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Ahmad, A.

Publications and source records attributed to Ahmad, A..

2 recordsLinked to original sources

Genome-scale metabolic reconstruction and metabolic versatility of an obligate methanotroph Methylococcus capsulatus str. Bath

The increase in greenhouse gases with high global warming potential such as methane is a matter of concern and requires multifaceted efforts to reduce its emission and increase its mitigation from the environment. Microbes such as methanotrophs can assist in methane mitigation. To understand the metabolic capabilities of methanotrophs, a complete genome-scale metabolic model of an obligate methanotroph, Methylococcus capsulatus str. Bath was reconstructed. The model contains 535 genes, 898 reactions and 784 unique metabolites and is named iMC535. The predictive potential of the model was validated using previously-reported experimental data. The model predicted the Entner-Duodoroff (ED) pathway to be essential for the growth of this bacterium, whereas the Embden-Meyerhof-Parnas (EMP) pathway was found non-essential. The performance of the model was simulated on various carbon and nitrogen sources and found that M. capsulatus can grow on amino acids. The analysis of network topology of the model identified that six amino acids were in the top-ranked metabolic hubs. Using flux balance analysis (FBA), 29% of the metabolic genes were predicted to be essential, and 76 double knockout combinations involving 92 unique genes were predicted to be lethal. In conclusion, we have reconstructed a genome-scale metabolic model of a unique methanotroph Methylococcus capsulatus str. Bath. The model will serve as a knowledge-base for deeper understanding, as a platform for exploring the metabolic potential, and as a tool to engineer this bacterium for methane mitigation and industrial applications.

bioengineering

Nociceptor translational profiling reveals the RagA-mTORC1 network as a critical generator of neuropathic pain

Pain sensing neurons, nociceptors, are key drivers of neuropathic pain. We used translating ribosome affinity purification (TRAP) to comprehensively characterize up-and down-regulated mRNA translation in Scn10a-positive nociceptors in chemotherapy-induced neuropathic pain. We provide evidence that an underlying mechanism driving these changes in gene expression is a sustained mTORC1 activation driven by MNK1-eIF4E signaling. RagA, a GTPase controlling mTORC1 activity, is identified as a novel target of MNK1-eIF4E signaling, demonstrating a new link between these distinct signaling pathways. Neuropathic pain and RagA translation are strongly attenuated by genetic ablation of eIF4E phosphorylation, MNK1 elimination or treatment with the MNK inhibitor eFT508. We reveal a novel translational circuit for the genesis of neuropathic pain with important implications for next generation neuropathic pain therapeutics.\n\nOne Sentence SummaryCell-specific sequencing of translating mRNAs elucidates signaling pathology that can be targeted to reverse neuropathic pain

neuroscience