A data analysis framework for combining multiple batches increases the power of isobaric proteomics experiments.

We present a framework for the analysis of multiplexed mass spectrometry proteomics data that reduces estimation error when combining multiple isobaric batches. Variations in the number and quality of observations have long complicated the analysis of isobaric proteomics data. Here we show that the power to detect statistical associations is substantially improved by utilizing models that directly account for known sources of variation in the number and quality of observations that occur across batches.In a multibatch benchmarking experiment, our open-source software (msTrawler) increases the power to detect changes, especially in the range of less than twofold changes, while simultaneously increasing quantitative proteome coverage by utilizing more low-signal observations. Further analyses of previously published multiplexed datasets of 4 and 23 batches highlight both increased power and the ability to navigate complex missing data patterns without relying on unverifiable imputations or discarding reliable measurements.

High-Throughput Proteome Profiling of Plasma and Native Plasma Complexes Using Native Chromatography.

We describe a high-throughput method for co-fractionation mass spectrometry (CF-MS) profiling for native plasma protein profiling. CF-MS allows the profiling of endogenous protein complexes between samples. Proteins often interact with other proteins and form macromolecular complexes that are different in disease states as well as cell states and cell types. This protocol describes an example for the sample preparation of 954 individual size exclusion chromatography (SEC) fractions, derived from 18 plasma samples that were separated into 53 fractions. Eighteen plasma samples were chosen based on the TMTpro multiplexing, but this methodology can be adapted for fewer or larger numbers of samples as appropriate. Our automated sample preparation method allows for high-throughput native plasma profiling, and we provide detailed methods for both a label-free and an isobaric labeling approach, discuss the merits of each approach, and detail the advantages of combining these strategies for comprehensive native plasma proteome profiling.

Triple-threat quantitative multiplexed plasma proteomics analysis on immune complex disease MRL-lpr mice.

Systemic lupus erythematosus is a common autoimmune inflammatory disease which is associated with increases in autoantibodies and immune complexes that deposit in the kidney. The MRL-lpr mouse is a common mouse model used for the study of lupus and immune complex glomerulonephritis but very little is known about the plasma proteome changes in this model. We performed in-depth quantitative proteome profiling on MRL-lpr and control (strain MpJ) mice to investigate the changes in the proteome, immunoglobulins and their glycoproteome as well as protein and immune complexes. Methodologies used included immunohistochemistry, immunoglobulin isotyping, multiplexed proteome profiling, immunoglobulin immunoprecipitation with glycoproteome profiling, and size exclusion chromatography (SEC) profiling to enable a comprehensive proteome profiling of proteins and protein complexes. We also used a novel native multiplexed plasma proteome profiling (NativeMP3) method that relies on native enrichment of plasma proteins enabling ultra-deep single shot profiling where we identified 922 plasma proteins at 1% false discovery rate (FDR) in a single shot mass spectrometry run. We observed many large plasma protein differences between the MRL-lpr and control strain including differences in the immunoglobulins, immunoglobulins against specific antigens, chemokines, and proteases as well as changes in protein complexes such as the immunoproteasome.

Tuning DO:DM Ratios Modulates MHC Class II Immunopeptidomes.

Major histocompatibility complex class II (MHC-II) antigen presentation underlies a wide range of immune responses in health and disease. However, how MHC-II antigen presentation is regulated by the peptide-loading catalyst HLA-DM (DM), its associated modulator, HLA-DO (DO), is incompletely understood. This is due largely to technical limitations: model antigen-presenting cell (APC) systems that express these MHC-II peptidome regulators at physiologically variable levels have not been described. Likewise, computational prediction tools that account for DO and DM activities are not presently available. To address these gaps, we created a panel of single MHC-II allele, HLA-DR4-expressing APC lines that cover a wide range of DO:DM ratio states. Using a combined immunopeptidomic and proteomic discovery strategy, we measured the effects DO:DM ratios have on peptide presentation by surveying over 10,000 unique DR4-presented peptides. The resulting data provide insight into peptide characteristics that influence their presentation with increasing DO:DM ratios. These include DM sensitivity, peptide abundance, binding affinity and motif, peptide length, and choice of binding register along the source protein. These findings have implications for designing improved HLA-II prediction algorithms and research strategies for dissecting the variety of functions that different APCs serve in the body.

Exercise plasma boosts memory and dampens brain inflammation via clusterin.

Physical exercise is generally beneficial to all aspects of human and animal health, slowing cognitive ageing and neurodegeneration1. The cognitive benefits of physical exercise are tied to an increased plasticity and reduced inflammation within the hippocampus2-4, yet little is known about the factors and mechanisms that mediate these effects. Here we show that 'runner plasma', collected from voluntarily running mice and infused into sedentary mice, reduces baseline neuroinflammatory gene expression and experimentally induced brain inflammation. Plasma proteomic analysis revealed a concerted increase in complement cascade inhibitors including clusterin (CLU). Intravenously injected CLU binds to brain endothelial cells and reduces neuroinflammatory gene expression in a mouse model of acute brain inflammation and a mouse model of Alzheimer's disease. Patients with cognitive impairment who participated in structured exercise for 6 months had higher plasma levels of CLU. These findings demonstrate the existence of anti-inflammatory exercise factors that are transferrable, target the cerebrovasculature and benefit the brain, and are present in humans who engage in exercise.

An Integrated Genomic, Proteomic, and Immunopeptidomic Approach to Discover Treatment-Induced Neoantigens.

All nucleated mammalian cells express major histocompatibility complex (MHC) proteins that present peptides on cell surfaces for immune surveillance. These MHC-presented peptides (pMHC) are necessary for directing T-cell responses against cells harboring non-self antigens derived from pathogens or from somatic mutations. Alterations in tumor-specific antigen repertoires - particularly novel MHC presentation of mutation-bearing peptides (neoantigens) - can be potent targets of anti-tumor immune responses. Here we employed an integrated genomic and proteomic antigen discovery strategy aimed at measuring how interferon gamma (IFN-γ) alters antigen presentation, using a human lymphoma cell line, GRANTA-519. IFN-γ treatment resulted in 126 differentially expressed proteins (2% of all quantified proteins), which included components of antigen presentation machinery and interferon signaling pathways, and MHC molecules themselves. In addition, several proteasome subunits were found to be modulated, consistent with previous reports of immunoproteasome induction by IFN-γ exposure. This finding suggests that a modest proteomic response to IFN-γ could create larger alteration to cells' antigen/epitope repertoires. Accordingly, MHC immunoprecipitation followed by mass spectrometric analysis of eluted peptide repertoires revealed exclusive signatures of IFN-γ induction, with 951 unique peptides reproducibly presented by MHC-I and 582 presented by MHC-II. Furthermore, an additional set of pMHCs including several candidate neoantigens, distinguished control and the IFN-γ samples by their altered relative abundances. Accordingly, we developed a classification system to distinguish peptides which are differentially presented due to altered expression from novel peptides resulting from changes in antigen processing. Taken together, these data demonstrate that IFN-γ can re-shape antigen repertoires by identity and by abundance. Extending this approach to models with greater clinical relevance could help develop strategies by which immunopeptide repertoires are intentionally reshaped to improve endogenous or vaccine-induced anti-tumor immune responses and potentially anti-viral immune responses.

Automated 16-Plex Plasma Proteomics with Real-Time Search and Ion Mobility Mass Spectrometry Enables Large-Scale Profiling in Naked Mole-Rats and Mice.

Performing large-scale plasma proteome profiling is challenging due to limitations imposed by lengthy preparation and instrument time. We present a fully automated multiplexed proteome profiling platform (AutoMP3) using the Hamilton Vantage liquid handling robot capable of preparing hundreds to thousands of samples. To maximize protein depth in single-shot runs, we combined 16-plex Tandem Mass Tags (TMTpro) with high-field asymmetric waveform ion mobility spectrometry (FAIMS Pro) and real-time search (RTS). We quantified over 40 proteins/min/sample, doubling the previously published rates. We applied AutoMP3 to investigate the naked mole-rat plasma proteome both as a function of the circadian cycle and in response to ultraviolet (UV) treatment. In keeping with the lack of synchronized circadian rhythms in naked mole-rats, we find few circadian patterns in plasma proteins over the course of 48 h. Furthermore, we quantify many disparate changes between mice and naked mole-rats at both 48 h and one week after UV exposure. These species differences in plasma protein temporal responses could contribute to the pronounced cancer resistance observed in naked mole-rats. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE [1] partner repository with the dataset identifier PXD022891.

Physiological blood-brain transport is impaired with age by a shift in transcytosis.

The vascular interface of the brain, known as the blood-brain barrier (BBB), is understood to maintain brain function in part via its low transcellular permeability1-3. Yet, recent studies have demonstrated that brain ageing is sensitive to circulatory proteins4,5. Thus, it is unclear whether permeability to individually injected exogenous tracers-as is standard in BBB studies-fully represents blood-to-brain transport. Here we label hundreds of proteins constituting the mouse blood plasma proteome, and upon their systemic administration, study the BBB with its physiological ligand. We find that plasma proteins readily permeate the healthy brain parenchyma, with transport maintained by BBB-specific transcriptional programmes. Unlike IgG antibody, plasma protein uptake diminishes in the aged brain, driven by an age-related shift in transport from ligand-specific receptor-mediated to non-specific caveolar transcytosis. This age-related shift occurs alongside a specific loss of pericyte coverage. Pharmacological inhibition of the age-upregulated phosphatase ALPL, a predicted negative regulator of transport, enhances brain uptake of therapeutically relevant transferrin, transferrin receptor antibody and plasma. These findings reveal the extent of physiological protein transcytosis to the healthy brain, a mechanism of widespread BBB dysfunction with age and a strategy for enhanced drug delivery.

Inter-domain dynamics drive cholesterol transport by NPC1 and NPC1L1 proteins.

Transport of LDL-derived cholesterol from lysosomes into the cytoplasm requires NPC1 protein; NPC1L1 mediates uptake of dietary cholesterol. We introduced single disulfide bonds into NPC1 and NPC1L1 to explore the importance of inter-domain dynamics in cholesterol transport. Using a sensitive method to monitor lysosomal cholesterol efflux, we found that NPC1's N-terminal domain need not release from the rest of the protein for efficient cholesterol export. Either introducing single disulfide bonds to constrain lumenal/extracellular domains or shortening a cytoplasmic loop abolishes transport activity by both NPC1 and NPC1L1. The widely prescribed cholesterol uptake inhibitor, ezetimibe, blocks NPC1L1; we show that residues that lie at the interface between NPC1L1's three extracellular domains comprise the drug's binding site. These data support a model in which cholesterol passes through the cores of NPC1/NPC1L1 proteins; concerted movement of various domains is needed for transfer and ezetimibe blocks transport by binding to multiple domains simultaneously.

A novel antibody-cell conjugation method to enhance and characterize cytokine-induced killer cells.

BACKGROUND: Cytokine-induced killer (CIK) cells are an ex vivo-expanded cellular therapy product with potent anti-tumor activity in a subset of patients with solid and hematologic malignancies. We hypothesize that directing CIK cells to a specific tumor antigen will enhance CIK cell anti-tumor cytotoxicity. METHODS: We present a newly developed method for affixing antibodies directly to cell surface proteins. First, we evaluated the anti-tumor potential of CIK cells after affixing tumor-antigen targeting monoclonal antibodies. Second, we evaluated whether this antibody-conjugation method can profile the surface proteome of CIK cells. RESULTS: We demonstrated that affixing rituximab or daratumumab to CIK cells enhances cytotoxic killing of multiple lymphoma cell lines in vitro. These 'armed' CIK cells exhibited enhanced intracellular signaling after engaging tumor targets. Cell surface proteome profiling suggested mechanisms by which antibody-armed CIK cells concurrently activated multiple surface proteins, leading to enhanced cytolytic activity. Our surface proteome analysis indicated that CIK cells display enhanced protein signatures indicative of immune responses, cellular activation and leukocyte migration. CONCLUSIONS: Here, we characterize the cell surface proteome of CIK cells using a novel methodology that can be rapidly applied to other cell types. Our study also demonstrates that without genetic modification CIK cells can be rapidly armed with monoclonal antibodies, which endows them with high specificity to kill tumor targets.

Predicting HLA class II antigen presentation through integrated deep learning.

Accurate prediction of antigen presentation by human leukocyte antigen (HLA) class II molecules would be valuable for vaccine development and cancer immunotherapies. Current computational methods trained on in vitro binding data are limited by insufficient training data and algorithmic constraints. Here we describe MARIA (major histocompatibility complex analysis with recurrent integrated architecture; https://maria.stanford.edu/ ), a multimodal recurrent neural network for predicting the likelihood of antigen presentation from a gene of interest in the context of specific HLA class II alleles. In addition to in vitro binding measurements, MARIA is trained on peptide HLA ligand sequences identified by mass spectrometry, expression levels of antigen genes and protease cleavage signatures. Because it leverages these diverse training data and our improved machine learning framework, MARIA (area under the curve = 0.89-0.92) outperformed existing methods in validation datasets. Across independent cancer neoantigen studies, peptides with high MARIA scores are more likely to elicit strong CD4+ T cell responses. MARIA allows identification of immunogenic epitopes in diverse cancers and autoimmune disease.

Acute myeloid leukemia immunopeptidome reveals HLA presentation of mutated nucleophosmin.

Somatic mutations in cancer are a potential source of cancer specific neoantigens. Acute myeloid leukemia (AML) has common recurrent mutations shared between patients in addition to private mutations specific to individuals. We hypothesized that neoantigens derived from recurrent shared mutations would be attractive targets for future immunotherapeutic approaches. Here we sought to study the HLA Class I and II immunopeptidome of thirteen primary AML tumor samples and two AML cell lines (OCI-AML3 and MV4-11) using mass spectrometry to evaluate for endogenous mutation-bearing HLA ligands from common shared AML mutations. We identified two endogenous, mutation-bearing HLA Class I ligands from nucleophosmin (NPM1). The ligands, AVEEVSLRK from two patient samples and C(cys)LAVEEVSL from OCI-AML3, are predicted to bind the common HLA haplotypes, HLA-A*03:01 and HLA-A*02:01 respectively. Since NPM1 is mutated in approximately one-third of patients with AML, the finding of endogenous HLA ligands from mutated NPM1 supports future studies evaluating immunotherapeutic approaches against this shared target, for this subset of patients with AML.

TagGraph reveals vast protein modification landscapes from large tandem mass spectrometry datasets.

Although mass spectrometry is well suited to identifying thousands of potential protein post-translational modifications (PTMs), it has historically been biased towards just a few. To measure the entire set of PTMs across diverse proteomes, software must overcome the dual challenges of covering enormous search spaces and distinguishing correct from incorrect spectrum interpretations. Here, we describe TagGraph, a computational tool that overcomes both challenges with an unrestricted string-based search method that is as much as 350-fold faster than existing approaches, and a probabilistic validation model that we optimized for PTM assignments. We applied TagGraph to a published human proteomic dataset of 25 million mass spectra and tripled confident spectrum identifications compared to its original analysis. We identified thousands of modification types on almost 1 million sites in the proteome. We show alternative contexts for highly abundant yet understudied PTMs such as proline hydroxylation, and its unexpected association with cancer mutations. By enabling broad characterization of PTMs, TagGraph informs as to how their functions and regulation intersect.

Multiple Click-Selective tRNA Synthetases Expand Mammalian Cell-Specific Proteomics.

Bioorthogonal tools enable cell-type-specific proteomics, a prerequisite to understanding biological processes in multicellular organisms. Here we report two engineered aminoacyl-tRNA synthetases for mammalian bioorthogonal labeling: a tyrosyl ( ScTyrY43G) and a phenylalanyl ( MmPheT413G) tRNA synthetase that incorporate azide-bearing noncanonical amino acids specifically into the nascent proteomes of host cells. Azide-labeled proteins are chemoselectively tagged via azide-alkyne cycloadditions with fluorophores for imaging or affinity resins for mass spectrometric characterization. Both mutant synthetases label human, hamster, and mouse cell line proteins and selectively activate their azido-bearing amino acids over 10-fold above the canonical. ScTyrY43G and MmPheT413G label overlapping but distinct proteomes in human cell lines, with broader proteome coverage upon their coexpression. In mice, ScTyrY43G and MmPheT413G label the melanoma tumor proteome and plasma secretome. This work furnishes new tools for mammalian residue-specific bioorthogonal chemistry, and enables more robust and comprehensive cell-type-specific proteomics in live mammals.

T-Cell Immunopeptidomes Reveal Cell Subtype Surface Markers Derived From Intracellular Proteins.

Immunopeptidomes promise novel surface markers as ideal immunotherapy targets, but their characterization by mass spectrometry (MS) remains challenging. Until recently, cell numbers exceeding 109 were needed to survey thousands of HLA ligands. Such limited analytical sensitivity has historically constrained the types of clinical specimens that can be evaluated to cell cultures or bulk tissues. Measuring immunopeptidomes from purified cell subpopulations would be preferable for many applications, particularly those evaluating rare, primary hematopoietic cell lineages. Here, we test the feasibility of immunopeptidome profiling from limited numbers of primary purified human regulatory T cells (TReg ), conventional T cells (Tconv ), and activated T cells. The combined T cell immunopeptide dataset reported here contains 13 804 unique HLA ligands derived from 5049 proteins. Of these, more than 700 HLA ligands were derived from 82 proteins that we exclusively identified from TReg -enriched cells. This study 1) demonstrates that primary, lineage-enriched T cell subpopulations recovered from single donors are compatible with immunopeptidome analysis; 2) presents new TReg -biased ligand candidates; and 3) supports immunopeptidome surveys' value for revealing T cell biology that may not be apparent from expression data alone. Taken together, these findings open up new avenues for targeting TReg and abrogating their suppressive functions to treat cancer.

Antigen presentation profiling reveals recognition of lymphoma immunoglobulin neoantigens.

Cancer somatic mutations can generate neoantigens that distinguish malignant from normal cells. However, the personalized identification and validation of neoantigens remains a major challenge. Here we discover neoantigens in human mantle-cell lymphomas by using an integrated genomic and proteomic strategy that interrogates tumour antigen peptides presented by major histocompatibility complex (MHC) class I and class II molecules. We applied this approach to systematically characterize MHC ligands from 17 patients. Remarkably, all discovered neoantigenic peptides were exclusively derived from the lymphoma immunoglobulin heavy- or light-chain variable regions. Although we identified MHC presentation of private polymorphic germline alleles, no mutated peptides were recovered from non-immunoglobulin somatically mutated genes. Somatic mutations within the immunoglobulin variable region were almost exclusively presented by MHC class II. We isolated circulating CD4+ T cells specific for immunoglobulin-derived neoantigens and found these cells could mediate killing of autologous lymphoma cells. These results demonstrate that an integrative approach combining MHC isolation, peptide identification, and exome sequencing is an effective platform to uncover tumour neoantigens. Application of this strategy to human lymphoma implicates immunoglobulin neoantigens as targets for lymphoma immunotherapy.

AFFIRM--a multiplexed immunoaffinity platform that combines recombinant antibody fragments and LC-SRM analysis.

Targeted measurements of low abundance proteins in complex mixtures are in high demand in many areas, not the least in clinical applications measuring biomarkers. We here present the novel platform AFFIRM (AFFInity sRM) that utilizes the power of antibody fragments (scFv) to efficiently enrich for target proteins from a complex background and the exquisite specificity of SRM-MS based detection. To demonstrate the ability of AFFIRM, three target proteins of interest were measured in a serum background in single-plexed and multiplexed experiments in a concentration range of 5-1000 ng/mL. Linear responses were demonstrated down to low ng/mL concentrations with high reproducibility. The platform allows for high throughput measurements in 96-well format, and all steps are amendable to automation and scale-up. We believe the use of recombinant antibody technology in combination with SRM MS analysis provides a powerful way to reach sensitivity, specificity, and reproducibility as well as the opportunity to build resources for fast on-demand implementation of novel assays.

Molecular design of recombinant scFv antibodies for site-specific photocoupling to ß-cyclodextrin in solution and onto solid support.

The ability to design and tailor-make antibodies to meet the biophysical demands required by the vast range of current and future antibody-based applications within biotechnology and biomedicine will be essential. In this proof-of-concept study, we have for the first time tailored human recombinant scFv antibodies for site-specific photocoupling through the use of an unnatural amino acid (UAA) and the dock'n'flash technology. In more detail, we have successfully explored the possibility to expand the genetic code of E. coli and introduced the photoreactive UAA p-benzoyl-L-phenylalanine (pBpa), and showed that the mutated scFv antibody could be expressed in E. coli with retained structural and functional properties, as well as binding affinity. The pBpa group was then used for affinity capture of the mutated antibody by ß-cyclodextrin (ß-CD), which provided the hydrogen atoms to be abstracted in the subsequent photocoupling process upon irradiation at 365nm. The results showed that the pBpa mutated antibody could be site-specifically photocoupled to free and surface (array) immobilized ß-CD. Taken together, this paves the way for novel means of tailoring recombinant scFv antibodies for site-specific photochemical-based tagging, functionalization and immobilization in numerous applications.

Protein expression profiling of formalin-fixed paraffin-embedded tissue using recombinant antibody microarrays.

Proteomics, the large-scale analysis of proteins, is a rapidly evolving field with an increasing number of key clinical applications, such as diagnosis, prognosis, and classification. In order to generate complete protein expression profiles, or protein atlases, any crude sample format must be addressable in a rapid, multiplex, and sensitive manner. A common and clinically central sample format, formalin-fixed, paraffin-embedded (FFPE) tissue material, holds great potential as a source for disease-associated biomarker signatures. However, despite major efforts, extraction and subsequent profiling of proteins from FFPE tissue has proven to be challenging. In this proof-of-concept study, we have demonstrated for the first time that proteins could be extracted, labeled, and subsequently profiled in a multiplex, sensitive, and reproducible manner using recombinant scFv antibody microarrays. Thus, we have added FFPE samples to the list of sample formats available for high-throughput analysis by affinity proteomics, paving the way for the next generation of biomarker-driven discovery projects.