Browsing by Author "Tabor, Jeffrey"

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    Antimicrobial Peptides Activity and Efficacy Prediction by Stochastic Models and Machine Learning Methods
    (2024-04-25) Nguyen, Thao; Kolomeisky, Anatoly; Onuchic, José; Tabor, Jeffrey
    The development of new antimicrobial drugs is becoming more urgent than ever due to the rapid emergence of antibiotic resistance and limitations in bacteria targets. A promising alternative that received considerable scientific attention is antimicrobial peptides (AMPs), also known as host defense peptides. In this work, we aim to facilitate the design of more effective peptides using computational tools by solving the following two main challenges in the field. First, the underlying microscopic mechanisms of how AMPs interact with bacteria and other pathogens remain inadequately understood. Second, the infinite possibilities in engineering new peptides is a time-consuming task. We developed a theoretical framework for the interactions of AMPs and bacteria on the single-cell and population levels. We also investigated the effect of AMP cooperativity on efficacy as measured by minimal inhibitory concentrations (MIC), fractional inhibitory concentrations (FIC), and our acceleration parameter R by looking at cases with 1, 2, 3, and eventually an arbitrary number m types of AMPs. Our results explained the broad concentration spectrum where different types of AMP operate more optimally, offering a mechanistic explanation of the bacterial clearance dynamics and AMP cooperativity mechanisms. Increasing the number of AMP components in a mixture while keeping the total amount fixed enhances their synergistic activities, and strong cooperativity can be achieved for weak intermolecular interactions, providing a qualitative measure for the degree of cooperativity applicable in natural systems. We also used feature selection methods to build our machine learning pipeline to extract features that make peptides antimicrobial. This model produced decent accuracy with manual hyperparameter tuning, and the results can be applied to engineer better AMPs.
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    The Potential and Challenges of Control over Alginate Production in Pseudomonas fluorescens for Use in Agriculture
    (2024-06-06) Roleck, Caleigh; Tabor, Jeffrey
    Climate change is creating an urgent need for new technologies to allow agriculture to adapt to predicted increases in drought severity. Exopolysaccharides (EPS) and EPSproducing bacteria are one potential solution, as previous studies have found EPS-treated soil has higher water potential than soils without EPS at the same water content level, thus better facilitating movement of water into plant roots in drier soils. However, EPSproducing bacteria and other plant growth promoting bacteria suffer have inconsistent performance due to the complex regulation controlling these functions. Using synthetic biology to uncouple these functions from their native regulation and place them under synthetic, predictable regulation is one potential solution, though it is limited by the level of current knowledge of these complex traits and potential fitness burdens that would be detrimental to field colonization. I engineered the soil bacteria Pseudomonas fluorescens for control over transcription of algR, the transcription factor responsible for regulating transcription of the genes for biosynthesis of the EPS alginate. While the system is not well studied in P. fluorescens, the alginate biosynthetic and regulatory system is highly conserved with Pseudomonas aeruginosa, for which the current mechanism of alginate regulation relies heavily upon differential transcription of algR. However, differential expression of algR in P. fluorescens did not allow for alginate production. Transcriptomics reveals that, unlike in P. aeruginosa, only one of the alginate biosynthetic transcripts is upregulated with increased AlgR. However, the other transcript’s expression patterns at various concentrations of AlgR reveals potential transcription factor cross-talk, and several potential candidates were identified. Deciphering this complex regulatory landscape is key to controlling alginate production, as directly controlling expression of these two transcripts might not be a viable strategy. Alginate production is metabolically intensive and may result in a fitness burden, however, P. fluorescens differentially regulates several other metabolic genes, which could serve to alter overall cellular processes for sustainable alginate production. From this thesis, I establish that deciphering the unique regulation of P. fluorescens’ algD operon and the overall impact of AlgR on fitness are important next steps in developing soil Pseudomonas species to promote plant growth and resilience under drought.