CiteULike: vrich's 454

Bacterial carbon processing by generalist species in the coastal ocean

Xiaozhen Mou — 2008-01-31T11:58:30-00:00

Nature (27 January 2008)

Bacterial flora typing with deep, targeted, chip-based Pyrosequencing

Andreas Sundquist — 2007-12-01T02:47:29-00:00

BMC Microbiology, Vol. 7 (30 November 2007), 108.

Pyrosequencing enumerates and contrasts soil microbial diversity

Luiz Roesch — 2008-05-11T22:34:31-00:00

ISME J, Vol. 1, No. 4. (5 July 2007), pp. 283-290.

Short pyrosequencing reads suffice for accurate microbial community analysis

Zongzhi Liu — 2007-11-08T10:23:10-00:00

Nucl. Acids Res., Vol. 35, No. 18. (25 September 2007), e120.

Pyrosequencing technology allows us to characterize microbial communities using 16S ribosomal RNA (rRNA) sequences orders of magnitude faster and more cheaply than has previously been possible. However, results from different studies using pyrosequencing and traditional sequencing are often difficult to compare, because amplicons covering different regions of the rRNA might yield different conclusions. We used sequences from over 200 globally dispersed environments to test whether studies that used similar primers clustered together mistakenly, without regard to environment. We then tested whether primer choice affects sequence-based community analyses using UniFrac, our recently-developed method for comparing microbial communities. We performed three tests of primer effects. We tested whether different simulated amplicons generated the same UniFrac clustering results as near-full-length sequences for three recent large-scale studies of microbial communities in the mouse and human gut, and the Guerrero Negro microbial mat. We then repeated this analysis for short sequences (100-, 150-, 200- and 250-base reads) resembling those produced by pyrosequencing. The results show that sequencing effort is best focused on gathering more short sequences rather than fewer longer ones, provided that the primers are chosen wisely, and that community comparison methods such as UniFrac are surprisingly robust to variation in the region sequenced. 10.1093/nar/gkm541

Metagenomic and small-subunit rRNA analyses of the genetic diversity of bacteria, archaea, fungi, and viruses in soil

Noah Fierer — 2007-09-23T17:38:12-00:00

Appl. Environ. Microbiol. (7 September 2007), AEM.00358-07.

Recent studies have highlighted the surprising richness of soil bacterial communities, however bacteria are not the only microorganisms found in soil. To our knowledge no study has compared the diversity of the four major microbial taxa: bacteria, archaea, fungi, and viruses, from an individual soil sample. We used metagenomic and small-subunit RNA-based sequence analysis techniques to compare the estimated richness and evenness of these groups in prairie, desert, and rainforest soils. By grouping sequences at the 97% sequence similarity level (an operational taxonomic unit, or OTU), we found that the archaeal and fungal communities were consistently less even than the bacterial communities. Although total richness levels are difficult to estimate with a high degree of certainty, the estimated number of unique archaeal or fungal OTUs appears to rival or exceed the number of unique bacterial OTUs in each of the collected soils. As the first study to comprehensively survey viral communities using a metagenomic approach, we found that soil viruses are taxonomically diverse and distinct from the communities of viruses found in other environments that have been surveyed using a similar approach. Within each of the four microbial groups, we observed minimal taxonomic overlap between sites, suggesting that soil archaea, bacteria, fungi, and viruses are globally as well as locally diverse. 10.1128/AEM.00358-07

Phylogenetic classification of short environmental DNA fragments

Lutz Krause — 2008-05-08T23:04:11-00:00

Nucl. Acids Res., Vol. 36, No. 7. (1 April 2008), pp. 2230-2239.

Metagenomics is providing striking insights into the ecology of microbial communities. The recently developed massively parallel 454 pyrosequencing technique gives the opportunity to rapidly obtain metagenomic sequences at a low cost and without cloning bias. However, the phylogenetic analysis of the short reads produced represents a significant computational challenge. The phylogenetic algorithm CARMA for predicting the source organisms of environmental 454 reads is described. The algorithm searches for conserved Pfam domain and protein families in the unassembled reads of a sample. These gene fragments (environmental gene tags, EGTs), are classified into a higher-order taxonomy based on the reconstruction of a phylogenetic tree of each matching Pfam family. The method exhibits high accuracy for a wide range of taxonomic groups, and EGTs as short as 27 amino acids can be phylogenetically classified up to the rank of genus. The algorithm was applied in a comparative study of three aquatic microbial samples obtained by 454 pyrosequencing. Profound differences in the taxonomic composition of these samples could be clearly revealed. 10.1093/nar/gkn038