Bio 2002: Research Project

"Microbial Diversity" cont.

For those among us who do not possess either the sophisticated laboratory equipment or the time required to sequence bacterial genomes, many student activities are still possible using the vast amount of information that is accumulating in databases around the world. The National Center for Biotechnology Information (NCBI) maintains the Genbank database which is accessible on the world wide web. With a computer and internet access, students can go to the NCBI web site and enter the name of an organism and call up the DNA sequence, the mRNA or the protein sequence for that organism. An example of the kind of question that could be investigated using this information is presented below.

Utilizing bacterial metabolic information from Margulis and Schwartz (1998), we asked whether the metabolic distinctions that exist within distinct groups of bacteria would be reflected in their DNA sequences. We then selected 10 different genera of bacteria that differed in their metabolic requirements. These organisms are listed in Table 1 below. We chose the 16s ribosomal gene to pull out of the database because it has been highly conserved over evolutionary time, though changes have occurred.

Table 1:  Microbial Metabolic Diversity

We searched the NCBI database <www.ncbi.nlm.nih.gov.> by entering the name of the bacteria, selecting "nucleotide" sequence, and then hitting "limit" and then  "molecule" and then "RNA". The sequence must be saved in "FASTA" format  (an abbreviated way to represent a nucleotide sequence). By  hitting "enter" the DNA sequence of the 16S ribosomal gene for that organism was obtained.  After saving each sequence in a word file, we then went to an internet site with the CLUSTAL W alignment program available in an interactive form <www.clustalw.genome.ad.jp>. We downloaded the sequences from the word file into the CLUSTAL W alignment window making sure there were no spaces in any of the sequences. Hitting "align multiple sequences"  matches the sequences between pairs of organisms and determines which are most closely matched. The program also gave us the option of producing an unrooted tree or a dendrogram. The resulting dendogram provides an opportunity for classroom discussion, comparing  the CLUSTAL dendogram to prevailing taxonomic treatments for these bacteria.

You need not restrict your analysis to the above list of bacteria; any organisms could be substituted depending upon the classroom topics you are considering.  This activity is a wonderful opportunity to consider the proposal to use molecular-sequence data to reorganize the living world into three domains and multiple kingdoms made by Woese, Kandler and Wheelis (1990) with the five kingdom system used by Margulis and Schwartz (1997).

Sample Results: See Figure 2

Sample Analysis Questions for Students

1. What gene is being used to make this dendogram?

2. How different are the Archaea bacterial genes from the eubacteria genes in terms of number of nucleotides?

3. How well does the gene- based dendogram match the classification of these bacteria by metabolic and morphological characteristics?

4.How is this method of comparing evolutionary differences between organisms similar and different from other methods?

Research extensions

1.   Compare the protein sequences or mRNA of the same ten bacteria using Genbank and Clustal W to determine whether they provide the same relationships.

2. Select a different gene like cytochrome c or tRNA and perform the same analysis.