# Metabolic and Microbial Community Profiles of Century-Old Pu-Erh Tea: An Integrative Metabolomic and Microbiomic Analysis

## TL;DR

This study explores how century-old Pu-erh tea changes over time by analyzing its chemical and microbial makeup, revealing unique flavor compounds and microbial shifts.

## Contribution

The study provides new insights into the microbe-metabolite co-evolution in century-old Pu-erh tea using integrated metabolomic and microbiomic analysis.

## Key findings

- Long-term aging enriches hydrolyzable tannins, sucrose, and bipyrrole aromatic derivatives in century-old Pu-erh tea.
- Century-old samples show simplified bacterial communities and increased fungal evenness, with enrichment of Thermodesulfobacterium and unclassified fungi.
- Key bacterial genera like Paenibacillus and Bacillus correlate with flavor precursors such as sugars and phenolic acids.

## Abstract

As a uniquely Chinese post-fermented tea, Pu-erh tea undergoes profound changes in quality and flavor during aging, a process primarily driven by microbially mediated metabolic transformations. However, the patterns of microbe–metabolite co-evolution spanning a century-long timescale remain unclear. This study employed three samples—S (1920 raw Pu-erh tea), Y (1999 raw Pu-erh tea), and Q (2024 ripe Pu-erh tea)—integrating non-targeted metabolomics and microbiomics technologies to systematically analyze the characteristics of metabolites and microbial communities in century-old Pu-erh tea. The study elucidated the metabolic characteristics at the endpoint of long-term natural aging: the specific enrichment of hydrolyzable tannins, sucrose, and bipyrrole aromatic derivatives, providing a chemical basis for its unique “century-old charm”. Microbial community analysis indicated that long-term aging leads to simplified bacterial communities but increased fungal evenness, with the century-old sample specifically enriching for Thermodesulfobacterium and a large number of unclassified fungi. Multivariate statistics further constructed a microbe–metabolite interaction network, confirming significant correlations between key bacterial genera such as Paenibacillus and Bacillus and flavor precursors like sugars and phenolic acids.