Jinghua Gu Ph.D.

Cardenas, J., Balaji, U. and Gu, J. (2020). “Cerina: systematic circRNA functional annotation based on integrative analysis of ceRNA interactions.” Sci Rep 10(1): 22165.

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Circular RNAs, a family of covalently circularized RNAs with tissue-specific expression, were recently demonstrated to play important roles in mammalian biology. Regardless of extensive research to predict, quantify, and annotate circRNAs, our understanding of their functions is still in its infancy. In this study, we developed a novel computational tool: Competing Endogenous RNA for INtegrative Annotations (Cerina), to predict biological functions of circRNAs based on the competing endogenous RNA model. Pareto Frontier Analysis was employed to integrate ENCODE mRNA/miRNA data with predicted microRNA response elements to prioritize tissue-specific ceRNA interactions. Using data from several circRNA-disease databases, we demonstrated that Cerina significantly improved the functional relevance of the prioritized ceRNA interactions by several folds, in terms of precision and recall. Proof-of-concept studies on human cancers and cardiovascular diseases further showcased the efficacy of Cerina on predicting potential circRNA functions in human diseases.

Davids, M., A. Pooran, C. Hermann, L. Mottay, F. Thompson, J. Cardenas, J. Gu, T. Koeuth, R. Meldau, J. Limberis, P. Gina, S. Srivastava, B. Calder, A. Esmail, M. Tomasicchio, J. Blackburn, T. Gumbo and K. Dheda (2020). “A Human Lung Challenge Model to Evaluate the Safety and Immunogenicity of PPD and Live Bacillus Calmette-Guérin.” Am J Respir Crit Care Med 201(10): 1277-1291.

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Rationale: A human model to better understand tuberculosis immunopathogenesis and facilitate vaccine development is urgently needed.Objectives: We evaluated the feasibility, safety, and immunogenicity of live bacillus Calmette-Guérin (BCG) in a lung-oriented controlled human infection model.Methods: We recruited 106 healthy South African participants with varying degrees of tuberculosis susceptibility. Live BCG, sterile PPD, and saline were bronchoscopically instilled into separate lung segments (n = 65). A control group (n = 34) underwent a single bronchoscopy without challenge. The primary outcome was safety. Cellular and antibody immune signatures were identified in BAL before and 3 days after challenge using flow cytometry, ELISA, RNA sequencing, and mass spectrometry.Measurements and Main Results: The frequency of adverse events was low (9.4%; n = 10), similar in the challenge versus control groups (P = 0.8), and all adverse events were mild and managed conservatively in an outpatient setting. The optimal PPD and BCG dose was 0.5 TU and 10(4) cfu, respectively, based on changes in BAL cellular profiles (P = 0.02) and antibody responses (P = 0.01) at incremental doses before versus after challenge. At 10(4) versus 10(3) cfu BCG, there was a significant increase in number of differentially expressed genes (367 vs. 3; P < 0.001) and dysregulated proteins (64 vs. 0; P < 0.001). Immune responses were highly setting specific (in vitro vs. in vivo) and compartment specific (BAL vs. blood) and localized to the challenged lung segments.Conclusions: A lung-oriented mycobacterial controlled human infection model using live BCG and PPD is feasible and safe. These data inform the study of tuberculosis immunopathogenesis and strategies for evaluation and development of tuberculosis vaccine candidates.

Chen, X., J. Gu, A. F. Neuwald, L. Hilakivi-Clarke, R. Clarke and J. Xuan (2020). “BICORN: An R package for integrative inference of de novo cis-regulatory modules.” Sci Rep 10(1): 7960.

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Genome-wide transcription factor (TF) binding signal analyses reveal co-localization of TF binding sites based on inferred cis-regulatory modules (CRMs). CRMs play a key role in understanding the cooperation of multiple TFs under specific conditions. However, the functions of CRMs and their effects on nearby gene transcription are highly dynamic and context-specific and therefore are challenging to characterize. BICORN (Bayesian Inference of COoperative Regulatory Network) builds a hierarchical Bayesian model and infers context-specific CRMs based on TF-gene binding events and gene expression data for a particular cell type. BICORN automatically searches for a list of candidate CRMs based on the input TF bindings at regulatory regions associated with genes of interest. Applying Gibbs sampling, BICORN iteratively estimates model parameters of CRMs, TF activities, and corresponding regulation on gene transcription, which it models as a sparse network of functional CRMs regulating target genes. The BICORN package is implemented in R (version 3.4 or later) and is publicly available on the CRAN server at https://cran.r-project.org/web/packages/BICORN/index.html.

Saravanan, P. B., S. Vasu, G. Yoshimatsu, C. M. Darden, X. Wang, J. Gu, M. C. Lawrence and B. Naziruddin (2019). “Differential Expression and Release of Exosomal Mirnas by Human Islets under Inflammatory and Hypoxic Stress.” Diabetologia 62(10): 1901-1914.

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AIMS/HYPOTHESIS: Pancreatic islets produce non-coding microRNAs (miRNAs) that regulate islet cell function and survival. Our earlier investigations revealed that human islets undergo significant damage due to various types of stresses following transplantation and release miRNAs. Here, we sought to identify and validate exosomal miRNAs (exo-miRNAs) produced by human islets under conditions of cellular stress, preceding loss of cell function and death. We also aimed to identify islet stress signalling pathways targeted by exo-miRNAs to elucidate potential regulatory roles in islet cell stress. METHODS: Human islets were subjected to proinflammatory cytokine and hypoxic cell stress and miRNA from exosomes was isolated for RNA sequencing and analysis. Stress-induced exo-miRNAs were evaluated for kinetics of expression and release by intact islets for up to 48 h exposure to cytokines and hypoxia. A subset of stress-induced exo-miRNAs were assessed for recovery and detection as biomarkers of islet cell stress in a diabetic nude mouse xenotransplant model and in patients undergoing total pancreatectomy with islet auto-transplantation (TPIAT). Genes and signalling pathways targeted by stress-induced exo-miRNAs were identified by Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and direct interactions of miRNAs with downstream signalling targets were validated in human islet cells using the miRNA Tests for Read Analysis and Prediction (MirTrap) system. RESULTS: Global exo-miRNA sequencing revealed that 879 miRNA species were released from human islets and 190 islet exo-miRNAs were differentially expressed in response to proinflammatory cytokines, hypoxia or both. Release of exo-miRNAs hsa-miR-29b-3p and hsa-miR-216a-5p was detected within 6 h of exposure to cytokines and hypoxia. The remaining subset of stress-induced exo-miRNAs, including hsa-miR-148a-3p and islet cell damage marker hsa-miR-375, showed delayed release at 24-48 h, correlating with apoptosis and cell death. Stress and damage exo-miRNAs were significantly elevated in the circulation in human-to-mouse xenotransplant models and in human transplant recipients. Elevated blood exo-miRNAs negatively correlated with post-transplant islet function based on comparisons of stress and damage exo-miRNA indices with Secretory Unit of Islet Transplant Objects (SUITO) indices. KEGG analysis and further validation of exo-miRNA targets by MirTrap analysis revealed significant enrichment of islet mRNAs involved in phosphoinositide 3-kinase/Akt and mitogen-activated protein kinase signalling pathways. CONCLUSIONS/INTERPRETATION: The study identifies exo-miRNAs differentially expressed and released by islets in response to damage and stress. These exo-miRNAs could serve as potential biomarkers for assessing islet damage and predicting outcomes in islet transplantation. Notably, exo-miRNAs 29b-3p and 216a-5p could be detected in islets prior to damage-released miRNAs and indicators of cellular apoptosis and death. Thus, these stress-induced exo-miRNAs may have potential diagnostic value for detecting early islet stress prior to progressive loss of islet cell mass and function. Further investigations are warranted to investigate the utility of these exo-miRNAs as early indicators of islet cell stress during prediabetic conditions.

Lawrence, M. C., C. M. Darden, S. Vasu, K. Kumano, J. Gu, X. Wang, J. Chan, Z. Xu, B. F. Lemoine, P. Nguyen, C. Smitherman, B. Naziruddin and G. Testa (2019). “Profiling Gene Programs in the Blood During Liver Regeneration in Living Liver Donors.” Liver Transpl 25(10): 1541-1560.

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The human liver’s capacity to rapidly regenerate to a full-sized functional organ after resection has allowed successful outcomes for living donor liver transplantation (LDLT) procedures. However, the ability to detect and track physiological changes occurring during liver regeneration after resection and throughout the restoration process is still lacking. We performed a comprehensive whole-transcriptome RNA sequencing analysis of liver and circulating blood tissue from 12 healthy LDLT donors to define biomarker signatures for monitoring physiological activities during liver regeneration at 14 time points for up to a 1-year procedural follow-up. LDLT donor liver tissue differentially expressed 1238 coding and noncoding genes after resection, and an additional 1260 genes were selectively regulated after LDLT. A total of 15,011 RNA transcript species were identified in the blood in response to liver resection. The transcripts most highly regulated were sequentially expressed within 3 distinct peaks that correlated with sets of functional genes involved in the induction of liver resection-specific innate immune response (peak 1), activation of the complement system (peak 2), and platelet activation and erythropoiesis (peak 3). Each peak corresponded with progressive phases of extracellular matrix degradation, remodeling, and organization during liver restoration. These processes could be tracked by distinct molecular signatures of up-regulated and down-regulated gene profiles in the blood during phases of liver repair and regeneration. In conclusion, the results establish temporal and dynamic transcriptional patterns of gene expression following surgical liver resection that can be detected in the blood and potentially used as biomarker signatures for monitoring phases of liver regeneration.