Phosphoproteomic Workflow Research Articles

Mapping Nanoscale-To-Single-Cell Phosphoproteomic Landscape by Chip-DIA.

Protein phosphorylation plays a crucial role in regulating disease phenotypes and serves as a key target for drug development. Mapping nanoscale-to-single-cell samples can unravel the heterogeneity of cellular signaling events. However, it remains a formidable analytical challenge due to the low detectability, abundance, and stoichiometry of phosphorylation sites. Here, we present a Chip-DIA strategy,integratinga microfluidic-based phosphoproteomic chip (iPhosChip) with data-independent acquisition mass spectrometry (DIA-MS) for ultrasensitive nanoscale-to-single-cell phosphoproteomic profiling. The iPhosChip operates as an all-in-one station that accommodates both quantifiable cell capture/imaging and the entire phosphoproteomic workflow in a highly streamlined and multiplexed manner. Coupled with a sample size-comparable library-based DIA-MS strategy, Chip-DIA achieved ultra-high sensitivity, detecting 1076±158 to 15869±1898 phosphopeptides from 10±0 to 1013±4 cells, and revealed the first single-cell phosphoproteomic landscape comprising druggable sites and basal phosphorylation-mediated networks in lung cancer. Notably, the sensitivity and coverage enabled the illumination of heterogeneous cytoskeleton remodeling and cytokeratin signatures in patient-derived cells resistant to third-generation EGFR therapy, stratifying mixed-lineage adenocarcinoma-squamous cell carcinoma subtypes, and identifying alternative targeted therapy for late-stage patients. With flexibility in module design and functionalization, Chip-DIA can be adapted to other PTM-omics to explore dysregulated PTM landscapes, thereby guiding therapeutic strategies toward precision oncology.

A Rapid One-Pot Workflow for Sensitive Microscale Phosphoproteomics.

Compared to advancements in single-cell proteomics, phosphoproteomics sensitivity has lagged behind due to low abundance, complex sample preparation, and substantial sample input requirements. We present a simple and rapid one-pot phosphoproteomics workflow (SOP-Phos) integrated with data-independent acquisition mass spectrometry (DIA-MS) for microscale phosphoproteomic analysis. SOP-Phos adapts sodium deoxycholate based one-step lysis, reduction/alkylation, direct trypsinization, and phosphopeptide enrichment by TiO2 beads in a single-tube format. By reducing surface adsorptive losses via utilizing n-dodecyl β-d-maltoside precoated tubes and shortening the digestion time, SOP-Phos is completed within 3-4 h with a 1.4-fold higher identification coverage. SOP-Phos coupled with DIA demonstrated >90% specificity, enhanced sensitivity, lower missing values (<1%), and improved reproducibility (8%-10% CV). With a sample size-comparable spectral library, SOP-Phos-DIA identified 33,787 ± 670 to 22,070 ± 861 phosphopeptides from 5 to 0.5 μg cell lysate and 30,433 ± 284 to 6,548 ± 21 phosphopeptides from 50,000 to 2,500 cells. Such sensitivity enabled mapping key lung cancer signaling sites, such as EGFR autophosphorylation sites Y1197/Y1172 and drug targets. The feasibility of SOP-Phos-DIA was demonstrated on EGFR-TKI sensitive and resistant cells, revealing the interplay of multipathway Hippo-EGFR-ERBB signaling cascades underlying the mechanistic insight into EGFR-TKI resistance. Overall, SOP-Phos-DIA is an efficient and robust protocol that can be easily adapted in the community for microscale phosphoproteomic analysis.

Dynamic Protein Phosphorylation in Streptococcus pyogenes during Growth, Stationary Phase, and Starvation.

Phosphorylation of proteins at serine, threonine, and tyrosine residues plays an important role in physiological processes of bacteria, such as cell cycle, metabolism, virulence, dormancy, and stationary phase functions. Little is known about the targets and dynamics of protein phosphorylation in Streptococcus pyogenes, which possesses a single known transmembrane serine/threonine kinase belonging to the class of PASTA kinases. A proteomics and phosphoproteomics workflow was performed with S. pyogenes serotype M49 under different growth conditions, stationary phase, and starvation. The quantitative analysis of dynamic phosphorylation, which included a subset of 463 out of 815 identified phosphorylation sites, revealed two main types of phosphorylation events. A small group of phosphorylation events occurred almost exclusively at threonine residues of proteins related to the cell cycle and was enhanced in growing cells. The majority of phosphorylation events occurred during stationary phase or starvation, preferentially at serine residues. PASTA kinase-dependent cell cycle regulation processes found in related bacteria are conserved in S. pyogenes. Increased protein phosphorylation during the stationary phase has also been described for some other bacteria, and could therefore be a general feature in the physiology of bacteria, whose functions and the kinases involved need to be elucidated in further analyses.

Phosphoproteomic Approaches for Identifying Phosphatase and Kinase Substrates.

Protein phosphorylation is a ubiquitous post-translational modification controlled by the opposing activities of protein kinases and phosphatases, which regulate diverse biological processes in all kingdoms of life. One of the key challenges to a complete understanding of phosphoregulatory networks is the unambiguous identification of kinase and phosphatase substrates. Liquid chromatography-coupled mass spectrometry (LC-MS/MS) and associated phosphoproteomic tools enable global surveys of phosphoproteome changes in response to signaling events or perturbation of phosphoregulatory network components. Despite the power of LC-MS/MS, it is still challenging to directly link kinases and phosphatases to specific substrate phosphorylation sites in many experiments. Here, we survey common LC-MS/MS-based phosphoproteomic workflows for identifying protein kinase and phosphatase substrates, noting key advantages and limitations of each. We conclude by discussing the value of inducible degradation technologies coupled with phosphoproteomics as a new approach that overcomes some limitations of current methods for substrate identification of kinases, phosphatases, and other regulatory enzymes.

Unravelling G protein-coupled receptor signalling networks using global phosphoproteomics.

G protein-coupled receptor (GPCR) activation initiates signalling via a complex network of intracellular effectors that combine to produce diverse cellular and tissue responses. Although we have an advanced understanding of the proximal events following receptor stimulation, the molecular detail of GPCR signalling further downstream often remains obscure. Unravelling these GPCR-mediated signalling networks has important implications for receptor biology and drug discovery. In this context, phosphoproteomics has emerged as a powerful approach for investigating global GPCR signal transduction. Here, we provide a brief overview of the phosphoproteomic workflow and discuss current limitations and future directions for this technology. By highlighting some of the novel insights into GPCR signalling networks gained using phosphoproteomics, we demonstrate the utility of global phosphoproteomics to dissect GPCR signalling networks and to accelerate discovery of new targets for therapeutic development. LINKED ARTICLES: This article is part of a themed issue Therapeutic Targeting of G Protein-Coupled Receptors: hot topics from the Australasian Society of Clinical and Experimental Pharmacologists and Toxicologists 2021 Virtual Annual Scientific Meeting. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v181.14/issuetoc.

Phospho-heavy-labeled-spiketide FAIMS stepped-CV DDA (pHASED) provides real-time phosphoproteomics data to aid in cancer drug selection

Global high-throughput phosphoproteomic profiling is increasingly being applied to cancer specimens to identify the oncogenic signaling cascades responsible for promoting disease initiation and disease progression; pathways that are often invisible to genomics analysis. Hence, phosphoproteomic profiling has enormous potential to inform and improve individualized anti-cancer treatment strategies. However, to achieve the adequate phosphoproteomic depth and coverage necessary to identify the activated, and hence, targetable kinases responsible for driving oncogenic signaling pathways, affinity phosphopeptide enrichment techniques are required and often coupled with offline high-pressure liquid chromatographic (HPLC) separation prior to nanoflow liquid chromatography–tandem mass spectrometry (nLC-MS/MS). These complex and time-consuming procedures, limit the utility of phosphoproteomics for the analysis of individual cancer patient specimens in real-time, and restrict phosphoproteomics to specialized laboratories often outside of the clinical setting. To address these limitations, here we have optimized a new protocol, phospho-heavy-labeled-spiketide FAIMS stepped-CV DDA (pHASED), that employs online phosphoproteome deconvolution using high-field asymmetric waveform ion mobility spectrometry (FAIMS) and internal phosphopeptide standards to provide accurate label-free quantitation (LFQ) data in real-time. Compared with traditional single-shot LFQ phosphoproteomics workflows, pHASED provided increased phosphoproteomic depth and coverage (phosphopeptides = 4617 pHASED, 2789 LFQ), whilst eliminating the variability associated with offline prefractionation. pHASED was optimized using tyrosine kinase inhibitor (sorafenib) resistant isogenic FLT3-mutant acute myeloid leukemia (AML) cell line models. Bioinformatic analysis identified differential activation of the serine/threonine protein kinase ataxia-telangiectasia mutated (ATM) pathway, responsible for sensing and repairing DNA damage in sorafenib-resistant AML cell line models, thereby uncovering a potential therapeutic opportunity. Herein, we have optimized a rapid, reproducible, and flexible protocol for the characterization of complex cancer phosphoproteomes in real-time, a step towards the implementation of phosphoproteomics in the clinic to aid in the selection of anti-cancer therapies for patients.

Optimal analytical strategies for sensitive and quantitative phosphoproteomics using TMT-based multiplexing.

In large-scale quantitative mass spectrometry (MS)-based phosphoproteomics, isobaric labeling with tandem mass tags (TMTs) coupled with offline high-pH reversed-phase peptide chromatographic fractionation maximizes depth of coverage. To investigate to what extent limited sample amounts affect sensitivity and dynamic range of the analysis due to sample losses, we benchmarked TMT-based fractionation strategies against single-shot label-free quantification with spectral library-free data independent acquisition (LFQ-DIA), for different peptide input per sample. To systematically examine how peptide input amounts influence TMT-fractionation approaches in a phosphoproteomics workflow, we compared two different high-pH reversed-phase fractionation strategies, microflow (MF) and stage-tip fractionation (STF), while scaling the peptide input amount down from 12.5 to 1μg per sample. Our results indicate that, for input amounts higher than 5μg per sample, TMT labeling, followed by microflow fractionation (MF) and phospho-enrichment, achieves the deepest phosphoproteome coverage, even compared to single shot direct-DIA analysis. Conversely, STF of enriched phosphopeptides (STF) is optimal for lower amounts, below 5μg/peptide per sample. As a result, we provide a decision tree to help phosphoproteomics users to choose the best workflow as a function of sample amount.

Mass spectrometry-based proteomics for abiotic stress studies.

Kinase assay linked phosphoproteomics (KALIP) and universal phosphoproteomics (UP) workflows are mass spectrometry (MS)-based phosphoproteomics technologies utilized for studying abiotic stress signaling networks. KALIP consists of executing isotope-labeled phosphorylation reactions in vitro and screening in vivo phosphorylated peptides/pools of substrates. For UP, guanidine hydrochloride (GdnHCl) is used to break down the cell wall before methanol-chloroform precipitation is applied to remove interferences. Both strategies conclude with subsequent analyses of enriched phosphopeptides by complementary MS techniques to determine phosphopeptide abundance changes and protein phosphorylation sites to uncover novel signaling components in the pathway.

Phosphoproteome Profiling Using an Isobaric Carrier without the Need for Phosphoenrichment.

Phosphorylation is a crucial component of cellular signaling cascades. It controls a variety of biological cellular functions, including cell growth and apoptosis. Owing to the low stoichiometry of phosphorylated proteins, the enrichment of phosphopeptides prior to LC-MS/MS is necessary for comprehensive phosphoproteome analysis, and quantitative phosphoproteomic workflows are typically limited by the amount of sample required. To address this issue, we developed an easy-to-establish, widely applicable, and reproducible strategy to increase phosphoproteomic signals from a small amount of sample without a phosphoenrichment step. By exploiting the multiplexing nature of isobaric labeling to generate a merged signal from multiple samples, and using a larger amount of enriched phosphopeptides as a carrier, we were able to increase trace amounts of phosphopeptides in the unpurified sample to an identifiable level and perform quantification using the reporter ion intensity of the isobaric tag. Our results showed that >1400 phosphopeptides were quantified from 250 ng of tryptic peptides prepared from cells. In a proof-of-concept of our strategy, we distinguished three types of lung cancer cell lines based on their quantitative phosphoproteomic data and identified changes in the phosphoproteome induced by drug treatment.

Proteomics and phosphoproteomics of C3 to CAM transition in the common ice plant.

Among all post-translational modifications of proteins, phosphorylation is one of the most common and most studied. Since plants are sessile organisms, many physiological processes on which their survival depends are regulated by phosphorylation and dephosphorylation. Understanding the extent to which a plant proteome is phosphorylated at specific developmental stages and/or under certain environmental conditions is essential for identifying molecular switches that regulate physiological processes and responses. While most phosphoproteomic workflows proposed in the literature provide tools to exclusively analyze phosphorylated proteins, it is imperative to examine both the proteome and the phosphoproteome to reveal the true complexity of a biological process. Here we describe a mass spectrometry-based phosphoproteomics workflow to analyze both total and phosphorylated proteins. Our method includes phenol-based protein extraction, as well as techniques to measure the quantity and quality of protein extracts. In addition, we compare in detail the efficiency and suitability of in-gel and in-solution trypsin digestion methods. A metal oxide affinity chromatography technique for rapid and efficient enrichment of phosphorylated peptides and an LC-MS/MS method for analysis of the phosphorylated peptides are described. Finally, we present and discuss the results generated by applying this workflow to our study of the C3 to CAM transition in the common ice plant (Mesembryanthemum crystallinum). Overall, our workflow provides robust methods for the identification of phosphoproteins and total proteins. It can be broadly applied to many other organisms and sample types, and the results provide a more accurate picture of the molecular switches that regulate different biological processes.

Motif-centric phosphoproteomics to target kinase-mediated signaling pathways

SummaryIdentifying cellular phosphorylation pathways based on kinase-substrate relationships is a critical step to understanding the regulation of physiological functions in cells. Mass spectrometry-based phosphoproteomics workflows have made it possible to comprehensively collect information on individual phosphorylation sites in a variety of samples. However, there is still no generic approach to uncover phosphorylation networks based on kinase-substrate relationships in rare cell populations. Here, we describe a motif-centric phosphoproteomics approach combined with multiplexed isobaric labeling, in which in vitro kinase reactions are used to generate targeted phosphopeptides, which are spiked into one of the isobaric channels to increase detectability. Proof-of-concept experiments demonstrate selective and comprehensive quantification of targeted phosphopeptides by using multiple kinases for motif-centric channels. More than 7,000 tyrosine phosphorylation sites were quantified from several tens of micrograms of starting materials. This approach enables the quantification of multiple phosphorylation pathways under physiological or pathological regulation in a motif-centric manner.

Multi-laboratory experiment PME11 for the standardization of phosphoproteome analysis

Global analysis of protein phosphorylation by mass spectrometry proteomic techniques has emerged in the last decades as a powerful tool in biological and biomedical research. However, there are several factors that make the global study of the phosphoproteome more challenging than measuring non-modified proteins. The low stoichiometry of the phosphorylated species and the need to retrieve residue specific information require particular attention on sample preparation, data acquisition and processing to ensure reproducibility, qualitative and quantitative robustness and ample phosphoproteome coverage in phosphoproteomic workflows. Aiming to investigate the effect of different variables in the performance of proteome wide phosphoprotein analysis protocols, ProteoRed-ISCIII and EuPA launched the Proteomics Multicentric Experiment 11 (PME11). A reference sample consisting of a yeast protein extract spiked in with different amounts of a phosphomix standard (Sigma/Merck) was distributed to 31 laboratories around the globe. Thirty-six datasets from 23 laboratories were analyzed. Our results indicate the suitability of the PME11 reference sample to benchmark and optimize phosphoproteomics strategies, weighing the influence of different factors, as well as to rank intra and inter laboratory performance.

Inference of kinase-signaling networks in human myeloid cell line models by Phosphoproteomics using kinase activity enrichment analysis (KAEA)

BackgroundDespite the introduction of targeted therapies, most patients with myeloid malignancies will not be cured and progress. Genomics is useful to elucidate the mutational landscape but remains limited in the prediction of therapeutic outcome and identification of targets for resistance. Dysregulation of phosphorylation-based signaling pathways is a hallmark of cancer, and therefore, kinase-inhibitors are playing an increasingly important role as targeted treatments. Untargeted phosphoproteomics analysis pipelines have been published but show limitations in inferring kinase-activities and identifying potential biomarkers of response and resistance.MethodsWe developed a phosphoproteomics workflow based on titanium dioxide phosphopeptide enrichment with subsequent analysis by liquid chromatography tandem mass spectrometry (LC-MS). We applied a novel Kinase-Activity Enrichment Analysis (KAEA) pipeline on differential phosphoproteomics profiles, which is based on the recently published SetRank enrichment algorithm with reduced false positive rates. Kinase activities were inferred by this algorithm using an extensive reference database comprising five experimentally validated kinase-substrate meta-databases complemented with the NetworKIN in-silico prediction tool. For the proof of concept, we used human myeloid cell lines (K562, NB4, THP1, OCI-AML3, MOLM13 and MV4–11) with known oncogenic drivers and exposed them to clinically established kinase-inhibitors.ResultsBiologically meaningful over- and under-active kinases were identified by KAEA in the unperturbed human myeloid cell lines (K562, NB4, THP1, OCI-AML3 and MOLM13). To increase the inhibition signal of the driving oncogenic kinases, we exposed the K562 (BCR-ABL1) and MOLM13/MV4–11 (FLT3-ITD) cell lines to either Nilotinib or Midostaurin kinase inhibitors, respectively. We observed correct detection of expected direct (ABL, KIT, SRC) and indirect (MAPK) targets of Nilotinib in K562 as well as indirect (PRKC, MAPK, AKT, RPS6K) targets of Midostaurin in MOLM13/MV4–11, respectively. Moreover, our pipeline was able to characterize unexplored kinase-activities within the corresponding signaling networks.ConclusionsWe developed and validated a novel KAEA pipeline for the analysis of differential phosphoproteomics MS profiling data. We provide translational researchers with an improved instrument to characterize the biological behavior of kinases in response or resistance to targeted treatment. Further investigations are warranted to determine the utility of KAEA to characterize mechanisms of disease progression and treatment failure using primary patient samples.Graphical abstract

Integrating site-specific peptide reporters and targeted mass spectrometry enables rapid substrate-specific kinase assay at the nanogram cell level

Dysregulation of phosphorylation-mediated signaling drives the initiation and progression of many diseases. A substrate-specific kinase assay capable of quantifying the altered site-specific phosphorylation of its phenotype-dependent substrates provides better specificity to monitor a disease state. We report a sensitive and rapid substrate-specific kinase assay by integrating site-specific peptide reporter and multiple reaction monitoring (MRM)-MS platform for relative and absolute quantification of substrate-specific kinase activity at the sensitivity of nanomolar kinase and nanogram cell lysate. Using non-small cell lung cancer as a proof-of-concept, three substrate peptides selected from constitutive phosphorylation in tumors (HDGF-S165, RALY-S135, and NRD1-S94) were designed to demonstrate the feasibility. The assay showed good accuracy (<15% nominal deviation) and reproducibility (<15% CV). In PC9 cells, the measured activity for HDGF-S165 was 3.2 ± 0.2 fmol μg−1 min−1, while RALY-S135 and NRD1-S94 showed 4- and 20-fold higher activity at the sensitivity of 25 ng and 5 ng lysate, respectively, suggesting different endogenous kinases for each substrate peptide. Without the conventional shotgun phosphoproteomics workflow, the overall pipeline from cell lysate to MS data acquisition only takes 3 h. The multiplexed analysis revealed differences in the phenotype-dependent substrate phosphorylation profiles across six NSCLC cell lines and suggested a potential association of HDGF-S165 and NRD1-S94 with TKI resistance. With the ease of design, sensitivity, accuracy, and reproducibility, this approach may offer rapid and sensitive assays for targeted quantification of the multiplexed substrate-specific kinase activity of small amounts of sample.

Label-Free Quantitative Phosphoproteomics of the Fission Yeast Schizosaccharomyces pombe Using Strong Anion Exchange- and Porous Graphitic Carbon-Based Fractionation Strategies.

The phosphorylation of proteins modulates various functions of proteins and plays an important role in the regulation of cell signaling. In recent years, label-free quantitative (LFQ) phosphoproteomics has become a powerful tool to analyze the phosphorylation of proteins within complex samples. Despite the great progress, the studies of protein phosphorylation are still limited in throughput, robustness, and reproducibility, hampering analyses that involve multiple perturbations, such as those needed to follow the dynamics of phosphoproteomes. To address these challenges, we introduce here the LFQ phosphoproteomics workflow that is based on Fe-IMAC phosphopeptide enrichment followed by strong anion exchange (SAX) and porous graphitic carbon (PGC) fractionation strategies. We applied this workflow to analyze the whole-cell phosphoproteome of the fission yeast Schizosaccharomyces pombe. Using this strategy, we identified 8353 phosphosites from which 1274 were newly identified. This provides a significant addition to the S. pombe phosphoproteome. The results of our study highlight that combining of PGC and SAX fractionation strategies substantially increases the robustness and specificity of LFQ phosphoproteomics. Overall, the presented LFQ phosphoproteomics workflow opens the door for studies that would get better insight into the complexity of the protein kinase functions of the fission yeast S. pombe.

Iron Deficiency Reprograms Phosphorylation Signaling and Reduces O-GlcNAc Pathways in Neuronal Cells.

Micronutrient sensing is critical for cellular growth and differentiation. Deficiencies in essential nutrients such as iron strongly affect neuronal cell development and may lead to defects in neuronal function that cannot be remedied by subsequent iron supplementation. To understand the adaptive intracellular responses to iron deficiency in neuronal cells, we developed and utilized a Stable Isotopic Labeling of Amino acids in Cell culture (SILAC)-based quantitative phosphoproteomics workflow. Our integrated approach was designed to comprehensively elucidate the changes in phosphorylation signaling under both acute and chronic iron-deficient cell models. In addition, we analyzed the differential cellular responses between iron deficiency and hypoxia (oxygen-deprived) in neuronal cells. Our analysis identified nearly 16,000 phosphorylation sites in HT-22 cells, a hippocampal-derived neuronal cell line, more than ten percent of which showed at least 2-fold changes in response to either hypoxia or acute/chronic iron deficiency. Bioinformatic analysis revealed that iron deficiency altered key metabolic and epigenetic pathways including the phosphorylation of proteins involved in iron sequestration, glutamate metabolism, and histone methylation. In particular, iron deficiency increased glutamine-fructose-6-phosphate transaminase (GFPT1) phosphorylation, which is a key enzyme in the glucosamine biosynthesis pathway and a target of 5′ AMP-activated protein kinase (AMPK), leading to reduced GFPT1 enzymatic activity and consequently lower global O-GlcNAc modification in neuronal cells. Taken together, our analysis of the phosphoproteome dynamics in response to iron and oxygen deprivation demonstrated an adaptive cellular response by mounting post-translational modifications that are critical for intracellular signaling and epigenetic programming in neuronal cells.

Feasibility of Phosphoproteomics on Leftover Samples After RNA Extraction With Guanidinium Thiocyanate

In daily practice, different types of biomolecules are usually extracted for large-scale “omics” analysis with tailored protocols. However, when sample material is limited, an all-in-one strategy is preferable. Although lysis of cells and tissues with urea is widely used for phosphoproteomic applications, DNA, RNA, and proteins can be simultaneously extracted from small samples using acid guanidinium thiocyanate–phenol–chloroform (AGPC). Use of AGPC for mass spectrometry–based phosphoproteomics was reported but has not yet been thoroughly evaluated against a classical phosphoproteomic protocol. Here we compared urea- with AGPC-based protein extraction, profiling phosphorylations in the DNA damage response pathway after ionizing irradiation of U2OS cells as proof of principle. On average we identified circa 9000 phosphosites per sample with both extraction methods. Moreover, we observed high similarity of phosphosite characteristics (e.g., 94% shared class 1 identifications) and deduced kinase activities (e.g., ATM, ATR, CHEK1/2, PRKDC). We furthermore extended our comparison to murine and human tissue samples yielding similar and highly correlated results for both extraction protocols. AGPC-based sample extraction can thus replace common cell lysates for phosphoproteomic workflows and may thus be an attractive way to obtain input material for multiple omics workflows, yielding several data types from a single sample.

Data Processing and Analysis for DIA-Based Phosphoproteomics Using Spectronaut.

Data-independent acquisition (DIA) for liquid chromatography tandem mass spectrometry (LC-MS/MS) can improve the depth and reproducibility of the acquired proteomics datasets. DIA solves some limitations of the conventional data-dependent acquisition (DDA) strategy, for example, bias in intensity-dependent precursor selection and limited dynamic range. These advantages, together with the recent developments in speed, sensitivity, and resolution in MS technology, position DIA as a great alternative to DDA. Recently, we demonstrated that the benefits of DIA are extendable to phosphoproteomics workflows, enabling increased depth, sensitivity, and reproducibility of our analysis of phosphopeptide-enriched samples. However, computational data analysis of phospho-DIA samples have some specific challenges and requirements to the software and downstream processing workflows. A step-by-step guide to analyze phospho-DIA raw data using either spectral libraries or directDIA in Spectronaut is presented here. Furthermore, a straightforward protocol to perform differential phosphorylation site analysis using the output results from Spectronaut is described.

Global Phosphoproteome Analysis Using High-Field Asymmetric Waveform Ion Mobility Spectrometry on a Hybrid Orbitrap Mass Spectrometer.

Mass spectrometry is the premier tool for identifying and quantifying protein phosphorylation on a global scale. Analysis of phosphopeptides requires enrichment, and even after the samples remain highly complex and exhibit broad dynamic range of abundance. Achieving maximal depth of coverage for phosphoproteomics therefore typically necessitates offline liquid chromatography prefractionation, a time-consuming and laborious approach. Here, we incorporate a recently commercialized aerodynamic high-field asymmetric waveform ion mobility spectrometry (FAIMS) device into the phosphoproteomic workflow. We characterize the effects of phosphorylation on the FAIMS separation, describe optimized compensation voltage settings for unlabeled phosphopeptides, and demonstrate the advantages of FAIMS-enabled gas-phase fractionation. Standard FAIMS single-shot analyses identified around 15-20% additional phosphorylation sites than control experiments without FAIMS. In comparison to liquid chromatography prefractionation, FAIMS experiments yielded similar or superior results when analyzing up to four discrete gas-phase fractions. Although using FAIMS led to a modest reduction in the precision of quantitative measurements when using label-free approaches, the data collected with FAIMS yielded a 26% increase in total reproducible measurements. Overall, we conclude that the new FAIMS technology is a valuable addition to any phosphoproteomic workflow, with greater benefits emerging from longer analyses and higher amounts of material.

Widespread arginine phosphorylation in human cells—a novel protein PTM revealed by mass spectrometry

Arginine phosphorylation (pArg) is recently discovered as a ubiquitous protein N-phosphorylation in bacteria. However, its prevalence and roles in mammalian cells remain largely unknown due to the lack of established workflow and the inherent lability of phosphoramidate (P–N) bond. Emerging evidences suggest that N-phosphorylation may extensively exist in eu-karyotes and play crucial roles. We report a phosphoproteomic workflow, which allows for the first time revealing the widespread occurrence of pArg in human cells by mass spectrometry. By virtue of this approach, we identified 152 high-confidence pArg sites derived from 118 proteins. Remarkably, the discovered pArg phosphorylation motif and gene ontology hint a possible cellular function of arginine phosphorylation which may regulate the favorability of propeptide convertase substrate. The obtained pArg dataset paves a way for a better understanding of the biological functions of eukaryotic pArg in the future.