Guest authors C. Brandon Ogbunugafor and Rafael F. Guerrero demystify higher order epistasis through a short story about the perfect brew.

Epistasis is the flavor of the month

Epistasis is one of the most popular and provocative topics in modern genetics.

It has many different definitions, but one especially useful one is that epistasis is the “surprise at the phenotype when mutations are combined, given the constituent mutations’ individual effects (1).” In particular, “higher-order epistasis” is intriguing, because it involves interactions between more than two genes or mutations. This concept challenges the notion that genes or mutations operate in isolation and proposes that complex phenotypes derive from multiway interactions among genetic components.

While higher-order epistasis is a challenging idea to think about, related concepts manifest in everyday life. In an effort to demystify higher-order epistasis, we introduce a primer based on the results of a new study published in GENETICS. In that study, a team of scientists measured the higher-order epistasis operating on a protein associated with antibiotic resistance. We found that the amount of epistasis is profoundly influenced by the presence of mutations in other parts of the genome (2).

Here we have re-cast the data into a fictional short story about factors that interact to affect properties of coffee. In doing so, we explain what higher-order epistasis is and how it works by discussing it in a relatable context.

Louise and Lourdes’s search for the ideal cup of coffee

Louise and Lourdes, two coffee connoisseurs in a remote town, have decided to open their own coffee shop. While a few already exist, many have suggested that the town could use a café that takes the craft of coffee-making more seriously. Most of the existing coffee shops use a mix of random ingredients, and the consensus is that the results are mediocre at best. Convinced that they deserve better, Louise and Lourdes set out to explore how to give their fellow citizens a sublime alternative.

Creating a truly exceptional cup of coffee is no easy feat, however. Coffee brewing is a fascinating topic precisely because it is intricate and complex. Preparing a delicious cup is the product of how many different ingredients interact: the coffee bean blend, the type of grind, the method of brewing, the temperature of the water, the addition of sweeteners, creamers, etc.

The town’s grocer offers a rather limited suite of ingredients and getting supplies to their landlocked town is both time-consuming and expensive. Consequently, they have decided to work within their constraints: they will use ingredients that they can produce themselves and items that are available in the town grocery store.

LL Café: your evidence-based caffeine solution

Before opening “LL Café,” they decide to investigate how their available ingredients contribute to the taste of coffee. That is, more than simply identifying how to make the best cup of coffee, they want to understand how the individual ingredients interact with each other.

Specifically, they want to measure how ingredients contribute to (1) the acidity of coffee and (2) the intensity (strength) of the coffee.

They decide to test these two traits independently, because these are two different aspects of what makes an ideal coffee cup: coffee can vary in acidity (a key component of taste), but also in strength (functionally how “awake” it makes you).

Before doing so, they identify the set of ingredients and objects that they have access to. They find that they have variations of the following:

Coffee beans

Both Louise and Lourdes own small patches of land where they grow crops, and each has tried their hand at growing coffee beans. The town grocery store only offers a single house blend of coffee, a mix of whichever beans are cheapest at the time (which explains the mediocrity and lack of diversity in existing coffee shops). Lourdes and Louise decide to try two single-origin beans: Nigerian (Louise’s; a smooth Coffea robusta varietal) and Colombian (Lourdes’s; a classic C. arabica).

In summary, Louise and Lourdes decide to use three different coffee bean types: (a) House blend, (b) Nigerian beans, and (c) Colombian beans.

Brewing method

While there are many different possible ways to brew a cup of coffee, Louise and Lourdes are sticking with what is familiar to them. Louise tends to use a pour-over instrument. Lourdes owns both a French press and a coffee percolator. Rather than attempt to use a new method, they decide to start their experiment by testing these existing methods.

This means that Louise and Lourdes are using three different brewing methods: (a) Pour-over, (b) French press, and (c) percolator.

Combinations of additives

Coffee connoisseurs differ in opinions on whether coffee additives are appropriate, and which additives work best with which coffee types. The limited options in the town help simplify this problem, as there is only a single type of milk, and a single type of sugar. To spice things up, they’ve decided to also evaluate cinnamon, which some people really enjoy in their coffee. Importantly, the additives in the coffee can co-occur in one cup in various combinations. This is unlike the coffee beans and brewing method: it is challenging to brew a cup of coffee that was produced with both a French press and a percolator, for example. Similarly, they would prefer to not brew a cup of coffee from a mix of their different coffee beans (Nigerian and Colombian), as they want to understand how each coffee varietal tastes on its own.

This means that Louise and Lourdes are testing three different additives—cinnamon, milk, and sugar—in all of their possible combinations. This equates to eight different possible combinations of additives:

Table 1. Combinations of coffee additives

Louise and Lourdes begin to realize that this experiment will not be simple. They have a total of eight different additive combinations that can each be added to three different coffee blends (house, Nigerian, Colombian), each of which can be brewed one of three different ways (pour-over, French press, percolator). This means that 72 total cups of coffee will need to be prepared. And from these 72, they will need to evaluate both the acidity and intensity. As this new coffee shop venture is important to them, they decide that it is definitely worth their time to perform this experiment responsibly (e.g. with replication).

The results

Louise and Lourdes prepare all 72 cups (in replicate) and carefully taste each. They calculate average scores for acidity (Figure 1) and intensity (Figure 2) for each of the combinations of additives (cinnamon, milk, sugar) across the set of possible brewing methods (Pour-over, French press, Percolator) and coffee blends (House, Nigerian, Colombian).

Figure 1. Coffee acidity score for all of the 72 possible coffee cup combinations.

Figure 2. Coffee intensity scores for all of the 72 possible coffee cup combinations.

From Figures 1 and 2, we can summarize some basic observations about whole cups of coffee: maybe surprisingly, the cups containing a combination of cinnamon, milk, and sugar measured with very high acidity scores in both the house and Nigerian coffee blends, when brewed in a percolator. The same cinnamon, milk, and sugar combination was less acidic in the Colombian roast. Even more interestingly, the most acidic mixture in the Colombian roast contained sugar and milk (but no cinnamon).  With regards to intensity, the results are different: the combination of cinnamon and sugar had a high intensity across the coffee blends (the highest in house and Nigerian blends).

These results, however, only tell Louise and Lourdes half of the story: they don’t simply want to know which cups of coffee are the most acidic or intense, but rather, to understand how the different components in their coffee system—coffee blend, coffee brewing method, and additive combination—influence these coffee traits (acidity and intensity). In order to do this, they perform a series of statistical tests that are designed to give more detailed information on how individual combinations of different factors contribute to a given coffee trait. Their aim is a representation that captures how the ingredients are interacting in different combinations.

Finally, Lourdes summarizes the results as treemaps (charts in which the area of boxes drawn represents the relative magnitude of factors in their experiment) for acidity (Figure 3) and intensity (Figure 4). Ingredients and their interactions can have positive or negative effects on these coffee traits, so she included a corresponding + or – sign in each box. Lastly, she colored the boxes in different shades of brown to represent the number of ingredients that are contributing to a given effect. The lighter the color brown of the box, the more ingredients are responsible for that effect on the coffee characteristic.

Figure 3. Coffee acidity: interactions between the different coffee factors.

Figure 4. Coffee Intensity: interactions between the different coffee factors.

From Figure 3 Louise and Lourdes could see that the largest single factor (main effect) influencing coffee acidity is its Nigerian origin. That is, of all single factors in the entire study—coffee blend, brewing method, additive combination—the Nigerian coffee blend has the largest single influence on acidity.

Also note that the effect is negative, that is, Nigerian coffee tends to have low acidity. The effect of the Nigerian blend is followed by the effect of the Colombian blend, which also has a negative effect on coffee acidity. These single factors are, however, not the most intriguing aspect of the acidity treemap. What is fascinating is that, in sum, effects involving combinations of two factors (pairwise effects) are more influential than single factors. No single coffee factor or ingredient is responsible for the acidity – it emerges from the interaction of multiple ingredients.

Figure 4 tells Louise an even more intriguing story as it applies to coffee intensity. Of all the boxes in the plot, 3-way interactions seem to be the most important. For example, adding sugar and milk to Colombian coffee has the largest effect of any individual box. And together, 3-way interactions are the most important in defining coffee intensity.

These results are illuminating. Louise and Lourdes reflect on the results and conclude:

Of any single component, the Nigerian and Colombian blends have the largest influence over the acidity and intensity of the coffee. With no other knowledge, one could estimate that a cup of coffee brewed with Nigerian or Colombian beans will be relatively non-acidic and not-very-intense (on average). Assuming that this is the case would be a huge mistake, however: the data also reveal that in order to better estimate how acidic or intense a cup of coffee will be, Louise and Lourdes must know exactly what additives were included, and how that cup was prepared.

For example: even though the Colombian blend is independently associated with low acidity, the combination of Colombian blend prepared with French press or percolator has a strongly positive effect on acidity! This means that the Colombian blends effect is very context-dependent: yes, it tends to decrease acidity, but only under certain circumstances.

This heightened level of understanding gives Louise and Lourdes confidence heading into their coffee shop opening. They are now equipped to handle a range of situations, to appeal to a range of requests:

• “I really like the house blend, but need it prepared in a manner that makes it the strongest.” (Answer: Brewed in a percolator, with cinnamon and sugar)
• “Which single additive is most likely to make a cup of coffee taste acidic?” (Answer: sugar)
• “I want the Colombian blend, and love cinnamon in my coffee: how can you prepare it such that it isn’t very acidic?” (Answer: Brewed in a pour-over, with cinnamon, sugar, and milk)

These types of questions can only be answered because Louise and Lourdes engaged in this rigorous analysis of interactions. It disentangled the higher-order interactions between coffee factors—coffee blends, brewing methods, and additives.

A few weeks later, Louise and Lourdes open LL Café, home to “the most scientific cup of coffee in the world.”

Back to real world genetics

As we mentioned, the data and figures discussed in the story come directly from an actual data set and analysis of mutations in a bacterial protein (2). We also suggest that, while the story is entirely hypothetical, the essential problem that Louise and Lourdes face is not unlike the current challenges facing modern genetics, and the question of how context frames the phenotypic impact of mutations is one that will continue to manifest in many realms. Our hope is that geneticists and citizen-scientists alike can all share in the mystery and intrigue of epistasis, one of the most important ideas in all of science.

CITATIONS

1) Should evolutionary geneticists worry about higher-order epistasis?

Daniel M Weinreich, YinghongLan, C Scott Wylie, Robert B.Heckendorn

Curr Opin Genet Dev. December 2013 23:700–7; https://doi.org/10.1016/j.gde.2013.10.007

2) Proteostasis Environment Shapes Higher-Order Epistasis Operating on Antibiotic Resistance

About the authors:

C. Brandon Ogbunugafor is in the Department of Ecology and Evolutionary Biology at Brown University. Twitter: @big_data_kane

Rafael F. Guerrero is in the Department of Computer Science at Indiana University. Twitter: @guerruhroh

Improved duplex sequencing identifies spontaneous mutations in bacteria without long-term culturing.

Spontaneous mutations are the driving force of evolution, yet, our ability to detect and study them can be limited to mutations that accumulate clonally. Sequencing technology often cannot identify very rare variants or discriminate between bona fide mutations and errors introduced during sample preparation. In GENETICS, Zhang et al. created an improved sequencing method to study low-abundance spontaneous mutations in the bacterium Escherichia coli.

To develop their method, the authors began with duplex sequencing, in which fragmented DNA molecules are tagged with an adaptor sequence for sequencing. This method is powerful, but at high read depths, it can erroneously call true mutations as PCR duplicates, making it ill-suited for finding rare mutations.

The authors first determined the error rate of the PCR step of duplex sequencing, where most experimental artifacts would be expected to occur. Because duplex sequencing can identify reads that came from the same parental DNA molecules (based on the adaptor sequences), the authors assumed that any such reads that had mismatches must have come from base changes during the PCR. By identifying these discrepancies, they determined the rates of different kinds of errors in the sequencing process.

The authors then sequenced E. coli genomes using a new method, which they termed improved duplex sequencing (IDS). IDS is similar to duplex sequencing, but it uses adaptor sequences of multiple different lengths. The use of more and different adaptor sequences minimizes the chance that two different DNA molecules that happen to break at the same place will be erroneously called as PCR replicates. By employing this method and accounting for the error rate of the PCRs, which they had already determined, the authors were able to confidently identify rare, random mutations in E. coli.

Having identified such mutations, the authors looked for patterns. They found that clusters of mutations occurred in regions of the genome that are known to be replication fork stopping regions. This is suggestive of transcriptional errors, as would be expected for spontaneous mutations. Interestingly, mutations in these hotspots were almost entirely in relatively unimportant regions of the genome—for instance, in the non-functional parts of tRNA genes. These vulnerable areas of the genome hint at mechanisms in E. coli that may protect more critical regions from damage.

CITATION:

Spatial Vulnerabilities of the Escherichia coli Genome to Spontaneous Mutations Revealed with Improved Duplex Sequencing

Xiaolong Zhang, Xuehong Zhang, Xia Zhang, Yuwei Liao, Luyao Song, Qingzheng Zhang, Peiying Li, Jichao Tian, Yanyan Shao, Aisha Mohammed AI-Dherasi, Yulong Li, Ruimei Liu, Tao Chen, Xiaodi Deng, Yu Zhang, Dekang Lv, Jie Zhao, Jun Chen, Zhiguang Li

Genetics October 2018 210: 547-558; https://doi.org/10.1534/genetics.118.301345

https://www.genetics.org/content/210/2/547

A strain of Staphylococcus epidermidis isolated from a hotel room may provide insight into how resistance develops outside of medical settings.

Although intense research and media interest has focused on drug-resistant bacteria in hospital settings, resistance can and does evolve outside the clinic. Methicillin-resistant Staphylococcus epidermidis is often isolated from infections of medical devices, but in a report in G3: Genes|Genomes|Genetics, Xu et al. studied drug resistance in a strain that was isolated from a public setting: a hotel room in London.

Although S. epidermidis isn’t as virulent as its infamous relative S. aureus, it can still cause infection and serve as an important reservoir for resistance genes, which can be transferred to more deadly bacteria. The authors sequenced the genome of their strain and tested its susceptibility to a panel of antibiotics.

After sequencing the new strain’s genome, the authors found that its chromosome and six plasmids contained a number of resistance genes, including the fosfomycin resistance gene fosB, the multidrug resistance gene msrA, and several others. A comparison between the hotel strain and other sequenced S. epidermidis genomes revealed that some of these genes were unique to the new isolate, such as the tetracycline resistance gene tet(K). They also tested the strain’s susceptibility to a panel of thirteen antibiotics and found that it was resistant to eleven of them.

This is the first genomic analysis of an S. epidermidis strain isolated from a general public setting,  and it demonstrates how antibiotic resistance can occur even outside of the specific evolutionary pressures of a sterile healthcare setting. More studies like this may help us to further understand—and combat—the spread of antibiotic-resistance among our ever-present bacterial guests.

CITATION:

Whole Genome Sequence and Comparative Genomics Analysis of Multi-drug Resistant Environmental Staphylococcus epidermidis ST59

Zhen Xu, Raju Misra, Dorota Jamrozy, Gavin K. Paterson, Ronald R. Cutler, Mark A. Holmes, Saheer Gharbia, Hermine V. Mkrtchyan

G3: Genes, Genomes, Genetics July 2018 8: 2225-2230; https://doi.org/10.1534/g3.118.200314

http://www.g3journal.org/content/8/7/2225

Guest post by Nina Wolff pays tribute to long-standing GSA member Margaret Lieb.

Margaret (Peggy) Lieb died on March 8, 2018 in South Pasadena, California at the age of 94. After attending schools in New Rochelle, NY, she graduated magna cum laude from Smith College, and subsequently studied with  H.J. Muller at Indiana University and with Francis Ryan at Columbia University, where she received her PhD degree. Following postdoctoral studies at Caltech in the laboratory of Max Delbruck, and in Paris at the Pasteur and Radium Institutes, Lieb taught at Brandeis University and then moved to the Medical School of the University of Southern California where she continued her research and teaching for 45 years. After her retirement, she continued to be active as an Emerita member of the faculty, and as a garden docent at the Huntington Museum and Botanical Garden.

While at Caltech, Lieb published one of the first studies of phage lambda, and subsequently isolated and characterized a large number of mutations in the repressor gene of the phage. Her studies of lysogenization indicated that the active repressor was a dimer, a conclusion later confirmed by biochemical studies in other laboratories. While mapping mutations in the lambda repressor gene, she observed that excess recombination (negative interference) was associated with mutations arising from the deamination of 5-methylcytosine. This led to the identification of a novel mismatch repair gene (vsr) in E. coli – a gene that is adjacent to the gene for cytosine methylase. The Vsr function reduces the probability of mutations that occur due to spontaneous deamination of 5meC. Although genes related to vsr appear to be limited to bacteria, the search for genes like vsr in eukaryotes, where 5-methycytosine has important regulatory functions, has led others to the discovery of additional specific repair activities in higher organisms.

In 1972-1973, Lieb served as Program Directory of the Genetic Biology program of the National Science Foundation. She was elected Chairman of the Virology Division of the ASM in 1975, and served on the editorial boards of Journal of Virology and GENE. She was a Fellow of the American Association for the Advancement of Science (AAAS).

Peggy Lieb maintained an active interest in the research of her colleagues, and will also be missed by the students and post-doctoral fellows who spent time in her lab. Her high standards of performance in the classroom and in the lab were challenging and also appreciated by those who knew her.

In the ruins of the Chernobyl Nuclear Power Plant—an area deemed unsafe for humans for the next 20,000 years after a catastrophic failure—life thrives. Fungi that reside there, along with other organisms that can survive large radiation doses, must have strategies to cope with the DNA-damaging effects of living at a meltdown site. In the April issue of GENETICS, Repar et al. report that radiation-resistant prokaryotes tend to have higher rates of genome rearrangements—a sign of improperly repaired double-strand breaks in DNA—than related species do, meaning that even these hardy organisms can’t fully prevent or fix radiation-induced DNA damage.

The failure to repair all DNA damage doesn’t result from lack of trying. Prior research showed that Deinococcus radiodurans, one of the most radiation-resistant organisms identified to date, has a special method for repairing double-strand breaks in DNA, and along with several other radiation-resistant prokaryotes, it can patch its genome back together after hundreds of double-strand breaks. Variation in the DNA repair machinery is under positive selection in radiation-resistant bacteria but not in related nonresistant bacteria, indicating that there’s a need to optimize these genes’ functions to cope with radiation.

Despite their adaptations to radiation bombardment, these species’ genomes are more shuffled around than their more radiation-sensitive relatives’ are. This suggests it’s not possible to prevent or patch up all the damage, even with super-charged DNA repair, but it’s also conceivable that the increased rate of genome rearrangements might actually be beneficial in conditions of stress. The rearrangements could cause mutations that allow the radiation-resistant organisms to survive in their dangerous environments. But Repar et al. found that radiation-resistant organisms were no different from their nonresistant cousins in selection for genome organization (i.e., against genome rearrangements), implying that their high rate of rearrangements does not affect their ability to adapt to radiation stress. Ultimately, although these extremophiles are uniquely skilled at fixing their genomes, they still end up with battle scars.

CITATION:

Repar, J.; Supek, F.; Klanjscek, T.; Warnecke, T.; Zahradka, K.; Zahradka, D. Elevated Rate of Genome Rearrangements in Radiation-Resistant Bacteria.
GENETICS, 205(4), 1677-1689.
DOI: 10.1534/genetics.116.196154
http://www.genetics.org/content/205/4/1677

Lurking in colonies of pathogenic bacteria are drug-resistant mutants. If the colony is exposed to antibiotics, these resistant mutants may survive, but they still face the challenge of recolonizing the host. Their success in this task depends on their diversity; a diverse population is more likely to harbor mutants that can withstand a second threat, such as the host’s immune response or another wave of antibiotics. Understanding the factors that contribute to diversity after a population bottleneck can help predict whether bacteria will rebound. Intuitively, it would seem that the more cells that survive, the more diverse the colony will be. Indeed, the number of types of mutants scales with colony population size. But under some conditions, Couce et al. show in the July issue of GENETICS, larger populations may actually be less diverse—and, as a result, more vulnerable to a second blow.

The key is that diversity isn’t defined solely by the number of mutant types: It also depends on how well-represented each type of mutant is in the population. This can be quantified by calculating the probability that two mutants chosen at random from a population will be siblings. Using a mathematical model, the researchers demonstrated that in a resistant subpopulation left standing after an antibiotic-induced bottleneck, diversity is only proportional to population size if the mutant’s growth rate is slower than or equal to the growth rate of the parent clone. If mutants grow faster, they become overrepresented in the population. As the population size increases, the faster-growing mutant clones overtake the rest in number, making the distribution of mutants more and more uneven.

To qualitatively verify their finding, the researchers used simulation and experimentation. Simulations allowed them to take into account factors such as “jackpot” events, in which a population is rich in mutants because of a mutation that appeared near the beginning of the colony’s growth. As would be predicted, “jackpot” events significantly reduced the diversity of resulting populations, but this effect didn’t change the fact that when mutants grow faster than wild-type, diversity is consistently lower.

As an empirical test, the researchers subjected large and small populations of the pathogenic bacteria Pseudomonas aeruginosa to the antibiotic fosfomycin. The researchers selected P. aeruginosa because it’s known that a mutation disabling a single gene is the only way these bacteria can resist fosfomycin, and mutations in this gene do not alter growth rate in the lab. When subjected to sublethal concentrations of fosfomycin, knocking out the resistance gene allows the mutants to grow 2.7 times faster than wild-type bacteria. In agreement with their model, the researchers found without fosfomycin, diversity increased as population size increased, since the mutants grew at the same rate as the wild type. In the presence of sublethal doses of the drug, in contrast, diversity remained low even in very large populations consisting of of several hundred billion individuals.

Since bacteria are routinely subjected to sublethal concentrations of antibiotics, these results may help us better understand how and why bacterial infections rebound as well as the emergence and spread of antibiotic-resistant “super-bugs.” The findings may also aid in the study of antitumor therapy because these treatments involve placing similar stressors on tumor cells. Other researchers have already demonstrated that the genetic diversity of a tumor predicts its response to various treatments, so understanding how and why this occurs could help inform infectious disease and cancer therapies alike.

CITATION:

Couce, A.; Rodríguez-Rojas, A.; Blázquez, J. Determinants of Genetic Diversity of Spontaneous Drug-Resistance in Bacteria.
GENETICS, 203(3), 1369-1380.
DOI: 10.1534/genetics.115.185355
http://www.genetics.org/content/203/3/1369

Antibiotics, a vital tool for fighting infections, were originally products of nature—the first antibiotic was serendipitously discovered in mold contaminating a bacterial culture. As antibiotic resistance becomes an increasingly serious threat, scientists are attempting to wring another type of pathogen-fighting drug from the wild: antimicrobial peptides.

Antimicrobial peptides, or AMPs, are found in almost every type of organism—even bacteria themselves. They’re part of the innate immune system, which helps to ward off many classes of intruders. Although some researchers are attempting to develop AMPs into drugs, not everyone is enthusiastic about the strategy. If a pathogen developed resistance to AMP-derived drugs, it might also become resistant to the host’s natural AMPs. This could have disastrous consequences for the host population. And fears of resistance may not be unfounded: AMP-resistant bacteria have already been bred in the lab.

Until now, the mutations responsible for AMP resistance have barely been studied. In a step toward finding and characterizing them, an article in the June issue of G3 reports a number of candidate genes involved in resistance to multiple classes of AMPs. To find the genes, the researchers treated Staphylococcus aureus with different AMPs at levels that allowed resistant strains to evolve. By comparing the genomes of the resistant strains to the original S. aureus genome, they found several genes that were mutated in the AMP-resistant bacteria. And supporting the notion that these mutations were involved in AMP resistance, the colonies resistant to a given AMP consistently carried mutations affecting the same gene or genes.

While compelling, this doesn’t prove that these mutations are truly responsible for AMP resistance. To determine whether or not the mutations were responsible for resistance, the researchers selected strains from the Nebraska Transposon Mutant Library with mutations that impaired the candidate genes. By treating these strains with AMPs, they found that the mutant strains were indeed altered in their susceptibility to their corresponding AMPs. This means it’s very likely that the genes they found are directly involved in the evolution of AMP resistance. As well as enabling us to predict how pathogens might gain resistance to any AMP-derived therapies, further research on these resistance-associated genes may also help us understand how AMPs function, providing insight into this widely-used component of innate immunity.

CITATION:

Johnston, P.; Dobson, A.; Rolff, J. Genomic Signatures of Experimental Adaptation to Antimicrobial Peptides in Staphylococcus aureus.
G3, 6(6), 1535-1539.
DOI: 10.1534/g3.115.023622
http://www.g3journal.org/content/6/6/1535.long

In the early 1940s, many biologists doubted bacteria had genes. After all, they seemed to play by their own genetic rules: they appeared to lack chromosomes, meiosis, mitosis, sex, and all the other trappings of Mendelian inheritance. They even seemed to show a kind of Lamarckian inheritance, in which an individual could pass on traits acquired during its lifetime.

Then, in 1943, Salvador Luria and Max Delbrück published an article in GENETICS that marked the birth of bacterial genetics, revealing that this apparently Lamarckian inheritance was in fact a case of random mutation. Luria and Delbrück’s work wasn’t just a boon for bacterial genetics. Brought together by biophysics and war, the duo’s brief decade of collaboration also fostered the emergence of molecular biology by developing the viruses that infect bacteria into a streamlined genetic model.

In the February issue of GENETICS, Andrew Murray introduces the 1943 paper as one of the journal’s 100th anniversary Classics.

The roots of Luria and Delbrück’s partnership traced back to a paper published just as war was brewing in Europe in 1935. Luria was in Italy, a newly qualified doctor who was bored with medicine; Delbrück was in Germany, a young physicist who had grown bored with physics. Delbrück had collaborated with some biologists from a discussion group—his “little club”— contributing a quantum mechanical model of the gene to a paper on mutations and gene structure. Luria read the paper a few years later when he was in Rome completing a specialty in radiology and dabbling in physics under soon-to-be-Nobel-Prize-winner Enrico Fermi’s wing. Luria’s imagination was sparked by the paper’s proposal that the abstract concept of a gene, which was then still hazy with mystery, could be investigated as a concrete “collection of atoms.” It seemed, he would later say, “to open the way to the Holy Grail of biophysics.”

Luria wondered how to test the new ideas and stumbled on a possibility. He met a microbiologist on a stalled trolley car who turned out to be measuring bacteria in the Tiber River using bacteriophages—viruses that infect bacteria. Luria became intrigued by the possibilities of probing gene structure using the phage as a stripped-back biological system.

Bacteriophages (white polygonal shapes) attached to a bacterial cell, ready to transfer their genome into the bacterium. By Dr Graham Beards [CC BY-SA 3.0] via Wikimedia Commons.

“I didn’t make much progress in reading these forbidding-looking papers; every genotype was about a mile long, terrible, and I just didn’t get any grasp of it.”

–Max Delbrück, 1978

Then he began talking to Emory Ellis, a postdoc in the department at Caltech who had isolated some bacteriophage from Los Angeles sewage; Delbrück realized that he had found the system he had been searching for:

“I was absolutely overwhelmed that there were such very simple procedures with which you could visualize individual virus particles; […] This seemed to me just beyond my wildest dreams of doing simple experiments on something like atoms in biology.”

–Max Delbrück, 1978

Back in Italy, Luria was encouraged to hear of Delbrück’s phage epiphany and, in 1938, hoped to use a government fellowship to travel to the US to work with the displaced physicist. But just as soon as he was awarded the money, Italian dictator Benito Mussolini announced a series of Nazi-influenced race laws. Luria’s fellowship was unceremoniously withdrawn because he was Jewish. With no funding to work with Delbrück, he sought shelter and grant money at Marie Curie’s Radium Institute in Paris, where he bombarded bacteriophage with radiation to study their molecular make up.

Then, on June 13, 1940, as the German Army advanced on Paris, Luria and his friends were forced to flee the city on bicycles. After making his way nearly 500 miles to Marseilles and the US embassy (via a combination of bike and freight train), Luria took a ship to New York. Once the US, he quickly obtained funding to restart his investigations and at a conference in December, he finally met the one other person in the world who thought phage was the key to understanding the gene: Delbrück. They immediately agreed to join forces.

French refugees, 19 June 1940. After the Nazi invasion, millions of people fled South. Photo: Bundesarchiv, Bild 146-1971-083-01 / Tritschler / CC-BY-SA 3.0 via Wikimedia Commons

Among the first problems the pair tackled was the emergence of resistance in bacteria. When a culture is grown from a single cell and then exposed to phage, the infected cells die. But if left for a few hours or days, virus-resistant cells start growing and the culture revives itself. Many biologists held the view that these survivors were the descendants of cells that had developed resistance to the phage as a result of some direct interaction between the virus and bacteria.

But others saw no reason to believe that bacteria operated under entirely new rules of heredity. Just as for plants and animals, they argued that resistance mutations arise at random, and the virus acts as selective force that enriches the population for pre-existing cells that happen to be resistant.

At first, Luria and Delbrück struggled to come up with experiments to put this disagreement to rest. Luria tried measuring the proportion of virus resistant cells in growing bacterial cultures, but he seemed to get different results every day. Then, he had a chance encounter with a colleague at a slot machine:

“Not a gambler myself, I was teasing him about his inevitable losses, when he suddenly hit a jackpot, about three dollars in dimes, gave me a dirty look, and walked away. Right then I began giving some thought to the actual numerology of slot machines; in so doing it dawned on me that slot machines and bacterial mutations have something to teach each other.”

-Salvador Luria 1984

Luria realized he could distinguish between the acquired resistance and the random mutation hypothesis using statistics. If resistance were caused by exposure to the virus, it should arise only after the virus was added, at a relatively consistent proportion. But if resistance emerged by mutation at random times, then the proportion of resistant cells would be much more variable, depending on how early the mutation arose. Delbrück calculated the statistical distribution they would expect from random mutations and, to their joy, Luria’s experimental data matched it. They had shown that bacteria had genes that mutate at random, providing fodder for natural selection. Their approach also provided a quantitative approach for studying bacterial mutation rates.

The Luria–Delbrück experiment. (A) If resistance is induced by the presence of the phage in the final, assay plate, independent cultures should yield roughly similar numbers of resistant colonies. (B) If resistance mutations arise spontaneously during the cell divisions prior to plating, the number of resistant colonies will depend on how early in the culture the mutation arose. Image: Madprime via Wikimedia commons

The fruit of this community-building was a transformative molecular understanding of heredity within a remarkably short period. Luria and Delbrück’s phage epiphanies turned out to be science jackpots.

CITATIONS

Bertani, G. (1992). Salvador Edward Luria (1912-1991). Genetics, 131(1), 1. http://www.genetics.org/content/131/1/1

Fischer, E. P. (2007). Max Delbrück. Genetics, 177(2), 673-676. http://www.genetics.org/content/177/2/673

Luria, S. E., & Delbrück, M. (1943). Mutations of bacteria from virus sensitivity to virus resistance. Genetics, 28(6), 491. http://www.genetics.org/content/28/6/491

Murray, A. (2016). Salvador Luria and Max Delbrück on Random Mutation and Fluctuation Tests Genetics 202(2) 367-368; DOI:10.1534/genetics.115.186163  http://www.genetics.org/content/202/2/367