For neglected infectious diseases, accurate diagnostic tools can be revolutionary, saving lives and shaping the health of entire communities.
One of these neglected diseases is human African trypanosomiasis (HAT). Also known as African sleeping sickness, HAT is a debilitating infection that affects thousands each year. Patients are often only diagnosed in the late stage of the disease by observing the parasites in cerebrospinal fluid, after the parasite has entered the central nervous system and caused grave illness. A low-cost, rapid “dipstick” test that could analyze a drop of patient’s blood and diagnose the illness early would make a huge impact.
Researchers have spent decades looking for proteins from the parasite itself in plasma, the liquid component of blood, with the goal of developing rapid diagnostic tests. While plasma represents an ideal source of biomarkers – a simple finger-prick is sufficient for testing – the fluid has a major flaw when it comes to diagnosis: it’s a murky soup of proteins, ranging from abundant ones such as albumin and globulins to scarcer ones such as proteins from infectious organisms.
Scientists in the Broad’s Proteomics Platform have recently developed and optimized analytic methods that, for the first time, can identify parasite proteins in the plasma of infected patients. The sophisticated approach overcomes what research scientist Rushdy Ahmad calls a “mismatch in dynamic range,” by effectively “zooming in” on the proteins they’re most interested in.
He explains that the dynamic range of proteins in plasma, meaning the lowest to highest abundance, is perhaps as great as 12 orders of magnitude. In other words, the most abundant proteins are 1 trillion times more numerous than the least abundant proteins. The dynamic range of a mass spectrometer – the gold standard for analyzing proteins – is much narrower, only 4 orders of magnitude. Running plasma through a mass spectrometer will only reveal the most abundant proteins, leaving the scarcer ones hidden below the threshold of detection.
In the new method, plasma is first “immunodepleted,” removing the top 50-70 most abundant human plasma proteins, including proteins such as albumin. “We want to collapse that dynamic range,” Ahmad explains. The technique is like skimming off the fat from soup to leave the nutritious broth, vegetables, and meat. The remaining sample is then “fractionated,” breaking it into 30 smaller samples, each containing proteins of a narrower range of abundance. “Those fractions are what we inject into the mass spectrometer,” he says. “The combination of abundant protein removal and subsequent fractionation enabled the mass spec to probe deeper into the proteome, beneath all the human proteins we’re not interested in.”
In collaboration with Terry Pearson and colleagues at the University of Victoria in British Columbia, Ahmad and platform director Steve Carr applied the new method to plasma samples from patients infected with African sleeping sickness. They were able to identify more than 250 proteins from the trypanosome parasites that underlie this dangerous disease, showing promise for the method to discover biomarkers of disease in plasma that could one day be incorporated into a diagnostic test.
More work remains before African sleeping sickness can be rapidly diagnosed in the field. The researchers must learn which of the 250 proteins make the best biomarkers to develop a diagnostic test against. In addition, the samples used in this study came from patients with late stage disease, and the team hopes to identify proteins present during early stages of infection, so they are working to get more samples from the field. They may also forge a partnership with a diagnostic company to actually create the assay.
Interestingly, the study detected more than 4000 low-abundance human proteins present in the plasma, the greatest depth of coverage of the human plasma proteome to date. Carr, Ahmad, and their colleagues are currently mining data on these thousands of proteins found in plasma to look for patterns of change during illness – signatures of host response – in diseases such as tuberculosis and malaria. Those signatures could then form the basis for new a diagnostic approach, which would use patterns of change in the levels of proteins as indicators of disease. The proteomic analysis of human plasma proteins also provides a window into disease biology and insights that could guide vaccine development.
The researchers also plan to investigate other illnesses that could benefit from improved diagnosis, such as another trypanosome illness, Chagas disease, or cancers with poor diagnostics, like lung cancer, in addition to other neglected diseases. “Now this opens up the door for all these other diseases that don’t get a lot of limelight because they’re out on the periphery,” he says. “For now, the science is progressing and this work shows the technological capability for discovery.”