Genome-scale reconstructions of the mammalian secretory pathway predict metabolic costs and limitations of protein secretion

Abstract

35Keywords 36 Metabolic network, secretory pathway, biotherapeutic production, systems biotechnology 37Indeed, recent studies have incorporated portions of the secretory pathway in metabolic models of yeast 55 3-5 . Furthermore, Lund and colleagues reconstructed a genetic interaction network of the mouse secretory 56 pathway and the unfolded protein response and analyzed it in the context of CHO cells 6 . However, such a 57 network does not encompass a stoichiometric reconstruction of the biochemical reactions involved in the 58 secretory pathway nor it is coupled to existing metabolic networks of mammalian cells. 59Here we present the first genome-scale stoichiometric reconstructions and computational models of 60 mammalian metabolism coupled to protein secretion. Specifically, we constructed these for human, 61 mouse, and CHO cells, called RECON2.2s, iMM1685s, and iCHO2048s, respectively. We first derive an 62 expression for computing the energetic cost of synthesizing and secreting a product in terms of molecules 63 of ATP equivalents per protein molecule. We use this expression and analyze how the energetic burden 64 of protein secretion has led to an overall suppression of more expensive secreted host cell proteins in 65 mammalian cells. Given its dominant role in biotherapeutic production, we further focus on the 66 biosynthetic capabilities of CHO cells. We then demonstrate that product-specific secretory pathway 67 models can be built to estimate CHO cell growth rates given the specific productivity of the recombinant 68 3 product as a constraint. We identify the features of secreted proteins that have the highest impact on 69 protein cost and productivity rates. Finally, we use our model to identify proteins that compete for cell 70 resources, thereby presenting targets for cell engineering. Through this study we demonstrate that a 71 systems-view of the secretory pathway now enables the analysis of many biomolecular mechanisms 72 controlling the efficacy and cost of protein expression in mammalian cells. We envision our models as 73 valuable tools for the study of normal physiological processes and engineering cell bioprocesses in 74 biotechnology. All models and data used in this study are freely available at 75 https://github.com/LewisLabUCSD/MammalianSecretoryRecon. 76 77 RESULTS 78 A stoichiometric expression of protein secretion energetics 79In any cell, the secretory machinery is concurrently processing thousands of secreted and membrane 80 proteins, which all compete for secretory pathway resources and pose a metabolic burden. To quantify 81 this burden, we estimated the energetic cost of synthesizing and/or secreting 5,641 and 3,538 82 endogenous proteins in the CHO and human secretome and membrane proteome in terms of total 83 number of ATP equivalent molecules consumed (see Methods). These protein costs were compared to 84 the cost of five recombinant proteins commonly produced in CHO cells (Fig. 1a). To refine estimates, we 85 predicted signal peptides 7 , GPI anchor attachment signals 8 , an...

Multiplex secretome engineering enhances recombinant protein production and purity

“…In addition, it has recently been shown that depletion of a highly abundant mRNA encoding a non-essential protein can improve growth and product titer, indicating that it is possible to free up energetic and secretory resources by rational cell line engineering strategies 33 . This observation was supported by a model of the secretory pathway, which was able to accurately predict the increase in growth and protein productivity 19 . These studies have so far been limited to single engineering targets, but could easily be applied on a larger scale.…”

“…A genome-scale model of protein secretion was adapted for use here 19 . Briefly, this model was adapted to focus on the bioenergetic costs of protein synthesis and translocation of each host-cell secreted protein.…”

“…For those genes without a UniProt match, we used the online tool PrediSi 21 to determine the presence of a signal peptide. To estimate ATP cost of secretion for all secreted genes identified, we added the following costs, adapted from the genome-scale model of protein secretion 19 . First, the energy cost of protein translation was equal to 4 x L ATP molecules where L is the length of the amino acid sequence.…”

“…However, the question remains regarding the bioenergetic investment made by the host cells on the secreted fraction of their proteome. To evaluate the resource and bioenergetic investment of CHO cells into their secretome, we calculated the cost of each protein using a model of CHO cell protein secretion 19 , scaled by its expression in RNA-Seq data 20 . In CHO-S cells, we found that 39.2% of the resources are dedicated to producing membrane and secreted proteins, most of which are processed through the secretory pathway ( Fig.…”

Correcting for sparsity and non-independence in glycomic data through a systems biology framework

“…Glycosylation is a highly abundant and complex post-translational modification, decorating between one-fifth and one-half of eukaryotic proteins 1,2 . These diverse carbohydrates account for 12-25% of dry mass, and have important functional and pathological roles 3,4 . Despite their essentiality, glycans are difficult to study; thus, our understanding of their impact is limited.…”