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A New Distribution Family for Microarray Data
Please note that, as of 18 July 2017, Microarrays has been renamed to High-Throughput and is now published here.
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Use of a Pan–Genomic DNA Microarray in Determination of the Phylogenetic Relatedness among Cronobacter spp. and Its Use as a Data Mining Tool to Understand Cronobacter Biology

Center of Food Safety and Applied Nutrition, U. S. Food and Drug Administration, Laurel, MD 20708, USA
Complex Microbial Systems Group Biosystems and Biomaterials Division, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA
UCD Centre for Food Safety, School of Public Health, Physiotherapy & Population Science, University College, Dublin, Belfield, Dublin D04 N2E5, Ireland
College of Life Sciences, University of Dundee, Dundee, DD1 5EH Scotland, UK
Food Directorate, Bureau of Microbial Hazards, Health Canada, Ottawa, ON K1A 0K9, Canada
Institute for Food Safety and Hygiene, University of Zurich, Winterthurerstr. 272, CH-8057 Zurich, Switzerland
Department of Food Science, University of Guelph, Guelph, ON N1G 2W1, Canada
Author to whom correspondence should be addressed.
Academic Editor: Massimo Negrini
Microarrays 2017, 6(1), 6;
Received: 31 October 2016 / Revised: 8 February 2017 / Accepted: 21 February 2017 / Published: 4 March 2017
(This article belongs to the Special Issue Microarrays for Food Safety and Quality)
Cronobacter (previously known as Enterobacter sakazakii) is a genus of Gram-negative, facultatively anaerobic, oxidase-negative, catalase-positive, rod-shaped bacteria of the family Enterobacteriaceae. These organisms cause a variety of illnesses such as meningitis, necrotizing enterocolitis, and septicemia in neonates and infants, and urinary tract, wound, abscesses or surgical site infections, septicemia, and pneumonia in adults. The total gene content of 379 strains of Cronobacter spp. and taxonomically-related isolates was determined using a recently reported DNA microarray. The Cronobacter microarray as a genotyping tool gives the global food safety community a rapid method to identify and capture the total genomic content of outbreak isolates for food safety, environmental, and clinical surveillance purposes. It was able to differentiate the seven Cronobacter species from one another and from non-Cronobacter species. The microarray was also able to cluster strains within each species into well-defined subgroups. These results also support previous studies on the phylogenic separation of species members of the genus and clearly highlight the evolutionary sequence divergence among each species of the genus compared to phylogenetically-related species. This review extends these studies and illustrates how the microarray can also be used as an investigational tool to mine genomic data sets from strains. Three case studies describing the use of the microarray are shown and include: (1) the determination of allelic differences among Cronobacter sakazakii strains possessing the virulence plasmid pESA3; (2) mining of malonate and myo-inositol alleles among subspecies of Cronobacter dublinensis strains to determine subspecies identity; and (3) lastly using the microarray to demonstrate sequence divergence and phylogenetic relatedness trends for 13 outer-membrane protein alleles among 240 Cronobacter and phylogenetically-related strains. The goal of this review is to describe microarrays as a robust tool for genomics research of this assorted and important genus, a criterion toward the development of future preventative measures to eliminate this foodborne pathogen from the global food supply. View Full-Text
Keywords: Cronobacter; microarray; data mining Cronobacter; microarray; data mining
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Tall, B.D.; Gangiredla, J.; Grim, C.J.; Patel, I.R.; Jackson, S.A.; Mammel, M.K.; Kothary, M.H.; Sathyamoorthy, V.; Carter, L.; Fanning, S.; Iversen, C.; Pagotto, F.; Stephan, R.; Lehner, A.; Farber, J.; Yan, Q.Q.; Gopinath, G.R. Use of a Pan–Genomic DNA Microarray in Determination of the Phylogenetic Relatedness among Cronobacter spp. and Its Use as a Data Mining Tool to Understand Cronobacter Biology. Microarrays 2017, 6, 6.

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