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The ability of an organism to change its phenotype in response to different environments, termed plasticity, is a particularly important characteristic to enable sessile plants to adapt to rapid changes in their surroundings. Plasticity is a quantitative trait that can provide a fitness advantage and mitigate negative effects due to environmental perturbations. Yet, its genetic basis is not fully understood. Alongside technological limitations, the main challenge in studying plasticity has been the selection of suitable approaches for quantification of phenotypic plasticity. Here, we propose a categorization of the existing quantitative measures of phenotypic plasticity into nominal and relative approaches. Moreover, we highlight the recent advances in the understanding of the genetic architecture underlying phenotypic plasticity in plants. We identify four pillars for future research to uncover the genetic basis of phenotypic plasticity, with emphasis on development of computational approaches and theories. These developments will allow us to perform specific experiments to validate the causal genes for plasticity and to discover their role in plant fitness and evolution.
Terrestrial environmental systems are characterised by numerous feedback links between their different compartments. However, scientific research is organized into disciplines that focus on processes within the respective compartments rather than on interdisciplinary links. Major feedback mechanisms between compartments might therefore have been systematically overlooked so far. Without identifying these gaps, initiatives on future comprehensive environmental monitoring schemes and experimental platforms might fail. We performed a comprehensive overview of feedbacks between compartments currently represented in environmental sciences and explores to what degree missing links have already been acknowledged in the literature. We focused on process models as they can be regarded as repositories of scientific knowledge that compile findings of numerous single studies. In total, 118 simulation models from 23 model types were analysed. Missing processes linking different environmental compartments were identified based on a meta-review of 346 published reviews, model inter-comparison studies, and model descriptions. Eight disciplines of environmental sciences were considered and 396 linking processes were identified and ascribed to the physical, chemical or biological domain. There were significant differences between model types and scientific disciplines regarding implemented interdisciplinary links. The most wide-spread interdisciplinary links were between physical processes in meteorology, hydrology and soil science that drive or set the boundary conditions for other processes (e.g., ecological processes). In contrast, most chemical and biological processes were restricted to links within the same compartment. Integration of multiple environmental compartments and interdisciplinary knowledge was scarce in most model types. There was a strong bias of suggested future research foci and model extensions towards reinforcing existing interdisciplinary knowledge rather than to open up new interdisciplinary pathways. No clear pattern across disciplines exists with respect to suggested future research efforts. There is no evidence that environmental research would clearly converge towards more integrated approaches or towards an overarching environmental systems theory. (c) 2017 Elsevier B.V. All rights reserved.
Maize is the cereal crop with the highest production worldwide, and its oil is a key energy resource. Improving the quantity and quality of maize oil requires a better understanding of lipid metabolism. To predict the function of maize genes involved in lipid biosynthesis, we assembled transcriptomic and lipidomic data sets from leaves of B73 and the high-oil line By804 in two distinct time-series experiments. The integrative analysis based on high-dimensional regularized regression yielded lipid-transcript associations indirectly validated by Gene Ontology and promoter motif enrichment analyses. The co-localization of lipid-transcript associations using the genetic mapping of lipid traits in leaves and seedlings of a B73 x By804 recombinant inbred line population uncovered 323 genes involved in the metabolism of phospholipids, galactolipids, sulfolipids and glycerolipids. The resulting association network further supported the involvement of 50 gene candidates in modulating levels of representatives from multiple acyl-lipid classes. Therefore, the proposed approach provides high-confidence candidates for experimental testing in maize and model plant species.
Metabolism is a key determinant of plant growth and modulates plant adaptive responses. Increased metabolic variation due to heterozygosity may be beneficial for highly homozygous plants if their progeny is to respond to sudden changes in the habitat. Here, we investigate the extent to which heterozygosity contributes to the variation in metabolism and size of hybrids of Arabidopsis thaliana whose parents are from a single growth habitat. We created full diallel crosses among seven parents, originating from Southern Germany, and analysed the inheritance patterns in primary and secondary metabolism as well as in rosette size in situ. In comparison to primary metabolites, compounds from secondary metabolism were more variable and showed more pronounced non-additive inheritance patterns which could be attributed to epistasis. In addition, we showed that glucosinolates, among other secondary metabolites, were positively correlated with a proxy for plant size. Therefore, our study demonstrates that heterozygosity in local A. thaliana population generates metabolic variation and may impact several tasks directly linked to metabolism.
The availability of high-throughput data from transcriptomics and metabolomics technologies provides the opportunity to characterize the transcriptional effects on metabolism. Here we propose and evaluate two computational approaches rooted in data reduction techniques to identify and categorize transcriptional effects on metabolism by combining data on gene expression and metabolite levels. The approaches determine the partial correlation between two metabolite data profiles upon control of given principal components extracted from transcriptomics data profiles. Therefore, they allow us to investigate both data types with all features simultaneously without doing preselection of genes. The proposed approaches allow us to categorize the relation between pairs of metabolites as being under transcriptional or post-transcriptional regulation. The resulting classification is compared to existing literature and accumulated evidence about regulatory mechanism of reactions and pathways in the cases of Escherichia coil, Saccharomycies cerevisiae, and Arabidopsis thaliana.
Bridging metabolomics with plant phenotypic responses is challenging. Multivariate analyses account for the existing dependencies among metabolites, and regression models in particular capture such dependencies in search for association with a given trait. However, special care should be undertaken with metabolomics data. Here we propose a modeling workflow that considers all caveats imposed by such large data sets.
Cells and organelles are not homogeneous but include microcompartments that alter the spatiotemporal characteristics of cellular processes. The effects of microcompartmentation on metabolic pathways are however difficult to study experimentally. The pyrenoid is a microcompartment that is essential for a carbon concentrating mechanism (CCM) that improves the photosynthetic performance of eukaryotic algae. Using Chlamydomonas reinhardtii, we obtained experimental data on photosynthesis, metabolites, and proteins in CCM-induced and CCM-suppressed cells. We then employed a computational strategy to estimate how fluxes through the Calvin-Benson cycle are compartmented between the pyrenoid and the stroma. Our model predicts that ribulose-1,5-bisphosphate (RuBP), the substrate of Rubisco, and 3-phosphoglycerate (3PGA), its product, diffuse in and out of the pyrenoid, respectively, with higher fluxes in CCM-induced cells. It also indicates that there is no major diffusional barrier to metabolic flux between the pyrenoid and stroma. Our computational approach represents a stepping stone to understanding microcompartmentalized CCM in other organisms.
Plant organs consist of multiple cell types that do not operate in isolation, but communicate with each other to maintain proper functions. Here, we extract models specific to three developmental stages of eight root cell types or tissue layers in Arabidopsis thaliana based on a state-of-the-art constraint-based modeling approach with all publicly available transcriptomics and metabolomics data from this system to date. We integrate these models into a multi-cell root model which we investigate with respect to network structure, distribution of fluxes, and concordance to transcriptomics and proteomics data. From a methodological point, we show that the coupling of tissue-specific models in a multi-tissue model yields a higher specificity of the interconnected models with respect to network structure and flux distributions. We use the extracted models to predict and investigate the flux of the growth hormone indole-3-actetate and its antagonist, trans-Zeatin, through the root. While some of predictions are in line with experimental evidence, constraints other than those coming from the metabolic level may be necessary to replicate the flow of indole-3-actetate from other simulation studies. Therefore, our work provides the means for data-driven multi-tissue metabolic model extraction of other Arabidopsis organs in the constraint-based modeling framework.
Methodological and technological advances have recently paved the way for metabolic flux profiling in higher organisms, like plants. However, in comparison with omics technologies, flux profiling has yet to provide comprehensive differential flux maps at a genome-scale and in different cell types, tissues, and organs. Here we highlight the recent advances in technologies to gather metabolic labeling patterns and flux profiling approaches. We provide an opinion of how recent local flux profiling approaches can be used in conjunction with the constraint-based modeling framework to arrive at genome-scale flux maps. In addition, we point at approaches which use metabolomics data without introduction of label to predict either non-steady state fluxes in a time-series experiment or flux changes in different experimental scenarios. The combination of these developments allows an experimentally feasible approach for flux-based large-scale systems biology studies.
Scenarios have become a key tool for supporting sustainability research on regional and global change. In this study we evaluate four regional scenario assessments: first, to explore a number of research challenges related to sustainability science and, second, to contribute to sustainability research in the specific case studies. The four case studies used commonly applied scenario approaches that are (i) a story and simulation approach with stakeholder participation in the Oum Zessar watershed, Tunisia, (ii) a participatory scenario exploration in the Rwenzori region, Uganda, (iii) a model-based prepolicy study in the Inner Niger Delta, Mali, and (iv) a model coupling-based scenario analysis in upper Thukela basin, South Africa. The scenario assessments are evaluated against a set of known challenges in sustainability science, with each challenge represented by two indicators, complemented by a survey carried out on the perception of the scenario assessments within the case study regions. The results show that all types of scenario assessments address many sustainability challenges, but that the more complex ones based on story and simulation and model coupling are the most comprehensive. The study highlights the need to investigate abrupt system changes as well as governmental and political factors as important sources of uncertainty. For an in-depth analysis of these issues, the use of qualitative approaches and an active engagement of local stakeholders are suggested. Studying ecological thresholds for the regional scale is recommended to support research on regional sustainability. The evaluation of the scenario processes and outcomes by local researchers indicates the most transparent scenario assessments as the most useful. Focused, straightforward, yet iterative scenario assessments can be very relevant by contributing information to selected sustainability problems.
Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated‐Gaussian reference function [AKDE], Silverman's rule of thumb, and least squares cross‐validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half‐sample cross‐validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation ( N̂ area
) to quantify the information content of each data set. We found that AKDE 95% area estimates were larger than conventional IID‐based estimates by a mean factor of 2. The median number of cross‐validated locations included in the hold‐out sets by AKDE 95% (or 50%) estimates was 95.3% (or 50.1%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing N̂ area. To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animal's movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small N̂ area. While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an N̂ area >1,000, where 30% had an N̂ area <30. In this frequently encountered scenario of small N̂ area, AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.
Moving in the Anthropocene
(2018)
Animal movement is fundamental for ecosystem functioning and species survival, yet the effects of the anthropogenic footprint on animal movements have not been estimated across species. Using a unique GPS-tracking database of 803 individuals across 57 species, we found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in areas with a low human footprint. We attribute this reduction to behavioral changes of individual animals and to the exclusion of species with long-range movements from areas with higher human impact. Global loss of vagility alters a key ecological trait of animals that affects not only population persistence but also ecosystem processes such as predator-prey interactions, nutrient cycling, and disease transmission.
Manganese (Mn) is an essential nutrient for intracellular activities; it functions as a cofactor for a variety of enzymes, including arginase, glutamine synthetase (GS), pyruvate carboxylase and Mn superoxide dismutase (Mn-SOD). Through these metalloproteins, Mn plays critically important roles in development, digestion, reproduction, antioxidant defense, energy production, immune response and regulation of neuronal activities. Mn deficiency is rare. In contrast Mn poisoning may be encountered upon overexposure to this metal. Excessive Mn tends to accumulate in the liver, pancreas, bone, kidney and brain, with the latter being the major target of Mn intoxication. Hepatic cirrhosis, polycythemia, hypermanganesemia, dystonia and Parkinsonism-like symptoms have been reported in patients with Mn poisoning. In recent years, Mn has come to the forefront of environmental concerns due to its neurotoxicity. Molecular mechanisms of Mn toxicity include oxidative stress, mitochondrial dysfunction, protein misfolding, endoplasmic reticulum (ER) stress, autophagy dysregulation, apoptosis, and disruption of other metal homeostasis. The mechanisms of Mn homeostasis are not fully understood. Here, we will address recent progress in Mn absorption, distribution and elimination across different tissues, as well as the intracellular regulation of Mn homeostasis in cells. We will conclude with recommendations for future research areas on Mn metabolism.
Arctic treelines are facing a strong temperature increase as a result of recent global warming, causing possible changes in forest extent, which will alter vegetation-climate feedbacks. However, the mode and strength of the response is rather unclear, as potential changes are happening in areas that are very remote and difficult to access, and empirical data are still largely lacking. Here, we assessed the current population structure and genetic differentiation of Larix Mill. tree stands within the northernmost latitudinal treeline reaching ~ 72° N in the southern lowlands of the Taymyr Peninsula (~ 100° E). We sampled 743 individuals belonging to different height classes (seedlings, saplings, trees) at 11 locations along a gradient from ‘single tree’ tundra over ‘forest line’ to ‘dense forest’ stands and conducted investigations applying eight highly polymorphic nuclear microsatellites. Results suggest a high diversity within sub-populations (HE = 0.826–0.893), coupled, however, with heterozygote deficits in all sub-populations, but pronounced in ‘forest line’ stands. Overall, genetic differentiation of sub-populations is low (FST = 0.005), indicating a region-wide high gene flow, although ‘forest line’ stands harbour few rare and private alleles, likely indicating greater local reproduction. ‘Single tree’ stands, located beyond the northern forest line, are currently not involved in treeline expansion, but show signs of a long-term refuge, namely asexual reproduction and change of growth-form from erect to creeping growth, possibly having persisted for thousands of years. The lack of differentiation between the sub-populations points to a sufficiently high dispersal potential, and thus a rapid northward migration of the Siberian arctic treeline under recent global warming seems potentially unconstrained, but observations show it to be unexpectedly slow.
Changes in species’ distributions are classically projected based on their climate envelopes. For Siberian forests, which have a tremendous significance for vegetation-climate feedbacks, this implies future shifts of each of the forest-forming larch (Larix) species to the north-east. However, in addition to abiotic factors, reliable projections must assess the role of historical biogeography and biotic interactions. Here, we use sedimentary ancient DNA and individual-based modelling to investigate the distribution of larch species and mitochondrial haplotypes through space and time across the treeline ecotone on the southern Taymyr peninsula, which at the same time presents a boundary area of two larch species. We find spatial and temporal patterns, which suggest that forest density is the most influential driver determining the precise distribution of species and mitochondrial haplotypes. This suggests a strong influence of competition on the species’ range shifts. These findings imply possible climate change outcomes that are directly opposed to projections based purely on climate envelopes. Investigations of such fine-scale processes of biodiversity change through time are possible using paleoenvironmental DNA, which is available much more readily than visible fossils and can provide information at a level of resolution that is not reached in classical palaeoecology.
Understanding interrelations between an environment's hydrological past and its current biogeochemistry is necessary for the assessment of biogeochemical and microbial responses to changing hydrological conditions. The question how previous dry-wet events determine the contemporary microbial and biogeochemical state is addressed in this study. Therefore, sediments exposed to the atmosphere of areas with a different hydrological past within one kettle hole, i.e. (1) the predominantly inundated pond center, (2) the pond margin frequently desiccated for longer periods and (3) an intermediate zone, were incubated with the same rewetting treatment. Physicochemical and textural characteristics were related to structural microbial parameters regarding carbon and nitrogen turnover, i.e. abundance of bacteria and fungi, denitrifiers (targeted by the nirK und nirS functional genes) and nitrate ammonifiers (targeted by the nrfA functional gene). Our study reveals that, in combination with varying sediment texture, the hydrological history creates distinct microbial habitats with defined boundary conditions within the kettle hole, mainly driven by redox conditions, pH and organic matter (OM) composition. OM mineralization, as indicated by CO2-outgassing, was most efficient in exposed sediments with a less stable hydrological past. The potential for nitrogen retention via nitrate ammonification was highest in the hydrologically rather stable pond center, counteracting nitrogen loss due to denitrification. Therefore, the degree of hydrological stability is an important factor leaving a microbial and biogeochemical legacy, which determines carbon and nitrogen losses from small lentic freshwater systems in the long term run.
Chytrids are zoosporic fungi that play an important, but yet understudied, ecological role in aquatic ecosystems. Many chytrid species have been morphologically described as parasites on phytoplankton. However, the majority of them have rarely been isolated and lack DNA sequence data. In this study we isolated and cultivated three parasitic chytrids, infecting a common volvocacean host species, Yamagishiella unicocca. To identify the chytrids, we characterized morphology and life cycle, and analyzed phylogenetic relationships based on 18S and 28S rDNA genes. Host range and specificity of the chytrids was determined by cross-infection assays with host strains, characterized by rbcL and ITS markers. We were able to confirm the identity of two chytrid strains as Endocoenobium eudorinae Ingold and Dangeardia mamillata Schroder and described the third chytrid strain as Algomyces stechlinensis gen. et sp. nov. The three chytrids were assigned to novel and phylogenetically distant clades within the phylum Chytridiomycota, each exhibiting different host specificities. By integrating morphological and molecular data of both the parasitic chytrids and their respective host species, we unveiled cryptic host-parasite associations. This study highlights that a high prevalence of (pseudo)cryptic diversity requires molecular characterization of both phytoplankton host and parasitic chytrid to accurately identify and compare host range and specificity, and to study phytoplankton-chytrid interactions in general.
Insight into how environmental change determines the production and distribution of cyanobacterial toxins is necessary for risk assessment. Management guidelines currently focus on hepatotoxins (microcystins). Increasing attention is given to other classes, such as neurotoxins (e.g., anatoxin-a) and cytotoxins (e.g., cylindrospermopsin) due to their potency. Most studies examine the relationship between individual toxin variants and environmental factors, such as nutrients, temperature and light. In summer 2015, we collected samples across Europe to investigate the effect of nutrient and temperature gradients on the variability of toxin production at a continental scale. Direct and indirect effects of temperature were the main drivers of the spatial distribution in the toxins produced by the cyanobacterial community, the toxin concentrations and toxin quota. Generalized linear models showed that a Toxin Diversity Index (TDI) increased with latitude, while it decreased with water stability. Increases in TDI were explained through a significant increase in toxin variants such as MC-YR, anatoxin and cylindrospermopsin, accompanied by a decreasing presence of MC-LR. While global warming continues, the direct and indirect effects of increased lake temperatures will drive changes in the distribution of cyanobacterial toxins in Europe, potentially promoting selection of a few highly toxic species or strains.
Under ongoing climate change and increasing anthropogenic activity, which continuously challenge ecosystem resilience, an in-depth understanding of ecological processes is urgently needed. Lakes, as providers of numerous ecosystem services, face multiple stressors that threaten their functioning. Harmful cyanobacterial blooms are a persistent problem resulting from nutrient pollution and climate-change induced stressors, like poor transparency, increased water temperature and enhanced stratification. Consistency in data collection and analysis methods is necessary to achieve fully comparable datasets and for statistical validity, avoiding issues linked to disparate data sources. The European Multi Lake Survey (EMLS) in summer 2015 was an initiative among scientists from 27 countries to collect and analyse lake physical, chemical and biological variables in a fully standardized manner. This database includes in-situ lake variables along with nutrient, pigment and cyanotoxin data of 369 lakes in Europe, which were centrally analysed in dedicated laboratories. Publishing the EMLS methods and dataset might inspire similar initiatives to study across large geographic areas that will contribute to better understanding lake responses in a changing environment.
1. Global pressures on freshwater ecosystems are high and rising. Viewed primarily as a resource for humans, current practices of water use have led to catastrophic declines in freshwater species and the degradation of freshwater ecosystems, including their genetic and functional diversity. Approximately three-quarters of the world's inland wetlands have been lost, one-third of the 28 000 freshwater species assessed for the International Union for Conservation of Nature (IUCN) Red List are threatened with extinction, and freshwater vertebrate populations are undergoing declines that are more rapid than those of terrestrial and marine species. This global loss continues unchecked, despite the importance of freshwater ecosystems as a source of clean water, food, livelihoods, recreation, and inspiration.
2. The causes of these declines include hydrological alterations, habitat degradation and loss, overexploitation, invasive species, pollution, and the multiple impacts of climate change. Although there are policy initiatives that aim to protect freshwater life, these are rarely implemented with sufficient conviction and enforcement. Policies that focus on the development and management of fresh waters as a resource for people almost universally neglect the biodiversity that they contain.
3. Here we introduce the Alliance for Freshwater Life, a global initiative, uniting specialists in research, data synthesis, conservation, education and outreach, and policymaking. This expert network aims to provide the critical mass required for the effective representation of freshwater biodiversity at policy meetings, to develop solutions balancing the needs of development and conservation, and to better convey the important role freshwater ecosystems play in human well-being. Through this united effort we hope to reverse this tide of loss and decline in freshwater biodiversity. We introduce several short- and medium-term actions as examples for making positive change, and invite individuals, organizations, authorities, and governments to join the Alliance for Freshwater Life.
Insight into how environmental change determines the production and distribution of cyanobacterial toxins is necessary for risk assessment. Management guidelines currently focus on hepatotoxins (microcystins). Increasing attention is given to other classes, such as neurotoxins (e.g., anatoxin-a) and cytotoxins (e.g., cylindrospermopsin) due to their potency. Most studies examine the relationship between individual toxin variants and environmental factors, such as nutrients, temperature and light. In summer 2015, we collected samples across Europe to investigate the effect of nutrient and temperature gradients on the variability of toxin production at a continental scale. Direct and indirect effects of temperature were the main drivers of the spatial distribution in the toxins produced by the cyanobacterial community, the toxin concentrations and toxin quota. Generalized linear models showed that a Toxin Diversity Index (TDI) increased with latitude, while it decreased with water stability. Increases in TDI were explained through a significant increase in toxin variants such as MC-YR, anatoxin and cylindrospermopsin, accompanied by a decreasing presence of MC-LR. While global warming continues, the direct and indirect effects of increased lake temperatures will drive changes in the distribution of cyanobacterial toxins in Europe, potentially promoting selection of a few highly toxic species or strains.
The continuously increasing pollution of aquatic environments with microplastics (plastic particles < 5 mm) is a global problem with potential implications for organisms of all trophic levels. For microorganisms, trillions of these floating microplastics particles represent a huge surface area for colonization. Due to the very low biodegradability, microplastics remain years to centuries in the environment and can be transported over thousands of kilometers together with the attached organisms. Since also pathogenic, invasive, or otherwise harmful species could be spread this way, it is essential to study microplastics-associated communities.
For this doctoral thesis, eukaryotic communities were analyzed for the first time on microplastics in brackish environments and compared to communities in the surrounding water and on the natural substrate wood. With Illumina MiSeq high-throughput sequencing, more than 500 different eukaryotic taxa were detected on the microplastics samples. Among them were various green algae, dinoflagellates, ciliates, fungi, fungal-like protists and small metazoans such as nematodes and rotifers. The most abundant organisms was a dinoflagellate of the genus Pfiesteria, which could include fish pathogenic and bloom forming toxigenic species. Network analyses revealed that there were numerous interaction possibilities among prokaryotes and eukaryotes in microplastics biofilms. Eukaryotic community compositions on microplastics differed significantly from those on wood and in water, and compositions were additionally distinct among the sampling locations. Furthermore, the biodiversity was clearly lower on microplastics in comparison to the diversity on wood or in the surrounding water.
In another experiment, a situation was simulated in which treated wastewater containing microplastics was introduced into a freshwater lake. With increasing microplastics concentrations, the resulting bacterial communities became more similar to those from the treated wastewater. Moreover, the abundance of integrase I increased together with rising concentrations of microplastics. Integrase I is often used as a marker for anthropogenic environmental pollution and is further linked to genes conferring, e.g., antibiotic resistance.
This dissertation gives detailed insights into the complexity of prokaryotic and eukaryotic communities on microplastics in brackish and freshwater systems. Even though microplastics provide novel microhabitats for various microbes, they might also transport toxigenic, pathogenic, antibiotic-resistant or parasitic organisms; meaning their colonization can pose potential threats to humans and the environment. Finally, this thesis explains the urgent need for more research as well as for strategies to minimize the global microplastic pollution.
Plastic pollution is ubiquitous on the planet since several millions of tons of plastic waste enter aquatic ecosystems each year. Furthermore, the amount of plastic produced is expected to increase exponentially shortly. The heterogeneity of materials, additives and physical characteristics of plastics are typical of these emerging contaminants and affect their environmental fate in marine and freshwaters. Consequently, plastics can be found in the water column, sediments or littoral habitats of all aquatic ecosystems. Most of this plastic debris will fragment as a product of physical, chemical and biological forces, producing particles of small size. These particles (< 5mm) are known as “microplastics” (MP). Given their high surface-to-volume ratio, MP stimulate biofouling and the formation of biofilms in aquatic systems.
As a result of their unique structure and composition, the microbial communities in MP biofilms are referred to as the “Plastisphere.” While there is increasing data regarding the distinctive composition and structure of the microbial communities that form part of the plastisphere, scarce information exists regarding the activity of microorganisms in MP biofilms. This surface-attached lifestyle is often associated with the increase in horizontal gene transfer (HGT) among bacteria. Therefore, this type of microbial activity represents a relevant function worth to be analyzed in MP biofilms. The horizontal exchange of mobile genetic elements (MGEs) is an essential feature of bacteria. It accounts for the rapid evolution of these prokaryotes and their adaptation to a wide variety of environments. The process of HGT is also crucial for spreading antibiotic resistance and for the evolution of pathogens, as many MGEs are known to contain antibiotic resistance genes (ARGs) and genetic determinants of pathogenicity.
In general, the research presented in this Ph.D. thesis focuses on the analysis of HGT and heterotrophic activity in MP biofilms in aquatic ecosystems. The primary objective was to analyze the potential of gene exchange between MP bacterial communities vs. that of the surrounding water, including bacteria from natural aggregates. Moreover, the thesis addressed the potential of MP biofilms for the proliferation of biohazardous bacteria and MGEs from wastewater treatment plants (WWTPs) and associated with antibiotic resistance. Finally, it seeks to prove if the physiological profile of MP biofilms under different limnological conditions is divergent from that of the water communities. Accordingly, the thesis is composed of three independent studies published in peer-reviewed journals. The two laboratory studies were performed using both model and environmental microbial communities. In the field experiment, natural communities from freshwater ecosystems were examined.
In Chapter I, the inflow of treated wastewater into a temperate lake was simulated with a concentration gradient of MP particles. The effects of MP on the microbial community structure and the occurrence of integrase 1 (int 1) were followed. The int 1 is a marker associated with mobile genetic elements and known as a proxy for anthropogenic effects on the spread of antimicrobial resistance genes. During the experiment, the abundance of int1 increased in the plastisphere with increasing MP particle concentration, but not in the surrounding water. In addition, the microbial community on MP was more similar to the original wastewater community with increasing microplastic concentrations. Our results show that microplastic particles indeed promote persistence of standard indicators of microbial anthropogenic pollution in natural waters.
In Chapter II, the experiments aimed to compare the permissiveness of aquatic bacteria towards model antibiotic resistance plasmid pKJK5, between communities that form biofilms on MP vs. those that are free-living. The frequency of plasmid transfer in bacteria associated with MP was higher when compared to bacteria that are free-living or in natural aggregates. Moreover, comparison increased gene exchange occurred in a broad range of phylogenetically-diverse bacteria. The results indicate a different activity of HGT in MP biofilms, which could affect the ecology of aquatic microbial communities on a global scale and the spread of antibiotic resistance.
Finally, in Chapter III, physiological measurements were performed to assess whether microorganisms on MP had a different functional diversity from those in water. General heterotrophic activity such as oxygen consumption was compared in microcosm assays with and without MP, while diversity and richness of heterotrophic activities were calculated by using Biolog® EcoPlates. Three lakes with different nutrient statuses presented differences in MP-associated biomass build up. Functional diversity profiles of MP biofilms in all lakes differed from those of the communities in the surrounding water, but only in the oligo-mesotrophic lake MP biofilms had a higher functional richness compared to the ambient water. The results support that MP surfaces act as new niches for aquatic microorganisms and can affect global carbon dynamics of pelagic environments.
Overall, the experimental works presented in Chapters I and II support a scenario where MP pollution affects HGT dynamics among aquatic bacteria. Among the consequences of this alteration is an increase in the mobilization and transfer efficiency of ARGs. Moreover, it supposes that changes in HGT can affect the evolution of bacteria and the processing of organic matter, leading to different catabolic profiles such as demonstrated in Chapter III. The results are discussed in the context of the fate and magnitude of plastic pollution and the importance of HGT for bacterial evolution and the microbial loop, i.e., at the base of aquatic food webs. The thesis supports a relevant role of MP biofilm communities for the changes observed in the aquatic microbiome as a product of intense human intervention.
Microbial processing of organic matter (OM) in the freshwater biosphere is a key component of global biogeochemical cycles. Freshwaters receive and process valuable amounts of leaf OM from their terrestrial landscape. These terrestrial subsidies provide an essential source of energy and nutrients to the aquatic environment as a function of heterotrophic processing by fungi and bacteria. Particularly in freshwaters with low in-situ primary production from algae (microalgae, cyanobacteria), microbial turnover of leaf OM significantly contributes to the productivity and functioning of freshwater ecosystems and not least their contribution to global carbon cycling.
Based on differences in their chemical composition, it is believed that leaf OM is less bioavailable to microbial heterotrophs than OM photosynthetically produced by algae. Especially particulate leaf OM, consisting predominantly of structurally complex and aromatic polymers, is assumed highly resistant to enzymatic breakdown by microbial heterotrophs. However, recent research has demonstrated that OM produced by algae promotes the heterotrophic breakdown of leaf OM in aquatic ecosystems, with profound consequences for the metabolism of leaf carbon (C) within microbial food webs. In my thesis, I aimed at investigating the underlying mechanisms of this so called priming effect of algal OM on the use of leaf C in natural microbial communities, focusing on fungi and bacteria.
The works of my thesis underline that algal OM provides highly bioavailable compounds to the microbial community that are quickly assimilated by bacteria (Paper II). The substrate composition of OM pools determines the proportion of fungi and bacteria within the microbial community (Paper I). Thereby, the fraction of algae OM in the aquatic OM pool stimulates the activity and hence contribution of bacterial communities to leaf C turnover by providing an essential energy and nutrient source for the assimilation of the structural complex leaf OM substrate. On the contrary, the assimilation of algal OM remains limited for fungal communities as a function of nutrient competition between fungi and bacteria (Paper I, II). In addition, results provide evidence that environmental conditions determine the strength of interactions between microalgae and heterotrophic bacteria during leaf OM decomposition (Paper I, III). However, the stimulatory effect of algal photoautotrophic activities on leaf C turnover remained significant even under highly dynamic environmental conditions, highlighting their functional role for ecosystem processes (Paper III).
The results of my thesis provide insights into the mechanisms by which algae affect the microbial turnover of leaf C in freshwaters. This in turn contributes to a better understanding of the function of algae in freshwater biogeochemical cycles, especially with regard to their interaction with the heterotrophic community.
Changes in species' distributions are classically projected based on their climate envelopes. For Siberian forests, which have a tremendous significance for vegetation-climate feedbacks, this implies future shifts of each of the forest-forming larch (Larix) species to the north-east. However, in addition to abiotic factors, reliable projections must assess the role of historical biogeography and biotic interactions. Here, we use sedimentary ancient DNA and individual-based modelling to investigate the distribution of larch species and mitochondrial haplotypes through space and time across the treeline ecotone on the southern Taymyr peninsula, which at the same time presents a boundary area of two larch species. We find spatial and temporal patterns, which suggest that forest density is the most influential driver determining the precise distribution of species and mitochondrial haplotypes. This suggests a strong influence of competition on the species' range shifts. These findings imply possible climate change outcomes that are directly opposed to projections based purely on climate envelopes. Investigations of such fine-scale processes of biodiversity change through time are possible using paleoenvironmental DNA, which is available much more readily than visible fossils and can provide information at a level of resolution that is not reached in classical palaeoecology.