It's been interesting to watch as microbiology's own cold fusion debate has been raging. It began with an extraordinary claim about bacteria using arsenate as a replacement when phosphate concentrations are low (1).
It progressed when at least two scientist / bloggers ( here, and here) (not bloggers! the horrror! how uncivil!) gave public "journal club" presentations on ... Read more
The other day, one of my commentors wrote that "a well-informed sixth-grader should be able to distinguish MRSA from E. coli".
Well, here's a nutrient agar plate with some of the bacteria that we isolated from a local creek last fall. We identified our bacteria by sequencing the 16S ribosomal DNA, but for various reasons, that I won't go into here, we don't know which sequences belong to which colonies.
In the class that I'm teaching, we found that several PCR products, amplified from the 16S ribosomal RNA genes from bacterial isolates, contain a mixed base in one or more positions.
We picked samples where the mixed bases were located in high quality regions of the sequence (Q >40), and determined that the mixed bases mostly likely come from different ribosomal RNA genes. Many species of bacteria have multiple copies of 16S ribosomal RNA genes and the copies can differ from each other within a single genome and between genomes.
Now, in one of our last projects we are determining where ... Read more
Do different kinds of biomes (forest vs. creek) support different kinds of bacteria?
Or do we find the same amounts of each genus wherever we look?
Those are the questions that we'll answer in this last video. We're going to use pivot tables and count all the genera that live in each biome. Then, we'll make pie graphs so that we can have a visual picture of which bacteria live in each environment.
The parts of this series are:
I. Downloading the data from iFinch and preparing it ... Read more
This is third video in our series on analyzing the DNA sequences that came from bacteria on the JHU campus.
In this video, we use a pivot table to count all the different types of bacteria that students found in 2004 and we make a pie graph to visualize the different numbers of each genus.
The parts of this series are:
I. Downloading the data from iFinch and preparing it for analysis. (this is the video below) (We split the data from one column into three).
II. ... Read more
What do you do after you've used DNA sequencing to identify the bacteria, viruses, or other organisms in the environment?
What's the next step?
This four part video series covers those next steps. In this part, we learn that a surprisingly large portion of bioinformatics, or any type of informatics is concerned with fixing data entry errors and spelling mistakes.
The parts of this series are:
I. Downloading the data from iFinch and preparing it for analysis. (this is the ... Read more
For the past few years, I've been collaborating with a friend, Dr. Rebecca Pearlman, who teaches introductory biology at the Johns Hopkins University. Her students isolate bacteria from different environments on campus, use PCR to amplify the 16S ribosomal RNA genes, send the samples to the JHU core lab for sequencing, and use blastn to identify what they found.
Every year, I collect the data from her students' experiments. Then, in the bioinformatics classes I teach, we work with the chromatograms and other data to see what we can find.
This is the first part of a four part video series ... Read more
or E. coli, or perhaps a little Giardia (just to loosen things up, of course), or maybe even Herpes.
All these scary pathogens become works of art, when Infectious Awareables puts the images on neckties.
And what could be funnier ... Read more
We have lots of DNA samples from bacteria that were isolated from dirt. Now it's time to our own metagenomics project and figure out what they are. Our class project is on a much smaller scale than the honeybee metagenomics project that I wrote about yesterday, but we're using many of the same principles.
The general process is this:
1. We sort the chromatogram data to identify good data and separate it from bad data. Informatics can help you determine if data is
For the record: Chlamydia is NOT a virus.
I am bummed. I like the little MicrobeWorld radio broadcasts, and the video podcasts are even more fun.
But I was perusing the archives and I found this:
I could ignore this if it came from a different source, but MicrobeWorld is produced with ... Read more
