Metagenomic DNA Datasets

Who Lives in That Place?

Ecologists ask questions about individual organisms as well as populations, how they interact with their environment and with other organisms of their same and/or other species. Central to answering many ecological questions is the ability to count or estimate the number of individuals of a given species. If we are talking elephants or mature white oak trees, then it may not be that hard a task. If we have to determine the number of blue jays or spring peeper frogs, it won’t be as easy and our best bet is an estimate based on sampling. Yet, what if we are interested in microbes, both prokaryotic and eukaryotic? For some, such as diatoms or ciliate protozoans, we could look at samples under the microscope although this will take some background knowledge of how to distinguish various taxa based on morphology. For bacteria, the choice for decades has been plating samples out on various culture media and counting colonies based on the assumption that each colony came from a single cell that was laid down at that spot. Colonies can then be identified using a variety of biochemical assays, stains, and growth-based tests.

Evidence has accumulated during the last two decades that cultured-based identification methods are not good estimators of microbial diversity because they catch only a small percentage (0.5-5%) of the microbial diversity present in any habitat at any time. Even after a century plus of efforts, we only can get a minority of bacteria to grow in culture. Given this problem, how can one detect the presence of a microorganism without growing it? Modern genetics gives us a new option – look at the DNA of all the organisms present in a microbial community.

To sample microbes in an unbiased manner, we typically use PCR (Polymerase Chain Reaction) and primers targeted to a gene found in all organisms – the 16S/18S rRNA gene. This gene is highly conserved, but it has slowly changed over evolutionary time and those changes are the basis of the currently accepted tree of life. They are also used to identify organisms. Certain parts of the 16S rRNA gene mutate faster than others and that dictates what regions are used for PCR amplification. With PCR, you don’t have to grow the organisms and you don’t have to have the entire genome intact. As long as you can amplify a small region of the 16S rRNA gene and determine its sequence, you have a chance to identify the organism. Easy enough if you start with a pure culture, but we are talking about sampling the unknown. If you apply the 16S rRNA gene PCR approach to an unknown assemblage of uncultured microbes, this is called metagenomics. Because you are isolating DNA from a mixed population, your PCR amplification product will be a mixture. The only way to get knowledge of specific sequences is to separate them from each other, usually by recombinant DNA cloning. More recently, scientists have begun to gather additional metagenomics data sets either by using PCR primers for other well-conserved genes or by sequencing random fragments in a large-scale fashion.

While you and your students can isolate metagenomic DNA from your own environmental samples and look for specific groups of organisms by PCR using our Metagenomics PCR Kits, Hiram Genomics Store also offers several large datasets of previously sequenced 16S rRNA gene sequences from different experiments. What follows is a brief description of two such experiments.

Example 1: The Microbial Community of the Human Armpit & the Impact of Deodorant

Our skin is a complex and variable habitat for microbes. While skin is composed of many layers, microbes only inhabit the outer surface on healthy individuals. The skin has factors such as variable temperature, moisture, and lipid content, high salt concentration, keratin (waterproofs the skin), low pH, and antimicrobial peptides that help protect against invasion. Some bacteria, such as Staphylococcus and Streptococcus, have evolved to survive in such an environment and may cause disease if a portal of entry presents itself. The subject of our investigation, the human armpit or axilla, is on the higher end of the warmth and moisture spectrum compared to the rest of the skin, analogous to tropical rainforests as compared to other biomes on Earth.

Our study volunteer was a 50-year-old male in good health who had not taken antibiotics for several months. The axilla were washed with water only for 10 days (no soap) prior to sampling. No deodorant was applied to the left axilla during that time, while deodorant was applied to the right axilla. The deodorant used contained propylene glycol as the potential active ingredient. At the end of 10 days, each axilla was rubbed with sterile swabs wetted with sterile 0.9% NaCl. The swabs were vortexed in 1 ml 0.9% NaCl to knock off bacteria, the cells pelleted, and total metagenomic DNA isolated. 16S rRNA gene sequences were amplified from each metagenomic DNA sample and subjected to next generation DNA sequencing. Your students can now analyze the sequence data to determine who lives on the surface of the human armpit and the impact of one type of deodorant on that microbial community.

Example 2: How Nutrients & Salinity Impact Marine Microbial Communities

The experiment started in the summer of 2009 with beach sand and seawater from the central Gulf coast of Florida (Anna Maria Island). A mixture of 100 ml of beach sand and 100 ml of sterile sand were added to each of 3 reused plastic bottles (washed and sterilized with ethanol) along with 4 g Na2CO3 (source of CO2 for autotrophs), 4 g MgSO4 (source of sulfate for sulfur redox cycle), and 2 g cellulose (complex carbohydrate for heterotrophs). One bottle was left as is (Bottle E). The other two bottles (A and B) also received some mineral salts solution (source of N, P, K) to mimic nutrient runoff from agriculture or human waste. To see the potential impact of evaporation in an isolated tidal pool on the seashore, 29.22 g NaCl was added to Bottle B only to mimic the increase in salinity upon evaporation. Finally, a mixture of 2/3 seawater and 1/3 sterile water was used to fill up each of the bottles to about 1 inch from the top. Light was provided by continual exposure to cool white fluorescent lights (8000 lux). The pictures below were taken at 4 time points after set up. At the last time point, each bottle was briefly mixed to dislodge bacteria from sediment particles and from the sides of the bottle, the sediment was allowed to settle briefly, and the liquid transferred into centrifuge tubes. The bacteria were then pelleted and total metagenomic DNA was isolated. 16S rRNA gene sequences were amplified from each metagenomic DNA sample and subjected to next generation DNA sequencing. Now your students can analyze the sequence data and determine which groups of bacteria are thriving under each condition and then use the scientific literature to develop hypotheses that might explain the data.