A Bayesian model of acquisition and clearance of bacterial colonization incorporating within-host variation

Model-based inference of a plant-specific dual role for HOPS in regulating guard cell vacuole fusion

Stomata are the pores on a leaf surface that regulate gas exchange. Each stoma consists of two guard cells whose movements regulate pore opening and thereby control CO2 fixation and water loss. Guard cell movements depend in part on the remodeling of vacuoles, which have been observed to change from a highly fragmented state to a fused morphology during stomata opening. This change in morphology requires a membrane fusion mechanism that responds rapidly to environmental signals, allowing plants to respond to diurnal and stress cues. With guard cell vacuoles being both large and responsive to external signals, stomata represent a unique system in which to delineate mechanisms of membrane fusion. Fusion of vacuole membranes is a highly conserved process in eukaryotes, with key roles played by two multi-subunit complexes: HOPS (homotypic fusion and vacuolar protein sorting) and SNARE (soluble NSF attachment protein receptor). HOPS is a vacuole tethering factor that is thought to chaperone SNAREs from apposing vacuole membranes into a fusion-competent complex capable of rearranging membranes. To resolve a counter-intuitive observation regarding the role of HOPS in regulating plant vacuole morphology, we derived a quantitative model of vacuole fusion dynamics and used it to generate testable predictions about HOPS-SNARE interactions. We derived our model by applying simulation-based inference to integrate prior knowledge about molecular interactions with limited, qualitative observations of emergent vacuole phenotypes. By constraining the model parameters to yield the emergent outcomes observed for stoma opening - as induced by two distinct chemical treatments - we predicted a dual role for HOPS and identified a stalled form of the SNARE complex that differs from phenomena reported in yeast. We predict that HOPS has contradictory actions at different points in the fusion signaling pathway, promoting the formation of SNARE complexes, but limiting their activity.

Bayesian modeling of the impact of antibiotic resistance on the efficiency of MRSA decolonization

Methicillin-resistant Staphylococcus aureus (MRSA) is a major cause of morbidity and mortality. Colonization by MRSA increases the risk of infection and transmission, underscoring the importance of decolonization efforts. However, success of these decolonization protocols varies, raising the possibility that some MRSA strains may be more persistent than others. Here, we studied how the persistence of MRSA colonization correlates with genomic presence of antibiotic resistance genes. Our analysis using a Bayesian mixed effects survival model found that genetic determinants of high-level resistance to mupirocin was strongly associated with failure of the decolonization protocol. However, we did not see a similar effect with genetic resistance to chlorhexidine or other antibiotics. Including strain-specific random effects improved the predictive performance, indicating that some strain characteristics other than resistance also contributed to persistence. Study subject-specific random effects did not improve the model. Our results highlight the need to consider the properties of the colonizing MRSA strain when deciding which treatments to include in the decolonization protocol.

On predictive inference for intractable models via approximate Bayesian computation

Approximate Bayesian computation (ABC) is commonly used for parameter estimation and model comparison for intractable simulator-based statistical models whose likelihood function cannot be evaluated. In this paper we instead investigate the feasibility of ABC as a generic approximate method for predictive inference, in particular, for computing the posterior predictive distribution of future observations or missing data of interest. We consider three complementary ABC approaches for this goal, each based on different assumptions regarding which predictive density of the intractable model can be sampled from. The case where only simulation from the joint density of the observed and future data given the model parameters can be used for inference is given particular attention and it is shown that the ideal summary statistic in this setting is minimal predictive sufficient instead of merely minimal sufficient (in the ordinary sense). An ABC prediction approach that takes advantage of a certain latent variable representation is also investigated. We additionally show how common ABC sampling algorithms can be used in the predictive settings considered. Our main results are first illustrated by using simple time-series models that facilitate analytical treatment, and later by using two common intractable dynamic models.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11222-022-10163-6.

Genomic Epidemiology Suggests Community Origins of Healthcare-Associated USA300 Methicillin-Resistant Staphylococcus aureus

BACKGROUND

Hospital-onset (HO) methicillin-resistant Staphylococcus aureus (MRSA) infections have declined over the past decade due to infection control strategies; community-onset (CO) and healthcare-associated community-onset (HACO) MRSA, particularly USA300, has declined less. We examined the role of community strains to explain the difference.

METHODS

We performed whole-genome sequencing (WGS) on MRSA clinical isolates from Cook County Health patients during 2011-2014. We defined infections as CO, HO, or HACO epidemiologically. We integrated genomic, community exposure, and statewide hospital discharge data to infer MRSA origin.

RESULTS

Among 1020 individuals with available WGS, most were USA300 wound infections (580 CO, 143 HO, 297 HACO). USA300 HO, CO, and HACO infections were intermixed on the USA300 phylogeny, consistent with common strains circulating across community and healthcare settings. Community exposures (eg, substance abuse, incarceration, homelessness) were associated with HACO and HO infections, and genetically linked individuals from both groups had little overlap in healthcare facilities, supporting community origins. Most repeat infections-over months to years-occurred in individuals persistently carrying their own strains. These individuals were more likely to have genetic linkages, suggesting a role of persistent colonization in transmission.

CONCLUSIONS

Efforts to reduce presumed nosocomial USA300 spread may require understanding and controlling community sources and transmission networks, particularly for repeat infections.

Genomic Analysis of Community Transmission Networks for MRSA among Females Entering a Large Inner-City Jail

Background

It is unclear if there are differences in MRSA risk between sexes in high-risk populations.

Methods

Females incarcerated at the Cook County Jail were enrolled within 72 hours of intake. Surveillance cultures (nares, throat, groin) were collected to determine prevalence of MRSA colonization. A survey was administered to identify colonization predictors. Univariate and multivariate analyses were performed to identify predictors of colonization at intake. Genomic sequencing was performed on MRSA colonization and archived clinical isolates.

Results

250 women were enrolled (70% AA, 15% Hispanic) with 70% previously in jail. The prevalence of MRSA colonization at intake was 20%, with 42% of those colonized solely in the throat or groin. Univariate predictors of MRSA colonization at entrance were illicit drug use, unstable housing, engaging in anal sex, recent exchange of sex for drugs/money, and a higher number of recent sexual partners. With multivariate adjustment for race/ethnicity, use of needles for illicit drugs was a significant predictor of MRSA. Use of illicit drugs was also associated with inclusion in a genomic cluster.

Nares colonization was significantly associated with not being in a genomic cluster (18.8% vs 78.6%, p<0.001), whereas exclusive extra-nasal colonization was associated (OR 15.89, p<0.001).

Conclusion

We found that a high proportion (20%) of females entered jail colonized with MRSA, suggesting that previously reported sex disparities of a lower risk in women may not apply to high-risk populations. Our findings suggest high-risk activities or venues in the community for MRSA, with potential for directing sex-specific interventions.

Solving the puzzle of Fe homeostasis by integrating molecular, mathematical, and societal models

To ensure optimal utilization and bioavailability, iron uptake, transport, subcellular localization, and assimilation are tightly regulated in plants. Herein, we examine recent advances in our understanding of cellular responses to Fe deficiency. We then use intracellular mechanisms of Fe homeostasis to discuss how formalizing cell biology knowledge via a mathematical model can advance discovery even when quantitative data is limited. Using simulation-based inference to identify plausible systems mechanisms that conform to known emergent phenotypes can yield novel, testable hypotheses to guide targeted experiments. However, this approach relies on the accurate encoding of domain-expert knowledge in exploratory mathematical models. We argue that this would be facilitated by fostering more "systems thinking" life scientists and that diversifying your research team may be a practical path to achieve that goal.