AGGRESCAN: a server for the prediction and evaluation of "hot spots" of aggregation in polypeptides

Wheat gluten amyloid fibrils: Conditions, mechanism, characterization, application, and future perspectives

Amyloid fibrils have excellent structural characteristics, such as a high aspect ratio, excellent stiffness, and a wide availability of functional groups on the surface. More studies are now focusing on the formation of amyloid fibrils using food proteins. Protein fibrillation is now becoming recognized as a promising strategy for enhancing the function of food proteins and expanding their range of applications. Wheat gluten is rich in glutamine (Q), hydrophobic amino acids, and the α-helix structure with high β-sheet tendency. These characteristics make it very easy for wheat gluten to form amyloid fibrils. The conditions, formation mechanism, characterization methods, and application of amyloid fibrils formed by wheat gluten are summarized in this review. Further exploration of amyloid fibrils formed by wheat gluten will reveal how they can play a significant role in food, biology, and other fields, especially in medicine.

On the Prevalence and Roles of Proteins Undergoing Liquid-Liquid Phase Separation in the Biogenesis of PML-Bodies

The formation and function of membrane-less organelles (MLOs) is one of the main driving forces in the molecular life of the cell. These processes are based on the separation of biopolymers into phases regulated by multiple specific and nonspecific inter- and intramolecular interactions. Among the realm of MLOs, a special place is taken by the promyelocytic leukemia nuclear bodies (PML-NBs or PML bodies), which are the intranuclear compartments involved in the regulation of cellular metabolism, transcription, the maintenance of genome stability, responses to viral infection, apoptosis, and tumor suppression. According to the accepted models, specific interactions, such as SUMO/SIM, the formation of disulfide bonds, etc., play a decisive role in the biogenesis of PML bodies. In this work, a number of bioinformatics approaches were used to study proteins found in the proteome of PML bodies for their tendency for spontaneous liquid-liquid phase separation (LLPS), which is usually caused by weak nonspecific interactions. A total of 205 proteins found in PML bodies have been identified. It has been suggested that UBC9, P53, HIPK2, and SUMO1 can be considered as the scaffold proteins of PML bodies. It was shown that more than half of the proteins in the analyzed proteome are capable of spontaneous LLPS, with 85% of the analyzed proteins being intrinsically disordered proteins (IDPs) and the remaining 15% being proteins with intrinsically disordered protein regions (IDPRs). About 44% of all proteins analyzed in this study contain SUMO binding sites and can potentially be SUMOylated. These data suggest that weak nonspecific interactions play a significantly larger role in the formation and biogenesis of PML bodies than previously expected.

Stabilization challenges and aggregation in protein-based therapeutics in the pharmaceutical industry

Protein-based therapeutics have revolutionized the pharmaceutical industry and become vital components in the development of future therapeutics. They offer several advantages over traditional small molecule drugs, including high affinity, potency and specificity, while demonstrating low toxicity and minimal adverse effects. However, the development and manufacturing processes of protein-based therapeutics presents challenges related to protein folding, purification, stability and immunogenicity that should be addressed. These proteins, like other biological molecules, are prone to chemical and physical instabilities. The stability of protein-based drugs throughout the entire manufacturing, storage and delivery process is essential. The occurrence of structural instability resulting from misfolding, unfolding, and modifications, as well as aggregation, poses a significant risk to the efficacy of these drugs, overshadowing their promising attributes. Gaining insight into structural alterations caused by aggregation and their impact on immunogenicity is vital for the advancement and refinement of protein therapeutics. Hence, in this review, we have discussed some features of protein aggregation during production, formulation and storage as well as stabilization strategies in protein engineering and computational methods to prevent aggregation.

Staphylococcal superantigen-like protein 10 enhances the amyloidogenic biofilm formation in Staphylococcus aureus

Staphylococcus aureus is a highly infectious pathogen that represents a significant burden on the current healthcare system. Bacterial attachment to medical implants and host tissue, and the establishment of a mature biofilm, play an important role in chronic diseases such as endocarditis, osteomyelitis and wound infections. These biofilms decrease bacterial susceptibility to antibiotics and immune defences, making the infections challenging to treatment. S. aureus produces numerous exotoxins that contribute to the pathogenesis of the bacteria. In this study, we have identified a novel function of staphylococcal superantigen-like protein 10 (SSL10) in enhancing the formation of staphylococcal biofilms. Biofilm biomass is significantly increased when SSL10 is added exogenously to bacterial cultures, whereas SSL2 and SSL12 are found to be less active. Exogenously added SSL10 mask the surface charge of the bacterial cells and lowers their zeta potential, leading to the aggregation of the cells. Moreover, the biofilm formation by SSL10 is governed by amyloid aggregation, as evident from spectroscopic and microscopic studies. These findings thereby give the first overview of the SSL-mediated amyloid-based biofilm formation and further drive the future research in identifying potential molecules for developing new antibacterial therapies against Staphylococcus aureus.

Biophysical evolution of the receptor-binding domains of SARS-CoVs

With hundreds of coronaviruses (CoVs) identified in bats that can infect humans, it is essential to understand how CoVs that affected the human population have evolved. Seven known CoVs have infected humans, of which three CoVs caused severe disease with high mortalities: severe acute respiratory syndrome (SARS)-CoV emerged in 2002, Middle East respiratory syndrome-CoV in 2012, and SARS-CoV-2 in 2019. SARS-CoV and SARS-CoV-2 belong to the same family, follow the same receptor pathway, and use their receptor-binding domain (RBD) of spike protein to bind to the angiotensin-converting enzyme 2 (ACE2) receptor on the human epithelial cell surface. The sequence of the two RBDs is divergent, especially in the receptor-binding motif that directly interacts with ACE2. We probed the biophysical differences between the two RBDs in terms of their structure, stability, aggregation, and function. Since RBD is being explored as an antigen in protein subunit vaccines against CoVs, determining these biophysical properties will also aid in developing stable protein subunit vaccines. Our results show that, despite RBDs having a similar three-dimensional structure, they differ in their thermodynamic stability. RBD of SARS-CoV-2 is significantly less stable than that of SARS-CoV. Correspondingly, SARS-CoV-2 RBD shows a higher aggregation propensity. Regarding binding to ACE2, less stable SARS-CoV-2 RBD binds with a higher affinity than more stable SARS-CoV RBD. In addition, SARS-CoV-2 RBD is more homogenous in terms of its binding stoichiometry toward ACE2 compared to SARS-CoV RBD. These results indicate that SARS-CoV-2 RBD differs from SARS-CoV RBD in terms of its stability, aggregation, and function, possibly originating from the diverse receptor-binding motifs. Higher aggregation propensity and decreased stability of SARS-CoV-2 RBD warrant further optimization of protein subunit vaccines that use RBD as an antigen by inserting stabilizing mutations or formulation screening.

Widespread amyloid aggregates formation by Zika virus proteins and peptides

Viral pathogenesis typically involves numerous molecular mechanisms. Protein aggregation is a relatively unknown characteristic of viruses, despite the fact that viral proteins have been shown to form terminally misfolded forms. Zika virus (ZIKV) is a neurotropic one with the potential to cause neurodegeneration. Its protein amyloid aggregation may link the neurodegenerative component to the pathogenicity associated with the viral infection. Therefore, we investigated protein aggregation in the ZIKV proteome as a putative pathogenic route and one of the alternate pathways. We discovered that it contains numerous anticipated aggregation-prone regions in this investigation. To validate our prediction, we used a combination of supporting experimental techniques routinely used for morphological characterization and study of amyloid aggregates. Several ZIKV proteins and peptides, including the full-length envelope protein, its domain III (EDIII) and fusion peptide, Pr N-terminal peptide, NS1 β-roll peptide, membrane-embedded signal peptide 2K, and cytosolic region of NS4B protein, were shown to be highly aggregating in our study. Because our findings show that viral proteins can form amyloids in vitro, we need to do a thorough functional study of these anticipated APRs to understand better the role of amyloids in the pathophysiology of ZIKV infection.

Predictors for progression in amyotrophic lateral sclerosis associated to SOD1 mutation: insight from two population-based registries

BACKGROUND

Uncovering distinct features and trajectories of amyotrophic lateral sclerosis (ALS) associated with SOD1 mutations (SOD1-ALS) can provide valuable insights for patient' counseling and stratification for trials, and interventions timing. Our study aims to pinpoint distinct clinical characteristics of SOD1-ALS by delving into genotype-phenotype correlations and factors that potentially impact disease progression.

METHODS

This is a retrospective observational study of a SOD1-ALS cohort from two Italian registers situated in the regions of Emilia-Romagna, Piedmont and Valle d'Aosta.

RESULTS

Out of 2204 genotyped ALS patients, 2.5% carried SOD1 mutations, with a M:F ratio of 0.83. SOD1-ALS patients were younger, and more frequently reported a family history of ALS and/or FTD. SOD1-ALS had a longer survival compared to patients without ALS-associated gene mutations. However, here was considerable variability in survival across distinct SOD1 mutations, with an average survival of less than a year for the L39V, G42S, G73S, D91N mutations. Among SOD1-ALS, multivariate analysis showed that, alongside established clinical prognostic factors such as advanced age at onset and high progression rate at diagnosis, mutations located in exon 2 or within highly conserved gene positions predicted worse survival. Conversely, among comorbidities, cancer history was independently associated with longer survival.

INTERPRETATION

Within the context of an overall slower disease, SOD1-ALS exhibits some degree of heterogeneity linked to the considerable genetic diversity arising from the multitude of potential mutations sites and specific clinical prognostic factors, including cancer history. Revealing the factors that modulate the phenotypic heterogeneity of SOD1-ALS could prove advantageous in improving the efficacy of upcoming therapeutic approaches.

Enhancing the Antimicrobial Properties of Peptides through Cell-Penetrating Peptide Conjugation: A Comprehensive Assessment

Combining antimicrobial peptides (AMPs) with cell-penetrating peptides (CPPs) has shown promise in boosting antimicrobial potency, especially against Gram-negative bacteria. We examined the CPP-AMP interaction with distinct bacterial types based on cell wall differences. Our investigation focused on AMPs incorporating penetratin CPP and dihybrid peptides containing both cell-penetrating TAT protein fragments from the human immunodeficiency virus and Antennapedia peptide (Antp). Assessment of the peptides TAT-AMP, AMP-Antp, and TAT-AMP-Antp revealed their potential against Gram-positive strains (Staphylococcus aureus, Methicillin-resistant Staphylococcus aureus (MRSA), and Bacillus cereus). Peptides TAT-AMP and AMP-Antp using an amyloidogenic AMP from S1 ribosomal protein Thermus thermophilus, at concentrations ranging from 3 to 12 μM, exhibited enhanced antimicrobial activity against B. cereus. TAT-AMP and TAT-AMP-Antp, using an amyloidogenic AMP from the S1 ribosomal protein Pseudomonas aeruginosa, at a concentration of 12 µM, demonstrated potent antimicrobial activity against S. aureus and MRSA. Notably, the TAT-AMP, at a concentration of 12 µM, effectively inhibited Escherichia coli (E. coli) growth and displayed antimicrobial effects similar to gentamicin after 15 h of incubation. Peptide characteristics determined antimicrobial activity against diverse strains. The study highlights the intricate relationship between peptide properties and antimicrobial potential. Mechanisms of AMP action are closely tied to bacterial cell wall attributes. Peptides with the TAT fragment exhibited enhanced antimicrobial activity against S. aureus, MRSA, and P. aeruginosa. Peptides containing only the Antp fragment displayed lower activity. None of the investigated peptides demonstrated cytotoxic or cytostatic effects on either BT-474 cells or human skin fibroblasts. In conclusion, CPP-AMPs offer promise against various bacterial strains, offering insights for targeted antimicrobial development.

In silico molecular and functional characterization of a dual function antimicrobial peptide, hepcidin (GIFT-Hep), isolated from genetically improved farmed tilapia (GIFT, Oreochromis niloticus)

BACKGROUND

Antimicrobial peptides (AMPs), innate immune response molecules in organisms, are also known for their dual functionality, exemplified by hepcidin-an immunomodulator and iron regulator. Identifying and studying various AMPs from fish species can provide valuable insights into the immune profiles of aquaculturally significant fish, which can be made use of in its culture.

RESULTS

Hepcidin, a dual-function antimicrobial peptide, was isolated from the gill tissue of Genetically Improved Farmed Tilapia (GIFT-Hep). GIFT-Hep consists of a 90 amino acid pre-propeptide with a 24-mer signal, a 40-mer propeptide, and a 26-mer mature peptide region. The mature peptide had a molecular weight of 3015.61 Da, a theoretical pI of 8.78, a net charge of +4.25, and a protein-binding potential of 2.06 kcal/mol. Four disulfide bonds were formed by eight cysteine residues in the mature region. The presence of positively charged arginine residues renders the peptide 50% hydrophobic. Molecular analysis of GIFT-Hep revealed the presence of a furin propeptide convertase motif, RX(K/R)R, which facilitates trimming of the peptide to yield the mature GIFT-Hep. The hypothetical iron regulatory sequence, QSHLSL, was also identified in the mature peptide. In silico predictions about the characteristics of GIFT-Hep, such as charge, hydrophobicity, high surface accessibility, transmembrane helical regions, hydrophobic faces, hot spots, and cell-penetrating properties, suggest that the peptide functions as an iron regulatory antimicrobial agent.

CONCLUSIONS

This study reports a hepcidin antimicrobial peptide with both HAMP1 and HAMP2 properties isolated from genetically improved farmed tilapia, and further evaluation of the properties will prove the feasibility of GIFT-Hep being used as a therapeutant in aquaculture.

O-GlcNAcylation regulates OTX2's proteostasis

O-GlcNAcylation is a key post-translational modification, playing a vital role in cell signaling during development, especially in the brain. In this study, we investigated the role of O-GlcNAcylation in regulating the homeobox protein OTX2, which contributes to various brain disorders, such as combined pituitary hormone deficiency, retinopathy, and medulloblastoma. Our research demonstrated that, under normal physiological conditions, the proteasome plays a pivotal role in breaking down endogenous OTX2. However, when the levels of OTX2 rise, it forms oligomers and/or aggregates that require macroautophagy for clearance. Intriguingly, we demonstrated that O-GlcNAcylation enhances the solubility of OTX2, thereby limiting the formation of these aggregates. Additionally, we unveiled an interaction between OTX2 and the chaperone protein CCT5 at the O-GlcNAc sites, suggesting a potential collaborative role in preventing OTX2 aggregation. Finally, our study demonstrated that while OTX2 physiologically promotes cell proliferation, an O-GlcNAc-depleted OTX2 is detrimental to cancer cells.

Pathologic polyglutamine aggregation begins with a self-poisoning polymer crystal

A long-standing goal of amyloid research has been to characterize the structural basis of the rate-determining nucleating event. However, the ephemeral nature of nucleation has made this goal unachievable with existing biochemistry, structural biology, and computational approaches. Here, we addressed that limitation for polyglutamine (polyQ), a polypeptide sequence that causes Huntington's and other amyloid-associated neurodegenerative diseases when its length exceeds a characteristic threshold. To identify essential features of the polyQ amyloid nucleus, we used a direct intracellular reporter of self-association to quantify frequencies of amyloid appearance as a function of concentration, conformational templates, and rational polyQ sequence permutations. We found that nucleation of pathologically expanded polyQ involves segments of three glutamine (Q) residues at every other position. We demonstrate using molecular simulations that this pattern encodes a four-stranded steric zipper with interdigitated Q side chains. Once formed, the zipper poisoned its own growth by engaging naive polypeptides on orthogonal faces, in a fashion characteristic of polymer crystals with intramolecular nuclei. We further show that self-poisoning can be exploited to block amyloid formation, by genetically oligomerizing polyQ prior to nucleation. By uncovering the physical nature of the rate-limiting event for polyQ aggregation in cells, our findings elucidate the molecular etiology of polyQ diseases.

Transcriptomic analyses reveal proinflammatory activation of human brain microvascular endothelial cells by aging-associated peptide medin and reversal by nanoliposomes

Medin is a common vascular amyloidogenic peptide recently implicated in Alzheimer's disease (AD) and vascular dementia and its pathology remains unknown. We aim to identify changes in transcriptomic profiles and pathways in human brain microvascular endothelial cells (HBMVECs) exposed to medin, compare that to exposure to β-amyloid (Aβ) and evaluate protection by monosialoganglioside-containing nanoliposomes (NL). HBMVECs were exposed for 20 h to medin (5 µM) without or with Aβ(1-42) (2 µM) or NL (300 µg/mL), and RNA-seq with signaling pathway analyses were performed. Separately, reverse transcription polymerase chain reaction of select identified genes was done in HBMVECs treated with medin (5 µM) without or with NFκB inhibitor RO106-9920 (10 µM) or NL (300 µg/mL). Medin caused upregulation of pro-inflammatory genes that was not aggravated by Aβ42 co-treatment but reversed by NL. Pathway analysis on differentially expressed genes revealed multiple pro-inflammatory signaling pathways, such as the tumor necrosis factor (TNF) and the nuclear factor-κB (NFkB) signaling pathways, were affected specifically by medin treatment. RO106-9920 and NL reduced medin-induced pro-inflammatory activation. Medin induced endothelial cell pro-inflammatory signaling in part via NFκB that was reversed by NL. This could have potential implications in the pathogenesis and treatment of vascular aging, AD and vascular dementia.

Potential of ADAM 17 Signal Peptide To Form Amyloid Aggregates in Vitro

ADAM 17, a disintegrin and metalloproteinase 17 belonging to the adamalysin protein family, is a Zn2+-dependent type-I transmembrane α-secretase protein. As a major sheddase, ADAM 17 acts as an indispensable regulator of chief cellular events and controls diverse cytokines, adhesion molecules, and growth factors. The signal peptide (residues 1-17) of ADAM 17 targets the protein to the secretory pathway and gets cleaved off afterward. No other function is documented for the ADAM 17 signal peptide (ADAM 17-SP) inside the cells. Here, we have taken a reductionist approach to understand the biophysical properties of ADAM 17-SP. Aiming to understand the possibility of aggregation, we found several aggregation-prone segments in the signal peptide. We performed in vitro experiments to show that the signal peptide forms amyloid-like aggregates in buffered conditions. We also studied its aggregation in the presence of sodium tripolyphosphate and heparin to correlate with the cellular conditions, as these biomolecules are naturally present inside cells. Further, we performed seeding experiments to observe the possibility of ADAM 17-SP aggregate interaction with the Aβ42 peptide. The results suggest that its seeds escalate the aggregation kinetics of the Aβ42 peptide and form heteromeric aggregates with it. We believe this finding could further intensify the aggregation studies on other signal peptides and shed light on the potential role of these segments other than signaling.

Understanding and controlling the molecular mechanisms of protein aggregation in mAb therapeutics

In antibody development and manufacturing, protein aggregation is a common challenge that can lead to serious efficacy and safety issues. To mitigate this problem, it is important to investigate its molecular origins. This review discusses (1) our current molecular understanding and theoretical models of antibody aggregation, (2) how various stress conditions related to antibody upstream and downstream bioprocesses can trigger aggregation, and (3) current mitigation strategies employed towards inhibiting aggregation. We discuss the relevance of the aggregation phenomenon in the context of novel antibody modalities and highlight how in silico approaches can be exploited to mitigate it.

iAMY-RECMFF: Identifying amyloidgenic peptides by using residue pairwise energy content matrix and features fusion algorithm

Various diseases, including Huntington's disease, Alzheimer's disease, and Parkinson's disease, have been reported to be linked to amyloid. Therefore, it is crucial to distinguish amyloid from non-amyloid proteins or peptides. While experimental approaches are typically preferred, they are costly and time-consuming. In this study, we have developed a machine learning framework called iAMY-RECMFF to discriminate amyloidgenic from non-amyloidgenic peptides. In our model, we first encoded the peptide sequences using the residue pairwise energy content matrix. We then utilized Pearson's correlation coefficient and distance correlation to extract useful information from this matrix. Additionally, we employed an improved similarity network fusion algorithm to integrate features from different perspectives. The Fisher approach was adopted to select the optimal feature subset. Finally, the selected features were inputted into a support vector machine for identifying amyloidgenic peptides. Experimental results demonstrate that our proposed method significantly improves the identification of amyloidgenic peptides compared to existing predictors. This suggests that our method may serve as a powerful tool in identifying amyloidgenic peptides. To facilitate academic use, the dataset and codes used in the current study are accessible at https://figshare.com/articles/online_resource/iAMY-RECMFF/22816916.

Protein reservoirs of seeds are amyloid composites employed differentially for germination and seedling emergence

Seed protein localization in seed storage protein bodies (SSPB) and their significance in germination are well recognized. SSPB are spherical and contain an assembly of water-soluble and salt-soluble proteins. Although the native structures of some SSPB proteins are explored, their structural arrangement to the functional correlation in SSPB remains unknown. SSPB are morphologically analogous to electron-dense amyloid-containing structures reported in other organisms. Here, we show that wheat, mungbean, barley, and chickpea SSPB exhibit a speckled pattern of amyloids interspersed in an amyloid-like matrix along with native structures, suggesting the composite nature of SSPB. This is confirmed by multispectral imaging methods, electron microscopy, infrared, and X-ray diffraction analysis, using in situ tissue sections, ex vivo protoplasts, and in vitro SSPB. Laser capture microdissection coupled with peptide fingerprinting has shown that globulin 1 and 3 in wheat, and 8S globulin and conglycinin in mungbean are the major amyloidogenic proteins. The amyloid composites undergo a sustained degradation during germination and seedling growth, facilitated by an intricate interplay of plant hormones and proteases. These results would lay down the foundation for understanding the amyloid composite structure during SSPB biogenesis and its evolution across the plant kingdom and have implications in both basic and applied plant biology.

Prediction of protein aggregation propensity employing SqFt-based logistic regression model

Here we present a novel machine-learning approach to predict protein aggregation propensity (PAP) which is a key factor in the formation of amyloid fibrils based on logistic regression (LR). Amyloid fibrils are associated with various neurodegenerative diseases (ND) such as Alzheimer's disease (AD) and Parkinson's disease (PD), which are caused by oxidative stress and impaired protein homeostasis. Accordingly, the paper uses a dataset of hexapeptides with known aggregation tendencies and eight physiochemical features to train and test the LR model. Also, it evaluates the performance of the LR model using F-measure and Matthews correlation coefficient (MCC) as metrics and compares it with other existing methods. Moreover, it investigates the effect of combining sequence and feature information in the prediction. In conclusion, the LR model with sequence and feature information achieves high F-measure (0.841) and MCC (0.6692), outperforming other methods and demonstrating its efficiency and reliability for PAP prediction. In addition, the overall performance of the concluded method was higher than the other known servers, for instance, Aggrescan, Metamyl, Foldamyloid, and PASTA 2.0. The LR model can be accessed at: https://github.com/KatherineEshari/Protein-aggregation-prediction.

Nanoscopic Elucidation of Spontaneous Self-Assembly of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Open Reading Frame 6 (ORF6) Protein

Open reading frame 6 (ORF6), the accessory protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that suppresses host type-I interferon signaling, possesses amyloidogenic sequences. ORF6 amyloidogenic peptides self-assemble to produce cytotoxic amyloid fibrils. Currently, the molecular properties of the ORF6 remain elusive. Here, we investigate the structural dynamics of the full-length ORF6 protein in a near-physiological environment using high-speed atomic force microscopy. ORF6 oligomers were ellipsoidal and readily assembled into ORF6 protofilaments in either a circular or a linear pattern. The formation of ORF6 protofilaments was enhanced at higher temperatures or on a lipid substrate. ORF6 filaments were sensitive to aliphatic alcohols, urea, and SDS, indicating that the filaments were predominantly maintained by hydrophobic interactions. In summary, ORF6 self-assembly could be necessary to sequester host factors and causes collateral damage to cells via amyloid aggregates. Nanoscopic imaging unveiled the innate molecular behavior of ORF6 and provides insight into drug repurposing to treat amyloid-related coronavirus disease 2019 complications.

AggBERT: Best in Class Prediction of Hexapeptide Amyloidogenesis with a Semi-Supervised ProtBERT Model

The prediction of peptide amyloidogenesis is a challenging problem in the field of protein folding. Large language models, such as the ProtBERT model, have recently emerged as powerful tools in analyzing protein sequences for applications, such as predicting protein structure and function. In this article, we describe the use of a semisupervised and fine-tuned ProtBERT model to predict peptide amyloidogenesis from sequences alone. Our approach, which we call AggBERT, achieved state-of-the-art performance, demonstrating the potential for large language models to improve the accuracy and speed of amyloid fibril prediction over simple heuristics or structure-based approaches. This work highlights the transformative potential of machine learning and large language models in the fields of chemical biology and biomedicine.

First Report of Lysozyme Amyloidosis with p.F21L/T88N Amino Acid Substitutions in a Russian Family

Lysozyme amyloidosis is caused by an amino acid substitution in the sequence of this protein. In our study, we described a clinical case of lysozyme amyloidosis in a Russian family. In our work, we described in detail the histological changes in tissues that appeared as a result of massive deposition of amyloid aggregates that affected almost all organ systems, with the exception of the central nervous system. We determined the type of amyloidosis and mutations using mass spectrometry. Using mass spectrometry, the protein composition of tissue samples of patient 1 (autopsy material) and patient 2 (biopsy material) with histologically confirmed amyloid deposits were analyzed. Amino acid substitutions p.F21L/T88N in the lysozyme sequence were identified in both sets of samples and confirmed by sequencing of the lysozyme gene of members of this family. We have shown the inheritance of these mutations in the lysozyme gene in members of the described family. For the first time, we discovered a mutation in the first exon p.F21L of the lysozyme gene, which, together with p.T88N amino acid substitution, led to amyloidosis in members of the studied family.

A3DyDB: exploring structural aggregation propensities in the yeast proteome

BACKGROUND

The budding yeast Saccharomyces cerevisiae (S. cerevisiae) is a well-established model system for studying protein aggregation due to the conservation of essential cellular structures and pathways found across eukaryotes. However, limited structural knowledge of its proteome has prevented a deeper understanding of yeast functionalities, interactions, and aggregation.

RESULTS

In this study, we introduce the A3D yeast database (A3DyDB), which offers an extensive catalog of aggregation propensity predictions for the S. cerevisiae proteome. We used Aggrescan 3D (A3D) and the newly released protein models from AlphaFold2 (AF2) to compute the structure-based aggregation predictions for 6039 yeast proteins. The A3D algorithm exploits the information from 3D protein structures to calculate their intrinsic aggregation propensities. To facilitate simple and intuitive data analysis, A3DyDB provides a user-friendly interface for querying, browsing, and visualizing information on aggregation predictions from yeast protein structures. The A3DyDB also allows for the evaluation of the influence of natural or engineered mutations on protein stability and solubility. The A3DyDB is freely available at http://biocomp.chem.uw.edu.pl/A3D2/yeast .

CONCLUSION

The A3DyDB addresses a gap in yeast resources by facilitating the exploration of correlations between structural aggregation propensity and diverse protein properties at the proteome level. We anticipate that this comprehensive database will become a standard tool in the modeling of protein aggregation and its implications in budding yeast.

Cryo-EM Structure of the Full-length hnRNPA1 Amyloid Fibril

Heterogeneous nuclear ribonucleoprotein A1 (hnRNPA1) is a multifunctional RNA-binding protein that is associated with neurodegenerative diseases, such as amyotrophic lateral sclerosis and multisystem proteinopathy. In this study, we have used cryo-electron microscopy to investigate the three-dimensional structure of amyloid fibrils from full-length hnRNPA1 protein. We find that the fibril core is formed by a 45-residue segment of the prion-like low-complexity domain of the protein, whereas the remaining parts of the protein (275 residues) form a fuzzy coat around the fibril core. The fibril consists of two fibril protein stacks that are arranged into a pseudo-21 screw symmetry. The ordered core harbors several of the positions that are known to be affected by disease-associated mutations, but does not encompass the most aggregation-prone segments of the protein. These data indicate that the structures of amyloid fibrils from full-length proteins may be more complex than anticipated by current theories on protein misfolding.

Investigating the aggregation perspective of Dengue virus proteome

Dengue viruses are human pathogens that are transmitted through mosquitoes. Apart from the typical symptoms associated with viral fevers, DENV infections are known to cause several neurological complications such as meningitis, encephalitis, intracranial haemorrhage, retinopathies along with the more severe, and sometimes fatal, vascular leakage and dengue shock syndrome. This study was designed to investigate, in detail, the predicted viral protein aggregation prone regions among all serotypes. Further, in order to understand the cross-talk between viral protein aggregation and aggregation of cellular proteins, cross-seeding experiments between the DENV NS1 (1-30), corresponding to the β-roll domain and the diabetes hallmark protein, amylin, were performed. Various techniques such as fluorescence spectroscopy, circular dichroism, atomic force microscopy and immunoblotting have been employed for this. We observe that the DENV proteomes have many predicted APRs and the NS1 (1-30) of DENV1-3, 2K and capsid anchor of DENV2 and DENV4 are capable of forming amyloids, in vitro. Further, the DENV NS1 (1-30), aggregates are also able to cross-seed and enhance amylin aggregation and vice-versa. This knowledge may lead to an opportunity for designing suitable inhibitors of protein aggregation that may be beneficial for viral infections and comorbidities.

Flanking regions, amyloid cores, and polymorphism: the potential interplay underlying structural diversity

The β-sheet-rich amyloid core is the defining feature of protein aggregates associated with neurodegenerative disorders. Recent investigations have revealed that there exist multiple examples of the same protein, with the same sequence, forming a variety of amyloid cores with distinct structural characteristics. These structural variants, termed as polymorphs, are hypothesized to influence the pathological profile and the progression of different neurodegenerative diseases, giving rise to unique phenotypic differences. Thus, identifying the origin and properties of these structural variants remain a focus of studies, as a preliminary step in the development of therapeutic strategies. Here, we review the potential role of the flanking regions of amyloid cores in inducing polymorphism. These regions, adjacent to the amyloid cores, show a preponderance for being structurally disordered, imbuing them with functional promiscuity. The dynamic nature of the flanking regions can then manifest in the form of conformational polymorphism of the aggregates. We take a closer look at the sequences flanking the amyloid cores, followed by a review of the polymorphic aggregates of the well-characterized proteins amyloid-β, α-synuclein, Tau, and TDP-43. We also consider different factors that can potentially influence aggregate structure and how these regions can be viewed as novel targets for therapeutic strategies by utilizing their unique structural properties.

Spike Protein Fragments Promote Alzheimer's Amyloidogenesis

Alzheimer's disease (AD) is a major cause of dementia inducing memory loss, cognitive decline, and mortality among the aging population. While the amyloid aggregation of peptide Aβ has long been implicated in neurodegeneration in AD, primarily through the production of toxic polymorphic aggregates and reactive oxygen species, viral infection has a less explicit role in the etiology of the brain disease. On the other hand, while the COVID-19 pandemic is known to harm human organs and function, its adverse effects on AD pathobiology and other human conditions remain unclear. Here we first identified the amyloidogenic potential of 1058HGVVFLHVTYV1068, a short fragment of the spike protein of SARS-CoV-2 coronavirus. The peptide fragment was found to be toxic and displayed a high binding propensity for the amyloidogenic segments of Aβ, thereby promoting the aggregation and toxicity of the peptide in vitro and in silico, while retarding the hatching and survival of zebrafish embryos upon exposure. Our study implicated SARS-CoV-2 viral infection as a potential contributor to AD pathogenesis, a little explored area in our quest for understanding and overcoming Long Covid.

Chaotic aging: intrinsically disordered proteins in aging-related processes

The development of aging is associated with the disruption of key cellular processes manifested as well-established hallmarks of aging. Intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) have no stable tertiary structure that provide them a power to be configurable hubs in signaling cascades and regulate many processes, potentially including those related to aging. There is a need to clarify the roles of IDPs/IDRs in aging. The dataset of 1702 aging-related proteins was collected from established aging databases and experimental studies. There is a noticeable presence of IDPs/IDRs, accounting for about 36% of the aging-related dataset, which is however less than the disorder content of the whole human proteome (about 40%). A Gene Ontology analysis of the used here aging proteome reveals an abundance of IDPs/IDRs in one-third of aging-associated processes, especially in genome regulation. Signaling pathways associated with aging also contain IDPs/IDRs on different hierarchical levels, revealing the importance of "structure-function continuum" in aging. Protein-protein interaction network analysis showed that IDPs present in different clusters associated with different aging hallmarks. Protein cluster with IDPs enrichment has simultaneously high liquid-liquid phase separation (LLPS) probability, "nuclear" localization and DNA-associated functions, related to aging hallmarks: genomic instability, telomere attrition, epigenetic alterations, and stem cells exhaustion. Intrinsic disorder, LLPS, and aggregation propensity should be considered as features that could be markers of pathogenic proteins. Overall, our analyses indicate that IDPs/IDRs play significant roles in aging-associated processes, particularly in the regulation of DNA functioning. IDP aggregation, which can lead to loss of function and toxicity, could be critically harmful to the cell. A structure-based analysis of aging and the identification of proteins that are particularly susceptible to disturbances can enhance our understanding of the molecular mechanisms of aging and open up new avenues for slowing it down.

Computational peptide engineering approach for selection of the new C05 antibody-driven peptide with potency to blocking influenza a virus attachment; from in silico to in vivo

Antiviral drugs are currently used to prevent or treat viral infections like influenza A Virus (IAV). Nonetheless, annual genetic mutations of influenza viruses make them resistant to efficient treatment by current medications. Antiviral peptides have recently attracted researchers' attention and can potentially supplant the current medications. This study aimed to design peptides against IAV propagation. For this purpose, P2 and P3 peptides were computationally designed based on the HCDR3 region of the C05 antibody (a monoclonal antibody that neutralizes influenza HA protein and inhibits the virus attachment). The synthesized peptides were tested against the influenza A virus (A/Puerto Rico/8/34 (H1N1)) in vitro, and the most efficient peptide was selected for in vivo experiments. It was shown that the designed peptide shows much more prophylactic and therapeutic effects against the virus. These findings demonstrated that the designed peptide can control the virus infection without any cytotoxicity effect. Antiviral peptide design is acknowledged as a critical tactic to manage viral infections by preventing viral binding to the host cells.Communicated by Ramaswamy H. Sarma.

Census of exposed aggregation-prone regions in proteomes

Loss of solubility usually leads to the detrimental elimination of protein function. In some cases, the protein aggregation is also required for beneficial functions. Given the duality of this phenomenon, it remains a fundamental question how natural selection controls the aggregation. The exponential growth of genomic sequence data and recent progress with in silico predictors of the aggregation allows approaching this problem by a large-scale bioinformatics analysis. Most of the aggregation-prone regions are hidden within the 3D structure, rendering them inaccessible for the intermolecular interactions responsible for aggregation. Thus, the most realistic census of the aggregation-prone regions requires crossing aggregation prediction with information about the location of the natively unfolded regions. This allows us to detect so-called 'exposed aggregation-prone regions' (EARs). Here, we analyzed the occurrence and distribution of the EARs in 76 reference proteomes from the three kingdoms of life. For this purpose, we used a bioinformatics pipeline, which provides a consensual result based on several predictors of aggregation. Our analysis revealed a number of new statistically significant correlations about the presence of EARs in different organisms, their dependence on protein length, cellular localizations, co-occurrence with short linear motifs and the level of protein expression. We also obtained a list of proteins with the conserved aggregation-prone sequences for further experimental tests. Insights gained from this work led to a deeper understanding of the relationship between protein evolution and aggregation.

Nucleolar- and Nuclear-Stress-Induced Membrane-Less Organelles: A Proteome Analysis through the Prism of Liquid-Liquid Phase Separation

Radical changes in the idea of the organization of intracellular space that occurred in the early 2010s made it possible to consider the formation and functioning of so-called membrane-less organelles (MLOs) based on a single physical principle: the liquid-liquid phase separation (LLPS) of biopolymers. Weak non-specific inter- and intramolecular interactions of disordered polymers, primarily intrinsically disordered proteins, and RNA, play a central role in the initiation and regulation of these processes. On the other hand, in some cases, the "maturation" of MLOs can be accompanied by a "liquid-gel" phase transition, where other types of interactions can play a significant role in the reorganization of their structure. In this work, we conducted a bioinformatics analysis of the propensity of the proteomes of two membrane-less organelles, formed in response to stress in the same compartment, for spontaneous phase separation and examined their intrinsic disorder predispositions. These MLOs, amyloid bodies (A-bodies) formed in the response to acidosis and heat shock and nuclear stress bodies (nSBs), are characterized by a partially overlapping composition, but show different functional activities and morphologies. We show that the proteomes of these biocondensates are differently enriched in proteins, and many have high potential for spontaneous LLPS that correlates with the different morphology and function of these organelles. The results of these analyses allowed us to evaluate the role of weak interactions in the formation and functioning of these important organelles.

AB-Amy: machine learning aided amyloidogenic risk prediction of therapeutic antibody light chains

Over 120 FDA-approved antibody-based therapeutics are used to treat a variety of diseases.However, many candidates could fail because of unfavorable physicochemical properties. Light-chain amyloidosis is one form of aggregation that can lead to severe safety risks in clinical development. Therefore, screening candidates with a less amyloidosis risk at the early stage can not only save the time and cost of antibody development but also improve the safety of antibody drugs. In this study, based on the dipeptide composition of 742 amyloidogenic and 712 non-amyloidogenic antibody light chains, a support vector machine-based model, AB-Amy, was trained to predict the light-chain amyloidogenic risk. The AUC of AB-Amy reaches 0.9651. The excellent performance of AB-Amy indicates that it can be a useful tool for the in silico evaluation of the light-chain amyloidogenic risk to ensure the safety of antibody therapeutics under clinical development. A web server is freely available at http://i.uestc.edu.cn/AB-Amy/.

Energy Landscapes and Heat Capacity Signatures for Monomers and Dimers of Amyloid-Forming Hexapeptides

Amyloid formation is a hallmark of various neurodegenerative disorders. In this contribution, energy landscapes are explored for various hexapeptides that are known to form amyloids. Heat capacity (CV) analysis at low temperature for these hexapeptides reveals that the low energy structures contributing to the first heat capacity feature above a threshold temperature exhibit a variety of backbone conformations for amyloid-forming monomers. The corresponding control sequences do not exhibit such structural polymorphism, as diagnosed via end-to-end distance and a dihedral angle defined for the monomer. A similar heat capacity analysis for dimer conformations obtained using basin-hopping global optimisation shows clear features in end-to-end distance versus dihedral correlation plots, where amyloid-forming sequences exhibit a preference for larger end-to-end distances and larger positive dihedrals. These results hold true for sequences taken from tau, amylin, insulin A chain, a de novo designed peptide, and various control sequences. While there is a little overall correlation between the aggregation propensity and the temperature at which the low-temperature CV feature occurs, further analysis suggests that the amyloid-forming sequences exhibit the key CV feature at a lower temperature compared to control sequences derived from the same protein.

Mechanistic insights into the aggregation pathway of the patient-derived immunoglobulin light chain variable domain protein FOR005

Systemic antibody light chain (AL) amyloidosis is characterized by deposition of amyloid fibrils. Prior to fibril formation, soluble oligomeric AL protein has a direct cytotoxic effect on cardiomyocytes. We focus on the patient derived λ-III AL variable domain FOR005 which is mutated at five positions with respect to the closest germline protein. Using solution-state NMR spectroscopy, we follow the individual steps involved in protein misfolding from the native to the amyloid fibril state. Unfavorable mutations in the complementary determining regions introduce a strain in the native protein structure which yields partial unfolding. Driven by electrostatic interactions, the protein converts into a high molecular weight, oligomeric, molten globule. The high local concentration of aggregation prone regions in the oligomer finally catalyzes the conversion into fibrils. The topology is determined by balanced electrostatic interactions in the fibril core implying a 180° rotational switch of the beta-sheets around the conserved disulfide bond.

Refinement of the Fusion Tag PagP for Effective Formation of Inclusion Bodies in Escherichia coli

Methods for efficient insoluble protein production require further exploration. PagP, an Escherichia coli outer membrane protein with high β-sheet content, could function as an efficient fusion partner for inclusion body-targeted expression of recombinant peptides. The primary structure of a given polypeptide determines to a large extent its propensity to aggregate. Herein, aggregation "hot spots" (HSs) in PagP were analyzed using the web-based software AGGRESCAN, leading to identification of a C-terminal region harboring numerous HSs. Moreover, a proline-rich region was found in the β-strands. Substitution of these prolines by residues with high β-sheet propensity and hydrophobicity significantly improved its ability to form aggregates. Consequently, the absolute yields of recombinant antimicrobial peptides Magainin II, Metchnikowin, and Andropin were increased significantly when expressed in fusion with this refined version of PagP. We describe separation of recombinant target proteins expressed in inclusion bodies fused with the tag. An artificial NHT linker peptide with three motifs was implemented for separation and purification of authentic recombinant antimicrobial peptides. IMPORTANCE Fusion tag-induced formation of inclusion bodies provides a powerful means to express unstructured or toxic proteins. For a given fusion tag, how to enhance the formation of inclusion bodies remains to be explored. Our study illustrated that the aggregation HSs in a fusion tag played important roles in mediating its insoluble expression. Efficient production of inclusion bodies could also be implemented by refining its primary structure to form a more stable β-sheet with higher hydrophobicity. This study provides a promising method for improvement of the insoluble expression of recombinant proteins.

Sequence-targeted Peptides Divert Functional Bacterial Amyloid Towards Destabilized Aggregates and Reduce Biofilm Formation

Functional bacterial amyloid provides structural stability in biofilm, making it a promising target for anti-biofilm therapeutics. Fibrils formed by CsgA, the major amyloid component in E. coli are extremely robust and can withstand very harsh conditions. Like other functional amyloids, CsgA contains relatively short aggregation-prone regions (APR) which drive amyloid formation. Here, we demonstrate the use of aggregation-modulating peptides to knock down CsgA protein into aggregates with low stability and altered morphology. Remarkably, these CsgA-peptides also modulate fibrillation of the unrelated functional amyloid protein FapC from Pseudomonas, possibly through recognition of FapC segments with structural and sequence similarity with CsgA. The peptides also reduce the level of biofilm formation in E. coli and P. aeruginosa, demonstrating the potential for selective amyloid targeting to combat bacterial biofilm.

An overview of descriptors to capture protein properties - Tools and perspectives in the context of QSAR modeling

Proteins are important ingredients in food and feed, they are the active components of many pharmaceutical products, and they are necessary, in the form of enzymes, for the success of many technical processes. However, production can be challenging, especially when using heterologous host cells such as bacteria to express and assemble recombinant mammalian proteins. The manufacturability of proteins can be hindered by low solubility, a tendency to aggregate, or inefficient purification. Tools such as in silico protein engineering and models that predict separation criteria can overcome these issues but usually require the complex shape and surface properties of proteins to be represented by a small number of quantitative numeric values known as descriptors, as similarly used to capture the features of small molecules. Here, we review the current status of protein descriptors, especially for application in quantitative structure activity relationship (QSAR) models. First, we describe the complexity of proteins and the properties that descriptors must accommodate. Then we introduce descriptors of shape and surface properties that quantify the global and local features of proteins. Finally, we highlight the current limitations of protein descriptors and propose strategies for the derivation of novel protein descriptors that are more informative.

The C-terminal 32-mer fragment of hemoglobin alpha is an amyloidogenic peptide with antimicrobial properties

Antimicrobial peptides (AMPs) are major components of the innate immune defense. Accumulating evidence suggests that the antibacterial activity of many AMPs is dependent on the formation of amyloid-like fibrils. To identify novel fibril forming AMPs, we generated a spleen-derived peptide library and screened it for the presence of amyloidogenic peptides. This approach led to the identification of a C-terminal 32-mer fragment of alpha-hemoglobin, termed HBA(111-142). The non-fibrillar peptide has membranolytic activity against various bacterial species, while the HBA(111-142) fibrils aggregated bacteria to promote their phagocytotic clearance. Further, HBA(111-142) fibrils selectively inhibited measles and herpes viruses (HSV-1, HSV-2, HCMV), but not SARS-CoV-2, ZIKV and IAV. HBA(111-142) is released from its precursor by ubiquitous aspartic proteases under acidic conditions characteristic at sites of infection and inflammation. Thus, HBA(111-142) is an amyloidogenic AMP that may specifically be generated from a highly abundant precursor during bacterial or viral infection and may play an important role in innate antimicrobial immune responses.

Preclinical safety and efficacy of a therapeutic antibody that targets SARS-CoV-2 at the sotrovimab face but is escaped by Omicron

The recurrent emerging of novel viral variants of concern (VOCs) with evasion of preexisting antibody immunity upholds severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) case numbers and maintains a persistent demand for updated therapies. We selected the patient-derived antibody CV38-142 based on its potency and breadth against the VOCs Alpha, Beta, Gamma, and Delta for preclinical development into a therapeutic. CV38-142 showed in vivo efficacy in a Syrian hamster VOC infection model after post-exposure and therapeutic application and revealed a favorable safety profile in a human protein library screen and tissue cross-reactivity study. Although CV38-142 targets the same viral surface as sotrovimab, which maintains activity against Omicron, CV38-142 did not neutralize the Omicron lineages BA.1 and BA.2. These results highlight the contingencies of developing antibody therapeutics in the context of antigenic drift and reinforce the need to develop broadly neutralizing variant-proof antibodies against SARS-CoV-2.

Machine Learning Approaches in Diagnosis, Prognosis and Treatment Selection of Cardiac Amyloidosis

Cardiac amyloidosis is an uncommon restrictive cardiomyopathy featuring an unregulated amyloid protein deposition that impairs organic function. Early cardiac amyloidosis diagnosis is generally delayed by indistinguishable clinical findings of more frequent hypertrophic diseases. Furthermore, amyloidosis is divided into various groups, according to a generally accepted taxonomy, based on the proteins that make up the amyloid deposits; a careful differentiation between the various forms of amyloidosis is necessary to undertake an adequate therapeutic treatment. Thus, cardiac amyloidosis is thought to be underdiagnosed, which delays necessary therapeutic procedures, diminishing quality of life and impairing clinical prognosis. The diagnostic work-up for cardiac amyloidosis begins with the identification of clinical features, electrocardiographic and imaging findings suggestive or compatible with cardiac amyloidosis, and often requires the histological demonstration of amyloid deposition. One approach to overcome the difficulty of an early diagnosis is the use of automated diagnostic algorithms. Machine learning enables the automatic extraction of salient information from “raw data” without the need for pre-processing methods based on the a priori knowledge of the human operator. This review attempts to assess the various diagnostic approaches and artificial intelligence computational techniques in the detection of cardiac amyloidosis.

A bacterial cold-active dye-decolorizing peroxidase from an Antarctic Pseudomonas strain

DyP (dye-decolorizing peroxidase) enzymes are hemeproteins that catalyze the H₂O₂-dependent oxidation of various molecules and also carry out lignin degradation, albeit with low activity. We identified a dyp gene in the genome of an Antarctic cold-tolerant microbe (Pseudomonas sp. AU10) that codes for a class B DyP. The recombinant protein (rDyP-AU10) was produced using Escherichia coli as a host and purified. We found that rDyP-AU10 is mainly produced as a dimer and has characteristics that resemble psychrophilic enzymes, such as high activity at low temperatures (20 °C) when using 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid (ABTS) and H₂O₂ as substrates, thermo-instability, low content of arginine, and a catalytic pocket surface larger than the DyPs from some mesophilic and thermophilic microbes. We also report the steady-state kinetic parameters of rDyP-AU10 for ABTS, hydroquinone, and ascorbate. Stopped-flow kinetics revealed that Compound I is formed with a rate constant of (2.07 ± 0.09) × 10⁶ M^-1 s^-1 at pH 5 and that this is the predominant species during turnover. The enzyme decolors dyes and modifies kraft lignin, suggesting that this enzyme may have potential use in bioremediation and in the cellulose and biofuel industries. KEY POINTS: • An Antarctic Pseudomonas strain produces a dye-decolorizing peroxidase. • The recombinant enzyme (rDyP-AU10) was produced in E. coli and purified. • rDyP-AU10 showed high activity at low temperatures. • rDyP-AU10 is potentially useful for biotechnological applications.

Common pathophysiology for ANXA11 disorders caused by aspartate 40 variants

OBJECTIVE

Mutations in ANXA11 cause amyotrophic lateral sclerosis (ALS) and have recently been identified as a cause of multisystem proteinopathy and adult-onset muscular dystrophy. These conditions are adult-onset diseases and result from the substitution of Aspartate 40 (Asp40) for an apolar residue in the intrinsically disordered domain (IDD) of ANXA11. Some ALS-related variants are known to affect ANXA11 IDD; however, the mechanism by which the myopathy occurs is unknown.

METHODS

Genetic analysis was performed using WES-trio. For the study of variant pathogenicity, we used recombinant proteins, muscle biopsy, and fibroblasts.

RESULTS

Here we describe an individual with severe and rapidly progressive childhood-onset oculopharyngeal muscular dystrophy who carries a new ANXA11 variant at position Asp40 (p.Asp40Ile; c.118_119delGAinsAT). p.Asp40Ile is predicted to enhance the aggregation propensity of ANXA11 to a greater extent than other changes affecting this residue. In vitro studies using recombinant ANXA11p.Asp40Ile showed abnormal phase separation and confirmed this variant is more aggregation-prone than the ALS-associated variant ANXA11p.Asp40Gly . The study of the patient's fibroblasts revealed defects in stress granules dynamics and clearance, and muscle histopathology showed a myopathic pattern with ANXA11 protein aggregates. Super-resolution imaging showed aggregates expressed as pearl strips or large complex structures in the sarcoplasm, and as layered subsarcolemmal chains probably reflecting ANXA11 multifunctionality.

INTERPRETATION

We demonstrate common pathophysiology for disorders associated with ANXA11 Asp40 allelic variants. Clinical phenotypes may result from different deleterious impacts of variants upon ANXA11 stability against aggregation, and differential muscle or motor neuron dysfunction expressed as a temporal and tissue-specific continuum.

Amyloidogenic proteins in the SARS-CoV and SARS-CoV-2 proteomes

The phenomenon of protein aggregation is associated with a wide range of human diseases. Our knowledge of the aggregation behaviour of viral proteins, however, is still rather limited. Here, we investigated this behaviour in the SARS-CoV and SARS-CoV-2 proteomes. An initial analysis using a panel of sequence-based predictors suggested the presence of multiple aggregation-prone regions (APRs) in these proteomes and revealed a strong aggregation propensity in some SARS-CoV-2 proteins. We then studied the in vitro aggregation of predicted aggregation-prone SARS-CoV and SARS-CoV-2 proteins and protein regions, including the signal sequence peptide and fusion peptides 1 and 2 of the spike protein, a peptide from the NSP6 protein, and the ORF10 and NSP11 proteins. Our results show that these peptides and proteins can form amyloid aggregates. We used circular dichroism spectroscopy to reveal the presence of β-sheet rich cores in aggregates and X-ray diffraction and Raman spectroscopy to confirm the formation of amyloid structures. Furthermore, we demonstrated that SARS-CoV-2 NSP11 aggregates are toxic to mammalian cell cultures. These results motivate further studies about the possible role of aggregation of SARS proteins in protein misfolding diseases and other human conditions.

The Strategies of Development of New Non-Toxic Inhibitors of Amyloid Formation

In recent years, due to the aging of the population and the development of diagnostic medicine, the number of identified diseases associated with the accumulation of amyloid proteins has increased. Some of these proteins are known to cause a number of degenerative diseases in humans, such as amyloid-beta (Aβ) in Alzheimer's disease (AD), α-synuclein in Parkinson's disease (PD), and insulin and its analogues in insulin-derived amyloidosis. In this regard, it is important to develop strategies for the search and development of effective inhibitors of amyloid formation. Many studies have been carried out aimed at elucidating the mechanisms of amyloid aggregation of proteins and peptides. This review focuses on three amyloidogenic peptides and proteins-Aβ, α-synuclein, and insulin-for which we will consider amyloid fibril formation mechanisms and analyze existing and prospective strategies for the development of effective and non-toxic inhibitors of amyloid formation. The development of non-toxic inhibitors of amyloid will allow them to be used more effectively for the treatment of diseases associated with amyloid.

A guide to studying protein aggregation

Disrupted protein folding or decreased protein stability can lead to the accumulation of (partially) un- or misfolded proteins, which ultimately cause the formation of protein aggregates. Much of the interest in protein aggregation is associated with its involvement in a wide range of human diseases and the challenges it poses for large-scale biopharmaceutical manufacturing and formulation of therapeutic proteins and peptides. On the other hand, protein aggregates can also be functional, as observed in nature, which triggered its use in the development of biomaterials or therapeutics as well as for the improvement of food characteristics. Thus, unmasking the various steps involved in protein aggregation is critical to obtain a better understanding of the underlying mechanism of amyloid formation. This knowledge will allow a more tailored development of diagnostic methods and treatments for amyloid-associated diseases, as well as applications in the fields of new (bio)materials, food technology and therapeutics. However, the complex and dynamic nature of the aggregation process makes the study of protein aggregation challenging. To provide guidance on how to analyse protein aggregation, in this review we summarize the most commonly investigated aspects of protein aggregation with some popular corresponding methods.

Bacterial production and biophysical characterization of a hard-to-fold scFv against myeloid leukemia cell surface marker, IL-1RAP

BACKGROUND

Interleukin-1 receptor accessory protein (IL-1RAP) is one of the most promising therapeutic targets proposed for myeloid leukemia. Antibodies (Abs) specific to IL-1RAP could be valuable tools for targeted therapy of this lethal malignancy. This study is about the preparation of a difficult-to-produce single-chain variable fragment (scFv) construct against the membrane-bound isoform of human IL-1RAP using Escherichia coli (E. coli).

METHODS

Different approaches were examined for refolding and characterization of the scFv. Binding activities of antibody fragments were comparatively evaluated using cell-based enzyme-linked immunosorbent assay (ELISA). Homogeneity and secondary structure of selected scFv preparation were analyzed using analytical size exclusion chromatography (SEC) and circular dichroism (CD) spectroscopy, respectively. The activity of the selected preparation was evaluated after long-term storage, repeated freeze-thaw cycles, or following incubation with normal and leukemic serum.

RESULTS

Strategies for soluble expression of the scFv failed. Even with the help of Trx, ≥ 98% of proteins were expressed as inclusion bodies (IBs). Among three different refolding methods, the highest recovery rate was obtained from the dilution method (11.2%). Trx-tag substantially enhanced the expression level (18%, considering the molecular weight (MW) differences), recovery rate (˃1.6-fold), and binding activity (˃2.6-fold increase in absorbance450nm). The produced scFv exhibited expected secondary structure as well as acceptable bio-functionality, homogeneity, and stability.

CONCLUSION

We were able to produce  21 mg/L culture functional and stable anti-IL-1RAP scFv via recovering IBs by pulse dilution procedure. The produced scFv as a useful targeting agent could be used in scheming new therapeutics or diagnostics for myeloid malignancies.

Plant Defense Elicitation by the Hydrophobin Cerato-Ulmin and Correlation with Its Structural Features

Cerato-ulmin (CU) is a 75-amino-acid-long protein that belongs to the hydrophobin family. It self-assembles at hydrophobic-hydrophilic interfaces, forming films that reverse the wettability properties of the bound surface: a capability that may confer selective advantages to the fungus in colonizing and infecting elm trees. Here, we show for the first time that CU can elicit a defense reaction (induction of phytoalexin synthesis and ROS production) in non-host plants (Arabidopsis) and exerts its eliciting capacity more efficiently when in its soluble monomeric form. We identified two hydrophobic clusters on the protein's loops endowed with dynamical and physical properties compatible with the possibility of reversibly interconverting between a disordered conformation and a β-strand-rich conformation when interacting with hydrophilic or hydrophobic surfaces. We propose that the plasticity of those loops may be part of the molecular mechanism that governs the protein defense elicitation capability.

Exploring cryptic amyloidogenic regions in prion-like proteins from plants

Prion-like domains (PrLDs) are intrinsically disordered regions (IDRs) of low sequence complexity with a similar composition to yeast prion domains. PrLDs-containing proteins have been involved in different organisms' regulatory processes. Regions of moderate amyloid propensity within IDRs have been shown to assemble autonomously into amyloid fibrils. These sequences tend to be rich in polar amino acids and often escape from the detection of classical bioinformatics screenings that look for highly aggregation-prone hydrophobic sequence stretches. We defined them as cryptic amyloidogenic regions (CARs) and recently developed an integrated database that collects thousands of predicted CARs in IDRs. CARs seem to be evolutionary conserved among disordered regions because of their potential to stablish functional contacts with other biomolecules. Here we have focused on identifying and characterizing CARs in prion-like proteins (pCARs) from plants, a lineage that has been poorly studied in comparison with other prionomes. We confirmed the intrinsic amyloid potential for a selected pCAR from Arabidopsis thaliana and explored functional enrichments and compositional bias of pCARs in plant prion-like proteins.

Connection between MHC class II binding and aggregation propensity: The antigenic peptide 10 of Paracoccidioides brasiliensis as a benchmark study

The aggregation of epitopes that are also able to bind major histocompatibility complex (MHC) alleles raises questions around the potential connection between the formation of epitope aggregates and their affinities to MHC receptors. We first performed a general bioinformatic assessment over a public dataset of MHC class II epitopes, finding that higher experimental binding correlates with higher aggregation-propensity predictors. We then focused on the case of P10, an epitope used as a vaccine candidate against Paracoccidioides brasiliensis that aggregates into amyloid fibrils. We used a computational protocol to design variants of the P10 epitope to study the connection between the binding stabilities towards human MHC class II alleles and their aggregation propensities. The binding of the designed variants was tested experimentally, as well as their aggregation capacity. High-affinity MHC class II binders in vitro were more disposed to aggregate forming amyloid fibrils capable of binding Thioflavin T and congo red, while low affinity MHC class II binders remained soluble or formed rare amorphous aggregates. This study shows a possible connection between the aggregation propensity of an epitope and its affinity for the MHC class II cleft.

PRIMA-1 inhibits Y220C p53 amyloid aggregation and synergizes with cisplatin in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths worldwide. Although many therapeutic options are available, several factors, including the presence of p53 mutations, impact tumor development and therapeutic resistance. TP53 is the second most frequently mutated gene in HCC, comprising more than 30% of cases. Mutations in p53 result in the formation of amyloid aggregates that promote tumor progression. The use of PRIMA-1, a small molecule capable of restoring p53, is a therapeutic strategy to pharmacologically target the amyloid state mutant p53. In this study, we characterize an HCC mutant p53 model for the study of p53 amyloid aggregation in HCC cell lines, from in silico analysis of p53 mutants to a 3D-cell culture model and demonstrate the unprecedented inhibition of Y220C mutant p53 aggregation by PRIMA-1. In addition, our data show beneficial effects of PRIMA-1 in several "gain of function" properties of mutant-p53 cancer cells, including migration, adhesion, proliferation, and drug resistance. We also demonstrate that the combination of PRIMA-1 and cisplatin is a promising approach for HCC therapy. Taken together, our data support the premise that targeting the amyloid-state of mutant p53 may be an attractive therapeutic approach for HCC, and highlight PRIMA-1 as a new candidate for combination therapy with cisplatin.

High concentration formulation developability approaches and considerations

The growing need for biologics to be administered subcutaneously and ocularly, coupled with certain indications requiring high doses, has resulted in an increase in drug substance (DS) and drug product (DP) protein concentrations. With this increase, more emphasis must be placed on identifying critical physico-chemical liabilities during drug development, including protein aggregation, precipitation, opalescence, particle formation, and high viscosity. Depending on the molecule, liabilities, and administration route, different formulation strategies can be used to overcome these challenges. However, due to the high material requirements, identifying optimal conditions can be slow, costly, and often prevent therapeutics from moving rapidly into the clinic/market. In order to accelerate and derisk development, new experimental and in-silico methods have emerged that can predict high concentration liabilities. Here, we review the challenges in developing high concentration formulations, the advances that have been made in establishing low mass and high-throughput predictive analytics, and advances in in-silico tools and algorithms aimed at identifying risks and understanding high concentration protein behavior.