(UB)
Research, Innovation and Economic Development
University at Buffalo (UB)
Research, Innovation and Economic Development
Research and Education in Energy,
Environment and Water
The RENEW Institute - A Multidisciplinary Initiative

Using the Rules of Antibiotic Resistance Development to Inform Wastewater Mitigation Strategies

Funding Agency: National Science Foundation

Collaborators: Diana Aga (PI, University at Buffalo); Adina Howe (Iowa State University); Laura Jarboe (Iowa State University); Liqing Zhang (Virginia Tech); Shannon Seneca (University at Buffalo)

Project Description: The increased prevalence of antimicrobial resistance (AMR) among bacteria threatens human, environmental, and agricultural health. When antibiotics no longer work, infections persist longer and pose a greater risk of death. Municipal wastewater treatment plants (WWTPs) are hotspots for the spread of AMR due to antibiotic residues, genes, and resistant bacteria. This project examines environmental factors, such as temperature, heavy metals, and contaminants, that influence AMR development. It combines field, lab, and computational studies to understand when resistant bacteria replace susceptible strains, helping develop models and strategies to prevent AMR proliferation. It also emphasizes education, poverty, and pollution, sharing knowledge with farmers, students, and stakeholders.

This research hypothesizes that environmental and genetic factors jointly influence the expression of antibiotic resistance genes (ARGs) and mutations. It suggests that the minimum selective concentration (MSC) of antibiotics promotes changes in resistance under conditions such as temperature shifts or the presence of chemical contaminants. The study will combine fieldwork, lab experiments, and computational methods to examine MSCs and factors affecting selection at sub-inhibitory antibiotic levels in microbial systems associated with WWTPs for two antibiotics.

The main goal of this research is to develop predictive models that explain how antibiotic resistance is selected within WWTP activated sludge systems for two representative antibiotics, and to investigate how environmental changes influence these selection processes.

This research aims to understand and apply the selection rules that shape antibiotic resistance in WWTPs, with four objectives. (1) model resistance cost–benefit dynamics at sub-inhibitory levels of ciprofloxacin and azithromycin using Escherichia coli K-12 MG1655, exploring temperature and chemical impacts; (2) map antibiotics, CECs, metals, and ARGs across WWTPs, simulating selection in lab conditions; (3) use machine learning to predict resistance dynamics, considering environmental factors such as metals, CECs, and temperature; and (4) develop educational materials to inform K–12 students, stakeholders, and policymakers about AMR and selection.

Recent Related Publications:

  1. Ahmed, S.; Emon, M.I.; Moumi, N.A.; Huang,L.; Zhou, D.; Vikesland, P.; Pruden, A.; *Zhang, L. ProtAlign-ARG: antibiotic resistance gene characterization integrating protein language models and alignment-based scoring.Scientific Reports. 2025. 15(1):30174
  2. Abir, A.R.; Dip S.A.; *Zhang, L. UnCOT-AD: Unpaired Cross-Omics Translation Enables Multi-Omics Integration for Alzheimer's Disease Prediction. Briefings in Bioinformatics. 2025. 26 (4): bbaf438
  3. Moumi, N.A.; Ahmed, S.; Brown, C.; Pruden, A.; *Zhang, L. ARGContextProfiler:extracting and scoring the genomic contexts of antibiotic resistance genes using assembly graphs. Frontiers in Microbiology. 2025.16:1604461
  4. Emon, M.I.; Cheung, Y.F.; Stoll, J.; Rumi, M.A.; Brown, C.; Choi, J.M.; Moumi, N.A.; Ahmed, S.; Song, H.; Sein, J.; Yao, S.; Khan, A.; Gupta, S.; Kulkarni, R.; Butt, A.; Vikesland, P.; Pruden, A.; *Zhang, L. CIWARS: a web server for antibiotic resistance surveillance using longitudinal metagenomic data. Journal of Molecular Biology. 2025. 437. 169159