The scientific literature represents a rich source for retrieval of knowledge on associations between biomedical concepts such as genes, diseases and cellular processes. A commonly used method to establish relationships between biomedical concepts from literature is co-occurrence. Apart from its use in knowledge retrieval, the co-occurrence method is also wellsuited to discover new, hidden relationships between biomedical concepts following a simple ABC-principle, in which A and C have no direct relationship, but are connected via shared B-intermediates. In this paper we describe CoPub Discovery, a tool that mines the literature for new relationships between biomedical concepts. Statistical analysis using ROC curves showed that CoPub Discovery performed well over a wide range of settings and keyword thesauri. We subsequently used CoPub Discovery to search for new relationships between genes, drugs, pathways and diseases. Several of the newly found relationships were validated using independent literature sources. In addition, new predicted relationships between compounds and cell proliferation were validated and confirmed experimentally in an in vitro cell proliferation assay. The results show that CoPub Discovery is able to identify novel associations between genes, drugs, pathways and diseases that have a high probability of being biologically valid. This makes CoPub Discovery a useful tool to unravel the mechanisms behind disease, to find novel drug targets, or to find novel applications for existing drugs. © 2010 Frijters et al.
In the life of flowering plants, seed germination is a critical step to ensure survival into the next generation. Generally the seed prior to germination has been in a dormant state with a low rate of metabolism. In the transition from a dormant seed to a germinating seed, various epigenetic mechanisms play a regulatory role. Here, we demonstrate that the over-expression of chromatin remodeling ATPase genes (AtCHR12 or AtCHR23) reduced the frequency of seed germination in Arabidopsis thaliana up to 30% relative to the wild-type seeds. On the other hand, single loss-of-function mutations of the two genes did not affect seed germination. The reduction of germination in over-expressing mutants was more pronounced in stress conditions (salt or high temperature), showing the impact of the environment. Reduced germinations upon over-expression coincided with increased transcript levels of seed maturation genes and with reduced degradation of their mRNAs stored in dry seeds. Our results indicate that repression of AtCHR12/23 gene expression in germinating wild-type Arabidopsis seeds is required for full germination. This establishes a functional link between chromatin modifiers and regulatory networks towards seed maturation and germination.
tmoA and related genes encode the alpha-subunit of the hydroxylase component of the major group (subgroup 1 of subfamily 2) of bacterial multicomponent mono-oxygenase enzyme complexes involved in aerobic benzene, toluene, ethylbenzene and xylene (BTEX) degradation. A PCR-denaturing gradient gel electrophoresis (DGGE) method was developed to assess the diversity of tmoA-like gene sequences in environmental samples using a newly designed moderately degenerate primer set suitable for that purpose. In 35 BTEX-degrading bacterial strains isolated from a hydrocarbon polluted aquifer, tmoA-like genes were only detected in two o-xylene degraders and were identical to the touA gene of Pseudomonas stutzeri OX1. The diversity of tmoA-like genes was examined in DNA extracts from contaminated and non-contaminated subsurface samples at a site containing a BTEX-contaminated groundwater plume. Differences in DGGE patterns were observed between strongly contaminated, less contaminated and non-contaminated samples and between different depths, suggesting that the diversity of tmoA-like genes was determined by environmental conditions including the contamination level. Phylogenetic analysis of the protein sequences deduced from the amplified amplicons showed that the diversity of TmoA-analogues in the environment is larger than suggested from described TmoA-analogues from cultured isolates, which was translated in the DGGE patterns. Although different positions on the DGGE gel can correspond to closely related TmoA-proteins, relationships could be noticed between the position of tmoA-like amplicons in the DGGE profile and the phylogenetic position of the deduced protein sequence.
Jaarlijks worden in Nederland ongeveer 600.000 mensen ziek door het eten van besmet voedsel. De voedselverwerkende industrie heeft sterke behoefte aan meer grip op het bewaken van de hygiëne in de fabrieken om te voorkomen dat besmette producten in de winkels komen. In het afgeronde RAAK-mkb project “Precision Food Safety” is onderzocht wat de meerwaarde is van de toepassing van Whole Genome Sequencing (WGS) bij het achterhalen van de transmissieroutes van de pathogene bacterie Listeria monocytogenes bij voedselverwerkende bedrijven. Er is een biobank opgebouwd met bijna 600 L. monocytogenes stammen afkomstig van de fabrieksomgeving en producten van vis-, vlees- en groente-verwerkende bedrijven. Deze stammen zijn gesequenced met behulp van Nanopore sequencing. Vervolgens is de verwantschap tussen de stammen bepaald met een in het project ontwikkelde bioinformatica pijplijn. Het project bleek zeer succesvol. In “Advanced Precision in Food Safety ” wordt het onderzoek naar voedselveiligheid verbreed, door L. monocytogenes al aan het begin van de voedselverwerkingsketen (in grondstoffen en ingrediënten) te monitoren. Verder zal de WGS-methodiek worden toegepast op Salmonella enterica en zal de huidige bioinformatica pijplijn worden aangepast om transmissieroutes van dit andere belangrijke voedselpathogeen te achterhalen. Ter verdieping zal het ziekteverwekkende karakter van L. monocytogenes stammen worden bepaald op basis van het serotype en de aanwezigheid van ~60 beschreven virulentiegenen. Daarbij worden gegevens uit verschillende databases, met sequence data van zowel humane als niet humane stammen, met elkaar vergeleken. Zowel in het laboratorium als in de fabrieksomgeving zal het effect van verschillende schoonmaakmiddelen en schoonmaaktechnieken worden onderzocht op het elimineren van L. monocytogenes van oppervlaktes. Tevens wordt onderzocht of shotgun metagenomics analyse kan worden ingezet om voedsel snel en breed op voedselpathogenen te monitoren. Een prototype van een webapplicatie, waarmee bedrijven verkregen resultaten kunnen inzien en aanvullen zal verder worden ontwikkeld en door voedselverwerkende bedrijven worden getest en geïmplementeerd.
Huntington’s disease (HD) and various spinocerebellar ataxias (SCA) are autosomal dominantly inherited neurodegenerative disorders caused by a CAG repeat expansion in the disease-related gene1. The impact of HD and SCA on families and individuals is enormous and far reaching, as patients typically display first symptoms during midlife. HD is characterized by unwanted choreatic movements, behavioral and psychiatric disturbances and dementia. SCAs are mainly characterized by ataxia but also other symptoms including cognitive deficits, similarly affecting quality of life and leading to disability. These problems worsen as the disease progresses and affected individuals are no longer able to work, drive, or care for themselves. It places an enormous burden on their family and caregivers, and patients will require intensive nursing home care when disease progresses, and lifespan is reduced. Although the clinical and pathological phenotypes are distinct for each CAG repeat expansion disorder, it is thought that similar molecular mechanisms underlie the effect of expanded CAG repeats in different genes. The predicted Age of Onset (AO) for both HD, SCA1 and SCA3 (and 5 other CAG-repeat diseases) is based on the polyQ expansion, but the CAG/polyQ determines the AO only for 50% (see figure below). A large variety on AO is observed, especially for the most common range between 40 and 50 repeats11,12. Large differences in onset, especially in the range 40-50 CAGs not only imply that current individual predictions for AO are imprecise (affecting important life decisions that patients need to make and also hampering assessment of potential onset-delaying intervention) but also do offer optimism that (patient-related) factors exist that can delay the onset of disease.To address both items, we need to generate a better model, based on patient-derived cells that generates parameters that not only mirror the CAG-repeat length dependency of these diseases, but that also better predicts inter-patient variations in disease susceptibility and effectiveness of interventions. Hereto, we will use a staggered project design as explained in 5.1, in which we first will determine which cellular and molecular determinants (referred to as landscapes) in isogenic iPSC models are associated with increased CAG repeat lengths using deep-learning algorithms (DLA) (WP1). Hereto, we will use a well characterized control cell line in which we modify the CAG repeat length in the endogenous ataxin-1, Ataxin-3 and Huntingtin gene from wildtype Q repeats to intermediate to adult onset and juvenile polyQ repeats. We will next expand the model with cells from the 3 (SCA1, SCA3, and HD) existing and new cohorts of early-onset, adult-onset and late-onset/intermediate repeat patients for which, besides accurate AO information, also clinical parameters (MRI scans, liquor markers etc) will be (made) available. This will be used for validation and to fine-tune the molecular landscapes (again using DLA) towards the best prediction of individual patient related clinical markers and AO (WP3). The same models and (most relevant) landscapes will also be used for evaluations of novel mutant protein lowering strategies as will emerge from WP4.This overall development process of landscape prediction is an iterative process that involves (a) data processing (WP5) (b) unsupervised data exploration and dimensionality reduction to find patterns in data and create “labels” for similarity and (c) development of data supervised Deep Learning (DL) models for landscape prediction based on the labels from previous step. Each iteration starts with data that is generated and deployed according to FAIR principles, and the developed deep learning system will be instrumental to connect these WPs. Insights in algorithm sensitivity from the predictive models will form the basis for discussion with field experts on the distinction and phenotypic consequences. While full development of accurate diagnostics might go beyond the timespan of the 5 year project, ideally our final landscapes can be used for new genetic counselling: when somebody is positive for the gene, can we use his/her cells, feed it into the generated cell-based model and better predict the AO and severity? While this will answer questions from clinicians and patient communities, it will also generate new ones, which is why we will study the ethical implications of such improved diagnostics in advance (WP6).
Kennisnetwerken in het Nederlandse onderwijsveld zijn door formalisering en schaalvergroting aan een nieuwe fase begonnen. In dit project wordt kennis over de effectiviteit van deze formele netwerken hertaald naar de huidige situatie.Doel Kennisnetwerken in het Nederlandse onderwijsveld richten zich op de ontwikkeling van onderwijsprofessionals en -organisaties. Het zijn geneste systemen met een collectieve verantwoordelijkheid voor organisatie-overstijgende onderwijsvraagstukken. Dit onderzoek brengt voor 12 regionale kennisnetwerken in kaart hoe zij als complex systeem functioneren, wat de opbrengsten zijn en onder welke omstandigheden die zich voordoen. Doel is ontwerprichtlijnen voor optimale, duurzame processen van kennisontwikkeling, -deling en -benutting in regionale kennisnetwerken te formuleren. Het gaat hier om netwerken waarin scholen, kennisinstellingen en bedrijven plaatsnemen en samenwerken aan bijv. een duurzame onderzoekscultuur. Resultaten ontwerprichtlijnen voor optimale, duurzame processen van kennisontwikkeling, -deling en -benutting in regionale kennisnetwerken jaarlijkse reflectiesessies voor de kennisnetwerken leidraden voor de kennisnetwerken en de gehele onderwijspraktijk wetenschappelijke artikelen en bijdragen aan congressen Looptijd 01 juli 2023 - 31 december 2027 Aanpak We zetten verschillende elkaar aanvullende kwalitatieve en kwantitatieve onderzoeksmethoden in zoals sociaal netwerk vragenlijsten, (groeps-)interviews en document/productanalyses ten behoeve van within-case en cross-case analyses. Vanuit lectoraat Werken in Onderwijs voegen wij o.a. expertise toe over sociaal netwerk analyse.
