A metabolic worldview
The huge quantities of data generated by powerful -omics technologies are providing a much fuller understanding of biological processes, yet our knowledge remains far from comprehensive. One challenge is to combine different types of information into models of complex biochemical pathways, which then have to be integrated into even larger models to show how multiple systems interact and are coordinated to produce specific outcomes for cells and organisms.
Stefan Kempa’s group at the MDC’s Berlin Institute for Medical Systems Biology established a sophisticated metabolomics and proteomics platform and is using it with the ultimate aim of decoding the regulation of metabolism at a molecular level. Their projects examine biological systems at various scales – from cells to organisms – to understand multiple levels of complexity in metabolic systems.
The platform is based on mass spectrometry and surveys cellular metabolites and proteins. A great number of mass spectrometry-based methods developed over the last few years now enable scientists to carry out quantitative and time-resolved analyses of cellular processes. “It’s like trying to figure out the rules of a game by observing the players (proteins) and balls (metabolites),” Stefan says.
Metabolic activity is a basic sign of life, and molecules are created as cells convert nutrients and other raw materials into all the substances and energy they need to grow and survive. This usually involves all layers of cellular regulation and is handled by molecular machines made of proteins and RNAs. As a result, the presence of a particular metabolite provides insights into the molecules and mechanisms that produce it, and the metabolomics platform provides a global view of these processes in cells and tissues. It can distinguish and count molecules at each stage of processing to reveal new details of pipelines and the ways cells regulate their output. Any disruption may prevent raw materials from being acquired or processed, cutting off essential supplies or causing a pile-up of intermediate forms that eventually become toxic.
Stefan says that mechanisms of “metabolic reprogramming” are a particular focus of the lab’s research. Reprogramming involves functional shifts in metabolic activity during processes such as stem cell differentiation, immune cell activation, and the development of cancer. “For over a century, metabolism has been considered be an excellent potential target for cancer therapies,” Stefan says. “So far, however, this concept hasn’t had much of a clinical impact. That’s not surprising given the limitations of past methods. We’re now seeing cases where pathways have side walks, or need to be revised, and have hints that they may not be regulated quite the way people have believed. That’s even true for metabolic processes that have been studied very intensively for many decades.”
Stefan’s lab is engaged in collaborations across the MDC to identify and quantify metabolites in many contexts, revealing changes in biochemistry that reflect the different metabolic requirements of various tissues and the changes they undergo as they carry out normal functions, or during the development of disease. Important findings from recent studies have made their way into high-ranking journals; the next few weeks will see more. The diversity and success of these projects exhibit the platform’s range and wide scientific potential.
One area with enormous potential, Stefan believes, is “personalized medicine”: metabolic processes vary from individual to individual. Metabolomics may represent the best way to study how subtle variations in patients’ enzymes influence the course and outcomes of diseases as well as their responses to drugs and other therapies. So far, scientists have tried to answer such questions through studies of huge cohorts of patients and family members. If variants are rare, or their effects too subtle, they’ll never be found. Even if they were, a correlation itself says nothing about the mechanisms that connect molecules to disease.
Such personalized approaches to medicine will strongly depend, Stefan says, on a system capable of quantitative analyses across a broad spectrum of metabolites captured with high time resolution, in a highly reproducible way. These considerations influenced the technology Stefan chose as he began establishing the platform a few years ago. One payoff has been the discovery of a wealth of new metabolites, some of which have been identified; the identities and origins of others, as well as the machinery involved in their processing, remain unclear. Knowing that they are there is the first step in resolving these questions.
These efforts require a parallel development of mathematical tools to analyze metabolites and sort huge amounts of quantitative data into meaningful models. So the technological and scientific activities surrounding the platform are supported by a computational effort that has an essential role in turning metabolic data into useful knowledge about organisms that will guide research for years to come.
