DES2 is a fatty acid Delta 11 desaturase capable of synthesizing palmitvaccenic acid in the arbuscular mycorrhizal fungus Rhizophagus irregularis

Arbuscular mycorrhizal (AM) fungi are oleaginous organisms, and the most abundant fatty acyl moiety usually found in their lipids is palmitvaccenic acid (16:1Δ11cis). However, it is not known how this uncommon fatty acid species is made. Here, we have cloned two homologs of Lepidopteran fatty acyl-CoenzymeA Δ11 desaturases from the AM fungus Rhizophagus irregularis. Both enzymes, DES1 and DES2, are expressed in intraradicle mycelium and can complement the unsaturated fatty acid-requiring auxotrophic growth phenotype of the Saccharomyces cerevisiae ole1Δ mutant. DES1 expression leads almost exclusively to oleic acid (18:1Δ9cis) production, whereas DES2 expression results in the production of 16:1Δ11cis and vaccenic acid (18:1Δ11cis). DES2 therefore encodes a Δ11 desaturase that is likely to be responsible for the synthesis of 16:1Δ11cis in R. irregularis

Production of human milk fat substitute by engineered strains of Yarrowia lipolytica.

Human milk fat has a distinctive stereoisomeric structure where palmitic acid is esterified to the middle (sn-2) position on the glycerol backbone of the triacylglycerol and unsaturated fatty acids to the outer (sn-1/3) positions. This configuration allows for more efficient nutrient absorption in the infant gut. However, the fat used in most infant formulas originates from plants, which exclude palmitic acid from the sn-2 position. Oleaginous yeasts provide an alternative source of lipids for human nutrition. However, these yeasts also exclude palmitic acid from the sn-2 position of their triacylglycerol. Here we show that Yarrowia lipolytica can be engineered to produce triacylglycerol with more than 60% of the palmitic acid in the sn-2 position, by expression of lysophosphatidic acid acyltransferases with palmitoyl-Coenzyme A specificity. The engineered Y. lipolytica strains can be cultured on glycerol, glucose, palm oil or a mixture of substrates, under nitrogen limited condition, to produce triacylglycerol with a fatty acid composition that resembles human milk fat, in terms of the major molecular species (palmitic, oleic and linoleic acids). Culture on palm oil or a mixture of glucose and palm oil produced the highest lipid titre and a triacylglycerol composition that is most similar with human milk fat. Our data show that an oleaginous yeast can be engineered to produce a human milk fat substitute (β-palmitate), that could be used as an ingredient in infant formulas

An interesting case of right ovarian cyst torsion: case report

Ovarian torsion is a comparatively rare gynecological emergency. It commonly presents with complaints of acute abdominal pain, nausea, and vomiting. It occurs due to twisting of the ovarian pedicle leading to ischemic changes in the ovary. It can even result in complete loss of blood supply, eventually necrosis of the ovary. It is diagnosed clinically and can be confirmed on ultrasound color doppler. The management of ovarian torsion depends on the age of the patient, size of the mass, ovary condition, and USG findings. Early diagnosis and treatment of torsion are necessary to preserve the viability of the ovary. We are reporting a case of a 30-year-old female with right ovarian cyst torsion of size 6.3×6.8×6 cm. Once torsion is diagnosed surgery is the mainstay of treatment, either detorsion and ovariopexy or oophorectomy if the ovary cannot be salvaged.

Engineering the stereoisomeric structure of seed oil to mimic human milk fat

Human milk fat substitute (HMFS) is a class of structured lipid that is widely used as an ingredient in infant formulas. Like human milk fat, HMFS is characterised by enrichment of palmitoyl (C16:0) groups specifically at the middle (sn-2 or β) position on the glycerol backbone, and there is evidence that triacylglycerol (TAG) with this unusual stereoisomeric structure provides nutritional benefits. HMFS production currently relies on enzyme-based catalysis since there is no appropriate biological source of fat with the equivalent structure, other than humans. Most of the fat currently used in infant formulas is obtained from plants, which exclude C16:0 from the middle position. In this study we have modified the metabolic pathway for TAG biosynthesis in the model oilseed Arabidopsis thaliana to increase the percentage of C16:0 at the middle (versus outer) positions by more than 20-fold (i.e. from ~3% in wild type to >70% in our final iteration). This level of C16:0 enrichment is comparable to human milk fat. We achieved this by relocating the C16:0-specific chloroplast isoform of the enzyme lysophosphatidic acid acyltransferase (LPAT) to the endoplasmic reticulum so that it functions within the cytosolic glycerolipid biosynthetic pathway to esterify C16:0 to the middle position. We then suppressed endogenous LPAT activity to relieve competition and knocked out phosphatidylcholine:diacylglycerol cholinephosphotransferase activity to promote the flux of newly-made diacylglycerol directly into TAG. Applying this technology to oilseed crops might provide a new source of HMFS for infant formula

A multimodal deep learning framework using local feature representations for face recognition

YesThe most recent face recognition systems are mainly dependent on feature representations obtained using either local handcrafted-descriptors, such as local binary patterns (LBP), or use a deep learning approach, such as deep belief network (DBN). However, the former usually suffers from the wide variations in face images, while the latter usually discards the local facial features, which are proven to be important for face recognition. In this paper, a novel framework based on merging the advantages of the local handcrafted feature descriptors with the DBN is proposed to address the face recognition problem in unconstrained conditions. Firstly, a novel multimodal local feature extraction approach based on merging the advantages of the Curvelet transform with Fractal dimension is proposed and termed the Curvelet–Fractal approach. The main motivation of this approach is that theCurvelet transform, a newanisotropic and multidirectional transform, can efficiently represent themain structure of the face (e.g., edges and curves), while the Fractal dimension is one of the most powerful texture descriptors for face images. Secondly, a novel framework is proposed, termed the multimodal deep face recognition (MDFR)framework, to add feature representations by training aDBNon top of the local feature representations instead of the pixel intensity representations. We demonstrate that representations acquired by the proposed MDFR framework are complementary to those acquired by the Curvelet–Fractal approach. Finally, the performance of the proposed approaches has been evaluated by conducting a number of extensive experiments on four large-scale face datasets: the SDUMLA-HMT, FERET, CAS-PEAL-R1, and LFW databases. The results obtained from the proposed approaches outperform other state-of-the-art of approaches (e.g., LBP, DBN, WPCA) by achieving new state-of-the-art results on all the employed datasets

Sugar versus fat: elimination of glycogen storage improves lipid accumulation in Yarrowia lipolytica

Triacylglycerol (TAG) and glycogen are the two major metabolites for carbon storage in most eukaryotic organisms. We investigated the glycogen metabolism of the oleaginous Y. lipolytica and found that this yeast accumulates up to 16% glycogen in its biomass. Assuming that elimination of glycogen synthesis would result in an improvement of lipid accumulation, we characterized and deleted the single gene coding for glycogen synthase, YlGSY1. The mutant was grown under lipogenic conditions with glucose and glycerol as substrates and we obtained up to 60% improvement in TAG accumulation compared to the wild type strain. Additionally, YlGSY1 was deleted in a background that was already engineered for high lipid accumulation. In this obese background, TAG accumulation was also further increased. The highest lipid content of 52% was found after 3 days of cultivation in nitrogen-limited glycerol medium. Furthermore, we constructed mutants of Y. lipolytica and S. cerevisiae that are deleted for both glycogen and TAG synthesis, demonstrating that the ability to store carbon is not essential. Overall, this work showed that glycogen synthesis is a competing pathway for TAG accumulation in oleaginous yeasts and that deletion of the glycogen synthase has beneficial effects on neutral lipid storage

Optimization of lipid production with a genome-scale model of Yarrowia lipolytica.

Background: Yarrowia lipolytica is a non-conventional yeast that is extensively investigated for its ability to excrete citrate or to accumulate large amounts of storage lipids, which is of great significance for single cell oil production. Both traits are thus of interest for basic research as well as for biotechnological applications but they typically occur simultaneously thus lowering the respective yields. Therefore, engineering of strains with high lipid content relies on novel concepts such as computational simulation to better understand the two competing processes and to eliminate citrate excretion. Results: Using a genome-scale model (GSM) of baker's yeast as a scaffold, we reconstructed the metabolic network of Y. lipolytica and optimized it for use in flux balance analysis (FBA), with the aim to simulate growth and lipid production phases of this yeast. We validated our model and found the predictions of the growth behavior of Y. lipolytica in excellent agreement with experimental data. Based on these data, we successfully designed a fed-batch strategy to avoid citrate excretion during the lipid production phase. Further analysis of the network suggested that the oxygen demand of Y. lipolytica is reduced upon induction of lipid synthesis. According to this finding we hypothesized that a reduced aeration rate might induce lipid accumulation. This prediction was indeed confirmed experimentally. In a fermentation combining these two strategies lipid content of the biomass was increased by 80 %, and lipid yield was improved more than four-fold, compared to standard conditions. Conclusions: Genome scale network reconstructions provide a powerful tool to predict the effects of genetic modifications and the metabolic response to environmental conditions. The high accuracy and the predictive value of a newly reconstructed GSM of Y. lipolytica to optimize growth conditions for lipid accumulation are demonstrated. Based on these findings, further strategies for engineering Y. lipolytica towards higher efficiency in single cell oil production are discussed