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In the cell, DNA is arranged into highly-organised and topologically-constrained (supercoiled) structures. It remains unclear how this supercoiling affects the detailed double-helical structure of DNA, largely because of limitations in spatial resolution of the available biophysical tools. Here, we overcome these limitations, by a combination of atomic force microscopy (AFM) and atomistic molecular dynamics (MD) simulations, to resolve structures of negatively-supercoiled DNA minicircles at base-pair resolution. We observe that negative superhelical stress induces local variation in the canonical B-form DNA structure by introducing kinks and defects that affect global minicircle structure and flexibility. We probe how these local and global conformational changes affect DNA interactions through the binding of triplex-forming oligonucleotides to DNA minicircles. We show that the energetics of triplex formation is governed by a delicate balance between electrostatics and bonding interactions. Our results provide mechanistic insight into how DNA supercoiling can affect molecular recognition, that may have broader implications for DNA interactions with other molecular species. In cells, DNA is arranged into topologically-constrained (supercoiled) structures, but how this supercoiling affects the detailed double-helical structure of DNA remains unclear. Here authors use atomic force microscopy and atomistic molecular dynamics simulations, to resolve structures of negatively-supercoiled DNA minicircles at base-pair resolution.

The membrane attack complex (MAC) is a hetero-oligomeric protein assembly that kills pathogens by perforating their cell envelopes. The MAC is formed by sequential assembly of soluble complement proteins C5b, C6, C7, C8 and C9, but little is known about the rate-limiting steps in this process. Here, we use rapid atomic force microscopy (AFM) imaging to show that MAC proteins oligomerize within the membrane, unlike structurally homologous bacterial pore-forming toxins. C5b-7 interacts with the lipid bilayer prior to recruiting C8. We discover that incorporation of the first C9 is the kinetic bottleneck of MAC formation, after which rapid C9 oligomerization completes the pore. This defines the kinetic basis for MAC assembly and provides insight into how human cells are protected from bystander damage by the cell surface receptor CD59, which is offered a maximum temporal window to halt the assembly at the point of C9 insertion. The membrane attack complex (MAC) is a hetero-oligomeric protein assembly that kills pathogens by perforating their cell envelopes. Here, the authors use atomic force microscopy to show that MAC proteins oligomerize within the membrane, allowing them to identify the kinetic bottleneck of MAC formation.

DNA topology is essential for regulating cellular processes and maintaining genome stability, yet it is challenging to quantify due to the size and complexity of topologically constrained DNA molecules. By combining high-resolution Atomic Force Microscopy (AFM) with a new high-throughput automated pipeline, we can quantify the length, conformation, and topology of individual complex DNA molecules with sub-molecular resolution. Our pipeline uses deep-learning methods to trace the backbone of individual DNA molecules and identify crossing points, efficiently determining which segment passes over which. We use this pipeline to determine the structure of stalled replication intermediates from Xenopus egg extracts, including theta structures and late replication products, and the topology of plasmids, knots and catenanes from the E. coli Xer recombination system. We use coarse-grained simulations to quantify the effect of surface immobilisation on twist-writhe partitioning. Our pipeline opens avenues for understanding how fundamental biological processes are regulated by DNA topology. Here the authors develop a pipeline combining atomic force microscopy and deep learning to trace and quantify the structure of complex DNA molecules like replication intermediates and recombination products. Furthermore, they characterise surface deposition effects using simulations.

NDP52 is an autophagy receptor involved in the recognition and degradation of invading pathogens and damaged organelles. Although NDP52 was first identified in the nucleus and is expressed throughout the cell, to date, there is no clear nuclear functions for NDP52. Here, we use a multidisciplinary approach to characterise the biochemical properties and nuclear roles of NDP52. We find that NDP52 clusters with RNA Polymerase II (RNAPII) at transcription initiation sites and that its overexpression promotes the formation of additional transcriptional clusters. We also show that depletion of NDP52 impacts overall gene expression levels in two model mammalian cells, and that transcription inhibition affects the spatial organisation and molecular dynamics of NDP52 in the nucleus. This directly links NDP52 to a role in RNAPII-dependent transcription. Furthermore, we also show that NDP52 binds specifically and with high affinity to double-stranded DNA (dsDNA) and that this interaction leads to changes in DNA structure in vitro. This, together with our proteomics data indicating enrichment for interactions with nucleosome remodelling proteins and DNA structure regulators, suggests a possible function for NDP52 in chromatin regulation. Overall, here we uncover nuclear roles for NDP52 in gene expression and DNA structure regulation. An autophagy receptor, NDP52, is recruited to the nucleus where it can bind DNA. The authors show this promotes changes in chromatin accessibility which supports transcription initiation, providing a direct link between autophagy and transcription regulation.

The spread of antimicrobial resistance stimulates discovery strategies that place emphasis on mechanisms circumventing the drawbacks of traditional antibiotics and on agents that hit multiple targets. Host defense peptides (HDPs) are promising candidates in this regard. Here we demonstrate that a given HDP sequence intrinsically encodes for tuneable mechanisms of membrane disruption. Using an archetypal HDP (cecropin B) we show that subtle structural alterations convert antimicrobial mechanisms from native carpet-like scenarios to poration and non-porating membrane exfoliation. Such distinct mechanisms, studied using low- and high-resolution spectroscopy, nanoscale imaging and molecular dynamics simulations, all maintain strong antimicrobial effects, albeit with diminished activity against pathogens resistant to HDPs. The strategy offers an effective search paradigm for the sequence probing of discrete antimicrobial mechanisms within a single HDP.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Complement proteins eliminate Gram-negative bacteria in serum via the formation of membrane attack complex (MAC) pores in the outer membrane. However, it remains unclear how outer membrane poration leads to inner membrane permeation and cell lysis. Using atomic force microscopy (AFM) on living Escherichia coli (E. coli), we probed MAC-induced changes in the cell envelope and correlated these with subsequent cell death. Initially, bacteria survived despite the formation of hundreds of MACs randomly distributed over the cell surface. This was followed by larger-scale disruption of the outer membrane, including propagating defects and fractures, and by an overall swelling and stiffening of the bacterial surface, which precede inner membrane permeation. We conclude that bacterial cell lysis is only an indirect effect of MAC formation; outer membrane poration leads to mechanical destabilization of the cell envelope, reducing its ability to contain the turgor pressure, causing inner membrane permeation and cell death. This represents a previously unknown route to bacterial cell death that could be exploited by novel antibiotic treatments.Competing Interest StatementThe authors have declared no competing interest.

ABSTRACTThe topology of DNA plays a crucial role in the regulation of cellular processes and genome stability. Despite its significance, DNA topology remains challenging to determine due to the length and conformational complexity of individual topologically constrained DNA molecules. We demonstrate unparalleled resolution of complex DNA topologies using Atomic Force Microscopy (AFM) in aqueous conditions. We present a new high-throughput automated pipeline to determine DNA topology from raw AFM images, using deep-learning methods to trace the backbone of individual DNA molecules and identify crossing points. Our pipeline efficiently determines which segment passes over which, including the handling of challenging crossings, where the path of each molecule may be harder to resolve. We demonstrate the wider applicability of our tracing method by determining the structure of stalled replication intermediates from Xenopus egg extracts, including theta structures and late replication products. By developing new methodologies to accurately trace the DNA path through every crossing, we determine the topology of plasmids, knots and catenanes from the E. coli Xer recombination system. In doing so we uncover a recurrent depositional effect and reveal its origins using coarse-grained simulations. Our approach is broadly applicable to a range of nucleic acid structures, including those which interact with proteins, and opens avenues for understanding fundamental biological processes which are regulated by or affect DNA topology.Competing Interest StatementThe authors have declared no competing interest.Footnotes* Updated to include additional simulations and to improve manuscript* https://www.github.com/AFM-SPM/TopoStats

Abstract We present TopoStats, a Python toolkit for automated editing and analysis of Atomic Force Microscopy images. The program automates identification and tracing of individual molecules in circular and linear conformations without user input. TopoStats was able to identify and trace a range of molecules within AFM images, finding, on average, 90% of all individual molecules and molecular assemblies within a wide field of view, and without the need for prior processing. DNA minicircles of varying size, DNA origami rings and pore forming proteins were identified and accurately traced with contour lengths of traces typically within 10 nm of the predicted contour length. TopoStats was also able to reliably identify and trace linear and enclosed circular molecules within a mixed population. The program is freely available via GitHub (https://github.com/afm-spm/TopoStats) and is intended to be modified and adapted for use if required. Competing Interest Statement The authors have declared no competing interest. Footnotes * Updated following review * https://github.com/AFM-SPM/TopoStats

Abstract In the cell, DNA is arranged into highly-organised and topologically-constrained (supercoiled) structures. It remains unclear how this supercoiling affects the detailed double-helical structure of DNA, largely because of limitations in spatial resolution of the available biophysical tools. Here, we overcome these limitations, by a combination of atomic force microscopy (AFM) and atomistic molecular dynamics (MD) simulations, to resolve structures of negatively-supercoiled DNA minicircles at base-pair resolution. We observe that negative superhelical stress induces local variation in the canonical B-form DNA structure by introducing kinks and defects that affect global minicircle structure and flexibility. We probe how these local and global conformational changes affect DNA interactions through the binding of triplex-forming oligonucleotides to DNA minicircles. We show that the energetics of triplex formation is governed by a delicate balance between electrostatics and bonding interactions. Our results provide mechanistic insight into how DNA supercoiling can affect molecular recognition, that may have broader implications for DNA interactions with other molecular species. Competing Interest Statement The authors have declared no competing interest. Footnotes * Manuscript and supplemental files both updated to include new data in response to peer review comments. * https://github.com/AFM-SPM/TopoStats * https://github.com/agnesnoy/WrLINE