RESUMEN
The pathway for assembling heme ends with a unique set of enzymes in Gram-positive bacteria. Substrates for these reactions include coproporphyrin III, Fe(II), and H2O2, which are highly reactive and toxic. Because these bacteria lack membranous compartments, we hypothesized that metabolite flux may occur via a transient protein-protein interaction between the final two pathway enzymes, coproporphyrin ferrochelatase (CpfC) and coproheme decarboxylase (ChdC). This hypothesis was tested using enzymes from the pathogen Staphylococcus aureus and a corresponding ΔchdC knockout strain. The ultraviolet-visible spectral features of coproporphyrin III served as an in vitro indicator of a protein-protein interaction. A CpfC-ChdC KD of 17 ± 7 µM was determined, consistent with transient complexation and supported by the observation that the catalytic competence of both enzymes was moderately suppressed in the stable complex. The ΔchdC S. aureus was transformed with plasmids containing single-amino acid mutants in the active site gate of ChdC. The porphyrin content and growth phenotypes of these mutants showed that K129 and Y133 promote the ChdC-CpfC interaction and revealed the importance of E120. Understanding the nature of interactions between these enzymes and those further upstream in the heme biosynthesis pathway could provide new means of specifically targeting pathogenic Gram-positive bacteria such as S. aureus.
Asunto(s)
Hemo/biosíntesis , Staphylococcus aureus/metabolismo , Proteínas Bacterianas/genética , Proteínas Bacterianas/metabolismo , Coproporfirinas/metabolismo , Fenotipo , Mutación PuntualRESUMEN
Drosophila melanogaster is a powerful, long-standing model for metazoan development and gene regulation. We profiled chromatin accessibility in almost 1 million and gene expression in half a million nuclei from overlapping windows spanning the entirety of embryogenesis. Leveraging developmental asynchronicity within embryo collections, we applied deep neural networks to infer the age of each nucleus, resulting in continuous, multimodal views of molecular and cellular transitions in absolute time. We identify cell lineages; infer their developmental relationships; and link dynamic changes in enhancer usage, transcription factor (TF) expression, and the accessibility of TFs' cognate motifs. With these data, the dynamics of enhancer usage and gene expression can be explored within and across lineages at the scale of minutes, including for precise transitions like zygotic genome activation.