Bone health in women with premature ovarian insufficiency/early menopause: a 23-year longitudinal analysis

STUDY QUESTION

What is the frequency of, and predictors for, osteoporosis, fractures, and osteoporosis management (investigation, treatment) in women with premature ovarian insufficiency (POI; menopause <40 years) and early menopause (EM; menopause 40-44years)?

SUMMARY ANSWER

Over the 23-year follow-up duration, at a mean age of 68 years, women with POI/EM had higher osteoporosis/fracture risk and prevalence, higher osteoporosis screening and anti-osteoporosis medication use compared to women with usual age menopause; increasing age was predictive of increased risk of osteoporosis/fracture and menopause hormone therapy (MHT) prior to or at study entry (aged 45-50 years) was protective.

WHAT IS KNOWN ALREADY

Women with POI/EM have increased risk of osteoporosis and fractures with limited data regarding risk factors for reduced bone density and fractures. Clinical guidelines recommend screening with dual X-ray absorptiometry (DXA) and treatment with MHT for most women with POI/EM to reduce osteoporosis and fracture risk; however, studies indicate gaps in osteoporosis knowledge, guideline uptake, and management adherence by clinicians and women.

STUDY DESIGN, SIZE, DURATION

The Australian Longitudinal Study on Women's Health is a prospective longitudinal study of Australian women. This study uses the cohort of women born between 1946 and 1951, surveyed nine times between 1996 and 2019. Data from the Australian administrative health records, including hospital admissions data (fractures, osteoporosis), Medicare Benefits Schedule (DXA), and the Pharmaceutical Benefits Scheme (PBS; MHT, anti-osteoporosis medication, available only from 2002) were linked to survey data.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Survey respondents with self-reported age of menopause were included. POI/EM was defined as menopause <45 years. T-test or chi-square were used for comparisons at baseline (P < 0.05 indicates significance). Generalized estimating equations for panel data explored predictors for the longitudinal outcomes of osteoporosis, fractures, DXA rates, MHT use, and anti-osteoporosis medication (in women with osteoporosis/fracture, from Survey 4 onwards only). Univariable regression was performed, and variables retained where P < 0.2, to form the multivariable model, and bootstrapping with 100 repetitions at 95% sampling of the original dataset to ensure robustness of results.

MAIN RESULTS AND THE ROLE OF CHANCE

Eight thousand six hundred and three women were included: 610 (7.1%) with POI/EM. Mean (SD) baseline age was 47.6 (1.45) years in the entire cohort and mean (SD) age of menopause was 38.2 (7.95) and 51.3 (3.04) years in women with POI/EM and usual age menopause, respectively (P < 0.001). Over the 23 years, of women with POI/EM, 303 (49.7%) had osteoporosis/fractures, 421 (69.0%) had DXA screening, 474 ever used MHT (77.7%), and 116 (39.1%) of those with osteoporosis/fractures used anti-osteoporosis medication. Of women with usual age menopause, 2929 (36.6%) had osteoporosis/fractures, 4920 (61.6%) had DXA screening, 4014 (50.2%) used MHT, and 964 (33.0%) of those with osteoporosis/fractures used anti-osteoporosis medication. Compared to women with menopause at age ≥45 years and after adjusting for other risk factors, women with POI/EM had increased risk of osteoporosis (odds ratio [OR] 1.37; 95% CI 1.07-1.77), fractures (OR 1.45; 1.15-1.81), DXA testing (OR 1.64; 1.42-1.90), MHT use (OR 6.87; 5.68-8.30), and anti-osteoporosis medication use (OR 1.50; 1.14-1.98). In women with POI/EM women, increasing age was associated with greater risk of osteoporosis/fracture (OR 1.09; 1.08-1.11), and MHT prior to or at study entry (aged 45-50 years), was protective (OR 0.65, 0.45-0.96). In women with POI/EM, age (OR 1.11; 1.10-1.12), fractures (OR 1.80, 1.38-2.34), current smoking (OR 0.60; 0.43-0.86), and inner (OR 0.68; 0.53-0.88) or outer regional (OR 0.63; 0.46-0.87) residential location were associated with DXA screening. In women with POI/EM, increasing age (OR 1.02; 1.01-1.02), and currently consuming alcohol (OR 1.17; 1.06-1.28), was associated with having ever used MHT. In the 299 women with POI/EM and osteoporosis/fractures, only 39.1% ever received treatment with an anti-osteoporosis medication. Increasing age (OR 1.07; 1.04-1.09) and lower BMI (OR 0.95; 0.92-0.98) were associated with greater likelihood of treatment with anti-osteoporosis medication.

LIMITATIONS, REASONS FOR CAUTION

Survey data including age of menopause were self-reported by participants; fracture questions were not included in the 2001 survey, and location or level of trauma of self-reported fractures was not asked. Additional risk/protective factors such as vitamin D status, calcium intake, and exercise were not able to be included. Due to sample size, POI and EM were combined for all analyses, and we were unable to differentiate between causes of POI/EM. PBS data were only available from 2004, and hospital admissions data were state-based, with all of Australia were only available from 2007.

WIDER IMPLICATIONS OF THE FINDINGS

This study supports previous literature indicating increased risk of osteoporosis and fractures in women with POI, and adds evidence for women with POI/EM, where there was a relative paucity of data. This is the first study to analyse a variety of clinical and demographic risk factors for osteoporosis and fractures in women with POI/EM, as well as analysing investigation and treatment rates. In these women, using MHT prior to or at study entry, aged 45-50 years, was protective for osteoporosis/fractures; however, having ever used MHT was not, highlighting the importance of early treatment with MHT in these women to preserve bone strength. Although women with POI/EM and osteoporosis or fractures were more likely to use anti-osteoporosis medications than those with usual age menopause, overall treatment rates are low at <40%, demonstrating a significant treatment gap that should be addressed to reduce future fracture risk.

STUDY FUNDING/COMPETING INTEREST(S)

This study was funded by The Australian NHMRC Centre of Research Excellence Women's Health in Reproductive Life (CRE-WHIRL, project number APP1171592). A.R.J. is the recipient of a National Health and Medical Research Council post-graduate research scholarship (grant number 1169192). P.R.E. is supported by a National Health and Medical Research Council grant 1197958. P.R.E. reports grants paid to their institution from Amgen, Sanofi, and Alexion, honoraria from Amgen paid to their institution, and honoraria from Alexion and Kyowa-Kirin.

TRIAL REGISTRATION NUMBER

N/A.

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.

A meta-analysis of rice phosphoproteomics data to understand variation in cell signalling across the rice pan-genome

Phosphorylation is the most studied post-translational modification, and has multiple biological functions. In this study, we have re-analysed publicly available mass spectrometry proteomics datasets enriched for phosphopeptides from Asian rice (Oryza sativa). In total we identified 15,522 phosphosites on serine, threonine and tyrosine residues on rice proteins. We identified sequence motifs for phosphosites, and link motifs to enrichment of different biological processes, indicating different downstream regulation likely caused by different kinase groups. We cross-referenced phosphosites against the rice 3,000 genomes, to identify single amino acid variations (SAAVs) within or proximal to phosphosites that could cause loss of a site in a given rice variety. The data was clustered to identify groups of sites with similar patterns across rice family groups, for example those highly conserved in Japonica, but mostly absent in Aus type rice varieties - known to have different responses to drought. These resources can assist rice researchers to discover alleles with significantly different functional effects across rice varieties. The data has been loaded into UniProt Knowledge-Base - enabling researchers to visualise sites alongside other data on rice proteins e.g. structural models from AlphaFold2, PeptideAtlas and the PRIDE database - enabling visualisation of source evidence, including scores and supporting mass spectra.

A systems approach reveals species differences in hepatic stress response capacity

To minimize the occurrence of unexpected toxicities in early phase preclinical studies of new drugs, it is vital to understand fundamental similarities and differences between preclinical species and humans. Species differences in sensitivity to acetaminophen (APAP) liver injury have been related to differences in the fraction of the drug that is bioactivated to the reactive metabolite N-acetyl-p-benzoquinoneimine (NAPQI). We have used physiologically based pharmacokinetic modeling to identify oral doses of APAP (300 and 1000 mg/kg in mice and rats, respectively) yielding similar hepatic burdens of NAPQI to enable the comparison of temporal liver tissue responses under conditions of equivalent chemical insult. Despite pharmacokinetic and biochemical verification of the equivalent NAPQI insult, serum biomarker and tissue histopathology analyses revealed that mice still exhibited a greater degree of liver injury than rats. Transcriptomic and proteomic analyses highlighted the stronger activation of stress response pathways (including the Nrf2 oxidative stress response and autophagy) in the livers of rats, indicative of a more robust transcriptional adaptation to the equivalent insult. Components of these pathways were also found to be expressed at a higher basal level in the livers of rats compared with both mice and humans. Our findings exemplify a systems approach to understanding differential species sensitivity to hepatotoxicity. Multiomics analysis indicated that rats possess a greater basal and adaptive capacity for hepatic stress responses than mice and humans, with important implications for species selection and human translation in the safety testing of new drug candidates associated with reactive metabolite formation.

GET_PANGENES: calling pangenes from plant genome alignments confirms presence-absence variation

Crop pangenomes made from individual cultivar assemblies promise easy access to conserved genes, but genome content variability and inconsistent identifiers hamper their exploration. To address this, we define pangenes, which summarize a species coding potential and link back to original annotations. The protocol get_pangenes performs whole genome alignments (WGA) to call syntenic gene models based on coordinate overlaps. A benchmark with small and large plant genomes shows that pangenes recapitulate phylogeny-based orthologies and produce complete soft-core gene sets. Moreover, WGAs support lift-over and help confirm gene presence-absence variation. Source code and documentation: https://github.com/Ensembl/plant-scripts .

Assessing Multiple Evidence Streams to Decide on Confidence for Identification of Post-Translational Modifications, within and Across Data Sets

Phosphorylation is a post-translational modification of great interest to researchers due to its relevance in many biological processes. LC-MS/MS techniques have enabled high-throughput data acquisition, with studies claiming identification and localization of thousands of phosphosites. The identification and localization of phosphosites emerge from different analytical pipelines and scoring algorithms, with uncertainty embedded throughout the pipeline. For many pipelines and algorithms, arbitrary thresholding is used, but little is known about the actual global false localization rate in these studies. Recently, it has been suggested to use decoy amino acids to estimate global false localization rates of phosphosites, among the peptide-spectrum matches reported. Here, we describe a simple pipeline aiming to maximize the information extracted from these studies by objectively collapsing from peptide-spectrum match to the peptidoform-site level, as well as combining findings from multiple studies while maintaining track of false localization rates. We show that the approach is more effective than current processes that use a simpler mechanism for handling phosphosite identification redundancy within and across studies. In our case study using eight rice phosphoproteomics data sets, 6368 unique sites were confidently identified using our decoy approach compared to 4687 using traditional thresholding in which false localization rates are unknown.

Integrated View of Baseline Protein Expression in Human Tissues

The availability of proteomics datasets in the public domain, and in the PRIDE database, in particular, has increased dramatically in recent years. This unprecedented large-scale availability of data provides an opportunity for combined analyses of datasets to get organism-wide protein abundance data in a consistent manner. We have reanalyzed 24 public proteomics datasets from healthy human individuals to assess baseline protein abundance in 31 organs. We defined tissue as a distinct functional or structural region within an organ. Overall, the aggregated dataset contains 67 healthy tissues, corresponding to 3,119 mass spectrometry runs covering 498 samples from 489 individuals. We compared protein abundances between different organs and studied the distribution of proteins across these organs. We also compared the results with data generated in analogous studies. Additionally, we performed gene ontology and pathway-enrichment analyses to identify organ-specific enriched biological processes and pathways. As a key point, we have integrated the protein abundance results into the resource Expression Atlas, where they can be accessed and visualized either individually or together with gene expression data coming from transcriptomics datasets. We believe this is a good mechanism to make proteomics data more accessible for life scientists.

Proteomics Standards Initiative at Twenty Years: Current Activities and Future Work

The Human Proteome Organization (HUPO) Proteomics Standards Initiative (PSI) has been successfully developing guidelines, data formats, and controlled vocabularies (CVs) for the proteomics community and other fields supported by mass spectrometry since its inception 20 years ago. Here we describe the general operation of the PSI, including its leadership, working groups, yearly workshops, and the document process by which proposals are thoroughly and publicly reviewed in order to be ratified as PSI standards. We briefly describe the current state of the many existing PSI standards, some of which remain the same as when originally developed, some of which have undergone subsequent revisions, and some of which have become obsolete. Then the set of proposals currently being developed are described, with an open call to the community for participation in the forging of the next generation of standards. Finally, we describe some synergies and collaborations with other organizations and look to the future in how the PSI will continue to promote the open sharing of data and thus accelerate the progress of the field of proteomics.

TriTrypDB: An integrated functional genomics resource for kinetoplastida

Parasitic diseases caused by kinetoplastid parasites are a burden to public health throughout tropical and subtropical regions of the world. TriTrypDB (https://tritrypdb.org) is a free online resource for data mining of genomic and functional data from these kinetoplastid parasites and is part of the VEuPathDB Bioinformatics Resource Center (https://veupathdb.org). As of release 59, TriTrypDB hosts 83 kinetoplastid genomes, nine of which, including Trypanosoma brucei brucei TREU927, Trypanosoma cruzi CL Brener and Leishmania major Friedlin, undergo manual curation by integrating information from scientific publications, high-throughput assays and user submitted comments. TriTrypDB also integrates transcriptomic, proteomic, epigenomic, population-level and isolate data, functional information from genome-wide RNAi knock-down and fluorescent tagging, and results from automated bioinformatics analysis pipelines. TriTrypDB offers a user-friendly web interface embedded with a genome browser, search strategy system and bioinformatics tools to support custom in silico experiments that leverage integrated data. A Galaxy workspace enables users to analyze their private data (e.g., RNA-sequencing, variant calling, etc.) and explore their results privately in the context of publicly available information in the database. The recent addition of an annotation platform based on Apollo enables users to provide both functional and structural changes that will appear as 'community annotations' immediately and, pending curatorial review, will be integrated into the official genome annotation.

The INSR/AKT/mTOR pathway regulates the pace of myogenesis in a syndecan-3-dependent manner

Muscle stem cells (MuSCs) are indispensable for muscle regeneration. A multitude of extracellular stimuli direct MuSC fate decisions from quiescent progenitors to differentiated myocytes. The activity of these signals is modulated by coreceptors such as syndecan-3 (SDC3). We investigated the global landscape of SDC3-mediated regulation of myogenesis using a phosphoproteomics approach which revealed, with the precision level of individual phosphosites, the large-scale extent of SDC3-mediated regulation of signal transduction in MuSCs. We then focused on INSR/AKT/mTOR as a key pathway regulated by SDC3 during myogenesis and mechanistically dissected SDC3-mediated inhibition of insulin receptor signaling in MuSCs. SDC3 interacts with INSR ultimately limiting signal transduction via AKT/mTOR. Both knockdown of INSR and inhibition of AKT rescue Sdc3^-/- MuSC differentiation to wild type levels. Since SDC3 is rapidly downregulated at the onset of differentiation, our study suggests that SDC3 acts a timekeeper to restrain proliferating MuSC response and prevent premature differentiation.

Is DIA proteomics data FAIR? Current data sharing practices, available bioinformatics infrastructure and recommendations for the future

Data independent acquisition (DIA) proteomics techniques have matured enormously in recent years, thanks to multiple technical developments in e.g. instrumentation and data analysis approaches. However, there are many improvements that are still possible for DIA data in the area of the FAIR (Findability, Accessibility, Interoperability and Reusability) data principles. These include more tailored data sharing practices and open data standards, since public databases and data standards for proteomics were mostly designed with DDA data in mind. Here we first describe the current state of the art in the context of FAIR data for proteomics in general, and for DIA approaches in particular. For improving the current situation for DIA data, we make the following recommendations for the future: (i) development of an open data standard for spectral libraries; (ii) make mandatory the availability of the spectral libraries used in DIA experiments in ProteomeXchange resources; (iii) improve the support for DIA data in the data standards developed by the Proteomics Standards Initiative; and (iv) improve the support for DIA datasets in ProteomeXchange resources, including more tailored metadata requirements. This article is protected by copyright. All rights reserved.

Method for Independent Estimation of the False Localization Rate for Phosphoproteomics

Phosphoproteomic methods are commonly employed to identify and quantify phosphorylation sites on proteins. In recent years, various tools have been developed, incorporating scores or statistics related to whether a given phosphosite has been correctly identified or to estimate the global false localization rate (FLR) within a given data set for all sites reported. These scores have generally been calibrated using synthetic datasets, and their statistical reliability on real datasets is largely unknown, potentially leading to studies reporting incorrectly localized phosphosites, due to inadequate statistical control. In this work, we develop the concept of scoring modifications on a decoy amino acid, that is, one that cannot be modified, to allow for independent estimation of global FLR. We test a variety of amino acids, on both synthetic and real data sets, demonstrating that the selection can make a substantial difference to the estimated global FLR. We conclude that while several different amino acids might be appropriate, the most reliable FLR results were achieved using alanine and leucine as decoys. We propose the use of a decoy amino acid to control false reporting in the literature and in public databases that re-distribute the data. Data are available via ProteomeXchange with identifier PXD028840.

Profiling the Human Phosphoproteome to Estimate the True Extent of Protein Phosphorylation

Public phosphorylation databases such as PhosphoSitePlus (PSP) and PeptideAtlas (PA) compile results from published papers or openly available mass spectrometry (MS) data. However, there is no database-level control for false discovery of sites, likely leading to the overestimation of true phosphosites. By profiling the human phosphoproteome, we estimate the false discovery rate (FDR) of phosphosites and predict a more realistic count of true identifications. We rank sites into phosphorylation likelihood sets and analyze them in terms of conservation across 100 species, sequence properties, and functional annotations. We demonstrate significant differences between the sets and develop a method for independent phosphosite FDR estimation. Remarkably, we report estimated FDRs of 84, 98, and 82% within sets of phosphoserine (pSer), phosphothreonine (pThr), and phosphotyrosine (pTyr) sites, respectively, that are supported by only a single piece of identification evidence─the majority of sites in PSP. We estimate that around 62 000 Ser, 8000 Thr, and 12 000 Tyr phosphosites in the human proteome are likely to be true, which is lower than most published estimates. Furthermore, our analysis estimates that 86 000 Ser, 50 000 Thr, and 26 000 Tyr phosphosites are likely false-positive identifications, highlighting the significant potential of false-positive data to be present in phosphorylation databases.

A Thermodynamic Model for Interpreting Tryptophan Excitation-Energy-Dependent Fluorescence Spectra Provides Insight Into Protein Conformational Sampling and Stability

It is now over 30 years since Demchenko and Ladokhin first posited the potential of the tryptophan red edge excitation shift (REES) effect to capture information on protein molecular dynamics. While there have been many key efforts in the intervening years, a biophysical thermodynamic model to quantify the relationship between the REES effect and protein flexibility has been lacking. Without such a model the full potential of the REES effect cannot be realized. Here, we present a thermodynamic model of the tryptophan REES effect that captures information on protein conformational flexibility, even with proteins containing multiple tryptophan residues. Our study incorporates exemplars at every scale, from tryptophan in solution, single tryptophan peptides, to multitryptophan proteins, with examples including a structurally disordered peptide, de novo designed enzyme, human regulatory protein, therapeutic monoclonal antibodies in active commercial development, and a mesophilic and hyperthermophilic enzyme. Combined, our model and data suggest a route forward for the experimental measurement of the protein REES effect and point to the potential for integrating biomolecular simulation with experimental data to yield novel insights.

Characterising proteolysis during SARS-CoV-2 infection identifies viral cleavage sites and cellular targets with therapeutic potential

SARS-CoV-2 is the causative agent behind the COVID-19 pandemic, responsible for over 170 million infections, and over 3.7 million deaths worldwide. Efforts to test, treat and vaccinate against this pathogen all benefit from an improved understanding of the basic biology of SARS-CoV-2. Both viral and cellular proteases play a crucial role in SARS-CoV-2 replication. Here, we study proteolytic cleavage of viral and cellular proteins in two cell line models of SARS-CoV-2 replication using mass spectrometry to identify protein neo-N-termini generated through protease activity. We identify previously unknown cleavage sites in multiple viral proteins, including major antigens S and N: the main targets for vaccine and antibody testing efforts. We discover significant increases in cellular cleavage events consistent with cleavage by SARS-CoV-2 main protease, and identify 14 potential high-confidence substrates of the main and papain-like proteases. We show that siRNA depletion of these cellular proteins inhibits SARS-CoV-2 replication, and that drugs targeting two of these proteins: the tyrosine kinase SRC and Ser/Thr kinase MYLK, show a dose-dependent reduction in SARS-CoV-2 titres. Overall, our study provides a powerful resource to understand proteolysis in the context of viral infection, and to inform the development of targeted strategies to inhibit SARS-CoV-2 and treat COVID-19.

Soil organic carbon is significantly associated with the pore geometry, microbial diversity and enzyme activity of the macro-aggregates under different land uses

Microbial activity strongly influences the stabilization of soil organic matter (SOM), and is affected by the abiotic properties within soil aggregates, which tend to differ between land uses. Here, we assessed the effects of SOM and pore geometry on the diversity and activity of microbial communities within aggregates formed under different land uses (undisturbed, plantation, pasture, and cropping). X-ray micro-computed tomography (μCT) revealed that macro-aggregates (2-8 mm) of undisturbed soils were porous, highly-connected, and had 200% more macro-pores compared with those from pasture and cropping soils. While the macro-aggregates of undisturbed soils had greater soil organic carbon (SOC) contents and N-acetyl β-glucosaminidase, β-glucosidase, and phosphatase activities, those of cropped soils harboured more diverse bacterial communities. Organic carbon was positively associated with the porosity of the macro-aggregates, which was negatively associated with microbial diversity and positively associated with enzyme activity. Thus, the biophysical processes in macro-aggregates may be important for SOC stabilization within the macro-aggregates.

MHCVision: estimation of global and local false discovery rate for MHC class I peptide binding prediction

Motivation

MHC-peptide binding prediction has been widely used for understanding the immune response of individuals or populations, each carrying different MHC molecules as well as for the development of immunotherapeutics. The results from MHC-peptide binding prediction tools are mostly reported as a predicted binding affinity (IC₅₀) and the percentile rank score, and global thresholds e.g. IC₅₀ value < 500 nM or percentile rank < 2% are generally recommended for distinguishing binding peptides from non-binding peptides. However, it is difficult to evaluate statistically the probability of an individual peptide binding prediction to be true or false solely considering predicted scores. Therefore, statistics describing the overall global false discovery rate (FDR) and local FDR, also called posterior error probability (PEP) are required to give statistical context to the natively produced scores.

Result

We have developed an algorithm and code implementation, called MHCVision, for estimation of FDR and PEP values for the predicted results of MHC-peptide binding prediction from the NetMHCpan tool. MHCVision performs parameter estimation using a modified expectation maximization framework for a two-component beta mixture model, representing the distribution of true and false scores of the predicted dataset. We can then estimate the PEP of an individual peptide’s predicted score, and conversely the probability that it is true. We demonstrate that the use of global FDR and PEP estimation can provide a better trade-off between sensitivity and precision over using currently recommended thresholds from tools.

Availability and implementation

https://github.com/PGB-LIV/MHCVision.

Supplementary information

Supplementary data are available at Bioinformatics online.

lcmsWorld: High-Performance 3D Visualization Software for Mass Spectrometry

Complex biological samples, in particular, in proteomics and metabolomics research, are often analyzed using mass spectrometry paired with liquid chromatography or gas chromatography. The chromatography stage adds a third dimension (retention time) to the usual 2D mass spectrometry output (mass/charge, detected ion counts). Experimental results are often discovered by complex computational analysis, but it is not always possible to know if the data has been correctly interpreted. To perform quality-control checks, it can often be helpful to verify the results by manually examining the raw data, and it is typically easier to understand the data in a graphical, rather than numerical, form. 3D graphics hardware is present in most modern computers but is rarely utilized by bioinformatics software, even when the data to be viewed are naturally 3D. lcmsWorld is new software that uses graphics hardware to quickly and smoothly examine and compare LC-MS data. A preprocessing step allows the software to subsequently access any area of the data instantly at multiple levels of detail. The data can then be freely navigated while the software automatically selects, loads, and displays the most appropriate detail. lcmsWorld is open source. Releases, source code, and example data files are available via https://github.com/PGB-LIV/lcmsWorld.

A Proteome-Wide Immunoinformatics Tool to Accelerate T-Cell Epitope Discovery and Vaccine Design in the Context of Emerging Infectious Diseases: An Ethnicity-Oriented Approach

Emerging infectious diseases (EIDs) caused by viruses are increasing in frequency, causing a high disease burden and mortality world-wide. The COVID-19 pandemic caused by the novel SARS-like coronavirus (SARS-CoV-2) underscores the need to innovate and accelerate the development of effective vaccination strategies against EIDs. Human leukocyte antigen (HLA) molecules play a central role in the immune system by determining the peptide repertoire displayed to the T-cell compartment. Genetic polymorphisms of the HLA system thus confer a strong variability in vaccine-induced immune responses and may complicate the selection of vaccine candidates, because the distribution and frequencies of HLA alleles are highly variable among different ethnic groups. Herein, we build on the emerging paradigm of rational epitope-based vaccine design, by describing an immunoinformatics tool (Predivac-3.0) for proteome-wide T-cell epitope discovery that accounts for ethnic-level variations in immune responsiveness. Predivac-3.0 implements both CD8+ and CD4+ T-cell epitope predictions based on HLA allele frequencies retrieved from the Allele Frequency Net Database. The tool was thoroughly assessed, proving comparable performances (AUC ~0.9) against four state-of-the-art pan-specific immunoinformatics methods capable of population-level analysis (NetMHCPan-4.0, Pickpocket, PSSMHCPan and SMM), as well as a strong accuracy on proteome-wide T-cell epitope predictions for HIV-specific immune responses in the Japanese population. The utility of the method was investigated for the COVID-19 pandemic, by performing in silico T-cell epitope mapping of the SARS-CoV-2 spike glycoprotein according to the ethnic context of the countries where the ChAdOx1 vaccine is currently initiating phase III clinical trials. Potentially immunodominant CD8+ and CD4+ T-cell epitopes and population coverages were predicted for each population (the Epitope Discovery mode), along with optimized sets of broadly recognized (promiscuous) T-cell epitopes maximizing coverage in the target populations (the Epitope Optimization mode). Population-specific epitope-rich regions (T-cell epitope clusters) were further predicted in protein antigens based on combined criteria of epitope density and population coverage. Overall, we conclude that Predivac-3.0 holds potential to contribute in the understanding of ethnic-level variations of vaccine-induced immune responsiveness and to guide the development of epitope-based next-generation vaccines against emerging pathogens, whose geographic distributions and populations in need of vaccinations are often well-defined for regional epidemics.

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.

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 (ML).

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.

Evidence Against Carbonization of the Thin-Film Filters of the Extreme Ultraviolet Variability Experiment onboard the Solar Dynamics Observatory

In spite of strict limits on outgassing from organic materials, some spacecraft instruments making long-term measurements of solar extreme ultraviolet (EUV) radiation still suffer significant degradation. While such measures have reduced the rate of degradation, they have not completely eliminated it in some cases. For example, in five years, the aluminum filters used in the Extreme Ultraviolet Variability Experiment (EVE) instruments onboard the Solar Dynamics Observatory (SDO) suffered losses exceeding 40% at 30.4 nm. Comparing those losses with the negligible losses of nearby zirconium filters on the same instruments indicated that the problem was not due to carbonization on the Sun-facing side of the filter. To investigate whether the loss was due to carbon deposition on the downstream face of the Al filter, we exposed the backsides of Al and Zr filters to EUV in the presence of a volatile organic solvent in the laboratory and concluded that this could not be the cause. Given that the residual gas composition in the SDO spacecraft likely has water vapor as well as organics, these findings suggest that the transmission loss in the Al filter originated with oxidation caused by UV-activated adsorbed water.

mzMLb: A Future-Proof Raw Mass Spectrometry Data Format Based on Standards-Compliant mzML and Optimized for Speed and Storage Requirements

With ever-increasing amounts of data produced by mass spectrometry (MS) proteomics and metabolomics, and the sheer volume of samples now analyzed, the need for a common open format possessing both file size efficiency and faster read/write speeds has become paramount to drive the next generation of data analysis pipelines. The Proteomics Standards Initiative (PSI) has established a clear and precise extensible markup language (XML) representation for data interchange, mzML, receiving substantial uptake; nevertheless, storage and file access efficiency has not been the main focus. We propose an HDF5 file format "mzMLb" that is optimized for both read/write speed and storage of the raw mass spectrometry data. We provide an extensive validation of the write speed, random read speed, and storage size, demonstrating a flexible format that with or without compression is faster than all existing approaches in virtually all cases, while with compression is comparable in size to proprietary vendor file formats. Since our approach uniquely preserves the XML encoding of the metadata, the format implicitly supports future versions of mzML and is straightforward to implement: mzMLb's design adheres to both HDF5 and NetCDF4 standard implementations, which allows it to be easily utilized by third parties due to their widespread programming language support. A reference implementation within the established ProteoWizard toolkit is provided.

A snapshot of human leukocyte antigen (HLA) diversity using data from the Allele Frequency Net Database

The extensive allelic variability observed in several genes related to the immune response and its significance in different areas including transplantation, disease association studies, diversity in human populations, among many others, has led the scientific community to analyse these variants among individuals. Serving as an electronic data warehouse, the Allele Frequency Net Database (AFND, http://www.allelefrequencies.net) contains data on the frequency of immune related genes and their corresponding alleles from more than 1700 worldwide population samples covering more than ten million unrelated individuals. The collection of population data sets available in AFND encompasses different polymorphic regions including the highly-polymorphic human leukocyte antigen (HLA) system for which more than 1200 populations are available. In this article, we provide an insight of the high diversity found in the HLA region by examining population data sets stored in AFND, as well as a description of the available data sets for further analyses.

Allele frequency net database (AFND) 2020 update: gold-standard data classification, open access genotype data and new query tools

The Allele Frequency Net Database (AFND, www.allelefrequencies.net) provides the scientific community with a freely available repository for the storage of frequency data (alleles, genes, haplotypes and genotypes) related to human leukocyte antigens (HLA), killer-cell immunoglobulin-like receptors (KIR), major histocompatibility complex Class I chain related genes (MIC) and a number of cytokine gene polymorphisms in worldwide populations. In the last five years, AFND has become more popular in terms of clinical and scientific usage, with a recent increase in genotyping data as a necessary component of Short Population Report article submissions to another scientific journal. In addition, we have developed a user-friendly desktop application for HLA and KIR genotype/population data submissions. We have also focused on classification of existing and new data into ‘gold–silver–bronze’ criteria, allowing users to filter and query depending on their needs. Moreover, we have also continued to expand other features, for example focussed on HLA associations with adverse drug reactions. At present, AFND contains >1600 populations from >10 million healthy individuals, making AFND a valuable resource for the analysis of some of the most polymorphic regions in the human genome.

VAPPER: High-throughput variant antigen profiling in African trypanosomes of livestock

BACKGROUND

Analysing variant antigen gene families on a population scale is a difficult challenge for conventional methods of read mapping and variant calling due to the great variability in sequence, copy number, and genomic loci. In African trypanosomes, hemoparasites of humans and animals, this is complicated by variant antigen repertoires containing hundreds of genes subject to various degrees of sequence recombination.

FINDINGS

We introduce Variant Antigen Profiler (VAPPER), a tool that allows automated analysis of the variant surface glycoprotein repertoires of the most prevalent livestock African trypanosomes. VAPPER produces variant antigen profiles for any isolate of the veterinary pathogens Trypanosoma congolense and Trypanosoma vivax from genomic and transcriptomic sequencing data and delivers publication-ready figures that show how the queried isolate compares with a database of existing strains. VAPPER is implemented in Python. It can be installed to a local Galaxy instance from the ToolShed (https://toolshed.g2.bx.psu.edu/) or locally on a Linux platform via the command line (https://github.com/PGB-LIV/VAPPER). The documentation, requirements, examples, and test data are provided in the Github repository.

CONCLUSION

By establishing two different, yet comparable methodologies, our approach is the first to allow large-scale analysis of African trypanosome variant antigens, large multi-copy gene families that are otherwise refractory to high-throughput analysis.

Informatics investigations into anti-thyroid drug induced agranulocytosis associated with multiple HLA-B alleles

INTRODUCTION

Adverse drug reactions have been linked with HLA alleles in different studies. These HLA proteins play an essential role in the adaptive immune response for the presentation of self and non-self peptides. Anti-thyroid drugs methimazole and propylthiouracil have been associated with drug induced agranulocytosis (severe lower white blood cell count) in patients with B*27:05, B*38:02 and DRB1*08:03 alleles in different populations: Taiwanese, Vietnamese, Han Chinese and Caucasian.

METHODS

In this study, informatics methods were used to investigate if any sequence or structural similarities exist between the two associated HLA-B alleles, compared with a set of "control" alleles assumed not be associated, which could help explain the molecular basis of the adverse drug reaction. We demonstrated using MHC Motif Viewer and MHCcluster that the two alleles do not have a propensity to bind similar peptides, and thus at a gross level the structure of the antigen presentation region of the two alleles are not similar. We also performed multiple sequence alignment to identify polymorphisms shared by the risk but not by the control alleles and molecular docking to compare the predicted binding poses of the drug-allele combinations.

RESULTS

Two residues, Cys67 and Thr80, were identified from the multiple sequence alignments to be unique to these risk alleles alone. The molecular docking showed the poses of the risk alleles to favour the F-pocket of the peptide binding groove, close to the Thr80 residue, with the control alleles generally favouring a different pocket. The data are thus suggestive that Thr80 may be a critical residue in HLA-mediated anti-thyroid drug induced agranulocytosis, and thus can guide future research and risk assessment.

Development of the MapMe intervention body image scales of known weight status for 4-5 and 10-11 year old children

Background

Parents tend to visually assess children to determine their weight status and typically underestimate child body size. A visual tool may aid parents to more accurately assess child weight status and so support strategies to reduce childhood overweight. Body image scales (BIS) are visual images of people ranging from underweight to overweight but none exist for children based on UK criteria. Our aim was to develop sex- and age-specific BIS for children, based on British growth reference (UK90) criteria.

Methods

BIS were developed using 3D surface body scans of children, their associated weight status using UK90 criteria from height and weight measurements, and qualitative work with parents and health professionals.

Results

Height, weight and 3D body scans were collected (211: 4–5 years; 177: 10–11 years). Overall, 12 qualitative sessions were held with 37 participants. Four BIS (4–5-year-old girls and boys, 10–11-year-old girls and boys) were developed.

Conclusions

This study has created the first sex- and age-specific BIS, based on UK90 criteria. The BIS have potential for use in child overweight prevention and management strategies, and in future research. This study also provides a protocol for the development of further BIS appropriate to other age groups and ethnicities.

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.

DNAscan: personal computer compatible NGS analysis, annotation and visualisation

BACKGROUND

Next Generation Sequencing (NGS) is a commonly used technology for studying the genetic basis of biological processes and it underpins the aspirations of precision medicine. However, there are significant challenges when dealing with NGS data. Firstly, a huge number of bioinformatics tools for a wide range of uses exist, therefore it is challenging to design an analysis pipeline. Secondly, NGS analysis is computationally intensive, requiring expensive infrastructure, and many medical and research centres do not have adequate high performance computing facilities and cloud computing is not always an option due to privacy and ownership issues. Finally, the interpretation of the results is not trivial and most available pipelines lack the utilities to favour this crucial step.

RESULTS

We have therefore developed a fast and efficient bioinformatics pipeline that allows for the analysis of DNA sequencing data, while requiring little computational effort and memory usage. DNAscan can analyse a whole exome sequencing sample in 1 h and a 40x whole genome sequencing sample in 13 h, on a midrange computer. The pipeline can look for single nucleotide variants, small indels, structural variants, repeat expansions and viral genetic material (or any other organism). Its results are annotated using a customisable variety of databases and are available for an on-the-fly visualisation with a local deployment of the gene.iobio platform. DNAscan is implemented in Python. Its code and documentation are available on GitHub: https://github.com/KHP-Informatics/DNAscan . Instructions for an easy and fast deployment with Docker and Singularity are also provided on GitHub.

CONCLUSIONS

DNAscan is an extremely fast and computationally efficient pipeline for analysis, visualization and interpretation of NGS data. It is designed to provide a powerful and easy-to-use tool for applications in biomedical research and diagnostic medicine, at minimal computational cost. Its comprehensive approach will maximise the potential audience of users, bringing such analyses within the reach of non-specialist laboratories, and those from centres with limited funding available.

mzTab-M: A Data Standard for Sharing Quantitative Results in Mass Spectrometry Metabolomics

Mass spectrometry (MS) is one of the primary techniques used for large-scale analysis of small molecules in metabolomics studies. To date, there has been little data format standardization in this field, as different software packages export results in different formats represented in XML or plain text, making data sharing, database deposition, and reanalysis highly challenging. Working within the consortia of the Metabolomics Standards Initiative, Proteomics Standards Initiative, and the Metabolomics Society, we have created mzTab-M to act as a common output format from analytical approaches using MS on small molecules. The format has been developed over several years, with input from a wide range of stakeholders. mzTab-M is a simple tab-separated text format, but importantly, the structure is highly standardized through the design of a detailed specification document, tightly coupled to validation software, and a mandatory controlled vocabulary of terms to populate it. The format is able to represent final quantification values from analyses, as well as the evidence trail in terms of features measured directly from MS (e.g., LC-MS, GC-MS, DIMS, etc.) and different types of approaches used to identify molecules. mzTab-M allows for ambiguity in the identification of molecules to be communicated clearly to readers of the files (both people and software). There are several implementations of the format available, and we anticipate widespread adoption in the field.

Allele Frequency Net Database

The allele frequency net database (AFND, http://www.allelefrequencies.net ) is an online web-based repository that contains information on the frequencies of immune-related genes and their corresponding alleles in worldwide human populations. At present, the system contains data from 1505 populations in more than ten million individuals on the frequency of genes from different polymorphic regions including data for the human leukocyte antigens (HLA) system. This resource has been widely used in a variety of contexts such as histocompatibility, immunology, epidemiology, pharmacogenetics, and population genetics, among many others. In this chapter, we present some of the more commonly used searching mechanisms and some of the most recent developments included in AFND.

Improvements to the Rice Genome Annotation Through Large-Scale Analysis of RNA-Seq and Proteomics Data Sets

Rice (Oryza sativa) is one of the most important worldwide crops. The genome has been available for over 10 years and has undergone several rounds of annotation. We created a comprehensive database of transcripts from 29 public RNA sequencing data sets, officially predicted genes from Ensembl plants, and common contaminants in which to search for protein-level evidence. We re-analyzed nine publicly accessible rice proteomics data sets. In total, we identified 420K peptide spectrum matches from 47K peptides and 8,187 protein groups. 4168 peptides were initially classed as putative novel peptides (not matching official genes). Following a strict filtration scheme to rule out other possible explanations, we discovered 1,584 high confidence novel peptides. The novel peptides were clustered into 692 genomic loci where our results suggest annotation improvements. 80% of the novel peptides had an ortholog match in the curated protein sequence set from at least one other plant species. For the peptides clustering in intergenic regions (and thus potentially new genes), 101 loci were identified, for which 43 had a high-confidence hit for a protein domain. Our results can be displayed as tracks on the Ensembl genome or other browsers supporting Track Hubs, to support re-annotation of the rice genome.

Does pre-operative anxiety and/or depression affect patient outcome after primary knee replacement arthroplasty?

BACKGROUND

Chronic pain is associated with psychological distress, most commonly manifested as anxiety and/or depression.

METHODS

In order to investigate the effect of such distress on outcome from knee arthroplasty, we prospectively investigated the anxiety and depression levels of 104 patients undergoing a total of 107 primary knee arthroplasty procedures and the outcomes they achieved pre-operatively and at six weeks, one year and seven years post-operatively. The Hospital Anxiety and Depression Scale was used to record psychological status. Oxford Knee Score and American Knee Society Score were used to record functional outcomes.

RESULTS

Forty-four percent (47/107) of the patients had an abnormal pre-operative anxiety and/or depression score. Mean anxiety and depression scores improved at six weeks and one year of follow-up, but then deteriorated slightly at seven years, albeit not back to baseline. Knee scores showed similar patterns over time. Regardless of pre-operative psychological status, mean AKSS Knee scores improved at six weeks and further improved at one year post-op. They then showed slight deterioration at seven years, but remained significantly better than pre-op.

CONCLUSIONS

Psychological distress is common in our patients pre-operatively. Improvements in knee pain and function as a result of surgery correlate well with lower levels of psychological distress post-operatively. Knee replacement surgery positively influences all of the outcome measures studied rather than recovery being negatively influenced by pre-operative states. Knee replacement arthroplasty is not contra-indicated by pre-operative psychological distress. Successful knee replacement improves knee pain and function, as well as symptoms of anxiety and depression. These improvements persist for many years after the surgery.

Critical assessment of approaches for molecular docking to elucidate associations of HLA alleles with adverse drug reactions

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All software assessed could dock Abacavir back into the risk allele structure but not always predict the exact binding mode.

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Most docking software assessed can distinguish between risk and control alleles.

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Docking performance can be degraded by using a homology model.

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Receptor flexibility can negatively affect the docking performance for complex HLA examples.

•

Using AutoDockFR cannot compensate for the added difficulty of docking to the unbound target.

Adverse drug reactions have been linked with genetic polymorphisms in HLA genes in numerous different studies. HLA proteins have an essential role in the presentation of self and non-self peptides, as part of the adaptive immune response. Amongst the associated drugs-allele combinations, anti-HIV drug Abacavir has been shown to be associated with the HLA-B*57:01 allele, and anti-epilepsy drug Carbamazepine with B*15:02, in both cases likely following the altered peptide repertoire model of interaction. Under this model, the drug binds directly to the antigen presentation region, causing different self peptides to be presented, which trigger an unwanted immune response. There is growing interest in searching for evidence supporting this model for other ADRs using bioinformatics techniques. In this study, in silico docking was used to assess the utility and reliability of well-known docking programs when addressing these challenging HLA-drug situations. The overall aim was to address the uncertainty of docking programs giving different results by completing a detailed comparative study of docking software, grounded in the MHC-ligand experimental structural data – for Abacavir and to a lesser extent Carbamazepine - in order to assess their performance. Four docking programs: SwissDock, ROSIE, AutoDock Vina and AutoDockFR, were used to investigate if each software could accurately dock the Abacavir back into the crystal structure for the protein arising from the known risk allele, and if they were able to distinguish between the HLA-associated and non-HLA-associated (control) alleles. The impact of using homology models on the docking performance and how using different parameters, such as including receptor flexibility, affected the docking performance were also investigated to simulate the approach where a crystal structure for a given HLA allele may be unavailable. The programs that were best able to predict the binding position of Abacavir were then used to recreate the docking seen for Carbamazepine with B*15:02 and controls alleles.

It was found that the programs investigated were sometimes able to correctly predict the binding mode of Abacavir with B*57:01 but not always. Each of the software packages that were assessed could predict the binding of Abacavir and Carbamazepine within the correct sub-pocket and, with the exception of ROSIE, was able to correctly distinguish between risk and control alleles. We found that docking to homology models could produce poorer quality predictions, especially when sequence differences impact the architecture of predicted binding pockets. Caution must therefore be used as inaccurate structures may lead to erroneous docking predictions. Incorporating receptor flexibility was found to negatively affect the docking performance for the examples investigated. Taken together, our findings help characterise the potential but also the limitations of computational prediction of drug-HLA interactions. These docking techniques should therefore always be used with care and alongside other methods of investigation, in order to be able to draw strong conclusions from the given results.

phpMs: A PHP-Based Mass Spectrometry Utilities Library

The recent establishment of cloud computing, high-throughput networking, and more versatile web standards and browsers has led to a renewed interest in web-based applications. While traditionally big data has been the domain of optimized desktop and server applications, it is now possible to store vast amounts of data and perform the necessary calculations offsite in cloud storage and computing providers, with the results visualized in a high-quality cross-platform interface via a web browser. There are number of emerging platforms for cloud-based mass spectrometry data analysis; however, there is limited pre-existing code accessible to web developers, especially for those that are constrained to a shared hosting environment where Java and C applications are often forbidden from use by the hosting provider. To remedy this, we provide an open-source mass spectrometry library for one of the most commonly used web development languages, PHP. Our new library, phpMs, provides objects for storing and manipulating spectra and identification data as well as utilities for file reading, file writing, calculations, peptide fragmentation, and protein digestion as well as a software interface for controlling search engines. We provide a working demonstration of some of the capabilities at http://pgb.liv.ac.uk/phpMs .

A remotely triggered fast neutron detection instrument based on a plastic organic scintillator

A detector system for the characterization of radiation fields of both fast neutrons and γ rays is described comprising of a gated photomultiplier tube (PMT), an EJ299-33 solid organic scintillator detector, and an external trigger circuit. The objective of this development was to conceive a means by which the PMT in such a system can be actuated remotely during the high-intensity bursts of pulsed γ-ray contamination that can arise during active interrogation procedures. The system is used to detect neutrons and γ rays using established pulse-shape discrimination (PSD) techniques. The gating circuit enables the PMT to be switched off remotely. This is compatible with use during intense radiation transients to avoid saturation and the disruption of the operation of the PMT during the burst. Data are presented in the form of pulse-height spectra and PSD scatter plots for the system triggered with a strobed light source. These confirm that the gain of the system and the throughput for both triggered and un-triggered scenarios are as expected, given the duty cycle of the stimulating radiation. This demonstrates that the triggering function does not perturb the system response of the detector.

The proBAM and proBed standard formats: enabling a seamless integration of genomics and proteomics data

On behalf of The Human Proteome Organization (HUPO) Proteomics Standards Initiative, we introduce here two novel standard data formats, proBAM and proBed, that have been developed to address the current challenges of integrating mass spectrometry-based proteomics data with genomics and transcriptomics information in proteogenomics studies. proBAM and proBed are adaptations of the well-defined, widely used file formats SAM/BAM and BED, respectively, and both have been extended to meet the specific requirements entailed by proteomics data. Therefore, existing popular genomics tools such as SAMtools and Bedtools, and several widely used genome browsers, can already be used to manipulate and visualize these formats "out-of-the-box." We also highlight that a number of specific additional software tools, properly supporting the proteomics information available in these formats, are now available providing functionalities such as file generation, file conversion, and data analysis. All the related documentation, including the detailed file format specifications and example files, are accessible at http://www.psidev.info/probam and at http://www.psidev.info/probed .

The Instruments and Capabilities of the Miniature X-Ray Solar Spectrometer (MinXSS) CubeSats

The Miniature X-ray Solar Spectrometer (MinXSS) CubeSat is the first solar science oriented CubeSat mission flown for the NASA Science Mission Directorate, with the main objective of measuring the solar soft X-ray (SXR) flux and a science goal of determining its influence on Earth's ionosphere and thermosphere. These observations can also be used to investigate solar quiescent, active region, and flare properties. The MinXSS X-ray instruments consist of a spectrometer, called X123, with a nominal 0.15 keV full-width at half-maximum (FWHM) resolution at 5.9 keV and a broadband X-ray photometer, called XP. Both instruments are designed to obtain measurements from 0.5 - 30 keV at a nominal time cadence of 10 s. A description of the MinXSS instruments, performance capabilities, and relation to the Geostationary Operational Environmental Satellite (GOES) 0.1 - 0.8 nm flux is given in this article. Early MinXSS results demonstrate the capability of measuring variations of the solar spectral soft X-ray (SXR) flux between 0.8 - 12 keV from at least GOES A5-M5 ( 5 × 10 - 8 - 5 × 10 - 5 W m - 2 ) levels and of inferring physical properties (temperature and emission measure) from the MinXSS data alone. Moreover, coronal elemental abundances can be inferred, specifically for Fe, Ca, Si, Mg, S, Ar, and Ni, when the count rate is sufficiently high at each elemental spectral feature. Additionally, temperature response curves and emission measure loci demonstrate the MinXSS sensitivity to plasma emission at different temperatures. MinXSS observations coupled with those from other solar observatories can help address some of the most compelling questions in solar coronal physics. Finally, simultaneous observations by MinXSS and the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) can provide the most spectrally complete soft X-ray solar flare photon flux measurements to date.

nmrML: A Community Supported Open Data Standard for the Description, Storage, and Exchange of NMR Data

NMR is a widely used analytical technique with a growing number of repositories available. As a result, demands for a vendor-agnostic, open data format for long-term archiving of NMR data have emerged with the aim to ease and encourage sharing, comparison, and reuse of NMR data. Here we present nmrML, an open XML-based exchange and storage format for NMR spectral data. The nmrML format is intended to be fully compatible with existing NMR data for chemical, biochemical, and metabolomics experiments. nmrML can capture raw NMR data, spectral data acquisition parameters, and where available spectral metadata, such as chemical structures associated with spectral assignments. The nmrML format is compatible with pure-compound NMR data for reference spectral libraries as well as NMR data from complex biomixtures, i.e., metabolomics experiments. To facilitate format conversions, we provide nmrML converters for Bruker, JEOL and Agilent/Varian vendor formats. In addition, easy-to-use Web-based spectral viewing, processing, and spectral assignment tools that read and write nmrML have been developed. Software libraries and Web services for data validation are available for tool developers and end-users. The nmrML format has already been adopted for capturing and disseminating NMR data for small molecules by several open source data processing tools and metabolomics reference spectral libraries, e.g., serving as storage format for the MetaboLights data repository. The nmrML open access data standard has been endorsed by the Metabolomics Standards Initiative (MSI), and we here encourage user participation and feedback to increase usability and make it a successful standard.

Genome-wide association study of nevirapine hypersensitivity in a sub-Saharan African HIV-infected population

Background

The antiretroviral nevirapine is associated with hypersensitivity reactions in 6%-10% of patients, including hepatotoxicity, maculopapular exanthema, Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN).

Objectives

To undertake a genome-wide association study (GWAS) to identify genetic predisposing factors for the different clinical phenotypes associated with nevirapine hypersensitivity.

Methods

A GWAS was undertaken in a discovery cohort of 151 nevirapine-hypersensitive and 182 tolerant, HIV-infected Malawian adults. Replication of signals was determined in a cohort of 116 cases and 68 controls obtained from Malawi, Uganda and Mozambique. Interaction with ERAP genes was determined in patients positive for HLA-C*04:01 . In silico docking studies were also performed for HLA-C*04:01 .

Results

Fifteen SNPs demonstrated nominal significance ( P  <   1 × 10 -5 ) with one or more of the hypersensitivity phenotypes. The most promising signal was seen in SJS/TEN, where rs5010528 ( HLA-C locus) approached genome-wide significance ( P  <   8.5 × 10 -8 ) and was below HLA -wide significance ( P  <   2.5 × 10 -4 ) in the meta-analysis of discovery and replication cohorts [OR 4.84 (95% CI 2.71-8.61)]. rs5010528 is a strong proxy for HLA-C*04:01 carriage: in silico docking showed that two residues (33 and 123) in the B pocket were the most likely nevirapine interactors. There was no interaction between HLA-C*04:01 and ERAP1 , but there is a potential protective effect with ERAP2 [ P  =   0.019, OR 0.43 (95% CI 0.21-0.87)].

Conclusions

HLA-C*04:01 predisposes to nevirapine-induced SJS/TEN in sub-Saharan Africans, but not to other hypersensitivity phenotypes. This is likely to be mediated via binding to the B pocket of the HLA-C peptide. Whether this risk is modulated by ERAP2 variants requires further study.

Proteomics Standards Initiative: Fifteen Years of Progress and Future Work

The Proteomics Standards Initiative (PSI) of the Human Proteome Organization (HUPO) has now been developing and promoting open community standards and software tools in the field of proteomics for 15 years. Under the guidance of the chair, cochairs, and other leadership positions, the PSI working groups are tasked with the development and maintenance of community standards via special workshops and ongoing work. Among the existing ratified standards, the PSI working groups continue to update PSI-MI XML, MITAB, mzML, mzIdentML, mzQuantML, mzTab, and the MIAPE (Minimum Information About a Proteomics Experiment) guidelines with the advance of new technologies and techniques. Furthermore, new standards are currently either in the final stages of completion (proBed and proBAM for proteogenomics results as well as PEFF) or in early stages of design (a spectral library standard format, a universal spectrum identifier, the qcML quality control format, and the Protein Expression Interface (PROXI) web services Application Programming Interface). In this work we review the current status of all of these aspects of the PSI, describe synergies with other efforts such as the ProteomeXchange Consortium, the Human Proteome Project, and the metabolomics community, and provide a look at future directions of the PSI.

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.

Mothers' perceptions of child weight status and the subsequent weight gain of their children: a population-based longitudinal study

BACKGROUND

There is a plethora of cross-sectional work on maternal perceptions of child weight status showing that mothers typically do not classify their overweight child as being overweight according to commonly used clinical criteria. Awareness of overweight in their child is regarded as an important prerequisite for mothers to initiate appropriate action. The gap in the literature is determining whether, if mothers do classify their overweight child's weight status correctly, this is associated with a positive outcome for the child's body mass index (BMI) at a later stage.

OBJECTIVE

To explore longitudinal perceptions of child weight status from mothers of a contemporary population-based birth cohort (Gateshead Millennium Study) and relationships of these perceptions with future child weight gain.

METHODS

Data collected in the same cohort at 7, 12 and 15 years of age: mothers' responses to two items concerning their child's body size; child's and mother's BMI; pubertal maturation; demographic information.

RESULTS

Mothers' perceptions of whether their child was overweight did not change markedly over time. Child BMI was the only significant predictor of mothers' classification of overweight status, and it was only at the extreme end of the overweight range and in the obese range that mothers reliably described their child as overweight. Even when mothers did appropriately classify their child as overweight at an earlier stage, this was not related to relatively lower child BMI a few years later.

CONCLUSIONS

Mothers tend to classify their child as overweight in only more extreme cases. It is an important finding that no beneficial impact was shown on later child BMI in overweight children whose mothers classified their child's weight status as overweight at an earlier stage.

Neopeptide Analyser: A software tool for neopeptide discovery in proteomics data

Experiments involving mass spectrometry (MS)-based proteomics are widely used for analyses of connective tissues. Common examples include the use of relative quantification to identify differentially expressed peptides and proteins in cartilage and tendon. We are working on characterising so-called ‘neopeptides’, i.e. peptides formed due to native cleavage of proteins, for example under pathological conditions. Unlike peptides typically quantified in MS workflows due to the in vitro use of an enzyme such as trypsin, a neopeptide has at least one terminus that was not due to the use of trypsin in the workflow. The identification of neopeptides within these datasets is important in understanding disease pathology, and the development of antibodies that could be utilised as diagnostic biomarkers for diseases, such as osteoarthritis, and targets for novel treatments. Our previously described neopeptide data analysis workflow was laborious and was not amenable to robust statistical analysis, which reduced confidence in the neopeptides identified. To overcome this, we developed ‘Neopeptide Analyser’, a user friendly neopeptide analysis tool used in conjunction with label-free MS quantification tool Progenesis QIP for proteomics. Neopeptide Analyser filters data sourced from Progenesis QIP output to identify neopeptide sequences, as well as give the residues that are adjacent to the peptide in its corresponding protein sequence. It also produces normalised values for the neopeptide quantification values and uses these to perform statistical tests, which are also included in the output. Neopeptide Analyser is available as a Java application for Mac, Windows and Linux. The analysis features and ease of use encourages data exploration, which could aid the discovery of novel pathways in extracellular matrix degradation, the identification of potential biomarkers and as a tool to investigate matrix turnover. Neopeptide Analyser is available from https://github.com/PGB-LIV/neo-pep-tool/releases/.

Review: Placental adaptations to the presence of maternal asthma during pregnancy

Asthma is a highly prevalent chronic medical condition affecting an estimated 12% of pregnant, women each year, with prevalence of asthma greatest (up to 16%) among the socially disadvantaged. Maternal asthma is associated with significant perinatal morbidity and mortality including preterm births, neonatal hospitalisations and low birthweight outcomes each year. We have identified that the placenta adapts to the presence of chronic, maternal asthma during pregnancy in a sex specific manner that may confer sex differences in fetal outcome. The male fetus was at greater risk of a poor outcome than a female fetus in the presence of maternal asthma and an acute inflammatory event such as an asthma exacerbation. This review will examine the role of sex specific differences in placental function on fetal growth and survival.

Enrichment of natural 15N abundance during soil N losses under 20years of continuous cereal cropping

It is generally accepted that the enrichment of natural ¹⁵N abundance in soil over time is reflective of historic N cycling and loss, but this process in cropping soils is not yet clear. In this study, we identified an enrichment gradient of natural ¹⁵N abundance during 20-year chronosequence of cereal cropping on Alfisols in southwest Queensland, Australia, that have no history of fertilisation. We demonstrate that the increase in soil ¹⁵N abundance is explained by isotopic fractionation of ¹⁵N during organic N mineralisation and nitrification, which lead to isotopically heavier ammonium retained in the soil and isotopically lighter soil nitrate taken up and removed by seasonal crops during harvest. Here we present a framework for natural ¹⁵N isotopic fractionation co-occurring with N losses during long-term cultivation.

Transition from paediatric surgery: how many patients do we need to plan for?

INTRODUCTION Transitional care is an NHS priority with newly published NICE guidance. Many paediatric surgical patients need quality care to continue into adulthood. We undertook an evaluation of our departmental activity to assess the magnitude of this issue. METHODS We identified all outpatients ≥ 15 years (potentially requiring imminent transition) seen over a 12 month period for all five general paediatric surgery consultants in our tertiary centre. Those patients requiring transition were highlighted and the appropriate adult team for referral recorded. RESULTS There were 2989 general paediatric surgery clinic appointments within the year; 289 (9.7%) were for young people aged 15 years or older; 62 patients (28% of those ≥ 15years) were deemed to require transition into adult care. Significantly more patients having colorectal surgery required follow-up (P = 0.0009 Chi-square test) compared with patients in other subspecialties. CONCLUSIONS More patients than expected required transition. This may be the case in other units. Current best practice includes time intensive preclinic planning, careful preparation of patient and family, followed by joint clinics. A joint clinic appointment takes 30 minutes, allowing for comprehensive handover and forging new relationships. In our department, we need at least ten transition clinics across 2 years. Coalition with adult colleagues is vital. These data enable us to plan services to provide quality care for our adolescent patients and highlights colorectal surgery as a priority.