ABSTRACT: Microbial decomposition of carbon and biogenic methane in coal is one of the most important issues in CBM exploration. Using metagenomic technologies, the microbial C-N-S functional genes in different hydraulic zones of high-rank coal reservoirs were systematically studied, demonstrating the high sensitivity of this ecosystem to hydrodynamic conditions. The results show that the hydrodynamic strength of coal reservoir #3 in the Shizhuangnan block gradually weakened from east to west, forming a transitional feature from a runoff area to a stagnant area. Compared with runoff areas, stagnant areas have higher reservoir pressure, gas content, and ion concentrations. The relative abundance of genes associated with C, N, and S cycling increased from the runoff area to the stagnant area, including cellulose-degrading genes (e.g., cellulose 1,4-beta-cellobiosidase), methane metabolism genes (e.g., mcr, fwd, mtd, mer, and mtr), N-cycling genes (e.g., nifDKH, amoB, narGHI, napAB, nirK, norC, and nosZ), and S-cycling genes (e.g., dsrAB, sir, cysN, sat, aprAB, and PAPSS). This indicates that the stagnant zone had a more active microbial C-N-S cycle. The machine learning model shows that these significantly different genes could be used as effective indices to distinguish runoff and stagnant areas. Carbon and hydrogen isotopes indicate that methane in the study area was thermally generated. Methanogens compete with anaerobic heterotrophic bacteria to metabolize limited substrates, resulting in a low abundance of methanogens. In addition, the existence of methane-oxidizing bacteria suggests that biogenic methane was consumed by methanotrophic bacteria, which is the main reason why biogenic methane in the study area was not effectively preserved. In addition, weakened hydrodynamic conditions increased genes involved in nutrient cycling, including organic matter decomposition, methanogenesis, denitrification, and sulfate reduction, which contributed to the increase in CO2 and consumption of sulfate and nitrate from runoff areas to stagnant areas.
