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

Building Structural Models of a Whole Mycoplasma Cell

Building structural models of entire cells has been a long-standing cross-discipline challenge for the research community, as it requires an unprecedented level of integration between multiple sources of biological data and enhanced methods for computational modeling and visualization. Here, we present the first 3D structural models of an entire Mycoplasma genitalium (MG) cell, built using the CellPACK suite of computational modeling tools. Our model recapitulates the data described in recent whole-cell system biology simulations and provides a structural representation for all MG proteins, DNA and RNA molecules, obtained by combining experimental and homology-modeled structures and lattice-based models of the genome. We establish a framework for gathering, curating and evaluating these structures, exposing current weaknesses of modeling methods and the boundaries of MG structural knowledge, and visualization methods to explore functional characteristics of the genome and proteome. We compare two approaches for data gathering, a manually-curated workflow and an automated workflow that uses homologous structures, both of which are appropriate for the analysis of mesoscale properties such as crowding and volume occupancy. Analysis of model quality provides estimates of the regularization that will be required when these models are used as starting points for atomic molecular dynamics simulations.

Disentangling direct from indirect relationships in association networks

Networks are vital tools for understanding and modeling interactions in complex systems in science and engineering, and direct and indirect interactions are pervasive in all types of networks. However, quantitatively disentangling direct and indirect relationships in networks remains a formidable task. Here, we present a framework, called iDIRECT (Inference of Direct and Indirect Relationships with Effective Copula-based Transitivity), for quantitatively inferring direct dependencies in association networks. Using copula-based transitivity, iDIRECT eliminates/ameliorates several challenging mathematical problems, including ill-conditioning, self-looping, and interaction strength overflow. With simulation data as benchmark examples, iDIRECT showed high prediction accuracies. Application of iDIRECT to reconstruct gene regulatory networks in Escherichia coli also revealed considerably higher prediction power than the best-performing approaches in the DREAM5 (Dialogue on Reverse Engineering Assessment and Methods project, #5) Network Inference Challenge. In addition, applying iDIRECT to highly diverse grassland soil microbial communities in response to climate warming showed that the iDIRECT-processed networks were significantly different from the original networks, with considerably fewer nodes, links, and connectivity, but higher relative modularity. Further analysis revealed that the iDIRECT-processed network was more complex under warming than the control and more robust to both random and target species removal (P < 0.001). As a general approach, iDIRECT has great advantages for network inference, and it should be widely applicable to infer direct relationships in association networks across diverse disciplines in science and engineering.

proChIPdb: a chromatin immunoprecipitation database for prokaryotic organisms

The transcriptional regulatory network in prokaryotes controls global gene expression mostly through transcription factors (TFs), which are DNA-binding proteins. Chromatin immunoprecipitation (ChIP) with DNA sequencing methods can identify TF binding sites across the genome, providing a bottom-up, mechanistic understanding of how gene expression is regulated. ChIP provides indispensable evidence toward the goal of acquiring a comprehensive understanding of cellular adaptation and regulation, including condition-specificity. ChIP-derived data's importance and labor-intensiveness motivate its broad dissemination and reuse, which is currently an unmet need in the prokaryotic domain. To fill this gap, we present proChIPdb (prochipdb.org), an information-rich, interactive web database. This website collects public ChIP-seq/-exo data across several prokaryotes and presents them in dashboards that include curated binding sites, nucleotide-resolution genome viewers, and summary plots such as motif enrichment sequence logos. Users can search for TFs of interest or their target genes, download all data, dashboards, and visuals, and follow external links to understand regulons through biological databases and the literature. This initial release of proChIPdb covers diverse organisms, including most major TFs of Escherichia coli, and can be expanded to support regulon discovery across the prokaryotic domain.

Assessing the impact of substrate-level enzyme regulations limiting ethanol titer in Clostridium thermocellum using a core kinetic model

Clostridium thermocellum is a promising candidate for consolidated bioprocessing because it can directly ferment cellulose to ethanol. Despite significant efforts, achieved yields and titers fall below industrially relevant targets. This implies that there still exist unknown enzymatic, regulatory, and/or possibly thermodynamic bottlenecks that can throttle back metabolic flow. By (i) elucidating internal metabolic fluxes in wild-type C. thermocellum grown on cellobiose via ¹³C-metabolic flux analysis (¹³C-MFA), (ii) parameterizing a core kinetic model, and (iii) subsequently deploying an ensemble-docking workflow for discovering substrate-level regulations, this paper aims to reveal some of these factors and expand our knowledgebase governing C. thermocellum metabolism. Generated ¹³C labeling data were used with ¹³C-MFA to generate a wild-type flux distribution for the metabolic network. Notably, flux elucidation through MFA alluded to serine generation via the mercaptopyruvate pathway. Using the elucidated flux distributions in conjunction with batch fermentation process yield data for various mutant strains, we constructed a kinetic model of C. thermocellum core metabolism (i.e. k-ctherm138). Subsequently, we used the parameterized kinetic model to explore the effect of removing substrate-level regulations on ethanol yield and titer. Upon exploring all possible simultaneous (up to four) regulation removals we identified combinations that lead to many-fold model predicted improvement in ethanol titer. In addition, by coupling a systematic method for identifying putative competitive inhibitory mechanisms using K-FIT kinetic parameterization with the ensemble-docking workflow, we flagged 67 putative substrate-level inhibition mechanisms across central carbon metabolism supported by both kinetic formalism and docking analysis.

Mining RNA-seq data reveals the massive regulon of GcvB small RNA and its physiological significance in maintaining amino acid homeostasis in Escherichia coli

Bacterial small RNAs regulate the expression of multiple genes through imperfect base-pairing with target mRNAs mediated by RNA chaperone proteins such as Hfq. GcvB is the master sRNA regulator of amino acid metabolism and transport in a wide range of Gram-negative bacteria. Recently, independent RNA-seq approaches identified a plethora of transcripts interacting with GcvB in Escherichia coli. In this study, the compilation of RIL-seq, CLASH, and MAPS data sets allowed us to identify GcvB targets with high accuracy. We validated 21 new GcvB targets repressed at the posttranscriptional level, raising the number of direct targets to >50 genes in E. coli. Among its multiple seed sequences, GcvB utilizes either R1 or R3 to regulate most of these targets. Furthermore, we demonstrated that both R1 and R3 seed sequences are required to fully repress the expression of gdhA, cstA, and sucC genes. In contrast, the ilvLXGMEDA polycistronic mRNA is targeted by GcvB through at least four individual binding sites in the mRNA. Finally, we revealed that GcvB is involved in the susceptibility of peptidase-deficient E. coli strain (Δpeps) to Ala-Gln dipeptide by regulating both Dpp dipeptide importer and YdeE dipeptide exporter via R1 and R3 seed sequences, respectively.

Inactivation of RNase P in Escherichia coli significantly changes post-transcriptional RNA metabolism

Ribonuclease P (RNase P), which is required for the 5'-end maturation of tRNAs in every organism, has been shown to play a limited role in other aspects of RNA metabolism in Escherichia coli. Using RNA-sequencing (RNA-seq), we demonstrate that RNase P inactivation affects the abundances of ~46% of the expressed transcripts in E. coli and provide evidence that its essential function is its ability to generate pre-tRNAs from polycistronic tRNA transcripts. The RNA-seq results agreed with the published data and northern blot analyses of 75/83 transcripts (mRNAs, sRNAs, and tRNAs). Changes in transcript abundances in the RNase P mutant also correlated with changes in their half-lives. Inactivating the stringent response did not alter the rnpA49 phenotype. Most notably, increases in the transcript abundances were observed for all genes in the cysteine regulons, multiple toxin-antitoxin modules, and sigma S-controlled genes. Surprisingly, poly(A) polymerase (PAP I) modulated the abundances of ~10% of the transcripts affected by RNase P. A comparison of the transcriptomes of RNase P, RNase E, and RNase III mutants suggests that they affect distinct substrates. Together, our work strongly indicates that RNase P is a major player in all aspects of post-transcriptional RNA metabolism in E. coli.

Modeling Approaches to Microbial Metabolism

Microbial systems are frequently used in biotechnology to convert substrates into valuable products. To make this efficient, knowledge on the specific metabolic characteristics of a system is required as well as a theoretical description that allows researchers to design the system for a profitable use in an industrial application. In this chapter, basics on mathematical modelling approaches are introduced and examples are provided.

Escherichia coli SymE is a DNA-binding protein that can condense the nucleoid

Type I toxin-antitoxin (TA) systems typically consist of a protein toxin that imbeds in the inner membrane where it can oligomerize and form pores that change membrane permeability, and an RNA antitoxin that interacts directly with toxin mRNA to inhibit its translation. In Escherichia coli, symE/symR is annotated as a type I TA system with a non-canonical toxin. SymE was initially suggested to be an endoribonuclease, but has predicted structural similarity to DNA binding proteins. To better understand SymE function, we used RNA-seq to examine cells ectopically producing it. Although SymE drives major changes in gene expression, we do not find strong evidence of endoribonucleolytic activity. Instead, our biochemical and cell biological studies indicate that SymE binds DNA. We demonstrate that the toxicity of symE overexpression likely stems from its ability to drive severe nucleoid condensation, which disrupts DNA and RNA synthesis and leads to DNA damage, similar to the effects of overproducing the nucleoid-associated protein H-NS. Collectively, our results suggest that SymE represents a new class of nucleoid-associated proteins that is widely distributed in bacteria.

Loss of YhcB results in dysregulation of coordinated peptidoglycan, LPS and phospholipid synthesis during Escherichia coli cell growth

The cell envelope is essential for viability in all domains of life. It retains enzymes and substrates within a confined space while providing a protective barrier to the external environment. Destabilising the envelope of bacterial pathogens is a common strategy employed by antimicrobial treatment. However, even in one of the best studied organisms, Escherichia coli, there remain gaps in our understanding of how the synthesis of the successive layers of the cell envelope are coordinated during growth and cell division. Here, we used a whole-genome phenotypic screen to identify mutants with a defective cell envelope. We report that loss of yhcB, a conserved gene of unknown function, results in loss of envelope stability, increased cell permeability and dysregulated control of cell size. Using whole genome transposon mutagenesis strategies, we report the comprehensive genetic interaction network of yhcB, revealing all genes with a synthetic negative and a synthetic positive relationship. These genes include those previously reported to have a role in cell envelope biogenesis. Surprisingly, we identified genes previously annotated as essential that became non-essential in a ΔyhcB background. Subsequent analyses suggest that YhcB functions at the junction of several envelope biosynthetic pathways coordinating the spatiotemporal growth of the cell, highlighting YhcB as an as yet unexplored antimicrobial target.

All life depends on a cell envelope to enclose the chemical reactions that make life possible. But how do cell envelopes grow? How each component of the cell envelope is incorporated into the envelope at the correct amount, in the correct place, and at the correct time, to prevent cell death, has been a long-standing question in bacteriology. Using a unique combination of high throughput chemical genetic screens we identified yhcB, a conserved gene of unknown function, required for the maintenance of cell envelope integrity in Escherichia coli. Loss of YhcB results in aberrant cell size driven by the production of excess membrane phospholipids. Subsequent molecular and biochemical analyses suggest YhcB influences the spatiotemporal biogenesis of LPS, peptidoglycan and membrane phospholipids. Our data indicate YhcB is a key regulator of cell envelope growth in Gram-negative bacteria playing a crucial role in coordinating cell width, elongation, and division to maintain cell envelope integrity.

ElyC and Cyclic Enterobacterial Common Antigen Regulate Synthesis of Phosphoglyceride-Linked Enterobacterial Common Antigen

The Gram-negative cell envelope is a complex structure delineating the cell from its environment. Recently, we found that enterobacterial common antigen (ECA) plays a role maintaining the outer membrane (OM) permeability barrier, which excludes toxic molecules including many antibiotics. ECA is a conserved carbohydrate found throughout Enterobacterales (e.g., Salmonella, Klebsiella, and Yersinia). There are two OM forms of ECA (phosphoglyceride-linked ECA_PG and lipopolysaccharide-linked ECA_LPS) and one periplasmic form of ECA (cyclic ECA_CYC). ECA_PG, found in the outer leaflet of the OM, consists of a linear ECA oligomer attached to phosphoglyceride through a phosphodiester linkage. The process through which ECA_PG is produced from polymerized ECA is unknown. Therefore, we set out to identify genes interacting genetically with ECA_PG biosynthesis in Escherichia coli K-12 using the competition between ECA and peptidoglycan biosynthesis. Through transposon-directed insertion sequencing, we identified an interaction between elyC and ECA_PG biosynthesis. ElyC is an inner membrane protein previously shown to alter peptidoglycan biosynthesis rates. We found ΔelyC was lethal specifically in strains producing ECA_PG without other ECA forms, suggesting ECA_PG biosynthesis impairment or dysregulation. Further characterization suggested ElyC inhibits ECA_PG synthesis in a posttranscriptional manner. Moreover, the full impact of ElyC on ECA levels requires the presence of ECA_CYC. Our data demonstrate ECA_CYC can regulate ECA_PG synthesis in strains wild type for elyC. Overall, our data demonstrate ElyC and ECA_CYC act in a novel pathway that regulates the production of ECA_PG, supporting a model in which ElyC provides feedback regulation of ECA_PG production based on the periplasmic levels of ECA_CYC.

RNase III, Ribosome Biogenesis and Beyond

The ribosome is the universal catalyst for protein synthesis. Despite extensive studies, the diversity of structures and functions of this ribonucleoprotein is yet to be fully understood. Deciphering the biogenesis of the ribosome in a step-by-step manner revealed that this complexity is achieved through a plethora of effectors involved in the maturation and assembly of ribosomal RNAs and proteins. Conserved from bacteria to eukaryotes, double-stranded specific RNase III enzymes play a large role in the regulation of gene expression and the processing of ribosomal RNAs. In this review, we describe the canonical role of RNase III in the biogenesis of the ribosome comparing conserved and unique features from bacteria to eukaryotes. Furthermore, we report additional roles in ribosome biogenesis re-enforcing the importance of RNase III.

Escherichia coli Data-Driven Strain Design Using Aggregated Adaptive Laboratory Evolution Mutational Data

Microbes are being engineered for an increasingly large and diverse set of applications. However, the designing of microbial genomes remains challenging due to the general complexity of biological systems. Adaptive Laboratory Evolution (ALE) leverages nature’s problem-solving processes to generate optimized genotypes currently inaccessible to rational methods. The large amount of public ALE data now represents a new opportunity for data-driven strain design. This study describes how novel strain designs, or genome sequences not yet observed in ALE experiments or published designs, can be extracted from aggregated ALE data and demonstrates this by designing, building, and testing three novel Escherichia coli strains with fitnesses comparable to ALE mutants. These designs were achieved through a meta-analysis of aggregated ALE mutations data (63 Escherichia coli K-12 MG1655 based ALE experiments, described by 93 unique environmental conditions, 357 independent evolutions, and 13 957 observed mutations), which additionally revealed global ALE mutation trends that inform on ALE-derived strain design principles. Such informative trends anticipate ALE-derived strain designs as largely gene-centric, as opposed to noncoding, and composed of a relatively small number of beneficial variants (approximately 6). These results demonstrate how strain design efforts can be enhanced by the meta-analysis of aggregated ALE data.

The economy of chromosomal distances in bacterial gene regulation

In the transcriptional regulatory network (TRN) of a bacterium, the nodes are genes and a directed edge represents the action of a transcription factor (TF), encoded by the source gene, on the target gene. It is a condensed representation of a large number of biological observations and facts. Nonrandom features of the network are structural evidence of requirements for a reliable systemic function. For the bacterium Escherichia coli we here investigate the (Euclidean) distances covered by the edges in the TRN when its nodes are embedded in the real space of the circular chromosome. Our work is motivated by 'wiring economy' research in Computational Neuroscience and starts from two contradictory hypotheses: (1) TFs are predominantly employed for long-distance regulation, while local regulation is exerted by chromosomal structure, locally coordinated by the action of structural proteins. Hence long distances should often occur. (2) A large distance between the regulator gene and its target requires a higher expression level of the regulator gene due to longer reaching times and ensuing increased degradation (proteolysis) of the TF and hence will be evolutionarily reduced. Our analysis supports the latter hypothesis.

The finding and researching algorithm for potentially oscillating enzymatic systems

Many processes in living organisms are subject to periodic oscillations at different hierarchical levels of their organization: from molecular-genetic to population and ecological. Oscillatory processes are responsible for cell cycles in both prokaryotes and eukaryotes, for circadian rhythms, for synchronous coupling of respiration with cardiac contractions, etc. Fluctuations in the numbers of organisms in natural populations can be caused by the populations' own properties, their age structure, and ecological relationships with other species. Along with experimental approaches, mathematical and computer modeling is widely used to study oscillating biological systems. This paper presents classical mathematical models that describe oscillatory behavior in biological systems. Methods for the search for oscillatory molecular-genetic systems are presented by the example of their special case - oscillatory enzymatic systems. Factors influencing the cyclic dynamics in living systems, typical not only of the molecular-genetic level, but of higher levels of organization as well, are considered. Application of different ways to describe gene networks for modeling oscillatory molecular-genetic systems is considered, where the most important factor for the emergence of cyclic behavior is the presence of feedback. Techniques for finding potentially oscillatory enzymatic systems are presented. Using the method described in the article, we present and analyze, in a step-by-step manner, first the structural models (graphs) of gene networks and then the reconstruction of the mathematical models and computational experiments with them. Structural models are ideally suited for the tasks of an automatic search for potential oscillating contours (linked subgraphs), whose structure can correspond to the mathematical model of the molecular-genetic system that demonstrates oscillatory behavior in dynamics. At the same time, it is the numerical study of mathematical models for the selected contours that makes it possible to confirm the presence of stable limit cycles in them. As an example of application of the technology, a network of 300 metabolic reactions of the bacterium Escherichia coli was analyzed using mathematical and computer modeling tools. In particular, oscillatory behavior was shown for a loop whose reactions are part of the tryptophan biosynthesis pathway.

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.

Spontaneous Phage Resistance in Avian Pathogenic Escherichia coli

Avian pathogenic Escherichia coli (APEC) is one of the most important bacterial pathogens affecting poultry worldwide. The emergence of multidrug-resistant pathogens has renewed the interest in the therapeutic use of bacteriophages (phages). However, a major concern for the successful implementation of phage therapy is the emergence of phage-resistant mutants. The understanding of the phage-host interactions, as well as underlying mechanisms of resistance, have shown to be essential for the development of a successful phage therapy. Here, we demonstrate that the strictly lytic Escherichia phage vB_EcoM-P10 rapidly selected for resistance in the APEC ST95 O1 strain AM621. Whole-genome sequence analysis of 109 spontaneous phage-resistant mutant strains revealed 41 mutants with single-nucleotide polymorphisms (SNPs) in their core genome. In 32 of these, a single SNP was detected while two SNPs were identified in a total of nine strains. In total, 34 unique SNPs were detected. In 42 strains, including 18 strains with SNP(s), gene losses spanning 17 different genes were detected. Affected by genetic changes were genes known to be involved in phage resistance (outer membrane protein A, lipopolysaccharide-, O- antigen-, or cell wall-related genes) as well as genes not previously linked to phage resistance, including two hypothetical genes. In several strains, we did not detect any genetic changes. Infecting phages were not able to overcome the phage resistance in host strains. However, interestingly the initial infection was shown to have a great fitness cost for several mutant strains, with up to ∼65% decrease in overall growth. In conclusion, this study provides valuable insights into the phage-host interaction and phage resistance in APEC. Although acquired resistance to phages is frequently observed in pathogenic E. coli, it may be associated with loss of fitness, which could be exploited in phage therapy.

Chemical biology-whole genome engineering datasets predict new antibacterial combinations

Trimethoprim and sulfamethoxazole are used commonly together as cotrimoxazole for the treatment of urinary tract and other infections. The evolution of resistance to these and other antibacterials threatens therapeutic options for clinicians. We generated and analysed a chemical-biology-whole-genome data set to predict new targets for antibacterial combinations with trimethoprim and sulfamethoxazole. For this we used a large transposon mutant library in Escherichia coli BW25113 where an outward-transcribing inducible promoter was engineered into one end of the transposon. This approach allows regulated expression of adjacent genes in addition to gene inactivation at transposon insertion sites, a methodology that has been called TraDIS-Xpress. These chemical genomic data sets identified mechanisms for both reduced and increased susceptibility to trimethoprim and sulfamethoxazole. The data identified that over-expression of FolA reduced trimethoprim susceptibility, a known mechanism for reduced susceptibility. In addition, transposon insertions into the genes tdk, deoR, ybbC, hha, ldcA, wbbK and waaS increased susceptibility to trimethoprim and likewise for rsmH, fadR, ddlB, nlpI and prc with sulfamethoxazole, while insertions in ispD, uspC, minC, minD, yebK, truD and umpG increased susceptibility to both these antibiotics. Two of these genes’ products, Tdk and IspD, are inhibited by AZT and fosmidomycin respectively, antibiotics that are known to synergise with trimethoprim. Thus, the data identified two known targets and several new target candidates for the development of co-drugs that synergise with trimethoprim, sulfamethoxazole or cotrimoxazole. We demonstrate that the TraDIS-Xpress technology can be used to generate information-rich chemical-genomic data sets that can be used for antibacterial development.

The vulnerable versatility of Salmonella antibiotic persisters during infection

Tolerance and persistence are superficially similar phenomena by which bacteria survive bactericidal antibiotics. It is assumed that the same physiology underlies survival of individual tolerant and persistent bacteria. However, by comparing tolerance and persistence during Salmonella Typhimurium infection, we reveal that these two phenomena are underpinned by different bacterial physiologies. Multidrug-tolerant mutant Salmonella enter a near-dormant state protected from immune-mediated genotoxic damages. However, the numerous tolerant cells, optimized for survival, lack the capabilities necessary to initiate infection relapse following antibiotic withdrawal. In contrast, persisters retain an active state. This leaves them vulnerable to accumulation of macrophage-induced dsDNA breaks but concurrently confers the versatility to initiate infection relapse if protected by RecA-mediated DNA repair. Accordingly, recurrent, invasive, non-typhoidal Salmonella clinical isolates display hallmarks of persistence rather than tolerance during antibiotic treatment. Our study highlights the complex trade-off that antibiotic-recalcitrant Salmonella balance to act as a reservoir for infection relapse.

Using a chemical genetic screen to enhance our understanding of the antimicrobial properties of copper

The competitive toxic and stress inducing nature of copper necessitates systems that sequester and export this metal from the cytoplasm of bacterial cells. Several predicted mechanisms of toxicity include the production of reactive oxygen species, thiol depletion, DNA and iron-sulfur cluster disruption. Accompanying these mechanisms include pathways of homeostasis such as chelation, oxidation, and transport. Still, the mechanisms of copper resistance and sensitivity are not fully understood. Furthermore, studies fail to recognize that the response to copper is likely a result of numerous mechanisms, as in the case for homeostasis, in which proteins and enzymes work as a collective to maintain appropriate copper concentrations. In this study we used the Keio collection, an array of 3985 Escherichia coli mutants, each with a deleted non-essential gene, to gain a better understanding of prolonged copper exposure. In short, we recovered two copper homeostatic gene and genes involved in transporting and assembling to be involved in mediating prolonged copper stress under the conditions assessed. The gene coding for the protein TolC was uncovered as a sensitive hit and we demonstrated that tolC, an outer membrane efflux channel, is key in mitigating copper sensitivity. Additionally, the activity of tRNA processing was enriched and the deletion of several proteins involved in import generated copper tolerance. Lastly, key genes belonging to central carbon metabolism and nicotinamide adenine dinucleotide biosynthesis were uncovered as tolerant hits. Overall, this study shows that copper sensitivity and tolerance are a result of numerous mechanisms acting in combination within the cell.

Multiple novel traits without immediate benefits originate in bacteria evolving on single antibiotics

How new traits originate in evolution is a fundamental question of evolutionary biology. When such traits arise, they can either be immediately beneficial in their environment of origin, or they may become beneficial only in a future environment. Compared to immediately beneficial novel traits, novel traits without immediate benefits remain poorly studied. Here we use experimental evolution to study novel traits that are not immediately beneficial but that allow bacteria to survive in new environments. Specifically, we evolved multiple E. coli populations in five antibiotics with different mechanisms of action, and then determined their ability to grow in more than 200 environments that are different from the environment in which they evolved. Our populations evolved viability in multiple environments that contain not just clinically relevant antibiotics, but a broad range of antimicrobial molecules, such as surfactants, organic and inorganic salts, nucleotide analogues and pyridine derivatives. Genome sequencing of multiple evolved clones shows that pleiotropic mutations are important for the origin of these novel traits. Our experiments, which lasted fewer than 250 generations, demonstrate that evolution can readily create an enormous reservoir of latent traits in microbial populations. These traits can facilitate adaptive evolution in a changing world.

Multiomics Study of Bacterial Growth Arrest in a Synthetic Biology Application

We investigated the scalability of a previously developed growth switch based on external control of RNA polymerase expression. Our results indicate that, in liter-scale bioreactors operating in fed-batch mode, growth-arrested Escherichia coli cells are able to convert glucose to glycerol at an increased yield. A multiomics quantification of the physiology of the cells shows that, apart from acetate production, few metabolic side effects occur. However, a number of specific responses to growth slow-down and growth arrest are launched at the transcriptional level. These notably include the downregulation of genes involved in growth-associated processes, such as amino acid and nucleotide metabolism and translation. Interestingly, the transcriptional responses are buffered at the proteome level, probably due to the strong decrease of the total mRNA concentration after the diminution of transcriptional activity and the absence of growth dilution of proteins. Growth arrest thus reduces the opportunities for dynamically adjusting the proteome composition, which poses constraints on the design of biotechnological production processes but may also avoid the initiation of deleterious stress responses.

Selection for phage resistance reduces virulence of Shigella flexneri

There is an increasing interest in phage therapy as an alternative to antibiotics for treating bacterial infections, especially using phages that select for evolutionary trade-offs between increased phage resistance and decreased fitness traits, such as virulence, in target bacteria. A vast repertoire of virulence factors allows the opportunistic bacterial pathogen Shigella flexneri to invade human gut epithelial cells, replicate intracellularly, and evade host immunity through intercellular spread. It has been previously shown that OmpA is necessary for the intercellular spread of S. flexneri. We hypothesized that a phage which uses OmpA as a receptor to infect S. flexneri should select for phage-resistant mutants with attenuated intercellular spread. Here, we show that phage A1-1 requires OmpA as a receptor and selects for reduced virulence in S. flexneri. We characterized five phage-resistant mutants by measuring phenotypic changes in various traits: cell-membrane permeability, total lipopolysaccharide (LPS), sensitivity to antibiotics, and susceptibility to other phages. The results separated the mutants into two groups: R1 and R2 phenotypically resembled ompA knockouts, whereas R3, R4, and R5 were similar to LPS-deficient strains. Whole-genome sequencing confirmed that R1 and R2 had mutations in ompA, while R3, R4, and R5 had mutations in the LPS inner-core biosynthesis genes gmhA and gmhC. Bacterial plaque assays confirmed that all the phage-resistant mutants were incapable of intercellular spread. We concluded that selection for S. flexneri resistance to phage A1-1 generally reduced virulence (i.e., intercellular spread), but this trade-off could be mediated by mutations either in ompA or in LPS-core genes that likely altered OmpA conformation.

IMPORTANCEShigella flexneri is a facultative intracellular pathogen of humans and a leading cause of bacillary dysentery. With few effective treatments and rising antibiotic resistance in these bacteria, there is increasing interest in alternatives to classical infection management of S. flexneri infections. Phage therapy poses an attractive alternative, particularly if a therapeutic phage can be found that results in an evolutionary trade-off between phage resistance and bacterial virulence. Here, we isolate a novel lytic phage from water collected in Cuatro Cienegas, Mexico, which uses the OmpA porin of S. flexneri as a receptor. We use phenotypic assays and genome sequencing to show that phage A1-1 selects for phage-resistant mutants which can be grouped into two categories: OmpA-deficient mutants and LPS-deficient mutants. Despite these underlying mechanistic differences, we confirmed that naturally occurring phage A1-1 selected for evolved phage resistance which coincided with impaired intercellular spread of S. flexneri in a eukaryotic infection model.

Assembling stable syntrophic Escherichia coli communities by comprehensively identifying beneficiaries of secreted goods

Metabolic cross-feeding frequently underlies mutualistic relationships in natural microbial communities and is often exploited to assemble synthetic microbial consortia. We systematically identified all single-gene knockouts suitable for imposing cross-feeding in Escherichia coli and used this information to assemble syntrophic communities. Most strains benefiting from shared goods were dysfunctional in biosynthesis of amino acids, nucleotides, and vitamins or mutants in central carbon metabolism. We tested cross-feeding potency in 1,444 strain pairs and mapped the interaction network between all functional groups of mutants. This network revealed that auxotrophs for vitamins are optimal cooperators. Lastly, we monitored how assemblies composed of dozens of auxotrophs change over time and observed that they rapidly and repeatedly coalesced to seven strain consortia composed primarily from vitamin auxotrophs. The composition of emerging consortia suggests that they were stabilized by multiple cross-feeding interactions. We conclude that vitamins are ideal shared goods since they optimize consortium growth while still imposing member co-dependence.

Quantifying the regulatory role of individual transcription factors in Escherichia coli

Gene regulation often results from the action of multiple transcription factors (TFs) acting at a promoter, obscuring the individual regulatory effect of each TF on RNA polymerase (RNAP). Here we measure the fundamental regulatory interactions of TFs in E. coli by designing synthetic target genes that isolate individual TFs' regulatory effects. Using a thermodynamic model, each TF's regulatory interactions are decoupled from TF occupancy and interpreted as acting through (de)stabilization of RNAP and (de)acceleration of transcription initiation. We find that the contribution of each mechanism depends on TF identity and binding location; regulation immediately downstream of the promoter is insensitive to TF identity, but the same TFs regulate by distinct mechanisms upstream of the promoter. These two mechanisms are uncoupled and can act coherently, to reinforce the observed regulatory role (activation/repression), or incoherently, wherein the TF regulates two distinct steps with opposing effects.

Potentiating antibiotic efficacy via perturbation of non-essential gene expression

Proliferation of multidrug-resistant (MDR) bacteria poses a threat to human health, requiring new strategies. Here we propose using fitness neutral gene expression perturbations to potentiate antibiotics. We systematically explored 270 gene knockout-antibiotic combinations in Escherichia coli, identifying 90 synergistic interactions. Identified gene targets were subsequently tested for antibiotic synergy on the transcriptomic level via multiplexed CRISPR-dCas9 and showed successful sensitization of E. coli without a separate fitness cost. These fitness neutral gene perturbations worked as co-therapies in reducing a Salmonella enterica intracellular infection in HeLa. Finally, these results informed the design of four antisense peptide nucleic acid (PNA) co-therapies, csgD, fnr, recA and acrA, against four MDR, clinically isolated bacteria. PNA combined with sub-minimal inhibitory concentrations of trimethoprim against two isolates of Klebsiella pneumoniae and E. coli showed three cases of re-sensitization with minimal fitness impacts. Our results highlight a promising approach for extending the utility of current antibiotics.

Cellular Self-Digestion and Persistence in Bacteria

Cellular self-digestion is an evolutionarily conserved process occurring in prokaryotic cells that enables survival under stressful conditions by recycling essential energy molecules. Self-digestion, which is triggered by extracellular stress conditions, such as nutrient depletion and overpopulation, induces degradation of intracellular components. This self-inflicted damage renders the bacterium less fit to produce building blocks and resume growth upon exposure to fresh nutrients. However, self-digestion may also provide temporary protection from antibiotics until the self-digestion-mediated damage is repaired. In fact, many persistence mechanisms identified to date may be directly or indirectly related to self-digestion, as these processes are also mediated by many degradative enzymes, including proteases and ribonucleases (RNases). In this review article, we will discuss the potential roles of self-digestion in bacterial persistence.

On the optimality of the enzyme-substrate relationship in bacteria

Much recent progress has been made to understand the impact of proteome allocation on bacterial growth; much less is known about the relationship between the abundances of the enzymes and their substrates, which jointly determine metabolic fluxes. Here, we report a correlation between the concentrations of enzymes and their substrates in Escherichia coli. We suggest this relationship to be a consequence of optimal resource allocation, subject to an overall constraint on the biomass density: For a cellular reaction network composed of effectively irreversible reactions, maximal reaction flux is achieved when the dry mass allocated to each substrate is equal to the dry mass of the unsaturated (or “free”) enzymes waiting to consume it. Calculations based on this optimality principle successfully predict the quantitative relationship between the observed enzyme and metabolite abundances, parameterized only by molecular masses and enzyme–substrate dissociation constants (K_m). The corresponding organizing principle provides a fundamental rationale for cellular investment into different types of molecules, which may aid in the design of more efficient synthetic cellular systems.

This study shows that in E. coli, the cellular mass of each metabolite approximately equals the combined mass of the free enzymes waiting to consume it; this simple relationship arises from the optimal utilization of cellular dry mass, and quantitatively describes available experimental data.

DNA Replication-Transcription Conflicts Do Not Significantly Contribute to Spontaneous Mutations Due to Replication Errors in Escherichia coli

Encounters between DNA replication and transcription can cause genomic disruption, particularly when the two meet head-on. Whether these conflicts produce point mutations is debated. This paper presents detailed analyses of a large collection of mutations generated during mutation accumulation experiments with mismatch repair (MMR)-defective Escherichia coli. With MMR absent, mutations are primarily due to DNA replication errors. Overall, there were no differences in the frequencies of base pair substitutions or small indels (i.e., insertion and deletions of ≤4 bp) in the coding sequences or promoters of genes oriented codirectionally versus head-on to replication. Among a subset of highly expressed genes, there was a 2- to 3-fold bias for indels in genes oriented head-on to replication, but this difference was almost entirely due to the asymmetrical genomic locations of tRNA genes containing mononucleotide runs, which are hot spots for indels. No additional orientation bias in mutation frequencies occurred when MMR⁻ strains were also defective for transcription-coupled repair (TCR). However, in contrast to other reports, loss of TCR slightly increased the overall mutation rate, meaning that TCR is antimutagenic. There was no orientation bias in mutation frequencies among the stress response genes that are regulated by RpoS or induced by DNA damage. Thus, biases in the locations of mutational targets can account for most, if not all, apparent biases in mutation frequencies between genes oriented head-on versus codirectional to replication. In addition, the data revealed a strong correlation of the frequency of base pair substitutions with gene length but no correlation with gene expression levels.

Transcriptional and Post-Transcriptional Polar Effects in Bacterial Gene Deletion Libraries

Single-gene deletions can affect the expression levels of other genes in the same operon in bacterial genomes. Here, we used proteomics for 133 Escherichia coli gene deletion mutants and transcriptome sequencing (RNA-seq) data from 71 mutants to probe the extent of transcriptional and post-transcriptional effects of gene deletions in operons. Transcriptional effects were common on genes located downstream of the deletion and were consistent across all operon members, with nearly 40% of operons showing greater than 2-fold up- or downregulation. Surprisingly, we observed an additional post-transcriptional effect that leads to the downregulation of the gene located directly downstream of the targeted gene. This effect was correlated with their intergenic distance, despite the ribosome binding site of the gene downstream remaining intact during library construction. Overall, the data presented can guide future library construction and highlight the importance of follow-up experiments for assessing direct effects of single-gene deletions in operons. IMPORTANCE Single-gene deletion libraries have allowed genome-wide characterization of gene function and interactions. While each mutant intends to disrupt the function of a single gene, it can unintentionally target other genes, such as those located in the same operon as the deletion. The extent to which such polar effects occur in deletion libraries has not been assessed. In this work, we use proteomics and transcriptomics data to show that transcript level changes lead to nearly 40% of deletions in operons affecting the protein levels of genes located downstream by at least 2-fold. Furthermore, we observed a post-transcriptional effect on the gene located directly downstream of the deletion. These results can guide the design of future gene deletion libraries and emphasizes the importance of follow-up work when linking genotypes to phenotypes.

Escherichia coli cryptic prophages sense nutrients to influence persister cell resuscitation

Cryptic prophages are not genomic junk but instead enable cells to combat myriad stresses as an active stress response. How these phage fossils affect persister cell resuscitation has, however, not been explored. Persister cells form as a result of stresses such as starvation, antibiotics and oxidative conditions, and resuscitation of these persister cells likely causes recurring infections such as those associated with tuberculosis, cystic fibrosis and Lyme disease. Deletion of each of the nine Escherichia coli cryptic prophages has no effect on persister cell formation. Strikingly, elimination of each cryptic prophage results in an increase in persister cell resuscitation with a dramatic increase in resuscitation upon deleting all nine prophages. This increased resuscitation includes eliminating the need for a carbon source and is due to activation of the phosphate import system resulting from inactivating the transcriptional regulator AlpA of the CP4-57 cryptic prophage. Deletion of alpA increases persister resuscitation, and AlpA represses phosphate regulator PhoR. Both phosphate regulators PhoP and PhoB stimulate resuscitation. This suggests a novel cellular stress mechanism controlled by cryptic prophages: regulation of phosphate uptake which controls the exit of the cell from dormancy and prevents premature resuscitation in the absence of nutrients.

Identification and Characterization of Pleiotropic High-Persistence Mutations in the Beta Subunit of the Bacterial RNA Polymerase

Mutations conferring resistance to bactericidal antibiotics reduce the average susceptibility of mutant populations. It is unknown, however, how those mutations affect the survival of individual bacteria. Since surviving bacteria can be a reservoir for recurring infections, it is important to know how survival rates may be affected by resistance mutations and by the choice of antibiotics. Here, we present evidence that (i) Escherichia coli mutants with 100 to 1,000 times increased frequency of survival in ciprofloxacin, an archetypal fluoroquinolone antibiotic, can be readily obtained in a stepwise selection; (ii) the high survival frequency is conferred by mutations in the switch region of the beta subunit of the RNA polymerase; (iii) the switch-region mutations are (p)ppGpp mimics, partially analogous to rpoB stringent mutations; (iv) the stringent and switch region rpoB mutations frequently occur in clinical isolates of E. coli, Acinetobacter baumannii, Mycobacterium tuberculosis, and Staphylococcus aureus, and at least one of them, RpoB S488L, which is a common rifampicin resistance mutations, dramatically increases the survival of a clinical methicillin-resistant S. aureus (MRSA) strain in ampicillin; and (v) the RpoB-associated high-survival phenotype can be reversed by subinhibitory concentrations of chloramphenicol.

The Effect of Impaired Polyamine Transport on Pneumococcal Transcriptome

Infections due to Streptococcus pneumoniae, a commensal in the nasopharynx, still claim a significant number of lives worldwide. Genome plasticity, antibiotic resistance, and limited serotype coverage of the available polysaccharide-based conjugate vaccines confounds therapeutic interventions to limit the spread of this pathogen. Pathogenic mechanisms that allow successful adaption and persistence in the host could be potential innovative therapeutic targets. Polyamines are ubiquitous polycationic molecules that regulate many cellular processes. We previously reported that deletion of polyamine transport operon potABCD, which encodes a putrescine/spermidine transporter (ΔpotABCD), resulted in an unencapsulated attenuated phenotype. Here, we characterize the transcriptome, metabolome, and stress responses of polyamine transport-deficient S. pneumoniae. Compared with the wild-type strain, the expression of genes involved in oxidative stress responses and the nucleotide sugar metabolism was reduced, while expression of genes involved in the Leloir, tagatose, and pentose phosphate pathways was higher in ΔpotABCD. A metabolic shift towards the pentose phosphate pathway will limit the synthesis of precursors of capsule polysaccharides. Metabolomics results show reduced levels of glutathione and pyruvate in the mutant. Our results also show that the potABCD operon protects pneumococci against hydrogen peroxide and nitrosative stress. Our findings demonstrate the importance of polyamine transport in pneumococcal physiology that could impact in vivo fitness. Thus, polyamine transport in pneumococci represents a novel target for therapeutic interventions.

Efficient and accurate identification of protein complexes from protein-protein interaction networks based on the clustering coefficient

•

Provided a family of efficient network algorithms for protein complex identification.

•

The parameter-free family outperforms existing approaches on different networks.

•

It exactly recovered ~ 35% of protein complexes in a pan-plant PPI network.

•

We examined of network perturbations on predicted protein complexes.

Identification of protein complexes from protein-protein interaction (PPI) networks is a key problem in PPI mining, solved by parameter-dependent approaches that suffer from small recall rates. Here we introduce GCC-v, a family of efficient, parameter-free algorithms to accurately predict protein complexes using the (weighted) clustering coefficient of proteins in PPI networks. Through comparative analyses with gold standards and PPI networks from Escherichia coli, Saccharomyces cerevisiae, and Homo sapiens, we demonstrate that GCC-v outperforms twelve state-of-the-art approaches for identification of protein complexes with respect to twelve performance measures in at least 85.71% of scenarios. We also show that GCC-v results in the exact recovery of ∼35% of protein complexes in a pan-plant PPI network and discover 144 new protein complexes in Arabidopsis thaliana, with high support from GO semantic similarity. Our results indicate that findings from GCC-v are robust to network perturbations, which has direct implications to assess the impact of the PPI network quality on the predicted protein complexes.

Role of inorganic phosphate concentrations in in vitro activity of fosfomycin

OBJECTIVES

The objective of this study was to evaluate the in vitro activity of fosfomycin under different physiological concentrations of inorganic phosphate (P_i).

METHODS

The wild-type BW25113 strain, four isogenic mutants (ΔglpT, ΔuhpT, ΔglpT-uhpT, and ΔphoB) and six clinical isolates of Escherichia coli with different fosfomycin susceptibilities were used. EUCAST breakpoints were used. Susceptibility was evaluated by agar dilution using standard Mueller-Hinton agar (P_i concentration of 1 mM similar to human plasma concentration) and supplemented with P_i (13 and 42 mM, minimum and maximum urinary P_i concentrations) and/or glucose-6-phosphate (25 mg/L). Fosfomycin transporter promoter activity was assayed using PglpT::gfpmut2 or PuhpT::gfpmut2 promoter fusions in standard Mueller-Hinton Broth (MHB), supplemented with P_i (13 or 42 mM) ± glucose-6-phosphate. Fosfomycin activity was quantified, estimating fosfomycin EC₅₀ under different P_i concentrations (1, 13 and 42 mM + glucose-6-phosphate) and in time-kill assays using fosfomycin concentrations of 307 (maximum plasma concentration (C_max)), 1053 and 4415 mg/L (urine C_max range), using MHB with 28 mM P_i (mean urine P_i concentration) + 25 mg/L glucose-6-phosphate.

RESULTS

All the strains showed decreased susceptibility to fosfomycin linked to increased P_i concentrations: 1-4 log₂ dilution differences from 1 to 13 mM, and 1-8 log₂ dilution differences at 42 mM P_i. Changes in phosphate concentration did not affect the expression of fosfomycin transporters. By increasing P_i concentrations higher fosfomycin EC₅₀ bacterial viability was observed, except against ΔglpT-uhpT. The increase in P_i reduced the bactericidal effect of fosfomycin.

DISCUSSION

P_i variations in physiological fluids may reduce fosfomycin activity against E. coli. Elevated P_i concentrations in urine may explain oral fosfomycin failure in non-wild-type but fosfomycin-susceptible E. coli strains.

Parallelism of intestinal secretory IgA shapes functional microbial fitness

Dimeric IgA secreted across mucous membranes in response to nonpathogenic taxa of the microbiota accounts for most antibody production in mammals. Diverse binding specificities can be detected within the polyclonal mucosal IgA antibody response^1-10, but limited monoclonal hybridomas have been studied to relate antigen specificity or polyreactive binding to functional effects on microbial physiology in vivo^11-17. Here we use recombinant dimeric monoclonal IgAs (mIgAs) to finely map the intestinal plasma cell response to microbial colonization with a single microorganism in mice. We identify a range of antigen-specific mIgA molecules targeting defined surface and nonsurface membrane antigens. Secretion of individual dimeric mIgAs targeting different antigens in vivo showed distinct alterations in the function and metabolism of intestinal bacteria, largely through specific binding. Even in cases in which the same microbial antigen is targeted, microbial metabolic alterations differed depending on IgA epitope specificity. By contrast, bacterial surface coating generally reduced motility and limited bile acid toxicity. The overall intestinal IgA response to a single microbe therefore contains parallel components with distinct effects on microbial carbon-source uptake, bacteriophage susceptibility, motility and membrane integrity.

First-principles model of optimal translation factors stoichiometry

Enzymatic pathways have evolved uniquely preferred protein expression stoichiometry in living cells, but our ability to predict the optimal abundances from basic properties remains underdeveloped. Here, we report a biophysical, first-principles model of growth optimization for core mRNA translation, a multi-enzyme system that involves proteins with a broadly conserved stoichiometry spanning two orders of magnitude. We show that predictions from maximization of ribosome usage in a parsimonious flux model constrained by proteome allocation agree with the conserved ratios of translation factors. The analytical solutions, without free parameters, provide an interpretable framework for the observed hierarchy of expression levels based on simple biophysical properties, such as diffusion constants and protein sizes. Our results provide an intuitive and quantitative understanding for the construction of a central process of life, as well as a path toward rational design of pathway-specific enzyme expression stoichiometry.

Unraveling the functions of uncharacterized transcription factors in Escherichia coli using ChIP-exo

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.

Fundamental limits on the rate of bacterial growth and their influence on proteomic composition

Despite abundant measurements of bacterial growth rate, cell size, and protein content, we lack a rigorous understanding of what sets the scale of these quantities and when protein abundances should (or should not) depend on growth rate. Here, we estimate the basic requirements and physical constraints on steady-state growth by considering key processes in cellular physiology across a collection of Escherichia coli proteomic data covering ≈4,000 proteins and 36 growth rates. Our analysis suggests that cells are predominantly tuned for the task of cell doubling across a continuum of growth rates; specific processes do not limit growth rate or dictate cell size. We present a model of proteomic regulation as a function of nutrient supply that reconciles observed interdependences between protein synthesis, cell size, and growth rate and propose that a theoretical inability to parallelize ribosomal synthesis places a firm limit on the achievable growth rate. A record of this paper's transparent peer review process is included in the supplemental information.

A phage-encoded nucleoid associated protein compacts both host and phage DNA and derepresses H-NS silencing

Nucleoid Associated Proteins (NAPs) organize the bacterial chromosome within the nucleoid. The interaction of the NAP H-NS with DNA also represses specific host and xenogeneic genes. Previously, we showed that the bacteriophage T4 early protein MotB binds to DNA, co-purifies with H-NS/DNA, and improves phage fitness. Here we demonstrate using atomic force microscopy that MotB compacts the DNA with multiple MotB proteins at the center of the complex. These complexes differ from those observed with H-NS and other NAPs, but resemble those formed by the NAP-like proteins CbpA/Dps and yeast condensin. Fluorescent microscopy indicates that expression of motB in vivo, at levels like that during T4 infection, yields a significantly compacted nucleoid containing MotB and H-NS. motB overexpression dysregulates hundreds of host genes; ∼70% are within the hns regulon. In infected cells overexpressing motB, 33 T4 late genes are expressed early, and the T4 early gene repEB, involved in replication initiation, is up ∼5-fold. We postulate that MotB represents a phage-encoded NAP that aids infection in a previously unrecognized way. We speculate that MotB-induced compaction may generate more room for T4 replication/assembly and/or leads to beneficial global changes in host gene expression, including derepression of much of the hns regulon.

Role of the Discriminator Sequence in the Supercoiling Sensitivity of Bacterial Promoters

DNA supercoiling acts as a global transcriptional regulator that contributes to the rapid transcriptional response of bacteria to many environmental changes. Although a large fraction of promoters from phylogenetically distant species respond to superhelical variations, the sequence or structural determinants of this behavior remain elusive. Here, we focus on the sequence of the "discriminator" element that was shown to modulate this response in several promoters. We develop a quantitative thermodynamic model of this regulatory effect, focusing on open complex formation during transcription initiation independently from promoter-specific regulatory proteins. We analyze previous and new expression data and show that the model predictions quantitatively match the in vitro and in vivo supercoiling response of selected promoters with mutated discriminator sequences. We then test the universality of this mechanism by a statistical analysis of promoter sequences from transcriptomes of phylogenetically distant bacteria under conditions of supercoiling variations (i) by gyrase inhibitors, (ii) by environmental stresses, or (iii) inherited in the longest-running evolution experiment. In all cases, we identify a robust and significant sequence signature in the discriminator region, suggesting that supercoiling-modulated promoter opening underpins a ubiquitous regulatory mechanism in the prokaryotic kingdom based on the fundamental mechanical properties of DNA and its basal interaction with RNA polymerase. IMPORTANCE In this study, we highlight the role of the discriminator as a global sensor of supercoiling variations and propose the first quantitative regulatory model of this principle, based on the specific step of promoter opening during transcription initiation. It defines the predictive rule by which DNA supercoiling quantitatively modulates the expression rate of bacterial promoters, depending on the G/C content of their discriminator and independently from promoter-specific regulatory proteins. This basal mechanism affects a wide range of species, which is tested by an extensive analysis of global high-throughput expression data. Altogether, ours results confirm and provide a quantitative framework for the long-proposed notion that the discriminator sequence is a significant determinant of promoter supercoiling sensitivity, underpinning the ubiquitous regulatory action of DNA supercoiling on the core transcriptional machinery, in particular in response to quick environmental changes.

Lisen&Curate: A platform to facilitate gathering textual evidence for curation of regulation of transcription initiation in bacteria

The number of published papers in biomedical research makes it rather impossible for a researcher to keep up to date. This is where manually curated databases contribute facilitating the access to knowledge. However, the structure required by databases strongly limits the type of valuable information that can be incorporated. Here, we present Lisen&Curate, a curation system that facilitates linking sentences or part of sentences (both considered sources) in articles with their corresponding curated objects, so that rich additional information of these objects is easily available to users. These sources are going to be offered both within RegulonDB and a new database, L-Regulon. To show the relevance of our work, two senior curators performed a curation of 31 articles on the regulation of transcription initiation of E. coli using Lisen&Curate. As a result, 194 objects were curated and 781 sources were recorded. We also found that these sources are useful to develop automatic approaches to detect objects in articles by observing word frequency patterns and by carrying out an open information extraction task. Sources may help to elaborate a controlled vocabulary of experimental methods. Finally, we discuss our ecosystem of interconnected applications, RegulonDB, L-Regulon, and Lisen&Curate, to facilitate the access to knowledge on regulation of transcription initiation in bacteria. We see our proposal as the starting point to change the way experimentalists connect a piece of knowledge with its evidence using RegulonDB.

Bacterial resistance to CRISPR-Cas antimicrobials

In the age of antibiotic resistance and precise microbiome engineering, CRISPR-Cas antimicrobials promise to have a substantial impact on the way we treat diseases in the future. However, the efficacy of these antimicrobials and their mechanisms of resistance remain to be elucidated. We systematically investigated how a target E. coli strain can escape killing by episomally-encoded CRISPR-Cas9 antimicrobials. Using Cas9 from Streptococcus pyogenes (SpCas9) we studied the killing efficiency and resistance mutation rate towards CRISPR-Cas9 antimicrobials and elucidated the underlying genetic alterations. We find that killing efficiency is not correlated with the number of cutting sites or the type of target. While the number of targets did not significantly affect efficiency of killing, it did reduce the emergence of chromosomal mutations conferring resistance. The most frequent target of resistance mutations was the plasmid-encoded SpCas9 that was inactivated by bacterial genome rearrangements involving translocation of mobile genetic elements such as insertion elements. This resistance mechanism can be overcome by re-introduction of an intact copy of SpCas9. The work presented here provides a guide to design strategies that reduce resistance and improve the activity of CRISPR-Cas antimicrobials.

Identification of a transcription factor, PunR, that regulates the purine and purine nucleoside transporter punC in E. coli

Many genes in bacterial genomes are of unknown function, often referred to as y-genes. Recently, the analytic methods have divided bacterial transcriptomes into independently modulated sets of genes (iModulons). Functionally annotated iModulons that contain y-genes lead to testable hypotheses to elucidate y-gene function. The inversely correlated expression of a putative transporter gene, ydhC, relative to purine biosynthetic genes, has led to the hypothesis that it encodes a purine-related transporter and revealed a LysR-family regulator, YdhB, with a predicted 23-bp palindromic binding motif. RNA-Seq analysis of a ydhB knockout mutant confirmed the YdhB-dependent activation of ydhC in the presence of adenosine. The deletion of either the ydhC or the ydhB gene led to a substantially decreased growth rate for E. coli in minimal medium with adenosine, inosine, or guanosine as the nitrogen source. Taken together, we provide clear evidence that YdhB activates the expression of the ydhC gene that encodes a purine transporter in E. coli. We propose that the genes ydhB and ydhC be re-named as punR and punC, respectively.

Rodionova et al. find that the putative transporter gene, ydhC and its regulator ydhB are involved in purine transportation and that the expression of the ydhC gene is activated by the YdhB in E. coli. The authors suggest renaming the regulator PunR and the transporter PunC, respectively.

Hawaiian Nysius Insects Rely on an Obligate Symbiont with a Reduced Genome That Retains a Discrete Nutritional Profile to Match Their Plant Seed Diet

Seed-feeding Nysius insects (Hemiptera: Lygaeidae) have a symbiotic association with distinct intracellular bacteria, “Candidatus Schneideria nysicola” (Gammaproteobacteria). Although many other hemipteran insect groups generally rely on bacterial symbionts that synthesize all ten essential amino acids lacking in their plant sap diets, the nutritional role of Schneideria in Nysius hosts that specialize on a more nutritionally complete seed-based diet has remained unknown. To determine the nutritional and functional capabilities of Schneideria, we sequenced the complete Schneideria genomes from three distantly related endemic Hawaiian Nysius seed bug species. The complete Schneideria genomes are highly conserved and perfectly syntenic among Hawaiian Nysius host species. Each circular chromosome is ∼0.57 Mb in size and encodes 537 protein-coding genes. They further exhibit a strong A + T nucleotide substitution bias with an average G + C nucleotide content of 29%. The predicted nutritional contribution of Schneideria includes four B vitamins and five of the ten essential amino acids that likely match its hosts’ seed-based diet. Disrupted and degraded genes in Schneideria suggests that Hawaiian lineages are undergoing continued gene losses observed in the smaller genomes of the other more ancient hemipteran symbionts.

Loss of N1-methylation of G37 in tRNA induces ribosome stalling and reprograms gene expression

N¹-methylation of G37 is required for a subset of tRNAs to maintain the translational reading-frame. While loss of m¹G37 increases ribosomal +1 frameshifting, whether it incurs additional translational defects is unknown. Here, we address this question by applying ribosome profiling to gain a genome-wide view of the effects of m¹G37 deficiency on protein synthesis. Using E coli as a model, we show that m¹G37 deficiency induces ribosome stalling at codons that are normally translated by m¹G37-containing tRNAs. Stalling occurs during decoding of affected codons at the ribosomal A site, indicating a distinct mechanism than that of +1 frameshifting, which occurs after the affected codons leave the A site. Enzyme- and cell-based assays show that m¹G37 deficiency reduces tRNA aminoacylation and in some cases peptide-bond formation. We observe changes of gene expression in m¹G37 deficiency similar to those in the stringent response that is typically induced by deficiency of amino acids. This work demonstrates a previously unrecognized function of m¹G37 that emphasizes its role throughout the entire elongation cycle of protein synthesis, providing new insight into its essentiality for bacterial growth and survival.

Nucleoid-associated proteins shape chromatin structure and transcriptional regulation across the bacterial kingdom

Genome architecture has proven to be critical in determining gene regulation across almost all domains of life. While many of the key components and mechanisms of eukaryotic genome organization have been described, the interplay between bacterial DNA organization and gene regulation is only now being fully appreciated. An increasing pool of evidence has demonstrated that the bacterial chromosome can reasonably be thought of as chromatin, and that bacterial chromosomes contain transcriptionally silent and transcriptionally active regions analogous to heterochromatin and euchromatin, respectively. The roles played by histones in eukaryotic systems appear to be shared across a range of nucleoid-associated proteins (NAPs) in bacteria, which function to compact, structure, and regulate large portions of bacterial chromosomes. The broad range of extant NAPs, and the extent to which they differ from species to species, has raised additional challenges in identifying and characterizing their roles in all but a handful of model bacteria. Here we review the regulatory roles played by NAPs in several well-studied bacteria and use the resulting state of knowledge to provide a working definition for NAPs, based on their function, binding pattern, and expression levels. We present a screening procedure which can be applied to any species for which transcriptomic data are available. Finally, we note that NAPs tend to play two major regulatory roles - xenogeneic silencers and developmental regulators - and that many unrecognized potential NAPs exist in each bacterial species examined.

An efficient dsRNA constitutive expression system in Escherichia coli

Synthetic dsRNA are valuable tools for reverse genetics research and virus silencing applications. Its synthesis can be performed both in vivo or in vitro. Whilst the latter presents the drawback of high production cost, the former has the advantage of being less expensive and suitable for scalable production. In general, dsRNAs are obtained in vivo from Escherichia coli heterologous systems that require the gene for the T7 RNA polymerase inducible by IPTG. The (ds)RNAs for gene of interest are then synthesized under the T7 promoter. In this work, we present a reliable vector system that includes the insulated promoter proD for the constitutive expression of dsRNA in E. coli that does not require any inducer and that renders elevated dsRNA yield. In tandem, the T7 and proD promoters render the highest dsRNA yield. The accumulation of dsRNA in this system entails a high metabolic cost for the cell. Bacterial RNA extractions that included dsRNAs homologous to the m5GFPer gene and derived from both the synthetic and constitutive promoters induce silencing of GFP expression in Nicotiana benthamiana 16c.Key points• A vector system that includes a constitutive promoter and a T7 promoter in tandem for maximizing dsRNA synthesis.• The metabolic cost for bacteria is maximum when the two promoters are operating simultaneously and results from the accumulation of dsRNA.• Bacterial RNA extractions from both the induced and constitutive systems that include a mGFP5er-derived dsRNA are capable of silencing the GFP expression in Nicotiana benthamiana 16c plants.

The EcoCyc Database in 2021

The EcoCyc model-organism database collects and summarizes experimental data for Escherichia coli K-12. EcoCyc is regularly updated by the manual curation of individual database entries, such as genes, proteins, and metabolic pathways, and by the programmatic addition of results from select high-throughput analyses. Updates to the Pathway Tools software that supports EcoCyc and to the web interface that enables user access have continuously improved its usability and expanded its functionality. This article highlights recent improvements to the curated data in the areas of metabolism, transport, DNA repair, and regulation of gene expression. New and revised data analysis and visualization tools include an interactive metabolic network explorer, a circular genome viewer, and various improvements to the speed and usability of existing tools.