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Related Concept Videos

Isotopes and Radioisotopes01:28

Isotopes and Radioisotopes

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In the early 1900s, English chemist Frederick Soddy realized that an element could have atoms with different masses that were chemically indistinguishable. These different types are called isotopes — atoms of the same element that differ in mass. Isotopes differ in mass because they have different numbers of neutrons but are chemically identical because they have the same number of protons. Soddy was awarded the Nobel Prize in Chemistry in 1921 for this discovery.
An isotope containing...
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Radioactivity and Nuclear Equations03:18

Radioactivity and Nuclear Equations

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Nuclear chemistry is the study of reactions that involve changes in nuclear structure. The nucleus of an atom is composed of protons and, except for hydrogen, neutrons. The number of protons in the nucleus is called the atomic number (Z) of the element, and the sum of the number of protons and the number of neutrons is the mass number (A). Atoms with the same atomic number but different mass numbers are isotopes of the same element.
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Atomic Fluorescence Spectroscopy01:29

Atomic Fluorescence Spectroscopy

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Atomic fluorescence spectroscopy (AFS) is an analytical technique that involves the electronic transitions of atoms in a flame, furnace, or plasma being excited by electromagnetic (EM) radiation. When these atoms absorb energy, they become excited and subsequently release energy as they return to their original state. This emitted light, or "fluorescence," is observed at a right angle to the incident beam. Both absorption and emission processes transpire at distinct wavelengths, which...
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Isotopes01:12

Isotopes

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Elements have a set number of protons that determines their atomic number (Z). For example, all atoms with eight protons are oxygen; however, the number of neutrons can vary for atoms of the same element. The sum of the number of protons and the number of neutrons is the mass number (A). Atoms with the same atomic number but different mass numbers are called isotopes. Elements can have multiple isotopes, for example, carbon-12, carbon-13, and carbon-14.
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Mass Spectrometry: Isotope Effect01:13

Mass Spectrometry: Isotope Effect

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Most elements exist in nature as a mixture of isotopes. The isotopes differ in weight due to their respective number of neutrons. The molecular weight of a molecule is different depending on the specific isotope of its elements involved. As a result, the mass spectrum of the molecule exhibits peaks from the same fragment at multiple positions. The positions of these mass signals depend on the difference between the molecular mass. Furthermore, the intensity of these signals is dependent on the...
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Workflow Based on the Combination of Isotopic Tracer Experiments to Investigate Microbial Metabolism of Multiple Nutrient Sources
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Stochastic simulation algorithm for isotope-based dynamic flux analysis.

Quentin Thommen1, Julien Hurbain2, Benjamin Pfeuty2

  • 1Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, UMR9020-U1277 - CANTHER - Cancer Heterogeneity Plasticity and Resistance to Therapies, F-59000, Lille, France.

Metabolic Engineering
|November 19, 2022
PubMed
Summary
This summary is machine-generated.

A new stochastic simulation algorithm (SSA) enables accurate metabolic flux analysis under non-stationary conditions. This method efficiently tracks isotopomer changes over time, overcoming limitations of traditional approaches for dynamic metabolic studies.

Keywords:
Flux balance analysisMetabolic flux analysisMetabolic network modelMetabolismStable-isotope tracersSystems biology

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Area of Science:

  • Biochemistry
  • Systems Biology
  • Metabolic Engineering

Background:

  • Carbon isotope labeling is crucial for metabolic flux analysis (MFA).
  • Existing MFA algorithms struggle with non-stationary metabolic conditions and high dimensionality.
  • There is a need for scalable and generalizable methods for dynamic metabolic studies.

Purpose of the Study:

  • To develop a novel stochastic simulation algorithm (SSA) for metabolic flux analysis.
  • To enable accurate flux quantification in non-stationary metabolic conditions.
  • To provide a computational approach whose time complexity is independent of the number of isotopomers.

Main Methods:

  • Derived a stochastic simulation algorithm (SSA) from the chemical master equation for isotope labeling systems.
  • Computed the time evolution of isotopomer concentrations under non-stationary conditions.
  • Benchmarked the SSA for 13C-Metabolic Flux Analysis (13C-MFA) in the pentose phosphate pathway and compared it with existing methods.

Main Results:

  • The SSA efficiently computes isotopomer concentrations over time without scaling with isotopomer number.
  • Demonstrated the algorithm's effectiveness for both forward and inverse problems in 13C-MFA.
  • Showcased the SSA's adaptability to complex metabolic networks, including central carbon metabolism.

Conclusions:

  • The SSA offers a powerful alternative to deterministic methods for metabolic flux analysis.
  • This approach is well-suited for comprehensive datasets and parallel labeling experiments.
  • Monte Carlo sampling can effectively address limitations related to sampling size in SSA.