Automatic Analysis of Dot Blot Images

Caridade, Cristina M. R.; Marçal, A.; Albuquerque, Pedro; Mendes, Marta V.; Tavares, Fernando

doi:10.1080/10798587.2015.1012849

Cited by 5 publications

(4 citation statements)

References 18 publications

(19 reference statements)

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“…Using a dedicated image analysis software previously described (Caridade et al, 2015), the dot blot results were converted in probability values of each dot being a positive result (Table 3). To ensure high confidence, only probability values higher than 0.5 were considered positive.…”

Section: Resultsmentioning

confidence: 99%

“…Hybridization with the labeled probes was carried out overnight at 68°C with washing and detection steps carried out according to the DIG system recommendations (Roche). A Molecular Imager Chemi Doc system (Bio Rad) was used to acquire the dot blot images, which were quantified using a custom-made image analysis software (Caridade et al, 2015). The results obtained with this software, which outputs the probability of each dot being a positive hybridization signal, were used to calculate the average probability values obtained for each probe/strain DNA combination (Table 3).…”

Section: Methodsmentioning

confidence: 99%

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Application of a Dot Blot Hybridization Platform to Assess Streptococcus uberis Population Structure in Dairy Herds

et al. 2017

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Streptococcus uberis is considered one of the most important pathogens associated with bovine mastitis. While traditionally acknowledged as an environmental pathogen, S. uberis has been shown to adopt a contagious epidemiological pattern in several dairy herds. Since different control strategies are employed depending on the mode of transmission, in-depth studies of S. uberis populations are essential to determine the best practices to control this pathogen. In this work, we optimized and validated a dot blot platform, combined with automatic image analysis, to rapidly assess the population structure of infective S. uberis, and evaluated its efficiency when compared to multilocus sequence analysis (MLSA) genotyping. Two dairy herds with prevalent S. uberis infections were followed in a 6 month period, in order to collect and characterize isolates from cows with persistent infections. These herds, located in Portugal (Barcelos and Maia regions), had similar management practices, with the herd from Barcelos being smaller and having a better milking parlor management, since infected cow segregation was immediate. A total of 54 S. uberis isolates were obtained from 24 different cows from the two herds. To overcome operator-dependent analysis of the dot blots and increase the technique's consistency and reliability, the hybridization signals were converted into probability values, with average probabilities higher than 0.5 being considered positive results. These data allowed to confirm the isolates' identity as S. uberis using taxa-specific markers and to determine the presence of virulence- and antibiotic resistance-related genes. In addition, MLSA allowed to disclose the most prevalent S. uberis clonal lineages in both herds. Seven different clusters were identified, with Barcelos showing a high clonal diversity and Maia a dominant lineage infecting most cows, suggesting distinct epidemiological patterns, with S. uberis displaying an environmental or contagious transmission pattern depending on the herd. Overall, this work showed the utility of dot blot and MLSA to characterize population structure and epidemiological patterns of mastitis-causing S. uberis. This approach allowed to disclose prevalent virulence patterns and clonal lineages of S. uberis in two distinct herds, and gain insights on the impact of herd management practices on pathogen population structure.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Application of a Dot Blot Hybridization Platform to Assess Streptococcus uberis Population Structure in Dairy Herds

et al. 2017

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“…Exposure time was measured using algorithms in MATLAB (https: / / www .mathworks .com/ products/ matlab .html) according to pixel saturation based on the saturation of a control dot, described in more detail in Marcal et al (2018). A probabilistic number was assigned to each dot based on the control dots, representing the hybridization signal for the combination of the S. uberis DNA sample and the known DNA probe (Caridade et al, 2015). Probability values greater than 0.5 were con-sidered positive, and the dot blot patterns were created according to the number of positive values.…”

Section: Dot Blot Hybridization and Pcrmentioning

confidence: 99%

Application of a dot blot hybridization assay for genotyping Streptococcus uberis from Brazilian dairy herds

Martins

Ribeiro

Tavares

et al. 2021

Journal of Dairy Science

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Streptococcus uberis is a major cause of environmental mastitis in many regions, and it is associated with clinical and subclinical infections. Although the main source of infection is the environment, reports of strains with a contagious profile have been described. Dot blot hybridization analysis allows the rapid identification of S. uberis population structures within and between herds, and it helps to identify strain diversity as well as possible clonal lineages that directly affect the control of bovine mastitis caused by this pathogen. The aim of this study was to evaluate the diversity of S. uberis isolates obtained from clinical (n = 22) and subclinical (n = 22) cases of mastitis in dairy herds (n = 13) in Brazil over a period of 12 mo. We submitted 44 S. uberis isolates to dot blot hybridization followed by automatic data analysis. We identified 8 different hybridization patterns using genetic markers associated with virulence factors and taxonomy, indicating diversity of S. uberis within the population and suggesting environmental transmission. However, the evidence of identical dot blot patterns in different mammary quarters from the same animal also suggested local contagious transmission. Of the virulence genes evaluated, we found a high prevalence of the genes sua, pauA, and gapC, highlighting the importance of these virulence factors for the adhesion, invasion, and multiplication of S. uberis in subclinical and clinical intramammary infections.

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“…The analysis of dot blot data was performed using an algorithm developed to automatically process the hybridization results obtained with a ChemiDoc imager. Briefly, this software adjusts each image to a user-defined grid and outputs the probability value of each dot being a positive result when compared to the positive and negative controls present in each membrane (Caridade et al, 2015). Therefore, the hybridization results can be converted into numerical values, which allows for a more robust analysis when compared to visual assessment of data.…”

Section: Quantitative Analysis Of Hybridization Datamentioning

confidence: 99%

A quantitative hybridization approach using 17 DNA markers for identification and clustering analysis of Ralstonia solanacearum

et al. 2015

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Ralstonia solanacearum (Rs) is a quarantine phytopathogenic bacterium accountable for heavy economic losses worldwide. Monitoring and eradication programmes required for this pathogen are dependent on the availability of time-and cost-efficient detection and typing methods. However, members of the Rs species complex are characterized by a high phenotypic and genetic diversity, which requires improved diagnostics methods. The currently available full genome sequences of several Rs strains allow for the selection of novel specific DNA markers using comparative genomics tools. In this work, 17 novel markers were selected based on Rs-specific protein domains and thoroughly validated for specificity and stability, both in silico and using 'wet lab' assays. Polymerase chain reaction-and hybridization-based validation assays revealed that the DNA regions selected as markers were unevenly distributed amongst the tested strains, with nine markers present throughout the species complex. The distribution of the remaining eight markers was highly variable between the different analysed strains and enabled the attainment of strain-specific dot blot hybridization patterns, particularly informative for typing. The average probability value of each strain being positive for each of the 17 markers was calculated by an algorithm and used to obtain a dendrogram representing hierarchical clustering analysis of Rs, according to the similarity of their hybridization patterns. This method should prove to be a robust and straightforward procedure for genotyping members of the Rs species complex. Furthermore, this quantitative hybridization approach will allow the construction of informative databases to determine new Rs genotypes and infer epidemiological patterns.

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Automatic Analysis of Dot Blot Images

Cited by 5 publications

References 18 publications

Application of a Dot Blot Hybridization Platform to Assess Streptococcus uberis Population Structure in Dairy Herds

Application of a Dot Blot Hybridization Platform to Assess Streptococcus uberis Population Structure in Dairy Herds

Application of a dot blot hybridization assay for genotyping Streptococcus uberis from Brazilian dairy herds

A quantitative hybridization approach using 17 DNA markers for identification and clustering analysis of Ralstonia solanacearum

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