Transcriptomics aids in uncovering the metabolic shifts and molecular machinery of Schizochytrium limacinum during biotransformation of hydrophobic substrates to docosahexaenoic acid.

BACKGROUND: Biotransformation of waste oil into value-added nutraceuticals provides a sustainable strategy. Thraustochytrids are heterotrophic marine protists and promising producers of omega (ω) fatty acids. Although the metabolic routes for the assimilation of hydrophilic carbon substrates such as glucose are known for these microbes, the mechanisms employed for the conversion of hydrophobic substrates are not well established. Here, thraustochytrid Schizochytrium limacinum SR21 was investigated for its ability to convert oils (commercial oils with varying fatty acid composition and waste cooking oil) into ω-3 fatty acid; docosahexaenoic acid (DHA). RESULTS: Within 72 h SR21 consumed ~ 90% of the oils resulting in enhanced biomass (7.5 g L- 1) which was 2-fold higher as compared to glucose. Statistical analysis highlights C16 fatty acids as important precursors of DHA biosynthesis. Transcriptomic data indicated the upregulation of multiple lipases, predicted to possess signal peptides for secretory, membrane-anchored and cytoplasmic localization. Additionally, transcripts encoding for mitochondrial and peroxisomal ß-oxidation along with acyl-carnitine transporters were abundant for oil substrates that allowed complete degradation of fatty acids to acetyl CoA. Further, low levels of oxidative biomarkers (H2O2, malondialdehyde) and antioxidants were determined for hydrophobic substrates, suggesting that SR21 efficiently mitigates the metabolic load and diverts the acetyl CoA towards energy generation and DHA accumulation. CONCLUSIONS: The findings of this study contribute to uncovering the route of assimilation of oil substrates by SR21. The thraustochytrid employs an intricate crosstalk among the extracellular and intracellular molecular machinery favoring energy generation. The conversion of hydrophobic substrates to DHA can be further improved using synthetic biology tools, thereby providing a unique platform for the sustainable recycling of waste oil substrates.

Ameliorating microalgal OMEGA production using omics platforms.

Over the past decade, the focus on omega (ω)-3 fatty acids from microalgae has intensified due to their diverse health benefits. Bioprocess optimization has notably increased ω-3 fatty acid yields, yet understanding of the genetic architecture and metabolic pathways of high-yielding strains remains limited. Leveraging genomics, transcriptomics, proteomics, and metabolomics tools can provide vital system-level insights into native ω-3 fatty acid-producing microalgae, further boosting production. In this review, we explore 'omics' studies uncovering alternative pathways for ω-3 fatty acid synthesis and genome-wide regulation in response to cultivation parameters. We also emphasize potential targets to fine-tune in order to enhance yield. Despite progress, an integrated omics platform is essential to overcome current bottlenecks in optimizing the process for ω-3 fatty acid production from microalgae, advancing this crucial field.

Integrating Target and Shadow Features for SAR Target Recognition.

Synthetic aperture radar (SAR) sensor often produces a shadow in pairs with the target due to its slant-viewing imaging. As a result, shadows in SAR images can provide critical discriminative features for classifiers, such as target contours and relative positions. However, shadows possess unique properties that differ from targets, such as low intensity and sensitivity to depression angles, making it challenging to extract depth features from shadows directly using convolutional neural networks (CNN). In this paper, we propose a new SAR image-classification framework to utilize target and shadow information comprehensively. First, we design a SAR image segmentation method to extract target regions and shadow masks. Second, based on SAR projection geometry, we propose a data-augmentation method to compensate for the geometric distortion of shadows due to differences in depression angles. Finally, we introduce a feature-enhancement module (FEM) based on depthwise separable convolution (DSC) and convolutional block attention module (CBAM), enabling deep networks to fuse target and shadow features adaptively. The experimental results on the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset show that when only using target and shadow information, the published deep-learning models can still achieve state-of-the-art performance after embedding the FEM.

Metabolomic response of microalgae towards diclofenac sodium during its removal from water and concomitant recovery of pigments and lipids.

The aim of this work was to assess the efficiency of freshwater green microalga, Chlorella sorokiniana for diclofenac sodium (DFS) removal, and metabolic response of alga to comprehend the metabolic pathways involved/affected during DFS decontamination. Results showed 91.51 % removal of DFS could be achieved within 9 days of algal treatment along with recovery of enhanced value-added bioresources i.e. chlorophyll, carotenoids, and lipids from the spent biomass. DFS also had an effect on enzyme activity including superoxide dismutase (SOD), catalase (CAT), and lipid peroxidation (MDA). Furthermore, metabolomics profiling provided an in-depth insight into changes in the metabolic response of C. sorokiniana wherein DFS induced 32 metabolites in microalgae compared to unexposed-control. This study offers microalgae as a green option for DFS removal, and the metabolomics study complemented with DFS could be an approach to understand the stress-induced strategies of C. sorokiniana for concomitant value-added products recovery in presence of DFS.

Channeling of Carbon Flux Towards Carotenogenesis in Botryococcus braunii: A Media Engineering Perspective.

Microalgae, due to their unique properties, gained attention for producing promising feedstocks having high contents of proteins, antioxidants, carotenoids, and terpenoids for applications in nutraceutical and pharmaceutical industries. Optimizing production of the high-value renewables (HVRs) in microalgae requires an in-depth understanding of their functional relationship of the genes involved in these metabolic pathways. In the present study, bioinformatic tools were employed for characterization of the protein-encoding genes of methyl erythritol phosphate (MEP) pathway involved in carotenoid and squalene biosynthesis based upon their conserved motif/domain organization. Our analysis demonstrates nearly 200 putative genes showing a conservation pattern within divergent microalgal lineages. Furthermore, phylogenomic studies confirm the close evolutionary proximity among these microalgal strains in the carotenoid and squalene biosynthetic pathways. Further analysis employing STRING predicts interactions among two rate-limiting genes, i.e., phytoene synthase (PSY) and farnesyl diphosphate farnesyl synthase (FPPS), which are specifically involved in the synthesis of carotenoids and squalene. Experimentally, to understand the carbon flux of these rate-limiting genes involved in carotenogenesis, an industrial potential strain, namely, Botryococcus braunii, was selected in this study for improved biomass productivity (i.e., 100 mg L-1 D-1) along with enhanced carotenoid content [0.18% dry cell weight (DCW)] when subjected to carbon supplementation. In conclusion, our approach of media engineering demonstrates that the channeling of carbon flux favors carotenogenesis rather than squalene synthesis. Henceforth, employing omics perspectives will further provide us with new insights for engineering regulatory networks for enhanced production of high-value carbon biorenewables without compromising growth.

Photosynthetic Carbon Partitioning and Metabolic Regulation in Response to Very-Low and High CO2 in Microchloropsis gaditana NIES 2587.

Photosynthetic organisms fix inorganic carbon through carbon capture machinery (CCM) that regulates the assimilation and accumulation of carbon around ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco). However, few constraints that govern the central carbon metabolism are regulated by the carbon capture and partitioning machinery. In order to divert the cellular metabolism toward lipids and/or biorenewables it is important to investigate and understand the molecular mechanisms of the CO2-driven carbon partitioning. In this context, strategies for enhancement of CO2 fixation which will increase the overall biomass and lipid yields, can provide clues on understanding the carbon assimilation pathway, and may lead to new targets for genetic engineering in microalgae. In the present study, we have focused on the physiological and metabolomic response occurring within marine oleaginous microalgae Microchloropsis gaditana NIES 2587, under the influence of very-low CO2 (VLC; 300 ppm, or 0.03%) and high CO2 (HC; 30,000 ppm, or 3% v/v). Our results demonstrate that HC supplementation in M. gaditana channelizes the carbon flux toward the production of long chain polyunsaturated fatty acids (LC-PUFAs) and also increases the overall biomass productivities (up to 2.0 fold). Also, the qualitative metabolomics has identified nearly 31 essential metabolites, among which there is a significant fold change observed in accumulation of sugars and alcohols such as galactose and phytol in VLC as compared to HC. In conclusion, our focus is to understand the entire carbon partitioning and metabolic regulation within these photosynthetic cell factories, which will be further evaluated through multiomics approach for enhanced productivities of biomass, biofuels, and bioproducts (B3).