Classifying patients in peritoneal dialysis by mass spectrometry-based profiling

Effect of Tryptic Digestion on Sensitivity and Specificity in MALDI-TOF-Based Molecular Diagnostics through Machine Learning

The digestion of protein into peptide fragments reduces the size and complexity of protein molecules. Peptide fragments can be analyzed with higher sensitivity (often > 102 fold) and resolution using MALDI-TOF mass spectrometers, leading to improved pattern recognition by common machine learning algorithms. In turn, enhanced sensitivity and specificity for bacterial sorting and/or disease diagnosis may be obtained. To test this hypothesis, four exemplar case studies have been pursued in which samples are sorted into dichotomous groups by machine learning (ML) software based on MALDI-TOF spectra. Samples were analyzed in 'intact' mode in which the proteins present in the sample were not digested with protease prior to MALDI-TOF analysis and separately after the standard overnight tryptic digestion of the same samples. For each case, sensitivity (sens), specificity (spc), and the Youdin index (J) were used to assess the ML model performance. The proteolytic digestion of samples prior to MALDI-TOF analysis substantially enhanced the sensitivity and specificity of dichotomous sorting. Two exceptions were when substantial differences in chemical composition between the samples were present and, in such cases, both 'intact' and 'digested' protocols performed similarly. The results suggest proteolytic digestion prior to analysis can improve sorting in MALDI/ML-based workflows and may enable improved biomarker discovery. However, when samples are easily distinguishable protein digestion is not necessary to obtain useful diagnostic results.

Plasma and serum exosome markers analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry coupled with electron multiplier

Although matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a simple, rapid, and high-throughput assay, its microchannel plate (MCP) detector is limited by the low sensitivity and ion saturation effect when analyzing macromolecules. Herein, we introduced a strategy that combined MALDI-TOF MS with electron multiplier (EM) for the direct analysis of exosomal proteins isolated from human plasma and serum. The results demonstrated that EM yielded a higher sensitivity than MCP detector in high-mass range (m/z 5000-100000). Through the analysis of MALDI-TOF MS coupled with EM, chemokine (C-X-C motif) ligand 12 (CXCL12) ion at m/z 7960 and its degradation products at m/z 7927, 7587, and 7553 were identified as characteristic exosomal proteins in plasma. CXCL4 ion at m/z 7765 was identified as a characteristic protein in serum exosomes. Additionally, the peak intensity of CXCL12 and CXCL4 standards exhibited great linear relationship (CXCL12, R² = 0.989; CXCL4, R² = 0.986) with the concentrations (ranging from 0.1 to 20 μg/mL) when using EM as detector. In conjunction with ultrasonic assisted matrix coating technology (UAMCT), this assay repeatability in our lab has been excellent with coefficient of variation (CV%) of 4.6% for CXCL12 and 9.3% for CXCL4. Finally, the spectra demonstrated that the intensity of exosome related peaks was significantly enhanced in plasma and serum of patients with Parkinson's disease (PD) (m/z 7553, P < 0.01; m/z 7587, P < 0.01; m/z 7927, P < 0.001; m/z 7980, P < 0.001; m/z 7765, P < 0.01), Alzheimer's disease (AD) (m/z 7553, P < 0.001; m/z 7587, P < 0.001; m/z 7927, P < 0.001; m/z 7980, P < 0.001), and ischemic cerebrovascular disease (ICD) (m/z 7553, P < 0.05; m/z 7587, P < 0.05; m/z 7927, P < 0.01; m/z 7980, P < 0.05; m/z 7765, P < 0.05) compared to that in healthy persons. The fingerprint information of CXCL12 in plasma exosomes has better clinical relevance than serum exosome CXCL4 in MALDI-TOF MS analysis.

Fast saccharide mapping method for quality consistency evaluation of commercial xylooligosaccharides collected in China

Due to the extensive use of xylooligosaccharides (XOS) as functional food ingredients, many inferior goods and even adulterants are generally found in the market, which may pose a health hazard to certain populations. Chromatography method such as high-performance liquid chromatography (HPLC) and high-performance thin-layer chromatography (HPTLC) is traditionally applied for the quality analysis of XOS. However, it is time consuming due to the prolonged separation and pre- or post- derivatization procedure. In this study, a fast saccharide mapping method based on matrix-assisted laser desorption/time-of-flight mass spectrometry (MALDI-TOF-MS) was developed for the quality consistency analysis of 22 batches of XOS collected from different manufacturers in China. The time needed for saccharides analysis using MALDI-MS was less than 30 min for one plate, at least 6 times faster than that by the traditional HPTLC chromatography method. In addition, MALDI-MS possessed higher resolution for XOS with DP4-DP7 based on the difference of m/z, which is hardly separated using HPTLC. The results showed that XOS were present only in samples XY01-XY11, samples XY12-XY14 only consisted of hex oligosaccharides, and samples XY15-XY22 were free of oligosaccharides. These indicate that the quality consistency of XOS products in the China market was poor, which should be carefully investigated.

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Fast saccharide mapping method was developed based on MADLI-TOF-MS.

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Quality consistency of commercial xylooligosaccharides collected in China was evaluated.

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Glycosidic linkage analysis was also used for identification of xylooligosaccharides.

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Fifty percent of commercial xylooligosaccharides are mislabeled.

Proteomic Research in Peritoneal Dialysis

Peritoneal dialysis (PD) is an established home care, cost-effective renal replacement therapy (RRT), which offers several advantages over the most used dialysis modality, hemodialysis. Despite its potential benefits, however, PD is an under-prescribed method of treating uremic patients. Infectious complications (primarily peritonitis) and bio-incompatibility of PD solutions are the main contributors to PD drop-out, due to their potential for altering the functional and anatomical integrity of the peritoneal membrane. To improve the clinical outcome of PD, there is a need for biomarkers to identify patients at risk of PD-related complications and to guide personalized interventions. Several recent studies have shown that proteomic investigation may be a powerful tool in the prediction, early diagnosis, prognostic assessment, and therapeutic monitoring of patients on PD. Indeed, analysis of the proteome present in PD effluent has uncovered several proteins involved in inflammation and pro-fibrotic insult, in encapsulating peritoneal sclerosis, or even in detecting early changes before any measurable modifications occur in the traditional clinical parameters used to evaluate PD efficacy. We here review the proteomic studies conducted thus far, addressing the potential use of such omics methodology in identifying potential new biomarkers of the peritoneal membrane welfare in relation to dialytic prescription and adequacy.

Vibrational Spectroscopy of Peritoneal Dialysis Effluent for Rapid Assessment of Patient Characteristics

Peritoneal dialysis (PD) offers specific advantages over hemodialysis, enabling increased autonomy of patients with end-stage renal disease, but PD-related complications need to be detected in a timely manner. Fourier transform infrared (FTIR) spectroscopy could provide rapid and essential insights into the patients' risk profiles via molecular fingerprinting of PD effluent, an abundant waste material that is rich in biological information. In this study, we measured FTIR spectroscopic profiles in PD effluent from patients taking part in a randomized controlled trial of alanyl-glutamine addition to the PD-fluid. Principal component analysis of FTIR spectra enabled us to differentiate between effluent samples from patients immediately after completion of instillation of the PD-fluid into the patients' cavity and 4 h later as well as between patients receiving PD-fluid supplemented with 8 mM alanyl-glutamine compared with control. Moreover, feasibility of FTIR spectroscopy coupled to supervised classification algorithms to predict patient-, PD-, as well as immune-associated parameters were investigated. PD modality (manual continuous ambulatory PD (CAPD) vs. cycler-assisted automated PD (APD)), residual urine output, ultrafiltration, transport parameters, and cytokine concentrations showed high predictive potential. This study provides proof-of-principle that molecular signatures determined by FTIR spectroscopy of PD effluent, combined with machine learning, are suitable for cost-effective, high-throughput diagnostic purposes in PD.

S2P: A software tool to quickly carry out reproducible biomedical research projects involving 2D-gel and MALDI-TOF MS protein data

BACKGROUND AND OBJECTIVE

2D-gel electrophoresis is widely used in combination with MALDI-TOF mass spectrometry in order to analyze the proteome of biological samples. For instance, it can be used to discover proteins that are differentially expressed between two groups (e.g. two disease conditions, case vs. control, etc.) thus obtaining a set of potential biomarkers. This procedure requires a great deal of data processing in order to prepare data for analysis or to merge and integrate data from different sources. This kind of work is usually done manually (e.g. copying and pasting data into spreadsheet files), which is highly time consuming and distracts the researcher from other important, core tasks. Moreover, engaging in a repetitive process in a non-automated, handling-based manner is prone to error, thus threatening reliability and reproducibility. The objective of this paper is to present S2P, an open source software to overcome these drawbacks.

METHODS

S2P is implemented in Java on top of the AIBench framework, and relies on well-established open source libraries to accomplish different tasks.

RESULTS

S2P is an AIBench based desktop multiplatform application, specifically aimed to process 2D-gel and MALDI-mass spectrometry protein identification-based data in a computer-aided, reproducible manner. Different case studies are presented in order to show the usefulness of S2P.

CONCLUSIONS

S2P is open source and free to all users at http://www.sing-group.org/s2p. Through its user-friendly GUI interface, S2P dramatically reduces the time that researchers need to invest in order to prepare data for analysis.

Themis: Batch Preprocessing for Ultrahigh-Resolution Mass Spectra of Complex Mixtures

Fourier transform ion cyclotron resonance mass spectrometry affords the resolving power to determine an unprecedented number of components in complex mixtures, such as petroleum. The software tools required to also analyze these data struggle to keep pace with advancing instrument capabilities and increasing quantities of data, particularly in terms of combining information efficiently across multiple replicates. Improved confidence in data and the use of replicates is particularly important where strategic decisions will be based upon the analysis. We present a new algorithm named Themis, developed using R, to jointly preprocess replicate measurements of a sample with the aim of improving consistency as a preliminary step to assigning peaks to chemical compositions. The main features of the algorithm are quality control criteria to detect failed runs, ensuring comparable magnitudes across replicates, peak alignment, and the use of an adaptive mixture model-based strategy to help distinguish true peaks from noise. The algorithm outputs a list of peaks reliably observed across replicates and facilitates data handling by preprocessing all replicates in a single step. The processed data produced by our algorithm can subsequently be analyzed by use of relevant specialized software. While Themis has been demonstrated with petroleum as an example of a complex mixture, its basic framework will be useful for complex samples arising from a variety of other applications.