Is it selfish to be filamentous in biofilms? Individual-based modeling links microbial growth strategies with morphology using the new and modular iDynoMiCS 2.0.

Microbial communities are found in all habitable environments and often occur in assemblages with self-organized spatial structures developing over time. This complexity can only be understood, predicted, and managed by combining experiments with mathematical modeling. Individual-based models are particularly suited if individual heterogeneity, local interactions, and adaptive behavior are of interest. Here we present the completely overhauled software platform, the individual-based Dynamics of Microbial Communities Simulator, iDynoMiCS 2.0, which enables researchers to specify a range of different models without having to program. Key new features and improvements are: (1) Substantially enhanced ease of use (graphical user interface, editor for model specification, unit conversions, data analysis and visualization and more). (2) Increased performance and scalability enabling simulations of up to 10 million agents in 3D biofilms. (3) Kinetics can be specified with any arithmetic function. (4) Agent properties can be assembled from orthogonal modules for pick and mix flexibility. (5) Force-based mechanical interaction framework enabling attractive forces and non-spherical agent morphologies as an alternative to the shoving algorithm. The new iDynoMiCS 2.0 has undergone intensive testing, from unit tests to a suite of increasingly complex numerical tests and the standard Benchmark 3 based on nitrifying biofilms. A second test case was based on the "biofilms promote altruism" study previously implemented in BacSim because competition outcomes are highly sensitive to the developing spatial structures due to positive feedback between cooperative individuals. We extended this case study by adding morphology to find that (i) filamentous bacteria outcompete spherical bacteria regardless of growth strategy and (ii) non-cooperating filaments outcompete cooperating filaments because filaments can escape the stronger competition between themselves. In conclusion, the new substantially improved iDynoMiCS 2.0 joins a growing number of platforms for individual-based modeling of microbial communities with specific advantages and disadvantages that we discuss, giving users a wider choice.

Plasmid permissiveness of wastewater microbiomes can be predicted from 16S rRNA sequences by machine learning.

MOTIVATION: Wastewater treatment plants (WWTPs) harbor a dense and diverse microbial community. They constantly receive antimicrobial residues and resistant strains, and therefore provide conditions for horizontal gene transfer (HGT) of antimicrobial resistance (AMR) determinants. This facilitates the transmission of clinically important genes between, e.g. enteric and environmental bacteria, and vice versa. Despite the clinical importance, tools for predicting HGT remain underdeveloped. RESULTS: In this study, we examined to which extent water cycle microbial community composition, as inferred by partial 16S rRNA gene sequences, can predict plasmid permissiveness, i.e. the ability of cells to receive a plasmid through conjugation, based on data from standardized filter mating assays using fluorescent bio-reporter plasmids. We leveraged a range of machine learning models for predicting the permissiveness for each taxon in the community, representing the range of hosts a plasmid is able to transfer to, for three broad host-range resistance IncP plasmids (pKJK5, pB10, and RP4). Our results indicate that the predicted permissiveness from the best performing model (random forest) showed a moderate-to-strong average correlation of 0.49 for pB10 [95% confidence interval (CI): 0.44-0.55], 0.43 for pKJK5 (0.95% CI: 0.41-0.49), and 0.53 for RP4 (0.95% CI: 0.48-0.57) with the experimental permissiveness in the unseen test dataset. Predictive phylogenetic signals occurred despite the broad host-range nature of these plasmids. Our results provide a framework that contributes to the assessment of the risk of AMR pollution in wastewater systems. AVAILABILITY AND IMPLEMENTATION: The predictive tool is available as an application at https://github.com/DaneshMoradigaravand/PlasmidPerm.

Flagellar interference with plasmid uptake in biofilms: a joint experimental and modeling study.

Plasmid conjugation is a key facilitator of horizontal gene transfer (HGT), and plasmids encoding antibiotic resistance drive the increasing prevalence of antibiotic resistance. In natural, engineered, and clinical environments, bacteria often grow in protective biofilms. Therefore, a better understanding of plasmid transfer in biofilms is needed. Our aim was to investigate plasmid transfer in a biofilm-adapted wrinkly colony mutant of Xanthomonas retroflexus (XRw) with enhanced matrix production and reduced motility. We found that XRw biofilms had an increased uptake of the broad host-range IncP-1ϵ plasmid pKJK5 compared to the wild type (WT). Proteomics revealed fewer flagellar-associated proteins in XRw, suggesting that flagella were responsible for reducing plasmid uptake. This was confirmed by the higher plasmid uptake of non-flagellated fliM mutants of the X. retroflexus wrinkly mutant as well as the wild type. Moreover, testing several flagellar mutants of Pseudomonas putida suggested that the flagellar effect was more general. We identified seven mechanisms with the potential to explain the flagellar effect and simulated them in an individual-based model. Two mechanisms could thus be eliminated (increased distances between cells and increased lag times due to flagella). Another mechanism identified as viable in the modeling was eliminated by further experiments. The possibility of steric hindrance of pilus movement and binding by flagella, reducing the frequency of contact and thus plasmid uptake, proved viable, and the three other viable mechanisms had a reduced probability of plasmid transfer in common. Our findings highlight the important yet complex effects of flagella during bacterial conjugation in biofilms.IMPORTANCEBiofilms are the dominant form of microbial life and bacteria living in biofilms are markedly different from their planktonic counterparts, yet the impact of the biofilm lifestyle on horizontal gene transfer (HGT) is still poorly understood. Horizontal gene transfer by conjugative plasmids is a major driver in bacterial evolution and adaptation, as exemplified by the troubling spread of antibiotic resistance. To either limit or promote plasmid prevalence and dissemination, we need a better understanding of plasmid transfer between bacterial cells, especially in biofilms. Here, we identified a new factor impacting the transfer of plasmids, flagella, which are required for many types of bacterial motility. We show that their absence or altered activity can lead to enhanced plasmid uptake in two bacterial species, Xanthomonas retroflexus and Pseudomonas putida. Moreover, we demonstrate the utility of mathematical modeling to eliminate hypothetical mechanisms.

Experimental evolution of Pseudomonas putida under silver ion versus nanoparticle stress.

Whether the antibacterial properties of silver nanoparticles (AgNPs) are simply due to the release of silver ions (Ag+ ) or, additionally, nanoparticle-specific effects, is not clear. We used experimental evolution of the model environmental bacterium Pseudomonas putida to ask whether bacteria respond differently to Ag+ or AgNP treatment. We pre-evolved five cultures of strain KT2440 for 70 days without Ag to reduce confounding adaptations before dividing the fittest pre-evolved culture into five cultures each, evolving in the presence of low concentrations of Ag+ , well-defined AgNPs or Ag-free controls for a further 75 days. The mutations in the Ag+ or AgNP evolved populations displayed different patterns that were statistically significant. The non-synonymous mutations in AgNP-treated populations were mostly associated with cell surface proteins, including cytoskeletal membrane protein (FtsZ), membrane sensor and regulator (EnvZ and GacS) and periplasmic protein (PP_2758). In contrast, Ag+ treatment was selected for mutations linked to cytoplasmic proteins, including metal ion transporter (TauB) and those with metal-binding domains (ThiL and PP_2397). These results suggest the existence of AgNP-specific effects, either caused by sustained delivery of Ag+ from AgNP dissolution, more proximate delivery from cell-surface bound AgNPs, or by direct AgNP action on the cell's outer membrane.

Predation Strategies of the Bacterium Bdellovibrio bacteriovorus Result in Overexploitation and Bottlenecks.

With increasing antimicrobial resistance, alternatives for treating infections or removing resistant bacteria are urgently needed, such as the bacterial predator Bdellovibrio bacteriovorus or bacteriophage. Therefore, we need to better understand microbial predator-prey dynamics. We developed mass-action mathematical models of predation for chemostats, which capture the low substrate concentration and slow growth typical for intended application areas of the predators such as wastewater treatment, aquaculture, or the gut. Our model predicted that predator survival required a minimal prey cell size, explaining why Bdellovibrio is much smaller than its prey. A predator considered to be "too good" (attack rate too high, mortality too low) overexploited its prey, leading to extinction (tragedy of the commons). Surprisingly, a predator taking longer to produce more offspring outcompeted a predator producing fewer offspring more rapidly (rate versus yield trade-off). Predation was only efficient in a narrow region around optimal parameters. Moreover, extreme oscillations under a wide range of conditions led to severe bottlenecks. These could be avoided when two prey species became available in alternating seasons. A bacteriophage outcompeted Bdellovibrio due to its higher burst size and faster life cycle. Together, results suggest that Bdellovibrio would struggle to survive on a single prey, explaining why it must be a generalist predator and suggesting it is better suited than phage to environments with multiple prey. IMPORTANCE The discovery of antibiotics led to a dramatic drop in deaths due to infectious disease. Increasing levels of antimicrobial resistance, however, threaten to reverse this progress. There is thus a need for alternatives, such as therapies based on phage and predatory bacteria that kill bacteria regardless of whether they are pathogens or resistant to antibiotics. To best exploit them, we need to better understand what determines their effectiveness. By using a mathematical model to study bacterial predation in realistic slow growth conditions, we found that the generalist predator Bdellovibrio is most effective within a narrow range of conditions for each prey. For example, a minimum prey cell size is required, and the predator should not be "too good," as this would result in overexploitation risking extinction. Together these findings give insights into the ecology of microbial predation and help explain why Bdellovibrio needs to be a generalist predator.

Dual Predation by Bacteriophage and Bdellovibrio bacteriovorus Can Eradicate Escherichia coli Prey in Situations where Single Predation Cannot.

Bacteria are preyed upon by diverse microbial predators, including bacteriophage and predatory bacteria, such as Bdellovibrio bacteriovorus While bacteriophage are used as antimicrobial therapies in Eastern Europe and are being applied for compassionate use in the United States, predatory bacteria are only just beginning to reveal their potential therapeutic uses. However, predation by either predator type can falter due to different adaptations arising in the prey bacteria. When testing poultry farm wastewater for novel Bdellovibrio isolates on Escherichia coli prey lawns, individual composite plaques were isolated containing both an RTP (rosette-tailed-phage)-like-phage and a B. bacteriovorus strain and showing central prey lysis and halos of extra lysis. Combining the purified phage with a lab strain of B. bacteriovorus HD100 recapitulated haloed plaques and increased killing of the E. coli prey in liquid culture, showing an effective side-by-side action of these predators compared to their actions alone. Using approximate Bayesian computation to select the best fitting from a variety of different mathematical models demonstrated that the experimental data could be explained only by assuming the existence of three prey phenotypes: (i) sensitive to both predators, (ii) genetically resistant to phage only, and (iii) plastic resistant to B. bacteriovorus only. Although each predator reduces prey availability for the other, high phage numbers did not abolish B. bacteriovorus predation, so both predators are competent to coexist and are causing different selective pressures on the bacterial surface while, in tandem, controlling prey bacterial numbers efficiently. This suggests that combinatorial predator therapy could overcome problems of phage resistance.IMPORTANCE With increasing levels of antibiotic resistance, the development of alternative antibacterial therapies is urgently needed. Two potential alternatives are bacteriophage and predatory bacteria. Bacteriophage therapy has been used, but prey/host specificity and the rapid acquisition of bacterial resistance to bacteriophage are practical considerations. Predatory bacteria are of interest due to their broad Gram-negative bacterial prey range and the lack of simple resistance mechanisms. Here, a bacteriophage and a strain of Bdellovibrio bacteriovorus, preyed side by side on a population of E. coli, causing a significantly greater decrease in prey numbers than either alone. Such combinatorial predator therapy may have greater potential than individual predators since prey surface changes selected for by each predator do not protect prey against the other predator.

Reducing discrepancies between 3D and 2D simulations due to cell packing density.

Modelling all three spatial dimensions is often much more computationally expensive than modelling a two-dimensional simplification of the same system. Researchers comparing these approaches in individual-based models of microbial biofilms report quantitative, but not qualitative, differences between 2D and 3D simulations. We show that a large part of the discrepancy is due to the different space packing densities of circles versus spheres, and demonstrate methods to compensate for this: the internal density of individuals or the distances between them can be scaled. This result is likely to be useful in similar models, such as smoothed particle hydrodynamics.

α-1-antitrypsin variants and the proteinase/antiproteinase imbalance in chronic obstructive pulmonary disease.

The excessive activities of the serine proteinases neutrophil elastase and proteinase 3 are associated with tissue damage in chronic obstructive pulmonary disease. Reduced concentrations and/or inhibitory efficiency of the main circulating serine proteinase inhibitor α-1-antitrypsin result from point mutations in its gene. In addition, α-2-macroglobulin competes with α-1-antitrypsin for proteinases, and the α-2-macroglobulin-sequestered enzyme can retain its catalytic activity. We have studied how serine proteinases partition between these inhibitors and the effects of α-1-antitrypsin mutations on this partitioning. Subsequently, we have developed a three-dimensional reaction-diffusion model to describe events occurring in the lung interstitium when serine proteinases diffuse from the neutrophil azurophil granule following degranulation and subsequently bind to either α-1-antitrypsin or α-2-macroglobulin. We found that the proteinases remained uninhibited on the order of 0.1 s after release and diffused on the order of 10 µm into the tissue before becoming sequestered. We have shown that proteinases sequestered to α-2-macroglobulin retain their proteolytic activity and that neutrophil elastase complexes with α-2-macroglobulin are able to degrade elastin. Although neutrophil elastase is implicated in the pathophysiology of emphysema, our results highlight a potentially important role for proteinase 3 because of its greater concentration in azurophil granules, its reduced association rate constant with all α-1-antitrypsin variants studied here, its greater diffusion distance, time spent uninhibited following degranulation, and its greater propensity to partition to α-2-macroglobulin where it retains proteolytic activity.

Repair rather than segregation of damage is the optimal unicellular aging strategy.

BACKGROUND: How aging, being unfavourable for the individual, can evolve is one of the fundamental problems of biology. Evidence for aging in unicellular organisms is far from conclusive. Some studies found aging even in symmetrically dividing unicellular species; others did not find aging in the same, or in different, unicellular species, or only under stress. Mathematical models suggested that segregation of non-genetic damage, as an aging strategy, would increase fitness. However, these models failed to consider repair as an alternative strategy or did not properly account for the benefits of repair. We used a new and improved individual-based model to examine rigorously the effect of a range of aging strategies on fitness in various environments. RESULTS: Repair of damage emerges as the best strategy despite its fitness costs, since it immediately increases growth rate. There is an optimal investment in repair that outperforms damage segregation in well-mixed, lasting and benign environments over a wide range of parameter values. Damage segregation becomes beneficial, and only in combination with repair, when three factors are combined: (i) the rate of damage accumulation is high, (ii) damage is toxic and (iii) efficiency of repair is low. In contrast to previous models, our model predicts that unicellular organisms should have active mechanisms to repair damage rather than age by segregating damage. Indeed, as predicted, all organisms have evolved active mechanisms of repair whilst aging in unicellular organisms is absent or minimal under benign conditions, apart from microorganisms with a different ecology, inhabiting short-lived environments strongly favouring early reproduction rather than longevity. CONCLUSIONS: Aging confers no fitness advantage for unicellular organisms in lasting environments under benign conditions, since repair of non-genetic damage is better than damage segregation.

A metagenomic study of antibiotic resistance genes in a hypereutrophic subtropical lake contaminated by anthropogenic sources.

Antibiotic resistance genes (ARGs) are a major threat to human and environmental health. This study investigated the occurrence and distribution of ARGs in Lake Cajititlán, a hypereutrophic subtropical lake in Mexico contaminated by anthropogenic sources (urban wastewater and runoff from crop and livestock production). ARGs (a total of 475 genes) were detected in 22 bacterial genera, with Pseudomonas (144 genes), Stenotrophomonas (88 genes), Mycobacterium (54 genes), and Rhodococcus (27 genes) displaying the highest frequencies of ARGs. Among these, Pseudomonas aeruginosa and Stenotrophomonas maltophilia showed the highest number of ARGs. The results revealed a diverse array of ARGs, including resistance to macrolides (11.55 %), aminoglycosides (8.22 %), glycopeptides (6.22 %), tetracyclines (4 %), sulfonamides (4 %), carbapenems (1.11 %), phenicols (0.88 %), fluoroquinolones (0.44 %), and lincosamides (0.22 %). The most frequently observed ARGs were associated with multidrug resistance (63.33 %), with MexF (42 genes), MexW (36 genes), smeD (31 genes), mtrA (25 genes), and KHM-1 (22 genes) being the most common. Lake Cajititlán is a recreational area for swimming, fishing, and boating, while also supporting irrigation for agriculture and potentially acting as a drinking water source for some communities. This raises concerns about the potential for exposure to antibiotic-resistant bacteria through these activities. The presence of ARGs in Lake Cajititlán poses a significant threat to both human and environmental health. Developing strategies to mitigate the risks of antibiotic resistance, including improving wastewater treatment, and promoting strategic antibiotic use and disposal, is crucial. This study represents a significant advancement in the understanding of antibiotic resistance dynamics in a hypereutrophic subtropical lake in a developing country, providing valuable insights for the scientific community and policymakers.

Modelling the impact of wastewater flows and management practices on antimicrobial resistance in dairy farms.

Dairy slurry is a major source of environmental contamination with antimicrobial resistant genes and bacteria. We developed mathematical models and conducted on-farm research to explore the impact of wastewater flows and management practices on antimicrobial resistance (AMR) in slurry. Temporal fluctuations in cephalosporin-resistant Escherichia coli were observed and attributed to farm activities, specifically the disposal of spent copper and zinc footbath into the slurry system. Our model revealed that resistance should be more frequently observed with relevant determinants encoded chromosomally rather than on plasmids, which was supported by reanalysis of sequenced genomes from the farm. Additionally, lower resistance levels were predicted in conditions with lower growth and higher death rates. The use of muck heap effluent for washing dirty channels did not explain the fluctuations in cephalosporin resistance. These results highlight farm-specific opportunities to reduce AMR pollution, beyond antibiotic use reduction, including careful disposal or recycling of waste antimicrobial metals.

The role of mathematical modelling in understanding prokaryotic predation.

With increasing levels of antimicrobial resistance impacting both human and animal health, novel means of treating resistant infections are urgently needed. Bacteriophages and predatory bacteria such as Bdellovibrio bacteriovorus have been proposed as suitable candidates for this role. Microbes also play a key environmental role as producers or recyclers of nutrients such as carbon and nitrogen, and predators have the capacity to be keystone species within microbial communities. To date, many studies have looked at the mechanisms of action of prokaryotic predators, their safety in in vivo models and their role and effectiveness under specific conditions. Mathematical models however allow researchers to investigate a wider range of scenarios, including aspects of predation that would be difficult, expensive, or time-consuming to investigate experimentally. We review here a history of modelling in prokaryote predation, from simple Lotka-Volterra models, through increasing levels of complexity, including multiple prey and predator species, and environmental and spatial factors. We consider how models have helped address questions around the mechanisms of action of predators and have allowed researchers to make predictions of the dynamics of predator-prey systems. We examine what models can tell us about qualitative and quantitative commonalities or differences between bacterial predators and bacteriophage or protists. We also highlight how models can address real-world situations such as the likely effectiveness of predators in removing prey species and their potential effects in shaping ecosystems. Finally, we look at research questions that are still to be addressed where models could be of benefit.

Antimicrobial resistance in dairy slurry tanks: A critical point for measurement and control.

Waste from dairy production is one of the largest sources of contamination from antimicrobial resistant bacteria (ARB) and genes (ARGs) in many parts of the world. However, studies to date do not provide necessary evidence to inform antimicrobial resistance (AMR) countermeasures. We undertook a detailed, interdisciplinary, longitudinal analysis of dairy slurry waste. The slurry contained a population of ARB and ARGs, with resistances to current, historical and never-used on-farm antibiotics; resistances were associated with Gram-negative and Gram-positive bacteria and mobile elements (ISEcp1, Tn916, Tn21-family transposons). Modelling and experimental work suggested that these populations are in dynamic equilibrium, with microbial death balanced by fresh input. Consequently, storing slurry without further waste input for at least 60 days was predicted to reduce ARB spread onto land, with > 99 % reduction in cephalosporin resistant Escherichia coli. The model also indicated that for farms with low antibiotic use, further reductions are unlikely to reduce AMR further. We conclude that the slurry tank is a critical point for measurement and control of AMR, and that actions to limit the spread of AMR from dairy waste should combine responsible antibiotic use, including low total quantity, avoidance of human critical antibiotics, and choosing antibiotics with shorter half-lives, coupled with appropriate slurry storage.

Growth dependence of conjugation explains limited plasmid invasion in biofilms: an individual-based modelling study.

Plasmid invasion in biofilms is often surprisingly limited in spite of the close contact of cells in a biofilm. We hypothesized that this poor plasmid spread into deeper biofilm layers is caused by a dependence of conjugation on the growth rate (relative to the maximum growth rate) of the donor. By extending an individual-based model of microbial growth and interactions to include the dynamics of plasmid carriage and transfer by individual cells, we were able to conduct in silico tests of this and other hypotheses on the dynamics of conjugal plasmid transfer in biofilms. For a generic model plasmid, we find that invasion of a resident biofilm is indeed limited when plasmid transfer depends on growth, but not so in the absence of growth dependence. Using sensitivity analysis we also find that parameters related to timing (i.e. a lag before the transconjugant can transfer, transfer proficiency and scan speed) and spatial reach (EPS yield, conjugal pilus length) are more important for successful plasmid invasion than the recipients' growth rate or the probability of segregational loss. While this study identifies one factor that can limit plasmid invasion in biofilms, the new individual-based framework introduced in this work is a powerful tool that enables one to test additional hypotheses on the spread and role of plasmids in microbial biofilms.

iDynoMiCS: next-generation individual-based modelling of biofilms.

Individual-based modelling of biofilms accounts for the fact that individual organisms of the same species may well be in a different physiological state as a result of environmental gradients, lag times in responding to change, or noise in gene expression, which we have become increasingly aware of with the advent of single-cell microbiology. But progress in developing and using individual-based modelling has been hampered by different groups writing their own code and the lack of an available standard model. We therefore set out to merge most features of previous models and incorporate various improvements in order to provide a common basis for further developments. Four improvements stand out: the biofilm pressure field allows for shrinking or consolidating biofilms; the continuous-in-time extracellular polymeric substances excretion leads to more realistic fluid behaviour of the extracellular matrix, avoiding artefacts; the stochastic chemostat mode allows comparison of spatially uniform and heterogeneous systems; and the separation of growth kinetics from the individual cell allows condition-dependent switching of metabolism. As an illustration of the model's use, we used the latter feature to study how environmentally fluctuating oxygen availability affects the diversity and composition of a community of denitrifying bacteria that induce the denitrification pathway under anoxic or low oxygen conditions. We tested the hypothesis that the existence of these diverse strategies of denitrification can be explained solely by assuming that faster response incurs higher costs. We found that if the ability to switch metabolic pathways quickly incurs no costs the fastest responder is always the best. However, if there is a trade-off where faster switching incurs higher costs, then there is a strategy with optimal response time for any frequency of environmental fluctuations, suggesting that different types of denitrifying strategies win in different environments. In a single environment, biodiversity of denitrifiers is higher in biofilms than chemostats, higher with than without costs and higher at intermediate frequency of change. The highly modular nature of the new computational model made this case study straightforward to implement, and reflects the sort of novel studies that can easily be executed with the new model.

Towards a general model for predicting minimal metal concentrations co-selecting for antibiotic resistance plasmids.

Many antibiotic resistance genes co-occur with resistance genes for transition metals, such as copper, zinc, or mercury. In some environments, a positive correlation between high metal concentration and high abundance of antibiotic resistance genes has been observed, suggesting co-selection due to metal presence. Of particular concern is the use of copper and zinc in animal husbandry, leading to potential co-selection for antibiotic resistance in animal gut microbiomes, slurry, manure, or amended soils. For antibiotics, predicted no effect concentrations have been derived from laboratory measured minimum inhibitory concentrations and some minimal selective concentrations have been investigated in environmental settings. However, minimal co-selection concentrations for metals are difficult to identify. Here, we use mathematical modelling to provide a general mechanistic framework to predict minimal co-selective concentrations for metals, given knowledge of their toxicity at different concentrations. We apply the method to copper (Cu), zinc (Zn), mercury (Hg), lead (Pb) and silver (Ag), predicting their minimum co-selective concentrations in mg/L (Cu: 5.5, Zn: 1.6, Hg: 0.0156, Pb: 21.5, Ag: 0.152). To exemplify use of these thresholds, we consider metal concentrations from slurry and slurry-amended soil from a UK dairy farm that uses copper and zinc as additives for feed and antimicrobial footbath: the slurry is predicted to be co-selective, but not the slurry-amended soil. This modelling framework could be used as the basis for defining standards to mitigate risks of antimicrobial resistance applicable to a wide range of environments, including manure, slurry and other waste streams.

EMBRACE-WATERS statement: Recommendations for reporting of studies on antimicrobial resistance in wastewater and related aquatic environments.

BACKGROUND: A One Health approach requires integrative research to elucidate antimicrobial resistance (AMR) in the environment and the risks it poses to human health. Research on this topic involves experts from diverse backgrounds and professions. Shortcomings exist in terms of consistent, complete, and transparent reporting in many environmental studies. Standardized reporting will improve the quality of scientific papers, enable meta-analyses and enhance the communication among different experts. In this study, we aimed to generate a consensus of reporting standards for AMR research in wastewater and related aquatic environments. METHODS: Based on a risk of bias assessment of the literature in a systematic review, we proposed a set of study quality indicators. We then used a multistep modified Delphi consensus to develop the EMBRACE-WATERS statement (rEporting antiMicroBial ResistAnCE in WATERS), a checklist of recommendations for reporting in studies of AMR in wastewater and related aquatic environments. FINDINGS: Consensus was achieved among a multidisciplinary panel of twenty-one experts in three steps. The developed EMBRACE-WATERS statement incorporates 21 items. Each item contains essential elements of high-quality reporting and is followed by an explanation of their rationale and a reporting-example. The EMBRACE-WATERS statement is primarily intended to be used by investigators to ensure transparent and comprehensive reporting of their studies. It can also guide peer-reviewers and editors in evaluation of manuscripts on AMR in the aquatic environment. This statement is not intended to be used to guide investigators on the methodology of their research. INTERPRETATION: We are hopeful that this statement will improve the reporting quality of future studies of AMR in wastewater and related aquatic environments. Its uptake would generate a common language to be used among researchers from different disciplines, thus advancing the One Health approach towards understanding AMR spread across aquatic environments. Similar initiatives are needed in other areas of One Health research.

Generalized voronoi tessellation as a model of two-dimensional cell tissue dynamics.

Voronoi tessellations have been used to model the geometric arrangement of cells in morphogenetic or cancerous tissues, however, so far only with flat hyper-surfaces as cell-cell contact borders. In order to reproduce the experimentally observed piecewise spherical boundary shapes, we develop a consistent theoretical framework of multiplicatively weighted distance functions, defining generalized finite Voronoi neighborhoods around cell bodies of varying radius, which serve as heterogeneous generators of the resulting model tissue. The interactions between cells are represented by adhesive and repelling force densities on the cell contact borders. In addition, protrusive locomotion forces are implemented along the cell boundaries at the tissue margin, and stochastic perturbations allow for non-deterministic motility effects. Simulations of the emerging system of stochastic differential equations for position and velocity of cell centers show the feasibility of this Voronoi method generating realistic cell shapes. In the limiting case of a single cell pair in brief contact, the dynamical nonlinear Ornstein-Uhlenbeck process is analytically investigated. In general, topologically distinct tissue conformations are observed, exhibiting stability on different time scales, and tissue coherence is quantified by suitable characteristics. Finally, an argument is derived pointing to a tradeoff in natural tissues between cell size heterogeneity and the extension of cellular lamellae.

Evolutionary causes and consequences of metabolic division of labour: why anaerobes do and aerobes don't.

Metabolic division of the labour of organic matter decomposition into several steps carried out by different types of microbes is typical for many anoxic - but not oxic environments. An explanation of this well-known pattern is proposed based on the combination of three key insights: (i) well-studied anoxic environments are high flux environments: they are only anoxic because their high organic matter influx leads to oxygen depletion; (ii) shorter, incomplete catabolic pathways provide the capacity for higher flux, but this capacity is only advantageous in high flux environments; (iii) longer, complete catabolic pathways have energetic happy ends but only with high redox potential electron acceptors. Thus, aerobic environments favour longer pathways. Bioreactors, in contrast, are high flux environments and therefore favour division of catabolic labour even if aeration keeps them aerobic; therefore, host strains and feeding strategies must be carefully engineered to resist this pull.