Development of an α-synuclein positron emission tomography tracer for imaging synucleinopathies.

Synucleinopathies are characterized by the accumulation of α-synuclein (α-Syn) aggregates in the brain. Positron emission tomography (PET) imaging of synucleinopathies requires radiopharmaceuticals that selectively bind α-Syn deposits. We report the identification of a brain permeable and rapid washout PET tracer [18F]-F0502B, which shows high binding affinity for α-Syn, but not for Aß or Tau fibrils, and preferential binding to α-Syn aggregates in the brain sections. Employing several cycles of counter screenings with in vitro fibrils, intraneuronal aggregates, and neurodegenerative disease brain sections from several mice models and human subjects, [18F]-F0502B images α-Syn deposits in the brains of mouse and non-human primate PD models. We further determined the atomic structure of the α-Syn fibril-F0502B complex by cryo-EM and revealed parallel diagonal stacking of F0502B on the fibril surface through an intense noncovalent bonding network via inter-ligand interactions. Therefore, [18F]-F0502B is a promising lead compound for imaging aggregated α-Syn in synucleinopathies.

Regulation and functions of non-m6A mRNA modifications.

Nucleobase modifications are prevalent in eukaryotic mRNA and their discovery has resulted in the emergence of epitranscriptomics as a research field. The most abundant internal (non-cap) mRNA modification is N6-methyladenosine (m6A), the study of which has revolutionized our understanding of post-transcriptional gene regulation. In addition, numerous other mRNA modifications are gaining great attention because of their major roles in RNA metabolism, immunity, development and disease. In this Review, we focus on the regulation and function of non-m6A modifications in eukaryotic mRNA, including pseudouridine (Ψ), N6,2'-O-dimethyladenosine (m6Am), N1-methyladenosine (m1A), inosine, 5-methylcytidine (m5C), N4-acetylcytidine (ac4C), 2'-O-methylated nucleotide (Nm) and internal N7-methylguanosine (m7G). We highlight their regulation, distribution, stoichiometry and known roles in mRNA metabolism, such as mRNA stability, translation, splicing and export. We also discuss their biological consequences in physiological and pathological processes. In addition, we cover research techniques to further study the non-m6A mRNA modifications and discuss their potential future applications.

Phase Separation of Disease-Associated SHP2 Mutants Underlies MAPK Hyperactivation.

The non-receptor protein tyrosine phosphatase (PTP) SHP2, encoded by PTPN11, plays an essential role in RAS-mitogen-activated protein kinase (MAPK) signaling during normal development. It has been perplexing as to why both enzymatically activating and inactivating mutations in PTPN11 result in human developmental disorders with overlapping clinical manifestations. Here, we uncover a common liquid-liquid phase separation (LLPS) behavior shared by these disease-associated SHP2 mutants. SHP2 LLPS is mediated by the conserved well-folded PTP domain through multivalent electrostatic interactions and regulated by an intrinsic autoinhibitory mechanism through conformational changes. SHP2 allosteric inhibitors can attenuate LLPS of SHP2 mutants, which boosts SHP2 PTP activity. Moreover, disease-associated SHP2 mutants can recruit and activate wild-type (WT) SHP2 in LLPS to promote MAPK activation. These results not only suggest that LLPS serves as a gain-of-function mechanism involved in the pathogenesis of SHP2-associated human diseases but also provide evidence that PTP may be regulated by LLPS that can be therapeutically targeted.

Better Together: A Hybrid Amyloid Signals Necroptosis.

A new solid-state NMR study determines the high-resolution hetero-amyloid structure of the RIPK1-RIPK3 signaling complex that is involved in mediating necroptosis. The structure demonstrates specific formation of hetero-amyloids over homo-amyloids and the structural basis for a functional amyloid to act as a platform to recruit and activate downstream partners in intracellular signaling.

PARP5A and RNF146 phase separation restrains RIPK1-dependent necroptosis.

Phase separation is a vital mechanism that mediates the formation of biomolecular condensates and their functions. Necroptosis is a lytic form of programmed cell death mediated by RIPK1, RIPK3, and MLKL downstream of TNFR1 and has been implicated in mediating many human diseases. However, whether necroptosis is regulated by phase separation is not yet known. Here, we show that upon the induction of necroptosis and recruitment by the adaptor protein TAX1BP1, PARP5A and its binding partner RNF146 form liquid-like condensates by multivalent interactions to perform poly ADP-ribosylation (PARylation) and PARylation-dependent ubiquitination (PARdU) of activated RIPK1 in mouse embryonic fibroblasts. We show that PARdU predominantly occurs on the K376 residue of mouse RIPK1, which promotes proteasomal degradation of kinase-activated RIPK1 to restrain necroptosis. Our data demonstrate that PARdU on K376 of mouse RIPK1 provides an alternative cell death checkpoint mediated by phase separation-dependent control of necroptosis by PARP5A and RNF146.

Base-resolution m5C profiling across the mammalian transcriptome by bisulfite-free enzyme-assisted chemical labeling approach.

5-methylcytosine (m5C) is a prevalent RNA modification crucial for gene expression regulation. However, accurate and sensitive m5C sites identification remains challenging due to severe RNA degradation and reduced sequence complexity during bisulfite sequencing (BS-seq). Here, we report m5C-TAC-seq, a bisulfite-free approach combining TET-assisted m5C-to-f5C oxidation with selective chemical labeling, therefore enabling direct base-resolution m5C detection through pre-enrichment and C-to-T transitions at m5C sites. With m5C-TAC-seq, we comprehensively profiled the m5C methylomes in human and mouse cells, identifying a substantially larger number of confident m5C sites. Through perturbing potential m5C methyltransferases, we deciphered the responsible enzymes for most m5C sites, including the characterization of NSUN5's involvement in mRNA m5C deposition. Additionally, we characterized m5C dynamics during mESC differentiation. Notably, the mild reaction conditions and preservation of nucleotide composition in m5C-TAC-seq allow m5C detection in chromatin-associated RNAs. The accurate and robust m5C-TAC-seq will advance research into m5C methylation functional investigation.

Stress Induces Dynamic, Cytotoxicity-Antagonizing TDP-43 Nuclear Bodies via Paraspeckle LncRNA NEAT1-Mediated Liquid-Liquid Phase Separation.

Despite the prominent role of TDP-43 in neurodegeneration, its physiological and pathological functions are not fully understood. Here, we report an unexpected role of TDP-43 in the formation of dynamic, reversible, liquid droplet-like nuclear bodies (NBs) in response to stress. Formation of NBs alleviates TDP-43-mediated cytotoxicity in mammalian cells and fly neurons. Super-resolution microscopy reveals distinct functions of the two RRMs in TDP-43 NB formation. TDP-43 NBs are partially colocalized with nuclear paraspeckles, whose scaffolding lncRNA NEAT1 is dramatically upregulated in stressed neurons. Moreover, increase of NEAT1 promotes TDP-43 liquid-liquid phase separation (LLPS) in vitro. Finally, we discover that the ALS-associated mutation D169G impairs the NEAT1-mediated TDP-43 LLPS and NB assembly, causing excessive cytoplasmic translocation of TDP-43 to form stress granules, which become phosphorylated TDP-43 cytoplasmic foci upon prolonged stress. Together, our findings suggest a stress-mitigating role and mechanism of TDP-43 NBs, whose dysfunction may be involved in ALS pathogenesis.

Assessing the utility of large language models for phenotype-driven gene prioritization in the diagnosis of rare genetic disease.

Phenotype-driven gene prioritization is fundamental to diagnosing rare genetic disorders. While traditional approaches rely on curated knowledge graphs with phenotype-gene relations, recent advancements in large language models (LLMs) promise a streamlined text-to-gene solution. In this study, we evaluated five LLMs, including two generative pre-trained transformers (GPT) series and three Llama2 series, assessing their performance across task completeness, gene prediction accuracy, and adherence to required output structures. We conducted experiments, exploring various combinations of models, prompts, phenotypic input types, and task difficulty levels. Our findings revealed that the best-performed LLM, GPT-4, achieved an average accuracy of 17.0% in identifying diagnosed genes within the top 50 predictions, which still falls behind traditional tools. However, accuracy increased with the model size. Consistent results were observed over time, as shown in the dataset curated after 2023. Advanced techniques such as retrieval-augmented generation (RAG) and few-shot learning did not improve the accuracy. Sophisticated prompts were more likely to enhance task completeness, especially in smaller models. Conversely, complicated prompts tended to decrease output structure compliance rate. LLMs also achieved better-than-random prediction accuracy with free-text input, though performance was slightly lower than with standardized concept input. Bias analysis showed that highly cited genes, such as BRCA1, TP53, and PTEN, are more likely to be predicted. Our study provides valuable insights into integrating LLMs with genomic analysis, contributing to the ongoing discussion on their utilization in clinical workflows.

Conformational strains of pathogenic amyloid proteins in neurodegenerative diseases.

Amyloid proteins, which are considered 'villains' in many neurodegenerative diseases, form enigmatic pathological strains that underlie disease pathogenesis and progression. Recent technical advances in cryogenic electron microscopy and solid-state NMR spectroscopy have enabled the high-resolution structures of full-length amyloid fibrils to be determined, initiating an era in which we have the opportunity to gain atomic-level structural understanding of pathogenic protein aggregation in neurodegenerative diseases. In this Review, we aim to explain the clinicopathological heterogeneity of neurodegenerative diseases by considering the polymorphic structures of amyloid fibrils. We decipher the structural basis for the generation of fibril polymorphs, how the fibril polymorphs differ in different disease contexts and how conformational changes alter the pathology caused by amyloid proteins during disease progression. Finally, we evaluate how this knowledge might aid clinical diagnostic and therapeutic strategies to treat neurodegenerative diseases.

The zinc finger protein DHHC09 S-acylates the kinase STRK1 to regulate H2O2 homeostasis and promote salt tolerance in rice.

Soil salinity results in oxidative stress and heavy losses to crop production. The S-acylated protein SALT TOLERANCE RECEPTOR-LIKE CYTOPLASMIC KINASE 1 (STRK1) phosphorylates and activates CATALASE C (CatC) to improve rice (Oryza sativa L.) salt tolerance, but the molecular mechanism underlying its S-acylation involved in salt signal transduction awaits elucidation. Here, we show that the DHHC-type zinc finger protein DHHC09 S-acylates STRK1 at Cys5, Cys10, and Cys14 and promotes salt and oxidative stress tolerance by enhancing rice H2O2-scavenging capacity. This modification determines STRK1 targeting to the plasma membrane or lipid nanodomains and is required for its function. DHHC09 promotes salt signaling from STRK1 to CatC via transphosphorylation, and its deficiency impairs salt signal transduction. Our findings demonstrate that DHHC09 S-acylates and anchors STRK1 to the plasma membrane to promote salt signaling from STRK1 to CatC, thereby regulating H2O2 homeostasis and improving salt stress tolerance in rice. Moreover, overexpression of DHHC09 in rice mitigates grain yield loss under salt stress. Together, these results shed light on the mechanism underlying the role of S-acylation in RLK/RLCK-mediated salt signal transduction and provide a strategy for breeding highly salt-tolerant rice.

Binding adaptability of chemical ligands to polymorphic α-synuclein amyloid fibrils.

α-synuclein (α-syn) assembles into structurally distinct fibril polymorphs seen in different synucleinopathies, such as Parkinson's disease and multiple system atrophy. Targeting these unique fibril structures using chemical ligands holds diagnostic significance for different disease subtypes. However, the molecular mechanisms governing small molecules interacting with different fibril polymorphs remain unclear. Here, we investigated the interactions of small molecules belonging to four distinct scaffolds, with different α-syn fibril polymorphs. Using cryo-electron microscopy, we determined the structures of these molecules when bound to the fibrils formed by E46K mutant α-syn and compared them to those bound with wild-type α-syn fibrils. Notably, we observed that these ligands exhibit remarkable binding adaptability, as they engage distinct binding sites across different fibril polymorphs. While the molecular scaffold primarily steered the binding locations and geometries on specific sites, the conjugated functional groups further refined this adaptable binding by fine-tuning the geometries and binding sites. Overall, our finding elucidates the adaptability of small molecules binding to different fibril structures, which sheds light on the diagnostic tracer and drug developments tailored to specific pathological fibril polymorphs.

Prospective, multi-site study of healthcare utilization after actionable monogenic findings from clinical sequencing.

As large-scale genomic screening becomes increasingly prevalent, understanding the influence of actionable results on healthcare utilization is key to estimating the potential long-term clinical impact. The eMERGE network sequenced individuals for actionable genes in multiple genetic conditions and returned results to individuals, providers, and the electronic health record. Differences in recommended health services (laboratory, imaging, and procedural testing) delivered within 12 months of return were compared among individuals with pathogenic or likely pathogenic (P/LP) findings to matched individuals with negative findings before and after return of results. Of 16,218 adults, 477 unselected individuals were found to have a monogenic risk for arrhythmia (n = 95), breast cancer (n = 96), cardiomyopathy (n = 95), colorectal cancer (n = 105), or familial hypercholesterolemia (n = 86). Individuals with P/LP results more frequently received services after return (43.8%) compared to before return (25.6%) of results and compared to individuals with negative findings (24.9%; p < 0.0001). The annual cost of qualifying healthcare services increased from an average of $162 before return to $343 after return of results among the P/LP group (p < 0.0001); differences in the negative group were non-significant. The mean difference-in-differences was $149 (p < 0.0001), which describes the increased cost within the P/LP group corrected for cost changes in the negative group. When stratified by individual conditions, significant cost differences were observed for arrhythmia, breast cancer, and cardiomyopathy. In conclusion, less than half of individuals received billed health services after monogenic return, which modestly increased healthcare costs for payors in the year following return.

TUnA: an uncertainty-aware transformer model for sequence-based protein-protein interaction prediction.

Protein-protein interactions (PPIs) are important for many biological processes, but predicting them from sequence data remains challenging. Existing deep learning models often cannot generalize to proteins not present in the training set and do not provide uncertainty estimates for their predictions. To address these limitations, we present TUnA, a Transformer-based uncertainty-aware model for PPI prediction. TUnA uses ESM-2 embeddings with Transformer encoders and incorporates a Spectral-normalized Neural Gaussian Process. TUnA achieves state-of-the-art performance and, importantly, evaluates uncertainty for unseen sequences. We demonstrate that TUnA's uncertainty estimates can effectively identify the most reliable predictions, significantly reducing false positives. This capability is crucial in bridging the gap between computational predictions and experimental validation.

The NS2B-PP1α-eIF2α axis: Inhibiting stress granule formation and Boosting Zika virus replication.

Stress granules (SGs), formed by untranslated messenger ribonucleoproteins (mRNPs) during cellular stress in eukaryotes, have been linked to flavivirus interference without clear understanding. This study reveals the role of Zika virus (ZIKV) NS2B as a scaffold protein mediating interaction between protein phosphatase 1α (PP1α) and eukaryotic initiation factor 2α (eIF2α). This interaction promotes eIF2α dephosphorylation by PP1α, inhibiting SG formation. The NS2B-PP1α complex exhibits remarkable stability, resisting ubiquitin-induced degradation and amplifying eIF2α dephosphorylation, thus promoting ZIKV replication. In contrast, the NS2BV35A mutant, interacting exclusively with eIF2α, fails to inhibit SG formation, resulting in reduced viral replication and diminished impact on brain organoid growth. These findings reveal PP1α's dual role in ZIKV infection, inducing interferon production as an antiviral factor and suppressing SG formation as a viral promoter. Moreover, we found that NS2B also serves as a versatile mechanism employed by flaviviruses to counter host antiviral defenses, primarily by broadly inhibiting SG formation. This research advances our comprehension of the complex interplay in flavivirus-host interactions, offering potential for innovative therapeutic strategies against flavivirus infections.

The protein phosphatase PC1 dephosphorylates and deactivates CatC to negatively regulate H2O2 homeostasis and salt tolerance in rice.

Catalase (CAT) is often phosphorylated and activated by protein kinases to maintain hydrogen peroxide (H2O2) homeostasis and protect cells against stresses, but whether and how CAT is switched off by protein phosphatases remains inconclusive. Here, we identified a manganese (Mn2+)-dependent protein phosphatase, which we named PHOSPHATASE OF CATALASE 1 (PC1), from rice (Oryza sativa L.) that negatively regulates salt and oxidative stress tolerance. PC1 specifically dephosphorylates CatC at Ser-9 to inhibit its tetramerization and thus activity in the peroxisome. PC1 overexpressing lines exhibited hypersensitivity to salt and oxidative stresses with a lower phospho-serine level of CATs. Phosphatase activity and seminal root growth assays indicated that PC1 promotes growth and plays a vital role during the transition from salt stress to normal growth conditions. Our findings demonstrate that PC1 acts as a molecular switch to dephosphorylate and deactivate CatC and negatively regulate H2O2 homeostasis and salt tolerance in rice. Moreover, knockout of PC1 not only improved H2O2-scavenging capacity and salt tolerance but also limited rice grain yield loss under salt stress conditions. Together, these results shed light on the mechanisms that switch off CAT and provide a strategy for breeding highly salt-tolerant rice.

Phase-separated ParB enforces diverse DNA compaction modes and stabilizes the parS-centered partition complex.

The tripartite ParABS system mediates chromosome segregation in the majority of bacterial species. Typically, DNA-bound ParB proteins around the parS sites condense the chromosomal DNA into a higher-order multimeric nucleoprotein complex for the ParA-driven partition. Despite extensive studies, the molecular mechanism underlying the dynamic assembly of the partition complex remains unclear. Herein, we demonstrate that Bacillus subtilis ParB (Spo0J), through the multimerization of its N-terminal domain, forms phase-separated condensates along a single DNA molecule, leading to the concurrent organization of DNA into a compact structure. Specifically, in addition to the co-condensation of ParB dimers with DNA, the engagement of well-established ParB condensates with DNA allows for the compression of adjacent DNA and the looping of distant DNA. Notably, the presence of CTP promotes the formation of condensates by a low amount of ParB at parS sites, triggering two-step DNA condensation. Remarkably, parS-centered ParB-DNA co-condensate constitutes a robust nucleoprotein architecture capable of withstanding disruptive forces of tens of piconewton. Overall, our findings unveil diverse modes of DNA compaction enabled by phase-separated ParB and offer new insights into the dynamic assembly and maintenance of the bacterial partition complex.

Neutral lysophosphatidylcholine mediates α-synuclein-induced synaptic vesicle clustering.

α-synuclein (α-Syn) is a presynaptic protein that is involved in Parkinson's and other neurodegenerative diseases and binds to negatively charged phospholipids. Previously, we reported that α-Syn clusters synthetic proteoliposomes that mimic synaptic vesicles. This vesicle-clustering activity depends on a specific interaction of α-Syn with anionic phospholipids. Here, we report that α-Syn surprisingly also interacts with the neutral phospholipid lysophosphatidylcholine (lysoPC). Even in the absence of anionic lipids, lysoPC facilitates α-Syn-induced vesicle clustering but has no effect on Ca2+-triggered fusion in a single vesicle-vesicle fusion assay. The A30P mutant of α-Syn that causes familial Parkinson disease has a reduced affinity to lysoPC and does not induce vesicle clustering. Taken together, the α-Syn-lysoPC interaction may play a role in α-Syn function.

Different charged biopolymers induce α-synuclein to form fibrils with distinct structures.

The aggregation of α-synuclein (α-syn) into amyloid fibrils, a key process in the development of Parkinson's disease (PD) and other synucleinopathies, is influenced by a range of factors such as charged biopolymers, chaperones, and metabolites. However, the specific impacts of different biopolymers on α-syn fibril structure are not well understood. In our work, we found that different polyanions and polycations, such as polyphosphate (polyP), polyuridine (polyU), and polyamines (including putrescine, spermidine, and spermine), markedly altered the fibrillation kinetics of α-syn in vitro. Furthermore, seeding assay revealed distinct cross-seeding capacities across different biopolymer-induced α-syn fibrils, suggesting the formation of structurally distinct strains under different conditions. Utilizing cryo-electron microscopy (cryo-EM), we further examined the detailed structural configuration of α-syn fibrils formed in the presence of these biopolymers. Notably, we found that while polyamines do not change the atomic structure of α-syn fibrils, polyU and polyP induce the formation of distinct amyloid fibrils, exhibiting a range of structural polymorphs. Our work offers valuable insights into how various charged biopolymers affect the aggregation process and the resultant structures of α-syn fibrils, thereby enhancing our understanding of the structural variations in α-syn fibrils across different pathological conditions.

Phosphorylation-Regulated Dynamic Phase Separation of HIP-55 Protects Against Heart Failure.

BACKGROUND: Heart failure (HF), which is the terminal stage of many cardiovascular diseases, is associated with low survival rates and a severe financial burden. The mechanisms, especially the molecular mechanism combined with new theories, underlying the pathogenesis of HF remain elusive. We demonstrate that phosphorylation-regulated dynamic liquid-liquid phase separation of HIP-55 (hematopoietic progenitor kinase 1-interacting protein of 55 kDa) protects against HF. METHODS: Fluorescence recovery after photobleaching assay, differential interference contrast analysis, pull-down assay, immunofluorescence, and immunohistochemical analysis were used to investigate the liquid-liquid phase separation capacity of HIP-55 and its dynamic regulation in vivo and in vitro. Mice with genetic deletion of HIP-55 and mice with cardiac-specific overexpression of HIP-55 were used to examine the role of HIP-55 on ß-adrenergic receptor hyperactivation-induced HF. Mutation analysis and mice with specific phospho-resistant site mutagenesis were used to identify the role of phosphorylation-regulated dynamic liquid-liquid phase separation of HIP-55 in HF. RESULTS: Genetic deletion of HIP-55 aggravated HF, whereas cardiac-specific overexpression of HIP-55 significantly alleviated HF in vivo. HIP-55 possesses a strong capacity for phase separation. Phase separation of HIP-55 is dynamically regulated by AKT-mediated phosphorylation at S269 and T291 sites, failure of which leads to impairment of HIP-55 dynamic phase separation by formation of abnormal aggregation. Prolonged sympathetic hyperactivation stress induced decreased phosphorylation of HIP-55 S269 and T291, dysregulated phase separation, and subsequent aggregate formation of HIP55. Moreover, we demonstrated the important role of dynamic phase separation of HIP-55 in inhibiting hyperactivation of the ß-adrenergic receptor-mediated P38/MAPK (mitogen-activated protein kinase) signaling pathway. A phosphorylation-deficient HIP-55 mutation, which undergoes massive phase separation and forms insoluble aggregates, loses the protective activity against HF. CONCLUSIONS: Our work reveals that the phosphorylation-regulated dynamic phase separation of HIP-55 protects against sympathetic/adrenergic system-mediated heart failure.

OARD: Open annotations for rare diseases and their phenotypes based on real-world data.

Diagnosis for rare genetic diseases often relies on phenotype-driven methods, which hinge on the accuracy and completeness of the rare disease phenotypes in the underlying annotation knowledgebase. Existing knowledgebases are often manually curated with additional annotations found in published case reports. Despite their potential, real-world data such as electronic health records (EHRs) have not been fully exploited to derive rare disease annotations. Here, we present open annotation for rare diseases (OARD), a real-world-data-derived resource with annotation for rare-disease-related phenotypes. This resource is derived from the EHRs of two academic health institutions containing more than 10 million individuals spanning wide age ranges and different disease subgroups. By leveraging ontology mapping and advanced natural-language-processing (NLP) methods, OARD automatically and efficiently extracts concepts for both rare diseases and their phenotypic traits from billing codes and lab tests as well as over 100 million clinical narratives. The rare disease prevalence derived by OARD is highly correlated with those annotated in the original rare disease knowledgebase. By performing association analysis, we identified more than 1 million novel disease-phenotype association pairs that were previously missed by human annotation, and >60% were confirmed true associations via manual review of a list of sampled pairs. Compared to the manual curated annotation, OARD is 100% data driven and its pipeline can be shared across different institutions. By supporting privacy-preserving sharing of aggregated summary statistics, such as term frequencies and disease-phenotype associations, it fills an important gap to facilitate data-driven research in the rare disease community.