We are pleased to announce that an article co-authored by Łukasz Łaczmański, PhD, head of the Laboratory of Genomics & Bioinformatics, has been published in the journal Science of The Total Environment (IF 8.2; MNiSW 200).

Sobieraj K, Żebrowska-Różańska P, Siedlecka A, Łaczmański Ł, Białowiec A. Analysis of microbial community potentially involved in carbon monoxide production in compost and its functional assessment: Utilized pathways, enzymes, and genes. Sci Total Environ. 2025 Mar 10;968:178860. doi: 10.1016/j.scitotenv.2025.178860

Carbon monoxide (CO) is a valuable compound widely used in industry, and its biological production aligns with the bioeconomy principles. This study introduces a novel perspective by exploring biowaste composting as a potential source of CO production. Using 16S rDNA sequencing, microbial communities within two zones of a compost pile, with low (CO/L, 119 ppm) and high CO concentration (CO/H, 785 ppm), were characterized. The metabolic potential of microbial communities was investigated using PICRUSt2, an advanced tool for functional analysis. Results revealed higher alpha diversity in CO/H samples compared to CO/L, likely influenced by the lower temperature at the CO/H sampling site (50 °C vs. 62 °C in CO/L). Importantly, in the PCoA plots, samples clustered together depending on the sampling site. The microbial community composition was dominated by Bacilli (up to 98.8 % and 55.4 % of CO/L and CO/H samples, respectively). One of the key results was the detection of the Wood-Ljungdahl pathway, a metabolic route for CO production, in nearly all compost samples. This pathway was more abundant in CO/H samples (0.011-0.027 %) compared to CO/L samples (0.000-0.002 %). Moreover, 7 enzymes and 7 genes responsible for CO production and metabolism were detected in compost samples, suggesting that the observed CO formation is likely of biotic origin.
In the described project, the staff of the Genomics and Bioinformatics Laboratory of IITD PAS used the unique method developed for the identification of the 16S rRNA gene, together with bioinformatics analysis enabling quantification of microbial composition and analysis of metabolic pathways.

link to publication: https://doi.org/10.1016/j.scitotenv.2025.178860