Precise Temporal Profiling of Signaling Complexes in Primary Cells Using SWATH Mass Spectrometry

GRB2 promotes thymocyte positive selection by facilitating THEMIS-mediated inactivation of SHP1

The T-lineage restricted protein THEMIS has been shown to play a critical role in T cell development. THEMIS, via its distinctive CABIT domains, inhibits the catalytic activity of the tyrosine phosphatase SHP1 (PTPN6). SHP1 and THEMIS bind to the ubiquitous cytosolic adapter GRB2, and the purported formation of a tri-molecular THEMIS-GRB2-SHP1 complex facilitates inactivation of SHP1 by THEMIS. The importance of this function of GRB2 among its numerous documented activities is unclear as GRB2 binds to multiple proteins and participates in several signaling responses in thymocytes. Here, we show that similar to Themis-/- thymocytes, the primary molecular defect in GRB2-deficient thymocytes is increased catalytically active SHP1 and the developmental block in GRB2-deficient thymocytes is alleviated by deletion or inhibition of SHP1 and is exacerbated by SHP1 overexpression. Thus, the principal role of GRB2 during T cell development is to promote THEMIS-mediated inactivation of SHP1 thereby enhancing the sensitivity of TCR signaling in CD4+CD8+ thymocytes to low affinity positively selecting self-ligands.

Unveiling the complexity of transcription factor networks in hematopoietic stem cells: implications for cell therapy and hematological malignancies

The functionality and longevity of hematopoietic tissue is ensured by a tightly controlled balance between self-renewal, quiescence, and differentiation of hematopoietic stem cells (HSCs) into the many different blood lineages. Cell fate determination in HSCs is influenced by signals from extrinsic factors (e.g., cytokines, irradiation, reactive oxygen species, O2 concentration) that are translated and integrated by intrinsic factors such as Transcription Factors (TFs) to establish specific gene regulatory programs. TFs also play a central role in the establishment and/or maintenance of hematological malignancies, highlighting the need to understand their functions in multiple contexts. TFs bind to specific DNA sequences and interact with each other to form transcriptional complexes that directly or indirectly control the expression of multiple genes. Over the past decades, significant research efforts have unraveled molecular programs that control HSC function. This, in turn, led to the identification of more than 50 TF proteins that influence HSC fate. However, much remains to be learned about how these proteins interact to form molecular networks in combination with cofactors (e.g. epigenetics factors) and how they control differentiation, expansion, and maintenance of cellular identity. Understanding these processes is critical for future applications particularly in the field of cell therapy, as this would allow for manipulation of cell fate and induction of expansion, differentiation, or reprogramming of HSCs using specific cocktails of TFs. Here, we review recent findings that have unraveled the complexity of molecular networks controlled by TFs in HSCs and point towards possible applications to obtain functional HSCs ex vivo for therapeutic purposes including hematological malignancies. Furthermore, we discuss the challenges and prospects for the derivation and expansion of functional adult HSCs in the near future.

Unlocking the potential of microfluidics in mass spectrometry-based immunopeptidomics for tumor antigen discovery

The identification of tumor-specific antigens (TSAs) is critical for developing effective cancer immunotherapies. Mass spectrometry (MS)-based immunopeptidomics has emerged as a powerful tool for identifying TSAs as physical molecules. However, current immunopeptidomics platforms face challenges in measuring low-abundance TSAs in a precise, sensitive, and reproducible manner from small needle-tissue biopsies (<1 mg). Inspired by recent advances in single-cell proteomics, microfluidics technology offers a promising solution to these limitations by providing improved isolation of human leukocyte antigen (HLA)-associated peptides with higher sensitivity. In this context, we highlight the challenges in sample preparation and the rationale for developing microfluidics technology in immunopeptidomics. Additionally, we provide an overview of promising microfluidic methods, including microchip pillar arrays, valved-based systems, droplet microfluidics, and digital microfluidics, and discuss the latest research on their application in MS-based immunopeptidomics and single-cell proteomics.

Mapping the SLP76 interactome in T cells lacking each of the GRB2-family adaptors reveals molecular plasticity of the TCR signaling pathway

The propagation and diversification of signals downstream of the T cell receptor (TCR) involve several adaptor proteins that control the assembly of multimolecular signaling complexes (signalosomes). The global characterization of changes in protein-protein interactions (PPI) following genetic perturbations is critical to understand the resulting phenotypes. Here, by combining genome editing techniques in T cells and interactomics studies based on affinity purification coupled to mass spectrometry (AP-MS) analysis, we determined and quantified the molecular reorganization of the SLP76 interactome resulting from the ablation of each of the three GRB2-family adaptors. Our data showed that the absence of GADS or GRB2 induces a major remodeling of the PPI network associated with SLP76 following TCR engagement. Unexpectedly, this PPI network rewiring minimally affects proximal molecular events of the TCR signaling pathway. Nevertheless, during prolonged TCR stimulation, GRB2- and GADS-deficient cells displayed a reduced level of activation and cytokine secretion capacity. Using the canonical SLP76 signalosome, this analysis highlights the plasticity of PPI networks and their reorganization following specific genetic perturbations.

POSREG: proteomic signature discovered by simultaneously optimizing its reproducibility and generalizability

Mass spectrometry-based proteomic technique has become indispensable in current exploration of complex and dynamic biological processes. Instrument development has largely ensured the effective production of proteomic data, which necessitates commensurate advances in statistical framework to discover the optimal proteomic signature. Current framework mainly emphasizes the generalizability of the identified signature in predicting the independent data but neglects the reproducibility among signatures identified from independently repeated trials on different sub-dataset. These problems seriously restricted the wide application of the proteomic technique in molecular biology and other related directions. Thus, it is crucial to enable the generalizable and reproducible discovery of the proteomic signature with the subsequent indication of phenotype association. However, no such tool has been developed and available yet. Herein, an online tool, POSREG, was therefore constructed to identify the optimal signature for a set of proteomic data. It works by (i) identifying the proteomic signature of good reproducibility and aggregating them to ensemble feature ranking by ensemble learning, (ii) assessing the generalizability of ensemble feature ranking to acquire the optimal signature and (iii) indicating the phenotype association of discovered signature. POSREG is unique in its capacity of discovering the proteomic signature by simultaneously optimizing its reproducibility and generalizability. It is now accessible free of charge without any registration or login requirement at https://idrblab.org/posreg/.

Proximity labeling and other novel mass spectrometric approaches for spatiotemporal protein dynamics

BACKGROUND

Proteins are highly dynamic and their biological function is controlled by not only temporal abundance changes but also via regulated protein-protein interaction networks, which respond to internal and external perturbations. A wealth of novel analytical reagents and workflows allow studying spatiotemporal protein environments with great granularity while maintaining high throughput and ease of analysis.

AREAS COVERED

We review technology advances for measuring protein-protein proximity interactions with an emphasis on proximity labeling, and briefly summarize other spatiotemporal approaches including protein localization, and their dynamic changes over time, specifically in human cells and mammalian tissues. We focus especially on novel technologies and workflows emerging within the past 5 years. This includes enrichment-based techniques (proximity labeling and crosslinking), separation-based techniques (organelle fractionation and size exclusion chromatography), and finally sorting-based techniques (laser capture microdissection and mass spectrometry imaging).

EXPERT OPINION

Spatiotemporal proteomics is a key step in assessing biological complexity, understanding refined regulatory mechanisms, and forming protein complexes and networks. Studying protein dynamics across space and time holds promise for gaining deep insights into how protein networks may be perturbed during disease and aging processes, and offer potential avenues for therapeutic interventions, drug discovery, and biomarker development.

ANPELA: analysis and performance assessment of the label-free quantification workflow for metaproteomic studies

Label-free quantification (LFQ) with a specific and sequentially integrated workflow of acquisition technique, quantification tool and processing method has emerged as the popular technique employed in metaproteomic research to provide a comprehensive landscape of the adaptive response of microbes to external stimuli and their interactions with other organisms or host cells. The performance of a specific LFQ workflow is highly dependent on the studied data. Hence, it is essential to discover the most appropriate one for a specific data set. However, it is challenging to perform such discovery due to the large number of possible workflows and the multifaceted nature of the evaluation criteria. Herein, a web server ANPELA (https://idrblab.org/anpela/) was developed and validated as the first tool enabling performance assessment of whole LFQ workflow (collective assessment by five well-established criteria with distinct underlying theories), and it enabled the identification of the optimal LFQ workflow(s) by a comprehensive performance ranking. ANPELA not only automatically detects the diverse formats of data generated by all quantification tools but also provides the most complete set of processing methods among the available web servers and stand-alone tools. Systematic validation using metaproteomic benchmarks revealed ANPELA's capabilities in 1 discovering well-performing workflow(s), (2) enabling assessment from multiple perspectives and (3) validating LFQ accuracy using spiked proteins. ANPELA has a unique ability to evaluate the performance of whole LFQ workflow and enables the discovery of the optimal LFQs by the comprehensive performance ranking of all 560 workflows. Therefore, it has great potential for applications in metaproteomic and other studies requiring LFQ techniques, as many features are shared among proteomic studies.

Stable and EGF-Induced Temporal Interactome Profiling of CBL and CBLB Highlights Their Signaling Complex Diversity

The epidermal growth factor receptor (EGFR) signal modulates cell proliferation, migration, and survival. Aberrant activation of EGFR constitutes the major cause of various cancers. Receptor ubiquitination and degradation mediated by CBL proteins play negative regulatory roles and control the intensity and duration of the signaling. With the construction of stable cell lines inducibly expressing FLAG-tagged CBL or CBLB, we identified 102 and 82 stable interacting proteins of CBL and CBLB, respectively, through the affinity purification followed by mass spectrometry (AP-MS) approach. Time-resolved profiling at six different time points combined with functional annotations of the temporal interactomes provides insights into the dynamic assembly of signal proteins upon EGFR signaling activation. Comparison between the interactomes of CBL and CBLB indicates their redundant but also complementary functions. Importantly, we validated the stable association of EPS15L1 and ITSN2 and temporal association of TNK2 to both CBL and CBLB through biochemical assays. Collectively, these results offer a useful resource for CBL and CBLB interactomes and highlight their prominent and diverse roles in the EGFR signaling network.

Spatiotemporal profiling of cytosolic signaling complexes in living cells by selective proximity proteomics

Signaling complexes are often organized in a spatiotemporal manner and on a minute timescale. Proximity labeling based on engineered ascorbate peroxidase APEX2 pioneered in situ capture of spatiotemporal membrane protein complexes in living cells, but its application to cytosolic proteins remains limited due to the high labeling background. Here, we develop proximity labeling probes with increased labeling selectivity. These probes, in combination with label-free quantitative proteomics, allow exploring cytosolic protein assemblies such as phosphotyrosine-mediated protein complexes formed in response to minute-scale EGF stimulation. As proof-of-concept, we systematically profile the spatiotemporal interactome of the EGFR signaling component STS1. For STS1 core complexes, our proximity proteomics approach shows comparable performance to affinity purification-mass spectrometry-based temporal interactome profiling, while also capturing additional—especially endosomally-located—protein complexes. In summary, we provide a generic approach for exploring the interactome of mobile cytosolic proteins in living cells at a temporal resolution of minutes.

APEX-based proximity labeling allows capturing protein interaction dynamics but its high labeling background limits its utility for cytosolic proteins. Here, the authors develop more selective proximity labeling probes, enabling the APEX-based characterization of time-resolved cytosolic protein interactomes.

SWATH-MS-Based Proteomics: Strategies and Applications in Plants

Most applied proteomic approaches require labeling steps. Recent technological advances provide an alternative label-free proteomics approach: SWATH-MS. This powerful tool is now widely used in animal studies but has drawn far less attention in plants. Here we summarize how this promising technology can be applied to facilitate functional analysis in plant research.

Quantitative Interactomics in Primary T Cells Provides a Rationale for Concomitant PD-1 and BTLA Coinhibitor Blockade in Cancer Immunotherapy

Deciphering how TCR signals are modulated by coinhibitory receptors is of fundamental and clinical interest. Using quantitative interactomics, we define the composition and dynamics of the PD-1 and BTLA coinhibitory signalosomes in primary effector T cells and at the T cell-antigen-presenting cell interface. We also solve the existing controversy regarding the role of the SHP-1 and SHP-2 protein-tyrosine phosphatases in mediating PD-1 coinhibition. PD-1 predominantly recruits SHP-2, but when absent, it recruits SHP-1 and remains functional. In contrast, BTLA predominantly recruits SHP-1 and to a lesser extent SHP-2. By separately analyzing the PD-1-SHP-1 and PD-1-SHP-2 complexes, we show that both dampen the TCR and CD28 signaling pathways equally. Therefore, our study illustrates how comparison of coinhibitory receptor signaling via quantitative interactomics in primary T cells unveils their extent of redundancy and provides a rationale for designing combinations of blocking antibodies in cancer immunotherapy on the basis of undisputed modes of action.

Approaching complexity: systems biology and ms-based techniques to address immune signaling

INTRODUCTION

Studying immune signaling has been critical for our understanding of immunology, pathogenesis, cancer, and homeostasis. To enhance the breadth of the analysis, high throughput methods have been developed to survey multiple areas simultaneously, including transcriptomics, reporter assays, and ELISAs. While these techniques have been extremely informative, mass-spectrometry-based technologies have been gaining momentum and starting to be widely used in the studies of immune signaling and systems immunology.

AREAS COVERED

We present established proteomic methods that have been used to address immune signaling and discuss the new mass-spectrometry- based techniques of interest to the expanding field of systems immunology. Established and new proteomic methods and their applications discussed here include post-translational modification analysis, protein quantification, secretome analysis, and interactomics. In addition, we present developments in small molecule and metabolite analysis, mass spectrometry imaging, and single cell analysis. Finally, we discuss the role of multi-omic integration in aiding leading edge investigation.

EXPERT OPINION

In science, available techniques enhance the breadth and depth of the studies. By incorporating proteomic techniques and their innovative use, it will be possible to expand the current studies and to address novel questions at the forefront of scientific discovery.

Proteome Analysis of Hordein-Null Barley Lines Reveals Storage Protein Synthesis and Compensation Mechanisms

Hordeins are the major barley seed storage proteins and are elicitors of celiac disease. Attempts to reduce the hordein level in barley have been made; however, the resultant pleiotropic effects are less understood. Here, data-independent acquisition mass spectrometry was used to measure proteome-wide abundance differences between wild-type and single hordein-null barley lines. Using comparative quantitative proteomics, we detected proteome-wide changes (∼59%) as a result of the specific reduction in hordein proteins. The comparative analysis and functional annotation revealed an increase in non-gluten storage proteins, such as globulins and lipid transfer proteins, and proteins rich in essential amino acids in the null lines. This study yields an informative molecular portrait of the hordein-null lines and the underlying mechanisms of storage protein biosynthesis. This study indicates the extent to which protein content can be manipulated without biological consequence, and we envision its wide-scale application for studying modified crops.

Quantitative interactomics in primary T cells unveils TCR signal diversification extent and dynamics

The activation of T cells by the T cell antigen receptor (TCR) results in the formation of signaling protein complexes (signalosomes), the composition of which has not been analyzed at a systems level. Here, we isolated primary CD4⁺ T cells from 15 gene-targeted mice, each expressing one tagged form of a canonical protein of the TCR-signaling pathway. Using affinity purification coupled with mass spectrometry, we analyzed the composition and dynamics of the signalosomes assembling around each of the tagged proteins over 600 s of TCR engagement. We showed that the TCR signal-transduction network comprises at least 277 unique proteins involved in 366 high-confidence interactions, and that TCR signals diversify extensively at the level of the plasma membrane. Integrating the cellular abundance of the interacting proteins and their interaction stoichiometry provided a quantitative and contextual view of each documented interaction, permitting anticipation of whether ablation of a single interacting protein can impinge on the whole TCR signal-transduction network.

Simultaneous Improvement in the Precision, Accuracy, and Robustness of Label-free Proteome Quantification by Optimizing Data Manipulation Chains

The label-free proteome quantification (LFQ) is multistep workflow collectively defined by quantification tools and subsequent data manipulation methods that has been extensively applied in current biomedical, agricultural, and environmental studies. Despite recent advances, in-depth and high-quality quantification remains extremely challenging and requires the optimization of LFQs by comparatively evaluating their performance. However, the evaluation results using different criteria (precision, accuracy, and robustness) vary greatly, and the huge number of potential LFQs becomes one of the bottlenecks in comprehensively optimizing proteome quantification. In this study, a novel strategy, enabling the discovery of the LFQs of simultaneously enhanced performance from thousands of workflows (integrating 18 quantification tools with 3,128 manipulation chains), was therefore proposed. First, the feasibility of achieving simultaneous improvement in the precision, accuracy, and robustness of LFQ was systematically assessed by collectively optimizing its multistep manipulation chains. Second, based on a variety of benchmark datasets acquired by various quantification measurements of different modes of acquisition, this novel strategy successfully identified a number of manipulation chains that simultaneously improved the performance across multiple criteria. Finally, to further enhance proteome quantification and discover the LFQs of optimal performance, an online tool (https://idrblab.org/anpela/) enabling collective performance assessment (from multiple perspectives) of the entire LFQ workflow was developed. This study confirmed the feasibility of achieving simultaneous improvement in precision, accuracy, and robustness. The novel strategy proposed and validated in this study together with the online tool might provide useful guidance for the research field requiring the mass-spectrometry-based LFQ technique.

Quantification of Dynamic Protein Interactions and Phosphorylation in LPS Signaling Pathway by SWATH-MS

Lipopolysaccharide (LPS)-induced macrophage activation is a prototype of innate immune response. Although key effector proteins in LPS signaling pathway have been revealed, the map of dynamic protein interactions and phosphorylation as well as the stoichiometry of protein complexes are lacking. Here we present a dynamic map of protein interactions and phosphorylation in MyD88, TRAF6 and NEMO complexes obtained by SWATH-MS. The comprehensive MS measurement leads to quantification of up to about 3,000 proteins across about 21-40 IP samples. We detected and quantified almost all known interactors of MyD88, TRAF6 and NEMO. By analyzing these quantitative data, we uncovered differential recruitment of IRAK family proteins to LPS-induced signaling complexes and determined the stoichiometry of the Myddosome complex. In addition, quantitative phosphoproteomics analysis identified a number of unreported high-confidence phosphosites on the key proteins in LPS signaling pathway. Collectively, data of dynamic protein interactions and phosphorylation presented by this study could be a resource for further study of the LPS signaling pathway.

CD5, an Undercover Regulator of TCR Signaling

T cells are critical components of adaptive immunity. As such, their activation is regulated by the T cell receptor (TCR) that constantly scan peptides associated with major histocompatibility complexes (MHC). TCR engagement initiates a series of molecular events leading to cytokine secretion, proliferation, and differentiation of T cells. As a second coincident event, activation of co-stimulatory molecules, such as CD28, synergize with the TCR in order to prolong and/or amplify intracellular signals. With the recent advances in immunotherapies targeting T cells, co-inhibitory receptors are of growing interest for immunologists due to their potential modulatory properties on T cell functions. However, special attention should be dedicated to avoid unwanted clinical outcomes (1). In particular, Manichean categorization of receptors based on incomplete functional knowledge can lead to an over-simplistic view of complex cellular regulations. Thus, analysis of the functions that characterize these receptors in diverse physiological contexts remains essential for their rational use in therapeutic protocols. Here we focus on CD5, a transmembrane receptor that regulates T cell functions and development but remains poorly characterized at the molecular level. We will review its roles in physiological conditions and suggest potential molecular effectors that could account for CD5-dependent regulation of TCR signaling.

The costimulatory molecule CD226 signals through VAV1 to amplify TCR signals and promote IL-17 production by CD4+ T cells

The activation of T cells requires the guanine nucleotide exchange factor VAV1. Using mice in which a tag for affinity purification was attached to endogenous VAV1 molecules, we analyzed by quantitative mass spectrometry the signaling complex that assembles around activated VAV1. Fifty VAV1-binding partners were identified, most of which had not been previously reported to participate in VAV1 signaling. Among these was CD226, a costimulatory molecule of immune cells. Engagement of CD226 induced the tyrosine phosphorylation of VAV1 and synergized with T cell receptor (TCR) signals to specifically enhance the production of interleukin-17 (IL-17) by primary human CD4⁺ T cells. Moreover, co-engagement of the TCR and a risk variant of CD226 that is associated with autoimmunity (rs763361) further enhanced VAV1 activation and IL-17 production. Thus, our study reveals that a VAV1-based, synergistic cross-talk exists between the TCR and CD226 during both physiological and pathological T cell responses and provides a rational basis for targeting CD226 for the management of autoimmune diseases.