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Articles by James M. Tiedje
Total Records ( 3 ) for James M. Tiedje
  Sarah M. Miller , Dieter M. Tourlousse , Robert D. Stedtfeld , Samuel W. Baushke , Amanda B. Herzog , Lukas M. Wick , Jean Marie Rouillard , Erdogan Gulari , James M. Tiedje and Syed A. Hashsham
  Pathogen detection tools with high reliability are needed for various applications, including food and water safety and clinical diagnostics. In this study, we designed and validated an in situ-synthesized biochip for detection of 12 microbial pathogens, including a suite of pathogens relevant to water safety. To enhance the reliability of presence/absence calls, probes were designed for multiple virulence and marker genes (VMGs) of each pathogen, and each VMG was targeted by an average of 17 probes. Hybridization of the biochip with amplicon mixtures demonstrated that 95% of the initially designed probes behaved as predicted in terms of positive/negative signals. The probes were further validated using DNA obtained from three different types of water samples and spiked with pathogen genomic DNA at decreasing relative abundance. Excellent specificity for making presence/absence calls was observed by using a cutoff of 0.5 for the positive fraction (i.e., the fraction of probes yielding a positive signal for a given VMG). A split multiplex PCR design for simultaneous amplification of the VMGs resulted in a detection limit of between 0.1 and 0.01% relative abundance, depending on the type of pathogen and the VMG. Thermodynamic analysis of the hybridization patterns obtained with DNA from the different water samples demonstrated that probes with a hybridization Gibbs free energy of approximately –19.3 kcal/mol provided the best trade-off between sensitivity and specificity. The developed biochip may be used to detect the described bacterial pathogens in water samples when parallel and specific detection is required.
  Erick Cardenas , Wei-Min Wu , Mary Beth Leigh , Jack Carley , Sue Carroll , Terry Gentry , Jian Luo , David Watson , Baohua Gu , Matthew Ginder-Vogel , Peter K. Kitanidis , Philip M. Jardine , Jizhong Zhou , Craig S. Criddle , Terence L. Marsh and James M. Tiedje
  Microbial enumeration, 16S rRNA gene clone libraries, and chemical analysis were used to evaluate the in situ biological reduction and immobilization of uranium(VI) in a long-term experiment (more than 2 years) conducted at a highly uranium-contaminated site (up to 60 mg/liter and 800 mg/kg solids) of the U.S. Department of Energy in Oak Ridge, TN. Bioreduction was achieved by conditioning groundwater above ground and then stimulating growth of denitrifying, Fe(III)-reducing, and sulfate-reducing bacteria in situ through weekly injection of ethanol into the subsurface. After nearly 2 years of intermittent injection of ethanol, aqueous U levels fell below the U.S. Environmental Protection Agency maximum contaminant level for drinking water and groundwater (<30 µg/liter or 0.126 µM). Sediment microbial communities from the treatment zone were compared with those from a control well without biostimulation. Most-probable-number estimations indicated that microorganisms implicated in bioremediation accumulated in the sediments of the treatment zone but were either absent or in very low numbers in an untreated control area. Organisms belonging to genera known to include U(VI) reducers were detected, including Desulfovibrio, Geobacter, Anaeromyxobacter, Desulfosporosinus, and Acidovorax spp. The predominant sulfate-reducing bacterial species were Desulfovibrio spp., while the iron reducers were represented by Ferribacterium spp. and Geothrix spp. Diversity-based clustering revealed differences between treated and untreated zones and also within samples of the treated area. Spatial differences in community structure within the treatment zone were likely related to the hydraulic pathway and to electron donor metabolism during biostimulation.
  Robert D. Stedtfeld , Samuel W. Baushke , Dieter M. Tourlousse , Sarah M. Miller , Tiffany M. Stedtfeld , Erdogan Gulari , James M. Tiedje and Syed A. Hashsham
  Development of quantitative PCR (QPCR) assays typically requires extensive screening within and across a given species to ensure specific detection and lucid identification among various pathogenic and nonpathogenic strains and to generate standard curves. To minimize screening requirements, multiple virulence and marker genes (VMGs) were targeted simultaneously to enhance reliability, and a predictive threshold cycle (CT) equation was developed to calculate the number of starting copies based on an experimental CT. The empirical equation was developed with Sybr green detection in nanoliter-volume QPCR chambers (OpenArray) and tested with 220 previously unvalidated primer pairs targeting 200 VMGs from 30 pathogens. A high correlation (R2 = 0.816) was observed between the predicted and experimental CTs based on the organism`s genome size, guanine and cytosine (GC) content, amplicon length, and stability of the primer`s 3` end. The performance of the predictive CT equation was tested using 36 validation samples consisting of pathogenic organisms spiked into genomic DNA extracted from three environmental waters. In addition, the primer success rate was dependent on the GC content of the target organisms and primer sequences. Targeting multiple assays per organism and using the predictive CT equation are expected to reduce the extent of the validation necessary when developing QPCR arrays for a large number of pathogens or other targets.
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