Comparison of bottom-up proteomic approaches for LC-MS analysis of complex proteomes

Recent Advancements in Subcellular Proteomics: Growing Impact of Organellar Protein Niches on the Understanding of Cell Biology

The mammalian cell is a complex entity, with membrane-bound and membrane-less organelles playing vital roles in regulating cellular homeostasis. Organellar protein niches drive discrete biological processes and cell functions, thus maintaining cell equilibrium. Cellular processes such as signaling, growth, proliferation, motility, and programmed cell death require dynamic protein movements between cell compartments. Aberrant protein localization is associated with a wide range of diseases. Therefore, analyzing the subcellular proteome of the cell can provide a comprehensive overview of cellular biology. With recent advancements in mass spectrometry, imaging technology, computational tools, and deep machine learning algorithms, studies pertaining to subcellular protein localization and their dynamic distributions are gaining momentum. These studies reveal changing interaction networks because of "moonlighting proteins" and serve as a discovery tool for disease network mechanisms. Consequently, this review aims to provide a comprehensive repository for recent advancements in subcellular proteomics subcontexting methods, challenges, and future perspectives for method developers. In summary, subcellular proteomics is crucial to the understanding of the fundamental cellular mechanisms and the associated diseases.

Novel functional insights into the microbiome inhabiting marine plastic debris: critical considerations to counteract the challenges of thin biofilms using multi-omics and comparative metaproteomics

BACKGROUND

Microbial functioning on marine plastic surfaces has been poorly documented, especially within cold climates where temperature likely impacts microbial activity and the presence of hydrocarbonoclastic microorganisms. To date, only two studies have used metaproteomics to unravel microbial genotype-phenotype linkages in the marine 'plastisphere', and these have revealed the dominance of photosynthetic microorganisms within warm climates. Advancing the functional representation of the marine plastisphere is vital for the development of specific databases cataloging the functional diversity of the associated microorganisms and their peptide and protein sequences, to fuel biotechnological discoveries. Here, we provide a comprehensive assessment for plastisphere metaproteomics, using multi-omics and data mining on thin plastic biofilms to provide unique insights into plastisphere metabolism. Our robust experimental design assessed DNA/protein co-extraction and cell lysis strategies, proteomics workflows, and diverse protein search databases, to resolve the active plastisphere taxa and their expressed functions from an understudied cold environment.

RESULTS

For the first time, we demonstrate the predominance and activity of hydrocarbonoclastic genera (Psychrobacter, Flavobacterium, Pseudomonas) within a primarily heterotrophic plastisphere. Correspondingly, oxidative phosphorylation, the citrate cycle, and carbohydrate metabolism were the dominant pathways expressed. Quorum sensing and toxin-associated proteins of Streptomyces were indicative of inter-community interactions. Stress response proteins expressed by Psychrobacter, Planococcus, and Pseudoalteromonas and proteins mediating xenobiotics degradation in Psychrobacter and Pseudoalteromonas suggested phenotypic adaptations to the toxic chemical microenvironment of the plastisphere. Interestingly, a targeted search strategy identified plastic biodegradation enzymes, including polyamidase, hydrolase, and depolymerase, expressed by rare taxa. The expression of virulence factors and mechanisms of antimicrobial resistance suggested pathogenic genera were active, despite representing a minor component of the plastisphere community.

CONCLUSION

Our study addresses a critical gap in understanding the functioning of the marine plastisphere, contributing new insights into the function and ecology of an emerging and important microbial niche. Our comprehensive multi-omics and comparative metaproteomics experimental design enhances biological interpretations to provide new perspectives on microorganisms of potential biotechnological significance beyond biodegradation and to improve the assessment of the risks associated with microorganisms colonizing marine plastic pollution. Video Abstract.

Systems Biology Approach to Investigate Biomarkers, Boron-10 Carriers, and Mechanisms Useful for Improving Boron Neutron Capture Therapy

Systems biology approach, carried out with high-throughput omics technologies, has become a fundamental aspect of the study of complex diseases like cancer. It can molecularly characterize subjects, physiopathological conditions, and interactions, allowing a precise description, to reach personalized medicine. In particular, proteomics, typically performed with liquid chromatography coupled to mass spectrometry, is a powerful tool for systems biology, giving the possibility to perform diagnosis, patient stratification, and prediction of therapy effects. Boron Neutron Capture Therapy (BNCT) is a selective antitumoral radiotherapy based on a nuclear reaction that occurs when ¹⁰B atoms are irradiated by low-energy thermal neutrons, leading to cell death, thanks to the production of high-energy α particles. Since BNCT is recently becoming an important therapy for the treatment of different types of solid tumors such as gliomas, head and neck cancers, and others, it can take advantage of molecular investigation to improve the understanding of effects and mechanisms and so help its clinical applications. In this context, proteomics can provide a better understanding of mechanisms related to BNCT effect, identify potential biomarkers, and individuate differential responses by specific patients, stratifying responders and nonresponders. Another key aspect of BNCT is the study of new potential Boron-10 carriers to improve the selectivity of Boron delivery to tumors and proteomics can be important in this application, studying the effectiveness of new boron delivery agents, including protein-based carriers, also using computational studies that can investigate new molecules, such as boronated monoclonal antibodies, for improving BNCT.

Ultrafast and Reproducible Proteomics from Small Amounts of Heart Tissue Enabled by Azo and timsTOF Pro

Global bottom-up mass spectrometry (MS)-based proteomics is widely used for protein identification and quantification to achieve a comprehensive understanding of the composition, structure, and function of the proteome. However, traditional sample preparation methods are time-consuming, typically including overnight tryptic digestion, extensive sample cleanup to remove MS-incompatible surfactants, and offline sample fractionation to reduce proteome complexity prior to online liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. Thus, there is a need for a fast, robust, and reproducible method for protein identification and quantification from complex proteomes. Herein, we developed an ultrafast bottom-up proteomics method enabled by Azo, a photocleavable, MS-compatible surfactant that effectively solubilizes proteins and promotes rapid tryptic digestion, combined with the Bruker timsTOF Pro, which enables deeper proteome coverage through trapped ion mobility spectrometry (TIMS) and parallel accumulation-serial fragmentation (PASEF) of peptides. We applied this method to analyze the complex human cardiac proteome and identified nearly 4000 protein groups from as little as 1 mg of human heart tissue in a single one-dimensional LC-TIMS-MS/MS run with high reproducibility. Overall, we anticipate this ultrafast, robust, and reproducible bottom-up method empowered by both Azo and the timsTOF Pro will be generally applicable and greatly accelerate the throughput of large-scale quantitative proteomic studies. Raw data are available via the MassIVE repository with identifier MSV000087476.

Electroblotting through a tryptic membrane for LC-MS/MS analysis of proteins separated in electrophoretic gels

Digestion of proteins separated via sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) remains a popular method for protein identification using mass-spectrometry based proteomics. Although robust and routine, the in-gel digestion procedure is laborious and time-consuming. Electroblotting to a capture membrane prior to digestion reduces preparation steps but requires on-membrane digestion that yields fewer peptides than in-gel digestion. This paper develops direct electroblotting through a trypsin-containing membrane to a capture membrane to simplify extraction and digestion of proteins separated by SDS-PAGE. Subsequent liquid chromatography-tandem mass spectrometry (LC-MS/MS) identifies the extracted peptides. Analysis of peptides from different capture membrane pieces shows that electrodigestion does not greatly disturb the spatial resolution of a standard protein mixture separated by SDS-PAGE. Electrodigestion of an Escherichia coli (E. coli) cell lysate requires four hours of total sample preparation and results in only 13% fewer protein identifications than in-gel digestion, which can take 24 h. Compared to simple electroblotting and protein digestion on a poly(vinylidene difluoride) (PVDF) capture membrane, adding a trypsin membrane to the electroblot increases the number of protein identifications by 22%. Additionally, electrodigestion experiments using capture membranes coated with polyelectrolyte layers identify a higher fraction of small proteolytic peptides than capture on PVDF or in-gel digestion.

Subcellular proteomics

The eukaryotic cell is compartmentalized into subcellular niches, including membrane-bound and membrane-less organelles. Proteins localize to these niches to fulfil their function, enabling discreet biological processes to occur in synchrony. Dynamic movement of proteins between niches is essential for cellular processes such as signalling, growth, proliferation, motility and programmed cell death, and mutations causing aberrant protein localization are associated with a wide range of diseases. Determining the location of proteins in different cell states and cell types and how proteins relocalize following perturbation is important for understanding their functions, related cellular processes and pathologies associated with their mislocalization. In this Primer, we cover the major spatial proteomics methods for determining the location, distribution and abundance of proteins within subcellular structures. These technologies include fluorescent imaging, protein proximity labelling, organelle purification and cell-wide biochemical fractionation. We describe their workflows, data outputs and applications in exploring different cell biological scenarios, and discuss their main limitations. Finally, we describe emerging technologies and identify areas that require technological innovation to allow better characterization of the spatial proteome.

Comparison of protein and peptide fractionation approaches in protein identification and quantification from Saccharomyces cerevisiae

Shotgun proteomics is a high-throughput technology which has been developed with the aim of investigating the maximum number of proteins in cells in a given experiment. However, protein discovery and data generation vary in depth and coverage when different technical strategies are selected. In this study, three different sample preparation approaches, and peptide or protein fractionation methods, were applied to identify and quantify proteins from log-phase yeast lysate: sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), filter-aided sample preparation coupled with gas phase fractionation (FASP-GPF), and FASP - high pH reversed phase fractionation (HpH). Fractions were initially analyzed and compared using nanoflow liquid chromatography - tandem mass spectrometry (nanoLC-MS/MS) employing data dependent acquisition on a linear ion trap instrument. The number of fractions and analytical replicates was adjusted so that each experiment used a similar amount of mass spectrometric instrument time. A second set of experiments was performed, comparing FASP-GPF, SDS-PAGE and FASP-HpH using a Q Exactive Orbitrap mass spectrometer. Compared with results from the linear ion trap mass spectrometer, the use of a Q Exactive Orbitrap mass spectrometer enabled a substantial increase in protein identifications, and an even greater increase in peptide identifications. This shows that the main advantage of using the higher resolution instrument is in increased proteome coverage. A total of 1035, 1357 and 2134 proteins were separately identified by FASP-GPF, SDS-PAGE and FASP-HpH. Combining results from the Orbitrap experiments, there were a total of 2269 proteins found, with 94% of them identified using the FASP-HpH method. Therefore, the FASP-HpH method is the optimal choice among these approaches, when applied to this type of sample.

Proteomic Workflows for High-Quality Quantitative Proteome and Post-Translational Modification Analysis of Clinically Relevant Samples from Formalin-Fixed Paraffin-Embedded Archives

Well-characterized archival formalin-fixed paraffin-embedded (FFPE) tissues are of much value for prospective biomarker discovery studies, and protocols that offer high throughput and good reproducibility are essential in proteomics. Therefore, we implemented efficient paraffin removal and protein extraction from FFPE tissues followed by an optimized two-enzyme digestion using suspension trapping (S-Trap). The protocol was then combined with TMTpro 16plex labeling and applied to lung adenocarcinoma patient samples. In total, 9585 proteins were identified, and proteins related to the clinical outcome were detected. Because acetylation is known to play a major role in cancer development, a fast on-trap acetylation protocol was developed for studying endogenous lysine acetylation, which allows identification and localization of the lysine acetylation together with quantitative comparison between samples. We demonstrated that FFPE tissues are equivalent to frozen tissues to study the degree of acetylation between patients. In summary, we present a reproducible sample preparation workflow optimized for FFPE tissues that resolves known proteomic-related challenges. We demonstrate compatibility of the S-Trap with isobaric labeling and for the first time, we prove that it is feasible to study endogenous lysine acetylation stoichiometry in FFPE tissues, contributing to better utility of the existing global tissue archives. The MS proteomic data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the data set identifiers PXD020157, PXD021986, and PXD021964.

Mass Spectrometry Advances and Perspectives for the Characterization of Emerging Adoptive Cell Therapies

Adoptive cell therapy is an emerging anti-cancer modality, whereby the patient's own immune cells are engineered to express T-cell receptor (TCR) or chimeric antigen receptor (CAR). CAR-T cell therapies have advanced the furthest, with recent approvals of two treatments by the Food and Drug Administration of Kymriah (trisagenlecleucel) and Yescarta (axicabtagene ciloleucel). Recent developments in proteomic analysis by mass spectrometry (MS) make this technology uniquely suited to enable the comprehensive identification and quantification of the relevant biochemical architecture of CAR-T cell therapies and fulfill current unmet needs for CAR-T product knowledge. These advances include improved sample preparation methods, enhanced separation technologies, and extension of MS-based proteomic to single cells. Innovative technologies such as proteomic analysis of raw material quality attributes (MQA) and final product quality attributes (PQA) may provide insights that could ultimately fuel development strategies and lead to broad implementation.

Evaluation of Sample Preparation Methods for Fast Proteotyping of Microorganisms by Tandem Mass Spectrometry

Tandem mass spectrometry-based proteotyping allows characterizing microorganisms in terms of taxonomy and is becoming an important tool for investigating microbial diversity from several ecosystems. Fast and automatable sample preparation for obtaining peptide pools amenable to tandem mass spectrometry is necessary for enabling proteotyping as a high-throughput method. First, the protocol to increase the yield of lysis of several representative bacterial and eukaryotic microorganisms was optimized by using a long and drastic bead-beating setting with 0.1 mm silica beads, 0.1 and 0.5 mm glass beads, in presence of detergents. Then, three different methods to obtain greater digestion yield from these extracts were tested and optimized for improve efficiency and reduce application time: denaturing electrophoresis of proteins and in-gel proteolysis, suspension-trapping filter-based approach (S-Trap) and, solid-phase-enhanced sample preparation named SP3. The latter method outperforms the other two in terms of speed and delivers also more peptides and proteins than with the in-gel proteolysis (2.2 fold for both) and S-trap approaches (1.3 and 1.2 fold, respectively). Thus, SP3 directly improves tandem mass spectrometry proteotyping.

A Standardized and Reproducible Proteomics Protocol for Bottom-Up Quantitative Analysis of Protein Samples Using SP3 and Mass Spectrometry

The broad utility of mass spectrometry (MS) for investigating the proteomes of a diverse array of sample types has significantly expanded the use of this technology in biological studies. This widespread use has resulted in a substantial collection of protocols and acquisition approaches designed to obtain the highest-quality data for each experiment. As a result, distilling this information to develop a standard operating protocol for essential workflows, such as bottom-up quantitative shotgun whole proteome analysis, can be complex for users new to MS technology. Further complicating this matter, in-depth description of the methodological choices is seldom given in the literature. In this work, we describe a workflow for quantitative whole proteome analysis that is suitable for biomarker discovery, giving detailed consideration to important stages, including (1) cell lysis and protein cleanup using SP3 paramagnetic beads, (2) quantitative labeling, (3) offline peptide fractionation, (4) MS analysis, and (5) data analysis and interpretation. Special attention is paid to providing comprehensive details for all stages of this proteomics workflow to enhance transferability to external labs. The standardized protocol described here will provide a simplified resource to the proteomics community toward efficient adaptation of MS technology in proteomics studies.

More Is Not Always Better: Evaluation of 1D and 2D-LC-MS/MS Methods for Metaproteomics

Metaproteomics, the study of protein expression in microbial communities, is a versatile tool for environmental microbiology. Achieving sufficiently high metaproteome coverage to obtain a comprehensive picture of the activities and interactions in microbial communities is one of the current challenges in metaproteomics. An essential step to maximize the number of identified proteins is peptide separation via liquid chromatography (LC) prior to mass spectrometry (MS). Thorough optimization and comparison of LC methods for metaproteomics are, however, currently lacking. Here, we present an extensive development and test of different 1D and 2D-LC approaches for metaproteomic peptide separations. We used fully characterized mock community samples to evaluate metaproteomic approaches with very long analytical columns (50 and 75 cm) and long gradients (up to 12 h). We assessed a total of over 20 different 1D and 2D-LC approaches in terms of number of protein groups and unique peptides identified, peptide spectrum matches (PSMs) generated, the ability to detect proteins of low-abundance species, the effect of technical replicate runs on protein identifications and method reproducibility. We show here that, while 1D-LC approaches are faster and easier to set up and lead to more identifications per minute of runtime, 2D-LC approaches allow for a higher overall number of identifications with up to >10,000 protein groups identified. We also compared the 1D and 2D-LC approaches to a standard GeLC workflow, in which proteins are pre-fractionated via gel electrophoresis. This method yielded results comparable to the 2D-LC approaches, however with the drawback of a much increased sample preparation time. Based on our results, we provide recommendations on how to choose the best LC approach for metaproteomics experiments, depending on the study aims.

Employing proteomics to understand the effects of nutritional intervention in cancer treatment

Lifestyle optimizations are implementable changes that can have an impact on health and disease. Nutrition is a lifestyle optimization that has been shown to be of great importance in cancer initiation, progression, and metastasis. Dozens of clinical trials are currently in progress that focus on the nutritional modifications that cancer patients can make prior to and during medical care that increase the efficacy of treatment. In this review, we discuss various nutritional inventions for cancer patients and the analytical approaches to characterize the downstream molecular effects. We first begin by briefly explaining the many different forms of nutritional intervention currently being used in cancer treatment as well as their motivating biology. The forms of nutrient modulation described in this review include calorie restriction, the different practices of fasting, and carbohydrate restriction. The review then shifts to explain how proteomics is used to determine biomarkers of cancer and how it can be utilized in the future to determine the metabolic phenotype of a tumor, and inform physicians if nutritional intervention should be recommended for a cancer patient. Nutrigenomics aims to understand the relationship of nutrients and gene expression and can be used to understand the downstream molecular effects of nutrition restriction, partially through proteomic analysis. Proteomics is just beginning to be used as cancer diagnostic and predictive tools. However, these approaches have not been used to their full potential to understand nutritional intervention in cancer. Graphical abstract ᅟ.

Assessment of Sample Preparation Bias in Mass Spectrometry-Based Proteomics

For mass spectrometry-based proteomics, the selected sample preparation strategy is a key determinant for information that will be obtained. However, the corresponding selection is often not based on a fit-for-purpose evaluation. Here we report a comparison of in-gel (IGD), in-solution (ISD), on-filter (OFD), and on-pellet digestion (OPD) workflows on the basis of targeted (QconCAT-multiple reaction monitoring (MRM) method for mitochondrial proteins) and discovery proteomics (data-dependent acquisition, DDA) analyses using three different human head and neck tissues (i.e., nasal polyps, parotid gland, and palatine tonsils). Our study reveals differences between the sample preparation methods, for example, with respect to protein and peptide losses, quantification variability, protocol-induced methionine oxidation, and asparagine/glutamine deamidation as well as identification of cysteine-containing peptides. However, none of the methods performed best for all types of tissues, which argues against the existence of a universal sample preparation method for proteome analysis.

Quantitative proteomic analysis of murine white adipose tissue for peritoneal cancer metastasis

Cancer metastasis risk increases in older individuals, but the mechanisms for this risk increase are unclear. Many peritoneal cancers, including ovarian cancer, preferentially metastasize to peritoneal fat depots. However, there is a dearth of studies exploring aged peritoneal adipose tissue in the context of cancer. Because adipose tissue produces signals which influence several diseases including cancer, proteomics of adipose tissue in aged and young mice may provide insight into metastatic mechanisms. We analyzed mesenteric, omental, and uterine adipose tissue groups from the peritoneal cavities of young and aged C57BL/6J mouse cohorts with a low-fraction SDS-PAGE gelLC-MS/MS method. We identified 2308 protein groups and quantified 2167 groups, among which several protein groups showed twofold or greater abundance differences between the aged and young cohorts. Cancer-related gene products previously identified as significant in another age-related study were found altered in this study. Several gene products known to suppress proliferation and cellular invasion were found downregulated in the aged cohort, including R-Ras, Arid1a, and heat shock protein β1. In addition, multiple protein groups were identified within single cohorts, including the proteins Cd11a, Stat3, and Ptk2b. These data suggest that adipose tissue is a strong candidate for analysis to identify possible contributors to cancer metastasis in older subjects. The results of this study, the first of its kind using uterine adipose tissue, contribute to the understanding of the role of adipose tissue in age-related alteration of oncogenic pathways, which may help elucidate the mechanisms of increased metastatic tumor burden in the aged. Graphical abstract We analyzed mesenteric, omental, and uterine adipose tissue groups from the peritoneal cavities of young and aged C57BL/6J mouse cohorts with a low-fraction SDS-PAGE gelLC-MS/MS method. These fat depots are preferential sites for many peritoneal cancers. The results of this study, the first of its kind using uterine adipose tissue, contribute to the understanding of the role of adipose tissue in age-related alteration of oncogenic pathways, which may help elucidate the mechanisms of increased metastatic tumor burden in the aged.

Comparative Evaluation of Small Molecular Additives and Their Effects on Peptide/Protein Identification

Detergents and salts are widely used in lysis buffers to enhance protein extraction from biological samples, facilitating in-depth proteomic analysis. However, these detergents and salt additives must be efficiently removed from the digested samples prior to LC-MS/MS analysis to obtain high-quality mass spectra. Although filter-aided sample preparation (FASP), acetone precipitation (AP), followed by in-solution digestion, and strong cation exchange-based centrifugal proteomic reactors (CPRs) are commonly used for proteomic sample processing, little is known about their efficiencies at removing detergents and salt additives. In this study, we (i) developed an integrative workflow for the quantification of small molecular additives in proteomic samples, developing a multiple reaction monitoring (MRM)-based LC-MS approach for the quantification of six additives (i.e., Tris, urea, CHAPS, SDS, SDC, and Triton X-100) and (ii) systematically evaluated the relationships between the level of additive remaining in samples following sample processing and the number of peptides/proteins identified by mass spectrometry. Although FASP outperformed the other two methods, the results were complementary in terms of peptide/protein identification, as well as the GRAVY index and amino acid distributions. This is the first systematic and quantitative study of the effect of detergents and salt additives on protein identification. This MRM-based approach can be used for an unbiased evaluation of the performance of new sample preparation methods. Data are available via ProteomeXchange under identifier PXD005405.

Soil and leaf litter metaproteomics-a brief guideline from sampling to understanding

The increasing application of soil metaproteomics is providing unprecedented, in-depth characterization of the composition and functionality of in situ microbial communities. Despite recent advances in high-resolution mass spectrometry, soil metaproteomics still suffers from a lack of effective and reproducible protein extraction protocols and standardized data analyses. This review discusses the opportunities and limitations of selected techniques in soil-, and leaf litter metaproteomics, and presents a step-by-step guideline on their application, covering sampling, sample preparation, extraction and data evaluation strategies. In addition, we present recent applications of soil metaproteomics and discuss how such approaches, linking phylogenetics and functionality, can help gain deeper insights into terrestrial microbial ecology. Finally, we strongly recommend that to maximize the insights environmental metaproteomics may provide, such methods should be employed within a holistic experimental approach considering relevant aboveground and belowground ecosystem parameters.

Proteomic challenges: sample preparation techniques for microgram-quantity protein analysis from biological samples

Proteins regulate many cellular functions and analyzing the presence and abundance of proteins in biological samples are central focuses in proteomics. The discovery and validation of biomarkers, pathways, and drug targets for various diseases can be accomplished using mass spectrometry-based proteomics. However, with mass-limited samples like tumor biopsies, it can be challenging to obtain sufficient amounts of proteins to generate high-quality mass spectrometric data. Techniques developed for macroscale quantities recover sufficient amounts of protein from milligram quantities of starting material, but sample losses become crippling with these techniques when only microgram amounts of material are available. To combat this challenge, proteomicists have developed micro-scale techniques that are compatible with decreased sample size (100 μg or lower) and still enable excellent proteome coverage. Extraction, contaminant removal, protein quantitation, and sample handling techniques for the microgram protein range are reviewed here, with an emphasis on liquid chromatography and bottom-up mass spectrometry-compatible techniques. Also, a range of biological specimens, including mammalian tissues and model cell culture systems, are discussed.