The Priority position paper: Protecting Europe's food chain from prions

Bovine spongiform encephalopathy (BSE) created a global European crisis in the 1980s and 90s, with very serious health and economic implications. Classical BSE now appears to be under control, to a great extent as a result of a global research effort that identified the sources of prions in meat and bone meal (MBM) and developed new animal-testing tools that guided policy. Priority (www.prionpriority.eu) was a European Union (EU) Framework Program 7 (FP7)-funded project through which 21 European research institutions and small and medium enterprises (SMEs) joined efforts between 2009 and 2014, to conduct coordinated basic and applied research on prions and prion diseases. At the end of the project, the Priority consortium drafted a position paper (www.prionpriority.eu/Priority position paper) with its main conclusions. In the present opinion paper, we summarize these conclusions.

With respect to the issue of re-introducing ruminant protein into the feed-chain, our opinion is that sustaining an absolute ban on feeding ruminant protein to ruminants is essential. In particular, the spread and impact of non-classical forms of scrapie and BSE in ruminants is not fully understood and the risks cannot be estimated. Atypical prion agents will probably continue to represent the dominant form of prion diseases in the near future in Europe. Atypical L-type BSE has clear zoonotic potential, as demonstrated in experimental models. Similarly, there are now data indicating that the atypical scrapie agent can cross various species barriers. More epidemiological data from large cohorts are necessary to reach any conclusion on the impact of its transmissibility on public health. Re-evaluations of safety precautions may become necessary depending on the outcome of these studies.

Intensified searching for molecular determinants of the species barrier is recommended, since this barrier is key for important policy areas and risk assessment. Understanding the structural basis for strains and the basis for adaptation of a strain to a new host will require continued fundamental research, also needed to understand mechanisms of prion transmission, replication and how they cause nervous system dysfunction and death. Early detection of prion infection, ideally at a preclinical stage, also remains crucial for development of effective treatment strategies.     

CORAL: Building up QSAR models for the chromosome aberration test

A high level of chromosomal aberrations in peripheral blood lymphocytes may be an early marker of cancer risk, but data on risk of specific cancers and types of chromosomal aberrations are limited. Consequently, the development of predictive models for chromosomal aberrations test is important task. Majority of models for chromosomal aberrations test are so-called knowledge-based rules system. The CORAL software (http://www.insilico.eu/coral, abbreviation of “CORrelation And Logic”) is an alternative for knowledge-based rules system. In contrast to knowledge-based rules system, the CORAL software gives possibility to estimate the influence upon the predictive potential of a model of different molecular alerts as well as different splits into the training set and validation set. This possibility is not available for the approaches based on the knowledge-based rules system. Quantitative Structure–Activity Relationships (QSAR) for chromosome aberration test are established for five random splits into the training, calibration, and validation sets. The QSAR approach is based on representation of the molecular structure by simplified molecular input-line entry system (SMILES) without data on physicochemical and/or biochemical parameters. In spite of this limitation, the statistical quality of these models is quite good.     

Improved method for predicting linear B-cell epitopes

Background

B-cell epitopes are the sites of molecules that are recognized by antibodies of the immune system. Knowledge of B-cell epitopes may be used in the design of vaccines and diagnostics tests. It is therefore of interest to develop improved methods for predicting B-cell epitopes. In this paper, we describe an improved method for predicting linear B-cell epitopes.

Results

In order to do this, three data sets of linear B-cell epitope annotated proteins were constructed. A data set was collected from the literature, another data set was extracted from the AntiJen database and a data sets of epitopes in the proteins of HIV was collected from the Los Alamos HIV database. An unbiased validation of the methods was made by testing on data sets on which they were neither trained nor optimized on. We have measured the performance in a non-parametric way by constructing ROC-curves.

Conclusion

The best single method for predicting linear B-cell epitopes is the hidden Markov model. Combining the hidden Markov model with one of the best propensity scale methods, we obtained the BepiPred method. When tested on the validation data set this method performs significantly better than any of the other methods tested. The server and data sets are publicly available at http://www.cbs.dtu.dk/services/BepiPred.     

Straightforward and complete deposition of NMR data to the PDBe

We present a suite of software for the complete and easy deposition of NMR data to the PDB and BMRB. This suite uses the CCPN framework and introduces a freely downloadable, graphical desktop application called CcpNmr Entry Completion Interface (ECI) for the secure editing of experimental information and associated datasets through the lifetime of an NMR project. CCPN projects can be created within the CcpNmr Analysis software or by importing existing NMR data files using the CcpNmr FormatConverter. After further data entry and checking with the ECI, the project can then be rapidly deposited to the PDBe using AutoDep, or exported as a complete deposition NMR-STAR file. In full CCPN projects created with ECI, it is straightforward to select chemical shift lists, restraint data sets, structural ensembles and all relevant associated experimental collection details, which all are or will become mandatory when depositing to the PDB. Instructions and download information for the ECI are available from the PDBe web site at http://www.ebi.ac.uk/pdbe/nmr/deposition/eci.html.     

Identification of potential ‘lifestyle-responsive’ epigenomic biomarkers in healthy women aged 18–40

Context: Human health is complex and multifaceted; there is a need for biomarkers that reflect the multidimensional nature of health.

Objective: To identify potential epigenomic biomarkers of health in women aged 18–40 participating in a six-month lifestyle intervention, next level health.

Materials and methods: Methylation data were obtained by reduced representation bisulphite sequencing of 21 female intervention participants as well as three non-participants. The Differential Methylation Analysis Package (DMAP) was used to investigate inter- and intra-individual variability and to identify potential targets of transient epigenetic control in the population studied.

Results: Eleven genes were identified as significantly differentially methylated post- intervention in all 21 participants. 1884 genomic locations were found to be differentially methylated amongst the total female population studied representing potential epigenomic biomarkers.

Conclusions: The ability to demonstrate epigenetic changes arising from a lifestyle intervention can provide key information on the relationship between gene regulation, human behaviour and health.     

CytokineDB: a database collecting biological information

Cytokines are subdivided in 12 sub-families and are described as multi-functional molecules that play an important biological activity in host defense system against pathogens, in homeostasis, tissue repair, cell growth and development. CytokineDB is an annotated database that collects biological information regarding the cytokines family in human and will be periodically updated by including new biological information. This database is freely available online and can be accessed at the URL: http://www.cro-m.eu/CytokineDB/     

ChiloKey,an interactive identification tool for the geophilomorph centipedes of Europe (Chilopoda,Geophilomorpha)

ChiloKey is a matrix-based, interactive key to all 179 species of Geophilomorpha (Chilopoda) recorded from Europe, including species of uncertain identity and those whose morphology is known partially only. The key is intended to assist in identification of subadult and adult specimens, by means of microscopy and simple dissection techniques whenever necessary. The key is freely available through the web at: http://www.biologia.unipd.it/chilokey/ and at http://www.interactive-keys.eu/chilokey/.     

Impact assessment of risk parameters of underground coal mining on the environment

Coal is an important energy source but it has a significant negative impact on the environmental processes. This paper analyses the impact, measurement, and input of parameters representing potential environmental polluters in the information system (IS).

The methodology of recording and systematization includes the following parameters: coal deposits; climate parameters; roads; rivers; land and surrounding objects; air polluters; water polluters; and soil polluters. Methods for calculating land deformation, air polluter emissions, and noise impact are also presented.

Based on the number and specificity of analyzed data, the paper provides a concept of the IS and an overview of environmental impact of underground coal mine technological units. The concept was used to present the results of a research conducted at the underground coal mine “Soko” in Serbia.

The results of this research can help many potential users realize their goals. Those goals are preventive by nature, since negative environmental impact can be predicted, which enables the environmental protection experts to take appropriate measures.     

Micronuclei as a marker for medical screening of subjects continuously occupationally exposed to low doses of ionizing radiation

Context: Genotoxicity assays are widely employed in human biomonitoring studies to assess genetic damage inflicted by genotoxic agents.

Objective: Evaluation of micronuclei (MN) as a screening marker of occupational ionizing radiation (IR) exposure.

Materials and methods: Using micronucleus test, peripheral blood lymphocytes (PBL) of 402 control and exposed subjects were screened for genetic damage.

Results: The mean frequencies of micronucleus test parameters were significantly higher in exposed persons. Increase of micronucleus yield with duration of exposure (DOE) by 0.303MN/year was revealed.

Discussion and conclusion: The obtained data encourage us to consider MN as valuable markers for preventive medical screening of occupationally exposed groups.     

Effect of confounding factors on a phospho-flow assay of ribosomal S6 protein for therapeutic drug monitoring of the mTOR-inhibitor everolimus in heart transplanted patients

Context: Several assays of monitoring immune cell function have been developed to enhance therapeutic drug monitoring.

Objective: An in vitro-validated whole-blood assay of phosphorylated ribosomal protein S6 (pS6RP) was evaluated for confounders to monitor the mTOR-inhibitor everolimus (ERL).

Materials and methods: Whole blood samples from 87 heart transplant recipients were analyzed for pS6RP-expression in CD3-positive T-cells by phospho-flow analysis.

Results: ERL blood concentration, laboratory parameters, co-medications, demographic and clinical data were reviewed.

Conclusion: Evaluating the pS6RP-assay revealed that pS6RP is influenced by cyclosporine A (CsA) blood concentration, duration of ERL treatment, co-medication with thiazide diuretics and different metabolic parameters.     

miRDeepFinder: a miRNA analysis tool for deep sequencing of plant small RNAs

miRDeepFinder is a software package developed to identify and functionally analyze plant microRNAs (miRNAs) and their targets from small RNA datasets obtained from deep sequencing. The functions available in miRDeepFinder include pre-processing of raw data, identifying conserved miRNAs, mining and classifying novel miRNAs, miRNA expression profiling, predicting miRNA targets, and gene pathway and gene network analysis involving miRNAs. The fundamental design of miRDeepFinder is based on miRNA biogenesis, miRNA-mediated gene regulation and target recognition, such as perfect or near perfect hairpin structures, different read abundances of miRNA and miRNA*, and targeting patterns of plant miRNAs. To test the accuracy and robustness of miRDeepFinder, we analyzed a small RNA deep sequencing dataset of Arabidopsis thaliana published in the GEO database of NCBI. Our test retrieved 128 of 131 (97.7%) known miRNAs that have a more than 3 read count in Arabidopsis. Because many known miRNAs are not associated with miRNA*s in small RNA datasets, miRDeepFinder was also designed to recover miRNA candidates without the presence of miRNA*. To mine as many miRNAs as possible, miRDeepFinder allows users to compare mature miRNAs and their miRNA*s with other small RNA datasets from the same species. Cleaveland software package was also incorporated into miRDeepFinder for miRNA target identification using degradome sequencing analysis. Using this new computational tool, we identified 13 novel miRNA candidates with miRNA*s from Arabidopsis and validated 12 of them experimentally. Interestingly, of the 12 verified novel miRNAs, a miRNA named AC1 spans the exons of two genes (UTG71C4 and UGT71C3). Both the mature AC1 miRNA and its miRNA* were also found in four other small RNA datasets. We also developed a tool, ??miRNA primer designer?? to design primers for any type of miRNAs. miRDeepFinder provides a powerful tool for analyzing small RNA datasets from all species, with or without the availability of genome information. miRDeepFinder and miRNA primer designer are freely available at http://www.leonxie.com/DeepFinder.php and at http://www.leonxie.com/miRNAprimerDesigner.php, respectively. A program (called RefFinder: http://www.leonxie.com/referencegene.php) was also developed for assessing the reliable reference genes for gene expression analysis, including miRNAs.     

Weather effect on widely distributed seabirds through migration flyways: a case study with the Northern Gannet Morus bassanus in the Bay of Biscay

Capsule: Northern Gannet Morus bassanus counts obtained from a coastal monitoring network in northern Spain were highly determined by wind conditions.

Aims: To determine how external factors including weather conditions affect seabird counts in a land-based seabird monitoring project (Red de observación de Aves y Mamíferos marinos, RAM project; Seabird & Marine Mammal Observation Network).

Methods: Seabird counts were obtained from four study capes situated in the southeastern part of the Bay of Biscay in northern Spain. Counts were conducted on a monthly-basis for a period of 3 hours starting at dawn on each sampling day. Data used here were compiled over a 10-year period (2006–15).

Results: Northern Gannet numbers were chiefly influenced by meteorological conditions at a local spatial scale. Northwesterly winds were found to positively influence gannet abundance, whereas high relative humidity caused a decrease in abundance. Moreover, gannets were more abundant during the non-breeding period as compared to breeding period.

Conclusion: We recommend considering the effect of the wind and relative humidity on land-based seabird counts in the Bay of Biscay when handling data from the RAM protocol in order to avoid biases and misinterpretation of data. Since seabirds approach the coast during harsh weather conditions, the RAM protocol should be improved in order to better account for the distance at which the birds are seen.     

Probabilistic Interaction Network of Evidence Algorithm and its Application to Complete Labeling of Peak Lists from Protein NMR Spectroscopy

The process of assigning a finite set of tags or labels to a collection of observations, subject to side conditions, is notable for its computational complexity. This labeling paradigm is of theoretical and practical relevance to a wide range of biological applications, including the analysis of data from DNA microarrays, metabolomics experiments, and biomolecular nuclear magnetic resonance (NMR) spectroscopy. We present a novel algorithm, called Probabilistic Interaction Network of Evidence (PINE), that achieves robust, unsupervised probabilistic labeling of data. The computational core of PINE uses estimates of evidence derived from empirical distributions of previously observed data, along with consistency measures, to drive a fictitious system M with Hamiltonian H to a quasi-stationary state that produces probabilistic label assignments for relevant subsets of the data. We demonstrate the successful application of PINE to a key task in protein NMR spectroscopy: that of converting peak lists extracted from various NMR experiments into assignments associated with probabilities for their correctness. This application, called PINE-NMR, is available from a freely accessible computer server (http://pine.nmrfam.wisc.edu). The PINE-NMR server accepts as input the sequence of the protein plus user-specified combinations of data corresponding to an extensive list of NMR experiments; it provides as output a probabilistic assignment of NMR signals (chemical shifts) to sequence-specific backbone and aliphatic side chain atoms plus a probabilistic determination of the protein secondary structure. PINE-NMR can accommodate prior information about assignments or stable isotope labeling schemes. As part of the analysis, PINE-NMR identifies, verifies, and rectifies problems related to chemical shift referencing or erroneous input data. PINE-NMR achieves robust and consistent results that have been shown to be effective in subsequent steps of NMR structure determination.     

Current state of the art for enhancing urine biomarker discovery

Introduction: Urine is a highly desirable biospecimen for biomarker analysis because it can be collected recurrently by non-invasive techniques, in relatively large volumes. Urine contains cellular elements, biochemicals, and proteins derived from glomerular filtration of plasma, renal tubule excretion, and urogenital tract secretions that reflect, at a given time point, an individual’s metabolic and pathophysiologic state.

Areas covered: High-resolution mass spectrometry, coupled with state of the art fractionation systems are revealing the plethora of diagnostic/prognostic proteomic information existing within urinary exosomes, glycoproteins, and proteins. Affinity capture pre-processing techniques such as combinatorial peptide ligand libraries and biomarker harvesting hydrogel nanoparticles are enabling measurement/identification of previously undetectable urinary proteins.

Expert commentary: Future challenges in the urinary proteomics field include a) defining either single or multiple, universally applicable data normalization methods for comparing results within and between individual patients/data sets, and b) defining expected urinary protein levels in healthy individuals.     

Biomarker discovery for drug-induced phospholipidosis: phenylacetylglycine to hippuric acid ratio in urine and plasma as potential markers

Context: Drug-induced phospholipidosis is one of the significant concerns in drug development, especially in safety assessment and noninvasive diagnostic tool is highly desirable.

Objective: The objective of this study is to explored novel biomarkers for phospholipidosis using a metabolomic approach.

Method: NMR spectrometry and LC/MS/MS analyses were applied to urine and plasma of rats administrated cationic amphiphilic drugs.

Results: The phenylacetylglycine to hippuric acid ratio in plasma was increased in time and dose-dependent manners; and it was well correlated with histopathological observation.

Conclusion: The plasma phenylacetylglycine to hippuric acid ratio is a potential marker in monitoring drug-induced phospholipidosis.     

Infant sitting postural control appears robust across changes in surface context

Aim of the study: Independent sitting requires the control of the involved body segments over the base of support using information obtained from the three sensory systems (visual, vestibular, and somatosensory). The contribution of somatosensory information in infant sitting has not been explored. To address this gap, we altered the context of the sitting support surface and examined the infants’ immediate postural responses.

Materials and methods: Ten 7-month-old typically developing infants sat on compliant and firm surfaces in one session. Spatial, frequency, and temporal measures of postural control were obtained using center of pressure data.

Results Our results suggest that infants’ postural sway is not immediately affected by the different types of foam surface while sitting.

Conclusions: It seems that mature sitter infants are able to adapt to different environmental constraints by disregarding the distorted somatosensory information from the support surface and relying more on their remaining senses (visual and vestibular) to control their sitting posture.     

Deciphering the MHC-associated peptidome: a review of naturally processed ligand data

Introduction: The availability of big data sets (‘OMICS’) has greatly impacted fundamental and translational science. High-throughput analysis of HLA class I and II associated peptidomes by mass spectrometry (MS) has generated large datasets, with the last decade witnessing tremendous growth in the breadth and number of studies.

Areas covered: For this, we first analyzed naturally processed peptide (NP) data captured within the IEDB to survey and characterize the current state of NP data. We next asked to what extent the NP data overlap with existing T cell epitope and MHC binding data.

Expert commentary: The current collection of NP data represents a large and diverse set of class I/II peptides mostly derived from self-antigens. These data overlap only marginally with existing immunogenicity and binding data and it is thus difficult to ascertain the correspondence between the different assay methodologies. This highlights a need for unbiased studies benchmarking in model antigen systems how well MHC binding and NP data predicts immunogenicity. Going forward, efforts at generating an integrated process for capturing all NP, curating associated metadata and accessing NP data from an immunological viewpoint will be important for development of novel methods for identifying optimal target antigens and for class I and II epitope prediction.     

BioGPS and GXD: mouse gene expression data—the benefits and challenges of data integration

Mouse gene expression data are complex and voluminous. To maximize the utility of these data, they must be made readily accessible through databases, and those resources need to place the expression data in the larger biological context. Here we describe two community resources that approach these problems in different but complementary ways: BioGPS and the Mouse Gene Expression Database (GXD). BioGPS connects its large and homogeneous microarray gene expression reference data sets via plugins with a heterogeneous collection of external gene centric resources, thus casting a wide but loose net. GXD acquires different types of expression data from many sources and integrates these data tightly with other types of data in the Mouse Genome Informatics (MGI) resource, with a strong emphasis on consistency checks and manual curation. We describe and contrast the “loose” and “tight” data integration strategies employed by BioGPS and GXD, respectively, and discuss the challenges and benefits of data integration. BioGPS is freely available at http://biogps.org. GXD is freely available through the MGI web site (www.informatics.jax.org) or directly at www.informatics.jax.org/expression.shtml.