Deep Profiling of Proteome and Phosphoproteome by Isobaric Labeling, Extensive Liquid Chromatography, and Mass Spectrometry

Turnover atlas of proteome and phosphoproteome across mouse tissues and brain regions

Understanding how proteins in different mammalian tissues are regulated is central to biology. Protein abundance, turnover, and post-translational modifications such as phosphorylation are key factors that determine tissue-specific proteome properties. However, these properties are challenging to study across tissues and remain poorly understood. Here, we present Turnover-PPT, a comprehensive resource mapping the abundance and lifetime of 11,000 proteins and 40,000 phosphosites in eight mouse tissues and various brain regions using advanced proteomics and stable isotope labeling. We reveal tissue-specific short- and long-lived proteins, strong correlations between interacting protein lifetimes, and distinct impacts of phosphorylation on protein turnover. Notably, we discover a remarkable pattern of turnover changes for peroxisome proteins in specific tissues and that phosphorylation regulates the stability of neurodegeneration-related proteins, such as Tau and α-synuclein. Thus, Turnover-PPT provides fundamental insights into protein stability, tissue dynamic proteotypes, and functional protein phosphorylation and is accessible via an interactive web-based portal at https://yslproteomics.shinyapps.io/tissuePPT.

Genetic modulation of protein expression in rat brain

Genetic variations in protein expression are implicated in a broad spectrum of common diseases and complex traits but remain less explored compared to mRNA and classical phenotypes. This study systematically analyzed brain proteomes in a rat family using tandem mass tag (TMT)-based quantitative mass spectrometry. We quantified 8,119 proteins across two parental strains (SHR/Olalpcv and BN-Lx/Cub) and 29 HXB/BXH recombinant inbred (RI) strains, identifying 597 proteins with differential expression and 464 proteins linked to cis-acting quantitative trait loci (pQTLs). Proteogenomics identified 95 variant peptides, and sex-specific analyses revealed both shared and distinct cis-pQTLs. We improved the ability to pinpoint candidate genes underlying pQTLs by utilizing the rat pangenome and explored the connections between pQTLs in rats and human disorders. Collectively, this study highlights the value of large proteo-genetic datasets in elucidating protein modulation in the brain and its links to complex central nervous system (CNS) traits.

Midkine Attenuates Aβ Fibril Assembly and Amyloid Plaque Formation

Proteomic profiling of Alzheimer's disease (AD) brains has identified numerous understudied proteins, including midkine (MDK), that are highly upregulated and correlated with Aβ since the early disease stage, but their roles in disease progression are not fully understood. Here we present that MDK attenuates Aβ assembly and influences amyloid formation in the 5xFAD amyloidosis mouse model. MDK protein mitigates fibril formation of both Aβ40 and Aβ42 peptides in Thioflavin T fluorescence assay, circular dichroism, negative stain electron microscopy, and NMR analysis. Knockout of Mdk gene in 5xFAD increases amyloid formation and microglial activation. Further comprehensive mass spectrometry-based profiling of whole proteome and detergent-insoluble proteome in these mouse models indicates significant accumulation of Aβ and Aβ-correlated proteins, along with microglial components. Thus, our structural and mouse model studies reveal a protective role of MDK in counteracting amyloid pathology in Alzheimer's disease.

Bipolar and schizophrenia risk gene AKAP11 encodes an autophagy receptor coupling the regulation of PKA kinase network homeostasis to synaptic transmission

Human genomic studies have identified protein-truncating variants in AKAP11 associated with both bipolar disorder (BD) and schizophrenia (SCZ), implicating a shared disease mechanism driven by loss-of-function. AKAP11, a protein kinase A (PKA) adaptor, plays a key role in degrading the PKA-RI complex through selective autophagy. However, the neuronal functions of AKAP11 and the impact of its loss-of-function remains largely uncharacterized. Through multi-omics approaches, cell biology, and electrophysiology analysis in mouse models and human induced neurons, we delineated a central role of AKAP11 in coupling PKA kinase network regulation to synaptic transmission. Loss of AKAP11 distorted compartment-specific PKA and GSK3α/β activities and impaired cellular functions that significantly overlap with pathways associated with BD and SCZ. Moreover, we identified interactions between AKAP11, the PKA-RI adaptor SPHKAP, and the ER-resident autophagy-related proteins VAPA/B, which co-adapt and mediate PKA-RI complex degradation in neurons. Notably, AKAP11 deficiency impaired neurotransmission, providing key insights into the mechanism underlying AKAP11-associated psychiatric diseases.

Advanced applications of two-dimensional liquid chromatography in quantitative analysis of natural products

Two-dimensional liquid chromatography (2D-LC) separation systems, based on two independent columns with different separation mechanisms, have exhibited strong resolving power for complex samples. Therefore, in recent years, the exceptional resolution of 2D-LC has significantly advanced the chemical separation of natural products, such as complex herbs, greatly facilitating their qualitative and quantitative analysis. This paper aims to review the latest strategies of 2D-LC in the quantitative analysis of complex chemical compositions in natural products. To this end, the major advantages and disadvantages of various column couplings in 2D-LC are discussed based on specific studies, along with suggested solutions to address the identified drawbacks. Moreover, the applications of different detectors combined with the latest chemometrics in 2D-LC for accurate quantitative analysis of natural products are reviewed and discussed.

Human and mouse proteomics reveals the shared pathways in Alzheimer's disease and delayed protein turnover in the amyloidome

Murine models of Alzheimer's disease (AD) are crucial for elucidating disease mechanisms but have limitations in fully representing AD molecular complexities. Here we present the comprehensive, age-dependent brain proteome and phosphoproteome across multiple mouse models of amyloidosis. We identified shared pathways by integrating with human metadata and prioritized components by multi-omics analysis. Collectively, two commonly used models (5xFAD and APP-KI) replicate 30% of the human protein alterations; additional genetic incorporation of tau and splicing pathologies increases this similarity to 42%. We dissected the proteome-transcriptome inconsistency in AD and 5xFAD mouse brains, revealing that inconsistent proteins are enriched within amyloid plaque microenvironment (amyloidome). Our analysis of the 5xFAD proteome turnover demonstrates that amyloid formation delays the degradation of amyloidome components, including Aβ-binding proteins and autophagy/lysosomal proteins. Our proteomic strategy defines shared AD pathways, identifies potential targets, and underscores that protein turnover contributes to proteome-transcriptome discrepancies during AD progression.

JUMPlib: Integrative Search Tool Combining Fragment Ion Indexing with Comprehensive TMT Spectral Libraries

The identification of peptides is a cornerstone of mass spectrometry-based proteomics. Spectral library-based algorithms are well-established methods to enhance the identification efficiency of peptides during database searches in proteomics. However, these algorithms are not specifically tailored for tandem mass tag (TMT)-based proteomics due to the lack of high-quality TMT spectral libraries. Here, we introduce JUMPlib, a computational tool for a TMT-based spectral library search. JUMPlib comprises components for generating spectral libraries, conducting library searches, filtering peptide identifications, and quantifying peptides and proteins. Fragment ion indexing in the libraries increases the search speed and utilizing the experimental retention time of precursor ions improves peptide identification. We found that methionine oxidation is a major factor contributing to large shifts in peptide retention time. To test the JUMPlib program, we curated two comprehensive human libraries for the labeling of TMT6/10/11 and TMT16/18 reagents, with ∼286,000 precursor ions and ∼304,000 precursor ions, respectively. Our analyses demonstrate that JUMPlib, employing the fragment ion index strategy, enhances search speed and exhibits high sensitivity and specificity, achieving approximately a 25% increase in peptide-spectrum matches compared to other search tools. Overall, JUMPlib serves as a streamlined computational platform designed to enhance peptide identification in TMT-based proteomics. Both the JUMPlib source code and libraries are publicly available.

Bipolar and schizophrenia risk gene AKAP11 encodes an autophagy receptor coupling the regulation of PKA kinase network homeostasis to synaptic transmission

Human genomic studies have identified protein-truncating variants in AKAP11 associated with both bipolar disorder and schizophrenia, implicating a shared disease mechanism driven by loss-of-function. AKAP11, a protein kinase A (PKA) adaptor, plays a key role in degrading the PKA-RI complex through selective autophagy. However, the neuronal functions of AKAP11 and the impact of its loss-of-function remains largely uncharacterized. Through multi-omics approaches, cell biology, and electrophysiology analysis in mouse models and human induced neurons, we delineated a central role of AKAP11 in coupling PKA kinase network regulation to synaptic transmission. Loss of AKAP11 disrupted PKA activity and impaired cellular functions that significantly overlap with pathways associated with the psychiatric disease. Moreover, we identified interactions between AKAP11, the PKA-RI adaptor SPHKAP, and the ER-resident autophagy-related proteins VAPA/B, which co-adapt and mediate PKA-RI degradation. Notably, AKAP11 deficiency impaired neurotransmission and decreased presynaptic protein levels in neurons, providing key insights into the mechanism underlying AKAP11-associated psychiatric diseases.

The ubiquitin-conjugating enzyme UBE2D maintains a youthful proteome and ensures protein quality control during aging by sustaining proteasome activity

Ubiquitin-conjugating enzymes (E2s) are key for protein turnover and quality control via ubiquitination. Some E2s also physically interact with the proteasome, but it remains undetermined which E2s maintain proteostasis during aging. Here, we find that E2s have diverse roles in handling a model aggregation-prone protein (huntingtin-polyQ) in the Drosophila retina: while some E2s mediate aggregate assembly, UBE2D/effete (eff) and other E2s are required for huntingtin-polyQ degradation. UBE2D/eff is key for proteostasis also in skeletal muscle: eff protein levels decline with aging, and muscle-specific eff knockdown causes an accelerated buildup in insoluble poly-ubiquitinated proteins (which progressively accumulate with aging) and shortens lifespan. Mechanistically, UBE2D/eff is necessary to maintain optimal proteasome function: UBE2D/eff knockdown reduces the proteolytic activity of the proteasome, and this is rescued by transgenic expression of human UBE2D2, an eff homolog. Likewise, human UBE2D2 partially rescues the lifespan and proteostasis deficits caused by muscle-specific effRNAi and re-establishes the physiological levels of effRNAi-regulated proteins. Interestingly, UBE2D/eff knockdown in young age reproduces part of the proteomic changes that normally occur in old muscles, suggesting that the decrease in UBE2D/eff protein levels that occurs with aging contributes to reshaping the composition of the muscle proteome. However, some of the proteins that are concertedly up-regulated by aging and effRNAi are proteostasis regulators (e.g., chaperones and Pomp) that are transcriptionally induced presumably as part of an adaptive stress response to the loss of proteostasis. Altogether, these findings indicate that UBE2D/eff is a key E2 ubiquitin-conjugating enzyme that ensures protein quality control and helps maintain a youthful proteome composition during aging.

Genetic regulation of human brain proteome reveals proteins implicated in psychiatric disorders

Psychiatric disorders are highly heritable yet polygenic, potentially involving hundreds of risk genes. Genome-wide association studies have identified hundreds of genomic susceptibility loci with susceptibility to psychiatric disorders; however, the contribution of these loci to the underlying psychopathology and etiology remains elusive. Here we generated deep human brain proteomics data by quantifying 11,608 proteins across 268 subjects using 11-plex tandem mass tag coupled with two-dimensional liquid chromatography-tandem mass spectrometry. Our analysis revealed 788 cis-acting protein quantitative trait loci associated with the expression of 883 proteins at a genome-wide false discovery rate <5%. In contrast to expression at the transcript level and complex diseases that are found to be mainly influenced by noncoding variants, we found protein expression level tends to be regulated by non-synonymous variants. We also provided evidence of 76 shared regulatory signals between gene expression and protein abundance. Mediation analysis revealed that for most (88%) of the colocalized genes, the expression levels of their corresponding proteins are regulated by cis-pQTLs via gene transcription. Using summary data-based Mendelian randomization analysis, we identified 4 proteins and 19 genes that are causally associated with schizophrenia. We further integrated multiple omics data with network analysis to prioritize candidate genes for schizophrenia risk loci. Collectively, our findings underscore the potential of proteome-wide linkage analysis in gaining mechanistic insights into the pathogenesis of psychiatric disorders.

Deletion of miR-33, a regulator of the ABCA1-APOE pathway, ameliorates neuropathological phenotypes in APP/PS1 mice

INTRODUCTION

Rare variants in ABCA1 increase the risk of developing Alzheimer's disease (AD). ABCA1 facilitates the lipidation of apolipoprotein E (apoE). This study investigated whether microRNA-33 (miR-33)-mediated regulation of this ABCA1-APOE pathway affects phenotypes of an amyloid mouse model.

METHODS

We generated mir-33+/+;APP/PS1 and mir-33-/-;APP/PS1 mice to determine changes in amyloid pathology using biochemical and histological analyses. We used RNA sequencing and mass spectrometry to identify the transcriptomic and proteomic changes between our genotypes. We also performed mechanistic experiments by determining the role of miR-33 in microglial migration and amyloid beta (Aβ) phagocytosis.

RESULTS

Mir-33 deletion increases ABCA1 levels and reduces Aβ accumulation and glial activation. Multi-omics studies suggested miR-33 regulates the activation and migration of microglia. We confirm that the inhibition of miR-33 significantly increases microglial migration and Aβ phagocytosis.

DISCUSSION

These results suggest that miR-33 might be a potential drug target by modulating ABCA1 level, apoE lipidation, Aβ level, and microglial function.

HIGHLIGHTS

Loss of microRNA-33 (miR-33) increased ABCA1 protein levels and the lipidation of apolipoprotein E. Loss of miR-33 reduced amyloid beta (Aβ) levels, plaque deposition, and gliosis. mRNAs and proteins dysregulated by miR-33 loss relate to microglia and Alzheimer's disease. Inhibition of miR-33 increased microglial migration and Aβ phagocytosis in vitro.

Human-mouse proteomics reveals the shared pathways in Alzheimer's disease and delayed protein turnover in the amyloidome

Murine models of Alzheimer's disease (AD) are crucial for elucidating disease mechanisms but have limitations in fully representing AD molecular complexities. We comprehensively profiled age-dependent brain proteome and phosphoproteome (n > 10,000 for both) across multiple mouse models of amyloidosis. We identified shared pathways by integrating with human metadata, and prioritized novel components by multi-omics analysis. Collectively, two commonly used models (5xFAD and APP-KI) replicate 30% of the human protein alterations; additional genetic incorporation of tau and splicing pathologies increases this similarity to 42%. We dissected the proteome-transcriptome inconsistency in AD and 5xFAD mouse brains, revealing that inconsistent proteins are enriched within amyloid plaque microenvironment (amyloidome). Determining the 5xFAD proteome turnover demonstrates that amyloid formation delays the degradation of amyloidome components, including Aβ-binding proteins and autophagy/lysosomal proteins. Our proteomic strategy defines shared AD pathways, identify potential new targets, and underscores that protein turnover contributes to proteome-transcriptome discrepancies during AD progression.

Transgenic sensors reveal compartment-specific effects of aggregation-prone proteins on subcellular proteostasis during aging

Loss of proteostasis is a hallmark of aging that underlies many age-related diseases. Different cell compartments experience distinctive challenges in maintaining protein quality control, but how aging regulates subcellular proteostasis remains underexplored. Here, by targeting the misfolding-prone FlucDM luciferase to the cytoplasm, mitochondria, and nucleus, we established transgenic sensors to examine subcellular proteostasis in Drosophila. Analysis of detergent-insoluble and -soluble levels of compartment-targeted FlucDM variants indicates that thermal stress, cold shock, and pro-longevity inter-organ signaling differentially affect subcellular proteostasis during aging. Moreover, aggregation-prone proteins that cause different neurodegenerative diseases induce a diverse range of outcomes on FlucDM insolubility, suggesting that subcellular proteostasis is impaired in a disease-specific manner. Further analyses with FlucDM and mass spectrometry indicate that pathogenic tauV337M produces an unexpectedly complex regulation of solubility for different FlucDM variants and protein subsets. Altogether, compartment-targeted FlucDM sensors pinpoint a diverse modulation of subcellular proteostasis by aging regulators.

An Extensive Atlas of Proteome and Phosphoproteome Turnover Across Mouse Tissues and Brain Regions

Understanding how proteins in different mammalian tissues are regulated is central to biology. Protein abundance, turnover, and post-translational modifications like phosphorylation, are key factors that determine tissue-specific proteome properties. However, these properties are challenging to study across tissues and remain poorly understood. Here, we present Turnover-PPT, a comprehensive resource mapping the abundance and lifetime of 11,000 proteins and 40,000 phosphosites across eight mouse tissues and various brain regions, using advanced proteomics and stable isotope labeling. We revealed tissue-specific short- and long-lived proteins, strong correlations between interacting protein lifetimes, and distinct impacts of phosphorylation on protein turnover. Notably, we discovered that peroxisomes are regulated by protein turnover across tissues, and that phosphorylation regulates the stability of neurodegeneration-related proteins, such as Tau and α-synuclein. Thus, Turnover-PPT provides new fundamental insights into protein stability, tissue dynamic proteotypes, and the role of protein phosphorylation, and is accessible via an interactive web-based portal at https://yslproteomics.shinyapps.io/tissuePPT.

CBFA2T3-GLIS2 mediates transcriptional regulation of developmental pathways through a gene regulatory network

CBFA2T3-GLIS2 is a fusion oncogene found in pediatric acute megakaryoblastic leukemia that is associated with a poor prognosis. We establish a model of CBFA2T3-GLIS2 driven acute megakaryoblastic leukemia that allows the distinction of fusion specific changes from those that reflect the megakaryoblast lineage of this leukemia. Using this model, we map fusion genome wide binding that in turn imparts the characteristic transcriptional signature. A network of transcription factor genes bound and upregulated by the fusion are found to have downstream effects that result in dysregulated signaling of developmental pathways including NOTCH, Hedgehog, TGFβ, and WNT. Transcriptional regulation is mediated by homo-dimerization and binding of the ETO transcription factor through the nervy homology region 2. Loss of nerve homology region 2 abrogated the development of leukemia, leading to downregulation of JAK/STAT, Hedgehog, and NOTCH transcriptional signatures. These data contribute to the understanding of CBFA2T3-GLIS2 mediated leukemogenesis and identify potential therapeutic vulnerabilities for future studies.

Dynamic Foxp3-chromatin interaction controls tunable Treg cell function

Nuclear factor Foxp3 determines regulatory T (Treg) cell fate and function via mechanisms that remain unclear. Here, we investigate the nature of Foxp3-mediated gene regulation in suppressing autoimmunity and antitumor immune response. Contrasting with previous models, we find that Foxp3-chromatin binding is regulated by Treg activation states, tumor microenvironment, and antigen and cytokine stimulations. Proteomics studies uncover dynamic proteins within Foxp3 proximity upon TCR or IL-2 receptor signaling in vitro, reflecting intricate interactions among Foxp3, signal transducers, and chromatin. Pharmacological inhibition and genetic knockdown experiments indicate that NFAT and AP-1 protein Batf are required for enhanced Foxp3-chromatin binding in activated Treg cells and tumor-infiltrating Treg cells to modulate target gene expression. Furthermore, mutations at the Foxp3 DNA-binding domain destabilize the Foxp3-chromatin association. These representative settings delineate context-dependent Foxp3-chromatin interaction, suggesting that Foxp3 associates with chromatin by hijacking DNA-binding proteins resulting from Treg activation or differentiation, which is stabilized by direct Foxp3-DNA binding, to dynamically regulate Treg cell function according to immunological contexts.

Unraveling the genetic and molecular landscape of sepsis and acute kidney injury: A comprehensive GWAS and machine learning approach

OBJECTIVES

This study aimed to explore the underlying mechanisms of sepsis and acute kidney injury (AKI), including sepsis-associated AKI (SA-AKI), a frequent complication in critically ill sepsis patients.

METHODS

GWAS data was analyzed for genetic association between AKI and sepsis. Then, we systematically applied three distinct machine learning algorithms (LASSO, SVM-RFE, RF) to rigorously identify and validate signature genes of SA-AKI, assessing their diagnostic and prognostic value through ROC curves and survival analysis. The study also examined the functional and immunological aspects of these genes, potential drug targets, and ceRNA networks. A mouse model of sepsis was created to test the reliability of these signature genes.

RESULTS

LDSC confirmed a positive genetic correlation between AKI and sepsis, although no significant shared loci were found. Bidirectional MR analysis indicated mutual increased risks of AKI and sepsis. Then, 311 key genes common to sepsis and AKI were identified, with 42 significantly linked to sepsis prognosis. Six genes, selected through LASSO, SVM-RFE, and RF algorithms, showed excellent predictive performance for sepsis, AKI, and SA-AKI. The models demonstrated near-perfect AUCs in both training and testing datasets, and a perfect AUC in a sepsis mouse model. Significant differences in immune cells, immune-related pathways, HLA, and checkpoint genes were found between high- and low-risk groups. The study identified 62 potential drug treatments for sepsis and AKI and constructed a ceRNA network.

CONCLUSIONS

The identified signature genes hold potential clinical applications, including prognostic evaluation and targeted therapeutic strategies for sepsis and AKI. However, further research is needed to confirm these findings.

Pancreatic cancer organoid-screening captures personalized sensitivity and chemoresistance suppression upon cytochrome P450 3A5-targeted inhibition

Cytochrome P450 3A5 (CYP3A5) has been proposed as a predictor of therapy response in subtypes of pancreatic ductal adenocarcinoma cancer (PDAC). To validate CYP3A5 as a therapeutic target, we developed a high-content image organoid-based screen to quantify the phenotypic responses to the selective inhibition of CYP3A5 enzymatic activity by clobetasol propionate (CBZ), using a cohort of PDAC-derived organoids (PDACOs). The chemoresistance of PDACOs to a panel of standard-of-care drugs, alone or in combination with CBZ, was investigated. PDACO pharmaco-profiling revealed CBZ to have anti-cancer activity that was dependent on the CYP3A5 level. In addition, CBZ restored chemo-vulnerability to cisplatin in a subset of PDACOs. A correlative proteomic analysis established that CBZ caused the suppression of multiple cancer pathways sustained by or associated with a mutant form of p53. Limiting the active pool of CYP3A5 enables targeted and personalized therapy to suppress pro-oncogenic mechanisms that fuel chemoresistance in some PDAC tumors.

Midkine Attenuates Aβ Fibril Assembly and AmyloidPlaque Formation

Proteomic profiling of Alzheimer's disease (AD) brains has identified numerous understudied proteins, including midkine (MDK), that are highly upregulated and correlated with Aβ since the early disease stage, but their roles in disease progression are not fully understood. Here we present that MDK attenuates Aβ assembly and influences amyloid formation in the 5xFAD amyloidosis mouse model. MDK protein mitigates fibril formation of both Aβ40 and Aβ42 peptides in Thioflavin T fluorescence assay, circular dichroism, negative stain electron microscopy, and NMR analysis. Knockout of Mdkgene in 5xFAD increases amyloid formation and microglial activation. Further comprehensive mass spectrometry-based profiling of whole proteome and aggregated proteome in these mouse models indicates significant accumulation of Aβ and Aβ-correlated proteins, along with microglial components. Thus, our structural and mouse model studies reveal a protective role of MDK in counteracting amyloid pathology in Alzheimer's disease.

Evaluation of Protein Identification and Quantification by the diaPASEF Method on timsTOF SCP

Accurate and precise quantification is crucial in modern proteomics, particularly in the context of exploring low-amount samples. While the innovative 4D-data-independent acquisition (DIA) quantitative proteomics facilitated by timsTOF mass spectrometers gives enhanced sensitivity and selectivity for protein identification, the diaPASEF (parallel accumulation-serial fragmentation combined with data-independent acquisition) parameters have not been systematically optimized, and a comprehensive evaluation of the quantification is currently lacking. In this study, we conducted a thorough optimization of key parameters on a timsTOF SCP instrument, including sample loading amount (50 ng), ramp/accumulation time (140 ms), isolation window width (20 m/z), and gradient time (60 min). To further improve the identification of proteins in low-amount samples, we utilized different column settings and introduced 0.02% n-dodecyl-β-d-maltoside (DDM) in the sample reconstitution solution, resulting in a remarkable 19-fold increase in protein identification at the single-cell-equivalent level. Moreover, a comprehensive comparison of protein quantification using a tandem mass tag reporter (TMT-reporter), complement TMT ions (TMTc), and diaPASEF revealed a strong correlation between these methods. Both diaPASEF and TMTc have effectively addressed the issue of ratio compression, highlighting the diaPASEF method's effectiveness in achieving accurate quantification data compared to TMT reporter quantification. Additionally, an in-depth analysis of in-group variation positioned diaPASEF between the TMT-reporter and TMTc methods. Therefore, diaPASEF quantification on the timsTOF SCP instrument emerges as a precise and accurate methodology for quantitative proteomics, especially for samples with small amounts.

Exercise-Regulated Mitochondrial and Nuclear Signalling Networks in Skeletal Muscle

Exercise perturbs energy homeostasis in skeletal muscle and engages integrated cellular signalling networks to help meet the contraction-induced increases in skeletal muscle energy and oxygen demand. Investigating exercise-associated perturbations in skeletal muscle signalling networks has uncovered novel mechanisms by which exercise stimulates skeletal muscle mitochondrial biogenesis and promotes whole-body health and fitness. While acute exercise regulates a complex network of protein post-translational modifications (e.g. phosphorylation) in skeletal muscle, previous investigations of exercise signalling in human and rodent skeletal muscle have primarily focused on a select group of exercise-regulated protein kinases [i.e. 5' adenosine monophosphate-activated protein kinase (AMPK), protein kinase A (PKA), Ca2+/calmodulin-dependent protein kinase (CaMK) and mitogen-activated protein kinase (MAPK)] and only a small subset of their respective protein substrates. Recently, global mass spectrometry-based phosphoproteomic approaches have helped unravel the extensive complexity and interconnection of exercise signalling pathways and kinases beyond this select group and phosphorylation and/or translocation of exercise-regulated mitochondrial and nuclear protein substrates. This review provides an overview of recent advances in our understanding of the molecular events associated with acute endurance exercise-regulated signalling pathways and kinases in skeletal muscle with a focus on phosphorylation. We critically appraise recent evidence highlighting the involvement of mitochondrial and nuclear protein phosphorylation and/or translocation in skeletal muscle adaptive responses to an acute bout of endurance exercise that ultimately stimulate mitochondrial biogenesis and contribute to exercise's wider health and fitness benefits.

Integrated proteomics reveals autophagy landscape and an autophagy receptor controlling PKA-RI complex homeostasis in neurons

Autophagy is a conserved, catabolic process essential for maintaining cellular homeostasis. Malfunctional autophagy contributes to neurodevelopmental and neurodegenerative diseases. However, the exact role and targets of autophagy in human neurons remain elusive. Here we report a systematic investigation of neuronal autophagy targets through integrated proteomics. Deep proteomic profiling of multiple autophagy-deficient lines of human induced neurons, mouse brains, and brain LC3-interactome reveals roles of neuronal autophagy in targeting proteins of multiple cellular organelles/pathways, including endoplasmic reticulum (ER), mitochondria, endosome, Golgi apparatus, synaptic vesicle (SV) for degradation. By combining phosphoproteomics and functional analysis in human and mouse neurons, we uncovered a function of neuronal autophagy in controlling cAMP-PKA and c-FOS-mediated neuronal activity through selective degradation of the protein kinase A - cAMP-binding regulatory (R)-subunit I (PKA-RI) complex. Lack of AKAP11 causes accumulation of the PKA-RI complex in the soma and neurites, demonstrating a constant clearance of PKA-RI complex through AKAP11-mediated degradation in neurons. Our study thus reveals the landscape of autophagy degradation in human neurons and identifies a physiological function of autophagy in controlling homeostasis of PKA-RI complex and specific PKA activity in neurons.

Profiling Protein-Protein Interactions in the Human Brain by Refined Cofractionation Mass Spectrometry

Proteins usually execute their biological functions through interactions with other proteins and by forming macromolecular complexes, but global profiling of protein complexes directly from human tissue samples has been limited. In this study, we utilized cofractionation mass spectrometry (CF-MS) to map protein complexes within the postmortem human brain with experimental replicates. First, we used concatenated anion and cation Ion Exchange Chromatography (IEX) to separate native protein complexes in 192 fractions and then proceeded with Data-Independent Acquisition (DIA) mass spectrometry to analyze the proteins in each fraction, quantifying a total of 4,804 proteins with 3,260 overlapping in both replicates. We improved the DIA's quantitative accuracy by implementing a constant amount of bovine serum albumin (BSA) in each fraction as an internal standard. Next, advanced computational pipelines, which integrate both a database-based complex analysis and an unbiased protein-protein interaction (PPI) search, were applied to identify protein complexes and construct protein-protein interaction networks in the human brain. Our study led to the identification of 486 protein complexes and 10054 binary protein-protein interactions, which represents the first global profiling of human brain PPIs using CF-MS. Overall, this study offers a resource and tool for a wide range of human brain research, including the identification of disease-specific protein complexes in the future.

The ubiquitin-conjugating enzyme UBE2D/eff maintains a youthful proteome and ensures protein quality control during aging

Ubiquitin-conjugating enzymes (E2s) are key for regulating protein function and turnover via ubiquitination but it remains undetermined which E2s maintain proteostasis during aging. Here, we find that E2s have diverse roles in handling a model aggregation-prone protein (huntingtin-polyQ) in the Drosophila retina: while some E2s mediate aggregate assembly, UBE2D/effete (eff) and other E2s are required for huntingtin-polyQ degradation. UBE2D/eff is key for proteostasis also in skeletal muscle: eff protein levels decline with aging, and muscle-specific eff knockdown causes an accelerated buildup in insoluble poly-ubiquitinated proteins (which progressively accumulate with aging) and shortens lifespan. Transgenic expression of human UBE2D2, homologous to eff, partially rescues the lifespan and proteostasis deficits caused by muscle-specific effRNAi by re-establishing the physiological levels of effRNAi-regulated proteins, which include several regulators of proteostasis. Interestingly, UBE2D/eff knockdown in young age reproduces part of the proteomic changes that normally occur in old muscles, suggesting that the decrease in UBE2D/eff protein levels that occurs with aging contributes to reshaping the composition of the muscle proteome. Altogether, these findings indicate that UBE2D/eff is a key E2 ubiquitin-conjugating enzyme that ensures protein quality control and helps maintain a youthful proteome composition during aging.

Selective CK1α degraders exert antiproliferative activity against a broad range of human cancer cell lines

Molecular-glue degraders are small molecules that induce a specific interaction between an E3 ligase and a target protein, resulting in the target proteolysis. The discovery of molecular glue degraders currently relies mostly on screening approaches. Here, we describe screening of a library of cereblon (CRBN) ligands against a panel of patient-derived cancer cell lines, leading to the discovery of SJ7095, a potent degrader of CK1α, IKZF1 and IKZF3 proteins. Through a structure-informed exploration of structure activity relationship (SAR) around this small molecule we develop SJ3149, a selective and potent degrader of CK1α protein in vitro and in vivo. The structure of SJ3149 co-crystalized in complex with CK1α + CRBN + DDB1 provides a rationale for the improved degradation properties of this compound. In a panel of 115 cancer cell lines SJ3149 displays a broad antiproliferative activity profile, which shows statistically significant correlation with MDM2 inhibitor Nutlin-3a. These findings suggest potential utility of selective CK1α degraders for treatment of hematological cancers and solid tumors.

Profiling Mouse Brain Single-Cell-Type Proteomes Via Adeno-Associated Virus-Mediated Proximity Labeling and Mass Spectrometry

Single-cell-type proteomics is an emerging field of research that combines cell-type specificity with the comprehensive proteome coverage offered by bulk proteomics. However, the extraction of single-cell-type proteomes remains a challenge, particularly for hard-to-isolate cells like neurons. In this chapter, we present an innovative technique for profiling single-cell-type proteomes using adeno-associated virus (AAV)-mediated proximity labeling (PL) and tandem-mass-tag (TMT) mass spectrometry. This technique eliminates the need for cell isolation and offers a streamlined workflow, including AAV delivery to express TurboID (an engineered biotin ligase) controlled by cell-type-specific promoters, biotinylated protein purification, on-bead digestion, TMT labeling, and liquid chromatography-mass spectrometry (LC-MS). We examined this method by analyzing distinct brain cell types in mice. Initially, recombinant AAVs were used to concurrently express TurboID and mCherry proteins driven by neuron- or astrocyte-specific promoters, which was validated through co-immunostaining with cellular markers. With biotin purification and TMT analysis, we successfully identified around 10,000 unique proteins from a few micrograms of protein samples with high reproducibility. Our statistical analyses revealed that these proteomes encompass cell-type-specific cellular pathways. By utilizing this technique, researchers can explore the proteomic landscape of specific cell types, paving the way for new insights into cellular processes, deciphering disease mechanisms, and identifying therapeutic targets in neuroscience and beyond.

Chemo-proteomics in antimalarial target identification and engagement

Humans have lived in tenuous battle with malaria over millennia. Today, while much of the world is free of the disease, areas of South America, Asia, and Africa still wage this war with substantial impacts on their social and economic development. The threat of widespread resistance to all currently available antimalarial therapies continues to raise concern. Therefore, it is imperative that novel antimalarial chemotypes be developed to populate the pipeline going forward. Phenotypic screening has been responsible for the majority of the new chemotypes emerging in the past few decades. However, this can result in limited information on the molecular target of these compounds which may serve as an unknown variable complicating their progression into clinical development. Target identification and validation is a process that incorporates techniques from a range of different disciplines. Chemical biology and more specifically chemo-proteomics have been heavily utilized for this purpose. This review provides an in-depth summary of the application of chemo-proteomics in antimalarial development. Here we focus particularly on the methodology, practicalities, merits, and limitations of designing these experiments. Together this provides learnings on the future use of chemo-proteomics in antimalarial development.

Multi-omic atlas of the parahippocampal gyrus in Alzheimer's disease

Alzheimer's disease (AD) is the most common form of dementia worldwide, with a projection of 151 million cases by 2050. Previous genetic studies have identified three main genes associated with early-onset familial Alzheimer's disease, however this subtype accounts for less than 5% of total cases. Next-generation sequencing has been well established and holds great promise to assist in the development of novel therapeutics as well as biomarkers to prevent or slow the progression of this devastating disease. Here we present a public resource of functional genomic data from the parahippocampal gyrus of 201 postmortem control, mild cognitively impaired (MCI) and AD individuals from the Mount Sinai brain bank, of which whole-genome sequencing (WGS), and bulk RNA sequencing (RNA-seq) were previously published. The genomic data include bulk proteomics and DNA methylation, as well as cell-type-specific RNA-seq and assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) data. We have performed extensive preprocessing and quality control, allowing the research community to access and utilize this public resource available on the Synapse platform at https://doi.org/10.7303/syn51180043.2 .

Dissecting Detergent-Insoluble Proteome in Alzheimer's Disease by TMTc-Corrected Quantitative Mass Spectrometry

Protein aggregation of amyloid-β peptides and tau are pathological hallmarks of Alzheimer's disease (AD), which are often resistant to detergent extraction and thus enriched in the insoluble proteome. However, additional proteins that coaccumulate in the detergent-insoluble AD brain proteome remain understudied. Here, we comprehensively characterized key proteins and pathways in the detergent-insoluble proteome from human AD brain samples using differential extraction, tandem mass tag (TMT) labeling, and two-dimensional LC-tandem mass spectrometry. To improve quantification accuracy of the TMT method, we developed a complement TMT-based strategy to correct for ratio compression. Through the meta-analysis of two independent detergent-insoluble AD proteome datasets (8914 and 8917 proteins), we identified 190 differentially expressed proteins in AD compared with control brains, highlighting the pathways of amyloid cascade, RNA splicing, endocytosis/exocytosis, protein degradation, and synaptic activity. To differentiate the truly detergent-insoluble proteins from copurified background during protein extraction, we analyzed the fold of enrichment for each protein by comparing the detergent-insoluble proteome with the whole proteome from the same AD samples. Among the 190 differentially expressed proteins, 84 (51%) proteins of the upregulated proteins (n = 165) were enriched in the insoluble proteome, whereas all downregulated proteins (n = 25) were not enriched, indicating that they were copurified components. The vast majority of these enriched 84 proteins harbor low-complexity regions in their sequences, including amyloid-β, Tau, TARDBP/TAR DNA-binding protein 43, SNRNP70/U1-70K, MDK, PTN, NTN1, NTN3, and SMOC1. Moreover, many of the enriched proteins in AD were validated in the detergent-insoluble proteome by five steps of differential extraction, proteomic analysis, or immunoblotting. Our study reveals a resource list of proteins and pathways that are exclusively present in the detergent-insoluble proteome, providing novel molecular insights to the formation of protein pathology in AD.

Tetraspanin Tspan8 restrains interferon signaling to stabilize intestinal epithelium by directing endocytosis of interferon receptor

Inflammation can impair intestinal barrier, while increased epithelial permeability can lead to inflammation. In this study, we found that the expression of Tspan8, a tetraspanin expressed specifically in epithelial cells, is downregulated in mouse model of ulcerative disease (UC) but correlated with those of cell-cell junction components, such as claudins and E-cadherin, suggesting that Tspan8 supports intestinal epithelial barrier. Tspan8 removal increases intestinal epithelial permeability and upregulates IFN-γ-Stat1 signaling. We also demonstrated that Tspan8 coalesces with lipid rafts and facilitates IFNγ-R1 localization at or near lipid rafts. As IFN-γ induces its receptor undergoing clathrin- or lipid raft-dependent endocytosis and IFN-γR endocytosis plays an important role in Jak-Stat1 signaling, our analysis on IFN-γR endocytosis revealed that Tspan8 silencing impairs lipid raft-mediated but promotes clathrin-mediated endocytosis of IFN-γR1, leading to increased Stat1 signaling. These changes in IFN-γR1 endocytosis upon Tspan8 silencing correlates with fewer lipid raft component GM1 at the cell surface and more clathrin heavy chain in the cells. Our findings indicate that Tspan8 determines the IFN-γR1 endocytosis route, to restrain Stat1 signaling, stabilize intestine epithelium, and subsequently prevent intestine from inflammation. Our finding also implies that Tspan8 is needed for proper endocytosis through lipid rafts.

Cellular responses to long-term phosphate starvation of fission yeast: Maf1 determines fate choice between quiescence and death associated with aberrant tRNA biogenesis

Inorganic phosphate is an essential nutrient acquired by cells from their environment. Here, we characterize the adaptative responses of fission yeast to chronic phosphate starvation, during which cells enter a state of quiescence, initially fully reversible upon replenishing phosphate after 2 days but resulting in gradual loss of viability during 4 weeks of starvation. Time-resolved analyses of changes in mRNA levels revealed a coherent transcriptional program in which phosphate dynamics and autophagy were upregulated, while the machineries for rRNA synthesis and ribosome assembly, and for tRNA synthesis and maturation, were downregulated in tandem with global repression of genes encoding ribosomal proteins and translation factors. Consistent with the transcriptome changes, proteome analysis highlighted global depletion of 102 ribosomal proteins. Concomitant with this ribosomal protein deficit, 28S and 18S rRNAs became vulnerable to site-specific cleavages that generated temporally stable rRNA fragments. The finding that Maf1, a repressor of RNA polymerase III transcription, was upregulated during phosphate starvation prompted a hypothesis that its activity might prolong lifespan of the quiescent cells by limiting production of tRNAs. Indeed, we found that deletion of maf1 results in precocious death of phosphate-starved cells via a distinctive starvation-induced pathway associated with tRNA overproduction and dysfunctional tRNA biogenesis.

Eucommia Polysaccharides Ameliorate Aging-Associated Gut Dysbiosis: A Potential Mechanism for Life Extension in Drosophila

The gut microbiota is increasingly considered to play a key role in human immunity and health. The aging process alters the microbiota composition, which is associated with inflammation, reactive oxygen species (ROS), decreased tissue function, and increased susceptibility to age-related diseases. It has been demonstrated that plant polysaccharides have beneficial effects on the gut microbiota, particularly in reducing pathogenic bacteria abundance and increasing beneficial bacteria populations. However, there is limited evidence of the effect of plant polysaccharides on age-related gut microbiota dysbiosis and ROS accumulation during the aging process. To explore the effect of Eucommiae polysaccharides (EPs) on age-related gut microbiota dysbiosis and ROS accumulation during the aging process of Drosophila, a series of behavioral and life span assays of Drosophila with the same genetic background in standard medium and a medium supplemented with EPs were performed. Next, the gut microbiota composition and protein composition of Drosophila in standard medium and the medium supplemented with EPs were detected using 16S rRNA gene sequencing analysis and quantitative proteomic analysis. Here, we show that supplementation of Eucommiae polysaccharides (EPs) during development leads to the life span extension of Drosophila. Furthermore, EPs decreased age-related ROS accumulation and suppressed Gluconobacter, Providencia, and Enterobacteriaceae in aged Drosophila. Increased Gluconobacter, Providencia, and Enterobacteriaceae in the indigenous microbiota might induce age-related gut dysfunction in Drosophila and shortens their life span. Our study demonstrates that EPs can be used as prebiotic agents to prevent aging-associated gut dysbiosis and reactive oxidative stress.

Proteasome inhibition targets the KMT2A transcriptional complex in acute lymphoblastic leukemia

Rearrangments in Histone-lysine-N-methyltransferase 2A (KMT2Ar) are associated with pediatric, adult and therapy-induced acute leukemias. Infants with KMT2Ar acute lymphoblastic leukemia (ALL) have a poor prognosis with an event-free-survival of 38%. Herein we evaluate 1116 FDA approved compounds in primary KMT2Ar infant ALL specimens and identify a sensitivity to proteasome inhibition. Upon exposure to this class of agents, cells demonstrate a depletion of histone H2B monoubiquitination (H2Bub1) and histone H3 lysine 79 dimethylation (H3K79me2) at KMT2A target genes in addition to a downregulation of the KMT2A gene expression signature, providing evidence that it targets the KMT2A transcriptional complex and alters the epigenome. A cohort of relapsed/refractory KMT2Ar patients treated with this approach on a compassionate basis had an overall response rate of 90%. In conclusion, we report on a high throughput drug screen in primary pediatric leukemia specimens whose results translate into clinically meaningful responses. This innovative treatment approach is now being evaluated in a multi-institutional upfront trial for infants with newly diagnosed ALL.

Evaluation of a Pooling Chemoproteomics Strategy with an FDA-Approved Drug Library

Chemoproteomics is a key platform for characterizing the mode of action for compounds, especially for targeted protein degraders such as proteolysis targeting chimeras (PROTACs) and molecular glues. With deep proteome coverage, multiplexed tandem mass tag-mass spectrometry (TMT-MS) can tackle up to 18 samples in a single experiment. Here, we present a pooling strategy for further enhancing the throughput and apply the strategy to an FDA-approved drug library (95 best-in-class compounds). The TMT-MS-based pooling strategy was evaluated in the following steps. First, we demonstrated the capability of TMT-MS by analyzing more than 15 000 unique proteins (> 12 000 gene products) in HEK293 cells treated with five PROTACs (two BRD/BET degraders and three degraders for FAK, ALK, and BTK kinases). We then introduced a rationalized pooling strategy to separate structurally similar compounds in different pools and identified the proteomic response to 14 pools from the drug library. Finally, we validated the proteomic response from one pool by reprofiling the cells via treatment with individual drugs with sufficient replicates. Interestingly, numerous proteins were found to change upon drug treatment, including AMD1, ODC1, PRKX, PRKY, EXO1, AEN, and LRRC58 with 7-hydroxystaurosporine; C6orf64, HMGCR, and RRM2 with Sorafenib; SYS1 and ALAS1 with Venetoclax; and ATF3, CLK1, and CLK4 with Palbocilib. Thus, pooling chemoproteomics screening provides an efficient method for dissecting the molecular targets of compound libraries.

Network-based assessment of HDAC6 activity predicts preclinical and clinical responses to the HDAC6 inhibitor ricolinostat in breast cancer

Inhibiting individual histone deacetylase (HDAC) is emerging as well-tolerated anticancer strategy compared with pan-HDAC inhibitors. Through preclinical studies, we demonstrated that the sensitivity to the leading HDAC6 inhibitor (HDAC6i) ricolinstat can be predicted by a computational network-based algorithm (HDAC6 score). Analysis of ~3,000 human breast cancers (BCs) showed that ~30% of them could benefice from HDAC6i therapy. Thus, we designed a phase 1b dose-escalation clinical trial to evaluate the activity of ricolinostat plus nab-paclitaxel in patients with metastatic BC (MBC) (NCT02632071). Study results showed that the two agents can be safely combined, that clinical activity is identified in patients with HR⁺/HER2^- disease and that the HDAC6 score has potential as predictive biomarker. Analysis of other tumor types also identified multiple cohorts with predicted sensitivity to HDAC6i's. Mechanistically, we have linked the anticancer activity of HDAC6i's to their ability to induce c-Myc hyperacetylation (ac-K148) promoting its proteasome-mediated degradation in sensitive cancer cells.

In-Depth Blood Proteome Profiling by Extensive Fractionation and Multiplexed Quantitative Mass Spectrometry

Blood in the circulatory system carries information of physiological and pathological status of the human body, so blood proteins are often used as biomarkers for diagnosis, prognosis, and therapy. Human blood proteome can be explored by the latest technologies in mass spectrometry (MS), creating an opportunity of discovering new disease biomarkers. The extreme dynamic range of protein concentrations in blood, however, poses a challenge to detect proteins of low abundance, namely, tissue leakage proteins. Here, we describe a strategy to directly analyze undepleted blood samples by extensive liquid chromatography (LC) fractionation and 18-plex tandem-mass-tag (TMT) mass spectrometry. The proteins in blood specimens (e.g., plasma or serum) are isolated by acetone precipitation and digested into peptides. The resulting peptides are TMT-labeled, separated by basic pH reverse-phase (RP) LC into at least 40 fractions, and analyzed by acidic pH RPLC and high-resolution MS/MS, leading to the quantification of ~3000 unique proteins. Further increase of basic pH RPLC fractions and adjustment of the fraction concatenation strategy can enhance the proteomic coverage (up to ~5000 proteins). Finally, the combination of multiple batches of TMT experiments allows the profiling of hundreds of blood samples. This TMT-MS-based method provides a powerful platform for deep proteome profiling of human blood samples.

Multi-omics analysis reveals expression complexity and functional diversity of mouse kinome

Protein kinases are a crucial component of signaling pathways involved in a wide range of cellular responses, including growth, proliferation, differentiation, and migration. Systematic investigation of protein kinases is critical to better understand phosphorylation-mediated signaling pathways and may provide insights into the development of potential therapeutic drug targets. Here we perform a systems-level analysis of the mouse kinome by analyzing multi-omics data. We used bulk and single-cell transcriptomic data from the C57BL/6J mouse strain to define tissue- and cell-type-specific expression of protein kinases, followed by investigating variations in sequence and expression between C57BL/6J and DBA/2J strains. We then profiled a deep brain phosphoproteome from C57BL/6J and DBA/2J strains as well as their reciprocal hybrids to infer the activity of the mouse kinome. Finally, we performed phenome-wide association analysis using the BXD recombinant inbred (RI) mice (a cross between C57BL/6J and DBA/2J strains) to identify any associations between variants in protein kinases and phenotypes. Collectively, our study provides a comprehensive analysis of the mouse kinome by investigating genetic sequence variation, tissue-specific expression patterns, and associations with downstream phenotypes.

Alzheimer's disease-associated U1 snRNP splicing dysfunction causes neuronal hyperexcitability and cognitive impairment

Recent proteome and transcriptome profiling of Alzheimer's disease (AD) brains reveals RNA splicing dysfunction and U1 small nuclear ribonucleoprotein (snRNP) pathology containing U1-70K and its N-terminal 40-KDa fragment (N40K). Here we present a causative role of U1 snRNP dysfunction to neurodegeneration in primary neurons and transgenic mice (N40K-Tg), in which N40K expression exerts a dominant-negative effect to downregulate full-length U1-70K. N40K-Tg recapitulates N40K insolubility, erroneous splicing events, neuronal degeneration and cognitive impairment. Specifically, N40K-Tg shows the reduction of GABAergic synapse components (e.g., the GABA receptor subunit of GABRA2), and concomitant postsynaptic hyperexcitability that is rescued by a GABA receptor agonist. Crossing of N40K-Tg and the 5xFAD amyloidosis model indicates that the RNA splicing defect synergizes with the amyloid cascade to remodel the brain transcriptome and proteome, deregulate synaptic proteins, and accelerate cognitive decline. Thus, our results support the contribution of U1 snRNP-mediated splicing dysfunction to AD pathogenesis.

Preclinical evaluation of proteolytic targeting of LCK as a therapeutic approach in T cell acute lymphoblastic leukemia

T cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy, and there is an unmet need for targeted therapies, especially for patients with relapsed disease. We have recently identified pre-T cell receptor and lymphocyte-specific protein tyrosine kinase (LCK) signaling as a common therapeutic vulnerability in T-ALL. LCK inhibitor dasatinib showed efficacy against T-ALL in preclinical studies and in patients with T-ALL; however, this is transient in most cases. Leveraging the proteolysis targeting chimera (PROTAC) approach, we developed a series of LCK degraders using dasatinib as an LCK ligand and phenyl-glutarimide as a cereblon-directing moiety. Our lead compound SJ11646 exhibited marked efficiency in cereblon-mediated LCK degradation in T-ALL cells. Relative to dasatinib, SJ11646 showed up to three orders of magnitude higher cytotoxicity in LCK-activated T-ALL cell lines and primary leukemia samples in vitro, with drastically prolonged suppression of LCK signaling. In vivo pharmacokinetic and pharmacodynamic profiling indicated a 630% increase in the duration of LCK suppression by SJ11646 over dasatinib in patient-derived xenograft models of T-ALL, which translated into its extended leukemia-free survival over dasatinib in vivo. Last, SJ11646 retained a high binding affinity to 51 human kinases, particularly ABL1, KIT, and DDR1, all of which are known drug targets in other cancers. Together, our dasatinib-based phenyl-glutarimide PROTACs are promising therapeutic agents in T-ALL and valuable tools for developing degradation-based therapeutics for other cancers.

Proteomic Alterations and Novel Markers of Neurotoxic Reactive Astrocytes in Human Induced Pluripotent Stem Cell Models

Astrocytes respond to injury, infection, and inflammation in the central nervous system by acquiring reactive states in which they may become dysfunctional and contribute to disease pathology. A sub-state of reactive astrocytes induced by proinflammatory factors TNF, IL-1α, and C1q ("TIC") has been implicated in many neurodegenerative diseases as a source of neurotoxicity. Here, we used an established human induced pluripotent stem cell (hiPSC) model to investigate the surface marker profile and proteome of TIC-induced reactive astrocytes. We propose VCAM1, BST2, ICOSL, HLA-E, PD-L1, and PDPN as putative, novel markers of this reactive sub-state. We found that several of these markers colocalize with GFAP+ cells in post-mortem samples from people with Alzheimer's disease. Moreover, our whole-cells proteomic analysis of TIC-induced reactive astrocytes identified proteins and related pathways primarily linked to potential engagement with peripheral immune cells. Taken together, our findings will serve as new tools to purify reactive astrocyte subtypes and to further explore their involvement in immune responses associated with injury and disease.

Mass Spectrometry for Neurobiomarker Discovery: The Relevance of Post-Translational Modifications

Neurodegenerative diseases are incurable, heterogeneous, and age-dependent disorders that challenge modern medicine. A deeper understanding of the pathogenesis underlying neurodegenerative diseases is necessary to solve the unmet need for new diagnostic biomarkers and disease-modifying therapy and reduce these diseases' burden. Specifically, post-translational modifications (PTMs) play a significant role in neurodegeneration. Due to its proximity to the brain parenchyma, cerebrospinal fluid (CSF) has long been used as an indirect way to measure changes in the brain. Mass spectrometry (MS) analysis in neurodegenerative diseases focusing on PTMs and in the context of biomarker discovery has improved and opened venues for analyzing more complex matrices such as brain tissue and blood. Notably, phosphorylated tau protein, truncated α-synuclein, APP and TDP-43, and many other modifications were extensively characterized by MS. Great potential is underlying specific pathological PTM-signatures for clinical application. This review focuses on PTM-modified proteins involved in neurodegenerative diseases and highlights the most important and recent breakthroughs in MS-based biomarker discovery.

Sex-Dependent Synaptic Remodeling of the Somatosensory Cortex in Mice With Prenatal Methadone Exposure

Rising opioid use among pregnant women has led to a growing population of neonates exposed to opioids during the prenatal period, but how opioids affect the developing brain remains to be fully understood. Animal models of prenatal opioid exposure have discovered deficits in somatosensory behavioral development that persist into adolescence suggesting opioid exposure induces long lasting neuroadaptations on somatosensory circuitry such as the primary somatosensory cortex (S1). Using a mouse model of prenatal methadone exposure (PME) that displays delays in somatosensory milestone development, we performed an un-biased multi-omics analysis and investigated synaptic functioning in the primary somatosensory cortex (S1), where touch and pain sensory inputs are received in the brain, of early adolescent PME offspring. PME was associated with numerous changes in protein and phosphopeptide abundances that differed considerably between sexes in the S1. Although prominent sex effects were discovered in the multi-omics assessment, functional enrichment analyses revealed the protein and phosphopeptide differences were associated with synapse-related cellular components and synaptic signaling-related biological processes, regardless of sex. Immunohistochemical analysis identified diminished GABAergic synapses in both layer 2/3 and 4 of PME offspring. These immunohistochemical and proteomic alterations were associated with functional consequences as layer 2/3 pyramidal neurons revealed reduced amplitudes and a lengthened decay constant of inhibitory postsynaptic currents. Lastly, in addition to reduced cortical thickness of the S1, cell-type marker analysis revealed reduced microglia density in the upper layer of the S1 that was primarily driven by PME females. Taken together, our studies show the lasting changes on synaptic function and microglia in S1 cortex caused by PME in a sex-dependent manner.

Deep Single-Cell-Type Proteome Profiling of Mouse Brain by Nonsurgical AAV-Mediated Proximity Labeling

Proteome profiling is a powerful tool in biological and biomedical studies, starting with samples at bulk, single-cell, or single-cell-type levels. Reliable methods for extracting specific cell-type proteomes are in need, especially for the cells (e.g., neurons) that cannot be readily isolated. Here, we present an innovative proximity labeling (PL) strategy for single-cell-type proteomics of mouse brain, in which TurboID (an engineered biotin ligase) is used to label almost all proteins in a specific cell type. This strategy bypasses the requirement of cell isolation and includes five major steps: (i) constructing recombinant adeno-associated viruses (AAVs) to express TurboID driven by cell-type-specific promoters, (ii) delivering the AAV to mouse brains by direct intravenous injection, (iii) enhancing PL labeling by biotin administration, (iv) purifying biotinylated proteins, followed by on-bead protein digestion, and (v) quantitative tandem-mass-tag (TMT) labeling. We first confirmed that TurboID can label a wide range of cellular proteins in human HEK293 cells and optimized the single-cell-type proteomic pipeline. To analyze specific brain cell types, we generated recombinant AAVs to coexpress TurboID and mCherry proteins, driven by neuron- or astrocyte-specific promoters and validated the expected cell expression by coimmunostaining of mCherry and cellular markers. Subsequent biotin purification and TMT analysis identified ∼10,000 unique proteins from a few micrograms of protein samples with excellent reproducibility. Comparative and statistical analyses indicated that these PL proteomes contain cell-type-specific cellular pathways. Although PL was originally developed for studying protein-protein interactions and subcellular proteomes, we extended it to efficiently tag the entire proteomes of specific cell types in the mouse brain using TurboID biotin ligase. This simple, effective in vivo approach should be broadly applicable to single-cell-type proteomics.

Identification of 14 Differentially-Expressed Metabolism-Related Genes as Potential Targets of Gastric Cancer by Integrated Proteomics and Transcriptomics

Although research on the metabolism related to gastric cancer (GC) is gradually gaining increasing interest, there are few studies regarding metabolism-related genes in GC. Understanding the characteristic changes of metabolism-related genes at the transcriptional and protein levels in GC will help us to identify new biomarkers and novel therapeutic targets. We harvested six pairs of samples from GC patients and evaluated the differentially expressed proteins using mass spectrometry-based proteomics. RNA sequencing was conducted simultaneously to detect the corresponding expression of mRNAs, and bioinformatics analysis was used to reveal the correlation of significant differentially expressed genes. A total of 57 genes were observed to be dysregulated both in proteomics and transcriptomics. Bioinformatics analysis showed that these differentially expressed genes were significantly associated with regulating metabolic activity. Further, 14 metabolic genes were identified as potential targets for GC patients and were related to immune cell infiltration. Moreover, we found that dysregulation of branched-chain amino acid transaminase 2 (BCAT2), one of the 14 differentially expressed metabolism-related genes, was associated with the overall survival time in GC patients. We believe that this study provides comprehensive information to better understand the mechanism underlying the progression of GC metastasis and explores the potential therapeutic and prognostic metabolism-related targets for GC.

Prenatal Opioid Exposure Impairs Endocannabinoid and Glutamate Transmission in the Dorsal Striatum

The opioid crisis has contributed to a growing population of children exposed to opioids during fetal development; however, many of the long-term effects of opioid exposure on development are unknown. We previously demonstrated that opioids have deleterious effects on endocannabinoid plasticity at glutamate synapses in the dorsal striatum of adolescent rodents, but it is unclear whether prenatal opioid exposure produces similar neuroadaptations. Using a mouse model of prenatal methadone exposure (PME), we performed proteomics, phosphoproteomics, and patch-clamp electrophysiology in the dorsolateral striatum (DLS) and dorsomedial striatum (DMS) to examine synaptic functioning in adolescent PME offspring. PME impacted the proteome and phosphoproteome in a region- and sex-dependent manner. Many proteins and phosphorylated proteins associated with glutamate transmission were differentially abundant in PME offspring, which was associated with reduced glutamate release in the DLS and altered the rise time of excitatory events in the DMS. Similarly, the intrinsic excitability properties of DMS neurons were significantly affected by PME. Last, pathway analyses revealed an enrichment in retrograde endocannabinoid signaling in the DLS, but not in the DMS, of males. Electrophysiology studies confirmed that endocannabinoid-mediated synaptic depression was impaired in the DLS, but not DMS, of PME-males. These results indicate that PME induces persistent neuroadaptations in the dorsal striatum and could contribute to the aberrant behavioral development described in offspring with prenatal opioid exposure.

Proteomic Profiling of Cerebrospinal Fluid by 16-Plex TMT-Based Mass Spectrometry

Mass spectrometry (MS) has become a mainstream platform for comprehensive profiling of proteome, especially with the improvement of multiplexed tandem mass tag labeling coupled with two-dimensional liquid chromatography and tandem mass spectrometry (TMT-LC/LC-MS/MS). Recently, we have established a robust method for direct profiling of undepleted cerebrospinal fluid (CSF) proteome with the 16-plex TMTpro method, in which we optimized parameters in experimental steps of sample preparation, TMT labeling, LC/LC fractionation, tandem mass spectrometry, and computational data processing. The extensive LC fractionation not only enhances proteome coverage of the CSF but also alleviates ratio distortion of TMT quantification. The crucial quality control steps and improvements specific for the TMT16 analysis are highlighted. More than 3000 proteins can be quantified in a single experiment from 16 different CSF samples. This multiplexed method offers a powerful tool for profiling a variety of complex biofluids samples such as CSF, serum/plasma, and other clinical specimens.

Integrated genomic and proteomic analyses identify stimulus-dependent molecular changes associated with distinct modes of skeletal muscle atrophy

Skeletal muscle atrophy is a debilitating condition that occurs with aging and disease, but the underlying mechanisms are incompletely understood. Previous work determined that common transcriptional changes occur in muscle during atrophy induced by different stimuli. However, whether this holds true at the proteome level remains largely unexplored. Here, we find that, contrary to this earlier model, distinct atrophic stimuli (corticosteroids, cancer cachexia, and aging) induce largely different mRNA and protein changes during muscle atrophy in mice. Moreover, there is widespread transcriptome-proteome disconnect. Consequently, atrophy markers (atrogenes) identified in earlier microarray-based studies do not emerge from proteomics as generally induced by atrophy. Rather, we identify proteins that are distinctly modulated by different types of atrophy (herein defined as “atroproteins”) such as the myokine CCN1/Cyr61, which regulates myofiber type switching during sarcopenia. Altogether, these integrated analyses indicate that different catabolic stimuli induce muscle atrophy via largely distinct mechanisms.

Skeletal muscle wasting is caused by many catabolic stimuli, which were thought to act via shared mechanisms. Hunt et al. now show that distinct catabolic stimuli induce muscle wasting via largely different molecular changes. The authors identify atrophy-associated proteins (“atroproteins”) that may represent diagnostic biomarkers and/or therapeutic targets.

Proteomic landscape of Alzheimer's Disease: novel insights into pathogenesis and biomarker discovery

Mass spectrometry-based proteomics empowers deep profiling of proteome and protein posttranslational modifications (PTMs) in Alzheimer's disease (AD). Here we review the advances and limitations in historic and recent AD proteomic research. Complementary to genetic mapping, proteomic studies not only validate canonical amyloid and tau pathways, but also uncover novel components in broad protein networks, such as RNA splicing, development, immunity, membrane transport, lipid metabolism, synaptic function, and mitochondrial activity. Meta-analysis of seven deep datasets reveals 2,698 differentially expressed (DE) proteins in the landscape of AD brain proteome (n = 12,017 proteins/genes), covering 35 reported AD genes and risk loci. The DE proteins contain cellular markers enriched in neurons, microglia, astrocytes, oligodendrocytes, and epithelial cells, supporting the involvement of diverse cell types in AD pathology. We discuss the hypothesized protective or detrimental roles of selected DE proteins, emphasizing top proteins in "amyloidome" (all biomolecules in amyloid plaques) and disease progression. Comprehensive PTM analysis represents another layer of molecular events in AD. In particular, tau PTMs are correlated with disease stages and indicate the heterogeneity of individual AD patients. Moreover, the unprecedented proteomic coverage of biofluids, such as cerebrospinal fluid and serum, procures novel putative AD biomarkers through meta-analysis. Thus, proteomics-driven systems biology presents a new frontier to link genotype, proteotype, and phenotype, accelerating the development of improved AD models and treatment strategies.

Ubiquitination is essential for recovery of cellular activities after heat shock

Eukaryotic cells respond to stress through adaptive programs that include reversible shutdown of key cellular processes, the formation of stress granules, and a global increase in ubiquitination. The primary function of this ubiquitination is thought to be for tagging damaged or misfolded proteins for degradation. Here, working in mammalian cultured cells, we found that different stresses elicited distinct ubiquitination patterns. For heat stress, ubiquitination targeted specific proteins associated with cellular activities that are down-regulated during stress, including nucleocytoplasmic transport and translation, as well as stress granule constituents. Ubiquitination was not required for the shutdown of these processes or for stress granule formation but was essential for the resumption of cellular activities and for stress granule disassembly. Thus, stress-induced ubiquitination primes the cell for recovery after heat stress.