Biology subjects

Jabeen, A.

Publications and source records attributed to Jabeen, A..

8 recordsLinked to original sources

bioRxiv2025

Structural insights into DNA annealing and recombination by herpesviral DNA-binding proteins ICP8 and BALF2

The DNA-binding proteins of herpesviruses are key factors involved in multiple stages of DNA replication and recombination. The well-studied ICP8 protein of Herpes Simplex Virus 1 binds single-stranded DNA in a cooperative manner and facilitates the annealing of complementary DNA strands in a process that involves the formation of double helical filaments. Moreover, it cooperates with UL12 alkaline nuclease to execute recombination between homologous DNA sequences. In this work, we present the structures of ICP8 and its homolog BALF2 of the Epstein-Barr Virus in complexes with DNA. These structures reveal a conserved conformation of the bound DNA in which several bases are rotated away from the protein, enabling homology search and base-pairing. The crystal structures of ICP8-DNA depict the pairing between two DNA strands, showing the flexibility of base-pairing. In the structure of the double filament of ICP8, we visualize the interactions between protein subunits within and between the antiparallel strands. Finally, we present the first complete structure of a ternary recombinase complex composed of ICP8 and UL12 bound to a model DNA. This structural landscape illustrates the different stages of the DNA recombination process in herpesviruses, shedding light on molecular mechanisms of their replication.

molecular biology↗

bioRxiv2025

SLFN11 Enhances Cisplatin Sensitivity in Pediatric Cancer via Activation of Stress-Response and Suppression of Survival Pathways

Pediatric cancers pose significant treatment challenges due to their biological heterogeneity and variable responses to chemotherapy. SLFN11, a DNA/RNA helicase-like protein known to sensitize adult tumors to DNA-damaging agents, remains underexplored in pediatric malignancies. Here, we investigate the role of SLFN11 across pediatric Wilms tumor, osteosarcoma, and medulloblastoma using integrated bioinformatics, epigenetic profiling, and functional assays. In silico analysis of TARGET and ICGC datasets revealed distinct correlations between SLFN11 expression and patient survival, with positive, negative, or neutral predictive value depending on tumor type. Baseline expression and promoter methylation analysis in pediatric cancer cell lines demonstrated epigenetic regulation of SLFN11, similar to adult cancers. Using CRISPR-dCas9-mediated activation, we successfully upregulated SLFN11, which significantly enhanced sensitivity to cisplatin and the PARP inhibitor talazoparib across all tested cell lines. Transcriptomic profiling under cisplatin treatment indicated that SLFN11 modulates DNA damage response and MAPK signaling pathways, potentially contributing to chemotherapy sensitivity. These findings establish SLFN11 as a context-dependent predictive biomarker and a potential therapeutic target to overcome chemoresistance in pediatric solid cancers.

cancer biology↗

bioRxiv2024

MUC2 Expression Modulates Immune Infiltration in Colorectal Cancer

IntroductionColorectal cancer (CRC) is a prevalent malignancy with significant morbidity and mortality worldwide. A deeper understanding of the interaction of cancer cells with other cells in the tumor microenvironment is crucial for devising effective therapeutic strategies. MUC2, a major component of the protective mucus layer in the gastrointestinal tract, has been implicated in CRC progression and immune response regulation. MethodIn this study, we sought to elucidate the relationship between MUC2 expression and immune infiltration within CRC, using in-vitro models involving two well-established cell lines, HT-29 and LS-174T. By employing CRISPR-mediated MUC2 knockout, we investigated the influence of MUC2 on tumor immune infiltration and its interplay with T cells and NK cells enriched peripheral blood mononuclear cells (PBMCs) in 3D spheroid cultures. ResultsWhile MUC2 was more abundant in LS-174T cell lines compared to HT-29, its knockout resulted in increased immune infiltration solely in the HT-29 cell line, but not in LS-174T. We revealed that the removal of MUC2 protein was compensated in LS-174T by the expression of other gel forming mucin proteins (Muc6, Muc5B) commonly expressed in gastrointestinal epithelium, while this was not observed in HT-29 cell line. DiscussionWe propose that the role of MUC2 documented in CRC progression can partially be explained by impairing immune infiltration due to physical barrier established by the gel forming proteins such as MUC2 in mucinous CRC. On the other hand, the removal of MUC2 expression can be compensated by alternative gel forming mucin proteins, thereby impeding any increase in tumor immune infiltration.

cancer biology↗

bioRxiv2023

Collection of Non Timber Forest Products (NTFPs) and their contribution to sustainable rural livelihoods in selected areas around Ayubia National Park, Pakistan

This study shows the Collection of Non Timber Forest Products (NTFPs) and their contribution to sustainable rural livelihoods in selected areas around Ayubia National Park, Pakistan. Forests are an important component for daily life of rural residents living near forested areas. A protected area is a geographically designated area for the purpose of biological conservation. Ayubia National Park (ANP) is a protected area in KPK, Pakistan that was designated with the purpose of management and preservation of nature. Non Timber Forest Products (NTFPs) have been defined as "All biological materials, excluding timber, which are extracted from forests for human use". NTFPs play an important role in income generation for indigenous people. Malaach Village, Pasala Village and Khanuspur Town present around ANP were selected study areas. Purposive sampling was used for selection of study areas. Quantitative research was done. Field visits were done for Questionnaire survey. 50 questionnaires were filled from each selected village/town and results were analysed using SPSS. Cross tabulation was done and Chi Square test was applied. It was found that Wild Vegetables, Wild Fruits, Medicinal Plants and Mushrooms are collected from forests in and around ANP by indigenous people. Chi square results showed significant relationship between gender and collection of NTFPs. Poverty is found to be the main reason for collecting NTFPs. Contribution of NTFPs to annual income of people is mostly less than 20% but this contribution is also 21%-40% and even 41%-60% for few people. ANP should be managed properly to inhibit the collection of NTFPs within the park. Indigenous people should cooperate in sustainable collection and use of NTFPs. The role of NTFPs to livelihoods in and around ANP are clearly understood by study and will be useful in the awareness and implementation of the conservation practices in the Ayubia National Park.

ecology↗

bioRxiv2023

Modulation of SLFN11 induces changes in DNA Damage response

BackgroundLack of Schlafen family member 11 (SLFN11) expression has been recently identified as a dominant genomic determinant of response to DNA damaging agents in numerous cancer types. Thus, strategies aimed at increasing SLFN11 could be used to restore chemosensitivity of refractory cancers. As oncogenic downregulation is often driven by methylation of the promotor region, we explore the demethylation effect of 5-aza-2-deoxycytidine (decitabine), on the SLFN11 gene methylation. Since SLFN11 has been reported as an interferon inducible gene, and interferon is secreted during an active anti-tumor immune response, we investigated the in vitro effect of IFN-{gamma} on SLFN11 expression in breast cancer cell lines. A second broader approach to show cross talk between immune cells and SLFN11 expression is indirect co-culture of breast cancer cells with activated PBMCs and evaluate if this can drive SLFN11 upregulation. Finally, as a definitive and specific way to modulate SLFN11 expression we implemented SLFN11 dCas9 (dead CRISPR associated protein 9) systems to specifically increase or decrease SLFN11 expression. ResultsWe first confirmed a correlation previously reported between methylation of SLFN11 promoter and its expression across multiple cell lines. We showed in-vitro that decitabine and IFN-{gamma} could increase moderately the expression of SLFN11 in both BT- 549 and T47D cell lines, but not in strongly methylated cell lines such as MDA-MB-231. Though, in-vitro, the co-culture of the same cell lines with CD8-CD25 activated PBMC failed to increase SLFN11 expression. On the one hand, the use of a CRISPR-dCas9 UNISAM system could increase SLFN11 expression significantly (up to 5-fold), stably and specifically in BT-549 and T47D cancer cell lines. Though, this system also failed to force a strong expression of SLFN11 in cell lines with robust SLFN11 promoter methylation such as MDA-MB-231. On the other hand, the use of CRISPR-dCas9 KRAB could significantly reduce the expression of SLFN11 in BT-549 and T47D. We then used the modified cell lines to confirm the alteration in chemo sensitivity of those cells to treatment with DNA Damaging Agents (DDAs) such as Cisplatin and Epirubicin or DNA Damage Response (DDRs) drugs like Olaparib. RNAseq was used to elucidate the mechanisms of action affected by the alteration in SLFN11 expression. ConclusionTo our knowledge this is the first report of the stable non-lethal increase of SLFN11 expression in a cancer cell line. Our results show that induction of SLFN11 expression can enhance DDA and DDR sensitivity in breast cancer cells and dCas9 systems may represent a novel approach to increase SLFN11 and achieve higher sensitivity to chemotherapeutic agents, improving outcome or decreasing required drug concentrations. SLFN11-targeting therapies might be explored pre-clinically to develop personalized approaches.

cancer biology↗

bioRxiv2021

TRPA1: A Potential Prognostic Indicator for Oral Squamous Cell Carcinoma

IntroductionTransient receptors are related to oral cancer pain. Previously capsaicin (TRPV1 agonist) was shown to induce cell death in oral cancer cells. We hypothesised that these receptors are present in oral cancer. MethodWe examined the presence of cannabinoid receptors (CB1 and CB2) and targets (TRPV1, TRPA1, CaV 3.1, CaV 3.2, CaV 3.3) via quantitative polymerase chain reaction (qPCR) in oral cancer cells SCC4, SCC9, SCC25, Cal27, and normal oral cell line OKF6. ResultCannabinoid receptors are absent in all the cell lines, while TRPA1 is only present in normal cells, but absent in all the oral cancer cell lines. Voltage-gated calcium channels are present in all the cell lines. Conclusion and Future AspectsTRPA1 could be the possible future prognostic indicator of oral squamous cell carcinoma. Future functionality assays could use precancerous cell lines to follow the loss of TRPA1.

cell biology↗

bioRxiv2018

Differential Expression Analysis of ZIKV Infected Human RNA Sequence Reveals Potential Biomarkers

Zika virus (ZIKV) is considered to be an emerging viral outbreak due to its link to diseases like microcephaly, Guillain-Barre Syndrome in human. In this paper, we identify differentially expressed genes (DEGs) using RNA-seq data. In this study, we adopted the RNA-seq analysis pipeline to quantify RNA-seq data into read counts. Our analysis uncovers the significant DEGs which may be involved in the altered biological process somehow. Here, we report the list of significant DEGs, out of which three genes are found to be highly differentially expressed. In addition, our analysis also predicts other moderate DEGs, low DEGs whose differential expression was induced due to ZIKV infections.

bioinformatics↗

bioRxiv2017

Machine Learning-Based State-Of-The-Art Methods For The Classification Of RNA-Seq Data

RNA-Seq measures expression levels of several transcripts simultaneously. The identified reads can be gene, exon, or other region of interest. Various computational tools have been developed for studying pathogen or virus from RNA-Seq data by classifying them according to the attributes in several predefined classes, but still computational tools and approaches to analyze complex datasets are still lacking. The development of classification models is highly recommended for disease diagnosis and classification, disease monitoring at molecular level as well as researching for potential disease biomarkers. In this chapter, we are going to discuss various machine learning approaches for RNA-Seq data classification and their implementation. Advancements in bioinformatics, along with developments in machine learning based classification, would provide powerful toolboxes for classifying transcriptome information available through RNA-Seq data.

bioinformatics↗