Detecting a difference – assessing generalisability when modelling metabolome fingerprint data in longer term studies of genetically modified plants

There is current debate on whether genetically-manipulated plants might contain unexpected, potentially undesirable, changes in overall metabolite composition relative to that of the progenitor genotype. However, appropriate analytical technology and acceptable metrics of compositional similarity require development, particularly to allow data integration from different laboratories and different harvests. For an initial comprehensive overview of compositional similarity, we explored the use of a rapid and relatively non-selective fingerprinting technique based on flow injection electrospray ionisation mass spectrometry (FIE-MS). Six conventionally-bred potato cultivars and six experimental bioengineered potato genotypes were produced in four field blocks during two growing seasons and analysed on two different analytical instruments (LCT, Micromass in 2001 and LTQ, Thermo Finnigan in 2003). Field effects and overall process variability was found to be negligible when compared to inherited genotype variance. The data derived separately for experiments using tubers from individual harvest years were compared to assess the generalisability of models for the comparison of GM and non-GM potato tubers under investigation. This procedure proved appropriate for not only rapid assessment of similarities between plant genotypes but also to predict the identity of metabolite signals that could explain differences between genotype classes irrespective of the instrument used for analysis. Importantly, despite differences in ionisation and data acquisition properties of the two instruments the generalisation of models could be confirmed after correlation analysis of explanatory variables correctly identified the molecular origin of differences between genotypes. We conclude that FIE-MS metabolomics fingerprinting technology coupled to machine learning data analysis has great potential as a robust tool for first-pass metabolic phenotyping and, therefore, initial assessments of compositional similarities prior to use of more targeted hyphenated gas or liquid chromatography-mass spectrometry techniques.     

Copy number variants and genetic traits: closer to the resolution of phenotypic to genotypic variability

A considerable and unanticipated plasticity of the human genome, manifested as inter-individual copy number variation, has been discovered. These structural changes constitute a major source of inter-individual genetic variation that could explain variable penetrance of inherited (Mendelian and polygenic) diseases and variation in the phenotypic expression of aneuploidies and sporadic traits, and might represent a major factor in the aetiology of complex, multifactorial traits. For these reasons, an effort should be made to discover all common and rare copy number variants (CNVs) in the human population. This will also enable systematic exploration of both SNPs and CNVs in association studies to identify the genomic contributors to the common disorders and complex traits.     

Metabolomic analysis reveals a common pattern of metabolic re-programming during invasion of three host plant species by Magnaporthe grisea

The mechanisms by which biotrophic and hemi-biotrophic fungal pathogens simultaneously subdue plant defences and sequester host nutrients are poorly understood. Using metabolite fingerprinting, we show that Magnaporthe grisea , the causal agent of rice blast disease, dynamically re-programmes host metabolism during plant colonization. Identical patterns of metabolic change occurred during M. grisea infections in barley, rice and Brachypodium distachyon . Targeted metabolite profiling by GC-MS confirmed the modulation of a conserved set of metabolites. In pre-symptomatic tissues, malate and polyamines accumulated, rather than being utilized to generate defensive reactive oxygen species, and the levels of metabolites associated with amelioration of redox stress in various cellular compartments increased dramatically. The activity of NADP-malic enzyme and generation of reactive oxygen species were localized to pathogen penetration sites, and both appeared to be suppressed in compatible interactions. Early diversion of the shikimate pathway to produce quinate was observed, as well as accumulation of non-polymerized lignin precursors. These data are consistent with modulation of defensive phenylpropanoid metabolism by M. grisea and the inability of susceptible hosts to mount a hypersensitive reaction or produce lignified papillae (both involving reactive oxygen species) to restrict pathogen invasion. Rapid proliferation of M. grisea hyphae in plant tissue after 3 days was associated with accelerated nutrient acquisition and utilization by the pathogen. Conversion of photoassimilate into mannitol and glycerol for carbon sequestration and osmolyte production appear to drive hyphal growth. Taken together, our results suggest that fungal pathogens deploy a common metabolic re-programming strategy in diverse host species to suppress plant defence and colonize plant tissue.     

Identification of piperazine-bisamide GHSR antagonists for the treatment of obesity

Piperazine-bisamide analogs were discovered as partial agonists of human growth hormone secretagogue receptor (GHSR) in a high throughput screen. The partial agonists were optimized for potency and converted into antagonists through structure–activity relationship (SAR) studies. The efforts also led to the identification of potent antagonist with favorable PK profile suitable as a tool compound for in vivo studies.