ASU Scholarship Showcase

Recent studies suggest a role for the microbiota in autism spectrum disorders (ASD), potentially arising from their role in modulating the immune system and gastrointestinal (GI) function or from gut–brain interactions dependent or independent from the immune system. GI problems such as chronic constipation and/or diarrhea are common in children with ASD, and significantly worsen their behavior and their quality of life. Here we first summarize previously published data supporting that GI dysfunction is common in individuals with ASD and the role of the microbiota in ASD. Second, by comparing with other publically available microbiome datasets, we provide some evidence that the shifted microbiota can be a result of westernization and that this shift could also be framing an altered immune system. Third, we explore the possibility that gut–brain interactions could also be a direct result of microbially produced metabolites.

There is a growing body of scientific evidence that the health of the microbiome (the trillions of microbes that inhabit the human host) plays an important role in maintaining the health of the host and that disruptions in the microbiome may play a role in certain disease processes. An increasing number of research studies have provided evidence that the composition of the gut (enteric) microbiome (GM) in at least a subset of individuals with autism spectrum disorder (ASD) deviates from what is usually observed in typically developing individuals. There are several lines of research that suggest that specific changes in the GM could be causative or highly associated with driving core and associated ASD symptoms, pathology, and comorbidities which include gastrointestinal symptoms, although it is also a possibility that these changes, in whole or in part, could be a consequence of underlying pathophysiological features associated with ASD. However, if the GM truly plays a causative role in ASD, then the manipulation of the GM could potentially be leveraged as a therapeutic approach to improve ASD symptoms and/or comorbidities, including gastrointestinal symptoms.

One approach to investigating this possibility in greater detail includes a highly controlled clinical trial in which the GM is systematically manipulated to determine its significance in individuals with ASD. To outline the important issues that would be required to design such a study, a group of clinicians, research scientists, and parents of children with ASD participated in an interdisciplinary daylong workshop as an extension of the 1st International Symposium on the Microbiome in Health and Disease with a Special Focus on Autism (www.microbiome-autism.com). The group considered several aspects of designing clinical studies, including clinical trial design, treatments that could potentially be used in a clinical trial, appropriate ASD participants for the clinical trial, behavioral and cognitive assessments, important biomarkers, safety concerns, and ethical considerations. Overall, the group not only felt that this was a promising area of research for the ASD population and a promising avenue for potential treatment but also felt that further basic and translational research was needed to clarify the clinical utility of such treatments and to elucidate possible mechanisms responsible for a clinical response, so that new treatments and approaches may be discovered and/or fostered in the future.

Dental microwear has been shown to reflect diet in a broad variety of fossil mammals. Recent studies have suggested that differences in microwear texture attributes between samples may also reflect environmental abrasive loads. Here, we examine dental microwear textures on the incisors of shrews, both to evaluate this idea and to expand the extant baseline to include Soricidae. Specimens were chosen to sample a broad range of environments, semi-desert to rainforest. Species examined were all largely insectivorous, but some are reported to supplement their diets with vertebrate tissues and others with plant matter. Results indicate subtle but significant differences between samples grouped by both diet independent of environment and environment independent of diet. Subtle diet differences were more evident in microwear texture variation considered by habitat (i.e., grassland). These results suggest that while environment does not swamp the diet signal in shrew incisor microwear, studies can benefit from control of habitat type.

We develop a general framework to analyze the controllability of multiplex networks using multiple-relation networks and multiple-layer networks with interlayer couplings as two classes of prototypical systems. In the former, networks associated with different physical variables share the same set of nodes and in the latter, diffusion processes take place. We find that, for a multiple-relation network, a layer exists that dominantly determines the controllability of the whole network and, for a multiple-layer network, a small fraction of the interconnections can enhance the controllability remarkably. Our theory is generally applicable to other types of multiplex networks as well, leading to significant insights into the control of complex network systems with diverse structures and interacting patterns.

Collective behaviors in social insect societies often emerge from simple local rules. However, little is known about how these behaviors are dynamically regulated in response to environmental changes. Here, we use a compartmental modeling approach to identify factors that allow harvester ant colonies to regulate collective foraging activity in response to their environment. We propose a set of differential equations describing the dynamics of: (1) available foragers inside the nest, (2) active foragers outside the nest, and (3) successful returning foragers, to understand how colony-specific parameters, such as baseline number of foragers, interactions among foragers, food discovery rates, successful forager return rates, and foraging duration might influence collective foraging dynamics, while maintaining functional robustness to perturbations. Our analysis indicates that the model can undergo a forward (transcritical) bifurcation or a backward bifurcation depending on colony-specific parameters. In the former case, foraging activity persists when the average number of recruits per successful returning forager is larger than one. In the latter case, the backward bifurcation creates a region of bistability in which the size and fate of foraging activity depends on the distribution of the foraging workforce among the model׳s compartments. We validate the model with experimental data from harvester ants (Pogonomyrmex barbatus) and perform sensitivity analysis. Our model provides insights on how simple, local interactions can achieve an emergent and robust regulatory system of collective foraging activity in ant colonies.

Dehalococcoides mccartyi strains are of particular importance for bioremediation due to their unique capability of transforming perchloroethene (PCE) and trichloroethene (TCE) to non-toxic ethene, through the intermediates cis-dichloroethene (cis-DCE) and vinyl chloride (VC). Despite the widespread environmental distribution of Dehalococcoides, biostimulation sometimes fails to promote dechlorination beyond cis-DCE. In our study, microcosms established with garden soil and mangrove sediment also stalled at cis-DCE, albeit Dehalococcoides mccartyi containing the reductive dehalogenase genes tceA, vcrA and bvcA were detected in the soil/sediment inocula. Reductive dechlorination was not promoted beyond cis-DCE, even after multiple biostimulation events with fermentable substrates and a lengthy incubation.

However, transfers from microcosms stalled at cis-DCE yielded dechlorination to ethene with subsequent enrichment cultures containing up to 10⁹ Dehalococcoides mccartyi cells mL^-1. Proteobacterial classes which dominated the soil/sediment communities became undetectable in the enrichments, and methanogenic activity drastically decreased after the transfers. We hypothesized that biostimulation of Dehalococcoides in the cis-DCE-stalled microcosms was impeded by other microbes present at higher abundances than Dehalococcoides and utilizing terminal electron acceptors from the soil/sediment, hence, outcompeting Dehalococcoides for H₂. In support of this hypothesis, we show that garden soil and mangrove sediment microcosms bioaugmented with their respective cultures containing Dehalococcoides in high abundance were able to compete for H² for reductive dechlorination from one biostimulation event and produced ethene with no obvious stall. Overall, our results provide an alternate explanation to consolidate conflicting observations on the ubiquity of Dehalococcoides mccartyi and occasional stalling of dechlorination at cis-DCE; thus, bringing a new perspective to better assess biological potential of different environments and to understand microbial interactions governing bioremediation.

Background: Buffering to achieve pH control is crucial for successful trichloroethene (TCE) anaerobic bioremediation. Bicarbonate (HCO3−) is the natural buffer in groundwater and the buffer of choice in the laboratory and at contaminated sites undergoing biological treatment with organohalide respiring microorganisms. However, HCO3− also serves as the electron acceptor for hydrogenotrophic methanogens and hydrogenotrophic homoacetogens, two microbial groups competing with organohalide respirers for hydrogen (H2). We studied the effect of HCO3− as a buffering agent and the effect of HCO3−-consuming reactions in a range of concentrations (2.5-30 mM) with an initial pH of 7.5 in H2-fed TCE reductively dechlorinating communities containing Dehalococcoides, hydrogenotrophic methanogens, and hydrogenotrophic homoacetogens.

Results: Rate differences in TCE dechlorination were observed as a result of added varying HCO3− concentrations due to H2-fed electrons channeled towards methanogenesis and homoacetogenesis and pH increases (up to 8.7) from biological HCO3− consumption. Significantly faster dechlorination rates were noted at all HCO3− concentrations tested when the pH buffering was improved by providing 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES) as an additional buffer. Electron balances and quantitative PCR revealed that methanogenesis was the main electron sink when the initial HCO3− concentrations were 2.5 and 5 mM, while homoacetogenesis was the dominant process and sink when 10 and 30 mM HCO3− were provided initially.

Conclusions: Our study reveals that HCO3− is an important variable for bioremediation of chloroethenes as it has a prominent role as an electron acceptor for methanogenesis and homoacetogenesis. It also illustrates the changes in rates and extent of reductive dechlorination resulting from the combined effect of electron donor competition stimulated by HCO3− and the changes in pH exerted by methanogens and homoacetogens.

Background: Influenza viruses are a major cause of morbidity and mortality worldwide. Vaccination remains a powerful tool for preventing or mitigating influenza outbreaks. Yet, vaccine supplies and daily administration capacities are limited, even in developed countries. Understanding how such constraints can alter the mitigating effects of vaccination is a crucial part of influenza preparedness plans. Mathematical models provide tools for government and medical officials to assess the impact of different vaccination strategies and plan accordingly. However, many existing models of vaccination employ several questionable assumptions, including a rate of vaccination proportional to the population at each point in time.

Methods: We present a SIR-like model that explicitly takes into account vaccine supply and the number of vaccines administered per day and places data-informed limits on these parameters. We refer to this as the non-proportional model of vaccination and compare it to the proportional scheme typically found in the literature.

Results: The proportional and non-proportional models behave similarly for a few different vaccination scenarios. However, there are parameter regimes involving the vaccination campaign duration and daily supply limit for which the non-proportional model predicts smaller epidemics that peak later, but may last longer, than those of the proportional model. We also use the non-proportional model to predict the mitigating effects of variably timed vaccination campaigns for different levels of vaccination coverage, using specific constraints on daily administration capacity.

Conclusions: The non-proportional model of vaccination is a theoretical improvement that provides more accurate predictions of the mitigating effects of vaccination on influenza outbreaks than the proportional model. In addition, parameters such as vaccine supply and daily administration limit can be easily adjusted to simulate conditions in developed and developing nations with a wide variety of financial and medical resources. Finally, the model can be used by government and medical officials to create customized pandemic preparedness plans based on the supply and administration constraints of specific communities.

Background: On 31 March 2013, the first human infections with the novel influenza A/H7N9 virus were reported in Eastern China. The outbreak expanded rapidly in geographic scope and size, with a total of 132 laboratory-confirmed cases reported by 3 June 2013, in 10 Chinese provinces and Taiwan. The incidence of A/H7N9 cases has stalled in recent weeks, presumably as a consequence of live bird market closures in the most heavily affected areas. Here we compare the transmission potential of influenza A/H7N9 with that of other emerging pathogens and evaluate the impact of intervention measures in an effort to guide pandemic preparedness.

Methods: We used a Bayesian approach combined with a SEIR (Susceptible-Exposed-Infectious-Removed) transmission model fitted to daily case data to assess the reproduction number (R) of A/H7N9 by province and to evaluate the impact of live bird market closures in April and May 2013. Simulation studies helped quantify the performance of our approach in the context of an emerging pathogen, where human-to-human transmission is limited and most cases arise from spillover events. We also used alternative approaches to estimate R based on individual-level information on prior exposure and compared the transmission potential of influenza A/H7N9 with that of other recent zoonoses.

Results: Estimates of R for the A/H7N9 outbreak were below the epidemic threshold required for sustained human-to-human transmission and remained near 0.1 throughout the study period, with broad 95% credible intervals by the Bayesian method (0.01 to 0.49). The Bayesian estimation approach was dominated by the prior distribution, however, due to relatively little information contained in the case data. We observe a statistically significant deceleration in growth rate after 6 April 2013, which is consistent with a reduction in A/H7N9 transmission associated with the preemptive closure of live bird markets. Although confidence intervals are broad, the estimated transmission potential of A/H7N9 appears lower than that of recent zoonotic threats, including avian influenza A/H5N1, swine influenza H3N2sw and Nipah virus.

Conclusion: Although uncertainty remains high in R estimates for H7N9 due to limited epidemiological information, all available evidence points to a low transmission potential. Continued monitoring of the transmission potential of A/H7N9 is critical in the coming months as intervention measures may be relaxed and seasonal factors could promote disease transmission in colder months.

Background: The impact of socio-demographic factors and baseline health on the mortality burden of seasonal and pandemic influenza remains debated. Here we analyzed the spatial-temporal mortality patterns of the 1918 influenza pandemic in Spain, one of the countries of Europe that experienced the highest mortality burden.

Methods: We analyzed monthly death rates from respiratory diseases and all-causes across 49 provinces of Spain, including the Canary and Balearic Islands, during the period January-1915 to June-1919. We estimated the influenza-related excess death rates and risk of death relative to baseline mortality by pandemic wave and province. We then explored the association between pandemic excess mortality rates and health and socio-demographic factors, which included population size and age structure, population density, infant mortality rates, baseline death rates, and urbanization.

Results: Our analysis revealed high geographic heterogeneity in pandemic mortality impact. We identified 3 pandemic waves of varying timing and intensity covering the period from Jan-1918 to Jun-1919, with the highest pandemic-related excess mortality rates occurring during the months of October-November 1918 across all Spanish provinces. Cumulative excess mortality rates followed a south–north gradient after controlling for demographic factors, with the North experiencing highest excess mortality rates. A model that included latitude, population density, and the proportion of children living in provinces explained about 40% of the geographic variability in cumulative excess death rates during 1918–19, but different factors explained mortality variation in each wave.

Conclusions: A substantial fraction of the variability in excess mortality rates across Spanish provinces remained unexplained, which suggests that other unidentified factors such as comorbidities, climate and background immunity may have affected the 1918-19 pandemic mortality rates. Further archeo-epidemiological research should concentrate on identifying settings with combined availability of local historical mortality records and information on the prevalence of underlying risk factors, or patient-level clinical data, to further clarify the drivers of 1918 pandemic influenza mortality.