Biology subjects

Aziz, M.

Publications and source records attributed to Aziz, M..

11 recordsLinked to original sources

bioRxiv2026

Robust Identification of Drug Mechanism of Action Associated Genes Across Heterogeneous Drug Treated Datasets

Identifying genes associated with the mechanism of action (MOA) of anticancer therapies is essential for understanding drug response. Functional genomics approaches, including genome-wide CRISPR knock out screens, enable systematic gene prioritization following treatment; however, findings from individual datasets are typically interpreted after identifying overlapping genes across datasets to confirm biological hypotheses. Integrating such heterogeneous datasets remains challenging due to variability across experimental conditions. Existing approaches can miss biologically relevant genes due to dataset-specific noise, can fail to capture genes exhibiting consistent but moderate effects across studies. Here, we present ConcuRx, a statistical framework for cross-study integration and gene prioritization across heterogeneous CRISPR drug-response screens. This approach produces more stable gene rankings than single-dataset analyses, improving prioritization of known MOA-associated genes and recovering biologically relevant genes that are overlooked by average- and overlap-based approaches. Applied to CRISPR drug-response screens for the synergistic drug pair of ATR and PARP inhibitors, ConcuRx strengthened support for 15 experimentally validated hypotheses collected from published studies, including mechanisms supported by independent studies not included in the ConcuRx analysis. These findings demonstrate that modelling between-study variability improves identification and prioritization of MOA-associated genes and provides a robust strategy for integrating heterogeneous functional genomics data in precision oncology.

bioinformatics↗

bioRxiv2026

Early developmental placental defects and pregnancy loss in lupus mice expressing human TLR8

Anti-phospholipid (APL) autoantibodies confer a high risk for adverse pregnancy outcomes, especially in Systemic Lupus Erythematosus (SLE). While human TLR8 (huTLR8) has been implicated in APL antibody-mediated placental injury in vitro, its in vivo role in pregnancy is unexplored. We report a novel mouse model of pregnancy loss in SLE-prone mice expressing huTLR8. Placental analysis revealed early developmental defects starting post-implantation, including a thin junctional zone, impaired vascularization, infarcts, and inflammation. Profound immune dysregulation was evident at E8.5 including increased myeloid cells and CD8 T cells and decreased uterine natural killer (uNK) cells. RNA sequencing revealed downregulated pregnancy-specific glycoproteins, reduced uNK cell-associated genes, and an upregulated myeloid cell signature. Bone marrow chimera studies demonstrated preferential activation of huTLR8-expressing placental Ly6C+ monocytes. Spatial transcriptomics at E9.5 confirmed uNK cell loss, decreased IL15 expression by both stromal and myeloid cells, and discrete inflammatory aggregates in the maternal layers containing myeloid cells and IFN{gamma}-expressing CD8 T cells. We propose that huTLR8, likely through myeloid cell activation and cytolytic T cell recruitment, drives placental injury in the context of SLE and APL autoantibodies. This model provides a valuable platform to dissect early pathogenic events in APL-associated pregnancy loss and identify new therapeutic targets.

immunology↗

bioRxiv2025

A Simultaneous Inhibition of ID1 and ID3 Protects Against Pulmonary Fibrosis

BackgroundIdiopathic pulmonary fibrosis (IPF) is a fatal lung disease for which novel therapeutic approaches are desperately needed. Inhibitor of DNA binding (ID) proteins are regulated by Transforming Growth Factor-{beta}. However, the regulation and the effects of ID proteins in IPF remain poorly understood. We aimed to assess the expression of ID proteins in IPF and determine the effects of ID proteins on human lung fibroblasts (HLF) in vitro and pulmonary fibrosis in vivo. MethodsThe expression of ID proteins in lungs and lung fibroblasts from mice and human patients with pulmonary fibrosis was evaluated. The effects of ID1/ID3 inhibition and overexpression on HLF were assessed. Genetic and pharmacological approaches were used in vivo to determine the role of ID1/ID3 in pulmonary fibrosis. ResultsID1/ID3 levels were elevated in HLFs isolated from pulmonary fibrosis-diseased patients and mice. ID1/ID3 knockdown decreased IPF-diseased HLF proliferation and differentiation into myofibroblasts. Bleomycin-exposed ID1/ID3 KO mice displayed improved lung function and presented with decreased lung fibrosis when compared to WT mice. A pharmacological inhibitor of ID1/ID3 decreased IPF-diseased HLF proliferation and differentiation in vitro and attenuated pulmonary fibrosis in vivo. A lung specific inhibition of ID1/ID3, using adeno-associated viruses expressing short hairpins targeting ID1 and ID3, reversed pulmonary fibrosis in mice. Mechanistically, ID1/ID3 inhibition decreased fibroblast proliferation through cell cycle genes and inhibited fibroblast differentiation through the MEK/ERK pathway. ConclusionsOur data indicate that a simultaneous inhibition of ID1 and ID3 attenuates pulmonary fibrosis. ID1/ID3 inhibition holds potential as a novel therapeutic treatment for IPF.

pathology↗

bioRxiv2023

Exploring the Therapeutic Potential of Cannabis Constituents in Parkinson's Disease: Insights from Molecular Docking Studies

Cannabis, often known as marihuana, marijuana, hashish, and hash, belongs to the genus Cannabis sativa L. This plant has excellent potential for the treatment of several brain disorders. Phytochemical compounds in this plant act as antioxidants, preserving synaptic plasticity and preventing neuronal degeneration. The neurodegenerative condition Parkinsons has emerged as one of the most significant health concerns of the twenty-first century. A detailed in silico molecular docking study was carried out to assess the neuroprotective effects of cannabis compounds against four potential targets of PD, including monoamine oxidase B (MAO-B), catechol-O-methyltransferase (COMT), alpha-synuclein (ASN), and Adenosine A2A receptor (A2A). Physicochemical properties, drug-likeness, toxicity, and ADMET profiles were also investigated. In this docking study, the cannabis compound cannabicyclol showed a superior docking score of -10.8 kcal/mol with the MAO-B protein. Based on these results, cannabicyclol and the target protein MAO-B were used to perform MD simulations to analyze their stability at 100 ns. Furthermore, it is crucial to carry out in vitro and in vivo investigations to enhance the potency of cannabis components and understand the processes underlying the suppression of Parkinsons disease-related enzymes. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=145 SRC="FIGDIR/small/566677v1_ufig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@15f455borg.highwire.dtl.DTLVardef@1c26038org.highwire.dtl.DTLVardef@3b32c6org.highwire.dtl.DTLVardef@82926b_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2023

In Silico Analysis of Drug Off-Target Effects on Diverse Isoforms of Cervical Cancer for Enhanced Therapeutic Strategies

Cervical cancer is a severe medical issue as 500,000 new cases of cervical cancer are identified in the world every year. The selection and analysis of the suitable gene target are the most crucial in the early phases of drug design. The emphasis at one protein while ignoring its several isoforms or splice variations may have unexpected therapeutic or harmful side effects. In this work, we provide a computational analysis of interactions between cervical cancer drugs and their targets that are influenced by alternative splicing. By using open-accessible databases, we targeted 45 FDA-approved cervical cancer drugs targeting various genes having more than two distinct protein-coding isoforms. Binding pocket interactions revealed that many drugs do not have possible targets at the isoform level. In terms of size, shape, electrostatic characteristics, and structural analysis have shown that various isoforms of the same gene with distinct ligand-binding pocket configurations. Our results emphasized the risks of ignoring possibly significant interactions at the isoform level by concentrating just on the canonical isoform and promoting consideration of the impacts of cervical cancer drugs on- and off-target at the isoform level to further research.

bioinformatics↗

bioRxiv2023

Whole Transcriptome and Functional Analyses Identify Novel Genes Involved in Meiosis and Fertility in Drosophila melanogaster

Reproductive success requires the development of viable oocytes and the accurate segregation of chromosomes during meiosis. Failure to segregate chromosomes properly can lead to infertility, miscarriages, or developmental disorders. A variety of factors contribute to accurate chromosome segregation and oocyte development, such as spindle assembly and sister chromatid cohesion. However, many proteins required for meiosis remain unknown. In this study, we aimed to identify and characterize novel meiotic and fertility genes using the genome of Drosophila melanogaster. To accomplish this goal, genes upregulated within meiotically active tissues were identified. About 200 genes with no known function were silenced using RNA interference (RNAi), and the effects on meiosis and fertility were assessed. We identified 65 genes that when silenced caused infertility and/or high levels of chromosomal nondisjunction. The vast majority of these genes have human and mouse homologs that are also poorly studied. Through this screening process, we identified novel genes that are crucial for meiosis and oocyte development but have not been extensively studied in human or model organisms. Understanding the function of these genes will be an important step towards the understanding of their biological significance during reproduction. Author SummaryIn this study, we aimed to identify and characterize novel meiotic and fertility genes within the genome of Drosophila melanogaster. We identified 65 genes that when silenced caused infertility and/or high levels of chromosomal nondisjunction. The vast majority of these genes have human and mouse homologs that are also poorly studied. Through this screening process, we identified novel genes that are crucial for meiosis and oocyte development, making them strong candidates for future studies to characterize their functions.

genetics↗

bioRxiv2021

Leakiness at the human-animal interface in Southeast Asia and implications for the spread of antibiotic resistance

International efforts to curb antimicrobial resistance have focused on drug development and limiting unnecessary use. However, in areas where water, sanitation, and hygiene infrastructure is lacking, and where biosecurity in food-animal production is poor, pathogen-flow between humans and animals could exacerbate the emergence and spread of resistant pathogens. Here, we compared mobile resistance elements among Escherichia coli recovered from humans and meat in Cambodia, a country with substantial connectivity between humans and animals, unregulated antibiotic use, and poor environmental controls. We identified multiple resistance-encoding plasmids and a novel, blaCTX-M and qnrS1-encoding transposon that were widely dispersed in both humans and animals, a phenomenon rarely observed in high-income settings. Our findings indicate that plugging leaks at human-animal interfaces should be a critical part of addressing antimicrobial resistance in low and middle-income countries.

ecology↗

bioRxiv2021

Integrating Sample Similarities into Latent Class Analysis: A Tree-Structured Shrinkage Approach

SO_SCPLOWUMMARYC_SCPLOWThis paper is concerned with using multivariate binary observations to estimate the probabilities of unobserved classes with scientific meanings. We focus on the setting where additional information about sample similarities is available and represented by a rooted weighted tree. Every leaf in the given tree contains multiple samples. Shorter distances over the tree between the leaves indicate a priori higher similarity in class probability vectors. We propose a novel data integrative extension to classical latent class models (LCMs) with tree-structured shrinkage. The proposed approach enables 1) borrowing of information across leaves, 2) estimating data-driven leaf groups with distinct vectors of class probabilities, and 3) individual-level probabilistic class assignment given the observed multivariate binary measurements. We derive and implement a scalable posterior inference algorithm in a variational Bayes framework. Extensive simulations show more accurate estimation of class probabilities than alternatives that suboptimally use the additional sample similarity information. A zoonotic infectious disease application is used to illustrate the proposed approach. The paper concludes by a brief discussion on model limitations and extensions.

genomics↗

bioRxiv2019

Bacteriophages can be used as infection control agents: A proof-of concept study involving anti-Acinetobacter baumannii phage

Hospital acquired infections are responsible for morbidity and mortality worldwide. Acinetobacter spp. infections are particularly notorious for complicating patient management in ICU settings. Extremely high mortality rates are associated with Acinetobacter infections because of their resistance to first- and second-line drugs. There is imminent need to develop infections control systems that are specific and environment friendly. Here, we report a proof-of-concept anti-Acinetobacter spp. bacteriophage-based infection control assay that is very target specific as well as innocuous to environment. extensively drug resistant (XDR) Acinetobacter baumannii strain was inoculated at various solid surfaces. A bacteriophage, enriched in the same strain, was applied on the inoculated surfaces. Phenol (carbolic acid) was used as a positive control. We show that bacteriophages can be used as infection control agents. In our assay, they killed XDR Acinetobacter baumannii present on solid surfaces. Our bacteriophage was extremely effective at reducing the CFU of inoculated strain to almost undetectable levels.

microbiology↗

bioRxiv2019

Extracellular CIRP as a Novel Endogenous TREM-1 Ligand to Fuel Inflammation

Extracellular cold-inducible RNA-binding protein (eCIRP) is a recently-discovered damage-associated molecular pattern. Understanding the precise mechanism by which it exacerbates inflammation in sepsis is essential. Here we identified that eCIRP is a new biologically active endogenous ligand of triggering receptor expressed on myeloid cells-1 (TREM-1), fueling inflammation in sepsis and ischemia-reperfusion. Surface plasmon resonance revealed a strong binding affinity between eCIRP and TREM-1, and FRET assay confirmed eCIRPs interaction with TREM-1 in macrophages. TREM-1 inhibition, either by its siRNA or a decoy peptide LP17, dramatically reduced eCIRP-induced inflammation. We developed a novel 7-aa peptide derived from human eCIRP, M3, which blocked the interaction of TREM-1 and eCIRP. M3 suppressed inflammation induced by eCIRP or agonist TREM-1 Ab crosslinking in murine macrophages or human peripheral blood monocytes. M3 also inhibited eCIRP-induced systemic inflammation and tissue injury. Treatment with M3 further protected mice from sepsis and intestinal ischemia-reperfusion, improved acute lung injury, and increased survival. Thus, we have discovered a novel TREM-1 ligand and developed a new peptide M3 to block eCIRP-TREM-1 interaction and improve the outcome of sepsis and sterile inflammation.

immunology↗

bioRxiv2018

Combinatorial recognition of clustered RNA elementsby a multidomain RNA-binding protein, IMP3

How multidomain RNA-binding proteins recognize their specific target sequences, based on a combinatorial code, represents a fundamental unsolved question and has not been studied systematically so far. Here we focus on a prototypical multidomain RNA-binding protein, IMP3 (also called IGF2BP3), which contains six RNA-binding domains (RBDs): four KH and two RRM domains. We have established an integrative systematic strategy, combining single-domain-resolved SELEX-seq, motif-spacing analyses, in vivo iCLIP, functional validation assays, and structural biology. This approach identifies the RNA-binding specificity and RNP topology of IMP3, involving all six RBDs and a cluster of up to five distinct and appropriately spaced CA-rich and GGC-core RNA elements, covering a >100 nucleotide-long target RNA region. Our generally applicable approach explains both specificity and flexibility of IMP3-RNA recognition, providing a paradigm for the function of multivalent interactions with multidomain RNA-binding proteins in gene regulation.

molecular biology↗