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.

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.

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.

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.

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.

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.

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.

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.

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.

Damage Repair versus Aging in an Individual-Based Model of Biofilms.

The extent of senescence due to damage accumulation-or aging-is evidently evolvable as it differs hugely between species and is not universal, suggesting that its fitness advantages depend on life history and environment. In contrast, repair of damage is present in all organisms studied. Despite the fundamental trade-off between investing resources into repair or into growth, repair and segregation of damage have not always been considered alternatives. For unicellular organisms, unrepaired damage could be divided asymmetrically between daughter cells, leading to senescence of one and rejuvenation of the other. Repair of "unicells" has been predicted to be advantageous in well-mixed environments such as chemostats. Most microorganisms, however, live in spatially structured systems, such as biofilms, with gradients of environmental conditions and cellular physiology as well as a clonal population structure. To investigate whether this clonal structure might favor senescence by damage segregation (a division-of-labor strategy akin to the germline-soma division in multicellular organisms), we used an individual-based computational model and developed an adaptive repair strategy where cells respond to their current intracellular damage levels by investing into repair machinery accordingly. Our simulations showed that the new adaptive repair strategy was advantageous provided that growth was limited by substrate availability, which is typical for biofilms. Thus, biofilms do not favor a germline-soma-like division of labor between daughter cells in terms of damage segregation. We suggest that damage segregation is beneficial only when extrinsic mortality is high, a degree of multicellularity is present, and an active mechanism makes segregation effective.IMPORTANCE Damage is an inevitable consequence of life. For unicellular organisms, this leads to a trade-off between allocating resources into damage repair or into growth coupled with segregation of damage upon cell division, i.e., aging and senescence. Few studies considered repair as an alternative to senescence. None considered biofilms, where the majority of unicellular organisms live, although fitness advantages in well-mixed systems often turn into disadvantages in spatially structured systems such as biofilms. We compared the fitness consequences of aging versus an adaptive repair mechanism based on sensing damage, using an individual-based model of a generic unicellular organism growing in biofilms. We found that senescence is not beneficial provided that growth is limited by substrate availability. Instead, it is useful as a stress response to deal with damage that failed to be repaired when (i) extrinsic mortality was high; (ii) a degree of multicellularity was present; and (iii) damage segregation was effective.

Comparison of antibiotic-resistant bacteria and antibiotic resistance genes abundance in hospital and community wastewater: A systematic review.

Antibiotic-resistant bacteria (ARB) and antibiotic-resistance genes (ARGs) are constantly shed into the aquatic environment, with hospital wastewater potentially acting as an important source for resistance spread into the environment. A systematic review was conducted aiming to investigate the role of hospital wastewater on dissemination of antimicrobial resistance in the aquatic environment. Studies included in the review compared the prevalence of ARB and/or ARGs in hospital versus community wastewater. Data were extracted on ARB and/or ARG prevalence. Data on sampling techniques, microbiological methodology and risk of bias of included studies were recorded. Thirty-seven studies were included. Higher frequencies of antibiotic resistance determinants were found in hospital wastewater compared to community sources in 30/37 (81%) of included studies. However, trends for specific multi-drug-resistant bacteria differed. Antibiotic-resistant Gram-negative were more prevalent in hospital compared to community wastewaters, with higher concentrations of extended-spectrum-beta-lactamase-producing pathogens and carbapenemase-producing Enterobacteriaceae in hospital sources in 9/9 studies and 6/7 studies, respectively. Hospitals did not contribute consistently to the abundance of vancomycin-resistant Enterococci (VRE); 5/10 studies found higher abundance of VRE in hospital compared to community wastewaters. Reporting on sampling methods, wastewater treatment processes and statistical analysis were at high risk of bias. Extreme heterogeneity in study methods and outcome reporting precluded meta-analysis. Current evidence concurs that hospital wastewater is an important source for antibiotic resistance in aquatic environments, mainly multidrug-resistant Gram-negative bacteria. Future research is needed to assess the effect of wastewater treatment processes on overall antibiotic resistance in the aquatic environment.

Toward Engineering Biosystems With Emergent Collective Functions.

Many complex behaviors in biological systems emerge from large populations of interacting molecules or cells, generating functions that go beyond the capabilities of the individual parts. Such collective phenomena are of great interest to bioengineers due to their robustness and scalability. However, engineering emergent collective functions is difficult because they arise as a consequence of complex multi-level feedback, which often spans many length-scales. Here, we present a perspective on how some of these challenges could be overcome by using multi-agent modeling as a design framework within synthetic biology. Using case studies covering the construction of synthetic ecologies to biological computation and synthetic cellularity, we show how multi-agent modeling can capture the core features of complex multi-scale systems and provide novel insights into the underlying mechanisms which guide emergent functionalities across scales. The ability to unravel design rules underpinning these behaviors offers a means to take synthetic biology beyond single molecules or cells and toward the creation of systems with functions that can only emerge from collectives at multiple scales.

A generalised model for generalised transduction: the importance of co-evolution and stochasticity in phage mediated antimicrobial resistance transfer.

Antimicrobial resistance is a major global challenge. Of particular concern are mobilizable elements that can transfer resistance genes between bacteria, leading to pathogens with new combinations of resistance. To date, mathematical models have largely focussed on transfer of resistance by plasmids, with fewer studies on transfer by bacteriophages. We aim to understand how best to model transfer of resistance by transduction by lytic phages. We show that models of lytic bacteriophage infection with empirically derived realistic phage parameters lead to low numbers of bacteria, which, in low population or localised environments, lead to extinction of bacteria and phage. Models that include antagonistic co-evolution of phage and bacteria produce more realistic results. Furthermore, because of these low numbers, stochastic dynamics are shown to be important, especially to spread of resistance. When resistance is introduced, resistance can sometimes be fixed, and at other times die out, with the probability of each outcome sensitive to bacterial and phage parameters. Specifically, that outcome most strongly depends on the baseline death rate of bacteria, with phage-mediated spread favoured in benign environments with low mortality over more hostile environments. We conclude that larger-scale models should consider spatial compartmentalisation and heterogeneous microenviroments, while encompassing stochasticity and co-evolution.

Potentiation of curing by a broad-host-range self-transmissible vector for displacing resistance plasmids to tackle AMR.

Plasmids are potent vehicles for spread of antibiotic resistance genes in bacterial populations and often persist in the absence of selection due to efficient maintenance mechanisms. We previously constructed non-conjugative high copy number plasmid vectors that efficiently displace stable plasmids from enteric bacteria in a laboratory context by blocking their replication and neutralising their addiction systems. Here we assess a low copy number broad-host-range self-transmissible IncP-1 plasmid as a vector for such curing cassettes to displace IncF and IncK plasmids. The wild type plasmid carrying the curing cassette displaces target plasmids poorly but derivatives with deletions near the IncP-1 replication origin that elevate copy number about two-fold are efficient. Verification of this in mini IncP-1 plasmids showed that elevated copy number was not sufficient and that the parB gene, korB, that is central to its partitioning and gene control system, also needs to be included. The resulting vector can displace target plasmids from a laboratory population without selection and demonstrated activity in a mouse model although spread is less efficient and requires additional selection pressure.

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.

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.