Decoding genome-wide GadEWX-transcriptional regulatory networks reveals multifaceted cellular responses to acid stress in Escherichia coli

ChIP-mini: a low-input ChIP-exo protocol for elucidating DNA-binding protein dynamics in intracellular pathogens

Genome-wide identification of binding profiles for DNA-binding proteins from the limited number of intracellular pathogens in infection studies is crucial for understanding virulence and cellular processes but remains challenging, as the current ChIP-exo is designed for high-input bacterial cells (>1010). Here, we developed an optimized ChIP-mini method, a low-input ChIP-exo utilizing a 5,000-fold reduced number of initial bacterial cells and an analysis pipeline, to identify genome-wide binding dynamics of DNA-binding proteins in host-infected pathogens. Applying ChIP-mini to intracellular Salmonella Typhimurium, we identified 642 and 1,837 binding sites of H-NS and RpoD, respectively, elucidating changes in their binding position and binding intensity during infection. Post-infection, we observed 21 significant reductions in H-NS binding at intergenic regions, exposing the promoter region of virulence genes, such as those in Salmonella pathogenicity islands-2, 3 and effectors. Furthermore, we revealed the crucial phenomenon that novel and significantly increased RpoD bindings were found within regions exhibiting diminished H-NS binding, thereby facilitating substantial upregulation of virulence genes. These findings markedly enhance our understanding of how H-NS and RpoD simultaneously coordinate the transcription initiation of virulence genes within macrophages. Collectively, this work demonstrates a broadly adaptable tool that will enable the elucidation of DNA-binding protein dynamics in diverse intracellular pathogens during infection.

iModulonDB 2.0: dynamic tools to facilitate knowledge-mining and user-enabled analyses of curated transcriptomic datasets

iModulons-sets of co-expressed genes identified through independent component analysis (ICA) of high-quality transcriptomic datasets-provide an unbiased, modular view of an organism's transcriptional regulatory network. Established in 2020, iModulonDB (iModulonDB.org) serves as a centralized repository of curated iModulon sets, enabling users to explore iModulons and download the associated transcriptomic data. This update reflects a significant expansion of the database-19 new ICA decompositions (+633%) spanning 8 925 expression profiles (+1370%), 503 studies (+2290%) and 12 additional organisms (+400%)-and introduces new features to help scientists decipher the mechanisms governing prokaryotic transcriptional regulation. To facilitate comprehension of the underlying expression profiles, the updated user-interface displays essential information about each data-generating study (e.g. the experimental conditions and publication abstract). Dashboards now include condition-specific coloring and highlight data generated from genetically perturbed strains, enabling users to rapidly interpret disruptions in transcriptional regulation. New interactive graphs rapidly convey omics-derived indicators (e.g. the explained variance of ICA decompositions, genetic overlap between iModulons and regulons). Direct links to operon diagrams (BioCyc) and protein-protein interaction networks (STRING) provide users with seamless access to external resources for further assessment of iModulons. Lastly, a new suite of search-driven and species-wide analysis tools promotes user-engagement with iModulons, reinforcing iModulonDB's role as a dynamic, interactive knowledgebase of prokaryotic transcriptional regulation.

New insight into acid-resistant enzymes from natural mutations of Escherichia coli Nissle 1917

The probiotic Escherichia coli Nissle 1917 (EcN), known for its superior acid resistance (AR), serves as a promising chassis for live therapeutics due to the effective colonization capabilities. However, the enzymatic activity regarding AR in EcN remains poorly understood. First, we investigated the AR systems of EcN by measuring cell growth under acidic stress and exploring the relationship of mutations to their corresponding enzymatic activities. As a result, the catalytic activity of inducible decarboxylases of GadB, AdiA and CadA, responsible for metabolizing glutamate, arginine, and lysine, exhibited an average 2-fold increase in EcN compared to the reference strain MG1655. Furthermore, we discovered that the glutamate-dependent AR2 system in EcN was meticulously regulated by specific regulons such as GadW. This study not only revealed the physiology of EcN under acidic conditions, but also highlighted that the mutated core enzymes in the AR system of EcN exhibit improved activities.

An Optimized Method for Reconstruction of Transcriptional Regulatory Networks in Bacteria Using ChIP-exo and RNA-seq Datasets

Transcriptional regulatory networks (TRNs) in bacteria are crucial for elucidating the mechanisms that regulate gene expression and cellular responses to environmental stimuli. These networks delineate the interactions between transcription factors (TFs) and their target genes, thereby uncovering the regulatory processes that modulate gene expression under varying environmental conditions. Analyzing TRNs offers valuable insights into bacterial adaptation, stress responses, and metabolic optimization from an evolutionary standpoint. Additionally, understanding TRNs can drive the development of novel antimicrobial therapies and the engineering of microbial strains for biofuel and bioproduct production. This protocol integrates advanced data analysis pipelines, including ChEAP, DEOCSU, and DESeq2, to analyze omics datasets that encompass genome-wide TF binding sites and transcriptome profiles derived from ChIP-exo and RNA-seq experiments. This approach minimizes both the time required and the risk of bias, making it accessible to non-expert users. Key steps in the protocol include preprocessing and peak calling from ChIP-exo data, differential expression analysis of RNA-seq data, and motif and regulon analysis. This method offers a comprehensive and efficient framework for TRN reconstruction across various bacterial strains, enhancing both the accuracy and reliability of the analysis while providing valuable insights for basic and applied research.

Increased antimicrobial resistance of acid-adapted pathogenic Escherichia coli, and transcriptomic analysis of polymyxin-resistant strain

This study investigated the acid adaptation and antimicrobial resistance of seven pathogenic Escherichia coli strains and one commensal strain under nutrient-rich acidic conditions. After acid adaptation, three pathogenic E. coli survived during 100 h incubation in tryptic soy broth at pH 3.25. Acid-adapted (AA) strains showed increased resistance to antimicrobials including ampicillin, ciprofloxacin and especially polymyxins (colistin and polymyxin B), the last resort antimicrobial for multidrug-resistant Gram-negative bacteria. Enterotoxigenic E. coli strain (NCCP 13717) showed significantly increased resistance to acids and polymyxins. Transcriptome analysis of the AA NCCP 13717 revealed upregulation of genes related to the acid fitness island and the arn operon, which reduces lipopolysaccharide binding affinity at the polymyxin site of action. Genes such as eptA, tolC, and ompCF were also upregulated to alter the structure of the cell membrane, reducing the outer membrane permeability compared to the control, which is likely to be another mechanism for polymyxin resistance. This study highlights the emergence of antimicrobial resistance in AA pathogenic E. coli strains, particularly polymyxin resistance, and the mechanisms behind the increased antimicrobial resistance, providing important insights for the development of risk management strategies to effectively control the antimicrobial resistant foodborne pathogens.

Engineering quorum sensing-based genetic circuits enhances growth and productivity robustness of industrial E. coli at low pH

BACKGROUND

Microbial organisms hold significant potential for converting renewable substrates into valuable chemicals. Low pH fermentation in industrial settings offers key advantages, including reduced neutralizer usage and decreased wastewater generation, particularly in the production of amino acids and organic acids. Engineering acid-tolerant strains represents a viable strategy to enhance productivity in acidic environments. Synthetic biology provides dynamic regulatory tools, such as gene circuits, facilitating precise expression of acid resistance (AR) modules in a just-in-time and just-enough manner.

RESULTS

In this study, we aimed to enhance the robustness and productivity of Escherichia coli, a workhorse for amino acid and organic acid production, in industrial fermentation under mild acidic conditions. We employed an Esa-type quorum sensing circuit to dynamically regulate the expression of an AR module (DsrA-Hfq) in a just-in-time and just-enough manner. Through careful engineering of the critical promoter PesaS and stepwise evaluation, we developed an optimal Esa-PBD(L) circuit that conferred upon an industrial E. coli strain SCEcL3 comparable lysine productivity and enhanced yield at pH 5.5 compared to the parent strain at pH 6.8.

CONCLUSIONS

This study exemplifies the practical application of gene circuits in industrial environments, which present challenges far beyond those of well-controlled laboratory conditions.

Methods for studying microbial acid stress responses: from molecules to populations

The study of how micro-organisms detect and respond to different stresses has a long history of producing fundamental biological insights while being simultaneously of significance in many applied microbiological fields including infection, food and drink manufacture, and industrial and environmental biotechnology. This is well-illustrated by the large body of work on acid stress. Numerous different methods have been used to understand the impacts of low pH on growth and survival of micro-organisms, ranging from studies of single cells to large and heterogeneous populations, from the molecular or biophysical to the computational, and from well-understood model organisms to poorly defined and complex microbial consortia. Much is to be gained from an increased general awareness of these methods, and so the present review looks at examples of the different methods that have been used to study acid resistance, acid tolerance, and acid stress responses, and the insights they can lead to, as well as some of the problems involved in using them. We hope this will be of interest both within and well beyond the acid stress research community.

The hallmarks of a tradeoff in transcriptomes that balances stress and growth functions

Fast growth phenotypes are achieved through optimal transcriptomic allocation, in which cells must balance tradeoffs in resource allocation between diverse functions. One such balance between stress readiness and unbridled growth in E. coli has been termed the fear versus greed (f/g) tradeoff. Two specific RNA polymerase (RNAP) mutations observed in adaptation to fast growth have been previously shown to affect the f/g tradeoff, suggesting that genetic adaptations may be primed to control f/g resource allocation. Here, we conduct a greatly expanded study of the genetic control of the f/g tradeoff across diverse conditions. We introduced 12 RNA polymerase (RNAP) mutations commonly acquired during adaptive laboratory evolution (ALE) and obtained expression profiles of each. We found that these single RNAP mutation strains resulted in large shifts in the f/g tradeoff primarily in the RpoS regulon and ribosomal genes, likely through modifying RNAP-DNA interactions. Two of these mutations additionally caused condition-specific transcriptional adaptations. While this tradeoff was previously characterized by the RpoS regulon and ribosomal expression, we find that the GAD regulon plays an important role in stress readiness and ppGpp in translation activity, expanding the scope of the tradeoff. A phylogenetic analysis found the greed-related genes of the tradeoff present in numerous bacterial species. The results suggest that the f/g tradeoff represents a general principle of transcriptome allocation in bacteria where small genetic changes can result in large phenotypic adaptations to growth conditions.IMPORTANCETo increase growth, E. coli must raise ribosomal content at the expense of non-growth functions. Previous studies have linked RNAP mutations to this transcriptional shift and increased growth but were focused on only two mutations found in the protein's central region. RNAP mutations, however, commonly occur over a large structural range. To explore RNAP mutations' impact, we have introduced 12 RNAP mutations found in laboratory evolution experiments and obtained expression profiles of each. The mutations nearly universally increased growth rates by adjusting said tradeoff away from non-growth functions. In addition to this shift, a few caused condition-specific adaptations. We explored the prevalence of this tradeoff across phylogeny and found it to be a widespread and conserved trend among bacteria.

Multiscale regulation of nutrient stress responses in Escherichia coli from chromatin structure to small regulatory RNAs

Recent research has indicated the presence of heterochromatin-like regions of extended protein occupancy and transcriptional silencing of bacterial genomes. We utilized an integrative approach to track chromatin structure and transcription in E. coli K-12 across a wide range of nutrient conditions. In the process, we identified multiple loci which act similarly to facultative heterochromatin in eukaryotes, normally silenced but permitting expression of genes under specific conditions. We also found a strong enrichment of small regulatory RNAs (sRNAs) among the set of differentially expressed transcripts during nutrient stress. Using a newly developed bioinformatic pipeline, the transcription factors regulating sRNA expression were bioinformatically predicted, with experimental follow-up revealing novel relationships for 36 sRNA-transcription factors candidates. Direct regulation of sRNA expression was confirmed by mutational analysis for five sRNAs of metabolic interest: IsrB, CsrB and CsrC, GcvB, and GadY. Our integrative analysis thus reveals additional layers of complexity in the nutrient stress response in E. coli and provides a framework for revealing similar poorly understood regulatory logic in other organisms.

Multitier regulation of the E. coli extreme acid stress response by CsrA

CsrA is an RNA-binding protein that regulates processes critical for growth and survival, including central carbon metabolism, motility, biofilm formation, stress responses, and expression of virulence factors in pathogens. Transcriptomics studies in Escherichia coli suggested that CsrA repressed genes involved in surviving extremely acidic conditions. Here, we examine the effects of disrupting CsrA-dependent regulation on the expression of genes and circuitry for acid stress survival and demonstrate CsrA-mediated repression at multiple levels. We show that this repression is critical for managing the trade-off between growth and survival; overexpression of acid stress genes caused by csrA disruption enhances survival under extreme acidity but is detrimental for growth under mildly acidic conditions. In vitro studies confirmed that CsrA binds specifically to mRNAs of structural and regulatory genes for acid stress survival, causing translational repression. We also found that translation of the top-tier acid stress regulator, evgA, is coupled to that of a small leader peptide, evgL, which is repressed by CsrA. Unlike dedicated acid stress response genes, csrA and its sRNA antagonists, csrB and csrC, did not exhibit a substantial response to acid shock. Furthermore, disruption of CsrA regulation of acid stress genes impacted host-microbe interactions in Caenorhabditis elegans, alleviating GABA deficiencies. This study expands the known regulon of CsrA to genes of the extreme acid stress response of E. coli and highlights a new facet of the global role played by CsrA in balancing the opposing physiological demands of stress resistance with the capacity for growth and modulating host interactions.IMPORTANCETo colonize/infect the mammalian intestinal tract, bacteria must survive exposure to the extreme acidity of the stomach. E. coli does this by expressing proteins that neutralize cytoplasmic acidity and cope with molecular damage caused by low pH. Because of the metabolic cost of these processes, genes for surviving acid stress are tightly regulated. Here, we show that CsrA negatively regulates the cascade of expression responsible for the acid stress response. Increased expression of acid response genes due to csrA disruption improved survival at extremely low pH but inhibited growth under mildly acidic conditions. Our findings define a new layer of regulation in the acid stress response of E. coli and a novel physiological function for CsrA.

Insights into the complementation potential of the extreme acidophile's orthologue in replacing Escherichia coli hfq gene-particularly in bacterial resistance to environmental stress

Acidithiobacillus caldus is a typical extreme acidophile widely used in the biohydrometallurgical industry, which often experiences extreme environmental stress in its natural habitat. Hfq, an RNA-binding protein, typically functions as a global regulator involved in various cellular physiological processes. Yet, the biological functions of Hfq derived from such extreme acidophile have not been extensively investigated. In this study, the recombinant strain Δhfq/Achfq, constructed by CRISPR/Cas9-mediated chromosome integration, fully or partially restored the phenotypic defects caused by hfq deletion in Escherichia coli, including impaired growth performance, abnormal cell morphology, impaired swarming motility, decreased stress resistance, decreased intracellular ATP and free amino acid levels, and attenuated biofilm formation. Particularly noteworthy, the intracellular ATP level and biofilm production of the recombinant strain were increased by 12.2% and 7.0%, respectively, compared to the Δhfq mutant. Transcriptomic analysis revealed that even under heterologous expression, AcHfq exerted global regulatory effects on multiple cellular processes, including metabolism, environmental signal processing, and motility. Finally, we established a potential working model to illustrate the regulatory mechanism of AcHfq in bacterial resistance to environmental stress.

CRISPR-dCas13a system for programmable small RNAs and polycistronic mRNA repression in bacteria

Bacterial small RNAs (sRNAs) function in post-transcriptional regulatory responses to environmental changes. However, the lack of eukaryotic RNA interference-like machinery in bacteria has limited the systematic engineering of RNA repression. Here, we report the development of clustered regularly interspaced short palindromic repeats (CRISPR)-guided dead CRIPSR-associated protein 13a (dCas13a) ribonucleoprotein that utilizes programmable CRISPR RNAs (crRNAs) to repress trans-acting and cis-acting sRNA as the target, altering regulatory mechanisms and stress-related phenotypes. In addition, we implemented a modular loop engineering of the crRNA to promote modular repression of the target gene with 92% knockdown efficiency and a single base-pair mismatch specificity. With the engineered crRNAs, we achieved targetable single-gene repression in the polycistronic operon. For metabolic application, 102 crRNAs were constructed in the biofoundry and used for screening novel knockdown sRNA targets to improve lycopene (colored antioxidant) production in Escherichia coli. The CRISPR-dCas13a system will assist as a valuable systematic tool for the discovery of novel sRNAs and the fine-tuning of bacterial RNA repression in both scientific and industrial applications.

Experimental promoter identification of a foodborne pathogen Salmonella enterica subsp. enterica serovar Typhimurium with near single base-pair resolution

Salmonella enterica serovar Typhimurium (S. Typhimurium) is a common foodborne pathogen which is frequently used as the reference strain for Salmonella. Investigating the sigma factor network and protomers is crucial to understand the genomic and transcriptomic properties of the bacterium. Its promoters were identified using various methods such as dRNA-seq, ChIP-chip, or ChIP-Seq. However, validation using ChIP-exo, which exhibits higher-resolution performance compared to conventional ChIP, has not been conducted to date. In this study, using the representative strain S. Typhimurium LT2 (LT2), the ChIP-exo experiment was conducted to accurately determine the binding sites of catalytic RNA polymerase subunit RpoB and major sigma factors (RpoD, RpoN, RpoS, and RpoE) during exponential phase. Integrated with the results of RNA-Seq, promoters and sigmulons for the sigma factors and their association with RpoB have been discovered. Notably, the overlapping regions among binding sites of each alternative sigma factor were found. Furthermore, comparative analysis with Escherichia coli str. K-12 substr. MG1655 (MG1655) revealed conserved binding sites of RpoD and RpoN across different species. In the case of small RNAs (sRNAs), 50 sRNAs observed their expression during the exponential growth of LT2. Collectively, the integration of ChIP-exo and RNA-Seq enables genome-scale promoter mapping with high resolution and facilitates the characterization of binding events of alternative sigma factors, enabling a comprehensive understanding of the bacterial sigma factor network and condition-specific active promoters.

Recent findings in molecular reactions of E. coli as exposed to alkylated, nano- and ordinary chitosans

The antibacterial effects of chitosan have been widely studied, but the underlying molecular mechanisms are not fully understood. We investigated the molecular responses of Escherichia coli MG1655 cell, a model gram-negative bacterium, upon exposure to chitosan (Cs), alkylated Cs (AlkCs), and chitosan nanoparticles (CsNPs). Nine target genes involved in relevant signaling pathways (ompF, ompC, ompA, mrcA, mrcB, mgtA, glnA, kdpA, lptA) were selected for analysis. A significant reduction in the expression of mrcA, mgtA, glnA, and lptA genes was observed in the cells treated with Cs. Those treated with Cs, AlkCs, and CsNPs revealed an increase in ompF gene expression, but the expression level was lower in the cells treated with AlkCs and CsNPs compared to Cs. This increase in porin expression suggests compromised membrane integrity and disrupted nutrient transport. In addition, the changes in the expression of mgtA, kdpA, and glnA are related to different effects on membrane permeability. The higher expression in the genes mrcA and mrcB is associated with morphological changes of cells treated with AlkCs and CsNPs. These findings contribute to our understanding of the molecular mechanisms underlying chitosan-induced stress responses and provide insights for the development of safer antimicrobial compounds in the future.

Ribosome profiling reveals the fine-tuned response of Escherichia coli to mild and severe acid stress

IMPORTANCE

Bacteria react very differently to survive in acidic environments, such as the human gastrointestinal tract. Escherichia coli is one of the extremely acid-resistant bacteria and has a variety of acid-defense mechanisms. Here, we provide the first genome-wide overview of the adaptations of E. coli K-12 to mild and severe acid stress at both the transcriptional and translational levels. Using ribosome profiling and RNA sequencing, we uncover novel adaptations to different degrees of acidity, including previously hidden stress-induced small proteins and novel key transcription factors for acid defense, and report mRNAs with pH-dependent differential translation efficiency. In addition, we distinguish between acid-specific adaptations and general stress response mechanisms using denoising autoencoders. This workflow represents a powerful approach that takes advantage of next-generation sequencing techniques and machine learning to systematically analyze bacterial stress responses.

A heritable iron memory enables decision-making in Escherichia coli

The importance of memory in bacterial decision-making is relatively unexplored. We show here that a prior experience of swarming is remembered when Escherichia coli encounters a new surface, improving its future swarming efficiency. We conducted >10,000 single-cell swarm assays to discover that cells store memory in the form of cellular iron levels. This "iron" memory preexists in planktonic cells, but the act of swarming reinforces it. A cell with low iron initiates swarming early and is a better swarmer, while the opposite is true for a cell with high iron. The swarming potential of a mother cell, which tracks with its iron memory, is passed down to its fourth-generation daughter cells. This memory is naturally lost by the seventh generation, but artificially manipulating iron levels allows it to persist much longer. A mathematical model with a time-delay component faithfully recreates the observed dynamic interconversions between different swarming potentials. We demonstrate that cellular iron levels also track with biofilm formation and antibiotic tolerance, suggesting that iron memory may impact other physiologies.

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.

tRNA queuosine modification is involved in biofilm formation and virulence in bacteria

tRNA modifications are crucial for fine-tuning of protein translation. Queuosine (Q) modification of tRNAs is thought to modulate the translation rate of NAU codons, but its physiological role remains elusive. Therefore, we hypothesize that Q-tRNAs control those physiological processes involving NAU codon-enriched genes (Q-genes). Here, we report a novel bioinformatic strategy to predict Q-genes, revealing a widespread enrichment in functions, especially those related to biofilm formation and virulence in bacteria, and particularly in human pathogens. Indeed, we experimentally verified that these processes were significantly affected by altering the degree of tRNA Q-modification in different model bacteria, representing the first report of a general mechanism controlling biofilm formation and virulence in Gram-positive and Gram-negative bacteria possibly through the coordination of the expression of functionally related genes. Furthermore, we propose that changes in Q availability in a microbiome would affect its functionality. Our findings open the door to the control of bacterial infections and biofilm formation by inhibition of tRNA Q-modification.

Genome-wide promoter responses to CRISPR perturbations of regulators reveal regulatory networks in Escherichia coli

Elucidating genome-scale regulatory networks requires a comprehensive collection of gene expression profiles, yet measuring gene expression responses for every transcription factor (TF)-gene pair in living prokaryotic cells remains challenging. Here, we develop pooled promoter responses to TF perturbation sequencing (PPTP-seq) via CRISPR interference to address this challenge. Using PPTP-seq, we systematically measure the activity of 1372 Escherichia coli promoters under single knockdown of 183 TF genes, illustrating more than 200,000 possible TF-gene responses in one experiment. We perform PPTP-seq for E. coli growing in three different media. The PPTP-seq data reveal robust steady-state promoter activities under most single TF knockdown conditions. PPTP-seq also enables identifications of, to the best of our knowledge, previously unknown TF autoregulatory responses and complex transcriptional control on one-carbon metabolism. We further find context-dependent promoter regulation by multiple TFs whose relative binding strengths determined promoter activities. Additionally, PPTP-seq reveals different promoter responses in different growth media, suggesting condition-specific gene regulation. Overall, PPTP-seq provides a powerful method to examine genome-wide transcriptional regulatory networks and can be potentially expanded to reveal gene expression responses to other genetic elements.

Elucidating the CodY regulon in Staphylococcus aureus USA300 substrains TCH1516 and LAC

CodY is a conserved broad-acting transcription factor that regulates the expression of genes related to amino acid metabolism and virulence in Gram-positive bacteria. Here, we performed the first in vivo determination of CodY target genes using a novel CodY monoclonal antibody in methicillin-resistant Staphylococcus aureus (MRSA) USA300. Our results showed (i) the same 135 CodY promoter binding sites regulating the 165 target genes identified in two closely related virulent S. aureus USA300 TCH1516 and LAC strains; (ii) the differential binding intensity for the same target genes under the same conditions was due to sequence differences in the same CodY-binding site in the two strains; (iii) a CodY regulon comprising 72 target genes that are differentially regulated relative to a CodY deletion strain, representing genes that are mainly involved in amino acid transport and metabolism, inorganic ion transport and metabolism, transcription and translation, and virulence, all based on transcriptomic data; and (iv) CodY systematically regulated central metabolic flux to generate branched-chain amino acids (BCAAs) by mapping the CodY regulon onto a genome-scale metabolic model of S. aureus. Our study performed the first system-level analysis of CodY in two closely related USA300 TCH1516 and LAC strains, revealing new insights into the similarities and differences of CodY regulatory roles between the closely related strains. IMPORTANCE With the increasing availability of whole-genome sequences for many strains within the same pathogenic species, a comparative analysis of key regulators is needed to understand how the different strains uniquely coordinate metabolism and expression of virulence. To successfully infect the human host, Staphylococcus aureus USA300 relies on the transcription factor CodY to reorganize metabolism and express virulence factors. While CodY is a known key transcription factor, its target genes are not characterized on a genome-wide basis. We performed a comparative analysis to describe the transcriptional regulation of CodY between two dominant USA300 strains. This study motivates the characterization of common pathogenic strains and an evaluation of the possibility of developing specialized treatments for major strains circulating in the population.

Iron Memory in E. coli

The importance of memory in bacterial decision-making is relatively unexplored. We show here that a prior experience of swarming is remembered when E. coli encounters a new surface, improving its future swarming efficiency. We conducted >10,000 single-cell swarm assays to discover that cells store memory in the form of cellular iron levels. This memory pre-exists in planktonic cells, but the act of swarming reinforces it. A cell with low iron initiates swarming early and is a better swarmer, while the opposite is true for a cell with high iron. The swarming potential of a mother cell, whether low or high, is passed down to its fourth-generation daughter cells. This memory is naturally lost by the seventh generation, but artificially manipulating iron levels allows it to persist much longer. A mathematical model with a time-delay component faithfully recreates the observed dynamic interconversions between different swarming potentials. We also demonstrate that iron memory can integrate multiple stimuli, impacting other bacterial behaviors such as biofilm formation and antibiotic tolerance.

The hallmarks of a tradeoff in transcriptomes that balances stress and growth functions

Fit phenotypes are achieved through optimal transcriptomic allocation. Here, we performed a high-resolution, multi-scale study of the transcriptomic tradeoff between two key fitness phenotypes, stress response (fear) and growth (greed), in Escherichia coli. We introduced twelve RNA polymerase (RNAP) mutations commonly acquired during adaptive laboratory evolution (ALE) and found that single mutations resulted in large shifts in the fear vs. greed tradeoff, likely through destabilizing the rpoB-rpoC interface. RpoS and GAD regulons drive the fear response while ribosomal proteins and the ppGpp regulon underlie greed. Growth rate selection pressure during ALE results in endpoint strains that often have RNAP mutations, with synergistic mutations reflective of particular conditions. A phylogenetic analysis found the tradeoff in numerous bacteria species. The results suggest that the fear vs. greed tradeoff represents a general principle of transcriptome allocation in bacteria where small genetic changes can result in large phenotypic adaptations to growth conditions.

Integrating Enzyme Evolution and Metabolic Engineering to Improve the Productivity of Γ-Aminobutyric Acid by Whole-Cell Biosynthesis in Escherichia Coli

γ-Aminobutyric acid (GABA) is used widely in various fields, such as agriculture, food, pharmaceuticals, and biobased chemicals. Based on glutamate decarboxylase (GadBM4) derived from our previous work, three mutants, GadM4-2, GadM4-8, and GadM4-31, were obtained by integrating enzyme evolution and high-throughput screening methods. The GABA productivity obtained through whole-cell bioconversion using recombinant Escherichia coli cells harboring mutant GadBM4-2 was enhanced by 20.27% compared to that of the original GadBM4. Further introduction of the central regulator GadE of the acid resistance system and the enzymes from the deoxyxylulose-5-phosphate-independent pyridoxal 5'-phosphate biosynthesis pathway resulted in a 24.92% improvement in GABA productivity, reaching 76.70 g/L/h without any cofactor addition with a greater than 99% conversion ratio. Finally, when one-step bioconversion was applied for the whole-cell catalysis in a 5 L bioreactor, the titer of GABA reached 307.5 ± 5.94 g/L with a productivity of 61.49 g/L/h by using crude l-glutamic acid (l-Glu) as the substrate. Thus, the biocatalyst constructed above combined with the whole-cell bioconversion method represents an effective approach for industrial GABA production.

Deep-learning optimized DEOCSU suite provides an iterable pipeline for accurate ChIP-exo peak calling

Recognizing binding sites of DNA-binding proteins is a key factor for elucidating transcriptional regulation in organisms. ChIP-exo enables researchers to delineate genome-wide binding landscapes of DNA-binding proteins with near single base-pair resolution. However, the peak calling step hinders ChIP-exo application since the published algorithms tend to generate false-positive and false-negative predictions. Here, we report the development of DEOCSU (DEep-learning Optimized ChIP-exo peak calling SUite), a novel machine learning-based ChIP-exo peak calling suite. DEOCSU entails the deep convolutional neural network model which was trained with curated ChIP-exo peak data to distinguish the visualized data of bona fide peaks from false ones. Performance validation of the trained deep-learning model indicated its high accuracy, high precision and high recall of over 95%. Applying the new suite to both in-house and publicly available ChIP-exo datasets obtained from bacteria, eukaryotes and archaea revealed an accurate prediction of peaks containing canonical motifs, highlighting the versatility and efficiency of DEOCSU. Furthermore, DEOCSU can be executed on a cloud computing platform or the local environment. With visualization software included in the suite, adjustable options such as the threshold of peak probability, and iterable updating of the pre-trained model, DEOCSU can be optimized for users' specific needs.

Model-driven experimental design workflow expands understanding of regulatory role of Nac in Escherichia coli

The establishment of experimental conditions for transcriptional regulator network (TRN) reconstruction in bacteria continues to be impeded by the limited knowledge of activating conditions for transcription factors (TFs). Here, we present a novel genome-scale model-driven workflow for designing experimental conditions, which optimally activate specific TFs. Our model-driven workflow was applied to elucidate transcriptional regulation under nitrogen limitation by Nac and NtrC, in Escherichia coli. We comprehensively predict alternative nitrogen sources, including cytosine and cytidine, which trigger differential activation of Nac using a model-driven workflow. In accordance with the prediction, genome-wide measurements with ChIP-exo and RNA-seq were performed. Integrative data analysis reveals that the Nac and NtrC regulons consist of 97 and 43 genes under alternative nitrogen conditions, respectively. Functional analysis of Nac at the transcriptional level showed that Nac directly down-regulates amino acid biosynthesis and restores expression of tricarboxylic acid (TCA) cycle genes to alleviate nitrogen-limiting stress. We also demonstrate that both TFs coherently modulate α-ketoglutarate accumulation stress due to nitrogen limitation by co-activating amino acid and diamine degradation pathways. A systems-biology approach provided a detailed and quantitative understanding of both TF's roles and how nitrogen and carbon metabolic networks respond complementarily to nitrogen-limiting stress.

Improving acid resistance of Escherichia coli base on the CfaS-mediated membrane engineering strategy derived from extreme acidophile

Industrial microorganisms used for the production of organic acids often face challenges such as inhibited cell growth and reduced production efficiency due to the accumulation of acidic metabolites. One promising way for improving the acid resistance of microbial cells is to reconstruct their membranes. Herein, the overexpression of cfa2 from extreme acidophile endowed E. coli with high-performance on resistance to the acid stress. The engineered strain M1-93-Accfa2, constructed by CRISPR/Cas9-mediated chromosome integration, also exhibited a significantly higher resistance to severe acid stress. The analysis of fatty acid profiles indicated that the proportion of Cy-19:0 in the cell membrane of M1-93-Accfa2 increased by 5.26 times compared with the control, while the proportion of C18:1w9c decreased by 5.81 times. Correspondingly, the permeability and fluidity of the membrane decreased significantly. HPLC analysis demonstrated that the contents of intracellular glutamic acid, arginine, methionine and aspartic acid of M1-93-Accfa2 were 2.59, 2.04, 22.07 and 2.65 times that of the control after environmental acidification, respectively. Meanwhile, transmission electron microscopy observation indicated that M1-93-Accfa2 could maintain a plumper cell morphology after acid stimulation. M1-93-Accfa2 also exhibited higher-performance on the resistance to organic acids, especially succinic acid stress. These results together demonstrated the great potential of M1-93-Accfa2 constructed here in the production of organic acids.

Heterogeneity and Evolutionary Tunability of Escherichia coli Resistance against Extreme Acid Stress

Since acidic environments often serve as an important line of defense against bacterial pathogens, it is important to fully understand how the latter manage to mount and evolve acid resistance mechanisms. Escherichia coli, a species harboring many pathovars, is typically equipped with the acid fitness island (AFI), a genomic region encoding the GadE master regulator together with several GadE-controlled functions to counter acid stress. This study reveals that gadE and consequently AFI functions are heterogeneously expressed even in the absence of any prior acid stress, thereby preemptively creating acid-resistant subpopulations within a clonal E. coli population. Directed evolution efforts selecting for modulated gadE expression confirm that a gain-of-function mutation in the EvgS sensor kinase can constitutively upregulate gadE expression and concomitant acid resistance. However, we reveal that such upregulation of EvgS also causes cross-resistance to heat stress because of SafA-mediated cross-activation of the PhoPQ regulon. Surprisingly, loss of function of the serC gene (encoding phosphoserine/phosphohydroxythreonine aminotransferase) can also significantly upregulate gadE expression, acid resistance, and heat cross-resistance, although via a currently cryptic mechanism. As such, our data reveal a noisy expression of gadE in E. coli that is functional for the survival of sudden acid stress and that can readily be genetically tuned. IMPORTANCE Acidic environments constitute one of the most important stresses for enteric bacteria and can be encountered in both natural (e.g., host gastrointestinal tract) and manmade (e.g., food processing) environments. The enteric species Escherichia coli harbors many pathovars and is well known for its ability to cope with acid stress. In this study, we uncover that E. coli's acid fitness island (AFI), a genomic region that encodes important functions to deal with acid stress, is by default expressed in a heterogeneous manner. In fact, using microfluidics-based single-cell approaches, we further demonstrate that this heterogeneity preemptively creates a clonal subpopulation that is much better equipped to survive a sudden acid shock. In addition, we reveal that environments with recurring acid stress can readily select for mutants displaying a higher fraction of AFI-expressing cells. These new insights are important to properly understand and anticipate the survival characteristics of E. coli.

Comparison of enrichment methods for isolating Enterohemorrhagic Escherichia coli in kimchi

This study was conducted to compare the efficiency of four enrichment methods of Enterohemorrhagic Escherichia coli by using the 16S rRNA amplicon sequencing and a predictive model. Four different methods (US FDA, ISO, Japan Food Hygiene Association and Korea Ministry of Food and Drug Safety) were used to enrich EHEC in kimchi inoculated with cocktails of EHEC strains (NCCP 13720, NCCP 13721, and NCCP 14134). The maximum growth rate (μ_max) and lag phase duration (LPD) were compared using the Baranyi model, and 16S rRNA targeted sequencing was performed with samples at the end of the exponential phase. As a result, the μ_max and LPD values of Baranyi model developed for the four enriched media ranged from 0.82 to 0.92 and from 2.35 to 2.68, respectively, suggesting that the growth of EHEC was similar in all four enrichment media. As for the relative abundance of the bacterial composition at the family level, Enterobacteriaceae was identified as the major component (>50%) in all four enriched media. The relative abundance of Enterobacteriaceae was highest (>90%) in the two enriched media with 20 mg/L novobiocin, demonstrating that significant growth of non-targeted bacteria takes place in enrichment broths utilizing <20 mg/L novobiocin or different antibiotics. In conclusion, this study suggests that all four enrichment broth are suitable for growing EHEC in kimchi and the use and concentration of antibiotics such as novobiocin in enrichment media may have a critical role in species diversity.

Cooperative Interaction between Acid and Copper Resistance in Escherichia coli

The persistence of pathogenic Escherichia coli under acidic conditions poses a serious risk to food safety, especially in acidic foods such as kimchi. To identify the bacterial factors required for acid resistance, transcriptomic analysis was conducted on an acid-resistant enterotoxigenic E. coli strain and the genes with significant changes in their expression under acidic pH were selected as putative resistance factors against acid stress. These genes included those associated with a glutamatedependent acid resistance (GDAR) system and copper resistance. E. coli strains lacking GadA, GadB, or YbaST, the components of the GDAR system, exhibited significantly attenuated growth and survival under acidic stress conditions. Accordantly, the inhibition of the GDAR system by 3-mercaptopropionic acid and aminooxyacetic acid abolished bacterial adaptation and survival under acidic conditions, indicating the indispensable role of a GDAR system in acid resistance. Intriguingly, the lack of cueR encoding a transcriptional regulator for copper resistance genes markedly impaired bacterial resistance to acid stress as well as copper. Conversely, the absence of YbaST severely compromised bacterial resistance against copper, suggesting an interplay between acid and copper resistance. These results suggest that a GDAR system can be a promising target for developing control measures to prevent E. coli resistance to acid and copper treatments.

RegulonDB 11.0: Comprehensive high-throughput datasets on transcriptional regulation in Escherichia coli K-12

Genomics has set the basis for a variety of methodologies that produce high-throughput datasets identifying the different players that define gene regulation, particularly regulation of transcription initiation and operon organization. These datasets are available in public repositories, such as the Gene Expression Omnibus, or ArrayExpress. However, accessing and navigating such a wealth of data is not straightforward. No resource currently exists that offers all available high and low-throughput data on transcriptional regulation in Escherichia coli K-12 to easily use both as whole datasets, or as individual interactions and regulatory elements. RegulonDB (https://regulondb.ccg.unam.mx) began gathering high-throughput dataset collections in 2009, starting with transcription start sites, then adding ChIP-seq and gSELEX in 2012, with up to 99 different experimental high-throughput datasets available in 2019. In this paper we present a radical upgrade to more than 2000 high-throughput datasets, processed to facilitate their comparison, introducing up-to-date collections of transcription termination sites, transcription units, as well as transcription factor binding interactions derived from ChIP-seq, ChIP-exo, gSELEX and DAP-seq experiments, besides expression profiles derived from RNA-seq experiments. For ChIP-seq experiments we offer both the data as presented by the authors, as well as data uniformly processed in-house, enhancing their comparability, as well as the traceability of the methods and reproducibility of the results. Furthermore, we have expanded the tools available for browsing and visualization across and within datasets. We include comparisons against previously existing knowledge in RegulonDB from classic experiments, a nucleotide-resolution genome viewer, and an interface that enables users to browse datasets by querying their metadata. A particular effort was made to automatically extract detailed experimental growth conditions by implementing an assisted curation strategy applying Natural language processing and machine learning. We provide summaries with the total number of interactions found in each experiment, as well as tools to identify common results among different experiments. This is a long-awaited resource to make use of such wealth of knowledge and advance our understanding of the biology of the model bacterium E. coli K-12.

The Identity of the Constriction Region of the Ribosomal Exit Tunnel Is Important to Maintain Gene Expression in Escherichia coli

Mutational changes in bacterial ribosomes often affect gene expression and consequently cellular fitness. Understanding how mutant ribosomes disrupt global gene expression is critical to determining key genetic factors that affect bacterial survival. Here, we describe gene expression and phenotypic changes presented in Escherichia coli cells carrying an uL22(K90D) mutant ribosomal protein, which displayed alterations during growth. Ribosome profiling analyses revealed reduced expression of operons involved in catabolism, indole production, and lysine-dependent acid resistance. In general, translation initiation of proximal genes in several of these affected operons was substantially reduced. These reductions in expression were accompanied by increases in the expression of acid-induced membrane proteins and chaperones, the glutamate-decarboxylase regulon, and the autoinducer-2 metabolic regulon. In agreement with these changes, uL22(K90D) mutant cells had higher glutamate decarboxylase activity, survived better in extremely acidic conditions, and generated more biofilm in static cultures compared to their parental strain. Our work demonstrates that a single mutation in a non-conserved residue of a ribosomal protein affects a substantial number of genes to alter pH resistance and the formation of biofilms. IMPORTANCE All newly synthesized proteins must pass through a channel in the ribosome named the exit tunnel before emerging into the cytoplasm, membrane, and other compartments. The structural characteristics of the tunnel could govern protein folding and gene expression in a species-specific manner but how the identity of tunnel elements influences gene expression is less well-understood. Our global transcriptomics and translatome profiling demonstrate that a single substitution in a non-conserved amino acid of the E. coli tunnel protein uL22 has a profound impact on catabolism, cellular signaling, and acid resistance systems. Consequently, cells bearing the uL22 mutant ribosomes had an increased ability to survive acidic conditions and form biofilms. This work reveals a previously unrecognized link between tunnel identity and bacterial stress adaptation involving pH response and biofilm formation.

Synthetic acid stress-tolerance modules improve growth robustness and lysine productivity of industrial Escherichia coli in fermentation at low pH

Background

During fermentation, industrial microorganisms encounter multiple stresses that inhibit cell growth and decrease fermentation yields, in particular acid stress, which is due to the accumulation of acidic metabolites in the fermentation medium. Although the addition of a base to the medium can counteract the effect of acid accumulation, the engineering of acid-tolerant strains is considered a more intelligent and cost-effective solution. While synthetic biology theoretically provides a novel approach for devising such tolerance modules, in practice it is difficult to assemble stress-tolerance modules from hundreds of stress-related genes.

Results

In this study, we designed a set of synthetic acid-tolerance modules for fine-tuning the expression of multi-component gene blocks comprising a member of the proton-consuming acid resistance system (gadE), a periplasmic chaperone (hdeB), and reactive oxygen species (ROS) scavengers (sodB and katE). Directed evolution was used to construct an acid-responsive asr promoter library, from which four variants were selected and used in the synthetic modules. The module variants were screened in a stepwise manner under mild acidic conditions (pH 5–6), first by cell growth using the laboratory Escherichia coli strain MG1655 cultured in microplates, and then by lysine production performance using the industrial lysine-producing E. coli strain MG1655 SCEcL3 cultured first in multiple 10-mL micro-bioreactors, and then in 1.3-L parallel bioreactors. The procedure resulted in the identification of a best strain with lysine titer and yield at pH 6.0 comparable to the parent strain at pH 6.8.

Conclusion

Our results demonstrate a promising synthetic-biology strategy to enhance the growth robustness and productivity of E. coli upon the mildly acidic conditions, in both a general lab strain MG1655 and an industrial lysine-producing strain SCEcL3, by using the stress-responsive synthetic acid-tolerance modules comprising a limited number of genes. This study provides a reliable and efficient method for achieving synthetic modules of interest, particularly in improving the robustness and productivity of industrial strains.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-022-01795-4.

Dynamic gene expression and growth underlie cell-to-cell heterogeneity in Escherichia coli stress response

Individual bacteria that share identical genomes and growth environments can display substantial cell-to-cell differences in expression of stress-response genes and single-cell growth rates. This phenotypic heterogeneity can impact the survival of single cells facing sudden stress. However, the windows of time that cells spend in vulnerable or tolerant states are often unknown. We quantify the temporal expression of a suite of stress-response reporters, while simultaneously monitoring growth. We observe pulsatile expression across genes with a range of stress-response functions, finding that single-cell growth rates are often anticorrelated with reporter levels. These dynamic phenotypic differences have a concrete link to function, in which individual cells undergoing a pulse of elevated expression and slow growth are predisposed to survive antibiotic exposure.

Cell-to-cell heterogeneity in gene expression and growth can have critical functional consequences, such as determining whether individual bacteria survive or die following stress. Although phenotypic variability is well documented, the dynamics that underlie it are often unknown. This information is important because dramatically different outcomes can arise from gradual versus rapid changes in expression and growth. Using single-cell time-lapse microscopy, we measured the temporal expression of a suite of stress-response reporters in Escherichia coli, while simultaneously monitoring growth rate. In conditions without stress, we found several examples of pulsatile expression. Single-cell growth rates were often anticorrelated with reporter levels, with changes in growth preceding changes in expression. These dynamics have functional consequences, which we demonstrate by measuring survival after challenging cells with the antibiotic ciprofloxacin. Our results suggest that fluctuations in both gene expression and growth dynamics in stress-response networks have direct consequences on survival.

Regulation of Escherichia coli fim gene transcription by GadE and other acid tolerance gene products

Uropathogenic Escherichia coli (UPEC) cause millions of urinary tract infections each year in the United States. Type 1 pili are important for adherence of UPEC to uroepithelial cells in the human and murine urinary tracts where osmolality and pH vary. Previous work has shown that an acidic pH adversely affects the expression of type 1 pili. To determine if acid tolerance gene products may be regulating E. coli fim gene expression, a bank of K-12 strain acid tolerance gene mutants were screened using fimA-lux, fimB-lux, and fimE-lux fusions on single copy number plasmids. We have determined that a mutation in gadE increased transcription of all three fim genes, suggesting that GadE may be acting as a repressor in a low pH environment. Complementation of the gadE mutation restored fim gene transcription to wild-type levels. Moreover, mutations in gadX, gadW, crp, and cya also affected transcription of the three fim genes. To verify the role GadE plays in type 1 pilus expression, the NU149 gadE UPEC strain was tested. The gadE mutant had higher fimE gene transcript levels, a higher frequency of Phase-OFF positioning of fimS, and hemagglutination titres that were lower in strain NU149 gadE cultured in low pH medium as compared to the wild-type bacteria. The data demonstrate that UPEC fim genes are regulated directly or indirectly by the GadE protein and this could have some future bearing on the ability to prevent urinary tract infections by acidifying the urine and shutting off fim gene expression.

Biosensor-assisted evolution for high-level production of 4-hydroxyphenylacetic acid in Escherichia coli

4-Hydroxyphenylacetic acid (4HPAA) is an important building block for synthesizing drugs, agrochemicals, and biochemicals, and requires sustainable production to meet increasing demand. Here, we use a 4HPAA biosensor to overcome the difficulty of conventional library screening in identification of preferred mutants. Strains with higher 4HPAA production and tolerance are successfully obtained by atmospheric and room temperature plasma (ARTP) mutagenesis coupled with adaptive laboratory evolution using this biosensor. Genome shuffling integrates preferred properties in the strain GS-2-4, which produces 25.42 g/L 4HPAA. Chromosomal mutations of the strain GS-2-4 are identified by whole genome sequencing. Through comprehensive analysis and experimental validation, important genes, pathways and regulations are revealed. The best gene combination in inverse engineering, acrD-aroG, increases 4HPAA production of strain GS-2-4 by 37% further. These results emphasize precursor supply and stress resistance are keys to efficient 4HPAA biosynthesis. Our work shows the power of biosensor-assisted screening of mutants from libraries. The methods developed here can be easily adapted to construct cell factories for the production of other aromatic chemicals. Our work also provides many valuable target genes to build cell factories for efficient 4HPAA production in the future.

Gain of Spontaneous clpX Mutations Boosting Motility via Adaption to Environments in Escherichia coli

Motility is finely regulated and is crucial to bacterial processes including colonization and biofilm formation. There is a trade-off between motility and growth in bacteria with molecular mechanisms not fully understood. Hypermotile Escherichia coli could be isolated by evolving non-motile cells on soft agar plates. Most of the isolates carried mutations located upstream of the flhDC promoter region, which upregulate the transcriptional expression of the master regulator of the flagellum biosynthesis, FlhDC. Here, we identified that spontaneous mutations in clpX boosted the motility of E. coli largely, inducing several folds of changes in swimming speed. Among the mutations identified, we further elucidated the molecular mechanism underlying the ClpX^V78F mutation on the regulation of E. coli motility. We found that the V78F mutation affected ATP binding to ClpX, resulting in the inability of the mutated ClpXP protease to degrade FlhD as indicated by both structure modeling and in vitro protein degradation assays. Moreover, our proteomic data indicated that the ClpX^V78F mutation elevated the stability of known ClpXP targets to various degrees with FlhD as one of the most affected. In addition, the specific tag at the C-terminus of FlhD being recognized for ClpXP degradation was identified. Finally, our transcriptome data characterized that the enhanced expression of the motility genes in the ClpX^V78F mutations was intrinsically accompanied by the reduced expression of stress resistance genes relating to the reduced fitness of the hypermotile strains. A similar pattern was observed for previously isolated hypermotile E. coli strains showing high expression of flhDC at the transcriptional level. Hence, clpX appears to be a hot locus comparable to the upstream of the flhDC promoter region evolved to boost bacterial motility, and our finding provides insight into the reduced fitness of the hypermotile bacteria.

Molecular Analysis of Glutamate Decarboxylases in Enterococcus avium

Enterococcus avium (E. avium) is a common bacterium inhabiting the intestines of humans and other animals. Most strains of this species can produce gamma-aminobutyric acid (GABA) via the glutamate decarboxylase (GAD) system, but the presence and genetic organization of their GAD systems are poorly characterized. In this study, our bioinformatics analyses showed that the GAD system in E. avium strains was generally encoded by three gadB genes (gadB1, gadB2, and gadB3), together with an antiporter gene (gadC) and regulator gene (gadR), and these genes are organized in a cluster. This finding contrasts with that for other lactic acid bacteria. E. avium SDMCC050406, a GABA producer isolated from human feces, was employed to investigate the contribution of the three gadB genes to GABA biosynthesis. The results showed that the relative expression level of gadB3 was higher than those of gadB1 and gadB2 in the exponential growth and stationary phases, and this was accompanied by the synchronous transcription of gadC. After heterologous expression of the three gadB genes in Escherichia coli BL21 (DE3), the K_m value of the purified GAD3 was 4.26 ± 0.48 mM, a value lower than those of the purified GAD1 and GAD2. Moreover, gadB3 gene inactivation caused decreased GABA production, accompanied by a reduction in resistance to acid stress. These results indicated that gadB3 plays a crucial role in GABA biosynthesis and this property endowed the strain with acid tolerance. Our findings provided insights into how E. avium strains survive the acidic environments of fermented foods and throughout transit through the stomach and gut while maintaining cell viability.

Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Susceptibility

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.

Synthetic biosensor accelerates evolution by rewiring carbon metabolism toward a specific metabolite

Proper carbon flux distribution between cell growth and production of a target compound is important for biochemical production because improper flux reallocation inhibits cell growth, thus adversely affecting production yield. Here, using a synthetic biosensor to couple production of a specific metabolite with cell growth, we spontaneously evolve cells under the selective condition toward the acquisition of genotypes that optimally reallocate cellular resources. Using 3-hydroxypropionic acid (3-HP) production from glycerol in Escherichia coli as a model system, we determine that mutations in the conserved regions of proteins involved in global transcriptional regulation alter the expression of several genes associated with central carbon metabolism. These changes rewire central carbon flux toward the 3-HP production pathway, increasing 3-HP yield and reducing acetate accumulation by alleviating overflow metabolism. Our study provides a perspective on adaptive laboratory evolution (ALE) using synthetic biosensors, thereby supporting future efforts in metabolic pathway optimization.

Extreme Acid Modulates Fitness Trade-Offs of Multidrug Efflux Pumps MdtEF-TolC and AcrAB-TolC in Escherichia coli K-12

Bacterial genomes encode various multidrug efflux pumps (MDR) whose specific conditions for fitness advantage are unknown. We show that the efflux pump MdtEF-TolC, in Escherichia coli, confers a fitness advantage during exposure to extreme acid (pH 2). Our flow cytometry method revealed pH-dependent fitness trade-offs between bile acids (a major pump substrate) and salicylic acid, a membrane-permeant aromatic acid that induces a drug resistance regulon but depletes proton motive force (PMF). The PMF drives MdtEF-TolC and related pumps such as AcrAB-TolC. Deletion of mdtE (with loss of the pump MdtEF-TolC) increased the strain's relative fitness during growth with or without salicylate or bile acids. However, when the growth cycle included a 2-h incubation at pH 2 (below the pH growth range), MdtEF-TolC conferred a fitness advantage. The fitness advantage required bile salts but was decreased by the presence of salicylate, whose uptake is amplified by acid. For comparison, AcrAB-TolC, the primary efflux pump for bile acids, conferred a PMF-dependent fitness advantage with or without acid exposure in the growth cycle. A different MDR pump, EmrAB-TolC, conferred no selective benefit during growth in the presence of bile acids. Without bile acids, all three MDR pumps incurred a large fitness cost with salicylate when exposed at pH 2. These results are consistent with the increased uptake of salicylate at low pH. Overall, we showed that MdtEF-TolC is an MDR pump adapted for transient extreme-acid exposure and that low pH amplifies the salicylate-dependent fitness cost for drug pumps. IMPORTANCE Antibiotics and other drugs that reach the gut must pass through stomach acid. However, little is known of how extreme acid modulates the effect of drugs on gut bacteria. We find that extreme-acid exposure leads to a fitness advantage for a multidrug pump that otherwise incurs a fitness cost. At the same time, extreme acid amplifies the effect of salicylate selection against multidrug pumps. Thus, organic acids and stomach acid could play important roles in regulating multidrug resistance in the gut microbiome. Our flow cytometry assay provides a way to measure the fitness effects of extreme-acid exposure to various membrane-soluble organic acids, including plant-derived nutrients and pharmaceutical agents. Therapeutic acids might be devised to control the prevalence of multidrug pumps in environmental and host-associated habitats.

The quantitative metabolome is shaped by abiotic constraints

Living systems formed and evolved under constraints that govern their interactions with the inorganic world. These interactions are definable using basic physico-chemical principles. Here, we formulate a comprehensive set of ten governing abiotic constraints that define possible quantitative metabolomes. We apply these constraints to a metabolic network of Escherichia coli that represents 90% of its metabolome. We show that the quantitative metabolomes allowed by the abiotic constraints are consistent with metabolomic and isotope-labeling data. We find that: (i) abiotic constraints drive the evolution of high-affinity phosphate transporters; (ii) Charge-, hydrogen- and magnesium-related constraints underlie transcriptional regulatory responses to osmotic stress; and (iii) hydrogen-ion and charge imbalance underlie transcriptional regulatory responses to acid stress. Thus, quantifying the constraints that the inorganic world imposes on living systems provides insights into their key characteristics, helps understand the outcomes of evolutionary adaptation, and should be considered as a fundamental part of theoretical biology and for understanding the constraints on evolution.

Insights into Emergence of Antibiotic Resistance in Acid-Adapted Enterohaemorrhagic Escherichia coli

The emergence of multidrug-resistant pathogens presents a global challenge for treating and preventing disease spread through zoonotic transmission. The water and foodborne Enterohaemorrhagic Escherichia coli (EHEC) are capable of causing intestinal and systemic diseases. The root cause of the emergence of these strains is their metabolic adaptation to environmental stressors, especially acidic pH. Acid treatment is desired to kill pathogens, but the protective mechanisms employed by EHECs cross-protect against antimicrobial peptides and thus facilitate opportunities for survival and pathogenesis. In this review, we have discussed the correlation between acid tolerance and antibiotic resistance, highlighting the identification of novel targets for potential production of antimicrobial therapeutics. We have also summarized the molecular mechanisms used by acid-adapted EHECs, such as the two-component response systems mediating structural modifications, competitive inhibition, and efflux activation that facilitate cross-protection against antimicrobial compounds. Moving beyond the descriptive studies, this review highlights low pH stress as an emerging player in the development of cross-protection against antimicrobial agents. We have also described potential gene targets for innovative therapeutic approaches to overcome the risk of multidrug-resistant diseases in healthcare and industry.

Engineering of the Small Noncoding RNA (sRNA) DsrA Together with the sRNA Chaperone Hfq Enhances the Acid Tolerance of Escherichia coli

Acid tolerance of microorganisms is a desirable phenotype for many industrial fermentation applications. In Escherichia coli, the stress response sigma factor RpoS is a promising target for engineering acid-tolerant phenotypes. However, the simple overexpression of RpoS alone is insufficient to confer these phenotypes. In this study, we show that the simultaneous overexpression of the noncoding small RNA (sRNA) DsrA and the sRNA chaperone Hfq, which act as RpoS activators, significantly increased acid tolerance in terms of cell growth under modest acidic pH, as well as cell survival upon extreme acid shock. Directed evolution of the DsrA-Hfq module further improved the acid tolerance, with the best mutants showing a 51 to 72% increase in growth performance at pH 4.5 compared with the starting strain, MG1655. Further analyses found that the improved acid tolerance of these DsrA-Hfq strains coincided with activation of genes associated with proton-consuming acid resistance system 2 (AR2), protein chaperone HdeB, and reactive oxygen species (ROS) removal in the exponential phase. This study illustrated that the fine-tuning of sRNAs and their chaperones can be a novel strategy for improving the acid tolerance of E. coli IMPORTANCE Many of the traditional studies on bacterial acid tolerance generally focused on improving cell survival under extreme-pH conditions, but cell growth under less harsh acidic conditions is more relevant to industrial applications. Under normal conditions, the general stress response sigma factor RpoS is maintained at low levels in the growth phase through a number of mechanisms. This study showed that RpoS can be activated prior to the stationary phase via engineering its activators, the sRNA DsrA and the sRNA chaperone Hfq, resulting in significantly improved cell growth at modest acidic pH. This work suggests that the sigma factors and likely other transcription factors can be retuned or retimed by manipulating the respective regulatory sRNAs along with the sufficient supply of the respective sRNA chaperones (i.e., Hfq). This provides a novel avenue for strain engineering of microbes.

Recent advances in constraint and machine learning-based metabolic modeling by leveraging stoichiometric balances, thermodynamic feasibility and kinetic law formalisms

Understanding the governing principles behind organisms' metabolism and growth underpins their effective deployment as bioproduction chassis. A central objective of metabolic modeling is predicting how metabolism and growth are affected by both external environmental factors and internal genotypic perturbations. The fundamental concepts of reaction stoichiometry, thermodynamics, and mass action kinetics have emerged as the foundational principles of many modeling frameworks designed to describe how and why organisms allocate resources towards both growth and bioproduction. This review focuses on the latest algorithmic advancements that have integrated these foundational principles into increasingly sophisticated quantitative frameworks.

Transcriptome changes and polymyxin resistance of acid-adapted Escherichia coli O157:H7 ATCC 43889

Background

Acid treatment is commonly used for controlling or killing pathogenic microorganisms on medical devices and environments; however, inadequate acid treatment may cause acid tolerance response (ATR) and offer cross-protection against environmental stresses, including antimicrobials. This study aimed to characterise an Escherichia coli strain that can survive in the acidic gastrointestinal environment.

Results

We developed an acid-tolerant E. coli O157:H7 ATCC 43889 (ATCC 43889) strain that can survive at pH 2.75 via cell adaptation in low pH conditions. We also performed RNA sequencing and qRT-PCR to compare differentially expressed transcripts between acid-adapted and non-adapted cells. Genes related to stress resistance, including kdpA and bshA were upregulated in the acid-adapted ATCC 43889 strain. Furthermore, the polymyxin resistance gene arnA was upregulated in the acid-adapted cells, and resistance against polymyxin B and colistin (polymyxin E) was observed. As polymyxins are important antibiotics, effective against multidrug-resistant gram-negative bacterial infections, the emergence of polymyxin resistance in acid-adapted E. coli is a serious public health concern.

Conclusion

The transcriptomic and phenotypic changes analysed in this study during the adaptation of E. coli to acid environments can provide useful information for developing intervention technologies and mitigating the risk associated with the emergence and spread of antimicrobial resistance.

Systems evaluation reveals novel transporter YohJK renders 3-hydroxypropionate tolerance in Escherichia coli

Previously, we have reported that 3-hydroxypropionate (3-HP) tolerance in Escherichia coli W is improved by deletion of yieP, a less-studied transcription factor. Here, through systems analyses along with physiological and functional studies, we suggest that the yieP deletion improves 3-HP tolerance by upregulation of yohJK, encoding putative 3-HP transporter(s). The tolerance improvement by yieP deletion was highly specific to 3-HP, among various C2-C4 organic acids. Mapping of YieP binding sites (ChIP-exo) coupled with transcriptomic profiling (RNA-seq) advocated seven potential genes/operons for further functional analysis. Among them, the yohJK operon, encoding for novel transmembrane proteins, was the most responsible for the improved 3-HP tolerance; deletion of yohJK reduced 3-HP tolerance regardless of yieP deletion, and their subsequent complementation fully restored the tolerance in both the wild-type and yieP deletion mutant. When determined by 3-HP-responsive biosensor, a drastic reduction of intracellular 3-HP was observed upon yieP deletion or yohJK overexpression, suggesting that yohJK encodes for novel 3-HP exporter(s).

Escherichia Coli Increases its ATP Concentration in Weakly Acidic Environments Principally through the Glycolytic Pathway

Acid resistance is an intrinsic characteristic of intestinal bacteria in order to survive passage through the stomach. Adenosine triphosphate (ATP), the ubiquitous chemical used to power metabolic reactions, activate signaling cascades, and form precursors of nucleic acids, was also found to be associated with the survival of Escherichia coli (E. coli) in acidic environments. The metabolic pathway responsible for elevating the level of ATP inside these bacteria during acid adaptation has been unclear. E. coli uses several mechanisms of ATP production, including oxidative phosphorylation, glycolysis and the oxidation of organic compounds. To uncover which is primarily used during adaptation to acidic conditions, we broadly analyzed the levels of gene transcription of multiple E. coli metabolic pathway components. Our findings confirmed that the primary producers of ATP in E. coli undergoing mild acidic stress are the glycolytic enzymes Glk, PykF and Pgk, which are also essential for survival under markedly acidic conditions. By contrast, the transcription of genes related to oxidative phosphorylation was downregulated, despite it being the major producer of ATP in neutral pH environments.

SdiA Improves the Acid Tolerance of E. coli by Regulating GadW and GadY Expression

The acid tolerance mechanism is important for Escherichia coli to resist acidic conditions encountered in mammalian host digestive tract environment. Here, we explored how the LuxR protein SdiA influenced E. coli acid tolerance ability in the context of the glutamate- and glutamine-dependent acid resistance system (AR2). First, using a growth and acid shock assay under different acid stresses, we demonstrated that the deletion of sdiA in SM10λpir or BW25113 led to impaired growth under the acidic environment of pH 3–6, which was restored by complementary expression of SdiA. Next, transcriptome sequencing and qPCR disclosed that the expression of glutamate decarboxylase W (GadW) and GadY, the key members of the AR2 system, were regulated by SdiA. Further, β-galactosidase reporter assays showed that the promoter activity of gadW and gadY was positively regulated by SdiA. Moreover, qPCR and β-galactosidase reporter assays confirmed that the regulation of SdiA on GadW, but not GadY, could be enhanced by quorum sensing (QS) signal molecules AHLs. Collectively, these data suggest that SdiA plays a crucial role in acid tolerance regulation of E. coli. Our findings provide new insights into the important contribution of quorum sensing system AHLs–SdiA to the networks that regulate acid tolerance.