| Affiliations: | Aggie Research Mentoring Program |
| Project Leader: | Aakansha Shaji, aakanshashaji@tamu.edu Chemical Engineering |
| Faculty Mentor: | Pushkar Lele, Ph.D. |
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Meeting Times:
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TBA |
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Team Size:
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4
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| Open Spots: | 0 |
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Special Opportunities:
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The candidates selected for our team will have the opportunity to gain hands-on experience with immune cells and bacterial culture techniques, molecular biology and genetic modification (PCR, DNA extraction), microscopy, and image and particle tracking algorithms (MATLAB). Candidates will gain experience in working with projects involving single-cell analysis, nanobiotechnology and molecular biology tools, and big data processing techniques to develop antibacterial technologies and cancer therapeutics. Candidates will receive opportunities to present their research findings at scientific workshops (e.g., TAMU Student Research Week). |
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Team Needs:
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-Our team is looking for candidates with broad interests in our research (http://pushkarlelelab.org/), who are eager to learn, have good organizational and communication skills, and are committed. A background in laboratory work, coding, and/or MATLAB are desired but not required. A minimum of 3-6 hours per week (depending on student objectives) are required. Ideally, candidates will join our lab for a duration longer than a semester or two |
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Description:
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The main project examines how bacteria evade our immune systems during an infection. We will test our central hypothesis that bacteria employ molecular sensors to detect chemical signatures from immune cells to escape these predatorial systems. To investigate, we will characterize the interactions between motile bacteria and standard chemical entities that aid the cells escape from unfavorable environments. Results will be analyzed by developing mathematical models of predator-prey systems. We will quantify the antibacterial efficacy and the ability of our natural immune systems to camouflage based on these characterizations. We will then compare these natural antibacterial systems with currently available industrial antibacterials to improve product design. We also propose to test different products for their effectiveness in curbing antibiotic resistance in microbes. Experimentation will involve genetic modifications of the model species Escherichia coli, EPA-based characterization of antibacterial activity against pathogenic bacteria, analysis of fluorescence and phase microscopy data with MATLAB algorithms, developing designs for 3D printing (CAD software) and microfluidics |