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Neurosci Biobehav Rev , IF:8.33 , 2019 Apr , V99 : P128-137 doi: 10.1016/j.neubiorev.2019.01.002

The structural connectome in traumatic brain injury: A meta-analysis of graph metrics.

Imms, Phoebe and Clemente, Adam and Cook, Mark and D'Souza, Wendyl and Wilson, Peter H and Jones, Derek K and Caeyenberghs, Karen

Mary MacKillop Institute for Heatlh Research, Faculty of Health Sciences, Australian Catholic University. 115 Victoria Parade, Melbourne, VIC, 3065, Australia. Electronic address: Phoebe.Imms@myacu.edu.au.; Mary MacKillop Institute for Heatlh Research, Faculty of Health Sciences, Australian Catholic University. 115 Victoria Parade, Melbourne, VIC, 3065, Australia. Electronic address: Adam.Clemente@myacu.edu.au.; Department of Medicine, St. Vincent's Hospital, University of Melbourne. 41 Victoria Parade, Melbourne, VIC, 3065, Australia. Electronic address: markcook@unimelb.edu.au.; Department of Medicine, St. Vincent's Hospital, University of Melbourne. 41 Victoria Parade, Melbourne, VIC, 3065, Australia. Electronic address: wendyl1@icloud.com.; Mary MacKillop Institute for Heatlh Research, Faculty of Health Sciences, Australian Catholic University. 115 Victoria Parade, Melbourne, VIC, 3065, Australia. Electronic address: Peter.Wilson@acu.edu.au.; Mary MacKillop Institute for Heatlh Research, Faculty of Health Sciences, Australian Catholic University. 115 Victoria Parade, Melbourne, VIC, 3065, Australia; Cardiff University Brain Research Imaging Centre, School of Psychology, and Neuroscience and Mental Health Research Institute, Cardiff University, Maindy Rd, Cardiff, CF24 4HQ, United Kingdom. Electronic address: JonesD27@cardiff.ac.uk.; Mary MacKillop Institute for Heatlh Research, Faculty of Health Sciences, Australian Catholic University. 115 Victoria Parade, Melbourne, VIC, 3065, Australia. Electronic address: Karen.Caeyenberghs@acu.edu.au.

Although recent structural connectivity studies of traumatic brain injury (TBI) have used graph theory to evaluate alterations in global integration and functional segregation, pooled analysis is needed to examine the robust patterns of change in graph metrics across studies. Following a systematic search, 15 studies met the inclusion criteria for review. Of these, ten studies were included in a random-effects meta-analysis of global graph metrics, and subgroup analyses examined the confounding effects of severity and time since injury. The meta-analysis revealed significantly higher values of normalised clustering coefficient (go=o1.445, CI=[0.512, 2.378], po=o0.002) and longer characteristic path length (go=o0.514, CI=[0.190, 0.838], po=o0.002) in TBI patients compared with healthy controls. Our findings suggest that the TBI structural network has shifted away from the balanced small-world network towards a regular lattice. Therefore, these graph metrics may be useful markers of neurocognitive dysfunction in TBI. We conclude that the pattern of change revealed by our analysis should be used to guide hypothesis-driven research into the role of graph metrics as diagnostic and prognostic biomarkers.

PMID: 30615935

J Exp Bot , IF:5.908 , 2019 Apr , V70 (9) : P2463-2477 doi: 10.1093/jxb/ery394

A multi-model framework for the Arabidopsis life cycle.

Zardilis, Argyris and Hume, Alastair and Millar, Andrew J

SynthSys and School of Biological Sciences, University of Edinburgh, Edinburgh, UK.; EPCC, University of Edinburgh, Edinburgh, UK.

Linking our understanding of biological processes at different scales is a major conceptual challenge in biology and aggravated by differences in research methods. Modelling can be a useful approach to consolidating our understanding across traditional research domains. The laboratory model species Arabidopsis is very widely used to study plant growth processes and has also been tested more recently in ecophysiology and population genetics. However, approaches from crop modelling that might link these domains are rarely applied to Arabidopsis. Here, we combine plant growth models with phenology models from ecophysiology, using the agent-based modelling language Chromar. We introduce a simpler Framework Model of vegetative growth for Arabidopsis, FM-lite. By extending this model to include inflorescence and fruit growth and seed dormancy, we present a whole-life-cycle, multi-model FM-life, which allows us to simulate at the population level in various genotype x environment scenarios. Environmental effects on plant growth distinguish between the simulated life history strategies that were compatible with previously described Arabidopsis phenology. Our results simulate reproductive success that is founded on the broad range of physiological processes familiar from crop models and suggest an approach to simulating evolution directly in future.

PMID: 31091320

J Biol Chem , IF:4.238 , 2019 Apr , V294 (14) : P5340-5351 doi: 10.1074/jbc.REV118.002958

Evolution of the multi-tRNA synthetase complex and its role in cancer.

Hyeon, Do Young and Kim, Jong Hyun and Ahn, Tae Jin and Cho, Yeshin and Hwang, Daehee and Kim, Sunghoon

From the Center for Plant Aging Research, Institute for Basic Science, Daegu Gyeongbuk Institute of Science and Technology, Daegu 711-873.; the Medicinal Bioconvergence Research Center and.; Department of Molecular Medicine and Biopharmaceutical Sciences, College of Pharmacy and Graduate School of Convergence Technologies, Seoul National University, Seoul 151-742.; the Handong Global University, Nehemiah 316, Handong-ro 558, Pohang, and.; From the Center for Plant Aging Research, Institute for Basic Science, Daegu Gyeongbuk Institute of Science and Technology, Daegu 711-873, daehee@snu.ac.kr.; the Department of New Biology, Daegu Gyeongbuk Institute of Science and Technology, Daegu 711-873, Republic of Korea.; the Medicinal Bioconvergence Research Center and sungkim@snu.ac.kr.

Aminoacyl-tRNA synthetases (ARSs) are enzymes that ligate their cognate amino acids to tRNAs for protein synthesis. However, recent studies have shown that their functions are expanded beyond protein synthesis through the interactions with diverse cellular factors. In this review, we discuss how ARSs have evolved to expand and control their functions by forming protein assemblies. We particularly focus on a macromolecular ARS complex in eukaryotes, named multi-tRNA synthetase complex (MSC), which is proposed to provide a channel through which tRNAs reach bound ARSs to receive their cognate amino acid and transit further to the translation machinery. Approximately half of the ARSs assemble into the MSC through cis-acting noncatalytic domains attached to their catalytic domains and trans-acting factors. Evolution of the MSC included its functional expansion, during which the MSC interaction network was augmented by additional cellular pathways present in higher eukaryotes. We also discuss MSC components that could be functionally involved in the pathophysiology of tumorigenesis. For example, the activities of some trans-acting factors have tumor-suppressing effects or maintain DNA integrity and are functionally compromised in cancer. On the basis of Gene Ontology analyses, we propose that the regulatory activities of the MSC-associated ARSs mainly converge on five biological processes, including mammalian target of rapamycin (mTOR) and DNA repair pathways. Future studies are needed to investigate how the MSC-associated and free-ARSs interact with each other and other factors in the control of multiple cellular pathways, and how aberrant or disrupted interactions in the MSC can cause disease.

PMID: 30782841

Microbiol Res , IF:3.97 , 2019 Apr , V221 : P50-59 doi: 10.1016/j.micres.2019.02.005

Enhanced nitrogen and phosphorus activation with an optimized bacterial community by endophytic fungus Phomopsis liquidambari in paddy soil.

Tang, Meng-Jun and Zhu, Qiang and Zhang, Feng-Min and Zhang, Wei and Yuan, Jie and Sun, Kai and Xu, Fang-Ji and Dai, Chuan-Chao

Jiangsu Key Laboratory for Microbes and Functional Genomics, Jiangsu Engineering and Technology Research Center for Industrialization of Microbial Resources, College of Life Sciences, Nanjing Normal University, Nanjing, Jiangsu Province, 210023, China.; Jiangsu Key Laboratory for Microbes and Functional Genomics, Jiangsu Engineering and Technology Research Center for Industrialization of Microbial Resources, College of Life Sciences, Nanjing Normal University, Nanjing, Jiangsu Province, 210023, China. Electronic address: daichuanchao@njnu.edu.cn.

The endophytic fungus Phomopsis liquidambari play a key role in habitat adaptation of rice (Oryza sativa L.) with potential multiple beneficial. However, our previous published work on this subject remains incomplete. Here, we performed a soil nutrient (nitrogen and phosphorus) transformation with related functional genes and elucidated how rhizosphere microbiota vary their response to P. liquidambari interaction throughout the plant's life cycle under field conditions by Illumina Miseq sequencing platforms in a nutrient-limited paddy soil. Our results showed that P. liquidambari symbiosis decreased the nitrogen and phosphorus loss by 24.59% and 17.46% per pot, respectively. Additionally, we suggest that the application of P. liquidambari altered the activation of soil nitrogen and phosphorus functional genes to accelerate nutrient turnover in the rice rhizosphere. High-throughput sequencing with co-occurrence network and species-related network analysis further revealed that P. liquidambari colonization influenced the patterns of microbiota shift in the rhizosphere, especially during the heading stages. This led to an optimized microbial community through the promotion and inhibition of indigenous soil microbes with a higher level of available nutrient supplies. Our study strongly proposes rice-P. liquidambari symbiosis as a useful candidate for improving N and P acquisition and utilization.

PMID: 30825941

Neuroscience , IF:3.056 , 2019 Apr , V403 : P35-53 doi: 10.1016/j.neuroscience.2017.10.033

Graph Theoretical Framework of Brain Networks in Multiple Sclerosis: A Review of Concepts.

Fleischer, Vinzenz and Radetz, Angela and Ciolac, Dumitru and Muthuraman, Muthuraman and Gonzalez-Escamilla, Gabriel and Zipp, Frauke and Groppa, Sergiu

Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Germany.; Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology, Institute of Emergency Medicine, Laboratory of Neurobiology and Medical Genetics, State University of Medicine and Pharmacy "Nicolae Testemitanu", Chisinau, Republic of Moldova.; Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Germany. Electronic address: segroppa@uni-mainz.de.

Network science provides powerful access to essential organizational principles of the human brain. It has been applied in combination with graph theory to characterize brain connectivity patterns. In multiple sclerosis (MS), analysis of the brain networks derived from either structural or functional imaging provides new insights into pathological processes within the gray and white matter. Beyond focal lesions and diffuse tissue damage, network connectivity patterns could be important for closely tracking and predicting the disease course. In this review, we describe concepts of graph theory, highlight novel issues of tissue reorganization in acute and chronic neuroinflammation and address pitfalls with regard to network analysis in MS patients. We further provide an outline of functional and structural connectivity patterns observed in MS, spanning from disconnection and disruption on one hand to adaptation and compensation on the other. Moreover, we link network changes and their relation to clinical disability based on the current literature. Finally, we discuss the perspective of network science in MS for future research and postulate its role in the clinical framework.

PMID: 29101079

R Soc Open Sci , IF:2.647 , 2019 Apr , V6 (4) : P190418 doi: 10.1098/rsos.190418

Dynamical modelling of secondary metabolism and metabolic switches in Streptomyces xiamenensis 318.

Zhu, Xiao-Mei and Zhang, Xing-Xing and Cheng, Run-Tan and Yu, He-Lin and Yuan, Ruo-Shi and Bu, Xu-Liang and Xu, Jun and Ao, Ping and Chen, Yong-Cong and Xu, Min-Juan

Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, People's Republic of China.; Shanghai Center for Quantitative Life Sciences and Physics Department, Shanghai University, Shanghai 200444, People's Republic of China.; School of Oceanography, State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China.

The production of secondary metabolites, while important for bioengineering purposes, presents a paradox in itself. Though widely existing in plants and bacteria, they have no definite physiological roles. Yet in both native habitats and laboratories, their production appears robust and follows apparent metabolic switches. We show in this work that the enzyme-catalysed process may improve the metabolic stability of the cells. The latter can be responsible for the overall metabolic behaviours such as dynamic metabolic landscape, metabolic switches and robustness, which can in turn affect the genetic formation of the organism in question. Mangrove-derived Streptomyces xiamenensis 318, with a relatively compact genome for secondary metabolism, is used as a model organism in our investigation. Integrated studies via kinetic metabolic modelling, transcriptase measurements and metabolic profiling were performed on this strain. Our results demonstrate that the secondary metabolites increase the metabolic fitness of the organism via stabilizing the underlying metabolic network. And the fluxes directing to NADH, NADPH, acetyl-CoA and glutamate provide the key switches for the overall and secondary metabolism. The information may be helpful for improving the xiamenmycin production on the strain.

PMID: 31183155

Naturwissenschaften , IF:2.09 , 2019 Apr , V106 (5-6) : P20 doi: 10.1007/s00114-019-1614-0

Ant species richness and interactions in canopies of two distinct successional stages in a tropical dry forest.

Antoniazzi, Reuber and Garro, Raphael N S L and Dattilo, Wesley and Ribeiro, Servio P and Neves, Frederico S

Red de Ecoetologia, Instituto de Ecologia A.C., Xalapa, Veracruz, Mexico. reuberjunior@gmail.com.; Programa de Pos-Graduacao Stricto Sensu em Ciencias Biologicas, Universidade Estadual de Montes Claros, Montes Claros, Minas Gerais, Brazil. reuberjunior@gmail.com.; Programa de Pos-Graduacao Stricto Sensu em Ciencias Biologicas, Universidade Estadual de Montes Claros, Montes Claros, Minas Gerais, Brazil.; Red de Ecoetologia, Instituto de Ecologia A.C., Xalapa, Veracruz, Mexico.; Laboratorio de Ecohealth e Ecologia de Insetos de Dossel e Sucessao Natural, Instituto de Ciencias Biologicas, Universidade Federal de Ouro Preto, Ouro Preto, Minas Gerais, Brazil.; Laboratorio de Ecologia de Insetos, Departamento de Genetica, Ecologia e Evolucao, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.

Canopy ecology is a fast-growing field, but still a scientific frontier in many ecological aspects. For instance, the hypothesis that tree traits shape patterns in ant-plant interactions lacks data, notably for tropical canopies in different successional stages. In this study, we investigated canopy traits, such as tree height, the presence of extrafloral nectaries (EFNs), connectivity among tree crowns, and successional stage, structure ant-tree interactions in a tropical dry forest (TDF), examining whether these are the determinant factors for ant species richness. We collected ants on trees in early and late successional stages over 2 years, in rainy and dry seasons. In the late successional stage, ant species richness was greater in the taller trees; in the early successional stage, the smallest trees had a greater ant species richness than the taller trees. The EFNs and connectivity among treetops had no effect on ant species richness. We obtained a tree-ant network of the early successional stage, involving 786 interactions among 57 ant species and 75 trees; in the late successional stage, the network had 914 interactions among 60 ant species and 75 trees. There were 27 species of trees in our study, 11 of which (40.7% of all individual trees) had EFNs. The ant-plant interactions were not randomly distributed, suggesting that various biotic factors structured the ant assemblies. This study presents new insights into ant-tree interactions, showing that both tree height and successional stage influence the occurrence of many species of ants in tree canopies of tropical dry forests.

PMID: 31041541