The ModelSEED Biochemistry Database for the integration of metabolic annotations and the reconstruction, comparison and analysis of metabolic models for plants, fungi and microbes.

For over 10 years, ModelSEED has been a primary resource for the construction of draft genome-scale metabolic models based on annotated microbial or plant genomes. Now being released, the biochemistry database serves as the foundation of biochemical data underlying ModelSEED and KBase. The biochemistry database embodies several properties that, taken together, distinguish it from other published biochemistry resources by: (i) including compartmentalization, transport reactions, charged molecules and proton balancing on reactions; (ii) being extensible by the user community, with all data stored in GitHub; and (iii) design as a biochemical 'Rosetta Stone' to facilitate comparison and integration of annotations from many different tools and databases. The database was constructed by combining chemical data from many resources, applying standard transformations, identifying redundancies and computing thermodynamic properties. The ModelSEED biochemistry is continually tested using flux balance analysis to ensure the biochemical network is modeling-ready and capable of simulating diverse phenotypes. Ontologies can be designed to aid in comparing and reconciling metabolic reconstructions that differ in how they represent various metabolic pathways. ModelSEED now includes 33,978 compounds and 36,645 reactions, available as a set of extensible files on GitHub, and available to search at https://modelseed.org/biochem and KBase.

Encapsulin carrier proteins for enhanced expression of antimicrobial peptides.

Antimicrobial peptides (AMPs) are regarded as attractive alternatives to conventional antibiotics, but their production in microbes remains challenging due to their inherent bactericidal nature. To address these limitations, we have developed a novel AMP fusion protein system based on an encapsulin nanocompartment protein and have demonstrated its utility in enhancing expression of HBCM2, an AMP with activity against Gram-negative bacteria. Here, HBCM2 was fused to the N-terminus of several Encapsulin monomer (Enc) variants engineered with multiple TEV protease recognition site insertions to facilitate proteolytic release of the fused HBCM2. Fusion of HBCM2 to the Enc variants, but not other common carrier proteins, enabled robust overexpression in Escherichia coli C43(DE3) cells. Interestingly, variants with a TEV site insertion following residue K71 in Enc exhibited the highest overexpression and HBCM2 release efficiencies compared to other variants but were deficient in cage formation. HBCM2 was purified from the highest expressing variant following TEV protease digestion and was found to be highly active in inhibiting E. coli growth (MIC = 5 µg/ml). Our study demonstrates the potential use of the Enc system to enhance expression of AMPs for biomanufacturing and therapeutic applications.

Combining multiple functional annotation tools increases coverage of metabolic annotation.

BACKGROUND: Genome-scale metabolic modeling is a cornerstone of systems biology analysis of microbial organisms and communities, yet these genome-scale modeling efforts are invariably based on incomplete functional annotations. Annotated genomes typically contain 30-50% of genes without functional annotation, severely limiting our knowledge of the "parts lists" that the organisms have at their disposal. These incomplete annotations may be sufficient to derive a model of a core set of well-studied metabolic pathways that support growth in pure culture. However, pathways important for growth on unusual metabolites exchanged in complex microbial communities are often less understood, resulting in missing functional annotations in newly sequenced genomes. RESULTS: Here, we present results on a comprehensive reannotation of 27 bacterial reference genomes, focusing on enzymes with EC numbers annotated by KEGG, RAST, EFICAz, and the BRENDA enzyme database, and on membrane transport annotations by TransportDB, KEGG and RAST. Our analysis shows that annotation using multiple tools can result in a drastically larger metabolic network reconstruction, adding on average 40% more EC numbers, 3-8 times more substrate-specific transporters, and 37% more metabolic genes. These results are even more pronounced for bacterial species that are phylogenetically distant from well-studied model organisms such as E. coli. CONCLUSIONS: Metabolic annotations are often incomplete and inconsistent. Combining multiple functional annotation tools can greatly improve genome coverage and metabolic network size, especially for non-model organisms and non-core pathways.

A phylogeny-driven genomic encyclopaedia of Bacteria and Archaea.

Sequencing of bacterial and archaeal genomes has revolutionized our understanding of the many roles played by microorganisms. There are now nearly 1,000 completed bacterial and archaeal genomes available, most of which were chosen for sequencing on the basis of their physiology. As a result, the perspective provided by the currently available genomes is limited by a highly biased phylogenetic distribution. To explore the value added by choosing microbial genomes for sequencing on the basis of their evolutionary relationships, we have sequenced and analysed the genomes of 56 culturable species of Bacteria and Archaea selected to maximize phylogenetic coverage. Analysis of these genomes demonstrated pronounced benefits (compared to an equivalent set of genomes randomly selected from the existing database) in diverse areas including the reconstruction of phylogenetic history, the discovery of new protein families and biological properties, and the prediction of functions for known genes from other organisms. Our results strongly support the need for systematic 'phylogenomic' efforts to compile a phylogeny-driven 'Genomic Encyclopedia of Bacteria and Archaea' in order to derive maximum knowledge from existing microbial genome data as well as from genome sequences to come.

Global transcriptome response to ionic liquid by a tropical rain forest soil bacterium, Enterobacter lignolyticus.

To process plant-based renewable biofuels, pretreatment of plant feedstock with ionic liquids has significant advantages over current methods for deconstruction of lignocellulosic feedstocks. However, ionic liquids are often toxic to the microorganisms used subsequently for biomass saccharification and fermentation. We previously isolated Enterobacter lignolyticus strain SCF1, a lignocellulolytic bacterium from tropical rain forest soil, and report here that it can grow in the presence of 0.5 M 1-ethyl-3-methylimidazolium chloride, a commonly used ionic liquid. We investigated molecular mechanisms of SCF1 ionic liquid tolerance using a combination of phenotypic growth assays, phospholipid fatty acid analysis, and RNA sequencing technologies. Potential modes of resistance to 1-ethyl-3-methylimidazolium chloride include an increase in cyclopropane fatty acids in the cell membrane, scavenging of compatible solutes, up-regulation of osmoprotectant transporters and drug efflux pumps, and down-regulation of membrane porins. These findings represent an important first step in understanding mechanisms of ionic liquid resistance in bacteria and provide a basis for engineering microbial tolerance.

From soil to structure, a novel dimeric ß-glucosidase belonging to glycoside hydrolase family 3 isolated from compost using metagenomic analysis.

A recent metagenomic analysis sequenced a switchgrass-adapted compost community to identify enzymes from microorganisms that were specifically adapted to switchgrass under thermophilic conditions. These enzymes are being examined as part of the pretreatment process for the production of "second-generation" biofuels. Among the enzymes discovered was JMB19063, a novel three-domain ß-glucosidase that belongs to the GH3 (glycoside hydrolase 3) family. Here, we report the structure of JMB19063 in complex with glucose and the catalytic variant D261N crystallized in the presence of cellopentaose. JMB19063 is first structure of a dimeric member of the GH3 family, and we demonstrate that dimerization is required for catalytic activity. Arg-587 and Phe-598 from the C-terminal domain of the opposing monomer are shown to interact with bound ligands in the D261N structure. Enzyme assays confirmed that these residues are absolutely essential for full catalytic activity.

Sequence, structure prediction, and epitope analysis of the polymorphic membrane protein family in Chlamydia trachomatis.

The polymorphic membrane proteins (Pmps) are a family of autotransporters that play an important role in infection, adhesion and immunity in Chlamydia trachomatis. Here we show that the characteristic GGA(I,L,V) and FxxN tetrapeptide repeats fit into a larger repeat sequence, which correspond to the coils of a large beta-helical domain in high quality structure predictions. Analysis of the protein using structure prediction algorithms provided novel insight to the chlamydial Pmp family of proteins. While the tetrapeptide motifs themselves are predicted to play a structural role in folding and close stacking of the beta-helical backbone of the passenger domain, we found many of the interesting features of Pmps are localized to the side loops jutting out from the beta helix including protease cleavage, host cell adhesion, and B-cell epitopes; while T-cell epitopes are predominantly found in the beta-helix itself. This analysis more accurately defines the Pmp family of Chlamydia and may better inform rational vaccine design and functional studies.

The Polymorphic Membrane Protein G Has a Neutral Effect and the Plasmid Glycoprotein 3 an Antagonistic Effect on the Ability of the Major Outer Membrane Protein to Elicit Protective Immune Responses against a Chlamydia muridarum Respiratory Challenge.

Chlamydia trachomatis is the most common bacterial sexually transmitted pathogen. The number of chlamydial infections continuous to increase and there is an urgent need for a safe and efficacious vaccine. To assess the ability of the Chlamydia muridarum polymorphic membrane protein G (PmpG) and the plasmid glycoprotein 3 (Pgp3) as single antigens, and in combination with the major outer-membrane protein (MOMP) to induce protection, BALB/c mice were immunized utilizing CpG-1826 and Montanide ISA 720 VG as adjuvants. Following vaccination with MOMP, significant humoral and cell-mediated immune responses were observed, while immunization with PmpG, or Pgp3, elicited weaker immune responses. Weaker immune responses were induced with MOMP+Pgp3 compared with MOMP alone. Following the intranasal challenge with C. muridarum, mice vaccinated with MOMP showed robust protection against body-weight loss, inflammatory responses in the lungs and number of Chlamydia recovered from the lungs. PmpG and Pgp3 elicited weaker protective responses. Mice immunized with MOMP+PmpG, were no better protected than animals vaccinated with MOMP only, while Pgp3 antagonized the protection elicited by MOMP. In conclusion, PmpG and Pgp3 elicited limited protective immune responses in mice against a respiratory challenge with C. muridarum and failed to enhance the protection induced by MOMP alone. The virulence of Pgp3 may result from its antagonistic effect on the immune protection induced by MOMP.

Glycoside hydrolases from a targeted compost metagenome, activity-screening and functional characterization.

BACKGROUND: Metagenomics approaches provide access to environmental genetic diversity for biotechnology applications, enabling the discovery of new enzymes and pathways for numerous catalytic processes. Discovery of new glycoside hydrolases with improved biocatalytic properties for the efficient conversion of lignocellulosic material to biofuels is a critical challenge in the development of economically viable routes from biomass to fuels and chemicals. RESULTS: Twenty-two putative ORFs (open reading frames) were identified from a switchgrass-adapted compost community based on sequence homology to related gene families. These ORFs were expressed in E. coli and assayed for predicted activities. Seven of the ORFs were demonstrated to encode active enzymes, encompassing five classes of hemicellulases. Four enzymes were over expressed in vivo, purified to homogeneity and subjected to detailed biochemical characterization. Their pH optima ranged between 5.5 - 7.5 and they exhibit moderate thermostability up to ~60-70°C. CONCLUSIONS: Seven active enzymes were identified from this set of ORFs comprising five different hemicellulose activities. These enzymes have been shown to have useful properties, such as moderate thermal stability and broad pH optima, and may serve as the starting points for future protein engineering towards the goal of developing efficient enzyme cocktails for biomass degradation under diverse process conditions.

Bacterial exometabolites influence Chlamydomonas cell cycle and double algal productivity.

Algal-bacterial interactions provide clues to algal physiology, but mutualistic interactions are complicated by dynamic exchange. We characterized the response of Chlamydomonas reinhardtii to the presence of a putative alga-benefitting commensal bacterium (Arthrobacter strain 'P2b'). Co-cultivation promoted chlorophyll content, biomass, average cell size, and number of dividing cells, relative to axenic cultures. Addition of bacterial spent medium (whole, size-fractionated and heat-treated) had similar effects, indicating P2b does not require algal interaction to promote growth. Nutrients and pH were excluded as putative effectors, collectively indicating a commensal interaction mediated by Arthrobacter-released small exometabolite(s). Proteogenomic comparison revealed similar response to co-cultivation and spent media, including differential cell cycle regulation, extensive downregulation of flagellar genes and histones, carbonic anhydrase and RubisCO downregulation, upregulation of some chlorophyll, amino acid and carbohydrate biosynthesis genes, and changes to redox and Fe homeostasis. Further, Arthrobacter protein expression indicated some highly expressed putative secondary metabolites. Together, these results revealed that low molecular weight bacterial metabolites can elicit major physiological changes in algal cell cycle regulation, perhaps through a more productive G1 phase, that lead to substantial increases in photosynthetically-produced biomass. This work illustrates that model commensal interactions can be used to shed light on algal response to stimulating bacteria.

Identification of biofilm matrix-associated proteins from an acid mine drainage microbial community.

In microbial communities, extracellular polymeric substances (EPS), also called the extracellular matrix, provide the spatial organization and structural stability during biofilm development. One of the major components of EPS is protein, but it is not clear what specific functions these proteins contribute to the extracellular matrix or to microbial physiology. To investigate this in biofilms from an extremely acidic environment, we used shotgun proteomics analyses to identify proteins associated with EPS in biofilms at two developmental stages, designated DS1 and DS2. The proteome composition of the EPS was significantly different from that of the cell fraction, with more than 80% of the cellular proteins underrepresented or undetectable in EPS. In contrast, predicted periplasmic, outer membrane, and extracellular proteins were overrepresented by 3- to 7-fold in EPS. Also, EPS proteins were more basic by ∼2 pH units on average and about half the length. When categorized by predicted function, proteins involved in motility, defense, cell envelope, and unknown functions were enriched in EPS. Chaperones, such as histone-like DNA binding protein and cold shock protein, were overrepresented in EPS. Enzymes, such as protein peptidases, disulfide-isomerases, and those associated with cell wall and polysaccharide metabolism, were also detected. Two of these enzymes, identified as ß-N-acetylhexosaminidase and cellulase, were confirmed in the EPS fraction by enzymatic activity assays. Compared to the differences between EPS and cellular fractions, the relative differences in the EPS proteomes between DS1 and DS2 were smaller and consistent with expected physiological changes during biofilm development.

Shotgun Immunoproteomic Approach for the Discovery of Linear B-Cell Epitopes in Biothreat Agents Francisella tularensis and Burkholderia pseudomallei.

Peptide-based subunit vaccines are coming to the forefront of current vaccine approaches, with safety and cost-effective production among their top advantages. Peptide vaccine formulations consist of multiple synthetic linear epitopes that together trigger desired immune responses that can result in robust immune memory. The advantages of linear compared to conformational epitopes are their simple structure, ease of synthesis, and ability to stimulate immune responses by means that do not require complex 3D conformation. Prediction of linear epitopes through use of computational tools is fast and cost-effective, but typically of low accuracy, necessitating extensive experimentation to verify results. On the other hand, identification of linear epitopes through experimental screening has been an inefficient process that requires thorough characterization of previously identified full-length protein antigens, or laborious techniques involving genetic manipulation of organisms. In this study, we apply a newly developed generalizable screening method that enables efficient identification of B-cell epitopes in the proteomes of pathogenic bacteria. As a test case, we used this method to identify epitopes in the proteome of Francisella tularensis (Ft), a Select Agent with a well-characterized immunoproteome. Our screen identified many peptides that map to known antigens, including verified and predicted outer membrane proteins and extracellular proteins, validating the utility of this approach. We then used the method to identify seroreactive peptides in the less characterized immunoproteome of Select Agent Burkholderia pseudomallei (Bp). This screen revealed known Bp antigens as well as proteins that have not been previously identified as antigens. Although B-cell epitope prediction tools Bepipred 2.0 and iBCE-EL classified many of our seroreactive peptides as epitopes, they did not score them significantly higher than the non-reactive tryptic peptides in our study, nor did they assign higher scores to seroreactive peptides from known Ft or Bp antigens, highlighting the need for experimental data instead of relying on computational epitope predictions alone. The present workflow is easily adaptable to detecting peptide targets relevant to the immune systems of other mammalian species, including humans (depending upon the availability of convalescent sera from patients), and could aid in accelerating the discovery of B-cell epitopes and development of vaccines to counter emerging biological threats.

Microbial genotype-phenotype mapping by class association rule mining.

MOTIVATION: Microbial phenotypes are typically due to the concerted action of multiple gene functions, yet the presence of each gene may have only a weak correlation with the observed phenotype. Hence, it may be more appropriate to examine co-occurrence between sets of genes and a phenotype (multiple-to-one) instead of pairwise relations between a single gene and the phenotype. Here, we propose an efficient class association rule mining algorithm, netCAR, in order to extract sets of COGs (clusters of orthologous groups of proteins) associated with a phenotype from COG phylogenetic profiles and a phenotype profile. netCAR takes into account the phylogenetic co-occurrence graph between COGs to restrict hypothesis space, and uses mutual information to evaluate the biconditional relation. RESULTS: We examined the mining capability of pairwise and multiple-to-one association by using netCAR to extract COGs relevant to six microbial phenotypes (aerobic, anaerobic, facultative, endospore, motility and Gram negative) from 11,969 unique COG profiles across 155 prokaryotic organisms. With the same level of false discovery rate, multiple-to-one association can extract about 10 times more relevant COGs than one-to-one association. We also reveal various topologies of association networks among COGs (modules) from extracted multiple-to-one correlation rules relevant with the six phenotypes; including a well-connected network for motility, a star-shaped network for aerobic and intermediate topologies for the other phenotypes. netCAR outperforms a standard CAR mining algorithm, CARapriori, while requiring several orders of magnitude less computational time for extracting 3-COG sets. AVAILABILITY: Source code of the Java implementation is available as Supplementary Material at the Bioinformatics online website, or upon request to the author. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

What are DNA sequence motifs?

Sequence motifs are becoming increasingly important in the analysis of gene regulation. How do we define sequence motifs, and why should we use sequence logos instead of consensus sequences to represent them? Do they have any relation with binding affinity? How do we search for new instances of a motif in this sea of DNA?

How does gene expression clustering work?

Clustering is often one of the first steps in gene expression analysis. How do clustering algorithms work, which ones should we use and what can we expect from them?

Proteomic Profiling of Burkholderia thailandensis During Host Infection Using Bio-Orthogonal Noncanonical Amino Acid Tagging (BONCAT).

Burkholderia pseudomallei and B. mallei are the causative agents of melioidosis and glanders, respectively, and are often fatal to humans and animals. Owing to the high fatality rate, potential for spread by aerosolization, and the lack of efficacious therapeutics, B. pseudomallei and B. mallei are considered biothreat agents of concern. In this study, we investigate the proteome of Burkholderia thailandensis, a closely related surrogate for the two more virulent Burkholderia species, during infection of host cells, and compare to that of B. thailandensis in culture. Studying the proteome of Burkholderia spp. during infection is expected to reveal molecular mechanisms of intracellular survival and host immune evasion; but proteomic profiling of Burkholderia during host infection is challenging. Proteomic analyses of host-associated bacteria are typically hindered by the overwhelming host protein content recovered from infected cultures. To address this problem, we have applied bio-orthogonal noncanonical amino acid tagging (BONCAT) to B. thailandensis, enabling the enrichment of newly expressed bacterial proteins from virtually any growth condition, including host cell infection. In this study, we show that B. thailandensis proteins were selectively labeled and efficiently enriched from infected host cells using BONCAT. We also demonstrate that this method can be used to label bacteria in situ by fluorescent tagging. Finally, we present a global proteomic profile of B. thailandensis as it infects host cells and a list of proteins that are differentially regulated in infection conditions as compared to bacterial monoculture. Among the identified proteins are quorum sensing regulated genes as well as homologs to previously identified virulence factors. This method provides a powerful tool to study the molecular processes during Burkholderia infection, a much-needed addition to the Burkholderia molecular toolbox.

Deciphering principles of transcription regulation in eukaryotic genomes.

Transcription regulation has been responsible for organismal complexity and diversity in the course of biological evolution and adaptation, and it is determined largely by the context-dependent behavior of cis-regulatory elements (CREs). Therefore, understanding principles underlying CRE behavior in regulating transcription constitutes a fundamental objective of quantitative biology, yet these remain poorly understood. Here we present a deterministic mathematical strategy, the motif expression decomposition (MED) method, for deriving principles of transcription regulation at the single-gene resolution level. MED operates on all genes in a genome without requiring any a priori knowledge of gene cluster membership, or manual tuning of parameters. Applying MED to Saccharomyces cerevisiae transcriptional networks, we identified four functions describing four different ways that CREs can quantitatively affect gene expression levels. These functions, three of which have extrema in different positions in the gene promoter (short-, mid-, and long-range) whereas the other depends on the motif orientation, are validated by expression data. We illustrate how nature could use these principles as an additional dimension to amplify the combinatorial power of a small set of CREs in regulating transcription.

Metagenomic analysis of intertidal hypersaline microbial mats from Elkhorn Slough, California, grown with and without molybdate.

Cyanobacterial mats are laminated microbial ecosystems which occur in highly diverse environments and which may provide a possible model for early life on Earth. Their ability to produce hydrogen also makes them of interest from a biotechnological and bioenergy perspective. Samples of an intertidal microbial mat from the Elkhorn Slough estuary in Monterey Bay, California, were transplanted to a greenhouse at NASA Ames Research Center to study a 24-h diel cycle, in the presence or absence of molybdate (which inhibits biohydrogen consumption by sulfate reducers). Here, we present metagenomic analyses of four samples that will be used as references for future metatranscriptomic analyses of this diel time series.

Genome Sequence of the Historical Clinical Isolate Burkholderia pseudomallei PHLS 6.

Here, we present the draft genome sequence of Burkholderia pseudomallei PHLS 6, a virulent clinical strain isolated from a melioidosis patient in Bangladesh in 1960. The draft genome consists of 39 contigs and is 7,322,181 bp long.