Mitochondria: The Powerhouse of the Placenta | TS Digest

While the placenta only lasts about nine months, dysfunction of this temporary organ can have long-term consequences for the health of the mother and baby.¹ “If the fetus doesn’t get everything it needs, the baby’s born, but it just doesn’t have the resilience that it would otherwise have,” said Rohan Lewis, a placental physiologist at the University of Southampton. Despite this organ’s importance, the mechanisms that contribute to the proper function of its cells are not well understood.

To help close this knowledge gap, Lewis, along with placenta researcher Michelle Desforges at the University of Manchester, and bioinformatician Michele Darrow at the Rosalind Franklin Institute, launched a citizen science initiative to characterize the crucial internal machinery of placental cells.

In the present study, they will analyze cells in the outermost layer of the placenta, which mediates the exchange of maternal nutrients and fetal waste products by using samples donated by women with healthy pregnancies and women who experienced complications like preeclampsia.

“These cells are metabolically really active,” said Lewis. “And cells that are metabolically active need a lot of mitochondria.” The researchers want to determine how the numbers, sizes, and structures of the mitochondria might link to the abilities of the cells, and by extension, the placenta as a whole, to function properly.

By using scanning electron microscopy, the researchers constructed three-dimensional images of the placental cells and the mitochondria they contained. Now, said Lewis, “We’ve got this gap where the technology for imaging is leaps ahead, but our capacity to analyze that data is still way behind.”

The team turned to the collective power of citizen scientists to overcome this challenge. Participants in the Placenta Profiles project will identify and tag mitochondria in this enormous bank of microscopy images, enabling researchers to assess mitochondrial dynamics and train machine learning models to perform this identification task in the future.

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Reference

1. Lewis RM et al. Placenta. 2012;33 Suppl:S28-32.