Donnelly Centre for Cellular and Biomolecular Research

PubMed

Recent Publications

Powerful gene set analysis in GWAS with the Generalized Berk-Jones statistic.

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Powerful gene set analysis in GWAS with the Generalized Berk-Jones statistic.

PLoS Genet. 2019 Mar 15;15(3):e1007530

Authors: Sun R, Hui S, Bader GD, Lin X, Kraft P

Abstract
A common complementary strategy in Genome-Wide Association Studies (GWAS) is to perform Gene Set Analysis (GSA), which tests for the association between one phenotype of interest and an entire set of Single Nucleotide Polymorphisms (SNPs) residing in selected genes. While there exist many tools for performing GSA, popular methods often include a number of ad-hoc steps that are difficult to justify statistically, provide complicated interpretations based on permutation inference, and demonstrate poor operating characteristics. Additionally, the lack of gold standard gene set lists can produce misleading results and create difficulties in comparing analyses even across the same phenotype. We introduce the Generalized Berk-Jones (GBJ) statistic for GSA, a permutation-free parametric framework that offers asymptotic power guarantees in certain set-based testing settings. To adjust for confounding introduced by different gene set lists, we further develop a GBJ step-down inference technique that can discriminate between gene sets driven to significance by single genes and those demonstrating group-level effects. We compare GBJ to popular alternatives through simulation and re-analysis of summary statistics from a large breast cancer GWAS, and we show how GBJ can increase power by incorporating information from multiple signals in the same gene. In addition, we illustrate how breast cancer pathway analysis can be confounded by the frequency of FGFR2 in pathway lists. Our approach is further validated on two other datasets of summary statistics generated from GWAS of height and schizophrenia.

PMID: 30875371 [PubMed - as supplied by publisher]



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netDx: interpretable patient classification using integrated patient similarity networks.

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netDx: interpretable patient classification using integrated patient similarity networks.

Mol Syst Biol. 2019 Mar 14;15(3):e8497

Authors: Pai S, Hui S, Isserlin R, Shah MA, Kaka H, Bader GD

Abstract
Patient classification has widespread biomedical and clinical applications, including diagnosis, prognosis, and treatment response prediction. A clinically useful prediction algorithm should be accurate, generalizable, be able to integrate diverse data types, and handle sparse data. A clinical predictor based on genomic data needs to be interpretable to drive hypothesis-driven research into new treatments. We describe netDx, a novel supervised patient classification framework based on patient similarity networks, which meets these criteria. In a cancer survival benchmark dataset integrating up to six data types in four cancer types, netDx significantly outperforms most other machine-learning approaches across most cancer types. Compared to traditional machine-learning-based patient classifiers, netDx results are more interpretable, visualizing the decision boundary in the context of patient similarity space. When patient similarity is defined by pathway-level gene expression, netDx identifies biological pathways important for outcome prediction, as demonstrated in breast cancer and asthma. netDx can serve as a patient classifier and as a tool for discovery of biological features characteristic of disease. We provide a free software implementation of netDx with automation workflows.

PMID: 30872331 [PubMed - in process]



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The ubiquitin interacting motifs of USP37 act on the proximal Ub of a di-Ub chain to enhance catalytic efficiency.

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The ubiquitin interacting motifs of USP37 act on the proximal Ub of a di-Ub chain to enhance catalytic efficiency.

Sci Rep. 2019 Mar 11;9(1):4119

Authors: Manczyk N, Veggiani G, Teyra J, Strilchuk AW, Sidhu SS, Sicheri F

Abstract
USP37 is a deubiquitinase (DUB) with roles in the regulation of DNA damage repair and the cohesion of sister chromatids during mitosis. USP37 contains a unique insert of three ubiquitin interacting motifs (UIMs) within its catalytic DUB domain. We investigated the role of the three UIMs in the ability of USP37 to cleave di-ubiquitin chains. We found that the third UIM of USP37 recognizes the proximal ubiquitin moiety of K48 di-Ub to potentiate cleavage activity and posit that this mechanism of action may be generalizable to other chain types. In the case of K48-linked ubiquitin chains this potentiation stemmed largely from a dramatic increase in catalytic rate (kcat). We also developed and characterized three ubiquitin variant (UbV) inhibitors that selectively engage distinct binding sites in USP37. In addition to validating the deduced functional roles of the three UIMs in catalysis, the UbVs highlight a novel and effective means to selectively inhibit members of the difficult to drug DUB family.

PMID: 30858488 [PubMed - in process]



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Emerging drug development technologies targeting Ubiquitination for Cancer therapeutics.

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Emerging drug development technologies targeting Ubiquitination for Cancer therapeutics.

Pharmacol Ther. 2019 Mar 06;:

Authors: Veggiani G, Gerpe MCR, Sidhu SS, Zhang W

Abstract
Development of effective cancer therapeutic strategies relies on our ability to interfere with cellular processes that are dysregulated in tumors. Given the essential role of the ubiquitin proteasome system (UPS) in regulating a myriad of cellular processes, it is not surprising that malfunction of UPS components is implicated in numerous human diseases, including many types of cancer. The clinical success of proteasome inhibitors in treating multiple myeloma has further stimulated enthusiasm for targeting UPS proteins for pharmacological intervention in cancer treatment, particularly in the precision medicine era. Unfortunately, despite tremendous efforts, the paucity of potent and selective UPS inhibitors has severely hampered attempts to exploit the UPS for therapeutic benefits. To tackle this problem, many groups have been working on technology advancement to rapidly and effectively screen for potent and specific UPS modulators as intracellular probes or early-phase therapeutic agents. Here, we review several emerging technologies for developing chemical- and protein-based molecules to manipulate UPS enzymatic activity, with the aim of providing an overview of strategies available to target ubiquitination for cancer therapy.

PMID: 30851297 [PubMed - as supplied by publisher]



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Innate Control of Tissue-Reparative Human Regulatory T Cells.

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Innate Control of Tissue-Reparative Human Regulatory T Cells.

J Immunol. 2019 Mar 08;:

Authors: Lam AJ, MacDonald KN, Pesenacker AM, Juvet SC, Morishita KA, Bressler B, iGenoMed Consortium, Pan JG, Sidhu SS, Rioux JD, Levings MK

Abstract
Regulatory T cell (Treg) therapy is a potential curative approach for a variety of immune-mediated conditions, including autoimmunity and transplantation, in which there is pathological tissue damage. In mice, IL-33R (ST2)-expressing Tregs mediate tissue repair by producing the growth factor amphiregulin, but whether similar tissue-reparative Tregs exist in humans remains unclear. We show that human Tregs in blood and multiple tissue types produced amphiregulin, but this was neither a unique feature of Tregs nor selectively upregulated in tissues. Human Tregs in blood, tonsil, synovial fluid, colon, and lung tissues did not express ST2, so ST2+ Tregs were engineered via lentiviral-mediated overexpression, and their therapeutic potential for cell therapy was examined. Engineered ST2+ Tregs exhibited TCR-independent, IL-33-stimulated amphiregulin expression and a heightened ability to induce M2-like macrophages. The finding that amphiregulin-producing Tregs have a noneffector phenotype and are progressively lost upon TCR-induced proliferation and differentiation suggests that the tissue repair capacity of human Tregs may be an innate function that operates independently from their classical suppressive function.

PMID: 30850479 [PubMed - as supplied by publisher]



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Modulated Protein Delivery to Engineer Tissue Repair.

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Modulated Protein Delivery to Engineer Tissue Repair.

Tissue Eng Part A. 2019 Mar 08;:

Authors: Shoichet MS, Hettiaratchi MH

Abstract
Protein delivery presents a powerful strategy to stimulate regeneration of damaged tissues. However, the clinical translation of many promising therapeutic proteins in the research pipeline has been hindered by the inability to localize and control their release within the injury site. The only biomaterials-based strategies that have been approved for controlled protein release clinically are the absorbable collagen sponge for bone morphogenetic protein-2 (BMP-2) delivery to repair large bone defects (Medtronic's Infuse Bone Graft) and poly(lactic-co-glycolic) acid (PLGA) microparticles for sustained human growth hormone (hGH) delivery (Genentech's Nutropin Depot). Despite their clinical approval, even these products possess inherent limitations that curb their widespread use: the collagen sponge exhibits rapid BMP-2 release that has been linked with numerous undesirable side effects [1], while commercialization of the long-acting hGH formulation was eventually halted due to manufacturing concerns over the low protein loading capacity of the PLGA particles [2]. Notwithstanding substantive research over the past 25 years, achieving effective control over protein delivery remains an ongoing challenge.

PMID: 30848169 [PubMed - as supplied by publisher]



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Expansion of Retinal Stem Cells and their Progeny Using Cell Microcarriers in a Bioreactor.

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Expansion of Retinal Stem Cells and their Progeny Using Cell Microcarriers in a Bioreactor.

Biotechnol Prog. 2019 Mar 06;:e2800

Authors: Baakdhah T, van der Kooy D

Abstract
Blindness as a consequence of degenerative eye diseases (e.g Age Related Macular Degeneration and Retinitis Pigmentosa) is a major health problem and numbers are expected to increase by up to 50% by 2020. Unfortunately, adult mouse and human retinal stem cells (RSCs), unlike fish and amphibians, are quiescent in vivo and do not regenerate following disease or injury. To replace lost cells, we used microcarriers (MCs) in a suspension stirring bioreactor (SSB) to help achieve numbers suitable for differentiation and transplantation. We achieved a significant 10-fold enrichment of RSC yield compared to conventional static culture techniques using a combination of FACTIII MCs and relative hypoxia (5%) inside the bioreactor. We found that hypoxia (5% O2 ) was associated with better RSC expansion across all platforms; and this can be attributed to hypoxia-induced increases in survival and/or symmetric division of stem cells. In the future we will target the differentiation of RSCs and their progeny towards rod and cone photoreceptor phenotypes using FACTIII MCs inside bioreactors to expand their populations in order to produce the large numbers of cells needed for transplantation. This article is protected by copyright. All rights reserved.

PMID: 30840351 [PubMed - as supplied by publisher]



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A novel protein domain in an ancestral splicing factor drove the evolution of neural microexons.

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A novel protein domain in an ancestral splicing factor drove the evolution of neural microexons.

Nat Ecol Evol. 2019 Mar 04;:

Authors: Torres-Méndez A, Bonnal S, Marquez Y, Roth J, Iglesias M, Permanyer J, Almudí I, O'Hanlon D, Guitart T, Soller M, Gingras AC, Gebauer F, Rentzsch F, Blencowe BJ, Valcárcel J, Irimia M

Abstract
The mechanisms by which entire programmes of gene regulation emerged during evolution are poorly understood. Neuronal microexons represent the most conserved class of alternative splicing in vertebrates, and are critical for proper brain development and function. Here, we discover neural microexon programmes in non-vertebrate species and trace their origin to bilaterian ancestors through the emergence of a previously uncharacterized 'enhancer of microexons' (eMIC) protein domain. The eMIC domain originated as an alternative, neural-enriched splice isoform of the pan-eukaryotic Srrm2/SRm300 splicing factor gene, and subsequently became fixed in the vertebrate and neuronal-specific splicing regulator Srrm4/nSR100 and its paralogue Srrm3. Remarkably, the eMIC domain is necessary and sufficient for microexon splicing, and functions by interacting with the earliest components required for exon recognition. The emergence of a novel domain with restricted expression in the nervous system thus resulted in the evolution of splicing programmes that qualitatively expanded the neuronal molecular complexity in bilaterians.

PMID: 30833759 [PubMed - as supplied by publisher]



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Patterns of joint involvement in juvenile idiopathic arthritis and prediction of disease course: A prospective study with multilayer non-negative matrix factorization.

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Patterns of joint involvement in juvenile idiopathic arthritis and prediction of disease course: A prospective study with multilayer non-negative matrix factorization.

PLoS Med. 2019 Feb;16(2):e1002750

Authors: Eng SWM, Aeschlimann FA, van Veenendaal M, Berard RA, Rosenberg AM, Morris Q, Yeung RSM, ReACCh-Out Research Consortium

Abstract
BACKGROUND: Joint inflammation is the common feature underlying juvenile idiopathic arthritis (JIA). Clinicians recognize patterns of joint involvement currently not part of the International League of Associations for Rheumatology (ILAR) classification. Using unsupervised machine learning, we sought to uncover data-driven joint patterns that predict clinical phenotype and disease trajectories.
METHODS AND FINDINGS: We analyzed prospectively collected clinical data, including joint involvement using a standard 71-joint homunculus, for 640 discovery patients with newly diagnosed JIA enrolled in a Canada-wide study who were followed serially for five years, treatment-naïve except for nonsteroidal anti-inflammatory drugs (NSAIDs) and diagnosed within one year of symptom onset. Twenty-one patients had systemic arthritis, 300 oligoarthritis, 125 rheumatoid factor (RF)-negative polyarthritis, 16 RF-positive polyarthritis, 37 psoriatic arthritis, 78 enthesitis-related arthritis (ERA), and 63 undifferentiated arthritis. At diagnosis, we observed global hierarchical groups of co-involved joints. To characterize these patterns, we developed sparse multilayer non-negative matrix factorization (NMF). Model selection by internal bi-cross-validation identified seven joint patterns at presentation, to which all 640 discovery patients were assigned: pelvic girdle (57 patients), fingers (25), wrists (114), toes (48), ankles (106), knees (283), and indistinct (7). Patterns were distinct from clinical subtypes (P < 0.001 by χ2 test) and reproducible through external data set validation on a 119-patient, prospectively collected independent validation cohort (reconstruction accuracy Q2 = 0.55 for patterns; 0.35 for groups). Some patients matched multiple patterns. To determine whether their disease outcomes differed, we further subdivided the 640 discovery patients into three subgroups by degree of localization-the percentage of their active joints aligning with their assigned pattern: localized (≥90%; 359 patients), partially localized (60%-90%; 124), or extended (<60%; 157). Localized patients more often maintained their baseline patterns (P < 0.05 for five groups by permutation test) than nonlocalized patients (P < 0.05 for three groups by permutation test) over a five-year follow-up period. We modelled time to zero joints in the discovery cohort using a multivariate Cox proportional hazards model considering joint pattern, degree of localization, and ILAR subtype. Despite receiving more intense treatment, 50% of nonlocalized patients had zero joints at one year compared to six months for localized patients. Overall, localized patients required less time to reach zero joints (partial: P = 0.0018 versus localized by log-rank test; extended: P = 0.0057). Potential limitations include the requirement for patients to be treatment naïve (except NSAIDs), which may skew the patient cohorts towards milder disease, and the validation cohort size precluded multivariate analyses of disease trajectories.
CONCLUSIONS: Multilayer NMF identified patterns of joint involvement that predicted disease trajectory in children with arthritis. Our hierarchical unsupervised approach identified a new clinical feature, degree of localization, which predicted outcomes in both cohorts. Detailed assessment of every joint is already part of every musculoskeletal exam for children with arthritis. Our study supports both the continued collection of detailed joint involvement and the inclusion of patterns and degrees of localization to stratify patients and inform treatment decisions. This will advance pediatric rheumatology from counting joints to realizing the potential of using data available from uncovering patterns of joint involvement.

PMID: 30807586 [PubMed - in process]



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Complex modifier landscape underlying genetic background effects.

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Complex modifier landscape underlying genetic background effects.

Proc Natl Acad Sci U S A. 2019 03 12;116(11):5045-5054

Authors: Hou J, Tan G, Fink GR, Andrews BJ, Boone C

Abstract
The phenotypic consequence of a given mutation can be influenced by the genetic background. For example, conditional gene essentiality occurs when the loss of function of a gene causes lethality in one genetic background but not another. Between two individual Saccharomyces cerevisiae strains, S288c and Σ1278b, ∼1% of yeast genes were previously identified as "conditional essential." Here, in addition to confirming that some conditional essential genes are modified by a nonchromosomal element, we show that most cases involve a complex set of genomic modifiers. From tetrad analysis of S288C/Σ1278b hybrid strains and whole-genome sequencing of viable hybrid spore progeny, we identified complex sets of multiple genomic regions underlying conditional essentiality. For a smaller subset of genes, including CYS3 and CYS4, each of which encodes components of the cysteine biosynthesis pathway, we observed a segregation pattern consistent with a single modifier associated with conditional essentiality. In natural yeast isolates, we found that the CYS3/CYS4 conditional essentiality can be caused by variation in two independent modifiers, MET1 and OPT1, each with roles associated with cellular cysteine physiology. Interestingly, the OPT1 allelic variation appears to have arisen independently from separate lineages, with rare allele frequencies below 0.5%. Thus, while conditional gene essentiality is usually driven by genetic interactions associated with complex modifier architectures, our analysis also highlights the role of functionally related, genetically independent, and rare variants.

PMID: 30804202 [PubMed - indexed for MEDLINE]



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