Nanoparticles, such as viruses, can enter cells via endocytosis, a process by which the cell membrane wraps around them. The role of nanoparticle size and shape on endocytosis has been well studied, but the biophysical details of how extracellular proteins on the cell membrane surface mediate uptake are less clear. Motivated by recent discoveries regarding extracellular vimentin in viral and bacterial uptake and the structure of coronaviruses, we construct a computational model with a cell-like and virus-like construct containing filamentous protein structures protruding from their surfaces. We study the impact of these additional degrees of freedom on viral wrapping. The cell surface is modeled as a deformable sheet with bending rigidity, and extracellular vimentin as semiflexible polymers, or extracellular components (ECC), placed randomly on the sheet. The virus is modeled as a deformable shell that also has explicit, freely rotating spike filaments on its surface. Our results indicate that cells with optimally populated filaments are more susceptible to infection as they take up the virus more quickly and utilize a relatively smaller area of the cell surface. At optimal ECC density, the cell surface forms a fold around the virus, which is faster and more efficient at wrapping than localized crumples. Additionally, cell surface bending rigidity aids in the generation of folds by increasing force transmission across the surface. Changing other mechanical parameters, such as the stretching stiffness of filamentous ECC or virus spikes, can result in localized crumple formation on the cell surface. We conclude with the implications of our study on the evolutionary pressures of virus-like particles, with a particular focus on the cellular microenvironment. Published by the American Physical Society2025
more »
« less
Mechanical and Non‐Mechanical Functions of Filamentous and Non‐Filamentous Vimentin
Abstract Intermediate filaments (IFs) formed by vimentin are less understood than their cytoskeletal partners, microtubules and F‐actin, but the unique physical properties of IFs, especially their resistance to large deformations, initially suggest a mechanical function. Indeed, vimentin IFs help regulate cell mechanics and contractility, and in crowded 3D environments they protect the nucleus during cell migration. Recently, a multitude of studies, often using genetic or proteomic screenings show that vimentin has many non‐mechanical functions within and outside of cells. These include signaling roles in wound healing, lipogenesis, sterol processing, and various functions related to extracellular and cell surface vimentin. Extracellular vimentin is implicated in marking circulating tumor cells, promoting neural repair, and mediating the invasion of host cells by viruses, including SARS‐CoV, or bacteria such asListeriaandStreptococcus. These findings underscore the fundamental role of vimentin in not only cell mechanics but also a range of physiological functions. Also see the video abstract herehttps://youtu.be/YPfoddqvz-g.
more »
« less
- Award ID(s):
- 2032861
- PAR ID:
- 10380676
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- BioEssays
- Volume:
- 42
- Issue:
- 11
- ISSN:
- 0265-9247
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Nanoparticles, such as viruses, can enter cells via endocytosis. During endocytosis, the cell surface wraps around the nanoparticle to effectively eat it. Prior focus has been on how nanoparticle size and shape impacts endocytosis. However, inspired by the noted presence of extracellular vimentin affecting viral and bacteria uptake, as well as the structure of coronaviruses, we construct a computational model in whichboththe cell-like construct and the virus-like construct contain filamentous protein structures protruding from their surfaces. We then study the impact of these additional degrees of freedom on viral wrapping. We find that cells with an optimal density of filamentous extracellular components (ECCs) are more likely to be infected as they uptake the virus faster and use relatively less cell surface area per individual virus. At the optimal density, the cell surface folds around the virus, and folds are faster and more efficient at wrapping the virus than crumple-like wrapping. We also find that cell surface bending rigidity helps generate folds, as bending rigidity enhances force transmission across the surface. However, changing other mechanical parameters, such as the stretching stiffness of filamentous ECCs or virus spikes, can drive crumple-like formation of the cell surface. We conclude with the implications of our study on the evolutionary pressures of virus-like particles, with a particular focus on the cellular microenvironment that may include filamentous ECCs.more » « less
-
Abstract Numerous artificial intelligence-based weather prediction (AIWP) models have emerged over the past 2 years, mostly in the private sector. There is an urgent need to evaluate these models from a meteorological perspective, but access to the output of these models is limited. We detail two new resources to facilitate access to AIWP model output data in the hope of accelerating the investigation of AIWP models by the meteorological community. First, a 3-yr (and growing) reforecast archive beginning in October 2020 containing twice daily 10-day forecasts forFourCastNet v2-small,Pangu-Weather, andGraphCast Operationalis now available via an Amazon Simple Storage Service (S3) bucket through NOAA’s Open Data Dissemination (NODD) program (https://noaa-oar-mlwp-data.s3.amazonaws.com/index.html). This reforecast archive was initialized with both the NOAA’s Global Forecast System (GFS) and ECMWF’s Integrated Forecasting System (IFS) initial conditions in the hope that users can begin to perform the feature-based verification of impactful meteorological phenomena. Second, real-time output for these three models is visualized on our web page (https://aiweather.cira.colostate.edu) along with output from the GFS and the IFS. This allows users to easily compare output between each AIWP model and traditional, physics-based models with the goal of familiarizing users with the characteristics of AIWP models and determine whether the output aligns with expectations, is physically consistent and reasonable, and/or is trustworthy. We view these two efforts as a first step toward evaluating whether these new AIWP tools have a place in forecast operations.more » « less
-
Abstract Macromolecular protein complexes carry out most functions in the cell including essential functions required for cell survival. Unfortunately, we lack the subunit composition for all human protein complexes. To address this gap we integrated >25,000 mass spectrometry experiments using a machine learning approach to identify > 15,000 human protein complexes. We show our map of protein complexes is highly accurate and more comprehensive than previous maps, placing ∼75% of human proteins into their physical contexts. We globally characterize our complexes using protein co-variation data (ProteomeHD.2) and identify co-varying complexes suggesting common functional associations. Our map also generates testable functional hypotheses for 472 uncharacterized proteins which we support using AlphaFold modeling. Additionally, we use AlphaFold modeling to identify 511 mutually exclusive protein pairs in hu.MAP3.0 complexes suggesting complexes serve different functional roles depending on their subunit composition. We identify expression as the primary way cells and organisms relieve the conflict of mutually exclusive subunits. Finally, we import our complexes to EMBL-EBI’s Complex Portal (https://www.ebi.ac.uk/complexportal/home) as well as provide complexes through our hu.MAP3.0 web interface (https://humap3.proteincomplexes.org/). We expect our resource to be highly impactful to the broader research community.more » « less
-
Abstract Engineered DNA will slow the growth of a host cell if it redirects limiting resources or otherwise interferes with homeostasis. Escape mutants that alleviate this burden can rapidly evolve and take over cell populations, making genetic engineering less reliable and predictable. Synthetic biologists often use genetic parts encoded on plasmids, but their burden is rarely characterized. We measured how 301 BioBrick plasmids affectedEscherichia coligrowth and found that 59 (19.6%) were burdensome, primarily because they depleted the limited gene expression resources of host cells. Overall, no BioBricks reduced the growth rate ofE. coliby >45%, which agreed with a population genetic model that predicts such plasmids should be unclonable. We made this model available online for education (https://barricklab.org/burden-model) and added our burden measurements to the iGEM Registry. Our results establish a fundamental limit on what DNA constructs and genetic modifications can be successfully engineered into cells.more » « less
An official website of the United States government
