#bacteriatest

August 12, 2020

Antimicrobial Resistance: Many reasons to act soon

We have a first-hand experience, thanks to COVID, of when infections become deadly. Now imagine if treatments for diseases like salmonella, tuberculosis, malaria, and other infections are ineffective because of antimicrobial resistance (AMR). This would undo almost a century of medical progress.

AMR is when microbes adapt to the antimicrobial drugs used to treat them, rendering the drugs ineffective. Every time microbes are exposed to a drug, susceptible strains die in the presence of the antibiotic, whereas resistant strains survive and then multiply without competition from the susceptible strains. Antibiotic use is on the rise, with a 40% increase in use over 10 years (2000-2010). However, around 50% of antibiotics prescribed in the US are unnecessarily or inappropriately prescribed.

Why unnecessarily? Because it takes a long time to get test results, doctors prescribe antimicrobials while they wait. Since this is basically a trial-and-error process, they may end up trying several different antimicrobials by the time they get the diagnostic result. After they get the results, they may have to prescribe something entirely new. This process basically trains the microbes how to become resistant to antibiotics.

There are two ways to address AMR. The first is creating new antimicrobial drugs that the microbes are susceptible to. While this is an important way we can combat AMR, developing new drugs is reactive, rather than proactive. As we expose microbes to these new drugs, they will begin to develop resistance. This puts us back in the same place we started, and requires continual drug development to stay ahead. Even then, there is no guarantee that researchers will be able to develop a new drug by the time a microbe becomes resistant to the old one.

The second method of addressing AMR is developing better diagnostics. Better diagnostics will allow medical professionals to know what they’re dealing with faster, which allows them to use specific and effective treatments. Since microbes are being exposed to fewer drugs, they have less opportunities to become resistant, ultimately slowing down the spread of AMR. Doctors can continue using existing antimicrobials, and it gives researchers more time to develop new ones.

Patients with an antimicrobial resistant strain of infection can expect longer hospitalizations or stays in intensive care. They will also likely need more tests, more expensive treatments, and spend more time not working, which increases the financial impact of the infection. Additionally, major surgery and many cancer treatments will be more dangerous without effective treatments for an infection. Hospital visits will be more risky, as hospital-associated infections (HAIs) are often antimicrobial resistant.

AMR also has significant impacts at the global level. 50,000 people die every year just in Europe and the US because of AMR right now, and these impacts keep getting worse as time goes on. By 2050, some researchers estimate that AMR will cause 10 million deaths, which would be 1.8 million more deaths than cancer. Additionally, Gross Domestic Product (GDP) would be 2-3.5% lower and 100 trillion dollars would be lost.

Addressing AMR promptly and decisively is imperative to lessen these catastrophic impacts. The United States government, the World Health Organization, and other organizations have urged more careful use of antibiotics in healthcare and agriculture. They have also increased their support for the discovery and development of new antibiotics and better diagnostics. In the end, it will take the government, physicians, and all of us to effectively combat the spread of AMR. At the individual level, we need to increase awareness of AMR, and do our part to avoid pressuring physicians to prescribe antibiotics, especially when they are not needed.

January 2, 2020

Infrared-based bacterial identification – a clinically viable alternative to PCR-based bacterial diagnostics

New Year’s greetings and best wishes for 2020 to all!

We had ended last year, coincidentally, pondering why wide spread application of PCR-based tests in bacterial diagnostics has been elusive and identified a couple of key features that limit their use. It seems appropriate to start the new year with a discussion on one technology that can address those limitations – Infrared-based identification (IR).

What, you might be wondering, – that dilapidated instrument I vaguely recall using in undergraduate chemistry lab? Well, not quite that instrument but yes, one that utilizes the same fundamental principles.

The concept of using IR for identifying bacteria is not new. The earliest reference that we have been able to find dates back to 1950s! But, instrumental and computational limitations held back the potential for using this technology for identifying bacteria until the early 1980s. Naumann and colleagues took advantage of computational advances to demonstrate the ability of this technology to identify bacteria rapidly. Since then the use of IR for rapid and reliable identification of microbes to the strain level have been well documented. Reference databases to facilitate rapid identification of microorganisms are already available with some containing as many as 7000 strains.

How does the technology work?
IR, as you may recall, is a widely used vibrational spectroscopy technique that is used to identify compounds, even those present in mixtures. It is routinely used in raw material testing in the pharmaceutical and other industries as well as in testing of milk and milk products. All of the components that make up a bacterium (proteins, lipids, sugars, etc.) contribute to an IR “fingerprint” (see figure below). The nature and concentration of these components differ from one strain to another resulting in unique IR-fingerprints. This bacterial fingerprint has been used to differentiate between multiple bacterial species and strains including differentiating between antibiotic-resistant and -susceptible strains.

Bacterial fingerprint obtained by Infrared spectroscopy. Each species and strain has a different composition and hence a unique fingerprint.

How does it compare to PCR-based identification?
Two key limitations of PCR-based tests that we had discussed previously were clinical sensitivity of the test and cost per test. If a PCR-test yielded a negative result, the clinician would not have any actionable information. On the other hand, with IR-based identification, the profile of a bacteria is very distinctive and its absence clearly indicates the absence of bacteria in the sample. In such a case, the clinician can actively consider whether administering antibiotics will be of any benefit to the patient. In the case of a positive result, the actions are similar to that with a PCR-based test with several important benefits. These are:

the result is available in ≤ 10 minutes
No custom labels or reagents are needed lowering the cost per test
It does not require specialized laboratory for operation
The bacteria is intact and viable after the analysis
Antibiotic resistance can be determined
The number of species and strains that are identified can be easily expanded without requiring new primers or antibiodies. This is done as a software update that consists of the fingerprint of the new bacteria and adjustments to the recognition algorithm, if needed.

You might be wondering at this stage why, if IR has all these benefits, there has not been any IR-based commercial instrument for use in bacterial ID? There are commercial instruments from Bruker, Thermo, and others that are used for bacterial ID in food safety testing. However the methodology used today requires bacteria to be cultured prior to identification (i.e. the same as most PCR-based tests). In addition, the bacteria has to be separated from the matrix components in order to make an accurate ID. Owing to these reasons, the technology has not yet seen widespread adoption for clinical use.

It is this aspect that we have impacted with the development of our separation cartridge. As mentioned previously, our separation cartridge can isolate and concentrate intact bacteria directly from blood with minimal manual intervention. The isolated bacteria can be identified using any technique. Using it upstream of IR however, permits rapid and sensitive identification of bacteria directly from patient sample without using any bacteria-specific labels or reagents. This combination of our separation cartridge and IR-based identification will, we believe, permit rapid, inexpensive, and hypothesis-free detection and identification. We aim to demonstrate this in 2020.

As we have said before, it’s not that IR (or any other ID technique) has to wholly replace PCR-based tests. The problem is large enough that multiple solutions will be needed. But, given the history of limited gains in developing effective PCR-based bacterial ID tests, the more diagnostic options we have, the better we can aid physicians in making the best decisions for treatment while slowing the spread of antimicrobial resistant bacteria. IR-based identification presents a compelling case to be a key diagnostic option.

December 23, 2019

Why is widespread clinical application of PCR for bacterial ID so elusive?

A common refrain in this post-antibiotic era is that we need new antibiotics and new diagnostics . While the challenges of developing a new antibiotic are better acknowledged and understood, many are very surprised that we still use fundamentally the same procedure as used pre-WWII.

So, how is it that we are, at the start of 2020 and ~30 years since the dawn of the PCR-era, still talking about the need for better bacterial diagnostics? There are multiple technical and real-world challenges that continue to stymie the development of PCR-based tests such as speed, volume that can be processed, number of bacteria identified, and so on. Sensitivity and Specificity of a PCR-based test (or rather the lack of sufficient Sensitivity and Specificity) are two key performance attributes that have held back widespread clinical use of PCR-based tests. For this discussion, we focus on identifying bacteria directly from blood for guiding treatment of bloodstream infections, especially those that might lead to severe sepsis or septic shock.

Multiple PCR-based approaches are being developed to rapidly identify bacteria from blood. To a neutral observer it would appear that the reason we do not have a suitable bacteria test is because we have not developed a good enough PCR-based test. And that suitably optimizing such a test would solve the problem. Is this correct? Or are there some fundamental limitations that have held back clinical application?

In our opinion, the fundamental technical limitation is centered around the sensitivity of PCR-based tests and a fundamental practical limitation is centered around the ability to lower costs to a level that the healthcare system can support.

There are numerous text books and reviews providing a basis for determining the sensitivity and specificity of a test. Here is one. Briefly, Sensitivity refers to how good a test is at correctly identifying people who have the disease. While Specificity is concerned with how good the test is at correctly identifying people who do not have the disease.

What can we learn from these numbers for a bacterial diagnostic based on PCR? Let’s take the case of a hospital that analyzes 100,000 bacterial ID tests a year.

The percentage of samples that turn positive upon blood culturing ranges from 5 to 10%. Using the upper end of this range it means that out of the 100,000 samples submitted for bacterial ID tests, ~10,000 turn positive. [Note: This is frequently viewed as the number of samples that actually contain bacteria though there is widespread acknowledgment that culturing underestimates the number. More on this later. But, for the moment, since culturing is the gold standard (albeit an imperfect one) let’s go with 10,000 samples out of the 100,000 samples contain bacteria and therefore represent an infection.]

Data from two commercially available PCR based tests exhibit sensitivity and specificity are shown in the table below.

	Sensitivity	Specificity
Septifast ®	42.9%	88.2%
SepsiTest ®	28.6%	85.3%

The sensitivity of these two tests range from 28.6% to 42.9%. In other words, if the PCR result came back negative (suggesting there is no bacteria), you could only be ~43% sure that there really was no infection! Think about that for a moment. If you were a physician making this decision, would you decide not to administer antibiotics based on this result? You’re most likely going to administer the antibiotics as you’re not that confident that you can rely on the negative result.
Similarly, the specificity of these two tests range from 85.3% to 88.2%. In this case, you can be 88% sure that if you got a positive result, the patient has an infection though there’s a 12% chance that the result may not be accurate.

Let’s apply the above numbers to our hospital that processes 100,000 blood culture samples. Suppose that these samples are tested by a PCR-based test instead of being submitted for blood culture testing. Using the Sensitivity and Specificity numbers from above, this means that, of the 100,000 samples, 15,400 will yield a positive result. But, only 4,600 of these are truly positive. So, you will end up administering antibiotics unnecessarily for a large number of patients based on the 10,800 positive results.
Similarly, you would have had 84,600 negative results of which 5,400 are false negatives. This means that you would have chosen not to administer antibiotics despite patients needing it.

	“True” Result
	Positive	Negative
PCR test positive	4,600	10,800
PCR test negative	5,400	79,200

As a physician or a hospital, the number of incorrect decisions resulting by relying on such a test is too high – jeopardizing patient safety. Does it really provide a significant benefit over the current practice where antibiotics are administered based largely on clinical judgment? At the present moment at least, the general opinion is no. Since it does not offer significantly helpful guidance relative to current practice it does nothing to correct overuse or misuse of antibiotics.

Most of the time when we consider how to use the result from a diagnostic test, we ask ourselves, if it yields a positive result would I know what to do next? That is an important question. But, in this application, it is equally (if not more) important to ask if the test yields a negative result, would I know what to do next? There is not sufficient data (and may never be) to guide treatment decisions when a PCR-based test is negative. This is the fundamental technical limitation.

Besides their performance, PCR-based tests also create problems due to their cost and operation. A single test costs $70 – $200 based on the number of bacteria identified. Using our example, if such a test were used for each sample currently submitted for blood culture, it would cost each hospital $7-$20 million (just in consumables). Which consumes a significant portion of a microbiology lab budget leaving little to no money for other tests. And still leaves a large number of bacteria unidentified!

In theory one can design a PCR test that is multiplexed to cover a large number of bacteria. But, this will increase the cost per test. Splitting the number of bacteria identified across multiple test panels is one way of covering a broader range. But, this takes away the advantages of cost reduction due to large volumes. How does one respond to new strains or species that are of urgent concern that was not anticipated? In different regions of the world? The modifications to the manufacturing process to address these different demands make it very challenging for the manufacturer to keep costs low.

So, at a fundamental level, PCR-based tests for identifying bacteria directly from blood face limitations due to poor performance, high costs, and appear to not aid decision-making or operational efficiency.

Significantly improving sensitivity and controlling costs are therefore necessary, but not sufficient, conditions for enabling widespread use of PCR as a bacterial ID test direct from patient sample. And until they are satisfactorily resolved, there will continue to be a reluctance in using such tests to guide antibiotic treatment.

Which means that we owe it to ourselves and all patients to consider and develop alternative ID techniques. It’s not that one technique is a winner and the other the loser in such an effort. The problem is large enough that multiple solutions will be needed. The more diagnostic options we have, the better we can aid physicians in making the best decisions for treatment while slowing the spread of antimicrobial resistant bacteria.