Complete genome sequences of 30 bacterial species from a synthetic community.

We present complete genome sequences from 30 bacterial species that can be used to construct defined synthetic communities that stably form in the laboratory under controlled conditions.

Foundation species stabilize an alternative eutrophic state in nutrient-disturbed ponds via selection on microbial community.

Eutrophication due to nutrient addition can result in major alterations in aquatic ecosystem productivity. Foundation species, individually and interactively, whether present as invasive species or as instruments of ecosystem management and restoration, can have unwanted effects like stabilizing turbid eutrophic states. In this study, we used whole-pond experimental manipulations to investigate the impacts of disturbance by nutrient additions in the presence and absence of two foundation species: Dreissena polymorpha (a freshwater mussel) and Myriophyllum spicatum (a macrophyte). We tracked how nutrient additions to ponds changed the prokaryotic and eukaryotic communities, using 16S, 18S, and COI amplicon sequencing. The nutrient disturbance and foundation species imposed strong selection on the prokaryotic communities, but not on the microbial eukaryotic communities. The prokaryotic communities changed increasingly over time as the nutrient disturbance intensified. Post-disturbance, the foundation species stabilized the prokaryotic communities as observed by the reduced rate of change in community composition. Our analysis suggests that prokaryotic community change contributed both directly and indirectly to major changes in ecosystem properties, including pH and dissolved oxygen. Our work shows that nutrient disturbance and foundation species strongly affect the prokaryotic community composition and stability, and that the presence of foundation species can, in some cases, promote the emergence and persistence of a turbid eutrophic ecosystem state.

Portable BLAST-like algorithm library and its implementations for command line, Python, and R.

Basic local-alignment search tool (BLAST) is a versatile and commonly used sequence analysis tool in bioinformatics. BLAST permits fast and flexible sequence similarity searches across nucleotide and amino acid sequences, leading to diverse applications such as protein domain identification, orthology searches, and phylogenetic annotation. Most BLAST implementations are command line tools which produce output as comma-separated values files. However, a portable, modular and embeddable implementation of a BLAST-like algorithm, is still missing from our toolbox. Here we present nsearch, a command line tool and C++11 library which provides BLAST-like functionality that can easily be embedded in any application. As an example of this portability we present Blaster which leverages nsearch to provide native BLAST-like functionality for the R programming language, as well as npysearch which provides similar functionality for Python. These packages permit embedding BLAST-like functionality into larger frameworks such as Shiny or Django applications. Benchmarks show that nsearch, npysearch, and Blaster are comparable in speed and accuracy to other commonly used modern BLAST implementations such as VSEARCH and BLAST+. We envision similar implementations of nsearch for other languages commonly used in data science such as Julia to facilitate sequence similarity comparisons. Nsearch, Blaster and npysearch are free to use under the BSD 3.0 license and available on Github Conda, CRAN (Blaster) and PyPi (npysearch).

Glyphosate and a glyphosate-based herbicide affect bumblebee gut microbiota.

Pollinator decline is one of the gravest challenges facing the world today, and the overuse of pesticides may be among its causes. Here, we studied whether glyphosate, the world's most widely used pesticide, affects the bumblebee gut microbiota. We exposed the bumblebee diet to glyphosate and a glyphosate-based herbicide and quantified the microbiota community shifts using 16S rRNA gene sequencing. Furthermore, we estimated the potential sensitivity of bee gut microbes to glyphosate based on previously reported presence of target enzyme. Glyphosate increased, whereas the glyphosate-based herbicide decreased gut microbiota diversity, indicating that negative effects are attributable to co-formulants. Both glyphosate and the glyphosate-based herbicide treatments significantly decreased the relative abundance of potentially glyphosate-sensitive bacterial species Snodgrasella alvi. However, the relative abundance of potentially glyphosate-sensitive Candidatus Schmidhempelia genera increased in bumblebees treated with glyphosate. Overall, 50% of the bacterial genera detected in the bee gut microbiota were classified as potentially resistant to glyphosate, while 36% were classified as sensitive. Healthy core microbiota have been shown to protect bees from parasite infections, change metabolism, and decrease mortality. Thus, the heavy use of glyphosate-based herbicides may have implications on bees and ecosystems.

Quantitative online survey of self-perceived knowledge and knowledge gaps of medicines research and development among Finnish general public.

OBJECTIVES: This study explored self-reported knowledge and interest to learn more about medicines research, development and health technology assessment among Finnish general public. It also aimed to define possible knowledge gaps and needs for public education regarding these topics. DESIGN: Online survey with 503 participants. The questionnaire was originally developed as a part of the Needs Assessment Work Package of the European Patients' Academy on Therapeutic Innovation Project. The survey was carried out in Finland in 2019. METHODS: The survey was conducted as an online survey by Kantar TNS Gallup Forum online panel. The data were analysed by using the freely available programming language R. Relationships between the demographic characteristics (such as age, gender and education level) of respondents and their knowledge or interest in medicines research and development were determined using Pearson's χ2 tests. Statistically significant responses of demographic characteristics in the respondents' knowledge or interest in medicines research were determined by logistic regression. RESULTS: Of the 503 respondents (age 16-64) only 12% reported having good or very good knowledge of medicines research and development in general. Regarding health technology assessment, pharmacoeconomics and regulation, the percentage of respondents reporting good or very good knowledge was as low as 8%. Respondents were most interested in learning more about predictive and personalised medicine (47%) and least interested in medicines regulation (30%) and pharmacoeconomics (31%). CONCLUSIONS: Self-reported knowledge about medicines research and development and health technology assessment appears to be very low in Finland. Patient and public participation is recognised as an important and essential element in up-to-date medical research and assessment of new treatments. In order to participate as an active and equal partner in these processes, the public needs more information and education in these topics.

Prider: multiplexed primer design using linearly scaling approximation of set coverage.

BACKGROUND: Designing oligonucleotide primers and probes is one of the key steps of various laboratory experiments such as multiplexed PCR or digital multiplexed ligation assays. When designing multiplexed primers and probes to complex, heterogeneous DNA data sets, an optimization problem can arise where the smallest number of oligonucleotides covering the largest diversity of the input dataset needs to be identified. Tools that provide this optimization in an efficient manner for large input data are currently lacking. RESULTS: Here we present Prider, an R package for designing primers and probes with a nearly optimal coverage for complex and large sequence sets. Prider initially prepares a full primer coverage of the input sequences, the complexity of which is subsequently reduced by removing components of high redundancy or narrow coverage. The primers from the resulting near-optimal coverage are easily accessible as data frames and their coverage across the input sequences can be visualised as heatmaps using Prider's plotting function. Prider permits efficient design of primers to large DNA datasets by scaling linearly to increasing sequence data, regardless of the diversity of the dataset. CONCLUSIONS: Prider solves a recalcitrant problem in molecular diagnostics: how to cover a maximal sequence diversity with a minimal number of oligonucleotide primers or probes. The combination of Prider with highly scalable molecular quantification techniques will permit an unprecedented molecular screening capability with immediate applicability in fields such as clinical microbiology, epidemic virus surveillance or antimicrobial resistance surveillance.

Wastewater constituents impact biofilm microbial community in receiving streams.

Microbial life in natural biofilms is dominated by prokaryotes and microscopic eukaryotes living in dense association. In stream ecosystems, microbial biofilms influence primary production, elemental cycles, food web interactions as well as water quality. Understanding how biofilm communities respond to anthropogenic impacts, such as wastewater treatment plant (WWTP) effluent, is important given the key role of biofilms in stream ecosystem function. Here, we implemented 16S and 18S rRNA gene sequencing of stream biofilms upstream (US) and downstream (DS) of WWTP effluents in four Swiss streams to test how bacterial and eukaryotic communities respond to wastewater constituents. Stream biofilm composition was strongly affected by geographic location - particularly for bacteria. However, the abundance of certain microbial community members was related to micropollutants in the wastewater - among bacteria, micropollutant-associated members were found e.g. in Alphaproteobacteria, and among eukaryotes e.g. in Bacillariophyta (algal diatoms). This study corroborates several previously characterized responses (e.g. as seen in diatoms), but also reveals previously unknown community responses - such as seen in Alphaproteobacteria. This study advances our understanding of the ecological impact of the current wastewater treatment practices and provides information about potential new marker organisms to assess ecological change in stream biofilms.

Stream microbial communities and ecosystem functioning show complex responses to multiple stressors in wastewater.

Multiple anthropogenic drivers are changing ecosystems globally, with a disproportionate and intensifying impact on freshwater habitats. A major impact of urbanization are inputs from wastewater treatment plants (WWTPs). Initially designed to reduce eutrophication and improve water quality, WWTPs increasingly release a multitude of micropollutants (MPs; i.e., synthetic chemicals) and microbes (including antibiotic-resistant bacteria) to receiving environments. This pollution may have pervasive impacts on biodiversity and ecosystem services. Viewed through multiple lenses of macroecological and ecotoxicological theory, we combined field, flume, and laboratory experiments to determine the effects of wastewater (WW) on microbial communities and organic-matter processing using a standardized decomposition assay. First, we conducted a mensurative experiment sampling 60 locations above and below WWTP discharges in 20 Swiss streams. Microbial respiration and decomposition rates were positively influenced by WW inputs via warming and nutrient enrichment, but with a notable exception: WW decreased the activation energy of decomposition, indicating a "slowing" of this fundamental ecosystem process in response to temperature. Second, next-generation sequencing indicated that microbial community structure below WWTPs was altered, with significant compositional turnover, reduced richness, and evidence of negative MP influences. Third, a series of flume experiments confirmed that although diluted WW generally has positive influences on microbial-mediated processes, the negative effects of MPs are "masked" by nutrient enrichment. Finally, transplant experiments suggested that WW-borne microbes enhance decomposition rates. Taken together, our results affirm the multiple stressor paradigm by showing that different aspects of WW (warming, nutrients, microbes, and MPs) jointly influence ecosystem functioning in complex ways. Increased respiration rates below WWTPs potentially generate ecosystem "disservices" via greater carbon evasion from streams and rivers. However, toxic MP effects may fundamentally alter ecological scaling relationships, indicating the need for a rapprochement between ecotoxicological and macroecological perspectives.

Digital multiplex ligation assay for highly multiplexed screening of ß-lactamase-encoding genes in bacterial isolates.

Increasing incidence of antibiotic resistance in clinical and environmental settings calls for increased scalability in their surveillance. Current screening technologies are limited by the number of samples and genes that can easily be screened. We demonstrate here digital multiplex ligation assay (dMLA) as a low-cost targeted genomic detection workflow capable of highly-parallel screening of bacterial isolates for multiple target gene regions simultaneously. Here, dMLA is used for simultaneous detection of 1187 ß-lactamase-encoding genes, including extended spectrum ß-lactamase (ESBL) genes, in 74 bacterial isolates. We demonstrate dMLA as a light-weight and cost-efficient workflow which provides a highly scalable tool for antimicrobial resistance surveillance and is also adaptable to genetic screening applications beyond antibiotic resistance.

The evolution of competitive ability for essential resources.

Competition for limiting resources is among the most fundamental ecological interactions and has long been considered a key driver of species coexistence and biodiversity. Species' minimum resource requirements, their R*s, are key traits that link individual physiological demands to the outcome of competition. However, a major question remains unanswered-to what extent are species' competitive traits able to evolve in response to resource limitation? To address this knowledge gap, we performed an evolution experiment in which we exposed Chlamydomonas reinhardtii for approximately 285 generations to seven environments in chemostats that differed in resource supply ratios (including nitrogen, phosphorus and light limitation) and salt stress. We then grew the ancestors and descendants in a common garden and quantified their competitive abilities for essential resources. We investigated constraints on trait evolution by testing whether changes in resource requirements for different resources were correlated. Competitive abilities for phosphorus improved in all populations, while competitive abilities for nitrogen and light increased in some populations and decreased in others. In contrast to the common assumption that there are trade-offs between competitive abilities for different resources, we found that improvements in competitive ability for a resource came at no detectable cost. Instead, improvements in competitive ability for multiple resources were either positively correlated or not significantly correlated. Using resource competition theory, we then demonstrated that rapid adaptation in competitive traits altered the predicted outcomes of competition. These results highlight the need to incorporate contemporary evolutionary change into predictions of competitive community dynamics over environmental gradients. This article is part of the theme issue 'Conceptual challenges in microbial community ecology'.

Author Correction: Proteome evolution under non-substitutable resource limitation.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Uncovering microbial inter-domain interactions in complex communities.

Interactions between unicellular eukaryotes and bacteria are difficult to characterize in the environment owing to their large number and inherently microscopic scale. Although particular co-occurrences can be recovered through targeted approaches, e.g. single-cell sequencing or fluorescence in situ hybridization, the vast majority of the interactions remain unseen. Here, we discuss Emulsion, Paired Isolation and Concatenation polymerase chain reaction (epicPCR) as a tool to uncover these interactions in very high throughput. Originally developed for taxonomy-to-function linkage in bacterial communities, epicPCR has the potential to recover the complete interaction network in a given environment at single-cell resolution. This approach relies on the encapsulation of protistan single cells in emulsion droplets that can subsequently be gelified into beads. In this way, encapsulated cells can be exposed to lysis reagents and further phylogenetic paired marker amplification. A bacterium that physically co-occurs with the eukaryote will be jointly trapped, and the amplification will generate a concatenated PCR product containing physically coupled taxonomic markers from both partners, creating a link. Further amplification and sequencing enable the construction of an association pattern with statistically verified physical co-occurrences. Here, we discuss the potential, challenges and limitations of epicPCR. We argue that the microscopic scale at which epicPCR operates, the high throughput it delivers and its exploratory nature make it an unparalleled approach to unravel associations between microbes directly from environmental samples. This article is part of a discussion meeting issue 'Single cell ecology'.

Occurrence of sul and tet(M) genes in bacterial community in Japanese marine aquaculture environment throughout the year: Profile comparison with Taiwanese and Finnish aquaculture waters.

The use of antibiotics in aquaculture causes selection pressure for antibiotic-resistant bacteria (ARB). Antibiotic resistance genes (ARGs) may persist in ARB and the environment for long time even after stopping drug administration. Here we show monthly differences in the occurrences of genes conferring resistance to sulfonamides (i.e. sul1, sul2, sul3), and tetracyclines (tet(M)) in Japanese aquaculture seawater accompanied by records of drug administration. sul2 was found to persist throughout the year, whereas the occurrences of sul1, sul3, and tet(M) changed month-to-month. sul3 and tet(M) were detected in natural bacterial assemblages in May and July, but not in colony-forming bacteria, thus suggesting that the sul3 was harbored by the non-culturable fraction of the bacterial community. Comparison of results from Taiwanese, Japanese, and Finnish aquaculture waters reveals that the profile of sul genes and tet(M) in Taiwan resembles that in Japan, but is distinct from that in Finland. To our knowledge, this work represents the first report to use the same method to compare the dynamics of sul genes and tet(M) in aquaculture seawater in different countries.

Proteome evolution under non-substitutable resource limitation.

Resource limitation is a major driver of the ecological and evolutionary dynamics of organisms. Short-term responses to resource limitation include plastic changes in molecular phenotypes including protein expression. Yet little is known about the evolution of the molecular phenotype under longer-term resource limitation. Here, we combine experimental evolution of the green alga Chlamydomonas reinhardtii under multiple different non-substitutable resource limitation regimes with proteomic measurements to investigate evolutionary adaptation of the molecular phenotype. We demonstrate convergent proteomic evolution of core metabolic functions, including the Calvin-Benson cycle and gluconeogenesis, across different resource limitation environments. We do not observe proteomic changes consistent with optimized uptake of particular limiting resources. Instead, we report that adaptation proceeds in similar directions under different types of non-substitutable resource limitation. This largely convergent evolution of the expression of core metabolic proteins is associated with an improvement in the resource assimilation efficiency of nitrogen and phosphorus into biomass.

Ecology determines how low antibiotic concentration impacts community composition and horizontal transfer of resistance genes.

Low concentrations of antibiotics have numerous effects on bacteria. However, it is unknown whether ecological factors such as trophic interactions and spatial structuring influence the effects of low concentrations of antibiotics on multispecies microbial communities. Here, we address this question by investigating the effects of low antibiotic concentration on community composition and horizontal transfer of an antibiotic resistance plasmid in a 62-strain bacterial community in response to manipulation of the spatial environment and presence of predation. The strong effects of antibiotic treatment on community composition depend on the presence of predation and spatial structuring that have strong community effects on their own. Overall, we find plasmid transfer to diverse recipient taxa. Plasmid transfer is likely to occur to abundant strains, occurs to a higher number of strains in the presence of antibiotic, and also occurs to low-abundance strains in the presence of spatial structures. These results fill knowledge gaps concerning the effects of low antibiotic concentrations in complex ecological settings.

Construction and Characterization of Synthetic Bacterial Community for Experimental Ecology and Evolution.

Experimental microbial ecology and evolution have yielded foundational insights into ecological and evolutionary processes using simple microcosm setups and phenotypic assays with one- or two-species model systems. The fields are now increasingly incorporating more complex systems and exploration of the molecular basis of observations. For this purpose, simplified, manageable and well-defined multispecies model systems are required that can be easily investigated using culturing and high-throughput sequencing approaches, bridging the gap between simpler and more complex synthetic or natural systems. Here we address this need by constructing a completely synthetic 33 bacterial strain community that can be cultured in simple laboratory conditions. We provide whole-genome data for all the strains as well as metadata about genomic features and phenotypic traits that allow resolving individual strains by amplicon sequencing and facilitate a variety of envisioned mechanistic studies. We further show that a large proportion of the strains exhibit coexistence in co-culture over serial transfer for 48 days in the absence of any experimental manipulation to maintain diversity. The constructed bacterial community can be a valuable resource in future experimental work.

Host range of antibiotic resistance genes in wastewater treatment plant influent and effluent.

Wastewater treatment plants (WWTPs) collect wastewater from various sources for a multi-step treatment process. By mixing a large variety of bacteria and promoting their proximity, WWTPs constitute potential hotspots for the emergence of antibiotic resistant bacteria. Concerns have been expressed regarding the potential of WWTPs to spread antibiotic resistance genes (ARGs) from environmental reservoirs to human pathogens. We utilized epicPCR (Emulsion, Paired Isolation and Concatenation PCR) to detect the bacterial hosts of ARGs in two WWTPs. We identified the host distribution of four resistance-associated genes (tetM, int1, qacEΔ1and blaOXA-58) in influent and effluent. The bacterial hosts of these resistance genes varied between the WWTP influent and effluent, with a generally decreasing host range in the effluent. Through 16S rRNA gene sequencing, it was determined that the resistance gene carrying bacteria include both abundant and rare taxa. Our results suggest that the studied WWTPs mostly succeed in decreasing the host range of the resistance genes during the treatment process. Still, there were instances where effluent contained resistance genes in bacterial groups not carrying these genes in the influent. By permitting exhaustive profiling of resistance-associated gene hosts in WWTP bacterial communities, the application of epicPCR provides a new level of precision to our resistance gene risk estimates.

Single-cell mass spectrometry reveals the importance of genetic diversity and plasticity for phenotypic variation in nitrogen-limited Chlamydomonas.

Phenotypic variation is vital for microbial populations to survive environmental perturbations. Both genetic and non-genetic factors contribute to an organism's phenotypic variation and therefore its fitness. To investigate the correlation between genetic diversity and phenotypic variation, we applied our recently developed mass spectrometry method that allows for the simultaneous measurement of more than 25 different lipids and pigments with high throughput in the unicellular microalga Chlamydomonas reinhardtii. We monitored the impact of nitrogen limitation on a genetically diverse wild-type strain CC-1690 and two isoclonal isolates from CC-1690 named ANC3 and ANC5. Measuring molecular composition of thousands of single cells at different time points of the experiment allowed us to capture a dynamic picture of the phenotypic composition and adaptation of the populations over time. Although the genetically diverse population maintained phenotypic variation over the whole time course of the experiment, the isoclonal cultures showed higher synchronicity in their phenotypic response. Furthermore, the genetically diverse population showed equal or greater phenotypic variation over the whole time range in multidimensional trait space compared with isoclonal populations. However, along individual trait axes non-genetic variance was higher in isoclonal populations.

Evaluating the mobility potential of antibiotic resistance genes in environmental resistomes without metagenomics.

Antibiotic resistance genes are ubiquitous in the environment. However, only a fraction of them are mobile and able to spread to pathogenic bacteria. Until now, studying the mobility of antibiotic resistance genes in environmental resistomes has been challenging due to inadequate sensitivity and difficulties in contig assembly of metagenome based methods. We developed a new cost and labor efficient method based on Inverse PCR and long read sequencing for studying mobility potential of environmental resistance genes. We applied Inverse PCR on sediment samples and identified 79 different MGE clusters associated with the studied resistance genes, including novel mobile genetic elements, co-selected resistance genes and a new putative antibiotic resistance gene. The results show that the method can be used in antibiotic resistance early warning systems. In comparison to metagenomics, Inverse PCR was markedly more sensitive and provided more data on resistance gene mobility and co-selected resistances.

"Every Gene Is Everywhere but the Environment Selects": Global Geolocalization of Gene Sharing in Environmental Samples through Network Analysis.

The spatial distribution of microbes on our planet is famously formulated in the Baas Becking hypothesis as "everything is everywhere but the environment selects." While this hypothesis does not strictly rule out patterns caused by geographical effects on ecology and historical founder effects, it does propose that the remarkable dispersal potential of microbes leads to distributions generally shaped by environmental factors rather than geographical distance. By constructing sequence similarity networks from uncultured environmental samples, we show that microbial gene pool distributions are not influenced nearly as much by geography as ecology, thus extending the Bass Becking hypothesis from whole organisms to microbial genes. We find that gene pools are shaped by their broad ecological niche (such as sea water, fresh water, host, and airborne). We find that freshwater habitats act as a gene exchange bridge between otherwise disconnected habitats. Finally, certain antibiotic resistance genes deviate from the general trend of habitat specificity by exhibiting a high degree of cross-habitat mobility. The strong cross-habitat mobility of antibiotic resistance genes is a cause for concern and provides a paradigmatic example of the rate by which genes colonize new habitats when new selective forces emerge.