Active Instrument Engagement Combined with a Real-Time Database Search for Improved Performance of Sample Multiplexing Workflows

Context-Specific Stress Causes Compartmentalized SARM1 Activation and Local Degeneration in Cortical Neurons

Sterile alpha and TIR motif containing 1 (SARM1) is an inducible NADase that localizes to mitochondria throughout neurons and senses metabolic changes that occur after injury. Minimal proteomic changes are observed upon either SARM1 depletion or activation, suggesting that SARM1 does not exert broad effects on neuronal protein homeostasis. However, whether SARM1 activation occurs throughout the neuron in response to injury and cell stress remains largely unknown. Using a semiautomated imaging pipeline and a custom-built deep learning scoring algorithm, we studied degeneration in both mixed-sex mouse primary cortical neurons and male human-induced pluripotent stem cell-derived cortical neurons in response to a number of different stressors. We show that SARM1 activation is differentially restricted to specific neuronal compartments depending on the stressor. Cortical neurons undergo SARM1-dependent axon degeneration after mechanical transection, and SARM1 activation is limited to the axonal compartment distal to the injury site. However, global SARM1 activation following vacor treatment causes both cell body and axon degeneration. Context-specific stressors, such as microtubule dysfunction and mitochondrial stress, induce axonal SARM1 activation leading to SARM1-dependent axon degeneration and SARM1-independent cell body death. Our data reveal that compartment-specific SARM1-mediated death signaling is dependent on the type of injury and cellular stressor.

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 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.

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.

Lysosomal storage disease proteo/lipidomic profiling using nMOST links ferritinophagy with mitochondrial iron deficiencies in cells lacking NPC2

Lysosomal storage diseases (LSDs) comprised ~50 monogenic diseases characterized by the accumulation of cellular material in lysosomes and associated defects in lysosomal function, but systematic molecular phenotyping is lacking. Here, we develop a nanoflow-based multi-omic single-shot technology (nMOST) workflow allowing simultaneously quantify HeLa cell proteomes and lipidomes from more than two dozen LSD mutants, revealing diverse molecular phenotypes. Defects in delivery of ferritin and its autophagic receptor NCOA4 to lysosomes (ferritinophagy) were pronounced in NPC2-/- cells, which correlated with increased lyso-phosphatidylcholine species and multi-lamellar membrane structures visualized by cryo-electron-tomography. Ferritinophagy defects correlated with loss of mitochondrial cristae, MICOS-complex components, and electron transport chain complexes rich in iron-sulfur cluster proteins. Strikingly, mitochondrial defects were alleviated when iron was provided through the transferrin system. This resource reveals how defects in lysosomal function can impact mitochondrial homeostasis in trans and highlights nMOST as a discovery tool for illuminating molecular phenotypes across LSDs.

Orthogonal IMiD-Degron Pairs Induce Selective Protein Degradation in Cells

Immunomodulatory imide drugs (IMiDs) including thalidomide, lenalidomide, and pomalidomide, can be used to induce degradation of a protein of interest that is fused to a short zinc finger (ZF) degron motif. These IMiDs, however, also induce degradation of endogenous neosubstrates, including IKZF1 and IKZF3. To improve degradation selectivity, we took a bump-and-hole approach to design and screen bumped IMiD analogs against 8380 ZF mutants. This yielded a bumped IMiD analog that induces efficient degradation of a mutant ZF degron, while not affecting other cellular proteins, including IKZF1 and IKZF3. In proof-of-concept studies, this system was applied to induce efficient degradation of TRIM28, a disease-relevant protein with no known small molecule binders. We anticipate that this system will make a valuable addition to the current arsenal of degron systems for use in target validation.

Proteome-scale tissue mapping using mass spectrometry based on label-free and multiplexed workflows

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in both normal and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of ~3500 proteins at a spatial resolution of 50 μm and the largest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provide robust protein quantifications in terms of identifying differentially abundant proteins and spatially co-variable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables to identify protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial co-expression analysis.

UFM1 E3 ligase promotes recycling of 60S ribosomal subunits from the ER

Reversible modification of target proteins by ubiquitin and ubiquitin-like proteins (UBLs) is widely used by eukaryotic cells to control protein fate and cell behaviour1. UFM1 is a UBL that predominantly modifies a single lysine residue on a single ribosomal protein, uL24 (also called RPL26), on ribosomes at the cytoplasmic surface of the endoplasmic reticulum (ER)2,3. UFM1 conjugation (UFMylation) facilitates the rescue of 60S ribosomal subunits (60S) that are released after ribosome-associated quality-control-mediated splitting of ribosomes that stall during co-translational translocation of secretory proteins into the ER3,4. Neither the molecular mechanism by which the UFMylation machinery achieves such precise target selection nor how this ribosomal modification promotes 60S rescue is known. Here we show that ribosome UFMylation in vivo occurs on free 60S and we present sequential cryo-electron microscopy snapshots of the heterotrimeric UFM1 E3 ligase (E3(UFM1)) engaging its substrate uL24. E3(UFM1) binds the L1 stalk, empty transfer RNA-binding sites and the peptidyl transferase centre through carboxy-terminal domains of UFL1, which results in uL24 modification more than 150 Å away. After catalysing UFM1 transfer, E3(UFM1) remains stably bound to its product, UFMylated 60S, forming a C-shaped clamp that extends all the way around the 60S from the transfer RNA-binding sites to the polypeptide tunnel exit. Our structural and biochemical analyses suggest a role for E3(UFM1) in post-termination release and recycling of the large ribosomal subunit from the ER membrane.

NAK-associated protein 1/NAP1 activates TBK1 to ensure accurate mitosis and cytokinesis

Subcellular location and activation of Tank Binding Kinase 1 (TBK1) govern precise progression through mitosis. Either loss of activated TBK1 or its sequestration from the centrosomes causes errors in mitosis and growth defects. Yet, what regulates its recruitment and activation on the centrosomes is unknown. We identified that NAK-associated protein 1 (NAP1) is essential for mitosis, binding to and activating TBK1, which both localize to centrosomes. Loss of NAP1 causes several mitotic and cytokinetic defects due to inactivation of TBK1. Our quantitative phosphoproteomics identified numerous TBK1 substrates that are not only confined to the centrosomes but are also associated with microtubules. Substrate motifs analysis indicates that TBK1 acts upstream of other essential cell cycle kinases like Aurora and PAK kinases. We also identified NAP1 as a TBK1 substrate phosphorylating NAP1 at S318 to promote its degradation by the ubiquitin proteasomal system. These data uncover an important distinct function for the NAP1-TBK1 complex during cell division.

Increasing the Throughput and Reproducibility of Activity-Based Proteome Profiling Studies with Hyperplexing and Intelligent Data Acquisition

Intelligent data acquisition (IDA) strategies, such as a real-time database search (RTS), have improved the depth of proteome coverage for experiments that utilize isobaric labels and gas phase purification techniques (i.e., SPS-MS3). In this work, we introduce inSeqAPI, an instrument application programing interface (iAPI) program that enables construction of novel data acquisition algorithms. First, we analyze biotinylated cysteine peptides from ABPP experiments to demonstrate that a real-time search method within inSeqAPI performs similarly to an equivalent vendor method. Then, we describe PairQuant, a method within inSeqAPI designed for the hyperplexing approach that utilizes protein-level isotopic labeling and peptide-level TMT labeling. PairQuant allows for TMT analysis of 36 conditions in a single sample and achieves ∼98% coverage of both peptide pair partners in a hyperplexed experiment as well as a 40% improvement in the number of quantified cysteine sites compared with non-RTS acquisition. We applied this method in the ABPP study of ligandable cysteine sites in the nucleus leading to an identification of additional druggable sites on protein- and DNA-interaction domains of transcription regulators and on nuclear ubiquitin ligases.

Disruption of lysosomal proteolysis in astrocytes facilitates midbrain organoid proteostasis failure in an early-onset Parkinson's disease model

Accumulation of advanced glycation end products (AGEs) on biopolymers accompanies cellular aging and drives poorly understood disease processes. Here, we studied how AGEs contribute to development of early onset Parkinson's Disease (PD) caused by loss-of-function of DJ1, a protein deglycase. In induced pluripotent stem cell (iPSC)-derived midbrain organoid models deficient for DJ1 activity, we find that lysosomal proteolysis is impaired, causing AGEs to accumulate, α-synuclein (α-syn) phosphorylation to increase, and proteins to aggregate. We demonstrated these processes are at least partly driven by astrocytes, as DJ1 loss reduces their capacity to provide metabolic support and triggers acquisition of a pro-inflammatory phenotype. Consistently, in co-cultures, we find that DJ1-expressing astrocytes are able to reverse the proteolysis deficits of DJ1 knockout midbrain neurons. In conclusion, astrocytes' capacity to clear toxic damaged proteins is critical to preserve neuronal function and their dysfunction contributes to the neurodegeneration observed in a DJ1 loss-of-function PD model.

Proteomics protocol for obtaining extracellular vesicle from human plasma using asymmetrical flow field-flow fractionation technology

Plasma extracellular vesicles (EVs) represent a potential resource for biomarkers of multiple diseases. Here, we present a protocol for obtaining EVs from human plasma using asymmetrical flow field-flow fractionation technology. We describe steps for using tandem mass tags to perform comparative proteomic studies of a large clinical cohort. We then detail targeted quantitative analysis of differential proteins based on a parallel reaction monitoring technique. For complete details on the use and execution of this protocol, please refer to Wu et al. (2020)1 and Li et al. (2023).2.

Characterization of nucleolar SUMO isopeptidases unveils a general p53-independent checkpoint of impaired ribosome biogenesis

Ribosome biogenesis is a multi-step process, in which a network of trans-acting factors ensures the coordinated assembly of pre-ribosomal particles in order to generate functional ribosomes. Ribosome biogenesis is tightly coordinated with cell proliferation and its perturbation activates a p53-dependent cell-cycle checkpoint. How p53-independent signalling networks connect impaired ribosome biogenesis to the cell-cycle machinery has remained largely enigmatic. We demonstrate that inactivation of the nucleolar SUMO isopeptidases SENP3 and SENP5 disturbs distinct steps of 40S and 60S ribosomal subunit assembly pathways, thereby triggering the canonical p53-dependent impaired ribosome biogenesis checkpoint. However, inactivation of SENP3 or SENP5 also induces a p53-independent checkpoint that converges on the specific downregulation of the key cell-cycle regulator CDK6. We further reveal that impaired ribosome biogenesis generally triggers the downregulation of CDK6, independent of the cellular p53 status. Altogether, these data define the role of SUMO signalling in ribosome biogenesis and unveil a p53-independent checkpoint of impaired ribosome biogenesis.

The anaphase-promoting complex controls a ubiquitination-phosphoprotein axis in chromatin during neurodevelopment

Mutations in the degradative ubiquitin ligase anaphase-promoting complex (APC) alter neurodevelopment by impairing proteasomal protein clearance, but our understanding of their molecular and cellular pathogenesis remains limited. Here, we employ the proteomic-based discovery of APC substrates in APC mutant mouse brain and human cell lines and identify the chromosome-passenger complex (CPC), topoisomerase 2a (Top2a), and Ki-67 as major chromatin factors targeted by the APC during neuronal differentiation. These substrates accumulate in phosphorylated form, suggesting that they fail to be eliminated after mitosis during terminal differentiation. The accumulation of the CPC kinase Aurora B within constitutive heterochromatin and hyperphosphorylation of its target histone 3 are corrected in the mutant brain by pharmacologic Aurora B inhibition. Surprisingly, the reduction of Ki-67, but not H3S10ph, rescued the function of constitutive heterochromatin in APC mutant neurons. These results expand our understanding of how ubiquitin signaling regulates chromatin during neurodevelopment and identify potential therapeutic targets in APC-related disorders.

Proteome census upon nutrient stress reveals Golgiphagy membrane receptors

During nutrient stress, macroautophagy degrades cellular macromolecules, thereby providing biosynthetic building blocks while simultaneously remodelling the proteome1,2. Although the machinery responsible for initiation of macroautophagy has been well characterized3,4, our understanding of the extent to which individual proteins, protein complexes and organelles are selected for autophagic degradation, and the underlying targeting mechanisms, is limited. Here we use orthogonal proteomic strategies to provide a spatial proteome census of autophagic cargo during nutrient stress in mammalian cells. We find that macroautophagy has selectivity for recycling membrane-bound organelles (principally Golgi and endoplasmic reticulum). Through autophagic cargo prioritization, we identify a complex of membrane-embedded proteins, YIPF3 and YIPF4, as receptors for Golgiphagy. During nutrient stress, YIPF3 and YIPF4 interact with ATG8 proteins through LIR motifs and are mobilized into autophagosomes that traffic to lysosomes in a process that requires the canonical autophagic machinery. Cells lacking YIPF3 or YIPF4 are selectively defective in elimination of a specific cohort of Golgi membrane proteins during nutrient stress. Moreover, YIPF3 and YIPF4 play an analogous role in Golgi remodelling during programmed conversion of stem cells to the neuronal lineage in vitro. Collectively, the findings of this study reveal prioritization of membrane protein cargo during nutrient-stress-dependent proteome remodelling and identify a Golgi remodelling pathway that requires membrane-embedded receptors.

Direct mapping of ligandable tyrosines and lysines in cells with chiral sulfonyl fluoride probes

Advances in chemoproteomic technology have revealed covalent interactions between small molecules and protein nucleophiles, primarily cysteine, on a proteome-wide scale. Most chemoproteomic screening approaches are indirect, relying on competition between electrophilic fragments and a minimalist electrophilic probe with inherently limited proteome coverage. Here we develop a chemoproteomic platform for direct electrophile-site identification based on enantiomeric pairs of clickable arylsulfonyl fluoride probes. Using stereoselective site modification as a proxy for ligandability in intact cells, we identify 634 tyrosines and lysines within functionally diverse protein sites, liganded by structurally diverse probes. Among multiple validated sites, we discover a chiral probe that modifies Y228 in the MYC binding site of the epigenetic regulator WDR5, as revealed by a high-resolution crystal structure. A distinct chiral probe stimulates tumour cell phagocytosis by covalently modifying Y387 in the recently discovered immuno-oncology target APMAP. Our work provides a deep resource of ligandable tyrosines and lysines for the development of covalent chemical probes.

Real-Time Spectral Library Matching for Sample Multiplexed Quantitative Proteomics

Sample multiplexed quantitative proteomics assays have proved to be a highly versatile means to assay molecular phenotypes. Yet, stochastic precursor selection and precursor coisolation can dramatically reduce the efficiency of data acquisition and quantitative accuracy. To address this, intelligent data acquisition (IDA) strategies have recently been developed to improve instrument efficiency and quantitative accuracy for both discovery and targeted methods. Toward this end, we sought to develop and implement a new real-time spectral library searching (RTLS) workflow that could enable intelligent scan triggering and peak selection within milliseconds of scan acquisition. To ensure ease of use and general applicability, we built an application to read in diverse spectral libraries and file types from both empirical and predicted spectral libraries. We demonstrate that RTLS methods enable improved quantitation of multiplexed samples, particularly with consideration for quantitation from chimeric fragment spectra. We used RTLS to profile proteome responses to small molecule perturbations and were able to quantify up to 15% more significantly regulated proteins in half the gradient time compared to traditional methods. Taken together, the development of RTLS expands the IDA toolbox to improve instrument efficiency and quantitative accuracy for sample multiplexed analyses.

Mouse Model of Fragile X Syndrome Analyzed by Quantitative Proteomics: A Comparison of Methods

Multiple methods for quantitative proteomics are available for proteome profiling. It is unclear which methods are most useful in situations involving deep proteome profiling and the detection of subtle distortions in the proteome. Here, we compared the performance of seven different strategies in the analysis of a mouse model of Fragile X Syndrome, involving the knockout of the fmr1 gene that is the leading cause of autism spectrum disorder. Focusing on the cerebellum, we show that data-independent acquisition (DIA) and the tandem mass tag (TMT)-based real-time search method (RTS) generated the most informative profiles, generating 334 and 329 significantly altered proteins, respectively, although the latter still suffered from ratio compression. Label-free methods such as BoxCar and a conventional data-dependent acquisition were too noisy to generate a reliable profile, while TMT methods that do not invoke RTS showed a suppressed dynamic range. The TMT method using the TMTpro reagents together with complementary ion quantification (ProC) overcomes ratio compression, but current limitations in ion detection reduce sensitivity. Overall, both DIA and RTS uncovered known regulators of the syndrome and detected alterations in calcium signaling pathways that are consistent with calcium deregulation recently observed in imaging studies. Data are available via ProteomeXchange with the identifier PXD039885.

Identifying E3 Ligase Substrates With Quantitative Degradation Proteomics

Controlled protein degradation by the ubiquitin-proteasome pathway is critical for almost all cellular processes. E3 ubiquitin ligases are responsible for targeting proteins for ubiquitylation and subsequent proteasomal degradation with spatial and temporal precision. While studies have revealed various E3-substrate pairs involved in distinct biological processes, the complete substrate profiles of individual E3 ligases are largely unknown. Here we report a new approach to identify substrates of an E3 ligase for proteasomal degradation using unnatural amino acid incorporation pulse-chase proteomics (degradomics). Applying this approach, we determine the steady-state substrates of the C-terminal to LisH (CTLH) E3 ligase, a multi-component complex with poorly defined substrates. By comparing the proteome degradation profiles of active and inactive CTLH-expressing cells, we successfully identify previously known and new potential substrates of CTLH ligase. Altogether, degradomics can comprehensively identify degradation substrates of an E3 ligase, which can be adapted for other E3 ligases in various cellular contexts.

Reverse-ChIP Techniques for Identifying Locus-Specific Proteomes: A Key Tool in Unlocking the Cancer Regulome

A phenotypic hallmark of cancer is aberrant transcriptional regulation. Transcriptional regulation is controlled by a complicated array of molecular factors, including the presence of transcription factors, the deposition of histone post-translational modifications, and long-range DNA interactions. Determining the molecular identity and function of these various factors is necessary to understand specific aspects of cancer biology and reveal potential therapeutic targets. Regulation of the genome by specific factors is typically studied using chromatin immunoprecipitation followed by sequencing (ChIP-Seq) that identifies genome-wide binding interactions through the use of factor-specific antibodies. A long-standing goal in many laboratories has been the development of a 'reverse-ChIP' approach to identify unknown binding partners at loci of interest. A variety of strategies have been employed to enable the selective biochemical purification of sequence-defined chromatin regions, including single-copy loci, and the subsequent analytical detection of associated proteins. This review covers mass spectrometry techniques that enable quantitative proteomics before providing a survey of approaches toward the development of strategies for the purification of sequence-specific chromatin as a 'reverse-ChIP' technique. A fully realized reverse-ChIP technique holds great potential for identifying cancer-specific targets and the development of personalized therapeutic regimens.

PARK15/FBXO7 is dispensable for PINK1/Parkin mitophagy in iNeurons and HeLa cell systems

The protein kinase PINK1 and ubiquitin ligase Parkin promote removal of damaged mitochondria via a feed-forward mechanism involving ubiquitin (Ub) phosphorylation (pUb), Parkin activation, and ubiquitylation of mitochondrial outer membrane proteins to support the recruitment of mitophagy receptors. The ubiquitin ligase substrate receptor FBXO7/PARK15 is mutated in an early-onset parkinsonian-pyramidal syndrome. Previous studies have proposed a role for FBXO7 in promoting Parkin-dependent mitophagy. Here, we systematically examine the involvement of FBXO7 in depolarization and ^mt UPR-dependent mitophagy in the well-established HeLa and induced-neurons cell systems. We find that FBXO7^-/- cells have no demonstrable defect in: (i) kinetics of pUb accumulation, (ii) pUb puncta on mitochondria by super-resolution imaging, (iii) recruitment of Parkin and autophagy machinery to damaged mitochondria, (iv) mitophagic flux, and (v) mitochondrial clearance as quantified by global proteomics. Moreover, global proteomics of neurogenesis in the absence of FBXO7 reveals no obvious alterations in mitochondria or other organelles. These results argue against a general role for FBXO7 in Parkin-dependent mitophagy and point to the need for additional studies to define how FBXO7 mutations promote parkinsonian-pyramidal syndrome.

Enhanced Multiplexing Technology for Proteomics

The identification of thousands of proteins and their relative levels of expression has furthered understanding of biological processes and disease and stimulated new systems biology hypotheses. Quantitative proteomics workflows that rely on analytical assays such as mass spectrometry have facilitated high-throughput measurements of proteins partially due to multiplexing. Multiplexing allows proteome differences across multiple samples to be measured simultaneously, resulting in more accurate quantitation, increased statistical robustness, reduced analysis times, and lower experimental costs. The number of samples that can be multiplexed has evolved from as few as two to more than 50, with studies involving more than 10 samples being denoted as enhanced multiplexing or hyperplexing. In this review, we give an update on emerging multiplexing proteomics techniques and highlight advantages and limitations for enhanced multiplexing strategies.

AzidoTMT Enables Direct Enrichment and Highly Multiplexed Quantitation of Proteome-Wide Functional Residues

Recent advances in targeted covalent inhibitors have aroused significant interest for their potential in drug development for difficult therapeutic targets. Proteome-wide profiling of functional residues is an integral step of covalent drug discovery aimed at defining actionable sites and evaluating compound selectivity in cells. A classical workflow for this purpose is called IsoTOP-ABPP, which employs an activity-based probe and two isotopically labeled azide-TEV-biotin tags to mark, enrich, and quantify proteome from two samples. Here we report a novel isobaric 11plex-AzidoTMT reagent and a new workflow, named AT-MAPP, that significantly expands multiplexing power as compared to the original isoTOP-ABPP. We demonstrate its application in identifying cysteine on- and off-targets using a KRAS G12C covalent inhibitor ARS-1620. However, changes in some of these hits can be explained by modulation at the protein and post-translational levels. Thus, it would be crucial to interrogate site-level bona fide changes in concurrence to proteome-level changes for corroboration. In addition, we perform a multiplexed covalent fragment screening using four acrylamide-based compounds as a proof-of-concept. This study identifies a diverse set of liganded cysteine residues in a compound-dependent manner with an average hit rate of 0.07% in intact cell. Lastly, we screened 20 sulfonyl fluoride-based compounds to demonstrate that the AT-MAPP assay is flexible for noncysteine functional residues such as tyrosine and lysine. Overall, we envision that 11plex-AzidoTMT will be a useful addition to the current toolbox for activity-based protein profiling and covalent drug development.

A proteome-wide atlas of drug mechanism of action

Defining the cellular response to pharmacological agents is critical for understanding the mechanism of action of small molecule perturbagens. Here, we developed a 96-well-plate-based high-throughput screening infrastructure for quantitative proteomics and profiled 875 compounds in a human cancer cell line with near-comprehensive proteome coverage. Examining the 24-h proteome changes revealed ligand-induced changes in protein expression and uncovered rules by which compounds regulate their protein targets while identifying putative dihydrofolate reductase and tankyrase inhibitors. We used protein-protein and compound-compound correlation networks to uncover mechanisms of action for several compounds, including the adrenergic receptor antagonist JP1302, which we show disrupts the FACT complex and degrades histone H1. By profiling many compounds with overlapping targets covering a broad chemical space, we linked compound structure to mechanisms of action and highlighted off-target polypharmacology for molecules within the library.

Integrated proteomics identifies p62-dependent selective autophagy of the supramolecular vault complex

In addition to membranous organelles, autophagy selectively degrades biomolecular condensates, in particular p62/SQSTM1 bodies, to prevent diseases including cancer. Evidence is growing regarding the mechanisms by which autophagy degrades p62 bodies, but little is known about their constituents. Here, we established a fluorescence-activated-particle-sorting-based purification method for p62 bodies using human cell lines and determined their constituents by mass spectrometry. Combined with mass spectrometry of selective-autophagy-defective mouse tissues, we identified vault, a large supramolecular complex, as a cargo within p62 bodies. Mechanistically, major vault protein directly interacts with NBR1, a p62-interacting protein, to recruit vault into p62 bodies for efficient degradation. This process, named vault-phagy, regulates homeostatic vault levels in vivo, and its impairment may be associated with non-alcoholic-steatohepatitis-derived hepatocellular carcinoma. Our study provides an approach to identifying phase-separation-mediated selective autophagy cargoes, expanding our understanding of the role of phase separation in proteostasis.

Hyperplexing Approaches for up to 45-Plex Quantitative Proteomic Analysis

Isobaric labeling has emerged as an indispensable quantitative proteomic approach for its unprecedented multiplexing capacity in a single analysis. Currently, different hyperplexing approaches have been developed to meet the demand for the increasing sample size in large-scale cohort analysis. In this report, we present a tribrid hyperplexing approach by the combinatorial use of three types of isobaric reagents, a novel isobaric tag 16-plex (IBT16) reagent and the widely used tandem mass tag (TMT; TMT11) and TMTpro (TMT18) reagents. After the determination of labeling efficiency and the optimization of testing conditions, we systematically evaluated the identification and quantification performance of the three labeling reagents in both independent and combinatorial manners using the mixtures of E. coli and HeLa peptides with different ratios. Our results reveal that the three reagents are quite similar in all testing aspects despite some differences, and the combination use of the three reagents could expand the multiplexing capacity to up to 45-plex. Furthermore, we conclude the advantages of IBT16 in the combination use and the preferred combinations for different practical applications. Data are available via ProteomeXchange with identifier PXD037498.

Sample multiplexing-based targeted pathway proteomics with real-time analytics reveals the impact of genetic variation on protein expression

Targeted proteomics enables hypothesis-driven research by measuring the cellular expression of protein cohorts related by function, disease, or class after perturbation. Here, we present a pathway-centric approach and an assay builder resource for targeting entire pathways of up to 200 proteins selected from >10,000 expressed proteins to directly measure their abundances, exploiting sample multiplexing to increase throughput by 16-fold. The strategy, termed GoDig, requires only a single-shot LC-MS analysis, ~1 µg combined peptide material, a list of up to 200 proteins, and real-time analytics to trigger simultaneous quantification of up to 16 samples for hundreds of analytes. We apply GoDig to quantify the impact of genetic variation on protein expression in mice fed a high-fat diet. We create several GoDig assays to quantify the expression of multiple protein families (kinases, lipid metabolism- and lipid droplet-associated proteins) across 480 fully-genotyped Diversity Outbred mice, revealing protein quantitative trait loci and establishing potential linkages between specific proteins and lipid homeostasis.

Mass Spectrometry-Based Proteomics Workflows in Cancer Research: The Relevance of Choosing the Right Steps

The qualitative and quantitative evaluation of proteome changes that condition cancer development can be achieved with liquid chromatography-mass spectrometry (LC-MS). LC-MS-based proteomics strategies are carried out according to predesigned workflows that comprise several steps such as sample selection, sample processing including labeling, MS acquisition methods, statistical treatment, and bioinformatics to understand the biological meaning of the findings and set predictive classifiers. As the choice of best options might not be straightforward, we herein review and assess past and current proteomics approaches for the discovery of new cancer biomarkers. Moreover, we review major bioinformatics tools for interpreting and visualizing proteomics results and suggest the most popular machine learning techniques for the selection of predictive biomarkers. Finally, we consider the approximation of proteomics strategies for clinical diagnosis and prognosis by discussing current barriers and proposals to circumvent them.

Evaluating Linear Ion Trap for MS3-Based Multiplexed Single-Cell Proteomics

There is a growing demand to develop high-throughput and high-sensitivity mass spectrometry methods for single-cell proteomics. The commonly used isobaric labeling-based multiplexed single-cell proteomics approach suffers from distorted protein quantification due to co-isolated interfering ions during MS/MS fragmentation, also known as ratio compression. We reasoned that the use of MS3-based quantification could mitigate ratio compression and provide better quantification. However, previous studies indicated reduced proteome coverages in the MS3 method, likely due to long duty cycle time and ion losses during multilevel ion selection and fragmentation. Herein, we described an improved MS acquisition method for MS3-based single-cell proteomics by employing a linear ion trap to measure reporter ions. We demonstrated that linear ion trap can increase the proteome coverages for single-cell-level peptides with even higher gain obtained via the MS3 method. The optimized real-time search MS3 method was further applied to study the immune activation of single macrophages. Among a total of 126 single cells studied, over 1200 and 1000 proteins were quantifiable when at least 50 and 75% nonmissing data were required, respectively. Our evaluation also revealed several limitations of the low-resolution ion trap detector for multiplexed single-cell proteomics and suggested experimental solutions to minimize their impacts on single-cell analysis.

Neutrophil profiles of pediatric COVID-19 and multisystem inflammatory syndrome in children

Multisystem inflammatory syndrome in children (MIS-C) is a delayed-onset, COVID-19-related hyperinflammatory illness characterized by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigenemia, cytokine storm, and immune dysregulation. In severe COVID-19, neutrophil activation is central to hyperinflammatory complications, yet the role of neutrophils in MIS-C is undefined. Here, we collect blood from 152 children: 31 cases of MIS-C, 43 cases of acute pediatric COVID-19, and 78 pediatric controls. We find that MIS-C neutrophils display a granulocytic myeloid-derived suppressor cell (G-MDSC) signature with highly altered metabolism that is distinct from the neutrophil interferon-stimulated gene (ISG) response we observe in pediatric COVID-19. Moreover, we observe extensive spontaneous neutrophil extracellular trap (NET) formation in MIS-C, and we identify neutrophil activation and degranulation signatures. Mechanistically, we determine that SARS-CoV-2 immune complexes are sufficient to trigger NETosis. Our findings suggest that hyperinflammatory presentation during MIS-C could be mechanistically linked to persistent SARS-CoV-2 antigenemia, driven by uncontrolled neutrophil activation and NET release in the vasculature.

Isobaric labeling: Expanding the breadth, accuracy, depth, and diversity of sample multiplexing

Isobaric labeling has rapidly become a predominant strategy for proteome-wide abundance measurements. Coupled to mass spectrometry, sample multiplexing techniques using isobaric labeling are unparalleled for profiling proteins and posttranslational modifications across multiple samples in a single experiment. Here, I highlight aspects of isobaric labeling in the context of expanding the breadth of multiplexing, improving quantitative accuracy and proteome depth, and developing a wide range of diverse applications. I underscore two facets that enhance quantitative accuracy and reproducibility, specifically the availability of quality control standards for isobaric labeling experiments and the evolution of data acquisition methods. I also emphasize the necessity for standardized methodologies, particularly for emerging high-throughput workflows. Future developments in sample multiplexing will further strengthen the importance of isobaric labeling for comprehensive proteome profiling.

Nanoscale Mapping of EGFR and c-MET Protein Environments on Lung Cancer Cell Surfaces via Therapeutic Antibody Photocatalyst Conjugates

Receptor tyrosine kinases are involved in essential signaling roles that impact cell growth, differentiation, and proliferation. The overexpression or mutation of these proteins can lead to aberrant signaling that has been directly linked to a number of diseases including cancer cell formation and progression. This has led to intense clinical focus on modulating RTK activity through direct targeting of signaling activity or cell types harboring aberrant RTK behavior. In particular, epidermal growth factor receptor (EGFR) has attracted intense clinical attention due to the impact of inhibiting this RTK on tumor growth. However, mutations incurred through targeting EGFR have led to therapeutic resistance that involves not only direct mutations to the EGFR protein but also the involvement of other RTKs, such as c-MET, that can overcome therapeutic-based EGFR inhibition effects. This has, not surprisingly, led to co-targeting strategies of RTKs such as EGFR and c-MET to overcome resistance mechanisms. While the ability to co-target these proteins has led to success in the clinic, a more comprehensive understanding of their proximal environments, particularly in the context of therapeutic modalities, could further enhance both our understanding of their signaling biology and provide additional avenues for targeting these surface proteins. Thus, to investigate EGFR and c-MET protein microenvironments, we utilized our recently developed iridium photocatalyst-based microenvironment mapping technology to catalog EGFR and c-MET surface environments on non-small cell lung cancer cell lines. Through this approach, we enriched EGFR and c-MET from the cell surface and identified known EGFR and c-MET associators as well as previously unidentified proximal proteins.

Comparative Assessment of Quantification Methods for Tumor Tissue Phosphoproteomics

With increasing sensitivity and accuracy in mass spectrometry, the tumor phosphoproteome is getting into reach. However, the selection of quantitation techniques best-suited to the biomedical question and diagnostic requirements remains a trial and error decision as no study has directly compared their performance for tumor tissue phosphoproteomics. We compared label-free quantification (LFQ), spike-in-SILAC (stable isotope labeling by amino acids in cell culture), and tandem mass tag (TMT) isobaric tandem mass tags technology for quantitative phosphosite profiling in tumor tissue. Compared to the classic SILAC method, spike-in-SILAC is not limited to cell culture analysis, making it suitable for quantitative analysis of tumor tissue samples. TMT offered the lowest accuracy and the highest precision and robustness toward different phosphosite abundances and matrices. Spike-in-SILAC offered the best compromise between these features but suffered from a low phosphosite coverage. LFQ offered the lowest precision but the highest number of identifications. Both spike-in-SILAC and LFQ presented susceptibility to matrix effects. Match between run (MBR)-based analysis enhanced the phosphosite coverage across technical replicates in LFQ and spike-in-SILAC but further reduced the precision and robustness of quantification. The choice of quantitative methodology is critical for both study design such as sample size in sample groups and quantified phosphosites and comparison of published cancer phosphoproteomes. Using ovarian cancer tissue as an example, our study builds a resource for the design and analysis of quantitative phosphoproteomic studies in cancer research and diagnostics.

Quantitative proteome remodeling characterization of two human reference pluripotent stem cell lines during neurogenesis and cardiomyogenesis

Human pluripotent stem cells (PSCs) have become popular tools within the research community to study developmental and model diseases. While many induced-PSCs (iPSCs) from various genetic background sources are currently available, scientific advancement has been hampered by the considerable phenotypic variations observed between different iPSC lines. A recent collaborative effort selected a novel iPSC line to address this and encourage the adoption of a standardized iPSC line termed KOLF2.1J. Here, leveraging the multiplexing power of isobaric labeling, we systematically investigate, at the 10k proteome level, the relative protein abundance profiles of the KOLF2.1J reference iPSC line upon two distinct cell state differentiation trajectories. In addition, we side-by-side systematically compare this line with the H9 line, an established embryonically derived PSC line that we previously characterized. We noticed differences in the basal proteome of the two cell lines and highlighted the differentially expressed proteins. While the difference between the cell line's proteome subsisted upon differentiation, the global proteome remodeling trajectory was highly similar during the tested differentiation routes. We thus conclude that the KOLF2.1J line performs well at the proteome level upon the neuro and cardiomyogenesis differentiation protocol used. We believe this dataset will serve as a resource of value for the research community.

Recent advances in proteomics and metabolomics in plants

Over the past decade, systems biology and plant-omics have increasingly become the main stream in plant biology research. New developments in mass spectrometry and bioinformatics tools, and methodological schema to integrate multi-omics data have leveraged recent advances in proteomics and metabolomics. These progresses are driving a rapid evolution in the field of plant research, greatly facilitating our understanding of the mechanistic aspects of plant metabolisms and the interactions of plants with their external environment. Here, we review the recent progresses in MS-based proteomics and metabolomics tools and workflows with a special focus on their applications to plant biology research using several case studies related to mechanistic understanding of stress response, gene/protein function characterization, metabolic and signaling pathways exploration, and natural product discovery. We also present a projection concerning future perspectives in MS-based proteomics and metabolomics development including their applications to and challenges for system biology. This review is intended to provide readers with an overview of how advanced MS technology, and integrated application of proteomics and metabolomics can be used to advance plant system biology research.

29-Plex tandem mass tag mass spectrometry enabling accurate quantification by interference correction

Tandem mass tag (TMT) mass spectrometry is a mainstream isobaric chemical labeling strategy for profiling proteomes. Here we present a 29-plex TMT method to combine the 11-plex and 18-plex labeling strategies. The 29-plex method was examined with a pooled sample composed of 1×, 3×, and 10× Escherichia coli peptides with 100× human background peptides, which generated two E. coli datasets (TMT11 and TMT18), displaying the distorted ratios of 1.0:1.7:4.2 and 1.0:1.8:4.9, respectively. This ratio compression from the expected 1:3:10 ratios was caused by co-isolated TMT-labeled ions (i.e., noise). Interestingly, the mixture of two TMT sets produced MS/MS spectra with unique features for the noise detection: (i) in TMT11-labeled spectra, TMT18-specific reporter ions (e.g., 135N) were shown as the noise; (ii) in TMT18-labeled spectra, the TMT11/TMT18-shared reporter ions (e.g., 131C) typically exhibited higher intensities than TMT18-specific reporter ions, due to contaminated TMT11-labeled ions in these shared channels. We further estimated the noise levels contributed by both TMT11- and TMT18-labeled peptides, and corrected reporter ion intensities in every spectrum. Finally, the anticipated 1:3:10 ratios were largely restored. This strategy was also validated using another 29-plex sample with 1:5 ratios. Thus the 29-plex method expands the TMT throughput and enhances the quantitative accuracy.

Profiling Yeast Deletion Strains Using Sample Multiplexing and Network-Based Analyses

The yeast, Saccharomyces cerevisiae, is a widely used model system for investigating conserved biological functions and pathways. Advancements in sample multiplexing have facilitated the study of the yeast proteome, yet many yeast proteins remain uncharacterized or only partially characterized. Yeast deletion strain collections are powerful resources for yeast proteome studies, uncovering the effects of gene function, genetic interactions, and cellular stresses. As complex biological systems cannot be understood by simply analyzing the individual components, a systems approach is often required in which a protein is represented as a component of large, interacting networks. Here, we evaluate the current state of yeast proteome analysis using isobaric tag-based sample multiplexing (TMTpro16) to profile the proteomes of 75 yeast deletion strains for which we measured the abundance of nearly 5000 proteins. Using statistical approaches, we highlighted covariance and regulation subnetworks and the enrichment of gene ontology classifications for covarying and coregulated proteins. This dataset presents a resource that is amenable to further data mining to study individual deletion strains, pathways, proteins, and/or interactions thereof while serving as a template for future network-based investigations using yeast deletion strain collections.

Cancer proteogenomics: current impact and future prospects

Genomic analyses in cancer have been enormously impactful, leading to the identification of driver mutations and development of targeted therapies. But the functions of the vast majority of somatic mutations and copy number variants in tumours remain unknown, and the causes of resistance to targeted therapies and methods to overcome them are poorly defined. Recent improvements in mass spectrometry-based proteomics now enable direct examination of the consequences of genomic aberrations, providing deep and quantitative characterization of tumour tissues. Integration of proteins and their post-translational modifications with genomic, epigenomic and transcriptomic data constitutes the new field of proteogenomics, and is already leading to new biological and diagnostic knowledge with the potential to improve our understanding of malignant transformation and therapeutic outcomes. In this Review we describe recent developments in proteogenomics and key findings from the proteogenomic analysis of a wide range of cancers. Considerations relevant to the selection and use of samples for proteogenomics and the current technologies used to generate, analyse and integrate proteomic with genomic data are described. Applications of proteogenomics in translational studies and immuno-oncology are rapidly emerging, and the prospect for their full integration into therapeutic trials and clinical care seems bright.

The nuclear lamina binds the EBV genome during latency and regulates viral gene expression

The Epstein Barr virus (EBV) infects almost 95% of the population worldwide. While typically asymptomatic, EBV latent infection is associated with several malignancies of epithelial and lymphoid origin in immunocompromised individuals. In latently infected cells, the EBV genome persists as a chromatinized episome that expresses a limited set of viral genes in different patterns, referred to as latency types, which coincide with varying stages of infection and various malignancies. We have previously demonstrated that latency types correlate with differences in the composition and structure of the EBV episome. Several cellular factors, including the nuclear lamina, regulate chromatin composition and architecture. While the interaction of the viral genome with the nuclear lamina has been studied in the context of EBV lytic reactivation, the role of the nuclear lamina in controlling EBV latency has not been investigated. Here, we report that the nuclear lamina is an essential epigenetic regulator of the EBV episome. We observed that in B cells, EBV infection affects the composition of the nuclear lamina by inducing the expression of lamin A/C, but only in EBV+ cells expressing the Type III latency program. Using ChIP-Seq, we determined that lamin B1 and lamin A/C bind the EBV genome, and their binding correlates with deposition of the histone repressive mark H3K9me2. By RNA-Seq, we observed that knock-out of lamin A/C in B cells alters EBV gene expression. Our data indicate that the interaction between lamins and the EBV episome contributes to the epigenetic control of viral gene expression during latency, suggesting a restrictive function of the nuclear lamina as part of the host response against viral DNA entry into the nucleus.

Epstein-Barr virus (EBV) is a common herpesvirus that establishes a lifelong latent infection in a small fraction of B cells of the infected individuals. In most cases, EBV infection is asymptomatic; however, especially in the context of immune suppression, EBV latent infection is associated with several malignancies. In EBV+ cancer cells, latent viral gene expression plays an essential role in sustaining the cancer phenotype. We and others have established that epigenetic modifications of the viral genome are critical to regulating EBV gene expression during latency. Understanding how the EBV genome is epigenetically regulated during latent infection may help identify new specific therapeutic targets for treating EBV+ malignancies. The nuclear lamina is involved in regulating the composition and structure of the cellular chromatin. In the present study, we determined that the nuclear lamina binds the EBV genome during latency, influencing viral gene expression. Depleting one component of the nuclear lamina, lamin A/C, increased the expression of latent EBV genes associated with cellular proliferation, indicating that the binding of the nuclear lamina with the viral genome is essential to control viral gene expression in infected cells. Our data show for the first time that the nuclear lamina may be involved in the cellular response against EBV infection by restricting viral gene expression.

Modern Data Acquisition Approaches in Proteomics Based on Dynamic Instrument Control

Traditionally, data acquisition in mass spectrometry-based proteomics is directed by user-defined parameters and relatively simple decision making, such as selection of the highest MS1 peaks for fragmentation. In recent years, access to two-way-communication with instrument codebases has led to a surge in algorithms instructing more complex decision processes on-the-fly. A closer matching between the time windows for monitoring peptides in targeted proteomics and their actual chromatographic elution peaks has been addressed through dynamic retention time scheduling and through triggered acquisition. Strategies based on real-time database searching and spectral matching have, among others, been used to adjust acquisition parameters for selected peptides for improved quantitative accuracy. While initial studies were mainly performed on a proof-of-concept level, dynamic acquisition approaches recently became more broadly available through software and increasing integration into standard instrument control and are likely to transform the field of proteomics in the coming years.

Brain-derived autophagosome profiling reveals the engulfment of nucleoid-enriched mitochondrial fragments by basal autophagy in neurons

Neurons depend on autophagy to maintain cellular homeostasis, and defects in autophagy are pathological hallmarks of neurodegenerative disease. To probe the role of basal autophagy in the maintenance of neuronal health, we isolated autophagic vesicles from mouse brain tissue and used proteomics to identify the major cargos engulfed within autophagosomes, validating our findings in rodent primary and human iPSC-derived neurons. Mitochondrial proteins were identified as a major cargo in the absence of mitophagy adaptors such as OPTN. We found that nucleoid-associated proteins are enriched compared with other mitochondrial components. In the axon, autophagic engulfment of nucleoid-enriched mitochondrial fragments requires the mitochondrial fission machinery Drp1. We proposed that localized Drp1-dependent fission of nucleoid-enriched fragments in proximity to the sites of autophagosome biogenesis enhances their capture. The resulting efficient autophagic turnover of nucleoids may prevent accumulation of mitochondrial DNA in the neuron, thus mitigating activation of proinflammatory pathways that contribute to neurodegeneration.

Optimized TMT-Based Quantitative Cross-Linking Mass Spectrometry Strategy for Large-Scale Interactomic Studies

Cross-linking mass spectrometry (XL-MS) is a powerful method for the investigation of protein-protein interactions (PPI) from highly complex samples. XL-MS combined with tandem mass tag (TMT) labeling holds the promise of large-scale PPI quantification. However, a robust and efficient TMT-based XL-MS quantification method has not yet been established due to the lack of a benchmarking dataset and thorough evaluation of various MS parameters. To tackle these limitations, we generate a two-interactome dataset by spiking in TMT-labeled cross-linked Escherichia coli lysate into TMT-labeled cross-linked HEK293T lysate using a defined mixing scheme. Using this benchmarking dataset, we assess the efficacy of cross-link identification and accuracy of cross-link quantification using different MS acquisition strategies. For identification, we compare various MS2- and MS3-based XL-MS methods, and optimize stepped higher energy collisional dissociation (HCD) energies for TMT-labeled cross-links. We observed a need for notably higher fragmentation energies compared to unlabeled cross-links. For quantification, we assess the quantification accuracy and dispersion of MS2-, MS3-, and synchronous precursor selection-MS3-based methods. We show that a stepped HCD-MS2 method with stepped collision energies 36-42-48 provides a vast number of quantifiable cross-links with high quantification accuracy. This widely applicable method paves the way for multiplexed quantitative PPI characterization from complex biological systems.

Real-Time Search-Assisted Acquisition on a Tribrid Mass Spectrometer Improves Coverage in Multiplexed Single-Cell Proteomics

In the young field of single-cell proteomics (scMS), there is a great need for improved global proteome characterization, both in terms of proteins quantified per cell and quantitative performance thereof. The recently introduced real-time search (RTS) on the Orbitrap Eclipse Tribrid mass spectrometer in combination with SPS-MS3 acquisition has been shown to be beneficial for the measurement of samples that are multiplexed using isobaric tags. Multiplexed scMS requires high ion injection times and high-resolution spectra to quantify the single-cell signal; however, the carrier channel facilitates peptide identification and thus offers the opportunity for fast on-the-fly precursor filtering before committing to the time-intensive quantification scan. Here, we compared classical MS2 acquisition against RTS-SPS-MS3, both using the Orbitrap Eclipse Tribrid MS with the FAIMS Pro ion mobility interface and present a new acquisition strategy termed RETICLE (RTS enhanced quant of single cell spectra) that makes use of fast real-time searched linear ion trap scans to preselect MS1 peptide precursors for quantitative MS2 Orbitrap acquisition. We show that classical MS2 acquisition is outperformed by both RTS-SPS-MS3 through increased quantitative accuracy at similar proteome coverage, and RETICLE through higher proteome coverage, with the latter enabling the quantification of over 1000 proteins per cell at an MS2 injection time of 750 ms using a 2 h gradient.

Novel Real-Time Library Search Driven Data Acquisition Strategy for Identification and Characterization of Metabolites

Structural characterization of novel metabolites in drug discovery or metabolomics is one of the most challenging tasks. Multilevel fragmentation (MSⁿ) based approaches combined with various dissociation modes are frequently utilized for facilitating structure assignment of unknown compounds. As each of the MS precursors undergoes MSⁿ, the instrument cycle time can limit the total number of precursors analyzed in a single LC run for complex samples. This necessitates splitting data acquisition into several analyses to target lower concentration analytes in successive experiments. Here we present a new LC/MS data acquisition strategy, termed Met-IQ, where the decision to perform an MSⁿ acquisition is automatically made in real time based on the similarity between the experimental MS² spectrum and a spectrum in a reference spectral library for the known compounds of interest. If similarity to a spectrum in the library is found, the instrument performs a decision-dependent event, such as an MS³ spectrum. Compared to an intensity-based, data-dependent MSⁿ experiment, only a limited number of MS³ are triggered using Met-IQ, increasing the overall MS² instrument sampling rate. We applied this strategy to an Amprenavir sample incubated with human liver microsomes. The number of MS² spectra increased 2-fold compared to a data dependent experiment where MS³ was triggered for each precursor, resulting in identification of 14-34% more unique potential metabolites. Furthermore, the MS² fragments were selected to focus likely sources of useful structural information, specifically higher mass fragments to maximize acquisition of MS³ data relevant for structure assignment. The described Met-IQ strategy is not limited to metabolism experiments and can be applied to analytical samples where the detection of unknown compounds structurally related to a known compound(s) is sought.

Motif-centric phosphoproteomics to target kinase-mediated signaling pathways

Identifying cellular phosphorylation pathways based on kinase-substrate relationships is a critical step to understanding the regulation of physiological functions in cells. Mass spectrometry-based phosphoproteomics workflows have made it possible to comprehensively collect information on individual phosphorylation sites in a variety of samples. However, there is still no generic approach to uncover phosphorylation networks based on kinase-substrate relationships in rare cell populations. Here, we describe a motif-centric phosphoproteomics approach combined with multiplexed isobaric labeling, in which in vitro kinase reactions are used to generate targeted phosphopeptides, which are spiked into one of the isobaric channels to increase detectability. Proof-of-concept experiments demonstrate selective and comprehensive quantification of targeted phosphopeptides by using multiple kinases for motif-centric channels. More than 7,000 tyrosine phosphorylation sites were quantified from several tens of micrograms of starting materials. This approach enables the quantification of multiple phosphorylation pathways under physiological or pathological regulation in a motif-centric manner.

Proximity labeling for investigating protein-protein interactions

The study of protein complexes and protein-protein interactions is of great importance due to their fundamental roles in cellular function. Proximity labeling, often coupled with mass spectrometry, has become a powerful and versatile tool for studying protein-protein interactions by enriching and identifying proteins in the vicinity of a specified protein-of-interest. Here, we describe and compare traditional approaches to investigate protein-protein interactions to current day state-of-the-art proximity labeling methods. We focus on the wide array of proximity labeling strategies and underscore studies using diverse model systems to address numerous biological questions. In addition, we highlight current advances in mass spectrometry-based technology that exhibit promise in improving the depth and breadth of the data acquired in proximity labeling experiments. In all, we show the diversity of proximity labeling strategies and emphasize the broad range of applications and biological inquiries that can be addressed using this technology.

APC7 mediates ubiquitin signaling in constitutive heterochromatin in the developing mammalian brain

Neurodevelopmental cognitive disorders provide insights into mechanisms of human brain development. Here, we report an intellectual disability syndrome caused by the loss of APC7, a core component of the E3 ubiquitin ligase anaphase promoting complex (APC). In mechanistic studies, we uncover a critical role for APC7 during the recruitment and ubiquitination of APC substrates. In proteomics analyses of the brain from mice harboring the patient-specific APC7 mutation, we identify the chromatin-associated protein Ki-67 as an APC7-dependent substrate of the APC in neurons. Conditional knockout of the APC coactivator protein Cdh1, but not Cdc20, leads to the accumulation of Ki-67 protein in neurons in vivo, suggesting that APC7 is required for the function of Cdh1-APC in the brain. Deregulated neuronal Ki-67 upon APC7 loss localizes predominantly to constitutive heterochromatin. Our findings define an essential function for APC7 and Cdh1-APC in neuronal heterochromatin regulation, with implications for understanding human brain development and disease.

Multiomic analysis identifies CPT1A as a potential therapeutic target in platinum-refractory, high-grade serous ovarian cancer

Resistance to platinum compounds is a major determinant of patient survival in high-grade serous ovarian cancer (HGSOC). To understand mechanisms of platinum resistance and identify potential therapeutic targets in resistant HGSOC, we generated a data resource composed of dynamic (±carboplatin) protein, post-translational modification, and RNA sequencing (RNA-seq) profiles from intra-patient cell line pairs derived from 3 HGSOC patients before and after acquiring platinum resistance. These profiles reveal extensive responses to carboplatin that differ between sensitive and resistant cells. Higher fatty acid oxidation (FAO) pathway expression is associated with platinum resistance, and both pharmacologic inhibition and CRISPR knockout of carnitine palmitoyltransferase 1A (CPT1A), which represents a rate limiting step of FAO, sensitize HGSOC cells to platinum. The results are further validated in patient-derived xenograft models, indicating that CPT1A is a candidate therapeutic target to overcome platinum resistance. All multiomic data can be queried via an intuitive gene-query user interface (https://sites.google.com/view/ptrc-cell-line).