Success Story
Protein shapes as biomarkers
Technology Translation
In order to function properly, proteins must fold into their specific 3-dimensional shape. When this process goes awry, it can lead to disease. Misfolded proteins are thought to play a crucial role in the development of neurodegenerative diseases such as Alzheimer’s or Parkinson’s disease. However, studying protein shapes is challenging, especially when a sample contains a mixture of many different proteins.
Traditionally, scientists analyze complex protein samples using mass spectrometry proteomics. “With this method you can, for instance, compare the levels of proteins in patients with a specific disease with those found in healthy individuals, and identify specific proteins that increase as the disease develops”, explains Paola Picotti from ETH Zurich. These specific proteins then become candidate biomarkers, and, once validated, can help to detect disease at an earlier stage.
In recent years, Picotti and her team have developed a new technique that does not focus on the amounts of proteins, but rather on their 3-dimensional structures. While methods such as X-ray-crystallography, NMR or cry-electron-microscopy can also determine the protein structures, but only of single proteins or protein complexes, Picotti’s innovation allows the structural analysis of samples containing thousands of different proteins and determining which ones change when different samples are compared. “This allows us to ask completely new questions”, she says.
The method, known as “Limited Proteolysis Coupled to Mass Spectrometry” (LiP-MS), also relies on mass spectrometry. However, before measurement, the protein samples are mixed for a short period of time with proteases, enzymes that act like molecular scissors, cutting proteins at specific sites depending on their shape. This produces a unique pattern of fragments. If a protein in the sample changes shape due to a certain disease, the resulting fragments will differ accordingly.
By analyzing these fragments with mass spectrometry, researchers obtain a specific structural “fingerprint” for each protein. “If the structure of a protein has changed as a result of disease, the fingerprint will look different”, Picotti explains. The resulting data is visualized as colorful barcodes, each bar representing a fragment.
Supported by a PHRT grant, Picotti has begun applying this method to a cohort of patients with Parkinson’s disease. To date, there are still no reliable biomarkers for this condition, and conventional proteomic analyses have revealed only small changes in protein levels as the disease progresses. Prior studies showed that a protein called alpha-synuclein changes shape in the brains of Parkinson’s patients, forming insoluble aggregates. However, detecting these changes in fluids that are biologically accessible has remained elusive.
In her study, Picotti’s team compared proteins in the cerebrospinal fluid (CSF) of 50 Parkinson’s patients and 50 healthy individuals. Because CSF is in direct contact with the brain, it reflects the proteins present there. Using LiP-MS, Picotti measured around 2000 proteins and identified 76 whose structure differed between patients and healthy controls. Interestingly, the alpha-synuclein protein was not among them, possibly because its concentration in CSF is too low to be properly detected. Yet, when these 76 structural biomarkers were combined with alpha-synuclein, the accuracy in diagnosing Parkinson’s disease improved significantly.
The 76 proteins can be grouped into various clusters: One set of proteins is found in the alpha-synuclein deposits that build up in the brains of Parkinson’s patients, another is linked to genes that are known risk factors for Parkinson’s, and a third involves proteins active at synapses, the communication points between neurons.
“We are still at the beginning of a very long biomarker discovery process”, Picotti says. The next step will be to analyze larger cohorts with thousands of patients. This is best done in international cohorts. “We need to find out whether these 76 proteins are truly specific to Parkinson’s disease or whether they are generic stress markers that also show up in other neurodegenerative conditions such as Alzheimer’s or Lewy Body Dementia. Preliminary results suggest that about half of the proteins are indeed specific to Parkinson’s disease.”
Using protein shapes rather than protein levels as biomarkers is a completely new concept. Picotti is often asked why one would want to identify biomarkers for a disease that currently has no cure. Why know early if you will develop a disease when nothing can be done about it? “Our perspective is that one reason we lack effective drugs for these diseases is that patients are being diagnosed too late, when the damage is already extensive”, she says. Enrolling patients in clinical trials at such a late stage may be the reason why so many drugs have failed. Earlier detection could make clinical trials far more effective and eventually lead to successful treatments.
This structural approach also holds promise for other conditions, beyond neurodegenerative diseases. In fact, clinicians at the University Hospital in Zurich have already begun applying the technique to samples from other diseases – proving that collaboration between research and clinical practice, the core goal of PHRT, is truly taking shape.