TomahaqCompanion: A Tool for the Creation and Analysis of Isobaric Label Based Multiplexed Targeted Assays

Exploring the dynamic landscape of immunopeptidomics: Unravelling posttranslational modifications and navigating bioinformatics terrain

Immunopeptidomics is becoming an increasingly important field of study. The capability to identify immunopeptides with pivotal roles in the human immune system is essential to shift the current curative medicine towards personalized medicine. Throughout the years, the field has matured, giving insight into the current pitfalls. Nowadays, it is commonly accepted that generalizing shotgun proteomics workflows is malpractice because immunopeptidomics faces numerous challenges. While many of these difficulties have been addressed, the road towards the ideal workflow remains complicated. Although the presence of Posttranslational modifications (PTMs) in the immunopeptidome has been demonstrated, their identification remains highly challenging despite their significance for immunotherapies. The large number of unpredictable modifications in the immunopeptidome plays a pivotal role in the functionality and these challenges. This review provides a comprehensive overview of the current advancements in immunopeptidomics. We delve into the challenges associated with identifying PTMs within the immunopeptidome, aiming to address the current state of the field.

Real-Time Spectral Library Matching for Sample Multiplexed Quantitative Proteomics

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

Proteomics in the pharmaceutical and biotechnology industry: a look to the next decade

INTRODUCTION

Pioneering technologies such as proteomics have helped fuel the biotechnology and pharmaceutical industry with the discovery of novel targets and an intricate understanding of the activity of therapeutics and their various activities in vitro and in vivo. The field of proteomics is undergoing an inflection point, where new sensitive technologies are allowing intricate biological pathways to be better understood, and novel biochemical tools are pivoting us into a new era of chemical proteomics and biomarker discovery. In this review, we describe these areas of innovation, and discuss where the fields are headed in terms of fueling biotechnological and pharmacological research and discuss current gaps in the proteomic technology landscape.

AREAS COVERED

Single cell sequencing and single molecule sequencing. Chemoproteomics. Biological matrices and clinical samples including biomarkers. Computational tools including instrument control software, data analysis.

EXPERT OPINION

Proteomics will likely remain a key technology in the coming decade, but will have to evolve with respect to type and granularity of data, cost and throughput of data generation as well as integration with other technologies to fulfill its promise in drug discovery.

Sensitive and Quantitative Detection of MHC-I Displayed Neoepitopes Using a Semiautomated Workflow and TOMAHAQ Mass Spectrometry

Advances in several key technologies, including MHC peptidomics, have helped fuel our understanding of basic immune regulatory mechanisms and the identification of T cell receptor targets for the development of immunotherapeutics. Isolating and accurately quantifying MHC-bound peptides from cells and tissues enables characterization of dynamic changes in the ligandome due to cellular perturbations. However, the current multistep analytical process is challenging, and improvements in throughput and reproducibility would enable rapid characterization of multiple conditions in parallel. Here, we describe a robust and quantitative method whereby peptides derived from MHC-I complexes from a variety of cell lines, including challenging adherent lines such as MC38, can be enriched in a semiautomated fashion on reusable, dry-storage, customized antibody cartridges. Using this method, a researcher, with very little hands-on time and in a single day, can perform up to 96 simultaneous enrichments at a similar level of quality as a manual workflow. TOMAHAQ (Triggered by Offset, Multiplexed, Accurate-mass, High-resolution, and Absolute Quantification), a targeted mass spectrometry technique that combines sample multiplexing and high sensitivity, was employed to characterize neoepitopes displayed on MHC-I by tumor cells and to quantitatively assess the influence of neoantigen expression and induced degradation on neoepitope presentation. This unique combination of robust semiautomated MHC-I peptide isolation and high-throughput multiplexed targeted quantitation allows for both the routine analysis of >4000 unique MHC-I peptides from 250 million cells using nontargeted methods, as well as quantitative sensitivity down to the low amol/μl level using TOMAHAQ targeted MS.

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Semiautomated peptide immunoprecipitation on reusable antibody cartridges.

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Application of TOMAHAQ for MHC-I detection and quantitation.

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Routine analysis of >4000 unique MHC-I peptides from 250 million cells via automation.

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Quantitative sensitivity down to the low amol/μl level using TOMAHAQ targeted MS.

Defining the carrier proteome limit for single-cell proteomics

Single-cell proteomics by mass spectrometry (SCoPE-MS) is a recently introduced method to quantify multiplexed single-cell proteomes. While this technique has generated great excitement, the underlying technologies (isobaric labeling and mass spectrometry (MS)) have technical limitations with the potential to affect data quality and biological interpretation. These limitations are particularly relevant when a carrier proteome, a sample added at 25-500× the amount of a single-cell proteome, is used to enable peptide identifications. Here we perform controlled experiments with increasing carrier proteome amounts and evaluate quantitative accuracy, as it relates to mass analyzer dynamic range, multiplexing level and number of ions sampled. We demonstrate that an increase in carrier proteome level requires a concomitant increase in the number of ions sampled to maintain quantitative accuracy. Lastly, we introduce Single-Cell Proteomics Companion (SCPCompanion), a software tool that enables rapid evaluation of single-cell proteomic data and recommends instrument and data analysis parameters for improved data quality.

Global quantitative analysis of the human brain proteome and phosphoproteome in Alzheimer's disease

Alzheimer's disease (AD) is characterized by an early, asymptomatic phase (AsymAD) in which individuals exhibit amyloid-beta (Aβ) plaque accumulation in the absence of clinically detectable cognitive decline. Here we report an unbiased multiplex quantitative proteomic and phosphoproteomic analysis using tandem mass tag (TMT) isobaric labeling of human post-mortem cortex (n = 27) across pathology-free controls, AsymAD and symptomatic AD individuals. With off-line high-pH fractionation and liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) on an Orbitrap Lumos mass spectrometer, we identified 11,378 protein groups across three TMT 11-plex batches. Immobilized metal affinity chromatography (IMAC) was used to enrich for phosphopeptides from the same TMT-labeled cases and 51,736 phosphopeptides were identified. Of these, 48,992 were quantified by TMT reporter ions representing 33,652 unique phosphosites. Two reference standards in each TMT 11-plex were included to assess intra- and inter-batch variance at the protein and peptide level. This comprehensive human brain proteome and phosphoproteome dataset will serve as a valuable resource for the identification of biochemical, cellular and signaling pathways altered during AD progression.

Sample multiplexing for targeted pathway proteomics in aging mice

Pathway proteomics strategies measure protein expression changes in specific cellular processes that carry out related functions. Using targeted tandem mass tags-based sample multiplexing, hundreds of proteins can be quantified across 10 or more samples simultaneously. To facilitate these highly complex experiments, we introduce a strategy that provides complete control over targeted sample multiplexing experiments, termed Tomahto, and present its implementation on the Orbitrap Tribrid mass spectrometer platform. Importantly, this software monitors via the external desktop computer to the data stream and inserts optimized MS2 and MS3 scans in real time based on an application programming interface with the mass spectrometer. Hundreds of proteins of interest from diverse biological samples can be targeted and accurately quantified in a sensitive and high-throughput fashion. It achieves sensitivity comparable to, if not better than, deep fractionation and requires minimal total sample input (∼10 µg). As a proof-of-principle experiment, we selected four pathways important in metabolism- and inflammation-related processes (260 proteins/520 peptides) and measured their abundance across 90 samples (nine tissues from five old and five young mice) to explore effects of aging. Tissue-specific aging is presented here and we highlight the role of inflammation- and metabolism-related processes in white adipose tissue. We validated our approach through comparison with a global proteome survey across the tissues, work that we also provide as a general resource for the community.

Enhancing Data Reliability in TOMAHAQ for Large-Scale Protein Quantification

The analytical scale of most mass-spectrometry-based targeted proteomics assays is usually limited by assay performance and instrument utilization. A recently introduced method, called triggered by offset, multiplexed, accurate mass, high resolution, and absolute quantitation (TOMAHAQ), combines both peptide and sample multiplexing to simultaneously improve analytical scale and quantitative performance. In the present work, critical technical requirements and data analysis considerations for successful implementation of the TOMAHAQ technique based on the study of a total of 185 target peptides across over 200 clinical plasma samples are discussed. Importantly, it is observed that significant interference originate from the TMTzero reporter ion used for the synthetic trigger peptides. This interference is not expected because only TMT10plex reporter ions from the target peptides should be observed under typical TOMAHAQ conditions. In order to unlock the great promise of the technique for high throughput quantification, here a post-acquisition data correction strategy to deconvolute the reporter ion superposition and recover reliable data is proposed.

Deep undepleted human serum proteome profiling toward biomarker discovery for Alzheimer's disease

Background

Blood-based protein measurement is a routine practice for detecting biomarkers in human disease. Comprehensive profiling of blood/plasma/serum proteome is a challenge due to an extremely large dynamic range, as exemplified by a small subset of highly abundant proteins. Antibody-based depletion of these abundant proteins alleviates the problem but introduces experimental variations. We aimed to establish a method for direct profiling of undepleted human serum and apply the method toward biomarker discovery for Alzheimer's disease (AD), as AD is the most common form of dementia without available blood-based biomarkers in clinic.

Methods

We present an ultra-deep analysis of undepleted human serum proteome by combining the latest 11-plex tandem-mass-tag (TMT) labeling, exhaustive two-dimensional liquid chromatography (LC/LC) fractionation (the 1st LC: 3 h for 180 fractions, and the 2nd LC: 3 h gradient per fraction), coupled with high resolution tandem mass spectrometry (MS/MS). AD (n = 6) and control (n = 5) sera were analyzed in this pilot study. In addition, we implemented a multiplexed targeted LC-MS3 method (TOMAHAQ) for the validation of selected target proteins.

Results

The TMT-LC/LC-MS/MS platform is capable of analyzing 4826 protein components (4368 genes), covering at least 6 orders of magnitude in dynamic range, representing one of the deepest serum proteome analysis. We defined intra- and inter- group variability in the AD and control groups. Statistical analysis revealed differentially expressed proteins in AD (26 decreased and 4 increased). Notably, these altered proteins are enriched in the known pathways of mitochondria, fatty acid beta oxidation, and AGE/RAGE. Finally, we set up a TOMAHAQ method to confirm the decrease of PCK2 and AK2 in our AD samples.

Conclusions

Our results show an ultra-deep serum discovery study by TMT-LC/LC-MS/MS, and a validation experiment by TOMAHAQ targeted LC-MS3. The MS-based discovery and validation methods are of general use for biomarker discovery from complex biofluids (e.g. serum proteome). This pilot study also identified deregulated proteins, in particular proteins associated with mitochondrial function in the AD serum samples. These proteins may serve as novel AD candidate biomarkers.