TMT-based quantitative proteomics is one of the most efficient and reliable methods in relative protein quantification and has made indispensable contributions in protein biology. To enable quantitative interactomic studies for protein-protein interaction profiling, we hereby developed a TMT-based quantitative cross-linking mass spectrometry workflow based on gas-phase cleavable cross-linker DSSO on a FAIMS enabled Obitrap Fusion Lumos mass spectrometer. For benchmarking, we tested different HCD fragmentation energies and acquisition strategies on TMT-labeled cross-links. We also constructed a two interactome dataset by preparing cross-linked E. coli and HeLa lysates and mixed them with different ratios to assess the level of ion interference. Collectively, we demonstrated a stepHCD method with optimized energies delivers the best result, as demonstrated by the highest number of identified and quantified cross-links as well as the most accurate quantitative information.

In recent years, life science research has experienced a significant shift, moving away from conducting bulk cell interrogation towards single-cell analysis. It is only through single-cell analysis that a complete understanding of cellular heterogeneity, and the interplay between various cell types fundamental to specific biological phenotypes can be achieved. The blood system is a prime example of such a complex hierarchy, where Hematopoietic stem cells are the origin of all cell lineages contained therein. Acute myeloid leukemia (AML), a perturbed state of hematopoiesis, is also hierarchically organized, with leukemia stem cells at the apex. Successful eradication of AML will likely depend on specific targeting of these tumour-initiating cells, in turn requiring their molecular characterization.

We have spent the past few years optimizing a proteomics workflow for analyzing single cells using Mass Spectrometry (scMS). Through isobaric labeling using latest-generation TMTPro reagents, we ensure highest possible cell throughput, bringing in-depth characterizations of >10,000 single cells within reach. We demonstrate both through pre-enrichment of cell populations and through a non-enriched unbiased approach that our workflow enables the exploration of cellular heterogeneity within healthy and aberrant blood hierarchies. We leverage a combination of fluorescence-activated cell sorting, automated liquid handling, next-generation chromatography, state-of-the-art MS instrumentation and complex data analysis workflows to provide a comprehensive suite of scMS tools. Combined, our workflow strikes a careful balance between cell throughput, proteome depth, quantitative accuracy and ease-of-implementation, and demonstrates the power of implementing global single-cell proteomics studies in labs across the world.

Single cell proteomics was revolutionized by the introduction of SCoPE-MS, a method that utilizes a carrier proteome added at 20x to 500x single cell channels to enable peptide detection, selection, and quantification. Recently, it has been demonstrated that adding excess carrier proteome may increase measurement variability as well as decrease measurement accuracy and dynamic range. This can be overcome by decreasing the amount of carrier proteome or increasing the number of ions sampled - but quantitative analysis is impacted at some level by the presence of carrier proteome reporter ions. Here, we introduce two advanced data acquisition approaches that utilize a carrier proteome labeled with an offset mass chemical tag (i.e., TMT-SH) that separates the carrier proteome peptide cluster from the multiplexed single cell proteomes and enables quantification of single cells in the absence of carrier proteome reporter ions. The first approach SureQuant-TMT enables the monitoring of up to 10,000 peptides derived from a TMT-SH labeled proteome, real-time peptide identification by peak matching, and subsequent selection of endogenous, multiplexed single cell samples only when a carrier proteome peptide is identified. This technique improves proteomics depth in both MS2 and MS3 analyses for peptides on the user’s inclusion list. The second approach introduces a novel API programming platform, called inSeqAPI, that enables facile construction of real-time data analysis methods. We demonstrate its utility by constructing a method that performs a real-time search on a TMT-SH labeled carrier proteome and triggers quantitative MS2 or MS3 analysis on endogenous TMT labeled single cell proteomes only when a carrier proteome peptide is identified. This unbiased approach enables deep proteomic analysis and sensitive quantification of single cell proteomes by quantifying peptides only after they are identified and removing the carrier proteome from isolation during quantitative scans.

Robust methods for deep-scale enrichment and site-specific identification of ubiquitylation sites is necessary for characterizing the myriad roles of protein ubiquitylation. UbiFast is a highly sensitive method for multiplexed ubiquitylation profiling in which K-ɛ-GG peptides are enriched using antibodies specific to ubiquitin remnants (K-ɛ-GG) followed by on-antibody labeling with TMT reagents. Here, we present methods for automation of the UbiFast method using anti-K-ε-GG antibody covalently linked to magnetic beads and a magnetic particle processer. The workflow enables processing of up to 96 samples in parallel and greatly reduces sample processing times and variability. We have also incorporated automated UbiFast as part of a serial enrichment strategy that enables efficient and sample-sparing analysis of limited biological and clinical samples. Optimized FAIMS MS methods for the analysis of Ub samples will also be described.

Increasing evidence indicates that Alzheimer’s disease (AD) develops from an intricate web of biochemical and cellular processes that extend far beyond amyloid and tau accumulation. This growing recognition surrounding the diversity of AD pathophysiology underscores the need for holistic systems-based approaches to explore AD pathogenesis. Using isobaric tandem mass tag (TMT) based mass spectrometry methods we describe how network-based proteomics has provided an informative framework for the complex protein pathophysiology underlying AD. Furthermore, we outline how the global brain network proteome can be leveraged to advance translational efforts including the discovery and validation of novel protein biomarkers in cerebrospinal fluid.

Protein post-translational modifications (PTMs) regulate many aspects of protein function, including localization, activation, stability, and protein-protein interactions. Protein PTMs tend to be dynamic and often occur at low stoichiometry, and thus can be challenging to identify and quantify. Indeed, enrichment of the selected PTM, or even subsets of the selected PTM, are often required prior to analysis. Despite these inherent challenges, PTM analyses (e.g., functional proteomics) can provide unprecedented insight into biological regulation in the context of health and disease, including identification of therapeutic drug targets, mechanisms of therapeutic resistance, and response to environmental perturbagens. Many cancer subtypes have limited therapeutic options beyond chemotherapy, and poor response rates and overall survival statistics. To identify potential therapeutic targets and therapeutic strategies, we have applied functional proteomics with multiplexed isobaric tags (TMT) for quantification to gain insight into activated signaling networks. Application of this approach to chemotherapy resistant triple negative breast cancer (CR-TNBC) identified a therapeutic target and biomarker signature. Modification of our functional proteomics approach has enabled multiplexed quantification of hundreds of signaling nodes in single sections or punches of FFPE-preserved tumor tissues, enabling the potential for a proteomics-based approach to personalized medicine.

In this presentation, we will show how to use Proteome Discoverer 2.5 to obtain high quality results for TMT quantification data acquired with Thermo Scientific Orbitrap MS-based instruments. We will first provide an overview of the key features in Proteome Discoverer for peptide identification, quantification, and statistical analysis. We will then follow up with a few example datasets to show how these features can be applied.

Tandem Mass Tags (TMT) enables the high-throughput MS analysis for proteome quantitation. The ultimate goal in TMT MS experiment and method development has always been the improvement in quantified ID coverage, quantitation precision and accuracy. In this session, we will introduce how to acquire high quality TMT quantification data on Thermo Scientific Orbitrap Eclipse Tribrid mass spectrometer, Thermo Scientific Orbitrap Exploris 480 and 240 mass spectrometers. We will walk through the instrument methods using the latest version of instrument control software on each platform and will also cover the implementation of real-time search (RTS) and Thermo Fisher Scientific High-Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) Pro interface in the data acquisition to further improve the quantitation performance of TMT workflows.

Over the last decade, tandem mass tag (TMT) technology has grown to become one of the predominant methods for global protein quantitation. Advancements in isobaric tag reagent chemistry, instrument hardware and data analysis software over the years have helped expand the level of proteomic sample multiplexing from 6 to 18 samples. This seminar will highlight advances in sample preparation necessary to prepare high quality peptide samples for isobaric tag labeling. Additionally, this seminar will provide an overview of methods for improving proteomics sample preparation reproducibility and depth of coverage depth for different sample types and limited sample amounts.

Cells are continuously exposed to various stresses originating from their own function, environmental changes, and pathogens. To understand the cellular responses to stresses, molecular systems approaches are required to assess and integrate the various global and molecular changes. Quantitative proteomics has proven particularly powerful to directly monitor underlying changes in protein abundance and modifications.

We focus on applying quantitative proteomics to study stress responses, such as proteostasis perturbation and host-pathogen interactions. To be able to determine the highly dynamic and time resolved effects of stresses, we develop proteomics tools capable of resolving these conditions. Therefore, we focus on approaches that combine pulse-SILAC labeling with tandem mass tag-multiplexing. I will present multiplexed enhanced protein dynamics (mePROD) proteomics that allow to globally monitor protein translation and will show examples of its use to understand cellular translatome changes upon inhibition of the integrated stress response and mTORC1 – two crucial cellular stress hubs. Then I will present data from cells infected with SARS-CoV-2. The use systems biology approaches focusing on multi-level proteomics allowed us to first predict and then validate a number of drugs that prevent SARS-CoV-2 replication in cells and have now moved towards the clinic.

Overall, I will give an overview over novel approaches to measure protein dynamics by proteomics including the required bioinformatics tools for their analyses. I will provide examples of the strength of these methods in studying cellular protein dynamics during stress and infection.

Performing large scale plasma profiling studies involving thousands of samples are challenging due to both lengthy sample preparation and long instrument time requirements. We present a fully Automated Multiplexed Proteome Profiling Platform (AutoMP3) that is capable of processing hundreds to thousands of samples. We combined 16-plex Tandem Mass Tags (TMTpro) with high-field asymmetric waveform ion mobility spectrometry (FAIMS Pro) and real-time search (RTS) to maximize protein depth in plasma. The concentration of plasma proteins spans a dynamic range of at least 12 orders of magnitude, resulting in poor protein identification depth. FAIMS Pro and RTS have been critical to enable deep coverage in single shot mass spectrometry runs.

We have applied this platform to multiple studies including naked mole rats treated with UV radiation, circadian rhythm samples, various mouse and human cohorts as well as diseased cohorts such as chronic kidney disease. We continue to improve the AutoMP3 workflow and extend its applications both in the sample type as well as post translational modification space and will present some of our recent efforts in these areas.

Isobaric labeling facilitates proteome-wide expression profiling across multiple samples within a closed system. A plethora of strategies have been published concerning sample processing and subsequent mass spectrometric data acquisition for isobaric tag-based experiments, including the streamlined-TMT (SL-TMT) protocol as highlighted here. This talk underscores several important aspects of such strategies, illustrates a basic sample processing and data acquisition framework, and suggests where further optimization may be necessary. Together, higher order multiplexing (TMTpro-18plex), high-field asymmetric-waveform ion-mobility spectrometry (FAIMS), and real-time database searching (RTS) can expand the depth, breadth, and accuracy of proteome-wide expression profiling. In addition, a single-step, medium-scale, phosphorylation experiment (“mini-phos”) can be integrated seamlessly into the workflow. This single spin column-based enrichment of the pooled TMT-labeled sample can routinely quantify several thousand phosphorylation sites from a TMTpro18-plex experiment starting from ~50 µg of protein per condition with minimal toll on time and cost. This talk showcases the general workflow using a TMTpro dataset in which the samples were processed with the SL-TMT protocol and the data were collected using FAIMS and RTS on an Orbitrap Eclipse mass spectrometer.

Sample multiplexing using isobaric tagging techniques allows for up to 18 samples to be simultaneously compared using the TMTpro18 reagent set. This talk will showcase the history of sample multiplexing using isobaric tagging and specifically the TMT reagent storyline. In addition, the challenge of overcoming ratio distortion due to co-isolation and co-fragmentation will be described along with possible solutions. Moreover, the use of emerging targeted proteomics methods for sample multiplexing will be explored. Finally, to highlight the ability of 16plex sample multiplexing to exploit complex experimental designs, I will describe a large unpublished dataset from a collaboration between my lab, Dr. Joao Paulo’s lab and Jackson labs quantifying tissue-specific protein expression differences across eight fully-sequenced inbred founder mouse strains with five females and five males from each strain. Twelve different tissues were examined using 60 separate TMT16plex experiments. Sex-, tissue-, and strain-specific differences will be highlighted.

Understanding biology is complicated! There are six major types of molecules (DNA, RNA, Proteins, Lipids, Glycans, Metabolites) that all work in concert to define whether a biological system is healthy or diseased. To truly understand health and disease we need quantitative maps of all of these molecules and how they relate to each other in terms of presence and abundance at any given time. We are still a long way from delivering on this holistic level, but significant progress in the development of analytical and quantitative methods for all of these molecular entities, led of course by nucleic acid research, have delivered major improvement in the breadth and depth of quantitation available.

Comprehensive analysis of the Proteome has been a long time in the making since the first mass spectrometry methods for peptide sequencing were introduced in the 1990s, and is hampered by our inability to amplify proteins and the sheer complexity created by post-translational changes. This complexity creates challenges in stochastic sampling high levels of missing data that dramatically impacts on the numbers of features quantified in unbiased proteomics studies. Several strategies have been introduced to reduce ‘missingness’ and this talk will focus on the particular role that Tandem Mass Tags® (TMT® & TMTpro™) are playing in the large-scale quantitation of proteins, peptides and post-translational modifications.

The underlying principle of isobaric mass tagging was invented by Dr. Andrew Thompson in the mid-1990s and Proteome Sciences acquired the technology in 2002 when Dr. Thompson also joined the Company. We have developed both TMT® reagents, starting at 6-plex and moving up to 11-plex, and then the TMTpro™ reagents to deliver even higher multiplexing with our 18plex set being the largest set of commercially available tags. Being able to mix samples after digestion gives greater throughput and the option to perform extensive fractionation for deep profiling, whilst retaining quantitative precision. We have also used the power of isobaric tagging to develop new workflows for enhanced biomarker discovery in biofluids and accurate quantification using internal calibration curves with parallel reaction monitoring assays. Others have used similar approaches to develop single-cell proteomics methods able to quantify >1,500 proteins.

Whilst we may still be some way from knowing what the whole proteome really is, the breadth and depth of quantification achievable with 18plex TMTpro™ is driving a better understanding of complex biological questions in basic research, drug development and diagnostic biomarker discovery. Whilst the last two decades have been the era of genomics, the 2020’s are shaping up to be the decade of multiplex proteomics.