Signatures of salinity gradients in the chemical composition of proteins (2020)

This vignette was compiled on 2024-03-11 with JMDplots 1.2.19-11 and canprot 1.1.2-39.

For Figure 3, the RefSeq database release NA is used for the proteomes of nif-bearing organisms (release 201 was used in the paper).

The QEC basis species (glutamine, glutamic acid, cysteine, H₂O, O₂) are used for the analysis of stoichiometric hydration state (n_H₂O).

Number of reactions for each amino acid in E. coli metabolic reconstruction

Reaction equations used for this calculation are from Feist et al. (2007).

gradH2O0()

## Glu Ser Asp Gln Ala Gly Met Cys Thr Arg 
##  52  25  23  18  15  15  15  13  12  11 
## Lys Asn Pro Trp Val Tyr His Ile Leu Phe 
##  10   9   9   8   7   7   6   6   6   5

Comparison of different sets of basis species (Figure 1)

gradH2O1()

Schematic of n_H₂O and Z_C calculations (Figure 2)

gradH2O2()

n_H₂O-Z_C scatterplots for redox gradients and the Baltic Sea (Figure 3)

gradH2O3()

Data sources: Bison Pool (BP; Havig et al., 2011; Swingley et al., 2012); diffuse submarine vents (DV; Reveillaud et al., 2016; Fortunato et al., 2018); Guerrero Negro microbial mat (GN; Kunin et al., 2008); nitrogenase-bearing organisms (NF; Poudel et al., 2018); Baltic Sea (Dupont et al., 2014).

n_H₂O for Baltic Sea metagenome and metatranscriptome in different size fractions (Figure 4)

gradH2O4()

Data sources: metagenome (Dupont et al., 2014) and metatranscriptome (Asplund-Samuelsson et al., 2016).

n_H₂O-Z_C for freshwater, marine, and hypersaline environments (Figure 5)

gradH2O5()

Data sources: Amazon river (Satinsky et al., 2015) and plume (Satinsky et al., 2014); freshwater and marine metagenomes (Eiler et al., 2014); hypersaline datasets Kulunda Steppe (KS; Vavourakis et al., 2016), Santa Pola (SP; Ghai et al., 2011; Fernandez et al., 2013), San Francisco South Bay (SB; Kimbrel et al., 2018).

n_H₂O-Z_C and GRAVY-pI plots for Baltic Sea and Rodriguez-Brito et al. data (Figure 6)

gradH2O6()

Data sources: Dupont et al. (2014) and Rodriguez-Brito et al. (2010).

Differential gene and protein expression; time-course experiments and NaCl or organic solutes (Figure 7)

gradH2O7()

Data sources: Panel (a): a–c: Kocharunchitt et al. (2014); d–f: Solheim et al. (2014); g–i: Finn et al. (2015); j–k: Han et al. (2017); l–n: Qiao et al. (2013). Panel (b): A–B: Kanesaki et al. (2002); C–D: Han et al. (2005); E–F: Kohler et al. (2015); G–J: Finn et al. (2015); K–L: Shabala et al. (2009); M–N: Withman et al. (2013). Panels (c) to (f): See the vignettes JMDplots::mkvig("osmotic_bact") and JMDplots::mkvig("osmotic_halo"). Links to static vignettes: osmotic_bact and osmotic_halo.

References

Asplund-Samuelsson J, Sundh J, Dupont CL, Allen AE, McCrow JP, Celepli NA, Bergman B, Ininbergs K, Ekman M. 2016. Diversity and expression of bacterial metacaspases in an aquatic ecosystem. Frontiers in Microbiology 7: 1043. doi: 10.3389/fmicb.2016.01043

Dupont CL, Larsson J, Yooseph S, Ininbergs K, Goll J, Asplund-Samuelsson J, McCrow JP, Celepli N, Allen LZ, Ekman M, et al. 2014. Functional tradeoffs underpin salinity-driven divergence in microbial community composition. PLOS One 9(2): e89549. doi: 10.1371/journal.pone.0089549

Eiler A, Zaremba-Niedzwiedzka K, Martínez-García M, McMahon KD, Stepanauskas R, Andersson SGE, Bertilsson S. 2014. Productivity and salinity structuring of the microplankton revealed by comparative freshwater metagenomics. Environmental Microbiology 16(9): 2682–2698 –. doi: 10.1111/1462-2920.12301

Fernandez AB, Ghai R, Martin-Cuadrado AB, Sanchez-Porro C, Rodriguez-Valera F, Ventosa A. 2013. Metagenome sequencing of prokaryotic microbiota from two hypersaline ponds of a marine saltern in Santa Pola, Spain. Genome Announcements 1(6): e00933–13. doi: 10.1128/genomea.00933-13

Finn S, Rogers L, Händler K, McClure P, Amézquita A, Hinton JCD, Fanning S. 2015. Exposure of Salmonella enterica serovar Typhimurium to three humectants used in the food industry induces different osmoadaptation systems. Applied and Environmental Microbiology 81(19): 6800–6811. doi: 10.1128/AEM.01379-15

Fortunato CS, Larson B, Butterfield DA, Huber JA. 2018. Spatially distinct, temporally stable microbial populations mediate biogeochemical cycling at and below the seafloor in hydrothermal vent fluids. Environmental Microbiology 20(2): 769–784. doi: 10.1111/1462-2920.14011

Ghai R, Pašić L, Fernández AB, Martin-Cuadrado A-B, Mizuno CM, McMahon KD, Papke RT, Stepanauskas R, Rodriguez-Brito B, Rohwer F, et al. 2011. New abundant microbial groups in aquatic hypersaline environments. Scientific Reports 1: 135. doi: 10.1038/srep00135

Han D, Link H, Liesack W. 2017. Response of Methylocystis sp. Strain SC2 to salt stress: Physiology, global transcriptome, and amino acid profiles. Applied and Environmental Microbiology 83(20): e00866–17. doi: 10.1128/AEM.00866-17

Han Y, Zhou D, Pang X, Zhang L, Song Y, Tong Z, Bao J, Dai E, Wang J, Guo Z, et al. 2005. Comparative transcriptome analysis of Yersinia pestis in response to hyperosmotic and high-salinity stress. Research in Microbiology 156(3): 403–415. doi: 10.1016/j.resmic.2004.10.004

Havig JR, Raymond J, Meyer-Dombard DR, Zolotova N, Shock EL. 2011. Merging isotopes and community genomics in a siliceous sinter-depositing hot spring. Journal of Geophysical Research 116: G01005. doi: 10.1029/2010JG001415

Kanesaki Y, Suzuki I, Allakhverdiev SI, Mikami K, Murata N. 2002. Salt stress and hyperosmotic stress regulate the expression of different sets of genes in Synechocystis sp. PCC 6803. Biochemical and Biophysical Research Communications 290(1): 339–348. doi: 10.1006/bbrc.2001.6201

Kimbrel JA, Ballor N, Wu Y-W, David MM, Hazen TC, Simmons BA, Singer SW, Jansson JK. 2018. Microbial community structure and functional potential along a hypersaline gradient. Frontiers in Microbiology 9: 1492. doi: 10.3389/fmicb.2018.01492

Kocharunchitt C, King T, Gobius K, Bowman JP, Ross T. 2014. Global genome response of Escherichia coli O157:H7 Sakai during dynamic changes in growth kinetics induced by an abrupt downshift in water activity. PLOS One 9(3): e90422. doi: 10.1371/journal.pone.0090422

Kohler C, Lourenço RF, Bernhardt J, Albrecht D, Schüler J, Hecker M, Gomes SL. 2015. A comprehensive genomic, transcriptomic and proteomic analysis of a hyperosmotic stress sensitive α-proteobacterium. BMC Microbiology 15: 71. doi: 10.1186/s12866-015-0404-x

Kunin V, Raes J, Harris JK, Spear JR, Walker JJ, Ivanova N, Mering C von, Bebout BM, Pace NR, Bork P, et al. 2008. Millimeter-scale genetic gradients and community-level molecular convergence in a hypersaline microbial mat. Molecular Systems Biology 4: 198. doi: 10.1038/msb.2008.35

Poudel S, Colman DR, Fixen KR, Ledbetter RN, Zheng Y, Pence N, Seefeldt LC, Peters JW, Harwood CS, Boyd ES. 2018. Electron transfer to nitrogenase in different genomic and metabolic backgrounds. Journal of Bacteriology 200(10): e00757–17. doi: 10.1128/JB.00757-17

Qiao J, Huang S, Te R, Wang J, Chen L, Zhang W. 2013. Integrated proteomic and transcriptomic analysis reveals novel genes and regulatory mechanisms involved in salt stress responses in Synechocystis sp. PCC 6803. Applied Microbiology and Biotechnology 97(18): 8253–8264. doi: 10.1007/s00253-013-5139-8

Reveillaud J, Reddington E, McDermott J, Algar C, Meyer JL, Sylva S, Seewald J, German CR, Huber JA. 2016. Subseafloor microbial communities in hydrogen-rich vent fluids from hydrothermal systems along the Mid-Cayman Rise. Environmental Microbiology 18(6): 1970–1987. doi: 10.1111/1462-2920.13173

Rodriguez-Brito B, Li L, Wegley L, Furlan M, Angly F, Breitbart M, Buchanan J, Desnues C, Dinsdale E, Edwards R, et al. 2010. Viral and microbial community dynamics in four aquatic environments. The ISME Journal 4: 739–751. doi: 10.1038/ismej.2010.1

Satinsky BM, Fortunato CS, Doherty M, Smith CB, Sharma S, Ward ND, Krusche AV, Yager PL, Richey JE, Moran MA, et al. 2015. Metagenomic and metatranscriptomic inventories of the lower Amazon River, May 2011. Microbiome 3(1): 39. doi: 10.1186/s40168-015-0099-0

Satinsky BM, Zielinski BL, Doherty M, Smith CB, Sharma S, Paul JH, Crump BC, Moran MA. 2014. The Amazon continuum dataset: Quantitative metagenomic and metatranscriptomic inventories of the Amazon River plume, June 2010. Microbiome 2(1): 17. doi: 10.1186/2049-2618-2-17

Shabala L, Bowman J, Brown J, Ross T, McMeekin T, Shabala S. 2009. Ion transport and osmotic adjustment in Escherichia coli in response to ionic and non-ionic osmotica. Environmental Microbiology 11(1): 137–148. doi: 10.1111/j.1462-2920.2008.01748.x

Solheim M, La Rosa SL, Mathisen T, Snipen LG, Nes IF, Brede DA. 2014. Transcriptomic and functional analysis of NaCl-induced stress in Enterococcus faecalis. PLOS One 9(4): 1–13. doi: 10.1371/journal.pone.0094571

Swingley WD, Meyer-Dombard DR, Shock EL, Alsop EB, Falenski HD, Havig JR, Raymond J. 2012. Coordinating environmental genomics and geochemistry reveals metabolic transitions in a hot spring ecosystem. PLOS One 7(6): e38108. doi: 10.1371/journal.pone.0038108

Vavourakis CD, Ghai R, Rodriguez-Valera F, Sorokin DY, Tringe SG, Hugenholtz P, Muyzer G. 2016. Metagenomic insights into the uncultured diversity and physiology of microbes in four hypersaline soda lake brines. Frontiers in Microbiology 7: 211. doi: 10.3389/fmicb.2016.00211

Withman B, Gunasekera TS, Beesetty P, Agans R, Paliy O. 2013. Transcriptional responses of uropathogenic Escherichia coli to increased environmental osmolality caused by salt or urea. Infection and Immunity 81(1): 80–89. doi: 10.1128/IAI.01049-12

JMDplots vignettes

Signatures of salinity gradients in the chemical composition of proteins (2020)

Number of reactions for each amino acid in E. coli metabolic reconstruction

Comparison of different sets of basis species (Figure 1)

Schematic of nH2O and ZC calculations (Figure 2)

nH2O-ZC scatterplots for redox gradients and the Baltic Sea (Figure 3)

nH2O for Baltic Sea metagenome and metatranscriptome in different size fractions (Figure 4)

nH2O-ZC for freshwater, marine, and hypersaline environments (Figure 5)