[CHNOSZ-commits] r904 - in pkg/CHNOSZ: . inst man vignettes
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Fri May 23 08:21:17 CEST 2025
Author: jedick
Date: 2025-05-23 08:21:17 +0200 (Fri, 23 May 2025)
New Revision: 904
Modified:
pkg/CHNOSZ/DESCRIPTION
pkg/CHNOSZ/inst/NEWS.Rd
pkg/CHNOSZ/man/extdata.Rd
pkg/CHNOSZ/vignettes/anintro.Rmd
pkg/CHNOSZ/vignettes/postprocess.sh
pkg/CHNOSZ/vignettes/vig.bib
Log:
Add Cas example for groupwise relative stabilities
Modified: pkg/CHNOSZ/DESCRIPTION
===================================================================
--- pkg/CHNOSZ/DESCRIPTION 2025-05-23 01:32:12 UTC (rev 903)
+++ pkg/CHNOSZ/DESCRIPTION 2025-05-23 06:21:17 UTC (rev 904)
@@ -1,6 +1,6 @@
Date: 2025-05-23
Package: CHNOSZ
-Version: 2.1.0-75
+Version: 2.1.0-76
Title: Thermodynamic Calculations and Diagrams for Geochemistry
Authors at R: c(
person("Jeffrey", "Dick", , "j3ffdick at gmail.com", role = c("aut", "cre"),
Modified: pkg/CHNOSZ/inst/NEWS.Rd
===================================================================
--- pkg/CHNOSZ/inst/NEWS.Rd 2025-05-23 01:32:12 UTC (rev 903)
+++ pkg/CHNOSZ/inst/NEWS.Rd 2025-05-23 06:21:17 UTC (rev 904)
@@ -87,7 +87,7 @@
\subsection{DOCUMENTATION}{
\itemize{
- \item Major revision of \file{anintro.Rmd}.
+ \item Major revision of \viglink{anintro}.
\item Add \file{demo/MgATP.R}: speciation of ATP with H\S{+} and
Mg\S{+2}, based on
@@ -177,8 +177,8 @@
is \dQuote{log \emph{f}O\s{2}}.
\item Add scripts and data files in \code{extdata/protein/Cas} for amino
- acid compositions of CRISPR-Cas proteins in different classes and
- subtypes listed by
+ acid compositions of CRISPR-associated (Cas) proteins in different
+ classes and subtypes listed by
\href{https://doi.org/10.1038/s41579-019-0299-x}{Makarova et al. (2020)}.
Modified: pkg/CHNOSZ/man/extdata.Rd
===================================================================
--- pkg/CHNOSZ/man/extdata.Rd 2025-05-23 01:32:12 UTC (rev 903)
+++ pkg/CHNOSZ/man/extdata.Rd 2025-05-23 06:21:17 UTC (rev 904)
@@ -31,7 +31,7 @@
\item \code{TBD+05.csv} lists genes with transcriptomic expression changes in carbon limitation stress response experiments in yeast (Tai et al., 2005).
\item \code{TBD+05_aa.csv} has the amino acid compositions of proteins coded by those genes.
The last two files are used in \code{demo{"rank.affinity"}}.
- \item \code{Cas} has scripts and data files for amino acid compositions of CRISPR-Cas proteins.
+ \item \code{Cas} has scripts and data files for amino acid compositions of CRISPR associated (Cas) proteins.
\itemize{
\item \file{Cas_uniprot.csv}: class, subtype, organism, locus tag, gene names, and effector proteins from Makarova et al. (2020); UniProt IDs found by searching databases.
\item \file{download.R}: script to download sequences in FASTA format from UniProt and UniParc.
Modified: pkg/CHNOSZ/vignettes/anintro.Rmd
===================================================================
--- pkg/CHNOSZ/vignettes/anintro.Rmd 2025-05-23 01:32:12 UTC (rev 903)
+++ pkg/CHNOSZ/vignettes/anintro.Rmd 2025-05-23 06:21:17 UTC (rev 904)
@@ -51,13 +51,6 @@
```
```{r HTML, include=FALSE}
-#logfO2 <- "log<i>f</i><sub>O<sub>2</sub></sub>"
-#zc <- "<i>Z</i><sub>C</sub>"
-#o2 <- "O<sub>2</sub>"
-#h2o <- "H<sub>2</sub>O"
-#sio2 <- "SiO<sub>2</sub>"
-#ch4 <- "CH<sub>4</sub>"
-
# Some frequently used HTML expressions
# Use lowercase because some of these are used as variables in the examples
h2o <- "H<sub>2</sub>O"
@@ -66,6 +59,7 @@
co2 <- "CO<sub>2</sub>"
h2s <- "H<sub>2</sub>S"
Psat <- "<i>P</i><sub>sat</sub>"
+zc <- "<i>Z</i><sub>C</sub>"
```
```{r setup, include=FALSE}
@@ -1553,7 +1547,7 @@
### 7. Additional protein analysis
-The **canprot** package provides a different interface for calculating *Z*~C~ and other chemical analyses of proteins from their amino acid composition:
+The **canprot** package provides a different interface for calculating `r zc` and other chemical analyses of proteins from their amino acid composition:
```{r protein_13}
# Load canprot package
@@ -1646,8 +1640,163 @@
normalization of protein formulas and optimizing physicochemical parameters.
The metastable equilibrium model provides a theoretical framework for predicting how chemical conditions influence relative protein abundances.
-### One more thing: Groupwise relative stabilities
+### Comparing evolutionary branches: Groupwise relative stabilities of CRISPR-associated (Cas) proteins
+CRISPR-associated proteins (Cas) have important functions in microbial immunity to viruses and in biotechnology for gene editing.
+Plotting their relative stabilities could relate their evolution to environmental variables.
+
+Unlike minerals or inorganic aqueous species, the scope of interest is not single molecules but rather sets of related sequences that belong to evolutionary classes or types.
+For example, each type of CRISPR-Cas system (numbered I--VI) is represented by various numbers of genomes in the classification presented by @MWI_20.
+This is visualized in the following diagram, showing the `r zc` and number of amino acids in the effector modules.
+(The effector module combines with CRISPR RNA (crRNA) to form the effector complex that targets a specific DNA sequence.)
+The larger size of effector modules of many Class 1 systems is associated with multiple Cas proteins, which were combined to calculate `r zc`.
+
+```{r Cas_Zc, echo=FALSE, fig.cap = "Carbon oxidation state and size of CRISPR-Cas effector complexes", cache=TRUE}
+# Read data table
+file <- system.file("extdata/protein/Cas/Cas_uniprot.csv", package = "CHNOSZ")
+dat <- read.csv(file)
+# Use UniProt ID as the file name
+ID <- dat$UniProt
+# In case UniProt ID is missing, use alternate ID
+ID[ID == ""] <- dat$Protein[ID == ""]
+# Store ID in data frame
+dat$ID <- ID
+# Remove missing IDs
+dat <- subset(dat, ID != "")
+# Keep proteins in effector complexes
+dat <- subset(dat, Effector)
+
+# Read amino acid compositions
+aafile <- system.file("extdata/protein/Cas/Cas_aa.csv", package = "CHNOSZ")
+aa <- read.csv(aafile)
+
+# Loop over subtypes (I-A, I-B etc.)
+subtypes <- unique(dat$Subtype)
+effector_aa_list <- lapply(subtypes, function(subtype) {
+ # Get the IDs for this subtype
+ idat <- dat$Subtype == subtype
+ ID <- dat$ID[idat]
+ # Sum the amino acid compositions of all effector proteins in this subtype
+ iaa <- aa$ref %in% ID
+ all_aa <- aa[iaa, ]
+ summed_aa <- sum_aa(all_aa)
+ # Put in all gene names and IDs
+ summed_aa$protein <- paste(all_aa$protein, collapse = ",")
+ summed_aa$ref <- paste(all_aa$ref, collapse = ",")
+ # Put in the subtype
+ summed_aa$abbrv <- subtype
+ # Return the amino acid composition for this subtype
+ summed_aa
+})
+# Make a data frame of amino acid compositions of effector proteins
+effector_aa <- do.call(rbind, effector_aa_list)
+
+# List each type (I to VI)
+type_names <- c("I", "II", "III", "IV", "V", "VI")
+# Find which subtypes belong to each type
+subtype_type <- sapply(strsplit(effector_aa$abbrv, "-"), "[", 1)
+# Get class for each subtype
+class <- ifelse(subtype_type %in% c("I", "III", "IV"), 1, 2)
+
+# Assign colors for classes
+col1 <- hcl.colors(5, "Peach")[1:3]
+col2 <- hcl.colors(5, "Purp")[1:3]
+type_col <- c(
+ # Class 1
+ I = col1[1], III = col1[2], IV = col1[3],
+ # Class 2
+ II = col2[1], V = col2[2], VI = col2[3]
+)
+# Assign point size for classes
+type_cex <- c(
+ I = 1, III = 1.5, IV = 2,
+ II = 1, V = 1.5, VI = 2
+)
+# Get colors and sizes for subtypes
+subtype_col <- type_col[subtype_type]
+subtype_cex <- type_cex[subtype_type]
+
+# Calculate Zc and number of amino acids in effector complexes
+Zc <- canprot::Zc(effector_aa)
+naa <- protein.length(effector_aa)
+# Make plot
+par(mar = c(5, 5, 1, 1))
+plot(naa, Zc, pch = class + 20, cex = subtype_cex, col = subtype_col, bg = subtype_col, xlab = "Number of amino acids", ylab = quote(italic(Z)[C]))
+legend("topright", c("I ", "III", "IV"), pch = 21, pt.cex = type_cex[1:3], col = col1, pt.bg = col1, title = "Class 1 ", cex = 0.95)
+legend("topright", c("II", "V", "VI"), pch = 22, pt.cex = type_cex[4:6], col = col2, pt.bg = col2, title = "Class 2", bty = "n", cex = 0.95)
+```
+
+<button id="B-Cas_Zc" onclick="ToggleDiv('Cas_Zc')">Show code</button>
+<div id="D-Cas_Zc" style="display: none">
+```{r Cas_Zc, eval=FALSE, cache=FALSE}
+```
+</div>
+
+Plotting the relative stabilies of Cas effector modules from all `r length(Zc)` genomes
+(the number of points in the previous diagram) would result in a complex, hard-to-interpret diagram.
+Instead, here we visualize relative stabilities of groups, one for each of the CRISPR-Cas types (I--VI).
+This is done by first calculating the formation affinities for all effector modules, ranking them, then finding the average rank for each type.
+
+The function used for this, `rank.affinity()`, includes a rescaling step to handle groups with different numbers of members.
+We can see that rescaling is necessary because the average rank of a group with one member is bounded by 1 and 42,
+but the average rank of a group with three members is bounded by 2 (the average of 1, 2, and 3) and 41 (the average of 40, 41, and 42).
+Instead of representing maximum affinity as in previous diagrams, the stability fields here represent maximum average rank of affinity after rescaling.
+
+```{r Cas_stability, echo=FALSE, fig.cap = "Groupwise relative stabilities of Cas effector modules in different types of CRISPR-Cas systems as a function of Eh and temperature; dashed line is water stability limit", cache=TRUE}
+# Setup plot
+par(mfrow = c(1, 2))
+
+# Load amino acid compositions to CHNOSZ
+iprotein <- add.protein(effector_aa)
+# Calculate affinities as a function of Eh and T
+basis("QEC+")
+swap.basis("O2", "e-")
+aout <- affinity(T = c(0, 120), Eh = c(-0.8, 0), iprotein = iprotein)
+
+# Identify types
+types <- lapply(type_names, `==`, subtype_type)
+names(types) <- type_names
+# Calculate average rank for each type
+arank <- rank.affinity(aout, groups = types)
+# Make first diagram
+d <- diagram(arank, fill = type_col[type_names])
+water.lines(d, lty = 2)
+title("Stable types", font.main = 1)
+
+# Take out stable types
+istable <- unique(as.numeric(d$predominant))
+stable_type_names <- type_names[istable]
+itype_stable <- subtype_type %in% stable_type_names
+
+# Get metastable types and subtypes
+type_names <- type_names[-istable]
+effector_aa <- effector_aa[!itype_stable, ]
+subtype_type <- sapply(strsplit(effector_aa$abbrv, "-"), "[", 1)
+types <- lapply(type_names, `==`, subtype_type)
+names(types) <- type_names
+
+# Make second diagram
+iprotein <- add.protein(effector_aa)
+aout <- affinity(T = c(0, 120), Eh = c(-0.8, 0), iprotein = iprotein)
+arank <- rank.affinity(aout, groups = types)
+d <- diagram(arank, fill = type_col[type_names])
+water.lines(d, lty = 2)
+title("Metastable types", font.main = 1)
+```
+
+<button id="B-Cas_stability" onclick="ToggleDiv('Cas_stability')">Show code</button>
+<div id="D-Cas_stability" style="display: none">
+```{r Cas_stability, eval=FALSE, cache=FALSE}
+```
+</div>
+
+The first diagram shows the stable types.
+These were then removed to show the metastable types in the second diagram.
+
+An interesting result is the relative stability of Type III effector modules at reducing conditions (low Eh).
+Notably, the Type III system was proposed to have evolved first in Class 1 [@MWK22].
+Taken together, these observations support the notion of adaptation of Type III Cas sequences to reducing conditions on early Earth.
+
## Further Resources - Demos
Explore demos with `demo(package = "CHNOSZ")`.
Modified: pkg/CHNOSZ/vignettes/postprocess.sh
===================================================================
--- pkg/CHNOSZ/vignettes/postprocess.sh 2025-05-23 01:32:12 UTC (rev 903)
+++ pkg/CHNOSZ/vignettes/postprocess.sh 2025-05-23 06:21:17 UTC (rev 904)
@@ -36,6 +36,7 @@
sed -i 's/<code>equilibrate(loga.balance\ =\ 0)/<code><a href="..\/html\/equilibrate.html" style="background-image:none;color:green;">equilibrate(loga.balance\ =\ 0)<\/a>/g' anintro.html
sed -i 's/<code>makeup()/<code><a href="..\/html\/makeup.html" style="background-image:none;color:green;">makeup()<\/a>/g' anintro.html
sed -i 's/<code>Berman()/<code><a href="..\/html\/Berman.html" style="background-image:none;color:green;">Berman()<\/a>/g' anintro.html
+sed -i 's/<code>rank.affinity()/<code><a href="..\/html\/rank.affinity.html" style="background-image:none;color:green;">rank.affinity()<\/a>/g' anintro.html
# Functions with side effects (red)
sed -i 's/<code>basis()/<code><a href="..\/html\/basis.html" style="background-image:none;color:red;">basis()<\/a>/g' anintro.html
Modified: pkg/CHNOSZ/vignettes/vig.bib
===================================================================
--- pkg/CHNOSZ/vignettes/vig.bib 2025-05-23 01:32:12 UTC (rev 903)
+++ pkg/CHNOSZ/vignettes/vig.bib 2025-05-23 06:21:17 UTC (rev 904)
@@ -828,3 +828,29 @@
volume = {97},
doi = {10.2113/gsecongeo.97.6.1167},
}
+
+ at Article{MWI_20,
+ author = {Makarova, Kira S. and Wolf, Yuri I. and Iranzo, Jaime and Shmakov, Sergey A. and Alkhnbashi, Omer S. and Brouns, Stan J. J. and Charpentier, Emmanuelle and Cheng, David and Haft, Daniel H. and Horvath, Philippe and Moineau, Sylvain and Mojica, Francisco J. M. and Scott, David and Shah, Shiraz A. and Siksnys, Virginijus and Terns, Michael P. and Venclovas, Česlovas and White, Malcolm F. and Yakunin, Alexander F. and Yan, Winston and Zhang, Feng and Garrett, Roger A. and Backofen, Rolf and van der Oost, John and Barrangou, Rodolphe and Koonin, Eugene V.},
+ journal = {Nature Reviews Microbiology},
+ title = {Evolutionary classification of {CRISPR-Cas} systems: a burst of class 2 and derived variants},
+ year = {2020},
+ number = {2},
+ pages = {67--83},
+ volume = {18},
+ doi = {10.1038/s41579-019-0299-x},
+ issn = {1740-1534},
+ refid = {Makarova2020},
+}
+
+
+ at InCollection{MWK22,
+ author = {Makarova, Kira S. and Wolf, Yuri I. and Koonin, Eugene V.},
+ booktitle = {CRISPR: Biology and Applications},
+ publisher = {John Wiley & Sons, Ltd},
+ title = {Evolutionary classification of {CRISPR-Cas} systems},
+ year = {2022},
+ chapter = {2},
+ pages = {13--38},
+ doi = {10.1002/9781683673798.ch2},
+ isbn = {9781683673798},
+}
More information about the CHNOSZ-commits
mailing list