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Identifying amyloid-related diseases by mapping mutations in low-complexity protein domains to pathologies.

ABSTRACT: Proteins including FUS, hnRNPA2, and TDP-43 reversibly aggregate into amyloid-like fibrils through interactions of their low-complexity domains (LCDs). Mutations in LCDs can promote irreversible amyloid aggregation and disease. We introduce a computational approach to identify mutations in LCDs of disease-associated proteins predicted to increase propensity for amyloid aggregation. We identify several disease-related mutations in the intermediate filament protein keratin-8 (KRT8). Atomic structures of wild-type and mutant KRT8 segments confirm the transition to a pleated strand capable of amyloid formation. Biochemical analysis reveals KRT8 forms amyloid aggregates, and the identified mutations promote aggregation. Aggregated KRT8 is found in Mallory-Denk bodies, observed in hepatocytes of livers with alcoholic steatohepatitis (ASH). We demonstrate that ethanol promotes KRT8 aggregation, and KRT8 amyloids co-crystallize with alcohol. Lastly, KRT8 aggregation can be seeded by liver extract from people with ASH, consistent with the amyloid nature of KRT8 aggregates and the classification of ASH as an amyloid-related condition.

SUBMITTER: Murray KA

PROVIDER: S-EPMC9205782 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Identifying amyloid-related diseases by mapping mutations in low-complexity protein domains to pathologies.

Murray Kevin A KA Hughes Michael P MP Hu Carolyn J CJ Sawaya Michael R MR Salwinski Lukasz L Pan Hope H French Samuel W SW Seidler Paul M PM Eisenberg David S DS

Nature structural & molecular biology 20220530 6

Proteins including FUS, hnRNPA2, and TDP-43 reversibly aggregate into amyloid-like fibrils through interactions of their low-complexity domains (LCDs). Mutations in LCDs can promote irreversible amyloid aggregation and disease. We introduce a computational approach to identify mutations in LCDs of disease-associated proteins predicted to increase propensity for amyloid aggregation. We identify several disease-related mutations in the intermediate filament protein keratin-8 (KRT8). Atomic structu ...[more]

PMID: 35637421

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Project description:Understanding complexity in healthcare has the potential to reduce decision and treatment uncertainty. Therefore, identifying both patient and task complexity may offer better task allocation and design recommendation for next-generation health information technology system design.To identify specific complexity-contributing factors in the infectious disease domain and the relationship with the complexity perceived by clinicians.We observed and audio recorded clinical rounds of three infectious disease teams. Thirty cases were observed for a period of four consecutive days. Transcripts were coded based on clinical complexity-contributing factors from the clinical complexity model. Ratings of complexity on day 1 for each case were collected. We then used statistical methods to identify complexity-contributing factors in relationship to perceived complexity of clinicians.A factor analysis (principal component extraction with varimax rotation) of specific items revealed three factors (eigenvalues>2.0) explaining 47% of total variance, namely task interaction and goals (10 items, 26%, Cronbach's Alpha=0.87), urgency and acuity (6 items, 11%, Cronbach's Alpha=0.67), and psychosocial behavior (4 items, 10%, Cronbach's alpha=0.55). A linear regression analysis showed no statistically significant association between complexity perceived by the physicians and objective complexity, which was measured from coded transcripts by three clinicians (Multiple R-squared=0.13, p=0.61). There were no physician effects on the rating of perceived complexity.Task complexity contributes significantly to overall complexity in the infectious diseases domain. The different complexity-contributing factors found in this study can guide health information technology system designers and researchers for intuitive design. Thus, decision support tools can help reduce the specific complexity-contributing factors. Future studies aimed at understanding clinical domain-specific complexity-contributing factors can ultimately improve task allocation and design for intuitive clinical reasoning.

Project description:BackgroundIn both prokaryotic and eukaryotic proteins, repeated occurrence of a single or a group of few amino acids are found. These regions are termed as low complexity regions (LCRs). It has been observed that amino acid bias in LCR is directly linked to their uncontrolled expansion and amyloid formation. But a comparative analysis of the behavior of LCR based on their constituent amino acids and their association with amyloidogenic propensity is not available.MethodsFirstly we grouped all LCRs on the basis of their composition: homo-polymers, positively charged amino acids, negatively charged amino acids, polar amino acids and hydrophobic amino acids. We analyzed the compositional pattern of LCRs in each group and their propensity to form amyloids. The functional characteristics of proteins containing different groups of LCRs were explored using DAVID. In addition, we also analyzed the classes, pathways and functions of human proteins that form amyloids in LCRs.ResultsAmong homopolymeric LCRs, the most common was Gln repeats. LCRs composed of repeats of Met and aromatic amino acids were amongst the least occurring. The results revealed that LCRs composed of negatively charged and polar amino acids were more common in comparison to LCRs formed by positively charged and hydrophobic amino acids. We also noted that generally proteins with LCRs were involved in transcription but those with Gly repeats were associated to translational activities. Our analysis suggests that proteins in which LCR is composed of hydrophobic residues are more prone toward amyloid formation. We also found that the human proteins with amyloid forming LCRs were generally involved in binding and catalytic activity.DiscussionThe presented analysis summarizes the most common and least occurring LCRs in proteins. Our results show that though repeats of Gln are the most abundant but Asn repeats make longest stretch of low complexity. The results showed that potential of LCRs to form amyloids varies with their amino acid composition.

Dataset Information

Identifying amyloid-related diseases by mapping mutations in low-complexity protein domains to pathologies.

Publications

Identifying amyloid-related diseases by mapping mutations in low-complexity protein domains to pathologies.

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