This vignette runs the code to make the plots from the following paper:
Dick JM, Meng D. 2023. Community- and genome-based evidence for a shaping influence of redox potential on bacterial protein evolution. mSystems 8(3): e00014-23. doi: 10.1128/msystems.00014-23
This vignette was compiled on 2024-03-11 with JMDplots 1.2.19-11 and chem16S 1.0.0-16.
## [1] "64 genera not matched to RefSeq"
## [1] "Archaeal genera: Methanobrevibacter Methanosphaera"
Data sources: List of strictly anaerobic and aerotolerant genera (Million and Raoult, 2018), Metaproteomes: Manus Basin Inactive Chimney (Meier et al., 2019), Manus Basin Active Chimneys (Pjevac et al., 2018), Soda Lake Biomats (Kleiner et al., 2017), Mock Communities (Kleiner et al., 2017), Saanich Inlet (Hawley et al., 2017).
Data sources: (b) ORP and pH (Diez-Ercilla et al., 2019) to calculate Eh7. (c) 16S rRNA gene sequences (Rundell et al., 2014) to calculate ZC.
Data sources: (a) coastlineWorld dataset in R package oce (Kelley and Richards, 2022); shapefiles for North American Great Lakes (USGS, 2010). (b) Outline is from Baas Becking et al. (1960).
Data sources: (a) Daya Bay (Wu et al., 2021), Bay of Biscay (Lanzén et al., 2021), Hunan Province (Meng et al., 2019). (c) 1 acidic and 2 circumneutral to alkaline New Zealand hot springs (Power et al., 2018), 3 Eastern Tibetan Plateau (Guo et al., 2020), 4 Uzon Caldera (Peltek et al., 2020), 5 Southern Tibetan Plateau (Ma et al., 2021).
colnames <- c("Ntot", "Npos", "Nneg", "p")
kable(orp16S_T1(), col.names = rep(colnames, 2)) %>%
add_header_above(c(" " = 1, "Bacteria" = 4, "Archaea" = 4))
Ntot | Npos | Nneg | p | Ntot | Npos | Nneg | p | |
---|---|---|---|---|---|---|---|---|
River & Seawater | 10 | 6 | 4 | 0.37700 | 4 | 4 | 0 | 0.06200 |
Lake & Pond | 9 | 6 | 3 | 0.25400 | 3 | 2 | 1 | 0.50000 |
Geothermal | 5 | 5 | 0 | 0.03100 | 4 | 1 | 3 | 0.93800 |
Hyperalkaline | 6 | 5 | 1 | 0.10900 | 3 | 2 | 1 | 0.50000 |
Groundwater | 10 | 7 | 3 | 0.17200 | 6 | 2 | 4 | 0.89100 |
Sediment | 16 | 11 | 5 | 0.10500 | 6 | 2 | 4 | 0.89100 |
Soil | 12 | 10 | 2 | 0.01900 | 5 | 2 | 3 | 0.81200 |
Total | 68 | 50 | 18 | 0.00007 | 31 | 15 | 16 | 0.63995 |
colnames <- c("Ntot", "Npos", "Nneg", "p")
kable(orp16S_T1(samesign = TRUE), col.names = rep(colnames, 2)) %>%
add_header_above(c(" " = 1, "Bacteria" = 4, "Archaea" = 4))
Ntot | Npos | Nneg | p | Ntot | Npos | Nneg | p | |
---|---|---|---|---|---|---|---|---|
River & Seawater | 3 | 3 | 0 | 0.12500 | 2 | 2 | 0 | 0.25000 |
Lake & Pond | 5 | 3 | 2 | 0.50000 | 1 | 1 | 0 | 0.50000 |
Geothermal | 3 | 3 | 0 | 0.12500 | 0 | 0 | 0 | NA |
Hyperalkaline | 3 | 3 | 0 | 0.12500 | 3 | 2 | 1 | 0.50000 |
Groundwater | 3 | 3 | 0 | 0.12500 | 2 | 0 | 2 | 1.00000 |
Sediment | 10 | 7 | 3 | 0.17200 | 3 | 0 | 3 | 1.00000 |
Soil | 9 | 9 | 0 | 0.00200 | 3 | 1 | 2 | 0.87500 |
Total | 36 | 31 | 5 | 0.00001 | 14 | 6 | 8 | 0.78802 |
# Read Dataset S3 (created by orp16S_D3())
dat <- read.csv(system.file("extdata/orp16S/Dataset_S3.csv", package = "JMDplots"))
perc_bac <- round(mean(subset(dat, lineage == "Bacteria")$mapperc))
perc_arc <- round(mean(subset(dat, lineage == "Archaea")$mapperc))
message(paste0(perc_bac, "% for bacteria, ", perc_arc, "% for archaea"))
## 86% for bacteria, 77% for archaea
Baas Becking LGM, Kaplan IR, Moore D. 1960. Limits of the natural environment in terms of pH and oxidation-reduction potentials. The Journal of Geology 68(3): 243–284. doi: 10.1086/626659
Diez-Ercilla M, Falagán C, Yusta I, Sánchez-España J. 2019. Metal mobility and mineral transformations driven by bacterial activity in acidic pit lake sediments: Evidence from column experiments and sequential extraction. Journal of Soils and Sediments 19(3): 1527–1542. doi: 10.1007/s11368-018-2112-2
Guo L, Wang G, Sheng Y, Sun X, Shi Z, Xu Q, Mu W. 2020. Temperature governs the distribution of hot spring microbial community in three hydrothermal fields, Eastern Tibetan Plateau Geothermal Belt, Western China. Science of The Total Environment 720: 137574. doi: 10.1016/j.scitotenv.2020.137574
Hawley AK, Torres-Beltrán M, Zaikova E, Walsh DA, Mueller A, Scofield M, Kheirandish S, Payne C, Pakhomova L, Bhatia M, et al. 2017. A compendium of multi-omic sequence information from the Saanich Inlet water column. Scientific Data 4(1): 170160. doi: 10.1038/sdata.2017.160
Kelley D, Richards C. 2022. oce: Analysis of Oceanographic Data. Available at https://cran.r-project.org/package=oce.
Kleiner M, Thorson E, Sharp CE, Dong X, Liu D, Li C, Strous M. 2017. Assessing species biomass contributions in microbial communities via metaproteomics. Nature Communications 8(1): 1558. doi: 10.1038/s41467-017-01544-x
Lanzén A, Mendibil I, Borja Á, Alonso-Sáez L. 2021. A microbial mandala for environmental monitoring: Predicting multiple impacts on estuarine prokaryote communities of the Bay of Biscay. Molecular Ecology 30(13): 2969–2987. doi: 10.1111/mec.15489
Ma L, Wu G, Yang J, Huang L, Phurbu D, Li W-J, Jiang H. 2021. Distribution of hydrogen-producing bacteria in Tibetan hot springs, China. Frontiers in Microbiology 12: 1789. doi: 10.3389/fmicb.2021.569020
Meier DV, Pjevac P, Bach W, Markert S, Schweder T, Jamieson J, Petersen S, Amann R, Meyerdierks A. 2019. Microbial metal-sulfide oxidation in inactive hydrothermal vent chimneys suggested by metagenomic and metaproteomic analyses. Environmental Microbiology 21(2): 682–701. doi: 10.1111/1462-2920.14514
Meng D, Li J, Liu T, Liu Y, Yan M, Hu J, Li X, Liu X, Liang Y, Liu H, et al. 2019. Effects of redox potential on soil cadmium solubility: Insight into microbial community. Journal of Environmental Sciences 75: 224–232. doi: 10.1016/j.jes.2018.03.032
Million M, Raoult D. 2018. Linking gut redox to human microbiome. Human Microbiome Journal 10: 27–32. doi: 10.1016/j.humic.2018.07.002
Peltek SE, Bryanskaya AV, Uvarova YE, Rozanov AS, Ivanisenko TV, Ivanisenko VA, Lazareva EV, Saik OV, Efimov VM, Zhmodik SM, et al. 2020. Young «oil site» of the Uzon Caldera as a habitat for unique microbial life. BMC Microbiology 20(2): 349. doi: 10.1186/s12866-020-02012-1
Pjevac P, Meier DV, Markert S, Hentschker C, Schweder T, Becher D, Gruber-Vodicka HR, Richter M, Bach W, Amann R, et al. 2018. Metaproteogenomic profiling of microbial communities colonizing actively venting hydrothermal chimneys. Frontiers in Microbiology 9: 680. doi: 10.3389/fmicb.2018.00680
Power JF, Carere CR, Lee CK, Wakerley GLJ, Evans DW, Button M, White D, Climo MD, Hinze AM, Morgan XC, et al. 2018. Microbial biogeography of 925 geothermal springs in New Zealand. Nature Communications 9(1): 2876. doi: 10.1038/s41467-018-05020-y
Rundell EA, Banta LM, Ward DV, Watts CD, Birren B, Esteban DJ. 2014. 16S rRNA gene survey of microbial communities in Winogradsky columns. PLOS One 9(8): e104134. doi: 10.1371/journal.pone.0104134
USGS. 2010. Great Lakes and Watersheds Shapefiles. U.S. Geological Survey. Available at https://www.sciencebase.gov/catalog/item/530f8a0ee4b0e7e46bd300dd.
Wu J, Hong Y, Liu X, Hu Y. 2021. Variations in nitrogen removal rates and microbial communities over sediment depth in Daya Bay, China. Environmental Pollution 286: 117267. doi: 10.1016/j.envpol.2021.117267