--A recent study uses a new approach to investigate the shiga toxin producing bacteria responsible for a serious disease outbreak in Germany in 2011. The real culprits behind the outbreak are the viruses that carry the gene for shiga toxin and transfer it to otherwise harmless bacteria --
What’s harder than finding a needle in a haystack? Finding the bacterial genome you’re looking for in a diarrhea sample. A recent study published on April 10, 2013 in the Journal of the American Medical Associaton (JAMA) made this task seem relatively easy. The bacteria being searched for was a rare shiga toxin producing bacteria that causes bloody diarrhea and other severe complications in humans upon infection. This study was done by an international team of researchers coordinated by Mark J. Pallen who recently became the head of Warwick Medical School’s new Division of Microbiology and Infection. The bacterial strain that caused an outbreak in Germany was especially rare making it hard to identify. Because of this, researchers employed a new method to identify the genome sequence of this highly pathogenic bacteria. Their method of detection was to sequence all the genetic material present in fecal samples from patients with diarrhea during the outbreak and sort through this genetic information to find the sequence of the disease causing strain.
The source of the outbreak in Germany during the summer of 2011 is believed to be from the consumpton of raw sprouts contaminated with the dangerous bacteria strain (2). This outbreak affected thousands of people in a wealthy, modern, industrialized society, causing more than 50 deaths (4). In times like this, quick identification of the causative pathogen (in this case a shiga toxin producing bacterial strain) is critical for the management of the outbreak. Traditionally, the standard for identifying pathogens in clinical samples is to isolate the disease causing bacteria from other microbiota in the samples and then sequence it once it is in pure culture. This study's approach is different becuase they directly sequenced the mixed communities of bacteria and anything else present within the feces sample and then analyzed the sequence data to find the disease causing bacteria. The sequencing of mixed microbial communities is called metagenomics and allows identification independent of laboratory isolation and culture of the causative bacteria.
To extract DNA, 45 fecal samples were taken from patients with diarrhea during the 2011 outbreak. After getting the sequence of the genomes in the fecal samples, bioinformatics was used in order to sort through and piece together the genome of the pathogenic strain of bacteria. The goal was to find what strain of bacteria all the infected people had in common. This involved a series of steps starting with screening out stretches of genomes that are known to be human DNA sequences. Next, the microbial genes were assembled into a collection of “environmental gene tags” (EGTs). EGT’s are short sequences of DNA that can be used to identify or characterize the organisms from which they come from. They also compared samples from healthy individuals to rule out bacteria present in those samples. Once the EGTs in common with the healthy individuals were discarded, just 450 outbreak-specific EGT’s were left in common between affected patients. Of these EGT’s, 65% were assigned to the Enterobacteriales, the order that contains E. coli. These EGT’s were used to reconstruct genome of the outbreak strain. Not all E. coli are pathogenic so it was important to identity what accessory genes were present in the E. coli strain that caused it to be harmful. One such accessory gene that was important in this outbreak is the shiga-toxin gene. The shiga toxin produced by the bacteria is responsible for the severe diarrhea and kidney damage in patients infected with this strain.
Figure 1. Bacteriophage infecting their host E. coli
The focus here is on the bacteria, but in order to understand the pathogenicity of this strain I’d like to bring attention back to the viruses that serve as their accomplices. Many of the E. coli that reside in our gut are not harmful. In order to become disease causing, the E. coli must acquire a combination of genetic elements . One of the most important changes that needs to happen is the ability to produce the shiga toxin. The gene coding for the shiga toxin does not come from the bacteria itself – it is a gene encoded by viruses that infect the bacteria (bacteriophages). So in order for the bacteria to be disease causing it needs to be infected by a bacteriophage (phage) that carries the shiga toxin gene.
Interestingly, this study found an unexpected copy number of shiga-toxin genes compared to other chromosome loci of the shiga-toxigenic Escherichia coli (STEC) outbreak strain. Overall there more shiga toxin encoding regions in the samples positive for STEC than expected. However this varied from sample to sample that were positive for the outbreak strain. Some patient samples had more and some had less of the phage genome relative to bacterial genome pieces. The researchers were not sure why this was the case. They speculate that this could have to do with detection of phage particles that are released from the bacteria upon the lytic phase of their life cycle. This also could be due to multiple phage insertions or duplications within individual E. coli genomes. Further studies are needed in order to clarify what is going on with the transfer of phage genomes in these bacteria and thier impact on disease. Further studies would be beneficial because it relates to treatment of this disease. Studies have found that antibiotics may actually be helping the shiga toxin viral genes to spread. When bacteria are exposed to certain types of antibiotics they undergo a stress response, which induces phage replication within the bacteria. Upon active replication, the bacteria cell bursts open and releases the newly synthesized viral particles. This also releases the toxin, which is why antibiotics are not used to treat these infections (4).
This metagenomics approach is an interesting one and in some ways superior to previous techniques used to identigy pathogens. The general method used for identifiying an outbreak strain involves isolating the bacteria in pure culture and then sequencing it. Metagenomics skips the step of in vitro culture by directly sequencing the mixed communities present within the feces sample. Previous in vitro methods of isolating the strain in pure culture can be slow difficult or even impossible to indentify certain strains. This becomes especially difficult when the outbreak strain is very rare like the outbreak stain in Germany in this study (5). This metagenomic approach is important because there actually is no single in vitro microbioloical test accepted as an official standard to detect STEC.
However this metagenomics approach is not bullet proof and continuous research is needed to improve it. The researchers of this study admit that this approach does not guarantee to find the single causative pathogen of the disease. Multiple pathogens were found in some of the samples and it was impossible to conclude with 100% certainty which of those is the cause of the disease. Another thing to keep in mind is that genome sequence without any information of function or about what species it is coming from is of little use. That is why more in vitro experiments are still needed so that we can continuously gain more functional information about the genes like those causing E. coli to be pathogenic. This metagenomic approach is also currently expensive and requires a lot of data anaylsis and processing. However researchers are optimistic because with the improvement of sequencing technology and the increase of annotated genetic information in databases these setbacks can be overcome.
Overall, using metagenomics, the direct sequencing of mixed microbial communities, is a very promising approach for identifying pathogens. The genomic sequence of the pathogen that causes an outbreak is very important for managing the outbreak. The fecal samples from patients have a mix of genomic data within them, human, viral, and bacterial. Sorting though all the mixed genomic data within a clinical sample is not easy, but this study shows it can be done successfully to isolate sequence of even a rare pathogen. What do you get when you mix metagenomics and poop samples? Lots of information! So we should all start ‘giving a poo’, for the sake of science.
After thought: Other applications of Metagenomics
The applications of metagenomics do not stop here at identifying outbreak strains of bacteria. While much clinical emphasis has been put on the microbes (bacteria, viruses, fungi, and protozoa) that cause disease, there are many microbes that contribute to our health like the bacteria in our gut that help us with digestion. Metagenomics is a powerful method to assess the microbiota which we are finding to be more and more important for our health. We already know that our microbial flora (those that call our body their home) out number our own cells 10-fold with a total gene content of 100-fold greater than our own genome. To find out more about why it has become fashionable to sequence poop, read the paper written by Harvard Professor Christopher Marx about the application of metagenomics for evolutionary studies (6).
1. Loman, N., Constantinidou, C., Christner, M., Rohde H., Chan, J., Quick, J., Weir, J., Qince, C., Smith, G., Betley, J., Aepfelbacher, M., Pallen, M. (2013) A Culture-Independent Sequence-Based Metagenomics Approach to the Investigation of an Outbreak of Shiga-Toxigenic Escherichia coli O104:H4. JAMA , 309(14): 1502-1510.
3.Viruses can turn harmless E. coli dangerous (2009) Science Daily: http://www.sciencedaily.com/releases/2009/04/090417195827.htm
4. Turner, M (2011) Antibiotic use may have driven the development of Europe's deadly E. coli. :
5. Bloch, S., Felczykowska, A., Nejman-Falenczyk, B. (2012) Escherichia coli O104:H4 outbreak – have we learnt a lesson from it?
6. Marx, Christopher (2013) “Can You Sequence Ecology? Metagenomics of Adaptive Diversification” http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001487