Phase separation drives RNA virus-induced activation of the NLRP6 inflammasome.

NLRP6 is important in host defense by inducing functional outcomes including inflammasome activation and interferon production. Here, we show that NLRP6 undergoes liquid-liquid phase separation (LLPS) upon interaction with double-stranded RNA (dsRNA) in vitro and in cells, and an intrinsically disordered poly-lysine sequence (K350-354) of NLRP6 is important for multivalent interactions, phase separation, and inflammasome activation. Nlrp6-deficient or Nlrp6K350-354A mutant mice show reduced inflammasome activation upon mouse hepatitis virus or rotavirus infection, and in steady state stimulated by intestinal microbiota, implicating NLRP6 LLPS in anti-microbial immunity. Recruitment of ASC via helical assembly solidifies NLRP6 condensates, and ASC further recruits and activates caspase-1. Lipoteichoic acid, a known NLRP6 ligand, also promotes NLRP6 LLPS, and DHX15, a helicase in NLRP6-induced interferon signaling, co-forms condensates with NLRP6 and dsRNA. Thus, LLPS of NLRP6 is a common response to ligand stimulation, which serves to direct NLRP6 to distinct functional outcomes depending on the cellular context.

A mouse model to distinguish NLRP6-mediated inflammasome-dependent and -independent functions.

The NOD-like receptor (NLR) family pyrin domain containing 6 (NLRP6) serves as a sensor for microbial dsRNA or lipoteichoic acid (LTA) in intestinal epithelial cells (IECs), and initiating multiple pathways including inflammasome pathway and type I interferon (IFN) pathway, or regulating nuclear factor-κB (NF-κB) and mitogen-activated protein kinase (MAPK) pathways. NLRP6 can exert its function in both inflammasome-dependent and inflammasome-independent manners. However, there is no tool to distinguish the contribution of individual NLRP6-mediated pathway to the physiology and pathology in vivo. Here, we validated that Arg39 and Trp50 residues in the pyrin domain (PYD) of murine NLRP6 are required for ASC recruitment and inflammasome activation, but are not important for the RNA binding and PYD-independent NLRP6 oligomerization. We further generated the Nlrp6R39E&W50E mutant mice, which showed reduced inflammasome activation in either steady state intestine or during viral infection. However, the type I IFN production in cells or intestine tissue from Nlrp6R39E&W50E mutant mice remain normal. Interestingly, NLRP6-mediated inflammasome activation or the IFN-I production seems to play distinct roles in the defense responses against different types of RNA viruses. Our work generated a useful tool to study the inflammasome-dependent role of NLRP6 in vivo, which might help to understand the complexity of multiple pathways mediated by NLRP6 in response to the complicated and dynamic environmental cues in the intestine.

Deep learning enables accurate brain tissue microstructure analysis based on clinically feasible diffusion magnetic resonance imaging.

Diffusion magnetic resonance imaging (dMRI) allows non-invasive assessment of brain tissue microstructure. Current model-based tissue microstructure reconstruction techniques require a large number of diffusion gradients, which is not clinically feasible due to imaging time constraints, and this has limited the use of tissue microstructure information in clinical settings. Recently, approaches based on deep learning (DL) have achieved promising tissue microstructure reconstruction results using clinically feasible dMRI. However, it remains unclear whether the subtle tissue changes associated with disease or age are properly preserved with DL approaches and whether DL reconstruction results can benefit clinical applications. Here, we provide the first evidence that DL approaches to tissue microstructure reconstruction yield reliable brain tissue microstructure analysis based on clinically feasible dMRI scans. Specifically, we reconstructed tissue microstructure from four different brain dMRI datasets with only 12 diffusion gradients, a clinically feasible protocol, and the neurite orientation dispersion and density imaging (NODDI) and spherical mean technique (SMT) models were considered. With these results we show that disease-related and age-dependent alterations of brain tissue were accurately identified. These findings demonstrate that DL tissue microstructure reconstruction can accurately quantify microstructural alterations in the brain based on clinically feasible dMRI.

Effects of the Fasting-Postprandial State on Arterial Spin Labeling MRI-Based Cerebral Perfusion Quantification in Alzheimer's Disease.

BACKGROUND: The fasting-postprandial state remains an underrecognized confounding factor for quantifying cerebral blood flow (CBF) in the cognitive assessment and differential diagnosis of Alzheimer's disease (AD). PURPOSE: To investigate the effects of fasting-postprandial state on arterial spin labeling (ASL)-based CBF in AD patients. STUDY TYPE: Prospective. SUBJECTS: Ninety-two subjects (mean age = 62.5 ± 6.4 years; females 29.3%), including 30 with AD, 32 with mild cognitive impairment (MCI), and 30 healthy controls (HCs). Differential diagnostic models were developed with a 4:1 training to testing set ratio. FIELD STRENGTH/SEQUENCE: 3-T, T1-weighted imaging using gradient echo and pseudocontinuous ASL imaging using turbo spin echo. ASSESSMENT: Two ASL scans were acquired to quantify fasting state and postprandial state regional CBFs based on an automated anatomical labeling atlas. Two-way ANOVA was used to assess the effects of fasting/postprandial state and disease state (AD, MCI, and HC) on regional CBF. Pearson's correlation analysis was conducted between regional CBF and cognitive scores (Mini-Mental State Examination [MMSE] and Montreal Cognitive Assessment [MoCA]). The diagnostic performances of the fasting state, postprandial state, and mixed state (random mixing of the fasting and postprandial state CBF) in differential diagnosis of AD were conducted using support vector machine and logistic regression models. STATISTICAL TESTS: Two-way ANOVA, Pearson's correlation, and area under the curve (AUC) of diagnostic model were performed. P values <0.05 indicated statistical significance. RESULTS: Fasting-state CBF was correlated with cognitive scores in more brain regions (17 vs. 4 [MMSE] and 15 vs. 9 [MoCA]) and had higher absolute correlation coefficients than postprandial-state CBF. In the differential diagnosis of AD patients from MCI patients and HCs, fasting-state CBF outperformed mixed-state CBF, which itself outperformed postprandial-state CBF. DATA CONCLUSION: Compared with postprandial CBF, fasting-state CBF performed better in terms of cognitive score correlations and in differentiating AD patients from MCI patients and HCs. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 3.

PfbZIP85 Transcription Factor Mediates ω-3 Fatty Acid-Enriched Oil Biosynthesis by Down-Regulating PfLPAT1B Gene Expression in Plant Tissues.

The basic leucine zipper (bZIP) transcription factor (TF) family is one of the biggest TF families identified so far in the plant kingdom, functioning in diverse biological processes including plant growth and development, signal transduction, and stress responses. For Perilla frutescens, a novel oilseed crop abundant in polyunsaturated fatty acids (PUFAs) (especially α-linolenic acid, ALA), the identification and biological functions of bZIP members remain limited. In this study, 101 PfbZIPs were identified in the perilla genome and classified into eleven distinct groups (Groups A, B, C, D, E, F, G, H, I, S, and UC) based on their phylogenetic relationships and gene structures. These PfbZIP genes were distributed unevenly across 18 chromosomes, with 83 pairs of them being segmental duplication genes. Moreover, 78 and 148 pairs of orthologous bZIP genes were detected between perilla and Arabidopsis or sesame, respectively. PfbZIP members belonging to the same subgroup exhibited highly conserved gene structures and functional domains, although significant differences were detected between groups. RNA-seq and RT-qPCR analysis revealed differential expressions of 101 PfbZIP genes during perilla seed development, with several PfbZIPs exhibiting significant correlations with the key oil-related genes. Y1H and GUS activity assays evidenced that PfbZIP85 downregulated the expression of the PfLPAT1B gene by physical interaction with the promoter. PfLPAT1B encodes a lysophosphatidate acyltransferase (LPAT), one of the key enzymes for triacylglycerol (TAG) assembly. Heterogeneous expression of PfbZIP85 significantly reduced the levels of TAG and UFAs (mainly C18:1 and C18:2) but enhanced C18:3 accumulation in both seeds and non-seed tissues in the transgenic tobacco lines. Furthermore, these transgenic tobacco plants showed no significantly adverse phenotype for other agronomic traits such as plant growth, thousand seed weight, and seed germination rate. Collectively, these findings offer valuable perspectives for understanding the functions of PfbZIPs in perilla, particularly in lipid metabolism, showing PfbZIP85 as a suitable target in plant genetic improvement for high-value vegetable oil production.

Multi-view feature representation and fusion for drug-drug interactions prediction.

BACKGROUND: Drug-drug interactions (DDIs) prediction is vital for pharmacology and clinical application to avoid adverse drug reactions on patients. It is challenging because DDIs are related to multiple factors, such as genes, drug molecular structure, diseases, biological processes, side effects, etc. It is a crucial technology for Knowledge graph to present multi-relation among entities. Recently some existing graph-based computation models have been proposed for DDIs prediction and get good performance. However, there are still some challenges in the knowledge graph representation, which can extract rich latent features from drug knowledge graph (KG). RESULTS: In this work, we propose a novel multi-view feature representation and fusion (MuFRF) architecture to realize DDIs prediction. It consists of two views of feature representation and a multi-level latent feature fusion. For the feature representation from the graph view and KG view, we use graph isomorphism network to map drug molecular structures and use RotatE to implement the vector representation on bio-medical knowledge graph, respectively. We design concatenate-level and scalar-level strategies in the multi-level latent feature fusion to capture latent features from drug molecular structure information and semantic features from bio-medical KG. And the multi-head attention mechanism achieves the optimization of features on binary and multi-class classification tasks. We evaluate our proposed method based on two open datasets in the experiments. Experiments indicate that MuFRF outperforms the classic and state-of-the-art models. CONCLUSIONS: Our proposed model can fully exploit and integrate the latent feature from the drug molecular structure graph (graph view) and rich bio-medical knowledge graph (KG view). We find that a multi-view feature representation and fusion model can accurately predict DDIs. It may contribute to providing with some guidance for research and validation for discovering novel DDIs.

Brain age gap in neuromyelitis optica spectrum disorders and multiple sclerosis.

OBJECTIVE: To evaluate the clinical significance of deep learning-derived brain age prediction in neuromyelitis optica spectrum disorder (NMOSD) relative to relapsing-remitting multiple sclerosis (RRMS). METHODS: This cohort study used data retrospectively collected from 6 tertiary neurological centres in China between 2009 and 2018. In total, 199 patients with NMOSD and 200 patients with RRMS were studied alongside 269 healthy controls. Clinical follow-up was available in 85 patients with NMOSD and 124 patients with RRMS (mean duration NMOSD=5.8±1.9 (1.9-9.9) years, RRMS=5.2±1.7 (1.5-9.2) years). Deep learning was used to learn 'brain age' from MRI scans in the healthy controls and estimate the brain age gap (BAG) in patients. RESULTS: A significantly higher BAG was found in the NMOSD (5.4±8.2 years) and RRMS (13.0±14.7 years) groups compared with healthy controls. A higher baseline disability score and advanced brain volume loss were associated with increased BAG in both patient groups. A longer disease duration was associated with increased BAG in RRMS. BAG significantly predicted Expanded Disability Status Scale worsening in patients with NMOSD and RRMS. CONCLUSIONS: There is a clear BAG in NMOSD, although smaller than in RRMS. The BAG is a clinically relevant MRI marker in NMOSD and RRMS.

A label-free G-quadruplex aptamer fluorescent aptasensor for visual and real-time kanamycin detection in lake and human samples.

Antibiotic abuse is considered a serious problem affecting human health, necessitating that great attention be paid to explore robust, simple and sensitive methods for rapid evaluation. In this paper, we developed a fluorescent aptasensor for visual and real-time kanamycin detection by taking advantage of the label-free strategy based on H-aggregate disassembly of a chiral cyanine dye induced by a G-quadruplex aptamer. The good sensitivity and selectivity enabled this aptasensor to have a detection limit as low as 43 nM and have high specificity for kanamycin recognition. Furthermore, this assay was successfully applied for the detection of kanamycin in lake water and urine with excellent recoveries.

Characterization and evaluation of substratum material selection for microalgal biofilm cultivation.

Biofilm cultivation is considered a promising method to achieve higher microalgae biomass productivity with less water consumption and easier harvest compared to conventional suspended cultivation. However, studies focusing on the selection of substratum material and optimization of the growth of certain microalgae species on specific substratum are limited. This study investigated the selection of membranous and fabric fiber substrata for the attachment of unicellular microalgae Scenedesmus dimorphus and filamentous microalgae Tribonema minus in biofilm cultivation. The results indicated that both algal species preferred hydrophilic membranous substrata and nitrate cellulose/cellulose acetate membrane (CN-CA) was selected as a suitable candidate on which the obtained biomass yields were up to 10.24 and 7.81 g m-2 day-1 for S. dimorphus and T. minus, respectively. Furthermore, high-thread cotton fiber (HCF) and low-thread polyester fiber (LPEF) were verified as the potential fabric fiber substrata for S. dimorphus (5.42 g m-2 day-1) and T. minus (5.49 g m-2 day-1) attachment, respectively. The regrowth of microalgae biofilm cultivation strategy was applied to optimize the algae growth on the fabric fiber substrata, with higher biomass density and shear resistibility achieved for both algal species. The present data highlight the importance to establish the standards for selection the suitable substratum materials in ensuring the high efficiency and sustainability of the attached microalgal biomass production. KEY POINTS: • CN-CA was suitable membranous substratum candidate for algal biofilm cultivation. • HCF and LPEF were potential fabric fiber substrata for S. dimorphus and T. minus. • Regrowth biofilm cultivation was effective in improving algal biomass and attachment.

Genome-Wide Analysis of Glycerol-3-Phosphate Acyltransferase (GPAT) Family in Perilla frutescens and Functional Characterization of PfGPAT9 Crucial for Biosynthesis of Storage Oils Rich in High-Value Lipids.

Glycerol-3-phosphate acyltransferase (GPAT) catalyzes the first step in triacylglycerol (TAG) biosynthesis. However, GPAT members and their functions remain poorly understood in Perilla frutescens, a special edible-medicinal plant with its seed oil rich in polyunsaturated fatty acids (mostly α-linolenic acid, ALA). Here, 14 PfGPATs were identified from the P. frutescens genome and classified into three distinct groups according to their phylogenetic relationships. These 14 PfGPAT genes were distributed unevenly across 11 chromosomes. PfGPAT members within the same subfamily had highly conserved gene structures and four signature functional domains, despite considerable variations detected in these conserved motifs between groups. RNA-seq and RT-qPCR combined with dynamic analysis of oil and FA profiles during seed development indicated that PfGPAT9 may play a crucial role in the biosynthesis and accumulation of seed oil and PUFAs. Ex vivo enzymatic assay using the yeast expression system evidenced that PfGPAT9 had a strong GPAT enzyme activity crucial for TAG assembly and also a high substrate preference for oleic acid (OA, C18:1) and ALA (C18:3). Heterogeneous expression of PfGPAT9 significantly increased total oil and UFA (mostly C18:1 and C18:3) levels in both the seeds and leaves of the transgenic tobacco plants. Moreover, these transgenic tobacco lines exhibited no significant negative effect on other agronomic traits, including plant growth and seed germination rate, as well as other morphological and developmental properties. Collectively, our findings provide important insights into understanding PfGPAT functions, demonstrating that PfGPAT9 is the desirable target in metabolic engineering for increasing storage oil enriched with valuable FA profiles in oilseed crops.

Genome-wide identification and functional analysis of Dof transcription factor family in Camelina sativa.

BACKGROUND: Dof transcription factors (TFs) containing C2-C2 zinc finger domains are plant-specific regulatory proteins, playing crucial roles in a variety of biological processes. However, little is known about Dof in Camelina sativa, an important oil crop worldwide, with high stress tolerance. In this study, a genome-wide characterization of Dof proteins is performed to examine their basic structural characteristics, phylogenetics, expression patterns, and functions to identify the regulatory mechanism underlying lipid/oil accumulation and the candidate Dofs mediating stress resistance regulation in C. sativa. RESULTS: Total of 103 CsDof genes unevenly distributed on 20 chromosomes were identified from the C. sativa genome, and they were classified into four groups (A, B, C and D) based on the classification of Arabidopsis Dof gene family. All of the CsDof proteins contained the highly-conserved typic CX2C-X21-CX2C structure. Segmental duplication and purifying selection were detected for CsDof genes. 61 CsDof genes were expressed in multiple tissues, and 20 of them showed tissue-specific expression patterns, suggesting that CsDof genes functioned differentially in different tissues of C. sativa. Remarkably, a set of CsDof members were detected to be possible involved in regulation of oil/lipid biosynthesis in C. sativa. Six CsDof genes exhibited significant expression changes in seedlings under salt stress treatment. CONCLUSIONS: The present data reveals that segmental duplication is the key force responsible for the expansion of CsDof gene family, and a strong purifying pressure plays a crucial role in CsDofs' evolution. Several CsDof TFs may mediate lipid metabolism and stress responses in C. sativa. Several CsDof TFs may mediate lipid metabolism and stress responses in C. sativa. Collectively, our findings provide a foundation for deep understanding the roles of CsDofs and genetic improvements of oil yield and salt stress tolerance in this species and the related crops.

Interpretable CNN for ischemic stroke subtype classification with active model adaptation.

BACKGROUND: TOAST subtype classification is important for diagnosis and research of ischemic stroke. Limited by experience of neurologist and time-consuming manual adjudication, it is a big challenge to finish TOAST classification effectively. We propose a novel active deep learning architecture to classify TOAST. METHODS: To simulate the diagnosis process of neurologists, we drop the valueless features by XGB algorithm and rank the remaining ones. Utilizing active learning framework, we propose a novel causal CNN, in which it combines with a mixed active selection criterion to optimize the uncertainty of samples adaptively. Meanwhile, KL-focal loss derived from the enhancement of Focal loss by KL regularization is introduced to accelerate the iterative fine-tuning of the model. RESULTS: To evaluate the proposed method, we construct a dataset which consists of totally 2310 patients. In a series of sequential experiments, we verify the effectiveness of each contribution by different evaluation metrics. Experimental results show that the proposed method achieves competitive results on each evaluation metric. In this task, the improvement of AUC is the most obvious, reaching 77.4. CONCLUSIONS: We construct a backbone causal CNN to simulate the neurologist process of that could enhance the internal interpretability. The research on clinical data also indicates the potential application value of this model in stroke medicine. Future work we would consider various data types and more comprehensive patient types to achieve fully automated subtype classification.

Identification and Functional Characterization of Acyl-ACP Thioesterases B (GhFatBs) Responsible for Palmitic Acid Accumulation in Cotton Seeds.

In spite of increasing use in the food industry, high relative levels of palmitic acid (C16:0) in cottonseed oil imposes harmful effects on human health when overconsumed in the diet. The limited understanding of the mechanism in controlling fatty acid composition has become a significant obstacle for breeding novel cotton varieties with high-quality oil. Fatty acyl-acyl carrier protein (ACP) thioesterase B (FatBs) are a group of enzymes which prefer to hydrolyze the thioester bond from saturated acyl-ACPs, thus playing key roles in controlling the accumulation of saturated fatty acids. However, FatB members and their roles in cotton are largely unknown. In this study, a genome-wide characterization of FatB members was performed in allotetraploid upland cotton, aiming to explore the GhFatBs responsible for high accumulations of C16:0 in cotton seeds. A total of 14 GhFatB genes with uneven distribution on chromosomes were identified from an upland cotton genome and grouped into seven subfamilies through phylogenetic analysis. The six key amino acid residues (Ala, Trys, Ile, Met, Arg and Try) responsible for substrate preference were identified in the N-terminal acyl binding pocket of GhFatBs. RNA-seq and qRT-PCR analysis revealed that the expression profiles of GhFatB genes varied in multiple cotton tissues, with eight GhFatBs (GhA/D-FatB3, GhA/D-FatB4, GhA/D-FatB5, and GhA/D-FatB7) having high expression levels in developing seeds. In particular, expression patterns of GhA-FatB3 and GhD-FatB4 were positively correlated with the dynamic accumulation of C16:0 during cotton seed development. Furthermore, heterologous overexpression assay of either GhA-FatB3 or GhD-FatB4 demonstrated that these two GhFatBs had a high substrate preference to 16:0-ACP, thus contributing greatly to the enrichment of palmitic acid in the tested tissues. Taken together, these findings increase our understanding on fatty acid accumulation and regulation mechanisms in plant seeds. GhFatBs, especially GhA-FatB3 and GhD-FatB4, could be molecular targets for genetic modification to reduce palmitic acid content or to optimize fatty acid profiles in cotton and other oil crops required for the sustainable production of healthy edible oil.

Coronatine Enhances Chilling Tolerance of Tomato Plants by Inducing Chilling-Related Epigenetic Adaptations and Transcriptional Reprogramming.

Low temperature is an important environmental factor limiting the widespread planting of tropical and subtropical crops. The application of plant regulator coronatine, which is an analog of Jasmonic acid (JA), is an effective approach to enhancing crop's resistance to chilling stress and other abiotic stresses. However, the function and mechanism of coronatine in promoting chilling resistance of tomato is unknown. In this study, coronatine treatment was demonstrated to significantly increase tomato chilling tolerance. Coronatine increases H3K4me3 modifications to make greater chromatin accessibility in multiple chilling-activated genes. Corresponding to that, the expression of CBFs, other chilling-responsive transcription factor (TF) genes, and JA-responsive genes is significantly induced by coronatine to trigger an extensive transcriptional reprogramming, thus resulting in a comprehensive chilling adaptation. These results indicate that coronatine enhances the chilling tolerance of tomato plants by inducing epigenetic adaptations and transcriptional reprogramming.

Exogenous Melatonin Improves Seed Germination of Wheat (Triticum aestivum L.) under Salt Stress.

Melatonin (MT) can effectively reduce oxidative damage induced by abiotic stresses such as salt in plants. However, the effects of MT on physiological responses and molecular regulation during wheat germination remains largely elusive. In this study, the response of wheat seeds to MT under salt stress during germination was investigated at physiological and transcriptome levels. Our results revealed that application of MT significantly reduced the negative influence of salt stress on wheat seed germination. The oxidative load was reduced by inducing high activities of antioxidant enzymes. In parallel, the content of gibberellin A3 (GA3) and jasmonic acid (JA) increased in MT-treated seedling. RNA-seq analysis demonstrated that MT alters oxidoreductase activity and phytohormone-dependent signal transduction pathways under salt stress. Weighted correlation network analysis (WGCNA) revealed that MT participates in enhanced energy metabolism and protected seeds via maintained cell morphology under salt stress during wheat seed germination. Our findings provide a conceptual basis of the MT-mediated regulatory mechanism in plant adaptation to salt stress, and identify the potential candidate genes for salt-tolerant wheat molecular breeding.

Characterization of type-2 diacylglycerol acyltransferases in Haematococcus lacustris reveals their functions and engineering potential in triacylglycerol biosynthesis.

BACKGROUND: Haematococcus lacustris is an ideal source of astaxanthin (AST), which is stored in oil bodies containing esterified AST (EAST) and triacylglycerol (TAG). Diacylglycerol acyltransferases (DGATs) catalyze the last step of acyl-CoA-dependent TAG biosynthesis and are also considered as crucial enzymes involved in EAST biosynthesis in H. lacustris. Previous studies have identified four putative DGAT2-encoding genes in H. lacustris, and only HpDGAT2D allowed the recovery of TAG biosynthesis, but the engineering potential of HpDGAT2s in TAG biosynthesis remains ambiguous. RESULTS: Five putative DGAT2 genes (HpDGAT2A, HpDGAT2B, HpDGAT2C, HpDGAT2D, and HpDGAT2E) were identified in H. lacustris. Transcription analysis showed that the expression levels of the HpDGAT2A, HpDGAT2D, and HpDGAT2E genes markedly increased under high light and nitrogen deficient conditions with distinct patterns, which led to significant TAG and EAST accumulation. Functional complementation demonstrated that HpDGAT2A, HpDGAT2B, HpDGAT2D, and HpDGAT2E had the capacity to restore TAG synthesis in a TAG-deficient yeast strain (H1246) showing a large difference in enzymatic activity. Fatty acid (FA) profile assays revealed that HpDGAT2A, HpDGAT2D, and HpDGAT2E, but not HpDGAT2B, preferred monounsaturated fatty acyl-CoAs (MUFAs) for TAG synthesis in yeast cells, and showed a preference for polyunsaturated fatty acyl-CoAs (PUFAs) based on their feeding strategy. The heterologous expression of HpDGAT2D in Arabidopsis thaliana and Chlamydomonas reinhardtii significantly increased the TAG content and obviously promoted the MUFAs and PUFAs contents. CONCLUSIONS: Our study represents systematic work on the characterization of HpDGAT2s by integrating expression patterns, AST/TAG accumulation, functional complementation, and heterologous expression in yeast, plants, and algae. These results (1) update the gene models of HpDGAT2s, (2) prove the TAG biosynthesis capacity of HpDGAT2s, (3) show the strong preference for MUFAs and PUFAs, and (4) offer target genes to modulate TAG biosynthesis by using genetic engineering methods.

Enhancing growth and oil accumulation of a palmitoleic acid-rich Scenedesmus obliquus in mixotrophic cultivation with acetate and its potential for ammonium-containing wastewater purification and biodiesel production.

A palmitoleic acid-rich Scenedesmus obliquus strain SXND-02 was isolated from ammonium-containing wastewater. Biomass and lipid production were examined for this microalgal strain in photoautotrophic, heterotrophic, and mixotrophic cultivations, respectively, in order to extend its application in wastewater purification coupled with production of valued bio-products. Among the tested conditions, the microalga had better growth and higher lipid accumulation in mixotrophy. NH4Cl inhibited the microalgal growth in photoautotrophic cultivation. However, NaAc alleviated this inhibition in both heterotrophy and mixotrophy. Using 7 g L-1 NaAc and 0.5 g L-1 NH4Cl as carbon and nitrogen sources significantly increased the algal biomass and lipid yields under mixotrophic cultivation, with the highest levels up to 1.0 g L-1 and 59.88%, respectively. Fatty acid profiling indicated that palmitoleic acid was 23% in the S. obliquus SXND-02 under mixotrophic condition, which was about 21-fold higher than that in the control S. obliquus. Furthermore, this microalgal strain was tested in the chicken farm wastewater (CFW) containing high ammonium. Compared with other treatments, the S. obliquus SXND-02 cultivated in the 1/2 CFW + NaAc medium produced larger amounts of biomass (2.18 g L-1) and lipids (50.22%), and simultaneously higher removal rates of total nitrogen (TN) (80%), total ammonium nitrogen (TAN) (68%), total phosphate (TP) (82%), biological oxygen demand (BOD) (86%) and chemical oxygen demand (COD) (89%) from wastewater. The present data indicate that this excellent microalga can be used in mixotrophic cultivation for wastewater purification coupled with commercial production of valued biomass and high-quality algal oils.

Advanced treatment of chicken farm flushing wastewater by integrating Fenton oxidation and algal cultivation process for algal growth and nutrients removal.

Algae based wastewater treatment has been considered as the most promising win-win strategy for nutrients removal and biomass accumulation. However, the poor linking between traditional wastewater treatment and algal cultivation limits the achievement of this goal. In this study, a novel combination of Fenton oxidation and algal cultivation (CFOAC) system was investigated for the treatment of chicken farm flushing wastewater (CFFW). Fenton oxidation (FO) was adopted to reduce the excessive ammonia nitrogen, which might inhibit the algal growth. The results showed that single FO pretreatment removed 70.5 %, 96.7 %, 86.1 %, and 96.2 % of TN, TAN, TP, and COD, respectively. The highest biomass (235.8 mg/L/d) and lipid (77.3 mg/L/d) productivities were achieved on optimized CFOAC system after 7 days batch cultivation. Accordingly, the nutrients removal efficiencies increased to almost 100 %. Further fatty acid profile analysis showed that algae grown on optimal CFOAC system accumulated a high level of total lipids (32.8 %) with C16-C18 fatty acid as the most abundant compositions (accounting for over 60.6 %), which were propitious to biodiesel production. In addition, this CFOAC system was magnified from 1 L flask to 50 L horizontal pipe photobioreactor (HPPB) in semi-continuously culture under optimal conditions. The average biomass and lipid productivities were 995.7 mg/L/d and 320.6 mg/L/d, respectively, when cultured at 6 days hydraulic retention time with 1/3 substitution every two days. These findings proved that the novel CFOAC system is efficient in nutrients removal, algal cultivation, and biomass production for advanced treatment of CFFW.

Identification of differentially expressed genes associated with aluminum resistance in the soybean plant.

Aluminum (Al) toxicity is a major limitation to crop production in countries where acidic soil is abundant. In China, soybean production is constrained by Al stress-induced toxicity. As such, there is growing interest to develop Al-resistant varieties. In the present study, we sought to determine potential genes, functions and pathways for screening and breeding of Al-resistant varieties of soybean. First, we mined the E-GEOD-18517 dataset and identified 729 differentially expressed genes (DEGs) between untreated and Al-treated groups. Next, we performed Gene Ontology and Kyoto Encyclopedia of Genes and Genome pathways enrichment analysis and observed that most of the screened genes were mainly enriched in defense response, plasma membrane and molecular transducer activity. They were also enriched in three important pathways, the phenylpropanoid biosynthesis, plant-pathogen interaction, and cutin, suberine and wax biosynthesis. Utilizing weighted gene co-expression network analysis of 815 DEGs screened by Venn diagram, we identified DEGs that were the most disparate between treated and untreated groups. LOC100793667 (probable protein phosphatase 2C 60, GLYMA_17G223800), LOC100780576 (ethylene-responsive transcription factor 1B, GLYMA_02G006200), and LOC100785578 (protein ESKIMO 1, GLYMA_02G258000) were the most differentially expressed, which were consistent with the qRT-PCR results. As these genes are known to participate in essential functions, such as cell junction and phenylpropanoid biosynthesis, these genes may be important for breeding Al-resistant varieties. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12298-021-01018-x.

Genome-wide identification and functional characterization of the Camelina sativa WRKY gene family in response to abiotic stress.

BACKGROUND: WRKY transcription factors are a superfamily of regulators involved in diverse biological processes and stress responses in plants. However, there is limited knowledge about the WRKY family in camelina (Camelina sativa), an important Brassicaceae oil crop with strong tolerance for various stresses. Here, a genome-wide characterization of WRKY proteins is performed to examine their gene structures, phylogenetics, expression, conserved motif organizations, and functional annotation to identify candidate WRKYs that mediate stress resistance regulation in camelinas. RESULTS: A total of 242 CsWRKY proteins encoded by 224 gene loci distributed unevenly over the chromosomes were identified, and they were classified into three groups by phylogenetic analysis according to their WRKY domains and zinc finger motifs. The 15 CsWRKY gene loci generated 33 spliced variants. Orthologous WRKY gene pairs were identified, with 173 pairs in the C. sativa and Arabidopsis genomes as well as 282 pairs in the C. sativa and B. napus genomes, respectively. A total of 137 segmental duplication events were observed, but there was no tandem duplication in the camelina genome. Ten major conserved motifs were examined, with WRKYGQK being the most conserved, and several variants were present in many CsWRKYs. Expression analysis revealed that 50% more CsWRKY genes were expressed constitutively, and a set of them displayed tissue-specific expression. Notably, 11 CsWRKY genes exhibited significant expression changes in seedlings under cold, salt, and drought stresses, showing a preferentially inducible expression pattern in response to the stress. CONCLUSIONS: The present article describes a detailed analysis of the CsWRKY gene family and its expression profiles in 12 tissues and under several stress conditions. Segmental duplication is the major force underlying the broad expansion of this gene family, and a strong purifying pressure occurred for CsWRKY proteins during their evolution. CsWRKY proteins play important roles in plant development, with differential functions in different tissues. Exceptionally, eleven CsWRKYs, particularly five alternative spliced isoforms, were found to be the possible key players in mediating plant responses to various stresses. Overall, our results provide a foundation for understanding the roles of CsWRKYs and the precise mechanism through which CsWRKYs regulate high stress resistance as well as the development of stress tolerance cultivars among Cruciferae crops.