Data for: Linking cell size, Vmax, and Km in phototrophs and chemotrophs: Insights from Bayesian inference
Data files
Jun 17, 2025 version files 6.69 MB
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Data_and_Programs.zip
6.69 MB
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README.md
2.69 KB
Abstract
Microbial growth is often described in terms of resource uptake rates, making the understanding and parameterization of these rate-limiting processes critical for microbial modeling. In phototrophic plankton, theoretical studies suggest that nutrient uptake is limited by mechanistic processes involving membrane transporters, and it has been observed that the cell-specific maximum resource uptake rate (Vmax) follows a power-law relationship with cell size, as well as a trade-off between Vmax and the half-saturation constant (Km). These constraints may also apply to chemotrophic microorganisms; however, many datasets lack direct cell-size measurements. We therefore leveraged the assumption that prokaryotic cell sizes, Vmax, and Km each follow log-normal distributions, drawing parallels with established phytoplankton scaling laws. Our analysis suggests that chemotrophic organisms generally exhibit higher maximum uptake rate per dry weight (VmaxDW) and Km values than phototrophs, and that VmaxDW and Km are not strongly correlated when all chemotroph data are combined. Furthermore, the Bayesian-derived exponents for VmaxDW and Km exceeded those expected from allometric scaling relationships based on the membrane-transport capacity observed for phototrophs, implying that a range of additional factors likely affect observed kinetic parameters.
This repository contains all data and scripts required to reproduce the analyses and figures presented in the study.
Directory Structure
Data_and_Programs
├── README.md
├── Original_data
│ ├── README.md
│ ├── Microbial_Parameter_database_kinetics.csv
│ └── Phytoplankton_Data
│ ├── Brandenburg_et_al_2018_Ecol_Lett_Aost15.xlsx
│ ├── Brandenburg_et_al_2018_Ecol_Lett_Aost16.xlsx
│ ├── Brandenburg_et_al_2018_Ecol_Lett_Baltic.xlsx
│ ├── Marañón_et_al_2012_Ecol_Lett.xlsx
│ ├── Perrin_et_al_2015_Biogeosciences.xlsx
│ └── Rees_2014_Mar_Ecol_Prog_Ser.xls
├── Derived_data
│ ├── README.md
│ ├── chain.csv
│ ├── dataAll.json
│ ├── KmDB.csv
│ ├── logLikes.csv
│ ├── VmaxDB.csv
│ └── vol_weight.json
└── Scripts
├── README.md
├── DataProcessingAndPDFs.wl
├── Generate_Figure1.nb
├── Generate_Other_Figures.nb
├── Hartigans_dip_test.R
└── PlotSettings.wl
Directory Overview
Original_data/
Contains the original datasets used in this study, including:- A compiled microbial kinetics database (
Microbial_Parameter_database_kinetics.csv) - Published phytoplankton datasets (Excel files)
- A compiled microbial kinetics database (
Derived_data/
Contains processed datasets generated through our analysis pipeline:- Data used for MCMC sampling and statistical fitting
- Summary statistics and transformed data files
Scripts/
Includes all analysis scripts and plotting notebooks:- Wolfram Language scripts for data processing and figure generation
- An R script used for Hartigan’s dip test
Reproducibility
All scripts and data are organized to ensure reproducibility.
To regenerate figures and tables:
- Load the
.nbnotebooks inScripts/(e.g.,Generate_Figure1.nb) in Wolfram Mathematica. - Ensure relative paths remain consistent with this directory structure.
- Required packages are included via
Get[]commands in the notebooks.
All computations and figure generations have been tested using Wolfram Mathematica version 12.0.0.
Functionality with other versions has not been verified and may result in unexpected behavior.
Contact
For questions regarding the dataset or code, please contact:
Mayumi Seto (seto@ics.nara-wu.ac.jp or setomayumi@gmail.com)
Department of Chemistry, Biology, and Environmental Science
Nara Women’s University, Japan
