Recognition of the ligand-type specificity of classical and non-classical MHC I proteins

Prediction of unconventional protein secretion by exosomes

MOTIVATION

In eukaryotes, proteins targeted for secretion contain a signal peptide, which allows them to proceed through the conventional ER/Golgi-dependent pathway. However, an important number of proteins lacking a signal peptide can be secreted through unconventional routes, including that mediated by exosomes. Currently, no method is available to predict protein secretion via exosomes.

RESULTS

Here, we first assembled a dataset including the sequences of 2992 proteins secreted by exosomes and 2961 proteins that are not secreted by exosomes. Subsequently, we trained different random forests models on feature vectors derived from the sequences in this dataset. In tenfold cross-validation, the best model was trained on dipeptide composition, reaching an accuracy of 69.88% ± 2.08 and an area under the curve (AUC) of 0.76 ± 0.03. In an independent dataset, this model reached an accuracy of 75.73% and an AUC of 0.840. After these results, we developed ExoPred, a web-based tool that uses random forests to predict protein secretion by exosomes.

CONCLUSION

ExoPred is available for free public use at http://imath.med.ucm.es/exopred/ . Datasets are available at http://imath.med.ucm.es/exopred/datasets/ .

Detecting virus-specific effects on post-infection temporal gene expression

Background

Different types of viruses have different envelope proteins, and may have their shared or distinctive host-virus interactions which result in various post-infection effects in humans and animals. These effects often do not appear at once but take time to unfold. To characterize the virus-specific effects, we applied a Multivariate Polynomial Time-dependent Genetic Association (MPTGA) method, previously proposed for detecting differences in temporal gene expression traits, to test for the differences in mouse lung transcriptome response to infection of different subtypes of influenza A viruses.

Results

We compared two methods: the Multivariate Polynomial Time-dependent Genetic Association (MPTGA) method, and the conventional modified t-test, to study the virus-specific effects on mouse lung gene expression. Both methods found H3N2 to be the most different virus among the three viruses tested, with the largest number of genes with H3N2-specific effects. However, the MPTGA method demonstrated much higher power of detection, and the detected genes with virus-specific effects showed better biological relevance.

Conclusions

Transcriptome response to virus infection is dynamic. MPTGA which leverages temporal gene expression traits showed increased power in detecting biologically relevant virus-specific effects comparing with conventional t-test method.

Restricting nonclassical MHC genes coevolve with TRAV genes used by innate-like T cells in mammals

Whereas major histocompatibility class-1 (MH1) proteins present peptides to T cells displaying a large T-cell receptor (TR) repertoire, MH1Like proteins, such as CD1D and MR1, present glycolipids and microbial riboflavin precursor derivatives, respectively, to T cells expressing invariant TR-α (iTRA) chains. The groove of such MH1Like, as well as iTRA chains used by mucosal-associated invariant T (MAIT) and natural killer T (NKT) cells, respectively, may result from a coevolution under particular selection pressures. Herein, we investigated the evolutionary patterns of the iTRA of MAIT and NKT cells and restricting MH1Like proteins: MR1 appeared 170 Mya and is highly conserved across mammals, evolving more slowly than other MH1Like. It has been pseudogenized or independently lost three times in carnivores, the armadillo, and lagomorphs. The corresponding TRAV1 gene also evolved slowly and harbors highly conserved complementarity determining regions 1 and 2. TRAV1 is absent exclusively from species in which MR1 is lacking, suggesting that its loss released the purifying selection on MR1. In the rabbit, which has very few NKT and no MAIT cells, a previously unrecognized iTRA was identified by sequencing leukocyte RNA. This iTRA uses TRAV41, which is highly conserved across several groups of mammals. A rabbit MH1Like gene was found that appeared with mammals and is highly conserved. It was independently lost in a few groups in which MR1 is present, like primates and Muridae, illustrating compensatory emergences of new MH1Like/Invariant T-cell combinations during evolution. Deciphering their role is warranted to search similar effector functions in humans.

Model for vaccine design by prediction of B-epitopes of IEDB given perturbations in peptide sequence, in vivo process, experimental techniques, and source or host organisms

Perturbation methods add variation terms to a known experimental solution of one problem to approach a solution for a related problem without known exact solution. One problem of this type in immunology is the prediction of the possible action of epitope of one peptide after a perturbation or variation in the structure of a known peptide and/or other boundary conditions (host organism, biological process, and experimental assay). However, to the best of our knowledge, there are no reports of general-purpose perturbation models to solve this problem. In a recent work, we introduced a new quantitative structure-property relationship theory for the study of perturbations in complex biomolecular systems. In this work, we developed the first model able to classify more than 200,000 cases of perturbations with accuracy, sensitivity, and specificity >90% both in training and validation series. The perturbations include structural changes in >50000 peptides determined in experimental assays with boundary conditions involving >500 source organisms, >50 host organisms, >10 biological process, and >30 experimental techniques. The model may be useful for the prediction of new epitopes or the optimization of known peptides towards computational vaccine design.