PhenoMeter: A Metabolome Database Search Tool Using Statistical Similarity Matching of Metabolic Phenotypes for High-Confidence Detection of Functional Links

Development of RIKEN Plant Metabolome MetaDatabase

The advancement of metabolomics in terms of techniques for measuring small molecules has enabled the rapid detection and quantification of numerous cellular metabolites. Metabolomic data provide new opportunities to gain a deeper understanding of plant metabolism that can improve the health of both plants and humans that consume them. Although major public repositories for general metabolomic data have been established, the community still has shortcomings related to data sharing, especially in terms of data reanalysis, reusability and reproducibility. To address these issues, we developed the RIKEN Plant Metabolome MetaDatabase (RIKEN PMM, http://metabobank.riken.jp/pmm/db/plantMetabolomics), which stores mass spectrometry-based (e.g. gas chromatography-MS-based) metabolite profiling data of plants together with their detailed, structured experimental metadata, including sampling and experimental procedures. Our metadata are described as Linked Open Data based on the Resource Description Framework using standardized and controlled vocabularies, such as the Metabolomics Standards Initiative Ontology, which are to be integrated with various life and biomedical science data using the World Wide Web. RIKEN PMM implements intuitive and interactive operations for plant metabolome data, including raw data (netCDF format), mass spectra (NIST MSP format) and metabolite annotations. The feature is suitable not only for biologists who are interested in metabolomic phenotypes, but also for researchers who would like to investigate life science in general through plant metabolomic approaches.

Use of Integrative Interactomics for Improvement of Farm Animal Health and Welfare: An Example with Fescue Toxicosis

Rapid scientific advances are increasing our understanding of the way complex biological interactions integrate to maintain homeostatic balance and how seemingly small, localized perturbations can lead to systemic effects. The ‘omics movement, alongside increased throughput resulting from statistical and computational advances, has transformed our understanding of disease mechanisms and the multi-dimensional interaction between environmental stressors and host physiology through data integration into multi-dimensional analyses, i.e., integrative interactomics. This review focuses on the use of high-throughput technologies in farm animal research, including health- and toxicology-related papers. Although limited, we highlight recent animal agriculture-centered reports from the integrative multi-‘omics movement. We provide an example with fescue toxicosis, an economically costly disease affecting grazing livestock, and describe how integrative interactomics can be applied to a disease with a complex pathophysiology in the pursuit of novel treatment and management approaches. We outline how ‘omics techniques have been used thus far to understand fescue toxicosis pathophysiology, lay out a framework for the fescue toxicosis integrome, identify some challenges we foresee, and offer possible means for addressing these challenges. Finally, we briefly discuss how the example with fescue toxicosis could be used for other agriculturally important animal health and welfare problems.

Bioinformatics Resources for Plant Abiotic Stress Responses: State of the Art and Opportunities in the Fast Evolving -Omics Era

Abiotic stresses are among the principal limiting factors for productivity in agriculture. In the current era of continuous climate changes, the understanding of the molecular aspects involved in abiotic stress response in plants is a priority. The rise of -omics approaches provides key strategies to promote effective research in the field, facilitating the investigations from reference models to an increasing number of species, tolerant and sensitive genotypes. Integrated multilevel approaches, based on molecular investigations at genomics, transcriptomics, proteomics and metabolomics levels, are now feasible, expanding the opportunities to clarify key molecular aspects involved in responses to abiotic stresses. To this aim, bioinformatics has become fundamental for data production, mining and integration, and necessary for extracting valuable information and for comparative efforts, paving the way to the modeling of the involved processes. We provide here an overview of bioinformatics resources for research on plant abiotic stresses, describing collections from -omics efforts in the field, ranging from raw data to complete databases or platforms, highlighting opportunities and still open challenges in abiotic stress research based on -omics technologies.

Redox-Regulation of Photorespiration through Mitochondrial Thioredoxin o1

Photorespiration sustains photosynthesis in the presence of oxygen due to rapid metabolization of 2-phosphoglycolate, the major side-product of the oxygenase activity of Rubisco that also directly impedes carbon assimilation and allocation. Despite the fact that both the biochemical reactions and the underlying genetics are well characterized, information concerning the regulatory mechanisms that adjust photorespiratory flux is rare. Here, we studied the impact of mitochondrial-localized thioredoxin o1 (TRXo1) on photorespiratory metabolism. The characterization of an Arabidopsis (Arabidopsis thaliana) transfer DNA insertional line (trxo1-1) revealed an increase in the stoichiometry of photorespiratory CO2 release and impaired Gly-to-Ser turnover after a shift from high-to-low CO2 without changes in Gly decarboxylase (GDC) gene or protein expression. These effects were distinctly pronounced in a double mutant, where the TRXo1 mutation was combined with strongly reduced GDC T-protein expression. The double mutant (TxGT) showed reduced growth in air but not in high CO2, decreased photosynthesis, and up to 54-fold more Gly alongside several redox-stress-related metabolites. Given that GDC proteins are potential targets for redox-regulation, we also examined the in vitro properties of recombinant GDC l-proteins (lipoamide dehydrogenase) from plants and the cyanobacterium Synechocystis species strain PCC6803 and observed a redox-dependent inhibition by either artificial reducing agents or TRXo1 itself. Collectively, our results demonstrate that TRXo1 potentially adjusts photorespiration via redox-regulation of GDC in response to environmental changes.

Wheat drought tolerance in the field is predicted by amino acid responses to glasshouse-imposed drought

Water limits crop productivity, so selecting for a minimal yield gap in drier environments is critical to mitigate against climate change and land-use pressure. We investigated the responses of relative water content (RWC), stomatal conductance, chlorophyll content, and metabolites in flag leaves of commercial wheat (Triticum aestivum L.) cultivars to three drought treatments in the glasshouse and in field environments. We observed strong genetic associations between glasshouse-based RWC, metabolites, and yield gap-based drought tolerance (YDT; the ratio of yield in water-limited versus well-watered conditions) across 18 field environments spanning sites and seasons. Critically, RWC response to glasshouse drought was strongly associated with both YDT (r2=0.85, P<8E-6) and RWC under field drought (r2=0.77, P<0.05). Moreover, multiple regression analyses revealed that 98% of genetic YDT variance was explained by drought responses of four metabolites: serine, asparagine, methionine, and lysine (R2=0.98; P<0.01). Fitted coefficients suggested that, for given levels of serine and asparagine, stronger methionine and lysine accumulation was associated with higher YDT. Collectively, our results demonstrate that high-throughput, targeted metabolic phenotyping of glasshouse-grown plants may be an effective tool for selection of wheat cultivars with high field-derived YDT.

Net photosynthetic CO2 assimilation: more than just CO2 and O2 reduction cycles

Net photosynthetic assimilation in C₃ plants is mostly viewed as a simple balance between CO₂ fixation by Rubisco-catalyzed carboxylation and CO₂ production by photorespiration (and to a lower extent, by day respiration) that can be easily manipulated during gas exchange experiments using the CO₂  : O₂ ratio of the environment. However, it now becomes clear that it is not so simple, because the photosynthetic response to gaseous conditions involves 'ancillary' metabolisms, even in the short-term. That is, carbon and nitrogen utilization by pathways other than the Calvin cycle and the photorespiratory cycle, as well as rapid signaling events, can influence the observed rate of net photosynthesis. The potential impact of such ancillary metabolisms is assessed as well as how it must be taken into account to avoid misinterpretation of photosynthetic CO₂ response curves or low O₂ effects in C₃ leaves.

Nitrogen deprivation in Fusarium oxysporum promotes mycotoxin production via intermediates in the Krebs cycle and unreported methylmalonyl-CoA mutase activity

INTRODUCTION

Fusarium oxysporum has a high affinity for lignin and cellulose-based substrates and is known to grow in a wide range of environments. It is these properties and its ability to produce mycotoxins that have contributed to its pathogenicity in cereal crops that can affect human and animal health when ingested.

OBJECTIVES

Identify the mechanisms of mycotoxin production and map the functional output of F. oxysporum under varying growth conditions.

METHODS

Liquid and gas-based chromatography coupled with mass spectrometry was used to identify and map the untargeted metabolic pathway of F. oxysporum grown using nitrogen limited and organic/inorganic nitrogen supplemented media.

RESULTS

Over 1300 metabolites were identified, relating to 42 metabolic pathways. Of these, 520 metabolites merged at pyruvate (glycolysis), succinate (Krebs cycle) and aspartate-glutamate metabolic pathways. CoA depletion at the growth stage triggered the initiation of fatty acid and branched amino acid degradation. This in turn activated propionyl CoA carnitine acetyltransferase enzymes, resulting in nitrogen preservation (urea, putrescine and organic acids end-products). CoA then transferred into the TCA cycle via previously unreported β-alanine and propionyl CoA metabolic pathways, the latter likely being a novel methylmalonyl-CoA mutase activity for F. oxysporum.

CONCLUSIONS

The lower supplementation of inorganic nitrogen compounds (≤ 50 mM) and the elimination of nitrates/organic nitrogen sources resulted in TCA autophagy events that boosted mycotoxin-based metabolism and decreased overall F. oxysporum growth. Such knowledge of functional mycotoxin production can be used to supplement agricultural crops and reduce the risk of mycotoxin contamination in human and animal food supplies.

When Transcriptomics and Metabolomics Work Hand in Hand: A Case Study Characterizing Plant CDF Transcription Factors

Over the last three decades, novel “omics” platform technologies for the sequencing of DNA and complementary DNA (cDNA) (RNA-Seq), as well as for the analysis of proteins and metabolites by mass spectrometry, have become more and more available and increasingly found their way into general laboratory life. With this, the ability to generate highly multivariate datasets on the biological systems of choice has increased tremendously. However, the processing and, perhaps even more importantly, the integration of “omics” datasets still remains a bottleneck, although considerable computational and algorithmic advances have been made in recent years. In this mini-review, we use a number of recent “multi-omics” approaches realized in our laboratories as a common theme to discuss possible pitfalls of applying “omics” approaches and to highlight some useful tools for data integration and visualization in the form of an exemplified case study. In the selected example, we used a combination of transcriptomics and metabolomics alongside phenotypic analyses to functionally characterize a small number of Cycling Dof Transcription Factors (CDFs). It has to be remarked that, even though this approach is broadly used, the given workflow is only one of plenty possible ways to characterize target proteins.

A lost opportunity for science: journals promote data sharing in metabolomics but do not enforce it

INTRODUCTION

Data sharing is being increasingly required by journals and has been heralded as a solution to the 'replication crisis'.

OBJECTIVES

(i) Review data sharing policies of journals publishing the most metabolomics papers associated with open data and (ii) compare these journals' policies to those that publish the most metabolomics papers.

METHODS

A PubMed search was used to identify metabolomics papers. Metabolomics data repositories were manually searched for linked publications.

RESULTS

Journals that support data sharing are not necessarily those with the most papers associated to open metabolomics data.

CONCLUSION

Further efforts are required to improve data sharing in metabolomics.

Compliance with minimum information guidelines in public metabolomics repositories

The Metabolomics Standards Initiative (MSI) guidelines were first published in 2007. These guidelines provided reporting standards for all stages of metabolomics analysis: experimental design, biological context, chemical analysis and data processing. Since 2012, a series of public metabolomics databases and repositories, which accept the deposition of metabolomic datasets, have arisen. In this study, the compliance of 399 public data sets, from four major metabolomics data repositories, to the biological context MSI reporting standards was evaluated. None of the reporting standards were complied with in every publicly available study, although adherence rates varied greatly, from 0 to 97%. The plant minimum reporting standards were the most complied with and the microbial and in vitro were the least. Our results indicate the need for reassessment and revision of the existing MSI reporting standards.

From chromatogram to analyte to metabolite. How to pick horses for courses from the massive web resources for mass spectral plant metabolomics

The grand challenge currently facing metabolomics is the expansion of the coverage of the metabolome from a minor percentage of the metabolic complement of the cell toward the level of coverage afforded by other post-genomic technologies such as transcriptomics and proteomics. In plants, this problem is exacerbated by the sheer diversity of chemicals that constitute the metabolome, with the number of metabolites in the plant kingdom generally considered to be in excess of 200 000. In this review, we focus on web resources that can be exploited in order to improve analyte and ultimately metabolite identification and quantification. There is a wide range of available software that not only aids in this but also in the related area of peak alignment; however, for the uninitiated, choosing which program to use is a daunting task. For this reason, we provide an overview of the pros and cons of the software as well as comments regarding the level of programing skills required to effectively exploit their basic functions. In addition, the torrent of available genome and transcriptome sequences that followed the advent of next-generation sequencing has opened up further valuable resources for metabolite identification. All things considered, we posit that only via a continued communal sharing of information such as that deposited in the databases described within the article are we likely to be able to make significant headway toward improving our coverage of the plant metabolome.

Increasing rigor in NMR-based metabolomics through validated and open source tools

The metabolome, the collection of small molecules associated with an organism, is a growing subject of inquiry, with the data utilized for data-intensive systems biology, disease diagnostics, biomarker discovery, and the broader characterization of small molecules in mixtures. Owing to their close proximity to the functional endpoints that govern an organism's phenotype, metabolites are highly informative about functional states. The field of metabolomics identifies and quantifies endogenous and exogenous metabolites in biological samples. Information acquired from nuclear magnetic spectroscopy (NMR), mass spectrometry (MS), and the published literature, as processed by statistical approaches, are driving increasingly wider applications of metabolomics. This review focuses on the role of databases and software tools in advancing the rigor, robustness, reproducibility, and validation of metabolomics studies.

On the metabolic interactions of (photo)respiration

Given that photorespiration is inextricably linked to the process of photosynthesis by virtue of sharing the common first enzyme Rubisco, the photorespiratory pathway has been less subject to study in isolation than many other metabolic pathways. That said, despite often being described to be linked to reactions of ammonia assimilation, C1 metabolism and respiratory metabolism, the precise molecular mechanisms governing these linkages in land plants remain partially obscure. The application of broad metabolite profiling on mutants with altered levels of metabolic enzymes has facilitated the identification of common and distinct metabolic responses among them. Here we provide an update of the recent findings from such studies, focusing particularly on the interplay between photorespiration and the metabolic reactions of mitochondrial respiration. In order to do so we evaluated (i) changes in organic acids following environmental perturbation of metabolism, (ii) changes in organic acid levels in a wide range of photorespiratory mutants, (iii) changes in levels of photorespiratory metabolites in transgenic tomato lines deficient in the expression of enzymes of the tricarboxylic acid cycle. In addition, we estimated the rates of photorespiration in a complete set of tricarboxylic acid cycle transgenic tomato lines. Finally, we discuss insight concerning the interaction between photorespiration and other pathways that has been attained following the development of (13)CO2-based flux profiling methods.