Super-SILAC mix for quantitative proteomics of human tumor tissue. Nat Methods. 2010;7:383-385. [PMID: 20364148 DOI: 10.1038/nmeth.1446]

Mass Spectrometry-Based Proteomics for Assessing Epitranscriptomic Regulations

Epitranscriptomics is a rapidly evolving field that explores chemical modifications in RNA and how they contribute to dynamic and reversible regulations of gene expression. These modifications, for example, N6-methyladenosine (m6A), are crucial in various RNA metabolic processes, including splicing, stability, subcellular localization, and translation efficiency of mRNAs. Mass spectrometry-based proteomics has become an indispensable tool in unraveling the complexities of epitranscriptomics, offering high-throughput, precise protein identification, and accurate quantification of differential protein expression. Over the past two decades, advances in mass spectrometry, including the improvement of high-resolution mass spectrometers and innovative sample preparation methods, have allowed researchers to perform in-depth analyses of epitranscriptomic regulations. This review focuses on the applications of bottom-up proteomics in the field of epitranscriptomics, particularly in identifying and quantifying epitranscriptomic reader, writer, and eraser (RWE) proteins and in characterizing their functions, posttranslational modifications, and interactions with other proteins. Together, by leveraging modern proteomics, researchers can gain deep insights into the intricate regulatory networks of RNA modifications, advancing fundamental biology, and fostering potential therapeutic applications.

Skeletal Editing by Hypervalent Iodine Mediated Nitrogen Insertion

Hypervalent iodine reagents are versatile and readily accessible reagents that have been extensively applied in contemporary synthesis in modern organic chemistry. Among them, iodonitrene (ArI=NR), is a powerful reactive species, widely used for a single-nitrogen-atom insertion reaction, and skeletal editing to construct N-heterocycles. Skeletal editing with reactive iodonitrene components has recently emerged as an exciting approach in modern chemical transformation. These reagents have been extensively used to produce biologically relevant heterocycles and functionalized molecular architectures. Recently, the insertion of a nitrogen-atom into hydrocarbons to generate N-heterocyclic compounds using hypervalent iodine reagents has been a significant focus in the field of molecular editing reactions. In this review, we discuss the rapidly emerging field of nitrene insertion, including skeletal editing and nitrogen insertion, using hypervalent iodine reagents to access nitrogen-containing heterocycles, and the current mechanistic understanding of these processes.

Fe-S cluster biosynthesis and maturation: Mass spectrometry-based methods advancing the field

Iron‑sulfur (FeS) clusters are inorganic protein cofactors that perform essential functions in many physiological processes. Spectroscopic techniques have historically been used to elucidate details of FeS cluster type, their assembly and transfer, and changes in redox and ligand binding properties. Structural probes of protein topology, complex formation, and conformational dynamics are also necessary to fully understand these FeS protein systems. Recent developments in mass spectrometry (MS) instrumentation and methods provide new tools to investigate FeS cluster and structural properties. With the unique advantage of sampling all species in a mixture, MS-based methods can be utilized as a powerful complementary approach to probe native dynamic heterogeneity, interrogate protein folding and unfolding equilibria, and provide extensive insight into protein binding partners within an entire proteome. Here, we highlight key advances in FeS protein studies made possible by MS methodology and contribute an outlook for its role in the field.

Combining Data Independent Acquisition With Spike-In SILAC (DIA-SiS) Improves Proteome Coverage and Quantification

Data-independent acquisition (DIA) is increasingly preferred over data-dependent acquisition due to its higher throughput and fewer missing values. Whereas data-dependent acquisition often uses stable isotope labeling to improve quantification, DIA mostly relies on label-free approaches. Efforts to integrate DIA with isotope labeling include chemical methods like mass differential tags for relative and absolute quantification and dimethyl labeling, which, while effective, complicate sample preparation. Stable isotope labeling by amino acids in cell culture (SILAC) achieves high labeling efficiency through the metabolic incorporation of heavy labels into proteins in vivo. However, the need for metabolic incorporation limits the direct use in clinical scenarios and certain high-throughput experiments. Spike-in SILAC (SiS) methods use an externally generated heavy sample as an internal reference, enabling SILAC-based quantification even for samples that cannot be directly labeled. Here, we combine DIA-SiS, leveraging the robust quantification of SILAC without the complexities associated with chemical labeling. We developed DIA-SiS and rigorously assessed its performance with mixed-species benchmark samples on bulk and single cell-like amount level. We demonstrate that DIA-SiS substantially improves proteome coverage and quantification compared to label-free approaches and reduces incorrectly quantified proteins. Additionally, DIA-SiS proves effective in analyzing proteins in low-input formalin-fixed paraffin-embedded tissue sections. DIA-SiS combines the precision of stable isotope-based quantification with the simplicity of label-free sample preparation, facilitating simple, accurate, and comprehensive proteome profiling.

Dual-species proteomics and targeted intervention of animal-pathogen interactions

INTRODUCTION

Host-microbe interactions are important to human health and ecosystems globally, so elucidating the complex host-microbe interactions and associated protein expressions drives the need to develop sensitive and accurate biochemical techniques. Current proteomics techniques reveal information from the point of view of either the host or microbe, but do not provide data on the corresponding partner. Moreover, it remains challenging to simultaneously study host-microbe proteomes that reflect the direct competition between host and microbe. This raises the need to develop a dual-species proteomics method for host-microbe interactions.

OBJECTIVES

We aim to establish a forward + reverse Stable Isotope Labeling with Amino acids in Cell culture (SILAC) proteomics approach to simultaneously label and quantify newly-expressed proteins of host and microbe without physical isolation, for investigating mechanisms in direct host-microbe interactions.

METHODS

Using Caenorhabditis elegans-Pseudomonas aeruginosa infection model as proof-of-concept, we employed SILAC proteomics and molecular pathway analysis to characterize the differentially-expressed microbial and host proteins. We then used molecular docking and chemical characterization to identify chemical inhibitors that intercept host-microbe interactions and eliminate microbial infection.

RESULTS

Based on our proteomics results, we studied the iron competition between pathogen iron scavenger and host iron uptake protein, where P. aeruginosa upregulated pyoverdine synthesis protein (PvdA) (fold-change of 5.2313) and secreted pyoverdine, and C. elegans expressed ferritin (FTN-2) (fold-change of 3.4057). Targeted intervention of iron competition was achieved using Galangin, a ginger-derived phytochemical that inhibited pyoverdine production and biofilm formation in P. aeruginosa. The Galangin-ciprofloxacin combinatorial therapy could eliminate P. aeruginosa biofilms in a fish wound infection model, and enabled animal survival.

CONCLUSION

Our work provides a novel SILAC-based proteomics method that can simultaneously evaluate host and microbe proteomes, with future applications in higher host organisms and other microbial species. It also provides insights into the mechanisms dictating host-microbe interactions, offering novel strategies for anti-infective therapy.

Mass spectrometry for the study of adipocyte cell secretome in cardiovascular diseases

Adipose tissue is classically considered the primary site of lipid storage, but in recent years has garnered appreciation for its broad role as an endocrine organ, capable of remotely signaling to other tissues to alter their metabolic program. The adipose tissue is now recognized as a crucial regulator of cardiovascular health, mediated by the secretion of several bioactive products, with a wide range of endocrine and paracrine effects on the cardiovascular system. Thanks to the development and improvement of high-throughput mass spectrometry, the size and components of the human secretome have been characterized. In this review, we summarized the recent advances in mass spectrometry-based studies of the cell and tissue secretome for the understanding of adipose tissue biology, which may help to decipher the complex molecular mechanisms controlling the crosstalk between the adipose tissue and the cardiovascular system, and their possible clinical translation.

An optimized and robust workflow for quantifying the canonical histone ubiquitination marks H2AK119ub and H2BK120ub by LC-MS/MS

The eukaryotic genome is packaged around histone proteins, which are subject to a myriad of post-translational modifications. By controlling DNA accessibility and the recruitment of protein complexes that mediate chromatin-related processes, these modifications constitute a key mechanism of epigenetic regulation. Since mass spectrometry can easily distinguish between these different modifications, it has become an essential technique in deciphering the histone code. Although robust LC-MS/MS methods are available to analyze modifications on the histone N-terminal tails, routine methods for characterizing ubiquitin marks on histone C-terminal regions, especially H2AK119ub, are less robust. Here we report the development of a simple workflow for the detection and improved quantification of the canonical histone ubiquitination marks H2AK119ub and H2BK120ub. The method entails a fully tryptic digestion of acid-extracted histones followed by derivatization with heavy or light propionic anhydride. A pooled sample is then spiked into oppositely labeled single samples as a reference channel for relative quantification, and data is acquired using PRM-based nanoLC-MS/MS. We validated our approach with synthetic peptides as well as treatments known to modulate the levels of H2AK119ub and H2BK120ub. This new method complements existing histone workflows, largely focused on the lysine-rich N-terminal regions, by extending modification analysis to other sequence contexts.

Progression of monoclonal gammopathy of undetermined significance to multiple myeloma is associated with enhanced translational quality control and overall loss of surface antigens

BACKGROUND

Despite significant advancements in treatment strategies, multiple myeloma remains incurable. Additionally, there is a distinct lack of reliable biomarkers that can guide initial treatment decisions and help determine suitable replacement or adjuvant therapies when relapse ensues due to acquired drug resistance.

METHODS

To define specific proteins and pathways involved in the progression of monoclonal gammopathy of undetermined significance (MGUS) to multiple myeloma (MM), we have applied super-SILAC quantitative proteomic analysis to CD138 + plasma cells from 9 individuals with MGUS and 37 with MM.

RESULTS

Unsupervised hierarchical clustering defined three groups: MGUS, MM, and MM with an MGUS-like proteome profile (ML) that may represent a group that has recently transformed to MM. Statistical analysis identified 866 differentially expressed proteins between MM and MGUS, and 189 between MM and ML, 177 of which were common between MGUS and ML. Progression from MGUS to MM is accompanied by upregulated EIF2 signaling, DNA repair, and proteins involved in translational quality control, whereas integrin- and actin cytoskeletal signaling and cell surface markers are downregulated.

CONCLUSION

Compared to the premalignant plasma cells in MGUS, malignant MM cells apparently have mobilized several pathways that collectively contribute to ensure translational fidelity and to avoid proteotoxic stress, especially in the ER. The overall reduced expression of immunoglobulins and surface antigens contribute to this and may additionally mediate evasion from recognition by the immune apparatus. Our analyses identified a range of novel biomarkers with potential prognostic and therapeutic value, which will undergo further evaluation to determine their clinical significance.

Proteogenomic Characterization of Bladder Cancer Reveals Sensitivity to Apoptosis Induced by Tumor Necrosis Factor-related Apoptosis-inducing Ligand in FGFR3-mutated Tumors

BACKGROUND

Molecular understanding of muscle-invasive (MIBC) and non-muscle-invasive (NMIBC) bladder cancer is currently based primarily on transcriptomic and genomic analyses.

OBJECTIVE

To conduct proteogenomic analyses to gain insights into bladder cancer (BC) heterogeneity and identify underlying processes specific to tumor subgroups and therapeutic outcomes.

DESIGN, SETTING, AND PARTICIPANTS

Proteomic data were obtained for 40 MIBC and 23 NMIBC cases for which transcriptomic and genomic data were already available. Four BC-derived cell lines harboring FGFR3 alterations were tested with interventions.

INTERVENTION

Recombinant tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), second mitochondrial-derived activator of caspases mimetic (birinapant), pan-FGFR inhibitor (erdafitinib), and FGFR3 knockdown.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Proteomic groups from unsupervised analyses (uPGs) were characterized using clinicopathological, proteomic, genomic, transcriptomic, and pathway enrichment analyses. Additional enrichment analyses were performed for FGFR3-mutated tumors. Treatment effects on cell viability for FGFR3-altered cell lines were evaluated. Synergistic treatment effects were evaluated using the zero interaction potency model.

RESULTS AND LIMITATIONS

Five uPGs, covering both NMIBC and MIBC, were identified and bore coarse-grained similarity to transcriptomic subtypes underlying common features of these different entities; uPG-E was associated with the Ta pathway and enriched in FGFR3 mutations. Our analyses also highlighted enrichment of proteins involved in apoptosis in FGFR3-mutated tumors, not captured through transcriptomics. Genetic and pharmacological inhibition demonstrated that FGFR3 activation regulates TRAIL receptor expression and sensitizes cells to TRAIL-mediated apoptosis, further increased by combination with birinapant.

CONCLUSIONS

This proteogenomic study provides a comprehensive resource for investigating NMIBC and MIBC heterogeneity and highlights the potential of TRAIL-induced apoptosis as a treatment option for FGFR3-mutated bladder tumors, warranting a clinical investigation.

PATIENT SUMMARY

We integrated proteomics, genomics, and transcriptomics to refine molecular classification of bladder cancer, which, combined with clinical and pathological classification, should lead to more appropriate management of patients. Moreover, we identified new biological processes altered in FGFR3-mutated tumors and showed that inducing apoptosis represents a new potential therapeutic option.

Robust dimethyl-based multiplex-DIA doubles single-cell proteome depth via a reference channel

Single-cell proteomics aims to characterize biological function and heterogeneity at the level of proteins in an unbiased manner. It is currently limited in proteomic depth, throughput, and robustness, which we address here by a streamlined multiplexed workflow using data-independent acquisition (mDIA). We demonstrate automated and complete dimethyl labeling of bulk or single-cell samples, without losing proteomic depth. Lys-N digestion enables five-plex quantification at MS1 and MS2 level. Because the multiplexed channels are quantitatively isolated from each other, mDIA accommodates a reference channel that does not interfere with the target channels. Our algorithm RefQuant takes advantage of this and confidently quantifies twice as many proteins per single cell compared to our previous work (Brunner et al, PMID 35226415), while our workflow currently allows routine analysis of 80 single cells per day. Finally, we combined mDIA with spatial proteomics to increase the throughput of Deep Visual Proteomics seven-fold for microdissection and four-fold for MS analysis. Applying this to primary cutaneous melanoma, we discovered proteomic signatures of cells within distinct tumor microenvironments, showcasing its potential for precision oncology.

Recent progress in quantitative phosphoproteomics

INTRODUCTION

Protein phosphorylation is a critical post-translational modification involved in the regulation of numerous cellular processes from signal transduction to modulation of enzyme activities. Knowledge of dynamic changes of phosphorylation levels during biological processes, under various treatments or between healthy and disease models is fundamental for understanding the role of each phosphorylation event. Thereby, LC-MS/MS based technologies in combination with quantitative proteomics strategies evolved as a powerful strategy to investigate the function of individual protein phosphorylation events.

AREAS COVERED

State-of-the-art labeling techniques including stable isotope and isobaric labeling provide precise and accurate quantification of phosphorylation events. Here, we review the strengths and limitations of recent quantification methods and provide examples based on current studies, how quantitative phosphoproteomics can be further optimized for enhanced analytic depth, dynamic range, site localization, and data integrity. Specifically, reducing the input material demands is key to a broader implementation of quantitative phosphoproteomics, not least for clinical samples.

EXPERT OPINION

Despite quantitative phosphoproteomics is one of the most thriving fields in the proteomics world, many challenges still have to be overcome to facilitate even deeper and more comprehensive analyses as required in the current research, especially at single cell levels and in clinical diagnostics.

Mass Spectrometry Contribution to Pediatric Cancers Research

For over four decades, mass spectrometry-based methods have provided a wealth of information relevant to various challenges in the field of cancers research. These challenges included identification and validation of novel biomarkers for various diseases, in particular for various forms of cancer. These biomarkers serve various objectives including monitoring patient response to the various forms of therapy, differentiating subgroups of the same type of cancer, and providing proteomic data to complement datasets generated by genomic, epigenetic, and transcriptomic methods. The same proteomic data can be used to provide prognostic information and could guide scientists and medics to new and innovative targeted therapies The past decade has seen a rapid emergence of epigenetics as a major contributor to carcinogenesis. This development has given a fresh momentum to MS-based proteomics, which demonstrated to be an unrivalled tool for the analyses of protein post-translational modifications associated with chromatin modifications. In particular, high-resolution mass spectrometry has been recently used for systematic quantification of chromatin modifications. Data generated by this approach are central in the search for new therapies for various forms of cancer and will help in attempts to decipher antitumor drug resistance. To appreciate the contribution of mass spectrometry-based proteomics to biomarkers discovery and to our understanding of mechanisms behind the initiation and progression of various forms of cancer, a number of recent investigations are discussed. These investigations also include results provided by two-dimensional gel electrophoresis combined with mass spectrometry.

Nitrogen atom insertion into indenes to access isoquinolines

We report a convenient protocol for a nitrogen atom insertion into indenes to afford isoquinolines. The reaction uses a combination of commercially available phenyliodine(iii) diacetate (PIDA) and ammonium carbamate as the nitrogen source to furnish a wide range of isoquinolines. Various substitution patterns and commonly used functional groups are well tolerated. The operational simplicity renders this protocol broadly applicable and has been successfully extended towards the direct interconversion of cyclopentadienes into the corresponding pyridines. Furthermore, this strategy enables the facile synthesis of ¹⁵N labelled isoquinolines, using ¹⁵NH₄Cl as a commercial ¹⁵N source.

Recent advances in mass spectrometry analysis of neuropeptides

Due to their involvement in numerous biochemical pathways, neuropeptides have been the focus of many recent research studies. Unfortunately, classic analytical methods, such as western blots and enzyme-linked immunosorbent assays, are extremely limited in terms of global investigations, leading researchers to search for more advanced techniques capable of probing the entire neuropeptidome of an organism. With recent technological advances, mass spectrometry (MS) has provided methodology to gain global knowledge of a neuropeptidome on a spatial, temporal, and quantitative level. This review will cover key considerations for the analysis of neuropeptides by MS, including sample preparation strategies, instrumental advances for identification, structural characterization, and imaging; insightful functional studies; and newly developed absolute and relative quantitation strategies. While many discoveries have been made with MS, the methodology is still in its infancy. Many of the current challenges and areas that need development will also be highlighted in this review.

Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice

Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.

Evaluation of Quantification and Normalization Strategies for Phosphoprotein Phosphatase Affinity Proteomics: Application to Breast Cancer Signaling

Accurate quantification of proteomics data is essential for revealing and understanding biological signaling processes. We have recently developed a chemical proteomic strategy termed phosphatase inhibitor beads and mass spectrometry (PIB-MS) to investigate endogenous phosphoprotein phosphatase (PPP) dephosphorylation signaling. Here, we compare the robustness and reproducibility of status quo quantification methods for optimal performance and ease of implementation. We then apply PIB-MS to an array of breast cancer cell lines to determine differences in PPP signaling between subtypes. Breast cancer, a leading cause of cancer death in women, consists of three main subtypes: estrogen receptor-positive (ER+), human epidermal growth factor receptor two positive (HER2+), and triple-negative (TNBC). Although there are effective treatment strategies for ER+ and HER2+ subtypes, tumors become resistant and progress. Furthermore, TNBC has few targeted therapies. Therefore, there is a need to identify new approaches for treating breast cancers. Using PIB-MS, we distinguished TNBC from non-TNBC based on subtype-specific PPP holoenzyme composition. In addition, we identified an increase in PPP interactions with Hippo pathway proteins in TNBC. These interactions suggest that phosphatases in TNBC play an inhibitory role on the Hippo pathway and correlate with increased expression of YAP/TAZ target genes both in TNBC cell lines and in TNBC patients.

Mitochondrial Aconitase ACO2 Links Iron Homeostasis with Tumorigenicity in Non-Small Cell Lung Cancer

The ability of a patient tumor to engraft an immunodeficient mouse is the strongest known independent indicator of poor prognosis in early-stage non-small cell lung cancer (NSCLC). Analysis of primary NSCLC proteomes revealed low-level expression of mitochondrial aconitase (ACO2) in the more aggressive, engrafting tumors. Knockdown of ACO2 protein expression transformed immortalized lung epithelial cells, whereas upregulation of ACO2 in transformed NSCLC cells inhibited cell proliferation in vitro and tumor growth in vivo. High level ACO2 increased iron response element binding protein 1 (IRP1) and the intracellular labile iron pool. Impaired cellular proliferation associated with high level ACO2 was reversed by treatment of cells with an iron chelator, whereas increased cell proliferation associated with low level ACO2 was suppressed by treatment of cells with iron. Expression of CDGSH iron-sulfur (FeS) domain-containing protein 1 [CISD1; also known as mitoNEET (mNT)] was modulated by ACO2 expression level and inhibition of mNT by RNA interference or by treatment of cells with pioglitazone also increased iron and cell death. Hence, ACO2 is identified as a regulator of iron homeostasis and mNT is implicated as a target in aggressive NSCLC.

IMPLICATIONS

FeS cluster-associated proteins including ACO2, mNT (encoded by CISD1), and IRP1 (encoded by ACO1) are part of an "ACO2-Iron Axis" that regulates iron homeostasis and is a determinant of a particularly aggressive subset of NSCLC.

Analysis of proteome adaptation reveals a key role of the bacterial envelope in starvation survival

Bacteria reorganize their physiology upon entry to stationary phase. What part of this reorganization improves starvation survival is a difficult question because the change in physiology includes a global reorganization of the proteome, envelope, and metabolism of the cell. In this work, we used several trade-offs between fast growth and long survival to statistically score over 2,000 Escherichia coli proteins for their global correlation with death rate. The combined ranking allowed us to narrow down the set of proteins that positively correlate with survival and validate the causal role of a subset of proteins. Remarkably, we found that important survival genes are related to the cell envelope, i.e., periplasm and outer membrane, because the maintenance of envelope integrity of E. coli plays a crucial role during starvation. Our results uncover a new protective feature of the outer membrane that adds to the growing evidence that the outer membrane is not only a barrier that prevents abiotic substances from reaching the cytoplasm but also essential for bacterial proliferation and survival.

Radiation-Induced Intestinal Normal Tissue Toxicity: Implications for Altered Proteome Profile

Radiation-induced toxicity to healthy/normal intestinal tissues, especially during radiotherapy, limits the radiation dose necessary to effectively eradicate tumors of the abdomen and pelvis. Although the pathogenesis of intestinal radiation toxicity is highly complex, understanding post-irradiation alterations in protein profiles can provide crucial insights that make radiotherapy safer and more efficient and allow for increasing the radiation dose during cancer treatment. Recent preclinical and clinical studies have advanced our current understanding of the molecular changes associated with radiation-induced intestinal damage by assessing changes in protein expression with mass spectrometry-based approaches and 2-dimensional difference gel electrophoresis. Studies by various groups have demonstrated that proteins that are involved in the inflammatory response, the apoptotic pathway, reactive oxygen species scavenging, and cell proliferation can be targeted to develop effective radiation countermeasures. Moreover, altered protein profiles serve as a crucial biomarkers for intestinal radiation damage. In this review, we present alterations in protein signatures following intestinal radiation damage as detected by proteomics approaches in preclinical and clinical models with the aim of providing a better understanding of how to accomplish intestinal protection against radiation damage.

Methods to improve quantitative glycoprotein coverage from bottom-up LC-MS data

Advances in mass spectrometry instrumentation, methods development, and bioinformatics have greatly improved the ease and accuracy of site-specific, quantitative glycoproteomics analysis. Data-dependent acquisition is the most popular method for identification and quantification of glycopeptides; however, complete coverage of glycosylation site glycoforms remains elusive with this method. Targeted acquisition methods improve the precision and accuracy of quantification, but at the cost of throughput and discoverability. Data-independent acquisition (DIA) holds great promise for more complete and highly quantitative site-specific glycoproteomics analysis, while maintaining the ability to discover novel glycopeptides without prior knowledge. We review additional features that can be used to increase selectivity and coverage to the DIA workflow: retention time modeling, which would simplify the interpretation of complex tandem mass spectra, and ion mobility separation, which would maximize the sampling of all precursors at a giving chromatographic retention time. The instrumentation and bioinformatics to incorporate these features into glycoproteomics analysis exist. These improvements in quantitative, site-specific analysis will enable researchers to assess glycosylation similarity in related biological systems, answering new questions about the interplay between glycosylation state and biological function.

Erythropoietin-driven dynamic proteome adaptations during erythropoiesis prevent iron overload in the developing embryo

Erythropoietin (Epo) ensures survival and proliferation of colony-forming unit erythroid (CFU-E) progenitor cells and their differentiation to hemoglobin-containing mature erythrocytes. A lack of Epo-induced responses causes embryonic lethality, but mechanisms regulating the dynamic communication of cellular alterations to the organismal level remain unresolved. By time-resolved transcriptomics and proteomics, we show that Epo induces in CFU-E cells a gradual transition from proliferation signature proteins to proteins indicative for differentiation, including heme-synthesis enzymes. In the absence of the Epo receptor (EpoR) in embryos, we observe a lack of hemoglobin in CFU-E cells and massive iron overload of the fetal liver pointing to a miscommunication between liver and placenta. A reduction of iron-sulfur cluster-containing proteins involved in oxidative phosphorylation in these embryos leads to a metabolic shift toward glycolysis. This link connecting erythropoiesis with the regulation of iron homeostasis and metabolic reprogramming suggests that balancing these interactions is crucial for protection from iron intoxication and for survival.

An overview of tools to decipher O-GlcNAcylation from historical approaches to new insights

O-GlcNAcylation is a post-translational modification which affects approximately 5000 human proteins. Its involvement has been shown in many if not all biological processes. Variations in O-GlcNAcylation levels can be associated with the development of diseases. Deciphering the role of O-GlcNAcylation is an important issue to (i) understand its involvement in pathophysiological development and (ii) develop new therapeutic strategies to modulate O-GlcNAc levels. Over the past 30 years, despite the development of several approaches, knowledge of its role and regulation have remained limited. This review proposes an overview of the currently available tools to study O-GlcNAcylation and identify O-GlcNAcylated proteins. Briefly, we discuss pharmacological modulators, methods to study O-GlcNAcylation levels and approaches for O-GlcNAcylomic profiling. This review aims to contribute to a better understanding of the methods used to study O-GlcNAcylation and to promote efforts in the development of new strategies to explore this promising modification.

Advances in stable isotope labeling: dynamic labeling for spatial and temporal proteomic analysis

The field of proteomics is continually improving, requiring the development of new quantitative methods. Stable isotope labeling in cell culture (SILAC) is a metabolic labeling technique originating in the early 2000s. By incorporating isotopically labeled amino acids into the media used for cell culture, unlabeled versus labeled cells can be differentiated by the mass spectrometer. Traditional SILAC labeling has been expanded to pulsed applications allowing for a new quantitative dimension of proteomics - temporal analysis. The complete introduction of Heavy SILAC labeling chased with surplus unlabeled medium mimics traditional pulse-chase experiments and allows for the loss of heavy signal to track proteomic changes over time. In a similar fashion, pulsed SILAC (pSILAC) monitors the initial incorporation of a heavy label across a period of time, which allows for the rate of protein label integration to be assessed. These innovative techniques have aided in inspiring numerous SILAC-based temporal and spatial labeling applications, including super SILAC, spike-in SILAC, spatial SILAC, and a revival in label multiplexing. This review reflects upon the evolution of SILAC and the pulsed SILAC application, introduces advances in SILAC labeling, and proposes future perspectives for this novel and exciting field.

Comparative Assessment of Quantification Methods for Tumor Tissue Phosphoproteomics

With increasing sensitivity and accuracy in mass spectrometry, the tumor phosphoproteome is getting into reach. However, the selection of quantitation techniques best-suited to the biomedical question and diagnostic requirements remains a trial and error decision as no study has directly compared their performance for tumor tissue phosphoproteomics. We compared label-free quantification (LFQ), spike-in-SILAC (stable isotope labeling by amino acids in cell culture), and tandem mass tag (TMT) isobaric tandem mass tags technology for quantitative phosphosite profiling in tumor tissue. Compared to the classic SILAC method, spike-in-SILAC is not limited to cell culture analysis, making it suitable for quantitative analysis of tumor tissue samples. TMT offered the lowest accuracy and the highest precision and robustness toward different phosphosite abundances and matrices. Spike-in-SILAC offered the best compromise between these features but suffered from a low phosphosite coverage. LFQ offered the lowest precision but the highest number of identifications. Both spike-in-SILAC and LFQ presented susceptibility to matrix effects. Match between run (MBR)-based analysis enhanced the phosphosite coverage across technical replicates in LFQ and spike-in-SILAC but further reduced the precision and robustness of quantification. The choice of quantitative methodology is critical for both study design such as sample size in sample groups and quantified phosphosites and comparison of published cancer phosphoproteomes. Using ovarian cancer tissue as an example, our study builds a resource for the design and analysis of quantitative phosphoproteomic studies in cancer research and diagnostics.

The proteogenomic subtypes of acute myeloid leukemia

Acute myeloid leukemia (AML) is an aggressive blood cancer with a poor prognosis. We report a comprehensive proteogenomic analysis of bone marrow biopsies from 252 uniformly treated AML patients to elucidate the molecular pathophysiology of AML in order to inform future diagnostic and therapeutic approaches. In addition to in-depth quantitative proteomics, our analysis includes cytogenetic profiling and DNA/RNA sequencing. We identify five proteomic AML subtypes, each reflecting specific biological features spanning genomic boundaries. Two of these proteomic subtypes correlate with patient outcome, but none is exclusively associated with specific genomic aberrations. Remarkably, one subtype (Mito-AML), which is captured only in the proteome, is characterized by high expression of mitochondrial proteins and confers poor outcome, with reduced remission rate and shorter overall survival on treatment with intensive induction chemotherapy. Functional analyses reveal that Mito-AML is metabolically wired toward stronger complex I-dependent respiration and is more responsive to treatment with the BCL2 inhibitor venetoclax.

Understanding the effect of carrier proteomes in single cell proteomic studies - key lessons

INTRODUCTION

Mass spectrometry based single cell proteomics (scMS) is experiencing rapid evolution due to the increased sensitivity of mass spectrometers as well as advances in multiplexing and sample preparation. To date, researchers have focused on two general approaches to scMS: label free and isobaric label based multiplexing. While label free analysis provides straightforward sample preparation and a clear path to automation, it currently lacks the throughput necessary to practically analyze thousands of single cells. Multiplexed analysis utilizing isobaric labels requires additional sample manipulation, but increases throughput such that analyzing thousands of cells is currently achievable. A key feature of multiplexed scMS experiments is a 'carrier proteome' - a sample added at 25x-500x the single cell samples that increases the number of proteins that can be identified in an MS analysis.

AREAS COVERED

Here, we review early examples of carrier proteomes in quantitative proteomics before summarizing advantages and challenges of using a carrier proteome in scMS experiments.

EXPERT OPINION

We conclude that the addition of carrier proteomes improves depth of identification for scMS, but high levels of carrier proteomes can have adverse effects on quantitative accuracy and precision.

Proteomic analysis in primary T cells reveals IL-7 alters T cell receptor thresholding via CYTIP/cytohesin/LFA-1 localisation and activation

The ability of the cellular immune system to discriminate self from foreign antigens depends on the appropriate calibration of the T cell receptor (TCR) signalling threshold. The lymphocyte homeostatic cytokine interleukin 7 (IL-7) is known to affect TCR thresholding, but the molecular mechanism is not fully elucidated. A better understanding of this process is highly relevant in the context of autoimmune disease therapy and cancer immunotherapy. We sought to characterise the early signalling events attributable to IL-7 priming; in particular, the altered phosphorylation of signal transduction proteins and their molecular localisation to the TCR. By integrating high-resolution proximity- phospho-proteomic and imaging approaches using primary T cells, rather than engineered cell lines or an in vitro expanded T cell population, we uncovered transduction events previously not linked to IL-7. We show that IL-7 leads to dephosphorylation of cytohesin interacting protein (CYTIP) at a hitherto undescribed phosphorylation site (pThr280) and alters the co-localisation of cytohesin-1 with the TCR and LFA-1 integrin. These results show that IL-7, acting via CYTIP and cytohesin-1, may impact TCR activation thresholds by enhancing the co-clustering of TCR and LFA-1 integrin.

New advances in quantitative proteomics research and current applications in asthma

INTRODUCTION

Asthma is the most common chronic respiratory disease and has been declared a global public health problem by the World Health Organization. Due to the high heterogeneity and complexity, asthma can be classified into different 'phenotypes' and it is still difficult to assess the phenotypes and stages of asthma by traditional methods. In recent years, mass spectrometry-based proteomics studies have made significant progress in sensitivity and accuracy of protein identification and quantitation, and are able to obtain differences in protein expression across samples, which provides new insights into the mechanisms and classification of asthma.

AREAS COVERED

In this article, we summarize research strategies in quantitative proteomics, including labeled, label-free and targeted quantification, and highlight the advantages and disadvantages of each. In addition, new applications of quantitative proteomics and the current status of research in asthma have also been discussed. In this study, online resources such as PubMed and Google Scholar were used for literature retrieval.

EXPERT OPINION

The application of quantitative proteomics in asthma has an important role in identifying asthma subphenotypes, revealing potential pathogenesis and therapeutic targets. But the proteomic studies on asthma are not sufficient, as most of them are in the phase of biomarker discovery.

SMG1 and CDK12 Link ΔNp63α Phosphorylation to RNA Surveillance in Keratinocytes

The tumor suppressor p53-like protein p63 is required for self-renewal of epidermal tissues. Loss of p63 or exposure to ultraviolet (UV) irradiation triggers terminal differentiation in keratinocytes. However, it remains unclear how p63 diverts epidermal cells from proliferation to terminal differentiation, thereby contributing to successful tissue self-renewal. Here, we used bottom-up proteomics to identify the proteome at the chromatin in normal human epidermal keratinocytes following UV irradiation and p63 depletion. We found that loss of p63 increased DNA damage and that UV irradiation recruited the cyclin-dependent kinase CDK12 and the serine/threonine protein kinase SMG1 to chromatin only in the presence of p63. A post-translational modification analysis of ΔNp63α with mass spectrometry revealed that phosphorylation of T357/S358 and S368 was dependent on SMG1, whereas CDK12 increased the phosphorylation of ΔNp63α at S66/S68 and S301. Indirect phosphorylation of ΔNp63α in the presence of SMG1 enabled ΔNp63α to bind to the tumor suppressor p53-specific DNA recognition sequence, whereas CDK12 rendered ΔNp63α less responsive to UV irradiation and was not required for specific DNA binding. CDK12 and SMG1 are known to regulate the transcription and splicing of RNAs and the decay of nonsense RNAs, respectively, and a subset of p63-specific protein-protein interactions at the chromatin also linked p63 to RNA transcription and decay. We observed that in the absence of p63, UV irradiation resulted in more ORF1p. ORF1p is the first protein product of the intronless non-LTR retrotransposon LINE-1, indicating a derailed surveillance of RNA processing and/or translation. Our results suggest that p63 phosphorylation and transcriptional activation might correspond to altered RNA processing and/or translation to protect proliferating keratinocytes from increased genotoxic stress.

Temporal Proteomic Profiling During Differentiation of Normal and Dystrophin-Deficient Human Muscle Cells

BACKGROUND

Myogenesis is a dynamic process involving temporal changes in the expression of many genes. Lack of dystrophin protein such as in Duchenne muscular dystrophy might alter the natural course of gene expression dynamics during myogenesis.

OBJECTIVE

To gain insight into the dynamic temporal changes in protein expression during differentiation of normal and dystrophin deficient myoblasts to myotubes.

METHOD

A super SILAC spike-in strategy in combination and LC-MS/MS was used for temporal proteome profiling of normal and dystrophin deficient myoblasts during differentiation. The acquired data was analyzed using Proteome Discoverer 2.2. and data clustering using R to define significant temporal changes in protein expression.

RESULTS

sFour major temporal protein clusters that showed sequential dynamic expression profiles during myogenesis of normal myoblasts were identified. Clusters 1 and 2, consisting mainly of proteins involved mRNA splicing and processing expression, were elevated at days 0 and 0.5 of differentiation then gradually decreased by day 7 of differentiation, then remained lower thereafter. Cluster 3 consisted of proteins involved contractile muscle and actomyosin organization. They increased in their expression reaching maximum at day 7 of differentiation then stabilized thereafter. Cluster 4 consisting of proteins involved in skeletal muscle development glucogenesis and extracellular remodeling had a lower expression during myoblast stage then gradually increased in their expression to reach a maximum at days 11-15 of differentiation. Lack of dystrophin expression in DMD muscle myoblast caused major alteration in temporal expression of proteins involved in cell adhesion, cytoskeleton, and organelle organization as well as the ubiquitination machinery.

CONCLUSION

Time series proteome profiling using super SILAC strategy is a powerful method to assess temporal changes in protein expression during myogenesis and to define the downstream consequences of lack of dystrophin on these temporal protein expressions. Key alterations were identified in dystrophin deficient myoblast differentiation compared to normal myoblasts. These alterations could be an attractive therapeutic target.

High-throughput proteomics and AI for cancer biomarker discovery

Biomarkers are assayed to assess biological and pathological status. Recent advances in high-throughput proteomic technology provide opportunities for developing next generation biomarkers for clinical practice aided by artificial intelligence (AI) based techniques. We summarize the advances and limitations of cancer biomarkers based on genomic and transcriptomic analysis, as well as classical antibody-based methodologies. Then we review recent progresses in mass spectrometry (MS)-based proteomics in terms of sample preparation, peptide fractionation by liquid chromatography (LC) and mass spectrometric data acquisition. We highlight applications of AI techniques in high-throughput clinical studies as compared with clinical decisions based on singular features. This review sets out our approach for discovering clinical biomarkers in studies using proteomic big data technology conjoined with computational and statistical methods.

Scaffold-free 3D cell culture of primary skin fibroblasts induces profound changes of the matrisome

The human skin has a highly developed extracellular matrix (ECM) that is vital for proper skin functioning, its 3D architecture playing a pivotal role in support and guidance of resident and invading cells. To establish relevant in vitro models mimicking the complex design observed in vivo, scaffold-based and scaffold-free 3D cell culture systems have been developed. Here we show that scaffold-free systems are well suited for the analysis of ECM protein regulation. Using quantitative mass spectrometry-based proteomics in combination with magnetic 3D bioprinting we characterize changes in the proteome of skin fibroblasts and squamous cell carcinoma cells. Transferring cells from 2D to 3D without any additional scaffold induces a profound upregulation of matrisome proteins indicating the generation of a complex, tissue-like ECM.

PIGNON: a protein-protein interaction-guided functional enrichment analysis for quantitative proteomics

Background

Quantitative proteomics studies are often used to detect proteins that are differentially expressed across different experimental conditions. Functional enrichment analyses are then typically used to detect annotations, such as biological processes that are significantly enriched among such differentially expressed proteins to provide insights into the molecular impacts of the studied conditions. While common, this analytical pipeline often heavily relies on arbitrary thresholds of significance. However, a functional annotation may be dysregulated in a given experimental condition, while none, or very few of its proteins may be individually considered to be significantly differentially expressed. Such an annotation would therefore be missed by standard approaches.

Results

Herein, we propose a novel graph theory-based method, PIGNON, for the detection of differentially expressed functional annotations in different conditions. PIGNON does not assess the statistical significance of the differential expression of individual proteins, but rather maps protein differential expression levels onto a protein–protein interaction network and measures the clustering of proteins from a given functional annotation within the network. This process allows the detection of functional annotations for which the proteins are differentially expressed and grouped in the network. A Monte-Carlo sampling approach is used to assess the clustering significance of proteins in an expression-weighted network. When applied to a quantitative proteomics analysis of different molecular subtypes of breast cancer, PIGNON detects Gene Ontology terms that are both significantly clustered in a protein–protein interaction network and differentially expressed across different breast cancer subtypes. PIGNON identified functional annotations that are dysregulated and clustered within the network between the HER2+, triple negative and hormone receptor positive subtypes. We show that PIGNON’s results are complementary to those of state-of-the-art functional enrichment analyses and that it highlights functional annotations missed by standard approaches. Furthermore, PIGNON detects functional annotations that have been previously associated with specific breast cancer subtypes.

Conclusion

PIGNON provides an alternative to functional enrichment analyses and a more comprehensive characterization of quantitative datasets. Hence, it contributes to yielding a better understanding of dysregulated functions and processes in biological samples under different experimental conditions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04042-6.

Quantitative proteomics identifies the core proteome of exosomes with syntenin-1 as the highest abundant protein and a putative universal biomarker

Exosomes are extracellular vesicles derived from the endosomal compartment that are potentially involved in intercellular communication. Here, we found that frequently used biomarkers of exosomes are heterogeneous, and do not exhibit universal utility across different cell types. To uncover ubiquitous and abundant proteins, we used an unbiased and quantitative proteomic approach based on super-stable isotope labeling with amino acids in cell culture (super-SILAC), coupled to high-resolution mass spectrometry. In total, 1,212 proteins were quantified in the proteome of exosomes, irrespective of the cellular source or isolation method. A cohort of 22 proteins was universally enriched. Fifteen proteins were consistently depleted in the proteome of exosomes compared to cells. Among the enriched proteins, we identified biogenesis-related proteins, GTPases and membrane proteins, such as CD47 and ITGB1. The cohort of depleted proteins in exosomes was predominantly composed of nuclear proteins. We identified syntenin-1 as a consistently abundant protein in exosomes from different cellular origins. Syntenin-1 is also present in exosomes across different species and biofluids, highlighting its potential use as a putative universal biomarker of exosomes. Our study provides a comprehensive quantitative atlas of core proteins ubiquitous to exosomes that can serve as a resource for the scientific community.

Genome-wide circadian rhythm detection methods: systematic evaluations and practical guidelines

Circadian rhythms are oscillations of behavior, physiology and metabolism in many organisms. Recent advancements in omics technology make it possible for genome-wide profiling of circadian rhythms. Here, we conducted a comprehensive analysis of seven existing algorithms commonly used for circadian rhythm detection. Using gold-standard circadian and non-circadian genes, we systematically evaluated the accuracy and reproducibility of the algorithms on empirical datasets generated from various omics platforms under different experimental designs. We also carried out extensive simulation studies to test each algorithm's robustness to key variables, including sampling patterns, replicates, waveforms, signal-to-noise ratios, uneven samplings and missing values. Furthermore, we examined the distributions of the nominal $P$-values under the null and raised issues with multiple testing corrections using traditional approaches. With our assessment, we provide method selection guidelines for circadian rhythm detection, which are applicable to different types of high-throughput omics data.

Proteomic Interrogation in Cancer Biomarker

Biomarkers factor into the diagnosis and treatment of almost every patient with cancer. The innovation in proteomics follows improvement of mass spectrometry techniques and data processing strategy. Recently, proteomics and typical biological studies have been the answer for clinical applications. The clinical proteomics techniques are now actively adapted to protein identification in large patient cohort, biomarker development for more sensitive and specific screening based on quantitative data. And, it is important for clinical, translational researchers to be acutely aware of the issues surrounding appropriate biomarker development, in order to facilitate entry of clinically useful biomarkers into the clinic. Here, we discuss in detail include the case research for clinical proteomics. Furthermore, we give an overview on the current developments and novel findings in proteomics-based cancer biomarker research.

Benchmarking accuracy and precision of intensity-based absolute quantification of protein abundances in Saccharomyces cerevisiae

Protein quantification via label-free mass spectrometry (MS) has become an increasingly popular method for predicting genome-wide absolute protein abundances. A known caveat of this approach, however, is the poor technical reproducibility, that is, how consistent predictions are when the same sample is measured repeatedly. Here, we measured proteomics data for Saccharomyces cerevisiae with both biological and inter-batch technical triplicates, to analyze both accuracy and precision of protein quantification via MS. Moreover, we analyzed how these metrics vary when applying different methods for converting MS intensities to absolute protein abundances. We demonstrate that our simple normalization and rescaling approach can perform as accurately, yet more precisely, than methods which rely on external standards. Additionally, we show that inter-batch reproducibility is worse than biological reproducibility for all evaluated methods. These results offer a new benchmark for assessing MS data quality for protein quantification, while also underscoring current limitations in this approach.

Application of Advanced Mass Spectrometry-Based Proteomics to Study Hypoxia Driven Cancer Progression

Cancer is one of the largest contributors to the burden of chronic disease in the world and is the second leading cause of death globally. It is associated with episodes of low-oxygen stress (hypoxia or ischemia/reperfusion) that promotes cancer progression and therapeutic resistance. Efforts have been made in the past using traditional proteomic approaches to decipher oxygen deprivation stress-related mechanisms of the disease initiation and progression and to identify key proteins as a therapeutic target for the treatment and prevention. Despite the potential benefits of proteomic in translational research for the discovery of new drugs, the therapeutic outcome with this approach has not met expectations in clinical trials. This is mainly due to the disease complexity which possess a multifaceted molecular pathology. Therefore, novel strategies to identify and characterize clinically important sets of modulators and molecular events for multi-target drug discovery are needed. Here, we review important past and current studies on proteomics in cancer with an emphasis on recent pioneered labeling approaches in mass spectrometry (MS)-based systematic quantitative analysis to improve clinical success. We also discuss the results of the selected innovative publications that integrate advanced proteomic technologies (e.g. MALDI-MSI, pSILAC/SILAC/iTRAQ/TMT-LC-MS/MS, MRM-MS) for comprehensive analysis of proteome dynamics in different biosystems, including cell type, cell species, and subcellular proteome (i.e. secretome and chromatome). Finally, we discuss the future direction and challenges in the application of these technological advancements in mass spectrometry within the context of cancer and hypoxia.

Analysis of ovarian cancer cell secretome during epithelial to mesenchymal transition reveals a protein signature associated with advanced stages of ovarian tumors

Ovarian cancer (OvCA) is the most lethal neoplasia among gynecologic malignancies and faces high rates of new cases particularly in South America. In special, the High Grade Serous Ovarian Carcinoma (HGSC) presents very poor prognosis with deaths caused mainly by metastasis. Among several mechanisms involved in metastasis, the Epithelial to Mesenchymal Transition (EMT) molecular reprogramming represents a model for latest stages of cancer progression. EMT promotes important cellular changes in cellular adhesion and cell-cell communication, which particularly depends on the paracrine signaling from neighbor cells. Considering the importance of cellular communication during EMT and metastasis, here we analyzed the changes in the secretome of the ovarian cancer cell line Caov-3 induced to EMT by Epidermal Growth Factor (EGF). Using a combination of GEL-LC-MS/MS and stable isotopic metabolic labelling (SILAC), we identified up-regulated candidates during EMT as a starting point to identify relevant proteins for HGSC. Based on public databases, our candidate proteins were validated and prioritized for further analysis. Importantly, several of the protein candidates were associated with cellular vesicles, which are important to the cell-cell communication and metastasis. Furthermore, the association of candidate proteins with gene expression data uncovered a subset of proteins correlated with the mesenchymal subtype of ovarian cancer. Based on this relevant molecular signature for aggressive ovarian cancer, supported by protein and gene expression data, we developed a targeted proteomic method to evaluate individual OvCA clinical samples. The quantitative information obtained for 33 peptides, representative of 18 proteins, was able to segregate HGSC from other tumor types. Our study highlighted the richness of the secretome and EMT to reveal relevant proteins for HGSC, which could be used in further studies and larger patient cohorts as a potential stratification signature for ovarian cancer tumor that could guide clinical conduct for patient treatment.

Quantitative proteomic profiling of Cervicovaginal fluid from pregnant women with term and preterm birth

Background

Preterm birth (PTB) is one of major causes of perinatal mortality and neonatal morbidity, but knowledge of its complex etiology is still limited. Here we present cervicovaginal fluid (CVF) protein profiles of pregnant women who subsequently delivered at spontaneous preterm or term, aiming to identify differentially expressed CVF proteins in PTB and term birth.

Methods

The CVF proteome of women who sequentially delivered at preterm and term was analyzed using isobaric tags for relative and absolute quantitation (iTRAQ) coupled with two-dimensional nanoflow liquid chromatography-tandem mass spectrometry (2D-nLC-MS/MS). We compared the CVF proteome of PTB (n = 5) and control subjects (term birth, n = 7) using pooled control CVF (term birth, n = 20) as spike-in standard.

Results

We identified 1294 CVF proteins, of which 605 were newly identified proteins. Of 990 proteins quantified in both PTB and term birth, 52 proteins were significantly up/down-regulated in PTB compared to term birth. The differentially expressed proteins were functionally associated to immune response, endopeptidase inhibitors and structural constituent of cytoskeleton. Finally, we confirm the down-regulation of SERPINB7 (a serine-type protease inhibitor) in PTB compared to control by Western blot.

Conclusions

Taken together, our study provide quantitative CVF proteome profiles of pregnant women who ultimately delivered at preterm and term. These promising results could help to improve the understanding of PTB etiology and to discover biomarkers for asymptomatic PTB.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12953-021-00171-1.

Kinase Signaling in Dendritic Development and Disease

Dendrites undergo extensive growth and remodeling during their lifetime. Specification of neurites into dendrites is followed by their arborization, maturation, and functional integration into synaptic networks. Each of these distinct developmental processes is spatially and temporally controlled in an exquisite fashion. Protein kinases through their highly specific substrate phosphorylation regulate dendritic growth and plasticity. Perturbation of kinase function results in aberrant dendritic growth and synaptic function. Not surprisingly, kinase dysfunction is strongly associated with neurodevelopmental and psychiatric disorders. Herein, we review, (a) key kinase pathways that regulate dendrite structure, function and plasticity, (b) how aberrant kinase signaling contributes to dendritic dysfunction in neurological disorders and (c) emergent technologies that can be applied to dissect the role of protein kinases in dendritic structure and function.

Clinical Proteomics of Metastatic Melanoma Reveals Profiles of Organ Specificity and Treatment Resistance

PURPOSE

Treatment of metastatic melanoma has dramatically improved in recent years, thanks to the development of immunotherapy and BRAF-MEK-targeted therapies. However, these developments revealed marked heterogeneity in patient response, which is yet to be fully understood. In this work, we aimed to associate the proteomic profiles of metastatic melanoma with the patient clinical information, to identify protein correlates with metastatic location and prior treatments.

EXPERIMENTAL DESIGN

We performed mass spectrometry-based proteomic analysis of 185 metastatic melanoma samples and followed with bioinformatics analysis to examine the association of metastatic location, BRAF status, survival, and immunotherapy response with the tumor molecular profiles.

RESULTS

Bioinformatics analysis showed a high degree of functional heterogeneity associated with the site of metastasis. Lung metastases presented higher immune-related proteins, and higher mitochondrial-related processes, which were shown previously to be associated with better immunotherapy response. In agreement, epidemiological analysis of data from the National Cancer Database showed improved response to anti-programmed death 1, mainly in patients with lung metastasis. Focus on lung metastases revealed prognostic and molecular heterogeneity and highlighted potential tissue-specific biomarkers. Analysis of the BRAF mutation status and prior treatments with MAPK inhibitors proposed the molecular basis of the effect on immunotherapy response and suggested coordinated combination of immunotherapy and targeted therapy may increase treatment efficacy.

CONCLUSIONS

Altogether, the proteomic data provided novel molecular determinants of critical clinical features, including the effects of sequential treatments and metastatic locations. These results can be the basis for development of site-specific treatments toward treatment personalization.

Virus systems biology: Proteomics profiling of dynamic protein networks during infection

The host cell proteome undergoes a variety of dynamic changes during viral infection, elicited by the virus itself or host cell defense mechanisms. Studying these changes on a global scale by integrating functional and physical interactions within protein networks during infection is an important tool to understand pathology. Indeed, proteomics studies dissecting protein signaling cascades and interaction networks upon infection showed how global information can significantly improve understanding of disease mechanisms of diverse viral infections. Here, we summarize and give examples of different experimental designs, proteomics approaches and bioinformatics analyses that allow profiling proteome changes and host-pathogen interactions to gain a molecular systems view of viral infection.

Analysis of Label-Based Quantitative Proteomics Data Using IsoProt

Isobaric labeling has become an essential method for quantitative mass spectrometry based experiments. This technique allows high-throughput proteomics while providing reasonable coverage of protein measurements across multiple samples. Here, the analysis of isobarically labeled mass spectrometry data with a special focus on quality control and potential pitfalls is discussed. The protocol is based on our fully integrated IsoProt workflow. The concepts discussed are nevertheless applicable to the analysis of any isobarically labeled experiment using alternative computational tools and algorithms.

Importance of Block Randomization When Designing Proteomics Experiments

Randomization is used in experimental design to reduce the prevalence of unanticipated confounders. Complete randomization can however create imbalanced designs, for example, grouping all samples of the same condition in the same batch. Block randomization is an approach that can prevent severe imbalances in sample allocation with respect to both known and unknown confounders. This feature provides the reader with an introduction to blocking and randomization, and insights into how to effectively organize samples during experimental design, with special considerations with respect to proteomics.

Quantitative Mass Spectrometry-Based Proteomics: An Overview

In recent decades, mass spectrometry has moved more than ever before into the front line of protein-centered research. After being established at the qualitative level, the more challenging question of quantification of proteins and peptides using mass spectrometry has become a focus for further development. In this chapter, we discuss and review actual strategies and problems of the methods for the quantitative analysis of peptides, proteins, and finally proteomes by mass spectrometry. The common themes, the differences, and the potential pitfalls of the main approaches are presented in order to provide a survey of the emerging field of quantitative, mass spectrometry-based proteomics.

Kinome Profiling of Primary Endometrial Tumors Using Multiplexed Inhibitor Beads and Mass Spectrometry Identifies SRPK1 as Candidate Therapeutic Target

Endometrial carcinoma (EC) is the most common gynecologic malignancy in the United States, with limited effective targeted therapies. Endometrial tumors exhibit frequent alterations in protein kinases, yet only a small fraction of the kinome has been therapeutically explored. To identify kinase therapeutic avenues for EC, we profiled the kinome of endometrial tumors and normal endometrial tissues using Multiplexed Inhibitor Beads and Mass Spectrometry (MIB-MS). Our proteomics analysis identified a network of kinases overexpressed in tumors, including Serine/Arginine-Rich Splicing Factor Kinase 1 (SRPK1). Immunohistochemical (IHC) analysis of endometrial tumors confirmed MIB-MS findings and showed SRPK1 protein levels were highly expressed in endometrioid and uterine serous cancer (USC) histological subtypes. Moreover, querying large-scale genomics studies of EC tumors revealed high expression of SRPK1 correlated with poor survival. Loss-of-function studies targeting SRPK1 in an established USC cell line demonstrated SRPK1 was integral for RNA splicing, as well as cell cycle progression and survival under nutrient deficient conditions. Profiling of USC cells identified a compensatory response to SRPK1 inhibition that involved EGFR and the up-regulation of IGF1R and downstream AKT signaling. Co-targeting SRPK1 and EGFR or IGF1R synergistically enhanced growth inhibition in serous and endometrioid cell lines, representing a promising combination therapy for EC.