Sci Total Environ , IF:7.963 , 2021 Aug , V784 : P147085 doi: 10.1016/j.scitotenv.2021.147085
Unfolding the synergy and interaction of water-land-food nexus for sustainable resource management: A supernetwork analysis.
School of Management Sci & Real Estate, Chongqing University, Chongqing 400045, PR China.; School of Management Sci & Real Estate, Chongqing University, Chongqing 400045, PR China. Electronic address: hongjingke@cqu.edu.cn.; Artificial Intelligence and Earth Perception Research Center, School of Automation Engineering, University of Electronic Science and Technology, Chengdu 610054, PR China; Shenzhen Shiruikongjian Technologies Co., Ltd, Shenzhen 518101, PR China.; Construction Science Technology Group Co., Ltd of China, Beijing 100013, PR China.
Given the large amounts of water, land, and food embodied in the trade of goods and services, a key step in decoupling extensive resource consumption from the economic system is to understand the full impact of socioeconomic development on the water-land-food nexus. This study integrates input-output analysis, ecological network analysis, and Dempster-Shafer evidence theory into a supernetwork model to detect the water-land-food nexus among economic sectors with an aim to explore effective strategic paths for resource management and to facilitate the construction of a resource-saving society. Results show that most sectors of China are resource inefficient and that all resource systems are unsustainable as reflected in the low performance of their Finn's cycling index and system robustness. Meanwhile, results of flow networks analysis show an extremely uneven land resource allocation where more than 94% of the land used in China is classified as direct agricultural land. The water-land-food nexus can gain resource saving bonus via enhancing the robustness of economy. However, the co-benefits from the nexus are negligibly small for the resource utilization efficiency. The results also indicate that the relevant resource-saving policies on food and water are highly likely to gain resource co-benefits due to their similarities in sectoral importance. Correspondingly, a set of strategic measures, including adopting a tiered resource price, deepening industrial convergence of agriculture, enhancing agriculture-food nexus, and managing water or land use from the food consumer side, are designed to build a resource-saving society. The findings of this study can provide additional insights into the impacts of the economy on the water-land-food nexus, which is beneficial for achieving an efficient and coordinated management of resources.
PMID: 34088023
J Behav Addict , IF:6.756 , 2021 Aug doi: 10.1556/2006.2021.00048
Understanding juveniles' problematic smartphone use and related influencing factors: A network perspective.
1State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.; 2School of Education, Henan University, Kaifeng, China.; 3Collaborative Innovation Centre of Assessment for Basic Education Quality, Beijing Normal University, Beijing, China.
Background and aims: To understand the interaction between problematic smartphone use (PSU) and related influencing factors (individual variables, family environment, and school environment) and to determine the most influential factors affecting the use of smartphones by juveniles to implement effective interventions in the future. Methods: A total of 3,442 children and adolescents (3,248 actual participants (males = 1,638, average age = 12.27 +/- 2.36)) were included in the study. This study measured juveniles' PSU and its influencing factors: individual variables (4 factors), family environments (13 factors), and school environments (5 factors). This study employed a network analysis approach for data assessment. Results: This study found that there were several central influencing factors (such as self-control ability, loss of control, parent-child relationship, and peer attitudes towards smartphone use) and bridge factors (such as peer attitudes towards smartphone use, peer pressure for smartphone use, and fear of missing out). Discussion and conclusions: Juveniles' PSU included several core symptoms and critical influencing factors. Intervention based on these factors may be effective, timely, and inexpensive.
PMID: 34406975
mSystems , IF:6.496 , 2021 Aug : Pe0017321 doi: 10.1128/mSystems.00173-21
Investigating the Chemolithoautotrophic and Formate Metabolism of Nitrospira moscoviensis by Constraint-Based Metabolic Modeling and (13)C-Tracer Analysis.
Department of Civil and Environmental Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA.; DOE Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, Wisconsin, USA.; Department of Microbiology, Radboud Institute for Biological and Environmental Sciences, Radboud University, Nijmegen, The Netherlands.; Department of Biotechnology, Delft University of Technologygrid.5292.c, Delft, The Netherlands.; Department of Bacteriology, University of Wisconsin-Madison, Madison, Wisconsin, USA.
Nitrite-oxidizing bacteria belonging to the genus Nitrospira mediate a key step in nitrification and play important roles in the biogeochemical nitrogen cycle and wastewater treatment. While these organisms have recently been shown to exhibit metabolic flexibility beyond their chemolithoautotrophic lifestyle, including the use of simple organic compounds to fuel their energy metabolism, the metabolic networks controlling their autotrophic and mixotrophic growth remain poorly understood. Here, we reconstructed a genome-scale metabolic model for Nitrospira moscoviensis (iNmo686) and used flux balance analysis to evaluate the metabolic networks controlling autotrophic and formatotrophic growth on nitrite and formate, respectively. Subsequently, proteomic analysis and [(13)C]bicarbonate and [(13)C]formate tracer experiments coupled to metabolomic analysis were performed to experimentally validate model predictions. Our findings corroborate that N. moscoviensis uses the reductive tricarboxylic acid cycle for CO2 fixation, and we also show that N. moscoviensis can indirectly use formate as a carbon source by oxidizing it first to CO2 followed by reassimilation, rather than direct incorporation via the reductive glycine pathway. Our study offers the first measurements of Nitrospira's in vivo central carbon metabolism and provides a quantitative tool that can be used for understanding and predicting their metabolic processes. IMPORTANCE Nitrospira spp. are globally abundant nitrifying bacteria in soil and aquatic ecosystems and in wastewater treatment plants, where they control the oxidation of nitrite to nitrate. Despite their critical contribution to nitrogen cycling across diverse environments, detailed understanding of their metabolic network and prediction of their function under different environmental conditions remains a major challenge. Here, we provide the first constraint-based metabolic model of Nitrospira moscoviensis representing the ubiquitous Nitrospira lineage II and subsequently validate this model using proteomics and (13)C-tracers combined with intracellular metabolomic analysis. The resulting genome-scale model will serve as a knowledge base of Nitrospira metabolism and lays the foundation for quantitative systems biology studies of these globally important nitrite-oxidizing bacteria.
PMID: 34402644
Int J Mol Sci , IF:5.923 , 2021 Aug , V22 (16) doi: 10.3390/ijms22168554
Integrating the Roles for Cytokinin and Auxin in De Novo Shoot Organogenesis: From Hormone Uptake to Signaling Outputs.
Department of Plant Physiology, Institute for Biological Research "Sinisa Stankovic"-National Institute of Republic of Serbia, University of Belgrade, Bulevar Despota Stefana 142, 11060 Belgrade, Serbia.; Laboratory of Hormonal Regulations in Plants, Institute of Experimental Botany of the Czech Academy of Sciences, Rozvojova 263, 16502 Prague 6, Czech Republic.; School of Life Science and Engineering, Southwest University of Science and Technology, Mianyang 621010, China.
De novo shoot organogenesis (DNSO) is a procedure commonly used for the in vitro regeneration of shoots from a variety of plant tissues. Shoot regeneration occurs on nutrient media supplemented with the plant hormones cytokinin (CK) and auxin, which play essential roles in this process, and genes involved in their signaling cascades act as master regulators of the different phases of shoot regeneration. In the last 20 years, the genetic regulation of DNSO has been characterized in detail. However, as of today, the CK and auxin signaling events associated with shoot regeneration are often interpreted as a consequence of these hormones simply being present in the regeneration media, whereas the roles for their prior uptake and transport into the cultivated plant tissues are generally overlooked. Additionally, sucrose, commonly added to the regeneration media as a carbon source, plays a signaling role and has been recently shown to interact with CK and auxin and to affect the efficiency of shoot regeneration. In this review, we provide an integrative interpretation of the roles for CK and auxin in the process of DNSO, adding emphasis on their uptake from the regeneration media and their interaction with sucrose present in the media to their complex signaling outputs that mediate shoot regeneration.
PMID: 34445260
Front Plant Sci , IF:5.753 , 2021 , V12 : P650252 doi: 10.3389/fpls.2021.650252
Transcriptome and Coexpression Network Analyses Reveal Hub Genes in Chinese Cabbage (Brassica rapa L. ssp. pekinensis) During Different Stages of Plasmodiophora brassicae Infection.
Institute of Horticulture, Henan Academy of Agricultural Sciences, Graduate T&R Base of Zhengzhou University, Zhengzhou, China.; School of Life Sciences, Zhengzhou University, Zhengzhou, China.
Clubroot, caused by the soil-borne protist Plasmodiophora brassicae, is one of the most destructive diseases of Chinese cabbage worldwide. However, the clubroot resistance mechanisms remain unclear. In this study, in both clubroot-resistant (DH40R) and clubroot-susceptible (DH199S) Chinese cabbage lines, the primary (root hair infection) and secondary (cortical infection) infection stages started 2 and 5 days after inoculation (dai), respectively. With the extension of the infection time, cortical infection was blocked and complete P. brassica resistance was observed in DH40R, while disease scales of 1, 2, and 3 were observed at 8, 13, and 22 dai in DH199S. Transcriptome analysis at 0, 2, 5, 8, 13, and 22 dai identified 5,750 relative DEGs (rDEGs) between DH40R and DH199S. The results indicated that genes associated with auxin, PR, disease resistance proteins, oxidative stress, and WRKY and MYB transcription factors were involved in clubroot resistance regulation. In addition, weighted gene coexpression network analysis (WGCNA) identified three of the modules whose functions were highly associated with clubroot-resistant, including ten hub genes related to clubroot resistance (ARF2, EDR1, LOX4, NHL3, NHL13, NAC29, two AOP1, EARLI 1, and POD56). These results provide valuable information for better understanding the molecular regulatory mechanism of Chinese cabbage clubroot resistance.
PMID: 34447397
Plant Physiol Biochem , IF:4.27 , 2021 Aug , V167 : P541-549 doi: 10.1016/j.plaphy.2021.08.028
Comparative transcriptomic of Stevia rebaudiana provides insight into rebaudioside D and rebaudioside M biosynthesis.
Dalian Engineering Research Center for Carbohydrate Agricultural Preparations, Liaoning Provincial Key Laboratory of Carbohydrates, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China; University of Chinese Academy of Sciences, Beijing, 100049, China. Electronic address: wangyu@dicp.ac.cn.; Dalian Engineering Research Center for Carbohydrate Agricultural Preparations, Liaoning Provincial Key Laboratory of Carbohydrates, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China. Electronic address: sunxue@dicp.ac.cn.; Dalian Engineering Research Center for Carbohydrate Agricultural Preparations, Liaoning Provincial Key Laboratory of Carbohydrates, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China. Electronic address: jiaxiaochen@dicp.ac.cn.; Zhucheng Haotian Pharm Co., Ltd, Shandong, 262200, China; Dongtai Hirye Biotechnology Co., Ltd, Jiangsu, 224200, China. Electronic address: Amy@zcht.cc.; Dalian Engineering Research Center for Carbohydrate Agricultural Preparations, Liaoning Provincial Key Laboratory of Carbohydrates, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China; University of Chinese Academy of Sciences, Beijing, 100049, China. Electronic address: yinheng@dicp.ac.cn.
Rebaudioside D (Reb D) and rebaudioside M (Reb M) are commercially important low/no-calorie natural sweeteners. However, they are present in a minor proportion of all steviol glycosides (SGs) in Stevia rebaudiana Bertoni (S. rebaudiana). Strain-dependent deviation in Reb D and Reb M biosynthesis is one key breach for breeding of S. rebaudiana, which has not been studied at the transcriptional level. Herein, five different S. rebaudiana varieties with distinct SGs contents, one cultivar having high stevioside content (HST), one cultivar having high Reb A content (HRA) and three cultivars having high Reb D and Reb M content (HDM1, HDM2, HDM3), were selected for RNA-seq analysis. In total, 131,655 de novo assembled unigenes were found in the RNA-seq data. According to Reb D and Reb M content divergence of S. rebaudiana accessions, 2186 differentially expressed genes (DEGs) were selected as potential genes related to Reb D and Reb M biosynthesis. Weighted Gene Co-expression Network Analysis (WGCNA) was used to explore the genes associated with the Reb D and Reb M biosynthesis. The unigenes from the positively associated turquoise module formed a layered co-expression network. There are 7 UDP-dependent glycosyltransferases (UGT) and 76 transcription factors (TFs) distributing at different regions which represented varying coherence of Reb D and Reb M biosynthesis. Particularly, two TFs having a strong correlation with two UGTs in the network were also discovered. The present study provided a comprehensive insight into networks for regulation of Reb D and Reb M contents in S. rebaudiana.
PMID: 34425398
PeerJ , IF:2.984 , 2021 , V9 : Pe11876 doi: 10.7717/peerj.11876
Potential Arabidopsis thaliana glucosinolate genes identified from the co-expression modules using graph clustering approach.
Centre for Bioinformatics Research, Institute of Systems Biology (INBIOSIS), Universiti Kebangsaan Malaysia, UKM Bangi, Selangor, Malaysia.; Institute of Marine Biotechnology, Universiti Malaysia Terengganu, Kuala Nerus, Terengganu, Malaysia.; Graduate School of Science and Technology & NAIST Data Science Center, Nara Institute of Science and Technology, Nara, Japan.; Department of Applied Physics, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, UKM Bangi, Selangor, Malaysia.
Background: Glucosinolates (GSLs) are plant secondary metabolites that contain nitrogen-containing compounds. They are important in the plant defense system and known to provide protection against cancer in humans. Currently, increasing the amount of data generated from various omics technologies serves as a hotspot for new gene discovery. However, sometimes sequence similarity searching approach is not sufficiently effective to find these genes; hence, we adapted a network clustering approach to search for potential GSLs genes from the Arabidopsis thaliana co-expression dataset. Methods: We used known GSL genes to construct a comprehensive GSL co-expression network. This network was analyzed with the DPClusOST algorithm using a density of 0.5. 0.6. 0.7, 0.8, and 0.9. Generating clusters were evaluated using Fisher's exact test to identify GSL gene co-expression clusters. A significance score (SScore) was calculated for each gene based on the generated p-value of Fisher's exact test. SScore was used to perform a receiver operating characteristic (ROC) study to classify possible GSL genes using the ROCR package. ROCR was used in determining the AUC that measured the suitable density value of the cluster for further analysis. Finally, pathway enrichment analysis was conducted using ClueGO to identify significant pathways associated with the GSL clusters. Results: The density value of 0.8 showed the highest area under the curve (AUC) leading to the selection of thirteen potential GSL genes from the top six significant clusters that include IMDH3, MVP1, T19K24.17, MRSA2, SIR, ASP4, MTO1, At1g21440, HMT3, At3g47420, PS1, SAL1, and At3g14220. A total of Four potential genes (MTO1, SIR, SAL1, and IMDH3) were identified from the pathway enrichment analysis on the significant clusters. These genes are directly related to GSL-associated pathways such as sulfur metabolism and valine, leucine, and isoleucine biosynthesis. This approach demonstrates the ability of the network clustering approach in identifying potential GSL genes which cannot be found from the standard similarity search.
PMID: 34430080