Perfecting prediction of mutational impact on the aggregation propensity of the <scp>ALS</scp>‐associated hn<scp>RNPA</scp>2 prion‐like protein

Batlle, Cristina; Fernández, María Rosario Salinas; Iglesias, Valentín; Ventura, Salvador

doi:10.1002/1873-3468.12698

Cited by 8 publications

(9 citation statements)

References 16 publications

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“…They can be single or multiple residues substitutions, as well as deletions and insertions. It exploits the highly significant correlation between the scores obtained from a parameterized linear function, that balances the contribution of both PrLDs composition and amyloid propensity [13], and the intracellular aggregation of hnRNPA2 variants; the unique prion-like protein for which a large set of mutations, both natural and artificial have been experimentally validated (Fig. 1a).…”

Section: Methodsmentioning

confidence: 99%

“…1Correlation between AMYCO and pRANK predictions and the aggregation propensity of human hnRNPA2 prion-like protein variants. a Graphic representation of the correlation between the mutants' AMYCO ( a ) and pRANK ( b ) scores and their ability to form prionic colonies (Ade+) when expressed in yeast, a direct reporter of their aggregation propensity [13]…”

Section: Methodsmentioning

confidence: 99%

“…Disease-linked mutations would enhance the self-association of these domains, facilitating the transition to amyloid-like states [11, 12]. We have recently shown that the impact of point and multiple mutations or deletions on the aggregation of the model ALS-associated prion-like hnRNPA2 protein is best predicted by a function that takes into account both compositional features and amyloidogenic propensities [13]. Here we introduce the AMYCO (combined AMYloid and Composition based prediction of prion-like aggregation propensity) web server, which implements this approach to perform automated and fast predictions on top of prion-like protein sequences.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

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

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

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“…An increasingly recognized process being implicated in several neurodegenerative diseases is the formation of membraneless liquid droplet-like organelles by the proteins containing prion-like domains through a process called liquid-liquid phase separation (LLPS) (Figure 5) (Shin and Brangwynne, 2017). Several RNA binding proteins like TDP-43, FUS, hnRNPA1 and hnRNPA2/B1 etc., contain intrinsically disordered regions and can undergo phase separation through transient intermolecular interactions (Burke et al, 2015; Lin et al, 2015; Molliex et al, 2015; Patel et al, 2015; Conicella et al, 2016; Batlle et al, 2017; Gopal et al, 2017; Li et al, 2017; Sun and Chakrabartty, 2017; Uversky, 2017). Proteins with a prion-like low complexity domain (LCD), exhibit in this region, an over-representation of polar and charged amino acids including arginine, lysine, glutamine, serine, glutamic acid and occasionally glycine, alanine and proline with interspersed aromatic residues, particularly tyrosine and phenylalanine (Shin and Brangwynne, 2017).…”

Section: Aggregation Of Tdp-43mentioning

confidence: 99%

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

Prasad

Bharathi

Sivalingam

et al. 2019

Front. Mol. Neurosci.

576

573

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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.

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“…A subsequent reanalysis of our data set showed that PrionW is also reasonably effective at predicting prion activity in yeast for our mutants, and that combining PrionW and PAPA may further improve prediction accuracy. 15 PrionW differs from PAPA in that it combines amino acid composition analysis with a position-specific matrix to identify predicted amyloid-prone segments. 16 Other algorithms show varying degrees of predictive success.…”

Section: Rationally Manipulating the Aggregation Activity Of A Human mentioning

confidence: 99%

Manipulating the aggregation activity of human prion-like proteins

Cascarina

Paul

Ross

2017

Prion

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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.

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

Cited by 8 publications

References 16 publications

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

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

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

Manipulating the aggregation activity of human prion-like proteins

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