The genetically and antigenically diverse group of noroviruses is the major cause of human viral epidemic gastroenteritis worldwide. Virus detection and control are thus crucial topics when aiming at containing and preventing the resulting large and often persisting outbreaks. Aptamers provide a promising alternative to antibodies concerning their ability to bind and thus detect and influence bio-active molecules. These small, single-stranded oligonucleotides are able to bind to a multitude of possible target molecules with high affinity. For a specific target the highest affinity aptamers are found by screening a randomized library. In this work a DNA aptamer capable of binding to the norovirus genotype II.4 capsid protein VP1 was found. The general approach is thereby not limited to norovirus capsid, but could be extended to almost any kind of biologically relevant molecule. The development of the library enrichment was further computationally analyzed in order to describe the enrichment during screening. This is the basis for a later extensive characterization of both target and aptamers that could lead to insights regarding the functional coherence of both partners. An abstract model describing this coherence could be utilized to generate a target-specific library, from which future aptamer screening runs could benefit.

Aptamers are an interesting alternative to antibodies in pharmaceutics and biosensorics, because they are able to bind to a multitude of possible target molecules with high affinity. Therefore the process of finding such aptamers, which is commonly a SELEX screening process, becomes crucial. The standard SELEX procedure schedules the validation of certain found aptamers via binding experiments, which is not leading to any detailed specification of the aptamer enrichment during the screening. For the purpose of advanced analysis of the accrued enrichment within the SELEX library we used sequence information gathered by next generation sequencing techniques in addition to the standard SELEX procedure. As sequence motifs are one possibility of enrichment description, the need of finding those recurring sequence motifs corresponding to substructures within the aptamers, which are characteristically fitted to specific binding sites of the target, arises. In this paper a motif search algorithm is presented, which helps to describe the aptamers enrichment in more detail. The extensive characterization of target and binding aptamers may later reveal a functional connection between these molecules, which can be modeled and used to optimize future SELEX runs in case of the generation of target-specific starting libraries.

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Summary 1.Terminal restriction fragment length polymorphism (TRFLP) analysis remains a useful technique to obtain insights into the genetic diversity of microbial populations. A crucial parameter of the technique is the selection of appropriate restriction endonucleases (REs) to achieve high resolution between the PCR-amplified fragments of a marker gene (usually a ribosomal RNA gene). However, despite the development of several computer-supported programmes to improve the selection of REs for TRFLP analysis, there is still a lack of software that offers both of two aspects: first, availability of a sequence data base from which sequences can easily and without further formatting and ranking be selected for analysis; secondly, selection of sets of REs for highest genetic resolution while providing the possibility to assess and quantify the correlation of the TRFs with the phylogeny of the target group of 16S rRNA sequences. 2. Here, we present a new and freely available software tool which utilises ARB in combination with the SILVA data base of hundreds of thousands of aligned ribosomal RNA genes or user-submitted sequences as basis for the selection of optimal sets of REs of various sizes. Apart from coping with missing sequence information and providing extensive information on the obtained TRF patterns, this new programme for Optimising EnZYme selection for best performing TRFLP analysis using ARB (OEZY) also assesses the level at which the resulting TRF pattern reflects the phylogeny based on the data base gene sequences. 3. Optimising EnZYme is a substantial extension to hitherto available software as it opens the chance to correctly predict the phylogenetic position of yet unknown sequence types. Choosing REs that lead to a high correlation between the resulting TRFs and the phylogeny of the micro-organisms based on the nucleotide sequence of the marker gene makes it likely that the TRFs also fall within the corresponding phylogenetic clade. OEZY therefore provides a diagnostic tool for the analysis of microbial populations.