Detoxified synthetic bacterial membrane vesicles as a vaccine platform against bacteria and SARS-CoV-2.

The development of vaccines based on outer membrane vesicles (OMV) that naturally bud off from bacteria is an evolving field in infectious diseases. However, the inherent inflammatory nature of OMV limits their use as human vaccines. This study employed an engineered vesicle technology to develop synthetic bacterial vesicles (SyBV) that activate the immune system without the severe immunotoxicity of OMV. SyBV were generated from bacterial membranes through treatment with detergent and ionic stress. SyBV induced less inflammatory responses in macrophages and in mice compared to natural OMV. Immunization with SyBV or OMV induced comparable antigen-specific adaptive immunity. Specifically, immunization with Pseudomonas aeruginosa-derived SyBV protected mice against bacterial challenge, and this was accompanied by significant reduction in lung cell infiltration and inflammatory cytokines. Further, immunization with Escherichia coli-derived SyBV protected mice against E. coli sepsis, comparable to OMV-immunized group. The protective activity of SyBV was driven by the stimulation of B-cell and T-cell immunity. Also, SyBV were engineered to display the SARS-CoV-2 S1 protein on their surface, and these vesicles induced specific S1 protein antibody and T-cell responses. Collectively, these results demonstrate that SyBV may be a safe and efficient vaccine platform for the prevention of bacterial and viral infections.

Chemical Changes On, and Through, The Bacterial Envelope in Escherichia coli Mutants Exhibiting Impaired Plasmid Transfer Identified Using Time-of-Flight Secondary Ion Mass Spectrometry.

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) using a (CO2)6k+ gas cluster ion beam (GCIB) was used to analyze Escherichia coli mutants previously identified as having impaired plasmid transfer capability related to the spread of antibiotic resistance. The subset of mutants selected were expected to result in changes in the bacterial envelope composition through the deletion of genes encoding for FabF, DapF, and Lpp, where the surface sensitivity of ToF-SIMS can be most useful. Analysis of arrays of spotted bacteria allowed changes in the lipid composition of the bacteria to be elucidated using multivariate analysis and confirmed through imaging of individual ion signals. Significant changes in chemical composition were observed, including a surprising loss of cyclopropanated fatty acids in the fabF mutant where FabF is associated with the elongation of FA(16:1) to FA(18:1) and not cyclopropane formation. The ability of the GCIB to generate increased higher mass signals from biological samples allowed intact lipid A (m/z 1796) to be detected on the bacteria and, despite a 40 keV impact energy, depth profiled through the bacterial envelope along with other high mass ions including species at m/z 1820 and 2428, attributed to ECACYC, that were only observed below the surface of the bacteria and were notably absent in the depth profile of the lpp mutant. The analysis provides new insights into the action of the specific pathways targeted in this study and paves the way for whole new avenues for the characterization of intact molecules within the bacterial envelope.

Prediction of antibiotic resistance in Escherichia coli from large-scale pan-genome data.

The emergence of microbial antibiotic resistance is a global health threat. In clinical settings, the key to controlling spread of resistant strains is accurate and rapid detection. As traditional culture-based methods are time consuming, genetic approaches have recently been developed for this task. The detection of antibiotic resistance is typically made by measuring a few known determinants previously identified from genome sequencing, and thus requires the prior knowledge of its biological mechanisms. To overcome this limitation, we employed machine learning models to predict resistance to 11 compounds across four classes of antibiotics from existing and novel whole genome sequences of 1936 E. coli strains. We considered a range of methods, and examined population structure, isolation year, gene content, and polymorphism information as predictors. Gradient boosted decision trees consistently outperformed alternative models with an average accuracy of 0.91 on held-out data (range 0.81-0.97). While the best models most frequently employed gene content, an average accuracy score of 0.79 could be obtained using population structure information alone. Single nucleotide variation data were less useful, and significantly improved prediction only for two antibiotics, including ciprofloxacin. These results demonstrate that antibiotic resistance in E. coli can be accurately predicted from whole genome sequences without a priori knowledge of mechanisms, and that both genomic and epidemiological data can be informative. This paves way to integrating machine learning approaches into diagnostic tools in the clinic.

Inhibiting conjugation as a tool in the fight against antibiotic resistance.

Antibiotic resistance, especially in gram-negative bacteria, is spreading globally and rapidly. Development of new antibiotics lags behind; therefore, novel approaches to the problem of antibiotic resistance are sorely needed and this commentary highlights one relatively unexplored target for drug development: conjugation. Conjugation is a common mechanism of horizontal gene transfer in bacteria that is instrumental in the spread of antibiotic resistance among bacteria. Most resistance genes are found on mobile genetic elements and primarily spread by conjugation. Furthermore, conjugative elements can act as a reservoir to maintain antibiotic resistance in the bacterial population even in the absence of antibiotic selection. Thus, conjugation can spread antibiotic resistance quickly between bacteria of the microbiome and pathogens when selective pressure (antibiotics) is introduced. Potential drug targets include the plasmid-encoded conjugation system and the host-encoded proteins important for conjugation. Ideally, a conjugation inhibitor will be used alongside antibiotics to prevent the spread of resistance to or within pathogens while not acting as a growth inhibitor itself. Inhibiting conjugation will be an important addition to our arsenal of strategies to combat the antibiotic resistance crisis, allowing us to extend the usefulness of antibiotics.

Investigating the Role of the Stringent Response in Lipid Modifications during the Stationary Phase in E. coli by Direct Analysis with Time-of-Flight-Secondary Ion Mass Spectrometry.

Escherichia coli is able to rapidly adjust the biophysical properties of its membrane phospholipids to adapt to environmental challenges including starvation stress. These membrane lipid modifications were investigated in glucose starved E. coli cultures and compared to a ΔrelAΔspoT (ppGpp(0)) mutant strain of E. coli, deficient in the stringent response, by means of time-of-flight-secondary ion mass spectrometry (TOF-SIMS). Recent advances in TOF-SIMS, through the implementation of gas cluster ion beams (GCIBs), now permit the analysis of higher mass species from native, underivatized, biological specimen, i.e., intact bacterial cells. Cultures in stationary phase were found to exhibit a radically different lipid composition as compared to cultures in the exponential growth phase. Wild-type E. coli reacted upon carbon starvation by lipid modifications including elongation, cyclopropanation, and increased cardiolipin formation. Observations are consistent with variants of cardiolipins (CL), phosphatidylglycerols (PG), phosphatidylethanolamines (PE), phosphatidic acids (PA), and fatty acids. Notably, despite having a proteomic profile and a gene expression profile somewhat similar to the wild-type during growth, the ppGpp(0) mutant E. coli strain was found to exhibit modified phospholipids corresponding to unsaturated analogues of those found in the wild-type. We concluded that the ppGpp(0) mutant reacts upon starvation stress by elongation and desaturation of fatty acyl chains, implying that only the last step of the lipid modification, the cyclopropanation, is under stringent control. These observations suggest alternative stress response mechanisms and illustrate the role of the RelA and SpoT enzymes in the biosynthetic pathway underlying these lipid modifications.

Discovery of novel inhibitors for Pseudomonas aeruginosa lipase enzyme from in silico and in vitro studies.

Pseudomonas aeruginosa is an opportunistic pathogen prone to developing drug-resistance and is a major cause of infection for burn patients and patients suffering from cystic fibrosis or are hospitalized in intensive care units. One of the virulence factors of this bacterium is the lipase enzyme that degrades the extracellular matrix of the host tissue and promotes invasion. Bromhexine is a mucolytic drug and has recently been reported to function as a competitive inhibitor of lipase with an IC50 value of 49 µM. In the present study, an attempt was made to identify stronger inhibitors from the ChEMBL database of bioactive compounds, as compared to the reference compound Bromhexine. Following docking and MD simulations, four hit compounds (N1-N4) were selected that showed promising binding modes and low RMSD values indicative of stable protein-ligand complexes. From subsequent binding pose metadynamics (BPMD) simulations, two of these (N2 and N4) stood out as more potent than Bromhexine, displaying stable interactions with residues in the catalytic site of the enzyme. Biological investigations were performed for all four compounds. Among them, the same two hit compounds were found to be the most effective binders with IC50 values of 22.1 and 27.5 µM, respectively; i.e. roughly twice as efficient as the reference Bromhexine. Taken together, our results show that these hits can be promising new candidates to use as leads for the development of drugs targeting the P. aeruginosa lipase enzyme.Communicated by Ramaswamy H. Sarma.

Increased RNA polymerase availability directs resources towards growth at the expense of maintenance.

Nutritionally induced changes in RNA polymerase availability have been hypothesized to be an evolutionary primeval mechanism for regulation of gene expression and several contrasting models have been proposed to explain how such 'passive' regulation might occur. We demonstrate here that ectopically elevating Escherichia coli RNA polymerase (Esigma(70)) levels causes an increased expression and promoter occupancy of ribosomal genes at the expense of stress-defense genes and amino acid biosynthetic operons. Phenotypically, cells overproducing Esigma(70) favours growth and reproduction at the expense of motility and damage protection; a response reminiscent of cells with no or diminished levels of the alarmone guanosine tetraphosphate (ppGpp). Consistently, we show that cells lacking ppGpp displayed markedly elevated levels of free Esigma(70) compared with wild-type cells and that the repression of ribosomal RNA expression and reduced growth rate of mutants with constitutively elevated levels of ppGpp can be suppressed by overproducing Esigma(70). We conclude that ppGpp modulates the levels of free Esigma(70) and that this is an integral part of the alarmone's means of regulating a trade-off between growth and maintenance.

Effect of anode material and dispersal limitation on the performance and biofilm community in microbial electrolysis cells.

In a microbial electrolysis cell (MEC), the oxidization of organic compounds is facilitated by an electrogenic biofilm on the anode surface. The biofilm community composition determines the function of the system. Both deterministic and stochastic factors affect the community, but the relative importance of different factors is poorly understood. Anode material is a deterministic factor as materials with different properties may select for different microorganisms. Ecological drift is a stochastic factor, which is amplified by dispersal limitation between communities. Here, we compared the effects of three anode materials (graphene, carbon cloth, and nickel) with the effect of dispersal limitation on the function and biofilm community assembly. Twelve MECs were operated for 56 days in four hydraulically connected loops and shotgun metagenomic sequencing was used to analyse the microbial community composition on the anode surfaces at the end of the experiment. The anode material was the most important factor affecting the performance of the MECs, explaining 54-80 % of the variance observed in peak current density, total electric charge generation, and start-up lag time, while dispersal limitation explained 10-16 % of the variance. Carbon cloth anodes had the highest current generation and shortest lag time. However, dispersal limitation was the most important factor affecting microbial community structure, explaining 61-98 % of the variance in community diversity, evenness, and the relative abundance of the most abundant taxa, while anode material explained 0-20 % of the variance. The biofilms contained nine Desulfobacterota metagenome-assembled genomes (MAGs), which made up 64-89 % of the communities and were likely responsible for electricity generation in the MECs. Different MAGs dominated in different MECs. Particularly two different genotypes related to Geobacter benzoatilyticus competed for dominance on the anodes and reached relative abundances up to 83 %. The winning genotype was the same in all MECs that were hydraulically connected irrespective of anode material used.

Genome-Wide Association Study Reveals Host Factors Affecting Conjugation in Escherichia coli.

The emergence and dissemination of antibiotic resistance threaten the treatment of common bacterial infections. Resistance genes are often encoded on conjugative elements, which can be horizontally transferred to diverse bacteria. In order to delay conjugative transfer of resistance genes, more information is needed on the genetic determinants promoting conjugation. Here, we focus on which bacterial host factors in the donor assist transfer of conjugative plasmids. We introduced the broad-host-range plasmid pKJK10 into a diverse collection of 113 Escherichia coli strains and measured by flow cytometry how effectively each strain transfers its plasmid to a fixed E. coli recipient. Differences in conjugation efficiency of up to 2.7 and 3.8 orders of magnitude were observed after mating for 24 h and 48 h, respectively. These differences were linked to the underlying donor strain genetic variants in genome-wide association studies, thereby identifying candidate genes involved in conjugation. We confirmed the role of fliF, fliK, kefB and ucpA in the donor ability of conjugative elements by validating defects in the conjugation efficiency of the corresponding lab strain single-gene deletion mutants. Based on the known cellular functions of these genes, we suggest that the motility and the energy supply, the intracellular pH or salinity of the donor affect the efficiency of plasmid transfer. Overall, this work advances the search for targets for the development of conjugation inhibitors, which can be administered alongside antibiotics to more effectively treat bacterial infections.

Evidence of competition between electrogens shaping electroactive microbial communities in microbial electrolysis cells.

In single-chamber microbial electrolysis cells (MECs), organic compounds are oxidized at the anode, liberating electrons that are used for hydrogen evolution at the cathode. Microbial communities on the anode and cathode surfaces and in the bulk liquid determine the function of the MEC. The communities are complex, and their assembly processes are poorly understood. We investigated MEC performance and community composition in nine MECs with a carbon cloth anode and a cathode of carbon nanoparticles, titanium, or stainless steel. Differences in lag time during the startup of replicate MECs suggested that the initial colonization by electrogenic bacteria was stochastic. A network analysis revealed negative correlations between different putatively electrogenic Deltaproteobacteria on the anode. Proximity to the conductive anode surface is important for electrogens, so the competition for space could explain the observed negative correlations. The cathode communities were dominated by hydrogen-utilizing taxa such as Methanobacterium and had a much lower proportion of negative correlations than the anodes. This could be explained by the diffusion of hydrogen throughout the cathode biofilms, reducing the need to compete for space.

Development of Dicationic Bisguanidine-Arylfuran Derivatives as Potent Agents against Gram-Negative Bacteria.

Antibiotic resistance among bacteria is a growing global challenge. A major reason for this is the limited progress in developing new classes of antibiotics active against Gram-negative bacteria. Here, we investigate the antibacterial activity of a dicationic bisguanidine-arylfuran, originally developed as an antitrypanosomal agent, and new derivatives thereof. The compounds showed good activity (EC50 2-20 µM) against antibiotic-resistant isolates of the Gram-negative members of the ESKAPE group (Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter spp.) and Escherichia coli with different antibiotic susceptibility patterns, including ESBL isolates. Cytotoxicity was moderate, and several of the new derivatives were less cytotoxic than the lead molecule, offering better selectivity indices (40-80 for several ESKAPE isolates). The molecular mechanism for the antibacterial activity of these molecules is unknown, but sensitivity profiling against human ESKAPE isolates and E. coli collections with known susceptibility patterns against established antibiotics indicates that it is distinct from lactam and quinolone antibiotics.

Conjugative transfer of multi-drug resistance IncN plasmids from environmental waterborne bacteria to Escherichia coli.

Watersheds contaminated with municipal, hospital, and agricultural residues are recognized as reservoirs for bacteria carrying antibiotic resistance genes (ARGs). The objective of this study was to determine the potential of environmental bacterial communities from the highly contaminated La Paz River basin in Bolivia to transfer ARGs to an Escherichia coli lab strain used as the recipient. Additionally, we tested ZnSO4 and CuSO4 at sub-inhibitory concentrations as stressors and analyzed transfer frequencies (TFs), diversity, richness, and acquired resistance profiles. The bacterial communities were collected from surface water in an urban site close to a hospital and near an agricultural area. High transfer potentials of a large set of resistance factors to E. coli were observed at both sites. Whole-genome sequencing revealed that putative plasmids belonging to the incompatibility group N (IncN, IncN2, and IncN3) were predominant among the transconjugants. All IncN variants were verified to be mobile by a second conjugation step. The plasmid backbones were similar to other IncN plasmids isolated worldwide and carried a wide range of ARGs extensively corroborated by phenotypic resistance patterns. Interestingly, all transconjugants also acquired the class 1 integron intl1, which is commonly known as a proxy for anthropogenic pollution. The addition of ZnSO4 and CuSO4 at sub-inhibitory concentrations did not affect the transfer rate. Metal resistance genes were absent from most transconjugants, suggesting a minor role, if any, of metals in the spread of multidrug-resistant plasmids at the investigated sites.

The Effect of Heavy Metals on Conjugation Efficiency of an F-Plasmid in Escherichia coli.

Conjugation, the process by which conjugative plasmids are transferred between bacteria, is regarded as a major contributor to the spread of antibiotic resistance, in both environmental and clinical settings. Heavy metals are known to co-select for antibiotic resistance, but the impact of the presence of these metals on conjugation itself is not clear. Here, we systematically investigate the impact that five heavy metals (arsenic, cadmium, copper, manganese, and zinc) have on the transfer of an IncF conjugative plasmid in Escherichia coli. Our results show that two of the metals, cadmium and manganese, have no significant impact, while arsenic and zinc both reduce conjugation efficiency by approximately 2-fold. Copper showed the largest impact, with an almost 100-fold decrease in conjugation efficiency. This was not mediated by any change in transcription from the major Py promoter responsible for transcription of the conjugation machinery genes. Further, we show that in order to have this severe impact on the transfer of the plasmid, copper sulfate needs to be present during the mating process, and we suggest explanations for this.

Genomic Epidemiology and Evolution of Escherichia coli in Wild Animals in Mexico.

Escherichia coli is a common bacterial species in the gastrointestinal tracts of warm-blooded animals and humans. Pathogenicity and antimicrobial resistance in E. coli may emerge via host switching from animal reservoirs. Despite its potential clinical importance, knowledge of the population structure of commensal E. coli within wild hosts and the epidemiological links between E. coli in nonhuman hosts and E. coli in humans is still scarce. In this study, we analyzed the whole-genome sequencing data of a collection of 119 commensal E. coli strains recovered from the guts of 55 mammal and bird species in Mexico and Venezuela in the 1990s. We observed low concordance between the population structures of E. coli isolates colonizing wild animals and the phylogeny, taxonomy, and ecological and physiological attributes of the host species, with distantly related E. coli strains often colonizing the same or similar host species and distantly related host species often hosting closely related E. coli strains. We found no evidence for recent transmission of E. coli genomes from wild animals to either domesticated animals or humans. However, multiple livestock- and human-related virulence factor genes were present in E. coli of wild animals, including virulence factors characteristic of Shiga toxin-producing E. coli (STEC) and atypical enteropathogenic E. coli (aEPEC), where several isolates from wild hosts harbored the locus of enterocyte effacement (LEE) pathogenicity island. Moreover, E. coli isolates from wild animal hosts often harbored known antibiotic resistance determinants, including those against ciprofloxacin, aminoglycosides, tetracyclines, and beta-lactams, with some determinants present in multiple, distantly related E. coli lineages colonizing very different host animals. We conclude that genome pools of E. coli colonizing the guts of wild animals and humans share virulence and antibiotic resistance genes, underscoring the idea that wild animals could serve as reservoirs for E. coli pathogenicity in human and livestock infections.IMPORTANCEEscherichia coli is a clinically important bacterial species implicated in human- and livestock-associated infections worldwide. The bacterium is known to reside in the guts of humans, livestock, and wild animals. Although wild animals are recognized as potential reservoirs for pathogenic E. coli strains, the knowledge of the population structure of E. coli in wild hosts is still scarce. In this study, we used fine resolution of whole-genome sequencing to provide novel insights into the evolution of E. coli genomes from a small yet diverse collection of strains recovered within a broad range of wild animal species (including mammals and birds), the coevolution of E. coli strains with their hosts, and the genetics of pathogenicity of E. coli strains in wild hosts in Mexico. Our results provide evidence for the clinical importance of wild animals as reservoirs for pathogenic strains and highlight the need to include nonhuman hosts in the surveillance programs for E. coli infections.

Machine Learning Prediction of Resistance to Subinhibitory Antimicrobial Concentrations from Escherichia coli Genomes.

Escherichia coli is an important cause of bacterial infections worldwide, with multidrug-resistant strains incurring substantial costs on human lives. Besides therapeutic concentrations of antimicrobials in health care settings, the presence of subinhibitory antimicrobial residues in the environment and in clinics selects for antimicrobial resistance (AMR), but the underlying genetic repertoire is less well understood. Here, we used machine learning to predict the population doubling time and cell growth yield of 1,407 genetically diverse E. coli strains expanding under exposure to three subinhibitory concentrations of six classes of antimicrobials from single-nucleotide genetic variants, accessory gene variation, and the presence of known AMR genes. We predicted cell growth yields in the held-out test data with an average correlation (Spearman's ρ) of 0.63 (0.36 to 0.81 across concentrations) and cell doubling times with an average correlation of 0.59 (0.32 to 0.92 across concentrations), with moderate increases in sample size unlikely to improve predictions further. This finding points to the remaining missing heritability of growth under antimicrobial exposure being explained by effects that are too rare or weak to be captured unless sample size is dramatically increased, or by effects other than those conferred by the presence of individual single-nucleotide polymorphisms (SNPs) and genes. Predictions based on whole-genome information were generally superior to those based only on known AMR genes and were accurate for AMR resistance at therapeutic concentrations. We pinpointed genes and SNPs determining the predicted growth and thereby recapitulated many known AMR determinants. Finally, we estimated the effect sizes of resistance genes across the entire collection of strains, disclosing the growth effects for known resistance genes in each individual strain. Our results underscore the potential of predictive modeling of growth patterns from genomic data under subinhibitory concentrations of antimicrobials, although the remaining missing heritability poses a challenge for achieving the accuracy and precision required for clinical use. IMPORTANCE Predicting bacterial growth from genome sequences is important for a rapid characterization of strains in clinical diagnostics and to disclose candidate novel targets for anti-infective drugs. Previous studies have dissected the relationship between bacterial growth and genotype in mutant libraries for laboratory strains, yet no study so far has examined the predictive power of genome sequence in natural strains. In this study, we used a high-throughput phenotypic assay to measure the growth of a systematic collection of natural Escherichia coli strains and then employed machine learning models to predict bacterial growth from genomic data under nontherapeutic subinhibitory concentrations of antimicrobials that are common in nonclinical settings. We found a moderate to strong correlation between predicted and actual values for the different collected data sets. Moreover, we observed that the known resistance genes are still effective at sublethal concentrations, pointing to clinical implications of these concentrations.

Teaching about antibiotic resistance to a broad audience: a multidisciplinary approach.

Education for the general public about antibiotic resistance is advocated as a key component of our response to this crisis. Since this is a multidisciplinary problem encompassing natural, medical and social sciences, it is an educational challenge as both students and lecturers will have vastly different backgrounds in the topics. Here we describe an online multidisciplinary course on antibiotic resistance spanning topics as diverse as chemistry and practical philosophy. The target group was any post-secondary school student and the participating students had different occupations and educational experience. Although as many as 38% of the students were currently studying natural sciences at university, the course included a diverse group with medical professionals (16%) and teachers (6%) making up a significant fraction of the class. The outcomes based on examination and the course evaluations were very positive and we have indications that the information students gained from this course has been spread to others. Unlike other online courses addressing antibiotic resistance, this course is both accessible to a wide range of students and covers a broad range of topics. We advocate courses like ours as an effective tool in educating the public about this crisis.

Increased antibiotic efficacy and noninvasive monitoring of Staphylococcus epidermidis biofilms using per-cysteamine-substituted γ-cyclodextrin - A delivery effect validated by fluorescence microscopy.

Limited and poor delivery of antibiotics is cited as one reason for the difficulty in treating antibiotic-resistant biofilms associated with chronic infections. We investigate the effectiveness of a positively charged, single isomer cyclodextrin derivative, octakis[6-(2-aminoethylthio)-6-deoxy]-γ-CD (γCys) to improve the delivery of antibiotics to biofilms. Using multiphoton laser scanning microscopy complemented with super-resolution fluorescence microscopy, we showed that γCys tagged with fluorescein (FITC) is uniformly distributed throughout live S. epidermidis biofilm cultures in vitro and results suggest it is localized extracellularly in the biofilm matrix. NMR spectroscopic data in aqueous solution confirm that γCys forms inclusion complexes with both the antibiotics oxacillin and rifampicin. Efficacy of γCys/antibiotic (oxacillin and rifampicin) was measured in the biofilms. While treatment with γCys/oxacillin had little improvement over oxacillin alone, γCys/rifampicin reduced the biofilm viability to background levels demonstrating a remarkable improvement over rifampicin alone. The strong synergistic effect for γCys/rifampicin is at this stage not clearly understood, but plausible explanations are related to increased solubility of rifampicin upon complexation and/or synergistic interference with components of the biofilm. The results demonstrate that designed cyclodextrin nanocarriers, like γCys, efficiently deliver suitable antibiotics to biofilms and that fluorescence microscopy offers a novel approach for mechanistic investigations.

A High-Throughput Method for Screening for Genes Controlling Bacterial Conjugation of Antibiotic Resistance.

The rapid horizontal transmission of antibiotic resistance genes on conjugative plasmids between bacterial host cells is a major cause of the accelerating antibiotic resistance crisis. There are currently no experimental platforms for fast and cost-efficient screening of genetic effects on antibiotic resistance transmission by conjugation, which prevents understanding and targeting conjugation. We introduce a novel experimental framework to screen for conjugation-based horizontal transmission of antibiotic resistance between >60,000 pairs of cell populations in parallel. Plasmid-carrying donor strains are constructed in high-throughput. We then mix the resistance plasmid-carrying donors with recipients in a design where only transconjugants can reproduce, measure growth in dense intervals, and extract transmission times as the growth lag. As proof-of-principle, we exhaustively explore chromosomal genes controlling F-plasmid donation within Escherichia coli populations, by screening the Keio deletion collection in high replication. We recover all seven known chromosomal gene mutants affecting conjugation as donors and identify many novel mutants, all of which diminish antibiotic resistance transmission. We validate nine of the novel genes' effects in liquid mating assays and complement one of the novel genes' effect on conjugation (rseA). The new framework holds great potential for exhaustive disclosing of candidate targets for helper drugs that delay resistance development in patients and societies and improve the longevity of current and future antibiotics. Further, the platform can easily be adapted to explore interspecies conjugation, plasmid-borne factors, and experimental evolution and be used for rapid construction of strains.IMPORTANCE The rapid transmission of antibiotic resistance genes on conjugative plasmids between bacterial host cells is a major cause of the accelerating antibiotic resistance crisis. There are currently no experimental platforms for fast and cost-efficient screening of genetic effects on antibiotic resistance transmission by conjugation, which prevents understanding and targeting conjugation. We introduce a novel experimental framework to screen for conjugation-based horizontal transmission of antibiotic resistance between >60,000 pairs of cell populations in parallel. As proof-of-principle, we exhaustively explore chromosomal genes controlling F-plasmid donation within E. coli populations. We recover all previously known and many novel chromosomal gene mutants that affect conjugation efficiency. The new framework holds great potential for rapid screening of compounds that decrease transmission. Further, the platform can easily be adapted to explore interspecies conjugation, plasmid-borne factors, and experimental evolution and be used for rapid construction of strains.

The tumor suppressor homolog in fission yeast, myh1(+), displays a strong interaction with the checkpoint gene rad1(+).

The DNA glycosylase MutY is strongly conserved in evolution, and homologs are found in most eukaryotes and prokaryotes examined. This protein is implicated in repair of oxidative DNA damage, in particular adenine mispaired opposite 7,8-dihydro-8-oxoguanine. Previous investigations in Escherichia coli, fission yeast, and mammalian cells show an association of mutations in MutY homologs with a mutator phenotype and carcinogenesis. Eukaryotic MutY homologs physically associate with several proteins with a role in replication, DNA repair, and checkpoint signaling, specifically the trimeric 9-1-1 complex. In a genetic investigation of the fission yeast MutY homolog, myh1(+), we show that the myh1 mutation confers a moderately increased UV sensitivity alone and in combination with mutations in several DNA repair genes. The myh1 rad1, and to a lesser degree myh1 rad9, double mutants display a synthetic interaction resulting in enhanced sensitivity to DNA damaging agents and hydroxyurea. UV irradiation of myh1 rad1 double mutants results in severe chromosome segregation defects and visible DNA fragmentation, and a failure to activate the checkpoint. Additionally, myh1 rad1 double mutants exhibit morphological defects in the absence of DNA damaging agents. We also found a moderate suppression of the slow growth and UV sensitivity of rhp51 mutants by the myh1 mutation. Our results implicate fission yeast Myh1 in repair of a wider range of DNA damage than previously thought, and functionally link it to the checkpoint pathway.

Exploring photoinactivation of microbial biofilms using laser scanning microscopy and confined 2-photon excitation.

One pertinent complication in bacterial infection is the growth of biofilms, that is, communities of surface-adhered bacteria resilient to antibiotics. Photodynamic inactivation (PDI) has been proposed as an alternative to antibiotic treatment; however, novel techniques complementing standard efficacy measures are required. Herein, we present an approach employing multiphoton microscopy complemented with Airyscan super-resolution microscopy, to visualize the distribution of curcumin in Staphylococcus epidermidis biofilms. The effects of complexation of curcumin with hydroxypropyl-γ-cyclodextrin (HPγCD) were studied. It was shown that HPγCD curcumin demonstrated higher bioavailability in the biofilms compared to curcumin, without affecting the subcellular uptake. Spectral quantification following PDI demonstrates a method for monitoring elimination of biofilms in real time using noninvasive 3D imaging. Additionally, spatially confined 2-photon inactivation was demonstrated for the first time in biofilms. These results support the feasibility of advanced optical microscopy as a sensitive tool for evaluating treatment efficacy in biofilms toward improved mechanistic studies of PDI.