The Uncultured Microbial Majority

Rappé, Michael S.; Giovannoni, Stephen J.

doi:10.1146/annurev.micro.57.030502.090759

Cited by 1,700 publications

(1,201 citation statements)

References 122 publications

(131 reference statements)

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“…Most of these studies depended on spore morphology and/or culture dependent methods for identification. As a majority of fungi are not readily cultured (Pace, 1997;Rappé and Giovannoni, 2003;Fröhlich-Nowoisky et al, 2009) or easily identified by spores alone (Burge, 1985), these results are expected to be an underestimation of airborne fungal diversity (Wu et al, 2004). Metagenomics, a new field in biology, uses new DNA sequencing technologies (e.g., pyrosequencing) to directly sequence and identify environmental microbes (Riesenfeld et al, 2004).…”

Section: Introductionmentioning

confidence: 99%

Identifying airborne fungi in Seoul, Korea using metagenomics

Fong

Park

et al. 2014

J Microbiol.

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Fungal spores are widespread and common in the atmosphere. In this study, we use a metagenomic approach to study the fungal diversity in six total air samples collected from April to May 2012 in Seoul, Korea. This springtime period is important in Korea because of the peak in fungal spore concentration and Asian dust storms, although the year of this study (2012) was unique in that were no major Asian dust events. Clustering sequences for operational taxonomic unit (OTU) identification recovered 1,266 unique OTUs in the combined dataset, with between 223-396 OTUs present in individual samples. OTUs from three fungal phyla were identified. For Ascomycota, Davidiella (anamorph: Cladosporium) was the most common genus in all samples, often accounting for more than 50% of all sequences in a sample. Other common Ascomycota genera identified were Alternaria, Didymella, Khuskia, Geosmitha, Penicillium, and Aspergillus. While several Basidiomycota genera were observed, Chytridiomycota OTUs were only present in one sample. Consistency was observed within sampling days, but there was a large shift in species composition from Ascomycota dominant to Basidiomycota dominant in the middle of the sampling period. This marked change may have been caused by meteorological events. A potential set of 40 allergyinducing genera were identified, accounting for a large proportion of the diversity present (22.5-77.2%). Our study identifies high fungal diversity and potentially high levels of fungal allergens in springtime air of Korea, and provides a good baseline for future comparisons with Asian dust storms.

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Section: Introductionmentioning

confidence: 99%

Identifying airborne fungi in Seoul, Korea using metagenomics

Fong

Park

et al. 2014

J Microbiol.

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“…Although culture-dependent strategies for the discovery of natural products have been very rewarding, this approach has likely missed the vast majority of naturally occurring bacterial metabolites. Only a tiny minority of the microbes present in nature is actually cultured using standard microbiological methods 2 . Even though most bacteria are not readily cultured in the laboratory, it is possible to extract microbial DNA directly from the naturally occurring consortia of bacteria present in environmental samples (environmental DNA (eDNA)).…”

Section: Introductionmentioning

confidence: 99%

Construction of soil environmental DNA cosmid libraries and screening for clones that produce biologically active small molecules

2007

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“…Sensitivity and precision increase from 92% and 93% on data with identical abundance levels to 97% and 99% on data with varying abundance levels. In order to explain this (somewhat counter-intuitive) phenomenon, we analyzed intermediate results, and found that two of the six pairs of genomes, (1,3) and (2,4), have high percentages of common repeats. These common repeats negatively affected the result on data with identical abundance levels.…”

Section: The Issue Of Abundance Levelsmentioning

confidence: 99%

Separating Metagenomic Short Reads into Genomes via Clustering

Tanaseichuk

Borneman

Jiang

2011

Lecture Notes in Computer Science

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Background:The metagenomics approach allows the simultaneous sequencing of all genomes in an environmental sample. This results in high complexity datasets, where in addition to repeats and sequencing errors, the number of genomes and their abundance ratios are unknown. Recently developed next-generation sequencing (NGS) technologies significantly improve the sequencing efficiency and cost. On the other hand, they result in shorter reads, which makes the separation of reads from different species harder. Among the existing computational tools for metagenomic analysis, there are similarity-based methods that use reference databases to align reads and composition-based methods that use composition patterns (i.e., frequencies of short words or l-mers) to cluster reads. Similarity-based methods are unable to classify reads from unknown species without close references (which constitute the majority of reads). Since composition patterns are preserved only in significantly large fragments, composition-based tools cannot be used for very short reads, which becomes a significant limitation with the development of NGS. A recently proposed algorithm, AbundanceBin, introduced another method that bins reads based on predicted abundances of the genomes sequenced. However, it does not separate reads from genomes of similar abundance levels. Results: In this work, we present a two-phase heuristic algorithm for separating short paired-end reads from different genomes in a metagenomic dataset. We use the observation that most of the l-mers belong to unique genomes when l is sufficiently large. The first phase of the algorithm results in clusters of l-mers each of which belongs to one genome. During the second phase, clusters are merged based on l-mer repeat information. These final clusters are used to assign reads. The algorithm could handle very short reads and sequencing errors. It is initially designed for genomes with similar abundance levels and then extended to handle arbitrary abundance ratios. The software can be download for free at http://www.cs.ucr.edu/ ∼ tanaseio/toss.htm. Conclusions: Our tests on a large number of simulated metagenomic datasets concerning species at various phylogenetic distances demonstrate that genomes can be separated if the number of common repeats is smaller than the number of genome-specific repeats. For such genomes, our method can separate NGS reads with a high precision and sensitivity.

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The Uncultured Microbial Majority

Cited by 1,700 publications

References 122 publications

Identifying airborne fungi in Seoul, Korea using metagenomics

Identifying airborne fungi in Seoul, Korea using metagenomics

Construction of soil environmental DNA cosmid libraries and screening for clones that produce biologically active small molecules

Separating Metagenomic Short Reads into Genomes via Clustering

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