N-glycosylation as a eukaryotic protective mechanism against protein aggregation.

The tendency for proteins to form aggregates is an inherent part of every proteome and arises from the self-assembly of short protein segments called aggregation-prone regions (APRs). While posttranslational modifications (PTMs) have been implicated in modulating protein aggregation, their direct role in APRs remains poorly understood. In this study, we used a combination of proteome-wide computational analyses and biophysical techniques to investigate the potential involvement of PTMs in aggregation regulation. Our findings reveal that while most PTM types are disfavored near APRs, N-glycosylation is enriched and evolutionarily selected, especially in proteins prone to misfolding. Experimentally, we show that N-glycosylation inhibits the aggregation of peptides in vitro through steric hindrance. Moreover, mining existing proteomics data, we find that the loss of N-glycans at the flanks of APRs leads to specific protein aggregation in Neuro2a cells. Our findings indicate that, among its many molecular functions, N-glycosylation directly prevents protein aggregation in higher eukaryotes.

Exploiting the aggregation propensity of beta-lactamases to design inhibitors that induce enzyme misfolding.

There is an arms race between beta-lactam antibiotics development and co-evolving beta-lactamases, which provide resistance by breaking down beta-lactam rings. We have observed that certain beta-lactamases tend to aggregate, which persists throughout their evolution under the selective pressure of antibiotics on their active sites. Interestingly, we find that existing beta-lactamase active site inhibitors can act as molecular chaperones, promoting the proper folding of these resistance factors. Therefore, we have created Pept-Ins, synthetic peptides designed to exploit the structural weaknesses of beta-lactamases by causing them to misfold into intracellular inclusion bodies. This approach restores sensitivity to a wide range of beta-lactam antibiotics in resistant clinical isolates, including those with Extended Spectrum variants that pose significant challenges in medical practice. Our findings suggest that targeted aggregation of resistance factors could offer a strategy for identifying molecules that aid in addressing the global antibiotic resistance crisis.

SNPeffect 5.0: large-scale structural phenotyping of protein coding variants extracted from next-generation sequencing data using AlphaFold models.

BACKGROUND: Next-generation sequencing technologies yield large numbers of genetic alterations, of which a subset are missense variants that alter an amino acid in the protein product. These variants can have a potentially destabilizing effect leading to an increased risk of misfolding and aggregation. Multiple software tools exist to predict the effect of single-nucleotide variants on proteins, however, a pipeline integrating these tools while starting from an NGS data output list of variants is lacking. RESULTS: The previous version SNPeffect 4.0 (De Baets in Nucleic Acids Res 40(D1):D935-D939, 2011) provided an online database containing pre-calculated variant effects and low-throughput custom variant analysis. Here, we built an automated and parallelized pipeline that analyzes the impact of missense variants on the aggregation propensity and structural stability of proteins starting from the Variant Call Format as input. The pipeline incorporates the AlphaFold Protein Structure Database to achieve high coverage for structural stability analyses using the FoldX force field. The effect on aggregation-propensity is analyzed using the established predictors TANGO and WALTZ. The pipeline focuses solely on the human proteome and can be used to analyze proteome stability/damage in a given sample based on sequencing results. CONCLUSION: We provide a bioinformatics pipeline that allows structural phenotyping from sequencing data using established stability and aggregation predictors including FoldX, TANGO, and WALTZ; and structural proteome coverage provided by the AlphaFold database. The pipeline and installation guide are freely available for academic users on https://github.com/vibbits/snpeffect and requires a computer cluster.

Exploiting the intrinsic misfolding propensity of the KRAS oncoprotein.

Mutant KRAS is a major driver of oncogenesis in a multitude of cancers but remains a challenging target for classical small molecule drugs, motivating the exploration of alternative approaches. Here, we show that aggregation-prone regions (APRs) in the primary sequence of the oncoprotein constitute intrinsic vulnerabilities that can be exploited to misfold KRAS into protein aggregates. Conveniently, this propensity that is present in wild-type KRAS is increased in the common oncogenic mutations at positions 12 and 13. We show that synthetic peptides (Pept-ins™) derived from two distinct KRAS APRs could induce the misfolding and subsequent loss of function of oncogenic KRAS, both of recombinantly produced protein in solution, during cell-free translation and in cancer cells. The Pept-ins exerted antiproliferative activity against a range of mutant KRAS cell lines and abrogated tumor growth in a syngeneic lung adenocarcinoma mouse model driven by mutant KRAS G12V. These findings provide proof-of-concept that the intrinsic misfolding propensity of the KRAS oncoprotein can be exploited to cause its functional inactivation.

De novo missense variants in the E3 ubiquitin ligase adaptor KLHL20 cause a developmental disorder with intellectual disability, epilepsy, and autism spectrum disorder.

PURPOSE: KLHL20 is part of a CUL3-RING E3 ubiquitin ligase involved in protein ubiquitination. KLHL20 functions as the substrate adaptor that recognizes substrates and mediates the transfer of ubiquitin to the substrates. Although KLHL20 regulates neurite outgrowth and synaptic development in animal models, a role in human neurodevelopment has not yet been described. We report on a neurodevelopmental disorder caused by de novo missense variants in KLHL20. METHODS: Patients were ascertained by the investigators through Matchmaker Exchange. Phenotyping of patients with de novo missense variants in KLHL20 was performed. RESULTS: We studied 14 patients with de novo missense variants in KLHL20, delineating a genetic syndrome with patients having mild to severe intellectual disability, febrile seizures or epilepsy, autism spectrum disorder, hyperactivity, and subtle dysmorphic facial features. We observed a recurrent de novo missense variant in 11 patients (NM_014458.4:c.1069G>A p.[Gly357Arg]). The recurrent missense and the 3 other missense variants all clustered in the Kelch-type ß-propeller domain of the KLHL20 protein, which shapes the substrate binding surface. CONCLUSION: Our findings implicate KLHL20 in a neurodevelopmental disorder characterized by intellectual disability, febrile seizures or epilepsy, autism spectrum disorder, and hyperactivity.

PyUUL provides an interface between biological structures and deep learning algorithms.

Structural bioinformatics suffers from the lack of interfaces connecting biological structures and machine learning methods, making the application of modern neural network architectures impractical. This negatively affects the development of structure-based bioinformatics methods, causing a bottleneck in biological research. Here we present PyUUL ( https://pyuul.readthedocs.io/ ), a library to translate biological structures into 3D tensors, allowing an out-of-the-box application of state-of-the-art deep learning algorithms. The library converts biological macromolecules to data structures typical of computer vision, such as voxels and point clouds, for which extensive machine learning research has been performed. Moreover, PyUUL allows an out-of-the box GPU and sparse calculation. Finally, we demonstrate how PyUUL can be used by researchers to address some typical bioinformatics problems, such as structure recognition and docking.

MAPRE2 mutations result in altered human cranial neural crest migration, underlying craniofacial malformations in CSC-KT syndrome.

Circumferential skin creases (CSC-KT) is a rare polymalformative syndrome characterised by intellectual disability associated with skin creases on the limbs, and very characteristic craniofacial malformations. Previously, heterozygous and homozygous mutations in MAPRE2 were found to be causal for this disease. MAPRE2 encodes for a member of evolutionary conserved microtubule plus end tracking proteins, the end binding (EB) family. Unlike MAPRE1 and MAPRE3, MAPRE2 is not required for the persistent growth and stabilization of microtubules, but plays a role in other cellular processes such as mitotic progression and regulation of cell adhesion. The mutations identified in MAPRE2 all reside within the calponin homology domain, responsible to track and interact with the plus-end tip of growing microtubules, and previous data showed that altered dosage of MAPRE2 resulted in abnormal branchial arch patterning in zebrafish. In this study, we developed patient derived induced pluripotent stem cell lines for MAPRE2, together with isogenic controls, using CRISPR/Cas9 technology, and differentiated them towards neural crest cells with cranial identity. We show that changes in MAPRE2 lead to alterations in neural crest migration in vitro but also in vivo, following xenotransplantation of neural crest progenitors into developing chicken embryos. In addition, we provide evidence that changes in focal adhesion might underlie the altered cell motility of the MAPRE2 mutant cranial neural crest cells. Our data provide evidence that MAPRE2 is involved in cellular migration of cranial neural crest and offers critical insights into the mechanism underlying the craniofacial dysmorphisms and cleft palate present in CSC-KT patients. This adds the CSC-KT disorder to the growing list of neurocristopathies.

Identification of genomic enhancers through spatial integration of single-cell transcriptomics and epigenomics.

Single-cell technologies allow measuring chromatin accessibility and gene expression in each cell, but jointly utilizing both layers to map bona fide gene regulatory networks and enhancers remains challenging. Here, we generate independent single-cell RNA-seq and single-cell ATAC-seq atlases of the Drosophila eye-antennal disc and spatially integrate the data into a virtual latent space that mimics the organization of the 2D tissue using ScoMAP (Single-Cell Omics Mapping into spatial Axes using Pseudotime ordering). To validate spatially predicted enhancers, we use a large collection of enhancer-reporter lines and identify ~ 85% of enhancers in which chromatin accessibility and enhancer activity are coupled. Next, we infer enhancer-to-gene relationships in the virtual space, finding that genes are mostly regulated by multiple, often redundant, enhancers. Exploiting cell type-specific enhancers, we deconvolute cell type-specific effects of bulk-derived chromatin accessibility QTLs. Finally, we discover that Prospero drives neuronal differentiation through the binding of a GGG motif. In summary, we provide a comprehensive spatial characterization of gene regulation in a 2D tissue.

Thermodynamic and Evolutionary Coupling between the Native and Amyloid State of Globular Proteins.

The amyloid-like aggregation propensity present in most globular proteins is generally considered to be a secondary side effect resulting from the requirements of protein stability. Here, we demonstrate, however, that mutations in the globular and amyloid state are thermodynamically correlated rather than simply associated. In addition, we show that the standard genetic code couples this structural correlation into a tight evolutionary relationship. We illustrate the extent of this evolutionary entanglement of amyloid propensity and globular protein stability. Suppressing a 600-Ma-conserved amyloidogenic segment in the p53 core domain fold is structurally feasible but requires 7-bp substitutions to concomitantly introduce two aggregation-suppressing and three stabilizing amino acid mutations. We speculate that, rather than being a corollary of protein evolution, it is equally plausible that positive selection for amyloid structure could have been a driver for the emergence of globular protein structure.