Understanding and predicting protein misfolding and aggregation: Insights from proteomics

Detergent-insoluble PFN1 inoculation expedites disease onset and progression in PFN1 transgenic rats

Accumulating evidence suggests a gain of elusive toxicity in pathogenically mutated PFN1. The prominence of PFN1 aggregates as a pivotal pathological hallmark in PFN1 transgenic rats underscores the crucial involvement of protein aggregation in the initiation and progression of neurodegeneration. Detergent-insoluble materials were extracted from the spinal cords of paralyzed rats afflicted with ALS and were intramuscularly administered to asymptomatic recipient rats expressing mutant PFN1, resulting in an accelerated development of PFN1 inclusions and ALS-like phenotypes. This effect diminished when the extracts derived from wildtype PFN1 transgenic rats were employed, as detergent-insoluble PFN1 was detected exclusively in mutant PFN1 transgenic rats. Consequently, the factor influencing the progression of ALS pathology in recipient rats is likely associated with the presence of detergent-insoluble PFN1 within the extracted materials. Noteworthy is the absence of disease course modification upon administering detergent-insoluble extracts to rats that already displayed PFN1 inclusions, suggesting a seeding rather than augmenting role of such extracts in initiating neuropathological changes. Remarkably, pathogenic PFN1 exhibited an enhanced affinity for the molecular chaperone DNAJB6, leading to the sequestration of DNAJB6 within protein inclusions, thereby depleting its availability for cellular functions. These findings shed light on a novel mechanism that underscores the prion-like characteristics of pathogenic PFN1 in driving neurodegeneration in the context of PFN1-related ALS.

Resolving Hidden Solution Conformations of Hemoglobin Using IMS-IMS on a Cyclic Instrument

Ion mobility spectrometry-mass spectrometry (IMS-MS) experiments on a cyclic IMS instrument were used to examine heterogeneous distributions of structures found in the 15+ to 18+ charge states of the hemoglobin tetramer (Hb). The resolving power of IMS measurements is known to increase with increasing drift-region length. This effect is not significant for Hb charge states as peaks were shown to broaden with increasing drift-region length. This observation suggests that multiple structures with similar cross sections may be present. To examine this hypothesis, selections of drift time distributions were isolated and subsequently reinjected into the mobility region for additional separation. These IMS-IMS experiments demonstrate that selected regions separate further upon additional passes around the drift cell, consistent with the idea that initial resolving power was limited due to the presence of many closely related conformations. Additional variable temperature electrospray ionization (vT-ESI) experiments were conducted to study how changing the solution temperature affects solution conformations. Some features in these IMS-IMS studies were observed to change similarly with solution temperature compared to features in the single IMS distribution. Other features changed differently in the selected mobility data, indicating that solution structures that were obscured upon IMS analysis because of the complex heterogeneity of the original distribution are discernible after reducing the number of conformers that are analyzed by further IMS analysis. These results illustrate that the combination of vT-ESI with IMS-IMS is useful for resolving and exploring conformer distributions and stabilities in systems that exhibit a large degree of structural heterogeneity.

Automated optimisation of solubility and conformational stability of antibodies and proteins

Biologics, such as antibodies and enzymes, are crucial in research, biotechnology, diagnostics, and therapeutics. Often, biologics with suitable functionality are discovered, but their development is impeded by developability issues. Stability and solubility are key biophysical traits underpinning developability potential, as they determine aggregation, correlate with production yield and poly-specificity, and are essential to access parenteral and oral delivery. While advances for the optimisation of individual traits have been made, the co-optimization of multiple traits remains highly problematic and time-consuming, as mutations that improve one property often negatively impact others. In this work, we introduce a fully automated computational strategy for the simultaneous optimisation of conformational stability and solubility, which we experimentally validate on six antibodies, including two approved therapeutics. Our results on 42 designs demonstrate that the computational procedure is highly effective at improving developability potential, while not affecting antigen-binding. We make the method available as a webserver at www-cohsoftware.ch.cam.ac.uk.

A male germ-cell-specific ribosome controls male fertility

Ribosomes are highly sophisticated translation machines that have been demonstrated to be heterogeneous in the regulation of protein synthesis^1,2. Male germ cell development involves complex translational regulation during sperm formation³. However, it remains unclear whether translation during sperm formation is performed by a specific ribosome. Here we report a ribosome with a specialized nascent polypeptide exit tunnel, Ribosome^ST, that is assembled with the male germ-cell-specific protein RPL39L, the paralogue of core ribosome (Ribosome^Core) protein RPL39. Deletion of Ribosome^ST in mice causes defective sperm formation, resulting in substantially reduced fertility. Our comparison of single-particle cryo-electron microscopy structures of ribosomes from mouse kidneys and testes indicates that Ribosome^ST features a ribosomal polypeptide exit tunnel of distinct size and charge states compared with Ribosome^Core. Ribosome^ST predominantly cotranslationally regulates the folding of a subset of male germ-cell-specific proteins that are essential for the formation of sperm. Moreover, we found that specialized functions of Ribosome^ST were not replaceable by Ribosome^Core. Taken together, identification of this sperm-specific ribosome should greatly expand our understanding of ribosome function and tissue-specific regulation of protein expression pattern in mammals.

Isolation and characterization of amyloid-like protein aggregates from soya beans and the effect of low pH and heat treatment on their stability

Purified soya bean proteins (glycinin and conglycinin) are known to form amyloid-like aggregates in vitro at a higher temperature. Soya beans (chunks) are textured proteinaceous vegetables made from defatted soya flour by heating it above 100°C and extruding under high pressure. Therefore, it was assumed that subjecting the soya bean proteins to high temperatures raises the possibility of forming amyloids or amyloid-like protein aggregates. Hence, the present study aimed to examine the presence of amyloid-like protein aggregates in soya beans. The isolated protein aggregates from hydrated soya beans displayed typical characteristics of amyloids, such as the red shift in the absorption maximum (λ_max ) of Congo red (CR), high Thioflavin T (ThT), and 8-Anilinonapthalene-1-sulfonate (ANS) binding, and fibrilar morphology. Furthermore, these aggregates were found to be stable against proteolytic hydrolysis, confirming the specific property of amyloids. The presence of amyloid-like structures in soya beans raises concerns about their implications for human nutrition and health. PRACTICAL APPLICATIONS: Protein aggregation has usually been considered detrimental. The traditional food-processing conditions, such as thermal processing, are associated with protein denaturation and aggregation. The formation of ordered protein aggregates with extensive β-sheet are progressively evident in various protein-rich foods known as amyloid, which expands food safety concerns. Instead, it is also associated with poor nutritional characteristics. The present study concerns the presence of amyloid-like protein aggregates in widely consumed native soya beans, which are manufactured by extensive heat treatment of defatted soy flour. Although there is no indication of their toxicity, these aggregates are found to be proteolytically resistant. The seminal findings in this manuscript suggest that it is time to adapt innovative food processing and supplementation of bioactive molecules that can prevent the formation of such protein aggregates and help maximize the utilization of protein-based nutritional values.

The effect of mutation on an aggregation-prone protein: An in vivo, in vitro, and in silico analysis

Aggregation of initially stably structured proteins is involved in more than 20 human amyloid diseases. Despite intense research, however, how this class of proteins assembles into amyloid fibrils remains poorly understood, principally because of the complex effects of amino acid substitutions on protein stability, solubility, and aggregation propensity. We address this question using β2-microglobulin (β2m) as a model system, focusing on D76N-β2m that is involved in hereditary amyloidosis. This amino acid substitution causes the aggregation-resilient wild-type protein to become highly aggregation prone in vitro, although the mechanism by which this occurs remained elusive. Here, we identify the residues key to protecting β2m from aggregation by coupling aggregation with antibiotic resistance in E. coli using a tripartite β-lactamase assay (TPBLA). By performing saturation mutagenesis at three different sites (D53X-, D76X-, and D98X-β2m) we show that residue 76 has a unique ability to drive β2m aggregation in vivo and in vitro. Using a randomly mutated D76N-β2m variant library, we show that all of the mutations found to improve protein behavior involve residues in a single aggregation-prone region (APR) (residues 60 to 66). Surprisingly, no correlation was found between protein stability and protein aggregation rate or yield, with several mutations in the APR decreasing aggregation without affecting stability. Together, the results demonstrate the power of the TPBLA to develop proteins that are resilient to aggregation and suggest a model for D76N-β2m aggregation involving the formation of long-range couplings between the APR and Asn76 in a nonnative state.

Amyloidogenic Peptides: New Class of Antimicrobial Peptides with the Novel Mechanism of Activity

Antibiotic-resistant bacteria are recognized as one of the leading causes of death in the world. We proposed and successfully tested peptides with a new mechanism of antimicrobial action “protein silencing” based on directed co-aggregation. The amyloidogenic antimicrobial peptide (AAMP) interacts with the target protein of model or pathogenic bacteria and forms aggregates, thereby knocking out the protein from its working condition. In this review, we consider antimicrobial effects of the designed peptides on two model organisms, E. coli and T. thermophilus, and two pathogenic organisms, P. aeruginosa and S. aureus. We compare the amino acid composition of proteomes and especially S1 ribosomal proteins. Since this protein is inherent only in bacterial cells, it is a good target for studying the process of co-aggregation. This review presents a bioinformatics analysis of these proteins. We sum up all the peptides predicted as amyloidogenic by several programs and synthesized by us. For the four organisms we studied, we show how amyloidogenicity correlates with antibacterial properties. Let us especially dwell on peptides that have demonstrated themselves as AMPs for two pathogenic organisms that cause dangerous hospital infections, and in which the minimal inhibitory concentration (MIC) turned out to be comparable to the MIC of gentamicin sulfate. All this makes our study encouraging for the further development of AAMP. The hybrid peptides may thus provide a starting point for the antibacterial application of amyloidogenic peptides.

Assessment of Therapeutic Antibody Developability by Combinations of In Vitro and In Silico Methods

Although antibodies have become the fastest-growing class of therapeutics on the market, it is still challenging to develop them for therapeutic applications, which often require these molecules to withstand stresses that are not present in vivo. We define developability as the likelihood of an antibody candidate with suitable functionality to be developed into a manufacturable, stable, safe, and effective drug that can be formulated to high concentrations while retaining a long shelf life. The implementation of reliable developability assessments from the early stages of antibody discovery enables flagging and deselection of potentially problematic candidates, while focussing available resources on the development of the most promising ones. Currently, however, thorough developability assessment requires multiple in vitro assays, which makes it labor intensive and time consuming to implement at early stages. Furthermore, accurate in vitro analysis at the early stage is compromised by the high number of potential candidates that are often prepared at low quantities and purity. Recent improvements in the performance of computational predictors of developability potential are beginning to change this scenario. Many computational methods only require the knowledge of the amino acid sequences and can be used to identify possible developability issues or to rank available candidates according to a range of biophysical properties. Here, we describe how the implementation of in silico tools into antibody discovery pipelines is increasingly offering time- and cost-effective alternatives to in vitro experimental screening, thus streamlining the drug development process. We discuss in particular the biophysical and biochemical properties that underpin developability potential and their trade-offs, review various in vitro assays to measure such properties or parameters that are predictive of developability, and give an overview of the growing number of in silico tools available to predict properties important for antibody development, including the CamSol method developed in our laboratory.

A3D 2.0 Update for the Prediction and Optimization of Protein Solubility

Protein aggregation propensity is a property imprinted in protein sequences and structures, being associated with the onset of human diseases and limiting the implementation of protein-based biotherapies. Computational approaches stand as cost-effective alternatives for reducing protein aggregation and increasing protein solubility. AGGRESCAN 3D (A3D) is a structure-based predictor of aggregation that takes into account the conformational context of a protein, aiming to identify aggregation-prone regions exposed in protein surfaces. Here we inspect the updated 2.0 version of the algorithm, which extends the application of A3D to previously inaccessible proteins and incorporates new modules to assist protein redesign. Among these features, the new server includes stability calculations and the possibility to optimize protein solubility using an experimentally validated computational pipeline. Finally, we employ defined examples to navigate the A3D RESTful service, a routine to handle extensive protein collections. Altogether, this chapter is conceived to train and assist A3D non-experts in the study of aggregation-prone regions and protein solubility redesign.

New Model for Stacking Monomers in Filamentous Actin from Skeletal Muscles of Oryctolagus cuniculus

To date, some scientific evidence (limited proteolysis, mass spectrometry analysis, electron microscopy (EM)) has accumulated, which indicates that the generally accepted model of double-stranded of filamentous actin (F-actin) organization in eukaryotic cells is not the only one. This entails an ambiguous understanding of many of the key cellular processes in which F-actin is involved. For a detailed understanding of the mechanism of F-actin assembly and actin interaction with its partners, it is necessary to take into account the polymorphism of the structural organization of F-actin at the molecular level. Using electron microscopy, limited proteolysis, mass spectrometry, X-ray diffraction, and structural modeling we demonstrated that F-actin presented in the EM images has no double-stranded organization, the regions of protease resistance are accessible for action of proteases in F-actin models. Based on all data, a new spatial model of filamentous actin is proposed, and the F-actin polymorphism is discussed.

Protein structure, amino acid composition and sequence determine proteome vulnerability to oxidation-induced damage

Oxidative stress alters cell viability, from microorganism irradiation sensitivity to human aging and neurodegeneration. Deleterious effects of protein carbonylation by reactive oxygen species (ROS) make understanding molecular properties determining ROS susceptibility essential. The radiation‐resistant bacterium Deinococcus radiodurans accumulates less carbonylation than sensitive organisms, making it a key model for deciphering properties governing oxidative stress resistance. We integrated shotgun redox proteomics, structural systems biology, and machine learning to resolve properties determining protein damage by γ‐irradiation in Escherichia coli and D. radiodurans at multiple scales. Local accessibility, charge, and lysine enrichment accurately predict ROS susceptibility. Lysine, methionine, and cysteine usage also contribute to ROS resistance of the D. radiodurans proteome. Our model predicts proteome maintenance machinery, and proteins protecting against ROS are more resistant in D. radiodurans. Our findings substantiate that protein‐intrinsic protection impacts oxidative stress resistance, identifying causal molecular properties.

Computational prediction of protein aggregation: Advances in proteomics, conformation-specific algorithms and biotechnological applications

Protein aggregation is a widespread phenomenon that stems from the establishment of non-native intermolecular contacts resulting in protein precipitation. Despite its deleterious impact on fitness, protein aggregation is a generic property of polypeptide chains, indissociable from protein structure and function. Protein aggregation is behind the onset of neurodegenerative disorders and one of the serious obstacles in the production of protein-based therapeutics. The development of computational tools opened a new avenue to rationalize this phenomenon, enabling prediction of the aggregation propensity of individual proteins as well as proteome-wide analysis. These studies spotted aggregation as a major force driving protein evolution. Actual algorithms work on both protein sequences and structures, some of them accounting also for conformational fluctuations around the native state and the protein microenvironment. This toolbox allows to delineate conformation-specific routines to assist in the identification of aggregation-prone regions and to guide the optimization of more soluble and stable biotherapeutics. Here we review how the advent of predictive tools has change the way we think and address protein aggregation.

An in vivo platform to select and evolve aggregation-resistant proteins

Protein biopharmaceuticals are highly successful, but their utility is compromised by their propensity to aggregate during manufacture and storage. As aggregation can be triggered by non-native states, whose population is not necessarily related to thermodynamic stability, prediction of poorly-behaving biologics is difficult, and searching for sequences with desired properties is labour-intensive and time-consuming. Here we show that an assay in the periplasm of E. coli linking aggregation directly to antibiotic resistance acts as a sensor for the innate (un-accelerated) aggregation of antibody fragments. Using this assay as a directed evolution screen, we demonstrate the generation of aggregation resistant scFv sequences when reformatted as IgGs. This powerful tool can thus screen and evolve ‘manufacturable’ biopharmaceuticals early in industrial development. By comparing the mutational profiles of three different immunoglobulin scaffolds, we show the applicability of this method to investigate protein aggregation mechanisms important to both industrial manufacture and amyloid disease.

Protein aggregation remains a significant challenge for manufacturing of protein biopharmaceuticals. Here, the authors demonstrate the use of directed evolution and an assay for in vivo innate protein aggregation-propensity to generate aggregation-resistant scFv fragments.

Comparative refolding of guanidinium hydrochloride denatured bovine serum albumin assisted by cationic and anionic surfactants via artificial chaperone protocol: Biophysical insight

In the present study, we report the cooperative refolding/renaturation behaviour of guanidinium hydrochloride (GdnHCl) denatured bovine serum albumin (BSA) in the presence of cationic surfactant cetyltrimethylammonium bromide (CTAB), anionic surfactant sodium dodecyl sulphate (SDS) and their catanionic mixture in the solution of 60 mM sodium phosphate buffer of physiological pH 7.4, using artificial chaperone-assisted two-step method. Here, we have employed biophysical techniques to characterize the refolding mechanism of denatured BSA after 200 times of dilution in the presence of cationic, anionic surfactants and their catanionic mixture, separately. We have found that minimum refolding of diluted BSA in the presence of 1:1 rational mixture of CTAB and SDS (CTAB/SDS = 50/50), it may be due to the micelles formation which is responsible for the unordered microstructure aggregate formation. Other mixtures (CTAB/SDS = 20/80 and 80/20) slightly played an effective role during refolding process in the presence of methyl-β-cyclodextrin. On other hand, CTAB and SDS are more effective and reflect a good renaturation tendency of denatured BSA solution separately and in existence of methyl-β-cyclodextrin as compare to their mixture compositions. But overall, CTAB has the better renaturation tendency as compare to SDS in the existence of methyl-β-cyclodextrin. These results ascribed the presence of charge head group and length of hydrophobic tail of CTAB surfactant that plays an important task during electrostatic and hydrophobic interactions at pH 7.4 at which BSA carries negative charge on their surface. These biophysical parameters suggest that, CTAB surfactant assisted artificial chaperone protocol may be utilized in the protein renaturation/refolding studies, which may address the associated problems of biotechnological industries for the development of efficient and inexpensive folding aides, which may also be used to produced genetically engineered cells related diseases, resulting from protein misfolding/aggregation.

Protein Solubility Predictions Using the CamSol Method in the Study of Protein Homeostasis

One of the major functions of the protein homeostasis system is to maintain proteins in their soluble states, and indeed several human disorders are associated with the aberrant aggregation of proteins. An active involvement of the protein homeostasis system is necessary to avoid aggregation because proteins are expressed at levels close to their solubility limits, hence being poorly soluble. The mechanisms by which the protein homeostasis system acts to control protein aggregation are, however, still not known in much detail. To facilitate systematic investigations of these mechanisms, we describe here the CamSol method of predicting protein solubility, and illustrate its initial applications. We anticipate that with the advent of powerful proteomics and transcriptomic methods, in combination with the use of the CamSol method and related approaches to predict the solubility and other biophysical properties of proteins, it will become possible to increase our understanding of the principles of protein homeostasis related to the maintenance of the proteome in its soluble form.

Protein misfolding and aggregation in neurodegenerative diseases: a review of pathogeneses, novel detection strategies, and potential therapeutics

Protein folding is a complex, multisystem process characterized by heavy molecular and cellular footprints. Chaperone machinery enables proper protein folding and stable conformation. Other pathways concomitant with the protein folding process include transcription, translation, post-translational modifications, degradation through the ubiquitin-proteasome system, and autophagy. As such, the folding process can go awry in several different ways. The pathogenic basis behind most neurodegenerative diseases is that the disruption of protein homeostasis (i.e. proteostasis) at any level will eventually lead to protein misfolding. Misfolded proteins often aggregate and accumulate to trigger neurotoxicity through cellular stress pathways and consequently cause neurodegenerative diseases. The manifestation of a disease is usually dependent on the specific brain region that the neurotoxicity affects. Neurodegenerative diseases are age-associated, and their incidence is expected to rise as humans continue to live longer and pursue a greater life expectancy. We presently review the sequelae of protein misfolding and aggregation, as well as the role of these phenomena in several neurodegenerative diseases including Alzheimer's disease, Huntington's disease, amyotrophic lateral sclerosis, Parkinson's disease, transmissible spongiform encephalopathies, and spinocerebellar ataxia. Strategies for treatment and therapy are also conferred with respect to impairing, inhibiting, or reversing protein misfolding.

From De Novo to "De Nono": The Majority of Novel Protein-Coding Genes Identified with Phylostratigraphy Are Old Genes or Recent Duplicates

The evolution of novel protein-coding genes from noncoding regions of the genome is one of the most compelling pieces of evidence for genetic innovations in nature. One popular approach to identify de novo genes is phylostratigraphy, which consists of determining the approximate time of origin (age) of a gene based on its distribution along a species phylogeny. Several studies have revealed significant flaws in determining the age of genes, including de novo genes, using phylostratigraphy alone. However, the rate of false positives in de novo gene surveys, based on phylostratigraphy, remains unknown. Here, I reanalyze the findings from three studies, two of which identified tens to hundreds of rodent-specific de novo genes adopting a phylostratigraphy-centered approach. Most putative de novo genes discovered in these investigations are no longer included in recently updated mouse gene sets. Using a combination of synteny information and sequence similarity searches, I show that ∼60% of the remaining 381 putative de novo genes share homology with genes from other vertebrates, originated through gene duplication, and/or share no synteny information with nonrodent mammals. These results led to an estimated rate of ∼12 de novo genes per million years in mouse. Contrary to a previous study (Wilson BA, Foy SG, Neme R, Masel J. 2017. Young genes are highly disordered as predicted by the preadaptation hypothesis of de novo gene birth. Nat Ecol Evol. 1:0146), I found no evidence supporting the preadaptation hypothesis of de novo gene formation. Nearly half of the de novo genes confirmed in this study are within older genes, indicating that co-option of preexisting regulatory regions and a higher GC content may facilitate the origin of novel genes.