Genome-resolved metagenomics reveals the effect of nutrient availability on bacterial genomic properties across 44 European freshwater lakes.

Understanding intricate microbial interactions in the environment is crucial. This is especially true for the relationships between nutrients and bacteria, as phosphorus, nitrogen and organic carbon availability are known to influence bacterial population dynamics. It has been suggested that low nutrient conditions prompt the evolutionary process of genome streamlining. This process helps conserve scarce nutrients and allows for proliferation. Genome streamlining is associated with genomic properties such as %GC content, genes encoding sigma factors, percent coding regions, gene redundancy, and functional shifts in processes like cell motility and ATP binding cassette transporters, among others. The current study aims to unveil the impact of nutrition on the genome size, %GC content, and functional properties of pelagic freshwater bacteria. We do this at finer taxonomic resolutions for many metagenomically characterized communities. Our study confirms the interplay of trophic level and genomic properties. It also highlights that different nutrient types, particularly phosphorus and nitrogen, impact these properties differently. We observed a covariation of functional traits with genome size. Larger genomes exhibit enriched pathways for motility, environmental interaction, and regulatory genes. ABC transporter genes reflect the availability of nutrients in the environment, with small genomes presumably relying more on metabolites from other organisms. We also discuss the distinct strategies different phyla adopt to adapt to oligotrophic environments. The findings contribute to our understanding of genomic adaptations within complex microbial communities.

Exploring the efficacy of metabarcoding and non-target screening for detecting treated wastewater.

Wastewater treatment processes can eliminate many pollutants, yet remainder pollutants contain organic compounds and microorganisms released into ecosystems. These remainder pollutants have the potential to adversely impact downstream ecosystem processes, but their presence is currently not being monitored. This study was set out with the aim of investigating the effectiveness and sensitivity of non-target screening of chemical compounds, 18S V9 rRNA gene, and full-length 16S rRNA gene metabarcoding techniques for detecting treated wastewater in receiving waters. We aimed at assessing the impact of introducing 33 % treated wastewater into a triplicated large-scale mesocosm setup during a 10-day exposure period. Discharge of treated wastewater significantly altered the chemical signature as well as the microeukaryotic and prokaryotic diversity of the mesocosms. Non-target screening, 18S V9 rRNA gene, and full-length 16S rRNA gene metabarcoding detected these changes with significant covariation of the detected pattern between methods. The 18S V9 rRNA gene metabarcoding exhibited superior sensitivity immediately following the introduction of treated wastewater and remained one of the top-performing methods throughout the study. Full-length 16S rRNA gene metabarcoding demonstrated sensitivity only in the initial hour, but became insignificant thereafter. The non-target screening approach was effective throughout the experiment and in contrast to the metabarcoding methods the signal to noise ratio remained similar during the experiment resulting in an increasing relative strength of this method. Based on our findings, we conclude that all methods employed for monitoring environmental disturbances from various sources are suitable. The distinguishing factor of these methods is their ability to detect unknown pollutants and organisms, which sets them apart from previously utilized approaches and allows for a more comprehensive perspective. Given their diverse strengths, particularly in terms of temporal resolution, these methods are best suited as complementary approaches.

Temporal disturbance of a model stream ecosystem by high microbial diversity from treated wastewater.

Microbial communities in freshwater streams play an essential role in ecosystem functioning via biogeochemical cycling. Yet, the impacts of treated wastewater influx into stream ecosystems on microbial strain diversity remain mostly unexplored. Here, we coupled full-length 16S ribosomal RNA gene Nanopore sequencing and strain-resolved metagenomics to investigate the impact of treated wastewater on a mesocosm system (AquaFlow) run with restored river water. Over 10 days, community Bray-Curtis dissimilarities between treated and control mesocosm decreased (0.57 ± 0.058 to 0.26 ± 0.046) based on ribosomal protein S3 gene clustering, finally converging to nearly identical communities. Similarly, strain-resolved metagenomics revealed a high diversity of bacteria and viruses after the introduction of treated wastewater; these microbes also decreased over time resulting in the same strain clusters in control and treatment at the end of the experiment. Specifically, 39.2% of viral strains detected in all samples were present after the introduction of treated wastewater only. Although bacteria present at low abundance in the treated wastewater introduced additional antibiotic resistance genes, signals of naturally occurring ARG-encoding organisms resembled the resistome at the endpoint. Our results suggest that the previously stressed freshwater stream and its microbial community are resilient to a substantial introduction of treated wastewater.

The Asymmetric Response Concept explains ecological consequences of multiple stressor exposure and release.

Our capacity to predict trajectories of ecosystem degradation and recovery is limited, especially when impairments are caused by multiple stressors. Recovery may be fast or slow and either complete or partial, sometimes result in novel ecosystem states or even fail completely. Here, we introduce the Asymmetric Response Concept (ARC) that provides a basis for exploring and predicting the pace and magnitude of ecological responses to, and release from, multiple stressors. The ARC holds that three key mechanisms govern population, community and ecosystem trajectories. Stress tolerance is the main mechanism determining responses to increasing stressor intensity, whereas dispersal and biotic interactions predominantly govern responses to the release from stressors. The shifting importance of these mechanisms creates asymmetries between the ecological trajectories that follow increasing and decreasing stressor intensities. This recognition helps to understand multiple stressor impacts and to predict which measures will restore communities that are resistant to restoration.

Paramecium epigenetics in development and proliferation.

The term epigenetics is used for any layer of genetic information aside from the DNA base-sequence information. Mammalian epigenetic research increased our understanding of chromatin dynamics in terms of cytosine methylation and histone modification during differentiation, aging, and disease. Instead, ciliate epigenetics focused more on small RNA-mediated effects. On the one hand, these do concern the transport of RNA from parental to daughter nuclei, representing a regulated transfer of epigenetic information across generations. On the other hand, studies of Paramecium, Tetrahymena, Oxytricha, and Stylonychia revealed an almost unique function of transgenerational RNA. Rather than solely controlling chromatin dynamics, they control sexual progeny's DNA content quantitatively and qualitatively. Thus epigenetics seems to control genetics, at least genetics of the vegetative macronucleus. This combination offers ciliates, in particular, an epigenetically controlled genetic variability. This review summarizes the epigenetic mechanisms that contribute to macronuclear heterogeneity and relates these to nuclear dimorphism. This system's adaptive and evolutionary possibilities raise the critical question of whether such a system is limited to unicellular organisms or binuclear cells. We discuss here the relevance of ciliate genetics and epigenetics to multicellular organisms.

The relationship between land cover and microbial community composition in European lakes.

Microbes are essential for element cycling and ecosystem functioning. However, many questions central to understanding the role of microbes in ecology are still open. Here, we analyze the relationship between lake microbiomes and the lakes' land cover. By applying machine learning methods, we quantify the covariance between land cover categories and the microbial community composition recorded in the largest amplicon sequencing dataset of European lakes available to date. Our results show that the aggregation of environmental features or microbial taxa before analysis can obscure ecologically relevant patterns. We observe a comparatively high covariation of the lakes' microbial community with herbaceous and open spaces surrounding the lake; nevertheless, the microbial covariation with land cover categories is generally lower than the covariation with physico-chemical parameters. Combining land cover and physico-chemical bioindicators identified from the same amplicon sequencing dataset, we develop analytical data structures that facilitate insights into the ecology of the lake microbiome. Among these, a list of the environmental parameters sorted by the number of microbial bioindicators we have identified for them points towards apparent environmental drivers of the lake microbial community composition, such as the altitude, conductivity, and area covered herbaceous vegetation surrounding the lake. Furthermore, the response map, a similarity matrix calculated from the Jaccard similarity of the environmental parameters' lists of bioindicators, allows us to study the ecosystem's structure from the standpoint of the microbiome. More specifically, we identify multiple clusters of highly similar and possibly functionally linked ecological parameters, including one that highlights the importance of the calcium-bicarbonate equilibrium for lake ecology. Taken together, we demonstrate the use of machine learning approaches in studying the interplay between microbial diversity and environmental factors and introduce novel approaches to integrate environmental molecular diversity into monitoring and water quality assessments.

Patterns of protist distribution and diversification in alpine lakes across Europe.

Biogeography in Europe is known to be crucially influenced by the large mountain ranges serving as biogeographical islands for cold-adapted taxa and geographical barriers for warm-adapted taxa. While biogeographical patterns are well-known for plants and animals in Europe, we here investigated diversity and distribution patterns of protist freshwater communities on a European scale (256 lakes) in the light of the well-studied post-glacial distribution patterns of macroorganisms. Thus, our study compared 43 alpine protist communities of lakes located in the Alps, Carpathians, Pyrenees, and the Sierra Nevada with that of surrounding lowland lakes. We verified altitudinal diversity gradients of freshwater protists with decreasing richness and diversity across altitudes similar to those observed for plants and animals. Alpine specialists and generalists could be identified differing significantly in richness and diversity, but hardly in occurrence and proportions of major taxonomic groups. High proportions of region-specific alpine specialists indicate an increased occurrence of distinct lineages within each mountain range and thus, suggested either separated glacial refugia or post-glacial diversification within mountain ranges. However, a few alpine specialists were shared between mountain ranges suggesting a post-glacial recolonization from a common lowland pool. Our results identified generalists with wide distribution ranges and putatively wide tolerance ranges toward environmental conditions as main drivers of protist diversification (specification) in alpine lakes, while there was hardly any diversification in alpine specialists.

A multi-omics study on quantifying antimicrobial resistance in European freshwater lakes.

The surveillance of wastewater for the Covid-19 virus during this unprecedented pandemic and mapped to the distribution and magnitude of the infected in the population near real-time exemplifies the importance of tracking rapidly changing trends of pathogens or public health problems at a large scale. The rising trends of antimicrobial resistance (AMR) with multidrug-resistant pathogens from the environmental water have similarly gained much attention in recent years. Wastewater-based epidemiology from water samples has shown that a wide range of AMR-related genes is frequently detected. Albeit sewage is treated before release and thus, the abundance of pathogens should be significantly reduced or even pathogen-free, several studies indicated the contrary. Pathogens are still measurable in the released water, ultimately entering freshwaters, such as rivers and lakes. Furthermore, socio-economic and environmental factors, such as chemical industries and animal farming nearby, impact the presence of AMR. Many bacterial species from the environment are intrinsically resistant and also contribute to the resistome of freshwater lakes. This study collected the most extensive standardized freshwater data set from hundreds of European lakes and conducted a comprehensive multi-omics analysis on antimicrobial resistance from these freshwater lakes. Our research shows that genes encoding for AMR against tetracyclines, cephalosporins, and quinolones were commonly identified, while for some, such as sulfonamides, resistance was less frequently present. We provide an estimation of the characteristic resistance of AMR in European lakes, which can be used as a comprehensive resistome dataset to facilitate and monitor temporal changes in the development of AMR in European freshwater lakes.

Quantification of the covariation of lake microbiomes and environmental variables using a machine learning-based framework.

It is known that microorganisms are essential for the functioning of ecosystems, but the extent to which microorganisms respond to different environmental variables in their natural habitats is not clear. In the current study, we present a methodological framework to quantify the covariation of the microbial community of a habitat and environmental variables of this habitat. It is built on theoretical considerations of systems ecology, makes use of state-of-the-art machine learning techniques and can be used to identify bioindicators. We apply the framework to a data set containing operational taxonomic units (OTUs) as well as more than twenty physicochemical and geographic variables measured in a large-scale survey of European lakes. While a large part of variation (up to 61%) in many environmental variables can be explained by microbial community composition, some variables do not show significant covariation with the microbial lake community. Moreover, we have identified OTUs that act as "multitask" bioindicators, i.e., that are indicative for multiple environmental variables, and thus could be candidates for lake water monitoring schemes. Our results represent, for the first time, a quantification of the covariation of the lake microbiome and a wide array of environmental variables for lake ecosystems. Building on the results and methodology presented here, it will be possible to identify microbial taxa and processes that are essential for functioning and stability of lake ecosystems.

Nutrient-driven genome evolution revealed by comparative genomics of chrysomonad flagellates.

Phototrophic eukaryotes have evolved mainly by the primary or secondary uptake of photosynthetic organisms. A return to heterotrophy occurred multiple times in various protistan groups such as Chrysophyceae, despite the expected advantage of autotrophy. It is assumed that the evolutionary shift to mixotrophy and further to heterotrophy is triggered by a differential importance of nutrient and carbon limitation. We sequenced the genomes of 16 chrysophyte strains and compared them in terms of size, function, and sequence characteristics in relation to photo-, mixo- and heterotrophic nutrition. All strains were sequenced with Illumina and partly with PacBio. Heterotrophic taxa have reduced genomes and a higher GC content of up to 59% as compared to phototrophic taxa. Heterotrophs have a large pan genome, but a small core genome, indicating a differential specialization of the distinct lineages. The pan genome of mixotrophs and heterotrophs taken together but not the pan genome of the mixotrophs alone covers the complete functionality of the phototrophic strains indicating a random reduction of genes. The observed ploidy ranges from di- to tetraploidy and was found to be independent of taxonomy or trophic mode. Our results substantiate an evolution driven by nutrient and carbon limitation.

Molecular Data Reveal a Cryptic Diversity in the Genus Urotricha (Alveolata, Ciliophora, Prostomatida), a Key Player in Freshwater Lakes, With Remarks on Morphology, Food Preferences, and Distribution.

Species of the ciliate genus Urotricha are key players in freshwater plankton communities. In the pelagial of lakes, about 20 urotrich species occur throughout an annual cycle, some of which play a pivotal role in aquatic food webs. For example, during the phytoplankton spring bloom, they consume a remarkable proportion of the algal production. In ecological studies, urotrich ciliates are usually merely identified to genus rank and grouped into size classes. This is unsatisfying considering the distinct autecological properties of individual species and their specific spatial and temporal distribution patterns. As a basis for future research, we characterized in detail four common urotrich morphotypes, i.e., specimens identified as U. furcata and tentatively as U. agilis, U. pseudofurcata, and U. castalia, using state-of-the-art methods. We used an integrative polyphasic approach, in which morphological studies (in vivo observation, silver staining methods, scanning electron microscopy) were linked with a molecular approach exploiting four different gene fragments as taxonomic DNA barcodes with different resolution potential (SSU rDNA, ITS-1, ITS-2, hypervariable V4 and V9 regions of the SSU rDNA). We shed light on the diversity of urotrich ciliates as well as on their global distribution patterns, and annual cycles. Additionally, we coupled individual species occurrences and environmental parameters, and subsequently modeled the distribution and occurrence, using logistic regressions. Furthermore, for one strain putatively identified as U. castalia, we ascertained the optimal cultivation media and food preferences. Thereby, our comprehensive view on these important freshwater ciliates that frequently occur in environmental high throughput sequencing datasets worldwide will allow future studies to better exploit protistan plankton data from lakes.

Natrix: a Snakemake-based workflow for processing, clustering, and taxonomically assigning amplicon sequencing reads.

BACKGROUND: Sequencing of marker genes amplified from environmental samples, known as amplicon sequencing, allows us to resolve some of the hidden diversity and elucidate evolutionary relationships and ecological processes among complex microbial communities. The analysis of large numbers of samples at high sequencing depths generated by high throughput sequencing technologies requires efficient, flexible, and reproducible bioinformatics pipelines. Only a few existing workflows can be run in a user-friendly, scalable, and reproducible manner on different computing devices using an efficient workflow management system. RESULTS: We present Natrix, an open-source bioinformatics workflow for preprocessing raw amplicon sequencing data. The workflow contains all analysis steps from quality assessment, read assembly, dereplication, chimera detection, split-sample merging, sequence representative assignment (OTUs or ASVs) to the taxonomic assignment of sequence representatives. The workflow is written using Snakemake, a workflow management engine for developing data analysis workflows. In addition, Conda is used for version control. Thus, Snakemake ensures reproducibility and Conda offers version control of the utilized programs. The encapsulation of rules and their dependencies support hassle-free sharing of rules between workflows and easy adaptation and extension of existing workflows. Natrix is freely available on GitHub ( https://github.com/MW55/Natrix ) or as a Docker container on DockerHub ( https://hub.docker.com/r/mw55/natrix ). CONCLUSION: Natrix is a user-friendly and highly extensible workflow for processing Illumina amplicon data.

Centers of endemism of freshwater protists deviate from pattern of taxon richness on a continental scale.

Here, we analyzed patterns of taxon richness and endemism of freshwater protists in Europe. Even though the significance of physicochemical parameters but also of geographic constraints for protist distribution is documented, it remains unclear where regional areas of high protist diversity are located and whether areas of high taxon richness harbor a high proportion of endemics. Further, patterns may be universal for protists or deviate between taxonomic groups. Based on amplicon sequencing campaigns targeting the SSU and ITS region of the rDNA we address these patterns at two different levels of phylogenetic resolution. Our analyses demonstrate that protists have restricted geographical distribution areas. For many taxonomic groups the regions of high taxon richness deviate from those having a high proportion of putative endemics. In particular, the diversity of high mountain lakes as azonal habitats deviated from surrounding lowlands, i.e. many taxa were found exclusively in high mountain lakes and several putatively endemic taxa occurred in mountain regions like the Alps, the Pyrenees or the Massif Central. Beyond that, taxonomic groups showed a pronounced accumulation of putative endemics in distinct regions, e.g. Dinophyceae along the Baltic Sea coastline, and Chrysophyceae in Scandinavia. Many other groups did not have pronounced areas of increased endemism but geographically restricted taxa were found across Europe.

Ecological Differentiation in Two Major Freshwater Bacterial Taxa Along Environmental Gradients.

Polynucleobacter (Burkholderiaceae, Betaproteobacteria) and Limnohabitans (Comamonadaceae, Betaproteobacteria) are abundant freshwater bacteria comprising large genetic and taxonomic diversities, with species adapted to physico-chemically distinct types of freshwater systems. The relative importance of environmental drivers, i.e., physico-chemistry, presence of microeukaryotes and geographic position for the diversity and prevalence has not been investigated for both taxa before. Here, we present the first pan-European study on this topic, comprising 255 freshwater lakes. We investigated Limnohabitans and Polynucleobacter using an amplicon sequencing approach of partial 16S rRNA genes along environmental gradients. We show that physico-chemical factors had the greatest impact on both genera. Analyses on environmental gradients revealed an exceptionally broad ecological spectrum of operational taxonomic units (OTUs). Despite the coarse resolution of the genetic marker, we found OTUs with contrasting environmental preferences within Polynucleobacter and Limnohabitans subclusters. Such an ecological differentiation has been characterized for PnecC and LimC before but was so far unknown for less well studied subclusters such as PnecA and PnecB. Richness and abundance of OTUs are geographically clustered, suggesting that geographic diversity patterns are attributable to region-specific physico-chemical characteristics (e.g., pH and temperature) rather than latitudinal gradients or lake sizes.

Factors shaping community patterns of protists and bacteria on a European scale.

Factors shaping community patterns of microorganisms are controversially discussed. Physical and chemical factors certainly limit the survival of individual taxa and maintenance of diversity. In recent years, a contribution of geographic distance and dispersal barriers to distribution patterns of protists and bacteria has been demonstrated. Organismic interactions such as competition, predation and mutualism further modify community structure and maintenance of distinct taxa. Here, we address the relative importance of these different factors in shaping protists and bacterial communities on a European scale using high-throughput sequencing data obtained from lentic freshwater ecosystems. We show that community patterns of protists are similar to those of bacteria. Our results indicate that cross-domain organismic factors are important variables with a higher influence on protists as compared with bacteria. Abiotic physical and chemical factors also contributed significantly to community patterns. The contribution of these latter factors was higher for bacteria, which may reflect a stronger biogeochemical coupling. The contribution of geographical distance was similar for both microbial groups.

Intraspecific Variation in Protists: Clues for Microevolution from Poteriospumella lacustris (Chrysophyceae).

Species delimitation in protists is still a challenge, attributable to the fact that protists are small, difficult to observe and many taxa are poor in morphological characters, whereas most current phylogenetic approaches only use few marker genes to measure genetic diversity. To address this problem, we assess genome-level divergence and microevolution in strains of the protist Poteriospumella lacustris, one of the first free-living, nonmodel organisms to study genome-wide intraspecific variation. Poteriospumella lacustris is a freshwater protist belonging to the Chrysophyceae with an assumed worldwide distribution. We examined three strains from different geographic regions (New Zealand, China, and Austria) by sequencing their genomes with the Illumina and PacBio platforms. The assembled genomes were small with 49-55 Mb but gene-rich with 16,000-19,000 genes, of which ∼8,000 genes could be assigned to functional categories. At least 68% of these genes were shared by all three species. Genetic variation occurred predominantly in genes presumably involved in ecological niche adaptation. Most surprisingly, we detected differences in genome ploidy between the strains (diploidy, triploidy, and tetraploidy). In analyzing intraspecific variation, several mechanisms of diversification were identified including SNPs, change of ploidy and genome size reduction.

Interaction-Specific Changes in the Transcriptome of Polynucleobacter asymbioticus Caused by Varying Protistan Communities.

We studied the impact of protist grazing and exudation on the growth and transcriptomic response of the prokaryotic prey species Polynucleobacter asymbioticus. Different single- and multi-species communities of chrysophytes were used to determine a species-specific response to the predators and the effect of chrysophyte diversity. We sequenced the mRNA of Pn. asymbioticus in communities with three single chrysophyte species (Chlorochromonas danica, Poterioochromonas malhamensis and Poteriospumella lacustris) and all combinations. The molecular responses of Pn. asymbioticus significantly changed in the presence of predators with different trophic modes and combinations of species. In the single-species samples we observed significant differences related to the relative importance of grazing and exudation in the protist-bacteria interaction, i.e., to the presence of either the heterotrophic Ps. lacustris or the mixotrophic C. danica. When grazing dominates the interaction, as in the presence of Ps. lacustris, genes acting in stress response are up-regulated. Further genes associated with transcription and translation are down-regulated indicating a reduced growth of Pn. asymbioticus. In contrast, when the potential use of algal exudates dominates the interaction, genes affiliated with iron transport are up-regulated. Rapid phototrophic growth of chrysophytes, with a high demand on soluble iron, could thus lead to iron-limitation and cause changes in the iron metabolism of Pn. asymbioticus. Additionally, we observe a benefit for Pn. asymbioticus from a more diverse protistan community, which could be due to shifts in the relative importance of phototrophy in the mixotrophic chrysophytes when competing for food with other species. Our study highlights the importance of biotic interactions and the specificity of such interactions, in particular the differential effect of grazing and algal exudation in the interaction of bacteria with mixotrophic protists.

Putatively asexual chrysophytes have meiotic genes: evidence from transcriptomic data.

Chrysophytes are a large group of heterotrophic, phototrophic, or even mixotrophic protists that are abundant in aquatic as well as terrestrial environments. Although much is known about chrysophyte biology and ecology, it is unknown if they are sexual or not. Here we use available transcriptomes of 18 isolates of 15 putatively asexual species to inventory the presence of genes used in meiosis. Since we were able to detect a set of nine meiosis-specific and 29 meiosis-related genes shared by the chrysophytes, we conclude that they are secretively sexual and therefore should be investigated further using genome sequencing to uncover any missed genes from the transcriptomes.

Silver stress differentially affects growth of phototrophic and heterotrophic chrysomonad flagellate populations.

Silver ions are among the predominant anthropogenic introduced pollutants in aquatic systems. As silver has effects on species at all trophic levels the community composition in aquatic habitats can be changed as a result of silver stress. The response of planktonic protists to environmental stressors is particularly important as they act both as producers and consumers in complex planktonic communities. Chrysomonad flagellates are of major interest, since this group includes heterotrophic, mixotrophic and phototrophic taxa, and therefore allows analysis of silver stress in organisms with contrasting nutritional strategies independent of a potential taxonomic bias. In a series of lab experiments, we compared the response of different trophic chrysophyte strains to low (5 µg L-1), medium (10 µg L-1) and high (20 µg L-1) nominal Ag concentrations in combination with changes in temperature and light intensity (phototrophs), temperature and food concentration (heterotrophs), or a combination of the above settings (mixotrophs). All tested strains were negatively affected by silver in their growth rates. The phototrophic strains reacted strongly to silver stress, whereas light intensity and temperature had only minor effects on growth rates. For heterotrophic strains, high food concentration toned down the effect of silver, whereas temperatures outside the growth optimum had a combined stress effect. The mixotrophic strains reacted differently depending on whether their nutritional mode was dominated by heterotrophy or by phototrophy. The precise response pattern across all variables was uniquely different for every single species we tested. The present work contributes to a deeper understanding of the effects of environmental stressors on complex planktonic communities. It indicates that silver will negatively impact planktonic communities and may create shifts in their composition and functioning.

SEDE-GPS: socio-economic data enrichment based on GPS information.

BACKGROUND: Microbes are essentail components of all ecosystems because they drive many biochemical processes and act as primary producers. In freshwater ecosystems, the biodiversity in and the composition of microbial communities can be used as indicators for environmental quality. Recently, some environmental features have been identified that influence microbial ecosystems. However, the impact of human action on lake microbiomes is not well understood. This is, in part, due to the fact that environmental data is, albeit theoretically accessible, not easily available. RESULTS: In this work, we present SEDE-GPS, a tool that gathers data that are relevant to the environment of an user-provided GPS coordinate. To this end, it accesses a list of public and corporate databases and aggregates the information in a single file, which can be used for further analysis. To showcase the use of SEDE-GPS, we enriched a lake microbial ecology sequencing dataset with around 18,000 socio-economic, climate, and geographic features. The sources of SEDE-GPS are public databases such as Eurostat, the Climate Data Center, and OpenStreetMap, as well as corporate sources such as Twitter. Using machine learning and feature selection methods, we were able to identify features in the data provided by SEDE-GPS that can be used to predict lake microbiome alpha diversity. CONCLUSION: The results presented in this study show that SEDE-GPS is a handy and easy-to-use tool for comprehensive data enrichment for studies of ecology and other processes that are affected by environmental features. Furthermore, we present lists of environmental, socio-economic, and climate features that are predictive for microbial biodiversity in lake ecosystems. These lists indicate that human action has a major impact on lake microbiomes. SEDE-GPS and its source code is available for download at http://SEDE-GPS.heiderlab.de.