When pathogens infect the cells of the body, the infection sets off a chain reaction involving the immune system that changes the expression of hundreds of genes. Gene expression is the process by which cells extract information from the genes and render it as molecules of protein or RNA. Cells have the capacity to express more or less of each molecule, creating a pattern of expression that changes in response to external influences, including infection by viruses. Many gene expression microarray studies have proposed distinct gene signatures to discriminate different viral infections or influenza from bacterial infections.
However, these experiments aim to reduce the effect of various biological and technical confounding factors as much as possible by focusing on only one viral infection in one tissue and using one type of microarray. Now, a study from researchers at Stanford University has identified a distinctive pattern of gene expression that distinguishes people with a viral infection from those with a bacterial infection. The team state their findings also identified a second pattern of gene expression that is more specific and can distinguish the flu from other respiratory infections. The opensource study is published in the journal Immunity.
Previous studies show that respiratory viruses such as influenza and SARS pose a major threat to global health, yet antiviral drugs have been difficult to develop. In addition, treating potential pandemic viral strains is problematic because of the many unknowns about the pathogenesis of infection. This is thought to be because the drug-development process requires the ability to identify specific host factors that are necessary for viral growth and virulence that could also be potential drug targets. The prevailing approach for studying gene expression profiles is limited in its ability to identify these multiple targets for broad-spectrum antiviral therapeutics. This standard, single-cohort approach increases the risk of confounding factors on gene expression profiles from the specific tissue, technologies, demographics, and inclusion criteria of the respective studies which can mask the broad pathways used by multiple viruses to establish infection. The current study identifies 396 human genes whose expression changes in a consistent pattern that reveals the presence of a viral infection; the pattern of changes, which they call the meta-virus signature, occurs in a range of viruses and is distinct from the pattern of gene expression in healthy people or in people with bacterial infections and is also present before a person has clear symptoms of infection.
The current study first looked at changes in gene expression in a set of publicly available data. Results show that in blood samples from 205 people infected with a flu, cold or respiratory syncytial virus, 396 genes were identified whose expression changed in the same way during all three types of infections, with an increase in the expression of 161 genes and a decrease in the expression of 235 genes. Data findings show the same pattern in a larger group of blood and tissue cell samples from 2,939 people consisting of healthy controls and those infected with a diverse array of pathogens, including viruses such as SARS coronavirus, enterovirus and adenovirus, as well as bacteria such as Escherichia coli, Staphylococcus aureus, Streptococcus pneumoniae and Salmonella.
Results show that the meta-virus signature identified individuals with an active viral infection and also those who were incubating one. By studying blood samples taken every eight hours for five days, the group identified the meta-virus signature pattern waving a red infection flag up to 24 hours before the first symptoms. The team state that the individual’s gene expression signature changed before they became sick, so they could predict up to 24 hours before who was going to show symptoms. They go on to note that their data also revealed that the meta-virus signature signal, the one indicating any virus, began first and a few hours later, the more-specific influenza meta-signature signal began in people with the flu.
The researchers also carried out three independent studies of flu vaccine recipients, judged to have responded to vaccination by other measures, and who also displayed the 11-gene influenza meta-signature; with nonrespondents showing no influenza meta-signature response. The lab state that, to their knowledge, no one has found the immune response that turns on in both the vaccination response and in actual infections. They conclude that their paper demonstrates for the first time a ‘transcriptional signature’ that can be used as a proxy for whatever immune mechanism is induced by both vaccination and infection and that they have identified the common signature that links infection and vaccination.
The team surmise that theoretically the meta-virus signature could be used clinically to distinguish viral from bacterial infections to determine if an antibiotic should be prescribed, and they have funding to develop such a test. For the future, the researchers state that the long-term goal is to find broad-spectrum antiviral drugs, much like the broad-spectrum antibiotics that have saved so many people from deadly bacterial infections.
Michelle Petersen is the founder of Healthinnovations, having worked in the health and science industry for over 21 years, which includes tenure within the NHS and Oxford University. Healthinnovations is a publication that has reported on, influenced, and researched current and future innovations in health for the past decade.
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An avid campaigner in the fight against child sex abuse and trafficking, Michelle is a passionate humanist striving for a better quality of life for all humans by helping to provide traction for new technologies and techniques within healthcare.