4 research outputs found

    Anthropogenic areas as incidental substitutes for original habitat

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    One speaks of ecological substitutes when an introduced species performs, to some extent, the ecosystem function of an extirpated native species. We suggest that a similar case exists for habitats. Species evolve within ecosystems, but habitats can be destroyed or modified by natural and human-made causes. Sometimes habitat alteration forces animals to move to or remain in a suboptimal habitat type. In that case, the habitat is considered a refuge, and the species is called a refugee. Typically refugee species have lower population growth rates than in their original habitats. Human action may lead to the unintended generation of artificial or semiartificial habitat types that functionally resemble the essential features of the original habitat and thus allow a population growth rate of the same magnitude or higher than in the original habitat. We call such areas substitution habitats and define them as human-made habitats within the focal species range that by chance are partial substitutes for the species' original habitat. We call species occupying a substitution habitat adopted species. These are 2 new terms in conservation biology. Examples of substitution habitats are dams for European otters, wheat and rice fields for many steppeland and aquatic birds, and urban areas for storks, falcons, and swifts. Although substitution habitats can bring about increased resilience against the agents of global change, the conservation of original habitat types remains a conservation priority.AMA was supported by a postdoctoral contract (Isidro Parga Pondal program) by Xunta de Galicia. We are also grateful to “Programa de Investigación Competitiva del Sistema Universitario Gallego” reference GRC2014/050 from Xunta de Galicia for financing our project “Grupo de Investigación en Biología Evolutiva (GIBE) de la Universidade da CoruñaPeer Reviewe

    In-depth resistome analysis by targeted metagenomics

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    [Background]: Antimicrobial resistance is a major global health challenge. Metagenomics allows analyzing the presence and dynamics of “resistomes” (the ensemble of genes encoding antimicrobial resistance in a given microbiome) in disparate microbial ecosystems. However, the low sensitivity and specificity of available metagenomic methods preclude the detection of minority populations (often present below their detection threshold) and/or the identification of allelic variants that differ in the resulting phenotype. Here, we describe a novel strategy that combines targeted metagenomics using last generation in-solution capture platforms, with novel bioinformatics tools to establish a standardized framework that allows both quantitative and qualitative analyses of resistomes. [Methods]: We developed ResCap, a targeted sequence capture platform based on SeqCapEZ (NimbleGene) technology, which includes probes for 8667 canonical resistance genes (7963 antibiotic resistance genes and 704 genes conferring resistance to metals or biocides), and 2517 relaxase genes (plasmid markers) and 78,600 genes homologous to the previous identified targets (47,806 for antibiotics and 30,794 for biocides or metals). Its performance was compared with metagenomic shotgun sequencing (MSS) for 17 fecal samples (9 humans, 8 swine). ResCap significantly improves MSS to detect “gene abundance” (from 2.0 to 83.2%) and “gene diversity” (26 versus 14.9 genes unequivocally detected per sample per million of reads; the number of reads unequivocally mapped increasing up to 300-fold by using ResCap), which were calculated using novel bioinformatic tools. ResCap also facilitated the analysis of novel genes potentially involved in the resistance to antibiotics, metals, biocides, or any combination thereof. [Conclusions]: ResCap, the first targeted sequence capture, specifically developed to analyze resistomes, greatly enhances the sensitivity and specificity of available metagenomic methods and offers the possibility to analyze genes related to the selection and transfer of antimicrobial resistance (biocides, heavy metals, plasmids). The model opens the possibility to study other complex microbial systems in which minority populations play a relevant role.This study was supported by the European Commission, Seven Framework Program (EVOTARFP7-HEALTH-282004 for VFL, FB, JLM, AA, DE, ER, RJLW, WvS, FdlC, and TMC), the Joint Programming Initiative in Antimicrobial Resistance (JPIAMR Third call, STARCS, JPIAMR2016-AC16/00039 to TMC, RJLW, WvS), the Joint Programming Initiative in Water (JPI Water StARE JPIW2013-089-C02-01 to JLM) and the Ministry of Economy and Competitiveness of Spain (BIO2014-54507-R to JLM, and PLASWIRES-612146/FP7-ICT-2013-10 and BFU2014-55534-C2-1-P for FdlC). The authors also acknowledge the European Development Regional Fund “A way to achieve Europe” (ERDF) for co-founding the Spanish R&D National Plan 2012-2019 (BIO2014-54507-R to JLM, PI15-0512 to TMC, PI15-00818 to FB, and BFU2014-55534-C2-1-P to FdlC), CIBER (CIBER in Epidemiology and Public Health, CIBERESP; CB06/02/0053 to FB), the Spanish Network for Research on Infectious Diseases (REIPI RD12/0015 to JLM) and the Regional Government of Madrid (InGeMICS- B2017/BMD-3691). Val F. Lanza was further funded by a Research Award Grant 2016 of the European Society for Clinical Microbiology and Infectious Diseases (ESCMID). Additional funding was from the Metagenopolis grant ANR-11-DPBS-0001 to DE.Peer reviewe
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