Functional analysis of 1440 Escherichia coli genes using the combination of knock-out library and phenotype microarrays

Budding and explosive membrane vesicle production by hypervesiculating Escherichia coli strain ΔrodZ

Escherichia coli produces extracellular vesicles called outer membrane vesicles. In this study, we investigated the mechanism underlying the hypervesiculation of deletion mutant ΔrodZ of E. coli. RodZ forms supramolecular complexes with actin protein MreB and peptidoglycan (PG) synthase, and plays an important role in determining the cell shape. Because mreB is an essential gene, an expression-repressed strain (mreB R3) was constructed using CRISPRi, in which the expression of mreB decreased to 20% of that in the wild-type (WT) strain. In shaken-flask culture, the ΔrodZ strain produced >50 times more vesicles than the WT strain. The mreB-repressed strain mreB R3 showed eightfold higher vesicle production than the WT. ΔrodZ and mreB R3 cells were observed using quick-freeze replica electron microscopy. As reported in previous studies, ΔrodZ cells were spherical (WT cells are rod-shaped). Some ΔrodZ cells (around 7% in total) had aberrant surface structures, such as budding vesicles and dented surfaces, or curved patterns on the surface. Holes in the PG layer and an increased cell volume were observed for ΔrodZ and mreB R3 cells compared with the WT. In conditions of osmotic support using sucrose, the OD660 value of the ΔrodZ strain increased significantly, and vesicle production decreased drastically, compared with those in the absence of sucrose. This study first clarified that vesicle production by the E. coli ΔrodZ strain is promoted by surface budding and a burst of cells that became osmotically sensitive because of their incomplete PG structure.

Knockout of a highly GC-rich gene in Burkholderia pyrrocinia by recombineering with freeze-thawing transformation

Genetic transformation is a valuable and essential method that provides powerful insights into the gene function of microorganisms and contributes to the construction of engineered bacteria. Here, we developed a novel genetic transformation system to easily knock out a highly GC-rich gene (74.71% GC) from Burkholderia pyrrocinia JK-SH007, a biocontrol strain of poplar canker disease. This system revealed a reliable selectable marker (trimethoprim resistance gene, Tmp) and a simplified, efficient transformation method (6,363.64 CFU/μg, pHKT2) that was developed via freeze-thawing. The knockout recombineering of B. pyrrocinia JK-SH007 was achieved through a suicide plasmid with a three-fragment mutagenesis construct. The three-fragment cassette for mutagenesis was generated by overlap extension and touchdown PCRs and composed of Tmp flanked by GC-rich upstream and downstream fragments from B. pyrrocinia JK-SH007. The mutant strain (ΔBpEG), which was verified by PCR, lost 93.3% of its ability to degrade carboxymethyl cellulose over 40 days. Overall, this system may contribute to future research on B. pyrrocinia traits.

Gene Dispensability in Escherichia coli Grown in Thirty Different Carbon Environments

While there has been much study of bacterial gene dispensability, there is a lack of comprehensive genome-scale examinations of the impact of gene deletion on growth in different carbon sources. In this context, a lot can be learned from such experiments in the model microbe Escherichia coli where much is already understood and there are existing tools for the investigation of carbon metabolism and physiology (1). Gene deletion studies have practical potential in the field of antibiotic drug discovery where there is emerging interest in bacterial central metabolism as a target for new antibiotics (2). Furthermore, some carbon utilization pathways have been shown to be critical for initiating and maintaining infection for certain pathogens and sites of infection (3–5). Here, with the use of high-throughput solid medium phenotyping methods, we have generated kinetic growth measurements for 3,796 genes under 30 different carbon source conditions. This data set provides a foundation for research that will improve our understanding of genes with unknown function, aid in predicting potential antibiotic targets, validate and advance metabolic models, and help to develop our understanding of E. coli metabolism.

Central metabolism is a topic that has been studied for decades, and yet, this process is still not fully understood in Escherichia coli, perhaps the most amenable and well-studied model organism in biology. To further our understanding, we used a high-throughput method to measure the growth kinetics of each of 3,796 E. coli single-gene deletion mutants in 30 different carbon sources. In total, there were 342 genes (9.01%) encompassing a breadth of biological functions that showed a growth phenotype on at least 1 carbon source, demonstrating that carbon metabolism is closely linked to a large number of processes in the cell. We identified 74 genes that showed low growth in 90% of conditions, defining a set of genes which are essential in nutrient-limited media, regardless of the carbon source. The data are compiled into a Web application, Carbon Phenotype Explorer (CarPE), to facilitate easy visualization of growth curves for each mutant strain in each carbon source. Our experimental data matched closely with the predictions from the EcoCyc metabolic model which uses flux balance analysis to predict growth phenotypes. From our comparisons to the model, we found that, unexpectedly, phosphoenolpyruvate carboxylase (ppc) was required for robust growth in most carbon sources other than most trichloroacetic acid (TCA) cycle intermediates. We also identified 51 poorly annotated genes that showed a low growth phenotype in at least 1 carbon source, which allowed us to form hypotheses about the functions of these genes. From this list, we further characterized the ydhC gene and demonstrated its role in adenosine efflux.

Enhanced synthesis of alginate oligosaccharides in Pseudomonas mendocina NK-01 by overexpressing MreB

This study aimed to investigate the effects of cytoskeleton protein MreB on bacterial cell morphology and the synthesis of alginate oligosaccharides (AO) and polyhydroxyalkanoate (PHA) by Pseudomonas mendocina NK-01. To overexpress the mreB gene, an expression vector encoding MreB-GFP fusion protein was constructed. The scanning electron microscope (SEM) showed that cells expressing MreB were longer than the wild ones, which agrees with MreB's relationship with the synthesis of peptidoglycan. Cells expressing the MreB-GFP fusion protein emitted green fluorescence under a fluorescence microscope, suggesting that MreB was functionally expressed in strain NK-01. Under a confocal laser scanning microscope, MreB was observed as located around the cell membrane. Furthermore, the recombinant strain could synthesize 0.961 g/L AO, which was 5.86-fold higher than wild-type strain. Through the medium optimization test, we finally selected the addition of 20 g/L glucose as the optimal glycogen addition for AO fermentation based on a high AO yield and high substrate transformation efficiency. The results indicated that overexpression of MreB affected the cell morphology, the activity of AO polymerase, and the efficiency of AO secretion. However, the synthesis of PHA for recombinant strain was slightly reduced. The results suggested that the overexpression of this cytoskeleton protein affected the yield of specific intracellular and extracellular products.

Novel Technologies for Optimal Strain Breeding

The implementation of a knowledge-based bioeconomy requires the rapid development of highly efficient microbial production strains that are able to convert renewable carbon sources to value-added products, such as bulk and fine chemicals, pharmaceuticals, or proteins at industrial scale. Starting from classical strain breeding by random mutagenesis and screening in the 1950s via rational design by metabolic engineering initiated in the 1970s, a range of powerful new technologies have been developed in the past two decades that can revolutionize future strain engineering. In particular, next-generation sequencing technologies combined with new methods of genome engineering and high-throughput screening based on genetically encoded biosensors have allowed for new concepts. In this chapter, selected new technologies relevant for breeding microbial production strains with a special emphasis on amino acid producers will be summarized.

Novel Functions and Regulation of Cryptic Cellobiose Operons in Escherichia coli

Presence of cellobiose as a sole carbon source induces mutations in the chb and asc operons of Escherichia coli and allows it to grow on cellobiose. We previously engineered these two operons with synthetic constitutive promoters and achieved efficient cellobiose metabolism through adaptive evolution. In this study, we characterized two mutations observed in the efficient cellobiose metabolizing strain: duplication of RBS of ascB gene, (β-glucosidase of asc operon) and nonsense mutation in yebK, (an uncharacterized transcription factor). Mutations in yebK play a dominant role by modulating the length of lag phase, relative to the growth rate of the strain when transferred from a rich medium to minimal cellobiose medium. Mutations in ascB, on the other hand, are specific for cellobiose and help in enhancing the specific growth rate. Taken together, our results show that ascB of the asc operon is controlled by an internal putative promoter in addition to the native cryptic promoter, and the transcription factor yebK helps to remodel the host physiology for cellobiose metabolism. While previous studies characterized the stress-induced mutations that allowed growth on cellobiose, here, we characterize the adaptation-induced mutations that help in enhancing cellobiose metabolic ability. This study will shed new light on the regulatory changes and factors that are needed for the functional coupling of the host physiology to the activated cryptic cellobiose metabolism.

Identifying essential genes in Mycobacterium tuberculosis by global phenotypic profiling

Transposon sequencing (TnSeq) is a next-generation deep sequencing-based method to quantitatively assess the composition of complex mutant transposon libraries after pressure from selection. Although this method can be used for any organism in which transposon mutagenesis is possible, this chapter describes its use in Mycobacterium tuberculosis. More specifically, the methods for generating complex libraries through transposon mutagenesis, design of selective pressure, extraction of genomic DNA, amplification and quantification of transposon insertions through next-generation deep sequencing are covered. Determining gene essentiality and statistical analysis on data collected are also discussed.

[Regulation of determination of bacterial shape]

Bacteria show various cell shape such as round, rod, helical, and so on. However, each bacterium has its own shape and their length and width are kept in a narrow range in a population. Abnormal cell shape often results in death of the cells. Therefore, it is important to maintain their shape. Rod-shaped bacterium Escherichia coli needs to regulate cell polarity, length and width in order to form rod shape. Bacterial shape is genetically regulated. Especially, MreB, a bacterial actin, and its interacting proteins are involved in the regulation. We have identified rodZ as a novel cell shape determinant and have been analyzing RodZ protein in the past few years. The rodZ mutant is round. We isolated suppressor mutants of the rodZ mutant. The shape of the suppressors was rod shape. By analyzing the rodZ mutant and the suppressors, we concluded that RodZ helps assembly of MreB filaments. MreB plays roles in regulation of cell polarity, length, and width, whereas RodZ is involved in regulation of length and width. In this review, I summarize our research and research from other groups on bacterial cell shape.

A mutation in the promoter region of zipA, a component of the divisome, suppresses the shape defect of RodZ-deficient cells

RodZ is important for maintaining the rod shape of Escherichia coli. Loss of RodZ causes conversion of the rod shape to a round shape and a growth rate slower than that of wild-type cells. Suppressor mutations that simultaneously restore both the growth rates and the rod shape were isolated. Most of the suppressor mutations are found in mreB, mrdA, or mrdB. One of the mutations was in the promoter region of zipA, which encodes a crucial component of the cell division machinery. In this study, we investigated the mechanism of the suppression by this mutation. ZipA was slightly but significantly increased in the suppressor cells and led to a delay in cell division. While round-shaped mreB and mrdA mutants lose cell bipolarity, we found that round-shaped rodZ mutants retained cell bipolarity. Therefore, we concluded that a delay in the completion of septation provides extra time to elongate the cell laterally so that the zipA suppressor mutant is able to recover its ovoid or rod shape. The suppression by zipA demonstrates that the regulation of timing of septation potentially contributes to the conversion of morphology in bacterial cells.

A case of adaptation through a mutation in a tandem duplication during experimental evolution in Escherichia coli

Background

DNA duplications constitute important precursors for genome variation. Here we analyzed an unequal duplication harboring a beneficial mutation that may provide alternative evolutionary outcomes.

Results

We characterized this evolutionary event during experimental evolution for only 100 generations of an Escherichia coli strain under glucose limitation within chemostats. By combining Insertion Sequence based Restriction Length Polymorphism experiments, pulsed field gel electrophoresis and two independent genome re-sequencing experiments, we identified an evolved lineage carrying a 180 kb duplication of the 46’ region of the E. coli chromosome. This evolved duplication revealed a heterozygous state, with one copy harboring a 2668 bp deletion that included part of the ogrK gene and both the yegR and yegS genes. By genetically manipulating ancestral and evolved strains, we showed that the single yegS inactivation was sufficient to confer a frequency dependent fitness increase under the chemostat selective conditions in both the ancestor and evolved genetic contexts, implying that the duplication itself was not a direct fitness contributor. Nonetheless, the heterozygous duplicated state was relatively stable in the conditions prevailing during evolution in chemostats, in striking contrast to non selective conditions in which the duplication resolved at high frequency into either its ancestral or deleted copy.

Conclusions

Our results suggest that the duplication state may constitute a second order selection process providing higher evolutionary potential. Moreover, its heterozygous nature may provide differential evolutionary opportunities in alternating environments. Our results also highlighted how careful analyses of whole genome data are needed to identify such complex rearrangements.

Genome-wide identification of the targets for genetic manipulation to improve L-lactate production by Saccharomyces cerevisiae by using a single-gene deletion strain collection

To identify genome-wide targets for gene manipulation for increasing L-lactate production in recombinant Saccharomyces cerevisiae strains, we transformed all available single-gene deletion strains of S. cerevisiae with a plasmid carrying the human L-lactate dehydrogenase gene, and examined L-lactate production in the obtained transformants. The thresholds of increased or decreased L-lactate production were determined based on L-lactate production by the standard strain in repetitive experiments. L-lactate production data for 4802 deletion strains were obtained, and deletion strains with increased or decreased L-lactate production were identified. Functional category analysis of genes whose deletion increased L-lactate production revealed that ribosome biogenesis-related genes were overrepresented. Most deletion strains for genes related to ribosome biogenesis exhibited increased L-lactate production in 200-ml batch cultures. We deleted the genes related to ribosome biogenesis in a recombinant strain of S. cerevisiae with a genetic background different from that of the above deletion strains, and examined the effect of target gene deletion on L-lactate production. We observed that deletion of genes related to ribosome biogenesis leads to increased L-lactate production by recombinant S. cerevisiae strains, and the single-gene deletion strain collection could be utilized in identifying target genes for improving L-lactate production in S. cerevisiae recombinant strains.

Mutations in cell elongation genes mreB, mrdA and mrdB suppress the shape defect of RodZ-deficient cells

RodZ interacts with MreB and both factors are required to maintain the rod shape of Escherichia coli. The assembly of MreB into filaments regulates the subcellular arrangement of a group of enzymes that synthesizes the peptidoglycan (PG) layer. However, it is still unknown how polymerization of MreB determines the rod shape of bacterial cells. Regulatory factor(s) are likely to be involved in controlling the function and dynamics of MreB. We isolated suppressor mutations to partially recover the rod shape in rodZ deletion mutants and found that some of the suppressor mutations occurred in mreB. All of the mreB mutations were in or in the vicinity of domain IA of MreB. Those mreB mutations changed the property of MreB filaments in vivo. In addition, suppressor mutations were found in the periplasmic regions in PBP2 and RodA, encoded by mrdA and mrdB genes. Similar to MreB and RodZ, PBP2 and RodA are pivotal to the cell wall elongation process. Thus, we found that mutations in domain IA of MreB and in the periplasmic domain of PBP2 and RodA can restore growth and rod shape to ΔrodZ cells, possibly by changing the requirements of MreB in the process.

Metabolic model refinement using phenotypic microarray data

Phenotypic microarray (PM) is a standardized, high-throughput technology for profiling phenotypes of microorganisms, which allows for characterization on around 2,000 different media conditions. The data generated using PM can be incorporated into genome-scale metabolic models to improve their predictive capability. In addition, a comparison of phenotypic profiles of wild-type and gene knockout mutants can give essential information about gene functions of unknown genes. In this chapter, we present a protocol to refine preconstructed metabolic models using the PM data. Both manual refinement and algorithmic approaches for integrating the PM data into metabolic models have been discussed.

The diversity of microbial aldo/keto reductases from Escherichia coli K12

The genome of Escherichia coli K12 contains 9 open reading frames encoding aldo/keto reductases (AKRs) that are differentially regulated and sequence diverse. A significant amount of data is available for the E. coli AKRs through the availability of gene knockouts and gene expression studies, which adds to the biochemical and kinetic data. This together with the availability of crystal structures for nearly half of the E. coli AKRs and homologues of several others provides an opportunity to look at the diversity of these representative bacterial AKRs. Based around the common AKR fold of (β/α)8 barrel with two additional α-helices, the E. coli AKRs have a loop structure that is more diverse than their mammalian counterparts, creating a variety of active site architectures. Nearly half of the AKRs are expected to be monomeric, but there are examples of dimeric, trimeric and octameric enzymes, as well as diversity in specificity for NAD as well as NADP as a cofactor. However in functional assignments and characterisation of enzyme activities there is a paucity of data when compared to the mammalian AKR enzymes.

Gap-filling analysis of the iJO1366 Escherichia coli metabolic network reconstruction for discovery of metabolic functions

Background

The iJO1366 reconstruction of the metabolic network of Escherichia coli is one of the most complete and accurate metabolic reconstructions available for any organism. Still, because our knowledge of even well-studied model organisms such as this one is incomplete, this network reconstruction contains gaps and possible errors. There are a total of 208 blocked metabolites in iJO1366, representing gaps in the network.

Results

A new model improvement workflow was developed to compare model based phenotypic predictions to experimental data to fill gaps and correct errors. A Keio Collection based dataset of E. coli gene essentiality was obtained from literature data and compared to model predictions. The SMILEY algorithm was then used to predict the most likely missing reactions in the reconstructed network, adding reactions from a KEGG based universal set of metabolic reactions. The feasibility of these putative reactions was determined by comparing updated versions of the model to the experimental dataset, and genes were predicted for the most feasible reactions.

Conclusions

Numerous improvements to the iJO1366 metabolic reconstruction were suggested by these analyses. Experiments were performed to verify several computational predictions, including a new mechanism for growth on myo-inositol. The other predictions made in this study should be experimentally verifiable by similar means. Validating all of the predictions made here represents a substantial but important undertaking.

Genotype-phenotype associations in a nonmodel prokaryote

To help define the biological functions of nonessential genes of Francisella novicida, we measured the growth of arrayed members of a comprehensive transposon mutant library under a variety of nutrition and stress conditions. Mutant phenotypes were identified for 37% of the genes, corresponding to ten carbon source utilization pathways, nine amino acid- and nucleotide-biosynthetic pathways, ten intrinsic antibiotic resistance traits, and six other stress resistance traits. The greatest surprise of the analysis was the large number of genotype-phenotype relationships that were not predictable from studies of Escherichia coli and other model species. The study identified candidate genes for a missing glycolysis function (phosphofructokinase), an unusual proline-biosynthetic pathway, parallel outer membrane lipid asymmetry maintenance systems, and novel antibiotic resistance functions. The analysis provides an evaluation of annotation predictions, identifies cases in which fundamental processes differ from those in model species, and helps create an empirical foundation for understanding virulence and other complex processes.

The value of genome sequences as foundations for analyzing complex traits in nonmodel organisms is limited by the need to rely almost exclusively on sequence similarities to predict gene functions in annotations. Many genes cannot be assigned functions, and some predictions are incorrect or incomplete. Due to these limitations, genome-scale experimental approaches that test and extend bioinformatics-based predictions are sorely needed. In this study, we describe such an approach based on phenotypic analysis of a comprehensive, sequence-defined transposon mutant library.

Genetic mechanism regulating bacterial cell shape and metabolism

The bacterium Escherichia coli is rod-shaped, and a unit cell keeps regular dimensions of about 1.5 microm long and 0.5 microm wide. The rod-shaped cell is composed of two parts: a cylinder in the center and caps at both ends. The length of the cylinder corresponds to the length of the rod cell. A recent paper reported the genetic regulation of the cell length by rodZ. RodZ is a membrane protein with bitopic topology that assembles underneath the cell membrane to form helical filaments along the lateral axis of the cell with the bacterial actin MreB. RodZ filaments probably interact with enzymes that contribute to peptidoglycan synthesis. Cells lacking rodZ shorten only along the lateral axis of the cell so that the cells become round-shaped instead of rod-shaped. Such spheroidal cells consist only of caps due to the loss of almost all of the cylinder. In addition, carbon metabolism is remarkably disturbed by the deficiency of RodZ. This suggests that the transport of nutrients at the surface of the cylinder is reduced in rodZ mutant cells. Thus, cell morphology is also critical for proper metabolism for cell proliferation.

E. coli histidine triad nucleotide binding protein 1 (ecHinT) is a catalytic regulator of D-alanine dehydrogenase (DadA) activity in vivo

Histidine triad nucleotide binding proteins (Hints) are highly conserved members of the histidine triad (HIT) protein superfamily. Hints comprise the most ancient branch of this superfamily and can be found in Archaea, Bacteria, and Eukaryota. Prokaryotic genomes, including a wide diversity of both Gram-negative and Gram-positive bacteria, typically have one Hint gene encoded by hinT (ycfF in E. coli). Despite their ubiquity, the foundational reason for the wide-spread conservation of Hints across all kingdoms of life remains a mystery. In this study, we used a combination of phenotypic screening and complementation analyses with wild-type and hinT knock-out Escherichia coli strains to show that catalytically active ecHinT is required in E. coli for growth on D-alanine as a sole carbon source. We demonstrate that the expression of catalytically active ecHinT is essential for the activity of the enzyme D-alanine dehydrogenase (DadA) (equivalent to D-amino acid oxidase in eukaryotes), a necessary component of the D-alanine catabolic pathway. Site-directed mutagenesis studies revealed that catalytically active C-terminal mutants of ecHinT are unable to activate DadA activity. In addition, we have designed and synthesized the first cell-permeable inhibitor of ecHinT and demonstrated that the wild-type E. coli treated with the inhibitor exhibited the same phenotype observed for the hinT knock-out strain. These results reveal that the catalytic activity and structure of ecHinT is essential for DadA function and therefore alanine metabolism in E. coli. Moreover, they provide the first biochemical evidence linking the catalytic activity of this ubiquitous protein to the biological function of Hints in Escherichia coli.

Environmental dependency of gene knockouts on phenotype microarray analysis in Escherichia coli

Systematic studies have revealed that single gene deletions often display little phenotypic effects under laboratory conditions and that in many cases gene dispensability depends on the experimental conditions. To elucidate the environmental dependency of genes, we analyzed the effects of gene deletions by Phenotype MicroArray™ (PM), a system for quantitative screening of thousands of phenotypes in a high-throughput manner. Here, we proposed a new statistical approach to minimize error inherent in measurements of low respiration rates and find which mutants showed significant phenotypic changes in comparison to the wild-type. We show analyzing results from comprehensive PM assays of 298 single-gene knockout mutants in the Keio collection and two additional mutants under 1,920 different conditions. We focused on isozymes of these genes as simple duplications and analyzed correlations between phenotype changes and protein expression levels. Our results revealed divergence of the environmental dependency of the gene among the knockout genes and have also given some insights into possibilities of alternative pathways and availabilities of information on protein synthesis patterns to classify or predict functions of target genes from systematic phenotype screening.

Dispensability of Escherichia coli's latent pathways

Gene-knockout experiments on single-cell organisms have established that expression of a substantial fraction of genes is not needed for optimal growth. This problem acquired a new dimension with the recent discovery that environmental and genetic perturbations of the bacterium Escherichia coli are followed by the temporary activation of a large number of latent metabolic pathways, which suggests the hypothesis that temporarily activated reactions impact growth and hence facilitate adaptation in the presence of perturbations. Here, we test this hypothesis computationally and find, surprisingly, that the availability of latent pathways consistently offers no growth advantage and tends, in fact, to inhibit growth after genetic perturbations. This is shown to be true even for latent pathways with a known function in alternate conditions, thus extending the significance of this adverse effect beyond apparently nonessential genes. These findings raise the possibility that latent pathway activation is in fact derivative of another, potentially suboptimal, adaptive response.

An automated phenotype-driven approach (GeneForce) for refining metabolic and regulatory models

Integrated constraint-based metabolic and regulatory models can accurately predict cellular growth phenotypes arising from genetic and environmental perturbations. Challenges in constructing such models involve the limited availability of information about transcription factor—gene target interactions and computational methods to quickly refine models based on additional datasets. In this study, we developed an algorithm, GeneForce, to identify incorrect regulatory rules and gene-protein-reaction associations in integrated metabolic and regulatory models. We applied the algorithm to refine integrated models of Escherichia coli and Salmonella typhimurium, and experimentally validated some of the algorithm's suggested refinements. The adjusted E. coli model showed improved accuracy (∼80.0%) for predicting growth phenotypes for 50,557 cases (knockout mutants tested for growth in different environmental conditions). In addition to identifying needed model corrections, the algorithm was used to identify native E. coli genes that, if over-expressed, would allow E. coli to grow in new environments. We envision that this approach will enable the rapid development and assessment of genome-scale metabolic and regulatory network models for less characterized organisms, as such models can be constructed from genome annotations and cis-regulatory network predictions.

Computational models of biological networks are useful for explaining experimental observations and predicting phenotypic behaviors. The construction of genome-scale metabolic and regulatory models is still a labor-intensive process, even with the availability of genome sequences and high-throughput datasets. Since our knowledge about biological systems is incomplete, these models are iteratively refined and validated as we discover new connections in biological networks, and eliminate inconsistencies between model predictions and experimental observations. To enable researchers to quickly determine what causes discrepancies between observed phenotypes and model predictions, we developed a new approach (GeneForce) that automatically corrects integrated metabolic and transcriptional regulatory network models. To illustrate the utility of the approach, we applied the developed method to well-curated models of E. coli metabolism and regulation. We found that the approach significantly improved the accuracy of phenotype predictions and suggested changes needed to the metabolic and/or regulatory models. We also used the approach to identify rescue non-growth phenotypes and to evaluate the conservation of transcriptional regulatory interactions between E. coli and S. typhimurium. The developed approach helps reconcile discrepancies between model predictions and experimental data by hypothesizing required network changes, and helps facilitate the development of new genome-scale models.

Systematic screening of Escherichia coli single-gene knockout mutants for improving recombinant whole-cell biocatalysts

Systematic screening of single-gene knockout collection of Escherichia coli BW25113 (the Keio collection) was performed to select mutants that could enhance the deethylation of 7-ethoxycoumarin catalyzed by CYP154A1. After 96-well plate high-throughput screening followed by test tube assays, four mutants (Delta cpxA, Delta gcvR, Delta glnL, and an unknown-gene-deleted one (Delta uk)) were able to increase the CYP154A1 activity by approximately 1.4-1.7 times compared with that of the control strain. When new mutants were constructed by disrupting individually the cpxA, gcvR, glnL, and uk genes in E. coli BW25113, three of them (Delta cpxA, Delta gcvR, and Delta glnL) showed high levels of CYP154A1 activity. However, the uk-disruptant failed to enhance the CYP154A1 activity, suggesting that the high CYP154A1 activity of the Delta uk mutant in the Keio collection was due to a spontaneous mutation in the chromosome. In-frame deletion mutants of Delta cpxA, Delta gcvR, and Delta glnL also exhibited high enzyme activity, and complementation of these mutations could decrease CYP154A1 activity. These results indicated that the enhancement of the enzyme activity was not caused by polar effects on their neighbor genes. To our knowledge, this is the first report on a genome-wide screening of the genes for deletion to improve the activity of a recombinant whole-cell biocatalyst.

Considerations to improve functional annotations in biological databases

Despite the great effort to design efficient systems allowing the electronic indexation of information concerning genes, proteins, structures, and interactions published daily in scientific journals, some problems are still observed in specific tasks such as functional annotation. The annotation of function is a critical issue for bioinformatic routines, such as for instance, in functional genomics and the further prediction of unknown protein function, which are highly dependent of the quality of existing annotations. Some information management systems evolve to efficiently incorporate information from large-scale projects, but often, annotation of single records from the literature is difficult and slow. In this short report, functional characterizations of a representative sample of the entire set of uncharacterized proteins from Escherichia coli K12 was compiled from Swiss-Prot, PubMed, and EcoCyc and demonstrate a functional annotation deficit in biological databases. Some issues are postulated as causes of the lack of annotation, and different solutions are evaluated and proposed to avoid them. The hope is that as a consequence of these observations, there will be new impetus to improve the speed and quality of functional annotation and ultimately provide updated, reliable information to the scientific community.

High-throughput, quantitative analyses of genetic interactions in E. coli

Large-scale genetic interaction studies provide the basis for defining gene function and pathway architecture. Recent advances in the ability to generate double mutants en masse in Saccharomyces cerevisiae have dramatically accelerated the acquisition of genetic interaction information and the biological inferences that follow. Here we describe a method based on F factor-driven conjugation, which allows for high-throughput generation of double mutants in Escherichia coli. This method, termed genetic interaction analysis technology for E. coli (GIANT-coli), permits us to systematically generate and array double-mutant cells on solid media in high-density arrays. We show that colony size provides a robust and quantitative output of cellular fitness and that GIANT-coli can recapitulate known synthetic interactions and identify previously unidentified negative (synthetic sickness or lethality) and positive (suppressive or epistatic) relationships. Finally, we describe a complementary strategy for genome-wide suppressor-mutant identification. Together, these methods permit rapid, large-scale genetic interaction studies in E. coli.

Systematic genome-wide scanning for genes involved in ATP generation in Escherichia coli

Adenosine 5'-triphosphate (ATP) generation is an essential biological reaction for all living cells. Recently, we developed a Permeable Cell Assay for high-throughput measurement of cellular ATP synthetic activity, mainly resulting from glycolysis [Hara, K.Y., Mori, H., 2006. An efficient method for quantitative determination of cellular ATP synthetic activity. J. Biomol. Screen. 11, 310-317]. By using this method, we determined the cellular ATP synthetic activity in the stationary phase of a complete set of single-gene deletion strains of Escherichia coli. Their activities ranged from a minimum of 2% to a maximum of 445%, relative to parental strains. Deletions of metabolism-related genes frequently caused an increase in the rate of ATP synthetic activity, while activity was reduced by deletions of a variety of functional genes, including many poorly characterized genes. We also demonstrated that the deletion of the ptsG gene doubled ATP-driven glutathione synthesis and increased cellular ATP synthetic activity. Our study also indicated that it should be easy to obtain active strains for ATP synthesis from deletion strains. Overall, the data set of this study may be useful to improve E. coli strains for ATP-dependent industrial processes and, therefore, may be important for the design of so-called cell factories.

A complete collection of single-gene deletion mutants of Acinetobacter baylyi ADP1

We have constructed a collection of single-gene deletion mutants for all dispensable genes of the soil bacterium Acinetobacter baylyi ADP1. A total of 2594 deletion mutants were obtained, whereas 499 (16%) were not, and are therefore candidate essential genes for life on minimal medium. This essentiality data set is 88% consistent with the Escherichia coli data set inferred from the Keio mutant collection profiled for growth on minimal medium, while 80% of the orthologous genes described as essential in Pseudomonas aeruginosa are also essential in ADP1. Several strategies were undertaken to investigate ADP1 metabolism by (1) searching for discrepancies between our essentiality data and current metabolic knowledge, (2) comparing this essentiality data set to those from other organisms, (3) systematic phenotyping of the mutant collection on a variety of carbon sources (quinate, 2-3 butanediol, glucose, etc.). This collection provides a new resource for the study of gene function by forward and reverse genetic approaches and constitutes a robust experimental data source for systems biology approaches.

Cyclic AMP-dependent catabolite repression is the dominant control mechanism of metabolic fluxes under glucose limitation in Escherichia coli

Although a whole arsenal of mechanisms are potentially involved in metabolic regulation, it is largely uncertain when, under which conditions, and to which extent a particular mechanism actually controls network fluxes and thus cellular physiology. Based on (13)C flux analysis of Escherichia coli mutants, we elucidated the relevance of global transcriptional regulation by ArcA, ArcB, Cra, CreB, CreC, Crp, Cya, Fnr, Hns, Mlc, OmpR, and UspA on aerobic glucose catabolism in glucose-limited chemostat cultures at a growth rate of 0.1 h(-1). The by far most relevant control mechanism was cyclic AMP (cAMP)-dependent catabolite repression as the inducer of the phosphoenolpyruvate (PEP)-glyoxylate cycle and thus low tricarboxylic acid cycle fluxes. While all other mutants and the reference E. coli strain exhibited high glyoxylate shunt and PEP carboxykinase fluxes, and thus high PEP-glyoxylate cycle flux, this cycle was essentially abolished in both the Crp and Cya mutants, which lack the cAMP-cAMP receptor protein complex. Most other mutations were phenotypically silent, and only the Cra and Hns mutants exhibited slightly altered flux distributions through PEP carboxykinase and the tricarboxylic acid cycle, respectively. The Cra effect on PEP carboxykinase was probably the consequence of a specific control mechanism, while the Hns effect appears to be unspecific. For central metabolism, the available data thus suggest that a single transcriptional regulation process exerts the dominant control under a given condition and this control is highly specific for a single pathway or cycle within the network.

Insights into the biology of Escherichia coli through structural proteomics

Escherichia coli has historically been an important organism for understanding a multitude of biological processes, and represents a model system as we attempt to simulate the workings of living cells. Many E. coli strains are also important human and animal pathogens for which new therapeutic strategies are required. For both reasons, a more complete and comprehensive understanding of the protein structure complement of E. coli is needed at the genome level. Here, we provide examples of insights into the mechanism and function of bacterial proteins that we have gained through the Bacterial Structural Genomics Initiative (BSGI), focused on medium-throughput structure determination of proteins from E. coli. We describe the structural characterization of several enzymes from the histidine biosynthetic pathway, the structures of three pseudouridine synthases, enzymes that synthesize one of the most abundant modified bases in RNA, as well as the combined use of protein structure and focused functional analysis to decipher functions for hypothetical proteins. Together, these results illustrate the power of structural genomics to contribute to a deeper biological understanding of bacterial processes.

Genome-wide screening of genes affecting glycogen metabolism in Escherichia coli K-12

A systematic and comprehensive gene-disrupted mutant collection of E. coli K-12 was used to identify genes whose deletions affect glycogen accumulation. Of the 3985 non-essential gene mutants of the collection, 35 displayed a glycogen-excess phenotype, whereas 30 displayed either glycogen-less or glycogen-deficient phenotypes. The genes whose deletions affect glycogen accumulation were classified into various functional categories, including energy production, envelope composition and integrity, protein translation and stability, transport of inorganic ions and nucleotides, and metabolism of carbohydrates and amino acids. The overall data indicate that glycogen metabolism is highly interconnected with a wide variety of cellular processes in E. coli.

Systems approach to refining genome annotation

Genome-scale models of Escherichia coli K-12 MG1655 metabolism have been able to predict growth phenotypes in most, but not all, defined growth environments. Here we introduce the use of an optimization-based algorithm that predicts the missing reactions that are required to reconcile computation and experiment when they disagree. The computer-generated hypotheses for missing reactions were verified experimentally in five cases, leading to the functional assignment of eight ORFs (yjjLMN, yeaTU, dctA, idnT, and putP) with two new enzymatic activities and four transport functions. This study thus demonstrates the use of systems analysis to discover metabolic and transport functions and their genetic basis by a combination of experimental and computational approaches.

Experimental and computational assessment of conditionally essential genes in Escherichia coli

Genome-wide gene essentiality data sets are becoming available for Escherichia coli, but these data sets have yet to be analyzed in the context of a genome scale model. Here, we present an integrative model-driven analysis of the Keio E. coli mutant collection screened in this study on glycerol-supplemented minimal medium. Out of 3,888 single-deletion mutants tested, 119 mutants were unable to grow on glycerol minimal medium. These conditionally essential genes were then evaluated using a genome scale metabolic and transcriptional-regulatory model of E. coli, and it was found that the model made the correct prediction in approximately 91% of the cases. The discrepancies between model predictions and experimental results were analyzed in detail to indicate where model improvements could be made or where the current literature lacks an explanation for the observed phenotypes. The identified set of essential genes and their model-based analysis indicates that our current understanding of the roles these essential genes play is relatively clear and complete. Furthermore, by analyzing the data set in terms of metabolic subsystems across multiple genomes, we can project which metabolic pathways are likely to play equally important roles in other organisms. Overall, this work establishes a paradigm that will drive model enhancement while simultaneously generating hypotheses that will ultimately lead to a better understanding of the organism.

The yfhQ gene of Escherichia coli encodes a tRNA:Cm32/Um32 methyltransferase

Background

Naturally occurring tRNAs contain numerous modified nucleosides. They are formed by enzymatic modification of the primary transcripts during the complex RNA maturation process. In model organisms Escherichia coli and Saccharomyces cerevisiae most enzymes involved in this process have been identified. Interestingly, it was found that tRNA methylation, one of the most common modifications, can be introduced by S-adenosyl-L-methionine (AdoMet)-dependent methyltransferases (MTases) that belong to two structurally and phylogenetically unrelated protein superfamilies: RFM and SPOUT.

Results

As a part of a large-scale project aiming at characterization of a complete set of RNA modification enzymes of model organisms, we have studied the Escherichia coli proteins YibK, LasT, YfhQ, and YbeA for their ability to introduce the last unassigned methylations of ribose at positions 32 and 34 of the tRNA anticodon loop. We found that YfhQ catalyzes the AdoMet-dependent formation of Cm32 or Um32 in tRNA^Ser1 and tRNA^Gln2 and that an E. coli strain with a disrupted yfhQ gene lacks the tRNA:Cm32/Um32 methyltransferase activity. Thus, we propose to rename YfhQ as TrMet(Xm32) according to the recently proposed, uniform nomenclature for all RNA modification enzymes, or TrmJ, according to the traditional nomenclature for bacterial tRNA MTases.

Conclusion

Our results reveal that methylation at position 32 is carried out by completely unrelated TrMet(Xm32) enzymes in eukaryota and prokaryota (RFM superfamily member Trm7 and SPOUT superfamily member TrmJ, respectively), mirroring the scenario observed in the case of the m¹G37 modification (introduced by the RFM member Trm5 in eukaryota and archaea, and by the SPOUT member TrmD in bacteria).

Seeking completeness in bacterial mutant hunts

The identification of most or all of the genetic functions that are required for a particular biological process could be achieved through phenotypic studies of high genome-coverage mutant collections. Technologies for creating such collections, in the form of mixed populations or individually arrayed sequence-defined mutants, are now available for numerous bacterial species. The analysis of mixed mutant collections using microarray-based detection procedures appears to be particularly effective in identifying functions required for complex processes such as virulence. The phenotypic analysis of sequence-defined mutant libraries provides a virtually complete identification of nonessential genes required for processes for which suitable screens can be devised. Such libraries also serve as a source of individual mutants for examining the biological relevance of gene associations revealed by transcriptional profiling or homology.

Construction of Escherichia coli K-12 in-frame, single-gene knockout mutants: the Keio collection

We have systematically made a set of precisely defined, single-gene deletions of all nonessential genes in Escherichia coli K-12. Open-reading frame coding regions were replaced with a kanamycin cassette flanked by FLP recognition target sites by using a one-step method for inactivation of chromosomal genes and primers designed to create in-frame deletions upon excision of the resistance cassette. Of 4288 genes targeted, mutants were obtained for 3985. To alleviate problems encountered in high-throughput studies, two independent mutants were saved for every deleted gene. These mutants—the ‘Keio collection'—provide a new resource not only for systematic analyses of unknown gene functions and gene regulatory networks but also for genome-wide testing of mutational effects in a common strain background, E. coli K-12 BW25113. We were unable to disrupt 303 genes, including 37 of unknown function, which are candidates for essential genes. Distribution is being handled via GenoBase (http://ecoli.aist-nara.ac.jp/).