Metabolomics & Systems Biology

Systems biology is an approach in biomedical research to understanding the larger picture be it at the level of the organism, tissue, or cell—by putting its pieces together. It's in stark contrast to decades of reductionist biology, which involves taking the pieces apart.

The primary aim of "omic" technologies is the nontargeted identification of all gene products (transcripts, proteins, and metabolites) present in a specific biological sample.  Thus, metabolomics is a key technology for systems biology

In this context, metabolic engineering is about engineering cell factories for the biological manufacturing of chemical and pharmaceutical products, whereas the main focus of synthetic biology is fundamental biological research facilitated by the use of synthetic DNA and genetic circuits.

Computational research methods utilize new advances in computing such as algorithms, models, simulations, and systems in order to understand complex social, biological, technological, and endless other patterns and behaviors.

Changes in plant metabolism are at the heart of plant developmental processes, underpinning many of the ways in which plants respond to the environment. As such, the comprehensive study of plant metabolism, or metabolomics, is highly valuable in identifying phenotypic effects of abiotic and biotic stresses on plants.

Pharmacometabolomics is a branch of metabolomics, the disciple that quantifies and analyzes the metabolites existing in a biological sample

NMR-based metabolomics provides a means to categorize organ-specific toxicity, monitor the onset and progression of toxicological effects, and identify biomarkers of toxicity. A future challenge, however, is to describe the cellular metabolome for purposes of understanding cellular functions

Mass spectrometry-based metabolomics offers quantitative analyses with high selectivity and sensitivity and the potential to identify metabolites. Mass spectrometry-based metabolomics approaches can enable detection and quantification of many thousands of metabolite features simultaneously. However, compound identification and reliable quantification are greatly complicated owing to the chemical complexity and dynamic range of the metabolome.

The two most common analytical approaches for the generation of metabolomics data are nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS). NMR is a spectroscopic technique based on the principle of energy absorption and re-emission of the atom nuclei due to variations in an external magnetic field.

Two main analytical techniques are currently being used in metabolomics: nuclear magnetic resonance (NMR) spectroscopy and high-resolution mass spectrometry (HRMS). Modern separation techniques, such as liquid chromatography (LC), gas chromatography (GC), or capillary electrophoresis (CE), are often coupled with HRMS.

At present, metabolomics is applied to investigate several human diseases, to improve their diagnosis and prevention, and to design better therapeutic strategies. In addition, metabolomic studies are also being carried out in areas such as toxicology and pharmacology, crop breeding, and plant biotechnology.

Metabolomics cancer research is being used to discover diagnostic cancer biomarkers in the clinic and in a research institute, to a better understand its complex heterogeneous nature, to discover pathways which involved in cancer that could be used for new targets and to monitor metabolic biomarkers during therapeutic intervention. These metabolomics approaches may also provide evidence to personalized cancer treatments by providing useful information to the clinician about the cancer patient’s response to medical interventions. The ultimate aims of most metabolomics cancer studies are to discover cancer-specific diagnostic, prognostic or predictive biomarkers for a patient. Untargeted metabolomics is an important and excellent tool for probing cancer-altered biochemical pathways.