Cellular quality control may miss nearly half of certain misfolded proteins, raising disease risk
核心洞察
A Penn State-led study found that proteins containing an entanglement in their native structure are 93% more likely to be tagged for degradation than proteins without one.
About a third of entangled proteins evade the cellular quality control system despite high misfolding rates, potentially accumulating and disrupting protein homeostasis.
Computer simulations showed tagged entangled proteins are four times more likely to misfold than untagged proteins without an entanglement.
As proteins are synthesized in a cell, they fold into the three-dimensional structures that enable them to function, but this process can sometimes go wrong. When it does, misfolded proteins lose some or all of their function and are typically tagged by the cell's quality assurance and maintenance machinery, which attempts to repair them or, failing that, strips them to recycle their components. A new study led by scientists at Penn State reveals that proteins containing a certain type of structure are more likely to misfold and be targeted for removal, yet nearly half still manage to evade the cellular maintenance crew. These persistent misfolded proteins could accumulate in cells, disrupting the balance of protein production and recycling and potentially contributing to aging and disease, according to the researchers. The paper was recently published in the journal Nature Communications.
"Like a tiny factory, cells make proteins," said Ed O'Brien, professor of chemistry in the Penn State Eberly College of Science and leader of the research team. "And like a factory, cells have quality control mechanisms to catch any errors on the production line. We've recently identified a new class of protein misfolding, and we were interested in if it had any impact on how the cellular quality control system maintains a balance of protein production, repair and recycling — protein homeostasis. Additionally, protein misfolding is known to contribute to diseases like Alzheimer's and Huntington's. Therefore, increasing our understanding of the basic biology underlying this novel class of misfolding could lead to the identification of new disease origins and treatments."
A novel class of misfolding driven by protein entanglement
The new class of misfolding occurs through a change in the entanglement of a segment of the protein. The string of amino acids that make up proteins can form a loop, and the end of the string can thread through the loop, forming a knot-like structure. Misfolding can occur either by this type of entanglement forming where it should not, or by failing to form when it is part of a protein's natural structure.
"We focused on proteins that have an entanglement as part of their native structure because we have shown in the past that they are more likely to misfold," said Yang Jiang, associate research professor of chemistry at Penn State and first author of the paper. "We used an existing database of proteins that have been tagged with a marker for degradation in human fibroblast cells and cross-referenced it with a database of protein structures so we could see the proportion of proteins with the entanglement that were marked by the cellular quality control mechanism."
Repurposing existing data to answer new questions
The study drew on publicly available datasets rather than new experiments, an approach central to the mission of the U.S. National Science Foundation (NSF) National Synthesis Center for Emergence in the Molecular and Cellular Sciences (NCEMS) at Penn State, which supported the research.
"In science, we often collect massive amounts of data to answer the specific questions that we are interested in and then that data sits unused," said O'Brien, who is director of NCEMS. "It's a labor-intensive and time-consuming part of the process and takes a large amount of tax-payer dollars to generate such data. So, at NCEMS, we are interested in finding new uses for old data that can accelerate scientific discoveries. The four different datasets we used in this study were collected for a different reason, but it was perfect for the questions we asked."
Key findings on degradation and evasion
The team found that proteins containing an entanglement as part of their native structure were 93% more likely to be tagged for degradation and removed by cellular maintenance crews than proteins without an entanglement. They also estimated how quickly the proteins get tagged for removal, finding that recently made, or young, proteins were already tagged — some even while they were still in the process of being made.
"We also used computer simulations to show that tagged proteins that have an entanglement as part of their structure are four times more likely to misfold than untagged proteins without an entanglement," said O'Brien, who is also a co-hire of the Penn State Institute for Computational and Data Sciences and principal investigator for NCEMS. "This suggests that the failure to form an entanglement increases the likelihood of a protein being tagged for degradation."
Notably, the researchers showed that about a third of proteins with an entanglement are not tagged for degradation, despite their high rate of misfolding.
"Sometimes a misfolded entanglement can be hidden deep within the structure of a protein, so that it isn't visible to the quality control system," Jiang said. "These proteins may therefore evade degradation and persist in the cell despite being non-functional. Eventually, these misfolded proteins can accumulate in a cell disrupting protein homeostasis and potentially contributing to aging and disease by gumming up the cellular works."
In addition to O'Brien and Jiang, the research team included Anushka Jain and Sina Ghaemmaghami at the University of Rochester, who are experts in mass spectrometry, the technique that generated the datasets used in the study. The work was funded by the National Institutes of Health's National Institute of General Medical Sciences under grant number R35-GM124818 and the U.S. National Science Foundation under grant number MCB-2335029.
