Phobos LIFE (Living Interplanetary Flight Experiment).

The Planetary Society's Phobos Living Interplanetary Flight Experiment (Phobos LIFE) flew in the sample return capsule of the Russian Federal Space Agency's Phobos Grunt mission and was to have been a test of one aspect of the hypothesis that life can move between nearby planets within ejected rocks. Although the Phobos Grunt mission failed, we present here the scientific and engineering design and motivation of the Phobos LIFE experiment to assist with the scientific and engineering design of similar future experiments. Phobos LIFE flew selected organisms in a simulated meteoroid. The 34-month voyage would have been the first such test to occur in the high-radiation environment outside the protection of Earth's magnetosphere for more than a few days. The patented Phobos LIFE "biomodule" is an 88 g cylinder consisting of a titanium outer shell, several types of redundant seals, and 31 individual Delrin sample containers. Phobos LIFE contained 10 different organisms, representing all three domains of life, and one soil sample. The organisms are all very well characterized, most with sequenced genomes. Most are extremophiles, and most have flown in low Earth orbit. Upon return from space, the health and characteristics of organisms were to have been compared with controls that remained on Earth and have not yet been opened.

Genomic Encyclopedia of Bacterial and Archaeal Type Strains, Phase III: the genomes of soil and plant-associated and newly described type strains.

The Genomic Encyclopedia of Bacteria and Archaea (GEBA) project was launched by the JGI in 2007 as a pilot project to sequence about 250 bacterial and archaeal genomes of elevated phylogenetic diversity. Herein, we propose to extend this approach to type strains of prokaryotes associated with soil or plants and their close relatives as well as type strains from newly described species. Understanding the microbiology of soil and plants is critical to many DOE mission areas, such as biofuel production from biomass, biogeochemistry, and carbon cycling. We are also targeting type strains of novel species while they are being described. Since 2006, about 630 new species have been described per year, many of which are closely aligned to DOE areas of interest in soil, agriculture, degradation of pollutants, biofuel production, biogeochemical transformation, and biodiversity.

Predicting and exploring network components involved in pathogenesis in the malaria parasite via novel subnetwork alignments.

BACKGROUND: Malaria is a major health threat, affecting over 40% of the world's population. The latest report released by the World Health Organization estimated about 207 million cases of malaria infection, and about 627,000 deaths in 2012 alone. During the past decade, new therapeutic targets have been identified and are at various stages of characterization, thanks to the emerging omics-based technologies. However, the mechanism of malaria pathogenesis remains largely unknown. In this paper, we employ a novel neighborhood subnetwork alignment approach to identify network components that are potentially involved in pathogenesis. RESULTS: Our module-based subnetwork alignment approach identified 24 functional homologs of pathogenesis-related proteins in the malaria parasite P. falciparum, using the protein-protein interaction networks in Escherichia coli as references. Eighteen out of these 24 proteins are associated with 418 other proteins that are related to DNA replication, transcriptional regulation, translation, signaling, metabolism, cell cycle regulation, as well as cytoadherence and entry to the host. CONCLUSIONS: The subnetwork alignments and subsequent protein-protein association network mining predicted a group of malarial proteins that may be involved in parasite development and parasite-host interaction, opening a new systems-level view of parasite pathogenesis and virulence.

Heavy path mining of protein-protein associations in the malaria parasite.

Annotating and understanding the function of proteins and other elements in a genome can be difficult in the absence of a well-studied and evolutionarily close relative. The causative agent of malaria, one of the oldest and most deadly global infectious diseases, is a good example of this problem. The burden of malaria is huge and there is a pressing need for new, more effective antimalarial strategies. However, techniques such as homology-dependent annotation transfer are severely impaired in this parasite because there are no well-understood close relatives. To circumvent this approach we developed a network-based method that uses a heavy path network-mining algorithm. We uncovered the protein-protein associations that are implicated in important cellular processes including genome integrity, DNA repair, transcriptional regulation, invasion, and pathogenesis, thus demonstrating the utility of this method. The URL of the source code for super-sequence mining method is http://www.cs.utsa.edu/~korkmaz/research/heavy-path-mining/.

Exploring systems affected by the heat shock response in Plasmodium falciparum via protein association networks.

The heat shock response is a general mechanism by which organisms deal with physical insults such as sudden changes in temperature, osmotic and oxidative stresses, and exposure to toxic substances. Plasmodium falciparum is exposed to drastic temperature changes as a part of its life cycle and maintains an extensive repertoire of heat shock response-related proteins. As these proteins serve to maintain the parasite in the face of anti-malarial drugs as well, better understanding of the heat shock-related systems in the malaria parasite will lead to therapeutic approaches that frustrate these systems, leading to more effective use of anti-malarials. Here we use protein association networks to broaden our understanding of the systems impacted by and/or implicated in the heat shock response.

Genomic Encyclopedia of Type Strains, Phase I: The one thousand microbial genomes (KMG-I) project.

The Genomic Encyclopedia of Bacteria and Archaea (GEBA) project was launched by the JGI in 2007 as a pilot project with the objective of sequencing 250 bacterial and archaeal genomes. The two major goals of that project were (a) to test the hypothesis that there are many benefits to the use the phylogenetic diversity of organisms in the tree of life as a primary criterion for generating their genome sequence and (b) to develop the necessary framework, technology and organization for large-scale sequencing of microbial isolate genomes. While the GEBA pilot project has not yet been entirely completed, both of the original goals have already been successfully accomplished, leading the way for the next phase of the project. Here we propose taking the GEBA project to the next level, by generating high quality draft genomes for 1,000 bacterial and archaeal strains. This represents a combined 16-fold increase in both scale and speed as compared to the GEBA pilot project (250 isolate genomes in 4+ years). We will follow a similar approach for organism selection and sequencing prioritization as was done for the GEBA pilot project (i.e. phylogenetic novelty, availability and growth of cultures of type strains and DNA extraction capability), focusing on type strains as this ensures reproducibility of our results and provides the strongest linkage between genome sequences and other knowledge about each strain. In turn, this project will constitute a pilot phase of a larger effort that will target the genome sequences of all available type strains of the Bacteria and Archaea.

A novel subnetwork alignment approach predicts new components of the cell cycle regulatory apparatus in Plasmodium falciparum.

BACKGROUND: According to the World Health organization, half the world's population is at risk of contracting malaria. They estimated that in 2010 there were 219 million cases of malaria, resulting in 660,000 deaths and an enormous economic burden on the countries where malaria is endemic. The adoption of various high-throughput genomics-based techniques by malaria researchers has meant that new avenues to the study of this disease are being explored and new targets for controlling the disease are being developed. Here, we apply a novel neighborhood subnetwork alignment approach to identify the interacting elements that help regulate the cell cycle of the malaria parasite Plasmodium falciparum. RESULTS: Our novel subnetwork alignment approach was used to compare networks in Escherichia coli and P. falciparum. Some 574 P. falciparum proteins were revealed as functional orthologs of known cell cycle proteins in E. coli. Over one third of these predicted functional orthologs were annotated as "conserved Plasmodium proteins" or "putative uncharacterized proteins" of unknown function. The predicted functionalities included cyclins, kinases, surface antigens, transcriptional regulators and various functions related to DNA replication, repair and cell division. CONCLUSIONS: The results of our analysis demonstrate the power of our subnetwork alignment approach to assign functionality to previously unannotated proteins. Here, the focus was on proteins involved in cell cycle regulation. These proteins are involved in the control of diverse aspects of the parasite lifecycle and of important aspects of pathogenesis.

Module-based subnetwork alignments reveal novel transcriptional regulators in malaria parasite Plasmodium falciparum.

BACKGROUND: Malaria causes over one million deaths annually, posing an enormous health and economic burden in endemic regions. The completion of genome sequencing of the causative agents, a group of parasites in the genus Plasmodium, revealed potential drug and vaccine candidates. However, genomics-driven target discovery has been significantly hampered by our limited knowledge of the cellular networks associated with parasite development and pathogenesis. In this paper, we propose an approach based on aligning neighborhood PPI subnetworks across species to identify network components in the malaria parasite P. falciparum. RESULTS: Instead of only relying on sequence similarities to detect functional orthologs, our approach measures the conservation between the neighborhood subnetworks in protein-protein interaction (PPI) networks in two species, P. falciparum and E. coli. 1,082 P. falciparum proteins were predicted as functional orthologs of known transcriptional regulators in the E. coli network, including general transcriptional regulators, parasite-specific transcriptional regulators in the ApiAP2 protein family, and other potential regulatory proteins. They are implicated in a variety of cellular processes involving chromatin remodeling, genome integrity, secretion, invasion, protein processing, and metabolism. CONCLUSIONS: In this proof-of-concept study, we demonstrate that a subnetwork alignment approach can reveal previously uncharacterized members of the subnetworks, which opens new opportunities to identify potential therapeutic targets and provide new insights into parasite biology, pathogenesis and virulence. This approach can be extended to other systems, especially those with poor genome annotation and a paucity of knowledge about cellular networks.

Protease-associated cellular networks in malaria parasite Plasmodium falciparum.

BACKGROUND: Malaria continues to be one of the most severe global infectious diseases, responsible for 1-2 million deaths yearly. The rapid evolution and spread of drug resistance in parasites has led to an urgent need for the development of novel antimalarial targets. Proteases are a group of enzymes that play essential roles in parasite growth and invasion. The possibility of designing specific inhibitors for proteases makes them promising drug targets. Previously, combining a comparative genomics approach and a machine learning approach, we identified the complement of proteases (degradome) in the malaria parasite Plasmodium falciparum and its sibling species 123, providing a catalog of targets for functional characterization and rational inhibitor design. Network analysis represents another route to revealing the role of proteins in the biology of parasites and we use this approach here to expand our understanding of the systems involving the proteases of P. falciparum. RESULTS: We investigated the roles of proteases in the parasite life cycle by constructing a network using protein-protein association data from the STRING database 4, and analyzing these data, in conjunction with the data from protein-protein interaction assays using the yeast 2-hybrid (Y2H) system 5, blood stage microarray experiments 678, proteomics 9101112, literature text mining, and sequence homology analysis. Seventy-seven (77) out of 124 predicted proteases were associated with at least one other protein, constituting 2,431 protein-protein interactions (PPIs). These proteases appear to play diverse roles in metabolism, cell cycle regulation, invasion and infection. Their degrees of connectivity (i.e., connections to other proteins), range from one to 143. The largest protease-associated sub-network is the ubiquitin-proteasome system which is crucial for protein recycling and stress response. Proteases are also implicated in heat shock response, signal peptide processing, cell cycle progression, transcriptional regulation, and signal transduction networks. CONCLUSIONS: Our network analysis of proteases from P. falciparum uses a so-called guilt-by-association approach to extract sets of proteins from the proteome that are candidates for further study. Novel protease targets and previously unrecognized members of the protease-associated sub-systems provide new insights into the mechanisms underlying parasitism, pathogenesis and virulence.

Comparative genomics of the family Vibrionaceae reveals the wide distribution of genes encoding virulence-associated proteins.

BACKGROUND: Species of the family Vibrionaceae are ubiquitous in marine environments. Several of these species are important pathogens of humans and marine species. Evidence indicates that genetic exchange plays an important role in the emergence of new pathogenic strains within this family. Data from the sequenced genomes of strains in this family could show how the genes encoded by all these strains, known as the pangenome, are distributed. Information about the core, accessory and panproteome of this family can show how, for example, genes encoding virulence-associated proteins are distributed and help us understand how virulence emerges. RESULTS: We deduced the complete set of orthologs for eleven strains from this family. The core proteome consists of 1,882 orthologous groups, which is 28% of the 6,629 orthologous groups in this family. There were 4,411 accessory orthologous groups (i.e., proteins that occurred in from 2 to 10 proteomes) and 5,584 unique proteins (encoded once on only one of the eleven genomes). Proteins that have been associated with virulence in V. cholerae were widely distributed across the eleven genomes, but the majority was found only on the genomes of the two V. cholerae strains examined. CONCLUSIONS: The proteomes are reflective of the differing evolutionary trajectories followed by different strains to similar phenotypes. The composition of the proteomes supports the notion that genetic exchange among species of the Vibrionaceae is widespread and that this exchange aids these species in adapting to their environments.

Genomic and systems evolution in Vibrionaceae species.

BACKGROUND: The steadily increasing number of prokaryotic genomes has accelerated the study of genome evolution; in particular, the availability of sets of genomes from closely related bacteria has facilitated the exploration of the mechanisms underlying genome plasticity. The family Vibrionaceae is found in the Gammaproteobacteria and is abundant in aquatic environments. Taxa from the family Vibrionaceae are diversified in their life styles; some species are free living, others are symbiotic, and others are human pathogens. This diversity makes this family a useful set of model organisms for studying bacterial evolution. This evolution is driven by several forces, among them gene duplication and lateral gene transfer, which are believed to provide raw material for functional redundancy and novelty. The resultant gene copy increase in one genome is then detected as lineage-specific expansion (LSE). RESULTS: Here we present the results of a detailed comparison of the genomes of eleven Vibrionaceae strains that have distinct life styles and distinct phenotypes. The core genome shared by all eleven strains is composed of 1,882 genes, which make up about 31%-50% of the genome repertoire. We further investigated the distribution and features of genes that have been specifically expanded in one unique lineage of the eleven strains. Abundant duplicate genes have been identified in the eleven Vibrionaceae strains, with 1-11% of the whole genomes composed lineage specific radiations. These LSEs occurred in two distinct patterns: the first type yields one or more copies of a single gene; we call this a single gene expansion. The second pattern has a high evolutionary impact, as the expansion involves two or more gene copies in a block, with the duplicated block located next to the original block (a contiguous block expansion) or at some distance from the original block (a discontiguous block expansion). We showed that LSEs involve genes that are tied to defense and pathogenesis mechanisms as well as in the fundamental life cycle of Vibrionaceae species. CONCLUSION: Our results provide evidence of genome plasticity and rapid evolution within the family Vibrionaceae. The comparisons point to sources of genomic variation and candidates for lineage-specific adaptations of each Vibrionaceae pathogen or nonpathogen strain. Such lineage specific expansions could reveal components in bacterial systems that, by their enhanced genetic variability, can be tied to responses to environmental challenges, interesting phenotypes, or adaptive pathogenic responses to host challenges.

Biological Resource Centers and Systems Biology.

There are hundreds of Biological Resource Centers (BRCs) around the world, holding many little-studied microorganism. The proportion of bacterial strains that is well represented in the sequence and literature databases may be as low as 1%. This body of unexplored diversity represents an untapped source of useful strains and derived products. However, a modicum of phenotypic data is available for almost all the bacterial strains held by BRCs around the world. It is at the phenotypic level that our knowledge of the well-studied strains of bacteria and the many yet-to-be studied strains intersects. This suggests we might leverage the phenotypic data from the data-poor bacteria with the omics data from the data-rich bacteria, using our knowledge of their evolutionary relationships, to map the metabolic networks of the little-known bacteria. This systems biology-based approach is a new way to explore the diversity harbored in BRCs.

A novel lineage of proteobacteria involved in formation of marine Fe-oxidizing microbial mat communities.

BACKGROUND: For decades it has been recognized that neutrophilic Fe-oxidizing bacteria (FeOB) are associated with hydrothermal venting of Fe(II)-rich fluids associated with seamounts in the world's oceans. The evidence was based almost entirely on the mineralogical remains of the microbes, which themselves had neither been brought into culture or been assigned to a specific phylogenetic clade. We have used both cultivation and cultivation-independent techniques to study Fe-rich microbial mats associated with hydrothermal venting at Loihi Seamount, a submarine volcano. METHODOLOGY/PRINCIPLE FINDINGS: Using gradient enrichment techniques, two iron-oxidizing bacteria, strains PV-1 and JV-1, were isolated. Chemolithotrophic growth was observed under microaerobic conditions; Fe(II) and Fe(0) were the only energy sources that supported growth. Both strains produced filamentous stalk-like structures composed of multiple nanometer sized fibrils of Fe-oxyhydroxide. These were consistent with mineralogical structures found in the iron mats. Phylogenetic analysis of the small subunit (SSU) rRNA gene demonstrated that strains PV-1 and JV-1 were identical and formed a monophyletic group deeply rooted within the Proteobacteria. The most similar sequence (85.3% similarity) from a cultivated isolate came from Methylophaga marina. Phylogenetic analysis of the RecA and GyrB protein sequences confirmed that these strains are distantly related to other members of the Proteobacteria. A cultivation-independent analysis of the SSU rRNA gene by terminal-restriction fragment (T-RF) profiling showed that this phylotype was most common in a variety of microbial mats collected at different times and locations at Loihi. CONCLUSIONS: On the basis of phylogenetic and physiological data, it is proposed that isolate PV-1(T) ( = ATCC BAA-1019: JCM 14766) represents the type strain of a novel species in a new genus, Mariprofundus ferrooxydans gen. nov., sp. nov. Furthermore, the strain is the first cultured representative of a new candidatus class of the Proteobacteria that is widely distributed in deep-sea environments, Candidatus zeta (zeta)-Proteobacteria cl. nov.

Genome evolution and functional divergence in Yersinia.

The steadily increasing number of prokaryotic genomes has accelerated the study of genome evolution; in particular, the availability of sets of genomes from closely related bacteria has made exploration of questions surrounding the evolution of pathogenesis tractable. Here we present the results of a detailed comparison of the genomes of Yersinia pseudotuberculosis IP32593 and three strains of Yersinia pestis (CO92, KIM10, and 91001). There appear to be between 241 and 275 multigene families in these organisms. There are 2,568 genes that are identical in the three Y. pestis strains, but differ from the Y. pseudotuberculosis strain. The changes found in some of these families, such as the kinases, proteases, and transporters, are illustrative of how the evolutionary jump from the free-living enteropathogen Y. pseudotuberculosis to the obligate host-borne blood pathogen Y. pestis was achieved. We discuss the composition of some of the most important families and discuss the observed divergence between Y. pseudotuberculosis and Y. pestis homologs.

Computational aspects of systematic biology.

We review the resources available to systematic biologists who wish to use computers to build classifications. Algorithm development is in an early stage, and only a few examples of integrated applications for systematic biology are available. The availability of data is crucial if systematic biology is to enter the computer age.

Self-organizing and self-correcting classifications of biological data.

MOTIVATION: Rapid, automated means of organizing biological data are required if we hope to keep abreast of the flood of data emanating from sequencing, microarray and similar high-throughput analyses. Faced with the need to validate the annotation of thousands of sequences and to generate biologically meaningful classifications based on the sequence data, we turned to statistical methods in order to automate these processes. RESULTS: An algorithm for automated classification based on evolutionary distance data was written in S. The algorithm was tested on a dataset of 1436 small subunit ribosomal RNA sequences and was able to classify the sequences according to an extant scheme, use statistical measurements of group membership to detect sequences that were misclassified within this scheme and produce a new classification. In this study, the use of the algorithm to address problems in prokaryotic taxonomy is discussed. AVAILABILITY: S-Plus is available from Insightful, Inc. An S-Plus implementation of the algorithm and the associated data are available at http://taxoweb.mmg.msu.edu/datasets

Exploring prokaryotic taxonomy.

Techniques drawn from exploratory data analysis, using tools found in the S-Plus statistical software package, have been used to inspect and maintain the Bergey's Taxonomic Outline and to move towards an automated and community-based means of working on the outline. These techniques can be used to classify sequences from unnamed and uncultured organisms, to visualize errors in the taxonomy or in the curation of the sequences, to suggest emendations to the taxonomy or to the classification of extant species and to complement the visualization of phylogenies based on treeing methods. A dataset of more than 9200 aligned small-subunit rRNA sequences was analysed in the context of the current taxonomic outline. The use of the algorithm in exploring and modifying the taxonomy is illustrated with an example drawn from the family Comamonadaceae.