Center for Biofilm Engineering (CBE)
Permanent URI for this communityhttps://scholarworks.montana.edu/handle/1/9334
At the Center for Biofilm Engineering (CBE), multidisciplinary research teams develop beneficial uses for microbial biofilms and find solutions to industrially relevant biofilm problems. The CBE was established at Montana State University, Bozeman, in 1990 as a National Science Foundation Engineering Research Center. As part of the MSU College of Engineering, the CBE gives students a chance to get a head start on their careers by working on research teams led by world-recognized leaders in the biofilm field.
Browse
Search Results
Item Subsurface hydrocarbon degradation strategies in low- and high-sulfate coal seam communities identified with activity-based metagenomics(Springer Science and Business Media LLC, 2022-02) Schweitzer, Hannah D.; Smith, Heidi J.; Barnhart, Elliott P.; McKay, Luke J.; Gerlach, Robin; Cunningham, Alfred B.; Malmstrom, Rex R.; Goudeau, Danielle; Fields, Matthew W.Environmentally relevant metagenomes and BONCAT-FACS derived translationally active metagenomes from Powder River Basin coal seams were investigated to elucidate potential genes and functional groups involved in hydrocarbon degradation to methane in coal seams with high- and low-sulfate levels. An advanced subsurface environmental sampler allowed the establishment of coal-associated microbial communities under in situ conditions for metagenomic analyses from environmental and translationally active populations. Metagenomic sequencing demonstrated that biosurfactants, aerobic dioxygenases, and anaerobic phenol degradation pathways were present in active populations across the sampled coal seams. In particular, results suggested the importance of anaerobic degradation pathways under high-sulfate conditions with an emphasis on fumarate addition. Under low-sulfate conditions, a mixture of both aerobic and anaerobic pathways was observed but with a predominance of aerobic dioxygenases. The putative low-molecular-weight biosurfactant, lichysein, appeared to play a more important role compared to rhamnolipids. The methods used in this study—subsurface environmental samplers in combination with metagenomic sequencing of both total and translationally active metagenomes—offer a deeper and environmentally relevant perspective on community genetic potential from coal seams poised at different redox conditions broadening the understanding of degradation strategies for subsurface carbon.Item In Situ Enhancement and Isotopic Labeling of Biogenic Coalbed Methane(American Chemical Society, 2022-02) Barnhart, Elliott P.; Ruppert, Leslie; Hiebert, Randy; Smith, Heidi J.; Schweitzer, Hannah D.; Clark, Arthur C.; Weeks, Edwin P.; Orem, William H.; Varonka, Matthew S.; Platt, George; Shelton, Jenna L.; Davis, Katherine J.; Hyatt, Robert J.; McIntosh, Jennifer C.; Ashley, Kilian; Ono, Shuhei; Martini, Anna M.; Hackley, Keith C.; Gerlach, Robin; Spangler, Lee; Phillips, Adrienne J.; Barry, Mark; Cunningham, Alfred B.; Fields, Matthew W.Subsurface microbial (biogenic) methane production is an important part of the global carbon cycle that has resulted in natural gas accumulations in many coal beds worldwide. Laboratory studies suggest that complex carbon-containing nutrients (e.g., yeast or algae extract) can stimulate methane production, yet the effectiveness of these nutrients within coal beds is unknown. Here, we use downhole monitoring methods in combination with deuterated water (D2O) and a 200-liter injection of 0.1% yeast extract (YE) to stimulate and isotopically label newly generated methane. A total dissolved gas pressure sensor enabled real time gas measurements (641 days preinjection and for 478 days postinjection). Downhole samples, collected with subsurface environmental samplers, indicate that methane increased 132% above preinjection levels based on isotopic labeling from D2O, 108% based on pressure readings, and 183% based on methane measurements 266 days postinjection. Demonstrating that YE enhances biogenic coalbed methane production in situ using multiple novel measurement methods has immediate implications for other field-scale biogenic methane investigations, including in situ methods to detect and track microbial activities related to the methanogenic turnover of recalcitrant carbon in the subsurface.Item Experimental Designs to Study the Aggregation and Colonization of Biofilms by Video Microscopy With Statistical Confidenc(Frontiers Media SA, 2022-01) Pettygrove, Brian A.; Smith, Heidi J.; Pallister, Kyler B.; Voyich, Jovanka M.; Stewart, Philip S.; Parker, Albert E.The goal of this study was to quantify the variability of confocal laser scanning microscopy (CLSM) time-lapse images of early colonizing biofilms to aid in the design of future imaging experiments. To accomplish this a large imaging dataset consisting of 16 independent CLSM microscopy experiments was leveraged. These experiments were designed to study interactions between human neutrophils and single cells or aggregates of Staphylococcus aureus (S. aureus) during the initial stages of biofilm formation. Results suggest that in untreated control experiments, variability differed substantially between growth phases (i.e., lag or exponential). When studying the effect of an antimicrobial treatment (in this case, neutrophil challenge), regardless of the inoculation level or of growth phase, variability changed as a frown-shaped function of treatment efficacy (i.e., the reduction in biofilm surface coverage). These findings were used to predict the best experimental designs for future imaging studies of early biofilms by considering differing (i) numbers of independent experiments; (ii) numbers of fields of view (FOV) per experiment; and (iii) frame capture rates per hour. A spreadsheet capable of assessing any user-specified design is included that requires the expected mean log reduction and variance components from user-generated experimental results. The methodology outlined in this study can assist researchers in designing their CLSM studies of antimicrobial treatments with a high level of statistical confidence.