Biology subjects

Rouchka, E. C.

Publications and source records attributed to Rouchka, E. C..

10 recordsLinked to original sources

bioRxiv2026

LVV SMRTcap reveals extensive proviral variation in lentiviral vector-transduced CAR T cells

Lentiviral vectors are commonly used to introduce chimeric antigen receptor transgenes into T cells, but routine assays quantify vector copy number or integration sites without sequencing full-length integrated vectors. HIV-1 proviruses often acquire large deletions and cytidine deaminase-driven hypermutation; whether similar variation occurs in therapeutic lentiviral vectors is unclear. We adapted a novel long-read capture approach to enrich long fragments spanning vector DNA and adjacent human sequence, enabling simultaneous integration-site mapping and proviral integrity analysis with single-molecule resolution. In research-grade CAR T cells produced with an experimental, transient-transfection lentiviral vector workflow, 40% of integrated vectors carried recurrent deletions that removed the internal promoter or parts of the chimeric antigen receptor cassette. The dominant promoter deletion was present in the viral stock. In clinical chimeric antigen receptor T cell products, promoter deletions were less frequent, but detectable pre-infusion and post-infusion. Across datasets we observed widespread G-to-A substitutions consistent with restriction factor editing, including changes predicted to introduce premature stop codons within the transgene open reading frame. Our method reveals proviral variants invisible to standard quality-control assays and provides a framework to improve vector production and monitor transgene integrity in clinical products.

cancer biology↗

bioRxiv2025

Impact of integration on persistent homology clustering and biological signal detection in scRNA-seq data

BackgroundAs the availability of single-cell RNA sequencing (scRNA-seq) data expands, there is a growing need for robust methods that enable integration and comparison across diverse biological conditions and experimental protocols. Persistent homology (PH), a technique from topological data analysis (TDA), provides a deformation-invariant framework for capturing structural patterns in high-dimensional data. MethodsIn this study, PH was applied to a diverse collection of scRNA-seq datasets spanning eight tissue types to investigate how data integration affects the topological features and biological interpretability of the resulting representations. Clustering was performed based on PH-derived pairwise distances and global topological structure was assessed through Betti curves, Euler characteristics, and persistence landscapes. By comparing these summaries across raw, normalized, and integrated datasets, we examined whether integration enhances the detection of biologically meaningful patterns, or, conversely, obscures fine-scale structure. ResultsThis approach demonstrates that PH can serve as a powerful complementary strategy for evaluating the impact of integration and reveals how topological summaries can help disentangle biological signal from batch-related noise in single-cell data. This work establishes a framework for using topological methods to assess integration quality and highlights new avenues for interpreting complex transcriptomic landscapes beyond conventional clustering.

bioinformatics↗

bioRxiv2023

Structural and functional classification of G-quadruplex families within the human genome

G quadruplexes are short secondary DNA structures located throughout genomic DNA and transcribed RNA. though G4 structures have been shown to form in vivo, no current search tools are known to exist to examine these structures based on previously identified G quadruplexes, much less filter them based on similar sequence, structure, and thermodynamic properties. We present a framework for clustering G quadruplex sequences into families using the CD-HIT, MeShClust and DNACLUST methods along with a combination of Starcode and BLAST. Utilizing this framework to filter and annotate clusters, 95 families of G quadruplex sequences were identified within the human genome. Profiles for each family were created using hidden Markov models to allow for identification of additional family members and generate homology probability scores. The thermodynamic folding energy properties, functional annotation of genes associated with the sequences, scores from different prediction algorithms and transcription factor binding and motif to the G4 region for the sequences within a family were used to annotate and compare the diversity within and across clusters. The resulting set of G quadruplex families can be used to further understand how different regions of the genome are regulated by factors targeting specific structures common to members of a specific cluster.

bioinformatics↗

bioRxiv2023

Construction of a searchable database for gene expression changes in spinal cord injury experiments

Spinal cord injury (SCI) is a debilitating disease resulting in an estimated 18,000 new cases in the United States on an annual basis. Significant behavioral research on animal models has led to a large amount of data, some of which has been catalogued in the Open Data Commons for Spinal Cord Injury (ODC-SCI). More recently, high throughput sequencing experiments have been utilized to understand molecular mechanisms associated with SCI, with nearly 6,000 samples from over 90 studies available in the Sequence Read Archive. However, to date, no resource is available for efficiently mining high throughput sequencing data from SCI experiments. Therefore, we have developed a protocol for processing RNA-Seq samples from high-throughput sequencing experiments related to SCI resulting in both raw and normalized data that can be efficiently mined for comparisons across studies as well as homologous discovery across species. We have processed 1,196 publicly available RNA-seq samples from 50 bulk RNA-Seq studies across nine different species, resulting in an SQLite database that can be used by the SCI research community for further discovery. We provide both the database as well as a web-based front-end that can be used to query the database for genes of interest, differential gene expression, genes with high variance, and gene set enrichments.

bioinformatics↗

bioRxiv2023

Analysis of nucleotide variations in human g-quadruplex forming regions associated with disease states

While the role of G4 G quadruplex structures has been identified in cancers and metabolic disorders, single nucleotide variations (SNVs) and their effect on G4s in disease contexts have not been extensively studied. The COSMIC and CLINVAR databases were used to detect SNVs present in G4s to identify sequence level changes and their effect on alteration of G4 secondary structure. 37,515 G4 SNVs in the COSMIC database and 2,115 in CLINVAR were identified. Of those, 7,236 COSMIC (19.3%) and 416 (18%) of the CLINVAR variants result in G4 loss, while 2,728 (COSMIC) and 112 (CLINVAR) SNVs gain a G4 structure. The gene ontology term "GnRH (Gonadotropin-releasing hormone) secretion" is enriched in 21 genes in this pathway that have a G4 destabilizing SNV. Analysis of mutational patterns in the G4 structure show a higher selective pressure (3-fold) in the coding region on the template strand compared to the non-template strand. At the same time, an equal proportion of SNVs were observed among intronic, promoter and enhancer regions across strands. Using GO and pathway enrichment, genes with SNVs for G4 forming propensity in the coding region are enriched for Regulation of Ras protein signal transduction and Src homology 3 (SH3) domain binding.

genomics↗

bioRxiv2022

Reactive myelopoiesis and FX-expressing monocyte-derived macrophages triggered by chemotherapy promote cancer lung metastasis

Chemotherapy offers long-term clinical benefits to many cancer patients. However, several pre-clinical studies have demonstrated that certain cytotoxic drugs enhance metastasis via multiple mechanisms. These studies have mainly focused on tumor cell-derived inflammation. The importance of host responses triggered by chemotherapy in regulating cancer metastasis has not been fully explored. Here, we showed that multi-dose Gemcitabine (GEM) treatment promoted breast cancer lung metastasis in a transgenic spontaneous breast cancer animal model. Both CCR2+ macrophages and monocytes were increased in the lungs of GEM-treated mice. Further, the increase of CCR2+ macrophages and monocytes were observed in naive (tumor-free) mice after GEM treatment. These changes were largely caused by chemotherapy-induced reactive myelopoiesis that are biased toward monocyte development. Mechanistically, enhanced production of mitochondrial ROS (mtROS) was observed in GEM-treated BM LSK cells and monocytes. Treatment with the mitochondrial targeted antioxidant abrogated GEM induced hyper differentiation of BM progenitors. In addition, GEM treatment induced up-regulation of host cell-derived CCL2, and CCL2/CCR2 axis played essential role in the pro-metastatic host response induced by chemotherapy. Further, GEM and Paclitaxel (PTX) in combination with Doxorubicin (DOX) treatment resulted in up-regulation of coagulation factor X (FX) in lung interstitial macrophages. Targeting activated FX (FXa) using FXa inhibitor or F10 gene knockdown reduced pro-metastatic effect of chemotherapy-triggered host response. Together, these studies suggest a novel mechanism for chemotherapy induced metastasis via the host response-induced accumulation of monocytes/macrophages and interplay between coagulation and inflammation in the lungs.

immunology↗

bioRxiv2022

Shoc2 controls ERK1/2-driven neural crest development by balancing components of the extracellular matrix

The extracellular signal-regulated kinase (ERK1/2) pathway is essential in embryonic development. The scaffold protein Shoc2 is a critical modulator of ERK1/2 signals, and mutations in the shoc2 gene lead to the human developmental disease known as Noonan-like syndrome with loose anagen hair (NSLH). The loss of Shoc2 and the shoc2 NSLH-causing mutations affect the tissues of neural crest (NC) origin. In this study, we utilized the zebrafish model to dissect the role of Shoc2-ERK1/2 signals in the development of NC. These studies established that the loss of Shoc2 significantly altered the expression of transcription factors regulating the specification and differentiation of NC cells. Using comparative transcriptome analysis of NC-derived cells from shoc2 CRISPR/Cas9 mutant larvae, we found that Shoc2-mediated signals regulate gene programs at several levels, including expression of genes coding for the proteins of extracellular matrix (ECM) and ECM regulators. Together, our results demonstrate that Shoc2 is an essential regulator of NC development. This study also indicates that disbalance in the turnover of the ECM may lead to the abnormalities found in NSLH patients.

developmental biology↗

bioRxiv2017

Elucidation of dose-dependent transcriptional events immediately following ionizing radiation exposure

Long duration space missions expose astronauts to ionizing radiation events associated with highly energetic and charged heavy particles. Such exposure can result in chromosomal aberrations increasing the likelihood of the development of cancer. Early detection and mitigation of these events is critical in providing positive outcomes. In order to aid in the development of portable devices used to measure radiation exposure, we constructed a genome-wide screen to detect transcriptional changes in peripheral blood lymphocytes shortly after (approximately 1 hour) radiation exposure at low (0.3 Gy), medium (1.5 Gy) and high (3.0 Gy) doses compared to control (0.0 Gy) using Affymetrix(R) Human Gene 1.0 ST v1 microarrays. Our results indicate a number of sensitive and specific transcriptional profiles induced by radiation exposure that can potentially be implemented as biomarkers for radiation exposure as well as dose effect. For overall immediate radiation exposure, KDELC1, MRPS30, RARS, and HEXIM1 were determined to be effective biomarkers while PRDM9, CHST4, and SLC26A10 were determined to be biomarkers specific to 0.3 Gy exposure; RPH, CCDC96, WDYHV1, and IFNA16 were identified for 1.5 Gy exposure; and CWC15, CHCHD7, and DNAAF2 were determined to be sensitive and specific to 3.0 Gy exposure. The resulting raw and analyzed data are publicly available through NCBI's Gene Expression Ominibus via accession GSE64375.

bioinformatics↗

bioRxiv2017

Identification of putative G-quadruplex forming sequences in three manatee papillomaviruses

The Florida manatee (Trichechus manatus latirotris) is considered a threatened aquatic mammal in United States coastal waters. Over the past decade, the appearance of papillomavirus-induced lesions and viral papillomatosis in manatees has been a concern for those involved in the management and rehabilitation of this species. To date, three manatee papillomaviruses (PVs) have been identified in Florida manatees, one forming cutaneous lesions (TmPV1) and two forming genital lesions (TmPV3 and TmPV4). In this study, we identified DNA sequences with the potential to form G-quadruplex structures in all three PVs. G-quadruplex structures (G4) are guanine-rich nucleic acid sequences capable of forming secondary structures in DNA and RNA. In humans, G4 are known to regulate molecular processes such as transcription and translation. Although G4 have been identified in several viral genomes, including human PVs, no attempt has been made to identify G4 in animal PVs. We found that sequences capable of forming G4 were present on both DNA strands and across coding and non-coding regions on all PVs. The vast majority of the identified sequences would allow the formation of non-canonical structures with only two G-tetrads. The formation of one such structure was supported through biophysical analysis. Computational analysis demonstrated enrichment of G4 sequences on the reverse strand in the E2/E4 region on all manatee PVs and on the forward strand in the E2/E4 region on one genital PV. Several G4 sequences occurred at similar regional locations on all PVs, most notably on the reverse strand in the E2 region. In other cases, G4 were identified at similar regional locations only on PVs forming genital lesions. On all PVs, G4 sequences were located near putative E2 binding sites in the non-coding region. Together, these findings suggest that G4 are likely regulatory elements in manatee PVs.\n\nAuthor summaryG-quadruplex structures (G4) are found in the DNA and RNA of many species and are known to regulate the expression of genes and the synthesis of proteins, among other important molecular processes. Recently, these structures have been identified in several viruses, including the human papillomavirus (PV). As regulatory structures, G4 are of great interest to researchers as drug targets for viral control. In this paper, we identify the first G4 sequences in three PVs infecting a non-human animal, the Florida manatee. Through computational and biophysical analysis, we find that a greater variety of sequence patterns may underlie the formation of these structures than previously identified. The sequences are found in all protein coding regions of the virus and near sites for viral replication in non-coding regions. Furthermore, the distribution of these sequences across the PV genomes supports the notion that sequences are conserved across PV types, suggesting they are under selective pressure. This paper extends previous research on G4 in human PVs with additional evidence for their role as regulators. The G4 sequences we identified also provide potential regulatory targets for researchers interested in controlling this virus in the Florida manatee, a threatened aquatic mammal.

molecular biology↗

bioRxiv2017

Framework For Reanalysis Of Publicly Available Affymetrix(R) Genechip(R) Data Sets Based On Functional Regions Of Interest

BackgroundSince the introduction of microarrays in 1995, researchers world-wide have used both commercial and custom-designed microarrays for understanding differential expression of transcribed genes. Public databases such as ArrayExpress and the Gene Expression Omnibus (GEO) have made millions of samples readily available. One main drawback to microarray data analysis involves the selection of probes to represent a specific transcript of interest, particularly in light of the fact that transcript-specific knowledge (notably alternative splicing) is dynamic in nature.\n\nResultsWe therefore developed a framework for reannotating and reassigning probe groups for Affymetrix(R) GeneChip(R) technology based on functional regions of interest. This framework addresses three issues of Affymetrix(R) GeneChip(R) data analyses: removing nonspecific probes, updating probe target mapping based on the latest genome knowledge and grouping probes into gene, transcript and region-based (UTR, individual exon, CDS) probe sets. Updated gene and transcript probe sets provide more specific analysis results based on current genomic and transcriptomic knowledge. The framework selects unique probes, aligns them to gene annotations and generates a custom Chip Description File (CDF). The analysis reveals only 87% of the Affymetrix(R) GeneChip(R) HG-U133 Plus 2 probes uniquely align to the current hg38 human assembly without mismatches. We also tested new mappings on the publicly available data series using rat and human data from GSE48611 and GSE72551 obtained from GEO, and illustrate that functional grouping allows for the subtle detection of regions of interest likely to have phenotypical consequences.\n\nConclusionThrough reanalysis of the publicly available data series GSE48611 and GSE72551, we profiled the contribution of UTR and CDS regions to the gene expression levels globally. The comparison between region and gene based results indicated that the detected expressed genes by gene-based and region-based CDFs show high consistency and regions based results allows us to detection of changes in transcript formation.

bioinformatics↗