New technique allows detailed study of partnerships between different microbes

Jim Crocker
17th January, 2026

New technique allows detailed study of partnerships between different microbes

Standard proteomic analysis shows that the high abundance of proteins from the alga Chlamydomonas reinhardtii in coculture suppresses the detection and measured abundance of proteins from the bacterium Mesorhizobium japonicum (b, c), creating a methodological artifact where the majority of bacterial proteins falsely appear to be downregulated (e).

Image adapted from: Dupuis et al. / CC BY (Source)

Key Findings

  • Studying interactions between algae and bacteria in coculture is challenging due to differences in cell size and abundance, leading to biased protein detection
  • A new “mono-mix” control, combining algal and bacterial proteins in proportions similar to coculture, improves the accuracy of bacterial protein detection
  • Combining the mono-mix strategy with sample fractionation significantly increases the number of detected bacterial proteins and reveals more accurate changes in protein abundance during symbiosis
Understanding how different organisms work together – symbiosis – is crucial for comprehending life on Earth, particularly how vital processes like nutrient cycling occur. A significant challenge in this field is accurately studying these interactions at a molecular level, especially when the organisms involved are very different in size and intimately connected. Researchers at UC Berkeley, the California Institute for Quantitative Biosciences, Pacific Northwest National Laboratory, and Lawrence Berkeley National Laboratory tackled this problem in a recent study[1], focusing on the well-known relationship between the single-celled alga Chlamydomonas reinhardtii and the bacterium Mesorhizobium japonicum. The study aimed to identify changes in protein levels within both organisms as they interact, hoping to reveal the mechanisms driving their symbiotic relationship. Proteins are the workhorses of cells, and measuring their abundance provides insights into what each organism is doing. However, a major obstacle arose when analyzing the data. Because the alga is far more abundant than the bacterium in the co-culture (where both organisms grow together), the sheer volume of algal proteins overwhelmed the detection system, making it difficult to accurately identify and quantify bacterial proteins. This led to many false positives – proteins that appeared to decrease in abundance simply because they were harder to detect, not because their levels had actually changed. This issue highlights a fundamental problem in biological research: when studying interacting species, the more dominant organism can mask the signals from the less abundant one. Standard methods for analyzing protein data, called differential expression analysis, rely on comparing protein levels between different conditions (in this case, algae alone versus algae and bacteria together). But if detection is biased, the results can be misleading. To overcome this, the researchers developed two key strategies. First, they created a “mono-mix” control. This involved combining algal and bacterial proteins in a test tube at the same relative proportions as found in the co-culture. By comparing the co-culture to this mono-mix, they ensured that bacterial proteins were detectable at similar levels in both samples, eliminating the detection bias. Second, they used a technique called sample fractionation, which separates proteins into different groups before analysis. This helped to concentrate the less abundant bacterial proteins, making them easier to identify. Combining these approaches allowed the team to accurately compare nearly 10,000 algal proteins and over 4,000 bacterial proteins. They successfully confirmed expected changes in the bacterial proteome, such as an increase in proteins involved in sugar transport – consistent with the idea that the bacteria utilize sugars released by the algae. Importantly, they also discovered new proteomic responses in the bacteria that provide clues about the specific interactions occurring between the two organisms. These findings build on previous research demonstrating cooperation between different microbial species in nutrient exchange[2][3][4]. For example, studies have shown that arbuscular mycorrhizal fungi (AMF) rely on bacteria to access organic phosphorus, with the fungus providing carbon to the bacteria in return. The fungus Rhizophagus irregularis releases fructose, which stimulates the bacteria Rahnella aquatilis to release enzymes that break down organic phosphorus into a usable form for the fungus[2]. Similarly, another study showed that Rhizophagus irregularis gains nitrogen from chitin with the help of Paenibacillus sp., and that the presence of a protist further enhances this process[3]. The current study complements these findings by providing a more precise method for investigating the molecular mechanisms underlying such cross-kingdom interactions, addressing a significant methodological limitation in the field. The techniques developed in this study are broadly applicable to other symbiotic systems, offering a powerful new way to unravel the complex interactions that shape microbial communities and drive biogeochemical cycles.

BiotechGeneticsEcology

References

Main Study

1) Mono-mix strategy enables comparative proteomics of a cross-kingdom microbial symbiosis

Published 16th January, 2026

https://doi.org/10.1371/journal.pone.0340253

Related Studies

2) Signal beyond nutrient, fructose, exuded by an arbuscular mycorrhizal fungus triggers phytate mineralization by a phosphate solubilizing bacterium.

https://doi.org/10.1038/s41396-018-0171-4

3) Organic nitrogen utilisation by an arbuscular mycorrhizal fungus is mediated by specific soil bacteria and a protist.

https://doi.org/10.1038/s41396-021-01112-8

4) Cross-kingdom nutrient exchange in the plant-arbuscular mycorrhizal fungus-bacterium continuum.

https://doi.org/10.1038/s41579-024-01073-7


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