Notes

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Expected final online publication date for the Annual Review of Biophysics, Volume 49 is May 6, 2020. Please see http//www.annualreviews.org/page/journal/pubdates for revised estimates.The FtsZ protein is a highly conserved bacterial tubulin homolog. In vivo, the functional form of FtsZ is the polymeric, ring-like structure (Z-ring) assembled at the future division site during cell division. While it is clear that the Z-ring plays an essential role in orchestrating cytokinesis, precisely what its functions are and how these functions are achieved remain elusive. In this article, we review what we have learned during the past decade about the Z-ring's structure, function, and dynamics, with a particular focus on insights generated by recent high-resolution imaging and single-molecule analyses. We suggest that the major function of the Z-ring is to govern nascent cell pole morphogenesis by directing the spatiotemporal distribution of septal cell wall remodeling enzymes through the Z-ring's GTP hydrolysis-dependent treadmilling dynamics. In this role, FtsZ functions in cell division as the counterpart of the cell shape-determining actin homolog MreB in cell elongation. Expected final online publication date for the Annual Review of Biophysics, Volume 49 is May 6, 2020. Please see http//www.annualreviews.org/page/journal/pubdates for revised estimates.Machine learning (ML) is transforming all areas of science. The complex and time-consuming calculations in molecular simulations are particularly suitable for an ML revolution and have already been profoundly affected by the application of existing ML methods. Here we review recent ML methods for molecular simulation, with particular focus on (deep) neural networks for the prediction of quantum-mechanical energies and forces, on coarse-grained molecular dynamics, on the extraction of free energy surfaces and kinetics, and on generative network approaches to sample molecular equilibrium structures and compute thermodynamics. To explain these methods and illustrate open methodological problems, we review some important principles of molecular physics and describe how they can be incorporated into ML structures. Finally, we identify and describe a list of open challenges for the interface between ML and molecular simulation. Expected final online publication date for the Annual Review of Physical Chemistry, Volume 71 is April 20, 2020. Please see http//www.annualreviews.org/page/journal/pubdates for revised estimates.In seeking to understand mental health and disease, it is fundamental to identify the biological substrates that draw together the experiences and physiological processes that underlie observed psychological changes. Mitochondria are subcellular organelles best known for their central role in energetics, producing adenosine triphosphate to power most cellular processes. Converging lines of evidence indicate that mitochondria play a key role in the biological embedding of adversity. Preclinical research documents the effects of stress exposure on mitochondrial structure and function, and recent human research suggests alterations constituting recalibrations, both adaptive and nonadaptive. Current research suggests dynamic relationships among stress exposure, neuroendocrine signaling, inflammation, and mitochondrial function. These complex relationships are implicated in disease risk, and their elucidation may inform prevention and treatment of stress- and trauma-related disorders. We review and evaluate the evidence for mitochondrial dysfunction as a consequence of stress exposure and as a contributing factor to psychiatric disease. Expected final online publication date for the Annual Review of Clinical Psychology, Volume 16 is May 7, 2020. Please see http//www.annualreviews.org/page/journal/pubdates for revised estimates.Synthetic signaling is a branch of synthetic biology that aims to understand native genetic regulatory mechanisms and to use these insights to engineer interventions and devices that achieve specified design parameters. Applying synthetic signaling approaches to plants offers the promise of mitigating the worst effects of climate change and providing a means to engineer crops for entirely novel environments, such as those in space travel. The ability to engineer new traits using synthetic signaling methods will require standardized libraries of biological parts and methods to assemble them; the decoupling of complex processes into simpler subsystems; and mathematical models that can accelerate the design-build-test-learn cycle. The field of plant synthetic signaling is relatively new, but it is poised for rapid advancement. Translation from the laboratory to the field is likely to be slowed, however, by the lack of constructive dialogue between researchers and other stakeholders. Expected final online publication date for the Annual Review of Plant Biology, Volume 71 is April 29, 2020. Please see http//www.annualreviews.org/page/journal/pubdates for revised estimates.Nucleotide-binding leucine-rich repeat receptors (NLRs) monitor the plant intracellular environment for signs of pathogen infection. Several mechanisms of NLR-mediated immunity arose independently across multiple species. These include the functional specialization of NLRs into sensors and helpers, the independent emergence of direct and indirect recognition within NLR subfamilies, the regulation of NLRs by small RNAs, and the formation of NLR networks. Understanding the evolutionary history of NLRs can shed light on both the origin of pathogen recognition and the common constraints on the plant immune system. Attempts to engineer disease resistance have been sparse and rarely informed by evolutionary knowledge. In this review, we discuss the evolution of NLRs, give an overview of previous engineering attempts, and propose how to use evolutionary knowledge to advance future research in the generation of novel disease-recognition capabilities. BODIPY 581/591 C11 mw Expected final online publication date for the Annual Review of Plant Biology, Volume 71 is April 29, 2020. Please see http//www.annualreviews.org/page/journal/pubdates for revised estimates.
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