# Wastewater metaproteomics: tracking microbial and human protein biomarkers

## TL;DR

This paper introduces a wastewater metaproteomics method to track microbial and human proteins, revealing health indicators and microbial communities in urban areas.

## Contribution

A novel wastewater metaproteomics approach with efficient protein extraction and a customized data-processing pipeline is developed.

## Key findings

- A core microbiome including gut bacteria and potential pathogens was identified in wastewater.
- Nearly 200 human proteins, including health indicators like immunoglobulins and cancer-related proteins, were detected.
- The method enables comprehensive metaproteomic coverage through de novo sequencing and customized databases.

## Abstract

Wastewater-based surveillance has become a powerful tool for monitoring the spread of pathogens, antibiotic resistance genes, and measuring population-level exposure to pharmaceuticals and chemicals. While surveillance methods commonly target small molecules, DNA, or RNA, wastewater also contains a vast spectrum of proteins. However, despite recent advances in environmental proteomics, large-scale monitoring of protein biomarkers in wastewater is still far from routine. Analyzing raw wastewater presents a challenge due to its heterogeneous mixture of organic and inorganic substances, microorganisms, cellular debris, and various chemical pollutants. To overcome these obstacles, we developed a wastewater metaproteomics approach including efficient protein extraction and an optimized data-processing pipeline. The pipeline utilizes de novo sequencing to customize large public sequence databases to enable comprehensive metaproteomic coverage. Using this approach, we analyzed wastewater samples collected over approximately three months from two urban locations. This revealed a core microbiome comprising a broad spectrum of microbes, gut bacteria and potential opportunistic pathogens. Additionally, we identified nearly 200 human proteins, including promising population-level health indicators, such as immunoglobulins, uromodulin, and cancer-associated proteins.