Good viruses visiting bad neighborhoods

Marco VignuzziWhat would happen to an RNA virus if its genome were placed in a bad neighborhood? The answer is that fitness plummets.

RNA virus populations are not composed of a single defined nucleic acid sequence, but are dynamic distributions of many nonidentical but related members. In the past I have referred to these populations as quasispecies but that is no longer the preferred term: mutant swarms or heterogeneous virus populations should be used instead.

The term for all possible combinations of a viral genome sequence is sequence space; for a 10,000 nucleotide genome this would be theoretically 410,000 different genomes – a huge number, more than the atoms in the universe. Any RNA virus population occupies only a fraction of this sequence space, in part because many mutations are deleterious. Studies have shown that viral genomes occupy specific parts of sequence space, called neighborhoods, and movement to different neighborhoods is important for viability. If the viral genome is placed in a bad neighborhood – one that is detrimental for virus fitness – the ability to explore sequence space is restricted.

An example of the effect of changing viral sequence space is shown by a study in which hundreds of synonymous mutations (they did not change the amino acid sequence) were introduced in the capsid region of poliovirus (link to paper). Such rewiring, which placed the virus in a different sequence space, reduced viral fitness and attenuated pathogenicity in a mouse model. In other words, the viral genome was placed in a bad neighborhood, from where it could not move to other neighborhoods needed for optimal replication and pathogenesis. While the genome rewiring did not affect the protein sequence, it might have had deleterious effects on RNA structures or codon or dinucleotide frequency. For example, introduction of codon pairs that are under-represented in the human genome can produce less fit viruses.

A recent study avoids these potential issues by introducing changes in the viral genome that do not affect protein coding, RNA structures or codon or dinucleotide frequency, yet place the viral genome in a different sequence space (link to paper). All 117 serine/leucine codons in the capsid region of Coxsackievirus B3 were changed so that a single nucleotide mutation would lead to a stop codon, terminating protein synthesis and virus replication (this virus is called 1-to-Stop). The serine codons were changed to UUA or UUG; one mutation changes these to the terminators UAA, UGA, or UAG. Another virus was made in which two mutations were needed to produce a stop codon (NoStop virus).

1-to-Stop viruses replicated normally, but when mutagenized, they had significantly lower fitness than wild type or NoStop viruses. Extensive passage of the virus in cells, which would be expected to cause accumulation of mutations, had the same effect on fitness. When a high fidelity RNA polymerase was introduced into 1-to-Stop virus, it replicated like wild type virus. Similar results were obtained with an influenza virus when one of its 8 genome segments was rewired to produce 1-to-Stop and NoStop counterparts.

The 1-to-Stop Coxsackieviruses were attenuated in a mouse model of infection. Furthermore, mice infected with 1-to-Stop virus were protected against replication and disease after challenge with wild type virus. These observations suggest that rewiring viral RNA genomes could be used to design vaccines.

These findings show that recoding a viral genome places it an different sequence space than wild type virus, in which single mutations can lead to inactivation of viral replication. This new neighborhood is unfavorable (‘bad’) because the virus cannot readily move to other neighborhoods to accommodate the effects of mutation.

For more discussion of viral sequence space and rewiring viral genomes, listen to the podcast This Week in Evolution #24: our guest is Marco Vignuzzi (pictured), senior author on the second paper discussed here.

A huge host contribution to virus mutation rates

HIV-1 mutation rateThe high mutation rate of RNA viruses enables them to evolve in the face of different selection pressures, such as entering a new host or countering host defenses. It has always been thought that the sources of such mutations are the enzymes that copy viral RNA genomes: they make random errors which they cannot correct. Now it appears that a cell enzyme makes an even greater contribution the mutation rate of an RNA virus.

Deep sequencing was used to determine the mutation rate of HIV-1 in the blood of AIDS patients by searching for premature stop codons in open reading frames of viral RNA. Because stop codons terminate protein synthesis, they do not allow production of infectious viruses. Therefore they can be used to calculate the mutation rate in the absence of selection. The mutation rate calculated in this way, 0.000093 mutations per base per cell, was slightly higher than previously calculated from studies in cell culture.

When HIV-1 infects a cell, the enzyme reverse transcriptase converts its RNA genome to DNA, which then integrates into the host cell genome. Identification of stop codons in integrated viral DNA should provide an even better estimate of the mutation rate of reverse transcriptase, because mutations that block the production of infectious virus have not yet been removed by selection. The mutation rate calculated by this approach was 0.0041 mutations per base per cell, or one mutation every 250 bases. This mutation rate is 44 times higher than the value calculated from viral RNA in patient plasma (illustrated).

Sequencing of integrated viral DNA from many patients revealed that the vast majority of mutations leading to insertion of stop codons – 98% – were the consequence of editing by the cellular enzyme APOBEC3G. This enzyme is a deaminase that changes dC to dU in the first strand of viral DNA synthesized by reverse transcriptase. APOBEC3G constitutes an intrinsic defense against HIV-1 infection, because extensive mutation of the viral DNA reduces viral infectivity. Indeed, most integrated HIV proviruses are not infectious as a consequence of APOBEC3G-induced mutations. That infection proceeds at all is due to incorporation of the viral protein vif in the virus particles. Vif binds APOBEC3G, leading to its degradation in cells.

The mutation rate of integrated HIV-1 DNA calculated by this method is much higher than that of other RNA viruses. This high mutation rate is driven by the cellular enzyme, APOBEC3G. At least half of the mutations observed in plasma viral RNAs are also contributed by this enzyme.

It has always been thought that error-prone viral RNA polymerases are largely responsible for the high mutation rates of RNA viruses. The results of this study add a new driver of viral variation, a cellular enzyme. APOBEC enzymes are known to introduce mutations in the genomes of other viruses, including hepatitis B virus, papillomaviruses, and herpesviruses. Furthermore, the cellular adenosine deaminase enzyme can edit the genomes of RNA viruses such as measles virus, parainfluenza virus, and respiratory syncytial virus. Cellular enzymes may therefore play a much greater role in the generation of viral diversity than previously imagined.

Viral variation in single cells

QuasispeciesIt is well known that virus populations display phenomenal diversity. Virus populations are dynamic distributions of nonidentical but related members called a quasispecies. This diversity is restricted in single cells, but is restored within two infectious cycles.

Single cells infected with vesicular stomatitis virus (VSV) were isolated using a glass microcapillary, and incubated overnight to allow completion of virus replication. Replication in a single cell imposes a genetic bottleneck, as few viral genomes are present. Virus-containing culture fluids were then subjected to plaque assay, during which 2 viral replication cycles took place. For each infected cell, 7-10 plaques were picked and used for massive parallel genome sequencing. A total of 881 plaques from 90 individual cells were analyzed in this way. Of the 532 single nucleotide differences  identified, 36 were also present in the parental virus stock.

An interesting observation was that over half of the infected cells contained multiple parental variants. However, the multiplicity of infection (MOI) that was used should have only resulted in multiple infections in 15% of the cells. The results cannot be explained by RNA recombination as this process occurs at a very low rate in VSV-infected cells. The key is that MOI only describes the infectious virus particles that are delivered to cells.  Because the particle-to-pfu ratio of VSV is high, it seems likely that many cells received both infectious and non-infectious particles. Furthermore, it is known that some RNA viruses may be transmitted to other cells in groups, either by aggregation of particles or within a membrane vesicle.

The conclusion from these results is very important: a single plaque-forming unit can contain multiple, genetically diverse particles.  Plaque purification has been used for years in virology to produce clonal virus stocks, but at least for VSV, a plaque is not produced by a single viral genome.

The 496 single nucleotide changes that were not present in the parent virus arose after the bottleneck imposed by single cell replication. Between 0 and 17 changes were identified in the 7-10 plaques isolated from each cell. The single-cell bottleneck restricted the parental virus diversity to 36 nucleotide changes. In contrast, within 2 viral generations, the viral diversity was over ten times greater (496 changes). This observation illustrates the capacity of the RNA virus genome to restore diversity after a bottleneck.

The number of changes identified in the 7-10 plaques isolated from each cell, between 0 and 17, shows that some cells produce more diverse progeny than others. At least two sources of this variation were identified. The viral yield per cell varied greatly, from 0 to over 3000 PFU. Greater virus yields means more viral RNA replication, and more change for diversity. Indeed, greater virus yields per cell was associated with more mutations in the progeny.

Another explanation for the variation in single-cell diversity comes from analysis of cell #36. This infected cell produced viruses with 17 changes not found in the parental virus, more than any other cell. One of these changes lead to a single amino acid change in the viral RNA polymerase. This amino acid change appears to increase the mutation rate of the enzyme. Similar mutators – changes that increase the error frequency – have also been described in the poliovirus RNA polymerase.

RNA viruses must carry out error-prone replication to adapt to new environments. A consequence is that RNA virus populations exist close to an error threshold beyond which infectivity is lost. How the balance is maintained is not understood. The results of this study suggest that some infected cells may produce a highly diverse population, while in others a more conserved sequence is maintained. This distribution of diversity might permit the necessary evolvability without the lethality conferred by having too many mutations.

I would be very interested to know if the conclusions of this work would be changed by the ability to determine the sequences of all the viral genomes recovered from a single infected cell. The authors note that this is not technically possible, but surely will be in the future.

TWiV 360: From Southeastern Michigan

On episode #360 of the science show This Week in Virology, Vincent visits the University of Michigan where he and Kathy speak with Michael, Adam, and Akira about polyomaviruses, virus evolution, and virus assembly, on the occasion of naming the department of Microbiology & Immunology a Milestones in Microbiology site.

You can find TWiV #360 at Or you can watch the video below.

Describing a viral quasispecies

QuasispeciesVirus populations do not consist of a single member with a defined nucleic acid sequence, but are dynamic distributions of nonidentical but related members called a quasispecies (illustrated at left). While next-generation sequencing methods have the capability of describing a quasispecies, the errors associated with this technology have limited progress in our understanding of the genetic structure of virus populations. A new method called CirSeq reduces next-generation sequencing errors to allow an accurate description of viral quasispecies.

The key to eliminating sequencing errors is a clever approach based on the conversion of viral RNAs to circular molecules. When copied with reverse transcriptase, tandemly repeated cDNAs are produced (illustrated below). Mutations in the original viral RNA will be shared by all repeats derived from a circle, but not errors produced during copying or sequencing. The latter can be computationally subtracted, reducing sequencing error to a point that is much lower than the estimated mutation rate of an RNA virus.CirSeq

CirSeq was used to characterize poliovirus populations produced by seven serial passages in HeLa cells. The calculated mutation frequency, 2 X 10-4 mutations per nucleotide, was substantially lower compared with estimates determined by conventional sequence analysis. Over 200,000 sequence reads per nucleotide position were used to detect >16,500 variants per population per passage. This number represents ~74% of all possible alleles. Many mutations were detected at nearly all positions in the viral RNA. Most mutations occur at a frequency between 1 in 1000 to 1 in 100,000. The conclusion is that the virus population produced in HeLa cells consists mainly of genomes with the consensus sequence, and small amounts of many variant genomes. These variants are only those that give rise to viable viruses; lethal mutations are not observed.

CirSeq was also used to calculate the mutation rate of poliovirus. The rates vary according to type: transitions occurred at a rate of 2.5 X 10-5 to 2.6 X 10-4 substitutions per site, while transversions were observed at a rate of 1.2 X 10-6 to 1.5 X 10-5 substitutions per site. Nucleotide-specific differences in mutation rate were also observed: C to U and G to A transitions were 10 times more frequent than U to C and A to G. These rates are consistent with previously determined values using other methods.

This method can also be used to determine the fitness of each base at every position in the genome, according to changes observed during the seven passages in HeLa cells. This analysis allows determination of which bases are neutral, and which are selected, and when combined with analysis of protein structure, can provide new insights into viral functions.

By enabling a sequencing approach that gives an accurate description of virus populations at a single-nucleotide level, CirSeq can be used to provide an unprecedented view of how virus populations change during evolution.

John Holland, 83

John Holland

John Holland, 1995

Virologist John Holland passed away on 11 October 2013. I asked former members of his laboratory for their thoughts on his career and what he meant to them.

Bert Semler

For more than 35 years, John Holland was a major figure and leading contributor in the study of RNA viruses.  His early pioneering work on poliovirus was the first demonstration that the block to poliovirus growth in non-primate cells was due to the absence of specific receptors on non-susceptible cells.  This critical discovery has been a guiding beacon for many subsequent studies on virus-cell interactions.  Holland was also a central figure in applying molecular biology approaches to the study of viruses.  His work on picornavirus protein processing and replication was innovative and characterized by a “simple but elegant” experimental approach.

For the last 20 – 25 years of his scientific career, Holland focused his studies on vesicular stomatitis virus (an RNA-containing rhabdovirus) as a model system for viral persistence and for the study of evolution of viral genomic RNAs.  His work on persistent infections lead to important discoveries about genome interactions between infecting viruses and the defective-interfering particles that they generate.  Some very far-reaching conclusions about the nature of virus-virus and virus-cell interactions during viral infections have emerged from Holland’s research efforts.  Perhaps his most influential findings resulted from experiments devoted to quantitation of the rates of mutation during the replication of viral genomic RNAs.  These studies, many of which were carried out with his long-term collaborator Esteban Domingo, led to the now widely-accepted concept of virus quasispecies. Indeed, using novel, quantitative experimental approaches, Holland and his co-workers greatly advanced our understanding of the molecular mechanisms that have generated genetic diversity among RNA viruses and, ultimately, among living organisms in general.

As one indication of Holland’s significant contributions to our basic understanding of viruses, one need only look at the more than 150 original research papers and review articles that he published. The publications are in the most respected and prestigious scientific journals.  Moreover, a number of these papers provided seminal biological tenets and have gone on to become classics in the field of molecular virology.  Holland also trained a significant number of Ph.D. students, postdoctoral fellows, and undergraduate researchers who now have academic positions in major universities and research institutions in the United States and Europe or positions in big pharma and biotechnology. Many of these individuals still carry out research in virology.

David Clarke

I spent six and a half years in John’s lab from 1987 to 1993. This period was a truly wonderful time in my life, in large part due to how John ran his lab and interacted with me and other lab members. John promoted a great sense of scientific freedom and actively encouraged creative thought.  He also was tremendously supportive when the pathway forward was fraught with difficulties and challenges and I found his immense knowledge and insights to be very helpful in rapidly determining how to proceed. John was a supremely competent and confident scientist and yet he maintained a great sense of humility about his own highly significant contributions, in part I believe due to his interest and global understanding of the many other branches of science, which extended to quantum mechanics and “string theory”. On a personal and worldly level John was also tremendously supportive and understanding; his advice in these areas nearly always hit the mark. When I first arrived at UCSD John accompanied me while I was arranging to rent an apartment and buy a car. As a newcomer to the USA it was a great comfort to have the presence of this physically imposing, experienced and knowledgeable guy at my side while I made the deals. My admiration and respect for John continued to grow during my tenure at UCSD; I saw eye-to-eye with John in nearly all things. When I left the Lab I stayed in regular contact with John by E-mail and visited John and his wife Dottie from time to time when they moved to Taos, NM and then Mesquite, NV. John was a very special and influential person in my life.  I feel hugely privileged to have known him as a mentor and a friend.

Esteban Domingo

From my sabbatical stays with him, I remember a few anecdotes and I include also some thoughts.

A visitor comes into John’s lab at UCSD and sees a guy with dirty hands trying to fix an oil pump on the floor. Do you know where can I find Professor Holland? I am Professor Holland. What can I do for you?

When I was on sabbatical with him, I prepared a manuscript for J. Virol. on work done in Madrid. John liked it, reviewed it prior to submission and corrected a few English mistakes. I sent the manuscript and one of the referees comments stated:  “English must be improved”. John’s comment: “You see Esteban, this is how things work. This incompetent reviewer added this comment because he / she knows you are Spanish”.

Most remarkably, John worked on his bench until retirement. He would supply cells to all of us (students, postdocts, visiting professors) for us to do the experiments. He maintained continuous conversation with us on scientific issues (from the lab or elsewhere) while working on the bench. These conversations were a great inspiration but he would allow absolute freedom to do the experiments each of us wanted to do. He was an example of honesty, authenticity and vision to anticipate towards where virology was heading to. It is said that he was offered by Joshua Lederberg to head a new institute on emerging infections, but he declined in order to remain active in the lab (if true, this would be very much in line with John’s personality, but I have no confirmation of such offer; he never told me anything about it).

He was very critical of population geneticists who objected to quasispecies. He would often say things such as: “You see Esteban, these guys treat viruses as if they were frogs. Just ignore them. Data are data”.

His review published in Science in 1982 (vol. 215, pages 1577- 1585) was a great inspiration to me and the beginning of a permanent contact until he passed away. One of his students (I believe David Steinhauer) told me that the Q beta work that allowed a calculation of a mutation rate in Charles Weissmann’s laboratory  (in which I participated) made John understand what was going on in the dynamics of DI [defective-interfering particle] generation and competition with standard VSV, and this is the reason why he honestly recognized the Q beta work so enthusiastically in the Science review.

Cristina Giachetti

When Bert sent the message a few weeks ago telling us that he had passed away I couldn’t stop thinking about him and my days in his lab at UCSD. He had a big influence on all of us that passed through his lab.

I came to his lab in May 1985, to do post-doctoral training after completing my Ph.D. at the University of Buenos Aires where I worked with Foot and Mouth Disease Virus. For all of us virologists in the late 70’s-early ‘80s, John Holland was a big name in the field, and to receive his letter welcoming me to pursue a post-doctoral fellowship in his lab was very exciting to me. But I did not know how different he (and his lab) was from what I imagined: He and everything in his lab was so relaxed and informal!

If I have to describe John, I would say that in addition to be very intelligent and creative, he was modest and extremely generous of his time and his lab resources. He strongly believed in being independent and a free thinker: he would not tell you what to do. I remember that when I arrived he said, “Here is the lab, take any open bench, talk to the people and think about what you would like to do and we could talk in a few weeks”. He always implied that you were able to do great work; he expressed confidence, and respect for the work we did and always listened with a very open mind. I believe that the sense of support that we experienced allowed us to grow. He was an excellent model for the ideal scientist.

Isabel Novella

It is no secret what an amazing a scientist John was, his scientific legacy is there for everybody to see. He was the smartest person I ever met, and knowledgeable to the point of ridiculous. We had a sort of running joke trying to come up with a question about anything, from history to quantum physics, that he did not have an answer for. Didn’t find it.

He was an even better person. Many of us think of John as a mix of mentor, friend and father (I’m stealing David Clark’s words). My most vivid memories are usually related to John worrying about the possibility of somebody being unhappy, or finding excuses for somebody’s human weaknesses.

There was a janitor, D., who would tell everybody the story of his ongoing divorce and how his wife wanted to take his two kids away from him. One day he disappeared, which was normal due to high turnout for his job. Months later John comes to the lab and says “Have you heard about D.? He is in jail. The police came to his home and it was full of computers and other stuff stolen from the University. The divorce drove him crazy!”

According to John, the devil himself is a really nice guy.

The worst of my time with him, hands down, was when I had to leave. However, on the positive side, that gave me a good enough excuse to finally give him a hug (he was very shy). He was, is, and will always be my hero. He made me a better person and is helping me even after his death. Not because I believe in any beyond, but because of his lessons in humanity.

Kathy Spindler

John was a terrific scientist and mentor. He taught us by example: he worked in the lab every day with joy, focus, and a sense of purpose. We had our scientific discussions with him at his lab bench or ours – not in his office. John also set an example of balancing science and other things in life; his outside pursuits included oil painting, gliding, hiking, and baking delicious French bread. For me his mentorship has been very important in the last couple years when I have been a professor with more administrative responsibilities – he was always willing to provide wise advice. John and I had an active email correspondence, and the week before he passed away we corresponded about some recent defective interfering particle research. Likewise he corresponded with many former Holland lab members, making each of us feel like we had a special bond with him and with each other.

David Steinhauer

I’m not sure who taped it up there, but during my time in John Holland’s lab there was a rather inconspicuous elementary school-like drawing of a palm tree with the caption “Fantasy Island” that hung as a permanent fixture above the sink at the center of the lab. In thinking back, it seems like an appropriate symbol for my memories of a special time of exciting science and great collegiality in John’s lab.

When I approached John in my first year of graduate school to ask if I could do my final rotation in his lab, he agreed, and pointed to the collection of lab reprints that were stacked in files on one of the office walls; “Grab five or six papers from there, go home, or go to the beach or something, and come back in a week and tell me what you want to do”. This was different from my previous rotations, and a week later I came back with a few rough ideas in my head, but no definitive project outlined. I was a bit apprehensive, but I had thoroughly digested the recent lab publications, and had a pretty good idea of the general themes and directions of the group. After a few minutes of discussion alongside John’s bench (not in his office), we informally outlined a set of experiments and goals that probably didn’t deviate much from what he would have “given” me as a rotation project right from the start – if John was a “normal” PI. The beauty of the process was that he made me think that I had come up with the idea for this project on my own! This encapsulates the secret to John Holland’s style of mentorship; it was a fluid blend of independent thought on our part, and guidance on his part that was sometimes firm, but more often so subtle that it bordered on the undetectable. During my graduate career John never had a single formal lab meeting, and he never micromanaged. In fact, by today’s admin-infested, documentation-oriented standards, John didn’t manage us at all. However, he fostered an environment of personal responsibility, collegiality, and support, that would have made formal lab meetings redundant. Maybe it worked because John was in the lab every day, but we all knew the ins-and-outs of other projects, and when anyone obtained a new result or developed a gel, we would congregate around the lightbox and offer feedback and suggestions on the spot. Soon after joining the lab, I learned that there should never be any embarrassment or shame in an “unexpected result” or “ugly gel”, because we all got them from time-to-time and you couldn’t get away with trying to hide it! Though such results usually led to a standard series of bad jokes and gentle ribbing, this was inevitably followed by the kind of support and constructive commentary that would have distinguished any formal lab meeting. Though unconventional, those of us fortunate enough to have been a part of John’s group know that the supportive environment, and the freedom to design experiments and pursue projects, allowed us to grow as independent thinkers and scientists, and offered the best training we could hope for.

The test of time reveals that everyone I overlapped with in John’s lab actually had career ambitions as a scientist, and we all now hold respectable jobs in academia and industry. However, at the time this was probably less apparent, and the lab often resembled a clubhouse for overgrown kids, with a generous degree of joking around, and people vacating periodically during the day for softball games and other outdoor pursuits in the inviting San Diego climate. True to his nature, John left us to our own devices; somehow having faith that we were also self-motivated, determined scientists who would let the experiments dictate our schedules, and in fact the lab routinely became a beehive of activity well into the evening and was always well populated over the weekends. Late afternoons were the highlight of each day as John was always in the lab, either passaging his viruses in the glass milk bottles that we used for cell culture, or synthesizing oligos for sequencing studies. Though he was inherently shy, John was always in his element during this time, when he was one of the gang participating in the banter that drifted aimlessly from science, to subjects such as politics and sports, and back again – jokes and cackles of laughter punctuating the proceedings all the way. However, in retrospect, my favorite time for interacting with John came during relatively quiet times on Saturday and Sunday mornings, when he would come in to the lab to passage his lines, and sometimes it was just the two of us. It was then that John would often discuss his experiences in science and in life, informally and interspersed with stories and anecdotes. These occasions constituted the best mentoring experiences I ever received, and bonded a friendship that lasted until his passing. The amazing thing is that John somehow seems to have created this kind of personal time for each of us that were privileged enough to have worked with him, and we have all led richer, more meaningful lives because of it.

Milton Taylor

I was sorry to hear of John Holland’s death.  John meant a lot to me. I was one of the first post-doc’s in his lab after he moved to Irvine, California. He was a very good mentor , and taught me the intricacies of cell culture  and virology, since I arrived in his lab with no previous experience of cell culture. It was a fun time in the lab, we were exploring the differences in tRNA profiles in cancers and normal cells, and working on mengovirus restriction, projects I continued with later in my own laboratory.  John created a very lively, questioning atmosphere.  He basically posed a problem or question and then said “go to it”.  He was a very modest person, but yet was willing to buck authority, particularly university administration. He and Dottie made us very welcome, and I felt really a part of this new institution (Irvine had only been open a year). There were always very lively discussions, not only of science but of the world at large.  This was a small group, and we really worked as a team, Clayton Buck, Morrie Granger, and one or two students.  John could be very hot tempered at times, but when his temper subsided there was no grudge.  We had quite a number of  undergraduate students around the lab, and I remember our conversations about avoiding the coffee when they were around, since this was the height of the LSD epidemic  that was occurring in Southern Orange County (Laguna beach in the 1960’s ). I was attracted to John’s lab because of his previous work with poliovirus. Amazing to think of how we worked in those days, using glass pipettes, mouth pipetting solutions including virus, glass prescription bottles instead of expensive plastic flasks, and most work done in the open bench. These were simpler bygone days.

Scott Vande Pol

John’s passing touched me, and has prompted some thoughts I am happy to share with you.  HIs output as a scientist was pretty impressive (defining viral receptors, viral protein translation,  the mechanism of viral persistence, the nature of RNA virus populations and evolution), but I think his life as a scientific mentor was certainly as great.   As I noted to Bert, by modern theories of proper scientific mentorship (weekly documented meetings with progress reports and specific aims achieved on schedule) John was a terrible mentor because he did none of those things.  But what a great mentor he was!  He treated his students as his colleagues and equals.  This man, who was smarter than me, more experienced, and more knowledgable, wanted to know MY opinion, because he was genuinely interested in what I thought.  And then we would talk.  This created a space into which we all had to grow, and it was a completely natural outcome of his humility.  Our formal lab meetings were nonexistent, but in some ways continuous, because he was almost always in the lab.  That does not mean it was all sweetness, because John had real scientific standards and would let you know when you did not meet them (but without crushing your spirit).   I remember when Mark Spector from Racker’s lab came to give a seminar at UCSD, and as we were walking back I asked John what he thought about the seminar and he replied that the seminar was entirely untrue (actually, stronger words to that effect).  He did not spare fools, and, he had a real temper that on rare occasions could be pretty ghastly.  You did not want to be on the receiving end of that.  But mostly he laughed a lot, and his lab was a place where games, tricks, and joy prevailed.  I remember that a sure-fire trick was to put a message on the blackboard that some super-prominent scientist has called him leaving a return number, which was actually “dial-a-prayer” in Seattle or New York.  John would always fall for this, but then laugh and laugh and laugh every time.  It was a happy place.

In John’s lab we did not work for John, we worked for ourselves with John.  When I came to the lab, he said:  “You can do anything you want for your thesis as long as it involves RNA viruses.”  That was it.  It was up to me to decide what I wanted to do, even for a rotation project.  So a student’s project in John’s lab belonged entirely to the student and John never told me what to do.  Some students wallowed, hell, I wallowed months away too.  But it developed in his students the ability to make things happen, because John was not going to do it for you.  Really, a BIT of structure might have helped, but that was not John’s way.   If you wanted advice about a specific idea, he was always there to give it, but your fate was entirely in your own hands.  In retrospect, it seems  to have worked well, although in today’s pressured environment few mentors seem to take that approach.

Without trying overtly, John attracted students who opened themselves to him, and part of him then seeped in. We cannot help being inspired by this man because we were changed by him.  I bet you are going to hear comments such as these a lot.

Scott Weaver

John was the consummate academic scientist, and being a student or postdoc in his lab was a unique experience. Even in the midst of teaching major introductory biology classes at UCSD, he worked in the lab every day and was always available for informal discussions at his bench or at the chalk board. During the later stages of his career, John maintained a small-to-medium sized research group so that he could continue to interact personally with his mentees every day. He also was also devoted to providing undergraduates with the opportunity to experience a basic research environment. In the era of disposable plasticware and reagent kits, he continued to use glass pipettes and cell culture bottles so that students could be employed in his lab and get a taste of research. The best ones progressed to experimental work and many of his most talented undergraduates went on to graduate, medical or veterinary school. Unlike many senior faculty, John always found time to meet with undergraduates to explain difficult concepts from biology classes or to provide career advice. Throughout his career, he influenced hundreds of students through his caring teaching and mentoring.

Photo credit: Kathy Spindler

Virology lecture #22: Evolution

Download: .wmv (393 MB) | .mp4 (102 MB)

Visit the virology W3310 home page for a complete list of course resources.

Why don’t DNA based organisms discard error repair?

quasispecies1The recent series of posts on polymerase error rates and viral evolution has elicited many excellent and thought provoking comments from readers of virology blog. Here is one that I had not thought of before, and which I’ll use on an exam in my virology course:

Here’s a tough question. In the follow up blog to this, you say that the high mutation rates of RNA viruses is beneficial to survival in a complex environment. If this is true, why don’t DNA viruses evolve high mutation rates also? It would be simple for them to delete their proofreading domain.

There is no answer to this question, so I’ll speculate. I believe that DNA viruses have error correction mechanisms so that they can have very long genomes. RNA viral genomes are no longer than 27-31 kb. This limit is probably imposed by their high error rate: if RNA genomes were longer, they would likely sustain too many lethal mutations to survive. Error correction mechanisms allow for DNA viral genomes up to 1.2 million bases in length. Smaller DNA viruses don’t have their own DNA polymerases – they use those of the cell. Cellular DNA polymerases have error repair to avoid mutations that lead to diseases such as cancer. Both forms of reproduction are evolutionarily sustainable: shorter RNAs with lots of errors; longer DNAs with fewer errors.

The reader who posed the original question then came back with this retort:

If reduced fidelity is beneficial to RNA viruses, because of the complex environment they are in, why don’t DNA viruses do the same thing?

I think the same endpoint, in terms of surviving in complex environments, is achieved by both strategies. RNA viruses have high diversity; DNA genomes have many more gene products which allow them to survive in diverse situations. Both strategies appear to be evolutionarily sustainable.

It’s important to keep in mind that the goal of viral evolution is survival. Evolution does not move a viral genome from “simple” to “complex”, or along a trajectory aimed at “perfection”. Change is effected by elimination of the ill adapted of the moment, not on the prospect of building something better for the future.

While researching this subject I came across a series of papers on DNA synthesis by African swine fever virus, a virus with a DNA genome of 168-189 kb. The viral genome encodes a complete DNA replication apparatus, including DNA polymerase and DNA repair enzymes. Incredibly, the DNA repair pathway itself is error-prone, which is believed to contribute to the genetic variability of the virus. There is some controversy concerning the error rate for this virus, so we don’t know the consequence of this observation for fidelity of DNA replication. Nevertheless, these observations suggest that evolution has seen fit to tinker with, and perhaps increase, the error rates of certain DNA based organisms.

Lamarche, B., Kumar, S., & Tsai, M. (2006). ASFV DNA Polymerase X Is Extremely Error-Prone under Diverse Assay Conditions and within Multiple DNA Sequence Contexts. Biochemistry, 45 (49), 14826-14833 DOI: 10.1021/bi0613325

Increased fidelity reduces viral fitness

pvrtgWe have spent over a week discussing the effects of polymerase error rates on viruses. RNA viruses have the highest error rates in nature, a property that is believed to benefit the viral population. For example, selective pressure from the immune system or antiviral drugs may lead to changes that are beneficial for the population. In fact, it has been hypothesized that high error rates are required for survival of RNA viruses in complex environments. The isolation of a poliovirus mutant with an RNA polymerase that makes fewer errors during replication made it possible to test this hypothesis.

Infection of an animal host poses perhaps the greatest challenges to viral propagation. Transmission, entry, host defenses, tissue diversity and anatomical restrictions all are serious obstacles to the ability of a virus to replicate, disseminate, and successfully spread to other hosts. Therefore the effect of viral diversity is most stringently tested in infection of an animal.

In these experiments, mice were inoculated with the poliovirus mutant containing the G64S amino acid change in the viral RNA polymerase that causes enhanced fidelity. Infection of mice with poliovirus typically leads to symptoms of poliomyelitis that are similar to those in humans. Compared with the wild-type parental virus, the G64S mutant was less pathogenic: it caused significantly less paralysis and lethality. This effect could be a consequence of restricting the viral quasispecies, or a replication defect in mice caused by the G64S mutation. To distinguish between these possibilities, the G64S mutant was propagated in cells in the presence of a mutagen, a procedure which expanded the number of viral mutants. This treatment – basically expanding the quasispecies – lead to a significant increase in lethality of the G64S virus, to nearly the same extent as wild type virus.

Why would a less complex quasispecies lead to reduced pathogenicity? Viral growth and spread in an animal likely requires a diverse viral population, comprising many mutants, which can replicate efficiently in the many different cell types in an animal. Support for this idea comes from a competition experiment in which the poliovirus G64S mutant was mixed with wild type virus and inoculated into the leg muscle of a mouse. Several days later the mice were sacrificed and the virus that had reached the brain was characterized.  The results showed that both wild type and the G64S virus could replicate in muscle, but the mutant virus spread to the brain less frequently.

These results show that mutations do benefit viral populations, especially in complex environments such as an animal. The ability to produce a quasispecies may allow virus populations to respond to the different environments encountered during spread between hosts, within organs and tissues, and in response to the pressure of the host immune response.

We’ll shortly return to influenza virus replication, but I hope you have been able to follow what to many must be a somewhat arcane discussion. From the silence I suspect that I might have lost some of you – it might help to go back over some of the posts. I’ll try to put up an index of some sort to make it easier to find articles. The blog format isn’t great when it comes to finding older material – once posts scroll off the bottom of the page, they don’t receive further notice.

Pfeiffer, J., & Kirkegaard, K. (2005). Increased fidelity reduces poliovirus fitness and virulence under selective pressure in mice PLoS Pathogens, 1 (2) DOI: 10.1371/journal.ppat.0010011

Vignuzzi, M., Stone, J., Arnold, J., Cameron, C., & Andino, R. (2005). Quasispecies diversity determines pathogenesis through cooperative interactions in a viral population Nature, 439 (7074), 344-348 DOI: 10.1038/nature04388

Pushing viruses over the error threshold

The capacity of RNA viruses to produce prodigious numbers of mutations is a powerful advantage. But remember that selection and survival must balance genetic fidelity and mutation rate. Many mutations are not compatible with viral replication. Consequently, if mutation rates are high, at some point accumulating base changes lead to lethal mutagenesis – the population is driven to extinction. The error threshold is a mathematical measurement of the genetic information that must be maintained to ensure survival of the population. The results of experiments clearly show that RNA viruses evolve close to their error threshold.

The first clues that viruses exist on the edge came from studies in which cells infected with the RNA viruses poliovirus and vesicular stomatitis virus were treated with base analogs that act as mutagens. These compounds, such as 5-azacytidine, are incorporated into the growing RNA chain during replication, leading to incorporation of incorrect bases. Treatment of virus infected cells with such drugs dramatically inhibits the production of new infectious virus particles, but stimulates mutagenesis of the viral RNA by only 2- or 3-fold. When the same experiment is done with cells infected with a DNA virus, the mutation frequency increases by several orders of magnitude.

A direct demonstration of error catastrophe was achieved by treating poliovirus-infected cells with the mutagen ribavirin. Treatment with a concentration of ribavirin that causes a 9.7-fold increase in mutagenesis lead to a 99.3% loss in poliovirus infectivity. A graph of the results shows that poliovirus exists at the edge of viability.


The line on the graph shows the infectivity of poliovirus RNA as a percentage of untreated viral RNA. The introduction of 2 mutations per genome reduces infectivity to about 30% of wild type RNA, while infectivity is nearly eliminated with 7 mutations per genome.

Ribavirin pushes poliovirus beyond the error threshold because it causes the RNA polymerase to make more errors than it already does. What would be the property of a poliovirus mutant resistant to this drug? A poliovirus mutant resistant to ribavirin was selected by passing the virus in the presence of increasing concentrations of the drug. Resistance to ribavirin is caused by a single amino acid change, G64S, in the viral RNA-dependent RNA polymerase. RNA synthesis of ribavirin-resistant poliovirus is characterized by fewer errors, in the absence of drug, compared with the parental virus. Therefore the mechanism of resistance to the mutagen ribavirin is achieved through an amino acid changes that makes a viral RNA polymerase with greater fidelity.

Now that we have an RNA polymerase that makes fewer errors, we can use it to limit viral diversity and test the theory that viral populations, not individual mutants, are the target of selection.

Crotty, S. (2001). RNA virus error catastrophe: Direct molecular test by using ribavirin Proceedings of the National Academy of Sciences, 98 (12), 6895-6900 DOI: 10.1073/pnas.111085598

Pfeiffer, J. (2003). A single mutation in poliovirus RNA-dependent RNA polymerase confers resistance to mutagenic nucleotide analogs via increased fidelity Proceedings of the National Academy of Sciences, 100 (12), 7289-7294 DOI: 10.1073/pnas.1232294100