A High-Throughput Method for Identifying Novel Genes That Influence Metabolic Pathways Reveals New Iron and Heme Regulation in Pseudomonas aeruginosa.

Heme is an essential metabolite for most life on earth. Bacterial pathogens almost universally require iron to infect a host, often acquiring this nutrient in the form of heme. The Gram-negative pathogen Pseudomonas aeruginosa is no exception, where heme acquisition and metabolism are known to be crucial for both chronic and acute infections. To unveil unknown genes and pathways that could play a role with heme metabolic flux in this pathogen, we devised an omic-based approach we dubbed "Met-Seq," for metabolite-coupled transposon sequencing. Met-Seq couples a biosensor with fluorescence-activated cell sorting (FACS) and massively parallel sequencing, allowing for direct identification of genes associated with metabolic changes. In this work, we first construct and validate a heme biosensor for use with P. aeruginosa and exploit Met-Seq to identify 188 genes that potentially influence intracellular heme levels. Identified genes largely consisted of metabolic pathways not previously associated with heme, including many secreted virulence effectors, as well as 11 predicted small RNAs (sRNAs) and riboswitches whose functions are not currently understood. We verify that five Met-Seq hits affect intracellular heme levels; a predicted extracytoplasmic function (ECF) factor, a phospholipid acquisition system, heme biosynthesis regulator Dnr, and two predicted antibiotic monooxygenase (ABM) domains of unknown function (PA0709 and PA3390). Finally, we demonstrate that PA0709 and PA3390 are novel heme-binding proteins. Our data suggest that Met-Seq could be extrapolated to other biological systems and metabolites for which there is an available biosensor, and provides a new template for further exploration of iron/heme regulation and metabolism in P. aeruginosa and other pathogens.IMPORTANCE The ability to simultaneously and more directly correlate genes with metabolite levels on a global level would provide novel information for many biological platforms yet has thus far been challenging. Here, we describe a method to help address this problem, which we dub "Met-Seq" (metabolite-coupled Tn sequencing). Met-Seq uses the powerful combination of fluorescent biosensors, fluorescence-activated cell sorting (FACS), and next-generation sequencing (NGS) to rapidly identify genes that influence the levels of specific intracellular metabolites. For proof of concept, we create and test a heme biosensor and then exploit Met-Seq to identify novel genes involved in the regulation of heme in the pathogen Pseudomonas aeruginosa Met-Seq-generated data were largely comprised of genes which have not previously been reported to influence heme levels in this pathogen, two of which we verify as novel heme-binding proteins. As heme is a required metabolite for host infection in P. aeruginosa and most other pathogens, our studies provide a new list of targets for potential antimicrobial therapies and shed additional light on the balance between infection, heme uptake, and heme biosynthesis.

The NtrYX Two-Component System Regulates the Bacterial Cell Envelope.

Activity of the NtrYX two-component system has been associated with important processes in diverse bacteria, ranging from symbiosis to nitrogen and energy metabolism. In the facultative alphaproteobacterium Rhodobacter sphaeroides, loss of the two-component system NtrYX results in increased lipid production and sensitivity to some known cell envelope-active compounds. In this study, we show that NtrYX directly controls multiple properties of the cell envelope. We find that the response regulator NtrX binds upstream of cell envelope genes, including those involved in peptidoglycan biosynthesis and modification and in cell division. We show that loss of NtrYX impacts the cellular levels of peptidoglycan precursors and lipopolysaccharide and alters cell envelope structure, increasing cell length and the thickness of the periplasm. Cell envelope function is also disrupted in the absence of NtrYX, resulting in increased outer membrane permeability. Based on the properties of R. sphaeroides cells lacking NtrYX and the target genes under direct control of this two-component system, we propose that NtrYX plays a previously undescribed, and potentially conserved, role in the assembly, structure, and function of the cell envelope in a variety of bacteria.IMPORTANCE The bacterial cell envelope provides many important functions. It protects cells from harsh environments, serves as a selective permeability barrier, houses bioenergetic functions, defines sensitivity to antibacterial agents, and plays a crucial role in biofilm formation, symbiosis, and virulence. Despite the important roles of this cellular compartment, we lack a detailed understanding of the biosynthesis and remodeling of the cell envelope. Here, we report that the R. sphaeroides two-component signaling system NtrYX is a previously undescribed regulator of cell envelope processes, providing evidence that it is directly involved in controlling transcription of genes involved in cell envelope assembly, structure, and function in this and possibly other bacteria. Thus, our data report on a newly discovered process used by bacteria to assemble and remodel the cell envelope.

Combining Genome-Scale Experimental and Computational Methods To Identify Essential Genes in Rhodobacter sphaeroides.

Rhodobacter sphaeroides is one of the best-studied alphaproteobacteria from biochemical, genetic, and genomic perspectives. To gain a better systems-level understanding of this organism, we generated a large transposon mutant library and used transposon sequencing (Tn-seq) to identify genes that are essential under several growth conditions. Using newly developed Tn-seq analysis software (TSAS), we identified 493 genes as essential for aerobic growth on a rich medium. We then used the mutant library to identify conditionally essential genes under two laboratory growth conditions, identifying 85 additional genes required for aerobic growth in a minimal medium and 31 additional genes required for photosynthetic growth. In all instances, our analyses confirmed essentiality for many known genes and identified genes not previously considered to be essential. We used the resulting Tn-seq data to refine and improve a genome-scale metabolic network model (GEM) for R. sphaeroides. Together, we demonstrate how genetic, genomic, and computational approaches can be combined to obtain a systems-level understanding of the genetic framework underlying metabolic diversity in bacterial species. IMPORTANCE Knowledge about the role of genes under a particular growth condition is required for a holistic understanding of a bacterial cell and has implications for health, agriculture, and biotechnology. We developed the Tn-seq analysis software (TSAS) package to provide a flexible and statistically rigorous workflow for the high-throughput analysis of insertion mutant libraries, advanced the knowledge of gene essentiality in R. sphaeroides, and illustrated how Tn-seq data can be used to more accurately identify genes that play important roles in metabolism and other processes that are essential for cellular survival.

Transcriptional program for nitrogen starvation-induced lipid accumulation in Chlamydomonas reinhardtii.

BACKGROUND: Algae accumulate lipids to endure different kinds of environmental stresses including macronutrient starvation. Although this response has been extensively studied, an in depth understanding of the transcriptional regulatory network (TRN) that controls the transition into lipid accumulation remains elusive. In this study, we used a systems biology approach to elucidate the transcriptional program that coordinates the nitrogen starvation-induced metabolic readjustments that drive lipid accumulation in Chlamydomonas reinhardtii. RESULTS: We demonstrate that nitrogen starvation triggered differential regulation of 2147 transcripts, which were co-regulated in 215 distinct modules and temporally ordered as 31 transcriptional waves. An early-stage response was triggered within 12 min that initiated growth arrest through activation of key signaling pathways, while simultaneously preparing the intracellular environment for later stages by modulating transport processes and ubiquitin-mediated protein degradation. Subsequently, central metabolism and carbon fixation were remodeled to trigger the accumulation of triacylglycerols. Further analysis revealed that these waves of genome-wide transcriptional events were coordinated by a regulatory program orchestrated by at least 17 transcriptional regulators, many of which had not been previously implicated in this process. We demonstrate that the TRN coordinates transcriptional downregulation of 57 metabolic enzymes across a period of nearly 4 h to drive an increase in lipid content per unit biomass. Notably, this TRN appears to also drive lipid accumulation during sulfur starvation, while phosphorus starvation induces a different regulatory program. The TRN model described here is available as a community-wide web-resource at http://networks.systemsbiology.net/chlamy-portal. CONCLUSIONS: In this work, we have uncovered a comprehensive mechanistic model of the TRN controlling the transition from N starvation to lipid accumulation. The program coordinates sequentially ordered transcriptional waves that simultaneously arrest growth and lead to lipid accumulation. This study has generated predictive tools that will aid in devising strategies for the rational manipulation of regulatory and metabolic networks for better biofuel and biomass production.

A refined genome-scale reconstruction of Chlamydomonas metabolism provides a platform for systems-level analyses.

Microalgae have reemerged as organisms of prime biotechnological interest due to their ability to synthesize a suite of valuable chemicals. To harness the capabilities of these organisms, we need a comprehensive systems-level understanding of their metabolism, which can be fundamentally achieved through large-scale mechanistic models of metabolism. In this study, we present a revised and significantly improved genome-scale metabolic model for the widely-studied microalga, Chlamydomonas reinhardtii. The model, iCre1355, represents a major advance over previous models, both in content and predictive power. iCre1355 encompasses a broad range of metabolic functions encoded across the nuclear, chloroplast and mitochondrial genomes accounting for 1355 genes (1460 transcripts), 2394 and 1133 metabolites. We found improved performance over the previous metabolic model based on comparisons of predictive accuracy across 306 phenotypes (from 81 mutants), lipid yield analysis and growth rates derived from chemostat-grown cells (under three conditions). Measurement of macronutrient uptake revealed carbon and phosphate to be good predictors of growth rate, while nitrogen consumption appeared to be in excess. We analyzed high-resolution time series transcriptomics data using iCre1355 to uncover dynamic pathway-level changes that occur in response to nitrogen starvation and changes in light intensity. This approach enabled accurate prediction of growth rates, the cessation of growth and accumulation of triacylglycerols during nitrogen starvation, and the temporal response of different growth-associated pathways to increased light intensity. Thus, iCre1355 represents an experimentally validated genome-scale reconstruction of C. reinhardtii metabolism that should serve as a useful resource for studying the metabolic processes of this and related microalgae.

Data-driven integration of genome-scale regulatory and metabolic network models.

Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription, and signaling) have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert-a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or more network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. In this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system.

CceR and AkgR regulate central carbon and energy metabolism in alphaproteobacteria.

UNLABELLED: Many pathways of carbon and energy metabolism are conserved across the phylogeny, but the networks that regulate their expression or activity often vary considerably among organisms. In this work, we show that two previously uncharacterized transcription factors (TFs) are direct regulators of genes encoding enzymes of central carbon and energy metabolism in the alphaproteobacterium Rhodobacter sphaeroides. The LacI family member CceR (RSP_1663) directly represses genes encoding enzymes in the Entner-Doudoroff pathway, while activating those encoding the F1F0 ATPase and enzymes of the tricarboxylic acid (TCA) cycle and gluconeogenesis, providing a direct transcriptional network connection between carbon and energy metabolism. We identified bases that are important for CceR DNA binding and showed that DNA binding by this TF is inhibited by 6-phosphogluconate. We also showed that the GntR family TF AkgR (RSP_0981) directly activates genes encoding several TCA cycle enzymes, and we identified conditions where its activity is increased. The properties of single and double ΔCceR and ΔAkgR mutants illustrate that these 2 TFs cooperatively regulate carbon and energy metabolism. Comparative genomic analysis indicates that CceR and AkgR orthologs are found in other alphaproteobacteria, where they are predicted to have a conserved function in regulating central carbon metabolism. Our characterization of CceR and AkgR has provided important new insight into the networks that control central carbon and energy metabolism in alphaproteobacteria that can be exploited to modify or engineer new traits in these widespread and versatile bacteria. IMPORTANCE: To extract and conserve energy from nutrients, cells coordinate a set of metabolic pathways into integrated networks. Many pathways that conserve energy or interconvert metabolites are conserved across cells, but the networks regulating these processes are often highly variable. In this study, we characterize two previously unknown transcriptional regulators of carbon and energy metabolism that are conserved in alphaproteobacteria, a group of abundant, environmentally and biotechnologically important organisms. We identify the genes they regulate, the DNA sequences they recognize, the metabolite that controls the activity of one of the regulators, and conditions where they are required for growth. We provide important new insight into conserved cellular networks that can also be used to improve a variety of hosts for converting feedstock into valuable products.

An integrated approach to reconstructing genome-scale transcriptional regulatory networks.

Transcriptional regulatory networks (TRNs) program cells to dynamically alter their gene expression in response to changing internal or environmental conditions. In this study, we develop a novel workflow for generating large-scale TRN models that integrates comparative genomics data, global gene expression analyses, and intrinsic properties of transcription factors (TFs). An assessment of this workflow using benchmark datasets for the well-studied γ-proteobacterium Escherichia coli showed that it outperforms expression-based inference approaches, having a significantly larger area under the precision-recall curve. Further analysis indicated that this integrated workflow captures different aspects of the E. coli TRN than expression-based approaches, potentially making them highly complementary. We leveraged this new workflow and observations to build a large-scale TRN model for the α-Proteobacterium Rhodobacter sphaeroides that comprises 120 gene clusters, 1211 genes (including 93 TFs), 1858 predicted protein-DNA interactions and 76 DNA binding motifs. We found that ~67% of the predicted gene clusters in this TRN are enriched for functions ranging from photosynthesis or central carbon metabolism to environmental stress responses. We also found that members of many of the predicted gene clusters were consistent with prior knowledge in R. sphaeroides and/or other bacteria. Experimental validation of predictions from this R. sphaeroides TRN model showed that high precision and recall was also obtained for TFs involved in photosynthesis (PpsR), carbon metabolism (RSP_0489) and iron homeostasis (RSP_3341). In addition, this integrative approach enabled generation of TRNs with increased information content relative to R. sphaeroides TRN models built via other approaches. We also show how this approach can be used to simultaneously produce TRN models for each related organism used in the comparative genomics analysis. Our results highlight the advantages of integrating comparative genomics of closely related organisms with gene expression data to assemble large-scale TRN models with high-quality predictions.

Quantifying the effects of light intensity on bioproduction and maintenance energy during photosynthetic growth of Rhodobacter sphaeroides.

Obtaining a better understanding of the physiology and bioenergetics of photosynthetic microbes is an important step toward optimizing these systems for light energy capture or production of valuable commodities. In this work, we analyzed the effect of light intensity on bioproduction, biomass formation, and maintenance energy during photoheterotrophic growth of Rhodobacter sphaeroides. Using data obtained from steady-state bioreactors operated at varying dilution rates and light intensities, we found that irradiance had a significant impact on biomass yield and composition, with significant changes in photopigment, phospholipid, and biopolymer storage contents. We also observed a linear relationship between incident light intensity and H2 production rate between 3 and 10 W m(-2), with saturation observed at 100 W m(-2). The light conversion efficiency to H2 was also higher at lower light intensities. Photosynthetic maintenance energy requirements were also significantly affected by light intensity, with links to differences in biomass composition and the need to maintain redox homeostasis. Inclusion of the measured condition-dependent biomass and maintenance energy parameters and the measured photon uptake rate into a genome-scale metabolic model for R. sphaeroides (iRsp1140) significantly improved its predictive performance. We discuss how our analyses provide new insights into the light-dependent changes in bioenergetic requirements and physiology during photosynthetic growth of R. sphaeroides and potentially other photosynthetic organisms.

Global analysis of photosynthesis transcriptional regulatory networks.

Photosynthesis is a crucial biological process that depends on the interplay of many components. This work analyzed the gene targets for 4 transcription factors: FnrL, PrrA, CrpK and MppG (RSP_2888), which are known or predicted to control photosynthesis in Rhodobacter sphaeroides. Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) identified 52 operons under direct control of FnrL, illustrating its regulatory role in photosynthesis, iron homeostasis, nitrogen metabolism and regulation of sRNA synthesis. Using global gene expression analysis combined with ChIP-seq, we mapped the regulons of PrrA, CrpK and MppG. PrrA regulates ∼34 operons encoding mainly photosynthesis and electron transport functions, while CrpK, a previously uncharacterized Crp-family protein, regulates genes involved in photosynthesis and maintenance of iron homeostasis. Furthermore, CrpK and FnrL share similar DNA binding determinants, possibly explaining our observation of the ability of CrpK to partially compensate for the growth defects of a ΔFnrL mutant. We show that the Rrf2 family protein, MppG, plays an important role in photopigment biosynthesis, as part of an incoherent feed-forward loop with PrrA. Our results reveal a previously unrealized, high degree of combinatorial regulation of photosynthetic genes and significant cross-talk between their transcriptional regulators, while illustrating previously unidentified links between photosynthesis and the maintenance of iron homeostasis.

Global insights into energetic and metabolic networks in Rhodobacter sphaeroides.

BACKGROUND: Improving our understanding of processes at the core of cellular lifestyles can be aided by combining information from genetic analyses, high-throughput experiments and computational predictions. RESULTS: We combined data and predictions derived from phenotypic, physiological, genetic and computational analyses to dissect the metabolic and energetic networks of the facultative photosynthetic bacterium Rhodobacter sphaeroides. We focused our analysis on pathways crucial to the production and recycling of pyridine nucleotides during aerobic respiratory and anaerobic photosynthetic growth in the presence of an organic electron donor. In particular, we assessed the requirement for NADH/NADPH transhydrogenase enzyme, PntAB during respiratory and photosynthetic growth. Using high-throughput phenotype microarrays (PMs), we found that PntAB is essential for photosynthetic growth in the presence of many organic electron donors, particularly those predicted to require its activity to produce NADPH. Utilizing the genome-scale metabolic model iRsp1095, we predicted alternative routes of NADPH synthesis and used gene expression analyses to show that transcripts from a subset of the corresponding genes were conditionally increased in a ΔpntAB mutant. We then used a combination of metabolic flux predictions and mutational analysis to identify flux redistribution patterns utilized in the ΔpntAB mutant to compensate for the loss of this enzyme. Data generated from metabolic and phenotypic analyses of wild type and mutant cells were used to develop iRsp1140, an expanded genome-scale metabolic reconstruction for R. sphaeroides with improved ability to analyze and predict pathways associated with photosynthesis and other metabolic processes. CONCLUSIONS: These analyses increased our understanding of key aspects of the photosynthetic lifestyle, highlighting the added importance of NADPH production under these conditions. It also led to a significant improvement in the predictive capabilities of a metabolic model for the different energetic lifestyles of a facultative organism.

Convergence of the transcriptional responses to heat shock and singlet oxygen stresses.

Cells often mount transcriptional responses and activate specific sets of genes in response to stress-inducing signals such as heat or reactive oxygen species. Transcription factors in the RpoH family of bacterial alternative σ factors usually control gene expression during a heat shock response. Interestingly, several α-proteobacteria possess two or more paralogs of RpoH, suggesting some functional distinction. We investigated the target promoters of Rhodobacter sphaeroides RpoH(I) and RpoH(II) using genome-scale data derived from gene expression profiling and the direct interactions of each protein with DNA in vivo. We found that the RpoH(I) and RpoH(II) regulons have both distinct and overlapping gene sets. We predicted DNA sequence elements that dictate promoter recognition specificity by each RpoH paralog. We found that several bases in the highly conserved TTG in the -35 element are important for activity with both RpoH homologs; that the T-9 position, which is over-represented in the RpoH(I) promoter sequence logo, is critical for RpoH(I)-dependent transcription; and that several bases in the predicted -10 element were important for activity with either RpoH(II) or both RpoH homologs. Genes that are transcribed by both RpoH(I) and RpoH(II) are predicted to encode for functions involved in general cell maintenance. The functions specific to the RpoH(I) regulon are associated with a classic heat shock response, while those specific to RpoH(II) are associated with the response to the reactive oxygen species, singlet oxygen. We propose that a gene duplication event followed by changes in promoter recognition by RpoH(I) and RpoH(II) allowed convergence of the transcriptional responses to heat and singlet oxygen stress in R. sphaeroides and possibly other bacteria.

Pathways involved in reductant distribution during photobiological H(2) production by Rhodobacter sphaeroides.

We used global transcript analyses and mutant studies to investigate the pathways that impact H(2) production in the photosynthetic bacterium Rhodobacter sphaeroides. We found that H(2) production capacity is related to the levels of expression of the nitrogenase and hydrogenase enzymes and the enzymes of the Calvin-Benson-Bassham pathway.

iRsp1095: a genome-scale reconstruction of the Rhodobacter sphaeroides metabolic network.

BACKGROUND: Rhodobacter sphaeroides is one of the best studied purple non-sulfur photosynthetic bacteria and serves as an excellent model for the study of photosynthesis and the metabolic capabilities of this and related facultative organisms. The ability of R. sphaeroides to produce hydrogen (H2), polyhydroxybutyrate (PHB) or other hydrocarbons, as well as its ability to utilize atmospheric carbon dioxide (CO2) as a carbon source under defined conditions, make it an excellent candidate for use in a wide variety of biotechnological applications. A genome-level understanding of its metabolic capabilities should help realize this biotechnological potential. RESULTS: Here we present a genome-scale metabolic network model for R. sphaeroides strain 2.4.1, designated iRsp1095, consisting of 1,095 genes, 796 metabolites and 1158 reactions, including R. sphaeroides-specific biomass reactions developed in this study. Constraint-based analysis showed that iRsp1095 agreed well with experimental observations when modeling growth under respiratory and phototrophic conditions. Genes essential for phototrophic growth were predicted by single gene deletion analysis. During pathway-level analyses of R. sphaeroides metabolism, an alternative route for CO2 assimilation was identified. Evaluation of photoheterotrophic H2 production using iRsp1095 indicated that maximal yield would be obtained from growing cells, with this predicted maximum ~50% higher than that observed experimentally from wild type cells. Competing pathways that might prevent the achievement of this theoretical maximum were identified to guide future genetic studies. CONCLUSIONS: iRsp1095 provides a robust framework for future metabolic engineering efforts to optimize the solar- and nutrient-powered production of biofuels and other valuable products by R. sphaeroides and closely related organisms.

Identification of surprisingly diverse type IV pili, across a broad range of gram-positive bacteria.

BACKGROUND: In Gram-negative bacteria, type IV pili (TFP) have long been known to play important roles in such diverse biological phenomena as surface adhesion, motility, and DNA transfer, with significant consequences for pathogenicity. More recently it became apparent that Gram-positive bacteria also express type IV pili; however, little is known about the diversity and abundance of these structures in Gram-positives. Computational tools for automated identification of type IV pilins are not currently available. RESULTS: To assess TFP diversity in Gram-positive bacteria and facilitate pilin identification, we compiled a comprehensive list of putative Gram-positive pilins encoded by operons containing highly conserved pilus biosynthetic genes (pilB, pilC). A surprisingly large number of species were found to contain multiple TFP operons (pil, com and/or tad). The N-terminal sequences of predicted pilins were exploited to develop PilFind, a rule-based algorithm for genome-wide identification of otherwise poorly conserved type IV pilins in any species, regardless of their association with TFP biosynthetic operons (http://signalfind.org). Using PilFind to scan 53 Gram-positive genomes (encoding >187,000 proteins), we identified 286 candidate pilins, including 214 in operons containing TFP biosynthetic genes (TBG+ operons). Although trained on Gram-positive pilins, PilFind identified 55 of 58 manually curated Gram-negative pilins in TBG+ operons, as well as 53 additional pilin candidates in operons lacking biosynthetic genes in ten species (>38,000 proteins), including 27 of 29 experimentally verified pilins. False positive rates appear to be low, as PilFind predicted only four pilin candidates in eleven bacterial species (>13,000 proteins) lacking TFP biosynthetic genes. CONCLUSIONS: We have shown that Gram-positive bacteria contain a highly diverse set of type IV pili. PilFind can be an invaluable tool to study bacterial cellular processes known to involve type IV pilus-like structures. Its use in combination with other currently available computational tools should improve the accuracy of predicting the subcellular localization of bacterial proteins.

Mutational and bioinformatic analysis of haloarchaeal lipobox-containing proteins.

A conserved lipid-modified cysteine found in a protein motif commonly referred to as a lipobox mediates the membrane anchoring of a subset of proteins transported across the bacterial cytoplasmic membrane via the Sec pathway. Sequenced haloarchaeal genomes encode many putative lipoproteins and recent studies have confirmed the importance of the conserved lipobox cysteine for signal peptide processing of three lipobox-containing proteins in the model archaeon Haloferax volcanii. We have extended these in vivo analyses to additional Hfx. volcanii substrates, supporting our previous in silico predictions and confirming the diversity of predicted Hfx. volcanii lipoproteins. Moreover, using extensive comparative secretome analyses, we identified genes encodining putative lipoproteins across a wide range of archaeal species. While our in silico analyses, supported by in vivo data, indicate that most haloarchaeal lipoproteins are Tat substrates, these analyses also predict that many crenarchaeal species lack lipoproteins altogether and that other archaea, such as nonhalophilic euryarchaeal species, transport lipoproteins via the Sec pathway. To facilitate the identification of genes that encode potential haloarchaeal Tat-lipoproteins, we have developed TatLipo, a bioinformatic tool designed to detect lipoboxes in haloarchaeal Tat signal peptides. Our results provide a strong foundation for future studies aimed at identifying components of the archaeal lipoprotein biogenesis pathway.

Haloferax volcanii flagella are required for motility but are not involved in PibD-dependent surface adhesion.

Although the genome of Haloferax volcanii contains genes (flgA1-flgA2) that encode flagellins and others that encode proteins involved in flagellar assembly, previous reports have concluded that H. volcanii is nonmotile. Contrary to these reports, we have now identified conditions under which H. volcanii is motile. Moreover, we have determined that an H. volcanii deletion mutant lacking flagellin genes is not motile. However, unlike flagella characterized in other prokaryotes, including other archaea, the H. volcanii flagella do not appear to play a significant role in surface adhesion. While flagella often play similar functional roles in bacteria and archaea, the processes involved in the biosynthesis of archaeal flagella do not resemble those involved in assembling bacterial flagella but, instead, are similar to those involved in producing bacterial type IV pili. Consistent with this observation, we have determined that, in addition to disrupting preflagellin processing, deleting pibD, which encodes the preflagellin peptidase, prevents the maturation of other H. volcanii type IV pilin-like proteins. Moreover, in addition to abolishing swimming motility, and unlike the flgA1-flgA2 deletion, deleting pibD eliminates the ability of H. volcanii to adhere to a glass surface, indicating that a nonflagellar type IV pilus-like structure plays a critical role in H. volcanii surface adhesion.