Search bioRxiv⌕ Search

bioRxiv · 10.1101/2025.01.21.634024

Molecular sorting of nitrogenase catalytic cofactors

Abstract

The free-living diazotroph Azotobacter vinelandii produces three genetically distinct but functionally and mechanistically similar nitrogenase isozymes, designated as Mo-dependent, V-dependent, and Fe-only. They respectively harbor nearly identical catalytic cofactors that are distinguished by a heterometal site occupied by Mo (FeMo-cofactor), V (FeV-cofactor), or Fe (FeFe-cofactor). Completion of FeMo-cofactor and FeV-cofactor formation occurs on molecular scaffolds prior to delivery to their catalytic partners. In contrast, completion of FeFe-cofactor assembly occurs directly within its cognate catalytic partner. Because hybrid nitrogenase species that contain the incorrect cofactor type cannot reduce N2 to support diazotrophic growth there must be a way to prevent misincorporation of an incorrect cofactor when different nitrogenase isozyme systems are produced at the same time. Here, we show that fidelity of the Fe-only nitrogenase is preserved by blocking the misincorporation of either FeMo-cofactor or FeV-cofactor during its maturation. This protection is accomplished by a two-domain protein, designated AnfO. It is shown that the N-terminal domain of AnfO binds to an immature form of the Fe-only nitrogenase and the C-terminal domain, tethered to the N-terminal domain by a flexible linker, has the capacity to capture FeMo- and FeV-cofactor. AnfO does not prevent the normal activation of Fe-only nitrogenase because completion of FeFe-cofactor assembly occurs within its catalytic partner and, therefore, is never available for capture by AnfO. These results support a post-translational mechanism involving the molecular sorting of structurally similar metallocofactors that involve both protein-protein interactions and metallocofactor binding while exploiting differential pathways for nitrogenase associated catalytic cofactor assembly.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Salinero-Lanzarote, A., Lian, J., Namkoong, G., Suess, D. L. M., Rubio, L. M., Dean, D. R., Perez-Gonzalez, A.. 2025-01-21. Molecular sorting of nitrogenase catalytic cofactors. https://doi.org/10.1101/2025.01.21.634024

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Deep reinforcement learning-driven discovery of a MsbA-targeted small-molecule antibiotic for the treatment of Acinetobacter baumannii infection

Antibiotics with new mechanisms are highly pursued to address the threat of infections caused by drug-resistant Gram-negative bacteria. Targeting MsbA, a key protein of the lipopolysaccharide biosynthesis pathway, represents a promising strategy to discover new classes of antibiotics. However, currently available MsbA-targeted molecules either lack sufficient potency or have unfavorable properties, necessitating expansion of chemical space. In this study, we chose the most promising cerastecin Cpd 4 as the template, and used two Artificial Intelligence (AI)-based tools, i.e. Link-INVENT and AutoMolDesigner for molecular design, performed chemical derivatization and antibacterial activity evaluation, which led to the discovery of Y-11 (MIC for A. baumannii: 0.5 g/mL). Encouragingly, Y-11 showed equivalent potency to Cpd4 for carbapenem-resistant A. baumannii, and less cytotoxicity and hemolysis as well as lower spontaneous resistance frequency. In vivo efficacy study demonstrated that Y-11 could effectively reduce bacterial loads in the mice infected by A. baumannii. The following mechanism study including molecular dynamics simulation, biochemical assay, and transmission electron microscope (TEM) analysis suggested that Y-11 inhibited the transport of lipooligosaccharide and impaired the formation of outer membrane, probably by competitively binding to the substrate binding site of MsbA and modulating ATPase activity. Taken together, we have discovered a MsbA-targeted small molecule Y-11 via AI-driven drug design, which provides a foundation for future antibiotic development.

biochemistry↗

Dynamic architecture of the Rixosome reveals mechanism of activation and ITS2 processing

Eukaryotic ribosome assembly requires the coordinated processing and extensive remodeling of pre-rRNAs. During late nuclear maturation of the 60S subunit, sequential removal of the internal transcribed spacer 2 (ITS2) is initiated by endonucleolytic cleavage at site C2 by the conserved Las1 nuclease. Las1 acts together with the kinase Grc3 and the Rix1 complex to form the Rixosome, which also functions in transcriptional regulation. However, the assembly of the Rixosome, its recruitment to pre-ribosomes, and its activation for ITS2 cleavage remain unclear. Here, we present cryo-EM structures of the human LAS1 complex, two structures of the isolated Rixosome and nine transition states of Rix1-bound pre-60S particles from Schizosaccharomyces pombe. These structures reveal a dynamic Rixosome architecture in which the heterotetrameric Las1 complex engages one or two copies of the Rix1 complex. Rix1 binding is highly flexible in the human Rixosome but rigid in the yeast complex. The isolated yeast Rixosome remains inactive, but binding to the pre-60S particle triggers a structural rearrangement that allows for substrate engagement and activation of the nuclease. Together, our results define the dynamic architecture of the Rixosome and provide a structural framework for ITS2 processing during nuclear maturation of the eukaryotic 60S ribosomal subunit.

biochemistry↗

SGFP-Grid Split GFP Graphene Grids

Affinity graphene grids provide a promising approach for selective protein capture in cryo-EM. Here, we introduce a split-GFP graphene grid platform(SGFP-G), in which graphene-conjugated GFP 1-10 selectively captures GFP11 tagged proteins from low concentration samples or cell lysates. This platform enables rapid assessment of target protein enrichment and particle distribution before vitrification via fluorescence imaging, while the grid design positions captured proteins away from the graphene surface and air-water interface. We also introduce a unique strategy to minimize nonspecific protein adsorption, thereby improving the selective enrichment of target proteins on this grid. Using GFP11-tagged apoferritin, we demonstrate fluorescence guided protein capture and obtain a 2.58 [A] cryoEM reconstruction, establishing SGFP-G as an affinity grid platform for high resolution structural studies with reduced sample requirements.

biochemistry↗