In-depth human plasma proteome analysis captures tissue proteins and transfer of protein variants across the placenta

Small molecule modulation of protein corona for deep plasma proteome profiling

The protein corona formed on nanoparticles (NPs) has potential as a valuable diagnostic tool for improving plasma proteome coverage. Here, we show that spiking small molecules, including metabolites, lipids, vitamins, and nutrients into plasma can induce diverse protein corona patterns on otherwise identical NPs, significantly enhancing the depth of plasma proteome profiling. The protein coronas on polystyrene NPs when exposed to plasma treated with an array of small molecules allows for the detection of 1793 proteins marking an 8.25-fold increase in the number of quantified proteins compared to plasma alone (218 proteins) and a 2.63-fold increase relative to the untreated protein corona (681 proteins). Furthermore, we discovered that adding 1000 µg/ml phosphatidylcholine could singularly enable the detection of 897 proteins. At this specific concentration, phosphatidylcholine selectively depletes the four most abundant plasma proteins, including albumin, thus reducing the dynamic range of plasma proteome and enabling the detection of proteins with lower abundance. Employing an optimized data-independent acquisition approach, the inclusion of phosphatidylcholine leads to the detection of 1436 proteins in a single plasma sample. Our molecular dynamics results reveal that phosphatidylcholine interacts with albumin via hydrophobic interactions, H-bonds, and water bridges. The addition of phosphatidylcholine also enables the detection of 337 additional proteoforms compared to untreated protein corona using a top-down proteomics approach. Given the critical role of plasma proteomics in biomarker discovery and disease monitoring, we anticipate the widespread adoption of this methodology for the identification and clinical translation of biomarkers.

The Circulating Proteome─Technological Developments, Current Challenges, and Future Trends

Recent improvements in proteomics technologies have fundamentally altered our capacities to characterize human biology. There is an ever-growing interest in using these novel methods for studying the circulating proteome, as blood offers an accessible window into human health. However, every methodological innovation and analytical progress calls for reassessing our existing approaches and routines to ensure that the new data will add value to the greater biomedical research community and avoid previous errors. As representatives of HUPO's Human Plasma Proteome Project (HPPP), we present our 2024 survey of the current progress in our community, including the latest build of the Human Plasma Proteome PeptideAtlas that now comprises 4608 proteins detected in 113 data sets. We then discuss the updates of established proteomics methods, emerging technologies, and investigations of proteoforms, protein networks, extracellualr vesicles, circulating antibodies and microsamples. Finally, we provide a prospective view of using the current and emerging proteomics tools in studies of circulating proteins.

Deep Plasma Proteome Profiling by Modulating Single Nanoparticle Protein Corona with Small Molecules

The protein corona, a dynamic biomolecular layer that forms on nanoparticle (NP) surfaces upon exposure to biological fluids is emerging as a valuable diagnostic tool for improving plasma proteome coverage analyzed by liquid chromatography-mass spectrometry (LC-MS/MS). Here, we show that spiking small molecules, including metabolites, lipids, vitamins, and nutrients (namely, glucose, triglyceride, diglycerol, phosphatidylcholine, phosphatidylethanolamine, L-α-phosphatidylinositol, inosine 5'-monophosphate, and B complex), into plasma can induce diverse protein corona patterns on otherwise identical NPs, significantly enhancing the depth of plasma proteome profiling. The protein coronas on polystyrene NPs when exposed to plasma treated with an array of small molecules (n=10) allowed for detection of 1793 proteins marking an 8.25-fold increase in the number of quantified proteins compared to plasma alone (218 proteins) and a 2.63-fold increase relative to the untreated protein corona (681 proteins). Furthermore, we discovered that adding 1000 μg/ml phosphatidylcholine could singularly enable the detection of 897 proteins. At this specific concentration, phosphatidylcholine selectively depleted the four most abundant plasma proteins, including albumin, thus reducing the dynamic range of plasma proteome and enabling the detection of proteins with lower abundance. By employing an optimized data-independent acquisition (DIA) approach, the inclusion of phosphatidylcholine led to the detection of 1436 proteins in a single plasma sample. Our molecular dynamic results revealed that phosphatidylcholine interacts with albumin via hydrophobic interactions, h-bonds, and water-bridges. Addition of phosphatidylcholine also enabled the detection of 337 additional proteoforms compared to untreated protein corona using a top-down proteomics approach. These significant achievements are made utilizing only a single NP type and one small molecule to analyze a single plasma sample, setting a new standard in plasma proteome profiling. Given the critical role of plasma proteomics in biomarker discovery and disease monitoring, we anticipate widespread adoption of this methodology for identification and clinical translation of proteomic biomarkers into FDA approved diagnostics.

Standardizing Protein Corona Characterization in Nanomedicine: A Multicenter Study to Enhance Reproducibility and Data Homogeneity

We recently revealed significant variability in protein corona characterization across various proteomics facilities, indicating that data sets are not comparable between independent studies. This heterogeneity mainly arises from differences in sample preparation protocols, mass spectrometry workflows, and raw data processing. To address this issue, we developed standardized protocols and unified sample preparation workflows, distributing uniform protein corona digests to several top-performing proteomics centers from our previous study. We also examined the influence of using similar mass spectrometry instruments on data homogeneity and standardized database search parameters and data processing workflows. Our findings reveal a remarkable stepwise improvement in protein corona data uniformity, increasing overlaps in protein identification from 11% to 40% across facilities using similar instruments and through a uniform database search. We identify the key parameters behind data heterogeneity and provide recommendations for designing experiments. Our findings should significantly advance the robustness of protein corona analysis for diagnostic and therapeutics applications.

SPRING is a Dedicated Licensing Factor for SREBP-Specific Activation by S1P

SREBP transcription factors are central regulators of lipid metabolism. Their proteolytic activation requires ER to the Golgi translocation and subsequent cleavage by site-1-protease (S1P). Produced as a proprotein, S1P undergoes autocatalytic cleavage from its precursor S1PA to mature S1PC form. Here, we report that SPRING (previously C12ORF29) and S1P interact through their ectodomains, and that this facilitates the autocatalytic cleavage of S1PA into its mature S1PC form. Reciprocally, we identified a S1P recognition-motif in SPRING and demonstrate that S1P-mediated cleavage leads to secretion of the SPRING ectodomain in cells, and in liver-specific Spring knockout (LKO) mice transduced with AAV-mSpring. By reconstituting SPRING variants into SPRINGKO cells we show that the SPRING ectodomain supports proteolytic maturation of S1P and SREBP signaling, but that S1P-mediated SPRING cleavage is not essential for these processes. Absence of SPRING modestly diminishes proteolytic maturation of S1PA→C and trafficking of S1PC to the Golgi. However, despite reaching the Golgi in SPRINGKO cells, S1PC fails to rescue SREBP signaling. Remarkably, whereas SREBP signaling was severely attenuated in SPRINGKO cells and LKO mice, that of ATF6, another S1P substrate, was unaffected in these models. Collectively, our study positions SPRING as a dedicated licensing factor for SREBP-specific activation by S1P.

Mustn1 is a smooth muscle cell-secreted microprotein that modulates skeletal muscle extracellular matrix composition

OBJECTIVE

Skeletal muscle plasticity and remodeling are critical for adapting tissue function to use, disuse, and regeneration. The aim of this study was to identify genes and molecular pathways that regulate the transition from atrophy to compensatory hypertrophy or recovery from injury. Here, we have used a mouse model of hindlimb unloading and reloading, which causes skeletal muscle atrophy, and compensatory regeneration and hypertrophy, respectively.

METHODS

We analyzed mouse skeletal muscle at the transition from hindlimb unloading to reloading for changes in transcriptome and extracellular fluid proteome. We then used qRT-PCR, immunohistochemistry, and bulk and single-cell RNA sequencing data to determine Mustn1 gene and protein expression, including changes in gene expression in mouse and human skeletal muscle with different challenges such as exercise and muscle injury. We generated Mustn1-deficient genetic mouse models and characterized them in vivo and ex vivo with regard to muscle function and whole-body metabolism. We isolated smooth muscle cells and functionally characterized them, and performed transcriptomics and proteomics analysis of skeletal muscle and aorta of Mustn1-deficient mice.

RESULTS

We show that Mustn1 (Musculoskeletal embryonic nuclear protein 1, also known as Mustang) is highly expressed in skeletal muscle during the early stages of hindlimb reloading. Mustn1 expression is transiently elevated in mouse and human skeletal muscle in response to intense exercise, resistance exercise, or injury. We find that Mustn1 expression is highest in smooth muscle-rich tissues, followed by skeletal muscle fibers. Muscle from heterozygous Mustn1-deficient mice exhibit differences in gene expression related to extracellular matrix and cell adhesion, compared to wild-type littermates. Mustn1-deficient mice have normal muscle and aorta function and whole-body glucose metabolism. We show that Mustn1 is secreted from smooth muscle cells, and that it is present in arterioles of the muscle microvasculature and in muscle extracellular fluid, particularly during the hindlimb reloading phase. Proteomics analysis of muscle from Mustn1-deficient mice confirms differences in extracellular matrix composition, and female mice display higher collagen content after chemically induced muscle injury compared to wild-type littermates.

CONCLUSIONS

We show that, in addition to its previously reported intracellular localization, Mustn1 is a microprotein secreted from smooth muscle cells into the muscle extracellular space. We explore its role in muscle ECM deposition and remodeling in homeostasis and upon muscle injury. The role of Mustn1 in fibrosis and immune infiltration upon muscle injury and dystrophies remains to be investigated, as does its potential for therapeutic interventions.

Optimizing and integrating depletion and precipitation methods for plasma proteomics through data-independent acquisition-mass spectrometry

The application of plasma proteomics is a reliable approach for the discovery of biomarkers. However, the utilization of mass spectrometry-based proteomics in plasma encounters limitations due to the presence of high-abundant proteins (HAPs) and the vast dynamic range. To address this issue, we conducted an optimization and integration of depletion and precipitation strategies eliminating interference from HAPs. The optimized procedure involved utilizing 40 µL of beads for the removal of 1 µL of plasma, and maintaining a ratio of 1:1:1 between plasma, urea, and trichloroacetic acid for the precipitation of 50 µL of plasma. To facilitate high-throughput processing, experimental procedures were carried out utilizing 96-well plates. The depletion method identified a total of 1510 proteins, whereas the precipitated method yielded a total of 802 proteins. The integration of these methods yielded a total of 1794 proteins, including a wide concentration range spanning over 8 orders of magnitude. Furthermore, these approaches exhibited a commendable level of reproducibility, as indicated by median coefficients of variation of 14.7 % and 21.1 % for protein intensities, respectively. The integrative method was found to be effective in precisely quantifying yeast proteins that were intentionally spiked in plasma at predetermined rations of 5, 2, 0.5, and 0.2 with a high genuine positive recovery with a range of 71 % to 91 % of all yeast proteins. The use of a complementary and finely tuned approach involving depletion and precipitation demonstrates tremendous potential in the field of discovering protein biomarkers from large-scale cohort studies.

Dilute to Enrich for Deeper Proteomics: A Yolk-Depleted Carrier for Limited Populations of Embryonic (Frog) Cells

Abundant proteins challenge deep mass spectrometry (MS) analysis of the proteome. Yolk, the source of food in many developing vertebrate embryos, complicates chemical separation and interferes with detection. We report here a strategy that enhances bottom-up proteomics in yolk-laden specimens by diluting the interferences using a yolk-depleted carrier (YODEC) proteome via isobaric multiplexing quantification. This method was tested on embryos of the South African Clawed Frog (Xenopus laevis), where a >90% yolk proteome content challenges deep proteomics. As a proof of concept, we isolated neural and epidermal fated cell clones from the embryo by dissection or fluorescence-activated cell sorting. Compared with the standard multiplexing carrier approach, YODEC more than doubled the detectable X. laevis proteome, identifying 5,218 proteins from D11 cell clones dissected from the embryo. Ca. ∼80% of the proteins were quantified without dropouts in any of the analytical channels. YODEC with high-pH fractionation quantified 3,133 proteins from ∼8,000 V11 cells that were sorted from ca. 2 embryos (1.5 μg total, or 150 ng yolk-free proteome), marking a 15-fold improvement in proteome coverage vs the standard proteomics approach. About 60% of these proteins were only quantifiable by YODEC, including molecular adaptors, transporters, translation, and transcription factors. While this study was tailored to limited populations of Xenopus cells, we anticipate the approach of "dilute to enrich" using a depleted carrier proteome to be adaptable to other biological models in which abundant proteins challenge deep MS proteomics.

The emerging Janus face of SVEP1 in development and disease

Sushi, von Willebrand factor type A, EGF, and pentraxin domain containing 1 (SVEP1) is a large extracellular matrix protein that is also detected in circulation. Recent plasma proteomic and genomic studies have revealed a large number of associations between SVEP1 and human traits, particularly chronic disease. These include associations with cardiac death and disease, diabetes, platelet traits, glaucoma, dementia, and aging; many of these are causal. Animal models demonstrate that SVEP1 is critical in vascular development and disease, but its molecular and cellular mechanisms remain poorly defined. Future studies should aim to characterize these mechanisms and determine the diagnostic, prognostic, and therapeutic value of measuring or intervening on this enigmatic protein.

A new SPRING in lipid metabolism

PURPOSE OF REVIEW

The SREBP transcription factors are master regulators of lipid homeostasis owing to their role in controlling cholesterol and fatty acid metabolism. The core machinery required to promote their trafficking and proteolytic activation has been established close to 20 years ago. In this review, we summarize the current understanding of a newly identified regulator of SREBP signaling, SPRING (formerly C12ORF49), its proposed mechanism of action, and its role in lipid metabolism.

RECENT FINDINGS

Using whole-genome functional genetic screens we, and others, have recently identified SPRING as a novel regulator of SREBP signaling. SPRING is a Golgi-resident single-pass transmembrane protein that is required for proteolytic activation of SREBPs in this compartment. Mechanistic studies identified regulation of S1P, the protease that cleaves SREBPs, and control of retrograde trafficking of the SREBP chaperone SCAP from the Golgi to the ER as processes requiring SPRING. Emerging studies suggest an important role for SPRING in regulating circulating and hepatic lipid levels in mice and potentially in humans.

SUMMARY

Current studies support the notion that SPRING is a novel component of the core SREBP-activating machinery. Additional studies are warranted to elucidate its role in cellular and systemic lipid metabolism.

Comprehensive proteomics and meta-analysis of COVID-19 host response

COVID-19 is characterised by systemic immunological perturbations in the human body, which can lead to multi-organ damage. Many of these processes are considered to be mediated by the blood. Therefore, to better understand the systemic host response to SARS-CoV-2 infection, we performed systematic analyses of the circulating, soluble proteins in the blood through global proteomics by mass-spectrometry (MS) proteomics. Here, we show that a large part of the soluble blood proteome is altered in COVID-19, among them elevated levels of interferon-induced and proteasomal proteins. Some proteins that have alternating levels in human cells after a SARS-CoV-2 infection in vitro and in different organs of COVID-19 patients are deregulated in the blood, suggesting shared infection-related changes.The availability of different public proteomic resources on soluble blood proteome alterations leaves uncertainty about the change of a given protein during COVID-19. Hence, we performed a systematic review and meta-analysis of MS global proteomics studies of soluble blood proteomes, including up to 1706 individuals (1039 COVID-19 patients), to provide concluding estimates for the alteration of 1517 soluble blood proteins in COVID-19. Finally, based on the meta-analysis we developed CoViMAPP, an open-access resource for effect sizes of alterations and diagnostic potential of soluble blood proteins in COVID-19, which is publicly available for the research, clinical, and academic community.

In-Depth Mass Spectrometry Analysis Reveals the Plasma Proteomic and N-Glycoproteomic Impact of an Amish-Enriched Cardioprotective Variant in B4GALT1

B4GALT1 encodes β-1,4-galactosyltransferase 1, an enzyme that plays a major role in glycan synthesis in the Golgi apparatus by catalyzing the addition of terminal galactose. Studies increasingly suggest that B4GALT1 may be involved in the regulation of lipid metabolism pathways. Recently, we discovered a single-site missense variant Asn352Ser (N352S) in the functional domain of B4GALT1 in an Amish population, which decreases the level of LDL-cholesterol (LDL-c) as well as the protein levels of ApoB, fibrinogen, and IgG in the blood. To systematically evaluate the effects of this missense variant on protein glycosylation, expression, and secretion, we developed a nano-LC-MS/MS-based platform combined with TMT-labeling for in-depth quantitative proteomic and glycoproteomic analyses in the plasma of individuals homozygous for the B4GALT1 missense variant N352S versus non-carriers (n = 5 per genotype). A total of 488 secreted proteins in the plasma were identified and quantified, 34 of which showed significant fold changes in protein levels between N352S homozygotes and non-carriers. We determined N-glycosylation profiles from 370 glycosylation sites in 151 glycoproteins and identified ten proteins most significantly associated with decreased galactosylation and sialyation in B4GALT1 N352S homozygotes. These results further support that B4GALT1 N352S alters the glycosylation profiles of a variety of critical target proteins, thus governing the functions of these proteins in multiple pathways, such as those involved in lipid metabolism, coagulation, and the immune response.

Proteomic analysis reveals microvesicles containing NAMPT as mediators of radioresistance in glioma

Tumor-initiating cells contained within the aggressive brain tumor glioma (glioma stem cells, GSCs) promote radioresistance and disease recurrence. However, mechanisms of resistance are not well understood. Herein, we show that the proteome-level regulation occurring upon radiation treatment of several patient-derived GSC lines predicts their resistance status, whereas glioma transcriptional subtypes do not. We identify a mechanism of radioresistance mediated by the transfer of the metabolic enzyme NAMPT to radiosensitive cells through microvesicles (NAMPT-high MVs) shed by resistant GSCs. NAMPT-high MVs rescue the proliferation of radiosensitive GSCs and fibroblasts upon irradiation, and upon treatment with a radiomimetic drug or low serum, and increase intracellular NAD(H) levels. Finally, we show that the presence of NAMPT within the MVs and its enzymatic activity in recipient cells are necessary to mediate these effects. Collectively, we demonstrate that the proteome of GSCs provides unique information as it predicts the ability of glioma to resist radiation treatment. Furthermore, we establish NAMPT transfer via MVs as a mechanism for rescuing the proliferation of radiosensitive cells upon irradiation.

Olink proteomics profiling platform reveals non-invasive inflammatory related protein biomarkers in autism spectrum disorder

Background

Owing to the lack of valid biomarkers, the diagnosis of autism spectrum disorder (ASD) diagnosis relies solely on the behavioral phenotypes of children. Several researchers have suggested an association between ASD and inflammation; however, the complex relationship between the two is unelucidated to date. Therefore, the current study aims to comprehensively identify novel circulating ASD inflammatory biomarkers.

Methods

Olink proteomics was applied to compare the plasma inflammation-related protein changes in a group of the healthy children (HC, n = 33) and another with ASD (n = 31). The areas under the receiver operating characteristic curves (AUCs) of the differentially expressed proteins (DEPs) were calculated. The functional analysis of the DEPs was performed using Gene Ontology and Kyoto Encyclopedia Genes and Genomes. Pearson correlation tests were used employed to analyze the correlation between the DEPs and clinical features.

Results

A total of 13 DEPs were significantly up-regulated in the ASD group compared with the HC group. The four proteins, namely, STAMBP, ST1A1, SIRT2, and MMP-10 demonstrated good diagnostic accuracy with the corresponding AUCs (95% confidence interval, CI) of 0.7218 (0.5946-0.8489), 0.7107 (0.5827-0.8387), 0.7016 (0.5713-0.8319), and 0.7006 (0.568-0.8332). Each panel of STAMBP and any other differential protein demonstrated a better classification performance [AUC values from 0.7147 (0.5858-0.8436, STAMBP/AXIN1) to 0.7681 (0.6496-0.8867, STAMBP/MMP-10)]. These DEP profiles were enriched in immune and inflammatory response pathways, including TNF and NOD-like receptor signaling pathways. The interaction between STAMBP and SIRT2 (R = 0.97, p = 8.52 × 10^-39) was found to be the most significant. In addition, several DEPs related to clinical features in patients with ASD, particularly AXIN1 (R = 0.36, p = 0.006), SIRT2 (R = 0.34, p = 0.010) and STAMBP (R = 0.34, p = 0.010), were positively correlated with age and parity, indicating that older age and higher parity may be the inflammation-related clinical factors in ASD.

Conclusion

Inflammation plays a crucial role in ASD, and the up-regulated inflammatory proteins may serve as potential early diagnostic biomarkers for ASD.

MS-based proteomics of body fluids: The end of the beginning

Accurate biomarkers are a crucial and necessary precondition for precision medicine, yet existing ones are often unspecific and new ones have been very slow to enter the clinic. Mass spectrometry (MS)-based proteomics excels by its untargeted nature, specificity of identification and quantification making it an ideal technology for biomarker discovery and routine measurement. It has unique attributes compared to affinity binder technologies, such as OLINK Proximity Extension Assay and SOMAscan. In a previous review we described technological and conceptual limitations that had held back success (Geyer et al., 2017). We proposed a 'rectangular strategy' to better separate true biomarkers by minimizing cohort-specific effects. Today, this has converged with advances in MS-based proteomics technology, such as increased sample throughput, depth of identification and quantification. As a result, biomarker discovery studies have become more successful, producing biomarker candidates that withstand independent verification and, in some cases, already outperform state-of-the-art clinical assays. We summarize developments over the last years, including the benefits of large and independent cohorts, which are necessary for clinical acceptance. They are also required for machine learning or deep learning. Shorter gradients, new scan modes and multiplexing are about to drastically increase throughput, cross-study integration, and quantification, including proxies for absolute levels. We have found that multi-protein panels are inherently more robust than current single analyte tests and better capture the complexity of human phenotypes. Routine MS measurement in the clinic is fast becoming a viable option. The full set of proteins in a body fluid (global proteome) is the most important reference and the best process control. Additionally, it increasingly has all the information that could be obtained from targeted analysis although the latter may be the most straightforward way to enter into regular use. Many challenges remain, not least of a regulatory and ethical nature, but the outlook for MS-based clinical applications has never been brighter.

The Potential of ICP-MS as a Complementary Tool in Nanoparticle-Protein Corona Analysis

The prolific applicability of nanomaterials has made them a common citizen in biological systems, where they interact with proteins forming a biological corona complex. These complexes drive the interaction of nanomaterials with and within the cells, bringing forward numerous potential applications in nanobiomedicine, but also arising toxicological issues and concerns. Proper characterization of the protein corona complex is a great challenge typically handled with the combination of several techniques. Surprisingly, despite inductively coupled plasma mass spectrometry (ICP-MS) being a powerful quantitative technique whose application in nanomaterials characterization and quantification has been consolidated in the last decade, its application to nanoparticle-protein corona studies is scarce. Furthermore, in the last decades, ICP-MS has experienced a turning point in its capabilities for protein quantification through sulfur detection, hence becoming a generic quantitative detector. In this regard, we would like to introduce the potential of ICP-MS in the nanoparticle protein corona complex characterization and quantification complementary to current methods and protocols.

Characterizing the origin of blood plasma proteins from organ tissues in rainbow trout (Oncorhynchus mykiss) using a comparative non-targeted proteomics approach

Protein expression patterns adapt to various cues to meet the needs of an organism. The dynamicity of an organism's proteome can therefore reveal information about an organism's health. Proteome databases contain limited information regarding organisms outside of medicinal biology. The UniProt human and mouse proteomes are extensively reviewed and ∼50 % of both proteomes include tissue specificity, while >99 % of the rainbow trout proteome lacks tissue specificity. This study aimed to expand knowledge on the rainbow trout proteome with a focus on understanding the origin of blood plasma proteins. Blood, brain, heart, liver, kidney, and gills were collected from adult rainbow trout, plasma and tissue proteins were analyzed using liquid chromatography tandem mass spectrometry. Over 10,000 proteins were identified across all groups. Our data indicated that the majority of the plasma proteome is shared amongst multiple tissue types, though 4-7 % of the plasma proteome is uniquely originated from each tissue (gill > heart > liver > kidney > brain).

SVEP1 is an endogenous ligand for the orphan receptor PEAR1

Sushi, von Willebrand factor type A, EGF and pentraxin domain containing 1 (SVEP1) is an extracellular matrix protein that causally promotes vascular disease and associates with platelet reactivity in humans. Here, using a human genomic and proteomic approach, we identify a high affinity, disease-relevant, and potentially targetable interaction between SVEP1 and the orphan receptor Platelet and Endothelial Aggregation Receptor 1 (PEAR1). This interaction promotes PEAR1 phosphorylation and disease associated AKT/mTOR signaling in vascular cells and platelets. Mice lacking SVEP1 have reduced platelet activation, and exogenous SVEP1 induces PEAR1-dependent activation of platelets. SVEP1 and PEAR1 causally and concordantly relate to platelet phenotypes and cardiovascular disease in humans, as determined by Mendelian Randomization. Targeting this receptor-ligand interaction may be a viable therapeutic strategy to treat or prevent cardiovascular and thrombotic disease.

A large-scale plasma proteome Mendelian randomization study identifies novel causal plasma proteins related to primary biliary cholangitis

Background and aims

Primary biliary cholangitis (PBC) is a progressive chronic autoimmune cholestatic liver disease characterized by the destruction of small intrahepatic bile ducts leading to biliary cirrhosis. Liver biopsy is required in the diagnosis of Antimitochondrial antibody-negative patients. Therefore, novel biomarkers are needed for the non-invasive diagnosis of PBC. To identify novel biomarkers for PBC, we conducted large-scale plasma proteome Mendelian randomization (MR).

Methods

A total of 21,593 protein quantitative trait loci (pQTLs) for 2297 circulating proteins were used and classified into four different groups. MR analyses were conducted in the four groups separately. Furthermore, the results were discovered and replicated in two different cohorts of PBC. Colocalization analysis and enrichment analysis were also conducted.

Results

Three plasma proteins (ficolin-1, CD40 and protein FAM177A1) were identified and replicated as being associated with PBC. All of them showed significant protective effects against PBC. An increase in ficolin-1 (OR=0.890 [0.843-0.941], p=3.50×10^-5), CD40 (OR=0.814 [0.741-0.895], p=1.96×10^-5) and protein FAM177A1 (OR=0.822 [0.754-0.897], p=9.75×10^-6) reduced the incidence of PBC. Ficolin-1 (PP4 = 0.994) and protein FAM177A1 (PP4 = 0.995) colocalized with the expression of the genes FCN1 and FAM177A1 in whole blood, respectively. Furthermore, CD40 (PP4 = 0.977) and protein FAM177A1 (PP4 = 0.897) strongly colocalized with PBC.

Conclusions

We expand the current biomarkers for PBC. In total, three (ficolin-1, CD40, and protein FAM177A1) plasma proteins were identified and replicated as being associated with PBC in MR analysis. All of them showed significant protective effects against PBC. These proteins can be potential biomarkers or drug targets for PBC.

Measurements of heterogeneity in proteomics analysis of the nanoparticle protein corona across core facilities

Robust characterization of the protein corona-the layer of proteins that spontaneously forms on the surface of nanoparticles immersed in biological fluids-is vital for prediction of the safety, biodistribution, and diagnostic/therapeutic efficacy of nanomedicines. Protein corona identity and abundance characterization is entirely dependent on liquid chromatography coupled to mass spectroscopy (LC-MS/MS), though the variability of this technique for the purpose of protein corona characterization remains poorly understood. Here we investigate the variability of LC-MS/MS workflows in analysis of identical aliquots of protein coronas by sending them to different proteomics core-facilities and analyzing the retrieved datasets. While the shared data between the cores correlate well, there is considerable heterogeneity in the data retrieved from different cores. Specifically, out of 4022 identified unique proteins, only 73 (1.8%) are shared across the core facilities providing semiquantitative analysis. These findings suggest that protein corona datasets cannot be easily compared across independent studies and more broadly compromise the interpretation of protein corona research, with implications in biomarker discovery as well as the safety and efficacy of our nanoscale biotechnologies.

High-Purity Corundum as Support for Affinity Extractions from Complex Samples

Nonporous corundum powder, known as an abrasive material in the industry, was functionalized covalently with protein binders to isolate and enrich specific proteins from complex matrices. The materials based on corundum were characterized by TEM, ESEM, BET, DLS, EDS, and zeta potential measurements. The strong Al-O-P bonds between the corundum surface and amino phosphonic acids were used to introduce functional groups for further conjugations. The common crosslinker glutaraldehyde was compared with a hyperbranched polyglycerol (PG) of around 10 kDa. The latter was oxidized with periodate to generate aldehyde groups that can covalently react with the amines of the surface and the amino groups from the protein via a reductive amination process. The amount of bound protein was quantified via aromatic amino acid analysis (AAAA). This work shows that oxidized polyglycerol can be used as an alternative to glutaraldehyde. With polyglycerol, more of the model protein bovine serum albumin (BSA) could be attached to the surface under the same conditions, and lower non-specific binding (NSB) was observed. As a proof of concept, IgG was extracted with protein A from crude human plasma. The purity of the product was examined by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). A binding capacity of 1.8 mg IgG per gram of corundum powder was achieved. The advantages of corundum include the very low price, extremely high physical and chemical stability, pressure resistance, favorable binding kinetics, convenient handling, and flexible application.

A review of suspension trapping digestion method in bottom-up proteomics

The standard bottom-up proteomic workflow is comprised of sample preparation, data acquisition, and data analysis. While the latter two parts have made considerable advances in the last decade, sample preparation has remained an important challenge within the workflow due to the multi-step nature of complex biological samples, and still requires much development. Several sample preparation methods have been developed and used in the last two decades, including in-gel, in-solution, on-bead, filter-aided sample preparation, and suspension trapping, to improve reproducibility, efficiency, scalability, and reduce handling time of this process. One of the most recent methods developed and applied in proteomics studies in recent years is suspension trapping, which combines rapid detergent removal, reactor-type protein digestion, and peptide clean-up in a tip or spin column. Suspension trapping is a simple, rapid, and reproducible digestion method that can effectively handle proteins in low microgram or sub-microgram amounts. This review discusses the benefits of the suspension trapping digestion method in relation to its development and application in bottom-up proteomics studies. We also discuss recent applications of suspension trapping digestion to different sample types and the features of the suspension trapping digestion method compared with other sample preparation methods. This article is protected by copyright. All rights reserved.

Comparing Efficiency of Lysis Buffer Solutions and Sample Preparation Methods for Liquid Chromatography-Mass Spectrometry Analysis of Human Cells and Plasma

The use of a proper sample processing methodology for maximum proteome coverage and high-quality quantitative data is an important choice to make before initiating a liquid chromatography–mass spectrometry (LC–MS)-based proteomics study. Popular sample processing workflows for proteomics involve in-solution proteome digestion and single-pot, solid-phase-enhanced sample preparation (SP3). We tested them on both HeLa cells and human plasma samples, using lysis buffers containing SDS, or guanidinium hydrochloride. We also studied the effect of using commercially available depletion mini spin columns before SP3, to increase proteome coverage in human plasma samples. Our results show that the SP3 protocol, using either buffer, achieves the highest number of quantified proteins in both the HeLa cells and plasma samples. Moreover, the use of depletion mini spin columns before SP3 results in a two-fold increase of quantified plasma proteins. With additional fractionation, we quantified nearly 1400 proteins, and examined lower-abundance proteins involved in neurodegenerative pathways and mitochondrial metabolism. Therefore, we recommend the use of the SP3 methodology for biological sample processing, including those after depletion of high-abundance plasma proteins.

Biomarker Candidates for Tumors Identified from Deep-Profiled Plasma Stem Predominantly from the Low Abundant Area

The plasma proteome has the potential to enable a holistic analysis of the health state of an individual. However, plasma biomarker discovery is difficult due to its high dynamic range and variability. Here, we present a novel automated analytical approach for deep plasma profiling and applied it to a 180-sample cohort of human plasma from lung, breast, colorectal, pancreatic, and prostate cancers. Using a controlled quantitative experiment, we demonstrate a 257% increase in protein identification and a 263% increase in significantly differentially abundant proteins over neat plasma. In the cohort, we identified 2732 proteins. Using machine learning, we discovered biomarker candidates such as STAT3 in colorectal cancer and developed models that classify the diseased state. For pancreatic cancer, a separation by stage was achieved. Importantly, biomarker candidates came predominantly from the low abundance region, demonstrating the necessity to deeply profile because they would have been missed by shallow profiling.

Proteomics of Human Biological Fluids for Biomarker Discoveries: Technical Advances and Recent Applications

INTRODUCTION

Biological fluids are routine samples for diagnostic testing and monitoring. Blood samples are typically measured because of their moderate collection invasiveness and high information content on health and disease. Several body fluids, such as cerebrospinal fluid (CSF), are also studied and suited to specific pathologies. Over the last two decades proteomics has quested to identify protein biomarkers but with limited success. Recent technologies and refined pipelines have accelerated the profiling of human biological fluids.

AREAS COVERED

We review proteomic technologies for the identification of biomarkers. Those are based on antibodies/aptamers arrays or mass spectrometry (MS), but new ones are emerging. Advances in scalability and throughput have allowed to better design studies and cope with the limited sample size that had until now prevailed due to technological constraints. With these enablers, plasma/serum, CSF, saliva, tears, urine, and milk proteomes have been further profiled; we provide a non-exhaustive picture of some recent highlights (mainly covering literature from last five years in the Scopus database) using MS-based proteomics.

EXPERT OPINION

While proteomics has been in the shadow of genomics for years, proteomic tools and methodologies have reached a certain maturity. They are better suited to discover innovative and robust biofluid biomarkers.

Plasma proteome profiling combined with clinical and genetic features reveals the pathophysiological characteristics of β-thalassemia

The phenotype of β-thalassemia underlies multigene interactions, making clinical stratification complicated. An increasing number of genetic modifiers affecting the disease severity have been identified, but are still unable to meet the demand of precision diagnosis. Here, we systematically conducted a comparative plasma proteomic profiling on patients with β-thalassemia and healthy controls. Among 246 dysregulated proteins, 13 core protein signatures with excellent biomarker potential are proposed. The combination of proteome and patients' clinical data revealed patients with codons 41/42 -TTCT mutations have an elevated risk of higher iron burden, dysplasia, and osteoporosis than patients with other genotypes. Notably, 85 proteins correlating to fetal hemoglobin (Hb F) were identified, among which the abundance of 27 proteins may affect the transfusion burden in patients with β-thalassemia. The current study thus provides protein signatures as potential diagnostic biomarkers or therapeutic clues for β-thalassemia.

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246 dysregulated proteins are detected in plasma of patients with β-thalassemia

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13 potential biomarkers and 27 proteins related to disease progression are found

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Variations in plasma proteome reveal the disease pathophysiological characteristics

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Codons 41/42 -TTCT carriers have higher ferritin levels compared to non-carriers

Applications of Tandem Mass Spectrometry (MS/MS) in Protein Analysis for Biomedical Research

Mass Spectrometry (MS) allows the analysis of proteins and peptides through a variety of methods, such as Electrospray Ionization-Mass Spectrometry (ESI-MS) or Matrix-Assisted Laser Desorption Ionization-Mass Spectrometry (MALDI-MS). These methods allow identification of the mass of a protein or a peptide as intact molecules or the identification of a protein through peptide-mass fingerprinting generated upon enzymatic digestion. Tandem mass spectrometry (MS/MS) allows the fragmentation of proteins and peptides to determine the amino acid sequence of proteins (top-down and middle-down proteomics) and peptides (bottom-up proteomics). Furthermore, tandem mass spectrometry also allows the identification of post-translational modifications (PTMs) of proteins and peptides. Here, we discuss the application of MS/MS in biomedical research, indicating specific examples for the identification of proteins or peptides and their PTMs as relevant biomarkers for diagnostic and therapy.

Engineered nanoparticles enable deep proteomics studies at scale by leveraging tunable nano-bio interactions

SignificanceDeep profiling of the plasma proteome at scale has been a challenge for traditional approaches. We achieve superior performance across the dimensions of precision, depth, and throughput using a panel of surface-functionalized superparamagnetic nanoparticles in comparison to conventional workflows for deep proteomics interrogation. Our automated workflow leverages competitive nanoparticle-protein binding equilibria that quantitatively compress the large dynamic range of proteomes to an accessible scale. Using machine learning, we dissect the contribution of individual physicochemical properties of nanoparticles to the composition of protein coronas. Our results suggest that nanoparticle functionalization can be tailored to protein sets. This work demonstrates the feasibility of deep, precise, unbiased plasma proteomics at a scale compatible with large-scale genomics enabling multiomic studies.

Kinetic Method of Producing Pores Inside Protein-Based Biomaterials without Compromising Their Structural Integrity

Hydrogels made from globular proteins cross-linked covalently into a stable network are becoming an important type of biomaterial, with applications in artificial tissue design and cell culture scaffolds, and represent a promising system to study the mechanical and biochemical unfolding of proteins in crowded environments. Due to the small size of the globular protein domains, typically 2-5 nm, the primary network allows for a limited transfer of protein molecules and prevents the passing of particles and aggregates with dimensions over 100 nm. Here, we demonstrate a method to produce protein materials with micrometer-sized pores and increased permeability. Our approach relies on forming two competing networks: a covalent network made from cross-linked bovine serum albumin (BSA) proteins via a light-activated reaction and a physical network triggered by the aggregation of a polysaccharide, alginate, in the presence of Ca²⁺ ions. By fine-tuning the reaction times, we produce porous-protein hydrogels that retain the mechanical characteristics of their less-porous counterparts. We further describe a simple model to investigate the kinetic balance between the nucleation of alginate and cross-linking of BSA molecules and find the upper rate of the alginate aggregation reaction driving pore formation. By enabling a more significant permeability for protein-based materials without compromising their mechanical response, our method opens new vistas into studying protein-protein interactions and cell growth and designing novel affinity methods.

Recent Developments in Clinical Plasma Proteomics—Applied to Cardiovascular Research

The human plasma proteome mirrors the physiological state of the cardiovascular system, a fact that has been used to analyze plasma biomarkers in routine analysis for the diagnosis and monitoring of cardiovascular diseases for decades. These biomarkers address, however, only a very limited subset of cardiovascular diseases, such as acute myocardial infarct or acute deep vein thrombosis, and clinical plasma biomarkers for the diagnosis and stratification cardiovascular diseases that are growing in incidence, such as heart failure and abdominal aortic aneurysm, do not exist and are urgently needed. The discovery of novel biomarkers in plasma has been hindered by the complexity of the human plasma proteome that again transforms into an extreme analytical complexity when it comes to the discovery of novel plasma biomarkers. This complexity is, however, addressed by recent achievements in technologies for analyzing the human plasma proteome, thereby facilitating the possibility for novel biomarker discoveries. The aims of this article is to provide an overview of the recent achievements in technologies for proteomic analysis of the human plasma proteome and their applications in cardiovascular medicine.

Blood-incompatibility in haemodialysis: alleviating inflammation and effects of coagulation

Blood-incompatibility is an inevitability of all blood-contacting device applications and therapies, including haemodialysis (HD). Blood leaving the environment of blood vessels and the protection of the endothelium is confronted with several stimuli of the extracorporeal circuit (ECC), triggering the activation of blood cells and various biochemical pathways of plasma. Prevention of blood coagulation, a major obstacle that needed to be overcome to make HD possible, remains an issue to contend with. While anticoagulation (mainly with heparin) successfully prevents clotting within the ECC to allow removal of uraemic toxins across the dialysis membrane wall, it is far from ideal, triggering heparin-induced thrombocytopenia in some instances. Soluble fibrin can form even in the presence of heparin and depending on the constitution of the patient and activation of platelets, could result in physical clots within the ECC (e.g. bubble trap chamber) and, together with other plasma and coagulation proteins, result in increased adsorption of proteins on the membrane surface. The buildup of this secondary membrane layer impairs the transport properties of the membrane to reduce the clearance of uraemic toxins. Activation of complement system-dependent immune response pathways leads to leukopenia, formation of platelet–neutrophil complexes and expression of tissue factor contributing to thrombotic processes and a procoagulant state, respectively. Complement activation also promotes recruitment and activation of leukocytes resulting in oxidative burst and release of pro-inflammatory cytokines and chemokines, thereby worsening the elevated underlying inflammation and oxidative stress condition of chronic kidney disease patients. Restricting all forms of blood-incompatibility, including potential contamination of dialysis fluid with endotoxins leading to inflammation, during HD therapies is thus still a major target towards more blood-compatible and safer dialysis to improve patient outcomes. We describe the mechanisms of various activation pathways during the interaction between blood and components of the ECC and describe approaches to mitigate the effects of these adverse interactions. The opportunities to develop improved dialysis membranes as well as implementation strategies with less potential for undesired biological reactions are discussed.

Proteome profiling of whole plasma and plasma-derived extracellular vesicles facilitates the detection of tissue biomarkers in the non-obese diabetic mouse

The mechanism by which pancreatic beta cells are destroyed in type 1 diabetes (T1D) remains to be fully understood. Recent observations indicate that the disease may arise because of different pathobiological mechanisms (endotypes). The discovery of one or several protein biomarkers measurable in readily available liquid biopsies (e.g. blood plasma) during the pre-diabetic period may enable personalized disease interventions. Recent studies have shown that extracellular vesicles (EVs) are a source of tissue proteins in liquid biopsies. Using plasma samples collected from pre-diabetic non-obese diabetic (NOD) mice (an experimental model of T1D) we addressed if combined analysis of whole plasma samples and plasma-derived EV fractions increases the number of unique proteins identified by mass spectrometry (MS) compared to the analysis of whole plasma samples alone. LC-MS/MS analysis of plasma samples depleted of abundant proteins and subjected to peptide fractionation identified more than 2300 proteins, while the analysis of EV-enriched plasma samples identified more than 600 proteins. Of the proteins detected in EV-enriched samples, more than a third were not identified in whole plasma samples and many were classified as either tissue-enriched or of tissue-specific origin. In conclusion, parallel profiling of EV-enriched plasma fractions and whole plasma samples increases the overall proteome depth and facilitates the discovery of tissue-enriched proteins in plasma. If applied to plasma samples collected longitudinally from the NOD mouse or from models with other pathobiological mechanisms, the integrated proteome profiling scheme described herein may be useful for the discovery of new and potentially endotype specific biomarkers in T1D.

Control of Blood Coagulation by Hemocompatible Material Surfaces-A Review

Hemocompatibility of biomaterials in contact with the blood of patients is a prerequisite for the short- and long-term applications of medical devices such as cardiovascular stents, artificial heart valves, ventricular assist devices, catheters, blood linings and extracorporeal devices such as artificial kidneys (hemodialysis), extracorporeal membrane oxygenation (ECMO) and cardiopulmonary bypass. Although lower blood compatibility of materials and devices can be handled with systemic anticoagulation, its side effects, such as an increased bleeding risk, make materials that have a better hemocompatibility highly desirable, particularly in long-term applications. This review provides a short overview on the basic mechanisms of blood coagulation including plasmatic coagulation and blood platelets, as well as the activation of the complement system. Furthermore, a survey on concepts for tailoring the blood response of biomaterials to improve the hemocompatibility of medical devices is given which covers different approaches that either inhibit interaction of material surfaces with blood components completely or control the response of the coagulation system, blood platelets and leukocytes.

Domont G, C. S. Nogueira F, Marko-Varga G, Sanchez A. Mapping the Melanoma Plasma Proteome (MPP) Using Single-Shot Proteomics Interfaced with the WiMT Database

Plasma analysis by mass spectrometry-based proteomics remains a challenge due to its large dynamic range of 10 orders in magnitude. We created a methodology for protein identification known as Wise MS Transfer (WiMT). Melanoma plasma samples from biobank archives were directly analyzed using simple sample preparation. WiMT is based on MS1 features between several MS runs together with custom protein databases for ID generation. This entails a multi-level dynamic protein database with different immunodepletion strategies by applying single-shot proteomics. The highest number of melanoma plasma proteins from undepleted and unfractionated plasma was reported, mapping >1200 proteins from >10,000 protein sequences with confirmed significance scoring. Of these, more than 660 proteins were annotated by WiMT from the resulting ~5800 protein sequences. We could verify 4000 proteins by MS1t analysis from HeLA extracts. The WiMT platform provided an output in which 12 previously well-known candidate markers were identified. We also identified low-abundant proteins with functions related to (i) cell signaling, (ii) immune system regulators, and (iii) proteins regulating folding, sorting, and degradation, as well as (iv) vesicular transport proteins. WiMT holds the potential for use in large-scale screening studies with simple sample preparation, and can lead to the discovery of novel proteins with key melanoma disease functions.

Clinical relevance of abstruse transport phenomena in haemodialysis

Haemodialysis (HD) utilizes the bidirectional properties of semipermeable membranes to remove uraemic toxins from blood while simultaneously replenishing electrolytes and buffers to correct metabolic acidosis. However, the nonspecific size-dependent transport across membranes also means that certain useful plasma constituents may be removed from the patient (together with uraemic toxins), or toxic compounds, e.g. endotoxin fragments, may accompany electrolytes and buffers of the dialysis fluids into blood and elicit severe biological reactions. We describe the mechanisms and implications of these undesirable transport processes that are inherent to all HD therapies and propose approaches to mitigate the effects of such transport. We focus particularly on two undesirable events that are considered to adversely affect HD therapy and possibly impact patient outcomes. Firstly, we describe how loss of albumin (and other essential substances) can occur while striving to eliminate larger uraemic toxins during HD and why hypoalbuminemia is a clinical condition to contend with. Secondly, we describe the origins and mode of transport of biologically active substances (from dialysis fluids with bacterial contamination) into the blood compartment and biological reactions they elicit. Endotoxin fragments activate various proinflammatory pathways to increase the underlying inflammation associated with chronic kidney disease. Both phenomena involve the physical as well as chemical properties of membranes that must be selected judiciously to balance the benefits with potential risks patients may encounter, in both the short and long term.

Advances and Utility of the Human Plasma Proteome

The study of proteins circulating in blood offers tremendous opportunities to diagnose, stratify, or possibly prevent diseases. With recent technological advances and the urgent need to understand the effects of COVID-19, the proteomic analysis of blood-derived serum and plasma has become even more important for studying human biology and pathophysiology. Here we provide views and perspectives about technological developments and possible clinical applications that use mass-spectrometry(MS)- or affinity-based methods. We discuss examples where plasma proteomics contributed valuable insights into SARS-CoV-2 infections, aging, and hemostasis and the opportunities offered by combining proteomics with genetic data. As a contribution to the Human Proteome Organization (HUPO) Human Plasma Proteome Project (HPPP), we present the Human Plasma PeptideAtlas build 2021-07 that comprises 4395 canonical and 1482 additional nonredundant human proteins detected in 240 MS-based experiments. In addition, we report the new Human Extracellular Vesicle PeptideAtlas 2021-06, which comprises five studies and 2757 canonical proteins detected in extracellular vesicles circulating in blood, of which 74% (2047) are in common with the plasma PeptideAtlas. Our overview summarizes the recent advances, impactful applications, and ongoing challenges for translating plasma proteomics into utility for precision medicine.

Liquid biopsy: state of reproductive medicine and beyond

Liquid biopsy is the process of sampling and analyzing body fluids, which enables non-invasive monitoring of complex biological systems in vivo. Liquid biopsy has myriad applications in health and disease as a wide variety of components, ranging from circulating cells to cell-free nucleic acid molecules, can be analyzed. Here, we review different components of liquid biopsy, survey state-of-the-art, non-invasive methods for detecting those components, demonstrate their clinical applications and discuss ethical considerations. Furthermore, we emphasize the importance of artificial intelligence in analyzing liquid biopsy data with the aim of developing ethically-responsible non-invasive technologies that can enhance individualized healthcare. While previous reviews have mainly focused on cancer, this review primarily highlights applications of liquid biopsy in reproductive medicine.

Development of standard definitions and grading for Maternal and Fetal Adverse Event Terminology

OBJECTIVE

Adverse event (AE) monitoring is central to assessing therapeutic safety. The lack of a comprehensive framework to define and grade maternal and fetal AEs in pregnancy trials severely limits understanding risks in pregnant women. We created AE terminology to improve safety monitoring for developing pregnancy drugs, devices and interventions.

METHOD

Existing severity grading for pregnant AEs and definitions/indicators of 'severe' and 'life-threatening' conditions relevant to maternal and fetal clinical trials were identified through a literature search. An international multidisciplinary group identified and filled gaps in definitions and severity grading using Medical Dictionary for Regulatory Activities (MedDRA) terms and severity grading criteria based on Common Terminology Criteria for Adverse Event (CTCAE) generic structure. The draft criteria underwent two rounds of a modified Delphi process with international fetal therapy, obstetric, neonatal, industry experts, patients and patient representatives.

RESULTS

Fetal AEs were defined as being diagnosable in utero with potential to harm the fetus, and were integrated into MedDRA. AE severity was graded independently for the pregnant woman and her fetus. Maternal (n = 12) and fetal (n = 19) AE definitions and severity grading criteria were developed and ratified by consensus.

CONCLUSIONS

This Maternal and Fetal AE Terminology version 1.0 allows systematic consistent AE assessment in pregnancy trials to improve safety.

Plasma proteome alterations by MAPK inhibitors in BRAFV600-mutated metastatic cutaneous melanoma

Approximately half of metastatic cutaneous melanomas (CM) harbor a mutation in the BRAF protooncogene, upregulating the mitogen-activated protein kinase (MAPK)-pathway. The development of inhibitors targeting the MAPK pathway (MAPKi), i.e., BRAF- and MEK-inhibitors (BRAFi and MEKi), have substantially improved the survival in BRAFV600E/K-mutated stage IV metastatic CM. However, most patients develop resistance to treatment and no predictive biomarkers exist in practice. This study aimed at discovering plasma proteome changes during treatment MAPKi in patients with metastatic (stage IV) CM. Matched plasma samples before (pre) and during treatment (trm) from 23 patients with stage IV CM, treated with BRAF-inhibitors (BRAFi) alone or BRAF- and MEK- inhibitors combined (BRAFi and MEKi), were collected and analyzed with targeted proteomics by proximity extension assays. Additionally, plasma from 9 patients treated with BRAFi and MEKi was analyzed with in-depth high-resolution isoelectric focusing liquid-chromatography mass-spectrometry proteomics. Alterations of plasma proteins involved in granzyme and interferon gamma pathways were detected in patients treated with BRAFi, and cell adhesion-, neutrophil degranulation-, and proteolysis pathways in patients treated with BRAFi and MEKi. Several proteins were associated with progression-free survival after MAPKi treatment. We show that the majority of the altered plasma proteins were traceable to BRAFV600E-mutant metastatic CM tissue at mRNA level in 154 patients from the TCGA, further strengthening their involvement in tumoral response to treatment. This wide screen of plasma proteins unravels proteins that may serve as predictive and/or prognostic biomarkers of MAPKi treatment, opening a window of opportunity for plasma biomarker discovery in MAPKi-treatment of BRAFV600-mutant metastatic CM.

Evaluation of Spin Columns for Human Plasma Depletion to Facilitate MS-Based Proteomics Analysis of Plasma

High abundant protein depletion is a common strategy applied to increase analytical depth in global plasma proteomics experiment setups. The standard strategies for depletion of the highest abundant proteins currently rely on multiple-use HPLC columns or multiple-use spin columns. Here we evaluate the performance of single-use spin columns for plasma depletion and show that the single-use spin reduces handling time by allowing parallelization and is easily adapted to a nonspecialized lab environment without reducing the high plasma proteome coverage and reproducibility. In addition, we evaluate the effect of viral heat inactivation on the plasma proteome, an additional step in the plasma preparation workflow that allows the sample preparation of SARS-Cov2-infected samples to be performed in a BSL3 laboratory, and report the advantage of performing the heat inactivation postdepletion. We further show the possibility of expanding the use of the depletion column cross-species to macaque plasma samples. In conclusion, we report that single-use spin columns for high abundant protein depletion meet the requirements for reproducibly in in-depth plasma proteomics and can be applied on a common animal model while also reducing the sample handling time.

Cancer diagnostics based on plasma protein biomarkers: hard times but great expectations

Cancer diagnostics based on the detection of protein biomarkers in blood has promising potential for early detection and continuous monitoring of disease. However, the currently available protein biomarkers and assay formats largely fail to live up to expectations, mainly due to insufficient diagnostic specificity. Here, we discuss what kinds of plasma proteins might prove useful as biomarkers of malignant processes in specific organs. We consider the need to search for biomarkers deep down in the lowest reaches of the proteome, below current detection levels. In this regard, we comment on the poor molecular detection sensitivity of current protein assays compared to nucleic acid detection reactions, and we discuss requirements for achieving detection of vanishingly small amounts of proteins, to ensure detection of early stages of malignant growth through liquid biopsy.

Identification of main influencing factors on the protein corona composition of PLGA and PLA nanoparticles

Poly(DL-lactic-co-glycolic acid) and poly(DL-lactic acid) are widely used for the preparation of nanoparticles due to favorable characteristics for medical use like biodegradability and controllable degradation behavior. The contact with different media like human plasma or serum leads to the formation of a protein corona that determines the NP's in vivo processing. In this study, the impact of surface end group identity, matrix polymer hydrophobicity, molecular weight, and incubation medium on the protein corona composition was evaluated. Corona proteins were quantified using Bradford assay, separated by SDS-PAGE, and identified via LC-MS/MS. The acquired data revealed that surface end group identity had the most profound effect on corona composition in both quantitative and qualitative terms. Regarding matrix polymer hydrophobicity, adsorption profiles on NP systems with similar physicochemical characteristics resembled each other. The molecular weight of the matrix polymers proved to impact quantity, but not quality of corona bound proteins. The corona of plasma incubated NP showed adsorption of incubation medium-specific proteins but resembled those of serum incubated NP in terms of protein function, average mass and isoelectric point. Overall, the NP physicochemical properties proved to be easily adjustable determining factors of protein corona formation in physiological environments.

High-throughput, in-depth and estimated absolute quantification of plasma proteome using data-independent acquisition/mass spectrometry ("HIAP-DIA")

Mass spectrometry-based plasma proteomics has been demonstrated to be a useful tool capable of quantifying hundreds of proteins in a single LC-MS/MS experiment, for biomarker discovery or elucidation of disease mechanisms. We developed a novel data-independent acquisition (DIA)/MS-based workflow for high-throughput, in-depth and estimated absolute quantification of plasma proteins (termed HIAP-DIA), without depleting high-abundant proteins, in a single-shot experiment. In HIAP-DIA workflow, we generated an ultra-deep cumulative undepleted and depleted spectral library which contained 55,157 peptides and 5,328 proteins, optimized column length (50 cm) and gradient (90 min) of liquid chromatography instrumentation, optimized 50 DIA segments with average isolation window 17 Th, and selected reference proteins for estimated absolute quantification of all plasma proteins. A total of 606 proteins were quantified in triplicate, and 427 proteins were quantified with CV <20% in plasma proteome. R-squared value of overlapped 208 endogenous PQ500 estimated protein amounts from HIAP-DIA and absolute quantification with internal standards was 0.82, indicating high quantification accuracy of HIAP-DIA. As a pilot study, the HIAP-DIA approach described here was applied to a myelodysplastic syndromes (MDS) disease cohort. We achieved absolute quantification of 789 plasma proteins in 22 clinical plasma samples, spanning less than six orders of magnitude with quantification limit 10-20 ng/mL, and discovered 95 differentially expressed proteins providing insights into MDS pathophysiology.

COVID-19: Nanomedicine Uncovers Blood-Clot Mystery

Further complications associated with infection by severe acute respiratory syndrome coronavirus 2 (a.k.a. SARS-CoV-2) continue to be reported. Very recent findings reveal that 20-30% of patients at high risk of mortality from COVID-19 infection experience blood clotting that leads to stroke and sudden death. Timely assessment of the severity of blood clotting will be of enormous help to clinicians in determining the right blood-thinning medications to prevent stroke or other life-threatening consequences. Therefore, rapid identification of blood-clotting-related proteins in the plasma of COVID-19 patients would save many lives. Several nanotechnology-based approaches are being developed to diagnose patients at high risk of death due to complications from COVID-19 infections, including blood clots. This Perspective outlines (i) the significant potential of nanomedicine in assessing the risk of blood clotting and its severity in SARS-CoV-2 infected patients and (ii) its synergistic roles with advanced mass-spectrometry-based proteomics approaches in identifying the important protein patterns that are involved in the occurrence and progression of this disease. The combination of such powerful tools might help us understand the clotting phenomenon and pave the way for development of new diagnostics and therapeutics in the fight against COVID-19.

Preparing for Life: Plasma Proteome Changes and Immune System Development During the First Week of Human Life

Neonates have heightened susceptibility to infections. The biological mechanisms are incompletely understood but thought to be related to age-specific adaptations in immunity due to resource constraints during immune system development and growth. We present here an extended analysis of our proteomics study of peripheral blood-plasma from a study of healthy full-term newborns delivered vaginally, collected at the day of birth and on day of life (DOL) 1, 3, or 7, to cover the first week of life. The plasma proteome was characterized by LC-MS using our established 96-well plate format plasma proteomics platform. We found increasing acute phase proteins and a reduction of respective inhibitors on DOL1. Focusing on the complement system, we found increased plasma concentrations of all major components of the classical complement pathway and the membrane attack complex (MAC) from birth onward, except C7 which seems to have near adult levels at birth. In contrast, components of the lectin and alternative complement pathways mainly decreased. A comparison to whole blood messenger RNA (mRNA) levels enabled characterization of mRNA and protein levels in parallel, and for 23 of the 30 monitored complement proteins, the whole blood transcript information by itself was not reflective of the plasma protein levels or dynamics during the first week of life. Analysis of immunoglobulin (Ig) mRNA and protein levels revealed that IgM levels and synthesis increased, while the plasma concentrations of maternally transferred IgG1-4 decreased in accordance with their in vivo half-lives. The neonatal plasma ratio of IgG1 to IgG2-4 was increased compared to adult values, demonstrating a highly efficient IgG1 transplacental transfer process. Partial compensation for maternal IgG degradation was achieved by endogenous synthesis of the IgG1 subtype which increased with DOL. The findings were validated in a geographically distinct cohort, demonstrating a consistent developmental trajectory of the newborn's immune system over the first week of human life across continents. Our findings indicate that the classical complement pathway is central for newborn immunity and our approach to characterize the plasma proteome in parallel with the transcriptome will provide crucial insight in immune ontogeny and inform new approaches to prevent and treat diseases.

Research on the Human Proteome Reaches a Major Milestone: >90% of Predicted Human Proteins Now Credibly Detected, According to the HUPO Human Proteome Project

According to the 2020 Metrics of the HUPO Human Proteome Project (HPP), expression has now been detected at the protein level for >90% of the 19 773 predicted proteins coded in the human genome. The HPP annually reports on progress made throughout the world toward credibly identifying and characterizing the complete human protein parts list and promoting proteomics as an integral part of multiomics studies in medicine and the life sciences. NeXtProt release 2020-01 classified 17 874 proteins as PE1, having strong protein-level evidence, up 180 from 17 694 one year earlier. These represent 90.4% of the 19 773 predicted coding genes (all PE1,2,3,4 proteins in neXtProt). Conversely, the number of neXtProt PE2,3,4 proteins, termed the "missing proteins" (MPs), was reduced by 230 from 2129 to 1899 since the neXtProt 2019-01 release. PeptideAtlas is the primary source of uniform reanalysis of raw mass spectrometry data for neXtProt, supplemented this year with extensive data from MassIVE. PeptideAtlas 2020-01 added 362 canonical proteins between 2019 and 2020 and MassIVE contributed 84 more, many of which converted PE1 entries based on non-MS evidence to the MS-based subgroup. The 19 Biology and Disease-driven B/D-HPP teams continue to pursue the identification of driver proteins that underlie disease states, the characterization of regulatory mechanisms controlling the functions of these proteins, their proteoforms, and their interactions, and the progression of transitions from correlation to coexpression to causal networks after system perturbations. And the Human Protein Atlas published Blood, Brain, and Metabolic Atlases.

Genetics meets proteomics: perspectives for large population-based studies

Proteomic analysis of cells, tissues and body fluids has generated valuable insights into the complex processes influencing human biology. Proteins represent intermediate phenotypes for disease and provide insight into how genetic and non-genetic risk factors are mechanistically linked to clinical outcomes. Associations between protein levels and DNA sequence variants that colocalize with risk alleles for common diseases can expose disease-associated pathways, revealing novel drug targets and translational biomarkers. However, genome-wide, population-scale analyses of proteomic data are only now emerging. Here, we review current findings from studies of the plasma proteome and discuss their potential for advancing biomedical translation through the interpretation of genome-wide association analyses. We highlight the challenges faced by currently available technologies and provide perspectives relevant to their future application in large-scale biobank studies.

Systemic vitamin intake impacting tissue proteomes

The kinetics and localization of the reactions of metabolism are coordinated by the enzymes that catalyze them. These enzymes are controlled via a myriad of mechanisms including inhibition/activation by metabolites, compartmentalization, thermodynamics, and nutrient sensing-based transcriptional or post-translational regulation; all of which are influenced as a network by the activities of metabolic enzymes and have downstream potential to exert direct or indirect control over protein abundances. Considering many of these enzymes are active only when one or more vitamin cofactors are present; the availability of vitamin cofactors likely yields a systems-influence over tissue proteomes. Furthermore, vitamins may influence protein abundances as nuclear receptor agonists, antioxidants, substrates for post-translational modifications, molecular signal transducers, and regulators of electrolyte homeostasis. Herein, studies of vitamin intake are explored for their contribution to unraveling vitamin influence over protein expression. As a body of work, these studies establish vitamin intake as a regulator of protein abundance; with the most powerful demonstrations reporting regulation of proteins directly related to the vitamin of interest. However, as a whole, the field has not kept pace with advances in proteomic platforms and analytical methodologies, and has not moved to validate mechanisms of regulation or potential for clinical application.

Cytokines in the grass, a lesson learnt: Measuring cytokines in plasma using multiple reaction monitoring mass spectrometry

RATIONALE

Cytokines are cell regulatory molecules of high importance as indicators for homeostasis and pathology in many species. The current method to measure cytokines in body fluids is reagent dependent, requiring highly specific paired antibodies.

METHODS

A liquid chromatography/multiple reaction monitoring mass spectrometry (LC/MRM-MS)-based approach was developed to simultaneously establish the limits of detection (LODs) and quantification (LOQs) for recombinant cytokines IL-1β, IL-6, IFNγ and TNFα as pure standards and in bovine sera. All experimental LC/MRM-MS data are available at CSIRO Data Access Portal repository under identifier doi.org/10.25919/5de8a0232a862.

RESULTS

The present method enabled LODs and LOQs as low as 1.05 and 1.12 fmol/μL in the experiment comprised of pure standards. Comparable results were obtained in the experiment where digested cytokines were mixed with pre-digested sera proteins. The intrinsic matrix effects were evident when intact cytokines were co-digested within undiluted and undigested sera decreasing the ability to detect and quantify cytokines by 10,000-fold compared with pure standards and pre-digested sera.

CONCLUSIONS

The developed LC/MRM-MS method provided insights into the difficulties in detecting the target peptides when embedded in complex matrices. Nonetheless, the method may potentially be readily applied in biomarker-focused research interrogating fluids of lesser complexity such as synovial fluid, cerebrospinal fluid and tissue culture media.