@article{KrohnMoltAlawiFoerstneretal.2017,
  author    = {Krohn-Molt, Ines and Alawi, Malik and F{\"o}rstner, Konrad U. and Wiegandt, Alena and Burkhardt, Lia and Indenbirken, Daniela and Thieß, Melanie and Grundhoff, Adam and Kehr, Julia and Tholey, Andreas and Streit, Wolfgang R.},
  title     = {Insights into microalga and bacteria interactions of selected phycosphere biofilms using metagenomic, transcriptomic, and proteomic approaches},
  series = {Frontiers in Microbiology},
  volume    = {2017},
  journal   = {Frontiers in Microbiology},
  number    = {8},
  doi       = {10.3389/fmicb.2017.01941},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-173701},
  year      = {2017},
  abstract  = {Microalga are of high relevance for the global carbon cycling and it is well-known that they are associated with a microbiota. However, it remains unclear, if the associated microbiota, often found in phycosphere biofilms, is specific for the microalga strains and which role individual bacterial taxa play. Here we provide experimental evidence that \(Chlorella\) \(saccharophila\), \(Scenedesmus\) \(quadricauda\), and \(Micrasterias\) \(crux-melitensis\), maintained in strain collections, are associated with unique and specific microbial populations. Deep metagenome sequencing, binning approaches, secretome analyses in combination with RNA-Seq data implied fundamental differences in the gene expression profiles of the microbiota associated with the different microalga. Our metatranscriptome analyses indicates that the transcriptionally most active bacteria with respect to key genes commonly involved in plant-microbe interactions in the Chlorella (Trebouxiophyceae) and Scenedesmus (Chlorophyceae) strains belong to the phylum of the α-Proteobacteria. In contrast, in the Micrasterias (Zygnematophyceae) phycosphere biofilm bacteria affiliated with the phylum of the Bacteroidetes showed the highest gene expression rates. We furthermore show that effector molecules known from plant-microbe interactions as inducers for the innate immunity are already of relevance at this evolutionary early plant-microbiome level.},
  language  = {en}
}
@article{HicklHeintzBuschartTrautweinSchultetal.2019,
  author    = {Hickl, Oskar and Heintz-Buschart, Anna and Trautwein-Schult, Anke and Hercog, Rajna and Bork, Peer and Wilmes, Paul and Becher, D{\"o}rte},
  title     = {Sample preservation and storage significantly impact taxonomic and functional profiles in metaproteomics studies of the human gut microbiome},
  series = {Microorganisms},
  volume    = {7},
  journal   = {Microorganisms},
  number    = {9},
  issn      = {2076-2607},
  doi       = {10.3390/microorganisms7090367},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-195976},
  year      = {2019},
  abstract  = {With the technological advances of the last decade, it is now feasible to analyze microbiome samples, such as human stool specimens, using multi-omic techniques. Given the inherent sample complexity, there exists a need for sample methods which preserve as much information as possible about the biological system at the time of sampling. Here, we analyzed human stool samples preserved and stored using different methods, applying metagenomics as well as metaproteomics. Our results demonstrate that sample preservation and storage have a significant effect on the taxonomic composition of identified proteins. The overall identification rates, as well as the proportion of proteins from Actinobacteria were much higher when samples were flash frozen. Preservation in RNAlater overall led to fewer protein identifications and a considerable increase in the share of Bacteroidetes, as well as Proteobacteria. Additionally, a decrease in the share of metabolism-related proteins and an increase of the relative amount of proteins involved in the processing of genetic information was observed for RNAlater-stored samples. This suggests that great care should be taken in choosing methods for the preservation and storage of microbiome samples, as well as in comparing the results of analyses using different sampling and storage methods. Flash freezing and subsequent storage at -80 °C should be chosen wherever possible.},
  language  = {en}
}