Plasma glycoproteomics delivers high-specificity disease biomarkers by detecting site-specific glycosylation abnormalities.

INTRODUCTION: The human plasma glycoproteome holds enormous potential to identify personalized biomarkers for diagnostics. Glycoproteomics has matured into a technology for plasma N-glycoproteome analysis but further evolution towards clinical applications depends on the clinical validity and understanding of protein- and site-specific glycosylation changes in disease. OBJECTIVES: Here, we exploited the uniqueness of a patient cohort of genetic defects in well-defined glycosylation pathways to assess the clinical applicability of plasma N-glycoproteomics. METHODS: Comparative glycoproteomics was performed of blood plasma from 40 controls and 74 patients with 13 different genetic diseases that impact the protein N-glycosylation pathway. Baseline glycosylation in healthy individuals was compared to reference glycome and intact transferrin protein mass spectrometry data. Use of glycoproteomics data for biomarker discovery and sample stratification was evaluated by multivariate chemometrics and supervised machine learning. Clinical relevance of site-specific glycosylation changes were evaluated in the context of genetic defects that lead to distinct accumulation or loss of specific glycans. Integrated analysis of site-specific glycoproteome changes in disease was performed using chord diagrams and correlated with intact transferrin protein mass spectrometry data. RESULTS: Glycoproteomics identified 191 unique glycoforms from 58 unique peptide sequences of 34 plasma glycoproteins that span over 3 magnitudes of abundance in plasma. Chemometrics identified high-specificity biomarker signatures for each of the individual genetic defects with better stratification performance than the current diagnostic standard method. Bioinformatic analyses revealed site-specific glycosylation differences that could be explained by underlying glycobiology and protein-intrinsic factors. CONCLUSION: Our work illustrates the strong potential of plasma glycoproteomics to significantly increase specificity of glycoprotein biomarkers with direct insights in site-specific glycosylation changes to better understand the glycobiological mechanisms underlying human disease.

Quantification of 782 Plasma Peptides by Multiplexed Targeted Proteomics.

Blood analysis is one of the foundations of clinical diagnostics. In recent years, the analysis of proteins in blood samples by mass spectrometry has taken a jump forward in terms of sensitivity and the number of identified proteins. The recent development of parallel reaction monitoring with parallel accumulation and serial fragmentation (prm-PASEF) combines ion mobility as an additional separation dimension. This increases the proteome coverage while allowing the use of shorter chromatographic gradients. To demonstrate the method's full potential, we used an isotope-labeled synthetic peptide mix of 782 peptides, derived from 579 plasma proteins, spiked into blood plasma samples with a prm-PASEF measurement allowing the quantification of 565 plasma proteins by targeted proteomics. As a less time-consuming alternative to the prm-PASEF method, we describe guided data independent acquisition (dia)-PASEF (g-dia-PASEF) and compare its application to prm-PASEF for measuring blood plasma. To demonstrate both methods' performance in clinical samples, 20 patient plasma samples from a colorectal cancer (CRC) cohort were analyzed. The analysis identified 14 differentially regulated proteins between the CRC patient and control individual plasma samples. This shows the technique's potential for the rapid and unbiased screening of blood proteins, abolishing the need for the preselection of potential biomarker proteins.

Naive Pluripotent and Trophoblastic Stem Cell Lines as a Model for Detecting Missing Proteins in the Context of the Chromosome-Centric Human Proteome Project.

The Chromosome-centric Human Proteome Project (C-HPP) aims at identifying the proteins as gene products encoded by the human genome, characterizing their isoforms and functions. The existence of products has now been confirmed for 93.2% of the genes at the protein level. The remaining mostly correspond to proteins of low abundance or difficult to access. Over the past years, we have significantly contributed to the identification of missing proteins in the human spermatozoa. We pursue our search in the reproductive sphere with a focus on early human embryonic development. Pluripotent cells, developing into the fetus, and trophoblast cells, giving rise to the placenta, emerge during the first weeks. This emergence is a focus of scientists working in the field of reproduction, placentation and regenerative medicine. Most knowledge has been harnessed by transcriptomic analysis. Interestingly, some genes are uniquely expressed in those cells, giving the opportunity to uncover new proteins that might play a crucial role in setting up the molecular events underlying early embryonic development. Here, we analyzed naive pluripotent and trophoblastic stem cells and discovered 4 new missing proteins, thus contributing to the C-HPP. The mass spectrometry proteomics data was deposited on ProteomeXchange under the data set identifier PXD035768.

The Parallel Reaction Monitoring-Parallel Accumulation-Serial Fragmentation (prm-PASEF) Approach for Multiplexed Absolute Quantitation of Proteins in Human Plasma.

Mass spectrometry (MS)-based quantitative proteomic methods have become some of the major tools for protein biomarker discovery and validation. The recently developed parallel reaction monitoring-parallel accumulation-serial fragmentation (prm-PASEF) approach on a Bruker timsTOF Pro mass spectrometer allows the addition of ion mobility as a new dimension to LC-MS-based proteomics and increases proteome coverage at a reduced analysis time. In this study, a prm-PASEF approach was used for the multiplexed absolute quantitation of proteins in human plasma using isotope-labeled peptide standards for 125 plasma proteins, over a broad (104-106) dynamic range. Optimization of LC and MS parameters, such as accumulation time and collision energy, resulted in improved sensitivity for more than half of the targets (73 out of 125 peptides) by increasing the signal-to-noise ratio by a factor of up to 10. Overall, 41 peptides showed up to a 2-fold increase in sensitivity, 25 peptides showed up to a 5-fold increase in sensitivity, and 7 peptides showed up to a 10-fold increase in sensitivity. Implementation of the prm-PASEF method allowed absolute protein quantitation (down to 1.13 fmol) in human plasma samples. A comparison of the concentration values of plasma proteins determined by MRM on a QTRAP instrument and by prm-PASEF on a timsTOF Pro revealed an excellent correlation (R2 = 0.97) with a slope of close to 1 (0.99), demonstrating that prm-PASEF is well suited for "absolute" quantitative proteomics.

Highly Multiplexed Targeted Proteomics Acquisition on a TIMS-QTOF.

Targeted proteomics allows the highly sensitive detection of specific peptides and proteins in complex biological samples. Here, we describe a methodology for targeted peptide quantification using a trapped ion mobility quadrupole time-of-flight mass spectrometer (timsTOF Pro). The prm-PASEF method exploits the multiplexing capability provided by the trapped ion mobility separation, allowing more than 200 peptides to be monitored over a 30 min liquid chromatography separation. Compared to conventional parallel reaction monitoring (PRM), precursor ions are accumulated in the trapped ion mobility spectrometry (TIMS) cells and separated according to their shape and charge before eluting into the quadrupole time-of-flight (QTOF) part of the mass spectrometer. The ion mobility trap allows measuring up to six peptides from a single 100 ms ion mobility separation with the current setup. Using these improved mass spectrometric capabilities, we detected and quantified 216 isotope-labeled synthetic peptides (AQUA peptides) spiked in HeLa human cell extract with limits of quantification of 17.2 amol for some peptides. The acquisition method is highly reproducible between injections and enables accurate quantification in biological samples, as demonstrated by quantifying KRas, NRas, and HRas as well as several Ras mutations in lung and colon cancer cell lines on fast 10 min gradient separations.

Identification of multiple proteoforms biomarkers on clinical samples by routine Top-Down approaches.

Top-Down approaches have an extremely high biological relevance, especially when it comes to biomarker discovery, but the necessary pre-fractionation constraints are not easily compatible with the robustness requirements and the size of clinical sample cohorts. We have demonstrated that intact protein profiling studies could be run on UHR-Q-ToF with limited pre-fractionation (Schmit et al., 2017) [1]. The dataset presented herein is an extension of this research. Proteoforms known to play a role in the pathophysiology process of Alzheimer's disease were identified as candidate biomarkers. In this article, mass spectrometry performance of these candidates are demonstrated.

Towards a routine application of Top-Down approaches for label-free discovery workflows.

Thanks to proteomics investigations, our vision of the role of different protein isoforms in the pathophysiology of diseases has largely evolved. The idea that protein biomarkers like tau, amyloid peptides, ApoE, cystatin, or neurogranin are represented in body fluids as single species is obviously over-simplified, as most proteins are present in different isoforms and subjected to numerous processing and post-translational modifications. Measuring the intact mass of proteins by MS has the advantage to provide information on the presence and relative amount of the different proteoforms. Such Top-Down approaches typically require a high degree of sample pre-fractionation to allow the MS system to deliver optimal performance in terms of dynamic range, mass accuracy and resolution. In clinical studies, however, the requirements for pre-analytical robustness and sample size large enough for statistical power restrict the routine use of a high degree of sample pre-fractionation. In this study, we have investigated the capacities of current-generation Ultra-High Resolution Q-Tof systems to deal with high complexity intact protein samples and have evaluated the approach on a cohort of patients suffering from neurodegenerative disease. Statistical analysis has shown that several proteoforms can be used to distinguish Alzheimer disease patients from patients suffering from other neurodegenerative disease. SIGNIFICANCE: Top-down approaches have an extremely high biological relevance, especially when it comes to biomarker discovery, but the necessary pre-fractionation constraints are not easily compatible with the robustness requirements and the size of clinical sample cohorts. We have demonstrated that intact protein profiling studies could be run on UHR-Q-ToF with limited pre-fractionation. The proteoforms that have been identified as candidate biomarkers in the-proof-of concept study are derived from proteins known to play a role in the pathophysiology process of Alzheimer disease.

Identification of a variety of Staphylococcus species by matrix-assisted laser desorption ionization-time of flight mass spectrometry.

Whole-cell fingerprinting by matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) in combination with a dedicated bioinformatic software tool (MALDI Biotyper 2.0) was used to identify 152 staphylococcal strains corresponding to 22 staphylococcal species. Spectra of the 152 isolates, previously identified at the species level using a sodA gene-based oligonucleotide array, were analyzed against the main spectra of 3,030 microorganisms. A total of 151 strains out of 152 (99.3%) were correctly identified at the species level; only one strain was identified at the genus level. The MALDI-TOF MS method revealed different clonal lineages of Staphylococcus epidermidis that were of either human or environmental origin, which suggests that the MALDI-TOF MS method could be useful in the profiling of staphylococcal strains. The topology of the dendrogram generated by the MALDI Biotyper 2.0 software from the spectra of 120 Staphylococcus reference strains (representing 36 species) was in general agreement with that inferred from the 16S rRNA gene-based analysis. Our findings indicate that the MALDI-TOF MS technology, associated with a broad-spectrum reference database, is an effective tool for the swift and reliable identification of Staphylococci.

Identification of Streptococcus agalactiae isolates from various phylogenetic lineages by matrix-assisted laser desorption ionization-time of flight mass spectrometry.

Variations in proteins related to bacterial diversity may affect species identification performed using matrix-assisted laser desorption ionization (MALDI)-time of flight mass spectrometry. Using this method, we identified 110 Streptococcus agalactiae isolates characterized by serotyping and multilocus sequence typing. Serotype III and sequence type 23 strains expressed the widest variation in molecular weight of putative "species-identifying" biomarker ions. Recognition of the diversity of MALDI patterns observed in strains that represent all major intraspecies lineages assists in the constitution of an optimal reference database.

NMR measure of translational diffusion and fractal dimension. Application to molecular mass measurement.

Experimental NMR diffusion measure on polymers and on globular proteins are presented. These results, complemented with results found in the literature, enable a general description of effective fractal dimension for objects such as small organic molecules, sugars, polymers, DNA, and proteins. Results are compared to computational simulations as well as to theoretical values. A global picture of the diffusion phenomenon emerges from this description. A power law relating molecular mass with diffusion coefficients is described and found to be valid over 4 orders of magnitude. From this law, the fractal dimension of the molecular family can be measured, with experimental values ranging from 1.41 to 2.56 in full agreement with theoretical approaches. Finally, a method for evaluating the molecular mass of unknown solutes is described and implemented as a Web page.