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.

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.

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.

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.