Efficient de novo production of bioactive cordycepin by Aspergillus oryzae using a food-grade expression platform.

BACKGROUND: Cordycepin (3'-deoxyadenosine) is an important bioactive compound in medical and healthcare markets. The drawbacks of commercial cordycepin production using Cordyceps spp. include long cultivation periods and low cordycepin yields. To overcome these limitations and meet the increasing market demand, the efficient production of cordycepin by the GRAS-status Aspergillus oryzae strain using a synthetic biology approach was developed in this study. RESULTS: An engineered strain of A. oryzae capable of cordycepin production was successfully constructed by overexpressing two metabolic genes (cns1 and cns2) involved in cordycepin biosynthesis under the control of constitutive promoters. Investigation of the flexibility of carbon utilization for cordycepin production by the engineered A. oryzae strain revealed that it was able to utilize C6-, C5-, and C12-sugars as carbon sources, with glucose being the best carbon source for cordycepin production. High cordycepin productivity (564.64 ± 9.59 mg/L/d) was acquired by optimizing the submerged fermentation conditions. CONCLUSIONS: This study demonstrates a powerful production platform for bioactive cordycepin production by A. oryzae using a synthetic biology approach. An efficient and cost-effective fermentation process for cordycepin production using an engineered strain was established, offering a powerful alternative source for further upscaling.

Functional insight into Cordyceps militaris sugar transporters by structure modeling, network analysis and allosteric regulation.

Insights into the structures, functions and dynamics of Cordyceps militaris (C. militaris) sugar transporters are necessary for understanding their versatile metabolic capability for fungal growth. The sequence-function relationship study of 85 C. militaris sugar transporters showed that there is a gap between phylogenetic-based subfamily classification and their functions. Beyond protein sequences, structural modeling and principal component analysis of the structural ensemble revealed the different folds of the Car and Org subfamilies. Performing channel detection and network analysis found that the Alp and Hex subfamilies can be specifically distinguished from others by the betweenness of channel residues. Signature dynamics analysis further suggested that the Hex subfamily demonstrates different dynamics, with high flexibility at the H1 region in TM11. Furthermore, the H1 region as an allosteric site was examined by network parameter calculations that guided allosteric pathways between this region and the channel cavity. Together with gene expression data of C. militaris, e.g., Hex06741 in the Hex subfamily, it was promisingly expressed when sugar utilization was altered. This work demonstrates an in silico framework for investigating C. militaris sugar transporters as an example case study of the allosteric activity of the Hex subfamily and can facilitate sugar transporter engineering design that can further optimize the preferable sugar utilization and fermentation process of C. militaris.

MetGEMs Toolbox: Metagenome-scale models as integrative toolbox for uncovering metabolic functions and routes of human gut microbiome.

Investigating metabolic functional capability of a human gut microbiome enables the quantification of microbiome changes, which can cause a phenotypic change of host physiology and disease. One possible way to estimate the functional capability of a microbial community is through inferring metagenomic content from 16S rRNA gene sequences. Genome-scale models (GEMs) can be used as scaffold for functional estimation analysis at a systematic level, however up to date, there is no integrative toolbox based on GEMs for uncovering metabolic functions. Here, we developed the MetGEMs (metagenome-scale models) toolbox, an open-source application for inferring metabolic functions from 16S rRNA gene sequences to facilitate the study of the human gut microbiome by the wider scientific community. The developed toolbox was validated using shotgun metagenomic data and shown to be superior in predicting functional composition in human clinical samples compared to existing state-of-the-art tools. Therefore, the MetGEMs toolbox was subsequently applied for annotating putative enzyme functions and metabolic routes related in human disease using atopic dermatitis as a case study.

Identification of potential candidate genes involved in the sex determination cascade in an aquatic firefly, Sclerotia aquatilis (Coleoptera, Lampyridae).

Sexual differentiation, dimorphism, and courtship behavior are the downstream developmental programs of the sex determination cascade. The sex determination cascade in arthropods often involves key genes, transformer (tra), doublesex (dsx), transformer-2 (tra2), and fruitless (fru). These genes are conserved among insect taxa; however, they have never been reported in fireflies. In this study, the candidate genes for these key genes were identified for the first time in an aquatic firefly, Sclerotia aquatilis using transcriptome analysis. A comparative protein-protein interaction (PPI) network of sex determination cascade was reconstructed for S. aquatilis based on a network of a model insect, Drosophila melanogaster. Subsequently, a sex determination cascade in S. aquatilis was proposed based on the amino acid sequence structures and expression profiles of these candidates. This study describes the first efforts toward understanding the molecular control of sex determination cascade in fireflies.

Alternative metabolic routes in channeling xylose to cordycepin production of Cordyceps militaris identified by comparative transcriptome analysis.

The responsive mechanism of C. militaris TBRC7358 on xylose utilization was investigated by comparative analysis of transcriptomes, growth kinetics and cordycepin productions. The result showed that the culture grown on xylose exhibited high production yield of cordycepin on dry biomass. Comparing xylose to other carbon sources, a set of significantly up-regulated genes in xylose were enriched in pentose and glucuronate interconversion, and cordycepin biosynthesis. After validating up-regulated genes using quantitative real-time PCR, interestingly, putative alternative 3'-AMP-associated metabolic route on cordycepin biosynthesis was identified. Through reporter metabolites analysis of C. militaris, significant metabolites (e.g., AMP, glycine and L-glutamate) were identified guiding involvement of growth and cordycepin production. These findings suggested that there was a cooperative mechanism in transcriptional control of the supplying precursors pool directed towards the cordycepin biosynthesis through main and putative alternative metabolic routes for leverage of cell growth and cordycepin production on xylose of C. militaris strain TBRC7358.

Iron-associated protein interaction networks reveal the key functional modules related to survival and virulence of Pasteurella multocida.

Pasteurella multocida causes respiratory infectious diseases in a multitude of birds and mammals. A number of virulence-associated genes were reported across different strains of P. multocida, including those involved in the iron transport and metabolism. Comparative iron-associated genes of P. multocida among different animal hosts towards their interaction networks have not been fully revealed. Therefore, this study aimed to identify the iron-associated genes from core- and pan-genomes of fourteen P. multocida strains and to construct iron-associated protein interaction networks using genome-scale network analysis which might be associated with the virulence. Results showed that these fourteen strains had 1587 genes in the core-genome and 3400 genes constituting their pan-genome. Out of these, 2651 genes associated with iron transport and metabolism were selected to construct the protein interaction networks and 361 genes were incorporated into the iron-associated protein interaction network (iPIN) consisting of nine different iron-associated functional modules. After comparing with the virulence factor database (VFDB), 21 virulence-associated proteins were determined and 11 of these belonged to the heme biosynthesis module. From this study, the core heme biosynthesis module and the core outer membrane hemoglobin receptor HgbA were proposed as candidate targets to design novel antibiotics and vaccines for preventing pasteurellosis across the serotypes or animal hosts for enhanced precision agriculture to ensure sustainability in food security.

Informatics for Metabolomics.

Metabolome profiling of biological systems has the powerful ability to provide the biological understanding of their metabolic functional states responding to the environmental factors or other perturbations. Tons of accumulative metabolomics data have thus been established since pre-metabolomics era. This is directly influenced by the high-throughput analytical techniques, especially mass spectrometry (MS)- and nuclear magnetic resonance (NMR)-based techniques. Continuously, the significant numbers of informatics techniques for data processing, statistical analysis, and data mining have been developed. The following tools and databases are advanced for the metabolomics society which provide the useful metabolomics information, e.g., the chemical structures, mass spectrum patterns for peak identification, metabolite profiles, biological functions, dynamic metabolite changes, and biochemical transformations of thousands of small molecules. In this chapter, we aim to introduce overall metabolomics studies from pre- to post-metabolomics era and their impact on society. Directing on post-metabolomics era, we provide a conceptual framework of informatics techniques for metabolomics and show useful examples of techniques, tools, and databases for metabolomics data analysis starting from preprocessing toward functional interpretation. Throughout the framework of informatics techniques for metabolomics provided, it can be further used as a scaffold for translational biomedical research which can thus lead to reveal new metabolite biomarkers, potential metabolic targets, or key metabolic pathways for future disease therapy.

The RAVEN toolbox and its use for generating a genome-scale metabolic model for Penicillium chrysogenum.

We present the RAVEN (Reconstruction, Analysis and Visualization of Metabolic Networks) Toolbox: a software suite that allows for semi-automated reconstruction of genome-scale models. It makes use of published models and/or the KEGG database, coupled with extensive gap-filling and quality control features. The software suite also contains methods for visualizing simulation results and omics data, as well as a range of methods for performing simulations and analyzing the results. The software is a useful tool for system-wide data analysis in a metabolic context and for streamlined reconstruction of metabolic networks based on protein homology. The RAVEN Toolbox workflow was applied in order to reconstruct a genome-scale metabolic model for the important microbial cell factory Penicillium chrysogenum Wisconsin54-1255. The model was validated in a bibliomic study of in total 440 references, and it comprises 1471 unique biochemical reactions and 1006 ORFs. It was then used to study the roles of ATP and NADPH in the biosynthesis of penicillin, and to identify potential metabolic engineering targets for maximization of penicillin production.

Performance comparison and evaluation of software tools for microRNA deep-sequencing data analysis.

With the development of next-generation sequencing (NGS) techniques, many software tools have emerged for the discovery of novel microRNAs (miRNAs) and for analyzing the miRNAs expression profiles. An overall evaluation of these diverse software tools is lacking. In this study, we evaluated eight software tools based on their common feature and key algorithms. Three deep-sequencing data sets were collected from different species and used to assess the computational time, sensitivity and accuracy of detecting known miRNAs as well as their capacity for predicting novel miRNAs. Our results provide useful information for researchers to facilitate their selection of the optimal software tools for miRNA analysis depending on their specific requirements, i.e. novel miRNAs discovery or miRNA expression profile analysis of sequencing data sets.

Unravelling evolutionary strategies of yeast for improving galactose utilization through integrated systems level analysis.

Identification of the underlying molecular mechanisms for a derived phenotype by adaptive evolution is difficult. Here, we performed a systems-level inquiry into the metabolic changes occurring in the yeast Saccharomyces cerevisiae as a result of its adaptive evolution to increase its specific growth rate on galactose and related these changes to the acquired phenotypic properties. Three evolved mutants (62A, 62B, and 62C) with higher specific growth rates and faster specific galactose uptake were isolated. The evolved mutants were compared with a reference strain and two engineered strains, SO16 and PGM2, which also showed higher galactose uptake rate in previous studies. The profile of intermediates in galactose metabolism was similar in evolved and engineered mutants, whereas reserve carbohydrates metabolism was specifically elevated in the evolved mutants and one evolved strain showed changes in ergosterol biosynthesis. Mutations were identified in proteins involved in the global carbon sensing Ras/PKA pathway, which is known to regulate the reserve carbohydrates metabolism. We evaluated one of the identified mutations, RAS2(Tyr112), and this mutation resulted in an increased specific growth rate on galactose. These results show that adaptive evolution results in the utilization of unpredicted routes to accommodate increased galactose flux in contrast to rationally engineered strains. Our study demonstrates that adaptive evolution represents a valuable alternative to rational design in bioengineering of improved strains and, that through systems biology, it is possible to identify mutations in evolved strain that can serve as unforeseen metabolic engineering targets for improving microbial strains for production of biofuels and chemicals.

Uncovering nutrients and energy related gene functions of black soldier fly Hermetia illucens strain KUP.

The black soldier fly (Hermetia illucens) has emerged as a significant insect species in the decomposition of organic waste for sustainable agricultural practices. Due to its remarkable characteristics and performance, H. illucens is increasingly utilised for insect farming, particularly for industrial-scale rearing throughout the world. In this study, we employed whole-genome sequencing to annotate the gene and protein functions of H. illucens and to explore the functional genomics related to nutrients and energy. As a result, a genome size of H. illucens strain KUP 1.68 Gb with a GC content of 42.13 % was achieved. Of the 14,036 coding sequences, we determined the function of 12,046 protein-coding genes. Based on metabolic functional assignment, we classified 4,218 protein-coding genes; the main category was metabolism (32.86 %). Comparative genomic analysis across the other H. illucens strain and insect species revealed that the major metabolic gene functions and pathways related to nutrient and energy sources of H. illucens KUP are involved in key amino acid metabolism (e.g., cysteine and methionine) as well as fatty acid biosynthesis and glycerolipid metabolism. These findings underscore the metabolic capability and versatility of H. illucens, which is regarded as a potential source of proteins and lipids. Our study contributes to the knowledge regarding the feed utilisation of H. illucens and offers insights into transforming waste into valuable products. H. illucens has the potential to create globally sustainable nutrients and environmentally friendly solutions, aligning with the goal of responsible resource utilisation.

Holistic transcriptional responses of Cordyceps militaris to different culture temperatures.

Cordyceps militaris is a medicinal entomopathogenic fungus containing valuable biometabolites for pharmaceutical applications. Its genetic inheritance and environmental factors play a crucial role in the production of biomass enriched with cordycepin. While temperature is a crucial controlled parameter for fungal cultivation, its impacts on growth and metabolite biosynthesis remains poorly characterized. This study aimed to investigate the metabolic responses and cordycepin production of C. militaris strain TBRC6039 under various temperature conditions through transcriptome analysis. Among 9599 expressed genes, 576 genes were significantly differentially expressed at culture temperatures of 15 and 25 °C. The changes in the transcriptional responses induced by these temperatures were found in several metabolisms involved in nutrient assimilation and energy source, including amino acids metabolism (e.g., glycine, serine and threonine metabolism) and lipid metabolism (e.g., biosynthesis of unsaturated fatty acids and steroid biosynthesis). At the lower temperature (15 °C), the biosynthetic pathways of lipids, specifically ergosterol and squalene, were the target for maintaining membrane function by transcriptional upregulation. Our study revealed the responsive mechanisms of C. militaris in acclimatization to temperature conditions that provide an insight on physiological manipulation for the production of metabolites by C. militaris.

Preliminary characterization of gut mycobiome enterotypes reveals the correlation trends between host metabolic parameter and diet: a case study in the Thai Cohort.

The association between the gut mycobiome and its potential influence on host metabolism in the Thai Cohort was assessed. Two distinct predominant enterotypes, Saccharomyces (Sa) and Aspergillus/Penicillium (Ap/Pe) showed differences in gut mycobiota diversity and composition. Notably, the Sa enterotype exhibited lower evenness and richness, likely due to the prevalence of Saccharomyces, while both enterotypes displayed unique metabolic behaviors related to nutrient metabolism and body composition. Fiber consumption was positively correlated with adverse body composition and fasting glucose levels in individuals with the Sa enterotype, whereas in the Ap/Pe enterotype it was positively correlated with fat and protein intake. The metabolic functional analysis revealed the Sa enterotype associated with carbohydrate metabolism, while the Ap/Pe enterotype involved in lipid metabolism. Very interestingly, the genes involved in the pentose and glucuronate interconversion pathway, such as polygalacturonase and L-arabinose-isomerase, were enriched in the Sa enterotype signifying a metabolic capacity for complex carbohydrate degradation and utilization of less common sugars as energy sources. These findings highlight the interplay between gut mycobiome composition, dietary habits, and metabolic outcomes within the Thai cohort studies.

Light-Exposed Metabolic Responses of Cordyceps militaris through Transcriptome-Integrated Genome-Scale Modeling.

The genome-scale metabolic model (GSMM) of Cordyceps militaris provides a comprehensive basis of carbon assimilation for cell growth and metabolite production. However, the model with a simple mass balance concept shows limited capability to probe the metabolic responses of C. militaris under light exposure. This study, therefore, employed the transcriptome-integrated GSMM approach to extend the investigation of C. militaris's metabolism under light conditions. Through the gene inactivity moderated by metabolism and expression (GIMME) framework, the iPS1474-tiGSMM model was furnished with the transcriptome data, thus providing a simulation that described reasonably well the metabolic responses underlying the phenotypic observation of C. militaris under the particular light conditions. The iPS1474-tiGSMM obviously showed an improved prediction of metabolic fluxes in correlation with the expressed genes involved in the cordycepin and carotenoid biosynthetic pathways under the sucrose culturing conditions. Further analysis of reporter metabolites suggested that the central carbon, purine, and fatty acid metabolisms towards carotenoid biosynthesis were the predominant metabolic processes responsible in light conditions. This finding highlights the key responsive processes enabling the acclimatization of C. militaris metabolism in varying light conditions. This study provides a valuable perspective on manipulating metabolic genes and fluxes towards the target metabolite production of C. militaris.

Follicular fluid-derived exosomal HMOX1 promotes granulosa cell ferroptosis involved in follicular atresia in geese (Anser cygnoides).

The proliferation and death of granulosa cells (GCs) in poultry play a decisive role in follicular fate and egg production. The follicular fluid (FF) contains a variety of nutrients and genetic substances to ensure the communication between follicular cells. Exosomes, as a new intercellular communication, could carry and transport the proteins, RNA, and lipids to react on GCs, which had been found in FF of various domestic animals. Whether exosomes of FF in poultry play a similar role is unclear. In this study, geese, a poultry with low egg production, were chosen, and the effect of FF exosomes on the proliferation and death of GCs was investigated. Firstly, there were not only a large number of healthy small yellow follicles (HSYFs) but also some atresia small yellow follicles (ASYFs) in the egg-laying stage. Also, the GC layers of ASYFs became loose interconnections, inward detachment, and diminished survival rate than that of HSYFs. Besides, compared to HSYFs, the contents of E2, P4, and the mRNA expression levels of ferroptosis-related genes GPX4, FPN1, and FTH1 were significantly decreased, while COX2, NCOA4, VDAC3 mRNA were significantly increased, and the structure of mitochondrial cristae disappeared and the outer membrane broke in the GC layers of ASYFs. Moreover, the ROS, MDA, and oxidation levels in the GC layers of ASYFs were significantly higher than those of HSYFs. All these hinted that ferroptosis might result in a large number of GCs death and involvement in follicle atresia. Secondly, FF exosomes were isolated from HSYFs and ASYFs, respectively, and identified by TEM, NTA, and detection of exosome marker proteins. Also, we found the exosomes were phagocytic by GCs by tracking CM-Dil. Moreover, the addition of ASYF-FF exosomes significantly elevated the MDA content, Fe2+ levels, and the mitochondrial membrane potential (MMP) in GCs, thus significantly inhibiting the proliferation of GCs, which was restored by the ferroptosis inhibitor ferrostatin-1. Thirdly, the proteomic sequencing was performed between FF-derived exosomes of HSYFs and ASYFs. We obtained 1615 differentially expressed proteins, which were mainly enriched in the protein transport and ferroptosis pathways. Among them, HMOX1 was enriched in the ferroptosis pathway based on differential protein-protein interaction network analysis. Finally, the role of HMOX1 in regulating ferroptosis in GCs was further explored. The highly expressed HMOX1 was observed in the exosomes of ASYF-FF than that in HSYF-FF. Overexpression of HMOX1 increased ATG5, LC3II, and NCOA4 expression and reduced the expression of FTH1, GPX4, PCBP2, FPN1 in the ferroptosis pathway, also promoted intracellular Fe2+ accumulation and MDA surge, which drove ferroptosis in GCs. The effects of HMOX1 on ferroptosis could be blocked by its inhibitor Znpp. Taken together, the important protein HMOX1 was identified in FF, which could be delivered to GCs via exosomes, triggering ferroptosis and thus determining the fate of follicles.

Dissecting Holistic Metabolic Acclimatization of Mucor circinelloides WJ11 Defective in Carotenoid Biosynthesis.

Mucor circinelloides WJ11 is a lipid-producing strain with industrial potential. A holistic approach using gene manipulation and bioprocessing development has improved lipid production and the strain's economic viability. However, the systematic regulation of lipid accumulation and carotenoid biosynthesis in M. circinelloides remains unknown. To dissect the metabolic mechanism underlying lipid and carotenoid biosynthesis, transcriptome analysis and reporter metabolites identification were implemented between the wild-type (WJ11) and ΔcarRP WJ11 strains of M. circinelloides. As a result, transcriptome analysis revealed 10,287 expressed genes, with 657 differentially expressed genes (DEGs) primarily involved in amino acid, carbohydrate, and energy metabolism. Integration with a genome-scale metabolic model (GSMM) identified reporter metabolites in the ΔcarRP WJ11 strain, highlighting metabolic pathways crucial for amino acid, energy, and nitrogen metabolism. Notably, the downregulation of genes associated with carotenoid biosynthesis and acetyl-CoA generation suggests a coordinated relationship between the carotenoid and fatty acid biosynthesis pathways. Despite disruptions in the carotenoid pathway, lipid production remains stagnant due to reduced acetyl-CoA availability, emphasizing the intricate metabolic interplay. These findings provide insights into the coordinated relationship between carotenoid and fatty acid biosynthesis in M. circinelloides that are valuable in applied research to design optimized strains for producing desired bioproducts through emerging technology.

Post genome-wide association studies functional characterization of prostate cancer risk loci.

BACKGROUND: Over the last decade, genome-wide association studies (GWAS) have discovered many risk associated single nucleotide polymorphisms (SNPs) of prostate cancer (PCa). However, the majority of the associated PCa SNPs, including those in linkage disequilibrium (LD) blocks, are generally not located in protein coding regions. The systematical investigation of the functional roles of these SNPs, especially the non-coding SNPs, becomes very necessary and helpful to the understanding of the molecular mechanism of PCa. RESULTS: In this work, we proposed a comprehensive framework at network level to integrate the SNP annotation, target gene assignment, gene ontology (GO) classification, pathway enrichment analysis and regulatory network reconstruction to illustrate the molecular functions of PCa associated SNPs. By LD expansion, we first identified 1828 LD SNPs using 49 reported GWAS SNPs as a start. We carefully annotated these 1828 LD SNPs via either UCSC known genes, UCSC regulation elements, or expression Quantitative Trait Loci (eQTL) data. As a result, we found 1154 SNPs were functionally annotated and obtained 205 unique PCa genes for further enrichment analysis. The enriched GO biological processes and pathways were found mainly related to regulation of cell death, apoptosis, cell proliferation, and metabolic process, which have been proved essential to cancer development. We constructed PCa genes specific transcription regulatory networks, finding several important genetic regulators for PCa, such as IGF-1/IGF-2 receptors, SP1, CREB1, and androgen receptor (AR). CONCLUSIONS: A comprehensive framework was proposed for integrative and systematic analysis of PCa SNPs, the analysis can provide essential information for the understanding of the regulatory function of GWAS SNPs in PCa, and will facilitate the discovery of novel candidate biomarkers for diagnosis and prognosis of PCa.

Biomedical text mining and its applications in cancer research.

Cancer is a malignant disease that has caused millions of human deaths. Its study has a long history of well over 100years. There have been an enormous number of publications on cancer research. This integrated but unstructured biomedical text is of great value for cancer diagnostics, treatment, and prevention. The immense body and rapid growth of biomedical text on cancer has led to the appearance of a large number of text mining techniques aimed at extracting novel knowledge from scientific text. Biomedical text mining on cancer research is computationally automatic and high-throughput in nature. However, it is error-prone due to the complexity of natural language processing. In this review, we introduce the basic concepts underlying text mining and examine some frequently used algorithms, tools, and data sets, as well as assessing how much these algorithms have been utilized. We then discuss the current state-of-the-art text mining applications in cancer research and we also provide some resources for cancer text mining. With the development of systems biology, researchers tend to understand complex biomedical systems from a systems biology viewpoint. Thus, the full utilization of text mining to facilitate cancer systems biology research is fast becoming a major concern. To address this issue, we describe the general workflow of text mining in cancer systems biology and each phase of the workflow. We hope that this review can (i) provide a useful overview of the current work of this field; (ii) help researchers to choose text mining tools and datasets; and (iii) highlight how to apply text mining to assist cancer systems biology research.

Transcriptome Landscapes of Salt-Susceptible Rice Cultivar IR29 Associated with a Plant Growth Promoting Endophytic Streptomyces.

Plant growth-promoting endophytic (PGPE) actinomycetes have been known to enhance plant growth and mitigate plant from abiotic stresses via their PGP-traits. In this study, PGPE Streptomyces sp. GKU 895 promoted growth and alleviated salt tolerance of salt-susceptible rice cultivar IR29 by augmentation of plant weight and declined ROS after irrigation with 150 mM NaCl in a pot experiment. Transcriptome analysis of IR29 exposed to the combination of strain GKU 895 and salinity demonstrated up and downregulated differentially expressed genes (DEGs) classified by gene ontology and plant reactome. Streptomyces sp. GKU 895 induced changes in expression of rice genes including transcription factors under salt treatment which involved in growth and development, photosynthesis, plant hormones, ROS scavenging, ion transport and homeostasis, and plant-microbe interactions regarding pathogenesis- and symbiosis-related proteins. Taken together, these data demonstrate that PGPE Streptomyces sp. GKU 895 colonized and enhanced growth of rice IR29 and triggered salt tolerance phenotype. Our findings suggest that utilisation of beneficial endophytes in the saline fields could allow for the use of such marginal soils for growing rice and possibly other crops.

Uncovering global lipid accumulation routes towards docosahexaenoic acid (DHA) production in Aurantiochytrium sp. SW1 using integrative proteomic analysis.

Aurantiochytrium sp., a marine thraustochytrid possesses a remarkable ability to produce lipid rich in polyunsaturated fatty acids (PUFAs), such as docosahexaenoic acid (DHA). Although gene regulation underlying lipid biosynthesis has been previously reported, proteomic analysis is still limited. In this study, high DHA accumulating strain Aurantiochytrium sp. SW1 has been used as a study model to elucidate the alteration in proteome profile under different cultivation phases i.e. growth, nitrogen-limitation and lipid accumulation. Of the total of 5146 identified proteins, 852 proteins were differentially expressed proteins (DEPs). The largest number of DEPs (488 proteins) was found to be uniquely expressed between lipid accumulating phase and growth phase. Interestingly, there were up-regulated proteins involved in glycolysis, glycerolipid, carotenoid and glutathione metabolism which were preferable metabolic routes towards lipid accumulation and DHA production as well as cellular oxidative defence. Integrated proteomic and transcriptomic data were also conducted to comprehend the gene and protein regulation underlying the lipid and DHA biosynthesis. A significant up-regulation of acetyl-CoA synthetase was observed which suggests alternative route of acetate metabolism for acetyl-CoA producer. This study presents the holistic routes underlying lipid accumulation and DHA production in Aurantiochytrium sp. SW1 and other relevant thraustochytrid.