Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry

The age-dependent regulation of pancreatic islet landscape is fueled by a HNF1a-immune signaling loop

Animal longevity is a function of global vital organ functionality and, consequently, a complex polygenic trait. Yet, monogenic regulators controlling overall or organ-specific ageing exist, owing their conservation to their function in growth and development. Here, by using pathway analysis combined with wet-biology methods on several dynamic timelines, we identified Hnf1a as a novel master regulator of the maturation and ageing in the adult pancreatic islet during the first year of life. Conditional transgenic mice bearing suboptimal levels of this transcription factor in the pancreatic islets displayed age-dependent changes, with a profile echoing precocious maturation. Additionally, the comparative pathway analysis revealed a link between Hnf1a age-dependent regulation and immune signaling, which was confirmed in the ageing timeline of an overly immunodeficient mouse model. Last, the global proteome analysis of human islets spanning three decades of life largely backed the age-specific regulation observed in mice. Collectively, our results suggest a novel role of Hnf1a as a monogenic regulator of the maturation and ageing process in the pancreatic islet via a direct or indirect regulatory loop with immune signaling.

Matrisome proteomics reveals novel mediators of muscle remodeling with aerobic exercise training

Skeletal muscle has a unique ability to remodel in response to stimuli such as contraction and aerobic exercise training. Phenotypic changes in muscle that occur with training such as a switch to a more oxidative fiber type, and increased capillary density contribute to the well-known health benefits of aerobic exercise. The muscle matrisome likely plays an important role in muscle remodeling with exercise. However, due to technical limitations in studying muscle ECM proteins, which are highly insoluble, little is known about the muscle matrisome and how it contributes to muscle remodeling. Here, we utilized two-fraction methodology to extract muscle proteins, combined with multiplexed tandem mass tag proteomic technology to identify 161 unique ECM proteins in mouse skeletal muscle. In addition, we demonstrate that aerobic exercise training induces remodeling of a significant proportion of the muscle matrisome. We performed follow-up experiments to validate exercise-regulated ECM targets in a separate cohort of mice using Western blotting and immunofluorescence imaging. Our data demonstrate that changes in several key ECM targets are strongly associated with muscle remodeling processes such as increased capillary density in mice. We also identify LOXL1 as a novel muscle ECM target associated with aerobic capacity in humans. In addition, publically available data and databases were used for in silico modeling to determine the likely cellular sources of exercise-induced ECM remodeling targets and identify ECM interaction networks. This work greatly enhances our understanding of ECM content and function in skeletal muscle and demonstrates an important role for ECM remodeling in the adaptive response to exercise. The raw MS data have been deposited to the ProteomeXchange with identifier PXD053003.

Ultrafast Proteomics

Current stage of proteomic research in the field of biology, medicine, development of new drugs, population screening, or personalized approaches to therapy dictates the need to analyze large sets of samples within the reasonable experimental time. Until recently, mass spectrometry measurements in proteomics were characterized as unique in identifying and quantifying cellular protein composition, but low throughput, requiring many hours to analyze a single sample. This was in conflict with the dynamics of changes in biological systems at the whole cellular proteome level upon the influence of external and internal factors. Thus, low speed of the whole proteome analysis has become the main factor limiting developments in functional proteomics, where it is necessary to annotate intracellular processes not only in a wide range of conditions, but also over a long period of time. Enormous level of heterogeneity of tissue cells or tumors, even of the same type, dictates the need to analyze biological systems at the level of individual cells. These studies involve obtaining molecular characteristics for tens, if not hundreds of thousands of individual cells, including their whole proteome profiles. Development of mass spectrometry technologies providing high resolution and mass measurement accuracy, predictive chromatography, new methods for peptide separation by ion mobility and processing of proteomic data based on artificial intelligence algorithms have opened a way for significant, if not radical, increase in the throughput of whole proteome analysis and led to implementation of the novel concept of ultrafast proteomics. Work done just in the last few years has demonstrated the proteome-wide analysis throughput of several hundred samples per day at a depth of several thousand proteins, levels unimaginable three or four years ago. The review examines background of these developments, as well as modern methods and approaches that implement ultrafast analysis of the entire proteome.

Covalent inhibition of pro-apoptotic BAX

BCL-2-associated X protein (BAX) is a promising therapeutic target for activating or restraining apoptosis in diseases of pathologic cell survival or cell death, respectively. In response to cellular stress, BAX transforms from a quiescent cytosolic monomer into a toxic oligomer that permeabilizes the mitochondria, releasing key apoptogenic factors. The mitochondrial lipid trans-2-hexadecenal (t-2-hex) sensitizes BAX activation by covalent derivatization of cysteine 126 (C126). In this study, we performed a disulfide tethering screen to discover C126-reactive molecules that modulate BAX activity. We identified covalent BAX inhibitor 1 (CBI1) as a compound that selectively derivatizes BAX at C126 and inhibits BAX activation by triggering ligands or point mutagenesis. Biochemical and structural analyses revealed that CBI1 can inhibit BAX by a dual mechanism of action: conformational constraint and competitive blockade of lipidation. These data inform a pharmacologic strategy for suppressing apoptosis in diseases of unwanted cell death by covalent targeting of BAX C126.

GPCR Function in Autophagy Control: A Systematic Approach of Chemical Intervention

Autophagy facilitates the degradation of cellular content via the lysosome and is involved in cellular homeostasis and stress response pathways. As such, malfunction of autophagy is linked to a variety of diseases ranging from organ-specific illnesses like cardiomyopathy to systemic illnesses such as cancer or metabolic syndromes. Given the variety of autophagic functions within a cell and tissue, regulation of autophagy is complex and contains numerous positive and negative feedback loops. While our knowledge of mechanisms for cargo selectivity has significantly improved over the last decade, our understanding of signaling routes activating individual autophagy pathways remains rather sparse. In this resource study, we report on a well-characterized chemical library containing 77 GPCR-targeting ligands that was used to systematically analyze LC3B-based autophagy as well as ER-phagy flux upon compound treatment. Upon others, compounds TC-G 1004, BAY 60-6583, PSNCBAM-1, TC-G 1008, LPA2 Antagonist 1, ML-154, JTC-801 and ML-290 targeting adenosine receptor A2a (ADORA2A), adenosine receptor A2b (ADORA2B), cannabinoid receptor 1 (CNR1), G-protein coupled receptor 39 (GPR39), lysophosphatidic acid receptor 2 (LPAR2), neuropeptide S receptor 1 (NPSR1), opioid related nociceptin receptor 1 (OPRL1), and relaxin receptor 1 (RXFP1), respectively, were hit compounds for general autophagy flux. From these compounds, only JTC-801 markly increased ER-phagy flux. In addition, the global impact of these selected hit compounds were analyzed by TMT-based mass spectrometry and demonstrated the differential impact of targeting GPCRs on autophagy-associated proteins. This chemical screening exercise indicates to a significant cross-talk between GPCR signaling and regulation of autophagy pathways.

Autophagic signaling promotes systems-wide remodeling in skeletal muscle upon oncometabolic stress by D2-HG

OBJECTIVES

Cachexia is a metabolic disorder and comorbidity with cancer and heart failure. The syndrome impacts more than thirty million people worldwide, accounting for 20% of all cancer deaths. In acute myeloid leukemia, somatic mutations of the metabolic enzyme isocitrate dehydrogenase 1 and 2 cause the production of the oncometabolite D2-hydroxyglutarate (D2-HG). Increased production of D2-HG is associated with heart and skeletal muscle atrophy, but the mechanistic links between metabolic and proteomic remodeling remain poorly understood. Therefore, we assessed how oncometabolic stress by D2-HG activates autophagy and drives skeletal muscle loss.

METHODS

We quantified genomic, metabolomic, and proteomic changes in cultured skeletal muscle cells and mouse models of IDH-mutant leukemia using RNA sequencing, mass spectrometry, and computational modeling.

RESULTS

D2-HG impairs NADH redox homeostasis in myotubes. Increased NAD+ levels drive activation of nuclear deacetylase Sirt1, which causes deacetylation and activation of LC3, a key regulator of autophagy. Using LC3 mutants, we confirm that deacetylation of LC3 by Sirt1 shifts its distribution from the nucleus into the cytosol, where it can undergo lipidation at pre-autophagic membranes. Sirt1 silencing or p300 overexpression attenuated autophagy activation in myotubes. In vivo, we identified increased muscle atrophy and reduced grip strength in response to D2-HG in male vs. female mice. In male mice, glycolytic intermediates accumulated, and protein expression of oxidative phosphorylation machinery was reduced. In contrast, female animals upregulated the same proteins, attenuating the phenotype in vivo. Network modeling and machine learning algorithms allowed us to identify candidate proteins essential for regulating oncometabolic adaptation in mouse skeletal muscle.

CONCLUSIONS

Our multi-omics approach exposes new metabolic vulnerabilities in response to D2-HG in skeletal muscle and provides a conceptual framework for identifying therapeutic targets in cachexia.

Introducing 'identification probability' for automated and transferable assessment of metabolite identification confidence in metabolomics and related studies

Methods for assessing compound identification confidence in metabolomics and related studies have been debated and actively researched for the past two decades. The earliest effort in 2007 focused primarily on mass spectrometry and nuclear magnetic resonance spectroscopy and resulted in four recommended levels of metabolite identification confidence - the Metabolite Standards Initiative (MSI) Levels. In 2014, the original MSI Levels were expanded to five levels (including two sublevels) to facilitate communication of compound identification confidence in high resolution mass spectrometry studies. Further refinement in identification levels have occurred, for example to accommodate use of ion mobility spectrometry in metabolomics workflows, and alternate approaches to communicate compound identification confidence also have been developed based on identification points schema. However, neither qualitative levels of identification confidence nor quantitative scoring systems address the degree of ambiguity in compound identifications in context of the chemical space being considered, are easily automated, or are transferable between analytical platforms. In this perspective, we propose that the metabolomics and related communities consider identification probability as an approach for automated and transferable assessment of compound identification and ambiguity in metabolomics and related studies. Identification probability is defined simply as 1/N, where N is the number of compounds in a reference library or chemical space that match to an experimentally measured molecule within user-defined measurement precision(s), for example mass measurement or retention time accuracy, etc. We demonstrate the utility of identification probability in an in silico analysis of multi-property reference libraries constructed from the Human Metabolome Database and computational property predictions, provide guidance to the community in transparent implementation of the concept, and invite the community to further evaluate this concept in parallel with their current preferred methods for assessing metabolite identification confidence.

Sequence-to-sequence translation from mass spectra to peptides with a transformer model

A fundamental challenge in mass spectrometry-based proteomics is the identification of the peptide that generated each acquired tandem mass spectrum. Approaches that leverage known peptide sequence databases cannot detect unexpected peptides and can be impractical or impossible to apply in some settings. Thus, the ability to assign peptide sequences to tandem mass spectra without prior information-de novo peptide sequencing-is valuable for tasks including antibody sequencing, immunopeptidomics, and metaproteomics. Although many methods have been developed to address this problem, it remains an outstanding challenge in part due to the difficulty of modeling the irregular data structure of tandem mass spectra. Here, we describe Casanovo, a machine learning model that uses a transformer neural network architecture to translate the sequence of peaks in a tandem mass spectrum into the sequence of amino acids that comprise the generating peptide. We train a Casanovo model from 30 million labeled spectra and demonstrate that the model outperforms several state-of-the-art methods on a cross-species benchmark dataset. We also develop a version of Casanovo that is fine-tuned for non-enzymatic peptides. Finally, we demonstrate that Casanovo's superior performance improves the analysis of immunopeptidomics and metaproteomics experiments and allows us to delve deeper into the dark proteome.

Spindle morphology changes between meiosis and mitosis driven by CK2 regulation of the Ran pathway

The transition from meiotic divisions in the oocyte to embryonic mitoses is a critical step in animal development. Despite negligible changes to cell size and shape, following fertilization the small, barrel-shaped meiotic spindle is replaced by a large zygotic spindle that nucleates abundant astral microtubules at spindle poles. To probe underlying mechanisms, we applied a drug screening approach using Ciona eggs and found that inhibition of Casein Kinase 2 (CK2) caused a shift from meiotic to mitotic-like spindle morphology with nucleation of robust astral microtubules, an effect reproduced in cytoplasmic extracts prepared from Xenopus eggs. In both species, CK2 activity decreased at fertilization. Phosphoproteomic differences between Xenopus meiotic and mitotic extracts that also accompanied CK2 inhibition pointed to RanGTP-regulated factors as potential targets. Interfering with RanGTP-driven microtubule formation suppressed astral microtubule growth caused by CK2 inhibition. These data support a model in which CK2 activity attenuation at fertilization leads to activation of RanGTP-regulated microtubule effectors that induce mitotic spindle morphology.

Covalent Interactions of Anthocyanins with Proteins: Activity-Based Protein Profiling of Cyanidin-3-O-glucoside

Anthocyanins are common natural pigments with a variety of physiological activities. Traditional perspectives attribute their molecular mechanism to noncovalent interactions influencing signaling pathways. However, this ignores the nature of its benzopyrylium skeleton, which readily reacts with the electron-rich groups of proteins. Here, we modified cyanidin-3-O-glucoside (C3G) via activity-based protein profiling technology by our previous synthesis route and prepared the covalent binding probe (C3G-Probe) and the noncovalent photoaffinity probe (C3G-Diazirine). The properties of C3G's covalent binding to proteins were also discovered by comparing the labeling of the two probes to the whole HepG2 cell proteome. We further explored its target proteins and enriched pathways in HepG2 and HeLa cells. Western blot analysis further confirmed the covalent binding of C3G to four target proteins: insulin-degrading enzyme, metal cation symporter ZIP14, spermatid perinuclear RNA-binding protein, and Cystatin-B. Pathway analysis showed that covalent targets of C3G were concentrated in metabolic pathways and several ribonucleoprotein complexes that were also coenriched. The results of this study provide new insights into the interaction of the naturally active molecule C3G with proteins.

Regulation of the DLC3 tumor suppressor by a novel phosphoswitch

Deleted in liver cancer 3 (DLC3) is a Rho GTPase-activating protein (RhoGAP) that plays a crucial role in maintaining adherens junction integrity and coordinating polarized vesicle transport by modulating Rho activity at the plasma membrane and endomembranes. By employing bioinformatical sequence analysis, in vitro experiments, and in cellulo assays we here identified a polybasic region (PBR) in DLC3 that facilitates the association of the protein with cellular membranes. Within the PBR, we mapped two serines whose phosphorylation can alter the electrostatic character of the region. Consequently, phosphomimetic mutations of these sites impaired the membrane association of DLC3. Furthermore, we found a new PBR-dependent localization of DLC3 at the midbody region, where the protein locally controlled Rho activity. Here, the phosphorylation-dependent regulation of DLC3 appeared to be required for proper cytokinesis. Our work thus provides a novel mechanism for spatiotemporal termination of Rho signaling by the RhoGAP protein DLC3.

Global protein turnover quantification in Escherichia coli reveals cytoplasmic recycling under nitrogen limitation

Protein turnover is critical for proteostasis, but turnover quantification is challenging, and even in well-studied E. coli, proteome-wide measurements remain scarce. Here, we quantify the turnover rates of ~3200 E. coli proteins under 13 conditions by combining heavy isotope labeling with complement reporter ion quantification and find that cytoplasmic proteins are recycled when nitrogen is limited. We use knockout experiments to assign substrates to the known cytoplasmic ATP-dependent proteases. Surprisingly, none of these proteases are responsible for the observed cytoplasmic protein degradation in nitrogen limitation, suggesting that a major proteolysis pathway in E. coli remains to be discovered. Lastly, we show that protein degradation rates are generally independent of cell division rates. Thus, we present broadly applicable technology for protein turnover measurements and provide a rich resource for protein half-lives and protease substrates in E. coli, complementary to genomics data, that will allow researchers to study the control of proteostasis.

The ribotoxic stress response drives UV-mediated cell death

While ultraviolet (UV) radiation damages DNA, eliciting the DNA damage response (DDR), it also damages RNA, triggering transcriptome-wide ribosomal collisions and eliciting a ribotoxic stress response (RSR). However, the relative contributions, timing, and regulation of these pathways in determining cell fate is unclear. Here we use time-resolved phosphoproteomic, chemical-genetic, single-cell imaging, and biochemical approaches to create a chronological atlas of signaling events activated in cells responding to UV damage. We discover that UV-induced apoptosis is mediated by the RSR kinase ZAK and not through the DDR. We identify two negative-feedback modules that regulate ZAK-mediated apoptosis: (1) GCN2 activation limits ribosomal collisions and attenuates ZAK-mediated RSR and (2) ZAK activity leads to phosphodegron autophosphorylation and its subsequent degradation. These events tune ZAK's activity to collision levels to establish regimes of homeostasis, tolerance, and death, revealing its key role as the cellular sentinel for nucleic acid damage.

FAM122A ensures cell cycle interphase progression and checkpoint control by inhibiting B55α/PP2A through helical motifs

The Ser/Thr protein phosphatase 2 A (PP2A) regulates the dephosphorylation of many phosphoproteins. Substrate recognition are mediated by B regulatory subunits. Here, we report the identification of a substrate conserved motif [RK]-V-x-x-[VI]-R in FAM122A, an inhibitor of B55α/PP2A. This motif is necessary for FAM122A binding to B55α, and computational structure prediction suggests the motif, which is helical, blocks substrate docking to the same site. In this model, FAM122A also spatially constrains substrate access by occluding the catalytic subunit. Consistently, FAM122A functions as a competitive inhibitor as it prevents substrate binding and dephosphorylation of CDK substrates by B55α/PP2A in cell lysates. FAM122A deficiency in human cell lines reduces the proliferation rate, cell cycle progression, and hinders G1/S and intra-S phase cell cycle checkpoints. FAM122A-KO in HEK293 cells attenuates CHK1 and CHK2 activation in response to replication stress. Overall, these data strongly suggest that FAM122A is a short helical motif (SHeM)-dependent, substrate-competitive inhibitor of B55α/PP2A that suppresses multiple functions of B55α in the DNA damage response and in timely progression through the cell cycle interphase.

Generation of a biliary tract cancer cell line atlas reveals molecular subtypes and therapeutic targets

Biliary tract cancers (BTCs) are a group of deadly malignancies encompassing intrahepatic and extrahepatic cholangiocarcinoma, gallbladder carcinoma, and ampullary carcinoma. Here, we present the integrative analysis of 63 BTC cell lines via multi-omics clustering and genome- scale CRISPR screens, providing a platform to illuminate BTC biology and inform therapeutic development. We identify dependencies broadly enriched in BTC compared to other cancers as well as dependencies selective to the anatomic subtypes. Notably, cholangiocarcinoma cell lines are stratified into distinct lineage subtypes based on biliary or dual biliary/hepatocyte marker signatures, associated with dependency on specific lineage survival factors. Transcriptional analysis of patient specimens demonstrates the prognostic significance of these lineage subtypes. Additionally, we delineate strategies to enhance targeted therapies or to overcome resistance in cell lines with key driver gene mutations. Furthermore, clustering based on dependencies and proteomics data elucidates unexpected functional relationships, including a BTC subgroup with partial squamous differentiation. Thus, this cell line atlas reveals potential therapeutic targets in molecularly defined BTCs, unveils biologically distinct disease subtypes, and offers a vital resource for BTC research.

Robustness of mitochondrial biogenesis and respiration explain aerobic glycolysis

A long-standing observation is that in fast-growing cells, respiration rate declines with increasing growth rate and is compensated by an increase in fermentation, despite respiration being more efficient than fermentation. This apparent preference for fermentation even in the presence of oxygen is known as aerobic glycolysis, and occurs in bacteria, yeast, and cancer cells. Considerable work has focused on understanding the potential benefits that might justify this seemingly wasteful metabolic strategy, but its mechanistic basis remains unclear. Here we show that aerobic glycolysis results from the saturation of mitochondrial respiration and the decoupling of mitochondrial biogenesis from the production of other cellular components. Respiration rate is insensitive to acute perturbations of cellular energetic demands or nutrient supplies, and is explained simply by the amount of mitochondria per cell. Mitochondria accumulate at a nearly constant rate across different growth conditions, resulting in mitochondrial amount being largely determined by cell division time. In contrast, glucose uptake rate is not saturated, and is accurately predicted by the abundances and affinities of glucose transporters. Combining these models of glucose uptake and respiration provides a quantitative, mechanistic explanation for aerobic glycolysis. The robustness of specific respiration rate and mitochondrial biogenesis, paired with the flexibility of other bioenergetic and biosynthetic fluxes, may play a broad role in shaping eukaryotic cell metabolism.

APIR: Aggregating Universal Proteomics Database Search Algorithms for Peptide Identification with FDR Control

Advances in mass spectrometry (MS) have enabled high-throughput analysis of proteomes in biological systems. The state-of-the-art MS data analysis relies on database search algorithms to quantify proteins by identifying peptide-spectrum matches (PSMs), which convert mass spectra to peptide sequences. Different database search algorithms use distinct search strategies and thus may identify unique PSMs. However, no existing approaches can aggregate all user-specified database search algorithms with a guaranteed increase in the number of identified peptides and a control on the false discovery rate (FDR). To fill in this gap, we proposed a statistical framework, Aggregation of Peptide Identification Results (APIR), that is universally compatible with all database search algorithms. Notably, under an FDR threshold, APIR is guaranteed to identify at least as many, if not more, peptides as individual database search algorithms do. Evaluation of APIR on a complex proteomics standard dataset showed that APIR outpowers individual database search algorithms and empirically controls the FDR. Real data studies showed that APIR can identify disease-related proteins and post-translational modifications missed by some individual database search algorithms. The APIR framework is easily extendable to aggregating discoveries made by multiple algorithms in other high-throughput biomedical data analysis, e.g., differential gene expression analysis on RNA sequencing data. The APIR R package is available at https://github.com/yiling0210/APIR.

SEMQuant: Extending Sipros-Ensemble with Match-Between-Runs for Comprehensive Quantitative Metaproteomics

Metaproteomics, utilizing high-throughput LC-MS, offers a profound understanding of microbial communities. Quantitative metaproteomics further enriches this understanding by measuring relative protein abundance and revealing dynamic changes under different conditions. However, the challenge of missing peptide quantification persists in metaproteomics analysis, particularly in data-dependent acquisition mode, where high-intensity precursors for MS2 scans are selected. To tackle this issue, the match-between-runs (MBR) technique is used to transfer peptides between LC-MS runs. Inspired by the benefits of MBR and the need for streamlined metaproteomics data analysis, we developed SEMQuant, an end-to-end software integrating Sipros-Ensemble's robust peptide identifications with IonQuant's MBR function. The experiments show that SEMQuant consistently obtains the highest or second highest number of quantified proteins with notable precision and accuracy. This demonstrates SEMQuant's effectiveness in conducting comprehensive and accurate quantitative metaproteomics analyses across diverse datasets and highlights its potential to propel advancements in microbial community studies. SEMQuant is freely available under the GNU GPL license at https://github.com/Biocomputing-Research-Group/SEMQuant.

Enhanced mapping of small-molecule binding sites in cells

Photoaffinity probes are routinely utilized to identify proteins that interact with small molecules. However, despite this common usage, resolving the specific sites of these interactions remains a challenge. Here we developed a chemoproteomic workflow to determine precise protein binding sites of photoaffinity probes in cells. Deconvolution of features unique to probe-modified peptides, such as their tendency to produce chimeric spectra, facilitated the development of predictive models to confidently determine labeled sites. This yielded an expansive map of small-molecule binding sites on endogenous proteins and enabled the integration with multiplexed quantitation, increasing the throughput and dimensionality of experiments. Finally, using structural information, we characterized diverse binding sites across the proteome, providing direct evidence of their tractability to small molecules. Together, our findings reveal new knowledge for the analysis of photoaffinity probes and provide a robust method for high-resolution mapping of reversible small-molecule interactions en masse in native systems.

A small-molecule microtubule-stabilizing agent safely reduces Aβ plaque and tau pathology in transgenic mouse models of Alzheimer's disease

INTRODUCTION

Intraneuronal inclusions composed of tau protein are found in Alzheimer's disease (AD) and other tauopathies. Tau normally binds microtubules (MTs), and its disengagement from MTs and misfolding in AD is thought to result in MT abnormalities. We previously identified triazolopyrimidine-containing MT-stabilizing compounds that provided benefit in AD mouse models and herein describe the characterization and efficacy testing of an optimized candidate, CNDR-51997.

METHODS

CNDR-51997 underwent pharmacokinetic, pharmacodynamic, safety pharmacology, and mouse tolerability testing. In addition, the compound was examined for efficacy in 5XFAD amyloid beta (Aβ) plaque mice and PS19 tauopathy mice.

RESULTS

CNDR-51997 significantly reduced Aβ plaques in 5XFAD mice and tau pathology in PS19 mice, with the latter also showing attenuated axonal dystrophy and gliosis. CNDR-51997 was well tolerated at doses that exceeded efficacy doses, with a good safety pharmacology profile.

DISCUSSION

CNDR-51997 may be a candidate for advancement as a potential therapeutic agent for AD and/or other tauopathies. Highlights There is evidence of microtubule alterations (MT) in Alzheimer's disease (AD) brain and in mouse models of AD pathology. Intermittent dosing with an optimized, brain-penetrant MT-stabilizing small-molecule, CNDR-51997, reduced both Aβ plaque and tau inclusion pathology in established mouse models of AD. CNDR-51997 attenuated axonal dystrophy and gliosis in a tauopathy mouse model, with a strong trend toward reduced hippocampal neuron loss. CNDR-51997 is well tolerated in mice at doses that are meaningfully greater than required for efficacy in AD mouse models, and the compound has a good safety pharmacology profile.

Structure and topography of the synaptic V-ATPase-synaptophysin complex

Synaptic vesicles are organelles with a precisely defined protein and lipid composition1,2, yet the molecular mechanisms for the biogenesis of synaptic vesicles are mainly unknown. Here we discovered a well-defined interface between the synaptic vesicle V-ATPase and synaptophysin by in situ cryo-electron tomography and single-particle cryo-electron microscopy of functional synaptic vesicles isolated from mouse brains3. The synaptic vesicle V-ATPase is an ATP-dependent proton pump that establishes the proton gradient across the synaptic vesicle, which in turn drives the uptake of neurotransmitters4,5. Synaptophysin6 and its paralogues synaptoporin7 and synaptogyrin8 belong to a family of abundant synaptic vesicle proteins whose function is still unclear. We performed structural and functional studies of synaptophysin-knockout mice, confirming the identity of synaptophysin as an interaction partner with the V-ATPase. Although there is little change in the conformation of the V-ATPase upon interaction with synaptophysin, the presence of synaptophysin in synaptic vesicles profoundly affects the copy number of V-ATPases. This effect on the topography of synaptic vesicles suggests that synaptophysin assists in their biogenesis. In support of this model, we observed that synaptophysin-knockout mice exhibit severe seizure susceptibility, suggesting an imbalance of neurotransmitter release as a physiological consequence of the absence of synaptophysin.

Rescoring Peptide Spectrum Matches: Boosting Proteomics Performance by Integrating Peptide Property Predictors Into Peptide Identification

Rescoring of peptide spectrum matches originating from database search engines enabled by peptide property predictors is exceeding the performance of peptide identification from traditional database search engines. In contrast to the peptide spectrum match scores calculated by traditional database search engines, rescoring peptide spectrum matches generates scores based on comparing observed and predicted peptide properties, such as fragment ion intensities and retention times. These newly generated scores enable a more efficient discrimination between correct and incorrect peptide spectrum matches. This approach was shown to lead to substantial improvements in the number of confidently identified peptides, facilitating the analysis of challenging datasets in various fields such as immunopeptidomics, metaproteomics, proteogenomics, and single-cell proteomics. In this review, we summarize the key elements leading up to the recent introduction of multiple data-driven rescoring pipelines. We provide an overview of relevant post-processing rescoring tools, introduce prominent data-driven rescoring pipelines for various applications, and highlight limitations, opportunities, and future perspectives of this approach and its impact on mass spectrometry-based proteomics.

The Hao-Fountain syndrome protein USP7 regulates neuronal connectivity in the brain via a novel p53-independent ubiquitin signaling pathway

Precise control of protein ubiquitination is essential for brain development, and hence, disruption of ubiquitin signaling networks can lead to neurological disorders. Mutations of the deubiquitinase USP7 cause the Hao-Fountain syndrome (HAFOUS), characterized by developmental delay, intellectual disability, autism, and aggressive behavior. Here, we report that conditional deletion of USP7 in excitatory neurons in the mouse forebrain triggers diverse phenotypes including sensorimotor deficits, learning and memory impairment, and aggressive behavior, resembling clinical features of HAFOUS. USP7 deletion induces neuronal apoptosis in a manner dependent of the tumor suppressor p53. However, most behavioral abnormalities in USP7 conditional mice persist despite p53 loss. Strikingly, USP7 deletion in the brain perturbs the synaptic proteome and dendritic spine morphogenesis independently of p53. Integrated proteomics analysis reveals that the neuronal USP7 interactome is enriched for proteins implicated in neurodevelopmental disorders and specifically identifies the RNA splicing factor Ppil4 as a novel neuronal substrate of USP7. Knockdown of Ppil4 in cortical neurons impairs dendritic spine morphogenesis, phenocopying the effect of USP7 loss on dendritic spines. These findings reveal a novel USP7-Ppil4 ubiquitin signaling link that regulates neuronal connectivity in the developing brain, with implications for our understanding of the pathogenesis of HAFOUS and other neurodevelopmental disorders.

An algorithm for decoy-free false discovery rate estimation in XL-MS/MS proteomics

MOTIVATION

Cross-linking tandem mass spectrometry (XL-MS/MS) is an established analytical platform used to determine distance constraints between residues within a protein or from physically interacting proteins, thus improving our understanding of protein structure and function. To aid biological discovery with XL-MS/MS, it is essential that pairs of chemically linked peptides be accurately identified, a process that requires: (i) database search, that creates a ranked list of candidate peptide pairs for each experimental spectrum and (ii) false discovery rate (FDR) estimation, that determines the probability of a false match in a group of top-ranked peptide pairs with scores above a given threshold. Currently, the only available FDR estimation mechanism in XL-MS/MS is the target-decoy approach (TDA). However, despite its simplicity, TDA has both theoretical and practical limitations that impact the estimation accuracy and increase run time over potential decoy-free approaches (DFAs).

RESULTS

We introduce a novel decoy-free framework for FDR estimation in XL-MS/MS. Our approach relies on multi-sample mixtures of skew normal distributions, where the latent components correspond to the scores of correct peptide pairs (both peptides identified correctly), partially incorrect peptide pairs (one peptide identified correctly, the other incorrectly), and incorrect peptide pairs (both peptides identified incorrectly). To learn these components, we exploit the score distributions of first- and second-ranked peptide-spectrum matches for each experimental spectrum and subsequently estimate FDR using a novel expectation-maximization algorithm with constraints. We evaluate the method on ten datasets and provide evidence that the proposed DFA is theoretically sound and a viable alternative to TDA owing to its good performance in terms of accuracy, variance of estimation, and run time.

AVAILABILITY AND IMPLEMENTATION

https://github.com/shawn-peng/xlms.

A learned score function improves the power of mass spectrometry database search

MOTIVATION

One of the core problems in the analysis of protein tandem mass spectrometry data is the peptide assignment problem: determining, for each observed spectrum, the peptide sequence that was responsible for generating the spectrum. Two primary classes of methods are used to solve this problem: database search and de novo peptide sequencing. State-of-the-art methods for de novo sequencing use machine learning methods, whereas most database search engines use hand-designed score functions to evaluate the quality of a match between an observed spectrum and a candidate peptide from the database. We hypothesized that machine learning models for de novo sequencing implicitly learn a score function that captures the relationship between peptides and spectra, and thus may be re-purposed as a score function for database search. Because this score function is trained from massive amounts of mass spectrometry data, it could potentially outperform existing, hand-designed database search tools.

RESULTS

To test this hypothesis, we re-engineered Casanovo, which has been shown to provide state-of-the-art de novo sequencing capabilities, to assign scores to given peptide-spectrum pairs. We then evaluated the statistical power of this Casanovo score function, Casanovo-DB, to detect peptides on a benchmark of three mass spectrometry runs from three different species. In addition, we show that re-scoring with the Percolator post-processor benefits Casanovo-DB more than other score functions, further increasing the number of detected peptides.

Alkylamine-tethered molecules recruit FBXO22 for targeted protein degradation

Targeted protein degradation (TPD) relies on small molecules to recruit proteins to E3 ligases to induce their ubiquitylation and degradation by the proteasome. Only a few of the approximately 600 human E3 ligases are currently amenable to this strategy. This limits the actionable target space and clinical opportunities and thus establishes the necessity to expand to additional ligases. Here we identify and characterize SP3N, a specific degrader of the prolyl isomerase FKBP12. SP3N features a minimal design, where a known FKBP12 ligand is appended with a flexible alkylamine tail that conveys degradation properties. We found that SP3N is a precursor and that the alkylamine is metabolized to an active aldehyde species that recruits the SCFFBXO22 ligase for FKBP12 degradation. Target engagement occurs via covalent adduction of Cys326 in the FBXO22 C-terminal domain, which is critical for ternary complex formation, ubiquitylation and degradation. This mechanism is conserved for two recently reported alkylamine-based degraders of NSD2 and XIAP, thus establishing alkylamine tethering and covalent hijacking of FBXO22 as a generalizable TPD strategy.

A novel clinical metaproteomics workflow enables bioinformatic analysis of host-microbe dynamics in disease

Clinical metaproteomics has the potential to offer insights into the host-microbiome interactions underlying diseases. However, the field faces challenges in characterizing microbial proteins found in clinical samples, usually present at low abundance relative to the host proteins. As a solution, we have developed an integrated workflow coupling mass spectrometry-based analysis with customized bioinformatic identification, quantification, and prioritization of microbial proteins, enabling targeted assay development to investigate host-microbe dynamics in disease. The bioinformatics tools are implemented in the Galaxy ecosystem, offering the development and dissemination of complex bioinformatic workflows. The modular workflow integrates MetaNovo (to generate a reduced protein database), SearchGUI/PeptideShaker and MaxQuant [to generate peptide-spectral matches (PSMs) and quantification], PepQuery2 (to verify the quality of PSMs), Unipept (for taxonomic and functional annotation), and MSstatsTMT (for statistical analysis). We have utilized this workflow in diverse clinical samples, from the characterization of nasopharyngeal swab samples to bronchoalveolar lavage fluid. Here, we demonstrate its effectiveness via analysis of residual fluid from cervical swabs. The complete workflow, including training data and documentation, is available via the Galaxy Training Network, empowering non-expert researchers to utilize these powerful tools in their clinical studies.

IMPORTANCE

Clinical metaproteomics has immense potential to offer functional insights into the microbiome and its contributions to human disease. However, there are numerous challenges in the metaproteomic analysis of clinical samples, including handling of very large protein sequence databases for sensitive and accurate peptide and protein identification from mass spectrometry data, as well as taxonomic and functional annotation of quantified peptides and proteins to enable interpretation of results. To address these challenges, we have developed a novel clinical metaproteomics workflow that provides customized bioinformatic identification, verification, quantification, and taxonomic and functional annotation. This bioinformatic workflow is implemented in the Galaxy ecosystem and has been used to characterize diverse clinical sample types, such as nasopharyngeal swabs and bronchoalveolar lavage fluid. Here, we demonstrate its effectiveness and availability for use by the research community via analysis of residual fluid from cervical swabs.

An autoinhibitory switch of the LSD1 disordered region controls enhancer silencing

Transcriptional coregulators and transcription factors (TFs) contain intrinsically disordered regions (IDRs) that are critical for their association and function in gene regulation. More recently, IDRs have been shown to promote multivalent protein-protein interactions between coregulators and TFs to drive their association into condensates. By contrast, here we demonstrate how the IDR of the corepressor LSD1 excludes TF association, acting as a dynamic conformational switch that tunes repression of active cis-regulatory elements. Hydrogen-deuterium exchange shows that the LSD1 IDR interconverts between transient open and closed conformational states, the latter of which inhibits partitioning of the protein's structured domains with TF condensates. This autoinhibitory switch controls leukemic differentiation by modulating repression of active cis-regulatory elements bound by LSD1 and master hematopoietic TFs. Together, these studies unveil alternative mechanisms by which disordered regions and their dynamic crosstalk with structured regions can shape coregulator-TF interactions to control cis-regulatory landscapes and cell fate.

RNA quality control factors nucleate Clr4/SUV39H and trigger constitutive heterochromatin assembly

In eukaryotes, the Suv39 family of proteins tri-methylate lysine 9 of histone H3 (H3K9me) to form constitutive heterochromatin. However, how Suv39 proteins are nucleated at heterochromatin is not fully described. In the fission yeast, current models posit that Argonaute1-associated small RNAs (sRNAs) nucleate the sole H3K9 methyltransferase, Clr4/SUV39H, to centromeres. Here, we show that in the absence of all sRNAs and H3K9me, the Mtl1 and Red1 core (MTREC)/PAXT complex nucleates Clr4/SUV39H at a heterochromatic long noncoding RNA (lncRNA) at which the two H3K9 deacetylases, Sir2 and Clr3, also accumulate by distinct mechanisms. Iterative cycles of H3K9 deacetylation and methylation spread Clr4/SUV39H from the nucleation center in an sRNA-independent manner, generating a basal H3K9me state. This is acted upon by the RNAi machinery to augment and amplify the Clr4/H3K9me signal at centromeres to establish heterochromatin. Overall, our data reveal that lncRNAs and RNA quality control factors can nucleate heterochromatin and function as epigenetic silencers in eukaryotes.

Top-down proteomics

Proteoforms, which arise from post-translational modifications, genetic polymorphisms and RNA splice variants, play a pivotal role as drivers in biology. Understanding proteoforms is essential to unravel the intricacies of biological systems and bridge the gap between genotypes and phenotypes. By analysing whole proteins without digestion, top-down proteomics (TDP) provides a holistic view of the proteome and can decipher protein function, uncover disease mechanisms and advance precision medicine. This Primer explores TDP, including the underlying principles, recent advances and an outlook on the future. The experimental section discusses instrumentation, sample preparation, intact protein separation, tandem mass spectrometry techniques and data collection. The results section looks at how to decipher raw data, visualize intact protein spectra and unravel data analysis. Additionally, proteoform identification, characterization and quantification are summarized, alongside approaches for statistical analysis. Various applications are described, including the human proteoform project and biomedical, biopharmaceutical and clinical sciences. These are complemented by discussions on measurement reproducibility, limitations and a forward-looking perspective that outlines areas where the field can advance, including potential future applications.

Reinvestigating the Correctness of Decoy-Based False Discovery Rate Control in Proteomics Tandem Mass Spectrometry

Traditional database search methods for the analysis of bottom-up proteomics tandem mass spectrometry (MS/MS) data are limited in their ability to detect peptides with post-translational modifications (PTMs). Recently, "open modification" database search strategies, in which the requirement that the mass of the database peptide closely matches the observed precursor mass is relaxed, have become popular as ways to find a wider variety of types of PTMs. Indeed, in one study, Kong et al. reported that the open modification search tool MSFragger can achieve higher statistical power to detect peptides than a traditional "narrow window" database search. We investigated this claim empirically and, in the process, uncovered a potential general problem with false discovery rate (FDR) control in the machine learning postprocessors Percolator and PeptideProphet. This problem might have contributed to Kong et al.'s report that their empirical results suggest that false discovery (FDR) control in the narrow window setting might generally be compromised. Indeed, reanalyzing the same data while using a more standard form of target-decoy competition-based FDR control, we found that, after accounting for chimeric spectra as well as for the inherent difference in the number of candidates in open and narrow searches, the data does not provide sufficient evidence that FDR control in proteomics MS/MS database search is inherently problematic.

PIPI2: Sensitive Tag-Based Database Search to Identify Peptides with Multiple Post-translational Modifications

Peptide identification is important in bottom-up proteomics. Post-translational modifications (PTMs) are crucial in regulating cellular activities. Many database search methods have been developed to identify peptides with PTMs and characterize the PTM patterns. However, the PTMs on peptides hinder the peptide identification rate and the PTM characterization precision, especially for peptides with multiple PTMs. To address this issue, we present a sensitive open search engine, PIPI2, with much better performance on peptides with multiple PTMs than other methods. With a greedy approach, we simplify the PTM characterization problem into a linear one, which enables characterizing multiple PTMs on one peptide. On the simulation data sets with up to four PTMs per peptide, PIPI2 identified over 90% of the spectra, at least 56% more than five other competitors. PIPI2 also characterized these PTM patterns with the highest precision of 77%, demonstrating a significant advantage in handling peptides with multiple PTMs. In the real applications, PIPI2 identified 30% to 88% more peptides with PTMs than its competitors.

mTORC1-CTLH E3 ligase regulates the degradation of HMG-CoA synthase 1 through the Pro/N-degron pathway

Mammalian target of rapamycin (mTOR) senses changes in nutrient status and stimulates the autophagic process to recycle amino acids. However, the impact of nutrient stress on protein degradation beyond autophagic turnover is incompletely understood. We report that several metabolic enzymes are proteasomal targets regulated by mTOR activity based on comparative proteome degradation analysis. In particular, 3-hydroxy-3-methylglutaryl (HMG)-coenzyme A (CoA) synthase 1 (HMGCS1), the initial enzyme in the mevalonate pathway, exhibits the most significant half-life adaptation. Degradation of HMGCS1 is regulated by the C-terminal to LisH (CTLH) E3 ligase through the Pro/N-degron motif. HMGCS1 is ubiquitylated on two C-terminal lysines during mTORC1 inhibition, and efficient degradation of HMGCS1 in cells requires a muskelin adaptor. Importantly, modulating HMGCS1 abundance has a dose-dependent impact on cell proliferation, which is restored by adding a mevalonate intermediate. Overall, our unbiased degradomics study provides new insights into mTORC1 function in cellular metabolism: mTORC1 regulates the stability of limiting metabolic enzymes through the ubiquitin system.

The MYCN oncoprotein is an RNA-binding accessory factor of the nuclear exosome targeting complex

The MYCN oncoprotein binds active promoters in a heterodimer with its partner protein MAX. MYCN also interacts with the nuclear exosome, a 3'-5' exoribonuclease complex, suggesting a function in RNA metabolism. Here, we show that MYCN forms stable high-molecular-weight complexes with the exosome and multiple RNA-binding proteins. MYCN binds RNA in vitro and in cells via a conserved sequence termed MYCBoxI. In cells, MYCN associates with thousands of intronic transcripts together with the ZCCHC8 subunit of the nuclear exosome targeting complex and enhances their processing. Perturbing exosome function results in global re-localization of MYCN from promoters to intronic RNAs. On chromatin, MYCN is then replaced by the MNT(MXD6) repressor protein, inhibiting MYCN-dependent transcription. RNA-binding-deficient alleles show that RNA-binding limits MYCN's ability to activate cell growth-related genes but is required for MYCN's ability to promote progression through S phase and enhance the stress resilience of neuroblastoma cells.

Targetable leukaemia dependency on noncanonical PI3Kγ signalling

Phosphoinositide-3-kinase-γ (PI3Kγ) is implicated as a target to repolarize tumour-associated macrophages and promote antitumour immune responses in solid cancers1-4. However, cancer cell-intrinsic roles of PI3Kγ are unclear. Here, by integrating unbiased genome-wide CRISPR interference screening with functional analyses across acute leukaemias, we define a selective dependency on the PI3Kγ complex in a high-risk subset that includes myeloid, lymphoid and dendritic lineages. This dependency is characterized by innate inflammatory signalling and activation of phosphoinositide 3-kinase regulatory subunit 5 (PIK3R5), which encodes a regulatory subunit of PI3Kγ5 and stabilizes the active enzymatic complex. We identify p21 (RAC1)-activated kinase 1 (PAK1) as a noncanonical substrate of PI3Kγ that mediates this cell-intrinsic dependency and find that dephosphorylation of PAK1 by PI3Kγ inhibition impairs mitochondrial oxidative phosphorylation. Treatment with the selective PI3Kγ inhibitor eganelisib is effective in leukaemias with activated PIK3R5. In addition, the combination of eganelisib and cytarabine prolongs survival over either agent alone, even in patient-derived leukaemia xenografts with low baseline PIK3R5 expression, as residual leukaemia cells after cytarabine treatment have elevated G protein-coupled purinergic receptor activity and PAK1 phosphorylation. Together, our study reveals a targetable dependency on PI3Kγ-PAK1 signalling that is amenable to near-term evaluation in patients with acute leukaemia.

Decitabine cytotoxicity is promoted by dCMP deaminase DCTD and mitigated by SUMO-dependent E3 ligase TOPORS

The nucleoside analogue decitabine (or 5-aza-dC) is used to treat several haematological cancers. Upon its triphosphorylation and incorporation into DNA, 5-aza-dC induces covalent DNA methyltransferase 1 DNA-protein crosslinks (DNMT1-DPCs), leading to DNA hypomethylation. However, 5-aza-dC's clinical outcomes vary, and relapse is common. Using genome-scale CRISPR/Cas9 screens, we map factors determining 5-aza-dC sensitivity. Unexpectedly, we find that loss of the dCMP deaminase DCTD causes 5-aza-dC resistance, suggesting that 5-aza-dUMP generation is cytotoxic. Combining results from a subsequent genetic screen in DCTD-deficient cells with the identification of the DNMT1-DPC-proximal proteome, we uncover the ubiquitin and SUMO1 E3 ligase, TOPORS, as a new DPC repair factor. TOPORS is recruited to SUMOylated DNMT1-DPCs and promotes their degradation. Our study suggests that 5-aza-dC-induced DPCs cause cytotoxicity when DPC repair is compromised, while cytotoxicity in wild-type cells arises from perturbed nucleotide metabolism, potentially laying the foundations for future identification of predictive biomarkers for decitabine treatment.

ZmPILS6 is an auxin efflux carrier required for maize root morphogenesis

Plant root systems play a pivotal role in plant physiology and exhibit diverse phenotypic traits. Understanding the genetic mechanisms governing root growth and development in model plants like maize is crucial for enhancing crop resilience to drought and nutrient limitations. This study focused on identifying and characterizing ZmPILS6, an annotated auxin efflux carrier, as a key regulator of various crown root traits in maize. ZmPILS6-modified roots displayed reduced network area and suppressed lateral root formation, which are desirable traits for the "steep, cheap, and deep" ideotype. The research revealed that ZmPILS6 localizes to the endoplasmic reticulum and plays a vital role in controlling the spatial distribution of indole-3-acetic acid (IAA or "auxin") in primary roots. The study also demonstrated that ZmPILS6 can actively efflux IAA when expressed in yeast. Furthermore, the loss of ZmPILS6 resulted in significant proteome remodeling in maize roots, particularly affecting hormone signaling pathways. To identify potential interacting partners of ZmPILS6, a weighted gene coexpression analysis was performed. Altogether, this research contributes to the growing knowledge of essential genetic determinants governing maize root morphogenesis, which is crucial for guiding agricultural improvement strategies.

Activity-Based Protein Profiling to Probe Relationships between Cytochrome P450 Enzymes and Early-Age Metabolism of Two Polycyclic Aromatic Hydrocarbons (PAHs): Phenanthrene and Retene

A growing body of literature has linked early-life exposures to polycyclic aromatic hydrocarbons (PAH) with adverse neurodevelopmental effects. Once in the body, metabolism serves as a powerful mediator of PAH toxicity by bioactivating and detoxifying PAH metabolites. Since enzyme expression and activity vary considerably throughout human development, we evaluated infant metabolism of PAHs as a potential contributing factor to PAH susceptibility. We measured and compared rates of phenanthrene and retene (two primary PAH constituents of woodsmoke) metabolism in human hepatic microsomes from individuals ≤21 months of age to a pooled sample (n = 200) consisting primarily of adults. We used activity-based protein profiling (ABPP) to characterize cytochrome P450 enzymes (CYPs) in the same hepatic microsome samples. Once incubated in microsomes, phenanthrene demonstrated rapid depletion. Best-fit models for phenanthrene metabolism demonstrated either 1 or 2 phases, depending on the sample, indicating that multiple enzymes could metabolize phenanthrene. We observed no statistically significant differences in phenanthrene metabolism as a function of age, although samples from the youngest individuals had the slowest phenanthrene metabolism rates. We observed slower rates of retene metabolism compared with phenanthrene also in multiple phases. Rates of retene metabolism increased in an age-dependent manner until adult (pooled) metabolism rates were achieved at ∼12 months. ABPP identified 28 unique CYPs among all samples, and we observed lower amounts of active CYPs in individuals ≤21 months of age compared to the pooled sample. Phenanthrene metabolism correlated to CYPs 1A1, 1A2, 2C8, 4A22, 3A4, and 3A43 and retene metabolism correlated to CYPs 1A1, 1A2, and 2C8 measured by ABPP and vendor-supplied substrate marker activities. These results will aid efforts to determine human health risk and susceptibility to PAHs exposure during early life.

SRC inhibition enables formation of a growth suppressive MAGI1-PP2A complex in isocitrate dehydrogenase-mutant cholangiocarcinoma

Intrahepatic cholangiocarcinoma (ICC) is an aggressive bile duct malignancy that frequently exhibits isocitrate dehydrogenase (IDH1/IDH2) mutations. Mutant IDH (IDHm) ICC is dependent on SRC kinase for growth and survival and is hypersensitive to inhibition by dasatinib, but the molecular mechanism underlying this sensitivity is unclear. We found that dasatinib reduced p70 S6 kinase (S6K) and ribosomal protein S6 (S6), leading to substantial reductions in cell size and de novo protein synthesis. Using an unbiased phosphoproteomic screen, we identified membrane-associated guanylate kinase, WW, and PDZ domain containing 1 (MAGI1) as an SRC substrate in IDHm ICC. Biochemical and functional assays further showed that SRC inhibits a latent tumor-suppressing function of the MAGI1-protein phosphatase 2A (PP2A) complex to activate S6K/S6 signaling in IDHm ICC. Inhibiting SRC led to activation and increased access of PP2A to dephosphorylate S6K, resulting in cell death. Evidence from patient tissue and cell line models revealed that both intrinsic and extrinsic resistance to dasatinib is due to increased phospho-S6 (pS6). To block pS6, we paired dasatinib with the S6K/AKT inhibitor M2698, which led to a marked reduction in pS6 in IDHm ICC cell lines and patient-derived organoids in vitro and substantial growth inhibition in ICC patient-derived xenografts in vivo. Together, these results elucidated the mechanism of action of dasatinib in IDHm ICC, revealed a signaling complex regulating S6K phosphorylation independent of mTOR, suggested markers for dasatinib sensitivity, and described a combination therapy for IDHm ICC that may be actionable in the clinic.

BCAA-nitrogen flux in brown fat controls metabolic health independent of thermogenesis

Brown adipose tissue (BAT) is best known for thermogenesis. Rodent studies demonstrated that enhanced BAT thermogenesis is tightly associated with increased energy expenditure, reduced body weight, and improved glucose homeostasis. However, human BAT is protective against type 2 diabetes, independent of body weight. The mechanism underlying this dissociation remains unclear. Here, we report that impaired mitochondrial catabolism of branched-chain amino acids (BCAAs) in BAT, by deleting mitochondrial BCAA carriers (MBCs), caused systemic insulin resistance without affecting energy expenditure and body weight. Brown adipocytes catabolized BCAA in the mitochondria as nitrogen donors for the biosynthesis of non-essential amino acids and glutathione. Impaired mitochondrial BCAA-nitrogen flux in BAT resulted in increased oxidative stress, decreased hepatic insulin signaling, and decreased circulating BCAA-derived metabolites. A high-fat diet attenuated BCAA-nitrogen flux and metabolite synthesis in BAT, whereas cold-activated BAT enhanced the synthesis. This work uncovers a metabolite-mediated pathway through which BAT controls metabolic health beyond thermogenesis.

Characterization of the Pristionchus pacificus "epigenetic toolkit" reveals the evolutionary loss of the histone methyltransferase complex PRC2

Comparative approaches have revealed both divergent and convergent paths to achieving shared developmental outcomes. Thus, only through assembling multiple case studies can we understand biological principles. Yet, despite appreciating the conservation-or lack thereof-of developmental networks, the conservation of epigenetic mechanisms regulating these networks is poorly understood. The nematode Pristionchus pacificus has emerged as a model system of plasticity and epigenetic regulation as it exhibits a bacterivorous or omnivorous morph depending on its environment. Here, we determined the "epigenetic toolkit" available to P. pacificus as a resource for future functional work on plasticity, and as a comparison with Caenorhabditis elegans to investigate the conservation of epigenetic mechanisms. Broadly, we observed a similar cast of genes with putative epigenetic function between C. elegans and P. pacificus. However, we also found striking differences. Most notably, the histone methyltransferase complex PRC2 appears to be missing in P. pacificus. We described the deletion/pseudogenization of the PRC2 genes mes-2 and mes-6 and concluded that both were lost in the last common ancestor of P. pacificus and a related species P. arcanus. Interestingly, we observed the enzymatic product of PRC2 (H3K27me3) by mass spectrometry and immunofluorescence, suggesting that a currently unknown methyltransferase has been co-opted for heterochromatin silencing. Altogether, we have provided an inventory of epigenetic genes in P. pacificus to compare with C. elegans. This inventory will enable reverse-genetic experiments related to plasticity and has revealed the first loss of PRC2 in a multicellular organism.

FGFR inhibition blocks NF-ĸB-dependent glucose metabolism and confers metabolic vulnerabilities in cholangiocarcinoma

Genomic alterations that activate Fibroblast Growth Factor Receptor 2 (FGFR2) are common in intrahepatic cholangiocarcinoma (ICC) and confer sensitivity to FGFR inhibition. However, the depth and duration of response is often limited. Here, we conduct integrative transcriptomics, metabolomics, and phosphoproteomics analysis of patient-derived models to define pathways downstream of oncogenic FGFR2 signaling that fuel ICC growth and to uncover compensatory mechanisms associated with pathway inhibition. We find that FGFR2-mediated activation of Nuclear factor-κB (NF-κB) maintains a highly glycolytic phenotype. Conversely, FGFR inhibition blocks glucose uptake and glycolysis while inciting adaptive changes, including switching fuel source utilization favoring fatty acid oxidation and increasing mitochondrial fusion and autophagy. Accordingly, FGFR inhibitor efficacy is potentiated by combined mitochondrial targeting, an effect enhanced in xenograft models by intermittent fasting. Thus, we show that oncogenic FGFR2 signaling drives NF-κB-dependent glycolysis in ICC and that metabolic reprogramming in response to FGFR inhibition confers new targetable vulnerabilities.

SUMOylated Golgin45 associates with PML-NB to transcriptionally regulate lipid metabolism genes during heat shock stress

Golgin tethers are known to mediate vesicular transport in the secretory pathway, whereas it is relatively unknown whether they may mediate cellular stress response within the cell. Here, we describe a cellular stress response during heat shock stress via SUMOylation of a Golgin tether, Golgin45. We found that Golgin45 is a SUMOylated Golgin via SUMO1 under steady state condition. Upon heat shock stress, the Golgin enters the nucleus by interacting with Importin-β2 and gets further modified by SUMO3. Importantly, SUMOylated Golgin45 appears to interact with PML and SUMO-deficient Golgin45 mutant functions as a dominant negative for PML-NB formation during heat shock stress, suppressing transcription of lipid metabolism genes. These results indicate that Golgin45 may play a role in heat stress response by transcriptional regulation of lipid metabolism genes in SUMOylation-dependent fashion.

Proteome profiling identifies a link between the mitochondrial pathways and host-microbial sensor ELMO1 following Salmonella infection

The host EnguLfment and cell MOtility protein 1 (ELMO1) is a cytosolic microbial sensor that facilitates bacterial sensing, internalization, clearance, and inflammatory responses. We have shown previously that ELMO1 binds bacterial effector proteins, including pathogenic effectors from Salmonella and controls host innate immune signaling. To understand the ELMO1-regulated host pathways, we have performed liquid chromatography Multinotch MS3-Tandem Mass Tag (TMT) multiplexed proteomics to determine the global quantification of proteins regulated by ELMO1 in macrophages during Salmonella infection. Comparative proteome analysis of control and ELMO1-depleted murine J774 macrophages after Salmonella infection quantified more than 7000 proteins with a notable enrichment in mitochondrial-related proteins. Gene ontology enrichment analysis revealed 19 upregulated and 11 downregulated proteins exclusive to ELMO1-depleted cells during infection, belonging to mitochondrial functions, metabolism, vesicle transport, and the immune system. By assessing the cellular energetics via Seahorse analysis, we found that Salmonella infection alters mitochondrial metabolism, shifting it from oxidative phosphorylation to glycolysis. Importantly, these metabolic changes are significantly influenced by the depletion of ELMO1. Furthermore, ELMO1 depletion resulted in a decreased ATP rate index following Salmonella infection, indicating its importance in counteracting the effects of Salmonella on immunometabolism. Among the proteins involved in mitochondrial pathways, mitochondrial fission protein DRP1 was significantly upregulated in ELMO1-depleted cells and in ELMO1-KO mice intestine following Salmonella infection. Pharmacological Inhibition of DRP1 revealed the link of the ELMO1-DRP1 pathway in regulating the pro-inflammatory cytokine TNF-α following infection. The role of ELMO1 has been further characterized by a proteome profile of ELMO1-depleted macrophage infected with SifA mutant and showed the involvement of ELMO1-SifA on mitochondrial function, metabolism and host immune/defense responses. Collectively, these findings unveil a novel role for ELMO1 in modulating mitochondrial functions, potentially pivotal in modulating inflammatory responses.

Significance Statement

Host microbial sensing is critical in infection and inflammation. Among these sensors, ELMO1 has emerged as a key regulator, finely tuning innate immune signaling and discriminating between pathogenic and non-pathogenic bacteria through interactions with microbial effectors like SifA of Salmonella . In this study, we employed Multinotch MS3-Tandem Mass Tag (TMT) multiplexed proteomics to determine the proteome alterations mediated by ELMO1 in macrophages following WT and SifA mutant Salmonella infection. Our findings highlight a substantial enrichment of host proteins associated with metabolic pathways and mitochondrial functions. Notably, we validated the mitochondrial fission protein DRP1 that is upregulated in ELMO1-depleted macrophages and in ELMO1 knockout mice intestine after infection. Furthermore, we demonstrated that Salmonella -induced changes in cellular energetics are influenced by the presence of ELMO1. This work shed light on a possible novel link between mitochondrial dynamics and microbial sensing in modulating immune responses.

Decoupling between the genetic potential and the metabolic regulation and expression in microbial organic matter cleavage across microbiomes

Metagenomics, metatranscriptomics, and metaproteomics are used to explore the microbial capability of enzyme secretion, but the links between protein-encoding genes and corresponding transcripts/proteins across ecosystems are underexplored. By conducting a multi-omics comparison focusing on key enzymes (carbohydrate-active enzymes [CAZymes] and peptidases) cleaving the main biomolecules across distinct microbiomes living in the ocean, soil, and human gut, we show that the community structure, functional diversity, and secretion mechanisms of microbial secretory CAZymes and peptidases vary drastically between microbiomes at metagenomic, metatranscriptomic, and metaproteomic levels. Such variations lead to decoupled relationships between CAZymes and peptidases from genetic potentials to protein expressions due to the different responses of key players toward organic matter sources and concentrations. Our results highlight the need for systematic analysis of the factors shaping patterns of microbial cleavage on organic matter to better link omics data to ecosystem processes.

IMPORTANCE

Omics tools are used to explore adaptive mechanism of microbes in diverse systems, but the advantages and limitations of different omics tools remain skeptical. Here, we reported distinct profiles in microbial secretory enzyme composition revealed by different omics methods. In general, the predicted function from metagenomic analysis decoupled from the expression of corresponding transcripts/proteins. Linking omics results to taxonomic origin, functional capability, substrate specificity, secretion preference, and enzymatic activity measurement suggested the substrate's source, concentration and stoichiometry impose strong filtering on the expression of extracellular enzymes, which may overwrite the genetic potentials. Our results present an integrated perspective on the need for multi-dimensional characterization of microbial adaptation in a changing environment.

Evidence that minocycline treatment confounds the interpretation of neurofilament as a biomarker

Neurofilament light (NfL) concentration in cerebrospinal fluid (CSF) and blood serves as an important biomarker in neurology drug development. Changes in NfL are generally assumed to reflect changes in neuronal damage, while little is known about the clearance of NfL from biofluids. We observed an NfL increase of 3.5-fold in plasma and 5.7-fold in CSF in an asymptomatic individual at risk for genetic prion disease following 6 weeks' treatment with oral minocycline for a dermatologic indication. Other biomarkers remained normal, and proteomic analysis of CSF revealed that the spike was exquisitely specific to neurofilaments. NfL dropped nearly to normal levels 5 weeks after minocycline cessation, and the individual remained free of disease 2 years later. Plasma NfL in dermatology patients was not elevated above normal controls. Dramatically high plasma NfL (>500 pg/mL) was variably observed in some hospitalized individuals receiving minocycline. In mice, treatment with minocycline resulted in variable increases of 1.3- to 4.0-fold in plasma NfL, with complete washout 2 weeks after cessation. In neuron-microglia co-cultures, minocycline increased NfL concentration in conditioned media by 3.0-fold without any visually obvious impact on neuronal health. We hypothesize that minocycline does not cause or exacerbate neuronal damage, but instead impacts the clearance of NfL from biofluids, a potential confounder for interpretation of this biomarker.

Fast and Accurate Disulfide Bridge Detection

Recombinant expression of proteins, propelled by therapeutic antibodies, has evolved into a multibillion dollar industry. Essential here is the quality control assessment of critical attributes, such as sequence fidelity, proper folding, and posttranslational modifications. Errors can lead to diminished bioactivity and, in the context of therapeutic proteins, an elevated risk for immunogenicity. Over the years, many techniques were developed and applied to validate proteins in a standardized and high-throughput fashion. One parameter has, however, so far been challenging to assess. Disulfide bridges, covalent bonds linking two cysteine residues, assist in the correct folding and stability of proteins and thus have a major influence on their efficacy. Mass spectrometry promises to be an optimal technique to uncover them in a fast and accurate fashion. In this work, we present a unique combination of sample preparation, data acquisition, and analysis facilitating the rapid and accurate assessment of disulfide bridges in purified proteins. Through microwave-assisted acid hydrolysis, the proteins are digested rapidly and artifact-free into peptides, with a substantial degree of overlap over the sequence. The nonspecific nature of this procedure, however, introduces chemical background, which is efficiently removed by integrating ion mobility preceding the mass spectrometric measurement. The nonspecific nature of the digestion step additionally necessitates new developments in data analysis, for which we extended the XlinkX node in Proteome Discoverer to efficiently process the data and ensure correctness through effective false discovery rate correction. The entire workflow can be completed within 1 h, allowing for high-throughput, high-accuracy disulfide mapping.

E-cadherin interacts with EGFR resulting in hyper-activation of ERK in multiple models of breast cancer

The loss of intercellular adhesion molecule E-cadherin is a hallmark of the epithelial-mesenchymal transition (EMT), during which tumor cells transition into an invasive phenotype. Accordingly, E-cadherin has long been considered a tumor suppressor gene; however, E-cadherin expression is paradoxically correlated with breast cancer survival rates. Using novel multi-compartment organoids and multiple in vivo models, we show that E-cadherin promotes a hyper-proliferative phenotype in breast cancer cells via interaction with the transmembrane receptor EGFR. The E-cad and EGFR interaction results in activation of the MEK/ERK signaling pathway, leading to a significant increase in proliferation via activation of transcription factors, including c-Fos. Pharmacological inhibition of MEK activity in E-cadherin positive breast cancer significantly decreases both tumor growth and macro-metastasis in vivo. This work provides evidence for a novel role of E-cadherin in breast tumor progression and identifies a new target to treat hyper-proliferative E-cadherin-positive breast tumors, thus providing the foundation to utilize E-cadherin as a biomarker for specific therapeutic success.

Profiling the interactome of oligonucleotide drugs by proximity biotinylation

Drug-ID is a novel method applying proximity biotinylation to identify drug-protein interactions inside living cells. The covalent conjugation of a drug with a biotin ligase enables targeted biotinylation and identification of the drug-bound proteome. We established Drug-ID for two small-molecule drugs, JQ1 and SAHA, and applied it for RNaseH-recruiting antisense oligonucleotides (ASOs). Drug-ID profiles the drug-protein interactome de novo under native conditions, directly inside living cells and at pharmacologically effective drug concentrations. It requires minimal amounts of cell material and might even become applicable in vivo. We studied the dose-dependent aggregation of ASOs and the effect of different wing chemistries (locked nucleic acid, 2'-methoxyethyl and 2'-Fluoro) and ASO lengths on the interactome. Finally, we demonstrate the detection of stress-induced, intracellular interactome changes (actinomycin D treatment) with an in situ variant of the approach, which uses a recombinant biotin ligase and does not require genetic manipulation of the target cell.

Impact of high-fat diet on cognitive behavior and central and systemic inflammation with aging and sex differences in mice

Aging and age-related diseases are associated with cellular stress, metabolic imbalance, oxidative stress, and neuroinflammation, accompanied by cognitive impairment. Lifestyle factors such as diet, sleep fragmentation, and stress can potentiate damaging cellular cascades and lead to an acceleration of brain aging and cognitive impairment. High-fat diet (HFD) has been associated with obesity, metabolic disorders like diabetes, and cardiovascular disease. HFD also induces neuroinflammation, impairs learning and memory, and may increase anxiety-like behavior. Effects of a HFD may also vary between sexes. The interaction between Age- and Sex- and Diet-related changes in neuroinflammation and cognitive function is an important and poorly understood area of research. This study was designed to examine the effects of HFD on neuroinflammation, behavior, and neurodegeneration in mice in the context of aging or sex differences. In a series of studies, young (2-3 months) or old (12-13 months) C57BL/6J male mice or young male and female C57Bl/6J mice were fed either a standard diet (SD) or a HFD for 5-6 months. Behavior was assessed in Activity Chamber, Y-maze, Novel Place Recognition, Novel Object Recognition, Elevated Plus Maze, Open Field, Morris Water Maze, and Fear Conditioning. Post-mortem analyses assessed a panel of inflammatory markers in the plasma and hippocampus. Additionally, proteomic analysis of the hypothalamus, neurodegeneration, neuroinflammation in the locus coeruleus, and neuroinflammation in the hippocampus were assessed in a subset of young and aged male mice. We show that HFD increased body weight and decreased locomotor activity across groups compared to control mice fed a SD. HFD altered anxiety-related exploratory behavior. HFD impaired spatial learning and recall in young male mice and impaired recall in cued fear conditioning in young and aged male mice, with no effects on spatial learning or fear conditioning in young female mice. Effects of Age and Sex were observed on neuroinflammatory cytokines, with only limited effects of HFD. HFD had a more significant impact on systemic inflammation in plasma across age and sex. Aged male mice had induction of microglial immunoreactivity in both the locus coeruleus (LC) and hippocampus an effect that HFD exacerbated in the hippocampal CA1 region. Proteomic analysis of the hypothalamus revealed changes in pathways related to metabolism and neurodegeneration with both aging and HFD in male mice. Our findings suggest that HFD induces widespread systemic inflammation and limited neuroinflammation. In addition, HFD alters exploratory behavior in male and female mice, and impairs learning and memory in male mice. These results provide valuable insight into the impact of diet on cognition and aging pathophysiology.