EMIRGE: reconstruction of full-length ribosomal genes from microbial community short read sequencing data

Recovery of ribosomal small subunit genes by assembly of short read community DNA sequence data generally fails, making taxonomic characterization difficult. Here, we solve this problem with a novel iterative method, based on the expectation maximization algorithm, that reconstructs full-length small subunit gene sequences and provides estimates of relative taxon abundances. We apply the method to natural and simulated microbial communities, and correctly recover community structure from known and previously unreported rRNA gene sequences. An implementation of the method is freely available at https://github.com/csmiller/EMIRGE

Immunological Change in a Parasite-Impoverished Environment: Divergent Signals from Four Island Taxa

Dramatic declines of native Hawaiian avifauna due to the human-mediated emergence of avian malaria and pox prompted an examination of whether island taxa share a common altered immunological signature, potentially driven by reduced genetic diversity and reduced exposure to parasites. We tested this hypothesis by characterizing parasite prevalence, genetic diversity and three measures of immune response in two recently-introduced species (Neochmia temporalis and Zosterops lateralis) and two island endemics (Acrocephalus aequinoctialis and A. rimitarae) and then comparing the results to those observed in closely-related mainland counterparts. The prevalence of blood parasites was significantly lower in 3 of 4 island taxa, due in part to the absence of certain parasite lineages represented in mainland populations. Indices of genetic diversity were unchanged in the island population of N. temporalis; however, allelic richness was significantly lower in the island population of Z. lateralis while both allelic richness and heterozygosity were significantly reduced in the two island-endemic species examined. Although parasite prevalence and genetic diversity generally conformed to expectations for an island system, we did not find evidence for a pattern of uniformly altered immune responses in island taxa, even amongst endemic taxa with the longest residence times. The island population of Z. lateralis exhibited a significantly reduced inflammatory cell-mediated response while levels of natural antibodies remained unchanged for this and the other recently introduced island taxon. In contrast, the island endemic A. rimitarae exhibited a significantly increased inflammatory response as well as higher levels of natural antibodies and complement. These measures were unchanged or lower in A. aequinoctialis. We suggest that small differences in the pathogenic landscape and the stochastic history of mutation and genetic drift are likely to be important in shaping the unique immunological profiles of small isolated populations. Consequently, predicting the impact of introduced disease on the many other endemic faunas of the remote Pacific will remain a challenge

Metagenomics - a guide from sampling to data analysis

Metagenomics applies a suite of genomic technologies and bioinformatics tools to directly access the genetic content of entire communities of organisms. The field of metagenomics has been responsible for substantial advances in microbial ecology, evolution, and diversity over the past 5 to 10 years, and many research laboratories are actively engaged in it now. With the growing numbers of activities also comes a plethora of methodological knowledge and expertise that should guide future developments in the field. This review summarizes the current opinions in metagenomics, and provides practical guidance and advice on sample processing, sequencing technology, assembly, binning, annotation, experimental design, statistical analysis, data storage, and data sharing. As more metagenomic datasets are generated, the availability of standardized procedures and shared data storage and analysis becomes increasingly important to ensure that output of individual projects can be assessed and compared

Metagenomic reconstructions of bacterial CRISPR loci constrain population histories.

Bacterial CRISPR-Cas systems provide insight into recent population history because they rapidly incorporate, in a unidirectional manner, short fragments (spacers) from coexisting infective virus populations into host chromosomes. Immunity is achieved by sequence identity between transcripts of spacers and their targets. Here, we used metagenomics to study the stability and dynamics of the type I-E CRISPR-Cas locus of Leptospirillum group II bacteria in biofilms sampled over 5 years from an acid mine drainage (AMD) system. Despite recovery of 452,686 spacers from CRISPR amplicons and metagenomic data, rarefaction curves of spacers show no saturation. The vast repertoire of spacers is attributed to phage/plasmid population diversity and retention of old spacers, despite rapid evolution of the targeted phage/plasmid genome regions (proto-spacers). The oldest spacers (spacers found at the trailer end) are conserved for at least 5 years, and 12% of these retain perfect or near-perfect matches to proto-spacer targets. The majority of proto-spacer regions contain an AAG proto-spacer adjacent motif (PAM). Spacers throughout the locus target the same phage population (AMDV1), but there are blocks of consecutive spacers without AMDV1 target sequences. Results suggest long-term coexistence of Leptospirillum with AMDV1 and periods when AMDV1 was less dominant. Metagenomics can be applied to millions of cells in a single sample to provide an extremely large spacer inventory, allow identification of phage/plasmids and enable analysis of previous phage/plasmid exposure. Thus, this approach can provide insights into prior bacterial environment and genetic interplay between hosts and their viruses

Elevated temperature alters proteomic responses of individual organisms within a biofilm community.

Microbial communities that underpin global biogeochemical cycles will likely be influenced by elevated temperature associated with environmental change. Here, we test an approach to measure how elevated temperature impacts the physiology of individual microbial groups in a community context, using a model microbial-based ecosystem. The study is the first application of tandem mass tag (TMT)-based proteomics to a microbial community. We accurately, precisely and reproducibly quantified thousands of proteins in biofilms growing at 40, 43 and 46 °C. Elevated temperature led to upregulation of proteins involved in amino-acid metabolism at the level of individual organisms and the entire community. Proteins from related organisms differed in their relative abundance and functional responses to temperature. Elevated temperature repressed carbon fixation proteins from two Leptospirillum genotypes, whereas carbon fixation proteins were significantly upregulated at higher temperature by a third member of this genus. Leptospirillum group III bacteria may have been subject to viral stress at elevated temperature, which could lead to greater carbon turnover in the microbial food web through the release of viral lysate. Overall, these findings highlight the utility of proteomics-enabled community-based physiology studies, and provide a methodological framework for possible extension to additional mixed culture and environmental sample analyses