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Kozlowski, L.

Publications and source records attributed to Kozlowski, L..

2 recordsLinked to original sources

Queuine, a bacterial derived hypermodified nucleobase, shows protection in in vitro models of neurodegeneration

Growing evidence suggests that human gut bacteria, comprising the microbiome that communicates with the brain through the so-called gut-brain-axis, are linked to neurodegenerative disorders. Imbalances in the microbiome of Parkinsons disease (PD) and Alzheimers disease (AD) patients have been detected in several studies. Queuine is a hypermodified nucleobase enriched in the brain and exclusively produced by bacteria and salvaged by humans through their gut epithelium. Queuine replaces guanine at the wobble position of tRNAs with GUN anticodons and promotes efficient cytoplasmic and mitochondrial mRNA translation. To elucidate whether queuine could facilitate protein folding and prevent aggregation and mitochondrial defects, hallmarks of neurodegenerative disorders, we tested the effect of chemically synthesized queuine, STL-101, in several in vitro models of neurodegeneration. Treatment with STL-101 led to increased neuronal survival as well as a significant decrease in hyper-phosphorylated alpha-synuclein, a marker of alpha-synuclein aggregation in a PD model and a decrease in tau hyperphosphorylation in an AD model. Our work has identified a new role for queuine in neuroprotection uncovering a therapeutic potential for STL-101 in neurological disorders.

neuroscience↗

A high-throughput screen for transcription activation domains reveals their sequence characteristics and permits reliable prediction by deep learning

Transcription activation domains (ADs) are encoded by a wide range of seemingly unrelated amino acid sequences, making it difficult to recognize features that permit their dynamic behavior, fuzzy interactions and target specificity. We screened a large set of random 30-mer peptides for AD function and trained a deep neural network (ADpred) on the AD-positive and negative sequences. ADpred correctly identifies known ADs within protein sequences and accurately predicts the consequences of mutations. We show that functional ADs are (1) located within intrinsically disordered regions with biased amino acid composition, (2) contain clusters of hydrophobic residues near acidic side chains, (3) are enriched or depleted for particular dipeptide sequences, and (4) have higher helical propensity than surrounding regions. Taken together, our findings fit the model of "fuzzy" binding through hydrophobic protein-protein interfaces, where activator-coactivator binding takes place in a dynamic hydrophobic environment rather than through combinations of sequence-specific interactions.

molecular biology↗