Regulatory bioinformatics for food and drug safety

Abstract "Regulatory Bioinformatics" strives to develop and implement a standardized and transparent bioinformatic framework to support the implementation of existing and emerging technologies in regulatory decision-making. It has great potential to improve public health through the development and use of clinically important medical products and tools to manage the safety of the food supply. However, the application of regulatory bioinformatics also poses new challenges and requires new knowledge and skill sets. In the latest Global Coalition on Regulatory Science Research (GCRSR) governed conference, Global Summit on Regulatory Science (GSRS2015), regulatory bioinformatics principles were presented with respect to global trends, initiatives and case studies. The discussion revealed that datasets, analytical tools, skills and expertise are rapidly developing, in many cases via large international collaborative consortia. It also revealed that significant research is still required to realize the potential applications of regulatory bioinformatics. While there is significant excitement in the possibilities offered by precision medicine to enhance treatments of serious and/or complex diseases, there is a clear need for further development of mechanisms to securely store, curate and share data, integrate databases, and standardized quality control and data analysis procedures. A greater understanding of the biological significance of the data is also required to fully exploit vast datasets that are becoming available. The application of bioinformatics in the microbiological risk analysis paradigm is delivering clear benefits both for the investigation of food borne pathogens and for decision making on clinically important treatments. It is recognized that regulatory bioinformatics will have many beneficial applications by ensuring high quality data, validated tools and standardized processes, which will help inform the regulatory science community of the requirements necessary to ensure the safe introduction and effective use of these applications

article ID bav101; V C The Author(s) Database

These authors contributed equally to this work. Abstract The DNA target sequence is the key element in designing detection methods for genetically modified organisms (GMOs). Unfortunately this information is frequently lacking, especially for unauthorized GMOs. In addition, patent sequences are generally poorly annotated, buried in complex and extensive documentation and hard to link to the corresponding GM event. Here, we present the JRC GMO-Amplicons, a database of amplicons collected by screening public nucleotide sequence databanks by in silico determination of PCR amplification with reference methods for GMO analysis. The European Union Reference Laboratory for Genetically Modified Food and Feed (EU-RL GMFF) provides these methods in the GMOMETHODS database to support enforcement of EU legislation and GM food/feed control. The JRC GMO-Amplicons database is composed of more than 240 000 amplicons, which can be easily accessed and screened through a web interface. To our knowledge, this is the first attempt at pooling and collecting publicly available sequences related to GMOs in food and feed. The JRC GMOAmplicons supports control laboratories in the design and assessment of GMO methods, providing inter-alia in silico prediction of primers specificity and GM targets coverage. The new tool can assist the laboratories in the analysis of complex issues, such as the detection and identification of unauthorized GMOs. Notably, the JRC GMO-Amplicons database allows the retrieval and characterization of GMO-related sequences included in patents documentation. Finally, it can help annotating poorly described GM sequences and identifying new relevant GMO-related sequences in public databases. The JRC GMO-Amplicons is freely accessible through a web-based portal that is hosted on the EU-RL GMFF website

Towards Plant Species Identification in Complex Samples: A Bioinformatics Pipeline for the Identification of Novel Nuclear Barcode Candidates

<div><p>Monitoring of the food chain to fight fraud and protect consumer health relies on the availability of methods to correctly identify the species present in samples, for which DNA barcoding is a promising candidate. The nuclear genome is a rich potential source of barcode targets, but has been relatively unexploited until now. Here, we show the development and use of a bioinformatics pipeline that processes available genome sequences to automatically screen large numbers of input candidates, identifies novel nuclear barcode targets and designs associated primer pairs, according to a specific set of requirements. We applied this pipeline to identify novel barcodes for plant species, a kingdom for which the currently available solutions are known to be insufficient. We tested one of the identified primer pairs and show its capability to correctly identify the plant species in simple and complex samples, validating the output of our approach.</p></div

An acute, double-blind, placebo-controlled crossover study of 320mg and 640mg doses of a special extract of Bacopa monnieri (CDRI 08) on sustained cognitive performance

Standardized extracts of the traditional Ayurvedic medicine Bacopa monnieri (BM) (Brahmi) have been recently shown to have cognitive enhancing effects in chronic administration studies. Pre-clinical work has also identified a number of acute anxiolytic, nootropic, and cardiovascular effects of BM. There has, however, been little research on the acute effects of BM on cognitive function. The current study aimed to assess the acute effects of a specific extract of BM (KeenMind® - CDRI 08) in a double-blind, placebo-controlled study in normal healthy participants who completed a cognitively demanding series of tests. Twenty-four healthy volunteers completed six repetitions of the Cognitive Demand Battery (CDB) after consuming a placebo, 320mg BM or 640mg of BM in a cross-over design and provided cardiovascular and mood assessments before and after treatment. Change from baseline scores indicated that the 320mg dose of BM improved performance at the first, second, and fourth repetition post-dosing on the CDB, and the treatments had no effect upon cardiovascular activity or in attenuating task-induced ratings of stress and fatigue. It was concluded that assessment of an earlier pharmacological window and use of less memory-specific cognitive tests together with more temporally sensitive measures of brain activity may improve our understanding of the acute neurocognitive properties of BM

Species detection in various samples using the 23579-aaa barcoding primers.

<p>The tested samples were (A) Purchased maize (<i>Zea mays</i>) DNA. (B) Purchased soya (<i>Glycine max</i>) DNA. (C) A leaf from a rice (<i>Oryza sativa</i>) plant. (D) Fresh strawberries from the supermarket (<i>Fragaria x ananassa</i>). (E) A commercial pack of fruit and cereal muesli. The results are shown on a simplified taxonomy line, with the number of NGS reads assigned to that specific location as a blue circle whose area is proportional to the numerical value. The values in parenthesis represent the (number of clusters:total number of reads).</p

Bioinformatics pipeline for the identification of DNA barcodes in the nuclear genome.

<p>Scheme representing the flow of the different steps in the bioinformatics pipeline designed to process input sequences (top left) in order to output potential primer pairs amplifying novel DNA barcoding targets (bottom right). See text and Supporting Information for details.</p

Expanding the Galaxy’s reference data

Properly and effectively managing reference datasets is an important task for many bioinformatics analyses. Refgenie is a reference asset management system that allows users to easily organize, retrieve and share such datasets. Here, we describe the integration of refgenie into the Galaxy platform. Server administrators are able to configure Galaxy to make use of reference datasets made available on a refgenie instance. In addition, a Galaxy Data Manager tool has been developed to provide a graphical interface to refgenie’s remote reference retrieval functionality. A large collection of reference datasets has also been made available using the CVMFS (CernVM File System) repository from GalaxyProject.org, with mirrors across the USA, Canada, Europe and Australia, enabling easy use outside of Galaxy. Availability and implementation The ability of Galaxy to use refgenie assets was added to the core Galaxy framework in version 22.01, which is available from https://github.com/galaxyproject/galaxy under the Academic Free License version 3.0. The refgenie Data Manager tool can be installed via the Galaxy ToolShed, with source code managed at https://github.com/BlankenbergLab/galaxy-tools-blankenberg/tree/main/data_managers/data_manager_refgenie_pull and released using an MIT license. Access to existing data is also available through CVMFS, with instructions at https://galaxyproject.org/admin/reference-data-repo/. No new data were generated or analyzed in support of this research