Spatiotemporal microbial evolution on antibiotic landscapes

Unitig-centered pan-genome machine learning approach for predicting antibiotic resistance and discovering novel resistance genes in bacterial strains

In current genomic research, the widely used methods for predicting antimicrobial resistance (AMR) often rely on prior knowledge of known AMR genes or reference genomes. However, these methods have limitations, potentially resulting in imprecise predictions owing to incomplete coverage of AMR mechanisms and genetic variations. To overcome these limitations, we propose a pan-genome-based machine learning approach to advance our understanding of AMR gene repertoires and uncover possible feature sets for precise AMR classification. By building compacted de Brujin graphs (cDBGs) from thousands of genomes and collecting the presence/absence patterns of unique sequences (unitigs) for Pseudomonas aeruginosa, we determined that using machine learning models on unitig-centered pan-genomes showed significant promise for accurately predicting the antibiotic resistance or susceptibility of microbial strains. Applying a feature-selection-based machine learning algorithm led to satisfactory predictive performance for the training dataset (with an area under the receiver operating characteristic curve (AUC) of > 0.929) and an independent validation dataset (AUC, approximately 0.77). Furthermore, the selected unitigs revealed previously unidentified resistance genes, allowing for the expansion of the resistance gene repertoire to those that have not previously been described in the literature on antibiotic resistance. These results demonstrate that our proposed unitig-based pan-genome feature set was effective in constructing machine learning predictors that could accurately identify AMR pathogens. Gene sets extracted using this approach may offer valuable insights into expanding known AMR genes and forming new hypotheses to uncover the underlying mechanisms of bacterial AMR.

Resistance mechanism of Escherichia coli strains with different ampicillin resistance levels

Antibiotic resistance is an important problem that threatens medical treatment. Differences in the resistance levels of microorganisms cause great difficulties in understanding the mechanisms of antibiotic resistance. Therefore, the molecular reasons underlying the differences in the level of antibiotic resistance need to be clarified. For this purpose, genomic and transcriptomic analyses were performed on three Escherichia coli strains with varying degrees of adaptive resistance to ampicillin. Whole-genome sequencing of strains with different levels of resistance detected five mutations in strains with 10-fold resistance and two additional mutations in strains with 95-fold resistance. Overall, three of the seven mutations occurred as a single base change, while the other four occurred as insertions or deletions. While it was thought that 10-fold resistance was achieved by the effect of mutations in the ftsI, marAR, and rpoC genes, it was found that 95-fold resistance was achieved by the synergistic effect of five mutations and the ampC mutation. In addition, when the general transcriptomic profiles were examined, it was found that similar transcriptomic responses were elicited in strains with different levels of resistance. This study will improve our view of resistance mechanisms in bacteria with different levels of resistance and provide the basis for our understanding of the molecular mechanism of antibiotic resistance in ampicillin-resistant E. coli strains. KEY POINTS: •The mutation of the ampC promoter may act synergistically with other mutations and lead to higher resistance. •Similar transcriptomic responses to ampicillin are induced in strains with different levels of resistance. •Low antibiotic concentrations are the steps that allow rapid achievement of high antibiotic resistance.

Evolution and spread of multiadapted pathogens in a spatially heterogeneous environment

Pathogen adaptation to multiple selective pressures challenges our ability to control their spread. Here we analyze the evolutionary dynamics of pathogens spreading in a heterogeneous host population where selection varies periodically in space. We study both the transient dynamics taking place at the front of the epidemic and the long-term evolution far behind the front. We identify five types of epidemic profiles arising for different levels of spatial heterogeneity and different costs of adaptation. In particular, we identify the conditions where a generalist pathogen carrying multiple adaptations can outrace a coalition of specialist pathogens. We also show that finite host populations promote the spread of generalist pathogens because demographic stochasticity enhances the extinction of locally maladapted pathogens. But higher mutation rates between genotypes can rescue the coalition of specialists and speed up the spread of epidemics for intermediate levels of spatial heterogeneity. Our work provides a comprehensive analysis of the interplay between migration, local selection, mutation, and genetic drift on the spread and on the evolution of pathogens in heterogeneous environments. This work extends our fundamental understanding of the outcome of the competition between two specialists and a generalist strategy (single- vs. multiadapted pathogens). These results have practical implications for the design of more durable control strategies against multiadapted pathogens in agriculture and in public health.

Limits on the evolutionary rates of biological traits

This paper focuses on the maximum speed at which biological evolution can occur. I derive inequalities that limit the rate of evolutionary processes driven by natural selection, mutations, or genetic drift. These rate limits link the variability in a population to evolutionary rates. In particular, high variances in the fitness of a population and of a quantitative trait allow for fast changes in the trait's average. In contrast, low variability makes a trait less susceptible to random changes due to genetic drift. The results in this article generalize Fisher's fundamental theorem of natural selection to dynamics that allow for mutations and genetic drift, via trade-off relations that constrain the evolutionary rates of arbitrary traits. The rate limits can be used to probe questions in various evolutionary biology and ecology settings. They apply, for instance, to trait dynamics within or across species or to the evolution of bacteria strains. They apply to any quantitative trait, e.g., from species' weights to the lengths of DNA strands.

Genetic Alternatives for Experimental Adaptation to Colistin in Three Pseudomonas aeruginosa Lineages

Pseudomonas aeruginosa is characterized by a high adaptive potential, developing resistance in response to antimicrobial pressure. We employed a spatiotemporal evolution model to disclose the pathways of adaptation to colistin, a last-resort polymyxin antimicrobial, among three unrelated P. aeruginosa lineages. The P. aeruginosa ATCC-27833 reference strain (Pa_ATCC), an environmental P. aeruginosa isolate (Pa_Environment), and a clinical isolate with multiple drug resistance (Pa_MDR) were grown over an increasing 5-step colistin concentration gradient from 0 to 400 mg/L. Pa_Environment demonstrated the highest growth pace, achieving the 400 mg/L band in 15 days, whereas it took 37 and 60 days for Pa_MDR and Pa_ATCC, respectively. To identify the genome changes that occurred during adaptation to colistin, the isolates selected during the growth of the bacteria (n = 185) were subjected to whole genome sequencing. In total, 17 mutation variants in eight lipopolysaccharide-synthesis-associated genes were detected. phoQ and lpxL/PA0011 were affected in all three lineages, whereas changes in pmrB were found in Pa_Environment and Pa_MDR but not in Pa_ATCC. In addition, mutations were detected in 34 general metabolism genes, and each lineage developed mutations in a unique set of such genes. Thus, the three examined distinct P. aeruginosa strains demonstrated different capabilities and genetic pathways of colistin adaptation.

The Use and Impact of Antibiotics in Plant Agriculture: A Review

Growers have depended on the specificity and efficacy of streptomycin and oxytetracycline as a part of their plant disease arsenal since the middle of the 20th century. With climate change intensifying plant bacterial epidemics, the established success of these antibiotics remains threatened. Our strong reliance on certain antibiotics for devastating diseases eventually gave way to resistance development. Although antibiotics in plant agriculture equal to less than 0.5% of overall antibiotic use in the United States, it is still imperative for humans to continue to monitor usage, environmental residues, and resistance in bacterial populations. This review provides an overview of the history and use, resistance and mitigation, regulation, environmental impact, and economics of antibiotics in plant agriculture. Bacterial issues, such as the ongoing Huanglongbing (citrus greening) epidemic in Florida citrus production, may need antibiotics for adequate control. Therefore, preserving the efficacy of our current antibiotics by utilizing more targeted application methods, such as trunk injection, should be a major focus. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Heterogeneity of SOS response expression in clinical isolates of Escherichia coli influences adaptation to antimicrobial stress

In recent years, new evidence has shown that the SOS response plays an important role in the response to antimicrobials, with involvement in the generation of clinical resistance. Here we evaluate the impact of heterogeneous expression of the SOS response in clinical isolates of Escherichia coli on response to the fluoroquinolone, ciprofloxacin. In silico analysis of whole genome sequencing data showed remarkable sequence conservation of the SOS response regulators, RecA and LexA. Despite the genetic homogeneity, our results revealed a marked differential heterogeneity in SOS response activation, both at population and single-cell level, among clinical isolates of E. coli in the presence of subinhibitory concentrations of ciprofloxacin. Four main stages of SOS response activation were identified and correlated with cell filamentation. Interestingly, there was a correlation between clinical isolates with higher expression of the SOS response and further progression to resistance. This heterogeneity in response to DNA damage repair (mediated by the SOS response) and induced by antimicrobial agents could be a new factor with implications for bacterial evolution and survival contributing to the generation of antimicrobial resistance.

Investigating antimicrobial resistance genes in Kenya, Uganda and Tanzania cattle using metagenomics

Antimicrobial resistance (AMR) is a growing problem in African cattle production systems, posing a threat to human and animal health and the associated economic value chain. However, there is a poor understanding of the resistomes in small-holder cattle breeds in East African countries. This study aims to examine the distribution of antimicrobial resistance genes (ARGs) in Kenya, Tanzania, and Uganda cattle using a metagenomics approach. We used the SqueezeMeta-Abricate (assembly-based) pipeline to detect ARGs and benchmarked this approach using the Centifuge-AMRplusplus (read-based) pipeline to evaluate its efficiency. Our findings reveal a significant number of ARGs of critical medical and economic importance in all three countries, including resistance to drugs of last resort such as carbapenems, suggesting the presence of highly virulent and antibiotic-resistant bacterial pathogens (ESKAPE) circulating in East Africa. Shared ARGs such as aph(6)-id (aminoglycoside phosphotransferase), tet (tetracycline resistance gene), sul2 (sulfonamide resistance gene) and cfxA_gen (betalactamase gene) were detected. Assembly-based methods revealed fewer ARGs compared to read-based methods, indicating the sensitivity and specificity of read-based methods in resistome characterization. Our findings call for further surveillance to estimate the intensity of the antibiotic resistance problem and wider resistome classification. Effective management of livestock and antibiotic consumption is crucial in minimizing antimicrobial resistance and maximizing productivity, making these findings relevant to stakeholders, agriculturists, and veterinarians in East Africa and Africa at large.

Interplay between environmental yielding and dynamic forcing modulates bacterial growth

Many bacterial habitats-ranging from gels and tissues in the body to cell-secreted exopolysaccharides in biofilms-are rheologically complex, undergo dynamic external forcing, and have unevenly distributed nutrients. How do these features jointly influence how the resident cells grow and proliferate? Here, we address this question by studying the growth of Escherichia coli dispersed in granular hydrogel matrices with defined and highly tunable structural and rheological properties, under different amounts of external forcing imposed by mechanical shaking, and in both aerobic and anaerobic conditions. Our experiments establish a general principle: that the balance between the yield stress of the environment that the cells inhabit, σy, and the external stress imposed on the environment, σ, modulates bacterial growth by altering transport of essential nutrients to the cells. In particular, when σy<σ, the environment is easily fluidized and mixed over large scales, providing nutrients to the cells and sustaining complete cellular growth. By contrast, when σy>σ, the elasticity of the environment suppresses large-scale fluid mixing, limiting nutrient availability and arresting cellular growth. Our work thus reveals a new mechanism, beyond effects that change cellular behavior via local forcing, by which the rheology of the environment may modulate microbial physiology in diverse natural and industrial settings.

Reinforcement learning informs optimal treatment strategies to limit antibiotic resistance

Antimicrobial resistance was estimated to be associated with 4.95 million deaths worldwide in 2019. It is possible to frame the antimicrobial resistance problem as a feedback-control problem. If we could optimize this feedback-control problem and translate our findings to the clinic, we could slow, prevent, or reverse the development of high-level drug resistance. Prior work on this topic has relied on systems where the exact dynamics and parameters were known a priori. In this study, we extend this work using a reinforcement learning (RL) approach capable of learning effective drug cycling policies in a system defined by empirically measured fitness landscapes. Crucially, we show that it is possible to learn effective drug cycling policies despite the problems of noisy, limited, or delayed measurement. Given access to a panel of 15 [Formula: see text]-lactam antibiotics with which to treat the simulated Escherichia coli population, we demonstrate that RL agents outperform two naive treatment paradigms at minimizing the population fitness over time. We also show that RL agents approach the performance of the optimal drug cycling policy. Even when stochastic noise is introduced to the measurements of population fitness, we show that RL agents are capable of maintaining evolving populations at lower growth rates compared to controls. We further tested our approach in arbitrary fitness landscapes of up to 1,024 genotypes. We show that minimization of population fitness using drug cycles is not limited by increasing genome size. Our work represents a proof-of-concept for using AI to control complex evolutionary processes.

Fish skin mucosal surface becomes a barrier of antibiotic resistance genes under apramycin exposure

Antibiotic resistance genes (ARGs) are a kind of emerging environmental contamination, and are commonly found in antibiotic application situations, attracting wide attention. Fish skin mucosal surface (SMS), as the contact interface between fish and water, is the first line of defense against external pollutant invasion. Antibiotics are widely used in aquaculture, and SMS may be exposed to antibiotics. However, what happens to SMS when antibiotics are applied, and whether ARGs are enriched in SMS are not clear. In this study, Zebrafish (Danio rerio) were exposed to antibiotic and antibiotic resistant bacteria in the laboratory to simulate the aquaculture situation, and the effects of SMS on the spread of ARGs were explored. The results showed that SMS maintained the stability of the bacterial abundance and diversity under apramycin (APR) and bacterial exposure effectively. Until 11 days after stopping APR exposure, the abundance of ARGs in SMS (mean value was 3.32 × 10-3 copies/16S rRNA copies) still did not recover to the initial stage before exposure, which means that enriched ARGs in SMS were persistently remained. Moreover, non-specific immunity played an important role in resisting infection of external contamination. Besides, among antioxidant proteins, superoxide dismutase showed the highest activity. Consequently, it showed that SMS became a barrier of antibiotic resistance genes under APR exposure, and ARGs in SMS were difficult to remove once colonized. This study provided a reference for understanding the transmission, enrichment process, and ecological impact of antibiotics and ARGs in aquatic environments.

Unravelling the complex interplay between antibiotic consumption and adaptive changes in methicillin-resistant Staphylococcus aureus

OBJECTIVES

This study aims to elucidate the genomic dynamics driving the emergence of antimicrobial resistance (AMR), with a specific focus on the interplay between AMR and antimicrobial usage.

METHODS

We conducted a comprehensive analysis using a ST239 methicillin-resistant Staphylococcus aureus (MRSA) dataset over a continuous 12-year period from a single hospital. Genomic analyses were performed tracking the changes in MRSA populations, particularly the emergence of reduced vancomycin susceptibility, and assessing the impact of glycopeptide use on these emergence events.

RESULTS

Our findings reveal a significant correlation between hospital glycopeptide usage and the selection of MRSA strains with reduced vancomycin susceptibility. Genomic analyses provided insights into the molecular mechanisms driving resistance emergence, including the slowing of the molecular clock rate in response to heightened antimicrobial consumption.

CONCLUSIONS

In conclusion, this study the highlights the complex dynamics between AMR and antimicrobial use at the hospital level. The observed correlation between antimicrobial consumption and the development of less susceptible MRSA strains underscores the importance of antimicrobial stewardship programmes and the establishment of optimal consumption thresholds for mitigating AMR effectively.

Range expansion can promote the evolution of plastic generalism in coarse-grained landscapes

Phenotypic plasticity is one way for organisms to deal with variable environments through generalism. However, plasticity is not found universally and its evolution may be constrained by costs and other limitations such as complexity: the need for multiple mutational steps before the adaptation is realized. Theory predicts that greater experienced heterogeneity, such as organisms may encounter when spatial heterogeneity is fine-grained relative to dispersal, should favor the evolution of a broader niche. Here we tested this prediction via simulation. We found that, contrary to classical predictions, coarse-grained landscapes can be the most favorable for the evolution of plasticity, but only when populations encounter those landscapes through range expansion. During these range expansions, coarse-grained landscapes select for each step in the complex mutational pathway to plastic generalism by blocking the dispersal of specialists. These circumstances provide ecological opportunities for innovative mutations that change the niche. Our results indicate a new mechanism by which range expansion and spatially structured landscapes interact to shape evolution and reveal that the environments in which a complex adaptation has the highest fitness may not be the most favorable for its evolution.

Susceptible bacteria can survive antibiotic treatment in the mammalian gastrointestinal tract without evolving resistance

Antibiotic resistance and evasion are incompletely understood and complicated by the fact that murine interval dosing models do not fully recapitulate antibiotic pharmacokinetics in humans. To better understand how gastrointestinal bacteria respond to antibiotics, we colonized germ-free mice with a pan-susceptible genetically barcoded Escherichia coli clinical isolate and administered the antibiotic cefepime via programmable subcutaneous pumps, allowing closer emulation of human parenteral antibiotic dynamics. E. coli was only recovered from intestinal tissue, where cefepime concentrations were still inhibitory. Strikingly, "some" E. coli isolates were not cefepime resistant but acquired mutations in genes involved in polysaccharide capsular synthesis increasing their invasion and survival within human intestinal cells. Deleting wbaP involved in capsular polysaccharide synthesis mimicked this phenotype, allowing increased invasion of colonocytes where cefepime concentrations were reduced. Additionally, "some" mutant strains exhibited a persister phenotype upon further cefepime exposure. This work uncovers a mechanism allowing "select" gastrointestinal bacteria to evade antibiotic treatment.

In Vitro Microevolution and Co-Selection Assessment of Amoxicillin and Cefotaxime Impact on Escherichia coli Resistance Development

The global spread of antimicrobial resistance has become a prominent issue in both veterinary and public health in the 21st century. The extensive use of amoxicillin, a beta-lactam antibiotic, and consequent resistance development are particularly alarming in food-producing animals, with a focus on the swine and poultry sectors. Another beta-lactam, cefotaxime, is widely utilized in human medicine, where the escalating resistance to third- and fourth-generation cephalosporins is a major concern. The aim of this study was to simulate the development of phenotypic and genotypic resistance to beta-lactam antibiotics, focusing on amoxicillin and cefotaxime. The investigation of the minimal inhibitory concentrations (MIC) of antibiotics was performed at 1×, 10×, 100×, and 1000× concentrations using the modified microbial evolution and growth arena (MEGA-plate) method. Our results indicate that amoxicillin significantly increased the MIC values of several tested antibiotics, except for oxytetracycline and florfenicol. In the case of cefotaxime, this increase was observed in all classes. A total of 44 antimicrobial resistance genes were identified in all samples. Chromosomal point mutations, particularly concerning cefotaxime, revealed numerous complex mutations, deletions, insertions, and single nucleotide polymorphisms (SNPs) that were not experienced in the case of amoxicillin. The findings suggest that, regarding amoxicillin, the point mutation of the acrB gene could explain the observed MIC value increases due to the heightened activity of the acrAB-tolC efflux pump system. However, under the influence of cefotaxime, more intricate processes occurred, including complex amino acid substitutions in the ampC gene promoter region, increased enzyme production induced by amino acid substitutions and SNPs, as well as mutations in the acrR and robA repressor genes that heightened the activity of the acrAB-tolC efflux pump system. These changes may contribute to the significant MIC increases observed for all tested antibiotics. The results underscore the importance of understanding cross-resistance development between individual drugs when choosing clinical alternative drugs. The point mutations in the mdtB and emrR genes may also contribute to the increased activity of the mdtABC-tolC and emrAB-tolC pump systems against all tested antibiotics. The exceptionally high mutation rate induced by cephalosporins justifies further investigations to clarify the exact mechanism behind.

Comparative genomics of fungal mutants provides a systemic view of extreme cadmium tolerance in eukaryotic microbes

Whether eukaryotic organisms can evolve for higher heavy metal resistance in laboratory conditions remains unknown. In this study, we challenged a macrofungi, Pleurotus ostreatus, in a designed microbial evolution and growth arena (MEGA)-plate with an extreme Cd gradient. Within months, the wild-type strain developed 10 mutants, exhibiting a maximum three-fold increase in Cd tolerance and slower growth rates. Genomic sequencing and re-sequencing of the wild-type and ten mutant strains generated about 51 GB data, allowing a comprehensive comparative genomics analysis. As a result, a total of 2512 common single nucleotide polymorphisms, 70 inserts and deletes, 39 copy number variations and 21 structural variations were found in the 10 mutants. The mutant genes were primarily involved in substrate transport. In combination with transcriptome analysis, we discovered that the ten mutants had a distinct Cd-resistant mechanism compared to the wild-type strain. Genes involved in oxidation-reduction, ion transmembrane transport, and metal compartment/efflux are primarily responsible for the extreme Cd tolerance in the P. ostreatus mutants. Our findings contribute to the understanding of eukaryotic Cd resistance at the genome level and establish a foundation for developing bioremediation tools utilizing highly tolerant macrofungi.

Range expansion is both slower and more variable with rapid evolution across a spatial gradient in temperature

Rapid evolution in colonising populations can alter our ability to predict future range expansions. Recent theory suggests that the dynamics of replicate range expansions are less variable, and hence more predictable, with increased selection at the expanding range front. Here, we test whether selection from environmental gradients across space produces more consistent range expansion speeds, using the experimental evolution of replicate duckweed populations colonising landscapes with and without a temperature gradient. We found that the range expansion across a temperature gradient was slower on average, with range-front populations displaying higher population densities, and genetic signatures and trait changes consistent with directional selection. Despite this, we found that with a spatial gradient range expansion speed became more variable and less consistent among replicates over time. Our results therefore challenge current theory, highlighting that chance can still shape the genetic response to selection to influence our ability to predict range expansion speeds.

Sub-inhibitory antibiotic treatment selects for enhanced metabolic efficiency

Bacterial growth and metabolic rates are often closely related. However, under antibiotic selection, a paradox in this relationship arises: antibiotic efficacy decreases when bacteria are metabolically dormant, yet antibiotics select for resistant cells that grow fastest during treatment. That is, antibiotic selection counterintuitively favors bacteria with fast growth but slow metabolism. Despite this apparent contradiction, antibiotic resistant cells have historically been characterized primarily in the context of growth, whereas the extent of analogous changes in metabolism is comparatively unknown. Here, we observed that previously evolved antibiotic-resistant strains exhibited a unique relationship between growth and metabolism whereby nutrient utilization became more efficient, regardless of the growth rate. To better understand this unexpected phenomenon, we used a simplified model to simulate bacterial populations adapting to sub-inhibitory antibiotic selection through successive bottlenecking events. Simulations predicted that sub-inhibitory bactericidal antibiotic concentrations could select for enhanced metabolic efficiency, defined based on nutrient utilization: drug-adapted cells are able to achieve the same biomass while utilizing less substrate, even in the absence of treatment. Moreover, simulations predicted that restoring metabolic efficiency would re-sensitize resistant bacteria exhibiting metabolic-dependent resistance; we confirmed this result using adaptive laboratory evolutions of Escherichia coli under carbenicillin treatment. Overall, these results indicate that metabolic efficiency is under direct selective pressure during antibiotic treatment and that differences in evolutionary context may determine both the efficacy of different antibiotics and corresponding re-sensitization approaches.IMPORTANCEThe sustained emergence of antibiotic-resistant pathogens combined with the stalled drug discovery pipelines highlights the critical need to better understand the underlying evolution mechanisms of antibiotic resistance. To this end, bacterial growth and metabolic rates are often closely related, and resistant cells have historically been characterized exclusively in the context of growth. However, under antibiotic selection, antibiotics counterintuitively favor cells with fast growth, and slow metabolism. Through an integrated approach of mathematical modeling and experiments, this study thereby addresses the significant knowledge gap of whether antibiotic selection drives changes in metabolism that complement, and/or act independently, of antibiotic resistance phenotypes.

Microfluidics for adaptation of microorganisms to stress: design and application

Microfluidic systems have fundamentally transformed the realm of adaptive laboratory evolution (ALE) for microorganisms by offering unparalleled control over environmental conditions, thereby optimizing mutant generation and desired trait selection. This review summarizes the substantial influence of microfluidic technologies and their design paradigms on microbial adaptation, with a primary focus on leveraging spatial stressor concentration gradients to enhance microbial growth in challenging environments. Specifically, microfluidic platforms tailored for scaled-down ALE processes not only enable highly autonomous and precise setups but also incorporate novel functionalities. These capabilities encompass fostering the growth of biofilms alongside planktonic cells, refining selection gradient profiles, and simulating adaptation dynamics akin to natural habitats. The integration of these aspects enables shaping phenotypes under pressure, presenting an unprecedented avenue for developing robust, stress-resistant strains, a feat not easily attainable using conventional ALE setups. The versatility of these microfluidic systems is not limited to fundamental research but also offers promising applications in various areas of stress resistance. As microfluidic technologies continue to evolve and merge with cutting-edge methodologies, they possess the potential not only to redefine the landscape of microbial adaptation studies but also to expedite advancements in various biotechnological areas. KEY POINTS: • Microfluidics enable precise microbial adaptation in controlled gradients. • Microfluidic ALE offers insights into stress resistance and distinguishes between resistance and persistence. • Integration of adaptation-influencing factors in microfluidic setups facilitates efficient generation of stress-resistant strains.

Laboratory Evolution of Antimicrobial Resistance in Bacteria to Develop Rational Treatment Strategies

Laboratory evolution studies, particularly with Escherichia coli, have yielded invaluable insights into the mechanisms of antimicrobial resistance (AMR). Recent investigations have illuminated that, with repetitive antibiotic exposures, bacterial populations will adapt and eventually become tolerant and resistant to the drugs. Through intensive analyses, these inquiries have unveiled instances of convergent evolution across diverse antibiotics, the pleiotropic effects of resistance mutations, and the role played by loss-of-function mutations in the evolutionary landscape. Moreover, a quantitative analysis of multidrug combinations has shed light on collateral sensitivity, revealing specific drug combinations capable of suppressing the acquisition of resistance. This review article introduces the methodologies employed in the laboratory evolution of AMR in bacteria and presents recent discoveries concerning AMR mechanisms derived from laboratory evolution. Additionally, the review outlines the application of laboratory evolution in endeavors to formulate rational treatment strategies.

In Vitro Microevolution and Co-Selection Assessment of Florfenicol Impact on Escherichia coli Resistance Development

The issue of antimicrobial resistance is becoming an increasingly serious challenge in both human and veterinary medicine. Prudent antimicrobial use in veterinary medicine is warranted and supported by international guidelines, with the Antimicrobial Advice Ad Hoc Expert Group (AMEG) placing particular emphasis on the critically important group B antimicrobials. These antimicrobials are commonly employed, especially in the poultry and swine industry. The impact of florfenicol, a veterinary antibiotic, was studied on the resistance development of Escherichia coli. The aim of the study was to investigate the effect of the use of florfenicol on the development of phenotypic and genomic resistances, not only to the drug itself but also to other drugs. The minimum inhibitory concentrations (MICs) of the antibiotics were investigated at 1×, 10×, 100× and 1000× concentrations using the adapted Microbial Evolution and Growth Arena (MEGA-plate) method. The results demonstrate that florfenicol can select for resistance to fluoroquinolone antibiotics (167× MIC value increase) and cephalosporins (67× MIC value increase). A total of 44 antimicrobial resistance genes were identified, the majority of which were consistent across the samples. Chromosomal point mutations, including alterations in resistance-associated and regulatory genes (acrB, acrR, emrR and robA), are thought to trigger multiple drug efflux pump activations, leading to phenotypically increased resistance. The study underscores the impact of florfenicol and its role in the development of antimicrobial resistance, particularly concerning fluoroquinolone antibiotics and cephalosporins. This study is the first to report florfenicol's dose-dependent enhancement of other antibiotics' MICs, linked to mutations in SOS-box genes (mdtABC-tolC, emrAB-tolC and acrAB-tolC) and increased multidrug efflux pump genes. Mutations in the regulatory genes acrR, emrR and rpbA support the possibility of increased gene expression. The results are crucial for understanding antimicrobial resistance and its development, highlighting the promising potential of in vitro evolutionary and coselection studies for future research.

Competition and evolutionary selection among core regulatory motifs in gene expression control

Gene products that are beneficial in one environment may become burdensome in another, prompting the emergence of diverse regulatory schemes that carry their own bioenergetic cost. By ensuring that regulators are only expressed when needed, we demonstrate that autoregulation generally offers an advantage in an environment combining mutation and time-varying selection. Whether positive or negative feedback emerges as dominant depends primarily on the demand for the target gene product, typically to ensure that the detrimental impact of inevitable mutations is minimized. While self-repression of the regulator curbs the spread of these loss-of-function mutations, self-activation instead facilitates their propagation. By analyzing the transcription network of multiple model organisms, we reveal that reduced bioenergetic cost may contribute to the preferential selection of autoregulation among transcription factors. Our results not only uncover how seemingly equivalent regulatory motifs have fundamentally different impact on population structure, growth dynamics, and evolutionary outcomes, but they can also be leveraged to promote the design of evolutionarily robust synthetic gene circuits.

Steering and controlling evolution - from bioengineering to fighting pathogens

Control interventions steer the evolution of molecules, viruses, microorganisms or other cells towards a desired outcome. Applications range from engineering biomolecules and synthetic organisms to drug, therapy and vaccine design against pathogens and cancer. In all these instances, a control system alters the eco-evolutionary trajectory of a target system, inducing new functions or suppressing escape evolution. Here, we synthesize the objectives, mechanisms and dynamics of eco-evolutionary control in different biological systems. We discuss how the control system learns and processes information about the target system by sensing or measuring, through adaptive evolution or computational prediction of future trajectories. This information flow distinguishes pre-emptive control strategies by humans from feedback control in biotic systems. We establish a cost-benefit calculus to gauge and optimize control protocols, highlighting the fundamental link between predictability of evolution and efficacy of pre-emptive control.

Short-term evolution of antibiotic responses in highly dynamic environments favors loss of regulation

Microbes inhabit natural environments that are remarkably dynamic, with sudden environmental shifts that require immediate action by the cell. To cope with changing environments, microbes are equipped with regulated response mechanisms that are only activated when needed. However, when exposed to extreme environments such as clinical antibiotic treatments, complete loss of regulation is frequently observed. Although recent studies suggest that the initial evolution of microbes in new environments tends to favor mutations in regulatory pathways, it is not clear how this evolution is affected by how quickly conditions change (i.e. dynamics), or which mechanisms are commonly used to implement new regulation. Here, we perform experimental evolution on continuous cultures of E. coli carrying the tetracycline resistance tet operon to identify specific types of mutations that adapt drug responses to different dynamical regimens of drug administration. When cultures are evolved under gradually increasing tetracycline concentrations, we observe no mutations in the tet operon, but a predominance of fine-tuning mutations increasing the affinity of alternative efflux pump AcrB to tetracycline. When cultures are instead periodically exposed to large drug doses, all populations developed transposon insertions in repressor TetR, resulting in loss of regulation of efflux pump TetA. We use a mathematical model of the dynamics of antibiotic responses to show that sudden exposure to large drug concentrations can overwhelm regulated responses, which cannot induce resistance fast enough, resulting in fitness advantage for constitutive expression of resistance. These results help explain the loss of regulation of antibiotic resistance by opportunistic pathogens evolving in clinical environments. Our experiment supports the notion that initial evolution in new ecological niches proceeds largely through regulatory mutations and suggests that transposon insertions are a main mechanism driving this process.

Pervasive gene deregulation underlies adaptation and maladaptation in trimethoprim-resistant E. coli

IMPORTANCE

Bacteria employ a number of mechanisms to adapt to antibiotics. Mutations in transcriptional regulators alter the expression levels of genes that can change the susceptibility of bacteria to antibiotics. Two-component signaling proteins are a major class of signaling molecule used by bacteria to regulate transcription. In previous work, we found that mutations in MgrB, a feedback regulator of the PhoQP two-component system, conferred trimethoprim tolerance to Escherichia coli. Here, we elucidate how mutations in MgrB have a domino-like effect on the gene regulatory network of E. coli. As a result, pervasive perturbation of gene regulation ensues. Depending on the environmental context, this pervasive deregulation is either adaptive or maladaptive. Our study sheds light on how deregulation of gene expression can be beneficial for bacteria when challenged with antibiotics, and why regulators like MgrB may have evolved in the first place.

The Outcome of Antibiotic Overuse before and during the COVID-19 Pandemic in a Tertiary Care Hospital in Oman

Antimicrobial resistance (AMR), a serious global public health challenge, may have accelerated development during the COVID-19 pandemic because antibiotics were prescribed for COVID-19. This study aimed to assess antibiotics use before and during the pandemic and correlate the results with the rate of resistant microorganisms detected in hospitalized patients during the study period. This single-center study looked retrospectively at four years of data (2018-2021) from Royal Hospital, Muscat, which is the biggest hospital in Oman with approximately 60,000 hospital admissions yearly. The consumption rate of ceftriaxone, piperacillin tazobactam, meropenem, and vancomycin was presented as the antibiotic consumption index, the ratio of defined daily dose (DDD) per 100 bed days. Analyses were performed using the nonparametric test for trend across the study period. Correlation between antibiotic consumption indexes and the isolated microorganisms in the four-year study period was performed using Spearman's rank correlation coefficient. We compared data from the pre-COVID-19 to the COVID-19 period. Though more patients were admitted pre-COVID-19 (132,828 versus 119,191 during COVID-19), more antibiotics were consumed during the pandemic (7350 versus 7915); vancomycin and ceftriaxone had higher consumption during than before the pandemic (p-values 0.001 and 0.036, respectively). Vancomycin-resistant Enterococcus (VRE) and Candida auris were detected more during the COVID-19 period with p-values of 0.026 and 0.004, respectively. Carbapenem-resistant Enterobacterales (CRE), vancomycin-resistant Enterococcus spp., and C. auris were detected more often during the pandemic with p-values of 0.011, 0.002, and 0.03, respectively. Significant positive correlations between antibiotic consumption and drug-resistant isolates were noted. This study confirms that the overuse of antibiotics triggers the development of bacterial resistance; our results emphasize the importance of antibiotic control.

Capsule Shedding and Membrane Binding Enhanced Photodynamic Killing of Gram-Negative Bacteria by a Unimolecular Conjugated Polyelectrolyte

The development of new antimicrobial agents to treat infections caused by Gram-negative bacteria is of paramount importance due to increased antibiotic resistance worldwide. Herein, we show that a water-soluble porphyrin-cored hyperbranched conjugated polyelectrolyte (PorHP) exhibits high photodynamic bactericidal activity against the Gram-negative bacteria tested, including a multidrug-resistant (MDR) pathogen, while demonstrating low cytotoxicity toward mammalian cells. Comprehensive analyses reveal that the antimicrobial activity of PorHP proceeds via a multimodal mechanism by effective bacterial capsule shedding, strong bacterial outer membrane binding, and singlet oxygen generation. Through this multimodal antimicrobial mechanism, PorHP displays significant performance for Gram-negative bacteria with >99.9% photodynamic killing efficacy. Overall, PorHP shows great potential as an antimicrobial agent in fighting the growing threat of Gram-negative bacteria.

Reinforcement Learning informs optimal treatment strategies to limit antibiotic resistance

Antimicrobial resistance was estimated to be associated with 4.95 million deaths worldwide in 2019. It is possible to frame the antimicrobial resistance problem as a feedback-control problem. If we could optimize this feedback-control problem and translate our findings to the clinic, we could slow, prevent or reverse the development of high-level drug resistance. Prior work on this topic has relied on systems where the exact dynamics and parameters were known a priori. In this study, we extend this work using a reinforcement learning (RL) approach capable of learning effective drug cycling policies in a system defined by empirically measured fitness landscapes. Crucially, we show that is possible to learn effective drug cycling policies despite the problems of noisy, limited, or delayed measurement. Given access to a panel of 15 β-lactam antibiotics with which to treat the simulated E. coli population, we demonstrate that RL agents outperform two naive treatment paradigms at minimizing the population fitness over time. We also show that RL agents approach the performance of the optimal drug cycling policy. Even when stochastic noise is introduced to the measurements of population fitness, we show that RL agents are capable of maintaining evolving populations at lower growth rates compared to controls. We further tested our approach in arbitrary fitness landscapes of up to 1024 genotypes. We show that minimization of population fitness using drug cycles is not limited by increasing genome size. Our work represents a proof-of-concept for using AI to control complex evolutionary processes.

Origin of Antibiotics and Antibiotic Resistance, and Their Impacts on Drug Development: A Narrative Review

Antibiotics have revolutionized medicine, saving countless lives since their discovery in the early 20th century. However, the origin of antibiotics is now overshadowed by the alarming rise in antibiotic resistance. This global crisis stems from the relentless adaptability of microorganisms, driven by misuse and overuse of antibiotics. This article explores the origin of antibiotics and the subsequent emergence of antibiotic resistance. It delves into the mechanisms employed by bacteria to develop resistance, highlighting the dire consequences of drug resistance, including compromised patient care, increased mortality rates, and escalating healthcare costs. The article elucidates the latest strategies against drug-resistant microorganisms, encompassing innovative approaches such as phage therapy, CRISPR-Cas9 technology, and the exploration of natural compounds. Moreover, it examines the profound impact of antibiotic resistance on drug development, rendering the pursuit of new antibiotics economically challenging. The limitations and challenges in developing novel antibiotics are discussed, along with hurdles in the regulatory process that hinder progress in this critical field. Proposals for modifying the regulatory process to facilitate antibiotic development are presented. The withdrawal of major pharmaceutical firms from antibiotic research is examined, along with potential strategies to re-engage their interest. The article also outlines initiatives to overcome economic challenges and incentivize antibiotic development, emphasizing international collaborations and partnerships. Finally, the article sheds light on government-led initiatives against antibiotic resistance, with a specific focus on the Middle East. It discusses the proactive measures taken by governments in the region, such as Saudi Arabia and the United Arab Emirates, to combat this global threat. In the face of antibiotic resistance, a multifaceted approach is imperative. This article provides valuable insights into the complex landscape of antibiotic development, regulatory challenges, and collaborative efforts required to ensure a future where antibiotics remain effective tools in safeguarding public health.

Systematic analyses identify modes of action of ten clinically relevant biocides and antibiotic antagonism in Acinetobacter baumannii

Concerns exist that widespread use of antiseptic or disinfectant biocides could contribute to the emergence and spread of multidrug-resistant bacteria. To investigate this, we performed transposon-directed insertion-site sequencing (TraDIS) on the multidrug-resistant pathogen, Acinetobacter baumannii, exposed to a panel of ten structurally diverse and clinically relevant biocides. Multiple gene targets encoding cell envelope or cytoplasmic proteins involved in processes including fatty acid biogenesis, multidrug efflux, the tricarboxylic acid cycle, cell respiration and cell division, were identified to have effects on bacterial fitness upon biocide exposure, suggesting that these compounds may have intracellular targets in addition to their known effects on the cell envelope. As cell respiration genes are required for A. baumannii fitness in biocides, we confirmed that sub-inhibitory concentrations of the biocides that dissipate membrane potential can promote A. baumannii tolerance to antibiotics that act intracellularly. Our results support the concern that residual biocides might promote antibiotic resistance in pathogenic bacteria.

Competitive interactions facilitate resistance development against antimicrobials

While the evolution of antimicrobial resistance is well studied in free-living bacteria, information on resistance development in dense and diverse biofilm communities is largely lacking. Therefore, we explored how the social interactions in a duo-species biofilm composed of the brewery isolates Pseudomonas rhodesiae and Raoultella terrigena influence the adaptation to the broad-spectrum antimicrobial sulfathiazole. Previously, we showed that the competition between these brewery isolates enhances the antimicrobial tolerance of P. rhodesiae. Here, we found that this enhanced tolerance in duo-species biofilms is associated with a strongly increased antimicrobial resistance development in P. rhodesiae. Whereas P. rhodesiae was not able to evolve resistance against sulfathiazole in monospecies conditions, it rapidly evolved resistance in the majority of the duo-species communities. Although the initial presence of R. terrigena was thus required for P. rhodesiae to acquire resistance, the resistance mechanisms did not depend on the presence of R. terrigena. Whole genome sequencing of resistant P. rhodesiae clones showed no clear mutational hot spots. This indicates that the acquired resistance phenotype depends on complex interactions between low-frequency mutations in the genetic background of the strains. We hypothesize that the increased tolerance in duo-species conditions promotes resistance by enhancing the selection of partially resistant mutants and opening up novel evolutionary trajectories that enable such genetic interactions. This hypothesis is reinforced by experimentally excluding potential effects of increased initial population size, enhanced mutation rate, and horizontal gene transfer. Altogether, our observations suggest that the community mode of life and the social interactions therein strongly affect the accessible evolutionary pathways toward antimicrobial resistance.IMPORTANCEAntimicrobial resistance is one of the most studied bacterial properties due to its enormous clinical and industrial relevance; however, most research focuses on resistance development of a single species in isolation. In the present study, we showed that resistance evolution of brewery isolates can differ greatly between single- and mixed-species conditions. Specifically, we observed that the development of antimicrobial resistance in certain species can be significantly enhanced in co-culture as compared to the single-species conditions. Overall, the current study emphasizes the need of considering the within bacterial interactions in microbial communities when evaluating antimicrobial treatments and resistance evolution.

Evolution of haploid and diploid populations reveals common, strong, and variable pleiotropic effects in non-home environments

Adaptation is driven by the selection for beneficial mutations that provide a fitness advantage in the specific environment in which a population is evolving. However, environments are rarely constant or predictable. When an organism well adapted to one environment finds itself in another, pleiotropic effects of mutations that made it well adapted to its former environment will affect its success. To better understand such pleiotropic effects, we evolved both haploid and diploid barcoded budding yeast populations in multiple environments, isolated adaptive clones, and then determined the fitness effects of adaptive mutations in 'non-home' environments in which they were not selected. We find that pleiotropy is common, with most adaptive evolved lineages showing fitness effects in non-home environments. Consistent with other studies, we find that these pleiotropic effects are unpredictable: they are beneficial in some environments and deleterious in others. However, we do find that lineages with adaptive mutations in the same genes tend to show similar pleiotropic effects. We also find that ploidy influences the observed adaptive mutational spectra in a condition-specific fashion. In some conditions, haploids and diploids are selected with adaptive mutations in identical genes, while in others they accumulate mutations in almost completely disjoint sets of genes.

Pleiotropic hubs drive bacterial surface competition through parallel changes in colony composition and expansion

Bacteria commonly adhere to surfaces where they compete for both space and resources. Despite the importance of surface growth, it remains largely elusive how bacteria evolve on surfaces. We previously performed an evolution experiment where we evolved distinct Bacilli populations under a selective regime that favored colony spreading. In just a few weeks, colonies of Bacillus subtilis showed strongly advanced expansion rates, increasing their radius 2.5-fold relative to that of the ancestor. Here, we investigate what drives their rapid evolution by performing a uniquely detailed analysis of the evolutionary changes in colony development. We find mutations in diverse global regulators, RicT, RNAse Y, and LexA, with strikingly similar pleiotropic effects: They lower the rate of sporulation and simultaneously facilitate colony expansion by either reducing extracellular polysaccharide production or by promoting filamentous growth. Combining both high-throughput flow cytometry and gene expression profiling, we show that regulatory mutations lead to highly reproducible and parallel changes in global gene expression, affecting approximately 45% of all genes. This parallelism results from the coordinated manner by which regulators change activity both during colony development-in the transition from vegetative growth to dormancy-and over evolutionary time. This coordinated activity can however also break down, leading to evolutionary divergence. Altogether, we show how global regulators function as major pleiotropic hubs that drive rapid surface adaptation by mediating parallel changes in both colony composition and expansion, thereby massively reshaping gene expression.

Metallo-β-lactamase SMB-1 evolves into a more efficient hydrolase under the selective pressure of meropenem

Metallo-β-lactamases (MβLs) are the primary mechanism of resistance to carbapenem antibiotics. To elucidate how MβLs have evolved with the introduction and use of antibiotics, the mutation and evolution of SMB-1 from Serratia marcescens were investigated in microbial evolution plates containing discontinuous meropenem (MEM) concentration gradients. The results revealed 2-point mutations, A242G and S257R; 1 double-site mutation, C240G/E258G; and 3 frameshift mutations, M5, M12, and M13, which are all missense mutations situated at the C-terminus. Compared with that of the wild-type (WT), the minimum inhibitory concentrations (MICs) of MEM for A242G, C240G/E258G, M5, M12, and M13 increased at least 120-fold, and that of S257R increased 8-fold. The catalytic efficiency kcat/Km increased by 365% and 647%, respectively. Concerning the structural changes, the structure at the active site changed from an ordered structure to an unordered conformation. Simultaneously, the flexibility of loop 1 was enhanced. These changes increased the volume of the active site cavity; thus, this was more conducive to exposing the Zn2+ site, facilitating substrate binding and conversion to products. In A242G, structural changes in Gly-242 can be transmitted to the active region via a network of interactions between the side chains of Gly-242 and the amino acid side chains near the active pocket. Together, these results pointed to the process of persistent drug tolerance and resistance, the SMB-1 enzyme evolved into a more exquisite structure with increased flexibility and stability, and stronger hydrolysis activity via genetic mutations and structural changes.

Hormones and the antioxidant transduction pathway and gene expression, mediated by Serratia marcescens DB1, lessen the lethality of heavy metals (As, Ni, and Cr) in Oryza sativa L

Microorganisms have recently gained recognition as efficient biological tool for reducing heavy metal toxicity in crops. In this experiment, we isolated a potent heavy metal (As, Ni, and Cr) resistant rhizobacterium Serratia marcescens DB1 and detected its plant growth promoting traits such as phosphate solubilization, gibberellin synthesis, organic acid production and amino acid regulation. Based on these findings, DB1 was further investigated for application in a rice var. Hwayeongbyeo subjected to 1 mM As, 4 mM Ni, and 4 mM Cr stress. The rice plants treated with Cr and Ni appeared healthy but were lethal, indicating unfitness for consumption due to toxic metal deposition, whereas the plants treated with > 1 mM As instantaneously died. Our results showed that DB1 inoculation significantly decreased metal accumulation in the rice shoots. Particularly, Cr uptake dropped by 16.55% and 22.12% in (Cr + DB1) and (Cr + As + Ni + DB1), respectively, As dropped by 48.90% and 35.82% in (As + DB1) and (Cr + As + Ni + DB1), respectively, and Ni dropped by 7.95% and 19.56% in (Ni + DB1) and (Cr + As + Ni + DB1), respectively. These findings were further validated by gene expression analysis results, which showed that DB1 inoculation significantly decreased the expression of OsPCS1 (a phytochelatin synthase gene), OsMTP1 (a metal transporting gene), and OsMTP5 (a gene for the expulsion of excess metal). Moreover, DB1 inoculation considerably enhanced the morphological growth of rice through modulation of endogenous phytohormones (abscisic acid, salicylic acid, and jasmonic acid) and uptake of essential elements such as K and P. These findings indicate that DB1 is an effective biofertilizer that can mitigate heavy metal toxicity in rice crops.

Bacterial motility can govern the dynamics of antibiotic resistance evolution

Spatial heterogeneity in antibiotic concentrations is thought to accelerate the evolution of antibiotic resistance, but current theory and experiments have overlooked the effect of cell motility on bacterial adaptation. Here, we study bacterial evolution in antibiotic landscapes with a quantitative model where bacteria evolve under the stochastic processes of proliferation, death, mutation and migration. Numerical and analytical results show that cell motility can both accelerate and decelerate bacterial adaptation by affecting the degree of genotypic mixing and ecological competition. Moreover, we find that for sufficiently high rates, cell motility can limit bacterial survival, and we derive conditions for all these regimes. Similar patterns are observed in more complex scenarios, namely where bacteria can bias their motion in chemical gradients (chemotaxis) or switch between motility phenotypes either stochastically or in a density-dependent manner. Overall, our work reveals limits to bacterial adaptation in antibiotic landscapes that are set by cell motility.

Intrahost evolution of the gut microbiota

A massive number of microorganisms, belonging to different species, continuously divide inside the guts of animals and humans. The large size of these communities and their rapid division times imply that we should be able to watch microbial evolution in the gut in real time, in a similar manner to what has been done in vitro. Here, we review recent findings on how natural selection shapes intrahost evolution (also known as within-host evolution), with a focus on the intestines of mice and humans. The microbiota of a healthy host is not as static as initially thought from the information measured at only one genomic marker. Rather, the genomes of each gut-colonizing species can be highly dynamic, and such dynamism seems to be related to the microbiota species diversity. Genetic and bioinformatic tools, and analysis of time series data, allow quantification of the selection strength on emerging mutations and horizontal transfer events in gut ecosystems. The drivers and functional consequences of gut evolution can now begin to be grasped. The rules of this intrahost microbiota evolution, and how they depend on the biology of each species, need to be understood for more effective development of microbiota therapies to help maintain or restore host health.

A 0D-2D Heterojunction Bismuth Molybdate-Anchored Multifunctional Hydrogel for Highly Efficient Eradication of Drug-Resistant Bacteria

Due to the increasing antibiotic resistance and the lack of broad-spectrum antibiotics, there is an urgent requirement to develop fresh strategies to combat multidrug-resistant pathogens. Herein, defect-rich bismuth molybdate heterojunctions [zero-dimensional (0D) Bi4MoO9/two-dimensional (2D) Bi2MoO6, MBO] were designed for rapid capture of bacteria and synergistic photocatalytic sterilization. The as-prepared MBO was experimentally and theoretically demonstrated to possess defects, heterojunctions, and irradiation triple-enhanced photocatalytic activity for efficient generation of reactive oxygen species (ROS) due to the exposure of more active sites and separation of effective electron-hole pairs. Meanwhile, dopamine-modified MBO (pMBO) achieved a positively charged and rough surface, which conferred strong bacterial adhesion and physical penetration to the nanosheets, effectively trapping bacteria within the damage range and enhancing ROS damage. Based on this potent antibacterial ability of pMBO, a multifunctional hydrogel consisting of poly(vinyl alcohol) cross-linked tannic acid-coated cellulose nanocrystals (CPTB) and pMBO, namely CPTB@pMBO, is developed and convincingly effective against methicillin-resistant Staphylococcus aureus in a mouse skin infection model. In addition, the strategy of combining a failed beta-lactam antibiotic with CPTB@pMBO to photoinactivation with no resistance observed was developed, which presented an idea to address the issue of antibiotic resistance in bacteria and to explore facile anti-infection methods. In addition, CPTB@pMBO can reduce excessive proteolysis of tissue and inflammatory response by regulating the expression of genes and pro-inflammatory factors in vivo, holding great potential for the effective treatment of wound infections caused by drug-resistant bacteria.

Combatting persister cells: The daunting task in post-antibiotics era

Over the years, much attention has been drawn to antibiotic resistance bacteria, but drug inefficacy caused by a subgroup of special phenotypic variants - persisters - has been largely neglected in both scientific and clinical field. Interestingly, this subgroup of phenotypic variants displayed their power of withstanding sufficient antibiotics exposure in a mechanism different from antibiotic resistance. In this review, we summarized the clinical importance of bacterial persisters, the evolutionary link between resistance, tolerance, and persistence, redundant mechanisms of persister formation as well as methods of studying persister cells. In the light of our recent findings of membrane-less organelle aggresome and its important roles in regulating bacterial dormancy depth, we propose an alternative approach for anti-persister therapy. That is, to force a persister into a deeper dormancy state to become a VBNC (viable but non-culturable) cell that is incapable of regrowth. We hope to provide the latest insights on persister studies and call upon more research interest into this field.

A stochastic analysis of the interplay between antibiotic dose, mode of action, and bacterial competition in the evolution of antibiotic resistance

The use of an antibiotic may lead to the emergence and spread of bacterial strains resistant to this antibiotic. Experimental and theoretical studies have investigated the drug dose that minimizes the risk of resistance evolution over the course of treatment of an individual, showing that the optimal dose will either be the highest or the lowest drug concentration possible to administer; however, no analytical results exist that help decide between these two extremes. To address this gap, we develop a stochastic mathematical model of bacterial dynamics under antibiotic treatment. We explore various scenarios of density regulation (bacterial density affects cell birth or death rates), and antibiotic modes of action (biostatic or biocidal). We derive analytical results for the survival probability of the resistant subpopulation until the end of treatment, the size of the resistant subpopulation at the end of treatment, the carriage time of the resistant subpopulation until it is replaced by a sensitive one after treatment, and we verify these results with stochastic simulations. We find that the scenario of density regulation and the drug mode of action are important determinants of the survival of a resistant subpopulation. Resistant cells survive best when bacterial competition reduces cell birth and under biocidal antibiotics. Compared to an analogous deterministic model, the population size reached by the resistant type is larger and carriage time is slightly reduced by stochastic loss of resistant cells. Moreover, we obtain an analytical prediction of the antibiotic concentration that maximizes the survival of resistant cells, which may help to decide which drug dosage (not) to administer. Our results are amenable to experimental tests and help link the within and between host scales in epidemiological models.

Using evolutionary principles to make clinical decisions: a case series of urinary tract infections

The principles of evolutionary medicine have significant potential to be useful in a wide variety of clinical situations. Despite this, few demonstrations of clinical applications exist. To address this paucity, a case series applying evolutionary medicine principles to urinary tract infections, a common medical condition is presented. This series demonstrates how applying evolutionary medicine principles can be used to augment clinical decision-making.

Guanidine-containing double-network silks with enhanced tensile and antibacterial property

The bacterial infection of surgical wounds results in prolonged hospitalization and even death of patients, calling for antibacterial function in modern suture products. To tackle this challenge, cationic guanidine-containing copolymer was synthesized, exhibiting antibacterial potency over 5 log reduction against both Gram-positive S. aureus and Gram-negative E. coli. Furthermore, we developed a double-network silk suture by integrating a guanidine-containing copolymer network into the silk fibroin network. This suture exhibited biocidal activity against S. aureus and E. coli, and superior strength compared to the commercial product in both dry and wet conditions. These results may bring general benefits to public health and medical equipment sustainability.

Selecting antibacterial aptamers against the BamA protein in Pseudomonas aeruginosa by incorporating genetic algorithm to optimise computational screening method

Antibiotic resistance is one of the biggest threats to global health resulting in an increasing number of people suffering from severe illnesses or dying due to infections that were once easily curable with antibiotics. Pseudomonas aeruginosa is a major pathogen that has rapidly developed antibiotic resistance and WHO has categorised this pathogen under the critical list. DNA aptamers can act as a potential candidate for novel antimicrobial agents. In this study, we demonstrated that an existing aptamer is able to affect the growth of P. aeruginosa. A computational screen for aptamers that could bind to a well-conserved and essential outer membrane protein, BamA in Gram-negative bacteria was conducted. Molecular docking of about 100 functional DNA aptamers with BamA protein was performed via both local and global docking approaches. Additionally, genetic algorithm analysis was carried out to rank the aptamers based on their binding affinity. The top hits of aptamers with good binding to BamA protein were synthesised to investigate their in vitro antibacterial activity. Among all aptamers, Apt31, which is known to bind to an antitumor, Daunomycin, exhibited the highest HADDOCK score and resulted in a significant (p < 0.05) reduction in P. aeruginosa growth. Apt31 also induced membrane disruption that resulted in DNA leakage. Hence, computational screening may result in the identification of aptamers that bind to the desired active site with high affinity.

Counterintuitive properties of evolutionary measures: A stochastic process study in cyclic population structures with periodic environments

Local environmental interactions are a major factor in determining the success of a new mutant in structured populations. Spatial variations in the concentration of genotype-specific resources change the fitness of competing strategies locally and thus can drastically change the outcome of evolutionary processes in unintuitive ways. The question is how such local environmental variations in network population structures change the condition for selection and fixation probability of an advantageous (or deleterious) mutant. We consider linear graph structures and focus on the case where resources have a spatial periodic pattern. This is the simplest model with two parameters, length scale and fitness scales, representing heterogeneity. We calculate fixation probability and fixation times for a constant population birth-death process as fitness heterogeneity and period vary. Fixation probability is affected by not only the level of fitness heterogeneity but also spatial scale of resources variations set by period of distribution T. We identify conditions for which a previously a deleterious mutant (in a uniform environment) becomes beneficial as fitness heterogeneity is increased. We observe cases where the fixation probability of both mutant and resident types are more than their neutral value, 1/N, simultaneously. This coincides with exponential increase in time to fixation which points to potential coexistence of resident and mutant types. Finally, we discuss the effect of the 'fitness shift' where the fitness function of two types has a phase difference. We observe significant increases (or decreases) in the fixation probability of the mutant as a result of such phase shift.

BODIPY-Functionalized Natural Polymer Coatings for Multimodal Therapy of Drug-Resistant Bacterial Infection

The fact that multidrug resistance (MDR) could induce medical device-related infections, along with the invalidation of traditional antibiotics has become an intractable global medical issue. Therefore, there is a pressing need for innovative strategies of antibacterial functionalization of medical devices. For this purpose, a multimodal antibacterial coating that combines photothermal and photodynamic therapies (PTT/PDT) is developed here based on novel heavy atom-free photosensitizer compound, BDP-6 (a kind of boron-dipyrromethene). The photothermal conversion efficiency of BDP-6 is of 55.9%, which could improve biocompatibility during PTT/PDT process by reducing the exciting light power density. Furthermore, BDP-6, together with oxidized hyaluronic acid, is crosslinked with a natural polymer, gelatin, to fabricate a uniform coating (denoted as polyurethane (PU)-GHB) on the surface of polyurethane. PU-GHB has excellent synergistic in vitro PTT/PDT antibacterial performance against both susceptible bacteria and MDR bacteria. The antibacterial mechanisms are revealed as that hyperthermia could reduce the bacterial activity and enhance the permeability of inner membrane to reactive oxygen species by disturbing cell membrane. Meanwhile, in an infected abdominal wall hernia model, the notable anti-infection performance, good in vivo compatibility, and photoacoustic imaging property of PU-GHB are verified. A promising strategy of developing multifunctional antibacterial coatings on implanted medical devices is provided here.

Long-range alteration of the physical environment mediates cooperation between Pseudomonas aeruginosa swarming colonies

Pseudomonas aeruginosa makes and secretes massive amounts of rhamnolipid surfactants that enable swarming motility over biogel surfaces. But how these rhamnolipids interact with biogels to assist swarming remains unclear. Here, I use a combination of optical techniques across scales and genetically engineered strains to demonstrate that rhamnolipids can induce agar gel swelling over distances >10,000× the body size of an individual cell. The swelling front is on the micrometric scale and is easily visible using shadowgraphy. Rhamnolipid transport is not restricted to the surface of the gel but occurs through the whole thickness of the plate and, consequently, the spreading dynamics depend on the local thickness. Surprisingly, rhamnolipids can cross the whole gel and induce swelling on the opposite side of a two-face Petri dish. The swelling front delimits an area where the mechanical properties of the surface properties are modified: water wets the surface more easily, which increases the motility of individual bacteria and enables collective motility. A genetically engineered mutant unable to secrete rhamnolipids (ΔrhlA), and therefore unable to swarm, is rescued from afar with rhamnolipids produced by a remote colony. These results exemplify the remarkable capacity of bacteria to change the physical environment around them and its ecological consequences.

Improvement of Akanthomyces lecanii resistance to tebuconazole through UV-C radiation and selective pressure on microbial evolution and growth arenas

Tebuconazole (TEB) is a fungicide widely used in agriculture; however, its constant application has increased the emergence of resistant plant pathogenic fungal strains and reduced the effectiveness of fungi as biological control agents; for instance, the entomopathogenic and hyperparasitic fungus Akanthomyces lecanii, suitable for simultaneous biological control of insect pest and plant pathogenic fungi, is highly sensitive to fungicides. We carried out the induction of resistance to TEB in two wild type strains of A. lecanii by UV radiation and selective pressure in increasing fungicide gradients using a modified Microbial Evolution and Growth Arena (MEGA), to produce A. lecanii strains that can be used as biological control agent in the presence of tebuconazole. Nine UV-induced and three naturally adapted A. lecanii strains were resistant to TEB at the agriculturally recommended dose, and three irradiated strains were resistant to TEB concentration ten times higher; moreover, growth, sporulation rates, production of hydrolytic enzymes, and virulence against the hemipteran Coccus viridis, a major pest of coffee crops, were not affected in the TEB-resistant strains. These A. lecanii TEB-resistant strains would have a greater opportunity to develop and to establish themselves in fields where the fungicide is present and can be used in a combined biological-chemical strategy to improve insect and plant pathogenic fungal control in agriculture. Also, the selective pressure through modified MEGA plate methodology can be used for the adaptation of entomopathogenic filamentous fungi to withstand other chemical or abiotic stresses that limits its effectiveness for pest control.

A bioinspired silica nanocomposite for enhanced multidrug-resistant bacteria treatment and wash-free imaging

Bacterial infections have posed significant threats to public health due to the emergence of antibiotic resistance. In this work, a novel antibacterial composite nanomaterial based on spiky mesoporous silica spheres loaded with poly(ionic liquid)s and aggregation-induced emission luminogens (AIEgens) was designed for efficient multidrug-resistant (MDR) bacteria treatment and imaging. The nanocomposite exhibited excellent and long-term antibacterial activity towards both Gram-negative and Gram-positive bacteria. Meanwhile, fluorescent AIEgens facilitate real-time bacterial imaging. Our study provides a multifunctional platform and a promising alternative to antibiotics for combating pathogenic MDR bacteria.

The role of the light source in antimicrobial photodynamic therapy

Antimicrobial photodynamic therapy (APDT) is a promising approach to fight the growing problem of antimicrobial resistance that threatens health care, food security and agriculture. APDT uses light to excite a light-activated chemical (photosensitiser), leading to the generation of reactive oxygen species (ROS). Many APDT studies confirm its efficacy in vitro and in vivo against bacteria, fungi, viruses and parasites. However, the development of the field is focused on exploring potential targets and developing new photosensitisers. The role of light, a crucial element for ROS production, has been neglected. What are the main parameters essential for effective photosensitiser activation? Does an optimal light radiant exposure exist? And finally, which light source is best? Many reports have described the promising antibacterial effects of APDT in vitro, however, its application in vivo, especially in clinical settings remains very limited. The restricted availability may partially be due to a lack of standard conditions or protocols, arising from the diversity of selected photosensitising agents (PS), variable testing conditions including light sources used for PS activation and methods of measuring anti-bacterial activity and their effectiveness in treating bacterial infections. We thus sought to systematically review and examine the evidence from existing studies on APDT associated with the light source used. We show how the reduction of pathogens depends on the light source applied, radiant exposure and irradiance of light used, and type of pathogen, and so critically appraise the current state of development of APDT and areas to be addressed in future studies. We anticipate that further standardisation of the experimental conditions will help the field advance, and suggest key optical and biological parameters that should be reported in all APDT studies. More in vivo and clinical studies are needed and are expected to be facilitated by advances in light sources, leading to APDT becoming a sustainable, alternative therapeutic option for bacterial and other microbial infections in the future.

A coevolution experiment between Flavobacterium johnsoniae and Burkholderia thailandensis reveals parallel mutations that reduce antibiotic susceptibility

One interference mechanism of bacterial competition is the production of antibiotics. Bacteria exposed to antibiotics can resist antibiotic inhibition through intrinsic or acquired mechanisms. Here, we performed a coevolution experiment to understand the long-term consequences of antibiotic production and antibiotic susceptibility for two environmental bacterial strains. We grew five independent lines of the antibiotic-producing environmental strain, Burkholderia thailandensis E264, and the antibiotic-inhibited environmental strain, Flavobacterium johnsoniae UW101, together and separately on agar plates for 7.5 months (1.5 month incubations), transferring each line five times to new agar plates. We observed that the F. johnsoniae ancestor could tolerate the B. thailandensis-produced antibiotic through efflux mechanisms, but that the coevolved lines had reduced susceptibility. We then sequenced genomes from the coevolved and monoculture F. johnsoniae lines, and uncovered mutational ramifications for the long-term antibiotic exposure. The coevolved genomes from F. johnsoniae revealed four potential mutational signatures of reduced antibiotic susceptibility that were not observed in the evolved monoculture lines. Two mutations were found in tolC: one corresponding to a 33 bp deletion and the other corresponding to a nonsynonymous mutation. A third mutation was observed as a 1 bp insertion coding for a RagB/SusD nutrient uptake protein. The last mutation was a G83R nonsynonymous mutation in acetyl-coA carboxylayse carboxyltransferase subunit alpha (AccA). Deleting the 33 bp from tolC in the F. johnsoniae ancestor reduced antibiotic susceptibility, but not to the degree observed in coevolved lines. Furthermore, the accA mutation matched a previously described mutation conferring resistance to B. thailandensis-produced thailandamide. Analysis of B. thailandensis transposon mutants for thailandamide production revealed that thailandamide was bioactive against F. johnsoniae, but also suggested that additional B. thailandensis-produced antibiotics were involved in the inhibition of F. johnsoniae. This study reveals how multi-generational interspecies interactions, mediated through chemical exchange, can result in novel interaction-specific mutations, some of which may contribute to reductions in antibiotic susceptibility.