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Functional annotation of open reading frames in microbial genomes remains substantially incomplete. Enzymes constitute the most prevalent functional gene class in microbial genomes and can be described by their specific catalytic functions using the Enzyme Commission (EC) number. Consequently, the ability to predict EC numbers could substantially reduce the number of un-annotated genes. Here we present a deep learning model, DeepECtransformer, which utilizes transformer layers as a neural network architecture to predict EC numbers. Using the extensively studied Escherichia coli K-12 MG1655 genome, DeepECtransformer predicted EC numbers for 464 un-annotated genes. We experimentally validated the enzymatic activities predicted for three proteins (YgfF, YciO, and YjdM). Further examination of the neural networks reasoning process revealed that the trained neural network relies on functional motifs of enzymes to predict EC numbers. Thus, DeepECtransformer is a method that facilitates the functional annotation of uncharacterized genes.

Inactivation kinetics of Escherichia coli K12 inoculated in blueberry, grapefruit, cantaloupe, and watermelon juices were evaluated at isothermal temperatures of 52 to 62 °C using thermal death time disks. Juices had variations in titratable acidity, pH, viscosity, and total soluble solids. Survival curves were described by Weibull and linear models, where D‐ and z‐values were determined using the first‐order model. D‐values in watermelon, cantaloupe, blueberry and grapefruit juices, were 6.57–0.64 min, 4.55–0.44 min, 3.94–0.27 min, and 3.03–0.24 min, respectively. The z‐values of E. coli K12 in tested fruit juices ranged from 5.33 to 5.89 °C. While there were no significant differences in the z‐values, the D‐values varied significantly. According to the results obtained, pH and heating temperature dramatically affect the thermal resistance of E. coli K12 under tested conditions. These findings offer a basis for developing predictive models for E. coli inactivation in fruit juices. Practical applications: Thermal death time (TDT) kinetics is extremely useful in ensuring microbial safety of fruit juices. The D‐ and z‐values calculated in this study can contribute to developing predictive models for inactivating E. coli in fruit juices with varied physicochemical attributes. Furthermore, the data and models can be used for optimization of pasteurization processes and regulatory compliance. TDT studies provide the scientific basis for process calculations and help juice manufacturers comply with regulatory requirements. Also, TDT studies help determine the minimal thermal treatments needed to inhibit spoilage organisms, ensuring the juice remains safe and palatable for longer periods. This research will help scientists understand the thermal resistance of E. coli in various fruit juice matrices. [ABSTRACT FROM AUTHOR]

The massive sequencing of transposon insertion mutant libraries (Tn-Seq) represents a commonly used method to determine essential genes in bacteria. Using a hypersaturated transposon mutant library consisting of 400,096 unique Tn insertions, 523 genes were classified as essential in Escherichia coli K-12 MG1655. This provided a useful genome-wide gene essentiality landscape for rapidly identifying 233 of 301 essential genes previously validated by a knockout study. However, there was a discrepancy in essential gene sets determined by conventional gene deletion methods and Tn-Seq, although different Tn-Seq studies reported different extents of discrepancy. We have elucidated two causes of this discrepancy. First, 68 essential genes not detected by Tn-Seq contain nonessential subgenic domains that are tolerant to transposon insertion, which leads to the false assignment of an essential gene as a nonessential or dispensable gene. These genes exhibited a high level of transposon insertion in their subgenic nonessential domains. In contrast, 290 genes were additionally categorized as essential by Tn-Seq, although their knockout mutants were available. The comparative analysis of Tn-Seq and high-resolution footprinting of nucleoid-associated proteins (NAPs) revealed that a protein-DNA interaction hinders transposon insertion. We identified 213 false-positive genes caused by NAP-genome interactions. These two limitations have to be considered when addressing essential bacterial genes using Tn-Seq. Furthermore, a comparative analysis of high-resolution Tn-Seq with other data sets is required for a more accurate determination of essential genes in bacteria. IMPORTANCE Transposon mutagenesis is an efficient way to explore gene essentiality of a bacterial genome. However, there was a discrepancy between the essential gene set determined by transposon mutagenesis and that determined using single-gene knockout strains. In this study, we generated a hypersaturated Escherichia coli transposon mutant library comprising approximately 400,000 different mutants. Determination of transposon insertion sites using next-generation sequencing provided a high-resolution essentiality landscape of the E. coli genome. We identified false negatives of essential gene discovery due to the permissive insertion of transposons in the C-terminal region. Comparisons between the transposon insertion landscape with binding profiles of DNA-binding proteins revealed interference of nucleoid-associated proteins to transposon insertion, generating false positives of essential gene discovery. Consideration of these findings is required to avoid the misinterpretation of transposon mutagenesis results.

This study focuses on micro-electrochemical screening to select microbial strains capable of directly transfer electrons to the working electrode dependent on specific enzymatic machinery. The main objective of this work is to select and identify promising strains for allow the bioelectrolysis production of hydrogen. To achieve this goal, microbial composites (artificial biofilms), have been developed using Escherichia coli CGE1 from LCPME. CNRS Fransh, Pseudomonas putrifisciens (CIP 69.13) (CIP, Collection Institut Pasteur, Fransh). Shewanella oneidensis MR-1 (ATCC 700550), and Thiobacillus denitrificans, from (ATCC, American Type Culture Collection), each one enclosed in a matrix carbon nanotubes and protamine matrix, forming an artificial biofilm on buckypaper. Cyclic Voltammetry (CV) measurements were performed over a potential range of +0.4 to -0.7V at 5mV/s under 30°C, using a saturated KCl Ag/AgCl reference electrode and a stainless-steel grid counter electrode. For E. coli and P. putrifisciens, the measurement focused on the oxidation of 20mM glucose, while the former bacteria were growth with and without O2. For S. oneidensis and T. denitrificans the focus was on the reduction of fumarate and 20 mM of NaNOH3+, respectively. As results, E. coli and P. putrifisciens species show no notable electrochemical activity, with no signal of glucose oxidation, due to the absence of type C cytochromes in the cytoplasmic membrane, unlike S. oneidensis and T. denitrificans, that demonstrate a direct electron transfer.

Queuosine (Q) is a conserved hypermodification of the wobble base of tRNA containing GUN anticodons but the physiological consequences of Q deficiency are poorly understood in bacteria. This work combines transcriptomic, proteomic and physiological studies to characterize a Q-deficient Escherichia coli K12 MG1655 mutant. The absence of Q led to an increased resistance to nickel and cobalt, and to an increased sensitivity to cadmium, compared to the wild-type (WT) strain. Transcriptomic analysis of the WT and Q-deficient strains, grown in the presence and absence of nickel, revealed that the nickel transporter genes (nikABCDE) are downregulated in the Q- mutant, even when nickel is not added. This mutant is therefore primed to resist to high nickel levels. Downstream analysis of the transcriptomic data suggested that the absence of Q triggers an atypical oxidative stress response, confirmed by the detection of slightly elevated reactive oxygen species (ROS) levels in the mutant, increased sensitivity to hydrogen peroxide and paraquat, and a subtle growth phenotype in a strain prone to accumulation of ROS.

Although Escherichia coli K-12 strains represent perhaps the best known model bacteria, we do not know the identity or functions of all of their transcription factors (TFs). It is now possible to systematically discover the physiological function of TFs in E. coli BW25113 using a set of synergistic methods; including ChIP-exo, growth phenotyping, conserved gene clustering, and transcriptome analysis. Among 47 LysR-type TFs (LTFs) found on the E. coli K-12 genome, many regulate nitrogen source utilization or amino acid metabolism. However, 19 LTFs remain unknown. In this study, we elucidated the regulation of seven of these 19 LTFs: YbdO, YbeF, YcaN, YbhD, YgfI, YiaU, YneJ. We show that: (1) YbdO (tentatively re-named CitR) regulation has an effect on bacterial growth at low pH with citrate supplementation. CitR is a repressor of the ybdNM operon and is implicated in the regulation of citrate lyase genes (citCDEFG); (2) YgfI (tentatively re-named DhfA) activates the dhaKLM operon that encodes the phosphotransferase system, DhfA is involved in formate, glycerol and dihydroxyacetone utilization; (3) YiaU (tentatively re-named LpsR) regulates the yiaT gene encoding an outer membrane protein, and waaPSBOJYZU operon is also important in determining cell density at the stationary phase and resistance to oxacillin microaerobically; (4) YneJ, re-named here as PtrR, directly regulates the expression of the succinate-semialdehyde dehydrogenase, Sad (also known as YneI), and is a predicted regulator of fnrS (a small RNA molecule). PtrR is important for bacterial growth in the presence of L-glutamate and putrescine as nitrogen/energy sources; and (5) YbhD and YcaN regulate adjacent y-genes on the genome. We have thus established the functions for four LTFs and identified the target genes for three LTFs.

The transcriptome of Esherichia coli cystlike dormant cells was investigated. RNA content in a single dormant cell was 0.26 fg, i.e., 13.5 times less than in a cell of a growing culture. The presence of mRNA in E. coli dormant cells has not been reported previously. The pools of gene reads for the dormant and growing cells were characterized, as well as the differential expression of all genes, calculated according to the special algorithm considering the average mRNA amount in a single cell. The notion of the genes active in every cell of the population was introduced. In each cell of the dormant and growing E. coli population, such genes were represented by the transcripts of 21 and 16% of the genes, respectively. The revealed cell heterogeneity regarding set of active genes is one of the reasons (and forms) of heterogeneity of bacterial populations. Sixty genes were revealed, for which activity increased twice or more during formation of E. coli dormant cells. These were the genes responsible for genome activity, structure and properties of the cell envelope, cell proliferation, stress adaptation, biofilm formation and functioning, and collective behavior, as well as the genes providing for survival of the cell population during germination of the dormant cells. [ABSTRACT FROM AUTHOR]

Bacteria regulate gene expression to adapt to changing environments through transcriptional regulatory networks (TRNs). Although extensively studied, no TRN is fully characterized since the identity and activity of all the transcriptional regulators comprising a TRN are not known. Here, we experimentally evaluate 40 uncharacterized proteins in Escherichia coli K-12 MG1655, which were computationally predicted to be transcription factors (TFs). First, we used a multiplexed chromatin immunoprecipitation method combined with lambda exonuclease digestion (multiplexed ChIP-exo) assay to characterize binding sites for these candidate TFs; 34 of them were found to be DNA-binding proteins. We then compared the relative location between binding sites and RNA polymerase (RNAP). We found 48% (283/588) overlap between the TFs and RNAP. Finally, we used these data to infer potential functions for 10 of the 34 TFs with validated DNA binding sites and consensus binding motifs. Taken together, this study: (i) significantly expands the number of confirmed TFs to 276, close to the estimated total of about 280 TFs; (ii) provides putative functions for the newly discovered TFs and (iii) confirms the functions of four representative TFs through mutant phenotypes.

In vitro antibiotic susceptibility testing often fails to accurately predict in vivo drug efficacies, in part due to differences in the molecular composition between standardized bacteriologic media and physiological environments within the body. Here, we investigate the interrelationship between antibiotic susceptibility and medium composition in Escherichia coli K-12 MG1655 as contextualized through machine learning of transcriptomics data. Application of independent component analysis, a signal separation algorithm, shows that complex phenotypic changes induced by environmental conditions or antibiotic treatment are directly traced to the action of a few key transcriptional regulators, including RpoS, Fur, and Fnr. Integrating machine learning results with biochemical knowledge of transcription factor activation reveals medium-dependent shifts in respiration and iron availability that drive differential antibiotic susceptibility. By extension, the data generation and data analytics workflow used here can interrogate the regulatory state of a pathogen under any measured condition and can be applied to any strain or organism for which sufficient transcriptomics data are available. IMPORTANCE Antibiotic resistance is an imminent threat to global health. Patient treatment regimens are often selected based on results from standardized antibiotic susceptibility testing (AST) in the clinical microbiology lab, but these in vitro tests frequently misclassify drug effectiveness due to their poor resemblance to actual host conditions. Prior attempts to understand the combined effects of drugs and media on antibiotic efficacy have focused on physiological measurements but have not linked treatment outcomes to transcriptional responses on a systems level. Here, application of machine learning to transcriptomics data identified medium-dependent responses in key regulators of bacterial iron uptake and respiratory activity. The analytical workflow presented here is scalable to additional organisms and conditions and could be used to improve clinical AST by identifying the key regulatory factors dictating antibiotic susceptibility.

The increasing frequency of antibiotic resistance poses myriad challenges to modern medicine. Environmental survival of multidrug-resistant bacteria in health care facilities, including hospitals, creates reservoirs for transmission of these difficult to treat pathogens. To prevent bacterial colonization, these facilities deploy an array of infection control measures, including bactericidal metals on surfaces, as well as implanted devices. Although antibiotics are routinely used in these health care environments, it is unknown whether and how antibiotic exposure affects metal resistance. We identified a multidrug-resistant Enterobacter clinical isolate that displayed heteroresistance to the antibiotic colistin, where only a minor fraction of cells within the population resist the drug. When this isolate was grown in the presence of colistin, a 9-kb DNA region was duplicated in the surviving resistant subpopulation, but surprisingly, was not required for colistin heteroresistance. Instead, the amplified region included a three-gene locus (ncrABC) that conferred resistance to the bactericidal metal, nickel. ncrABC expression alone was sufficient to confer nickel resistance to E. coli K-12. Due to its selection for the colistin-resistant subpopulation harboring the duplicated 9-kb region that includes ncrABC, colistin treatment led to enhanced nickel resistance. Taken together, these data suggest that the use of antibiotics may inadvertently promote enhanced resistance to antimicrobial metals, with potentially profound implications for bacterial colonization and transmission in the health care environment.IMPORTANCE To inhibit bacterial transmission and infection, health care facilities use bactericidal metal coatings to prevent colonization of surfaces and implanted devices. In these environments, antibiotics are commonly used, but their effect on metal resistance is unclear. The data described here reveal that exposure of a human isolate of Enterobacter cloacae to a last-line antibiotic, colistin, resulted in a DNA amplification that does not confer antibiotic resistance but instead facilitates resistance to the toxic metal nickel. This highlights a novel aspect of antibiotic and metal interplay. Concerningly, these data suggest the use of antibiotics could in some cases promote bacterial survival and colonization in the health care environment and ultimately increase transmission and infection of patients.

Sustaining a robust metabolic network requires a balanced and fully functioning proteome. In addition to amino acids, many enzymes require cofactors (coenzymes and engrafted prosthetic groups) to function properly. Extensively validated resource allocation models, such as genome-scale models of metabolism and gene expression (ME-models), have the ability to compute an optimal proteome composition underlying a metabolic phenotype, including the provision of all required cofactors. Here we apply the ME-model for Escherichia coli K-12 MG1655 to computationally examine how environmental conditions change the proteome and its accompanying cofactor usage. We found that: (1) The cofactor requirements computed by the ME-model mostly agree with the standard biomass objective function used in models of metabolism alone (M-models); (2) ME-model computations reveal non-intuitive variability in cofactor use under different growth conditions; (3) An analysis of ME-model predicted protein use in aerobic and anaerobic conditions suggests an enrichment in the use of peroxyl scavenging acids in the proteins used to sustain aerobic growth; (4) The ME-model could describe how limitation in key protein components affect the metabolic state of E. coli. Genome-scale models have thus reached a level of sophistication where they reveal intricate properties of functional proteomes and how they support different E. coli lifestyles.

BACKGROUND:The reconstruction of metabolic networks and the three-dimensional coverage of protein structures have reached the genome-scale in the widely studied Escherichia coli K-12 MG1655 strain. The combination of the two leads to the formation of a structural systems biology framework, which we have used to analyze differences between the reactive oxygen species (ROS) sensitivity of the proteomes of sequenced strains of E. coli. As proteins are one of the main targets of oxidative damage, understanding how the genetic changes of different strains of a species relates to its oxidative environment can reveal hypotheses as to why these variations arise and suggest directions of future experimental work. RESULTS:Creating a reference structural proteome for E. coli allows us to comprehensively map genetic changes in 1764 different strains to their locations on 4118 3D protein structures. We use metabolic modeling to predict basal ROS production levels (ROStype) for 695 of these strains, finding that strains with both higher and lower basal levels tend to enrich their proteomes with antioxidative properties, and speculate as to why that is. We computationally assess a strain's sensitivity to an oxidative environment, based on known chemical mechanisms of oxidative damage to protein groups, defined by their localization and functionality. Two general groups - metalloproteins and periplasmic proteins - show enrichment of their antioxidative properties between the 695 strains with a predicted ROStype as well as 116 strains with an assigned pathotype. Specifically, proteins that a) utilize a molybdenum ion as a cofactor and b) are involved in the biogenesis of fimbriae show intriguing protective properties to resist oxidative damage. Overall, these findings indicate that a strain's sensitivity to oxidative damage can be elucidated from the structural proteome, though future experimental work is needed to validate our model assumptions and findings. CONCLUSION:We thus demonstrate that structural systems biology enables a proteome-wide, computational assessment of changes to atomic-level physicochemical properties and of oxidative damage mechanisms for multiple strains in a species. This integrative approach opens new avenues to study adaptation to a particular environment based on physiological properties predicted from sequence alone.

Antibiotic resistance is one of the most challenging issues in public health. Antibiotics have been increasingly used not only for humans and animals but also for crop protection as pesticides. Thus, antibiotics often coexist with pesticides in some environments. To investigate the effects of the co-occurring, nonantibiotic pesticides on the development of antibiotic resistance, we conducted long-term exposure experiments using an Escherichia coli K-12 model strain. The results reveal that (1) the exposure to pesticides (in mg/L) alone led to the emergence of mutants with significantly higher resistance to streptomycin; (2) the exposure to pesticides (in μg/L) together with a subinhibitory level (in high μg/L) of ampicillin synergistically stimulated the selection of ampicillin resistance and the cross-resistance to other antibiotics (i.e., ciprofloxacin, chloramphenicol, and tetracycline). Distinct and diversified genetic mutations emerged in the resistant mutants selected from the coexposure to both pesticides and ampicillin. The genetic mutations likely caused a holistic transcriptional regulation (e.g., biofilm formation, oxidative stress defense) when grown under antibiotic stress and led to increased antibiotic resistance. Together, these findings provide important fundamental insights into the development of antibiotic resistance and the resistance mechanisms under environmentally relevant conditions where antibiotics and nonantibiotic micropollutants coexist.

The release of a wide variety of persistent chemical contaminants into wastewater has become a growing concern due to their potential health and environmental risks. While the toxic effects of these pollutants on aquatic organisms have been extensively studied, their impact on microbial pathogens and their virulence mechanisms remains largely unexplored. This research paper focuses on the identification and prioritization of chemical pollutants that increase bacterial pathogenicity, which is a public health concern. In order to predict how chemical compounds, such as pesticides and pharmaceuticals, would affect the virulence mechanisms of three bacterial strains (Escherichia coli K12, Pseudomonas aeruginosa H103, and Salmonella enterica serovar. Typhimurium), this study has developed quantitative structure–activity relationship (QSAR) models. The use of analysis of variance (ANOVA) functions assists in developing QSAR models based on the chemical structure of the compounds, to predict their effect on the growth and swarming behavior of the bacterial strains. The results showed an uncertainty in the created model, and that increases in virulence factors, including growth and motility of bacteria, after exposure to the studied compounds are possible to be predicted. These results could be more accurate if the interactions between groups of functions are included. For that, to make an accurate and universal model, it is essential to incorporate a larger number of compounds of similar and different structures. [ABSTRACT FROM AUTHOR]

Type II single-span membrane proteins, such as CadC or RodZ, lacking a signal sequence and having a far-downstream hydrophobic segment, require the SecA secretion motor for insertion into the inner membrane of Escherichia coli. Using two chimeric single-span proteins containing a designed hydrophobic segment H, we have determined the requirements for SecA-mediated secretion, the molecular distinction between TM domains and signal peptides, and the propensity for hydrophobic H-segments to remain embedded within the bilayer after targeting. By means of engineered H-segments and a strategically placed SPase I cleavage site, we determined how targeting and stability of the chimeric proteins are affected by the length and hydrophobicity of the H-segment. Very hydrophobic segments (e.g., 16 Leu) are stably incorporated into the inner membrane, resulting in a C-terminal anchored membrane protein, while a 24L construct was not targeted to the membrane by SecA and remained in the cytoplasm. However, a construct carrying preMalE at the N-terminus led to SecA targeting to SecYEG via the native signal sequence and stable insertion of the downstream 24L H-segment. We show that the RseP intramembrane protease degrades weakly stable H-segments and is a useful tool for investigating the borderline between stable and unstable TM segments. Using RseP- cells, we find that moderately hydrophobic sequences (e.g., 5Leu + 11Ala) are targeted to SecYEG by SecA and inserted, but subsequently drop out of the membrane into the cytoplasm. Therefore, the free energy of transfer from translocon to bilayer is different from the transfer free energy from membrane to water.

Evidence suggests that novel enzyme functions evolved from low-level promiscuous activities in ancestral enzymes. Yet, the evolutionary dynamics and physiological mechanisms of how such side activities contribute to systems-level adaptations are not well characterized. Furthermore, it remains untested whether knowledge of an organism's promiscuous reaction set, or underground metabolism, can aid in forecasting the genetic basis of metabolic adaptations. Here, we employ a computational model of underground metabolism and laboratory evolution experiments to examine the role of enzyme promiscuity in the acquisition and optimization of growth on predicted non-native substrates in Escherichia coli K-12 MG1655. After as few as approximately 20 generations, evolved populations repeatedly acquired the capacity to grow on five predicted non-native substrates-D-lyxose, D-2-deoxyribose, D-arabinose, m-tartrate, and monomethyl succinate. Altered promiscuous activities were shown to be directly involved in establishing high-efficiency pathways. Structural mutations shifted enzyme substrate turnover rates toward the new substrate while retaining a preference for the primary substrate. Finally, genes underlying the phenotypic innovations were accurately predicted by genome-scale model simulations of metabolism with enzyme promiscuity.

Experimental studies of Escherichia coli K-12 MG1655 often implicate poorly annotated genes in cellular phenotypes. However, we lack a systematic understanding of these genes. How many are there? What information is available for them? And what features do they share that could explain the gap in our understanding? Efforts to build predictive, whole-cell models of E. coli inevitably face this knowledge gap. We approached these questions systematically by assembling annotations from the knowledge bases EcoCyc, EcoGene, UniProt and RegulonDB. We identified the genes that lack experimental evidence of function (the 'y-ome') which include 1600 of 4623 unique genes (34.6%), of which 111 have absolutely no evidence of function. An additional 220 genes (4.7%) are pseudogenes or phantom genes. y-ome genes tend to have lower expression levels and are enriched in the termination region of the E. coli chromosome. Where evidence is available for y-ome genes, it most often points to them being membrane proteins and transporters. We resolve the misconception that a gene in E. coli whose primary name starts with 'y' is unannotated, and we discuss the value of the y-ome for systematic improvement of E. coli knowledge bases and its extension to other organisms.

Systems biology describes cellular phenotypes as properties that emerge from the complex interactions of individual system components. Little is known about how these interactions have affected the evolution of metabolic enzymes. Here, we combine genome-scale metabolic modeling with population genetics models to simulate the evolution of enzyme turnover numbers (kcats) from a theoretical ancestor with inefficient enzymes. This systems view of biochemical evolution reveals strong epistatic interactions between metabolic genes that shape evolutionary trajectories and influence the magnitude of evolved kcats. Diminishing returns epistasis prevents enzymes from developing higher kcats in all reactions and keeps the organism far from the potential fitness optimum. Multifunctional enzymes cause synergistic epistasis that slows down adaptation. The resulting fitness landscape allows kcat evolution to be convergent. Predicted kcat parameters show a significant correlation with experimental data, validating our modeling approach. Our analysis reveals how evolutionary forces shape modern kcats and the whole of metabolism.

Transcriptional regulation enables cells to respond to environmental changes. Of the estimated 304 candidate transcription factors (TFs) in Escherichia coli K-12 MG1655, 185 have been experimentally identified, but ChIP methods have been used to fully characterize only a few dozen. Identifying these remaining TFs is key to improving our knowledge of the E. coli transcriptional regulatory network (TRN). Here, we developed an integrated workflow for the computational prediction and comprehensive experimental validation of TFs using a suite of genome-wide experiments. We applied this workflow to (i) identify 16 candidate TFs from over a hundred uncharacterized genes; (ii) capture a total of 255 DNA binding peaks for ten candidate TFs resulting in six high-confidence binding motifs; (iii) reconstruct the regulons of these ten TFs by determining gene expression changes upon deletion of each TF and (iv) identify the regulatory roles of three TFs (YiaJ, YdcI, and YeiE) as regulators of l-ascorbate utilization, proton transfer and acetate metabolism, and iron homeostasis under iron-limited conditions, respectively. Together, these results demonstrate how this workflow can be used to discover, characterize, and elucidate regulatory functions of uncharacterized TFs in parallel.

A mechanistic understanding of how new phenotypes develop to overcome the loss of a gene product provides valuable insight on both the metabolic and regulatory functions of the lost gene. The pgi gene, whose product catalyzes the second step in glycolysis, was deleted in a growth-optimized Escherichia coli K-12 MG1655 strain. The initial knockout (KO) strain exhibited an 80% drop in growth rate that was largely recovered in eight replicate, but phenotypically distinct, cultures after undergoing adaptive laboratory evolution (ALE). Multi-omic data sets showed that the loss of pgi substantially shifted pathway usage, leading to a redox and sugar phosphate stress response. These stress responses were overcome by unique combinations of innovative mutations selected for by ALE. Thus, the coordinated mechanisms from genome to metabolome that lead to multiple optimal phenotypes after the loss of a major gene product were revealed.IMPORTANCE A mechanistic understanding of how microbes are able to overcome the loss of a gene through regulatory and metabolic changes is not well understood. Eight independent adaptive laboratory evolution (ALE) experiments with pgi knockout strains resulted in eight phenotypically distinct endpoints that were able to overcome the gene loss. Utilizing multi-omics analysis, the coordinated mechanisms from genome to metabolome that lead to multiple optimal phenotypes after the loss of a major gene product were revealed.

Biological regulatory network architectures are multi-scale in their function and can adaptively acquire new functions. Gene knockout (KO) experiments provide an established experimental approach not just for studying gene function, but also for unraveling regulatory networks in which a gene and its gene product are involved. Here we study the regulatory architecture of Escherichia coli K-12 MG1655 by applying adaptive laboratory evolution (ALE) to metabolic gene KO strains. Multi-omic analysis reveal a common overall schema describing the process of adaptation whereby perturbations in metabolite concentrations lead regulatory networks to produce suboptimal states, whose function is subsequently altered and re-optimized through acquisition of mutations during ALE. These results indicate that metabolite levels, through metabolite-transcription factor interactions, have a dominant role in determining the function of a multi-scale regulatory architecture that has been molded by evolution.

BACKGROUND:Our understanding of the regulation of gene expression has benefited from the availability of high-throughput technologies that interrogate the whole genome for the binding of specific transcription factors and gene expression profiles. In the case of widely used model organisms, such as Escherichia coli K-12, the new knowledge gained from these approaches needs to be integrated with the legacy of accumulated knowledge from genetic and molecular biology experiments conducted in the pre-genomic era in order to attain the deepest level of understanding possible based on the available data. RESULTS:In this paper, we describe an expansion of RegulonDB, the database containing the rich legacy of decades of classic molecular biology experiments supporting what we know about gene regulation and operon organization in E. coli K-12, to include the genome-wide dataset collections from 32 ChIP and 19 gSELEX publications, in addition to around 60 genome-wide expression profiles relevant to the functional significance of these datasets and used in their curation. Three essential features for the integration of this information coming from different methodological approaches are: first, a controlled vocabulary within an ontology for precisely defining growth conditions; second, the criteria to separate elements with enough evidence to consider them involved in gene regulation from isolated transcription factor binding sites without such support; and third, an expanded computational model supporting this knowledge. Altogether, this constitutes the basis for adequately gathering and enabling the comparisons and integration needed to manage and access such wealth of knowledge. CONCLUSIONS:This version 10.0 of RegulonDB is a first step toward what should become the unifying access point for current and future knowledge on gene regulation in E. coli K-12. Furthermore, this model platform and associated methodologies and criteria can be emulated for gathering knowledge on other microbial organisms.

In all living organisms, adenosine triphosphate (ATP) and NAD(H) represent universal molecular currencies for energy and redox state, respectively, and are thus widely applicable molecular proxies for an organism's viability and activity. To this end, corresponding luciferase-based assays in combination with a microplate reader were established with the marine model bacterium Phaeobacter inhibens DSM 17395 (Escherichia coli K12 served as reference). Grey multiwell plates best balanced sensitivity and crosstalk, and optimal incubation times were 5 min and 30 min for the ATP and NAD(H) assay, respectively, together allowing limits of detection of 0.042, 0.470 and 0.710 nM for ATP, NAD+, and NADH, respectively. Quenching of bacterial cell samples involved Tris-EDTA-DTAB and bicarbonate base-DTAB for ATP and NAD(H) assays, respectively. The ATP and NAD(H) yields determined for P. inhibens DSM 17395 at ¼ ODmax were found to reside well within the range previously reported for E. coli and other bacteria, e.g., 3.28 µmol ATP (g cellsdry)−1. Thus, the here described methods for luciferase-based determination of ATP/NAD(H) pools open a promising approach to investigate energy and redox states in marine (environmental) bacteria. [ABSTRACT FROM AUTHOR]

Adaptive laboratory evolution (ALE) is a widely-used method for improving the fitness of microorganisms in selected environmental conditions. It has been applied previously to Escherichia coli K-12 MG1655 during aerobic exponential growth on glucose minimal media, a frequently used model organism and growth condition, to probe the limits of E. coli growth rate and gain insights into fast growth phenotypes. Previous studies have described up to 1.6-fold increases in growth rate following ALE, and have identified key causal genetic mutations and changes in transcriptional patterns. Here, we report for the first time intracellular metabolic fluxes for six such adaptively evolved strains, as determined by high-resolution 13C-metabolic flux analysis. Interestingly, we found that intracellular metabolic pathway usage changed very little following adaptive evolution. Instead, at the level of central carbon metabolism the faster growth was facilitated by proportional increases in glucose uptake and all intracellular rates. Of the six evolved strains studied here, only one strain showed a small degree of flux rewiring, and this was also the strain with unique genetic mutations. A comparison of fluxes with two other wild-type (unevolved) E. coli strains, BW25113 and BL21, showed that inter-strain differences are greater than differences between the parental and evolved strains. Principal component analysis highlighted that nearly all flux differences (95%) between the nine strains were captured by only two principal components. The distance between measured and flux balance analysis predicted fluxes was also investigated. It suggested a relatively wide range of similar stoichiometric optima, which opens new questions about the path-dependency of adaptive evolution.

In bacteria various tactic responses are mediated by the same cellular pathway, but sensing of physical stimuli remains poorly understood. Here, we combine an in-vivo analysis of the pathway activity with a microfluidic taxis assay and mathematical modeling to investigate the thermotactic response of Escherichia coli. We show that in the absence of chemical attractants E. coli exhibits a steady thermophilic response, the magnitude of which decreases at higher temperatures. Adaptation of wild-type cells to high levels of chemoattractants sensed by only one of the major chemoreceptors leads to inversion of the thermotactic response at intermediate temperatures and bidirectional cell accumulation in a thermal gradient. A mathematical model can explain this behavior based on the saturation-dependent kinetics of adaptive receptor methylation. Lastly, we find that the preferred accumulation temperature corresponds to optimal growth in the presence of the chemoattractant serine, pointing to a physiological relevance of the observed thermotactic behavior.

Acid-adapted strains of Escherichia coli K-12 W3110 were obtained by serial culture in medium buffered at pH 4.6 (M. M. Harden, A. He, K. Creamer, M. W. Clark, I. Hamdallah, K. A. Martinez, R. L. Kresslein, S. P. Bush, and J. L. Slonczewski, Appl Environ Microbiol 81:1932-1941, 2015, https://doi.org/10.1128/AEM.03494-14). Revised genomic analysis of these strains revealed insertion sequence (IS)-driven insertions and deletions that knocked out regulators CadC (acid induction of lysine decarboxylase), GadX (acid induction of glutamate decarboxylase), and FNR (anaerobic regulator). Each acid-evolved strain showed loss of one or more amino acid decarboxylase systems, which normally help neutralize external acid (pH 5 to 6) and increase survival in extreme acid (pH 2). Strains from populations B11, H9, and F11 had an IS5 insertion or IS-mediated deletion in cadC, while population B11 had a point mutation affecting the arginine activator adiY The cadC and adiY mutants failed to neutralize acid in the presence of exogenous lysine or arginine. In strain B11-1, reversion of an rpoC (RNA polymerase) mutation partly restored arginine-dependent neutralization. All eight strains showed deletion or downregulation of the Gad acid fitness island. Strains with the Gad deletion lost the ability to produce GABA (gamma-aminobutyric acid) and failed to survive extreme acid. Transcriptome sequencing (RNA-seq) of strain B11-1 showed upregulated genes for catabolism of diverse substrates but downregulated acid stress genes (the biofilm regulator ariR, yhiM, and Gad). Other strains showed downregulation of H2 consumption mediated by hydrogenases (hya and hyb) which release acid. Strains F9-2 and F9-3 had a deletion of fnr and showed downregulation of FNR-dependent genes (dmsABC, frdABCD, hybABO, nikABCDE, and nrfAC). Overall, strains that had evolved in buffered acid showed loss or downregulation of systems that neutralize unbuffered acid and showed altered regulation of catabolism.IMPORTANCE Experimental evolution of an enteric bacterium under a narrow buffered range of acid pH leads to loss of genes that enhance fitness above or below the buffered pH range, including loss of enzymes that may raise external pH in the absence of buffer. Prominent modes of evolutionary change involve IS-mediated insertions and deletions that knock out key regulators. Over generations of acid stress, catabolism undergoes reregulation in ways that differ for each evolving strain.

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 flagellar system in Escherichia coli K12 is expressed under the control of the flhDC-encoded master regulator FlhDC. Transposition of insertion sequence (IS) elements to the upstream flhDC promoter region up-regulates transcription of this operon, resulting in a more rapid motility. Wang and Wood (ISME J 2011;5:1517-1525) provided evidence that insertion of IS5 into upstream activating sites occurs at higher rates in semi-solid agar media in which swarming behaviour is allowed as compared with liquid or solid media where swarming cannot occur. We confirm this conclusion and show that three IS elements, IS1, IS3 and IS5, transpose to multiple upstream sites within a 370 bp region of the flhDC operon control region. Hot spots for IS insertion correlate with positions of stress-induced DNA duplex destabilization (SIDD). We show that IS insertion occurs at maximal rates in 0.24 % agar, with rates decreasing dramatically with increasing or decreasing agar concentrations. In mixed cultures, we show that these mutations preferentially arise from the wild-type parent at frequencies of up to 3×10-3 cell-1 day-1 when the inoculated parental and co-existing IS-activated mutant cells are entering the stationary growth phase. We rigorously show that the apparent increased mutation frequencies cannot be accounted for by increased swimming or by increased growth under the selective conditions used. Thus, our data are consistent with the possibility that appropriate environmental conditions, namely those that permit but hinder flagellar rotation, result in the activation of a mutational pathway that involves IS element insertion upstream of the flhDC operon.

Escherichia coli K-12 and Salmonella enterica serovar Typhimurium LT2 became standard organisms for genetic analysis during the Truman administration. Half a century later, genetic analysis with these strains had become an art form, interpreted through 23 articles in the ambitious two-volume masterpiece edited by the late Fred Neidhardt and colleagues. These legacy articles now are available through EcoSal Plus, so as to inform and inspire contemporary genetic analyses in these standard organisms and their relatives.

Escherichia coli K-12 W3110 grows in the presence of membrane-permeant organic acids that can depress cytoplasmic pH and accumulate in the cytoplasm. We conducted experimental evolution by daily diluting cultures in increasing concentrations of benzoic acid (up to 20 mM) buffered at external pH 6.5, a pH at which permeant acids concentrate in the cytoplasm. By 2,000 generations, clones isolated from evolving populations showed increasing tolerance to benzoate but were sensitive to chloramphenicol and tetracycline. Sixteen clones grew to stationary phase in 20 mM benzoate, whereas the ancestral strain W3110 peaked and declined. Similar growth occurred in 10 mM salicylate. Benzoate-evolved strains grew like W3110 in the absence of benzoate, in media buffered at pH 4.8, pH 7.0, or pH 9.0, or in 20 mM acetate or sorbate at pH 6.5. Genomes of 16 strains revealed over 100 mutations, including single-nucleotide polymorphisms (SNPs), large deletions, and insertion knockouts. Most strains acquired deletions in the benzoate-induced multiple antibiotic resistance (Mar) regulon or in associated regulators such as rob and cpxA, as well as the multidrug resistance (MDR) efflux pumps emrA, emrY, and mdtA Strains also lost or downregulated the Gad acid fitness regulon. In 5 mM benzoate or in 2 mM salicylate (2-hydroxybenzoate), most strains showed increased sensitivity to the antibiotics chloramphenicol and tetracycline; some strains were more sensitive than a marA knockout strain. Thus, our benzoate-evolved strains may reveal additional unknown drug resistance components. Benzoate or salicylate selection pressure may cause general loss of MDR genes and regulators. Benzoate is a common food preservative, and salicylate is the primary active metabolite of aspirin. In the gut microbiome, genetic adaptation to salicylate may involve loss or downregulation of inducible multidrug resistance systems. This discovery implies that aspirin therapy may modulate the human gut microbiome to favor salicylate tolerance at the expense of drug resistance. Similar aspirin-associated loss of drug resistance might occur in bacterial pathogens found in arterial plaques.

The release of a wide variety of persistent chemical contaminants into wastewater has become a growing concern due to their potential health and environmental risks. While the toxic effects of these pollutants on aquatic organisms have been extensively studied, their impact on microbial pathogens and their virulence mechanisms remains largely unexplored. This research paper focuses on the identification and prioritization of chemical pollutants that increase bacterial pathogenicity, which is a public health concern. In order to predict how chemical compounds, such as pesticides and pharmaceuticals, would affect the virulence mechanisms of three bacterial strains (Escherichia coli K12, Pseudomonas aeruginosa H103, and Salmonella enterica serovar. Typhimurium), this study has developed quantitative structure–activity relationship (QSAR) models. The use of analysis of variance (ANOVA) functions assists in developing QSAR models based on the chemical structure of the compounds, to predict their effect on the growth and swarming behavior of the bacterial strains. The results showed an uncertainty in the created model, and that increases in virulence factors, including growth and motility of bacteria, after exposure to the studied compounds are possible to be predicted. These results could be more accurate if the interactions between groups of functions are included. For that, to make an accurate and universal model, it is essential to incorporate a larger number of compounds of similar and different structures.

Van Hofwegen et al. demonstrated that Escherichia coli rapidly evolves the ability to use citrate when long selective periods are provided (D. J. Van Hofwegen, C. J. Hovde, and S. A. Minnich, J Bacteriol 198:1022-1034, 2016, http://dx.doi.org/10.1128/JB.00831-15). This contrasts with the extreme delay (15 years of daily transfers) seen in the long-term evolution experiments of Lenski and coworkers. Their idea of "historical contingency" may require reinterpretation. Rapid evolution seems to involve selection for duplications of the whole cit locus that are too unstable to contribute when selection is provided in short pulses.

To study how a bacterium allocates its resources, we compared the costs and benefits of most (86%) of the proteins in Escherichia coli K-12 during growth in minimal glucose medium. The cost or investment in each protein was estimated from ribosomal profiling data, and the benefit of each protein was measured by assaying a library of transposon mutants. We found that proteins that are important for fitness are usually highly expressed, and 95% of these proteins are expressed at above 13 parts per million (ppm). Conversely, proteins that do not measurably benefit the host (with a benefit of less than 5% per generation) tend to be weakly expressed, with a median expression of 13 ppm. In aggregate, genes with no detectable benefit account for 31% of protein production, or about 22% if we correct for genetic redundancy. Although some of the apparently unnecessary expression could have subtle benefits in minimal glucose medium, the majority of the burden is due to genes that are important in other conditions. We propose that at least 13% of the cell's protein is "on standby" in case conditions change.

DNA-binding motifs that are recognized by transcription factors (TFs) have been well studied; however, challenges remain in determining the in vivo architecture of TF-DNA complexes on a genome-scale. Here, we determined the in vivo architecture of Escherichia coli arginine repressor (ArgR)-DNA complexes using high-throughput sequencing of exonuclease-treated chromatin-immunoprecipitated DNA (ChIP-exo). The ChIP-exo has a unique peak-pair pattern indicating 5' and 3' ends of ArgR-binding region. We identified 62 ArgR-binding loci, which were classified into three groups, comprising single, double and triple peak-pairs. Each peak-pair has a unique 93 base pair (bp)-long (±2 bp) ArgR-binding sequence containing two ARG boxes (39 bp) and residual sequences. Moreover, the three ArgR-binding modes defined by the position of the two ARG boxes indicate that DNA bends centered between the pair of ARG boxes facilitate the non-specific contacts between ArgR subunits and the residual sequences. Additionally, our approach may also reveal other fundamental structural features of TF-DNA interactions that have implications for studying genome-scale transcriptional regulatory networks.

Adaptive laboratory evolution (ALE) has emerged as an effective tool for scientific discovery and addressing biotechnological needs. Much of ALE's utility is derived from reproducibly obtained fitness increases. Identifying causal genetic changes and their combinatorial effects is challenging and time-consuming. Understanding how these genetic changes enable increased fitness can be difficult. A series of approaches that address these challenges was developed and demonstrated using Escherichia coli K-12 MG1655 on glucose minimal media at 37°C. By keeping E. coli in constant substrate excess and exponential growth, fitness increases up to 1.6-fold were obtained compared to the wild type. These increases are comparable to previously reported maximum growth rates in similar conditions but were obtained over a shorter time frame. Across the eight replicate ALE experiments performed, causal mutations were identified using three approaches: identifying mutations in the same gene/region across replicate experiments, sequencing strains before and after computationally determined fitness jumps, and allelic replacement coupled with targeted ALE of reconstructed strains. Three genetic regions were most often mutated: the global transcription gene rpoB, an 82-bp deletion between the metabolic pyrE gene and rph, and an IS element between the DNA structural gene hns and tdk. Model-derived classification of gene expression revealed a number of processes important for increased growth that were missed using a gene classification system alone. The methods described here represent a powerful combination of technologies to increase the speed and efficiency of ALE studies. The identified mutations can be examined as genetic parts for increasing growth rate in a desired strain and for understanding rapid growth phenotypes.

Adaptive laboratory evolution (ALE) has emerged as a valuable method by which to investigate microbial adaptation to a desired environment. Here, we performed ALE to 42 °C of ten parallel populations of Escherichia coli K-12 MG1655 grown in glucose minimal media. Tightly controlled experimental conditions allowed selection based on exponential-phase growth rate, yielding strains that uniformly converged toward a similar phenotype along distinct genetic paths. Adapted strains possessed as few as 6 and as many as 55 mutations, and of the 144 genes that mutated in total, 14 arose independently across two or more strains. This mutational recurrence pointed to the key genetic targets underlying the evolved fitness increase. Genome engineering was used to introduce the novel ALE-acquired alleles in random combinations into the ancestral strain, and competition between these engineered strains reaffirmed the impact of the key mutations on the growth rate at 42 °C. Interestingly, most of the identified key gene targets differed significantly from those found in similar temperature adaptation studies, highlighting the sensitivity of genetic evolution to experimental conditions and ancestral genotype. Additionally, transcriptomic analysis of the ancestral and evolved strains revealed a general trend for restoration of the global expression state back toward preheat stressed levels. This restorative effect was previously documented following evolution to metabolic perturbations, and thus may represent a general feature of ALE experiments. The widespread evolved expression shifts were enabled by a comparatively scant number of regulatory mutations, providing a net fitness benefit but causing suboptimal expression levels for certain genes, such as those governing flagellar formation, which then became targets for additional ameliorating mutations. Overall, the results of this study provide insight into the adaptation process and yield lessons important for the future implementation of ALE as a tool for scientific research and engineering.

The ferric uptake regulator (Fur) plays a critical role in the transcriptional regulation of iron metabolism. However, the full regulatory potential of Fur remains undefined. Here we comprehensively reconstruct the Fur transcriptional regulatory network in Escherichia coli K-12 MG1655 in response to iron availability using genome-wide measurements. Integrative data analysis reveals that a total of 81 genes in 42 transcription units are directly regulated by three different modes of Fur regulation, including apo- and holo-Fur activation and holo-Fur repression. We show that Fur connects iron transport and utilization enzymes with negative-feedback loop pairs for iron homeostasis. In addition, direct involvement of Fur in the regulation of DNA synthesis, energy metabolism and biofilm development is found. These results show how Fur exhibits a comprehensive regulatory role affecting many fundamental cellular processes linked to iron metabolism in order to coordinate the overall response of E. coli to iron availability.

A central unresolved issue in evolutionary biology is how metabolic innovations emerge. Low-level enzymatic side activities are frequent and can potentially be recruited for new biochemical functions. However, the role of such underground reactions in adaptation toward novel environments has remained largely unknown and out of reach of computational predictions, not least because these issues demand analyses at the level of the entire metabolic network. Here, we provide a comprehensive computational model of the underground metabolism in Escherichia coli. Most underground reactions are not isolated and 45% of them can be fully wired into the existing network and form novel pathways that produce key precursors for cell growth. This observation allowed us to conduct an integrated genome-wide in silico and experimental survey to characterize the evolutionary potential of E. coli to adapt to hundreds of nutrient conditions. We revealed that underground reactions allow growth in new environments when their activity is increased. We estimate that at least ∼20% of the underground reactions that can be connected to the existing network confer a fitness advantage under specific environments. Moreover, our results demonstrate that the genetic basis of evolutionary adaptations via underground metabolism is computationally predictable. The approach used here has potential for various application areas from bioengineering to medical genetics.

In bacteria, the clustered regularly interspaced short palindromic repeats (CRISPR)-associated (Cas) DNA-targeting complex Cascade (CRISPR-associated complex for antiviral defense) uses CRISPR RNA (crRNA) guides to bind complementary DNA targets at sites adjacent to a trinucleotide signature sequence called the protospacer adjacent motif (PAM). The Cascade complex then recruits Cas3, a nuclease-helicase that catalyzes unwinding and cleavage of foreign double-stranded DNA (dsDNA) bearing a sequence matching that of the crRNA. Cascade comprises the CasA-E proteins and one crRNA, forming a structure that binds and unwinds dsDNA to form an R loop in which the target strand of the DNA base pairs with the 32-nt RNA guide sequence. Single-particle electron microscopy reconstructions of dsDNA-bound Cascade with and without Cas3 reveal that Cascade positions the PAM-proximal end of the DNA duplex at the CasA subunit and near the site of Cas3 association. The finding that the DNA target and Cas3 colocalize with CasA implicates this subunit in a key target-validation step during DNA interference. We show biochemically that base pairing of the PAM region is unnecessary for target binding but critical for Cas3-mediated degradation. In addition, the L1 loop of CasA, previously implicated in PAM recognition, is essential for Cas3 activation following target binding by Cascade. Together, these data show that the CasA subunit of Cascade functions as an essential partner of Cas3 by recognizing DNA target sites and positioning Cas3 adjacent to the PAM to ensure cleavage.

Gene regulation in bacteria is usually described as an adaptive response to an environmental change so that genes are expressed when they are required. We instead propose that most genes are under indirect control: their expression responds to signal(s) that are not directly related to the genes' function. Indirect control should perform poorly in artificial conditions, and we show that gene regulation is often maladaptive in the laboratory. In Shewanella oneidensis MR-1, 24% of genes are detrimental to fitness in some conditions, and detrimental genes tend to be highly expressed instead of being repressed when not needed. In diverse bacteria, there is little correlation between when genes are important for optimal growth or fitness and when those genes are upregulated. Two common types of indirect control are constitutive expression and regulation by growth rate; these occur for genes with diverse functions and often seem to be suboptimal. Because genes that have closely related functions can have dissimilar expression patterns, regulation may be suboptimal in the wild as well as in the laboratory.

EcoCyc (http://EcoCyc.org) is a model organism database built on the genome sequence of Escherichia coli K-12 MG1655. Expert manual curation of the functions of individual E. coli gene products in EcoCyc has been based on information found in the experimental literature for E. coli K-12-derived strains. Updates to EcoCyc content continue to improve the comprehensive picture of E. coli biology. The utility of EcoCyc is enhanced by new tools available on the EcoCyc web site, and the development of EcoCyc as a teaching tool is increasing the impact of the knowledge collected in EcoCyc.

Nanosized alginate-based particles (NAPs) were obtained in a one-pot solvent-free synthesis procedure, achieving the design of a biocompatible nanocarrier for the encapsulation of IbM6 antimicrobial peptide (IbM6). IbM6 is integrated in the nascent nanosized hydrogel self-assembly guided by electrostatic interactions and by weak interactions, typical of soft matter. The formation of the nanogel is a dynamic and complex process, which presents an interesting temporal evolution. In this work, we optimized the synthesis conditions of IbM6-NAPs based on small-angle X-ray scattering (SAXS) measurements and evaluated its time evolution over several weeks by sensing the IbM6 environment in IbM6-NAPs from photochemical experiments. Fluorescence deactivation experiments revealed that the accessibility of different quenchers to the IbM6 peptide embedded in NAPs is dependent on the aging time of the alginate network. Lifetimes measurements indicate that the deactivation paths of the excited state of the IbM6 in the nanoaggregates are reduced when compared with those exhibited by the peptide in aqueous solution, and are also dependent on the aging time of the nanosized alginate network. Finally, the entrapment of IbM6 in NAPs hinders the degradation of the peptide by trypsin, increasing its antimicrobial activity against Escherichia coli K-12 in simulated operation conditions., (© 2024. The Author(s), under exclusive licence to European Photochemistry Association, European Society for Photobiology.)

Tetrahydrofuran (THF) is a universal solvent widely used in the synthesis of chemicals and pharmaceuticals. As a refractory organic contaminant, it can only be degraded by a small group of microbes. In this study, a thiamine auxotrophic THF-degrading bacterium, Rhodococcus ruber ZM07, was isolated from an enrichment culture H-1. It was cocultured with Escherichia coli K12 (which cannot degrade THF but can produce thiamine) and/or Escherichia coli K12ΔthiE (which can neither degrade THF nor produce thiamine) with or without exogenous thiamine. This study aims to understand the interaction mechanisms between ZM07 and K12. We found that K12 accounted for 30% of the total when cocultured and transferred with ZM07 in thiamine-free systems; in addition, in the three-strain (ZM07, K12, and K12ΔthiE) cocultured system without thiamine, K12ΔthiE disappeared in the 8th transfer, while K12 could still stably exist (the relative abundance remained at approximately 30%). The growth of K12 was significantly inhibited in the thiamine-rich system. Its proportion was almost below 4% after the fourth transfer in both the two-strain (ZM07 and K12) and three-strain (ZM07, K12, and K12ΔthiE) systems; K12ΔthiE’s percentage was higher than K12’s in the three-strain (ZM07, K12, and K12ΔthiE) cocultured system with exogenous thiamine, and both represented only a small proportion (less than 1% by the fourth transfer). The results of the coculture of K12 and K12ΔthiE in thiamine-free medium indicated that intraspecific competition between them may be one of the main reasons for the extinction of K12ΔthiE in the three-strain (ZM07, K12, and K12ΔthiE) system without exogenous thiamine. Furthermore, we found that ZM07 could cooperate with K12 through extracellular metabolites exchanges without physical contact. This study provides novel insight into how microbes cooperate and compete with one another during THF degradation.

Bacteria and archaea acquire resistance to viruses and plasmids by integrating short fragments of foreign DNA into clustered regularly interspaced short palindromic repeats (CRISPRs). These repetitive loci maintain a genetic record of all prior encounters with foreign transgressors. CRISPRs are transcribed and the long primary transcript is processed into a library of short CRISPR-derived RNAs (crRNAs) that contain a unique sequence complementary to a foreign nucleic-acid challenger. In Escherichia coli, crRNAs are incorporated into a multisubunit surveillance complex called Cascade (CRISPR-associated complex for antiviral defence), which is required for protection against bacteriophages. Here we use cryo-electron microscopy to determine the subnanometre structures of Cascade before and after binding to a target sequence. These structures reveal a sea-horse-shaped architecture in which the crRNA is displayed along a helical arrangement of protein subunits that protect the crRNA from degradation while maintaining its availability for base pairing. Cascade engages invading nucleic acids through high-affinity base-pairing interactions near the 5' end of the crRNA. Base pairing extends along the crRNA, resulting in a series of short helical segments that trigger a concerted conformational change. This conformational rearrangement may serve as a signal that recruits a trans-acting nuclease (Cas3) for destruction of invading nucleic-acid sequences.

EcoCyc (http://EcoCyc.org) is a comprehensive model organism database for Escherichia coli K-12 MG1655. From the scientific literature, EcoCyc captures the functions of individual E. coli gene products; their regulation at the transcriptional, post-transcriptional and protein level; and their organization into operons, complexes and pathways. EcoCyc users can search and browse the information in multiple ways. Recent improvements to the EcoCyc Web interface include combined gene/protein pages and a Regulation Summary Diagram displaying a graphical overview of all known regulatory inputs to gene expression and protein activity. The graphical representation of signal transduction pathways has been updated, and the cellular and regulatory overviews were enhanced with new functionality. A specialized undergraduate teaching resource using EcoCyc is being developed.

Tetrahydrofuran (THF) is a universal solvent widely used in the synthesis of chemicals and pharmaceuticals. As a refractory organic contaminant, it can only be degraded by a small group of microbes. In this study, a thiamine auxotrophic THF-degrading bacterium, Rhodococcus ruber ZM07, was isolated from an enrichment culture H-1. It was cocultured with Escherichia coli K12 (which cannot degrade THF but can produce thiamine) and/or Escherichia coli K12Δ thiE (which can neither degrade THF nor produce thiamine) with or without exogenous thiamine. This study aims to understand the interaction mechanisms between ZM07 and K12. We found that K12 accounted for 30% of the total when cocultured and transferred with ZM07 in thiamine-free systems; in addition, in the three-strain (ZM07, K12, and K12Δ thiE) cocultured system without thiamine, K12Δ thiE disappeared in the 8th transfer, while K12 could still stably exist (the relative abundance remained at approximately 30%). The growth of K12 was significantly inhibited in the thiamine-rich system. Its proportion was almost below 4% after the fourth transfer in both the two-strain (ZM07 and K12) and three-strain (ZM07, K12, and K12Δ thiE) systems; K12Δ thiE 's percentage was higher than K12's in the three-strain (ZM07, K12, and K12Δ thiE) cocultured system with exogenous thiamine, and both represented only a small proportion (less than 1% by the fourth transfer). The results of the coculture of K12 and K12Δ thiE in thiamine-free medium indicated that intraspecific competition between them may be one of the main reasons for the extinction of K12Δ thiE in the three-strain (ZM07, K12, and K12Δ thiE) system without exogenous thiamine. Furthermore, we found that ZM07 could cooperate with K12 through extracellular metabolites exchanges without physical contact. This study provides novel insight into how microbes cooperate and compete with one another during THF degradation. [ABSTRACT FROM AUTHOR]

Nanoparticles (NPs) represent a potential optoelectronic source capable of significantly boosting hydrogen production; however, their inevitable cytotoxicity may lead to oxidative damage of bacterial cell membranes. In this study, we employed non-photosynthetic Escherichia coli K-12 as a model organism and utilized self-assembled cadmium sulfide (CdS) nanoparticles to construct a low-toxicity and hydrogen-production-enhancing self-photosensitive hybrid system. To mitigate the cytotoxicity of CdS NPs and synthesize biocompatible CdS NPs on the cell surface, we employed engineered E. coli ( efeB /OE) for bioremediation, achieving this goal through the overexpression of the peroxidase enzyme (EfeB). A comparative analysis with E. coli -CdS revealed a significant downregulation of genes encoding oxidative stress proteins in efeB /OE-CdS post-irradiation. Atomic force microscopy (AFM) confirmed the stability of bacterial cell membranes. Due to the enhanced stability of the cell membrane, the hydrogen yield of the efeB /OE-CdS system increased by 1.3 times compared to the control, accompanied by a 49.1% reduction in malondialdehyde (MDA) content. This study proposes an effective strategy to alleviate the toxicity of mixed biological nanoparticle systems and efficiently harness optoelectronic electrons, thereby achieving higher hydrogen production in bioremediation.

Lacto-N-tetraose (LNT) is a human milk oligosaccharide with average concentrations ranging from 0.74 to 1.07 g/L in breastmilk, depending on the lactation stage. In this study, the preclinical safety of LNT produced by the Escherichia coli K-12 E2083 production strain was assessed. LNT was negative in both the bacterial reverse mutation assay and the in vitro micronucleus assay, demonstrating the absence of genotoxic potential for this substance. In the OECD 408 guideline compliant 90-day oral toxicity study rat, LNT did not induce any adverse effects in any treatment group up to and including the highest dose tested, and no LOAEL could be determined. Therefore, the no-observed-adverse effect level (NOAEL) is set at the highest dose level tested, i.e. a dietary level of 5 % (w/w), corresponding to ≥2856 mg/kg bw/day and ≥3253 mg/kg bw/day for males and females, respectively. This might be an underestimation of the NOAEL, caused by the range of dose levels tested. The results obtained in the current study are in good agreement with available data generated using other biotechnologically produced LNT batches and therefore support its safe use as a food ingredient., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Dianne J. Delsing reports a relationship with FrieslandCampina that includes: employment. Hester van der Woude reports a relationship with FrieslandCampina that includes: consulting or advisory. Sylvia M.J.G. Pelgrom reports a relationship with FrieslandCampina that includes: consulting or advisory. Carin Buskens reports a relationship with FrieslandCampina that includes: consulting or advisory. Roy Hoffmans reports a relationship with FrieslandCampina that includes: consulting or advisory. Nora Krajcs reports a relationship with FrieslandCampina that includes: consulting or advisory., (Copyright © 2024 Elsevier Inc. All rights reserved.)