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

Unveiling the power of proteomics in advancing tropical animal health and production

Proteomics, the large-scale study of proteins in biological systems has emerged as a pivotal tool in the field of animal and veterinary sciences, mainly for investigating local and rustic breeds. Proteomics provides valuable insights into biological processes underlying animal growth, reproduction, health, and disease. In this review, we highlight the key proteomics technologies, methodologies, and their applications in domestic animals, particularly in the tropical context. We also discuss advances in proteomics research, including integration of multi-omics data, single-cell proteomics, and proteogenomics, all of which are promising for improving animal health, adaptation, welfare, and productivity. However, proteomics research in domestic animals faces challenges, such as sample preparation variation, data quality control, privacy and ethical considerations relating to animal welfare. We also provide recommendations for overcoming these challenges, emphasizing the importance of following best practices in sample preparation, data quality control, and ethical compliance. We therefore aim for this review to harness the full potential of proteomics in advancing our understanding of animal biology and ultimately improve animal health and productivity in local breeds of diverse animal species in a tropical context.

A High-Throughput PIXUL-Matrix-Based Toolbox to Profile Frozen and Formalin-Fixed Paraffin-Embedded Tissues Multiomes

Large-scale high-dimensional multiomics studies are essential to unravel molecular complexity in health and disease. We developed an integrated system for tissue sampling (CryoGrid), analytes preparation (PIXUL), and downstream multiomic analysis in a 96-well plate format (Matrix), MultiomicsTracks96, which we used to interrogate matched frozen and formalin-fixed paraffin-embedded (FFPE) mouse organs. Using this system, we generated 8-dimensional omics data sets encompassing 4 molecular layers of intracellular organization: epigenome (H3K27Ac, H3K4m3, RNA polymerase II, and 5mC levels), transcriptome (messenger RNA levels), epitranscriptome (m6A levels), and proteome (protein levels) in brain, heart, kidney, and liver. There was a high correlation between data from matched frozen and FFPE organs. The Segway genome segmentation algorithm applied to epigenomic profiles confirmed known organ-specific superenhancers in both FFPE and frozen samples. Linear regression analysis showed that proteomic profiles, known to be poorly correlated with transcriptomic data, can be more accurately predicted by the full suite of multiomics data, compared with using epigenomic, transcriptomic, or epitranscriptomic measurements individually.

K6-linked ubiquitylation marks formaldehyde-induced RNA-protein crosslinks for resolution

Reactive aldehydes are produced by normal cellular metabolism or after alcohol consumption, and they accumulate in human tissues if aldehyde clearance mechanisms are impaired. Their toxicity has been attributed to the damage they cause to genomic DNA and the subsequent inhibition of transcription and replication. However, whether interference with other cellular processes contributes to aldehyde toxicity has not been investigated. We demonstrate that formaldehyde induces RNA-protein crosslinks (RPCs) that stall the ribosome and inhibit translation in human cells. RPCs in the messenger RNA (mRNA) are recognized by the translating ribosomes, marked by atypical K6-linked ubiquitylation catalyzed by the RING-in-between-RING (RBR) E3 ligase RNF14, and subsequently resolved by the ubiquitin- and ATP-dependent unfoldase VCP. Our findings uncover an evolutionary conserved formaldehyde-induced stress response pathway that protects cells against RPC accumulation in the cytoplasm, and they suggest that RPCs contribute to the cellular and tissue toxicity of reactive aldehydes.

Quantitative Analysis of mRNA and Protein Expression Levels of Aldo-Keto Reductase and Short-Chain Dehydrogenase/Reductase Isoforms in the Human Intestine

Enzymes catalyzing the reduction reaction of xenobiotics are mainly members of the aldo-keto reductase (AKR) and short-chain dehydrogenase/reductase (SDR) superfamilies. The intestine, together with the liver, is responsible for first-pass effects and is an organ that determines the bioavailability of orally administered drugs. In this study, we evaluated the mRNA and protein expression levels of 12 AKR isoforms (AKR1A1, AKR1B1, AKR1B10, AKR1B15, AKR1C1, AKR1C2, AKR1C3, AKR1C4, AKR1D1, AKR1E2, AKR7A2, and AKR7A3) and 7 SDR isoforms (CBR1, CBR3, CBR4, DCXR, DHRS4, HSD11B1, and HSD17B12) in each region of the human intestine using next-generation sequencing and data-independent acquisition proteomics. At both the mRNA and protein levels, most AKR isoforms were highly expressed in the upper regions of the intestine, namely the duodenum and jejunum, and then declined toward the rectum. Among the members in the SDR superfamily, CBR1 and DHRS4 were highly expressed in the upper regions, whereas the expression levels of the other isoforms were almost uniform in all regions. Significant positive correlations between mRNA and protein levels were observed in AKR1A1, AKR1B1, AKR1B10, AKR1C3, AKR7A2, AKR7A3, CBR1, and CBR3. The mRNA level of AKR1B10 was highest, followed by AKR7A3 and CBR1, each accounting for more than 10% of the sum of all AKR and SDR levels in the small intestine. This expression profile in the human intestine was greatly different from that in the human liver, where AKR1C isoforms are predominantly expressed. SIGNIFICANCE STATEMENT: In this study comprehensively determined the mRNA and protein expression profiles of aldo-keto reductase (AKR) and short-chain dehydrogenase/reductase isoforms involved in xenobiotic metabolism in the human intestine and found that most of them are highly expressed in the upper region, where AKR1B10, AKR7A3, and CBR1 are predominantly expressed. Since the intestine is significantly involved in the metabolism of orally administered drugs, the information provided here is valuable for pharmacokinetic studies in drug development.

Control of Selective mRNA Translation in Neuronal Subcellular Compartments in Health and Disease

In multiple cell types, mRNAs are transported to subcellular compartments, where local translation enables rapid, spatially localized, and specific responses to external stimuli. Mounting evidence has uncovered important roles played by local translation in vivo in axon survival, axon regeneration, and neural wiring, as well as strong links between dysregulation of local translation and neurologic disorders. Omic studies have revealed that >1000 mRNAs are present and can be selectively locally translated in the presynaptic and postsynaptic compartments from development to adulthood in vivo A large proportion of the locally translated mRNAs is specifically upregulated or downregulated in response to distinct extracellular signals. Given that the local translatome is large, selectively translated, and cue-specifically remodeled, a fundamental question concerns how selective translation is achieved locally. Here, we review the emerging regulatory mechanisms of local selective translation in neuronal subcellular compartments, their mRNA targets, and their orchestration. We discuss mechanisms of local selective translation that remain unexplored. Finally, we describe clinical implications and potential therapeutic strategies in light of the latest advances in gene therapy.

A microglial activity state biomarker panel differentiates FTD-granulin and Alzheimer's disease patients from controls

BACKGROUND

With the emergence of microglia-modulating therapies there is an urgent need for reliable biomarkers to evaluate microglial activation states.

METHODS

Using mouse models and human induced pluripotent stem cell-derived microglia (hiMGL), genetically modified to yield the most opposite homeostatic (TREM2-knockout) and disease-associated (GRN-knockout) states, we identified microglia activity-dependent markers. Non-targeted mass spectrometry was used to identify proteomic changes in microglia and cerebrospinal fluid (CSF) of Grn- and Trem2-knockout mice. Additionally, we analyzed the proteome of GRN- and TREM2-knockout hiMGL and their conditioned media. Candidate marker proteins were tested in two independent patient cohorts, the ALLFTD cohort (GRN mutation carriers versus non-carriers), as well as the proteomic data set available from the EMIF-AD MBD study.

RESULTS

We identified proteomic changes between the opposite activation states in mouse microglia and CSF, as well as in hiMGL cell lysates and conditioned media. For further verification, we analyzed the CSF proteome of heterozygous GRN mutation carriers suffering from frontotemporal dementia (FTD). We identified a panel of six proteins (FABP3, MDH1, GDI1, CAPG, CD44, GPNMB) as potential indicators for microglial activation. Moreover, we confirmed three of these proteins (FABP3, GDI1, MDH1) to be significantly elevated in the CSF of Alzheimer's (AD) patients. Remarkably, each of these markers differentiated amyloid-positive cases with mild cognitive impairment (MCI) from amyloid-negative individuals.

CONCLUSIONS

The identified candidate proteins reflect microglia activity and may be relevant for monitoring the microglial response in clinical practice and clinical trials modulating microglial activity and amyloid deposition. Moreover, the finding that three of these markers differentiate amyloid-positive from amyloid-negative MCI cases in the AD cohort suggests that these proteins associate with a very early immune response to seeded amyloid. This is consistent with our previous findings in the Dominantly Inherited Alzheimer's Disease Network (DIAN) cohort, where soluble TREM2 increases as early as 21 years before symptom onset. Moreover, in mouse models for amyloidogenesis, seeding of amyloid is limited by physiologically active microglia further supporting their early protective role. The biological functions of some of our main candidates (FABP3, CD44, GPNMB) also further emphasize that lipid dysmetabolism may be a common feature of neurodegenerative disorders.

Prediction of Feed Efficiency and Performance-Based Traits in Fish via Integration of Multiple Omics and Clinical Covariates

Fish aquaculture is a rapidly expanding global industry, set to support growing demands for sources of marine protein. Enhancing feed efficiency (FE) in farmed fish is required to reduce production costs and improve sector sustainability. Recognising that organisms are complex systems whose emerging phenotypes are the product of multiple interacting molecular processes, systems-based approaches are expected to deliver new biological insights into FE and growth performance. Here, we establish 14 diverse layers of multi-omics and clinical covariates to assess their capacities to predict FE and associated performance traits in a fish model (Oncorhynchus tshawytscha) and uncover the influential variables. Inter-omic relatedness between the different layers revealed several significant concordances, particularly between datasets originating from similar material/tissue and between blood indicators and some of the proteomic (liver), metabolomic (liver), and microbiomic layers. Single- and multi-layer random forest (RF) regression models showed that integration of all data layers provide greater FE prediction power than any single-layer model alone. Although FE was among the most challenging of the traits we attempted to predict, the mean accuracy of 40 different FE models in terms of root-mean square errors normalized to percentage was 30.4%, supporting RF as a feature selection tool and approach for complex trait prediction. Major contributions to the integrated FE models were derived from layers of proteomic and metabolomic data, with substantial influence also provided by the lipid composition layer. A correlation matrix of the top 27 variables in the models highlighted FE trait-associations with faecal bacteria (Serratia spp.), palmitic and nervonic acid moieties in whole body lipids, levels of free glycerol in muscle, and N-acetylglutamic acid content in liver. In summary, we identified subsets of molecular characteristics for the assessment of commercially relevant performance-based metrics in farmed Chinook salmon.

A MICROGLIAL ACTIVITY STATE BIOMARKER PANEL DIFFERENTIATES FTD-GRANULIN AND ALZHEIMER'S DISEASE PATIENTS FROM CONTROLS

Background

With the emergence of microglia-modulating therapies there is an urgent need for reliable biomarkers to evaluate microglial activation states.

Methods

Using mouse models and human induced pluripotent stem cell-derived microglia (hiMGL), which were genetically modified to yield the most opposite homeostatic ( TREM2- knockout) and disease-associated ( GRN -knockout) states, we identified microglia activity-dependent markers. Non-targeted mass spectrometry was used to identify changes in microglial and cerebrospinal (CSF) proteome of Grn - and Trem2 -knockout mice. Additionally, we analyzed the proteome of GRN - and TREM2 -knockout hiMGL and their conditioned media. Candidate marker proteins were tested in two independent patient cohorts, the ALLFTD cohort with 11 GRN mutation carriers and 12 non-carriers, as well as the proteomic data set available from the European Medical Information Framework Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD).

Findings

We identified proteomic changes between the opposite activation states in mouse microglia and cerebrospinal fluid (CSF), as well as in hiMGL cell lysates and conditioned media. For further verification, we analyzed the CSF proteome of heterozygous GRN mutation carriers suffering from frontotemporal dementia (FTD). We identified a panel of six proteins (FABP3, MDH1, GDI1, CAPG, CD44, GPNMB) as potential indicators for microglial activation. Moreover, we confirmed three of these proteins (FABP3, GDI1, MDH1) to be significantly elevated in the CSF of AD patients. In AD, these markers differentiated amyloid-positive cases with mild cognitive impairment (MCI) from amyloid-negative individuals.

Interpretation

The identified candidate proteins reflect microglia activity and may be relevant for monitoring the microglial response in clinical practice and clinical trials modulating microglial activity and amyloid deposition. Moreover, the finding that three of these markers differentiate amyloid-positive from amyloid-negative MCI cases in the AD cohort suggests that these marker proteins associate with a very early immune response to seeded amyloid. This is consistent with our previous findings in the DIAN (Dominantly Inherited Alzheimer's Disease Network) cohort, where soluble TREM2 increases as early as 21 years before symptom onset. Moreover, in mouse models for amyloidogenesis, seeding of amyloid is limited by physiologically active microglia further supporting their early protective role. The biological functions of some of our main candidates (FABP3, CD44, GPNMB) also further emphasize that lipid dysmetabolism may be a common feature of neurodegenerative disorders.

Funding

This work was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy - ID 390857198 to CH, SFL and DP) and a Koselleck Project HA1737/16-1 (to CH).

Automated Sample Preparation for Mass Spectrometry-Based Clinical Proteomics

Mass spectrometry (MS)-based proteomics is a rapidly maturing discipline, thus gaining momentum for routine molecular profiling of clinical specimens to improve disease classification, diagnostics, and therapy development. Yet, hurdles need to be overcome to enhance reproducibility in preanalytical sample processing, especially in large, quantity-limited sample cohorts. Therefore, automated sonication and single-pot solid-phase-enhanced sample preparation (autoSP3) was developed as a streamlined workflow that integrates all tasks from tissue lysis and protein extraction, protein cleanup, and proteolysis. It enables the concurrent processing of 96 clinical samples of any type (fresh-frozen or FFPE tissue, liquid biopsies, or cells) on an automated liquid handling platform, which can be directly interfaced to LC-MS for proteome analysis of clinical specimens with high sensitivity, high reproducibility, and short turn-around times.

Proteomic Analysis of Adenovirus 5 by UHPLC-MS/MS: Development of a Robust and Reproducible Sample Preparation Workflow

Adenoviruses (AdVs) have recently become widely used therapeutic vectors for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine. AdVs are large, nonenveloped viruses with an icosahedral capsid formed from several proteins that encloses double-stranded DNA. These proteins are the main components and key players in initial stages of infection by the virus particles, so their heterogeneity and content must be evaluated to ensure product and process consistency. Peptide mapping can provide detailed information on these proteins, e.g., their amino acid sequences and post-translational modifications (PTMs), which is crucial for the development and optimization of the manufacturing processes. However, sample preparation remains the main bottleneck for successful proteomic analysis of the viral proteins (VPs) of AdVs due to their low concentrations and vast stoichiometric ranges. To address this problem, we have developed a fast and efficient protocol for preparing samples for proteomic analysis of VPs of AdV5 that requires no cleaning step prior to liquid chromatography-tandem mass spectrometry (LC-MS/MS). The approach enabled identification of 92% of amino acids in AdV5 VPs on average and quantification of 53 PTMs in a single LC-MS/MS experiment using trypsin protease. The data obtained demonstrate the method's potential utility for supporting the development of novel AdV-based gene therapy products (GTPs).

Proteomic analysis of archival breast cancer clinical specimens identifies biological subtypes with distinct survival outcomes

Despite advances in genomic classification of breast cancer, current clinical tests and treatment decisions are commonly based on protein level information. Formalin-fixed paraffin-embedded (FFPE) tissue specimens with extended clinical outcomes are widely available. Here, we perform comprehensive proteomic profiling of 300 FFPE breast cancer surgical specimens, 75 of each PAM50 subtype, from patients diagnosed in 2008-2013 (n = 178) and 1986-1992 (n = 122) with linked clinical outcomes. These two cohorts are analyzed separately, and we quantify 4214 proteins across all 300 samples. Within the aggressive PAM50-classified basal-like cases, proteomic profiling reveals two groups with one having characteristic immune hot expression features and highly favorable survival. Her2-Enriched cases separate into heterogeneous groups differing by extracellular matrix, lipid metabolism, and immune-response features. Within 88 triple-negative breast cancers, four proteomic clusters display features of basal-immune hot, basal-immune cold, mesenchymal, and luminal with disparate survival outcomes. Our proteomic analysis characterizes the heterogeneity of breast cancer in a clinically-applicable manner, identifies potential biomarkers and therapeutic targets, and provides a resource for clinical breast cancer classification.

Protein level information enables the identification of potential biomarkers and therapeutic targets for breast cancer. Here, the authors perform proteomic analysis of 2 cohorts of breast cancer surgical specimens and identify distinct subtypes, immune features and survival outcomes.

Proteomic profiling in cerebral amyloid angiopathy reveals an overlap with CADASIL highlighting accumulation of HTRA1 and its substrates

Cerebral amyloid angiopathy (CAA) is an age-related condition and a major cause of intracerebral hemorrhage and cognitive decline that shows close links with Alzheimer's disease (AD). CAA is characterized by the aggregation of amyloid-β (Aβ) peptides and formation of Aβ deposits in the brain vasculature resulting in a disruption of the angioarchitecture. Capillaries are a critical site of Aβ pathology in CAA type 1 and become dysfunctional during disease progression. Here, applying an advanced protocol for the isolation of parenchymal microvessels from post-mortem brain tissue combined with liquid chromatography tandem mass spectrometry (LC-MS/MS), we determined the proteomes of CAA type 1 cases (n = 12) including a patient with hereditary cerebral hemorrhage with amyloidosis-Dutch type (HCHWA-D), and of AD cases without microvascular amyloid pathology (n = 13) in comparison to neurologically healthy controls (n = 12). ELISA measurements revealed microvascular Aβ1-40 levels to be exclusively enriched in CAA samples (mean: > 3000-fold compared to controls). The proteomic profile of CAA type 1 was characterized by massive enrichment of multiple predominantly secreted proteins and showed significant overlap with the recently reported brain microvascular proteome of patients with cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), a hereditary cerebral small vessel disease (SVD) characterized by the aggregation of the Notch3 extracellular domain. We found this overlap to be largely attributable to the accumulation of high-temperature requirement protein A1 (HTRA1), a serine protease with an established role in the brain vasculature, and several of its substrates. Notably, this signature was not present in AD cases. We further show that HTRA1 co-localizes with Aβ deposits in brain capillaries from CAA type 1 patients indicating a pathologic recruitment process. Together, these findings suggest a central role of HTRA1-dependent protein homeostasis in the CAA microvasculature and a molecular connection between multiple types of brain microvascular disease.

Proximity labeling for investigating protein-protein interactions

The study of protein complexes and protein-protein interactions is of great importance due to their fundamental roles in cellular function. Proximity labeling, often coupled with mass spectrometry, has become a powerful and versatile tool for studying protein-protein interactions by enriching and identifying proteins in the vicinity of a specified protein-of-interest. Here, we describe and compare traditional approaches to investigate protein-protein interactions to current day state-of-the-art proximity labeling methods. We focus on the wide array of proximity labeling strategies and underscore studies using diverse model systems to address numerous biological questions. In addition, we highlight current advances in mass spectrometry-based technology that exhibit promise in improving the depth and breadth of the data acquired in proximity labeling experiments. In all, we show the diversity of proximity labeling strategies and emphasize the broad range of applications and biological inquiries that can be addressed using this technology.

Effect of polyethylene glycol 20 000 on protein extraction efficiency of formalin-fixed paraffin-embedded tissues in South Africa

BACKGROUND

Optimal protocols for efficient and reproducible protein extraction from formalin-fixed paraffin-embedded (FFPE) tissues are not yet standardised and new techniques are continually developed and improved. The effect of polyethylene glycol (PEG) 20 000 on protein extraction efficiency has not been evaluated using human FFPE colorectal cancer tissues and there is no consensus on the protein extraction solution required for efficient, reproducible extraction.

OBJECTIVE

The impact of PEG 20 000 on protein extraction efficiency, reproducibility and protein selection bias was evaluated using FFPE colonic tissue via liquid chromatography tandem mass spectrometry analysis.

METHODS

This study was conducted from August 2017 to July 2019 using human FFPE colorectal carcinoma tissues from the Anatomical Pathology department at Tygerberg Hospital in South Africa. Samples were analysed via label-free liquid chromatography tandem mass spectrometry to determine the impact of using PEG 20 000 in the protein extraction solution. Data were assessed regarding peptide and protein identifications, method efficiency, reproducibility, protein characteristics and organisation relating to gene ontology categories.

RESULTS

Polyethylene glycol 20 000 exclusion increased peptides and proteins identifications and the method was more reproducible compared to the samples processed with PEG 20 000. However, no differences were observed with regard to protein selection bias. We found that higher protein concentrations (> 10 µg) compromised the function of PEG.

CONCLUSION

This study indicates that protocols generating high protein yields from human FFPE tissues would benefit from the exclusion of PEG 20 000 in the protein extraction solution.

Strategies for mass spectrometry-based phosphoproteomics using isobaric tagging

INTRODUCTION

Protein phosphorylation is a primary mechanism of signal transduction in cellular systems. Isobaric tagging can be used to investigate alterations in phosphorylation events in sample multiplexing experiments where quantification extends across all conditions. As such, innovations in tandem mass tag methods can facilitate the expansion of the depth and breadth of phosphoproteomic analyses.

AREAS COVERED

This review discusses the current state of tandem mass tag-centric phosphoproteomics and highlights advances in reagent chemistry, instrumentation, data acquisition, and data analysis. We stress that approaches for phosphoproteomic investigations require high-specificity enrichment, sensitive detection, and accurate phosphorylation site localization.

EXPERT OPINION

Tandem mass tag-centric phosphoproteomics will continue to be an important conduit for our understanding of signal transduction in living organisms. We anticipate that progress in phosphopeptide enrichment methodologies, enhancements in instrumentation and data acquisition technologies, and further refinements in analytical strategies will be key to the discovery of biologically relevant findings from phosphoproteomics studies.

Proteotranscriptomic classification and characterization of pancreatic neuroendocrine neoplasms

Pancreatic neuroendocrine neoplasms (PNENs) are biologically and clinically heterogeneous. Here, we use a multi-omics approach to uncover the molecular factors underlying this heterogeneity. Transcriptomic analysis of 84 PNEN specimens, drawn from two cohorts, is substantiated with proteomic profiling and identifies four subgroups: Proliferative, PDX1-high, Alpha cell-like and Stromal/Mesenchymal. The Proliferative subgroup, consisting of both well- and poorly differentiated specimens, is associated with inferior overall survival probability. The PDX1-high and Alpha cell-like subgroups partially resemble previously described subtypes, and we further uncover distinctive metabolism-related features in the Alpha cell-like subgroup. The Stromal/Mesenchymal subgroup exhibits molecular characteristics of YAP1/WWTR1(TAZ) activation suggestive of Hippo signaling pathway involvement in PNENs. Whole-exome sequencing reveals subgroup-enriched mutational differences, supported by activity inference analysis, and identifies hypermorphic proto-oncogene variants in 14.3% of sequenced PNENs. Our study reveals differences in cellular signaling axes that provide potential directions for PNEN patient stratification and treatment strategies.

A Semiautomated Paramagnetic Bead-Based Platform for Isobaric Tag Sample Preparation

The development of streamlined and high-throughput sample processing workflows is important for capitalizing on emerging advances and innovations in mass spectrometry-based applications. While the adaptation of new technologies and improved methodologies is fast paced, automation of upstream sample processing often lags. Here we have developed and implemented a semiautomated paramagnetic bead-based platform for isobaric tag sample preparation. We benchmarked the robot-assisted platform by comparing the protein abundance profiles of six common parental laboratory yeast strains in triplicate TMTpro16-plex experiments against an identical set of experiments in which the samples were manually processed. Both sets of experiments quantified similar numbers of proteins and peptides with good reproducibility. Using these data, we constructed an interactive website to explore the proteome profiles of six yeast strains. We also provide the community with open-source templates for automating routine proteomics workflows on an opentrons OT-2 liquid handler. The robot-assisted platform offers a versatile and affordable option for reproducible sample processing for a wide range of protein profiling applications.

Evaluation of Protein Purification Techniques and Effects of Storage Duration on LC-MS/MS Analysis of Archived FFPE Human CRC Tissues

To elucidate cancer pathogenesis and its mechanisms at the molecular level, the collecting and characterization of large individual patient tissue cohorts are required. Since most pathology institutes routinely preserve biopsy tissues by standardized methods of formalin fixation and paraffin embedment, these archived FFPE tissues are important collections of pathology material that include patient metadata, such as medical history and treatments. FFPE blocks can be stored under ambient conditions for decades, while retaining cellular morphology, due to modifications induced by formalin. However, the effect of long-term storage, at resource-limited institutions in developing countries, on extractable protein quantity/quality has not yet been investigated. In addition, the optimal sample preparation techniques required for accurate and reproducible results from label-free LC-MS/MS analysis across block ages remains unclear. This study investigated protein extraction efficiency of 1, 5, and 10-year old human colorectal carcinoma resection tissue and assessed three different gel-free protein purification methods for label-free LC-MS/MS analysis. A sample size of n = 17 patients per experimental group (with experiment power = 0.7 and α = 0.05, resulting in 70% confidence level) was selected. Data were evaluated in terms of protein concentration extracted, peptide/protein identifications, method reproducibility and efficiency, sample proteome integrity (due to storage time), as well as protein/peptide distribution according to biological processes, cellular components, and physicochemical properties. Data are available via ProteomeXchange with identifier PXD017198. The results indicate that the amount of protein extracted is significantly dependent on block age (p < 0.0001), with older blocks yielding less protein than newer blocks. Detergent removal plates were the most efficient and overall reproducible protein purification method with regard to number of peptide and protein identifications, followed by the MagReSyn® SP3/HILIC method (with on-bead enzymatic digestion), and lastly the acetone precipitation and formic acid resolubilization method. Overall, the results indicate that long-term storage of FFPE tissues (as measured by methionine oxidation) does not considerably interfere with retrospective proteomic analysis (p > 0.1). Block age mainly affects initial protein extraction yields and does not extensively impact on subsequent label-free LC-MS/MS analysis results.

Advances in quantitative high-throughput phosphoproteomics with sample multiplexing

Eukaryotic protein phosphorylation modulates nearly every major biological process. Phosphorylation regulates protein activity, mediates cellular signal transduction, and manipulates cellular structure. Consequently, the dysregulation of kinase and phosphatase pathways has been linked to a multitude of diseases. Mass spectrometry-based proteomic techniques are increasingly used for the global interrogation of perturbations in phosphorylation-based cellular signaling. Strategies for studying phosphoproteomes require high-specificity enrichment, sensitive detection, and accurate localization of phosphorylation sites with advanced LC-MS/MS techniques and downstream informatics. Sample multiplexing with isobaric tags has also been integral to recent advancements in throughput and sensitivity for phosphoproteomic studies. Each of these facets of phosphoproteomics analysis present distinct challenges and thus opportunities for improvement and innovation. Here, we review current methodologies, explore persistent challenges, and discuss the outlook for isobaric tag-based quantitative phosphoproteomic analysis.

Covalent Modification of Proteins by Plant-Derived Natural Products: Proteomic Approaches and Biological Impacts

Plant-derived natural products (NPs) with electrophilic functional groups engage various subsets of the proteome via covalent modification of nucleophilic cysteine residues. This electrophile-nucleophile interaction can change protein conformation, alter protein function, and modulate their biological action. The biological significance of these covalent protein modifications in health and disease is increasingly recognized. One way to understand covalent NP-protein interactions is to utilize traditional proteomics and modern mass spectrometry (MS)-based proteomic strategies. These strategies have proven effective in uncovering specific NP protein targets and are critical first steps that allow for a much deeper understanding of the ability of NPs to modulate cellular processes. Here, plant-derived NPs that covalently modify proteins are reviewed, the biological significance of these covalent modifications, and the different proteomic strategies that have been employed to study these NP-protein interactions.

Liquid Biopsy of Bile based on Targeted Mass Spectrometry for the Diagnosis of Malignant Biliary Strictures

Bile holds biomarkers of malignant biliary strictures (MBS) but is unsuited for automated analyzers used in routine diagnostic laboratories. Selected reaction monitoring (SRM) is a flexible high‐throughput analytical approach based on targeted mass spectrometry (MS) already implemented in clinical settings. We tested the hypothesis that SRM could be used to quantify cancer biomarkers in human bile. An SRM‐based assay was developed to simultaneously quantify up to 37 peptides from 13 bile proteins in a developmental cohort of 15 patients (MBS, n = 8; benign biliary stricture or obstruction (BBS), n = 7). The most reliable biomarkers were then absolutely quantified by SRM in a verification cohort of 67 patients (MBS, n = 37; BBS, n = 30). The diagnostic performances of single and combined biomarkers were assessed. In the developmental cohort, SRM‐based analysis revealed six protein biomarkers with significantly higher peptide ratios (endogenous vs. standard) in bile from MBS vs. BBS. In the verification cohort, five of these biomarkers proved good diagnostic ability (individual receiver operating characteristic‐area under the receiver operating characteristic curve (ROC‐AUC) up to 0.889, accuracies from 67.8% to 83.1%). Combining bile biomarkers and serum CA19‐9 in 2 panels allowed differentiating MBS from BBS with up to 0.929 ROC‐AUC and 89.8% accuracy. In this study, a newly developed SRM‐based assay proved able to simultaneously quantify multiple biomarkers in bile samples. The combination of bile biomarkers with serum CA19‐9 was highly accurate for the diagnosis of MBS. Liquid biopsy of bile based on targeted MS is eligible to support MBS diagnosis in clinical practice.

Growth media selection alters the proteome profiles of three model microorganisms

The selection of growth media is a very important consideration of any cell-based proteomics experiment. Alterations thereof may result in differences in basal proteomes simply due to disparities in the metabolite composition of the media. We investigate the effect of growth media on the proteomes of three microorganisms, specifically E. coli, S. cerevisiae, and S. pombe, using tandem mass tag (TMT)-based quantitative proteomics. We compared the protein abundance profiles of these microorganisms propagated in two distinct growth media that are commonly used for the respective organism. Our sample preparation strategy included SP3 bead-assisted protein isolation and digestion. In addition, we assembled a replicate set of samples in which we altered the proteolytic digestion from sequential treatment with LysC and trypsin to only LysC. Despite differences in peptides identified and a drop in quantified proteins, the results were similar between the two datasets for all three microorganisms. Approximately 10% of the proteins of each respective microorganism were significantly altered in each dataset. As expected, gene ontology analysis revealed that the majority of differentially expressed proteins are implicated in metabolism. These data emphasize further the importance and the potential consequences of growth media selection. SIGNIFICANCE: Various microorganisms are used as model systems throughout in biological studies, including proteomics-based investigations. The growth conditions of these organisms are of utmost importance, of which one major consideration is the choice of growth media. We hypothesize that growth media selection has a considerable impact on the baseline proteome of a given microorganism. To test this hypothesis, we used tandem mass tag (TMT)-based quantitative multiplexed proteomics to profile the proteomes of E. coli, S. cerevisiae, and S. pombe each grown in two different, yet common, growth media for the respective species. Our data show that approximately 10% of the proteins of each respective microorganism were significantly altered and that many of the differentially expressed proteins are implicated in metabolism. We provide several datasets which are potentially valuable for growth media selection with respect to downstream biochemical analysis.

Multiplexed proteome profiling of carbon source perturbations in two yeast species with SL-SP3-TMT

Saccharomyces cerevisiae and Schizosaccharomyces pombe are the most commonly studied yeast model systems, yet comparisons of global proteome remodeling between these yeast species are scarce. Here, we profile the proteomes of S. cerevisiae and S. pombe cultured with either glucose or pyruvate as the sole carbon source to define common and distinctive alterations in the protein landscape across species. In addition, we develop an updated streamlined-tandem mass tag (SL-TMT) strategy that substitutes chemical-based precipitation with more versatile bead-based protein aggregation method (SP3) prior to enzymatic digestion and TMT labeling. Our new workflow, SL-SP3-TMT, allow for near-complete proteome profiles in a single experiment for each species. The data reveal expected alterations in protein abundance and differences between species, highlighted complete canonical biochemical pathways, and provided insight into previously uncharacterized proteins. The techniques used herein, namely SL-SP3-TMT, can be applied to virtually any experiment aiming to study remodeling of the proteome using a high-throughput, comprehensive, yet streamlined mass spectrometry-based strategy. SIGNIFICANCE: Saccharomyces cerevisiae and Schizosaccharomyces pombe are single-celled eukaryotes that diverged from a common ancestor over a period of 100 million years, such that evolution has driven fundamental differences between the two species. Cellular metabolism and the regulation thereof are vital for living organisms. Here, we hypothesize that large scale proteomic alterations are prevalent upon the substitution of glucose with another carbon source, in this case pyruvate. To efficiently process our samples, we developed an updated streamlined-tandem mass tag (SL-TMT) strategy with more versatile bead-based protein aggregation. The data revealed expected alterations in protein abundance and illustrated differences between species. We highlighted complete canonical biochemical pathways and provided insight into previously uncharacterized proteins.

Local translation in neurons: visualization and function

Neurons are among the most compartmentalized and interactive of all cell types. Like all cells, neurons use proteins as the main sensors and effectors. The modification of the proteome in axons and dendrites is used to guide the formation of synaptic connections and to store information. In this Review, we discuss the data indicating that an important source of protein for dendrites, axons and their associated elements is provided by the local synthesis of proteins. We review the data indicating the presence of the machinery required for protein synthesis, the direct visualization and demonstration of protein synthesis, and the established functional roles for local translation for many different neuronal functions. Finally, we consider the open questions and future directions in this field.