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  • 1
    ISSN: 1574-6968
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Biology
    Notes: The immobilization of recombinant staphylococci onto cellulose fibers through surface display of a fungal cellulose-binding domain (CBD) was investigated. Chimeric proteins containing the CBD from Trichoderma reesei cellulase Cel6A were found to be correctly targeted to the cell wall of Staphylococcus carnosus cells, since full-length proteins could be extracted and affinity-purified. Furthermore, surface accessibility of the CBD was verified using a monoclonal antibody and functionality in terms of cellulose-binding was demonstrated in two different assays in which recombinant staphylococci were found to efficiently bind to cotton fibers. The implications of this strategy of directed immobilization for the generation of whole-cell microbial tools for different applications will be discussed.
    Type of Medium: Electronic Resource
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  • 2
    Publication Date: 2022-02-17
    Description: We have implemented the pypgatk package and the pgdb workflow to create proteogenomics databases based on ENSEMBL resources. The tools allow the generation of protein sequences from novel protein-coding transcripts by performing a three-frame translation of pseudogenes, lncRNAs, and other non-canonical transcripts, such as those produced by alternative splicing events. It also includes exonic out-of-frame translation from otherwise canonical protein-coding mRNAs. Moreover, the tool enables the generation of variant protein sequences from multiple sources of genomic variants including COSMIC, cBioportal, gnomAD, and mutations detected from sequencing of patient samples. pypgatk and pgdb provide multiple functionalities for database handling, notably optimized target/decoy generation by the algorithm DecoyPyrat. Finally, we perform a reanalysis of four public datasets in PRIDE by generating cell-type specific databases for 65 cell lines using the pypgatk and pgdb workflow, revealing a wealth of non-canonical or cryptic peptides amounting to more than 10% of the total number of peptides identified (43,501 out of 402,512).
    Language: English
    Type: article , doc-type:article
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