With advances in high-throughput technologies and next-generation sequencing, the amount of genomic and proteomic data is dramatically increasing in the post-genomic era. One of the biggest challenges that has arisen is the connection of sequences to their activities and the understanding of their cellular functions and interactions. In this dissertation, I present three different strategies for mining, predicting and visualizing biological functions. In the first part, I present the COMputational Bridges to Experiments (COMBREX) project, which facilitates the functional annotation of microbial proteins by leveraging the power of scientific community. The goal is to bring computational biologists and biochemists together to expand our knowledge. A database-driven web portal has been built to serve as a hub for the community. Predicted annotations will be deposited into the database and the recommendation system will guide biologists to the predictions whose experimental validation will be more beneficial to our knowledge of microbial proteins. In addition, by taking advantage of the rich content, we develop a web service to help community members enrich their genome annotations. In the second part, I focus on identifying the genes for enzyme activities that lack genetic details in the major biological databases. Protein sequences are unknown for about one-third of the characterized enzyme activities listed in the EC system, the so-called orphan enzymes. Our approach considers the similarities between enzyme activities, enabling us to deal with broad types of orphan enzymes in eukaryotes. I apply our framework to human orphan enzymes and show that we can successfully fill the knowledge gaps in the human metabolic network. In the last part, I construct a platform for visually analyzing the eco-system level metabolic network. Most microbes live in a multiple-species environment. The underlying nutrient exchange can be seen as a dynamic eco-system level metabolic network. The complexity of the network poses new visualization challenges. Using the data predicted by Computation Of Microbial Ecosystems in Time and Space (COMETS), I demonstrate that our platform is a powerful tool for investigating the interactions of the microbial community. We apply it to the exploration of a simulated microbial eco-system in the human gut. The result reflects both known knowledge and novel mutualistic interactions, such as the nutrients exchanges between E. coli, C. difficile and L. acidophilus.

abstract: Finding habitable worlds is a key driver of solar system exploration. Many solar system missions seek environments providing liquid water, energy, and nutrients, the three ingredients necessary to sustain life. Such environments include hydrothermal systems, spatially-confined systems where hot aqueous fluid circulates through rock by convection. I sought to characterize hydrothermal microbial communities, collected in hot spring sediments and mats at Yellowstone National Park, USA, by measuring their bulk elemental composition. To do so, one must minimize the contribution of non-biological material to the samples analyzed. I demonstrate that this can be achieved using a separation method that takes advantage of the density contrast between cells and sediment and preserves cellular elemental contents. Using this method, I show that in spite of the tremendous physical, chemical, and taxonomic diversity of Yellowstone hot springs, the composition of microorganisms there is surprisingly ordinary. This suggests the existence of a stoichiometric envelope common to all life as we know it. Thus, future planetary investigations could use elemental fingerprints to assess the astrobiological potential of hydrothermal settings beyond Earth. Indeed, hydrothermal activity may be widespread in the solar system. Most solar system worlds larger than 200 km in radius are dwarf planets, likely composed of an icy, cometary mantle surrounding a rocky, chondritic core. I enhance a dwarf planet evolution code, including the effects of core fracturing and hydrothermal circulation, to demonstrate that dwarf planets likely have undergone extensive water-rock interaction. This supports observations of aqueous products on their surfaces. I simulate the alteration of chondritic rock by pure water or cometary fluid to show that aqueous alteration feeds back on geophysical evolution: it modifies the fluid antifreeze content, affecting its persistence over geological timescales; and the distribution of radionuclides, whose decay is a chief heat source on dwarf planets. Interaction products can be observed if transported to the surface. I simulate numerically how cryovolcanic transport is enabled by primordial and hydrothermal volatile exsolution. Cryovolcanism seems plausible on dwarf planets in light of images recently returned by spacecrafts. Thus, these coupled geophysical-geochemical models provide a comprehensive picture of dwarf planet evolution, processes, and habitability. / Dissertation/Thesis / Doctoral Dissertation Astrophysics 2015

The habitability of Earth is dependent upon the global recycling of elements essential for life, such as nitrogen, sulfur and carbon. Nutrient-cycling by micro-organisms is vital to these biogeochemical cycles because many key steps are mediated primarily, or exclusively, by microbial life. The dynamics of these cycles are highly complex, and environmental perturbations (such as changes in the oceanic oxygen concentration) can have unexpected or catastrophic effects; often causing abrupt switches between chemical states. Despite the importance of these environmental perturbations however, few theoretical models have addressed how they affect the dynamical behaviour of nutrient-cycling microbial ecosystems. In this work, we investigate the effect of environmental perturbations on microbially-mediated nutrient cycles and assess the likelihood of "sudden transitions" between chemical states of the ecosystem occurring in a variety of ecological contexts. To do this, we first use computational modelling of microbial nutrient-cycling, using a "box model" approach. We then move on to an experimental study using the microbial sulfur cycle as a model ecosystem, with freshwater pond sediment/water microcosms. These microcosms have the advantage of retaining many of the features of the real ecosystem (such as microbial diversity, spatial structure, and abiotic interactions) while allowing the controlled manipulation of environmental perturbations. We study these microcosms using a combination of chemical measurements and high-throughput sequencing of the microbial community. Finally, we return to the computational side, and attempt to reproduce chemical data from our experiments in a mathematical model containing realistic abiotic chemical interactions.

Doctor of Philosophy / Department of Agronomy / Charles W. Rice / Soil C sequestration in agricultural ecosystems is an immediate and significant option to mitigate the increase in the atmospheric CO2 concentration. The objectives of this study were to determine 1) the influence of crop and soil management practices applicable to Kansas (i.e., tillage, N fertilization, and crop rotations) on soil C and N, C sequestration rates, soil aggregation and aggregate-associated C and N; and 2) the influence of long-term tillage practices on SOC and total N, soil aggregation and aggregate-associated C and N in three soil types: an Oxisol (Brazil), a Vertisol (Argentina), and a Mollisol (Kansas, USA). The Kansas experiments included: tillage (conventional tillage (CT), reduced tillage (RT) and no-tillage (NT)) and native prairie; nitrogen (N) fertilization rates; and crop rotations comprising various combinations of winter wheat (Triticum aestivum L.), grain sorghum (Sorghum bicolor L. Moench), and soybean (Glycine max L. Merrill). The presence of a fallow period negatively affected C sequestration rates even under NT systems. Nitrogen fertilization generally increased C sequestration rates. Rotations that contained wheat or sorghum had the greatest C sequestration rates while continuous soybean had the lowest rates. Cultivation decreased the amount of macroaggregates with a concomitment increased in the amount of microaggregates. Wheat and sorghum increased total C in the macroaggregate fraction (>250 mm) under NT while soybean had the lowest C concentration. Cultivation reduced microbial biomass C and N and potentially mineralizable C and N. The combination of conservation tillage and rotations that produced a greater amount of residue had greater C sequestration rates. In the Oxisol, NT had greater amounts of large macroaggregates (>2000 mm) than CT, however no differences between tillage practices were detected in the Vertisol and Mollisol. Cultivation of native grassland reduced the amount of macroaggregates and the associated C and N concentration; however NT tended to be more similar to the native grassland. Overall, our results indicated that the use of conservation tillage could be an important strategy to sequester C in these agroecosystems. The adoption of management practices that enhance C sequestration would be important for reducing GHGs emissions and maintaining the sustainability of agricultural systems.

On the reefs of Bermuda, the coral Diploria labyrinthiformis is rarely infected with black band disease (BBD) while BBD-infected colonies of D. strigosa are common. This study investigated several possible explanations for the documented difference in BBD prevalence including: 1) temperature and light conditions differentially affect the progression of the disease among these two species; 2) the bacterial communities associated with each species are different and 3) the bacterial composition of BBD in Bermuda is unique from that of other geographical regions where D. labyrinthiformis has been reported with BBD. Results suggest that light and temperature are important variables in determining BBD progression for both species; reef location, rather than coral species dictates the coral associated bacterial diversity; and the BBD bacterial mat in Bermuda is unique compared to other regions of the Caribbean. Many factors are likely responsible for the low occurrence of BBD among D. labyrinthiformis in Bermuda.

Thesis advisor: Babak Momeni / Microbial communities are complex networks comprised of multiple species that are facilitating and inhibiting one another (as well as themselves). Currently, we lack an understanding of what mechanisms drive coexistence within these communities. We aimed to remedy this by studying the dynamics of coexisting communities, focusing on the complexity of their interaction networks, the impact of spatial dynamics, and the interplay of facilitating and inhibiting interactions. These limitations in our understanding prevent the furtherment of designing intentional communities for bioremediation, maintenance of healthy microbiota, and other functional communities. To better understand these microbial dynamics, we chose to address the problem from two fronts: computational modeling and exploring dynamics of cocultures. Through our 1-D model, spatial structure fostering more coexistence – especially when facilitation is present. For the coexistence assays, we determined that contact-dependent growth inhibition is a density dependent mechanism, and the use of a Tn-Seq mutant library to predict species interactions is possible, but needs further optimization to reconcile density dependent effects of interactions. / Thesis (MS) — Boston College, 2021. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Biology.

Presented diploma thesis focuses on a new type of lightweight polyurethane foam (PUR), which has been manufactured with the intention of it being biodegradable within currently valid norms on biodegradation of plastic materials. The future use of said polyurethane foam is as carrier for odor repellent to avoid wildlife-vehicle collisions in agriculture landscape, where, after the end of its lifespan it could be left to biodegrade in soil the environment. The examined material, PUR BIO-10, was tested for biodegradability in laboratory microcosms according to standardized method ASTM D5988-03. Biodegradability was tested in two separate soil types - forest soil and agricultural soil, which have been selected with the future use of the material in mind. According to the method biodegradability was measured as mineralization of the material by capturing evolved carbon dioxide. During the first trial the mineralization of polyurethane foam was 10.65 ± 2.54 % in the forest soil and 20.48 ± 9.18 % in the agricultural soil. During the second trial the mineralization was 3.88 ± 3.42 % in the forest soil and 8.96 ± 1.79 % in the agricultural soil. In the second trial the difference between the soils was statistically significant. After the end of the biodegradation experiments the tested material was...

Thesis advisor: Babak Momeni / Diseases of the upper respiratory tract encompass a plethora of complex multifaceted etiologies ranging from acute viral and bacterial infections to chronic diseases of the lung and nasal cavity. Due to this inherent complexity, typical treatments often fail in the face of recalcitrant infections and/or severe forms of chronic disease, including asthma. Thus, in order to provide improved standard of care, the mechanisms at play in hard-to-treat etiologies must be better understood. More recently, research has demonstrated a significant association between microbiota and many URT diseases. Previous work has also identified species capable of directly inhibiting standard treatments used to control asthma exacerbations. Despite an exhaustive collection of data characterizing microbiota composition in states of both health and disease, our knowledge of what microbiota profiles are observed in what specific disease etiologies is severely lacking. Yet, gaining these insights is crucial for the translation of such data into application. In this thesis I sought to: 1) identify gut microbiota profiles associated with severe and treatment resistant forms of childhood asthma, and 2) formulate a predictive model to facilitate the restructuring of microbiota for desired therapeutic outcomes. To identify gut microbiota and metabolites enriched in severe and treatment resistant childhood asthma, I looked to an ongoing longitudinal human study on vitamin D and childhood asthma. In this study, I find several fecal bacterial taxa and metabolites associated with more severe (i.e., higher wheeze proportion) and treatment resistant asthma in children at age 3 years. Specifically, several Veillonella species were enriched in children with higher wheeze proportion and in children that responded poorly to inhaled corticosteroid treatment (ICS) (i.e., non-responders). Haemophilus parainfluenzae, a species previously identified as enriched in the airway of adults with ICS-resistant asthma, was also uniquely enriched in children considered ICS non-responders in this study. Several metabolic pathways were also distinctly enriched: histidine metabolism was enriched in children with higher wheeze proportion while sphingolipid metabolism was enriched in ICS non-responders. Both metabolic pathways have been previously identified in association with asthma, further corroborating their role in this disease. Yet, this study is the first to identify these taxa and metabolites in children with preexisting and treatment resistant asthma. In the pursuit of improved treatment outcomes for recalcitrant URT diseases, recent efforts have turned towards microbiota-based therapies. While such treatments have proven successful in the treatment of gastrointestinal infections, these methods have not yet been extended to other conditions. Considering this, I ask whether a predictive model describing microbial interactions can facilitate the restructuring of microbiota for desired therapeutic outcomes. For this, I use a community of nasal microbiota to determine when a simply Lotka-Volterra-like (LV) model is a suitable representation for microbial interactions. I then utilize our LV-like model to examine whether environmental fluctuations have a major influence on community assembly and composition. For this, I looked specifically at pH fluctuations. In this study, I found that LV-like models are most suitable for describing community dynamics in complex low nutrient conditions. I also identified simple in vitro experiments that can reliably predict the suitability of a LV-like model for describing outcomes of a two-species community. When our LV-like model was applied to an in silico community of nasal species to determine the impact of environmental fluctuations, I find that nasal communities are generally robust against pH fluctuations and that, in this condition, facilitative interactions are a stabilizing force, and thus, selected for in in silico enrichment experiments. Overall, this thesis further corroborates the association of microbiota with URT diseases and treatment outcomes while also providing unique insight into their association with specific etiologies in childhood asthma. This thesis also provides a framework for developing models able to facilitate the development of future microbiota-based therapies while also determining how, and when, environmental factors impact community assembly and composition. / Thesis (PhD) — Boston College, 2021. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Biology.

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Anthropogenic activities such as construction and agriculture directly affect its surrounding environments. Many studies have focused on how megafauna and flora are impacted by human activities, however, relatively little is known how new occupation of land affects smaller organisms such as insects and microbes. Additionally, other stressors such as predation can impact host physiology. The grasshopper species Melanopussanguinipes was chosen to be used in a study to measure how stress caused by artificial sound and predation can alter exoskeleton and gut microbiomes once exposed to these stressors.