The sequence comparison index: A novel method for comparing proteins and proteomes

Historically morphological features were used as the primary means to classify organisms. However, the age of molecular genetics has allowed us to approach this field from the perspective of the organism's genetic code. Early work used highly conserved sequences, such as ribosomal RNA. The increasing number of complete genomes in the public data repositories provides the opportunity to look not only at a single gene, but at organisms' entire parts list. ^ Here the Sequence Comparison Index (SCI) and the Organism Comparison Index (OCI), algorithms and methods to compare proteins and proteomes, are presented. The complete proteomes of 104 sequenced organisms were compared. Over 280 million full Smith-Waterman alignments were performed on sequence pairs which had a reasonable expectation of being related. From these alignments a whole proteome phylogenetic tree was constructed. This method was also used to compare the small subunit (SSU) rRNA from each organism and a tree constructed from these results. The SSU rRNA tree by the SCI/OCI method looks very much like accepted SSU rRNA trees from sources such as the Ribosomal Database Project, thus validating the method. The SCI/OCI proteome tree showed a number of small but significant differences when compared to the SSU rRNA tree and proteome trees constructed by other methods. Horizontal gene transfer does not appear to affect the SCI/OCI trees until the transferred genes make up a large portion of the proteome. ^ As part of this work, the Database of Related Local Alignments (DaRLA) was created and contains over 81 million rows of sequence alignment information. DaRLA, while primarily used to build the whole proteome trees, can also be applied shared gene content analysis, gene order analysis, and creating individual protein trees. ^ Finally, the standard BLAST method for analyzing shared gene content was compared to the SCI method using 4 spirochetes. The SCI system performed flawlessly, finding all proteins from one organism against itself and finding all the ribosomal proteins between organisms. The BLAST system missed some proteins from its respective organism and failed to detect small ribosomal proteins between organisms. ^

Clinical and microbiological aspects of linezolid resistance mediated by the cfr gene encoding a 23S rRNA methyltransferase.

The cfr (chloramphenicol-florfenicol resistance) gene encodes a 23S rRNA methyltransferase that confers resistance to linezolid. Detection of linezolid resistance was evaluated in the first cfr-carrying human hospital isolate of linezolid and methicillin-resistant Staphylococcus aureus (designated MRSA CM-05) by dilution and diffusion methods (including Etest). The presence of cfr was investigated in isolates of staphylococci colonizing the patient's household contacts and clinical isolates recovered from patients in the same unit where MRSA CM-05 was isolated. Additionally, 68 chloramphenicol-resistant Colombian MRSA isolates recovered from hospitals between 2001 and 2004 were screened for the presence of the cfr gene. In addition to erm(B), the erm(A) gene was also detected in CM-05. The isolate belonged to sequence type 5 and carried staphylococcal chromosomal cassette mec type I. We were unable to detect the cfr gene in any of the human staphylococci screened (either clinical or colonizing isolates). Agar and broth dilution methods detected linezolid resistance in CM-05. However, the Etest and disk diffusion methods failed to detect resistance after 24 h of incubation. Oxazolidinone resistance mediated by the cfr gene is rare, and acquisition by a human isolate appears to be a recent event in Colombia. The detection of cfr-mediated linezolid resistance might be compromised by the use of the disk diffusion or Etest method.

Characterization of fecal contamination targeting 16S rRNA bacteroides molecular markers in the Santa Cruz River, Arizona

Understanding the origins, transport and fate of contamination is essential to effective management of water resources and public health. Individuals and organizations with management responsibilities need to understand the risks to ecosystems and to humans from contact with contamination. Managers also need to understand how key contaminants vary over time and space in order to design and prioritize mitigation strategies. Tumacacori National Historic Park (NHP) is responsible for management of its water resources for the benefit of the park and for the health of its visitors. The existence of microbial contaminants in the park poses risks that must be considered in park planning and operations. The water quality laboratory at the Maricopa Agricultural Center (in collaboration with stakeholder groups and individuals located in the ADEQ-targeted watersheds) identified biological changes in surface water quality in impaired reaches rivers to determine the sources of Escherichia coli (E. coli); bacteria utilizing innovative water quality microbial/bacterial source tracking methods. The end goal was to support targeted watershed groups and ADEQ towards E. coli reductions. In the field monitoring was conducted by the selected targeted watershed groups in conjunction with The University of Arizona Maricopa Agricultural Center Water Quality Laboratory. This consisted of collecting samples for Bacteroides testing from multiple locations on select impaired reaches, to determine contamination resulting from cattle, human recreation, and other contributions. Such testing was performed in conjunction with high flow and base flow conditions in order to accurately portray water quality conditions and variations. Microbial monitoring was conducted by The University of Arizona Water Quality Laboratory at the Maricopa Agricultural Center using genetic typing to differentiate among two categories of Bacteroides: human and all (total). Testing used microbial detection methodologies and molecular source tracking techniques.^