Publications by Colleges and Departments (MSU - Bozeman)
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Item Imaging and plate counting to quantify the effect of an antimicrobial: A case study of a photo‐activated chlorine dioxide treatment(Wiley, 2022-09) Parker, Albert E.; Miller, Lindsey; Adams, Jacob; Pettigrew, Charles; Buckingham‐Meyer, Kelli; Summers, Jennifer; Christen, Andres; Goeres, DarlaAim. To assess removal versus kill efficacies of antimicrobial treatments against thick biofilms with statistical confidence. Methods and results. A photo-activated chlorine dioxide treatment (Photo ClO2) was tested in two independent experiments against thick (>100 μm) Pseudomonas aeruginosa biofilms. Kill efficacy was assessed by viable plate counts. Removal efficacy was assessed by 3D confocal scanning laser microscope imaging (CSLM). Biovolumes were calculated using an image analysis approach that models the penetration limitation of the laser into thick biofilms using Beer's Law. Error bars are provided that account for the spatial correlation of the biofilm's surface. The responsiveness of the biovolumes and plate counts to the increasing contact time of Photo ClO2 were quite different, with a massive 7 log reduction in viable cells (95% confidence interval [CI]: 6.2, 7.9) but a more moderate 73% reduction in biovolume (95% CI: [60%, 100%]). Results are leveraged to quantitatively assess candidate CSLM experimental designs of thick biofilms. Conclusions. Photo ClO2 kills biofilm bacteria but only partially removes the biofilm from the surface. To maximize statistical confidence in assessing removal, imaging experiments should use fewer pixels in each z-slice, and more importantly, at least two independent experiments even if there is only a single field of view in each experiment. Significance and impact of study There is limited penetration depth when collecting 3D confocal images of thick biofilms. Removal can be assessed by optimally fitting Beer's Law to all of the intensities in a 3D image and by accounting for the spatial correlation of the biofilm's surface. For thick biofilms, other image analysis approaches are biased or do not provide error bars. We generate unbiased estimates of removal and assess candidate CSLM experimental designs of thick biofilms with different pixilations, numbers of fields of view and number of experiments using the included design tool.Item Experimental Designs to Study the Aggregation and Colonization of Biofilms by Video Microscopy With Statistical Confidenc(Frontiers Media SA, 2022-01) Pettygrove, Brian A.; Smith, Heidi J.; Pallister, Kyler B.; Voyich, Jovanka M.; Stewart, Philip S.; Parker, Albert E.The goal of this study was to quantify the variability of confocal laser scanning microscopy (CLSM) time-lapse images of early colonizing biofilms to aid in the design of future imaging experiments. To accomplish this a large imaging dataset consisting of 16 independent CLSM microscopy experiments was leveraged. These experiments were designed to study interactions between human neutrophils and single cells or aggregates of Staphylococcus aureus (S. aureus) during the initial stages of biofilm formation. Results suggest that in untreated control experiments, variability differed substantially between growth phases (i.e., lag or exponential). When studying the effect of an antimicrobial treatment (in this case, neutrophil challenge), regardless of the inoculation level or of growth phase, variability changed as a frown-shaped function of treatment efficacy (i.e., the reduction in biofilm surface coverage). These findings were used to predict the best experimental designs for future imaging studies of early biofilms by considering differing (i) numbers of independent experiments; (ii) numbers of fields of view (FOV) per experiment; and (iii) frame capture rates per hour. A spreadsheet capable of assessing any user-specified design is included that requires the expected mean log reduction and variance components from user-generated experimental results. The methodology outlined in this study can assist researchers in designing their CLSM studies of antimicrobial treatments with a high level of statistical confidence.Item Systematic Statistical Analysis of Microbial Data from Dilution Series(Springer Science and Business Media LLC, 2020-05) Christen, J. Andrés; Parker, Albert E.In microbial studies, samples are often treated under different experimental conditions and then tested for microbial survival. A technique, dating back to the 1880's, consists of diluting the samples several times and incubating each dilution to verify the existence of microbial Colony Forming Units or CFU's, seen by the naked eye. The main problem in the dilution series data analysis is the uncertainty quantification of the simple point estimate of the original number of CFU's in the sample (i.e., at dilution zero). Common approaches such as log-normal or Poisson models do not seem to handle well extreme cases with low or high counts, among other issues. We build a novel binomial model, based on the actual design of the experimental procedure including the dilution series. For repetitions we construct a hierarchical model for experimental results from a single lab and in turn a higher hierarchy for inter-lab analyses. Results seem promising, with a systematic treatment of all data cases, including zeros, censored data, repetitions, intra and inter-laboratory studies. Using a Bayesian approach, a robust and efficient MCMC method is used to analyze several real data sets.Item Evaluation of the Antimicrobial Efficacy of N-Acetyl-l-Cysteine, Rhamnolipids, and Usnic Acid—Novel Approaches to Fight Food-Borne Pathogens(MDPI, 2021) Chlumsky, Ondrej; Smith, Heidi J.; Parker, Albert E.; Brileya, Kristen; Wilking, James N.; Purkrtova, Sabina; Michova, Hana; Ulbrich, Pavel; Viktorova, Jitka; Demnerova, KaterinaIn the food industry, the increasing antimicrobial resistance of food-borne pathogens to conventional sanitizers poses the risk of food contamination and a decrease in product quality and safety. Therefore, we explored alternative antimicrobials N-Acetyl-L-cysteine (NAC), rhamnolipids (RLs), and usnic acid (UA) as a novel approach to prevent biofilm formation and reduce existing biofilms formed by important food-borne pathogens (three strains of Salmonella enterica and two strains of Escherichia coli, Listeria monocytogenes, Staphylococcus aureus). Their effectiveness was evaluated by determining minimum inhibitory concentrations needed for inhibition of bacterial growth, biofilm formation, metabolic activity, and biofilm reduction. Transmission electron microscopy and confocal scanning laser microscopy followed by image analysis were used to visualize and quantify the impact of tested substances on both planktonic and biofilm-associated cells. The in vitro cytotoxicity of the substances was determined as a half-maximal inhibitory concentration in five different cell lines. The results indicate relatively low cytotoxic effects of NAC in comparison to RLs and UA. In addition, NAC inhibited bacterial growth for all strains, while RLs showed overall lower inhibition and UA inhibited only the growth of Gram-positive bacteria. Even though tested substances did not remove the biofilms, NAC represents a promising tool in biofilm prevention.Item Drip flow reactor method exhibits excellent reproducibility based on a 10-laboratory collaborative study(Elsevier BV, 2020) Goeres, Darla M.; Parker, Albert E.; Walker, Diane K.; Meier, Kelsey; Lorenz, Lindsey A.; Buckingham-Meyer, KelliA standard method for growing Pseudomonas aeruginosa biofilm in the Drip Flow Biofilm Reactor was assessed in a 10-laboratory study. The mean log density was 9.29 Log10(CFU/cm2). The repeatability and reproducibility SDs were equal to 0.22 and 0.24, respectively, providing statistical confidence in data generated by the method.Item Activity-based cell sorting reveals responses of uncultured archaea and bacteria to substrate amendment(Springer Science and Business Media LLC, 2020) Reichart, Nicholas J.; Jay, Zachary J.; Krukenberg, Viola; Parker, Albert E.; Lange Spietz, Rachel K.; Hatzenpichler, RolandMetagenomic studies have revolutionized our understanding of the metabolic potential of uncultured microorganisms in various ecosystems. However, many of these genomic predictions have yet to be experimentally tested, and the functional expression of genomic potential often remains unaddressed. In order to obtain a more thorough understanding of cell physiology, novel techniques capable of testing microbial metabolism under close to in situ conditions must be developed. Here, we provide a benchmark study to demonstrate that bioorthogonal non-canonical amino acid tagging (BONCAT) in combination with fluorescence-activated cell sorting (FACS) and 16S rRNA gene sequencing can be used to identify anabolically active members of a microbial community incubated in the presence of various growth substrates or under changing physicochemical conditions. We applied this approach to a hot spring sediment microbiome from Yellowstone National Park (Wyoming, USA) and identified several microbes that changed their activity levels in response to substrate addition, including uncultured members of the phyla Thaumarchaeota, Acidobacteria, and Fervidibacteria. Because shifts in activity in response to substrate amendment or headspace changes are indicative of microbial preferences for particular growth conditions, results from this and future BONCAT-FACS studies could inform the development of cultivation media to specifically enrich uncultured microbes. Most importantly, BONCAT-FACS is capable of providing information on the physiology of uncultured organisms at as close to in situ conditions as experimentally possible.Item Bayesian estimation and uncertainty quantification in models of urea hydrolysis by E. coli biofilms(Informa UK Limited, 2021-02) Jackson, Benjamin D.; Connolly, James M.; Gerlach, Robin; Klapper, Issac; Parker, Albert E.Urea-hydrolysing biofilms are crucial to applications in medicine, engineering, and science. Quantitative information about ureolysis rates in biofilms is required to model these applications. We formulate a novel model of urea consumption in a biofilm that allows different kinetics, for example either first order or Michaelis-Menten. The model is fit it to synthetic data to validate and compare two approaches: Bayesian and nonlinear least squares (NLS), commonly used by biofilm practitioners. The shortcomings of NLS motivate the Bayesian approach where a simple Markov Chain Monte Carlo (MCMC) sampler is applied. The model is then fit to real data of influent and effluent urea concentrations from experiments on biofilms of Escherichia coli. Results from synthetic data aid in interpreting results from real data, where first order and Michaelis-Menten kinetic models are compared. The method shows potential for general applications requiring biofilm kinetic information.Item Design and fabrication of biofilm reactors(2020) Goeres, Darla M.; Pedersen, Stephen; Warwood, B. K.; Walker, Diane K.; Parker, Albert E.; Mettler, Madelyn; Sturman, Paul J.Laboratory biofilm reactors are tools that researchers use to grow biofilms that exhibit characteristics sufficiently similar to the environment of interest. Numerous biofilm reactors that model various fluid dynamics are described in scientific literature, each with its associated list of advantages and limitations. This chapter focuses on the process used to design and fabricate biofilm reactors with the stated goal of generating a commercial product. The process begins with identifying the environment of interest and key attributes the reactor should include or model. A prototype is then designed, built, and tested in the laboratory. Modifications are made based upon laboratory performance until a design is achieved that is affordable, practical, operationally simple, and relevant and that provides repeatable, convincing results. This process was used to design the industrial surfaces biofilm reactor, developed to model cooling tower biofilms but suitable to study biofilms grown under low shear, high gas transfer, and intermittently wet conditions.Item Interlaboratory study for the evaluation of three microtiter plate-based biofilm quantification methods(2021-07) Allkja, Jontana; van Charante, Frits; Aizawa, Juliana; Reigada, Ines; Guarch-Perez, Clara; Vazquez-Rodriguez, Jesus Augusto; Cos, Paul; Coenye, Tom; Fallarero, Adyary; Zaat, Sebastian A. J.; Felici, Antonio; Ferrari, Livia; Azevado, Nuno F.; Parker, Albert E.; Goeres, Darla M.Microtiter plate methods are commonly used for biofilm assessment. However, results obtained with these methods have often been difficult to reproduce. Hence, it is important to obtain a better understanding of the repeatability and reproducibility of these methods. An interlaboratory study was performed in five different laboratories to evaluate the reproducibility and responsiveness of three methods to quantify Staphylococcus aureus biofilm formation in 96-well microtiter plates: crystal violet, resazurin, and plate counts. An inter-lab protocol was developed for the study. The protocol was separated into three steps: biofilm growth, biofilm challenge, biofilm assessment. For control experiments participants performed the growth and assessment steps only. For treatment experiments, all three steps were performed and the efficacy of sodium hypochlorite (NaOCl) in killing S. aureus biofilms was evaluated. In control experiments, on the log10-scale, the reproducibility SD (SR) was 0.44 for crystal violet, 0.53 for resazurin, and 0.92 for the plate counts. In the treatment experiments, plate counts had the best responsiveness to different levels of efficacy and also the best reproducibility with respect to responsiveness (Slope/SR = 1.02), making it the more reliable method to use in an antimicrobial efficacy test. This study showed that the microtiter plate is a versatile and easy-to-use biofilm reactor, which exhibits good repeatability and reproducibility for different types of assessment methods, as long as a suitable experimental design and statistical analysis is applied.Item Optimal surface estimation and thresholding of confocal microscope images of biofilms using Beer's Law(2020-05) Parker, Albert E.; Christen, J. A.; Lorenz, Lindsey A.; Smith, Heidi J.Beer's Law explains how light attenuates into thick specimens, including thick biofilms. We use a Bayesian optimality criterion, the maximum of the posterior probability distribution, and computationally efficiently fit Beer's Law to the 3D intensity data collected from thick living biofilms by a confocal scanning laser microscope. Using this approach the top surface of the biofilm and an optimal image threshold can be estimated. Biofilm characteristics, such as bio-volumes, can be calculated from this surface. Results from the Bayesian approach are compared to other approaches including the method of maximum likelihood or simply counting bright pixels. Uncertainty quantification (i.e., error bars) can be provided for the parameters of interest. This approach is applied to confocal images of stained biofilms of a common lab strain of Pseudomonas aeruginosa, stained biofilms of Janthinobacterium isolated from the Antarctic, and biofilms of Staphylococcus aureus that have been genetically modified to fluoresce green.