IU Indianapolis ScholarWorks :: Browsing by Subject "Transcriptome"

Browsing by Subject "Transcriptome"

Now showing 1 - 10 of 36

A Fur family protein BosR is a novel RNA-binding protein that controls rpoS RNA stability in the Lyme disease pathogen
(Oxford University Press, 2024) Raghunandanan, Sajith; Priya, Raj; Alanazi, Fuad; Lybecker, Meghan C.; Schlax, Paula Jean; Yang, X. Frank; Microbiology and Immunology, School of Medicine
2´-O-methylation (Nm) is one of the most abundant modifications found in both mRNAs and noncoding RNAs. It contributes to many biological processes, such as the normal functioning of tRNA, the protection of mRNA against degradation by the decapping and exoribonuclease (DXO) protein, and the biogenesis and specificity of rRNA. Recent advancements in single-molecule sequencing techniques for long read RNA sequencing data offered by Oxford Nanopore technologies have enabled the direct detection of RNA modifications from sequencing data. In this study, we propose a bio-computational framework, Nm-Nano, for predicting the presence of Nm sites in direct RNA sequencing data generated from two human cell lines. The Nm-Nano framework integrates two supervised machine learning (ML) models for predicting Nm sites: Extreme Gradient Boosting (XGBoost) and Random Forest (RF) with K-mer embedding. Evaluation on benchmark datasets from direct RNA sequecing of HeLa and HEK293 cell lines, demonstrates high accuracy (99% with XGBoost and 92% with RF) in identifying Nm sites. Deploying Nm-Nano on HeLa and HEK293 cell lines reveals genes that are frequently modified with Nm. In HeLa cell lines, 125 genes are identified as frequently Nm-modified, showing enrichment in 30 ontologies related to immune response and cellular processes. In HEK293 cell lines, 61 genes are identified as frequently Nm-modified, with enrichment in processes like glycolysis and protein localization. These findings underscore the diverse regulatory roles of Nm modifications in metabolic pathways, protein degradation, and cellular processes. The source code of Nm-Nano can be freely accessed at https://github.com/Janga-Lab/Nm-Nano.
A graph neural network model to estimate cell-wise metabolic flux using single-cell RNA-seq data
(Cold Spring Harbor Laboratory, 2021) Alghamdi, Norah; Chang, Wennan; Dang, Pengtao; Lu, Xiaoyu; Wan, Changlin; Gampala, Silpa; Huang, Zhi; Wang, Jiashi; Ma, Qin; Zang, Yong; Fishel, Melissa; Cao, Sha; Zhang, Chi; Medical and Molecular Genetics, School of Medicine
The metabolic heterogeneity and metabolic interplay between cells are known as significant contributors to disease treatment resistance. However, with the lack of a mature high-throughput single-cell metabolomics technology, we are yet to establish systematic understanding of the intra-tissue metabolic heterogeneity and cooperative mechanisms. To mitigate this knowledge gap, we developed a novel computational method, namely, single-cell flux estimation analysis (scFEA), to infer the cell-wise fluxome from single-cell RNA-sequencing (scRNA-seq) data. scFEA is empowered by a systematically reconstructed human metabolic map as a factor graph, a novel probabilistic model to leverage the flux balance constraints on scRNA-seq data, and a novel graph neural network-based optimization solver. The intricate information cascade from transcriptome to metabolome was captured using multilayer neural networks to capitulate the nonlinear dependency between enzymatic gene expressions and reaction rates. We experimentally validated scFEA by generating an scRNA-seq data set with matched metabolomics data on cells of perturbed oxygen and genetic conditions. Application of scFEA on this data set showed the consistency between predicted flux and the observed variation of metabolite abundance in the matched metabolomics data. We also applied scFEA on five publicly available scRNA-seq and spatial transcriptomics data sets and identified context- and cell group-specific metabolic variations. The cell-wise fluxome predicted by scFEA empowers a series of downstream analyses including identification of metabolic modules or cell groups that share common metabolic variations, sensitivity evaluation of enzymes with regards to their impact on the whole metabolic flux, and inference of cell-tissue and cell-cell metabolic communications.
A pan-cancer organoid platform for precision medicine
(Elsevier, 2021) Larsen, Brian M.; Kannan, Madhavi; Langer, Lee F.; Leibowitz, Benjamin D.; Bentaieb, Aicha; Cancino, Andrea; Dolgalev, Igor; Drummond, Bridgette E.; Dry, Jonathan R.; Ho, Chi-Sing; Khullar, Gaurav; Krantz, Benjamin A.; Mapes, Brandon; McKinnon, Kelly E.; Metti, Jessica; Perera, Jason F.; Rand, Tim A.; Sanchez-Freire, Veronica; Shaxted, Jenna M.; Stein, Michelle M.; Streit, Michael A.; Tan, Yi-Hung Carol; Zhang, Yilin; Zhao, Ende; Venkataraman, Jagadish; Stumpe, Martin C.; Borgia, Jeffrey A.; Masood, Ashiq; Catenacci, Daniel V. T.; Mathews, Jeremy V.; Gursel, Demirkan B.; Wei, Jian-Jun; Welling, Theodore H.; Simeone, Diane M.; White, Kevin P.; Khan, Aly A.; Igartua, Catherine; Salahudeen, Ameen A.; Medicine, School of Medicine
Patient-derived tumor organoids (TOs) are emerging as high-fidelity models to study cancer biology and develop novel precision medicine therapeutics. However, utilizing TOs for systems-biology-based approaches has been limited by a lack of scalable and reproducible methods to develop and profile these models. We describe a robust pan-cancer TO platform with chemically defined media optimized on cultures acquired from over 1,000 patients. Crucially, we demonstrate tumor genetic and transcriptomic concordance utilizing this approach and further optimize defined minimal media for organoid initiation and propagation. Additionally, we demonstrate a neural-network-based high-throughput approach for label-free, light-microscopy-based drug assays capable of predicting patient-specific heterogeneity in drug responses with applicability across solid cancers. The pan-cancer platform, molecular data, and neural-network-based drug assay serve as resources to accelerate the broad implementation of organoid models in precision medicine research and personalized therapeutic profiling programs.
A remarkable adaptive paradigm of heart performance and protection emerges in response to marked cardiac-specific overexpression of ADCY8
(eLife Sciences, 2022-12-14) Tarasov, Kirill V.; Chakir, Khalid; Riordon, Daniel R.; Lyashkov, Alexey E.; Ahmet, Ismayil; Perino, Maria Grazia; Silvester, Allwin Jennifa; Zhang, Jing; Wang, Mingyi; Lukyanenko, Yevgeniya O.; Qu, Jia-Hua; Barrera, Miguel Calvo-Rubio; Juhaszova, Magdalena; Tarasova, Yelena S.; Ziman, Bruce; Telljohann, Richard; Kumar, Vikas; Ranek, Mark; Lammons, John; Bychkov, Rostislav; de Cabo, Rafael; Jun, Seungho; Keceli, Gizem; Gupta, Ashish; Yang, Dongmei; Aon, Miguel A.; Adamo, Luigi; Morrell, Christopher H.; Otu, Walter; Carroll, Cameron; Chambers, Shane; Paolocci, Nazareno; Huynh, Thanh; Pacak, Karel; Weiss, Robert; Field, Loren; Sollott, Steven J.; Lakatta, Edward G.; Medicine, School of Medicine
Adult (3 month) mice with cardiac-specific overexpression of adenylyl cyclase (AC) type VIII (TGAC8) adapt to an increased cAMP-induced cardiac workload (~30% increases in heart rate, ejection fraction and cardiac output) for up to a year without signs of heart failure or excessive mortality. Here, we show classical cardiac hypertrophy markers were absent in TGAC8, and that total left ventricular (LV) mass was not increased: a reduced LV cavity volume in TGAC8 was encased by thicker LV walls harboring an increased number of small cardiac myocytes, and a network of small interstitial proliferative non-cardiac myocytes compared to wild type (WT) littermates; Protein synthesis, proteosome activity, and autophagy were enhanced in TGAC8 vs WT, and Nrf-2, Hsp90α, and ACC2 protein levels were increased. Despite increased energy demands in vivo LV ATP and phosphocreatine levels in TGAC8 did not differ from WT. Unbiased omics analyses identified more than 2,000 transcripts and proteins, comprising a broad array of biological processes across multiple cellular compartments, which differed by genotype; compared to WT, in TGAC8 there was a shift from fatty acid oxidation to aerobic glycolysis in the context of increased utilization of the pentose phosphate shunt and nucleotide synthesis. Thus, marked overexpression of AC8 engages complex, coordinate adaptation "circuity" that has evolved in mammalian cells to defend against stress that threatens health or life (elements of which have already been shown to be central to cardiac ischemic pre-conditioning and exercise endurance cardiac conditioning) that may be of biological significance to allow for proper healing in disease states such as infarction or failure of the heart.
Aberrant epigenetic and transcriptional events associated with breast cancer risk
(BMC, 2022-02-09) Marino, Natascia; German, Rana; Podicheti, Ram; Rusch, Douglas B.; Rockey, Pam; Huang, Jie; Sandusky, George E.; Temm, Constance J.; Althouse, Sandra; Nephew, Kenneth P.; Nakshatri, Harikrishna; Liu, Jun; Vode, Ashley; Cao, Sha; Storniolo, Anna Maria V.; Medicine, School of Medicine
Background: Genome-wide association studies have identified several breast cancer susceptibility loci. However, biomarkers for risk assessment are still missing. Here, we investigated cancer-related molecular changes detected in tissues from women at high risk for breast cancer prior to disease manifestation. Disease-free breast tissue cores donated by healthy women (N = 146, median age = 39 years) were processed for both methylome (MethylCap) and transcriptome (Illumina's HiSeq4000) sequencing. Analysis of tissue microarray and primary breast epithelial cells was used to confirm gene expression dysregulation. Results: Transcriptomic analysis identified 69 differentially expressed genes between women at high and those at average risk of breast cancer (Tyrer-Cuzick model) at FDR < 0.05 and fold change ≥ 2. Majority of the identified genes were involved in DNA damage checkpoint, cell cycle, and cell adhesion. Two genes, FAM83A and NEK2, were overexpressed in tissue sections (FDR < 0.01) and primary epithelial cells (p < 0.05) from high-risk breasts. Moreover, 1698 DNA methylation changes were identified in high-risk breast tissues (FDR < 0.05), partially overlapped with cancer-related signatures, and correlated with transcriptional changes (p < 0.05, r ≤ 0.5). Finally, among the participants, 35 women donated breast biopsies at two time points, and age-related molecular alterations enhanced in high-risk subjects were identified. Conclusions: Normal breast tissue from women at high risk of breast cancer bears molecular aberrations that may contribute to breast cancer susceptibility. This study is the first molecular characterization of the true normal breast tissues, and provides an opportunity to investigate molecular markers of breast cancer risk, which may lead to new preventive approaches.
Advances in translational bioinformatics facilitate revealing the landscape of complex disease mechanisms
(Springer (Biomed Central Ltd.), 2014) Yang, Jack Y.; Dunker, A. Keith; Liu, Jun S.; Qin, Xiang; Arabnia, Hamid R.; Yang, William; Niemierko, Andrzej; Chen, Zhongxue; Luo, Zuojie; Wang, Liangjiang; Liu, Yunlong; Xu, Dong; Deng, Youping; Tong, Weida; Yang, Mary Qu; Department of Biochemistry and Molecular Biology, IU School of Medicine
Advances of high-throughput technologies have rapidly produced more and more data from DNAs and RNAs to proteins, especially large volumes of genome-scale data. However, connection of the genomic information to cellular functions and biological behaviours relies on the development of effective approaches at higher systems level. In particular, advances in RNA-Seq technology has helped the studies of transcriptome, RNA expressed from the genome, while systems biology on the other hand provides more comprehensive pictures, from which genes and proteins actively interact to lead to cellular behaviours and physiological phenotypes. As biological interactions mediate many biological processes that are essential for cellular function or disease development, it is important to systematically identify genomic information including genetic mutations from GWAS (genome-wide association study), differentially expressed genes, bidirectional promoters, intrinsic disordered proteins (IDP) and protein interactions to gain deep insights into the underlying mechanisms of gene regulations and networks. Furthermore, bidirectional promoters can co-regulate many biological pathways, where the roles of bidirectional promoters can be studied systematically for identifying co-regulating genes at interactive network level. Combining information from different but related studies can ultimately help revealing the landscape of molecular mechanisms underlying complex diseases such as cancer.
AKT1 Transcriptomic Landscape in Breast Cancer Cells
(MDPI, 2022-07-25) George, Bijesh; Gui, Bin; Raguraman, Rajeswari; Paul, Aswathy Mary; Nakshatri, Harikrishna; Pillai, Madhavan Radhakrishna; Kumar, Rakesh; Surgery, School of Medicine
Overexpression and hyperactivation of the serine/threonine protein kinase B (AKT) pathway is one of the most common cellular events in breast cancer progression. However, the nature of AKT1-specific genome-wide transcriptomic alterations in breast cancer cells and breast cancer remains unknown to this point. Here, we delineate the impact of selective AKT1 knock down using gene-specific siRNAs or inhibiting the AKT activity with a pan-AKT inhibitor VIII on the nature of transcriptomic changes in breast cancer cells using the genome-wide RNA-sequencing analysis. We found that changes in the cellular levels of AKT1 lead to changes in the levels of a set of differentially expressed genes and, in turn, imply resulting AKT1 cellular functions. In addition to an expected positive relationship between the status of AKT1 and co-expressed cellular genes, our study unexpectedly discovered an inherent role of AKT1 in inhibiting the expression of a subset of genes in both unstimulated and growth factor stimulated breast cancer cells. We found that depletion of AKT1 leads to upregulation of a subset of genes-many of which are also found to be downregulated in breast tumors with elevated high AKT1 as well as upregulated in breast tumors with no detectable AKT expression. Representative experimental validation studies in two breast cancer cell lines showed a reasonable concurrence between the expression data from the RNA-sequencing and qRT-PCR or data from ex vivo inhibition of AKT1 activity in cancer patient-derived cells. In brief, findings presented here provide a resource for further understanding of AKT1-dependent modulation of gene expression in breast cancer cells and broaden the scope and significance of AKT1 targets and their functions.
An atlas of healthy and injured cell states and niches in the human kidney
(Springer Nature, 2023) Lake, Blue B.; Menon, Rajasree; Winfree, Seth; Hu, Qiwen; Ferreira, Ricardo Melo; Kalhor, Kian; Barwinska, Daria; Otto, Edgar A.; Ferkowicz, Michael; Diep, Dinh; Plongthongkum, Nongluk; Knoten, Amanda; Urata, Sarah; Mariani, Laura H.; Naik, Abhijit S.; Eddy, Sean; Zhang, Bo; Wu, Yan; Salamon, Diane; Williams, James C.; Wang, Xin; Balderrama, Karol S.; Hoover, Paul J.; Murray, Evan; Marshall, Jamie L.; Noel, Teia; Vijayan, Anitha; Hartman, Austin; Chen, Fei; Waikar, Sushrut S.; Rosas, Sylvia E.; Wilson, Francis P.; Palevsky, Paul M.; Kiryluk, Krzysztof; Sedor, John R.; Toto, Robert D.; Parikh, Chirag R.; Kim, Eric H.; Satija, Rahul; Greka, Anna; Macosko, Evan Z.; Kharchenko, Peter V.; Gaut, Joseph P.; Hodgin, Jeffrey B.; KPMP Consortium; Eadon, Michael T.; Dagher, Pierre C.; El-Achkar, Tarek M.; Zhang, Kun; Kretzler, Matthias; Jain, Sanjay; Medicine, School of Medicine
Understanding kidney disease relies on defining the complexity of cell types and states, their associated molecular profiles and interactions within tissue neighbourhoods1. Here we applied multiple single-cell and single-nucleus assays (>400,000 nuclei or cells) and spatial imaging technologies to a broad spectrum of healthy reference kidneys (45 donors) and diseased kidneys (48 patients). This has provided a high-resolution cellular atlas of 51 main cell types, which include rare and previously undescribed cell populations. The multi-omic approach provides detailed transcriptomic profiles, regulatory factors and spatial localizations spanning the entire kidney. We also define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive (successful or maladaptive repair), transitioning and degenerative states. Molecular signatures permitted the localization of these states within injury neighbourhoods using spatial transcriptomics, while large-scale 3D imaging analysis (around 1.2 million neighbourhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways that are relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents a comprehensive benchmark of cellular states, neighbourhoods, outcome-associated signatures and publicly available interactive visualizations.
Cellular metabolism constrains innate immune responses in early human ontogeny
(Nature Research, 2018-11-16) Kan, Bernard; Michalski, Christina; Fu, Helen; Au, Hilda H.T.; Lee, Kelsey; Marchant, Elizabeth A.; Cheng, Maye F.; Anderson-Baucum, Emily; Aharoni-Simon, Michal; Tilley, Peter; Mirmira, Raghavendra G.; Ross, Colin J.; Luciani, Dan S.; Jan, Eric; Lavoie, Pascal M.; Medicine, School of Medicine
Pathogen immune responses are profoundly attenuated in fetuses and premature infants, yet the mechanisms underlying this developmental immaturity remain unclear. Here we show transcriptomic, metabolic and polysome profiling and find that monocytes isolated from infants born early in gestation display perturbations in PPAR-γ-regulated metabolic pathways, limited glycolytic capacity and reduced ribosomal activity. These metabolic changes are linked to a lack of translation of most cytokines and of MALT1 signalosome genes essential to respond to the neonatal pathogen Candida. In contrast, they have little impact on house-keeping phagocytosis functions. Transcriptome analyses further indicate a role for mTOR and its putative negative regulator DNA Damage Inducible Transcript 4-Like in regulating these metabolic constraints. Our results provide a molecular basis for the broad susceptibility to multiple pathogens in these infants, and suggest that the fetal immune system is metabolically programmed to avoid energetically costly, dispensable and potentially harmful immune responses during ontogeny.
Chronic cAMP activation induces adipocyte browning through discordant biphasic remodeling of transcriptome and chromatin accessibility
(Elsevier, 2022) So, Jisun; Taleb, Solaema; Wann, Jamie; Strobel, Olivia; Kim, Kyungchan; Roh, Hyun Cheol; Biochemistry and Molecular Biology, School of Medicine
Objective: Adipose tissue thermogenesis has been suggested as a new therapeutic target to promote energy metabolism for obesity and metabolic disease. Cold-inducible thermogenic adipocytes, called beige adipocytes, have attracted significant attention for their potent anti-obesity activity in adult humans. In this study, we identified the mechanisms underlying beige adipocyte recruitment, so-called adipocyte browning, by different stimuli. Methods: We generated a new adipocyte cell line with enhanced browning potentials and determined its transcriptomic and epigenomic responses following cAMP (forskolin, FSK) versus PPARγ activation (rosiglitazone). We performed time-course RNA-seq and compared the treatments and in vivo adipocyte browning. We also developed an improved protocol for Assay for Transposase Accessible Chromatin-sequencing (ATAC-seq) and defined changes in chromatin accessibility in a time course. The RNA-seq and ATAC-seq data were integrated to determine the kinetics of their coordinated regulation and to identify a transcription factor that drives these processes. We conducted functional studies using pharmacological and genetic approaches with specific inhibitors and shRNA-mediated knockdown, respectively. Results: FSK, not rosiglitazone, resulted in a biphasic transcriptomic response, resembling the kinetics of in vivo cold-induced browning. FSK promoted tissue remodeling first and subsequently shifted energy metabolism, concluding with a transcriptomic profile similar to that induced by rosiglitazone. The thermogenic effects of FSK were abolished by PPARγ antagonists, indicating PPARγ as a converging point. ATAC-seq uncovered that FSK leads to a significant chromatin remodeling that precedes or persists beyond transcriptomic changes, whereas rosiglitazone induces minimal changes. Motif analysis identified nuclear factor, interleukin 3 regulated (NFIL3) as a transcriptional regulator connecting the biphasic response of FSK-induced browning, as indicated by disrupted thermogenesis with NFIL3 knockdown. Conclusions: Our findings elucidated unique dynamics of the transcriptomic and epigenomic remodeling in adipocyte browning, providing new mechanistic insights into adipose thermogenesis and molecular targets for obesity treatment.

Browsing by Subject "Transcriptome"

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