BACKGROUND: Sperm metabolic pathways that generate energy for motility are compartmentalized within the flagellum. Dysfunctions in metabolic compartments, namely mitochondrial respiration and glycolysis, can compromise motility and male fertility. Studying these compartments is thus required for fertility treatment. However, it is very challenging to capture images of metabolic compartments in motile spermatozoa because the fast beating of the flagellum introduces motion blur. Therefore, most approaches immobilize spermatozoa prior to imaging. RESULTS: Our findings indicate that immobilizing sperm alters their metabolic profile, highlighting the necessity for measuring metabolism in spermatozoa during movement. We achieved this by encapsulating mouse epididymis in a hydrogel followed by two-photon fluorescence lifetime imaging microscopy for imaging motile sperm in situ. The autofluorescence of endogenous metabolites-FAD, NADH, and NADPH-enabled us to visualize sperm metabolic compartments without staining. We trained machine learning for automated image segmentation and generated metabolic fingerprints using object-based phasor analysis. We show that metabolic fingerprints of spermatozoa and the mitochondrial compartment (1) can distinguish individual males by genetic background, age, or fecundity status, (2) correlate with fertility, and (3) change with age likely due to increased oxidative metabolism. CONCLUSIONS: Our approach eliminates the need for sperm immobilization and labeling and captures the native state of sperm metabolism. This technique could be adapted for metabolism-based sperm selection for assisted reproduction.

Department of Computer Science and Artificial Intelligence University of Basque Country UPV EHU San Sebastián Spain

Imaging Methods Core Facility at BIOCEV Faculty of Science Charles University Vestec Czech Republic

Laboratory of Germ Cell Development Division BIOCEV Institute of Molecular Genetics of the Czech Academy of Sciences Prague Czech Republic

Present address Department of Meiosis Max Planck Institute for Multidisciplinary Sciences Göttingen Germany

Present addresses Instituto Biofisika CSIC UPV EHU Leioa Spain

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