Examining the response of Escherichia coli and Pseudomonas aeruginosa to organic acid stress.

Weak organic acids have been used for centuries to treat infections and preserve food. However, the detailed mechanisms by which they exert their effect on the cell are not fully understood. Two aspects of organic acid action are presented in this thesis. In the first study, a combination of transcriptomics, transposon-insertion sequencing (TraDIS) and evolution were used to probe the molecular mechanism by which acetic, propionic and butyric acid at both neutral and mildly acidic pH affect cellular process in the UPEC strain E. coli EO499. The effects were numerous and complex, with all three organic acids having a large impact on metabolic processes. Six populations of EO 499 evolved independently at pH 5.5 with 4 mM acetic acid showed increased fitness in that environment, but that fitness was not replicated in an environment of pH 5.5 alone. A cross-comparison of the data derived from these different approaches reveals a highly complex network of genes and responses which are not easily interpreted. Comparison of the methods revealed some overlap between the TraDIS and RNAseq data, with a large proportion of the genes which were considered significant in TraDIS also showing differential regulation. This indicates that with more sophisticated bioinformatics techniques, it should be possible to build up intricate networks of the response to organic acids. The second study examined the inhibition of growth and biofilm formation in P. aeruginosa PA01 and a clinical isolate PA1054 by a range of organic acids. This study was devised to help inform the use of organic acids as a topical treatment for burn wounds. A laboratory plate reader was used to generate growth data in eight different organic acids at three different concentrations and five different pH. This data was then analysed (in collaboration with colleagues) using three mathematical approaches, two parametric and one Bayesian. The plates used for growth were also stained to quantify biofilm formation. This study found that the most effective acid at inhibiting both growth and biofilm formation was propionic acid and the least effective was benzoic acid. The effects of all acids were significantly enhanced by reduction in pH. These data indicate that the use of organic acids as a topical treatment would likely inhibit wound infections. However, the currently used concentrations of ~800 mM could be reduced if combined with mildly acidic solution

Synergistic impacts of organic acids and pH on growth of Pseudomonas aeruginosa: a comparison of parametric and Bayesian non-parametric methods to model growth

Different weak organic acids have significant potential as topical treatments for wounds infected by opportunistic pathogens that are recalcitrant to standard treatments. These acids have long been used as bacteriostatic compounds in the food industry, and in some cases are already being used in the clinic. The effects of different organic acids vary with pH, concentration, and the specific organic acid used, but no studies to date on any opportunistic pathogens have examined the detailed interactions between these key variables in a controlled and systematic way. We have therefore comprehensively evaluated the effects of several different weak organic acids on growth of the opportunistic pathogen Pseudomonas aeruginosa. We used a semi-automated plate reader to generate growth profiles for two different strains (model laboratory strain PAO1 and clinical isolate PA1054 from a hospital burns unit) in a range of organic acids at different concentrations and pH, with a high level of replication for a total of 162,960 data points. We then compared two different modeling approaches for the interpretation of this time-resolved dataset: parametric logistic regression (with or without a component to include lag phase) vs. non-parametric Gaussian process (GP) regression. Because GP makes no prior assumptions about the nature of the growth, this method proved to be superior in cases where growth did not follow a standard sigmoid functional form, as is common when bacteria grow under stress. Acetic, propionic and butyric acids were all more detrimental to growth than the other acids tested, and although PA1054 grew better than PAO1 under non-stress conditions, this difference largely disappeared as the levels of stress increased. As expected from knowledge of how organic acids behave, their effect was significantly enhanced in combination with low pH, with this interaction being greatest in the case of propionic acid. Our approach lends itself to the characterization of combinatorial interactions between stressors, especially in cases where their impacts on growth render logistic growth models unsuitable.</p

Synergistic Impacts of Organic Acids and pH on Growth of Pseudomonas aeruginosa: A Comparison of Parametric and Bayesian Non-parametric Methods to Model Growth

Different weak organic acids have significant potential as topical treatments for wounds infected by opportunistic pathogens that are recalcitrant to standard treatments. These acids have long been used as bacteriostatic compounds in the food industry, and in some cases are already being used in the clinic. The effects of different organic acids vary with pH, concentration, and the specific organic acid used, but no studies to date on any opportunistic pathogens have examined the detailed interactions between these key variables in a controlled and systematic way. We have therefore comprehensively evaluated the effects of several different weak organic acids on growth of the opportunistic pathogen Pseudomonas aeruginosa. We used a semi-automated plate reader to generate growth profiles for two different strains (model laboratory strain PAO1 and clinical isolate PA1054 from a hospital burns unit) in a range of organic acids at different concentrations and pH, with a high level of replication for a total of 162,960 data points. We then compared two different modeling approaches for the interpretation of this time-resolved dataset: parametric logistic regression (with or without a component to include lag phase) vs. non-parametric Gaussian process (GP) regression. Because GP makes no prior assumptions about the nature of the growth, this method proved to be superior in cases where growth did not follow a standard sigmoid functional form, as is common when bacteria grow under stress. Acetic, propionic and butyric acids were all more detrimental to growth than the other acids tested, and although PA1054 grew better than PAO1 under non-stress conditions, this difference largely disappeared as the levels of stress increased. As expected from knowledge of how organic acids behave, their effect was significantly enhanced in combination with low pH, with this interaction being greatest in the case of propionic acid. Our approach lends itself to the characterization of combinatorial interactions between stressors, especially in cases where their impacts on growth render logistic growth models unsuitable

correction novel chemical probes for the investigation of nonribosomal peptide assembly

Correction for 'Novel chemical probes for the investigation of nonribosomal peptide assembly' by Y. T. Candace Ho et al., Chem. Commun., 2017, 53, 7088–7091

Human Antibodies that Slow Erythrocyte Invasion Potentiate Malaria-Neutralizing Antibodies.

The Plasmodium falciparum reticulocyte-binding protein homolog 5 (PfRH5) is the leading target for next-generation vaccines against the disease-causing blood-stage of malaria. However, little is known about how human antibodies confer functional immunity against this antigen. We isolated a panel of human monoclonal antibodies (mAbs) against PfRH5 from peripheral blood B cells from vaccinees in the first clinical trial of a PfRH5-based vaccine. We identified a subset of mAbs with neutralizing activity that bind to three distinct sites and another subset of mAbs that are non-functional, or even antagonistic to neutralizing antibodies. We also identify the epitope of a novel group of non-neutralizing antibodies that significantly reduce the speed of red blood cell invasion by the merozoite, thereby potentiating the effect of all neutralizing PfRH5 antibodies as well as synergizing with antibodies targeting other malaria invasion proteins. Our results provide a roadmap for structure-guided vaccine development to maximize antibody efficacy against blood-stage malaria. Copyright © 2019 The Author(s). Published by Elsevier Inc. All rights reserved

Mapping the Transcriptional and Fitness Landscapes of a Pathogenic E. coli Strain: The Effects of Organic Acid Stress under Aerobic and Anaerobic Conditions

Several methods are available to probe cellular responses to external stresses at the whole genome level. RNAseq can be used to measure changes in expression of all genes following exposure to stress, but gives no information about the contribution of these genes to an organism&rsquo;s ability to survive the stress. The relative contribution of each non-essential gene in the genome to the fitness of the organism under stress can be obtained using methods that use sequencing to estimate the frequencies of members of a dense transposon library grown under different conditions, for example by transposon-directed insertion sequencing (TraDIS). These two methods thus probe different aspects of the underlying biology of the organism. We were interested to determine the extent to which the data from these two methods converge on related genes and pathways. To do this, we looked at a combination of biologically meaningful stresses. The human gut contains different organic short-chain fatty acids (SCFAs) produced by fermentation of carbon compounds, and Escherichia coli is exposed to these in its passage through the gut. Their effect is likely to depend on both the ambient pH and the level of oxygen present. We, therefore, generated RNAseq and TraDIS data on a uropathogenic E. coli strain grown at either pH 7 or pH 5.5 in the presence or absence of three SCFAs (acetic, propionic and butyric), either aerobically or anaerobically. Our analysis identifies both known and novel pathways as being likely to be important under these conditions. There is no simple correlation between gene expression and fitness, but we found a significant overlap in KEGG pathways that are predicted to be enriched following analysis of the data from the two methods, and the majority of these showed a fitness signature that would be predicted from the gene expression data, assuming expression to be adaptive. Genes which are not in the E. coli core genome were found to be particularly likely to show a positive correlation between level of expression and contribution to fitness

A Bayesian non-parametric mixed-effects model of microbial growth curves

Substantive changes in gene expression, metabolism, and the proteome are manifested in overall changes in microbial population growth. Quantifying how microbes grow is therefore fundamental to areas such as genetics, bioengineering, and food safety. Traditional parametric growth curve models capture the population growth behavior through a set of summarizing parameters. However, estimation of these parameters from data is confounded by random effects such as experimental variability, batch effects or differences in experimental material. A systematic statistical method to identify and correct for such confounding effects in population growth data is not currently available. Further, our previous work has demonstrated that parametric models are insufficient to explain and predict microbial response under non-standard growth conditions. Here we develop a hierarchical Bayesian non-parametric model of population growth that identifies the latent growth behavior and response to perturbation, while simultaneously correcting for random effects in the data. This model enables more accurate estimates of the biological effect of interest, while better accounting for the uncertainty due to technical variation. Additionally, modeling hierarchical variation provides estimates of the relative impact of various confounding effects on measured population growth

Design of Methylprednisolone Biodegradable Microspheres Intended for Intra-articular Administration

This study aimed to design methyprednisolone (MP)-loaded poly(d,l lactide-co-glycolide) (PLGA) microspheres (MS) intended for intra-articular administration. MP was encapsulated in four different types of PLGA by using an S/O/W technique. The effects of β-irradiation at the dose of 25 kGy were evaluated on the chemical and physicochemical properties of MS and the drug release profiles. The S/O/W technique with hydroxypropylmethylcellulose (HPMC) as surfactant allowed obtaining MS in the tolerability size (7–50 µm) for intra-articular administration. The MP encapsulation efficiency ranged 56–60%. HPMC traces were evidenced in the loaded and placebo MS by attenuated total reflectance Fourier transform infrared spectroscopy. MS made of the capped PLGA DL5050 2M (MS 2M) and uncapped PLGA DL5050 3A (MS 3A) prolonged the release of MP over a 2- to 3-month period with a triphasic (burst release–dormant period–second release pulse) and biphasic release pattern, respectively. The β-irradiation did not significantly alter the morphology, chemical, and physicochemical properties of MS. The only variation was evidenced in the drug release for MS 2M in term of shorting of the dormant period. The minimal variations in the properties of irradiated PLGA MS, which are in disagreement with literature data, may be attributed to a radioprotecting effect exerted by HPMC