Micro-trace fossils reveal pervasive reworking of Pliocene sapropels by low-oxygen-adapted benthic meiofauna.

Animal burrowers leave an indelible signature on the sedimentary record in most marine environments, with the seeming exception of low-oxygen environments. In modern sedimentary settings, however, sub-millimetre-sized benthic animals (meiofauna) are adapted to low oxygen and even sulfidic conditions. Almost nothing is known about their impact on ancient marine sediments because they leave few recognizable traces. Here we show, in classic Pliocene-aged anoxic facies from the Mediterranean, the first reported trace fossil evidence of meiofaunal activity and its relation to changing oxygenation. A novel approach utilizing electron imaging of ion-polished samples shows that meiofauna pervasively reworked sediment under oxygen-depleted conditions that excluded macrofauna, fragmenting organic laminae and emplacing 15- to 70-µm-diameter faecal pellets without macroscopically influencing the fabric. The extent of reworking raises the question: how pervasively altered are other sediments presently assumed to lack animal influence and how far into the geological record does this influence extend?

Predicting protein function from structure: unique structural features of proteases.

We have noted consistent structural similarities among unrelated proteases. In comparison with other proteins of similar size, proteases have smaller than average surface areas, smaller radii of gyration, and higher C(alpha) densities. These findings imply that proteases are, as a group, more tightly packed than other proteins. There are also notable differences in secondary structure content between these two groups of proteins: proteases have fewer helices and more loops. We speculate that both high packing density and low alpha-helical content coevolved in proteases to avoid autolysis. By using the structural parameters that seem to show some separation between proteases and nonproteases, a neural network has been trained to predict protease function with over 86% accuracy. Moreover, it is possible to identify proteases whose folds were not represented during training. Similar structural analyses may be useful for identifying other classes of proteins and may be of great utility for categorizing the flood of structures soon to flow from structural genomics initiatives.