Protein post-translational modifications (PTMs) tend to be dynamic and often occur at low stoichiometry, and thus can be challenging to identify and quantify. 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 poor response rates, poor overall survival statistics, and limited therapeutic options beyond chemotherapy. To identify potential therapeutic targets and therapeutic strategies for these tumors, we have applied functional proteomics with multiplexed isobaric tags (TMT) for quantification to gain insight into activated signaling networks. To enable reproducible quantification of low-abundance phosphorylation sites, in collaboration with ThermoFisher Scientific we have developed SureQuant pTyr 2.0, a method enabling the targeted quantification of ~1100 pTyr sites across almost all facets of cell biology. Application of TMT-based multiplexed phosphoproteomics and SureQuant pTyr 2.0 to cell lines and tumor specimens, including single sections or punches of frozen or FFPE-preserved tumor tissues, quantifies activated signaling networks with high sensitivity and reproducibility, enabling the identification of putative therapeutic targets from small amounts of starting material.

Protein degradation is a critical regulatory mechanism for controlling protein levels. However, proteome-wide degradation measurements remain technically challenging, and even in the well-studied E. coli model, reliable measurements remain scarce.

Here, we quantify the degradation of ~3k E. coli proteins under 14 conditions by combining heavy isotope labeling with accurate multiplexed proteomics and find that E. coli recycles its cytoplasmic proteins when nitrogen-limited. Furthermore, we show that protein degradation rates do not scale with division rates. With knockout experiments, we identify substrates of the known ATP-dependent proteases but show that none is responsible for the cytoplasmic protein degradation in nitrogen starvation, suggesting that a major pathway in E. coli is still undiscovered. 

Thus, we introduce broadly-applicable technology for protein turnover measurements. We provide a rich resource for protein half-lives and protease substrates in E. coli that will allow researchers to complement genomics data to decipher the control of protein homeostasis.

Introduction
The proteomics field lacks standardized reagents and methods for sample preparation as already adopted in genomic and transcriptomic fields. Current methods are tedious, time-consuming, highly variable, unsuitable for processing large numbers of samples, and tend to negatively affect the robustness of the LC-MS instrumentation. Therefore, we developed an automated sample preparation solution that simplifies and standardizes mass spectrometry (MS) sample preparation. The new automated sample preparation platform is an intuitive turnkey system (instrument, software, reagents) that enables standardized, hands-off operation and provides robust workflows for label-free proteomics and TMT applications.

Methods 
The automated platform enables hands-off protein lysis, DNA removal, protein reduction and alkylation, digestion, TMT labeling, pooling and cleanup, and peptide concentration measurement, providing several workflows and companion reagents to perform several LFQ, TMT11plex, and TMTpro workflows at different sample scales. It guides the researchers across the whole workflow using an embedded user interface to easily place reagents and samples and recover processed samples. A SW ecosystem enables researchers to be assisted during the design of their experiments according to the biological changes. The prepared samples are ready to be injected into the external LC-MS system with known concentrations. The system was used in conjunction with built-for-purpose reagent sets.

Preliminary Date 
The automated sample preparation platform can process up to 36 samples containing 10-100 μg of initial protein input within 4-6 hours depending on the workflows. The final peptides have a minimum missed cleavage rate of less than 5% and complete reduction and alkylation.  Most importantly, the liquid handler has an integrated UV spectrometer that allows peptides to be readily analyzed by LC-MS with a known concentration.

If we are to understand cellular function – and dysfunction – at a systems level, then we must understand how proteome state drives the diversity of form and function embodied by human cells. Thanks in large part to mass spectrometry-based proteomics technology, it has become possible to profile the proteome in its many dimensions, from protein abundance and post-translational modification status to protein stability, proximity, interactions, and subcellular localization. Nevertheless, this remains a daunting experimental challenge due to the complexity and malleability of the proteome.

By increasing throughput, consistency of detection, and precision of quantification, isobaric labeling can enable proteome profiling with exceptional breadth and accuracy. Yet considerable effort is required to attain optimal results. I will describe the rationale behind the methods the Gygi lab has developed to execute isobaric labeling experiments with optimal depth and quantitative accuracy. I will then describe how we have deployed these methods to identify short-lived proteins in multiple cell lines and to profile protein expression across hundreds of cancer cell lines. These prototypes will serve as useful examples of how isobaric labeling with TMT reagents and state-of-the-art mass spectrometry instrumentation can be deployed at small and large scale to address fundamental questions of proteome biology.

The increase in available genetic data has led to the knowledge of hundreds of thousands of disease associated sequence variants. Traditional molecular biology techniques to understand how pathogenic variations impact protein-protein interactions requires extensive cloning and tagging or specific antibody development. We propose the use of thermal proteome profiling (TPP) for studying the impact of these disease related sequence variants on a systems wide level. TPP is a bottom up, TMT-based, quantitative mass spectrometry technique for determining the melt curves and changes in stability of 1000s of proteins simultaneously. This seminar covers the definition and workflow of TPP. TPP is then successfully utilized to characterize the global impacts of temperature sensitive proteasome subunit mutants in yeast. We describe the use of a “boost” channel of a purified protein complex to reproducibly quantify and measure melt shifts of proteins of interest across TPP multiplexes, and a new version of our open source, freely available software for analyzing TPP data (InflectSSP). Collaborations with rare disease labs have allowed us to perform global and TPP proteomics on Diamond-Blackfan Anemia (DBA) patient derived lymphoblastic cell lines suggesting this haploinsufficient ribosomopathy stabilizes the ubiquitin translation IFN degradation pathways. We have also piloted multi-tissue TPP with Drosophila as a model for pontocerebellar hypoplasia type PCH1B, characterized by cerebellar and motor neuron degeneration arising from tissue specific impacts of variants in the RNA exosome subunit EXOSC3.

Cysteine is a relatively low abundant amino acid that is present in almost all mammalian proteins (2.26% occurrence). However, more than 95% of all human proteins contain one or more cysteine residues. Cysteine contains a sulfhydryl group which makes it very reactive and can participate in several possible modifications making it a central amino acid in free radical driven processes. However, in normal proteomics workflows cysteine-containing peptides are used for identification and quantitation on an equal level compared to peptides without cysteines, as proteins conventionally are reduced and alkylated prior to digestion and quantitative analysis.

Conserved Cysteines are often located in active site of enzymes, such as Tyrosine phosphatases or Ubiquitylation ligases, as well as in the hydrophilic part where they are exposed to the cellular solvents and therefore capable of performing interactions with other molecules1. The reactive sulfhydryl group allows it to form irreversible (covalent) bond with groups such as sulfonic acid, in addition to making reversible (oxidative) bonds with several groups such as S-nitrosylation, S-sulfenylation, S-glutathionylation, S;sulfhydration, S-acylation as well as inter- and intra- disulphide bonds2. In a cellular context, cysteine can be modified with any of the above groups and attain unique functional capabilities, mostly in disulphide bond formation and metal binding. Moreover, it can make such reversible bonds very quickly and in response to sensitive factors such as change in pH or change in cellular oxidative state due to cellular activation with various factors. These attributes allow protein containing redox sensitive cysteine residues to function as a oxidases, reductases, peroxidases, disulphide isomerases and transcription factors; critical for maintenance of redox homeostasis of the cell3. With its fast response and posibility to modulate protein structure and function one can imaging a significant role of redox sensitive cystenes in signal transduction processes.

In the present talk we will introduce cysteine modifications, various tools for assessing these and various applications were we have used cysteine-specific proteomics to characterize important cysteine residues in key proteins for cellular signalling, such as T-cell activation and nerve-terminal stimulation.

Large scale proteomic profiling of cell lines can reveal molecular signatures attributed to variable genotypes or induced perturbations. Although isobaric labelling has greatly increased the throughput of proteomic analysis, the commonly used sample preparation workflows often require time-consuming steps and costly consumables, limiting their suitability for large scale studies. Here, we present a simplified and cost effective one-pot reaction workflow in a 96-well plate format (SimPLIT), based on a sodium deoxycholate lysis buffer, that minimizes processing steps and demonstrates improved reproducibility compared to alternative approaches. We showcase the applicability of the workflow in a panel of colorectal cancer cell lines and by performing target discovery for a set of molecular glue degraders in different cell lines, in a 96-sample assay. Using this workflow, we identify frequently dysregulated proteins in colorectal cancer cells and uncover cell-dependent protein degradation profiles of cereblon E3 ligase modulators. Overall, SimPLIT is a robust method that can be easily implemented in any proteomics laboratory for medium-to-large scale TMT-based studies for deep profiling of cell lines.

Proteomic profiling describes the molecular landscape of proteins in cells immediately available to sense, transduce, and enact the appropriate responses to extracellular queues. Transcriptional profiling has proven invaluable to our understanding of cellular responses; however, insights may be lost as mounting evidence suggests transcript levels only moderately correlate with protein levels in steady state cells. Mass spectrometry-based quantitative proteomics is a well-suited and widely used analytical tool for studying global protein abundances. Typical proteomic workflows are often limited by the amount of sample input that is required for deep and quantitative proteome profiling. This is especially true if the cells of interest need to be purified by fluorescence-activated cell sorting (FACS) and one wants to avoid ex vivo culturing. To address this need, we developed an easy to implement, streamlined workflow that enables quantitative proteome profiling from roughly 2 μg of protein input per experimental condition. Utilizing a combination of facile cell collection from cell sorting, solid-state isobaric labeling and multiplexing of peptides, and small-scale fractionation, we profiled the proteomes of 12 freshly isolated, primary murine immune cell types. Analyzing half of the 3e5 cells collected per cell type, we quantified over 7000 proteins across 12 key immune cell populations directly from their resident tissues. We show that low input proteomics is precise, and the data generated accurately reflects many aspects of known immunology, while expanding the list of cell-type specific proteins across the cell types profiled. The low input proteomics methods we developed are readily adaptable and broadly applicable to any cell or sample types and should enable proteome profiling in systems previously unattainable.

Most approved drugs today target proteins. There are approximately 20,000 proteins in the human proteome, of which, ~5,000 play critical roles in human disease. Of these 5,000, roughly 12% have been successfully targeted with small molecules and the remainder remain effectively un-assayable for drug development. Belharra Therapeutics is developing and employing a novel chemo-proteomic drug discovery engine utilizing drug-like photoaffinity probes to uncover functional and actionable ligands for any protein, in any state, in any cell type. Paramount to achieving this vision is enabling a high-throughput chemo-proteomics screening platform which is centered on quantitative mass-spectrometry (MS) based analysis. Historically, MS technology has been underutilized for discovery screening efforts due to limitations with throughput (low multiplexing) and the perception of high costs. As MS instrumentation has advanced, multiplexing capabilities have expanded, and automation in sample preparation has become feasible, the tools are in place to enable high-throughput chemo-proteomics is within reach. The data presented will highlight our efforts to address both throughput and cost challenges associated with MS-based proteomics approaches. We have optimized TMT reagent usage with our platform to appropriately balance over- and under-labeling, while reducing reagent associated costs and hands on time associated with aliquoting reagents. Taken together, these advances have enabled us to screen more than 100 compounds per day per mass spectrometer, realizing a 4X to >10X gain in throughput depending on sample complexity.

Genomic, transcriptomic, proteomic, phosphoproteomic and microbiomic studies were performed for the clinical tissue samples from Chinese intrahepatic cholangiocarcinoma (iCCA) patients. The genetic characteristics of iCCA were revealed by analyzing the genetic information. It was found that the samples contained aflatoxin-induced gene mutation "fingerprint", and the mutation "fingerprint" was associated with tumor genesis, proliferation and immunosuppression. Correlation analysis of somatic chromatin copy number alterations showed that cis/trans effects of CNA caused changes in mRNA, protein and phosphorylation. Pathway enrichment analysis showed that cis/trans effects were significantly correlated with changes in some protein and related pathways. In addition, the related signal of genetic mutations showed that TP53, KRAS, BAP1 and IDH1/2 gene mutations could affect downstream related protein and phosphorylation abundance, thus affecting the occurrence and development of disease. It was found that TP53/KRAS dual mutations may promote iCCA metastasis through the integrin-FAK /SRC pathway, resulting in poorer prognosis. In conjunction with the drug target database, it was found that higher expression of the target protein in gene mutation-related patient group could be used for personalized treatment, which was validated by patient-derived primary cancer cell lines. The iCCA patients were divided into four subgroups by proteomic analysis, and these four subgroups have specific characteristics. Four subgroup-specific protein biomarkers from each proteomic subgroup were identified by omic data dimension reduction analysis. And these four biomarkers were further validated in this and another independent patient cohort by immunofluorescence staining. Two potential protein biomarkers of iCCA, SLC16A3 protein and HKDC1 protein, were identified by clinical risk model analysis of proteomic data. Further analysis and verification showed that these two proteins were associated.

Targets are one of the most important element in both phenotypic drug discovery and target-based drug discovery.  Over the last decade, quantitative proteomics have become an efficient approach to deciphering action mechanisms and identifying targets of bioactive compounds. In this presentation, I will briefly introduce TMT-based thermal proteome profiling (TPP) and provide examples for identifying targets of different classes of compounds. Quantitative proteomics are also employed to determine the functions of flavonoids at molecular, cellular, tissue, and organism levels. I will also discuss the advantages and challenges of TPP in drug discovery.

Host responses to SARS-CoV-2 are dynamic and complex. Here I will present applications of advanced proteomics technologies to interrogate host responses in the sera, urine and tissue specimens from COVID-19 patients. Our proteomic analyses of COVID-19 specimens nominated potential intervention strategies that may be exploited to facilitate therapeutics against COVID-19.