土壤中有机碳的可用性对于塑造微生物群落至关重要，但微生物对碳水平的适应以及由此产生的生态和进化后果仍存在不确定性。本研究调查了经过 40 年化学和有机施肥的土壤中的有机碳代谢、抗生素抗性以及病毒与宿主的相互作用，这些施肥方式导致了不同的碳可用性，即分别为碳贫乏和碳丰富的土壤。碳贫乏的土壤促使参与有机物分解的推定基因富集，并在利用复杂有机化合物方面表现出专业化，反映了激烈的竞争。这种专业化赋予了碳贫乏土壤中微生物群落竞争优势，但降低了它们在有机碳代谢方面的缓冲能力，使其更容易受到环境波动的影响。此外，在碳贫乏的土壤中，与有机碳代谢相关的病毒辅助代谢基因通过类似于 “搭胜者便车” 的策略增加了宿主的竞争力和环境适应性。而且，推定的抗生素抗性基因，特别是在低丰度药物类别中，在碳贫乏的土壤中富集，这是化学战（即干扰竞争）的进化结果。这引发了人们对仅依赖化学施肥的传统农业中抗生素抗性潜在传播的担忧。
因此，长期仅化学施肥导致的碳饥饿增加了微生物对竞争的适应能力，强调了实施可持续农业实践以减轻抗菌素耐药性的出现和传播以及增加土壤碳储存的重要性。
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Fig. 1: Summary of putative CAZyme genes in chemical-only fertilized soils (CF) and organic-only fertilized soils (OF). (A) Abundance of CAZyme genes at the class level. Red and blue dots indicate enrichment in CF and OF, respectively. GT: glycosyl transferase; GH: glycoside hydrolase; CE: carbohydrate esterase; CBM, carbohydrate-binding module; PL: polysaccharide lyase; AA, auxiliary activities. The annotation of CAZyme genes was based on the Carbohydrate-Active enZYmes database using open reading frames (ORFs) from metagenomics. A linear mixed model was used to compare gene abundance in CF and OF. In the model, the “Fertilization regime” (CF or OF) factor was fixed, and the “Sites” (four locations) factor was considered a random effect. (B) Enriched CAZyme genes in different soils. The size of the circles indicates the response ratio. The response ratio was determined by calculating the natural logarithm of the ratio of the mean gene abundances between CF and OF. (C) Microbes contributing to the enriched CAZyme genes. The size of the circles and octagons indicate the contribution of microbes and gene abundance, respectively. The font size matches the size of the corresponding circles or octagons. The colors of the circles indicate microbial phyla, and the colors of the octagons indicate CAZyme gene enrichment. The relationships between the functions and their contributors were estimated through sequence annotation against both functional and taxonomic databases. (D) Potential substrates of enriched CAZyme genes. The related processes are grouped under biosynthesis, binding, biodegradation, and auxiliary activities. This information was sourced from the Carbohydrate-Active enZYmes database.![]()
Fig. 2: Summary of viral AMGs in chemical-only fertilized soils (CF) and organic-only fertilized soils (OF). (A) Abundance of viral AMGs annotated as CAZyme genes at the class level. The annotation of CAZyme genes was based on the Carbohydrate-Active enZYmes database using AMGs identified from viral sequences. A linear mixed model was used to compare gene abundance in CF and OF. In the model, the “Fertilization regime” (CF or OF) factor was fixed, and the “Sites” (four locations) factor was considered a random effect. (B) Viruses contributing to the enriched AMGs annotated as CAZyme genes. The size of the circles and octagons indicate the contribution of microbes and AMG abundance, respectively. These AMGs were involved in the biosynthesis of cell wall components. The relationships between the functions and their contributors were estimated based on viral sequences containing both AMGs and taxonomic information. (C) The functions and origins of enriched AMGs, as well as the viral hosts. The virus contribution to AMGs (size of the circle), AMG abundance (size of the octagon), and host abundance (size of the square) are shown. The viral hosts were identified using three methods: homology matches, tRNAs similarity, and CRISPR spacer similarity, based on the high-quality MAGs recovered in this study. The functional information was sourced from KEGG Database.
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Fig. 3: Summary of putative ARGs in chemical-only fertilized soils (CF) and organic-only soils (OF). (A) Abundance of ARGs at the drug level. Red and blue dots indicate enrichment in CF and OF, respectively. The annotation of antibiotic resistance genes was based on the Comprehensive Antibiotic Resistance Database using open reading frames (ORFs) from metagenomics. A linear mixed model was used to compare gene abundance in CF and OF. In the model, the “Fertilization regime” (CF or OF) factor was fixed, and the “Sites” (four locations) factor was considered a random effect. (B) Enriched ARGs in different soils. The size of the circle indicates the response ratio. The response ratio was determined by calculating the natural logarithm of the ratio of the mean gene abundances between CF and OF. (C) Microbes contributing to the enriched ARGs. The sizes of the circles and octagons indicate the contribution of microbes and gene abundance, respectively. The font size matches the size of the corresponding circles or octagons. The color of the circles indicates microbial phyla, and the color of the octagons indicates ARG enrichment. The relationships between the functions and their contributors were estimated through sequence annotation against both functional and taxonomic databases. (D) Associated antibiotics of enriched ARGs. This information was sourced from the Comprehensive Antibiotic Resistance Database.
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Fig. 4: Summary of metagenome-assembled genomes (MAGs) in chemical-only fertilized soils (CF) and organic-only fertilized soils (OF). Phylogenetic tree of MAGs, taxonomic information, MAG abundances in OF and CF, MAG enrichment, detection of ARGs in MAGs, and the abundance of CAZyme genes in MAGs are displayed from the inner to outer circles. The graphs in the upper right corner of the figure show CAZyme gene abundance, percentage of MAGs with ARGs, genome size, and coding sequences in MAGs enriched in CF or OF soils. The taxonomic annotation of MAGs and phylogenetic tree were constructed based on the Genome Taxonomy database Release 207 (GTDB). A Wilcoxon rank-sum test was used to compare the parameters in MAGs enriched in CF and OF soils. 在长期的化肥与有机肥施用实验中，研究团队揭示了不同施肥方式对土壤化学性质和微生物群落的深远影响。与仅使用化肥相比，单独使用有机肥显著提升了土壤有机碳（SOC）含量，增幅达38%，同时总氮（TN）含量提升了31%。此外，长期施用有机肥使土壤维持中性pH值，而仅使用化肥的土壤则呈现酸性。研究表明，温度、降水量及光照等环境因素也对土壤性质产生了显著影响。在微生物竞争方面，仅施用化肥的土壤中，物种间的竞争加剧，表现为物种共现网络中的关联度显著提高。这种竞争机制使得化肥土壤中的负相关性显著增加，表明在碳资源贫乏的土壤中，微生物之间的竞争更加激烈。通过基因组学与代谢组学分析，研究团队进一步揭示了有机碳代谢与微生物群落在不同施肥土壤中的适应性。仅施化肥的土壤中，碳水化合物活性酶（CAZymes）基因的丰度显著增加，特别是在多糖裂解酶（PL）和氧化还原酶（AA）类基因中，显示出微生物群落在碳资源有限的环境中对复杂碳源的依赖性更强。这种现象反映出微生物在碳匮乏条件下，通过分泌多样的胞外酶来分解有机化合物以获取能量和营养，这种策略被称为“资源争夺型竞争”。
在病毒与宿主关系中，研究表明，在碳资源贫乏的土壤中，病毒通过辅助代谢基因（AMGs）增强宿主的竞争力和环境适应性。研究发现，Hollowayvirus通过增强宿主的γ-氨基丁酸（GABA）代谢，使其在碳匮乏环境中具备更强的生存能力，而在碳丰富的土壤中，Fletchervirus则通过增加宿主ATP的合成，提升宿主的生理活动。此外，研究还发现，长期的化肥施用导致土壤中抗生素抗性基因（ARGs）显著增加，尤其是在低丰度抗药基因类别中。这一发现表明，微生物之间在碳资源竞争中的“化学战争”加剧了抗药基因的富集，可能对公共卫生产生潜在影响。总之，本研究深刻揭示了微生物在碳资源有限条件下的适应机制，尤其是在有机碳代谢、病毒-宿主相互作用及抗生素抗性方面的表现。这些发现不仅丰富了我们对土壤微生物竞争的理解，也为未来开发更可持续的农业实践提供了科学依据。
