The Pangea of Commerce Part 2: Is it alive?
I've recently begun putting together the pieces of what will be my thesis project as a graduate student in marine and environmental biology over at USC. In this project I will be testing the idea that the networks formed by ocean shipping traffic will have a measurable impact on the biodiversity in the waters in and around the ports in question. My hypothesis is that the similarity in the composition marine microbial communities, that is the type and relative abundance of species, between two ports will track the rise and fall of shipping traffic between them. My prediction then is that a rise in shipping between two port, say Los Angeles and San Diego, will cause the microbial communities in both ports to look more similar than before.
Seems straightforward enough, at least given modern ship tracking and genomic sequencing, but there are a number of complications which are going to arise in getting meaning out of this data. One such complication is that sequencing the genomes of all the microbes in a sample of water will give you a census of microbial populations, but it will not tell you how active any of the species may be, or even if they're alive at the time of sampling.
Over the years a number of methods have been developed to try and measure the metabolic activity of microorganisms. One method involves feeding sugars, with altered isotopic ratios, to a sample of microbes and measuring how quickly the altered sugars are incorporated into organic material of the microbes. This can involve shifting the amount of carbon-12 to carbon-13, or oxygen-18 to oxygen-16. Once a group of microbes has been feeding on foods with different isotopic ratios a microbiologist can send a sample of their biological material through a mass spectrometer and see how much of the altered carbon, oxygen, etc has been incorporated into the microbes' body masses. This gives a good measure of how quickly the microbes are eating in the first place. This method has been useful in studying microbes which can be readily cultured in the lab, however many of the species I will be looking at in ocean water are not readily cultured. Also, I will probably be studying dozens, if not hundreds, of total samples. This method will probably not scale very well on account of these issues.
Is there a method for measuring the activity levels of a large number of microbial samples, even when a number of the species involved cannot be readily cultured in the lab? It turns out that there is, sort of.
In part 1 I mentioned the use of sequencing ribosomal genes as as method for determining the relative populations of microbes in a sample of water. These genes are coded in DNA, which is the molecule that stores the raw instructional information for cells. In this case the genes which code for an organisms ribosomes are known as ribosomal DNA (rDNA). The way this information is then executed in a cell is through the use of RNA. RNA is used to make copies of particular genes, which are written in DNA as messenger RNA (mRNA) with the assistance of transfer RNA (tRNA) . This mRNA then works with a series of structures in the cell known as ribosomes, which are composed of ribosomal RNA (rRNA), to synthesize the proteins which perform all of the functions of life. This process results in large variations in the amount of rRNA versus the corresponding rDNA.
As protein synthesis is associated with the activity of a cell it was then assumed that measuring the amount of rRNA versus rDNA would give a straightforward picture of how active a population of cells were. If this were the case I could add some very precise activity data on top of microbial census. Unfortunately it turns out that there is no set relationship between the level of rRNA versus rDNA and cell activity. The rRNA to rDNA ratio varies between species, and doesn't even scale linearly with metabolic activity and cell division rates. It also turns out that cells can have a high rRNA to rDNA ratio while they are currently in a state of low metabolic activity as a way for a cell to prepare for times of high metabolism, even if they are currently in a dormant period.
What does this mean? The rRNA to rDNA ratio does increase during times of high growth and metabolism as cells are busy synthesizing proteins. However the rate is non-linear and varies from species to species. In addition to that there is a temporal uncertainty as it cannot be determined from one measurement if the cells are currently active or preparing for being active. Will it then be worth sequencing the rRNA component of all of these cells along with their rDNA component? Yes, if only because I plan to look at samples from the same ports on a repeated basis. My hope is that repeated measurements will help to reduce some of the uncertainty in time, especially in differentiating currently active from potentially active cells. At the very least this data may turn out to be quite useful for some aspect of my project yet unconsidered.
How then to determine the frequency and duration of measuring these populations? I will try and address this matter in part 3.
Seems straightforward enough, at least given modern ship tracking and genomic sequencing, but there are a number of complications which are going to arise in getting meaning out of this data. One such complication is that sequencing the genomes of all the microbes in a sample of water will give you a census of microbial populations, but it will not tell you how active any of the species may be, or even if they're alive at the time of sampling.
Over the years a number of methods have been developed to try and measure the metabolic activity of microorganisms. One method involves feeding sugars, with altered isotopic ratios, to a sample of microbes and measuring how quickly the altered sugars are incorporated into organic material of the microbes. This can involve shifting the amount of carbon-12 to carbon-13, or oxygen-18 to oxygen-16. Once a group of microbes has been feeding on foods with different isotopic ratios a microbiologist can send a sample of their biological material through a mass spectrometer and see how much of the altered carbon, oxygen, etc has been incorporated into the microbes' body masses. This gives a good measure of how quickly the microbes are eating in the first place. This method has been useful in studying microbes which can be readily cultured in the lab, however many of the species I will be looking at in ocean water are not readily cultured. Also, I will probably be studying dozens, if not hundreds, of total samples. This method will probably not scale very well on account of these issues.
Is there a method for measuring the activity levels of a large number of microbial samples, even when a number of the species involved cannot be readily cultured in the lab? It turns out that there is, sort of.
In part 1 I mentioned the use of sequencing ribosomal genes as as method for determining the relative populations of microbes in a sample of water. These genes are coded in DNA, which is the molecule that stores the raw instructional information for cells. In this case the genes which code for an organisms ribosomes are known as ribosomal DNA (rDNA). The way this information is then executed in a cell is through the use of RNA. RNA is used to make copies of particular genes, which are written in DNA as messenger RNA (mRNA) with the assistance of transfer RNA (tRNA) . This mRNA then works with a series of structures in the cell known as ribosomes, which are composed of ribosomal RNA (rRNA), to synthesize the proteins which perform all of the functions of life. This process results in large variations in the amount of rRNA versus the corresponding rDNA.
As protein synthesis is associated with the activity of a cell it was then assumed that measuring the amount of rRNA versus rDNA would give a straightforward picture of how active a population of cells were. If this were the case I could add some very precise activity data on top of microbial census. Unfortunately it turns out that there is no set relationship between the level of rRNA versus rDNA and cell activity. The rRNA to rDNA ratio varies between species, and doesn't even scale linearly with metabolic activity and cell division rates. It also turns out that cells can have a high rRNA to rDNA ratio while they are currently in a state of low metabolic activity as a way for a cell to prepare for times of high metabolism, even if they are currently in a dormant period.
What does this mean? The rRNA to rDNA ratio does increase during times of high growth and metabolism as cells are busy synthesizing proteins. However the rate is non-linear and varies from species to species. In addition to that there is a temporal uncertainty as it cannot be determined from one measurement if the cells are currently active or preparing for being active. Will it then be worth sequencing the rRNA component of all of these cells along with their rDNA component? Yes, if only because I plan to look at samples from the same ports on a repeated basis. My hope is that repeated measurements will help to reduce some of the uncertainty in time, especially in differentiating currently active from potentially active cells. At the very least this data may turn out to be quite useful for some aspect of my project yet unconsidered.
How then to determine the frequency and duration of measuring these populations? I will try and address this matter in part 3.
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| The process of mRNA, tRNA, and rRNA synthesizing proteins. |
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