Abstract
Almost nothing is known about the activities and diversities of microbial communities involved in As methylation in arsenic-rich shallow and deep sediments; the correlations between As biomethylation and environmental parameters also remain to be elucidated. To address these issues, we collected 9 arsenic-rich soil/sediment samples from the depths of 1, 30, 65, 95, 114, 135, 175, 200, and 223 m in Jianghan Plain, China. We used microcosm assays to determine the As-methylating activities of the microbial communities in the samples. To exclude false negative results, we amended the microcosms with 0.2 mM As(III) and 20.0 mM lactate. The results indicated that the microbial communities in all of the samples significantly catalyzed arsenic methylation. The arsM genes were detectable from all the samples with the exception of 175 m, and 90 different arsM genes were identified. All of these genes code for new or new-type ArsM proteins, suggesting that new As-methylating microorganisms are widely distributed in the samples from shallow to deep sediments. To determine whether microbial biomethylation of As occurs in the sediments under natural geochemical conditions, we conducted microcosm assays without exogenous As and carbons. After 80.0 days of incubation, approximately 4.5-15.5 μg/L DMAs(V) were detected in all of the microcosms with the exception of that from 30 m, and 2.0-9.0 μg/L MMAs(V) were detected in the microcosms of 65, 114, 135, 175, 200, and 223 m; moreover, approximately 18.7-151.5 μg/L soluble As(V) were detected from the nine sediment samples. This suggests that approximately 5.3, 0, 8.1, 28.9, 18.0, 8.7, 13.8, 10.2, and 14.9% of total dissolved As were methylated by the microbial communities in the sediment samples from 1, 30, 65, 95, 114, 135, 175, 200, and 223 m, respectively. The concentrations of biogenic DMAs(V) show significant positive correlations with the depths of sediments, and negative correlations with the environmental NH(4)(+) and NaCl concentrations, but show no significant correlations with other environmental parameters, such as NO(3)(-), SO(4)(2+), TOC, TON, Fe, Sb, Cu, K, Ca, Mg, Mn, and Al. This work helps to better understand the biogeochemical cycles of arsenic in arsenic-rich shallow and deep sediments.