Biology subjects

Abdullah, N.

Publications and source records attributed to Abdullah, N..

7 recordsLinked to original sources

bioRxiv2026

Exosome-like biogenesis from the Golgi releases extracellular vesicles lacking conventional tetraspanins that mediate immune evasion in cancer

Immunotherapy has improved survival across multiple malignancies but remains largely ineffective in solid cancers such as lung, breast, and pancreatic cancer. A key driver of resistance is the immunosuppressive tumor microenvironment (TME). Although numerous mediators of TME immunosuppression have been identified, therapeutic targeting has provided limited clinical benefit. Tumor-derived extracellular vesicles (EVs) have recently emerged as contributors to resistance, yet their mechanisms remain unclear. We developed human non-small cell lung cancer models to investigate EV-mediated immunosuppression. We identified a distinct Golgi-derived EV subpopulation that potently suppress T cell function and tumor infiltration. These EVs express the trans-Golgi network marker TGOLN2, and exhibit minimal levels of canonical EV markers. TGOLN2 overexpression drives this suppressive phenotype. Clinically, elevated TGOLN2 associates with poor survival and correlate with an immunosuppressive TME signature across more than 20 cancer types, including NSCLC. Collectively, this work defines a previously unrecognized mechanism of TGOLN2-driven, EV-mediated immunosuppression. Statement of SignificanceWe revealed TGOLN2 overexpression as a new immune evasion mechanism that mediates T cell suppression through increased secretion of a Golgi-derived extracellular vesicle (EV) subpopulation. These findings redefine current paradigms of EV biology and nominate TGOLN2 as a potential biomarker and therapeutic target in immunosuppressive cancers.

cell biology↗

bioRxiv2025

Genome-Wide CRISPR/Cas9 Screening Reveals Lipid Metabolism and Inflammatory Signalling as Modulators of Ganoderic Acid DM Cytotoxicity

Ganoderic Acid DM (GA-DM), a triterpenoid derived from Ganoderma lucidum, exhibits anti-cancer and anti-diabetic activities, but the underlying mechanisms of action remain unclear. To identify genetic modulators of GA-DM response, we conducted a genome-wide CRISPR/Cas9 knockout screen in human melanoma cells. The screen revealed key roles for genes regulating lipid metabolism and inflammatory signalling, particularly the SREBP (Sterol Regulatory Element-binding Protein) and NF-{kappa}B (Nuclear Factor kappa-light-chain-enhancer of activated B cells) pathways, in the cellular response to GA-DM. While loss of genes involved in regulation of cholesterol biosynthesis conferred resistance to GA-DM, the disruption of ubiquitin-mediated proteolysis and the Hippo pathway genes sensitised cells to GA-DM. Inflammatory genes enriched at later time points suggests that a delayed cellular response contributes to cytotoxicity. Our findings propose a mechanistic model wherein GA-DM perturbs lipid and inflammatory pathways to exert cytotoxic effects and highlights potential targets to enhance its therapeutic efficacy. This work demonstrates the utility of functional genomics in elucidating natural product mechanisms and guiding rational drug development.

genomics↗

bioRxiv2025

Oral Microbiota Interactions with Titanium Implants: A pilot in-vivo and in-vitro study on the impact of Peri-implantitis

IntroductionDental implant therapy is widely recognized as the best solution for replacing missing teeth. However, it still has a 1.9-11% failure rate. Oral microbiota is suspected to play a significant role in implant failure and peri-implant infections. Hence the impact of oral microbiota on titanium dental implants, particularly in the context of dysbiosis and peri-implant diseases, was investigated by in-vivo and in-vitro methods in this study. Materials and MethodsThis pilot study aimed to investigate the role of oral microbiota in peri-implant diseases associated with titanium implants. For the in-vivo study, oral microbiota was collected from titanium and hydroxyapatite (tooth-mimicking) discs placed in a custom-made intra-oral device worn by four healthy subjects. Biofilm formation, pathobionts, and bacterial diversity were assessed using DAPI staining, qPCR, and next generation sequencing (NGS)-16S rRNA sequencing. For the in-vitro study scanning electron microscopy was employed to examine the effect of oral pathogens on titanium implants. ResultsThe study found enhanced biofilm formation on titanium implants compared to controls (p < 0.0002). Systematic colonization by Streptococcus oralis, Actinomyces naeslundii, Veillonella parvula, Fusobacterium nucleatum, Porphyromonas gingivalis, and Aggregatibacter actinomycetemcomitans was observed. An abundance of Firmicutes and Bacteroidetes, with a decrease in Proteobacteria on titanium implants was observed by NGS. SEM showed corrosion and damage to titanium implants caused by oral pathogens. ConclusionThe results demonstrate that the use of titanium-based dental implants promotes oral microbiota dysbiosis, tipping the scale towards oral pathogens, which in turn contributes to the damage of the titanium implant surface. Increased biofilm formation of periodontal pathogens and microbial dysbiosis may play a role in implant failure and peri-implant diseases.

cell biology↗

bioRxiv2023

Induction of antiviral Interferon-Stimulated Genes (ISGs) by neuronal STING promotes the resolution of pain

Inflammation and pain are intertwined responses to injury, infection, or chronic diseases. While acute inflammation is essential in determining pain resolution and opioid analgesia, maladaptive processes occurring during resolution can lead to the transition to chronic pain. Here we found that inflammation activates the cytosolic DNA-sensing protein Stimulator of Interferon Genes (STING) in DRG nociceptors. Neuronal activation of STING promotes signaling through TANK-binding kinase 1 (TBK1) and triggers an interferon-beta (IFN{beta}) response that mediates pain resolution. Notably, we found that mice expressing a nociceptor-specific gain-of-function mutation in STING exhibited an IFN gene signature that reduced nociceptor excitability and inflammatory hyperalgesia through a KChIP1-Kv4.3 regulation. Our findings reveal a role of IFN-regulated genes (IRGs) and KChIP1 downstream of STING, in the resolution of inflammatory pain.

neuroscience↗

bioRxiv2020

A common human variant of GIPR improves systemic glucose homeostasis in a sexual dimorphic manner

Glucose-dependent insulinotropic polypeptide (GIP) has a role in controlling postprandial metabolic tone. In humans, a GIP receptor (GIPR) variant (Q354, rs1800437) is associated with a lower body mass index (BMI) and increased risk for Type 2 Diabetes. To isolate the contribution of GIPR in metabolic control, we generated a mouse model of the GIPR-Q354 variant (GIPR-Q350 mice). Female GIPR-Q350 mice are leaner than littermate controls, and male GIPR-Q350 mice are resistant to diet-induced obesity, in line with the association of the variant with reduced BMI in humans. GIPR-Q350 mice of both sexes are more glucose tolerant and exhibit an increased sensitivity to GIP. Postprandial GIP levels are reduced in GIPR-Q350 mice, revealing feedback regulation that balances the increased sensitivity of GIP target tissues to secretion of GIP from intestinal endocrine cells. The increased GIP sensitivity is recapitulated ex vivo during glucose stimulated insulin secretion assays in islets. Generation of cAMP in islets downstream of GIPR activation is not affected by the Q354 substitution. However, post-activation traffic of GIPR-Q354 variant in {beta}-cells is altered, characterized by enhanced intracellular dwell time and increased localization to the Trans-Golgi Network (TGN). Consequently, our data link altered intracellular traffic of the GIPR-Q354 variant with GIP control of metabolism. We propose that this change in spatiotemporal signaling underlies the physiologic effects of GIPR-Q350/4 and GIPR-E350/4 in mice and humans. These findings contribute to a more complete understanding of the impact of GIPR-Q354 variant on glucose homeostasis that could perhaps be leveraged to enhance pharmacologic targeting of GIPR for the treatment of metabolic disease.

physiology↗

bioRxiv2020

LC-Based Metabolomics and Multivariate Analyses Reveal Metabolite Variations in Different Propagation Methods of Eurycoma longifolia Roots Harvested at Different Ages and Locations

Eurycoma longifolia is a well-known medicinal plant with pharmacological effects and important bioactive compounds such as alkaloids and quassinoids. The suitable age of harvesting E. longifolia root for commercial use is relatively unknown and could influence the overall bioactive compounds present in the plant. In this study, non-targeted liquid chromatography mass spectrometer (LC-MS) and multivariate analyses (MVA) were performed to determine the chemical constituent of aqueous extract of 3-month-old E. longifolia hairy root (HR) culture, 1-, 4- and 11-year-old harvested E. longifolia roots. Unsupervised principle component analysis (PCA) and supervised partial least square discriminant analysis (PLSDA) were applied to evaluate metabolic similarities and differences in E. longifolia roots and hairy root in response to different harvesting age, locations and propagation methods. A total of 34 significant buckets with variable importance in projection (VIP) exceeding 1 were selected and identified. It was found that putatively identified quassinoids were significantly higher in 1-, 4- and 11-year-old E. longifolia roots whereas putative canthin-6-one alkaloids were abundantly present in 3-month-old E. longifolia hairy root (HR). These findings may be applicable to improve the harvesting age and increase the content of bioactive compounds in E. longifolia roots.

systems biology↗

bioRxiv2018

Comparison of Prognostic Accuracy of the quick Sepsis-Related Organ Failure Assessment between Short- & Long-term Mortality in Patients Presenting Outside of The Intensive Care Unit - A Systematic Review & Meta-analysis

ObjectiveIn year 2016, quick Sepsis-Related Organ Failure Assessment (qSOFA) was introduced as a better sepsis screening tool compared to systemic inflammatory response syndrome (SIRS). The purpose of this systematic review and meta-analysis is to evaluate the ability of the qSOFA in predicting short- and long-term mortality among patients outside the intensive care unit setting.\n\nMethodStudies reporting on the qSOFA and mortality from MEDLINE (published between 1946 and 15th December 2017) and SCOPUS (published before 15th December 2017). Hand-checking of the references of relevant articles was carried out. Studies were included if they involved inclusion of patients presenting to the ED; usage of Sepsis-3 definition with suspected infection; usage of qSOFA score for mortality prognostication; and written in English. Study details, patient demographics, qSOFA scores, short-term (<30 days) and long-term ([≥]30 days) mortality were extracted. Two reviewers conducted all reviews and data extraction independently.\n\nResults and DiscussionA total of 39 studies met the selection criteria for full text review and only 36 studies were included. Data on qSOFA scores and mortality rate were extracted from 36 studies from 15 countries. The pooled odds ratio was 5.5 and 4.7 for short-term and long-term mortality respectively. The overall pooled sensitivity and specificity for the qSOFA was 48% and 85% for short-term mortality and 32% and 92% for long-term mortality, respectively. Studies reporting on short-term mortality were heterogeneous (Tau=24%, I2=94%, P<0.001), while long-term mortality studies were homogenous (Tau=0%, I2<0.001, P=0.52). The factors contributing to heterogeneity may be wide age group, various clinical settings, variation in the timing of qSOFA scoring, and broad range of clinical diagnosis and criteria. There was no publication bias for short-term mortality analysis.\n\nConclusionqSOFA score showed a poor sensitivity but moderate specificity for both short and long-term mortality prediction in patients with suspected infection. qSOFA score may be a cost-effective tool for sepsis prognostication outside of the ICU setting.

epidemiology↗