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JustinA posted in Plaques appear on spot test, don't appear in titer
Viknesh Sivanathan posted in Plaques appear on spot test, don't appear in titer
JustinA posted in Plaques appear on spot test, don't appear in titer
Viknesh Sivanathan posted in Plaques appear on spot test, don't appear in titer
RyanWheeler posted in Plaques appear on spot test, don't appear in titer
All posts created by cdshaffer
Link to this post | posted 17 Mar, 2021 22:38 | |
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What an interesting and cool question! Here is an update with some more evidence: I checked 5 BK1 by hand and all have that CCCAAAT sequence. I then realized we should just look at all the sequences in the pham. So I looked at the multiple sequence alignment for the pham 5495 which include the G gene for BE and BK phages. The CCCAAAT is found in all the BK1 G genes (they all have gene numbers in the 30's) but that sequence is not found in any of the BE (genes in the 50's-60's) so if this is the slippery sequence you have to argue that it changed to CCCGGAA and yet it is still slippery -or- that the location of the slip has moved since the BE and BK genes diverged. This is fruitful ground for reasonable well trained annotators to disagree, since it is all based on individual estimations of the likelihoods of certain events occurring over evolution. Do we have any evidence of the frequency of slippery sequence turn over rates in the mycobacteriophage? That is a much more comprehensive set might be informative. Alternatively if you back up a few bases there is a sequence which is conserved for 7 of 8 residues across all phage sequences and the one degenerate position is always a pyrimidine I.e. AA(C/T)GACCC. This may not fit any pattern seen among the bench validated slippery sequences but the sample size there is low enough I am not sure how much confidence we should put in those observed patterns.
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Link to this post | posted 17 Mar, 2021 21:41 | |
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I would guess there is a slippery sequence here but there is no way to find it as it has yet to be discovered in the lab. As an annotator I would never intentionally "make up" a slippery sequence. So even though there is likely a slippery sequence somewhere in that genome I have no way to find it. This means I know I cannot get the "right" answer. Then, if I cannot get the "right" answer, the best I can do is try to find the "least worst" answer. For me, the "least worst" is to annotate as much of the T region as I can as a gene. I know this is very likely wrong but it is "less wrong" than the alternatives of either picking a slipper sequence with no support or having no gene annotated for that region at all. And yes for many of the BK1's the "longest" form is really really short, so we just annotate that tiny gene and give it the tail assembly chaperone and hope that anyone that runs across the annotation will know enough (or go to the literature to find out) what is really going on here. But there is really no way to annotate these regions that works well for a naive reader. But I agree with Deb, if we can come up with a hypothesis that makes sense based on the published properties of slippery sequences then that is better than the current solution. I will look for the XXXYYYZ in our BK1's. P.S. for those unfamiliar with the G/T nomenclature see this page: https://seaphagesbioinformatics.helpdocsonline.com/article-6 |
Link to this post | posted 12 Mar, 2021 18:47 | |
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Your question about false positives is an interesting one. I had always assumed the algorithms were specifically designed to distinguish the differences between membrane domains and simple hydrophobic helices. So I went back to the 2001 paper for TMHMM (doi:10.1006/jmbi.2000.4315). The intro in the paper has a really good discussion on the early methods used to distinguish just that issue. There is also a whole section of the paper on this issue. Bottom line is there are other structures and length requirements that help in the determination which helps distinguish a "real" transmembrane domain. Might even be worth pointing out this paper to students who are interested, if only to read the intro. As for the issue of false positives with TM-HMM, according to the paper, the algorithm has a specificity of around 99% if there is not a leader peptide, so I think the protocol as defined is a pretty good one and further support from BLAST is not required. But this issue that a leader peptide reduces the quality of the results is very interesting. Maybe the SEA-phages protocol should be amended if a leader peptide is predicted. That is really a good question for a faculty workshop I think. |
Link to this post | posted 11 Mar, 2021 17:39 | |
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Yes I agree, I was not trying to imply otherwise. My thought experiment was more with the idea of a outside reviewer. There are many papers out there that talk about how poor the annotations are in genbank as a whole, so I could imagine a naive reviewer liking the "published set" over and above the "all genbank set". This brings up the point that one might pick all SEA-PHAGES as a test set over all phages in genbank or all published phage if annotation consistency was important to the analysis. Again, the experimenter should pick the best possible dataset for the question. |
Link to this post | posted 10 Mar, 2021 18:03 | |
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to me this is mostly an issue of good experimental design and picking the right dataset for your experiments. So consider these two possible sentences you could write in a hypothetical paper and decide which one would be better at convincing the reviewer to accept your paper and its conclusions: 1. "To cast a wide net and compare as many as possible we collected and analyzed all phage in genbank" 2. "To ensure the highest quality of data and gene annotations we selected only phage genomes which have been published in peer-reviewed journals" if I were a reviewer I would be fine with option 1 if the study was mostly about sequence variation with little or no input from annotations. The more your experimental conclusions rely on annotations the more I would favor option 2. As a middle ground, you could also consider all the phage in the refseq database instead of all of genbank. |
Link to this post | posted 06 Mar, 2021 21:29 | |
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I would always prefer the HHPRED matches (if I find them) over the blast results. This is due, in no small part, on the quality of the different databases being searched and the relative sensitivity of the algorithms. The source for many of these "discrepancies" like your list is that the alignments are only matching to part of your protein or to just part of the subject. Since some proteins have multiple functional parts all connected together in a single polypeptide chain this can lead to what I would call a "partial annotation". Also note that your first two possibilities do not really "disagree" they really are just different levels of specificity. When trying to decide on levels of specificity, I first direct my students to try to understand the differences in what the terms mean, good sources include the sea-phages approved terms list, the EXPASY enzyme class list, Wikipedia, intro bio text books etc. are all good sources. Once you have a better understanding of the terms you can then look for evidence to help you decide if a higher level of specificity is justified or not. As for this particular protein, if I scan through the top 15-20 hits from prokaryotes (i.e. I am going to ignore the two human mitochondrial proteins) I see many hits to proteins that are described to have BOTH a helicase activity AND a nuclease activity. This explains the "discrepant" results, so the question becomes: does this protein from crewmate also have those two domains or just one. This is why you see annotators often talk about the size of the protein and the size of the match. I quickly focus on the length of the alignment and which part of the subject is matching. Most of these alignments cover about 75% of crewmate 28 but you can see that they only match a much shorter part of the subjects that are described to have both a nuclease and a helicase activity (like residues 1005-1232, 790-1014 or 129-368 ). So likely crewmate is similar to either the nuclease or the helicase part of these larger proteins, but I cannot tell which based simply on the summary data presented in the table. Looking at the other matches I can see hits to pfam domains and "cd conserved domains" that are all different types of exonucleases. So what we have here is likely an exonuclease that is often found as part of a large helix/nuclease combo protein. So I am pretty convinced that either of the first two options on your list could be appropriate here. When talking about this with my students I would point out that since they are the first author it is really up to them to read up on the two terms and decide if they think the "cas4" is better than the generic "exo" but I would be willing to put my name as an author on either of those annotations since one is just a more specific subtype of the other. |
Link to this post | posted 27 Feb, 2021 19:03 | |
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in the database there are 11 phage genes with subcluster B1 they all appear in current pham 48591: for the totally geeky here is the mysql query I used:
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Link to this post | posted 19 Feb, 2021 18:12 | |
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The current versions of both chrome and firefox have stopped support for FTP. I started up an old version of the SEA-VM and used the really old version of firefox therein to confirm that the FTP server is up and running. So to access it directly you will need to use an FTP client to connect. In the past, on Windows machines, I have used Filezilla and cyberduck to access FTP sites. If you have a mac, you can also just connect using the finder -> go menu -> connect to server -> enter address of ftp://cobamide2.bio.pitt.edu/ -> click connect -> select connect as guest => click connect. This will open a finder window which is connected to the ftp server. Be patient with file loading it can be slow; the file you want (dna master.exe) is in the DNAMas folder. You can use typical drag and drop to copy the file. Final step, of course, is to transfer the file to your windows machine by whatever method you find most convenient. |
Link to this post | posted 17 Feb, 2021 16:53 | |
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The issues you are having are related to the restructuring of the database that was undertaken last fall. You will need to upgrade to a compatible version of PhamNexus. I can see that Christian in the Hatfull lab is still keeping it up to date as he posted code changes last October to make it compatible with the new database format. He will need to tell you how to update to that working version. |
Link to this post | posted 09 Feb, 2021 19:33 | |
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This was due to a database versioning issue (i.e. starterator was still on version 391 and phagesdb had upated to version 392). The report is now available here. If you want all the details on the how and why this happens, and how to check versions see this thread: this thread If you want to see which version Phamerator.org, pecaan and starterator are on use these instructions: phagesdb see: http://databases.hatfull.org/Actino_Draft/Actino_Draft.version starterator see: http://phages.wustl.edu/starterator/database.version pecaan: look on any "pham maps" page just above the map phamerator.org: open the pull down menu in the top left |