Amazonian deforestation and soil biodiversity.

Clearance and perturbation of Amazonian forests are one of the greatest threats to tropical biodiversity conservation of our times. A better understanding of how soil communities respond to Amazonian deforestation is crucially needed to inform policy interventions that effectively protect biodiversity and the essential ecosystem services it provides. We assessed the impact of deforestation and ecosystem conversion to arable land on Amazonian soil biodiversity through a meta-analysis. We analyzed 274 pairwise comparisons of soil biodiversity in Amazonian primary forests and sites under different stages of deforestation and land-use conversion: disturbed (wildfire and selective logging) and slash-and-burnt forests, pastures, and cropping systems. Overall, 60% and 51% of responses of soil macrofauna and microbial community attributes (i.e., abundance, biomass, richness, and diversity indexes) to deforestation were negative, respectively. We found few studies on mesofauna (e.g., microarthropods) and microfauna (e.g., protozoa and nematodes), so those groups could not be analyzed. Macrofauna abundance and biomass were more vulnerable to the displacement of forests by pastures than by agricultural fields, whereas microbes showed the opposite pattern. Effects of Amazonian deforestation on macrofauna were more detrimental at sites with mean annual precipitation >1900 mm, and higher losses of microbes occurred in highly acidic soils (pH < 4.5). Limited geographic coverage, omission of meso- and microfauna, and low taxonomic resolution were main factors impairing generalizations from the data set. Few studies assessed the impacts of within-forest disturbance (wildfires and selective logging) on soil species in Amazonia, where logging operations rapidly expand across public lands and more frequent severe dry seasons are increasing the prevalence of wildfires.

Deforestación en el Amazonas y Biodiversidad del Suelo Resumen Actualmente, el despeje y la perturbación de los bosques del Amazonas son las principales amenazas para la conservación de la biodiversidad tropical. Se requiere urgentemente de un mejor entendimiento sobre cómo las comunidades del suelo responden a la deforestación amazónica para informar a las intervenciones políticas que protegen efectivamente a la biodiversidad y a los servicios ambientales esenciales que proporciona. Evaluamos el impacto de la deforestación y la conversión del ecosistema a suelo arable sobre la biodiversidad del suelo amazónico por medio de un meta-análisis. Analizamos 274 comparaciones por pares de la biodiversidad del suelo amazónico en bosques primarios y sitios bajo diferentes etapas de deforestación y conversión de uso de suelo: bosques perturbados (incendios forestales y tala selectiva) y de corte-y-quema, pasturas, y sistemas agrícolas. En general, el 60% y el 51% de las respuestas de los atributos (es decir, abundancia, biomasa, riqueza, e índices de biodiversidad) de la macrofauna del suelo y de las comunidades microbianas ante la deforestación fueron negativas, respectivamente. Encontramos pocos estudios sobre la mesofauna (p. ej.: microartrópodos) y la microfauna (p. ej.: protozoarios y nematodos), así que estos grupos no pudieron ser analizados. La abundancia de la macrofauna y la biomasa fueron más vulnerables al desplazamiento de bosques por las pasturas que por los campos agrícolas, mientras que los microbios mostraron el patrón opuesto. Los efectos de la deforestación amazónica sobre la macrofauna fueron más dañinos en sitios con una precipitación anual media mayor a los 1,900 mm, y ocurrieron pérdidas más elevadas de microbios en suelos con una acidez alta (pH < 4.5). La cobertura geográfica limitada, la omisión de la mesofauna y la microfauna, y la baja resolución taxonómica fueron los factores principales que obstaculizaron las generalizaciones del conjunto de datos. Pocos estudios evaluaron los impactos de las perturbaciones internas del bosque (incendios forestales y tala selectiva) sobre las especies del suelo amazónico, a la vez que las operaciones de tala se expanden rápidamente en los terrenos públicos y la ocurrencia con mayor frecuencia de temporadas con sequía grave aumentan la prevalencia de los incendios forestales.

Curation, integration and visualization of bacterial virulence factors in PATRIC.

MOTIVATION: We've developed a highly curated bacterial virulence factor (VF) library in PATRIC (Pathosystems Resource Integration Center, www.patricbrc.org) to support infectious disease research. Although several VF databases are available, there is still a need to incorporate new knowledge found in published experimental evidence and integrate these data with other information known for these specific VF genes, including genomic and other omics data. This integration supports the identification of VFs, comparative studies and hypothesis generation, which facilitates the understanding of virulence and pathogenicity. RESULTS: We have manually curated VFs from six prioritized NIAID (National Institute of Allergy and Infectious Diseases) category A-C bacterial pathogen genera, Mycobacterium, Salmonella, Escherichia, Shigella, Listeria and Bartonella, using published literature. This curated information on virulence has been integrated with data from genomic functional annotations, trancriptomic experiments, protein-protein interactions and disease information already present in PATRIC. Such integration gives researchers access to a broad array of information about these individual genes, and also to a suite of tools to perform comparative genomic and transcriptomics analysis that are available at PATRIC. AVAILABILITY AND IMPLEMENTATION: All tools and data are freely available at PATRIC (http://patricbrc.org). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Comparative genomic analysis at the PATRIC, a bioinformatic resource center.

The Pathosystems Resource Integration Center (PATRIC) is a genomics-centric relational database and bioinformatics resource designed to assist scientists in infectious-disease research. This method paper provides detailed instructions on using this resource to finding data specific to genomes, saving it in a personalized workspace and using a variety of interactive tools to analyze that data. While PATRIC contains many diverse tools and functionalities to explore both genome-scale and gene expression data, the main focus of this chapter is on comparative analysis of bacterial genomes.

Comparative phylogenomics and evolution of the Brucellae reveal a path to virulence.

Brucella species include important zoonotic pathogens that have a substantial impact on both agriculture and human health throughout the world. Brucellae are thought of as "stealth pathogens" that escape recognition by the host innate immune response, modulate the acquired immune response, and evade intracellular destruction. We analyzed the genome sequences of members of the family Brucellaceae to assess its evolutionary history from likely free-living soil-based progenitors into highly successful intracellular pathogens. Phylogenetic analysis split the genus into two groups: recently identified and early-dividing "atypical" strains and a highly conserved "classical" core clade containing the major pathogenic species. Lateral gene transfer events brought unique genomic regions into Brucella that differentiated them from Ochrobactrum and allowed the stepwise acquisition of virulence factors that include a type IV secretion system, a perosamine-based O antigen, and systems for sequestering metal ions that are absent in progenitors. Subsequent radiation within the core Brucella resulted in lineages that appear to have evolved within their preferred mammalian hosts, restricting their virulence to become stealth pathogens capable of causing long-term chronic infections.

PATRIC, the bacterial bioinformatics database and analysis resource.

The Pathosystems Resource Integration Center (PATRIC) is the all-bacterial Bioinformatics Resource Center (BRC) (http://www.patricbrc.org). A joint effort by two of the original National Institute of Allergy and Infectious Diseases-funded BRCs, PATRIC provides researchers with an online resource that stores and integrates a variety of data types [e.g. genomics, transcriptomics, protein-protein interactions (PPIs), three-dimensional protein structures and sequence typing data] and associated metadata. Datatypes are summarized for individual genomes and across taxonomic levels. All genomes in PATRIC, currently more than 10,000, are consistently annotated using RAST, the Rapid Annotations using Subsystems Technology. Summaries of different data types are also provided for individual genes, where comparisons of different annotations are available, and also include available transcriptomic data. PATRIC provides a variety of ways for researchers to find data of interest and a private workspace where they can store both genomic and gene associations, and their own private data. Both private and public data can be analyzed together using a suite of tools to perform comparative genomic or transcriptomic analysis. PATRIC also includes integrated information related to disease and PPIs. All the data and integrated analysis and visualization tools are freely available. This manuscript describes updates to the PATRIC since its initial report in the 2007 NAR Database Issue.

The condition-dependent transcriptional landscape of Burkholderia pseudomallei.

Burkholderia pseudomallei (Bp), the causative agent of the often-deadly infectious disease melioidosis, contains one of the largest prokaryotic genomes sequenced to date, at 7.2 Mb with two large circular chromosomes (1 and 2). To comprehensively delineate the Bp transcriptome, we integrated whole-genome tiling array expression data of Bp exposed to >80 diverse physical, chemical, and biological conditions. Our results provide direct experimental support for the strand-specific expression of 5,467 Sanger protein-coding genes, 1,041 operons, and 766 non-coding RNAs. A large proportion of these transcripts displayed condition-dependent expression, consistent with them playing functional roles. The two Bp chromosomes exhibited dramatically different transcriptional landscapes--Chr 1 genes were highly and constitutively expressed, while Chr 2 genes exhibited mosaic expression where distinct subsets were expressed in a strongly condition-dependent manner. We identified dozens of cis-regulatory motifs associated with specific condition-dependent expression programs, and used the condition compendium to elucidate key biological processes associated with two complex pathogen phenotypes--quorum sensing and in vivo infection. Our results demonstrate the utility of a Bp condition-compendium as a community resource for biological discovery. Moreover, the observation that significant portions of the Bp virulence machinery can be activated by specific in vitro cues provides insights into Bp's capacity as an "accidental pathogen", where genetic pathways used by the bacterium to survive in environmental niches may have also facilitated its ability to colonize human hosts.

Bacterial DNA sifted from the Trichoplax adhaerens (Animalia: Placozoa) genome project reveals a putative rickettsial endosymbiont.

Eukaryotic genome sequencing projects often yield bacterial DNA sequences, data typically considered as microbial contamination. However, these sequences may also indicate either symbiont genes or lateral gene transfer (LGT) to host genomes. These bacterial sequences can provide clues about eukaryote-microbe interactions. Here, we used the genome of the primitive animal Trichoplax adhaerens (Metazoa: Placozoa), which is known to harbor an uncharacterized Gram-negative endosymbiont, to search for the presence of bacterial DNA sequences. Bioinformatic and phylogenomic analyses of extracted data from the genome assembly (181 bacterial coding sequences [CDS]) and trace read archive (16S rDNA) revealed a dominant proteobacterial profile strongly skewed to Rickettsiales (Alphaproteobacteria) genomes. By way of phylogenetic analysis of 16S rDNA and 113 proteins conserved across proteobacterial genomes, as well as identification of 27 rickettsial signature genes, we propose a Rickettsiales endosymbiont of T. adhaerens (RETA). The majority (93%) of the identified bacterial CDS belongs to small scaffolds containing prokaryotic-like genes; however, 12 CDS were identified on large scaffolds comprised of eukaryotic-like genes, suggesting that T. adhaerens might have recently acquired bacterial genes. These putative LGTs may coincide with the placozoan's aquatic niche and symbiosis with RETA. This work underscores the rich, and relatively untapped, resource of eukaryotic genome projects for harboring data pertinent to host-microbial interactions. The nature of unknown (or poorly characterized) bacterial species may only emerge via analysis of host genome sequencing projects, particularly if these species are resistant to cell culturing, as are many obligate intracellular microbes. Our work provides methodological insight for such an approach.

Functional assignment of Mycobacterium tuberculosis proteome revealed by genome-scale fold-recognition.

Hundreds of putative enzymes from Mycobacterium tuberculosis as well as other mycobacteria remain categorized as "conserved hypothetical proteins" or "hypothetical proteins", offering little or no information on their functional role in pathogenic and non-pathogenic processes. In this study we have predicted the fold and 3-D structure of more than 99% of all proteins encoded in the genome of M. tuberculosis H37Rv. Fold-recognition, database search, 3-D modelling was performed using Protein Homology/analogy Recognition Engine V 2.0 (Phyre2). These results are used to tentatively assign potential function for unannotated enzymes and proteins. In summary, fold-recognition and structural homology might be used as a complementary tool in genome annotation efforts and furthermore, it can deliver primary sequence-independent information regarding structure, ligands and even substrate specificity for enzymes that display low primary sequence identity with potential homologues in other species.

Helicobacter pylori colonization ameliorates glucose homeostasis in mice through a PPAR γ-dependent mechanism.

BACKGROUND: There is an inverse secular trend between the incidence of obesity and gastric colonization with Helicobacter pylori, a bacterium that can affect the secretion of gastric hormones that relate to energy homeostasis. H. pylori strains that carry the cag pathogenicity island (PAI) interact more intimately with gastric epithelial cells and trigger more extensive host responses than cag(-) strains. We hypothesized that gastric colonization with H. pylori strains differing in cag PAI status exert distinct effects on metabolic and inflammatory phenotypes. METHODOLOGY/PRINCIPAL FINDINGS: To test this hypothesis, we examined metabolic and inflammatory markers in db/db mice and mice with diet-induced obesity experimentally infected with isogenic forms of H. pylori strain 26695: the cag PAI wild-type and its cag PAI mutant strain 99-305. H. pylori colonization decreased fasting blood glucose levels, increased levels of leptin, improved glucose tolerance, and suppressed weight gain. A response found in both wild-type and mutant H. pylori strain-infected mice included decreased white adipose tissue macrophages (ATM) and increased adipose tissue regulatory T cells (Treg) cells. Gene expression analyses demonstrated upregulation of gastric PPAR γ-responsive genes (i.e., CD36 and FABP4) in H. pylori-infected mice. The loss of PPAR γ in immune and epithelial cells in mice impaired the ability of H. pylori to favorably modulate glucose homeostasis and ATM infiltration during high fat feeding. CONCLUSIONS/SIGNIFICANCE: Gastric infection with some commensal strains of H. pylori ameliorates glucose homeostasis in mice through a PPAR γ-dependent mechanism and modulates macrophage and Treg cell infiltration into the abdominal white adipose tissue.

Comparative genomics of early-diverging Brucella strains reveals a novel lipopolysaccharide biosynthesis pathway.

UNLABELLED: Brucella species are Gram-negative bacteria that infect mammals. Recently, two unusual strains (Brucella inopinata BO1T and B. inopinata-like BO2) have been isolated from human patients, and their similarity to some atypical brucellae isolated from Australian native rodent species was noted. Here we present a phylogenomic analysis of the draft genome sequences of BO1T and BO2 and of the Australian rodent strains 83-13 and NF2653 that shows that they form two groups well separated from the other sequenced Brucella spp. Several important differences were noted. Both BO1T and BO2 did not agglutinate significantly when live or inactivated cells were exposed to monospecific A and M antisera against O-side chain sugars composed of N-formyl-perosamine. While BO1T maintained the genes required to synthesize a typical Brucella O-antigen, BO2 lacked many of these genes but still produced a smooth LPS (lipopolysaccharide). Most missing genes were found in the wbk region involved in O-antigen synthesis in classic smooth Brucella spp. In their place, BO2 carries four genes that other bacteria use for making a rhamnose-based O-antigen. Electrophoretic, immunoblot, and chemical analyses showed that BO2 carries an antigenically different O-antigen made of repeating hexose-rich oligosaccharide units that made the LPS water-soluble, which contrasts with the homopolymeric O-antigen of other smooth brucellae that have a phenol-soluble LPS. The results demonstrate the existence of a group of early-diverging brucellae with traits that depart significantly from those of the Brucella species described thus far. IMPORTANCE: This report examines differences between genomes from four new Brucella strains and those from the classic Brucella spp. Our results show that the four new strains are outliers with respect to the previously known Brucella strains and yet are part of the genus, forming two new clades. The analysis revealed important information about the evolution and survival mechanisms of Brucella species, helping reshape our knowledge of this important zoonotic pathogen. One discovery of special importance is that one of the strains, BO2, produces an O-antigen distinct from any that has been seen in any other Brucella isolates to date.

Comparative genomics of early-diverging Brucella strains reveals a novel lipopolysaccharide biosynthesis pathway.

UNLABELLED: Brucella species are Gram-negative bacteria that infect mammals. Recently, two unusual strains (Brucella inopinata BO1(T) and B. inopinata-like BO2) have been isolated from human patients, and their similarity to some atypical brucellae isolated from Australian native rodent species was noted. Here we present a phylogenomic analysis of the draft genome sequences of BO1(T) and BO2 and of the Australian rodent strains 83-13 and NF2653 that shows that they form two groups well separated from the other sequenced Brucella spp. Several important differences were noted. Both BO1(T) and BO2 did not agglutinate significantly when live or inactivated cells were exposed to monospecific A and M antisera against O-side chain sugars composed of N-formyl-perosamine. While BO1(T) maintained the genes required to synthesize a typical Brucella O-antigen, BO2 lacked many of these genes but still produced a smooth LPS (lipopolysaccharide). Most missing genes were found in the wbk region involved in O-antigen synthesis in classic smooth Brucella spp. In their place, BO2 carries four genes that other bacteria use for making a rhamnose-based O-antigen. Electrophoretic, immunoblot, and chemical analyses showed that BO2 carries an antigenically different O-antigen made of repeating hexose-rich oligosaccharide units that made the LPS water-soluble, which contrasts with the homopolymeric O-antigen of other smooth brucellae that have a phenol-soluble LPS. The results demonstrate the existence of a group of early-diverging brucellae with traits that depart significantly from those of the Brucella species described thus far. IMPORTANCE: This report examines differences between genomes from four new Brucella strains and those from the classic Brucella spp. Our results show that the four new strains are outliers with respect to the previously known Brucella strains and yet are part of the genus, forming two new clades. The analysis revealed important information about the evolution and survival mechanisms of Brucella species, helping reshape our knowledge of this important zoonotic pathogen. One discovery of special importance is that one of the strains, BO2, produces an O-antigen distinct from any that has been seen in any other Brucella isolates to date.

A Rickettsia genome overrun by mobile genetic elements provides insight into the acquisition of genes characteristic of an obligate intracellular lifestyle.

We present the draft genome for the Rickettsia endosymbiont of Ixodes scapularis (REIS), a symbiont of the deer tick vector of Lyme disease in North America. Among Rickettsia species (Alphaproteobacteria: Rickettsiales), REIS has the largest genome sequenced to date (>2 Mb) and contains 2,309 genes across the chromosome and four plasmids (pREIS1 to pREIS4). The most remarkable finding within the REIS genome is the extraordinary proliferation of mobile genetic elements (MGEs), which contributes to a limited synteny with other Rickettsia genomes. In particular, an integrative conjugative element named RAGE (for Rickettsiales amplified genetic element), previously identified in scrub typhus rickettsiae (Orientia tsutsugamushi) genomes, is present on both the REIS chromosome and plasmids. Unlike the pseudogene-laden RAGEs of O. tsutsugamushi, REIS encodes nine conserved RAGEs that include F-like type IV secretion systems similar to that of the tra genes encoded in the Rickettsia bellii and R. massiliae genomes. An unparalleled abundance of encoded transposases (>650) relative to genome size, together with the RAGEs and other MGEs, comprise ~35% of the total genome, making REIS one of the most plastic and repetitive bacterial genomes sequenced to date. We present evidence that conserved rickettsial genes associated with an intracellular lifestyle were acquired via MGEs, especially the RAGE, through a continuum of genomic invasions. Robust phylogeny estimation suggests REIS is ancestral to the virulent spotted fever group of rickettsiae. As REIS is not known to invade vertebrate cells and has no known pathogenic effects on I. scapularis, its genome sequence provides insight on the origin of mechanisms of rickettsial pathogenicity.

PATRIC: the comprehensive bacterial bioinformatics resource with a focus on human pathogenic species.

Funded by the National Institute of Allergy and Infectious Diseases, the Pathosystems Resource Integration Center (PATRIC) is a genomics-centric relational database and bioinformatics resource designed to assist scientists in infectious-disease research. Specifically, PATRIC provides scientists with (i) a comprehensive bacterial genomics database, (ii) a plethora of associated data relevant to genomic analysis, and (iii) an extensive suite of computational tools and platforms for bioinformatics analysis. While the primary aim of PATRIC is to advance the knowledge underlying the biology of human pathogens, all publicly available genome-scale data for bacteria are compiled and continually updated, thereby enabling comparative analyses to reveal the basis for differences between infectious free-living and commensal species. Herein we summarize the major features available at PATRIC, dividing the resources into two major categories: (i) organisms, genomes, and comparative genomics and (ii) recurrent integration of community-derived associated data. Additionally, we present two experimental designs typical of bacterial genomics research and report on the execution of both projects using only PATRIC data and tools. These applications encompass a broad range of the data and analysis tools available, illustrating practical uses of PATRIC for the biologist. Finally, a summary of PATRIC's outreach activities, collaborative endeavors, and future research directions is provided.

Integration and visualization of host-pathogen data related to infectious diseases.

MOTIVATION: Infectious disease research is generating an increasing amount of disparate data on pathogenic systems. There is a growing need for resources that effectively integrate, analyze, deliver and visualize these data, both to improve our understanding of infectious diseases and to facilitate the development of strategies for disease control and prevention. RESULTS: We have developed Disease View, an online host-pathogen resource that enables infectious disease-centric access, analysis and visualization of host-pathogen interactions. In this resource, we associate infectious diseases with corresponding pathogens, provide information on pathogens, pathogen virulence genes and the genetic and chemical evidences for the human genes that are associated with the diseases. We also deliver the relationships between pathogens, genes and diseases in an interactive graph and provide the geolocation reports of associated diseases around the globe in real time. Unlike many other resources, we have applied an iterative, user-centered design process to the entire resource development, including data acquisition, analysis and visualization. AVAILABILITY AND IMPLEMENTATION: Freely available at http://www.patricbrc.org; all major web browsers supported. CONTACT: cmao@vbi.vt.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Supervised learning and prediction of physical interactions between human and HIV proteins.

BACKGROUND: Infectious diseases result in millions of deaths each year. Physical interactions between pathogen and host proteins often form the basis of such infections. While a number of methods have been proposed for predicting protein-protein interactions (PPIs), they have primarily focused on intra-species protein-protein interactions. METHODOLOGY: We present an application of a supervised learning method for predicting physical interactions between host and pathogen proteins, using the human-HIV system. Using a Support Vector Machine with a linear kernel, we explore the use of a number of features including domain profiles, protein sequence k-mers, and properties of human proteins in a human PPI network. We achieve the best cross-validation performance when we use a combination of all three of these features. At a precision value of 70% we obtain recall values greater than 40%, depending on the ratio of positive examples to negative examples used during training. We use a classifier trained using these features to predict new PPIs between human and HIV proteins. We focus our discussion on those predicted interactions that involve human proteins known to be critical for HIV replication and propagation. Examples of predicted interactions with support in the literature include those necessary for viral attachment to the host membrane and subsequent invasion of the host cell. SIGNIFICANCE: Unlike intra-species PPIs, host-pathogen PPIs have not yet been experimentally detected on a large scale, though they are likely to play important roles in pathogenesis and disease outcomes. Computational methods that can robustly and accurately predict host-pathogen PPIs hold the promise of guiding future experiments and gaining insights into potential mechanisms of pathogenesis.

Analysis of high-throughput sequencing data.

Next-generation sequencing has revolutionized biology by exponentially increasing sequencing output while dramatically lowering costs. High-throughput sequence data with shorter reads has opened up new applications such as whole genome resequencing, indel and SNP detection, transcriptome sequencing, etc. Several tools are available for the analysis of high-throughput sequencing data. In this chapter, we describe the use of an ultrafast alignment program, Bowtie, to align short-read sequence (SRS) data against the Arabidopsis reference genome. The alignment files generated from Bowtie will be used to identify SNPs and indels using Maq.

Abscisic acid regulates inflammation via ligand-binding domain-independent activation of peroxisome proliferator-activated receptor gamma.

Abscisic acid (ABA) has shown efficacy in the treatment of diabetes and inflammation; however, its molecular targets and the mechanisms of action underlying its immunomodulatory effects remain unclear. This study investigates the role of peroxisome proliferator-activated receptor γ (PPAR γ) and lanthionine synthetase C-like 2 (LANCL2) as molecular targets for ABA. We demonstrate that ABA increases PPAR γ reporter activity in RAW 264.7 macrophages and increases ppar γ expression in vivo, although it does not bind to the ligand-binding domain of PPAR γ. LANCL2 knockdown studies provide evidence that ABA-mediated activation of macrophage PPAR γ is dependent on lancl2 expression. Consistent with the association of LANCL2 with G proteins, we provide evidence that ABA increases cAMP accumulation in immune cells. ABA suppresses LPS-induced prostaglandin E(2) and MCP-1 production via a PPAR γ-dependent mechanism possibly involving activation of PPAR γ and suppression of NF-κB and nuclear factor of activated T cells. LPS challenge studies in PPAR γ-expressing and immune cell-specific PPAR γ null mice demonstrate that ABA down-regulates toll-like receptor 4 expression in macrophages and T cells in vivo through a PPAR γ-dependent mechanism. Global transcriptomic profiling and confirmatory quantitative RT-PCR suggest novel candidate targets and demonstrate that ABA treatment mitigates the effect of LPS on the expression of genes involved in inflammation, metabolism, and cell signaling, in part, through PPAR γ. In conclusion, ABA decreases LPS-mediated inflammation and regulates innate immune responses through a bifurcating pathway involving LANCL2 and an alternative, ligand-binding domain-independent mechanism of PPAR γ activation.

The human-bacterial pathogen protein interaction networks of Bacillus anthracis, Francisella tularensis, and Yersinia pestis.

BACKGROUND: Bacillus anthracis, Francisella tularensis, and Yersinia pestis are bacterial pathogens that can cause anthrax, lethal acute pneumonic disease, and bubonic plague, respectively, and are listed as NIAID Category A priority pathogens for possible use as biological weapons. However, the interactions between human proteins and proteins in these bacteria remain poorly characterized leading to an incomplete understanding of their pathogenesis and mechanisms of immune evasion. METHODOLOGY: In this study, we used a high-throughput yeast two-hybrid assay to identify physical interactions between human proteins and proteins from each of these three pathogens. From more than 250,000 screens performed, we identified 3,073 human-B. anthracis, 1,383 human-F. tularensis, and 4,059 human-Y. pestis protein-protein interactions including interactions involving 304 B. anthracis, 52 F. tularensis, and 330 Y. pestis proteins that are uncharacterized. Computational analysis revealed that pathogen proteins preferentially interact with human proteins that are hubs and bottlenecks in the human PPI network. In addition, we computed modules of human-pathogen PPIs that are conserved amongst the three networks. Functionally, such conserved modules reveal commonalities between how the different pathogens interact with crucial host pathways involved in inflammation and immunity. SIGNIFICANCE: These data constitute the first extensive protein interaction networks constructed for bacterial pathogens and their human hosts. This study provides novel insights into host-pathogen interactions.

Transcriptome sequencing and comparative analysis of cucumber flowers with different sex types.

BACKGROUND: Cucumber, Cucumis sativus L., is an economically and nutritionally important crop of the Cucurbitaceae family and has long served as a primary model system for sex determination studies. Recently, the sequencing of its whole genome has been completed. However, transcriptome information of this species is still scarce, with a total of around 8,000 Expressed Sequence Tag (EST) and mRNA sequences currently available in GenBank. In order to gain more insights into molecular mechanisms of plant sex determination and provide the community a functional genomics resource that will facilitate cucurbit research and breeding, we performed transcriptome sequencing of cucumber flower buds of two near-isogenic lines, WI1983G, a gynoecious plant which bears only pistillate flowers, and WI1983H, a hermaphroditic plant which bears only bisexual flowers. RESULT: Using Roche-454 massive parallel pyrosequencing technology, we generated a total of 353,941 high quality EST sequences with an average length of 175bp, among which 188,255 were from gynoecious flowers and 165,686 from hermaphroditic flowers. These EST sequences, together with approximately 5,600 high quality cucumber EST and mRNA sequences available in GenBank, were clustered and assembled into 81,401 unigenes, of which 28,452 were contigs and 52,949 were singletons. The unigenes and ESTs were further mapped to the cucumber genome and more than 500 alternative splicing events were identified in 443 cucumber genes. The unigenes were further functionally annotated by comparing their sequences to different protein and functional domain databases and assigned with Gene Ontology (GO) terms. A biochemical pathway database containing 343 predicted pathways was also created based on the annotations of the unigenes. Digital expression analysis identified approximately 200 differentially expressed genes between flowers of WI1983G and WI1983H and provided novel insights into molecular mechanisms of plant sex determination process. Furthermore, a set of SSR motifs and high confidence SNPs between WI1983G and WI1983H were identified from the ESTs, which provided the material basis for future genetic linkage and QTL analysis. CONCLUSION: A large set of EST sequences were generated from cucumber flower buds of two different sex types. Differentially expressed genes between these two different sex-type flowers, as well as putative SSR and SNP markers, were identified. These EST sequences provide valuable information to further understand molecular mechanisms of plant sex determination process and forms a rich resource for future functional genomics analysis, marker development and cucumber breeding.

Phylogeny of gammaproteobacteria.

The phylogeny of the large bacterial class Gammaproteobacteria has been difficult to resolve. Here we apply a telescoping multiprotein approach to the problem for 104 diverse gammaproteobacterial genomes, based on a set of 356 protein families for the whole class and even larger sets for each of four cohesive subregions of the tree. Although the deepest divergences were resistant to full resolution, some surprising patterns were strongly supported. A representative of the Acidithiobacillales routinely appeared among the outgroup members, suggesting that in conflict with rRNA-based phylogenies this order does not belong to Gammaproteobacteria; instead, it (and, independently, "Mariprofundus") diverged after the establishment of the Alphaproteobacteria yet before the betaproteobacteria/gammaproteobacteria split. None of the orders Alteromonadales, Pseudomonadales, or Oceanospirillales were monophyletic; we obtained strong support for clades that contain some but exclude other members of all three orders. Extreme amino acid bias in the highly A+T-rich genome of Candidatus Carsonella prevented its reliable placement within Gammaproteobacteria, and high bias caused artifacts that limited the resolution of the relationships of other insect endosymbionts, which appear to have had multiple origins, although the unbiased genome of the endosymbiont Sodalis acted as an attractor for them. Instability was observed for the root of the Enterobacteriales, with nearly equal subsets of the protein families favoring one or the other of two alternative root positions; the nematode symbiont Photorhabdus was identified as a disruptor whose omission helped stabilize the Enterobacteriales root.