Laboratory research studies require a huge commitment of time, money and resources. To help ensure the investment pays off in the form of key insights, simple precautions such as good sample collection practices should be utilized. All too often, studies are delayed or even derailed entirely due to avoidable errors. For example, while hand-written labels are common practice in laboratories, something as small as an ink smudge or illegible handwriting could be detrimental to a study and its results.
As interest in metabolomics grows for biopharma, population health and other industries the need to process hundreds of samples quickly has become increasingly important.
To help you avoid sample handling mistakes, keep your timelines on track and achieve the best results from your study, Metabolon has created the Metabolon Study Success Sample Handling Kit. By leveraging our 20 years of best-in-class metabolomics study experience, the Sample Handling Kit was designed with the needs of the researcher in mind – to maintain consistent and efficient workflow, reduce the risk of traceability errors, ensure sample integrity during shipment and maximize study speed and quality assurance.
Applying industry best practices, the Metabolon Study Success Sample Handling Kit was developed with the understanding that each research program is unique. Not just an off-the-shelf item, every Kit is tailored to support your study design, providing the foundational first step of study success with the right quantity and type of tubes for your specific sample type.
One of the challenges researchers often face in metabolomics studies is separating the noise to draw actionable insights, and not all tubes are created equal. With that in mind, Metabolon’s development team carefully evaluated many vendors and hand-selected the most suitable tubes, offering the greatest durability and lowest levels of artifact contribution, such as leaching of plastic and mold releasing agents. This level of diligence will help to ensure the most reliable results to your study every time.
The Metabolon Study Success Sample Handling Kit also aims to plug a crucial gap in studies – traceability. All tubes provided in the Kit are prelabeled with globally unique barcodes, making manual transcription errors or illegible handwritten labels a thing of the past. The pre-programmed hand-held barcode scanner included in the Kit allows the user to easily generate an accurate tracking record. This feature helps to streamline the sample intake process, delivering quick and accurate results.
When you open your Metabolon Study Success Sample Handling Kit you will receive the barcoded tubes and racks in specially designed cardboard cradles to protect them during transfer and shipping. The cradles are meant to be re-used when preparing your samples for return shipment to Metabolon in order to reduce the risk of breakage, spills and contamination.
All these factors add up to support financial success. There is a cost accrued from inconsistency or errors in labeling, be it financial, turn-around time or – worst-case scenario – data quality. Cutting down on errors improves financial success, and ultimately, study success.
At Metabolon we are committed to your study success. There isn’t another company that offers this all-encompassing support package. From study design and execution, through interpretation and recommended next steps, we are focused on customer success and quality assurance at each step of the program journey.
Wondering what metabolomics can bring to your studies? Contact us today at hello@metabolon.com to get started.
When Annie Evans, Ph.D., first joined Metabolon, she had no idea of the breakthroughs she would be a part of, and how metabolomics would grow into an important ‘omics technology. “We’re impacting areas of the life sciences that I never thought possible,” she noted. After completing her Doctorate in Biological Mass Spectrometry at the University of Virginia, she joined Metabolon in 2004 as a research scientist. Early on, she was praised for her straightforward nature and presentation style, two things that played a crucial role in the development of the Metabolon we know now. Today, she is the Director of Research and Development.
Dr. Evans’ background in chemistry led to a fascinating discovery early in Metabolon’s history that may have otherwise gone unnoticed. The study involved a pharmaceutical company that wanted to pinpoint diagnostic markers of a drug that caused gut toxicity. The researchers ran plasma samples of drugs that were known to cause gut issues and some that did not.
Dr. Evans discovered a molecule that biologists deemed impossible to occur in mammals, but the presence of the molecule could not be denied. That is when metabolomics revealed that gut toxicity could be recognized through metabolites from the gut that passed into circulating plasma. What they were seeing for the first time were microbial derived metabolites in the blood, a discovery made 13 years ago. Even today, metabolomics is the only ‘omic able to identify gut microbiome activity in the blood.
Clinical metabolomics has the potential to make precision medicine a reality delivering transformational medicine. Traditional clinical testing of patient samples involves analyzing and measuring individual analytes or biomarkers. In the case of IEM’s, the screening method typically includes three panels, which measure in the range of 50-60 small molecules. Metabolon’s application of clinical metabolomics extends the number of biomarkers that can be measured significantly. Instead of 50-60, we can identify more than 500 small molecules, giving researchers a broader range of biomarkers to mine for insights.
The application of metabolomics is exceptionally significant for IEM and rare disease detection. There are hundreds of IEM diseases, and often the clinical manifestations of those diseases are vague, or the metabolic pathway that is disturbed is not immediately apparent. Applying global, or untargeted, analytical approaches, where prior knowledge of the affected metabolic pathway is not required, provides advantages over targeted analytical approaches and can extend the diagnostic potential of IEM screens beyond the 34-58 disorders that are currently evaluated in newborn screening programs, especially in complex cases. That makes throwing out this wide net to measure as many biomarkers as possible invaluable in a clinical setting.
When evaluating large quantities of information, it is paramount to make data quality a top priority. A critical step in drawing insights from untargeted metabolomics is accurate metabolite identification. Metabolon’s Precision Metabolomics™ workflow delivers Tier 1-2 identifications for detected metabolites and uniquely provides high confidence in the identification of compounds. By contrast, most metabolomic practitioners operate primarily with annotations that only meet the standards of Tiers 3-5, where some unique features are identified. Still, there is low confidence in confirming the metabolite. Data quality is extremely important to Metabolon, with exceptionally high standards applied to our work in clinical metabolomics. From start to finish, we emphasize quality control measures and checks and balances.
Metabolon’s method of clinical metabolomics is validated by Clinical Laboratory Improvement Amendments (CLIA), a regulatory standard for all testing of patient samples. Metabolon is ISO 9001: 2015 certified for analytical and diagnostic testing of biological specimens and accredited by the College of American Pathologists for diagnostic testing on human specimens. Additionally, Metabolon has a New York State Department of Health Clinical Laboratory permit to perform Quantose IR and IGT testing for the identification of insulin resistance and impaired glucose tolerance under the categories of Clinical Chemistry and Endocrinology.
In addition to the validation work we do to demonstrate the properties of the method, such as precision and accuracy, we also run the method under very specific quality control guidelines, which are even stricter than our research guidelines, including running batch controls for each of the analytic batches. We start by setting up the assays following policies that dictate how to establish a reference population, how you qualify the normalizing matrix, and so on. The typical regulatory requirements for review of the results is exceeded, with an additional analytical and lab director review in addition to our typical sub-level review. All of these steps ensure data quality and accurate insights.
In the early 2000s when Metabolon was formed, there were very few metabolomics practitioners. In fact, the term “metabolomics” was not yet part of the common scientific language. The practitioners mainly composed of academic universities referred to the science as “metabonomics,” and primarily used Nuclear Magnetic Resonance (NMR) technology. Metabolon, on the other hand, focused on a mass spectrometry-based platform that delivered on a global scale. Metabolon ultimately decided to standardize its methodology on the use of LCMS because the company quickly noticed the short-comings of both GCMS and NMR technology in terms of specificity and sensitivity. By choosing LCMS, Metabolon was able to identify more compounds than NMR technology allowed, while also enabling greater processing speed and reducing process variability beyond what is possible with GCMS. While using LCMS in the study of metabolomics was less common at the time, this methodology has allowed Metabolon to maintain its focus on the biology and the meaning of its findings—to interpret and make sense of the data that is revealed.
In its early years, Metabolon employed fewer than 15 scientists who studied just 50 to 100 small molecules. Today, the company has more than 200 employees, has run over 10,000 projects and has identified more than 2,000 named molecules in human plasma from a database of over 5,300 biologically relevant compounds. This comprises the world’s largest metabolomics knowledgebase.
In addition to traditional metabolites, Metabolon’s library features more than 1,000 complex lipids, analyzed on the Lipidyzer™, which the company co-developed with Sciex in 2012.
Metabolon’s compound database is remarkable not only for its size, but for its quality. From the beginning, Metabolon adopted a validated identification methodology, which required the identification of a compound based on multiple orthogonal criteria to an authentic standard analyzed using the same methodology. Compound identification confidence levels were later described and formalized in Sumner et. al., as Tiers ranging from 1 to 5 for each metabolite, with Tiers 1 and 2 being of the highest level of confidence. In untargeted metabolomics, accurate metabolite information is the key step in separating noise from insight. Today, more than 85% of compounds in Metabolon’s library meet the Tier 1 criteria. Though tier rating is a critical part of confidence in compound identification, it is a difficult and expensive process that takes tremendous resources and experience to be successful. As a result, few other metabolomics service providers are able to deliver the same level of confidence in metabolite identification offered from Metabolon’s Precision Metabolomics™ solution.
Today, Metabolon remains committed to investing in and advancing leading-edge metabolomics technologies. This emphasis is improving the understanding of systems biology, enhancing identification of clinically relevant biomarkers, accelerating drug development, improving patient stratification and revealing new insights in the rapidly advancing field of microbiome research.
For Dr. Evans, each success is a motivator to make the science even better. Once the power of the science has been revealed, the reward motivates both her and other scientists to continue making it better for everyone who is involved. She remarks that each scientist has been heavily involved in the trajectory of the company, each playing pivotal roles to move the science and technology from the small lab they began in to where they are today. “How could you not just fall in love with any technology where you can take something that you love and really feel like you’re impacting people and improving lives,” Dr. Evans said.
Dr. Annie Evans leads the discovery metabolomics and lipidomics profiling research and development team at Metabolon, Inc. The metabolomics and lipidomics platforms developed under Dr. Evans have been the analytical basis for thousands of commercial studies from over 700 institutions since 2004. She has over 30 publications covering the analytical methodology as well as informatics, data processing requirements and approaches for global profiling metabolomics and lipidomics workflows. These publications have been cumulatively cited over 2000 times, with a foundational metabolomics methodology paper being cited over 650 times. These publications have spanned various technology journals such of the Analytical Chemistry and the Journal of Chromatography, biological journals such as Blood and PNAS as well as high impact journals such as Nature Genetics. Dr. Evans currently holds an h-index of 35, with a JCR of 13. She is involved in industry establishment of quality control methods through the National Institutes of Health Metabolomics Quality Assurance & Quality Control Consortium (mQACC).
We sat down for a conversation with Nikole Kimes, Ph.D., Co-Founder and CEO of Siolta. The company’s name, which is pronounced sheel-ta, is a Gaelic word for “seeds” and speaks to the company’s microbial therapeutics that are created to reseed the depleted gut microbiome with naturally occurring bacteria, which are essential for a healthy immune system.
Dr. Kimes’ interest in science resulted from two passions: human health and environmental ecosystems. Her intrinsic understanding that these two concepts are inevitably linked fueled her interest in science and eventually converged at an understanding of how the world around us impacts our biological ecosystem.
As a student I studied holistic health and microbial ecology at different points in my training, and both underscored the complex interactions of dynamic biological systems. Through my interest in health, I learned the ecological concepts of systems biology and applied the latest microbial genomic tools to different ecosystems, such as coral reefs and the Gulf of Mexico following the Deepwater Horizon oil spill. Subsequently, I transferred these skills and concepts to the realm of the human microbiome when I joined the laboratory of Dr. Susan Lynch, Professor of Medicine at the University of California San Francisco (UCSF), Director of the Benioff Center for Microbiome Medicine, and Co-founder of Siolta Therapeutics. Dr. Lynch’s focus on the human microbiome in human health from an ecological perspective was a perfect fit for my particular interests, background, and skill set. It is there that we worked on rationally designing microbial medicines for the prevention of disease based on years of work performed by Dr. Lynch and her collaborators.
The decision to translate our academic findings into a clinical application resulted at yet another convergence point, one in which the science, interest in the field, and a compelling sense of necessity all aligned. It was at this point that Dr. Lynch and I co-founded Siolta in partnership with Samir Kaul, Founding Partner and Managing Director at Khosla Ventures, in order to translate this ground-breaking research into innovative clinical applications.
The answer is simple, our approach is science-driven. We are focusing on early life because this is where the science is telling us we could have the most transformative impact. There is now substantial evidence that the developing microbiome is instrumental in establishing and maintaining healthy immune responses. Moreover, disruption to this process is thought to underlie a myriad of chronic diseases, including allergic, metabolic, and neurodevelopmental diseases; all of which are increasing in incidence at alarming rates in our children. This unique early-life window has the potential to be instrumental in approaching disease from an innovative prevention standpoint. We are developing a method where the underlying causes of chronic disease are addressed through early intervention, rather than treating downstream symptoms later in disease development. This has a lot of positive outcomes – lower costs, fewer side-effects and the potential to eliminate the long-term treatment modalities used for asthma and allergy sufferers today.
What we have learned over the last decade is that the human microbiome, like any other ecosystem, begins as a relatively naïve system. Early “founder” microorganisms play an important role in shaping the local environment in a way that subsequently impacts the additional accumulation of diversity. This is important not only from a perspective of what microbes are present, but more importantly for what functionality the community represents. Notably, the science suggests that different founding communities impact the trajectory of immune development in different ways, and likely microbial metabolism is one of the mechanisms by which they do this. Thus, our growing understanding of the human microbiome and its interconnectedness to our health has both identified potential mechanisms of action and novel strategies for addressing disease.
Metabolomics provides another layer of analyses that allows us to more directly address the functional contribution of the microbiome to human physiology. It adds to the tool box that we have available to better characterize both general phenomena, through untargeted metabolomics, and more specific mechanisms of action, through targeted metabolite analysis. Both of which are important drivers of research and development in this emerging field.
You can refer to the published work from Dr. Lynch’s lab to see how untargeted metabolomics has helped characterize early-life signatures of infants at risk for developing allergy and asthma. Their work establishes that different microbial profiles are associated with different metabolic signatures, immunological impacts, and disease outcomes1,2. Furthermore, they use this approach to identify specific metabolites associated with high risk infants for allergy and asthma, as well as the associated microbial genes capable of producing such metabolites, that are capable of impeding immune tolerance3. Thus, Dr. Lynch’s work established a potential mechanistic link between early life microbiome perturbations and disease development later in life, while also identifying a potential biomarker for high risk infants.
At Siolta, we are also utilizing both untargeted and targeted metabolomic approaches to help characterize the overall metabolic signatures associated with treatment and response and potentially provide insight into patient stratification for more precise therapeutic approaches moving forward. We start with untargeted metabolomics, casting a wide net to characterize general metabolic shifts across different pathways and to identify the biomarkers that we may not know are there yet. Once the analysis is complete and we have pinpointed the biomarkers we want to focus on, we work to develop a targeted assay. In this way, Metabolon has the capacity to support our work through the complete research continuum.
The genomic revolution that has occurred over the past few decades is fundamental to our current understanding of complex microbial communities, including the human microbiome. The resulting advancements in technology have led to increased awareness of the role microbial communities play in environmental and human health, including the vast functional potential harbored by these complex systems. Metabolomics, generally speaking, allows us to investigate a step further, moving from what potential is present to what functions are being fulfilled. This is a critical step in pushing the boundaries of our knowledge beyond who and what is present and moving towards functional characterization and finer resolution of metabolic networks.
View for our webinar – to hear more from Dr. Kimes and other researchers who are successfully applying metabolomics to their microbiome research.
References:
1. Fujimura KE, Sitarik AR, Havstad S, Lin DL, Levan S, Fadrosh D, et al. Neonatal gut microbiota associates with childhood multisensitized atopy and T cell differentiation. Nature Medicine. 2016Dec;22(10):1187–91.
2. Durack J, Kimes NE, Lin DL, Rauch M, Mckean M, Mccauley K, et al. Delayed gut microbiota development in high-risk for asthma infants is temporarily modifiable by Lactobacillus supplementation. Nature Communications. 2018;9(1).
3. Levan SR, Stamnes KA, Lin DL, Panzer AR, Fukui Eundefined, McCauley K, et al. Elevated faecal 12,13-diHOME concentration in neonates at high risk for asthma is produced by gut bacteria and impedes immune tolerance. Nature Microbiology. 2019Jul22;4:1851–61.
The fountain of youth is what most people desire as they begin to notice faint lines of wisdom. Factors from a person’s biology or genetics to their environment and lifestyle, including sleep habits, alter metabolite levels affecting the health and appearance of skin. These mechanisms lead to the aging process long before we see the impact on our skin.
The fountain of youth is what most people desire as they begin to notice faint lines of wisdom. Factors from a person’s biology or genetics to their environment and lifestyle, including sleep habits, alter metabolite levels affecting the health and appearance of skin. These mechanisms lead to the aging process long before we see the impact on our skin.
Estee Lauder Companies is leveraging metabolomics, with circadian rhythm, to deepen its knowledge of skin conditions to improve the health of aging skin. Estee Lauder Companies presented their findings at the World Congress of Dermatology 2019 in Milan, Italy, during a symposium titled “Metabolomics as a New Diagnostic to Assess Skin Health” on Wednesday, June 12, 2019. The poster can be viewed here.
During the symposium, renowned circadian rhythm expert Paolo Sassone-Corsi, Ph.D., of the University of California – Irvine, highlighted how circadian cycles impact almost every element of our biology, including skin health. Next, Metabolon’s Kirk Beebe, Ph.D., presented how Metabolon’s Precision Metabolomics platform can provide deep insight into an array of biological processes surrounding skin health. Bringing it all together, Estee Lauder Companies Vice President of Skin Biology & BioActives, Nadine Pernodet, Ph.D., presented results of the first ever metabolomics study demonstrating temporal facial skin metabolome differences in young and mature skin, with and without treatment in vivo, using non-invasive methods.
“Figure 8 in the poster presentation says it all,” says Dr. Beebe. “It shows that with proper treatment, the rhythmicity for many of the skin metabolites can be reestablished, helping to synchronize skin with its natural youthful rhythm of dynamic repair. The blue line denotes young skin, the red is for mature, and the green represents mature skin treated with Estee Lauder’s night repair. These are powerful metabolomic insights.”
In a recent press release, Estee Lauder Companies notes it is the first in the industry to use metabolomics with time to more thoroughly understand factors of skin repair efficiency and damage accumulation and their relationship to skin circadian rhythm. The company plans to continue to apply this knowledge to formulate products that can address and improve optimal skin processes, leading to younger-looking skin. #thenightisyours.
At Metabolon, we realize the importance of metabolomics in understanding skin biology and have invested a tremendous effort in developing methods and tools for skin research. The tools we use for skin analysis, such as skin biopsies and tape strips, will not only promote a better understanding of the basic principles governing skin biology but will also become a frontline approach for understanding the complex interaction between the host and microbiota that govern skin health.
For more information on understanding the skin metabolome and microbiome, please contact us hello@metabolon.com.
Researchers continue to mine the genome for clues that assist in understanding susceptibility to disease, selection of targets for combating disease, and the biomarkers indicating response. Surprisingly, though, a fast and valuable source of data that can either lead or strengthen this pursuit is not always part of the equation.
While we should retain our commitment to understanding biology through standard cell and molecular biology tools, it is important to remind ourselves that metabolites have been, and continue to be, a staple for clinical and in vivo decision making.
There is a strong, well-established association between the metabolite and the phenotype. In fact, this understanding formed the basis of almost a century of metabolic investigation from famous researchers including Krebs, Warburg, Cori and Pasteur.
Despite this, the last several decades have intensely focused on the molecular genetic basis of biology. Metabolism research didn’t fade because it lacked value in understanding biology; it was simply the genuine and vigorous interest in gene function that relegated it to a less favored life science discipline.
Although undeniably important as our foundational blueprint, DNA reflects the risk or potential for disease. In many instances, though, a complex network of genes, transcripts, proteins and regulation conspires with the environment and microbiome to result in a physiological or phenotypic change.
Key to the value of metabolites is that they may reflect all of these factors, and metabolites themselves may play an integral role in the activity of genes and proteins through epigenetic alterations and post-translational modifications.
From a biomarker discovery perspective, metabolites are particularly attractive since they can be identified from any biological sample type, including cells, media, tissues, body fluids, and even exhaled breath condensate.
In addition, since metabolism is central to all living things, many pathways are highly conserved, making findings particularly translatable across species. Therefore, if a biomarker is identified in a pre-clinical model, it has a strong potential to have relevance in human disease.
So, why aren’t metabolites routinely surveyed to address biomarker and R&D objectives? Aside from the genomic focus mentioned above, another issue at the heart of this question is the fact that building the technology is extremely challenging. Until recently, technologies that could fully exploit the information embedded in the metabolome did not exist.
Given the chemical diversity of metabolites (e.g., carbohydrates, organic acids, lipids, etc.), immense technical challenges existed in tapping into this data stream, but a key advance came from the development of software tools that could provide rapid metabolite identification and QC of the data. Today, metabolomics, the technology for widespread metabolic analysis, offers an extremely effective, accurate means for examining metabolism.
Metabolomics can be done on an industrial scale resulting in the discovery of novel biomarkers and actionable biological insight. As appreciated by over a century of biochemistry and contemporary clinical testing, surveying metabolism offers an integrated vantage-point for understanding complex biological states, such as disease or drug response. The signatures that accompany these states can serve as clinically useful biomarkers.
Metabolomics frequently produces unexpected biomarkers and disease insight, even in extensively studied disease states. Perhaps the best example of this is in cancer, where it is now appreciated that all major oncogenic drivers induce a change in the metabolic phenotype.
Metabolomic studies in recent years, as evidenced by the proliferation of peer-reviewed publications (including top journal publications), have led to breakthroughs in disease understanding and treatments. Like genomics, metabolomics offers value in any biological research area. In fact, metabolomics has resulted in successful outcomes in numerous fields, including oncology, metabolic disease, cardiovascular disease, respiratory and rare diseases.
No matter the disease area, metabolites are an important probe of phenotypic or physiological inquiry that goes beyond genomics. Metabolomics has matured to a point where meaningful advancement of biological insights and identification of sensitive and specific biomarkers can occur in a range of different diseases.
Metabolomics applications continue to grow and provide unprecedented knowledge for clinicians and life sciences researchers across many industries and academic and government organizations. This expanding technology for biomarker discovery is now routinely used in disease research, pharmaceutical development, nutrition and agriculture. Metabolomics is also rapidly moving into clinical applications to promote wellness and diagnose and treat diseases.
If you’d like to learn how to add metabolomics to your research, please contact us.
A new study showed the potentially negative impact of the widely used, over-the-counter drug acetaminophen (paracetamol) on sex hormones, which has significant implications for reproductive health. It also highlights the power of genomic and metabolomic profiling to better understand drug mechanisms of action and metabolism even in common drugs such as acetaminophen.
A new study showed the potentially negative impact of the widely used, over-the-counter drug acetaminophen (paracetamol) on sex hormones, which has significant implications for reproductive health. It also highlights the power of genomic and metabolomic profiling to better understand drug mechanisms of action and metabolism even in common drugs such as acetaminophen.
A new metabolomics and genomics-informed study conducted by researchers at Human Longevity, Inc. (HLI), Metabolon, University of California at San Diego, JCVI and King’s College shows that use of acetaminophen (Tylenol®) has unexpected effects on the regulation of sex hormones. The study was recently published in EBioMedicine.
The study showed the potentially negative impact of the widely used, over-the-counter drug acetaminophen (paracetamol) on sex hormones, which has significant implications for reproductive health. It also highlights the power of genomic and metabolomic profiling to better understand drug mechanisms of action and metabolism even in common drugs such as acetaminophen.
The researchers first looked at 455 active adults over age 18 who were divided into two groups—a 208-person machine-learning training set and a 247-person test set. As a validation set, the team included 1,880 European ancestry twins from the TwinsUK cohort and 1,235 individuals of African American and Hispanic ancestry from the Insulin Resistance Atherosclerosis Study. Metabolomic analysis of more than 700 metabolites was conducted by Metabolon.
The team identified depletion of sulfated sex hormones associated with acetaminophen use in all the study populations. The results showed that use of acetaminophen is roughly equivalent to 35 years of aging on sulfated hormone levels, which could affect placental health and general reproductive health. While there are many factors that go into reproductive health, this new study identified an area of acetaminophen’s effects that weren’t previously known, offering some insight into previous studies suggesting that acetaminophen exposure during gestation may impact development of masculine and behavioral characteristics.
These sulfated sex hormones, also referred to as neurosteroids, have many effects in the brain. There are no currently approved drugs that are specifically designed to target neurosteroid metabolism. Drugs that target this pathway could potentially treat many diseases of the nervous system, for example chronic pain and depression.
“These findings are significant for they showcase how the body is impacted by seemingly innocuous everyday medications like Tylenol,” said Amalio Telenti. “There are hundreds of other drugs that no one has done this research for. We delineate a general strategy that should be applied broadly in the study of medications in common use.”
First author Isaac Cohen, PharmD candidate at UC San Diego, added, “This study reveals significant new opportunities for pharmaceutical research to better understand common medications and their effects on human health and patient safety. Our research also emphasizes how the integration of genomics and metabolomics should enable better outcomes for clinical trials.”
Because of our long history with the science and technology of metabolomics, we’re often asked about the utility of various technologies. Here is our comparison of two popular metabolomics technology platforms – NMR versus LC-MS.
Every chemist and biochemist is familiar with nuclear magnetic resonance (NMR). It is a long established, powerful technique dating back to the 1940s used to determine molecular identity and structure. I suspect that NMR is actually quite broadly known about. Perhaps you will have experienced NMR in a different way via magnetic resonance imaging (MRI), which is basically NMR applied to imaging. Indeed, MRI was first known as NMR Imaging, but at least partly due to the use of the word “nuclear” and patients’ concerns raised about that word, the nuclear in NMR Imaging was mostly dropped by the 1980s.
At this point I am going to admit to, and proudly express, a bias. During and since my PhD I have worked with mass spectrometry (MS; mass spec). It is a technique I know and love, and in my opinion it is the most powerful analytical technique currently in the armoury of the analytical scientist, particularly when coupled to liquid chromatography (LC).
It is very broadly used to analyze a whole range of samples such as water and food to check for chemical impurities such as pesticides; in the clinical lab for therapeutic drug monitoring; in sports anti-doping to catch sporting cheats who are enhancing their performance with drugs; in the clinical microbiology lab to identify infectious bacteria; in the pharmaceutical industry to look at how a drug is metabolized; and, in academia, particularly in life science and clinical research, to broadly analyze proteins with proteomics and metabolites with metabolomics. This is actually a very short and incomplete list of examples. The uses of mass spec are far greater than this.
There are areas where both NMR and MS may be applied. One such area is metabolomics, the comprehensive analysis of metabolites in a biological sample such as a tissue or cell culture. Most research conducted with metabolomics is carried out using a hybrid technology called liquid chromatography-mass spectrometry (LC-MS), but gas chromatography-mass spectrometry (GC-MS) and NMR are also used.
Here, I’ll limit my comparison to NMR and LC-MS. Both have their strengths and weaknesses, but I will give the game away somewhat and tell you now that I strongly favour LC-MS as the analytical tool of choice to be used for successful metabolomics studies.
I can boil the reason down to two very key, very critical areas of analytical performance. Firstly, mass spec is sensitive while NMR is not. It’s that simple, and the difference between the two is as night and day. Indeed, mass spec is several orders of magnitude more sensitive than NMR. What is the consequence of that?
We come now to my second reason: in biological samples NMR detects only a handful of abundant metabolites, such as glucose and pyruvate, whereas an LC-MS approach, properly developed, as at Metabolon, will identify on the order of 1,000 metabolites in a sample such as blood plasma. If you also choose to study complex lipids, then more than 2,000 small molecule metabolites and lipids in total are typically identified. The approach developed by Metabolon based on LC-MS detects metabolites at a much lower concentration than an NMR-based approach. In addition, LC-MS-based approaches continue to improve, and it is foreseeable that in the next several years this number will be greatly exceeded.
To discover what is changing in metabolism, for example the differences between diseased samples relative to ‘normal’ (control) samples, often requires the maximum sensitivity that can be achieved. Even if a scientist thinks they know what they are looking for and that they already know what is of importance, they will often receive unexpected surprises that may elucidate the mechanism of disease or possibly identify biomarkers that may be of future clinical relevance diagnostically or prognostically. In addition, our current understanding of the human metabolome constituents, of say plasma, is incomplete. Mass spec is the only approach with a realistic possibility of identifying unknown metabolites present at a low level.
In genetics, a genome wide association study (GWAS) is an examination of a genome-wide set of genetic variants such as single-nucleotide polymorphisms (SNPs) to see if any variant (allele) is associated with a specific phenotypic trait, for example high blood pressure, or the aetiology of a disease. If one type of variant is particularly frequent in people with a disease, then the variant is said to be associated with that disease. These associated SNPs are then considered to mark a region of the human genome that may influence the risk for that disease. As usual, Wikipedia contains a useful summary.
A typical GWAS performed today might well involve tens of thousands of individuals, sometimes more, to increase the probability of finding associations. The reason for this large size is the drive toward detecting ‘risk-SNPs’ that have smaller odds ratios (a statistical measure of the strength of an association in a population) and lower allele frequency. In other words, these associations are difficult to identify with a typical GWAS unless a very large population cohort is studied, or so goes the general perception.
Could metabolomics enhance our ability to identify associations that might inform us about disease, for example, and enable the use of a smaller population cohort to identify significant associations? This could be very relevant to the study of rare or complex diseases or to reduce the cost associated with population health studies.
A number of studies have been performed looking for association of genes with metabolism, for example, to identify the metabolic function of genes and/or to uncover metabolic pathophysiology underlying established disease variants. For the purposes of comparison between NMR and LC-MS metabolomics approaches, two recent studies are worth describing, one using NMR, the other using LC-MS.
In 2016, Kettunen et al1 wrote, ”We conduct an extended genome-wide association study of genetic influences on 123 circulating metabolic traits quantified by nuclear magnetic resonance metabolomics from up to 24,925 individuals and identify eight novel loci for amino acids, pyruvate and fatty acids. The LPA locus link with cardiovascular risk exemplifies how detailed metabolic profiling may inform underlying aetiology via extensive associations with very-low-density lipoprotein and triglyceride metabolism.”
Picking that apart a little, 123 is actually a small number of ‘metabolic traits’ to study, and of that total, many were not actual small molecule metabolites but were, for example, lipoprotein particles. Amino acids, pyruvate and fatty acids are rather abundant species, and eight novel loci is a small number for nearly 25,000 individuals studied, as you will see by comparison with the paper published in 2017 in Nature Genetics by Long et al.2
“Many blood metabolites are intermediate phenotypes linking cellular functions to diseases,” wrote Long et al. “We conducted a whole genome sequencing study of common, low-frequency, and rare variants to map causal genetic variation for blood metabolite levels using comprehensive metabolite profiling in 1,960 individuals. We focused the analysis on 644 metabolites with consistent levels across three separate longitudinal data collections exhibiting high heritability (median h2 = 49%). Levels of 246 (38%) metabolites were associated with genetic sequence variation at 101 loci (p-value < 1.9×10-11). The genetic information supported the identification of unknown metabolites. In addition, we identified 175 individuals (113 unrelated, 10.7% of all unrelated individuals in the cohort) with rare variants likely influencing function of 17 genes, among which 35 individuals (26 unrelated, 2.5% of all unrelated) had metabolite levels beyond four standard deviations from the mean. Thirteen of the 17 genes are associated with inborn errors of metabolism or known pediatric genetic conditions. This study extends the map of loci influencing the metabolome and highlights the importance of heterozygous rare variants in determining abnormal blood metabolome phenotypes in adults.”
Far more metabolites were studied using Metabolon’s advanced Precision Metabolomics™ approach. Over the course of three measurements that were separated in time by years, LC-MS metabolomics measurements were stable. In addition, far more were associated with genetic sequence variation, some of which variation was rare.
A simple but telling measurement of the success of the two approaches is this: the NMR-based approach identified eight novel loci, while the LC-MS-based approach identified 48 loci associated to metabolites which were completely novel. There were even previously unknown metabolites identified using the LC-MS approach. Not all of the “metabolic traits” studied with NMR were actually measurements of metabolites. A last point worth strongly emphasizing is that the number of individuals necessary for the LC-MS metabolomics-GWAS was more than ten times fewer than in the NMR association study.
NMR has real benefits. The data generated by NMR is relatively straightforward; it quickly creates a single data file without any up-front complex separation, producing insight for some applications, including metabolomics. LC-MS requires some sample preparation, and for comprehensive, precision metabolomics, different types of chromatographic separation coupled with mass spec detection to identify as many metabolites as possible are needed to cover as much of the metabolome as possible. Each of the x4 LC-MS experiments performed by Metabolon take several minutes.
However, the benefits of NMR are far outweighed by those of LC-MS in the context of metabolomics, because of NMR weaknesses that are currently impossible to overcome, namely a lack of sensitivity and inability to detect the great majority of metabolite components in a complex sample. These are the strengths of the LC-MS-based Precision Metabolomics approach taken by Metabolon. NMR’s deficits limit its usefulness. While LC-MS certainly requires more effort, the benefits of superior coverage of the total metabolome make the extra effort worthwhile.
The conclusion from the comparison of GWAS coupled with metabolomics for the two metabolomics platforms seems straightforward. We see more associations of gene to metabolite identified with far fewer individuals studied using an LC-MS metabolomics approach. This implies very strongly that the LC-MS metabolomics approach from Metabolon was superior analytically at identifying metabolic associations than the NMR-based approach.
The ability to identify many hundreds of metabolites from all the major pathways of metabolism in a complex, rich sample such as plasma, the sample where biomarkers lie, and in tissues, diseased and otherwise, is compelling. The uses for this robust data across many areas of life sciences research, population health and precision medicine are many-fold. The combination of rich LC-MS data with the advanced bioinformatics and QC tools of Precision Metabolomics are simply too potent, too powerful, too useful not to use.
To learn more about Precision Metabolomics, visit www.metabolon.com.
References
1. Kettunen J, Demirkan A, Würtz P, Draisma HH, Haller T, Rawal R, Vaarhorst A, Kangas AJ, Lyytikäinen LP, Pirinen M, Pool R. Genome-wide study for circulating metabolites identifies 62 loci and reveals novel systemic effects of LPA. Nature communications. 2016 Mar 23;7.
2. Long T, Hicks M, Yu HC, Biggs WH, Kirkness EF, Menni C, Zierer J, Small KS, Mangino M, Messier H, Brewerton S, Turpaz Y, Perkins BA, Evans AM, Miller LA, Guo L, Caskey CT, Schork NJ, Garner C, Spector TD, Venter JC, Telenti A. Whole-genome sequencing identifies common-to-rare variants associated with human blood metabolites. Nat Genet. 2017 Mar 6. doi: 10.1038/ng.3809. [Epub ahead of print]
We asked David Nieman, D.Ph., FACSM, an expert in exercise science, to share his experience with metabolomics and how it has impacted his research.
David is a professor in the College of Health Sciences at Appalachian State University and director of the Human Performance Laboratory at the North Carolina Research Campus (NCRC) in Kannapolis, NC. He is a pioneer in the research area of exercise immunology. His current work is centered on investigating unique nutritional products as countermeasures to exercise- and obesity-induced immune dysfunction, inflammation, illness and oxidative stress.
Prolonged and intense exercise bouts induce physiologic stress, inflammation, oxidative stress, immune dysfunction and prolonged metabolic perturbations. The mission of the Human Performance Laboratory at the North Carolina Research Campus (NCRC) is to investigate unique nutritional products and other strategies as countermeasures to exercise-induced physiologic stress.
We also conduct randomized clinical trials with obese community adults. Many of the acute indicators of exercise stress are chronically elevated, albeit at lower levels, in obese individuals. Nutritional products that are efficacious with athletes during heavy training may be of benefit to those who have placed themselves at high disease risk through excessive weight gain during adulthood.
The earliest metabolomics-based studies were published by research groups in China and Europe during 2009 and 2010, and I became very interested in the potential for new research discoveries using this methodology. We conducted a few metabolomics-based exercise studies in 2010 and 2011 and then started working with Metabolon in 2012.
We quickly learned that high-quality data generated through metabolomics-based studies demand an extensive standards reference library, rigorous quality control procedures, highly sensitive and advanced mass spectrometry technology, sophisticated bioinformatics statistical support, and experienced biochemists to help interpret the findings. Metabolon provided all of this, and even worked with us in writing our research papers.
Some of our most significant metabolomics-based discoveries include:
Using metabolomics, we were the first to show that heavy exertion induced accelerated release of small phenolics from the gut following two weeks of supplementation with blueberry and green tea extract. (PLoS One. 2013 Aug 15;8(8):e72215. PMID: 23967286.)
Endurance athletes experienced a profound systemic shift in blood metabolites related to energy production, especially from the lipid super pathway, following heavy exertion. This was not fully restored to pre-exercise levels after 14 hours after recovery. (J Proteome Res. 2013;12(10):4577-84. PMID: 23984841.)
13- and 9-hydroxy-octadecadienoic acid (13-HODE + 9-HODE) increased 3.1-fold following 75-km cycling and was positively correlated with post-exercise F2-isoprostanes. These data for the first time supported the use of 13-HODE + 9-HODE as an oxidative stress biomarker in acute exercise investigations. (Am J Physiol Regul Integr Comp Physiol. 2014;307(1):R68-74. PMID: 24760997.)
Pistachios consumed before and during heavy exertion were related to the release of the trisaccharide raffinose into the blood stream and impaired performance (-5%) in endurance cyclists. Metabolomics revealed that the post-exercise increase in plasma raffinose correlated significantly with the leukotoxin 9,10-DiHOME and other oxidative stress metabolites. (PLoS One. 2014 Nov 19;9(11):e113725. PMID: 25409020.)
Please briefly summarize the research you’re presenting at Experimental Biology 2016 and what it means for athletes – both professionals and “weekend warriors.”
Many athletes and fitness enthusiasts believe they must consume sports drinks to support exercise training and competition. At the NCRC, we are interested in more healthful alternatives to sports drinks, especially fruit (PLoS One. 2012;7(5):e37479. PMID: 22616015).
Bananas and pears vary in sugar and phenolic profiles, and we worked with Metabolon to measure the influence of acute banana or pear ingestion on 75-km cycling performance and recovery. Performance times were faster with fruit ingestion compared to water alone, and the athletes experienced reductions in stress hormones and inflammation.
Metabolomics revealed that 107 metabolites increased more than 2-fold during 75-km cycling when drinking only water. Our most important finding was that the overall magnitude of increase in these metabolites was cut down by half during banana or pear ingestion. Additionally, increases in metabolites unique to bananas and pears improved antioxidant capacity in the athletes during exercise.
So, fruit ingestion is not only healthy—it also supports high-level performance and a quicker exercise recovery and contributes unique phenolics that augment antioxidant capacity. (J Proteome Res. 2015 Dec 4;14(12):5367-77. PMID: 26561314.)
We are currently working with Metabolon and Dole Foods in an exercise-based study with two different types of bananas that differ in sugar and phenolic content. Our focus is on multiple measurements during the 2-day period after 75-km cycling to better define how banana sugar and phenolics improve the rate of recovery.
We also plan to test whether brisk walking can augment the release of gut-derived phenolics back into the body, similar to what we found during prolonged and intensive exertion. Most ingested berry polyphenols go to the colon and then pass out of the body. Our hypothesis is that the combination of brisk walking and a diet high in berry polyphenols is synergistic, stimulating the translocation of phenolics degraded by colon bacteria back into the circulation and into various tissues where healthful bioactive effects take place.
Yes, definitely. Metabolon’s technology allows us to evaluate exercise and nutrition interventions from a whole body, systems level, improving our chances of making new discoveries. I liken this to shooting at a target with a shotgun versus a single bullet—much easier to hit the target of truth.
To learn how Metabolon can help you get more meaningful research results, contact us today.