3 resultados para detection methods

em DigitalCommons@University of Nebraska - Lincoln


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Strains of Lysobacter enzymogenes, a bacterial species with biocontrol activity, have been detected via 16S rDNA sequences in soil in different parts of the world. In most instances, however, their occurrence could not be confirmed by isolation, presumably because the species occurred in low numbers relative to faster-growing species of Bacillus or Pseudomonas. In this study, we developed DNA-based detection and enrichment culturing methods for Lysobacter spp. and L. enzymogenes specifically. In the DNA-based method, a region of 16S rDNA conserved among Lysobacter spp. (L4: GAG CCG ACG TCG GAT TAG CTA GTT), was used as the forward primer in PCR amplification. When L4 and universal bacterial primer 1525R were used to amplify DNA from various bacterial species, an 1100-bp product was found in Lysobacter spp. exclusively. The enrichment culturing method involved culturing soils for 3 days in a chitin-containing broth amended with antibiotics. Bacterial strains in the enrichment culture were isolated on yeast-cell agar and then identified by 16S rDNA sequence analysis. A strain of L. enzymogenes added to soils was detected at populations as low as 102 and 104 CFU/g soil by PCR amplification and enrichment culturing, respectively. In a survey of 58 soil samples, Lysobacter was detected in 41 samples by PCR and enrichment culture, out of which 6 yielded strains of Lysobacter spp. by enrichment culture. Among isolated strains, all were identified to be L. enzymogenes, with the exception of a strain of L. antibioticus. Although neither method alone is completely effective at detecting L. enzymogenes, they are complementary when used together and may provide new information on the spatial distribution of the species in soil.

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Surveillance and control activities related to bovine tuberculosis (TB) in free-ranging, Michigan white-tailed deer (Odocoileus virginianus) have been underway for over a decade, with significant progress. However, foci of higher TB prevalence on private lands and limited agency ability to eliminate them using broad control strategies have led to development and trial of new control strategies, such as live trapping, testing, and culling or release. Such strategies require a prompt, accurate live animal test, which has thus far been lacking. We report here the ability of seven candidate blood assays to determine the TB infection status of Michigan deer. Our aims were twofold: to characterize the accuracy of the tests using field-collected samples and to evaluate the feasibility of the tests for use in a test-and-cull strategy. Samples were collected from 760 deer obtained via five different surveys conducted between 2004 and 2007. Blood samples were subjected to one or more of the candidate blood assays and evaluated against the results of mycobacterial culture of the cranial lymph nodes. Sensitivities of the tests ranged from 46% to 68%, whereas specificities and negative predictive values were all .92%. Positive predictive values were highly variable. An exploratory analysis of associations among several host and sampling-related factors and the agreement between blood assay and culture results suggested these assays were minimally affected. This study demonstrated the capabilities and limitations of several available blood tests for Mycobacterium bovis on specimens obtained through a variety of field surveillance methods. Although these blood assays cannot replace mass culling, information on their performance may prove useful as wildlife disease managers develop innovative methods of detecting infected animals where mass culling is publicly unacceptable and cannot be used as a control strategy.

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Double-observer line transect methods are becoming increasingly widespread, especially for the estimation of marine mammal abundance from aerial and shipboard surveys when detection of animals on the line is uncertain. The resulting data supplement conventional distance sampling data with two-sample mark–recapture data. Like conventional mark–recapture data, these have inherent problems for estimating abundance in the presence of heterogeneity. Unlike conventional mark–recapture methods, line transect methods use knowledge of the distribution of a covariate, which affects detection probability (namely, distance from the transect line) in inference. This knowledge can be used to diagnose unmodeled heterogeneity in the mark–recapture component of the data. By modeling the covariance in detection probabilities with distance, we show how the estimation problem can be formulated in terms of different levels of independence. At one extreme, full independence is assumed, as in the Petersen estimator (which does not use distance data); at the other extreme, independence only occurs in the limit as detection probability tends to one. Between the two extremes, there is a range of models, including those currently in common use, which have intermediate levels of independence. We show how this framework can be used to provide more reliable analysis of double-observer line transect data. We test the methods by simulation, and by analysis of a dataset for which true abundance is known. We illustrate the approach through analysis of minke whale sightings data from the North Sea and adjacent waters.