Back

Hyperaccumulation of Vanadium in animals: two sponges compete with urochordates

de Pao Mendonca, K.; Chaurand, P.; Campos, A.; Angeletti, B.; Rovezzi, M.; Delage, L.; Borchiellini, C.; Le Bivic, A.; issartel, j.; RENARD, E.; Levard, C.

2023-06-05 ecology
10.1101/2023.06.02.543482 bioRxiv
Show abstract

Vanadium (V) is the second most abundant transition metal in the oceans. Nevertheless, its concentration in organisms is generally low despite its involvement in various physiological or enzymatic functions. Because exposure to high concentrations was shown to be harmful for various organisms including animals, the unexpected very high concentrations found in urochordates and annelids yielded additional studies to decipher their biological meaning. Here we report cases of V hyperaccumulators in a distinct animal phylum (Porifera): the two homoscleromorph sponge species Oscarella lobularis and Oscarella tuberculata (up to 30 mg/g dw). These high concentrations overpass those reported previously in urochordates and annelids and are not found in the 5 other sponge species studied here. In both Oscarella species, vanadium is mainly accumulated in the 100 m surface tissues, and in particular in mesohylar cells, as vanadyl (+4) before being partly reduced to V (+3) in the deeper tissues. Genomic surveys failed to find any previously described gene implicated in vanadium metabolism, suggesting that V hyperaccumulation emerged convergently in this lineage. This feature may be of interest for developing bioremediation strategies in marine ecosystems or bioinspired processes to recycle this critical metal. SynopsisThis study reports extremely high concentrations of vanadium in two sponges. This unusual bioaccumulation of reduced V (+3) in mesohylar cells relies on unknown molecular mechanisms.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.