Reducing impacts of organism variability in metabolomics via time trajectory in vivo NMR

Anaraki, Maryam Tabatabaei; Simpson, Myrna J.; Simpson, André J.

doi:10.1002/mrc.4759

Cited by 22 publications

(37 citation statements)

References 33 publications

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“…As such, researchers must choose between variables such as the number of replicates, the experiment duration, and the time resolution for time-series. Furthermore, traditional metabolomics experimental designs face the challenges of extraction biases (Sitnikov et al, 2016) and the confounding of biological and analytical variance (Tabatabaei Anaraki et al, 2018). While many studies employ sample preparation and extraction approaches effectively, direct or in vivo measurements are fundamentally simpler to obtain and interpret.…”

Section: Introductionmentioning

confidence: 99%

Continuous in vivo Metabolism by NMR

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Tayyari

et al. 2019

Front. Mol. Biosci.

104

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Dense time-series metabolomics data are essential for unraveling the underlying dynamic properties of metabolism. Here we extend high-resolution-magic angle spinning (HR-MAS) to enable continuous in vivo monitoring of metabolism by NMR (CIVM-NMR) and provide analysis tools for these data. First, we reproduced a result in human chronic lymphoid leukemia cells by using isotope-edited CIVM-NMR to rapidly and unambiguously demonstrate unidirectional flux in branched-chain amino acid metabolism. We then collected untargeted CIVM-NMR datasets for Neurospora crassa , a classic multicellular model organism, and uncovered dynamics between central carbon metabolism, amino acid metabolism, energy storage molecules, and lipid and cell wall precursors. Virtually no sample preparation was required to yield a dynamic metabolic fingerprint over hours to days at ~4-min temporal resolution with little noise. CIVM-NMR is simple and readily adapted to different types of cells and microorganisms, offering an experimental complement to kinetic models of metabolism for diverse biological systems.

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Section: Introductionmentioning

confidence: 99%

Continuous in vivo Metabolism by NMR

Judge

Tayyari

et al. 2019

Front. Mol. Biosci.

104

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“…While approaches such as lipid suppression techniques 32−34 and newly developed 1 H NMR sequences to reduce susceptibility broadening 31 hold great potential, combining isotopic labeling of the living organisms with 2D 1 H– 13 C NMR detection has proven to be the most robust approach. 3,4,35−37…”

Section: Resultsmentioning

confidence: 99%

“…20 Amino acid concentrations are of particular significance as their levels are perturbed in the vast majority of stress responses, and as such, they act as an excellent proxy to gauge first-order stress. 2−4,35,36…”

Section: Resultsmentioning

confidence: 99%

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Selective Amino Acid-Only in Vivo NMR: A Powerful Tool To Follow Stress Processes

et al. 2019

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In vivo NMR of small 13 C-enriched aquatic organisms is developing as a powerful tool to detect and explain toxic stress at the biochemical level. Amino acids are a very important category of metabolites for stress detection as they are involved in the vast majority of stress response pathways. As such, they are a useful proxy for stress detection in general, which could then be a trigger for more in-depth analysis of the metabolome. 1 H– 13 C heteronuclear single quantum coherence (HSQC) is commonly used to provide additional spectral dispersion in vivo and permit metabolite assignment. While some amino acids can be assigned from HSQC, spectral overlap makes monitoring them in vivo challenging. Here, an experiment typically used to study protein structures is adapted for the selective detection of amino acids inside living Daphnia magna (water fleas). All 20 common amino acids can be selectively detected in both extracts and in vivo. By monitoring bisphenol-A exposure, the in vivo amino acid-only approach identified larger fluxes in a greater number of amino acids when compared to published works using extracts from whole organism homogenates. This suggests that amino acid-only NMR of living organisms may be a very sensitive tool in the detection of stress in vivo and is highly complementary to more traditional metabolomics-based methods. The ability of selective NMR experiments to help researchers to “look inside” living organisms and only detect specific molecules of interest is quite profound and paves the way for the future development of additional targeted experiments for in vivo research and monitoring.

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“…Figure 1 compares the full 1 H- 13 C HSQC (1A), conventional 1 H projection (1B), and 13 C projection (1C) against the information rich complete projection (1D) (termed here as “spikelet projection”) for in vivo Daphnia magna . Maryam Tabatabaei Anaraki et al [20] have discussed the impacts of anoxic stress on Daphnia magna . In the study, it was demonstrated that the separation along PC1 arises from the accumulation of lactic acid, whereas the separation along PC2 arises from slight differences in the lipids between the 3 different populations of Daphnia magna .…”

Section: Resultsmentioning

confidence: 99%

1D “Spikelet” Projections from Heteronuclear 2D NMR Data—Permitting 1D Chemometrics While Preserving 2D Dispersion

et al. 2019

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Nuclear magnetic resonance (NMR) spectroscopy is a powerful tool for the non-targeted metabolomics of intact biofluids and even living organisms. However, spectral overlap can limit the information that can be obtained from 1D 1H NMR. For example, magnetic susceptibility broadening in living organisms prevents any metabolic information being extracted from solution-state 1D 1H NMR. Conversely, the additional spectral dispersion afforded by 2D 1H-13C NMR allows a wide range of metabolites to be assigned in-vivo in 13C enriched organisms, as well as a greater depth of information for biofluids in general. As such, 2D 1H-13C NMR is becoming more and more popular for routine metabolic screening of very complex samples. Despite this, there are only a very limited number of statistical software packages that can handle 2D NMR datasets for chemometric analysis. In comparison, a wide range of commercial and free tools are available for analysis of 1D NMR datasets. Overtime, it is likely more software solutions will evolve that can handle 2D NMR directly. In the meantime, this application note offers a simple alternative solution that converts 2D 1H-13C Heteronuclear Single Quantum Correlation (HSQC) data into a 1D “spikelet” format that preserves not only the 2D spectral information, but also the 2D dispersion. The approach allows 2D NMR data to be converted into a standard 1D Bruker format that can be read by software packages that can only handle 1D NMR data. This application note uses data from Daphnia magna (water fleas) in-vivo to demonstrate how to generate and interpret the converted 1D spikelet data from 2D datasets, including the code to perform the conversion on Bruker spectrometers.

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Reducing impacts of organism variability in metabolomics via time trajectory in vivo NMR

Cited by 22 publications

References 33 publications

Continuous in vivo Metabolism by NMR

Continuous in vivo Metabolism by NMR

Selective Amino Acid-Only in Vivo NMR: A Powerful Tool To Follow Stress Processes

1D “Spikelet” Projections from Heteronuclear 2D NMR Data—Permitting 1D Chemometrics While Preserving 2D Dispersion

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