One of influenza virus’s main weapons is actually a double-edged sword.
The virus‘s ability to rapidly mutate lets it escape from the immune system’s memory and explains why people can be repeatedly re-infected with flu – unlike measles or polio.
But those mutations can also blow the virus’s cover, Howard Hughes Medical Institute Investigator Jesse Bloom and colleagues reported May 8, 2019, in the Journal of Virology.
“We usually think of the flu virus’s ability to mutate and evolve as a bad thing for us,” Bloom says.
It lets the virus jump from one species to another and evade the defenses provided by the flu vaccine. But, he says, “mutating has a downside for the virus, too.”
The work catalogs the different effects mutated and unmutated viruses have on individual human cells.
It’s the first time scientists have taken such a cell-by-cell look and could help explain why people’s reactions to the flu vary so much.
A flu infection begins when flu viruses enter a handful of cells.
The viral proteins get to work replicating their genomes and tricking infected cells into making viral proteins.
New viruses bearing a copy of the invader’s genome quickly package themselves up and find more cells to invade.
Some of those new viruses are exact copies of the original and others contain mistakes.
Billions of viruses will soon infect cells throughout the body – that’s when the aches and pains begin.
But not everyone becomes equally sick.
One of the reasons for this variation, Bloom says, is that some individuals’ immune systems are better at quickly and robustly controlling the infection.
Before immune cells respond, though, infected cells – usually lung cells – have to detect the virus and let nearby cells know.
If the immune system has seen a particular strain before, even in the form of a vaccine, it quickly remembers how to fight it.
If the virus has mutated too much since the last infection, the body will need extra time.
That’s how the virus’s high mutation rate hampers the body’s defenses, Bloom says.
But it doesn’t explain the variation seen in the severity of people’s infections, he says.
Bloom, a virologist at the Fred Hutchinson Cancer Research Center, thought those first few infected cells might hold the answer.
Until now, scientists studying flu had largely studied armies of viruses infecting scads of cells. Bloom’s team wanted to tease apart the effect of single viruses on single cells.
“We’ve known for a long time that flu virus mutations exist,” he says, “but it had never before been possible to see the mutations and their effects in individual cells.”
His team infected human lung cells in a dish with lab-generated influenza viruses with relatively uniform genetic sequences.
Then, they let the viruses infect and replicate within the cells and assessed their responses. To determine whether a given cell had detected its invader, they measured production of interferon, a molecule used to activate anti-viral defenses.
To see how well an invading virus had replicated, they measured levels of viral messenger RNA, the building instructions for viral proteins.
The team also combined several genomic technologies to identify mutations that had cropped up as the virus multiplied within the cells.
Cells’ responses to infection seemed to be related to the genomic quirks of the infecting virus, the team found.
For example, an unmutated virus was more likely to produce lots of viral RNA and less likely to trigger the cellular alarm. Mutated viruses generally had the opposite effect.
“That’s where the virus’s high mutation rate becomes a double-edged sword,” Bloom says. “Some of its mutations inevitably foil its hiding mechanisms.”
If someone is infected by mutated viruses, the immune system might more easily gain the upper hand than in someone infected by unmutated viruses, he says.
“So the initial variation might help determine how an infection proceeds and why the flu affects people so differently,” says Bloom. What’s next is to verify the finding in animals, he says, to see what happens when a full immune system is present.
Minimalist pathogens like RNA viruses survive dynamic host environments by virtue of their extreme adaptability.
This adaptability is driven by a high rate of genetic variation, mediated by error-prone genome replication (Sanjuán et al., 2010).
Most missense mutations have deleterious consequences for protein function, often owing to either thermodynamic (reduced stability of the native state or enhanced stability of unfolded/misfolded states) or kinetic (slow folding or enhanced misfolding/aggregation) effects on folding (DePristo et al., 2005).
In the context of viruses, these phenomena may underpin the observation that the distribution of mutational fitness effects can be largely accounted for by considering protein folding biophysics (Wylie and Shakhnovich, 2011; Chéron et al., 2016; Tokuriki and Tawfik, 2009a).
Indeed, stable proteins tend to be more evolvable, as any given missense mutation is less likely to severely disrupt protein folding or structure (Bloom et al., 2006; Gong et al., 2013).
In cells, protein folding challenges are addressed by proteostasis networks composed of chaperones and quality control factors that work in concert to shepherd nascent proteins to folded, functional conformations (Balch et al., 2008; Hartl et al., 2011; Powers and Balch, 2013).
Important work focused primarily on the Hsp90 chaperone has suggested a critical role for chaperones in modulating the evolution of their endogenous clients, (Cowen and Lindquist, 2005; Queitsch et al., 2002; Lachowiec et al., 2015; Sangster et al., 2007, 2008a, 2008b; Rohner et al., 2013; Whitesell et al., 2014; Geiler-Samerotte et al., 2016; Rutherford and Lindquist, 1998) in part by buffering deleterious effects of non-synonymous mutations.
The consequences of Hsp90 activity for protein evolution may be due to Hsp90 directly engaging an evolving client protein (termed a primary effect).
Alternatively, the effects of Hsp90 may be secondary, mediated indirectly by Hsp90 influencing the folding of other endogenous clients that themselves engage relevant evolving proteins.
For instance, Hsp90-dependent azole resistance in Candida albicans is mediated by secondary effects of Hsp90 on calcineurin, an Hsp90 client that regulates responses to environmental stimuli (Cowen and Lindquist, 2005).
Efforts to look beyond Hsp90 to understand how other components of the metazoan proteostasis machinery modulate evolution (e.g., Hsp40/70 chaperones or protein misfolding stress responses like the heat shock response) have been slowed by the paucity of chemical biology tools to perturb the activities of these systems.
However, Tawfik and coworkers have shown that the GroEL/ES chaperonin system can govern the fitness of certain client protein variants in bacteria (Tokuriki and Tawfik, 2009b), and computational modeling suggests that other chaperones may also have roles in evolution (Bogumil and Dagan, 2012; Cetinbaş and Shakhnovich, 2013).
Chaperones and other proteostasis mechanisms are theoretically well-positioned to address the biophysical challenges created by high mutation rates in viruses.
Intriguingly, most RNA viruses lack autonomous chaperones or other co-factors to assist their proteins with folding.
Instead, viral proteins engage host chaperones, (Melville et al., 1999; Momose et al., 2002; Naito et al., 2007; York et al., 2014; Watanabe et al., 2010) and host chaperone inhibitors have been shown to limit the viability of certain RNA viruses (Geller et al., 2007; Heaton et al., 2016; Taguwa et al., 2015; Chase et al., 2008; Geller et al., 2012). However, the possibility that host chaperones can shape the evolution of viral pathogens has not been investigated.
In summary, it is clear that: (1) high genetic variability is essential to support RNA virus adaptability; (2) missense mutations important for viral adaptation are often biophysically deleterious, constraining the accessible mutational landscape; and (3) many viruses engage host chaperones to fold their proteins.
An important but still untested hypothesis is that host proteostasis modulates RNA virus evolutionary trajectories.
Experimentally testing this hypothesis requires methods to regulate the host cell’s proteostasis network without significantly perturbing cell health or the ability of an RNA virus to propagate.
Here, we achieve this goal in the context of long-term influenza propagation by using small molecules to either modulate the heat shock response in a stress-independent manner (Shoulders et al., 2013; Moore et al., 2016) or to inhibit Hsp90 at sub-lethal concentrations (Ying et al., 2012).
We find that the resulting perturbations to host proteostasis mechanisms significantly impact both the extent and the nature of selection pressure on the influenza genome. We conclude that host proteostasis is a critical, under-appreciated player in influenza evolution, with significant implications for our ability to predict and prevent the evolution of influenza and other RNA viral pathogens.
More information: Alistair B. Russell et al. Single-cell virus sequencing of influenza infections that trigger innate immunity, Journal of Virology(2019). DOI: 10.1128/JVI.00500-19
Journal information: Journal of Virology
Provided by Howard Hughes Medical Institute
