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Article by Christoph Bahn
This article originally appeared on Mayo Clinic Laboratories Insights.
Shotgun metagenomic sequencing (aka “shotgun metagenomics”) is a revolutionary new way to detect infectious organisms. Currently, this technology is undergoing validation for clinical testing in Mayo Clinic’s Clinical Microbiology Laboratory. By sequencing all of the DNA (or RNA in some instances) in a patient’s sample, the new tool can identify which potentially infectious organism (or organisms) is present. Traditional microbiology has not always been able to do this because certain microorganisms cannot be grown in culture; or, if a microorganism is present in a patient but has been suppressed to low levels by treatment, it may not be amenable to growth in culture.
Identifying pathogens in prosthetic joint infections
Based on a recent study at Mayo, the tool has already shown great promise in identifying the causes of prosthetic joint infections (PJIs), which have been challenging to identify—hence, in some cases, physicians and surgeons have had to treat infections with antibiotics that cover a wide range of suspected pathogens, which may or may not include those affecting their patients. This approach leads to over-treatment of some patients and under-treatment of others.
For the study, fluid sampling biofilms on the surfaces of joint replacements were taken from the joint sites of 408 patients who had undergone total hip or knee joint replacements. Each sample then underwent shotgun metagenomic testing.
“With this approach, we sequence everything that’s in each clinical sample,” says Robin Patel, M.D., Chair of the Division of Clinical Microbiology and Director of the Infectious Diseases Research Laboratory, where this study was done. “Then we use bioinformatics tools to remove or erase the sequences that belong to humans, which make up most of our samples. After that, we look at what is left over. If the patient happens to have an infection, we should be able to see the DNA of whatever microorganism is causing their infection, whether it’s a bacterium, a fungus, a parasite, or even a virus. We are not looking for specific microorganisms or microorganism types; instead, we are looking for any microorganism.”
According to study results, the tool identified known infectious agents in almost all of the PJI cases that were “culture-positive.” More importantly, it detected new infectious agents in 44 percent of PJIs from which no organisms had been grown in culture and, thus, had previously tested “culture-negative.”
This technology’s high level of sensitivity is good news, given that PJIs are associated with significant morbidity and cost.
An invaluable technology for orthopedic surgeons
“Many patients with PJI are diagnosed with only one microorganism, so we may be missing a lot of microorganisms,” says Matthew Abdel, M.D., surgeon in Mayo’s Department of Orthopedic Surgery and Director of the Orthopedic Genetic Host Variation Laboratory. “There could be one, two, three, four, or even more, microorganisms present. Metagenomics allows us to pick up additional microorganisms in patient cases where more than one is present. And that’s important because not identifying or treating all the microorganisms present may be the reason some hip and knee replacements fail.”
From an orthopedic surgeon’s clinical perspective, another advantage of shotgun metagenomics is its sensitivity to pick up microorganisms that, otherwise, do not show up in culture, and thus test culture-negative. In fact, five to 20 percent of cases that meet clinical criteria for PJI are culture-negative.
“We’ll see a patient who we know is infected—that is their clinical presentation, and laboratory tests indicate an infection—but cultures don’t grow anything,” says Dr. Abdel, who co-authored the study paper. “The metagenomic technique is able to identify microorganisms in this ‘culture-negative’ group. So the technique is a big win for this subset of patients, who have been the most difficult to treat.”
In another anomalous subgroup of cases, the patient has a knee or hip replacement in which clinicians suspect no infection, which is confirmed by conventional laboratory tests. However, the joint replacement ends up failing.
“You do the surgery to remove the failed joint replacement and, through metagenomics testing, find out it was indeed infected, and failed because of infectious reasons that we had missed altogether,” says Dr. Abdel. “So this technology can also identify an infection in cases where we thought—at least in the past—there wasn’t one, allowing us to treat it and reduce the chance of joint failure.”
Discovering pathogens previously unknown in PJI cases
As part of the Mayo study, a 52-year-old man came to Dr. Abdel following a total right knee replacement at an outside institution. After the knee replacement, the patient had developed a PJI. Fluid samples from the knee were culture-negative; eventually, the joint replacement failed and required removal.
At Mayo, the joint replacement was removed and, since the patient’s samples still tested culture-negative, he underwent six weeks of injected antibiotics to treat usual pathogens. He then received a new replacement of the right knee, but unfortunately, he again developed a PJI.
“No one could figure out what pathogen was causing the infection,” says Dr. Patel, who co-led the case study with Dr. Abdel. “Every time they did a culture on this patient, nothing would grow. But between the immune cell types in his joint tissues and fluids, and the way he presented, he was obviously infected.”
For the study, Mayo investigators re-analyzed a specimen from the patient’s original arthroplasty removal (which had been in freezer storage), using the shotgun metagenomic approach. Remarkably, the tool identified an unusual microorganism, Mycoplasma salivarium (now renamed Metamycoplasma salivarium).
“This was a classic negative-culture case where we had identified no microorganism, but we absolutely knew there was an infection, so we used shotgun metagenomics on his sample,” says Dr. Abdel. “We expected it to identify a microorganism that we’re used to seeing with PJIs. We never expected it to be M. salivarium. ”
Dr. Patel was also astonished. “It was surprising when this organism was identified,” she says. “M. salivarium had never before been reported to cause infections associated with joint replacements. So, we would not ordinarily have been looking for it. The only way we found it was by using a technique that looks for everything. This result was particularly significant because M. salivarium needs a special type of antibiotic treatment.”
The next step was to confirm the result, using more conventional testing. “Once we had an idea of what microorganism he had, we ran some special cultures and were able to grow the same organism that shotgun metagenomics had detected,” says. Dr. Patel. “This proved that M. salivarium was the cause of his infection.”
The patient then received special treatment for his specific infection. Since then, he has been doing well.
“This was a unique win for medicine in two regards,” says Dr. Abdel. “One, we identified a microorganism, and two, we identified one that had never been known to cause infection in a knee replacement.”
Changing the paradigm of infection diagnosis
The case study of the 52-year-old patient is a great example of how this technology can work in the future. And the best part is that this tool is not limited to PJIs. It can be applied to sample-types like spinal fluid, blood, or secretions from deep down in the lungs — almost any place in the body really — to identify infectious pathogens. Thus, shotgun metagenomics has the potential to change how many infections are diagnosed.
“A lot of our traditional molecular tests only look for one microorganism at a time, like Staphylococcus aureus, for example,” says Dr. Patel. “But if the test doesn’t find that bacterium, it’s not helpful. We’ve just wasted time and money, and still don’t know what is going on — though we at least know what isn’t going on. Shotgun metagenomics can look for any kind of microorganism. It’s what we refer to as ‘unbiased’. If there’s a microorganism present, it may be able to find it, no matter what type of microorganism it is, and that’s really exciting.”
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