Antibiotic Resistance as a Force of Nature

My research focuses on antibiotics – specifically antibiotic resistance. Last week I gave a seminar on my work, which was followed by some excellent questions about the origins and evolution of resistance. While I don’t personally get my hands dirty studying molecular evolution or microbial ecology, I think about these topics often, for a couple reasons. First, the origins and evolution of resistance factors have interesting implications that contextualize the structure and function of resistance factors – it helps me make sense of the molecules I study. Second and more importantly, the evolution of antibiotic resistance gets at a fundamental understanding of the environment and the world around us. We tend to focus on the problems that resistance create in medicine, but in nature, the relationship between microbes is much more complicated than we might assume. Antibiotics and resistance give us a window into the fascinating world of microorganisms and their strange and complicated existence.

In the discussion after my talk, I brought up a recent paper in Nature. In this report, a group at Harvard Medical School modelled the community dynamics of antibiotic-producing and -resistant microbes. The headline finding was that antibiotic production and resistance can stabilize microbial environments. The production and degradation of antibiotics are an intrinsic feature of mature microbial communities.

This seems counterintuitive – how would antibiotics, substances that kill bacteria, bring stability to an ecosystem?

It isn’t as ridiculous as it may sound. While a majority of antibiotics research focuses on the medical applications and repercussions, a less celebrated contingent of microbiologists look at the environmental role of antibiotics. These researchers find that antimicrobials play a more nuanced role than we have been led to believe. Rather than the chaotic battle royale we picture when we think of the microscopic struggle for survival, they find that antibiotic resistance often plays subtler roles in the microbial world. Let’s look into that world.

Microbes live in complex communities, pass toxins and signalling molecules back in forth in a complicated web of interactions. Image adapted from the Lewis Lab at Northeastern University. Image created by Anthony D'Onofrio, William H. Fowle, Eric J. Stewart and Kim Lewis.
Microbes live in complex communities, pass toxins and signalling molecules back in forth in a complicated web of interaction.
Image adapted from the Lewis Lab at Northeastern University. Image created by Anthony D’Onofrio, William H. Fowle, Eric J. Stewart and Kim Lewis.

What is Antibiotic Resistance?

We should get some definitions out of the way. An antibacterial is a chemical compound that kills or stops the growth of a bacterium. Antimicrobials are less well defined, and include antibacterials as well as antifungal and antiparasitic compounds, sometimes antivirals as well. Antibiotic was coined to specifically refer to a chemical that kills or stops bacteria but doesn’t affect animal cells – a nontoxic antibacterial. It since expanded to include some compounds that also target fungi and protists, but not antiviral compounds. In common speech, “antimicrobial” and “antibiotic” frequently mean “antibacterial”, so I’ll use them interchangeably here.

Antibiotic resistance is a catch-all term we give to many different mechanisms a bacterium can use to survive and/or grow, in the presence of an antibiotic. Every antibiotic has a specific target it interacts with, and anything that keeps the antibiotic and target from binding will result in resistance. Common mechanisms of antibiotic resistance include:

  • Chemical breakdown of the antibiotic
  • Molecular pumps that kick it out of the cell
  • Changes to the microbial target that block the antibiotic
  • Bypass the target molecule to allow the microbe to grow even when the target is productively blocked

Resistance factors are the molecules that give the bacterium resistance, by any of the above mechanisms. These resistance factors have diverse origins. In some cases, they’re still controversial. But broadly speaking, there’s two types of antibiotic resistance: new resistance and ancient resistance.

Two Origins of Antibiotic Resistance

New resistance makes sense. It is what we think of when we talk about antibiotic resistance as an example of Darwinian evolution. A spontaneous mutation emerges that confers resistance, and selective pressures drive it to succeed and take over the population. This is a common phenomenon that we have seen in the clinic and can induce in the lab, but is far from the only means by which antibiotic resistance happens.

Today I’ll focus on a second type of antibiotic resistance – the transfer of ancient antibiotic resistance factors from environmental bacteria into the strains that cause human disease. It was found in the 1970s that some antibiotic resistance factors appear to come from the microbes that produce the antibiotic. The thinking was that they act as a means of self-protection for the bacteria from their own toxin. This is one origin for resistance factors, although the original origin of many of these environmental resistance factors remain unknown.

Transfer of an environmental resistance factor to disease-causing bacteria results in resistance within the pathogen. In cases where this has happened multiple times, we get superbugs with resistance to multiple antibiotics. The collective environmenal pool of antibiotic resistance factors has been dubbed the “antibiotic resistome“. These resistance factors form a latent environmental reservoir, ready to jump into the strains that make us sick.

Antibiotic Resistance as a Healthcare Menace

Most of our concerns about antibiotic resistance come from the impact it has on medicine. Antibiotics are critical to our treatment of infectious disease, and are also necessary in prophylactic use for surgeries, cancer treatment, neonatal care, and many other intensive medical procedures. The spread of antibiotic resistance in pathogens could remove our ability to treat these infections, or care for many of our society’s most vulnerable members. This could lead to a transition to a “post-antibiotic era” where once again these miracle drugs are not available to us. A minor infection from a scraped knee, sore throat, or scratch off a rosebush could be fatal.

While spontaneous emergence of antibiotic resistance occurs, resistance frequently comes from environmental cross-over. A benign soil microbe meets a pathogen, shares some genetic material, and that pathogen becomes resistant. A notorious recent example of this is the emergence and worldwide spread of the New Delhi beta-Metallolactamase, a resistance factor that knocks out some of our last-resort antibiotics.

In the face of this ongoing menace, what do we do? For decades, the answer has always been “find more antibiotics”. This is important to do, but not enough. We search the world for more obscure microbes that might produce a new antibiotic, and we’re beginning to find a few, but we are still falling behind. Searching for new antibiotics is a game of whack-a-mole, finding new drugs as nature sends more sources of resistance to knock down. We’ve kept up for a while, but now we’re falling behind.

Some of the search for new ways of killing microbes involves looking for new targets to bind antibiotics to – reading the antibiotics literature, everyone and their grandmother wants to sell you a new potential antibiotic target. Other strategies include directly inhibiting antibiotic resistance factors, blocking bacterial toxins to “disarm” the bacterium, or more obscure methods like bacteriophages. But none of these strategies have yet led to sustainable long-term solutions for treating resistance. We may be doomed to fail – we’re going up against a fundamental feature of nature.

Antibiotic Resistance as a Force of Nature

Almost as long as we’ve had antibiotics, we’ve had antibiotic resistance. In his 1945 Nobel Prize Lecture for the 1928 discovery of penicillin, Alexander Fleming said:

It is not difficult to make microbes resistant to penicillin in the laboratory by exposing them to concentrations not sufficient to kill them

Since Fleming’s time, any newly-developed antibiotic has had only a few years of use before a case of antibiotic resistance was identified. This observation alone suggested that antibiotic resistance existed in the environment before we began to use these compounds to cure ourselves. Recent studies of permafrost cores and isolated cave systems have also produced compelling evidence that antibiotic resistance factors have existed in the environment long before humans came around.

The idea of transfer of bacterial resistance factors took some time to catch on. Discovered in the 1950s in Japan, the greater scientific establishment received this finding with disbelief and scorn. It took many additional reports for researchers to believe that resistance could move from one bacterial species to another. By the time the greater scientific community clued in, antibiotic resistance was already running rampant in some clinical strains. Since that point we have been in a constant search for new antibiotics, often falling behind the spread of resistance.

A Microbial Cold War

Starting with the first discoveries of antibiotics, we’ve considered them to be weapons in an ongoing environmental war between microbes. Selman Waksman, Nobel laureate for the discovery of streptomycin*, developed his entire research program on this assumption – that there are microbes in the environment that produce antibiotics in order to kill those around them and gain selective advantage. This program was replicated in many labs, resulting in the 1940’s-1960’s golden age of antibiotic discovery.

Waksman envisioned the environment as an ongoing microbial war. An antibiotic is the bacterium’s sword, resistance is it’s opponent’s shield. But what if that’s the wrong way to think about it?

What if this microscopic battle between bacteria was more of a Cold War? An ongoing stand-off that only occasionally breaks out into active conflict? That’s what microbial researchers seem to keep finding. Microbes play games of rock, paper, scissors using antibiotics. They punish freeloaders, engage in brinksmanship and even cooperate in difficult times. These bacteria are in competition, but this competition generates a kind of rolling stability as they hold each other in check.

Things get even more interesting when we decrease the concentration of an antibiotic below the range at which it kills – to “sub-therapeutic”, “sub-lethal”, or “sub-inhibitory” concentrations. In toxicology, we talk about how “the dose makes the poison” – the same thing applies for bacteria. At low concentrations of antibiotic, bacteria can trigger adaptive stress responses, go into dormant states, adjust their metabolism, trigger complex growth modes (biofilms) or change their behaviour in even more subtle ways. At the extreme of this concentration range, it’s even been suggested that antibiotics might instead be thought of as signalling molecules rather than toxins.

With an environment full of these compounds at various concentrations, microbes are in constant cross-talk with each other. Studies like the most recent paper on community stability find that even in mixtures of a few strains of bacteria, antibiotics and resistance can keep competing stains in check, stabilizing a community and keeping any particular one from growing out of control. With 10-50 000 different species in a single gram of soil, the interrelationships are almost limitless.

As metagenomics studies and other work teach us more about the diversity of resistance in the environment, we find that microbial communities are complex, with different producers and resistant strains in constant rolling flux. Add to this an understanding of things like quorum sensing, and a picture of a complex, dynamic ecosystem emerges. A network of chemical cross-talk forms, and we are only starting to scratch the surface of this environmental complexity.

The use of chemical compounds to influence each other are not an exception, but the rule. The diversity of microbial species also drive a diversity of chemical compounds used to fight, defend, and communicate with each other. These countless microbial compounds have a name: the parvome. We harvest chemicals from this source for use in medicine, but must remain aware that any environmental molecule will also have corresponding mechanisms of resistance.

Rather than the all-out war that Waksman envisioned, the microbial world works like international diplomacy or a financial market. Every interaction trickles through a network and affects everything else. Booms and busts happen, but on average, the system selects for a kind of greater stability, so the entire community gains as a whole. Outright conflict is a zero-sum game. Most microbes prefer a tense collaboration, quietly manipulating their neighbours but avoiding actual battle. A microscopic Cold War. That war only rarely comes to active conflict, when we strip away diversity and release the bacteria from their self-imposed order.

Fear in a Handful of Dust

When we realize that the microbial world works this way, it means that antibiotic resistance is everywhere. Screen any environmental sample for resistance and you’ll find it. If an antibiotic exists, so do its resistance factors. Even antibiotics we haven’t yet discovered have resistance in the environment. This is a fascinating and terrifying thought at the same time.

It’s terrifying because antibiotic resistance is an enormously urgent public health concern. We’re running out of time. And as we understand that resistance is all around us, we realize that we’ll never eliminate it. We can only beat it back, and we can only play the game of antibiotic-resistance whack-a-mole for so long. Resistance seems to be an intrinsic property of the microbial world that we’ll never escape. As a great mathematician once said: Life finds a way.

I’m cynical whenever I see headlines about new breakthrough antibiotics or antimicrobial game-changers. All these do is kick the eventual resistance down the road a little bit farther. Even though I study mechanisms of resistance in hopes of blocking them, I think the most important solutions to antibiotic resistance will come from systems approaches: policy, sanitation, rapid diagnostics/response, and surveillance programs. We can’t control what resistance is out there, but we can take steps to limit the transfer of that environmental resistance to pathogens. Agricultural antibiotic use requires urgent action. Improved sanitation and means of reducing the spread of pathogenic microbes is critical.

As we struggle to deal with our impending antibiotic crisis, we are starting to realize how inevitable it probably was. It emerges from a complicated network of microbial cross-talk. Countless microbes silently jostle against their neighbours, subtly nudging with chemical signals, and being poked back with molecular weapons. This microscopic opera happens around us at all times, silently shaping our world and occasionally making our worst diseases even harder to  fight.

The complexity is beautiful, and it is terrible.

* It should be noted that Waksman’s student, Albert Schatz, was heavily involved in the discovery of the compound, and by many accounts was snubbed by the Nobel committee when they presented the award to Waksman alone.

Embracing the Molecular Jiggle

A molecule is intangible. It’s too small to see, too small to feel. Trillions could fit on the sharp end of a pin. These strange entities lives in a world very different from our own, at the boundary between quantum uncertainty and statistical chaos.

Many processes in chemistry, biology, and medicine depend on our understanding of molecules in this alien world. However, it can be a challenge to accurately represent what molecules are really like. To simplify things, we often cheat and draw them as “blobology” – featureless coloured circles and squares. If we have structural data, we can do better and present them as a ball-and-stick models, ribbon drawings, or molecular surfaces. While helpful, these more detailed representations are still cheating. Images of a molecular structure all share a major limitation: they’re static. They don’t move.

A molecule’s function depends not just on its structure, but in the change of structure as it interacts with other molecules. This includes large, dramatic movements that translocate thousands of atoms, small movements of individual atoms, and everything in between. Macromolecules that carry out biological processes contain thousands to millions of atoms, each with some freedom of motion. They are intrinsically dynamic and flexible, and this motion is critical to our understanding of how they work.

I’ve mentioned before that I often think of molecules like LEGO, snapping together to build more complicated systems. But if we think about jiggly molecules, we should think less “brick” and more “jellyfish”, “slinky”, “JELL-O”, or “Flying Spaghetti Monster“. This is a case where a descriptive adjective can be really helpful, like greasy polypeptides, oily odorants, fuzzy electron density, and squishy polymers.

How can we best describe biological macromolecules? They’re jiggly.

Jiggle jiggle jiggle. T4 lysozyme, PDB ID 2LZM
Jiggle jiggle jiggle. T4 lysozyme, PDB ID 2LZM

Shake what mother nature gave you

A drop of water may look serene, but on the molecular scale, it is a violent mosh pit of collisions between molecules. Think soccer riot, demolition derby, or a playground full of kids on espresso. Particles move in all directions, flailing about wildly, constantly crashing into each other. Inside a biological cell, the chaos is even wilder, with thousands of different types of molecule bumping, wiggling, twisting, and squirming around. The Brownian motion of particles in this soup puts molecules in a state of constant fluxuation and vibration. They bend, twist, and bounce. They sample an almost infinite number of shapes, switching between states at breakneck speed.

While molecular scientists understand the complexity of this world, we can skim over it when communicating our work. Worse, sometimes we outright forget. We talk about how “the structure” of a molecule was solved. We assume that the shape of a molecule determined from crystals represents its shape at all times. We pretend that “disordered” parts of the molecule don’t exist. In many cases, these approximations are good enough to answer the questions we want to ask. Other times, they hold us back.

We should always remember the importance of flexibility. But if we know that molecules are intrinsically flexible, why do we fall back to talking about static shapes? The technology we’ve used to study molecules, and the history of the field have both played a role.

Structural biology: picking the low-hanging fruit

Structural biology has been an extremely powerful set of techniques to look at the high-resolution structure of molecules. But limitations of these techniques have trapped our thinking at times to picturing molecules as static, blocky particles. X-ray crystallography and electron microscopy calculate an average structure, which represents a huge ensemble of possible conformations. We sometimes refer to parts of molecules we can’t resolve by these techniques as “disordered”, although what we really mean is that is that all of the molecules we are looking at have different shapes, and we can’t average them into a meaningful representative model. As a byproduct of the technique, we miss some of the forest for trees. Other techniques like nuclear magnetic resonance (NMR), more easily acommodates multiple models, but because of the precedent set by crystallography, we still frequently treat NMR structures as a single model.

These techniques also bias us toward samples that are “well-behaved” – that is, they easily crystallize, purify, or otherwise make the life of the scientist easy. The problem here is that the molecules that purify or crystallize more easily are often those that show less flexibility. Lab lore dictates that flexible molecules cause problems in structural biology labs. As a result, scientists have picked a lot of the low-hanging fruit, leaving the most flexible (and some might argue, most interesting) molecules alone. As structural techniques mature, they are beginning to seriously tackle the idea of flexibility, but we still contend with a historical legacy of studying the easier, less flexible molecules.

Biochemistry: From floppy to blocky

The history of biochemistry has also affected our thinking about molecular flexibility. The history of the field tracks our growing understanding of how large molecules work. With more data and more powerful techniques, we have developed increasingly nuanced ways of thinking about these complicated microscopic machines, but that history leaves a legacy.

Without knowing details of molecular structures, the first biochemists were left to assume that strings of atoms will exist as a floppy or disorganized shape in solution, waving around unpredictably. This was changed by the father of biochemistry, Emil Fischer. In 1890 he proposed a model that changed how we viewed biological molecules. The “lock and key” model involves two molecules with rigid, complementary shapes. Features of the smaller molecule (the “key”) perfectly match features of the larger (“lock”) so that they can specifically interact. A well-defined, rigid structure is necessary for this mechanism to work.

However, alongside Hofmeister, Fischer also determined that biological macro-molecules are made as flexible chains of atoms. This raises a problem. How does a floppy string-like molecule become a blocky shape that can form the “lock” to interact with its “key”?

This problem wasn’t conclusively resolved until 1961. Anfinsen showed that the sequence of atoms in one of these floppy chains can guide the molecule to adopt a compact, blocky shape spontaneously on its own, by interacting with itself in reproducible ways encoded in the molecular sequence. The understanding that came from this work came to be known as Anfinsen’s Dogma: One sequence makes one structure. This is the blocky model of macromolecules, where floppy chains of atoms fold into a reproducible, rigid, blocky shape. More than 50 years after Anfinsen, the idea persists that molecules fold upon themselves to this single, rigid state.

And yet, it moves

We know a lot more now than we did in 1961. We know that folded molecules keep some fundamental flexibility and still move and jiggle, despite their folded shape. Anfinsen’s Dogma isn’t incompatible with this understanding, it only needs one concession: Folding a molecule into a three-dimensional shape restrains a molecule’s flexibility, but doesn’t remove it.

Over the intervening years, more complicated models for molecular behaviour have emerged that take flexibility into account. These models can sometimes still treat flexibility as the exception rather than the rule, but are a welcome improvement. Biochemists and biophysicists fight over the relative contributions of competing induced-fit and conformational selection models. Despite this bickering, these models are compatible and are starting to be reconciled in a new synthesis of molecular flexibility and action. Key to understanding this phenomenon: jiggliness. From floppy to blocky, this is now the beginning of the jiggly-molecule paradigm.

Several grand challenges in biochemistry depend on a nuanced understanding of molecular flexibility. If we want to start to solve these problems, we need to get better about talking about jiggly molecules. We need to know not just what a molecule’s structure is, but also how that molecule moves. Some specific problems that require an understanding of flexibility include:

  • Prediction of two interacting molecules. Fischer’s lock and key model is conceptually useful, but high-resolution models have shown that it is usually too simplistic. Upon interaction, molecules will change shape as they come together. It’s a rubber key in a JELL-O lock. Because of this, it is still almost impossible to predict the productive interaction of two molecules without accounting for flexibility.
  • Determining the impact of amino acid changes on molecular function. Reductionism often fails when we try to pull apart the action of a single amino acid on a protein’s function. While we can make changes that disrupt interactions, prediction of changes that form new interactions requires understanding dynamic flexibility. We also know that mutations that have no effect on the protein structure can have dramatic effects on dynamics, and hence function.
  • Allosteric effects are still impossible to predict. Changes caused by binding of a compound that alter a molecule’s properties are almost never easily determined by their shape alone. Flexibility, dynamics, and interaction energies are critical to understanding how allosteric transitions take place.
  • The active state of a protein is not well populated in experiments. The state of a protein that carries out its function is almost always not the “rest state” – that is, the most stable state. We find low-energy states in crystallography and other techniques, but the states of proteins that are poorly occupied are frequently the most important states. We usually have to infer the active state from the data we are able to measure. Understanding dynamics and flexibility are necessary to learn and model how molecules reach their active state.

Move past static structures – Embrace the molecular jiggle!

The paradigm of the jiggly molecule is starting to take hold. New technologies like free-electron lasers and improved cryo-electron microscopes are starting to allow us to look at single molecules. This will allow us to directly observe states of molecules and compare them. Single-molecule fluorescence and biophysical studies let us harvest data from single particles, to appreciate the subtleties of their action.

Molecular dynamics simulations get us closer to an ensemble-level understanding of molecular data, and are more powerful every year by Moore’s law to model complicated and flexible systems of molecules. Well-designed experiments can use NMR techniques to their true potential, to probe the flexibility and structure of biomolecules. Although in their infancy, ensemble methods are starting to be used in crystallography and scattering methods. Hybrid methodologies further combine information from many sources to begin to integrate into comprehensive models.

The developments I’m most excited about, however, have come from outside of the scientific world. Developments in animation are bringing the molecular world to life, and animators are merging the science and art of displaying molecules. The jiggliness of molecules becomes completely clear once you observe them in video.

Viewing the movement of a simulated molecule grants an intuitive understanding of the world of a molecule much better than a 1900-word blog post ever could. If a picture is worth a thousand words, an animation is worth a billion. Professional molecular animators are using experimental data to inform their illustrations of molecular behaviour. As we move from publication on printed paper journals to digital publication, these animations will play an ever-larger role in illustrating the behaviour of substances on the molecular level.

An intuitive understanding of jiggly molecules opens up a new level of problems we can approach in biochemistry. No matter what you know about molecules, appreciate the complexity these dynamic, flexible objects show. Appreciate and embrace the jiggle. If things are just right, the molecules might embrace you back.