Unlocking the genome of the non-sourdough Kazachstania humilis MAW1: insights into inhibitory factors and phenotypic properties.

BACKGROUND: Ascomycetous budding yeasts are ubiquitous environmental microorganisms important in food production and medicine. Due to recent intensive genomic research, the taxonomy of yeast is becoming more organized based on the identification of monophyletic taxa. This includes genera important to humans, such as Kazachstania. Until now, Kazachstania humilis (previously Candida humilis) was regarded as a sourdough-specific yeast. In addition, any antibacterial activity has not been associated with this species. RESULTS: Previously, we isolated a yeast strain that impaired bio-hydrogen production in a dark fermentation bioreactor and inhibited the growth of Gram-positive and Gram-negative bacteria. Here, using next generation sequencing technologies, we sequenced the genome of this strain named K. humilis MAW1. This is the first genome of a K. humilis isolate not originating from a fermented food. We used novel phylogenetic approach employing the 18 S-ITS-D1-D2 region to show the placement of the K. humilis MAW1 among other members of the Kazachstania genus. This strain was examined by global phenotypic profiling, including carbon sources utilized and the influence of stress conditions on growth. Using the well-recognized bacterial model Escherichia coli AB1157, we show that K. humilis MAW1 cultivated in an acidic medium inhibits bacterial growth by the disturbance of cell division, manifested by filament formation. To gain a greater understanding of the inhibitory effect of K. humilis MAW1, we selected 23 yeast proteins with recognized toxic activity against bacteria and used them for Blast searches of the K. humilis MAW1 genome assembly. The resulting panel of genes present in the K. humilis MAW1 genome included those encoding the 1,3-ß-glucan glycosidase and the 1,3-ß-glucan synthesis inhibitor that might disturb the bacterial cell envelope structures. CONCLUSIONS: We characterized a non-sourdough-derived strain of K. humilis, including its genome sequence and physiological aspects. The MAW1, together with other K. humilis strains, shows the new organization of the mating-type locus. The revealed here pH-dependent ability to inhibit bacterial growth has not been previously recognized in this species. Our study contributes to the building of genome sequence-based classification systems; better understanding of K.humilis as a cell factory in fermentation processes and exploring bacteria-yeast interactions in microbial communities.

A stochastic programming approach to the antibiotics time machine problem.

Antibiotics Time Machine is an important problem to understand antibiotic resistance and how it can be reversed. Mathematically, it can be modeled as follows: Consider a set of genotypes, each of which contain a set of mutated and unmutated genes. Suppose that a set of growth rate measurements of each genotype under a set of antibiotics is given. The transition probabilities of a 'realization' of a Markov chain associated with each arc under each antibiotic are computable via a predefined function given the growth rate realizations. The aim is to maximize the expected probability of reaching to the genotype with all unmutated genes given the initial genotype in a predetermined number of transitions, considering the following two sources of uncertainties: (i) the randomness in growth rates, (ii) the randomness in transition probabilities, which are functions of growth rates. We develop stochastic mixed-integer linear programming and dynamic programming approaches to solve static and dynamic versions of the Antibiotics Time Machine Problem under the aforementioned uncertainties. We adapt a Sample Average Approximation approach that exploits the special structure of the problem and provide accurate solutions that perform very well in an out-of-sample analysis.

Proliferation of psychrotrophic bacteria in cold-stored platelet concentrates.

BACKGROUND AND OBJECTIVES: Platelet concentrates (PC) are stored at 20-24°C to maintain platelet functionality, which may promote growth of contaminant bacteria. Alternatively, cold storage of PC limits bacterial growth; however, data related to proliferation of psychotrophic species in cold-stored PC (CSP) are scarce, which is addressed in this study. MATERIALS AND METHODS: Eight laboratories participated in this study with a pool/split approach. Two split PC units were spiked with ~25 colony forming units (CFU)/PC of Staphylococcus aureus, Klebsiella pneumoniae, Serratia liquefaciens, Pseudomonas fluorescens and Listeria monocytogenes. One unit was stored under agitation at 20-24°C/7 days while the second was stored at 1-6°C/no agitation for 21 days. PC were sampled periodically to determine bacterial loads. Five laboratories repeated the study with PC inoculated with lyophilized inocula (~30 CFU/mL) of S. aureus and K. pneumoniae. RESULTS: All species proliferated in PC stored at 20-24°C, reaching concentrations of ≤109 CFU/mL by day 7. Psychrotrophic P. fluorescens and S. liquefaciens proliferated in CSP to ~106 CFU/mL and ~105 CFU/mL on days 10 and 17 of storage, respectively, followed by L. monocytogenes, which reached ~102 CFU/mL on day 21. S. aureus and K. pneumoniae did not grow in CSP. CONCLUSION: Psychrotrophic bacteria, which are relatively rare contaminants in PC, proliferated in CSP, with P. fluorescens reaching clinically significant levels (≥105 CFU/mL) before day 14 of storage. Cold storage reduces bacterial risk of PC to levels comparable with RBC units. Safety of CSP could be further improved by implementing bacterial detection systems or pathogen reduction technologies if storage is beyond 10 days.

Strain-specific Growth Parameters are Important to Accurately Model Bacterial Growth on Baby Spinach in Simulation Models.

Digital tools to predict produce shelf life have the potential to reduce food waste and improve consumer satisfaction. To address this need, we (i) performed an observational study on the microbial quality of baby spinach, (ii) completed growth experiments of bacteria that are representative of the baby spinach microbiota, and (iii) developed an initial simulation model of bacterial growth on baby spinach. Our observational data showed that the predominant genera found on baby spinach were Pseudomonas, Pantoea and Exiguobacterium. Rifampicin-resistant mutants (rifR mutants) of representative bacterial subtypes were subsequently generated to obtain strain-specific growth parameters on baby spinach. These experiments showed that: (i) it is difficult to select rifR mutants that do not have fitness costs affecting growth (9 of 15 rifR mutants showed substantial differences in growth, compared to their corresponding wild-type strain) and (ii) based on estimates from primary growth models, the mean (geometric) maximum population of rifR mutants on baby spinach (7.6 log10 CFU/g, at 6°C) appears lower than that of the spinach microbiota (9.6 log10 CFU/g, at 6°C), even if rifR mutants did not have substantial growth-related fitness costs. Thus, a simulation model, parameterized with the data obtained here as well as literature data on home refrigeration temperatures, underestimated bacterial growth on baby spinach. The root mean square error of the simulation's output, compared against data from the observational study, was 1.11 log10 CFU/g. Sensitivity analysis was used to identify key parameters (e.g., strain maximum population) that impact the simulation model's output, allowing for prioritization of future data collection to improve the simulation model. Overall, this study provides a roadmap for the development of models to predict bacterial growth on leafy vegetables with strain-specific parameters and suggests that additional data are required to improve these models.

Short communication: Investigating optimal laboratory growth conditions of Gracilibacillus halotolerans in media supplemented with salt.

Gracilibacillus halotolerans, a new and relatively unstudied extremophile, extracted from the Great Salt Lake USA, survives in an extreme saline environment. Uncovering optimal laboratory growth conditions can be useful to improve treatment strategies against antibiotic resistance and biofilm formation. In the current study, G. halotolerans growth optimization was tested to determine the ideal saline concentration. In addition, a variety of G. halotolerans'-derived survival strategies were reviewed. The major findings of the current study includes the optimal laboratory growth condition for G. halotolerans that requires the supplement of 5% NaCl. In addition, optimal growth was observed up to 72 h in Luria Bertani (LB) broth. Identifying the optimal laboratory growth conditions for G. halotolerans will standardize growth methods, reduce laboratory cost, and can improve future investigations of extremophile bacteria as model organisms to combat antibiotic resistance, biofilm, and other persister cell characteristics that negatively affect research and clinical settings.

Initial cyclic-di-GMP upregulation triggers sporadic cellular expansion leading to improved cellular survival.

Bacterial second messenger c-di-GMP upregulation is associated with the transition from planktonic to sessile microbial lifestyle, inhibiting cellular motility, and virulence. However, in-depth elucidation of the cellular processes resulting from c-di-GMP upregulation has not been fully explored. Here, we report the role of upregulated cellular c-di-GMP in promoting planktonic cell growth of Escherichia coli K12 and Pseudomonas aeruginosa PAO1. We found a rapid expansion of cellular growth during initial cellular c-di-GMP upregulation, resulting in a larger planktonic bacterial population. The initial increase in c-di-GMP levels promotes bacterial swarming motility during the growth phase, which is subsequently inhibited by the continuous increase of c-di-GMP, and ultimately facilitates the formation of biofilms. We demonstrated that c-di-GMP upregulation triggers key bacterial genes linked to bacterial growth, swarming motility, and biofilm formation. These genes are mainly controlled by the master regulatory genes csgD and csrA. This study provides us a glimpse of the bacterial behavior of evading potential threats through adapting lifestyle changes via c-di-GMP regulation.

Microbial Primer: Bacterial growth kinetics.

tGrowth of microorganisms and interpretation of growth data are core skills required by microbiologists. While science moves forward, it is of paramount importance that essential skills are not lost. The bacterial growth curve and the information that can gleaned from it is of great value to all of microbiology, whether this be a simple growth experiment, comparison of mutant strains or the establishment of conditions for a large-scale multi-omics experiment. Increasingly, the basics of plotting and interpreting growth curves and growth data are being overlooked. This primer article serves as a refresher for microbiologists on the fundamentals of microbial growth kinetics.

Optimal enzyme profiles in unbranched metabolic pathways.

How to optimize the allocation of enzymes in metabolic pathways has been a topic of study for many decades. Although the general problem is complex and nonlinear, we have previously shown that it can be solved by convex optimization. In this paper, we focus on unbranched metabolic pathways with simplified enzymatic rate laws and derive analytic solutions to the optimization problem. We revisit existing solutions based on the limit of mass-action rate laws and present new solutions for other rate laws. Furthermore, we revisit a known relationship between flux control coefficients and enzyme abundances in optimal metabolic states. We generalize this relationship to models with density constraints on enzymes and metabolites, and present a new local relationship between optimal reaction elasticities and enzyme amounts. Finally, we apply our theory to derive simple kinetics-based formulae for protein allocation during bacterial growth.

Measuring differential fitness costs and interactions between genetic cassettes using fluorescent spectrophotometry.

In this article, we present a method for designing, executing, and analyzing data from a microbial competition experiment. We use fluorescent reporters to label different competing strains and resolve individual growth curves using a fluorescent spectrophotometer. Our comprehensive data analysis pipeline integrates multiple experiments to simultaneously infer sources of variation, extract selection coefficients, and estimate the genetic contributions to fitness for various synthetic genetic cassettes (SGCs). To demonstrate the method, we employ a synthetic biological system based on Escherichia coli. Strains carry 1 of 10 different plasmids and one of three genomically integrated fluorescent markers. All strains are co-cultured to obtain real-time measurements of optical density (total population density) and fluorescence (sub-population densities). We identify challenges in calibrating between fluorescence and density and of fluorescent proteins maturing at different rates. To resolve these issues, we compare two methods of fluorescence calibration and correct for maturation by measuring in vivo maturation times. We provide evidence of genetic interactions occurring between our SGCs and further show how to use our statistical model to test some hypotheses about microbial growth and the costs of protein expression.IMPORTANCEFluorescently labeled co-cultures are becoming increasingly popular. The approach proposed here offers a high standard for experimental design and data analysis to measure selection coefficients and growth rates in competition. Measuring competitive differences is useful in many laboratory studies, allowing for fitness cost-correction of growth rates and ecological interactions and testing hypotheses in synthetic biology. Using time-resolved growth curves, rather than endpoint measurements, for competition assays allows us to construct a detailed scientific model that can be used to ask questions about fine-grained phenomena, such as bacterial growth dynamics, as well as higher-level phenomena, such as the interactions between synthetic cassette expression.

BactEXTRACT: an R Shiny app to quickly extract, plot and analyse bacterial growth and gene expression data.

To streamline the analysis and visualization of bacterial growth and gene expression data obtained by microtitre plate readers, we developed BactEXTRACT, an intuitive, easy-to-use R Shiny application. BactEXTRACT simplifies the transition from raw optical density, fluorescence and luminescence measurements to publication-ready plots. This package offers a user-friendly interface that reduces the complexity involved in growth curve and gene expression analysis and is generally applicable. BactEXTRACT is available at https://veeninglab.com/bactextract.

Corrigendum: Tranexamic acid in combination with vancomycin or gentamicin has a synergistic effect against staphylococci.

[This corrects the article DOI: 10.3389/fmicb.2022.935646.].

The Growth Yield of Aminobacter niigataensis MSH1 on the Micropollutant 2,6-Dichlorobenzamide Decreases Substantially at Trace Substrate Concentrations.

2,6-Dichlorobenzamide (BAM) is an omnipresent micropollutant in European groundwaters. Aminobacter niigataensis MSH1 is a prime candidate for biologically treating BAM-contaminated groundwater since this organism is capable of utilizing BAM as a carbon and energy source. However, detailed information on the BAM degradation kinetics by MSH1 at trace concentrations is lacking, while this knowledge is required for predicting and optimizing the degradation process. Contaminating assimilable organic carbon (AOC) in media makes the biodegradation experiment a mixed-substrate assay and hampers exploration of pollutant degradation at trace concentrations. In this study, we examined how the BAM concentration affects MSH1 growth and BAM substrate utilization kinetics in a AOC-restricted background to avoid mixed-substrate conditions. Conventional Monod kinetic models were unable to predict kinetic parameters at low concentrations from kinetics determined at high concentrations. Growth yields on BAM were concentration-dependent and decreased substantially at trace concentrations; i.e., growth of MSH1 diminished until undetectable levels at BAM concentrations below 217 µg-C/L. Nevertheless, BAM degradation continued. Decreasing growth yields at lower BAM concentrations might relate to physiological adaptations to low substrate availability or decreased expression of downstream steps of the BAM catabolic pathway beyond 2,6-dichlorobenzoic acid (2,6-DCBA) that ultimately leads to Krebs cycle intermediates for growth and energy conservation.

Three distinct metabolic phases of polychlorinated biphenyls/biphenyl degrader Acidovorax sp. KKS102 in nutrient broth.

Acidovorax sp. KKS102 is a beta-proteobacterium capable of degrading polychlorinated biphenyls (PCBs). In this study, we examined its growth in liquid nutrient broth supplemented with different carbon sources. KKS102 had at least 3 distinct metabolic phases designated as metabolic phases 1-3, with phase 2 having 2 sub-phases. For example, succinate, fumarate, and glutamate, known to repress the PCB/biphenyl catabolic operon in KKS102, were utilized in phase 1, while acetate, arabinose, and glycerol in phase 2, and glucose and mannose in phase 3. We also showed that the BphQ response regulator mediating catabolite control in KKS102, whose expression level increased moderately through the growth, plays important roles in carbon metabolism in phases 2 and 3. Our study elucidates the hierarchical growth of KKS102 in nutrient-rich media. This insight is crucial for studies exploiting microbial biodegradation capabilities and advancing studies for catabolite regulation mechanisms.

Temperature Adaptation of Aquatic Bacterial Community Growth Is Faster in Response to Rising than to Falling Temperature.

Bacteria are key organisms in energy and nutrient cycles, and predicting the effects of temperature change on bacterial activity is important in assessing global change effects. A changing in situ temperature will affect the temperature adaptation of bacterial growth in lake water, both long term in response to global change, and short term in response to seasonal variations. The rate of adaptation may, however, depend on whether temperature is increasing or decreasing, since bacterial growth and turnover scale with temperature. Temperature adaptation was studied for winter (in situ temperature 2.5 °C) and summer communities (16.5 °C) from a temperate lake in Southern Sweden by exposing them to a temperature treatment gradient between 0 and 30 °C in ~ 5 °C increments. This resulted mainly in a temperature increase for the winter and a decrease for the summer community. Temperature adaptation of bacterial community growth was estimated as leucine incorporation using a temperature Sensitivity Index (SI, log growth at 35 °C/4 °C), where higher values indicate adaptation to higher temperatures. High treatment temperatures resulted in higher SI within days for the winter community, resulting in an expected level of community adaptation within 2 weeks. Adaptation for the summer community was also correlated to treatment temperature, but the rate of adaption was slower. Even after 5 weeks, the bacterial community had not fully adapted to the lowest temperature conditions. Thus, during periods of increasing temperature, the bacterial community will rapidly adapt to function optimally, while decreasing temperature may result in long periods of non-optimal functioning.

Modularized Design and Construction of Tunable Microbial Consortia with Flexible Topologies.

Complex and fluid bacterial community compositions are critical to diversity, stability, and function. However, quantitative and mechanistic descriptions of the dynamics of such compositions are still lacking. Here, we develop a modularized design framework that allows for bottom-up construction and the study of synthetic bacterial consortia with different topologies. We showcase the microbial consortia design and building process by constructing amensalism and competition consortia using only genetic circuit modules to engineer different strains to form the community. Functions of modules and hosting strains are validated and quantified to calibrate dynamic parameters, which are then directly fed into a full mechanistic model to accurately predict consortia composition dynamics for both amensalism and competition without further fitting. More importantly, such quantitative understanding successfully identifies the experimental conditions to achieve coexistence composition dynamics. These results illustrate the process of both computationally and experimentally building up bacteria consortia complexity and hence achieve robust control of such fluid systems.

Machine learning identifies key metabolic reactions in bacterial growth on different carbon sources.

Carbon source-dependent control of bacterial growth is fundamental to bacterial physiology and survival. However, pinpointing the metabolic steps important for cell growth is challenging due to the complexity of cellular networks. Here, the elastic net model and multilayer perception model that integrated genome-wide gene-deletion data and simulated flux distributions were constructed to identify metabolic reactions beneficial or detrimental to Escherichia coli grown on 30 different carbon sources. Both models outperformed traditional in silico methods by identifying not just essential reactions but also nonessential ones that promote growth. They successfully predicted metabolic reactions beneficial to cell growth, with high convergence between the models. The models revealed that biosynthetic pathways generally promote growth across various carbon sources, whereas the impact of energy-generating pathways varies with the carbon source. Intriguing predictions were experimentally validated for findings beyond experimental training data and the impact of various carbon sources on the glyoxylate shunt, pyruvate dehydrogenase reaction, and redundant purine biosynthesis reactions. These highlight the practical significance and predictive power of the models for understanding and engineering microbial metabolism.

Bacteriology and clinical outcomes of urine mixed bacterial growth in pregnancy.

INTRODUCTION AND HYPOTHESIS: The objective was to analyse the risk of significant bacteriuria in repeat urine cultures from pregnant women, following initial mixed bacterial results. METHODS: This retrospective study examined maternal characteristics and clinical features of women who repeated urine cultures due to previous mixed cultures results. RESULTS: Of 262 women included, 80 (30.5%) had negative cultures and 125 (47.7%) had mixed bacterial growth in their repeat cultures. Positive results (≥104 CFU/ml of a urinary pathogen) were obtained for 57 women (21.8% [95% CI 17.1-27.0]). For 37 (14.1%), the repeat specimen grew 104-105 CFU/ml of microorganisms; whereas for 20 women (7.6% [95% CI 4.9-11.3]), it grew ≥105 CFU/ml. Among women with positive (>104 CFU/ml) compared with those with negative or mixed growth, rates of urinary symptoms were higher (38.6% vs 23.4%, p=0.028), abnormal dipstick results (49.1% vs 21.0%, p<0.001) and hydronephrosis, as demonstrated by renal ultrasound (12.3% vs 2.0, p=0.003). In a multivariate logistic regression analysis, hydronephrosis was associated with the occurrence of a positive repeat culture (aOR = 10.65, 95% CI 2.07-54.90). The sensitivity and specificity for predicting a repeat urine culture with ≥105 CFU/ml were 12.9% and 94.3% respectively, for urinary symptoms; and 19.7% and 97.4% respectively, for abnormal dipstick results. CONCLUSIONS: Mixed bacterial growth might represent a true urinary tract infection in a considerable proportion of women who are symptomatic and have an abnormal dipstick urinalysis.

Personal stethoscope disinfection practices and bacterial contamination: A cross-sectional study at the University Hospital Emergency Department in Belgrade, Serbia.

BACKGROUND: A significant reduction in bacterial growth on stethoscope membranes has been noticed after performing daily disinfection. Nevertheless, disinfection is rarely performed. We aimed to assess self-reported stethoscope disinfection practices among medical doctors, detect bacterial contamination on personal stethoscopes, and estimate the effectiveness of 70% ethanol as a stethoscope disinfecting agent. METHODS: To determine stethoscope disinfection practices, participants filled out a questionnaire (N = 47), followed by providing stethoscopes for bacterial analysis. Differences in bacterial contamination were observed through the self-reported frequency and method of stethoscope disinfection. The effect of disinfecting with 70% ethanol was evaluated by comparing the presence of bacterial growth before and after disinfection. RESULTS: The presence of bacterial growth was found in 78.7% of the stethoscope samples, with the median (interquartile range) number of colony-forming units at 25 (10-105). The frequency of disinfection greatly impacted the number of colony-forming units, and the method affected the presence of bacterial growth. Disinfection of stethoscope membranes using 70% ethanol resulted in a compelling 97.3% reduction of bacterial growth. CONCLUSIONS: Adequate stethoscope disinfection is highly efficient in reducing bacterial contamination and as such should be considered a critical step in hygienic practices.

Luz UVC como estratégia de desinfecção do ar e superfícies hospitalares / Luz UV-C como estrategia de desinfección del aire y superficies hospitalarias / UVC light as a strategy for disinfection of hospital air and surfaces

Resumo Objetivo Avaliar a eficácia antimicrobiana de um dispositivo fixo emissor de luz UV-C na desinfecção de diferentes superfícies do ambiente hospitalar e sua eficácia antifúngica na qualidade do ar. Métodos Estudo quase-experimental realizado em uma unidade de internação hospitalar, que utilizou o Bioamostrador de ar Andersen® de seis estágios para análise do ar; e na avaliação das superfícies, utilizaram-se três suspensões de microrganismos (Acinetobacter sp. MDR, Escherichia coli e Klebsiella pneumoniae produtora de KPC) para contaminar o ambiente. Para ambos foram feitas coletas pré (controle) e pós-acionamento da luz UV-C (teste). Resultados Na avaliação do ar houve uma redução importante da contagem de colônias após a luz UV-C e não foram encontrados fungos patogênicos ou toxigênicos em nenhum dos dois momentos. Em relação à desinfecção das superfícies, nenhum crescimento bacteriano foi observado após a intervenção da luz, demonstrando 100% de inativação bacteriana nas condições testadas. Conclusão A utilização da tecnologia com emissão de luz UV-C fixa foi eficaz e pode ser considerada uma intervenção promissora para protocolos de desinfecção de superfícies hospitalares.

Resumen Objetivo Evaluar la eficacia antimicrobiana de un dispositivo fijo emisor de luz UV-C para la desinfección de diferentes superficies del ambiente hospitalario y su eficacia antifúngica en la calidad del aire. Métodos Estudio cuasi experimental realizado en una unidad de internación hospitalaria, en que se utilizó el biomuestreador de aire Andersen® de seis etapas para el análisis del aire. En el análisis de las superficies, se utilizaron tres suspensiones de microorganismos (Acinetobacter sp. MDR, Escherichia coli y Klebsiella pneumoniae productora de KPC) para contaminar el ambiente. En ambos se tomó una muestra antes (control) y después de accionar la luz UV-C (prueba). Resultados En el análisis del aire hubo una reducción importante del recuento de colonias después de la luz UV-C y no se encontraron hongos patógenos ni toxigénicos en ninguno de los dos momentos. Con relación a la desinfección de las superficies, no se observó ningún crecimiento bacteriano después de la intervención de la luz, lo que demuestra un 100 % de inactivación bacteriana en las condiciones analizadas. Conclusión El uso de la tecnología con emisión de luz UV-C fija fue eficaz y puede ser considerada una intervención prometedora para protocolos de desinfección de superficies hospitalarias.

Abstract Objective To evaluate a fixed UV-C light emitting device for its antimicrobial effectiveness in the disinfection of distinct surfaces and its antifungal effectiveness on air quality in the hospital environment. Methods This quasi-experimental study was conducted in a hospital inpatient unit, in which a six-stage air Biosampler (Andersen®) was used for air analysis. In the evaluation of surfaces, three suspensions of microorganisms (Acinetobacter sp. multidrug-resistant, Escherichia coli, and KPC-producing Klebsiella pneumoniae) were used to contaminate the environment. In both evaluations, pre- (control) and post-activation of UV-C light (test) collections were made. Results In the air evaluation, an important reduction was observed in the colony count after irradiation with UV-C light, and pathogenic or toxigenic fungi were not found in either of the two moments. Regarding the disinfection of surfaces, no bacterial growth was observed after the application of UV-C light, showing 100% bacterial inactivation under the tested conditions. Conclusion The use of fixed UV-C light emission technology was effective and can be considered a promising intervention for hospital surface disinfection protocols.

Droplet-based methodology for investigating bacterial population dynamics in response to phage exposure.

An alarming rise in antimicrobial resistance worldwide has spurred efforts into the search for alternatives to antibiotic treatments. The use of bacteriophages, bacterial viruses harmless to humans, represents a promising approach with potential to treat bacterial infections (phage therapy). Recent advances in microscopy-based single-cell techniques have allowed researchers to develop new quantitative methodologies for assessing the interactions between bacteria and phages, especially the ability of phages to eradicate bacterial pathogen populations and to modulate growth of both commensal and pathogen populations. Here we combine droplet microfluidics with fluorescence time-lapse microscopy to characterize the growth and lysis dynamics of the bacterium Escherichia coli confined in droplets when challenged with phage. We investigated phages that promote lysis of infected E. coli cells, specifically, a phage species with DNA genome, T7 (Escherichia virus T7) and two phage species with RNA genomes, MS2 (Emesvirus zinderi) and Qß (Qubevirus durum). Our microfluidic trapping device generated and immobilized picoliter-sized droplets, enabling stable imaging of bacterial growth and lysis in a temperature-controlled setup. Temporal information on bacterial population size was recorded for up to 25 h, allowing us to determine growth rates of bacterial populations and helping us uncover the extent and speed of phage infection. In the long-term, the development of novel microfluidic single-cell and population-level approaches will expedite research towards fundamental understanding of the genetic and molecular basis of rapid phage-induced lysis and eco-evolutionary aspects of bacteria-phage dynamics, and ultimately help identify key factors influencing the success of phage therapy.