Biology subjects

Pai, R.

Publications and source records attributed to Pai, R..

7 recordsLinked to original sources

bioRxiv2026

Profiling and Targeting of Regulatory RNAs to Upregulate Gene Expression

Transcription of long noncoding RNAs (lncRNAs), including enhancer RNAs (eRNAs) and promoter-associated RNAs (paRNAs), collectively termed regulatory RNAs (regRNAs), is a hallmark of active gene expression, yet it remains unknown whether regRNAs can be targeted to selectively enhance transcription in cis. We developed regRNA Capture-seq, a high-throughput method to profile regRNAs, and applied it to primary human hepatocytes, annotating thousands of regRNAs at [~]2,000 enhancers and promoters. Using this approach, we interrogated a genetically validated enhancer of the ornithine transcarbamylase (OTC) gene, mutations of which cause OTC deficiency (OTCD), the most common urea cycle disorder. Antisense oligonucleotides (ASOs) targeting enhancer-derived regRNAs led to dose-dependent upregulation of OTC in hepatocytes. Mechanistically, ASOs altered regRNA structure, elevated regRNA levels, displaced transcriptional repressors, and increased H3K27 acetylation at the targeted enhancer. This work establishes a potential therapeutic strategy for addressing haploinsufficiency and highlights regRNAs as actionable targets for ASO-mediated upregulation of gene expression.

genomics↗

bioRxiv2023

Charting spatial ligand-target activity using Renoir

The advancement of single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics has enabled the inference of cellular interactions in a tissue microenvironment. Despite the development of cell-cell interaction inference methods, there is a lack of methods capable of mapping the influence of ligands on downstream target genes across a spatial topology with specific cell type composition, with the potential to shed light on niche-specific relationship between ligands and their downstream targets. Here we present Renoir for charting the ligand-target activities across a spatial topology and delineating spatial communication niches harboring specific ligand-target activities. Renoir also spatially maps pathway-level activity of ligand-target genesets and identifies domain-specific ligand-target activities. Across spatial datasets with varying resolution (spot to single-cell) ranging from development to disease, Renoir inferred cellular niches with distinct ligand-target interactions, spatially mapped pathway activities, and identified context-specific novel cell-cell interactions. Renoir uncovers biological insights and therapeutically-relevant cellular crosstalk from spatial transcriptomics data.

bioinformatics↗

bioRxiv2023

Effect of Nivolumab therapy on Metastatic Lung Cancer in Human Microbiome

Nivolumab, a type of immunotherapy, has enhanced the 5-year survival of patients with renal cell cancer, melanoma, and lung cancer which is now mechanistically understood. However, relatively sparse information assesses its relationship with shaping the gut microbiome. We aimed to assess the degree to which nivolumab treatment contributes to alterations in the species composition of the colon in lung cancer patients undergoing nivolumab treatment. Our pilot study utilized stool samples of five lung cancer patients at Inland Hematology Oncology (IHO) before administration of nivolumab and three months after initiation of treatment. 16S and ITS rRNA sequence analysis were used to assess alterations in species abundance and richness of the colon. After sequencing, statistical analysis, specifically a paired t-test, was performed to assess if any significant differences in any microbial species were observed before and after immunotherapy treatment. Although different proportions of microorganisms existed at baseline prior to treatment for each patient, a significant reduction in the Megasphaera elsdenii population was observed (p=.0488; n=4), when comparing before and after treatment. Our findings differ from that of Huang et. al (2022), who has recently posited that a positive association exists between Megasphaera elsdenii and the survival of patients with pancreatic ductal adenocarcinomas. Our conclusions suggest that different cancers may elicit differential effects on Megasphaera elsdenii in the gut microbiome. ImportanceNivolumab is a relatively new form of cancer therapy called immunotherapy, which enables the body to use its own immune system to effectively fight cancer. Due to advances in microbial sequencing in 16S rRNA, this project explores differences in the abundance of microbial communities before and three months of treatment in patients who have advanced on chemotherapy. Our findings suggest that reduction of Megasphaera elsdenii, a metabolically active bacterium, is associated with positive outcomes, which differs from findings from other literature. Our project advocates for a more robust profiling of the microbiome during lung cancer treatment, and immunotherapy, in particular, to establish a more substantive profile of the changing gut in the midst of treatment.

cancer biology↗

bioRxiv2022

STOmics-GenX: CRISPR based approach to improve cell identity specific gene detection from spatially resolved transcriptomics

The spatial organisation of cells defines the biological functions of tissue ecosystems from development to disease. Recently, an array of technologies have been developed to query gene expression in a spatial context. These include techniques such as employing barcoded oligonucleotides, single-molecule fluorescence in situ hybridization (smFISH), and DNA nanoball (DNB)-patterned arrays. However, resolution and efficiency vary across platforms and technologies. To obtain spatially relevant biological information from spatially resolved transcriptomics, we combined the Stereo-seq workflow with CRISPRclean technology to develop the STOmics-GenX pipeline. STOmics-GenX not only allowed us to reduce genomic, mitochondrial, and ribosomal reads, but also lead to a [~]2.1-fold increase in the number of detected genes when compared to conventional Stereo-seq (STOmics). Additionally, the STOmics-GenX pipeline resulted in an improved detection of cell type specific genes, thereby improving cellular annotations. Most importantly, STOmics-GenX allowed for enhanced detection of clinically relevant biomarkers such as Alpha-fetoprotein (AFP), enabling the identification of two spatially distinct subsets of hepatocytes in hepatocellular carcinoma tissue. Thereby, combining CRISPRclean technology with STOmics not only allowed improved gene detection but also paved the way for spatial precision oncology by improved detection of clinically relevant biomarkers.

molecular biology↗

bioRxiv2022

Editing the core region in HPFH deletions alters fetal and adult globin expression for treatment of β-hemoglobinopathies

Reactivation of fetal hemoglobin (HbF) is the commonly adapted strategy to ameliorate {beta}-hemoglobinopathies. However, the continued production of defective adult hemoglobin (HbA) limits the HbF tetramer production affecting the therapeutic benefits. Here, we tested various deletional hereditary persistence of fetal hemoglobin (HPFH) mutations and identified a 11 kb sequence, encompassing Putative Repressor Region (PRR) to {beta}-globin Exon-1 ({beta}E1), as the core deletion that ablates HbA and exhibit superior production of HbF compared to HPFH or other well-established targets. The PRR-{beta}E1 edited hematopoietic stem and progenitor cells (HSPCs) retained engraftment potential to repopulate for long-term hematopoiesis in immunocompromised mice generating HbF+ cells in vivo. Importantly, the editing induces therapeutically relevant levels of HbF to reverse the phenotypes of both sickle cell disease and {beta}-thalassemia major. These results indicate that the PRR-{beta}E1 gene editing in patient HSPCs can potentially lead to superior therapeutic outcomes for {beta}-hemoglobinopathies gene therapy.

biochemistry↗

bioRxiv2020

scRNA-seq reveals ACE2 and TMPRSS2 expression in TROP2+ Liver Progenitor Cells: Implications in COVID-19 associated Liver Dysfunction

The recent pandemic of coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 was first reported in China (December 2019) and now prevalent in [~]170 countries across the globe. Entry of SARS-CoV-2 into mammalian cells require the binding of viral Spike (S) proteins to the ACE2 (angiotensin converting enzyme 2) receptor. Once entered the S protein is primed by a specialised serine protease, TMPRSS2 (Transmembrane Serine Protease 2) in the host cell. Importantly, beside respiratory symptoms, consistent with other common respiratory virus infection when patients become viraemic, a significant number of COVID-19 patients also develop liver comorbidities. We explored if specific target cell-type in the mammalian liver, could be implicated in disease pathophysiology other than the general deleterious response to cytokine storms. Here we employed single-cell RNA-seq (scRNA-seq) to survey the human liver and identified potentially implicated liver cell-type for viral ingress. We report the co-expression of ACE2 and TMPRSS2 in a TROP2+ liver progenitor population. Importantly, we fail to detect the expression of ACE2 in hepatocyte or any other liver (immune and stromal) cell types. These results indicated that in COVID-19 associated liver dysfunction and cell death, viral infection of TROP2+ progenitors in liver may significantly impaired liver regeneration and could lead to pathology. Highlights- EPCAM+ Liver progenitors co-express ACE2 and TMPRSS2 - ACE2 and TMPRSS2 expression is highest in TROP2high progenitors - ACE2 and TMPRSS2 cells express cholangiocyte biased fate markers - ACE2 and TMPRSS2 positive cells are absent in human fetal liver

genomics↗

bioRxiv2019

Super-resolution imaging reveals the evolution of higher-order chromatin folding in early carcinogenesis

Aberrant chromatin structure is a hallmark in cancer cells and has long been used for clinical diagnosis of cancer. However, underlying higher-order chromatin folding during malignant transformation remains elusive, due to the lack of molecular scale resolution. Using optimized stochastic optical reconstruction microscopy (STORM) for pathological tissue (PathSTORM), we uncovered a gradual decompaction and fragmented higher-order chromatin folding throughout all stages of carcinogenesis in multiple tumor types, even prior to the tumor formation. Our integrated imaging, genomic, and transcriptomic analyses reveal the functional consequences in enhanced formation of transcription factories, spatial juxtaposition with relaxed nanosized chromatin domains and impaired genomic stability. We also demonstrate the potential of imaging higher-order chromatin decompaction to detect high-risk precursors that cannot be distinguished by conventional pathology. Taken together, our findings reveal the gradual decompaction and fragmentation of higher-order chromatin structure as an enabling characteristic in early carcinogenesis to facilitate malignant transformation, which may improve cancer diagnosis, risk stratification, and prevention.\n\nSIGNIFICANCEGenomic DNA is folded into a higher-order structure that regulates transcription and maintains genomic stability. Although much progress has been made on understanding biochemical characteristics of epigenetic modifications in cancer, the higher-order folding of chromatin structure remains largely unknown. Using optimized super-resolution microscopy, we uncover de-compacted and fragmented chromatin folding in tumor initiation and stepwise progression in multiple tumor types, even prior to the presence of tumor cells. This study underlines the significance of unfolding higher-order chromatin structure as an enabling characteristic to promote tumorigenesis, which may facilitate the development and evaluation of new preventive strategies. The potential of imaging higher-order chromatin folding to improve cancer detection and risk stratification is demonstrated by detecting high-risk precursors that cannot be distinguished by conventional pathology.

cancer biology↗