Pulsed-Field Gel Electrophoresis of Yersinia pestis

Revazishvili, Tamara; Johnson, Judith A.

doi:10.1007/978-1-4939-2599-5_11

Cited by 2 publications

(1 citation statement)

References 7 publications

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“…Now and after finishing the previous seven steps we have all the information required for calculating the similarity between the samples and generating the corresponding phylogenetic tree such as the number of the samples, the position of each band in the sample and molecular weights. The software implements UPGMA clustering algorithm which is considered as one of the most used methods for generating phylogenetic tree [18] in which all of GelClust, gelQuest [19], BioNumerics software [20], a laboratory technique called Pulsed-field gel electrophoresis (PFGE) [21], [22], GelJ [23] are used UPGMA algorithm to generate the phylogenetic tree. The process of generating the phylogenetic tree is done by calculating the centroid point for bands in each lane then using Euclidean distance to get the distance between each lane and calculate the distance matrix then passing this matrix to the implemented UPGMA clustering algorithm to construct the Phylogenetic tree.…”

Section: G Generating the Phylogenetic Treementioning

confidence: 99%

EGBIOIMAGE: A Software Tool for Gel Images Analysis and Hierarchical Clustering

2020

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This paper presents a novel software called EGBioImage that is implemented for analyzing gel Electrophoresis images, computing the molecular weights of the bands of the unknown size, detecting the types of the bands, grouping the bands according to their molecular weights and labeled each band with its group number in the gel image and generating the corresponding phylogenetic tree using the data extracted from the analyzed gel image. Students and Researchers working in molecular biology and genetics would benefit greatly from EGBioImage. This software is designed and developed under windows operating system using a C-sharp programming language. It uses Emgu CV platform to extract contours objects from an image that uses the green theorem to detect the bands in each detected lane. It uses polynomial regression to calculate the molecular weights of the bands of unknown size. It uses K-means clustering algorithm to cluster bands according to their molecular weights. It uses each of upgma algorithm and the matching bands amongst lanes and to construct the phylogenetic tree. EGBioImage provides a very friendly Graphical User Interface that guides the user from the step of uploading a gel image toward getting the molecular weights of the bands of unknown size and generating the Phylogenetic Tree. Moreover, EGBioImage provides the user with the ability of processing the gel image using a completely manual processing and automatic processing with the ability of manual correction of lanes and bands ''Semi-automatic process'' and it is more accurate than comparable software in some respects and the only software that divides the bands into groups and labeled them with numbers in the gel image based on their group by implementing k-means algorithm and these claims are supported with experiments. EGBioImage is suitable for students and researchers who do not have access to commercial software. INDEX TERMS Gel electrophoresis, image processing, phylogenetic tree, band matching, polynomial regression, UPGMA algorithm, k-means algorithm, software.

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Section: G Generating the Phylogenetic Treementioning

confidence: 99%

EGBIOIMAGE: A Software Tool for Gel Images Analysis and Hierarchical Clustering

2020

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Genome and Evolution of Yersinia pestis

Cui

Song

2016

Advances in Experimental Medicine and Biology

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This chapter summarizes researches on genome and evolution features of Yersinia pestis, the young pathogen that evolved from Y. pseudotuberculosis at least 5000 years ago. Y. pestis is a highly clonal bacterial species with closed pan-genome. Comparative genomic analysis revealed that genome of Y. pestis experienced highly frequent rearrangement and genome decay events during the evolution. The genealogy of Y. pestis includes five major branches, and four of them seemed raised from a "big bang" node that is associated with the Black Death. Although whole genome-wide variation of Y. pestis reflected a neutral evolutionary process, the branch length in the genealogical tree revealed over dispersion, which was supposedly caused by varied historical molecular clock that is associated with demographical effect by alternate cycles of enzootic disease and epizootic disease in sylvatic plague foci. In recent years, palaeomicrobiology researches on victims of the Black Death, and Justinian's plague verified that two historical pandemics were indeed caused by Y. pestis, but the etiological lineages might be extinct today.

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Pulsed-Field Gel Electrophoresis of Yersinia pestis

Cited by 2 publications

References 7 publications

EGBIOIMAGE: A Software Tool for Gel Images Analysis and Hierarchical Clustering

EGBIOIMAGE: A Software Tool for Gel Images Analysis and Hierarchical Clustering

Genome and Evolution of Yersinia pestis

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