Lisa Fetter*, Anna Nguyen, Marlea Kudlauskas, Jena Jacobs, Jessica Daniel*, Aviva Bulow, Susan Jett*, Derek Clark, Jonathan Richards*, Laura Roon*, Kathryn Norquest*, Stephen Schaffner*, Ryan Masterson*, Ilia Mazin, Nazar Dubchak, Ryan Warren, Tonya Santaus, Kyra Brandt, Elina Baravik*, Josh Sowick, Becky Addison, Jody Stephens*, Yerelsy Reyna*, Jeremy O’Brien, Travis Ingraham, Matthew Stoddard, Morgan Miller, Amanda Faux, Mason Preusser, Sarai Graves, Tiffany Ashbaugh, Michael McCoy, Ebony Miller
(* denotes a researcher with a publication from the lab)
Dr. Andrew J. Bonham
Associate Professor of Chemistry
Dr. Bonham’s Curriculum Vitae
Dr. Bonham’s work focuses on understanding and investigating Transcription Factors, essential human proteins that regulate the bodies growth and response to disease. These transcription factors are essential components of gene regulation, and there is great interest in probing their presence and activity in both academic analysis and clinical diagnostics. Current methods to address these questions are often time-intensive or require specialized reagents, such as antibodies. At Metropolitan State University of Denver, Dr. Bonham is leading an innovative undergraduate research program focused on engineering new tools for sensitive and quick detection of TF:DNA interactions.
Lab Member 2016-
Project: Creation and Characterization of Gold-Nanoparticle Containing Conductive Scaffolds for Culturing Cardiomyocytes
Cardiomyopathies, diseases of the heart, are one of the major causes of death in the United States, and thus there is great interest in preventing and treating these complications. However, due to the nature of limited availability of donors, many techniques and solutions are inadequate to meet the needs of the field. In particular, heart tissue transplantation, culturing human tissues/tissue-derived cells and tissue engineering, and finding a suitable extracellular environment that closely resembles the natural environment of cardiomyocytes in vivo are difficult to attain. As such, a great deal of work has gone into efforts to produce polymers which mimic the natural cell environment in properties such as binding sites, stiffness, reactivity, and hydration. In our research, we are investigating the development and characterization of conductive polymer scaffolds providing cardiac tissue support, which will ideally aid in culturing cardiomyocytes for academic, research, and medical use. The core of our model is the incorporation of conductive gold nanorods into reverse thermal gel polymers. Synthesized gold nanorods utilized in this procedure are made with a high aspect ratio, at high purity and with defined surface functionalization. These conducting scaffolds should properly accommodate cardiac cells in building functional cardiac tissue constructs and further improving cell retention, spreading, homogenous distribution of cardiac specific markers, cell-cell coupling and synchronized beating behavior at the tissue level. The nanoparticles have been synthesized, then covalently coupled into these scaffolds, resulting in order-of-magnitude increases in conductivity. The goal of this work aims to improve cardiac tissue engineering, so that it can be directed to ultimately repairing damaged heart muscle and improve overall cardiac function in cardiovascular diseases whether they have been acquired from past medical complications or developed through hereditary traits.
Mycoplasma bacteria are highly infectious agents of human disease and laboratory contamination. For example, Mycoplasma pneumonia infects almost two million people every year with contagious upper respiratory infections also known as atypical or ‘walking pneumonia’. In addition to human disease, Mycoplasma is a major source of contamination of laboratory human cell cultures. However, current methods of detection for Mycoplasma strains, such as molecular-based assays, PCR and serological analysis, are time consuming, expensive, and less suitable for working under stringent conditions such as extreme temperature or pH. To provide a rapid and accurate alternative, we have focused on detecting the presence of Mycoplasma with a diagnostic electrochemical biosensor that detects lipoprotein P48, which is shed from the surface of several strains into the surrounding blood serum or growth media. This biosensor is based on a previously identified DNA aptamer that binds to the secreted P48 protein with high affinity. We have expressed P48 recombinantly in E. coli to serve as a positive control, and our results show rapid and sensitive binding of the target, as well as convenient electrochemical signaling from these binding events. This approach will allow us to potentially improve both prevention and diagnosis of Mycoplasma in cell culture platforms as well as patients who present a proposed infection.
Mycobacterium Tuberculosis (TB) is one of the world’s most prevalent bacterial pathogens. It is estimated that almost 10 million cases of TB emerge every year, and roughly one-fifth of these cases are fatal. The current detection and diagnosis of TB is done primarily via two methods; the TB skin test and the TB blood tests. Neither of these tests can differentiate between latent TB infection and TB disease. In order to differentiate these states, time-consuming sputum tests are required, which rely on culturing the mycobacterium. Designing a sensitive serologic biosensor would dramatically decrease the time line of diagnosis and therefore improve patient outcomes. One possible avenue for improved detection lies in the cell wall of TB, which includes many complex glycolipids—many of which are believed to have immunopathogenic mechanisms in physiologic pathways. Mannose-capped lipoarabinomannan (ManLAM) is one of the most prevalent of these glycolipids, and presents a novel target as a bio-marker for the sensitive detection of TB and related Mycobacterium strains. Here, we have utilized an existing aptamer sequence that binds to ManLAM to generate a sensitive electrochemical, DNA-based biosensor for the detection of TB. This biosensor is able to adopt multiple different folded conformations, only one of which presents the core aptamer sequence in a state capable of binding ManLAM. An appended redox-active tag (methylene blue) generates a measurable difference in electrochemical current upon this conformational change, providing a sensitive and quantitative measurement of ManLAM concentration. Such biosensors may ultimately allow rapid, on site, diagnosis of TB infection within the time constraints of patient-doctor interaction.
Electrochemical biosensors based on the conformational dynamics of DNA aptamers have found success against a wide variety of proteins, toxins, antibodies, and heavy metals. However, the mechanistic underpinnings of the mechanism by which these surface-bound DNA molecules change conformation upon target binding, thus changing the dynamics of an appended redox-active tag and generating a measurable signal, is poorly understood. Our first target for investigation was a previously reported Ricin Chain A binding atamer biosensor. Here, we have investigated this biosensor using a variety of nucleic acid assays, including PCR-termination via basepair modification, fluorescence anisotropy, gel mobility shift assays, and FRET tagging to determine 3D orientation. These have allowed us to better characterize the basepair interactions involved in binding targets, as well as offer clues to the changing three dimensional folded structures of these biosensors. These results will help inform the field of biosensors and aptamers in general on strategies for future optimization.
Oligonucleotide-based biosensors have been demonstrated as effective tools for detecting heavy metals, small molecule drugs, and protein targets. Recent efforts to move these biosensors from the lab bench to practical use in industry and medicine rely on the ability to rapidly and effectively adapt them to detect new targets of interest. One compelling aspect of DNA and RNA-based biosensors is the great strides that have been made in computational prediction of the three-dimensional structures that they can assume. However, interpreting predicted structures and using that knowledge to design functional biosensors ab initio remains a challenging problem. We hypothesize that by representing a potential DNA biosensor as a node-weighted graph, we can simplify the challenge of automated structure interpretation and sorting. If correct, this would allow a researcher to provide a core sequence of interest (such as a DNA recognition element or artificially-selected aptamer) and have a software tool design the ideal DNA biosensor for the sensitive detection of that target. This process builds on ideas from our oligionucleotide fold scoring algorithm, Fealden. With this new implementation of Fealden, we are achieving significantly more flexibility, allowing us to analyze any structure type. Because of this we are able to traverse a search space of tens of thousands of possible sequences to determine a “best candidate” biosensor. Additionally, with this increased flexibility we hope to implement some very desirable features in our software, generally, different types of design constraints that a researcher can specify for their biosensor.