陆生蓝藻滑动运动及其关键影响因素研究进展

doi:10.7522/j.issn.1000-694X.2025.00108

摘要/Abstract

摘要：

蓝藻是具有光合能力的原核生物，是地球上最古老的产氧生物，作为初级生产者在生态系统碳氮循环中发挥重要作用。蓝藻的运动能力与其极强的适应性密切相关。全面梳理了陆生蓝藻滑动及其关键影响因素的研究进展，综合分析了蓝藻对包括水分、光照、昼夜节律、气体浓度、盐度和营养物质浓度在内的多种因素变化进行响应等方面的研究成果。蓝藻的滑动运动依赖其产生的胞外分泌物，这些分泌物不仅提供物理支撑，其厚度和成分还会影响蓝藻滑动的速度和方向。蓝藻能感知光照、水分、盐度等环境因素，并通过滑动做出响应。此外，气体、营养物质和昼夜节律等因素也能影响蓝藻的滑动行为。当前，影响陆生蓝藻滑动的环境因素研究仍面临微环境调控、实时观测及量化手段、分子机制多样性等挑战。未来，需深化蓝藻趋向性运动生态功能解析，突破分子调控机制研究瓶颈，阐明其通过信号转导途径调控滑动行为的作用机理。建议整合分子生物学与遗传学方法，系统鉴定驱动滑动运动的关键基因与蛋白质互作网络，解析多环境因子协同作用的整合调控机制，为揭示微生物环境适应策略提供理论范式与技术支撑。

关键词: 蓝藻, 滑动, 运动性, 趋光性, 趋化性, 生物复合体

Abstract:

As photosynthetic prokaryotes and the oldest oxygen-producing organisms on Earth， cyanobaceria play vital rolse as primary producers in the carbon and nitrogen cycles of ecosystems. The motility of cyanobacteria is closely linked to their remarkable adaptability. This article comprehensively reviewed research advances in the gliding motility of terrestrial cyanobacteria and key influencing factors of this process. The review integrated findings made on the migrational responses of cyanobacteria to diverse environmental factors， including water availability， light， circadian rhythms， gas concentrations， salinity， and nutrient levels. The gliding motility of cyanobacteria relies on the secretion of extracellular polymeric substances， which not only provide physical support but can also modulate the speed and direction of the gliding movement through its thickness and composition. Cyanobacteria can sense environmental cues such as light， moisture， and salinity， and respond via gliding. Factors like dissolved gas concentrations， nutrient availability， and circadian rhythms have been shown to also be able to influence the gliding behavior. Current research on the drivers of terrestrial cyanobacterial gliding faces challenges， technically， choices of in situ visualization techniques are limited； also the microenvironmental regulatory processes， as well as the underlaying molecular mechanisms are still not yet fully elucidated. Future studies should strive to deepen the understading of the ecological functions cyanobacterial gliding， reveal the underlaying molecular regulatory mechanisms， and clarify the mechanistic role of signal transduction pathways in regulating gliding behavior. We recommend adopting integrated molecular biology and genetic approaches to systematically identify key genes and protein interaction networks driving gliding motility， while deciphering the integrated regulatory mechanisms underlying the synergistic effects of multiple environmental factors. Such efforts will establish both theoretical paradigms and technical foundations for revealing microbial environmental adaptation strategies.

Key words: cyanobacteria, gliding, motility, phototaxis, chemotaxis, biological matrix

中图分类号:

方焱, 李彤, 张元明. 陆生蓝藻滑动运动及其关键影响因素研究进展[J]. 中国沙漠, 2025, 45(6): 154-165.

Yan Fang, Tong Li, Yuanming Zhang. Research progress on the gliding motility of terrestrial cyanobacteria and key influencing factors thereof[J]. Journal of Desert Research, 2025, 45(6): 154-165.

图/表 3

图1 集胞藻细胞受到左侧光源（箭头表示）照射下运动不同阶段的照片［56］注：（A）第一阶段，大部分细胞独立运动，四周有少数成对细胞，没有表现出强烈的偏向光源的运动；（B）第二阶段，细胞开始聚集形成更大的群体，运动速率比第一阶段更快，但仍没有强烈偏向光源运动；（C）第三阶段，细胞群周围出现明显的冠状结构（短箭头所示），运动速率比第二阶段更快，右上方形成一个小型指状突起，在此突起中细胞挤在前面，有向光方向移动的倾向；（D）减小放大倍数，可观察到所形成的指状突起，每个“手指”长约 2 mm，前端细胞密集，可在6 h内移动1 mm，此时细胞的运动速率约为第一阶段的6~7倍［56］

Fig.1 Photos of Synechocystis at different movement stages under left-side light irradiation （indicated by yellow arrows）［56］

图2 非圆形光斑导致的藻丝边界积累现象［55］注：上排是在约17~21 h光照后藻丝的显微镜照片；下排是数值模拟中藻丝模型的时间平均向列序取向，颜色的饱和度经过调整以反映藻丝的平均密度，颜色越亮表示藻丝密度越高，藻丝数量越少呈现的颜色越暗。图F中提供了藻丝排列长轴方向的颜色代码，每种颜色与藻丝滑动的方向相对应，每种形状对应的绕数（winding number）显示在图片左上角［55］

Fig.2 Accumulation patterns for non-circular illumination［55］

图3 将3种蓝藻接种于BG11培养基上，并分别在不同温度下培养72 h后取样，可以看出不同温度对EPS生物物理特性的影响［19］注：图A、B表示Nostoc sp.（FACHB-2009）的鞘，图C、D表示Dolichospermum sp.（FACHB-82）的荚膜，图E、F表示Microcystis sp.（FACHB-3296）的黏液。黑色实心三角形表示在25 ℃下每种EPS的生物物理特性作为比对基准，彩色三角形表示10 ℃和35 ℃下EPS物理特性的变化程度［19］

Fig.3 Effects of different temperatures on the biophysical properties of external layers at the final sampling time （72 h）［19］

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