Tag Archives: plasmid

What is a Superbug??


You hear it every day in the popular press. It instills fear upon its very mention in a news release. But what exactly is a “Superbug?”

Let’s start with a search for “Superbug” on the internet. I did a google search and came up with a few definitions:

Maryn McKenna is a science writer and author of the popular book “Superbug.” She has written some fantastic blogs under the Wired Science blog Superbug. Her book focused on methicillin-resistant Staphylococcus aureus (MRSA), and her blogs have had a major emphasis on multidrug resistant (MDR) bacteria and the implications of antibiotic use on the rise of MDR bacteria. So, it would seem from Maryn’s standpoint that MDR bacteria with pathogenic potential represent a Superbug. That seems pretty logical to me.

Wikipedia states that “pathogens resistant to multiple antibiotics are considered multidrug resistant (MDR) or, more colloquially, superbugs.” States the same that McKenna implies.

Merriam-Webster dictionary defines Superbug as “a pathogenic microorganism and especially a bacterium that has developed resistance to the medications normally used against it.”

It looks like most sources agree on the definition of a Superbug. A pretty simple and straightforward one at that.

Now we get into shades of grey. What if we have trouble defining MDR and/or defining pathogen? For example, what if we find an MDR E. coli isolate on retail chicken such as that reported in the recent Consumer Reports investigation? The authors of this article spend a great deal of time discussing the implications of pathogen contamination of retail meat. But, if you look at the data, the prevalence of true pathogens of concern (such as Salmonella) is actually quite low, while E. coli isolation is more frequent. Still, they lump these together as “presence of bacteria on retail meat”. To make it clear, the classical diarrheagenic E. coli such as O157:H7 are not found on chicken. The biggest risk of E. coli in chicken is that some of these E. coli may have the potential to cause extraintestinal infections in humans, such as urinary tract infections (although this is still a controversial topic). However, the majority of E. coli from poultry do not seem to possess this potential. Survey studies such as the one conducted by Consumer Reports do not distinguish between whether or not an E. coli isolated from a chicken breast actually represents a possible human pathogen.

Let’s also look at the same report and their discussion of MDR. Their data (presented here) illustrates that MDR in pathogens of concern is again very low. Yet, they chose to lump all bacteria together in statements such as “Our test results found that 49.7 percent of our samples contained at least one multidrug-resistant bacterium.” This is again a shady area of the use of the word Superbug, since by definition it is a pathogen that has acquired MDR. Lumping all of these bacteria together as potential Superbugs is not appropriate. If the data were parsed to categorize Superbugs by pathogen type and MDR phenotype, then the data would be much less convincing. While it is convenient and sensational to lump them all together, it is an inappropriate use of the data.

Fortunately, the CDC is taking a lead on a better definition of Superbug. An article in CNN describes CDC’s proposal to categorize Superbugs by threat level. The levels are “urgent,” “serious,” and “concerning.” Those falling in the urgent category include MDR Clostridium difficile (C dif infections), carbapenem resistant Enterobacteriaceae (Klebsiella, E. coli, and Salmonella resistant to carbapenems), and Neisseria gonorrhoeae (causative agent of gonorrhoeae).

So, it seems that we are on the path to appropriately defining a Superbug, taking into account not only that a pathogen is MDR but also the ability of said pathogen to cause disease and hamper antibiotic treatment. A final issue is what policies should be taken to reduce the spread of these Superbugs. Here is probably the most important point – not all Superbugs become so in the same way. Some, such as CRE, pick up plasmids that make them MDR. Others acquire mutations that make them MDR over time. And they all spread differently, some through horizontal gene transfer, some through clonal dissemination, some using both. It is frustrating to see the media and activist groups misuse definitions to promote an agenda. Take, for example, the National Resources Defense Council, which starts this recent article with the following statement: “Feeding low levels of antibiotics to cows, pigs and chickens that aren’t even sick breeds “super bugs” — dangerous germs that are able to fight off antibiotics that spread to our communities and families.”

Now, I don’t disagree that we should judiciously use antibiotics in all settings, including animals. But as I have stated before, blanket statements such as the above one by NRDC are inappropriate. First, it implies that Superbugs as a whole are all impacted by use of subtherapeutic antibiotics in animal agriculture. Not true. Also, none of these reports ever reference articles demonstrating that subtherapeutic use of antibiotics in animals drives the emergence of Superbugs. I challenge you to do literature searches for articles demonstrating in a controlled experiment that this is the case. Believe me, I have tried, and there is nothing out there that convincingly demonstrates that this happens. This is why USDA/FDA have been lobbying for educated removal of certain drugs from animal production versus the mass removal of all antibiotics under a given claim. I think we really need to better consider the underlying science of policy making in this country, and support more science to make better decisions.

All this said, Superbugs are real. The name provokes a lot of unimaginable thoughts to people reading an article. We as humans are very good at sensationalizing and placing blame, less effective at promoting the right forms of change. Using a more concise definition of Superbug, let’s also promote the necessary science to address issues and solutions, rather than using public fear to promote changes in the absence of science.

Measuring plasmid fitness cost and conjugation

We have struggled a lot with the best measures for plasmid cost and conjugative capacity. The challenges lie in 1) relevance, and 2) choosing an in vitro method. I often waffle (to my students’ disliking) about the best way to go about experiments measuring these parameters. If you look in the literature, there is some fantastic work that addresses in vitro measures of plasmid fitness cost (just google scholar “plasmid fitness cost”). In its most primitive form, you can measure the fitness cost of a plasmid by competing plasmid-free versus plasmid-containing bacteria in broth cultures over the course of several passages, measuring the proportions of each cell population on a daily basis (see here). Some great work by Eva Top’s group has come up with “sexier” and likely more accurate means to measure fitness cost of plasmids using multiple parameters and modeling approaches (see here). In our experience, any of these approaches result in a great deal of variation even when controlling for everything we can think of. I think this is because of the nature of the plasmids we are studying (IncA/C) which imposes a very small fitness cost on its hosts. Contrast this to previous work where fitness costs are much larger and easier to measure accurately. A second confounding component – I believe – is that rapid adaptation to IncA/C plasmids occurs when introduced into a host, but there are many factors about this we don’t understand (conditional dependency, cell density impact, temperature impact, role of host genetic background, plasmid-encoded transcriptional regulators, etc.).

We are finding that host background plays a huge role in the persistence and cost of carrying IncA/C plasmids. It has been shown that IncA/C plasmids will be lost over time in some in vitro approaches (see here), however we are finding that in wild type recipients these plasmids are rarely lost in vitro and impose virtually no fitness cost. My opinion is that doing these experiments in a strain like E. coli DH10B does not come even close to reality, and should be avoided.

As for conjugation, filter matings have become the method of choice for measuring conjugative ability of a plasmid. We have tried about every type of mating experiment we can think of, including time point filter matings, liquid conjugations, solid plate matings, etc. for IncA/C plasmids. Measuring conjugation with these plasmids seems to be more reliable and straightforward than measuring fitness cost, however we again see a variety of conjugative frequencies depending on donor and recipient. This is not at all unusual for a broad-host-range plasmid (see here) but it certainly drives me crazy when trying to determine the best approach for measuring conjugation – there are limitless possibilities. For these reasons, we have mostly stuck with E. coli K-12 (which I feel is at least a better choice than DH10B) as a donor/recipient for these experiments in an effort to first establish a baseline from which to pull what’s left of my hair out in future experiments.

I guess the point of this blog is to spew my frustrations with these types of experiments and remind myself the cautions of interpreting their results. Comments are welcome!