AI Article Synopsis
- A new method has been developed for large-scale characterization of proteins in wastewater, focusing on non-microbial proteins.
- This approach reveals distinct protein profiles at different collection sites, likely influenced by local human populations and industrial activities.
- The research suggests that wastewater proteomics could lead to new health and environmental biomarkers and improve monitoring methods for public health and industrial impacts.
Article Abstract
Classically, the characterization of wastewater components has been restricted to the measurement of indirect parameters (chemical and biological oxygen demand, total nitrogen) and small molecules of interest in epidemiology or for environmental control. Despite the fact that metaproteomics has provided important knowledge about the microbial communities in these waters, practically nothing is known about other non-microbial proteins transported in the wastewater. The method described here has allowed us to perform a large-scale characterization of the wastewater proteome. Wastewater protein profiles have shown to be very different in different collection sites probably reflecting their human population and industrial activities. We believe that wastewater proteomics is opening the doors to the discovery of new environmental and health biomarkers and the development of new, more effective monitoring devices for issues like monitorization of population health, pest control, or control of industry discharges. The method developed is relatively simple and combines procedures for the separation of the soluble and particulate fractions of wastewater and their concentration, and conventional shotgun proteomics using high-resolution mass spectrometry for protein identification. •Unprecedented method for wastewater proteome characterization.•Proteins as new potential biomarkers for sewage chemical-information mining, wastewater epidemiology and environmental monitoring.•Wastewater protein profiles reflect human and industrial activities.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10579522 | PMC |
| http://dx.doi.org/10.1016/j.mex.2023.102403 | DOI Listing |
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