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Mapping multi-substrate specificity of Arabidopsis aminotransferases

Nature Plants volume 11, pages 1863–1876 (2025)Cite this article

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Abstract

Nitrogen is an essential element in all organisms, and its availability and use efficiency directly impact organismal growth and performance, especially in plants. Aminotransferases are core enzymes of the nitrogen metabolic network for synthesizing various organonitrogen compounds. Although each aminotransferase can potentially catalyse hundreds of transamination reactions with different combinations of amino and keto acid substrates, the full functionality of many aminotransferases remains elusive. Here we employed high-throughput gene synthesis and enzyme assay platforms to determine the substrate specificities of 38 aminotransferases of Arabidopsis thaliana and unveiled many previously unrecognized activities among a total of 4,104 reactions tested. The integration of these biochemical data in an enzyme-constrained metabolic model of Arabidopsis and in silico simulation further revealed that the promiscuity of aminotransferases may alter nitrogen distribution profiles and contribute to the robustness of the nitrogen metabolic network. This study provides foundational knowledge for deciphering the plant nitrogen metabolic network and improving nitrogen use efficiency in crops.

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Fig. 1: Characterization of the Arabidopsis AT enzyme family.
Fig. 2: Mapping the substrate specificity of AT family enzymes identified previously unrecognized activities of many AT enzymes of Arabidopsis.
Fig. 3: Multiple AT enzymes, including AspAT3 and BCAT4, have Aro AT activity.
Fig. 4: ALD1 and VAS1 have broad substrate specificity.
Fig. 5: Distantly related AGD2 and WIN1 from class I and II ATs, respectively, can catalyse AAD-AT activity involved in Lys degradation.
Fig. 6: The presence and absence of mitochondrial Ala:hydroxypyruvate AT activity altered 15N enrichment of several amino acids.

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Data availability

The unique identifiers of all AT enzymes, along with publicly available datasets, are provided in the figures and Extended Data. The AT genes inserted into the pEU vector are available to the community via GitHub at https://nfluxmap.github.io/resources/.

Code availability

The code used for the in silico enrichment, knockouts and optimal growth analyses is available via GitHub at https://github.com/sebahu/AraCore_AT_enhancement.

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Acknowledgements

This work was supported by the US Department of Energy (DOE), Office of Science, Office of Biological and Environmental Research, Genomic Science Program grant no. DE-SC0020390 to T.E.T., Z.N. and H.A.M.; the Joint Genome Institute award no. CSP-503757 to T.E.T. and H.A.M.; and the US NSF PGRP award no. IOS-2312181 to S.Y.R. and H.A.M. S. Hataya was supported by Hokkaido University–Hitachi Joint Cooperative Support Program for Education and Research. Z.N. and S. Huß acknowledge support from the German Research Foundation, project numbers NI 1472/13-1 and Collaborative Research Center 1644. We thank S. Friedrich from the UW Botany Media Studio for making final adjustments to the main figures. The AT gene synthesis was carried out as a part of the CSP-503757 project by Y. Yoshikuni, J.-F. Cheng, M. Harmon-Smith, S. Nath and A. Tarver at the DOE Joint Genome Institute, a DOE Office of Science User Facility, which is supported by the DOE Office of Science operated under contract no. DE-AC02-05CH11231.

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Authors and Affiliations

  1. Department of Botany, University of Wisconsin–Madison, Madison, WI, USA

    Kaan Koper, Marcos V. V. de Oliveira & Hiroshi A. Maeda

  2. Bioinformatics Department, Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Germany

    Sebastian Huß, Fayaz Soleymani & Zoran Nikoloski

  3. Systems Biology and Mathematical Modelling Group, Max Planck Institute of Molecular Plant Physiology, Potsdam, Germany

    Sebastian Huß, Fayaz Soleymani & Zoran Nikoloski

  4. Research Faculty of Agriculture, Hokkaido University, Sapporo, Japan

    Shogo Hataya & Taichi E. Takasuka

  5. Plant Resilience Institute, Michigan State University, East Lansing, MI, USA

    Charles Hawkins & Seung Y. Rhee

  6. Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, USA

    Charles Hawkins & Seung Y. Rhee

  7. Department of Plant Biology, Michigan State University, East Lansing, MI, USA

    Seung Y. Rhee

  8. Department of Plant, Soil, and Microbial Sciences, Michigan State University, East Lansing, MI, USA

    Seung Y. Rhee

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  1. Kaan Koper
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Contributions

H.A.M., T.E.T. and Z.N. conceptualized the project. K.K., M.V.V.O., S. Hataya, S. Huß and F.S. conducted the investigation. M.V.V.O., H.A.M., K.K., S. Hataya, S. Huß, F.S. and C.H. analysed the data. M.V.V.O., K.K., H.A.M., S. Huß and S. Hataya visualized the data. H.A.M., Z.N. and S.Y.R. were responsible for project administration. H.A.M., K.K. and S. Huß wrote the original draft of the paper. H.A.M., K.K., S. Huß, Z.N., M.V.V.O., S. Hataya, T.E.T., C.H. and S.Y.R. reviewed and edited the paper.

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Correspondence to Hiroshi A. Maeda.

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Extended data

Extended Data Table 1 Enzyme kinetic data
Full size table
Extended Data Table 2 AT reactions incorporated into the eAraCore model
Full size table

Extended Data Fig. 1 Reciprocal activities were largely detected, with a few exceptions reflecting preferred reaction directions.

Consistent with the reversibility of AT reactions, most enzymes showed similar activities for both forward and reverse reactions, when analyzed. A few exceptions include: AspAT2 and 3 preferred forward reactions to produce Phe as compared to the transamination of Phe into phenylpyruvate. AlaAT1 and 2 preferred forward reaction to produce Ala using Glu amino donor, as compared to the transamination of Ala to pyruvate.

Extended Data Fig. 2 Independent testing of Trp AT activity, in reverse direction, for Arabidopsis AT enzymes.

The average Trp AT activity (right panel), in % conversion of indole-3-pyruvate (IPA) to Trp using one of seven amino donors tested (Fig. 2a), was compared with the Trp AT activity assays in the reverse direction (left panel, Trp to IPA conversion) using an independent method. Thirty-three AT enzymes were individually incubated with the Trp substrate (5 mM) and the mixture of three keto acid substrates, α-ketoglutarate, pyruvate, 4MTOB (1 mM each) for one hour, and the production of IPA was monitored after the reaction with the Salkowski reagent, which provides a distinct absorption at 530 nm. Data are means ± s.e.m. (n = 3 independent reactions). Individual data points are shown. Background values detected from the reactions with empty vector control were subtracted. A red arrow denotes the lack of Trp AT activity in TAA1 in the AT mapping data due to the substrate inhibition by IPA (Sato et al., 2022).

Extended Data Fig. 3 AT substrate screening of TAA1 in the presence and absence of indole-3-pyruvate (IPA).

(a) The initial substrate screening of TAA1 rarely detected any AT activity. (b) The subsequent AT screening by omitting the IPA keto acid substrate, which was previously reported as a potent inhibitor of TAA1 (Sato et al., 2022), resulted in detection of AT activity with multiple substrate combinations. Thus, this result is represented in Fig. 2a.

Extended Data Fig. 4 Enzyme activities and expression profiles of AT enzymes that can mediate glycine formation.

(a) Validating glycine formation from glyoxylate using glutamate (Glu) or alanine (Ala) amino donor in multiple Arabidopsis AT enzymes. Enzyme assays were carried out for Glu:glyoxylate and Ala:glyoxylate AT activities at non-saturated reaction conditions for AlaAT1, AlaAT2, PSAT1, PSAT2, AGT3, and WIN1, along with GGAT1 as a positive control, which was previously reported to have both of these activities. The individual enzyme was incubated with the glyoxylate keto acid substrate (1 mM), PLP (25 µM) and Glu or Ala amino donor (4 mM) for 5 min at indicated enzyme concentrations (n = 1 at multiple enzyme concentrations). GGAT1 having the strongest activities showed linear increase in the product formation only at the lower enzyme concentrations. (b) Cell-type specific expression profiles of GGAT1, GGAT2, AlaAT1, and AlaAT2. The expression profiles of GGAT1 (AT1G23310), GGAT2 (AT1G70580), AlaAT1 (AT1G17290), and AlaAT2 (AT1G72330) that exhibited strong GGAT activity (Fig. 2a) were evaluated using publicly available single-cell expression data of Arabidopsis thaliana (https://www.psb.ugent.be/sc-leaf-yieldlab/). The analysis showed that peroxisomal GGAT1 is most strongly expressed in mesophyll cells. While GGAT2 and AlaAT2 appear to have very low expression, mitochondrial AlaAT1 appears to be expressed preferentially in the vasculature (for example, xylem and phloem parenchyma cells).

Extended Data Fig. 5 Gain- and loss-of-function lines of VAS1 in Arabidopsis.

(a) The gain-of-function lines were generated by overexpressing the genomic sequence of VAS1/ISS1 (At1g80360) under the constitutive Cauliflower Mosaic Virus (CaMV) 35S promoter and screening positive transformants using the seed-specific expression of the red fluorescence protein (RFP). (b) Four independent homozygous vas1 knockout (ko) lines were generated by CRISPR-Cas9 and sgRNAs targeting the first and eight exons. The line ko-42, 46 and 49 had the majority of the 1,908 bp coding region deleted as indicated by red scissors, while the line ko-62 had the entire coding region plus additional neighboring sequences deleted. (c) qPCR analyses showed that all three VAS1 overexpression (OX) lines showed elevated VAS1 transcript levels, which were nearly undetectable in four ko lines. Data are means ± s.e.m. (n = 3 independent biological samples). Individual data points are shown. (d) Representative plant phenotypes of three independent VAS1-OX and four vas1-ko lines grown at 12 hr light/12 hr dark condition for 4 weeks after germination. Similar phenotypes were observed in ten plants for each independent line.

Extended Data Fig. 6 Metabolite profiling of amino acids in VAS1 overexpression (VAS1-OX) and CRISPR knockout (vas1-ko) lines.

A fully expanded mature leaf was harvested (a) before bolting, 5 weeks after germination and (b) after bolting, 7 weeks after germination. Box plots represent the distribution of individual data points, where the center line marks the median (50th percentile), box edges indicate the 25th and 75th percentiles, and whiskers extend from minimum to maximum values (n = 9 of independent biological samples, except Gln, His, Arg, Lys being n = 5 for wild-type and line 40 and n = 6 for lines 42, 44, 46, 47, 49, and 62. α-Tocopherol after bolting is n = 8 for wild-type and line 40 and n = 9 for lines 42, 44, 46, 47, 49, 62). Asterisks denote statistically significant changes relative to the Wt control according to one-way ANOVA followed by multiple comparison, two-sided Holm-Sidak test, *p < 0.05, **p < 0.01). All individual points and significant p values are shown.

Extended Data Fig. 7 The validation of AAD-AT activity detected in AGD2 and WIN1.

(a) AGD2 and WIN1 showed AAD AT activity in addition to previously reported DAP AT and AcOrn AT activity, respectively, whereas ALD1 showed very little AAD AT activity. Each enzyme at the indicated concentration was incubated with various amino donors (5 mM) with αKG as the keto acceptor (5 mM) for 5 min (n = 1 at multiple enzyme concentration). (b) Keto acceptor (left) and amino donor (right) preference was determined by incubating AGD2, WIN1, or ALD1 with the indicated substrate combinations at 1 mM of each keto acceptor and 4 mM of each amino donor for 5 min (n = 1 for each reaction).

Extended Data Fig. 8 No association of observed enzymatic activities to activities predicted by recent deep learning models for catalytic rates.

(a) The catalytic rates predicted by TurNuP49 for the donor-receptor combinations explored in the experiments have a Spearman correlation value of -0.023 with the observed activities. (b) The catalytic rates predicted by UniKP51 for the individual donors and receptors have a Spearman correlation value of -0.032 with the observed activities.

Supplementary information

Reporting Summary

Supplementary Data 1

The list of known and predicted AT genes from A. thaliana.

Supplementary Data 2

AT reactions that are deposited to PMN16.

Supplementary Data 3

Per cent conversion rates of the LC–MS screening shown in Fig. 2a.

Supplementary Data 4

Protein MS analysis of the BCAT4 enzyme preparation.

Supplementary Data 5

The AT mapping data matched with predicted kcat values.

Supplementary Table 1

Primers and nucleotides used in this study.

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Koper, K., de Oliveira, M.V.V., Huß, S. et al. Mapping multi-substrate specificity of Arabidopsis aminotransferases. Nat. Plants 11, 1863–1876 (2025). https://doi.org/10.1038/s41477-025-02095-6

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