Recent and potential developments of biofluid analyses in metabolomics

Metabolomics, one of the ‘omic’ sciences in systems biology, is the global assessment and validation of endogenous small-molecule metabolites within a biologic system. Analysis of these key metabolites in body fluids has become an important role to monitor the state of biological organisms and is a widely used diagnostic tool for disease. A majority of these metabolites are being applied to metabolic profiling of the biological samples, for example, plasma and whole blood, serum, urine, saliva, cerebrospinal fluid, synovial fluid, semen, and tissue homogenates. However, the recognition of the need for a holistic approach to metabolism led to the application of metabolomics to biological fluids for disease diagnostics. A recent surge in metabolomic applications which are probably more accurate than routine clinical practice, dedicated to characterizing the biological fluids. While developments in the analysis of biofluid samples encompassing an important impediment, it must be emphasized that these biofluids are complementary. Metabolomics provides potential advantages that classical diagnostic approaches do not, based on following discovery of a suite of clinically relevant biomarkers that are simultaneously affected by the disease. Emerging as a promising biofocus, metabolomics will drive biofluid analyses and offer great benefits for public health in the long-term.     

Online coupling of capillary electrophoresis with mass spectrometry for the identification of biomarkers for clinical diagnosis

Proteomic screening of complex biologic samples is of increasing importance in clinical research and diagnosis. In the postgenomic area it is evident that changes of the composition of body fluids, as well as post-translational modifications of proteins and peptides, provide more information than genetic typing. The study of these changes allows the state of health or disease of particular organs, and consequently, the whole organism, to be described. This review describes the application of capillary electrophoresis coupled online to an electrospray ionization time-of-flight mass spectrometer to the analysis of body fluids obtained from patients for the identification of biomarkers for diagnostic purposes.     

Online coupling of capillary electrophoresis with mass spectrometry for the identification of biomarkers for clinical diagnosis

Proteomic screening of complex biologic samples is of increasing importance in clinical research and diagnosis. In the postgenomic area it is evident that changes of the composition of body fluids, as well as post-translational modifications of proteins and peptides, provide more information than genetic typing. The study of these changes allows the state of health or disease of particular organs, and consequently, the whole organism, to be described. This review describes the application of capillary electrophoresis coupled online to an electrospray ionization time-of-flight mass spectrometer to the analysis of body fluids obtained from patients for the identification of biomarkers for diagnostic purposes.     

Intermediate filaments and stress

Before we can explain why so many closely related intermediate filament genes have evolved in vertebrates, while maintaining such dramatically tissue specific expression, we need to understand their function. The best evidence for intermediate filament function comes from observing the consequences of mutation and mis-expression, primarily in human tissues. Mostly these observations suggest that intermediate filaments are important in allowing individual cells, the tissues and whole organs to cope with various types of stress, in health and disease. Exactly how they do this is unclear and many aspects of cell dysfunction have been associated with intermediate filaments to date. In particular, it is still not clear whether the non-mechanical functions now being attributed to intermediate filaments are primary functions of these structural proteins, or secondary consequences of their function to respond to mechanical stress. We discuss selected situations in which responses to stress are clearly influenced by intermediate filaments.     

Absent MicroRNAs in Different Tissues of Patients with Acquired Cardiomyopathy

MicroRNAs (miRNAs) can be found in a wide range of tissues and body fluids, and their specific signatures can be used to determine diseases or predict clinical courses. The miRNA profiles in biological samples (tissue, serum, peripheral blood mononuclear cells or other body fluids) differ significantly even in the same patient and therefore have their own specificity for the presented con-dition. Complex profiles of deregulated miRNAs are of high interest, whereas the importance of non-expressed miRNAs was ignored. Since miRNAs regulate gene expression rather negatively, absent miRNAs could indicate genes with unaltered expression that therefore are normally expressed in specific compartments or under specific disease situations. For the first time, non-detectable miRNAs in different tissues and body fluids from patients with different diseases (cardiomyopathies, Alzheimer’s disease, bladder cancer, and ocular cancer) were analyzed and com-pared in this study. miRNA expression data were generated by microarray or TaqMan PCR-based platforms. Lists of absent miRNAs of primarily cardiac patients (myocardium, blood cells, and serum) were clustered and analyzed for potentially involved pathways using two prediction platforms, i.e., miRNA enrichment analysis and annotation tool (miEAA) and DIANA miRPath. Extensive search in biomedical publication databases for the relevance of non-expressed miRNAs in predicted pathways revealed no evidence for their involvement in heart-related pathways as indicated by software tools, confirming proposed approach.     

The control of histone methylation and gene expression by oxidative stress, hypoxia, and metals

The harmful consequences of carcinogenic metals, such as nickel, arsenic, and chromium, are thought to be in part due to their ability to induce oxidative stress. The ubiquity of oxidative stress in biological systems has made it a fairly obvious culprit in causing cellular damage and/or development of disease. However, the full extent of oxidative stress-induced damage is not limited to its direct effects on cellular components, such as lipids, proteins, and DNA, but may extend to its ability to alter gene expression. Gene expression regulation is an important component of cellular and/or tissue homeostasis, and its alteration can have detrimental consequences. Therefore, a growing amount of interest is being paid to understanding how oxidative stress can influence gene expression. Oxidative stress-induced epigenetic dysregulation in the form of posttranslational histone modifications, in particular, is a popular topic of research. This review will therefore primarily focus on discussing the role of oxidative stress and hypoxia on histone methylation and/or gene expression alterations. The sources of oxidative stress discussed here are carcinogenic metals, such as, nickel, arsenic, and chromium.     

The Hemolymph Proteome of Fed and Starved Drosophila Larvae

The co-operation of specialized organ systems in complex multicellular organisms depends on effective chemical communication. Thus, body fluids (like blood, lymph or intraspinal fluid) contain myriads of signaling mediators apart from metabolites. Moreover, these fluids are also of crucial importance for immune and wound responses. Compositional analyses of human body fluids are therefore of paramount diagnostic importance. Further improving their comprehensiveness should increase our understanding of inter-organ communication. In arthropods, which have trachea for gas exchange and an open circulatory system, the single dominating interstitial fluid is the hemolymph. Accordingly, a detailed analysis of hemolymph composition should provide an especially comprehensive picture of chemical communication and defense in animals. Therefore we used an extensive protein fractionation workflow in combination with a discovery-driven proteomic approach to map out the detectable protein composition of hemolymph isolated from Drosophila larvae. Combined mass spectrometric analysis revealed more than 700 proteins extending far beyond the previously known Drosophila hemolymph proteome. Moreover, by comparing hemolymph isolated from either fed or starved larvae, we provide initial provisional insights concerning compositional changes in response to nutritional state. Storage proteins in particular were observed to be strongly reduced by starvation. Our hemolymph proteome catalog provides a rich basis for data mining, as exemplified by our identification of potential novel cytokines, as well as for future quantitative analyses by targeted proteomics.     

Metabolomics of forage plants: a review

Background

Forage plant breeding is under increasing pressure to deliver new cultivars with improved yield, quality and persistence to the pastoral industry. New innovations in DNA sequencing technologies mean that quantitative trait loci analysis and marker-assisted selection approaches are becoming faster and cheaper, and are increasingly used in the breeding process with the aim to speed it up and improve its precision. High-throughput phenotyping is currently a major bottle neck and emerging technologies such as metabolomics are being developed to bridge the gap between genotype and phenotype; metabolomics studies on forages are reviewed in this article.

Scope

Major challenges for pasture production arise from the reduced availability of resources, mainly water, nitrogen and phosphorus, and metabolomics studies on metabolic responses to these abiotic stresses in Lolium perenne and Lotus species will be discussed here. Many forage plants can be associated with symbiotic microorganisms such as legumes with nitrogen fixing rhizobia, grasses and legumes with phosphorus-solubilizing arbuscular mycorrhizal fungi, and cool temperate grasses with fungal anti-herbivorous alkaloid-producing Neotyphodium endophytes and metabolomics studies have shown that these associations can significantly affect the metabolic composition of forage plants. The combination of genetics and metabolomics, also known as genetical metabolomics can be a powerful tool to identify genetic regions related to specific metabolites or metabolic profiles, but this approach has not been widely adopted for forages yet, and we argue here that more studies are needed to improve our chances of success in forage breeding.

Conclusions

Metabolomics combined with other ‘-omics’ technologies and genome sequencing can be invaluable tools for large-scale geno- and phenotyping of breeding populations, although the implementation of these approaches in forage breeding programmes still lags behind. The majority of studies using metabolomics approaches have been performed with model species or cereals and findings from these studies are not easily translated to forage species. To be most effective these approaches should be accompanied by whole-plant physiology and proof of concept (modelling) studies. Wider considerations of possible consequences of novel traits on the fitness of new cultivars and symbiotic associations need also to be taken into account.     

The human secretome atlas initiative: Implications in health and disease conditions

Proteomic analysis of human body fluids is highly challenging, therefore many researchers are redirecting efforts toward secretome profiling. The goal is to define potential biomarkers and therapeutic targets in the secretome that can be traced back in accessible human body fluids. However, currently there is a lack of secretome profiles of normal human primary cells making it difficult to assess the biological meaning of current findings. In this study we sought to establish secretome profiles of human primary cells obtained from healthy donors with the goal of building a human secretome atlas. Such an atlas can be used as a reference for discovery of potential disease associated biomarkers and eventually novel therapeutic targets. As a preliminary study, secretome profiles were established for six different types of human primary cell cultures and checked for overlaps with the three major human body fluids including plasma, cerebrospinal fluid and urine. About 67% of the 1054 identified proteins in the secretome of these primary cells occurred in at least one body fluid. Furthermore, comparison of the secretome profiles of two human glioblastoma cell lines to this new human secretome atlas enabled unambiguous identification of potential brain tumor biomarkers. These biomarkers can be easily monitored in different body fluids using stable isotope labeled standard proteins. The long term goal of this study is to establish a comprehensive online human secretome atlas for future use as a reference for any disease related secretome study. This article is part of a Special Issue entitled: An Updated Secretome.     

Quantitative metabolomics based on gas chromatography mass spectrometry: status and perspectives

Metabolomics involves the unbiased quantitative and qualitative analysis of the complete set of metabolites present in cells, body fluids and tissues (the metabolome). By analyzing differences between metabolomes using biostatistics (multivariate data analysis; pattern recognition), metabolites relevant to a specific phenotypic characteristic can be identified. However, the reliability of the analytical data is a prerequisite for correct biological interpretation in metabolomics analysis. In this review the challenges in quantitative metabolomics analysis with regards to analytical as well as data preprocessing steps are discussed. Recommendations are given on how to optimize and validate comprehensive silylation-based methods from sample extraction and derivatization up to data preprocessing and how to perform quality control during metabolomics studies. The current state of method validation and data preprocessing methods used in published literature are discussed and a perspective on the future research necessary to obtain accurate quantitative data from comprehensive GC-MS data is provided.     

Digging Deep into Peptidomics Applied to Body Fluids

Peptidomics techniques have allowed the identification of thousands of peptides that are derived from proteins in body fluids, despite the considerable challenges behind sample handling, MS‐based identification, data analysis, and integration with bioinformatics tools. Body fluids’ naturally occurring peptides are known to perform a variety of local and systemic functions; however, its knowledge is limited. Even so, the biological meaning that can be retrieved from peptidomics applied to the identification of disease markers and to the development of therapies using peptides has driven the progresses made in this field. In this review, a comparative analysis of body fluids’ peptidome data retrieved from databases and from scientific papers is performed to identify the biological processes modulated by naturally occurring peptides. This integrative analysis highlights several interesting facts, such as the small overlap between blood‐derived serum and plasma, which illustrates the impact of sample handling on these fluids peptidome. Urine is the body fluid with more naturally occurring peptides identified so far, most of which are derived from collagens. In saliva, the majority of peptides are originated from extracellular matrix proteins. Cerebrospinal fluid presents a high number of peptides derived from distinct proteins, mostly involved in the regulation of nervous system homeostasis. The lowest number of endogenous peptides was found in tears, most of which present antimicrobial activity. Collectively, data analysis highlights a peptidome signature for each body fluid, which comprehension will certainly help to improve disease management.     

Proteomic applications in ecotoxicology

Within the growing body of proteomics studies, issues addressing problems of ecotoxicology are on the rise. Generally speaking, ecotoxicology uses quantitative expression changes of distinct proteins known to be involved in toxicological responses as biomarkers. Unlike these directed approaches, proteomics examines how multiple expression changes are associated with a contamination that is suspected to be detrimental. Consequently, proteins involved in toxicological responses that have not been described previously may be revealed. Following identification of key proteins indicating exposure or effect, proteomics can potentially be employed in environmental risk assessment. To this end, bioinformatics may unveil protein patterns specific to an environmental stress that would constitute a classifier able to distinguish an exposure from a control state. The combined use of sets of marker proteins associated with a given pollution impact may prove to be more reliable, as they are based not only on a few unique markers which are measured independently, but reflect the complexity of a toxicological response. Such a proteomic pattern might also integrate some of the already established biomarkers of environmental toxicity. Proteomics applications in ecotoxicology may also comprise functional examination of known classes of proteins, such as glutathione transferases or metallothioneins, to elucidate their toxicological responses.     

Patterns of bushmeat hunting and perceptions of disease risk among central African communities

There is a great need to determine the factors that influence the hunting, butchering and eating of bushmeat to better manage the important social, public health and conservation consequences of these activities. In particular, the hunting and butchering of wild animals can lead to the transmission of diseases that have potentially serious consequences for exposed people and their communities. Comprehension of these risks may lead to decreased levels of these activities. To investigate these issues, 3971 questionnaires were completed to examine the determinants of the hunting, butchering and eating of wild animals and perceptions of disease risk in 17 rural central African villages. A high proportion of individuals reported perceiving a risk of disease infection with bushmeat contact. Individuals who perceived risk were significantly less likely to butcher wild animals than those who perceived no risk. However, perception of risk was not associated with hunting and eating bushmeat (activities that, compared with butchering, involve less contact with raw blood and body fluids). This suggests that some individuals may act on perceived risk to avoid higher risk activity. These findings reinforce the notion that conservation programs in rural villages in central Africa should include health-risk education. This has the potential to reduce the levels of use of wild animals, particularly of certain endangered species (e.g. many non-human primates) that pose a particular risk to human health. However, as the use of wild game is likely to continue, people should be encouraged to undertake hunting and butchering more safely for their own and their community's health.     

Current progress in computational metabolomics

Being a relatively new addition to the 'omics' field, metabolomics is still evolving its own computational infrastructure and assessing its own computational needs. Due to its strong emphasis on chemical information and because of the importance of linking that chemical data to biological consequences, metabolomics must combine elements of traditional bioinformatics with traditional cheminformatics. This is a significant challenge as these two fields have evolved quite separately and require very different computational tools and skill sets. This review is intended to familiarize readers with the field of metabolomics and to outline the needs, the challenges and the recent progress being made in four areas of computational metabolomics: (i) metabolomics databases; (ii) metabolomics LIMS; (iii) spectral analysis tools for metabolomics and (iv) metabolic modeling.     

Metabolomics in the fight against malaria

Metabolomics uses high-resolution mass spectrometry to provide a chemical fingerprint of thousands of metabolites present in cells, tissues or body fluids. Such metabolic phenotyping has been successfully used to study various biologic processes and disease states. High-resolution metabolomics can shed new light on the intricacies of host-parasite interactions in each stage of the Plasmodium life cycle and the downstream ramifications on the host’s metabolism, pathogenesis and disease. Such data can become integrated with other large datasets generated using top-down systems biology approaches and be utilised by computational biologists to develop and enhance models of malaria pathogenesis relevant for identifying new drug targets or intervention strategies. Here, we focus on the promise of metabolomics to complement systems biology approaches in the quest for novel interventions in the fight against malaria. We introduce the Malaria Host-Pathogen Interaction Center (MaHPIC), a new systems biology research coalition. A primary goal of the MaHPIC is to generate systems biology datasets relating to human and non-human primate (NHP) malaria parasites and their hosts making these openly available from an online relational database. Metabolomic data from NHP infections and clinical malaria infections from around the world will comprise a unique global resource.