Perfecting prediction of mutational impact on the aggregation propensity of the ALS-associated hnRNPA2 prion-like protein

SGnn: A Web Server for the Prediction of Prion-Like Domains Recruitment to Stress Granules Upon Heat Stress

Proteins bearing prion-like domains (PrLDs) are essential players in stress granules (SG) assembly. Analysis of data on heat stress-induced recruitment of yeast PrLDs to SG suggests that this propensity might be connected with three defined protein biophysical features: aggregation propensity, net charge, and the presence of free cysteines. These three properties can be read directly in the PrLDs sequences, and their combination allows to predict protein recruitment to SG under heat stress. On this basis, we implemented SGnn, an online predictor of SG recruitment that exploits a feed-forward neural network for high accuracy classification of the assembly behavior of PrLDs. The simplicity and precision of our strategy should allow its implementation to identify heat stress-induced SG-forming proteins in complete proteomes.

Prion-like proteins: from computational approaches to proteome-wide analysis

Prions are self-perpetuating proteins able to switch between a soluble state and an aggregated-and-transmissible conformation. These proteinaceous entities have been widely studied in yeast, where they are involved in hereditable phenotypic adaptations. The notion that such proteins could play functional roles and be positively selected by evolution has triggered the development of computational tools to identify prion-like proteins in different kingdoms of life. These algorithms have succeeded in screening multiple proteomes, allowing the identification of prion-like proteins in a diversity of unrelated organisms, evidencing that the prion phenomenon is well conserved among species. Interestingly enough, prion-like proteins are not only connected with the formation of functional membraneless protein-nucleic acid coacervates, but are also linked to human diseases. This review addresses state-of-the-art computational approaches to identify prion-like proteins, describes proteome-wide analysis efforts, discusses these unique proteins' functional role, and illustrates recently validated examples in different domains of life.

From Prions to Stress Granules: Defining the Compositional Features of Prion-Like Domains That Promote Different Types of Assemblies

Stress granules are ribonucleoprotein assemblies that form in response to cellular stress. Many of the RNA-binding proteins found in stress granule proteomes contain prion-like domains (PrLDs), which are low-complexity sequences that compositionally resemble yeast prion domains. Mutations in some of these PrLDs have been implicated in neurodegenerative diseases, including amyotrophic lateral sclerosis and frontotemporal dementia, and are associated with persistent stress granule accumulation. While both stress granules and prions are macromolecular assemblies, they differ in both their physical properties and complexity. Prion aggregates are highly stable homopolymeric solids, while stress granules are complex dynamic biomolecular condensates driven by multivalent homotypic and heterotypic interactions. Here, we use stress granules and yeast prions as a paradigm to examine how distinct sequence and compositional features of PrLDs contribute to different types of PrLD-containing assemblies.

In silico Characterization of Human Prion-Like Proteins: Beyond Neurological Diseases

Prion-like behavior has been in the spotlight since it was first associated with the onset of mammalian neurodegenerative diseases. However, a growing body of evidence suggests that this mechanism could be behind the regulation of processes such as transcription and translation in multiple species. Here, we perform a stringent computational survey to identify prion-like proteins in the human proteome. We detected 242 candidate polypeptides and computationally assessed their function, protein–protein interaction networks, tissular expression, and their link to disease. Human prion-like proteins constitute a subset of modular polypeptides broadly expressed across different cell types and tissues, significantly associated with disease, embedded in highly connected interaction networks, and involved in the flow of genetic information in the cell. Our analysis suggests that these proteins might play a relevant role not only in neurological disorders, but also in different types of cancer and viral infections.

Molecular Mechanisms of TDP-43 Misfolding and Pathology in Amyotrophic Lateral Sclerosis

TAR DNA binding protein 43 (TDP-43) is a versatile RNA/DNA binding protein involved in RNA-related metabolism. Hyper-phosphorylated and ubiquitinated TDP-43 deposits act as inclusion bodies in the brain and spinal cord of patients with the motor neuron diseases: amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD). While the majority of ALS cases (90-95%) are sporadic (sALS), among familial ALS cases 5-10% involve the inheritance of mutations in the TARDBP gene and the remaining (90-95%) are due to mutations in other genes such as: C9ORF72, SOD1, FUS, and NEK1 etc. Strikingly however, the majority of sporadic ALS patients (up to 97%) also contain the TDP-43 protein deposited in the neuronal inclusions, which suggests of its pivotal role in the ALS pathology. Thus, unraveling the molecular mechanisms of the TDP-43 pathology seems central to the ALS therapeutics, hence, we comprehensively review the current understanding of the TDP-43's pathology in ALS. We discuss the roles of TDP-43's mutations, its cytoplasmic mis-localization and aberrant post-translational modifications in ALS. Also, we evaluate TDP-43's amyloid-like in vitro aggregation, its physiological vs. pathological oligomerization in vivo, liquid-liquid phase separation (LLPS), and potential prion-like propagation propensity of the TDP-43 inclusions. Finally, we describe the various evolving TDP-43-induced toxicity mechanisms, such as the impairment of endocytosis and mitotoxicity etc. and also discuss the emerging strategies toward TDP-43 disaggregation and ALS therapeutics.

AMYCO: evaluation of mutational impact on prion-like proteins aggregation propensity

Background

Around 1% of human proteins are predicted to contain a disordered and low complexity prion-like domain (PrLD). Mutations in PrLDs have been shown promote a transition towards an aggregation-prone state in several diseases.

Results

Recently, we have shown that an algorithm that considers the effects of mutations on PrLDs composition, as well as on localized amyloid propensity can predict the impact of these amino acid changes on protein intracellular aggregation. In this application note, we implement this concept into the AMYCO web server, a refined algorithm that forecasts the influence of amino acid changes in prion-like proteins aggregation propensity better than state-of-the-art predictors.

Conclusions

The AMYCO web server allows for a fast and automated evaluation of the effect of mutations on the aggregation properties of prion-like proteins. This might uncover novel disease-linked amino acid changes in the sequences of human prion-like proteins. Additionally, it can find application in the in silico design of synthetic prion-like proteins with tuned aggregation propensities for different purposes. AMYCO does not require previous registration and is freely available to all users at: http://bioinf.uab.cat/amyco/.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2601-3) contains supplementary material, which is available to authorized users.

Manipulating the aggregation activity of human prion-like proteins

Considerable advances in understanding the protein features favoring prion formation in yeast have facilitated the development of effective yeast prion prediction algorithms. Here we discuss a recent study in which we systematically explored the utility of the yeast prion prediction algorithm PAPA for designing mutations to modulate the aggregation activity of the human prion-like protein hnRNPA2B1. Mutations in hnRNPA2B1 cause multisystem proteinopathy in humans, and accelerate aggregation of the protein in vitro. Additionally, mutant hnRNPA2B1 forms cytoplasmic inclusions when expressed in Drosophila, and the mutant prion-like domain can substitute for a portion of a yeast prion domain in supporting prion activity in yeast. PAPA was quite successful at predicting the effects of PrLD mutations on prion activity in yeast and on in vitro aggregation propensity. Additionally, PAPA successfully predicted the effects of most, but not all, mutations in the PrLD of the hnRNPA2B1 protein when expressed in Drosophila. These results suggest that PAPA is quite effective at predicting the effects of mutations on intrinsic aggregation propensity, but that intracellular factors can influence aggregation and prion-like activity in vivo. A more complete understanding of these intracellular factors may inform the next generation of prion prediction algorithms.