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Water and soil contain a multiplicity of particulate material coated with bacterial populations and communities. Microbiotic particles are any type of small particle (measuring less than 2 mm) to which bacteria and other microbes attach, resulting in medium to long-term colonization. This study reviews the interactions of ecologically distant bacterial organisms on microbiotic particles in soil and water as a method for explaining the evolution and spread of antibiotic resistance traits. These particles include bacteria-bacteria aggregates, which can merge with particles from fungi, protozoa, phytoplankton, zooplankton, and biodetritus resulting from animal and vegetal decomposition, humus, mineral particles (clay, carbonates, silicates), and anthropogenic particles (including wastewater particles and microplastics). In turn, these complex particles can interact and coalesce. Natural phenomena (waterflow, tides, tsunamis, currents, and strong winds) and anthropogenic activity (agriculture, waste-water management, mining, excavation/construction) favor the interaction and merging of microbiotic particles in soil and water, resulting in enhanced recombinant communities capable of exchanging genetic material, including antimicrobial resistance genes, particularly in antimicrobial-polluted environments. In this review, we propose that the worldwide spread of antimicrobial resistance might be related to the environmental dynamics of microbiotic particles, and we discuss possible methods for reducing this problem that threatens One Health and Planetary Health.

Wild birds have been suggested to be reservoirs of antimicrobial resistant and/or pathogenic Enterococcus faecalis (Efs) strains, but the scarcity of studies and available sequences limit our understanding of the population structure of the species in these hosts. Here, we analysed the clonal and plasmid diversity of 97 Efs isolates from wild migratory birds. We found a high diversity, with most sequence types (STs) being firstly described here, while others were found in other hosts including some predominant in poultry. We found that pheromone-responsive plasmids predominate in wild bird Efs while 35% of the isolates entirely lack plasmids. Then, to better understand the ecology of the species, the whole genome of fivestrains with known STs (ST82, ST170, ST16 and ST55) were sequenced and compared with all the Efs genomes available in public databases. Using several methods to analyse core and accessory genomes (AccNET, PLACNET, hierBAPS and PANINI), we detected differences in the accessory genome of some lineages (e.g. ST82) demonstrating specific associations with birds. Conversely, the genomes of other Efs lineages exhibited divergence in core and accessory genomes, reflecting different adaptive trajectories in various hosts. This pangenome divergence, horizontal gene transfer events and occasional epidemic peaks could explain the population structure of the species.

Background: Antibiotic resistance is a major biomedical problem upon which public health systems demand solutions to construe the dynamics and epidemiological risk of resistant bacteria in anthropogenically-altered environments. The implementation of computable models with reciprocity within and between levels of biological organization (i.e. essential nesting) is central for studying antibiotic resistances. Antibiotic resistance is not just the result of antibiotic-driven selection but more properly the consequence of a complex hierarchy of processes shaping the ecology and evolution of the distinct subcellular, cellular and supra-cellular vehicles involved in the dissemination of resistance genes. Such a complex background motivated us to explore the P-system standards of membrane computing an innovative natural computing formalism that abstracts the notion of movement across membranes to simulate antibiotic resistance evolution processes across nested levels of micro- and macro-environmental organization in a given ecosystem. Results: In this article, we introduce ARES (Antibiotic Resistance Evolution Simulator) a software device that simulates P-system model scenarios with five types of nested computing membranes oriented to emulate a hierarchy of eco-biological compartments, i.e. a) peripheral ecosystem; b) local environment; c) reservoir of supplies; d) animal host; and e) host's associated bacterial organisms (microbiome). Computational objects emulating molecular entities such as plasmids, antibiotic resistance genes, antimicrobials, and/or other substances can be introduced into this framework and may interact and evolve together with the membranes, according to a set of pre-established rules and specifications. ARES has been implemented as an online server and offers additional tools for storage and model editing and downstream analysis. Conclusions: The stochastic nature of the P-system model implemented in ARES explicitly links within and between host dynamics into a simulation, with feedback reciprocity among the different units of selection influenced by antibiotic exposure at various ecological levels. ARES offers the possibility of modeling predictive multilevel scenarios of antibiotic resistance evolution that can be interrogated, edited and re-simulated if necessary, with different parameters, until a correct model description of the process in the real world is convincingly approached. ARES can be accessed at http://gydb.org/ares.

Extended-spectrum beta-lactamases (ESBL) constitute a key antibiotic-resistance mechanism affecting Gram-negative bacteria, and also an excellent model for studying evolution in real time. A shift in the epidemiology of ESBLs is being observed, which is characterized by the explosive diversification and increase in frequency of the CTX-M-type beta-lactamases in different settings. This provides a unique opportunity for studying a protein evolutionary radiation by the sequential acquisition of specific mutations enhancing protein efficiency and fitness concomitantly. The existence of driver antibiotic molecules favoring protein divergence has been investigated by combining evolutionary analyses and experimental site-specific mutagenesis. Phylogenetic reconstruction with all the CTX-M variants described so far provided a hypothetical evolutionary scenario showing at least three diversification events. CTX-M-3 was likely the enzyme at the origin of the diversification in the CTX-M-1 cluster, which was coincident with positive selection acting on several amino acid positions. Sixty-three CTX-M-3 derivatives containing all combinations of mutations under positively selected positions were constructed, and their phenotypic efficiency was evaluated. The CTX-M-3 diversification process can only be explained in a complex selective landscape with at least two antibiotics (cefotaxime and ceftazidime), indicating the need to invoke mixtures of selective drivers in order to understand the final evolutionary outcome. Under this hypothesis, we found congruent results between the in silico and in vitro analyses of evolutionary trajectories. Three pathways driving the diversification of CTX-M-3 towards the most complex and efficient variants were identified. Whereas the P167S pathway has limited possibilities of further diversification, the D240G route shows a robust diversification network. In the third route, drift may have played a role in the early stages of CTX-M-3 evolution. Antimicrobial agents should not be considered only as selectors for efficient mechanisms of resistance but also as diversifying agents of the evolutionary trajectories. Different trajectories were identified using a combination of phylogenetic reconstructions and directed mutagenesis analyses, indicating that such an approach might be useful to fulfill the desirable goal of predicting evolutionary trajectories in antimicrobial resistance.

This document is the result of the Rural Territorial Dynamics Program, implemented by Rimisp in several Latin American countries in collaboration with numerous partners. The program has been supported by the International Development Research Center (IDRC, Canada). We authorize the non-for-profit partial or full reproduction and dissemination of this document, subject to the source being properly acknowledged.

As the Science of Biology is constantly changing due to new discoveries and advanced techniques it is essential that a systematic study of the environmental causes of natural selection on microorganisms be conducted. Very small phenotypic differences among individuals within bacterial populations arise as a result of spontaneous genetic variation, but the evolutionary importance of these small changes is frequently considered to be non-significant. Recent in vitro experiments indicate that efficient selection of these very small differences may take place in environmental compartments where a particular intensity of the selective agent is exerted. Model studies based on competition between bacterial populations only differing in one or two amino acid changes of a detoxifying antibiotic enzyme (e.g. beta-lactamase) have shown that at a narrow range of antibiotic concentrations the variant population is strongly selected over the original type, despite the extremely low phenotypic differences in antibiotic susceptibility. These selective concentrations are expected to occur in precise environmental compartments (selective compartments). Due to the high frequency of structured habitats in natural environments, the intensity of selective agents is commonly exerted along certain gradients. Each one of the points forming these gradients (or intersection among gradients) may have a particular selective ability for a specific genetic variant. Considering the environment as a composition of an extremely high number of specific selective compartments may help to understand the existence of high levels of genetic variability in natural bacterial populations. This may be one of the clues towards the unraveling of bacterial evolution.

An allele-specific amplification method based on two genetic polymorphisms to differentiate Mycobacterium tuberculosis from Mycobacterium bovis was tested. Based on the differences found at position 169 in the pncA genes from M. tuberculosis and M. bovis, a PCR system which was able to differentiate most of the 237 M. tuberculosis complex isolates tested in one of the two species was developed. All 121 M. tuberculosis strains showed the expected base (cytosine) at position 169. Most of the M. bovis isolates had a guanine at the cited position. Nevertheless, 18 of the 116 M. bovis isolates, all of them goat isolates, showed the pncA polymorphism specific to M. tuberculosis. These results suggest that goat M. bovis may be the nicotinamidase-missing link at the origin of the M. tuberculosis species. Based on the polymorphism found at position 285 in the oxyR gene, the same system was used to differentiate M. tuberculosis from M. bovis. In this case, DNAs from all 121 M. tuberculosis isolates had the expected base (guanine) at this position. In addition, all 116 M. bovis isolates, including those from goats, showed the identical polymorphism (adenine). The oxyR allele-specific amplification method can differentiate M. bovis from M. tuberculosis, is rapid (results can be obtained in less than 3 h), and is easy to perform.

The biochemistry and genetics of antibiotic resistance are far better known than the equally important events underlying the selection of resistant populations. The hidden selection of low-level resistant variants may be a key process in the emergence of high-level antibiotic resistance. Different low-level resistant bacterial subpopulations may be specifically selected by different low antibiotic concentrations. The space in the environment (human body) where a given selective concentration exists represents the selective compartment. For pharmacokinetic reasons, low antibiotic concentrations occur in a larger selective compartment and persist longer than high antibiotic concentrations. The specific selection of low-level variants by low concentrations of antibiotic can be reproduced in experimental in vitro models using mixtures of susceptible and low-level resistant populations. We demonstrated this in Escherichia coli strains harbouring TEM-1, TEM-12 and TEM-10 beta-lactamases challenged by cefotaxime, and also Streptococcus pneumoniae strains with various levels of penicillin resistance challenged by amoxicillin or cefotaxime. In both cases, four hours of antibiotic challenge produced selective peaks of low-level resistant variant populations at low-level antibiotic concentrations. We conclude that variants with small decreases in antibiotic susceptibility may be fully selectable under in vivo circumstances; on the other hand, low-level antibiotic concentrations may have a considerable selective effect on the emergence of antibiotic resistance.

Serology is a good alternative, minimally invasive, diagnostic and screening test for Helicobacter pylori infection. Several immunoglobulin G (IgG) enzyme-linked immunosorbent assay (ELISA) commercial kits have been evaluated. Information on IgA ELISAs is relatively poor, and on the combined use of IgG and IgA ELISAs very scarce.We intended to evaluate the sensitivity, specificity and predictive values of two quantitative commercial IgG and IgA ELISAs (Helico-G and GAP, respectively) and more particularly the accuracy of their combined use.Serum samples and gastric biopsy specimen culture findings from 400 patients were evaluated.The sensitivity, specificity, positive and negative predictive values of the IgG ELISA Helico-G test in detecting IgG antibodies to H. pylori were 97.2, 85.4, 98.3 and 77.8%, respectively, when compared with those of the reference method used. The corresponding findings for detection of IgA antibodies with the GAP test were 96.4, 80.5, 97.7 and 71.1%, respectively. When considering a patient infected with H. pylori when both tests were positive, the sensitivity, specificity, positive and negative predictive values were 94.1, 85.3, 98.2 and 62.5%, respectively. On the other hand, when at least one test was positive, the corresponding values were 99, 80, 97 and 94%, respectively.The IgG ELISA Helico-G and IgA ELISA GAP, taken separately, are good and reliable tests for the detection of antibodies to H. pylori. Furthermore, the combined use of both serological methods provided more useful information compared with single IgG and IgA determinations.

Exposure to biocides may result in cross-resistance to other antimicrobials. Changes in biocide and antibiotic susceptibilities, metabolism, and fitness costs were studied here in biocide-selected Escherichia coli and Klebsiella pneumoniae mutants. E. coli and K. pneumoniae mutants with various degrees of triclosan susceptibility were obtained after exposure to triclosan (TRI), benzalkonium chloride (BKC), chlorhexidine (CHX) or sodium hypochlorite (SHC), and ampicillin or ciprofloxacin. Alterations in antimicrobial susceptibility and metabolism in mutants were tested using Phenotype MicroArrays. The expression of AcrAB pump and global regulators (SoxR, MarA, and RamA) was measured by quantitative reverse transcription-PCR (qRT-PCR), and the central part of the fabI gene was sequenced. The fitness costs of resistance were assessed by a comparison of relative growth rates. Triclosan-resistant (TRI r ) and triclosan-hypersusceptible (TRI hs ) mutants of E. coli and K. pneumoniae were obtained after selection with biocides and/or antibiotics. E. coli TRI r mutants, including those with mutations in the fabI gene or in the expression of acrB , acrF , and marA , exhibited changes in susceptibility to TRI, CHX, and antibiotics. TRI r mutants for which the TRI MIC was high presented improved metabolism of carboxylic acids, amino acids, and carbohydrates. In TRI r mutants, resistance to one antimicrobial provoked hypersusceptibility to another one(s). TRI r mutants had fitness costs, particularly marA -overexpressing ( E. coli ) or ramA -overexpressing ( K. pneumoniae ) mutants. TRI, BKC, and CIP exposure frequently yielded TRI r mutants exhibiting alterations in AraC-like global regulators (MarA, SoxR, and RamA), AcrAB-TolC, and/or FabI, and influencing antimicrobial susceptibility, fitness, and metabolism. These various phenotypes suggest a trade-off of different selective processes shaping the evolution toward antibiotic/biocide resistance and influencing other adaptive traits.