Mag-Net: Rapid enrichment of membrane-bound particles enables high coverage quantitative analysis of the plasma proteome.

Membrane-bound particles in plasma are composed of exosomes, microvesicles, and apoptotic bodies and represent ~1-2% of the total protein composition. Proteomic interrogation of this subset of plasma proteins augments the representation of tissue-specific proteins, representing a "liquid biopsy," while enabling the detection of proteins that would otherwise be beyond the dynamic range of liquid chromatography-tandem mass spectrometry of unfractionated plasma. We have developed an enrichment strategy (Mag-Net) using hyper-porous strong-anion exchange magnetic microparticles to sieve membrane-bound particles from plasma. The Mag-Net method is robust, reproducible, inexpensive, and requires <100 µL plasma input. Coupled to a quantitative data-independent mass spectrometry analytical strategy, we demonstrate that we can collect results for >37,000 peptides from >4,000 plasma proteins with high precision. Using this analytical pipeline on a small cohort of patients with neurodegenerative disease and healthy age-matched controls, we discovered 204 proteins that differentiate (q-value < 0.05) patients with Alzheimer's disease dementia (ADD) from those without ADD. Our method also discovered 310 proteins that were different between Parkinson's disease and those with either ADD or healthy cognitively normal individuals. Using machine learning we were able to distinguish between ADD and not ADD with a mean ROC AUC = 0.98 ± 0.06.

MBNL1 Regulates Programmed Postnatal Switching Between Regenerative and Differentiated Cardiac States.

BACKGROUND: Discovering determinants of cardiomyocyte maturity is critical for deeply understanding the maintenance of differentiated states and potentially reawakening endogenous regenerative programs in adult mammalian hearts as a therapeutic strategy. Forced dedifferentiation paired with oncogene expression is sufficient to drive cardiac regeneration, but elucidation of endogenous developmental regulators of the switch between regenerative and mature cardiomyocyte cell states is necessary for optimal design of regenerative approaches for heart disease. MBNL1 (muscleblind-like 1) regulates fibroblast, thymocyte, and erythroid differentiation and proliferation. Hence, we examined whether MBNL1 promotes and maintains mature cardiomyocyte states while antagonizing cardiomyocyte proliferation. METHODS: MBNL1 gain- and loss-of-function mouse models were studied at several developmental time points and in surgical models of heart regeneration. Multi-omics approaches were combined with biochemical, histological, and in vitro assays to determine the mechanisms through which MBNL1 exerts its effects. RESULTS: MBNL1 is coexpressed with a maturation-association genetic program in the heart and is regulated by the MEIS1/calcineurin signaling axis. Targeted MBNL1 overexpression early in development prematurely transitioned cardiomyocytes to hypertrophic growth, hypoplasia, and dysfunction, whereas loss of MBNL1 function increased cardiomyocyte cell cycle entry and proliferation through altered cell cycle inhibitor transcript stability. Moreover, MBNL1-dependent stabilization of estrogen-related receptor signaling was essential for maintaining cardiomyocyte maturity in adult myocytes. In accordance with these data, modulating MBNL1 dose tuned the temporal window of neonatal cardiac regeneration, where increased MBNL1 expression arrested myocyte proliferation and regeneration and MBNL1 deletion promoted regenerative states with prolonged myocyte proliferation. However, MBNL1 deficiency was insufficient to promote regeneration in the adult heart because of cell cycle checkpoint activation. CONCLUSIONS: Here, MBNL1 was identified as an essential regulator of cardiomyocyte differentiated states, their developmental switch from hyperplastic to hypertrophic growth, and their regenerative potential through controlling an entire maturation program by stabilizing adult myocyte mRNAs during postnatal development and throughout adulthood. Targeting loss of cardiomyocyte maturity and downregulation of cell cycle inhibitors through MBNL1 deletion was not sufficient to promote adult regeneration.

De novo design of high-affinity binders of bioactive helical peptides.

Many peptide hormones form an α-helix on binding their receptors1-4, and sensitive methods for their detection could contribute to better clinical management of disease5. De novo protein design can now generate binders with high affinity and specificity to structured proteins6,7. However, the design of interactions between proteins and short peptides with helical propensity is an unmet challenge. Here we describe parametric generation and deep learning-based methods for designing proteins to address this challenge. We show that by extending RFdiffusion8 to enable binder design to flexible targets, and to refining input structure models by successive noising and denoising (partial diffusion), picomolar-affinity binders can be generated to helical peptide targets by either refining designs generated with other methods, or completely de novo starting from random noise distributions without any subsequent experimental optimization. The RFdiffusion designs enable the enrichment and subsequent detection of parathyroid hormone and glucagon by mass spectrometry, and the construction of bioluminescence-based protein biosensors. The ability to design binders to conformationally variable targets, and to optimize by partial diffusion both natural and designed proteins, should be broadly useful.

Evaluating the Performance of the Astral Mass Analyzer for Quantitative Proteomics Using Data-Independent Acquisition.

We evaluate the quantitative performance of the newly released Asymmetric Track Lossless (Astral) analyzer. Using data-independent acquisition, the Thermo Scientific Orbitrap Astral mass spectrometer quantifies 5 times more peptides per unit time than state-of-the-art Thermo Scientific Orbitrap mass spectrometers, which have long been the gold standard for high-resolution quantitative proteomics. Our results demonstrate that the Orbitrap Astral mass spectrometer can produce high-quality quantitative measurements across a wide dynamic range. We also use a newly developed extracellular vesicle enrichment protocol to reach new depths of coverage in the plasma proteome, quantifying over 5000 plasma proteins in a 60 min gradient with the Orbitrap Astral mass spectrometer.

Dynamic Data-Independent Acquisition Mass Spectrometry with Real-Time Retrospective Alignment.

Data-independent acquisition (DIA) mass spectrometry has grown in popularity in recent years, because of the reproducibility and quantitative rigor of a systematic tandem mass spectrometry (MS/MS) sampling method. However, traditional DIA methods may spend valuable instrument time acquiring MS/MS spectra with no usable information in them, affecting sensitivity and quantitative performance. We developed a DIA strategy that dynamically adjusts the MS/MS windows during the chromatographic separation. The method focuses MS/MS acquisition on the most relevant mass range at each point in time─increasing the quantitative sensitivity by increasing the time spent on each DIA window. We demonstrate an improved lower limit of quantification, on average, without sacrificing the number of peptides detected.

Proteogenomic data and resources for pan-cancer analysis.

The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) investigates tumors from a proteogenomic perspective, creating rich multi-omics datasets connecting genomic aberrations to cancer phenotypes. To facilitate pan-cancer investigations, we have generated harmonized genomic, transcriptomic, proteomic, and clinical data for >1000 tumors in 10 cohorts to create a cohesive and powerful dataset for scientific discovery. We outline efforts by the CPTAC pan-cancer working group in data harmonization, data dissemination, and computational resources for aiding biological discoveries. We also discuss challenges for multi-omics data integration and analysis, specifically the unique challenges of working with both nucleotide sequencing and mass spectrometry proteomics data.

The mitochondrially targeted peptide elamipretide (SS-31) improves ADP sensitivity in aged mitochondria by increasing uptake through the adenine nucleotide translocator (ANT).

Aging muscle experiences functional decline in part mediated by impaired mitochondrial ADP sensitivity. Elamipretide (ELAM) rapidly improves physiological and mitochondrial function in aging and binds directly to the mitochondrial ADP transporter ANT. We hypothesized that ELAM improves ADP sensitivity in aging leading to rescued physiological function. We measured the response to ADP stimulation in young and old muscle mitochondria with ELAM treatment, in vivo heart and muscle function, and compared protein abundance, phosphorylation, and S-glutathionylation of ADP/ATP pathway proteins. ELAM treatment increased ADP sensitivity in old muscle mitochondria by increasing uptake of ADP through the ANT and rescued muscle force and heart systolic function. Protein abundance in the ADP/ATP transport and synthesis pathway was unchanged, but ELAM treatment decreased protein s-glutathionylation incuding of ANT. Mitochondrial ADP sensitivity is rapidly modifiable. This research supports the hypothesis that ELAM improves ANT function in aging and links mitochondrial ADP sensitivity to physiological function. ELAM binds directly to ANT and ATP synthase and ELAM treatment improves ADP sensitivity, increases ATP production, and improves physiological function in old muscles. ADP (adenosine diphosphate), ATP (adenosine triphosphate), VDAC (voltage-dependent anion channel), ANT (adenine nucleotide translocator), H+ (proton), ROS (reactive oxygen species), NADH (nicotinamide adenine dinucleotide), FADH2 (flavin adenine dinucleotide), O2 (oxygen), ELAM (elamipretide), -SH (free thiol), -SSG (glutathionylated protein).

A peptide-centric quantitative proteomics dataset for the phenotypic assessment of Alzheimer's disease.

Alzheimer's disease (AD) is a looming public health disaster with limited interventions. Alzheimer's is a complex disease that can present with or without causative mutations and can be accompanied by a range of age-related comorbidities. This diverse presentation makes it difficult to study molecular changes specific to AD. To better understand the molecular signatures of disease we constructed a unique human brain sample cohort inclusive of autosomal dominant AD dementia (ADD), sporadic ADD, and those without dementia but with high AD histopathologic burden, and cognitively normal individuals with no/minimal AD histopathologic burden. All samples are clinically well characterized, and brain tissue was preserved postmortem by rapid autopsy. Samples from four brain regions were processed and analyzed by data-independent acquisition LC-MS/MS. Here we present a high-quality quantitative dataset at the peptide and protein level for each brain region. Multiple internal and external control strategies were included in this experiment to ensure data quality. All data are deposited in the ProteomeXchange repositories and available from each step of our processing.

MBNL1 regulates programmed postnatal switching between regenerative and differentiated cardiac states.

Discovering determinants of cardiomyocyte maturity and the maintenance of differentiated states is critical to both understanding development and potentially reawakening endogenous regenerative programs in adult mammalian hearts as a therapeutic strategy. Here, the RNA binding protein Muscleblind-like 1 (MBNL1) was identified as a critical regulator of cardiomyocyte differentiated states and their regenerative potential through transcriptome-wide control of RNA stability. Targeted MBNL1 overexpression early in development prematurely transitioned cardiomyocytes to hypertrophic growth, hypoplasia, and dysfunction, whereas loss of MBNL1 function increased cardiomyocyte cell cycle entry and proliferation through altered cell cycle inhibitor transcript stability. Moreover, MBNL1-dependent stabilization of the estrogen-related receptor signaling axis was essential for maintaining cardiomyocyte maturity. In accordance with these data, modulating MBNL1 dose tuned the temporal window of cardiac regeneration, where enhanced MBNL1 activity arrested myocyte proliferation, and MBNL1 deletion promoted regenerative states with prolonged myocyte proliferation. Collectively these data suggest MBNL1 acts as a transcriptome-wide switch between regenerative and mature myocyte states postnatally and throughout adulthood.

Improved Analysis of Cross-Linking Mass Spectrometry Data with Kojak 2.0, Advanced by Integration into the Trans-Proteomic Pipeline.

Fragmentation ion spectral analysis of chemically cross-linked proteins is an established technology in the proteomics research repertoire for determining protein interactions, spatial orientation, and structure. Here we present Kojak version 2.0, a major update to the original Kojak algorithm, which was developed to identify cross-linked peptides from fragment ion spectra using a database search approach. A substantially improved algorithm with updated scoring metrics, support for cleavable cross-linkers, and identification of cross-links between 15N-labeled homomultimers are among the newest features of Kojak 2.0 presented here. Kojak 2.0 is now integrated into the Trans-Proteomic Pipeline, enabling access to dozens of additional tools within that suite. In particular, the PeptideProphet and iProphet tools for validation of cross-links improve the sensitivity and accuracy of correct cross-link identifications at user-defined thresholds. These new features improve the versatility of the algorithm, enabling its use in a wider range of experimental designs and analysis pipelines. Kojak 2.0 remains open-source and multiplatform.

A Targeted Liquid Chromatography-Tandem Mass Spectrometry Method for Simultaneous Quantification of Peptides from the Carboxyl-terminal Region of Type III Procollagen, Biomarkers of Collagen Turnover.

BACKGROUND: The development of analytical approaches to help reduce the risk of growth hormone (GH) doping is important to fair competition and the health of athletes. However, the reliable detection of GH use remains challenging. The identification of novel biomarkers of GH administration could lead to a better understanding of the physiological response to GH, more sensitive detection of the illicit use of GH in sport, and better management of patients treated for GH disorders. METHODS: We developed a targeted liquid chromatography-tandem mass spectrometry method to simultaneously quantify the carboxyl-terminal propeptide of type III procollagen (P-III-CP) and type III collagen degradation products in human serum. Following proteolysis, we instituted a simple acid precipitation step to reduce digested sample complexity before peptide immunoenrichment, which improved the recovery of one target peptide from serum. We evaluated the concentration of each biomarker at different age ranges and after GH administration in healthy participants. RESULTS: The assay was linear over an estimated concentration range of 0.3 to1.0 nM and 0.1 to 0.4 nM for each surrogate peptide of P-III-CP and collagen fragments, respectively. Intra-day and inter-day coefficients of variation were ≤15%. Biomarker concentrations appeared to vary with age and to reflect age-specific collagen turnover. Moreover, their concentrations changed after GH administration. CONCLUSIONS: Our method quantifies the proteins belonging to the family of P-III-CP and type III collagen degradation products in human serum, which could be used to detect GH administration in athletes and better understand diseases involving GH therapy or altered type III collagen turnover.

Tandem Mass Spectrometry-Based Amyloid Typing Using Manual Microdissection and Open-Source Data Processing.

OBJECTIVES: Standard implementations of amyloid typing by liquid chromatography-tandem mass spectrometry use capabilities unavailable to most clinical laboratories. To improve accessibility of this testing, we explored easier approaches to tissue sampling and data processing. METHODS: We validated a typing method using manual sampling in place of laser microdissection, pairing the technique with a semiquantitative measure of sampling adequacy. In addition, we created an open-source data processing workflow (Crux Pipeline) for clinical users. RESULTS: Cases of amyloidosis spanning the major types were distinguishable with 100% specificity using measurements of individual amyloidogenic proteins or in combination with the ratio of λ and κ constant regions. Crux Pipeline allowed for rapid, batched data processing, integrating the steps of peptide identification, statistical confidence estimation, and label-free protein quantification. CONCLUSIONS: Accurate mass spectrometry-based amyloid typing is possible without laser microdissection. To facilitate entry into solid tissue proteomics, newcomers can leverage manual sampling approaches in combination with Crux Pipeline and related tools.

Building Spectral Libraries from Narrow-Window Data-Independent Acquisition Mass Spectrometry Data.

Advances in library-based methods for peptide detection from data-independent acquisition (DIA) mass spectrometry have made it possible to detect and quantify tens of thousands of peptides in a single mass spectrometry run. However, many of these methods rely on a comprehensive, high-quality spectral library containing information about the expected retention time and fragmentation patterns of peptides in the sample. Empirical spectral libraries are often generated through data-dependent acquisition and may suffer from biases as a result. Spectral libraries can be generated in silico, but these models are not trained to handle all possible post-translational modifications. Here, we propose a false discovery rate-controlled spectrum-centric search workflow to generate spectral libraries directly from gas-phase fractionated DIA tandem mass spectrometry data. We demonstrate that this strategy is able to detect phosphorylated peptides and can be used to generate a spectral library for accurate peptide detection and quantitation in wide-window DIA data. We compare the results of this search workflow to other library-free approaches and demonstrate that our search is competitive in terms of accuracy and sensitivity. These results demonstrate that the proposed workflow has the capacity to generate spectral libraries while avoiding the limitations of other methods.

Mitochondrial Inorganic Polyphosphate (polyP) Is a Potent Regulator of Mammalian Bioenergetics in SH-SY5Y Cells: A Proteomics and Metabolomics Study.

Inorganic polyphosphate (polyP) is an ancient, ubiquitous, and well-conserved polymer which is present in all the studied organisms. It is formed by individual subunits of orthophosphate which are linked by structurally similar bonds and isoenergetic to those found in ATP. While the metabolism and the physiological roles of polyP have already been described in some organisms, including bacteria and yeast, the exact role of this polymer in mammalian physiology still remains poorly understood. In these organisms, polyP shows a co-localization with mitochondria, and its role as a key regulator of the stress responses, including the maintenance of appropriate bioenergetics, has already been demonstrated by our group and others. Here, using Wild-type (Wt) and MitoPPX (cells enzymatically depleted of mitochondrial polyP) SH-SY5Y cells, we have conducted a comprehensive study of the status of cellular physiology, using proteomics and metabolomics approaches. Our results suggest a clear dysregulation of mitochondrial physiology, especially of bioenergetics, in MitoPPX cells when compared with Wt cells. Moreover, the effects induced by the enzymatic depletion of polyP are similar to those present in the mitochondrial dysfunction that is observed in neurodegenerative disorders and in neuronal aging. Based on our findings, the metabolism of mitochondrial polyP could be a valid and innovative pharmacological target in these conditions.

Putting Humpty Dumpty Back Together Again: What Does Protein Quantification Mean in Bottom-Up Proteomics?

Bottom-up proteomics provides peptide measurements and has been invaluable for moving proteomics into large-scale analyses. Commonly, a single quantitative value is reported for each protein-coding gene by aggregating peptide quantities into protein groups following protein inference or parsimony. However, given the complexity of both RNA splicing and post-translational protein modification, it is overly simplistic to assume that all peptides that map to a singular protein-coding gene will demonstrate the same quantitative response. By assuming that all peptides from a protein-coding sequence are representative of the same protein, we may miss the discovery of important biological differences. To capture the contributions of existing proteoforms, we need to reconsider the practice of aggregating protein values to a single quantity per protein-coding gene.

Prebiotic Membranes and Micelles Do Not Inhibit Peptide Formation During Dehydration.

Cycles of dehydration and rehydration could have enabled formation of peptides and RNA in otherwise unfavorable conditions on the early Earth. Development of the first protocells would have hinged upon colocalization of these biopolymers with fatty acid membranes. Using atomic force microscopy, we find that a prebiotic fatty acid (decanoic acid) forms stacks of membranes after dehydration. Using LC-MS-MS (liquid chromatography-tandem mass spectrometry) with isotope internal standards, we measure the rate of formation of serine dipeptides. We find that dipeptides form during dehydration at moderate temperatures (55 °C) at least as fast in the presence of decanoic acid membranes as in the absence of membranes. Our results are consistent with the hypothesis that protocells could have formed within evaporating environments on the early Earth.

Mass spectrometric identification of immunogenic SARS-CoV-2 epitopes and cognate TCRs.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections elicit both humoral and cellular immune responses. For the prevention and treatment of COVID-19, the disease caused by SARS-CoV-2, it has become increasingly apparent that T cell responses are equally if not more important than humoral responses in mediating recovery and immune protection. One major challenge in developing T cell-based therapies for infectious and malignant diseases has been the identification of immunogenic epitopes that can elicit a meaningful T cell response. Traditionally, this has been achieved using sophisticated in silico methods to predict putative epitopes deduced from binding affinities. Our studies find that, in contrast to current convention, "immunodominant" SARS-CoV-2 peptides defined by such in silico methods often fail to elicit T cell responses recognizing naturally presented SARS-CoV-2 epitopes. We postulated that immunogenic epitopes for SARS-CoV-2 are best defined empirically by directly analyzing peptides eluted from the naturally processed peptide-major histocompatibility complex (MHC) and then validating immunogenicity by determining whether such peptides can elicit T cells recognizing SARS-CoV-2 antigen-expressing cells. Using a tandem mass spectrometry approach, we identified epitopes derived from not only structural but also nonstructural genes in regions highly conserved among SARS-CoV-2 strains, including recently recognized variants. Finally, there are no reported T cell receptor-engineered T cell technology that can redirect T cell specificity to recognize and kill SARS-CoV-2 target cells. We report here several SARS-CoV-2 epitopes defined by mass spectrometric analysis of MHC-eluted peptides, provide empiric evidence for their immunogenicity, and demonstrate engineered TCR-redirected killing.

Elamipretide (SS-31) treatment attenuates age-associated post-translational modifications of heart proteins.

It has been demonstrated that elamipretide (SS-31) rescues age-related functional deficits in the heart but the full set of mechanisms behind this have yet to be determined. We investigated the hypothesis that elamipretide influences post-translational modifications to heart proteins. The S-glutathionylation and phosphorylation proteomes of mouse hearts were analyzed using shotgun proteomics to assess the effects of aging on these post-translational modifications and the ability of the mitochondria-targeted drug elamipretide to reverse age-related changes. Aging led to an increase in oxidation of protein thiols demonstrated by increased S-glutathionylation of cysteine residues on proteins from Old (24 months old at the start of the study) mouse hearts compared to Young (5-6 months old). This shift in the oxidation state of the proteome was almost completely reversed by 8 weeks of treatment with elamipretide. Many of the significant changes that occurred were in proteins involved in mitochondrial or cardiac function. We also found changes in the mouse heart phosphoproteome that were associated with age, some of which were partially restored with elamipretide treatment. Parallel reaction monitoring of a subset of phosphorylation sites revealed that the unmodified peptide reporting for Myot S231 increased with age, but not its phosphorylated form and that both phosphorylated and unphosphorylated forms of the peptide covering cMyBP-C S307 increased, but that elamipretide treatment did not affect these changes. These results suggest that changes to thiol redox state and phosphorylation status are two ways in which age may affect mouse heart function, which can be restored by treatment with elamipretide.

De novo design of tyrosine and serine kinase-driven protein switches.

Kinases play central roles in signaling cascades, relaying information from the outside to the inside of mammalian cells. De novo designed protein switches capable of interfacing with tyrosine kinase signaling pathways would open new avenues for controlling cellular behavior, but, so far, no such systems have been described. Here we describe the de novo design of two classes of protein switch that link phosphorylation by tyrosine and serine kinases to protein-protein association. In the first class, protein-protein association is required for phosphorylation by the kinase, while in the second class, kinase activity drives protein-protein association. We design systems that couple protein binding to kinase activity on the immunoreceptor tyrosine-based activation motif central to T-cell signaling, and kinase activity to reconstitution of green fluorescent protein fluorescence from fragments and the inhibition of the protease calpain. The designed switches are reversible and function in vitro and in cells with up to 40-fold activation of switching by phosphorylation.

Proteomic profiling dataset of chemical perturbations in multiple biological backgrounds.

While gene expression profiling has traditionally been the method of choice for large-scale perturbational profiling studies, proteomics has emerged as an effective tool in this context for directly monitoring cellular responses to perturbations. We previously reported a pilot library containing 3400 profiles of multiple perturbations across diverse cellular backgrounds in the reduced-representation phosphoproteome (P100) and chromatin space (Global Chromatin Profiling, GCP). Here, we expand our original dataset to include profiles from a new set of cardiotoxic compounds and from astrocytes, an additional neural cell model, totaling 5300 proteomic signatures. We describe filtering criteria and quality control metrics used to assess and validate the technical quality and reproducibility of our data. To demonstrate the power of the library, we present two case studies where data is queried using the concept of "connectivity" to obtain biological insight. All data presented in this study have been deposited to the ProteomeXchange Consortium with identifiers PXD017458 (P100) and PXD017459 (GCP) and can be queried at https://clue.io/proteomics .