1. Comparative genomics and CRISPR-CCas9-mediated editing of antibiotic resistance genes in clinically relevant bacterial isolates 2. Microbiome dynamics and metabolomic profiling of gut pathogens under varying dietary interventions 3. Characterization of bacteriophage therapy potential against multi-drug resistant Klebsiella pneumoniae isolates 4. Evaluation of quorum sensing inhibitors to attenuate virulence in Pseudomonas aeruginosa biofilms 5. Metagenomic and functional profiling of soil microbiota in bioremediation of hydrocarbon-contaminated sites 6. Development of rapid CRISPR-based diagnostics for detection of pathogenic enteric bacteria 7. Antimicrobial peptides from environmental samples: isolation, mechanism of action, and therapeutic potential 8. In vitro and in vivo assessment of probiotic strains for modulation of inflammatory gut diseases 9. Transcriptomic analysis of bacterial stress responses to metal nanoparticles 10. Exploring bacteriophage-host interactions in dairy-associated Listeria monocytogenes strains 11. Characterization of antimicrobial resistance plasmids in wastewater microbiomes 12. Isolation and genomic analysis of extremophilic fungi and their antimicrobial properties 13. Assessing the impact of CRISPR-Cas systems on virulence factor regulation in Staphylococcus aureus 14. Functional metagenomics of air microbiomes in urban environments and health implications 15. Development of a biosensor-based toolkit for rapid detection of environmental pathogens

Project Abstract

This study integrates comparative genomics, CRISPR-Cas9–mediated genome editing, microbiome dynamics, metabolomics, and functional metagenomics to elucidate the determinants of antibiotic resistance, virulence, and pathogen fitness across clinically relevant bacterial isolates, gut ecosystems, and environmental settings. We will (i) construct a pan-genomic framework for key multidrug-resistant taxa to identify resistance determinants, mobile genetic elements, and CRISPR-Cas system configurations, and (ii) employ CCas9 engineering to precisely edit resistance genes to validate causative roles in phenotype expression, fitness costs, and horizontal transfer potential under clinical-relevant conditions. Parallel metagenomic and 1H-NMR/LC-MS metabolomic analyses of gut microbiota under controlled dietary perturbations will map dynamic ecological interactions that modulate pathogen colonization, resistance gene abundance, and metabolite signatures linked to host inflammatory responses. The bacteriophage therapy component will characterize lytic phages and phage cocktails targeting Klebsiella pneumoniae, assessing adsorption efficiency, resistance development, and synergy with conventional antibiotics in biofilm and planktonic states. Quorum sensing inhibitors will be evaluated for their capacity to disrupt Pseudomonas aeruginosa biofilm maturation and virulence gene expression, integrating transcriptomic profiling to reveal network rewiring and potential compensatory pathways. Soil metagenomics and functional assays will reveal microbial community shifts and hydrocarbon degradation pathways in contaminated sites, identifying keystone taxa and metabolic networks that enhance bioremediation while mitigating resistance gene reservoirs. The rapid CRISPR-based diagnostics module will develop and validate multiplexed, point-of-need assays for enteric pathogens, emphasizing sensitivity, specificity, and robustness in complex matrices. A library of antimicrobial peptides derived from environmental sources will be screened for antibacterial spectrum, membrane disruption mechanisms, and synergy with existing antimicrobials. Probiotic candidates will be screened in vitro for anti-inflammatory properties and in vivo efficacy in murine colitis models, with microbiome and host transcriptomic readouts guiding mechanistic interpretation. Transcriptomic responses of bacteria to metal nanoparticles will inform stress adaptation and resistance potential. Additional themes include CRISPR-Cas regulation of virulence determinants in Staphylococcus aureus and the interplay between phage-host dynamics in dairy-associated Listeria monocytogenes, integrating data across hosts and environments. Data integration through machine learning will identify predictive markers of resistance and virulence, enabling risk assessment and targeted interventions. The project aims to deliver actionable insights into resistance gene control, pathogen containment, and environmental bioremediation strategies, with translational potential for diagnostics, therapeutics, and public health surveillance.

Project Overview

What This Project Is About

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This project combines genetics, microbiology, and environmental science to explore how bacteria change and interact with their surroundings. It looks at antibiotic resistance, gut microbes, viruses that infect bacteria (bacteriophages), how tiny communications signals control bacterial behavior, and new quick diagnostic tools. The aim is to understand threats to health and find practical ways to study, prevent, or treat them in simple, approachable terms.

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The Problem It Addresses

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Objectives of the Project

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1. Understand how bacteria share and modify resistance genes using simple genome comparisons.
2. Explore how diet changes gut microbes and their chemical signals in a non-technical way.
3. Assess whether bacteriophages can target drug-resistant bacteria effectively.
4. Test compounds that block bacterial communication to reduce their harmful behavior.
5. Investigate how soil microbes help clean up hydrocarbon pollution.
6. Learn to create rapid tests that can detect dangerous gut bacteria.
7. Isolate and study natural antimicrobial agents from environmental sources.
8. Evaluate probiotics for balancing inflammatory gut conditions in lab models.

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What You Will Do Step by Step

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Review background literature; collect simple samples or data; perform basic genome comparison; test digestion or growth under dietary changes; trial phage activity in safe models; screen anti-quorum sensing compounds; analyze soil microbial data; prototype a quick diagnostic assay; extract potential natural antimicrobials; test probiotic effects in basic tests.

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Expected Outcome