Zhang Man, Hu Yang, Ma Yue, Hou Tianyu, Wang Juanhong, Che Qingxuan, Chen Bolang, Wang Qinghui, Feng Gu
College of Resources and Environment, Xinjiang Agricultural University, Urumqi, 830052, Xinjiang, China.
Agricultural Mechanisation Institute, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, Xinjiang, China.
Microb Ecol. 2025 May 6;88(1):39. doi: 10.1007/s00248-025-02540-1.
Xinjiang is situated in an arid and semi-arid region, where abundant heat and sunlight create highly favorable conditions for cotton cultivation. Xinjiang's cotton output accounts for nearly one-quarter of global production. Moreover, the implementation of advanced planting techniques, such as 'dwarfing, high-density, early-maturing' strategies combined with mulched drip irrigation, ensures stable and high yields in this region. Despite these advancements, limited research has focused on the microbial mechanisms in cotton fields employing these advanced planting methods. In this study, high-throughput sequencing technology was utilized to investigate the diversity and composition of bacterial and phoD (Alkaline phosphatases encoding gene) communities in the rhizosphere of cotton grown under different yield levels in Xinjiang Province, China. The Mantel test, redundancy analysis (RDA) and partial least squares path modeling (PLS-PM) were employed to explore the interactions between soil bacterial and phoD communities, their network structures, and environmental factors. The bacterial and phoD communities in the cotton rhizosphere were predominantly composed of nine bacterial phyla (i.e., Proteobacteria, Actinobacteria, Acidobacteria, Gemmatimonadetes, Chloroflexi, Bacteroidetes, Rokubacteria, Firmicutes, and Nitrospirae) and five phoD phyla (i.e., Proteobacteria, Actinobacteria, Planctomycetes, Acidobacteria, and Firmicutes), respectively. Alpha diversity analysis indicated that the medium yield cotton field (MYF) exhibited higher bacterial richness and diversity indices compared to low yield (LYF) and high yield (HYF) fields. The symbiotic network analysis of LYF revealed greater values of average degree, number of edges, and modularity, suggesting a more complex network structure in both bacterial and phoD communities. The Mantel test, RDA, and PLS-PM model identified soil pH, electrical conductivity (EC), organic phosphorus (OP), available phosphorus (AP), total nitrogen (TN), microbial biomass carbon (MBC), and clay content as the main driving factors influencing changes in the rhizosphere bacterial community diversity and network structure. These findings provide a theoretical basis for future research aimed at improving soil quality and cotton yield.
新疆地处干旱和半干旱地区，丰富的热量和充足的阳光为棉花种植创造了极为有利的条件。新疆的棉花产量占全球总产量的近四分之一。此外，“矮化、高密度、早熟”策略与膜下滴灌相结合等先进种植技术的实施，确保了该地区棉花的稳定高产。尽管有这些进展，但针对采用这些先进种植方法的棉田微生物机制的研究仍然有限。在本研究中，利用高通量测序技术调查了中国新疆不同产量水平下棉花根际细菌和phoD（碱性磷酸酶编码基因）群落的多样性和组成。采用Mantel检验、冗余分析（RDA）和偏最小二乘路径建模（PLS-PM）来探讨土壤细菌和phoD群落之间的相互作用、它们的网络结构以及环境因素。棉花根际的细菌和phoD群落主要分别由九个细菌门（即变形菌门、放线菌门、酸杆菌门、芽单胞菌门、绿弯菌门、拟杆菌门、罗库菌门、厚壁菌门和硝化螺旋菌门）和五个phoD门（即变形菌门、放线菌门、浮霉菌门、酸杆菌门和厚壁菌门）组成。α多样性分析表明，与低产田（LYF）和高产田（HYF）相比，中产棉田（MYF）的细菌丰富度和多样性指数更高。LYF的共生网络分析显示平均度、边数和模块性的值更大，表明细菌和phoD群落中的网络结构更为复杂。Mantel检验、RDA和PLS-PM模型确定土壤pH值、电导率（EC）、有机磷（OP）、有效磷（AP）、总氮（TN）、微生物量碳（MBC）和粘土含量是影响根际细菌群落多样性和网络结构变化的主要驱动因素。这些发现为未来旨在改善土壤质量和棉花产量的研究提供了理论基础。
