scholarly journals Specificity and sensitivity evaluation of novel and existing Bacteroidales and Bifidobacteria-specific PCR assays on feces and sewage samples and their application for microbial source tracking in Ireland

2009 ◽  
Vol 43 (19) ◽  
pp. 4980-4988 ◽  
Author(s):  
Siobhán Dorai-Raj ◽  
Justin O' Grady ◽  
Emer Colleran
2008 ◽  
Vol 74 (22) ◽  
pp. 6839-6847 ◽  
Author(s):  
Yong-Jin Lee ◽  
Marirosa Molina ◽  
Jorge W. Santo Domingo ◽  
Jonathan D. Willis ◽  
Michael Cyterski ◽  
...  

ABSTRACT Exposure to feces in two watersheds with different management histories was assessed by tracking cattle feces bacterial populations using multiple host-specific PCR assays. In addition, environmental factors affecting the occurrence of these markers were identified. Each assay was performed using DNA extracts from water and sediment samples collected from a watershed directly impacted by cattle fecal pollution (WS1) and from a watershed impacted only through runoff (WS2). In WS1, the ruminant-specific Bacteroidales 16S rRNA gene marker CF128F was detected in 65% of the water samples, while the non-16S rRNA gene markers Bac1, Bac2, and Bac5 were found in 32 to 37% of the water samples. In contrast, all source-specific markers were detected in less than 6% of the water samples from WS2. Binary logistic regressions (BLRs) revealed that the occurrence of Bac32F and CF128F was significantly correlated with season as a temporal factor and watershed as a site factor. BLRs also indicated that the dynamics of fecal-source-tracking markers correlated with the density of a traditional fecal indicator (P < 0.001). Overall, our results suggest that a combination of 16S rRNA gene and non-16S rRNA gene markers provides a higher level of confidence for tracking unknown sources of fecal pollution in environmental samples. This study also provided practical insights for implementation of microbial source-tracking practices to determine sources of fecal pollution and the influence of environmental variables on the occurrence of source-specific markers.


2021 ◽  
Vol 232 (2) ◽  
Author(s):  
Meriane Demoliner ◽  
Juliana Schons Gularte ◽  
Viviane Girardi ◽  
Ana Karolina Antunes Eisen ◽  
Fernanda Gil de Souza ◽  
...  

Agronomy ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1489
Author(s):  
Tammy Stackhouse ◽  
Sumyya Waliullah ◽  
Alfredo D. Martinez-Espinoza ◽  
Bochra Bahri ◽  
Emran Ali

Dollar spot is one of the most destructive diseases in turfgrass. The causal agents belong to the genus Clarireedia, which are known for causing necrotic, sunken spots in turfgrass that coalesce into large damaged areas. In low tolerance settings like turfgrass, it is of vital importance to rapidly detect and identify the pathogens. There are a few methods available to identify the genus Clarireedia, but none of those are rapid enough and characterize down to the species level. This study produced a co-dominant cleaved amplified polymorphic sequences (CAPS) test that differentiates between C. jacksonii and C. monteithiana, the two species that cause dollar spot disease within the United States. The calmodulin gene (CaM) was targeted to generate Clarireedia spp. specific PCR primers. The CAPS assay was optimized and tested for specificity and sensitivity using DNA extracted from pure cultures of two Clarireedia spp. and other closely related fungal species. The results showed that the newly developed primer set could amplify both species and was highly sensitive as it detected DNA concentrations as low as 0.005 ng/µL. The assay was further validated using direct PCR to speed up the diagnosis process. This drastically reduces the time needed to identify the dollar spot pathogens. The resulting assay could be used throughout turfgrass settings for a rapid and precise identification method in the US.


2014 ◽  
Vol 8 (1) ◽  
pp. e2671 ◽  
Author(s):  
Laetitia Fabre ◽  
Simon Le Hello ◽  
Chrystelle Roux ◽  
Sylvie Issenhuth-Jeanjean ◽  
François-Xavier Weill

Author(s):  
Jan Lorenz Soliman ◽  
Alex Dekhtyar ◽  
Jennifer Vanderkellen ◽  
Aldrin Montana ◽  
Michael Black ◽  
...  

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