Lipopolysaccharide structure modulates cationic biocide susceptibility and crystalline biofilm formation in Proteus mirabilis.

Chlorhexidine (CHD) is a cationic biocide used ubiquitously in healthcare settings. Proteus mirabilis, an important pathogen of the catheterized urinary tract, and isolates of this species are often described as "resistant" to CHD-containing products used for catheter infection control. To identify the mechanisms underlying reduced CHD susceptibility in P. mirabilis, we subjected the CHD tolerant clinical isolate RS47 to random transposon mutagenesis and screened for mutants with reduced CHD minimum inhibitory concentrations (MICs). One mutant recovered from these screens (designated RS47-2) exhibited ~ 8-fold reduction in CHD MIC. Complete genome sequencing of RS47-2 showed a single mini-Tn5 insert in the waaC gene involved in lipopolysaccharide (LPS) inner core biosynthesis. Phenotypic screening of RS47-2 revealed a significant increase in cell surface hydrophobicity and serum susceptibility compared to the wildtype, and confirmed defects in LPS production congruent with waaC inactivation. Disruption of waaC was also associated with increased susceptibility to a range of other cationic biocides but did not affect susceptibility to antibiotics tested. Complementation studies showed that repression of smvA efflux activity in RS47-2 further increased susceptibility to CHD and other cationic biocides, reducing CHD MICs to values comparable with the most CHD susceptible isolates characterized. The formation of crystalline biofilms and blockage of urethral catheters was also significantly attenuated in RS47-2. Taken together, these data show that aspects of LPS structure and upregulation of the smvA efflux system function in synergy to modulate susceptibility to CHD and other cationic biocides, and that LPS structure is also an important factor in P. mirabilis crystalline biofilm formation.

Streamlined variational inference for higher level group-specific curve models.

A two-level group-specific curve model is such that the mean response of each member of a group is a separate smooth function of a predictor of interest. The three-level extension is such that one grouping variable is nested within another one, and higher level extensions are analogous. Streamlined variational inference for higher level group-specific curve models is a challenging problem. We confront it by systematically working through two-level and then three-level cases and making use of the higher level sparse matrix infrastructure laid down in Nolan and Wand (2019). A motivation is analysis of data from ultrasound technology for which three-level group-specific curve models are appropriate. Whilst extension to the number of levels exceeding three is not covered explicitly, the pattern established by our systematic approach sheds light on what is required for even higher level group-specific curve models.

Fast and Accurate Binary Response Mixed Model Analysis Via Expectation Propagation.

Expectation propagation is a general prescription for approximation of integrals in statistical inference problems. Its literature is mainly concerned with Bayesian inference scenarios. However, expectation propagation can also be used to approximate integrals arising in frequentist statistical inference. We focus on likelihood-based inference for binary response mixed models and show that fast and accurate quadrature-free inference can be realized for the probit link case with multivariate random effects and higher levels of nesting. The approach is supported by asymptotic calculations in which expectation propagation is seen to provide consistent estimation of the exact likelihood surface. Numerical studies reveal the availability of fast, highly accurate and scalable methodology for binary mixed model analysis. Supplementary materials for this article are available online.

De-repression of the smvA efflux system arises in clinical isolates of Proteus mirabilis and reduces susceptibility to chlorhexidine and other biocides.

Proteus mirabilis is a common pathogen of the catheterised urinary tract and often described as intrinsically resistant to the biocide chlorhexidine (CHD). Here we demonstrate that de-repression of the smvA efflux system has occurred in clinical isolates of P. mirabilis and reduces susceptibility to CHD and other cationic biocides. Compared to other isolates examined, P. mirabilis RS47 exhibited a significantly higher CHD MIC (≥512 µg/ml) and significantly greater expression of smvA. Comparison of the RS47 smvA and cognate smvR repressor with sequences from other isolates, indicated that RS47 encodes an inactivated smvR. Complementation of RS47 with a functional smvR from isolate RS50a (which exhibited the lowest smvA expression and lowest CHD MIC) reduced smvA expression by ∼59-fold, and markedly lowered the MIC of CHD and other cationic biocides. Although complementation of RS47 did not reduce MICs to concentrations observed in isolate RS50a, the significantly lower polymyxin B MIC of RS50a indicated that differences in LPS structure are also a factor in P. mirabilis CHD susceptibility. To determine if exposure to CHD can select for mutations in smvR, clinical isolates with the lowest CHD MICs were adapted to grow at increasing concentrations of CHD up to 512 µg/ml. Analysis of the smvR in adapted populations indicated that mutations predicted to inactivate smvR occurred following CHD exposure in some isolates. Collectively, our data show that smvA de-repression contributes to reduced biocide susceptibility in P. mirabilis, but differences in LPS structure between strains are also likely to be an important factor.

Pseudomonas aeruginosa adapts to octenidine in the laboratory and a simulated clinical setting, leading to increased tolerance to chlorhexidine and other biocides.

BACKGROUND: Octenidine is frequently used for infection prevention in neonatal and burn intensive care units, where Pseudomonas aeruginosa has caused nosocomial outbreaks. AIM: To investigate the efficacy and impact of using octenidine against P. aeruginosa. METHODS: Seven clinical isolates of P. aeruginosa were exposed to increasing concentrations of octenidine over several days. Fitness, minimum bactericidal concentrations after 1 min, 5 min and 24 h, and minimum inhibitory concentrations (MICs) of a variety of antimicrobials were measured for the parental and octenidine-adapted P. aeruginosa strains. Octenidine and chlorhexidine MICs of a population of P. aeruginosa isolated from a hospital drain trap, exposed to a diluted octenidine formulation four times daily for three months, were also tested. FINDINGS: Some planktonic cultures of P. aeruginosa survived >50% of the working concentration of an in-use octenidine formulation at the recommended exposure time. Seven strains of P. aeruginosa stably adapted following continuous exposure to increasing concentrations of octenidine. Adaptation increased tolerance to octenidine formulations and chlorhexidine up to 32-fold. In one strain, it also led to increased MICs of antipseudomonal drugs. Subsequent to continuous octenidine exposure of a multi-species community in a simulated clinical setting, up to eight-fold increased tolerance to octenidine and chlorhexidine of P. aeruginosa was also found, which was lost upon removal of octenidine. CONCLUSION: Incorrect use of octenidine formulations may lead to inadequate decontamination, and even increased tolerance of P. aeruginosa to octenidine, with resulting cross-resistance to other biocides.

Growth media and assay plate material can impact on the effectiveness of cationic biocides and antibiotics against different bacterial species.

The effectiveness of several cationic disinfectants as well as colistin and polymyxin B were assessed under different growth conditions against Staphylococcus aureus, Escherichia coli and Pseudomonas aeruginosa strains. These conditions included different media (MH1, MH2, TSB and LB) and plate material (polypropylene and polystyrene). Results showed that Minimum inhibitory and bactericidal concentrations (MIC/MBC) values of colistin and polymyxin B were significantly lower on polypropylene plates when compared to polystyrene plates regardless of media used. There were also differences in MIC/MBC values to certain biocides e.g. chlorhexidine and octenidine particularly for S. aureus and E. coli strains, with polypropylene again showing lower values. Other biocides appear to be mostly unaffected by plate type. Whether biocide efficacy was altered by media composition was organism dependent with S. aureus and E. coli more affected than P. aeruginosa. Lower MIC values were more commonly associated with MH2 media and higher MIC values with TSB media for both polypropylene and polystyrene plates, although there were exceptions. Results obtained for standard strains were, in general, indicative for other S. aureus, E. coli and P. aeruginosa strains tested. This study demonstrates the importance of media composition and plate material on biocide effectiveness and highlights the need for optimized disinfectant testing methods. SIGNIFICANCE AND IMPACT OF THE STUDY: There are an increasing number of reports of bacterial strains that are multi-drug resistant. The use of biocides as part of infection control is crucial in helping to combat the spread of these particular strains. Unlike for antibiotics, there are few standardized measuring techniques to understand if an isolate has become more resistant to biocides. This study demonstrates the importance of media composition and plate material on variation and reporting of susceptibility of several bacterial species to specific cationic biocides. It is a useful comparison study to highlight the need to standardize biocide susceptibility testing.

Varying activity of chlorhexidine-based disinfectants against Klebsiella pneumoniae clinical isolates and adapted strains.

BACKGROUND: Control of multi-drug-resistant (MDR) organisms relies increasingly on the use of biocides, including chlorhexidine, to limit the risk of infection. The concentration and formulation of chlorhexidine can vary hugely between products. AIM: To establish the activity of chlorhexidine and in-use chlorhexidine formulations against 14 clinical Klebsiella pneumoniae strains isolated before and since the use of chlorhexidine became routine, and strains that have adapted following sublethal chlorhexidine exposure. METHODS: Minimum inhibitory concentrations (MICs) and minimum bactericidal concentrations (MBCs) of five chlorhexidine-containing formulations were measured at 5min, 15min, 30min and 24h for the panel of K. pneumoniae strains. FINDINGS: After 5min, MBCs of five formulations varied from 0.006 to >50% working concentration (WC) or from 78 to 2500µg/mL chlorhexidine. For one formulation, MBCs were >50% WC for five of the 14 strains, and for another formulation, four of the 14 strains could resist 25% WC. NCTC 13368 was consistently most tolerant to chlorhexidine, whereas the strains isolated before the use of chlorhexidine became routine were more sensitive. One pre-chlorhexidine era and five modern strains increased MICs up to 16-fold following exposure to sublethal concentrations of chlorhexidine. A hand disinfectant with MBCs of 0.39% WC for all six of the wild-type strains, had MBCs of 50% WC for the chlorhexidine-adapted strains. CONCLUSION: Not all chlorhexidine formulations kill MDR K. pneumoniae after the recommended exposure time. Activity, especially against chlorhexidine-adapted strains, depends on additional ingredients. Careful formulation of chlorhexidine products is therefore important to maintain and enhance the activity of chlorhexidine products, and avoid potential breakdown in infection control.

Establishment of a multi-species biofilm model to evaluate chlorhexidine efficacy.

BACKGROUND: Chronic infections, for example, diabetic foot ulcers, have a large impact in terms of patient morbidity and mortality. These wounds are characterized by complex polymicrobial communities of bacteria, which may include a number of difficult-to-eradicate multidrug-resistant pathogens. AIM: To establish a multi-species biofilm model to test the efficacy of chlorhexidine and chlorhexidine-containing formulas in eradication of polymicrobial biofilms. METHODS: A Centers for Disease Control and Prevention bioreactor was used to establish a multi-species biofilm incorporating Klebsiella pneumoniae, Pseudomonas aeruginosa, Staphylococcus aureus and Enterococcus faecalis with equal numbers of each pathogen. This model was used to test the effectiveness of chlorhexidine at controlling the pre-formed biofilm. FINDINGS: Chlorhexidine digluconate (CHD) was added to the bioreactor at a range of concentrations. K. pneumoniae and P. aeruginosa survived within multi-species biofilms, up to and including 4% CHD, whereas S. aureus was reduced to below the level of detection at 1%. Wiping the biofilm-containing coupons from the bioreactor with chlorhexidine-containing medical wipes resulted in >3 to <4log10 reduction after 24h, for all species. When the coupons were embedded in a simulated wound bed, formed in an agar plate, CHD-containing medical dressings completely eliminated S. aureus (>8log10 reduction), but had minimal effect (<3log10) against the other species tested. CONCLUSION: The study demonstrates that the effectiveness of chlorhexidine may be limited in settings where it is required to act on multi-species biofilms. This may compromise the ability of chlorhexidine to control the infection and spread of these pathogens.

Evaluation of the effectiveness of hydrogen-peroxide-based disinfectants on biofilms formed by Gram-negative pathogens.

BACKGROUND: Hydrogen peroxide (H2O2)-based disinfectants are widely used in a number of different healthcare settings to control bacterial colonization and contamination, and reduce the risk of cross-infection. Efficacy tests of these formulations are performed on planktonic cultures, although it is well known that biofilms are the dominant form of bacterial contamination and more difficult to eradicate. AIM: To determine if the biofilms of three different Gram-negative pathogens associated with multi-drug-resistant phenotypes can be eradicated effectively using different H2O2-based disinfectants. METHODS: Planktonic cultures and single-species 24-h biofilms of seven strains of Acinetobacter spp., seven strains of Klebsiella pneumoniae and seven strains of Pseudomonas aeruginosa, including clinical isolates, were exposed to working concentrations of H2O2 and H2O2-based formulations for 1 min to 24h. Survival was monitored. FINDINGS: The levels of susceptibility of planktonic cultures to unformulated and formulated H2O2 were similar in all organisms and strains tested, with minimum inhibitory concentrations ranging from 0.5 to 20mM H2O2. However, biofilms showed up to 266-fold less sensitivity to H2O2 and its formulations. The level of reduced susceptibility correlated with the strain's propensity to form biofilm, and differed between species. The two formulations with additional acidic active ingredients performed better at short exposure times, whereas ethanol-containing products required longer exposure times to be effective. CONCLUSION: Biofilms of a significant number of clinical isolates of multi-drug-resistant nosocomial pathogens are not susceptible to working concentrations of several H2O2-based disinfectants. This may compromise the ability to control these pathogens with such products.

Marginal longitudinal semiparametric regression via penalized splines.

We study the marginal longitudinal nonparametric regression problem and some of its semiparametric extensions. We point out that, while several elaborate proposals for efficient estimation have been proposed, a relative simple and straightforward one, based on penalized splines, has not. After describing our approach, we then explain how Gibbs sampling and the BUGS software can be used to achieve quick and effective implementation. Illustrations are provided for nonparametric regression and additive models.

Highest density difference region estimation with application to flow cytometric data.

Motivated by the needs of scientists using flow cytometry, we study the problem of estimating the region where two multivariate samples differ in density. We call this problem highest density difference region estimation and recognise it as a two-sample analogue of highest density region or excess set estimation. Flow cytometry samples are typically in the order of 10,000 and 100,000 and with dimension ranging from about 3 to 20. The industry standard for the problem being studied is called Frequency Difference Gating, due to Roederer and Hardy (2001). After couching the problem in a formal statistical framework we devise an alternative estimator that draws upon recent statistical developments such as patient rule induction methods. Improved performance is illustrated in simulations. While motivated by flow cytometry, the methodology is suitable for general multivariate random samples where density difference regions are of interest.

Automation in high-content flow cytometry screening.

High-content flow cytometric screening (FC-HCS) is a 21st Century technology that combines robotic fluid handling, flow cytometric instrumentation, and bioinformatics software, so that relatively large numbers of flow cytometric samples can be processed and analysed in a short period of time. We revisit a recent application of FC-HCS to the problem of cellular signature definition for acute graft-versus-host-disease. Our focus is on automation of the data processing steps using recent advances in statistical methodology. We demonstrate that effective results, on par with those obtained via manual processing, can be achieved using our automatic techniques. Such automation of FC-HCS has the potential to drastically improve diagnosis and biomarker identification.

Semiparametric regression during 2003-2007.

Semiparametric regression is a fusion between parametric regression and nonparametric regression that integrates low-rank penalized splines, mixed model and hierarchical Bayesian methodology - thus allowing more streamlined handling of longitudinal and spatial correlation. We review progress in the field over the five-year period between 2003 and 2007. We find semiparametric regression to be a vibrant field with substantial involvement and activity, continual enhancement and widespread application.

Streamlined variance calculations for semiparametric mixed models.

Semiparametric mixed model analysis benefits from variability estimates such as standard errors of effect estimates and variability bars to accompany curve estimates. We show how the underlying variance calculations can be done extremely efficiently compared with the direct naïve approach. These streamlined calculations are linear in the number of subjects, representing a two orders of magnitude improvement.

Loss of mammary epithelial prolactin receptor delays tumor formation by reducing cell proliferation in low-grade preinvasive lesions.

Top quartile serum prolactin levels confer a twofold increase in the relative risk of developing breast cancer. Prolactin exerts this effect at an ill defined point in the carcinogenic process, via mechanisms involving direct action via prolactin receptors within mammary epithelium and/or indirect action through regulation of other hormones such as estrogen and progesterone. We have addressed these questions by examining mammary carcinogenesis in transplants of mouse mammary epithelium expressing the SV40T oncogene, with or without the prolactin receptor, using host animals with a normal endocrine system. In prolactin receptor knockout transplants the area of neoplasia was significantly smaller (7 versus 17%; P < 0.001 at 22 weeks and 7 versus 14%; P = 0.009 at 32 weeks). Low-grade neoplastic lesions displayed reduced BrdU incorporation rate (11.3 versus 17% P = 0.003) but no change in apoptosis rate. Tumor latency increased (289 days versus 236 days, P < 0.001). Tumor frequency, growth rate, morphology, cell proliferation and apoptosis were not altered. Thus, prolactin acts directly on the mammary epithelial cells to increase cell proliferation in preinvasive lesions, resulting in more neoplasia and acceleration of the transition to invasive carcinoma. Targeting of mammary prolactin signaling thus provides a strategy to prevent the early progression of neoplasia to invasive carcinoma.

Multilevel modelling of the incidence of visceral leishmaniasis in Teresina, Brazil.

Epidemics of visceral leishmaniasis (VL) in major Brazilian cities are new phenomena since 1980. As determinants of transmission in urban settings probably operate at different geographic scales, and information is not available for each scale, a multilevel approach was used to examine the effect of canine infection and environmental and socio-economic factors on the spatial variability of incidence rates of VL in the city of Teresina. Details on an outbreak of greater than 1200 cases of VL in Teresina during 1993-1996 were available at two hierarchical levels: census tracts (socio-economic characteristics, incidence rates of human VL) and districts, which encompass census tracts (prevalence of canine infection). Remotely sensed data obtained by satellite generated environmental information at both levels. Data from census tracts and districts were analysed simultaneously by multilevel modelling. Poor socio-economic conditions and increased vegetation were associated with a high incidence of human VL. Increasing prevalence of canine infection also predicted a high incidence of human VL, as did high prevalence of canine infection before and during the epidemic. Poor socio-economic conditions had an amplifying effect on the association between canine infection and the incidence of human VL. Focusing interventions on areas with characteristics identified by multilevel analysis could be a cost-effective strategy for controlling VL. Because risk factors for infectious diseases operate simultaneously at several levels and ecological data usually are available at different geographical scales, multilevel modelling is a valuable tool for epidemiological investigation of disease transmission.

Additive models for geo-referenced failure time data.

Asthma researchers have found some evidence that geographical variations in susceptibility to asthma could reflect the effect of community level factors such as exposure to violence. Our methodology was motivated by a study of age at onset of asthma among children of inner-city neighbourhoods in East Boston. Cox's proportional hazards model was not appropriate since there was not enough information about the nature of geographical variations so as to impose a parametric relationship. In addition, some of the known risk factors were believed to have non-linear log-hazard ratios. We extend the geoadditive models of Kamman and Wand to the case where the outcome measure is a possibly censored time to event. We reduce the problem to one of fitting a Poisson mixed model by using Poisson approximations in conjunction with a mixed model formulation of generalized additive modelling. Our method allows for low-rank additive modelling, provides likelihood-based estimation of all parameters including the amount of smoothing and can be implemented using standard software. We illustrate our method on the East Boston data.

Detecting antibodies with similar reactivity patterns in the HLDA8 blind panel of flow cytometry data.

The blind panel collected for the 8th Human Leucocyte Differentiation Antigens Workshop (HLDA8; ) included 49 antibodies of known CD specificities and 76 antibodies of unknown specificity. We have identified groups of antibodies showing similar patterns of reactivity that need to be investigated by biochemical methods to evaluate whether the antibodies within these groups are reacting with the same molecule. Our approach to data analysis was based on the work of Salganik et al. (in press) [Salganik, M.P., Milford E.L., Hardie D.L., Shaw, S., Wand, M.P., in press. Classifying antibodies using flow cytometry data: class prediction and class discovery. Biometrical Journal].

Simple fitting of subject-specific curves for longitudinal data.

We present a simple semiparametric model for fitting subject-specific curves for longitudinal data. Individual curves are modelled as penalized splines with random coefficients. This model has a mixed model representation, and it is easily implemented in standard statistical software. We conduct an analysis of the long-term effect of radiation therapy on the height of children suffering from acute lymphoblastic leukaemia using penalized splines in the framework of semiparametric mixed effects models. The analysis revealed significant differences between therapies and showed that the growth rate of girls in the study cannot be fully explained by the group-average curve and that individual curves are necessary to reflect the individual response to treatment. We also show how to implement these models in S-PLUS and R in the appendix.

A local likelihood proportional hazards model for interval censored data.

We discuss the use of local likelihood methods to fit proportional hazards regression models to right and interval censored data. The assumed model allows for an arbitrary, smoothed baseline hazard on which a vector of covariates operates in a proportional manner, and thus produces an interpretable baseline hazard function along with estimates of global covariate effects. For estimation, we extend the modified EM algorithm suggested by Betensky, Lindsey, Ryan and Wand. We illustrate the method with data on times to deterioration of breast cosmeses and HIV-1 infection rates among haemophiliacs.