Marvin E. Frazier

Characterization and expression of the cbbE′ gene of Coxiella burnetii.

A gene which is unique to the QpRS plasmid from chronic isolates of Coxiella burnetii was cloned, sequenced, and expressed in Escherichia coli. This gene, termed cbbE, codes for a putative surface protein of approximately 55 kDa, termed the E protein. The cbbE gene is 1485 bp in length, and is preceded by predicted promoter regulatory sequences of TTTAAT (-35), TATAAT (-10), and a Shine-Dalgarno sequence of GGAGAGA, all of which closely resemble those of E. coli and other rickettsiae. The open reading frame (ORF) of cbbE ends with a UAA codon followed by a second in-frame UAG stop codon and a region of dyad symmetry which may act as a rho-factor-independent terminator. The ORF of cbbE is capable of coding for a polypeptide of 495 amino acids with a predicted molecular mass of 55893 Da. The E protein has a predicted pI of approximately 8.7, and contains a distinct hydrophobic region of 12 amino acid residues. In vitro transcription/translation and E. coli expression of recombinant plasmids containing cbbE produce a protein of approximately 55 kDa. The in vivo expression of cbbE yields a novel protein that can be detected on immunoblots developed with rabbit antiserum generated against purified outer membrane from C. burnetii. DNA hybridization analysis shows that cbbE is unique to the QpRS plasmid found in chronic isolates of C. burnetii, and is absent in chromosomal DNA and plasmids (QpH1, QpDG) from other isolates of C. burnetii. A search of various DNA and amino acid sequence data bases revealed no homologies to cbbE.

Sequence and linkage analysis of the Coxiella burnetii citrate synthase-encoding gene

The nucleotide (nt) sequence of the Coxiella burnetii citrate synthase-encoding gene (gltA), previously cloned in Escherichia coli, was determined. The nt sequence analysis revealed an open reading frame (ORF) of 1290 bp capable of coding for a protein of 430 amino acids (aa) with a deduced Mr of 48,633. Preceding an ATG start codon, a possible transcription start point (tsp) with homology to the E. coli promoter consensus was detected. A poly-purine-rich region occurred immediately upstream from the gltA reading frame and potentially serves as a ribosome-binding site. Additionally, a G + C-rich region of dyad symmetry 3 to the translational stop codon was found that could possibly function as a Rho-independent transcriptional termination signal. A large, nearly perfect, inverted repeat was identified upstream from the gltA tsp and was shown by Southern analysis to be present in multiple copies in the C. burnetii genome. The deduced aa sequence of C. burnetii GltA was optimally aligned with enzymes from various prokaryotic sources and one eukaryotic source (pig heart). Using perfect aa identity, the C. burnetii enzyme demonstrated the greatest homology with GltA from Acinetobacter anitratum (65%). Although only 26% aa identity was seen with the pig heart enzyme, many of the residues identified in ligand binding appear to be conserved. Sequencing studies of a region centered approx. 5.6 kb upstream from gltA revealed an ORF read with opposite polarity that encodes a peptide highly homologous to the C terminus of the flavoprotein subunit of E. coli succinate dehydrogenase. This report represents the first nt sequence analysis of a gene of known function from the obligate intracellular parasite, C. burnetii.

Stability of plasmid sequences in an acute Q-fever strain of Coxiella burnetii.

The rickettsial pathogen Coxiella burnetii undergoes a variation in which virulent isolates (phase 1) become avirulent (phase 2) after repeated passage in a non-immunologically competent host. Biochemically, this variation is associated with a lipopolysaccharide modification and possibly other factors. Genetically, the regions of DNA responsible for phase variation have not been identified. We have sought to determine whether the plasmid identified in acute disease isolates, QpH1, which represents approximately 5% of the coding capacity of this organism is involved in phase variation. Plasmids from phase 1 and phase 2 variants (designated QpH1 and QpH2, respectively) were compared by restriction endonuclease digestion and Southern blot hybridization to determine whether sequence changes in the phase 2 plasmid might account for changes in the virulence of phase 2 organisms compared with that of phase 1 cells. Using over 20 different restriction enzymes, no changes in DNA restriction fragment patterns were detected regardless of whether the phase change occurred during egg or tissue culture passage. The plasmid-specific mRNAs produced from metabolically active, purified cells were identical for each phase type. Using QpH1 or QpH2 DNA as a template, the mRNA produced by an E. coli extract was also identical. Finally, the proteins encoded by either plasmid in an in vitro transcription/translation reaction were identical. These data indicate that within the limits of our analysis, the plasmid DNA from C. burnetii phase variants is structurally and functionally the same and is therefore unlikely to be involved in phase variation.

Stepping up the pace of discovery: the genomes to life program

Genomes to Life (GTL), the U.S. Department of Energy Office of Sciences systems biology program, focuses on environmental microbiology. Over the next 10 to 20 years, GTLs key goal is to understand the life processes of thousands of microbes and microbial systems in their native environments. This focus demands that we address huge gaps in knowledge, technology, computing, data capture and analysis, and systems-level integration. Distinguishing features include: (1) strategies for unprecedented, comprehensive, and high-throughput data collection; (2) advanced computing, mathematics, algorithms, and data-management technologies; (3) a focus on potential microbial capabilities to help solve energy and environmental challenges; and (4) new research and management models that link production-scale systems biology facilities in an accessible environment. This unprecedented opportunity to provide the scientific foundation for solving urgent problems in energy, global climate change, and environmental cleanup demands that we take bold steps to achieve a much faster, more efficient pace of biological discovery.

EXPLORING THE OCEAN'S MICROBES: SEQUENCING THE SEVEN SEAS

Marvin E. Frazier,Douglas B. Rusch, Aaron L. Halpern, Karla B. Heidelberg, Granger Sutton, Shannon Williamson, Shibu Yooseph, Dongying Wu, Jonathan A. Eisen, Jeff Hoffman, Charles H. Howard, Cyrus Foote, Brooke A. Dill, Karin Remington, Karen Beeson, Bao Tran, Hamilton Smith, Holly Baden-Tillson, Clare Stewart, Joyce Thorpe, Jason Freemen, Cindy Pfannkoch, Joseph E. Venter, John Heidelberg, Terry Utterback, Yu-Hui Rogers, Shaojie Zhang, Vineet Bafna, Luisa Falcon, Valeria Souza,German Bonilla, Luis E. Eguiarte , David M. Karl, Ken Nealson, Shubha Sathyendranath, Trevor Platt, Eldredge Bermingham, Victor Gallardo, Giselle Tamayo, Robert Friedman, Robert Strausberg, J. Craig Venter 1 J. Craig Venter Institute, Rockville, Maryland, United States Of America 2 The Institute For Genomic Research, Rockville, Maryland, United States Of America 3 Department of Computer Science, University of California San Diego 4 Instituto de Ecologia Dept. Ecologia Evolutiva, National Autonomous University of Mexico Mexico City, 04510 Distrito Federal, Mexico 5 University of Hawaii, Honolulu, United States of America 6 Dept. of Earth Sciences, University of Southern California, Los Angeles, California, United States of America 7 Dalhousie University, Halifax, Nova Scotia, Canada 8 Smithsonian Tropical Research Institute, Balboa, Ancon, Republic of Panama 9 University of Concepcion, Concepcion, Chile 10 University of Costa Rica, San Pedro, San Jose, Republic of Costa Rica

Computing for the DOE genomes to life program

A key goal of the DOE office of sciences systems biology program, genomes to life (GTL), is to achieve, over the next 10 to 20 years, a basic understanding of thousands of environmental microbes and microbial systems in their native environments. This goal demands that we develop new models for scientific discovery that integrate methods and systems which tightly couple advanced computing, mathematics, algorithms, and data-management technologies with large-scale experimental data generation.