Development of highly multiplex targeted proteomics assays in biofluids using the Stellar mass spectrometer.

The development of targeted assays that monitor biomedically relevant proteins is an important step in bridging discovery experiments to large scale clinical studies. Targeted assays are currently unable to scale to hundreds or thousands of targets. We demonstrate the generation of large-scale assays using a novel hybrid nominal mass instrument. The scale of these assays is achievable with the Stellar™ mass spectrometer through the accommodation of shifting retention times by real-time alignment, while being sensitive and fast enough to handle many concurrent targets. Assays were constructed using precursor information from gas-phase fractionated (GPF) data-independent acquisition (DIA). We demonstrate the ability to schedule methods from an orbitrap and linear ion trap acquired GPF DIA library and compare the quantification of a matrix-matched calibration curve from orbitrap DIA and linear ion trap parallel reaction monitoring (PRM). Two applications of these proposed workflows are shown with a cerebrospinal fluid (CSF) neurodegenerative disease protein PRM assay and with a Mag-Net enriched plasma extracellular vesicle (EV) protein survey PRM assay.

A framework for quality control in quantitative proteomics.

A thorough evaluation of the quality, reproducibility, and variability of bottom-up proteomics data is necessary at every stage of a workflow from planning to analysis. We share real-world case studies applying adaptable quality control (QC) measures to assess sample preparation, system function, and quantitative analysis. System suitability samples are repeatedly measured longitudinally with targeted methods, and we share examples where they are used on three instrument platforms to identify severe system failures and track function over months to years. Internal QCs incorporated at protein and peptide-level allow our team to assess sample preparation issues and to differentiate system failures from sample-specific issues. External QC samples prepared alongside our experimental samples are used to verify the consistency and quantitative potential of our results during batch correction and normalization before assessing biological phenotypes. We combine these controls with rapid analysis using Skyline, longitudinal QC metrics using AutoQC, and server-based data deposition using PanoramaWeb. We propose that this integrated approach to QC be used as a starting point for groups to facilitate rapid quality control assessment to ensure that valuable instrument time is used to collect the best quality data possible.

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.

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.

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 extra-cellular vesicle enrichment protocol to reach new depths of coverage in the plasma proteome, quantifying over 5,000 plasma proteins in a 60-minute gradient with the Orbitrap Astral mass spectrometer.

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.

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.

A mass spectrometry-based proteomic analysis of Homer2-interacting proteins in the mouse brain.

In the brain, the Homer protein family modulates excitatory signal transduction and receptor plasticity through interactions with other proteins in dendritic spines. Homer proteins are implicated in a variety of psychiatric disorders such as schizophrenia and addiction. Since long Homers serve as scaffolding proteins, identifying their interacting partners is an important first step in understanding their biological function and could help to guide the design of new therapeutic strategies. The present study set out to document Homer2-interacting proteins in the mouse brain using a co-immunoprecipitation-based mass spectrometry approach where Homer2 knockout samples were used to filter out non-specific interactors. We found that in the mouse brain, Homer2 interacts with a limited subset of its previously reported interacting partners (3 out of 31). Importantly, we detected an additional 15 novel Homer2-interacting proteins, most of which are part of the N-methyl-D-aspartate receptor signaling pathway. These results corroborate the central role Homer2 plays in glutamatergic transmission and expand the network of proteins potentially contributing to the behavioral abnormalities associated with altered Homer2 expression. SIGNIFICANCE: Long Homer proteins are scaffolding proteins that regulate signal transduction in neurons. Identifying their interacting partners is key to understanding their function. We used co-immunoprecipitation in combination with mass spectrometry to establish the first comprehensive list of Homer2-interacting partners in the mouse brain. The specificity of interactions was evaluated using Homer2 knockout brain tissue as a negative control. The set of proteins that we identified minimally overlaps with previously reported interacting partners of Homer2; however, we identified novel interactors that are part of a signaling cascade activated by glutamatergic transmission, which improves our mechanistic understanding of the role of Homer2 in behavior.

VAMP-associated Proteins (VAP) as Receptors That Couple Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) Proteostasis with Lipid Homeostasis.

Unesterified cholesterol accumulates in late endosomes in cells expressing the misfolded cystic fibrosis transmembrane conductance regulator (CFTR). CFTR misfolding in the endoplasmic reticulum (ER) or general activation of ER stress led to dynein-mediated clustering of cholesterol-loaded late endosomes at the Golgi region, a process regulated by ER-localized VAMP-associated proteins (VAPs). We hypothesized that VAPs serve as intracellular receptors that couple lipid homeostasis through interactions with two phenylalanines in an acidic track (FFAT) binding signals (found in lipid sorting and sensing proteins, LSS) with proteostasis regulation. VAPB inhibited the degradation of ΔF508-CFTR. The activity was mapped to the ligand-binding major sperm protein (MSP) domain, which was sufficient in regulating CFTR biogenesis. We identified mutations in an unstructured loop within the MSP that uncoupled VAPB-regulated CFTR biogenesis from basic interactions with FFAT. Using this information, we defined functional and physical interactions between VAPB and proteostasis regulators (ligands), including the unfolded protein response sensor ATF6 and the ER degradation cluster that included FAF1, VCP, BAP31, and Derlin-1. VAPB inhibited the degradation of ΔF508-CFTR in the ER through interactions with the RMA1-Derlin-BAP31-VCP pathway. Analysis of pseudoligands containing tandem FFAT signals supports a competitive model for VAP interactions that direct CFTR biogenesis. The results suggest a model in which VAP-ligand binding couples proteostasis and lipid homeostasis leading to observed phenotypes of lipid abnormalities in protein folding diseases.

Maximizing peptide identification events in proteomic workflows using data-dependent acquisition (DDA).

Current analytical strategies for collecting proteomic data using data-dependent acquisition (DDA) are limited by the low analytical reproducibility of the method. Proteomic discovery efforts that exploit the benefits of DDA, such as providing peptide sequence information, but that enable improved analytical reproducibility, represent an ideal scenario for maximizing measureable peptide identifications in "shotgun"-type proteomic studies. Therefore, we propose an analytical workflow combining DDA with retention time aligned extracted ion chromatogram (XIC) areas obtained from high mass accuracy MS1 data acquired in parallel. We applied this workflow to the analyses of sample matrixes prepared from mouse blood plasma and brain tissues and observed increases in peptide detection of up to 30.5% due to the comparison of peptide MS1 XIC areas following retention time alignment of co-identified peptides. Furthermore, we show that the approach is quantitative using peptide standards diluted into a complex matrix. These data revealed that peptide MS1 XIC areas provide linear response of over three orders of magnitude down to low femtomole (fmol) levels. These findings argue that augmenting "shotgun" proteomic workflows with retention time alignment of peptide identifications and comparative analyses of corresponding peptide MS1 XIC areas improve the analytical performance of global proteomic discovery methods using DDA.

Multiplexed MS/MS for improved data-independent acquisition.

In mass spectrometry-based proteomics, data-independent acquisition (DIA) strategies can acquire a single data set useful for both identification and quantification of detectable peptides in a complex mixture. However, DIA data are noisy owing to a typical five- to tenfold reduction in precursor selectivity compared to data obtained with data-dependent acquisition or selected reaction monitoring. We demonstrate a multiplexing strategy, MSX, for DIA analysis that increases precursor selectivity fivefold.

Label-free differential analysis of murine postsynaptic densities.

This chapter provides detailed methodology for the enrichment and label-free differential analysis of postsynaptic density (PSD) proteins. Methods discussed will include tissue homogenization, subcellular fractionation, protein digestion, and label-free differential analysis after liquid chromatography-tandem mass spectrometry. When combined, these protocols facilitate the identification of receptors and signal transducers that comprise the PSD and provide an optimized workflow for the differential analysis of PSD proteomes. This strategy supports a utility for coupling fractionation with proteomics analysis to enrich for low-abundant proteins in cellular localizations that would otherwise be lost in a global tissue context.

Improved precision of proteomic measurements in immunoprecipitation based purifications using relative quantitation.

Mass spectrometry coupled immunoprecipitation (MS-IP) studies are useful in identifying and quantitating potential binding partners of a target protein. However, they are often conducted without appropriate loading controls. Western blots are often used to analyze loading controls, yet there are limitations to their usefulness as analytical tools. One remedy for this is the use of selected reaction monitoring (SRM), where the areas under the curve (AUCs) of peptides from a protein of interest can be normalized to those from the constant regions of the immunoglobulins used for the IP. Using this normalization method, significant changes in relative peptide abundance were observed between samples when there appeared to be an unequal load based on immunoglobulin peptide abundance.

Context-sensitive markov models for peptide scoring and identification from tandem mass spectrometry.

Peptide and protein identification via tandem mass spectrometry (MS/MS) lies at the heart of proteomic characterization of biological samples. Several algorithms are able to search, score, and assign peptides to large MS/MS datasets. Most popular methods, however, underutilize the intensity information available in the tandem mass spectrum due to the complex nature of the peptide fragmentation process, thus contributing to loss of potential identifications. We present a novel probabilistic scoring algorithm called Context-Sensitive Peptide Identification (CSPI) based on highly flexible Input-Output Hidden Markov Models (IO-HMM) that capture the influence of peptide physicochemical properties on their observed MS/MS spectra. We use several local and global properties of peptides and their fragment ions from literature. Comparison with two popular algorithms, Crux (re-implementation of SEQUEST) and X!Tandem, on multiple datasets of varying complexity, shows that peptide identification scores from our models are able to achieve greater discrimination between true and false peptides, identifying up to ∼25% more peptides at a False Discovery Rate (FDR) of 1%. We evaluated two alternative normalization schemes for fragment ion-intensities, a global rank-based and a local window-based. Our results indicate the importance of appropriate normalization methods for learning superior models. Further, combining our scores with Crux using a state-of-the-art procedure, Percolator, we demonstrate the utility of using scoring features from intensity-based models, identifying ∼4-8 % additional identifications over Percolator at 1% FDR. IO-HMMs offer a scalable and flexible framework with several modeling choices to learn complex patterns embedded in MS/MS data.

FIP3-endosome-dependent formation of the secondary ingression mediates ESCRT-III recruitment during cytokinesis.

The final cytokinesis event involves severing of the connecting intercellular bridge (ICB) between daughter cells. FIP3-positive recycling endosomes (FIP3 endosomes) and ESCRT complexes have been implicated in mediating the final stages of cytokinesis. Here we analyse the spatiotemporal dynamics of the actin cytoskeleton, FIP3-endosome fusion and ESCRT-III localization during cytokinesis to show that the ICB narrows by a FIP3-endosome-mediated secondary ingression, whereas the ESCRT-III complex is needed only for the last scission step of cytokinesis. We characterize the role of FIP3 endosomes during cytokinesis to demonstrate that FIP3 endosomes deliver SCAMP2/3 and p50RhoGAP to the ICB during late telophase, proteins required for the formation of the secondary ingression. We also show that the FIP3-endosome-induced secondary ingression is required for the recruitment of the ESCRT-III complex to the abscission site. Finally, we characterize a FIP3-endosome-dependent regulation of the ICB cortical actin network through the delivery of p50RhoGAP. These results provide a framework for the coordinated efforts of actin, FIP3 endosomes and the ESCRTs to regulate cytokinesis and abscission.

Proteomic characterization of integral membrane proteins using thermostatted liquid chromatography coupled with tandem mass spectrometry.

Due to the hydrophobicity and localization of integral membrane proteins, they are difficult to study using conventional biochemical methods that are compatible with proteomic analyses. This chapter describes the coupling of multiple crucial steps that lead to the optimized shotgun proteomic analysis of integral membrane proteins while maintaining empirical topology information. Namely, a membrane shaving method is utilized to separate protease accessible peptides from membrane embedded peptides and elevated temperatures during chromatographic separation is utilized to augment the recovery of hydrophobic peptides for in-line analysis using tandem mass spectrometry. This combination of steps facilitates increased identification of membrane proteins while also maintaining information regarding protein topology.

Platform-independent and label-free quantitation of proteomic data using MS1 extracted ion chromatograms in skyline: application to protein acetylation and phosphorylation.

Despite advances in metabolic and postmetabolic labeling methods for quantitative proteomics, there remains a need for improved label-free approaches. This need is particularly pressing for workflows that incorporate affinity enrichment at the peptide level, where isobaric chemical labels such as isobaric tags for relative and absolute quantitation and tandem mass tags may prove problematic or where stable isotope labeling with amino acids in cell culture labeling cannot be readily applied. Skyline is a freely available, open source software tool for quantitative data processing and proteomic analysis. We expanded the capabilities of Skyline to process ion intensity chromatograms of peptide analytes from full scan mass spectral data (MS1) acquired during HPLC MS/MS proteomic experiments. Moreover, unlike existing programs, Skyline MS1 filtering can be used with mass spectrometers from four major vendors, which allows results to be compared directly across laboratories. The new quantitative and graphical tools now available in Skyline specifically support interrogation of multiple acquisitions for MS1 filtering, including visual inspection of peak picking and both automated and manual integration, key features often lacking in existing software. In addition, Skyline MS1 filtering displays retention time indicators from underlying MS/MS data contained within the spectral library to ensure proper peak selection. The modular structure of Skyline also provides well defined, customizable data reports and thus allows users to directly connect to existing statistical programs for post hoc data analysis. To demonstrate the utility of the MS1 filtering approach, we have carried out experiments on several MS platforms and have specifically examined the performance of this method to quantify two important post-translational modifications: acetylation and phosphorylation, in peptide-centric affinity workflows of increasing complexity using mouse and human models.

Identification of ejaculated proteins in the house mouse (Mus domesticus) via isotopic labeling.

BACKGROUND: Seminal fluid plays an important role in successful fertilization, but knowledge of the full suite of proteins transferred from males to females during copulation is incomplete. The list of ejaculated proteins remains particularly scant in one of the best-studied mammalian systems, the house mouse (Mus domesticus), where artificial ejaculation techniques have proven inadequate. Here we investigate an alternative method for identifying ejaculated proteins, by isotopically labeling females with 15N and then mating them to unlabeled, vasectomized males. Proteins were then isolated from mated females and identified using mass spectrometry. In addition to gaining insights into possible functions and fates of ejaculated proteins, our study serves as proof of concept that isotopic labeling is a powerful means to study reproductive proteins. RESULTS: We identified 69 male-derived proteins from the female reproductive tract following copulation. More than a third of all spectra detected mapped to just seven genes known to be structurally important in the formation of the copulatory plug, a hard coagulum that forms shortly after mating. Seminal fluid is significantly enriched for proteins that function in protection from oxidative stress and endopeptidase inhibition. Females, on the other hand, produce endopeptidases in response to mating. The 69 ejaculated proteins evolve significantly more rapidly than other proteins that we previously identified directly from dissection of the male reproductive tract. CONCLUSION: Our study attempts to comprehensively identify the proteins transferred from males to females during mating, expanding the application of isotopic labeling to mammalian reproductive genomics. This technique opens the way to the targeted monitoring of the fate of ejaculated proteins as they incubate in the female reproductive tract.