文献信息:
Fang Linfa, Lakshmanan Prakash, Zhang Hailin, Deng Yue, Xiao Ran, Wen Teng, Ma Bin, Ge Tida, Müller Christoph, Zhang Jinbo, Chen Xinping, Zhu Yongguan, Su Xiaoxuan*. Ciprofloxacin-driven purifying selection on viral genomes accelerates soil N2O production. Proceedings of the National Academy of Sciences of the United States of America, 2025, 122(29): e2503199122. https://doi.org/10.1073/pnas.2503199122
Significance: Viruses, the most abundant biological entities, have great potential in regulating nutrient biogeochemistry and influencing ecosystem functions. However, their contributions to biogeochemical cycling and greenhouse gas emissions, particularly under environmental stress, remain largely unexplored. We report that antibiotic stress increases viral contributions to greenhouse gas N2O production by 18 to 29%, thereby advancing our understanding of the vital roles of viruses in biogeochemical cycles. Our results also reveal that antibiotic stress induces synonymous mutations in viral genomes, facilitating viral adaptation to hosts and promoting interactions with denitrifiers, which in turn enhances their metabolic potential. This study opens avenues for understanding the role of viral evolution in biogeochemistry, particularly in the context of increasing environmental stress of the Anthropocene.
Abstract: Viruses are ubiquitous regulators of microbial dynamics and may thus greatly influence global microbial-driven greenhouse gas emissions. Anthropogenic stressors, such as chemical contamination, are likely to amplify these viral contributions; however, their global significance and underlying mechanisms remain elusive. Utilizing 15N tracing, metagenomics, and laboratory assays, we explore soil viral communities and their evolutionary potential under the stress from antibiotic ciprofloxacin (CIP), focusing on their roles in regulating nitrogen cycling and N2O production. Through isolation and reinoculation of soil viruses, we demonstrate that CIP stimulates soil denitrification-derived N2O production, with 18 to 29% of the increase attributed to viral activity. Under CIP stress, soil viruses shift toward a lysogenic lifestyle, promoting mutualism with denitrifiers by horizontally transferring viral denitrification-related auxiliary metabolic genes (AMGs). The observed synonymous mutations in these AMGs, driven by CIP, suggest enhanced purifying selection, likely optimizing codon usage to align with host preferences. This optimization likely enhances the expression of denitrifying AMGs and increases N2O production. This study provides insights into the overlooked role of viral dynamics and genomic mutations in modulating N2O production under stressful environments, highlighting their evolutionary significance and impact on biogeochemical cycles in the Anthropocene.
Fig. 1. Soil gross N transformation and N2O production rate. Different letters indicate significant differences among treatments (P < 0.05). Org-Nlab, labile organic N; Org-Nrec, recalcitrant organic N; NH4+abs, abiotic adsorbed NH4+; MNlab, mineralization of labile organic N; MNrec, mineralization of recalcitrant organic N; INH4-Nrec, immobilization of NH4+ to recalcitrant organic N; ONrec, oxidation of recalcitrant organic N to NO3−; INH4-Nlab, immobilization of NH4+ to labile organic N; ONH4, oxidation of NH4+ to NO3−; ANH4, abiotic NH4+ adsorption; DNRA, dissimilatory NO3− reduction to NH4+.
Fig. 2. Summary of MAGs in bacteria and archaea. (A) Phylogenetic trees, taxonomic information, completeness, contamination, genes encoded in different N transformation processes, and fold changes of MAGs abundances in “M vs. CK” and “C1 vs. M.” (B) Distribution of key metabolic features involved in N cycling, cellular motility, DNA mutation and repair, efflux pumps, oxidative stress defense, SOS response, and toxin-antitoxin systems. Analysis of top 10 MAGs with their relative abundances increased or decreased by CIP exposure compared to the M treatment. Features shown in white were not detected in the MAGs.
Fig. 3. Compositions, lifestyle, and AMGs involved in N-cycling of viruses. (A) Proportion of viral types in CIP-contaminated soils. (B) Predicted viral lifestyle distributions across treatments. (C) Abundances of viral AMGs in each treatment. (D) Fold change of viral AMGs associated with N cycling between treatments (C1 vs. M). The left gray region represents downregulated AMGs in C1 compared to the M treatment, while the right white region represents upregulated AMGs. The length and size of the circle indicate fold changes and P value, respectively. Bar plot indicates the transcript per kilobase per million mapped reads (TPM) of each viral AMG. (E) Links between MAGs and viruses encoding N-cycling AMGs are shown, where light blue circles, red rectangles, and indigo rectangles represent MAGs, viral taxonomy, and N-cycling AMGs, respectively. (F) A schematic that illustrates the insertion of viral genes disrupting the host genome (MAG49). TSS, transcript start sites; CDSo, only exons; PolyA, polyA tail area. Different letters indicate significant differences among treatments (P < 0.05).
Fig. 4. Evolutionary analysis of viral AMGs related to N cycling under CIP exposure. (A) Overall statistics of evolutionary analysis under CIP exposure compared to the M treatment. (B) Evolutionary analysis of individual AMGs among treatments, with the bold black and indigo text indicating significant differences (P< 0.05) between M and C1 treatments. (C) Ka/Ks ratios of viral N-cycling AMGs under CIP exposure relative to M treatment.
Fig. 5. Viral adaptation of N-cycling AMGs to host. (A) CAI of various viral N-cycling AMGs between CIP and M treatments. (B) Scatterplots of CAI values in viral genomes and host MAGs, with lines and their 95% CI representing univariate linear regression smooths fitted to the data. W indicates Kendall’s coefficient of concordance. * and ** indicate significant differences among treatments with P < 0.05 and P < 0.01, respectively.
Fig. 6. VP extraction and validation. (A) Schematic diagram showing soil VP extraction, incubation, re-extraction, and reincubation experimental design. (B) Transmission electron microscope images of VP in soil extraction. (C) The cumulative N2O production in soils inoculated with active or inactive VP on day 7. The top row shows the cumulative N2O production during the first 7-d incubation following viral inoculation, while the bottom row depicts production during the second 7-d incubation after reinoculating the soil with extracted VP from the first incubation. Different letters indicate significant differences among treatments (P < 0.05). Con, control, no viral particles; −VP, inactive viral particles; +VP, active viral particles; +VPS, active viral particles + suspension.
GT5000便携式多参数土壤呼吸测量系统是芬兰Gasmet公司生产的一款基于傅里叶变换红外光谱(FTIR)技术的便携式高精度土壤温室气体排放监测系统。该仪器可以在数秒内同时测定多种主要的温室气体成分,如:N2O,CH4,CO2,H2O,CO和NH3,且测量精度可达ppb级。GT5000便携式多参数土壤呼吸测量系统可用于农田,湿地,森林,牧场,电厂,火灾现场等各种环境中的温室气体通量测量。
采用傅里叶变换红外光谱技术;
同时测量N2O,CH4,CO2,H2O,CO和NH3等6种温室气体,最多可同时测量50种气体;
多种无线连接方式,如WI-FI或蓝牙。无需专业知识,用户可通过导航进行操作;
一键测量和即时的在线处理结果;
五种不同的视图展示相关的测量信息;
自动气室有机械臂,可缓慢升降;
通气口的设计可确保稳定的大气压力,且不会通过反向扩散影响测量;
气室的内部进出回路可有效的促进气体混合
测量原理:FTIR傅里叶变换红外光谱;
气体测定种类:可同时测定50种气体;
响应时间:通常<120s,基于所测定的气体和测量时间;
电池:锂离子电池,单节电池可维持3小时;
充电电源:115/230V AC;
分析软件:Calcmet(需Win7或10操作系统);
数据连接:USB,以太网,蓝牙,WI-FI;
采样泵流速:2 L/min;
气体采样过滤:带有2μm孔径聚四氟乙烯过滤器的采样探头;
采样气体进/出口配件:6mm快速接头;
外壳大小:450×287×166mm(H×W×D) ;材料:ABS PC;防护等级:IP54(适用于野外便携式设备);
重量:9.4kg(含电池)/8.0kg(不含电池)
光谱仪:分辨率:8cm-1;扫描频率:10次/s;检测器:碲镉汞(MCT)光电探测器;分束器材料:硒化锌(ZnSe);波数范围:900-4200cm-1;
样品室结构:多通道,固定光程长度5m;反射镜:固定式,镀金;体积:0.5L;
产品链接:https://www.eco-mind.cn/productinfo/1143246.html