Browsing by Author "Fang, Shuyi"
Now showing 1 - 10 of 11
Results Per Page
Sort Options
Item ADGRG1 enriches for functional human hematopoietic stem cells following ex vivo expansion-induced mitochondrial oxidative stress(The American Society for Clinical Investigation, 2021) Chen, Yandan; Fang, Shuyi; Ding, Qingwei; Jiang, Rongzhen; He, Jiefeng; Wang, Qin; Jin, Yuting; Huang, Xinxin; Liu, Sheng; Capitano, Maegan L.; Trinh, Thao; Teng, Yincheng; Meng, Qingyou; Wan, Jun; Broxmeyer, Hal E.; Guo, Bin; BioHealth Informatics, School of Informatics and ComputingThe heterogeneity of human hematopoietic stem cells (HSCs) and hematopoietic progenitor cells (HPCs) under stress conditions such as ex vivo expansion is poorly understood. Here, we report that the frequencies of SCID-repopulating cells were greatly decreased in cord blood (CB) CD34+ HSCs and HPCs upon ex vivo culturing. Transcriptomic analysis and metabolic profiling demonstrated that mitochondrial oxidative stress of human CB HSCs and HPCs notably increased, along with loss of stemness. Limiting dilution analysis revealed that functional human HSCs were enriched in cell populations with low levels of mitochondrial ROS (mitoROS) during ex vivo culturing. Using single-cell RNA-Seq analysis of the mitoROS low cell population, we demonstrated that functional HSCs were substantially enriched in the adhesion GPCR G1-positive (ADGRG1+) population of CD34+CD133+ CB cells upon ex vivo expansion stress. Gene set enrichment analysis revealed that HSC signature genes including MSI2 and MLLT3 were enriched in CD34+CD133+ADGRG1+ CB HSCs. Our study reveals that ADGRG1 enriches for functional human HSCs under oxidative stress during ex vivo culturing, which can be a reliable target for drug screening of agonists of HSC expansion.Item Advanced Functions Embedded in the Second Version of Database, Global Evaluation of SARS-CoV-2/hCoV-19 Sequences 2(Frontiers Media, 2022-04-11) Li, Kailing; Wang, Audrey K.Y.; Liu, Sheng; Fang, Shuyi; Lu, Alex Z.; Shen, Jikui; Yang, Lei; Hu, Chang-Deng; Yang, Kai; Wan, Jun; BioHealth Informatics, School of Informatics and ComputingThe Global Evaluation of SARS-CoV-2/hCoV-19 Sequences 2 (GESS v2 https://shiny.ph.iu.edu/GESS_v2/) is an updated version of GESS, which has offered a handy query platform to analyze single-nucleotide variants (SNVs) on millions of high coverages and high-quality severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) complete genomes provided by the Global Initiative on Sharing Avian Influenza Data (GISAID). Including the tools in the first version, the GESS v2 is embedded with new functions, which allow users to search SNVs, given the viral nucleotide or amino acid sequence. The GESS v2 helps users to identify SNVs or SARS-CoV-2 lineages enriched in countries of user's interest and show the migration path of a selected lineage on a world map during specific time periods chosen by the users. In addition, the GESS v2 can recognize the dynamic variations of newly emerging SNVs in each month to help users monitor SNVs, which will potentially become dominant soon. More importantly, multiple sets of analyzed results about SNVs can be downloaded directly from the GESS v2 by which users can conduct their own independent research. With these significant updates, the GESS v2 will continue to serve as a public open platform for researchers to explore SARS-CoV-2 evolutionary patterns from the perspectives of the prevalence and impact of SNVs.Item A Comprehensive Survey and Deep Learning-Based Prediction on G-quadruplex Formation and Biological Functions(2022-09) Fang, Shuyi; Wan, Jun; Liu, Yunlong; Yan, Jingwen; Zhang, JieThe G-quadruplexes (G4s) are guanine-rich four-stranded DNA/RNA structures, which have been found throughout the human genome. G4s have been reported to affect chromatin structure and are involved in important biological processes at transcriptional and epigenetic levels. However, the underlying molecular mechanisms and locating of G4 still remain elusive due to the complexity of G4s. Taking advantage of the development of high-throughput sequencing technologies and machine learning approaches, we constructed this comprehensive investigation on G4 structures, including discovery of a novel marker for functional human hematopoietic stem cells and gained interest in G4 structure, exploring association between G4 and genomic factors by incorporating multi-omics data, and development of a deep-learningbased G4 prediction tool with G4 motif. First, we discovered ADGRG1 as a novel marker for functional human hematopoietic stem cells and its regulation through transcription activities. Our interest in G4s was stimulated while the transcription-related investigations. Next, we analyzed the genome-wide distribution properties of G4s and uncovered the associations of G4 with other epigenetic and transcriptional mechanisms to coordinate gene transcription. We explored that different-confidence G4 groups correlated differently with epigenetic regulatory elements and revealed that G4 structures could correlate with gene expression in two opposite ways depending on their locations and forming strands. Some transcription factors were identified to be over-represented with G4 emergence. We found distinct consensus sequences enriched in the G4 feet, with a high GC content in the feet of high-confidence G4s and a high TA content in solely predicted G4 feet. As for the last part, we developed a novel deep-learning-based prediction tool for DNA G4s with G4 motifs. Considering the classical G4 motif, we applied bi-directional LSTM model with attention method, which captures sequential information, and showed good performance in whole-genome level prediction of DNA G4s with the certified G4 pattern. Our comprehensive work investigated G4 with its functions and predictions and provided a better understanding of G4s on multi-omics level and computational information capture riding the wave of deep learning.Item A critical role of AREG for bleomycin-induced skin fibrosis(BMC, 2021) Zhang, Mary Yinghua; Fang, Shuyi; Gao, Hongyu; Zhang, Xiaoli; Gu, Dongsheng; Liu, Yunlong; Wan, Jun; Xie, Jingwu; Pediatrics, School of MedicineWe report our discovery of an important player in the development of skin fibrosis, a hallmark of scleroderma. Scleroderma is a fibrotic disease, affecting 70,000 to 150,000 Americans. Fibrosis is a pathological wound healing process that produces an excessive extracellular matrix to interfere with normal organ function. Fibrosis contributes to nearly half of human mortality. Scleroderma has heterogeneous phenotypes, unpredictable outcomes, no validated biomarkers, and no effective treatment. Thus, strategies to slow down scleroderma progression represent an urgent medical need. While a pathological wound healing process like fibrosis leaves scars and weakens organ function, oral mucosa wound healing is a scarless process. After re-analyses of gene expression datasets from oral mucosa wound healing and skin fibrosis, we discovered that several pathways constitutively activated in skin fibrosis are transiently induced during oral mucosa wound healing process, particularly the amphiregulin (Areg) gene. Areg expression is upregulated ~ 10 folds 24hrs after oral mucosa wound but reduced to the basal level 3 days later. During bleomycin-induced skin fibrosis, a commonly used mouse model for skin fibrosis, Areg is up-regulated throughout the fibrogenesis and is associated with elevated cell proliferation in the dermis. To demonstrate the role of Areg for skin fibrosis, we used mice with Areg knockout, and found that Areg deficiency essentially prevents bleomycin-induced skin fibrosis. We further determined that bleomycin-induced cell proliferation in the dermis was not observed in the Areg null mice. Furthermore, we found that inhibiting MEK, a downstream signaling effector of Areg, by selumetinib also effectively blocked bleomycin-based skin fibrosis model. Based on these results, we concluded that the Areg-EGFR-MEK signaling axis is critical for skin fibrosis development. Blocking this signaling axis may be effective in treating scleroderma.Item Decoding regulatory associations of G-quadruplex with epigenetic and transcriptomic functional components(Frontiers Media, 2022-08-25) Fang, Shuyi; Liu, Sheng; Yang, Danzhou; Yang, Lei; Hu, Chang-Deng; Wan, Jun; BioHealth Informatics, School of Informatics and ComputingG-quadruplex (G4) has been previously observed to be associated with gene expression. In this study, we performed integrative analysis on G4 multi-omics data from in-silicon prediction and ChIP-seq in human genome. Potential G4 sites were classified into three distinguished groups, such as one group of high-confidence G4-forming locations (G4-II) and groups only containing either ChIP-seq detected G4s (G4-I) or predicted G4 motif candidates (G4-III). We explored the associations of different-confidence G4 groups with other epigenetic regulatory elements, including CpG islands, chromatin status, enhancers, super-enhancers, G4 locations compared to the genes, and DNA methylation. Our elastic net regression model revealed that G4 structures could correlate with gene expression in two opposite ways depending on their locations to the genes as well as G4-forming DNA strand. Some transcription factors were identified to be over-represented with G4 emergence. The motif analysis discovered distinct consensus sequences enriched in the G4 feet, the flanking regions of two groups of G4s. We found high GC content in the feet of high-confidence G4s (G4-II) when compared to high TA content in solely predicted G4 feet of G4-III. Overall, we uncovered the comprehensive associations of G4 formations or predictions with other epigenetic and transcriptional elements which potentially coordinate gene transcription.Item Follicular regulatory T cells inhibit the development of granzyme B-expressing follicular helper T cells(American Society for Clinical Investigation, 2019-08-22) Xie, Markus M.; Fang, Shuyi; Chen, Qiang; Liu, Hong; Wan, Jun; Dent, Alexander L.; Microbiology and Immunology, School of MedicineT follicular regulatory (TFR) cells are found in the germinal center (GC) response and help shape the antibody (Ab) response. However, the precise role of TFR cells in the GC is controversial. Here, we addressed TFR cell function using mice with impaired TFR cell development (Bcl6-flox/Foxp3-cre, or Bcl6FC mice), mice with augmented TFR cell development (Blimp1-flox/Foxp3-cre, or Blimp1FC mice), and two different methods of immunization. Unexpectedly, GC B cell levels positively correlated with TFR cell levels. Using a gene profiling approach, we found that TFH cells from TFR-deficient mice showed strong upregulation of granzyme B (Gzmb) and other effector CD8+ T cell genes, many of which were Stat4 dependent. The upregulation of cytotoxic genes was the highest in TFH cells from TFR-deficient mice where Blimp1 was also deleted in Foxp3+ regulatory T cells (Bcl6-flox/Prdm1-flox/Foxp3-cre [DKO] mice). Granzyme B- and Eomesodermin-expressing TFH cells correlated with a higher rate of apoptotic GC B cells. Klrg1+ TFH cells from DKO mice expressed higher levels of Gzmb. Our data show that TFR cells repress the development of abnormal cytotoxic TFH cells, and the presence of cytotoxic TFH cells correlates with a lower GC and Ab response. Our data show what we believe is a novel mechanism of action for TFR cells helping the GC response.Item Genetic Spectrum and Distinct Evolution Patterns of SARS-CoV-2(Frontiers Media, 2020-09-25) Liu, Sheng; Shen, Jikui; Fang, Shuyi; Li, Kailing; Liu, Juli; Yang, Lei; Hu, Chang-Deng; Wan, Jun; Medical and Molecular Genetics, School of MedicineFour signature groups of frequently occurred single-nucleotide variants (SNVs) were identified in over twenty-eight thousand high-quality and high-coverage SARS-CoV-2 complete genome sequences, representing different viral strains. Some SNVs predominated but were mutually exclusively presented in patients from different countries and areas. These major SNV signatures exhibited distinguishable evolution patterns over time. A few hundred patients were detected with multiple viral strain-representing mutations simultaneously, which may stand for possible co-infection or potential homogenous recombination of SARS-CoV-2 in environment or within the viral host. Interestingly nucleotide substitutions among SARS-CoV-2 genomes tended to switch between bat RaTG13 coronavirus sequence and Wuhan-Hu-1 genome, indicating the higher genetic instability or tolerance of mutations on those sites or suggesting that major viral strains might exist between Wuhan-Hu-1 and RaTG13 coronavirus.Item GESS: a database of global evaluation of SARS-CoV-2/hCoV-19 sequences(Oxford University Press, 2020-10-12) Fang, Shuyi; Li, Kailing; Shen, Jikui; Liu, Sheng; Liu, Juli; Yang, Lei; Hu, Chang-Deng; Wan, Jun; BioHealth Informatics, School of Informatics and ComputingThe COVID-19 outbreak has become a global emergency since December 2019. Analysis of SARS-CoV-2 sequences can uncover single nucleotide variants (SNVs) and corresponding evolution patterns. The Global Evaluation of SARS-CoV-2/hCoV-19 Sequences (GESS, https://wan-bioinfo.shinyapps.io/GESS/) is a resource to provide comprehensive analysis results based on tens of thousands of high-coverage and high-quality SARS-CoV-2 complete genomes. The database allows user to browse, search and download SNVs at any individual or multiple SARS-CoV-2 genomic positions, or within a chosen genomic region or protein, or in certain country/area of interest. GESS reveals geographical distributions of SNVs around the world and across the states of USA, while exhibiting time-dependent patterns for SNV occurrences which reflect development of SARS-CoV-2 genomes. For each month, the top 100 SNVs that were firstly identified world-widely can be retrieved. GESS also explores SNVs occurring simultaneously with specific SNVs of user's interests. Furthermore, the database can be of great help to calibrate mutation rates and identify conserved genome regions. Taken together, GESS is a powerful resource and tool to monitor SARS-CoV-2 migration and evolution according to featured genomic variations. It provides potential directive information for prevalence prediction, related public health policy making, and vaccine designs.Item Protein arginine methyltransferase 5 promotes pICln-dependent androgen receptor transcription in castration-resistant prostate cancer(American Association for Cancer Research, 2020-11-15) Beketova, Elena; Fang, Shuyi; Owens, Jake L.; Liu, Sheng; Chen, Xufeng; Zhang, Qingfu; Asberry, Andrew M.; Deng, Xuehong; Malola, Jonathan; Huang, Jiaoti; Li, Chenglong; Pili, Roberto; Elzey, Bennett D.; Ratliff, Timothy L.; Wan, Jun; Hu, Chang-Deng; BioHealth Informatics, School of Informatics and ComputingThe majority of advanced prostate cancer therapies aim to inhibit androgen receptor (AR) signaling. However, AR reactivation inevitably drives disease progression to castration-resistant prostate cancer (CRPC). Here we demonstrate that protein arginine methyltransferase 5 (PRMT5) functions as an epigenetic activator of AR transcription in CRPC, requiring cooperation with a methylosome subunit pICln. In vitro and in xenograft tumors in mice, targeting PRMT5 or pICln suppressed growth of CRPC cells. Full-length AR and AR-V7 transcription activation required both PRMT5 and pICln but not MEP50. This activation of transcription was accompanied by PRMT5-mediated symmetric dimethylation of H4R3 at the proximal AR promoter. Further, knockdown of PRMT5 abolished the binding of pICln (but not vice versa) to the AR proximal promoter region, suggesting that PRMT5 recruits pICln to the AR promoter to activate AR transcription. Differential gene expression analysis in 22Rv1 cells confirmed that PRMT5 and pICln both regulate the androgen signaling pathway. In addition, PRMT5 and pICln protein expression positively correlated with AR and AR-V7 protein expression in CRPC tissues and their expression was highly correlated at the mRNA level across multiple publicly available CRPC datasets. Our results suggest that targeting PRMT5 or pICln may be explored as a novel therapy for CRPC treatment by suppressing expression of AR and AR splice variants to circumvent AR reactivation. SIGNIFICANCE: This study provides evidence that targeting PRMT5 can eliminate expression of AR and can be explored as a novel therapeutic approach to treat metastatic hormone-naïve and castration-resistant prostate cancer.Item Updated SARS-CoV-2 Single Nucleotide Variants and Mortality Association(Cold Spring Harbor Laboratory Press, 2021) Fang, Shuyi; Liu, Sheng; Shen, Jikui; Lu, Alex Z.; Zhang, Yucheng; Li, Kailing; Liu, Juli; Yang, Lei; Hu, Chang-Deng; Wan, Jun; BioHealth Informatics, School of Informatics and ComputingSince its outbreak in December 2019, COVID-19 has caused 100,5844,555 cases and 2,167,313 deaths as of Jan 27, 2021. Comparing our previous study of SARS-CoV-2 single nucleotide variants (SNVs) before June 2020, we found out that the SNV clustering had changed considerably since June 2020. Apart from that the group SNVs represented by two non-synonymous mutations A23403G (S: D614G) and C14408T (ORF1ab: P4715L) became dominant and carried by over 95% genomes, a few emerging groups of SNVs were recognized with sharply increased monthly occurrence ratios up to 70% in November 2020. Further investigation revealed that several SNVs were strongly associated with the mortality, but they presented distinct distribution in specific countries, e.g., Brazil, USA, Saudi Arabia, India, and Italy. SNVs including G25088T, T25A, G29861T and G29864A were adopted in a regularized logistic regression model to predict the mortality status in Brazil with the AUC of 0.84. Protein structure analysis showed that the emerging subgroups of non-synonymous SNVs and those mortality-related ones in Brazil were located on protein surface area. The clashes in protein structure introduced by these mutations might in turn affect virus pathogenesis through conformation changes, leading to the difference in transmission and virulence. Particularly, we found that SNVs tended to occur in intrinsic disordered regions (IDRs) of Spike (S) and ORF1ab, suggesting a critical role of SNVs in protein IDRs to determine protein folding and immune evasion.