Genomic paradigms for food-borne enteric pathogen analysis at the USFDA: case studies highlighting method utility, integration and resolution.
Food Addit Contam Part A Chem Anal Control Expo Risk Assess. 2012 Dec 3;
Authors: Elkins CA, Kotewicz ML, Jackson SA, Lacher DW, Abu-Ali GS, Patel IR
Modern risk control and food safety practices involving food-borne bacterial pathogens are benefiting from new genomic technologies for rapid, yet highly specific, strain characterisations. Within the United States Food and Drug Administration (USFDA) Center for Food Safety and Applied Nutrition (CFSAN), optical genome mapping and DNA microarray genotyping have been used for several years to quickly assess genomic architecture and gene content, respectively, for outbreak strain subtyping and to enhance retrospective trace-back analyses. The application and relative utility of each method varies with outbreak scenario and the suspect pathogen, with comparative analytical power enhanced by database scale and depth. Integration of these two technologies allows high-resolution scrutiny of the genomic landscapes of enteric food-borne pathogens with notable examples including Shiga toxin-producing Escherichia coli (STEC) and Salmonella enterica serovars from a variety of food commodities. Moreover, the recent application of whole genome sequencing technologies to food-borne pathogen outbreaks and surveillance has enhanced resolution to the single nucleotide scale. This new wealth of sequence data will support more refined next-generation custom microarray designs, targeted re-sequencing and "genomic signature recognition" approaches involving a combination of genes and single nucleotide polymorphism detection to distil strain-specific fingerprinting to a minimised scale. This paper examines the utility of microarrays and optical mapping in analysing outbreaks, reviews best practices and the limits of these technologies for pathogen differentiation, and it considers future integration with whole genome sequencing efforts.
PMID: 23199033 [PubMed - as supplied by publisher]
The T393C polymorphism of GNAS1 is a predictor for relapse and survival in resectable non-small cell lung cancer.
Lung Cancer. 2012 Nov 29;
Authors: Uzunoglu FG, Heumann A, Musici S, Kutup A, Koenig A, Roch N, Thomssen A, Dohrmann T, Tsui TY, Mann O, Izbicki JR, Vashist YK
INTRODUCTION: The GNAS1 T393C single nucleotide polymorphism (T393C-SNP) correlates with Gαs mRNA stability and protein expression and augmented apoptosis. Genetic germ line variations as stable and reproducible markers potentially serve as prognostic marker in oncology. The aim of this study was to evaluate the potential prognostic value of T393C-SNP in complete resected non-small cell lung cancer (NSCLC). PATIENTS AND METHODS: In total 163 Caucasian patients, who had been surgically treated for NSCLC between 1998 and 2010, were included in this study. Genotyping of peripheral blood cells was performed by polymerase chain reaction and digestion using the restriction enzyme FokI. The T393C-SNP was correlated with clinic-pathological parameters and survival. Chi-square test, Kaplan-Meier estimator and cox regression hazard model were used to assess the prognostic value of the T393C-SNP. RESULTS: C-allele carriers had a higher recurrence rate (p=0.018) and a shorter disease-free survival compared to homozygous T-allele carriers (12.26 months vs. 44.65 months, p=0.009). The overall survival in homozygous C allele carriers was shorter (19.10 months vs. 53.95 months, p=0.019). Multivariate Cox regression identified the CC genotype as a negative independent prognostic factor for recurrence (hazard ratio 2.36, p=0.007) and survival (hazard ratio 2.51, p=0.008). CONCLUSION: Determination of T393C-SNP preoperatively potentially allows allocation of NSCLC patients into different risk profiles and may influence the therapeutic strategy.
PMID: 23201296 [PubMed - as supplied by publisher]
A linkage and association analysis study in the multidrug resistance gene 1 (mdr1) in renal patients.
Int J Mol Epidemiol Genet. 2012;3(4):314-20
Authors: Bazrafshani MR, Poulton KV, Mahmoodi M
Several investigations demonstrated that the polymorphisms of multidrug resistance gene (MDR1) gene contribute to interindividual variability in bioavailability and tissue distribution of its substrates. Genotyping of closely spaced single-nucleotide polymorphism (SNP) markers frequently yields highly correlated data, owing to extensive linkage disequilibrium (LD) between markers. The product of multidrug resistance gene (P-gp) is an important molecule, which regulating the bioavailability of many drugs, including calcineurin inhibitors. It also reported that some MDR1 gene polymorphisms (such as 3435C>T) was associated with significantly reduced intestinal P-gp expression in T/T homozygotes. The aim of this study is to develop genotyping assays for polymorphisms of the MDR1 gene, which are believed to have functional properties and to assess the distribution of variant alleles in renal patients (UK Caucasoid). A total of ten polymorphisms in the MDR-1 gene were selected for analysis. Haplotype assays were performed by using EH programme in 172 individuals. The following possible haplotype was apparent (G-41, C-145, C-129, C+139, C+1236, G+2677, G+2956, C+3435, C+4030 and A+4036). This finding suggests the importance of haplotype assignment for the MDR1 gene.
PMID: 23205183 [PubMed - in process]
Development of a novel, fully-automated genotyping system: principle and applications.
Sensors (Basel). 2012;12(12):16614-27
Authors: Suzuki S, Komori M, Hirai M, Ureshino N, Kimura S
Genetic testing prior to treatment, pharmacogenetic analysis, is key to realizing personalized medicine which is a topic that has attracted much attention recently. Through the optimization of therapy selection and dosage, a reduction in side effects is expected. Genetic testing has been conducted as a type of pharmacogenetic analysis in recent years, but it faces challenges in terms of cost effectiveness and its complicated procedures. Here we report on the development of a novel platform for genetic testing, the i-densyTM, with the use of quenching probe system (QP-system) as principle of mutant detection. The i-densyTM automatically performs pre-treatment, PCR and detection to provide the test result from whole blood and extracted DNA within approximately 90 and 60 min, respectively. Integration of all steps into a single platform greatly reduces test time and complicated procedures. An even higher-precision genetic analysis has been achieved through the development of novel and highly-specific detection methods. The applications of items measured using the i-densyTM are diverse, from single nucleotide polymorphism (SNP), such as CYP2C19 and UGT1A1, to somatic mutations associated with cancer, such as EGFR, KRAS and JAK2. The i-densyTM is a useful tool for optimization of anticancer drug therapy and can contribute to personalized medicine.
PMID: 23208557 [PubMed - in process]