eSGA: E. coli synthetic genetic array analysis

Defined single-gene and multi-gene deletion mutant collections in Salmonella enterica sv Typhimurium

We constructed two collections of targeted single gene deletion (SGD) mutants and two collections of targeted multi-gene deletion (MGD) mutants in Salmonella enterica sv Typhimurium 14028s. The SGD mutant collections contain (1), 3517 mutants in which a single gene is replaced by a cassette containing a kanamycin resistance (KanR) gene oriented in the sense direction (SGD-K), and (2), 3376 mutants with a chloramphenicol resistance gene (CamR) oriented in the antisense direction (SGD-C). A combined total of 3773 individual genes were deleted across these SGD collections. The MGD collections contain mutants bearing deletions of contiguous regions of three or more genes and include (3), 198 mutants spanning 2543 genes replaced by a KanR cassette (MGD-K), and (4), 251 mutants spanning 2799 genes replaced by a CamR cassette (MGD-C). Overall, 3476 genes were deleted in at least one MGD collection. The collections with different antibiotic markers permit construction of all viable combinations of mutants in the same background. Together, the libraries allow hierarchical screening of MGDs for different phenotypic followed by screening of SGDs within the target MGD regions. The mutants of these collections are stored at BEI Resources (www.beiresources.org) and publicly available.

Genetic interaction analysis of point mutations enables interrogation of gene function at a residue-level resolution: exploring the applications of high-resolution genetic interaction mapping of point mutations

We have achieved a residue-level resolution of genetic interaction mapping - a technique that measures how the function of one gene is affected by the alteration of a second gene - by analyzing point mutations. Here, we describe how to interpret point mutant genetic interactions, and outline key applications for the approach, including interrogation of protein interaction interfaces and active sites, and examination of post-translational modifications. Genetic interaction analysis has proven effective for characterizing cellular processes; however, to date, systematic high-throughput genetic interaction screens have relied on gene deletions or knockdowns, which limits the resolution of gene function analysis and poses problems for multifunctional genes. Our point mutant approach addresses these issues, and further provides a tool for in vivo structure-function analysis that complements traditional biophysical methods. We also discuss the potential for genetic interaction mapping of point mutations in human cells and its application to personalized medicine.

Colony-live--a high-throughput method for measuring microbial colony growth kinetics--reveals diverse growth effects of gene knockouts in Escherichia coli

Background

Precise quantitative growth measurements and detection of small growth changes in high-throughput manner is essential for fundamental studies of bacterial cell. However, an inherent tradeoff for measurement quality in high-throughput methods sacrifices some measurement quality. A key challenge has been how to enhance measurement quality without sacrificing throughput.

Results

We developed a new high-throughput measurement system, termed Colony-live. Here we show that Colony-live provides accurate measurement of three growth values (lag time of growth (LTG), maximum growth rate (MGR), and saturation point growth (SPG)) by visualizing colony growth over time. By using a new normalization method for colony growth, Colony-live gives more precise and accurate growth values than the conventional method. We demonstrated the utility of Colony-live by measuring growth values for the entire Keio collection of Escherichia coli single-gene knockout mutants. By using Colony-live, we were able to identify subtle growth defects of single-gene knockout mutants that were undetectable by the conventional method quantified by fixed time-point camera imaging. Further, Colony-live can reveal genes that influence the length of the lag-phase and the saturation point of growth.

Conclusions

Measurement quality is critical to achieving the resolution required to identify unique phenotypes among a diverse range of phenotypes. Sharing high-quality genome-wide datasets should benefit many researchers who are interested in specific gene functions or the architecture of cellular systems. Our Colony-live system provides a new powerful tool to accelerate accumulation of knowledge of microbial growth phenotypes.

gitter: a robust and accurate method for quantification of colony sizes from plate images

Colony-based screens that quantify the fitness of clonal populations on solid agar plates are perhaps the most important source of genome-scale functional information in microorganisms. The images of ordered arrays of mutants produced by such experiments can be difficult to process because of laboratory-specific plate features, morphed colonies, plate edges, noise, and other artifacts. Most of the tools developed to address this problem are optimized to handle a single setup and do not work out of the box in other settings. We present gitter, an image analysis tool for robust and accurate processing of images from colony-based screens. gitter works by first finding the grid of colonies from a preprocessed image and then locating the bounds of each colony separately. We show that gitter produces comparable colony sizes to other tools in simple cases but outperforms them by being able to handle a wider variety of screens and more accurately quantify colony sizes from difficult images. gitter is freely available as an R package from http://cran.r-project.org/web/packages/gitter under the LGPL. Tutorials and demos can be found at http://omarwagih.github.io/gitter.

Death by a thousand cuts: the challenges and diverse landscape of lignocellulosic hydrolysate inhibitors

Lignocellulosic hydrolysate (LCH) inhibitors are a large class of bioactive molecules that arise from pretreatment, hydrolysis, and fermentation of plant biomass. These diverse compounds reduce lignocellulosic biofuel yields by inhibiting cellular processes and diverting energy into cellular responses. LCH inhibitors present one of the most significant challenges to efficient biofuel production by microbes. Development of new strains that lessen the effects of LCH inhibitors is an economically favorable strategy relative to expensive detoxification methods that also can reduce sugar content in deconstructed biomass. Systems biology analyses and metabolic modeling combined with directed evolution and synthetic biology are successful strategies for biocatalyst development, and methods that leverage state-of-the-art tools are needed to overcome inhibitors more completely. This perspective considers the energetic costs of LCH inhibitors and technologies that can be used to overcome their drain on conversion efficiency. We suggest academic and commercial research groups could benefit by sharing data on LCH inhibitors and implementing "translational biofuel research."

Something old, something new: revisiting natural products in antibiotic drug discovery

Antibiotic discovery is in crisis. Despite a growing need for new drugs resulting from the increasing number of multi-antibiotic-resistant pathogens, there have been only a handful of new antibiotics approved for clinical use in the past 2 decades. Faced with scientific, economic, and regulatory challenges, the pharmaceutical sector seems unable to respond to what has been called an “apocalyptic” threat. Natural products produced by bacteria and fungi are genetically encoded products of natural selection that have been the mainstay sources of the antibiotics in current clinical use. The pharmaceutical industry has largely abandoned these compounds in favor of large libraries of synthetic molecules because of difficulties in identifying new natural product antibiotics scaffolds. Advances in next-generation genome sequencing, bioinformatics, and analytical chemistry are combining to overcome barriers to natural products. Coupled with new strategies in antibiotic discovery, including inhibition of resistance, novel drug combinations, and new targets, natural products are poised for a renaissance to address what is a pressing health care crisis.

The binary protein-protein interaction landscape of Escherichia coli

Efforts to map the Escherichia coli interactome have identified several hundred macromolecular complexes, but direct binary protein-protein interactions (PPIs) have not been surveyed on a large scale. Here we performed yeast two-hybrid screens of 3,305 baits against 3,606 preys (∼70% of the E. coli proteome) in duplicate to generate a map of 2,234 interactions, which approximately doubles the number of known binary PPIs in E. coli. Integration of binary PPI and genetic-interaction data revealed functional dependencies among components involved in cellular processes, including envelope integrity, flagellum assembly and protein quality control. Many of the binary interactions that we could map in multiprotein complexes were informative regarding internal topology of complexes and indicated that interactions in complexes are substantially more conserved than those interactions connecting different complexes. This resource will be useful for inferring bacterial gene function and provides a draft reference of the basic physical wiring network of this evolutionarily important model microbe.

Quantitative genome-wide genetic interaction screens reveal global epistatic relationships of protein complexes in Escherichia coli

Large-scale proteomic analyses in Escherichia coli have documented the composition and physical relationships of multiprotein complexes, but not their functional organization into biological pathways and processes. Conversely, genetic interaction (GI) screens can provide insights into the biological role(s) of individual gene and higher order associations. Combining the information from both approaches should elucidate how complexes and pathways intersect functionally at a systems level. However, such integrative analysis has been hindered due to the lack of relevant GI data. Here we present a systematic, unbiased, and quantitative synthetic genetic array screen in E. coli describing the genetic dependencies and functional cross-talk among over 600,000 digenic mutant combinations. Combining this epistasis information with putative functional modules derived from previous proteomic data and genomic context-based methods revealed unexpected associations, including new components required for the biogenesis of iron-sulphur and ribosome integrity, and the interplay between molecular chaperones and proteases. We find that functionally-linked genes co-conserved among γ-proteobacteria are far more likely to have correlated GI profiles than genes with divergent patterns of evolution. Overall, examining bacterial GIs in the context of protein complexes provides avenues for a deeper mechanistic understanding of core microbial systems.

Genome-wide genetic interaction (GI) screens have been performed in yeast, but no analogous large-scale studies have yet been reported for bacteria. Here, we have used E. coli synthetic genetic array (eSGA) technology developed by our group to quantitatively map GIs to reveal epistatic dependencies and functional cross-talk among ∼600,000 digenic mutant combinations. By combining this epistasis information with functional modules derived by our group's earlier efforts from proteomic and genomic context (GC)-based methods, we identify several unexpected pathway-level dependencies, functional links between protein complexes, and biological roles of uncharacterized bacterial gene products. As part of the study, two of our pathway predictions from GI screens were validated experimentally, where we confirmed the role of these new components in iron-sulphur biogenesis and ribosome integrity. We also extrapolated the epistatic connectivity diagram of E. coli to 233 distantly related γ-proteobacterial species lacking GI information, and identified co-conserved genes and functional modules important for bacterial pathogenesis. Overall, this study describes the first genome-scale map of GIs in gram-negative bacterium, and through integrative analysis with previously derived protein-protein and GC-based interaction networks presents a number of novel insights into the architecture of bacterial pathways that could not have been discerned through either network alone.

The MoxR ATPase RavA and its cofactor ViaA interact with the NADH:ubiquinone oxidoreductase I in Escherichia coli

MoxR ATPases are widespread throughout bacteria and archaea. The experimental evidence to date suggests that these proteins have chaperone-like roles in facilitating the maturation of dedicated protein complexes that are functionally diverse. In Escherichia coli, the MoxR ATPase RavA and its putative cofactor ViaA are found to exist in early stationary-phase cells at 37 °C at low levels of about 350 and 90 molecules per cell, respectively. Both proteins are predominantly localized to the cytoplasm, but ViaA was also unexpectedly found to localize to the cell membrane. Whole genome microarrays and synthetic lethality studies both indicated that RavA-ViaA are genetically linked to Fe-S cluster assembly and specific respiratory pathways. Systematic analysis of mutant strains of ravA and viaA indicated that RavA-ViaA sensitizes cells to sublethal concentrations of aminoglycosides. Furthermore, this effect was dependent on RavA's ATPase activity, and on the presence of specific subunits of NADH:ubiquinone oxidoreductase I (Nuo Complex, or Complex I). Importantly, both RavA and ViaA were found to physically interact with specific Nuo subunits. We propose that RavA-ViaA facilitate the maturation of the Nuo complex.

Exploring mitochondrial system properties of neurodegenerative diseases through interactome mapping

Mitochondria are double membraned, dynamic organelles that are required for a large number of cellular processes, and defects in their function have emerged as causative factors for a growing number of human disorders and are highly associated with cancer, metabolic, and neurodegenerative (ND) diseases. Biochemical and genetic investigations have uncovered small numbers of candidate mitochondrial proteins (MPs) involved in ND disease, but given the diversity of processes affected by MP function and the difficulty of detecting interactions involving these proteins, many more likely remain unknown. However, high-throughput proteomic and genomic approaches developed in genetically tractable model prokaryotes and lower eukaryotes have proven to be effective tools for querying the physical (protein-protein) and functional (gene-gene) relationships between diverse types of proteins, including cytosolic and membrane proteins. In this review, we highlight how experimental and computational approaches developed recently by our group and others can be effectively used towards elucidating the mitochondrial interactome in an unbiased and systematic manner to uncover network-based connections. We discuss how the knowledge from the resulting interaction networks can effectively contribute towards the identification of new mitochondrial disease gene candidates, and thus further clarify the role of mitochondrial biology and the complex etiologies of ND disease.

BIOLOGICAL SIGNIFICANCE

Biochemical and genetic investigations have uncovered small numbers of candidate mitochondrial proteins (MPs) involved in neurodegenerative (ND) diseases, but given the diversity of processes affected by MP function and the difficulty of detecting interactions involving these proteins, many more likely remain unknown. Large-scale proteomic and genomic approaches developed in model prokaryotes and lower eukaryotes have proven to be effective tools for querying the physical (protein-protein) and functional (gene-gene) relationships between diverse types of proteins. Extension of this new framework to the mitochondrial sub-system in human will likewise provide a universally informative systems-level view of the physical and functional landscape for exploring the evolutionary principles underlying mitochondrial function. In this review, we highlight how experimental and computational approaches developed recently by our group and others can be effectively used towards elucidating the mitochondrial interactome in an unbiased and systematic manner to uncover network-based connections. We anticipate that the knowledge from these resulting interaction networks can effectively contribute towards the identification of new mitochondrial disease gene candidates, and thus foster a deeper molecular understanding of mitochondrial biology as well as the etiology of mitochondrial diseases. This article is part of a Special Issue: Can Proteomics Fill the Gap Between Genomics and Phenotypes?

High-resolution network biology: connecting sequence with function

Proteins are not monolithic entities; rather, they can contain multiple domains that mediate distinct interactions, and their functionality can be regulated through post-translational modifications at multiple distinct sites. Traditionally, network biology has ignored such properties of proteins and has instead examined either the physical interactions of whole proteins or the consequences of removing entire genes. In this Review, we discuss experimental and computational methods to increase the resolution of protein-protein, genetic and drug-gene interaction studies to the domain and residue levels. Such work will be crucial for using interaction networks to connect sequence and structural information, and to understand the biological consequences of disease-associated mutations, which will hopefully lead to more effective therapeutic strategies.

From structure to systems: high-resolution, quantitative genetic analysis of RNA polymerase II

RNA polymerase II (RNAPII) lies at the core of dynamic control of gene expression. Using 53 RNAPII point mutants, we generated a point mutant epistatic miniarray profile (pE-MAP) comprising ∼60,000 quantitative genetic interactions in Saccharomyces cerevisiae. This analysis enabled functional assignment of RNAPII subdomains and uncovered connections between individual regions and other protein complexes. Using splicing microarrays and mutants that alter elongation rates in vitro, we found an inverse relationship between RNAPII speed and in vivo splicing efficiency. Furthermore, the pE-MAP classified fast and slow mutants that favor upstream and downstream start site selection, respectively. The striking coordination of polymerization rate with transcription initiation and splicing suggests that transcription rate is tuned to regulate multiple gene expression steps. The pE-MAP approach provides a powerful strategy to understand other multifunctional machines at amino acid resolution.

Systematic triple-mutant analysis uncovers functional connectivity between pathways involved in chromosome regulation

Genetic interactions reveal the functional relationships between pairs of genes. In this study, we describe a method for the systematic generation and quantitation of triple mutants, termed triple-mutant analysis (TMA). We have used this approach to interrogate partially redundant pairs of genes in S. cerevisiae, including ASF1 and CAC1, two histone chaperones. After subjecting asf1Δ cac1Δ to TMA, we found that the Swi/Snf Rdh54 protein compensates for the absence of Asf1 and Cac1. Rdh54 more strongly associates with the chromatin apparatus and the pericentromeric region in the double mutant. Moreover, Asf1 is responsible for the synthetic lethality observed in cac1Δ strains lacking the HIRA-like proteins. A similar TMA was carried out after deleting both CLB5 and CLB6, cyclins that regulate DNA replication, revealing a strong functional connection to chromosome segregation. This approach can reveal functional redundancies that cannot be uncovered through traditional double-mutant analyses.

SGAtools: one-stop analysis and visualization of array-based genetic interaction screens

Screening genome-wide sets of mutants for fitness defects provides a simple but powerful approach for exploring gene function, mapping genetic networks and probing mechanisms of drug action. For yeast and other microorganisms with global mutant collections, genetic or chemical-genetic interactions can be effectively quantified by growing an ordered array of strains on agar plates as individual colonies, and then scoring the colony size changes in response to a genetic or environmental perturbation. To do so, requires efficient tools for the extraction and analysis of quantitative data. Here, we describe SGAtools (http://sgatools.ccbr.utoronto.ca), a web-based analysis system for designer genetic screens. SGAtools outlines a series of guided steps that allow the user to quantify colony sizes from images of agar plates, correct for systematic biases in the observations and calculate a fitness score relative to a control experiment. The data can also be visualized online to explore the colony sizes on individual plates, view the distribution of resulting scores, highlight genes with the strongest signal and perform Gene Ontology enrichment analysis.

Reprint of: Iron/sulfur proteins biogenesis in prokaryotes: formation, regulation and diversity

Iron/sulfur centers are key cofactors of proteins intervening in multiple conserved cellular processes, such as gene expression, DNA repair, RNA modification, central metabolism and respiration. Mechanisms allowing Fe/S centers to be assembled, and inserted into polypeptides have attracted much attention in the last decade, both in eukaryotes and prokaryotes. Basic principles and recent advances in our understanding of the prokaryotic Fe/S biogenesis ISC and SUF systems are reviewed in the present communication. Most studies covered stem from investigations in Escherichia coli and Azotobacter vinelandii. Remarkable insights were brought about by complementary structural, spectroscopic, biochemical and genetic studies. Highlights of the recent years include scaffold mediated assembly of Fe/S cluster, A-type carriers mediated delivery of clusters and regulatory control of Fe/S homeostasis via a set of interconnected genetic regulatory circuits. Also, the importance of Fe/S biosynthesis systems in mediating soft metal toxicity was documented. A brief account of the Fe/S biosynthesis systems diversity as present in current databases is given here. Moreover, Fe/S biosynthesis factors have themselves been the object of molecular tailoring during evolution and some examples are discussed here. An effort was made to provide, based on the E. coli system, a general classification associating a given domain with a given function such as to help next search and annotation of genomes. This article is part of a Special Issue entitled: Metals in Bioenergetics and Biomimetics Systems.

Physical and functional interactions of a monothiol glutaredoxin and an iron sulfur cluster carrier protein with the sulfur-donating radical S-adenosyl-L-methionine enzyme MiaB

The biosynthesis of iron sulfur (FeS) clusters, their trafficking from initial assembly on scaffold proteins via carrier proteins to final incorporation into FeS apoproteins, is a highly coordinated process enabled by multiprotein systems encoded in iscRSUAhscBAfdx and sufABCDSE operons in Escherichia coli. Although these systems are believed to encode all factors required for initial cluster assembly and transfer to FeS carrier proteins, accessory factors such as monothiol glutaredoxin, GrxD, and the FeS carrier protein NfuA are located outside of these defined systems. These factors have been suggested to function both as shuttle proteins acting to transfer clusters between scaffold and carrier proteins and in the final stages of FeS protein assembly by transferring clusters to client FeS apoproteins. Here we implicate both of these factors in client protein interactions. We demonstrate specific interactions between GrxD, NfuA, and the methylthiolase MiaB, a radical S-adenosyl-L-methionine-dependent enzyme involved in the maturation of a subset of tRNAs. We show that GrxD and NfuA physically interact with MiaB with affinities compatible with an in vivo function. We furthermore demonstrate that NfuA is able to transfer its cluster in vitro to MiaB, whereas GrxD is unable to do so. The relevance of these interactions was demonstrated by linking the activity of MiaB with GrxD and NfuA in vivo. We observe a severe defect in in vivo MiaB activity in cells lacking both GrxD and NfuA, suggesting that these proteins could play complementary roles in maturation and repair of MiaB.

Comprehensive mapping of DNA damage: from static genetic maps to condition-specific maps

DNA damage can dramatically affect the cell; thus, cells developed multiple pathways to detect and repair such damage. In this issue, Guénolé et al. (2013) systematically map genetic interactions in different DNA damage conditions, uncovering specific repair pathways.

The contribution of systematic approaches to characterizing the proteins and functions of the endoplasmic reticulum

The endoplasmic reticulum (ER) is a complex organelle responsible for a range of functions including protein folding and secretion, lipid biosynthesis, and ion homeostasis. Despite its central and essential roles in eukaryotic cells during development, growth, and disease, many ER proteins are poorly characterized. Moreover, the range of biochemical reactions that occur within the ER membranes, let alone how these different activities are coordinated, is not yet defined. In recent years, focused studies on specific ER functions have been complemented by systematic approaches and innovative technologies for high-throughput analysis of the location, levels, and biological impact of given components. This article focuses on the recent progress of these efforts, largely pioneered in the budding yeast Saccharomyces cerevisiae, and also addresses how future systematic studies can be geared to uncover the "dark matter" of uncharted ER functions.

A systematic mammalian genetic interaction map reveals pathways underlying ricin susceptibility

Genetic interaction (GI) maps, comprising pairwise measures of how strongly the function of one gene depends on the presence of a second, have enabled the systematic exploration of gene function in microorganisms. Here, we present a two-stage strategy to construct high-density GI maps in mammalian cells. First, we use ultracomplex pooled shRNA libraries (25 shRNAs/gene) to identify high-confidence hit genes for a given phenotype and effective shRNAs. We then construct double-shRNA libraries from these to systematically measure GIs between hits. A GI map focused on ricin susceptibility broadly recapitulates known pathways and provides many unexpected insights. These include a noncanonical role for COPI, a previously uncharacterized protein complex affecting toxin clearance, a specialized role for the ribosomal protein RPS25, and functionally distinct mammalian TRAPP complexes. The ability to rapidly generate mammalian GI maps provides a potentially transformative tool for defining gene function and designing combination therapies based on synergistic pairs.

Iron/sulfur proteins biogenesis in prokaryotes: formation, regulation and diversity

Iron/sulfur centers are key cofactors of proteins intervening in multiple conserved cellular processes, such as gene expression, DNA repair, RNA modification, central metabolism and respiration. Mechanisms allowing Fe/S centers to be assembled, and inserted into polypeptides have attracted much attention in the last decade, both in eukaryotes and prokaryotes. Basic principles and recent advances in our understanding of the prokaryotic Fe/S biogenesis ISC and SUF systems are reviewed in the present communication. Most studies covered stem from investigations in Escherichia coli and Azotobacter vinelandii. Remarkable insights were brought about by complementary structural, spectroscopic, biochemical and genetic studies. Highlights of the recent years include scaffold mediated assembly of Fe/S cluster, A-type carriers mediated delivery of clusters and regulatory control of Fe/S homeostasis via a set of interconnected genetic regulatory circuits. Also, the importance of Fe/S biosynthesis systems in mediating soft metal toxicity was documented. A brief account of the Fe/S biosynthesis systems diversity as present in current databases is given here. Moreover, Fe/S biosynthesis factors have themselves been the object of molecular tailoring during evolution and some examples are discussed here. An effort was made to provide, based on the E. coli system, a general classification associating a given domain with a given function such as to help next search and annotation of genomes. This article is part of a Special Issue entitled: Metals in Bioenergetics and Biomimetics Systems.

The iron-sulfur cluster assembly machineries in plants: current knowledge and open questions

Many metabolic pathways and cellular processes occurring in most sub-cellular compartments depend on the functioning of iron-sulfur (Fe-S) proteins, whose cofactors are assembled through dedicated protein machineries. Recent advances have been made in the knowledge of the functions of individual components through a combination of genetic, biochemical and structural approaches, primarily in prokaryotes and non-plant eukaryotes. Whereas most of the components of these machineries are conserved between kingdoms, their complexity is likely increased in plants owing to the presence of additional assembly proteins and to the existence of expanded families for several assembly proteins. This review focuses on the new actors discovered in the past few years, such as glutaredoxin, BOLA and NEET proteins as well as MIP18, MMS19, TAH18, DRE2 for the cytosolic machinery, which are integrated into a model for the plant Fe-S cluster biogenesis systems. It also discusses a few issues currently subjected to an intense debate such as the role of the mitochondrial frataxin and of glutaredoxins, the functional separation between scaffold, carrier and iron-delivery proteins and the crosstalk existing between different organelles.

Getting the most out of parasitic helminth transcriptomes using HelmDB: implications for biology and biotechnology

Compounded by a massive global food shortage, many parasitic diseases have a devastating, long-term impact on animal and human health and welfare worldwide. Parasitic helminths (worms) affect the health of billions of animals. Unlocking the systems biology of these neglected pathogens will underpin the design of new and improved interventions against them. Currently, the functional annotation of genomic and transcriptomic sequence data for socio-economically important parasitic worms relies almost exclusively on comparative bioinformatic analyses using model organism- and other databases. However, many genes and gene products of parasitic helminths (often >50%) cannot be annotated using this approach, because they are specific to parasites and/or do not have identifiable homologs in other organisms for which sequence data are available. This inability to fully annotate transcriptomes and predicted proteomes is a major challenge and constrains our understanding of the biology of parasites, interactions with their hosts and of parasitism and the pathogenesis of disease on a molecular level. In the present article, we compiled transcriptomic data sets of key, socioeconomically important parasitic helminths, and constructed and validated a curated database, called HelmDB (www.helmdb.org). We demonstrate how this database can be used effectively for the improvement of functional annotation by employing data integration and clustering. Importantly, HelmDB provides a practical and user-friendly toolkit for sequence browsing and comparative analyses among divergent helminth groups (including nematodes and trematodes), and should be readily adaptable and applicable to a wide range of other organisms. This web-based, integrative database should assist 'systems biology' studies of parasitic helminths, and the discovery and prioritization of novel drug and vaccine targets. This focus provides a pathway toward developing new and improved approaches for the treatment and control of parasitic diseases, with the potential for important biotechnological outcomes.

Mapping bacterial functional networks and pathways in Escherichia Coli using synthetic genetic arrays

Phenotypes are determined by a complex series of physical (e.g. protein-protein) and functional (e.g. gene-gene or genetic) interactions (GI)(1). While physical interactions can indicate which bacterial proteins are associated as complexes, they do not necessarily reveal pathway-level functional relationships1. GI screens, in which the growth of double mutants bearing two deleted or inactivated genes is measured and compared to the corresponding single mutants, can illuminate epistatic dependencies between loci and hence provide a means to query and discover novel functional relationships(2). Large-scale GI maps have been reported for eukaryotic organisms like yeast(3-7), but GI information remains sparse for prokaryotes(8), which hinders the functional annotation of bacterial genomes. To this end, we and others have developed high-throughput quantitative bacterial GI screening methods(9, 10). Here, we present the key steps required to perform quantitative E. coli Synthetic Genetic Array (eSGA) screening procedure on a genome-scale(9), using natural bacterial conjugation and homologous recombination to systemically generate and measure the fitness of large numbers of double mutants in a colony array format. Briefly, a robot is used to transfer, through conjugation, chloramphenicol (Cm) - marked mutant alleles from engineered Hfr (High frequency of recombination) 'donor strains' into an ordered array of kanamycin (Kan) - marked F- recipient strains. Typically, we use loss-of-function single mutants bearing non-essential gene deletions (e.g. the 'Keio' collection(11)) and essential gene hypomorphic mutations (i.e. alleles conferring reduced protein expression, stability, or activity(9, 12, 13)) to query the functional associations of non-essential and essential genes, respectively. After conjugation and ensuing genetic exchange mediated by homologous recombination, the resulting double mutants are selected on solid medium containing both antibiotics. After outgrowth, the plates are digitally imaged and colony sizes are quantitatively scored using an in-house automated image processing system(14). GIs are revealed when the growth rate of a double mutant is either significantly better or worse than expected(9). Aggravating (or negative) GIs often result between loss-of-function mutations in pairs of genes from compensatory pathways that impinge on the same essential process(2). Here, the loss of a single gene is buffered, such that either single mutant is viable. However, the loss of both pathways is deleterious and results in synthetic lethality or sickness (i.e. slow growth). Conversely, alleviating (or positive) interactions can occur between genes in the same pathway or protein complex(2) as the deletion of either gene alone is often sufficient to perturb the normal function of the pathway or complex such that additional perturbations do not reduce activity, and hence growth, further. Overall, systematically identifying and analyzing GI networks can provide unbiased, global maps of the functional relationships between large numbers of genes, from which pathway-level information missed by other approaches can be inferred(9).

Hierarchical modularity and the evolution of genetic interactomes across species

To date, cross-species comparisons of genetic interactomes have been restricted to small or functionally related gene sets, limiting our ability to infer evolutionary trends. To facilitate a more comprehensive analysis, we constructed a genome-scale epistasis map (E-MAP) for the fission yeast Schizosaccharomyces pombe, providing phenotypic signatures for ~60% of the nonessential genome. Using these signatures, we generated a catalog of 297 functional modules, and we assigned function to 144 previously uncharacterized genes, including mRNA splicing and DNA damage checkpoint factors. Comparison with an integrated genetic interactome from the budding yeast Saccharomyces cerevisiae revealed a hierarchical model for the evolution of genetic interactions, with conservation highest within protein complexes, lower within biological processes, and lowest between distinct biological processes. Despite the large evolutionary distance and extensive rewiring of individual interactions, both networks retain conserved features and display similar levels of functional crosstalk between biological processes, suggesting general design principles of genetic interactomes.

Conserved rules govern genetic interaction degree across species

Background

Synthetic genetic interactions have recently been mapped on a genome scale in the budding yeast Saccharomyces cerevisiae, providing a functional view of the central processes of eukaryotic life. Currently, comprehensive genetic interaction networks have not been determined for other species, and we therefore sought to model conserved aspects of genetic interaction networks in order to enable the transfer of knowledge between species.

Results

Using a combination of physiological and evolutionary properties of genes, we built models that successfully predicted the genetic interaction degree of S. cerevisiae genes. Importantly, a model trained on S. cerevisiae gene features and degree also accurately predicted interaction degree in the fission yeast Schizosaccharomyces pombe, suggesting that many of the predictive relationships discovered in S. cerevisiae also hold in this evolutionarily distant yeast. In both species, high single mutant fitness defect, protein disorder, pleiotropy, protein-protein interaction network degree, and low expression variation were significantly predictive of genetic interaction degree. A comparison of the predicted genetic interaction degrees of S. pombe genes to the degrees of S. cerevisiae orthologs revealed functional rewiring of specific biological processes that distinguish these two species. Finally, predicted differences in genetic interaction degree were independently supported by differences in co-expression relationships of the two species.

Conclusions

Our findings show that there are common relationships between gene properties and genetic interaction network topology in two evolutionarily distant species. This conservation allows use of the extensively mapped S. cerevisiae genetic interaction network as an orthology-independent reference to guide the study of more complex species.

Predicting synthetic lethal genetic interactions in Saccharomyces cerevisiae using short polypeptide clusters

BACKGROUND

Protein synthetic lethal genetic interactions are useful to define functional relationships between proteins and pathways. However, the molecular mechanism of synthetic lethal genetic interactions remains unclear.

RESULTS

In this study we used the clusters of short polypeptide sequences, which are typically shorter than the classically defined protein domains, to characterize the functionalities of proteins. We developed a framework to identify significant short polypeptide clusters from yeast protein sequences, and then used these short polypeptide clusters as features to predict yeast synthetic lethal genetic interactions. The short polypeptide clusters based approach provides much higher coverage for predicting yeast synthetic lethal genetic interactions. Evaluation using experimental data sets showed that the short polypeptide clusters based approach is superior to the previous protein domain based one.

CONCLUSION

We were able to achieve higher performance in yeast synthetic lethal genetic interactions prediction using short polypeptide clusters as features. Our study suggests that the short polypeptide cluster may help better understand the functionalities of proteins.

Multiple genetic interaction experiments provide complementary information useful for gene function prediction

Genetic interactions help map biological processes and their functional relationships. A genetic interaction is defined as a deviation from the expected phenotype when combining multiple genetic mutations. In Saccharomyces cerevisiae, most genetic interactions are measured under a single phenotype - growth rate in standard laboratory conditions. Recently genetic interactions have been collected under different phenotypic readouts and experimental conditions. How different are these networks and what can we learn from their differences? We conducted a systematic analysis of quantitative genetic interaction networks in yeast performed under different experimental conditions. We find that networks obtained using different phenotypic readouts, in different conditions and from different laboratories overlap less than expected and provide significant unique information. To exploit this information, we develop a novel method to combine individual genetic interaction data sets and show that the resulting network improves gene function prediction performance, demonstrating that individual networks provide complementary information. Our results support the notion that using diverse phenotypic readouts and experimental conditions will substantially increase the amount of gene function information produced by genetic interaction screens.

Separate FeS scaffold and carrier functions for SufB₂C₂ and SufA during in vitro maturation of [2Fe2S] Fdx

Iron-sulfur (FeS) clusters are inorganic cofactors required for a variety of biological processes. In vivo biogenesis of FeS clusters proceeds via complex pathways involving multiple protein complexes. In the Suf FeS cluster biogenesis system, SufB may be a scaffold for nascent FeS cluster assembly whereas SufA is proposed to act as either a scaffold or an FeS cluster carrier from the scaffold to target apo-proteins. However, SufB can form multiple stable complexes with other Suf proteins, such as SufB(2)C(2) and SufBC(2)D and the specific functions of these complexes in FeS cluster assembly are not clear. Here we compare the ability of the SufB(2)C(2) and SufBC(2)D complexes as well as SufA to promote in vitro maturation of the [2Fe2S] ferredoxin (Fdx). We found that SufB(2)C(2) was most proficient as a scaffold for de novo assembly of holo-Fdx using sulfide and iron as freely available building blocks while SufA was best at direct transfer of a pre-formed FeS cluster to Fdx. Furthermore, cluster transfer from [4Fe4S] SufB(2)C(2) or SufBC(2)D to Fdx will proceed through a SufA intermediate to Fdx if SufA is present. Finally, addition of ATP repressed cluster transfer from [4Fe4S] SufB(2)C(2) to Fdx and from SufBC(2)D to [2Fe2S] SufA or Fdx. These studies indicate that SufB(2)C(2) can serve as a terminal scaffold to load the SufA FeS cluster carrier for in vitro maturation of [2Fe2S] enzymes like Fdx. This work is the first to systematically compare the cluster transfer rates of a scaffold (SufB) to the transfer rates of a carrier (SufA) under the same conditions to the same target enzyme and is also the first to reconstitute the full transfer pathway (from scaffold to carrier to target enzyme) in a single reaction.

Membrane transport metabolons

In this review evidence from a wide variety of biological systems is presented for the genetic, functional, and likely physical association of membrane transporters and the enzymes that metabolize the transported substrates. This evidence supports the hypothesis that the dynamic association of transporters and enzymes creates functional membrane transport metabolons that channel substrates typically obtained from the extracellular compartment directly into their cellular metabolism. The immediate modification of substrates on the inner surface of the membrane prevents back-flux through facilitated transporters, increasing the efficiency of transport. In some cases products of the enzymes are themselves substrates for the transporters that efflux the products in an exchange or antiport mechanism. Regulation of the binding of enzymes to transporters and their mutual activities may play a role in modulating flux through transporters and entry of substrates into metabolic pathways. Examples showing the physical association of transporters and enzymes are provided, but available structural data is sparse. Genetic and functional linkages between membrane transporters and enzymes were revealed by an analysis of Escherichia coli operons encoding polycistronic mRNAs and provide a list of predicted interactions ripe for further structural studies. This article supports the view that membrane transport metabolons are important throughout Nature in organisms ranging from bacteria to humans.

Monothiol CGFS glutaredoxins and BolA-like proteins: [2Fe-2S] binding partners in iron homeostasis

Monothiol glutaredoxins (Grxs) with a signature CGFS active site and BolA-like proteins have recently emerged as novel players in iron homeostasis. Elegant genetic and biochemical studies examining the functional and physical interactions of CGFS Grxs in the fungi Saccharomyces cerevisiae and Schizosaccharomyces pombe have unveiled their essential roles in intracellular iron signaling, iron trafficking, and the maturation of Fe-S cluster proteins. Biophysical and biochemical analyses of the [2Fe-2S] bridging interaction between CGFS Grxs and a BolA-like protein in S. cerevisiae provided the first molecular-level understanding of the iron regulation mechanism in this model eukaryote and established the ubiquitous CGFS Grxs and BolA-like proteins as novel Fe-S cluster-binding regulatory partners. Parallel studies focused on Escherichia coli and human homologues for CGFS Grxs and BolA-like proteins have supported the studies in yeast and provided additional clues about their involvement in cellular iron metabolism. Herein, we review recent progress in uncovering the cellular and molecular mechanisms by which CGFS Grxs and BolA-like proteins help regulate iron metabolism in both eukaryotic and prokaryotic organisms.

Genome-scale genetic manipulation methods for exploring bacterial molecular biology

Bacteria are diverse and abundant, playing key roles in human health and disease, the environment, and biotechnology. Despite progress in genome sequencing and bioengineering, much remains unknown about the functional organization of prokaryotes. For instance, roughly a third of the protein-coding genes of the best-studied model bacterium, Escherichia coli, currently lack experimental annotations. Systems-level experimental approaches for investigating the functional associations of bacterial genes and genetic structures are essential for defining the fundamental molecular biology of microbes, preventing the spread of antibacterial resistance in the clinic, and driving the development of future biotechnological applications. This review highlights recently introduced large-scale genetic manipulation and screening procedures for the systematic exploration of bacterial gene functions, molecular relationships, and the global organization of bacteria at the gene, pathway, and genome levels.

Bacterial genome reengineering

The web application PrimerPair at ecogene.org generates large sets of paired DNA sequences surrounding- all protein and RNA genes of Escherichia coli K-12. Many DNA fragments, which these primers amplify, can be used to implement a genome reengineering strategy using complementary in vitro cloning and in vivo recombineering. The integration of a primer design tool with a model organism database increases the level of quality control. Computer-assisted design of gene primer pairs relies upon having highly accurate genomic DNA sequence information that exactly matches the DNA of the cells being used in the laboratory to ensure predictable DNA hybridizations. It is equally crucial to have confidence that the predicted start codons define the locations of genes accurately. Annotations in the EcoGene database are queried by PrimerPair to eliminate pseudogenes, IS elements, and other problematic genes before the design process starts. These projects progressively familiarize users with the EcoGene content, scope, and application interfaces that are useful for genome reengineering projects. The first protocol leads to the design of a pair of primer sequences that were used to clone and express a single gene. The N-terminal protein sequence was experimentally verified and the protein was detected in the periplasm. This is followed by instructions to design PCR primer pairs for cloning gene fragments encoding 50 periplasmic proteins without their signal peptides. The design process begins with the user simply designating one pair of forward and reverse primer endpoint positions relative to all start and stop codon positions. The gene name, genomic coordinates, and primer DNA sequences are reported to the user. When making chromosomal deletions, the integrity of the provisional primer design is checked to see whether it will generate any unwanted double deletions with adjacent genes. The bad designs are recalculated and replacement primers are provided alongside the requested primers. A list of all genes with overlaps includes those expressed from the translational coupling motifs 5'-UGAUG-3' and 5'-AUGA-3'. Rigid alignments of the 893 ribosome binding sites (RBSs) linked to the AUG codons of this coupled subset are assessed for information content using WebLogo 3.0. These specialized logos are missing the G at the prominent information peak position normally seen in the rigid alignment of all genes. This novel GHOLE motif was apparently masked by the normal RBSs in two previously published rigid alignments. We propose a model constraining the distance between the ATG and the RBS, obviating- the need for a flexible linker model to reveal a Shine-Dalgarno-like sequence.

Differential network biology

Protein and genetic interaction maps can reveal the overall physical and functional landscape of a biological system. To date, these interaction maps have typically been generated under a single condition, even though biological systems undergo differential change that is dependent on environment, tissue type, disease state, development or speciation. Several recent interaction mapping studies have demonstrated the power of differential analysis for elucidating fundamental biological responses, revealing that the architecture of an interactome can be massively re-wired during a cellular or adaptive response. Here, we review the technological developments and experimental designs that have enabled differential network mapping at very large scales and highlight biological insight that has been derived from this type of analysis. We argue that differential network mapping, which allows for the interrogation of previously unexplored interaction spaces, will become a standard mode of network analysis in the future, just as differential gene expression and protein phosphorylation studies are already pervasive in genomic and proteomic analysis.

Comparative interaction networks: bridging genotype to phenotype

Over the past decade, biomedical research has witnessed an exponential increase in the throughput of the characterization of biological systems. Here we review the recent progress in large-scale methods to determine protein-protein, genetic and chemical-genetic interaction networks. We discuss some of the limitations and advantages of the different methods and give examples of how these networks are being used to study the evolutionary process. Comparative studies have revealed that different types of protein-protein interactions diverge at different rates with high conservation of co-complex membership but rapid divergence of more promiscuous interactions like those that mediate post-translational modifications. These evolutionary trends have consistent genetic consequences with highly conserved epistatic interactions within complex subunits but faster divergence of epistatic interactions across complexes or pathways. Finally, we discuss how these evolutionary observations are being used to interpret cross-species chemical-genetic studies and how they might shape therapeutic strategies. Together, these interaction networks offer us an unprecedented level of detail into how genotypes are translated to phenotypes, and we envision that they will be increasingly useful in the interpretation of genetic and phenotypic variation occurring within populations as well as the rational design of combinatorial therapeutics.

Genetic co-occurrence network across sequenced microbes

The phenotype of any organism on earth is, in large part, the consequence of interplay between numerous gene products encoded in the genome, and such interplay between gene products affects the evolutionary fate of the genome itself through the resulting phenotype. In this regard, contemporary genomes can be used as molecular records that reveal associations of various genes working in their natural lifestyles. By analyzing thousands of orthologs across ∼600 bacterial species, we constructed a map of gene-gene co-occurrence across much of the sequenced biome. If genes preferentially co-occur in the same organisms, they were called herein correlogs; in the opposite case, called anti-correlogs. To quantify correlogy and anti-correlogy, we alleviated the contribution of indirect correlations between genes by adapting ideas developed for reverse engineering of transcriptional regulatory networks. Resultant correlogous associations are highly enriched for physically interacting proteins and for co-expressed transcripts, clearly differentiating a subgroup of functionally-obligatory protein interactions from conditional or transient interactions. Other biochemical and phylogenetic properties were also found to be reflected in correlogous and anti-correlogous relationships. Additionally, our study elucidates the global organization of the gene association map, in which various modules of correlogous genes are strikingly interconnected by anti-correlogous crosstalk between the modules. We then demonstrate the effectiveness of such associations along different domains of life and environmental microbial communities. These phylogenetic profiling approaches infer functional coupling of genes regardless of mechanistic details, and may be useful to guide exogenous gene import in synthetic biology.

From the regulation of peptidoglycan synthesis to bacterial growth and morphology

How bacteria grow and divide while retaining a defined shape is a fundamental question in microbiology, but technological advances are now driving a new understanding of how the shape-maintaining bacterial peptidoglycan sacculus grows. In this Review, we highlight the relationship between peptidoglycan synthesis complexes and cytoskeletal elements, as well as recent evidence that peptidoglycan growth is regulated from outside the sacculus in Gram-negative bacteria. We also discuss how growth of the sacculus is sensitive to mechanical force and nutritional status, and describe the roles of peptidoglycan hydrolases in generating cell shape and of D-amino acids in sacculus remodelling.

Genetic interaction maps in Escherichia coli reveal functional crosstalk among cell envelope biogenesis pathways

As the interface between a microbe and its environment, the bacterial cell envelope has broad biological and clinical significance. While numerous biosynthesis genes and pathways have been identified and studied in isolation, how these intersect functionally to ensure envelope integrity during adaptive responses to environmental challenge remains unclear. To this end, we performed high-density synthetic genetic screens to generate quantitative functional association maps encompassing virtually the entire cell envelope biosynthetic machinery of Escherichia coli under both auxotrophic (rich medium) and prototrophic (minimal medium) culture conditions. The differential patterns of genetic interactions detected among >235,000 digenic mutant combinations tested reveal unexpected condition-specific functional crosstalk and genetic backup mechanisms that ensure stress-resistant envelope assembly and maintenance. These networks also provide insights into the global systems connectivity and dynamic functional reorganization of a universal bacterial structure that is both broadly conserved among eubacteria (including pathogens) and an important target.

Proper assembly of the cell envelope is essential for bacterial growth, environmental adaptation, and drug resistance. Yet, while the biological roles of the many genes and pathways involved in biosynthesis of the cell envelope have been studied extensively in isolation, how the myriad components intersect functionally to maintain envelope integrity under different growth conditions has not been explored systematically. Genome-scale genetic interaction screens have increasingly been performed to great impact in yeast; no analogous comprehensive studies have yet been reported for bacteria despite their prominence in human health and disease. We addressed this by using a synthetic genetic array technology to generate quantitative maps of genetic interactions encompassing virtually all the components of the cell envelope biosynthetic machinery of the classic model bacterium E. coli in two common laboratory growth conditions (rich and minimal medium). From the resulting networks of high-confidence genetic interactions, we identify condition-specific functional dependencies underlying envelope assembly and global remodeling of genetic backup mechanisms that ensure envelope integrity under environmental challenge.

Evidence-based annotation of gene function in Shewanella oneidensis MR-1 using genome-wide fitness profiling across 121 conditions

Most genes in bacteria are experimentally uncharacterized and cannot be annotated with a specific function. Given the great diversity of bacteria and the ease of genome sequencing, high-throughput approaches to identify gene function experimentally are needed. Here, we use pools of tagged transposon mutants in the metal-reducing bacterium Shewanella oneidensis MR-1 to probe the mutant fitness of 3,355 genes in 121 diverse conditions including different growth substrates, alternative electron acceptors, stresses, and motility. We find that 2,350 genes have a pattern of fitness that is significantly different from random and 1,230 of these genes (37% of our total assayed genes) have enough signal to show strong biological correlations. We find that genes in all functional categories have phenotypes, including hundreds of hypotheticals, and that potentially redundant genes (over 50% amino acid identity to another gene in the genome) are also likely to have distinct phenotypes. Using fitness patterns, we were able to propose specific molecular functions for 40 genes or operons that lacked specific annotations or had incomplete annotations. In one example, we demonstrate that the previously hypothetical gene SO_3749 encodes a functional acetylornithine deacetylase, thus filling a missing step in S. oneidensis metabolism. Additionally, we demonstrate that the orphan histidine kinase SO_2742 and orphan response regulator SO_2648 form a signal transduction pathway that activates expression of acetyl-CoA synthase and is required for S. oneidensis to grow on acetate as a carbon source. Lastly, we demonstrate that gene expression and mutant fitness are poorly correlated and that mutant fitness generates more confident predictions of gene function than does gene expression. The approach described here can be applied generally to create large-scale gene-phenotype maps for evidence-based annotation of gene function in prokaryotes.

Many computationally predicted gene annotations in bacteria are incomplete or wrong. Consequently, experimental methods to systematically determine gene function in bacteria are required. Here, we describe a genetic approach to meet this challenge. We constructed a large transposon mutant library in the metal-reducing bacterium Shewanella oneidensis MR-1 and profiled the fitness of this collection in more than 100 diverse experimental conditions. In addition to identifying a phenotype for more than 2,000 genes, we demonstrate that mutant fitness profiles can be used to assign “evidence-based” gene annotations for enzymes, signaling proteins, transporters, and transcription factors, a subset of which we verify experimentally.

The E. coli monothiol glutaredoxin GrxD forms homodimeric and heterodimeric FeS cluster containing complexes

Monothiol glutaredoxins (mono-Grx) represent a highly evolutionarily conserved class of proteins present in organisms ranging from prokaryotes to humans. Mono-Grxs have been implicated in iron sulfur (FeS) cluster biosynthesis as potential scaffold proteins and in iron homeostasis via an FeS-containing complex with Fra2p (homologue of E. coli BolA) in yeast and are linked to signal transduction in mammalian systems. However, the function of the mono-Grx in prokaryotes and the nature of an interaction with BolA-like proteins have not been established. Recent genome-wide screens for E. coli genetic interactions reported the synthetic lethality (combination of mutations leading to cell death; mutation of only one of these genes does not) of a grxD mutation when combined with strains defective in FeS cluster biosynthesis (isc operon) functions [Butland, G., et al. (2008) Nature Methods 5, 789-795]. These data connected the only E. coli mono-Grx, GrxD to a potential role in FeS cluster biosynthesis. We investigated GrxD to uncover the molecular basis of this synthetic lethality and observed that GrxD can form FeS-bound homodimeric and BolA containing heterodimeric complexes. These complexes display substantially different spectroscopic and functional properties, including the ability to act as scaffold proteins for intact FeS cluster transfer to the model [2Fe-2S] acceptor protein E. coli apo-ferredoxin (Fdx), with the homodimer being significantly more efficient. In this work, we functionally dissect the potential cellular roles of GrxD as a component of both homodimeric and heterodimeric complexes to ultimately uncover if either of these complexes performs functions linked to FeS cluster biosynthesis.

Phenotype enhancement screen of a regulatory spx mutant unveils a role for the ytpQ gene in the control of iron homeostasis

Spx is a global regulator of genes that are induced by disulfide stress in Bacillus subtilis. The regulon that it governs is comprised of over 120 genes based on microarray analysis, although it is not known how many of these are under direct Spx control. Most of the Spx-regulated genes (SRGs) are of unknown function, but many encode products that are conserved in low %GC Gram-positive bacteria. Using a gene-disruption library of B. subtilis genomic mutations, the SRGs were screened for phenotypes related to Spx-controlled activities, such as poor growth in minimal medium and sensitivity to methyglyoxal, but nearly all of the SRG mutations showed little if any phenotype. To uncover SRG function, the mutations were rescreened in an spx mutant background to determine which mutant SRG allele would enhance the spx mutant phenotype. One of the SRGs, ytpQ was the site of a mutation that, when combined with an spx null mutation, elevated the severity of the Spx mutant phenotype, as shown by reduced growth in a minimal medium and by hypersensitivity to methyglyoxal. The ytpQ mutant showed elevated oxidative protein damage when exposed to methylglyoxal, and reduced growth rate in liquid culture. Proteomic and transcriptomic data indicated that the ytpQ mutation caused the derepression of the Fur and PerR regulons of B. subtilis. Our study suggests that the ytpQ gene, encoding a conserved DUF1444 protein, functions directly or indirectly in iron homeostasis. The ytpQ mutant phenotype mimics that of a fur mutation, suggesting a condition of low cellular iron. In vitro transcription analysis indicated that Spx stimulates transcription from the ytpPQR operon within which the ytpQ gene resides. The work uncovers a link between Spx and control of iron homeostasis.

Generalized schemes for high-throughput manipulation of the Desulfovibrio vulgaris genome

The ability to conduct advanced functional genomic studies of the thousands of sequenced bacteria has been hampered by the lack of available tools for making high-throughput chromosomal manipulations in a systematic manner that can be applied across diverse species. In this work, we highlight the use of synthetic biological tools to assemble custom suicide vectors with reusable and interchangeable DNA "parts" to facilitate chromosomal modification at designated loci. These constructs enable an array of downstream applications, including gene replacement and the creation of gene fusions with affinity purification or localization tags. We employed this approach to engineer chromosomal modifications in a bacterium that has previously proven difficult to manipulate genetically, Desulfovibrio vulgaris Hildenborough, to generate a library of over 700 strains. Furthermore, we demonstrate how these modifications can be used for examining metabolic pathways, protein-protein interactions, and protein localization. The ubiquity of suicide constructs in gene replacement throughout biology suggests that this approach can be applied to engineer a broad range of species for a diverse array of systems biological applications and is amenable to high-throughput implementation.

Deciphering the regulatory codes in bacterial genomes

Interactions between cis-regulatory elements and trans-acting factors are fundamental for cellular functions such as transcription. With the revolution in microarrays and sequencing technologies, genome-wide binding locations of trans-acting factors are being determined in large numbers. The richness of the genome-scale information has revealed that the nature of the bacterial transcriptome and regulome are considerably more complex than previously expected. In addition, the emerging view of the bacterial transcriptome is revising the concept of the operon organization of the genome. This review describes current advances in the genome-scale analysis of the interaction between cis-regulatory elements and trans-acting factors in microorganisms.

Exploring the conservation of synthetic lethal genetic interaction networks

High-throughput studies have enabled the large-scale mapping of synthetic lethal genetic interaction networks in the budding yeast Saccharomyces cerevisiae (S. cerevisiae). Recently, complementary high-throughput methods have been developed to map genetic interactions in the fission yeast Schizosaccharomyces pombe (S. pombe), enabling comparative analyses of genetic interaction networks between S. pombe and S. cerevisiae, two species separated by hundreds of millions of years of evolution. The resultant data has providing our first view of a possible core genetic interaction network shared between two distantly related eukaryotes, and identified numerous species-specific interactions that may contribute to the unique biology of these two different organisms. These and other results suggest that comparative interactomic studies will provide novel insights into the structure of genetic interaction networks.