Benchmarking network propagation methods for disease gene identification

In-silico identification of potential target genes for disease is an essential aspect of drug target discovery. Recent studies suggest that successful targets can be found through by leveraging genetic, genomic and protein interaction information. Here, we systematically tested the ability of 12 varied algorithms, based on network propagation, to identify genes that have been targeted by any drug, on gene-disease data from 22 common non-cancerous diseases in OpenTargets. We considered two biological networks, six performance metrics and compared two types of input gene-disease association scores. The impact of the design factors in performance was quantified through additive explanatory models. Standard cross-validation led to over-optimistic performance estimates due to the presence of protein complexes. In order to obtain realistic estimates, we introduced two novel protein complex-aware cross-validation schemes. When seeding biological networks with known drug targets, machine learning and diffusion-based methods found around 2-4 true targets within the top 20 suggestions. Seeding the networks with genes associated to disease by genetics decreased performance below 1 true hit on average. The use of a larger network, although noisier, improved overall performance. We conclude that diffusion-based prioritisers and machine learning applied to diffusion-based features are suited for drug discovery in practice and improve over simpler neighbour-voting methods. We also demonstrate the large impact of choosing an adequate validation strategy and the definition of seed disease genesPeer ReviewedPostprint (published version

eBank UK: linking research data, scholarly communication and learning

This paper includes an overview of the changing landscape of scholarly communication and describes outcomes from the innovative eBank UK project, which seeks to build links from e-research through to e-learning. As introduction, the scholarly knowledge cycle is described and the role of digital repositories and aggregator services in linking data-sets from Grid-enabled projects to e-prints through to peer-reviewed articles as resources in portals and Learning Management Systems, are assessed. The development outcomes from the eBank UK project are presented including the distributed information architecture, requirements for common ontologies, data models, metadata schema, open linking technologies, provenance and workflows. Some emerging challenges for the future are presented in conclusion

Directing Differentiation of Pluripotent Stem Cells Toward Retinal Pigment Epithelium Lineage

Development of efficient and reproducible conditions for directed differentiation of pluripotent stem cells into specific cell types is important not only to understand early human development but also to enable more practical applications, such as in vitro disease modeling, drug discovery, and cell therapies. The differentiation of stem cells to retinal pigment epithelium (RPE) in particular holds promise as a source of cells for therapeutic replacement in age-related macular degeneration. Here we show development of an efficient method for deriving homogeneous RPE populations in a period of 45 days using an adherent, monolayer system and defined xeno-free media and matrices. The method utilizes sequential inhibition and activation of the Activin and bone morphogenetic protein signaling pathways and can be applied to both human embryonic stem cells and induced pluripotent stem cells as the starting population. In addition, we use whole genome transcript analysis to characterize cells at different stages of differentiation that provides further understanding of the developmental dynamics and fate specification of RPE. We show that with the described method, RPE develop through stages consistent with their formation during embryonic development. This characterization- together with the absence of steps involving embryoid bodies, three-dimensional culture, or manual dissections, which are common features of other protocols-makes this process very attractive for use in research as well as for clinical applications. SIGNIFICANCE: This report describes a novel method of directed differentiation to generate retinal pigment epithelium (RPE) cells from pluripotent stem cells. The employed method is based on adherent monolayer culture using xeno-free conditions and manipulation of the Activin and bone morphogenetic protein signaling pathway using small molecules and recombinant proteins. Whole genome microarray analysis was performed to characterize the differentiation process and understand the developmental path of RPE generation in vitro. This method can be applied for generation of RPE for research as well as for clinical applications

Single-cell RNAseq reveals seven classes of colonic sensory neuron.

OBJECTIVE: Integration of nutritional, microbial and inflammatory events along the gut-brain axis can alter bowel physiology and organism behaviour. Colonic sensory neurons activate reflex pathways and give rise to conscious sensation, but the diversity and division of function within these neurons is poorly understood. The identification of signalling pathways contributing to visceral sensation is constrained by a paucity of molecular markers. Here we address this by comprehensive transcriptomic profiling and unsupervised clustering of individual mouse colonic sensory neurons. DESIGN: Unbiased single-cell RNA-sequencing was performed on retrogradely traced mouse colonic sensory neurons isolated from both thoracolumbar (TL) and lumbosacral (LS) dorsal root ganglia associated with lumbar splanchnic and pelvic spinal pathways, respectively. Identified neuronal subtypes were validated by single-cell qRT-PCR, immunohistochemistry (IHC) and Ca2+-imaging. RESULTS: Transcriptomic profiling and unsupervised clustering of 314 colonic sensory neurons revealed seven neuronal subtypes. Of these, five neuronal subtypes accounted for 99% of TL neurons, with LS neurons almost exclusively populating the remaining two subtypes. We identify and classify neurons based on novel subtype-specific marker genes using single-cell qRT-PCR and IHC to validate subtypes derived from RNA-sequencing. Lastly, functional Ca2+-imaging was conducted on colonic sensory neurons to demonstrate subtype-selective differential agonist activation. CONCLUSIONS: We identify seven subtypes of colonic sensory neurons using unbiased single-cell RNA-sequencing and confirm translation of patterning to protein expression, describing sensory diversity encompassing all modalities of colonic neuronal sensitivity. These results provide a pathway to molecular interrogation of colonic sensory innervation in health and disease, together with identifying novel targets for drug development

Comprehensive molecular characterisation of epilepsy-associated glioneuronal tumours

Glioneuronal tumours are an important cause of treatment-resistant epilepsy. Subtypes of tumour are often poorly discriminated by histological features and may be difficult to diagnose due to a lack of robust diagnostic tools. This is illustrated by marked variability in the reported frequencies across different epilepsy surgical series. To address this, we used DNA methylation arrays and RNA sequencing to assay the methylation and expression profiles within a large cohort of glioneuronal tumours. By adopting a class discovery approach, we were able to identify two distinct groups of glioneuronal tumour, which only partially corresponded to the existing histological classification. Furthermore, by additional molecular analyses, we were able to identify pathogenic mutations in BRAF and FGFR1, specific to each group, in a high proportion of cases. Finally, by interrogating our expression data, we were able to show that each molecular group possessed expression phenotypes suggesting different cellular differentiation: astrocytic in one group and oligodendroglial in the second. Informed by this, we were able to identify CCND1, CSPG4, and PDGFRA as immunohistochemical targets which could distinguish between molecular groups. Our data suggest that the current histological classification of glioneuronal tumours does not adequately represent their underlying biology. Instead, we show that there are two molecular groups within glioneuronal tumours. The first of these displays astrocytic differentiation and is driven by BRAF mutations, while the second displays oligodendroglial differentiation and is driven by FGFR1 mutations

Digital PCR analysis of circulating tumor DNA: a biomarker for chondrosarcoma diagnosis, prognostication, and residual disease detection

Conventional chondrosarcoma is the most common primary bone tumor in adults. Prognosis corresponds with tumor grade but remains variable, especially for individuals with grade (G) II disease. There are currently no biomarkers available for monitoring or prognostication of chondrosarcoma. Circulating tumor DNA (ctDNA) has recently emerged as a promising biomarker for a broad range of tumor types. To date, little has been done to study the presence of ctDNA and its potential utility in the management of sarcomas, including chondrosarcoma. In this study, we have assessed ctDNA levels in a cohort of 71 patients, 32 with sarcoma, including 29 individuals with central chondrosarcoma (CS) and 39 with locally aggressive and benign bone and soft tissue tumors, using digital PCR. In patients with CS, ctDNA was detected in pretreatment samples in 14/29 patients, which showed clear correlation with tumor grade as demonstrated by the detection of ctDNA in all patients with GIII and dedifferentiated disease (n = 6) and in 8/17 patients with GII disease, but never associated with GI CS. Notably detection of ctDNA preoperatively in GII disease was associated with a poor outcome. A total of 14 patients with CS had ctDNA levels assessed at multiple time points and in most patients there was a clear reduction following surgical removal. This research lays the foundation for larger studies to assess the utility of ctDNA for chondrosarcoma diagnosis, prognostication, early detection of residual disease and monitoring disease progression

Enhancing the early student experience

This paper is concerned with identifying how the early student experience can be enhanced in order to improve levels of student retention and achievement. The early student experience is the focus of this project as the literature has consistently declared the first year to be the most critical in shaping persistence decisions. Programme managers of courses with high and low retention rates have been interviewed to identify activities that appear to be associated with good retention rates. The results show that there are similarities in the way programmes with high retention are run, with these features not being prevalent on programmes with low retention. Recommendations of activities that appear likely to enhance the early student experience are provided

Glioblastoma adaptation traced through decline of an IDH1 clonal driver and macro-evolution of a double-minute chromosome

In a glioblastoma tumour with multi-region sequencing before and after recurrence, we find an IDH1 mutation that is clonal in the primary but lost at recurrence. We also describe the evolution of a double-minute chromosome encoding regulators of the PI3K signalling axis that dominates at recurrence, emphasizing the challenges of an evolving and dynamic oncogenic landscape for precision medicin

Limitations to recording larger mammalian predators in savannah using camera traps and spoor

Traditionally, spoor (tracks, pug marks) have been used as a cost effective tool to assess the presence of larger mammals. Automated camera traps are now increasingly utilized to monitor wildlife, primarily as the cost has greatly declined and statistical approaches to data analysis have improved. While camera traps have become ubiquitous, we have little understanding of their effectiveness when compared to traditional approaches using spoor in the field. Here, we a) test the success of camera traps in recording a range of carnivore species against spoor; b) ask if simple measures of spoor size taken by amateur volunteers is likely to allow individual identification of leopards and c) for a trained tracker, ask if this approach may allow individual leopards to be followed with confidence in savannah habitat. We found that camera traps significantly under-recorded mammalian top and meso-carnivores, with camera traps more likely under-record the presence of smaller carnivores (civet 64%; genet 46%, Meller’s mongoose 45%) than larger (jackal sp. 30%, brown hyena 22%), while leopard was more likely to be recorded by camera trap (all recorded by camera trap only). We found that amateur trackers could be beneficial in regards to collecting presence data; however the large variance in measurements of spoor taken in the field by volunteers suggests that this approach is unlikely to add further data. Nevertheless, the use of simple spoor measurements in the field by a trained field researcher increases their ability to reliably follow a leopard trail in difficult terrain. This allows researchers to glean further data on leopard behaviour and habitat utilisation without the need for complex analysis