Soil viral diversity and carbon metabolism genes profiling in Xixi Wetland

doi:10.17520/biods.2025190

Abstract

Abstract:

Aims: The purpose of this study is to systematically examine soil viral community composition and assess their carbon metabolic functional potential across urban wetland ecosystems.

Methods: We took five habitat types of sample plots, including trees, shrubs and grasslands, shrub grasslands, reed marshes, shoals and ponds, distributed widely in Hangzhou Xixi National Wetland Park, Zhejiang Province (Xixi Wetland) as the research objects. This study investigated soil viral diversity patterns and carbon metabolic gene composition across these five habitat types using virus metagenomic sequencing coupled with bioinformatics analysis.

Results: There were significant differences in viral richness and diversity among the five habitat types (P < 0.05), with hierarchical rankings as follows: shrub grasslands > trees, shrubs and grasslands > reed marshes > shoals > ponds; The structural equation modeling analysis showed that this spatial pattern was predominantly mainly driven by soil physicochemical properties, with the order of effect size was pH > soil moisture > SOC (soil organic carbon) ≈ TN (total nitrogen) > soil temperature. The contribution of comprehensive effect size of viral host and viral diversity was in the order of TN > SOC > soil temperature, and the direct effect of viral host on viral diversity was the strongest (effect size = 0.87); A total of 158 unique carbohydrate transport and metabolism (G) genes were identified, including 13 distinct carbohydrates active enzyme (CAZyme) families. Among these glycosyltransferases accounted for the highest proportion (65.8%), indicating that soil viruses may play an important role in wetland carbon cycling through glycosylation-mediated processes.

Conclusion: The diversity of soil viruses in Xixi Wetland exhibits significant spatial heterogeneity. This distribution pattern is closely linked to variations in soil physicochemical properties (especially the key factors such as SOC, TN and soil moisture). The CAZyme genes identified in five habitat types contribute to wetland carbon cycling processes through regulating the metabolic pathways of host microorganisms.

Key words: wetlands, viral metagenomic sequencing, soil organic carbon sequestration, CAZymes genes, ecological function

Xinyi Hong, Yilang Cai, Jiale Fang, Kekan Yao, Jiale Li, Yixiang Wang, Shangbin Bai, Nan Wang, Xiumei Zhou. Soil viral diversity and carbon metabolism genes profiling in Xixi Wetland[J]. Biodiv Sci, 2025, 33(9): 25190.

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URL: https://www.biodiversity-science.net/EN/10.17520/biods.2025190

https://www.biodiversity-science.net/EN/Y2025/V33/I9/25190

Figures/Tables 10

Table 1 Soil physicochemical properties across different habitat types in Xixi Wetland. The data is the mean ± SD.

	土壤温度 Soil temperature (℃)	土壤湿度 Soil moisture (%)	pH	土壤有机碳 Soil organic carbon (g/kg)	土壤全氮 Total nitrogen (g/kg)
乔灌草地 Trees, shrubs and grasslands	9.1 ± 0.2^ab	32.60 ± 14.06^bc	6.84 ± 0.44^a	41.3 ± 24.5^a	3.4 ± 1.8^a
灌草地 Shrub grasslands	8.9 ± 1.4^b	25.29 ± 3.67^c	6.36 ± 0.50^a	30.8 ± 9.6^ab	2.8 ± 0.3^ab
芦苇地 Reed marshes	7.1 ± 0.3^c	39.24 ± 11.89^b	5.57 ± 0.41^b	26.0 ± 10.4^b	2.2 ± 0.8^b
池塘 Ponds	7.4 ± 0.1^c	51.70 ± 10.56^ab	6.56 ± 0.04^a	13.6 ± 0.8^c	1.1 ± 0.1^c
浅滩 Shoals	11.1 ± 0.5^a	74.13 ± 8.35^a	5.47 ± 0.12^b	16.2 ± 1.1^bc	1.4 ± 0.1^c

Fig. 1 The distribution of contig lengths for different habitat types in Xixi Wetland. A, Trees, shrubs and grasslands; B, Shrub grasslandes; C, Reed marshes; D, Ponds; E, Shoals.

Table 2 Summary of the predicted viral hosts with over 50 sequence counts and their distribution across different habitat types

宿主属 Host genus	病毒序列数量 Number of viral sequences	占总预测病毒宿主序列数的比值 Proportion of predicted viral host sequences (%)	乔灌草地 Trees, shrubs and grasslands	灌草地 Shrub grasslands	芦苇地 Reed marshes	池塘 Ponds	浅滩 Shoals
不动杆菌属 Acinetobacter	76	1.23	57	69	12	2	2
伯克霍尔德氏菌属 Burkholderia	105	1.70	58	87	45	2	2
汉密尔顿菌属(暂定类群) Candidatus_Hamiltonella	76	1.23	33	64	6	0	0
蛭弧菌属 Bdellovibrio	1,939	31.38	1,372	1,563	99	4	2
柄杆菌属 Caulobacter	155	2.51	105	136	55	2	2
埃希氏菌属 Escherichia	375	6.07	257	320	62	6	1
地芽孢杆菌属 Geobacillus	63	1.02	39	52	4	0	0
螺杆菌属 Helicobacter	61	0.99	39	46	6	2	0
黏液乳杆菌属 Limosilactobacillus	104	1.68	55	82	14	1	0
李斯特菌属 Listeria	120	1.94	50	86	27	10	0
中慢生根瘤菌属 Mesorhizobium	76	1.23	52	60	21	0	0
分枝杆菌属 Mycolicibacterium	114	1.84	71	89	39	0	0
副拟杆菌属 Parabacteroides	68	1.10	51	54	8	0	0
土球腔菌属 Pedosphaera	50	0.81	31	47	12	0	0
普雷斯科特氏菌属 Prescottella	77	1.25	53	70	7	0	0
原绿球藻属 Prochlorococcus	50	0.81	39	32	3	0	0
假单胞菌属 Pseudomonas	203	3.28	109	173	34	2	2
红杆菌属 Rhodobacter	69	1.12	57	61	26	2	3
红育菌属 Rhodovulum	53	0.86	34	45	14	2	2
罗格氏菌属 Ruegeria	54	0.87	38	41	10	1	1
中华根瘤菌属 Sinorhizobium	57	0.92	40	42	32	1	1
弧菌属 Vibrio	129	2.09	84	102	26	4	2
未知 Unknown	266	4.30	161	213	105	3	2

Table 3 Shannon index, Simpson index and Chao1 index of virus across different habitat types in Xixi Wetland

多样性指数 Diversity index	乔灌草地 Trees, shrubs and grasslands	灌草地 Shrub grasslands	芦苇地 Reed marshes	池塘 Ponds	浅滩 Shoals
Shannon指数 Shannon index	6.30^b	8.26^a	7.50^ab	3.88^c	5.83^bc
Simpson指数 Simpson index	0.95^a	0.96^a	0.88^b	0.84^b	0.86^b
Chao1指数 Chao1 index	15,357.66^ab	20,083.64^a	4,650.26^b	257.23^c	543.23^bc

Fig. 2 Viral community structure of different habitat types in Xixi Wetland. A, Trees, shrubs and grasslands; B, Shrub grasslands; C, Reed marshes; D, Ponds; E, Shoals.

Fig. 3 Composition of horizontal community structure of viral order level in different habitat types of Xixi Wetland. RPKM, Reads per Kilobase per Million mapped reads.

Fig. 4 Correlation between viral families composition and soil physicochemical properties in Xixi Wetland. SWC, Soil water content; ST, Soil temperature; SOC, Soil organic carbon; TN, Total nitrogen. * P < 0.05, ** P < 0.01.

Fig. 5 The structural equation modeling of soil physicochemical properties and viral host. The e represents the residual term; The one-way arrow indicates the direct effect relationship between variables, where positive values indicate a positive correlation (the higher the value, the stronger the correlation) and negative values indicate a negative correlation (the larger the absolute value, the stronger the correlation); The double arrow indicates fitted lines, with positive values meaning observed values are greater than model-predicted values and negative values meaning observed values are less than model-predicted values.

Fig. 6 The structural equation modeling of soil physicochemical properties and viral diversity. The e represents the residual term; The one-way arrow indicates the direct effect relationship between variables, where positive values indicate a positive correlation (the higher the value, the stronger the correlation) and negative values indicate a negative correlation (the larger the absolute value, the stronger the correlation); The double arrow indicates fitted lines, with positive values meaning observed values are greater than model-predicted values and negative values meaning observed values are less than model-predicted values.

Fig. 7 The structural equation modeling of soil physicochemical properties-viral host-viral diversity. A solid green one-way arrow (pointing to the observed variable) indicates a direct positive correlation, while a dashed green one-way arrow indicates an indirect correlation, and the double arrow indicates the fitting line, the solid red line indicates a direct negative correlation. Negative values represent a negative (inhibitory) effect, while positive values represent a positive effect. Chao1, Chao1 index; Shannon, Shannon index; SOC, Soil organic carbon; TN, Total nitrogen; Temp, Temperature; Viral_diversity, Viral diversity; Viral_host, Viral host; Soil_Env, Soil environment.

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