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This article describes PhenoMeter, a new type of metabolomics database search that accepts metabolite response patterns as queries and searches the MetaPhen database of reference patterns for responses that are statistically significantly similar or inverse for the purposes of detecting functional links. To identify a similarity measure that would detect functional links as reliably as possible, we compared the performance of four statistics in correctly top-matching metabolic phenotypes of Arabidopsis thaliana metabolism mutants affected in different steps of the photorespiration metabolic pathway to reference phenotypes of mutants affected in the same enzymes by independent mutations. The best performing statistic, the PhenoMeter Score (PM Score), was a function of both Pearson correlation and Fisher’s Exact Test of directional overlap. This statistic outperformed Pearson correlation, biweight midcorrelation and Fisher’s Exact Test used alone. To demonstrate general applicability, we show that the PhenoMeter reliably retrieved the most closely functionally-linked response in the database when queried with responses to a wide variety of environmental and genetic perturbations. Attempts to match metabolic phenotypes between independent studies were met with varying success and possible reasons for this are discussed. Overall, our results suggest that integration of pattern-based search tools into metabolomics databases will aid functional annotation of newly recorded metabolic phenotypes analogously to the way sequence similarity search algorithms have aided the functional annotation of genes and proteins. PhenoMeter is freely available at MetabolomeExpress (https://www.metabolome-express.org/phenometer.php).

The cytosolic ribosomal proteome of Arabidopsis thaliana has been studied intensively by a range of proteomics approaches and is now one of the best-characterised eukaryotic ribosomal proteomes. Plant cytosolic ribosomes are distinguished from other eukaryotic ribosomes by unique proteins, unique post-translational modifications and an abundance of ribosomal proteins for which multiple divergent paralogs are expressed and incorporated. Study of the A. thaliana ribosome has now progressed well beyond a simple cataloging of protein parts and is focused strongly on elucidating the functional roles of specific ribosomal proteins, their paralogous isoforms and covalent modifications. This review will summarise the current state of knowledge concerning the Arabidopsis cytosolic ribosomal proteome and highlight potentially fruitful areas of future research in this fast moving and important area.

Although plant metabolomics is largely carried out on Arabidopsis it is essentially genome-independent, and thus potentially applicable to a wide range of species. However, transfer of between species, or even between different tissues of the same species, is not facile. This is because the reliability of protocols for harvesting, handling and analysis depends on the biological features and chemical composition of the plant tissue. In parallel with the diversification of model species it is important to establish good handling and analytic practice, in order to augment computational comparisons between tissues and species. LC-MS-based metabolomics is one of the powerful approaches for metabolite profiling. By using a combination of different extraction methods, separation columns and ion detection, a very wide range of metabolites can be analysed. However, its application requires careful attention to exclude potential pitfalls, including artifactual changes in metabolite levels during sample preparation and analytic errors due to ion-suppression. Here we provide case studies with two different LC-MS-based metabolomics platforms and four species (Arabidopsis thaliana, Chlamydomonas reinhardtii, Solanum lycopersicum and Oryza sativa) that illustrate how such dangers can be detected and circumvented.

Bone mineral density (BMD) of the whole body and hind limb of young adult rats, with and without a sham-operated stifle joint was studied, using dual energy x-ray absorptiometry (DEXA) at three time points. Data from the whole body scan were used for analyses of BMD, bone mineral content (BMC), fat, lean, body weight (BW), percentage of BMC (%BMC), percentage of fat (%fat), and percentage of lean (%lean), none of which were significantly different between the groups at any time point. Significant (P < 0.05) differences in BMD, BMC, %BMC, BW, fat, %fat, and %lean were apparent at the second and third scans, compared with the initial scan, within both groups. Changes in whole body BMD, BMC, and %BMC as well as BW were highly correlated with time in both groups. In the hind limb scans, regions of interest (ROIs) were created to obtain values of BMD and BMC from the whole femur, whole tibia including the fibula, distal portion of the femur, and proximal portion of the tibia. Significant differences were not found between the groups for any ROIs. However, significant BMD and BMC increases were evident in all ROIs at the second and third scans, compared with the initial scan. Similar to those in the whole body scan, BMD and BMC obtained from ROIs were highly correlated with time. The positioning technique for the whole body and appendicular scans was analyzed by calculating percentage of the coefficient of variation (%CV) at the beginning of the study. The %CV was low and acceptable in ROIs for the hind limb and for all parameters of the whole body scan, except fat. The results suggest that in vivo DEXA scanning of the rat whole body and appendicular skeleton is highly reproducible and useful to study the whole skeleton, as well as a region of a long bone of the rat. Values for the sham-operated rats were not significantly different from those for the untreated controls, which suggests that soft tissue damage around the stifle joint did not alter BMD in the subchondral bone of the distal portion of the femur and proximal portion of the tibia.