Mitochondrial dysfunction governs immunometabolism in leukocytes of patients with acute-on-chronic liver failure.

BACKGROUND & AIMS: Patients with acute-on-chronic liver failure (ACLF) present a systemic hyperinflammatory response associated with increased circulating levels of small-molecule metabolites. To investigate whether these alterations reflect inadequate cell energy output, we assessed mitochondrial morphology and central metabolic pathways with emphasis on the tricarboxylic acid (TCA) cycle in peripheral leukocytes from patients with acutely decompensated (AD) cirrhosis, with and without ACLF. METHODS: The study included samples from patients with AD cirrhosis (108 without and 128 with ACLF) and 41 healthy individuals. Leukocyte mitochondrial ultrastructure was visualized by transmission electron microscopy and cytosolic and mitochondrial metabolic fluxes were determined by assessing NADH/FADH2 production from various substrates. Plasma GDF15 and FGF21 were determined by Luminex and acylcarnitines by LC-MS/MS. Gene expression was analyzed by RNA-sequencing and PCR-based glucose metabolism profiler array. RESULTS: Mitochondrial ultrastructure in patients with advanced cirrhosis was distinguished by cristae rarefication and swelling. The number of mitochondria per leukocyte was higher in patients, accompanied by a reduction in their size. Increased FGF21 and C6:0- and C8:0-carnitine predicted mortality whereas GDF15 strongly correlated with a gene set signature related to leukocyte activation. Metabolic flux analyses revealed increased energy production in mononuclear leukocytes from patients with preferential involvement of extra-mitochondrial pathways, supported by upregulated expression of genes encoding enzymes of the glycolytic and pentose phosphate pathways. In patients with ACLF, mitochondrial function analysis uncovered break-points in the TCA cycle at the isocitrate dehydrogenase and succinate dehydrogenase level, which were bridged by anaplerotic reactions involving glutaminolysis and nucleoside metabolism. CONCLUSIONS: Our findings provide evidence at the cellular, organelle and biochemical levels that severe mitochondrial dysfunction governs immunometabolism in leukocytes from patients with AD cirrhosis and ACLF. LAY SUMMARY: Patients at advanced stages of liver disease have dismal prognosis due to vital organ failures and the lack of treatment options. In this study, we report that the functioning of mitochondria, which are known as the cell powerhouse, is severely impaired in leukocytes of these patients, probably as a consequence of intense inflammation. Mitochondrial dysfunction is therefore a hallmark of advanced liver disease.

UPLC-TOF-MS Method for Simultaneous Quantification of Steroid Hormones in Tissue Homogenates of Zebrafish with Solid-Phase Extraction.

The quantification of steroid hormones of individual zebrafish (Danio rerio) provides perspective to understand endogenous hormone function. A UPLC-TOF-MS method was developed to provide a reproducible, sensitive, and efficient assay to determine the concentration of steroid hormones, including cortisol, testosterone, androstenedione, 11-deoxycortisol, 11-deoxycorticosterone, and 17-hydroxyprogesterone in whole-body homogenates of each zebrafish. Solid-phase extraction was used to sample matrix clean-up and acquired a recovery from 89.7% to 107.9%. The analytes were separated on an Aquity BEH C18 column using gradient elution. Mass spectrometric analysis was performed by single reaction monitoring (SRM) using positive electrospray ionization mode. The total running time was 6 min, which was greatly shortened compared with a previously reported method. The developed method exhibited excellent linearity for all the analytes, with regression coefficients higher than 0.99. The limit of detection varied between 0.1 and 0.5 ng/L and the limit of quantification was 0.5-1.7 ng/L for all analytes. The precision of the method was assessed on replicate measurements and was found to be in the ranges of 1.9 % to 6.6% and 4.3% to 8.6%, for intra- and inter-day analysis, respectively. This method was validated according to FDA guidance and applied to determine steroid hormone levels in the tissue homogenate of zebrafish acutely treated with caffeine and ethanol.

Quantitative Proteome Data Analysis of Tandem Mass Tags Labeled Samples.

In mass spectrometry-based proteomics, relative quantitative approaches enable differential protein abundance analysis. Isobaric labeling strategies, such as tandem mass tags (TMT), provide simultaneous quantification of several samples (e.g., up to 16 using 16plex TMTpro) owing to its multiplexing capability. This technology improves sample throughput and thereby minimizes both measurement time and overall experimental variation. However, TMT-based MS data processing and statistical analysis are probably the crucial parts of this pipeline to obtain reliable, plausible, and significantly quantified results. Here, we provide a step-by-step guide to the analysis and evaluation of TMT quantitative proteomics data.

Toward Comprehensive Per- and Polyfluoroalkyl Substances Annotation Using FluoroMatch Software and Intelligent High-Resolution Tandem Mass Spectrometry Acquisition.

Thousands of per- and polyfluoroalkyl substances (PFAS) exist in the environment and pose a potential health hazard. Suspect and nontarget screening with liquid chromatography (LC)-high-resolution tandem mass spectrometry (HRMS/MS) can be used for comprehensive characterization of PFAS. To date, no automated open source PFAS data analysis software exists to mine these extensive data sets. We introduce FluoroMatch, which automates file conversion, chromatographic peak picking, blank feature filtering, PFAS annotation based on precursor and fragment masses, and annotation ranking. The software library currently contains ∼7 000 PFAS fragmentation patterns based on rules derived from standards and literature, and the software automates a process for users to add additional compounds. The use of intelligent data-acquisition methods (iterative exclusion) nearly doubled the number of annotations. The software application is demonstrated by characterizing PFAS in landfill leachate as well as in leachate foam generated to concentrate the compounds for remediation purposes. FluoroMatch had wide coverage, returning 27 PFAS annotations for landfill leachate samples, explaining 71% of the all-ion fragmentation (CF2)n related fragments. By improving the throughput and coverage of PFAS annotation, FluoroMatch will accelerate the discovery of PFAS posing significant human risk.

Mass Spectrometric Method for the Unambiguous Profiling of Cellular Dynamic Glycosylation.

Various biological processes at the cellular level are regulated by glycosylation which is a highly microheterogeneous post-translational modification (PTM) on proteins and lipids. The dynamic nature of glycosylation can be studied through metabolic incorporation of non-natural sugars into glycan epitopes and their detection using bio-orthogonal probes. However, this approach possesses a significant drawback due to nonspecific background reactions and ambiguity of non-natural sugar metabolism. Here, we report a probe-free strategy for their direct detection by glycoproteomics and glycomics using mass spectrometry (MS). The method dramatically simplifies the detection of non-natural functional group bearing monosaccharides installed through promiscuous sialic acid, N-acetyl-d-galactosamine (GalNAc) and N-acetyl-d-glucosamine (GlcNAc) biosynthetic pathways. Multistage enrichment of glycoproteins by cellular fractionation, subsequent ZIC-HILIC (zwitterionic-hydrophilic interaction chromatography) based glycopeptide enrichment, and a spectral enrichment algorithm for the MS data processing enabled direct detection of non-natural monosaccharides that are incorporated at low abundance on the N/O-glycopeptides along with their natural counterparts. Our approach allowed the detection of both natural and non-natural sugar bearing glycopeptides, N- and O-glycopeptides, differentiation of non-natural monosaccharide types on the glycans and also their incorporation efficiency through quantitation. Through this, we could deduce interconversion of monosaccharides during their processing through glycan salvage pathway and subsequent incorporation into glycan chains. The study of glycosylation dynamics through this method can be conducted in high throughput, as few sample processing steps are involved, enabling understanding of glycosylation dynamics under various external stimuli and thereby could bolster the use of metabolic glycan engineering in glycosylation functional studies.

Targeted toxicometabolomics of endosulfan sulfate in adult zebrafish (Danio rerio) using GC-MS/MS in multiple reaction monitoring mode.

Endosulfan sulfate is a major oxidative metabolite of the chlorinated insecticide endosulfan. In this study, a targeted metabolomics approach was used to investigate the toxic mechanisms of endosulfan sulfate in adult zebrafish using the multiple reaction monitoring mode of a GC-MS/MS. The LC50 of endosulfan sulfate in adult zebrafish was determined and then zebrafish were exposed to endosulfan sulfate at one-tenth the LC50 (0.1LC50) or the LC50 for 24 and 48 h. After exposure, the fish were extracted, derivatized and analyzed by GC-MS/MS for 379 metabolites to identify 170 metabolites. Three experimental groups (control, 0.1LC50 and LC50) were clearly separated in PLS-DA score plots. Based on the VIP, ANOVA, and fold change results, 40 metabolites were selected as biomarkers. Metabolic pathways associated with those metabolites were identified using MetaboAnalyst 4.0 as follows: aminoacyl-tRNA biosynthesis, valine/leucine/isoleucine biosynthesis, citrate cycle, glycerolipid metabolism, and arginine/proline metabolism. Gene expression studies confirmed the activation of citrate cycle and glycerolipids metabolism. MDA levels of the exposed group significantly increased in oxidative toxicity assay tests. Such significant perturbations of important metabolites within key biochemical pathways must result in biologically hazardous effects in zebrafish.

Sex-specific Estrogen Levels and Reference Intervals from Infancy to Late Adulthood Determined by LC-MS/MS.

CONTEXT: The lack of sensitive and robust analytical methods has hindered the reliable quantification of estrogen metabolites in subjects with low concentrations. OBJECTIVE: To establish sex-specific reference ranges for estrone (E1) and estradiol (E2) throughout life and to evaluate sex-differences using the state-of-the-art liquid chromatography tandem mass spectrometry (LC-MS/MS) method for quantification of E1, E2, and estriol (E3). DESIGN: LC-MS/MS method development and construction of estrogen reference ranges. SETTINGS: Population-based cross-sectional cohorts from the greater Copenhagen and Aarhus areas. PARTICIPANTS: Healthy participants aged 3 months to 61 years (n = 1838). RESULTS: An isotope diluted LC-MS/MS method was developed and validated for measurements of serum E1, E2, and E3. Limits of detections (LODs) were 3 pmol/L (E1), 4 pmol/L (E2), and 12 pmol/L (E3), respectively. This sensitive method made it possible to differentiate between male and female concentration levels of E1 and E2 in children. In girls, E2 levels ranged from

Proof of concept for identifying cystic fibrosis from perspiration samples.

The gold standard for cystic fibrosis (CF) diagnosis is the determination of chloride concentration in sweat. Current testing methodology takes up to 3 h to complete and has recognized shortcomings on its diagnostic accuracy. We present an alternative method for the identification of CF by combining desorption electrospray ionization mass spectrometry and a machine-learning algorithm based on gradient boosted decision trees to analyze perspiration samples. This process takes as little as 2 min, and we determined its accuracy to be 98 ± 2% by cross-validation on analyzing 277 perspiration samples. With the introduction of statistical bootstrap, our method can provide a confidence estimate of our prediction, which helps diagnosis decision-making. We also identified important peaks by the feature selection algorithm and assigned the chemical structure of the metabolites by high-resolution and/or tandem mass spectrometry. We inspected the correlation between mild and severe CFTR gene mutation types and lipid profiles, suggesting a possible way to realize personalized medicine with this noninvasive, fast, and accurate method.

Enhancing Metabolome Coverage in Data-Dependent LC-MS/MS Analysis through an Integrated Feature Extraction Strategy.

In untargeted metabolomics, conventional data preprocessing software (e.g., XCMS, MZmine 2, MS-DIAL) are used extensively due to their high efficiency in metabolic feature extraction. However, these programs present limitations in recognizing low-abundance metabolic features, thus hindering complete metabolome coverage from the analysis. In this work, we explored the possibility of enhancing the metabolome coverage of data-dependent liquid chromatography-tandem mass spectrometry (LC-MS/MS) results by rescuing metabolic features that are missed by conventional software. To achieve this goal, we first categorized the metabolic features into four confidence levels based on their chromatographic peak shapes and the presence of corresponding MS/MS spectra. We then assessed the false positives and quantitative accuracy of the metabolic features that contain MS/MS spectra but are not recognized by conventional software. Our results indicate that these missed features contain valid and important metabolic information and should be integrated into the conventional metabolomics results. Thus, we developed a data-preprocessing pipeline to extract low-abundance metabolic features and integrate them with the results from conventional programs. This integrated feature extraction strategy was tested on a set of fecal metabolomic data retrieved from mice who have undergone normal diet vs high-fat diet treatments. In our test data set, the integrated feature extraction approach increased the number of significant features being extracted by 24.4% and identified five additional metabolites bearing critical biological meanings. Our results show that this integrated feature extraction strategy remarkably improves the metabolome coverage beyond that of conventional data preprocessing, therefore facilitating the confirmation of metabolites of interest and accomplishment of a higher success rate in de novo metabolite identification.

LC-MS/MS Software for Screening Unknown Erectile Dysfunction Drugs and Analogues: Artificial Neural Network Classification, Peak-Count Scoring, Simple Similarity Search, and Hybrid Similarity Search Algorithms.

Screening and identifying unknown erectile dysfunction (ED) drugs and analogues, which are often illicitly added to health supplements, is a challenging analytical task. The analytical technique most commonly used for this purpose, liquid chromatography-tandem mass spectrometry (LC-MS/MS), is based on the strategy of searching the LC-MS/MS spectra of target compounds against database spectra. However, such a strategy cannot be applied to unknown ED drugs and analogues. To overcome this dilemma, we have constructed a standalone software named AI-SIDA (artificial intelligence screener of illicit drugs and analogues). AI-SIDA consists of three layers: LC-MS/MS viewer, AI classifier, and Identifier. In the second AI classifier layer, an artificial neural network (ANN) classification model, which was constructed by training 149 LC-MS/MS spectra (including 27 sildenafil-type, 6 vardenafil-type, 11 tadalafil-type ED drugs/analogues and other 105 compounds), is included to classify the LC-MS/MS spectra of the query compound into four categories: i.e., sildenafil, vardenafil, and tadalafil families and non-ED compounds. This ANN model was found to show 100% classification accuracy for the 187 LC-MS/MS modeling and test data sets. In the third Identifier layer, three search algorithms (pick-count scoring, simple similarity search, and hybrid similarity search) are implemented. In particular, the hybrid similarity search was found to be very powerful in identifying unknown ED drugs/analogues with a single modification from the library ED drugs/analogues. Altogether, the AI-SIDA software provides a very useful and powerful platform for screening unknown ED drugs and analogues.

MS2-Deisotoper: A Tool for Deisotoping High-Resolution MS/MS Spectra in Normal and Heavy Isotope-Labelled Samples.

High-resolution MS/MS spectra of peptides can be deisotoped to identify monoisotopic masses of peptide fragments. The use of such masses should improve protein identification rates. However, deisotoping is not universally used and its benefits have not been fully explored. Here, MS2-Deisotoper, a tool for use prior to database search, is used to identify monoisotopic peaks in centroided MS/MS spectra. MS2-Deisotoper works by comparing the mass and relative intensity of each peptide fragment peak to every other peak of greater mass, and by applying a set of rules concerning mass and intensity differences. After comprehensive parameter optimization, it is shown that MS2-Deisotoper can improve the number of peptide spectrum matches (PSMs) identified by up to 8.2% and proteins by up to 2.8%. It is effective with SILAC and non-SILAC MS/MS data. The identification of unique peptide sequences is also improved, increasing the number of human proteoforms by 3.7%. Detailed investigation of results shows that deisotoping increases Mascot ion scores, improves FDR estimation for PSMs, and leads to greater protein sequence coverage. At a peptide level, it is found that the efficacy of deisotoping is affected by peptide mass and charge. MS2-Deisotoper can be used via a user interface or as a command-line tool.

Integration of targeted metabolite profiling and sequential optimization method for discovery of chemical marker combination to identify the closely-related plant species.

BACKGROUND: Quality control of herbal medicines based on characteristic components is an important trend. Although the plant metabolomics provide a powerful tool for species classification, the discovered marker is usually limited in practical application. For rapid discovery of efficient marker combination, we proposed a strategy integrating targeted metabolite profiling and sequential optimization method. METHODS: This strategy included: (1) directional enrichment and chemical profiling of targeted metabolites by matrix solid phase dispersion (MSPD) combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS). (2) Partial least squares discrimination analysis (PLS-DA)-based sequential screening of efficient marker combination was constructed for various species predictions. Five Lonicera species and their characteristic metabolites, sponins, were taken as a case study. RESULTS: A total of 19 saponins were identified, and 12 major and available saponins were enriched based on MSPD and quantified by LC-MS/MS in 5 Lonicera species flower buds. Followed by 3 runs of PLS-DA-based screening, a combination consisting of macranthoidin B, dipsacoside B and α-hederin was discovered as the effective chemical marker for 5 analogous Lonicera flower classification. CONCLUSION: Our study provides an effective and applicable approach to select the practical marker combination for the assessment of analogical herb medicines.

Updated MS²PIP web server delivers fast and accurate MS² peak intensity prediction for multiple fragmentation methods, instruments and labeling techniques.

MS²PIP is a data-driven tool that accurately predicts peak intensities for a given peptide's fragmentation mass spectrum. Since the release of the MS²PIP web server in 2015, we have brought significant updates to both the tool and the web server. In addition to the original models for CID and HCD fragmentation, we have added specialized models for the TripleTOF 5600+ mass spectrometer, for TMT-labeled peptides, for iTRAQ-labeled peptides, and for iTRAQ-labeled phosphopeptides. Because the fragmentation pattern is heavily altered in each of these cases, these additional models greatly improve the prediction accuracy for their corresponding data types. We have also substantially reduced the computational resources required to run MS²PIP, and have completely rebuilt the web server, which now allows predictions of up to 100 000 peptide sequences in a single request. The MS²PIP web server is freely available at https://iomics.ugent.be/ms2pip/.

TagGraph reveals vast protein modification landscapes from large tandem mass spectrometry datasets.

Although mass spectrometry is well suited to identifying thousands of potential protein post-translational modifications (PTMs), it has historically been biased towards just a few. To measure the entire set of PTMs across diverse proteomes, software must overcome the dual challenges of covering enormous search spaces and distinguishing correct from incorrect spectrum interpretations. Here, we describe TagGraph, a computational tool that overcomes both challenges with an unrestricted string-based search method that is as much as 350-fold faster than existing approaches, and a probabilistic validation model that we optimized for PTM assignments. We applied TagGraph to a published human proteomic dataset of 25 million mass spectra and tripled confident spectrum identifications compared to its original analysis. We identified thousands of modification types on almost 1 million sites in the proteome. We show alternative contexts for highly abundant yet understudied PTMs such as proline hydroxylation, and its unexpected association with cancer mutations. By enabling broad characterization of PTMs, TagGraph informs as to how their functions and regulation intersect.

Optimization and Comparison of Information-Dependent Acquisition (IDA) to Sequential Window Acquisition of All Theoretical Fragment Ion Spectra (SWATH) for High-Resolution Mass Spectrometry in Clinical Toxicology.

BACKGROUND: Untargeted data acquisition on high-resolution mass spectrometers (HRMSs) has been used in clinical toxicology for screening and identifying unknown compounds in patient samples. A common modality for untargeted HRMS data acquisition is information-dependent acquisition (IDA), which analyzes the most abundant small molecules within an acquisition cycle. This process can potentially lead to false negatives of clinically relevant compounds at low concentrations. Sequential window acquisition of all theoretical fragment ion spectra (SWATH) has emerged as a method of unbiased, untargeted HRMS data acquisition in which no spectral data are lost. SWATH has yet to be optimized and assessed for use in clinical toxicology. METHOD: We developed a variable-window SWATH method (vSWATH) and compared it to IDA by limit of detection studies in drug-supplemented urine (81 compounds) and against a retrospective cohort of 50 clinical urine samples characterized by LC-MS/MS. RESULTS: vSWATH had a lower limit of detection than IDA for 33 (41%) drugs and metabolites added into urine samples. Both IDA and vSWATH were equivalent in discovering compounds from clinical urine samples and confirmed 26 additional compounds not previously discovered by targeted LC-MS/MS. Lastly, the unbiased acquisition of spectra in vSWATH allowed for identification of 5 low-abundance compounds missed by IDA. CONCLUSIONS: This vSWATH method for clinical toxicology demonstrated equivalent analytical sensitivity and specificity for untargeted drug screening and identification in urine samples. vSWATH provided the additional benefit of collecting all tandem mass spectrometry spectra in a sample, which could be useful in discovering low-abundance compounds not discovered by IDA.

Extended diagnosis of purine and pyrimidine disorders from urine: LC MS/MS assay development and clinical validation.

BACKGROUND AND AIMS: Inborn errors of purine and pyrimidine metabolism are a diverse group of disorders with possible serious or life-threatening symptoms. They may be associated with neurological symptoms, renal stone disease or immunodeficiency. However, the clinical presentation can be nonspecific and mild so that a number of cases may be missed. Previously published assays lacked detection of certain diagnostically important biomarkers, including SAICAr, AICAr, beta-ureidoisobutyric acid, 2,8-dihydroxyadenine and orotidine, necessitating the use of separate assays for their detection. Moreover, the limited sensitivity for some analytes in earlier assays may have hampered the reliable detection of mild cases. Therefore, we aimed to develop a liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay that allows the simultaneous and sensitive detection of an extended range of purine and pyrimidine biomarkers in urine. METHODS: The assay was developed and validated using LC-MS/MS and clinically tested by analyzing ERNDIM Diagnostic Proficiency Testing (DPT) samples and further specimens from patients with various purine and pyrimidine disorders. RESULTS: Reliable determination of 27 analytes including SAICAr, AICAr, beta-ureidoisobutyric acid, 2,8-dihydroxyadenine and orotidine was achieved in urine following a simple sample preparation. The method clearly distinguished pathological and normal samples and differentiated between purine and pyrimidine defects in all clinical specimens. CONCLUSIONS: A LC-MS/MS assay allowing the simultaneous, sensitive and reliable diagnosis of an extended range of purine and pyrimidine disorders has been developed. The validated method has successfully been tested using ERNDIM Diagnostic Proficiency Testing (DPT) samples and further clinical specimens from patients with various purine and pyrimidine disorders. Sample preparation is simple and assay duration is short, facilitating an easier inclusion of the assay into the diagnostic procedures.

Targeted Metabolite Profiling-Based Identification of Antifungal 5-n-Alkylresorcinols Occurring in Different Cereals against Fusarium oxysporum.

A rapid and convenient biochemometrics-based analysis of several cereal-derived extracts was used to identify n-alkyl(enyl)resorcinols (AR) as antifungals against Fusarium oxysporum. Total AR content and liquid chromatography/mass spectrometry (LC-MS)-based profiles were recorded for each extract, in addition to their antifungal activity, to help integrate these chemical and biological datasets by orthogonal partial least squares regression. In this study, we developed and used a micro-scale amended medium (MSAM) assay to evaluate the in vitro mycelial growth inhibition at low amounts of extracts. Triticale husk-derived extracts had the highest AR content (662.1 µg olivetol equivalent/g dry extract), exhibiting >79% inhibition at the highest doses (10.0⁻1.0 µg/µL). Correlation of the chemical and antifungal datasets using supervised metabolite profiling revealed that 5-n-nonadecanylresorcinol, 5-n-heneicosylresorcinol, and 5-n-tricosyl-resorcinol were the most active ARs occurring in cereal products from Colombia. Hence, we propose the biochemometrics-based approach as a useful tool for identifying AR-like antifungals against F. oxysporum.

Advanced bioinformatics methods for practical applications in proteomics.

Mass spectrometry (MS)-based proteomics has undergone rapid advancements in recent years, creating challenging problems for bioinformatics. We focus on four aspects where bioinformatics plays a crucial role (and proteomics is needed for clinical application): peptide-spectra matching (PSM) based on the new data-independent acquisition (DIA) paradigm, resolving missing proteins (MPs), dealing with biological and technical heterogeneity in data and statistical feature selection (SFS). DIA is a brute-force strategy that provides greater width and depth but, because it indiscriminately captures spectra such that signal from multiple peptides is mixed, getting good PSMs is difficult. We consider two strategies: simplification of DIA spectra to pseudo-data-dependent acquisition spectra or, alternatively, brute-force search of each DIA spectra against known reference libraries. The MP problem arises when proteins are never (or inconsistently) detected by MS. When observed in at least one sample, imputation methods can be used to guess the approximate protein expression level. If never observed at all, network/protein complex-based contextualization provides an independent prediction platform. Data heterogeneity is a difficult problem with two dimensions: technical (batch effects), which should be removed, and biological (including demography and disease subpopulations), which should be retained. Simple normalization is seldom sufficient, while batch effect-correction algorithms may create errors. Batch effect-resistant normalization methods are a viable alternative. Finally, SFS is vital for practical applications. While many methods exist, there is no best method, and both upstream (e.g. normalization) and downstream processing (e.g. multiple-testing correction) are performance confounders. We also discuss signal detection when class effects are weak.

Optimization Workflow for the Analysis of Cross-Linked Peptides Using a Quadrupole Time-of-Flight Mass Spectrometer.

Cross-linking mass spectrometry is an emerging structural biology technique. Almost exclusively, the analyzer of choice for such an experiment has been the Orbitrap. We present an optimized protocol for the use of a Synapt G2-Si for the analysis of cross-linked peptides. We first tested six different energy ramps and analyzed the fragmentation behavior of cross-linked peptides identified by xQuest. By combining the most successful energy ramps, cross-link yield can be increased by up to 40%. When compared to previously published Orbitrap data, the Synapt G2-Si also offers improved fragmentation of the ß peptide. In order to improve cross-link quality control we have also developed ValidateXL, a programmatic solution that works with existing cross-linking software to improve cross-link quality control.

When results matter: reliable creatinine concentrations in hyperbilirubinemia patients.

Background Failure to report a creatinine concentration, especially in icteric patients who are eligible for a liver transplant, can result in a life-threatening situation. We assessed the influence of bilirubin interference on several creatinine assays and investigated ways to circumvent icteric interference without interfering with our normal automated sample logistics. Methods Using icteric patient sera (total bilirubin >255 µmol/L) we determined creatinine concentrations using an enzymatic and Jaffé assay (Roche Diagnostics) in both normal (i.e. undiluted) and decreased mode (i.e. diluted) as well as an enzyme-coupled amperometric assay on a Radiometer ABL837 FLEX analyzer. Creatinine concentrations from the five methods were compared with an in-house developed LC-MS/MS method. Passing and Bablok (proportional and constant bias) as well as difference plot parameters (bias and 95% limits of agreement [LoA]) were calculated. Interferograph-based regression analysis of the enzymatic and Jaffé results was used to investigate if such an approach could be used to report corrected creatinine concentrations in icteric patient sera. Results In icteric patient sera the enzyme-coupled amperometric assay was hardly influenced by icteric interference as shown by a difference plot bias of -1.5% (95% LoA -11.6 to +8.5%). The undiluted Jaffé method had a bias of -1.4% with a very broad 95% LoA (-35.1 to +32.2%) emphasizing the poor specificity of this method. The undiluted enzymatic method had the largest bias (-13.4%, 95% LoA -35.8 to +9.0%). Diluting sera in the enzymatic method did not improve the bias (-10.5%, 95% LoA -25.4 to 4.4%), while diluting the Jaffé method resulted in a bias increase (+11.4%, 95% LoA -14.7 to 37.5%). Using interferograph-based regression analysis we were able to reliably correct enzymatic creatinine concentrations in 97 out of 100 icteric patient sera. Conclusions Analytically, quantifying creatinine in icteric sera using the Radiometer ABL837 FLEX analyzer is the method of choice within our laboratory. However, not all laboratories are equipped with this method and even if available, the limited number of highly icteric patient sera makes this method costly. For those laboratories using the Roche enzymatic method, mathematically correcting an icteric creatinine concentration using an interferograph based on an LC-MS/MS reference method is a suitable alternative to report reliable creatinine results in icteric patients.