Qualitative and quantitative characterization of plasma proteins when incorporating traveling wave ion mobility into a liquid chromatography-mass spectrometry workflow for biomarker discovery: use of product ion quantitation as an alternative data analysis tool for label free quantitation

Michael addition–elimination–cyclization based turn-on fluorescence (MADELCY TOF) probes for cellular cysteine imaging and estimation of blood serum cysteine and aminoacylase-1

Michael addition–elimination–cyclization based turn-on fluorescence (MADELCY TOF) probes for the highly sensitive estimation of Cys and aminoacylase-1 (ACY-1).

High-speed Analysis of Large Sample Sets - How Can This Key Aspect of the Omics Be Achieved?

High-speed analysis of large (prote)omics sample sets at the rate of thousands or millions of samples per day on a single platform has been a challenge since the beginning of proteomics. For many years, ESI-based MS methods have dominated proteomics because of their high sensitivity and great depth in analyzing complex proteomes. However, despite improvements in speed, ESI-based MS methods are fundamentally limited by their sample introduction, which excludes off-line sample preparation/fractionation because of the time required to switch between individual samples/sample fractions, and therefore being dependent on the speed of on-line sample preparation methods such as liquid chromatography. Laser-based ionization methods have the advantage of moving from one sample to the next without these limitations, being mainly restricted by the speed of modern sample stages, i.e. 10 ms or less between samples. This speed matches the data acquisition speed of modern high-performing mass spectrometers whereas the pulse repetition rate of the lasers (>1 kHz) provides a sufficient number of desorption/ionization events for successful ion signal detection from each sample at the above speed of the sample stages. Other advantages of laser-based ionization methods include the generally higher tolerance to sample additives and contamination compared with ESI MS, and the contact-less and pulsed nature of the laser used for desorption, reducing the risk of cross-contamination. Furthermore, new developments in MALDI have expanded its analytical capabilities, now being able to fully exploit high-performing hybrid mass analyzers and their strengths in sensitivity and MS/MS analysis by generating an ESI-like stable yield of multiply charged analyte ions. Thus, these new developments and the intrinsically high speed of laser-based methods now provide a good basis for tackling extreme sample analysis speed in the omics.

Using Skyline to Analyze Data-Containing Liquid Chromatography, Ion Mobility Spectrometry, and Mass Spectrometry Dimensions

Recent advances in ion mobility spectrometry (IMS) have illustrated its power in determining the structural characteristics of a molecule, especially when coupled with other separations dimensions such as liquid chromatography (LC) and mass spectrometry (MS). However, these three separation techniques together greatly complicate data analyses, making better informatics tools essential for assessing the resulting data. In this manuscript, Skyline was adapted to analyze LC-IMS-CID-MS data from numerous instrument vendor datasets and determine the effect of adding the IMS dimension into the normal LC-MS molecular pipeline. For the initial evaluation, a tryptic digest of bovine serum albumin (BSA) was spiked into a yeast protein digest at seven different concentrations, and Skyline was able to rapidly analyze the MS and CID-MS data for 38 of the BSA peptides. Calibration curves for the precursor and fragment ions were assessed with and without the IMS dimension. In all cases, addition of the IMS dimension removed noise from co-eluting peptides with close m/z values, resulting in calibration curves with greater linearity and lower detection limits. This study presents an important informatics development since to date LC-IMS-CID-MS data from the different instrument vendors is often assessed manually and cannot be analyzed quickly. Because these evaluations require days for the analysis of only a few target molecules in a limited number of samples, it is unfeasible to evaluate hundreds of targets in numerous samples. Thus, this study showcases Skyline's ability to work with the multidimensional LC-IMS-CID-MS data and provide biological and environmental insights rapidly. Graphical Abstract ᅟ.

Specificity of the osmotic stress response in Candida albicans highlighted by quantitative proteomics

Stress adaptation is critical for the survival of microbes in dynamic environments, and in particular, for fungal pathogens to survive in and colonise host niches. Proteomic analyses have the potential to significantly enhance our understanding of these adaptive responses by providing insight into post-transcriptional regulatory mechanisms that contribute to the outputs, as well as testing presumptions about the regulation of protein levels based on transcript profiling. Here, we used label-free, quantitative mass spectrometry to re-examine the response of the major fungal pathogen of humans, Candida albicans, to osmotic stress. Of the 1,262 proteins that were identified, 84 were down-regulated in response to 1M NaCl, reflecting the decrease in ribosome biogenesis and translation that often accompanies stress. The 64 up-regulated proteins included central metabolic enzymes required for glycerol synthesis, a key osmolyte for this yeast, as well as proteins with functions during stress. These data reinforce the view that adaptation to salt stress involves a transient reduction in ribosome biogenesis and translation together with the accumulation of the osmolyte, glycerol. The specificity of the response to salt stress is highlighted by the small proportion of quantified C. albicans proteins (5%) whose relative elevated abundances were statistically significant.

DIA-SIFT: A Precursor and Product Ion Filter for Accurate Stable Isotope Data-Independent Acquisition Proteomics

Quantitative mass spectrometry-based protein profiling is widely used to measure protein levels across different treatments or disease states, yet current mass spectrometry acquisition methods present distinct limitations. While data-independent acquisition (DIA) bypasses the stochastic nature of data-dependent acquisition (DDA), fragment spectra derived from DIA are often complex and challenging to deconvolve. In-line ion mobility separation (IMS) adds an additional dimension to increase peak capacity for more efficient product ion assignment. As a similar strategy to sequential window acquisition methods (SWATH), IMS-enabled DIA methods rival DDA methods for protein annotation. Here we evaluate IMS-DIA quantitative accuracy using stable isotope labeling by amino acids in cell culture (SILAC). Since SILAC analysis doubles the sample complexity, we find that IMS-DIA analysis is not sufficiently accurate for sensitive quantitation. However, SILAC precursor pairs share common retention and drift times, and both species cofragment to yield multiple quantifiable isotopic y-ion peak pairs. Since y-ion SILAC ratios are intrinsic for each quantified precursor, combined MS1 and y-ion ratio analysis significantly increases the total number of measurements. With increased sampling, we present DIA-SIFT ( SILAC Intrinsic Filtering Tool), a simple statistical algorithm to identify and eliminate poorly quantified MS1 and/or MS2 events. DIA-SIFT combines both MS1 and y-ion ratios, removes outliers, and provides more accurate and precise quantitation (<15% CV) without removing any proteins from the final analysis. Overall, pooled MS1 and MS2 quantitation increases sampling in IMS-DIA SILAC analyses for accurate and precise quantitation.

Scanning Quadrupole Data-Independent Acquisition, Part A: Qualitative and Quantitative Characterization

A novel data-independent acquisition (DIA) method incorporating a scanning quadrupole in front of a collision cell and orthogonal acceleration time-of-flight mass analyzer is described. The method has been characterized for the qualitative and quantitative label-free proteomic analysis of complex biological samples. The principle of the scanning quadrupole DIA method is discussed, and analytical instrument characteristics, such as the quadrupole transmission width, scan/integration time, and chromatographic separation, have been optimized in relation to sample complexity for a number of different model proteomes of varying complexity and dynamic range including human plasma, cell lines, and bacteria. In addition, the technological merits over existing DIA approaches are described and contrasted. The qualitative and semiquantitative performance of the method is illustrated for the analysis of relatively simple protein digest mixtures and a well-characterized human cell line sample using untargeted and targeted search strategies. Finally, the results from a human cell line were compared against publicly available data that used similar chromatographic conditions but were acquired with DDA technology and alternative mass analyzer systems. Qualitative comparison showed excellent concordance of results with >90% overlap of the detected proteins.

Adding a new separation dimension to MS and LC-MS: What is the utility of ion mobility spectrometry?

Ion mobility spectrometry is an analytical technique known for more than 100 years, which entails separating ions in the gas phase based on their size, shape, and charge. While ion mobility spectrometry alone can be useful for some applications (mostly security analysis for detecting certain classes of narcotics and explosives), it becomes even more powerful in combination with mass spectrometry and high-performance liquid chromatography. Indeed, the limited resolving power of ion mobility spectrometry alone can be tackled when combining this analytical strategy with mass spectrometry or liquid chromatography with mass spectrometry. Over the last few years, the hyphenation of ion mobility spectrometry to mass spectrometry or liquid chromatography with mass spectrometry has attracted more and more interest, with significant progresses in both technical advances and pioneering applications. This review describes the theoretical background, available technologies, and future capabilities of these techniques. It also highlights a wide range of applications, from small molecules (natural products, metabolites, glycans, lipids) to large biomolecules (proteins, protein complexes, biopharmaceuticals, oligonucleotides).

Correlated S-palmitoylation profiling of Snail-induced epithelial to mesenchymal transition

Epithelial cells form spatially-organized adhesion complexes that establish polarity gradients, regulate cell proliferation, and direct wound healing. As cells accumulate oncogenic mutations, these key tumor suppression mechanisms are disrupted, eliminating many adhesion complexes and bypassing contact inhibition. The transcription factor Snail is often expressed in malignant cancers, where it promotes transcriptional reprogramming to drive epithelial-mesenchymal transition (EMT) and establishes a more invasive state. S-Palmitoylation describes the fatty-acyl post-translational modification of cysteine residues in proteins, and is required for membrane anchoring, trafficking, localization and function of hundreds of proteins involved in cell growth, polarity, and signaling. Since Snail-expression disrupts apico-basolateral cell polarity, we asked if Snail-dependent transformation induces proteome-wide changes in S-palmitoylation. MCF10A breast cancer cells were retrovirally transduced with Snail and correlated proteome-wide changes in protein abundance and S-palmitoylation were profiled by using stable isotope labeling in cell culture with amino acid (SILAC) mass spectrometry. This analysis identified increased levels of proteins involved in migration, glycolysis, and cell junction remodeling, and decreased levels of proteins involved in cell adhesion. Overall, protein S-palmitoylation is highly correlated with protein abundance, yet for a subset of proteins, this correlation is uncoupled. These findings suggest that Snail-overexpression affects the S-palmitoylation cycle of some proteins, which may participate in cell polarity and tumor suppression.

Comprehensive Proteomic Profiling of Wheat Gluten Using a Combination of Data-Independent and Data-Dependent Acquisition

Wheat is the most important food crop in the world, the unique physiochemical properties of wheat gluten enabling a diverse range of food products to be manufactured. However, genetic and environmental factors affect the technological properties of gluten in unpredictable ways. Although newer proteomic methods have the potential to offer much greater levels of information, it is the older gel-based methods that remain most commonly used to identify compositional differences responsible for the variation in gluten functionality, in part due to the nature of their primary sequences. A combination of platforms were investigated for comprehensive gluten profiling: a QTOF with a data independent schema, which incorporated ion mobility (DIA-IM-MS) and a data dependent acquisition (DDA) workflow using a linear ion trap quadrupole (LTQ) instrument. In conjunction with a manually curated gluten sequence database a total of 2736 gluten peptides were identified with only 157 peptides identified by both platforms. These data showed 127 and 63 gluten protein accessions to be inferred with a minimum of one and three unique peptides respectively. Of the 63 rigorously identified proteins, 26 were gliadin species (4 ω-, 14 α-, and 8 γ-gliadins) and 37 glutenins (including 29 LMW glutenin and 8 HMW glutenins). Of the HMW glutenins, three were 1Dx type and five were 1Bx type illustrating the challenge of unambiguous identification of highly polymorphic proteins without cultivar specific gene sequences. The capacity of the platforms to sequence longer peptides was crucial to achieving the number of identifications, the combination of QTOF-LTQ technology being more important than extraction method to obtain a comprehensive profile. Widespread glutamine deamidation, a post-translational modification, was observed adding complexity to an already highly polymorphic mixture of proteins, with numerous insertions, deletions and substitutions. The data shown is the most comprehensive and detailed proteomic profile of gluten to date.

Advances in quadrupole and time-of-flight mass spectrometry for peptide MRM based translational research analysis

The application of unit resolution tandem quadrupole and high-resolution orthogonal acceleration ToF mass spectrometers for the quantitation and translational analysis of proteolytic peptides is described. The MS platforms were contrasted in terms of sensitivity and linear response. Moreover, the selectivity of the platforms was investigated and the effect on quantitative precision studied. Chromatographic LC conditions, including gradient length and configuration, were investigated with respect to speed/throughput, while minimizing isobaric interferences, thereby providing information with regard to practical sample cohort size limitations of LC-MS for large cohort experiments. In addition to these fundamental analytical performance metrics, precision and linear dynamic ranges were also studied. An LC-MS configuration that encompasses the best combination of throughput and analytical accuracy for translational studies was chosen, despite the MS platforms giving similar quantitative performance, and instances were identified where alternative combinations were found to be beneficial. This configuration was utilized to demonstrate that proteolytically digested nondepleted samples from heart failure patients could be classified with good discriminative power using a subset of proteins previously suggested as candidate biomarkers for cardiovascular diseases.

Design and expression of a QconCAT protein to validate Hi3 protein quantification of influenza vaccine antigens

Quantification of the antigens hemagglutinin and neuraminidase in influenza vaccines has been reported using an antibody-free liquid chromatography-mass spectrometry (LC-MS) based method known as MS(E) "Hi3". This approach is based on the average signal intensity of the three most intense tryptic peptides relative to a primary standard. This strategy assumes that the Hi3 signal responses are consistent for all proteins, and therefore comparable to a spiked reference for absolute quantification. This method is much faster than the current standard methods; however, the results can vary significantly which brought the method's accuracy into question. To address this question we generated synthetic proteins comprising a concatenation of the peptides used to quantify the proteins of interest (QconCAT). Complete tryptic digestion of a QconCAT protein produces equal molar peptide amounts, allowing verification of equal signal response of Hi3 peptides for the proteins of interest. The generation of an intact, stable, QconCAT protein that digest completely is challenging. We have designed and analyzed five QconCAT proteins with unique design elements to address these challenges. We conclude that a suitable QconCAT protein can be produced and that the results obtained reinforce the validity of the Hi3 approach for quantifying proteins in annual influenza vaccine formulations.

SIGNIFICANCE

The advances in quantitative proteomics have allowed the adaptation and application of these methods to numerous fields. In this paper we have validated a Hi3 approach to augment the antigen quantification for influenza vaccines injected into many millions annually. This methodology allows analysis of multiple antigens simultaneously without the need to generate antibodies. Key circumstances where this is advantageous are for quantitation of very similar antigens, such as the new quadravalent products and when time is critical such as in a flu pandemic.

In-depth evaluation of software tools for data-independent acquisition based label-free quantification

Label-free quantification (LFQ) based on data-independent acquisition workflows currently experiences increasing popularity. Several software tools have been recently published or are commercially available. The present study focuses on the evaluation of three different software packages (Progenesis, synapter, and ISOQuant) supporting ion mobility enhanced data-independent acquisition data. In order to benchmark the LFQ performance of the different tools, we generated two hybrid proteome samples of defined quantitative composition containing tryptically digested proteomes of three different species (mouse, yeast, Escherichia coli). This model dataset simulates complex biological samples containing large numbers of both unregulated (background) proteins as well as up- and downregulated proteins with exactly known ratios between samples. We determined the number and dynamic range of quantifiable proteins and analyzed the influence of applied algorithms (retention time alignment, clustering, normalization, etc.) on quantification results. Analysis of technical reproducibility revealed median coefficients of variation of reported protein abundances below 5% for MS(E) data for Progenesis and ISOQuant. Regarding accuracy of LFQ, evaluation with synapter and ISOQuant yielded superior results compared to Progenesis. In addition, we discuss reporting formats and user friendliness of the software packages. The data generated in this study have been deposited to the ProteomeXchange Consortium with identifier PXD001240 (http://proteomecentral.proteomexchange.org/dataset/PXD001240).