@article{NumbergerGanzertZoccaratoetal.2019, author = {Numberger, Daniela and Ganzert, Lars and Zoccarato, Luca and M{\"u}hldorfer, Kristin and Sauer, Sascha and Grossart, Hans-Peter and Greenwood, Alex D.}, title = {Characterization of bacterial communities in wastewater with enhanced taxonomic resolution by full-length 16S rRNA sequencing}, series = {Scientific reports}, volume = {9}, journal = {Scientific reports}, publisher = {Nature Publ. Group}, address = {London}, issn = {2045-2322}, doi = {10.1038/s41598-019-46015-z}, pages = {14}, year = {2019}, abstract = {Wastewater treatment is crucial to environmental hygiene in urban environments. However, wastewater treatment plants (WWTPs) collect chemicals, organic matter, and microorganisms including pathogens and multi-resistant bacteria from various sources which may be potentially released into the environment via WWTP effluent. To better understand microbial dynamics in WWTPs, we characterized and compared the bacterial community of the inflow and effluent of a WWTP in Berlin, Germany using full-length 16S rRNA gene sequences, which allowed for species level determination in many cases and generally resolved bacterial taxa. Significantly distinct bacterial communities were identified in the wastewater inflow and effluent samples. Dominant operational taxonomic units (OTUs) varied both temporally and spatially. Disease associated bacterial groups were efficiently reduced in their relative abundance from the effluent by the WWTP treatment process, except for Legionella and Leptospira species which demonstrated an increase in relative proportion from inflow to effluent. This indicates that WWTPs, while effective against enteric bacteria, may enrich and release other potentially pathogenic bacteria into the environment. The taxonomic resolution of full-length 16S rRNA genes allows for improved characterization of potential pathogenic taxa and other harmful bacteria which is required to reliably assess health risk.}, language = {en} } @article{KettnerOberbeckmannLabrenzetal.2019, author = {Kettner, Marie Therese and Oberbeckmann, Sonja and Labrenz, Matthias and Grossart, Hans-Peter}, title = {The Eukaryotic Life on Microplastics in Brackish Ecosystems}, series = {Frontiers in Microbiology}, volume = {10}, journal = {Frontiers in Microbiology}, publisher = {Frontiers Media}, address = {Lausanne}, issn = {1664-302X}, doi = {10.3389/fmicb.2019.00538}, pages = {13}, year = {2019}, abstract = {Microplastics (MP) constitute a widespread contaminant all over the globe. Rivers and wastewater treatment plants (WWTP) transport annually several million tons of MP into freshwaters, estuaries and oceans, where they provide increasing artificial surfaces for microbial colonization. As knowledge on MP-attached communities is insufficient for brackish ecosystems, we conducted exposure experiments in the coastal Baltic Sea, an in-flowing river and a WWTP within the drainage basin. While reporting on prokaryotic and fungal communities from the same set-up previously, we focus here on the entire eukaryotic communities. Using high-throughput 18S rRNA gene sequencing, we analyzed the eukaryotes colonizing on two types of MP, polyethylene and polystyrene, and compared them to the ones in the surrounding water and on a natural surface (wood). More than 500 different taxa across almost all kingdoms of the eukaryotic tree of life were identified on MP, dominated by Alveolata, Metazoa, and Chloroplastida. The eukaryotic community composition on MP was significantly distinct from wood and the surrounding water, with overall lower diversity and the potentially harmful dinoflagellate Pfiesteria being enriched on MP. Co-occurrence networks, which include prokaryotic and eukaryotic taxa, hint at possibilities for dynamic microbial interactions on MP. This first report on total eukaryotic communities on MP in brackish environments highlights the complexity of MP-associated biofilms, potentially leading to altered microbial activities and hence changes in ecosystem functions.}, language = {en} } @article{RojasJimenezRieckWurzbacheretal.2019, author = {Rojas-Jimenez, Keilor and Rieck, Angelika and Wurzbacher, Christian and J{\"u}rgens, Klaus and Labrenz, Matthias and Grossart, Hans-Peter}, title = {A Salinity Threshold Separating Fungal Communities in the Baltic Sea}, series = {Frontiers in Microbiology}, volume = {10}, journal = {Frontiers in Microbiology}, publisher = {Frontiers Media}, address = {Lausanne}, issn = {1664-302X}, doi = {10.3389/fmicb.2019.00680}, pages = {9}, year = {2019}, abstract = {Salinity is a significant factor for structuring microbial communities, but little is known for aquatic fungi, particularly in the pelagic zone of brackish ecosystems. In this study, we explored the diversity and composition of fungal communities following a progressive salinity decline (from 34 to 3 PSU) along three transects of ca. 2000 km in the Baltic Sea, the world's largest estuary. Based on 18S rRNA gene sequence analysis, we detected clear changes in fungal community composition along the salinity gradient and found significant differences in composition of fungal communities established above and below a critical value of 8 PSU. At salinities below this threshold, fungal communities resembled those from freshwater environments, with a greater abundance of Chytridiomycota, particularly of the orders Rhizophydiales, Lobulomycetales, and Gromochytriales. At salinities above 8 PSU, communities were more similar to those from marine environments and, depending on the season, were dominated by a strain of the LKM11 group (Cryptomycota) or by members of Ascomycota and Basidiomycota. Our results highlight salinity as an important environmental driver also for pelagic fungi, and thus should be taken into account to better understand fungal diversity and ecological function in the aquatic realm.}, language = {en} } @phdthesis{Tong2019, author = {Tong, Hao}, title = {Dissection of genetic architecture of intermediate phenotypes and predictions in plants}, school = {Universit{\"a}t Potsdam}, pages = {127}, year = {2019}, abstract = {Determining the relationship between genotype and phenotype is the key to understand the plasticity and robustness of phenotypes in nature. While the directly observable plant phenotypes (e.g. agronomic, yield and stress resistance traits) have been well-investigated, there is still a lack in our knowledge about the genetic basis of intermediate phenotypes, such as metabolic phenotypes. Dissecting the links between genotype and phenotype depends on suitable statistical models. The state-of-the-art models are developed for directly observable phenotypes, regardless the characteristics of intermediate phenotypes. This thesis aims to fill the gaps in understanding genetic architecture of intermediate phenotypes, and how they tie to composite traits, namely plant growth. The metabolite levels and reaction fluxes, as two aspects of metabolic phenotypes, are shaped by the interrelated chemical reactions formed in genome-scale metabolic network. Here, I attempt to answer the question: Can the knowledge of underlying genome-scale metabolic network improve the model performance for prediction of metabolic phenotypes and associated plant growth? To this end, two projects are investigated in this thesis. Firstly, we propose an approach that couples genomic selection with genome-scale metabolic network and metabolic profiles in Arabidopsis thaliana to predict growth. This project is the first integration of genomic data with fluxes predicted based on constraint-based modeling framework and data on biomass composition. We demonstrate that our approach leads to a considerable increase of prediction accuracy in comparison to the state-of-the-art methods in both within and across environment predictions. Therefore, our work paves the way for combining knowledge on metabolic mechanisms in the statistical approach underlying genomic selection to increase the efficiency of future plant breeding approaches. Secondly, we investigate how reliable is genomic selection for metabolite levels, and which single nucleotide polymorphisms (SNPs), obtained from different neighborhoods of a given metabolic network, contribute most to the accuracy of prediction. The results show that the local structure of first and second neighborhoods are not sufficient for predicting the genetic basis of metabolite levels in Zea mays. Furthermore, we find that the enzymatic SNPs can capture most the genetic variance and the contribution of non-enzymatic SNPs is in fact small. To comprehensively understand the genetic architecture of metabolic phenotypes, I extend my study to a local Arabidopsis thaliana population and their hybrids. We analyze the genetic architecture in primary and secondary metabolism as well as in growth. In comparison to primary metabolites, compounds from secondary metabolism were more variable and show more non-additive inheritance patterns which could be attributed to epistasis. Therefore, our study demonstrates that heterozygosity in local Arabidopsis thaliana population generates metabolic variation and may impact several tasks directly linked to metabolism. The studies in this thesis improve the knowledge of genetic architecture of metabolic phenotypes in both inbreed and hybrid population. The approaches I proposed to integrate genome-scale metabolic network with genomic data provide the opportunity to obtain mechanistic insights about the determinants of agronomically important polygenic traits.}, language = {en} } @article{FerrariProostJanowskietal.2019, author = {Ferrari, Camilla and Proost, Sebastian and Janowski, Marcin Andrzej and Becker, J{\"o}rg and Nikoloski, Zoran and Bhattacharya, Debashish and Price, Dana and Tohge, Takayuki and Bar-Even, Arren and Fernie, Alisdair R. and Stitt, Mark and Mutwil, Marek}, title = {Kingdom-wide comparison reveals the evolution of diurnal gene expression in Archaeplastida}, series = {Nature Communications}, volume = {10}, journal = {Nature Communications}, publisher = {Nature Publ. Group}, address = {London}, issn = {2041-1723}, doi = {10.1038/s41467-019-08703-2}, pages = {13}, year = {2019}, abstract = {Plants have adapted to the diurnal light-dark cycle by establishing elaborate transcriptional programs that coordinate many metabolic, physiological, and developmental responses to the external environment. These transcriptional programs have been studied in only a few species, and their function and conservation across algae and plants is currently unknown. We performed a comparative transcriptome analysis of the diurnal cycle of nine members of Archaeplastida, and we observed that, despite large phylogenetic distances and dramatic differences in morphology and lifestyle, diurnal transcriptional programs of these organisms are similar. Expression of genes related to cell division and the majority of biological pathways depends on the time of day in unicellular algae but we did not observe such patterns at the tissue level in multicellular land plants. Hence, our study provides evidence for the universality of diurnal gene expression and elucidates its evolutionary history among different photosynthetic eukaryotes.}, language = {en} } @article{LangaryNikoloski2019, author = {Langary, Damoun and Nikoloski, Zoran}, title = {Inference of chemical reaction networks based on concentration profiles using an optimization framework}, series = {Chaos : an interdisciplinary journal of nonlinear science}, volume = {29}, journal = {Chaos : an interdisciplinary journal of nonlinear science}, number = {11}, publisher = {American Institute of Physics}, address = {Melville}, issn = {1054-1500}, doi = {10.1063/1.5120598}, pages = {12}, year = {2019}, abstract = {Understanding the structure of reaction networks along with the underlying kinetics that lead to particular concentration readouts of the participating components is the first step toward optimization and control of (bio-)chemical processes. Yet, solutions to the problem of inferring the structure of reaction networks, i.e., characterizing the stoichiometry of the participating reactions provided concentration profiles of the participating components, remain elusive. Here, we present an approach to infer the stoichiometric subspace of a chemical reaction network from steady-state concentration data profiles obtained from a continuous isothermal reactor. The subsequent problem of finding reactions consistent with the observed subspace is cast as a series of mixed-integer linear programs whose solution generates potential reaction vectors together with a measure of their likelihood. We demonstrate the efficiency and applicability of the proposed approach using data obtained from synthetic reaction networks and from a well-established biological model for the Calvin-Benson cycle. Furthermore, we investigate the effect of missing information, in the form of unmeasured species or insufficient diversity within the data set, on the ability to accurately reconstruct the network reactions. The proposed framework is, in principle, applicable to many other reaction systems, thus providing future extensions to understanding reaction networks guiding chemical reactors and complex biological mixtures. (C) 2019 Author(s).}, language = {en} } @article{PandeyYuOmranianetal.2019, author = {Pandey, Prashant K. and Yu, Jing and Omranian, Nooshin and Alseekh, Saleh and Vaid, Neha and Fernie, Alisdair R. and Nikoloski, Zoran and Laitinen, Roosa A. E.}, title = {Plasticity in metabolism underpins local responses to nitrogen in Arabidopsis thaliana populations}, series = {Plant Direct}, volume = {3}, journal = {Plant Direct}, number = {11}, publisher = {John Wiley \& sonst LTD}, address = {Chichester}, issn = {2475-4455}, doi = {10.1002/pld3.186}, pages = {6}, year = {2019}, abstract = {Nitrogen (N) is central for plant growth, and metabolic plasticity can provide a strategy to respond to changing N availability. We showed that two local A. thaliana populations exhibited differential plasticity in the compounds of photorespiratory and starch degradation pathways in response to three N conditions. Association of metabolite levels with growth-related and fitness traits indicated that controlled plasticity in these pathways could contribute to local adaptation and play a role in plant evolution.}, language = {en} } @article{NunesNesiAlseekhdeOliveiraSilvaetal.2019, author = {Nunes-Nesi, Adriano and Alseekh, Saleh and de Oliveira Silva, Franklin Magnum and Omranian, Nooshin and Lichtenstein, Gabriel and Mirnezhad, Mohammad and Romero Gonzalez, Roman R. and Sabio y Garcia, Julia and Conte, Mariana and Leiss, Kirsten A. and Klinkhamer, Peter Gerardus Leonardus and Nikoloski, Zoran and Carrari, Fernando and Fernie, Alisdair R.}, title = {Identification and characterization of metabolite quantitative trait loci in tomato leaves and comparison with those reported for fruits and seeds}, series = {Metabolomics}, volume = {15}, journal = {Metabolomics}, number = {46}, publisher = {Springer}, address = {New York}, issn = {1573-3882}, doi = {10.1007/s11306-019-1503-8}, pages = {13}, year = {2019}, abstract = {IntroductionTo date, most studies of natural variation and metabolite quantitative trait loci (mQTL) in tomato have focused on fruit metabolism, leaving aside the identification of genomic regions involved in the regulation of leaf metabolism.ObjectiveThis study was conducted to identify leaf mQTL in tomato and to assess the association of leaf metabolites and physiological traits with the metabolite levels from other tissues.MethodsThe analysis of components of leaf metabolism was performed by phenotypying 76 tomato ILs with chromosome segments of the wild species Solanum pennellii in the genetic background of a cultivated tomato (S. lycopersicum) variety M82. The plants were cultivated in two different environments in independent years and samples were harvested from mature leaves of non-flowering plants at the middle of the light period. The non-targeted metabolite profiling was obtained by gas chromatography time-of-flight mass spectrometry (GC-TOF-MS). With the data set obtained in this study and already published metabolomics data from seed and fruit, we performed QTL mapping, heritability and correlation analyses.ResultsChanges in metabolite contents were evident in the ILs that are potentially important with respect to stress responses and plant physiology. By analyzing the obtained data, we identified 42 positive and 76 negative mQTL involved in carbon and nitrogen metabolism.ConclusionsOverall, these findings allowed the identification of S. lycopersicum genome regions involved in the regulation of leaf primary carbon and nitrogen metabolism, as well as the association of leaf metabolites with metabolites from seeds and fruits.}, language = {en} } @article{SmithDupontMcCarthyetal.2019, author = {Smith, Sarah R. and Dupont, Chris L. and McCarthy, James K. and Broddrick, Jared T. and Obornik, Miroslav and Horak, Ales and F{\"u}ssy, Zolt{\´a}n and Cihlar, Jaromir and Kleessen, Sabrina and Zheng, Hong and McCrow, John P. and Hixson, Kim K. and Araujo, Wagner L. and Nunes-Nesi, Adriano and Fernie, Alisdair R. and Nikoloski, Zoran and Palsson, Bernhard O. and Allen, Andrew E.}, title = {Evolution and regulation of nitrogen flux through compartmentalized metabolic networks in a marine diatom}, series = {Nature Communications}, volume = {10}, journal = {Nature Communications}, publisher = {Nature Publ. Group}, address = {London}, issn = {2041-1723}, doi = {10.1038/s41467-019-12407-y}, pages = {14}, year = {2019}, abstract = {Diatoms outcompete other phytoplankton for nitrate, yet little is known about the mechanisms underpinning this ability. Genomes and genome-enabled studies have shown that diatoms possess unique features of nitrogen metabolism however, the implications for nutrient utilization and growth are poorly understood. Using a combination of transcriptomics, proteomics, metabolomics, fluxomics, and flux balance analysis to examine short-term shifts in nitrogen utilization in the model pennate diatom in Phaeodactylum tricornutum, we obtained a systems-level understanding of assimilation and intracellular distribution of nitrogen. Chloroplasts and mitochondria are energetically integrated at the critical intersection of carbon and nitrogen metabolism in diatoms. Pathways involved in this integration are organelle-localized GS-GOGAT cycles, aspartate and alanine systems for amino moiety exchange, and a split-organelle arginine biosynthesis pathway that clarifies the role of the diatom urea cycle. This unique configuration allows diatoms to efficiently adjust to changing nitrogen status, conferring an ecological advantage over other phytoplankton taxa.}, language = {en} } @article{SongLiNowaketal.2019, author = {Song, Yu and Li, Gang and Nowak, Jacqueline and Zhang, Xiaoqing and Xu, Dongbei and Yang, Xiujuan and Huang, Guoqiang and Liang, Wanqi and Yang, Litao and Wang, Canhua and Bulone, Vincent and Nikoloski, Zoran and Hu, Jianping and Persson, Staffan and Zhang, Dabing}, title = {The Rice Actin-Binding Protein RMD Regulates Light-Dependent Shoot Gravitropism}, series = {Plant physiology : an international journal devoted to physiology, biochemistry, cellular and molecular biology, biophysics and environmental biology of plants}, volume = {181}, journal = {Plant physiology : an international journal devoted to physiology, biochemistry, cellular and molecular biology, biophysics and environmental biology of plants}, number = {2}, publisher = {American Society of Plant Physiologists}, address = {Rockville}, issn = {0032-0889}, doi = {10.1104/pp.19.00497}, pages = {630 -- 644}, year = {2019}, abstract = {Light and gravity are two key determinants in orientating plant stems for proper growth and development. The organization and dynamics of the actin cytoskeleton are essential for cell biology and critically regulated by actin-binding proteins. However, the role of actin cytoskeleton in shoot negative gravitropism remains controversial. In this work, we report that the actin-binding protein Rice Morphology Determinant (RMD) promotes reorganization of the actin cytoskeleton in rice (Oryza sativa) shoots. The changes in actin organization are associated with the ability of the rice shoots to respond to negative gravitropism. Here, light-grown rmd mutant shoots exhibited agravitropic phenotypes. By contrast, etiolated rmd shoots displayed normal negative shoot gravitropism. Furthermore, we show that RMD maintains an actin configuration that promotes statolith mobility in gravisensing endodermal cells, and for proper auxin distribution in light-grown, but not dark-grown, shoots. RMD gene expression is diurnally controlled and directly repressed by the phytochrome-interacting factor-like protein OsPIL16. Consequently, overexpression of OsPIL16 led to gravisensing and actin patterning defects that phenocopied the rmd mutant. Our findings outline a mechanism that links light signaling and gravity perception for straight shoot growth in rice.}, language = {en} }