Custom Workflow for the Confident Identification of Sulfotyrosine-Containing Peptides and Their Discrimination from Phosphopeptides.

Protein tyrosine sulfation (sY) is a post-translational modification (PTM) catalyzed by Golgi-resident tyrosyl protein sulfo transferases (TPSTs). Information on sY in humans is currently limited to ∼50 proteins, with only a handful having verified sites of sulfation. As such, the contribution of sulfation to the regulation of biological processes remains poorly defined. Mass spectrometry (MS)-based proteomics is the method of choice for PTM analysis but has yet to be applied for systematic investigation of the "sulfome", primarily due to issues associated with discrimination of sY-containing from phosphotyrosine (pY)-containing peptides. In this study, we developed an MS-based workflow for sY-peptide characterization, incorporating optimized Zr4+ immobilized metal-ion affinity chromatography (IMAC) and TiO2 enrichment strategies. Extensive characterization of a panel of sY- and pY-peptides using an array of fragmentation regimes (CID, HCD, EThcD, ETciD, UVPD) highlighted differences in the generation of site-determining product ions and allowed us to develop a strategy for differentiating sulfated peptides from nominally isobaric phosphopeptides based on low collision energy-induced neutral loss. Application of our "sulfomics" workflow to a HEK-293 cell extracellular secretome facilitated identification of 21 new sulfotyrosine-containing proteins, several of which we validate enzymatically, and reveals new interplay between enzymes relevant to both protein and glycan sulfation.

Serum protein signatures differentiate paediatric autoimmune/inflammatory disorders.

Because of their rarity, limited awareness among non-specialists, and significant overlaps in their clinical presentation, childhood autoimmune/inflammatory conditions represent a diagnostic and therapeutic challenge. Juvenile idiopathic arthritis (JIA), with its 7 sub-forms, is the most common paediatric "rheumatic" disease. Juvenile-onset systemic lupus erythematosus (jSLE) is a severe autoimmune/inflammatory disease that can affect any organ system and shares clinical features with JIA. To overcome issues around diagnostic approaches in the context of clinical overlap, we aimed at the definition of disease sub-form specific cytokine and chemokine profiles. Serum samples from patients with JIA (n = 77) and jSLE (n = 48), as well as healthy controls (n = 30), were collected. Samples were analysed using the Meso Scale Discovery (MSD) U-PLEX Biomarker Group 1 (hu) panel. Distinct serum protein signatures associate with JIA vs jSLE disease groups. Proteins with high discriminatory ability include IL-23, MIP-1ß, MCP-1, M-CSF and MDC. Furthermore, serum IL-18, MIF, MIP-5 and YKL-40 discriminate between systemic JIA and other JIA subtypes. Thus, simultaneous quantification of serum proteins in a panel format may provide an avenue for the diagnosis and monitoring of childhood autoimmune/inflammatory conditions.

A Hybrid Virtual Fracture Clinic is Safe and Efficacious in the COVID-19 Era: Stay at Home and Save Lives.

Introduction The coronavirus disease 2019 (COVID-19) pandemic necessitated a change in the manner outpatient fracture clinics are conducted due to the need to reduce footfall in hospitals. While studies regarding virtual fracture clinics have shown these to be useful and effective, they focus exclusively on remote consultations. However, our service was bespoke to the patient - either a face-to-face, a telephone consultation or both, depending on patient need - a 'hybrid virtual fracture clinic' (HVFC). We report patient satisfaction and outcomes with this service from the first wave of the pandemic. Methods We retrospectively interviewed patients who availed of the HVFC service at our institution during the first two weeks of national lockdown in England from March 23 to April 5, 2020. The number and type of consultations, patient vulnerability to COVID-19, and type of management (surgical vs non-surgical) were among the factors taken into consideration. Patient experience was assessed using the Net Promoter Score (NPS), Customer Effort Score (CES), and Customer Satisfaction Score (CSS) on a scale of 0-10. Patient-reported outcomes were assessed using the EuroQol-5D-5L score (including EQ Visual Analogue Scale {EQ-VAS} scoring on a scale of 0-100). Results The mean overall NPS, CES, and CSS for the service were 7.32, 7.24, and 7.49, respectively. The mean self-reported EQ-VAS rating was 77.5. Of 442 consultations, 246 were conducted virtually; 10% were face-to-face, 29% virtual, and 61% were hybrid consultations. The HVFC resulted in a 55.65% reduction in footfall. Statistical analysis showed no significant difference across any outcome measure when compared between hybrid, virtual, and face-to-face consultations. Patients vulnerable to COVID-19 and those who did not require surgery tended to report better overall scores. Conclusion Our study indicates that the HVFC format can reduce patient footfall significantly (>50%) while providing effective and satisfactory outpatient care. There appears to be no difference in patient-reported outcomes between face-to-face consultations and hybrid or virtual consultations. Patients would recommend HVFC to family and friends, found it was easy to use, and reported good satisfaction with the service.

An OMICs-based meta-analysis to support infection state stratification.

MOTIVATION: A fundamental problem for disease treatment is that while antibiotics are a powerful counter to bacteria, they are ineffective against viruses. Often, bacterial and viral infections are confused due to their similar symptoms and lack of rapid diagnostics. With many clinicians relying primarily on symptoms for diagnosis, overuse and misuse of modern antibiotics are rife, contributing to the growing pool of antibiotic resistance. To ensure an individual receives optimal treatment given their disease state and to reduce over-prescription of antibiotics, the host response can in theory be measured quickly to distinguish between the two states. To establish a predictive biomarker panel of disease state (viral/bacterial/no-infection), we conducted a meta-analysis of human blood infection studies using machine learning. RESULTS: We focused on publicly available gene expression data from two widely used platforms, Affymetrix and Illumina microarrays as they represented a significant proportion of the available data. We were able to develop multi-class models with high accuracies with our best model predicting 93% of bacterial and 89% viral samples correctly. To compare the selected features in each of the different technologies, we reverse-engineered the underlying molecular regulatory network and explored the neighbourhood of the selected features. The networks highlighted that although on the gene-level the models differed, they contained genes from the same areas of the network. Specifically, this convergence was to pathways including the Type I interferon Signalling Pathway, Chemotaxis, Apoptotic Processes and Inflammatory/Innate Response. AVAILABILITY: Data and code are available on the Gene Expression Omnibus and github. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Temporal modulation of the NF-κB RelA network in response to different types of DNA damage.

Different types of DNA damage can initiate phosphorylation-mediated signalling cascades that result in stimulus specific pro- or anti-apoptotic cellular responses. Amongst its many roles, the NF-κB transcription factor RelA is central to these DNA damage response pathways. However, we still lack understanding of the co-ordinated signalling mechanisms that permit different DNA damaging agents to induce distinct cellular outcomes through RelA. Here, we use label-free quantitative phosphoproteomics to examine the temporal effects of exposure of U2OS cells to either etoposide (ETO) or hydroxyurea (HU) by monitoring the phosphorylation status of RelA and its protein binding partners. Although few stimulus-specific differences were identified in the constituents of phosphorylated RelA interactome after exposure to these DNA damaging agents, we observed subtle, but significant, changes in their phosphorylation states, as a function of both type and duration of treatment. The DNA double strand break (DSB)-inducing ETO invoked more rapid, sustained responses than HU, with regulated targets primarily involved in transcription, cell division and canonical DSB repair. Kinase substrate prediction of ETO-regulated phosphosites suggest abrogation of CDK and ERK1 signalling, in addition to the known induction of ATM/ATR. In contrast, HU-induced replicative stress mediated temporally dynamic regulation, with phosphorylated RelA binding partners having roles in rRNA/mRNA processing and translational initiation, many of which contained a 14-3-3ε binding motif, and were putative substrates of the dual specificity kinase CLK1. Our data thus point to differential regulation of key cellular processes and the involvement of distinct signalling pathways in modulating DNA damage-specific functions of RelA.

Use of the Polo-like kinase 4 (PLK4) inhibitor centrinone to investigate intracellular signalling networks using SILAC-based phosphoproteomics.

Polo-like kinase 4 (PLK4) is the master regulator of centriole duplication in metazoan organisms. Catalytic activity and protein turnover of PLK4 are tightly coupled in human cells, since changes in PLK4 concentration and catalysis have profound effects on centriole duplication and supernumerary centrosomes, which are associated with aneuploidy and cancer. Recently, PLK4 has been targeted with a variety of small molecule kinase inhibitors exemplified by centrinone, which rapidly induces inhibitory effects on PLK4 and leads to on-target centrosome depletion. Despite this, relatively few PLK4 substrates have been identified unequivocally in human cells, and PLK4 signalling outside centriolar networks remains poorly characterised. We report an unbiased mass spectrometry (MS)-based quantitative analysis of cellular protein phosphorylation in stable PLK4-expressing U2OS human cells exposed to centrinone. PLK4 phosphorylation was itself sensitive to brief exposure to the compound, resulting in PLK4 stabilisation. Analysing asynchronous cell populations, we report hundreds of centrinone-regulated cellular phosphoproteins, including centrosomal and cell cycle proteins and a variety of likely 'non-canonical' substrates. Surprisingly, sequence interrogation of ∼300 significantly down-regulated phosphoproteins reveals an extensive network of centrinone-sensitive [Ser/Thr]Pro phosphorylation sequence motifs, which based on our analysis might be either direct or indirect targets of PLK4. In addition, we confirm that NMYC and PTPN12 are PLK4 substrates, both in vitro and in human cells. Our findings suggest that PLK4 catalytic output directly controls the phosphorylation of a diverse set of cellular proteins, including Pro-directed targets that are likely to be important in PLK4-mediated cell signalling.

Strong anion exchange-mediated phosphoproteomics reveals extensive human non-canonical phosphorylation.

Phosphorylation is a key regulator of protein function under (patho)physiological conditions, and defining site-specific phosphorylation is essential to understand basic and disease biology. In vertebrates, the investigative focus has primarily been on serine, threonine and tyrosine phosphorylation, but mounting evidence suggests that phosphorylation of other "non-canonical" amino acids also regulates critical aspects of cell biology. However, standard methods of phosphoprotein characterisation are largely unsuitable for the analysis of non-canonical phosphorylation due to their relative instability under acidic conditions and/or elevated temperature. Consequently, the complete landscape of phosphorylation remains unexplored. Here, we report an unbiased phosphopeptide enrichment strategy based on strong anion exchange (SAX) chromatography (UPAX), which permits identification of histidine (His), arginine (Arg), lysine (Lys), aspartate (Asp), glutamate (Glu) and cysteine (Cys) phosphorylation sites on human proteins by mass spectrometry-based phosphoproteomics. Remarkably, under basal conditions, and having accounted for false site localisation probabilities, the number of unique non-canonical phosphosites is approximately one-third of the number of observed canonical phosphosites. Our resource reveals the previously unappreciated diversity of protein phosphorylation in human cells, and opens up avenues for high-throughput exploration of non-canonical phosphorylation in all organisms.

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.

Scanning Quadrupole Data-Independent Acquisition, Part B: Application to the Analysis of the Calcineurin-Interacting Proteins during Treatment of Aspergillus fumigatus with Azole and Echinocandin Antifungal Drugs.

Calcineurin is a critical cell-signaling protein that orchestrates growth, stress response, virulence, and antifungal drug resistance in several fungal pathogens. Blocking calcineurin signaling increases the efficacy of several currently available antifungals and suppresses drug resistance. We demonstrate the application of a novel scanning quadrupole DIA method for the analysis of changes in the proteins coimmunoprecipitated with calcineurin during therapeutic antifungal drug treatments of the deadly human fungal pathogen Aspergillus fumigatus. Our experimental design afforded an assessment of the precision of the method as demonstrated by peptide- and protein-centric analysis from eight replicates of the study pool QC samples. Two distinct classes of clinically relevant antifungal drugs that are guideline recommended for the treatment of invasive "aspergillosis" caused by Aspergillus fumigatus, the azoles (voriconazole) and the echinocandins (caspofungin and micafungin), which specifically target the fungal plasma membrane and the fungal cell wall, respectively, were chosen to distinguish variations occurring in the proteins coimmunoprecipitated with calcineurin. Novel potential interactors were identified in response to the different drug treatments that are indicative of the possible role for calcineurin in regulating these effectors. Notably, treatment with voriconazole showed increased immunoprecipitation of key proteins involved in membrane ergosterol biosynthesis with calcineurin. In contrast, echinocandin (caspofungin or micafungin) treatments caused increased immunoprecipitation of proteins involved in cell-wall biosynthesis and septation. Furthermore, abundant coimmunoprecipitation of ribosomal proteins with calcineurin occurred exclusively in echinocandins treatment, indicating reprogramming of cellular growth mechanisms during different antifungal drug treatments. While variations in the observed calcineurin immunoprecipitated proteins may also be due to changes in their expression levels under different drug treatments, this study suggests an important role for calcineurin-dependent cellular mechanisms in response to antifungal treatment of A. fumigatus that warrants future studies.

Evaluation of Parameters for Confident Phosphorylation Site Localization Using an Orbitrap Fusion Tribrid Mass Spectrometer.

Confident identification of sites of protein phosphorylation by mass spectrometry (MS) is essential to advance understanding of phosphorylation-mediated signaling events. However, the development of novel instrumentation requires that methods for MS data acquisition and its interrogation be evaluated and optimized for high-throughput phosphoproteomics. Here we compare and contrast eight MS acquisition methods on the novel tribrid Orbitrap Fusion MS platform using both a synthetic phosphopeptide library and a complex phosphopeptide-enriched cell lysate. In addition to evaluating multiple fragmentation regimes (HCD, EThcD, and neutral-loss-triggered ET(ca/hc)D) and analyzers for MS/MS (orbitrap (OT) versus ion trap (IT)), we also compare two commonly used bioinformatics platforms, Andromeda with PTM-score, and MASCOT with ptmRS for confident phosphopeptide identification and, crucially, phosphosite localization. Our findings demonstrate that optimal phosphosite identification is achieved using HCD fragmentation and high-resolution orbitrap-based MS/MS analysis, employing MASCOT/ptmRS for data interrogation. Although EThcD is optimal for confident site localization for a given PSM, the increased duty cycle compared with HCD compromises the numbers of phosphosites identified. Finally, our data highlight that a charge-state-dependent fragmentation regime and a multiple algorithm search strategy are likely to be of benefit for confident large-scale phosphosite localization.

The mzIdentML Data Standard Version 1.2, Supporting Advances in Proteome Informatics.

The first stable version of the Proteomics Standards Initiative mzIdentML open data standard (version 1.1) was published in 2012-capturing the outputs of peptide and protein identification software. In the intervening years, the standard has become well-supported in both commercial and open software, as well as a submission and download format for public repositories. Here we report a new release of mzIdentML (version 1.2) that is required to keep pace with emerging practice in proteome informatics. New features have been added to support: (1) scores associated with localization of modifications on peptides; (2) statistics performed at the level of peptides; (3) identification of cross-linked peptides; and (4) support for proteogenomics approaches. In addition, there is now improved support for the encoding of de novo sequencing of peptides, spectral library searches, and protein inference. As a key point, the underlying XML schema has only undergone very minor modifications to simplify as much as possible the transition from version 1.1 to version 1.2 for implementers, but there have been several notable updates to the format specification, implementation guidelines, controlled vocabularies and validation software. mzIdentML 1.2 can be described as backwards compatible, in that reading software designed for mzIdentML 1.1 should function in most cases without adaptation. We anticipate that these developments will provide a continued stable base for software teams working to implement the standard. All the related documentation is accessible at http://www.psidev.info/mzidentml.

The mzqLibrary--An open source Java library supporting the HUPO-PSI quantitative proteomics standard.

The mzQuantML standard has been developed by the Proteomics Standards Initiative for capturing, archiving and exchanging quantitative proteomic data, derived from mass spectrometry. It is a rich XML-based format, capable of representing data about two-dimensional features from LC-MS data, and peptides, proteins or groups of proteins that have been quantified from multiple samples. In this article we report the development of an open source Java-based library of routines for mzQuantML, called the mzqLibrary, and associated software for visualising data called the mzqViewer. The mzqLibrary contains routines for mapping (peptide) identifications on quantified features, inference of protein (group)-level quantification values from peptide-level values, normalisation and basic statistics for differential expression. These routines can be accessed via the command line, via a Java programming interface access or a basic graphical user interface. The mzqLibrary also contains several file format converters, including import converters (to mzQuantML) from OpenMS, Progenesis LC-MS and MaxQuant, and exporters (from mzQuantML) to other standards or useful formats (mzTab, HTML, csv). The mzqViewer contains in-built routines for viewing the tables of data (about features, peptides or proteins), and connects to the R statistical library for more advanced plotting options. The mzqLibrary and mzqViewer packages are available from https://code.google.com/p/mzq-lib/.

ProteoAnnotator--open source proteogenomics annotation software supporting PSI standards.

The recent massive increase in capability for sequencing genomes is producing enormous advances in our understanding of biological systems. However, there is a bottleneck in genome annotation--determining the structure of all transcribed genes. Experimental data from MS studies can play a major role in confirming and correcting gene structure--proteogenomics. However, there are some technical and practical challenges to overcome, since proteogenomics requires pipelines comprising a complex set of interconnected modules as well as bespoke routines, for example in protein inference and statistics. We are introducing a complete, open source pipeline for proteogenomics, called ProteoAnnotator, which incorporates a graphical user interface and implements the Proteomics Standards Initiative mzIdentML standard for each analysis stage. All steps are included as standalone modules with the mzIdentML library, allowing other groups to re-use the whole pipeline or constituent parts within other tools. We have developed new modules for pre-processing and combining multiple search databases, for performing peptide-level statistics on mzIdentML files, for scoring grouped protein identifications matched to a given genomic locus to validate that updates to the official gene models are statistically sound and for mapping end results back onto the genome. ProteoAnnotator is available from http://www.proteoannotator.org/. All MS data have been deposited in the ProteomeXchange with identifiers PXD001042 and PXD001390 (http://proteomecentral.proteomexchange.org/dataset/PXD001042; http://proteomecentral.proteomexchange.org/dataset/PXD001390).

Numerical compression schemes for proteomics mass spectrometry data.

The open XML format mzML, used for representation of MS data, is pivotal for the development of platform-independent MS analysis software. Although conversion from vendor formats to mzML must take place on a platform on which the vendor libraries are available (i.e. Windows), once mzML files have been generated, they can be used on any platform. However, the mzML format has turned out to be less efficient than vendor formats. In many cases, the naïve mzML representation is fourfold or even up to 18-fold larger compared with the original vendor file. In disk I/O limited setups, a larger data file also leads to longer processing times, which is a problem given the data production rates of modern mass spectrometers. In an attempt to reduce this problem, we here present a family of numerical compression algorithms called MS-Numpress, intended for efficient compression of MS data. To facilitate ease of adoption, the algorithms target the binary data in the mzML standard, and support in main proteomics tools is already available. Using a test set of 10 representative MS data files we demonstrate typical file size decreases of 90% when combined with traditional compression, as well as read time decreases of up to 50%. It is envisaged that these improvements will be beneficial for data handling within the MS community.

The utility of porous graphitic carbon as a stationary phase in proteomics workflows: two-dimensional chromatography of complex peptide samples.

We present the first investigation into the utility of porous graphitic carbon (PGC) as a stationary phase in proteomic workflows involving complex samples. PGC offers chemical and physical robustness and is capable of withstanding extremes of pH and higher temperatures than traditional stationary phases, without the likelihood of catastrophic failure. In addition, unlike separations driven by ion exchange mechanisms, there is no requirement for high levels of non-volatile salts such as potassium chloride in the elution buffers, which must be removed prior to LC-MS analysis. Here we present data which demonstrate that PGC affords excellent peptide separation in a complex whole cell lysate digest sample, with good orthogonality to a typical low pH reversed-phase system. As strong cation exchange (SCX) is currently the most popular first dimension for 2D peptide separations, we chose to compare the performance of a PGC and SCX separation as the first dimension in a comprehensive 2D-LC-MS/MS workflow. A significant increase, in the region of 40%, in peptide identifications is reported with off-line PGC fractionation compared to SCX. Around 14,000 unique peptides were identified at an estimated false discovery rate of 1% (n=3 replicates) from starting material constituting only 100 µg of protein extract.

Web-based design and evaluation of T-cell vaccine candidates.

UNLABELLED: We present a suite of on-line tools to design candidate vaccine proteins, and to assess antigen potential, using coverage of k-mers (as proxies for potential T-cell epitopes) as a metric. The vaccine design tool uses the recently published 'mosaic' method to generate protein sequences optimized for coverage of high-frequency k-mers; the coverage-assessment tools facilitate coverage comparisons for any potential antigens. To demonstrate these tools, we designed mosaic protein sets for B-clade HIV-1 Gag, Pol and Nef, and compared them to antigens used in a recent human vaccine trial. AVAILABILITY: http://hiv.lanl.gov/content/sequence/MOSAIC/.

Polyvalent vaccines for optimal coverage of potential T-cell epitopes in global HIV-1 variants.

HIV-1/AIDS vaccines must address the extreme diversity of HIV-1. We have designed new polyvalent vaccine antigens comprised of sets of 'mosaic' proteins, assembled from fragments of natural sequences via a computational optimization method. Mosaic proteins resemble natural proteins, and a mosaic set maximizes the coverage of potential T-cell epitopes (peptides of nine amino acids) for a viral population. We found that coverage of viral diversity using mosaics was greatly increased compared to coverage by natural-sequence vaccine candidates, for both variable and conserved proteins; for conserved HIV-1 proteins, global coverage may be feasible. For example, four mosaic proteins perfectly matched 74% of 9-amino-acid potential epitopes in global Gag sequences; 87% of potential epitopes matched at least 8 of 9 positions. In contrast, a single natural Gag protein covered only 37% (9 of 9) and 67% (8 of 9). Mosaics provide diversity coverage comparable to that afforded by thousands of separate peptides, but, because the fragments of natural proteins are compressed into a small number of native-like proteins, they are tractable for vaccines.

Accurate on-line support vector regression.

Batch implementations of support vector regression (SVR) are inefficient when used in an on-line setting because they must be retrained from scratch every time the training set is modified. Following an incremental support vector classification algorithm introduced by Cauwenberghs and Poggio (2001), we have developed an accurate on-line support vector regression (AOSVR) that efficiently updates a trained SVR function whenever a sample is added to or removed from the training set. The updated SVR function is identical to that produced by a batch algorithm. Applications of AOSVR in both on-line and cross-validation scenarios are presented. In both scenarios, numerical experiments indicate that AOSVR is faster than batch SVR algorithms with both cold and warm start.