Biomedical subjects

Kate Montgomery

Publications and source records attributed to Kate Montgomery.

4 recordsLinked to original sources

PubMed2006

Genomic analysis reveals that Pseudomonas aeruginosa virulence is combinatorial.

BACKGROUND: Pseudomonas aeruginosa is a ubiquitous environmental bacterium and an important opportunistic human pathogen. Generally, the acquisition of genes in the form of pathogenicity islands distinguishes pathogenic isolates from nonpathogens. We therefore sequenced a highly virulent strain of P. aeruginosa, PA14, and compared it with a previously sequenced (and less pathogenic) strain, PAO1, to identify novel virulence genes. RESULTS: The PA14 and PAO1 genomes are remarkably similar, although PA14 has a slightly larger genome (6.5 megabses [Mb]) than does PAO1 (6.3 Mb). We identified 58 PA14 gene clusters that are absent in PAO1 to determine which of these genes, if any, contribute to its enhanced virulence in a Caenorhabditis elegans pathogenicity model. First, we tested 18 additional diverse strains in the C. elegans model and observed a wide range of pathogenic potential; however, genotyping these strains using a custom microarray showed that the presence of PA14 genes that are absent in PAO1 did not correlate with the virulence of these strains. Second, we utilized a full-genome nonredundant mutant library of PA14 to identify five genes (absent in PAO1) required for C. elegans killing. Surprisingly, although these five genes are present in many other P. aeruginosa strains, they do not correlate with virulence in C. elegans. CONCLUSION: Genes required for pathogenicity in one strain of P. aeruginosa are neither required for nor predictive of virulence in other strains. We therefore propose that virulence in this organism is both multifactorial and combinatorial, the result of a pool of pathogenicity-related genes that interact in various combinations in different genetic backgrounds.

Base Sequence↗

PubMed2006

Utilization of a whole genome SNP panel for efficient genetic mapping in the mouse.

Phenotype-driven genetics can be used to create mouse models of human disease and birth defects. However, the utility of these mutant models is limited without identification of the causal gene. To facilitate genetic mapping, we developed a fixed single nucleotide polymorphism (SNP) panel of 394 SNPs as an alternative to analyses using simple sequence length polymorphism (SSLP) marker mapping. With the SNP panel, chromosomal locations for 22 monogenic mutants were identified. The average number of affected progeny genotyped for mapped monogenic mutations is nine. Map locations for several mutants have been obtained with as few as four affected progeny. The average size of genetic intervals obtained for these mutants is 43 Mb, with a range of 17-83 Mb. Thus, our SNP panel allows for identification of moderate resolution map position with small numbers of mice in a high-throughput manner. Importantly, the panel is suitable for mapping crosses from many inbred and wild-derived inbred strain combinations. The chromosomal localizations obtained with the SNP panel allow one to quickly distinguish between potentially novel loci or remutations in known genes, and facilitates fine mapping and positional cloning. By using this approach, we identified DNA sequence changes in two ethylnitrosourea-induced mutants.

Animals↗

PubMed2005

Assessment of nutritional status in hemodialysis patients using patient-generated subjective global assessment.

OBJECTIVE: To evaluate the scored Patient-Generated Subjective Global Assessment (PG-SGA) as a nutrition assessment tool in hemodialysis patients. DESIGN: A cross-sectional observational study assessing the nutritional status of hemodialysis patients. SETTING: Private tertiary Australian hospital. SUBJECTS: Sixty patients, ages 63.9 +/- 16.2 years. INTERVENTION: Scored PG-SGA questionnaire, comparison of PG-SGA score > or =9 with subjective global assessment (SGA), albumin, corrected arm muscle area, and triceps skinfold. RESULTS: According to SGA, 80% of patients were well nourished and 20% of patients were malnourished. Patients classified as well nourished (SGA-A) attained a significantly lower median PG-SGA score compared with those rated as moderately malnourished or at risk of malnutrition (SGA-B). A PG-SGA score > or =9 had a sensitivity of 83% and a specificity of 92% at predicting SGA classification. There were significant correlations between the PG-SGA score and serum albumin, PG-SGA score, and percentage weight loss over the past 6 months. There was no association between PG-SGA score and body mass index or anthropometric measurements. CONCLUSION: The scored PG-SGA is an easy-to-use nutrition assessment tool that allows quick identification of malnutrition in hemodialysis patients.

Aged↗

PubMed2002

Microarray-based copy number and expression profiling in dedifferentiated and pleomorphic liposarcoma.

Sixteen dedifferentiated and pleomorphic liposarcomas were analyzed by comparative genomic hybridization (CGH) to genomic microarrays (matrix-CGH), cDNA-derived microarrays for expression profiling, and by quantitative PCR. Matrix-CGH revealed copy number gains of numerous oncogenes, i.e., CCND1, MDM2, GLI, CDK4, MYB, ESR1, and AIB1, several of which correlate with a high level of transcripts from the respective gene. In addition, a number of genes were found differentially expressed in dedifferentiated and pleomorphic liposarcomas. Application of dedicated clustering algorithms revealed that both tumor subtypes are clearly separated by the genomic profiles but only with a lesser power by the expression profiles. Using a support vector machine, a subset of five clones was identified as "class discriminators." Thus, for the distinction of these types of liposarcomas, genomic profiling appears to be more advantageous than RNA expression analysis.

Algorithms↗