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

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.

Characterization of Chemosynthetic Microbial Mats Associated with Intertidal Hydrothermal Sulfur Vents in White Point, San Pedro, CA, USA

“…Remarkably, there were also dozens of novel phylotypes affiliated with the Thiotrichales detected using 16S rRNA as well as aprA gene sequencing. Other studies of shallow vents have found members of the Thiotrichales to be key members of the chemoautotrophic vent communities ( Brinkhoff et al, 1999 ; Dawson et al, 2016 ). However, a number of studies in both shallow and deep-sea vents systems have found mesophilic Epsilonproteobacteria such as Sulfurovum and Sulfurimonas to be the most common groups of SOxB recovered by molecular means ( Flores et al, 2012 ; Sylvan et al, 2012 ; Wang et al, 2015 ) and cultivation ( Inagaki et al, 2003 , 2004 ).…”

“…This raises the possibility of a complete biological sulfur cycle mediated by partnerships between oxidative and reductive sulfur bacteria. Tightly coupled (cryptic) sulfur cycling, where physically associated oxidative and reductive metabolic types co-exist, has been identified in phototrophic microbial mats and consortia ( Fike et al, 2008 ; Wilbanks et al, 2014 ), and has recently been demonstrated in a companion investigation to this one ( Dawson et al, 2016 ) in the White Point (WP) chemosynthetic vent mat communities found in the Palos Verdes (PV) hydrothermal vent field in San Pedro, CA, USA. However, it is not clear how significant a role biological sulfur/sulfate reduction plays in the WP mats.…”

Characterizing Chemoautotrophy and Heterotrophy in Marine Archaea and Bacteria With Single-Cell Multi-isotope NanoSIP

“…(e.g., Kopf et al, 2015;Dawson et al, 2016;Wegener et al, 2016). Despite the frequent application of multi-isotope nanoSIP in relatively low-throughput analyses targeting particular taxa (e.g., dozens of FISH-identified cells), it has rarely been used as a high-throughput metabolic screening technique to characterize hundreds to thousands of individual, unidentified cells (Dawson et al, 2016;Arandia-Gorostidi et al, 2017). Used in this manner, it has the potential to analyze enough cells to generate metabolic activity profiles representative of the entire community.…”

“…These questions require culture independent, quantitative, singlecell approaches. Techniques to accomplish this exist, such as nanoSIP (Pett-Ridge and Weber, 2012) and microautoradiography (Okabe et al, 2004), and illustrate within-population variation in metabolism and growth (e.g., Popa et al, 2007;Finzi-Hart et al, 2009;Kopf et al, 2015;Zimmermann et al, 2015;Dawson et al, 2016;Dekas et al, 2016). However, these studies are often limited in scope due to their low-throughput, typically analyzing a few to dozens of cells per analysis.…”

Schrödinger’s microbes: Tools for distinguishing the living from the dead in microbial ecosystems

“…Nano-scale secondary ion mass spectrometry (NanoSIMS) has also been used to detect the uptake of labeled substrates as an indicator of metabolic activity, allowing for single-cell resolution, which can be useful for describing rare members of the community [ 156 , 157 ]. In combination, NanoSIMS and FISH can be used to link metabolism to phylogeny, allowing for the identification of active members of a microbial community [ 158 , 159 ].…”