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Metagenomic studies have revolutionized our understanding of the metabolic potential of uncultured microorganisms in various ecosystems. However, many of these genomic predictions have yet to be experimentally tested, and the functional expression of genomic potential often remains unaddressed. In order to obtain a more thorough understanding of cell physiology, novel techniques capable of testing microbial metabolism under close to in situ conditions must be developed. Here, we provide a benchmark study to demonstrate that bioorthogonal non-canonical amino acid tagging (BONCAT) in combination with fluorescence-activated cell sorting (FACS) and 16S rRNA gene sequencing can be used to identify anabolically active members of a microbial community incubated in the presence of various growth substrates or under changing physicochemical conditions. We applied this approach to a hot spring sediment microbiome from Yellowstone National Park (Wyoming, USA) and identified several microbes that changed their activity levels in response to substrate addition, including uncultured members of the phyla Thaumarchaeota, Acidobacteria, and Fervidibacteria. Because shifts in activity in response to substrate amendment or headspace changes are indicative of microbial preferences for particular growth conditions, results from this and future BONCAT-FACS studies could inform the development of cultivation media to specifically enrich uncultured microbes. Most importantly, BONCAT-FACS is capable of providing information on the physiology of uncultured organisms at as close to in situ conditions as experimentally possible.

In microbial studies, samples are often treated under different experimental conditions and then tested for microbial survival. A technique, dating back to the 1880s, consists of diluting the samples several times and incubating each dilution to verify the existence of microbial colony-forming units or CFU’s, seen by the naked eye. The main problem in the dilution series data analysis is the uncertainty quantification of the simple point estimate of the original number of CFU’s in the sample (i.e., at dilution zero). Common approaches such as log-normal or Poisson models do not seem to handle well extreme cases with low or high counts, among other issues. We build a novel binomial model, based on the actual design of the experimental procedure including the dilution series. For repetitions, we construct a hierarchical model for experimental results from a single laboratory and in turn a higher hierarchy for inter-laboratory analyses. Results seem promising, with a systematic treatment of all data cases, including zeros, censored data, repetitions, intra- and inter-laboratory studies. Using a Bayesian approach, a robust and efficient MCMC method is used to analyze several real data sets.

Tracheal intubation disrupts physiological homeostasis of secretion production and clearance, resulting in secretion accumulation within endotracheal tubes (ETTs). Novel in vitro and in vivo models were developed to specifically recapitulate the clinical manifestations of ETT occlusion. The novel Sharklet™ micropatterned ETT was evaluated, using these models, for the ability to reduce the accumulation of both bacterial biofilm and airway mucus compared to a standard care ETT. Novel ETTs with micropattern on the inner and outer surfaces were placed adjacent to standard care ETTs in in vitro biofilm and airway patency (AP) models. The primary outcome for the biofilm model was to compare commercially-available ETTs (standard care and silver-coated) to micropatterned for quantity of biofilm accumulation. The AP model's primary outcome was to evaluate accumulation of artificial airway mucus. A 24-h ovine mechanical ventilation model evaluated the primary outcome of relative quantity of airway secretion accumulation in the ETTs tested. The secondary outcome was measuring the effect of secretion accumulation in the ETTs on airway resistance. Micropatterned ETTs significantly reduced biofilm by 71% (p = 0.016) compared to smooth ETTs. Moreover, micropatterned ETTs reduced lumen occlusion, in the AP model, as measured by cross-sectional area, in distal (85%, p = 0.005), middle (84%, p = 0.001) and proximal (81%, p = 0.002) sections compared to standard care ETTs. Micropatterned ETTs reduced the volume of secretion accumulation in a sheep model of occlusion by 61% (p

We review reproducibility results for methods that test antimicrobial efficacy against biofilms, spores and bacteria dried onto a surface. Our review, that included test results for Pseudomonas aeruginosa, Salmonella choleraesuis and Bacillus subtilis, suggests that the level of reproducibility depends on the efficacy of the antimicrobial agent being tested for each microbe and microbial environment. To determine the reproducibility of a method, several laboratories must independently test the same antimicrobial agent using the method. Little variability among the efficacy results suggests good reproducibility. Such reproducibility assessments currently are hampered by the absence of an objective process for deciding whether the variability is sufficiently small. We present a quantitative decision process that objectively determines whether any method that assesses antimicrobial efficacy is reproducible. Because the perception of acceptable reproducibility may differ among stakeholders, the decision process is governed by a stakeholder’s specifications that necessarily includes the efficacy of the agents to be tested.

Constructed wetlands offer an effective means for treatment of wastewater from a variety of sources. An understanding of the microbial ecology controlling nitrogen, carbon and sulfur cycles in constructed wetlands has been identified as the greatest gap for optimizing performance of these promising treatment systems. It is suspected that operational factors such as plant types and hydraulic operation influence the subsurface wetland environment, especially redox, and that the observed variation in effluent quality is due to shifts in the microbial populations and/or their activity. This study investigated the biofilm associated sulfate reducing bacteria and ammonia oxidizing bacteria (using the dsrB and amoA genes, respectively) by examining a variety of surfaces within a model wetland (gravel, thick roots, fine roots, effluent), and the changes in activity (gene abundance) of these functional groups as influenced by plant species and season. Molecular techniques were used including quantitative PCR and denaturing gradient gel electrophoresis (DGGE), both with and without propidium monoazide (PMA) treatment. PMA treatment is a method for excluding from further analysis those cells with compromised membranes. Rigorous statistical analysis showed an interaction between the abundance of these two functional groups with the type of plant and season (p

Biofilm-related infections have become a major clinical concern. Typically, animal models that involve inoculation with planktonic bacteria have been used to create positive infection signals and examine antimicrobial strategies for eradicating or preventing biofilm-related infection. However, it is estimated that 99.9% of bacteria in nature dwell in established biofilms. As such, open wounds have significant potential to become contaminated with bacteria that reside in a well-established biofilm. In this study, a modified CDC biofilm reactor was developed to repeatably grow mature biofilms of Staphylococcus aureus on the surface of polyetheretherketone (PEEK) membranes for inoculation in a future animal model of orthopaedic implant biofilm-related infection. Results indicated that uniform, mature biofilms repeatably grew on the surface of the PEEK membranes.

In this paper we investigate the bifurcations of solutions to a class of constrained optimization problems. This study was motivated by annealing problems which have been used to successfully cluster data in many different applications. Solving these problems numerically is challenging due to the size of the space being optimized over, which depends on the size and the complexity of the data being analyzed. The type of constraints and the form of the cost functions make them invariant to the action of the symmetric group on N symbols, S N , and we capitalize on this symmetry to describe the bifurcation structure. We ascertain the existence of bifurcating branches, address their stability, and compare the stability to optimality in the constrained problem. These theoretical results are used to explain numerical results obtained from an annealing problem used to cluster data.