Emerging trends and applications of metabolomics in food science and nutrition

The study of all chemical processes involving metabolites is known as metabolomics. It has been developed into an essential tool in several disciplines, such as the study of plant physiology, drug development, human diseases, and nutrition. The field of food science, diagnostic biomarker research, etiological analysis in the field of medical therapy, and raw material quality, processing, and safety have all benefited from the use of metabolomics recently. Food metabolomics includes the use of metabolomics in food production, processing, and human diets. As a result of changing consumer habits and the rising of food industries all over the world, there is a remarkable increase in interest in food quality and safety. It requires the employment of various technologies for the food supply chain, processing of food, and even plant breeding. This can be achieved by understanding the metabolome of food, including its biochemistry and composition. Additionally, Food metabolomics can be used to determine the similarities and differences across crop kinds, as an indicator for tracking the process of ripening to increase crops' shelf life and attractiveness, and identifying metabolites linked to pathways responsible for postharvest disorders. Moreover, nutritional metabolomics is used to investigate the connection between diet and human health through detection of certain biomarkers. This review assessed and compiled literature on food metabolomics research with an emphasis on metabolite extraction, detection, and data processing as well as its applications to the study of food nutrition, food-based illness, and phytochemical analysis. Several studies have been published on the applications of metabolomics in food but further research concerning the use of standard reproducible procedures must be done. The results published showed promising uses in the food industry in many areas such as food production, processing, and human diets. Finally, metabolome-wide association studies (MWASs) could also be a useful predictor to detect the connection between certain diseases and low molecular weight biomarkers.

Antioxidant Metabolites in Primitive, Wild, and Cultivated Citrus and Their Role in Stress Tolerance

The genus Citrus contains a vast range of antioxidant metabolites, dietary metabolites, and antioxidant polyphenols that protect plants from unfavorable environmental conditions, enhance their tolerance to abiotic and biotic stresses, and possess multiple health-promoting effects in humans. This review summarizes various antioxidant metabolites such as organic acids, amino acids, alkaloids, fatty acids, carotenoids, ascorbic acid, tocopherols, terpenoids, hydroxycinnamic acids, flavonoids, and anthocyanins that are distributed in different citrus species. Among these antioxidant metabolites, flavonoids are abundantly present in primitive, wild, and cultivated citrus species and possess the highest antioxidant activity. We demonstrate that the primitive and wild citrus species (e.g., Atalantia buxifolia and C. latipes) have a high level of antioxidant metabolites and are tolerant to various abiotic and biotic stresses compared with cultivated citrus species (e.g., C. sinensis and C. reticulata). Additionally, we highlight the potential usage of citrus wastes (rag, seeds, fruit peels, etc.) and the health-promoting properties of citrus metabolites. Furthermore, we summarize the genes that are involved in the biosynthesis of antioxidant metabolites in different citrus species. We speculate that the genome-engineering technologies should be used to confirm the functions of candidate genes that are responsible for the accumulation of antioxidant metabolites, which will serve as an alternative tool to breed citrus cultivars with increased antioxidant metabolites.

Pre-Harvest and Post-Harvest Techniques for Plant Disease Detections

As the agriculture industry is growing fast, many efforts are introduced to ensure a high quality of produce. Diseases and defects found in plants and crops affect greatly the agriculture industry. Hence, many techniques and technologies have been developed to help solve or reduce the impact of plant diseases. Imagining analysis tools and gas sensors are becoming more frequently integrated into smart systems for plant disease detection. Many disease detection systems incorporate imaging analysis tools and VOC (Volatile Organic Compound) profiling techniques to detect early symptoms of diseases and defects of plants, fruits, and vegetative produce. These disease detection techniques can be further categorized into two main groups: preharvest disease detection and postharvest disease detection techniques. This paper aims to introduce the available disease detection techniques and to compare them with the latest innovative smart systems that feature visible imaging, hyperspectral imaging, and VOC profiling. In addition, this paper considers the efforts to automate imaging techniques to help accelerate the disease detection process. Different approaches are analyzed and compared in terms of work environment, automation, implementation, and accuracy of disease identification along with the future evolution perspective in this field.

Mass spectrometry imaging as a potential technique for diagnostic of Huanglongbing disease using fast and simple sample preparation

Huanglongbing (HLB) is a disease of worldwide incidence that affects orange trees, among other commercial varieties, implicating in great losses to the citrus industry. The disease is transmitted through Diaphorina citri vector, which inoculates Candidatus Liberibacter spp. in the plant sap. HLB disease lead to blotchy mottle and fruit deformation, among other characteristic symptoms, which induce fruit drop and affect negatively the juice quality. Nowadays, the disease is controlled by eradication of sick, symptomatic plants, coupled with psyllid control. Polymerase chain reaction (PCR) is the technique most used to diagnose the disease; however, this methodology involves high cost and extensive sample preparation. Mass spectrometry imaging (MSI) technique is a fast and easily handled sample analysis that, in the case of Huanglongbing allows the detection of increased concentration of metabolites associated to the disease, including quinic acid, phenylalanine, nobiletin and sucrose. The metabolites abieta-8,11,13-trien-18-oic acid, suggested by global natural product social molecular networking (GNPS) analysis, and 4-acetyl-1-methylcyclohexene showed a higher distribution in symptomatic leaves and have been directly associated to HLB disease. Desorption electrospray ionization coupled to mass spectrometry imaging (DESI-MSI) allows the rapid and efficient detection of biomarkers in sweet oranges infected with Candidatus Liberibacter asiaticus and can be developed into a real-time, fast-diagnostic technique.

Metabolome and Microbiome Signatures in the Roots of Citrus Affected by Huanglongbing

Huanglongbing (HLB) is a severe, incurable citrus disease caused by the bacterium 'Candidatus Liberibacter asiaticus' (CLas). Although citrus leaves serve as the site of initial infection, CLas is known to migrate to and colonize the root system; however, little is known about the impact of CLas infection on root metabolism and resident microbial communities. Scions of 'Lisbon' lemon and 'Washington Navel' orange grafted onto 'Carrizo' rootstock were grafted with either CLas-infected citrus budwood or uninfected budwood. Roots were obtained from trees 46 weeks after grafting and analyzed via ¹H nuclear magnetic resonance spectroscopy to identify water-soluble root metabolites and high-throughput sequencing of 16S rRNA and ITS gene amplicons to determine the relative abundance of bacterial and fungal taxa in the root rhizosphere and endosphere. In both citrus varieties, 27 metabolites were identified, of which several were significantly different between CLas(+) and control plants. CLas infection also appeared to alter the microbial community structure near and inside the roots of citrus plants. Nonmetric multidimensional scaling (NMDS) and a principal coordinate analysis (PCoA) revealed distinct metabolite and microbial profiles, demonstrating that CLas impacts the root metabolome and microbiome in a manner that is variety-specific.

GC-MS metabolite profiling for specific detection of dwarf somaclonal variation in banana plants

PREMISE OF THE STUDY

The production of banana (Musa spp.; Musaceae) plants is affected by various types of somaclonal variations (SV), including dwarfism. However, methods for specific detection of SV are still scarce. To overcome this, a metabolite-based method for detection of dwarf variants was evaluated.

METHODS

The gas chromatography-mass spectrometry (GC-MS) metabolite profile of dwarf banana variants was investigated and compared to that of normal-healthy (N) and cucumber mosaic virus (CMV)-infected plants using principal components analysis and partial least squares discriminant analysis (PLS-DA).

RESULTS

Significant differences among the sample groups were observed in 82 metabolites. Rhamnose was exclusively present in dwarf plants but allothreonine and trehalose were present in all but SV samples. Cellobiose was only detected in N plants, while 45 other metabolites, including methyl-glucopyranoside, allopyranose, lactose, phenylalanine, and l-lysine were detected in all but CMV-infected samples. PLS-DA models were able to detect SV, CMV, and N plants with 100% accuracy and specificity.

DISCUSSION

The GC-MS metabolite profile can be used for the rapid, specific detection of SV at early plant production stages. This is the first metabolite-based characterization and detection of somaclonal variation in plants.

Metabolite Profiling of Candidatus Liberibacter Infection in Hamlin Sweet Oranges

Huanglongbing (HLB), also known as citrus greening disease, caused by Candidatus Liberibacter asiaticus (CLas), is considered the most serious citrus disease in the world. CLas infection has been shown to greatly affect metabolite profiles in citrus fruits. However, because of uneven distribution of CLas throughout the tree and a minimum bacterial titer requirement for polymerase chain reaction (PCR) detection, the infected trees may test false negative. To prevent this, metabolites of healthy Hamlin oranges (CLas-) obtained from the citrus undercover protection systems (CUPS) were investigated. Comparison of the metabolite profile of juice obtained from CLas- and CLas+ (asymptomatic and symptomatic) trees revealed significant differences in both volatile and nonvolatile metabolites. However, no consistent pattern could be observed in alcohols, esters, sesquiterpenes, sugars, flavanones, and limonoids as compared to previous studies. These results suggest that CLas may affect metabolite profiles of citrus fruits earlier than detecting infection by PCR. Citric acid, nobiletin, malic acid, and phenylalanine were identified as the metabolic biomarkers associated with the progression of HLB. Thus, the differential metabolites found in this study may serve as the biomarkers of HLB in its early stage, and the metabolite signature of CLas infection may provide useful information for developing a potential treatment strategy.

Rapid two-dimensional ALSOFAST-HSQC experiment for metabolomics and fluxomics studies: application to a 13C-enriched cancer cell model treated with gold nanoparticles

Isotope labeling enables the use of ¹³C-based metabolomics techniques with strongly improved resolution for a better identification of relevant metabolites and tracing of metabolic fluxes in cell and animal models, as required in fluxomics studies. However, even at high NMR-active isotope abundance, the acquisition of one-dimensional ¹³C and classical two-dimensional ¹H,¹³C-HSQC experiments remains time consuming. With the aim to provide a shorter, more efficient alternative, herein we explored the ALSOFAST-HSQC experiment with its rapid acquisition scheme for the analysis of ¹³C-labeled metabolites in complex biological mixtures. As an initial step, the parameters of the pulse sequence were optimized to take into account the specific characteristics of the complex samples. We then applied the fast two-dimensional experiment to study the effect of different kinds of antioxidant gold nanoparticles on a HeLa cancer cell model grown on ¹³C glucose-enriched medium. As a result, ¹H,¹³C-2D correlations could be obtained in a couple of seconds to few minutes, allowing a simple and reliable identification of various ¹³C-enriched metabolites and the determination of specific variations between the different sample groups. Thus, it was possible to monitor glucose metabolism in the cell model and study the antioxidant effect of the coated gold nanoparticles in detail. Finally, with an experiment time of only half an hour, highly resolved ¹H,¹³C-HSQC spectra using the ALSOFAST-HSQC pulse sequence were acquired, revealing the isotope-position-patterns of the corresponding ¹³C-nuclei from carbon multiplets. Graphical abstract Fast NMR applied to metabolomics and fluxomics studies with gold nanoparticles.

The influence of bacteria on multitrophic interactions among plants, psyllids, and pathogen

The recent emergence of several plant diseases caused by psyllid-borne bacterial pathogens worldwide (Candidatus Liberibacter spp.) has created renewed interest on the interaction between psyllids and bacteria. In spite of these efforts to understand psyllid association with bacteria, many aspects of their interactions remain poorly understood. As more organisms are studied, subtleties on the molecular interactions as well as on the effects of the bacteria on the psyllid host are being uncovered. Additionally, psyllid-borne bacterial phytopathogens can also affect the host plant, which in turn can impact psyllid physiology and behavior. Here, we review the current literature on different aspects of the influence of bacteria on multitrophic interactions among plants, psyllids, and pathogens. We then highlight gaps that need to be addressed to advance this field, which can have significant implications for controlling these newly emergent and other plant diseases.

Metabolic variations in different citrus rootstock cultivars associated with different responses to Huanglongbing

Huanglongbing (HLB) is one of the most destructive bacterial diseases of citrus. No resistant cultivars have been identified, although tolerance has been observed in the genus Poncirus and some of its hybrids with Citrus that are commonly used as rootstocks. In this study we exploited this tolerance by comparing five different tolerant hybrids with a cultivar that shows pronounced HLB sensitivity to discern potential contributing metabolic factors. Whole leaves of infected and non-infected greenhouse-grown seedlings were extracted and subjected to untargeted GC-TOF MS based metabolomics. After BinBase data filtering, 342 (experiment 1) and 650 (experiment 2) unique metabolites were quantified, of which 122 and 195, respectively, were assigned by chemical structures. The number of metabolites found to be differently regulated in the infected state compared with the non-infected state varied between the cultivars and was largest (166) in the susceptible cultivar Cleopatra mandarin (Citrus reticulata) and lowest (3) in the tolerant cultivars US-897 (C. reticulata 'Cleopatra' × Poncirus trifoliata) and US-942 (C. reticulata 'Sunki' × P. trifoliata) from experiment 2. Tolerance to HLB did not appear to be associated with accumulation of higher amounts of protective metabolites in response to infection. Many metabolites were found in higher concentrations in the tolerant cultivars compared with susceptible Cleopatra mandarin and may play important roles in conferring tolerance to HLB. Lower availability of specific sugars necessary for survival of the pathogen may also be a contributing factor in the decreased disease severity observed for these cultivars.

Metabolite signature of Candidatus Liberibacter asiaticus infection in two citrus varieties

Huanglongbing (HLB), also known as Citrus Greening Disease, is caused by the bacterium 'Candidatus Liberibacter asiaticus' (CLas) and is a serious threat to the citrus industry. To understand the effect of CLas infection on the citrus metabolome, juice from healthy (n = 18), HLB-asymptomatic (n = 18), and HLB-symptomatic Hamlin (n = 18), as well as from healthy (n = 18) and HLB-symptomatic (n = 18) Valencia sweet oranges (from southern and eastern Florida) were evaluated using (1)H NMR-based metabolomics. Differences in the concentration of several metabolites including phenylalanine, histidine, limonin, and synephrine between control or asymptomatic fruit and symptomatic fruit were observed regardless of the citrus variety or location. There were no clear differences between the metabolite profiles of Hamlin fruits classified by PCR as asymptomatic and control, suggesting that some of the control fruit may have been infected. Taken together, these data indicate that infection due to CLas presents a strong metabolic response that is observed across different cultivars and regions, suggesting the potential for generation of metabolite-based biomarkers of CLas infection.

An HPLC-MS characterization of the changes in sweet orange leaf metabolite profile following infection by the bacterial pathogen Candidatus Liberibacter asiaticus

Huanglongbing (HLB) presumably caused by Candidatus Liberibacter asiaticus (CLas) threatens the commercial U.S. citrus crop of an annual value of $3 billion. The earliest shift in metabolite profiles of leaves from greenhouse-grown sweet orange trees infected with Clas, and of healthy leaves, was characterized by HPLC-MS concurrently with PCR testing for the presence of Clas bacteria and observation of disease symptoms. Twenty, 8-month-old ‘Valencia’ and ‘Hamlin’ trees were grafted with budwood from PCR-positive HLB source trees. Five graft-inoculated trees of each variety and three control trees were sampled biweekly and analyzed by HPLC-MS and PCR. Thirteen weeks after inoculation, Clas was detected in newly growing flushes in 33% and 55% of the inoculated ‘Hamlin’ and ‘Valencia’ trees, respectively. Inoculated trees remained asymptomatic in the first 20 weeks, but developed symptoms 30 weeks after grafting. No significant differences in the leaf metabolite profiles were detected in Clas-infected trees 23 weeks after inoculation. However, 27 weeks after inoculation, differences in metabolite profiles between control leaves and those of Clas-infected trees were evident. Affected compounds were identified with authentic standards or structurally classified by their UV and mass spectra. Included among these compounds are flavonoid glycosides, polymethoxylated flavones, and hydroxycinnamates. Four structurally related hydroxycinnamate compounds increased more than 10-fold in leaves from ‘Hamlin’ and ‘Valencia’ sweet orange trees in response to Clas infection. Possible roles of these hydroxycinnamates as plant defense compounds against the Clas infection are discussed.

Metabolomics in plants and humans: applications in the prevention and diagnosis of diseases

In the recent years, there has been an increase in the number of metabolomic approaches used, in parallel with proteomic and functional genomic studies. The wide variety of chemical types of metabolites available has also accelerated the use of different techniques in the investigation of the metabolome. At present, metabolomics is applied to investigate several human diseases, to improve their diagnosis and prevention, and to design better therapeutic strategies. In addition, metabolomic studies are also being carried out in areas such as toxicology and pharmacology, crop breeding, and plant biotechnology. In this review, we emphasize the use and application of metabolomics in human diseases and plant research to improve human health.

Detection of the dynamic response of cucumber leaves to fusaric acid using thermal imaging

Fusarium wilt is a major disease that causes severe losses in crop yield. Fusaric acid (FA), a non-specific fungal toxin produced by many Fusarium species, can accelerate the wilting of many crops. Unraveling the role of FA in the wilt process can enrich the understanding of the mechanism of pathogenesis. To investigate the dynamic process of the cucumber's response to FA, we used digital infrared thermography (DIT) to detect leaf temperature during the alternation of light and dark conditions in greenhouse hydroponic experiments. During FA treatment, we found that the leaf temperature of cucumber plants increased when stomata closure was induced by FA. Under the alternation of light and dark, FA-treated plants had a higher leaf temperature in the light and a lower temperature in the dark, when compared to untreated plants. To confirm the uncontrolled water loss was from damaged leaf cells, as a result of FA treatment, and not from the stomata, an experiment was conducted using a split-root system in which spatially separated cucumber roots were each supplied 0 ppm or 100 ppm of FA. In the split-root system, the low temperature areas of the leaves in the dark had a higher FA concentration and more severe membrane injury than the high temperature areas, demonstrating that FA is primary xylem transported. We concluded that membrane injury caused by FA led to non-stomata water loss and, ultimately, to wilting. Combining the response of the leaves under the light and dark conditions with the DIT employed in the present study permitted noninvasive monitoring and direct visualization of wilting development.

Metabolomics as a tool to investigate abiotic stress tolerance in plants

Metabolites reflect the integration of gene expression, protein interaction and other different regulatory processes and are therefore closer to the phenotype than mRNA transcripts or proteins alone. Amongst all –omics technologies, metabolomics is the most transversal and can be applied to different organisms with little or no modifications. It has been successfully applied to the study of molecular phenotypes of plants in response to abiotic stress in order to find particular patterns associated to stress tolerance. These studies have highlighted the essential involvement of primary metabolites: sugars, amino acids and Krebs cycle intermediates as direct markers of photosynthetic dysfunction as well as effectors of osmotic readjustment. On the contrary, secondary metabolites are more specific of genera and species and respond to particular stress conditions as antioxidants, Reactive Oxygen Species (ROS) scavengers, coenzymes, UV and excess radiation screen and also as regulatory molecules. In addition, the induction of secondary metabolites by several abiotic stress conditions could also be an effective mechanism of cross-protection against biotic threats, providing a link between abiotic and biotic stress responses. Moreover, the presence/absence and relative accumulation of certain metabolites along with gene expression data provides accurate markers (mQTL or MWAS) for tolerant crop selection in breeding programs.

The ABC transporters in Candidatus Liberibacter asiaticus

Candidatus Liberibacter asiaticus (Ca. L. asiaticus) is a Gram-negative bacterium and the pathogen of Citrus Greening disease (Huanglongbing, HLB). As a parasitic bacterium, Ca. L. asiaticus harbors ABC transporters that play important roles in exchanging chemical compounds between Ca. L. asiaticus and its host. Here, we analyzed all the ABC transporter-related proteins in Ca. L. asiaticus. We identified 14 ABC transporter systems and predicted their structures and substrate specificities. In-depth sequence and structure analysis including multiple sequence alignment, phylogenetic tree reconstruction, and structure comparison further support their function predictions. Our study shows that this bacterium could use these ABC transporters to import metabolites (amino acids and phosphates) and enzyme cofactors (choline, thiamine, iron, manganese, and zinc), resist to organic solvent, heavy metal, and lipid-like drugs, maintain the composition of the outer membrane (OM), and secrete virulence factors. Although the features of most ABC systems could be deduced from the abundant experimental data on their orthologs, we reported several novel observations within ABC system proteins. Moreover, we identified seven nontransport ABC systems that are likely involved in virulence gene expression regulation, transposon excision regulation, and DNA repair. Our analysis reveals several candidates for further studies to understand and control the disease, including the type I virulence factor secretion system and its substrate that are likely related to Ca. L. asiaticus pathogenicity and the ABC transporter systems responsible for bacterial OM biosynthesis that are good drug targets.

Predictive sequence analysis of the Candidatus Liberibacter asiaticus proteome

Candidatus Liberibacter asiaticus (Ca. L. asiaticus) is a parasitic Gram-negative bacterium that is closely associated with Huanglongbing (HLB), a worldwide citrus disease. Given the difficulty in culturing the bacterium and thus in its experimental characterization, computational analyses of the whole Ca. L. asiaticus proteome can provide much needed insights into the mechanisms of the disease and guide the development of treatment strategies. In this study, we applied state-of-the-art sequence analysis tools to every Ca. L. asiaticus protein. Our results are available as a public website at http://prodata.swmed.edu/liberibacter_asiaticus/. In particular, we manually curated the results to predict the subcellular localization, spatial structure and function of all Ca. L. asiaticus proteins (http://prodata.swmed.edu/liberibacter_asiaticus/curated/). This extensive information should facilitate the study of Ca. L. asiaticus proteome function and its relationship to disease. Pilot studies based on the information from our website have revealed several potential virulence factors, discussed herein.

GC-MS metabolomic differentiation of selected citrus varieties with different sensitivity to citrus huanglongbing

Huanglongbing (HLB) is the most destructive disease of citrus worldwide. The rapid identification of tolerant varieties is considered a critical step towards controlling HLB. GC-MS metabolite profiles were used to differentiate HLB-tolerant citrus varieties 'Poncirus trifoliata' (TR) and 'Carrizo citrange' (CAR) from HLB-sensitive varieties 'Madam Vinous sweet orange' (MV) and 'Duncan' grapefruit (DG). PCR analyses revealed that MV was the most sensitive variety followed by DG and the tolerant varieties CAR and TR. Metabolomic multivariate analysis allowed classification of the cultivars in apparent agreement with PCR results. Higher levels of the amino acids l-proline, l-serine, and l-aspartic acid, as well as the organic acids butanedioic and tetradecanoic acid, and accumulation of galactose in healthy plants were characteristic of the most sensitive variety MV when compared to all other varieties. Only galactose was significantly higher in DG when compared to the tolerant varieties TR and CAR. The tolerant varieties showed higher levels of l-glycine and mannose when compared to sensitive varieties MV and DG. Profiling of the sensitive varieties MV and DG over a 20-week period after inoculation of those with the HLB-containing material revealed strong responses of metabolites to HLB infection that differed from the response of the tolerant varieties. Significant changes of l-threonine level in the leaves from old mature flushes and l-serine, l-threonine, scyllo-inositol, hexadecanoic acid, and mannose in the leaves from young developing flushes were observed in MV. Significant changes in myo-inositol in old flushes and l-proline, indole, and xylose in new flushes were observed in DG.

Metabolomics in food science

Metabolomics, the newest member of the omics techniques, has become an important tool in agriculture, pharmacy, and environmental sciences. Advances in compound extraction, separation, detection, identification, and data analysis have allowed metabolomics applications in food sciences including food processing, quality, and safety. This chapter discusses recent advances and applications of metabolomics in food science.

GC-MS analysis of headspace and liquid extracts for metabolomic differentiation of citrus Huanglongbing and zinc deficiency in leaves of 'Valencia' sweet orange from commercial groves

INTRODUCTION

Citrus Huanglongbing (HLB) is considered the most destructive citrus disease worldwide. Symptoms-based detection of HLB is difficult due to similarities with zinc deficiency.

OBJECTIVE

To find metabolic differences between leaves from HLB-infected, zinc-deficient, and healthy 'Valencia' orange trees by using GC-MS based metabolomics.

METHODOLOGY

Analysis based on GC-MS methods for untargeted metabolite analysis of citrus leaves was developed and optimized. Sample extracts from healthy, zinc deficient, or HLB-infected sweet orange leaves were submitted to headspace solid phase micro-extraction (SPME) and derivatization treatments prior to GC-MS analysis.

RESULTS

Principal components analysis achieved correct classification of all the derivatized liquid extracts. Analysis of variance revealed 6 possible biomarkers for HLB, of which 5 were identified as proline, β-elemene, (-)trans- caryophyllene, and α-humulene. Significant (P < 0.05) differences in oxo-butanedioic acid, arabitol, and neo-inositol were exclusively detected in samples from plants with zinc deficiency. Levels of isocaryophyllen, α-selinene, β-selinene, and fructose were significantly (P < 0.05) different in healthy leaves only.

CONCLUSION

Results suggest the potential of using identified HLB biomarkers for rapid differentiation of HLB from zinc deficiency.

Soybean metabolites regulated in root hairs in response to the symbiotic bacterium Bradyrhizobium japonicum

Nodulation of soybean (Glycine max) root hairs by the nitrogen-fixing symbiotic bacterium Bradyrhizobium japonicum is a complex process coordinated by the mutual exchange of diffusible signal molecules. A metabolomic study was performed to identify small molecules produced in roots and root hairs during the rhizobial infection process. Metabolites extracted from roots and root hairs mock inoculated or inoculated with B. japonicum were analyzed by gas chromatography-mass spectrometry and ultraperformance liquid chromatography-quadrupole time of flight-mass spectrometry. These combined approaches identified 2,610 metabolites in root hairs. Of these, 166 were significantly regulated in response to B. japonicum inoculation, including various (iso)flavonoids, amino acids, fatty acids, carboxylic acids, and various carbohydrates. Trehalose was among the most strongly induced metabolites produced following inoculation. Subsequent metabolomic analyses of root hairs inoculated with a B. japonicum mutant defective in the trehalose synthase, trehalose 6-phosphate synthase, and maltooligosyltrehalose synthase genes showed that the trehalose detected in the inoculated root hairs was primarily of bacterial origin. Since trehalose is generally considered an osmoprotectant, these data suggest that B. japonicum likely experiences osmotic stress during the infection process, either on the root hair surface or within the infection thread.