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European Journal of Clinical Microbiology and Infectious Diseases 2017-Aug

Genetic makeup of Shiga toxin-producing Escherichia coli in relation to clinical symptoms and duration of shedding: a microarray analysis of isolates from Swedish children.

Vain rekisteröityneet käyttäjät voivat kääntää artikkeleita
Kirjaudu sisään Rekisteröidy
Linkki tallennetaan leikepöydälle
A Matussek
C Jernberg
I-M Einemo
S Monecke
R Ehricht
I Engelmann
S Löfgren
S Mernelius

Avainsanat

Abstrakti

Shiga toxin (Stx)-producing Escherichia coli (STECs) cause non-bloody diarrhea, hemorrhagic colitis, and hemolytic uremic syndrome, and are the primary cause of acute renal failure in children worldwide. This study investigated the correlation of genetic makeup of STEC strains as revealed by DNA microarray to clinical symptoms and the duration of STEC shedding. All STEC isolated (n = 96) from patients <10 years of age in Jönköping County, Sweden from 2003 to 2015 were included. Isolates were characterized by DNA microarray, including almost 280 genes. Clinical data were collected through a questionnaire and by reviewing medical records. Of the 96 virulence genes (including stx) in the microarray, 62 genes were present in at least one isolate. Statistically significant differences in prevalence were observed for 21 genes when comparing patients with bloody diarrhea (BD) and with non-bloody stool (18 of 21 associated with BD). Most genes encode toxins (e.g., stx2 alleles, astA, toxB), adhesion factors (i.e. espB_O157, tir, eae), or secretion factors (e.g., espA, espF, espJ, etpD, nleA, nleB, nleC, tccP). Seven genes were associated with prolonged stx shedding; the presence of three genes (lpfA, senB, and stx1) and the absence of four genes (espB_O157, espF, astA, and intI1). We found STEC genes that might predict severe disease outcome already at diagnosis. This can be used to develop diagnostic tools for risk assessment of disease outcome. Furthermore, genes associated with the duration of stx shedding were detected, enabling a possible better prediction of length of STEC carriage after infection.

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