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optiPRM: A Targeted Immunopeptidomics LC-MS Workflow With Ultra-High Sensitivity for the Detection of Mutation-Derived Tumor Neoepitopes From Limited Input Material.

Personalized cancer immunotherapies such as therapeutic vaccines and adoptive transfer of T cell receptor-transgenic T cells rely on the presentation of tumor-specific peptides by human leukocyte antigen class I molecules to cytotoxic T cells. Such neoepitopes can for example arise from somatic mutations and their identification is crucial for the rational design of new therapeutic interventions. Liquid chromatography mass spectrometry (LC-MS)-based immunopeptidomics is the only method to directly prove actual peptide presentation and we have developed a parameter optimization workflow to tune targeted assays for maximum detection sensitivity on a per peptide basis, termed optiPRM. Optimization of collision energy using optiPRM allows for the improved detection of low abundant peptides that are very hard to detect using standard parameters. Applying this to immunopeptidomics, we detected a neoepitope in a patient-derived xenograft from as little as 2.5 × 106 cells input. Application of the workflow on small patient tumor samples allowed for the detection of five mutation-derived neoepitopes in three patients. One neoepitope was confirmed to be recognized by patient T cells. In conclusion, optiPRM, a targeted MS workflow reaching ultra-high sensitivity by per peptide parameter optimization, makes the identification of actionable neoepitopes possible from sample sizes usually available in the clinic.

Humans

Reframing Proteomics Measurement: Super Mass Spectrometry Framework and the Role of Delayed Electrospray Ionization Technique.

Dynamic range, repeatability, and reproducibility remain the central limitations of data-independent acquisition (DIA) proteomics. Current workflows emphasize protein group identification counts and throughput, but these metrics mask the fundamental measurement challenge: generating a repeatable, reproducible, high-fidelity, and relatively complete digital representation of complex proteomes. In particular, plasma proteomics spans more than 10 orders of magnitude in protein abundance, far exceeding the capacity and dynamic range of any single mass spectrometer. Incremental advances have not closed this gap. In this Perspectives article, I introduce the Super Mass Spectrometry framework and then highlight the Delayed Electrospray Ionization (Delayed-ESI) technique, as a practical approach to address these limitations. By producing compositionally identical but temporally staggered ion beams, the Delayed-ESI technique enables deterministic remeasurement of the same analyte profile, supporting various novel strategies to improve analytical figures of merit. While recent implementations of the Delayed-ESI technique have emphasized throughput, I argue that the broader value of the Delayed-ESI technique lies in extending dynamic range and improving repeatability and reproducibility─objectives that should take precedence if proteomics is to evolve into a robust measurement science capable of supporting population-scale proteomics studies.

Proteomics

A streamlined workflow for high throughput metaproteomic analysis of the rumen microbiome.

Metaproteomics can provide direct functional insights into complex microbial communities, yet its application in rumen research remains limited due to labor-intensive and low-throughput sample preparation workflows before the MS analysis. This work aimed to develop and characterize a streamlined, high throughput metaproteomic workflow optimized for rumen samples. Key steps, including microbial cell extraction, cell lysis, protein digestion, and LC-MS/MS acquisition, were systematically assessed and optimized to reduce hands-on time while maintaining deep proteome coverage. The optimized workflow integrates a minimized cell extraction protocol using 0.5 g starting material and in-solution tryptic digestion. Application of the final workflow to 72 samples from in vitro fermentation revealed that biological variability between inocula dominated technical variability, which remained moderate (median CV of 21-24% across batches). Overall, the optimized workflow supports robust taxonomic and functional characterization of the rumen microbiome with improved scalability. These advances provide a foundation for applying metaproteomics to larger experimental designs, including nutritional trials and cohort studies, thereby enabling broader functional interrogation of rumen microbial ecosystems. SIGNIFICANCE: This study addresses current limitations in the application of metaproteomics to rumen microbiome research by developing a streamlined and scalable sample preparation workflow. By optimizing key steps and reducing sample input while maintaining reproducibility and proteome coverage, this work enables more efficient processing of larger sample sets. These advances support the broader use of metaproteomics in rumen studies and facilitate functional investigations relevant to animal nutrition and sustainable livestock production.

Animals

Canalesolide A, a Structurally Unique Polyhydroxy Macrolide from the Marine Cyanobacterium Okeania sp. with Potent Antitrypanosomal Activity.

The discovery of structurally novel natural products remains central to expanding biologically relevant chemical space, particularly within underexplored marine metabolite classes. Herein, we report the discovery and complete structural elucidation of canalesolide A, a new polyhydroxylated macrolide isolated from the marine cyanobacterium Okeania sp. The compound was identified through an integrated workflow combining phenotypic screening against Trypanosoma brucei and LC-MS/MS-based molecular networking, enabling rapid prioritization of bioactive fractions and dereplication of known metabolite families. Spectroscopic analysis revealed that canalesolide A belongs to the bastimolide-related class of macrolides but exhibits a distinct structural architecture. Its structure was established by integrating ultrahigh-resolution NMR spectroscopy, empirical configurational analysis of polyol systems, targeted model compound synthesis, and controlled chemical degradation and derivatization. This combined strategy resolved stereochemical motifs that were inaccessible by direct analysis of the intact macrolide alone, providing a transferable approach for assigning densely oxygenated marine macrolides. Genome mining identified the putative biosynthetic gene cluster and proposed biosynthetic pathway for a bastimolide-related macrolide. Canalesolide A displays potent, low nanomolar antitrypanosomal activity against human-infective subspecies of T. brucei with rapid elimination of parasites within 1 h at 1 μM. Although moderate mammalian cytotoxicity was observed, preliminary in vivo efficacy/toxicity studies in infected mice suggest a narrow therapeutic window highlighting the need for improved selectivity. This study expands the structural and biosynthetic diversity of polyhydroxylated macrolides and establishes a generalizable framework for resolving stereochemically complex natural products.

Macrolides

Multi-omic analyses of the same sample using metabolomics, lipidomics, proteomics, phosphoproteomics, and glycoproteomics.

Mass spectrometry (MS)-based multi-omics offers powerful tools to comprehensively characterize proteins, post-translational modifications, metabolites, and lipids. However, these measurements are typically performed using separate sample preparation workflows and modality-specific liquid chromatography mass spectrometry (LC-MS) platforms, limiting integration and constraining applications to small amounts of sample materials, especially scarce clinical specimens. Here, we describe a unified nano-LC-MS framework that enables metabolomic, lipidomic, proteomic, phosphoproteomic, and glycoproteomic analyses from the same starting material using a single nano-LC-MS platform, with only the chromatographic conditions, acquisition methods, and enrichment procedures tailored to each omics. This integrated strategy reduces workflow complexity and sample consumption while improves analytical continuity across molecular layers. By enabling deep multi-omics characterization from the same sample, this platform provides a practical foundation for comprehensive analysis of precious clinical samples.

Proteomics

Benchmarking the OptiSpray-μPAC Workflow against a Traditional Nanospray Capillary Interface for Multiplexed Quantitative Proteomics.

Nanoflow liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) underpins modern quantitative proteomics, yet the column-to-mass spectrometer interface remains an important yet often underappreciated determinant of analytical depth, sensitivity, and reproducibility. Here, we benchmark an integrated workflow comprising the newly developed OptiSpray ion source and a micropillar array column (μPAC) cartridge against a conventional Nanospray Flex Source with an Accucore resin-packed capillary column. We performed a TMTpro 18-plex experiment across nine human cell lines on a FAIMS Pro-equipped Orbitrap Exploris 480. Following basic-pH reversed-phase fractionation, 12 fractions were analyzed on both workflow configurations under matched chromatographic gradient and acquisition conditions. Across both configurations, we quantified >9000 protein groups with highly comparable quantitative reproducibility and principal component clustering. Direct comparison of protein abundance ratios across cell lines showed agreement (Pearson R2 ≈ 0.7-0.8) without systematic bias. These results were achieved without workflow-specific optimization of the OptiSpray-μPAC platform, enabling direct transfer of established acquisition methods. Despite differences in column architecture, both configurations delivered comparable proteome coverage and quantitative fidelity. These findings establish the OptiSpray-μPAC workflow as a standardized alternative to conventional capillary-based interfaces, offering simplified operation while preserving quantitative performance.

Humans

13C Stable Isotope Tracing-Based MFA Reveals the Contribution of Glucose to Glycolytic and TCA Fluxes and Its Application in Depression Research.

Metabolomics is widely applied to dissect metabolic pathways and their correlations with biological phenotypes. Unlike genomics and proteomics, metabolites exhibit substantial heterogeneity in chemical structure, physicochemical properties, and biological origin. Accordingly, pathway enrichment and annotation relying merely on alterations in metabolite abundance are prone to incomplete coverage, ionization bias, and ambiguous annotation, which inevitably impair the accuracy of pathway interpretation. Metabolic flux analysis (MFA) coupled with stable isotope-resolved metabolomics (SIRM) offers a powerful quantitative framework for tracing in vivo carbon flow and estimating reaction fluxes across key metabolic nodes. Glucose metabolism lies at the core of systemic energy homeostasis; however, most current investigations are confined to cell lines or in vitro systems, and a simple, easy-to-implement computational pipeline for in vivo glucose flux analysis in animal models is still lacking. Herein, we established an in vivo 13C-labeling-based MFA workflow to trace and resolve the systemic metabolic fate of glucose in rats. The pipeline covers tracer administration, sample preparation, LC-MS detection, isotopologue data acquisition and correction, construction of a glucose-metabolism-related metabolite database, MFA model establishment, and metabolic flux quantification. By infusing rats with [U-13C6]-glucose and [U-13C3]-sodium L-lactate, we precisely characterized the in vivo metabolic fates of circulating glucose and lactate and quantified their respective contributions to glycolytic flux and tricarboxylic acid (TCA) cycle flux. We further applied this workflow to profile energy metabolic reprogramming in depression. The results revealed a systemic shift toward aerobic glycolysis in rats exposed to chronic unpredictable mild stress (CUMS). Overall, the expanded application of this MFA strategy can provide mechanistic and quantitative insights into the regulation of metabolic pathways.

Animals

PANAMA-enabled high-sensitivity dual nanoflow LC-MS metabolomics and proteomics analysis.

High-sensitivity nanoflow liquid chromatography (nLC) is seldom employed in untargeted metabolomics because current sample preparation techniques are inefficient at preventing nanocapillary column performance degradation. Here, we describe an nLC-based tandem mass spectrometry workflow that enables seamless joint analysis and integration of metabolomics (including lipidomics) and proteomics from the same samples without instrument duplication. This workflow is based on a robust solid-phase micro-extraction step for routine sample cleanup and bioactive molecule enrichment. Our method, termed proteomic and nanoflow metabolomic analysis (PANAMA), improves compound resolution and detection sensitivity without compromising the depth of coverage as compared with existing widely used analytical procedures. Notably, PANAMA can be applied to a broad array of specimens, including biofluids, cell lines, and tissue samples. It generates high-quality, information-rich metabolite-protein datasets while bypassing the need for specialized instrumentation.

Proteomics

2-Mercaptoethanol/DMSO Workflow Enables Highly Reproducible Quantitative Proteomics.

Proteomics provides a systematic and high-throughput approach to comprehensively characterize protein networks, enabling insights into cellular functions and disease mechanisms. Carbamidomethylation using iodoacetamide (IAA), a common method for cysteine alkylation, is known to cause nonspecific modifications that increase spectral complexity in mass spectrometry and reduce quantitative accuracy. Here, we established a reproducibility-focused 2-mercaptoethanol (2-ME)/dimethyl sulfoxide (DMSO) workflow and systematically evaluated its quantitative performance at the proteome-wide level. Mouse liver proteomes were processed using either 2-ME/DMSO or conventional IAA treatment, followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. The optimized 2-ME treatment increased the number of cysteine-modified peptides by 1.6- to 1.9-fold. Although total protein identifications were comparable, 77% of proteins exhibited improved sequence coverage with the optimized 2-ME treatment. Quantitative reproducibility was also enhanced, with the peptide quantified CV ≤ 20% increasing from 61.4% with IAA treatment to 86.1% with 2-ME treatment, and protein quantified CV ≤ 20% increasing from 80.6% with IAA treatment to 93.5% with 2-ME treatment. Application of this new workflow to ovarian clear cell carcinoma reliably detected cisplatin-induced alterations. The 2-ME/DMSO workflow offers a simple and highly reproducible proteomics strategy for accurate quantitative proteomics.

Animals

An Instrumental Optimization of a Label-Free Proteomic Method for Trace Protein Input.

Liquid chromatography-mass spectrometry (LC-MS)-based proteomics of trace-level samples, such as tens of cells or spatially resolved tissue regions, offers unique biological insights but is often constrained by the requirement for specialized, costly instrumentation. In this study, we developed a scalable workflow for the deep proteomic analysis of low- to ultralow-input samples by systematically optimizing a widely adopted Orbitrap and UHPLC platform to maximize sensitivity, precision, and throughput. This optimized workflow identified over 5600 proteins from 5 ng of peptides and 3400 proteins from 20 sorted cells, achieving a throughput of 30 analyses per day while maintaining deep proteome coverage and high quantitative reproducibility. Furthermore, by applying this method to spatially resolved proteomics, we identified over 6100 proteins from microscale regions of interest (ROIs) within a formalin-fixed, paraffin-embedded (FFPE) tissue. A data-driven normalization strategy was employed to correct for variable cellularity across tissue regions, effectively revealing intratumor heterogeneity and distinct molecular and functional signatures, including pathway activations not apparent in parallel spatial transcriptomic analysis. Ultimately, this accessible, high-performance method substantially lowers the instrumentation barrier for the deep proteomic profiling of trace-level biological samples.

Proteomics

ChromID: A Protocol for Mapping Protein Chromatin Interactions in Living Cells.

Chromatin modifications regulate genome function by recruiting proteins that control transcription, genome organization, and DNA repair. Identifying the proteins associated with specific chromatin modifications is therefore essential for understanding how these regulatory processes operate. Traditional approaches, including chromatin immunoprecipitation and affinity purification coupled to mass spectrometry, have uncovered many chromatin-associated proteins. However, they often rely on crosslinking and chromatin fragmentation, which can disrupt native chromatin architecture and limit the detection of transient interactions. Here, we describe a proximity-labeling protocol for identifying the chromatin-dependent protein interactome associated with specific chromatin marks, termed ChromID. ChromID uses engineered chromatin readers (eCRs) fused to a promiscuous biotin ligase, which labels proteins in the immediate vicinity of the targeted chromatin mark. The protocol includes in vivo biotin labeling, nuclear extract preparation, streptavidin-based enrichment, and tryptic digestion for downstream LC-MS/MS analysis. The protocol has been validated across multiple cell types and chromatin contexts and can be extended to other chromatin-associated proteins, providing a versatile approach to profile chromatin-associated proteomes within their native cellular environment. Key features • Maps proteins associated with different chromatin modifications in living cells using engineered chromatin readers fused to TurboID, BASU, or other promiscuous biotin ligases. • Preserves native chromatin organization and captures transient chromatin-associated interactions that are often lost during conventional affinity purification workflows. • Validated across multiple chromatin contexts, including histone modifications, DNA methylation, transcription factors, RNA polymerase II, and DNA damage-associated chromatin states. • Applicable to diverse cell types and organisms and adaptable to other chromatin-associated proteins, including transcription factors and chromatin regulators.

Biotin proximity labeling

Targeted Modulation of Abundant Proteins Enhances Proteomic Profiling of Ovarian Cancer Ascites: A Pilot Technical Workflow Comparison.

Ascites from ovarian cancer patients are increasingly recognized as a valuable biofluid for cancer research, as its protein composition reflects the disease state and may reveal biomarkers of treatment sensitivity and response. However, the detection of low-abundance proteins is hindered by the presence of highly abundant proteins such as albumin. In this study, we evaluated five protein preparation methods for their effectiveness in depleting high-abundance or enriching low-abundance proteins in ovarian cancer ascites. The Norgen (Nor), Minutes (Min), and Perchloric acid (PerCA) methods were based on abundant protein depletion, while the Urine (Uri) and Nanomics (Nano) kits focused on low-abundance protein enrichment. Processed samples were analyzed using label-free quantitative bottom-up proteomics by LC-MS/MS, followed by a bioinformatics assessment. Compared with undepleted ascites (UnD), Min, Nor, Nano, and PerCA increased protein identifications, whereas Uri produced profiles similar to those of UnD. Notably, PerCA and Nano enabled the identification of distinct protein subsets associated with cancer-related pathways, including immune responses and autophagy. PerCA enriched transmembrane and secreted immunomodulatory glycoproteins, whereas Nano enrichment primarily captured secreted, nuclear, and cytoplasmic soluble proteins. Overall, our results show that both high-abundance protein depletion and low-abundance enrichment improve ascites proteome coverage, each offering distinct advantages in identifying biologically relevant low-abundance proteins.

Female

Proteomic profiling of the aqueous extract from the antennal gland of the Pacific white shrimp, Litopenaeus vannamei.

The antennal gland (AnG) of decapod crustaceans has been proposed as a potential source of bioactive molecules involved in chemical communication; however, its protein composition remains largely unexplored. Here, we present the first reference proteomic map of the aqueous extract from the antennal gland of the Pacific white shrimp Litopenaeus vannamei. Protein extracts from immature and mature females were analyzed using an integrated workflow combining one-dimensional SDS-PAGE, reverse-phase high-performance liquid chromatography (RP-HPLC), and nanoLC-tandem mass spectrometry. Electrophoretic and chromatographic analyses revealed a high degree of qualitative similarity between reproductive stages. SDS-PAGE resolved six major protein bands (∼227, 166, 77, 42, 35, and 17 kDa), most comprising multiple co-migrating proteins as revealed by LC-MS/MS. Hemocyanin was identified as the predominant protein and was detected across several electrophoretic bands. Additional proteins were associated with innate immunity, including β-1,3-glucan-binding protein and coagulable hemolymph protein; reproductive processes, including vitellogenin, spermatogonial stem-cell renewal factor, farnesoic acid O-methyltransferase, estrogen sulfotransferase, and prostaglandin reductase 1; as well as energy metabolism, protein homeostasis, cytoskeletal organization, and intracellular trafficking. Because several identified proteins are widely distributed or known hemolymph components, their detection cannot be assumed to reflect AnG-specific expression or function. Collectively, these findings establish a molecular reference for the L. vannamei AnG and reveal protein components associated with multiple physiological processes. This dataset provides a proteomic framework for future comparative and functional studies aimed at elucidating antennal gland physiology and experimentally evaluating the potential involvement of proteinaceous or peptide-based molecules in chemical communication in decapod crustaceans.

Animals

Relaxin-2: Shaping the Proteomic Landscape of Skeletal Muscle Physiology, Glucose Trafficking, and Mitochondrial Function in Rat.

Relaxin-2 is a hormone with robust beneficial effects on the heart and blood vessels and potential as a therapy for cardiovascular (CV) disease. Considering the interorgan communication between skeletal muscle and heart, and the relation between muscle quality/composition and CV events, we hypothesize that relaxin-2 may regulate skeletal muscle physiology and metabolism. We aim to evaluate the impact of relaxin-2 on the proteome of skeletal muscle from healthy Sprague-Dawley rats. Animals were treated with 0.4 mg/kg/day of serelaxin (recombinant form of human relaxin-2) or vehicle (PBS) for 2 weeks employing subcutaneous osmotic minipumps. Skeletal muscle protein identification and quantification were performed by LC-MS/MS using a Data-Independent Acquisition (DIA)-Sequential Window Acquisition of All Theoretical Fragment Ion Spectra (SWATH) method. SWATH/MS quantitative analysis identified that relaxin-2 significantly decreased 95 proteins and significantly increased 32 proteins in rat skeletal muscle when compared to control rats. From these, 34 proteins were associated with muscle function, myogenesis, muscle differentiation and/or regeneration, 20 are mitochondrial proteins (six from the complexes of the electron transport chain), and 10 proteins participate in glucose metabolism. Qualitative data-dependent workflow analysis identified 35 proteins exclusive to the skeletal muscle of the relaxin-2-treated group: eight proteins related to processes of skeletal muscle function (size, ion homeostasis or organization of caveolae structures and cytoskeleton) and myogenesis, and two proteins involved in muscle differentiation. Our work highlighted for the first time the role of relaxin-2 in crucial processes of muscle physiology and energetic metabolism, which could influence several processes involved in myopathy and CV.

Animals

Mass spectrometry-based ligand binding assays in biomedical research.

INTRODUCTION: Ligand binding assays combining immunoaffinity enrichment steps with mass spectrometry (MS) readout have gained attention as a highly specific and sensitive tool for protein quantification. These techniques typically combine enzymatic fragmentation of the sample or enriched protein with capture on the protein or peptide-level for quantification. Antibodies ensure specific target recognition, while MS offers quantitative accuracy with isotopically labeled internal standards. This dual approach supports a broad dynamic range, enabling protein measurements from picomolar to nanomolar levels. These methods have diverse applications, from quantifying signaling proteins in basic research to biomarker monitoring in clinical trials and analyzing the pharmacokinetics of therapeutic proteins. AREAS COVERED: This review delves into the diverse workflows of immunoaffinity-MS, shedding light on the innovative strategies employed, their practical applications, efficacy, and inherent limitations in the realm of protein quantification. EXPERT OPINION: Immunoaffinity-MS has transformed protein analysis, but widespread adoption is hindered by complex workflows, high instrument costs, and limited capture molecule availability. Efforts to enhance automation, standardize workflows, and advance technological innovation aim to overcome these barriers. Improvements in mass spectrometer sensitivity, advances in recombinant capture technologies, and support from public initiatives are poised to further improve the reliability and accessibility of this method.

Mass Spectrometry

Non-invasive embryo assessment: Cell-free DNA-based genetic testing and amino acid metabolomics in relation to morphology: A case-control study.

BACKGROUND: Cell-free DNA (cfDNA) in spent culture medium (SCM) offers a non-invasive option for preimplantation genetic testing, but its low concentration and fragmentation reduce clinical reliability. Combining genetic assessment with metabolomic profiling may provide complementary information about embryo competence. OBJECTIVE: This study assessed pre-analytical cfDNA processing workflows and examined whether SCM amino acid metabolic patterns could act as practical markers of embryo quality. MATERIALS AND METHODS: In this case-control study (2021-2023), 90 embryos were evaluated using fluorescence in situ hybridization or array comparative genomic hybridization. SCM samples underwent rapid boiling, silica-based purification, or whole-genome amplification (WGA). Sex determination was performed using quantitative polymerase chain reaction (qPCR). For cfDNA quality control and aneuploidy screening, the multiplex IRFiling kit and quantitative fluorescent polymerase chain reaction (QF-PCR) were used. Amino acid profiles across embryonic developmental stages and quality grades were quantified via liquid chromatography-tandem mass spectrometry. RESULTS: Rapid boiling resulted in complete failure of DNA amplification. Conversely, silica-based purification yielded 70.0% concordance for qPCR-based sexing and 56.7% for QF-PCR. WGA achieved the highest efficacy (73.3% qPCR and 56.7% QF-PCR concordance), although quality control checks flagged occasional misclassifications. LC-MS/MS profiling revealed significantly elevated alanine and arginine levels in tripronuclear embryos. Furthermore, high-quality blastocysts exhibited elevated glutamic acid levels alongside a pronounced overall depletion of extracellular amino acids compared to low-quality counterparts and controls. CONCLUSION: WGA improves cfDNA detectability and qPCR accuracy compared with boiling or purification, but remains inadequate as a standalone screening approach. SCM amino acid profiling provides informative, complementary metabolic signatures of developmental competence, supporting a multimodal strategy for non-invasive embryo assessment.

Amino acid metabolism

On-filter fractionation by empFASP improves identification of membrane peptides in proteomic experiments.

Membrane proteins remain among the most analytically challenging targets in bottom-up proteomics due to their limited solubility and low abundance of protease-accessible sites within transmembrane domains. In addition, hydrophobic peptides are frequently lost during detergent removal and the on-filter processing steps. Here, we present empFASP, a straightforward on-filter-fractionation-based modification of the enhanced filter-aided sample preparation (eFASP) workflow that enhances recovery of membrane-embedded peptides otherwise lost during digestion and cleanup. The method combines controlled on-filter inversion with sequential ethyl acetate extraction at defined pH values, enabling recovery of peptide material retained on the filter and redistributed into detergent micelles. Compared with SP3 and SP4 in HEK293T lysates, empFASP increased unique hydrophobic peptide identifications by up to 48% and increased the proportion of detected transmembrane peptides. Application to mouse mitochondrial membranes and phosphatidylethanolamine-deficient and PE-containing Escherichia coli membranes showed that the additional fractions of empFASP contribute complementary recovery of hydrophobic and membrane-associated peptides, with the strongest gains observed at the peptide level. Because empFASP requires no specialized reagents or instrumentation, it can be readily implemented in standard proteomics workflows to improve coverage of membrane-embedded regions. SIGNIFICANCE: The empFASP (enhanced membrane peptide) workflow offers a practical solution to one of the persistent limitations in membrane proteomics-the underrepresentation of hydrophobic and transmembrane peptides in standard digests. By integrating simple pH-controlled extractions into an on-filter format, empFASP recovers peptides otherwise lost through adsorption or detergent micelle retention, substantially improving coverage of the membrane proteome. This method expands the analytical reach of bottom-up proteomics without requiring specialized instrumentation, making it immediately applicable for studies of membrane topology, protein-lipid interactions, and the structural consequences of altered membrane composition.

Proteomics