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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.

ABSTRACT: 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.

SUBMITTER: Tall BD

PROVIDER: S-EPMC5374366 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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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.

Tall Ben D BD Gangiredla Jayanthi J Grim Christopher J CJ Patel Isha R IR Jackson Scott A SA Mammel Mark K MK Kothary Mahendra H MH Sathyamoorthy Venugopal V Carter Laurenda L Fanning Séamus S Iversen Carol C Pagotto Franco F Stephan Roger R Lehner Angelika A Farber Jeffery J Yan Qiong Q QQ Gopinath Gopal R GR

Microarrays (Basel, Switzerland) 20170304 1

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 <i ...[more]

PMID: 28273858

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Project description:BACKGROUND: Inflammation is a hallmark of many human diseases. Elucidating the mechanisms underlying systemic inflammation has long been an important topic in basic and clinical research. When primary pathogenetic events remains unclear due to its immense complexity, construction and analysis of the gene regulatory network of inflammation at times becomes the best way to understand the detrimental effects of disease. However, it is difficult to recognize and evaluate relevant biological processes from the huge quantities of experimental data. It is hence appealing to find an algorithm which can generate a gene regulatory network of systemic inflammation from high-throughput genomic studies of human diseases. Such network will be essential for us to extract valuable information from the complex and chaotic network under diseased conditions. RESULTS: In this study, we construct a gene regulatory network of inflammation using data extracted from the Ensembl and JASPAR databases. We also integrate and apply a number of systematic algorithms like cross correlation threshold, maximum likelihood estimation method and Akaike Information Criterion (AIC) on time-lapsed microarray data to refine the genome-wide transcriptional regulatory network in response to bacterial endotoxins in the context of dynamic activated genes, which are regulated by transcription factors (TFs) such as NF-kappaB. This systematic approach is used to investigate the stochastic interaction represented by the dynamic leukocyte gene expression profiles of human subject exposed to an inflammatory stimulus (bacterial endotoxin). Based on the kinetic parameters of the dynamic gene regulatory network, we identify important properties (such as susceptibility to infection) of the immune system, which may be useful for translational research. Finally, robustness of the inflammatory gene network is also inferred by analyzing the hubs and "weak ties" structures of the gene network. CONCLUSION: In this study, Data mining and dynamic network analyses were integrated to examine the gene regulatory network in the inflammatory response system. Compared with previous methodologies reported in the literatures, the proposed gene network perturbation method has shown a great improvement in analyzing the systemic inflammation.

Project description:Cronobacter species are opportunistic pathogens capable of causing life-threatening infections in humans, with serious complications arising in neonates, infants, immuno-compromised individuals, and elderly adults. The genus is comprised of seven species: Cronobacter sakazakii, Cronobacter malonaticus, Cronobacter turicensis, Cronobacter muytjensii, Cronobacter dublinensis, Cronobacter universalis, and Cronobacter condimenti. Despite a multiplicity of genomic data for the genus, little is known about likely transmission vectors. Using DNA microarray analysis, in parallel with whole genome sequencing, and targeted PCR analyses, the total gene content of two C. malonaticus, three C. turicensis, and 14 C. sakazaki isolated from various filth flies was assessed. Phylogenetic relatedness among these and other strains obtained during surveillance and outbreak investigations were comparatively assessed. Specifically, microarray analysis (MA) demonstrated its utility to cluster strains according to species-specific and sequence type (ST) phylogenetic relatedness, and that the fly strains clustered among strains obtained from clinical, food and environmental sources from United States, Europe, and Southeast Asia. This combinatorial approach was useful in data mining for virulence factor genes, and phage genes and gene clusters. In addition, results of plasmidotyping were in agreement with the species identity for each strain as determined by species-specific PCR assays, MA, and whole genome sequencing. Microarray and BLAST analyses of Cronobacter fly sequence datasets were corroborative and showed that the presence and absence of virulence factors followed species and ST evolutionary lines even though such genes were orthologous. Additionally, zebrafish infectivity studies showed that these pathotypes were as virulent to zebrafish embryos as other clinical strains. In summary, these findings support a striking phylogeny amongst fly, clinical, and surveillance strains isolated during 2010-2015, suggesting that flies are capable vectors for transmission of virulent Cronobacter spp.; they continue to circulate among United States and European populations, environments, and that this "pattern of circulation" has continued over decades.

Project description:BackgroundThis paper describes the results of a Gene Ontology (GO) term enrichment analysis of chicken microarray data using the Bioconductor packages. By checking the enriched GO terms in three contrasts, MM8-PM8, MM8-MA8, and MM8-MM24, of the provided microarray data during this workshop, this analysis aimed to investigate the host reactions in chickens occurring shortly after a secondary challenge with either a homologous or heterologous species of Eimeria. The results of GO enrichment analysis using GO terms annotated to chicken genes and GO terms annotated to chicken-human orthologous genes were also compared. Furthermore, a locally adaptive statistical procedure (LAP) was performed to test differentially expressed chromosomal regions, rather than individual genes, in the chicken genome after Eimeria challenge.ResultsGO enrichment analysis identified significant (raw p-value < 0.05) GO terms for all three contrasts included in the analysis. Some of the GO terms linked to, generally, primary immune responses or secondary immune responses indicating the GO enrichment analysis is a useful approach to analyze microarray data. The comparisons of GO enrichment results using chicken gene information and chicken-human orthologous gene information showed more refined GO terms related to immune responses when using chicken-human orthologous gene information, this suggests that using chicken-human orthologous gene information has higher power to detect significant GO terms with more refined functionality. Furthermore, three chromosome regions were identified to be significantly up-regulated in contrast MM8-PM8 (q-value < 0.01).ConclusionOverall, this paper describes a practical approach to analyze microarray data in farm animals where the genome information is still incomplete. For farm animals, such as chicken, with currently limited gene annotation, borrowing gene annotation information from orthologous genes in well-annotated species, such as human, will help improve the pathway analysis results substantially. Furthermore, LAP analysis approach is a relatively new and very useful way to be applied in microarray analysis.

Dataset Information

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.

Publications

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.

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