Examinando por Autor "Crandall, K."

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  • Miniatura
    Ítem
    Evaluation of computational methods for human microbiome analysis using simulated data
    (PeerJ Inc., 2020) Miossec, M.; Valenzuela, S.; Perez-Losada, M.; Evan Johnson, W.; Crandall, K.; Castro-Nallar, E.
    Background: Our understanding of the composition, function, and health implications of human microbiota has been advanced by high-throughput sequencing and the development of new genomic analyses. However, trade-offs among alternative strategies for the acquisition and analysis of sequence data remain understudied. Methods: We assessed eight popular taxonomic profiling pipelines; MetaPhlAn2, metaMix, PathoScope 2.0, Sigma, Kraken, ConStrains, Centrifuge and Taxator-tk, against a battery of metagenomic datasets simulated from real data. The metagenomic datasets were modeled on 426 complete or permanent draft genomes stored in the Human Oral Microbiome Database and were designed to simulate various experimental conditions, both in the design of a putative experiment; read length (75-1,000 bp reads), sequence depth (100K-10M), and in metagenomic composition; number of species present (10, 100, 426), species distribution. The sensitivity and specificity of each of the pipelines under various scenarios were measured. We also estimated the relative root mean square error and average relative error to assess the abundance estimates produced by different methods. Additional datasets were generated for five of the pipelines to simulate the presence within a metagenome of an unreferenced species, closely related to other referenced species. Additional datasets were also generated in order to measure computational time on datasets of ever-increasing sequencing depth (up to 6 × 107). Results: Testing of eight pipelines against 144 simulated metagenomic datasets initially produced 1,104 discrete results. Pipelines using a marker gene strategy; MetaPhlAn2 and ConStrains, were overall less sensitive, than other pipelines; with the notable exception of Taxator-tk. This difference in sensitivity was largely made up in terms of runtime, significantly lower than more sensitive pipelines that rely on whole-genome alignments such as PathoScope2.0. However, pipelines that used strategies to speed-up alignment between genomic references and metagenomic reads, such as kmerization, were able to combine both high sensitivity and low run time, as is the case with Kraken and Centrifuge. Absent species genomes in the database mostly led to assignment of reads to the most closely related species available in all pipelines. Our results therefore suggest that taxonomic profilers that use kmerization have largely superseded those that use gene markers, coupling low run times with high sensitivity and specificity. Taxonomic profilers using more time-consuming read reassignment, such as PathoScope 2.0, provided the most sensitive profiles under common metagenomic sequencing scenarios.
  • Miniatura
    Ítem
    Grapevine treatment with bagasse vermicompost changes the microbiome of Albariño must and wine and improves wine quality
    (International Viticulture and Enology Society, 2022-08) Rosado, D.; Ramos-Tapia, I.; Crandall, K.; Pérez-Losada, M.; Domínguez, J.
    Winemaking is a well-known process comprising several steps to produce must and wine. Grape marc is a byproduct of wine production that can be vermicomposted and used as organic fertiliser. Grape marc vermicompost has a richer and more stable microbiome than grape marc alone and when added to the soil of vineyards it can improve grape production and wine quality. We compared Albariño must and wine microbiotas from grapevines treated with vermicompost derived from Albariño grape marc and controls (standard fertilisation). We hypothesised that observed microbial changes are connected to improved organoleptic properties observed in fertilised must and wine. Treated Albariño vines showed increased grape production and the final wine showed improved organoleptic properties. Metataxonomic analyses of the 16S rRNA and ITS gene regions showed that the Albariño must and wine microbiome varied in their taxonomic composition. Must bacteriotas showed no significant (p < 0.05) variation in alpha or beta-diversity, while wine bacteriotas and must and wine mycobiotas showed significant differences in richness and evenness, as well as in microbial structure (beta-diversity) between treated and control grapevines. Must and wine bacteriotas also showed significant (p < 0.05) changes in their predicted metabolic pathways. Our study suggests that changes in the abundance of specific bacterial and fungal taxa and the metabolic processes they carry out during Albariño winemaking can improve the productivity of the grapevine and the organoleptic properties of the wine.