James R. Mihelcic

Vertical-flow constructed wetlands were investigated for ammonium and nitrate removal from synthetic wastewater in bench-scale wetland columns. Total ammonia and nitrate were measured as wastewater and fed through planted and unplanted columns over three 4-week phases: downflow, upflow, and downflow-upflow in series. Mass balance results showed that downflow columns removed >90% of influent ammonium, regardless of vegetation. Unplanted downflow columns removed 15% of nitrate and 14% of total nitrogen. Planted downflow columns removed only 1% of nitrate and total nitrogen. Unplanted upflow columns removed 55% of ammonium, 50% nitrate, and 31% of total nitrogen, whereas planted upflow columns removed 59, 60, and 40% of nitrogen species, respectively. For downflow-upflow columns in series, unplanted columns removed 79% of the ammonium, 1% of nitrate, and 4% of total nitrogen. In-series planted columns removed 93, 62, and 59%, respectively. These results suggest that downflow wetlands may be more appr...

Background: Phenotypes exhibited by microorganisms can be useful for several purposes, e.g., ethanol as an alternate fuel. Sometimes, the target phenotype maybe required in combination with other phenotypes, in order to be useful, for e.g., an industrial process may require that the organism survive in an anaerobic, alcohol rich environment and be able to feed on both hexose and pentose sugars to produce ethanol. This combination of traits may not be available in any existing organism or if they do exist, the mechanisms involved in the phenotype-expression may not be efficient enough to be useful. Thus, it may be required to genetically modify microorganisms. However, before any genetic modification can take place, it is important to identify the underlying cellular subsystems responsible for the expression of the target phenotype. Results: In this paper, we develop a method to identify statistically significant and phenotypically-biased functional modules. The method can compare the organismal network information from hundreds of phenotype expressing and phenotype non-expressing organisms to identify cellular subsystems that are more prone to occur in phenotype-expressing organisms than in phenotype non-expressing organisms. We have provided literature evidence that the phenotype-biased modules identified for phenotypes such as hydrogen production (dark and light fermentation), respiration, gram-positive, gram-negative and motility, are indeed phenotype-related. Conclusion: Thus we have proposed a methodology to identify phenotype-biased cellular subsystems. We have shown the effectiveness of our methodology by applying it to several target phenotypes. The code and all supplemental files can be downloaded from (http://freescience.org/cs/phenotype-biased-biclusters/).

Background: A latent behavior of a biological cell is complex. Deriving the underlying simplicity, or the fundamental rules governing this behavior has been the Holy Grail of systems biology. Data-driven prediction of the system components and their component interplays that are responsible for the target system’s phenotype is a key and challenging step in this endeavor.Results: The proposed approach, which we call System Phenotype-related Interplaying Components Enumerator (Spice), iteratively enumerates statistically significant system components that are hypothesized (1) to play an important role in defining the specificity of the target system’s phenotype(s); (2) to exhibit a functionally coherent behavior, namely, act in a coordinated manner to perform the phenotype-specific function; and (3) to improve the predictive skill of the system’s phenotype(s) when used collectively in the ensemble of predictive models.Spicecan be applied to both instance-based data and network-based data. When validated,Spiceeffectively identified system components related to three target phenotypes: biohydrogen production, motility, and cancer. Manual results curation agreed with the known phenotype-related system components reported in literature. Additionally, using the identified system components as discriminatory features improved the prediction accuracy by 10% on the phenotype-classification task when compared to a number of state-of-the-art methods applied to eight benchmark microarray data sets.Conclusion: We formulate a problem—enumeration of phenotype-determining system component interplays—and propose an effective methodology (Spice) to address this problem.Spiceimproved identification of cancer-related groups of genes from various microarray data sets and detected groups of genes associated with microbial biohydrogen production and motility, many of which were reported in literature.Spicealso improved the predictive skill of the system’s phenotype determination compared to individual classifiers and/or other ensemble methods, such as bagging, boosting, random forest, nearest shrunken centroid, and random forest variable selection method.

Microbial communities in their natural environments exhibit phenotypes that can directly cause particular diseases, convert biomass or wastewater to energy, or degrade various environmental contaminants. Understanding how these communities realize specific phenotypic traits (e.g., carbon fixation, hydrogen production) is critical for addressing health, bioremediation, or bioenergy problems.

Background: Identifying cellular subsystems that are involved in the expression of a target phenotype has been a very active research area for the past several years. In this paper,cellular subsystemrefers to a group of genes (or proteins) that interact and carry out a common function in the cell. Most studies identify genes associated with a phenotype on the basis of some statistical bias, others have extended these statistical methods to analyze functional modules and biological pathways for phenotype-relatedness. However, a biologist might often have a specific question in mind while performing such analysis and most of the resulting subsystems obtained by the existing methods might be largely irrelevant to the question in hand. Arguably, it would be valuable to incorporate biologist's knowledge about the phenotype into the algorithm. This way, it is anticipated that the resulting subsytems would not only be related to the target phenotype but also contain information that the biologist is likely to be interested in.Results: In this paper we introduce a fast and theoretically guranteed method calledDENSE(Dense and ENriched Subgraph Enumeration) that can take in as input a biologist'spriorknowledge as a set of query proteins and identify all the dense functional modules in a biological network that contain some part of the query vertices. The density (in terms of the number of network egdes) and the enrichment (the number of query proteins in the resulting functional module) can be manipulated via two parameters γ andμ, respectively.Conclusion: This algorithm has been applied to the protein functional association network ofClostridium acetobutylicumATCC 824, a hydrogen producing, acid-tolerant organism. The algorithm was able to verify relationships known to exist in literature and also some previously unknown relationships including those with regulatory and signaling functions. Additionally, we were also able to hypothesize that some uncharacterized proteins are likely associated with the target phenotype. The DENSE code can be downloaded fromhttp://www.freescience.org/cs/DENSE/

Small island developing states (SIDS) have limited access to imported goods, and their associated patterns of consumption and waste generation are affected by space limitations. They are also impacted by the global presence of marine litter that reaches their shores from the ocean. A material flow analysis (MFA) was applied to household solid waste and marine litter collected from Kayangel Island in the Republic of Palau to provide a comprehensive characterization and spatial accounting of the inflow of nonputrescible materials that become solid waste. Approximately 15,100 kg of nonputrescible solid waste are generated annually on Kayangel Island (0.42 kg per capita per day), with 57% being marine litter derived from the ocean and 43% derived from household activities. Household generation of nonputrescible solid waste (that ignores inputs of marine litter) ranged from 0.14–0.18 kg/capita-day for the school in session and nonschool periods, respectively. The most significant waste categories (by mass) in...

The relationship between temperature, high pH, desiccation, decomposition, pathogen destruction, and user operation in active double vault urine diverting (DVUD) composting latrines located in the Bocas del Toro region of Panama was assessed. Latrine samples were analyzed for temperature, pH, % moisture, carbon-to-nitrogen (C/N) ratio, and presence of specific pathogens. Surveys and visual inspections were used to verify use and type of dry material desiccant added. Measurements supported findings that compost latrines do not reach temperatures sufficient to destroy all pathogens. pH measurements showed that many latrines were operating within the range for ideal aerobic decomposition, a pH of 7.5–8.5, but only 17% of latrines measured pH 9 or above. Almost 100% of composting latrine users added sawdust and wood ash, to lower moisture level and provide carbon for decomposition. However, the recommended amount of desiccant added was insufficient to reduce moisture to the suggested 25% for pathogen destruction and C/N ratios remained in the range of raw human faeces. Importantly, pathogens, mainly helminths, were still present in compost stored for the 6-month contact time. The latrines have conflicting goals of pathogen destruction and aerobic decomposition. Recommendations are made regarding operation of composting latrines and disposal of composted material.

The operation of wastewater lagoons systems located in the South Yungas Province of Bolivia has been analyzed over a 2-year period. Facultative and maturation lagoons were evaluated for their performance in removing total suspended solids (TSS), biochemical oxygen demand (BOD), chemical oxygen demand (COD), nitrogen, phosphorus, and coliforms. Facultative lagoons operating in San Antonio were found to remove approximately 74% total suspended solids, 70–89% BOD, 62–85% COD, 53% nitrogen, 52% phosphorus and 97.8–99.9% coliforms. Maturation ponds were found to remove 74–93% total suspended solids, 22–62% BOD, 10–95% COD, 3% nitrogen, 20–95% phosphorus and 77.4–99.96% coliforms. Results from the 2-year study indicate that these wastewater treatment systems are currently performing as expected; however regular maintenance, specifically removing algae every (2 weeks) is required. The removal percentages of the treatment systems (comparing influent to effluent) ranged from 74–97% TSS, 78–98% BOD, 70–99.7% COD, 58–77% nitrogen, 62–99.9% phosphorus, and 99.99% coliforms.