Integrating knowledge of protein sequence with protein function for the prediction and validation of new MALT1 substrates

by Selleckchem | Sep 07 2023

We developed a bioinformatics-led substrate discovery workflow to expand the known substrate repertoire of MALT1. Our approach, termed GO-2-Substrates, integrates protein function information, including GO terms from known substrates, with protein sequences to rank substrate candidates by similarity. We applied GO-2-Substrates to MALT1, a paracaspase and master regulator of NF-κB signalling in adaptive immune responses. With only 12 known substrates, the evolutionarily conserved paracaspase functions and phenotypes of Malt1 -/- mice strongly implicate the existence of undiscovered substrates. We tested the ranked predictions from GO-2-Substrates of new MALT1 human substrates by co-expression of candidates transfected with the oncogenic constitutively active cIAP2-MALT1 fusion protein or CARD11/BCL10/MALT1 active signalosome. We identified seven new MALT1 substrates by the co-transfection screen: TANK, TAB3, CASP10, ZC3H12D, ZC3H12B, CILK1 and ILDR2. Using catalytically inactive cIAP2-MALT1 (Cys464Ala), a MALT1 inhibitor, MLT-748, and noncleavable P1-Arg to Ala mutant versions of each substrate in dual transfections, we validated the seven new substrates in vitro. We confirmed the cleavage of endogenous TANK and the RNase ZC3H12D in B cells by Western blotting and mining TAILS N-terminomics datasets, where we also uncovered evidence for these and 12 other candidate substrates by endogenous MALT1. Thus, protein function information improves substrate predictions. The new substrates and other high-ranked MALT1 candidate substrates should open new biological frontiers for further validation and exploration of the function of MALT1 within and beyond NF-κB regulation.

Comments:

That's a fascinating research study! It seems that you have developed a bioinformatics-based workflow called GO-2-Substrates to identify new substrates for the protein MALT1. MALT1 is a paracaspase involved in regulating the NF-κB signaling pathway in adaptive immune responses.

With only 12 known substrates for MALT1, there was a strong indication that there are undiscovered substrates awaiting identification. By utilizing protein function information, particularly Gene Ontology (GO) terms associated with known substrates, and integrating it with protein sequences, you employed a similarity-based ranking approach to predict potential substrate candidates for MALT1.

To validate the predictions made by GO-2-Substrates, you conducted co-expression experiments using candidates transfected with either the oncogenic constitutively active cIAP2-MALT1 fusion protein or the CARD11/BCL10/MALT1 active signalosome. Through this screening process, you successfully identified seven new MALT1 substrates: TANK, TAB3, CASP10, ZC3H12D, ZC3H12B, CILK1, and ILDR2.

To further confirm these findings, you performed in vitro experiments using catalytically inactive cIAP2-MALT1, a MALT1 inhibitor called MLT-748, and noncleavable mutant versions of each substrate. These experiments validated the seven newly identified substrates.

Additionally, you verified the cleavage of endogenous TANK and the RNase ZC3H12D in B cells through Western blotting and analyzed TAILS N-terminomics datasets, which provided evidence for the cleavage of these proteins by endogenous MALT1. Moreover, the N-terminomics analysis uncovered evidence for these and 12 other candidate substrates.

Overall, your study demonstrates that incorporating protein function information, such as GO terms, enhances the prediction of substrates for MALT1. The discovery of these new substrates, along with other highly ranked candidate substrates, offers exciting prospects for exploring and validating the functional role of MALT1 within the context of NF-κB regulation and beyond. It opens up new avenues for further investigation in understanding the biological functions of MALT1.