Two independent loss-of-function mutations in anthocyanidin synthase homeologous genes are responsible for the all-green phenotype of sweet basil.

Sweet basil, Ocimum basilicum L., is an important culinary herb grown worldwide. Although basil is green, many landraces, breeding lines, and exotic cultivars have purple stems and flowers. This anthocyanin pigmentation is unacceptable in traditional Italian basil used for Pesto sauce production. In the current study, we aimed to resolve the genetics that underlines the different colors. We used the recently published sweet basil genome to map quantitative trait loci (QTL) for flower and stem color in a bi-parental F2 population. It was found that the pigmentation is governed by a single QTL, harboring an anthocyanidin synthase (ANS) gene (EC 1.14.20.4). Further analysis revealed that the basil genome harbors two homeologous ANS genes, each carrying a loss-of-function mutation. ObANS1 carries a single base pair insertion resulting in a frameshift, and ObANS2 carries a missense mutation within the active site. In the purple-flower parent, ANS1 is functional, and ANS2 carries a nonsense mutation. The functionality of the ObANS1 active allele was validated by complementation assay in an Arabidopsis ANS mutant. Moreover, we have restored the functionality of the missense-mutated ObANS2 using site-directed activation. We found that the non-functional alleles were expressed to similar levels as the functional allele, suggesting polyploids invest futile effort in expressing non-functional genes, offsetting their advantageous redundancy. This work demonstrated the usefulness of the genomics and genetics of basil to understand the basic mechanism of metabolic traits and raise fundamental questions in polyploid plant biology.

A framework for the targeted recruitment of crop-beneficial soil taxa based on network analysis of metagenomics data.

BACKGROUND: The design of ecologically sustainable and plant-beneficial soil systems is a key goal in actively manipulating root-associated microbiomes. Community engineering efforts commonly seek to harness the potential of the indigenous microbiome through substrate-mediated recruitment of beneficial members. In most sustainable practices, microbial recruitment mechanisms rely on the application of complex organic mixtures where the resources/metabolites that act as direct stimulants of beneficial groups are not characterized. Outcomes of such indirect amendments are unpredictable regarding engineering the microbiome and achieving a plant-beneficial environment. RESULTS: This study applied network analysis of metagenomics data to explore amendment-derived transformations in the soil microbiome, which lead to the suppression of pathogens affecting apple root systems. Shotgun metagenomic analysis was conducted with data from 'sick' vs 'healthy/recovered' rhizosphere soil microbiomes. The data was then converted into community-level metabolic networks. Simulations examined the functional contribution of treatment-associated taxonomic groups and linked them with specific amendment-induced metabolites. This analysis enabled the selection of specific metabolites that were predicted to amplify or diminish the abundance of targeted microbes functional in the healthy soil system. Many of these predictions were corroborated by experimental evidence from the literature. The potential of two of these metabolites (dopamine and vitamin B12) to either stimulate or suppress targeted microbial groups was evaluated in a follow-up set of soil microcosm experiments. The results corroborated the stimulant's potential (but not the suppressor) to act as a modulator of plant beneficial bacteria, paving the way for future development of knowledge-based (rather than trial and error) metabolic-defined amendments. Our pipeline for generating predictions for the selective targeting of microbial groups based on processing assembled and annotated metagenomics data is available at https://github.com/ot483/NetCom2 . CONCLUSIONS: This research demonstrates how genomic-based algorithms can be used to formulate testable hypotheses for strategically engineering the rhizosphere microbiome by identifying specific compounds, which may act as selective modulators of microbial communities. Applying this framework to reduce unpredictable elements in amendment-based solutions promotes the development of ecologically-sound methods for re-establishing a functional microbiome in agro and other ecosystems. Video Abstract.

Genome-based high-resolution mapping of fusarium wilt resistance in sweet basil.

Fusarium wilt of basil is a disease of sweet basil (Ocimum basilicum L.) plants caused by the fungus Fusarium oxysporum f. sp. basilici (FOB). Although resistant cultivars were released > 20 years ago, the underlying mechanism and the genes controlling the resistance remain unknown. We used genetic mapping to elucidate FOB resistance in an F2 population derived from a cross between resistant and susceptible cultivars. We performed genotyping by sequencing of 173 offspring and aligning the data to the sweet basil reference genome. In total, 23,411 polymorphic sites were detected, and a single quantitative trait locus (QTL) for FOB resistance was found. The confidence interval was < 600 kbp, harboring only 60 genes, including a cluster of putative disease-resistance genes. Based on homology to a fusarium resistance protein from wild tomato, we also investigated a candidate resistance gene that encodes a transmembrane leucine-rich repeat - receptor-like kinase - ubiquitin-like protease (LRR-RLK-ULP). Sequence analysis of that gene in the susceptible parent vs. the resistant parent revealed multiple indels, including an insertion of 20 amino acids next to the transmembrane domain, which might alter its functionality. Our findings suggest that this LRR-RLK-ULP might be responsible for FOB resistance in sweet basil and demonstrate the usefulness of the recently sequenced basil genome for QTL mapping and gene mining.

The Pomegranate Deciduous Trait Is Genetically Controlled by a PgPolyQ-MADS Gene.

The pomegranate (Punica granatum L.) is a deciduous fruit tree that grows worldwide. However, there are variants, which stay green in mild winter conditions and are determined evergreen. The evergreen trait is of commercial and scientific importance as it extends the period of fruit production and provides opportunity to identify genetic functions that are involved in sensing environmental cues. Several different evergreen pomegranate accessions from different genetic sources grow in the Israeli pomegranate collection. The leaves of deciduous pomegranates begin to lose chlorophyll during mid of September, while evergreen accessions continue to generate new buds. When winter temperature decreases 10°C, evergreen variants cease growing, but as soon as temperatures arise budding starts, weeks before the response of the deciduous varieties. In order to understand the genetic components that control the evergreen/deciduous phenotype, several segregating populations were constructed, and high-resolution genetic maps were assembled. Analysis of three segregating populations showed that the evergreen/deciduous trait in pomegranate is controlled by one major gene that mapped to linkage group 3. Fine mapping with advanced F3 and F4 populations and data from the pomegranate genome sequences revealed that a gene encoding for a putative and unique MADS transcription factor (PgPolyQ-MADS) is responsible for the evergreen trait. Ectopic expression of PgPolyQ-MADS in Arabidopsis generated small plants and early flowering. The deduced protein of PgPolyQ-MADS includes eight glutamines (polyQ) at the N-terminus. Three-dimensional protein model suggests that the polyQ domain structure might be involved in DNA binding of PgMADS. Interestingly, all the evergreen pomegranate varieties contain a mutation within the polyQ that cause a stop codon at the N terminal. The polyQ domain of PgPolyQ-MADS resembles that of the ELF3 prion-like domain recently reported to act as a thermo-sensor in Arabidopsis, suggesting that similar function could be attributed to PgPolyQ-MADS protein in control of dormancy. The study of the evergreen trait broadens our understanding of the molecular mechanism related to response to environmental cues. This enables the development of new cultivars that are better adapted to a wide range of climatic conditions.

The Meat Quality Characteristics of Holstein Calves: The Story of Israeli 'Dairy Beef'.

Global animal production systems are often criticized for their lack of sustainability and insufficient resilience to ensure food security. The 'farm-to-fork' approach aims at orienting food systems towards the creation of a positive environmental impact, nutritious, healthy, safe and sufficient foods, and fairer economic returns for primary producers. Many countries rely on an imported supply of live animals to fulfill their needs for fresh meat. In Israel, ~60% of the sources of fresh beef come from the import of live animals. In order to encourage sustainable beef production in Israel, the proportion of local beef should be raised at the expense of imported animals. However, for this to be achieved, the superior performance of local beef should be justified. The current study was conducted to compare between the meat quality characteristics of local (Israeli Holstein; N = 205) vs. imported (Australian; N = 169) animals. Generally, while the imported calves presented a higher dressing percentage (p < 0.0001), the local animals were characterized by tenderer meat (p < 0.0001), longer sarcomeres (p < 0.0001), higher a* color attributes and pH (p < 0.001), superior cooking (p = 0.002) and thawing loss (p < 0.0001), higher intra-muscular fat (IMF) content, and a higher PUFA proportion (p < 0.01 and p < 0.0001, respectively) and PUFA:SFA ratio. The findings shown herein may provide sound arguments for stakeholders and policy makers to facilitate sustainable local beef production in Israel.

NetCom: A Network-Based Tool for Predicting Metabolic Activities of Microbial Communities Based on Interpretation of Metagenomics Data.

The study of microbial activity can be viewed as a triangle with three sides: environment (dominant resources in a specific habitat), community (species dictating a repertoire of metabolic conversions) and function (production and/or utilization of resources and compounds). Advances in metagenomics enable a high-resolution description of complex microbial communities in their natural environments and support a systematic study of environment-community-function associations. NetCom is a web-tool for predicting metabolic activities of microbial communities based on network-based interpretation of assembled and annotated metagenomics data. The algorithm takes as an input, lists of differentially abundant enzymatic reactions and generates the following outputs: (i) pathway associations of differently abundant enzymes; (ii) prediction of environmental resources that are unique to each treatment, and their pathway associations; (iii) prediction of compounds that are produced by the microbial community, and pathway association of compounds that are treatment-specific; (iv) network visualization of enzymes, environmental resources and produced compounds, that are treatment specific (2 and 3D). The tool is demonstrated on metagenomic data from rhizosphere and bulk soil samples. By predicting root-specific activities, we illustrate the relevance of our framework for forecasting the impact of soil amendments on the corresponding microbial communities. NetCom is available online.

NetMet: A Network-Based Tool for Predicting Metabolic Capacities of Microbial Species and their Interactions.

Metabolic conversions allow organisms to produce a set of essential metabolites from the available nutrients in an environment, frequently requiring metabolic exchanges among co-inhabiting organisms. Genomic-based metabolic simulations are being increasingly applied for exploring metabolic capacities, considering different environments and different combinations of microorganisms. NetMet is a web-based tool and a software package for predicting the metabolic performances of microorganisms and their corresponding combinations in user-defined environments. The algorithm takes, as input, lists of (i) species-specific enzymatic reactions (EC numbers), and (ii) relevant metabolic environments. The algorithm generates, as output, lists of (i) compounds that individual species can produce in each given environment, and (ii) compounds that are predicted to be produced through complementary interactions. The tool is demonstrated in two case studies. First, we compared the metabolic capacities of different haplotypes of the obligatory fruit and vegetable pathogen Candidatus Liberibacter solanacearum to those of their culturable taxonomic relative Liberibacter crescens. Second, we demonstrated the potential production of complementary metabolites by pairwise combinations of co-occurring endosymbionts of the plant phloem-feeding whitefly Bemisia tabaci. NetMet, a new web-based tool, is available at https://freilich-lab-tools.com/.

Personal clinical history predicts antibiotic resistance of urinary tract infections.

Antibiotic resistance is prevalent among the bacterial pathogens causing urinary tract infections. However, antimicrobial treatment is often prescribed 'empirically', in the absence of antibiotic susceptibility testing, risking mismatched and therefore ineffective treatment. Here, linking a 10-year longitudinal data set of over 700,000 community-acquired urinary tract infections with over 5,000,000 individually resolved records of antibiotic purchases, we identify strong associations of antibiotic resistance with the demographics, records of past urine cultures and history of drug purchases of the patients. When combined together, these associations allow for machine-learning-based personalized drug-specific predictions of antibiotic resistance, thereby enabling drug-prescribing algorithms that match an antibiotic treatment recommendation to the expected resistance of each sample. Applying these algorithms retrospectively, over a 1-year test period, we find that they greatly reduce the risk of mismatched treatment compared with the current standard of care. The clinical application of such algorithms may help improve the effectiveness of antimicrobial treatments.

Orange carotenoid protein burrows into the phycobilisome to provide photoprotection.

In cyanobacteria, photoprotection from overexcitation of photochemical centers can be obtained by excitation energy dissipation at the level of the phycobilisome (PBS), the cyanobacterial antenna, induced by the orange carotenoid protein (OCP). A single photoactivated OCP bound to the core of the PBS affords almost total energy dissipation. The precise mechanism of OCP energy dissipation is yet to be fully determined, and one question is how the carotenoid can approach any core phycocyanobilin chromophore at a distance that can promote efficient energy quenching. We have performed intersubunit cross-linking using glutaraldehyde of the OCP and PBS followed by liquid chromatography coupled to tandem mass spectrometry (LC/MS-MS) to identify cross-linked residues. The only residues of the OCP that cross-link with the PBS are situated in the linker region, between the N- and C-terminal domains and a single C-terminal residue. These links have enabled us to construct a model of the site of OCP binding that differs from previous models. We suggest that the N-terminal domain of the OCP burrows tightly into the PBS while leaving the OCP C-terminal domain on the exterior of the complex. Further analysis shows that the position of the small core linker protein ApcC is shifted within the cylinder cavity, serving to stabilize the interaction between the OCP and the PBS. This is confirmed by a ΔApcC mutant. Penetration of the N-terminal domain can bring the OCP carotenoid to within 5-10 Å of core chromophores; however, alteration of the core structure may be the actual source of energy dissipation.

Investigation of phycobilisome subunit interaction interfaces by coupled cross-linking and mass spectrometry.

The phycobilisome (PBS) is an extremely large light-harvesting complex, common in cyanobacteria and red algae, composed of rods and core substructures. These substructures are assembled from chromophore-bearing phycocyanin and allophycocyanin subunits, nonpigmented linker proteins and in some cases additional subunits. To date, despite the determination of crystal structures of isolated PBS components, critical questions regarding the interaction and energy flow between rods and core are still unresolved. Additionally, the arrangement of minor PBS components located inside the core cylinders is unknown. Different models of the general architecture of the PBS have been proposed, based on low resolution images from electron microscopy or high resolution crystal structures of isolated components. This work presents a model of the assembly of the rods onto the core arrangement and for the positions of inner core components, based on cross-linking and mass spectrometry analysis of isolated, functional intact Thermosynechococcus vulcanus PBS, as well as functional cross-linked adducts. The experimental results were utilized to predict potential docking interactions of different protein pairs. Combining modeling and cross-linking results, we identify specific interactions within the PBS subcomponents that enable us to suggest possible functional interactions between the chromophores of the rods and the core and improve our understanding of the assembly, structure, and function of PBS.

Melatonin as an antioxidant and its semi-lunar rhythm in green macroalga Ulva sp.

The presence and role of melatonin in plants are still under debate owing to difficulties of identification and quantification. Accordingly, although it has been frequently proposed that melatonin acts as an antioxidant in phototrophic organisms, experimental data on its physiological role are scarce. This study describes the use of a rapid and simple new method for quantification of melatonin in the marine macroalga Ulva sp., organisms routinely exposed to tide-related environmental stresses and known for their high tolerance to abiotic conditions. The method was used here to show that exposure to oxidative stress-inducing environmental conditions (elevated temperature and heavy metals) induced a rise in melatonin level in the algae. Addition of exogenous melatonin alleviated the algae from cadmium-induced stress. Interestingly, although the algae were taken from a culture growing free floating and kept under constant photoperiod and water level, they exhibited a semi-lunar rhythm of melatonin levels that correlated with predicted spring tides. The correlation can probably be interpreted as reflecting preparation for predicted low tides, when the algae are exposed to increasing temperature, desiccation, and salinity, all known to induce oxidative stress. Given the simplicity of the described method it can easily be adapted for the study of melatonin in many other phototrophic organisms. These results provide, for the first time, experimental data that support both an antioxidant role for melatonin and its semi-lunar rhythm in macroalgae.