Deciphering the determinants of recombinant protein expression across the human secretomeShow others and affiliations
2025 (English)In: Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, E-ISSN 1091-6490, Vol. 122, no 41Article in journal (Refereed) Published
Abstract [en]
Protein secretion is an essential process of mammalian cells. In biomanufacturing, this process can be optimized to enhance production yields and biotherapeutic quality. While cell line engineering and bioprocess optimization have yielded high protein titers for some recombinant proteins, many remain difficult to express. Here, we investigated factors influencing protein expression in Chinese hamster ovary (CHO) cells, expressing 2,135 Human Secretome Project proteins. While the abundance of mRNA from recombinant proteins explained less than 1% of observed variation in secretion titers, analysis of 218 biochemical and biophysical descriptors uncovered intrinsic protein features that account for ~15% of secretion variability, pinpointing key drivers such as molecular weight, cysteine content, and N-linked glycosylation, and establishing a roadmap for rational design of difficult-to-express proteins. We subsequently analyzed RNA-Seq data from 95 CHO cell cultures, each expressing a distinct recombinant protein, spanning a wide range of titers. Host cell transcriptomic signatures showed strong correlations with titer, thereby providing insights into cellular processes that covary with expression. Cells failing to produce proteins exhibited increased ubiquitin-mediated proteasomal degradation, including ER-associated degradation; whereas high-producing cells demonstrated enhanced lipid metabolism and a stronger response to oxidative stress, suggesting these factors may support successful recombinant protein productions. Together, using this resource, we quantified the contributions of various protein and cellular factors that correlate with the expression of diverse recombinant human proteins in a heterologous host, thereby providing insights for next-generation CHO cell engineering.
Place, publisher, year, edition, pages
Proceedings of the National Academy of Sciences , 2025. Vol. 122, no 41
Keywords [en]
Chinese hamster ovary cells, machine learning, protein secretion, recombinant protein, transcriptomics
National Category
Molecular Biology Bioprocess Technology Medical Biotechnology (Focus on Cell Biology, (incl. Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Identifiers
URN: urn:nbn:se:kth:diva-372360DOI: 10.1073/pnas.2506036122PubMedID: 41055974Scopus ID: 2-s2.0-105017946891OAI: oai:DiVA.org:kth-372360DiVA, id: diva2:2011842
Note
QC 20251106
2025-11-062025-11-062025-11-06Bibliographically approved