The Glycan Structure Dictionary-a dictionary describing commonly used glycan structure terms

Recent technological advances in glycobiology have resulted in a large influx of data and the publication of many papers describing discoveries in glycoscience. However, the terms used in describing glycan structural features are not standardized, making it difficult to harmonize data across biomolecular databases, hampering the harvesting of information across studies and hindering text mining and curation efforts. To address this shortcoming, the Glycan Structure Dictionary has been developed as a reference dictionary to provide a standardized list of widely used glycan terms that can help in the curation and mapping of glycan structures described in publications. Currently, the dictionary has 190 glycan structure terms with 297 synonyms linked to 3,332 publications. For a term to be included in the dictionary, it must be present in at least 2 peer-reviewed publications. Synonyms, annotations, and cross-references to GlyTouCan, GlycoMotif, and other relevant databases and resources are also provided when available. The purpose of this effort is to facilitate biocuration, assist in the development of text mining tools, improve the harmonization of search, and browse capabilities in glycoinformatics resources and help to map glycan structures to function and disease. It is also expected that authors will use these terms to describe glycan structures in their manuscripts over time. A mechanism is also provided for researchers to submit terms for potential incorporation. The dictionary is available at https://wiki.glygen.org/Glycan_structure_dictionary.

Updated assessment of occupational safety and health hazards of climate change

Workers, particularly outdoor workers, are among the populations most disproportionately affected by climate-related hazards. However, scientific research and control actions to comprehensively address these hazards are notably absent. To assess this absence, a seven-category framework was developed in 2009 to characterize the scientific literature published from 1988-2008. Using this framework, a second assessment examined the literature published through 2014, and the current one examines literature from 2014-2021. The objectives were to present literature that updates the framework and related topics and increases awareness of the role of climate change in occupational safety and health. In general, there is substantial literature on worker hazards related to ambient temperatures, biological hazards, and extreme weather but less on air pollution, ultraviolet radiation, industrial transitions, and the built environment. There is growing literature on mental health and health equity issues related to climate change, but much more research is needed. The socioeconomic impacts of climate change also require more research. This study illustrates that workers are experiencing increased morbidity and mortality related to climate change. In all areas of climate-related worker risk, including geoengineering, research is needed on the causality and prevalence of hazards, along with surveillance to identify, and interventions for hazard prevention and control.

Prevalence of depression and anxiety in older people in low- and middle- income countries in Africa, Asia and South America: A systematic review and meta-analysis

BACKGROUND

There is rapid growth of older people in Low- and Middle- Income Countries (LMICs). The aim of this review was to assess the literature on prevalence of anxiety and depression in this demographic, which to our knowledge, has not yet been conducted.

METHODS

Databases including Medline, PsychInfo, Embase, Scielo and African Journals Online were searched for terms including "mental disorders", "neurotic disorders", "mood disorders" and "anxiety disorders". Studies published between 1990 and 2020 providing data on older people (≥50 years) in LMICs (defined by World Bank Criteria) were included and quality-assessed. Meta-analysis was conducted on a subset of higher-quality studies to derive pooled prevalence estimates of depression.

RESULTS

One hundred and forty relevant studies were identified, of which thirty-two were included in meta-analysis. One hundred and fifteen studies reported depression prevalence only, 19 reported both depression and anxiety, and six reported anxiety only. In all studies identified, depression prevalence ranged from 0.5 % to 62.7 %, and Generalised Anxiety Disorder prevalence ranged from 0.2 % to 32.2 %. The pooled prevalence of depression on meta-analysis was 10.5 % (95 % CI, 8.9 % - 11.2 %). Reported prevalence rates of depression were significantly different in studies using ICD-10 compared with DSM criteria, and between community and clinical settings.

LIMITATIONS

The search strategy contained bias towards English language papers and high income country (HIC) publications. There is significant heterogeneity within the meta-analysis.

DISCUSSION

A wide range of methodologies and clinical criteria are used in prevalence studies of depression and anxiety in older people. Studies using screening tools found higher prevalence rates; clinicians and researchers should ensure diagnosis is made with gold-standard clinical criteria. Meta-analysis data suggest that rates of depression are similar in older people in LMICs compared to HICs but mental healthcare resources are limited, suggesting a large potential treatment gap.

A Preliminary Investigation into the Neural Correlates of Knee Loading during a Change of Direction Task in Individuals after Anterior Cruciate Ligament Reconstruction

Background

Central nervous system (CNS) function after ACLR, quantified by the blood oxygen level dependent (BOLD) response, is altered in regions of sensory function during knee movement after ACLR. However, it is unknown how this altered neural response may manifest in knee loading and response to sensory perturbations during sport specific movements.

Purpose

To investigate the relationship among CNS function and lower extremity kinetics, under multiple visual conditions, during 180° change of direction task in individuals with a history of ACLR.

Methods

Eight participants, 39.3 ± 37.1 months after primary, left ACLR performed repetitive active knee flexion and extension of their involved knee during fMRI scanning. Participants separately performed 3D motion capture analysis of a 180° change of direction task under full vision (FV) and stroboscopic vision (SV) conditions. A neural correlate analysis was performed to associate BOLD signal to knee loading of the left lower extremity.

Results

Involved limb peak internal knee extension moment (pKEM) was significantly lower in the SV condition (1.89 ± 0.37 N*m/Kg) compared to the FV condition (2.0 ± 0.34 N*m/Kg) (p = .018). Involved limb pKEM during the SV condition was positively correlated with BOLD signal in the contralateral precuneus and superior parietal lobe (Voxels: 53; p = .017; z-stat max: 6.47; MNI peak: 6, -50, 66).

Conclusion

There is a positive association between involved limb pKEM in the SV condition and BOLD response in areas of visual-sensory integration. Activation of contralateral precuneus and superior parietal lobe brain regions may be a strategy to maintain joint loading when vision is perturbed.

Level of Evidence

Level 3.

Development and validation of LC-MS/MS method for quantification of protease inhibitor Pepstatin A to monitor its robust clearance in vaccine downstream process

Pepstatin A reversibly inhibits aspartic acid proteases and minimizes the impact of protease-induced degradation in recombinant protein manufacturing process. Pepstatin A is considered as a process-related impurity and must be characterized and controlled during manufacturing. Herein we describe the development and validation of an LC-MS/MS method for the quantitation of pepstatin A to monitor its robust clearance in vaccine purification process. Analyte extraction from process intermediates was carried out using 10% acetonitrile/water extraction method. Acetyl-pepstatin was used as internal standard (IS). Pepstatin A and IS were resolved on a C18 column using 10 mM ammonium acetate in water and methanol/acetonitrile mobile phase system. A triple quadrupole mass spectrometer operating in the positive electrospray ionization mode with multiple reaction monitoring was used to detect Pepstatin A and IS transitions of m/z 686.5 to 229.3 and 644.5 to 229.3, respectively. The method was validated for specificity, linearity, accuracy, repeatability (precision), intermediate precision, and assay robustness. The assay was linear over the range of calibration standards 0.5-100 ng/mL. The Lower-limit-of-quantification (LLOQ) of the method was 0.50 ng/mL.

SCExecute: custom cell barcode-stratified analyses of scRNA-seq data

MOTIVATION

In single-cell RNA-sequencing (scRNA-seq) data, stratification of sequencing reads by cellular barcode is necessary to study cell-specific features. However, apart from gene expression, the analyses of cell-specific features are not sufficiently supported by available tools designed for high-throughput sequencing data.

RESULTS

We introduce SCExecute, which executes a user-provided command on barcode-stratified, extracted on-the-fly, single-cell binary alignment map (scBAM) files. SCExecute extracts the alignments with each cell barcode from aligned, pooled single-cell sequencing data. Simple commands, monolithic programs, multi-command shell scripts or complex shell-based pipelines are then executed on each scBAM file. scBAM files can be restricted to specific barcodes and/or genomic regions of interest. We demonstrate SCExecute with two popular variant callers-GATK and Strelka2-executed in shell-scripts together with commands for BAM file manipulation and variant filtering, to detect single-cell-specific expressed single nucleotide variants from droplet scRNA-seq data (10X Genomics Chromium System).In conclusion, SCExecute facilitates custom cell-level analyses on barcoded scRNA-seq data using currently available tools and provides an effective solution for studying low (cellular) frequency transcriptome features.

AVAILABILITY AND IMPLEMENTATION

SCExecute is implemented in Python3 using the Pysam package and distributed for Linux, MacOS and Python environments from https://horvathlab.github.io/NGS/SCExecute.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Non-neoplastic pathologies mimicking sarcoma - Experience from a tertiary referral centre multidisciplinary team

OBJECTIVE

Distinguishing non-neoplastic tumour-mimicking pathologies from bone and soft tissue tumours is one of the fundamental aims of a tertiary centre sarcoma multidisciplinary team (MDT) service. In this study, we aim to analyse the incidence of non-neoplastic lesions referred to a tertiary referral service as suspected sarcoma, and to analyse the spectrum of conditions comprising these tumour-mimicking pathologies.

MATERIALS AND METHODS

We conducted a retrospective observational study compiling the biopsy-proven non-neoplastic outcomes of suspected sarcoma cases referred to our MDT in the last year. We identified all referrals made to our service between 1st January 2020 and 31st December 2020 and compiled their histological diagnoses.

RESULTS

A total of 976 new cases were referred to our MDT as suspected sarcoma in one year. Of these referrals, 8.6% (84/976) received a biopsy-proven outcome of non-neoplastic pathology. These non-neoplastic outcomes were categorised into the following types of pathology: 32.1% vascular, 31.0% inflammatory, 14.3% traumatic, 6.0% degenerative, 6.0% idiopathic, 4.8% infective, 3.6% metabolic, 1.2% autoimmune, and 1.2% genetic.

CONCLUSION

A significant proportion of pathologies referred to a tertiary centre sarcoma MDT are non-neoplastic in nature. These lesions are made up of a range of pathologies, with vascular and inflammatory conditions being the most common. Our study, the first of its kind, offers clinicians an insight into tumour-mimicking pathologies encountered by a tertiary centre.

Health system recovery from Covid-19: What policies are health systems using to tackle backlogs and bring down waiting times in the wake of the pandemic?

The pandemic has left even the most well-equipped health systems vulnerable and required difficult trade-offs to balance both Covid-19 and non-Covid-19 health services. Across the globe, planned and routine health services have been scaled down during peaks of the crisis to meet the needs of acute and Covid-19-related care, resulting in growing care backlogs and increase in the number of patients waiting for treatment. To identify potential policy solutions, we have consulted the Covid-19 Health System Response Monitor, interviewed experts and analysed recovery strategies in 16 OECD and EU countries. Many country responses display striking similarities despite very real differences in the organisation of health and care services. These include:

1) increasing the supply of workforce by widening the scope of authority for different roles, investing heavily in recruitment and training for key roles, and improving the terms and conditions of work;

2) boosting productivity by introducing financial incentives and targets, reconfiguring facilities to better separate planned and emergency work”, optimising referrals and waiting list management, and outsourcing more care to the private sector; and

3) investing in out-of-hospital alternatives to care, including expanding primary and community care models and developing digital, home care and rehabilitative capacity

Policymakers will need to balance the immediate pressures of clearing backlogs with long-term measures that place services on a more sustainable footing. International experience shows how these can be at odds, especially if actions taken in the short term exhaust an already depleted workforce, or resolve Covid-19-specific problems but leave services less prepared for tomorrow's challenges.

Community evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysis

Glycoproteomics is a powerful yet analytically challenging research tool. Software packages aiding the interpretation of complex glycopeptide tandem mass spectra have appeared, but their relative performance remains untested. Conducted through the HUPO Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates solutions for system-wide glycopeptide analysis. The same mass spectrometrybased glycoproteomics datasets from human serum were shared with participants and the relative team performance for N- and O-glycopeptide data analysis was comprehensively established by orthogonal performance tests. Although the results were variable, several high-performance glycoproteomics informatics strategies were identified. Deep analysis of the data revealed key performance-associated search parameters and led to recommendations for improved 'high-coverage' and 'high-accuracy' glycoproteomics search solutions. This study concludes that diverse software packages for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies and specifies key variables that will guide future software developments and assist informatics decision-making in glycoproteomics.

Primary Health Care during the COVID-19 pandemic: an analysis based on the HSRM

The COVID-19 pandemic has had a dramatic impact on workload and responsibilities for those working at primary health care (PHC) level in the European region - much of which has gone unnoticed relative to the focus on hospitals. Based on the PHC-relevant data extracted from the HSRM, we describe PHC models of care and the political and system levers that supported them. Three key themes emerged: (1) varied forms of PHC multidisciplinary collaboration were developed to manage the emergency response - supported by the movement of staff to areas requiring support; (2) vulnerable patients were identified and prioritized for medical outreach within PHC, and were supported through financial incentives and complementary action from centralized and local governments that used much broader definitions of vulnerability; and (3) digital solutions for remote triage, medical advice and treatment enhanced the effectiveness of the PHC response and were facilitated through centralized investment in digital technologies. Based on our analysis, we raise opportunities for the future of PHC, namely that multidisciplinary approaches to PHC service delivery are essential to future infectious and non-infectious outbreaks, and the agility and rapid pace of change that took place among PHC providers should continue. PHC providers lacked visibility during the pandemic and should work together to develop a strong voice in all health systems.

SCReadCounts: estimation of cell-level SNVs expression from scRNA-seq data

BACKGROUND

Recent studies have demonstrated the utility of scRNA-seq SNVs to distinguish tumor from normal cells, characterize intra-tumoral heterogeneity, and define mutation-associated expression signatures. In addition to cancer studies, SNVs from single cells have been useful in studies of transcriptional burst kinetics, allelic expression, chromosome X inactivation, ploidy estimations, and haplotype inference.

RESULTS

To aid these types of studies, we have developed a tool, SCReadCounts, for cell-level tabulation of the sequencing read counts bearing SNV reference and variant alleles from barcoded scRNA-seq alignments. Provided genomic loci and expected alleles, SCReadCounts generates cell-SNV matrices with the absolute variant- and reference-harboring read counts, as well as cell-SNV matrices of expressed Variant Allele Fraction (VAFRNA) suitable for a variety of downstream applications. We demonstrate three different SCReadCounts applications on 59,884 cells from seven neuroblastoma samples: (1) estimation of cell-level expression of known somatic mutations and RNA-editing sites, (2) estimation of cell- level allele expression of biallelic SNVs, and (3) a discovery mode assessment of the reference and each of the three alternative nucleotides at genomic positions of interest that does not require prior SNV information. For the later, we applied SCReadCounts on the coding regions of KRAS, where it identified known and novel somatic mutations in a low-to-moderate proportion of cells. The SCReadCounts read counts module is benchmarked against the analogous modules of GATK and Samtools. SCReadCounts is freely available ( https://github.com/HorvathLab/NGS ) as 64-bit self-contained binary distributions for Linux and MacOS, in addition to Python source.

CONCLUSIONS

SCReadCounts supplies a fast and efficient solution for estimation of cell-level SNV expression from scRNA-seq data. SCReadCounts enables distinguishing cells with monoallelic reference expression from those with no gene expression and is applicable to assess SNVs present in only a small proportion of the cells, such as somatic mutations in cancer.

Enhancing the interoperability of glycan data flow between ChEBI, PubChem, and GlyGen

Glycans play a vital role in health, disease, bioenergy, biomaterials, and bio-therapeutics. As a result, there is keen interest to identify and increase glycan data in bioinformatics databases like ChEBI and PubChem, and connecting them to resources at the EMBL-EBI and NCBI to facilitate access to important annotations at a global level. GlyTouCan is a comprehensive archival database that contains glycans obtained primarily through batch upload from glycan repositories, glycoprotein databases, and individual laboratories. In many instances, the glycan structures deposited in GlyTouCan may not be fully defined or have supporting experimental evidence and citations. Databases like ChEBI and PubChem were designed to accommodate complete atomistic structures with well-defined chemical linkages. As a result, they cannot easily accommodate the structural ambiguity inherent in glycan databases. Consequently, there is a need to improve the organization of glycan data coherently to enhance connectivity across the major NCBI, EMBL-EBI, and glycoscience databases. This paper outlines a workflow developed in collaboration between GlyGen, ChEBI, and PubChem to improve the visibility and connectivity of glycan data across these resources. GlyGen hosts a subset of glycans (~29,000) from the GlyTouCan database and has submitted valuable glycan annotations to the PubChem database and integrated over 10,500 (including ambiguously defined) glycans into the ChEBI database. The integrated glycans were prioritized based on links to PubChem and connectivity to glycoprotein data. The pipeline provides a blueprint for how glycan data can be harmonized between different resources. The current PubChem, ChEBI, and GlyTouCan mappings can be downloaded from GlyGen (https://data.glygen.org).

The glycoconjugate ontology (GlycoCoO) for standardizing the annotation of glycoconjugate data and its application

Recent years have seen great advances in the development of glycoproteomics protocols and methods resulting in a sustainable increase in the reporting proteins, their attached glycans and glycosylation sites. However, only very few of these reports find their way into databases or data repositories. One of the major reasons is the absence of digital standard to represent glycoproteins and the challenging annotations with glycans. Depending on the experimental method, such a standard must be able to represent glycans as complete structures or as compositions, store not just single glycans but also represent glycoforms on a specific glycosylation side, deal with partially missing site information if no site mapping was performed, and store abundances or ratios of glycans within a glycoform of a specific site. To support the above, we have developed the GlycoConjugate Ontology (GlycoCoO) as a standard semantic framework to describe and represent glycoproteomics data. GlycoCoO can be used to represent glycoproteomics data in triplestores and can serve as a basis for data exchange formats. The ontology, database providers and supporting documentation are available online (https://github.com/glycoinfo/GlycoCoO).

GlyGen data model and processing workflow

Summary

Glycoinformatics plays a major role in glycobiology research, and the development of a comprehensive glycoinformatics knowledgebase is critical. This application note describes the GlyGen data model, processing workflow and the data access interfaces featuring programmatic use case example queries based on specific biological questions. The GlyGen project is a data integration, harmonization and dissemination project for carbohydrate and glycoconjugate-related data retrieved from multiple international data sources including UniProtKB, GlyTouCan, UniCarbKB and other key resources.

Availability and implementation

GlyGen web portal is freely available to access at https://glygen.org. The data portal, web services, SPARQL endpoint and GitHub repository are also freely available at https://data.glygen.org, https://api.glygen.org, https://sparql.glygen.org and https://github.com/glygener, respectively. All code is released under license GNU General Public License version 3 (GNU GPLv3) and is available on GitHub https://github.com/glygener. The datasets are made available under Creative Commons Attribution 4.0 International (CC BY 4.0) license.

Supplementary information

Supplementary data are available at Bioinformatics online.

Low back pain and golf: A review of biomechanical risk factors

Golf is an international sport played by a variety of age groups and fitness levels, and although golf has a low to moderate aerobic intensity level, injuries are common among professional and amateur golfers. High amounts of force experienced during the golf swing can lead to injury when golfers lack appropriate strength or technique with the lower back most commonly injured. Research has indicated that trunk muscle activation, hip strength and mobility, and pelvis and trunk rotation are associated with low back pain (LBP). Based on anecdotal evidence, golf practitioners specifically address issues in weight shift, lumbar positioning, and pelvis sequencing for golfers with LBP. This review aims to elucidate the effects of proper and improper golf swing technique on LBP and to help golf practitioners understand how to approach the alleviation of LBP in their clientele.

Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma

To elucidate the deregulated functional modules that drive clear cell renal cell carcinoma (ccRCC), we performed comprehensive genomic, epigenomic, transcriptomic, proteomic, and phosphoproteomic characterization of treatment-naive ccRCC and paired normal adjacent tissue samples. Genomic analyses identified a distinct molecular subgroup associated with genomic instability. Integration of proteogenomic measurements uniquely identified protein dysregulation of cellular mechanisms impacted by genomic alterations, including oxidative phosphorylation-related metabolism, protein translation processes, and phospho-signaling modules. To assess the degree of immune infiltration in individual tumors, we identified microenvironment cell signatures that delineated four immune-based ccRCC subtypes characterized by distinct cellular pathways. This study reports a large-scale proteogenomic analysis of ccRCC to discern the functional impact of genomic alterations and provides evidence for rational treatment selection stemming from ccRCC pathobiology.

Harnessing autophagy to overcome mitogen-activated protein kinase kinase inhibitor-induced resistance in metastatic melanoma

BACKGROUND

Patients with malignant melanoma often relapse after treatment with BRAF and/or mitogen-activated protein kinase kinase (MEK) inhibitors (MEKi) owing to development of drug resistance.

OBJECTIVES

To establish the temporal pattern of CD271 regulation during development of resistance by melanoma to trametinib, and determine the association between development of resistance to trametinib and induction of prosurvival autophagy.

METHODS

Immunohistochemistry for CD271 and p62 was performed on human naevi and primary malignant melanoma tumours. Western blotting was used to analyse expression of CD271, p62 and LC3 in melanoma subpopulations. Flow cytometry and immunofluorescence microscopy was used to evaluate trametinib-induced cell death and CD271 expression. MTS viability assays and zebrafish xenografts were used to evaluate the effect of CD271 and autophagy modulation on trametinib-resistant melanoma cell survival and invasion, respectively.

RESULTS

CD271 and autophagic signalling are increased in stage III primary melanomas vs. benign naevi. In vitro studies demonstrate MEKi of BRAF-mutant melanoma induced cytotoxic autophagy, followed by the emergence of CD271-expressing subpopulations. Trametinib-induced CD271 reduced autophagic flux, leading to activation of prosurvival autophagy and development of MEKi resistance. Treatment of CD271-expressing melanoma subpopulations with RNA interference and small-molecule inhibitors to CD271 reduced the development of MEKi resistance, while clinically applicable autophagy modulatory agents - including Δ9-tetrahydrocannabinol and Vps34 - reduced survival of MEKi-resistant melanoma cells. Combined MEK/autophagy inhibition also reduced the invasive and metastatic potential of MEKi-resistant cells in an in vivo zebrafish xenograft.

CONCLUSIONS

These results highlight a novel mechanism of MEKi-induced drug resistance and suggest that targeting autophagy may be a translatable approach to resensitize drug-resistant melanoma cells to the cytotoxic effects of MEKi.

Systematic pan-cancer analysis of somatic allele frequency

Imbalanced expression of somatic alleles in cancer can suggest functional and selective features, and can therefore indicate possible driving potential of the underlying genetic variants. To explore the correlation between allele frequency of somatic variants and total gene expression of their harboring gene, we used the unique data set of matched tumor and normal RNA and DNA sequencing data of 5523 distinct single nucleotide variants in 381 individuals across 10 cancer types obtained from The Cancer Genome Atlas (TCGA). We analyzed the allele frequency in the context of the variant and gene functional features and linked it with changes in the total gene expression. We documented higher allele frequency of somatic variants in cancer-implicated genes (Cancer Gene Census, CGC). Furthermore, somatic alleles bearing premature terminating variants (PTVs), when positioned in CGC genes, appeared to be less frequently degraded via nonsense-mediated mRNA decay, indicating possible favoring of truncated proteins by the tumor transcriptome. Among the genes with multiple PTVs with high allele frequency, ARID1, TP53 and NSD1 were known key cancer genes. All together, our analyses suggest that high allele frequency of tumor somatic variants can indicate driving functionality and can serve to identify potential cancer-implicated genes.

Genesis, design and methods of the Beef CRC Maternal Productivity Project

Australian seedstock cattle breeders have expressed concerns that while there has been genetic improvement in feedlot and abattoir performance of cows, it could have led to a decline in maternal productivity, especially under variable nutritional conditions. This paper describes a substantial project with two components designed to address these issues. The first sub-project was to monitor bodyweight and composition of 7760 young Angus and Hereford cows as they experience variable physiological states (pregnancy and lactation) and seasons. This was conducted on large numbers in seedstock herds. The second sub-project was to monitor more regularly bodyweight, body composition, and calf rearing performance of 500 Angus cows that are genetically divergent for either fat or residual feed intake at two research centres. This also included two levels of nutrition and recording of weekly feed intake of small groups of cows for at least three parities to allow reporting of genotype × nutrition effects on maternal productivity and efficiency. Results from the project are reported in a series of papers with each one having a defined focus.

Dietary Restriction Ameliorates Age-Related Increase in DNA Damage, Senescence and Inflammation in Mouse Adipose Tissuey

Ageing is associated with redistribution of fat around the body and saturation of visceral adipose depots. Likewise, the presence of excess fat in obesity or during ageing places extra stress on visceral depots, resulting in chronic inflammation and increased senescence. This process can contribute to the establishment of the metabolic syndrome and accelerated ageing. Dietary restriction (DR) is known to alleviate physiological signs of inflammation, ageing and senescence in various tissues including adipose tissue.

OBJECTIVES

Our pilot study aimed to analyse senescence and inflammation parameters in mouse visceral fat tissue during ageing and by short term, late-onset dietary restriction as a nutritional intervention. Design, measurements: In this study we used visceral adipose tissue from mice between 5 and 30 months of age and analysed markers of senescence (adipocyte size, γH2A.X, p16, p21) and inflammation (e.g. IL-6, TNFα, IL-1β, macrophage infiltration) using immuno-staining, as well as qPCR for gene expression analysis. Fat tissues from 3 mice per group were analysed.

RESULTS

We found that the amount of γH2A.X foci as well as the expression of senescence and inflammation markers increased during ageing but decreased with short term DR. In contrast, the increase in amounts of single or aggregated macrophages in fat depots occurred only at higher ages. Surprisingly, we also found that adipocyte size as well as some senescence parameters decreased at very high age (30 months).

CONCLUSIONS

Our results demonstrate increased senescence and inflammation during ageing in mouse visceral fat while DR was able to ameliorate several of these parameters as well as increased adipocyte size at 17.5 months of age. This highlights the health benefits of a decreased nutritional intake over a relatively short period of time at middle age.

Predicting nsSNPs that Disrupt Protein-Protein Interactions Using Docking

The human genome contains a large number of protein polymorphisms due to individual genome variation. How many of these polymorphisms lead to altered protein-protein interaction is unknown. We have developed a method to address this question. The intersection of the SKEMPI database (of affinity constants among interacting proteins) and CAPRI 4.0 docking benchmark was docked using HADDOCK, leading to a training set of 166 mutant pairs. A random forest classifier based on the differences in resulting docking scores between the 166 mutant pairs and their wild-types was used, to distinguish between variants that have either completely or partially lost binding ability. Fifty percent of non-binders were correctly predicted with a false discovery rate of only 2 percent. The model was tested on a set of 15 HIV-1 - human, as well as seven human- human glioblastoma-related, mutant protein pairs: 50 percent of combined non-binders were correctly predicted with a false discovery rate of 10 percent. The model was also used to identify 10 protein-protein interactions between human proteins and their HIV-1 partners that are likely to be abolished by rare non-synonymous single-nucleotide polymorphisms (nsSNPs). These nsSNPs may represent novel and potentially therapeutically-valuable targets for anti-viral therapy by disruption of viral binding.

Overexpressed somatic alleles are enriched in functional elements in Breast Cancer

Asymmetric allele content in the transcriptome can be indicative of functional and selective features of the underlying genetic variants. Yet, imbalanced alleles, especially from diploid genome regions, are poorly explored in cancer. Here we systematically quantify and integrate the variant allele fraction from corresponding RNA and DNA sequence data from patients with breast cancer acquired through The Cancer Genome Atlas (TCGA). We test for correlation between allele prevalence and functionality in known cancer-implicated genes from the Cancer Gene Census (CGC). We document significant allele-preferential expression of functional variants in CGC genes and across the entire dataset. Notably, we find frequent allele-specific overexpression of variants in tumor-suppressor genes. We also report a list of over-expressed variants from non-CGC genes. Overall, our analysis presents an integrated set of features of somatic allele expression and points to the vast information content of the asymmetric alleles in the cancer transcriptome.

Surface Glycoproteins of Exosomes Shed by Myeloid-Derived Suppressor Cells Contribute to Function

In this report, we use a proteomic strategy to identify glycoproteins on the surface of exosomes derived from myeloid-derived suppressor cells (MDSCs), and then test if selected glycoproteins contribute to exosome-mediated chemotaxis and migration of MDSCs. We report successful modification of a surface chemistry method for use with exosomes and identify 21 surface N-glycoproteins on exosomes released by mouse mammary carcinoma-induced MDSCs. These glycoprotein identities and functionalities are compared with 93 N-linked glycoproteins identified on the surface of the parental cells. As with the lysate proteomes examined previously, the exosome surface N-glycoproteins are primarily a subset of the glycoproteins on the surface of the suppressor cells that released them, with related functions and related potential as therapeutic targets. The "don't eat me" molecule CD47 and its binding partners thrombospondin-1 (TSP1) and signal regulatory protein α (SIRPα) were among the surface N-glycoproteins detected. Functional bioassays using antibodies to these three molecules demonstrated that CD47, TSP1, and to a lesser extent SIRPα facilitate exosome-mediated MDSC chemotaxis and migration.

RNA2DNAlign: nucleotide resolution allele asymmetries through quantitative assessment of RNA and DNA paired sequencing data

We introduce RNA2DNAlign, a computational framework for quantitative assessment of allele counts across paired RNA and DNA sequencing datasets. RNA2DNAlign is based on quantitation of the relative abundance of variant and reference read counts, followed by binomial tests for genotype and allelic status at SNV positions between compatible sequences. RNA2DNAlign detects positions with differential allele distribution, suggesting asymmetries due to regulatory/structural events. Based on the type of asymmetry, RNA2DNAlign outlines positions likely to be implicated in RNA editing, allele-specific expression or loss, somatic mutagenesis or loss-of-heterozygosity (the first three also in a tumor-specific setting). We applied RNA2DNAlign on 360 matching normal and tumor exomes and transcriptomes from 90 breast cancer patients from TCGA. Under high-confidence settings, RNA2DNAlign identified 2038 distinct SNV sites associated with one of the aforementioned asymetries, the majority of which have not been linked to functionality before. The performance assessment shows very high specificity and sensitivity, due to the corroboration of signals across multiple matching datasets. RNA2DNAlign is freely available from http://github.com/HorvathLab/NGS as a self-contained binary package for 64-bit Linux systems.

Extracellular vesicle proteomes reflect developmental phases of Bacillus subtilis

BACKGROUND

Extracellular vesicles (EV) are spherical membrane-bound vesicles with nano-scale diameters, which are shed to the extracellular region by most eukaryotic and prokaryotic cells. Bacterial EV are proposed to contribute to intercellular communication, bacterial survival and human pathogenesis as a novel secretion system. EV have been characterized from many Gram-negative species and, more recently, from several vegetative Gram-positive bacteria. Further characterization of EV and their molecular cargos will contribute to understanding bacterial physiology and to developing therapeutic approaches.

RESULTS

Bacillus subtilis were observed to release EV to a similar extent during sporulation as during the vegetative growth phase. However, the two vesicular cargos show qualitatively and quantitatively different proteomes. Among 193 total proteins identified across both samples, 61 were shown to be significantly more abundant in EV shed by sporulating cells, with (log) ratio of spectral counts RSC > 1 and Fisher-exact test FDR < 5 %. Sixty-two proteins were found to be significantly more abundant in EV shed by vegetative cells. Membrane fusion was shown to take place between these EVs and Gram-positive cells.

CONCLUSION

Biogenesis of EV is a continuous process over the entire life cycle of this sporulating bacterium. The formation of EV during sporulation is strongly supported by the delineation of protein content that differs from the proteome of EV formed by vegetative spores.