Calculation and Interpretation of Substrate Assimilation Rates in Microbial Cells Based on Isotopic Composition Data Obtained by nanoSIMS

Abstract

Stable isotope probing (SIP) combined with nano-scale secondary ion mass spectrometry (nanoSIMS) is a powerful approach to quantify assimilation rates of elements such as C and N into individual microbial cells. Here, we use mathematical modeling to investigate how the derived rate estimates depend on the model used to describe substrate assimilation by a cell during a SIP incubation. We show that the most commonly used model, which is based on the simplifying assumptions of linearly increasing biomass of individual cells over time and no cell division, can yield underestimated assimilation rates when compared to rates derived from a model that accounts for cell division. This difference occurs because the isotopic labeling of a dividing cell increases more rapidly over time compared to a non-dividing cell and becomes more pronounced as the labeling increases above a threshold value that depends on the cell cycle stage of the measured cell. Based on the modeling results, we present formulae for estimating assimilation rates in cells and discuss their underlying assumptions, conditions of applicability, and implications for the interpretation of intercellular variability in assimilation rates derived from nanoSIMS data, including the impacts of storage inclusion metabolism. We offer the formulae as a Matlab script to facilitate rapid data evaluation by nanoSIMS users.

Polyphosphate Dynamics in Cable Bacteria

“…However, it is difficult to envision how the rate of poly-P synthesis can vary within a single cell, as one expects the concentration of both substrates (e.g., P i ) and catalysts (poly-P kinases) to be homogeneous within the cytoplasm of a single cell. Therefore, a more important factor could be the timing of poly-P synthesis and breakdown in individual poly-P granules in combination with the poly-P content of granules at the beginning of the labeling period ( Polerecky et al, 2021 ). As discussed above, substantial poly-P turnover likely occurred during our incubations, potentially involving multiple cycles of synthesis and breakdown ( Supplementary Model ).…”

“…Yet, even when the 18 O incorporation rate is similar and the labeling period is synchronized and identical among granules, one can expect variation, as differences in the 18 O labeling of poly-P granules can also arise due to a different granule size at the beginning of the labeling period. For example, if 18 O-labeled poly-P is incorporated into two differently sized granules and the rate of incorporation is the same for both granules, the smaller granule will have a greater 18 O atom fraction at the end of the incubation than the larger one ( Polerecky et al, 2021 ). This is because the incorporated 18 O is mixed across the whole granule, thus providing lower labeling levels for larger granules.…”

Resting cells of Skeletonema marinoi assimilate organic compounds and respire by dissimilatory nitrate reduction to ammonium in dark, anoxic conditions

“…We assume that resting cells are maintaining cell integrity but not dividing, and did therefore not compensate for divisions as described in (Polerecky et al, 2021). Potential turnover time (years) of cellular C or N, T , was calculated using the following formula: $$$$ T\ \left({\mathrm{year}\mathrm{s}}^{-1}\right)=\frac{1}{k\left({\mathrm{year}}^{-1}\right)} $$$$ …”

“…We assume that resting cells are maintaining cell integrity but not dividing, and did therefore not compensate for divisions as described in (Polerecky et al, 2021). Potential turnover time (years) of cellular C or N, T, was calculated using the following formula:…”

Ion Mobility Mass Spectrometry for the Separation and Characterization of Small Molecules

“…Single-cell MS has the advantages of direct and rapid detection without sample pretreatment and has a broad application prospect in the analysis of trace cell metabolites. 233 The commonly used ion sources are electrospray ionization (ESI), LAESI, secondary ion mass spectroscopy, 234 and MALDI. In the analysis process, there are usually the same challenges as ambient ionization MS, such as high matrix interference and difficulty in distinguishing isomers.…”