Trends Plant Sci , IF:14.416 , 2020 Aug doi: 10.1016/j.tplants.2020.07.008
Menage a Trois: Unraveling the Mechanisms Regulating Plant-Microbe-Arthropod Interactions.
Department of Biotechnology and Systems Biology, National Institute of Biology, Ljubljana, Slovenia. Electronic address: kristina.gruden@nib.si.; Department of Soil Microbiology and Symbiotic Systems, Estacion Experimental del Zaidin, CSIC, Granada, Spain.; Department of Biotechnology and Systems Biology, National Institute of Biology, Ljubljana, Slovenia.; Department of Knowledge Technologies, Jozef Stefan Institute, Ljubljana, Slovenia.; Metabolic Integration and Cell Signaling Laboratory, Department of Ciencias Agrarias y del Medio Natural, Universitat Jaume I; Unidad Asociada al Consejo Superior de Investigaciones Cientificas (EEZ-CSIC)-Universitat Jaume I, Castellon, Spain.; Department of Biochemistry and Biotechnology, Laboratory of Plant and Environmental Biotechnology, University of Thessaly, Biopolis, Larissa, Greece.; Department of Agricultural Development, Faculty of Agricultural Sciences and Forestry, Democritus University of Thrace, Orestiada, Greece.; Plant-Microbe Interaction, Institute of Natural Resources and Agrobiology of Salamanca, IRNASA-CSIC, Salamanca, Spain.; Instituto de Hortofruticultura Subtropical y Mediterranea 'La Mayora', Universidad de Malaga-Consejo Superior de Investigaciones Cientificas (IHSM-UMA-CSIC), Department Biologia Celular, Genetica y Fisiologia, Universidad de Malaga, Malaga, Spain.; Department of Terrestrial Ecology, Netherlands Institute of Ecology (NIOO-KNAW), Wageningen, The Netherlands.; Department of Soil Microbiology and Symbiotic Systems, Estacion Experimental del Zaidin, CSIC, Granada, Spain. Electronic address: mjpozo@eez.csic.es.
Plant-microbe-arthropod (PMA) three-way interactions have important implications for plant health. However, our poor understanding of the underlying regulatory mechanisms hampers their biotechnological applications. To this end, we searched for potential common patterns in plant responses regarding taxonomic groups or lifestyles. We found that most signaling modules regulating two-way interactions also operate in three-way interactions. Furthermore, the relative contribution of signaling modules to the final plant response cannot be directly inferred from two-way interactions. Moreover, our analyses show that three-way interactions often result in the activation of additional pathways, as well as in changes in the speed or intensity of defense activation. Thus, detailed, basic knowledge of plant-microbe-arthropod regulation will be essential for the design of environmentally friendly crop management strategies.
PMID: 32828689
Proc Natl Acad Sci U S A , IF:9.412 , 2020 Aug , V117 (32) : P19556-19565 doi: 10.1073/pnas.2003601117
Gene coexpression patterns predict opiate-induced brain-state transitions.
Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104.; Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104.; Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104.; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104.; Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA 19104.; Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, PA 19104.; Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen University, 52074 Aachen, Germany.; Department of Mechanical Engineering, University of California, Riverside, CA 92521.; Santa Fe Institute, Santa Fe, NM 87501.; Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104; blendy@pennmedicine.upenn.edu.
Opioid addiction is a chronic, relapsing disorder associated with persistent changes in brain plasticity. Reconfiguration of neuronal connectivity may explain heightened abuse liability in individuals with a history of chronic drug exposure. To characterize network-level changes in neuronal activity induced by chronic opiate exposure, we compared FOS expression in mice that are morphine-naive, morphine-dependent, or have undergone 4 wk of withdrawal from chronic morphine exposure, relative to saline-exposed controls. Pairwise interregional correlations in FOS expression data were used to construct network models that reveal a persistent reduction in connectivity strength following opiate dependence. Further, we demonstrate that basal gene expression patterns are predictive of changes in FOS correlation networks in the morphine-dependent state. Finally, we determine that regions of the hippocampus, striatum, and midbrain are most influential in driving transitions between opiate-naive and opiate-dependent brain states using a control theoretic approach. This study provides a framework for predicting the influence of specific therapeutic interventions on the state of the opiate-dependent brain.
PMID: 32694207
Brief Bioinform , IF:8.99 , 2020 Aug doi: 10.1093/bib/bbaa166
A powerful framework for an integrative study with heterogeneous omics data: from univariate statistics to multi-block analysis.
INRAE.; Laboratoire de Recherche en Sciences Vegetales and the Institut de Mathematiques de Toulouse.; CNRS, France.; CNRS and studies plant cell walls.; Toulouse University III-Paul Sabatier.; Institut de Mathematiques, Toulouse University.
High-throughput data generated by new biotechnologies require specific and adapted statistical treatment in order to be efficiently used in biological studies. In this article, we propose a powerful framework to manage and analyse multi-omics heterogeneous data to carry out an integrative analysis. We have illustrated this using the mixOmics package for R software as it specifically addresses data integration issues. Our work also aims at applying the most recent functionalities of mixOmics to real datasets. Although multi-block integrative methodologies exist, we hope to encourage a more widespread use of such approaches in an operational framework by biologists. We have used natural populations of the model plant Arabidopsis thaliana in this work, but the framework proposed is not limited to this plant and can be deployed whatever the organisms of interest and the biological question may be. Four omics datasets (phenomics, metabolomics, cell wall proteomics and transcriptomics) were collected, analysed and integrated to study the cell wall plasticity of plants exposed to sub-optimal temperature growth conditions. The methodologies presented here start from basic univariate statistics leading to multi-block integration analysis. We have also highlighted the fact that each method, either unsupervised or supervised, is associated with one biological issue. Using this powerful framework enabled us to arrive at novel conclusions on the biological system, which would not have been possible using standard statistical approaches.
PMID: 32778869
Plant J , IF:6.141 , 2020 Aug doi: 10.1111/tpj.14961
CropPAL for discovering protein subcellular location divergence in crops to support strategies for molecular crop breeding.
ARC Centre of Excellence in Plant Energy Biology, The University of Western Australia, Crawley, WA, 6009, Australia.; Precision Medicine Theme, South Australian Health and Medical Research Institute, Adelaide, South Australian, 5000, Australia.; Robinson Research Institute & Adelaide Health and Medical Sciences, University of Adelaide, Adelaide, South Australia, 5000, Australia.; University Library, The University of Western Australia, Crawley, WA, 6009, Australia.
Agriculture faces increasing demand for yield, higher plant-derived protein content and diversity while facing pressure to achieve sustainability. Although genomes of many of the important crops are sequenced, the subcellular locations of most proteins encoded remain unknown or are only predicted. Protein subcellular location is crucial in determining protein function and accumulation patterns in plants and is critical for targeted improvements of yield and resilience. Integrating location data from >800 studies for 12 major crop species into the data collection cropPAL2020 showed that while >80% of proteins in most species are not localised by experimental data, combining species data or integrating predictions can help bridge gaps at similar accuracy. The collation and integration of >61,505 experimental localisations and > 6 million predictions showed that the relative sizes of the protein catalogues located in different subcellular compartments are comparable between crops and Arabidopsis. A comprehensive cross-species comparison showed that between 50-80% of the subcellulomes are conserved across species and that conservation only depends to some degree on the species phylogenetic relationship. Protein subcellular locations in major biosynthesis pathways are more often conserved than in metabolism. Underlying this conservation is a clear potential for protein location subcellular diversity between species by means of gene duplication and alternative splicing. Our cropPAL data set and search platform (https://crop-pal.org) provide a comprehensive subcellular proteomics resource to drive compartmentation-based approaches for improving yield, protein composition and resilience in future crop varieties.
PMID: 32780488
FEMS Microbiol Ecol , IF:3.675 , 2020 Aug doi: 10.1093/femsec/fiaa165
Early ecological succession patterns of bacterial, fungal and plant communities along a chronosequence in a recently deglaciated area of Italian Alps.
Department of Earth and Environmental Sciences (DISAT) - University of Milano-Bicocca, Milano, Italy.; Department of Environmental Science and Policy, University of Milano, Milano, Italy.; Department of Earth Science "Ardito Desio", University of Milano, Milano, Italy.; Department of Agricultural, Food and Environmental Sciences, University of Perugia, Perugia, Italy.
In this study, the early ecological succession patterns of Forni Glacier (Ortles-Cevedale group, Italian Alps) forefield along 18-year long chronosequence (with a temporal resolution of one year) has been reported. Bacterial and fungal community structures were inferred by high throughput sequencing of 16S rRNA gene and ITS, respectively. Besides, the occurrence of both herbaceous and arboreous plants was also recorded at each plot. A significant decrease of alpha-diversity in more recently deglaciated areas was observed for both bacteria and plants. Time since deglaciation and pH affected the structure of both fungal and bacterial communities. Pioneer plants could be a major source of colonization for both bacterial and fungal communities. Consistently, some of the most abundant bacterial taxa and some of those significantly varying with pH along the chronosequence (Polaromonas, Granulicella, Thiobacillus, Acidiferrobacter) are known to be actively involved in rock-weathering processes due to their chemolithotrofic metabolism, thus suggesting that the early phase of the chronosequence could be mainly shaped by the biologically controlled bioavailability of metals and inorganic compounds. Fungal communities were dominated by ascomycetous filamentous fungi and basidiomycetous yeasts. Their role as cold-adapted organic matter decomposers, due to their heterotrophic metabolism, was suggested.
PMID: 32815995
Waste Manag Res , IF:2.771 , 2020 Aug : P734242X20945375 doi: 10.1177/0734242X20945375
Quantification of geographical proximity of sugarcane bagasse ash sources to ready-mix concrete plants for sustainable waste management and recycling.
Department of Civil Engineering, Birla Institute of Technology and Science Pilani, Hyderabad, India.
As stated in the European Commission's waste framework directive, the geographic proximity of wastes to the potential recovery/disposal site is of paramount importance in attaining an effective resource recycling paradigm. The global interest in achieving an end-of-waste scenario encourages the recovery of useful products/secondary raw materials from locally available waste materials. Sugarcane bagasse ash is an abundantly available waste (44,200 tonnes day(-1)) from sugar plants in India which has the potential to be used as a partial replacement to cement in ready-mix concrete plants. Although pozzolanic performance of sugarcane bagasse ash and its ability in reducing the carbon emissions associated with concrete production have been reported in earlier research studies, its use in concrete is hindered due to the lack of availability and accessibility data. In this study, the geographical distribution of sugar plants and the available quantity of sugarcane bagasse ash in India have been determined. In addition, a detailed network analysis using a geographic information system was conducted to quantify the geographic proximity of bagasse ash, fly ash and slag sources to ready-mix concrete plants. The study results indicate that for most of the ready-mix concrete plants in India, the probability of having a bagasse ash source in proximity is higher than the probability of encountering slag/fly ash sources.
PMID: 32787672