Molecular phylogeny, or phylogenetics, is used to study relationships among organisms. The most common approach these days involves examining nucleic acid sequences or protein data from specific genetic loci; frequently the goal is to define data down to the species level. All life forms on earth trace back to a few organisms that lived billions of years ago and all share a common descent. Groups of organisms that are closely related to each other diverged from more recent shared common ancestors. Phylogeny remains one of the only effective means of describing these relationships, which can be difficult to assess by other means.
The goals of phylogenetics are to 1) reconstruct the correct genealogical relationship between organisms/genes/sequence data and 2) to estimate their divergence since sharing a common ancestor. The process of phylogenetic reconstruction relies heavily on correct comparison of the traits under question, whether it is morphological data (such as wing lengths) or sequence data. For sequence data, comparison is made by the alignment of a set of orthologous sequences, which we will do in lab from the 16s rRNA gene.
Today, we have a choice of algorithms (distance-based, neighbor-joining, parsimony, likelihood, and other) for reconstructing a phylogenetic tree that depicts the relationships among aligned sequences. A number of models for defining how the mutations between sequences (genetic substitution) are assessed are also available. Each of these methods and models has advantages and disadvantages, which are closely considered (ideally!) in any formal published phylogenetics study. In the world of microbial community analysis, a popular choice is the neighbor-joining method (Saitou and Nei, 1987), which is one of the methods that deals most accurately and consistently with large data sets. Regardless of the best method, however, the result -- a reconstructed phylogenetic tree -- has proven to be an extremely useful qualitative and often even quantitative tool for examining the relationships among organisms.
Part 1: Bird microbiome analysis
You will take several steps to analyze your bird stool sequencing data, as individuals, pairs, and ultimately the entire class:
- For each ### clone of yours (e.g., #716-1 through #716-8), you will trim and combine the forward and reverse sequencing results to get one intact 16S rRNA gene.
- For each sequence, you will use BLAST to determine the closest known bacterial species to that sequence.
- You will post both the sequences and a summary of the species that you found, according to a specific template.
- You will then pair with your ### clone partner (see the Day 2 Talk page) to align all your sequences, up to 16 of them, in a program called MEGA, and to subsequently construct a phylogenetic tree.
- T/R section will align sequences from the first two of four ### samples, and post the alignment file.
- W/F section will add the sequences from the remaining two ### samples to the same alignment file!
- These trees will be posted so that cross-class comparisons can be made.
- T/R will post provisional trees to show progress.
- W/F will post complete trees that everyone can share.
- Finally, you may compare the MA versus AK trees by inspection, as some of them will be pretty homogeneous, or you may optionally run a UniFrac analysis. (Some guidance about UniFrac will be posted later this week.) You might also want to compare composite trees for MA (up to 16x4 sequences) versus AK (ditto), which we will attempt to facilitate.
Part A: Understand possible insert orientations within vector
- Recall from Day 2 the sequences of the forward and reverse primers used to broadly amplify bacterial 16S rRNA genes:
- Forward: 5' AGAGTTTGATCCTGGCTCAG
- Reverse: 5' ACGGGCGGTGTGTACA
- Based on these sequences, you might expect that your insert will always begin with "AGA" and always end with "CGT." (Draw a picture to make sure you understand why the last three bases are as they are written here.)
- However, in blunt-end cloning, the insert -- here our PCR product -- can face in either orientation. Take a moment to figure out what other basepairs you might expect to see at the beginning or end of your sequenced insert. For now, pretend that you are using forward sequencing primers only, which will read out the coding strand.
- The kind of cloning we are doing is called non-directional cloning. Directional cloning is possible when, for example, two different restriction enzymes are used to create overhangs that are complementary to the vector but not to each other.
Part B: How to download a sequence
- The data from Genewiz is available at the company website, linked here.
- Choose the "Login" link and then use "firstname.lastname@example.org" and "be20109" to log in.
- At the bottom right should be a section called Recent Results. Click on More to expand it, and then click the icon under the Results column for your particular plate.
- T/R orders were placed on 2/27, and W/F orders were placed on 02/28.
- T/R Blue, your last two samples were moved to Plate 3, and T/R Platinum, so were yours. I had to move these because wells 95 and 96 are used by Genewiz for controls.
- The quickest way to start working with a particular sequence is to follow the "View" link under the Seq File heading. For ambiguous data, you may want to look directly at the Trace File as well.
Part C: Prepare sequences for analysis
- Begin by downloading this file, which contains the DNA sequence of the vector we are using in GenBank format. Open the file in ApE (A plasmid Editor, created by M. Wayne Davis at the University of Utah), which is found on your desktop. Three items of interested are highlighted: the forward priming site, the reverse priming site and the two basepairs between which your sequence should be inserted.
- Follow the steps below for each clone that had successful forward and reverse sequencing reactions. In cases where only one reaction was successful, briefly check whether you can locate an insert. However, note that there is a known problem with this cloning procedure wherein sometimes an incomplete vector (with no insert and also missing a chunk of the vector) is returned. You should also scroll down to the bottom to check if any of your failed reactions were repeated; these are noted with an "R" and in some cases worked the second time around.
- Paste the forward sequence of your first candidate into a new ApE file. Locate where the vector ends and the insert begins; trim away the vector.
- While it is easiest to find the insert by doing Edit → Find (or Apple-F) using the base pairs right before the insert should begin, note that the string "CCC" may be mis-sequenced as "CC" or "CCCC" because long stretches of the same base (particularly Gs and Cs) are prone to error.
- Paste the reverse sequence of your first candidate into yet another ApE file. Immediately use Edit → Reverse Complement to adjust the sequence, and again trim away the vector.
- Why is it more convenient to work with the reverse complement when sequencing from the reverse direction?
- In ApE, use Tools → Align Sequence to find where the forward and reverse sequences overlap. Combine them into one sequence with no repeated parts; where both forward and reverse sequence have coverage of the gene, choose whatever combination has the fewest Ns (ideally none!). Save this sequence as a new file called YourTeamDay-YourTeamColor_YourSampleID-"C"Candidate Number (e.g., WF-Purple_737-C1).
- You may find it easiest to print out the alignment in order to choose where to switch from using forward to using reverse sequence.
- In pilot testing, we have run into one case in which the forward and reverse sequences have almost no overlap. It's not clear what caused this error. Before assuming that this error has struck your data, too, be sure that you reverse-complemented your reverse sequence!
- Finally, depending on the orientation of your insert, you may want to reverse complement the entire sequence. Use the original sequences of the forward and reverse 16S primers to guide your decision.
- You must now save each sequence in .txt format. If anyone can figure out how to do this task directly in ApE, let us know! Otherwise, you can copy-paste the sequence into a program such as TextEdit, choose File → Save, and in the pulldown menu select Plain Text.
Part D: Identify species from sequences
- The "nucleotide BLAST" alignment program can be accessed through the NCBI BLAST page or directly from this link. Follow the steps below for each clone, one at a time.
- Paste the sequence text that you prepared above into the "Query" box. If there were ambiguous areas of your sequencing results, these will be listed as "N" rather than "A" "T" "G" or "C" and it's fine to include Ns in the query.
- Under Choose Search Set, select "16S ribosomal RNA sequences (Bacteria and Archaea)" from the Database pulldown menu.
- Click on the BLAST button. Matches will be shown by vertical lines between the aligned sequences, while mismatches and gaps will be shown with a dash.
- Because this gene is highly conserved, a number of species should come up as highly matched. However, one should (usually) be a best choice. Using the linked template, write down this strain and its accession number, its associated max score, query coverage, max identity, gaps, mismatches, and full taxonomy; write down these parameters for the second most closely matched species as well. The taxonomy information can be found by clicking on the accession number and looking under the "organism" heading.
- Taxonomy order is kingdom, phylum, class, order, family, genus, and species.
- When a particular clone is very closely matched to two different species, you might choose to define it at a higher order, such as genus or family. When a particular clone is not well-matched to any known species (perhaps representing an unidentified or undocumented species), you might also choose to define it at a higher order when submitting this information in the phylogenetics program.
- Be sure to rename the candidates according to your section day, team color, and clone number.
- Please post all of your .txt files (up to 8) and also your Excel file to the table on today's Talk page when you have finished.
Part E: Align sequences and construct tree
For this next part you will use freely available software called Molecular Evolutionary Genetics analysis, or MEGA. Feel free to read additional information about this software at the MEGA website. What you need should already be downloaded on your laboratory computers, or you can download onto your personal computers if you wish.
You are welcome to get together with your clone ### partner for this next part, or if you really want to you can work alone from each other's text files and Excel write-ups -- but that's twice the work!
- Open MEGA. In the upper left corner, click on the icon labeled Align, and choose Edit/Build Alignment from the pulldown menu. This selection should open the Alignment Explorer. When you are prompted, choose "DNA" alignment of course.
- Under Edit, choose Insert Sequence from File and select your first .txt file. It should appear in the explorer.
- Double-click to rename according to the species. Note that each sequence must have a unique name. Thus, it is best that you name according to both species and clone: for example, "Klebsiella oxytoca (TR-Blu-4B). This approach will also allow us to track which sequences came from which individual preps, which might be useful information.
- Please use the following 3-letter abbreviations for your colors: Red, Org, Ylw, Grn, Blu, Pnk, Prp, Plt. "B" indicates the right-hand partner in the sequencing plate.
- When you have input all sequences from your section (up to 16), choose Edit → Select All, followed by Alignment → Align by Clustal-W.
- Now choose Data → Save Session and name the alignment according to section and clone (such as "TR-716-alignment"). Post this file on today's Talk page. That way W/F data can readily be combined with T/R data into one-tree, per gull sample, by using Open Saved Alignment Session followed by copy and paste.
- To be clear, T/R will post 16-sequence alignment files, and W/F will post 32-sequence alignment files. Ditto for trees.
- Under Data, choose Phylogenetic Analysis. When prompted, should you answer that the DNA is protein-coding or not protein-coding?
- Now leave Alignment Explorer and go back to the original MEGA window.
- From the Phylogeny icon pulldown menu, select Construct/Test Neighbor-Joining Tree. To proceed, click on Compute.
- Finally, choose Image → Save as PDF File to document your tree. Save according to section and sample number as before.
- Please post the trees on today's Talk page, so we can see that everyone had the chance to do tree analysis on their own.
- T/R section will post trees representing T/R data only.
- W/F section will post trees that include both T/R and W/F sequences.
- In larger groups, for example at Thursday office hours, we can construct trees wherein all data from a given region are combined.
Part F: Compare sets of trees
Guidance to come in a few days...
Part 2: Microsporidia primer analysis
Sample order/gel prep will be written up Mon evening or Tue morning
For next time
Some of you have journal clubs next time. No other required homework is due on Day 8.
- The following bonus assignment may be submitted on Day 8: Prepare a figure and caption for your primer design summary that shows your raw PCR results -- the agarose gel. (Later you might decide to process this data in some way, but not necessarily.) Write an early draft of the accompanying main text paragraph.
- Agarose gels
- 2:1 mixture of high-resolution:standard agarose
- Prepared in TAE buffer
- With SYBR Safe stain (Invitrogen)
- used at manufacturer's recommended concentration, 10000-fold dilution
- Loading dye
- 0.25% xylene cyanol
- 30% glycerol
- Gels made and run in 1X TAE buffer
- 40 mM Tris
- 20 mM Acetic Acid
- 1 mM EDTA, pH 8.3
- 100 bp DNA ladder from New England BioLabs