The analysis of different biomolecules is of prime importance for life science research and medical diagnostics. Due to the discovery of new molecules and new emerging bioanalytical problems, there is an ongoing demand for a technology platform that provides a broad range of assays with a user-friendly flexibility and rapid adaptability to new applications. Here we describe a highly versatile microscopy platform, VideoScan, for the rapid and simultaneous analysis of various assay formats based on fluorescence microscopic detection. The technological design is equally suitable for assays in solution, microbead-based assays and cell pattern recognition. The multiplex real-time capability for tracking of changes under dynamic heating conditions makes it a useful tool for PCR applications and nucleic acid hybridization, enabling kinetic data acquisition impossible to obtain by other technologies using endpoint detection. The paper discusses the technological principle of the platform regarding data acquisition and processing. Microbead-based and solution applications for the detection of diverse biomolecules, including antigens, antibodies, peptides, oligonucleotides and amplicons in small reaction volumes, are presented together with a high-content detection of autoimmune antibodies using a HEp-2 cell assay. Its adaptiveness and versatility gives VideoScan a competitive edge over other bioanalytical technologies.

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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.

The rapid and simultaneous detection of DNA and protein biomarkers is necessary to detect the outbreak of a disease or to monitor a disease. For example, cardiovascular diseases are a major cause of adult mortality worldwide. We have developed a rapidly adaptable platform to assess biomarkers using a microfluidic technology. Our model mimics autoantibodies against three proteins, C-reactive protein (CRP), brain natriuretic peptide (BNP), and low-density lipoprotein (LDL). Cell-free mitochondrial DNA (cfmDNA) and DNA controls are detected via fluorescence probes. The biomarkers are covalently bound on the surface of size- (11–15 μm) and dual-color encoded microbeads and immobilized as planar layer in a microfluidic chip flow cell. Binding events of target molecules were analyzed by fluorescence measurements with a fully automatized fluorescence microscope (end-point and real-time) developed in house. The model system was optimized for buffers and immobilization strategies of the microbeads to enable the simultaneous detection of protein and DNA biomarkers. All prime target molecules (anti-CRP, anti-BNP, anti-LDL, cfmDNA) and the controls were successfully detected both in independent reactions and simultaneously. In addition, the biomarkers could also be detected in spiked human serum in a similar way as in the optimized buffer system. The detection limit specified by the manufacturer is reduced by at least a factor of five for each biomarker as a result of the antibody detection and kinetic experiments indicate that nearly 50 % of the fluorescence intensity is achieved within 7 min. For rapid data inspection, we have developed the open source software digilogger, which can be applied for data evaluation and visualization. Graphical abstract Electronic supplementary materialThe online version of this article (10.1007/s00216-019-02199-x) contains supplementary material, which is available to authorized users.

Amplification curves from quantitative Real-Time PCR experiments typically exhibit a sigmoidal shape. They can roughly be divided into a ground or baseline phase, an exponential amplification phase, a linear phase and finally a plateau phase, where in the latter, the PCR product concentration no longer increases. Nevertheless, in some cases the plateau phase displays a negative trend, e.g. in hydrolysis probe assays. This cycle-to-cycle fluorescence decrease is commonly referred to in the literature as the hook effect. Other detection chemistries also exhibit this negative trend, however the underlying molecular mechanisms are different.In this study we present two approaches to automatically detect hook effect-like curvatures based on linear (hookreg) and nonlinear regression (hookregNL). As the hook effect is typical for qPCR data, both algorithms can be employed for the automated identification of regular structured qPCR curves. Therefore, our algorithms streamline quality control, but can also be used for assay optimization or machine learning.