The microbial community of a Colombian high mountain hot spring, El Coquito, was analyzed using three different culture-independent assessments of 16S ribosomal RNA genes: clone libraries, pyrosequencing of the V5-V6 hypervariable region, and microarray. This acidic spring had a diverse community composed mainly of Bacteria that shared characteristics with those from other hot springs and extreme acidic environments. The microbial community was dominated by Proteobacteria, Firmicutes, and Planctomycetes and contained chemotrophic bacteria potentially involved in cycling of ferrous and sulfur-containing minerals and phototrophic organisms, most of which were eukaryotic micro-algae. Despite the presence of a large proportion of novel, unclassified sequences, the taxonomic profiles obtained with each strategy showed similarities at higher taxonomic levels. However, some groups, such as Spirochaetes and Aquificae, were identified using only one methodology, and more taxa were detected with the gene array, which also shared more groups with the pyrosequencing data. Overall, the combined use of different approaches provided a broader view of the microbial community in this acidic hot spring.
BackgroundChanges in respiratory tract microbiota have been associated with diseases such as tuberculosis, a global public health problem that affects millions of people each year. This pilot study was carried out using sputum, oropharynx, and nasal respiratory tract samples collected from patients with pulmonary tuberculosis and healthy control individuals, in order to compare sample types and their usefulness in assessing changes in bacterial and fungal communities.FindingsMost V1-V2 16S rRNA gene sequences belonged to the phyla Firmicutes, Bacteroidetes, Proteobacteria, Actinobacteria, and Fusobacteria, with differences in relative abundances and in specific taxa associated with each sample type. Most fungal ITS1 sequences were classified as Ascomycota and Basidiomycota, but abundances differed for the different samples. Bacterial and fungal community structures in oropharynx and sputum samples were similar to one another, as indicated by several beta diversity analyses, and both differed from nasal samples. The only difference between patient and control microbiota was found in oropharynx samples for both bacteria and fungi. Bacterial diversity was greater in sputum samples, while fungal diversity was greater in nasal samples.ConclusionsRespiratory tract microbial communities were similar in terms of the major phyla identified, yet they varied in terms of relative abundances and diversity indexes. Oropharynx communities varied with respect to health status and resembled those in sputum samples, which are collected from tuberculosis patients only due to the difficulty in obtaining sputum from healthy individuals, suggesting that oropharynx samples can be used to analyze community structure alterations associated with tuberculosis.
BackgroundThe taxonomic and phylogenetic classification based on sequence analysis of the ITS1 genomic region has become a crucial component of fungal ecology and diversity studies. Nowadays, there is no accurate alignment-free classification tool for fungal ITS1 sequences for large environmental surveys. This study describes the development of a machine learning-based classifier for the taxonomical assignment of fungal ITS1 sequences at the genus level.ResultsA fungal ITS1 sequence database was built using curated data. Training and test sets were generated from it. A Naïve Bayesian classifier was built using features from the primary sequence with an accuracy of 87 % in the classification at the genus level.ConclusionsThe final model was based on a Naïve Bayes algorithm using ITS1 sequences from 510 fungal genera. This classifier, denoted as Mycofier, provides similar classification accuracy compared to BLASTN, but the database used for the classification contains curated data and the tool, independent of alignment, is more efficient and contributes to the field, given the lack of an accurate classification tool for large data from fungal ITS1 sequences. The software and source code for Mycofier are freely available at https://github.com/ldelgado-serrano/mycofier.git.Electronic supplementary materialThe online version of this article (doi:10.1186/s13104-016-2203-3) contains supplementary material, which is available to authorized users.
Microbial explorations of hot springs have led to remarkable discoveries and improved our understanding of life under extreme conditions. The Andean Mountains harbor diverse habitats, including an extensive chain of geothermal heated water sources. In this study, we describe and compare the planktonic microbial communities present in five high-mountain hot springs with distinct geochemical characteristics, at varying altitudes and geographical locations in the Colombian Andes. The diversity and structure of the microbial communities were assessed by pyrosequencing the V5 - V6 region of the 16S rRNA gene. The planktonic communities varied in terms of diversity indexes and were dominated by the bacterial phyla Proteobacteria, Aquificae, Chloroflexi, Cyanobacteria, Firmicutes, Nitrospirae, and Thermotogae, with site-specific bacterial taxa also observed in some cases. Statistical analyses showed that these microbial communities were distinct from one another and that they clustered in a manner consistent with physicochemical parameters of the environment sampled. Multivariate analysis suggested that pH and sulfate were among the main variables influencing population structure and diversity. The results show that despite their geographical proximity and some shared geochemical characteristics, there were few shared operational taxonomic units (OTUs) and that community structure was influenced mainly by environmental factors that have resulted in different microbial populations.
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