Protein identification by liquid chromatography-mass spectrometry using retention time prediction

Liquid chromatography has been coupled with mass spectrometry to improve the dynamic range and to reduce the complexity of sample introduced to the mass spectrometer at any given time. The chromatographic separation also provides information on the analytes, such as peptides in enzymatic digests of proteins; information that can be used when identifying the proteins by peptide mass fingerprinting. This paper discusses a recently introduced method based on retention time prediction to extract information from chromatographic separations and the applications of this method to protein identification in organisms with small and large genomes.     

HPLC Retention time prediction for metabolome analysi

Liquid Chromatography Time-of-Flight Mass Spectrometry (LC-TOF-MS) is widely used for profiling metabolite compounds. LC-TOF-MS is a chemical analysis technique that combines the physical separation capabilities of high-pressure liquid chromatography (HPLC) with the mass analysis capabilities of Time-of-Flight Mass Spectrometry (TOF-MS) which utilizes the difference in the flight time of ions due to difference in the mass-to-charge ratio. Since metabolite compounds have various chemical characteristics, their precise identification is a crucial problem of metabolomics research. Contemporaneously analyzed reference standards are commonly required for mass spectral matching and retention time matching, but there are far fewer reference standards than there are compounds in the organism. We therefore developed a retention time prediction method for HPLC to improve the accuracy of identification of metabolite compounds. This method uses a combination of Support Vector Regression and Multiple Linear Regression adaptively to the measured retention time. We achieved a strong correlation (correlation coefficient = 0.974) between measured and predicted retention times for our experimental data. We also demonstrated a successful identification of an E. coli metabolite compound that cannot be identified by precise mass alone.     

A transformer architecture for retention time prediction in liquid chromatography mass spectrometry-based proteomics

Accurate retention time (RT) prediction is important for spectral library-based analysis in data-independent acquisition mass spectrometry-based proteomics. The deep learning approach has demonstrated superior performance over traditional machine learning methods for this purpose. The transformer architecture is a recent development in deep learning that delivers state-of-the-art performance in many fields such as natural language processing, computer vision, and biology. We assess the performance of the transformer architecture for RT prediction using datasets from five deep learning models Prosit, DeepDIA, AutoRT, DeepPhospho, and AlphaPeptDeep. The experimental results on holdout datasets and independent datasets exhibit state-of-the-art performance of the transformer architecture. The software and evaluation datasets are publicly available for future development in the field.     

Retention time prediction using the model of liquid chromatography of biomacromolecules at critical conditions in LC‐MS phosphopeptide analysis

LC combined with MS/MS analysis of complex mixtures of protein digests is a reliable and sensitive method for characterization of protein phosphorylation. Peptide retention times (RTs) measured during an LC‐MS/MS run depend on both the peptide sequence and the location of modified amino acids. These RTs can be predicted using the LC of biomacromolecules at critical conditions model (BioLCCC). Comparing the observed RTs to those obtained from the BioLCCC model can provide additional validation of MS/MS‐based peptide identifications to reduce the false discovery rate and to improve the reliability of phosphoproteome profiling. In this study, energies of interaction between phosphorylated residues and the surface of RP separation media for both “classic” alkyl C18 and polar‐embedded C18 stationary phases were experimentally determined and included in the BioLCCC model extended for phosphopeptide analysis. The RTs for phosphorylated peptides and their nonphosphorylated analogs were predicted using the extended BioLCCC model and compared with their experimental RTs. The extended model was evaluated using literary data and a complex phosphoproteome data set distributed through the Association of Biomolecular Resource Facilities Proteome Informatics Research Group 2010 study. The reported results demonstrate the capability of the extended BioLCCC model to predict RTs which may lead to improved sensitivity and reliability of LC‐MS/MS‐based phosphoproteome profiling.     

Prediction of retention volumes and UV spectra of peptides in reversed phase HPLC

A method for calculating retention volumes of linear peptides with known primary structures and the values of their UV absorption at chosen wavelengths in reversed phase HPLC are described. These parameters are calculated for every peptide on the basis of the contributions of its amino acid residues determining its degree of retention and its UV spectrum. The contribution values are experimentally found from chromatograms of the free amino acids obtained by multiwavelength photometric detection under the conditions of the peptide chromatography. Thirty peptides have been chromatographed for the evaluation of the proposed method, and the correlation coefficients between the calculated and the experimental retention volumes have been found to be 0.95.     

Increased quantitative proteome coverage with (13)C/(12)C-based, acid-cleavable isotope-coded affinity tag reagent and modified data acquisition scheme

Quantitative protein profiling using the isotope-coded affinity tag (ICAT) method and tandem mass spectrometry (MS) enables the pair-wise comparison of protein expression levels in biological samples. A new version of the ICAT reagent with an acid-cleavable bond, which allows removal of the biotin moiety prior to MS and which utilizes (13)C substitution for (12)C in the heavy-ICAT reagent rather than (2)H (for (1)H) as in the original reagent, was investigated. We developed and validated an MS data acquisition strategy using this new reagent that results in an increased number of protein identifications per experiment, without losing the accuracy of protein quantification. This was achieved by following a single survey (precursor) ion scan and serial collision induced dissociations (CIDs) of four different precursor ions observed in the prior survey scan. This strategy is common to many high-performance liquid chromatography-electrospray ionization (HPLC-ESI)-MS shotgun proteomic strategies, but heretofore not to ICAT experiments. This advance is possible because the new ICAT reagent uses (13)C as the "heavy" element rather than (2)H, thus, eliminating the slight delay in retention time of ICAT-labeled "light" peptides on a C18-based HPLC separation that occurs with (2)H and (1)H. Analyses using this new scheme of an ICAT-labeled trypsin-digested six protein mixture as well as a tryptic digest of a total yeast lysate, indicated that about two times more proteins were identified in a single analysis, and that there was no loss in accuracy of quantification.     

A 3D Homochiral MOF [Cd2(d‐cam)3]•2Hdma•4dma for HPLC Chromatographic Enantioseparation

Up to now, some chiral metal‐organic frameworks (MOFs) have been reported for enantioseparation in liquid chromatography. Here we report a homochiral MOF, [Cd2(d‐cam)3]·2Hdma·4dma, used as a new chiral stationary phase for high‐performance liquid chromatographic enantioseparation. Nine racemates of alcohol, naphthol, ketone, and base compounds were used as analytes for evaluating the separation properties of the chiral MOF packed column. Moreover, some effects such as mobile phase composition, column temperature, and analytes mass for separations on this chiral column also were investigated. The relative standard deviations for the resolution values of run‐to‐run and column‐to‐column were less than 2.1% and 3.2%, respectively. The experimental results indicate that the homochiral MOF offered good recognition ability, which promotes the application of chiral MOFs use as stationary phase for enantioseparation. Chirality 28:340–346, 2016. © 2016 Wiley Periodicals, Inc.     

Preparation of a New Chiral Stationary Phase Based on Macrocyclic Amide Chiral Selector for the Liquid Chromatographic Chiral Separations

A new chiral stationary phase (CSP) based on macrocyclic amide receptor was prepared starting from (1R,2R)‐1,2‐diphenylethylenediamine. The new CSP was successfully applied to the resolution of various N‐(substituted benzoyl)‐α‐amino amides with reasonably good separation factors and resolutions (α = 1.75 ~ 2.97 and R_S = 2.89 ~ 6.82 for 16 analytes). The new CSP was also applied to the resolution of 3‐substituted 1,4‐benzodiazepin‐2‐ones and some diuretic chiral drugs including bendroflumethiazide and methylchlothiazide and metolazone. The resolution results for 3‐substituted 1,4‐benzodiazepin‐2‐ones and some diuretic chiral drugs were also reasonably good. Chirality 28:253–258, 2016. © 2016 Wiley Periodicals, Inc.     

Chromatographic enantioseparation by poly(biphenylylacetylene) derivatives with memory of both axial chirality and macromolecular helicity

Novel poly(biphenylylacetylene) derivatives bearing two acetyloxy groups at the 2‐ and 2′‐positions and an alkoxycarbonyl group at the 4′‐position of the biphenyl pendants (poly‐ Ac 's) were synthesized by the polymerization of the corresponding biphenylylacetylenes using a rhodium catalyst. The obtained stereoregular (cis ‐transoidal ) poly‐ Ac 's folded into a predominantly one‐handed helical conformation accompanied by a preferred‐handed axially twisted conformation of the biphenyl pendants through noncovalent interactions with a chiral alcohol and both the induced main‐chain helicity and the pendant axial chirality were maintained, that is, memorized, after complete removal of the chiral alcohol. The stability of the helicity memory of the poly‐ Ac 's in a solution was lower than that of the analogous poly(biphenylylacetylene)s bearing two methoxymethoxy groups at the 2‐ and 2′‐positions of the biphenyl pendants (poly‐ MOM 's). In the solid state, however, the helicity memory of the poly‐ Ac 's was much more stable and showed a better chiral recognition ability toward several racemates than that of the previously reported poly‐ MOM when used as a chiral stationary phase for high‐performance liquid chromatography. In particular, the poly‐ Ac ‐based CSP with a helicity memory efficiently separated racemic benzoin derivatives into enantiomers.     

Building blocks for the synthesis of post‐translationally modified glycated peptides and proteins

Growing interest in synthetic peptides carrying post‐traslational modifications, in general, and the Amadori modification in particular, raises the need for specific building blocks that can be used in stepwise peptide synthesis. Herein, we report the synthesis of N^α‐Fmoc‐Lys‐OH derivatives containing N^ε‐1‐deoxyfructopyranosyl moiety. Copyright © 2008 European Peptide Society and John Wiley & Sons, Ltd.     

Removal of Triosephosphate,Isomerase from Albumins

Commercial serum albumin and ovalbumin from a variety of sources contain triosephosphate isomerase activity which can interfere with many enzyme assays and metabolic studies. A simple procedure is described for the removal of this contaminant by preparative electrophoresis or electrofocus-ing.     

Accurate retention time determination of co‐eluting proteins in analytical chromatography by means of spectral data

Chromatography is the method of choice for the separation of proteins, at both analytical and preparative scale. Orthogonal purification strategies for industrial use can easily be implemented by combining different modes of adsorption. Nevertheless, with flexibility comes the freedom of choice and optimal conditions for consecutive steps need to be identified in a robust and reproducible fashion. One way to address this issue is the use of mathematical models that allow for an in silico process optimization. Although this has been shown to work, model parameter estimation for complex feedstocks becomes the bottleneck in process development. An integral part of parameter assessment is the accurate measurement of retention times in a series of isocratic or gradient elution experiments. As high‐resolution analytics that can differentiate between proteins are often not readily available, pure protein is mandatory for parameter determination. In this work, we present an approach that has the potential to solve this problem. Based on the uniqueness of UV absorption spectra of proteins, we were able to accurately measure retention times in systems of up to four co‐eluting compounds. The presented approach is calibration‐free, meaning that prior knowledge of pure component absorption spectra is not required. Actually, pure protein spectra can be determined from co‐eluting proteins as part of the methodology. The approach was tested for size‐exclusion chromatograms of 38 mixtures of co‐eluting proteins. Retention times were determined with an average error of 0.6 s (1.6% of average peak width), approximated and measured pure component spectra showed an average coefficient of correlation of 0.992. Biotechnol. Bioeng. 2013; 110: 683–693. © 2012 Wiley Periodicals, Inc.     

A comparison of the beta-geometric model with landmarking for dynamic prediction of time to pregnancy

We conducted a simulation study to compare two methods that have been recently used in clinical literature for the dynamic prediction of time to pregnancy. The first is landmarking, a semi-parametric method where predictions are updated as time progresses using the patient subset still at risk at that time point. The second is the beta-geometric model that updates predictions over time from a parametric model estimated on all data and is specific to applications with a discrete time to event outcome. The beta-geometric model introduces unobserved heterogeneity by modelling the chance of an event per discrete time unit according to a beta distribution. Due to selection of patients with lower chances as time progresses, the predicted probability of an event decreases over time. Both methods were recently used to develop models predicting the chance to conceive naturally. The advantages, disadvantages and accuracy of these two methods are unknown. We simulated time-to-pregnancy data according to different scenarios. We then compared the two methods by the following out-of-sample metrics: bias and root mean squared error in the average prediction, root mean squared error in individual predictions, Brier score and c statistic. We consider different scenarios including data-generating mechanisms for which the models are misspecified. We applied the two methods on a clinical dataset comprising 4999 couples. Finally, we discuss the pros and cons of the two methods based on our results and present recommendations for use of either of the methods in different settings and (effective) sample sizes.     

General method for selective labelling of double‐chain cysteine‐rich peptides with a lanthanide chelate via solid‐phase synthesis

The use of lanthanides in preference to radioisotopes as probes for various biological assays has gained enormous popularity. The introduction of lanthanide chelates to peptides/proteins can be carried out either in solution using a commercially available labelling kit or by solid‐phase peptide synthesis using an appropriate lanthanide chelate. Herein, a detailed protocol for the latter is provided for the labelling of peptides or small proteins with diethylenetriamine‐N, N, N″, N″‐tetra‐tert‐butyl acetate‐N′‐acetic acid (DTPA) chelate or other similar chelates on a solid support using a chimeric insulin‐like peptide composed of human insulin‐like peptide 5 (INSL5) A‐chain and relaxin‐3 B‐chain as a model peptide. Copyright © 2011 European Peptide Society and John Wiley & Sons, Ltd.     

Development of an LC‐MS method for simultaneous quantitation of amentoflavone and biapigenin,the minor and major biflavones from Hypericum perforatum L., in human plasma and its application to real blood

Introduction – Biflavones of Hypericum perforatum L. are bioactive compounds used in the treatment of inflammation and depression. Determination of amentoflavone and biapigenin from blood is challenging owing to their similar structures and low concentrations. Objective – To develop a rapid, sensitive and accurate method based on liquid‐phase extraction followed by high‐performance liquid chromatography and electrospray ionisation mass spectrometry (HPLC‐ESI‐MS) for quantification of biflavones in human plasma. Methodology – After extraction from blood, the analytes were subjected to HPLC with an XTerra® MS C₁₈ column and a binary mobile phase consisting of 2% formic acid in water and acetonitrile under isocratic elution conditions, with ESI‐MS detection in the negative ion mode and multiple reaction monitoring (MRM). Results – Both calibration curves showed good linearity within the concentration range 1–500 ng/mL. Limits of detection (S/N = 3) were 0.1 ng for pure substances and the limits of quantitation (S/N = 5) were 1.0 ng/mL from analyte‐spiked serum. The grand mean recovery was 90% from several subsamples of each biflavone. The imprecision (RSD) of peak areas was between 5% (intraday) and 10% (interday) for high concentrations (250 ng/mL) and between 10% (intraday) and 15% (interday) for low concentrations (1 ng/mL). Inaccuracy of the mean was less than 20% at the lower limit of quantitation. Conclusion – The developed and validated method for determination of biflavones from human plasma was effectively applied to pharmacokinetic studies of 13 probands and preliminary results indicate biphasic concentration–time curves. Copyright © 2010 John Wiley & Sons, Ltd.     

Metabolite changes during the life history of Porphyra haitanensis

Plant metabolomics is essentially the comprehensive analysis of complex metabolites of plant extracts. Metabolic fingerprinting is an important part of plant metabolomics research. In this study, metabolic fingerprinting of different stages of the life history of the red alga Porphyra haitanensis was performed. The stages included conchocelis filaments, sporangial branchlets, conchosporangia, discharged conchospores and conchosporangial branchlets after conchospore discharge. Metabolite extracts were analysed with ultra‐performance liquid chromatography coupled with electrospray ionisation quadrupole‐time of flight mass spectrometry. Analyses profiles were subjected to principal components analysis and orthogonal projection to latent structures discriminant analysis using the SIMCA‐P software for biomarker selection and identification. Based on the MS/MS spectra and data from the literature, potential biomarkers, mainly of phosphatidylcholine and lysophosphatidylcholine, were identified. Identification of these biomarkers suggested that plasma membrane phospholipids underwent major changes during the life history of P. haitanensis. The levels of phosphatidylcholine and lysophosphatidylcholine increased in sporangial branchlets and decreased in discharged conchospores. Moreover, levels of sphingaine (d18:0) decreased in sporangial branchlets and increased in discharged conchospores, which indicates that membrane lipids were increasingly synthesised as energy storage in sporangial branchlets, while energy was consumed in sporangial branchlets to discharged conchospores. A metabolomic study of different growth phases of P. haitanensis will enhance our understanding of its physiology and ecology.     

MMS2plot: An R Package for Visualizing Multiple MS/MS Spectra for Groups of Modified and Non‐Modified Peptides

A large number of post‐translational modifications (PTMs) in proteins are buried in the unassigned mass spectrometric (MS) spectra in shot‐gun proteomics datasets. Because the modified peptide fragments are low in abundance relative to the corresponding non‐modified versions, it is critical to develop tools that allow facile evaluation of assignment of PTMs based on the MS/MS spectra. Such tools will preferably have the ability to allow comparison of fragment ion spectra and retention time between the modified and unmodified peptide pairs or group. Herein, MMS2plot, an R package for visualizing peptide‐spectrum matches (PSMs) for multiple peptides, is described. MMS2plot features a batch mode and generates the output images in vector graphics file format that facilitate evaluation and publication of the PSM assignment. MMS2plot is expected to play an important role in PTM discovery from large‐scale proteomics datasets generated by liquid chromatography‐MS/MS. The MMS2plot package is freely available at https://github.com/lileir/MMS2plot under the GPL‐3 license.     

QCMAP: An Interactive Web‐Tool for Performance Diagnosis and Prediction of LC‐MS Systems

The increasing role played by liquid chromatography‐mass spectrometry (LC‐MS)‐based proteomics in biological discovery has led to a growing need for quality control (QC) on the LC‐MS systems. While numerous quality control tools have been developed to track the performance of LC‐MS systems based on a pre‐defined set of performance factors (e.g., mass error, retention time), the precise influence and contribution of the performance factors and their generalization property to different biological samples are not as well characterized. Here, a web‐based application (QCMAP) is developed for interactive diagnosis and prediction of the performance of LC‐MS systems across different biological sample types. Leveraging on a standardized HeLa cell sample run as QC within a multi‐user facility, predictive models are trained on a panel of commonly used performance factors to pinpoint the precise conditions to a (un)satisfactory performance in three LC‐MS systems. It is demonstrated that the learned model can be applied to predict LC‐MS system performance for brain samples generated from an independent study. By compiling these predictive models into our web‐application, QCMAP allows users to benchmark the performance of their LC‐MS systems using their own samples and identify key factors for instrument optimization. QCMAP is freely available from: http://shiny.maths.usyd.edu.au/QCMAP/ .