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Medvedeva, V. P.

Publications and source records attributed to Medvedeva, V. P..

2 recordsLinked to original sources

Inverse stable isotope labeling (InverSIL) links predicted catecholate siderophore gene clusters to their products in diverse bacteria

Bacteria produce high-affinity iron-chelating secondary metabolites called siderophores to access insoluble Fe(III) in their environments. Genome mining has revealed many predicted siderophore biosynthetic gene clusters (BGCs) in bacterial genomes, however the structures of their siderophore products remain mostly undetermined. This limits our molecular-level understanding of how bacteria acquire iron, as well as how they interact with other taxa that may use the same siderophores within bacterial communities. Here, we apply inverse stable isotope labeling (InverSIL) to rapidly connect predicted siderophore BGCs to their products. With InverSIL, bacteria are grown on 13C-substituted carbon sources and then fed predicted biosynthetic precursors at their natural isotopic abundance to identify BGC products by mass spectrometry, which removes issues with the availability of isotopically substituted precursors. We use InverSIL to determine the structures of the siderophore products of predicted BGCs from the methylotrophic genera Methylophilus and Methylobacterium, and the siderophores produced by the opportunistic pathogen Chromobacterium violaceum, which were previously shown to be essential for virulence yet remained structurally uncharacterized. We next use this approach to reveal the unexpected production of enterobactin by the genera Kushneria and Paracoccus, which was difficult to predict from genome sequences due to the distributed nature of the biosynthetic genes within the genomes. Finally, we use InverSIL to discover new siderophores, cellulochelin A and B, from the cellulose-degrading plant symbiont Cellulomonas sp. strain Leaf334. These findings demonstrate the utility of InverSIL for functional BGC characterization and expand our molecular understanding of bacterial iron acquisition strategies. IMPORTANCEIron acquisition is essential for microbial survival, and bacteria produce secondary metabolites called siderophores to scavenge iron from the environment. While bacterial genome sequences show many predicted genes for making siderophores, most remain unlinked to their metabolic products. Understanding which siderophores bacteria produce is critical for elucidating microbial iron acquisition strategies, ecological interactions, and potential roles in host-microbe interactions. Here, we demonstrate how inverse stable isotope labeling (InverSIL) can rapidly link predicted siderophore gene clusters to their corresponding metabolites. By applying InverSIL to diverse bacterial strains, we validate known siderophore products and uncover unexpected products, highlighting the limitations of current in silico predictions. This study highlights the value of combining experimental approaches with genome mining to advance our understanding of how bacteria interact with each other and their environment.

microbiology↗

Functional characterization of RELN missense mutations involved in recessive and dominant forms of Neuronal Migration Disorders

RELN is a large secreted glycoprotein that acts at multiple steps of cerebral cortex development, including neuronal migration. Only recessive mutations of the Reelin gene (RELN) have been associated with human cortical malformations and none has been functionally characterized. We identified novel missense RELN mutations in both compound and de novo heterozygous patients exhibiting an array of neuronal migration disorders (NMDs) as diverse as pachygyria, polymicrogyria and heterotopia. Most mutations caused defective RELN secretion in vitro and, when ectopically expressed in the embryonic mouse cortex, affected neuronal aggregation and/or migration in vivo. We determined the de novo heterozygous mutations acted as dominant negative and demonstrated that RELN mutations mediate not only recessive, but also dominant NMDs. This work assesses for the first time the pathogenicity of RELN mutations showing a strong genotype-phenotype correlation. In particular, the behavior of the mutant proteins in vitro and in vivo predicts the severity of cortical malformations and provides valuable insight into the pathogenesis of these disorders.

neuroscience↗