From d8cd0cc8bbf94dc9232a58eb1fb1981fbf287183 Mon Sep 17 00:00:00 2001 From: Iva Veseli Date: Thu, 6 Jun 2024 12:54:59 +0200 Subject: [PATCH] typos metabolism tutorial --- tutorials/fmt-mag-metabolism/index.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tutorials/fmt-mag-metabolism/index.md b/tutorials/fmt-mag-metabolism/index.md index 5112836..f2defc0 100644 --- a/tutorials/fmt-mag-metabolism/index.md +++ b/tutorials/fmt-mag-metabolism/index.md @@ -346,7 +346,7 @@ The `pathwise_copy_number` column reports the copy number of the maximally-compl We also generated the path- and step-specific output files in the previous command, and you can see the per-path and per-step copy numbers in those files. -The copy number results aren't that interesting here because we are only working with a single genome, so we only get copy numbers of 0, 1 or NA. It's not really a metric meant for individual populations (unless you are working with an organism that has lots of genome duplications). However, it is extremely useful for analyzing metagenomes. We won't be doing that just yet, but the section ["Estimating pathway copy number in a metagenome assembly"](#estimating-pathway-copy-number-in-a-metagenome-assembly) below demonstrates this capability. You can also see an example of how we use it in [this reproducible workflow](https://merenlab.org/data/ibd-gut-metabolism) (and [this section](https://merenlab.org/data/ibd-gut-metabolism/#metabolism-analyses-for-metagenomes) of it in particular). +The copy number results aren't that interesting here because we are only working with a single genome, so we mostly get copy numbers of 0, 1 or NA. It's not really a metric meant for individual populations (unless you are working with an organism that has lots of genome duplications). However, it is extremely useful for analyzing metagenomes. We won't be doing that just yet, but the section ["Estimating pathway copy number in a metagenome assembly"](#estimating-pathway-copy-number-in-a-metagenome-assembly) below demonstrates this capability. You can also see an example of how we use it in [this reproducible workflow](https://merenlab.org/data/ibd-gut-metabolism) (and [this section](https://merenlab.org/data/ibd-gut-metabolism/#metabolism-analyses-for-metagenomes) of it in particular). #### Manual inspection of KOfam hits @@ -354,7 +354,7 @@ Remember when we were excited about _A. muciniphila_ because it can degrade muci There are a couple of ways to get around this limitation -- one of those is to define your own metabolic pathways (which we will discuss in the next section), and the second is to look at individual KOfam hits for KOs which do not belong to a particular metabolic module, but may be representative of a metabolism of interest. We'll go through the latter strategy first since 1) it sets up a bit of background on the enzymes required for mucin degradation and 2) it is more limited and more tedious, so the impact of user-defined metabolism will be clear once we get there. -In the case of mucin degradation, the enzymes that break up mucin (by destroying the gylcosidic bonds between the mucin molecules) are called Glycoside hydrolases (GHs). Several GHs work sequentially to degrade the different parts of mucin glycans ([Bell and Juge 2020](https://doi.org/10.1093/glycob/cwaa097), [Tailford 2015](https://www.frontiersin.org/articles/10.3389/fgene.2015.00081/full)). In _A. muciniphila_, several of these enzymes have already been characterized through biochemical methods ([Derrien 2007](https://www.proquest.com/openview/6a566a24e19814c28d9d413e877b2618/1?cbl=2026366&diss=y&pq-origsite=gscholar&parentSessionId=O1DpssTMOgvTUrVO8PcgOwxMr839IcOJSQw%2FeyQlr2o%3D)), but information on the specific genes that are involved is a bit hard to find. In a recent analysis using transposon mutant libraries, it was discovered that genes important for the mucin degradation phenogype include those encoding a sialidase (GH33), a fucosidase (GH95), an outer membrane-associated endo O-glycanase (GH16), a β-galactosidase (GH2), an α-N-acetylglucosaminidase (GH89), an α-amylase (GH13), a galactosidase (GH43) and a β-hexosaminidase (GH20) ([Davey et al. 2023](https://doi.org/10.1038/s41564-023-01407-w)). The classification of each of those enzymes, as defined by [the CAZy database](http://www.cazy.org/Glycoside-Hydrolases.html), is given in parentheses in that list. +In the case of mucin degradation, the enzymes that break up mucin (by destroying the gylcosidic bonds between the mucin molecules) are called Glycoside hydrolases (GHs). Several GHs work sequentially to degrade the different parts of mucin glycans ([Bell and Juge 2020](https://doi.org/10.1093/glycob/cwaa097), [Tailford 2015](https://www.frontiersin.org/articles/10.3389/fgene.2015.00081/full)). In _A. muciniphila_, several of these enzymes have already been characterized through biochemical methods ([Derrien 2007](https://www.proquest.com/openview/6a566a24e19814c28d9d413e877b2618/1?cbl=2026366&diss=y&pq-origsite=gscholar&parentSessionId=O1DpssTMOgvTUrVO8PcgOwxMr839IcOJSQw%2FeyQlr2o%3D)), but information on the specific genes that are involved is a bit hard to find. In a recent analysis using transposon mutant libraries, it was discovered that genes important for the mucin degradation phenotype include those encoding a sialidase (GH33), a fucosidase (GH95), an outer membrane-associated endo O-glycanase (GH16), a β-galactosidase (GH2), an α-N-acetylglucosaminidase (GH89), an α-amylase (GH13), a galactosidase (GH43) and a β-hexosaminidase (GH20) ([Davey et al. 2023](https://doi.org/10.1038/s41564-023-01407-w)). The classification of each of those enzymes, as defined by [the CAZy database](http://www.cazy.org/Glycoside-Hydrolases.html), is given in parentheses in that list. If we look for genes that are annotated with those enzyme names, then we should be able to manually reconstruct the mucin degradation pathway in our _A. muciniphila_ genome. We've been working with KOfam annotations so far, and `anvi-estimate-metabolism` can give us some quick info on the KOfam annotations in our genome, so let's see if we can find some of these enzyme families in the KEGG Orthology database. While we are at it, we can also check for links to these families in other databases. Here is what I got: