A Caltech Library Service

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

Dawson, Katherine S. and Scheller, Silvan and Dillon, Jesse G. and Orphan, Victoria J. (2016) Stable Isotope Phenotyping via Cluster Analysis of NanoSIMS Data As a Method for Characterizing Distinct Microbial Ecophysiologies and Sulfur-Cycling in the Environment. Frontiers in Microbiology, 7 . Art. No. 774. ISSN 1664-302X. PMCID PMC4881376.

[img] PDF - Published Version
Creative Commons Attribution.

[img] PDF - Supplemental Material
Creative Commons Attribution.


Use this Persistent URL to link to this item:


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 33S-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.

Item Type:Article
Related URLs:
URLURL TypeDescription Material CentralArticle
Dawson, Katherine S.0000-0001-8856-4609
Scheller, Silvan0000-0002-0667-9224
Orphan, Victoria J.0000-0002-5374-6178
Additional Information:© 2016 Dawson, Scheller, Dillon and Orphan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Received: 11 January 2016; Accepted: 09 May 2016; Published: 26 May 2016. We thank Y. Guan in Caltech's Center for Microanalysis for technical assistance with the NanoSIMS 50L measurements, P. Miranda for the introduction and assistance with field work at White Point, and A. Saxena-Green, A. Pasulka, and R. Hatzenpichler for helpful discussions. This research is funded by the Gordon and Betty Moore Foundation through Grant GBMF 3306, a grant from the National Science Foundation (EAR-1123391), as well as the NASA Astrobiology Institute (Award # NNA13AA92A; to VO). This is NAI-Life Underground Publication Number 80. Author Contributions: KD designed and carried out experiments and wrote the manuscript. VO designed experiments and wrote the manuscript. SS developed the labeled sulfur oxidation protocol and provided feedback on the manuscript. JD provided valuable contextual information for experimental design and feedback on the manuscript. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Funding AgencyGrant Number
Gordon and Betty Moore FoundationGBMF 3306
Subject Keywords:NanoSIMS, sulfur-cycling, stable isotope probing, ecophysiology, cluster analysis
PubMed Central ID:PMC4881376
Record Number:CaltechAUTHORS:20160620-104423818
Persistent URL:
Official Citation:Dawson KS, Scheller S, Dillon JG and Orphan VJ (2016) Stable Isotope Phenotyping via Cluster Analysis of NanoSIMS Data As a Method for Characterizing Distinct Microbial Ecophysiologies and Sulfur-Cycling in the Environment. Front. Microbiol. 7:774. doi: 10.3389/fmicb.2016.00774
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:68526
Deposited By: Tony Diaz
Deposited On:20 Jun 2016 18:06
Last Modified:03 Oct 2019 19:54

Repository Staff Only: item control page