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Wauer, N.

Publications and source records attributed to Wauer, N..

3 recordsLinked to original sources

Condensate-Like Organization in Respiratory Aerosols Modulates the Dynamics of an Airborne Virus

The molecular behavior of viruses within respiratory aerosols plays a critical role in airborne disease transmission yet remains largely inaccessible to experimental characterization. Here, we use a billion-atom all-atom molecular dynamics simulation of a virus-laden respiratory aerosol to uncover how respiratory proteins, lipids, ions, and water collectively assemble around SARS-CoV-2, giving rise to structured microenvironments that influence viral stability and spike dynamics. We find that respiratory components rapidly evolve into heterogeneous networks characterized by protein-rich aggregates, patchy lipid assemblies, and spatially structured ion and water dynamics. These features create distinct microenvironments that constrain molecular transport and stabilize regions surrounding the virion. Within this crowded aerosol context, we observe sustained and selective interactions between aerosol components and the viral spike protein, including preferential recruitment of surfactant lipids and persistent coordination by divalent cations. These interactions modulate spike conformational dynamics, enhancing domain breathing motions and flexibility at key hinge regions while preserving a stable membrane anchor. Together, these observations reveal a condensate-like physical regime in which multivalent aerosol components coalesce into a soft, heterogeneous matrix that selectively modulates viral protein dynamics under extreme crowding. By framing virus-laden respiratory aerosols within this physical context, this work establishes an in situ molecular framework for understanding how aerosols influence viral persistence and offers a platform for exploring mechanisms relevant to airborne disease transmission and mitigation strategies. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=115 SRC="FIGDIR/small/721971v1_ufig1.gif" ALT="Figure 1"> View larger version (58K): org.highwire.dtl.DTLVardef@4d0f60org.highwire.dtl.DTLVardef@12c9d1forg.highwire.dtl.DTLVardef@1ff6c29org.highwire.dtl.DTLVardef@15feec_HPS_FORMAT_FIGEXP M_FIG C_FIG SynopsisRespiratory aerosols exhibit condensate-like physical properties that govern the evolution of the particle and modulate the behavior of airborne SARS-CoV-2.

biophysics↗

#COVIDisAirborne: AI-Enabled Multiscale Computational Microscopy of Delta SARS-CoV-2 in a Respiratory Aerosol

We seek to completely revise current models of airborne transmission of respiratory viruses by providing never-before-seen atomic-level views of the SARS-CoV-2 virus within a respiratory aerosol. Our work dramatically extends the capabilities of multiscale computational microscopy to address the significant gaps that exist in current experimental methods, which are limited in their ability to interrogate aerosols at the atomic/molecular level and thus ob-scure our understanding of airborne transmission. We demonstrate how our integrated data-driven platform provides a new way of exploring the composition, structure, and dynamics of aerosols and aerosolized viruses, while driving simulation method development along several important axes. We present a series of initial scientific discoveries for the SARS-CoV-2 Delta variant, noting that the full scientific impact of this work has yet to be realized. ACM Reference FormatAbigail Dommer1{dagger}, Lorenzo Casalino1{dagger}, Fiona Kearns1{dagger}, Mia Rosenfeld1, Nicholas Wauer1, Surl-Hee Ahn1, John Russo,2 Sofia Oliveira3, Clare Morris1, AnthonyBogetti4, AndaTrifan5,6, Alexander Brace5,7, TerraSztain1,8, Austin Clyde5,7, Heng Ma5, Chakra Chennubhotla4, Hyungro Lee9, Matteo Turilli9, Syma Khalid10, Teresa Tamayo-Mendoza11, Matthew Welborn11, Anders Christensen11, Daniel G. A. Smith11, Zhuoran Qiao12, Sai Krishna Sirumalla11, Michael OConnor11, Frederick Manby11, Anima Anandkumar12,13, David Hardy6, James Phillips6, Abraham Stern13, Josh Romero13, David Clark13, Mitchell Dorrell14, Tom Maiden14, Lei Huang15, John McCalpin15, Christo- pherWoods3, Alan Gray13, MattWilliams3, Bryan Barker16, HarindaRajapaksha16, Richard Pitts16, Tom Gibbs13, John Stone6, Daniel Zuckerman2*, Adrian Mulholland3*, Thomas MillerIII11,12*, ShantenuJha9*, Arvind Ramanathan5*, Lillian Chong4*, Rommie Amaro1*. 2021. #COVIDisAirborne: AI-Enabled Multiscale Computational Microscopy ofDeltaSARS-CoV-2 in a Respiratory Aerosol. In Supercomputing 21: International Conference for High Perfor-mance Computing, Networking, Storage, and Analysis. ACM, New York, NY, USA, 14 pages. https://doi.org/finalDOI

biophysics↗

Derlin rhomboid pseudoproteases employ substrate engagement and lipid distortion function for retrotranslocation of ER multi-spanning membrane substrates

Nearly one-third of proteins are initially targeted to the endoplasmic reticulum (ER) membrane where they are correctly folded, assembled, and then delivered to their final cellular destinations. In order to prevent the accumulation of misfolded membrane proteins, ER associated degradation (ERAD) moves these clients from the ER membrane to the cytosol; a process known as retrotranslocation. Our recent work in S. cerevisiae has revealed a derlin rhomboid pseudoprotease, Dfm1, is involved in the retrotranslocation of ubiquitinated ERAD membrane substrates. In this study, we sought to understand the mechanism associated with Dfm1s actions and found that Dfm1s conserved rhomboid residues are critical for membrane protein retrotranslocation. Specifically, we identified several retrotranslocation-deficient Loop 1 mutants that display impaired binding to membrane substrates. Furthermore, Dfm1 has retained the lipid thinning functions of its rhomboid protease predecessors to facilitate in the removal of ER membrane substrates. We find this substrate engagement and lipid thinning feature is conserved in its human homolog, Derlin-1. Utilizing interaction studies and molecular dynamics simulations, this work reveals that derlin rhomboid pseudoproteases employ novel mechanisms of substrate engagement and lipid thinning for catalyzing extraction of multi-spanning membrane substrates.

cell biology↗