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通过纳米二次离子质谱数据聚类分析进行稳定同位素表型分析,作为一种表征环境中不同微生物生态生理学和硫循环的方法。

Stable Isotope Phenotyping via Cluster Analysis of NanoSIMS Data As a Method for Characterizing Distinct Microbial Ecophysiologies and Sulfur-Cycling in the Environment.

作者信息

Dawson Katherine S, Scheller Silvan, Dillon Jesse G, Orphan Victoria J

机构信息

Division of Geological and Planetary Sciences, California Institute of Technology Pasadena, CA, USA.

Department of Biological Sciences, California State University Long Beach Long Beach, CA, USA.

出版信息

Front Microbiol. 2016 May 26;7:774. doi: 10.3389/fmicb.2016.00774. eCollection 2016.

Abstract

Stable isotope probing (SIP) is a valuable tool for gaining insights into ecophysiology and biogeochemical cycling of environmental microbial communities by tracking isotopically labeled compounds into cellular macromolecules as well as into byproducts of respiration. SIP, in conjunction with nanoscale secondary ion mass spectrometry (NanoSIMS), allows for the visualization of isotope incorporation at the single cell level. In this manner, both active cells within a diverse population as well as heterogeneity in metabolism within a homogeneous population can be observed. The ecophysiological implications of these single cell stable isotope measurements are often limited to the taxonomic resolution of paired fluorescence in situ hybridization (FISH) microscopy. Here we introduce a taxonomy-independent method using multi-isotope SIP and NanoSIMS for identifying and grouping phenotypically similar microbial cells by their chemical and isotopic fingerprint. This method was applied to SIP experiments in a sulfur-cycling biofilm collected from sulfidic intertidal vents amended with (13)C-acetate, (15)N-ammonium, and (33)S-sulfate. Using a cluster analysis technique based on fuzzy c-means to group cells according to their isotope ((13)C/(12)C, (15)N/(14)N, and (33)S/(32)S) and elemental ratio (C/CN and S/CN) profiles, our analysis partitioned ~2200 cellular regions of interest (ROIs) into five distinct groups. These isotope phenotype groupings are reflective of the variation in labeled substrate uptake by cells in a multispecies metabolic network dominated by Gamma- and Deltaproteobacteria. Populations independently grouped by isotope phenotype were subsequently compared with paired FISH data, demonstrating a single coherent deltaproteobacterial cluster and multiple gammaproteobacterial groups, highlighting the distinct ecophysiologies of spatially-associated microbes within the sulfur-cycling biofilm from White Point Beach, CA.

摘要

稳定同位素探测(SIP)是一种宝贵的工具,可通过追踪同位素标记的化合物进入细胞大分子以及呼吸副产物,深入了解环境微生物群落的生态生理学和生物地球化学循环。SIP与纳米二次离子质谱(NanoSIMS)相结合,能够在单细胞水平上可视化同位素掺入情况。通过这种方式,可以观察到不同群体中的活跃细胞以及同一群体内代谢的异质性。这些单细胞稳定同位素测量的生态生理学意义通常仅限于配对荧光原位杂交(FISH)显微镜的分类分辨率。在此,我们介绍一种不依赖分类学的方法,使用多同位素SIP和NanoSIMS,通过化学和同位素指纹识别和分组表型相似的微生物细胞。该方法应用于从添加了(13)C-乙酸盐、(15)N-铵和(33)S-硫酸盐的硫化潮间带喷口采集的硫循环生物膜的SIP实验。使用基于模糊c均值的聚类分析技术,根据细胞的同位素((13)C/(12)C、(15)N/(14)N和(33)S/(32)S)和元素比率(C/CN和S/CN)谱对细胞进行分组,我们的分析将约2200个细胞感兴趣区域(ROI)分为五个不同的组。这些同位素表型分组反映了以γ-和δ-变形菌为主的多物种代谢网络中细胞对标记底物摄取的变化。随后将按同位素表型独立分组的群体与配对的FISH数据进行比较,结果显示出一个连贯的δ-变形菌簇和多个γ-变形菌群,突出了加利福尼亚州白点海滩硫循环生物膜中空间相关微生物的不同生态生理学特征。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2c5/4881376/5753e4221cae/fmicb-07-00774-g0001.jpg

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