Molecular mechanisms of neutron radiation dose effects on M1 generation peas.

The dose effect of radiation has long been a topic of concern, but the molecular mechanism behind it is still unclear. In this study, dried pea seeds were irradiated with 252Cf fission neutron source. Through analyzing the transcriptome and proteome of M1 generation pea (Pisum sativum L.) leaves, we studied the molecular rule and mechanism of neutron dose effect. Our results showed three important rules of global gene expression in the studied dose range. The rule closely related to the neutron absorbed dose at the transcription and translation levels is: the greater the difference in neutron absorbed dose between two radiation treatment groups, the greater the difference in differential expression between the two groups and the control group. We also obtained important sensitive metabolic pathways of neutron radiation, as well as related key genes. Furthermore, the overall molecular regulation mechanism of dose effect was revealed based on the main functional items obtained. Our research results can be applied to appropriate radiation dose estimation and agricultural production practice.

The dominant role of extracellular polymeric substances produced by Achromobacter xylosoxidans BP1 in Cr(VI) microbial reduction.

Extracellular polymeric substances (EPS) have demonstrated significant benefits for reducing multivalent metal contamination. Using Achromobacter xylosoxidans BP1 isolated from a coal chemical site in China, this study elucidated the contribution of EPS production to Cr (VI) reduction and revealed its biological removal mechanism. BP1 grew at an optimum pH of 8 and the lowest inhibitory concentration of Cr(VI) was 300 mg/L. The spent medium completely removed Cr(VI), whereas resting cells were only able to remove 10.47 % and inactivated cells were nearly incapable of Cr(VI) removal. S-EPS and B-EPS reduced Cr(VI) by 98.59 % and 11.64 %, respectively. SEM-EDS analysis showed that the BP1 cells were stimulated to produce EPS under Cr stress. The XPS results showed that 29.63 % of Cr(VI) was enriched by intracellular bioaccumulation or biosorption and 70.37 % of Cr(VI) was reduced by extracellular enzymes to produce Cr(OH)3 and organic Cr(III) complexes. According to FTIR, EPS with -OH, COO-, and amide groups supplied binding sites and electrons for the reductive adsorption of Cr(VI). Genomic studies showed that BP1 primarily produces extracellular polysaccharides, metabolises sulphur and nitrogen, and reduces reactive oxygen species damage as a result of DNA repair proteases.

Integrating Data Mining with Metabolomics to Analyze the Mechanism of the "Pearl-Borneol" Pair in Promoting Healing of Diabetic Wounds.

INTRODUCTION: Chronic diabetic wounds pose a significant threat to the health of diabetic patients, representing severe and enduring complications. Globally, an estimated 2.5% to 15% of the annual health budget is associated with diabetes, with diabetic wounds accounting for a substantial share. Exploring new therapeutic agents and approaches to address delayed and impaired wound healing in diabetes becomes imperative. Traditional Chinese medicine (TCM) has a long history and remarkable efficacy in treating chronic wound healing. In this study, all topically applied proprietary Chinese medicines (pCMs) for wound healing officially approved by the National Medical Products Administration (NMPA) were collected from the NMPA TCM database. Data mining was employed to obtain a high-frequency TCM ingredients pair, Pearl-Borneol (1:1). METHOD: This study investigated the effect and molecular mechanism of the Pearl-Borneol pair on the healing of diabetic wounds by animal experiments and metabolomics. The results from animal experiments showed that the Pearl-Borneol pair significantly accelerated diabetic wound healing, exhibiting a more potent effect than the Pearl or Borneol treatment alone. Meanwhile, the metabolomics analysis identified significant differences in metabolic profiles in wounds between the model and normal groups, indicating that diabetic wounds had distinct metabolic characteristics from normal wounds. Moreover, Vaseline-treated wounds exhibited similar metabolic profiles to the wounds from the model group, suggesting that Vaseline might have a negligible impact on diabetic wound metabolism. In addition, wounds treated with Pearl, Borneol, and Pearl-Borneol pair displayed significantly different metabolic profiles from Vaseline-treated wounds, signifying the influence of these treatments on wound metabolism. Subsequent enrichment analysis of the metabolic pathway highlighted the involvement of the arginine metabolic pathway, closely associated with diabetic wounds, in the healing process under Pearl- Borneol pair treatment. Further analysis revealed elevated levels of arginine and citrulline, coupled with reduced nitric oxide (NO) in both the model and Vaseline-treated wounds compared to normal wounds, pointing to impaired arginine utilization in diabetic wounds. Interestingly, treatment with Pearl and Pearl-Borneol pair lowered arginine and citrulline levels while increasing NO content, suggesting that these treatments may promote the catabolism of arginine to generate NO, thereby facilitating faster wound closure. Additionally, borneol alone significantly elevated NO content in wounds, potentially due to its ability to directly reduce nitrates/nitrites to NO. Oxidative stress is a defining characteristic of impaired metabolism in diabetic wounds. RESULTS: The result showed that both Pearl and Pearl-Borneol pair decreased the oxidative stress biomarker methionine sulfoxide level in diabetic wounds compared to those treated with Vaseline, indicating that Pearl alone or combined with Borneol may enhance the oxidative stress microenvironment in diabetic wounds. CONCLUSION: In summary, the findings validate the effectiveness of the Pearl-Borneol pair in accelerating the healing of diabetic wounds, with effects on reducing oxidative stress, enhancing arginine metabolism, and increasing NO generation, providing a mechanistic basis for this therapeutic approach.

AFP: Finding pathways accounting for stoichiometry along with atom group tracking in metabolic network.

Automatically finding novel pathways plays an important role in the initial designs of metabolic pathways in synthetic biology and metabolic engineering. Although path-finding methods have been successfully applied in identifying valuable synthetic pathways, few efforts have been made in fusing atom group tracking into building stoichiometry model to search metabolic pathways from arbitrary start compound via Mixed Integer Linear Programming (MILP). We propose a novel method called AFP to find metabolic pathways by incorporating atom group tracking into reaction stoichiometry via MILP. AFP tracks the movements of atom groups in the reaction stoichiometry to construct MILP model to search the pathways containing atom groups exchange in the reactions and adapts the MILP model to provide the options of searching pathways from an arbitrary or given compound to the target compound. Combining atom group tracking with reaction stoichiometry to build MILP model for pathfinding may promote the search of well-designed alternative pathways at the stoichiometric modeling level. The experimental comparisons to the known pathways show that our proposed method AFP is more effective to recover the known pathways than other existing methods and is capable of discovering biochemically feasible pathways producing the metabolites of interest.

Engineered Leukocyte Biomimetic Colorimetric Sensor Enables High-Efficient Detection of Tumor Cells Based on Bioorthogonal Chemistry.

Accurate detection of heterogeneous circulating tumor cells (CTCs) is critical as they can make tumor cells more aggressive, drug-resistant, and metastasizing. Although the leukocyte membrane coating strategy is promising in meeting the challenge of detecting heterogeneous CTCs due to its inherent antiadhesive properties, it is still limited by the reduction or loss of expression of known markers. Bioorthogonal glycol-metabolic engineering is expected to break down this barrier by feeding the cells with sugar derivatives with a unique functional group to establish artificial targets on the surface of tumor cells. Herein, an engineered leukocyte biomimetic colorimetric sensor was accordingly fabricated for high-efficient detection of heterogeneous CTCs. Compared with conventional leukocyte membrane coating, the sensor could covalently bound to the heterogeneous CTCs models fed with Ac4ManNAz in vitro through the synergy of bioorthogonal chemistry and metabolic glycoengineering, ignoring the phenotypic changes of heterogeneous CTCs. Meanwhile, a sandwich structure composed of leukocyte biomimetic layer/CTCs/MoS2 nanosheet was formed for visual detection of HeLa cells as low as 10 cells mL-1. Overall, this approach can overcome the dependence of conventional cell membrane biomimetic technology on specific cell phenotypes and provide a new viewpoint to highly efficiently detect heterogeneous CTCs.

Ferroptosis: a novel mechanism of cell death in ophthalmic conditions.

Ferroptosis, a new type of programmed cell death proposed in recent years, is characterized mainly by reactive oxygen species and iron-mediated lipid peroxidation and differs from programmed cell death, such as apoptosis, necrosis, and autophagy. Ferroptosis is associated with a variety of physiological and pathophysiological processes. Recent studies have shown that ferroptosis can aggravate or reduce the occurrence and development of diseases by targeting metabolic pathways and signaling pathways in tumors, ischemic organ damage, and other degenerative diseases related to lipid peroxidation. Increasing evidence suggests that ferroptosis is closely linked to the onset and progression of various ophthalmic conditions, including corneal injury, glaucoma, age-related macular degeneration, diabetic retinopathy, retinal detachment, and retinoblastoma. Our review of the current research on ferroptosis in ophthalmic diseases reveals significant advancements in our understanding of the pathogenesis, aetiology, and treatment of these conditions.

UPLC-LTQ-Orbitrap Study on Rat Urinary Metabolites of 5-Methoxy-Alpha-Methyltryptamine.

OBJECTIVE: 5-Methoxy-α-Methyltryptamine (5-MeO-AMT) is a new psychoactive substance which is abused due to its hallucinogenic and euphoric effects. This study aimed to study the metabolic characteristics of 5-MeO-AMT. METHODS: Five rats were given intraperitoneal injection at a dose of 50 mg/kg of 5-MeO-AMT, and their urine was subsequently collected at different times within 7 days. Ultra-high performance liquid chromatography-- tandem high-resolution mass spectrometry (UPLC-LTQ-Orbitrap) was used to detect the precise molecular weight and fragment ions of 5-MeO-AMT and its possible metabolites in the urine sample extracted with benzene-ethyl acetate. RESULTS: Three metabolites, including OH-5-MeO-AMT, α-Me-5-HT, and N-Acetyl-5-MeO-AMT were identified in rats' urine. The major metabolic pathways involved O-demethylation, hydroxylation of indole ring, and Acetylation on aliphatic amines. CONCLUSION: The results of this study are an important reference for the identification and screening of toxicants of 5-MeO-AMT.

Unraveling the mechanisms of benzo[a]pyrene degradation by Pigmentiphaga kullae strain KIT-003 using a multi-omics approach.

Polycyclic aromatic hydrocarbons (PAHs), notably benzo[a]pyrene (BaP), are environmental contaminants with multiple adverse ecological implications. Numerous studies have suggested the use of BaP biodegradation using various bacterial strains to remove BaP from the environment. This study investigates the BaP biodegradation capability of Pigmentiphaga kullae strain KIT-003, isolated from the Nak-dong River (South Korea) under specific environmental conditions. The optimum conditions of biodegradation were found to be pH 7.0, 35°C, and a salinity of 0 %. GC-MS analysis suggested alternative pathways by which KIT-003 produced catechol from BaP through several intermediate metabolites, including 4-formylchrysene-5-carboxylic acid, 5,6-dihydro-5,6-dihydroxychrysene-5-carboxylic acid (isomer: 3,4-dihydro-3,4-dihydroxychrysene-4-carboxylic acid), naphthalene-1,2-dicarboxylic acid, and 2-hydroxy-1-naphthoic acid. Proteomic profiles indicated upregulation of enzymes associated with aromatic compound degradation, such as nahAc and nahB, and of those integral to the tricarboxylic acid cycle, reflecting the strain's adaptability to and degradation of BaP. Lipidomic analysis of KIT-003 demonstrated that BaP exposure induced an accumulation of glycerolipids such as diacylglycerol and triacylglycerol, indicating their crucial role in bacterial adaptation mechanisms under BaP stress. This study provides significant scientific knowledge regarding the intricate mechanisms involved in BaP degradation by microorganisms.

PuERF008-PuFAD2 module regulates aroma formation via the fatty acid pathway in response to calcium signaling in 'Nanguo' pear.

Calcium acts as a secondary messenger in plants and is essential for plant growth and development. However, studies on the pathway of aroma synthesis in 'Nanguo' pear (Pyrus ussriensis Maxim.) are scarce. In this study, a bioinformatics analysis of transcriptomic data from calcium-treated 'Nanguo' pear was performed, which identified two fatty acid desaturases, PuFAD2 and PuFAD3, and eight AP2/ERF transcription factors, all exhibiting the same expression patterns. Transient expression experiments showed overexpression of PuFAD2 and PuFAD3 significantly increased the levels of aromatic substrates linoleic acid, hexanal, linolenic acid, and (E)-2-hexenal, but RNAi (RNA interference) had the opposite expression. Promoter sequences analysis revealed that PuFAD2 and PuFAD3 have ERE (estrogen response element) motifs on their promoters. The strongest activation of PuFAD2 by PuERF008 was verified using a dual-luciferase reporting system. Additionally, yeast one-hybrid and electrophoretic mobility shift assays revealed PuERF008 could active PuFAD2. Transient overexpression and RNAi analyses of PuERF008 showed a strong correlation with the expression of PuFAD2. This study provides insights into the process of aroma biosynthesis in 'Nanguo' pear and offers a theoretical basis for elucidating the role of calcium signaling in aroma synthesis.

Causality of metabolites and metabolic pathways on cholestatic liver diseases: a Mendelian randomization study.

Background and Aims: Blood metabolite abnormalities have revealed an association with cholestatic liver diseases (CLDs), while the underlying metabolic mechanisms have remained sluggish yet. Accordingly, the present evaluation aims to investigate the causal relationship between blood metabolites and the risk of two major CLDs, including primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC). Methods: Univariable and multivariable Mendelian randomization (MR) approaches were employed to uncover potential causal associations between blood metabolites and 2 CLDs, including PBS and PSC, through extracting instrumental variables (IVs) for metabolites from genome-wide association studies (GWAS) conducted on European individuals. The GWAS summary data of PBC or PSC were sourced from two distinct datasets. The initial analysis employed inverse variance weighted (IVW) and an array of sensitivity analyses, followed by replication and meta-analysis utilizing FinnGen consortium data. Finally, a multivariable MR analysis was carried out to ascertain the independent effects of each metabolite. Furthermore, the web-based tool MetaboAnalyst 5.0 was used to perform metabolic pathway examination. Results: A genetic causality between 15 metabolites and CLDs was recognized after preliminary analysis and false discovery rate (FDR) correction. Subsequently, 9 metabolites consistently represented an association through replication and meta-analysis. Additionally, the independent causal effects of 7 metabolites were corroborated by multivariable MR analysis. Specifically, the metabolites isovalerylcarnitine (odds ratio [OR] = 3.146, 95% confidence intervals [CI]: 1.471-6.726, p = 0.003), valine (OR = 192.44, 95%CI: 4.949-7483.27, p = 0.005), and mannose (OR = 0.184, 95%CI: 0.068-0.499, p < 0.001) were found to have a causal relationship with the occurrence of PBC. Furthermore, erythrose (OR = 5.504, 95%CI: 1.801-16.821, p = 0.003), 1-stearoylglycerophosphocholine (OR = 6.753, 95%CI: 2.621-17.399, p = 7.64 × 10-5), X-11847 (OR = 0.478, 95%CI: 0.352-0.650, p = 2.28 × 10-6), and X-12405 (OR = 3.765, 95%CI: 1.771-8.005, p = 5.71 × 10-4) were independently associated with the occurrence of PSC. Furthermore, the analysis of metabolic pathways identified seven significant pathways in two CLDs. Conclusion: The findings of the present study have unveiled robust causal relationships between 7 metabolites and 2 CLDs, thereby providing novel insights into the metabolic mechanisms and therapeutic strategies for these disorders.

Metatranscriptomics reveals microbial community function succession and characteristic flavor formation mechanisms during black rice wine fermentation.

Black rice wine (BRW) is a traditional Chinese rice wine with unique flavors; however, the formation pathways of flavor compounds driven by microbiota remain unclear. This study employed HPLC and GC-MS to reveal that during BRW fermentation, free amino acids increased sevenfold, volatile compounds doubled, and 28 key characteristic flavor compounds were identified. Metatranscriptomic analysis indicated that during fermentation, driven by physicochemical factors and microbial interactions, Saccharomyces gradually became the dominant active microorganism (relative abundance 87.01%-97.70%). Other dominant microorganisms (relative abundance >0.1%), including Saccharomycopsis, Pediococcus, Wickerhamomyces, and Weissella, significantly decreased. Meanwhile, the microflora's signature functions underwent succession: transcription early, carbohydrate metabolism mid-stage, and autophagy late. These microbial and functional successions facilitated the accumulation of flavor compounds. Metabolic network reconstruction revealed that Saccharomyces was pivotal in substrate degradation and flavor formation, while other dominant microorganisms actively promoted these processes. This study provides insights into regulating BRW's flavor through microorganisms.

Acute toxicity profiling of medicinal herb Ardisia elliptica leaf extract by conventional evaluations and proton nuclear magnetic resonance (NMR) metabolomics.

Background and aim: Interest in the safety of herbal medicine is growing rapidly regarding knowledge and challenges in natural products. Hence, this study aimed to reveal the toxicological profile of Ardisia elliptica, a traditional medicinal plant used in the treatment of various illnesses. Experimental procedure: Acute toxicity study was performed on female and male Sprague Dawley rats with a single oral administration of 2000 mg/kg BW of 70% ethanolic A. elliptica leaf extract, using a combination of conventional investigations and 1H-NMR-based metabolomics approaches. Results: Physical, hematological, biochemical, and histopathological assessments demonstrated the usual rat profile, with no mortality and delayed toxicity 14 days after administration. 1H NMR serum metabolomics depicted similar metabolites between normal and treated groups. Nevertheless, 1H NMR of urinary metabolomics revealed perturbation in carbohydrate, amino acid, and energy metabolism within 24h after extract administration, while no accumulation of toxic biomarkers in the collected biological fluids on Day 14. A minor gender-based difference revealed the influence of sex hormones and different energy expenditure on response to extract treatment. Conclusion: This study suggested that 2000 mg/kg BW of 70% ethanolic A. elliptica leaf extract is considered as safe for consumption and offered a comprehensive overview of the response of physiological and metabolic aspects applicable to food and herbal product development.

Deciphering the roles of nitrogen source in sharping synchronous metabolic pathways of linear alkylbenzene sulfonate and nitrogen in a membrane biofilm for treating greywater.

Nitrogen (N) source is an important factor affecting biological wastewater treatment. Although the oxygen-based membrane biofilm showed excellent greywater treatment performance, how N source impacts the synchronous removal of organics and N is still unclear. In this work, how N species (urea, nitrate and ammonia) affect synchronous metabolic pathways of organics and N were evaluated during greywater treatment in the membrane biofilm. Urea and ammonia achieved efficient chemical oxygen demand (>97.5%) and linear alkylbenzene sulfonate (LAS, >98.5%) removal, but nitrate enabled the maximum total N removal (80.8 ± 2.6%). The nitrate-added system had poor LAS removal ratio and high residual LAS, promoting the accumulation of effluent protein-like organics and fulvic acid matter. N source significantly induced bacterial community succession, and the increasing of corresponded functional flora can promote the transformation and utilization of microbial-mediated N. The nitrate system was more conducive to the accumulation of denitrification related microorganisms and enzymes, enabling the efficient N removal. Combining with high amount of ammonia monooxygenase that contributing to LAS and N co-metabolism, LAS mineralization related microbes and functional enzymes were generously accumulated in the urea and ammonia systems, which achieved the high efficiency of organics and LAS removal.

Physicochemical, structural and metabolic products of yogurt as affected by Coriolus versicolor fermented sweet potato pulp water.

Sweet potato pulp water (SPPW) is a kind of sweet potato starch processing by-product with rich nutrition but low utilization. The impacts of different proportions of Coriolus versicolor (C. versicolor, CV) fermented sweet potato pulp water (CV-SPPW) on the physicochemical, structural and metabolic properties of yogurt were investigated. Compared with 0% group, the hardness index, elasticity index and cohesion of the 10% sample group increased by 1.9-fold, 55.7% and 1.39-fold, respectively. When CV-SPPW was added at an amount of 10%, the microstructure and sensory scores of yogurts were considered as the optimal. Metabolic pathway analysis indicated that the changes of yogurts were mainly involved in sugar metabolism and amino acid metabolism, and that the carbohydrate metabolites produced mainly included cellobiose, maltitol, d-trehalose and d-maltose. The CV-SPPW improved the structural characteristics of yogurts to varying degrees and the fermented yogurts exhibited better viscosity properties.

Genetic insights of blood lipid metabolites on polycystic ovary syndrome risk: a bidirectional two-sample Mendelian randomization study.

Background: Pathologically, metabolic disorder plays a crucial role in polycystic ovarian syndrome (PCOS). However, there is no conclusive evidence lipid metabolite levels to PCOS risk. Methods: In this study, genome-wide association study (GWAS) genetic data for 122 lipid metabolites were used to assign instrumental variables (IVs). PCOS GWAS were derived from a large-scale meta-analysis of 10,074 PCOS cases and 103,164 controls. An inverse variance weighted (IVW) analysis was the primary methodology used for Mendelian randomization (MR). For sensitivity analyses, Cochran Q test, MR-Egger intercept, MR-PRESSO, leave-one-out analysis,and Steiger test were performed. Furthermore, we conducted replication analysis, meta-analysis, and metabolic pathway analysis. Lastly, reverse MR analysis was used to determine whether the onset of PCOS affected lipid metabolites. Results: This study detected the blood lipid metabolites and potential metabolic pathways that have a genetic association with PCOS onset. After IVW, sensitivity analyses, replication and meta-analysis, two pathogenic lipid metabolites of PCOS were finally identified: Hexadecanedioate (OR=1.85,95%CI=1.27-2.70, P=0.001) and Dihomo-linolenate (OR=2.45,95%CI=1.30-4.59, P=0.005). Besides, It was found that PCOS may be mediated by unsaturated fatty acid biosynthesis and primary bile acid biosynthesis metabolic pathways. Reverse MR analysis showed the causal association between PCOS and 2-tetradecenoyl carnitine at the genetic level (OR=1.025, 95% CI=1.003-1.048, P=0.026). Conclusion: Genetic evidence suggests a causal relationship between hexadecanedioate and dihomo-linolenate and the risk of PCOS. These compounds could potentially serve as metabolic biomarkers for screening PCOS and selecting drug targets. The identification of these metabolic pathways is valuable in guiding the exploration of the pathological mechanisms of PCOS, although further studies are necessary for confirmation.

PEMPS: a phylogenetic software tool to model the evolution of metabolic pathways.

BACKGROUND: Metabolic pathways support the enzyme flux that converts input chemicals into energy and cellular building blocks. With a constant rate of input, steady-state flux is achieved when metabolite concentrations and reaction rates remain constant over time. Individual genes undergo mutation, while selection acts on higher level functions of the pathway, such as steady-state flux where applicable. Modeling the evolution of metabolic pathways through mechanistic sets of ordinary differential equations is a piece of the genotype-phenotype map model for interpreting genetic variation and inter-specific differences. Such models can generate distinct compensatory changes and adaptive changes from directional selection, indicating single nucleotide polymorphisms and fixed differences that could affect phenotype. If used for inference, this would ultimately enable detection of selection on metabolic pathways as well as inference of ancestral states for metabolic pathway function. RESULTS: A software tool for simulating the evolution of metabolic pathways based upon underlying biochemistry, phylogenetics, and evolutionary considerations is presented. The Python program, Phylogenetic Evolution of Metabolic Pathway Simulator (PEMPS), implements a mutation-selection framework to simulate the evolution of the pathway over a phylogeny by interfacing with COPASI to calculate the steady-state flux of the metabolic network, introducing mutations as alterations in parameter values according to a model, and calculating a fitness score and corresponding probability of fixation based on the change in steady-state flux value(s). Results from simulations are consistent with a priori expectations of fixation probabilities and systematic change in model parameters. CONCLUSIONS: The PEMPS program simulates the evolution of a metabolic pathway with a mutation-selection modeling framework based on criteria like steady-state flux that is designed to work with SBML-formatted kinetic models, and Newick-formatted phylogenetic trees. The Python software is run on the Linux command line and is available at https://github.com/nmccloskey/PEMPS .

Gtie-Rt: A comprehensive graph learning model for predicting drugs targeting metabolic pathways in human.

Drugs often target specific metabolic pathways to produce a therapeutic effect. However, these pathways are complex and interconnected, making it challenging to predict a drug's potential effects on an organism's overall metabolism. The mapping of drugs with targeting metabolic pathways in the organisms can provide a more complete understanding of the metabolic effects of a drug and help to identify potential drug-drug interactions. In this study, we proposed a machine learning hybrid model Graph Transformer Integrated Encoder (GTIE-RT) for mapping drugs to target metabolic pathways in human. The proposed model is a composite of a Graph Convolution Network (GCN) and transformer encoder for graph embedding and attention mechanism. The output of the transformer encoder is then fed into the Extremely Randomized Trees Classifier to predict target metabolic pathways. The evaluation of the GTIE-RT on drugs dataset demonstrates excellent performance metrics, including accuracy (>95%), recall (>92%), precision (>93%) and F1-score (>92%). Compared to other variants and machine learning methods, GTIE-RT consistently shows more reliable results.

Combining transcriptome and metabolome analysis to understand the response of sorghum to Melanaphis sacchari.

BACKGROUND: The sorghum aphid Melanaphis sacchari (Zehntner) (Homoptera: Aphididae) is an important insect in the late growth phase of sorghum (Sorghum bicolor L.). However, the mechanisms of sorghum response to aphid infestation are unclear. RESULTS: In this paper, the mechanisms of aphid resistance in different types of sorghum varieties were revealed by studying the epidermal cell structure and performing a transcriptome and metabolome association analysis of aphid-resistant and aphid-susceptible varieties. The epidermal cell results showed that the resistance of sorghum to aphids was positively correlated with epidermal cell regularity and negatively correlated with the intercellular space and leaf thickness. Transcriptome and metabolomic analyses showed that differentially expressed genes in the resistant variety HN16 and susceptible variety BTX623 were mainly enriched in the flavonoid biosynthesis pathway and differentially expressed metabolites were mainly related to isoflavonoid biosynthesis and flavonoid biosynthesis. The q-PCR results of key genes were consistent with the transcriptome expression results. Meanwhile, the metabolome test results showed that after aphidinfestation, naringenin and genistein were significantly upregulated in the aphid-resistant variety HN16 and aphid-susceptible variety BTX623 while luteolin was only significantly upregulated in BTX623. These results show that naringenin, genistein, and luteolin play important roles in plant resistance to aphid infestation. The results of exogenous spraying tests showed that a 1‰ concentration of naringenin and genistein is optimal for improving sorghum resistance to aphid feeding. CONCLUSIONS: In summary, the physical properties of the sorghum leaf structure related to aphid resistance were studied to provide a reference for the breeding of aphid-resistant varieties. The flavonoid biosynthesis pathway plays an important role in the response of sorghum aphids and represents an important basis for the biological control of these pests. The results of the spraying experiment provide insights for developing anti-aphid substances in the future.

Enhanced degradation and methane production of food waste anaerobic digestate using an integrated system of anaerobic digestion and microbial electrolysis cells for long-term operation.

The integrated system of anaerobic digestion and microbial electrolysis cells (AD-MEC) was a novel approach to enhance the degradation of food waste anaerobic digestate and recover methane. Through long-term operation, the start-up method, organic loading, and methane production mechanism of the digestate have been investigated. At an organic loading rate of 4000 mg/L, AD-MEC increased methane production by 3-4 times and soluble chemical oxygen demand (SCOD) removal by 20.3% compared with anaerobic digestion (AD). The abundance of bacteria Fastidiosipila and Geobacter, which participated in the acid degradation and direct electron transfer in the AD-MEC, increased dramatically compared to that in the AD. The dominant methanogenic archaea in the AD-MEC and AD were Methanobacterium (44.4-56.3%) and Methanocalculus (70.05%), respectively. Geobacter and Methanobacterium were dominant in the AD-MEC by direct electron transfer of organic matter into synthetic methane intermediates. AD-MEC showed a perfect SCOD removal efficiency of the digestate, while methane as clean energy was obtained. Therefore, AD-MEC was a promising technology for deep energy transformation from digestate.

Planning biosynthetic pathways of target molecules based on metabolic reaction prediction and AND-OR tree search.

Bioretrosynthesis problem is to predict synthetic routes using substrates for given natural products (NPs). However, the huge number of metabolic reactions leads to a combinatorial explosion of searching space, which is high time-consuming and costly. Here, we propose a framework called BioRetro to predict bioretrosynthesis pathways using a one-step bioretrosynthesis network, termed HybridMLP combined with AND-OR tree heuristic search. The HybridMLP predicts precursors that will produce the target NPs, while the AND-OR tree generates the iterative multi-step biosynthetic pathways. The one-step bioretrosynthesis prediction experiments are conducted on MetaNetX dataset by using HybridMLP, which achieves 46.5%, 74.6%, 81.6% in terms of the top-1, top-5, top-10 accuracies. The great performance demonstrates the effectiveness of HybridMLP in one-step bioretrosynthesis. Besides, the evaluation of two benchmark datasets reveals that BioRetro can significantly improve the speed and success rate in predicting biosynthesis pathways. In addition, the BioRetro is further shown to find the synthetic pathway of compounds, such as ginsenoside F1 with the same substrates as reported but different enzymes, which may be the novel potential enzyme to have better catalytic performance.