Transcriptome and proteome analyses reveal the potential mechanism of seed dormancy release in Amomum tsaoko during warm stratification.

BACKGROUND: In Amomum tsaoko breeding, the low germination rate is the major limitation for their large-scale reproduction. We found that warm stratification was an effective treatment to break the seed dormancy of A. tsaoko prior to sowing and could be an important component of improving breeding programs. The mechanism of seed dormancy release during warm stratification remains unclear. Therefore, we studied the differences between transcripts and proteomes at 0, 30, 60, and 90 days of warm stratification, to identify some regulatory genes and functional proteins that may cause seed dormancy release in A. tsaoko and reveal their regulatory mechanism. RESULTS: RNA-seq was performed for the seed dormancy release process, and the number of differentially expressed genes (DEGs) was 3196 in three dormancy release periods. Using TMT-labelling quantitative proteome analysis, a total of 1414 proteins were defined as differentially expressed proteins (DEPs). Functional enrichment analyses revealed that the DEGs and DEPs were mainly involved in signal transduction pathways (MAPK signaling, hormone) and metabolism processes (cell wall, storage and energy reserves), suggesting that these differentially expressed genes and proteins are somehow involved in response to seed dormancy release process, including MAPK, PYR/PYL, PP2C, GID1, GH3, ARF, AUX/IAA, TPS, SPS, and SS. In addition, transcription factors ARF, bHLH, bZIP, MYB, SBP, and WRKY showed differential expression during the warm stratification stage, which may relate to dormancy release. Noteworthy, XTH, EXP, HSP and ASPG proteins may be involved in a complex network to regulate cell division and differentiation, chilling response and the seed germination status in A. tsaoko seed during warm stratification. CONCLUSION: Our transcriptomic and proteomic analysis highlighted specific genes and proteins that warrant further study in fully grasping the precise molecular mechanisms that control the seed dormancy and germination of A. tsaoko. A hypothetical model of the genetic regulatory network provides a theoretical basis for overcoming the physiological dormancy in A. tsaoko in the future.

Regulatory mechanism of GA3 on tuber growth by DELLA-dependent pathway in yam (Dioscorea opposita).

KEY MESSAGE: Endogenous and exogenous GA3 responses to DoEXP and DoXTH depend on the DoGA20ox1, DoGA3ox1, DoGA2ox3, DoGA2ox4, DoGID1a, and DoDELLA1 to regulate yam tuber growth. Yam tuber undergoes significant alteration in morphogenesis and functions during growth, and gibberellins (GA) are considered potentially important regulators of tuber growth. However, it is little known about the regulation of GA metabolism and GA signaling components genes in tuber growth of yam. In this study, the cloning and expressions of GA3 level, GA metabolism and signaling genes, and cell wall genes in tuber growth in response to GA3 and GA biosynthesis inhibitor paclobutrazol (PP333) treatments were studied. The contents of GA3 accumulated at the tuber growth, with the highest levels in the early expansion stage. DoGA20ox1, DoGA3ox1, and four DoGA2ox genes were significantly abundant in the early expansion stage of tuber and gradually declined along with tuber growth. Three DoGID1 and three DoDELLA genes were showed different expression patterns in the early expansion stage of tuber and gradually declined along with tuber growth. Five DoEXP and three DoXTH genes expression levels were higher in the early expansion stage than in other stages. Exogenous GA3 increased endogenous GA3 levels, whereas the expression levels of DoGA20ox1, DoGA3ox1, DoGID1a, and DoDELLA1 were down-regulated in the early expansion stage of tuber by GA3 treatment, DoGA2ox3 and DoGA2ox4 were up-regulated. PP333 application exhibited opposite consequences. Thus, a mechanism of GA3 regulating yam tuber growth by DELLA-dependent pathway is established.

Integrated mRNA and miRNA transcriptome analysis reveals a regulatory network for tuber expansion in Chinese yam (Dioscorea opposita).

BACKGROUND: Yam tuber is a storage organ, derived from the modified stem. Tuber expansion is a complex process, and depends on the expressions of genes that can be influenced by environmental and endogenous factors. However, little is known about the regulatory mechanism of tuber expansion. In order to identify the genes and miRNAs involved in tuber expansion, we examined the mRNAs and small RNAs in Dioscorea opposita (Chinese yam) cv. Guihuai 16 tuber during its initiation and expansion stages. RESULTS: A total of 14,238 differentially expressed genes in yam tuber at its expansion stage were identified by using RNA sequencing technology. Among them, 5723 genes were up-regulated, and 8515 genes were down-regulated. Functional analysis revealed the coordination of tuber plant involved in processes of cell events, metabolism, biosynthesis, and signal transduction pathways at transcriptional level, suggesting that these differentially expressed genes are somehow involved in response to tuber expansion, including CDPK, CaM, CDL, SAUR, DELLA, SuSy, and expansin. In addition, 541 transcription factor genes showed differential expression during the expansion stage at transcriptional level. MADS, bHLH, and GRAS were involved in cell differentiation, division, and expansion, which may relate to tuber expansion. Noteworthy, data analysis revealed that 22 known tuber miRNAs belong to 10 miRNA families, and 50 novel miRNAs were identified. The integrated analysis of miRNA-mRNA showed that 4 known miRNAs and 11 genes formed 14 miRNA-target mRNA pairs were co-expressed in expansion stage. miRNA160, miRNA396, miRNA535 and miRNA5021 may be involved in complex network to regulate cell division and differentiation in yam during its expansion stage. CONCLUSION: The mRNA and miRNA datasets presented here identified a subset of candidate genes and miRNAs that are putatively associated with tuber expansion in yam, a hypothetical model of genetic regulatory network associated with tuber expansion in yam was put forward, which may provide a foundation for molecular regulatory mechanism researching on tuber expansion in Dioscorea species.

Identifying rice field weeds from unmanned aerial vehicle remote sensing imagery using deep learning.

BACKGROUND: Rice field weed object detection can provide key information on weed species and locations for precise spraying, which is of great significance in actual agricultural production. However, facing the complex and changing real farm environments, traditional object detection methods still have difficulties in identifying small-sized, occluded and densely distributed weed instances. To address these problems, this paper proposes a multi-scale feature enhanced DETR network, named RMS-DETR. By adding multi-scale feature extraction branches on top of DETR, this model fully utilizes the information from different semantic feature layers to improve recognition capability for rice field weeds in real-world scenarios. METHODS: Introducing multi-scale feature layers on the basis of the DETR model, we conduct a differentiated design for different semantic feature layers. The high-level semantic feature layer adopts Transformer structure to extract contextual information between barnyard grass and rice plants. The low-level semantic feature layer uses CNN structure to extract local detail features of barnyard grass. Introducing multi-scale feature layers inevitably leads to increased model computation, thus lowering model inference speed. Therefore, we employ a new type of Pconv (Partial convolution) to replace traditional standard convolutions in the model. RESULTS: Compared to the original DETR model, our proposed RMS-DETR model achieved an average recognition accuracy improvement of 3.6% and 4.4% on our constructed rice field weeds dataset and the DOTA public dataset, respectively. The average recognition accuracies reached 0.792 and 0.851, respectively. The RMS-DETR model size is 40.8 M with inference time of 0.0081 s. Compared with three classical DETR models (Deformable DETR, Anchor DETR and DAB-DETR), the RMS-DETR model respectively improved average precision by 2.1%, 4.9% and 2.4%. DISCUSSION: This model is capable of accurately identifying rice field weeds in complex real-world scenarios, thus providing key technical support for precision spraying and management of variable-rate spraying systems.

Disinfection of wastewater by a complete equipment based on a novel ultraviolet light source of microwave discharge electrodeless lamp: Characteristics of bacteria inactivation, reactivation and full-scale studies.

Ultraviolet (UV) light is widely used for wastewater disinfection. Traditional electrode-excited UV lamps, such as low-pressure mercy lamps (LPUV), encounter drawbacks like electrode aging and rapid light attenuation. A novel UV source of microwave discharge electrodeless lamp (MDEL) has aroused attention, yet its disinfection performance is unclear and still far from practical application. Here, we successfully developed a complete piece of equipment based on MDELs and achieved the application for disinfection in wastewater treatment plants (WWTPs). The light emitted by an MDEL (MWUV) shared a spectrum similar to that of LPUV, with the main emission wavelength at 254 nm. The inactivation rate of Gram-negative E. coli by MWUV reached 4.5 log at an intensity of 1.6 mW/cm2 and a dose of 20 mJ/cm2. For Gram-positive B. subtilis, an MWUV dose of 50 mJ/cm2 and a light intensity of 1.2 mW/cm2 reached an inactivation rate of 3.4 log. A higher MWUV intensity led to a better disinfection effect and a lower photoreactivation rate of E. coli. When inactivated by MWUV with an intensity of 1.2 mW/cm2 and a dose of 16 mJ/cm2, the maximum photoreactivation rate and reactivation rate constant Kmax of E. coli were 0.63 % and 0.11 % h-1 respectively. Compared with the photoreactivation, the dark repair of E. coli was insignificant. The full-scale application of the MDEL equipment was conducted in two WWTPs (10,000 m3/d and 15,000 m3/d). Generally 2-3 log inactivation rates of fecal coliforms in secondary effluent were achieved within 5-6 s contact time, and the disinfected effluent met the emission standard (1000 CFU/L). This study successfully applied MDEL for disinfection in WWTPs for the first time and demonstrated that MDEL has broad application prospects.

Transcriptomics and metabolomics association analysis revealed the responses of Gynostemma pentaphyllum to cadmium.

Gynostemma pentaphyllum an important medicinal herb, can absorb high amounts of cadmium (Cd) which can lead to excessive Cd contamination during the production of medicines and tea. Hence, it is crucial to investigate the response mechanism of G. pentaphyllum under Cd stress to develop varieties with low Cd accumulation and high tolerance. Physiological response analysis, transcriptomics and metabolomics were performed on G. pentaphyllum seedlings exposed to Cd stress. Herein, G. pentaphyllum seedlings could significantly enhance antioxidant enzyme activities (POD, CAT and APX), proline and polysaccharide content subject to Cd stress. Transcriptomics analysis identified the secondary metabolites, carbohydrate metabolism, amino acid metabolism, lipid metabolism, and signal transduction pathways associated with Cd stress, which mainly involved the XTH, EXP and GST genes. Metabolomics analysis identified 126 differentially expressed metabolites, including citric acid, flavonoid and amino acids metabolites, which were accumulated under Cd stress. Multi-omics integrative analysis unraveled that the phenylpropanoid biosynthesis, starch, and sucrose metabolism, alpha-linolenic acid metabolism, and ABC transporter were significantly enriched at the gene and metabolic levels in response to Cd stress in G. pentaphyllum. In conclusion, the genetic regulatory network sheds light on Cd response mechanisms in G. pentaphyllum.

Amomum tsaoko DRM1 regulate seed germination and improve heat tolerance in Arabidopsis.

Seed dormancy and germination are critical to medicinal plant reproduction. Dormancy-associated gene (DRM1) has been involved in the regulation of dormancy in Arabidopsis meristematic tissues or organs. However, research on molecular functions and regulations of DRM1 in Amomum tsaoko, an important medicinal plant, is rare. In this study, the DRM1 was isolated from embryos of A. tsaoko, and the results of protein subcellular localization in Arabidopsis protoplast indicated that DRM1 was mainly nucleus and cytoplasm. Expression analysis showed that DRM1 especially exhibited the highest transcript level in dormant seed and short-time stratification while displaying a high response of hormone and abiotic stress. Further investigation showed that ectopic expression of DRM1 in Arabidopsis exhibited delayed seed germination and germination capability to high temperatures. Additionally, DRM1 transgenic Arabidopsis exhibited increased tolerance to heat stress by enhancing antioxidative capacities and regulating stress-associated genes (AtHsp25.3-P, AtHsp18.2-CI, AtHsp70B, AtHsp101, AtGolS1, AtMBF1c, AtHsfA2, AtHsfB1 and AtHsfB2). Overall, our results reveal the role of DRM1 in seed germination and abiotic stress response.

Nanoparticle surface decoration mediated efficient protein and peptide co-encapsulation with precise ratiometric control for self-regulated drug release.

Accuratly controlling drug release from a smart "self-regulated" drug delivery system is still an ongoing challenge. Herein, we developed a surface decoration strategy to achieve an efficient drug encapsulation with precise ratiometric control. Thanks to the surface decoration with cationic carrier materials by electrostatic attraction, the surface properties of different protein and peptide nanoparticles were uniformed to those adsorbed carrier materials. These carrier materials endowed protein and peptide nanoparticles with good dispersity in the oil phase and significantly inhibited the drug transfer from oil to water. With uniform surface properties, we realized the co-encapsulation of multiple types of proteins and peptides with precise ratiometric control. The encapsulation efficiency was higher than 87.8% for insulin. After solidification, the adsorbed materials on the surface of nanoparticles formed a solid protection layer, which prolonged the mean residence time of insulin from 3.3 ± 0.1 h (for insulin solution) to 47.5 ± 1.3 h. In type 1 diabetes, the spermine-modified acetalated dextran microparticle co-loaded with insulin, glucose oxidase and catalase maintained the blood glucose level within the normal range for 7 days.

Dendritic cell-targeting chemokines inhibit colorectal cancer progression.

Aim: Recent progress in cancer immunotherapy has shown its promise and prompted researchers to develop novel therapeutic strategies. Dendritic cells (DCs) are professional antigen-presenting cells crucial for initiating adaptive anti-tumor immunity, therefore a promising target for cancer treatment. Here, anti-tumor activities of DC-targeting chemokines were explored in murine colorectal tumor models. Methods: The correlation of chemokine messenger RNA (mRNA) expression with DC markers was analyzed using The Cancer Genome Atlas (TCGA) dataset. Murine colorectal tumor cell lines (CT26 and MC38) stably overexpressing mouse C-C motif chemokine ligand 3 (CCL3), CCL19, CCL21, and X-C motif chemokine ligand 1 (XCL1) were established by lentiviral transduction. The effect of chemokines on tumor cell proliferation/survival was evaluated in vitro by cell counting kit-8 (CCK-8) assay and colony formation assay. Syngeneic subcutaneous tumor models were used to study the effects of these chemokines on tumor growth. Ki-67 expression in tumors was examined by immunohistochemistry. Immune cells in the tumor microenvironment (TME) and lymph nodes were analyzed by flow cytometry. Results: Expression of the four chemokines was positively correlated with the two DC markers [integrin alpha X (ITGAX) and CLEC9A] in human colorectal tumor samples. Tumoral overexpression of DC-targeting chemokines had little or no effect on tumor cell proliferation/survival in vitro while significantly suppressing tumor growth in vivo. Fluorescence-activated cell sorting (FACS) analysis showed that CCL19, CCL21, and XCL1 boosted the ratios of DCs and T cells in CD45+ leukocytes while CCL3 increased the percentage of CD45+ leukocytes in total cells in MC38 tumor. XCL1 had an additional positive effect on antigen uptake by DCs in the TME and antigen transfer to tumor-draining lymph nodes. Conclusions: CCL3, CCL19, CCL21, and XCL1 exhibited potent anti-tumor activities in vivo, although they might differentially regulate immune cells in the TME and antigen transfer to lymph nodes.

Cyclodextrin boostered-high density lipoprotein for antiatherosclerosis by regulating cholesterol efflux and efferocytosis.

A promising therapy for atherosclerosis treatment was designed by targeting LXR receptor (LXR) on atherosclerotic macrophage, where LXR activation could regulate cholesterol efflux and efferocytosis. Herein, a sequential-targeting nanoplatform (HT-rHDL) was constructed to deliver LXR agonist into macrophage, which was composed of discoidal reconstituted high-density lipoprotein (d-rHDL) core for agonist encapsulation and external modifications: (i) the outermost hyaluronan, targeting injured endothelium; (ii) modified ß-cyclodextrin of d-rHDL, accelerating cholesterol efflux of foam cells; (iii) conjugated apolipoprotein A-I of d-rHDL, targeting macrophage. This design underlines that the nanoplatform could increase its plaque accumulation, accomplish cholesterol efflux-remodeling-drug delivery behavior and specifically activate LXR in macrophage. After a 3-month treatment with HT-rHDL, 31.47% plaque area reduction, 56.0% lipid accumulation decrease, obvious inflammation resolution and enhanced plaque stability were observed. Furthermore, the atherosclerosis intervention was demonstrated to benefit from the upregulations of ABC transporters and Mer tyrosine kinase. Collectively, HT-rHDL provides new strategies to regress atherosclerosis.

[Bioluminescence in-vivo imaging technology and its application in the study of viral infection--a review].

Bioluminescence imaging is one of the bio-optical imaging techniques which report definite biological event in living animals with genetic modification. With high sensitivity, simple operation and high precision, it is particularly applied in observing vital processes like viral infection and tumor growth in vivo. We summarize the principle of bioluminescence imaging, introduce its application in finding virus replication site, study of interferon (IFN) inhibiting-virus effect and real-time visualization of viral latent infection and reactivation, and preview the trend of bioluminescence imaging technological development.

Transcriptome analysis reveals significant difference in gene expression and pathways between two peanut cultivars under Al stress.

Aluminum (Al) toxicity is an important factor in limiting peanut growth on acidic soil. The molecular mechanisms underlying peanut responses to Al stress are largely unknown. In this study, we performed transcriptome analysis of the root tips (0-1 cm) of peanut cultivar ZH2 (Al-sensitive) and 99-1507 (Al-tolerant) respectively. Root tips of peanuts that treated with 100 µM Al for 8 h and 24 h were analyzed by RNA-Seq, and a total of 8,587 differentially expressed genes (DEGs) were identified. GO and KEGG pathway analysis excavated a group of important Al-responsive genes related to organic acid transport, metal cation transport, transcription regulation and programmed cell death (PCD). These homologs were promising targets to modulate Al tolerance in peanuts. It was found that the rapid transcriptomic response to Al stress in 99-1507 helped to activate effective Al tolerance mechanisms. Protein and protein interaction analysis indicated that MAPK signal transduction played important roles in the early response to Al stress in peanuts. Moreover, weighted correlation network analysis (WGCNA) identified a predicted EIL (EIN3-like) gene with greatly increased expression as an Al-associated gene, and revealed a link between ethylene signaling transduction and Al resistance related genes in peanut, which suggested the enhanced signal transduction mediated the rapid transcriptomic responses. Our results revealed key pathways and genes associated with Al stress, and improved the understanding of Al response in peanut.

Recent advances in studies of 15-PGDH as a key enzyme for the degradation of prostaglandins.

15-hydroxyprostaglandin dehydrogenase (15-PGDH; encoded by HPGD) is ubiquitously expressed in mammalian tissues and catalyzes the degradation of prostaglandins (PGs; mainly PGE2, PGD2, and PGF2α) in a process mediated by solute carrier organic anion transport protein family member 2A1 (SLCO2A1; also known as PGT, OATP2A1, PHOAR2, or SLC21A2). As a key enzyme, 15-PGDH catalyzes the rapid oxidation of 15-hydroxy-PGs into 15-keto-PGs with lower biological activity. Increasing evidence suggests that 15-PGDH plays a key role in many physiological and pathological processes in mammals and is considered a potential pharmacological target for preventing organ damage, promoting bone marrow graft recovery, and enhancing tissue regeneration. Additionally, results of whole-exome analyses suggest that recessive inheritance of an HPGD mutation is associated with idiopathic hypertrophic osteoarthropathy. Interestingly, as a tumor suppressor, 15-PGDH inhibits proliferation and induces the differentiation of cancer cells (including those associated with colorectal, lung, and breast cancers). Furthermore, a recent study identified 15-PGDH as a marker of aging tissue and a potential novel therapeutic target for resisting the complex pathology of aging-associated diseases. Here, we review and summarise recent information on the molecular functions of 15-PGDH and discuss its pathophysiological implications.

Effective connectivity in autism.

The aim was to go beyond functional connectivity, by measuring in the first large-scale study differences in effective, that is directed, connectivity between brain areas in autism compared to controls. Resting-state functional magnetic resonance imaging was analyzed from the Autism Brain Imaging Data Exchange (ABIDE) data set in 394 people with autism spectrum disorder and 473 controls, and effective connectivity (EC) was measured between 94 brain areas. First, in autism, the middle temporal gyrus and other temporal areas had lower effective connectivities to the precuneus and cuneus, and these were correlated with the Autism Diagnostic Observational Schedule total, communication, and social scores. This lower EC from areas implicated in face expression analysis and theory of mind to the precuneus and cuneus implicated in the sense of self may relate to the poor understanding of the implications of face expression inputs for oneself in autism, and to the reduced theory of mind. Second, the hippocampus and amygdala had higher EC to the middle temporal gyrus in autism, and these are thought to be back projections based on anatomical evidence and are weaker than in the other direction. This may be related to increased retrieval of recent and emotional memories in autism. Third, some prefrontal cortex areas had higher EC with each other and with the precuneus and cuneus. Fourth, there was decreased EC from the temporal pole to the ventromedial prefrontal cortex, and there was evidence for lower activity in the ventromedial prefrontal cortex, a brain area implicated in emotion-related decision-making. Autism Res 2020, 13: 32-44. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: To understand autism spectrum disorders better, it may be helpful to understand whether brain systems cause effects on each other differently in people with autism. In this first large-scale neuroimaging investigation of effective connectivity in people with autism, it is shown that parts of the temporal lobe involved in facial expression identification and theory of mind have weaker effects on the precuneus and cuneus implicated in the sense of self. This may relate to the poor understanding of the implications of face expression inputs for oneself in autism, and to the reduced theory of mind.

Adolescent binge drinking disrupts normal trajectories of brain functional organization and personality maturation.

Adolescent binge drinking has been associated with higher risks for the development of many health problems throughout the lifespan. Adolescents undergo multiple changes that involve the co-development processes of brain, personality and behavior; therefore, certain behavior, such as alcohol consumption, can have disruptive effects on both brain development and personality maturation. However, these effects remain unclear due to the scarcity of longitudinal studies. In the current study, we used multivariate approaches to explore discriminative features in brain functional architecture, personality traits, and genetic variants in 19-year-old individuals (n = 212). Taking advantage of a longitudinal design, we selected features that were more drastically altered in drinkers with an earlier onset of binge drinking. With the selected features, we trained a hierarchical model of support vector machines using a training sample (n = 139). Using an independent sample (n = 73), we tested the model and achieved a classification accuracy of 71.2%. We demonstrated longitudinally that after the onset of binge drinking the developmental trajectory of improvement in impulsivity slowed down. This study identified the disrupting effects of adolescent binge drinking on the developmental trajectories of both brain and personality.

An asymptotic theory for cross-correlation between auto-correlated sequences and its application on neuroimaging data.

BACKGROUND: Functional connectivity is among the most important tools to study brain. The correlation coefficient, between time series of different brain areas, is the most popular method to quantify functional connectivity. Correlation coefficient in practical use assumes the data to be temporally independent. However, the time series data of brain can manifest significant temporal auto-correlation. NEW METHOD: A widely applicable method is proposed for correcting temporal auto-correlation. We considered two types of time series models: (1) auto-regressive-moving-average model, (2) nonlinear dynamical system model with noisy fluctuations, and derived their respective asymptotic distributions of correlation coefficient. These two types of models are most commonly used in neuroscience studies. We show the respective asymptotic distributions share a unified expression. RESULT: We have verified the validity of our method, and shown our method exhibited sufficient statistical power for detecting true correlation on numerical experiments. Employing our method on real dataset yields more robust functional network and higher classification accuracy than conventional methods. COMPARISON WITH EXISTING METHODS: Our method robustly controls the type I error while maintaining sufficient statistical power for detecting true correlation in numerical experiments, where existing methods measuring association (linear and nonlinear) fail. CONCLUSIONS: In this work, we proposed a widely applicable approach for correcting the effect of temporal auto-correlation on functional connectivity. Empirical results favor the use of our method in functional network analysis.