Proteome Map Research Articles

Engineered allostery in light-regulated LOV-Turbo enables precise spatiotemporal control of proximity labeling in living cells.

The incorporation of light-responsive domains into engineered proteins has enabled control of protein localization, interactions and function with light. We integrated optogenetic control into proximity labeling, a cornerstone technique for high-resolution proteomic mapping of organelles and interactomes in living cells. Through structure-guided screening and directed evolution, we installed the light-sensitive LOV domain into the proximity labeling enzyme TurboID to rapidly and reversibly control its labeling activity with low-power blue light. 'LOV-Turbo' works in multiple contexts and dramatically reduces background in biotin-rich environments such as neurons. We used LOV-Turbo for pulse-chase labeling to discover proteins that traffic between endoplasmic reticulum, nuclear and mitochondrial compartments under cellular stress. We also showed that instead of external light, LOV-Turbo can be activated by bioluminescence resonance energy transfer from luciferase, enabling interaction-dependent proximity labeling. Overall, LOV-Turbo increases the spatial and temporal precision of proximity labeling, expanding the scope of experimental questions that can be addressed with proximity labeling.

Abstract A031: KRAS (G12C) mediated mRNA translation program

Abstract KRAS-dependent activation of mRNA translation signaling is a common feature in cancer however, the KRAS-specific translation landscape and functional proteome are not fully characterized in a genome-wide manner. We show that mutant KRAS drives specific mechanisms of translational control to support cancer growth. We have utilized the technology of ribosome footprinting combined with advanced sequencing methodology to define the translation landscape affected by a specific inhibitor of KRAS, sotorasib that targets G12C mutant KRAS activity. We show that acute treatment of sotorasib inhibits the translation of key oncogenic proteins including MYC and MYC targets. KRAS (G12C) inhibition profoundly affects the translation of ribosomal proteins and translation elongation factors. G12C mutant KRAS remarkably affects the translation of proteins involved in the ROS and DNA repair pathways in cancer. Moreover, these translational changes are mediated through specific RNA motifs and RNA binding proteins. In summary, our study defines the KRAS (G12C) specific regulation of translation and provides the mechanism of KRAS (G12C) mediated regulation of cancer proteome. Citation Format: Kamini Singh. KRAS (G12C) mediated mRNA translation program [abstract]. In: Proceedings of the AACR Special Conference: Targeting RAS; 2023 Mar 5-8; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Res 2023;21(5_Suppl):Abstract nr A031.

Proteomic signature associated with chronic kidney disease (CKD) progression identified by data-independent acquisition mass spectrometry

BackgroundHalting progression of chronic kidney disease (CKD) to established end stage kidney disease is a major goal of global health research. The mechanism of CKD progression involves pro-inflammatory, pro-fibrotic, and vascular pathways, but pathophysiological differentiation is currently lacking.MethodsPlasma samples of 414 non-dialysis CKD patients, 170 fast progressors (with ∂ eGFR-3 ml/min/1.73 m2/year or worse) and 244 stable patients (∂ eGFR of − 0.5 to + 1 ml/min/1.73 m2/year) with a broad range of kidney disease aetiologies, were obtained and interrogated for proteomic signals with SWATH-MS. We applied a machine learning approach to feature selection of proteins quantifiable in at least 20% of the samples, using the Boruta algorithm. Biological pathways enriched by these proteins were identified using ClueGo pathway analyses.ResultsThe resulting digitised proteomic maps inclusive of 626 proteins were investigated in tandem with available clinical data to identify biomarkers of progression. The machine learning model using Boruta Feature Selection identified 25 biomarkers as being important to progression type classification (Area Under the Curve = 0.81, Accuracy = 0.72). Our functional enrichment analysis revealed associations with the complement cascade pathway, which is relevant to CKD as the kidney is particularly vulnerable to complement overactivation. This provides further evidence to target complement inhibition as a potential approach to modulating the progression of diabetic nephropathy. Proteins involved in the ubiquitin–proteasome pathway, a crucial protein degradation system, were also found to be significantly enriched.ConclusionsThe in-depth proteomic characterisation of this large-scale CKD cohort is a step toward generating mechanism-based hypotheses that might lend themselves to future drug targeting. Candidate biomarkers will be validated in samples from selected patients in other large non-dialysis CKD cohorts using a targeted mass spectrometric analysis.

Abstract 5638: Total-sync ultra-content microscopic opto-biotinylation enables high-sensitivity hypothesis-free subcellular protein discovery

Abstract High-sensitivity hypothesis-free subcellular proteomics is challenging due to the limited sensitivity of mass spectrometry and the lack of amplification tools for proteins. Without such technology, it is not possible to discover proteins at specific locations of interest in cells or tissue samples. Here, we introduce a total-sync ultra-content microscopic system termed MicroscoopTM that integrates microscopy, optics, FPGA-based mechatronics, photochemistry, and deep learning or computer vision to enable high-content in situ photolabeling. MicroscoopTM photolabels proteins at user defined regions of interests (ROIs) under a microscope utilizing directed photochemistry in one field of view (FOV) at a time for tens of thousands of FOVs with similar morphological features. With this platform, we are able to photolabel proteins with biotin probes in cellular organelles, granules or cell-cell contact surfaces with a high precision at nanoscale resolution, and obtain sufficient amount of biotinylated proteins for mass spectrometry. We made a robust demonstration in the proteome mapping of human cellular nucleus from single-shot experiment to >1000 nuclear protein identification with > 90% specificity. Further data analysis revealed identification of a hundred of low protein copy number proteins and a high coverage of nuclear complexes. In proteome mapping of the nucleolus, we ranked proteins by order of abundance and revealed that 97 out of the top 100 proteins were annotated as nucleolar proteins. Unexpectedly, in mapping the stress granule (SG) proteome, a relatively low SG specificity (74%) were found in the top 50 abundant proteins, therefore we further characterize the proteins that have no prior SG annotation by immunostaining. Nine out of the thirteen unexplored proteins including PDLIM7, EIF3CL, YWHAE, RPSA, UGDH, DDX17, ANLN, PSMA6, and MCM2 were found to have SG patterns and co-localized with SG marker (G3BP1), raising our top 50 SG specificity to up to 92%. Together, our total-sync ultra-content microscopic platform enables hypothesis-free, de novo subcellular proteome mapping at user defined ROIs with high sensitivity and specificity, thereby broadly benefits the cell biology field in finding novel proteins or biomarkers. Citation Format: Jung-Chi Liao, Chih-Wei Chang, Yi-De Chen, Chantal Hoi Yin Cheung, Chia-Wen Chung, Hsiao-Jen Chang, Yong-Da Sie, You-Pi Liu, Yu-Chih Lin, Hsiang-Ju Kai, Weng Man Chong, Hsin-Yi Wu. Total-sync ultra-content microscopic opto-biotinylation enables high-sensitivity hypothesis-free subcellular protein discovery. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5638.

Abstract 185: Global mapping of pathway modules and phosphorylation networks in PDX and corresponding organoid (PDXO) models treated with targeted therapies

Abstract Introduction: Multi-omics-based strategies in precision medicine, including genomic, transcriptomic and proteomic data, have contributed to the molecular-level characterization of cancers and the identification of novel driver genes, as well as a better comprehension of resistance mechanisms. Patient-derived tumor models, including patient-derived xenograft (PDX) and in vitro 3D organoid counterparts (PDXO), are widely recognized as predictive preclinical cancer models closely recapitulating both tumor complexity and patient response and enabling the study of tumor identity for personalized medicine. Taking advantage of Crown Bioscience large PDX collection, with genomic and phenotypic annotation and pharmacological validation, a series of PDXO models have been established and characterized to be used as scalable and high throughput compatible drug screening platforms. Methods: Drug response in matched PDX and PDXO models were investigated on the functional and systems level through deep whole- and phospho-proteomic analysis. For this purpose, analysis and comparisons were made across dose and time series, the effect of several targeted therapies on protein expression and phosphorylation in both PDX and PDXO tumor models. More specifically, a KRAS inhibitor (AMG510), a BCR-ABL TKI (ponatinib) and an EGFR TKI (afatinib) were tested respectively in a lung NSCLC model carrying KRAS G12C mutation, a colorectal model with RET fusion and a lung NSCLC model with EGFR exon 19 deletion. Results: Based on previous data, a specific relationship between area under the curve (AUC) value of organoid drug dose response and in vivo tumor growth has been observed, irrespective of the drug treatment. To interrogate the pathways involved, both PDX and PDXO models were subjected to deep proteome and phospho-proteome profiling using state-of-the-art mass spectrometry-based workflows. An extensive dataset was generated where 16,797 proteins and 12,578 proteins were robustly quantified in PDX and PDXO models respectively. From the same samples, 35,403 phospho-sites were quantified across all PDX samples while 40,754 phospho-sites were quantified across all PDXO models. These data enabled the validation of known pathways (such as RAF/MEK/ERK, PI3K/AKT) and pinpoint new ones modulated through three small molecule inhibitors each targeting a defined genetic background. Conclusion: The predictivity of organoid cultures was demonstrated to model in vivo drug responses and also to serve as a powerful platform to investigate target identification, mechanism of action and resistance mechanism via functional proteome and phospho-proteome analysis. Citation Format: Martin Mehnert, Xiaoxi Xu, Tobias Treiber, Limei Shang, Leilei Chen, Jessie Wang, Marco Tognetti, Christopher Below, Roland Bruderer, Jakob Vowinckel, Binchen Mao, Wubin Qian, Sheng Guo, Ludovic Bourré, Yuehan Feng. Global mapping of pathway modules and phosphorylation networks in PDX and corresponding organoid (PDXO) models treated with targeted therapies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 185.

Recent advances of data‐independent acquisition mass spectrometry‐based proteomics

Recent advances of data‐independent acquisition mass spectrometry‐based proteomics

Deep thermal profiling for detection of functional proteoform groups.

The complexity of the functional proteome extends considerably beyond the coding genome, resulting in millions of proteoforms. Investigation of proteoforms and their functional roles is important to understand cellular physiology and its deregulation in diseases but challenging to perform systematically. Here we applied thermal proteome profiling with deep peptide coverage to detect functional proteoform groups in acute lymphoblastic leukemia cell lines with different cytogenetic aberrations. We detected 15,846 proteoforms, capturing differently spliced, cleaved and post-translationally modified proteins expressed from 9,290 genes. We identified differential co-aggregation of proteoform pairs and established links to disease biology. Moreover, we systematically made use of measured biophysical proteoform states to find specific biomarkers of drug sensitivity. Our approach, thus, provides a powerful and unique tool for systematic detection and functional annotation of proteoform groups.

PROTEOMAS: a workflow enabling harmonized proteomic meta-analysis and proteomic signature mapping

Toxicological evaluation of substances in regulation still often relies on animal experiments. Understanding the substances’ mode-of-action is crucial to develop alternative test strategies. Omics methods are promising tools to achieve this goal. Until now, most attention was focused on transcriptomics, while proteomics is not yet routinely applied in toxicology despite the large number of datasets available in public repositories. Exploiting the full potential of these datasets is hampered by differences in measurement procedures and follow-up data processing. Here we present the tool PROTEOMAS, which allows meta-analysis of proteomic data from public origin. The workflow was designed for analyzing proteomic studies in a harmonized way and to ensure transparency in the analysis of proteomic data for regulatory purposes. It agrees with the Omics Reporting Framework guidelines of the OECD with the intention to integrate proteomics to other omic methods in regulatory toxicology. The overarching aim is to contribute to the development of AOPs and to understand the mode of action of substances. To demonstrate the robustness and reliability of our workflow we compared our results to those of the original studies. As a case study, we performed a meta-analysis of 25 proteomic datasets to investigate the toxicological effects of nanomaterials at the lung level. PROTEOMAS is an important contribution to the development of alternative test strategies enabling robust meta-analysis of proteomic data. This workflow commits to the FAIR principles (Findable, Accessible, Interoperable and Reusable) of computational protocols.

FungiProteomeDB: a database for the molecular weight and isoelectric points of the fungal proteomes.

Proteins' molecular weight (MW) and isoelectric point (pI) are crucial for their subcellular localization and subsequent function. These are also useful in 2D gel electrophoresis, liquid chromatography-mass spectrometry and X-ray protein crystallography. Moreover, visualizations like a virtual 2D proteome map of pI vs. MW are worthwhile to discuss the proteome diversity among different species. Although the genome sequence data of the fungi kingdom improved enormously, the proteomic details have been poorly elaborated. Therefore, we have calculated the MW and pI of the fungi proteins and reported them in, FungiProteomeDB, an online database (DB) https://vision4research.com/fungidb/. We analyzed the proteome of 685 fungal species that contain 7 127 141 protein sequences. The DB provides an easy-to-use and efficient interface for various search options, summary statistics and virtual 2D proteome map visualizations. The MW and pI of a protein can be obtained by searching the name of a protein, a keyword or a list of accession numbers. It also allows querying protein sequences. The DB will be helpful in hypothesis formulation and in various biotechnological applications. Database URL https://vision4research.com/fungidb/.

Proximity proteome mapping reveals PD-L1-dependent pathways disrupted by anti-PD-L1 antibody specifically in EGFR-mutant lung cancer cells

BackgroundPD-L1, a transmembrane ligand for immune checkpoint receptor PD1, has been successfully targeted to activate an anti-tumor immune response in a variety of solid tumors, including non-small cell lung cancer (NSCLC). Despite the success of targeting PD-L1, only about 20% of patients achieve a durable response. The reasons for the heterogeneity in response are not understood, although some molecular subtypes (e.g., mutant EGF receptor tumors) are generally poor responders. Although PD-L1 is best characterized as a transmembrane PD1 ligand, the emerging view is that PD-L1 has functions independent of activating PD1 signaling. It is not known whether these cell-intrinsic functions of PD-L1 are shared among non-transformed and transformed cells, if they vary among cancer molecular subtypes, or if they are impacted by anti-PD-L1 therapy.MethodsHere we use quantitative microscopy techniques and APEX2 proximity mapping to describe the behavior of PD-L1 and to identify PD-L1's proximal proteome in human lung epithelial cells.ResultsOur data reveal growth factor control of PD-L1 recycling as a mechanism for acute and reversible regulation of PD-L1 density on the plasma membrane. In addition, we describe novel PD-L1 biology restricted to mutant EGFR cells. Anti-PD-L1 antibody treatment of mutant EGFR cells perturbs cell intrinsic PD-L1 functions, leading to reduced cell migration, increased half-life of EGFR and increased extracellular vesicle biogenesis, whereas anti-PD-L1 antibody does not induce these changes in wild type EGFR cells.ConclusionsGrowth factor acute regulation of PD-L1 trafficking, by contributing to the control of plasma membrane density, might contribute to the regulation of PD-L1's immune checkpoint activity, whereas the specific effects of anti-PD-L1 on mutant EGFR cells might contribute to the poor anti-PD-L1 response of mutant EGFR tumors.5zzQ_mo5e1oawe5DznU6q-Video

Strategies for Competitive Activity‐Based Protein Profiling in Small Molecule Inhibitor Discovery and Characterization

AbstractSince its introduction by Cravatt and colleagues in 1999, activity‐based protein profiling (ABPP) has become widely utilized throughout academia, government, and industry laboratories to study enzymes spanning numerous gene families in a multitude of biological systems. As a variation of ABPP, competitive ABPP provides a powerful approach to characterize the binding behavior of small molecule probes and clinical drugs throughout the functional proteome. The power and flexibility of competitive ABPP are exemplified by a wide range of creative adaptions which increase assay throughput, enable diverse detection schemes, and support the implementation of this approach within a hybrid target‐based screening platform. We review major developments in competitive ABPP through a compare‐contrast format to provide a useful introduction to this enabling technology for scientists in chemical biology and drug discovery.

ANALYSIS OF THE COMPOSITION OF OSMOTICALLY ACTIVE PROTEIN FRACTION IN BLOOD SERUM FROM ATLANTIC COD <i>GADUS MORHUA</i>

A search and identification of osmotically active proteins (OAP) in the composition of blood serum anodic fraction from Atlantic cod Gadus morhua were undertaken using polyacrylamide gel electrophoresis and MALDI mass-spectrometry. 17 OAP have been identified. According to the annotations of Gene Ontology for candidates, 13 OAP were classified as extracellular and 4 OAP- as intracellular proteins. The relative content of OAP in cod serum was ~50% of the total protein. Extracellular proteins apolipoproteins (in the composition of high-density lipoproteins) and hemopexin were dominated in OAP pool. Moreover, the relative content of ApoA-I was ~25% of the total serum protein. Of the intracellular proteins on the serum proteomic map, low molecular weight fragments of the myosin heavy chain were dominated. The results obtained are consistent with the provisions of the “albumin-free” hypothesis of capillary exchange, which considers multiple extracellular and intracellular proteins from different functional classes as osmotically active plasma proteins of “albumin-free” teleost fish.

Genome-wide genotype-serum proteome mapping provides insights into the cross-ancestry differences in cardiometabolic disease susceptibility

Identification of protein quantitative trait loci (pQTL) helps understand the underlying mechanisms of diseases and discover promising targets for pharmacological intervention. For most important class of drug targets, genetic evidence needs to be generalizable to diverse populations. Given that the majority of the previous studies were conducted in European ancestry populations, little is known about the protein-associated genetic variants in East Asians. Based on data-independent acquisition mass spectrometry technique, we conduct genome-wide association analyses for 304 unique proteins in 2,958 Han Chinese participants. We identify 195 genetic variant-protein associations. Colocalization and Mendelian randomization analyses highlight 60 gene-protein-phenotype associations, 45 of which (75%) have not been prioritized in Europeans previously. Further cross-ancestry analyses uncover key proteins that contributed to the differences in the obesity-induced diabetes and coronary artery disease susceptibility. These findings provide novel druggable proteins as well as a unique resource for the trans-ancestry evaluation of protein-targeted drug discovery.

Improving the genome and proteome annotations of the marine model diatom Thalassiosira pseudonana using a proteogenomics strategy

Diatoms are unicellular eukaryotic phytoplankton that account for approximately 20% of global carbon fixation and 40% of marine primary productivity; thus, they are essential for global carbon biogeochemical cycling and climate. The availability of ten diatom genome sequences has facilitated evolutionary, biological and ecological research over the past decade; however, a complimentary map of the diatom proteome with direct measurements of proteins and peptides is still lacking. Here, we present a proteome map of the model marine diatom Thalassiosira pseudonana using high-resolution mass spectrometry combined with a proteogenomic strategy. In-depth proteomic profiling of three different growth phases and three nutrient-deficient samples identified 9526 proteins, accounting for ~ 81% of the predicted protein-coding genes. Proteogenomic analysis identified 1235 novel genes, 975 revised genes, 104 splice variants and 234 single amino acid variants. Furthermore, our quantitative proteomic analysis experimentally demonstrated that a considerable number of novel genes were differentially translated under different nutrient conditions. These findings substantially improve the genome annotation of T. pseudonana and provide insights into new biological functions of diatoms. This relatively comprehensive diatom proteome catalog will complement available diatom genome and transcriptome data to advance biological and ecological research of marine diatoms.

The transcript interactome of skeletal muscle RNA binding protein motif 3 (RBM3).

Post-transcriptional regulation of gene expression represents a critical regulatory step in the production of a functional proteome. Elevated expression of post-transcriptional regulator RNA binding motif protein 3 (RBM3), an RNA binding protein in the cold-shock family, is positively correlated with skeletal muscle growth in adult mice. However, mechanisms through which RBM3 exerts its effects are largely unknown. The purpose of this study was to perform RNA immunoprecipitation followed by RNA sequencing (RIP-seq) and apply a network science approach to understand biological processes (BPs) most associated with RBM3-bound mRNAs. In addition, through nucleotide-sequence-scanning of enriched transcripts, we predicted the motif for skeletal muscle RBM3 binding. Gene set enrichment analysis followed by enrichment mapping of RBM3-bound transcripts (fold change >3; p.adj <0.01) revealed significant enrichment of BPs associated with "Contractile apparatus," "Translation initiation," and "Proteosome complex." Clusters were driven largely by enrichment of Myh1 (FC: 4.43), Eif4b (FC: 5.03), and Trim63 (FC: 5.84), respectively. Motif scanning of enriched sequences revealed a discrete 14 nucleotide-wide motif found most prominently at the junction between the protein coding region's termination sequence and the start of the 3' untranslated region (UTR; E-Value: 1.1 e-015 ). Proof of concept investigation of motif location along enriched transcripts Myh1 and Myl4 revealed 3' UTR binding, suggesting RBM3 involvement in transcript half-life regulation. Together, these results demonstrate the potential influence of RBM3 in reshaping the skeletal muscle proteome through post-transcriptional regulation of mRNAs crucial to muscle adaptations.

Naturally forming benzoic acid orientates perilipin to facilitate glyceride-type polyunsaturated fatty acid degradation via fermentation behavior

Naturally forming benzoic acid in fermented dairy products accumulates in organisms and biomagnifies through collateral transport. The association between benzoic acid agglomeration and susceptible lipid nutrients remains obscure. Horizontal analysis of lipidomic alteration in response to benzoic acid was conducted and the spatially proteomic map was constructed using label-free quantitative proteomics. From synergistic integration of multi-omics in benzoic acid accumulated fermented goat milk model, the biological processes of significant proteins mostly focused on glyceride-type polyunsaturated fatty acids degradation (143.818 ± 0.51 mg/kg to 104.613 ± 0.29 mg/kg). As a physiological barrier shield, perilipin, which is coated on the surface of lipid droplets, protects triacylglycerols from cytosolic lipases, thus preventing triglyceride hydrolysis. The expression of perilipin decreased by 90% compared with the control group, leading to the decrease of triglycerides. Benzoic acid suppressed phosphatidylethanolamines and phosphatidylcholines synthesis by attenuating choline phosphotransferase and ethanolamine phosphotransferase. Less diglyceride generated by the dephosphorylation of phosphatidic acid entered choline phosphotransferase and ethanolamine phosphotransferase-mediated glycerophospholipid metabolisms. Fermentation of goat milk at a low temperature and less incubation time leads to the production of less benzoic acid and mitigation of lipid nutrient loss. The present study delineated the molecular landscape of fermented goat milk containing endogenous benzoic acid and further dissected the trajectory guiding lipid alteration to advance control of benzoic acid residue.

Estimating Total Quantitative Protein Content in Escherichia coli, Saccharomyces cerevisiae, and HeLa Cells.

The continuous improvement of proteomic techniques, most notably mass spectrometry, has generated quantified proteomes of many organisms with unprecedented depth and accuracy. However, there is still a significant discrepancy in the reported numbers of total protein molecules per specific cell type. In this article, we explore the results of proteomic studies of Escherichia coli, Saccharomyces cerevisiae, and HeLa cells in terms of total protein copy numbers per cell. We observe up to a ten-fold difference between reported values. Investigating possible reasons for this discrepancy, we conclude that neither an unmeasured fraction of the proteome nor biases in the quantification of individual proteins can explain the observed discrepancy. We normalize protein copy numbers in each study using a total protein amount per cell as reported in the literature and create integrated proteome maps of the selected model organisms. Our results indicate that cells contain from one to three million protein molecules per µm3 and that protein copy density decreases with increasing organism complexity.

A Proteomics Data Mining Strategy for the Identification of Quinoa Grain Proteins with Potential Immunonutritional Bioactivities.

Quinoa proteins are attracting global interest for their wide amino acid profile and as a promising source for the development of biomedical treatments, including those against immune-mediated diseases. However, information about the bioactivity of quinoa proteins is scarce. In this study, a quinoa grain proteome map obtained by label-free mass spectrometry-based shotgun proteomics was investigated for the identification of quinoa grain proteins with potential immunonutritional bioactivities, including those related to cancer. After carefully examining the sequence similarities of the 1211 identified quinoa grain proteins against already described bioactive proteins from other plant organisms, 71, 48, and 3 of them were classified as antimicrobial peptides (AMPs), oxidative stress induced peptides (OSIPs), and serine-type protease inhibitors (STPIs), respectively, suggesting their potential as immunomodulatory, anti-inflammatory, and anticancer agents. In addition, data interpretation using Venn diagrams, heat maps, and scatterplots revealed proteome similarities and differences with respect to the AMPs, OSIPs, and STPIs, and the most relevant bioactive proteins in the predominant commercial quinoa grains (i.e., black, red, white (from Peru), and royal (white from Bolivia)). The presented proteomics data mining strategy allows easy screening for potentially relevant quinoa grain proteins and commercial classes for immunonutrition, as a basis for future bioactivity testing.

Proteome Mapping of Cervical Mucus and Its Potential as a Source of Biomarkers in Female Tract Disorders.

Cervical mucus (CM) is a viscous fluid that is produced by the cervical glands and functions as a uterine cervix plug. Its viscosity decreases during ovulation, providing a window for non-invasive sampling. This study focuses on proteomic characterization of CM to evaluate its potential as a non-invasively acquired source of biomarkers and in understanding of molecular (patho)physiology of the female genital tract. The first objective of this work was to optimize experimental workflow for CM processing and the second was to assess differences in the proteomic composition of CM during natural ovulatory cycles obtained from intrauterine insemination (IUI) cycles and in vitro fertilization (IVF) cycles with controlled ovarian hyperstimulation. Proteomic analysis of CM samples revealed 4370 proteins involved in processes including neutrophil degranulation, cellular stress responses, and hemostasis. Differential expression analysis revealed 199 proteins enriched in IUI samples and 422 enriched in IVF. The proteins enriched in IUI were involved in phosphatidic acid synthesis, responses to external stimulus, and neutrophil degranulation, while those enriched in IVF samples were linked to neutrophil degranulation, formation of a cornified envelope and hemostasis. Subsequent analyses clarified the protein composition of the CM and how it is altered by hormonal stimulation of the uterus.

Cell Surface Biotinylation Using Furan Cross-Linking Chemistry.

A detailed study of the cellular surfaceome poses major challenges for mass spectrometry analysis. Surface proteins are low abundant compared to intracellular proteins, and their inefficient extraction in aqueous medium leads to their aggregation and precipitation. To tackle such problems, surface biotinylation is frequently used to tag surface proteins with biotin, allowing for their enrichment, leading to a more sensitive mapping of surface proteomes. We here detail a new surface biotinylation protocol based on furan-biotin affinity purification to enrich plasma membrane proteins for proteomics. This protocol involves biotinylation of cell surface membrane proteins on viable cells, followed by affinity enrichment using streptavidin beads, trypsin digestion, peptide cleanup, and LC-MS/MS analysis.