Identification of key yeast species and microbe-microbe interactions impacting larval growth of Drosophila in the wild.

Microbiota consisting of various fungi and bacteria have a significant impact on the physiological functions of the host. However, it is unclear which species are essential to this impact and how they affect the host. This study analyzed and isolated microbes from natural food sources of Drosophila larvae, and investigated their functions. Hanseniaspora uvarum is the predominant yeast responsible for larval growth in the earlier stage of fermentation. As fermentation progresses, Acetobacter orientalis emerges as the key bacterium responsible for larval growth, although yeasts and lactic acid bacteria must coexist along with the bacterium to stabilize this host-bacterial association. By providing nutrients to the larvae in an accessible form, the microbiota contributes to the upregulation of various genes that function in larval cell growth and metabolism. Thus, this study elucidates the key microbial species that support animal growth under microbial transition.

The Thing Metabolome Repository family (XMRs): comparable untargeted metabolome databases for analyzing sample-specific unknown metabolites.

The identification of unknown chemicals has emerged as a significant issue in untargeted metabolome analysis owing to the limited availability of purified standards for identification; this is a major bottleneck for the accumulation of reusable metabolome data in systems biology. Public resources for discovering and prioritizing the unknowns that should be subject to practical identification, as well as further detailed study of spending costs and the risks of misprediction, are lacking. As such a resource, we released databases, Food-, Plant- and Thing-Metabolome Repository (http://metabolites.in/foods, http://metabolites.in/plants, and http://metabolites.in/things, referred to as XMRs) in which the sample-specific localization of unknowns detected by liquid chromatography-mass spectrometry in a wide variety of samples can be examined, helping to discover and prioritize the unknowns. A set of application programming interfaces for the XMRs facilitates the use of metabolome data for large-scale analysis and data mining. Several applications of XMRs, including integrated metabolome and genome analyses, are presented. Expanding the concept of XMRs will accelerate the identification of unknowns and increase the discovery of new knowledge.

Surface plasmon resonance sensor using a polarization-maintaining fiber on a hetero-core optical fiber structure with gold thin film.

This study experimentally demonstrated the effects of two polarization-maintaining fibers (PMFs) as a sensing region instead of conventional single-mode fiber (SMF) using Au-coated hetero-core optical fiber surface plasmon resonance (SPR) sensor. We experimentally observed that the SPR resonant wavelength is shifted toward longer wavelength with refractive index (RI) increasing from 1.332 to 1.396. A PMF sensor exhibits the broad SPR spectra, resulting in a higher sensitivity with a 1.5-fold change in the light intensity at 850 nm relative to RI, compared with the SMF case. Discussions most likely responsible for this effect are given by the lower angular distribution peak in the hetero-core region of PMFs.

Recent applications of metabolomics in plant breeding.

Metabolites play a central role in maintaining organismal life and in defining crop phenotypes, such as nutritional value, fragrance, color, and stress resistance. Among the 'omes' in biology, the metabolome is the closest to the phenotype. Consequently, metabolomics has been applied to crop improvement as method for monitoring changes in chemical compositions, clarifying the mechanisms underlying cellular functions, discovering markers and diagnostics, and phenotyping for mQTL, mGWAS, and metabolite-genome predictions. In this review, 359 reports of the most recent applications of metabolomics to plant breeding-related studies were examined. In addition to the major crops, more than 160 other crops including rare medicinal plants were considered. One bottleneck associated with using metabolomics is the wide array of instruments that are used to obtain data and the ambiguity associated with metabolite identification and quantification. To further the application of metabolomics to plant breeding, the features and perspectives of the technology are discussed.

Development of two-dimensional qualitative visualization method for isoflavones secreted from soybean roots using sheets with immobilized bovine serum albumin.

A visualization method for the qualitative evaluation of soybean isoflavones secreted from soybean roots by transferring them onto a sheet with immobilized bovine serum albumin (BSA) was developed. BSA was chemically bonded onto a glass microfiber filter. The fluorescence quenching resulting from the interaction of BSA with soybean isoflavones such as daidzein and daidzin was utilized. Fluorescence images before and after soybean roots were placed in contact with the sheets with immobilized BSA were taken with an electron-multiplying charge-coupled device camera. The fluorescence quenching in the images was visualized and analyzed. Soybean isoflavones were extracted from the sheets for quantitative analysis, and the correlation coefficient between the quenched fluorescence intensity per sheet and the total amount of soybean isoflavones was 0.78 (p < 0.01), indicating a high correlation. The quenched fluorescence intensity was lower in pumpkin roots, which do not secrete soybean isoflavone. It was found from analyzed images that soybean isoflavone is secreted in larger amounts from the basal region of the taproot and the tips of the lateral roots of soybean.

MassBase: A large-scaled depository of mass spectrometry datasets for metabolome analysis.

Depository of low-molecular-weight compounds or metabolites detected in various organisms in a non-targeted manner is indispensable for metabolomics research. Due to the diverse chemical compounds, various mass spectrometry (MS) setups with state-of-the-art technologies have been used. Over the past two decades, we have analyzed various biological samples by using gas chromatography-mass spectrometry, liquid chromatography-mass spectrometry, or capillary electrophoresis-mass spectrometry, and archived the datasets in the depository MassBase (http://webs2.kazusa.or.jp/massbase/). As the format of MS datasets depends on the MS setup used, we converted each raw binary dataset of the mass chromatogram to text file format, and thereafter, information of the chromatograph peak was extracted in the text file from the converted file. In total, the depository comprises 46,493 datasets, of which 38,750 belong to the plant species and 7,743 are authentic or mixed chemicals as well as other sources (microorganisms, animals, and foods), as on August 1, 2020. All files in the depository can be downloaded in bulk from the website. Mass chromatograms of 90 plant species obtained by LC-Fourier transform ion cyclotron resonance MS or Orbitrap MS, which detect the ionized molecules with high accuracy allowing speculation of chemical compositions, were converted to text files by the software PowerGet, and the chemical annotation of each peak was added. The processed datasets were deposited in the annotation database KomicMarket2 (http://webs2.kazusa.or.jp/km2/). The archives provide fundamental resources for comparative metabolomics and functional genomics, which may result in deeper understanding of living organisms.

TOMATOMET: A metabolome database consists of 7118 accurate mass values detected in mature fruits of 25 tomato cultivars.

The total number of low-molecular-weight compounds in the plant kingdom, most of which are secondary metabolites, is hypothesized to be over one million, although only a limited number of plant compounds have been characterized. Untargeted analysis, especially using mass spectrometry (MS), has been useful for understanding the plant metabolome; however, due to the limited availability of authentic compounds for MS-based identification, the identities of most of the ion peaks detected by MS remain unknown. Accurate mass values of peaks obtained by high accuracy mass measurement and, if available, MS/MS fragmentation patterns provide abundant annotation for each peak. Here, we carried out an untargeted analysis of compounds in the mature fruit of 25 tomato cultivars using liquid chromatography-Orbitrap MS for accurate mass measurement, followed by manual curation to construct the metabolome database TOMATOMET (http://metabolites.in/tomato-fruits/). The database contains 7,118 peaks with accurate mass values, in which 1,577 ion peaks are annotated as members of a chemical group. Remarkably, 71% of the mass values are not found in the accurate masses detected previously in Arabidopsis thaliana, Medicago truncatula or Jatropha curcas, indicating significant chemical diversity among plant species that remains to be solved. Interestingly, substantial chemical diversity exists also among tomato cultivars, indicating that chemical profiling from distinct cultivars contributes towards understanding the metabolome, even in a single organ of a species, and can prioritize some desirable metabolic targets for further applications such as breeding.

Metabolome analysis using multiple data mining approaches suggests luteolin biosynthesis in Physcomitrella patens.

The model land plant Physcomitrella patens synthesizes flavonoids which may act as protectant of ultraviolet-B radiation. We aimed to uncover its flavonoid profile, for which metabolome analysis using liquid chromatography coupled with Ion trap/Orbitrap mass spectrometry was performed. From the 80% methanol extracts, 661 valid peaks were detected. Prediction of the elemental compositions within a mass accuracy of 2 ppm indicated that 217 peaks had single elemental composition. A compound database search revealed 47 peaks to be annotated as secondary metabolites based on the compound database search. Comprehensive substituent search by ShiftedIonsFinder showed there were 13 peaks of potential flavonoid derivatives. Interestingly, a peak having m/z 287.0551, corresponding to that of luteolin, was detected, even though flavone synthase has never been identified in P. patens. Using P. patens labeled with stable isotopes (13C-, 15N-, 18O-, and 34S), we confirmed the elemental composition of the peak as C15H10O6. By a comparison of MS/MS spectra with that of authentic standard, the peak was identified as luteolin or related flavone isomers. This is the first report of luteolin or related flavones synthesis and the possibility of the existence of an unknown enzyme with flavone synthase activity in P. patens.

Metabolome profile of Negi-Nira chive, an interspecies hybrid of green spring onion (Allium fistulosum) and Chinese chive (A. tuberosum).

Metabolome analysis of flavored vegetables, green spring onion (Allium fistulosum), Chinese chive (A. tuberosum), and their interspecies hybrid Negi-Nira chive, was conducted using liquid chromatography-Fourier transform ion cyclotron resonance-mass spectrometry, with ca. 2 ppm mass accuracy. Ion peaks in the chromatograms of four biological replicates of the vegetable leaves were processed using the alignment software PowerGet for metabolite comparison, from which we obtained the potential chemical formulae. In total, 860 ion peaks were reproducibly detected; of these, 506, 525, and 336 peaks were found in the hybrid, A. tuberosum, and A. fistulosum, respectively. There were 130 peaks specific to the hybrid; from these, 31 metabolites were annotated by searching compound databases. The sulfur-containing compounds and flavonoids were further analyzed using bioinformatics, to examine the sulfur metabolism of Allium volatiles and the flavonoid pathways in these species. In conclusion, our metabolome analysis of this interspecies hybrid and its parents provides a unique opportunity to elucidate their metabolic background.

An Artificial Conversion of Roots into Organs with Shoot Stem Characteristics by Inducing Two Transcription Factors.

Somatic plant cells can regenerate shoots and/or roots or adventitious embryonic calluses, which may induce organ formation under certain conditions. Such regenerations occur via dedifferentiation of somatic cells, induction of organs, and their subsequent outgrowth. Despite recent advances in understanding of plant regeneration, many details of shoot induction remain unclear. Here, we artificially induced shoot stem-like green organs (SSOs) in Arabidopsis thaliana roots via simultaneous induction of two transcription factors (TFs), ARABIDOPSIS THALIANA HOMEOBOX PROTEIN 25 (ATHB25, At5g65410) and the B3 family transcription factor REPRODUCTIVE MERISTEM 7 (REM7, At3g18960). The SSOs exhibited negative gravitropism and differentiated vascular bundle phenotypes. The ATHB25/REM7 induced the expression of genes controlling shoot stem characteristics by ectopic expression in roots. Intriguingly, the restoration of root growth was seen in the consecutive and adjacent parts of the SSOs under gene induction conditions. Our findings thus provide insights into the development and regeneration of plant shoot stems.

Differential annotation of converted metabolites (DAC-Met): Exploration of Maoto (Ma-huang-tang)-derived metabolites in plasma using high-resolution mass spectrometry.

INTRODUCTION: Traditional herbal medicine (THM) contains a vast number of natural compounds with varying degrees of pharmacological activity. To elucidate the mode of action, comprehensive metabolite profiling in the plasma before and after administration of THM is essential. OBJECTIVE: The aim of this study was to explore and identify/annotate converted metabolites after administration of THM in humans. METHODS: We performed untargeted metabolome analysis of human plasma collected before and after administration of maoto (ma-huang-tang), a traditional Japanese Kampo medicine. Maoto-derived metabolites were then selected and annotated following the DAC-Met strategy, which is an annotation method that uses mass differences of major metabolic reactions among the detected peaks and a differential network analysis. RESULTS: About 80% of maoto-derived components were found to be converted forms. Following DAC-Met, the structures of 15 previously unidentified metabolites were determined, and five of these were later confirmed with authentic standards. Using published literature, we also reconstructed the metabolic pathway of maoto components in humans. A kinetic time-course analysis revealed their diverse kinetic profiles. CONCLUSION: The results demonstrated that time-resolved comprehensive metabolite profiling in plasma using the DAC-Met strategy is highly useful for elucidating the complex nature of THM.

Metabolome Analysis Identified Okaramines in the Soybean Rhizosphere as a Legacy of Hairy Vetch.

Inter-organismal communications below ground, such as plant-microbe interactions in the rhizosphere, affect plant growth. Metabolites are shown to play important roles in biological communication, but there still remain a large number of metabolites in soil to be uncovered. Metabolomics, a technique for the comprehensive analysis of metabolites in samples, may uncover the molecules that intermediate these interactions. We conducted a multivariate analysis using liquid chromatography (LC)-mass spectrometry (MS)-based untargeted metabolomics in several soil samples and also targeted metabolome analysis for the identification of the candidate compounds in soil. We identified okaramine A, B, and C in the rhizosphere soil of hairy vetch. Okaramines are indole alkaloids first identified in soybean pulp (okara) inoculated with Penicillium simplicissimum AK-40 and are insecticidal. Okaramine B was detected in the rhizosphere from an open field growing hairy vetch. Okaramine B was also detected in both bulk and rhizosphere soils of soybean grown following hairy vetch, but not detected in soils of soybean without hairy vetch growth. These results suggested that okaramines might be involved in indirect defense of plants against insects. To our knowledge, this is the first report of okaramines in the natural environment. Untargeted and targeted metabolomics would be useful to uncover the chemistry of the rhizosphere.

A Cytosol-Localized Geranyl Diphosphate Synthase from Lithospermum erythrorhizon and Its Molecular Evolution.

Geranyl diphosphate (GPP) is the direct precursor of all monoterpenoids and is the prenyl source of many meroterpenoids, such as geranylated coumarins. GPP synthase (GPPS) localized in plastids is responsible for providing the substrate for monoterpene synthases and prenyltransferases for synthesis of aromatic substances that are also present in plastids, but GPPS activity in Lithospermum erythrorhizon localizes to the cytosol, in which GPP is utilized for the biosynthesis of naphthoquinone pigments, which are shikonin derivatives. This study describes the identification of the cytosol-localized GPPS gene, LeGPPS, through EST- and homology-based approaches followed by functional analyses. The deduced amino acid sequence of the unique LeGPPS showed greater similarity to that of farnesyl diphosphate synthase (FPPS), which generally localizes to the cytosol, than to plastid-localized conventional GPPS. Biochemical characterization revealed that recombinant LeGPPS predominantly produces GPP along with a trace amount of FPP. LeGPPS expression was mainly detected in root bark, in which shikonin derivatives are produced, and in shikonin-producing cultured cells. The GFP fusion protein in onion (Allium cepa) cells localized to the cytosol. Site-directed mutagenesis of LeGPPS and another FPPS homolog identified in this study, LeFPPS1, showed that the His residue at position 100 of LeGPPS, adjacent to the first Asp-rich motif, contributes to substrate preference and product specificity, leading to GPP formation. These results suggest that LeGPPS, which is involved in shikonin biosynthesis, is recruited from cytosolic FPPS and that point mutation(s) result in the acquisition of GPPS activity.

Lipid remodeling regulator 1 (LRL1) is differently involved in the phosphorus-depletion response from PSR1 in Chlamydomonas reinhardtii.

The elucidation of lipid metabolism in microalgae has attracted broad interest, as their storage lipid, triacylglycerol (TAG), can be readily converted into biofuel via transesterification. TAG accumulates in the form of oil droplets, especially when cells undergo nutrient deprivation, such as for nitrogen (N), phosphorus (P), or sulfur (S). TAG biosynthesis under N-deprivation has been comprehensively studied in the model microalga Chlamydomonas reinhardtii, during which TAG accumulates dramatically. However, the resulting rapid breakdown of chlorophyll restricts overall oil yield productivity and causes cessation of cell growth. In contrast, P-deprivation results in oil accumulation without disrupting chloroplast integrity. We used a reverse genetics approach based on co-expression analysis to identify a transcription factor (TF) that is upregulated under P-depleted conditions. Transcriptomic analysis revealed that the mutants showed repression of genes typically associated with lipid remodeling under P-depleted conditions, such as sulfoquinovosyl diacylglycerol 2 (SQD2), diacylglycerol acyltransferase (DGTT1), and major lipid droplet protein (MLDP). As accumulation of sulfoquinovosyl diacylglycerol and TAG were suppressed in P-depleted mutants, we designated the protein as lipid remodeling regulator 1 (LRL1). LRL1 mutants showed slower growth under P-depletion. Moreover, cell size in the mutant was significantly reduced, and TAG and starch accumulation per cell were decreased. Transcriptomic analysis also suggested the repression of several genes typically upregulated in adaptation to P-depletion that are associated with the cell cycle and P and lipid metabolism. Thus, our analysis of LRL1 provides insights into P-allocation and lipid remodeling under P-depleted conditions in C. reinhardtii. OPEN RESEARCH BADGES: This article has earned an Open Data Badge for making publicly available the digitally-shareable data necessary to reproduce the reported results. The sequencing data were made publicly available under the BioProject Accession number PRJDB6733 and an accession number LC488724 at the DNA Data Bank of Japan (DDBJ). The data is available at https://trace.ddbj.nig.ac.jp/BPSearch/bioproject?acc=PRJDB6733; http://getentry.ddbj.nig.ac.jp/getentry/na/LC488724. The metabolome data were made publicly available and can be accessed at http://metabolonote.kazusa.or.jp/SE195:/; http://webs2.kazusa.or.jp/data/nur/.

ConfeitoGUI: A toolkit for size-sensitive community detection from a correlation network.

Analysis of the large amounts of data accumulated in public databanks can facilitate a more comprehensive understanding of molecular biological processes. Community detection from molecular biological data is paramount in characterizing evolutionary and functional traits of organisms based on gene homology and co-expression, respectively. Although there are common tools to detect local communities from a large network, no toolkit exists for detecting communities that include an element of interest based on size sensitivity, i.e., functionality to obtain local communities with preferred sizes. Herein, we present the ConfeitoGUI toolkit for detecting local communities from a correlation network involving size sensitivity. We compared the toolkit with other common tools for detection in reconstructing communities of microarray experiments of mice. In the results, ConfeitoGUI was observed to be preferable for detecting communities whose sizes are similar to those of original communities compared to other common tools. By changing simple parameters representing sizes for the toolkit, a user can obtain local communities with preferred sizes, which is beneficial for further analysis of members belonging to the communities.

Comparative multi-omics analysis reveals diverse latex-based defense strategies against pests among latex-producing organs of the fig tree (Ficus carica).

MAIN CONCLUSION: Latexes in immature fruit, young petioles and lignified trunks of fig trees protect the plant using toxic proteins and metabolites in various organ-dependent ways. Latexes from plants contain high amounts of toxic proteins and metabolites, which attack microbes and herbivores after exudation at pest-induced wound sites. The protein and metabolite constituents of latexes are highly variable, depending on the plant species and organ. To determine the diversity of latex-based defense strategies in fig tree (Ficus carica) organs, we conducted comparative proteomic, transcriptomic and metabolomic analyses on latexes isolated from immature fruit, young petioles and lignified trunks of F. carica after constructing a unigene sequence library using RNA-seq data. Trypsin inhibitors were the most abundant proteins in petiole latex, while cysteine proteases ("ficins") were the most abundant in immature fruit and trunk latexes. Galloylglycerol, a possible defense-related metabolite, appeared to be highly accumulated in all three latexes. The expression levels of pathogenesis-related proteins were highest in the latex of trunk, suggesting that this latex had adapted a defensive role against microbe attacks. Although young petioles and immature fruit are both unlignified soft organs, and potential food for herbivorous insects, unigenes for the sesquiterpenoid pathway, which likely produces defense-associated volatiles, and the phenylpropanoid pathway, which produces toxic furanocoumarins, were expressed less in immature fruit latex. This difference may indicate that while petioles and fruit protect the plant from attack by herbivores, the fruit must also attract insect pollinators at younger stages and animals after ripening. We also suggest possible candidate transcription factors and signal transduction proteins that are involved in the differential expression of the unigenes.

UC2 search: using unique connectivity of uncharged compounds for metabolite annotation by database searching in mass spectrometry-based metabolomics.

Summary: For metabolite annotation in metabolomics, variations in the registered states of compounds (charged molecules and multiple components, such as salts) and their redundancy among compound databases could be the cause of misannotations and hamper immediate recognition of the uniqueness of metabolites while searching by mass values measured using mass spectrometry. We developed a search system named UC2 (Unique Connectivity of Uncharged Compounds), where compounds are tentatively neutralized into uncharged states and stored on the basis of their unique connectivity of atoms after removing their stereochemical information using the first block in the hash of the IUPAC International Chemical Identifier, by which false-positive hits are remarkably reduced, both charged and uncharged compounds are properly searched in a single query and records having a unique connectivity are compiled in a single search result. Availability and implementation: The UC2 search tool is available free of charge as a REST web service (http://webs2.kazusa.or.jp/mfsearcher) and a Java-based GUI tool. Contact: sakurai@kazusa.or.jp. Supplementary information: Supplementary data are available at Bioinformatics online.

Co-expressed Pathways DataBase for Tomato: a database to predict pathways relevant to a query gene.

BACKGROUND: Gene co-expression, the similarity of gene expression profiles under various experimental conditions, has been used as an indicator of functional relationships between genes, and many co-expression databases have been developed for predicting gene functions. These databases usually provide users with a co-expression network and a list of strongly co-expressed genes for a query gene. Several of these databases also provide functional information on a set of strongly co-expressed genes (i.e., provide biological processes and pathways that are enriched in these strongly co-expressed genes), which is generally analyzed via over-representation analysis (ORA). A limitation of this approach may be that users can predict gene functions only based on the strongly co-expressed genes. RESULTS: In this study, we developed a new co-expression database that enables users to predict the function of tomato genes from the results of functional enrichment analyses of co-expressed genes while considering the genes that are not strongly co-expressed. To achieve this, we used the ORA approach with several thresholds to select co-expressed genes, and performed gene set enrichment analysis (GSEA) applied to a ranked list of genes ordered by the co-expression degree. We found that internal correlation in pathways affected the significance levels of the enrichment analyses. Therefore, we introduced a new measure for evaluating the relationship between the gene and pathway, termed the percentile (p)-score, which enables users to predict functionally relevant pathways without being affected by the internal correlation in pathways. In addition, we evaluated our approaches using receiver operating characteristic curves, which concluded that the p-score could improve the performance of the ORA. CONCLUSIONS: We developed a new database, named Co-expressed Pathways DataBase for Tomato, which is available at http://cox-path-db.kazusa.or.jp/tomato . The database allows users to predict pathways that are relevant to a query gene, which would help to infer gene functions.

FlavonoidSearch: A system for comprehensive flavonoid annotation by mass spectrometry.

Currently, in mass spectrometry-based metabolomics, limited reference mass spectra are available for flavonoid identification. In the present study, a database of probable mass fragments for 6,867 known flavonoids (FsDatabase) was manually constructed based on new structure- and fragmentation-related rules using new heuristics to overcome flavonoid complexity. We developed the FlavonoidSearch system for flavonoid annotation, which consists of the FsDatabase and a computational tool (FsTool) to automatically search the FsDatabase using the mass spectra of metabolite peaks as queries. This system showed the highest identification accuracy for the flavonoid aglycone when compared to existing tools and revealed accurate discrimination between the flavonoid aglycone and other compounds. Sixteen new flavonoids were found from parsley, and the diversity of the flavonoid aglycone among different fruits and vegetables was investigated.

Ectopic expression of AtDGAT1, encoding diacylglycerol O-acyltransferase exclusively committed to TAG biosynthesis, enhances oil accumulation in seeds and leaves of Jatropha.

BACKGROUND: Jatropha curcas is an important biofuel crop due to the presence of high amount of oil in its seeds suitable for biodiesel production. Triacylglycerols (TAGs) are the most abundant form of storage oil in plants. Diacylglycerol O-acyltransferase (DGAT1) enzyme is responsible for the last and only committed step in seed TAG biosynthesis. Direct upregulation of TAG biosynthesis in seeds and vegetative tissues through overexpression of the DGAT1 could enhance the energy density of the biomass, making significant impact on biofuel production. RESULTS: The enzyme diacylglycerol O-acyltransferase is the rate-limiting enzyme responsible for the TAG biosynthesis in seeds. We generated transgenic Jatropha ectopically expressing an Arabidopsis DGAT1 gene through Agrobacterium-mediated transformation. The resulting AtDGAT1 transgenic plants showed a dramatic increase in lipid content by 1.5- to 2 fold in leaves and 20-30 % in seeds, and an overall increase in TAG and DAG, and lower free fatty acid (FFA) levels compared to the wild-type plants. The increase in oil content in transgenic plants is accompanied with increase in average plant height, seeds per tree, average 100-seed weight, and seed length and breadth. The enhanced TAG accumulation in transgenic plants had no penalty on the growth rates, growth patterns, leaf number, and leaf size of plants. CONCLUSIONS: In this study, we produced transgenic Jatropha ectopically expressing AtDGAT1. We successfully increased the oil content by 20-30 % in seeds and 1.5- to 2.0-fold in leaves of Jatropha through genetic engineering. Transgenic plants had reduced FFA content compared with control plants. Our strategy of increasing energy density by enhancing oil accumulation in both seeds and leaves in Jatropha would make it economically more sustainable for biofuel production.