Metabolomics provides crucial insights into physiological mechanisms in health and disease, integrating a combined read-out of genetics, environment, and lifestyle. Mass spectrometry is the technology of choice, allowing the quantification of metabolites with high selectivity and sensitivity. The range of mass spectrometry platforms is growing steadily, and so is our kit application portfolio. For the first time, the MxP® Quant 500 kit for broad, quantitative metabolic profiling is now available for Agilent triple quadrupole (TQ) instruments.

Over the last year, the MxP® Quant 500 kit became the leading metabolomics tool for broad metabolic profiling with a focus on host-microbiome-diet interaction. This ready-to-use kit provides a simple automated workflow for the quality-controlled analysis of 630 small molecules and lipids from 26 compound classes. With more than 230 predefined metabolite sums and ratios of metabolic pathways, it facilitates advanced biological data interpretation and increased statistical power. The MxP® Quant 500 kit is the most comprehensive metabolomics kit on the market – and now it’s also accessible to Agilent users.

Optimizing for excellence

The Agilent 6495B and 6495C TQ LC/MS systems are widely used instrument bases. To adapt the MxP® Quant 500 kit to these platforms, we’ve optimized all instrumental parameters, from sample preparation setup to mass spectrometric features. A comprehensive set of defined human plasma samples was used to validate the Agilent 6495B and 6495C TQ mass spectrometers, coupled to an Agilent 1290 Infinity II UHPLC. All 13 small molecule classes were analyzed by UHPLC-ESI-MS/MS, while hexoses and all 12 lipid classes were analyzed by FIA-MS/MS.

The results were impressive:
– All detected analytes had excellent intra- and inter-batch accuracy (85-115% for LC analytes, 80-120% for FIA analytes) and precision (CV <15% for LC analytes, CV <20% for FIA analytes).
– Highly comparable results were generated using the NIST standard reference material (SRM) 1950 across multiple 6495B and 6495C TQ LC/MS systems. This also allows for pooling of data between laboratories.
– In a typical human plasma sample, 540 metabolites and lipids were found to be routinely detected (>LOD) from a small sample volume of only 10 µl. We also saw impressive results testing other sample matrices, including human feces and mouse liver homogenate.

This means that Agilent platform users can rely on the MxP® Quant 500 kit for benefits such as:
– A ready-to-use solution including all consumables and instrument-specific acquisition methods
– An automated, software-guided workflow from sample registration to data interpretation
– Fast turnaround times to guarantee high throughput analyses
– Reliable standardized quantification of the full range of metabolites and lipids.

The MxP® Quant 500 kit combined with the Agilent 6495B or 6495C TQ LC/MS system provides high-quality results with excellent reproducibility. This robust solution provides a powerful tool for broad, quantitative metabolic profiling.

All details and results of the adaptation on the 6495C TQ LC/MS system can be found in the application note 35044.
To find out more about the MxP® Quant 500 kit, please visit the product page.

Get a fuller picture of microbiome, diet, and energy metabolism

Short- and medium-chain fatty acids in health and disease

Short-chain fatty acids (SCFAs) and medium-chain fatty acids (MCFAs) are well-established as important diet-based energy sources.

In recent years, their role as signaling molecules involved in the regulation of carbohydrate and lipid metabolism has been revealed in a growing number of studies (reviewed by Schönfeld and Wojtczak 2016). Genetic defects in the metabolism of both SCFAs and MCFAs can result in inborn errors of metabolism.

Persistent aberrations in SCFA and MCFA concentrations, such as those caused by a western-style diet, may lead to inflammation and insulin resistance, eventually resulting in disorders including diabetes, neurodegenerative diseases, and cancer.

Could the combined analysis of SCFAs and MCFAs offer fresh insights into diet-microbiome-host interactions, energy homeostasis, and health status?

Short-chain fatty acids (SCFAs)

In mammals, SCFAs are primarily generated by the gut microbiome through fermentation of dietary fibers. Dietary proteins and peptides can also be a source of SCFAs.

The branched-chain amino acids valine, leucine, and isoleucine can be metabolized by intestinal bacteria to branched-chain fatty acids (BCFAs) like isobutyric acid and isovaleric acid.

These BCFAs are crucial mediators of the gut-brain axis, modulating the release of the neurotransmitter serotonin by specialized cells in the gut epithelium.

The most abundant SCFAs – acetic acid, propionic acid, and butyric acid – perform tissue-specific regulatory functions and are central mediators of the gut-immune axis.

In general, SCFAs boost immunity and promote metabolic health via the following mechanisms:

• Binding to G-protein coupled receptors (GPCRs)
• Inhibiting of histone deacetylases (HDACs)
• Integrating with the central energy metabolism (tricarboxylic acid cycle and β-oxidation)

Several studies have shown that supplementation with prebiotic SCFAs or precursors or probiotic SCFA-producing bacteria, promote health effects including weight reduction, reduction of fasting glucose levels, and increased insulin release (reviewed by Koh et al. 2016).

Medium-chain fatty acids (MCFAs)

MCFAs, such as caprylic acid and lauric acid, derive mainly from dietary medium-chain triglycerides, as found in dairy milk or palm kernel oil.

Circulating free MCFAs are not only energy fuels and precursors of ketone bodies, but they also act as tissue-specific metabolic signaling molecules involved in the regulation of inflammatory processes and insulin sensitivity.

This occurs through the following mechanisms:

• Interaction with cell membrane G-protein coupled receptors (GPCRs)
• Binding to the nuclear receptor peroxisome proliferator-activated receptor gamma (PPARY)
• Interaction with the cytosolic second messenger adenosine monophosphate (AMP)

MCFAs may have beneficial effects on glucose and lipid metabolism, and have been shown to have ameliorating effects on metabolic and neurological disorders in clinical trials (reviewed by Huang et al. 2021).

Consider your pre-analytical factors

In metabolomic studies, pre-analytical factors play a fundamental role. The concentration of a metabolite measured in a sample may be affected by when and how a sample is collected, processed, and stored.

When using fecal samples, the site from where an aliquot is drawn already makes a difference. Fecal samples are highly inhomogeneous, so pooling aliquots from different sites instead of a single spot can minimize the variance in SCFA and MCFA concentrations.

A multi-spot sampling approach is highly recommended to compensate for intra-sample variations and obtain reliable and comparable data.

For serum and plasma samples, storage time and temperature can affect the stability of certain SCFAs and MCFAs. Interestingly, SCFA concentrations often increase with time and temperature, probably due to continuous degradation of other metabolites.

This means that blood-based samples should be collected within a relatively short timeframe and stored as soon as possible at -80°C to ensure stability before analysis.

Overall, it is essential to collect and treat the samples used in a study for the analysis of SCFAs and MCFAs as consistently as possible. Find more detailed information on how to handle fecal, serum, and plasma samples for the analysis of SCFAs and MCFAs in the Application note 35045-SCFA+ assay (v1-2021).

If you are interested in measuring SCFAs or MCFAs, have a look at the SCFA+ assay. This will allow you to get a fuller picture of diet-microbiome-host interactions, energy homeostasis, and health status.

References

Huang L, Gao L, Chen C.: Role of Medium-Chain Fatty Acids in Healthy Metabolism: A Clinical Perspective (2021) Trends Endocrinol Metab | https://doi.org/10.1016/j.tem.2021.03.002

Koh A, Vadder F de, Kovatcheva-Datchary P, Bäckhed F.: From Dietary Fiber to Host Physiology: Short-Chain Fatty Acids as Key Bacterial Metabolites (2016) Cell | https://doi.org/10.1016/j.cell.2016.05.041

Schönfeld P, Wojtczak L. Short- and medium-chain fatty acids in energy metabolism: the cellular perspective (2016) J. Lipid Res. | https://doi.org/10.1194/jlr.R067629

Metabolomics provides crucial insights into physiological mechanisms in health and disease, integrating a combined read-out of genetics, environment, and lifestyle. Mass spectrometry is the technology of choice, allowing the quantification of metabolites with high selectivity and sensitivity. The range of mass spectrometry platforms is growing steadily, and so is our kit application portfolio. For the first time, the MxP® Quant 500 kit for broad, quantitative metabolic profiling is now available for Agilent triple quadrupole instruments.

Over the last year, the MxP® Quant 500 kit became the leading metabolomics tool for broad metabolic profiling with a focus on host-microbiome-diet interaction. This ready-to-use kit provides a simple automated workflow for the quality-controlled analysis of 630 small molecules and lipids from 26 compound classes. With more than 230 predefined metabolite sums and ratios of metabolic pathways, it facilitates advanced biological data interpretation and increased statistical power. The MxP® Quant 500 kit is the most comprehensive metabolomics kit on the market – and now it’s also accessible to Agilent users.

Optimizing for excellence

The Agilent 6495C triple quadrupole LC/MS system is a widely used instrument base. To adapt the MxP® Quant 500 kit to this platform, we’ve optimized all instrumental parameters, from sample preparation setup to mass spectrometric features. A comprehensive set of defined human plasma samples was used to validate the Agilent 6495C TQ mass spectrometer, coupled to an Agilent 1290 Infinity II UHPLC. All 13 small molecule classes were analyzed by UHPLC-ESI-MS/MS, while hexoses and all 12 lipid classes were analyzed by FIA-MS/MS.

The results were impressive:
– All detected analytes had excellent intra- and inter-batch accuracy (85-115% for LC analytes, 80-120% for FIA analytes) and precision (CV <15% for LC analytes, CV <20% for FIA analytes).
– Highly comparable results were generated using the NIST standard reference material (SRM) 1950 across three separate 6495C TQ LC/MS systems. This also allows for pooling of data between laboratories.
– In a typical human plasma sample, 540 metabolites and lipids were found to be routinely detected (>LOD) from a small sample volume of only 10 µl. We also saw impressive results testing other sample matrices, including human feces and mouse liver homogenate.

This means that Agilent platform users can rely on the MxP® Quant 500 kit for benefits such as:
– A ready-to-use solution including all consumables and instrument-specific acquisition methods
– An automated, software-guided workflow from sample registration to data interpretation
– Fast turnaround times to guarantee high throughput analyses
– Reliable standardized quantification of the full range of metabolites and lipids.

The MxP® Quant 500 kit combined with the Agilent 6495C triple quadrupole LC/MS system provides high-quality results with excellent reproducibility. This robust solution provides a powerful tool for broad, quantitative metabolic profiling.

All details and results of the adaptation can be found in the application note 35044.
To find out more about the MxP® Quant 500 kit, please visit the product page.

Central nervous system (CNS) infections, especially bacterial meningitis, remain a severe health issue with high morbidity and mortality. Since an early and differential diagnosis of the infection is crucial for fast and effective treatment, biomarkers for rapid assessment and identification of different CNS infections would be a huge advantage.

This was the ambitious goal of a recent study led by PD Dr. Frank Pessler from the Helmholtz Centre for Infection Research in Hannover, Germany. The group chose cerebrospinal fluid (CSF) as sample matrix, and included 132 patients with bacterial meningitis, viral meningitis or encephalitis, and noninflamed controls. Since lipids have previously been shown to represent promising biomarkers for CNS disorders, lipid profiles in CSF were obtained through targeted metabolomics.

The analyses revealed that in patients with bacterial meningitis, CSF levels of 54 phosphatidylcholines (PCs) were significantly elevated compared to both viral infection and controls. Following internal cross-validation, 10 PCs were determined as the most robust markers. Indeed, 4 of the top 5 PCs showed a better overall discriminative performance compared to standard CSF parameters. Although promising, the results have not yet been validated in an independent data set.

Since PCs are the main building blocks of lipid bilayers in biological systems, the elevated levels of free PCs in CSF can be explained by disruptions of neuronal membranes resulting from CNS infection. Although an increase in released PCs is not unique to bacterial infections, the levels measured here are considerably higher than in viral CNS infections. This most likely reflects more pronounced cell damage. In addition, there was very little overlap between the top phosphatidylcholine biomarkers observed between bacterial and viral meningitis.

Interestingly, the changes in PCs due to bacterial meningitis correlated more strongly with markers for local CNS disease than systemic inflammation. These markers reflected dysfunction of the blood-CSF barrier and cell death. In serum, PC concentrations did not change significantly. Together, this indicates that increased PC levels do not reflect systemic inflammation, but result from local disease activity. PC levels in CSF could also distinguish bacterial meningitis caused by classical pathogens from that caused by atypical pathogens. In patients with a classical infection, concentrations were significantly higher, which is, again, likely due to a more severe cell damage.

Overall, the authors of this study have identified free PCs in CSF as highly promising biomarker candidates for an improved and more differential diagnosis of bacterial meningitis. It would be interesting to see if and how the top markers could be combined in a marker signature, instead of considered as single markers.

Please visit our focus pages on neurology and infectious diseases, if you are interested in more applications from these fields.

Al-Mekhlafi A, Sühs K-W, Schuchardt S, Kuhn M, Müller-Vahl K, Trebst C et al.: Elevated Free Phosphatidylcholine Levels in Cerebrospinal Fluid Distinguish Bacterial from Viral CNS Infections. (2021) | https://doi.org/10.3390/cells10051115

Dietary intervention is crucial for the prevention and management of many diseases, including type 2 diabetes (T2D). Therefore, accurate record keeping of a person’s diet is often key in nutritional studies. However, self-reported dietary intake is biased, and food intake is frequently underestimated. To avoid this source of error, blood metabolites measured in the general population can be used to objectively assess adherence to dietary advices.

In a recent Europe-wide study led by Prof. Gary Frost from the Imperial College in London, researchers have applied a previously developed predictive model (T_pred) to a large population-based cohort in order to explore the relationship between diet and cardiometabolic risk. The T_pred was originally developed to classify the healthiness of diets based on urinary metabolite profiles. Here, it was applied to plasma metabolomics data from the European Union Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) multicenter prospective cohort study involving leading academic institutions and pharmaceutical companies. Baseline metabolic profiles were assessed in fasting plasma samples from 861 participants with either normal or pre-diabetic glucose regulation (cohort 1, n = 403) or diagnosed with T2D (cohort 2, n = 458).

The researchers found in both cohorts a higher T_pred score reflecting healthier dietary patterns, including higher intake of wholegrains, fruits, and vegetables, and a lower intake of saturated fats and sugars. In accordance with these findings, a higher T_pred was also linked to a lower body weight and favorable blood lipid profiles like lower triglycerides and higher HDL (high-density lipoprotein) cholesterol.

This is the first study to assess dietary metabolite profiling in combination with T2D risk, and one of the very few ones on metabolic profiling of dietary patterns on a population level.

Since the T_pred does not capture direct dietary metabolites, it may work as a great example indicating that it’s not necessary to focus on dietary metabolites alone. There are additional lifestyle and non-lifestyle factors, such as the gut microbiota, that influence the relationship between diet and cardiometabolic health. Overall, the T_pred score provides an objective and more accurate measurement of dietary patterns compared to traditional nutritional analysis methods relying mainly on food frequency questionnaires. It is, thus, a very promising validation tool to be utilized in nutritional studies to reduce misreporting and measurement bias existing in self-reported diet recordings and to enhance adherence to dietary advices.

If you are interested in more examples on how metabolic profiling can be applied in nutrition studies, please visit the literature section on nutrition and wellbeing on our webpage.

Eriksen et al.: Dietary metabolite profiling brings new insight into the relationship between nutrition and metabolic risk: An IMI DIRECT study. (2020) EBioMedicine | https://doi.org/10.1016/j.ebiom.2020.102932

In cancer, clinicians continue to struggle with patients not responding to targeted treatments, despite the presence of the potential drug target. It is, therefore, of utmost importance to understand how a drug is metabolized as a basis for improved drug selection and prevention of undesired effects. Early in the drug development process, circulating metabolites may provide the desired answers and markers to understand this mechanism of action.

Moreover, access to human tumor tissue is often limited, and biomarkers in minimal invasive matrices, like blood plasma, are favored. The use of preclinical models, such as mouse xenografts, for the identification of biomarkers that can be translated into clinical settings would further facilitate pharmacological studies.

In a recent study led by Dr. Florence Reynaud from the Institute of Cancer Research in London, UK, the researchers investigated a novel cancer drug in preclinical mouse models and evaluated its performance in early clinical trials. This is already the third study by this group proving the successful application of targeted metabolomics to identify drug-related changes in preclinical samples that can be translated to clinical ones. In the current study, the team deals with a multi-target AGC kinase inhibitor; the previous studies were dedicated to a PI3K inhibitor and a MEK inhibitor, respectively.

The multi-AGC kinase inhibitor AT13148 affected plasma levels of 45 metabolites in non-tumor bearing mice compared to untreated mice, whereas in mice with human tumor xenografts, surprisingly, no robust signature could be revealed. Indeed, 44 out of these 45 metabolites were confirmed to be altered in plasma from advanced cancer patients treated with AT13148 in a Phase I dose-escalation clinical study. A gene-metabolite network analysis showed a strong link to an activated nitric oxide synthase (NOS) pathway. This is in line with the observed decreased plasma levels of asymmetric dimethylarginine (ADMA), an endogenous NOS inhibitor, and simultaneous increased hypotension in patients at higher doses. The underlying mechanism for the clinically observed phenotype can be explained with an AT13148-triggered NOS activation leading to an enhanced production of the vasodilator NO and, thus, leading to hypotension.

Though circulating metabolites have been shown to be promising pharmacodynamic or even predictive markers translatable from preclinical to clinical trials in previous studies with single-target drugs, this seems to be especially challenging in the case of multi-target drugs. However, in the present study, it was demonstrated that changes in circulating metabolite levels induced by a multi-AGC kinase inhibitor in mice and patients may contribute to a better understanding of its mechanism of action.

If you are interested in more examples on how metabolic profiling can be applied in pharmacological studies, please visit the literature section on pharmacology on our webpage.

Pal A, Asad Y, Ruddle R, et al.: Metabolomic changes of the multi (-AGC-) kinase inhibitor AT13148 in cells, mice and patients are associated with NOS regulation. (2020) Metabolomics | https//doi.org/10.1007/s11306-020-01676-0

Chronic inflammation is known to increase with aging. But the molecular mechanism that connects chronic inflammation to physical frailty and functional decline in older adults are yet to be elucidated. This was the aim of a research group led by Dr. Peter Abadir from the Division of Geriatric Medicine and Gerontology at the Johns Hopkins University in Baltimore, USA.

First, the researchers conducted metabolomic analyses using a mouse model of chronic inflammation. The mice showed reduced plasma levels of the essential amino acid tryptophan and elevated concentrations of the tryptophan degradation product kynurenine compared to control mice that did not have chronic inflammation. Consequently, the kynurenine/tryptophan ratio reflecting the activity of the rate-limiting enzyme indoleamine-2,3-dioxygenase (IDO) converting tryptophan to kynurenine was increased in middle-aged and old pro-inflammatory mice compared to younger ones.

In a second step, these results were validated in human subjects, where frail older individuals showed even higher kynurenine/tryptophan ratios than non-frail ones. The ratio also correlated with levels of inflammatory cytokines like TNF-α, IFN-γ, and IL-6 that are known to induce IDO activity. In addition, lower levels of serotonin, another degradation product of tryptophan, were detected in serum from older individuals, independent from frailty, compared to younger adults. Furthermore, kynurenine metabolites known to have neurotoxic properties, 3-hydroxykynurenine and quinolinic acid, were elevated in both the frail subjects as well as frail and non-frail adults, respectively.

Together, accumulation of neurotoxic kynurenine metabolites with aging and, even more, with frailty could be identified as the mechanism of neuromuscular defects in older adults. Induction of IDO activity by inflammatory cytokines might be the underlying cause. The resulting degeneration of the motor nerve may be responsible for the decline in muscle mass and strength with aging. Besides alterations in the tryptophan metabolism, also changes in the arginine metabolism have been observed in this study which point towards kidney dysfunction in older adults.

This study not only identified a previously unclear molecular mechanism linking chronic inflammation to functional decline and physical frailty with aging, it is also an excellent example for the translatability of results from mouse to man.

If you want to learn more about the quatification of different tryptophan metabolites, please visit our webpage on the Tryptophan metabolism assay.

Related articles:

Blog article: Metabolite of the month – Kynurenine

Westbrook R, Chung T, Lovett J, Ward C, Joca H, Yang H et al. Kynurenines link chronic inflammation to functional decline and physical frailty. (2020) JCI Insight | https://doi.org/10.1172/jci.insight.136091

Coronary heart disease (CHD) is a complex and heterogenic disease that is increasingly becoming a public health burden worldwide. Current risk assessment is based on classic risk factors (BMI, systolic blood pressure, diabetes, total cholesterol) and two established clinical biomarkers, high-sensitivity C-reactive protein (hsCRP) and high-sensitivity troponin I (hsTnI). An improved risk stratification process would advance preventive actions.

The multinational Biomarker for Cardiovascular Risk Assessment in Europe (BiomarCaRE) consortium aimed to evaluate the association between circulating metabolites and CHD in a large, prospective population-based cohort and to assess the capability of metabolomics for CHD risk stratification. For the present study, baseline serum samples from more than 12,000 individuals with over 2,000 incident CHD events over a median follow-up time of 9.2 years were analyzed.

Of the 141 metabolites quantified, five phosphatidylcholines (PC ae C40:6, PC aa C40:6, PC ae C38:6, PC aa C38:6, PC aa C38:5) showed significant inverse association with the risk of incident CHD after correction for multiple testing: increasing levels of phosphatidylcholines were protective against incident CHD, which is in accordance with previous studies. These circulating metabolites showed a comparable discrimination to classic risk factors and established clinical biomarkers.

These findings not only contribute to a better understanding of the pathophysiology of CHD, but also demonstrate the potential of phosphatidylcholines in the risk assessment of coronary heart disease, underlining the value of metabolomics for biomarker discovery.

If you are interested in carrying out a large, multi-center study, our standardized metabolomics kits are the ideal tool to accomplish such a task. Please visit the products and services webpages for additional information, or contact us for support.

Cavus E, Karakas M, Ojeda FM, Kontto J, Veronesi G, Ferrario MM et al. Association of Circulating Metabolites With Risk of Coronary Heart Disease in a European Population: Results From the Biomarkers for Cardiovascular Risk Assessment in Europe (BiomarCaRE) Consortium. (2019) JAMA Cardiol | https://doi.org/10.1001/jamacardio.2019.4130

Incidence of non-alcoholic steatohepatitis (NASH), an advanced form of non-alcoholic fatty liver disease (NAFLD), is rapidly increasing globally and may progress to hepatocellular carcinoma (HCC) with or without cirrhosis. The progression cascade from NAFLD via NASH to HCC may be promoted by alterations in the gut microbiome and the bile acid homeostasis, both essential parts of the gut-liver axis.

This is what a recent study led by a German research group from the University Hospital Magdeburg aimed to investigate for NASH-related HCC. Stool and serum samples from 87 subjects divided into five groups (NASH, NASH with cirrhosis, NASH-HCC, NASH-HCC with cirrhosis, and healthy controls) were included in the analysis.

Serum levels of total bile acids and individual conjugated primary bile acids increased with disease severity, which is even more pronounced in patients with cirrhosis. Unlike in NASH, serum levels of the fibroblast growth factor 19 (FGF19), a suppressor of hepatic bile acid synthesis induced by the nuclear receptor farnesoid X receptor (FXR), were elevated in NASH-HCC patients. This indicates that different mechanisms lead to the accumulation of bile acids, independent from cirrhosis. Along with the alteration in bile acid homeostasis, the diversity of certain intestinal bacteria was affected. An increased abundance of Lactobacilli, for instance, is thought to be a consequence of the increased availability of primary conjugated bile acids as a substrate for deconjugating enzymes of these bacteria.

Overall, the researchers propose that an increase in bile acid levels might contribute to fibrogenesis, liver injury, and tumorigenesis in NASH-HCC, while there seem to be two distinct mechanisms in hepatocarcinogenesis, a cirrhosis-dependent and an –independent one, reflected by even higher serum BA levels.

If you are interested in learning more about the gut microbiota and in quantifying bile acids or other microbial-derived metabolites, please visit our products and services webpages, or contact us for support.

Sydor S, Best J, Messerschmidt I, Manka P, Vilchez-Vargas R, Brodesser S, Lucas C, Wegehaupt A, Wenning C, Aßmuth S, Hohenester S, Link A, Faber KN, Moshage H, Cubero FJ, Friedman SL, Gerken G, Trauner M, Canbay A, Bechmann LP: Altered Microbiota Diversity and Bile Acid Signaling in Cirrhotic and Noncirrhotic NASH-HCC (2020) Clin Transl Gastroenterol | https://doi.org/10.14309/ctg.0000000000000131

Although Robert Koch won the Nobel Prize for his discovery of the tuberculosis-causing bacterium, Mycobacterium tuberculosis,  more than 100 years ago, tuberculosis remains the deadliest infectious disease globally with 1.5 million deaths per year. However, its diagnosis remains a challenge as current methods cannot discriminate active from asymptomatic, non-contagious latent tuberculosis.

In a recent study, Cho and colleagues from the Yonsei University College of Medicine in Seoul, Republic of Korea identified a set of metabolites as potential biomarkers to diagnose active tuberculosis. The metabolite levels were quantified in serum samples from subjects with active pulmonary tuberculosis, latent tuberculosis, and healthy controls by employing targeted metabolomics. Despite the relatively small sample size of this cross-sectional study, the design and the statistical methods were carefully chosen.

Based on their metabolic profiles, patients with active tuberculosis could easily be distinguished from patients with latent tuberculosis or healthy controls. Active tuberculosis patients experienced higher serum concentrations of glutamate, methionine sulfoxide, and aspartate as well as lower concentrations of glutamine, methionine, and asparagine than the other two groups. Together with these single metabolites, also their biologically meaningful ratios, glutamate/glutamine, methionine sulfoxide/methionine, and aspartate/asparagine, showed a good clinical performance in diagnosing active tuberculosis.

In consistency with previous findings, the authors suggested that the observed metabolic changes reflect both adaptive mechanisms of M. tuberculosis and immune responses of the host. For instance, the increased glutamate/glutamine ratio in active tuberculosis patients reflects the enzymatic activity of the bacterial glutamate synthase. This enzyme converts glutamine to glutamate to generate neutral pH conditions in the cytoplasm of the host cell creating a pleasant environment for the intracellular pathogen. Collectively, these findings pave the way for certain amino acids and their ratios to be exploited as diagnostic markers of active pulmonary tuberculosis.

If you are interested in finding biomarkers for differential diagnostics or patient stratification, please have a look at our products and services. For more information on biologically meaningful metabolic ratios go to our MetaboINDICATOR™ tool or contact us.

Yonggeun Cho, Youngmok Park, Bora Sim, Jungho Kim, Hyejon Lee, Sang-Nae Cho, Young Ae Kang, Sang-Guk Lee. Identification of serum biomarkers for active pulmonary tuberculosis using a targeted metabolomics approach. Sci Rep 2020; https://doi.org/10.1038/s41598-020-60669-0