Niche differentiation among annually recurrent coastal marine group II Euryarchaeota

Since the discovery of archaeoplankton in 1992, the euryarchaeotal Marine Group II (MGII) remains uncultured and less understood than other planktonic archaea. We characterized the seasonal dynamics of MGII populations in the southern North Sea on a genomic and microscopic level over the course of four years. We recovered 34 metagenome-assembled genomes (MAGs) of MGIIa and MGIIb that corroborated proteorhodopsin-based photoheterotrophic lifestyles. However, MGIIa and MGIIb MAG genome sizes differed considerably (~1.9 vs. ~1.4 Mbp), as did their transporter, peptidase, flagella and sulfate assimilation gene repertoires. MGIIb populations were characteristic of winter samples, whereas MGIIa accounted for up to 23% of the community at the beginning of summer. Both clades consisted of annually recurring, sequence-discrete populations with low intra-population sequence diversity. Oligotyping of filtered cell-size fractions and microscopy consistently suggested that MGII cells were predominantly free-living. Cells were coccoid and ~0.7 µm in diameter, likely resulting in grazing avoidance. Based on multiple lines of evidence, we propose distinct niche adaptations of MGIIa and MGIIb Euryarchaeota populations that are characteristic of summer and winter conditions in the coastal North Sea

Functional characterization of polysaccharide utilization loci in the marine Bacteroidetes 'Gramella forsetii' KT0803

Members of the phylum Bacteroidetes are abundant in many marine ecosystems and are known to have a pivotal role in the mineralization of complex organic substrates such as polysaccharides and proteins. We studied the decomposition of the algal glycans laminarin and alginate by 'Gramella forsetii' KT0803, a bacteroidetal isolate from North Sea surface waters. A combined application of isotope labeling, subcellular protein fractionation and quantitative proteomics revealed two large polysaccharide utilization loci (PULs) that were specifically induced, one by alginate and the other by laminarin. These regulons comprised genes of surface-exposed proteins such as oligomer transporters, substrate-binding proteins, carbohydrate-active enzymes and hypothetical proteins. Besides, several glycan-specific TonB-dependent receptors and SusD-like substrate-binding proteins were expressed also in the absence of polysaccharide substrates, suggesting an anticipatory sensing function. Genes for the utilization of the beta-1,3-glucan laminarin were found to be co-regulated with genes for glucose and alpha-1,4-glucan utilization, which was not the case for the non-glucan alginate. Strong syntenies of the PULs of 'G. forsetii' with similar loci in other Bacteroidetes indicate that the specific response mechanisms of 'G. forsetii' to changes in polysaccharide availability likely apply to other Bacteroidetes. Our results can thus contribute to an improved understanding of the ecological niches of marine Bacteroidetes and their roles in the polysaccharide decomposition part of carbon cycling in marine ecosystems

The Evolution of Bat Vestibular Systems in the Face of Potential Antagonistic Selection Pressures for Flight and Echolocation

PMCID: PMC3634842This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Genome-wide signatures of convergent evolution in echolocating mammals

Evolution is typically thought to proceed through divergence of genes, proteins, and ultimately phenotypes(1-3). However, similar traits might also evolve convergently in unrelated taxa due to similar selection pressures(4,5). Adaptive phenotypic convergence is widespread in nature, and recent results from a handful of genes have suggested that this phenomenon is powerful enough to also drive recurrent evolution at the sequence level(6-9). Where homoplasious substitutions do occur these have long been considered the result of neutral processes. However, recent studies have demonstrated that adaptive convergent sequence evolution can be detected in vertebrates using statistical methods that model parallel evolution(9,10) although the extent to which sequence convergence between genera occurs across genomes is unknown. Here we analyse genomic sequence data in mammals that have independently evolved echolocation and show for the first time that convergence is not a rare process restricted to a handful of loci but is instead widespread, continuously distributed and commonly driven by natural selection acting on a small number of sites per locus. Systematic analyses of convergent sequence evolution in 805,053 amino acids within 2,326 orthologous coding gene sequences compared across 22 mammals (including four new bat genomes) revealed signatures consistent with convergence in nearly 200 loci. Strong and significant support for convergence among bats and the dolphin was seen in numerous genes linked to hearing or deafness, consistent with an involvement in echolocation. Surprisingly we also found convergence in many genes linked to vision: the convergent signal of many sensory genes was robustly correlated with the strength of natural selection. This first attempt to detect genome-wide convergent sequence evolution across divergent taxa reveals the phenomenon to be much more pervasive than previously recognised

TACOA – Taxonomic classification of environmental genomic fragments using a kernelized nearest neighbor approach

Diaz NN, Krause L, Goesmann A, Niehaus K, Nattkemper TW. TACOA - Taxonomic classification of environmental genomic fragments using a kernelized nearest neighbor approach. BMC Bioinformatics. 2009;10(1):56.Background: Metagenomics, or the sequencing and analysis of collective genomes (metagenomes) of microorganisms isolated from an environment, promises direct access to the "unculturable majority". This emerging field offers the potential to lay solid basis on our understanding of the entire living world. However, the taxonomic classification is an essential task in the analysis of metagenomics data sets that it is still far from being solved. We present a novel strategy to predict the taxonomic origin of environmental genomic fragments. The proposed classifier combines the idea of the k-nearest neighbor with strategies from kernel-based learning. Results Our novel strategy was extensively evaluated using the leave-one-out cross validation strategy on fragments of variable length (800 bp – 50 Kbp) from 373 completely sequenced genomes. TACOA is able to classify genomic fragments of length 800 bp and 1 Kbp with high accuracy until rank class. For longer fragments ≥ 3 Kbp accurate predictions are made at even deeper taxonomic ranks (order and genus). Remarkably, TACOA also produces reliable results when the taxonomic origin of a fragment is not represented in the reference set, thus classifying such fragments to its known broader taxonomic class or simply as "unknown". We compared the classification accuracy of TACOA with the latest intrinsic classifier PhyloPythia using 63 recently published complete genomes. For fragments of length 800 bp and 1 Kbp the overall accuracy of TACOA is higher than that obtained by PhyloPythia at all taxonomic ranks. For all fragment lengths, both methods achieved comparable high specificity results up to rank class and low false negative rates are also obtained. Conclusion: An accurate multi-class taxonomic classifier was developed for environmental genomic fragments. TACOA can predict with high reliability the taxonomic origin of genomic fragments as short as 800 bp. The proposed method is transparent, fast, accurate and the reference set can be easily updated as newly sequenced genomes become available. Moreover, the method demonstrated to be competitive when compared to the most current classifier PhyloPythia and has the advantage that it can be locally installed and the reference set can be kept up-to-date. Background

The Darkening Cloud of Diabetes: Do trends in cardiovascular risk management provide a silver lining?

OBJECTIVE—We aimed to evaluate the changes in cardiovascular-related health care utilization (drug therapies, hospitalizations) and mortality for the diabetic population during a 9-year period in Saskatchewan, Canada

Simultaneous genome sequencing of symbionts and their hosts

Second-generation sequencing has made possible the sequencing of genomes of interest for even small research groups. However, obtaining separate clean cultures and clonal or inbred samples of metazoan hosts and their bacterial symbionts is often difficult. We present a computational pipeline for separating metazoan and bacterial DNA in silico rather than at the bench. The method relies on the generation of deep coverage of all the genomes in a mixed sample using Illumina short-read sequencing technology, and using aggregate properties of the different genomes to identify read sets belonging to each. This inexpensive and rapid approach has been used to sequence several nematode genomes and their bacterial endosymbionts in the last year in our laboratory and can also be used to visualize and identify unexpected contaminants (or possible symbionts) in genomic DNA samples. We hope that this method will enable researchers studying symbiotic systems to move from gene-centric to genome-centric approaches

Bat conservation and zoonotic disease risk: a research agenda to prevent misguided persecution in the aftermath of COVID-19

Letter to the EditorCOVID-19 has spread around the globe, with massive impacts on global human health, national economies and conservation activities. In the timely editorial about conservation in the maelstrom of COVID-19, Evans et al. (2020) urged the conservation community to collaborate with other relevant sectors of society in the search for solutions to the challenges posed by the current pandemic, as well as future zoonotic outbreaks. Considering the association of COVID 19 with bats (Zhou et al., 2020), bat conservationists will undoubtedly be key actors in this dialogue, and thus an action plan on how best to adjust bat conservation to this new reality, alongside a transdisciplinary research agenda, are clear prioritiesinfo:eu-repo/semantics/publishedVersio

Adaptive Evolution of the Myo6 Gene in Old World Fruit Bats (Family: Pteropodidae)

PMCID: PMC3631194This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Joint Analysis of Multiple Metagenomic Samples

The availability of metagenomic sequencing data, generated by sequencing DNA pooled from multiple microbes living jointly, has increased sharply in the last few years with developments in sequencing technology. Characterizing the contents of metagenomic samples is a challenging task, which has been extensively attempted by both supervised and unsupervised techniques, each with its own limitations. Common to practically all the methods is the processing of single samples only; when multiple samples are sequenced, each is analyzed separately and the results are combined. In this paper we propose to perform a combined analysis of a set of samples in order to obtain a better characterization of each of the samples, and provide two applications of this principle. First, we use an unsupervised probabilistic mixture model to infer hidden components shared across metagenomic samples. We incorporate the model in a novel framework for studying association of microbial sequence elements with phenotypes, analogous to the genome-wide association studies performed on human genomes: We demonstrate that stratification may result in false discoveries of such associations, and that the components inferred by the model can be used to correct for this stratification. Second, we propose a novel read clustering (also termed “binning”) algorithm which operates on multiple samples simultaneously, leveraging on the assumption that the different samples contain the same microbial species, possibly in different proportions. We show that integrating information across multiple samples yields more precise binning on each of the samples. Moreover, for both applications we demonstrate that given a fixed depth of coverage, the average per-sample performance generally increases with the number of sequenced samples as long as the per-sample coverage is high enough