Cell Cycle-Dependent Microtubule-Based Dynamic Transport of Cytoplasmic Dynein in Mammalian Cells

BACKGROUND:Cytoplasmic dynein complex is a large multi-subunit microtubule (MT)-associated molecular motor involved in various cellular functions including organelle positioning, vesicle transport and cell division. However, regulatory mechanism of the cell-cycle dependent distribution of dynein has not fully been understood. METHODOLOGY/PRINCIPAL FINDINGS:Here we report live-cell imaging of cytoplasmic dynein in HeLa cells, by expressing multifunctional green fluorescent protein (mfGFP)-tagged 74-kDa intermediate chain (IC74). IC74-mfGFP was successfully incorporated into functional dynein complex. In interphase, dynein moved bi-directionally along with MTs, which might carry cargos such as transport vesicles. A substantial fraction of dynein moved toward cell periphery together with EB1, a member of MT plus end-tracking proteins (+TIPs), suggesting +TIPs-mediated transport of dynein. In late-interphase and prophase, dynein was localized at the centrosomes and the radial MT array. In prometaphase and metaphase, dynein was localized at spindle MTs where it frequently moved from spindle poles toward chromosomes or cell cortex. +TIPs may be involved in the transport of spindle dyneins. Possible kinetochore and cortical dyneins were also observed. CONCLUSIONS AND SIGNIFICANCE:These findings suggest that cytoplasmic dynein is transported to the site of action in preparation for the following cellular events, primarily by the MT-based transport. The MT-based transport may have greater advantage than simple diffusion of soluble dynein in rapid and efficient transport of the limited concentration of the protein

Combination of searches for heavy spin-1 resonances using 139 fb−1 of proton-proton collision data at s = 13 TeV with the ATLAS detector

A combination of searches for new heavy spin-1 resonances decaying into different pairings of W, Z, or Higgs bosons, as well as directly into leptons or quarks, is presented. The data sample used corresponds to 139 fb−1 of proton-proton collisions at = 13 TeV collected during 2015–2018 with the ATLAS detector at the CERN Large Hadron Collider. Analyses selecting quark pairs (qq, bb, , and tb) or third-generation leptons (τν and ττ) are included in this kind of combination for the first time. A simplified model predicting a spin-1 heavy vector-boson triplet is used. Cross-section limits are set at the 95% confidence level and are compared with predictions for the benchmark model. These limits are also expressed in terms of constraints on couplings of the heavy vector-boson triplet to quarks, leptons, and the Higgs boson. The complementarity of the various analyses increases the sensitivity to new physics, and the resulting constraints are stronger than those from any individual analysis considered. The data exclude a heavy vector-boson triplet with mass below 5.8 TeV in a weakly coupled scenario, below 4.4 TeV in a strongly coupled scenario, and up to 1.5 TeV in the case of production via vector-boson fusion

Accuracy versus precision in boosted top tagging with the ATLAS detector

Abstract The identification of top quark decays where the top quark has a large momentum transverse to the beam axis, known as top tagging, is a crucial component in many measurements of Standard Model processes and searches for beyond the Standard Model physics at the Large Hadron Collider. Machine learning techniques have improved the performance of top tagging algorithms, but the size of the systematic uncertainties for all proposed algorithms has not been systematically studied. This paper presents the performance of several machine learning based top tagging algorithms on a dataset constructed from simulated proton-proton collision events measured with the ATLAS detector at √ s = 13 TeV. The systematic uncertainties associated with these algorithms are estimated through an approximate procedure that is not meant to be used in a physics analysis, but is appropriate for the level of precision required for this study. The most performant algorithms are found to have the largest uncertainties, motivating the development of methods to reduce these uncertainties without compromising performance. To enable such efforts in the wider scientific community, the datasets used in this paper are made publicly available.</jats:p

Dynein and Dynactin Leverage Their Bivalent Character to Form a High-Affinity Interaction

Amanda E. Siglin is with Thomas Jefferson University, Shangjin Sun is with University of Delaware, Jeffrey K. Moore is with Washington University in Saint Louis, Sarah Tan is with UT Austin, Martin Poenie is with UT Austin, James D. Lear is with University of Pennsylvania, Tatyana Polenova is with University of Delaware, John A. Cooper is with Washington University in Saint Louis, and John C. Williams is with Thomas Jefferson University and Beckman Research Institute at City of Hope.Cytoplasmic dynein and dynactin participate in retrograde transport of organelles, checkpoint signaling and cell division. The principal subunits that mediate this interaction are the dynein intermediate chain (IC) and the dynactin p150Glued; however, the interface and mechanism that regulates this interaction remains poorly defined. Herein, we use multiple methods to show the N-terminus of mammalian dynein IC, residues 10–44, is sufficient for binding p150Glued. Consistent with this mapping, monoclonal antibodies that antagonize the dynein-dynactin interaction also bind to this region of the IC. Furthermore, double and triple alanine point mutations spanning residues 6 to 19 in the yeast IC homolog, Pac11, produce significant defects in spindle positioning. Using the same methods we show residues 381 to 530 of p150Glued form a minimal fragment that binds to the dynein IC. Sedimentation equilibrium experiments indicate that these individual fragments are predominantly monomeric, but admixtures of the IC and p150Glued fragments produce a 2:2 complex. This tetrameric complex is sensitive to salt, temperature and pH, suggesting that the binding is dominated by electrostatic interactions. Finally, circular dichroism (CD) experiments indicate that the N-terminus of the IC is disordered and becomes ordered upon binding p150Glued. Taken together, the data indicate that the dynein-dynactin interaction proceeds through a disorder-to-order transition, leveraging its bivalent-bivalent character to form a high affinity, but readily reversible interaction.This work was supported in part by National Institutes of Health R21NS071166 (J.C.W.), R01GM085306 (J.C.W. & T.P.), NCRR SRR022316A (J.C.W.), GM 47337 (J.A.C.), NCRR 5P20RR017716-07 (T.P.), 5-T32-DK07705 (A.E.S) and The American Heart Association 0715196U (A.E.S). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Cellular and Molecular Biolog