An efficient way to classify soil microorganisms

A healthy soil microbiome supports climate regulation and food security. However, traditional methods for studying microorganisms within soil samples are often inefficient and can damage the cells.

Su et al. developed a precise, automated process for efficiently classifying soil microorganisms, the Automated Two-Level Enrichment System (ATLES).

“Extracting microorganisms from soil for metagenomic analysis is notoriously difficult due to the highly complex and heterogeneous structure of the soil matrix,” said author Zuxian Pan. “Efficient and gentle classification is essential because accurately profiling the soil microbiome is the foundation for understanding soil ecology, plant health, and broader environmental impacts.”

Pan describes ATLES as a continuously self-cleaning sieve that uses a fluid pump to both circulate and unclog the membrane.

“Instead of pushing a messy soil mixture straight down a filter, which causes it to clog almost immediately, ATLES constantly sweeps the liquid across the surface of the membrane,” she said.

By consistently clearing the sievelike pores, ATLES allows its users to continuously sort large and small soil components — like fungi and bacteria, respectively — without damaging them. In tests, ATLES was able to separate bacteria smaller than 2 micrometers from fungi larger than 3 micrometers about 30% of the time, though the researchers say this can be further improved by increasing the device’s capacity.

The authors are working to make ATLES field-deployable and hope it will become a standard tool in real-time analyses ranging from agriculture to ecology for assessing soil health, tracking microbiomes, and studying pathogens.

Source: “An automated two-level system for size-based enrichment of soil microbiomes,” by Hengxiang Su, Zuxian Pan, Fangzhou Zhang, Yi Zhou, Bo Liu, and Shilun Feng, Nanotechnology and Precision Engineering (2026). The article can be accessed at https://doi.org/10.1063/5.0322089 .