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Record W3177372388 · doi:10.1093/plcell/koab147

Playing with Pyr: alternate sources of mitochondrial pyruvate fuel plant respiration

2021· letter· en· W3177372388 on OpenAlexaff
Brendan M. O’Leary

Bibliographic record

VenueThe Plant Cell · 2021
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsRespirationBiologyCellular respirationBiochemistryBotany

Abstract

fetched live from OpenAlex

One of the most distinctive features of plant metabolism is a high degree of flexibility at the pathway level. Consider the textbook example of glucose respiration by glycolysis, the TCA cycle, and the mitochondrial electron transport chain. In animals, if metabolic flow at any point through this standard pathway is disrupted, the organism will face major, often lethal, problems. By contrast, if you disrupt a particular enzyme along this pathway in plants, most of the time there will be no obvious effect. Plants still require the ability to respire glucose; they just usually have a viable metabolic detour. Metabolic flexibility likely represents a series of adaptations enabling plants to better survive diverse environmental stresses. The pattern of enhanced metabolic complexity holds true in the case of plant transporters (Lee and Millar, 2016). The obvious intracellular transporter needed for glucose respiration is a mitochondrial pyruvate transporter to import cytosolic pyruvate produced by glycolysis and fuel the mitochondrial TCA cycle. In mice, loss of the mitochondrial pyruvate carrier (MPC) is embryo lethal (Vanderperre et al., 2016). By contrast, as Le et al. (2021) demonstrate in this issue, disruption of Arabidopsis MPC1 leads to a complete loss of the MPC protein complex, but no obvious growth phenotype. To be sure, previous research has detected an enhanced cadmium sensitive phenotype for Atmpc1 (He et al., 2019); but under most circumstances, MPC deficient plant mitochondria apparently obtain sufficient pyruvate by another route (or two). To identify and qualify the contribution of these routes, Le et al. combined detailed metabolic labeling with genetic and pharmaceutical inhibition of target enzymes. When isolated mitochondria are fed with external 13C-labelled pyruvate, mpc1 mitochondria display negligible rates of pyruvate import. This means that another mitochondrial pyruvate transporter does not compensate for the loss of MPC; it must be something else. In plants, mitochondrial NAD malic enzyme (NAD-ME) interconverts malate and pyruvate and thus represents an internal source for mitochondrial pyruvate. When fed with external 13C-labelled malate, mpc1 mitochondria display increased production of 13C-labelled pyruvate. This means that mpc1 mitochondria display increased metabolic flux through NAD-ME, which may allow sufficient mitochondrial pyruvate production from imported malate. When the authors produced a triple mutant me1.me2.mpc1, which lacked both NAD-ME and MPC1 activity, they observed a moderately retarded growth phenotype compared with me1.me2 or mpc1. Isolated me1.me2.mpc1 mitochondria could neither uptake external pyruvate nor produce pyruvate internally from malate. This result was surprising because if the me1.me2.mpc1 mitochondria cannot acquire pyruvate, the plants should display a more severe growth phenotype owing to respiratory malfunction. Could there be a third way for plant mitochondria to obtain pyruvate in vivo? Diurnal metabolomic analysis revealed that me1.me2.mpc1 leaves produced few metabolite shifts compared to WT, which centered on increased alanine and 2-oxoglutarate levels. Both of these metabolites are products of a single reaction whereby pyruvate receives the nitrogen (amino) group of glutamate to become alanine. This reversible pyruvate:glutamate transamination is catalyzed by the enzyme alanine aminotransferase, which exists in both the mitochondria and cytosol and could allow alanine import to be a third source of mitochondrial pyruvate. Indeed, the authors found the growth of me1.me2.mpc1 seedlings were hypersensitive to cycloserine, an inhibitor of alanine aminotransferase (see Figure). Ultimately, it required the sequential disruption of three independent pyruvate transport mechanisms to observe the effect of mitochondrial pyruvate starvation in plants. Further metabolic flux studies will be required to understand how each pathway contributes to mitochondrial pyruvate supply under varying developmental and environmental circumstances. Genetic and pharmaceutical disruptions reveal three pathways of mitochondria pyruvate supply. mpc1 and especially me1.me.2.mpc1 seedlings show conditional growth phenotypes upon the inhibition of alanine aminotransferase by cycloserine treatment. Adapted fromLe et al. (2021) Figure 6. Genetic and pharmaceutical disruptions reveal three pathways of mitochondria pyruvate supply. mpc1 and especially me1.me.2.mpc1 seedlings show conditional growth phenotypes upon the inhibition of alanine aminotransferase by cycloserine treatment. Adapted fromLe et al. (2021) Figure 6.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0020.003
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0240.027
Insufficient payload (model declined to judge)0.0040.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.209
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations3
Published2021
Admission routes1
Has abstractno

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