1
|
Ji B, Xue Y, Xu Y, Liu S, Gough AH, Xie XQ, Wang J. Drug-Drug Interaction Between Oxycodone and Diazepam by a Combined in Silico Pharmacokinetic and Pharmacodynamic Modeling Approach. ACS Chem Neurosci 2021; 12:1777-1790. [PMID: 33950681 PMCID: PMC8374491 DOI: 10.1021/acschemneuro.0c00810] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Opioids and benzodiazepines have complex drug-drug interactions (DDIs), which serve as an important source of adverse drug effects. In this work, we predicted the DDI between oxycodone (OXY) and diazepam (DZP) in the human body by applying in silico pharmacokinetic (PK) and pharmacodynamic (PD) modeling and simulation. First, we studied the PK interaction between OXY and DZP with a physiologically based pharmacokinetic (PBPK) model. Second, we applied molecular modeling techniques including molecular docking, molecular dynamics (MD) simulation, and the molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA) free energy method to predict the PD-DDI between these two drugs. The PK interaction between OXY and DZP predicted by the PBPK model was not obvious. No significant interaction was observed between the two drugs at normal doses, though very high doses of DZP demonstrated a non-negligible inhibitory effect on OXY metabolism. On the contrary, the molecular modeling study shows that DZP has potential to compete with OXY at the same binding pocket of the active μ-opioid receptor (MOR) and κ-opioid receptor (KOR). MD simulation and MM-PBSA calculation results demonstrated that there is likely a synergetic effect between OXY and DZP binding to opioid receptors, as OXY is likely to target the active MOR while DZP selectively binds to the active KOR. Thus, pharmacokinetics contributes slightly to the DDI between OXY and DZP although an overdose of DZP has been brought to attention. Pharmacodynamics is likely to play a more important role than pharmacokinetics in revealing the mechanism of DDI between OXY and DZP.
Collapse
Affiliation(s)
- Beihong Ji
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, The University of Pittsburgh, 3501 Terrace St, Pittsburgh, PA 15261,NIH National Center of Excellence for Computational Drug Abuse Research, The University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA
| | - Ying Xue
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, The University of Pittsburgh, 3501 Terrace St, Pittsburgh, PA 15261,NIH National Center of Excellence for Computational Drug Abuse Research, The University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA.,Department of Pharmacy and Therapeutics, School of Pharmacy, The University of Pittsburgh, 3501 Terrace St, Pittsburgh, PA 15261
| | - Yuanyuan Xu
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, The University of Pittsburgh, 3501 Terrace St, Pittsburgh, PA 15261,NIH National Center of Excellence for Computational Drug Abuse Research, The University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA
| | - Shuhan Liu
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, The University of Pittsburgh, 3501 Terrace St, Pittsburgh, PA 15261,NIH National Center of Excellence for Computational Drug Abuse Research, The University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA
| | - Albert H Gough
- Computational and Systems Biology, The University of Pittsburgh, Drug Discovery Institute, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, Pennsylvania, 15260, USA
| | - Xiang Qun Xie
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, The University of Pittsburgh, 3501 Terrace St, Pittsburgh, PA 15261,NIH National Center of Excellence for Computational Drug Abuse Research, The University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA.,To whom correspondence should be addressed: Xiang-Qun Xie: Corresponding author, , School of Pharmacy, University of Pittsburgh; Junmei Wang: Corresponding author, , School of Pharmacy, University of Pittsburgh
| | - Junmei Wang
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, The University of Pittsburgh, 3501 Terrace St, Pittsburgh, PA 15261,NIH National Center of Excellence for Computational Drug Abuse Research, The University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA.,To whom correspondence should be addressed: Xiang-Qun Xie: Corresponding author, , School of Pharmacy, University of Pittsburgh; Junmei Wang: Corresponding author, , School of Pharmacy, University of Pittsburgh
| |
Collapse
|
2
|
Li X, George SM, Vernetti L, Gough AH, Taylor DL. A glass-based, continuously zonated and vascularized human liver acinus microphysiological system (vLAMPS) designed for experimental modeling of diseases and ADME/TOX. Lab Chip 2018; 18:2614-2631. [PMID: 30063238 PMCID: PMC6113686 DOI: 10.1039/c8lc00418h] [Citation(s) in RCA: 78] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
The vLAMPS is a human, biomimetic liver MPS, in which the ECM and cell seeding of the intermediate layer prior to assembly, simplifies construction of the model and makes the platform user-friendly. This primarily glass microfluidic device is optimal for real-time imaging, while minimizing the binding of hydrophobic drugs/biologics to the materials that constitute the device. The assembly of the three layered device with primary human hepatocytes and liver sinusoidal endothelial cells (LSECs), and human cell lines for stellate and Kupffer cells, creates a vascular channel separated from the hepatic channel (chamber) by a porous membrane that allows communication between channels, recapitulating the 3D structure of the liver acinus. The vascular channel can be used to deliver drugs, immune cells, as well as various circulating cells and other factors to a stand-alone liver MPS and/or to couple the liver MPS to other organ MPS. We have successfully created continuous oxygen zonation by controlling the flow rates of media in the distinct vascular and hepatic channels and validated the computational modeling of zonation with oxygen sensitive and insensitive beads. This allows the direct investigation of the role of zonation in physiology, toxicology and disease progression. The vascular channel is lined with human LSECs, recapitulating partial immunologic functions within the liver sinusoid, including the activation of LSECs, promoting the binding of polymorphonuclear leukocytes (PMNs) followed by transmigration into the hepatic chamber. The vLAMPS is a valuable platform to investigate the functions of the healthy and diseased human liver using all primary human cell types and/or iPSC-derived cells.
Collapse
Affiliation(s)
- Xiang Li
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15260, USA.
| | | | | | | | | |
Collapse
|
3
|
Lee-Montiel FT, George SM, Gough AH, Sharma AD, Wu J, DeBiasio R, Vernetti LA, Taylor DL. Control of oxygen tension recapitulates zone-specific functions in human liver microphysiology systems. Exp Biol Med (Maywood) 2017; 242:1617-1632. [PMID: 28409533 PMCID: PMC5661766 DOI: 10.1177/1535370217703978] [Citation(s) in RCA: 90] [Impact Index Per Article: 12.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2016] [Accepted: 03/07/2017] [Indexed: 12/20/2022] Open
Abstract
This article describes our next generation human Liver Acinus MicroPhysiology System (LAMPS). The key demonstration of this study was that Zone 1 and Zone 3 microenvironments can be established by controlling the oxygen tension in individual devices over the range of ca. 3 to 13%. The oxygen tension was computationally modeled using input on the microfluidic device dimensions, numbers of cells, oxygen consumption rates of hepatocytes, the diffusion coefficients of oxygen in different materials and the flow rate of media in the MicroPhysiology System (MPS). In addition, the oxygen tension was measured using a ratiometric imaging method with the oxygen sensitive dye, Tris(2,2'-bipyridyl) dichlororuthenium(II) hexahydrate (RTDP) and the oxygen insensitive dye, Alexa 488. The Zone 1 biased functions of oxidative phosphorylation, albumin and urea secretion and Zone 3 biased functions of glycolysis, α1AT secretion, Cyp2E1 expression and acetaminophen toxicity were demonstrated in the respective Zone 1 and Zone 3 MicroPhysiology System. Further improvements in the Liver Acinus MicroPhysiology System included improved performance of selected nonparenchymal cells, the inclusion of a porcine liver extracellular matrix to model the Space of Disse, as well as an improved media to support both hepatocytes and non-parenchymal cells. In its current form, the Liver Acinus MicroPhysiology System is most amenable to low to medium throughput, acute through chronic studies, including liver disease models, prioritizing compounds for preclinical studies, optimizing chemistry in structure activity relationship (SAR) projects, as well as in rising dose studies for initial dose ranging. Impact statement Oxygen zonation is a critical aspect of liver functions. A human microphysiology system is needed to investigate the impact of zonation on a wide range of liver functions that can be experimentally manipulated. Because oxygen zonation has such diverse physiological effects in the liver, we developed and present a method for computationally modeling and measuring oxygen that can easily be implemented in all MPS models. We have applied this method in a liver MPS in which we are then able to control oxygenation in separate devices and demonstrate that zonation-dependent hepatocyte functions in the MPS recapitulate what is known about in vivo liver physiology. We believe that this advance allows a deep experimental investigation on the role of zonation in liver metabolism and disease. In addition, modeling and measuring oxygen tension will be required as investigators migrate from PDMS to plastic and glass devices.
Collapse
Affiliation(s)
| | - Subin M George
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15260, USA
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260,USA
| | - Albert H Gough
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15260, USA
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260,USA
| | - Anup D Sharma
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15260, USA
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260,USA
| | - Juanfang Wu
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Richard DeBiasio
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Lawrence A Vernetti
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15260, USA
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260,USA
| | - D Lansing Taylor
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15260, USA
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260,USA
- Pittsburgh Cancer Institute, University of Pittsburgh, Pittsburgh, PA 15260, USA
| |
Collapse
|
4
|
Shun T, Gough AH, Sanker S, Hukriede NA, Vogt A. Exploiting Analysis of Heterogeneity to Increase the Information Content Extracted from Fluorescence Micrographs of Transgenic Zebrafish Embryos. Assay Drug Dev Technol 2017; 15:257-266. [PMID: 28800244 DOI: 10.1089/adt.2017.793] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Zebrafish embryos are a near-ideal animal model for drug discovery because of their high genetic and physiological similarity to mammals, small size, high fecundity, and optical transparency. The latter properties make zebrafish at larval stages especially suited for high-content analysis and high throughput screening (HTS). However, inherent biological complexity and the inability to screen multiple specimens in a single well present a challenge for HTS because limiting replicates and high variability often prevent assays from reaching the stringent performance criteria demanded of large-scale screening assays. In this report, we present methodology that overcomes these obstacles. We used our previously developed Tg(lhx1a:EGFP)pt303 line, which expresses a fluorescent transgene that enables live real-time measurements of kidney progenitor cell expansion. Since transgenes are expressed in specific cell populations, whose localization is precisely controlled, both spatially and temporally, we considered the developing embryo to be a "host" for a cell population, analogous to a well of a cell culture microplate, rather than a single specimen. By adopting this view, parameters routinely used to analyze cultured cells became applicable to characterize and quantify zebrafish transgene appearance beyond the overall intensity or area measurements, which are analogous to calculating well average data. Using the pixel-level distribution of transgene intensity as a proxy to cell-level data, we applied population-based intensity and heterogeneity measurements to quantitatively describe and characterize transgene expression in each embryo. Subsequent linear discriminant analysis on eight such parameters captured and condensed this information into a single assay parameter that maximizes the difference between positive and negative responses. The improvements in assay performance resulted in the Tg(lhx1a:EGFP)pt303 assay achieving HTS compatible assay performance in multi-day variability studies, documenting readiness for HTS of compounds that expand kidney progenitor cell populations.
Collapse
Affiliation(s)
- Tongying Shun
- 1 University of Pittsburgh Drug Discovery Institute , Pittsburgh, Pennsylvania
| | - Albert H Gough
- 1 University of Pittsburgh Drug Discovery Institute , Pittsburgh, Pennsylvania.,2 Department of Computational and Systems Biology, University of Pittsburgh Drug Discovery Institute , Pittsburgh, Pennsylvania
| | - Subramaniam Sanker
- 3 Department of Developmental Biology, University of Pittsburgh Drug Discovery Institute , Pittsburgh, Pennsylvania
| | - Neil A Hukriede
- 3 Department of Developmental Biology, University of Pittsburgh Drug Discovery Institute , Pittsburgh, Pennsylvania.,4 Center for Critical Care Nephrology, University of Pittsburgh , Pittsburgh, Pennsylvania
| | - Andreas Vogt
- 1 University of Pittsburgh Drug Discovery Institute , Pittsburgh, Pennsylvania.,2 Department of Computational and Systems Biology, University of Pittsburgh Drug Discovery Institute , Pittsburgh, Pennsylvania
| |
Collapse
|
5
|
Gough AH, Chen N, Shun TY, Lezon TR, Boltz RC, Reese CE, Wagner J, Vernetti LA, Grandis JR, Lee AV, Stern AM, Schurdak ME, Taylor DL. Identifying and quantifying heterogeneity in high content analysis: application of heterogeneity indices to drug discovery. PLoS One 2014; 9:e102678. [PMID: 25036749 PMCID: PMC4103836 DOI: 10.1371/journal.pone.0102678] [Citation(s) in RCA: 47] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2014] [Accepted: 06/22/2014] [Indexed: 12/04/2022] Open
Abstract
One of the greatest challenges in biomedical research, drug discovery and diagnostics is understanding how seemingly identical cells can respond differently to perturbagens including drugs for disease treatment. Although heterogeneity has become an accepted characteristic of a population of cells, in drug discovery it is not routinely evaluated or reported. The standard practice for cell-based, high content assays has been to assume a normal distribution and to report a well-to-well average value with a standard deviation. To address this important issue we sought to define a method that could be readily implemented to identify, quantify and characterize heterogeneity in cellular and small organism assays to guide decisions during drug discovery and experimental cell/tissue profiling. Our study revealed that heterogeneity can be effectively identified and quantified with three indices that indicate diversity, non-normality and percent outliers. The indices were evaluated using the induction and inhibition of STAT3 activation in five cell lines where the systems response including sample preparation and instrument performance were well characterized and controlled. These heterogeneity indices provide a standardized method that can easily be integrated into small and large scale screening or profiling projects to guide interpretation of the biology, as well as the development of therapeutics and diagnostics. Understanding the heterogeneity in the response to perturbagens will become a critical factor in designing strategies for the development of therapeutics including targeted polypharmacology.
Collapse
Affiliation(s)
- Albert H. Gough
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Department of Computational & Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- * E-mail:
| | - Ning Chen
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Tong Ying Shun
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Timothy R. Lezon
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Department of Computational & Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Robert C. Boltz
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Department of Computational & Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Celeste E. Reese
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Jacob Wagner
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Lawrence A. Vernetti
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Department of Computational & Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Jennifer R. Grandis
- University of Pittsburgh Cancer Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Department of Otolaryngology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Department of Pharmacology and Chemical Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Adrian V. Lee
- University of Pittsburgh Cancer Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Department of Pharmacology and Chemical Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Andrew M. Stern
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Department of Computational & Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Mark E. Schurdak
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Department of Computational & Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- University of Pittsburgh Cancer Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - D. Lansing Taylor
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- Department of Computational & Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- University of Pittsburgh Cancer Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| |
Collapse
|
6
|
Giuliano KA, Gough AH, Taylor DL, Vernetti LA, Johnston PA. Early safety assessment using cellular systems biology yields insights into mechanisms of action. ACTA ACUST UNITED AC 2010; 15:783-97. [PMID: 20639501 DOI: 10.1177/1087057110376413] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The integration of high-content screening (HCS) readers with organ-specific cell models, panels of functional biomarkers, and advanced informatics is a powerful approach to identifying the toxic liabilities of compounds early in the development process and forms the basis of "early safety assessment." This cellular systems biology (CSB) approach (CellCiphr profile) has been used to integrate rodent and human cellular hepatic models with panels of functional biomarkers measured at multiple time points to profile both the potency and specificity of the cellular toxicological response. These profiles also provide initial insights on the mechanism of the toxic response. The authors describe here mechanistic assay profiles designed to further dissect the toxic mechanisms of action and elucidate subtle effects apparent in subpopulations of cells. They measured 8 key mechanisms of toxicity with multiple biomarker feature measurements made simultaneously in populations of living primary hepatocytes and HepG2 cells. Mining the cell population response from these mechanistic profiles revealed the concentration dependence and nature of the heterogeneity of the response, as well as relationships between the functional responses. These more detailed mechanistic profiles define differences in compound activities that are not apparent in the average population response. Because cells and tissues encounter wide ranges of drug doses in space and time, these mechanistic profiles build on the CellCiphr profile and better reflect the complexity of the response in vivo.
Collapse
|
7
|
Abstract
High content screening (HCS) platforms integrate fluorescence microscopy with image analysis algorithms and informatics to automate cell analysis. The initial applications of HCS to secondary screening in drug discovery have spread throughout the discovery pipeline, and now into the expanding research field of systems cell biology, in which new manipulation tools enable the use of large scale screens to understand cellular pathways, and cell functions. In this chapter we discuss the requirements for HCS and the systems that have been designed to meet these application needs. The number of HCS systems available in the market place, and the range of features available, has grown considerably in the past 2 yr. Of the two general optical designs, the confocal systems have dominated the high-throughput HCS market, whereas the more cost effective wide-field systems have dominated all other market segments, and have a much larger market share. The majority of available systems have been optimized for fixed cell applications; however, there is growing interest in live cell kinetic assays, and four systems have successfully penetrated this application area. The breadth of applications for these systems continues to expand, especially with the integration of new technologies. New applications, improved software, better data visualization tools, and new detection methods such as multispectral imaging and fluorescence lifetime are predicted to drive the development of future HCS platforms.
Collapse
|
8
|
Taylor DL, Burton K, DeBiasio RL, Giuliano KA, Gough AH, Leonardo T, Pollock JA, Farkas DL. Automated light microscopy for the study of the brain: cellular and molecular dynamics, development, and tumorigenesis. Ann N Y Acad Sci 1997; 820:208-28. [PMID: 9237457 DOI: 10.1111/j.1749-6632.1997.tb46197.x] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Affiliation(s)
- D L Taylor
- Center for Light Microscope Imaging and Biotechnology, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| | | | | | | | | | | | | | | |
Collapse
|
9
|
Abstract
Calmodulin is a calcium transducer that activates key regulatory and structural proteins through calcium-induced binding to the target proteins. A fluorescent analog of calmodulin in conjunction with ratio imaging, relative to a volume indicator, has demonstrated that calmodulin is uniformly distributed in serum-deprived fibroblasts and there is no immediate change in the distribution upon stimulation with complete serum. The same fluorescent analog of calmodulin together with steady state fluorescence anisotropy imaging microscopy has been used to define the temporal and spatial changes in calmodulin binding to cellular targets during stimulation of serum-deprived fibroblasts and in polarized fibroblasts during wound healing. In serum-deprived fibroblasts, which exhibit a low free calcium ion concentration, a majority of the fluorescent analog of calmodulin remained unbound (fraction bound, fB < 10%). However, upon stimulation of the serum-deprived cells with complete serum, calmodulin binding (maximum fB approximately 95%) was directly correlated with the time course of the elevation and decline of the free calcium ion concentration, while the contraction of stress fibers continued for an hour or more. Calmodulin binding was also elevated in the leading lamellae of fibroblasts (maximum FB approximately 50%) during the lamellar contraction phase of wound healing and was spatially correlated with the contraction of transverse fibers containing myosin II. Highly polarized and motile fibroblasts exhibited the highest anisotropy (calmodulin binding) in the retracting tails and in association with contracting transverse fibers in the cortex of the cell. These results suggest that local activation of myosin II-based contractions involves the local binding of calmodulin to target proteins. The results also demonstrate a powerful yet simple mode of light microscopy that will be valuable for mapping molecular binding of suitably labeled macromolecules in living cells.
Collapse
Affiliation(s)
- A H Gough
- Center for Light Microscope Imaging and Biotechnology, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
| | | |
Collapse
|
10
|
Williams SP, Athey BD, Muglia LJ, Schappe RS, Gough AH, Langmore JP. Chromatin fibers are left-handed double helices with diameter and mass per unit length that depend on linker length. Biophys J 1986; 49:233-48. [PMID: 3955173 PMCID: PMC1329627 DOI: 10.1016/s0006-3495(86)83637-2] [Citation(s) in RCA: 195] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Four classes of models have been proposed for the internal structure of eukaryotic chromosome fibers--the solenoid, twisted-ribbon, crossed-linker, and superbead models. We have collected electron image and x-ray scattering data from nuclei, and isolated chromatin fibers of seven different tissues to distinguish between these models. The fiber diameters are related to the linker lengths by the equation: D(N) = 19.3 + 0.23 N, where D(N) is the external diameter (nm) and N is the linker length (base pairs). The number of nucleosomes per unit length of the fibers is also related to linker length. Detailed studies were done on the highly regular chromatin from erythrocytes of Necturus (mud puppy) and sperm of Thyone (sea cucumber). Necturus chromatin fibers (N = 48 bp) have diameters of 31 nm and have 7.5 +/- 1 nucleosomes per 10 nm along the axis. Thyone chromatin fibers (N = 87 bp) have diameters of 39 nm and have 12 +/- 2 nucleosomes per 10 nm along the axis. Fourier transforms of electron micrographs of Necturus fibers showed left-handed helical symmetry with a pitch of 25.8 +/- 0.8 nm and pitch angle of 32 +/- 3 degrees, consistent with a double helix. Comparable conclusions were drawn from the Thyone data. The data do not support the solenoid, twisted-ribbon, or supranucleosomal particle models. The data do support two crossed-linker models having left-handed double-helical symmetry and conserved nucleosome interactions.
Collapse
|