In my first year in the Eisen lab, I was lucky to be able to participate on the Undergraduate Genome Sequencing Project in which I published the draft genome of Curtobacterium flaccumfaciens, the first of it’s genus. An important aspect of this project was blogging about what we were doing: All the successes, the failures, and everything in between, something that I was terrible at evidenced by my one maybe two blog posts. However, the longer I have been in this lab, I find the significance of social media in science, both to myself and the world, grows.
After almost a year since the paper was published, the Eisen lab received an email inquiring about my blog post on Curtobacterium and the difficulties we had with getting enough active DNA and continuing with sequencing. They wanted to know if we were having trouble with DNA extractions on the bacteria, especially since they were interested in sequencing other species of Curtobacterium and were worried if the genus was finicky. We had later found that the viability of our ligase decreased with each successive freeze-thaw causing the huge issue in DNA library prep and were able to inform them that extracting DNA and sequencing Curtobacterium should be a relatively painless process.
There were two things that stuck me as interesting when David, my supervisor on the project, informed me about the email exchange. First, that it was awesome that a blog post that I, an insignificant undergraduate, wrote was seen by other researchers and contained information (as small as it was) that could help them in their research. Second, and more abstract, that science has increasingly become more of a collaborative effort. When I originally thought about sharing in science, the infamous Koch-Pasteur rivalry quickly came to mind. Information simply wasn’t shared as readily at that time. I like to think idealistically that the idea of hoarding information to get ahead of contemporaries has become less common and science will become even more collaborative than it is now. Or the idea of charging to view more than just the Abstract will cease to exist and the number of open-access articles will continue to grow because at the root of researchers (at least originally) is the pursuit of knowledge and dissemination of information. Just some musings I had and who am I to talk? I haven’t even graduated undergrad yet and haven’t joined the race to find the richly rewarding cure to cancer.
First off I hope everyone had a great Thanksgiving break!
If you read Andrew’s previous posts regarding the project, you would know that we have decided to scrap all of the samples we have extracted DNA from and start from the beginning. This is so we will have water chemistry data collected at the same time as DNA is collected thus providing the most consistent and accurate data.
On Tuesday, we received a portion of our water chemistry kit, which tests Hardness, Sulfites, Alkalinity, Iron, pH, and Chloride. We decided to do a practice run on a couple of the tanks so we can familiarize ourselves with the reagents as well as fine tune our sampling procedure. The results are listed below:
Freshwater Tank A
Hardness Test: 93 ppm CaCO3
Sulfite Test: 2 ppm Na2SO3
Alkalinity Test: 90 ppm CaCO3
Iron Test: No detectable amount
Chloride Test: 20 ppm Cl-
Iron Test: No detectable amount
We learned a couple of important points through this test run that will speed up our water chemistry sampling process in the future. For every single test we did, we started using the high concentration detection procedure, but found all of the concentrations in the tanks were extremely low, and had to redo it using the low concentration detection procedure. For our real samples that we will hopefully will be taking in the next week, we can save reagents and time and just jump right to the low detection procedures. We also noticed that the Hardness and Alkalinity tests detected the same molecule (CaCO3) and also had similar concentrations and have thus decided to use only one of the tests. (I will get back to you with the chemistry behind this reasoning, which I didn’t really understand). For both the Freshwater and Saltwater Test, we were not able to get a detectable amount of Iron and will likely scrap that water chemistry test. Lastly our pH meter results were a little different from Russell’s highly sensitive pH meter (pH=8.3) that takes continuous measurements and Tweets them. (Eisen is probably going to like the idea of that!) We will either scrap our pH meter and just use his or will have to verify if our pH meter is giving is accurate readings, by putting it in solutions of known low acidity. This is just an idea of mine, not sure if it’s a good way to check for its accuracy.
That’s where we are in the project as of Tuesday. I will get back to you about the differences between Hardness and Alkalinity and also update when we start taking samples again!
So the project is finally in full swing! After a couple of weeks of practice sampling and getting used to different protocols for extracting, purifying and amplifying the DNA, we have now moved on to working with our real samples. We have extracted DNA from 18 samples (includes replicates of 3) from the tropical tank and the cold water tank. Funnily, the hardest part of the project so far has been running gels. We initially hit a couple of problems such as thickness of the gel, a loose wire in a gel box and differences in loading buffers and dyes. However, now that Akshay is going to be coming in, hopefully he can give us a couple of hints from his experience from IGEM, cause god knows how many gels he had to make this summer 😛
Hi, this is a really long overdo post, but I figured it was about time to start blogging. My name is Jennifer and I am a third year Cell Biology and double in Communications. I am slightly new to the lab, jumping onto the Undergraduate Genome Project in late May. When I jumped on, I was posed with the task of rescuing the lost Curtobacterium from a myriad of petri dishes. After being sure we made a glycerol stock and running the 16S sequence through BLAST we identified the microbe to be Curtobacterium flaccumfaciens (which I will henceforth refer to as AKU), a gram positive soil bacteria and known plant pathogen. AKU could easily be identified as a phylogenetically informative microbe, because after checking RAST, we saw that neither Curtobacterium flaccumfaciens nor any other Curtobacterium species had been sequenced. However, everything afterwards proved to be far more difficult. After many failed library preps, particularly in the qPCR step (we weren’t getting enough active DNA) we decided that we would combine a TruSeq library and a Nextera library, hoping that the biases would be checked by each other. The bias mostly arose from the fact that we had to PCR 18 times for the Nextera library to get enough DNA which would definitely bias the reads for a microbe with as high of a GC content as AKU. We were eventually able to sequence both AKU and THP (Dietzia) with the new 250bp read MiSeq. However, we found that there was a large amount of E. Coli contamination an unfortunate side product of Nextera libraries. We were eventually able to throw out most of the E. Coli reads by lowering the stringency A5 uses to determine what is “trash” DNA. We also found that A5 can only accommodate 160bp reads so for now we are using a trimmer that cuts off 90bp so that we are at least able to run the assembly and not have it crash. We are hoping that we can somehow include those 90bp that we chopped off and even better be able to run A5 with 250bp reads. I will update you on more failures and triumphs in the near future!