Automated phosphopeptide enrichment from minute quantities of frozen malignant melanoma tissue

Incremental Modification in the Existing Approaches for Affinity Chromatographic Enrichment of Phosphoproteins Improves Their Profile in Liquid Chromatography-Tandem Mass Spectrometry Analysis

Cell signalling is a vital process in cell physiology, which is driven by protein phosphorylation. Global phosphoproteome analysis by liquid chromatography-tandem mass spectrometry (LC-MS/MS) has thus gained importance in cell signalling research. However, phosphoprotein identification by LC-MS/MS in whole cell lysates, which are complex protein mixtures, is hindered by their poor ionization coupled with suppression of peaks due to low abundance. Enrichment by immobilized metal ion- and metal oxide-affinity chromatography (IMAC and MOAC), which preferentially enrich multi- and mono-phosphorylated proteins, respectively, have improved their detection by MS. However, preferential enrichment limits phosphoproteome coverage in global analyses of cell lysates which contain mono- and multi-phosphorylated proteins. Improvement in their coverage by sequential elution approach that exploits the complementary chemistries of these matrices has been reported. In this study, we observed that the number of phosphoproteins detected using the sequential elution approach was lower (∼250-400) as compared to the theoretically predicted number (>500) based on their reported 30% abundance in the cell proteome (1700-2200 proteins detected by MS in our cell lines). Acknowledging the merit of using multiple matrices, we used IMAC and MOAC individually and pooled the data. We observed a remarkable increase (>30%) in phosphoproteome coverage. Further, though 98% of phosphoproteins were enriched by IMAC, among the remaining 2%, those detected exclusively by MOAC were biologically important. This justified the use of multiple matrices. Thus, an incremental modification of using multiple matrices individually rather than sequentially and pooling the data markedly improved the phosphoproteome coverage, which can positively impact cell signalling research.

Immobilized metal ion affinity chromatography: waltz of metal ions and biomacromolecules

INTRODUCTION

Immobilized metal ion affinity chromatography (IMAC) is an effective method developed in the 1980s for the separation and purification of proteins. The system consists of a solid-phase matrix, a linking ligand, and a metal ion. The method is based on the ability of metal ions to bind specifically to certain specific amino acid residues of proteins, thereby selectively enriching and purifying proteins.

AREAS COVERED

This review aims to describe current knowledge of fundamental principle of IMAC and summarize the supports, chelating ligands, and metal ions of IMAC. In addition, how IMAC technology is used in proteomics and DNA research are highlighted.

EXPERT OPINION

Over the past decades, IMAC has been extensively utilized as a predominant technique for protein enrichment in a variety of biological and medical research, such as disease diagnosis, tumor biomarker identification, protein purification, and nucleic acid research. In the future, IMAC should be integrated with other proteomics technologies to promote the applications of metalloproteomes in disease diagnosis, metallodrug development and clinical translation.

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.

Principles of phosphoproteomics and applications in cancer research

Phosphorylation constitutes the most common and best-studied regulatory post-translational modification in biological systems and archetypal signalling pathways driven by protein and lipid kinases are disrupted in essentially all cancer types. Thus, the study of the phosphoproteome stands to provide unique biological information on signalling pathway activity and on kinase network circuitry that is not captured by genetic or transcriptomic technologies. Here, we discuss the methods and tools used in phosphoproteomics and highlight how this technique has been used, and can be used in the future, for cancer research. Challenges still exist in mass spectrometry phosphoproteomics and in the software required to provide biological information from these datasets. Nevertheless, improvements in mass spectrometers with enhanced scan rates, separation capabilities and sensitivity, in biochemical methods for sample preparation and in computational pipelines are enabling an increasingly deep analysis of the phosphoproteome, where previous bottlenecks in data acquisition, processing and interpretation are being relieved. These powerful hardware and algorithmic innovations are not only providing exciting new mechanistic insights into tumour biology, from where new drug targets may be derived, but are also leading to the discovery of phosphoproteins as mediators of drug sensitivity and resistance and as classifiers of disease subtypes. These studies are, therefore, uncovering phosphoproteins as a new generation of disruptive biomarkers to improve personalised anti-cancer therapies.

Proteomics as a tool to improve novel insights into skin diseases: what we know and where we should be going

BACKGROUND

Biochemical processes involved in complex skin diseases (skin cancers, psoriasis, and wound) can be identified by combining proteomics analysis and bioinformatics tools, which gain a next-level insight into their pathogenesis, diagnosis, and therapeutic targets.

METHODS

Articles were identified through a search of PubMed, Embase, and MEDLINE references dated to May 2022, to perform system data mining, and a search of the Web of Science (WoS) Core Collection was utilized to conduct a visual bibliometric analysis.

RESULTS

An increased trend line revealed that the number of publications related to proteomics utilized in skin diseases has sharply increased recent years, reaching a peak in 2021. The hottest fields focused on are skin cancer (melanoma), inflammation skin disorder (psoriasis), and skin wounds. After deduplication and title, abstract, and full-text screening, a total of 486 of the 7,822 outcomes met the inclusion/exclusion criteria for detailed data mining in the field of skin disease tooling with proteomics, with regard to skin cancer. According to the data, cell death, metabolism, skeleton, immune, and inflammation enrichment pathways are likely the major part and hotspots of proteomic analysis found in skin diseases. Also, the focuses of proteomics in skin disease are from superficial presumption to depth mechanism exploration within more comprehensive validation, from basic study to a combination or guideline for clinical applications. Furthermore, we chose skin cancer as a typical example, compared with other skin disorders. In addition to finding key pathogenic proteins and differences between diseases, proteomic analysis is also used for therapeutic evaluation or can further obtain in-depth mechanisms in the field of skin diseases.

CONCLUSION

Proteomics has been regarded as an irreplaceable technology in the study of pathophysiological mechanism and/or therapeutic targets of skin diseases, which could provide candidate key proteins for the insight into the biological information after gene transcription. However, depth pathogenesis and potential clinical applications need further studies with stronger evidence within a wider range of skin diseases.

Toward Zero Variance in Proteomics Sample Preparation: Positive-Pressure FASP in 96-Well Format (PF96) Enables Highly Reproducible, Time- and Cost-Efficient Analysis of Sample Cohorts

As novel liquid chromatography–mass spectrometry (LC-MS) technologies for proteomics offer a substantial increase in LC-MS runs per day, robust and reproducible sample preparation emerges as a new bottleneck for throughput. We introduce a novel strategy for positive-pressure 96-well filter-aided sample preparation (PF96) on a commercial positive-pressure solid-phase extraction device. PF96 allows for a five-fold increase in throughput in conjunction with extraordinary reproducibility with Pearson product-moment correlations on the protein level of r = 0.9993, as demonstrated for mouse heart tissue lysate in 40 technical replicates. The targeted quantification of 16 peptides in the presence of stable-isotope-labeled reference peptides confirms that PF96 variance is barely assessable against technical variation from nanoLC-MS instrumentation. We further demonstrate that protein loads of 36–60 μg result in optimal peptide recovery, but lower amounts ≥3 μg can also be processed reproducibly. In summary, the reproducibility, simplicity, and economy of time provide PF96 a promising future in biomedical and clinical research.

An Observational Study on the Molecular Profiling of Primary Melanomas Reveals a Progression Dependence on Mitochondrial Activation

Melanoma in advanced stages is one of the most aggressive tumors and the deadliest of skin cancers. To date, the histopathological staging focuses on tumor thickness, and clinical staging is a major estimate of the clinical behavior of primary melanoma. Here we report on an observational study with in-depth molecular profiling at the protein level including post-translational modifications (PTMs) on eleven primary tumors from melanoma patients. Global proteomics, phosphoproteomics, and acetylomics were performed on each sample. We observed an up-regulation of key mitochondrial functions, including the mitochondrial translation machinery and the down-regulation of structural proteins involved in cell adhesion, the cytoskeleton organization, and epidermis development, which dictates the progression of the disease. Additionally, the PTM level pathways related to RNA processing and transport, as well as chromatin organization, were dysregulated in relation to the progression of melanoma. Most of the pathways dysregulated in this cohort were enriched in genes differentially expressed at the transcript level when similar groups are compared or metastasis to primary melanomas. At the genome level, we found significant differences in the mutation profiles between metastatic and primary melanomas. Our findings also highlighted sex-related differences in the molecular profiles. Remarkably, primary melanomas in women showed higher levels of antigen processing and presentation, and activation of the immune system response. Our results provide novel insights, relevant for developing personalized precision treatments for melanoma patients.

Automated Phosphopeptide Enrichment for Gram-Positive Bacteria

Protein phosphorylation in prokaryotes has gained more attention in recent years as several studies linked it to regulatory and signaling functions, indicating importance similar to protein phosphorylation in eukaryotes. Studies on bacterial phosphorylation have so far been conducted using manual or HPLC-supported phosphopeptide enrichment, whereas automation of phosphopeptide enrichment has been established in eukaryotes, allowing for high-throughput sampling. To facilitate the prospect of studying bacterial phosphorylation on a systems level, we here established an automated Ser/Thr/Tyr phosphopeptide enrichment workflow on the Agilent AssayMap platform. We present optimized buffer conditions for TiO₂ and Fe(III)-NTA-IMAC cartridge-based enrichment and the most advantageous, species-specific loading amounts for Streptococcus pyogenes, Listeria monocytogenes, and Bacillus subtilis. For higher sample amounts (≥250 μg), we observed superior performance of the Fe(III)-NTA cartridges, whereas for lower sample amounts (≤100 μg), TiO₂-based enrichment is equally efficient. Both cartridges largely enriched the same set of phosphopeptides, suggesting no improvement of peptide yield by the complementary use of the two cartridges. Our data represent, to the best of our knowledge, the largest phosphoproteome identified in a single study for each of these bacteria.

The Human Melanoma Proteome Atlas-Complementing the melanoma transcriptome

The MM500 meta-study aims to establish a knowledge basis of the tumor proteome to serve as a complement to genome and transcriptome studies. Somatic mutations and their effect on the transcriptome have been extensively characterized in melanoma. However, the effects of these genetic changes on the proteomic landscape and the impact on cellular processes in melanoma remain poorly understood. In this study, the quantitative mass-spectrometry-based proteomic analysis is interfaced with pathological tumor characterization, and associated with clinical data. The melanoma proteome landscape, obtained by the analysis of 505 well-annotated melanoma tumor samples, is defined based on almost 16 000 proteins, including mutated proteoforms of driver genes. More than 50 million MS/MS spectra were analyzed, resulting in approximately 13,6 million peptide spectrum matches (PSMs). Altogether 13 176 protein-coding genes, represented by 366 172 peptides, in addition to 52 000 phosphorylation sites, and 4 400 acetylation sites were successfully annotated. This data covers 65% and 74% of the predicted and identified human proteome, respectively. A high degree of correlation (Pearson, up to 0.54) with the melanoma transcriptome of the TCGA repository, with an overlap of 12 751 gene products, was found. Mapping of the expressed proteins with quantitation, spatiotemporal localization, mutations, splice isoforms, and PTM variants was proven not to be predicted by genome sequencing alone. The melanoma tumor molecular map was complemented by analysis of blood protein expression, including data on proteins regulated after immunotherapy. By adding these key proteomic pillars, the MM500 study expands the knowledge on melanoma disease.

Protein Expression in Metastatic Melanoma and the Link to Disease Presentation in a Range of Tumor Phenotypes

Malignant melanoma is among the most aggressive skin cancers and it has among the highest metastatic potentials. Although surgery to remove the primary tumor is the gold standard treatment, once melanoma progresses and metastasizes to the lymph nodes and distal organs, i.e., metastatic melanoma (MM), the usual outcome is decreased survival. To improve survival rates and life span, advanced treatments have focused on the success of targeted therapies in the MAPK pathway that are based on BRAF (BRAF V600E) and MEK. The majority of patients with tumors that have higher expression of BRAF V600E show poorer prognosis than patients with a lower level of the mutated protein. Based on the molecular basis of melanoma, these findings are supported by distinct tumor phenotypes determined from differences in tumor heterogeneity and protein expression profiles. With these aspects in mind, continued challenges are to: (1) deconvolute the complexity and heterogeneity of MM; (2) identify the signaling pathways involved; and (3) determine protein expression to develop targeted therapies. Here, we provide an overview of the results from protein expression in MM and the link to disease presentation in a variety of tumor phenotypes and how these will overcome the challenges of clinical problems and suggest new promising approaches in metastatic melanoma and cancer therapy.

Automated sample preparation with SP3 for low-input clinical proteomics

High-throughput and streamlined workflows are essential in clinical proteomics for standardized processing of samples from a variety of sources, including fresh-frozen tissue, FFPE tissue, or blood. To reach this goal, we have implemented single-pot solid-phase-enhanced sample preparation (SP3) on a liquid handling robot for automated processing (autoSP3) of tissue lysates in a 96-well format. AutoSP3 performs unbiased protein purification and digestion, and delivers peptides that can be directly analyzed by LCMS, thereby significantly reducing hands-on time, reducing variability in protein quantification, and improving longitudinal reproducibility. We demonstrate the distinguishing ability of autoSP3 to process low-input samples, reproducibly quantifying 500-1,000 proteins from 100 to 1,000 cells. Furthermore, we applied this approach to a cohort of clinical FFPE pulmonary adenocarcinoma (ADC) samples and recapitulated their separation into known histological growth patterns. Finally, we integrated autoSP3 with AFA ultrasonication for the automated end-to-end sample preparation and LCMS analysis of 96 intact tissue samples. Collectively, this constitutes a generic, scalable, and cost-effective workflow with minimal manual intervention, enabling reproducible tissue proteomics in a broad range of clinical and non-clinical applications.

Enrichments of post-translational modifications in proteomic studies

More than 300 different protein post-translational modifications are currently known, but only a few have been extensively investigated because modified proteoforms are commonly present in sub-stoichiometry amount. For this reason, improvement of specific enrichment techniques is particularly useful for the proteomic characterization of post-translationally modified proteins. Enrichment proteomic strategies could help the researcher in the challenging issue to decipher the complex molecular cross-talk existing between the different factors influencing the cellular pathways. In this review the state of art of the platforms applied for the enrichment of specific and most common post-translational modifications, such as glycosylation and glycation, phosphorylation, sulfation, redox modifications (i.e. sulfydration and nitrosylation), methylation, acetylation, and ubiquitinylation, are described. Enrichments strategies applied to characterize less studied post-translational modifications are also briefly discussed.

Automating Complex, Multistep Processes on a Single Robotic Platform to Generate Reproducible Phosphoproteomic Data

Mass spectrometry-based phosphoproteomics holds promise for advancing drug treatment and disease diagnosis; however, its clinical translation has thus far been limited. This is in part due to an unstandardized and segmented sample preparation process that involves cell lysis, protein digestion, peptide desalting, and phosphopeptide enrichment. Automating this entire sample preparation process will be key in facilitating standardization and clinical translation of phosphoproteomics. While peptide desalting and phosphopeptide enrichment steps have been individually automated, integrating these two extractions and, further, the entire process requires more advanced robotic platforms as well as automation-friendly extraction tools. Here we describe a fully automated peptide desalting and phosphopeptide enrichment method using IMCStips on a Hamilton STAR. Using our established automated method, we identified more than 10,000 phosphopeptides from 200 µg of HCT116 cell lysate without fractionation with >85% phosphopeptide specificities. Compared with titania-based Spin Tip products, the automated IMCStips-based method gave 50% higher phosphopeptide identifications. The method reproducibility was further assessed using multiple reaction monitoring (MRM) to show >50% phosphopeptide recoveries after the automated phosphopeptide extraction with coefficients of variation (CVs) of <20% over a 3-week period. The established automated method is a step toward standardization of the sample preparation of phosphopeptide samples and could be further expanded upon to create a fully automated "cells to phosphopeptides" method.