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Biology subjects

Akhtar, F.

Publications and source records attributed to Akhtar, F..

5 recordsLinked to original sources

Enabling subcellular DESI-MSI for broad adoption: Acquisition, analysis, and application

Subcellular mass spectrometry imaging (MSI) has required specialized instrumentation and approaches. Additionally, data analysis has required expensive proprietary software, or code-based open-source tools. These barriers render spatial metabolomics less accessible than peer spatial omics techniques (transcriptomics, proteomics). Here we demonstrate subcellular MSI on standard commercial hardware, analyzed using code-free, open-source software. An inexpensive, fully reversible modification of a stock DESI source takes the platform past its typical 5-10 m pixels to routine 2x2 m pixels, and 1x1 m in proof-of-principle experiments. At a tissue-glass boundary imaged at 2x2 m, tissue-specific ions showed no measurable spillover onto the adjacent glass within the {+/-}4.4 m uncertainty of the edge position. To make these data interpretable, we extend MSI.EAGLE, an open-source, vendor-agnostic application with two new methods: i) Spatial UMAP preserves tissue architecture alongside subcellular detail, where conventional clustering breaks apart at high resolution; ii) Histology Fit performs landmark-free co-registration, and recovers synthetic misalignments of up to 8 m to within one pixel of a reference registration. Together, these enable previously high-burden spatial metabolomics experiments. In mouse brain tissue, we demonstrate genuine subcellular signal by resolving mitochondrial cardiolipin into perinuclear puncta, quantifying cytoplasmic enrichment across 6,073 cells. Cell identities are assigned to MSI pixels using histology-predicted transcriptomics, linking cell provenance to metabolism in 2D space directly. Finally, we recover cell-type-specific metabolomes consistent with the transcriptomic identities. This workflow allows cellular and subcellular spatial metabolomics linked to cell provenance, with only stock MSI hardware, open-source GUI-based software, and common histology techniques, putting it within reach of many researchers and laboratories.

molecular biology↗

MSI.EAGLE: An Open-Source GUI for Streamlined Mass Spectrometry Imaging Analysis

Mass Spectrometry Imaging (MSI) is an emergent tool for analyzing spatial molecular distributions, yet data complexity often hinders effective analysis. MSI.EAGLE, an open-source R-Shiny application, makes analysis accessible for non-specialists by integrating advanced tools in a user-friendly interface. The workflow leverages tools from the Cardinal MSI package, with enhanced phenotyping, segmentation, statistical analysis and visualization. The application addresses a gap in spatial biology research by empowering a broader scientific community.

pathology↗

Integrated Respirometry and Metabolomics Unveil Circadian Metabolic Dynamics in Drosophila

Sleep and circadian rhythms shape organismal energy patterns, but how this timing connects to oxygen use and carbon dioxide production remains incompletely understood. We combined high-resolution respirometry with LC-MS-based metabolomics to characterize respiratory dynamics and metabolic states in Drosophila melanogaster, resolving genotype-specific impacts of sleep disruption and circadian regulation. Wild-type flies under light-dark cycles (WT-LD) showed rhythmic respiratory patterns reflective of anticipatory coordination of mitochondrial energy metabolism, amino acid turnover, and redox cycling. Short-sleep mutants (fmn, sss) exhibited elevated metabolic rates with reactive shifts of fuel preferences toward lipid and amino acid catabolism and altered mitochondrial respiration. The clock-mutant (per01) and flies under constant darkness (WT-DD) showed reactive and widespread metabolic dysregulation and impaired redox homeostasis. These findings demonstrate that both sleep and circadian systems contribute to aligning metabolic substrate selection with energy demands, offering mechanistic insights into how disruptions in behavioral states compromise metabolic health.

biochemistry↗

Functional characterization of the disease-associated CCL2 rs1024611G-rs13900T haplotype: The role of the RNA-binding protein HuR

CC-chemokine ligand 2 (CCL2) is involved in the pathogenesis of several diseases associated with monocyte/macrophage recruitment, such as HIV-associated neurocognitive disorder (HAND), tuberculosis, and atherosclerosis. The rs1024611 (alleles: A>G; G is the risk allele) polymorphism in the CCL2 cis-regulatory region is associated with increased CCL2 expression in vitro and ex vivo, leukocyte mobilization in vivo, and deleterious disease outcomes. However, the molecular basis for the rs1024611-associated differential CCL2 expression remains poorly characterized. It is conceivable that genetic variant(s) in linkage disequilibrium (LD) with rs1024611 could mediate such effects. Previously, we used rs13900 (alleles: C>T) in the CCL2 3 untranslated region (3 UTR) that is in perfect LD with rs1024611 to demonstrate allelic expression imbalance (AEI) of CCL2 in heterozygous individuals. Here we tested the hypothesis that the rs13900 could modulate CCL2 expression by altering mRNA turnover and/or translatability. The rs13900 T allele conferred greater stability to the CCL2 transcript when compared to the rs13900 C allele. The rs13900 T allele also had increased binding to Human Antigen R (HuR), an RNA-binding protein, in vitro and ex vivo. The rs13900 alleles imparted differential activity to reporter vectors and influenced the translatability of the reporter transcript. We further demonstrated the role of HuR in mediating allele-specific effects on CCL2 expression in overexpression and silencing studies. Our studies suggest that the differential interactions of HuR with rs13900 could modulate CCL2 expression and could in part explain the interindividual differences in CCL2-mediated disease susceptibility.

genomics↗

The Association between Alcohol Consumption and Telomere Length: A Meta-Analysis Focusing on Observational Studies

BackgroundBoth telomere length and alcohol consumption play important roles in carcinogenesis and biological age. Many efforts have been made to investigate the association between alcohol consumption and telomere length. However, no consensus has been reached yet.\n\nMethodsIn this article, we performed a meta-analysis to integrate the investigation results in the literature about the association between alcohol consumption and telomere length. After searching articles published between 2000 and 2016, 21 articles (including 27 analyses, total sample size 35,891) met our eligibility criteria.\n\nResultsWe found a significant association between alcohol consumption and telomere length (Fishers combined p-value = 3.52E-8 and Liptaks weighted p-value = 8.24E-3). We also found that the significance of the association between alcohol consumption and telomere length varies with study type (cohort, case-control, or cross-sectional) and study population (Europe, Asia, American, or Australia).\n\nConclusionsCombined evidence showed that alcohol consumption is associated with telomere length. The consistent quantifications of alcohol consumption and telomere length would benefit the future aggregation of the evidence from different studies.

cancer biology↗