Stable isotope phenotyping via cluster analysis of NanoSIMS data as a method for characterizing distinct microbial ecophysiologies and sulfur-cycling in the environment

Research output: Contribution to journalArticleScientificpeer-review

Researchers

Research units

  • California Institute of Technology
  • California State University Long Beach

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 13C-acetate, 15N-ammonium, and 33S-sulfate. Using a cluster analysis technique based on fuzzy c-means to group cells according to their isotope (13C/12C, 15N/14N, and 33S/32S) 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.

Details

Original languageEnglish
Article number774
Pages (from-to)1-15
JournalFrontiers in Microbiology
Volume7
Issue numberMAY
Publication statusPublished - 2016
MoE publication typeA1 Journal article-refereed

    Research areas

  • Cluster analysis, Ecophysiology, NanoSIMS, Stable isotope probing, Sulfur-cycling

ID: 15325362