Expanding the arsenal of bacterial spearguns.

Contractile injection systems are nanomachines used by bacteria to puncture target cell membranes, thereby mediating bacterial competition and infection of eukaryotic cells. Two studies shed light on the structural diversity of these molecular spearguns using advanced multiscale imaging techniques

Deep learning improves macromolecule identification in 3D cellular cryo-electron tomograms.

Cryogenic electron tomography (cryo-ET) visualizes the 3D spatial distribution of macromolecules at nanometer resolution inside native cells. However, automated identification of macromolecules inside cellular tomograms is challenged by noise and reconstruction artifacts, as well as the presence of many molecular species in the crowded volumes. Here, we present DeepFinder, a computational procedure that uses artificial neural networks to simultaneously localize multiple classes of macromolecules. Once trained, the inference stage of DeepFinder is faster than template matching and performs better than other competitive deep learning methods at identifying macromolecules of various sizes in both synthetic and experimental datasets. On cellular cryo-ET data, DeepFinder localized membrane-bound and cytosolic ribosomes (roughly 3.2 MDa), ribulose 1,5-bisphosphate carboxylase–oxygenase (roughly 560 kDa soluble complex) and photosystem II (roughly 550 kDa membrane complex) with an accuracy comparable to expert-supervised ground truth annotations. DeepFinder is therefore a promising algorithm for the semiautomated analysis of a wide range of molecular targets in cellular tomograms

Author Correction: Deep learning improves macromolecule identification in 3D cellular cryo-electron tomograms (Nature Methods, (2021), 18, 11, (1386-1394), 10.1038/s41592-021-01275-4).

In the version of this Article initially published, there was an error in Fig. 2b. The image labeled “Segmentation target” was a duplicate of Fig. 2a; the image has been replaced with the correct version. In the Fig. 4 caption for panels “b,c, Score maps…,” the text “(25 Å)” has been removed from the end of the sentence. For the final table in the online Methods, under “Evaluation,” the data are unchanged but have been reorganized for clarity. Finally, the two callouts to “Fig. 4” in Extended Data Fig. 5 caption should instead have referred to “Extended Data Fig. 4” and have now been corrected. The changes have been made to the online version of the article