Metabolomics combined with transcriptomics analyses of mechanism regulating testa pigmentation in peanut

Peanut testa (seed coat) contains large amounts of flavonoids that significantly influence seed color, taste, and nutritional qualities. There are various colors of peanut testa, however, their precise flavonoid components and regulatory mechanism of pigmentation remain unclear. In this study, a total of 133 flavonoids were identified and absolutely quantified in the seed coat of four peanut cultivars with different testa color using a widely targeted metabolomic approach. Black peanut skin had more types and substantial higher levels of cyanidin-based anthocyanins, which possibly contribute to its testa coloration. Procyanidins and flavan-3-ols were the major co-pigmented flavonoids in the red, spot and black peanuts, while flavanols were the most abundant constitutes in white cultivar. Although the concentrations as well as composition characteristics varied, the content ratios of procyanidins to flavan-3-ols were similar in all samples except for white peanut. Furthermore, MYB-like transcription factors, anthocyanidin reductases (ANR), and UDP-glycosyltransferases (UGT) were found to be candidate genes involved in testa pigmentation via RNA-seq and weighted gene co-expression network analysis. It is proposed that UGTs and ANR compete for the substrate cyanidin and the prevalence of UGTs activities over ANR one will determine the color pattern of peanut testa. Our results provide a comprehensive report examining the absolute abundance of flavonoid profiles in peanut seed coat, and the finding are expected to be useful for further understanding of regulation mechanisms of seed coat pigmentation in peanut and other crops

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Biosynthesis of cuticular alkylresorcinols in selected grass species Brachypodium distachyon and Secale cereale

Alkylresorcinols are phenolic lipids which occur in diverse plant species as well as microorganisms. In plants, alkylresorcinols are usually deposited at or near the surfaces where they are thought to serve as a first line of defense. Earlier work in our lab had shown the surface accumulation of alkylresorcinols in Secale cereale leaves was mainly restricted to the cuticle. However, direct evidence showing the protective role of these bioactive compounds at the surface is still insufficient. The current work was to investigate the biosynthesis of cuticular alkylresorcinols in order to get a better understanding of their biological function. This research focused on S. cereale, since it had previously been shown to contain relatively large amounts of alkylresorcinols, and on Brachypodium distachyon, a closely related genetic model system with completely sequenced genome. First, chemical analyses revealed that the cuticular wax covering leaves of B. distachyon included 5% of alkylresorcinols with alkyl chains varying from C₁₇ to C₂₅. Therefore, it was hypothesized that both species have genes encoding alkylresorcinol synthases (ARSs). A central goal of this work was to clone and characterize potential ARSs. One ARS (BdARS) was cloned from B. distachyon by mining the Brachypodium expressed sequence tag libraries and one ARS (ScARS) was cloned from S. cereale using a homology-based cloning strategy. In vivo biochemical characterization in yeast Saccharomyces cerevisiae demonstrated that both enzymes were capable of using C₁₀ to C₂₂ fatty acyl-CoAs with malonyl-CoA to generate a broad range of alkylresorcinols. Organ-specific expression in leaves but not in roots was observed for both BdARS and ScARS. Additionally, the expression pattern of ScARS matched the time-course of cuticular alkylresorcinol accumulation along the leaf of S. cereale. An investigation into their subcellular localization revealed that both ARSs were likely localized to the endoplasmic reticulum membrane. All these results taken together support the idea that BdARS and ScARS are the enzymes responsible for the biosynthesis of cuticular alkylresorcinols, and that the cuticular alkylresorcinols are indeed biosynthesized for a protective function associated with the wax lining the surface of grass leaves.Science, Faculty ofBotany, Department ofGraduat

Land use as an important indicator for water quality prediction in a region under rapid urbanization

Land use and land cover (LULC) have significant impacts on river water quality, particularly in regions subjected to rapid urbanization. However, it is unclear whether LULC (LULC type and pattern index) can be used as an effective indicator to predict water quality over the rapid urbanization regions. Here, we investigated the spatiotemporal changes of LULC and their impacts on the water quality of a river flowing through a rapidly developed area in China. Then, a cellular automata-Markov model was established to predict the LULC, which was used as a key indicator to predict future water quality by a multiple linear regression model. The results showed that construction land experienced rapid growth between 2000 and 2010 taking over arable land to a great extent, and the number of patch (NP) showed a significant downward trend during 2000–2010. The biochemical oxygen demand in five days (BOD5), total nitrogen (TN), and total phosphorus (TP) exhibited significantly positive correlations with construction land, while dissolved oxygen (DO) showed a significantly negative correlation with construction land. The DO exhibited a significantly positive correlation with the number of patch (NP), but TN and TP showed significantly negative correlations with NP. The water quality prediction model based on LULC performed well, especially TN prediction has a coefficient of determination of 0.691 and a mean relative error of 12.14%. The prediction of water quality in 2030 indicated that TN will not increase further, but TP will exhibit a remarkable increase in Zhenjiang city if the current development trend continues and no extra pollution control measures are taken

Full-length transcriptome sequencing provides insights into alternative splicing under cold stress in peanut

IntroductionPeanut (Arachis hypogaea L.), also called groundnut is an important oil and cash crop grown widely in the world. The annual global production of groundnuts has increased to approximately 50 million tons, which provides a rich source of vegetable oils and proteins for humans. Low temperature (non-freezing) is one of the major factors restricting peanut growth, yield, and geographic distribution. Since the complexity of cold-resistance trait, the molecular mechanism of cold tolerance and related gene networks were largely unknown in peanut.MethodsIn this study, comparative transcriptomic analysis of two peanut cultivars (SLH vs. ZH12) with differential cold tolerance under low temperature (10°C) was performed using Oxford Nanopore Technology (ONT) platform.Results and discussionAs a result, we identified 8,949 novel gene loci and 95,291 new/novel isoforms compared with the reference database. More differentially expressed genes (DEGs) were discovered in cold-sensitive cultivar (ZH12) than cold-tolerant cultivar (SLH), while more alternative splicing events were found in SLH compared to ZH12. Gene Ontology (GO) analyses of the common DEGs showed that the “response to stress”, “chloroplast part”, and “transcription factor activity” were the most enriched GO terms, indicating that photosynthesis process and transcription factors play crucial roles in cold stress response in peanut. We also detected a total of 708 differential alternative splicing genes (DASGs) under cold stress compared to normal condition. Intron retention (IR) and exon skipping (ES) were the most prevalent alternative splicing (AS) events. In total, 4,993 transcription factors and 292 splicing factors were detected, many of them had differential expression levels and/or underwent AS events in response to cold stress. Overexpression of two candidate genes (encoding trehalose-6-phosphatephosphatases, AhTPPs) in yeast improves cold tolerance. This study not only provides valuable resources for the study of cold resistance in peanut but also lay a foundation for genetic modification of cold regulators to enhance stress tolerance in crop

Downregulation of exosomal let-7a-5p in dust exposed- workers contributes to lung cancer development

Abstract Background Either chronic or acute exposure to dust particles may lead to pneumoconiosis and lung cancer, and lung cancer mortality among patients diagnosed with pneumoconiosis is increasing. Utilizing genome-wide sequencing technology, this study aimed to identify methods to decrease the number of patients with pneumoconiosis who die from lung cancer. Methods One hundred fifty-four subjects were recruited, including 54 pneumoconiosis patients and 100 healthy controls. Exosomes were isolated from the venous blood of every subject. Distinctive miRNAs were identified using high throughput sequencing technology, and bioinformatics analysis predicted target genes involved in lung cancer as well as their corresponding biological functions. Moreover, cross-cancer alterations of genes related to lung cancer were investigated, and survival analysis was performed using 2437 samples with an average follow-up period of 49 months. Results Let-7a-5p was revealed to be downregulated by 21.67% in pneumoconiosis. Out of the 683 let-7a-5p target genes identified from bioinformatics analysis, four genes related to five signaling pathways were confirmed to be involved in lung cancer development. Alterations in these four target genes were then explored in 4105 lung cancer patients, and BCL2L1 and IGF1R were demonstrated to be aberrantly expressed. Survival analysis further revealed that high expression of BCL2L1 corresponded to reduced survival of lung cancer patients (HR (95%CI) = 1.75(1.33~2.30)), while patient survival time was unaffected by expression of IGF1R (HR (95%CI) = 1.15 (0.98~1.36)). Conclusions In patients with lung adenocarcinoma, simultaneous downregulation of exosomal let-7a-5p and elevated expression of BCL2L1 are useful as predictive biomarkers for poor survival

Machine learning in prediction of residual stress in laser shock peening for maximizing residual compressive stress formation

Laser Shock Peening (LSP) is an advanced technique for enhancing surface properties, drawing significant interest for its ability to induce beneficial residual stresses in materials. Traditional LSP design processes, reliant on manual parameter selection, often result in imprecise control over the stress distribution, necessitating multiple iterations and high costs. This study introduces a machine learning (ML)-based approach, utilizing the Random Forest (RF) algorithm, to automate and optimize the design of LSP parameters for nickel-aluminium bronze surfaces. Our findings demonstrate the RF model’s capability to accurately predict and optimize residual stress distributions, achieving compressive stresses up to 472 MPa with a notable reduction in design iterations. The model forecasts both uniform and non-uniform stress patterns, particularly identifying areas susceptible to Residual Stress Holes (RSH) with improved precision. With an Absolute Percentage Error (APE) of only 6.2 %, our approach significantly outperforms traditional ML algorithms, offering a novel method for efficiently designing complex residual stress fields in LSP applications

Analysis for discharge within 2 days after thoracoscopic anatomic lung cancer surgery

Abstract Objectives The risk and beneficial factors of early discharge after thoracoscopic anatomic lung cancer surgery are unknown, and this study aims to investigate predictors and associated 30‐day readmission for early discharge. Methods We performed a single‐center retrospective analysis of 10,834 consecutive patients who underwent thoracoscopic anatomic lung cancer surgery. Two groups were determined based on discharge date: “discharged by postoperative Day 2” and “discharged after postoperative Day 2.” Univariable and multivariable analysis were conducted to identify predictors for discharge. Using propensity score matching (PSM) to compare 30‐day readmission rate between two cohorts. Results A total of 1911 patients were discharged by postoperative Day 2. Multivariable analysis identified older age (odds ratio (OR) = 1.014, p < 0.001), male sex (OR = 1.183, p = 0.003), larger tumor size (OR = 1.248, p < 0.001), pleural adhesions (OR = 1.638, p = 0.043), lymph nodes calcification (OR = 1.443, p = 0.009), advanced clinical T stage (vs. T < 2, OR = 1.470, p = 0.010), lobectomy resection (vs. segmentectomy resection, OR = 2.145, p < 0.001) and prolonged operative time (OR = 1.011, p < 0.001) as independent risk factors for discharge after postoperative Day 2. Three adjustable variables including higher FEV1/FVC (OR = 0.989, p = 0.001), general anesthesia (GA) plus thoracic paravertebral blockade (vs. GA alone, OR = 0.823, p = 0.006) and uni‐portal thoracoscopic surgery (vs. multi‐portal, OR = 0.349, p < 0.001) were associated with a decreased likelihood of discharge after postoperative Day 2. Before and after a 1:1 PSM, discharged by postoperative Day 2 did not increase the risk of 30‐day readmission compared to counterparts. Conclusions Carefully selected patients can be safely discharged within 2 days after thoracoscopic anatomic lung cancer surgery. Three modifiable variables may be favorable for promoting discharge by postoperative Day 2