An anti-TNF-glucocorticoid receptor modulator antibody-drug conjugate is efficacious against immune-mediated inflammatory diseases.

Glucocorticoids (GCs) are efficacious drugs used for treating many inflammatory diseases, but the dose and duration of administration are limited because of severe side effects. We therefore sought to identify an approach to selectively target GCs to inflamed tissue. Previous work identified that anti-tumor necrosis factor (TNF) antibodies that bind to transmembrane TNF undergo internalization; therefore, an anti-TNF antibody-drug conjugate (ADC) would be mechanistically similar, where lysosomal catabolism could release a GC receptor modulator (GRM) payload to dampen immune cell activity. Consequently, we have generated an anti-TNF-GRM ADC with the aim of inhibiting pro-inflammatory cytokine production from stimulated human immune cells. In an acute mouse model of contact hypersensitivity, a murine surrogate anti-TNF-GRM ADC inhibited inflammatory responses with minimal effect on systemic GC biomarkers. In addition, in a mouse model of collagen-induced arthritis, single-dose administration of the ADC, delivered at disease onset, was able to completely inhibit arthritis for greater than 30 days, whereas an anti-TNF monoclonal antibody only partially inhibited disease. ADC treatment at the peak of disease was also able to attenuate the arthritic phenotype. Clinical data for a human anti-TNF-GRM ADC (ABBV-3373) from a single ascending dose phase 1 study in healthy volunteers demonstrated antibody-like pharmacokinetic profiles and a lack of impact on serum cortisol concentrations at predicted therapeutic doses. These data suggest that an anti-TNF-GRM ADC may provide improved efficacy beyond anti-TNF alone in immune mediated diseases while minimizing systemic side effects associated with standard GC treatment.

Identification of Plasma Biomarkers from Rheumatoid Arthritis Patients Using an Optimized Sequential Window Acquisition of All THeoretical Mass Spectra (SWATH) Proteomics Workflow.

Rheumatoid arthritis (RA) is a systemic autoimmune and inflammatory disease. Plasma biomarkers are critical for understanding disease mechanisms, treatment effects, and diagnosis. Mass spectrometry-based proteomics is a powerful tool for unbiased biomarker discovery. However, plasma proteomics is significantly hampered by signal interference from high-abundance proteins, low overall protein coverage, and high levels of missing data from data-dependent acquisition (DDA). To achieve quantitative proteomics analysis for plasma samples with a balance of throughput, performance, and cost, we developed a workflow incorporating plate-based high abundance protein depletion and sample preparation, comprehensive peptide spectral library building, and data-independent acquisition (DIA) SWATH mass spectrometry-based methodology. In this study, we analyzed plasma samples from both RA patients and healthy donors. The results showed that the new workflow performance exceeded that of the current state-of-the-art depletion-based plasma proteomic platforms in terms of both data quality and proteome coverage. Proteins from biological processes related to the activation of systemic inflammation, suppression of platelet function, and loss of muscle mass were enriched and differentially expressed in RA. Some plasma proteins, particularly acute-phase reactant proteins, showed great power to distinguish between RA patients and healthy donors. Moreover, protein isoforms in the plasma were also analyzed, providing even deeper proteome coverage. This workflow can serve as a basis for further application in discovering plasma biomarkers of other diseases.

Epithelial dysfunction is prevented by IL-22 treatment in a Citrobacter rodentium-induced colitis model that shares similarities with inflammatory bowel disease.

Inflammatory bowel disease (IBD) is characterized by a dysregulated intestinal epithelial barrier leading to breach of barrier immunity. Here we identified similar protein expression changes between IBD and Citrobacter rodentium-infected FVB mice with respect to dysregulation of solute transporters as well as components critical for intestinal barrier integrity. We attribute the disease associated changes in the model to the emergence of undifferentiated intermediate intestinal epithelial cells. Prophylactic treatment with IL-22.Fc in C. rodentium-infected FVB mice reduced disease severity and rescued the mice from lethality. Multi-omics and solute analyses revealed that IL-22.Fc treatment prevented disease-associated changes including disruption of the solute transporter machinery and restored proper physiological functions of the intestine, respectively. Taken together, we established the disease relevance of the C. rodentium-induced colitis model to IBD, demonstrated the protective role of IL-22 in amelioration of epithelial dysfunction and elucidated the molecular mechanisms with IL-22's effect on intestinal epithelial cells.

RP58 Represses Transcriptional Programs Linked to Nonneuronal Cell Identity and Glioblastoma Subtypes in Developing Neurons.

How mammalian neuronal identity is progressively acquired and reinforced during development is not understood. We have previously shown that loss of RP58 (ZNF238 or ZBTB18), a BTB/POZ-zinc finger-containing transcription factor, in the mouse brain leads to microcephaly, corpus callosum agenesis, and cerebellum hypoplasia and that it is required for normal neuronal differentiation. The transcriptional programs regulated by RP58 during this process are not known. Here, we report for the first time that in embryonic mouse neocortical neurons a complex set of genes normally expressed in other cell types, such as those from mesoderm derivatives, must be actively repressed in vivo and that RP58 is a critical regulator of these repressed transcriptional programs. Importantly, gene set enrichment analysis (GSEA) analyses of these transcriptional programs indicate that repressed genes include distinct sets of genes significantly associated with glioma progression and/or pluripotency. We also demonstrate that reintroducing RP58 in glioma stem cells leads not only to aspects of neuronal differentiation but also to loss of stem cell characteristics, including loss of stem cell markers and decrease in stem cell self-renewal capacities. Thus, RP58 acts as an in vivo master guardian of the neuronal identity transcriptome, and its function may be required to prevent brain disease development, including glioma progression.

Distinct mechanisms control genome recognition by p53 at its target genes linked to different cell fates.

The tumor suppressor p53 integrates stress response pathways by selectively engaging one of several potential transcriptomes, thereby triggering cell fate decisions (e.g., cell cycle arrest, apoptosis). Foundational to this process is the binding of tetrameric p53 to 20-bp response elements (REs) in the genome (RRRCWWGYYYN0-13RRRCWWGYYY). In general, REs at cell cycle arrest targets (e.g. p21) are of higher affinity than those at apoptosis targets (e.g., BAX). However, the RE sequence code underlying selectivity remains undeciphered. Here, we identify molecular mechanisms mediating p53 binding to high- and low-affinity REs by showing that key determinants of the code are embedded in the DNA shape. We further demonstrate that differences in minor/major groove widths, encoded by G/C or A/T bp content at positions 3, 8, 13, and 18 in the RE, determine distinct p53 DNA-binding modes by inducing different Arg248 and Lys120 conformations and interactions. The predictive capacity of this code was confirmed in vivo using genome editing at the BAX RE to interconvert the DNA-binding modes, transcription pattern, and cell fate outcome.

A comparative study of evaluating missing value imputation methods in label-free proteomics.

The presence of missing values (MVs) in label-free quantitative proteomics greatly reduces the completeness of data. Imputation has been widely utilized to handle MVs, and selection of the proper method is critical for the accuracy and reliability of imputation. Here we present a comparative study that evaluates the performance of seven popular imputation methods with a large-scale benchmark dataset and an immune cell dataset. Simulated MVs were incorporated into the complete part of each dataset with different combinations of MV rates and missing not at random (MNAR) rates. Normalized root mean square error (NRMSE) was applied to evaluate the accuracy of protein abundances and intergroup protein ratios after imputation. Detection of true positives (TPs) and false altered-protein discovery rate (FADR) between groups were also compared using the benchmark dataset. Furthermore, the accuracy of handling real MVs was assessed by comparing enriched pathways and signature genes of cell activation after imputing the immune cell dataset. We observed that the accuracy of imputation is primarily affected by the MNAR rate rather than the MV rate, and downstream analysis can be largely impacted by the selection of imputation methods. A random forest-based imputation method consistently outperformed other popular methods by achieving the lowest NRMSE, high amount of TPs with the average FADR < 5%, and the best detection of relevant pathways and signature genes, highlighting it as the most suitable method for label-free proteomics.

A multicenter study benchmarking single-cell RNA sequencing technologies using reference samples.

Comparing diverse single-cell RNA sequencing (scRNA-seq) datasets generated by different technologies and in different laboratories remains a major challenge. Here we address the need for guidance in choosing algorithms leading to accurate biological interpretations of varied data types acquired with different platforms. Using two well-characterized cellular reference samples (breast cancer cells and B cells), captured either separately or in mixtures, we compared different scRNA-seq platforms and several preprocessing, normalization and batch-effect correction methods at multiple centers. Although preprocessing and normalization contributed to variability in gene detection and cell classification, batch-effect correction was by far the most important factor in correctly classifying the cells. Moreover, scRNA-seq dataset characteristics (for example, sample and cellular heterogeneity and platform used) were critical in determining the optimal bioinformatic method. However, reproducibility across centers and platforms was high when appropriate bioinformatic methods were applied. Our findings offer practical guidance for optimizing platform and software selection when designing an scRNA-seq study.

Immunopathogenesis of hidradenitis suppurativa and response to anti-TNF-α therapy.

Hidradenitis suppurativa (HS) is a highly prevalent, morbid inflammatory skin disease with limited treatment options. The major cell types and inflammatory pathways in skin of patients with HS are poorly understood, and which patients will respond to TNF-α blockade is currently unknown. We discovered that clinically and histologically healthy appearing skin (i.e., nonlesional skin) is dysfunctional in patients with HS with a relative loss of immune regulatory pathways. HS skin lesions were characterized by quantitative and qualitative dysfunction of type 2 conventional dendritic cells, relatively reduced regulatory T cells, an influx of memory B cells, and a plasma cell/plasmablast infiltrate predominantly in end-stage fibrotic skin. At the molecular level, there was a relative bias toward the IL-1 pathway and type 1 T cell responses when compared with both healthy skin and psoriatic patient skin. Anti-TNF-α therapy markedly attenuated B cell activation with minimal effect on other inflammatory pathways. Finally, we identified an immune activation signature in skin before anti-TNF-α treatment that correlated with subsequent lack of response to this modality. Our results reveal the fundamental immunopathogenesis of HS and provide a molecular foundation for future studies focused on stratifying patients based on likelihood of clinical response to TNF-α blockade.

Persistence of Inflammatory Phenotype in Residual Psoriatic Plaques in Patients on Effective Biologic Therapy.

Many psoriasis patients treated with biologics do not achieve total skin clearance. These patients possess residual plaques despite ongoing biologic treatment. To elucidate mechanisms of plaque persistence despite overall good drug response, we studied 50 subjects: psoriasis patients with residual plaques treated with one of three different biologics, untreated patients, and healthy controls. Skin biopsies from all subjects were characterized using three methods: mRNA expression, histology, and FACS of hematopoietic skin cells. Although all three methods provided evidence of drug effect, gene expression analysis revealed the persistence of key psoriasis pathways in treated plaques, including granulocyte adhesion and diapedesis, T helper type17 activation pathway, and interferon signaling with no novel pathways emerging. Focal decreases in parakeratosis and keratinocyte proliferation and differential reduction in IL-17 producing CD103- T cells, but no change in CD103+ tissue-resident memory T cells were observed. Of note, antitumor necrosis factor increased the interferon signaling pathway already present. Interestingly mast cells were the dominant source of IL-22 in all psoriasis subjects. These data suggest that while subtle differences can be observed in drug-treated plaques, underlying biologic mechanisms are similar to those present in untreated psoriatic lesions.

Immune landscapes associated with different glioblastoma molecular subtypes.

Recent work has highlighted the tumor microenvironment as a central player in cancer. In particular, interactions between tumor and immune cells may help drive the development of brain tumors such as glioblastoma multiforme (GBM). Despite significant research into the molecular classification of glioblastoma, few studies have characterized in a comprehensive manner the immune infiltrate in situ and within different GBM subtypes.In this study, we use an unbiased, automated immunohistochemistry-based approach to determine the immune phenotype of the four GBM subtypes (classical, mesenchymal, neural and proneural) in a cohort of 98 patients. Tissue Micro Arrays (TMA) were stained for CD20 (B lymphocytes), CD5, CD3, CD4, CD8 (T lymphocytes), CD68 (microglia), and CD163 (bone marrow derived macrophages) antibodies. Using automated image analysis, the percentage of each immune population was calculated with respect to the total tumor cells. Mesenchymal GBMs displayed the highest percentage of microglia, macrophage, and lymphocyte infiltration. CD68+ and CD163+ cells were the most abundant cell populations in all four GBM subtypes, and a higher percentage of CD163+ cells was associated with a worse prognosis. We also compared our results to the relative composition of immune cell type infiltration (using RNA-seq data) across TCGA GBM tumors and validated our results obtained with immunohistochemistry with an external cohort and a different method. The results of this study offer a comprehensive analysis of the distribution and the infiltration of the immune components across the four commonly described GBM subgroups, setting the basis for a more detailed patient classification and new insights that may be used to better apply or design immunotherapies for GBM.

Integrative Analysis of Transcriptomic and Proteomic Profiling in Inflammatory Bowel Disease Colon Biopsies.

BACKGROUND: Crohn's disease (CD) and ulcerative colitis (UC) are intestinal chronic inflammatory conditions characterized by altered epithelial barrier function and tissue damage. Despite significant efforts to understanding the biological mechanisms responsible for gut inflammation, the pathophysiology of CD and UC remains poorly understood. METHODS: To help elucidate the potential mechanisms responsible for gut inflammation in CD and UC, transcriptomic and proteomic profiling of human colon biopsy specimens was performed. Dysregulated genes and proteins in disease tissues compared with normal tissues were characterized from the expression profiles and further subjected to pathway analysis to identify altered biological processes and signaling pathways. RESULTS: Sample analysis showed 4250 genes with matched protein expression and a wide range of correlation of RNA-protein abundance across samples. Pathway analysis of dysregulated genes and proteins in CD and UC showed alterations in immune and inflammatory responses, complement cascade, and the suppression of metabolic processes and PPAR signaling. In CD, increased T-helper cell differentiation and elevated toll-like receptor and JAK/STAT signaling were observed. Interestingly, increased MAPK signaling was only observed in UC. Weighted gene co-expression network analysis suggested a possible role of epigenetic regulation in UC. Of note, a large discrepancy between regulation of RNA and protein levels in inflamed colon samples was detected for previously identified biomarkers including MMP14 and LAMP1. CONCLUSIONS: With the analysis of dysregulated genes and pathways, the present study unravels key mechanisms contributing to CD and UC pathogenesis and emphasizes that integrative analysis of multi-omics data sets can provide more insight into understanding complex disease mechanisms.

Exome sequencing identifies gene variants and networks associated with extreme respiratory outcomes following preterm birth.

BACKGROUND: Previous studies have identified genetic variants associated with bronchopulmonary dysplasia (BPD) in extremely preterm infants. However, findings with genome-wide significance have been rare, and not replicated. We hypothesized that whole exome sequencing (WES) of premature subjects with extremely divergent phenotypic outcomes could facilitate the identification of genetic variants or gene networks contributing disease risk. RESULTS: The Prematurity and Respiratory Outcomes Program (PROP) recruited a cohort of > 765 extremely preterm infants for the identification of markers of respiratory morbidity. We completed WES on 146 PROP subjects (85 affected, 61 unaffected) representing extreme phenotypes of early respiratory morbidity. We tested for association between disease status and individual common variants, screened for rare variants exclusive to either affected or unaffected subjects, and tested the combined association of variants across gene loci. Pathway analysis was performed and disease-related expression patterns were assessed. Marginal association with BPD was observed for numerous common and rare variants. We identified 345 genes with variants unique to BPD-affected preterm subjects, and 292 genes with variants unique to our unaffected preterm subjects. Of these unique variants, 28 (19 in the affected cohort and 9 in unaffected cohort) replicate a prior WES study of BPD-associated variants. Pathway analysis of sets of variants, informed by disease-related gene expression, implicated protein kinase A, MAPK and Neuregulin/epidermal growth factor receptor signaling. CONCLUSIONS: We identified novel genes and associated pathways that may play an important role in susceptibility/resilience for the development of lung disease in preterm infants.

Characterization of brain tumor initiating cells isolated from an animal model of CNS primitive neuroectodermal tumors.

CNS Primitive Neuroectodermal tumors (CNS-PNETs) are members of the embryonal family of malignant childhood brain tumors, which remain refractory to current therapeutic treatments. Current paradigm of brain tumorigenesis implicates brain tumor-initiating cells (BTIC) in the onset of tumorigenesis and tumor maintenance. However, despite their significance, there is currently no comprehensive characterization of CNS-PNETs BTICs. Recently, we described an animal model of CNS-PNET generated by orthotopic transplantation of human Radial Glial (RG) cells - the progenitor cells for adult neural stem cells (NSC) - into NOD-SCID mice brain and proposed that BTICs may play a role in the maintenance of these tumors. Here we report the characterization of BTIC lines derived from this CNS-PNET animal model. BTIC's orthotopic transplantation generated highly aggressive tumors also characterized as CNS-PNETs. The BTICs have the hallmarks of NSCs as they demonstrate self-renewing capacity and have the ability to differentiate into astrocytes and early migrating neurons. Moreover, the cells demonstrate aberrant accumulation of wild type tumor-suppressor protein p53, indicating its functional inactivation, highly up-regulated levels of onco-protein cMYC and the BTIC marker OCT3/4, along with metabolic switch to glycolysis - suggesting that these changes occurred in the early stages of tumorigenesis. Furthermore, based on RNA- and DNA-seq data, the BTICs did not acquire any transcriptome-changing genomic alterations indicating that the onset of tumorigenesis may be epigenetically driven. The study of these BTIC self-renewing cells in our model may enable uncovering the molecular alterations that are responsible for the onset and maintenance of the malignant PNET phenotype.

Identifying the substrate proteins of U-box E3s E4B and CHIP by orthogonal ubiquitin transfer.

E3 ubiquitin (UB) ligases E4B and carboxyl terminus of Hsc70-interacting protein (CHIP) use a common U-box motif to transfer UB from E1 and E2 enzymes to their substrate proteins and regulate diverse cellular processes. To profile their ubiquitination targets in the cell, we used phage display to engineer E2-E4B and E2-CHIP pairs that were free of cross-reactivity with the native UB transfer cascades. We then used the engineered E2-E3 pairs to construct "orthogonal UB transfer (OUT)" cascades so that a mutant UB (xUB) could be exclusively used by the engineered E4B or CHIP to label their substrate proteins. Purification of xUB-conjugated proteins followed by proteomics analysis enabled the identification of hundreds of potential substrates of E4B and CHIP in human embryonic kidney 293 cells. Kinase MAPK3 (mitogen-activated protein kinase 3), methyltransferase PRMT1 (protein arginine N-methyltransferase 1), and phosphatase PPP3CA (protein phosphatase 3 catalytic subunit alpha) were identified as the shared substrates of the two E3s. Phosphatase PGAM5 (phosphoglycerate mutase 5) and deubiquitinase OTUB1 (ovarian tumor domain containing ubiquitin aldehyde binding protein 1) were confirmed as E4B substrates, and ß-catenin and CDK4 (cyclin-dependent kinase 4) were confirmed as CHIP substrates. On the basis of the CHIP-CDK4 circuit identified by OUT, we revealed that CHIP signals CDK4 degradation in response to endoplasmic reticulum stress.

Identifying the ubiquitination targets of E6AP by orthogonal ubiquitin transfer.

E3 ubiquitin (UB) ligases are the ending modules of the E1-E2-E3 cascades that transfer UB to cellular proteins and regulate their biological functions. Identifying the substrates of an E3 holds the key to elucidate its role in cell regulation. Here, we construct an orthogonal UB transfer (OUT) cascade to identify the substrates of E6AP, a HECT E3 also known as Ube3a that is implicated in cancer and neurodevelopmental disorders. We use yeast cell surface display to engineer E6AP to exclusively transfer an affinity-tagged UB variant (xUB) to its substrate proteins. Proteomic identification of xUB-conjugated proteins in HEK293 cells affords 130 potential E6AP targets. Among them, we verify that MAPK1, CDK1, CDK4, PRMT5, ß-catenin, and UbxD8 are directly ubiquitinated by E6AP in vitro and in the cell. Our work establishes OUT as an efficient platform to profile E3 substrates and reveal the cellular circuits mediated by the E3 enzymes.

Cancer-Associated IDH1 Promotes Growth and Resistance to Targeted Therapies in the Absence of Mutation.

Oncogenic mutations in two isocitrate dehydrogenase (IDH)-encoding genes (IDH1 and IDH2) have been identified in acute myelogenous leukemia, low-grade glioma, and secondary glioblastoma (GBM). Our in silico and wet-bench analyses indicate that non-mutated IDH1 mRNA and protein are commonly overexpressed in primary GBMs. We show that genetic and pharmacologic inactivation of IDH1 decreases GBM cell growth, promotes a more differentiated tumor cell state, increases apoptosis in response to targeted therapies, and prolongs the survival of animal subjects bearing patient-derived xenografts (PDXs). On a molecular level, diminished IDH1 activity results in reduced α-ketoglutarate (αKG) and NADPH production, paralleled by deficient carbon flux from glucose or acetate into lipids, exhaustion of reduced glutathione, increased levels of reactive oxygen species (ROS), and enhanced histone methylation and differentiation marker expression. These findings suggest that IDH1 upregulation represents a common metabolic adaptation by GBMs to support macromolecular synthesis, aggressive growth, and therapy resistance.

Stabilization of HIF-1α and HIF-2α, up-regulation of MYCC and accumulation of stabilized p53 constitute hallmarks of CNS-PNET animal model.

Recently, we described a new animal model of CNS primitive neuroectodermal tumors (CNS-PNET), which was generated by orthotopic transplantation of human Radial Glial (RG) cells into NOD-SCID mice's brain sub-ventricular zone. In the current study we conducted comprehensive RNA-Seq analyses to gain insights on the mechanisms underlying tumorigenesis in this mouse model of CNS-PNET. Here we show that the RNA-Seq profiles derived from these tumors cluster with those reported for patients' PNETs. Moreover, we found that (i) stabilization of HIF-1α and HIF-2α, which are involved in mediation of the hypoxic responses in the majority of cell types, (ii) up-regulation of MYCC, a key onco-protein whose dysregulation occurs in ~70% of human tumors, and (iii) accumulation of stabilized p53, which is commonly altered in human cancers, constitute hallmarks of our tumor model, and might represent the basis for CNS-PNET tumorigenesis in this model. We discuss the possibility that these three events might be interconnected. These results indicate that our model may prove invaluable to uncover the molecular events leading to MYCC and TP53 alterations, which would be of broader interest considering their relevance to many human malignancies. Lastly, this mouse model might prove useful for drug screening targeting MYCC and related members of its protein interaction network.

Identification of Genetic and Epigenetic Variants Associated with Breast Cancer Prognosis by Integrative Bioinformatics Analysis.

INTRODUCTION: Breast cancer being a multifaceted disease constitutes a wide spectrum of histological and molecular variability in tumors. However, the task for the identification of these variances is complicated by the interplay between inherited genetic and epigenetic aberrations. Therefore, this study provides an extrapolate outlook to the sinister partnership between DNA methylation and single-nucleotide polymorphisms (SNPs) in relevance to the identification of prognostic markers in breast cancer. The effect of these SNPs on methylation is defined as methylation quantitative trait loci (meQTL). MATERIALS AND METHODS: We developed a novel method to identify prognostic gene signatures for breast cancer by integrating genomic and epigenomic data. This is based on the hypothesis that multiple sources of evidence pointing to the same gene or pathway are likely to lead to reduced false positives. We also apply random resampling to reduce overfitting noise by dividing samples into training and testing data sets. Specifically, the common samples between Illumina 450 DNA methylation, Affymetrix SNP array, and clinical data sets obtained from the Cancer Genome Atlas (TCGA) for breast invasive carcinoma (BRCA) were randomly divided into training and test models. An intensive statistical analysis based on log-rank test and Cox proportional hazard model has established a significant association between differential methylation and the stratification of breast cancer patients into high- and low-risk groups, respectively. RESULTS: The comprehensive assessment based on the conjoint effect of CpG-SNP pair has guided in delaminating the breast cancer patients into the high- and low-risk groups. In particular, the most significant association was found with respect to cg05370838-rs2230576, cg00956490-rs940453, and cg11340537-rs2640785 CpG-SNP pairs. These CpG-SNP pairs were strongly associated with differential expression of ADAM8, CREB5, and EXPH5 genes, respectively. Besides, the exclusive effect of SNPs such as rs10101376, rs140679, and rs1538146 also hold significant prognostic determinant. CONCLUSIONS: Thus, the analysis based on DNA methylation and SNPs have resulted in the identification of novel susceptible loci that hold prognostic relevance in breast cancer.

Orthogonal ubiquitin transfer identifies ubiquitination substrates under differential control by the two ubiquitin activating enzymes.

Protein ubiquitination is mediated sequentially by ubiquitin activating enzyme E1, ubiquitin conjugating enzyme E2 and ubiquitin ligase E3. Uba1 was thought to be the only E1 until the recent identification of Uba6. To differentiate the biological functions of Uba1 and Uba6, we applied an orthogonal ubiquitin transfer (OUT) technology to profile their ubiquitination targets in mammalian cells. By expressing pairs of an engineered ubiquitin and engineered Uba1 or Uba6 that were generated for exclusive interactions, we identified 697 potential Uba6 targets and 527 potential Uba1 targets with 258 overlaps. Bioinformatics analysis reveals substantial differences in pathways involving Uba1- and Uba6-specific targets. We demonstrate that polyubiquitination and proteasomal degradation of ezrin and CUGBP1 require Uba6, but not Uba1, and that Uba6 is involved in the control of ezrin localization and epithelial morphogenesis. These data suggest that distinctive substrate pools exist for Uba1 and Uba6 that reflect non-redundant biological roles for Uba6.