Skeletal Muscle Proteome Modifications following Antibiotic-Induced Microbial Disturbances in Cancer Cachexia.

Cancer cachexia is an involuntary loss of body weight, mostly of skeletal muscle. Previous research favors the existence of a microbiota-muscle crosstalk, so the aim of the study was to evaluate the impact of microbiota alterations induced by antibiotics on skeletal muscle proteins expression. Skeletal muscle proteome changes were investigated in control (CT) or C26 cachectic mice (C26) with or without antibiotic treatment (CT-ATB or C26-ATB, n = 8 per group). Muscle protein extracts were divided into a sarcoplasmic and myofibrillar fraction and then underwent label-free liquid chromatography separation, mass spectrometry analysis, Mascot protein identification, and METASCAPE platform data analysis. In C26 mice, the atrogen mafbx expression was 353% higher than CT mice and 42.3% higher than C26-ATB mice. No effect on the muscle protein synthesis was observed. Proteomic analyses revealed a strong effect of antibiotics on skeletal muscle proteome outside of cachexia, with adaptative processes involved in protein folding, growth, energy metabolism, and muscle contraction. In C26-ATB mice, proteome adaptations observed in CT-ATB mice were blunted. Differentially expressed proteins were involved in other processes like glucose metabolism, oxidative stress response, and proteolysis. This study confirms the existence of a microbiota-muscle axis, with a muscle response after antibiotics that varies depending on whether cachexia is present.

Proteomic Analysis of Dictyostelium discoideum by Mass Spectrometry.

The large-scale proteomic analysis of Dictyostelium discoideum has contributed to our understanding of intracellular as well as secreted proteins in this versatile model eukaryote. Mass spectrometry-based proteomic analysis is a robust, sensitive, and rapid analytical method for identification and characterization of proteins extracted from tissues, cells, cell fractions, or pull-down assays. The availability of core facilities which make proteomics inexpensive and easy to do has facilitated a wide range of research projects. In this chapter, we present a simple standard methodology to extract proteins and prepare samples from D. discoideum for mass spectrometry and methods to analyze the identified proteins.

Quantitative urinary proteome analysis reveals potential biomarkers for disease activity of Behcet's disease uveitis.

PURPOSE: Behçet's disease-associated uveitis (BDU) is a severe, recurrent inflammatory condition affecting the eye and is part of a systemic vasculitis with unknown etiology, making biomarker discovery essential for disease management. In this study, we intend to investigate potential urinary biomarkers to monitor the disease activity of BDU. METHODS: Firstly, label-free data-dependent acquisition (DDA) and tandem mass tag (TMT)-labeled quantitative proteomics methods were used to profile the proteomes of urine from active and quiescent BDU patients, respectively. For further exploration, the remaining fifty urine samples were analyzed by a data-independent acquisition (DIA) quantitative proteomics method. RESULTS: Twenty-nine and 21 differential proteins were identified in the same urine from BDU patients by label-free DDA and TMT-labeled analyses, respectively. Seventy-nine differentially expressed proteins (DEPs) were significantly changed in other active BDU urine samples compared to those in quiescent BDU urine samples by IDA analysis. Gene Ontology (GO) and protein-protein interaction (PPI) analyses revealed that the DEPs were associated with multiple functions, including the immune and neutrophil activation responses. Finally, seven proteins were identified as candidate biomarkers for BDU monitoring and recurrence prediction, namely, CD38, KCRB, DPP4, FUCA2, MTPN, S100A8 and S100A9. CONCLUSIONS: Our results showed that urine can be a good source of biomarkers for BDU. These dysregulated proteins provide potential urinary biomarkers for BDU activity monitoring and provide valuable clues for the analysis of the pathogenic mechanisms of BDU.

Integrated serum proteomic and N-glycoproteomic characterization of dengue patients.

Dengue fever is a mosquito-borne viral disease caused by the dengue virus (DENV). It poses a public health threat globally and, while most people with dengue have mild symptoms or are asymptomatic, approximately 5% of affected individuals develop severe disease and need hospital care. However, knowledge of the molecular mechanisms underlying dengue infection and the interaction between the virus and its host remains limited. In the present study, we performed a quantitative proteomic and N-glycoproteomic analysis of serum from 19 patients with dengue and 11 healthy people. The results revealed distinct proteomic and N-glycoproteomic landscapes between the two groups. Notably, we report for the first time the changes in the serum N glycosylation pattern following dengue infection and provide abundant information on glycoproteins, glycosylation sites, and intact N-glycopeptides using recently developed site-specific glycoproteomic approaches. Furthermore, a series of key functional pathways in proteomic and N-glycoproteomic were identified. Collectively, our findings significantly improve understanding of host and DENV interactions and the general pathogenesis and pathology of DENV, laying a foundation for functional studies of glycosylation and glycan structures in dengue infection.

Changes in cerebrospinal fluid proteome of patients with tick-borne encephalitis.

Tick-borne encephalitis (TBE) is one of the main diseases transmitted by ticks, the incidence of which is increasing. Moreover, its diagnosis and therapy are often long and difficult according to nonspecific symptoms and complex etiology. This study aimed to observe changes in the proteome of cerebrospinal fluid from TBE patients. Cerebrospinal fluid (CSF) of TBE patients (n = 20) and healthy individuals (n = 10) was analyzed using a proteomic approach (QExactiveHF-Orbitrap mass spectrometer) and zymography. Obtained results show that in CSF of TBE patients, the top-upregulated proteins are involved in pro-inflammatory reaction (interleukins), as well as antioxidant/protective response (peroxiredoxins, heat shock proteins). Moreover, changes in the proteome of CSF are not only the result of this disease development, but they can also be an indicator of its course. This mainly applies to proteins involved in proteolysis including serpins and metalloproteinases, whose activity is proportional to the length of patients' convalescence. The obtained proteomic data strongly direct attention to the changes caused by the development of TBE to antioxidant, pro-inflammatory, and proteolytic proteins, knowledge about which can significantly contribute to faster and more accurate diagnosis of various clinical forms of TBE.

[A highly sensitive approach for the analysis of tyrosine phosphoproteome in primary T cells].

Tyrosine phosphorylation, a common post-translational modification process for proteins, is involved in a variety of biological processes. However, the abundance of tyrosine-phosphorylated proteins is very low, making their identification by mass spectrometry (MS) is difficult; thus, milligrams of the starting material are often required for their enrichment. For example, tyrosine phosphorylation plays an important role in T cell signal transduction. However, the number of primary T cells derived from biological tissue samples is very small, and these cells are difficult to culture and expand; thus, the study of T cell signal transduction is usually carried out on immortalized cell lines, which can be greatly expanded. However, the data from immortalized cell lines cannot fully mimic the signal transduction processes observed in the real physiological state, and they usually lead to conclusions that are quite different from those of primary T cells. Therefore, a highly sensitive proteomic method was developed for studying tyrosine phosphorylation modification signals in primary T cells. To address the issue of the limited T cells numbers, a comprehensive protocol was first optimized for the isolation, activation, and expansion of primary T cells from mouse spleen. CD3+ primary T cells were successfully sorted; more than 91% of the T cells collected were well activated on day 2, and the number of T cells expanded to over 7-fold on day 4. Next, to address the low abundance of tyrosine-phosphorylated proteins, we used SH2-superbinder affinity enrichment and immobilized Ti4+affinity chromatography (Ti4+-IMAC) to enrich the tyrosine-phosphorylated polypeptides of primary T cells that were co-stimulated with anti-CD3 and anti-CD28. These polypeptides were resolved using nanoscale liquid chromatography-tandem mass spectrometry (nanoLC-MS/MS). Finally, 282 tyrosine phosphorylation sites were successfully identified in 1 mg of protein, including many tyrosine phosphorylation sites on the immunoreceptor tyrosine-based activation motif (ITAM) in the intracellular region of the T cell receptor membrane protein CD3, as well as the phosphotyrosine sites of ZAP70, LAT, VAV1, and other proteins related to signal transduction under costimulatory conditions. In summary, to solve the technical problems of the limited number of primary cells, low abundance of tyrosine-phosphorylated proteins, and difficulty of detection by MS, we developed a comprehensive proteomic method for the in-depth analysis of tyrosine phosphorylation modification signals in primary T cells. This protocol may be applied to map signal transduction networks that are closely related to physiological states.

Proteomic Analysis of In Vitro Plant Tissues (Coffea canephora): A Case of Study.

Since the term proteomics was coined by Marc Wilkins in 1994, there has been an explosion in the number of articles reporting the use of the proteomics technique. As the layers of biological organization and their regulation increase, the complexity of living beings increases. Thus, we go from the genome to tissues, cells, cellular compartments, and phenotypes and the complexity of the tools used to study this complexity also increases. Unlike the genome study, in the case of the proteome, we have a more complex panorama. We have a spatial and temporal proteome. Proteomics helps to answer complex biological questions since proteins' function depends on their molecular structure, subcellular localization, and posttranslational modifications. In this protocol, we describe a methodology to extract proteins using different methods, separating proteins by electrophoresis in double-dimensional gels and analyzing the gels using specialized software that allows obtaining information on the number and abundance of the proteins from the gels.

Proteomics Analyses of Small Extracellular Vesicles of Aqueous Humor: Identification and Validation of GAS6 and SPP1 as Glaucoma Markers.

Cataracts and glaucoma account for a high percentage of vision loss and blindness worldwide. Small extracellular vesicles (sEVs) are released into different body fluids, including the eye's aqueous humor. Information about their proteome content and characterization in ocular pathologies is not yet well established. In this study, aqueous humor sEVs from healthy individuals, cataracts, and glaucoma patients were studied, and their specific protein profiles were characterized. Moreover, the potential of identified proteins as diagnostic glaucoma biomarkers was evaluated. The protein content of sEVs from patients' aqueous humor with cataracts and glaucoma compared to healthy individuals was analyzed by quantitative proteomics. Validation was performed by western blot (WB) and ELISA. A total of 828 peptides and 192 proteins were identified and quantified. After data analysis with the R program, 8 significantly dysregulated proteins from aqueous humor sEVs in cataracts and 16 in glaucoma showed an expression ratio ≥ 1.5. By WB and ELISA using directly aqueous humor samples, the dysregulation of 9 proteins was mostly confirmed. Importantly, GAS6 and SPP1 showed high diagnostic ability of glaucoma, which in combination allowed for discriminating glaucoma patients from control individuals with an area under the curve of 76.1% and a sensitivity of 65.6% and a specificity of 87.7%.

Repurposed 3D Printer Allows Economical and Programmable Fraction Collection for Proteomics of Nanogram Scale Samples.

In this work, we describe the construction and application of a repurposed 3D-printer as a fraction collector. We utilize a nano-LC to ensure minimal volumes and surfaces although any LC can be coupled. The setup operates as a high-pH fractionation system capable of effectively working with nanogram scales of lysate digests. The 2D RP-RP system demonstrated superior proteome coverage over single-shot data-dependent acquisition (DDA) analysis using only 5 ng of human cell lysate digest with performance increasing with increasing amounts of material. We found that the fractionation system allowed over 60% signal recovery at the peptide level and, more importantly, we observed improved protein level intensity coverage, which indicates the complexity reduction afforded by the system outweighs the sample losses endured. The application of data-independent acquisition (DIA) and wide window acquisition (WWA) to fractionated samples allowed nearly 8000 proteins to be identified from 50 ng of the material. The utility of the 2D system was further investigated for phosphoproteomics (>21 000 phosphosites from 50 µg starting material) and pull-down type experiments and showed substantial improvements over single-shot experiments. We show that the 2D RP-RP system is a highly versatile and powerful tool for many proteomics workflows.

Identification and characterization of plasma proteins associated with intra-amniotic inflammation and/or infection in women with preterm labor.

This study aimed to identify plasma proteins that could serve as potential biomarkers for microbial invasion of the amniotic cavity (MIAC) or intra-amniotic inflammation (IAI) in women with preterm labor (PTL). A retrospective cohort comprised singleton pregnant women with PTL (24-34 weeks) who underwent amniocentesis. Pooled plasma samples were analyzed by label-free liquid chromatography-tandem mass spectrometry for proteome profiling in a nested case-control study (concomitant MIAC/IAI cases vs. non-MIAC/IAI controls [n = 10 per group]). Eight target proteins associated with MIAC/IAI were further verified by immunoassays in a large cohort (n = 230). Shotgun proteomic analysis revealed 133 differentially expressed proteins (fold change > 1.5, P < 0.05) in the plasma of MIAC/IAI cases. Further quantification confirmed that the levels of AFP were higher and those of kallistatin and TGFBI were lower in the plasma of women with MIAC and that the levels of kallistatin and TGFBI were lower in the plasma of women with IAI than in those without these conditions. The area under the curves of plasma AFP, kallistatin, and TGFBI ranged within 0.67-0.81 with respect to each endpoint. In summary, plasma AFP, kallistatin, and TGFBI may represent valuable non-invasive biomarkers for predicting MIAC or IAI in women with PTL.

Metaproteomic Analysis of Fecal Samples from Human Subjects and Rodent Models.

Fecal metaproteomics is a useful approach to measure changes in microbial and host protein abundance and to infer which members of the gut microbiota are involved in specific functions and pathways. This chapter describes a protocol enabling analysis and characterization of fecal metaproteomes, successfully applied to human, mouse, and rat stool samples. The protocol combines mechanical and thermal treatments for protein extraction, a centrifugal filter-based procedure for cleanup and digestion, long-gradient liquid chromatography for peptide separation, and high-resolution mass spectrometry for peptide detection.

Proteomics for Microalgae Extracts by High-Resolution Mass Spectrometry.

Two protocols of protein extraction from Arthrospira platensis (spirulina) microalgae to study their proteome by mass spectrometry (MS) are here presented. The first is based on an aqueous buffer solution of Tris-HCl and the second on cold acetone. The identification of proteins was carried out by a bottom-up approach, which involves enzymatic digestion of extracted proteins followed by either matrix-assisted laser desorption ionization with time-of-flight (MALDI-TOF) MS or liquid chromatography (LC) coupled with electrospray ionization (ESI) and Fourier-transform tandem MS. While MALDI-TOF MS allowed for a fast peptide mass fingerprinting (PMF) check yet identifying less than 20 proteins in the extracted samples, the data-dependent acquisitions (DDA) mode of reversed-phase (RP) LC-ESI tandem FTMS/MS separations allowed us to recognize more than one hundred proteins by searching into dedicated spectral libraries. The application of MALDI-TOF MS analysis was found, however, of great support for preliminary investigations of cyanobacteria samples before proceeding with the RPLC-ESI-MS/MS DDA investigation, which definitively allows for a qualitative proteome analysis also of minor spirulina proteins in processed foodstuffs. Although the protein content in spirulina can be influenced by cultivation and environmental conditions, e.g., light intensity, climate, and water/air quality, here the qualitative chemical profiles of the examined samples were characterized by similar composition in high-quality proteins as phycocyanins and phycoerythrins.

Metaproteomics for Coinfections in the Upper Respiratory Tract: The Case of COVID-19.

The upper respiratory tract (URT) is home to a diverse range of microbial species. Respiratory infections disturb the microbial flora in the URT, putting people at risk of secondary infections. The potential dangers and clinical effects of bacterial and fungal coinfections with SARS-CoV-2 support the need to investigate the microbiome of the URT using clinical samples. Mass spectrometry (MS)-based metaproteomics analysis of microbial proteins is a novel approach to comprehensively assess the clinical specimens with complex microbial makeup. The coronavirus that causes severe acute respiratory syndrome (SARS-CoV-2) is responsible for the COVID-19 pandemic resulting in a plethora of microbial coinfections impeding therapy, prognosis, and overall disease management. In this chapter, the corresponding workflows for MS-based shotgun proteomics and metaproteomic analysis are illustrated.

Extracellular Microenvironment Alterations in Ductal Carcinoma In Situ and Invasive Breast Cancer Pathologies by Multiplexed Spatial Proteomics.

Ductal carcinoma in situ (DCIS) is a heterogeneous breast disease that remains challenging to treat due to its unpredictable progression to invasive breast cancer (IBC). Contemporary literature has become increasingly focused on extracellular matrix (ECM) alterations with breast cancer progression. However, the spatial regulation of the ECM proteome in DCIS has yet to be investigated in relation to IBC. We hypothesized that DCIS and IBC present distinct ECM proteomes that could discriminate between these pathologies. Tissue sections of pure DCIS, mixed DCIS-IBC, or pure IBC (n = 22) with detailed pathological annotations were investigated by multiplexed spatial proteomics. Across tissues, 1,005 ECM peptides were detected in pathologically annotated regions and their surrounding extracellular microenvironments. A comparison of DCIS to IBC pathologies demonstrated 43 significantly altered ECM peptides. Notably, eight fibrillar collagen peptides could distinguish with high specificity and sensitivity between DCIS and IBC. Lesion-targeted proteomic imaging revealed heterogeneity of the ECM proteome surrounding individual DCIS lesions. Multiplexed spatial proteomics reported an invasive cancer field effect, in which DCIS lesions in closer proximity to IBC shared a more similar ECM profile to IBC than distal counterparts. Defining the ECM proteomic microenvironment provides novel molecular insights relating to DCIS and IBC.

Exploring novel protein-based biomarkers for advancing breast cancer diagnosis: A review.

This review provides a contemporary examination of the evolving landscape of breast cancer (BC) diagnosis, focusing on the pivotal role of novel protein-based biomarkers. The overview begins by elucidating the multifaceted nature of BC, exploring its prevalence, subtypes, and clinical complexities. A critical emphasis is placed on the transformative impact of proteomics, dissecting the proteome to unravel the molecular intricacies of BC. Navigating through various sources of samples crucial for biomarker investigations, the review underscores the significance of robust sample processing methods and their validation in ensuring reliable outcomes. The central theme of the review revolves around the identification and evaluation of novel protein-based biomarkers. Cutting-edge discoveries are summarised, shedding light on emerging biomarkers poised for clinical application. Nevertheless, the review candidly addresses the challenges inherent in biomarker discovery, including issues of standardisation, reproducibility, and the complex heterogeneity of BC. The future direction section envisions innovative strategies and technologies to overcome existing challenges. In conclusion, the review summarises the current state of BC biomarker research, offering insights into the intricacies of proteomic investigations. As precision medicine gains momentum, the integration of novel protein-based biomarkers emerges as a promising avenue for enhancing the accuracy and efficacy of BC diagnosis. This review serves as a compass for researchers and clinicians navigating the evolving landscape of BC biomarker discovery, guiding them toward transformative advancements in diagnostic precision and personalised patient care.

Plasma proteomics analysis reveals potential biomarkers for intracranial aneurysm formation and rupture.

The aim of this study was to investigate the plasma proteome in individuals with intracranial aneurysms (IAs) and identify biomarkers associated with the formation and rupture of IAs. Proteomic profiles (N = 1069 proteins) were assayed in plasma (N = 120) collected from patients with ruptured and unruptured intracranial aneurysms (RIA and UIA), traumatic subarachnoid hemorrhage (tSAH), and healthy controls (HC) using tandem mass tag (TMT) labeling quantitative proteomics analysis. Gene ontology (GO) and pathway analysis revealed that these relevant proteins were involved in immune response and extracellular matrix organization pathways. Seven candidate biomarkers were verified by ELISA in a completely separate cohort for validation (N = 90). Among them, FN1, PON1, and SERPINA1 can be utilized as diagnosis biomarkers of IA, with a combined area under the ROC curve of 0.891. The sensitivity was 93.33%, specificity was 75.86%, and accuracy was 87.64%. PFN1, ApoA-1, and SERPINA1 can serve as independent risk factors for predicting aneurysm rupture. The combined prediction of aneurysm rupture yielded an area under the ROC curve of 0.954 with a sensitivity of 96.15%, specificity of 81.48%, and accuracy of 88.68%. This prediction model was more effective than PHASES score. In conclusion, high-throughput proteomics analysis with population validation was performed to assess blood-based protein expression characteristics. This revealed the potential mechanism of IA formation and rupture, facilitating the discovery of biomarkers. SIGNIFICANCE: Although the annual rupture rate of small unruptured aneurysms is believed to be minimal, studies have indicated that ruptured aneurysms typically have an average size of 6.28 mm, with 71.8% of them being <7 mm in diameter. Hence, evaluating the possibility of rupture in UIA and making a choice between aggressive treatment and conservative observation emerges as a significant challenge in the management of UIA. No biomarker or scoring system has been able to satisfactorily address this issue to date. It would be significant to develop biomarkers that could be used for early diagnosis of IA as well as for prediction of IA rupture. After TMT proteomics analysis and ELISA validation in independent populations, we found that FN1, PON1, and SERPINA1 can be utilized as diagnostic biomarkers for IA, and PFN1, ApoA-1, and SERPINA1 can serve as independent risk factors for predicting aneurysm rupture. Especially, when combined with ApoA-1, SERPINA1, and PFN1 for predicting IA rupture, the area under the curve (AUC) was 0.954 with a sensitivity of 96.15%, specificity of 81.48%, and accuracy of 88.68%. This prediction model was more effective than PHASES score.

Integrative proteome analysis of bone marrow interstitial fluid and serum reveals candidate signature for acute myeloid leukemia.

Acute myeloid leukemia (AML) is an aggressive form of blood cancer and clinically highly heterogeneous characterized by the accumulation of clonally proliferative immature precursors of myeloid lineage leading to bone marrow failure. Although, the current diagnostic methods for AML consist of cytogenetic and molecular assessment, there is a need for new markers that can serve as useful candidates in diagnosis, prognosis and understanding the pathophysiology of the disease. This study involves the investigation of alterations in the bone marrow interstitial fluid and serum proteome of AML patients compared to controls using label-free quantitative proteomic approach. A total of 201 differentially abundant proteins were identified in AML BMIF, while in the case of serum 123 differentially abundant proteins were identified. The bioinformatics analysis performed using IPA revealed several altered pathways including FAK signalling, IL-12 signalling and production of macrophages etc. Verification experiments were performed in a fresh independent cohort of samples using MRM assays led to the identification of a panel of three proteins viz., PPBP, APOH, ENOA which were further validated in a new cohort of serum samples by ELISA. The three-protein panel could be helpful in the diagnosis, prognosis and understanding of the pathophysiology of AML in the future. BIOLOGICAL SIGNIFICANCE: Acute Myeloid Leukemia (AML) is a type haematological malignancy which constitute one third of total leukemias and it is the most common acute leukemia in adults. In the current clinical practice, the evaluation of diagnosis and progression of AML is largely based on morphologic, immunophenotypic, cytogenetic and molecular assessment. There is a need for new markers/signatures which can serve as useful candidates in diagnosis and prognosis. The present study aims to identify and validate candidate biosignature for AML which can be useful in diagnosis, prognosis and understand the pathophysiology of the disease. Here, we identified 201 altered proteins in AML BMIF and 123 in serum. Among these altered proteins, a set of three proteins viz., pro-platelet basic protein (CXCL7), enolase 1 (ENO1) and beta-2-glycoprotein 1 (APOH) were significantly increased in AML BMIF and serum suggest that this panel of proteins could help in future AML disease management and thereby improving the survival expectancy of AML patients.

Characterization of Aspergillus fumigatus secretome during sublethal infection of Galleria mellonella larvae.

Introduction. The fungal pathogen Aspergillus fumigatus can induce prolonged colonization of the lungs of susceptible patients, resulting in conditions such as allergic bronchopulmonary aspergillosis and chronic pulmonary aspergillosis.Hypothesis. Analysis of the A. fumigatus secretome released during sub-lethal infection of G. mellonella larvae may give an insight into products released during prolonged human colonisation.Methodology. Galleria mellonella larvae were infected with A. fumigatus, and the metabolism of host carbohydrate and proteins and production of fungal virulence factors were analysed. Label-free qualitative proteomic analysis was performed to identify fungal proteins in larvae at 96 hours post-infection and also to identify changes in the Galleria proteome as a result of infection.Results. Infected larvae demonstrated increasing concentrations of gliotoxin and siderophore and displayed reduced amounts of haemolymph carbohydrate and protein. Fungal proteins (399) were detected by qualitative proteomic analysis in cell-free haemolymph at 96 hours and could be categorized into seven groups, including virulence (n = 25), stress response (n = 34), DNA repair and replication (n = 39), translation (n = 22), metabolism (n = 42), released intracellular (n = 28) and cellular development and cell cycle (n = 53). Analysis of the Gallerial proteome at 96 hours post-infection revealed changes in the abundance of proteins associated with immune function, metabolism, cellular structure, insect development, transcription/translation and detoxification.Conclusion. Characterizing the impact of the fungal secretome on the host may provide an insight into how A. fumigatus damages tissue and suppresses the immune response during long-term pulmonary colonization.

TSWIFT, a novel method for iterative staining of embedded and mounted human brain sections.

Comprehensive characterization of protein networks in mounted brain tissue represents a major challenge in brain and neurodegenerative disease research. In this study, we develop a simple staining method, called TSWIFT, to iteratively stain pre-mounted formalin fixed, paraffin embedded (FFPE) brain sections, thus enabling high-dimensional sample phenotyping. We show that TSWIFT conserves tissue architecture and allows for relabeling a single mounted FFPE sample more than 10 times, even after prolonged storage at 4 °C. Our results establish TSWIFT as an efficient method to obtain integrated high-dimensional knowledge of cellular proteomes by analyzing mounted FFPE human brain tissue.

A secreted proteomic footprint for stem cell pluripotency.

With a view to developing a much-needed non-invasive method for monitoring the healthy pluripotent state of human stem cells in culture, we undertook proteomic analysis of the waste medium from cultured embryonic (Man-13) and induced (Rebl.PAT) human pluripotent stem cells (hPSCs). Cells were grown in E8 medium to maintain pluripotency, and then transferred to FGF2 and TGFß deficient E6 media for 48 hours to replicate an early, undirected dissolution of pluripotency. We identified a distinct proteomic footprint associated with early loss of pluripotency in both hPSC lines, and a strong correlation with changes in the transcriptome. We demonstrate that multiplexing of four E8- against four E6- enriched secretome biomarkers provides a robust, diagnostic metric for the pluripotent state. These biomarkers were further confirmed by Western blotting which demonstrated consistent correlation with the pluripotent state across cell lines, and in response to a recovery assay.