NEW YORK (GenomeWeb News) – A pair of new PLoS ONE studies suggests specific gene expression signatures in host blood samples correspond with symptomatic viral and bacterial infections — information that may ultimately lead to more effective ways of detecting, tracking, and treating such diseases.
"The opportunity is there to screen individuals after a known exposure, after a set time point, and actually detect a signal that might indicate that they are likely to become infected," Duke University Institute for Genome Sciences and Policy researcher Geoffrey Ginsburg told GenomeWeb Daily News.
In the absence of a known exposure, on the other hand, gene expression patterns may help in determining an infection's cause and selecting a suitable treatment, he explained. And as the research advances there are hints that such blood-based infection signatures may be useful in a prognostic context.
Ginsburg is senior author on one of the studies — an array search for blood-based transcription signatures in individuals with influenza H1N1 or H3N2 infections. He also co-senior authored the other study, which involved profiling gene expression patterns in blood samples from mice and humans infected with Staphylococcus aureus bacteria.
"These are good proof-of-concept studies in fairly small numbers of individuals," Ginsburg said. "The next step is to do this in many, many more well-phenotyped — microbiologically and clinically phenotyped — individuals so that we can really understand the accuracy and specificity of the technology."
The Duke team has filed a patent application related to its genomic signature-based strategy for assaying for infectious diseases. They are not currently partnering with any groups to commercialize the approach.
"We hope that someday it might evolve into something that's commercializable," Ginsburg noted. "We're certainly working on migrating the assays onto PCR platforms and other things that are more clinically tractable than microarrays."
Because pathogens prompt the body to mount an immune response, researchers have reasoned for some time that it might be possible to detect or even characterize infections by gauging host gene expression patterns.
"At least in concept, the idea that this could be done has been around for the good part of the last decade," Ginsburg said. "But to actually put it into practice, I think, has been enabled by the advent of fairly reliable, robust genome-wide technologies such as array-based transcriptomics and now RNA sequencing."
For the flu study, for instance, the researchers inoculated 41 healthy volunteers between the ages of 20 and 41 years old with one of two influenza A strains — either the H1N1 virus A/Brisbane/59/2007 or the H3N2 virus A/Wisconsin/67/2005.
They then collected blood samples from these individuals every 8 hours over the course of a week, using Affymetrix U133a 2.0 arrays to assess gene expression patterns in their blood over time.
In the 24 individuals infected with H1N1, nine went on to show flu symptoms. In those individuals, the team identified a gene signature that differed from that found in blood samples from the asymptomatic H1N1 carriers.
Similarly, the researchers saw distinct gene expression shifts in blood samples from the nine H3N2-infected volunteers who developed flu symptoms compared with the eight individuals with asymptomic H3N2 infections.
And those telltale expression changes typically appeared days before individuals showed the first signs of outward disease, suggesting they could offer an early peek at disease development or perhaps even symptom severity.
When the researchers looked at blood samples collected from three-dozen individuals treated for H1N1 infections at Duke University Hospital and 45 healthy controls, meanwhile, they found that the newly discovered H1N1 expression signature correctly classified around 92 percent of authentic flu cases and 93 percent of healthy samples.
Bacterial infections prompted gene expression changes that could be detected in blood, too, the researchers found.
In a second PLoS ONE study, Ginsburg and Duke researcher Vance Fowler Jr. co-led a group describing a series of experiments on mouse and human samples that revealed gene expression patterns for pinning bloodstream infections on the bacterial pathogen S. aureus.
For that work, researchers also profiled host expression patterns with an eye to distinguishing infections by the Gram-positive S. aureus bug from cases caused by Gram-negative Escherichia coli bacteria.
Such bacterial infections produced host expression responses that were markedly different from those found during the symptomatic influenza infections assayed for the first study, Ginsburg explained, noting that "human response to viral and bacterial illness is very distinct and highly distinguishable."
In addition, viral and bacterial infection signatures found so far have been noticeably different from those described for mice with bloodstream infections caused by the fungal pathogen Candida albicans — a situation that members of the same team tested for a study published in 2010 in Science Translational Medicine.
Together, such studies hint at a few potential diagnostic and therapeutic applications for gene expression profiling in individuals infected with or exposed to various pathogens.
In individuals with existing infections, for instance, expression signatures in the blood might help to determine whether an individual suffers from a viral, bacterial, or fungal infection, Ginsburg explained. And that, in turn, may help clinicians determine whether antibiotics are an appropriate treatment option or whether an alternative treatment is more apt to work.
Moreover, as researchers rack up host expression profiles corresponding to infection by an ever-expanding list of pathogens, they hope to get find finer-scale patterns coinciding with the presence of a particular pathogen or combination of pathogens.
It remains to be seen if and when blood-based gene expression patterns can be reliably linked to specific viral strains or bacterial species. But there are hints that at least some related pathogens can produce subtly different responses in their hosts.
In their influenza study, for instance, the researchers found many of the same genes showing expression boosts or dips in all of the symptomatic individuals infected with influenza A. But there were also subtle differences in the genes involved in the infection signatures depending on whether the infection involved the H1N1 or H3N2 strains.
"There are some differences and we're beginning to explore other means to sub-speciate, if we can," Ginsburg said. Still, he cautioned that some groups of pathogens may also trigger relatively common immune responses that are tricky to tell apart.
"If it were ever to become a potential diagnostic platform," he explained, "ideally it would be tethered to an antigen-profiling platform to first figure out what a person has — is it viral or bacterial or something else — and then … to target the types of assays that you need to understand what species of virus or what species of bacterial infection is underlying the illness."
Likewise, Ginsburg said researchers still have more to learn about gene expression patterns in the subset of individuals exposed to a given pathogen who do not develop obvious disease symptoms, since those profiles could prove useful for finding those at risk of unwittingly spreading infection.
The group is also continuing to flesh out the host responses associated with symptomatic infections in an even larger group of individuals infected with a wide swath of viral, bacterial, and other pathogens.
"Our hope is really to create a catalog of these host response signatures that could be hopefully used someday clinically," Ginsburg said.