Proteolytic cleavage of the membrane-bound Interleukin-6 receptor (IL-6R) by the metalloprotease ADAM17 releases an agonistic soluble form of the IL-6R (sIL-6R), which is responsible for the pro-inflammatory trans-signaling branch of the cytokine's activities. This proteolytic step, which is also called ectodomain shedding, is critically regulated by the cleavage site within the IL-6R stalk, because mutations or small deletions within this region are known to render the IL-6R irresponsive towards proteolysis. In the present study, we employed cleavage site profiling data of ADAM17 to generate an IL-6R with increased cleavage susceptibility. Using site-directed mutagenesis, we showed that the non-prime sites P3 and P2 and the prime site P1' were critical for this increase in proteolysis, whereas other positions within the cleavage site were of minor importance. Insertion of this optimized cleavage site into the stalk of the Interleukin-11 receptor (IL-11R) was not sufficient to enable ADAM17-mediated proteolysis, but transfer of different parts of the IL-6R stalk enabled shedding by ADAM17. These findings shed light on the cleavage site specificities of ADAM17 using a native substrate and reveal further differences in the proteolysis of IL-6R and IL-11R.
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http://dx.doi.org/10.1016/j.biocel.2017.01.014 | DOI Listing |
RNA Biol
December 2025
Department of Cell and Molecular Biology, Biomedical Centre, Uppsala University, Uppsala, Sweden.
We show that a small biotin-binding RNA aptamer that folds into a pseudoknot structure acts as a substrate for bacterial RNase P RNA (RPR) with and without the RNase P C5 protein. Cleavage in the single-stranded region in loop 1 was shown to depend on the presence of a RCCA-motif at the 3' end of the substrate. The nucleobase and the 2'hydroxyl at the position immediately 5' of the cleavage site contribute to both cleavage efficiency and site selection, where C at this position induces significant cleavage at an alternative site, one base upstream of the main cleavage site.
View Article and Find Full Text PDFNucleic Acids Res
January 2025
Key Laboratory of Applied Surface and Colloid Chemistry, Ministry of Education, Key Laboratory of Analytical Chemistry for Life Science of Shaanxi Province, School of Chemistry & Chemical Engineering, Shaanxi Normal University, 620 West Chang'an Avenue, Chang'an District, Xi'an, Shaanxi 710119, P.R. China.
We present a robust 'splice-at-will' CRISPR RNA (crRNA) engineering mechanism that overcomes the limitations of clustered regularly interspaced short palindromic repeats (CRISPR)/Cas system in directly detecting ultrashort RNAs. In this strategy, an intact Cas12a crRNA can be split from almost any site of the spacer region to obtain a truncated crRNA (tcrRNA) that cannot activate Cas12a even after binding an auxiliary DNA activator. While splicing tcrRNAs with a moiety of ultrashort RNA, the formed combination can work together to activate Cas12a efficiently, enabling 'splice-at-will' crRNA engineering.
View Article and Find Full Text PDFProteolysis targeting chimeras (PROTACs) are pivotal in cancer therapy for their ability to degrade specific proteins. However, their non-specificity can lead to systemic toxicity due to protein degradation in normal cells. To address this, we have integrated a nanobody into the PROTACs framework and leveraged the tumor microenvironment to enhance drug specificity.
View Article and Find Full Text PDFThe ongoing panzootic of highly pathogenic avian influenza (HPAI) A(H5) viruses is the largest in history, with unprecedented transmission to multiple mammalian species. Avian influenza A viruses of the H5 subtype circulate globally among birds and are classified into distinct clades based on their hemagglutinin (HA) genetic sequences. Thus, the ability to accurately and rapidly assign clades to newly sequenced isolates is key to surveillance and outbreak response.
View Article and Find Full Text PDFCRISPR-Cas enzymes must recognize a protospacer-adjacent motif (PAM) to edit a genomic site, significantly limiting the range of targetable sequences in a genome. Machine learning-based protein engineering provides a powerful solution to efficiently generate Cas protein variants tailored to recognize specific PAMs. Here, we present Protein2PAM, an evolution-informed deep learning model trained on a dataset of over 45,000 CRISPR-Cas PAMs.
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