, defined as the relative positioning of either co-functional or co-regulated genes, stems from two main approaches. Firstly, the analysis of contiguous genome segments across species, has highlighted the conservation of gene arrangement (synteny) along chromosomal regions. Secondly, the study of long-range interactions along a chromosome has emphasised regularities in the positioning of microbial genes that are co-regulated, co-expressed or evolutionarily correlated. While one-dimensional pattern analysis is a mature field, it is often powerless on biological datasets which tend to be incomplete, and partly incorrect. Moreover, there is a lack of comprehensive, user-friendly tools to systematically analyse, visualise, integrate and exploit regularities along genomes.

RESULTS

Here we present the Genome REgulatory and Architecture Tools SCAN (GREAT:SCAN) software for the systematic study of the interplay between genome layout and gene expression regulation.

GREAT

SCAN is a collection of related and interconnected applications currently able to perform systematic analyses of genome regularities as well as to improve transcription factor binding sites (TFBS) and gene regulatory network predictions based on gene positional information.

CONCLUSIONS

We demonstrate the capabilities of these tools by studying on one hand the regular patterns of genome layout in the major regulons of the bacterium Escherichia coli. On the other hand, we demonstrate the capabilities to improve TFBS prediction in microbes. Finally, we highlight, by visualisation of multivariate techniques, the interplay between position and sequence information for effective transcription regulation.

Systems Metabolic Engineering of Escherichia coli

Systems metabolic engineering, which recently emerged as metabolic engineering integrated with systems biology, synthetic biology, and evolutionary engineering, allows engineering of microorganisms on a systemic level for the production of valuable chemicals far beyond its native capabilities. Here, we review the strategies for systems metabolic engineering and particularly its applications in Escherichia coli. First, we cover the various tools developed for genetic manipulation in E. coli to increase the production titers of desired chemicals. Next, we detail the strategies for systems metabolic engineering in E. coli, covering the engineering of the native metabolism, the expansion of metabolism with synthetic pathways, and the process engineering aspects undertaken to achieve higher production titers of desired chemicals. Finally, we examine a couple of notable products as case studies produced in E. coli strains developed by systems metabolic engineering. The large portfolio of chemical products successfully produced by engineered E. coli listed here demonstrates the sheer capacity of what can be envisioned and achieved with respect to microbial production of chemicals. Systems metabolic engineering is no longer in its infancy; it is now widely employed and is also positioned to further embrace next-generation interdisciplinary principles and innovation for its upgrade. Systems metabolic engineering will play increasingly important roles in developing industrial strains including E. coli that are capable of efficiently producing natural and nonnatural chemicals and materials from renewable nonfood biomass.

Transcription profile of Escherichia coli: genomic SELEX search for regulatory targets of transcription factors

Bacterial genomes are transcribed by DNA-dependent RNA polymerase (RNAP), which achieves gene selectivity through interaction with sigma factors that recognize promoters, and transcription factors (TFs) that control the activity and specificity of RNAP holoenzyme. To understand the molecular mechanisms of transcriptional regulation, the identification of regulatory targets is needed for all these factors. We then performed genomic SELEX screenings of targets under the control of each sigma factor and each TF. Here we describe the assembly of 156 SELEX patterns of a total of 116 TFs performed in the presence and absence of effector ligands. The results reveal several novel concepts: (i) each TF regulates more targets than hitherto recognized; (ii) each promoter is regulated by more TFs than hitherto recognized; and (iii) the binding sites of some TFs are located within operons and even inside open reading frames. The binding sites of a set of global regulators, including cAMP receptor protein, LeuO and Lrp, overlap with those of the silencer H-NS, suggesting that certain global regulators play an anti-silencing role. To facilitate sharing of these accumulated SELEX datasets with the research community, we compiled a database, ‘Transcription Profile of Escherichia coli’ (www.shigen.nig.ac.jp/ecoli/tec/).

Genome-Wide Assessment of Outer Membrane Vesicle Production in Escherichia coli

The production of outer membrane vesicles by Gram-negative bacteria has been well documented; however, the mechanism behind the biogenesis of these vesicles remains unclear. Here a high-throughput experimental method and systems-scale analysis was conducted to determine vesiculation values for the whole genome knockout library of Escherichia coli mutant strains (Keio collection). The resultant dataset quantitatively recapitulates previously observed phenotypes and implicates nearly 150 new genes in the process of vesiculation. Gene functional and biochemical pathway analyses suggest that mutations that truncate outer membrane structures such as lipopolysaccharide and enterobacterial common antigen lead to hypervesiculation, whereas mutants in oxidative stress response pathways result in lower levels. This study expands and refines the current knowledge regarding the cellular pathways required for outer membrane vesiculation in E. coli.

Proteins Related to the Type I Secretion System Are Associated with Secondary SecA_DEAD Domain Proteins in Some Species of Planctomycetes, Verrucomicrobia, Proteobacteria, Nitrospirae and Chlorobi

A number of bacteria belonging to the PVC (Planctomycetes-Verrucomicrobia-Chlamydiae) super-phylum contain unusual ribosome-bearing intracellular membranes. The evolutionary origins and functions of these membranes are unknown. Some proteins putatively associated with the presence of intracellular membranes in PVC bacteria contain signal peptides. Signal peptides mark proteins for translocation across the cytoplasmic membrane in prokaryotes, and the membrane of the endoplasmic reticulum in eukaryotes, by highly conserved Sec machinery. This suggests that proteins might be targeted to intracellular membranes in PVC bacteria via the Sec pathway. Here, we show that canonical signal peptides are significantly over-represented in proteins preferentially present in PVC bacteria possessing intracellular membranes, indicating involvement of Sec translocase in their cellular targeting. We also characterized Sec proteins using comparative genomics approaches, focusing on the PVC super-phylum. While we were unable to detect unique changes in Sec proteins conserved among membrane-bearing PVC species, we identified (1) SecA ATPase domain re-arrangements in some Planctomycetes, and (2) secondary SecA_DEAD domain proteins in the genomes of some Planctomycetes, Verrucomicrobia, Proteobacteria, Nitrospirae and Chlorobi. This is the first report of potentially duplicated SecA in Gram-negative bacteria. The phylogenetic distribution of secondary SecA_DEAD domain proteins suggests that the presence of these proteins is not related to the occurrence of PVC endomembranes. Further genomic analysis showed that secondary SecA_DEAD domain proteins are located within genomic neighborhoods that also encode three proteins possessing domains specific for the Type I secretion system.