Department Environmental Microbiology

Multi-step substrate consumption pathways can promote microbial biodiversity via cross-feeding. If one cell type preferentially consumes a primary substrate rather than the subsequently formed intermediates, then other cell types can specialize in consuming the intermediates. While this mechanism for promoting biodiversity is established, predicting the long-term persistence of such cross-feeding interactions remains challenging. Under what conditions will the interaction (and thus biodiversity) persist or disappear? To address this question, we propagated co-cultures of two isogenic strains of the bacterium Pseudomonas stutzeri. One completely reduces nitrate to nitrogen gas but preferentially reduces nitrate rather than nitrite (referred to as the generalist), while the other only reduces nitrite to nitrogen gas (referred to as the specialist). We found that the two strains coexist via nitrite cross-feeding when grown together, but the initial ratio of specialist-to-generalist (r_S/G) determines the long-term dynamics of the co-culture. Co-cultures with large initial r_S/Gs converge to the same r_S/G and persist thereafter. Co-cultures with small initial r_S/Gs also converge to the same r_S/G but then become increasingly dominated by the generalist. The likely cause of these different dynamics is that the initial r_S/G determines the initial environment, which in turn determines the initial selection pressures and phenotypes acquired by the generalist. Our results demonstrate that initial community composition controls the long-term dynamics and persistence of a cross-feeding interaction, and is therefore an important factor for community development and for engineering communities to achieve desired outcomes.

β-Amino residues are regarded as extremely rare features among ribosomal products. They can be installed by a remarkable non-canonical enzymatic splicing process occurring in some Nif11-type ribosomally synthesized and posttranslationally modified peptide (RiPP) pathways from select cyanobacteria. The functions of the final pathway products remained unknown. Here, a global bioinformatic analysis suggested an unexpectedly broad distribution of ribosomal β-amino acid products in diverse bacterial lineages as well as archaea. Characterization of 27 bacterial splicease-substrate pairs confirmed the modification in all cases. The “spliceotide” products include many previously unrecognized RiPP types as well as proteins, contain 35 to >600 residues, and feature single to multiple α-keto-β-amino acid moieties, with 15 different naturally occurring β units characterized and 20 predicted. Of three tested spliceotides, all exhibited exceptionally potent protease inhibitory activity, providing a potential rationale for the widespread splicease chemistry in prokaryotes and highlighting substantial potential for drug discovery and gene-based biomolecule diversification.

Marine microbial communities are a wellspring of biochemical transformations, with discovery fueled by the ever-expanding development of biotechnological methodologies. Meta-omic strategies—from genome-based studies to enzymology and molecular-level investigations— have shed light on the involvement of microbial dark matter in the biosynthesis of bioactive metabolites. Herein, we describe the enzymology and biosynthesis of natural products derived from marine invertebrates, highlighting the diversity of this vast biochemical resource.

【Objective】Viruses exist almost everywhere on Earth. They can infect humans, animals, plants, fungi, and even bacteria, and thus play critical roles in the biogeochemical cycling of elements and energy. Knowledge of the viruses' community patterns and genomic information is key for proper understanding of their crucial ecological functions. This study aims to quantify the viral community patterns and functions in a farmland black soil of Northeast China and analyze their potential roles in soil ecosystems. 【Method】The metagenome sequences of the viruses were obtained based on metagenomics sequencing technology and were analyzed individually for functional gene analysis, host prediction, and genome assembly of viral Contigs. A bioinformatics software was employed to analyze the diversity patterns of the viruses. 【Result】The results showed that the majority of the viruses in the farmland black soil belonged to Caudovirales(59.38%)and Herpesvirales(2.56%)orders. This consisted of 29 families, with Siphoviridae and Microviridae representing the top two abundant families and accounting for about 44.48% and 20.53%, respectively. Gene annotation analysis revealed that soil viruses may actively contribute to numerous biogeochemical cycling processes, including nitrogen compounds metabolism, catabolism, biosynthesis, methylation, multi-organism metabolism, cellular metabolism, primary metabolism, nucleobase-containing small molecules metabolism, and organic substance metabolism, etc. Additional analysis showed that the virus hosts could be classified into 35 genera that belong to 5 phyla. 【Conclusion】With these quantitative measurements, this study provides necessary information towards advancing the virus gene database of the black soil and its ecological functions.

Metabolic division of labor (MDOL) represents a widespread natural phenomenon, whereby a complex metabolic pathway is shared between different strains within a community in a mutually beneficial manner. However, little is known about how the composition of such a microbial community is regulated. We hypothesized that when degradation of an organic compound is carried out via MDOL, the concentration and toxicity of the substrate modulate the benefit allocation between the two microbial populations, thus affecting the structure of this community. We tested this hypothesis by combining modeling with experiments using a synthetic consortium. Our modeling analysis suggests that the proportion of the population executing the first metabolic step can be simply estimated by Monod-like formulas governed by substrate concentration and toxicity. Our model and the proposed formula were able to quantitatively predict the structure of our synthetic consortium. Further analysis demonstrates that our rule is also applicable in estimating community structures in spatially structured environments. Together, our work clearly demonstrates that the structure of MDOL communities can be quantitatively predicted using available information on environmental factors, thus providing novel insights into how to manage artificial microbial systems for the wide application of the bioindustry.

Although the accomplishments of microbiome engineering highlight its significance for the targeted manipulation of microbial communities, knowledge and technical gaps still limit the applications of microbiome engineering in biotechnology, especially for environmental use. Addressing the environmental challenges of refractory pollutants and fluctuating environmental conditions requires an adequate understanding of the theoretical achievements and practical applications of microbiome engineering. Here, we review recent cutting-edge studies on microbiome engineering strategies and their classical applications in bioremediation. Moreover, a framework is summarized for combining both top-down and bottom-up approaches in microbiome engineering toward improved applications. A strategy to engineer microbiomes for environmental use, which avoids the build-up of toxic intermediates that pose a risk to human health, is suggested. We anticipate that the highlighted framework and strategy will be beneficial for engineering microbiomes to address difficult environmental challenges such as degrading multiple refractory pollutants and sustain the performance of engineered microbiomes in situ with indigenous microorganisms under fluctuating conditions.

Since acidic environments often serve as an important line of defense against bacterial pathogens, it is important to fully understand how the latter manage to mount and evolve acid resistance mechanisms. Escherichia coli, a species harboring many pathovars, is typically equipped with the acid fitness island (AFI), a genomic region encoding the GadE master regulator together with several GadE-controlled functions to counter acid stress. This study reveals that gadE and consequently AFI functions are heterogeneously expressed even in the absence of any prior acid stress, thereby preemptively creating acid-resistant subpopulations within a clonal E. coli population. Directed evolution efforts selecting for modulated gadE expression confirm that a gain-of-function mutation in the EvgS sensor kinase can constitutively upregulate gadE expression and concomitant acid resistance. However, we reveal that such upregulation of EvgS also causes cross-resistance to heat stress because of SafA-mediated cross-activation of the PhoPQ regulon. Surprisingly, loss of function of the serC gene (encoding phosphoserine/phosphohydroxythreonine aminotransferase) can also significantly upregulate gadE expression, acid resistance, and heat cross-resistance, although via a currently cryptic mechanism. As such, our data reveal a noisy expression of gadE in E. coli that is functional for the survival of sudden acid stress and that can readily be genetically tuned.

Antibiotic resistance is a leading cause of hospitalization and death worldwide. Heavy metals such as arsenic have been shown to drive co-selection of antibiotic resistance, suggesting arsenic-contaminated drinking water is a risk factor for antibiotic resistance carriage. This study aimed to determine the prevalence and abundance of antibiotic-resistant Escherichia coli (AR-Ec) among people and drinking water in high (Hajiganj, >100 μg/L) and low arsenic-contaminated (Matlab, <20 μg/L) areas in Bangladesh. Drinking water and stool from mothers and their children (<1 year) were collected from 50 households per area. AR-Ec was detected via selective culture plating and isolates were tested for antibiotic resistance, arsenic resistance, and diarrheagenic genes by PCR. Whole-genome sequencing (WGS) analysis was done for 30 E. coli isolates from 10 households. Prevalence of AR-Ec was significantly higher in water in Hajiganj (48%) compared to water in Matlab (22%, p <0.05) and among children in Hajiganj (94%) compared to children in Matlab (76%, p <0.05), but not among mothers. A significantly higher proportion of E. coli isolates from Hajiganj were multidrug-resistant (83%) compared to isolates from Matlab (71%, p <0.05). Co-resistance to arsenic and multiple antibiotics (MAR index >0.2) was observed in a higher proportion of water (78%) and child stool (100%) isolates in Hajiganj than in water (57%) and children (89%) in Matlab (p <0.05). The odds of arsenic-resistant bacteria being resistant to third-generation cephalosporin antibiotics were higher compared to arsenic-sensitive bacteria (odds ratios, OR 1.2–7.0, p <0.01). WGS-based phylogenetic analysis of E. coli isolates did not reveal any clustering based on arsenic exposure and no significant difference in resistome was found among the isolates between the two areas. The positive association detected between arsenic exposure and antibiotic resistance carriage among children in arsenic-affected areas in Bangladesh is an important public health concern that warrants redoubling efforts to reduce arsenic exposure.

Bacteria are essential drivers of global biogeochemical cycles, including the carbon cycle. They play an important role in the degradation of organic matter that involves the breakdown of carbon polymers. These carbon polymers are too large to be taken up by bacterial cells. Therefore, bacteria often secrete extracellular enzymes to cleave the polymers into smaller oligomers and monomers that can be imported into the cell and metabolized. However, secreted enzymes and the released breakdown products can be lost through diffusion or flow. Mathematical models and experimental evidence suggest that aggregation of cells can reduce diffusional loss of secreted compounds and released nutrients. According to these findings, bacteria might benefit from forming aggregates when growing on carbon polymers due to the increased cell density and synergistic interactions between them. In this thesis, I used a wellstudied model system - the aquatic bacterium Caulobacter crescentus - to study the dynamics of bacterial behavior in response to growth on polymeric carbon sources. I used a microfluidics setup combined with automated time-lapse microscopy and quantitative image analysis to track growth dynamics and spatial organization of this bacterium at the single-cell level. [...]

Bakterien sind wesentliche Triebkräfte der globalen biogeochemischen Kreisläufe, einschließlich des Kohlenstoffkreislaufs. Sie spielen eine wichtige Rolle beim Abbau von organischem Material, der die Zersetzung von Kohlenstoffpolymeren beinhaltet. Diese Kohlenstoffpolymere sind zu groß, um von den Bakterienzellen aufgenommen zu werden. Daher scheiden Bakterien häufig extrazelluläre Enzyme aus, um die Polymere in kleinere Oligomere und Monomere zu spalten, die in die Zelle importiert und verstoffwechselt werden können. Allerdings können die sezernierten Enzyme und die freigesetzten Abbauprodukte durch Diffusion oder Strömung verloren gehen. Mathematische Modelle und experimentelle Beweise deuten darauf hin, dass die Aggregation von Zellen den Diffusionsverlust von sekretierten Verbindungen und freigesetzten Nährstoffen verringern kann. Diesen Erkenntnissen zufolge könnten Bakterien von der Bildung von Aggregaten profitieren, wenn sie auf Kohlenstoffpolymeren wachsen, da die Zelldichte erhöht wird und synergistische Wechselwirkungen zwischen den Zellen stattfinden. In dieser Arbeit habe ich ein gut untersuchtes Modellsystem - das aquatische Bakterium Caulobacter crescentus - verwendet, um die Dynamik des bakteriellen Verhaltens als Reaktion auf das Wachstum auf polymeren Kohlenstoffquellen zu untersuchen. Ich verwendete einen mikrofluidischen Aufbau in Kombination mit automatisierter Zeitraffermikroskopie und quantitativer Bildanalyse, um die Wachstumsdynamik und die räumliche Organisation dieses Bakteriums auf der Ebene einzelner Zellen zu verfolgen. [...]

The objective of the Reducing Enteropathy, Undernutrition, and Contamination in the Environment (REDUCE) program is to identify exposure pathways to fecal pathogens that are significant contributors to morbidity among young children in the Democratic Republic of the Congo (DRC), and on developing and evaluating scalable interventions to reduce fecal contamination from these pathways. This prospective cohort study of 270 children under 5 years of age was conducted in rural South Kivu, DRC, to investigate the association between Escherichia coli in hand rinse, soil, food, object, surface, stored water, and water source samples and child developmental outcomes. Child developmental outcomes were assessed by communication, fine motor, gross motor, personal social, problem-solving, and combined scores measured by the Extended Ages and Stages Questionnaire (EASQ) at a 6-month follow-up. Children having E. coli present in the soil in their play spaces had significantly lower combined EASQ z scores (coefficient: -0.38 (95% CI: -0.73, -0.03)). E. coli on children’s hands was associated with lower communication EASQ z scores (-0.37 (95% CI: -0.0.10, -0.01), and E. coli in stored drinking water was associated with lower gross motor EASQ z scores (-0.40 (95% CI: -0.68, -0.12). In the REDUCE cohort study, E. coli in soil in child play spaces, on children’s hands, and in stored drinking water was associated with lower developmental outcome scores (communication, gross motor, fine motor, and problem-solving skills). These results suggest the need for interventions to reduce fecal contamination in the household environment to protect the cognitive development of susceptible pediatric populations in rural DRC.

The amount of bacterial diversity present on many surfaces is enormous; however, how these levels of diversity persist in the face of the purifying processes that occur as bacterial communities expand across space (referred to here as range expansion) remains enigmatic. We shed light on this apparent paradox by providing mechanistic evidence for a strong role of fungal hyphae-mediated dispersal on regulating bacterial diversity during range expansion. Using pairs of fluorescently labeled bacterial strains and a hyphae-forming fungal strain that expand together across a nutrient-amended surface, we show that a hyphal network increases the spatial intermixing and extent of range expansion of the bacterial strains. This is true regardless of the type of interaction (competition or resource cross-feeding) imposed between the bacterial strains. We further show that the underlying cause is that flagellar motility drives bacterial dispersal along the hyphal network, which counteracts the purifying effects of ecological drift at the expansion frontier. We finally demonstrate that hyphae-mediated spatial intermixing increases the conjugation-mediated spread of plasmid-encoded antibiotic resistance. In conclusion, fungal hyphae are important regulators of bacterial diversity and promote plasmid-mediated functional novelty during range expansion in an interaction-independent manner.

DNA from more than 1,000 marine microbial communities around the world was used to reconstruct around 26,000 genomes. The analyses identified a highly biosynthetically diverse family of bacteria in the open ocean, as well as new enzymes and biochemical compounds.

Proteins are key molecular players in a cell, and their abundance is extensively regulated not just at the level of gene expression but also post-transcriptionally. Here, we describe a genetic screen in yeast that enables systematic characterization of how protein abundance regulation is encoded in the genome. The screen combines a CRISPR/Cas9 base editor to introduce point mutations with fluorescent tagging of endogenous proteins to facilitate a flow-cytometric readout. We first benchmarked base editor performance in yeast with individual gRNAs as well as in positive and negative selection screens. We then examined the effects of 16,452 genetic perturbations on the abundance of eleven proteins representing a variety of cellular functions. We uncovered hundreds of regulatory relationships, including a novel link between the GAPDH isoenzymes Tdh1/2/3 and the Ras/PKA pathway. Many of the identified regulators are specific to one of the eleven proteins, but we also found genes that, upon perturbation, affected the abundance of most of the tested proteins. While the more specific regulators usually act transcriptionally, broad regulators often have roles in protein translation. Overall, our novel screening approach provides unprecedented insights into the components, scale and connectedness of the protein regulatory network.

Miniature ecosystems provide insights into general ecological principles

Wastewater-based epidemiology (WBE) has emerged as an effective tool for monitoring SARS-CoV-2 dynamics during the COVID-19 pandemic. Here, we add a spatial component to WBE and use it to investigate SARS-CoV-2 spread in the canton of Ticino during the onset of the pandemic in Switzerland (end of February 2020 to beginning of March 2020). Ticino is located at the border to Northern Italy, where a large COVID-19 outbreak occurred in February 2020. Not surprisingly, Ticino was the site of the first clinically confirmed COVID-19 case in Switzerland. We retrospectively analyzed daily influent samples from nine wastewater treatment plants in Ticino that jointly cover an area of 20 km × 60 km and 351,000 people (>99% of the population). Our result is a fine-grained view of the spatiotemporal evolution of the COVID-19 pandemic in this canton. The wastewater analysis revealed that by February 29, 2020, SARS-CoV-2 had already spread to all catchments. At the same time, only four individual cases had been clinically confirmed across the region served by the treatment plants investigated. Our results demonstrate that WBE could serve as a versatile tool to monitor the introduction and spread of an infectious agent on a regional scale. To fully exploit its utility, WBE should be implemented in real time and become an integral part of future disease surveillance efforts.

Using biodegradable instead of conventional plastics in agricultural applications promises to help overcome plastic pollution of agricultural soils. However, analytical limitations impede our understanding of plastic biodegradation in soils. Utilizing stable carbon isotope (¹³C-)labelled poly(butylene succinate) (PBS), a synthetic polyester, we herein present an analytical approach to continuously quantify PBS mineralization to ¹³CO₂ during soil incubations and, thereafter, to determine non-mineralized PBS-derived ¹³C remaining in the soil. We demonstrate extensive PBS mineralization (65 % of added ¹³C) and a closed mass balance on PBS-¹³C over 425 days of incubation. Extraction of residual PBS from soils combined with kinetic modeling of the biodegradation data and results from monomer (i.e., butanediol and succinate) mineralization experiments suggest that PBS hydrolytic breakdown controlled the overall PBS biodegradation rate. Beyond PBS biodegradation in soil, the presented methodology is broadly applicable to investigate biodegradation of other biodegradable polymers in various receiving environments.

Microbial communities execute metabolic pathways to drive global nutrient cycles. Within a community, functionally specialized strains can perform different yet complementary steps within a linear pathway, a phenomenon termed metabolic division of labor (MDOL). However, little is known about how such metabolic behaviors shape microbial communities. Here, we derive a theoretical framework to define the assembly of a community that degrades an organic compound through MDOL. The framework indicates that to ensure community stability, the strains performing the initial steps should hold a growth advantage (m) over the “private benefit” (n) of the strain performing the last step. The steady-state frequency of the last strain is then determined by the quotient of n and m. Our experiments show that the framework accurately predicts the assembly of our synthetic consortia that degrade naphthalene through MDOL. Our results provide insights for designing and managing stable microbial systems for metabolic pathway optimization.

Phage-bacterium interactions influence soil microbial life and ecological functions, including microbial evolution, community patterns, and nutrient cycling. However, understanding of phage-mediated soil bacterial lysis dynamics, and impacts on soil carbon (C) and nitrogen (N) cycling, remains elusive. Here, we used a short-term laboratory incubation microcosm model system (which did not contain actual soil) consisting of a soil bacterium Bacillus cereus LB2 and an exclusive B. cereus phage SWEP1 to illustrate how a single soil phage manipulates bacterial lysis and the associated necromass formation under different nutrient conditions, and the associated changes on C and N dynamics. Results showed that the phage-induced bacterial lysis significantly increased the total amounts of necromass C and N, which was correlated to nutrient conditions. Bacteria populations were effectively eliminated by phages under eutrophic conditions, whereas the lysis rate of SWEP1 slowed down under oligotrophic conditions. The presence of phage clearly stimulated necromass accumulation, albeit with a reduced proportion of dissolved NH₄⁺-N content from the supernatant. Therefore, phages may enhance microbial necromass formation, and actively contribute to soil organic matter (SOM) stabilisation and C and N cycling in soil ecosystem.

Opportunistic pathogens belonging to the genus Legionella are among the most reported waterborne-associated pathogens in industrialized countries. Legionella colonize a variety of engineered aquatic ecosystems and persist in biofilms where they interact with a multitude of other resident microorganisms. In this review, we assess how some of these interactions could be used to develop a biological-driven "probiotic" control approach against Legionella. We focus on: (i) mechanisms limiting the ability of Legionella to establish and replicate within some of their natural protozoan hosts; (ii) exploitative and interference competitive interactions between Legionella and other microorganisms; and (iii) the potential of predatory bacteria and phages against Legionella. This field is still emergent, and we therefore specifically highlight research for future investigations, and propose perspectives on the feasibility and public acceptance of a potential probiotic approach.

The continuing emergence of SARS-CoV-2 variants of concern and variants of interest emphasizes the need for early detection and epidemiological surveillance of novel variants. We used genomic sequencing of 122 wastewater samples from three locations in Switzerland to monitor the local spread of B.1.1.7 (Alpha), B.1.351 (Beta) and P.1 (Gamma) variants of SARS-CoV-2 at a population level. We devised a bioinformatics method named COJAC (Co-Occurrence adJusted Analysis and Calling) that uses read pairs carrying multiple variant-specific signature mutations as a robust indicator of low-frequency variants. Application of COJAC revealed that a local outbreak of the Alpha variant in two Swiss cities was observable in wastewater up to 13 d before being first reported in clinical samples. We further confirmed the ability of COJAC to detect emerging variants early for the Delta variant by analysing an additional 1,339 wastewater samples. While sequencing data of single wastewater samples provide limited precision for the quantification of relative prevalence of a variant, we show that replicate and close-meshed longitudinal sequencing allow for robust estimation not only of the local prevalence but also of the transmission fitness advantage of any variant. We conclude that genomic sequencing and our computational analysis can provide population-level estimates of prevalence and fitness of emerging variants from wastewater samples earlier and on the basis of substantially fewer samples than from clinical samples. Our framework is being routinely used in large national projects in Switzerland and the UK.

Facultative multicellular behaviors expand the metabolic capacity and physiological resilience of bacteria. Despite their ubiquity in nature, we lack an understanding of how these behaviors emerge from cellular-scale phenomena. Here, we show how the coupling between growth and resource gradient formation leads to the emergence of multicellular lifecycles in a marine bacterium. Under otherwise carbon-limited growth conditions, Vibrio splendidus 12B01 forms clonal multicellular groups to collectively harvest carbon from soluble polymers of the brown-algal polysaccharide alginate. As they grow, groups phenotypically differentiate into two spatially distinct sub-populations: a static "shell" surrounding a motile, carbon-storing "core." Differentiation of these two sub-populations coincides with the formation of a gradient in nitrogen-source availability within clusters. Additionally, we find that populations of cells containing a high proportion of carbon-storing individuals propagate and form new clusters more readily on alginate than do populations with few carbon-storing cells. Together, these results suggest that local metabolic activity and differential partitioning of resources leads to the emergence of reproductive cycles in a facultatively multicellular bacterium.

Correct species identification and description are fundamental to understand the health status of marine ecosystems. The use of a single identification tool for species distinction may lead to species misidentifications, having major consequences for ecological studies. In the present research, we used an integrative taxonomic approach to identify benthic decapods belonging to the genera of Galathea Fabricius, 1793 and Eualus Thallwitz, 1891, collected in the Mediterranean Sea. 23 Galathea and 22 Eualus individuals were morphologically analyzed and sequenced at the mitochondrial COI gene to confirm their identity using the BOLD Identification Engine. Morphological identification revealed the presence of two Galathea and three Eualus species, while species delimitation based on DNA barcoding of COI sequences strongly suggested the presence of three Galathea and four Eualus species. Molecular analyses suggested the potential presence of two still undescribed species: one cryptic to Galathea squamifera and one cryptic to Galathea intermedia. Contrasting results obtained via morphological identification and the BOLD Identification Engine impeded the recognition of Eualus specimens and suggested misidentifications among BOLD reference records of Eualus cranchii, Eualus occultus, and Eualus pusiolus. These results demonstrated that morphological identification overlooks cryptic species and that misidentifications may occur, highlighting the importance of using an integrative approach to increase the current taxonomic knowledge of benthic invertebrates.

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.

BACKGROUND: The effective reproductive number, R_e, is a critical indicator to monitor disease dynamics, inform regional and national policies, and estimate the effectiveness of interventions. It describes the average number of new infections caused by a single infectious person through time. To date, R_e estimates are based on clinical data such as observed cases, hospitalizations, and/or deaths. These estimates are temporarily biased when clinical testing or reporting strategies change.
OBJECTIVES: We show that the dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater can be used to estimate R_e in near real time, independent of clinical data and without the associated biases.
METHODS: We collected longitudinal measurements of SARS-CoV-2 RNA in wastewater in Zurich, Switzerland, and San Jose, California, USA. We combined this data with information on the temporal dynamics of shedding (the shedding load distribution) to estimate a time series proportional to the daily COVID-19 infection incidence. We estimated a wastewater-based R_e from this incidence.
RESULTS: The method to estimate R_e from wastewater worked robustly on data from two different countries and two wastewater matrices. The resulting estimates were as similar to the R_e estimates from case report data as R_e estimates based on observed cases, hospitalizations, and deaths are among each other. We further provide details on the effect of sampling frequency and the shedding load distribution on the ability to infer R_e.
DISCUSSION: To our knowledge, this is the first time R_e has been estimated from wastewater. This method provides a low-cost, rapid, and independent way to inform SARS-CoV-2 monitoring during the ongoing pandemic and is applicable to future wastewater-based epidemiology targeting other pathogens.

Background: Biocatalysis offers a promising path for plastic waste management and valorization, especially for hydrolysable plastics such as polyethylene terephthalate (PET). Microbial whole-cell biocatalysts for simultaneous PET degradation and growth on PET monomers would offer a one-step solution toward PET recycling or upcycling. We set out to engineer the industry-proven bacterium Pseudomonas putida for (i) metabolism of PET monomers as sole carbon sources, and (ii) efficient extracellular expression of PET hydrolases. We pursued this approach for both PET and the related polyester polybutylene adipate co-terephthalate (PBAT), aiming to learn about the determinants and potential applications of bacterial polyester-degrading biocatalysts.
Results: P. putida was engineered to metabolize the PET and PBAT monomer terephthalic acid (TA) through genomic integration of four tphII operon genes from Comamonas sp. E6. Efficient cellular TA uptake was enabled by a point mutation in the native P. putida membrane transporter MhpT. Metabolism of the PET and PBAT monomers ethylene glycol and 1,4-butanediol was achieved through adaptive laboratory evolution. We then used fast design-build-test-learn cycles to engineer extracellular PET hydrolase expression, including tests of (i) the three PET hydrolases LCC, HiC, and IsPETase; (ii) genomic versus plasmid-based expression, using expression plasmids with high, medium, and low cellular copy number; (iii) three different promoter systems; (iv) three membrane anchor proteins for PET hydrolase cell surface display; and (v) a 30-mer signal peptide library for PET hydrolase secretion. PET hydrolase surface display and secretion was successfully engineered but often resulted in host cell fitness costs, which could be mitigated by promoter choice and altering construct copy number. Plastic biodegradation assays with the best PET hydrolase expression constructs genomically integrated into our monomer-metabolizing P. putida strains resulted in various degrees of plastic depolymerization, although self-sustaining bacterial growth remained elusive.
Conclusion: Our results show that balancing extracellular PET hydrolase expression with cellular fitness under nutrient-limiting conditions is a challenge. The precise knowledge of such bottlenecks, together with the vast array of PET hydrolase expression tools generated and tested here, may serve as a baseline for future efforts to engineer P. putida or other bacterial hosts towards becoming efficient whole-cell polyester-degrading biocatalysts.

Natural microbial communities are phylogenetically and metabolically diverse. In addition to underexplored organismal groups, this diversity encompasses a rich discovery potential for ecologically and biotechnologically relevant enzymes and biochemical compounds. However, studying this diversity to identify genomic pathways for the synthesis of such compounds and assigning them to their respective hosts remains challenging. The biosynthetic potential of microorganisms in the open ocean remains largely uncharted owing to limitations in the analysis of genome-resolved data at the global scale. Here we investigated the diversity and novelty of biosynthetic gene clusters in the ocean by integrating around 10,000 microbial genomes from cultivated and single cells with more than 25,000 newly reconstructed draft genomes from more than 1,000 seawater samples. These efforts revealed approximately 40,000 putative mostly new biosynthetic gene clusters, several of which were found in previously unsuspected phylogenetic groups. Among these groups, we identified a lineage rich in biosynthetic gene clusters (‘Candidatus Eudoremicrobiaceae’) that belongs to an uncultivated bacterial phylum and includes some of the most biosynthetically diverse microorganisms in this environment. From these, we characterized the phospeptin and pythonamide pathways, revealing cases of unusual bioactive compound structure and enzymology, respectively. Together, this research demonstrates how microbiomics-driven strategies can enable the investigation of previously undescribed enzymes and natural products in underexplored microbial groups and environments.

Differences between species promote stable coexistence in a resource-limited environment. These differences can result from interspecies competition leading to character shifts, a process referred to as character displacement. While character displacement is often interpreted as a consequence of genetically fixed trait differences between species, it can also be mediated by phenotypic plasticity in response to the presence of another species. Here, we test whether phenotypic plasticity leads to a shift in proteome allocation during co-occurrence of two bacterial species from the abundant, leaf-colonizing families Sphingomonadaceae and Rhizobiaceae in their natural habitat. Upon mono-colonizing of the phyllosphere, both species exhibit specific and shared protein functions indicating a niche overlap. During co-colonization, quantitative differences in the protein repertoire of both bacterial populations occur as a result of bacterial coexistence in planta. Specifically, the Sphingomonas strain produces enzymes for the metabolization of xylan, while the Rhizobium strain reprograms its metabolism to beta-oxidation of fatty acids fueled via the glyoxylate cycle and adapts its biotin acquisition. We demonstrate the conditional relevance of cross-species facilitation by mutagenesis leading to loss of fitness in competition in planta. Our results show that dynamic character displacement and niche facilitation mediated by phenotypic plasticity can contribute to species coexistence.

Oxygenations of aromatic soil and water contaminants with molecular O₂ catalyzed by Rieske dioxygenases are frequent initial steps of biodegradation in natural and engineered environments. Many of these non-heme ferrous iron enzymes are known to be involved in contaminant metabolism, but the understanding of enzyme-substrate interactions that lead to successful biodegradation is still elusive. Here, we studied the mechanisms of O₂ activation and substrate hydroxylation of two nitroarene dioxygenases to evaluate enzyme- and substrate-specific factors that determine the efficiency of oxygenated product formation. Experiments in enzyme assays of 2-nitrotoluene dioxygenase (2NTDO) and nitrobenzene dioxygenase (NBDO) with methyl-, fluoro-, chloro-, and hydroxy-substituted nitroaromatic substrates reveal that typically 20-100% of the enzyme's activity involves unproductive paths of O₂ activation with generation of reactive oxygen species through so-called O₂ uncoupling. The ¹⁸O and ¹³C kinetic isotope effects of O₂ activation and nitroaromatic substrate hydroxylation, respectively, suggest that O₂ uncoupling occurs after generation of Fe^III-(hydro)peroxo species in the catalytic cycle. While 2NTDO hydroxylates ortho-substituted nitroaromatic substrates more efficiently, NBDO favors meta-substituted, presumably due to distinct active site residues of the two enzymes. Our data implies, however, that the O₂ uncoupling and hydroxylation activity cannot be assessed from simple structure-reactivity relationships. By quantifying O₂ uncoupling by Rieske dioxygenases, our work provides a mechanistic link between contaminant biodegradation, the generation of reactive oxygen species, and possible adaptation strategies of microorganisms to the exposure of new contaminants.

Experimental and numerical approaches have their own advantages and limitations, in particular, when dealing with complex phenomena such as snow particles falling at moderate Reynolds numbers (Re). Time-resolved, three-dimensional particle tracking velocimetry (4D-PTV) experiments of free-falling, three-dimensional (3D)-printed snowflakes' analogs shed light on the elaborate falling dynamics of irregular snow particles but present a lower resolution (tracer seeding density) and a limited field of view (domain size) to fully capture the wake flow. Delayed-detached eddy simulations of fixed snow particles do not realistically represent all the physics of a falling ice particle, especially for cases with unsteady falling attitudes, but accurately predict the drag coefficient and capture the wake characteristics for steadily falling snowflakes. In this work, we compare both approaches on time- and space-averaged flow quantities in the snowflake wake. First, we cross validate the two approaches for low Re cases, where close agreement of the wake features is expected, and second, we assess how strongly the unsteady falling motion perturbs the average wake pattern as compared to a fixed particle at higher Re. For steadily falling snowflakes, the fixed-particle model can properly represent the wake flow with errors within the experimental uncertainty (±15%). At moderate/high Re (unsteady falling motion), larger differences are present. Applying a co-moving frame to the experimental data to account for the particle movement or filtering the numerical data on larger grids reduces these differences only to some extent, implying that an unsteady fall significantly alters the average wake structure as compared to a fixed particle model.

Rieske dioxygenases catalyze the initial steps in the hydroxylation of aromatic compounds and are critical for the metabolism of xenobiotic substances. Because substrates do not bind to the mononuclear non-heme Fe^II center, elementary steps leading to O₂ activation and substrate hydroxylation are difficult to delineate, thus making it challenging to rationalize divergent observations on enzyme mechanisms, reactivity, and substrate specificity. Here, we show for nitrobenzene dioxygenase, a Rieske dioxygenase capable of transforming nitroarenes to nitrite and substituted catechols, that unproductive O₂ activation with the release of the unreacted substrate and reactive oxygen species represents an important path in the catalytic cycle. Through correlation of O₂ uncoupling for a series of substituted nitroaromatic compounds with ¹⁸O and ¹³C kinetic isotope effects of dissolved O₂ and aromatic substrates, respectively, we show that O₂ uncoupling occurs after the rate-limiting formation of Fe^III-(hydro)peroxo species from which substrates are hydroxylated. Substituent effects on the extent of O₂ uncoupling suggest that the positioning of the substrate in the active site rather than the susceptibility of the substrate for attack by electrophilic oxygen species is responsible for unproductive O₂ uncoupling. The proposed catalytic cycle provides a mechanistic basis for assessing the very different efficiencies of substrate hydroxylation vs unproductive O₂ activation and generation of reactive oxygen species in reactions catalyzed by Rieske dioxygenases.

The prevalence of fecal colonization with extended-spectrum β-lactamase-producing Escherichia coli (ESBL-Ec) among children in low- and middle-income countries is alarmingly high. This study aimed to identify the sources of ESBL-Ec colonization in children < 1 year old through comparative analysis of E. coli isolates from child stool, child's mother stool, and point-of-use drinking water from 46 rural households in Bangladesh. The pairwise similarity in antibiotic susceptibility of E. coli from all three sources was evaluated, followed by phylogenetic clustering using enterobacterial repetitive intergenic consensus polymerase chain reaction and whole-genome sequence analysis of the isolates. Matching antibiotic susceptibility and enterobacterial repetitive intergenic consensus polymerase chain reaction patterns were found among ESBL-Ec isolates from child–mother dyads of 24 and 11 households, respectively, from child–water dyads of 5 and 4 households, respectively, and from child–mother–water triads of 3 and 4 households, respectively. Whole-genome sequence analysis of 30 isolates from 10 households revealed that ESBL-Ec from children in five households (50%) was clonally related to ESBL-Ec either from their mothers (2 households), drinking water sources (2 households), or both mother and drinking-water sources (1 household) based on serotype, phylogroup, sequence type, antibiotic resistance genes, mobile genetic elements, core single-nucleotide polymorphisms, and whole-genome multilocus sequence typing. Overall, this study provides empirical evidence that ESBL-Ec colonization in children is linked to the colonization status of mothers and exposure to the household environments contaminated with ESBL-Ec. Interventions such as improved hygiene practices and a safe drinking water supply may help reduce the transmission of ESBL-Ec at the household level.

Cyanuric acid (CYA) is used commercially for maintaining active chlorine to inactivate microbial and viral pathogens in swimming pools and hot tubs. Repeated CYA addition can cause a lack of available chlorine and adequate disinfection. Acceptable CYA levels can potentially be restored via cyanuric acid hydrolases (CAH), enzymes that hydrolyze CYA to biuret under mild conditions. Here we describe a previously unknown CAH enzyme from Pseudolabrys sp. Root1462 (CAH-PR), mined from public databases by bioinformatic analysis of potential CAH genes, which we show to be suitable in a cell-free form for industrial applications based upon favorable enzymatic and physical properties, combined with high-yield expression in aerobic cell culture. The kinetic parameters and modeled structure were similar to known CAH enzymes, but the new enzyme displayed a surprising thermal and storage stability. The new CAH enzyme was applied, following addition of inexpensive sodium sulfite, to hydrolyze CYA to biuret. At the desired endpoint, hypochlorite addition inactivated remaining enzyme and oxidized biuret to primarily dinitrogen and carbon dioxide gases. The mechanism of biuret oxidation with hypochlorite under conditions relevant to recreational pools is described.

Healthy development of the gut microbiome provides long-term health benefits. Children raised in countries with high infectious disease burdens are frequently exposed to diarrhoeal pathogens and antibiotics, which perturb gut microbiome assembly. A recent cluster-randomized trial leveraging >4,000 child observations in Dhaka, Bangladesh, found that automated water chlorination of shared taps effectively reduced child diarrhoea and antibiotic use. In this substudy, we leveraged stool samples collected from 130 children 1 year after chlorine doser installation to examine differences between treatment and control children's gut microbiota. Water chlorination was associated with increased abundance of several bacterial genera previously linked to improved gut health; however, we observed no effects on the overall richness or diversity of taxa. Several clinically relevant antibiotic resistance genes were relatively more abundant in the gut microbiome of treatment children, possibly due to increases in Enterobacteriaceae. While further studies on the long-term health impacts of drinking chlorinated water would be valuable, we conclude that access to chlorinated water did not substantially impact child gut microbiome development in this setting, supporting the use of chlorination to increase global access to safe drinking water.

BackgroundThroughout the COVID-19 pandemic, SARS-CoV-2 genetic variants of concern (VOCs) have repeatedly and independently arisen. VOCs are characterised by increased transmissibility, increased virulence or reduced neutralisation by antibodies obtained from prior infection or vaccination. Tracking the introduction and transmission of VOCs relies on sequencing, typically whole genome sequencing of clinical samples. Wastewater surveillance is increasingly used to track the introduction and spread of SARS-CoV-2 variants through sequencing approaches.AimHere, we adapt and apply a rapid, high-throughput method for detection and quantification of the relative frequency of two deletions characteristic of the Alpha, Beta, and Gamma VOCs in wastewater.MethodsWe developed drop-off RT-dPCR assays and an associated statistical approach implemented in the R package WWdPCR to analyse temporal dynamics of SARS-CoV-2 signature mutations (spike Δ69-70 and ORF1a Δ3675-3677) in wastewater and quantify transmission fitness advantage of the Alpha VOC.ResultsBased on analysis of Zurich wastewater samples, the estimated transmission fitness advantage of SARS-CoV-2 Alpha based on the spike Δ69-70 was 0.34 (95% confidence interval (CI): 0.30-0.39) and based on ORF1a Δ3675-3677 was 0.53 (95% CI: 0.49-0.57), aligning with the transmission fitness advantage of Alpha estimated by clinical sample sequencing in the surrounding canton of 0.49 (95% CI: 0.38-0.61).ConclusionDigital PCR assays targeting signature mutations in wastewater offer near real-time monitoring of SARS-CoV-2 VOCs and potentially earlier detection and inference on transmission fitness advantage than clinical sequencing.

When stay-at-home orders were issued to slow the spread of COVID-19, building occupancy (and water demand) was drastically decreased in many buildings. There was concern that widespread low water demand may cause unprecedented Legionella occurrence and Legionnaires' disease incidence. In lieu of evidenced-based guidance, many people flushed their water systems as a preventative measure, using highly variable practices. Here, we present field-scale research from a building before, during, and after periods of low occupancy, and controlled stagnation experiments. We document no change, a > 4-log increase, and a > 1.5-log decrease of L. pneumophila during 3- to 7-week periods of low water demand. L. pneumophila increased by > 1-log after precautionary flushing prior to reoccupancy, which was repeated in controlled boiler flushing experiments. These results demonstrate that the impact of low water demand (colloquially called stagnation) is not as straight forward as is generally assumed, and that some flushing practices have potential unintended consequences. In particular, stagnation must be considered in context with other Legionella growth factors like temperature and flow profiles. Boiler flushing practices that dramatically increase the flow rate and rapidly deplete boiler temperature may mobilize Legionella present in biofilms and sediment.

Private wells can become contaminated with waterborne pathogens during flooding events; however, testing efforts focus almost exclusively on fecal indicator bacteria. Opportunistic pathogens (OPs), which are the leading cause of identified waterborne disease in the United States, are understudied in private wells. We conducted a quantitative polymerase chain reaction survey of Legionella spp., L. pneumophila, Mycobacterium spp., M. avium, Naegleria fowleri, and shiga toxin-producing Escherichia coli gene markers and total coliform and E. coli in drinking water supplied by private wells following the Louisiana Floods (2016), Hurricane Harvey (2017), Hurricane Irma (2017), and Hurricane Florence (2018). Self-reported well characteristics and recovery status were collected via questionnaires. Of the 211 water samples collected, 40.3% and 5.2% were positive for total coliform and E. coli, which were slightly elevated positivity rates compared to prior work in coastal aquifers. DNA markers for Legionella and Mycobacterium were detected in 54.5% and 36.5% of samples, with L. pneumophila and M. avium detected in 15.6% and 17.1%, which was a similar positivity rate relative to municipal system surveys. Total bacterial 16S rRNA gene copies were positively associated with Legionella and Mycobacterium, indicating that conditions that favor occurrence of general bacteria can also favor OPs. N. fowleri DNA was detected in 6.6% of samples and was the only OP that was more prevalent in submerged wells compared to non-submerged wells. Self-reported well characteristics were not associated with OP occurrence. This study exposes the value of routine baseline monitoring and timely sampling after flooding events in order to effectively assess well water contamination risks.

Microbes are social organisms that commonly live in sessile biofilms. Spatial patterns of populations within biofilms can be important determinants of community-level properties. Spatial intermixing emerging from microbial interaction is one of the best-studied characteristics of spatial patterns. The specific levels of spatial intermixing critically contribute to how the dynamics and functioning of such communities are governed. However, the precise factors that determine spatial patterns and intermixing remain unclear. Here, we investigated the spatial patterning and intermixing of an engineered synthetic consortium composed of two mutualistic Pseudomonas stutzeri strains that degrade salicylate via metabolic cross-feeding. We found that the consortium self-organizes across space to form a previously unreported spatial pattern (here referred to as a 'bubble-burst' pattern) that exhibits a low level of intermixing. Interestingly, when the genes encoding type IV pili were deleted from both strains, a highly intermixed spatial pattern developed and increased the productivity of the entire community. The intermixed pattern was maintained in a robust manner across a wide range of initial ratios between the two strains. Our findings show that the type IV pilus plays a role in mitigating spatial intermixing of different populations in surface-attached microbial communities, with consequences for governing community-level properties. These insights provide tangible clues for the engineering of synthetic microbial systems that perform highly in spatially structured environments.

Risk-based water safety interventions are one approach to improve drinking water quality and consequently reduce the number of people consuming faecally contaminated water. Despite broad acceptance of water safety planning approaches globally, there is a lack of evidence of their effectiveness for community-managed piped water supplies in rural areas of developing countries. Our research, in the form of a cluster-based controlled pre-post intervention analysis, investigated the impact of a combined water safety intervention on outcomes of microbial water quality, users' perceptions and piped system functionality in rural Nepal. The study enrolled 21 treatment systems and 12 control systems across five districts of the Karnali and Sudurpaschim provinces. Treatment group interventions included field laboratories for microbial analysis, regular monitoring of water quality including sanitary inspections, targeted treatment and infrastructure improvements, household hygiene and water filter promotion, and community training. In certain systems, regular system-level chlorination was implemented. Before and after the interventions, the microbial water quality was measured at multiple points within the water system. This information was complemented by household interviews and sanitary inspections. The main result to emerge from this study is that chlorination is the only identified intervention that led to a significant reduction in E. coli concentration at the point of consumption. Secondly, the effectiveness of other interventions was presumably reduced due to higher contamination at endline in general, brought about by the monsoon. All the interventions had a positive impact on users' perceptions about their water system, as measured by expectations for future functionality, satisfaction with the services received, and awareness of the potential health risks of drinking contaminated water. For future applications we would recommend the more broadly applied use of chlorination methods at system level as a key component of the package of risk-based water safety interventions.

Phototrophic biofilms form complex spatial patterns in streams and rivers, yet, how community patchiness, structure and function are coupled and contribute to larger-scale metabolism remains unkown. Here, we combined optical coherence tomography with automated O2 microprofiling and amplicon sequencing in a flume experiment to show how distinct community patches interact with the hydraulic environment and how this affects the internal distribution of oxygen. We used numerical simulations to derive rates of community photosynthetic activity and respiration at the patch scale and use the obtained parameter to upscale from individual patches to the larger biofilm landscape. Our biofilm landscape approach revealed evidence of parallels in the structure-function coupling between phototrophic biofilms and their streambed habitat.

Spatial self-organization is a hallmark of surface-associated microbial communities that is governed by local environmental conditions and further modified by interspecific interactions. Here, we hypothesize that spatial patterns of microbial cell-types can stabilize the composition of cross-feeding microbial communities under fluctuating environmental conditions. We tested this hypothesis by studying the growth and spatial self-organization of microbial co-cultures consisting of two metabolically interacting strains of the bacterium Pseudomonas stutzeri. We inoculated the co-cultures onto agar surfaces and allowed them to expand (i.e. range expansion) while fluctuating environmental conditions that alter the dependency between the two strains. We alternated between anoxic conditions that induce a mutualistic interaction and oxic conditions that induce a competitive interaction. We observed co-occurrence of both strains in rare and highly localized clusters (referred to as “spatial jackpot events”) that persist during environmental fluctuations. To resolve the underlying mechanisms for the emergence of spatial jackpot events, we used a mechanistic agent-based mathematical model that resolves growth and dispersal at the scale relevant to individual cells. While co-culture composition varied with the strength of the mutualistic interaction and across environmental fluctuations, the model provides insights into the formation of spatially resolved substrate landscapes with localized niches that support the co-occurrence of the two strains and secure co-culture function. This study highlights that in addition to spatial patterns that emerge in response to environmental fluctuations, localized spatial jackpot events ensure persistence of strains across dynamic conditions.

Lipopeptides represent a large group of microbial natural products that include important antibacterial and antifungal drugs and some of the most-powerful known biosurfactants. The vast majority of lipopeptides comprise cyclic peptide backbones N-terminally equipped with various fatty acyl moieties. The known compounds of this type are biosynthesized by nonribosomal peptide synthetases, giant enzyme complexes that assemble their products in a non-gene-encoded manner. Here, we report the genome-guided discovery of ribosomally derived, fatty-acylated lipopeptides, termed selidamides. Heterologous reconstitution of three pathways, two from cyanobacteria and one from an arctic, ocean-derived alphaproteobacterium, allowed structural characterization of the probable natural products and suggest that selidamides are widespread over various bacterial phyla. The identified representatives feature cyclic peptide moieties and fatty acyl units attached to (hydroxy)ornithine or lysine side chains by maturases of the GCN5-related N-acetyltransferase superfamily. In contrast to nonribosomal lipopeptides that are usually produced as congener mixtures, the three selidamides are selectively fatty acylated with C₁₀, C₁₂, or C₁₆ fatty acids, respectively. These results highlight the ability of ribosomal pathways to emulate products with diverse, nonribosomal-like features and add to the biocatalytic toolbox for peptide drug improvement and targeted discovery.

Due to increasing nitrogen (N) deposition from the atmosphere, temperate forests are progressively becoming phosphorus (P) limited. Trees take up P mainly from the soil solution, which soil microorganisms can replenish by mineralizing organic P through enzymatic hydrolysis (e.g. using phosphatases). We investigated how bacterial (including phosphatase harboring bacteria) and fungal communities in organic horizons with contrasting nutrient status respond within months to changes in soil N and P concentrations. A field experiment with water-soluble N (NH₄NO₃) and P (KH₂PO₄) additions was conducted at a high-P and a low-P beech (Fagus sylvatica L.) forest site in Germany. Bacterial (16S rRNA), fungal (ITS), and alkaline (phoD) and acid (acpA) phosphatase harboring community structure was investigated by molecular fingerprinting. Bacterial and fungal community structure was mainly related to available P (resin P) in the high-P site but related to more stable P pools (sequentially extracted NaOH/EDTA P) and total P in the low-P site. The increased importance of strategies to access more stable P forms in the low-P site was reflected by a higher relative abundance of some dominant alkaline phosphatase harboring taxa. In the high-P site, increased available P following P addition was the main influencing factor on community structure. By contrast, in the low-P site predominantly N addition induced differences in the microbial communities, which was linked to decreased P concentrations in several soil pools. Increasing N deposition might thus pose greater impacts on microbial communities in low-P compared to high-P sites, by further increasing the already high competition for P. Our findings illustrate that the soil P status in the organic horizon can shape the structure of microbial communities and their roles in the P cycle.

Transformation studies of chlorinated paraffins (CPs) and the effects of CP transformation products on humans, biota and environment are rare. The focus here is on hydroxylation reactions. As for polyhalogenated persistent organic pollutants (POPs) in general, hydroxylation reactions convert lipophilic material to more polar compounds with increased mobility. We investigated the in-vitro transformation of single-chain CP-mixtures to hydroxylated products with the dehalogenase LinB from Sphingobium indicum. C₁₁-, C₁₂- and C₁₃-single-chain CP-homologues were exposed to LinB and mono-hydroxylated (CP-ols) and di-hydroxylated (CP-diols) transformation products were formed. Liquid-chromatography coupled to mass-spectrometry (LC-MS) was used to detect hydroxylated products and to separate them from the starting material. The presented data can be used to identify these CP-ol and CP-diol homologues in other samples. Hydroxylated products had lower chlorination degrees (n_Cl) than respective CP-starting-materials. Reactive and persistent CP-material was found in each homologue group. Reactive material is converted within hours by LinB, while more persistent CPs are transformed within days. Homologue-specific kinetic models were established to simulate the stepwise hydroxylation of persistent CPs to mono- and di-hydroxylated products. First-order rate constants for the formation of CP-ols (k₁) and CP-diols (k₂) were deduced for different homologues. Lower-chlorinated CP-ols did not accumulate to large extent and were transformed quickly to CP-diols, while higher-chlorinated CP-ols and -diols both accumulated. By enzymatic transformation of single-chain CPs with LinB, we synthesized unique sets of mono- and di-hydroxylated materials, which can be used as analytical standards and as starting materials for metabolic, toxicity and environmental fate studies.

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.

Cell attachment onto electrode-forming biocathodes is a promising alternative to expensive catalysts used for electricity production in bioelectrochemical systems (BESs). Though BESs have been extensively studied for decades, the processes, underlying mechanisms, and determinant driving forces of microalgal biocathode formation remain largely unknown. In this study, we employed a model unicellular motile microalga, Chlamydomonas microsphaera, to investigate the microalgal attachment processes onto the electrode surface of a BES and to identify the determinant factors. Results showed that the initial attachment of C. micrrosphaera cells is determined by the applied external voltage rather than nutrient availability and occurs via electrotaxis-mediated cell motility. The subsequent development of the C. microsphaera biofilm is then increasingly determined by nutrient availability. Our results revealed that, in the absence of an external voltage, nutrient availability remains a dominant factor controlling the fate of the microalgal surface attachment and subsequent biofilm formation processes. Thus, our results show that electrotactic and chemotactic movements are crucial to facilitate the initial attachment and subsequent biofilm formation of C. microsphaera onto the electrode surfaces of BES. This study provides new insights into the mechanisms of microalgal surface attachment and biofilm formation processes on microalgal biocathodes, which hold great promise for improving the electrochemical properties of cathodes.

Organisms throughout the tree of life accumulate chemical resources, in particular forms or compartments, to secure their availability for future use. Here we review microbial storage and its ecological significance by assembling several rich but disconnected lines of research in microbiology, biogeochemistry, and the ecology of macroscopic organisms. Evidence is drawn from various systems, but we pay particular attention to soils, where microorganisms play crucial roles in global element cycles. An assembly of genus-level data demonstrates the likely prevalence of storage traits in soil. We provide a theoretical basis for microbial storage ecology by distinguishing a spectrum of storage strategies ranging from surplus storage (storage of abundant resources that are not immediately required) to reserve storage (storage of limited resources at the cost of other metabolic functions). This distinction highlights that microorganisms can invest in storage at times of surplus and under conditions of scarcity. We then align storage with trait-based microbial life-history strategies, leading to the hypothesis that ruderal species, which are adapted to disturbance, rely less on storage than microorganisms adapted to stress or high competition. We explore the implications of storage for soil biogeochemistry, microbial biomass, and element transformations and present a process-based model of intracellular carbon storage. Our model indicates that storage can mitigate against stoichiometric imbalances, thereby enhancing biomass growth and resource-use efficiency in the face of unbalanced resources. Given the central roles of microbes in biogeochemical cycles, we propose that microbial storage may be influential on macroscopic scales, from carbon cycling to ecosystem stability.

It has been a landmark year for artificial intelligence (AI) and biotechnology. Perhaps the most noteworthy of these advances was Google DeepMind's AlphaFold2 algorithm which smashed records in protein structure prediction (Jumper et al., 2021, Nature, 596, 583) complemented by progress made by other research groups around the globe (Baek et al., 2021, Science, 373, 871; Zheng et al., 2021, Proteins). For the first time in history, AI achieved protein structure models rivalling the accuracy of experimentally determined structures. The power of accurate protein structure prediction at our fingertips has countless implications for drug discovery, de novo protein design and fundamental research in chemical biology. While acknowledging the significance of these breakthroughs, this perspective aims to cut through the hype and examine some key limitations using AlphaFold2 as a lens to consider the broader implications of AI for microbial biotechnology for the next 15 years and beyond.