@article {19716, title = {TIGRFAMs and Genome Properties in 2013.}, journal = {Nucleic Acids Res}, volume = {41}, year = {2013}, month = {2013 Jan}, pages = {D387-95}, abstract = {

TIGRFAMs, available online at http://www.jcvi.org/tigrfams is a database of protein family definitions. Each entry features a seed alignment of trusted representative sequences, a hidden Markov model (HMM) built from that alignment, cutoff scores that let automated annotation pipelines decide which proteins are members, and annotations for transfer onto member proteins. Most TIGRFAMs models are designated equivalog, meaning they assign a specific name to proteins conserved in function from a common ancestral sequence. Models describing more functionally heterogeneous families are designated subfamily or domain, and assign less specific but more widely applicable annotations. The Genome Properties database, available at http://www.jcvi.org/genome-properties, specifies how computed evidence, including TIGRFAMs HMM results, should be used to judge whether an enzymatic pathway, a protein complex or another type of molecular subsystem is encoded in a genome. TIGRFAMs and Genome Properties content are developed in concert because subsystems reconstruction for large numbers of genomes guides selection of seed alignment sequences and cutoff values during protein family construction. Both databases specialize heavily in bacterial and archaeal subsystems. At present, 4284 models appear in TIGRFAMs, while 628 systems are described by Genome Properties. Content derives both from subsystem discovery work and from biocuration of the scientific literature.

}, keywords = {Databases, Protein, Genome, Archaeal, Genome, Bacterial, Genomics, Internet, Markov chains, Molecular Sequence Annotation, Proteins, sequence alignment}, issn = {1362-4962}, doi = {10.1093/nar/gks1234}, author = {Haft, Daniel H and Jeremy D Selengut and Richter, Roland A and Harkins, Derek and Basu, Malay K and Beck, Erin} } @article {19723, title = {Archaeosortases and exosortases are widely distributed systems linking membrane transit with posttranslational modification.}, journal = {J Bacteriol}, volume = {194}, year = {2012}, month = {2012 Jan}, pages = {36-48}, abstract = {

Multiple new prokaryotic C-terminal protein-sorting signals were found that reprise the tripartite architecture shared by LPXTG and PEP-CTERM: motif, TM helix, basic cluster. Defining hidden Markov models were constructed for all. PGF-CTERM occurs in 29 archaeal species, some of which have more than 50 proteins that share the domain. PGF-CTERM proteins include the major cell surface protein in Halobacterium, a glycoprotein with a partially characterized diphytanylglyceryl phosphate linkage near its C terminus. Comparative genomics identifies a distant exosortase homolog, designated archaeosortase A (ArtA), as the likely protein-processing enzyme for PGF-CTERM. Proteomics suggests that the PGF-CTERM region is removed. Additional systems include VPXXXP-CTERM/archeaosortase B in two of the same archaea and PEF-CTERM/archaeosortase C in four others. Bacterial exosortases often fall into subfamilies that partner with very different cohorts of extracellular polymeric substance biosynthesis proteins; several species have multiple systems. Variant systems include the VPDSG-CTERM/exosortase C system unique to certain members of the phylum Verrucomicrobia, VPLPA-CTERM/exosortase D in several alpha- and deltaproteobacterial species, and a dedicated (single-target) VPEID-CTERM/exosortase E system in alphaproteobacteria. Exosortase-related families XrtF in the class Flavobacteria and XrtG in Gram-positive bacteria mark distinctive conserved gene neighborhoods. A picture emerges of an ancient and now well-differentiated superfamily of deeply membrane-embedded protein-processing enzymes. Their target proteins are destined to transit cellular membranes during their biosynthesis, during which most undergo additional posttranslational modifications such as glycosylation.

}, keywords = {Amino Acid Sequence, Aminoacyltransferases, Archaeal Proteins, Bacterial Proteins, Cell Membrane, Cysteine Endopeptidases, Gene Expression Regulation, Archaeal, Gene Expression Regulation, Bacterial, Gene Expression Regulation, Enzymologic, Molecular Sequence Data, Protein Processing, Post-Translational}, issn = {1098-5530}, doi = {10.1128/JB.06026-11}, author = {Haft, Daniel H and Payne, Samuel H and Jeremy D Selengut} } @article {19718, title = {Genomic insights to SAR86, an abundant and uncultivated marine bacterial lineage.}, journal = {ISME J}, volume = {6}, year = {2012}, month = {2012 Jun}, pages = {1186-99}, abstract = {

Bacteria in the 16S rRNA clade SAR86 are among the most abundant uncultivated constituents of microbial assemblages in the surface ocean for which little genomic information is currently available. Bioinformatic techniques were used to assemble two nearly complete genomes from marine metagenomes and single-cell sequencing provided two more partial genomes. Recruitment of metagenomic data shows that these SAR86 genomes substantially increase our knowledge of non-photosynthetic bacteria in the surface ocean. Phylogenomic analyses establish SAR86 as a basal and divergent lineage of γ-proteobacteria, and the individual genomes display a temperature-dependent distribution. Modestly sized at 1.25-1.7 Mbp, the SAR86 genomes lack several pathways for amino-acid and vitamin synthesis as well as sulfate reduction, trends commonly observed in other abundant marine microbes. SAR86 appears to be an aerobic chemoheterotroph with the potential for proteorhodopsin-based ATP generation, though the apparent lack of a retinal biosynthesis pathway may require it to scavenge exogenously-derived pigments to utilize proteorhodopsin. The genomes contain an expanded capacity for the degradation of lipids and carbohydrates acquired using a wealth of tonB-dependent outer membrane receptors. Like the abundant planktonic marine bacterial clade SAR11, SAR86 exhibits metabolic streamlining, but also a distinct carbon compound specialization, possibly avoiding competition.

}, keywords = {Computational Biology, Gammaproteobacteria, Genome, Bacterial, Genomic Library, metagenomics, Oceans and Seas, Phylogeny, plankton, Rhodopsin, RNA, Ribosomal, 16S, Seawater}, issn = {1751-7370}, doi = {10.1038/ismej.2011.189}, author = {Dupont, Chris L and Rusch, Douglas B and Yooseph, Shibu and Lombardo, Mary-Jane and Richter, R Alexander and Valas, Ruben and Novotny, Mark and Yee-Greenbaum, Joyclyn and Jeremy D Selengut and Haft, Dan H and Halpern, Aaron L and Lasken, Roger S and Nealson, Kenneth and Friedman, Robert and Venter, J Craig} } @article {19721, title = {InterPro in 2011: new developments in the family and domain prediction database.}, journal = {Nucleic Acids Res}, volume = {40}, year = {2012}, month = {2012 Jan}, pages = {D306-12}, abstract = {

InterPro (http://www.ebi.ac.uk/interpro/) is a database that integrates diverse information about protein families, domains and functional sites, and makes it freely available to the public via Web-based interfaces and services. Central to the database are diagnostic models, known as signatures, against which protein sequences can be searched to determine their potential function. InterPro has utility in the large-scale analysis of whole genomes and meta-genomes, as well as in characterizing individual protein sequences. Herein we give an overview of new developments in the database and its associated software since 2009, including updates to database content, curation processes and Web and programmatic interfaces.

}, keywords = {Databases, Protein, Protein Structure, Tertiary, Proteins, Sequence Analysis, Protein, software, Terminology as Topic, User-Computer Interface}, issn = {1362-4962}, doi = {10.1093/nar/gkr948}, author = {Hunter, Sarah and Jones, Philip and Mitchell, Alex and Apweiler, Rolf and Attwood, Teresa K and Bateman, Alex and Bernard, Thomas and Binns, David and Bork, Peer and Burge, Sarah and de Castro, Edouard and Coggill, Penny and Corbett, Matthew and Das, Ujjwal and Daugherty, Louise and Duquenne, Lauranne and Finn, Robert D and Fraser, Matthew and Gough, Julian and Haft, Daniel and Hulo, Nicolas and Kahn, Daniel and Kelly, Elizabeth and Letunic, Ivica and Lonsdale, David and Lopez, Rodrigo and Madera, Martin and Maslen, John and McAnulla, Craig and McDowall, Jennifer and McMenamin, Conor and Mi, Huaiyu and Mutowo-Muellenet, Prudence and Mulder, Nicola and Natale, Darren and Orengo, Christine and Pesseat, Sebastien and Punta, Marco and Quinn, Antony F and Rivoire, Catherine and Sangrador-Vegas, Amaia and Jeremy D Selengut and Sigrist, Christian J A and Scheremetjew, Maxim and Tate, John and Thimmajanarthanan, Manjulapramila and Thomas, Paul D and Wu, Cathy H and Yeats, Corin and Yong, Siew-Yit} } @article {19717, title = {Whole genome analysis of Leptospira licerasiae provides insight into leptospiral evolution and pathogenicity.}, journal = {PLoS Negl Trop Dis}, volume = {6}, year = {2012}, month = {2012}, pages = {e1853}, abstract = {

The whole genome analysis of two strains of the first intermediately pathogenic leptospiral species to be sequenced (Leptospira licerasiae strains VAR010 and MMD0835) provides insight into their pathogenic potential and deepens our understanding of leptospiral evolution. Comparative analysis of eight leptospiral genomes shows the existence of a core leptospiral genome comprising 1547 genes and 452 conserved genes restricted to infectious species (including L. licerasiae) that are likely to be pathogenicity-related. Comparisons of the functional content of the genomes suggests that L. licerasiae retains several proteins related to nitrogen, amino acid and carbohydrate metabolism which might help to explain why these Leptospira grow well in artificial media compared with pathogenic species. L. licerasiae strains VAR010(T) and MMD0835 possess two prophage elements. While one element is circular and shares homology with LE1 of L. biflexa, the second is cryptic and homologous to a previously identified but unnamed region in L. interrogans serovars Copenhageni and Lai. We also report a unique O-antigen locus in L. licerasiae comprised of a 6-gene cluster that is unexpectedly short compared with L. interrogans in which analogous regions may include >90 such genes. Sequence homology searches suggest that these genes were acquired by lateral gene transfer (LGT). Furthermore, seven putative genomic islands ranging in size from 5 to 36 kb are present also suggestive of antecedent LGT. How Leptospira become naturally competent remains to be determined, but considering the phylogenetic origins of the genes comprising the O-antigen cluster and other putative laterally transferred genes, L. licerasiae must be able to exchange genetic material with non-invasive environmental bacteria. The data presented here demonstrate that L. licerasiae is genetically more closely related to pathogenic than to saprophytic Leptospira and provide insight into the genomic bases for its infectiousness and its unique antigenic characteristics.

}, keywords = {DNA, Bacterial, Evolution, Molecular, Gene Transfer, Horizontal, Genome, Bacterial, Genomic islands, HUMANS, Leptospira, Molecular Sequence Data, Multigene Family, Prophages, Sequence Analysis, DNA, Virulence factors}, issn = {1935-2735}, doi = {10.1371/journal.pntd.0001853}, author = {Ricaldi, Jessica N and Fouts, Derrick E and Jeremy D Selengut and Harkins, Derek M and Patra, Kailash P and Moreno, Angelo and Lehmann, Jason S and Purushe, Janaki and Sanka, Ravi and Torres, Michael and Webster, Nicholas J and Vinetz, Joseph M and Matthias, Michael A} } @article {19722, title = {ProPhylo: partial phylogenetic profiling to guide protein family construction and assignment of biological process.}, journal = {BMC Bioinformatics}, volume = {12}, year = {2011}, month = {2011}, pages = {434}, abstract = {

BACKGROUND: Phylogenetic profiling is a technique of scoring co-occurrence between a protein family and some other trait, usually another protein family, across a set of taxonomic groups. In spite of several refinements in recent years, the technique still invites significant improvement. To be its most effective, a phylogenetic profiling algorithm must be able to examine co-occurrences among protein families whose boundaries are uncertain within large homologous protein superfamilies.

RESULTS: Partial Phylogenetic Profiling (PPP) is an iterative algorithm that scores a given taxonomic profile against the taxonomic distribution of families for all proteins in a genome. The method works through optimizing the boundary of each protein family, rather than by relying on prebuilt protein families or fixed sequence similarity thresholds. Double Partial Phylogenetic Profiling (DPPP) is a related procedure that begins with a single sequence and searches for optimal granularities for its surrounding protein family in order to generate the best query profiles for PPP. We present ProPhylo, a high-performance software package for phylogenetic profiling studies through creating individually optimized protein family boundaries. ProPhylo provides precomputed databases for immediate use and tools for manipulating the taxonomic profiles used as queries.

CONCLUSION: ProPhylo results show universal markers of methanogenesis, a new DNA phosphorothioation-dependent restriction enzyme, and efficacy in guiding protein family construction. The software and the associated databases are freely available under the open source Perl Artistic License from ftp://ftp.jcvi.org/pub/data/ppp/.

}, keywords = {algorithms, Archaea, Archaeal Proteins, DNA, Methane, Phylogeny, software}, issn = {1471-2105}, doi = {10.1186/1471-2105-12-434}, author = {Basu, Malay K and Jeremy D Selengut and Haft, Daniel H} } @article {19725, title = {Sites Inferred by Metabolic Background Assertion Labeling (SIMBAL): adapting the Partial Phylogenetic Profiling algorithm to scan sequences for signatures that predict protein function.}, journal = {BMC Bioinformatics}, volume = {11}, year = {2010}, month = {2010}, pages = {52}, abstract = {

BACKGROUND: Comparative genomics methods such as phylogenetic profiling can mine powerful inferences from inherently noisy biological data sets. We introduce Sites Inferred by Metabolic Background Assertion Labeling (SIMBAL), a method that applies the Partial Phylogenetic Profiling (PPP) approach locally within a protein sequence to discover short sequence signatures associated with functional sites. The approach is based on the basic scoring mechanism employed by PPP, namely the use of binomial distribution statistics to optimize sequence similarity cutoffs during searches of partitioned training sets.

RESULTS: Here we illustrate and validate the ability of the SIMBAL method to find functionally relevant short sequence signatures by application to two well-characterized protein families. In the first example, we partitioned a family of ABC permeases using a metabolic background property (urea utilization). Thus, the TRUE set for this family comprised members whose genome of origin encoded a urea utilization system. By moving a sliding window across the sequence of a permease, and searching each subsequence in turn against the full set of partitioned proteins, the method found which local sequence signatures best correlated with the urea utilization trait. Mapping of SIMBAL "hot spots" onto crystal structures of homologous permeases reveals that the significant sites are gating determinants on the cytosolic face rather than, say, docking sites for the substrate-binding protein on the extracellular face. In the second example, we partitioned a protein methyltransferase family using gene proximity as a criterion. In this case, the TRUE set comprised those methyltransferases encoded near the gene for the substrate RF-1. SIMBAL identifies sequence regions that map onto the substrate-binding interface while ignoring regions involved in the methyltransferase reaction mechanism in general. Neither method for training set construction requires any prior experimental characterization.

CONCLUSIONS: SIMBAL shows that, in functionally divergent protein families, selected short sequences often significantly outperform their full-length parent sequence for making functional predictions by sequence similarity, suggesting avenues for improved functional classifiers. When combined with structural data, SIMBAL affords the ability to localize and model functional sites.

}, keywords = {algorithms, Amino Acid Sequence, Gene Expression Profiling, Molecular Sequence Data, Phylogeny, Proteins, Sequence Analysis, Protein, Structure-Activity Relationship}, issn = {1471-2105}, doi = {10.1186/1471-2105-11-52}, author = {Jeremy D Selengut and Rusch, Douglas B and Haft, Daniel H} } @article {19724, title = {Unexpected abundance of coenzyme F(420)-dependent enzymes in Mycobacterium tuberculosis and other actinobacteria.}, journal = {J Bacteriol}, volume = {192}, year = {2010}, month = {2010 Nov}, pages = {5788-98}, abstract = {

Regimens targeting Mycobacterium tuberculosis, the causative agent of tuberculosis (TB), require long courses of treatment and a combination of three or more drugs. An increase in drug-resistant strains of M. tuberculosis demonstrates the need for additional TB-specific drugs. A notable feature of M. tuberculosis is coenzyme F(420), which is distributed sporadically and sparsely among prokaryotes. This distribution allows for comparative genomics-based investigations. Phylogenetic profiling (comparison of differential gene content) based on F(420) biosynthesis nominated many actinobacterial proteins as candidate F(420)-dependent enzymes. Three such families dominated the results: the luciferase-like monooxygenase (LLM), pyridoxamine 5{\textquoteright}-phosphate oxidase (PPOX), and deazaflavin-dependent nitroreductase (DDN) families. The DDN family was determined to be limited to F(420)-producing species. The LLM and PPOX families were observed in F(420)-producing species as well as species lacking F(420) but were particularly numerous in many actinobacterial species, including M. tuberculosis. Partitioning the LLM and PPOX families based on an organism{\textquoteright}s ability to make F(420) allowed the application of the SIMBAL (sites inferred by metabolic background assertion labeling) profiling method to identify F(420)-correlated subsequences. These regions were found to correspond to flavonoid cofactor binding sites. Significantly, these results showed that M. tuberculosis carries at least 28 separate F(420)-dependent enzymes, most of unknown function, and a paucity of flavin mononucleotide (FMN)-dependent proteins in these families. While prevalent in mycobacteria, markers of F(420) biosynthesis appeared to be absent from the normal human gut flora. These findings suggest that M. tuberculosis relies heavily on coenzyme F(420) for its redox reactions. This dependence and the cofactor{\textquoteright}s rarity may make F(420)-related proteins promising drug targets.

}, keywords = {Actinobacteria, Amino Acid Sequence, Binding Sites, Coenzymes, Flavonoids, Gene Expression Profiling, Gene Expression Regulation, Bacterial, Genome, Bacterial, molecular biology, Molecular Sequence Data, Molecular Structure, Mycobacterium tuberculosis, Phylogeny, Protein Conformation, Riboflavin}, issn = {1098-5530}, doi = {10.1128/JB.00425-10}, author = {Jeremy D Selengut and Haft, Daniel H} } @article {19726, title = {Three genomes from the phylum Acidobacteria provide insight into the lifestyles of these microorganisms in soils.}, journal = {Appl Environ Microbiol}, volume = {75}, year = {2009}, month = {2009 Apr}, pages = {2046-56}, abstract = {

The complete genomes of three strains from the phylum Acidobacteria were compared. Phylogenetic analysis placed them as a unique phylum. They share genomic traits with members of the Proteobacteria, the Cyanobacteria, and the Fungi. The three strains appear to be versatile heterotrophs. Genomic and culture traits indicate the use of carbon sources that span simple sugars to more complex substrates such as hemicellulose, cellulose, and chitin. The genomes encode low-specificity major facilitator superfamily transporters and high-affinity ABC transporters for sugars, suggesting that they are best suited to low-nutrient conditions. They appear capable of nitrate and nitrite reduction but not N(2) fixation or denitrification. The genomes contained numerous genes that encode siderophore receptors, but no evidence of siderophore production was found, suggesting that they may obtain iron via interaction with other microorganisms. The presence of cellulose synthesis genes and a large class of novel high-molecular-weight excreted proteins suggests potential traits for desiccation resistance, biofilm formation, and/or contribution to soil structure. Polyketide synthase and macrolide glycosylation genes suggest the production of novel antimicrobial compounds. Genes that encode a variety of novel proteins were also identified. The abundance of acidobacteria in soils worldwide and the breadth of potential carbon use by the sequenced strains suggest significant and previously unrecognized contributions to the terrestrial carbon cycle. Combining our genomic evidence with available culture traits, we postulate that cells of these isolates are long-lived, divide slowly, exhibit slow metabolic rates under low-nutrient conditions, and are well equipped to tolerate fluctuations in soil hydration.

}, keywords = {Anti-Bacterial Agents, bacteria, Biological Transport, Carbohydrate Metabolism, Cyanobacteria, DNA, Bacterial, Fungi, Genome, Bacterial, Macrolides, Molecular Sequence Data, Nitrogen, Phylogeny, Proteobacteria, Sequence Analysis, DNA, sequence homology, Soil Microbiology}, issn = {1098-5336}, doi = {10.1128/AEM.02294-08}, author = {Ward, Naomi L and Challacombe, Jean F and Janssen, Peter H and Henrissat, Bernard and Coutinho, Pedro M and Wu, Martin and Xie, Gary and Haft, Daniel H and Sait, Michelle and Badger, Jonathan and Barabote, Ravi D and Bradley, Brent and Brettin, Thomas S and Brinkac, Lauren M and Bruce, David and Creasy, Todd and Daugherty, Sean C and Davidsen, Tanja M and DeBoy, Robert T and Detter, J Chris and Dodson, Robert J and Durkin, A Scott and Ganapathy, Anuradha and Gwinn-Giglio, Michelle and Han, Cliff S and Khouri, Hoda and Kiss, Hajnalka and Kothari, Sagar P and Madupu, Ramana and Nelson, Karen E and Nelson, William C and Paulsen, Ian and Penn, Kevin and Ren, Qinghu and Rosovitz, M J and Jeremy D Selengut and Shrivastava, Susmita and Sullivan, Steven A and Tapia, Roxanne and Thompson, L Sue and Watkins, Kisha L and Yang, Qi and Yu, Chunhui and Zafar, Nikhat and Zhou, Liwei and Kuske, Cheryl R} } @article {16270, title = {Genome sequence and comparative analysis of the model rodent malaria parasite Plasmodium yoelii yoelii}, journal = {Nature}, volume = {419}, year = {2002}, month = {2002/10/03/}, pages = {512 - 519}, abstract = {Species of malaria parasite that infect rodents have long been used as models for malaria disease research. Here we report the whole-genome shotgun sequence of one species, Plasmodium yoelii yoelii, and comparative studies with the genome of the human malaria parasite Plasmodium falciparum clone 3D7. A synteny map of 2,212 P. y. yoelii contiguous DNA sequences (contigs) aligned to 14 P. falciparum chromosomes reveals marked conservation of gene synteny within the body of each chromosome. Of about 5,300 P. falciparum genes, more than 3,300 P. y. yoelii orthologues of predominantly metabolic function were identified. Over 800 copies of a variant antigen gene located in subtelomeric regions were found. This is the first genome sequence of a model eukaryotic parasite, and it provides insight into the use of such systems in the modelling of Plasmodium biology and disease.}, isbn = {0028-0836}, doi = {10.1038/nature01099}, url = {http://www.nature.com/nature/journal/v419/n6906/full/nature01099.html}, author = {Carlton,Jane M. and Angiuoli,Samuel V and Suh,Bernard B. and Kooij,Taco W. and Pertea,Mihaela and Silva,Joana C. and Ermolaeva,Maria D. and Allen,Jonathan E and Jeremy D Selengut and Koo,Hean L. and Peterson,Jeremy D. and Pop, Mihai and Kosack,Daniel S. and Shumway,Martin F. and Bidwell,Shelby L. and Shallom,Shamira J. and Aken,Susan E. van and Riedmuller,Steven B. and Feldblyum,Tamara V. and Cho,Jennifer K. and Quackenbush,John and Sedegah,Martha and Shoaibi,Azadeh and Cummings,Leda M. and Florens,Laurence and Yates,John R. and Raine,J. Dale and Sinden,Robert E. and Harris,Michael A. and Cunningham,Deirdre A. and Preiser,Peter R. and Bergman,Lawrence W. and Vaidya,Akhil B. and Lin,Leo H. van and Janse,Chris J. and Waters,Andrew P. and Smith,Hamilton O. and White,Owen R. and Salzberg,Steven L. and Venter,J. Craig and Fraser,Claire M. and Hoffman,Stephen L. and Gardner,Malcolm J. and Carucci,Daniel J.} }