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Plant roots play a dominant role in shaping the rhizosphere, the environment in which interaction with diverse microorganisms occurs. Tracking the dynamics of root–microbe interactions at high spatial resolution is currently limited because of methodological intricacy. Here, we describe a microfluidics-based approach enabling direct imaging of root–bacteria interactions in real time. The microfluidic device, which we termed tracking root interactions system (TRIS), consists of nine independent chambers that can be monitored in parallel. The principal assay reported here monitors behavior of fluorescently labeled Bacillus subtilis as it colonizes the root of Arabidopsis thaliana within the TRIS device. Our results show a distinct chemotactic behavior of B. subtilis toward a particular root segment, which we identify as the root elongation zone, followed by rapid colonization of that same segment over the first 6 h of root–bacteria interaction. Using dual inoculation experiments, we further show active exclusion of Escherichia coli cells from the root surface after B. subtilis colonization, suggesting a possible protection mechanism against root pathogens. Furthermore, we assembled a double-channel TRIS device that allows simultaneous tracking of two root systems in one chamber and performed real-time monitoring of bacterial preference between WT and mutant root genotypes. Thus, the TRIS microfluidics device provides unique insights into the microscale microbial ecology of the complex root microenvironment and is, therefore, likely to enhance the current rate of discoveries in this momentous field of research.

Microbial communities employ a variety of complex strategies to compete successfully against competitors sharing their niche, with antibiotic production being a common strategy of aggression. Here, by systematic evaluation of four non-ribosomal peptides/polyketide (NRPs/PKS) antibiotics produced by Bacillus subtilis clade, we revealed that they acted synergistically to effectively eliminate phylogenetically distinct competitors. The production of these antibiotics came with a fitness cost manifested in growth inhibition, rendering their synthesis uneconomical when growing in proximity to a phylogenetically close species, carrying resistance against the same antibiotics. To resolve this conflict and ease the fitness cost, antibiotic production was only induced by the presence of a peptidoglycan cue from a sensitive competitor, a response mediated by the global regulator of cellular competence, ComA. These results experimentally demonstrate a general ecological concept – closely related communities are favoured during competition, due to compatibility in attack and defence mechanisms. Microbial communities employ a variety of strategies to compete against competitors sharing their niche, for instance, by producing antibiotics. This study reveals that antibiotics produced by Bacillus subtilis act synergistically to eliminate phylogenetically distinct competitors and are regulated accordingly.

In tackling the obesity pandemic, considerable efforts are devoted to the development of effective weight reduction strategies, yet many dieting individuals fail to maintain a long-term weight reduction, and instead undergo excessive weight regain cycles. The mechanisms driving recurrent post-dieting obesity remain largely elusive. Here we identify an intestinal microbiome signature that persists after successful dieting of obese mice and contributes to faster weight regain and metabolic aberrations upon re-exposure to obesity-promoting conditions. Faecal transfer experiments show that the accelerated weight regain phenotype can be transmitted to germ-free mice. We develop a machine-learning algorithm that enables personalized microbiome-based prediction of the extent of post-dieting weight regain. Additionally, we find that the microbiome contributes to diminished post-dieting flavonoid levels and reduced energy expenditure, and demonstrate that flavonoid-based ‘post-biotic’ intervention ameliorates excessive secondary weight gain. Together, our data highlight a possible microbiome contribution to accelerated post-dieting weight regain, and suggest that microbiome-targeting approaches may help to diagnose and treat this common disorder. The identification of an intestinal microbiome signature that persists after successful dieting in obese mice and contributes to faster weight regain upon re-exposure to an obesity-promoting diet, and that transmits the altered weight regain phenotype to non-dieting mice. Understanding post-diet weight gain Many people who diet to lose weight find it impossible to maintain a long-term weight reduction, and instead undergo excessive weight regain cycles. The mechanisms driving this phenomenon remain elusive. Eran Elinav and colleagues identify an intestinal microbiome signature that persists after successful dieting in mice and contributes to exacerbated weight regain and metabolic alterations upon re-exposure to an obesity-promoting diet. The enhanced weight regain phenotype can be transmitted to non-dieting mice via faecal transfer. The authors also develop a machine-learning algorithm that allows personalized microbiome-based prediction of the extent of post-dieting weight regain.

Plant metabolic engineering is commonly used in the production of functional foods and quality trait improvement. However, to date, computational model-based approaches have only been scarcely used in this important endeavor, in marked contrast to their prominent success in microbial metabolic engineering. In this study we present a computational pipeline for the reconstruction of fully compartmentalized tissue-specific models of Arabidopsis thaliana on a genome scale. This reconstruction involves automatic extraction of known biochemical reactions in Arabidopsis for both primary and secondary metabolism, automatic gap-filling, and the implementation of methods for determining subcellular localization and tissue assignment of enzymes. The reconstructed tissue models are amenable for constraint-based modeling analysis, and significantly extend upon previous model reconstructions. A set of computational validations (i.e., cross-validation tests, simulations of known metabolic functionalities) and experimental validations (comparison with experimental metabolomics datasets under various compartments and tissues) strongly testify to the predictive ability of the models. The utility of the derived models was demonstrated in the prediction of measured fluxes in metabolically engineered seed strains and the design of genetic manipulations that are expected to increase vitamin E content, a significant nutrient for human health. Overall, the reconstructed tissue models are expected to lay down the foundations for computational-based rational design of plant metabolic engineering. The reconstructed compartmentalized Arabidopsis tissue models are MIRIAM-compliant and are available upon request.

Steroidal glycoalkaloids (SGAs) are cholesterol-derived molecules produced by solanaceous species. They contribute to pathogen defence but are toxic to humans and considered as anti-nutritional compounds. Here we show that GLYCOALKALOID METABOLISM 9 ( GAME9 ), an APETALA2/Ethylene Response Factor, related to regulators of alkaloid production in tobacco and Catharanthus roseus , controls SGA biosynthesis. GAME9 knockdown and overexpression in tomato and potato alters expression of SGAs and upstream mevalonate pathway genes including the cholesterol biosynthesis gene STEROL SIDE CHAIN REDUCTASE 2 ( SSR2 ). Levels of SGAs, C24-alkylsterols and the upstream mevalonate and cholesterol pathways intermediates are modified in these plants. Δ(7)-STEROL-C5(6)-DESATURASE (C5-SD) in the hitherto unresolved cholesterol pathway is a direct target of GAME9. Transactivation and promoter-binding assays show that GAME9 exerts its activity either directly or cooperatively with the SlMYC2 transcription factor as in the case of the C5-SD gene promoter. Our findings provide insight into the regulation of SGA biosynthesis and means for manipulating these metabolites in crops. Steroidal glycoalkaloids (SGAs) accumulate in solanaceous plants and contribute to plant defence but are toxic to humans. Here the authors show that the GAME9 transcription factor is a regulator of the SGA biosynthetic pathways providing a potential way to manipulate SGA levels in crops.

Annotation of metabolites is an essential, yet problematic, aspect of mass spectrometry (MS)-based metabolomics assays. The current repertoire of definitive annotations of metabolite spectra in public MS databases is limited and suffers from lack of chemical and taxonomic diversity. Furthermore, the heterogeneity of the data prevents the development of universally applicable metabolite annotation tools. Here we present a combined experimental and computational platform to advance this key issue in metabolomics. WEIZMASS is a unique reference metabolite spectral library developed from high-resolution MS data acquired from a structurally diverse set of 3,540 plant metabolites. We also present MatchWeiz, a multi-module strategy using a probabilistic approach to match library and experimental data. This strategy allows efficient and high-confidence identification of dozens of metabolites in model and exotic plants, including metabolites not previously reported in plants or found in few plant species to date. Unambiguous metabolite annotation is a critical, yet problematic step, in mass spectrometry based metabolomics. Here, Shahaf et al . present WEIZMASS, a platform consisting of a diverse spectral library of more than 3500 plant metabolites and software to aid their identification in biological samples.

Laboratory model systems enable controlled studies of marine microbial processes; however, the microbial complexity of the culture can influence the outcome. In this study, we employ a systematic approach to assess the impact of the bacterial ability to produce the antibiotic TDA in laboratory cultures with varying microbial complexities (from bacterial monocultures to bacterial co-cultures and algal-bacterial tri-cultures). Our findings demonstrate altered effects of the tdaB gene deletion with increasing microbial complexity, showing distinct impacts on microbial fitness. Since antibiotics like TDA mediate microbial interactions, it is important to examine them within ecologically relevant model systems that reflect inter- and intra-trophic interactions, including bacteria-bacteria and algae-bacteria relationships. Overall, our study highlights the importance of accounting for culture complexity when designing laboratory experiments to investigate microbial interactions and the compounds that mediate them.

Root exudates are thought to play an important role in plant-microbial interactions. In return for nutrition, soil bacteria can increase the bioavailability of soil nutrients. However, root exudates typically decrease in situations such as drought, calling into question the efficacy of solvation and bacteria-dependent mineral uptake in such stress. Here, we tested the hypothesis of exudate-driven microbial priming on Cupressus saplings grown in forest soil in custom-made rhizotron boxes. A 1-month imposed drought and concomitant inoculations with a mix of Bacillus subtilis and Pseudomonas stutzeri , bacteria species isolated from the forest soil, were applied using factorial design. Direct bacteria counts and visualization by confocal microscopy showed that both bacteria associated with Cupressus roots. Interestingly, root exudation rates increased 2.3-fold with bacteria under drought, as well as irrigation. Forty-four metabolites in exudates were significantly different in concentration between irrigated and drought trees, including phenolic acid compounds and quinate. When adding these metabolites as carbon and nitrogen sources to bacterial cultures of both bacterial species, eight of nine metabolites stimulated bacterial growth. Importantly, soil phosphorous bioavailability was maintained only in inoculated trees, mitigating drought-induced decrease in leaf phosphorus and iron. Our observations of increased root exudation rate when drought and inoculation regimes were combined support the idea of root recruitment of beneficial bacteria, especially under water stress. The soil surrounding the roots of trees, termed the rhizosphere, is full of bacteria and other communities of microorganisms. Trees secrete organic compounds in to the soil which are thought to influence the behavior of bacteria in the rhizosphere. Specifically, these root secretions, or ‘exudates’, attract and feed soil bacteria, which, in return, release nutrients that benefit the tree. In 2020, a group of researchers found that some trees in the Mediterranean forest produce more exudates during the long dry season. This suggests that the compounds secreted by roots may help trees to tolerate stress conditions, such as drought. To test this hypothesis, Oppenheimer-Shaanan et al. – including some of the researchers involved in the 2020 study – grew young Cupressus sempervirens conifer trees in drought conditions that starved them of the nutrients phosphorous and iron. Each tree was planted in a custom-built box which allowed easy access to roots growing in the soil. Two species of bacteria from the forest soil C. sempervirens trees naturally live in were then added to the soil in each box. Microscopy revealed that both species of bacteria, which had been tagged with fluorescent markers, were attracted to the roots of the trees, boosting the bacterial community in the rhizosphere. Oppenheimer-Shaanan et al. found that the recruitment of the two bacterial species caused the rate at which exudates were secreted from the roots to increase. Compounds in the exudate stimulated the bacteria to grow. Ultimately, levels of phosphorous and iron in the leaves of the starved trees increased when in the presence of these soil bacteria. This suggests that bacteria in the rhizosphere helps trees to survive when they are under stress and have low levels of water. These findings provide further evidence that plants and bacteria can live together in symbiosis and benefit one another. This could have important implications for forest ecology and potentially how trees are grown in orchards and gardens. For example, specific bacteria and organic compounds in the rhizosphere may be able to improve tree health. However, further work is needed to investigate whether the exudate compounds identified in this study are found more widely in nature.

The majority of mitochondrial proteins are encoded in the nuclear genome. Many of them lack clear targeting signals. Therefore, what constitutes the entire mitochondrial proteome is still unclear. We here build on our previously developed bi-genomic (BiG) split-GFP assay (Bader et al., 2020) to solidify the list of matrix and inner membrane mitochondrial proteins. The assay relies on one fragment (GFP 1-10 ) encoded in the mitochondrial DNA enabling specific visualization of only the proteins tagged with a smaller fragment, GFP 11 , and localized to the mitochondrial matrix or the inner membrane. We used the SWAp-Tag (SWAT) strategy to tag every protein with GFP 11 and mated them with the BiG GFP strain. Imaging the collection in six different conditions allowed us to visualize almost 400 mitochondrial proteins, 50 of which were never visualized in mitochondria before, and many are poorly studied dually localized proteins. We use structure-function analysis to characterize the dually localized protein Gpp1, revealing an upstream start codon that generates a mitochondrial targeting signal and explore its unique function. We also show how this data can be applied to study mitochondrial inner membrane protein topology and sorting. This work brings us closer to finalizing the mitochondrial proteome and the freely distributed library of GFP 11 -tagged strains will be a useful resource to study protein localization, biogenesis, and interactions.

Mass spectrometry imaging (MSI) is a mass spectrometry based molecular ion imaging technique. It provides the means for ascertaining the spatial distribution of a large variety of analytes directly on tissue sample surfaces without any labeling or staining agents. These advantages make it an attractive molecular histology tool in medical, pharmaceutical, and biological research. Likewise, MSI has started gaining popularity in plant sciences; yet, information regarding sample preparation methods for plant tissues is still limited. Sample preparation is a crucial step that is directly associated with the quality and authenticity of the imaging results, it therefore demands in-depth studies based on the characteristics of plant samples. In this review, a sample preparation pipeline is discussed in detail and illustrated through selected practical examples. In particular, special concerns regarding sample preparation for plant imaging are critically evaluated. Finally, the applications of MSI techniques in plants are reviewed according to different classes of plant metabolites.