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The standard screening test for the recognition of autoimmune diseases is the proof of autoantibodies in serum of patients by indirect immunofluorescence (IIF) based on HEp‐2 cells. Manual evaluation of this test is very subjective, slow, and there are no objective parameters as guidelines available. Interlaboratory tests showed occasionally large deviations in the test evaluation resulting in a high variance of results. The aim of this project is fast, objective, safe, and economical automatic analysis of HEp‐2 IIF patterns. Images of IIF patterns were completely and automatically captured using an inverse motorized fluorescence microscope. Thereby, device‐specific parameters were controlled automatically, too. For fast analysis of IIF patterns new algorithms of image processing were developed. Artifacts were recognized and excluded from analysis by the developed software. Analysis of more than 80,000 images clearly demonstrated full automatization and fast processing of IIF patterns. Additionally serum‐specific fluorescence could be easily distinguished from background. Even very weak but positive patterns can be recognized and used for diagnosis. A detailed separation into different basic patterns is possible. Objective, fast, and disease‐related economical analysis of HEp‐2 immunofluorescence patterns is feasible. The implemented software algorithms allowed a mathematical way of describing IIF patterns and can therefore be a useful tool for the needed standardization process.
Intestinal colonization is influenced by the ability of the bacterium to inhabit a niche, which is based on the expression of colonization factors. Escherichia coli carries a broad range of virulence-associated genes (VAGs) which contribute to intestinal (inVAGs) and extraintestinal (exVAGs) infection. Moreover, initial evidence indicates that inVAGs and exVAGs support intestinal colonization. We developed new screening tools to genotypically and phenotypically characterize E. coli isolates originating in humans, domestic pigs, and 17 wild mammal and avian species. We analyzed 317 isolates for the occurrence of 44 VAGs using a novel multiplex PCR microbead assay (MPMA) and for adhesion to four epithelial cell lines using a new adhesion assay. We correlated data for the definition of new adhesion genes. inVAGs were identified only sporadically, particularly in roe deer (Capreolus capreolus) and the European hedgehog ( Erinaceus europaeus). The prevalence of exVAGs depended on isolation from a specific host. Human uropathogenic E. coli isolates carried exVAGs with the highest prevalence, followed by badger (Meles meles) and roe deer isolates. Adhesion was found to be very diverse. Adhesion was specific to cells, host, and tissue, though it was also unspecific. Occurrence of the following VAGs was associated with a higher rate of adhesion to one or more cell lines: afa-dra, daaD, tsh, vat, ibeA, fyuA, mat, sfa-foc, malX, pic, irp2, and papC. In summary, we established new screening methods which enabled us to characterize large numbers of E. coli isolates. We defined reservoirs for potential pathogenic E. coli. We also identified a very broad range of colonization strategies and defined potential new adhesion genes.
Abstract
BACKGROUND:
Different strategies of colonization or infection by E. coli result in formation of certain adhesion patterns which help also in classifying intestinal E. coli into pathotypes. Little is known about adhesion patterns and host- and tissue adaption of commensal E. coli and about E. coli originating in clinically healthy hosts carrying pathotype-specific virulence-associated genes.
FINDINGS:
Adhesion pattern of E. coli (n = 282) from humans and from 18 animal species were verified on intestinal human Caco-2 and porcine IPEC-J2 cells and, furthermore, for comparison on human urinary bladder 5637, porcine kidney PK-15 epithelial and HEp-2 cells. The analysis was carried out on 150,000 images of adhesion assays.Adhesion patterns were very diverse; 88 isolates were completely non-adherent, whereas 194 adhered to at least one cell line with the dominant adhesion patterns "diffusely distributed" and "microcolony formation". Adhesion patterns "chains" and "clumps" were also visible. Chain formation was mediated by the presence of epithelial cells. Clump formation was very specific on only the 5637 cell line. All enteropathogenic (eae+) E. coli (EPEC; n = 14) were able to form microcolonies which was cell line specific for each isolate. Most EPEC formed microcolonies on intestinal IPEC-J2 and Caco-2 but several also on urinary tract cells. Shigatoxin-producing (stx+) E. coli (n = 10) showed no specific adhesion patterns.
CONCLUSIONS:
E. coli isolates were highly diverse. Commensal and pathogenic isolates can adhere in various forms, including diffuse distribution, microcolonies, chains and clumps. Microcolony formation seems to be a global adhesion strategy also for commensal E. coli.