Urban water systems under climate stress : An isotopic perspective from Berlin, Germany

ACKNOWLEDGMENTS This project was funded by the German Research Foundation (DFG) as part of the Research Training Group “Urban Water Interfaces (UWI)” (GRK 2032, Project W1: “Ecohydrological controls on urban groundwater recharge: an isotope‐based approach”) and supported by the project “Modelling surface and groundwater with isotopes in urban catchments (MOSAIC)” funded by the Einstein‐Foundation. We thank all colleagues involved in the sample collection (A. Smith, N. Weiß, L. Kleine, L. Lachmann, E. Brakkee, W. Lehmann, A. Douinot, K. Dyck, D. Dubbert, H. Dämpfling, A. Wieland), D. Dubbert for support with the isotope analysis, our colleagues in the chemical analytics laboratory at IGB for their support with the chemical analysis, in particular T. Goldhammer, as well as T. Rossoll for help with the measurement equipment. We further thank the BWB and especially the Berlin Senate Department for the Environment, Transport and Climate Protection for the support in accessing groundwater wells and the provided data.Peer reviewedPublisher PDFPublisher PD

How much do we really lose?—Yield losses in the proximity of natural landscape elements in agricultural landscapes

Natural landscape elements (NLEs) in agricultural landscapes contribute to biodiversity and ecosystem services, but are also regarded as an obstacle for large‐scale agricultural production. However, the effects of NLEs on crop yield have rarely been measured. Here, we investigated how different bordering structures, such as agricultural roads, field‐to‐field borders, forests, hedgerows, and kettle holes, influence agricultural yields. We hypothesized that (a) yield values at field borders differ from mid‐field yields and that (b) the extent of this change in yields depends on the bordering structure. We measured winter wheat yields along transects with log‐scaled distances from the border into the agricultural field within two intensively managed agricultural landscapes in Germany (2014 near Göttingen, and 2015–2017 in the Uckermark). We observed a yield loss adjacent to every investigated bordering structure of 11%–38% in comparison with mid‐field yields. However, depending on the bordering structure, this yield loss disappeared at different distances. While the proximity of kettle holes did not affect yields more than neighboring agricultural fields, woody landscape elements had strong effects on winter wheat yields. Notably, 95% of mid‐field yields could already be reached at a distance of 11.3 m from a kettle hole and at a distance of 17.8 m from hedgerows as well as forest borders. Our findings suggest that yield losses are especially relevant directly adjacent to woody landscape elements, but not adjacent to in‐field water bodies. This highlights the potential to simultaneously counteract yield losses close to the field border and enhance biodiversity by combining different NLEs in agricultural landscapes such as creating strips of extensive grassland vegetation between woody landscape elements and agricultural fields. In conclusion, our results can be used to quantify ecocompensations to find optimal solutions for the delivery of productive and regulative ecosystem services in heterogeneous agricultural landscapes

A direct comparison of the KB™ Basecaller and phred for identifying the bases from DNA sequencing using chain termination chemistry

<p>Abstract</p> <p>Background</p> <p>Relatively recently, the software KB™ Basecaller has replaced <it>phred </it>for identifying the bases from raw sequence data in DNA sequencing employing dideoxy chemistry. We have measured quantitatively the consequences of that change.</p> <p>Results</p> <p>The high quality sequence segment of reads derived from the KB™ Basecaller were, on average, 30-to-50 bases longer than reads derived from <it>phred</it>. However, microbe identification appeared to have been unaffected by the change in software.</p> <p>Conclusions</p> <p>We have demonstrated a modest, but statistically significant, superiority in high quality read length of the KB™ Basecaller compared to <it>phred</it>. We found no statistically significant difference between the numbers of microbial species identified from the sequence data.</p

Transkingdom Networks: A Systems Biology Approach to Identify Causal Members of Host-Microbiota Interactions

Improvements in sequencing technologies and reduced experimental costs have resulted in a vast number of studies generating high-throughput data. Although the number of methods to analyze these "omics" data has also increased, computational complexity and lack of documentation hinder researchers from analyzing their high-throughput data to its true potential. In this chapter we detail our data-driven, transkingdom network (TransNet) analysis protocol to integrate and interrogate multi-omics data. This systems biology approach has allowed us to successfully identify important causal relationships between different taxonomic kingdoms (e.g. mammals and microbes) using diverse types of data

Prospecting environmental mycobacteria: combined molecular approaches reveal unprecedented diversity

Background: Environmental mycobacteria (EM) include species commonly found in various terrestrial and aquatic environments, encompassing animal and human pathogens in addition to saprophytes. Approximately 150 EM species can be separated into fast and slow growers based on sequence and copy number differences of their 16S rRNA genes. Cultivation methods are not appropriate for diversity studies; few studies have investigated EM diversity in soil despite their importance as potential reservoirs of pathogens and their hypothesized role in masking or blocking M. bovis BCG vaccine. Methods: We report here the development, optimization and validation of molecular assays targeting the 16S rRNA gene to assess diversity and prevalence of fast and slow growing EM in representative soils from semi tropical and temperate areas. New primer sets were designed also to target uniquely slow growing mycobacteria and used with PCR-DGGE, tag-encoded Titanium amplicon pyrosequencing and quantitative PCR. Results: PCR-DGGE and pyrosequencing provided a consensus of EM diversity; for example, a high abundance of pyrosequencing reads and DGGE bands corresponded to M. moriokaense, M. colombiense and M. riyadhense. As expected pyrosequencing provided more comprehensive information; additional prevalent species included M. chlorophenolicum, M. neglectum, M. gordonae, M. aemonae. Prevalence of the total Mycobacterium genus in the soil samples ranged from 2.3×107 to 2.7×108 gene targets g−1; slow growers prevalence from 2.9×105 to 1.2×107 cells g−1. Conclusions: This combined molecular approach enabled an unprecedented qualitative and quantitative assessment of EM across soil samples. Good concordance was found between methods and the bioinformatics analysis was validated by random resampling. Sequences from most pathogenic groups associated with slow growth were identified in extenso in all soils tested with a specific assay, allowing to unmask them from the Mycobacterium whole genus, in which, as minority members, they would have remained undetected

Identification of an α(1→6) mannopyranosyltransferase (MptA), involved in Corynebacterium glutamicum lipomanann biosynthesis, and identification of its orthologue in Mycobacterium tuberculosis

Corynebacterium glutamicum and Mycobacterium tuberculosis share a similar cell wall architecture, and the availability of their genome sequences has enabled the utilization of C. glutamicum as a model for the identification and study of, otherwise essential, mycobacterial genes involved in lipomannan (LM) and lipoarabinomannan (LAM) biosynthesis. We selected the putative glycosyltransferase-Rv2174 from M. tuberculosis and deleted its orthologue NCgl2093 from C. glutamicum. This resulted in the formation of a novel truncated lipomannan (Cg-t-LM) and a complete ablation of LM/LAM biosynthesis. Purification and characterization of Cg-t-LM revealed an overall decrease in molecular mass, a reduction of α(1→6) and α(1→2) glycosidic linkages illustrating a reduced degree of branching compared with wild-type LM. The deletion mutant's biochemical phenotype was fully complemented by either NCgl2093 or Rv2174. Furthermore, the use of a synthetic neoglycolipid acceptor in an in vitro cell-free assay utilizing the sugar donor β-d-mannopyranosyl-1-monophosphoryl-decaprenol together with the neoglycolipid acceptor α-d-Manp-(1→6)-α-d-Manp-O-C8 as a substrate, confirmed NCgl2093 and Rv2174 as an α(1→6) mannopyranosyltransferase (MptA), involved in the latter stages of the biosynthesis of the α(1→6) mannan core of LM. Altogether, these studies have identified a new mannosyltransferase, MptA, and they shed further light on the biosynthesis of LM/LAM in Corynebacterianeae

Networks of Gene Sharing among 329 Proteobacterial Genomes Reveal Differences in Lateral Gene Transfer Frequency at Different Phylogenetic Depths

Lateral gene transfer (LGT) is an important mechanism of natural variation among prokaryotes. Over the full course of evolution, most or all of the genes resident in a given prokaryotic genome have been affected by LGT, yet the frequency of LGT can vary greatly across genes and across prokaryotic groups. The proteobacteria are among the most diverse of prokaryotic taxa. The prevalence of LGT in their genome evolution calls for the application of network-based methods instead of tree-based methods to investigate the relationships among these species. Here, we report networks that capture both vertical and horizontal components of evolutionary history among 1,207,272 proteins distributed across 329 sequenced proteobacterial genomes. The network of shared proteins reveals modularity structure that does not correspond to current classification schemes. On the basis of shared protein-coding genes, the five classes of proteobacteria fall into two main modules, one including the alpha-, delta-, and epsilonproteobacteria and the other including beta- and gammaproteobacteria. The first module is stable over different protein identity thresholds. The second shows more plasticity with regard to the sequence conservation of proteins sampled, with the gammaproteobacteria showing the most chameleon-like evolutionary characteristics within the present sample. Using a minimal lateral network approach, we compared LGT rates at different phylogenetic depths. In general, gene evolution by LGT within proteobacteria is very common. At least one LGT event was inferred to have occurred in at least 75% of the protein families. The average LGT rate at the species and class depth is about one LGT event per protein family, the rate doubling at the phylum level to an average of two LGT events per protein family. Hence, our results indicate that the rate of gene acquisition per protein family is similar at the level of species (by recombination) and at the level of classes (by LGT). The frequency of LGT per genome strongly depends on the species lifestyle, with endosymbionts showing far lower LGT frequencies than free-living species. Moreover, the nature of the transferred genes suggests that gene transfer in proteobacteria is frequently mediated by conjugation