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ABSTRACTThe oral microbiome plays an important role in protecting oral health. Here, we established a controlled mixed-species in vitro biofilm model and used it to assess the impact of glucose and lactate on the ability of Streptococcus mutans, an acidogenic and aciduric species, to compete with commensal oral bacteria. A chemically defined medium was developed that supported the growth of S. mutans and four common early colonizers of dental plaque: Streptococcus gordonii, Actinomyces oris, Neisseria subflava, and Veillonella parvula. Biofilms containing the early colonizers were developed in a continuous flow bioreactor, exposed to S. mutans, and incubated for up to 7 days. The abundance of bacteria was estimated by quantitative polymerase chain reaction (qPCR). At high glucose and high lactate, the pH in bulk fluid rapidly decreased to approximately 5.2, and S. mutans outgrew other species in biofilms. In low glucose and high lactate, the pH remained above 5.5, and V. parvula was the most abundant species in biofilms. By contrast, in low glucose and low lactate, the pH remained above 6.0 throughout the experiment, and the microbial community in biofilms was relatively balanced. Fluorescence in situ hybridization confirmed that all species were present in the biofilm and the majority of cells were viable using live/dead staining. These data demonstrate that carbon source concentration is critical for microbial homeostasis in model oral biofilms. Furthermore, we established an experimental system that can support the development of computational models to predict transitions to microbial dysbiosis based on metabolic interactions.IMPORTANCEWe developed a controlled (by removing host factor) dynamic system metabolically representative of early colonization of Streptococcus mutans not measurable in vivo. Hypotheses on factors influencing S. mutans colonization, such as community composition and inoculation sequence and the effect of metabolite concentrations, can be tested and used to predict the effect of interventions such as dietary modifications or the use of toothpaste or mouthwash on S. mutans colonization. The defined in vitro model (species and medium) can be simulated in an in silico model to explore more of the parameter space.

The removal of phosphorus (P) from domestic wastewater is primarily to reduce the potential for eutrophication in receiving waters, and is mandated and common in many countries. However, most P-removal technologies have been developed for use at larger wastewater treatment plants that have economies-of-scale, rigorous monitoring, and in-house operating expertise. Smaller treatment plants often do not have these luxuries, which is problematic because there is concern that P releases from small treatment systems may have greater environmental impact than previously believed. Here P-removal technologies are reviewed with the goal of determining which treatment options are amenable to small-scale applications. Significant progress has been made in developing some technologies for small-scale application, namely sorptive media. However, as this review shows, there is a shortage of treatment technologies for P-removal at smaller scales, particularly sustainable and reliable options that demand minimal operating and maintenance expertise or are suited to northern latitudes. In view of emerging regulatory pressure, investment should be made in developing new or adapting existing P-removal technologies, specifically for implementation at small-scale treatment works.

Cellular heterogeneity influences bioprocess performance in ways that until date are not completely elucidated. In order to account for this phenomenon in the design and operation of bioprocesses, reliable analytical and mathematical descriptions are required. We present an overview of the single cell analysis, and the mathematical modeling frameworks that have potential to be used in bioprocess control and optimization, in particular for microbial processes. In order to be suitable for bioprocess monitoring, experimental methods need to be high throughput and to require relatively short processing time. One such method used successfully under dynamic conditions is flow cytometry. Population balance and individual based models are suitable modeling options, the latter one having in particular a good potential to integrate the various data collected through experimentation. This will be highly beneficial for appropriate process design and scale up as a more rigorous approach may prevent a priori unwanted performance losses. It will also help progressing synthetic biology applications to industrial scale.