Posts Tagged ‘Metabolite’

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

The metabolite pool of cells and tissues represents the end result of metabolism determined by genetic, environmental and nutritional factors. The metabolic profile of biological systems is closely related to the individual phenotype and reflects the biological endpoint of a multitude of pathways and their interaction with any confounding stimuli. Cancer cells exhibit activation of specific metabolic pathways to compensate for their extremely high energy demands. Indeed increased glucose uptake and lactate production and decreased respiration are key phenomena of tumour cell metabolism. In particular, the generation of an acidic microenvironment through increased lactate production, even under aerobic conditions, may confer extracellular matrix degeneration and exert toxic effects on surrounding cell populations, while being harmless for the cancer cell itself. Thus, the metabolic adaptations may indeed be critical for the development of accelerated proliferation and the invasive growth of tumour cell populations. The molecular mechanisms underlying the metabolic hallmarks of cancer are still poorly understood, although genetic, epigenetic and environmental factors driving cancer development and progression will interact to determine the metabolic phenotype of tumour cells. Recent studies suggest that metabolic changes play a pivotal role in the biology of renal cell carcinoma – a tumour entity that is largely resistant to conventional chemo- and radiotherapy. The metabolic profile of renal tumours may thus serve as a reliable biomarker of malignant transformation and biological behaviour.

Recent advances in metabolic profiling technologies by providing quantitative measures of metabolite profiles from gas chromatography time-of-flight mass spectrometry (GC-TOF-MS) based technology present the opportunity to apply this technique in human specimens. Global metabolic profiling has emerged as a promising approach to characterize the metabolite pool within a cell, tissue or bodily fluid under certain conditions, such as health or disease status. Metabolic profiling is applied to monitor the health to disease continuum and has the potential of increasing our understanding of the mechanisms of disease. Thus the characterization of the metabolic features in tumours is expected to provide a better understanding of the mechanisms of malignant transformation and progression and may lead to the identification of metabolic biomarkers for cancer detection and prognostication. However, comparative profiling of low molecular weight compounds, such as sugars, lipids and amino acids, in cancer as compared to the corresponding normal tissue is a rather unexplored area. The objective of this study was to characterize the key metabolic features of renal cell carcinoma using GC-TOF-MS and mutual information as well as decision tree-based data analysis.

Hypoxia is key in tumour cell behaviour. Hypoxia, via hypoxia inducible factor, plays a key role in the metabolic changes in the kidney cancer cell and influences different pathways. Pathways that use tyrosine kinases and mammalian target of rapamycin are well studied. Hypoxia-related effects on vascular epithelial growth factors and angiogenesis will influence the metabolic status of the cell significantly. This is the basis of inhibitor-type drugs or antibody blocking agents and the effect on the clinical course of renal cell carcinoma patients. Detailed information about metabolic changes is crucial to understanding these mechanisms more clearly. Treating renal cell carcinoma patients is not like treating one disease. Renal cell carcinoma has different morphologic entities with distinct differences in cytogenetic background. These differences should be reflected in the different approaches of diagnostic and therapeutic strategies. This consideration will help to increase the efficacy of novel agents and decrease unnecessary side-effects. Metabolomics explains the importance of explaining genetic changes and the functional outcome of the tumour cells. In addition, epidemiologic differences in incidence and prevalence in different parts of the world may help provide insight into the etiology of kidney cancer. Factors that may influence renal cancer likelihood (eg, obesity, antihypertensive therapy) may have an explanation in metabolomics.

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World of Metabolites:  Lawrence Berkeley National Laboratory developed Imaging Technique for their Capturing

Reporter: Aviva Lev-Ari, PhD, RN


UPDATED on 9/27/2017

From: “Dr. Larry Bernstein” <larry.bernstein@gmail.com>

Reply-To: “Dr. Larry Bernstein” <larry.bernstein@gmail.com>

Date: Tuesday, September 26, 2017 at 10:45 AM

To: Aviva Lev-Ari <AvivaLev-Ari@alum.berkeley.edu>

Precision or personalized medicine seeks to provide the right drug to the right patient at the right time. Hence the significance of the principal omics: disciplines of genomics, proteomics, and last but not least metabolomics, as diagnostic enablers. 

Primacy among the ‘omics is debatable, but the notion that metabolomics reflects the most accurate picture of disease states has reached significant momentum. “Almost every factor affecting health exerts its influence by altering metabolite levels,” says Mike Milburn, Ph.D., Chief Scientific Officer at Metabolon (Morrisville, North Carolina, USA). 

Where clinical chemistry blood tests typically quantify individual species for example, glucose or cholesterol, metabolomics measures hundreds or even thousands of metabolites to provide a nuanced view of disease states. 

Metabolon employs standard liquid chromatography-mass spectrometry (LC-MS) for metabolomic studies. Its proprietary informatics and processing platform, Precision MetabolomicsTM, overcomes the “big data” challenge, a natural consequence of measuring hundreds or thousands of small-molecule entities with widely differing concentrations in a single sample. Precision Metabolomics enables “n of 1” studies — meaningful clinical trials on a single patient, Milburn adds:

Diagnostic metabolomics resembles other medical testing, where results are compared against readings from healthy individuals or a reference population. Many metabolites serve that purpose but none on its own is sufficiently specific or diagnostic for a diagnosis — otherwise it would comprise a standalone test. Hence the reliance on metabolite panels or networks, which together may provide a clearer view of disease states than any single diagnostic molecule.


Imaging technique captures ever-changing world of metabolites

Thu, 06/13/2013 – 7:38am

The kinetic world of metabolites comes to life in this merged overlay of mass spectrometry images. It shows new versus pre-existing metabolites in a tumor section (yellow and red indicate newer metabolites). Image: Lawrence Berkeley National LaboratoryThe kinetic world of metabolites comes to life in this merged overlay of mass spectrometry images. It shows new versus pre-existing metabolites in a tumor section (yellow and red indicate newer metabolites). Image: Lawrence Berkeley National LaboratoryWhat would you do with a camera that can take a picture of something and tell you how new it is? If you’re Lawrence Berkeley National Laboratory scientists Katherine Louie, Ben Bowen, Jian-Hua Mao and Trent Northen, you use it to gain a better understanding of the ever-changing world of metabolites, the molecules that drive life-sustaining chemical transformations within cells.

They’re part of a team of researchers that developed a mass spectrometry imaging technique that not only maps the whereabouts of individual metabolites in a biological sample, but how new the metabolites are too.

That’s a big milestone, because metabolites are constantly in flux. They’re synthesized on-demand in order to sustain an organism’s energy requirements. When you eat lunch, metabolites momentarily fire up in various cell populations throughout your body to fuel your day. But they also have a dark side. Cancer cells tap metabolites to drive tumor development.

Unfortunately, the current ways to clinically analyze metabolites don’t capture their kinetics. Microscopy maps the cells and biomarkers in a tumor section. And traditional mass spectrometry reveals the abundance and spatial distribution of molecules such as metabolites.

But these images are static snapshots of a highly dynamic process. They’re blind to how recently the metabolites were synthesized, which is a key piece of information. The metabolic status of a cell population is a good indicator of what the cells were up to when the sample was taken.

To image the ebb and flow of metabolites, the scientists paired mass spectrometry with a clinically accepted way to label tissue that uses a hydrogen isotope called deuterium.

As reported in Nature Scientific Reports, they administered deuterium to mice with tumors. Newly synthesized lipids (a hallmark of metabolic activity) became labeled with deuterium, while pre-existing lipids remained unlabeled. The scientists then removed tumor sections and analyzed them with a type of mass spectrometry.

The resulting images look like freeze-frames of a slow-motion fireworks show. They reveal when and where metabolic turnover occurs in a tumor section, with the brighter colors depicting newly synthesized lipids.

The scientists also found that regions with new lipids had a higher tumor grade, which is a good predictor of how quickly a tumor is likely to grow.

“Our approach, called kinetic mass spectrometry imaging, could provide clinicians with quantifiable information they can use,” says Bowen.

The scientists are now applying their imaging technique to study metabolic flux in other biological systems, such as microbial communities.

Source: Lawrence Berkeley National Laboratory



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Unraveling Retrograde Signaling Pathways

Reporter: Larry H. Bernstein, MD, FCAP

Unraveling Retrograde Signaling

Image Source: Created by Noam Steiner Tomer 8/10/2020

Unraveling retrograde signaling pathways: finding candidate signaling molecules via metabolomics and systems biology driven approaches
C Caldana, AR Fernie, L Willmitzer and D Steinhauser
Front. Plant Sci. 2012; 3:267.                    http://dx.doi.org/10.3389/fpls.2012.00267

http://fpls.com/Unraveling retrograde signaling pathways: finding candidate signaling molecules via
metabolomics and systems biology driven approaches

signals can be generated within organelles, such as chloroplasts and mitochondria,

  • modulating the nuclear gene expression in a process called
    • retrograde signaling.

Recently, integrative genomics approaches, in which correlation analysis has been applied on transcript and metabolite profiling data
of Arabidopsis thaliana, revealed the identification of metabolites which are

  • putatively acting as mediators of nuclear gene expression.


English: Plant Pathology in Arabidopsis thaliana

English: Plant Pathology in Arabidopsis thaliana (Photo credit: Wikipedia)

B0004313 Gene expression in normal and cancer ...

B0004313 Gene expression in normal and cancer cells (Photo credit: wellcome images)

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