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

Shewanella oneidensis: Biotechnological Application of Metal-Reducing Bacteria

What is an unconventional organism in biotechnology? The γ-proteobacterium Shewanella oneidensis might fall into this category as it was initially established as a laboratory model organism for a process that was not seen as potentially interesting for biotechnology. The reduction of solid-state extracellular electron acceptors such as iron and manganese oxides is highly relevant for many biogeochemical cycles, although it turned out in recent years to be quite relevant for many potential biotechnological applications as well. Applications started with the production of nanoparticles and dramatically increased after understanding that electrodes in bioelectrochemical systems can also be used by these organisms. From the potential production of current and hydrogen in these systems and the development of biosensors, the field expanded to anode-assisted fermentations enabling fermentation reactions that were - so far - dependent on oxygen as an electron acceptor. Now the field expands further to cathode-dependent production routines. As a side product to all these application endeavors, S. oneidensis was understood more and more, and our understanding and genetic repertoire is at eye level to E. coli. Corresponding to this line of thought, this chapter will first summarize the available arsenal of tools in molecular biology that was established for working with the organism and thereafter describe so far established directions of application. Last but not least, we will highlight potential future directions of work with the unconventional model organism S. oneidensis.

The Y-ome Conundrum: Insights into Uncharacterized Genes and Approaches for Functional Annotation

The ever-increasing availability of genome sequencing data has revealed a substantial number of uncharacterized genes without known functions across various organisms. The first comprehensive genome sequencing of E. coli K12 revealed that more than 50% of its open reading frames corresponded to transcripts with no known functions. The group of protein-coding genes without a functional description and/or a recognized pathway, beginning with the letter "Y", is classified as the "y-ome". Several efforts have been made to elucidate the functions of these genes and to recognize their role in biological processes. This review provides a brief update on various strategies employed when studying the y-ome, such as high-throughput experimental approaches, comparative omics, metabolic engineering, gene expression analysis, and data integration techniques. Additionally, we highlight recent advancements in functional annotation methods, including the use of machine learning, network analysis, and functional genomics approaches. Novel approaches are required to produce more precise functional annotations across the genome to reduce the number of genes with unknown functions.

CAGI, the Critical Assessment of Genome Interpretation, establishes progress and prospects for computational genetic variant interpretation methods

BACKGROUND

The Critical Assessment of Genome Interpretation (CAGI) aims to advance the state-of-the-art for computational prediction of genetic variant impact, particularly where relevant to disease. The five complete editions of the CAGI community experiment comprised 50 challenges, in which participants made blind predictions of phenotypes from genetic data, and these were evaluated by independent assessors.

RESULTS

Performance was particularly strong for clinical pathogenic variants, including some difficult-to-diagnose cases, and extends to interpretation of cancer-related variants. Missense variant interpretation methods were able to estimate biochemical effects with increasing accuracy. Assessment of methods for regulatory variants and complex trait disease risk was less definitive and indicates performance potentially suitable for auxiliary use in the clinic.

CONCLUSIONS

Results show that while current methods are imperfect, they have major utility for research and clinical applications. Emerging methods and increasingly large, robust datasets for training and assessment promise further progress ahead.

Bile acid fitness determinants of a Bacteroides fragilis isolate from a human pouchitis patient

IMPORTANCE

The Gram-negative bacterium Bacteroides fragilis is a common member of the human gut microbiota that colonizes multiple host niches and can influence human physiology through a variety of mechanisms. Identification of genes that enable B. fragilis to grow across a range of host environments has been impeded in part by the relatively limited genetic tractability of this species. We have developed a high-throughput genetic resource for a B. fragilis strain isolated from a UC pouchitis patient. Bile acids limit microbial growth and are altered in abundance in UC pouches, where B. fragilis often blooms. Using this resource, we uncovered pathways and processes that impact B. fragilis fitness in bile and that may contribute to population expansions during bouts of gut inflammation.

Large-scale genetic characterization of the model sulfate-reducing bacterium, Desulfovibrio vulgaris Hildenborough

Sulfate-reducing bacteria (SRB) are obligate anaerobes that can couple their growth to the reduction of sulfate. Despite the importance of SRB to global nutrient cycles and their damage to the petroleum industry, our molecular understanding of their physiology remains limited. To systematically provide new insights into SRB biology, we generated a randomly barcoded transposon mutant library in the model SRB Desulfovibrio vulgaris Hildenborough (DvH) and used this genome-wide resource to assay the importance of its genes under a range of metabolic and stress conditions. In addition to defining the essential gene set of DvH, we identified a conditional phenotype for 1,137 non-essential genes. Through examination of these conditional phenotypes, we were able to make a number of novel insights into our molecular understanding of DvH, including how this bacterium synthesizes vitamins. For example, we identified DVU0867 as an atypical L-aspartate decarboxylase required for the synthesis of pantothenic acid, provided the first experimental evidence that biotin synthesis in DvH occurs via a specialized acyl carrier protein and without methyl esters, and demonstrated that the uncharacterized dehydrogenase DVU0826:DVU0827 is necessary for the synthesis of pyridoxal phosphate. In addition, we used the mutant fitness data to identify genes involved in the assimilation of diverse nitrogen sources and gained insights into the mechanism of inhibition of chlorate and molybdate. Our large-scale fitness dataset and RB-TnSeq mutant library are community-wide resources that can be used to generate further testable hypotheses into the gene functions of this environmentally and industrially important group of bacteria.

Three Novel Antisense Overlapping Genes in E. coli O157:H7 EDL933

The abundance of long overlapping genes in prokaryotic genomes is likely to be significantly underestimated. To date, only a few examples of such genes are fully established. Using RNA sequencing and ribosome profiling, we found expression of novel overlapping open reading frames in Escherichia coli O157:H7 EDL933 (EHEC). Indeed, the overlapping candidate genes are equipped with typical structural elements required for transcription and translation, i.e., promoters, transcription start sites, as well as terminators, all of which were experimentally verified. Translationally arrested mutants, unable to produce the overlapping encoded protein, were found to have a growth disadvantage when grown competitively against the wild type. Thus, the phenotypes found imply biological functionality of the genes at the level of proteins produced. The addition of 3 more examples of prokaryotic overlapping genes to the currently limited, yet constantly growing pool of such genes emphasizes the underestimated coding capacity of bacterial genomes. IMPORTANCE The abundance of long overlapping genes in prokaryotic genomes is likely to be significantly underestimated, since such genes are not allowed in genome annotations. However, ribosome profiling catches mRNA in the moment of being template for protein production. Using this technique and subsequent experiments, we verified 3 novel overlapping genes encoded in antisense of known genes. This adds more examples of prokaryotic overlapping genes to the currently limited, yet constantly growing pool of such genes.

Flux-Balance Analysis and Mobile CRISPRi-Guided Deletion of a Conditionally Essential Gene in Shewanella oneidensis MR-1

Carbon-neutral production of valuable bioproducts is critical to sustainable development but remains limited by the slow engineering of photosynthetic organisms. Improving existing synthetic biology tools to engineer model organisms to fix carbon dioxide is one route to overcoming the limitations of photosynthetic organisms. In this work, we describe a pipeline that enabled the deletion of a conditionally essential gene from the Shewanella oneidensis MR-1 genome. S. oneidensis is a simple bacterial host that could be used for electricity-driven conversion of carbon dioxide in the future with further genetic engineering. We used Flux Balance Analysis (FBA) to model carbon and energy flows in central metabolism and assess the effects of single and double gene deletions. We modeled the growth of deletion strains under several alternative conditions to identify substrates that restore viability to an otherwise lethal gene knockout. These predictions were tested in vivo using a Mobile-CRISPRi gene knockdown system. The information learned from FBA and knockdown experiments informed our strategy for gene deletion, allowing us to successfully delete an "expected essential" gene, gpmA. FBA predicted, knockdown experiments supported, and deletion confirmed that the "essential" gene gpmA is not needed for survival, dependent on the medium used. Removal of gpmA is a first step toward driving electrode-powered CO2 fixation via RuBisCO. This work demonstrates the potential for broadening the scope of genetic engineering in S. oneidensis as a synthetic biology chassis. By combining computational analysis with a CRISPRi knockdown system in this way, one can systematically assess the impact of conditionally essential genes and use this knowledge to generate mutations previously thought unachievable.

Gradients in gene essentiality reshape antibacterial research

Essential genes encode the processes that are necessary for life. Until recently, commonly applied binary classifications left no space between essential and non-essential genes. In this review, we frame bacterial gene essentiality in the context of genetic networks. We explore how the quantitative properties of gene essentiality are influenced by the nature of the encoded process, environmental conditions and genetic background, including a strain's distinct evolutionary history. The covered topics have important consequences for antibacterials, which inhibit essential processes. We argue that the quantitative properties of essentiality can thus be used to prioritize antibacterial cellular targets and desired spectrum of activity in specific infection settings. We summarize our points with a case study on the core essential genome of the cystic fibrosis pathobiome and highlight avenues for targeted antibacterial development.

Here and there: the double-side transgene localization

Random transgene integration is a powerful tool for developing new genome-wide screening approaches. These techniques have already been used for functional gene annotation by transposon-insertion sequencing, for identif ication of transcription factor binding sites and regulatory sequences, and for dissecting chromatin position effects. Precise localization of transgenes and accurate artifact f iltration are essential for this type of method. To date, many mapping assays have been developed, including Inverse-PCR, TLA, LAM-PCR, and splinkerette PCR. However, none of them is able to ensure localization of both transgene’s f lanking regions simultaneously, which would be necessary for some applications. Here we proposed a cheap and simple NGS-based approach that overcomes this limitation. The developed assay requires using intentionally designed vectors that lack recognition sites of one or a set of restriction enzymes used for DNA fragmentation. By looping and sequencing these DNA fragments, we obtain special data that allows us to link the two f lanking regions of the transposon. This can be useful for precise insertion mapping and for screening approaches in the f ield of chromosome engineering, where chromosomal recombination events between transgenes occur in a cell population. To demonstrate the method’s feasibility, we applied it for mapping SB transposon integration in the human HAP1 cell line. Our technique allowed us to eff iciently localize genomic transposon integrations, which was conf irmed via PCR analysis. For practical application of this approach, we proposed a set of recommendations and a normalization strategy. The developed method can be used for multiplex transgene localization and detection of rearrangements between them.

Functional genetics of human gut commensal Bacteroides thetaiotaomicron reveals metabolic requirements for growth across environments

Harnessing the microbiota for beneficial outcomes is limited by our poor understanding of the constituent bacteria, as the functions of most of their genes are unknown. Here, we measure the growth of a barcoded transposon mutant library of the gut commensal Bacteroides thetaiotaomicron on 48 carbon sources, in the presence of 56 stress-inducing compounds, and during mono-colonization of gnotobiotic mice. We identify 516 genes with a specific phenotype under only one or a few conditions, enabling informed predictions of gene function. For example, we identify a glycoside hydrolase important for growth on type I rhamnogalacturonan, a DUF4861 protein for glycosaminoglycan utilization, a 3-keto-glucoside hydrolase for disaccharide utilization, and a tripartite multidrug resistance system specifically for bile salt tolerance. Furthermore, we show that B. thetaiotaomicron uses alternative enzymes for synthesizing nitrogen-containing metabolic precursors based on ammonium availability and that these enzymes are used differentially in vivo in a diet-dependent manner.

DEG 15, an update of the Database of Essential Genes that includes built-in analysis tools

Essential genes refer to genes that are required by an organism to survive under specific conditions. Studies of the minimal-gene-set for bacteria have elucidated fundamental cellular processes that sustain life. The past five years have seen a significant progress in identifying human essential genes, primarily due to the successful use of CRISPR/Cas9 in various types of human cells. DEG 15, a new release of the Database of Essential Genes (www.essentialgene.org), has provided major advancements, compared to DEG 10. Specifically, the number of eukaryotic essential genes has increased by more than fourfold, and that of prokaryotic ones has more than doubled. Of note, the human essential-gene number has increased by more than tenfold. Moreover, we have developed built-in analysis modules by which users can perform various analyses, such as essential-gene distributions between bacterial leading and lagging strands, sub-cellular localization distribution, enrichment analysis of gene ontology and KEGG pathways, and generation of Venn diagrams to compare and contrast gene sets between experiments. Additionally, the database offers customizable BLAST tools for performing species- and experiment-specific BLAST searches. Therefore, DEG comprehensively harbors updated human-curated essential-gene records among prokaryotes and eukaryotes with built-in tools to enhance essential-gene analysis.

Mapping the Transcriptional and Fitness Landscapes of a Pathogenic E. coli Strain: The Effects of Organic Acid Stress under Aerobic and Anaerobic Conditions

Several methods are available to probe cellular responses to external stresses at the whole genome level. RNAseq can be used to measure changes in expression of all genes following exposure to stress, but gives no information about the contribution of these genes to an organism’s ability to survive the stress. The relative contribution of each non-essential gene in the genome to the fitness of the organism under stress can be obtained using methods that use sequencing to estimate the frequencies of members of a dense transposon library grown under different conditions, for example by transposon-directed insertion sequencing (TraDIS). These two methods thus probe different aspects of the underlying biology of the organism. We were interested to determine the extent to which the data from these two methods converge on related genes and pathways. To do this, we looked at a combination of biologically meaningful stresses. The human gut contains different organic short-chain fatty acids (SCFAs) produced by fermentation of carbon compounds, and Escherichia coli is exposed to these in its passage through the gut. Their effect is likely to depend on both the ambient pH and the level of oxygen present. We, therefore, generated RNAseq and TraDIS data on a uropathogenic E. coli strain grown at either pH 7 or pH 5.5 in the presence or absence of three SCFAs (acetic, propionic and butyric), either aerobically or anaerobically. Our analysis identifies both known and novel pathways as being likely to be important under these conditions. There is no simple correlation between gene expression and fitness, but we found a significant overlap in KEGG pathways that are predicted to be enriched following analysis of the data from the two methods, and the majority of these showed a fitness signature that would be predicted from the gene expression data, assuming expression to be adaptive. Genes which are not in the E. coli core genome were found to be particularly likely to show a positive correlation between level of expression and contribution to fitness.

Construction of a complete set of Neisseria meningitidis mutants and its use for the phenotypic profiling of this human pathogen

The bacterium Neisseria meningitidis causes life-threatening meningitis and sepsis. Here, we construct a complete collection of defined mutants in protein-coding genes of this organism, identifying all genes that are essential under laboratory conditions. The collection, named NeMeSys 2.0, consists of individual mutants in 1584 non-essential genes. We identify 391 essential genes, which are associated with basic functions such as expression and preservation of genome information, cell membrane structure and function, and metabolism. We use this collection to shed light on the functions of diverse genes, including a gene encoding a member of a previously unrecognised class of histidinol-phosphatases; a set of 20 genes required for type IV pili function; and several conditionally essential genes encoding antitoxins and/or immunity proteins. We expect that NeMeSys 2.0 will facilitate the phenotypic profiling of a major human bacterial pathogen.

A decade of advances in transposon-insertion sequencing

It has been 10 years since the introduction of modern transposon-insertion sequencing (TIS) methods, which combine genome-wide transposon mutagenesis with high-throughput sequencing to estimate the fitness contribution or essentiality of each genetic component in a bacterial genome. Four TIS variations were published in 2009: transposon sequencing (Tn-Seq), transposon-directed insertion site sequencing (TraDIS), insertion sequencing (INSeq) and high-throughput insertion tracking by deep sequencing (HITS). TIS has since become an important tool for molecular microbiologists, being one of the few genome-wide techniques that directly links phenotype to genotype and ultimately can assign gene function. In this Review, we discuss the recent applications of TIS to answer overarching biological questions. We explore emerging and multidisciplinary methods that build on TIS, with an eye towards future applications.

In this Review, several experts discuss progress in the decade since the development of transposon-based approaches for bacterial genetic screens. They describe how advances in both experimental technologies and analytical strategies are resulting in insights into diverse biological processes.

NADH dehydrogenases Nuo and Nqr1 contribute to extracellular electron transfer by Shewanella oneidensis MR-1 in bioelectrochemical systems

Shewanella oneidensis MR-1 is quickly becoming a synthetic biology workhorse for bioelectrochemical technologies due to a high level of understanding of its interaction with electrodes. Transmembrane electron transfer via the Mtr pathway has been well characterized, however, the role of NADH dehydrogenases in feeding electrons to Mtr has been only minimally studied in S. oneidensis MR-1. Four NADH dehydrogenases are encoded in the genome, suggesting significant metabolic flexibility in oxidizing NADH under a variety of conditions. A strain lacking the two dehydrogenases essential for aerobic growth exhibited a severe growth defect with an anode (+0.4 V_SHE) or Fe(III)-NTA as the terminal electron acceptor. Our study reveals that the same NADH dehydrogenase complexes are utilized under oxic conditions or with a high potential anode. Our study also supports the previously indicated importance of pyruvate dehydrogenase activity in producing NADH during anerobic lactate metabolism. Understanding the role of NADH in extracellular electron transfer may help improve biosensors and give insight into other applications for bioelectrochemical systems.

A phenotypic screening bioassay for Escherichia coli stress and antibiotic responses based on Fourier-transform infrared (FTIR) spectroscopy and multivariate analysis

AIMS

To develop and optimize a Fourier-transform infrared spectroscopy (FTIRS) phenotypic screening bioassay for stress responses, regarding the effect of nutrient content, bacterial growth phase and stress agent exposure time.

METHODS AND RESULTS

A high-throughput FTIRS bioassay was developed to distinguish the stress responses of Escherichia coli to sodium hydroxide, hydrochloric acid, sodium chloride, sodium hypochlorite and ethanol. Principal component analysis and hierarchical clustering were used to quantify the effect of each parameter on bioassay performance, namely its reproducibility and metabolic resolution. Bioassay performance varied greatly, ranging from poor to very good. Spectra were partitioned into biologically relevant regions to evaluate their contributions to bioassay performance, but further improvements were not observed. Bioassay optimization was validated against empirical parameters, which confirmed a closer representation of known mechanisms on the antibiotic-induced stress responses.

CONCLUSIONS

The optimized bioassay used standard nutrient content, cells in the late-stationary growth phase and a one-shift exposure duration. Only the optimized bioassay adequately and reproducibly distinguished the E. coli stress and antibiotic responses. The absence of performance improvements using partitioned spectra indicated that stress responses are imprinted on the whole-spectra metabolic signature.

SIGNIFICANCE AND IMPACT OF THE STUDY

Highly optimized FTIRS bioassay parameters are vital in capturing whole-spectra metabolic signatures that can be used for satisfactory and reproducible phenotypic screening of stress and antibiotic responses.

Shewanella oneidensis NADH dehydrogenase mutants exhibit an amino acid synthesis defect

Shewanella oneidensis MR-1 is a dissimilatory metal reducing bacterium with a highly branched respiratory electron transport chain. The S. oneidensis MR-1 genome encodes four NADH dehydrogenases, any of which may be used during respiration. We previously determined that a double-knockout of two NADH dehydrogenases, Nuo and Nqr1, eliminated aerobic growth in minimal medium. However, the double-knockout strain was able to grow aerobically in rich medium. Here, we determined that amino acid supplementation rescued growth of the mutant strain in oxic minimal medium. To determine the mechanism of the growth defect, we monitored growth, metabolism, and total NAD(H) pools in S. oneidensis MR-1 and the NADH dehydrogenase knockout strain. We also used a genetically encoded redox sensing system and determined that NADH/NAD⁺ was higher in the mutant strain than in the wild-type. We observed that the double-knockout strain was able to metabolize d,l-lactate and N-acetylglucosamine when supplemented with tryptone, but excreted high concentrations of pyruvate and acetate. The requirement for amino acid supplementation, combined with an apparent inability of the mutant strain to oxidize pyruvate or acetate suggests that TCA cycle activity was inhibited in the mutant strain by a high NADH/NAD⁺.

ePath: an online database towards comprehensive essential gene annotation for prokaryotes

Experimental techniques for identification of essential genes (EGs) in prokaryotes are usually expensive, time-consuming and sometimes unrealistic. Emerging in silico methods provide alternative methods for EG prediction, but often possess limitations including heavy computational requirements and lack of biological explanation. Here we propose a new computational algorithm for EG prediction in prokaryotes with an online database (ePath) for quick access to the EG prediction results of over 4,000 prokaryotes ( https://www.pubapps.vcu.edu/epath/ ). In ePath, gene essentiality is linked to biological functions annotated by KEGG Ortholog (KO). Two new scoring systems, namely, E_score and P_score, are proposed for each KO as the EG evaluation criteria. E_score represents appearance and essentiality of a given KO in existing experimental results of gene essentiality, while P_score denotes gene essentiality based on the principle that a gene is essential if it plays a role in genetic information processing, cell envelope maintenance or energy production. The new EG prediction algorithm shows prediction accuracy ranging from 75% to 91% based on validation from five new experimental studies on EG identification. Our overall goal with ePath is to provide a comprehensive and reliable reference for gene essentiality annotation, facilitating the study of those prokaryotes without experimentally derived gene essentiality information.

NETWORK ANALYSIS OF COMMON DIFFERENTIAL GENES IDENTIFIES KEY GENES AND IMPORTANT MODULES UNDERLYING EXTRACELLULAR ELECTRON TRANSFER PROCESSES

Electricigens can transfer electrons that produced in intracellular metabolic processes to cellular surface to restore extracellular insoluble electron acceptors (extracellular electron transfer, EET). To uncover the molecular mechanisms underlying EET processes, we integrated transcriptome changes accompanying such processes with molecular network. Firstly, time-series expression datasets for Shewanella oneidensis MR-1 under limited/changed [Formula: see text] conditions were obtained from the GEO database, and a total of 336 common differentially expressed genes (DEGs) were identified. Then, we constructed the protein–protein interaction (PPI) network that involved in EET processes from these DEGs. Furthermore, by using centralization analysis and community detection, network analysis of the PPI network was performed. Although the fundamental EET genes are similar to previous studies, important new genes have been discovered. Taking together, our study identified many literature-validated genes critical to EET processes, and also proposed some novel genes that were putatively involved in EET processes.

Global Analysis of Genes Essential for Francisella tularensis Schu S4 Growth In Vitro and for Fitness during Competitive Infection of Fischer 344 Rats

The highly virulent intracellular pathogen Francisella tularensis is a Gram-negative bacterium that has a wide host range, including humans, and is the causative agent of tularemia. To identify new therapeutic drug targets and vaccine candidates and investigate the genetic basis of Francisella virulence in the Fischer 344 rat, we have constructed an F. tularensis Schu S4 transposon library. This library consists of more than 300,000 unique transposon mutants and represents a transposon insertion for every 6 bp of the genome. A transposon-directed insertion site sequencing (TraDIS) approach was used to identify 453 genes essential for growth in vitro Many of these essential genes were mapped to key metabolic pathways, including glycolysis/gluconeogenesis, peptidoglycan synthesis, fatty acid biosynthesis, and the tricarboxylic acid (TCA) cycle. Additionally, 163 genes were identified as required for fitness during colonization of the Fischer 344 rat spleen. This in vivo selection screen was validated through the generation of marked deletion mutants that were individually assessed within a competitive index study against the wild-type F. tularensis Schu S4 strain.IMPORTANCE The intracellular bacterial pathogen Francisella tularensis causes a disease in humans characterized by the rapid onset of nonspecific symptoms such as swollen lymph glands, fever, and headaches. F. tularensis is one of the most infectious bacteria known and following pulmonary exposure can have a mortality rate exceeding 50% if left untreated. The low infectious dose of this organism and concerns surrounding its potential as a biological weapon have heightened the need for effective and safe therapies. To expand the repertoire of targets for therapeutic development, we initiated a genome-wide analysis. This study has identified genes that are important for F. tularensis under in vitro and in vivo conditions, providing candidates that can be evaluated for vaccine or antibacterial development.

The novel EHEC gene asa overlaps the TEGT transporter gene in antisense and is regulated by NaCl and growth phase

Only a few overlapping gene pairs are known in the best-analyzed bacterial model organism Escherichia coli. Automatic annotation programs usually annotate only one out of six reading frames at a locus, allowing only small overlaps between protein-coding sequences. However, both RNAseq and RIBOseq show signals corresponding to non-trivially overlapping reading frames in antisense to annotated genes, which may constitute protein-coding genes. The transcription and translation of the novel 264 nt gene asa, which overlaps in antisense to a putative TEGT (Testis-Enhanced Gene Transfer) transporter gene is detected in pathogenic E. coli, but not in two apathogenic E. coli strains. The gene in E. coli O157:H7 (EHEC) was further analyzed. An overexpression phenotype was identified in two stress conditions, i.e. excess in salt or arginine. For this, EHEC overexpressing asa was grown competitively against EHEC with a translationally arrested asa mutant gene. RT-qPCR revealed conditional expression dependent on growth phase, sodium chloride, and arginine. Two potential promoters were computationally identified and experimentally verified by reporter gene expression and determination of the transcription start site. The protein Asa was verified by Western blot. Close homologues of asa have not been found in protein databases, but bioinformatic analyses showed that it may be membrane associated, having a largely disordered structure.

Metabolic models and gene essentiality data reveal essential and conserved metabolism in prokaryotes

Essential metabolic reactions are shaping constituents of metabolic networks, enabling viable and distinct phenotypes across diverse life forms. Here we analyse and compare modelling predictions of essential metabolic functions with experimental data and thereby identify core metabolic pathways in prokaryotes. Simulations of 15 manually curated genome-scale metabolic models were integrated with 36 large-scale gene essentiality datasets encompassing a wide variety of species of bacteria and archaea. Conservation of metabolic genes was estimated by analysing 79 representative genomes from all the branches of the prokaryotic tree of life. We find that essentiality patterns reflect phylogenetic relations both for modelling and experimental data, which correlate highly at the pathway level. Genes that are essential for several species tend to be highly conserved as opposed to non-essential genes which may be conserved or not. The tRNA-charging module is highlighted as ancestral and with high centrality in the networks, followed closely by cofactor metabolism, pointing to an early information processing system supplied by organic cofactors. The results, which point to model improvements and also indicate faults in the experimental data, should be relevant to the study of centrality in metabolic networks and ancient metabolism but also to metabolic engineering with prokaryotes.

If we tried to list every known chemical reaction within an organism–human, plant or even bacteria–we would get quite a long and confusing read. But when this information is represented in so-called genome-scale metabolic networks, we have the means to access computationally each of those reactions and their interconnections. Some parts of the network have alternatives, while others are unique and therefore can be essential for growth. Here, we simulate growth and compare essential reactions and genes for the simplest type of unicellular species–prokaryotes–to understand which parts of their metabolism are universally essential and potentially ancestral. We show that similar patterns of essential reactions echo phylogenetic relationships (this makes sense, as the genome provides the building plan for the enzymes that perform those reactions). Our computational predictions correlate strongly with experimental essentiality data. Finally, we show that a crucial step of protein synthesis (tRNA charging) and the synthesis and transformation of small molecules that enzymes require (cofactors) are the most essential and conserved parts of metabolism in prokaryotes. Our results are a step further in understanding the biology and evolution of prokaryotes but can also be relevant in applied studies including metabolic engineering and antibiotic design.

Genome-Wide Analysis of Transcriptional Changes and Genes That Contribute to Fitness during Degradation of the Anthropogenic Pollutant Pentachlorophenol by Sphingobium chlorophenolicum

Pentachlorophenol (PCP) is a highly toxic pesticide that was first introduced in the 1930s. The alphaproteobacterium Sphingobium chlorophenolicum, which was isolated from PCP-contaminated sediment, has assembled a metabolic pathway capable of completely degrading PCP. This pathway produces four toxic intermediates, including a chlorinated benzoquinone that is a potent alkylating agent and three chlorinated hydroquinones that react with O2 to produce reactive oxygen species (ROS). RNA-seq analysis revealed that PCP causes a global stress response that resembles responses to proton motive force uncoupling and membrane disruption, while surprisingly, little of the response resembles the responses expected to be produced by the PCP degradation intermediates. Tn-seq was used to identify genes important for fitness in the presence of PCP. By comparing the genes that are important for fitness in wild-type S. chlorophenolicum and a non-PCP-degrading mutant, we identified genes that are important only when the PCP degradation intermediates are produced. These include genes encoding two enzymes that are likely to be involved in protection against ROS. In addition to these enzymes, the endogenous levels of other enzymes that protect cells from oxidative stress appear to mitigate the toxic effects of the chlorinated benzoquinone and hydroquinone metabolites of PCP. The combination of RNA-seq and Tn-seq results identify important mechanisms for defense against the toxicity of PCP. IMPORTANCE Phenolic compounds such as pentachlorophenol (PCP), triclosan, and 2,4-dichlorophenoxyacetic acid (2,4-D) represent a common class of anthropogenic biocides. Despite the novelty of these compounds, many can be degraded by microbes isolated from contaminated sites. However, degradation of this class of chemicals often generates toxic intermediates, which may contribute to their recalcitrance to biodegradation. We have addressed the stresses associated with degradation of PCP by Sphingobium chlorophenolicum by examining the transcriptional response after PCP exposure and identifying genes necessary for growth during both exposure to and degradation of PCP. This work identifies some of the mechanisms that protect cells from this toxic compound and facilitate its degradation. This information could be used to engineer strains capable of improved biodegradation of PCP or similar phenolic pollutants.

Use of genetic and chemical synthetic lethality as probes of complexity in bacterial cell systems

Different conditions and genomic contexts are known to have an impact on gene essentiality and interactions. Synthetic lethal interactions occur when a combination of perturbations, either genetic or chemical, result in a more profound fitness defect than expected based on the effect of each perturbation alone. Synthetic lethality in bacterial systems has long been studied; however, during the past decade, the emerging fields of genomics and chemical genomics have led to an increase in the scale and throughput of these studies. Here, we review the concepts of genomics and chemical genomics in the context of synthetic lethality and their revolutionary roles in uncovering novel biology such as the characterization of genes of unknown function and in antibacterial drug discovery. We provide an overview of the methodologies, examples and challenges of both genetic and chemical synthetic lethal screening platforms. Finally, we discuss how to apply genetic and chemical synthetic lethal approaches to rationalize the synergies of drugs, screen for new and improved antibacterial therapies and predict drug mechanism of action.

Genome-wide analysis of fitness data and its application to improve metabolic models

Background

Synthetic biology and related techniques enable genome scale high-throughput investigation of the effect on organism fitness of different gene knock-downs/outs and of other modifications of genomic sequence.

Results

We develop statistical and computational pipelines and frameworks for analyzing high throughput fitness data over a genome scale set of sequence variants. Analyzing data from a high-throughput knock-down/knock-out bacterial study, we investigate differences and determinants of the effect on fitness in different conditions. Comparing fitness vectors of genes, across tens of conditions, we observe that fitness consequences strongly depend on genomic location and more weakly depend on gene sequence similarity and on functional relationships. In analyzing promoter sequences, we identified motifs associated with conditions studied in bacterial media such as Casaminos, D-glucose, Sucrose, and other sugars and amino-acid sources.

We also use fitness data to infer genes associated with orphan metabolic reactions in the iJO1366 E. coli metabolic model. To do this, we developed a new computational method that integrates gene fitness and gene expression profiles within a given reaction network neighborhood to associate this reaction with a set of genes that potentially encode the catalyzing proteins. We then apply this approach to predict candidate genes for 107 orphan reactions in iJO1366. Furthermore - we validate our methodology with known reactions using a leave-one-out approach. Specifically, using top-20 candidates selected based on combined fitness and expression datasets, we correctly reconstruct 39.7% of the reactions, as compared to 33% based on fitness and to 26% based on expression separately, and to 4.02% as a random baseline. Our model improvement results include a novel association of a gene to an orphan cytosine nucleosidation reaction.

Conclusion

Our pipeline for metabolic modeling shows a clear benefit of using fitness data for predicting genes of orphan reactions. Along with the analysis pipelines we developed, it can be used to analyze similar high-throughput data.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2341-9) contains supplementary material, which is available to authorized users.

Need for Laboratory Ecosystems To Unravel the Structures and Functions of Soil Microbial Communities Mediated by Chemistry

The chemistry underpinning microbial interactions provides an integrative framework for linking the activities of individual microbes, microbial communities, plants, and their environments. Currently, we know very little about the functions of genes and metabolites within these communities because genome annotations and functions are derived from the minority of microbes that have been propagated in the laboratory. Yet the diversity, complexity, inaccessibility, and irreproducibility of native microbial consortia limit our ability to interpret chemical signaling and map metabolic networks. In this perspective, we contend that standardized laboratory ecosystems are needed to dissect the chemistry of soil microbiomes. We argue that dissemination and application of standardized laboratory ecosystems will be transformative for the field, much like how model organisms have played critical roles in advancing biochemistry and molecular and cellular biology. Community consensus on fabricated ecosystems ("EcoFABs") along with protocols and data standards will integrate efforts and enable rapid improvements in our understanding of the biochemical ecology of microbial communities.

The evolutionary signal in metagenome phyletic profiles predicts many gene functions

BACKGROUND

The function of many genes is still not known even in model organisms. An increasing availability of microbiome DNA sequencing data provides an opportunity to infer gene function in a systematic manner.

RESULTS

We evaluated if the evolutionary signal contained in metagenome phyletic profiles (MPP) is predictive of a broad array of gene functions. The MPPs are an encoding of environmental DNA sequencing data that consists of relative abundances of gene families across metagenomes. We find that such MPPs can accurately predict 826 Gene Ontology functional categories, while drawing on human gut microbiomes, ocean metagenomes, and DNA sequences from various other engineered and natural environments. Overall, in this task, the MPPs are highly accurate, and moreover they provide coverage for a set of Gene Ontology terms largely complementary to standard phylogenetic profiles, derived from fully sequenced genomes. We also find that metagenomes approximated from taxon relative abundance obtained via 16S rRNA gene sequencing may provide surprisingly useful predictive models. Crucially, the MPPs derived from different types of environments can infer distinct, non-overlapping sets of gene functions and therefore complement each other. Consistently, simulations on > 5000 metagenomes indicate that the amount of data is not in itself critical for maximizing predictive accuracy, while the diversity of sampled environments appears to be the critical factor for obtaining robust models.

CONCLUSIONS

In past work, metagenomics has provided invaluable insight into ecology of various habitats, into diversity of microbial life and also into human health and disease mechanisms. We propose that environmental DNA sequencing additionally constitutes a useful tool to predict biological roles of genes, yielding inferences out of reach for existing comparative genomics approaches.

Transcriptomic dissection of Bradyrhizobium sp. strain ORS285 in symbiosis with Aeschynomene spp. inducing different bacteroid morphotypes with contrasted symbiotic efficiency

To circumvent the paucity of nitrogen sources in the soil legume plants establish a symbiotic interaction with nitrogen-fixing soil bacteria called rhizobia. During symbiosis, the plants form root organs called nodules, where bacteria are housed intracellularly and become active nitrogen fixers known as bacteroids. Depending on their host plant, bacteroids can adopt different morphotypes, being either unmodified (U), elongated (E) or spherical (S). E- and S-type bacteroids undergo a terminal differentiation leading to irreversible morphological changes and DNA endoreduplication. Previous studies suggest that differentiated bacteroids display an increased symbiotic efficiency (E > U and S > U). In this study, we used a combination of Aeschynomene species inducing E- or S-type bacteroids in symbiosis with Bradyrhizobium sp. ORS285 to show that S-type bacteroids present a better symbiotic efficiency than E-type bacteroids. We performed a transcriptomic analysis on E- and S-type bacteroids formed by Aeschynomene afraspera and Aeschynomene indica nodules and identified the bacterial functions activated in bacteroids and specific to each bacteroid type. Extending the expression analysis in E- and S-type bacteroids in other Aeschynomene species by qRT-PCR on selected genes from the transcriptome analysis narrowed down the set of bacteroid morphotype-specific genes. Functional analysis of a selected subset of 31 bacteroid-induced or morphotype-specific genes revealed no symbiotic phenotypes in the mutants. This highlights the robustness of the symbiotic program but could also indicate that the bacterial response to the plant environment is partially anticipatory or even maladaptive. Our analysis confirms the correlation between differentiation and efficiency of the bacteroids and provides a framework for the identification of bacterial functions that affect the efficiency of bacteroids.© 2018 Society for Applied Microbiology and John Wiley & Sons Ltd.

Shewanella oneidensis MR-1 Utilizes both Sodium- and Proton-Pumping NADH Dehydrogenases during Aerobic Growth

Shewanella oneidensis MR-1 is a metal-reducing bacterium with the ability to utilize many different terminal electron acceptors, including oxygen and solid-metal oxides. Both metal oxide reduction and aerobic respiration have been studied extensively in this organism. However, electron transport chain processes upstream of the terminal oxidoreductases have been relatively understudied in this organism, especially electron transfer from NADH to respiratory quinones. Genome annotation indicates that S. oneidensis MR-1 encodes four NADH dehydrogenases, a proton-translocating dehydrogenase (Nuo), two sodium ion-translocating dehydrogenases (Nqr1 and Nqr2), and an “uncoupling” dehydrogenase (Ndh), but none of these complexes have been studied. Therefore, we conducted a study specifically focused on the effects of individual NADH dehydrogenase knockouts in S. oneidensis MR-1. We observed that two of the single-mutant strains, the ΔnuoN and ΔnqrF1 mutants, exhibited significant growth defects compared with the wild type. However, the defects were minor and only apparent under certain growth conditions. Further testing of the ΔnuoN ΔnqrF1 double-mutant strain yielded no growth in minimal medium under oxic conditions, indicating that Nuo and Nqr1 have overlapping functions, but at least one is necessary for aerobic growth. Coutilization of proton- and sodium ion-dependent energetics has important implications for the growth of this organism in environments with varied pH and salinity, including microbial electrochemical systems.

IMPORTANCE Bacteria utilize a wide variety of metabolic pathways that allow them to take advantage of different energy sources, and to do so with varied efficiency. The efficiency of a metabolic process determines the growth yield of an organism, or the amount of biomass it produces per amount of substrate consumed. This parameter has important implications in biotechnology and wastewater treatment, where low growth yields are often preferred to minimize the production of microbial biomass. In this study, we investigated respiratory pathways containing NADH dehydrogenases with varied efficiency (i.e., the number of ions translocated per NADH oxidized) in the metal-reducing bacterium Shewanella oneidensis MR-1. We observed that two different respiratory pathways are used concurrently, and at least one pathway must be functional for growth under oxic conditions.

Mutant phenotypes for thousands of bacterial genes of unknown function

One-third of all protein-coding genes from bacterial genomes cannot be annotated with a function. Here, to investigate the functions of these genes, we present genome-wide mutant fitness data from 32 diverse bacteria across dozens of growth conditions. We identified mutant phenotypes for 11,779 protein-coding genes that had not been annotated with a specific function. Many genes could be associated with a specific condition because the gene affected fitness only in that condition, or with another gene in the same bacterium because they had similar mutant phenotypes. Of the poorly annotated genes, 2,316 had associations that have high confidence because they are conserved in other bacteria. By combining these conserved associations with comparative genomics, we identified putative DNA repair proteins; in addition, we propose specific functions for poorly annotated enzymes and transporters and for uncharacterized protein families. Our study demonstrates the scalability of microbial genetics and its utility for improving gene annotations.

Gracob: a novel graph-based constant-column biclustering method for mining growth phenotype data

Motivation

Growth phenotype profiling of genome-wide gene-deletion strains over stress conditions can offer a clear picture that the essentiality of genes depends on environmental conditions. Systematically identifying groups of genes from such high-throughput data that share similar patterns of conditional essentiality and dispensability under various environmental conditions can elucidate how genetic interactions of the growth phenotype are regulated in response to the environment.

Results

We first demonstrate that detecting such ‘co-fit’ gene groups can be cast as a less well-studied problem in biclustering, i.e. constant-column biclustering. Despite significant advances in biclustering techniques, very few were designed for mining in growth phenotype data. Here, we propose Gracob, a novel, efficient graph-based method that casts and solves the constant-column biclustering problem as a maximal clique finding problem in a multipartite graph. We compared Gracob with a large collection of widely used biclustering methods that cover different types of algorithms designed to detect different types of biclusters. Gracob showed superior performance on finding co-fit genes over all the existing methods on both a variety of synthetic data sets with a wide range of settings, and three real growth phenotype datasets for E. coli, proteobacteria and yeast.

Availability and Implementation

Our program is freely available for download at http://sfb.kaust.edu.sa/Pages/Software.aspx.

Supplementary information

Supplementary data are available at Bioinformatics online.

The Small RNA RyhB Is a Regulator of Cytochrome Expression in Shewanella oneidensis

Shewanella oneidensis produces an extensive electron transfer network that results in metabolic flexibility. A large number of c-type cytochromes are expressed by S. oneidensis and these function as the fundamental electron transport chain proteins. Although several S. oneidensis cytochromes have been well-characterized, little is known about how their expression is regulated. In this study, we investigate the role of the ferric uptake regulator (Fur) and the sRNA RyhB in regulation. Our results demonstrate that loss of Fur leads to diminished growth and an apparent decrease in heme-containing proteins. Remarkably, deleting the Fur-repressed ryhB gene almost completely reverses these physiological changes, indicating that the phenotypes resulting from loss of Fur are (at least partially) dependent on RyhB. RNA sequencing identified a number of possible RyhB repressed genes. A large fraction of these encode c-type cytochromes, among them two of the most abundant periplasmic cytochromes CctA (also known as STC) and ScyA. We show that RyhB destabilizes the mRNA of four of its target genes, cctA, scyA, omp35, and nrfA and this requires the presence of the RNA chaperone Hfq. Iron limitation decreases the expression of the RyhB target genes cctA and scyA and this regulation relies on the presence of both Fur and RyhB. Overall, this study suggests that controlling cytochrome expression is of importance to maintain iron homeostasis and that sRNAs molecules are important players in the regulation of fundamental processes in S. oneidensis MR-1.

Filling gaps in bacterial amino acid biosynthesis pathways with high-throughput genetics

For many bacteria with sequenced genomes, we do not understand how they synthesize some amino acids. This makes it challenging to reconstruct their metabolism, and has led to speculation that bacteria might be cross-feeding amino acids. We studied heterotrophic bacteria from 10 different genera that grow without added amino acids even though an automated tool predicts that the bacteria have gaps in their amino acid synthesis pathways. Across these bacteria, there were 11 gaps in their amino acid biosynthesis pathways that we could not fill using current knowledge. Using genome-wide mutant fitness data, we identified novel enzymes that fill 9 of the 11 gaps and hence explain the biosynthesis of methionine, threonine, serine, or histidine by bacteria from six genera. We also found that the sulfate-reducing bacterium Desulfovibrio vulgaris synthesizes homocysteine (which is a precursor to methionine) by using DUF39, NIL/ferredoxin, and COG2122 proteins, and that homoserine is not an intermediate in this pathway. Our results suggest that most free-living bacteria can likely make all 20 amino acids and illustrate how high-throughput genetics can uncover previously-unknown amino acid biosynthesis genes.

For a few bacteria, it is well known how they can make all 20 of the standard amino acids (the building blocks of proteins). For many other bacteria, their genome sequence implies that there are gaps in these biosynthetic pathways, so that the bacteria cannot make all of the amino acids and would need to take up some of them from their environment instead. But many bacteria can grow in minimal media (without any amino acids) despite these apparent gaps. We studied 10 bacteria with predicted gaps in amino acid biosynthesis that nevertheless grow in minimal media. Most of these gaps were spurious, but 11 of the gaps were genuine and could not be explained by current knowledge. Using high-throughput genetics, we systematically identified genes that were required for growth in minimal media and identified the biosynthetic genes that fill 9 of the 11 gaps. We hope that this approach can be applied to many more bacteria and will eventually allow us to accurately predict the nutritional requirements of a bacterium from its genome sequence.

Advances in gap-filling genome-scale metabolic models and model-driven experiments lead to novel metabolic discoveries

With rapid improvements in next-generation sequencing technologies, our knowledge about metabolism of many organisms is rapidly increasing. However, gaps in metabolic networks exist due to incomplete knowledge (e.g., missing reactions, unknown pathways, unannotated and misannotated genes, promiscuous enzymes, and underground metabolic pathways). In this review, we discuss recent advances in gap-filling algorithms based on genome-scale metabolic models and the importance of both high-throughput experiments and detailed biochemical characterization, which work in concert with in silico methods, to allow a more accurate and comprehensive understanding of metabolism.

Antibiotics Disrupt Coordination between Transcriptional and Phenotypic Stress Responses in Pathogenic Bacteria

Bacterial genes that change in expression upon environmental disturbance have commonly been seen as those that must also phenotypically matter. However, several studies suggest that differentially expressed genes are rarely phenotypically important. We demonstrate, for Gram-positive and Gram-negative bacteria, that these seemingly uncoordinated gene sets are involved in responses that can be linked through topological network analysis. However, the level of coordination is stress dependent. While a well-coordinated response is triggered in response to nutrient stress, antibiotics trigger an uncoordinated response in which transcriptionally and phenotypically important genes are neither linked spatially nor in their magnitude. Moreover, a gene expression meta-analysis reveals that genes with large fitness changes during stress have low transcriptional variation across hundreds of other conditions, and vice versa. Our work suggests that cellular responses can be understood through network models that incorporate regulatory and genetic relationships, which could aid drug target predictions and genetic network engineering.

The essential genomic landscape of the commensal Bifidobacterium breve UCC2003

Bifidobacteria are common gut commensals with purported health-promoting effects. This has encouraged scientific research into bifidobacteria, though recalcitrance to genetic manipulation and scarcity of molecular tools has hampered our knowledge on the precise molecular determinants of their health-promoting attributes and gut adaptation. To overcome this problem and facilitate functional genomic analyses in bifidobacteria, we created a large Tn5 transposon mutant library of the commensal Bifidobacterium breve UCC2003 that was further characterized by means of a Transposon Directed Insertion Sequencing (TraDIS) approach. Statistical analysis of transposon insertion distribution revealed a set of 453 genes that are essential for or markedly contribute to growth of this strain under laboratory conditions. These essential genes encode functions involved in the so-called bifid-shunt, most enzymes related to nucleotide biosynthesis and a range of housekeeping functions. Comparison to the Bifidobacterium and B. breve core genomes highlights a high degree of conservation of essential genes at the species and genus level, while comparison to essential gene datasets from other gut bacteria identified essential genes that appear specific to bifidobacteria. This work establishes a useful molecular tool for scientific discovery of bifidobacteria and identifies targets for further studies aimed at characterizing essential functions not previously examined in bifidobacteria.

Microbial metal resistance and metabolism across dynamic landscapes: high-throughput environmental microbiology

Multidimensional gradients of inorganic compounds influence microbial activity in diverse pristine and anthropogenically perturbed environments. Here, we suggest that high-throughput cultivation and genetics can be systematically applied to generate quantitative models linking gene function, microbial community activity, and geochemical parameters. Metal resistance determinants represent a uniquely universal set of parameters around which to study and evaluate microbial fitness because they represent a record of the environment in which all microbial life evolved. By cultivating microbial isolates and enrichments in laboratory gradients of inorganic ions, we can generate quantitative predictions of limits on microbial range in the environment, obtain more accurate gene annotations, and identify useful strategies for predicting and engineering the trajectory of natural ecosystems.

Validating regulatory predictions from diverse bacteria with mutant fitness data

Although transcriptional regulation is fundamental to understanding bacterial physiology, the targets of most bacterial transcription factors are not known. Comparative genomics has been used to identify likely targets of some of these transcription factors, but these predictions typically lack experimental support. Here, we used mutant fitness data, which measures the importance of each gene for a bacterium’s growth across many conditions, to test regulatory predictions from RegPrecise, a curated collection of comparative genomics predictions. Because characterized transcription factors often have correlated fitness with one of their targets (either positively or negatively), correlated fitness patterns provide support for the comparative genomics predictions. At a false discovery rate of 3%, we identified significant cofitness for at least one target of 158 TFs in 107 ortholog groups and from 24 bacteria. Thus, high-throughput genetics can be used to identify a high-confidence subset of the sequence-based regulatory predictions.

Regulation of acetyl-CoA synthetase transcription by the CrbS/R two-component system is conserved in genetically diverse environmental pathogens

The CrbS/R two-component signal transduction system is a conserved regulatory mechanism through which specific Gram-negative bacteria control acetate flux into primary metabolic pathways. CrbS/R governs expression of acetyl-CoA synthase (acsA), an enzyme that converts acetate to acetyl-CoA, a metabolite at the nexus of the cell’s most important energy-harvesting and biosynthetic reactions. During infection, bacteria can utilize this system to hijack host acetate metabolism and alter the course of colonization and pathogenesis. In toxigenic strains of Vibrio cholerae, CrbS/R-dependent expression of acsA is required for virulence in an arthropod model. Here, we investigate the function of the CrbS/R system in Pseudomonas aeruginosa, Pseudomonas entomophila, and non-toxigenic V. cholerae strains. We demonstrate that its role in acetate metabolism is conserved; this system regulates expression of the acsA gene and is required for growth on acetate as a sole carbon source. As a first step towards describing the mechanism of signaling through this pathway, we identify residues and domains that may be critical for phosphotransfer. We further demonstrate that although CrbS, the putative hybrid sensor kinase, carries both a histidine kinase domain and a receiver domain, the latter is not required for acsA transcription. In order to determine whether our findings are relevant to pathogenesis, we tested our strains in a Drosophila model of oral infection previously employed for the study of acetate-dependent virulence by V. cholerae. We show that non-toxigenic V. cholerae strains lacking CrbS or CrbR are significantly less virulent than are wild-type strains, while P. aeruginosa and P. entomophila lacking CrbS or CrbR are fully pathogenic. Together, the data suggest that the CrbS/R system plays a central role in acetate metabolism in V. cholerae, P. aeruginosa, and P. entomophila. However, each microbe’s unique environmental adaptations and pathogenesis strategies may dictate conditions under which CrbS/R-mediated acs expression is most critical.

Growth Trade-Offs Accompany the Emergence of Glycolytic Metabolism in Shewanella oneidensis MR-1

Bacteria increase their metabolic capacity via the acquisition of genetic material or by the mutation of genes already present in the genome. Here, we explore the mechanisms and trade-offs involved when Shewanella oneidensis, a bacterium that typically consumes small organic and amino acids, rapidly evolves to expand its metabolic capacity to catabolize glucose after a short period of adaptation to a glucose-rich environment. Using whole-genome sequencing and genetic approaches, we discovered that deletions in a region including the transcriptional repressor (nagR) that regulates the expression of genes associated with catabolism of N-acetylglucosamine are the common basis for evolved glucose metabolism across populations. The loss of nagR results in the constitutive expression of genes for an N-acetylglucosamine permease (nagP) and kinase (nagK). We demonstrate that promiscuous activities of both NagP and NagK toward glucose allow for the transport and phosphorylation of glucose to glucose-6-phosphate, the initial events of glycolysis otherwise thought to be absent in S. oneidensis. ¹³C-based metabolic flux analysis uncovered that subsequent utilization was mediated by the Entner-Doudoroff pathway. This is an example whereby gene loss and preexisting enzymatic promiscuity, and not gain-of-function mutations, were the drivers of increased metabolic capacity. However, we observed a significant decrease in the growth rate on lactate after adaptation to glucose catabolism, suggesting that trade-offs may explain why glycolytic function may not be readily observed in S. oneidensis in natural environments despite it being readily accessible through just a single mutational event.

IMPORTANCE Gains in metabolic capacity are frequently associated with the acquisition of novel genetic material via natural or engineered horizontal gene transfer events. Here, we explored how a bacterium that typically consumes small organic acids and amino acids expands its metabolic capacity to include glucose via a loss of genetic material, a process frequently associated with a deterioration of metabolic function. Our findings highlight how the natural promiscuity of transporters and enzymes can be a key driver in expanding metabolic diversity and that many bacteria may possess a latent metabolic capacity accessible through one or a few mutations that remove regulatory functions. Our discovery of trade-offs between growth on lactate and on glucose suggests why this easily gained trait is not observed in nature.

A Genome-Scale Model of Shewanella piezotolerans Simulates Mechanisms of Metabolic Diversity and Energy Conservation

The well-studied nature of the metabolic diversity of Shewanella bacteria makes species from this genus a promising platform for investigating the evolution of carbon metabolism and energy conservation. The Shewanella phylogeny is diverged into two major branches, referred to as group 1 and group 2. While the genotype-phenotype connections of group 2 species have been extensively studied with metabolic modeling, a genome-scale model has been missing for the group 1 species. The metabolic reconstruction of Shewanella piezotolerans strain WP3 represented the first model for Shewanella group 1 and the first model among piezotolerant and psychrotolerant deep-sea bacteria. The model brought insights into the mechanisms of energy conservation in WP3 under anaerobic conditions and highlighted its metabolic flexibility in using diverse carbon sources. Overall, the model opens up new opportunities for investigating energy conservation and metabolic adaptation, and it provides a prototype for systems-level modeling of other deep-sea microorganisms.

Shewanella piezotolerans strain WP3 belongs to the group 1 branch of the Shewanella genus and is a piezotolerant and psychrotolerant species isolated from the deep sea. In this study, a genome-scale model was constructed for WP3 using a combination of genome annotation, ortholog mapping, and physiological verification. The metabolic reconstruction contained 806 genes, 653 metabolites, and 922 reactions, including central metabolic functions that represented nonhomologous replacements between the group 1 and group 2 Shewanella species. Metabolic simulations with the WP3 model demonstrated consistency with existing knowledge about the physiology of the organism. A comparison of model simulations with experimental measurements verified the predicted growth profiles under increasing concentrations of carbon sources. The WP3 model was applied to study mechanisms of anaerobic respiration through investigating energy conservation, redox balancing, and the generation of proton motive force. Despite being an obligate respiratory organism, WP3 was predicted to use substrate-level phosphorylation as the primary source of energy conservation under anaerobic conditions, a trait previously identified in other Shewanella species. Further investigation of the ATP synthase activity revealed a positive correlation between the availability of reducing equivalents in the cell and the directionality of the ATP synthase reaction flux. Comparison of the WP3 model with an existing model of a group 2 species, Shewanella oneidensis MR-1, revealed that the WP3 model demonstrated greater flexibility in ATP production under the anaerobic conditions. Such flexibility could be advantageous to WP3 for its adaptation to fluctuating availability of organic carbon sources in the deep sea.

IMPORTANCE The well-studied nature of the metabolic diversity of Shewanella bacteria makes species from this genus a promising platform for investigating the evolution of carbon metabolism and energy conservation. The Shewanella phylogeny is diverged into two major branches, referred to as group 1 and group 2. While the genotype-phenotype connections of group 2 species have been extensively studied with metabolic modeling, a genome-scale model has been missing for the group 1 species. The metabolic reconstruction of Shewanella piezotolerans strain WP3 represented the first model for Shewanella group 1 and the first model among piezotolerant and psychrotolerant deep-sea bacteria. The model brought insights into the mechanisms of energy conservation in WP3 under anaerobic conditions and highlighted its metabolic flexibility in using diverse carbon sources. Overall, the model opens up new opportunities for investigating energy conservation and metabolic adaptation, and it provides a prototype for systems-level modeling of other deep-sea microorganisms.

Rapid construction of a whole-genome transposon insertion collection for Shewanella oneidensis by Knockout Sudoku

Whole-genome knockout collections are invaluable for connecting gene sequence to function, yet traditionally, their construction has required an extraordinary technical effort. Here we report a method for the construction and purification of a curated whole-genome collection of single-gene transposon disruption mutants termed Knockout Sudoku. Using simple combinatorial pooling, a highly oversampled collection of mutants is condensed into a next-generation sequencing library in a single day, a 30- to 100-fold improvement over prior methods. The identities of the mutants in the collection are then solved by a probabilistic algorithm that uses internal self-consistency within the sequencing data set, followed by rapid algorithmically guided condensation to a minimal representative set of mutants, validation, and curation. Starting from a progenitor collection of 39,918 mutants, we compile a quality-controlled knockout collection of the electroactive microbe Shewanella oneidensis MR-1 containing representatives for 3,667 genes that is functionally validated by high-throughput kinetic measurements of quinone reduction.

Knockout collections provide a valuable tool to explore gene function, yet are expensive and technically challenging to produce at a genome-wide scale. Here Baym et al. devise a cost-effective transposon-based method to quickly develop a knockout collection for the electroactive microbe Shewanella oneidensis.

Cold adaptation regulated by cryptic prophage excision in Shewanella oneidensis

Among the environmental stresses experienced by bacteria, temperature shifts are one of the most important. In this study, we discovered a novel cold adaptation mechanism in Shewanella oneidensis that occurs at the DNA level and is regulated by cryptic prophage excision. Previous studies on bacterial cold tolerance mainly focus on the structural change of cell membrane and changes at the RNA and protein levels. Whether or not genomic change can also contribute to this process has not been explored. Here we employed a whole-genome deep-sequencing method to probe the changes at DNA level in a model psychrotrophic bacteria strain. We found that temperature downshift induced a 10 000-fold increase of the excision of a novel P4-like cryptic prophage. Importantly, although prophage excision only occurred in a relatively small population of bacteria, it was able to facilitate biofilm formation and promote the survival of the entire population. This prophage excision affected cell physiology by disrupting a critical gene encoding transfer-messenger RNA (tmRNA). In addition, we found that the histone-like nucleoid-structuring protein (H-NS) could silence prophage excision via binding to the promoter of the putative excisionase gene at warm temperatures. H-NS level was reduced at cold temperatures, leading to de-repression of prophage excision. Collectively, our results reveal that cryptic prophage excision acts as a regulatory switch to enable the survival of the host at low temperature by controlling the activity of tmRNA and biofilm formation.

Exometabolomics Assisted Design and Validation of Synthetic Obligate Mutualism

Synthetic microbial ecology has the potential to enhance the productivity and resiliency of biotechnology processes compared to approaches using single isolates. Engineering microbial consortia is challenging; however, one approach that has attracted significant attention is the creation of synthetic obligate mutualism using auxotrophic mutants that depend on each other for exchange or cross-feeding of metabolites. Here, we describe the integration of mutant library fitness profiling with mass spectrometry based exometabolomics as a method for constructing synthetic mutualism based on cross-feeding. Two industrially important species lacking known ecological interactions, Zymomonas mobilis and Escherichia coli, were selected as the test species. Amino acid exometabolites identified in the spent medium of Z. mobilis were used to select three corresponding E. coli auxotrophs (proA, pheA and IlvA), as potential E. coli counterparts for the coculture. A pooled mutant fitness assay with a Z. mobilis transposon mutant library was used to identify mutants with improved growth in the presence of E. coli. An auxotroph mutant in a gene (ZMO0748) with sequence similarity to cysteine synthase A (cysK), was selected as the Z. mobilis counterpart for the coculture. Exometabolomic analysis of spent E. coli medium identified glutathione related metabolites as potentially available for rescue of the Z. mobilis cysteine synthase mutant. Three sets of cocultures between the Z. mobilis auxotroph and each of the three E. coli auxotrophs were monitored by optical density for growth and analyzed by flow cytometry to confirm high cell counts for each species. Taken together, our methods provide a technological framework for creating synthetic mutualisms combining existing screening based methods and exometabolomics for both the selection of obligate mutualism partners and elucidation of metabolites involved in auxotroph rescue.

Evidence for the recent origin of a bacterial protein-coding, overlapping orphan gene by evolutionary overprinting

BACKGROUND

Gene duplication is believed to be the classical way to form novel genes, but overprinting may be an important alternative. Overprinting allows entirely novel proteins to evolve de novo, i.e., formerly non-coding open reading frames within functional genes become expressed. Only three cases have been described for Escherichia coli. Here, a fourth example is presented.

RESULTS

RNA sequencing revealed an open reading frame weakly transcribed in cow dung, coding for 101 residues and embedded completely in the -2 reading frame of citC in enterohemorrhagic E. coli. This gene is designated novel overlapping gene, nog1. The promoter region fused to gfp exhibits specific activities and 5' rapid amplification of cDNA ends indicated the transcriptional start 40-bp upstream of the start codon. nog1 was strand-specifically arrested in translation by a nonsense mutation silent in citC. This Nog1-mutant showed a phenotype in competitive growth against wild type in the presence of MgCl2. Small differences in metabolite concentrations were also found. Bioinformatic analyses propose Nog1 to be inner membrane-bound and to possess at least one membrane-spanning domain. A phylogenetic analysis suggests that the orphan gene nog1 arose by overprinting after Escherichia/Shigella separated from the other γ-proteobacteria.

CONCLUSIONS

Since nog1 is of recent origin, non-essential, short, weakly expressed and only marginally involved in E. coli's central metabolism, we propose that this gene is in an initial stage of evolution. While we present specific experimental evidence for the existence of a fourth overlapping gene in enterohemorrhagic E. coli, we believe that this may be an initial finding only and overlapping genes in bacteria may be more common than is currently assumed by microbiologists.

Genetic dissection of chlorate respiration in Pseudomonas stutzeri PDA reveals syntrophic (per)chlorate reduction

Genes important for growth of Pseudomonas stutzeri PDA on chlorate were identified using a randomly DNA bar-coded transposon mutant library. During chlorate reduction, mutations in genes encoding the chlorate reductase clrABC, predicted molybdopterin cofactor chaperon clrD, molybdopterin biosynthesis and two genes of unknown function (clrE, clrF) had fitness defects in pooled mutant assays (Bar-seq). Markerless in-frame deletions confirmed that clrA, clrB and clrC were essential for chlorate reduction, while clrD, clrE and clrF had less severe growth defects. Interestingly, the key detoxification gene cld was essential for chlorate reduction in isogenic pure culture experiments, but showed only minor fitness defects in Bar-seq experiments. We hypothesized this was enabled through chlorite dismutation by the community, as most strains in the Bar-seq library contained an intact cld. In support of this, Δcld grew with wild-type PDA or ΔclrA, and purified Cld also restored growth to the Δcld mutant. Expanding on this, wild-type PDA and a Δcld mutant of the perchlorate reducer Azospira suillum PS grew on perchlorate in co-culture, but not individually. These results demonstrate that co-occurrence of cld and a chloroxyanion reductase within a single organism is not necessary and raises the possibility of syntrophic (per)chlorate respiration in the environment.

Escherichia coli ASKA Clone Library Harboring tRNA-Specific Adenosine Deaminase (tadA) Reveals Resistance towards Xanthorrhizol

Xanthorrhizol is a potent antimicrobial compound isolated from the rhizome of Curcuma xanthorrhiza. However, the mechanism of xanthorrhizol action is unknown. To screen for probable target(s), we introduced the ASKA pooled-plasmid library into Escherichia coli W3110 imp4213 and enriched the library for resistant clones with increasing concentrations of xanthorrhizol. After three rounds of enrichment, we found nine genes that increased xanthorrhizol resistance. The resistant clones were able to grow in LB medium containing 256 µg/mL xanthorrhizol, representing a 16-fold increase in the minimum inhibitory concentration. Subsequent DNA sequence analysis revealed that overexpression of tadA, galU, fucU, ydeA, ydaC, soxS, nrdH, yiiD, and mltF genes conferred increased resistance towards xanthorrhizol. Among these nine genes, tadA is the only essential gene. tadA encodes a tRNA-specific adenosine deaminase. Overexpression of E. coli W3110 imp4213 (pCA24N-tadA) conferred resistance to xanthorrhizol up to 128 µg/mL. Moreover, overexpression of two tadA mutant enzymes (A143V and F149G) led to a twofold increase in the MIC. These results suggest that the targets of xanthorrhizol may include tadA, which has never before been explored as an antibiotic target.