FIRRM and FIGNL1: partners in the regulation of homologous recombination

Predictomes, a classifier-curated database of AlphaFold-modeled protein-protein interactions

Protein-protein interactions (PPIs) are ubiquitous in biology, yet a comprehensive structural characterization of the PPIs underlying cellular processes is lacking. AlphaFold-Multimer (AF-M) has the potential to fill this knowledge gap, but standard AF-M confidence metrics do not reliably separate relevant PPIs from an abundance of false positive predictions. To address this limitation, we used machine learning on curated datasets to train a structure prediction and omics-informed classifier (SPOC) that effectively separates true and false AF-M predictions of PPIs, including in proteome-wide screens. We applied SPOC to an all-by-all matrix of nearly 300 human genome maintenance proteins, generating ∼40,000 predictions that can be viewed at predictomes.org, where users can also score their own predictions with SPOC. High-confidence PPIs discovered using our approach enable hypothesis generation in genome maintenance. Our results provide a framework for interpreting large-scale AF-M screens and help lay the foundation for a proteome-wide structural interactome.

Extensive homologous recombination safeguards oocyte genome integrity in mammals

Meiosis in mammalian oocytes is interrupted by a prolonged arrest at the germinal vesicle stage, during which oocytes have to repair DNA lesions to ensure genome integrity or otherwise undergo apoptosis. The FIRRM/FLIP-FIGNL1 complex dissociates RAD51 from the joint DNA molecules in both homologous recombination (HR) and DNA replication. However, as a type of non-meiotic, non-replicative cells, whether this RAD51-dismantling mechanism regulates genome integrity in oocytes remains elusive. Here, we show that FIRRM/FLIP is required for disassembly of RAD51-filaments and maintenance of genome integrity in oocytes. Deletion of FIRRM in oocytes leads to formation of massive nuclear RAD51 foci in oocytes of primordial follicles and activated follicles in mice. These RAD51 foci colocalize with the sites of DNA damage repair, as indicated by RPA2 and EdU, suggesting substantial DNA damage and extensive HR in oocytes. Especially in fully-grown FIRRM-deleted oocytes, RAD51 forms a net-like structure. As a consequence, FIRRM-deleted females are infertile due to aberrant homologous chromosome segregation at metaphase I and primordial follicle insufficiency at young adulthood. Hence, our study demonstrates the physiological importance of HR in maintaining genome integrity in oocytes.

FIGNL1-FIRRM is essential for meiotic recombination and prevents DNA damage-independent RAD51 and DMC1 loading

During meiosis, nucleoprotein filaments of the strand exchange proteins RAD51 and DMC1 are crucial for repairing SPO11-generated DNA double-strand breaks (DSBs) by homologous recombination (HR). A balanced activity of positive and negative RAD51/DMC1 regulators ensures proper recombination. Fidgetin-like 1 (FIGNL1) was previously shown to negatively regulate RAD51 in human cells. However, FIGNL1's role during meiotic recombination in mammals remains unknown. Here, we decipher the meiotic functions of FIGNL1 and FIGNL1 Interacting Regulator of Recombination and Mitosis (FIRRM) using male germline-specific conditional knock-out (cKO) mouse models. Both FIGNL1 and FIRRM are required for completing meiotic prophase in mouse spermatocytes. Despite efficient recruitment of DMC1 on ssDNA at meiotic DSB hotspots, the formation of late recombination intermediates is defective in Firrm cKO and Fignl1 cKO spermatocytes. Moreover, the FIGNL1-FIRRM complex limits RAD51 and DMC1 accumulation on intact chromatin, independently from the formation of SPO11-catalyzed DSBs. Purified human FIGNL1ΔN alters the RAD51/DMC1 nucleoprotein filament structure and inhibits strand invasion in vitro. Thus, this complex might regulate RAD51 and DMC1 association at sites of meiotic DSBs to promote proficient strand invasion and processing of recombination intermediates.

Predictomes: A classifier-curated database of AlphaFold-modeled protein-protein interactions

Protein-protein interactions (PPIs) are ubiquitous in biology, yet a comprehensive structural characterization of the PPIs underlying biochemical processes is lacking. Although AlphaFold-Multimer (AF-M) has the potential to fill this knowledge gap, standard AF-M confidence metrics do not reliably separate relevant PPIs from an abundance of false positive predictions. To address this limitation, we used machine learning on well curated datasets to train a Structure Prediction and Omics informed Classifier called SPOC that shows excellent performance in separating true and false PPIs, including in proteome-wide screens. We applied SPOC to an all-by-all matrix of nearly 300 human genome maintenance proteins, generating ~40,000 predictions that can be viewed at predictomes.org, where users can also score their own predictions with SPOC. High confidence PPIs discovered using our approach suggest novel hypotheses in genome maintenance. Our results provide a framework for interpreting large scale AF-M screens and help lay the foundation for a proteome-wide structural interactome.