1
|
Liu Y, Xiang J, Gong H, Yu T, Gao M, Huang Y. The Regulation of TDP-43 Structure and Phase Transitions: A Review. Protein J 2025; 44:113-132. [PMID: 39987392 DOI: 10.1007/s10930-025-10261-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/08/2025] [Indexed: 02/24/2025]
Abstract
The transactive response DNA binding protein 43 (TDP-43) is an RNA/DNA-binding protein that is involved in a number of cellular functions, including RNA processing and alternative splicing, RNA transport and translation, and stress granule assembly. It has attracted significant attention for being the primary component of cytoplasmic inclusions in patients with amyotrophic lateral sclerosis or frontotemporal dementia. Mounting evidence suggests that both cytoplasmic aggregation of TDP-43 and loss of nuclear TDP-43 function contribute to TDP-43 pathology. Furthermore, recent studies have demonstrated that TDP-43 is an important component of many constitutive or stress-induced biomolecular condensates. Dysregulation or liquid-to-gel transition of TDP-43 condensates can lead to alterations in TDP-43 function and the formation of TDP-43 amyloid fibrils. In this review, we summarize recent research progress on the structural characterization of TDP-43 and the TDP-43 phase transition. In particular, the roles that disease-associated genetic mutations, post-translational modifications, and extrinsic stressors play in the transitions among TDP-43 monomers, liquid condensates, solid condensates, and fibrils are discussed. Finally, we discuss the effectiveness of available regulators of TDP-43 phase separation and aggregation. Understanding the underlying mechanisms that drive the pathological transformation of TDP-43 could help develop therapeutic strategies for TDP-43 pathology.
Collapse
Affiliation(s)
- Yanqing Liu
- Cooperative Innovation Center of Industrial Fermentation (Ministry of Education & Hubei Province), Hubei University of Technology, Wuhan, 430068, China
- Hubei Key Laboratory of Industrial Microbiology, Hubei University of Technology, Wuhan, 430068, China
- Key Laboratory of Industrial Fermentation (Ministry of Education), Hubei University of Technology, Wuhan, 430068, China
| | - Jiani Xiang
- Cooperative Innovation Center of Industrial Fermentation (Ministry of Education & Hubei Province), Hubei University of Technology, Wuhan, 430068, China
- Hubei Key Laboratory of Industrial Microbiology, Hubei University of Technology, Wuhan, 430068, China
- Key Laboratory of Industrial Fermentation (Ministry of Education), Hubei University of Technology, Wuhan, 430068, China
| | - Hang Gong
- Cooperative Innovation Center of Industrial Fermentation (Ministry of Education & Hubei Province), Hubei University of Technology, Wuhan, 430068, China
- Hubei Key Laboratory of Industrial Microbiology, Hubei University of Technology, Wuhan, 430068, China
- Key Laboratory of Industrial Fermentation (Ministry of Education), Hubei University of Technology, Wuhan, 430068, China
| | - Tianxiong Yu
- Cooperative Innovation Center of Industrial Fermentation (Ministry of Education & Hubei Province), Hubei University of Technology, Wuhan, 430068, China
- Hubei Key Laboratory of Industrial Microbiology, Hubei University of Technology, Wuhan, 430068, China
- Key Laboratory of Industrial Fermentation (Ministry of Education), Hubei University of Technology, Wuhan, 430068, China
| | - Meng Gao
- Cooperative Innovation Center of Industrial Fermentation (Ministry of Education & Hubei Province), Hubei University of Technology, Wuhan, 430068, China.
- Hubei Key Laboratory of Industrial Microbiology, Hubei University of Technology, Wuhan, 430068, China.
- Key Laboratory of Industrial Fermentation (Ministry of Education), Hubei University of Technology, Wuhan, 430068, China.
| | - Yongqi Huang
- Cooperative Innovation Center of Industrial Fermentation (Ministry of Education & Hubei Province), Hubei University of Technology, Wuhan, 430068, China.
- Hubei Key Laboratory of Industrial Microbiology, Hubei University of Technology, Wuhan, 430068, China.
- Key Laboratory of Industrial Fermentation (Ministry of Education), Hubei University of Technology, Wuhan, 430068, China.
| |
Collapse
|
2
|
Kreutzberger MAB, Sonani RR, Egelman EH. Cryo-EM reconstruction of helical polymers: Beyond the simple cases. Q Rev Biophys 2024; 57:e16. [PMID: 39658802 PMCID: PMC11730170 DOI: 10.1017/s0033583524000155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2024]
Abstract
Helices are one of the most frequently encountered symmetries in biological assemblies. Helical symmetry has been exploited in electron microscopic studies as a limited number of filament images, in principle, can provide all the information needed to do a three-dimensional reconstruction of a polymer. Over the past 25 years, three-dimensional reconstructions of helical polymers from cryo-EM images have shifted completely from Fourier-Bessel methods to single-particle approaches. The single-particle approaches have allowed people to surmount the problem that very few biological polymers are crystalline in order, and despite the flexibility and heterogeneity present in most of these polymers, reaching a resolution where accurate atomic models can be built has now become the standard. While determining the correct helical symmetry may be very simple for something like F-actin, for many other polymers, particularly those formed from small peptides, it can be much more challenging. This review discusses why symmetry determination can be problematic, and why trial-and-error methods are still the best approach. Studies of many macromolecular assemblies, such as icosahedral capsids, have usually found that not imposing symmetry leads to a great reduction in resolution while at the same time revealing possibly interesting asymmetric features. We show that for certain helical assemblies asymmetric reconstructions can sometimes lead to greatly improved resolution. Further, in the case of supercoiled flagellar filaments from bacteria and archaea, we show that the imposition of helical symmetry can not only be wrong, but is not necessary, and obscures the mechanisms whereby these filaments supercoil.
Collapse
Affiliation(s)
- Mark A B Kreutzberger
- Department of Biochemistry and Molecular Genetics, University of Virginia Medical School, Charlottesville, VA, USA
| | - Ravi R Sonani
- Department of Biochemistry and Molecular Genetics, University of Virginia Medical School, Charlottesville, VA, USA
| | - Edward H Egelman
- Department of Biochemistry and Molecular Genetics, University of Virginia Medical School, Charlottesville, VA, USA
| |
Collapse
|
3
|
Khan MA. Targeting Iron Responsive Elements (IREs) of APP mRNA into Novel Therapeutics to Control the Translation of Amyloid-β Precursor Protein in Alzheimer's Disease. Pharmaceuticals (Basel) 2024; 17:1669. [PMID: 39770511 PMCID: PMC11677800 DOI: 10.3390/ph17121669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2024] [Revised: 11/30/2024] [Accepted: 12/04/2024] [Indexed: 01/11/2025] Open
Abstract
The hallmark of Alzheimer's disease (AD) is the buildup of amyloid-β (Aβ), which is produced when the amyloid precursor protein (APP) misfolds and deposits as neurotoxic plaques in the brain. A functional iron responsive element (IRE) RNA stem loop is encoded by the APP 5'-UTR and may be a target for regulating the production of Alzheimer's amyloid precursor protein. Since modifying Aβ protein expression can give anti-amyloid efficacy and protective brain iron balance, targeted regulation of amyloid protein synthesis through modulation of 5'-UTR sequence function is a novel method for the prospective therapy of Alzheimer's disease. Numerous mRNA interference strategies target the 2D RNA structure, even though messenger RNAs like tRNAs and rRNAs can fold into complex, three-dimensional structures, adding even another level of complexity. The IRE family is among the few known 3D mRNA regulatory elements. This review seeks to describe the structural and functional aspects of IREs in transcripts, including that of the amyloid precursor protein, that are relevant to neurodegenerative diseases, including AD. The mRNAs encoding the proteins involved in iron metabolism are controlled by this family of similar base sequences. Like ferritin IRE RNA in their 5'-UTR, iron controls the production of APP in their 5'-UTR. Iron misregulation by iron regulatory proteins (IRPs) can also be investigated and contrasted using measurements of the expression levels of tau production, Aβ, and APP. The development of AD is aided by iron binding to Aβ, which promotes Aβ aggregation. The development of small chemical therapeutics to control IRE-modulated expression of APP is increasingly thought to target messenger RNAs. Thus, IRE-modulated APP expression in AD has important therapeutic implications by targeting mRNA structures.
Collapse
Affiliation(s)
- Mateen A Khan
- Department of Life Science, College of Science and General Studies, Alfaisal University, Riyadh 11533, Saudi Arabia
| |
Collapse
|
4
|
Bartolomé-Nafría A, García-Pardo J, Ventura S. Mutations in human prion-like domains: pathogenic but not always amyloidogenic. Prion 2024; 18:28-39. [PMID: 38512820 PMCID: PMC10962614 DOI: 10.1080/19336896.2024.2329186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 03/04/2024] [Accepted: 03/06/2024] [Indexed: 03/23/2024] Open
Abstract
Heterogeneous nuclear ribonucleoproteins (hnRNPs) are multifunctional proteins with integral roles in RNA metabolism and the regulation of alternative splicing. These proteins typically contain prion-like domains of low complexity (PrLDs or LCDs) that govern their assembly into either functional or pathological amyloid fibrils. To date, over 60 mutations targeting the LCDs of hnRNPs have been identified and associated with a spectrum of neurodegenerative diseases including amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), and Alzheimer's disease (AD). The cryo-EM structures of pathological and functional fibrils formed by different hnRNPs have been recently elucidated, including those of hnRNPA1, hnRNPA2, hnRNPDL-2, TDP-43, and FUS. In this review, we discuss the structural features of these amyloid assemblies, placing particular emphasis on scrutinizing the impact of prevalent disease-associated mutations mapping within their LCDs. By performing systematic energy calculations, we reveal a prevailing trend of destabilizing effects induced by these mutations in the amyloid structure, challenging the traditionally assumed correlation between pathogenicity and amyloidogenic propensity. Understanding the molecular basis of this discrepancy might provide insights for developing targeted therapeutic strategies to combat hnRNP-associated diseases.
Collapse
Affiliation(s)
- Andrea Bartolomé-Nafría
- Institut de Biotecnologia i de Biomedicina (IBB) and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Javier García-Pardo
- Institut de Biotecnologia i de Biomedicina (IBB) and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Salvador Ventura
- Institut de Biotecnologia i de Biomedicina (IBB) and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Barcelona, Spain
| |
Collapse
|
5
|
Jang S, Bedwell G, Singh S, Yu H, Arnarson B, Singh P, Radhakrishnan R, Douglas A, Ingram Z, Freniere C, Akkermans O, Sarafianos S, Ambrose Z, Xiong Y, Anekal P, Montero Llopis P, KewalRamani V, Francis A, Engelman A. HIV-1 usurps mixed-charge domain-dependent CPSF6 phase separation for higher-order capsid binding, nuclear entry and viral DNA integration. Nucleic Acids Res 2024; 52:11060-11082. [PMID: 39258548 PMCID: PMC11472059 DOI: 10.1093/nar/gkae769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Revised: 08/13/2024] [Accepted: 08/25/2024] [Indexed: 09/12/2024] Open
Abstract
HIV-1 integration favors nuclear speckle (NS)-proximal chromatin and viral infection induces the formation of capsid-dependent CPSF6 condensates that colocalize with nuclear speckles (NSs). Although CPSF6 displays liquid-liquid phase separation (LLPS) activity in vitro, the contributions of its different intrinsically disordered regions, which includes a central prion-like domain (PrLD) with capsid binding FG motif and C-terminal mixed-charge domain (MCD), to LLPS activity and to HIV-1 infection remain unclear. Herein, we determined that the PrLD and MCD both contribute to CPSF6 LLPS activity in vitro. Akin to FG mutant CPSF6, infection of cells expressing MCD-deleted CPSF6 uncharacteristically arrested at the nuclear rim. While heterologous MCDs effectively substituted for CPSF6 MCD function during HIV-1 infection, Arg-Ser domains from related SR proteins were largely ineffective. While MCD-deleted and wildtype CPSF6 proteins displayed similar capsid binding affinities, the MCD imparted LLPS-dependent higher-order binding and co-aggregation with capsids in vitro and in cellulo. NS depletion reduced CPSF6 puncta formation without significantly affecting integration into NS-proximal chromatin, and appending the MCD onto a heterologous capsid binding protein partially restored virus nuclear penetration and integration targeting in CPSF6 knockout cells. We conclude that MCD-dependent CPSF6 condensation with capsids underlies post-nuclear incursion for viral DNA integration and HIV-1 pathogenesis.
Collapse
Affiliation(s)
- Sooin Jang
- Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Gregory J Bedwell
- Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Satya P Singh
- Institute of Molecular Biophysics, Department of Biological Sciences, Florida State University, Tallahassee, FL 32304, USA
| | - Hyun Jae Yu
- Model Development Section, Cancer Innovation Laboratory, National Cancer Institute, Frederick, MD 21702, USA
| | - Bjarki Arnarson
- Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Parmit K Singh
- Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Rajalingam Radhakrishnan
- Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - AidanDarian W Douglas
- Institute of Molecular Biophysics, Department of Biological Sciences, Florida State University, Tallahassee, FL 32304, USA
| | - Zachary M Ingram
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA 15219, USA
| | - Christian Freniere
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06511, USA
| | - Onno Akkermans
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Stefan G Sarafianos
- Center for ViroScience and Cure, Laboratory of Biochemical Pharmacology, Department of Pediatrics, School of Medicine, Emory University, Atlanta, GA 30322, USA
| | - Zandrea Ambrose
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA 15219, USA
| | - Yong Xiong
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06511, USA
| | - Praju V Anekal
- MicRoN Core, Harvard Medical School, Boston, MA 02215, USA
| | | | - Vineet N KewalRamani
- Model Development Section, Cancer Innovation Laboratory, National Cancer Institute, Frederick, MD 21702, USA
| | - Ashwanth C Francis
- Institute of Molecular Biophysics, Department of Biological Sciences, Florida State University, Tallahassee, FL 32304, USA
| | - Alan N Engelman
- Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| |
Collapse
|
6
|
Zalewski M, Iglesias V, Bárcenas O, Ventura S, Kmiecik S. Aggrescan4D: A comprehensive tool for pH-dependent analysis and engineering of protein aggregation propensity. Protein Sci 2024; 33:e5180. [PMID: 39324697 PMCID: PMC11425640 DOI: 10.1002/pro.5180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2024] [Revised: 09/03/2024] [Accepted: 09/06/2024] [Indexed: 09/27/2024]
Abstract
Aggrescan4D (A4D) is an advanced computational tool designed for predicting protein aggregation, leveraging structural information and the influence of pH. Building upon its predecessor, Aggrescan3D (A3D), A4D has undergone numerous enhancements aimed at assisting the improvement of protein solubility. This manuscript reviews A4D's updated functionalities and explains the fundamental principles behind its pH-dependent calculations. Additionally, it presents an antibody case study to evaluate its performance in comparison with other structure-based predictors. Notably, A4D integrates advanced protein engineering protocols with pH-dependent calculations, enhancing its utility in advising solubility-enhancing mutations. A4D considers the impact of structural flexibility on aggregation propensities, and includes a large set of precalculated predictions. These capabilities should help to open new avenues for both understanding and managing protein aggregation. A4D is accessible through a dedicated web server at https://biocomp.chem.uw.edu.pl/a4d/.
Collapse
Affiliation(s)
- Mateusz Zalewski
- Faculty of Chemistry, Biological and Chemical Research Center, University of Warsaw, Warsaw, Poland
| | - Valentin Iglesias
- Departament de Bioquímica i Biologia Molecular, Institut de Biotecnologia i de Biomedicina, Universitat Autònoma de Barcelona, Barcelona, Spain
- Clinical Research Centre, Medical University of Białystok, Białystok, Poland
| | - Oriol Bárcenas
- Departament de Bioquímica i Biologia Molecular, Institut de Biotecnologia i de Biomedicina, Universitat Autònoma de Barcelona, Barcelona, Spain
- Institute of Advanced Chemistry of Catalonia (IQAC), CSIC, Barcelona, Spain
| | - Salvador Ventura
- Departament de Bioquímica i Biologia Molecular, Institut de Biotecnologia i de Biomedicina, Universitat Autònoma de Barcelona, Barcelona, Spain
- Hospital Universitari Parc Taulí, Institut d'Investigació i Innovació Parc Taulí (I3PT-CERCA), Universitat Autònoma de Barcelona, Sabadell, Spain
| | - Sebastian Kmiecik
- Faculty of Chemistry, Biological and Chemical Research Center, University of Warsaw, Warsaw, Poland
| |
Collapse
|