How many human proteoforms are there?

De Novo-Designed APC/C Inhibitors Provide a Rationale for Targeting RING-Type E3 Ubiquitin Ligases

The ubiquitin system represents an attractive pharmacological target for numerous pathological processes, including cancer and neurodegeneration. RING domain-containing E3 ubiquitin ligases constitute the largest class of ubiquitin enzymes, providing a scaffold for substrate recognition and catalysis. Their shallow groove recognition interfaces involving discontinuous epitopes and a lack of defined binding pockets have largely rendered them undruggable. Inspired by natural RING inhibitors, we have developed a pharmacophore-based strategy for the rational design of peptidomimetics targeting RING domains, and we demonstrate its feasibility by using the macromolecular APC/C complex (anaphase-promoting complex/cyclosome). We designed scaffolds binding to the APC/C RING domain and efficiently inhibiting its activity in vitro. Iterative structure-based design and experimental studies to optimize their chemical stability, permeability, and specificity lead to new hydrocarbon-stapled-based molecules inhibiting APC/C in vitro and in cancer cells. Our results provide a robust rationale for targeting RING-containing enzymes of therapeutic value and promising leads for clinical APC/C inhibition.

Fucosylation of hemocyanin is critical for antibacterial immunity in Penaeus vannamei

Posttranslational modifications (PTMs) play a pivotal role in expanding the function of immune related proteins, especially during pathogen infections. However, the precise impact of PTMs on the functional diversity of proteins such as respiratory glycoproteins and hemocyanins remains incompletely understood. In this study, we investigated the fucosylation modification of Penaeus vannamei hemocyanin (PvHMC) and its impact on antibacterial immunity. Our findings reveal that PvHMC underwent fucosylation, mediated by Penaeus vannamei fucosyltransferase 8/10 (PvFUT8/10), which enhances its antibacterial immunity and binding ability against Gram-negative bacteria. Conversely, defucosylation of PvHMC, catalyzed by Penaeus vannamei fucosidase (PvAFU) weakens its antibacterial activity in vitro. These results highlight the regulatory role of fucosylation in modulating the antibacterial function of PvHMC in shrimp.

Capillary Electrophoresis-Mass Spectrometry for Top-Down Proteomics

Mass spectrometry (MS)-based top-down proteomics (TDP) characterizes proteoforms in cells, tissues, and biological fluids (e.g., human plasma) to better our understanding of protein function and to discover new protein biomarkers for disease diagnosis and therapeutic development. Separations of proteoforms with high peak capacity are needed due to the high complexity of biological samples. Capillary electrophoresis (CE)-MS has been recognized as a powerful analytical tool for protein analysis since the 1980s owing to its high separation efficiency and sensitivity of CE-MS for proteoforms. Here, we review benefits of CE-MS for advancing TDP, challenges and solutions of the method, and the main research areas in which CE-MS-based TDP can make significant contributions. We provide a brief perspective of CE-MS-based TDP moving forward.

StageTip: a little giant unveiling the potential of mass spectrometry-based proteomics

This review highlights the growing impact of StageTips (Stop and Go Extraction Tips), a pipette tip-based LC column in MS-based proteomics. By packing standard pipette tips with reversed-phase, ion-exchange, or metal oxide materials, StageTips enable efficient peptide desalting, fractionation, selective enrichment, and in-tip reactions with minimal sample loss. Recent improvements, including new resin designs and integrated workflows, have further expanded the applications to phosphoproteomics, protein terminomics, and single-cell proteomics. With their simplicity, high reproducibility, and low cost, StageTips offer a versatile platform that can be seamlessly integrated into automated pipelines, increasing the throughput and the depth of proteome analysis. As materials and protocols continue to evolve, StageTips will continue to develop as an essential keystone for robust sample preparation in next-generation proteomics research.

Top-Down Proteomics: Why and When?

Manifold biological processes at all levels of transcription and translation can lead to the formation of a high number of different protein species (i.e., proteoforms), which outnumber the sequences encoded in the genome by far. Due to the large number of protein molecules formed in this way, which span an enormous range of different physicochemical properties, proteoforms are the functional drivers of all biological processes, creating the need for powerful analytical approaches to decipher this language of life. While bottom-up proteomics has become the most widely used approach, providing features such as high sensitivity, depth of analysis, and throughput, it has its limitations when it comes to identifying, quantifying, and characterizing proteoforms. In particular, the major bottleneck is to assign peptide-level information to the original proteoforms. In contrast, top-down proteomics (TDP) targets the direct analysis of intact proteoforms. Despite being characterized by a number of technological challenges, the TDP community has established numerous protocols that allow easy implementation in any proteomics laboratory. In this viewpoint, we compare both approaches, argue that it is worth embedding TDP experiments, and show fields of research in which TDP can be successfully implemented to perform integrative multi-level proteoformics.

Engineered Proteins and Chemical Tools to Probe the Cell Surface Proteome

The cell surface proteome, or surfaceome, is the hub for cells to interact and communicate with the outside world. Many disease-associated changes are hard-wired within the surfaceome, yet approved drugs target less than 50 cell surface proteins. In the past decade, the proteomics community has made significant strides in developing new technologies tailored for studying the surfaceome in all its complexity. In this review, we first dive into the unique characteristics and functions of the surfaceome, emphasizing the necessity for specialized labeling, enrichment, and proteomic approaches. An overview of surfaceomics methods is provided, detailing techniques to measure changes in protein expression and how this leads to novel target discovery. Next, we highlight advances in proximity labeling proteomics (PLP), showcasing how various enzymatic and photoaffinity proximity labeling techniques can map protein-protein interactions and membrane protein complexes on the cell surface. We then review the role of extracellular post-translational modifications, focusing on cell surface glycosylation, proteolytic remodeling, and the secretome. Finally, we discuss methods for identifying tumor-specific peptide MHC complexes and how they have shaped therapeutic development. This emerging field of neo-protein epitopes is constantly evolving, where targets are identified at the proteome level and encompass defined disease-associated PTMs, complexes, and dysregulated cellular and tissue locations. Given the functional importance of the surfaceome for biology and therapy, we view surfaceomics as a critical piece of this quest for neo-epitope target discovery.

Aggregation of α-synuclein splice isoforms through a phase separation pathway

The aggregation of α-synuclein (αSyn) is associated with Parkinson's disease and other related synucleinopathies. Considerable efforts have thus been directed at understanding this process. However, the recently discovered condensation pathway, which involves the formation of phase-separated liquid intermediate states, has added further complexity. In parallel, it has been reported that different αSyn splice isoforms may be implicated in aggregate formation in disease. In this study, we compare the phase behavior of four αSyn isoforms (αSyn-140, αSyn-126, αSyn-112, and αSyn-98). Using different biophysical tools including confocal microscopy, kinetic assays and microfluidic-based approaches, we find stark differences between the four systems in their propensities to undergo phase separation and aggregation. Furthermore, we show that even small amounts of αSyn-112, one of the predominant isoforms after αSyn-140, can affect the phase separation of αSyn-140. These results highlight the importance of conducting further investigations to elucidate the role of alternative splicing in synucleinopathies.

The role of glycan-lectin interactions in the tumor microenvironment: immunosuppression regulators of colorectal cancer

Colorectal cancer (CRC) is a common malignant tumour and a serious global health issue. Glycosylation, a type of posttranslational modification, has been extensively studied in relation to cancer growth and metastasis. Aberrant glycosylation alters how the immune system in the microenvironment perceives the tumour and drives immune suppression through glycan-binding receptors. Interestingly, specific glycan signatures can be regarded as a new pattern of immune checkpoints. Lectins are a group of proteins that exhibit high affinity for glycosylation structures. Lectins and their ligands are found on endothelial cells (ECs), immune cells and tumour cells and play important roles in the tumour microenvironment (TME). In CRC, glycan-lectin interactions can accelerate immune evasion promoting the differentiation of tumour-associated M2 macrophages, altering T cell, dendritic cell (DC), natural killer (NK) cell, and regulatory T (Treg) cell activity to modify the functions of antigen-presenting cells functions. Here, we review our current knowledge on how glycan-lectin interactions affect immune-suppressive circuits in the TME and discuss their roles in the development of more effective immunotherapies for CRC.

Advances in the chemical synthesis of human proteoforms

Access to structurally-defined human proteoforms is essential to the biochemical studies on human health and medicine. Chemical protein synthesis provides a bottom-up and atomic-resolution approach for the preparation of homogeneous proteoforms bearing any number of post-translational modifications of any structure, at any position, and in any combination. In this review, we summarize the development of chemical protein synthesis, focusing on the recent advances in synthetic methods, product characterizations, and biomedical applications. By analyzing the chemical protein synthesis studies on human proteoforms reported to date, this review demonstrates the significant methodological improvements that have taken place in the field of human proteoform synthesis, especially in the last decade. Our analysis shows that although further method development is needed, all the human proteoforms could be within reach in a cost-effective manner through a divide-and-conquer chemical protein synthesis strategy. The synthetic proteoforms have been increasingly used to support biomedical research, including spatial-temporal studies and interaction network analysis, activity quantification and mechanism elucidation, and the development and evaluation of diagnostics and therapeutics.

Proteoform-predictor: Increasing the Phylogenetic Reach of Top-Down Proteomics

Proteoforms are distinct molecular forms of proteins that act as building blocks of organisms, with post-translational modifications (PTMs) being one of the key changes that generate these variations. Mass spectrometry (MS)-based top-down proteomics (TDP) is the leading technology for proteoform identification due to its preservation of intact proteoforms for analysis, making it well-suited for comprehensive PTM characterization. A crucial step in TDP is searching MS data against a database of candidate proteoforms. To extend the reach of TDP to organisms with limited PTM annotations, we developed Proteoform-predictor, an open-source tool that integrates homology-based PTM site prediction into proteoform database creation. The new tool creates databases of proteoform candidates after registration of homologous sequences, transferring PTM sites from well-characterized species to those with less comprehensive proteomic data. Our tool features a user-friendly interface and intuitive workflow, making it accessible to a wide range of researchers. We demonstrate that Proteoform-predictor expands proteoform databases with tens of thousands of proteoforms for three bacterial strains by comparing them to the reference proteome of Escherichia coli (E. coli) K12. Subsequent TDP analysis for Serratia marcescens (S. marcescens) and Salmonella typhimurium (S. typhimurium) demonstrated significant improvement in protein and proteoform identification, even for proteins with variant sequences. As TDP technology advances, Proteoform-predictor will become an important tool for expanding the applicability of proteoform identification and PTM biology to more diverse species across the phylogenetic tree of life.

Normalized and Directional Interplay Scoring for the Interrogation of Proteoform Data

Histone proteoforms, often presenting multiple co-occurring post-translational modifications (PTMs), are central to chromatin regulation and gene expression. A proteoform is a specific form of a protein that includes variations arising from genetic changes, alternative RNA splicing, proteolytic processing, and PTMs. Genome-indexed histone proteoforms define the histone code, influencing cellular phenotype by dictating DNA interacting partners. Understanding the dynamics of histone proteoforms is essential for elucidating chromatin-based regulatory mechanisms. Advances in middle-down and top-down proteomics enable accurate identification and quantitation of thousands of proteoforms in a single run. However, the resulting data complexity presents significant challenges for analysis and visualization. Here, we introduce two new computational methods to analyze the dynamics of histone PTMs and demonstrate their use in mouse organs during aging. The score that we term "normalized interplay" addresses limitations of the original crosstalk score "interplay" providing a more complete and accurate measure of PTM crosstalk. The second score, ΔI or "directional interplay" is an asymmetric measure quantifying the magnitude and directionality of crosstalk between PTMs. Applying our two-stage scoring approach to data from CrosstalkDB reveals the dynamics of histone H3 modifications during aging.

Widespread variation in molecular interactions and regulatory properties among transcription factor isoforms

Most human transcription factor (TF) genes encode multiple protein isoforms differing in DNA-binding domains, effector domains, or other protein regions. The global extent to which this results in functional differences between isoforms remains unknown. Here, we systematically compared 693 isoforms of 246 TF genes, assessing DNA binding, protein binding, transcriptional activation, subcellular localization, and condensate formation. Relative to reference isoforms, two-thirds of alternative TF isoforms exhibit differences in one or more molecular activities, which often could not be predicted from sequence. We observed two primary categories of alternative TF isoforms: "rewirers" and "negative regulators," both of which were associated with differentiation and cancer. Our results support a model wherein the relative expression levels of, and interactions involving, TF isoforms add an understudied layer of complexity to gene regulatory networks, demonstrating the importance of isoform-aware characterization of TF functions and providing a rich resource for further studies.

The nonlinear cysteine redox dynamics in the i-space: A proteoform-centric theory of redox regulation

The post-translational redox regulation of protein function by cysteine oxidation controls diverse biological processes, from cell division to death. However, most current site-centric paradigms fail to capture the nonlinear and emergent nature of redox regulation in proteins with multiple cysteines. Here, we present a proteoform-centric theory of redox regulation grounded in the i-space. The i-space encapsulates the theoretical landscape of all possible cysteine proteoforms. Using computational approaches, we quantify the vast size of the abstract i-space, revealing its scale-free architecture-elucidating the disproportionate influence of cysteine-rich proteins. We define mathematical rules governing cysteine proteoform dynamics. Their dynamics are inherently nonlinear, context-dependent, and fundamentally constrained by protein copy numbers. Monte Carlo simulations of the human protein PTP1B reveal extensive i-space sampling beyond site-centric models, supporting the "oxiform conjecture". This conjecture posits that highly oxidised proteoforms, molecules bearing multiple oxidised cysteines, are central to redox regulation. In support, even 90%-reduced proteomes can house vast numbers of unique, potentially functioanlly diverse, oxiforms. This framework offers a transformative lens for understanding the redox biology of proteoforms.

Fc Proteoforms of ACPA IgG Discriminate Autoimmune Responses in Plasma and Synovial Fluid of Rheumatoid Arthritis Patients and Associate with Disease Activity

Autoantibodies and their post-translational modifications (PTMs) are insightful markers of autoimmune diseases providing diagnostic and prognostic clues, thereby informing clinical decisions. However, current autoantibody analyses focus mostly on IgG1 glycosylation representing only a subpopulation of the actual IgG proteome. Here, by taking rheumatoid arthritis (RA) as prototypic autoimmune disease, we sought to circumvent these shortcomings and illuminate the importance of (auto)antibody proteoforms employing a novel comprehensive mass spectrometry (MS)-based analytical workflow. Profiling of anti-citrullinated protein antibodies (ACPA) IgG and total IgG in paired samples of plasma and synovial fluid revealed a clear distinction of autoantibodies from total IgG and between biofluids. This discrimination relied on comprehensive subclass-specific PTM profiles including previously neglected features such as IgG3 CH3 domain glycosylation, allotype ratios, and non-glycosylated IgG. Intriguingly, specific proteoforms were found to correlate with markers of inflammation and disease accentuating the need of such approaches in clinical investigations and calling for further mechanistic studies to comprehend the role of autoantibody proteoforms in defining autoimmune responses.

Causal machine learning for single-cell genomics

Advances in single-cell '-omics' allow unprecedented insights into the transcriptional profiles of individual cells and, when combined with large-scale perturbation screens, enable measuring of the effect of targeted perturbations on the whole transcriptome. These advances provide an opportunity to better understand the causative role of genes in complex biological processes. In this Perspective, we delineate the application of causal machine learning to single-cell genomics and its associated challenges. We first present the causal model that is most commonly applied to single-cell biology and then identify and discuss potential approaches to three open problems: the lack of generalization of models to novel experimental conditions, the complexity of interpreting learned models, and the difficulty of learning cell dynamics.

Review: Utility of mass spectrometry in rare disease research and diagnosis

Individuals affected by a rare disease often experience a long and arduous diagnostic odyssey. Delivery of genetic answers in a timely manner is critical to affected individuals and their families. Multi-omics, a term which usually encompasses genomics, transcriptomics, proteomics, metabolomics and lipidomics, has gained increasing popularity in rare disease research and diagnosis over the past decade. Mass spectrometry (MS) is a technique allowing the study of proteins, metabolites and lipids and their fragments at scale, enabling researchers to effectively determine the presence and abundance of thousands of molecules in a single test, accurately quantify their specific levels, identify potential therapeutic biomarkers, detect differentially expressed proteins in patients with rare diseases, and monitor disease progression and treatment response. In this review, we focus on mass spectrometry (MS)-based omics and survey the literature describing the utility of different MS-based omics and how they have transformed rare disease research and diagnosis.

Obtaining Narrow Distributions of Single-Molecule Peptide Signals Enables Sensitive Peptide Discrimination with α-Hemolysin Nanopores

Biological nanopore technology has emerged as a promising tool for analyzing peptides and post-translational modifications at the single-molecule level. However, a broader application is currently limited by the partial separation of peptides and low-throughput, mainly due to the nonuniform peptide signals detected by nanopores. Narrowing the peptide signal distribution is crucial for improving the nanopore's sensing ability but remains a bottleneck. Here, we demonstrate that capturing peptides with electrophoretic force against electroosmotic flow can provoke more uniform blockades in α-hemolysin nanopores. By using buffers with 2 M KCl at pH 3.8, we obtain the most uniform peptide signals, which may be correlated to the shape, linearization, and actual dwelling position of peptides. Five peptides with acetylation and phosphorylation, including isomeric peptides, can be readily separated from each other. The citrullination replacement of arginine and the β-hydroxybutyrylation modification in another peptide sequence are also discriminated in a mixture. A series of peptides with different compositions induced uniform peptide blockades when they were analyzed with our method. Our work presents an efficient approach to optimize nanopore signals for peptide analysis using α-hemolysin nanopores.

The Role of the Sirtuin Family Histone Deacetylases in Acute Myeloid Leukemia-A Promising Road Ahead

Acute myeloid leukemia (AML) corresponds to a heterogeneous group of clonal hematopoietic diseases, which are characterized by uncontrolled proliferation of malignant transformed myeloid precursors and their inability to differentiate into mature blood cells. The prognosis of AML depends on many variables, including the genetic features of the disease. Treatment outcomes, despite the introduction of new targeted therapies, are still unsatisfactory. Recently, there have been an increasing number of reports on enzymatic proteins of the sirtuin family and their potential importance in cancer in general. Sirtuins are a group of 7 (SIRT1-7) NAD+-dependent histone deacetylases with pleiotropic effects on metabolism, aging processes, and cell survival. They are not only responsible for post-translational modification of histones but also play various biochemical functions and interact with other proteins regulating cell survival, such as p53. Thus, their role in key mechanisms of tumorigenesis makes them a worthwhile topic in AML. Different sirtuins have been shown to act oppositely depending on the biological context, the mechanism of which requires further exploration. This review provides a comprehensive description of the significance and role of sirtuins in AML in light of the current state of knowledge. It focuses in particular on molecular mechanisms regulated by sirtuins and signaling pathways involved in leukemogenesis, as well as clinical aspects and potential therapeutic targets in AML.

NMR and semi-synthesis in synergy to study protein regulation

Structural biology as a field has advanced immensely in the last few years, but the mechanistic roles of protein disordered regions and their associated post-translational modifications on the molecular level are still poorly understood. Nuclear magnetic resonance offers the possibility to investigate these regions with atomic resolution and understand the effect of protein modification, and thus protein regulation. However, obtaining suitable and well-defined samples is not straightforward. Here, I review some approaches to protein semi-synthesis for nuclear magnetic resonance purposes, and their applications. I hope to demonstrate that these chemical and structural biology techniques create a powerful synergy that enables structural studies of protein regulation.

Computational electrostatic engineering of nanobodies for enhanced SARS-CoV-2 receptor binding domain recognition

This study presents a novel computational approach for engineering nanobodies (Nbs) for improved interaction with receptor-binding domain (RBD) of the SARS-CoV-2 spike protein. Using Protein Structure Reliability reports, RBD (7VYR_R) was selected and refined for subsequent Nb-RBD interactions. By leveraging electrostatic complementarity (EC) analysis, we engineered and characterized five Electrostatically Complementary Nbs (ECSb1-ECSb5) based on the CeVICA library's SR6c3 Nb. Through targeted modifications in the complementarity-determining regions (CDR) and framework regions (FR), we optimized electrostatic interactions to improve binding affinity and specificity. The engineered Nbs (ECSb3, ECSb4, and ECSb5) demonstrated high binding specificity for AS3, CA1, and CA2 epitopes. Interestingly, ECSb1 and ECSb2 selectively engaged with AS3 and CA1 instead of AS1 and AS2, respectively, due to a preference for residues that conferred superior binding complementarities. Furthermore, ECSbs significantly outperformed SR6c3 Nb in MM/GBSA results, notably, ECSb4 and ECSb3 exhibited superior binding free energies of -182.58 kcal.mol-1 and -119.07 kcal.mol-1, respectively, compared to SR6c3 (-105.50 kcal.mol-1). ECSbs exhibited significantly higher thermostability (100.4-148.3 kcal·mol⁻1) compared to SR6c3 (62.6 kcal·mol⁻1). Similarly, enhanced electrostatic complementarity was also observed for ECSb4-RBD and ECSb3-RBD (0.305 and 0.390, respectively) relative to SR6c3-RBD (0.233). Surface analyses confirmed optimized electrostatic patches and reduced aggregation propensity in the engineered Nb. This integrated EC and structural engineering approach successfully developed engineered Nbs with enhanced binding specificity, increased thermostability, and reduced aggregation, laying the groundwork for novel therapeutic applications targeting the SARS-CoV-2 spike protein.

Spatial top-down proteomics for the functional characterization of human kidney

BACKGROUND

The Human Proteome Project has credibly detected nearly 93% of the roughly 20,000 proteins which are predicted by the human genome. However, the proteome is enigmatic, where alterations in amino acid sequences from polymorphisms and alternative splicing, errors in translation, and post-translational modifications result in a proteome depth estimated at several million unique proteoforms. Recently mass spectrometry has been demonstrated in several landmark efforts mapping the human proteoform landscape in bulk analyses. Herein, we developed an integrated workflow for characterizing proteoforms from human tissue in a spatially resolved manner by coupling laser capture microdissection, nanoliter-scale sample preparation, and mass spectrometry imaging.

RESULTS

Using healthy human kidney sections as the case study, we focused our analyses on the major functional tissue units including glomeruli, tubules, and medullary rays. After laser capture microdissection, these isolated functional tissue units were processed with microPOTS (microdroplet processing in one-pot for trace samples) for sensitive top-down proteomics measurement. This provided a quantitative database of 616 proteoforms that was further leveraged as a library for mass spectrometry imaging with near-cellular spatial resolution over the entire section. Notably, several mitochondrial proteoforms were found to be differentially abundant between glomeruli and convoluted tubules, and further spatial contextualization was provided by mass spectrometry imaging confirming unique differences identified by microPOTS, and further expanding the field-of-view for unique distributions such as enhanced abundance of a truncated form (1-74) of ubiquitin within cortical regions.

CONCLUSIONS

We developed an integrated workflow to directly identify proteoforms and reveal their spatial distributions. Of the 20 differentially abundant proteoforms identified as discriminate between tubules and glomeruli by microPOTS, the vast majority of tubular proteoforms were of mitochondrial origin (8 of 10) while discriminate proteoforms in glomeruli were primarily hemoglobin subunits (9 of 10). These trends were also identified within ion images demonstrating spatially resolved characterization of proteoforms that has the potential to reshape discovery-based proteomics because the proteoforms are the ultimate effector of cellular functions. Applications of this technology have the potential to unravel etiology and pathophysiology of disease states, informing on biologically active proteoforms, which remodel the proteomic landscape in chronic and acute disorders.

Superhydrophilic Nanostructured Microparticles for Enhanced Phosphoprotein Enrichment from Alzheimer's Disease Brain

Alzheimer's disease (AD) is an incurable neurodegenerative disorder and closely related to abnormal phosphoproteoforms. The analysis of low-abundance phosphoproteoforms relies heavily on the enrichment of phosphoproteins. However, existing phosphoprotein enrichment materials suffer from either low selectivity or low coverage due to the unavoidable unspecific adsorption of background proteins. Here, we propose a strategy of nanostructure-enabled superhydrophilic surfaces and synthesize Ti4+-functionalized superhydrophilic nanostructured microparticles (SNMs-Ti4+) via an emulsion interfacial polymerization process. In this process, hydrophilic and hydrophobic monomers assemble into a stable oil-in-water emulsion, producing microparticles with abundant hydrophilic phosphate nanoprotrusions on the surface. The microparticles are subsequently functionalized with Ti4+. SNMs-Ti4+ exhibit enormous nanoprotrusions and abundant Ti4+ modifications, which allow SNMs-Ti4+ to effectively adsorb the phosphoproteins and suppress the unspecific adsorption of background proteins. Using these SNMs-Ti4+, we identified 2256 phosphoproteins from HeLa cells, twice the number of those enriched with commercial kits. From AD mouse brains, 2603 phosphoproteins were successfully enriched, and 10 times of AD-related differentially regulated phosphoproteins were discovered than those without enrichment. These microparticles show great prospects for biomarker detection, disease diagnosis, and downstream biological process disclosure.

Genetic architecture of the red blood cell proteome in genetically diverse mice reveals central role of hemoglobin beta cysteine redox status in maintaining circulating glutathione pools

Red blood cells (RBCs) transport oxygen but accumulate oxidative damage over time, reducing function in vivo and during storage-critical for transfusions. To explore genetic influences on RBC resilience, we profiled proteins, metabolites, and lipids from fresh and stored RBCs obtained from 350 genetically diverse mice. Our analysis identified over 6,000 quantitative trait loci (QTL). Compared to other tissues, prevalence of trans genetic effects over cis reflects the absence of de novo protein synthesis in anucleated RBCs. QTL hotspots at Hbb, Hba, Mon1a, and storage-specific Steap3 linked ferroptosis to hemolysis. Proteasome components clustered at multiple loci, underscoring the importance of degrading oxidized proteins. Post-translational modifications (PTMs) mapped predominantly to hemoglobins, particularly cysteine residues. Loss of reactive C93 in humanized mice (HBB C93A) disrupted redox balance, affecting glutathione pools, protein glutathionylation, and redox PTMs. These findings highlight genetic regulation of RBC oxidation, with implications for transfusion biology and oxidative stress-dependent hemolytic disorders.

The main sources of molecular organization in the cell. Atlas of self-organized and self-regulated dynamic biostructures

One of the most important goals of contemporary biology is to understand the principles of the molecular order underlying the complex dynamic architecture of cells. Here, we present an overview of the main driving forces involved in the cellular molecular complexity and in the emergent functional dynamic structures, spanning from the most basic molecular organization levels to the complex emergent integrative systemic behaviors. First, we address the molecular information processing which is essential in many complex fundamental mechanisms such as the epigenetic memory, alternative splicing, regulation of transcriptional system, and the adequate self-regulatory adaptation to the extracellular environment. Next, we approach the biochemical self-organization, which is central to understand the emergency of metabolic rhythms, circadian oscillations, and spatial traveling waves. Such a complex behavior is also fundamental to understand the temporal compartmentalization of the cellular metabolism and the dynamic regulation of many physiological activities. Numerous examples of biochemical self-organization are considered here, which show that practically all the main physiological processes in the cell exhibit this type of dynamic molecular organization. Finally, we focus on the biochemical self-assembly which, at a primary level of organization, is a basic but important mechanism for the order in the cell allowing biomolecules in a disorganized state to form complex aggregates necessary for a plethora of essential structures and physiological functions. In total, more than 500 references have been compiled in this review. Due to these main sources of order, systemic functional structures emerge in the cell, driving the metabolic functionality towards the biological complexity.

Toward Identification of Markers for Brain-Derived Extracellular Vesicles in Cerebrospinal Fluid: A Large-Scale, Unbiased Analysis Using Proximity Extension Assays

Extracellular vesicles (EVs) captured in biofluids have opened a new frontier for liquid biopsies. To enrich for vesicles coming from a particular cell type or tumour, scientists utilize antibodies to transmembrane proteins that are relatively unique to the cell type of interest. However, recent evidence has called into question the basic assumption that all transmembrane proteins measured in biofluids are, in fact, EV-associated. To identify both candidate markers for brain-derived EV immunocapture and cargo proteins to validate the EVs' cell of origin, we conducted an unbiased Olink screen, measuring 5416 unique proteins in cerebrospinal fluid after size exclusion chromatography. We identified proteins that demonstrated a clear EV fractionation pattern and created a searchable dataset of candidate EV-associated markers-both proteins that are cell type-specific within the brain, and proteins found across multiple cell types for use as general EV markers. We further implemented the DeepTMHMM deep learning model to differentiate predicted cytosolic, transmembrane, and external proteins and found that intriguingly, only 10% of the predicted transmembrane proteins have a clear EV fractionation pattern based on our stringent criteria. This dataset further bolsters the critical importance of verifying EV association of candidate proteins using methods such as size exclusion chromatography before downstream use of the targets for EV analysis.

Functional proteoform group deconvolution reveals a broader spectrum of ibrutinib off-targets

Proteome-wide profiling has revealed that targeted drugs can have complex protein interaction landscapes. However, it's a challenge to profile drug targets while systematically accounting for the dynamic protein variations that produce populations of multiple proteoforms. We address this problem by combining thermal proteome profiling (TPP) with functional proteoform group detection to refine the target landscape of ibrutinib. In addition to known targets, we implicate additional specific functional proteoform groups linking ibrutinib to mechanisms in immunomodulation and cellular processes like Golgi trafficking, endosomal trafficking, and glycosylation. Further, we identify variability in functional proteoform group profiles in a CLL cohort, linked to treatment status and ex vivo response and resistance. This offers deeper insights into the impacts of functional proteoform groups in a clinical treatment setting and suggests complex biological effects linked to off-target engagement. These results provide a framework for interpreting clinically observed off-target processes and adverse events, highlighting the importance of functional proteoform group-level deconvolution in understanding drug interactions and their functional impacts with potential applications in precision medicine.

Emerging opportunities for intact and native protein analysis using chemical proteomics

Chemical proteomics has advanced small molecule ligand discovery by providing insights into protein-ligand binding mechanism and enabling medicinal chemistry optimization of protein selectivity on a global scale. Mass spectrometry is the predominant analytical method for chemoproteomics, and various approaches have been deployed to investigate and target a rapidly growing number of protein classes and biological systems. Two methods, intact mass analysis (IMA) and top-down proteomics (TDMS), have gained interest in recent years due to advancements in high resolution mass spectrometry instrumentation. Both methods apply mass spectrometry analysis at the proteoform level, as opposed to the peptide level of bottom-up proteomics (BUMS), thus addressing some of the challenges of protein inference and incomplete information on modification stoichiometry. This Review covers recent research progress utilizing MS-based proteomics methods, discussing in detail the capabilities and opportunities for improvement of each method. Further, heightened attention is given to IMA and TDMS, highlighting these methods' strengths and considerations when utilized in chemoproteomic studies. Finally, we discuss the capabilities of native mass spectrometry (nMS) and ion mobility mass spectrometry (IM-MS) and how these methods can be used in chemoproteomics research to complement existing approaches to further advance the field of functional proteomics.

Gel-Based Sample Fractionation with SP3-Purification for Top-Down Proteomics

Precise prefractionation of proteome samples is a potent method for realizing in-depth analysis in top-down proteomics. PEPPI-MS (Passively Eluting Proteins from Polyacrylamide gels as Intact species for MS), a gel-based sample fractionation method, enables high-resolution proteome fractionation based on molecular weight by highly efficient extraction of proteins from polyacrylamide gels after SDS-PAGE separation. Thereafter it is essential to effectively remove contaminants such as CBB and SDS from the PEPPI fraction prior to mass spectrometry. In this study, we developed a complete, robust, and simple sample preparation workflow named PEPPI-SP3 for top-down proteomics by combining PEPPI-MS with the magnetic bead-based protein purification approach used in SP3 (single-pot, solid-phase-enhanced sample preparation), now one of the standard sample preparation methods in bottom-up proteomics. In PEPPI-SP3, proteins extracted from the gel are collected on the surface of SP3 beads, washed with organic solvents, and recovered intact with 100 mM ammonium bicarbonate containing 0.05% (w/v) SDS. The recovered proteins are subjected to mass spectrometry after additional purification using an anion-exchange StageTip. Performance validation using human cell lysates showed a significant improvement in low-molecular-weight protein recovery with a lower coefficient of variation compared to conventional PEPPI workflows using organic solvent precipitation or ultrafiltration.

Defining proteoform-specific interactions for drug targeting in a native cell signalling environment

Understanding the dynamics of membrane protein-ligand interactions within a native lipid bilayer is a major goal for drug discovery. Typically, cell-based assays are used, however, they are often blind to the effects of protein modifications. In this study, using the archetypal G protein-coupled receptor rhodopsin, we found that the receptor and its effectors can be released directly from retina rod disc membranes using infrared irradiation in a mass spectrometer. Subsequent isolation and dissociation by infrared multiphoton dissociation enabled the sequencing of individual retina proteoforms. Specifically, we categorized distinct proteoforms of rhodopsin, localized labile palmitoylations, discovered a Gβγ proteoform that abolishes membrane association and defined lipid modifications on G proteins that influence their assembly. Given reports of undesirable side-effects involving vision, we characterized the off-target drug binding of two phosphodiesterase 5 inhibitors, vardenafil and sildenafil, to the retina rod phosphodiesterase 6 (PDE6). The results demonstrate differential off-target reactivity with PDE6 and an interaction preference for lipidated proteoforms of G proteins. In summary, this study highlights the opportunities for probing proteoform-ligand interactions within natural membrane environments.

Understanding the molecular diversity of synapses

Synapses are composed of thousands of proteins, providing the potential for extensive molecular diversity to shape synapse type-specific functional specializations. In this Review, we explore the landscape of synaptic diversity and describe the mechanisms that expand the molecular complexity of synapses, from the genotype to the regulation of gene expression to the production of specific proteoforms and the formation of localized protein complexes. We emphasize the importance of examining every molecular layer and adopting a systems perspective to understand how these interconnected mechanisms shape the diverse functional and structural properties of synapses. We explore current frameworks for classifying synapses and methodologies for investigating different synapse types at varying scales, from synapse-type-specific proteomics to advanced imaging techniques with single-synapse resolution. We highlight the potential of synapse-type-specific approaches for integrating molecular data with cellular functions, circuit organization and organismal phenotypes to enable a more holistic exploration of neuronal phenomena across different scales.

Proteomic Analysis of Biological Fluids

Biological fluids are proteinaceous liquids or suspensions released through different body orifices or through penetration of the skin. These fluids are the result of multiple tissues and cell types and contain extensive, highly complex, and dynamic protein populations that reflect both the transcriptional program of the originating cells and a record of the individual's health status. Body fluids are readily accessible to clinicians and researchers, and as such proteomic analyses are an important component of clinical studies, fertility studies, oral health studies, and forensic investigations. Current mass spectrometry (MS) datasets have a dynamic range of up to six orders of magnitude and are as diverse as the originating tissue types. Mass spectrometry has the potential to provide information across a wide range of applications, including basic research into human biology and pathology, biochemical analysis of protein function, biomarker discovery and detection, as well as forensic investigations wherein investigators interpret a protein profile to identify the body site origin of a biological fluid. The method below describes a specimen processing workflow that is flexible in terms of biological fluid type, sample state (e.g., a dried sample extracted from evidence or neat fluid), and level of degradation. The method described here is compatible with both high sensitivity shotgun liquid chromatography-mass spectrometry LC/MS analysis and targeted (qualitative or quantitative) MS-based analysis of biomarker candidates.

Nanofluidic Lab-On-A-Chip Systems for Biosensing in Healthcare

Biosensing plays a vital role in healthcare monitoring, disease detection, and treatment planning. In recent years, nanofluidic technology has been increasingly explored to be developed into lab-on-a-chip biosensing systems. Given now the possibility of fabricating geometrically defined nanometric channels that are commensurate with the size of many biomolecules, nanofluidic-based devices are likely to become a key technology for the analysis of various clinical biomarkers, including DNA (deoxyribonucleic acid) and proteins in liquid biopsies. This review summarizes the fundamentals and technological advances of nanofluidics from the purview of single-molecule analysis, detection of low-abundance molecules, and single-cell analysis at the subcellular level. The extreme confinement and dominant surface charge effects in nanochannels provide unique advantages to nanofluidic devices for the manipulation and transport of target biomarkers. When coupled to a microfluidic network to facilitate sample introduction, integrated micro-nanofluidic biosensing devices are proving to be more sensitive and specific in molecular analysis compared to conventional assays in many cases. Based on recent progress in nanofluidics and current clinical trends, the review concludes with a discussion of near-term challenges and future directions for the development of nanofluidic-based biosensing systems toward enabling a new wave of lab-on-a-chip technology for personalized and preventive medicine.

Using TECHnology to predict the future of biomedical education

Biomedical research is currently benefiting from a technological revolution in which multiple forms of omics are permitting unprecedented characterization of molecular pathways. Likewise, medical device and Ai-assisted technologies now make diagnoses and medical imaging more accurate. The field of education is also starting to embrace how technology can promote pedagogical development and student learning. But how will this landscape look like in 2050? With the premise that collaboration will be central to teaching and learning practices, that Together, Everything Can Happen (TECH), we examine the emerging trends and innovations in biomedical education, exploring how they will influence the field's evolution and shape future teaching practices in the coming years.

Investigation of protein post-translational modifications with site-specifically incorporated non-canonical amino acids

Despite the important functions of protein post-translational modifications (PTMs) in numerous cellular processes, understanding the biological roles of PTMs remains quite challenging. Here, we summarize our efforts in recent years to incorporate a variety of non-canonical amino acids (ncAAs) to study the biological functions of protein PTMs in mammalian cells, with a focus on the use of ncAA tools to probe the biological functions of various protein PTMs. We design length-tunable lipidation mimics for studying lipidation function and designing protein drugs. We highlight the use of genetically encoded lysine aminoacylations as chemical baits to identify aminoacylated lysine ubiquitination. Finally, we discuss the use of genetically encoded electron-rich Trp derivatives to design binding affinity-enhancing histone methylations readers.

Digital Microfluidics for Sample Preparation in Low-Input Proteomics

Low-input proteomics, also referred to as micro- or nanoproteomics, has become increasingly popular as it allows one to elucidate molecular processes in rare biological materials. A major prerequisite for the analytics of minute protein amounts, e.g., derived from low cell numbers, down to single cells, is the availability of efficient sample preparation methods. Digital microfluidics (DMF), a technology allowing the handling and manipulation of low liquid volumes, has recently been shown to be a powerful and versatile tool to address the challenges in low-input proteomics. Here, an overview is provided on recent advances in proteomics sample preparation using DMF. In particular, the capability of DMF to isolate proteomes from cells and small model organisms, and to perform all necessary chemical sample preparation steps, such as protein denaturation and proteolytic digestion on-chip, are highlighted. Additionally, major prerequisites to making these steps compatible with follow-up analytical methods such as liquid chromatography-mass spectrometry will be discussed.

Chemical tools to expand the ligandable proteome: Diversity-oriented synthesis-based photoreactive stereoprobes

Chemical proteomics enables the global analysis of small molecule-protein interactions in native biological systems and has emerged as a versatile approach for ligand discovery. The range of small molecules explored by chemical proteomics has, however, remained limited. Here, we describe a diversity-oriented synthesis (DOS)-inspired library of stereochemically defined compounds bearing diazirine and alkyne units for UV light-induced covalent modification and click chemistry enrichment of interacting proteins, respectively. We find that these "photo-stereoprobes" interact in a stereoselective manner with hundreds of proteins from various structural and functional classes in human cells and demonstrate that these interactions can form the basis for high-throughput screening-compatible NanoBRET assays. Integrated phenotypic screening and chemical proteomics identified photo-stereoprobes that modulate autophagy by engaging the mitochondrial serine protease CLPP. Our findings show the utility of DOS-inspired photo-stereoprobes for expanding the ligandable proteome, furnishing target engagement assays, and facilitating the discovery and characterization of bioactive compounds in phenotypic screens.

How to build the virtual cell with artificial intelligence: Priorities and opportunities

Cells are essential to understanding health and disease, yet traditional models fall short of modeling and simulating their function and behavior. Advances in AI and omics offer groundbreaking opportunities to create an AI virtual cell (AIVC), a multi-scale, multi-modal large-neural-network-based model that can represent and simulate the behavior of molecules, cells, and tissues across diverse states. This Perspective provides a vision on their design and how collaborative efforts to build AIVCs will transform biological research by allowing high-fidelity simulations, accelerating discoveries, and guiding experimental studies, offering new opportunities for understanding cellular functions and fostering interdisciplinary collaborations in open science.

Top-Down Stability of Proteins from Rates of Oxidation (TD-SPROX) Approach for Measuring Proteoform-Specific Folding Stability

The crucial roles of proteoforms in biological processes and disease mechanisms have been increasingly recognized. However, the rate at which new proteoforms are being discovered using top-down proteomics has far outpaced the rate at which the functional significance of different proteoforms can be determined. Because of the close connection between protein folding and protein function, protein folding stability measurements on proteoforms have the potential to identify functionally significant proteoforms of a given protein. While a number of mass spectrometry-based proteomics methods for making protein folding stability measurements on the proteomic scale have been reported over the past decade, none have been interfaced with top-down proteomics. Described here is a top-down (TD) stability of proteins from the rates of oxidation (SPROX) approach for making proteoform specific folding stability measurements. This approach is validated using a mixture of three model proteins with well-characterized protein folding behavior by conventional SPROX as well as other more conventional biophysical techniques. The method is also used to evaluate the relative folding stabilities of the <30 kDa protein fraction isolated from an MCF-7 cell lysate. The relative folding stabilities of 150 proteoforms from 83 proteins were successfully characterized in the cell lysate analysis using the TD-SPROX approach.

A Conformation-Specific Approach to Native Top-down Mass Spectrometry

Native top-down mass spectrometry is a powerful approach for characterizing proteoforms and has recently been applied to provide similarly powerful insights into protein conformation. Current approaches, however, are limited such that structural insights can only be obtained for the entire conformational landscape in bulk or without any direct conformational measurement. We report a new ion-mobility-enabled method for performing native top-down MS in a conformation-specific manner. Our approach identified conformation-linked differences in backbone dissociation for the model protein calmodulin, which simultaneously informs upon proteoform variations and provides structural insights. We also illustrate that our method can be applied to protein-ligand complexes, either to identify components or to probe ligand-induced structural changes.

Protein Glycosylation Patterns Shaped By the IRE1-XBP1s Arm of the Unfolded Protein Response

The unfolded protein response (UPR) is a sensing and signaling pathway that surveys the endoplasmic reticulum (ER) for protein folding challenges and responds whenever issues are detected. UPR activation leads to upregulation of secretory pathway chaperones and quality control factors, as well as reduces the nascent protein load on the ER, thereby restoring and maintaining proteostasis. This paradigm-defining view of the role of the UPR is accurate, but it elides additional key functions of the UPR in cell biology. In particular, recent work has revealed that the UPR can shape the structure and function of N- and O-glycans installed on ER client proteins. This crosstalk between the UPR's response to protein misfolding and the regulation of glycosylation remains insufficiently understood. Still, emerging evidence makes it clear that the UPR, and particularly the IRE1-XBP1s arm of the UPR, may be a central regulator of protein glycosylation with important biological consequences. In this review, we discuss the crosstalk between proteostasis, the UPR, and glycosylation, present progress towards understanding biological functions of this crosstalk, and examine potential roles in diseases such as cancer.

Top-Down Proteomics Identifies Plasma Proteoform Signatures of Liver Cirrhosis Progression

Cirrhosis, advanced liver disease, affects 2 to 5 million Americans. While most patients have compensated cirrhosis and may be fairly asymptomatic, many decompensate and experience life-threatening complications such as gastrointestinal bleeding, confusion (hepatic encephalopathy), and ascites, reducing life expectancy from 12 to less than 2 years. Among patients with compensated cirrhosis, identifying patients at high risk of decompensation is critical to optimize care and reduce morbidity and mortality. Therefore, it is important to preferentially direct them towards specialty care which cannot be provided to all patients with cirrhosis. We used discovery top-down proteomics to identify differentially expressed proteoforms (DEPs) in the plasma of patients with progressive stages of liver cirrhosis with the ultimate goal to identify candidate biomarkers of disease progression. In this pilot study, we identified 209 DEPs across three stages of cirrhosis (compensated, compensated with portal hypertension, and decompensated), of which 115 derived from proteins enriched in the liver at a transcriptional level and discriminated the three stages of cirrhosis. Enrichment analyses demonstrated DEPs are involved in several metabolic and immunological processes known to be impacted by cirrhosis progression. We have preliminarily defined the plasma proteoform signatures of cirrhosis patients, setting the stage for ongoing discovery and validation of biomarkers for early diagnosis, risk stratification, and disease monitoring.

Top-down mass spectrometry of native proteoforms and their complexes: a community study

The combination of native electrospray ionization with top-down fragmentation in mass spectrometry (MS) allows simultaneous determination of the stoichiometry of noncovalent complexes and identification of their component proteoforms and cofactors. Although this approach is powerful, both native MS and top-down MS are not yet well standardized, and only a limited number of laboratories regularly carry out this type of research. To address this challenge, the Consortium for Top-Down Proteomics initiated a study to develop and test protocols for native MS combined with top-down fragmentation of proteins and protein complexes across 11 instruments in nine laboratories. Here we report the summary of the outcomes to provide robust benchmarks and a valuable entry point for the scientific community.

Lipid-polymer hybrid-vesicles interrupt nucleation of amyloid fibrillation

Solubility and aggregation of proteins are crucial factors for their functional and further biological roles. Aggregation of proteins in vivo, such as the amyloid beta (Aβ1-40) peptide into fibrils, is significantly modulated by membrane lipids, abundantly present in cells. We developed a model membrane system, composed of lipid hybrid-vesicles bearing embedded hydrophilic polymers to in vitro study the aggregation of the Aβ1-40 peptide. Focus is to understand and inhibit the primordial, nucleation stages of their fibrillation by added hybrid-vesicles, composed of a natural lipid and amphiphilic polymers. These designed hybrid-vesicles are based on 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine (POPC), displaying embedded hydrophilic (EO) m P n A_EG polymers (m = 2 or 3; P n = 10 to 52 with M n = 2800-9950 gmol-1) in amounts ranging from 5-20 mol%, anchored to the POPC vesicles via hydrophobic hexadecyl-, glyceryl- and cholesteryl-moieties, affixed to the polymers as end-groups. All investigated hybrid-vesicles significantly delay fibrillation of the Aβ1-40 peptide as determined by thioflavin T (ThT) assays. We observed that the hybrid-vesicles interacted with early aggregating species of Aβ1-40 peptide, irrespective of their composition or size. A substantial perturbation of both primary (k + k n ) and secondary (k + k 2) nucleation rates of Aβ1-40 by the POPC-polymer vesicles compared to POPC vesicles was observed, particularly for the cholesteryl-anchored polymers, interfering with the fragmentation and elongation steps of Aβ1-40. Furthermore, morphological differences of the aggregates were revealed by transmission electron microscopy (TEM) images supported the inhibitory kinetic signatures.

Extended range proteomic analysis of blood plasma from schizophrenia patients

Introduction

The high prevalence of schizophrenia worldwide makes it necessary to proceed from subjective assessment of patient's clinical symptoms in diagnosis making to searching for circulating blood biomarkers. On the one hand, searching for molecular markers and targets for therapeutics will make it possible to refine and detail the molecular mechanisms of pathology development, while on the other hand, it will offer new opportunities for elaborating novel approaches to disease diagnosis and enhance efficacy and timeliness of drug therapy.

Methods

In this study, we performed an extended-range proteomic analysis of plasma samples collected from 48 study subjects with confirmed diagnosis of schizophrenia and 50 healthy volunteers. The high-resolution tandem mass spectra recorded in the data-dependent acquisition mode were analyzed using the MaxQuant algorithm for the library of known protein sequences and the PowerNovo algorithm for de novo protein sequencing.

Results

It was demonstrated that both strategies show similar results for high-abundance proteins (≥1 μg/mL). For mid-abundance (10 ng/mL - 1 μg/mL) and low-abundance (<10 ng/mL) proteins, the results obtained by the two search strategies complement each other.

Discussion

Group-specific proteins for the samples of schizophrenia patients were identified, presumably being involved in synaptic plasticity, angiogenesis, transcriptional regulation, protein stabilization and degradation.

Normalized and Directional Interplay Scoring for the Interrogation of Proteoform Data

Histone proteoforms, often presenting multiple co-occurring post-translational modifications (PTMs), are central to chromatin regulation and gene expression. A proteoform is a specific form of a protein that includes variations arising from genetic changes, alternative RNA splicing, proteolytic processing, and PTMs. Genomic context-dependent histone proteoforms define the histone code, influencing cellular phenotype by dictating interactions with DNA and chromatin-associated proteins. Understanding the dynamics of histone proteoforms is essential for elucidating chromatin-based regulatory mechanisms. Advances in middle-down and top-down proteomics methods enable accurate identification and quantitation of hundreds to thousands of proteoforms in a single run. However, the resulting data complexity presents significant challenges for analysis and visualization. Here, we introduce new computational methods to analyze the dynamics of histone PTMs and demonstrate their use in mouse organs during aging. We have developed and benchmarked two novel PTM crosstalk scores. The score that we term 'Normalized Interplay' addresses limitations of the original crosstalk score 'Interplay' providing a more complete and accurate measure of PTM crosstalk. The second score, 'delta I' or Directional Interplay is an asymmetric measure quantifying the magnitude and directionality of crosstalk between PTMs. Applying our two-stage scoring approach to data from CrosstalkDB, a community resource that curates proteoform-level data, reveals the dynamics of histone H3 modifications during aging. The source code is available under an Apache license at https://github.com/k-p4/ptm_interplay_scoring.

Small molecule modulation of protein corona for deep plasma proteome profiling

The protein corona formed on nanoparticles (NPs) has potential as a valuable diagnostic tool for improving plasma proteome coverage. Here, we show that spiking small molecules, including metabolites, lipids, vitamins, and nutrients into plasma can induce diverse protein corona patterns on otherwise identical NPs, significantly enhancing the depth of plasma proteome profiling. The protein coronas on polystyrene NPs when exposed to plasma treated with an array of small molecules allows for the detection of 1793 proteins marking an 8.25-fold increase in the number of quantified proteins compared to plasma alone (218 proteins) and a 2.63-fold increase relative to the untreated protein corona (681 proteins). Furthermore, we discovered that adding 1000 µg/ml phosphatidylcholine could singularly enable the detection of 897 proteins. At this specific concentration, phosphatidylcholine selectively depletes the four most abundant plasma proteins, including albumin, thus reducing the dynamic range of plasma proteome and enabling the detection of proteins with lower abundance. Employing an optimized data-independent acquisition approach, the inclusion of phosphatidylcholine leads to the detection of 1436 proteins in a single plasma sample. Our molecular dynamics results reveal that phosphatidylcholine interacts with albumin via hydrophobic interactions, H-bonds, and water bridges. The addition of phosphatidylcholine also enables the detection of 337 additional proteoforms compared to untreated protein corona using a top-down proteomics approach. Given the critical role of plasma proteomics in biomarker discovery and disease monitoring, we anticipate the widespread adoption of this methodology for the identification and clinical translation of biomarkers.

Assessment of Data-Independent Acquisition Mass Spectrometry (DIA-MS) for the Identification of Single Amino Acid Variants

Proteogenomics integrates genomic and proteomic data to elucidate cellular processes by identifying variant peptides, including single amino acid variants (SAAVs). In this study, we assessed the capability of data-independent acquisition mass spectrometry (DIA-MS) to identify SAAV peptides in HeLa cells using various search engine pipelines. We developed a customised sequence database (DB) incorporating SAAV sequences from the HeLa genome and conducted searches using DIA-NN, Spectronaut, and Fragpipe-MSFragger. Our evaluation focused on identifying true positive SAAV peptides and false positives through entrapment DBs. This study revealed that DIA-MS provides reproducible and comprehensive coverage of the proteome, identifying a substantial proportion of SAAV peptides. Notably, the DIA-MS searches maintained consistent identification of SAAV peptides despite varying sizes of the entrapment DB. A comparative analysis showed that Fragpipe-MSFragger (FP-DIA) demonstrated the most conservative and effective performance, exhibiting the lowest false discovery match ratio (FDMR). Additionally, integrating DIA and data-dependent acquisition (DDA) MS data search outputs enhanced SAAV peptide identification, with a lower false discovery rate (FDR) observed in DDA searches. The validation using stable isotope dilution and parallel reaction monitoring (SID-PRM) confirmed the SAAV peptides identified by DIA-MS and DDA-MS searches, highlighting the reliability of our approach. Our findings underscore the effectiveness of DIA-MS in proteogenomic workflows for identifying SAAV peptides, offering insights into optimising search engine pipelines and DB construction for accurate proteomics analysis. These methodologies advance the understanding of proteome variability, contributing to cancer research and the identification of novel proteoform therapeutic targets.

Using phage display for rational engineering of a higher affinity humanized 3'phosphohistidine-specific antibody

Histidine phosphorylation (pHis) is a non-canonical post-translational modification (PTM) that is historically understudied due to a lack of robust reagents that are required for its investigation, such as high affinity pHis-specific antibodies. Engineering pHis-specific antibodies is very challenging due to the labile nature of the phosphoramidate (P-N) bond and the stringent requirements for selective recognition of the two isoforms, 1-phosphohistidine (1-pHis) and 3-phosphohistidine (3-pHis). Here, we present a strategy for in vitro engineering of antibodies for detection of native 3-pHis targets. Specifically, we humanized the rabbit SC44-8 anti-3-pTza (a stable 3-pHis mimetic) mAb into a scaffold (herein referred to as hSC44) that was suitable for phage display. We then constructed six unique Fab phage-displayed libraries using the hSC44 scaffold and selected high affinity 3-pHis binders. Our selection strategy was carefully designed to enrich antibodies that bound 3-pHis with high affinity and had specificity for 3-pHis versus 3-pTza. hSC44.20N32F L , the best engineered antibody, has an ∼10-fold higher affinity for 3-pHis than the parental hSC44. Eleven new Fab structures, including the first reported antibody-pHis peptide structures were solved by X-ray crystallography. Structural and quantum mechanical calculations provided molecular insights into 3-pHis and 3-pTza discrimination by different hSC44 variants and their affinity increase obtained through in vitro engineering. Furthermore, we demonstrate the utility of these newly developed high-affinity 3-pHis-specific antibodies for recognition of pHis proteins in mammalian cells by immunoblotting and immunofluorescence staining. Overall, our work describes a general method for engineering PTM-specific antibodies and provides a set of novel antibodies for further investigations of the role of 3-pHis in cell biology.

Significance Statement

Histidine phosphorylation is an elusive PTM whose role in mammalian cell biology is largely unknown due to the lack of robust tools and methods for its analysis. Here we report the development of antibodies with unprecedented affinity and specificity towards 3-pHis and present the first crystal structures of a pHis peptide in complex with an antibody. Finally, we show how these antibodies can be used in standard molecular biology workflows to investigate pHis-dependent biology.

Mechanisms of assembly and remodelling of the extracellular matrix

The extracellular matrix (ECM) is the complex meshwork of proteins and glycans that forms the scaffold that surrounds and supports cells. It exerts key roles in all aspects of metazoan physiology, from conferring physical and mechanical properties on tissues and organs to modulating cellular processes such as proliferation, differentiation and migration. Understanding the mechanisms that orchestrate the assembly of the ECM scaffold is thus crucial to understand ECM functions in health and disease. This Review discusses novel insights into the compositional diversity of matrisome components and the mechanisms that lead to tissue-specific assemblies and architectures tailored to support specific functions. The Review then highlights recently discovered mechanisms, including post-translational modifications and metabolic pathways such as amino acid availability and the circadian clock, that modulate ECM secretion, assembly and remodelling in homeostasis and human diseases. Last, the Review explores the potential of 'matritherapies', that is, strategies to normalize ECM composition and architecture to achieve a therapeutic benefit.