Plant microbiota controls an alternative root branching regulatory mechanism in plants.

The establishment of beneficial interactions with microbes has helped plants to modulate root branching plasticity in response to environmental cues. However, how the plant microbiota harmonizes with plant roots to control their branching is unknown. Here, we show that the plant microbiota influences root branching in the model plant Arabidopsis thaliana. We define that the microbiota's ability to control some stages in root branching can be independent of the phytohormone auxin that directs lateral root development under axenic conditions. In addition, we revealed a microbiota-driven mechanism controlling lateral root development that requires the induction of ethylene response pathways. We show that the microbial effects on root branching can be relevant for plant responses to environmental stresses. Thus, we discovered a microbiota-driven regulatory pathway controlling root branching plasticity that could contribute to plant adaptation to different ecosystems.

A 1-aminocyclopropane-1-carboxylic-acid (ACC) dipeptide elicits ethylene responses through ACC-oxidase mediated substrate promiscuity.

Plants produce the volatile hormone ethylene to regulate many developmental processes and to deal with (a)biotic stressors. In seed plants, ethylene is synthesized from 1-aminocyclopropane-1-carboxylic acid (ACC) by the dedicated enzyme ACC oxidase (ACO). Ethylene biosynthesis is tightly regulated at the level of ACC through ACC synthesis, conjugation and transport. ACC is a non-proteinogenic amino acid, which also has signaling roles independent from ethylene. In this work, we investigated the biological function of an uncharacterized ACC dipeptide. The custom-synthesized di-ACC molecule can be taken up by Arabidopsis in a similar way as ACC, in part via Lysine Histidine Transporters (e.g., LHT1). Using Nano-Particle Assisted Laser Desoprtion/Ionization (Nano-PALDI) mass-spectrometry imaging, we revealed that externally fed di-ACC predominantly localizes to the vasculature tissue, despite it not being detectable in control hypocotyl segments. Once taken up, the ACC dimer can evoke a triple response phenotype in dark-grown seedlings, reminiscent of ethylene responses induced by ACC itself, albeit less efficiently compared to ACC. Di-ACC does not act via ACC-signaling, but operates via the known ethylene signaling pathway. In vitro ACO activity and molecular docking showed that di-ACC can be used as an alternative substrate by ACO to form ethylene. The promiscuous nature of ACO for the ACC dimer also explains the higher ethylene production rates observed in planta, although this reaction occurred less efficiently compared to ACC. Overall, the ACC dipeptide seems to be transported and converted into ethylene in a similar way as ACC, and is able to augment ethylene production levels and induce subsequent ethylene responses in Arabidopsis.

A transporter of 1-aminocyclopropane-1-carboxylic acid affects thallus growth and fertility in Marchantia polymorpha.

In seed plants, 1-aminocyclopropane-1-carboxylic acid (ACC) is the precursor of the plant hormone ethylene but also has ethylene-independent signaling roles. Nonseed plants produce ACC but do not efficiently convert it to ethylene. In Arabidopsis thaliana, ACC is transported by amino acid transporters, LYSINE HISTIDINE TRANSPORTER 1 (LHT1) and LHT2. In nonseed plants, LHT homologs have been uncharacterized. Here, we isolated an ACC-insensitive mutant (Mpain) that is defective in ACC uptake in the liverwort Marchantia polymorpha. Mpain contained a frameshift mutation (1 bp deletion) in the MpLHT1 coding sequence, and was complemented by expression of a wild-type MpLHT1 transgene. Additionally, ACC insensitivity was re-created in CRISPR/Cas9-Mplht1 knockout mutants. We found that MpLHT1 can also transport l-hydroxyproline and l-histidine. We examined the physiological functions of MpLHT1 in vegetative growth and reproduction based on mutant phenotypes. Mpain and Mplht1 plants were smaller and developed fewer gemmae cups compared to wild-type plants. Mplht1 mutants also had reduced fertility, and archegoniophores displayed early senescence. These findings reveal that MpLHT1 serves as an ACC and amino acid transporter in M. polymorpha and has diverse physiological functions. We propose that MpLHT1 contributes to homeostasis of ACC and other amino acids in M. polymorpha growth and reproduction.

Virtual monoenergetic micro-CT imaging in mice with artificial intelligence.

Micro cone-beam computed tomography (µCBCT) imaging is of utmost importance for carrying out extensive preclinical research in rodents. The imaging of animals is an essential step prior to preclinical precision irradiation, but also in the longitudinal assessment of treatment outcomes. However, imaging artifacts such as beam hardening will occur due to the low energetic nature of the X-ray imaging beam (i.e., 60 kVp). Beam hardening artifacts are especially difficult to resolve in a 'pancake' imaging geometry with stationary source and detector, where the animal is rotated around its sagittal axis, and the X-ray imaging beam crosses a wide range of thicknesses. In this study, a seven-layer U-Net based network architecture (vMonoCT) is adopted to predict virtual monoenergetic X-ray projections from polyenergetic X-ray projections. A Monte Carlo simulation model is developed to compose a training dataset of 1890 projection pairs. Here, a series of digital anthropomorphic mouse phantoms was derived from the reference DigiMouse phantom as simulation geometry. vMonoCT was trained on 1512 projection pairs (= 80%) and tested on 378 projection pairs (= 20%). The percentage error calculated for the test dataset was 1.7 ± 0.4%. Additionally, the vMonoCT model was evaluated on a retrospective projection dataset of five mice and one frozen cadaver. It was found that beam hardening artifacts were minimized after image reconstruction of the vMonoCT-corrected projections, and that anatomically incorrect gradient errors were corrected in the cranium up to 15%. Our results disclose the potential of Artificial Intelligence to enhance the µCBCT image quality in biomedical applications. vMonoCT is expected to contribute to the reproducibility of quantitative preclinical applications such as precision irradiations in X-ray cabinets, and to the evaluation of longitudinal imaging data in extensive preclinical studies.