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Summary: Marine sponges represent one of the few eukaryotic groups that frequently harbour symbiotic members of the Thaumarchaeota, which are important chemoautotrophic ammonia‐oxidizers in many environments. However, in most studies, direct demonstration of ammonia‐oxidation by these archaea within sponges is lacking, and little is known about sponge‐specific adaptations of ammonia‐oxidizing archaea (AOA). Here, we characterized the thaumarchaeal symbiont of the marine sponge Ianthella basta using metaproteogenomics, fluorescence in situ hybridization, qPCR and isotope‐based functional assays. 'Candidatus Nitrosospongia ianthellae' is only distantly related to cultured AOA. It is an abundant symbiont that is solely responsible for nitrite formation from ammonia in I. basta that surprisingly does not harbour nitrite‐oxidizing microbes. Furthermore, this AOA is equipped with an expanded set of extracellular subtilisin‐like proteases, a metalloprotease unique among archaea, as well as a putative branched‐chain amino acid ABC transporter. This repertoire is strongly indicative of a mixotrophic lifestyle and is (with slight variations) also found in other sponge‐associated, but not in free‐living AOA. We predict that this feature as well as an expanded and unique set of secreted serpins (protease inhibitors), a unique array of eukaryotic‐like proteins, and a DNA‐phosporothioation system, represent important adaptations of AOA to life within these ancient filter‐feeding animals. [ABSTRACT FROM AUTHOR]

Summary: Recent metagenomic analyses have revealed a high diversity of viruses in the pelagic ocean and uncovered clear habitat‐specific viral distribution patterns. Conversely, similar insights into the composition, host specificity and function of viruses associated with marine organisms have been limited by challenges associated with sampling and computational analysis. Here, we performed targeted viromic analysis of six coral reef invertebrate species and their surrounding seawater to deliver taxonomic and functional profiles of viruses associated with reef organisms. Sponges and corals' host species‐specific viral assemblages with low sequence identity to known viral genomes. While core viral genes involved in capsid formation, tail structure and infection mechanisms were observed across all reef samples, auxiliary genes including those involved in herbicide resistance and viral pathogenesis pathways such as host immune suppression were differentially enriched in reef hosts. Utilising a novel OTU based assessment, we also show a prevalence of dsDNA viruses belonging to the Mimiviridae, Caudovirales and Phycodnaviridae in reef environments and further highlight the abundance of ssDNA viruses belonging to the Circoviridae, Parvoviridae, Bidnaviridae and Microviridae in reef invertebrates. These insights into coral reef viruses provide an important framework for future research into how viruses contribute to the health and evolution of reef organisms. [ABSTRACT FROM AUTHOR]

Stony corals (Scleractinia) are marine invertebrates that form the foundation and framework upon which tropical reefs are built. The coral animal associates with a diverse microbiome comprised of dinoflagellate algae and other protists, bacteria, archaea, fungi and viruses. Using a metagenomics approach, we analysed the DNA and RNA viral assemblages of seven coral species from the central Great Barrier Reef (GBR), demonstrating that tailed bacteriophages of the Caudovirales dominate across all species examined, and ssDNA viruses, notably the Microviridae, are also prevalent. Most sequences with matches to eukaryotic viruses were assigned to six viral families, including four Nucleocytoplasmic Large DNA Viruses (NCLDVs) families: Iridoviridae, Phycodnaviridae, Mimiviridae, and Poxviridae, as well as Retroviridae and Polydnaviridae. Contrary to previous findings, Herpesvirales were rare in these GBR corals. Sequences of a ssRNA virus with similarities to the dinornavirus, Heterocapsa circularisquama ssRNA virus of the Alvernaviridae that infects free-living dinoflagellates, were observed in three coral species. We also detected viruses previously undescribed from the coral holobiont, including a virus that targets fungi associated with the coral species Acropora tenuis. Functional analysis of the assembled contigs indicated a high prevalence of latency-associated genes in the coral-associated viral assemblages, several host-derived auxiliary metabolic genes (AMGs) for photosynthesis (psbA, psbD genes encoding the photosystem II D1 and D2 proteins respectively), as well as potential nematocyst toxins and antioxidants (genes encoding green fluorescent- like chromoprotein). This study expands the currently limited knowledge on coral- associated viruses by characterising viral composition and function across seven GBR coral species. [ABSTRACT FROM AUTHOR]

Abundant bioinformatics resources are available for the study of complex microbial metagenomes, however their utility in viral metagenomics is limited. HoloVir is a robust and flexible data analysis pipeline that provides an optimized and validated workflow for taxonomic and functional characterization of viral metagenomes derived from invertebrate holobionts. Simulated viral metagenomes comprising varying levels of viral diversity and abundance were used to determine the optimal assembly and gene prediction strategy, and multiple sequence assembly methods and gene prediction tools were tested in order to optimize our analysis workflow. HoloVir performs pairwise comparisons of single read and predicted gene datasets against the viral RefSeq database to assign taxonomy and additional comparison to phage-specific and cellular markers is undertaken to support the taxonomic assignments and identify potential cellular contamination. Broad functional classification of the predicted genes is provided by assignment of COG microbial functional category classifications using EggNOG and higher resolution functional analysis is achieved by searching for enrichment of specific Swiss-Prot keywords within the viral metagenome. Application of HoloVir to viral metagenomes from the coral Pocillopora damicornis and the sponge Rhopaloeides odorabile demonstrated that HoloVir provides a valuable tool to characterize holobiont viral communities across species, environments, or experiments. [ABSTRACT FROM AUTHOR]

Background: The diverse microbial communities in agricultural biogas fermenters are assumed to be well adapted for the anaerobic transformation of plant biomass to methane. Compared to natural systems, biogas reactors are limited in their hydrolytic potential. The reasons for this are not understood. Results: In this paper, we show that a typical industrial biogas reactor fed with maize silage, cow manure, and chicken manure has relatively lower hydrolysis rates compared to feces samples from herbivores. We provide evidence that on average, 2.5 genes encoding cellulolytic GHs/Mbp were identified in the biogas fermenter compared to 3.8 in the elephant feces and 3.2 in the cow rumen data sets. The ratio of genes coding for cellulolytic GH enzymes affiliated with the Firmicutes versus the Bacteroidetes was 2.8:1 in the biogas fermenter compared to 1:1 in the elephant feces and 1.4:1 in the cow rumen sample. Furthermore, RNA-Seq data indicated that highly transcribed cellulases in the biogas fermenter were four times more often affiliated with the Firmicutes compared to the Bacteroidetes, while an equal distribution of these enzymes was observed in the elephant feces sample. Conclusions: Our data indicate that a relatively lower abundance of bacteria affiliated with the phylum of Bacteroidetes and, to some extent, Fibrobacteres is associated with a decreased richness of predicted lignocellulolytic enzymes in biogas fermenters. This difference can be attributed to a partial lack of genes coding for cellulolytic GH enzymes derived from bacteria which are affiliated with the Fibrobacteres and, especially, the Bacteroidetes. The partial deficiency of these genes implies a potentially important limitation in the biogas fermenter with regard to the initial hydrolysis of biomass. Based on these findings, we speculate that increasing the members of Bacteroidetes and Fibrobacteres in biogas fermenters will most likely result in an increased hydrolytic performance. [ABSTRACT FROM AUTHOR]

The systems biology of microbial communities, organismal communities inhabiting all ecological niches on earth, has in recent years been strongly facilitated by the rapid development of experimental, sequencing and data analysis methods. Novel experimental approaches and binning methods in metagenomics render the semi-automatic reconstructions of near-complete genomes of uncultivable bacteria possible, while advances in high-resolution amplicon analysis allow for efficient and less biased taxonomic community characterization. This will also facilitate predictive modeling approaches, hitherto limited by the low resolution of metagenomic data. In this review, we pinpoint the most promising current developments in metagenomics. They facilitate microbial systems biology towards a systemic understanding of mechanisms in microbial communities with scopes of application in many areas of our daily life. [ABSTRACT FROM AUTHOR]

Cellular functions are based on the complex interplay of proteins, therefore the structure and dynamics of these protein-protein interaction (PPI) networks are the key to the functional understanding of cells. In the last years, large-scale PPI networks of several model organisms were investigated. A number of theoretical models have been developed to explain both the network formation and the current structure. Favored are models based on duplication and divergence of genes, as they most closely represent the biological foundation of network evolution. However, studies are often based on simulated instead of empirical data or they cover only single organisms. Methodological improvements now allow the analysis of PPI networks of multiple organisms simultaneously as well as the direct modeling of ancestral networks. This provides the opportunity to challenge existing assumptions on network evolution. We utilized present-day PPI networks from integrated datasets of seven model organisms and developed a theoretical and bioinformatic framework for studying the evolutionary dynamics of PPI networks. A novel filtering approach using percolation analysis was developed to remove low confidence interactions based on topological constraints. We then reconstructed the ancient PPI networks of different ancestors, for which the ancestral proteomes, as well as the ancestral interactions, were inferred. Ancestral proteins were reconstructed using orthologous groups on different evolutionary levels. A stochastic approach, using the duplication-divergence model, was developed for estimating the probabilities of ancient interactions from today's PPI networks. The growth rates for nodes, edges, sizes and modularities of the networks indicate multiplicative growth and are consistent with the results from independent static analysis. Our results support the duplication-divergence model of evolution and indicate fractality and multiplicative growth as general properties of the PPI network structure and dynamics. [ABSTRACT FROM AUTHOR]

The olfactory environment is first represented by glomerular activity patterns in the olfactory bulb. It remains unclear how these representations intersect with sampling behavior to account for the time required to discriminate odors. Using different chemical classes, we investigate glomerular representations and sniffing behavior during olfactory decision-making. Mice rapidly discriminate odorants and learn to increase sniffing frequency at a fixed latency after trial initiation, independent of odor identity. Relative to the increase in sniffing frequency, monomolecular odorants are discriminated within 10–40 ms, while binary mixtures require an additional 60–70 ms. Intrinsic imaging of glomerular activity in anesthetized and awake mice reveals that Euclidean distance between activity patterns and the time needed for discriminations are anti-correlated. Therefore, the similarity of glomerular patterns and their activation strengths, rather than sampling behavior, define the extent of neuronal processing required for odor discrimination, establishing a neural metric to predict olfactory discrimination time. • Similarity and strength of glomerular activity predict odor discrimination time • Stimulus-independent, fixed-latency sniffing increases at decision-making • Odors of different similarity show sniff-invariant odor discrimination times • Discrimination occurs in tens of milliseconds, similarity-dependent processing in 60 ms Bhattacharjee et al. show that mice require more neuronal processing time to discriminate odors of different similarity, irrespective of sniffing. Sniffing is invariably increased at the onset of the decision-making time window. A metric defines discrimination time as a function of similarity and strength of glomerular activity. [ABSTRACT FROM AUTHOR]

Summary The history of humankind is marked by the constant adoption of new dietary habits affecting human physiology, metabolism, and even the development of nutrition-related disorders. Despite clear archaeological evidence for the shift from hunter-gatherer lifestyle to agriculture in Neolithic Europe [ 1 ], very little information exists on the daily dietary habits of our ancestors. By undertaking a complementary -omics approach combined with microscopy, we analyzed the stomach content of the Iceman, a 5,300-year-old European glacier mummy [ 2, 3 ]. He seems to have had a remarkably high proportion of fat in his diet, supplemented with fresh or dried wild meat, cereals, and traces of toxic bracken. Our multipronged approach provides unprecedented analytical depth, deciphering the nutritional habit, meal composition, and food-processing methods of this Copper Age individual. [ABSTRACT FROM AUTHOR]

Coral disease outbreaks contribute to the ongoing degradation of reef ecosystems, however, microbial mechanisms underlying the onset and progression of most coral diseases are poorly understood. Black band disease (BBD) manifests as a cyanobacterial-dominated microbial mat that destroys coral tissues as it rapidly spreads over coral colonies. To elucidate BBD pathogenesis, we apply a comparative metagenomic and metatranscriptomic approach to identify taxonomic and functional changes within microbial lesions during in-situ development of BBD from a comparatively benign stage termed cyanobacterial patches. Results suggest that photosynthetic CO2-fixation in Cyanobacteria substantially enhances productivity of organic matter within the lesion during disease development. Photosynthates appear to subsequently promote sulfide-production by Deltaproteobacteria, facilitating the major virulence factor of BBD. Interestingly, our metagenome-enabled transcriptomic analysis reveals that BBD-associated cyanobacteria have a putative mechanism that enables them to adapt to higher levels of hydrogen sulfide within lesions, underpinning the pivotal roles of the dominant cyanobacterium within the polymicrobial lesions during the onset of BBD. The current study presents sequence-based evidence derived from whole microbial communities that unravel the mechanism of development and progression of BBD. [ABSTRACT FROM AUTHOR]

Methods for assembly, taxonomic profiling and binning are key to interpreting metagenome data, but a lack of consensus about benchmarking complicates performance assessment. The Critical Assessment of Metagenome Interpretation (CAMI) challenge has engaged the global developer community to benchmark their programs on highly complex and realistic data sets, generated from ∼700 newly sequenced microorganisms and ∼600 novel viruses and plasmids and representing common experimental setups. Assembly and genome binning programs performed well for species represented by individual genomes but were substantially affected by the presence of related strains. Taxonomic profiling and binning programs were proficient at high taxonomic ranks, with a notable performance decrease below family level. Parameter settings markedly affected performance, underscoring their importance for program reproducibility. The CAMI results highlight current challenges but also provide a roadmap for software selection to answer specific research questions.

The gut microbiota generates a huge pool of unknown metabolites, and their identification and characterization is a key challenge in metabolomics. However, there are still gaps on the studies of gut microbiota and their chemical structures. In this investigation, an unusual class of bacterial sulfonolipids (SLs) is detected in mouse cecum, which was originally found in environmental microbes. We have performed a detailed molecular level characterization of this class of lipids by combining high-resolution mass spectrometry and liquid chromatography analysis. Eighteen SLs that differ in their capnoid and fatty acid chain compositions were identified. The SL called "sulfobacin B" was isolated, characterized, and was significantly increased in mice fed with high-fat diets. To reveal bacterial producers of SLs, metagenome analysis was acquired and only two bacterial genera, i.e., Alistipes and Odoribacter, were revealed to be responsible for their production. This knowledge enables explaining a part of the molecular complexity introduced by microbes to the mammalian gastrointestinal tract and can be used as chemotaxonomic evidence in gut microbiota.