TSignal: a transformer model for signal peptide prediction

Improving Signal and Transit Peptide Predictions Using AlphaFold2-predicted Protein Structures

Many proteins contain cleavable signal or transit peptides that direct them to their final subcellular locations. Such peptides are usually predicted from sequence alone using methods such as TargetP 2.0 and SignalP 6.0. While these methods are usually very accurate, we show here that an analysis of a protein's AlphaFold2-predicted structure can often be used to identify false positive predictions. We start by showing that when given a protein's full-length sequence, AlphaFold2 builds experimentally annotated signal and transit peptides in orientations that point away from the main body of the protein. This indicates that AlphaFold2 correctly identifies that a signal is not destined to be part of the mature protein's structure and suggests, as a corollary, that predicted signals that AlphaFold2 folds with high confidence into the main body of the protein are likely to be false positives. To explore this idea, we analyzed predicted signal peptides in 48 proteomes made available in DeepMind's AlphaFold2 database (https://alphafold.ebi.ac.uk). Applying TargetP 2.0 and SignalP 6.0 to the 561,562 proteins in the database results in 95,236 being predicted to contain a cleavable signal or transit peptide. In 95.1% of these cases, the AlphaFold2 structure of the full-length protein is fully consistent with the prediction of TargetP 2.0 or SignalP 6.0. In the remaining 4.9% of cases where the AlphaFold2 structure does not appear consistent with the prediction, the signal is often only predicted with low confidence. The potential false positives identified here may be useful for training even more accurate signal prediction methods.

SignalP: The Evolution of a Web Server

SignalP ( https://services.healthtech.dtu.dk/services/SignalP-6.0/ ) is a very popular prediction method for signal peptides, the intrinsic signals that make proteins secretory. The SignalP web server has existed since 1995 and is now in its sixth major version. In this historical account, we (three authors who have taken part in the entire journey plus the first author of the latest version) describe the differences between the versions and discuss the various decisions taken along the way.

Functional Characterization of Eight Zinc Finger Motif-Containing Proteins in Toxoplasma gondii Type I RH Strain Using the CRISPR-Cas9 System

The Zinc finger protein (ZFP) family is widely distributed in eukaryotes and interacts with DNA, RNA, and various proteins to participate in many molecular processes. In the present study, the biological functions of eight ZFP genes in the lytic cycle and the pathogenicity of Toxoplasma gondii were examined using the CRISPR-Cas9 system. Immunofluorescence showed that four ZFPs (RH248270-HA, RH255310-HA, RH309200-HA, and RH236640-HA) were localized in the cytoplasm, and one ZFP (RH273150-HA) was located in the nucleus, while the expression level of RH285190-HA, RH260870-HA, and RH248450-HA was undetectable. No significant differences were detected between seven RHΔzfp strains (RHΔ285190, RHΔ248270, RHΔ260870, RHΔ255310, RHΔ309200, RHΔ248450, and RHΔ236640) and the wild-type (WT) strain in the T. gondii lytic cycle, including plaque formation, invasion, intracellular replication, and egress, as well as in vitro virulence (p > 0.05). However, the RHΔ273150 strain exhibited significantly lower replication efficiency compared to the other seven RHΔzfp strains and the WT strain, while in vivo virulence in mice was not significantly affected. Comparative expression analysis of the eight zfp genes indicates that certain genes may have essential functions in the sexual reproductive stage of T. gondii. Taken together, these findings expand our current understanding of the roles of ZFPs in T. gondii.