Operation Moonshot: rapid translation of a SARS-CoV-2 targeted peptide immunoaffinity liquid chromatography-tandem mass spectrometry test from research into routine clinical use.

OBJECTIVES: During 2020, the UK's Department of Health and Social Care (DHSC) established the Moonshot programme to fund various diagnostic approaches for the detection of SARS-CoV-2, the pathogen behind the COVID-19 pandemic. Mass spectrometry was one of the technologies proposed to increase testing capacity. METHODS: Moonshot funded a multi-phase development programme, bringing together experts from academia, industry and the NHS to develop a state-of-the-art targeted protein assay utilising enrichment and liquid chromatography tandem mass spectrometry (LC-MS/MS) to capture and detect low levels of tryptic peptides derived from SARS-CoV-2 virus. The assay relies on detection of target peptides, ADETQALPQRK (ADE) and AYNVTQAFGR (AYN), derived from the nucleocapsid protein of SARS-CoV-2, measurement of which allowed the specific, sensitive, and robust detection of the virus from nasopharyngeal (NP) swabs. The diagnostic sensitivity and specificity of LC-MS/MS was compared with reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) via a prospective study. RESULTS: Analysis of NP swabs (n=361) with a median RT-qPCR quantification cycle (Cq) of 27 (range 16.7-39.1) demonstrated diagnostic sensitivity of 92.4% (87.4-95.5), specificity of 97.4% (94.0-98.9) and near total concordance with RT-qPCR (Cohen's Kappa 0.90). Excluding Cq>32 samples, sensitivity was 97.9% (94.1-99.3), specificity 97.4% (94.0-98.9) and Cohen's Kappa 0.95. CONCLUSIONS: This unique collaboration between academia, industry and the NHS enabled development, translation, and validation of a SARS-CoV-2 method in NP swabs to be achieved in 5 months. This pilot provides a model and pipeline for future accelerated development and implementation of LC-MS/MS protein/peptide assays into the routine clinical laboratory.

Cov2MS: An Automated and Quantitative Matrix-Independent Assay for Mass Spectrometric Measurement of SARS-CoV-2 Nucleocapsid Protein.

The pandemic readiness toolbox needs to be extended, targeting different biomolecules, using orthogonal experimental set-ups. Here, we build on our Cov-MS effort using LC-MS, adding SISCAPA technology to enrich proteotypic peptides of the SARS-CoV-2 nucleocapsid (N) protein from trypsin-digested patient samples. The Cov2MS assay is compatible with most matrices including nasopharyngeal swabs, saliva, and plasma and has increased sensitivity into the attomole range, a 1000-fold improvement compared to direct detection in a matrix. A strong positive correlation was observed with qPCR detection beyond a quantification cycle of 30-31, the level where no live virus can be cultured. The automatable sample preparation and reduced LC dependency allow analysis of up to 500 samples per day per instrument. Importantly, peptide enrichment allows detection of the N protein in pooled samples without sensitivity loss. Easily multiplexed, we detect variants and propose targets for Influenza A and B detection. Thus, the Cov2MS assay can be adapted to test for many different pathogens in pooled samples, providing longitudinal epidemiological monitoring of large numbers of pathogens within a population as an early warning system.

Evaluation of acquisition modes for semi-quantitative analysis by targeted and untargeted mass spectrometry.

RATIONALE: Analyte quantitation by mass spectrometry underpins a diverse range of scientific endeavors. The fast-growing field of mass spectrometer development has resulted in several targeted and untargeted acquisition modes suitable for these applications. By characterizing the acquisition methods available on an ion mobility (IM)-enabled orthogonal acceleration time-of-flight (oa-ToF) instrument, the optimum modes for analyte semi-quantitation can be deduced. METHODS: Serial dilutions of commercial metabolite, peptide, or cross-linked peptide analytes were prepared in matrices of human urine or Escherichia coli digest. Each analyte dilution was introduced into an IM separation-enabled oa-ToF mass spectrometer by reversed-phase liquid chromatography and electrospray ionization. Data were acquired for each sample in duplicate using nine different acquisition modes, including four IM-enabled acquisitions modes, available on the mass spectrometer. RESULTS: Five (metabolite) or seven (peptide/cross-linked peptide) point calibration curves were prepared for analytes across each of the acquisition modes. A nonlinear response was observed at high concentrations for some modes, attributed to saturation effects. Two correction methods, one MS1 isotope-correction and one MS2 ion intensity-correction, were applied to address this observation, resulting in an up to twofold increase in dynamic range. By averaging the semi-quantitative results across analyte classes, two parameters, linear dynamic range (LDR) and lower limit of quantification (LLOQ), were determined to evaluate each mode. CONCLUSION: A comparison of the acquisition modes revealed that data-independent acquisition and parallel reaction monitoring methods are most robust for semi-quantitation when considering achievable LDR and LLOQ. IM-enabled modes exhibited sensitivity increases, but a simultaneous reduction in dynamic range required correction methods to recover. These findings will assist users in identifying the optimum acquisition mode for their analyte quantitation needs, supporting a diverse range of applications and providing guidance for future acquisition mode developments.

The influence of hypoxia on the prostate cancer proteome.

Prostate cancer accounts for around 15% of male deaths in Western Europe and is the second leading cause of cancer death in men after lung cancer. Mounting evidence suggests that prostate cancer deposits exist within a hypoxic environment and this contributes to radio-resistance thus hampering one of the major therapies for this cancer. Recent reports have shown that nitric oxide (NO) donating non-steroidal anti-inflammatory drugs (NSAIDs) reduced tumour hypoxia as well as maintaining a radio-sensitising/therapeutic effect on prostate cancer cells. The aim of this study was to evaluate the impact of hypoxia on the proteome of the prostate and to establish whether NO-NSAID treatment reverted the protein profiles back to their normoxic status. To this end an established hormone insensitive prostate cancer cell line, PC-3, was cultured under hypoxic and normoxic conditions before and following exposure to NO-NSAID in combination with selected other common prostate cancer treatment types. The extracted proteins were analysed by ion mobility-assisted data independent acquisition mass spectrometry (MS), combined with multivariate statistical analyses, to measure hypoxia-induced alterations in the proteome of these cells. The analyses demonstrated that under hypoxic conditions there were well-defined, significantly regulated/differentially expressed proteins primarily involved with structural and binding processes including, for example, TUBB4A, CIRP and PLOD1. Additionally, the exposure of hypoxic cells to NSAID and NO-NSAID agents, resulted in some of these proteins being differentially expressed; for example, both PCNA and HNRNPA1L were down-regulated, corresponding with disruption in the nucleocytoplasmic shuttling process.

Elevation of glycoprotein nonmetastatic melanoma protein B in type 1 Gaucher disease patients and mouse models.

Gaucher disease is caused by inherited deficiency of lysosomal glucocerebrosidase. Proteome analysis of laser-dissected splenic Gaucher cells revealed increased amounts of glycoprotein nonmetastatic melanoma protein B (gpNMB). Plasma gpNMB was also elevated, correlating with chitotriosidase and CCL18, which are established markers for human Gaucher cells. In Gaucher mice, gpNMB is also produced by Gaucher cells. Correction of glucocerebrosidase deficiency in mice by gene transfer or pharmacological substrate reduction reverses gpNMB abnormalities. In conclusion, gpNMB acts as a marker for glucosylceramide-laden macrophages in man and mouse and gpNMB should be considered as candidate biomarker for Gaucher disease in treatment monitoring.

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.

Verification of a Parkinson's disease protein signature in T-lymphocytes by multiple reaction monitoring.

Diagnosis of Parkinson's disease, the second most common neurodegenerative disease, is based on the appearance of motor symptoms. A panel of protein biomarkers in the T-lymphocyte proteome was previously proposed as a Parkinson's disease signature. Here, we designed an LC-MS based method to quantitatively evaluate this protein signature by multiple reaction monitoring (MRM) in T-lymphocytes and peripheral blood mononuclear cells from a new cohort of nine patients with Parkinson's disease and nine unaffected subjects. Patients were classified using the discriminant function obtained from two-dimensional electrophoresis and protein amounts measured by MRM, thus assigning seven controls out of nine as true negatives and nine patients out of nine as true positives. A good discriminant power was obtained by selecting a subset of peptides from the protein signature, with an area under the receiver operating characteristic curve of 0.877. A similar result is achieved by evaluating all peptides of a selected panel of proteins (gelsolin, moesin, septin-6, twinfilin-2, lymphocyte-specific protein 1, vimentin, transaldolase), with an area under the curve of 0.840. Conversely, the signature was not able to classify the enrolled subjects when evaluated in whole mononuclear cells. Overall, this report shows the portability of the proposed method to a large-scale clinical validation study.

A probabilistic framework for peptide and protein quantification from data-dependent and data-independent LC-MS proteomics experiments.

A probability-based quantification framework is presented for the calculation of relative peptide and protein abundance in label-free and label-dependent LC-MS proteomics data. The results are accompanied by credible intervals and regulation probabilities. The algorithm takes into account data uncertainties via Poisson statistics modified by a noise contribution that is determined automatically during an initial normalization stage. Protein quantification relies on assignments of component peptides to the acquired data. These assignments are generally of variable reliability and may not be present across all of the experiments comprising an analysis. It is also possible for a peptide to be identified to more than one protein in a given mixture. For these reasons the algorithm accepts a prior probability of peptide assignment for each intensity measurement. The model is constructed in such a way that outliers of any type can be automatically reweighted. Two discrete normalization methods can be employed. The first method is based on a user-defined subset of peptides, while the second method relies on the presence of a dominant background of endogenous peptides for which the concentration is assumed to be unaffected. Normalization is performed using the same computational and statistical procedures employed by the main quantification algorithm. The performance of the algorithm will be illustrated on example data sets, and its utility demonstrated for typical proteomics applications. The quantification algorithm supports relative protein quantification based on precursor and product ion intensities acquired by means of data-dependent methods, originating from all common isotopically-labeled approaches, as well as label-free ion intensity-based data-independent methods.

Design and application of a data-independent precursor and product ion repository.

The functional design and application of a data-independent LC-MS precursor and product ion repository for protein identification, quantification, and validation is conceptually described. The ion repository was constructed from the sequence search results of a broad range of discovery experiments investigating various tissue types of two closely related mammalian species. The relative high degree of similarity in protein complement, ion detection, and peptide and protein identification allows for the analysis of normalized precursor and product ion intensity values, as well as standardized retention times, creating a multidimensional/orthogonal queryable, qualitative, and quantitative space. Peptide ion map selection for identification and quantification is primarily based on replication and limited variation. The information is stored in a relational database and is used to create peptide- and protein-specific fragment ion maps that can be queried in a targeted fashion against the raw or time aligned ion detections. These queries can be conducted either individually or as groups, where the latter affords pathway and molecular machinery analysis of the protein complement. The presented results also suggest that peptide ionization and fragmentation efficiencies are highly conserved between experiments and practically independent of the analyzed biological sample when using similar instrumentation. Moreover, the data illustrate only minor variation in ionization efficiency with amino acid sequence substitutions occurring between species. Finally, the data and the presented results illustrate how LC-MS performance metrics can be extracted and utilized to ensure optimal performance of the employed analytical workflows.

Using ion purity scores for enhancing quantitative accuracy and precision in complex proteomics samples.

To accurately determine the quantitative change of peptides and proteins in complex proteomics samples requires knowledge of how well each ion has been measured. The precision of each ions' calculated area is predicated on how uniquely it occupies its own space in m/z and elution time. Given an initial assumption that prior to the addition of the "heavy" label, all other ion detections are unique, which is arguably untrue, an initial attempt at quantifying the pervasiveness of ion interference events in a representative binary SILAC experiment was made by comparing the centered m/z and retention time of the ion detections from the "light" variant to its "heavy" companion. Ion interference rates were determined for LC-MS data acquired at mass resolving powers of 20 and 40 K with and without ion mobility separation activated. An ion interference event was recorded, if present in the companion dataset was an ion within ± its Δ mass at half-height, ±15 s of its apex retention time and if utilized by ±1 drift bin. Data are presented illustrating a definitive decrease in the frequency of ion interference events with each additional increase in selectivity of the analytical workflow. Regardless of whether the quantitative experiment is a composite of labeled samples or label free, how well each ion is measured can be determined given knowledge of the instruments mass resolving power across the entire m/z scale and the ion detection algorithm reporting both the centered m/z and Δ mass at half-height for each detected ion. Given these measurements, an effective resolution can be calculated and compared with the expected instrument performance value providing a purity score for the calculated ions' area based on mass resolution. Similarly, chromatographic and drift purity scores can be calculated. In these instances, the error associated to an ions' calculated peak area is estimated by examining the variation in each measured width to that of their respective experimental median. Detail will be disclosed as to how a final ion purity score was established, providing a first measure of how accurately each ions' area was determined as well as how precise the calculated quantitative change between labeled or unlabelled pairs were determined. Presented is how common ion interference events are in quantitative proteomics LC-MS experiments and how ion purity filters can be utilized to overcome and address them, providing ultimately more accurate and precise quantification results across a wider dynamic range.

Plasma biomarker identification in S-adenosylhomocysteine hydrolase deficiency.

S-Adenosylhomocysteine hydrolase (AHCY) deficiency is a rare congenital disorder in methionine metabolism clinically characterized by white matter atrophy, delayed myelination, slowly progressive myopathy, retarded psychomotor development and mildly active chronic hepatitis. In the present study, we utilized a comparative proteomics strategy based on 2-DE/MALDI-MS and LC/ESI-MS to analyze plasma proteins from three AHCY-deficient patients prior to and after receiving dietary treatment designed to alleviate disease symptoms. Obtained results revealed candidate biomarkers for the detection of myopathy specifically associated with AHCY deficiency, such as carbonic anhydrase 3, creatine kinase, and thrombospondin 4. Several proteins mediating T-cell activation and function were identified as well, including attractin and diacylglycerol kinase α. Further validation and functional analysis of identified proteins with clinical value would ensure that these biomarkers make their way into routine diagnosis and management of AHCY deficiency.

Simulating and validating proteomics data and search results.

The computational simulation of complete proteomic data sets and their utility to validate detection and interpretation algorithms, to aid in the design of experiments and to assess protein and peptide false discovery rates is presented. The simulation software has been developed for emulating data originating from data-dependent and data-independent LC-MS workflows. Data from all types of commonly used hybrid mass spectrometers can be simulated. The algorithms are based on empirically derived physicochemical liquid and gas phase models for proteins and peptides. Sample composition in terms of complexity and dynamic range, as well as chromatographic, experimental and MS conditions, can be controlled and adjusted independently. The effect of on-column amounts, gradient length, mass resolution and ion mobility on search specificity will be demonstrated using tryptic peptides from human and yeast cellular lysates simulated over five orders of magnitude in dynamic range. Initial justification of the simulated data sets is achieved by comparing and contrasting the in silico simulated data to experimentally derived results from a 48 protein mixture, spanning a similar magnitude of five orders of magnitude. Additionally, experimental data from replicate and dilutions series experiments will be utilized to determine error rates at the peptide and protein level with respect to mass, area, retention and drift time. The data presented reveal a high degree of similarity at the ion detection, peptide and protein level when analyzed under similar conditions.

Towards a proteome signature for invasive ductal breast carcinoma derived from label-free nanoscale LC-MS protein expression profiling of tumorous and glandular tissue.

As more and more alternative treatments become available for breast carcinoma, there is a need to stratify patients and individual molecular information seems to be suitable for this purpose. In this study, we applied label-free protein quantitation by nanoscale LC-MS and investigated whether this approach could be used for defining a proteome signature for invasive ductal breast carcinoma. Tissue samples from healthy breast and tumor were collected from three patients. Protein identifications were based on LC-MS peptide fragmentation data which were obtained simultaneously to the quantitative information. Hereby, an invasive ductal breast carcinoma proteome signature was generated which contains 60 protein entries. The on-column concentrations for osteoinductive factor, vimentin, GAP-DH, and NDKA are provided as examples. These proteins represent distinctive gene ontology groups of differentially expressed proteins and are discussed as risk markers for primary tumor pathogenesis. The developed methodology has been found well applicable in a clinical environment in which standard operating procedures can be kept; a prerequisite for the definition of molecular parameter sets that shall be capable for stratification of patients.

Database searching and accounting of multiplexed precursor and product ion spectra from the data independent analysis of simple and complex peptide mixtures.

A novel database search algorithm is presented for the qualitative identification of proteins over a wide dynamic range, both in simple and complex biological samples. The algorithm has been designed for the analysis of data originating from data independent acquisitions, whereby multiple precursor ions are fragmented simultaneously. Measurements used by the algorithm include retention time, ion intensities, charge state, and accurate masses on both precursor and product ions from LC-MS data. The search algorithm uses an iterative process whereby each iteration incrementally increases the selectivity, specificity, and sensitivity of the overall strategy. Increased specificity is obtained by utilizing a subset database search approach, whereby for each subsequent stage of the search, only those peptides from securely identified proteins are queried. Tentative peptide and protein identifications are ranked and scored by their relative correlation to a number of models of known and empirically derived physicochemical attributes of proteins and peptides. In addition, the algorithm utilizes decoy database techniques for automatically determining the false positive identification rates. The search algorithm has been tested by comparing the search results from a four-protein mixture, the same four-protein mixture spiked into a complex biological background, and a variety of other "system" type protein digest mixtures. The method was validated independently by data dependent methods, while concurrently relying on replication and selectivity. Comparisons were also performed with other commercially and publicly available peptide fragmentation search algorithms. The presented results demonstrate the ability to correctly identify peptides and proteins from data independent acquisition strategies with high sensitivity and specificity. They also illustrate a more comprehensive analysis of the samples studied; providing approximately 20% more protein identifications, compared to a more conventional data directed approach using the same identification criteria, with a concurrent increase in both sequence coverage and the number of modified peptides.

The detection, correlation, and comparison of peptide precursor and product ions from data independent LC-MS with data dependant LC-MS/MS.

The detection, correlation, and comparison of peptide and product ions from a data independent LC-MS acquisition strategy with data dependent LC-MS/MS is described. The data independent mode of acquisition differs from an LC-MS/MS data acquisition since no ion transmission window is applied with the first mass analyzer prior to collision induced disassociation. Alternating the energy applied to the collision cell, between low and elevated energy, on a scan-to-scan basis, provides accurate mass precursor and associated product ion spectra from every ion above the LOD of the mass spectrometer. The method therefore provides a near 100% duty cycle, with an inherent increase in signal intensity due to the fact that both precursor and product ion data are collected on all isotopes of every charge-state across the entire chromatographic peak width. The correlation of product to precursor ions, after deconvolution, is achieved by using reconstructed retention time apices and chromatographic peak shapes. Presented are the results from the comparison of a simple four protein mixture, in the presence and absence of an enzymatically digested protein extract from Escherichia coli. The samples were run in triplicate by both data dependant analysis (DDA) LC-MS/MS and data-independent, alternate scanning LC-MS. The detection and identification of precursor and product ions from the combined DDA search results of the four protein mixture were used for comparison to all other data. Each individual set of data-independent LC-MS data provides a more comprehensive set of detected ions than the combined peptide identifications from the DDA LC-MS/MS experiments. In the presence of the complex E. coli background, over 90% of the monoisotopic masses from the combined LC-MS/MS identifications were detected at the appropriate retention time. Moreover, the fragmentation pattern and number of associated elevated energy product ions in each replicate experiment was found to be very similar to the DDA identifications. In the case of the corresponding individual DDA LC-MS/MS experiment, 43% of the possible detectable peptides of interest were identified. The presented data illustrates that the time-aligned data from data-independent alternate scanning LC-MS experiments is highly comparable to the data obtained via DDA. The obtained information can therefore be effectively and correctly deconvolved to correlate product ions with parent precursor ions. The ability to generate precursor-product ion tables from this information and subsequently identify the correct parent precursor peptide will be illustrated in a companion manuscript.

Qualitative and quantitative proteomic profiling of cripto(-/-) embryonic stem cells by means of accurate mass LC-MS analysis.

Cripto is one of the key regulators of embryonic stem cells (ESCs) differentiation into cardiomyocites vs neuronal fate. Cripto(-/-) murine ESCs have been utilized to investigate the molecular mechanisms underlying early events of mammalian lineage differentiation. 2D/LC-MS/MS and a label-free LC-MS approaches were used to qualitatively and quantitatively profile the cripto(-/-) ESC proteome, providing an integral view of the alterations induced in stem cell functions by deleting the cripto gene.

Proteomic profiling of proliferating and differentiated neural mes-c-myc A1 cell line from mouse embryonic mesencephalon by LC-MS.

The proteomic profiling, by means of label-free qualitative and quantitative LC-MS analysis of proliferating/undifferentiated vs nonproliferating/differentiated mes-c-myc A1 cell line (A1), has been performed. A1 cells were generated from mouse embryonic central nervous system. The study was aimed at surveying the molecular changes following neural differentiation. The results provide a list of candidate proteins with potential relevance for the transition of A1 cells from the proliferative to the differentiated status.

A proteome approach defines protective functions of tobacco leaf trichomes.

The leaf surface of most terrestrial plants is covered with plant hairs called trichomes. These epidermal appendages are thought to contribute to many aspects of plant defense against biotic and abiotic stresses in a variety of species. Trichome development has been intensively studied in Arabidopsis, and the phytochemical composition of trichomes was analyzed in a number of plant species. However, comparatively little is known of the proteins expressed. We therefore initiated a proteome approach to better define the cellular mechanisms operating in plant trichomes using two-dimensional gel electrophoresis to separate proteins of whole leaves and isolated trichomes. Tobacco was chosen due to the presence of glandular trichomes involved in the secretion of defense compounds. Comparative image analysis of the protein patterns indicated a number of spots, which were highly enriched in trichomes relative to leaves. These spots were excised for identification by mass spectrometry. The results showed that among the proteins specifically enriched in trichomes, the components of stress defense responses were strongly represented. The high expression of stress-related proteins was verified by Western blotting. Superoxide dismutase isoforms were additionally analyzed by activity staining. Our results demonstrate feasibility of the proteome approach to elucidate the cell biology of plant trichomes.

Mass spectrometry proteomic analysis of stress adaptation reveals both common and distinct response pathways in Propionibacterium freudenreichii.

Microorganisms used in food technology and probiotics are exposed to technological and digestive stresses, respectively. Traditionally used as Swiss-type cheese starters, propionibacteria also constitute promising human probiotics. Stress tolerance and cross-protection in Propionibacterium freudenreichii were thus examined after exposure to heat, acid, or bile salts stresses. Adapted cells demonstrated acquired homologous tolerance. Cross-protection between bile salts and heat adaptation was demonstrated. By contrast, bile salts pretreatment sensitized cells to acid challenge and vice versa. Surprisingly, heat and acid responses did not present significant cross-protection in P. freudenreichii. During adaptations, important changes in cellular protein synthesis were observed using two-dimensional electrophoresis. While global protein synthesis decreased, several proteins were overexpressed during stress adaptations. Thirty-four proteins were induced by acid pretreatment, 34 by bile salts pretreatment, and 26 by heat pretreatment. Six proteins are common to all stresses and represent general stress-response components. Among these polypeptides, general stress chaperones, and proteins involved in energetic metabolism, oxidative stress response, or SOS response were identified. These results bring new insight into the tolerance of P. freudenreichii to heat, acid, and bile salts, and should be taken into consideration in the development of probiotic preparations.