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      Spatial and Temporal Shifts of Endophytic Bacteria in Conifer Seedlings of Abies religiosa (Kunth) Schltdl. & Cham.

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          Abstract

          Endophytes play an important role in plant development, survival, and establishment, but their temporal dynamics in young conifer plants are still largely unknown. In this study, the bacterial community was determined by metabarcoding of the 16S rRNA gene in the rhizoplane, roots, and aerial parts of 1- and 5-month-old seedlings of natural populations of Abies religiosa (Kunth) Schltdl. & Cham. In 1-month-old seedlings, Pseudomonas dominated aerial parts (relative abundance 71.6%) and roots (37.9%). However, the roots exhibited significantly higher bacterial species richness than the aerial parts, with the dissimilarity between these plant sections mostly explained by the loss of bacterial amplification sequence variants. After 5 months, Mucilaginibacter dominated in the rhizoplane (9.0%), Streptomyces in the roots (12.2%), and Pseudomonas in the aerial parts (18.1%). The bacterial richness and community structure differed significantly between the plant sections, and these variations were explained mostly by 1-for-1 substitution. The relative abundance of putative metabolic pathways significantly differed between the plant sections at both 1 and 5 months. All the dominant bacterial genera (e.g., Pseudomonas and Burkholderia-Caballeronia-Paraburkholderia) have been reported to have plant growth-promoting capacities and/or antagonism against pathogens, but what defines their role for plant development has still to be determined. This investigation improves our understanding of the early plant-bacteria interactions essential for natural regeneration of A. religiosa forest.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s00248-024-02398-9.

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          DADA2: High resolution sample inference from Illumina amplicon data

          We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
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            The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

            SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
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              Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

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                Author and article information

                Contributors
                dendoove@cinvestav.mx
                yendiebenezer.navarro.n@uatx.mx
                Journal
                Microb Ecol
                Microb Ecol
                Microbial Ecology
                Springer US (New York )
                0095-3628
                1432-184X
                3 July 2024
                3 July 2024
                2024
                : 87
                : 1
                : 90
                Affiliations
                [1 ]GRID grid.512574.0, Laboratory of Soil Ecology, , Cinvestav, ; Mexico City, Mexico
                [2 ]Laboratorio de Interacciones Bióticas, Centro de Investigación en Ciencias Biológicas, Universidad Autónoma de Tlaxcala, ( https://ror.org/021vseb03) San Felipe Ixtacuixtla, Mexico
                Author information
                http://orcid.org/0000-0002-4148-2283
                http://orcid.org/0000-0002-7191-7815
                Article
                2398
                10.1007/s00248-024-02398-9
                11222277
                38958675
                1d4a89ce-5b5a-4f8a-8dce-015c01e516c0
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 19 March 2024
                : 9 June 2024
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100008688, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional;
                Funded by: Consejo Nacional de Humanidades Ciencia y Tecnología (CONAHCyT)
                Award ID: 591213
                Award ID: INFR-2015-01-253217
                Award Recipient :
                Categories
                Research
                Custom metadata
                © Springer Science+Business Media, LLC, part of Springer Nature 2024

                Microbiology & Virology
                high mountain ecosystems,tree microbiome,forest conservation,plant-microbe interaction,plant microbiome

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