Formaldehyde Derivatization: An Unexpected Side Reaction During Filter-Aided Sample Preparation

From bottom-up to cell surface proteomics: detergents or no detergents, that is the question

Measuring the expression levels of membrane proteins (MPs) is crucial for understanding cell differentiation and tissue specificity, defining disease characteristics, identifying biomarkers, and developing therapeutics. While bottom-up proteomics addresses the need for accurately surveying the membrane proteome, the lower abundance and hydrophobic nature of MPs pose challenges in sample preparation. As MPs normally reside in the lipid bilayer, conventional extraction methods rely on detergents, introducing here a paradox - detergents prevent aggregation and facilitate protein processing, but themselves become contaminants that interfere with downstream analytical applications. Various detergent removal methods exist to mitigate this issue, including filter-aided sample preparation, SP3, suspension trapping, and membrane mimetics. This review delves into the fundamentals of each strategy, applications, merits, and limitations, providing insights into their effectiveness in MP research.

Comparison of filter membranes in the analysis of 183 veterinary and other drugs by liquid chromatography-tandem mass spectrometry

Although filtration is one of the most common steps in sample preparation for chemical analysis, filter membrane materials can leach contaminants and/or retain some analytes in the filtered solutions. In multiclass, multiresidue analysis of veterinary drugs, it is challenging to find one type of filter membrane that does not retain at least some of the analytes before injection in ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). In this study, different filter membranes were tested for use in UHPLC-MS/MS analysis of 183 diverse drugs in bovine muscle, kidney, and liver tissues. Membranes evaluated consisted of polytetrafluoroethylene (PTFE), polyvinylidene difluoride (PVDF), polyethersulfone, nylon, and regenerated cellulose. Drug classes represented among the analytes included β-agonists, β-lactams, anthelmintics, macrolides, tetracyclines, sulfonamides, tranquilizers, (fluoro)quinolones, anti-inflammatories, nitroimidazoles, coccidiostats, phenicols, and others. Although the presence of a matrix helped reduce the binding of analytes on surface active sites, all of the filter types partially retained at least some of the drugs in the final extracts. In testing by flow-injection analysis, all of the membrane filters were also observed to leach interfering components. Ultimately, filtration was avoided altogether in the final sample preparation approach known as the quick, easy, cheap, effective, rugged, safe, efficient, and robust (QuEChERSER) mega-method, and ultracentrifugation was chosen as an alternative.

102-Plex Approach for Accurate and Multiplexed Proteome Quantification

Hyperplexing approaches have been aimed to meet the demand for large-scale proteomic analyses. Currently, the analysis capacity has expanded to up to 54 samples within a single experiment by utilizing different isotopic and isobaric reagent combinations. In this report, we propose a super multiplexed approach to enable the analysis of up to 102 samples in a single experiment, by the combination of our recently developed TAG-TMTpro and TAG-IBT16 labeling. We systematically investigated the identification and quantification performance of the 102-plex approach using the mixtures of E. coli and HeLa peptides. Our results revealed that all labeling series demonstrated accurate and reliable quantification performance. The combination of TAG-IBT16 and TAG-TMTpro approaches expands the multiplexing capacity to 102 plexes, providing a more multiplexed quantification method for even larger-scale proteomic analysis. Data are available via ProteomeXchange with the identifier PXD042398.

Influence of different sample preparation strategies on hypothesis-driven shotgun proteomic analysis of human saliva

This research aimed to find an efficient and repeatable bottom-up proteolytic strategy to process the unstimulated human saliva. The focus is on monitoring immune system activation via the cytokine and interleukin signaling pathways. Carbohydrate metabolism is also being studied as a possible trigger of inflammation and joint damage in the context of the diagnostic procedure of temporomandibular joint disorder. The preparation of clean peptide mixtures for liquid chromatography–mass spectrometry analysis was performed considering different aspects of sample preparation: the filter-aided sample preparation (FASP) with different loadings of salivary proteins, the unfractionated saliva, amylase-depleted, and amylase-enriched salivary fractions. To optimize the efficiency of the FASP method, the protocols with the digestion in the presence of 80% acetonitrile and one-step digestion in the presence of 80% acetonitrile were used, omitting protein reduction and alkylation. The digestion procedures were repeated in the standard in-solution mode. Alternatively, the temperature of 24 and 37°C was examined during the trypsin digestion. DyNet analysis of the hierarchical networks of Gene Ontology terms corresponding to each sample preparation method for the bottom-up assay revealed the wide variability in protein properties. The method can easily be tailored to the specific samples and groups of proteins to be examined.

In Search of a Universal Method: A Comparative Survey of Bottom-Up Proteomics Sample Preparation Methods

Robust, efficient, and reproducible protein extraction and sample processing is a key step for bottom-up proteomics analyses. While many sample preparation protocols for mass spectrometry have been described, selecting an appropriate method remains challenging since some protein classes may require specialized solubilization, precipitation, and digestion procedures. Here, we present a comprehensive comparison of the 16 most widely used sample preparation methods, covering in-solution digests, device-based methods, and commercially available kits. We find a remarkably good performance of the majority of the protocols with high reproducibility, little method dependency, and low levels of artifact formation. However, we revealed method-dependent differences in the recovery of specific protein features, which we summarized in a descriptive guide matrix. Our work thereby provides a solid basis for the selection of MS sample preparation strategies for a given proteomics project.

The Acyl-Proteome of Syntrophus aciditrophicus Reveals Metabolic Relationships in Benzoate Degradation

Syntrophus aciditrophicus is a model syntrophic bacterium that degrades fatty and aromatic acids into acetate, CO2, formate, and H2 that are utilized by methanogens and other hydrogen-consuming microbes. S. aciditrophicus benzoate degradation proceeds by a multistep pathway with many intermediate reactive acyl-coenzyme A species (RACS) that can potentially Nε-acylate lysine residues. Herein, we describe the identification and characterization of acyl-lysine modifications that correspond to RACS in the benzoate degradation pathway. The amounts of modified peptides are sufficient to analyze the post-translational modifications without antibody enrichment, enabling a range of acylations located, presumably, on the most extensively acylated proteins throughout the proteome to be studied. Seven types of acyl modifications were identified, six of which correspond directly to RACS that are intermediates in the benzoate degradation pathway including 3-hydroxypimeloylation, a modification first identified in this system. Indeed, benzoate-degrading enzymes are heavily represented among the acylated proteins. A total of 125 sites were identified in 60 proteins. Functional deacylase enzymes are present in the proteome, indicating a potential regulatory system/mechanism by which S. aciditrophicus modulates acylation. Uniquely, Nε-acyl-lysine RACS are highly abundant in these syntrophic bacteria, raising the compelling possibility that post-translational modifications modulate benzoate degradation in this and potentially other, syntrophic bacteria. Our results outline candidates for further study of how acylations impact syntrophic consortia.

Integrated Strategy for Discovery and Validation of Glycated Candidate Biomarkers for Hemodialysis Patients with Cardiovascular Complications

Glycation plays a pathogenic role in many age-related degenerative pathological conditions, such as diabetes, end-stage renal diseases, and cardiovascular diseases. Mass spectrometry-based qualitative and quantitative analysis methods have been greatly developed and contribute to our understanding of protein glycation. However, it is still challenging to sensitively and accurately quantify endogenous glycated proteome in biological samples. Herein, we proposed an integrated and robust quantitative strategy for comprehensive profiling of early-stage glycated proteome. In this strategy, a filter-assisted sample preparation method was applied to reduce sample loss and improve reproducibility of sample preparation, contributing to high-throughput analysis and accurate quantification of endogenous glycated proteins with low abundance. Standard glycated peptides were spiked and performed the subsequent process together with complex samples both in label-free quantification and multiple reaction monitoring (MRM) analysis, contributing to the improvement of quantitative accuracy. In parallel, a novel approach was developed for the synthesis of heavy isotope-labeled glycated peptides used in MRM analysis. By this way, a total of 1128 endogenous glycated peptides corresponding to 203 serum proteins were identified from 60 runs of 10 pairs of hemodialysis patients with and without cardiovascular complications, and 234 glycated peptides corresponding to 63 proteins existed in >70% runs, among which 17 peptides were discovered to be differentially glycated (P < 0.05, fold-change > 1.5 or <0.67). Furthermore, we validated the glycation difference of four target peptides in 46 serum samples using MRM analysis, which were consistent with our results of label-free quantification.