The double-membrane nature of mitochondria generates an intermembrane volume through which ions, reactive oxygen species, and metabolites must flux to reach the matrix or cytosol, but whether this volume is a genetically specified structure remains unknown. We identify SPRIZ (spatial regulator of the intermembrane zone), the product of Ccdc127 , a gene conserved across deuterostome animals. SPRIZ assembles into an ∼18-nanometer homodimeric tether anchored in the outer mitochondrial membrane (OMM) and inserted into the inner mitochondrial membrane (IMM) through vertebrate-specific hydrophobic loops, physically spacing the two membranes and setting local intermembrane volume. Cryo-electron tomography of native mitochondria revealed rod-like densities spanning the intermembrane space (IMS), consistent with SPRIZ’s predicted rigid coiled-coil architecture and membrane-spanning topology. In mouse liver, two-dimensional morphometry measured ∼3-fold expansion of IMS area with SPRIZ and ∼5.5-fold with lengthened mitochondrial artificial increaser of the IMS (MARTINI); 3D electron tomography confirmed MARTINI’s greater OMM–IMM separation and normalized IMS volume. This expansion was functionally validated by increased 14 C-mannitol accessibility to the IMS and by impaired mitochondrial Ca 2+ uptake. Constitutive Ccdc127/SPRIZ knockout produced viable mice and, in liver mitochondria, preserved overall ultrastructure but caused modest IMS expansion, consistent with loss of local OMM–IMM constraints that stabilize membrane geometry at discrete sites. We therefore identify IMS volume as a genetically encoded and tunable architectural parameter of vertebrate mitochondria. In this model, SPRIZ is a molecular spacing system that locally sets OMM–IMM separation, shaping the environment through which metabolites, ions, and signals diffuse and establishing local gradients within the IMS.
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It is demonstrated that linker-free PROTACs can outperform traditional designs, marking a paradigm shift in PROTAC development for targeted protein degradation.
Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or seque...
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