24 research outputs found

    ExpoSeq: simplified analysis of high-throughput sequencing data from antibody discovery campaigns

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    High-throughput sequencing (HTS) offers a modern, fast, and explorative solution to unveil the full potential of display techniques, like antibody phage display, in molecular biology. However, a significant challenge lies in the processing and analysis of such data. Furthermore, there is a notable absence of open-access user-friendly software tools that can be utilized by scientists lacking programming expertise. Here, we present ExpoSeq as an easy-to-use tool to explore, process, and visualize HTS data from antibody discovery campaigns like an expert while only requiring a beginner's knowledge. The pipeline is distributed via GitHub and PyPI, and it can either be installed as a package with pip or the user can choose to clone the repository

    Cross-reactivity trends when selecting scFv antibodies against snake toxins using a phage display-based cross-panning strategy

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    Abstract Antibodies with cross-reactive binding and broad toxin-neutralizing capabilities are advantageous for treating indications such as infectious diseases and animal envenomings. Such antibodies have been successfully selected against closely related antigens using phage display technology. However, the mechanisms driving antibody cross-reactivity typically remain to be elucidated. Therefore, we sought to explore how a previously reported phage display-based cross-panning strategy drives the selection of cross-reactive antibodies using seven different snake toxins belonging to three protein (sub-)families: phospholipases A2, long-chain α-neurotoxins, and short-chain α-neurotoxins. We showcase how cross-panning can increase the chances of discovering cross-reactive single-chain variable fragments (scFvs) from phage display campaigns. Further, we find that the feasibility of discovering cross-reactive antibodies using cross-panning cannot easily be predicted by analyzing the sequence, structural, or surface similarity of the antigens alone. However, when antigens share the (exact) same functions, this seems to increase the chances of selecting cross-reactive antibodies, which may possibly be due to the existence of structurally similar motifs on the antigens

    AHA: AI-guided tool for the quantification of venom-induced haemorrhage in mice

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    Venom-induced haemorrhage constitutes a severe pathology in snakebite envenomings, especially those inflicted by viperid species. To both explore venom activity accurately and evaluate the efficacy of viperid antivenoms for the neutralisation of haemorrhagic activity it is essential to have available a precise, quantitative tool for empirically determining venom-induced haemorrhage. Thus, we have built on our prior approach and developed a new AI-guided tool (AHA) for the quantification of venom-induced haemorrhage in mice. Using a smartphone, it takes less than a minute to take a photo, upload the image, and receive accurate information on the magnitude of a venom-induced haemorrhagic lesion in mice. This substantially decreases analysis time, reduces human error, and does not require expert haemorrhage analysis skills. Furthermore, its open access web-based graphical user interface makes it easy to use and implement in laboratories across the globe. Together, this will reduce the resources required to preclinically assess and control the quality of antivenoms, whilst also expediting the profiling of haemorrhagic activity in venoms for the wider toxinology community
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