Neuroproteomics of the Synapse: Subcellular Quantification of Protein Networks and Signaling Dynamics

Induced-pluripotent stem cells and neuroproteomics as tools for studying neurodegeneration

The investigation of neurodegenerative diseases advanced significantly with the advent of cell-reprogramming technology, leading to the creation of new models of human illness. These models, derived from induced pluripotent stem cells (iPSCs), facilitate the study of sporadic as well as hereditary diseases and provide a comprehensive understanding of the molecular mechanisms involved with neurodegeneration. Through proteomics, a quantitative tool capable of identifying thousands of proteins from small sample volumes, researchers have attempted to identify disease mechanisms by detecting differentially expressed proteins and proteoforms in disease models, biofluids, and postmortem brain tissue. The integration of these two technologies allows for the identification of novel pathological targets within the realm of neurodegenerative diseases. Here, we highlight studies from the past 5 years on the contributions of iPSCs within neuroproteomic investigations, which uncover the molecular mechanisms behind these illnesses.

Advances in neuroproteomics for neurotrauma: unraveling insights for personalized medicine and future prospects

Neuroproteomics, an emerging field at the intersection of neuroscience and proteomics, has garnered significant attention in the context of neurotrauma research. Neuroproteomics involves the quantitative and qualitative analysis of nervous system components, essential for understanding the dynamic events involved in the vast areas of neuroscience, including, but not limited to, neuropsychiatric disorders, neurodegenerative disorders, mental illness, traumatic brain injury, chronic traumatic encephalopathy, and other neurodegenerative diseases. With advancements in mass spectrometry coupled with bioinformatics and systems biology, neuroproteomics has led to the development of innovative techniques such as microproteomics, single-cell proteomics, and imaging mass spectrometry, which have significantly impacted neuronal biomarker research. By analyzing the complex protein interactions and alterations that occur in the injured brain, neuroproteomics provides valuable insights into the pathophysiological mechanisms underlying neurotrauma. This review explores how such insights can be harnessed to advance personalized medicine (PM) approaches, tailoring treatments based on individual patient profiles. Additionally, we highlight the potential future prospects of neuroproteomics, such as identifying novel biomarkers and developing targeted therapies by employing artificial intelligence (AI) and machine learning (ML). By shedding light on neurotrauma's current state and future directions, this review aims to stimulate further research and collaboration in this promising and transformative field.

Cell-Type-Specific Neuroproteomics of Synapses

In the last two decades, our knowledge of synaptic proteomes and their relationship to normal brain function and neuropsychiatric disorders has been expanding rapidly through the use of more powerful neuroproteomic approaches. However, mass spectrometry (MS)-based neuroproteomic studies of synapses still require cell-type, spatial, and temporal proteome information. With the advancement of sample preparation and MS techniques, we have just begun to identify and understand proteomes within a given cell type, subcellular compartment, and cell-type-specific synapse. Here, we review the progress and limitations of MS-based neuroproteomics of synapses in the mammalian CNS and highlight the recent applications of these approaches in studying neuropsychiatric disorders such as major depressive disorder and substance use disorders. Combining neuroproteomic findings with other omics studies can generate an in-depth, comprehensive map of synaptic proteomes and possibly identify new therapeutic targets and biomarkers for several central nervous system disorders.

Protein Networks Associated with Native Metabotropic Glutamate 1 Receptors (mGlu1) in the Mouse Cerebellum

The metabotropic glutamate receptor 1 (mGlu1) plays a pivotal role in synaptic transmission and neuronal plasticity. Despite the fact that several interacting proteins involved in the mGlu1 subcellular trafficking and intracellular transduction mechanisms have been identified, the protein network associated with this receptor in specific brain areas remains largely unknown. To identify novel mGlu1-associated protein complexes in the mouse cerebellum, we used an unbiased tissue-specific proteomic approach, namely co-immunoprecipitation followed by liquid chromatography/tandem mass spectrometry analysis. Many well-known protein complexes as well as novel interactors were identified, including G-proteins, Homer, δ2 glutamate receptor, 14-3-3 proteins, and Na/K-ATPases. A novel putative interactor, KCTD12, was further investigated. Reverse co-immunoprecipitation with anti-KCTD12 antibodies revealed mGlu1 in wild-type but not in KCTD12-knock-out homogenates. Freeze-fracture replica immunogold labeling co-localization experiments showed that KCTD12 and mGlu1 are present in the same nanodomain in Purkinje cell spines, although at a distance that suggests that this interaction is mediated through interposed proteins. Consistently, mGlu1 could not be co-immunoprecipitated with KCTD12 from a recombinant mammalian cell line co-expressing the two proteins. The possibility that this interaction was mediated via GABAB receptors was excluded by showing that mGlu1 and KCTD12 still co-immunoprecipitated from GABAB receptor knock-out tissue. In conclusion, this study identifies tissue-specific mGlu1-associated protein clusters including KCTD12 at Purkinje cell synapses.

Long-term maintenance of synaptic plasticity by Fullerenol Ameliorates lead-induced-impaired learning and memory in vivo

Fullerenol, a functional and water-soluble fullerene derivative, plays an important role in antioxidant, antitumor and antivirus, implying its enormous potential in biomedical applications. However, the in vivo performance of fullerenol remains largely unclear. We aimed to investigate the effect of fullerenol (i.p., 5 mg/kg) on the impaired hippocampus in a rat model of lead exposure. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) is a kind of newly developed soft-ionization mass spectrometry technology. In the present study, an innovative strategy for biological distribution analysis using MALDI-TOF-MS confirmed that fullerenol could across the blood-brain barrier and accumulate in the brain. Results from behavioral tests showed that a low dose of fullerenol could improve the impaired learning and memory induced by lead. Furthermore, electrophysiology examinations indicated that this potential repair effect of fullerenol was mainly due to the long-term changes in hippocampal synaptic plasticity, with enhancement lasting for more than 2-3 h. In addition, morphological observations and biochemistry analyses manifested that the long-term change in synaptic efficacy was accompanied by some structural alteration in synaptic connection. Our study demonstrates the therapeutic feature of fullerenol will be beneficial to the discovery and development as a new drug and lays a solid foundation for further biomedical applications of nanomedicines.

Proteomics Reveals Molecular Changes in Insomnia Patients with More Dreams

Background

Insomnia is a sleep disorder and the cause of many healthy problems. However, there are few studies on patients with insomnia and dreaminess at present. Therefore, this study is aimed at exploring the pathological molecular mechanisms and potential diagnostic and therapeutic targets related to insomnia patients with more dreams.

Methods

Sleep characteristics of 36 primary insomnia patients with more dreams and 36 well sleeping participants were assessed using polysomnography (PSG) and Pittsburgh Sleep Quality Index (PSQI). Serum samples from 9 insomnia patients and 9 controls were randomly selected for proteomic detection. Differentially expressed proteins (DEPs) between the two groups were identified; enrichment analysis and PPI network were performed. The top 10 most connected proteins in the PPI network were subjected to targeted drug prediction and screened key proteins. Proteins with targeted drugs were recognized as key proteins and subjected to ELISA detection.

Results

Insomnia patients had a distinct REM behavior disorder signature compared with controls. Proteomic sequencing identified 76 DEPs. Enrichment analysis found that DEPs were significantly enriched in the complement and coagulation cascades. Metabolic responses were also activated in insomnia patients. Among the hub proteins screened in the PPI network, APOA1, APOB, F2, and SPARC may be targeted by many herbal medicines and considered as key proteins. ELISA assays validated their differential expression between insomnia and controls.

Conclusion

In this study, we identified the potential key proteins of insomnia patients with more dreams. The pathological process may associate with inflammation and metabolic response. These results provide molecular targets for diagnostic and therapeutic targets. The results of our analysis suggest that the expression changes of key proteins have a good predictive diagnostic role for the occurrence of insomnia with more dreams in patients.