Aggregation is a Context-Dependent Constraint on Protein Evolution

High-throughput Selection of Human de novo-emerged sORFs with High Folding Potential

De novo genes emerge from previously noncoding stretches of the genome. Their encoded de novo proteins are generally expected to be similar to random sequences and, accordingly, with no stable tertiary fold and high predicted disorder. However, structural properties of de novo proteins and whether they differ during the stages of emergence and fixation have not been studied in depth and rely heavily on predictions. Here we generated a library of short human putative de novo proteins of varying lengths and ages and sorted the candidates according to their structural compactness and disorder propensity. Using Förster resonance energy transfer combined with Fluorescence-activated cell sorting, we were able to screen the library for most compact protein structures, as well as most elongated and flexible structures. We find that compact de novo proteins are on average slightly shorter and contain lower predicted disorder than less compact ones. The predicted structures for most and least compact de novo proteins correspond to expectations in that they contain more secondary structure content or higher disorder content, respectively. Our experiments indicate that older de novo proteins have higher compactness and structural propensity compared with young ones. We discuss possible evolutionary scenarios and their implications underlying the age-dependencies of compactness and structural content of putative de novo proteins.

RNA sequestration driven by amyloid formation: the alpha synuclein case

Nucleic acids can act as potent modulators of protein aggregation, and RNA has the ability to either hinder or facilitate protein assembly, depending on the molecular context. In this study, we utilized a computational approach to characterize the physico-chemical properties of regions involved in amyloid aggregation. In various experimental datasets, we observed that while the core is hydrophobic and highly ordered, external regions, which are more disordered, display a distinct tendency to interact with nucleic acids. To validate our predictions, we performed aggregation assays with alpha-synuclein (aS140), a non-nucleic acid-binding amyloidogenic protein, and a mutant truncated at the acidic C-terminus (aS103), which is predicted to have a higher tendency to interact with RNA. For both aS140 and aS103, we observed an acceleration of aggregation upon RNA addition, with a significantly stronger effect for aS103. Due to favorable electrostatics, we noted an enhanced nucleic acid sequestration ability for the aggregated aS103, allowing it to entrap a larger amount of RNA compared to the aggregated wild-type counterpart. Overall, our research suggests that RNA sequestration might be a common phenomenon linked to protein aggregation, constituting a gain-of-function mechanism that warrants further investigation.

Transmembrane Helices 7 and 8 Confer Aggregation Sensitivity to the Cystic Fibrosis Transmembrane Conductance Regulator

The Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) is a large multi-spanning membrane protein that is susceptible to misfolding and aggregation. We have identified here the region responsible for this instability. Temperature-induced aggregation of C-terminally truncated versions of CFTR demonstrated that all truncations up to the second transmembrane domain (TMD2), including the R region, largely resisted aggregation. Limited proteolysis identified a folded structure that was prone to aggregation and consisted of TMD2 and at least part of the Regulatory Region R. Only when both TM7 (TransMembrane helix 7) and TM8 were present, TMD2 fragments became as aggregation-sensitive as wild-type CFTR, in line with increased thermo-instability of late CFTR nascent chains and in silico prediction of aggregation propensity. In accord, isolated TMD2 was degraded faster in cells than isolated TMD1. We conclude that TMD2 extended at its N-terminus with part of the R region forms a protease-resistant structure that induces heat instability in CFTR and may be responsible for its limited intracellular stability.

Shapeshifter TDP-43: Molecular mechanism of structural polymorphism, aggregation, phase separation and their modulators

TDP-43 is a nucleic acid-binding protein that performs physiologically essential functions and is known to undergo phase separation and aggregation during stress. Initial observations have shown that TDP-43 forms heterogeneous assemblies, including monomer, dimer, oligomers, aggregates, phase-separated assemblies, etc. However, the significance of each assembly of TDP-43 concerning its function, phase separation, and aggregation is poorly known. Furthermore, how different assemblies of TDP-43 are related to each other is unclear. In this review, we focus on the various assemblies of TDP-43 and discuss the plausible origin of the structural heterogeneity of TDP-43. TDP-43 is involved in multiple physiological processes like phase separation, aggregation, prion-like seeding, and performing physiological functions. However, the molecular mechanism behind the physiological process performed by TDP-43 is not well understood. The current review discusses the plausible molecular mechanism of phase separation, aggregation, and prion-like propagation of TDP-43.

Assessing structure and disorder prediction tools for de novo emerged proteins in the age of machine learning

Background: De novo protein coding genes emerge from scratch in the non-coding regions of the genome and have, per definition, no homology to other genes. Therefore, their encoded de novo proteins belong to the so-called "dark protein space". So far, only four de novo protein structures have been experimentally approximated. Low homology, presumed high disorder and limited structures result in low confidence structural predictions for de novo proteins in most cases. Here, we look at the most widely used structure and disorder predictors and assess their applicability for de novo emerged proteins. Since AlphaFold2 is based on the generation of multiple sequence alignments and was trained on solved structures of largely conserved and globular proteins, its performance on de novo proteins remains unknown. More recently, natural language models of proteins have been used for alignment-free structure predictions, potentially making them more suitable for de novo proteins than AlphaFold2. Methods: We applied different disorder predictors (IUPred3 short/long, flDPnn) and structure predictors, AlphaFold2 on the one hand and language-based models (Omegafold, ESMfold, RGN2) on the other hand, to four de novo proteins with experimental evidence on structure. We compared the resulting predictions between the different predictors as well as to the existing experimental evidence. Results: Results from IUPred, the most widely used disorder predictor, depend heavily on the choice of parameters and differ significantly from flDPnn which has been found to outperform most other predictors in a comparative assessment study recently. Similarly, different structure predictors yielded varying results and confidence scores for de novo proteins. Conclusions: We suggest that, while in some cases protein language model based approaches might be more accurate than AlphaFold2, the structure prediction of de novo emerged proteins remains a difficult task for any predictor, be it disorder or structure.

ALS/FTD: Evolution, Aging, and Cellular Metabolic Exhaustion

Amyotrophic lateral sclerosis and frontotemporal dementia (ALS/FTD) are neurodegenerations with evolutionary underpinnings, expansive clinical presentations, and multiple genetic risk factors involving a complex network of pathways. This perspective considers the complex cellular pathology of aging motoneuronal and frontal/prefrontal cortical networks in the context of evolutionary, clinical, and biochemical features of the disease. We emphasize the importance of evolution in the development of the higher cortical function, within the influence of increasing lifespan. Particularly, the role of aging on the metabolic competence of delicately optimized neurons, age-related increased proteostatic costs, and specific genetic risk factors that gradually reduce the energy available for neuronal function leading to neuronal failure and disease.

The Interplay Between Disordered Regions in RNAs and Proteins Modulates Interactions Within Stress Granules and Processing Bodies

Condensation, or liquid-like phase separation, is a phenomenon indispensable for the spatiotemporal regulation of molecules within the cell. Recent studies indicate that the composition and molecular organization of phase-separated organelles such as Stress Granules (SGs) and Processing Bodies (PBs) are highly variable and dynamic. A dense contact network involving both RNAs and proteins controls the formation of SGs and PBs and an intricate molecular architecture, at present poorly understood, guarantees that these assemblies sense and adapt to different stresses and environmental changes. Here, we investigated the physico-chemical properties of SGs and PBs components and studied the architecture of their interaction networks. We found that proteins and RNAs establishing the largest amount of contacts in SGs and PBs have distinct properties and intrinsic disorder is enriched in all protein-RNA, protein-protein and RNA-RNA interaction networks. The increase of disorder in proteins is accompanied by an enrichment in single-stranded regions of RNA binding partners. Our results suggest that SGs and PBs quickly assemble and disassemble through dynamic contacts modulated by unfolded domains of their components.