Toward prediction and control of antibiotic-resistance evolution

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.

Evolutionary Epidemiology Consequences of Trait-Dependent Control of Heterogeneous Parasites

AbstractDisease control can induce both demographic and evolutionary responses in host-parasite systems. Foreseeing the outcome of control therefore requires knowledge of the eco-evolutionary feedback between control and system. Previous work has assumed that control strategies have a homogeneous effect on the parasite population. However, this is not true when control targets those traits that confer to the parasite heterogeneous levels of resistance, which can additionally be related to other key parasite traits through evolutionary trade-offs. In this work, we develop a minimal model coupling epidemiological and evolutionary dynamics to explore possible trait-dependent effects of control strategies. In particular, we consider a parasite expressing continuous levels of a trait-determining resource exploitation and a control treatment that can be either positively or negatively correlated with that trait. We demonstrate the potential of trait-dependent control by considering that the decision maker may want to minimize both the damage caused by the disease and the use of treatment, due to possible environmental or economic costs. We identify efficient strategies showing that the optimal type of treatment depends on the amount applied. Our results pave the way for the study of control strategies based on evolutionary constraints, such as collateral sensitivity and resistance costs, which are receiving increasing attention for both public health and agricultural purposes.

Pervasive genotype-by-environment interactions shape the fitness effects of antibiotic resistance mutations

The fitness effects of antibiotic resistance mutations are a major driver of resistance evolution. While the nutrient environment affects bacterial fitness, experimental studies of resistance typically measure fitness of mutants in a single environment only. We explored how the nutrient environment affected the fitness effects of rifampicin-resistant rpoB mutations in Escherichia coli under several conditions critical for the emergence and spread of resistance-the presence of primary or secondary antibiotic, or the absence of any antibiotic. Pervasive genotype-by-environment (GxE) interactions determined fitness in all experimental conditions, with rank order of fitness in the presence and absence of antibiotics being strongly dependent on the nutrient environment. GxE interactions also affected the magnitude and direction of collateral effects of secondary antibiotics, in some cases so drastically that a mutant that was highly sensitive in one nutrient environment exhibited cross-resistance to the same antibiotic in another. It is likely that the mutant-specific impact of rpoB mutations on the global transcriptome underpins the observed GxE interactions. The pervasive, mutant-specific GxE interactions highlight the importance of doing what is rarely done when studying the evolution and spread of resistance in experimental and clinical work: assessing fitness of antibiotic-resistant mutants across a range of relevant environments.

The effect of local anesthetics against planktonic forms and film formation of S. aureus strains and its dependence on antiseptics activity

Today surgical site infections (SSIs) remain the second among hospital acquired infections in Europe and the USA. Staphylococcus aureus as a pathogen of nosocomial infections occur more frequently in surgical hospitals. The work was aimed to establish the effect of local anesthetics against planktonic forms and biofilm-formation of S. aureus clinical strains and the relationship between the sensitivity of S. aureus strains to local anesthetics and antiseptics in vitro. The antimicrobial activity of local anesthetics (0.5%, bupivacaine, 2.0% lidocaine, 0.375% ropivacaine) and antiseptics (decamethoxine 0.02%, chlorhexidine 0.05%) against clinical strains of S. aureus was observed and studied their ability to produce biofilms. The antimicrobial effect of local anesthetics was lower compared to antiseptics, but we observed inhibition of growth and reproduction of S. aureus in their presence. The ropivacaine solution and the lidocaine solution demonstrated almost the same activity against the studied microorganism isolates. Along with this, bupivacaine solution had the highest activity against the studied microorganisms. The minimal inhibitory concentration of bupivacaine for S. aureus was 2.2 times lower than the minimal inhibitory concentration of lidocaine and 2.1 times lower than the minimal inhibitory concentration of ropivacaine significantly (p < 0.05). Scientific research on various aspects of the formation of bacterial biofilms is a relevant area that will change approaches to the prophylaxis and treatment of a number of infections, including SSIs.

Adaptive Laboratory Evolution of Microorganisms: Methodology and Application for Bioproduction

Adaptive laboratory evolution (ALE) is a useful experimental methodology for fundamental scientific research and industrial applications to create microbial cell factories. By using ALE, cells are adapted to the environment that researchers set based on their objectives through the serial transfer of cell populations in batch cultivations or continuous cultures and the fitness of the cells (i.e., cell growth) under such an environment increases. Then, omics analyses of the evolved mutants, including genome sequencing, transcriptome, proteome and metabolome analyses, are performed. It is expected that researchers can understand the evolutionary adaptation processes, and for industrial applications, researchers can create useful microorganisms that exhibit increased carbon source availability, stress tolerance, and production of target compounds based on omics analysis data. In this review article, the methodologies for ALE in microorganisms are introduced. Moreover, the application of ALE for the creation of useful microorganisms as cell factories has also been introduced.

Analysis of the evolution of resistance to multiple antibiotics enables prediction of the Escherichia coli phenotype-based fitness landscape

The fitness landscape represents the complex relationship between genotype or phenotype and fitness under a given environment, the structure of which allows the explanation and prediction of evolutionary trajectories. Although previous studies have constructed fitness landscapes by comprehensively studying the mutations in specific genes, the high dimensionality of genotypic changes prevents us from developing a fitness landscape capable of predicting evolution for the whole cell. Herein, we address this problem by inferring the phenotype-based fitness landscape for antibiotic resistance evolution by quantifying the multidimensional phenotypic changes, i.e., time-series data of resistance for eight different drugs. We show that different peaks of the landscape correspond to different drug resistance mechanisms, thus supporting the validity of the inferred phenotype-fitness landscape. We further discuss how inferred phenotype-fitness landscapes could contribute to the prediction and control of evolution. This approach bridges the gap between phenotypic/genotypic changes and fitness while contributing to a better understanding of drug resistance evolution.

Stochastic establishment of β-lactam-resistant Escherichia coli mutants reveals conditions for collective resistance

For antibiotic resistance to arise, new resistant mutants must establish in a bacterial population before they can spread via natural selection. Comprehending the stochastic factors that influence mutant establishment is crucial for a quantitative understanding of antibiotic resistance emergence. Here, we quantify the single-cell establishment probability of four Escherichia coli strains expressing β-lactamase alleles with different activity against the antibiotic cefotaxime, as a function of antibiotic concentration in both unstructured (liquid) and structured (agar) environments. We show that concentrations well below the minimum inhibitory concentration (MIC) can substantially hamper establishment, particularly for highly resistant mutants. While the pattern of establishment suppression is comparable in both tested environments, we find greater variability in establishment probability on agar. Using a simple branching model, we investigate possible sources of this stochasticity, including environment-dependent lineage variability, but cannot reject other possible causes. Lastly, we use the single-cell establishment probability to predict each strain's MIC in the absence of social interactions. We observe substantially higher measured than predicted MIC values, particularly for highly resistant strains, which indicates cooperative effects among resistant cells at large cell numbers, such as in standard MIC assays.

Identification of Bacterial Drug-Resistant Cells by the Convolutional Neural Network in Transmission Electron Microscope Images

The emergence of bacteria that are resistant to antibiotics is common in areas where antibiotics are used widely. The current standard procedure for detecting bacterial drug resistance is based on bacterial growth under antibiotic treatments. Here we describe the morphological changes in enoxacin-resistant Escherichia coli cells and the computational method used to identify these resistant cells in transmission electron microscopy (TEM) images without using antibiotics. Our approach was to create patches from TEM images of enoxacin-sensitive and enoxacin-resistant E. coli strains, use a convolutional neural network for patch classification, and identify the strains on the basis of the classification results. The proposed method was highly accurate in classifying cells, achieving an accuracy rate of 0.94. Using a gradient-weighted class activation mapping to visualize the region of interest, enoxacin-resistant and enoxacin-sensitive cells were characterized by comparing differences in the envelope. Moreover, Pearson's correlation coefficients suggested that four genes, including lpp, the gene encoding the major outer membrane lipoprotein, were strongly associated with the image features of enoxacin-resistant cells.

Potential risks of treating bacterial infections with a combination of β-lactam and aminoglycoside antibiotics: A systematic quantification of antibiotic interactions in E. coli blood stream infection isolates

BACKGROUND

Treatment of Blood Stream Infections (BSIs) with a combination of a β-lactam and an aminoglycoside antibiotic is widely used in intensive care units (ICUs) around the world. However, no studies have systematically examined how these drugs interact and potentially influence the antimicrobial efficacy of the overall treatment.

METHODS

We collected 500 E. coli isolates from the Uppsala University hospital that were isolated from blood of patients with suspicion of infection. Of those we tested the efficacy of combinations of 2 common β-lactam antibiotics (Ampicillin and Cefotaxime) combined with 2 common aminoglycosides (Gentamicin and Tobramycin) on 254 isolates. The efficacy of all 4 pairwise combinations in inhibiting bacterial growth was then examined on all susceptible strains. That was done by quantifying the Fractional Inhibitory index (FICi), a robust metric for antibiotic combinatorial behaviour, of all possible treatments on every strain. When non additive interactions were identified, results of the original screen were verified with time kill assays. Finally, combination behaviours were analysed for potential cross correlations.

FINDINGS

Out of the 4 antibiotic combinations screened none exhibited synergistic effects on any of the 254 strains. On the contrary all 4 exhibited important antagonistic effects on several isolates. Specifically, the combinations of AMP-GEN and CTX-GEN were antagonistic in 1.97% and 1.18% of strains respectively. Similarly, the combinations of AMP-TOB were antagonistic on 0.78% of all strains. PCA analysis revealed that an important factor on the responses to the combination treatments was the choice of a specific aminoglycoside over another. Subsequent cross correlation analysis revealed that the interaction profiles of combinations including the same aminoglycoside are significantly correlated (Spearman's cross correlation test p<0.001).

INTERPRETATION

The findings of this study elucidate potential risks of the common combination treatment for blood stream infections. They also demonstrate, previously unquantified metrics on how antibiotics in combination therapies are not interchangeable with others of the same class. Finally, they reiterate the need for case-by-case testing of antibiotic interactions in a clinical setting.

FUNDING

This work was funded by grants to DIA from the Swedish Research Council, the Wallenberg foundation and the Swedish Strategic Research Foundation.

Lanza V, Rodríguez-Beltrán J, Galán JC, San Millán A, Cantón R, Coque TM. Evolutionary Pathways and Trajectories in Antibiotic Resistance

Evolution is the hallmark of life. Descriptions of the evolution of microorganisms have provided a wealth of information, but knowledge regarding "what happened" has precluded a deeper understanding of "how" evolution has proceeded, as in the case of antimicrobial resistance. The difficulty in answering the "how" question lies in the multihierarchical dimensions of evolutionary processes, nested in complex networks, encompassing all units of selection, from genes to communities and ecosystems. At the simplest ontological level (as resistance genes), evolution proceeds by random (mutation and drift) and directional (natural selection) processes; however, sequential pathways of adaptive variation can occasionally be observed, and under fixed circumstances (particular fitness landscapes), evolution is predictable. At the highest level (such as that of plasmids, clones, species, microbiotas), the systems' degrees of freedom increase dramatically, related to the variable dispersal, fragmentation, relatedness, or coalescence of bacterial populations, depending on heterogeneous and changing niches and selective gradients in complex environments. Evolutionary trajectories of antibiotic resistance find their way in these changing landscapes subjected to random variations, becoming highly entropic and therefore unpredictable. However, experimental, phylogenetic, and ecogenetic analyses reveal preferential frequented paths (highways) where antibiotic resistance flows and propagates, allowing some understanding of evolutionary dynamics, modeling and designing interventions. Studies on antibiotic resistance have an applied aspect in improving individual health, One Health, and Global Health, as well as an academic value for understanding evolution. Most importantly, they have a heuristic significance as a model to reduce the negative influence of anthropogenic effects on the environment.

Prediction of nitrofurantoin resistance among Enterobacteriaceae and mutational landscape of in vitro selected resistant E. coli

Nitrofurantoin (NIT) has long been a drug of choice in the treatment of lower urinary tract infections. Recent emergence of NIT resistant Enterobacteriaceae is a global concern. An ordinal logistic regression model based on PCR amplification patterns of five genes associated with NIT resistance (nfsA, nfsB, ribE, oqxA, and oqxB) among 100 clinical Enterobacteriaceae suggested that a combination of oqxB, nfsB, ribE, and oqxA is ideal for NIT resistance prediction. In addition, four Escherichia coli NIT-resistant mutants were in vitro generated by exposing an NIT-susceptible E. coli to varying concentrations of NIT. The in vitro selected NIT resistant mutants (NI2, NI3, NI4 and NI5) were found to have mutations resulting in frameshifts, premature/lost stop codons or failed amplification of nfsA and/or nfsB genes. The in vitro selected NI5 and the transductant colonies with reconstructed NI5 genotype exhibited reduced fitness compared to their parent strain NS30, while growth of a resistant clinical isolate (NR42) was found to be unaffected in the absence of NIT. These results emphasize the importance of strict adherence to prescribed antibiotic treatment regimens and dosage duration. If left unchecked, these resistant bacteria may thrive at sub-therapeutic concentrations of NIT and spread in the community.

High-throughput characterization of mutations in genes that drive clonal evolution using multiplex adaptome capture sequencing

Understanding how cells are likely to evolve can guide medical interventions and bioengineering efforts that must contend with unwanted mutations. The adaptome of a cell-the neighborhood of genetic changes that are most likely to drive adaptation in a given environment-can be mapped by tracking rare beneficial variants during the early stages of clonal evolution. We used multiplex adaptome capture sequencing (mAdCap-seq), a procedure that combines unique molecular identifiers and hybridization-based enrichment, to characterize mutations in eight Escherichia coli genes known to be under selection in a laboratory environment. We tracked 301 mutations at frequencies as low as 0.01% and inferred the fitness effects of 240 of these mutations. There were distinct molecular signatures of selection on protein structure and function for the three genes with the most beneficial mutations. Our results demonstrate how mAdCap-seq can be used to deeply profile a targeted portion of a cell's adaptome.

Antibiotic Breakdown by Susceptible Bacteria Enhances the Establishment of β-Lactam Resistant Mutants

For a better understanding of the evolution of antibiotic resistance, it is imperative to study the factors that determine the initial establishment of mutant resistance alleles. In addition to the antibiotic concentration, the establishment of resistance alleles may be affected by interactions with the surrounding susceptible cells from which they derive, for instance via the release of nutrients or removal of the antibiotic. Here, we investigate the effects of social interactions with surrounding susceptible cells on the establishment of Escherichia coli mutants with increasing β-lactamase activity (i.e., the capacity to hydrolyze β-lactam antibiotics) from single cells under the exposure of the antibiotic cefotaxime (CTX) on agar plates. We find that relatively susceptible cells, expressing a β-lactamase with very low antibiotic-hydrolyzing activity, increase the probability of mutant cells to survive and outgrow into colonies due to the active breakdown of the antibiotic. However, the rate of breakdown by the susceptible strain is much higher than expected based on its low enzymatic activity. A detailed theoretical model suggests that this observation may be explained by cell filamentation causing delayed lysis. While susceptible cells may hamper the spread of higher-resistant β-lactamase mutants at relatively high frequencies, our findings show that they promote their initial establishment.

Acquisition of Tigecycline Resistance by Carbapenem-Resistant Klebsiella pneumoniae Confers Collateral Hypersensitivity to Aminoglycosides

Tigecycline is a last-resort antibiotic for infections caused by carbapenem-resistant Klebsiella pneumoniae (CRKP). This study aimed to broaden our understanding of the acquisition of collateral hypersensitivity by CRKP, as an evolutionary trade-off of developing resistance to tigecycline. Experimental induction of tigecycline resistance was conducted with tigecycline-sensitive CRKP clinical isolates. Antimicrobial susceptibility testing, microbial fitness assessment, genotypic analysis and full-genome sequencing were carried out for these clinical isolates and their resistance-induced descendants. We found that tigecycline resistance was successfully induced after exposing CRKP clinical isolates to tigecycline at gradually increased concentrations, at a minor fitness cost of bacterial cells. Quantitative reverse transcription-polymerase chain reaction (RT-PCR) found higher expression of the efflux pump gene acrB (5.3–64.5-fold) and its regulatory gene ramA (7.4–65.8-fold) in resistance-induced strains compared to that in the tigecycline-sensitive clinical isolates. Stable hypersensitivities to aminoglycosides and other antibiotics were noticed in resistance-induced strains, showing significantly lowered MICs (X 4 – >500 times). Full genome sequencing and plasmid analysis suggested the induced collateral hypersensitivity might be multifaceted, with the loss of an antimicrobial resistance (AMR) plasmid being a possible major player. This study rationalized the sequential combination of tigecycline with aminoglycosides for the treatment of CRKP infections.

Insights into collateral susceptibility and collateral resistance in Acinetobacter baumannii during antimicrobial adaptation

The susceptibility of Acinetobacter baumannii exposed to primary antibiotic can be either increased or decreased when exposed to secondary antibiotic. This study was designed to assess the relative fitness, collateral susceptibility and collateral resistance of polymyxin B- (PMB-) adapted A. baumannii to ciprofloxacin (CIP), meropenem (MER), PMB, tetracycline (TET) and tobramycin (TOB). Strains of wild-type A. baumannii KACC 12454 (AB^KACC ), wild-type A. baumannii CCARM 12088 (AB^CCARM ), PMB-adapted AB^KACC , PMB-adapted AB^CCARM , stabilized AB^KACC and stabilized AB^CCARM were used in this study. Compared to the wild-type AB^KACC , the MICs of PMB were increased from 2 to 128 μg ml^-1 against PMB-adapted AB^KACC , while MICs of CIP, MER, TET and TOB were decreased from 2 to 1 μg ml^-1 , 16 to 1 μg ml^-1 , 16 to 2 μg ml^-1 and 64 to 16 μg ml^-1 , respectively. The PMB-adapted AB^CCARM was resistant to CIP (32 μg ml^-1 ) and PMB (64 μg ml^-1 ) compared to the wild-type AB^CCARM . The resistance of stabilized AB^KACC and AB^CCARM to all antibiotics was lost after antibiotic-free culture in the exception of CIP and TET. The susceptibilities of wild-type, PMB-adapted and stabilized AB^KACC and AB^CCARM to CIP, MER, PMB, TET and TOB were increased in the presence of β-lactamase and efflux pump inhibitors. The high levels of relative fitness were observed for stabilized AB^KACC , PMB-adapted AB^CCARM and stabilized AB^CCARM . The stabilized AB^KACC and PMB-adapted AB^CCARM were highly heteroresistance to PMB and TET, respectively. The PMB-adapted AB^KACC and AB^CCARM showed various antibiotic patterns, known as collateral susceptibility and collateral resistance. The results provide useful information for designing effective antibiotic regimens that can enhance the antibiotic activity against A. baumannii infections.

Effects of three antibiotics on growth and antioxidant response of Chlorella pyrenoidosa and Anabaena cylindrica

Antibiotics are essential for treatments of bacterial infection and play important roles in the fields of aquaculture and animal husbandry. Antibiotics are accumulated in water and soil due to the excessive consumption and incomplete treatment of antibiotic wastewater. The accumulation of antibiotics in ecological systems leads to global environmental risks. The toxic effects of spiramycin (SPI), tigecycline (TGC), and amoxicillin (AMX) on Chlorella pyrenoidesa and Anabaena cylindrica were evaluated based on growth inhibition experiments, and determinations of ROS production and antioxidant enzyme activities (catalase, superoxide dismutase, and malondialdehyde). Half maximal effective concentrations (EC50) of TGC, SPI, and AMX for A. cylindrica were 62.52 μg/L, 38.40 μg/L, and 7.66 mg/L, respectively. Those were 6.20 mg/L, 4.58 mg/L, and > 2 g/L for C. pyrenoidesa, respectively. It was shown that A. cylindrica was much more sensitive to these antibiotics than C. pyrenoidesa. In addition, EC50 values of SPI and TGC were lower than that of AMX. It was indicated that SPI and TGC had higher toxic than AMX to C. pyrenoidesa and A. cylindrica. The current study is helpful to evaluating possible ecological risks of TGC, SPI, and AMX by green microalgae and cyanobacteria.

High-throughput laboratory evolution reveals evolutionary constraints in Escherichia coli

Understanding the constraints that shape the evolution of antibiotic resistance is critical for predicting and controlling drug resistance. Despite its importance, however, a systematic investigation of evolutionary constraints is lacking. Here, we perform a high-throughput laboratory evolution of Escherichia coli under the addition of 95 antibacterial chemicals and quantified the transcriptome, resistance, and genomic profiles for the evolved strains. Utilizing machine learning techniques, we analyze the phenotype–genotype data and identified low dimensional phenotypic states among the evolved strains. Further analysis reveals the underlying biological processes responsible for these distinct states, leading to the identification of trade-off relationships associated with drug resistance. We also report a decelerated evolution of β-lactam resistance, a phenomenon experienced by certain strains under various stresses resulting in higher acquired resistance to β-lactams compared to strains directly selected by β-lactams. These findings bridge the genotypic, gene expression, and drug resistance gap, while contributing to a better understanding of evolutionary constraints for antibiotic resistance.

Understanding evolutionary constraints in antibiotic resistance is crucial for prediction and control. Here, the authors use high-throughput laboratory evolution of Escherichia coli alongside machine learning to identify trade-off relationships associated with drug resistance.

Dissemination of antibiotic resistance genes (ARGs) via integrons in Escherichia coli: A risk to human health

With the induction of various emerging environmental contaminants such as antibiotic resistance genes (ARGs), environment is considered as a key indicator for the spread of antimicrobial resistance (AMR). As such, the ARGs mediated environmental pollution raises a significant public health concern worldwide. Among various genetic mechanisms that are involved in the dissemination of ARGs, integrons play a vital role in the dissemination of ARGs. Integrons are mobile genetic elements that can capture and spread ARGs among environmental settings via transmissible plasmids and transposons. Most of the ARGs are found in Gram-negative bacteria and are primarily studied for their potential role in antibiotic resistance in clinical settings. As one of the most common microorganisms, Escherichia coli (E. coli) is widely studied as an indicator carrying drug-resistant genes, so this article aims to provide an in-depth study on the spread of ARGs via integrons associated with E. coli outside clinical settings and highlight their potential role as environmental contaminants. It also focuses on multiple but related aspects that do facilitate environmental pollution, i.e. ARGs from animal sources, water treatment plants situated at or near animal farms, agriculture fields, wild birds and animals. We believe that this updated study with summarized text, will facilitate the readers to understand the primary mechanisms as well as a variety of factors involved in the transmission and spread of ARGs among animals, humans, and the environment.

Development of coinage metal nanoclusters as antimicrobials to combat bacterial infections

Infections from antibiotic-resistant bacteria have caused huge economic loss and numerous deaths over the past decades. Researchers are exploring multiple strategies to combat these bacterial infections. Metal nanomaterials have been explored as therapeutics against these infections owing to their relatively low toxicity, broad-spectrum activity, and low bacterial resistance development. Some coinage metal nanoclusters, such as gold, silver, and copper nanoclusters, can be readily synthesized. These nanoclusters can feature multiple useful properties, including ultra-small size, high catalytic activity, unique photoluminescent properties, and photothermal effect. Coinage metal nanoclusters have been investigated as antimicrobials, but more research is required to tap their full potential. In this review, we discuss multiple advantages and the prospect of using gold/silver/copper nanoclusters as antimicrobials.

BODIPYs bearing a dimethylaminopropoxy substituent for imaging and photodynamic inactivation of bacteria

A new BODIPY (BDP 1) bearing a dimethylaminopropoxy group attached to a phenylene unit was synthesized. This compound was brominated to obtain the halogenated analog BDP 2, which was designed to enhance the photodynamic effect of BODIPY to kill bacteria without an intrinsic cationic charge. The basic amino group located at the end of the propoxy bridge can acquire a positive charge by protonation in an aqueous medium, increasing the binding to bacterial cells. Interaction and photokilling activity mediated by these compounds was evaluated in Staphylococcus aureus and Escherichia coli. BDP 1 and BDP 2 were rapidly bound to bacterial cells, showing bioimages with green emission. Complete elimination of S. aureus was detected when cells were incubated with 1 μM BDP 2 and irradiated for 5 min. Comparable photoinactivation was obtained with E. coli, after an irradiation of 30 min. Furthermore, BDP 2 was effective to kill bacteria at very low concentration (0.5 μM). Thus, BDP 1 showed mainly interesting properties as a fluorophore, whereas BDP 2 was highly effective photosensitizer as a broad-spectrum antibacterial agent.

The Ascidian-Derived Metabolites with Antimicrobial Properties

Among the sub-phylum of Tunicate, ascidians represent the most abundant class of marine invertebrates, with 3000 species by heterogeneous habitat, that is, from shallow water to deep sea, already reported. The chemistry of these sessile filter-feeding organisms is an attractive reservoir of varied and peculiar bioactive compounds. Most secondary metabolites isolated from ascidians stand out for their potential as putative therapeutic agents in the treatment of several illnesses like microbial infections. In this review, we present and discuss the antibacterial activity shown by the main groups of ascidian-derived products, such as sulfur-containing compounds, meroterpenes, alkaloids, peptides, furanones, and their derivatives. Moreover, the direct evidence of a symbiotic association between marine ascidians and microorganisms shed light on the real producers of many extremely potent marine natural compounds. Hence, we also report the antibacterial potential, joined to antifungal and antiviral activity, of metabolites isolated from ascidian-associate microorganisms by culture-dependent methods.

Understanding metabolic adaptation by using bacterial laboratory evolution and trans-omics analysis

Many diseases such as metabolic syndrome, cancer, inflammatory diseases, and pathological phenomena can be understood as an adaptive reconstitution of the metabolic state (metabolic adaptation). One of the effective approaches to reveal the property of metabolic networks is using model organisms such as microorganisms that are easier to experiment with than higher organisms. Using the laboratory evolution approach, we can elucidate the evolutionary dynamics in various stress environments, which provide us an understanding of the metabolic adaptation. In addition, the integration of omics data and phenotypic data enables us to clarify the genetic and phenotypic alterations during adaptation. In this review, we describe our recent studies on bacterial laboratory evolution and the omics approach to clarify the stress adaptation process. We have also obtained high-dimensional phenotypic data using our automated culture system. By combining these genomic and transcriptomic data within high-throughput phenotypic data, we can discuss the complex trans-omics network of metabolic adaptation.

Marine Actinobacteria: Screening for Predation Leads to the Discovery of Potential New Drugs against Multidrug-Resistant Bacteria

Predatory bacteria constitute a heterogeneous group of prokaryotes able to lyse and feed on the cellular constituents of other bacteria in conditions of nutrient scarcity. In this study, we describe the isolation of Actinobacteria predator of other bacteria from the marine water of the Moroccan Atlantic coast. Only 4 Actinobacteria isolates showing strong predation capability against native or multidrug-resistant Gram-positive or Gram-negative bacteria were identified among 142 isolated potential predatory bacteria. These actinobacterial predators were shown to belong to the Streptomyces genus and to inhibit the growth of various native or multidrug-resistant micro-organisms, including Micrococcus luteus, Staphylococcus aureus (native and methicillin-resistant), and Escherichia coli (native and ampicillin-resistant). Even if no clear correlation could be established between the antibacterial activities of the selected predator Actinobacteria and their predatory activity, we cannot exclude that some specific bio-active secondary metabolites were produced in this context and contributed to the killing and lysis of the bacteria. Indeed, the co-cultivation of Actinobacteria with other bacteria is known to lead to the production of compounds that are not produced in monoculture. Furthermore, the production of specific antibiotics is linked to the composition of the growth media that, in our co-culture conditions, exclusively consisted of the components of the prey living cells. Interestingly, our strategy led to the isolation of bacteria with interesting inhibitory activity against methicillin-resistant S. aureus (MRSA) as well as against Gram-negative bacteria.

Bacteriochlorin-bis(spermine) conjugate affords an effective photodynamic action to eradicate microorganisms

A novel bacteriochlorin bearing two spermine units (BCS) was synthesized from 3,13-dibromo-8,8,18,18-tetramethylbacteriochlorin (BC-Br ^3,13 ). The synthesis involved the Suzuki coupling of BC-Br ^3,13 to obtain a bacteriochlorin-dibenzaldehyde (BCA), which was subjected to reductive amination with spermine. The resulting bacteriochlorin BCS presents a strong near-infrared absorption band at 747 nm, emits at 750 nm with fluorescence quantum yield of 0.14, and generates singlet molecular oxygen, O₂ (¹ Δ_g ), with a quantum yield of 0.27. Photokilling capacities mediated by BCS were evaluated in microbial cells. The viability of Staphylococcus aureus decreased 7 logs when cells were incubated with 1 μM BCS and irradiated for 15 minutes. Comparable photocytotoxic effect was obtained with Escherichia coli, when cells were treated for 30 minutes with visible light. BCS was also an effective photosensitizer to inactivate Candida albicans. In addition, this bacteriochlorin was able to eradicate bacteria at short incubation times. The structure of BCS contains eight basic amino groups that, when protonated in water, increase the binding to the cell envelope. In summary, the readily accessible bacteriochlorin BCS was highly effective at low concentrations as a broad-spectrum antimicrobial photosensitizer.

The effect of spatiotemporal antibiotic inhomogeneities on the evolution of resistance

Combating the evolution of widespread antibiotic resistance is one of the most pressing challenges facing modern medicine. Recent research has demonstrated that the evolution of pathogens with high levels of resistance can be accelerated by spatial and temporal inhomogeneities in antibiotic concentration, which frequently arise in patients and the environment. Strategies to predict and counteract the effects of such inhomogeneities will be critical in the fight against resistance. In this paper we develop a mechanistic framework for modelling the adaptive evolution of resistance in the presence of spatiotemporal antibiotic concentrations, which treats the adaptive process as an interaction between two mutually orthogonal forces; the first returns cells to their wild-type state in the absence of antibiotic selection, and the second selects for increased coping ability in the presence of an antibiotic. We apply our model to investigate laboratory adaptation experiments, and then extend it to consider the case in which multiple strategies for resistance undergo competitive evolution.

Soft sweep development of resistance in Escherichia coli under fluoroquinolone stress

We employed a stepwise selection model for investigating the dynamics of antibiotic-resistant variants in Escherichia coli K-12 treated with increasing concentrations of ciprofloxacin (CIP). Firstly, we used Sanger sequencing to screen the variations in the fluoquinolone target genes, then, employed Illumina NGS sequencing for amplicons targeted regions with variations. The results demonstrated that variations G81C in gyrA and K276N and K277L in parC are standing resistance variations (SRVs), while S83A and S83L in gyrA and G78C in parC were emerging resistance variations (ERVs). The variants containing SRVs and/or ERVs were selected successively based on their sensitivities to CIP. Variant strain 1, containing substitution G81C in gyrA, was immediately selected following ciprofloxacin exposure, with obvious increases in the parC SRV, and parC and gyrA ERV allele frequencies. Variant strain 2, containing the SRVs, then dominated the population following a 20× increase in ciprofloxacin concentration, with other associated allele frequencies also elevated. Variant strains 3 and 4, containing ERVs in gyrA and parC, respectively, were then selected at 40× and 160× antibiotic concentrations. Two variants, strains 5 and 6, generated in the selection procedure, were lost because of higher fitness costs or a lower level of resistance compared with variants 3 and 4. For the second induction, all variations/indels were already present as SRVs and selected out step by step at different passages. Whatever the first induction or second induction, our results confirmed the soft selective sweep hypothesis and provided critical information for guiding clinical treatment of pathogens containing SRVs.

Structure-based drug design and in vitro testing reveal new inhibitors of enoyl-acyl carrier protein reductases

The need for new antibacterial agents is increasingly becoming of great importance as bacterial resistance to current drugs is quickly spreading. Enoyl-acyl carrier protein reductases (FabI) are important enzymes for fatty acid biosynthesis in bacteria and other micro-organisms. In this project, we conducted structure-based virtual screening against the FabI enzyme, and accordingly, 37 compounds were selected for experimental testing. Interestingly, five compounds were able to demonstrate antimicrobial effect with variable inhibition activity against various strains of bacteria and fungi. Minimum inhibitory concentrations of the active compounds were determined and showed to be in low to medium micromolar range. Subsequently, enzyme inhibition assay was carried out for our five antimicrobial hits to confirm their biological target and determine their IC₅₀ values. Three of these tested compounds exhibited inhibition activity for the FabI enzyme where our best hit MN02 had an IC₅₀ value of 7.8 μM. Furthermore, MN02 is a small bisphenolic compound that is predicted to have all required features to firmly bind with the target enzyme. To sum up, hits discovered in this work can act as a good starting point for the future development of new and potent antimicrobial agents.

Broad Bactericidal Activity of the Myoviridae Bacteriophage Lysins LysAm24, LysECD7, and LysSi3 against Gram-Negative ESKAPE Pathogens

The extremely rapid spread of multiple-antibiotic resistance among Gram-negative pathogens threatens to move humankind into the so-called “post-antibiotic era” in which the most efficient and safe antibiotics will not work. Bacteriophage lysins represent promising alternatives to antibiotics, as they are capable of digesting bacterial cell wall peptidoglycans to promote their osmotic lysis. However, relatively little is known regarding the spectrum of lysin bactericidal activity against Gram-negative bacteria. In this study, we present the results of in vitro activity assays of three putative and newly cloned Myoviridae bacteriophage endolysins (LysAm24, LysECD7, and LysSi3). The chosen proteins represent lysins with diverse domain organization (single-domain vs. two-domain) and different predicted mechanisms of action (lysozyme vs. peptidase). The enzymes were purified, and their properties were characterized. The enzymes were tested against a panel of Gram-negative clinical bacterial isolates comprising all Gram-negative representatives of the ESKAPE group. Despite exhibiting different structural organizations, all of the assayed lysins were shown to be capable of lysing Pseudomonas aeruginosa, Acinetobacter baumannii, Klebsiella pneumoniae, Escherichia coli, and Salmonella typhi strains. Less than 50 μg/mL was enough to eradicate growing cells over more than five orders of magnitude. Thus, LysAm24, LysECD7, and LysSi3 represent promising therapeutic agents for drug development.

Two-layer Electrospun System Enabling Wound Exudate Management and Visual Infection Response

The spread of antimicrobial resistance calls for chronic wound management devices that can engage with the wound exudate and signal infection by prompt visual effects. Here, the manufacture of a two-layer fibrous device with independently-controlled exudate management capability and visual infection responsivity was investigated by sequential free surface electrospinning of poly(methyl methacrylate-co-methacrylic acid) (PMMA-co-MAA) and poly(acrylic acid) (PAA). By selecting wound pH as infection indicator, PMMA-co-MAA fibres were encapsulated with halochromic bromothymol blue (BTB) to trigger colour changes at infection-induced alkaline pH. Likewise, the exudate management capability was integrated via the synthesis of a thermally-crosslinked network in electrospun PAA layer. PMMA-co-MAA fibres revealed high BTB loading efficiency (>80 wt.%) and demonstrated prompt colour change and selective dye release at infected-like media (pH > 7). The synthesis of the thermally-crosslinked PAA network successfully enabled high water uptake (WU = 1291 ± 48 - 2369 ± 34 wt.%) and swelling index (SI = 272 ± 4 - 285 ± 3 a.%), in contrast to electrospun PAA controls. This dual device functionality was lost when the same building blocks were configured in a single-layer mesh of core-shell fibres, whereby significant BTB release (~70 wt.%) was measured even at acidic pH. This study therefore demonstrates how the fibrous configuration can be conveniently manipulated to trigger structure-induced functionalities critical to chronic wound management and monitoring.

Palindromic Molecular Beacon Based Z-Scheme BiOCl-Au-CdS Photoelectrochemical Biodetection

This work presented an innovative and rationally engineered palindromic molecular beacon (PMB) based "Z-scheme" photoelectrochemical (PEC) biosensing protocol for the selective screening of kanamycin (Kana) through DNA hybridization-induced conformational conversion. Interestingly, the ingeniously designed PMB integrated the multifunctional elements including recognition region, primer-like palindromic fragment, and polymerization-nicking template. The cosensitized structures consisted of CdS quantum dot functionalized hairpin DNA2 (QD-HP2) and region-selectively deposited gold nanoparticles onto {001} facets of bismuth oxychloride (BiOCl-Au). Compared with BiOCl-Au alone, the attachment of CdS QDs onto BiOCl-Au (i.e., BiOCl-Au-CdS QDs) exhibited evidently enhanced photocurrent intensity thanks to the synergistic effect of Z-scheme BiOCl-Au-CdS QDs. After incubation with target Kana, Kana-aptamer binding could induce the exposure of PMB region for hairpin DNA1 (HP1). The exposed palindromic tails hybridized with each other (like a molecular machine) to consume the substrates (dNTPs) and fuels (enzyme) for the releasing of numerous nick fragments (Nick). The as-generated nick fragments could specifically hybridize with the complementary region of QD-HP2, thus resulting in decreasing photocurrent because of the increasing spatial distance for electron transfer between two-type photosensitizers. Under optimum conditions, the PMB-based sensing system exhibited satisfying photocurrent responses toward target Kana within the working range from 50 to 5000 fM at a low detection limit of 29 fM. Impressively, the concept of a palindromic fragment-mediated primer-free biosensing strategy offers a new avenue for advanced development of efficient and convenient biodetection systems.

Structures, Activities and Drug-Likeness of Anti-Infective Xanthone Derivatives Isolated from the Marine Environment: A Review

Marine organisms represent almost half of total biodiversity and are a very important source of new bioactive substances. Within the varied biological activities found in marine products, their antimicrobial activity is one of the most relevant. Infectious diseases are responsible for high levels of morbidity and mortality and many antimicrobials lose their effectiveness with time due to the development of resistance. These facts justify the high importance of finding new, effective and safe anti-infective agents. Among the variety of biological activities of marine xanthone derivatives, one that must be highlighted is their anti-infective properties. In this work, a literature review of marine xanthones with anti-infective activity, namely antibacterial, antifungal, antiparasitic and antiviral, is presented. Their structures, biological activity, sources and the methods used for bioactivity evaluation are described. The xanthone derivatives are grouped in three sets: xanthones, hydroxanthones and glycosylated derivatives. Moreover, molecular descriptors, biophysico-chemical properties, and pharmacokinetic parameters were calculated, and the chemical space occupied by marine xanthone derivatives is recognized. The chemical space was compared with marketed drugs and framed accordingly to the drug-likeness concept in order to profile the pharmacokinetic of anti-infective marine xanthone derivatives.

Integrated Experimental and Computational Analyses Reveal Differential Metabolic Functionality in Antibiotic-Resistant Pseudomonas aeruginosa

Metabolic adaptations accompanying the development of antibiotic resistance in bacteria remain poorly understood. To study this relationship, we profiled the growth of lab-evolved antibiotic-resistant lineages of the opportunistic pathogen Pseudomonas aeruginosa across 190 unique carbon sources. Our data revealed that the evolution of antibiotic resistance resulted in systems-level changes to growth dynamics and metabolic phenotype. A genome-scale metabolic network reconstruction of P. aeruginosa was paired with whole-genome sequencing data to predict genes contributing to observed changes in metabolism. We experimentally validated computational predictions to identify mutations in resistant P. aeruginosa affecting loss of catabolic function. Finally, we found a shared metabolic phenotype between lab-evolved P. aeruginosa and clinical isolates with similar mutational landscapes. Our results build upon previous knowledge of antibiotic-induced metabolic adaptation and provide a framework for the identification of metabolic limitations in antibiotic-resistant pathogens.

Platinum Nanozyme-Catalyzed Gas Generation for Pressure-Based Bioassay Using Polyaniline Nanowires-Functionalized Graphene Oxide Framework

Pressure-based bioassays incorporating biomolecular recognition with a catalyzed gas-generation reaction have been developed for gas biosensors, but most involve poor sensitivity and are unsuitable for routine use. Herein we design an innovative gas pressure-based biosensing platform for the detection of Kanamycin (Kana) on polyaniline nanowires-functionalized reduced graphene oxide (PANI/rGO) framework by using platinum nanozyme-catalyzed gas generation. The signal was amplified by coupling with catalytic hairpin assembly (CHA) and strand-displacement amplification (SDA). Upon target Kana introduction, the analyte initially triggered a SDA reaction between hairpin DNA1 and hairpin DNA2, and then induced CHA conjugation between magnetic bead-labeled hairpin DNA3 (MB-H3) and platinum nanoparticle-labeled hairpin DNA4 (Pt-H4) to form a three-dimensional network. Numerous platinum nanoparticles (peroxidase-like nanozymes) were carried over with magnetic beads to reduce hydrogen peroxide into oxygen. The as-produced gas compressed PANI/rGO frameworks (modified to polyurethane sponge, used as the piezoelectric materials) in a homemade pressure-tight device, thus causing the increasing current of PANI/rGO sponge thanks to its deformation. The change in the current caused by the as-generated gas pressure was determined on an electrochemical workstation. Under optimum conditions, PANI/rGO sponge exhibited outstanding compressibility, stable signal-waveform output, fast response and recovery time (≈109 ms), and the current increased with the increasing Kana concentration within a dynamic working range of 0.2-50 pM at a detection limit of 0.063 pM. Good reproducibility, specificity, and acceptable precision were acquired for Kana analysis. In addition, the accuracy of this method was monitored to evaluate real milk samples with the well-matched results obtained by using the referenced Kana ELISA kit.

The Metabolic Redox Regime of Pseudomonas putida Tunes Its Evolvability toward Novel Xenobiotic Substrates

During evolution of biodegradation pathways for xenobiotic compounds involving Rieske nonheme iron oxygenases, the transition toward novel substrates is frequently associated with faulty reactions. Such events release reactive oxygen species (ROS), which are endowed with high mutagenic potential. In this study, we evaluated how the operation of the background metabolic network by an environmental bacterium may either foster or curtail the still-evolving pathway for 2,4-dinitrotoluene (2,4-DNT) catabolism. To this end, the genetically tractable strain Pseudomonas putida EM173 was implanted with the whole genetic complement necessary for the complete biodegradation of 2,4-DNT (recruited from the environmental isolate Burkholderia sp. R34). By using reporter technology and direct measurements of ROS formation, we observed that the engineered P. putida strain experienced oxidative stress when catabolizing the nitroaromatic substrate. However, the formation of ROS was neither translated into significant activation of the SOS response to DNA damage nor did it result in a mutagenic regime (unlike what has been observed in Burkholderia sp. R34, the original host of the pathway). To inspect whether the tolerance of P. putida to oxidative challenges could be traced to its characteristic reductive redox regime, we artificially altered the NAD(P)H pool by means of a water-forming, NADH-specific oxidase. Under the resulting low-NAD(P)H status, catabolism of 2,4-DNT triggered a conspicuous mutagenic and genomic diversification scenario. These results indicate that the background biochemical network of environmental bacteria ultimately determines the evolvability of metabolic pathways. Moreover, the data explain the efficacy of some bacteria (e.g., pseudomonads) to host and evolve with new catabolic routes.IMPORTANCE Some environmental bacteria evolve with new capacities for the aerobic biodegradation of chemical pollutants by adapting preexisting redox reactions to novel compounds. The process typically starts by cooption of enzymes from an available route to act on the chemical structure of the substrate-to-be. The critical bottleneck is generally the first biochemical step, and most of the selective pressure operates on reshaping the initial reaction. The interim uncoupling of the novel substrate to preexisting Rieske nonheme iron oxygenases usually results in formation of highly mutagenic ROS. In this work, we demonstrate that the background metabolic regime of the bacterium that hosts an evolving catabolic pathway (e.g., biodegradation of the xenobiotic 2,4-DNT) determines whether the cells either adopt a genetic diversification regime or a robust ROS-tolerant status. Furthermore, our results offer new perspectives to the rational design of efficient whole-cell biocatalysts, which are pursued in contemporary metabolic engineering.