Human protein secretory pathway genes are expressed in a tissue-specific pattern to match processing demands of the secretome

Improved reference quality genome sequence of the plastic-degrading greater wax moth, Galleria mellonella

Galleria mellonella is a pest of honeybees in many countries because its larvae feed on beeswax. However, G. mellonella larvae can also eat various plastics, including polyethylene, polystyrene, and polypropylene, and therefore, the species is garnering increasing interest as a tool for plastic biodegradation research. This paper presents an improved genome (99.3% completed lepidoptera_odb10 BUSCO; genome mode) for G. mellonella. This 472 Mb genome is in 221 contigs with an N50 of 6.4 Mb and contains 13,604 protein-coding genes. Genes that code for known and putative polyethylene-degrading enzymes and their similarity to proteins found in other Lepidoptera are highlighted. An analysis of secretory proteins more likely to be involved in the plastic catabolic process has also been carried out.

Osiris17 is essential for stable integrin localization and function during insect wing epithelia remodeling

The dynamic adhesion between cells and their extracellular matrix is essential for the development and function of organs. During insect wing development, two epithelial sheets contact each other at their basal sites through the interaction of βPS integrins with the extracellular matrix. We report that Osiris17 contributes to the maintenance of βPS integrins localization and function in developing wing of Drosophila and locust. In flies with reduced Osiris17 expression the epithelia sheets fail to maintain the integrity of basal cytoplasmic junctional bridges and basal adhesion. In contrast to the continuous basal integrin localization in control wings, this localization is disrupted during late stages of wing development in Osiris17 depleted flies. In addition, the subcellular localization revealed that Osiris17 co-localizes with the endosomal markers Rab5 and Rab11. This observation suggests an involvement of Osiris17 in endosomal recycling of integrins. Indeed, Osiris17 depletion reduced the numbers of Rab5 and Rab11 positive endosomes. Moreover, overexpression of Osiris17 increased co-localization of Rab5 and βPS integrins and partially rescued the detachment phenotype in flies with reduced βPS integrins. Taken together, our data suggest that Osiris17 is an endosome related protein that contributes to epithelial remodeling and morphogenesis by assisting basal integrins localization in insects.

Inferring secretory and metabolic pathway activity from omic data with secCellFie

Understanding protein secretion has considerable importance in biotechnology and important implications in a broad range of normal and pathological conditions including development, immunology, and tissue function. While great progress has been made in studying individual proteins in the secretory pathway, measuring and quantifying mechanistic changes in the pathway's activity remains challenging due to the complexity of the biomolecular systems involved. Systems biology has begun to address this issue with the development of algorithmic tools for analyzing biological pathways; however most of these tools remain accessible only to experts in systems biology with extensive computational experience. Here, we expand upon the user-friendly CellFie tool which quantifies metabolic activity from omic data to include secretory pathway functions, allowing any scientist to infer properties of protein secretion from omic data. We demonstrate how the secretory expansion of CellFie (secCellFie) can help predict metabolic and secretory functions across diverse immune cells, hepatokine secretion in a cell model of NAFLD, and antibody production in Chinese Hamster Ovary cells.

Senescence: An Identity Crisis Originating from Deep Within the Nucleus

Cellular senescence is implicated in a wide range of physiological and pathological conditions throughout an organism's entire lifetime. In particular, it has become evident that senescence plays a causative role in aging and age-associated disorders. This is not due simply to the loss of function of senescent cells. Instead, the substantial alterations of the cellular activities of senescent cells, especially the array of secretory factors, impact the surrounding tissues or even entire organisms. Such non-cell-autonomous functionality is largely coordinated by tissue-specific genes, constituting a cell fate-determining state. Senescence can be viewed as a gain-of-function phenotype or a process of cell identity shift. Cellular functionality or lineage-specific gene expression is tightly linked to the cell type-specific epigenetic landscape, reinforcing the heterogeneity of senescence across cell types. Here, we aim to define the senescence cellular functionality and epigenetic features that may contribute to the gain-of-function phenotype.

Regulation of the COPII secretory machinery via focal adhesions and extracellular matrix signaling

Proteins that enter the secretory pathway are transported from their place of synthesis in the endoplasmic reticulum to the Golgi complex by COPII-coated carriers. The networks of proteins that regulate these components in response to extracellular cues have remained largely elusive. Using high-throughput microscopy, we comprehensively screened 378 cytoskeleton-associated and related proteins for their functional interaction with the coat protein complex II (COPII) components SEC23A and SEC23B. Among these, we identified a group of proteins associated with focal adhesions (FERMT2, MACF1, MAPK8IP2, NGEF, PIK3CA, and ROCK1) that led to the downregulation of SEC23A when depleted by siRNA. Changes in focal adhesions induced by plating cells on ECM also led to the downregulation of SEC23A and decreases in VSVG transport from ER to Golgi. Both the expression of SEC23A and the transport defect could be rescued by treatment with a focal adhesion kinase inhibitor. Altogether, our results identify a network of cytoskeleton-associated proteins connecting focal adhesions and ECM-related signaling with the gene expression of the COPII secretory machinery and trafficking.

Enhanced metabolism and negative regulation of ER stress support higher erythropoietin production in HEK293 cells

Recombinant protein production can cause severe stress on cellular metabolism, resulting in limited titer and product quality. To investigate cellular and metabolic characteristics associated with these limitations, we compare HEK293 clones producing either erythropoietin (EPO) (secretory) or GFP (non-secretory) protein at different rates. Transcriptomic and functional analyses indicate significantly higher metabolism and oxidative phosphorylation in EPO producers compared with parental and GFP cells. In addition, ribosomal genes exhibit specific expression patterns depending on the recombinant protein and the production rate. In a clone displaying a dramatically increased EPO secretion, we detect higher gene expression related to negative regulation of endoplasmic reticulum (ER) stress, including upregulation of ATF6B, which aids EPO production in a subset of clones by overexpression or small interfering RNA (siRNA) knockdown. Our results offer potential target pathways and genes for further development of the secretory power in mammalian cell factories.

Harnessing secretory pathway differences between HEK293 and CHO to rescue production of difficult to express proteins

Biologics represent the fastest growing group of therapeutics, but many advanced recombinant protein moieties remain difficult to produce. Here, we identify metabolic engineering targets limiting expression of recombinant human proteins through a systems biology analysis of the transcriptomes of CHO and HEK293 during recombinant expression. In an expression comparison of 24 difficult to express proteins, one third of the challenging human proteins displayed improved secretion upon host cell swapping from CHO to HEK293. Guided by a comprehensive transcriptomics comparison between cell lines, especially highlighting differences in secretory pathway utilization, a co-expression screening of 21 secretory pathway components validated ATF4, SRP9, JUN, PDIA3 and HSPA8 as productivity boosters in CHO. Moreover, more heavily glycosylated products benefitted more from the elevated activities of the N- and O-glycosyltransferases found in HEK293. Collectively, our results demonstrate the utilization of HEK293 for expression rescue of human proteins and suggest a methodology for identification of secretory pathway components for metabolic engineering of HEK293 and CHO.

Radioresistance of Human Cancers: Clinical Implications of Genetic Expression Signatures

Although radiotherapy is given to more than 50% of cancer patients, little progress has been made in identifying optimal radiotherapy - drug combinations to improve treatment efficacy. Using molecular data from The Cancer Genome Atlas (TCGA), we extracted a total of 1016 cancer patients that received radiotherapy. The patients were diagnosed with head-and-neck (HNSC - 294 patients), cervical (CESC - 166 patients) and breast (BRCA - 549 patients) cancer. We analyzed mRNA expression patterns of 50 hallmark gene sets of the MSigDB collection, which we divided in eight categories based on a shared biological or functional process. Tumor samples were split into upregulated, neutral or downregulated mRNA expression for all gene sets using a gene set analysis (GSEA) pre-ranked analysis and assessed for their clinical relevance. We found a prognostic association between three of the eight gene set categories (Radiobiological, Metabolism and Proliferation) and overall survival in all three cancer types. Furthermore, multiple single associations were revealed in the other categories considered. To the best of our knowledge, our study is the first report suggesting clinical relevance of molecular characterization based on hallmark gene sets to refine radiation strategies.

Dysregulation of the secretory pathway connects Alzheimer's disease genetics to aggregate formation

Amyloid disorders such as Alzheimer's disease (AD) involve the aggregation of secreted proteins. However, it is largely unclear how secretory-pathway proteins contribute to amyloid formation. We developed a systems biology framework integrating expression data with protein-protein interaction networks to estimate a tissue's fitness for producing specific secreted proteins and analyzed the fitness of the secretory pathway of various brain regions and cell types for synthesizing the AD-associated amyloid precursor protein (APP). While key amyloidogenic pathway components were not differentially expressed in AD brains, we found Aβ deposition correlates with systemic down- and upregulation of the secretory-pathway components proximal to APP and amyloidogenic secretases, respectively, in AD. Our analyses suggest that perturbations from three AD risk loci cascade through the APP secretory-support network and into the endocytosis pathway, connecting amyloidogenesis to dysregulation of secretory-pathway components supporting APP and suggesting novel therapeutic targets for AD. A record of this paper's transparent peer review process is included in the supplemental information.

A unique esophageal extracellular matrix proteome alters normal fibroblast function in severe eosinophilic esophagitis

BACKGROUND

Eosinophilic esophagitis (EoE) is a chronic TH2 disorder complicated by tissue fibrosis and loss of esophageal luminal patency. The fibrostenotic esophagus does not respond well to therapy, but profibrotic therapeutic targets are largely unclear.

OBJECTIVE

Our aim was to utilize proteomics and primary cells as a novel approach to determine relevant profibrotic factors.

METHODS

We utilized primary esophageal EoE and normal fibroblasts, their derivative extracellular matrixes (ECMs), an approach of fibroblast culture on autologous versus nonautologous ECM, and proteomics to elucidate EoE ECM proteins that dysregulate cellular function.

RESULTS

We cultured esophageal fibroblasts from normal esophagi and esophagi from patients with severe EoE on autologous versus nonautologous ECM. The EoE ECM proteome shifted normal esophageal fibroblast protein expression. Proteomic analysis demonstrated that thrombospondin-1 is detected only in the EoE ECM, is central in the EoE ECM protein-protein interactome, is found at significantly elevated levels in biopsy specimens from patients with active EoE, and induces fibroblast collagen I production.

CONCLUSION

Fibroblasts from patients with EoE secrete a unique ECM proteome that reflects their in vivo state and induces collagen I and α-smooth muscle actin protein expression from normal fibroblasts. Thrombospondin-1 is a previously unappreciated profibrotic molecule in EoE.

Machine learning-based investigation of the cancer protein secretory pathway

Deregulation of the protein secretory pathway (PSP) is linked to many hallmarks of cancer, such as promoting tissue invasion and modulating cell-cell signaling. The collection of secreted proteins processed by the PSP, known as the secretome, is often studied due to its potential as a reservoir of tumor biomarkers. However, there has been less focus on the protein components of the secretory machinery itself. We therefore investigated the expression changes in secretory pathway components across many different cancer types. Specifically, we implemented a dual approach involving differential expression analysis and machine learning to identify PSP genes whose expression was associated with key tumor characteristics: mutation of p53, cancer status, and tumor stage. Eight different machine learning algorithms were included in the analysis to enable comparison between methods and to focus on signals that were robust to algorithm type. The machine learning approach was validated by identifying PSP genes known to be regulated by p53, and even outperformed the differential expression analysis approach. Among the different analysis methods and cancer types, the kinesin family members KIF20A and KIF23 were consistently among the top genes associated with malignant transformation or tumor stage. However, unlike most cancer types which exhibited elevated KIF20A expression that remained relatively constant across tumor stages, renal carcinomas displayed a more gradual increase that continued with increasing disease severity. Collectively, our study demonstrates the complementary nature of a combined differential expression and machine learning approach for analyzing gene expression data, and highlights key PSP components relevant to features of tumor pathophysiology that may constitute potential therapeutic targets.

The secretory pathway is a series of intracellular compartments and enzymes that process and export proteins from the cell to its surrounding environment. Dysfunction of the secretory pathway is associated with many diseases, including cancer, and therefore constitutes a potential target for novel therapeutic strategies. The large number of interacting components that comprise the secretory pathway pose a challenge when attempting to identify where the dysfunction originates or how to restore healthy function. To improve our understanding of how the secretory pathway is changed within tumors, we used gene expression data from normal tissue and tumor samples from thousands of individuals which included many different types of cancers. The data was analyzed using different machine learning algorithms which we trained to predict sample characteristics, such as disease severity. This training quantified the relative degree to which each gene was associated with the tumor characteristic, allowing us to predict which secretory pathway components were important for processes such as tumor progression—both within specific cancer types and across many different cancer types. The machine learning-based approach demonstrated excellent performance compared to traditional gene expression analysis methods and identified several secretory pathway components with strong evidence of involvement in tumor development.

Nuclear receptors FXR and SHP regulate protein N-glycan modifications in the liver

Nuclear receptors farnesoid X receptor (FXR) and small heterodimer partner (SHP) are key regulators of metabolism. Here, we report a previously unknown function for the hepatic FXR-SHP axis in controlling protein N-linked glycosylation. Transcriptome analysis in liver-specific Fxr-Shp double knockout (LDKO) livers revealed induction of genes encoding enzymes in the N-glycosylation pathway, including Mgat5, Fut8, St3gal6, and St6gal1 FXR activation suppressed Mgat5, while Shp deletion induced St3gal6 and St6gal1 Increased percentages of core-fucosylated and triantennary glycan moieties were seen in LDKO livers, and proteins with the "hyperglycoforms" preferentially localized to exosomes and lysosomes. This up-regulation of N-glycosylation machinery was specific to the Golgi apparatus and not the endoplasmic reticulum. The increased glycan complexity in the LDKO correlated well with dilated unstacked Golgi ribbons and alterations in the secretion of albumin, cholesterol, and triglycerides. Our findings demonstrate a role for the FXR-SHP axis in maintaining glycoprotein diversity in the liver.

In situ detection of protein interactions for recombinant therapeutic enzymes

Despite their therapeutic potential, many protein drugs remain inaccessible to patients since they are difficult to secrete. Each recombinant protein has unique physicochemical properties and requires different machinery for proper folding, assembly, and posttranslational modifications (PTMs). Here we aimed to identify the machinery supporting recombinant protein secretion by measuring the protein-protein interaction (PPI) networks of four different recombinant proteins (SERPINA1, SERPINC1, SERPING1, and SeAP) with various PTMs and structural motifs using the proximity-dependent biotin identification (BioID) method. We identified PPIs associated with specific features of the secreted proteins using a Bayesian statistical model and found proteins involved in protein folding, disulfide bond formation, and N-glycosylation were positively correlated with the corresponding features of the four model proteins. Among others, oxidative folding enzymes showed the strongest association with disulfide bond formation, supporting their critical roles in proper folding and maintaining the ER stability. Knockdown of disulfide-isomerase PDIA4, a measured interactor with significance for SERPINC1 but not SERPINA1, led to the decreased secretion of SERPINC1, which relies on its extensive disulfide bonds, compared to SERPINA1, which has no disulfide bonds. Proximity-dependent labeling successfully identified the transient interactions supporting synthesis of secreted recombinant proteins and refined our understanding of key molecular mechanisms of the secretory pathway during recombinant protein production.

Functional Pro-metastatic Heterogeneity Revealed by Spiked-scRNAseq Is Shaped by Cancer Cell Interactions and Restricted by VSIG1

How cells with metastatic potential, or pro-metastatic states, arise within heterogeneous primary tumors remains unclear. Here, we have used one index primary colon cancer to develop spiked-scRNAseq to link omics-defined single-cell clusters with cell behavior. Using spiked-scRNAseq we uncover cell populations with differential metastatic potential in which pro-metastatic states are correlated with the expression of signaling and vesicle-trafficking genes. Analyzing such heterogeneity, we define an anti-metastatic, non-cell-autonomous interaction originating from non-/low-metastatic cells, and identify membrane VSIG1 as a critical mediator of this interaction. VSIG1 acts to restrict the development of pro-metastatic states autonomously and non-cell autonomously, in part by inhibiting YAP/TAZ-TEAD signaling. As VSIG1 re-expression is able to reduce metastatic behavior from multiple colon cancer cell types, the regulation of VSIG1 or its effectors opens new interventional opportunities. In general, we propose that crosstalk between cancer cells, including the action of VSIG1, dynamically defines the degree of pro-metastatic intra-tumoral heterogeneity.

A Quantitative Proteome Map of the Human Body

Determining protein levels in each tissue and how they compare with RNA levels is important for understanding human biology and disease as well as regulatory processes that control protein levels. We quantified the relative protein levels from over 12,000 genes across 32 normal human tissues. Tissue-specific or tissue-enriched proteins were identified and compared to transcriptome data. Many ubiquitous transcripts are found to encode tissue-specific proteins. Discordance of RNA and protein enrichment revealed potential sites of synthesis and action of secreted proteins. The tissue-specific distribution of proteins also provides an in-depth view of complex biological events that require the interplay of multiple tissues. Most importantly, our study demonstrated that protein tissue-enrichment information can explain phenotypes of genetic diseases, which cannot be obtained by transcript information alone. Overall, our results demonstrate how understanding protein levels can provide insights into regulation, secretome, metabolism, and human diseases.

IMPAD1 and KDELR2 drive invasion and metastasis by enhancing Golgi-mediated secretion

Non-small cell lung cancer (NSCLC) is the deadliest form of cancer worldwide, due in part to its proclivity to metastasize. Identifying novel drivers of invasion and metastasis holds therapeutic potential for the disease. We conducted a gain-of-function invasion screen, which identified two separate hits, IMPAD1 and KDELR2, as robust, independent drivers of lung cancer invasion and metastasis. Given that IMPAD1 and KDELR2 are known to be localized to the ER-Golgi pathway, we studied their common mechanism of driving in vitro invasion and in vivo metastasis and demonstrated that they enhance Golgi-mediated function and secretion. Therapeutically inhibiting matrix metalloproteases (MMPs) suppressed both IMPAD1- and KDELR2-mediated invasion. The hits from this unbiased screen and the mechanistic validation highlight Golgi function as one of the key cellular features altered during invasion and metastasis.

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

In mammalian cells, >25% of synthesized proteins are exported through the secretory pathway. The pathway complexity, however, obfuscates its impact on the secretion of different proteins. Unraveling its impact on diverse proteins is particularly important for biopharmaceutical production. Here we delineate the core secretory pathway functions and integrate them with genome-scale metabolic reconstructions of human, mouse, and Chinese hamster ovary cells. The resulting reconstructions enable the computation of energetic costs and machinery demands of each secreted protein. By integrating additional omics data, we find that highly secretory cells have adapted to reduce expression and secretion of other expensive host cell proteins. Furthermore, we predict metabolic costs and maximum productivities of biotherapeutic proteins and identify protein features that most significantly impact protein secretion. Finally, the model successfully predicts the increase in secretion of a monoclonal antibody after silencing a highly expressed selection marker. This work represents a knowledgebase of the mammalian secretory pathway that serves as a novel tool for systems biotechnology.

A Systematic Investigation of the Malignant Functions and Diagnostic Potential of the Cancer Secretome

The collection of proteins secreted from a cell-the secretome-is of particular interest in cancer pathophysiology due to its diagnostic potential and role in tumorigenesis. However, cancer secretome studies are often limited to one tissue or cancer type or focus on biomarker prediction without exploring the associated functions. We therefore conducted a pan-cancer analysis of secretome gene expression changes to identify candidate diagnostic biomarkers and to investigate the underlying biological function of these changes. Using transcriptomic data spanning 32 cancer types and 30 healthy tissues, we quantified the relative diagnostic potential of secretome proteins for each cancer. Furthermore, we offer a potential mechanism by which cancer cells relieve secretory pathway stress by decreasing the expression of tissue-specific genes, thereby facilitating the secretion of proteins promoting invasion and proliferation. These results provide a more systematic understanding of the cancer secretome, facilitating its use in diagnostics and its targeting for therapeutic development.

Intrasurgical Protein Layer on Titanium Arthroplasty Explants: From the Big Twelve to the Implant Proteome

PURPOSE

Aseptic loosening in total joint replacement due to insufficient osteointegration is an unsolved problem in orthopaedics. The purpose of the study is to obtain a picture of the initial protein adsorption layer on femoral endoprosthetic surfaces as the key to the initiation of osseointegration.

EXPERIMENTAL DESIGN

The paper describes the first study of femoral stem explants from patients for proteome analysis of the primary protein layer. After 2 min in situ, the stems are explanted and frozen in liquid nitrogen. Proteins are eluted under reducing conditions and analyzed by LC-MS/MS.

RESULTS

After exclusion of proteins identified by a single peptide, the implant proteome is found to consist of 2802 unique proteins. Of these, 77% are of intracellular origin, 9% are derived from the plasma proteome, 8% from the bone proteome, and four proteins with highest specificity score could be assigned to the bone marrow proteome (transcriptome). The most abundant protein in the adsorbed total protein layer is hemoglobin (8-11%) followed by serum albumin (3.6-6%).

CONCLUSIONS

A detailed knowledge of the initial protein film deposited onto the implants, as demonstrated here for the first time, may help to understand and predict the response of the osseous microenvironment to implant surfaces.

The emerging role of systems biology for engineering protein production in CHO cells

To meet the ever-growing demand for effective, safe, and affordable protein therapeutics, decades of intense efforts have aimed to maximize the quantity and quality of recombinant proteins produced in CHO cells. Bioprocessing innovations and cell engineering efforts have improved product titer; however, uncharacterized cellular processes and gene regulatory mechanisms still hinder cell growth, specific productivity, and protein quality. Herein, we summarize recent advances in systems biology and data-driven approaches aiming to unravel how molecular pathways, cellular processes, and extrinsic factors (e.g. media supplementation) influence recombinant protein production. In particular, as the available omics data for CHO cells continue to grow, predictive models and screens will be increasingly used to unravel the biological drivers of protein production, which can be used with emerging genome editing technologies to rationally engineer cells to further control the quantity, quality and affordability of many biologic drugs.