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      The rhizosphere microbiome of 51 potato cultivars with diverse plant growth characteristics

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          Abstract

          Rhizosphere microbial communities play a substantial role in plant productivity. We studied the rhizosphere bacteria and fungi of 51 distinct potato cultivars grown under similar greenhouse conditions using a metabarcoding approach. As expected, individual cultivars were the most important determining factor of the rhizosphere microbial composition; however, differences were also obtained when grouping cultivars according to their growth characteristics. We showed that plant growth characteristics were related to deterministic and stochastic assembly processes of bacterial and fungal communities, respectively. The bacterial genera Arthrobacter and Massilia (known to produce indole acetic acid and siderophores) exhibited greater relative abundance in high- and medium-performing cultivars. Bacterial co-occurrence networks were larger in the rhizosphere of these cultivars and were characterized by a distinctive combination of plant beneficial Proteobacteria and Actinobacteria along with a module of diazotrophs namely Azospira, Azoarcus, and Azohydromonas. Conversely, the network within low-performing cultivars revealed the lowest nodes, hub taxa, edges density, robustness, and the highest average path length resulting in reduced microbial associations, which may potentially limit their effectiveness in promoting plant growth. Our findings established a clear pattern between plant productivity and the rhizosphere microbiome composition and structure for the investigated potato cultivars, offering insights for future management practices.

          Abstract

          The study on 51 potato cultivars revealed a clear pattern between plant productivity and rhizosphere microbial composition, highlighting distinct features in high-performing cultivars conducive to enhanced plant growth.

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          Modularity and community structure in networks

          M. Newman (2006)
          Many networks of interest in the sciences, including social networks, computer networks, and metabolic and regulatory networks, are found to divide naturally into communities or modules. The problem of detecting and characterizing this community structure is one of the outstanding issues in the study of networked systems. One highly effective approach is the optimization of the quality function known as "modularity" over the possible divisions of a network. Here I show that the modularity can be expressed in terms of the eigenvectors of a characteristic matrix for the network, which I call the modularity matrix, and that this expression leads to a spectral algorithm for community detection that returns results of demonstrably higher quality than competing methods in shorter running times. I illustrate the method with applications to several published network data sets.
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            Every base matters: assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples.

            Microbial community analysis via high-throughput sequencing of amplified 16S rRNA genes is an essential microbiology tool. We found the popular primer pair 515F (515F-C) and 806R greatly underestimated (e.g. SAR11) or overestimated (e.g. Gammaproteobacteria) common marine taxa. We evaluated marine samples and mock communities (containing 11 or 27 marine 16S clones), showing alternative primers 515F-Y (5'-GTGYCAGCMGCCGCGGTAA) and 926R (5'-CCGYCAATTYMTTTRAGTTT) yield more accurate estimates of mock community abundances, produce longer amplicons that can differentiate taxa unresolvable with 515F-C/806R, and amplify eukaryotic 18S rRNA. Mock communities amplified with 515F-Y/926R yielded closer observed community composition versus expected (r(2)  = 0.95) compared with 515F-Y/806R (r(2)  ∼ 0.5). Unexpectedly, biases with 515F-Y/806R against SAR11 in field samples (∼4-10-fold) were stronger than in mock communities (∼2-fold). Correcting a mismatch to Thaumarchaea in the 515F-C increased their apparent abundance in field samples, but not as much as using 926R rather than 806R. With plankton samples rich in eukaryotic DNA (> 1 μm size fraction), 18S sequences averaged ∼17% of all sequences. A single mismatch can strongly bias amplification, but even perfectly matched primers can exhibit preferential amplification. We show that beyond in silico predictions, testing with mock communities and field samples is important in primer selection.
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              The rhizosphere microbiome and plant health.

              The diversity of microbes associated with plant roots is enormous, in the order of tens of thousands of species. This complex plant-associated microbial community, also referred to as the second genome of the plant, is crucial for plant health. Recent advances in plant-microbe interactions research revealed that plants are able to shape their rhizosphere microbiome, as evidenced by the fact that different plant species host specific microbial communities when grown on the same soil. In this review, we discuss evidence that upon pathogen or insect attack, plants are able to recruit protective microorganisms, and enhance microbial activity to suppress pathogens in the rhizosphere. A comprehensive understanding of the mechanisms that govern selection and activity of microbial communities by plant roots will provide new opportunities to increase crop production. Copyright © 2012 Elsevier Ltd. All rights reserved.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: Writing - original draftRole: Writing - review & editing
                Role: ConceptualizationRole: MethodologyRole: Project administrationRole: SupervisionRole: Writing - review & editing
                Role: ConceptualizationRole: MethodologyRole: ResourcesRole: Writing - review & editing
                Role: MethodologyRole: ResourcesRole: Writing - review & editing
                Role: MethodologyRole: VisualizationRole: Writing - review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: SupervisionRole: Writing - review & editing
                Journal
                FEMS Microbiol Ecol
                FEMS Microbiol Ecol
                femsec
                FEMS Microbiology Ecology
                Oxford University Press
                0168-6496
                1574-6941
                August 2024
                05 June 2024
                05 June 2024
                : 100
                : 8
                : fiae088
                Affiliations
                Research Unit for Comparative Microbiome Analysis (COMI), Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH) , Ingolstädter Landstraße 1, 85764 Neuherberg, Germany
                Research Unit for Comparative Microbiome Analysis (COMI), Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH) , Ingolstädter Landstraße 1, 85764 Neuherberg, Germany
                Plant Breeding and Acclimatization Institute – National Research Institute in Radzików, Bonin Division, Department of Potato Protection and Seed Science at Bonin , Bonin Str 3, 76-009 Bonin, Poland
                Plant Breeding and Acclimatization Institute – National Research Institute in Radzików, Bonin Division, Department of Potato Protection and Seed Science at Bonin , Bonin Str 3, 76-009 Bonin, Poland
                Research Unit for Environmental Simulation (EUS), Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH) , Ingolstädter Landstraße 1, 85764 Neuherberg, Germany
                Research Unit for Comparative Microbiome Analysis (COMI), Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH) , Ingolstädter Landstraße 1, 85764 Neuherberg, Germany
                Chair for Environmental Microbiology, Department of Life Science Systems, School of Life Sciences, Technical University of Munich , Alte Akademie 8, 85354 Freising, Germany
                Author notes
                Corresponding author. Research Unit for Comparative Microbiome Analysis (COMI), Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, 85764 Neuherberg, Germany. E-mail: michael.schloter@ 123456helmholtz-munich.de
                Author information
                https://orcid.org/0000-0002-3952-4042
                Article
                fiae088
                10.1093/femsec/fiae088
                11242454
                38839598
                3df5acb1-804f-4248-a218-23a31d7a005b
                © The Author(s) 2024. Published by Oxford University Press on behalf of FEMS.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 08 January 2024
                : 22 April 2024
                : 04 June 2024
                : 12 July 2024
                Page count
                Pages: 16
                Funding
                Funded by: German Research Foundation, DOI 10.13039/501100001659;
                Award ID: 771134
                Categories
                Research Article
                AcademicSubjects/SCI01150

                Microbiology & Virology
                co-occurrence network,community assembly processes,microbiome,plant growth,potato cultivars,rhizosphere

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