MicrobiologyBytes

The most amazing thing about the “common cold”, or at least, the proportion of this spectrum of diseases which is caused by rhinoviruses (as opposed to adenoviruses, coronaviruses, or something else), is how little we still know about it. A few years ago I was involved in a proposal for a large project which would look at some of the issues adressed by a new research paper which has just appeared.  That proposal eventually collapsed under its own weight, so it’s fascinating to read these new results and see what we might have found.

The new study describes a phylogenetic analysis to compare the relative distribution of HRV species or serotypes according to the respiratory site (upper respiratory tract (URT) versus lower respiratory tract (LRT) ) and in protracted infection in hospital patients and immunosuppressed lung transplant recipients. In one case, rhinovirus genome variation was followed in the URT and LRT over a period of 27 months using both classical and ultra-deep sequencing methods.

Based on phylogenetic analysis, the frequency distribution of strains infecting the URT and LRT did not reveal any apparent correlation between a given HRV serotype or species and their ability to infect the LRT. Five lung transplant recipients were chronically infected with HRV during periods of time ranging from three to 27 months. Mutation mapping along the HRV genome showed that synonymous changes were roughly spread along the entire ORF, whereas non-synonymous changes clustered mostly in the capsid VP2, VP3, and VP1 genes. The capsid genes are also the most variable during acute infections in immunocompetent hosts.

As expected, the data suggests that immunocompromised patients cannot clear virus infections as well as immunocompetent individuals, and represent a potential reservoir for the emergence of new variants and inter-host transmission due to chronic virus infection. In addition, these patients may be co-infected by two viruses, thus opening the door to recombination, another putative driving force of rhinovirus evolution. With the emergence of new therapies and progress in transplantation, the population of immunocompromised patients is constantly increasing. Our results suggest that this could accelerate the ability of viruses to adapt to the host, evolve, and propagate and may favor a more rapid emergence of new viral variants.

Rhinovirus Genome Variation during Chronic Upper and Lower Respiratory Tract Infections. (2011) PLoS ONE 6(6): e21163. doi:10.1371/journal.pone.0021163
Routine screening of lung transplant recipients and hospital patients for respiratory virus infections allowed to identify human rhinovirus (HRV) in the upper and lower respiratory tracts, including immunocompromised hosts chronically infected with the same strain over weeks or months. Phylogenetic analysis of 144 HRV-positive samples showed no apparent correlation between a given viral genotype or species and their ability to invade the lower respiratory tract or lead to protracted infection. By contrast, protracted infections were found almost exclusively in immunocompromised patients, thus suggesting that host factors rather than the virus genotype modulate disease outcome, in particular the immune response. Complete genome sequencing of five chronic cases to study rhinovirus genome adaptation showed that the calculated mutation frequency was in the range observed during acute human infections. Analysis of mutation hot spot regions between specimens collected at different times or in different body sites revealed that non-synonymous changes were mostly concentrated in the viral capsid genes VP1, VP2 and VP3, independent of the HRV type. In an immunosuppressed lung transplant recipient infected with the same HRV strain for more than two years, both classical and ultra-deep sequencing of samples collected at different time points in the upper and lower respiratory tracts showed that these virus populations were phylogenetically indistinguishable over the course of infection, except for the last month. Specific signatures were found in the last two lower respiratory tract populations, including changes in the 5′ UTR polypyrimidine tract and the VP2 immunogenic site 2. These results highlight for the first time the ability of a given rhinovirus to evolve in the course of a natural infection in immunocompromised patients and complement data obtained from previous experimental inoculation studies in immunocompetent volunteers.

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The media is buzzing today with the latest incarnation of the “Zinc cures common cold” story. This isn’t new. The first report to show that zinc might be a useful treatment for the common cold was published in 1984. Since then, 18 more trials of zinc for colds have been conducted: 11 of them showed zinc to be a useful treatment, while 7 other trials showed no benefit. The present flap comes about because of a new meta-analysis published in the Cochrane Database of Systematic Reviews.

Sadly, this meta-analysis has got its facts in a twist and obscured the truth. Why? Because there is no evidence that zinc is effective against any viruses other than human rhinoviruses (HRV). And, as I’ve been telling my students for the past few weeks – “the common cold” is not a disease, it’s a symptom, caused by at least five different kinds of virus. Four of which zinc does nothing to. (By the way BBC News, human rinovirus isn’t spread primarily by sneezes, it’s spread by people sticking contaminated fingers up their noses).

So don’t get too excited folks. The next time you get a cold, it won’t be common, you won’t know what virus has infected you and you won’t know whether it’s worth risking the toxic effects of zinc ingestion for a potential “cure” (or not). Nice story, shame about the facts.

Zinc for the common cold (Review). The Cochrane Library 2011, Issue 2

Related:

• BBC News: Zinc can be an ‘effective treatment’ for common colds
• NY Times: For Cold Virus, Zinc May Edge Out Even Chicken Soup
• and many others…

Human rhinoviruses (HRV) are the most frequent cause of respiratory infection in humans. These viruses belong to the Picornaviridae, one of the oldest and most diversified human virus family, characterized by a non-enveloped, single positive-stranded RNA genome. Although rhinovirus replication is often restricted to the upper respiratory tract leading to self-limited illnesses of short duration, such as the common cold, HRV can also invade the lower respiratory tract and lead to more serious infections. Similar to many other RNA viruses, the error-prone rhinoviral polymerase can accumulate a large number of nucleotide mutations over a very short period of time, a feature that favors viral adaptation. The error rate of picornavirus RNA polymerases has been estimated to range between 10⁻³ and 10⁻⁴ errors/nucleotide/cycle of replication. This variability is a driving force for virus evolution and results in a large genetic and phenotypic diversity illustrated by the very high number of different HRV serotypes identified to date.

By using ultra-deep sequencing technology, researchers were able to pinpoint HRV evolution at the level of a quasispecies population both in vivo and in vitro. The data illustrate the ability of rhinoviruses to produce several new variants as rapidly as 5 days’ post-infection.

Rhinovirus Genome Evolution during Experimental Human Infection. 2010 PLoS ONE 5(5): e10588. doi:10.1371/journal.pone.0010588
Human rhinoviruses (HRVs) evolve rapidly due in part to their error-prone RNA polymerase. Knowledge of the diversity of HRV populations emerging during the course of a natural infection is essential and represents a basis for the design of future potential vaccines and antiviral drugs. To evaluate HRV evolution in humans, nasal wash samples were collected daily for five days from 15 immunocompetent volunteers experimentally infected with a reference stock of HRV-39. In parallel, HeLa-OH cells were inoculated to compare HRV evolution in vitro. Nasal wash in vivo assessed by real-time PCR showed a viral load that peaked at 48–72 h. Ultra-deep sequencing was used to compare the low-frequency mutation populations present in the HRV-39 inoculum in two human subjects and one HeLa-OH supernatant collected 5 days post-infection. The analysis revealed hypervariable mutation locations in VP2, VP3, VP1, 2C and 3C genes and conserved regions in VP4, 2A, 2B, 3A, 3B and 3D genes. These results were confirmed by classical sequencing of additional samples, both from inoculated volunteers and independent cell infections, and suggest that HRV inter-host transmission is not associated with a strong bottleneck effect. A specific analysis of the VP1 capsid gene of 15 human cases confirmed the high mutation incidence in this capsid region, but not in the antiviral drug-binding pocket. We could also estimate a mutation frequency in vivo of 3.4×10⁻⁴ mutations/nucleotides and 3.1×10⁻⁴ over the entire ORF and VP1 gene, respectively. In vivo, HRV generate new variants rapidly during the course of an acute infection due to mutations that accumulate in hot spot regions located at the capsid level, as well as in 2C and 3C genes.

Related:

• Virus incubation periods
• Sleep and susceptibility to the common cold

Acute respiratory viruses cause substantial morbidity and mortality worldwide. Lower respiratory-tract infections are the leading cause of communicable disease death and among the top five contributors to disability-adjusted life years. Viruses are the primary cause of lower respiratory-tract infections in children and a substantial cause of such infections in all age-groups. The incubation period of an infectious disease is the time between infection and symptom onset. This period is widely reported because it is useful in infectious disease surveillance and control, in which the time of symptom onset may be the only indication of the time of infection. The incubation period plays an essential part in surveillance for healthcare-associated infections, and may aid in diagnosis if laboratory facilities are unavailable. The incubation period is clinically relevant in the administration of antiviral medications, many of which are most effective when given before or immediately after symptom onset. Epidemiological studies depend on the incubation period to identify potential sources of infection. Predictive models designed to inform policy decisions use the incubation period to evaluate the potential of surveillance programmes and interventions to confront emerging epidemics.

The length of the incubation period by comparison with the latent period (the time between infection and becoming infectious) determines the potential effectiveness of control measures that target symptomatic individuals. “4–5 days” may refer to the most common range, the highest and lowest incubation periods in a study, or some other interval. Without knowing which summary measure is being stated, it is hard to use this information to make clinical or infection control decisions. Estimates given without attribution or based on few observations do not meet the standards of evidence we demand for modern medical information. A recent paper reviews the literature on nine respiratory viruses selected for their clinical or public-health importance: adenovirus, human coronavirus, SARS-associated coronavirus, influenza, measles, human metapneumovirus, parainfluenza, respiratory syncytial virus (RSV), and rhinovirus. By systematic review and analysis of published estimates and data, the authors aimed to capture the consensus in the medical literature on these incubation periods, characterise the evidence underlying this consensus, and provide improved estimates of incubation periods for these infections.

Incubation periods of acute respiratory viral infections: a systematic review. Lancet Infect Dis 2009;
9: 291–300
Knowledge of the incubation period is essential in the investigation and control of infectious disease, but statements of incubation period are often poorly referenced, inconsistent, or based on limited data. In a systematic review of the literature on nine respiratory viral infections of public-health importance, we identified 436 articles with statements of incubation period and 38 with data for pooled analysis. We fitted a log-normal distribution to pooled data and found the median incubation period to be 5·6 days (95% CI 4·8–6·3) for adenovirus, 3·2 days (95% CI 2·8–3·7) for human coronavirus, 4·0 days (95% CI 3·6–4·4) for severe acute respiratory syndrome coronavirus, 1·4 days (95% CI 1·3–1·5) for influenza A, 0·6 days (95% CI 0·5–0·6) for influenza B, 12·5 days (95% CI 11·8–13·3) for measles, 2·6 days (95% CI 2·1–3·1) for parainfluenza, 4·4 days (95% CI 3·9–4·9) for respiratory syncytial virus, and 1·9 days (95% CI 1·4–2·4) for rhinovirus. When using the incubation period, it is important to consider its full distribution: the right tail for quarantine policy, the central regions for likely times and sources of infection, and the full distribution for models used in pandemic planning. Our estimates combine published data to give the detail necessary for these and other applications.

Related:

• One virus particle can be enough to cause infection
• Adenoviruses
• SARS Virus May Be Tough To Beat