Cell SystemsSystems BiologyPeer-reviewed journal article
A reconstruction of the mammalian secretory pathway identifies mechanisms regulating antibody production
Helen O. MassoniD, Jasmine TatiD, Pablo Di GiustoiD, Athanasios AntonakoudisiD, Isaac ShamieiD, Hratch BaghdassarianiD, Mojtaba Samoudi, Caressa M. Robinson, Chih‐Chung Kuo, Natalia Koga, Sonia Singh, Angel Gezalyan, Zerong LiiD, Alexia Movsessian, Anne RichelleiD, Nathan E. LewisiD
Abstract
The secretory pathway processes >30% of mammalian proteins, orchestrating their synthesis, modification, trafficking, and quality control. However, its complexity-- spanning multiple organelles and dependent on coordinated protein interactions--limits our ability to decipher how protein secretion is controlled in biomedical and biotechnological applications. To advance such research, we present secRecon--a comprehensive reconstruction of the mammalian secretory pathway, comprising 1,127 manually curated genes organized within an ontology of 77 secretory process terms, annotated with functional roles, subcellular localization, protein interactions, and complex composition. Using secRecon to integrate multi-omics data, we identified distinct secretory topologies in antibody-producing plasma cells compared to CHO cells. Genes within proteostasis, translocation, and N-glycosylation are deficient in CHO cells, highlighting them as potential engineering targets to boost secretion capacity. Applying secRecon to single-cell transcriptomics and SEC-seq data, we uncovered secretory pathway signatures underlying secretion diversity among IgG-secreting plasma cells. Different transcriptomic clusters had unique secretory phenotypes characterized by variations in the unfolded protein response (UPR), endoplasmic reticulum-associated degradation (ERAD), and vesicle trafficking pathways. Additionally, we discovered specific secretory machinery genes as new markers for plasma cell differentiation. These findings demonstrate secRecon can identify mechanisms regulating protein secretion and guide diverse studies in biomedical research and biotechnology. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=73 SRC="FIGDIR/small/623668v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@f9f865org.highwire.dtl.DTLVardef@122db7forg.highwire.dtl.DTLVardef@1788a1aorg.highwire.dtl.DTLVardef@b2b2bd_HPS_FORMAT_FIGEXP M_FIG C_FIG
- organism: mouse
- organism: human
- assay: bulk RNA-seq
- assay: spatial transcriptomics
- research focus: gene regulatory network inference
- research focus: cell type annotation
- approach: statistical model
- Citations
- 6
- FWCI
- 2.98
- Field percentile
- top 8%
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