Saravanan Dayalan

Data standards can boost metabolomics research, and if there is a will, there is a way

Thousands of articles using metabolomics approaches are published every year. With the increasing amounts of data being produced, mere description of investigations as text in manuscripts is not sufficient to enable re-use anymore: the underlying data needs to be published together with the findings in the literature to maximise the benefit from public and private expenditure and to take advantage of an enormous opportunity to improve scientific reproducibility in metabolomics and cognate disciplines. Reporting recommendations in metabolomics started to emerge about a decade ago and were mostly concerned with inventories of the information that had to be reported in the literature for consistency. In recent years, metabolomics data standards have developed extensively, to include the primary research data, derived results and the experimental description and importantly the metadata in a machine-readable way. This includes vendor independent data standards such as mzML for mass spectrometry and nmrML for NMR raw data that have both enabled the development of advanced data processing algorithms by the scientific community. Standards such as ISA-Tab cover essential metadata, including the experimental design, the applied protocols, association between samples, data files and the experimental factors for further statistical analysis. Altogether, they pave the way for both reproducible research and data reuse, including meta-analyses. Further incentives to prepare standards compliant data sets include new opportunities to publish data sets, but also require a little “arm twisting” in the author guidelines of scientific journals to submit the data sets to public repositories such as the NIH Metabolomics Workbench or MetaboLights at EMBL-EBI. In the present article, we look at standards for data sharing, investigate their impact in metabolomics and give suggestions to improve their adoption.

Lipidomic Profiling of Adipose Tissue Reveals an Inflammatory Signature in Cancer-Related and Primary Lymphedema.

Cancer-related and primary lymphedema (LE) are associated with the production of adipose tissue (AT). Nothing is known, however, about the lipid-based molecules that comprise LE AT. We therefore analyzed lipid molecules in lipoaspirates and serum obtained from LE patients, and compared them to lipoaspirates from cosmetic surgery patients and healthy control cohort serum. LE patient serum analysis demonstrated that triglycerides, HDL- and LDL-cholesterol and lipid transport molecules remained within the normal range, with no alterations in individual fatty acids. The lipidomic analysis also identified 275 lipid-based molecules, including triacylglycerides, diacylglycerides, fatty acids and phospholipids in AT oil and fat. Although the majority of lipid molecules were present in a similar abundance in LE and non-LE samples, there were several small changes: increased C20:5-containing triacylglycerides, reduced C10:0 caprinic and C24:1 nervonic acids. LE AT oil also contained a signature of increased cyclopropane-type fatty acids and inflammatory mediators arachidonic acid and ceramides. Interestingly C20:5 and C22:6 omega-3-type lipids are increased in LE AT, correlating with LE years. Hence, LE AT has a normal lipid profile containing a signature of inflammation and omega-3-lipids. It remains unclear, however, whether these differences reflect a small-scale global metabolic disturbance or effects within localised inflammatory foci.

A multi-platform metabolomics approach demonstrates changes in energy metabolism and the transsulfuration pathway in Chironomus tepperi following exposure to zinc

Measuring biological responses in resident biota is a commonly used approach to monitoring polluted habitats. The challenge is to choose sensitive and, ideally, stressor-specific endpoints that reflect the responses of the ecosystem. Metabolomics is a potentially useful approach for identifying sensitive and consistent responses since it provides a holistic view to understanding the effects of exposure to chemicals upon the physiological functioning of organisms. In this study, we exposed the aquatic non-biting midge, Chironomus tepperi, to two concentrations of zinc chloride and measured global changes in polar metabolite levels using an untargeted gas chromatography-mass spectrometry (GC-MS) analysis and a targeted liquid chromatography-mass spectrometry (LC-MS) analysis of amine-containing metabolites. These data were correlated with changes in the expression of a number of target genes. Zinc exposure resulted in a reduction in levels of intermediates in carbohydrate metabolism (i.e., glucose 6-phosphate, fructose 6-phosphate and disaccharides) and an increase in a number of TCA cycle intermediates. Zinc exposure also resulted in decreases in concentrations of the amine containing metabolites, lanthionine, methionine and cystathionine, and an increase in metallothionein gene expression. Methionine and cystathionine are intermediates in the transsulfuration pathway which is involved in the conversion of methionine to cysteine. These responses provide an understanding of the pathways affected by zinc toxicity, and how these effects are different to other heavy metals such as cadmium and copper. The use of complementary metabolomics analytical approaches was particularly useful for understanding the effects of zinc exposure and importantly, identified a suite of candidate biomarkers of zinc exposure useful for the development of biomonitoring programs.

Embedding standards in metabolomics: the Metabolomics Society data standards task group

Metabolomics has reached a maturity as a field. Yet, there remain some challenges to overcome, particularly in metabolite identification and reporting such results, as well as the need for continuous improvements in data standards and data sharing. For over a decade now, the metabolomics community, has built a dedicated international society with an affiliated journal, Metabolomics. In 2007 several leaders within the community, established a set of standards and minimum reporting guidelines for experimental descriptors and data, known as the Metabolomics Standards Initiative (MSI), summarized by Goodacre et al. (Goodacre 2013). Since 2012, resources and repositories have been established, notably EMBL-EBI MetaboLights (Haug et al. 2012) and the NIH funded Metabolomics Workbench, where experimental data and metadata can be shared with the community, all of which is publicly accessible. A central tenet of science is the reproducibility of results. However, this may be challenging to achieve in metabolomics, owing to the complex nature of the metabolome, the diversity of technologies and data analysis techniques used (Beisken et al. 2015). Despite these difficulties the principle of reproducibility must hold. Data sharing is not just simply making raw files available via a website link nor sharing the end results of data processing and analysis pipelines, usually in an excel spreadsheet. Key steps are required to achieve meaningful data sharing, ensuring that the results are reusable and the experimental results can be reproduced. Additionally, substantial curation efforts are often required to ensure optimal reporting, enriched metadata annotation within a study, but also to ensure consistency across studies, which may be achieved through checking compliance with annotation checklists such as the MSI guidelines (Salek et al. 2013). Ideally, data sharing should be shouldered by dedicated, institution backed repositories, thus guaranteeing continued support and long-term preservation. Initial standardization efforts focused on study description and instrument generated metadata reporting. Experimental metadata associated to datasets can now be & Reza M. Salek reza.salek@ebi.ac.uk

Synergy between the KEAP1/NRF2 and PI3K Pathways Drives Non-Small-Cell Lung Cancer with an Altered Immune Microenvironment

The lung presents a highly oxidative environment, which is tolerated through engagement of tightly controlled stress response pathways. A critical stress response mediator is the transcription factor nuclear factor erythroid-2-related factor 2 (NFE2L2/NRF2), which is negatively regulated by Kelch-like ECH-associated protein 1 (KEAP1). Alterations in the KEAP1/NRF2 pathway have been identified in 23% of lung adenocarcinomas, suggesting that deregulation of the pathway is a major cancer driver. We demonstrate that inactivation of Keap1 and Pten in the mouse lung promotes adenocarcinoma formation. Notably, metabolites identified in the plasma of Keap1f/f/Ptenf/f tumor-bearing mice indicate that tumorigenesis is associated with reprogramming of the pentose phosphate pathway. Furthermore, the immune milieu was dramatically changed by Keap1 and Pten deletion, and tumor regression was achieved utilizing immune checkpoint inhibition. Thus, our study highlights the ability to exploit both metabolic and immune characteristics in the detection and treatment of lung tumors harboring KEAP1/NRF2 pathway alterations.

Comparative Metabolomics of Mycoplasma bovis and Mycoplasma gallisepticum Reveals Fundamental Differences in Active Metabolic Pathways and Suggests Novel Gene Annotations

Mycoplasmas are pathogenic bacteria that cause serious chronic infections in production animals, resulting in considerable losses worldwide, as well as causing disease in humans. These bacteria have extremely reduced genomes and are thought to have limited metabolic flexibility, even though they are highly successful persistent parasites in a diverse number of species. The extent to which different Mycoplasma species are capable of catabolizing host carbon sources and nutrients, or synthesizing essential metabolites, remains poorly defined. We have used advanced metabolomic techniques to identify metabolic pathways that are active in two species of Mycoplasma that infect distinct hosts (poultry and cattle). We show that these species exhibit marked differences in metabolite steady-state levels and carbon source utilization. This information has been used to functionally characterize previously unknown genes in the genomes of these pathogens. These species-specific differences are likely to reflect important differences in host nutrient levels and pathogenic mechanisms. ABSTRACT Mycoplasmas are simple, but successful parasites that have the smallest genome of any free-living cell and are thought to have a highly streamlined cellular metabolism. Here, we have undertaken a detailed metabolomic analysis of two species, Mycoplasma bovis and Mycoplasma gallisepticum, which cause economically important diseases in cattle and poultry, respectively. Untargeted gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry analyses of mycoplasma metabolite extracts revealed significant differences in the steady-state levels of many metabolites in central carbon metabolism, while 13C stable isotope labeling studies revealed marked differences in carbon source utilization. These data were mapped onto in silico metabolic networks predicted from genome wide annotations. The analyses elucidated distinct differences, including a clear difference in glucose utilization, with a marked decrease in glucose uptake and glycolysis in M. bovis compared to M. gallisepticum, which may reflect differing host nutrient availabilities. The 13C-labeling patterns also revealed several functional metabolic pathways that were previously unannotated in these species, allowing us to assign putative enzyme functions to the products of a number of genes of unknown function, especially in M. bovis. This study demonstrates the considerable potential of metabolomic analyses to assist in characterizing significant differences in the metabolism of different bacterial species and in improving genome annotation. IMPORTANCE Mycoplasmas are pathogenic bacteria that cause serious chronic infections in production animals, resulting in considerable losses worldwide, as well as causing disease in humans. These bacteria have extremely reduced genomes and are thought to have limited metabolic flexibility, even though they are highly successful persistent parasites in a diverse number of species. The extent to which different Mycoplasma species are capable of catabolizing host carbon sources and nutrients, or synthesizing essential metabolites, remains poorly defined. We have used advanced metabolomic techniques to identify metabolic pathways that are active in two species of Mycoplasma that infect distinct hosts (poultry and cattle). We show that these species exhibit marked differences in metabolite steady-state levels and carbon source utilization. This information has been used to functionally characterize previously unknown genes in the genomes of these pathogens. These species-specific differences are likely to reflect important differences in host nutrient levels and pathogenic mechanisms.

MASTR-MS: a web-based collaborative laboratory information management system (LIMS) for metabolomics

BackgroundAn increasing number of research laboratories and core analytical facilities around the world are developing high throughput metabolomic analytical and data processing pipelines that are capable of handling hundreds to thousands of individual samples per year, often over multiple projects, collaborations and sample types. At present, there are no Laboratory Information Management Systems (LIMS) that are specifically tailored for metabolomics laboratories that are capable of tracking samples and associated metadata from the beginning to the end of an experiment, including data processing and archiving, and which are also suitable for use in large institutional core facilities or multi-laboratory consortia as well as single laboratory environments.ResultsHere we present MASTR-MS, a downloadable and installable LIMS solution that can be deployed either within a single laboratory or used to link workflows across a multisite network. It comprises a Node Management System that can be used to link and manage projects across one or multiple collaborating laboratories; a User Management System which defines different user groups and privileges of users; a Quote Management System where client quotes are managed; a Project Management System in which metadata is stored and all aspects of project management, including experimental setup, sample tracking and instrument analysis, are defined, and a Data Management System that allows the automatic capture and storage of raw and processed data from the analytical instruments to the LIMS.ConclusionMASTR-MS is a comprehensive LIMS solution specifically designed for metabolomics. It captures the entire lifecycle of a sample starting from project and experiment design to sample analysis, data capture and storage. It acts as an electronic notebook, facilitating project management within a single laboratory or a multi-node collaborative environment. This software is being developed in close consultation with members of the metabolomics research community. It is freely available under the GNU GPL v3 licence and can be accessed from, https://muccg.github.io/mastr-ms/.

Best practice data life cycle approaches for the life sciences

Throughout history, the life sciences have been revolutionised by technological advances; in our era this is manifested by advances in instrumentation for data generation, and consequently researchers now routinely handle large amounts of heterogeneous data in digital formats. The simultaneous transitions towards biology as a data science and towards a ‘life cycle’ view of research data pose new challenges. Researchers face a bewildering landscape of data management requirements, recommendations and regulations, without necessarily being able to access data management training or possessing a clear understanding of practical approaches that can assist in data management in their particular research domain. Here we provide an overview of best practice data life cycle approaches for researchers in the life sciences/bioinformatics space with a particular focus on ‘omics’ datasets and computer-based data processing and analysis. We discuss the different stages of the data life cycle and provide practical suggestions for useful tools and resources to improve data management practices.

Establishing a distributed national research infrastructure providing bioinformatics support to life science researchers in Australia

Abstract EMBL Australia Bioinformatics Resource (EMBL-ABR) is a developing national research infrastructure, providing bioinformatics resources and support to life science and biomedical researchers in Australia. EMBL-ABR comprises 10 geographically distributed national nodes with one coordinating hub, with current funding provided through Bioplatforms Australia and the University of Melbourne for its initial 2-year development phase. The EMBL-ABR mission is to: (1) increase Australia’s capacity in bioinformatics and data sciences; (2) contribute to the development of training in bioinformatics skills; (3) showcase Australian data sets at an international level and (4) enable engagement in international programs. The activities of EMBL-ABR are focussed in six key areas, aligning with comparable international initiatives such as ELIXIR, CyVerse and NIH Commons. These key areas—Tools, Data, Standards, Platforms, Compute and Training—are described in this article.

Metabolite profiling of Mycoplasma gallisepticum mutants, combined with bioinformatic analysis, can reveal the likely functions of virulence-associated genes

Mycoplasma gallisepticum is an economically important pathogen of commercial poultry. An improved understanding of M. gallisepticum pathogenesis is required to develop better control methods. We recently identified a number of M. gallisepticum mutants with defects in colonization and persistence in chickens using signature-tagged transposon mutagenesis. Loss of virulence was associated with mutations in a putative oligopeptide/dipeptide (opp/dpp) ATP-binding cassette (ABC) transporter (where the transposon was inserted into the MGA_0220 (oppD1) gene and two hypothetical proteins (encoded by MGA_1102 and MGA_0588), one of which (MGA_1102) contains a putative peptidase motif. To further characterise the function of these proteins, we compared the metabolome of each transposon mutant with that of wild type bacteria. Two independent LC/MS analyses revealed consistent significant decreases in the abundances of several amino acids and the dipeptide alanyl-glycine (Ala-Gly) in the MGA_0220 mutant, consistent with this protein being a peptide transporter. Similarly, lysine and Ala-Gly were significantly decreased in the MGA_1102 mutant, consistent with our bioinformatic analysis suggesting that MGA_1102 encodes a membrane-located peptidase. Few differences were observed in metabolite levels in the MGA_0588 mutant, suggesting that the disrupted protein has a non-metabolic role. Overall, this study indicates that metabolomics is a useful tool in the functional analysis of mutants.