TY - JOUR A1 - Cuadrat, Rafael R. C. A1 - Ionescu, Danny A1 - Davila, Alberto M. R. A1 - Grossart, Hans-Peter T1 - Recovering genomics clusters of secondary metabolites from lakes using genome-resolved metagenomics JF - Frontiers in microbiology N2 - Metagenomic approaches became increasingly popular in the past decades due to decreasing costs of DNA sequencing and bioinformatics development. So far, however, the recovery of long genes coding for secondary metabolites still represents a big challenge. Often, the quality of metagenome assemblies is poor, especially in environments with a high microbial diversity where sequence coverage is low and complexity of natural communities high. Recently, new and improved algorithms for binning environmental reads and contigs have been developed to overcome such limitations. Some of these algorithms use a similarity detection approach to classify the obtained reads into taxonomical units and to assemble draft genomes. This approach, however, is quite limited since it can classify exclusively sequences similar to those available (and well classified) in the databases. In this work, we used draft genomes from Lake Stechlin, north-eastern Germany, recovered by MetaBat, an efficient binning tool that integrates empirical probabilistic distances of genome abundance, and tetranucleotide frequency for accurate metagenome binning. These genomes were screened for secondary metabolism genes, such as polyketide synthases (PKS) and non-ribosomal peptide synthases (NRPS), using the Anti-SMASH and NAPDOS workflows. With this approach we were able to identify 243 secondary metabolite clusters from 121 genomes recovered from our lake samples. A total of 18 NRPS, 19 PKS, and 3 hybrid PKS/NRPS clusters were found. In addition, it was possible to predict the partial structure of several secondary metabolite clusters allowing for taxonomical classifications and phylogenetic inferences. Our approach revealed a high potential to recover and study secondary metabolites genes from any aquatic ecosystem. KW - metagenomics 2.0 KW - PKS KW - NRPS KW - freshwater KW - environmental genomics Y1 - 2018 U6 - https://doi.org/10.3389/fmicb.2018.00251 SN - 1664-302X VL - 9 PB - Frontiers Research Foundation CY - Lausanne ER - TY - JOUR A1 - Gubelit, Yulia I. A1 - Grossart, Hans-Peter T1 - New Methods, New Concepts BT - What Can Be Applied to Freshwater Periphyton? JF - Frontiers in Microbiology N2 - Microbial interactions play an essential role in aquatic ecosystems and are of the great interest for both marine and freshwater ecologists. Recent development of new technologies and methods allowed to reveal many functional mechanisms and create new concepts. Yet, many fundamental aspects of microbial interactions have been almost exclusively studied for marine pelagic and benthic ecosystems. These studies resulted in a formulation of the Black Queen Hypothesis, a development of the phycosphere concept for pelagic communities, and a realization of microbial communication as a key mechanism for microbial interactions. In freshwater ecosystems, especially for periphyton communities, studies focus mainly on physiology, biodiversity, biological indication, and assessment, but the many aspects of microbial interactions are neglected to a large extent. Since periphyton plays a great role for aquatic nutrient cycling, provides the basis for water purification, and can be regarded as a hotspot of microbial biodiversity, we highlight that more in-depth studies on microbial interactions in periphyton are needed to improve our understanding on functioning of freshwater ecosystems. In this paper we first present an overview on recent concepts (e.g., the “Black Queen Hypothesis”) derived from state-of-the-art OMICS methods including metagenomics, metatranscriptomics, and metabolomics. We then point to the avenues how these methods can be applied for future studies on biodiversity and the ecological role of freshwater periphyton, a yet largely neglected component of many freshwater ecosystems. KW - freshwater KW - lake periphyton KW - microbial interactions KW - Black Queen Hypothesis KW - OMICs tools Y1 - 2020 U6 - https://doi.org/10.3389/fmicb.2020.01275 SN - 1664-302X VL - 11 PB - Frontiers Media CY - Lausanne ER -