Understanding localized meteorology is integral to understanding tropospheric ozone behavior. This field campaign took place during 2023 AGES+, a nationwide atmospheric chemistry campaign to better understand air quality and patterns in major metropolitan regions. Our objective was to measure ozone, temperature, pressure, and winds in the lower atmosphere near Chiwaukee Prairie in southeastern Wisconsin. This analysis investigates the potential effect of overwater wind patterns, measured by UAS, on ozone levels measured by the Chiwaukee Prairie Department of Natural Resources ground station.
Atmospheric pollutants are a huge problem in today’s environment. Ozone is one of these pollutants. It is harmful to human health and is a main pollutant in photochemical smog. Counties near Lake Michigan in Eastern Wisconsin suffer from poor air quality due to high ozone events and are in nonattainment of federal ozone standards. This is due to lake breeze circulation patterns and trapping of ozone and its precursors over Lake Michigan. To collect data on air quality in this area we have recently purchased an Aurelia S6 drone as a measurement platform for ozone, temperature, humidity, pressure, and NO2. While some of these have been measured before via UAS, we have recently custom-built an NO2 instrument, so careful consideration needs to be done to mount and fly the instruments under safe conditions. Here, we describe the UAS capabilities, strategies for mounting instrumentation, and flight campaign protocols to comply with FAA regulations and gather data safely.
Grazing steers utilize their rumen microbiomes to convert plant-derived carbohydrates into meat. Considering the socioeconomic importance of the beef industry, it is critical to develop strategies that maintain quality while lessening negative environmental impacts. Diet supplementation and hormonal growth implants have been shown to variably impact methane emissions and animal performance. A previous study examines grazing steers across four treatment groups: diet supplemented, hormonal implanted, combined diet and implant, and no intervention. They found no significant impact on emissions and performance. However, the rumen microbiome response to these treatments remains relatively unknown. Here, we will analyze 16S and ITS rRNA gene amplicon sequencing from those steers. We found that all treatments led to an increase in 16S and ITS alpha diversity over time; however, only the 16S diet group displayed a significant increase. Neither the 16S nor the ITS rumen microbiome composition significantly differed across treatments; however, both were significantly different over time. Future analyses will look at individual microbial and fungal responses to diet, grazing time periods, and associations with methane and performance data. Ultimately, our results will provide insight into rumen microbiome dynamics during the life cycle of a grazing steer, further informing sustainable management strategies.
Cattle that eat the same feed and come from the same environment can emit methane (CH4), a potent greenhouse gas, at vastly different levels. An estimated 32% of anthropogenic CH4 can be traced to ‘enteric fermentation’ in livestock production. During enteric fermentation, specialized microorganisms will digest complex plant fiber to create compounds like acetate and hydrogen (H2). Some of these organisms, called methanogens, will consume and use these products to produce CH4. Emerging data suggests natural inter-animal variation in CH4 emissions could derive from host genetics or differences in rumen microbial digestion. Here, we analyze 16S rRNA gene amplicon sequencing from the rumen of twenty beef cattle of varying CH4 emission levels to look for differences in the structure and composition of their microbial communities. There was no significant difference in microbial community diversity by host CH4 emission level. Association tests at the genus and ASV levels revealed relationships between low residual CH4 emissions and the genera Megasphaera, Prevotellaceae, Ruminococcus, and Gastranaerophilales. Network analysis of the high and low CH4 communities revealed disrupted relationships between methanogens and other members of the community. The methanogens Methanobrevibacter and Candidatus Methanomethylophilus were significantly associated with Gastranaerophilales and Prevotellaceae, respectively in the low CH4 network. These interactions were absent in the high CH4 network. This suggests that the interactions of the low CH4-associated microbiome members and methanogens contributes to the reduced CH4 emissions. The findings of our work begin to explain why some cattle emit higher methane levels compared to others, and may aid in finding solutions to reduce methane emissions in cattle while keeping their feeding efficiency and meat production high.
G-protein coupled receptors (GPCR) are a diverse group of cell surface receptors that bind ligands, undergo a conformational change, and initiate an intracellular signaling cascade through binding to a G-protein. The receptor group binds to molecules of a vast chemical space and is known to have regulatory role in functions ranging from growth sensation to hormone responses. This research investigates the chemical environment and hardness of GPCR active sites through protein visualization, electronic structure calculations, and experimental docking analysis using molecules from chemical informatics database with known inhibitory potentials. Based on the hard-soft acid-base principle, it is hypothesized that the GPCR active site is predominately soft in nature due to its location within the cell membrane; however, several critical polar residues likely optimize ligand orientation. Characterization of this chemical environment will inform future drug design and research to optimize inhibition potential of GPCR receptors.
This research looks to investigate environmental and substituent effects on nitrogen-donor-SO3 complexes utilizing a combination of theory and experiment, including quantum chemistry calculations and low temperature matrix-isolation and spectroscopy. The first step is to explore various computational methods and basis sets to provide structural information that is compared to experimental data. For CH3CN-SO3, we have identified a few reliable theoretical methods through an extensive validation study based on predicting the experimental structure and vibrational frequencies of SO3 using a wide range of available computational methodologies. Using these, we have determined the eclipsed confirmation to have a larger binding energy, shorter N-S bond length, compared to the staggered confirmation, and it lacks imaginary frequencies. In addition to minimum-energy structures, we have also obtained information on vibrational frequencies, binding energy, and bond length in various dielectric media for CH3CN-SO3 and mapped potential curves along the N-S bond lengths. We will continue to collect information on binding energies across methods and basis sets to verify which perform the best to be used for future compounds such as ClCH3CN-SO3 and FCH3CN-SO3 and eventually compare our computations to experimental data from our laboratory.
Organic–inorganic composite films of close-packed, alkanethiol-capped gold nanoparticles and dithiol crosslinkers were assembled at the air–water interface in a Langmuir trough. Mechanical properties were evaluated using Langmuir compression isotherms, providing minimum collapse pressures and qualitative collapse behavior to compare film stability. The data indicate that increased crosslinker rigidity can enhance resistance to collapse relative to flexible linkers, supporting structure–property design criteria for durable nanoparticle films. These results motivate continued measurements to refine component-specific trends and guide the design of nanoarchitectures with targeted chemical, physical, and mechanical properties.
In today’s setting of biomolecular research, it is important that researchers have a large array of different tools at their disposal to further our understanding of the way in which biomolecules interact with each other. One tool that shows incredible promise in this aspect is Raman spectroscopy. What makes Raman spectroscopy special is its ability to provide detailed information at the molecular level of almost any form of sample, including aqueous(in water) samples, such as saliva, or other biological fluids; this is unlike other more widely used forms of atomic investigation such as infrared spectroscopy, which struggles with the interference of water in its signal. The work of this project is focused on investigating how Raman spectroscopy can be used to investigate biomolecules in aqueous and/or biological media, in our case for the detection of cancer biomarkers in saliva, as well as the effect of crowding on functional proteins. Based on the work already completed, the use of Raman spectroscopy seems promising, as it has provided clean spectra for both saliva samples for detection of cancer biomarkers, as well as for a number of amino acid and protein samples (proline, tryptophan, bovine serum albumin, and prolyl-tRNA synthetase) in the presence polyethylene glycol (PEG 8k) as a crowding agent. The preliminary results of our research will be presented.
Many enzymatic studies aimed at understanding the structure–function–dynamics relationship are conducted under dilute conditions. However, the intracellular environment is highly crowded with biomolecules of varying shapes, sizes, and chemical properties, which can impact a protein's structure and thereby its function. This discrepancy between scientific study and real-world data can lead to incomplete or misleading conclusions about enzyme behavior in vivo. In the proposed study, we investigate the effects of molecular crowding on Escherichia coli Prolyl-tRNA Synthetase (Ec ProRS), a multidomain enzyme responsible for catalyzing the ligation of proline to tRNAPro during protein biosynthesis. To observe cellular crowding, we employ Atomic Force Microscopy (AFM), a high-resolution scanning probe technique capable of producing nanometer-scale topographic images. AFM enables both qualitative and quantitative analysis of protein samples. Qualitative insights, such as surface roughness and clustering, can reveal structural changes due to crowding, while quantitative measurements of height, area, and volume provide a deeper understanding of protein stability and conformational shifts because of crowding. In this study, we analyze the impact of various crowder molecules, including protein-based crowders (bovine serum albumin and lysozyme) and synthetic polymers, such as polyethylene glycol 20k, on the structure of Ec ProRS. In addition to observing protein crowding, we will present comparative results of AFM studies conducted in air versus in aqueous phase. This approach aims to bridge the gap between conventional dilute-condition studies and the complex, crowded environments in which enzymes naturally operate, offering a more physiologically relevant perspective on enzyme structure and function.
Extradiol dehydrogenases are known to convert catechol into muconic semialdehydes. These muconic semialdehydes and their derivatives serve as precursors for the synthesis of nylon and other key building blocks. However, catechol derivatives are unstable, have limited commercial availability, and are challenging to synthesize due to the presence of titratable OH groups. Conversely, precursor salicylaldehydes are commercially available, simple to modify by cross-coupling reactions, and can be converted to catechols via the Dakin oxidation. Therefore, optimizing a reaction scheme utilizing salicylaldehydes to produce catechol in vitro can more effectively create valuable precursors. HAPMO (4-hydroxyacetophenone monooxygenase), was found to perform a non-native Dakin reaction on 4-fluorosalicylaldehyde to make 4-fluorocatechol. However, no other substrates have been tested in this reaction, and no downstream reactions have been demonstrated. We have found that, when used in an enzymatic cascade with BphC, an extradiol dehydrogenase, HAPMO can be used to create muconic semialdehydes. In this work, we are optimizing semialdehyde production, and screening different salicylaldehydes in the reaction, with a particular focus on preparative scale conditions. Preliminary results suggest that this can be reasonably achieved with wild type HAPMO. These findings will be leveraged to further explore the utility of these catalysts for building block synthesis.
In synthetic chemistry, the generation of reactive building block materials is critical to producing complex materials, like natural products and pharmaceuticals. To produce wide varieties of these building blocks, the starting materials must be reasonably amenable to divergent synthesis, wherein one compound can be converted to a diverse array of materials in few steps. One class of underexplored synthetic building blocks are catechols, which are key components of numerous valuable compounds. However, catechols remain a challenging starting material to access, as they are prone to oxidation, and difficult to modify due to the acidic 1,2-diol moiety. In contrast, salicylaldehydes can be diversified without protection procedures through cross-coupling reactions to generate a library of catechol precursors. We have identified an enzyme called HAPMO, which performs a Dakin oxidation to generate catechol from salicylaldehyde. HAPMO reactivity is underexplored and has only been shown for fluorinated derivatives. In this work, we synthesized a small library of potential salicylaldehyde substrates with unique substituents to probe the steric and electronic limitations of HAPMO. We have also begun testing substrates in reactions with purified HAPMO. The results of this study will inform future synthesis of salicylaldehyde substrates, and further studies on the native reactivity of HAPMO.
Viral RNA sensing by human RIG-I-like Receptors (RLRs) is a key innate immune function in all cells. Activation of the RLR MDA5 by viral double-stranded RNA (dsRNA) is coupled with ATP hydrolysis and leads to the expression of genes encoding Type I Interferons (IFNs). In response, viral genomes have evolved to encode proteins that inhibit or weaken the Type I IFN response pathway via inhibition of RLR function. Here we aim to identify whether Nodamura virus protein B2 (NoV-B2), a viral dsRNA-binding protein, inhibits MDA5 in vitro. Human MDA5 and NoV-B2 were expressed exogenously in E. coli and purified by affinity and ion exchange chromatography. The RNA-dependent ATPase activity of MDA5 was measured in vitro by the colorimetric Malachite Green Phosphate Assay using poly(I:C) as a mimic of viral dsRNA. We then assayed this activity with NoV-B2 present to measure inhibition in vitro. Future directions for this project include: (1) investigating the mechanism of inhibition using a mutant NoV-B2 that cannot bind dsRNA, and (2) testing other viral proteins that may inhibit MDA5. These experiments help elucidate one of the mechanisms of inhibition of an immune response during viral infection.
Comparing the biochemical activity of Methylobacterium extorquens AM1 grown in separate medias with La3+ and Ca2+ as cofactorsof methanol dehydrogenase (MDH). Recent studies have demonstrated that some enzymes in bacteria isolated from lanthanide-richareas use lanthanides as metal cofactors in place of more common metals like calcium and that these lanthanide-enzymes haveenhanced catalytic properties. The bioelectrocatalytic activity of MDH from M. extorquens grown in La3+ rich media is compared toMDH from M. extorquens grown in typical Ca2+ rich media. A coupled assay of phenazine methosulfate-dichlorophenolindophenol isperformed to determine the enzyme activity. Different redox polymer films have been tested to determine the optimal film toimmobilize the bacteria while still allowing bioelectrocatalysis to be performed. The bioelectrochemical activities from these bacteriahave not previously been compared. If La3+ grown M. extorquens has higher bioelectrochemical activity than Ca2+ grown M.extorquens, then improved biofuel cells and sensors can be created.
