Speed, Sensitivity, and High-throughput Analysis: The Latest Advancements in Metabolomics
Speed, Sensitivity, and High-throughput Analysis: The Latest Advancements in Metabolomics
Metabolomics is a field dedicated to the study of small molecules, or metabolites, present in a biological system. Analysis of the metabolites present within an organism (the metabolome) or cell provides a chemical fingerprint of its physiological status.
Characterizing the metabolome has a wide range of applications in a number of fields, from nutrition and food science, to understanding human disease. The applications of this rapidly growing field are only set to expand as analytical technologies continue to advance and increase in capability.
To find out more about the recent advances in metabolomics and the technologies that have evolved alongside it, we spoke with Lucy Woods, Global Technology Leader at Bruker Daltonics.
Molly Campbell (MC): The metabolomics field has advanced rapidly in recent years. It appears that there is now a general recognition in the scientific community that it is equally as important to understand the metabolome as it is to understand the genome, transcriptome and the proteome. Why do you think there has been such a sudden recognition?
Lucy Woods (LW): One reason for this increased recognition is related to the fact that changes in the metabolome are most closely connected to the phenotype which is a personalized view of how each individual responds to a specific stimulus. Coupled to the recently discovered significance of the microbiome and the myriad of small molecule signaling pathways that are influenced by this symbiotic interaction, has thrust metabolomics further into the spotlight.
Let's imagine what happens to the different OMICS levels when you eat a hamburger. The effect on the genome level is likely to be negligible on a timescale of hours to minutes. The transcriptome and proteome on the other hand will change, for example genes encoding for lipases will be transcribed some-time after eating. These transcripts will finally lead to higher amounts of lipases to ease the digestion of the food. The human metabolome will react even faster. The lipases that are already present in the body will start to metabolize the food. Changes in lipids and metabolites will therefore be detectable very quickly. As soon as the transcripts are translated into higher amounts of proteins, the degradation of the lipids will accelerate. This example explains why it is important to understand the interaction of genome, transcriptome, proteome and the metabolome. Similarly, monitoring the metabolome can provide direct feedback on the current health status of a person using biomarkers that are identified in large cohort profiling studies.
Advances in technology have also opened up the metabolomics field to enable more researchers to study cross-OMICS approaches. Standard operation procedures (SOPs) for sample preparation, hardware and software workflows are now available, offering turnkey solutions that encompass both mass spectrometry (MS) and nuclear magnetic resonance (NMR) techniques, are lowering the entry barrier to this research field. As a result, we are seeing an increased interest in metabolomics research.
MC: What mass spectrometry technologies do Bruker offer for metabolomics analyses? How have these technologies been optimized to meet such purpose?
LW: Bruker adds confidence to metabolomics analyses by introducing an additional dimension of separation. Trapped ion mobility spectrometry (TIMS) is a unique type of ion mobility separation that removes isobaric interferences and separates isomeric compounds without compromising sensitivity. The timsTOF Pro is the foundation of the well-established PASEF method, enabling high-throughput and high-sensitivity analyses in the proteomics field. Unique methods exploiting PASEF have been optimized for metabolomics and lipidomics, providing the same advancements in speed and sensitivity as for proteomics. In lipidomics analyses, isobaric lipids that differ by just a few millidalton often coelute. However, these lipids can be separated used TIMS separation. This enables each lipid to be fragmented separately using PASEF, reducing chimeric spectra and adding to the confidence of annotation for all lipids.
Bruker is also pioneering the MALDI guided SpatialOmx approach, where tissues can be imaged using endogenous molecules like lipids, glycans and other small molecules to help decipher molecular signaling. Using SpatialOmx, specific sub-cellular regions from tissue samples can be further selected for deeper metabolomics analysis to better understand how cells distal to tumor regions begin to change. The timsTOF fleX instrument in combination with SCILS and MetaboScape is the first of a kind workflow to empower a SpatialOmX approach to understanding tissue microheterogeneity using a metabolomics driven approach.
The need for high-throughput analyses is driving an increasing interest in large-scale phenomics research studies. To analyze large sample cohorts, systems must be both sensitive and able to measure samples consistently over several weeks. Robustness studies have shown Bruker QTOF technology is able to analyze thousands of samples with no decline in performance, demonstrating industry-leading results for phenomics studies.
MC: Please can you provide some examples of exciting cutting-edge metabolomics research that is being undertaken by Bruker customers?
LW: The Australian National Phenome Centre (ANPC) is the outcome of a collaboration between Murdoch University and Bruker to form the leading international center of expertise for metabolic phenotyping. Established by international pioneers in phenomics Professor Jeremy Nicholson and Professor Elaine Holmes, the ANPC is a key next step in expanding the boundaries of knowledge of human health and the causes and prevention of disease. It is an affiliate of the International Phenome Center Network (IPCN), founded under the leadership of Professor Nicholson. The ANPC will work closely with major hospitals, universities and medical research institutes to enable researchers to examine the complex interactions of genes, the environment and lifestyle on human metabolic health, helping transform how long and how well people live.
Several complementary NMR and MS approaches will be combined to achieve this goal, including utilizing PASEF metabolomic workflows on the timsTOF Pro. To further increase sample throughput, an innovative flow injection analysis, MRMS aXelerate, will be employed to allow for the screening of more than 250 samples per day. Using resolutions of > 1 million on the MRMS platform allows unambiguous elemental formula determination using isotopic fine structure. This is the unique mass spectral signature arising from naturally occurring isotopes within the molecule being measured. Combinations of these elements create unique patterns thanks to different mass defects of the isotopic contributions of compounds to be acquired, resulting in a confident molecular formula assignment.
MC: What are some of the greatest challenges that researchers encounter in metabolomic research? How do Bruker look to overcome such challenges?
LW: One of the greatest challenges is the reliable identification of known compounds and subsequently the identification of unknowns. Using isotopic fine structure is one method to assign molecular formula to unknowns to discover what exists within the “dark metabolome”. For reliable identification, a library-based approach is routinely used in which retention time, accurate mass, accurate isotopic pattern information and fragment spectra must be available to confidently annotate compounds found in complex samples. The timsTOF technology allows for the addition of an additional distinctive characteristic, the collisional cross section (CCS), to add confidence to structural annotations. CCS values are properties of the gaseous ion and can be reproducibly measured independently of the type chromatography that is used. Using TIMS, CCS values can be reliably and reproducibly calculated for all types of analyte. Moreover, CCS values can be predicted for lipids from all common classes, so unknown lipid structures can be assigned based on predicted CCS values. This CCSPredict tool is built into the software Metaboscape, an intuitive and user-friendly software for data evaluation provided by Bruker.
MC: What do you envision the field of metabolomics to look like in five years' time?
LW: We are in the age of big data and software will play a much bigger role in five years’ time as longitudinal studies and large cohort studies become routine analysis. The drive to lower the cost of the metabolome will become vital as genomics, proteomics and phenotypic data will be needed to positively influence human health. Changes in the person's metabolome have the potential to become prognostic, especially if the longitudinal data could be used as the basis for a person’s baseline health. The human genome was decoded nearly twenty years ago, the proteomics effort is now nearly twenty years old, and large scale metabolomic studies have just started. The impact these cross-omics will have in terms of clinical utility, combined with the rapid advance in computing science will be truly exciting in the next five years.
Lucy Woods, Global Technology Leader (UHR-QTOF) at Bruker Daltonics, was speaking with Molly Campbell, Science Writer, Technology Networks.