Community Assembly Mechanisms and Cross-niche Network Correlation between Robusta Coffee Cherry Surface and Soil Microbiomes

doi:10.13560/j.cnki.biotech.bull.1985.2025-1455

Abstract

Abstract:

Objective The microbiome associated with Robusta coffee (Coffea canephora) plays a critical role in plant health and quality. However, the community assembly mechanisms and the connectivity between the coffee cherry surface and soil niches remain poorly understood. This study aimed to elucidate the microbial community construction mechanisms and characterize the cross-niche correlation network between the coffee cherry surface and the underlying soil environment. Method Quantitative PCR (qPCR) and high-throughput sequencing technologies were employed to analyze the microbial community characteristics across three distinct niches: Coffee cherry surfaces (CF), coffee bulk soil (CRBS), and coffee rhizosphere soil (CRS). Subsequently, comprehensive bioinformatic analyses were performed, including fast expectation-maximization for microbial source tracking, community assembly process modeling, and cross-niche correlation network construction. Result The microbial community abundance and diversity exhibited a significant decreasing gradient from soil to coffee cherry. Significant differences in community structure were observed between the coffee cherry and soil compartments (P<0.05). Source tracking analysis revealed that the soil contribution to the coffee cherry surface community was less than 6%, suggesting a distinct origin for the coffee cherry surface microbiome. Furthermore, the community assembly processes differed significantly across niches: soil prokaryotic community assembly was primarily governed by deterministic processes, whereas the coffee cherry surface community was dominated by stochastic processes. Fungal communities, conversely, were generally driven by dispersal limitation across all niches. The cross-niche correlation network displayed a highly modular architecture, identifying Spirosoma and Ascobolus as core keystone taxa. These taxa acted as critical hubs, facilitating potential functional synergy and environmental responses between the soil and coffee cherry surface. Conclusion This study demonstrates that the microbial community on Hainan C. canephora cherry surfaces possesses a distinct stochastic assembly pattern that differs significantly from soil communities. Despite these structural differences, potential functional synergy exists between these niches, mediated by specific keystone taxa. We conclude that future coffee agricultural management should prioritize the regulation of key cross-niche network nodes, such as Spirosoma and Ascobolus.

Key words: Robusta coffee, niche differentiation, microbial source tracking, community assembly, cross-niche network

PI Wen-zhi, WANG Qun, LIU Xin-yuan, WANG Zhu-jun. Community Assembly Mechanisms and Cross-niche Network Correlation between Robusta Coffee Cherry Surface and Soil Microbiomes[J]. Biotechnology Bulletin, 2026, 42(5): 147-157.

Figures/Tables 5

Fig. 1 Diversity and structural differences of coffee cherry and soil microbial communitiesAbundance of prokaryotes (A) and fungi (B) based on qPCR gene copy numbers. Error bars indicate the standard deviation (SD). Different lowercase letters indicate significant differences based on ANOVA (P<0.05). The same below. Microbial community composition of prokaryotes (C) and fungi (D) at the phylum level. LEfSe analysis identifies characteristic biomarkers for prokaryotes (E) and fungi (F) (LDA score>4.0, P<0.05). Principal Coordinate Analysis (PCoA) of prokaryotic (G) and fungal (H) communities based on Bray-Curtis distances. The values displayed in the plots represent F-values and P-values derived from PERMANOVA tests (*** P<0.001). CF, Coffee cherry (n = 18); CRBS, bulk soil (n = 6); CRS, rhizosphere soil (n = 6), the same below

Table 1 Properties of the cross-niche correlation networks

组别 Group		网络属性 Network property
组别 Group		节点 Nodes	边 Edges	正相关边 Positive edges	平均度 Average degree	平均路径长度 Average path length	网络直径 Network diameter	连通度 Connectivity	模块化 Modularity
原核生物	CF-CRBS	679	1009	625	2.97	1.65	4	0.0044	0.97
	CF-CRS	661	1107	652	3.35	1.94	4	0.0032	0.95
	CRBS-CRS	795	2380	1310	5.99	1.90	7	0.0075	0.92
真菌	CF-CRBS	602	752	370	2.50	1.47	2	0.0042	0.98
	CF-CRS	707	1120	559	3.17	2.73	8	0.0045	0.95
	CRBS-CRS	765	1568	911	4.10	2.94	8	0.0054	0.94

Fig. 2 Microbial source tracking and differences in community assembly based on phylogeny-based null models in coffee cherry and soilFast expectation-maximization for microbial source tracking of prokaryotic (A) and fungal (B) communities. The βNTI values and proportions of community assembly processes for prokaryotes (C, E) and fungi (D, F)

Fig. 3 Cross-niche correlation networks of coffee cherry- soil microbiomesCross-niche correlation networks of prokaryotic (A-C) and fungal (D-F) communities

Fig. 4 Keystone nodes and their subnetworks in the coffee cherry-soil microbial cross-niche correlation networkCross-niche keystone nodes for prokaryotes (A-C) and fungi (D-F) in coffee cherry and soil environments. In the cross-domain networks, keystone nodes were identified based on their within-module connectivity (Zi ) and among-module connectivity (Pi ). Module hubs were defined as nodes with Zi >2.5. Subnetworks of these cross-niche keystone nodes are shown for prokaryotes (G-I) and fungi (J-K)

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