Protein sequences evolved to fold in cells, including cotranslational folding of nascent polypeptide chains during their synthesis by the ribosome. The vectorial (N- to C-terminal) nature of cotranslational folding constrains the conformations of the nascent polypeptide chain in a manner not experienced by full-length chains diluted out of denaturant. We are still discovering to what extent these constraints affect later, posttranslational folding events. Here we directly address whether conformational constraints imposed by cotranslational folding affect the partitioning between productive folding to the native structure versus aggregation. We isolated polyribosomes from Escherichia coli cells expressing GFP, analyzed the nascent chain length distribution to determine the number of nascent chains that were long enough to fold to the native fluorescent structure, and calculated the folding yield for these nascent chains upon ribosome release versus the folding yield of an equivalent concentration of full-length, chemically denatured GFP polypeptide chains. We find that the yield of native fluorescent GFP is dramatically higher upon ribosome release of nascent chains versus dilution of full-length chains from denaturant. For kinetically trapped native structures such as GFP, folding correctly the first time, immediately after release from the ribosome, can lead to lifelong population of the native structure, as opposed to aggregation.

Cotranslational protein maturation is often studied in cell-free translation mixtures, using stalled ribosome-nascent chain complexes produced by translating truncated mRNA. This approach has two limitations: (i) it can be technically challenging, and (ii) it only works in vitro, where the concentrations of cellular components differ from concentrations in vivo. We have developed a method to produce stalled ribosomes bearing nascent chains of a specified length by using a 'stall sequence', derived from the Escherichia coli SecM protein, which interacts with residues in the ribosomal exit tunnel to stall SecM translation. When the stall sequence is expressed at the end of nascent chains, stable translation-arrested ribosome complexes accumulate in intact cells or cell-free extracts. SecM-directed stalling is efficient, with negligible effects on viability. This method is straightforward and suitable for producing stalled ribosome complexes in vivo, permitting study of the length-dependent maturation of nascent chains in the cellular milieu.

Mucopolysaccharidosis type IIIA (MPS-IIIA, Sanfilippo syndrome) is a Lysosomal Storage Disease caused by cellular deficiency of N-sulfoglucosamine sulfohydrolase (SGSH). Given the large heterogeneity of genetic mutations responsible for the disease, a comprehensive understanding of the mechanisms by which these mutations affect enzyme function is needed to guide effective therapies. We developed a multiparametric computational algorithm to assess how patient genetic mutations in SGSH affect overall enzyme biogenesis, stability, and function. 107 patient mutations for the SGSH gene were obtained from the Human Gene Mutation Database representing all of the clinical mutations documented for Sanfilippo syndrome. We assessed each mutation individually using ten distinct parameters to give a comprehensive predictive score of the stability and misfolding capacity of the SGSH enzyme resulting from each of these mutations. The predictive score generated by our multiparametric algorithm yielded a standardized quantitative assessment of the severity of a given SGSH genetic mutation toward overall enzyme activity. Application of our algorithm has identified SGSH mutations in which enzymatic malfunction of the gene product is specifically due to impairments in protein folding. These scores provide an assessment of the degree to which a particular mutation could be treated using approaches such as chaperone therapies. Our multiparametric protein biogenesis algorithm advances a key understanding in the overall biochemical mechanism underlying Sanfilippo syndrome. Importantly, the design of our multiparametric algorithm can be tailored to many other diseases of genetic heterogeneity for which protein misfolding phenotypes may constitute a major component of disease manifestation.

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