Between Common and Digital Library – 600 years of experience and innovation. An insight into Cambridge University Library, Great Britain

This is the final version of the article. It first appeared from De Gruyter via https://doi.org/10.1515/bd-2017-0118Zusammenfassung Die Cambridge University Library, Großbritannien, mit einer über 600jährigen Tradition und Geschichte widmet sich verstärkt den digitalen Transformationsprozessen. Nicht nur Entwicklungen im Bereich Open Science, sondern auch in der Digitalen Bibliothek kennzeichnen diesen Fortschritt.</jats:p

An evaluation of the Wii Nunchuk as an alternative assistive device for people with intellectual and physical disabilities using switch controlled software

Many people with intellectual disabilities also have physical difficulties which prevent them from using standard computer control devices. Custom made alternative devices for those with special needs can be expensive and the low unit turnover makes the prospect unattractive to potential manufacturers. One solution is to explore the potential of devices used in contemporary gaming technology, such as the Nintendo Wii. The Wii Nunchuk has the potential to replace joystick functions with the advantages of not being surface bound and easier for some individuals to grasp. This study evaluated the feasibility of using the Nunchuk by comparing its performance as a switch with the participant's usual switch. Twenty three volunteers aged between 17 and 21 with intellectual and physical disabilities completed a Single Switch Performance Test using the new device and their familiar device. For most functions of the switch, there was no significant difference between the participants' performance using the Nunchuck and their familiar device. Additional analysis found that some participants' performance did improve whilst using the Nunchuck, but this was not significantly related to physical or cognitive ability. Those whose performance was better with the Nunchuk were more likely to hold it in the conventional way than were those who had better performance with their familiar device. This merits it being offered as a possible alternative to currently available switches for those with physical difficulties affecting their grip

Bioremediation of 27 Micropollutants by Symbiotic Microorganisms of Wetland Macrophytes

Background: Micropollutants in bodies of water represent many challenges. We addressedthese challenges by the application of constructed wetlands, which represent advanced treatmenttechnology for the removal of micropollutants from water. However, which mechanisms specificallycontribute to the removal efficiency often remains unclear. Methods: Here, we focus on the removalof 27 micropollutants by bioremediation. For this, macrophytesPhragmites australis,Iris pseudacorusandLythrum salicariawere taken from established wetlands, and a special experimental set-up wasdesigned. In order to better understand the impact of the rhizosphere microbiome, we determinedthe microbial composition using 16S rRNA gene sequencing and investigated the role of identifiedgenera in the micropollutant removal of micropollutants. Moreover, we studied the colonizationof macrophyte roots by arbuscular mycorrhizal fungi, which are known for their symbiotic rela-tionship with plants. This symbiosis could result in increased removal of present micropollutants.Results: We foundIris pseudacorusto be the most successful bioremediative system, as it removed22 compounds, including persistent ones, with more than 80% efficiency. The most abundant generathat contributed to the removal of micropollutants werePseudomonas, Flavobacterium, Variovorax,Methylotenera, Reyranella, AmaricoccusandHydrogenophaga.Iris pseudacorusexhibited the highest colo-nization rate (56%). Conclusions: Our experiments demonstrate the positive impact of rhizospheremicroorganisms on the removal of micropollutants

The gut microbiome molecular complex in human health and disease

The human gut microbiome produces a functional complex of biomolecules, including nucleic acids, (poly) peptides, structural molecules, and metabolites. This impacts human physiology in multiple ways, especially by triggering inflammatory pathways in disease. At present, much remains to be learned about the identity of key effectors and their causal roles

miRTrail - a comprehensive webserver for analyzing gene and miRNA patterns to enhance the understanding of regulatory mechanisms in diseases

<p>Abstract</p> <p>Background</p> <p>Expression profiling provides new insights into regulatory and metabolic processes and in particular into pathogenic mechanisms associated with diseases. Besides genes, non-coding transcripts as microRNAs (miRNAs) gained increasing relevance in the last decade. To understand the regulatory processes of miRNAs on genes, integrative computer-aided approaches are essential, especially in the light of complex human diseases as cancer.</p> <p>Results</p> <p>Here, we present miRTrail, an integrative tool that allows for performing comprehensive analyses of interactions of genes and miRNAs based on expression profiles. The integrated analysis of mRNA and miRNA data should generate more robust and reliable results on deregulated pathogenic processes and may also offer novel insights into the regulatory interactions between miRNAs and genes. Our web-server excels in carrying out gene sets analysis, analysis of miRNA sets as well as the combination of both in a systems biology approach. To this end, miRTrail integrates information on 20.000 genes, almost 1.000 miRNAs, and roughly 280.000 putative interactions, for Homo sapiens and accordingly for Mus musculus and Danio rerio. The well-established, classical Chi-squared test is one of the central techniques of our tool for the joint consideration of miRNAs and their targets. For interactively visualizing obtained results, it relies on the network analyzers and viewers BiNA or Cytoscape-web, also enabling direct access to relevant literature. We demonstrated the potential of miRTrail by applying our tool to mRNA and miRNA data of malignant melanoma. MiRTrail identified several deregulated miRNAs that target deregulated mRNAs including miRNAs hsa-miR-23b and hsa-miR-223, which target the highest numbers of deregulated mRNAs and regulate the pathway "basal cell carcinoma". In addition, both miRNAs target genes like PTCH1 and RASA1 that are involved in many oncogenic processes.</p> <p>Conclusions</p> <p>The application on melanoma samples demonstrates that the miRTrail platform may open avenues for investigating the regulatory interactions between genes and miRNAs for a wide range of human diseases. Moreover, miRTrail cannot only be applied to microarray based expression profiles, but also to NGS-based transcriptomic data. The program is freely available as web-server at mirtrail.bioinf.uni-sb.de.</p

Comparison of initial oral microbiomes of young adults with and without cavitated dentin caries lesions using an in situ biofilm model

Dental caries is caused by acids released from bacterial biofilms. However, the in vivo formation of initial biofilms in relation to caries remains largely unexplored. The aim of this study was to compare the oral microbiome during the initial phase of bacterial colonization for individuals with (CC) and without (NC) cavitated dentin caries lesions. Bovine enamel slabs on acrylic splints were worn by the volunteers (CC: 14, NC: 13) for in situ biofilm formation (2 h, 4 h, 8 h, 1 ml saliva as reference). Sequencing of the V1/V2 regions of the 16S rRNA gene was performed (MiSeq). The relative abundances of individual operational taxonomic units (OTUs) were compared between samples from the CC group and the NC group. Random forests models were furthermore trained to separate the groups. While the overall heterogeneity did not differ substantially between CC and NC individuals, several individual OTUs were found to have significantly different relative abundances. For the 8 h samples, most of the significant OTUs showed higher relative abundances in the CC group, while the majority of significant OTUs in the saliva samples were more abundant in the NC group. Furthermore, using OTU signatures enabled a separation between both groups, with area-under-the-curve (AUC) values of ~0.8. In summary, the results suggest that initial oral biofilms provide the potential to differentiate between CC and NC individuals

Routes of dispersion of antibiotic resistance genes from the poultry farm system

Poultry farms are hotspots for the development and spread of antibiotic resistance genes (ARGs), due to high stocking densities and extensive use of antibiotics, posing a threat of spread and contagion to workers and the external environment. Here, we applied shotgun metagenome sequencing to characterize the gut microbiome and resistome of poultry, workers and their households - also including microbiomes from the internal and external farm environment – in three different farms in Italy during a complete rearing cycle. Our results highlighted a relevant overlap among the microbiomes of poultry, workers, and their families (gut and skin), with clinically relevant ARGs and associated mobile elements shared in both poultry and human samples. On a finer scale, the reconstruction of species-level genome bins (SGBs) allowed us to delineate the dynamics of microorganism and ARGs dispersion from farm systems. We found the associations with worker microbiomes representing the main route of ARGs dispersion from poultry to human populations. Collectively, our findings clearly demonstrate the urgent need to implement more effective procedures to counteract ARGs dispersion from poultry food systems and the relevance of metagenomics-based metacommunity approaches to monitor the ARGs dispersion process for the safety of the working environment on farms

PathoFact: a pipeline for the prediction of virulence factors and antimicrobial resistance genes in metagenomic data

Background Pathogenic microorganisms cause disease by invading, colonizing, and damaging their host. Virulence factors including bacterial toxins contribute to pathogenicity. Additionally, antimicrobial resistance genes allow pathogens to evade otherwise curative treatments. To understand causal relationships between microbiome compositions, functioning, and disease, it is essential to identify virulence factors and antimicrobial resistance genes in situ. At present, there is a clear lack of computational approaches to simultaneously identify these factors in metagenomic datasets. Results Here, we present PathoFact, a tool for the contextualized prediction of virulence factors, bacterial toxins, and antimicrobial resistance genes with high accuracy (0.921, 0.832 and 0.979, respectively) and specificity (0.957, 0.989 and 0.994). We evaluate the performance of PathoFact on simulated metagenomic datasets and perform a comparison to two other general workflows for the analysis of metagenomic data. PathoFact outperforms all existing workflows in predicting virulence factors and toxin genes. It performs comparably to one pipeline regarding the prediction of antimicrobial resistance while outperforming the others. We further demonstrate the performance of PathoFact on three publicly available case-control metagenomic datasets representing an actual infection as well as chronic diseases in which either pathogenic potential or bacterial toxins are hypothesized to play a role. In each case, we identify virulence factors and AMR genes which differentiated between the case and control groups, thereby revealing novel gene associations with the studied diseases. Conclusion PathoFact is an easy-to-use, modular, and reproducible pipeline for the identification of virulence factors, bacterial toxins, and antimicrobial resistance genes in metagenomic data. Additionally, our tool combines the prediction of these pathogenicity factors with the identification of mobile genetic elements. This provides further depth to the analysis by considering the genomic context of the pertinent genes. Furthermore, PathoFact’s modules for virulence factors, toxins, and antimicrobial resistance genes can be applied independently, thereby making it a flexible and versatile tool. PathoFact, its models, and databases are freely available at https://pathofact.lcsb.uni.lu

Integrated multi-omics of the human gut microbiome in a case study of familial type 1 diabetes.

The gastrointestinal microbiome is a complex ecosystem with functions that shape human health. Studying the relationship between taxonomic alterations and functional repercussions linked to disease remains challenging. Here, we present an integrative approach to resolve the taxonomic and functional attributes of gastrointestinal microbiota at the metagenomic, metatranscriptomic and metaproteomic levels. We apply our methods to samples from four families with multiple cases of type 1 diabetes mellitus (T1DM). Analysis of intra- and inter-individual variation demonstrates that family membership has a pronounced effect on the structural and functional composition of the gastrointestinal microbiome. In the context of T1DM, consistent taxonomic differences were absent across families, but certain human exocrine pancreatic proteins were found at lower levels. The associated microbial functional signatures were linked to metabolic traits in distinct taxa. The methodologies and results provide a foundation for future large-scale integrated multi-omic analyses of the gastrointestinal microbiome in the context of host-microbe interactions in human health and disease