Better, Faster, Cheaper

The 2024 AMP annual meeting and expo was filled with exciting talks and innovative research. Early into the event, Robin Patel, Professor of Individualized Medicine at Mayo Clinic, presented “Infectious disease diagnostics – from gram stain to next-generation sequencing.” Now, she joins us to share more about her experience with infectious disease research and combating persistent bottlenecks with modern diagnostic tests.

In your AMP presentation, you mentioned that clinicians are also to blame for antimicrobial resistance (AMR)…
 

Firstly, this statement was not meant to point fingers, but to reflect on how we’ve reached where we are with antimicrobial resistance and what we can do better moving forward. Antibiotics have been lifesaving, and the medical profession has therefore used them extensively – when necessary and when we aren’t sure if they are needed – to avoid missing anyone who might benefit. The latter approach, while well-intentioned, has contributed to resistance over time.

When resistance develops, we turn to broader-spectrum antibiotics. However, this leads to further resistance, creating the challenges we face today. In the past, we lacked diagnostic tools to precisely identify who needed antibiotics and which to use. Without those tools, prescribing empirically has often been the only option, even if it is not ideal.

Looking back, it’s clear that some practices weren’t perfect, but they were based on the knowledge and resources available at the time. We didn’t foresee the extent of resistance we now face. We need better diagnostics to guide antibiotic use, allowing us to target treatment more effectively and reduce overuse of broad-spectrum antibiotics.

This reminds me of the opioid epidemic, where well-meaning decisions contributed to unintended consequences. Just as we’re working to correct past mistakes with opioids, we need to do the same with antibiotics. Acknowledging these issues isn’t to assign blame – it’s about learning and improving. Resistance isn’t something we can eliminate, but by understanding how we got here and focusing on better practices, we can work toward minimizing its impact.

How can modern diagnostic tests help curb the emergence of AMR?
 

This overuse of antibiotics – especially broad-spectrum agents – contributes to resistance. With better diagnostics, we can identify exactly who needs antibiotics and which ones are appropriate, reducing overall use and favoring narrower-spectrum options that are less likely to drive resistance. We can do better for both current and future patients by using antibiotics more wisely.

Can you tell us about your work to increase understanding of infectious diseases?
 

There’s often a misconception that medicine has all the answers about infectious diseases, but that’s far from true. Many infectious diseases exist that we haven’t identified yet. For example, mosquito- and tick-borne diseases that have been discovered in recent years, including by our group, are not new – they’ve been around, but we didn’t recognize, name, or diagnose them. Today, there are patients we could help if we knew more about infectious diseases – in other words, there is more to discover.

I also highlighted examples of diseases that were previously not considered infectious but are now known to be caused by infections. A well-known example is Helicobacter pylori, which causes peptic ulcer disease, initially thought to be linked to lifestyle factors like stress or smoking. We now know it’s an infectious disease, and therefore treatment has drastically changed as a result.

Another fascinating example is hyperammonemia syndrome in lung transplant patients. A small percentage of lung transplant recipients develop high blood ammonia levels in the immediate post-transplant period, which can cause brain damage (encephalopathy) and even death. Previously, this was thought to be a metabolic disorder, and treatment focused on managing the biochemical abnormality – often unsuccessfully.

Our team and others discovered that the cause is Ureaplasma (Ureaplasma urealyticum or Ureaplasma parvum). These bacteria produce high ammonia levels through the enzyme urease. Once we identified this, patients were treated with antibiotics targeting Ureaplasma species, enabling a cure. This was a breakthrough, as we hadn’t historically considered this syndrome to be infectious.

These cases highlight how much we still must learn about infectious diseases and the potential to discover and treat conditions we don’t yet fully understand.

At AMP, you stated you could give a whole additional talk on what tech clinical microbiology needs – could you give us a couple examples?
 

We’re making progress, though slowly, in getting the tools we need. At a high level, the ideal diagnostic test should be accurate, fast, inexpensive, easy-to-use, and – most importantly – it should improve patient outcomes. That’s the goal.

As for the technologies involved, I am open to innovation and surprise – tools we haven’t even imagined yet that could make a real difference. Broadly speaking, we’re looking at automation, ease of use, testing closer to our patients, and capabilities beyond what current technology offers. AI and machine learning are becoming part of our practice, but they’re also just tools.

Ultimately, diagnostics are not the goal themselves; they’re a way to improve how we care for patients.

Why is digitization so important for the lab of the future?
 

In traditional microbiology laboratories, much of the work was manual – people recorded observations with pens and paper. This approach made it difficult to standardize, analyze, and fully use the data. To improve, all data – written notes, test results, and visual observations like stains and plates – needs to be digitized.

When data are digitized, they can be analyzed and even reanalyzed with new and improved tools as they become available. For example, if a new analytic method is developed, we can quickly apply it to existing digital data without redoing tests. This enables rapid adoption of faster, better, and less expensive diagnostics over time.

Digitizing also helps integrate lab data with patient information, giving a clearer picture of what’s happening in the lab and with the patient. Because we live in a digital world, continuing to expand digitization will enhance patient care. We’ve made progress, but the more we digitize, the better the outcomes we can achieve.

How have technologies like MALDI-TOF mass spectrometry and molecular genomics revolutionized diagnostics?
 

MALDI-TOF mass spectrometry in bacteriology and mycology is a great example of transformative technology. If you had asked me 20 years ago whether we’d routinely use proteomics to identify bacteria and fungi in clinical labs, I would have said no – but today, it’s common practice. This was made possible by combining the technology of MALDI-TOF mass spectrometry with advanced computer systems and databases that quickly analyze data.

Interestingly, the idea was not new. In the 1970s, researchers like John Anhalt and Catherine Fenselau speculated about this possibility, but the technology and informatics needed to make it work didn’t exist until much later. Once everything aligned, MALDI-TOF mass spectrometry revolutionized microbiology. When we first tested it, we quickly realized it was a game-changer and replaced older methods almost immediately.

What made MALDI-TOF mass spectrometry stand out is that it met all three of my criteria for a great new test – better, faster, and cheaper. Few technologies manage this trifecta. Many innovations improve only one area, which makes adoption trickier. But when something hits all three, like MALDI-TOF mass spectrometry did, it’s an obvious choice.

This example gives me hope for future breakthroughs – technologies we can’t yet imagine, that will reshape the field. Of course, not every new idea works, but when one does, it has the potential to transform how we work and care for humanity. I can’t wait to be surprised by what future technologies hold!

What excites you about metagenomic sequencing – what could this technology mean for future diagnostics?
 

Metagenomic sequencing involves analyzing all the genetic material in a sample. In infectious disease diagnostics, it’s used to detect microorganisms by identifying their DNA and RNA sequences. Though it has the potential to find any microorganism in a sample, it is not perfect yet. Sometimes a pathogen’s genetic material is not present in a sample, even if the patient has an infection. There is still a lot of development needed.

One exciting application is identifying antimicrobial resistance. By sequencing deeply enough, we can detect antibiotic resistance genes and antibiotic resistance associated mutations (SNPs) directly from a sample. If we know which genes or mutations cause resistance, we can not only identify the microorganism but also determine how to treat it – all in one step. However, this process is complex and requires further research and development.

Another area of interest is assessing the host immune response. Most samples contain an abundance of human genetic material, allowing examination as to how the patient’s immune system is reacting. This can help determine if a detected microorganism is causing disease or is just present without harm. It can even provide evidence that a microorganism may be causing disease even when the microorganism cannot be detected. Finally, this can potentially be used to track whether treatments are working.

Additionally, while I focus on microbiology, sequencing can also reveal genetic risks for certain diseases or even detect unrelated conditions like cancer, all from the same data. The possibilities are exciting.

Why do you not like the term “next-generation sequencing”?
 

It feels temporary – sequencing technology is evolving, and there will likely be advancements beyond what we call "next-generation" today. It is hard to know what term will fit future improvements, so "next-generation" already feels outdated as we think ahead.

To what extent do you think POCT and at-home testing will shape the future of infectious disease diagnostics?
 

POCT and at-home testing will play a major role in the future of infectious disease diagnostics. The COVID-19 pandemic showed that people can successfully collect their own specimens and run their own tests, when given the right resources. Many infectious diseases could be diagnosed this way – in other convenient locations close to the people that need them. This shift will greatly benefit humanity; we are already moving in this direction and will continue to do so.