Max Planck Institute of Molecular Plant Physiology

Molecular and physiological changes across crop developmental stages shape the plant phenome and render its prediction from genetic markers challenging. Here we present dynamicGP, an efficient computational approach that combines genomic prediction with dynamic mode decomposition to characterize the temporal changes and to predict genotype-specific dynamics for multiple morphometric, geometric and colourimetric traits scored by high-throughput phenotyping. Using genetic markers and data from high-throughput phenotyping of a maize multiparent advanced generation inter-cross population and an Arabidopsis thaliana diversity panel, we show that dynamicGP outperforms a baseline genomic prediction approach for the multiple traits. We demonstrate that the developmental dynamics of traits whose heritability varies less over time can be predicted with higher accuracy. The approach paves the way for interrogating and integrating the dynamical interactions between genotype and environment over plant development to improve the prediction accuracy of agronomically relevant traits.

Short-read RNA-seq studies of grafted plants have led to the proposal that thousands of messenger RNAs (mRNAs) move over long distances between plant tissues 1–7 , potentially acting as signals 8–12 . Transport of mRNAs between cells and tissues has been shown to play a role in several physiological and developmental processes in plants, such as tuberization ¹³ , leaf development ¹⁴ and meristem maintenance ¹⁵ ; yet for most mobile mRNAs, the biological relevance of transport remains to be determined 16–19 . Here we perform a meta-analysis of existing mobile mRNA datasets and examine the associated bioinformatic pipelines. Taking technological noise, biological variation, potential contamination and incomplete genome assemblies into account, we find that a high percentage of currently annotated graft-mobile transcripts are left without statistical support from available RNA-seq data. This meta-analysis challenges the findings of previous studies and current views on mRNA communication.

Metabolites acting as substrates and regulators of all biochemical reactions play an important role in maintaining the functionality of cellular metabolism. Despite advances in the constraint-based framework for genome-scale metabolic modeling, we lack reliable proxies for metabolite concentrations that can be efficiently determined and that allow us to investigate the relationship between metabolite concentrations in specific metabolic states in the absence of measurements. Here, we introduce a constraint-based approach, the flux-sum coupling analysis (FSCA), which facilitates the study of the interdependencies between metabolite concentrations by determining coupling relationships based on the flux-sum of metabolites. Application of FSCA on metabolic models of Escherichia coli, Saccharomyces cerevisiae, and Arabidopsis thaliana showed that the three coupling relationships are present in all models and pinpointed similarities in coupled metabolite pairs. Using the available concentration measurements of E. coli metabolites, we demonstrated that the coupling relationships identified by FSCA can capture the qualitative associations between metabolite concentrations and that flux-sum is a reliable proxy for metabolite concentration. Therefore, FSCA provides a novel tool for exploring and understanding the intricate interdependencies between the metabolite concentrations, advancing the understanding of metabolic regulation, and improving flux-centered systems biology approaches.

The direct reduction of CO2 into one-carbon molecules is key to highly efficient biological CO2-fixation. However, this strategy is currently restricted to anaerobic organisms and low redox potentials. In this study, we introduce the CORE cycle, a synthetic metabolic pathway that converts CO2 to formate at aerobic conditions and ambient CO2 levels, using only NADPH as a reductant. Combining theoretical pathway design and analysis, enzyme bioprospecting and high-throughput screening, modular assembly and adaptive laboratory evolution, we realize the CORE cycle in vivo and demonstrate that the cycle supports growth of E. coli by supplementing C1-metabolism and serine biosynthesis from CO2. We further analyze the theoretical potential of the CORE cycle as a new entry-point for carbon in photorespiration and autotrophy. Overall, our work expands the solution space for biological carbon reduction, offering a promising approach to enhance CO2 fixation processes such as photosynthesis, and opening avenues for synthetic autotrophy.

Alanine, an abundant non‐proteinogenic amino acid, acts as a precursor for coenzyme A and plays a role in various stress responses. However, a comprehensive understanding of its metabolism in plants remains incomplete. Previous metabolic genome‐wide association studies (mGWAS) identified ALANINE:GLYOXYLATE AMINOTRANSFERASE2 (AGT2 , AT4G39660) linked to β‐alanine levels in Arabidopsis under normal conditions. In this study, we aimed to deepen our insights into β‐alanine regulation by conducting mGWAS under two contrasting environmental conditions: control (12 h photoperiod, 21°C, 150 μmol m ⁻² sec ⁻¹ ) and stress (harvested after 1820 min at 32°C and darkness). We identified two highly significant quantitative trait loci (QTL) for β‐alanine, including the AGT2 locus associated in both environments and ALDEHYDE DEHYDROGENASE6B2 ( ALDH6B2 , AT2G14170) associated only under stress conditions. A coexpression‐correlation network revealed that the regulatory pathway involving β‐alanine levels, AGT2 , and ALDH6B2 connects the branched chained amino acid (BCAA) degradation through the propionate pathway. Metabolic profiles of AGT2 overexpression (OE) and knock‐out (KO) lines ( agt2 ) across various organs and developmental stages established the critical role of AGT2 in β‐alanine metabolism. This work underscores the importance of β‐alanine homeostasis for proper growth and development in Arabidopsis.

The green alga Chlamydomonas is an important and versatile model organism for research topics ranging from photosynthesis and metabolism, cilia, and basal bodies to cellular communication and the cellular cycle and is of significant interest for green bioengineering processes. The genome in this unicellular green alga is contained in 17 haploid chromosomes and codes for 16 883 protein coding genes. Functional genomics, as well as biotechnological applications, rely on the ability to remove, add, and change these genes in a controlled and efficient manner. In this review, the history of gene editing in Chlamydomonas is put in the context of the wider developments in genetics to demonstrate how many of the key developments to engineer these algae follow the global trends and the availability of technology. Building on this background, an overview of the state of the art in Chlamydomonas engineering is given, focusing primarily on the practical aspects while giving examples of recent applications. Commonly encountered Chlamydomonas ‐specific challenges, recent developments, and community resources are presented, and finally, a comprehensive discussion on the emergence and evolution of CRISPR/Cas‐based precision gene editing is given. An outline of possible future paths for gene editing based on current global trends in genetic engineering and tools for gene editing is presented.

Gene organization in operons and co-expression as polycistronic transcripts is characteristic of prokaryotes. With the evolution of the eukaryotic translation machinery, operon structure and expression of polycistrons were largely abandoned. Whether eukaryotes still possess the ability to express polycistrons, and how they functionally activate bacterial operons acquired by horizontal DNA transfer is unknown. Here, we demonstrate that a polycistron can be rapidly activated in yeast by induction of bicistronic expression under selection. We show that induced translation of the downstream cistron in a bicistronic transcript is based on a novel type of reinitiation mediated by the 80S ribosome and triggered by inefficient stop codon recognition, and that induced bicistronic expression is stable and independent of cis-elements. These results provide key insights into the epigenetic mechanism of the pathway of activation. We also developed a yeast strain that efficiently expresses bicistronic constructs, but does not carry any genomic DNA sequence change, and utilized this strain to synthesize a high-value metabolite from a bicistronic expression construct. Together, our results reveal the capacity of yeast to express bicistrons in a previously unrecognized pathway. While this capacity is normally hidden, it can be rapidly induced by selection to improve fitness.

Understanding crop responses to drought stress is crucial for securing future agricultural productivity. Guard cells regulate tran-spiration and thus the yield burden under drought conditions. Therefore, the influence of repeated drought stress on the guard cell metabolome of Zea mays L. was investigated to improve our understanding of crop resilience mechanisms. A controlled greenhouse experiment with physiological evaluation and a non-targeted metabolomics approach was used to analyse unprimed and primed guard cells. Primed and unprimed maize plants showed similar overall physiological and metabolic responses to drought, with gas exchange and general metabolic patterns largely unaffected by priming. However, distinct priming effects emerged in specific metabolites. Metabolites of the alanine and aspartate pathway, as well as those of the glycine, serine and threonine pathway were less impacted by drought stress in guard cells than in mesophyll cells, suggesting the emphasis of plants to maintain stable guard cell metabolomes for functional integrity. In contrast, the increase in sugar concentrations in guard cells was similar to that in mesophyll cells, suggesting a pivotal role of sugars in guard cells during drought conditions. New insights into cell type-specific metabolic responses to drought stress will contribute to a better understanding of stress memory in maize. Enhancing guard cell resilience could help optimise water use efficiency for sustainable agricultural production under climate change conditions.

Arbuscular mycorrhiza (AM) improves mineral nutrient supply, stress tolerance, and growth of host plants through re‐programing of plant physiology. We investigated the effect of AM on the root secondary metabolome of the model legume Lotus japonicus using untargeted metabolomics. Acetonitrile extracts of AM and control roots were analysed using ultra‐high‐performance liquid chromatography‐electrospray ionization‐ion mobility‐time‐of‐flight‐mass spectrometry (UPLC‐ESI‐IM‐ToF‐MS). We characterized AM‐regulated metabolites using co‐chromatography with authentic standards or isolation and structure identification from L. japonicus roots using preparative high‐performance liquid chromatography and nuclear magnetic resonance spectroscopy. Arbuscular mycorrhiza triggered major changes in the root metabolome, with most features representing unknown compounds. We identified three novel polyphenols: 5,7‐dihydroxy‐4′‐methoxycoumaronochromone (lotuschromone), 4‐hydroxy‐2‐(2′‐hydroxy‐4′‐methoxyphenyl)‐6‐methoxybenzofuran‐3‐carbaldehyde (lotusaldehyde), and 7‐hydroxy‐3,9‐dimethoxypterocarp‐6a‐ene (lotuscarpene). Further AM‐enhanced secondary metabolites included the previously known lupinalbin A and B, ayamenin D, biochanin A, vestitol, acacetin, coumestrol, and betulinic acid. Lupinalbin A, biochanin A, ayamenin D, liquiritigenin, isoliquiritigenin, lotuscarpene, medicarpin, daidzein, genistein, and 2′‐hydroxygenistein inhibited Rhizophagus irregularis spore germination upon direct application. Our results show that AM enhances the production of polyphenols in L. japonicus roots and highlights a treasure trove of numerous unknown plant secondary metabolites awaiting structural identification and functional characterization.

Tartary buckwheat (Fagopyrum tataricum) is esteemed as a medicinal crop due to its high nutritional and health value. However, the genetic basis for the variations in Tartary buckwheat grain ionome remains inadequately understood. Through genome‐wide association studies (GWAS) on grain ionome, 52 genetic loci are identified associated with 10 elements undergoing selection. Molecular experiments have shown that the variation in FtACA13’s promoter (an auto‐inhibited Ca²⁺‐ATPase) is accountable for grain sodium concentration and salt tolerance, which underwent selection during domestication. FtYPQ1 (a vacuolar amino acid transporter) exhibits zinc transport activity, enhancing tolerance to excessive zinc stress and raising zinc accumulation. Additionally, FtNHX2 (a Na⁺/H⁺ exchanger) positively regulates arsenic content. Further genomic comparative analysis of “20A1” (wild accession) and “Pinku” (cultivated accession) unveiled structural variants in key genes involved in ion uptake and transport that may result in considerable changes in their functions. This research establishes the initial comprehensive grain ionome atlas in Tartary buckwheat, which will significantly aid in genetic improvement for nutrient biofortification.

Plant metabolism is profoundly affected by various abiotic stresses. Consequently, plants must reconfigure their metabolic networks to sustain homeostasis while synthesizing compounds that mitigate stress. This aspect, with the current intensified climate impact results in more frequent abiotic stresses on a global scale. Advances in metabolomics and systems biology in the last decades have enabled both a comprehensive overview and a detailed analysis of key components involved in the plant metabolic response to abiotic stresses. This review addresses metabolic responses to altered atmospheric CO2 and O3, water deficit, temperature extremes, light intensity fluctuations including the importance of UV-B, ionic imbalance, and oxidative stress predicted to be caused by climate change, long-term shifts in temperatures and weather patterns. It also assesses both the commonalities and specificities of metabolic responses to diverse abiotic stresses, drawing on data from the literature. Classical stress-related metabolites such as proline, and polyamines are revisited, with an emphasis on the critical role of branched-chain amino acid metabolism under stress conditions. Finally, where possible, mechanistic insights into the regulation of metabolic processes and further outlook on combinatory stresses are discussed.

Background Identifying transcriptional cis-regulatory elements (CREs) and understanding their role in gene expression are essential for the precise manipulation of gene expression and associated phenotypes. This knowledge is fundamental for advancing genetic engineering and improving crop traits. Results We here demonstrate that CREs can be accurately predicted and utilized to precisely regulate gene expression beyond the range of natural variation. We firstly build two sequence-to-expression deep learning models to respectively identify distal and proximal CREs by combining them with interpretability methods in multiple crops. A large number of distal CREs are verified for enhancer activity in vitro using UMI-STARR-seq on 12,000 synthesized sequences. These comprehensively characterized CREs and their precisely predicted effects further contribute to the design of in silico editing schemes for precise engineering of gene expression. We introduce a novel concept of “editingplasticity” to evaluate the potential of promoter editing to alter expression of each gene. As a proof of concept, both exhaustive prediction and random knockout mutants are analyzed within the promoter region of ZmVTE4, a key gene affecting α-tocopherol content in maize. A high degree of agreement between predicted and observed expression is observed, extending the range of natural variation and thereby allowing the creation of an optimal phenotype. Conclusions Our study provides a robust computational framework that advances knowledge-guided gene editing for precise regulation of gene expression and crop improvement. By reliably predicting and validating CREs, we offer a tool for targeted genetic modifications, enhancing desirable traits in crops.

Background Biotechnological applications are steadily growing and have become an important tool to reinvent the synthesis of chemicals and pharmaceuticals for lower dependence on fossil resources. In order to sustain this progression, new feedstocks for biotechnological hosts have to be explored. One-carbon (C1-)compounds, including formate, derived from CO2 or organic waste are accessible in large quantities with renewable energy, making them promising candidates. Previous studies showed that introducing the formate assimilation machinery from Methylorubrum extorquens into Escherichia coli allows assimilation of formate through the C1-tetrahydrofolate (C1-H4F) metabolism. Applying this route for formate assimilation, we here investigated utilisation of formate for the synthesis of value-added building blocks in E. coli using S-adenosylmethionine (SAM)-dependent methyltransferases (MT). Results We first used a two-vector system to link formate assimilation and SAM-dependent methylation with three different MTs in E. coli BL21. By feeding isotopically labelled formate, methylated products with 51–81% ¹³C-labelling could be obtained without substantial changes in conversion rates. Focussing on improvement of product formation with one MT, we analysed the engineered C1-auxotrophic E. coli strain C1S. Screening of different formate concentrations allowed doubling of the conversion rate in comparison to the not formate-supplemented BL21 strain with a share of more than 70% formate-derived methyl groups. Conclusions Within this study transformation of formate into methyl groups is demonstrated in E. coli. Our findings support that feeding formate can improve the availability of usable C1-compounds and, as a result, increase whole-cell methylation with engineered E. coli. Using this as a starting point, the introduction of additional auxiliary enzymes and ideas to make the system more energy-efficient are discussed for future applications. Graphical abstract

Plant acclimation occurs through system-wide mechanisms that include proteome shifts, some of which occur at the level of protein synthesis. All proteins are synthesized by ribosomes. Rather than being monolithic, transcript-to-protein translation machines, ribosomes can be selective and cause proteome shifts. In this study, we use apical root meristems of germinating seedlings of the monocotyledonous plant barley as a model to examine changes in protein abundance and synthesis during cold acclimation. We measured metabolic and physiological parameters that allowed us to compare protein synthesis in the cold to optimal rearing temperatures. We demonstrated that the synthesis and assembly of ribosomal proteins are independent processes in root proliferative tissue. We report the synthesis and accumulation of various macromolecular complexes and propose how ribosome compositional shifts may be associated with functional proteome changes that are part of successful cold acclimation. Our study indicates that translation initiation is limiting during cold acclimation while the ribosome population is remodelled. The distribution of the triggered ribosomal protein heterogeneity suggests that altered compositions may confer 60S subunits selective association capabilities towards translation initiation complexes. To what extent selective translation depends on heterogeneous ribo-proteome compositions in barley proliferative root tissue remains a yet unresolved question. This article is part of the discussion meeting issue ‘Ribosome diversity and its impact on protein synthesis, development and disease’.

The glycocalyx, a highly heterogeneous glycoprotein layer of cilia regulates adhesion and force transduction and is involved in signaling. The high‐resolution molecular architecture of this layer is currently not understood. The structure of the ciliary coat is described in the green alga Chlamydomonas reinhardtii by cryo‐electron tomography and proteomic approaches and the high‐resolution cryoEM structure of the main component, FMG1B is solved. FMG1B is described as a mucin orthologue which lacks the major O‐glycosylation of mammalian mucins but is N‐glycosylated. FMG1A, a previously undescribed isoform of FMG1B is expressed in C. reinhardtii. By microflow‐based adhesion assays, increased surface adhesion in the glycocalyx deficient double‐mutant fmg1b‐fmg1a is observed. It is found this mutant is capable of surface‐gliding, with neither isoform required for extracellular force transduction by intraflagellar transport. The results find FMG1 to form a protective layer with adhesion‐regulative instead of adhesion‐conferring properties and an example of an undescribed class of mucins.

Photorespiration is an essential metabolic repair process in oxygenic photosynthesis, as it detoxifies Rubisco's inhibitory oxygenase byproduct, 2-phosphoglycolate (2-PG). It has been demonstrated that improving endogenous photorespiration in C3 plants through enzyme overexpression can enhance photosynthesis and promote plant growth. However, the potential impact of improved photorespiration in leaves on heterotrophic roots remained unexplored. To address this, we conducted a metabolome analysis of Arabidopsis leaves and roots using transgenic lines with enhanced glycine decarboxylase (GDC) activity, achieved by overexpressing the mitochondrial lipoamide dehydrogenase (mtLPD1) subunit. In the leaves, mtLPD1 overexpression primarily resulted in reduced steady-state levels of intermediates associated with photorespiration, the tricarboxylic acid (TCA) cycle, and soluble sugars, while intermediates related to nitrogen metabolism were elevated. In roots, where mtLPD1 expression was unchanged, we observed contrasting accumulation patterns in the transgenic lines compared to the wildtype, including increased levels of photorespiratory and TCA-cycle intermediates. Notably, we also detected elevated amounts of soluble sugars, nitrate, and starch. Phloem exudate analysis revealed altered metabolite profiles in the overexpressors, particularly with respect to photorespiratory intermediates linked to the GDC reaction, as well as soluble sugars and metabolites involved in cellular redox homeostasis. This suggested an increased transport of these metabolites from shoots to roots, thereby altering sink organ metabolism. In summary, we hypothesize that optimizing photorespiration enhances photosynthesis, which leads to an increased export of carbon surplus to heterotrophic tissues. Thus, improving photorespiration may hold potential for increasing yields in beet- and tuber-forming plants.

Auxotrophic metabolic sensors (AMS) are microbial strains modified so that biomass formation correlates with the availability of specific metabolites. These sensors are essential for bioengineering (e.g., in growth-coupled designs) but creating them is often a time-consuming and low-throughput process that can be streamlined by in silico analysis. Here, we present a systematic workflow for designing, implementing, and testing versatile AMS based on Escherichia coli. Glyoxylate, a key metabolite in (synthetic) CO2 fixation and carbon-conserving pathways, served as the test analyte. Through iterative screening of a compact metabolic model, we identify non-trivial growth-coupled designs that result in six AMS with a wide sensitivity range for glyoxylate, spanning three orders of magnitude in the detected analyte concentration. We further adapt these E. coli AMS for sensing glycolate and demonstrate their utility in both pathway engineering (testing a key metabolic module for carbon assimilation via glyoxylate) and environmental monitoring (quantifying glycolate produced by photosynthetic microalgae). Adapting this workflow to the sensing of different metabolites could facilitate the design and implementation of AMS for diverse biotechnological applications.