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Ahmed, A. A.

Publications and source records attributed to Ahmed, A. A..

23 records · Page 2Linked to original sources

Enhanced virus detection and metagenomic sequencing in patients with meningitis and encephalitis

Meningitis and encephalitis are leading causes of central nervous system (CNS) disease and often result in severe neurological compromise or death. Traditional diagnostic workflows largely rely on pathogen-specific diagnostic tests, sometimes over days to weeks. Metagenomic next-generation sequencing (mNGS) is a high-throughput platform that profiles all nucleic acid in a sample. We prospectively enrolled 68 patients from New England with known or suspected CNS infection and performed mNGS from both RNA and DNA to identify potential pathogens. Using a computational metagenomic classification pipeline based on KrakenUniq and BLAST, we detected pathogen nucleic acid in cerebrospinal fluid (CSF) from 22 subjects. This included some pathogens traditionally diagnosed by serology or not typically identified in CSF, including three transmitted by Ixodes scapularis ticks (Powassan virus, Borrelia burgdorferi, Anaplasma phagocytophilum). Among 24 subjects with no clinical diagnosis, we detected enterovirus in two subjects and Epstein Barr virus in one subject. We also evaluated two methods to enhance detection of viral nucleic acid, hybrid capture and methylated DNA depletion. Hybrid capture nearly universally increased viral read recovery. Although results for methylated DNA depletion were mixed, it allowed detection of varicella zoster virus DNA in two samples that were negative by standard mNGS. Overall, mNGS is a promising approach that can test for multiple pathogens simultaneously, with similar efficacy to pathogen-specific tests, and can uncover geographically relevant infectious CNS disease, such as tick-borne infections in New England. With further laboratory and computational enhancements, mNGS may become a mainstay of workup for encephalitis and meningitis. ImportanceMeningitis and encephalitis are leading global causes of central nervous system (CNS) disability and mortality. Current diagnostic workflows remain inefficient, requiring costly pathogen-specific assays and sometimes invasive surgical procedures. Despite intensive diagnostic efforts, 40-60% of people with meningitis or encephalitis have no clear cause of their CNS disease identified. As diagnostic uncertainty often leads to costly inappropriate therapies, the need for novel pathogen detection methods is paramount. Metagenomic next-generation sequencing (mNGS) offers the unique opportunity to circumvent these challenges using unbiased laboratory and computational methods. Here, we performed comprehensive mNGS from 68 patients with suspected CNS infection, and define enhanced methods to improve the detection of CNS pathogens, including those not traditionally identified in the CNS by nucleic acid detection. Overall, our work helps elucidate how mNGS can become a mainstay in the diagnostic toolkit for CNS infections.

neuroscience↗

STK32A is a dual-specificity AGC kinase with a preference for acidic substrates

The STK32 kinases are a small subfamily of three uncharacterised serine/threonine kinases from the AGC kinase family whose functional role is so far unknown. Here, we analyse the consensus peptide sequence for STK32A phosphorylation, showing that STK32A is directed towards acidic substrate sequences and exhibits dual-specificity for serine/threonine and tyrosine residues. A crystal structure of STK32A reveals an overall structure typical of the AGC protein kinase family but with significant and unique features including an altered binding mode of the hydrophobic motif to the N-terminal lobe of the kinase domain, and a novel alpha-helix in between the turn motif and the hydrophobic motif. The crystal structure combined with phylogenetic analysis reveals the evolutionary conservation of the acidic substrate preference. In vitro binding assays demonstrated that the STK32 kinases bind significant numbers of clinically used kinase inhibitors.

biochemistry↗

Saccade vigor as an implicit measure of subjective economic value

Decisions are made based on the subjective value that the brain assigns to options. However, subjective value is a mathematical construct that cannot be measured directly, but rather inferred from choices. Recent results have demonstrated that reaction time and velocity of movements are modulated by reward, raising the possibility that there is a link between how the brain evaluates an option, and how it controls movements toward that option. Here, we asked people to choose among risky options represented by abstract stimuli, some associated with gain, others with loss. From their choices in decision trials we estimated the subjective value that they assigned to each stimulus. In probe trials, they were presented with a single stimulus at center and made a saccade to a peripheral location. We found that the reaction time and peak velocity of that saccade varied roughly linearly from loss to gain with the subjective value of the stimulus. Naturally, participants differed in how much they valued a given stimulus. Remarkably, those who valued a stimulus more, as evidenced by their choices in decision trials, tended to move with greater vigor in response to that stimulus in probe trials. Thus, saccade vigor partly reflected the subjective value that the brain assigned the stimulus. However, the influence of subjective value on vigor was only a modest predictor of preference: vigor in probe trials allowed us to predict choice in decision trials with roughly 60% accuracy. New and NoteworthyWe found that saccade vigor tends to vary monotonically with subjective value: smallest for stimuli that predict a loss, and highest for stimuli that predict a gain. Notably, between-subject differences in valuation could be gleaned from the between-subject differences in their patterns of vigor. However, the influence of subjective value on vigor was modest, allowing partial ability to infer subjective value for the purpose of predicting choice in decision trials.

neuroscience↗

The repertoire of serous ovarian cancer non-genetic heterogeneity revealed by single-cell sequencing of normal fallopian tube epithelial cells

The inter-differentiation between cell states promotes cancer cell survival under stress and fosters non-genetic heterogeneity (NGH). NGH is, therefore, a surrogate of tumor resilience but its quantification is confounded by genetic heterogeneity. Here we show that NGH can be accurately measured when informed by the molecular signatures of the normal cells of origin. We surveyed the transcriptomes of [~] 4000 normal fallopian tube epithelial (FTE) cells, the cells of origin of serous ovarian cancer (SOC), and identified six FTE subtypes. We used subtype signatures to deconvolute SOC expression data and found substantial intra-tumor NGH that was previously unrecognized. Importantly, NGH-based stratification of [~]1700 tumors robustly predicted survival. Our findings lay the foundation for accurate prognostic and therapeutic stratification of SOC.\n\nHighlightsO_LIThe projection of FTE subtypes refines the molecular classification of serous OC\nC_LIO_LIComprehensive single-cell profiling of FTE cells identifies 6 molecular subtypes\nC_LIO_LISubstantial non-genetic heterogeneity of HGSOC identified in 1700 tumors\nC_LIO_LIA mesenchymal-high HGSOC subtype is robustly correlated with poor prognosis\nC_LI

cancer biology↗

Genome And Epigenome Engineering CRISPR Toolkit For Probing In Vivo cis-Regulatory Interactions In The Chicken Embryo

CRISPR-Cas9 genome engineering has revolutionised all aspects of biological research, with epigenome engineering transforming gene regulation studies. Here, we present a highly efficient toolkit enabling genome and epigenome engineering in the chicken embryo, and demonstrate its utility by probing gene regulatory interactions mediated by neural crest enhancers. First, we optimise efficient guide-RNA expression from novel chick U6-mini-vectors, provide a strategy for rapid somatic gene knockout and establish protocol for evaluation of mutational penetrance by targeted next generation sequencing. We show that CRISPR/Cas9-mediated disruption of transcription factors causes a reduction in their cognate enhancer-driven reporter activity. Next, we assess endogenous enhancer function using both enhancer deletion and nuclease-deficient Cas9 (dCas9) effector fusions to modulate enhancer chromatin landscape, thus providing the first report of epigenome engineering in a developing embryo. Finally, we use the synergistic activation mediator (SAM) system to activate an endogenous target promoter. The novel genome and epigenome engineering toolkit developed here enables manipulation of endogenous gene expression and enhancer activity in chicken embryos, facilitating high-resolution analysis of gene regulatory interactions in vivo.\n\nSummary StatementWe present an optimised toolkit for efficient genome and epigenome engineering using CRISPR in chicken embryos, with a particular focus on probing gene regulatory interactions during neural crest development.\n\nList of AbbreviationsGenome Engineering (GE), Epigenome Engineering (EGE), single guide RNA (sgRNA), Neural Crest (NC), Transcription Factor (TF), Next Generation Sequencing (NGS), somite stage (ss), Hamburger Hamilton (HH).

developmental biology↗