ISME:罗丹菌在环境压力下鞭毛脱落和生物膜生长的分子机制和环境适应性

文摘   2024-08-22 08:04   南非  
原文献信息:Mingfei Chen, Valentine V Trotter, Peter J Walian, Yan Chen, Romario Lopez, Lauren M Lui, Torben N Nielsen, Ria Gracielle Malana, Michael P Thorgersen, Andrew J Hendrickson, Heloise Carion, Adam M Deutschbauer, Christopher J Petzold, Heidi J Smith, Adam P Arkin, Michael W W Adams, Matthew W Fields, Romy Chakraborty, Molecular mechanisms and environmental adaptations of flagellar loss and biofilm growth of Rhodanobacter under environmental stress, The ISME Journal, 2024;, wrae151.

摘要:

生物膜通过直接和间接机制帮助细菌粘附在表面,并且生物膜的形成被认为是细菌在次优环境条件下适应和生存的重要策略。然而,在地下沉积物/地下水生态系统中,微生物常常经历营养输入、pH值、硝酸盐或金属浓度波动的情况下,生物膜形成的分子基础尚未得到充分研究。我们研究了16株从地下水井中分离的Rhodanobacter菌株在不同营养、pH值、金属和硝酸盐条件下的生物膜形成情况,这些水井的pH值范围从3.5到5,硝酸盐水平从13.7到146 mM不等。八株Rhodanobacter菌株在低pH值条件下表现出显著的生物膜生长,表明它们适应了在低pH值条件下生存和生长。在铝应激下,特别是那些具有较少与生物膜形成相关的遗传特征的菌株中,生物膜形成加剧,这需要进一步的研究。通过RB-TnSeq、蛋白质组学、特定突变体的使用和透射电子显微镜分析,我们发现铝应激下鞭毛的丧失,表明运动性、金属耐受性和生物膜生长之间可能存在关系。比较基因组分析显示,在高生物膜形成菌株FW021-MT20中,缺乏鞭毛和趋化性基因,而存在推测的VI型分泌系统。本研究识别了在金属应激下与生物膜生长相关的遗传决定因素,并识别了有助于在污染的地下环境中生存和适应的特征。

研究结果:

本文研究了Rhodanobacter菌株在生物膜形成过程中的可变反应,特别是关注于营养条件、pH值、硝酸盐以及金属(特别是铝)对其生物膜生长的影响。主要发现总结如下:
营养条件的影响:通过比较最小(SGW)和广泛营养(NLDM)培养基中的生长情况,发现尽管两种培养基的总溶解有机碳(OC)含量显著不同,但在相同pH或硝酸盐水平下,生物膜生长没有显著差异。这表明营养条件的变化对特定条件下的生物膜生长影响有限。
pH值和硝酸盐的特异性反应:不同菌株对pH和硝酸盐的反应各异。一些菌株的生物膜生长与pH呈正相关,而另一些则与硝酸盐呈负相关。特别地,来自FW106和FW510井的菌株在NLDM培养基中硝酸盐水平与生物膜生长显著负相关,但在SGW中未观察到此现象。
铝对生物膜生长的触发作用:在多种金属测试中,铝在大多数条件下显著促进了生物膜的生长。不同菌株对铝的响应具有特异性,高浓度铝则抑制了部分菌株的生长。菌株FW104-10B01在铝压力下表现出特别的适应性,通过BarSeq、蛋白质组学和TEM分析揭示了鞭毛相关基因的下调和形态变化,以及次级代谢物代谢(如c-di-GMP和cAMP)的显著变化。
特定基因在生物膜生长中的作用:通过转座子突变体测试,发现一些基因(如Crp、FlhA、FliA和Fis家族转录调节因子)在特定条件下(如SGW无铝压力)促进了生物膜的生长。TEM成像显示这些突变体在鞭毛缺失的同时,菌毛增加,导致细胞自我关联增加。
基因组学见解:比较基因组学和泛基因组分析揭示了Rhodanobacter属内不同菌株的系统发育关系和遗传多样性。尽管基因组相似度较高,但菌株间仍存在显著差异,特别是在生物膜形成相关特征上。这些发现强调了Rhodanobacter菌株在生物膜生长中的复杂性和菌株特异性。
综上所述,本研究通过多层面分析揭示了Rhodanobacter菌株在生物膜形成中的可变反应,特别是环境因素(如营养、pH、硝酸盐、金属)和遗传特征对生物膜生长的影响,为深入理解该属细菌的生物学特性和生态功能提供了重要信息。

文中图表:    

Figure 1: Heatmap results highlighting the biofilm growth capabilities of 16 Rhodanobacter isolates under varying pH conditions (ranging from pH 4 to pH 7) and nitrate conditions (ranging from 0 mM to 300 mM), carried out across two different media (SGW, NLDM). (A): Nitrate, SGW, (B): Nitrate, NLDM, (C): pH, SGW, (D): pH, NLDM. The OD550 values are calculated from the mean values observed in the corresponding isolates for each medium. The row is clustered using euclidean distance in between the values measured from each sample.

Figure 2: Heatmap showing biofilm growth capacities of eight selected Rhodanobacter strains under various metal stress conditions (aluminum, cobalt, copper, manganese, nickel, zinc). Biofilm quantification was performed using crystal violet staining, with readings taken at OD550. The mean value of the triplicates for individual isolates under certain metal stress was calculated against the “positive control” (no stress condition) to get the log2FC values shown in the heatmap.    

Figure 3: TEM images of Rhodanobacter (A-D) FW104-10B01 and (E) FW021-MT20 cultured in synthetic groundwater media supplemented with 1 mM Aluminum Chloride (B-D), and in the absence of any metal additions (A, E). Key features observed include (B) loss of pili and/or flagellar, (C) blebbing, cell morphology change and (D) particle adsorption for FW104-10B01 strains under aluminum stress conditions, and the lack of flagella for FW021-MT20 strains under normal conditions. Scale bar: 1 µm.

Figure 4: Phylogenetic relationship of the 16 Rhodanobacter strains analyzed in this study. (A) The 16 Rhodanobacter genomes (highlighted in red color) were compared with a set of related, publicly available genomes (in black). Tree scale: 0.1. The phylogenetic tree was made from Interactive Tree of Life (iTOL) v6 [94]. (B) A heatmap of ANI (green) and AAI (pink) values of the 16 Rhodanobacter genomes. The cluster was calculated using the hclust function in R.    

Figure 5: Pangenome of Rhodanobacter. The 16 Rhodanobacter genomes obtained in this study are shown in orange, and the other 48 publicly available genomes are shown in blue. Core genes are genes present in all 64 genomes, soft core genes are genes present in 61 to 63 genomes, cloud genes are genes present in 1 to 3 genomes, and the remaining genes are shell genes. Hierarchical clustering was performed on the ANI index calculated from fastANI. SCG, single-copy genes.

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