Proteins need to fold into specific shapes to perform their functions in cells, but they occasionally misfold, which can prevent them from properly functioning and even lead to disease. A new study by researchers at Penn State found that, in E. coli, proteins containing a widespread structural 3D pattern, known as a motif, are more likely to misfold than proteins that lack it. The team also discovered that how essential the protein is for the cell's survival influences how strongly cellular quality-control systems correct misfolding in the motif.
A paper describing the study, in which the researchers suggest that essential proteins may have evolved to allow misfolding of the motif to be rescued by other proteins called chaperones, published this week (Dec. 12) in the journal Nature Communications.
"To function properly, proteins must fold into a three-dimensional structure," said Ian Sitarik, a staff scientist in the U.S. National Science Foundation (NSF) National Synthesis Center for Emergence in the Molecular and Cellular Sciences (NCEMS) at Penn State and the first author of the study. "Until recently, there was only a handful of mechanisms known through which proteins could misfold, but our lab recently identified a new mechanism involving the loss of non-covalent lasso entanglements (NCLEs), a motif found in the native 3D structure of many proteins. We were interested in how prevalent this type of misfolding is and whether these misfolds would be recognized and repaired by chaperones."
Proteins are composed of long strings of amino acids - sometimes described as beads on string - that are then folded into loops, helixes and other 3D structures. NCLEs occur when one end of the string is threaded through a loop, forming an entanglement. Many proteins include NCLEs as part of their native structure, and they can misfold when the loop closes before being threaded or if the loop captures the wrong end of the string or another part of the protein. Misfolding can also result in NCLEs forming where they don't belong.
To investigate misfolded NCLEs, the research team used preexisting publicly available data on the structures of hundreds of proteins collected by a separate research group. This group originally compared two essentially identical samples of the complete proteome - the entire set of proteins expressed by an organism - of E. coli. In one set, the proteins were denatured, or unfolded, and then allowed to refold - introducing the potential to misfold - whereas the other set were kept in their natural state. The original researchers then cut the proteins in both samples into small pieces using enzymes - proteins that functions like molecular scissors - and identified them using mass-spectrometry, an advanced characterization technique.
"The enzymes must be able to access specific regions of the proteins to cut them, but these regions can be obscured deep in the 3D structure of a protein," said Sitarik, who earned a doctoral degree in chemistry at Penn State earlier this year. "When a protein misfolds, different regions may be accessible to the enzymes, so they can be cut differently than the protein in its native state, and we will see a different pattern of pieces from the same protein. We can then use databases of experimentally derived or predicted 3D protein structures to see how any changes we see relate to the location of native NCLEs."
Analyzing this pre-existing data, the team at Penn State found that proteins with NCLEs in their native structures were twice as likely to misfold - and the misfolds were 40% more likely to occur at the site of the NCLE in the protein. They also looked at preexisting data where the denatured proteins were allowed to refold in the presence of chaperone proteins to see if misfolded NCLEs would be rescued by the cellular quality control machinery.
"We found that the misfolding of native NCLEs in proteins that are essential to the bacteria - when they are experimentally removed or broken the bacteria dies - are rescued by chaperones at a higher rate than non-essential proteins," said co-author Ed O'Brien, professor of chemistry, a co-hire of the Penn State Institute for Computational and Data Sciences (ICDS), and director of the NCEMS. "This suggests that there may be a mechanism that evolved to make essential proteins with native NCLEs more amenable to repair."
Statistical analysis of NCLEs between essential and non-essential proteins, O'Brien said, revealed that the amino acids that close the loop of NCLEs in essential proteins tended to make weaker connections than the amino acids in the loop closures of non-essential proteins.
"These weaker loop closures could have evolved to allow chaperones to access and fix misfolded NCLEs in this crucial subset of proteins," Sitarik said. "For non-essential proteins, there would not have been the evolutionary pressure to fix their misfolds as they can likely persist in a misfolded state without causing too much damage to the bacteria."
The study is the first high-throughput analysis - studying hundreds of proteins simultaneously - of NCLE misfolding, according to the researchers, who said that leveraging existing data allowed them to more efficiently perform the analysis, without the need to invest time and money in additional experiments.
"At NCEMS, a big part of our approach is to work with multidisciplinary teams to reuse publicly available data to gain new, deeper and broader insights," O'Brien said. "While this study used data from E. coli, we know that this type of misfolding occurs in other organisms, including humans. Protein misfolding is associated with several human diseases, and we hope that eventually learning more about NCLEs could lead to a better understanding of some of these diseases and potentially new, effective treatments."
In addition to Sitarik and O'Brien, the research team at Penn State included Quyen V. Vu, postdoctoral researcher in chemistry; Justin Petucci, research and design engineer in the ICDS; Paulina Frutos, graduate student in biology; and Hyebin Song, assistant professor of statistics.
The NSF and the U.S. National Institutes of Health funded the research. The NCEMS at Penn State receives support from the Huck Institutes of the Life Sciences, the Institute for Computational and Data Sciences, the Eberly College of Sciences, and the College of Information Sciences and Technology.
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