scholarly journals A multi-scale model of the yeast chromosome-segregation system

2018 ◽  
Author(s):  
Cai Tong Ng ◽  
Li Deng ◽  
Chen Chen ◽  
Hong Hwa Lim ◽  
Jian Shi ◽  
...  
Keyword(s):  
Chromosome Segregation ◽  
Scale Model ◽  
Microtubule Depolymerization ◽  
Multi Scale ◽  
Yeast Chromosome ◽  
Dividing Cells ◽  
Electron Cryotomography ◽  
Binding Position

ABSTRACTIn dividing cells, depolymerizing spindle microtubules move chromosomes by pulling at their kinetochores. While kinetochore subcomplexes have been studied extensively in vitro, little is known about their in vivo structure and interactions with microtubules or their response to spindle damage. Here we combine electron cryotomography of serial cryosections with genetic and pharmacological perturbation to study the yeast chromosome-segregation machinery at molecular resolution in vivo. Each kinetochore microtubule has one (rarely, two) Dam1C/DASH outer-kinetochore assemblies.Dam1C/DASH only contacts the flat surface of the microtubule and does so with its flexible “bridges”. In metaphase, 40% of the Dam1C/DASH assemblies are complete rings; the rest are partial rings. Ring completeness and binding position along the microtubule are sensitive to kinetochore attachment and tension, respectively. Our study supports a model in which each kinetochore must undergo cycles of conformational change to couple microtubule depolymerization to chromosome movement.

scholarly journals Electron cryotomography analysis of Dam1C/DASH at the kinetochore–spindle interface in situ

2018 ◽  
Vol 218 (2) ◽  
pp. 455-473 ◽  
Author(s):  
Cai Tong Ng ◽  
Li Deng ◽  
Chen Chen ◽  
Hong Hwa Lim ◽  
Jian Shi ◽  
...  
Keyword(s):  
Chromosome Segregation ◽  
Microtubule Depolymerization ◽  
Yeast Chromosome ◽  
Dividing Cells ◽  
Spindle Microtubules ◽  
Electron Cryotomography ◽  
Binding Position

In dividing cells, depolymerizing spindle microtubules move chromosomes by pulling at their kinetochores. While kinetochore subcomplexes have been studied extensively in vitro, little is known about their in vivo structure and interactions with microtubules or their response to spindle damage. Here we combine electron cryotomography of serial cryosections with genetic and pharmacological perturbation to study the yeast chromosome segregation machinery in vivo. Each kinetochore microtubule has one (rarely, two) Dam1C/DASH outer kinetochore assemblies. Dam1C/DASH contacts the microtubule walls and does so with its flexible “bridges”; there are no contacts with the protofilaments’ curved tips. In metaphase, ∼40% of the Dam1C/DASH assemblies are complete rings; the rest are partial rings. Ring completeness and binding position along the microtubule are sensitive to kinetochore attachment and tension, respectively. Our study and those of others support a model in which each kinetochore must undergo cycles of conformational change to couple microtubule depolymerization to chromosome movement.

scholarly journals A multi-scale pipeline linking drug transcriptomics with pharmacokinetics predicts in vivo interactions of tuberculosis drugs

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Joseph M. Cicchese ◽  
Awanti Sambarey ◽  
Denise Kirschner ◽  
Jennifer J. Linderman ◽  
Sriram Chandrasekaran
Keyword(s):  
Drug Interactions ◽  
Scale Model ◽  
Relative Distribution ◽  
Combination Therapies ◽  
Multi Scale ◽  
Machine Learning Model ◽  
Drug Regimens ◽  
New Treatments

AbstractTuberculosis (TB) is the deadliest infectious disease worldwide. The design of new treatments for TB is hindered by the large number of candidate drugs, drug combinations, dosing choices, and complex pharmaco-kinetics/dynamics (PK/PD). Here we study the interplay of these factors in designing combination therapies by linking a machine-learning model, INDIGO-MTB, which predicts in vitro drug interactions using drug transcriptomics, with a multi-scale model of drug PK/PD and pathogen-immune interactions called GranSim. We calculate an in vivo drug interaction score (iDIS) from dynamics of drug diffusion, spatial distribution, and activity within lesions against various pathogen sub-populations. The iDIS of drug regimens evaluated against non-replicating bacteria significantly correlates with efficacy metrics from clinical trials. Our approach identifies mechanisms that can amplify synergistic or mitigate antagonistic drug interactions in vivo by modulating the relative distribution of drugs. Our mechanistic framework enables efficient evaluation of in vivo drug interactions and optimization of combination therapies.

scholarly journals A multi-scale pipeline linking drug transcriptomics with pharmacokinetics predicts in vivo interactions of tuberculosis drugs

2020 ◽  
Author(s):  
Joseph Cicchese ◽  
Awanti Sambarey ◽  
Denise Kirschner ◽  
Jennifer Linderman ◽  
Sriram Chandrasekaran
Keyword(s):  
Drug Interactions ◽  
Scale Model ◽  
Relative Distribution ◽  
Combination Therapies ◽  
Multi Scale ◽  
Machine Learning Model ◽  
Drug Regimens ◽  
New Treatments

AbstractTuberculosis (TB) is the deadliest infectious disease worldwide. The design of new treatments for TB is hindered by the large number of candidate drugs, drug combinations, dosing choices, and complex pharmaco-kinetics/dynamics (PK/PD). Here we study the interplay of these factors in designing combination therapies by linking a machine-learning model, INDIGO-MTB, which predicts in vitro drug interactions using drug transcriptomics, with a multi-scale model of drug PK/PD and pathogen-immune interactions called GranSim. We calculate an in vivo drug interaction score (iDIS) from dynamics of drug diffusion, spatial distribution, and activity within lesions against various pathogen sub-populations. The iDIS of drug regimens evaluated against non-replicating bacteria significantly correlates with efficacy metrics from clinical trials. Our approach identifies mechanisms that can amplify synergistic or mitigate antagonistic drug interactions in vivo by modulating the relative distribution of drugs. Our mechanistic framework enables efficient evaluation of in vivo drug interactions and optimization of combination therapies.

scholarly journals Lentiviral Vectors for Delivery of Gene-Editing Systems Based on CRISPR/Cas: Current State and Perspectives

Viruses ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1288
Author(s):  
Wendy Dong ◽  
Boris Kantor
Keyword(s):  
Large Scale ◽  
Lentiviral Vector ◽  
Clinical Applications ◽  
Scale Production ◽  
Base Editing ◽  
Epigenome Editing ◽  
Vector Systems ◽  
Dividing Cells

CRISPR/Cas technology has revolutionized the fields of the genome- and epigenome-editing by supplying unparalleled control over genomic sequences and expression. Lentiviral vector (LV) systems are one of the main delivery vehicles for the CRISPR/Cas systems due to (i) its ability to carry bulky and complex transgenes and (ii) sustain robust and long-term expression in a broad range of dividing and non-dividing cells in vitro and in vivo. It is thus reasonable that substantial effort has been allocated towards the development of the improved and optimized LV systems for effective and accurate gene-to-cell transfer of CRISPR/Cas tools. The main effort on that end has been put towards the improvement and optimization of the vector’s expression, development of integrase-deficient lentiviral vector (IDLV), aiming to minimize the risk of oncogenicity, toxicity, and pathogenicity, and enhancing manufacturing protocols for clinical applications required large-scale production. In this review, we will devote attention to (i) the basic biology of lentiviruses, and (ii) recent advances in the development of safer and more efficient CRISPR/Cas vector systems towards their use in preclinical and clinical applications. In addition, we will discuss in detail the recent progress in the repurposing of CRISPR/Cas systems related to base-editing and prime-editing applications.

scholarly journals Overexpressed Pituitary Tumor-Transforming Gene Causes Aneuploidy in Live Human Cells

Endocrinology ◽  
2003 ◽  
Vol 144 (11) ◽  
pp. 4991-4998 ◽  
Author(s):  
Run Yu ◽  
Wenge Lu ◽  
Jiandong Chen ◽  
Chris J. McCabe ◽  
Shlomo Melmed
Keyword(s):  
Cancer Cells ◽  
Chromosome Segregation ◽  
Pituitary Tumor ◽  
Fluorescent Protein ◽  
Human Cancer ◽  
Live Cells ◽  
Pituitary Tumor Transforming Gene ◽  
Transforming Gene

Abstract The mammalian securin, pituitary tumor-transforming gene (PTTG), is overexpressed in several tumors and transforms cells in vitro and in vivo. To test the hypothesis that PTTG overexpression causes aneuploidy, enhanced green fluorescent protein (EGFP)-tagged PTTG (PTTG-EGFP) was expressed in human H1299 cancer cells (with undetectable endogenous PTTG expression) and mitosis of individual live cells observed. Untransfected cells and cells expressing EGFP alone exhibited appropriate mitosis. PTTG-EGFP markedly prolonged prophase and metaphase, indicating that PTTG blocks progression of mitosis to anaphase. In cells that underwent apparently normal mitosis (35 of 65 cells), PTTG-EGFP was degraded about 1 min before anaphase onset. Cells that failed to degrade PTTG-EGFP exhibited asymmetrical cytokinesis without chromosome segregation (18 of 65 cells) or chromosome decondensation without cytokinesis (9 of 65 cells), resulting in appearance of a macronucleus. Fifty-one of 55 cells expressing a nondegradable mutant PTTG exhibited asymmetrical cytokinesis without chromosome segregation, and some (4 of 55) decondensed chromosomes, both resulting in macronuclear formation. During this abnormal cytokinesis, all chromosomes and spindles and both centrosomes moved to one daughter cell, suggesting potential chaos in the subsequent mitosis. In conclusion, failure of PTTG degradation or enhanced PTTG accumulation, as a consequence of overexpression, inhibits mitosis progression and chromosome segregation but does not directly affect cytokinesis, resulting in aneuploidy. These results demonstrate that PTTG induces aneuploidy in single, live, human cancer cells.

scholarly journals Intrinsic elasticity of nucleosomes is encoded by histone variants and calibrated by their binding partners

2019 ◽  
Vol 116 (48) ◽  
pp. 24066-24074 ◽  
Author(s):  
Daniël P. Melters ◽  
Mary Pitman ◽  
Tatini Rakshit ◽  
Emilios K. Dimitriadis ◽  
Minh Bui ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Chromosome Segregation ◽  
Binding Proteins ◽  
Histone Variants ◽  
Histone Variant ◽  
Binding Partners ◽  
Damage Repair ◽  
Fine Tune

Histone variants fine-tune transcription, replication, DNA damage repair, and faithful chromosome segregation. Whether and how nucleosome variants encode unique mechanical properties to their cognate chromatin structures remains elusive. Here, using in silico and in vitro nanoindentation methods, extending to in vivo dissections, we report that histone variant nucleosomes are intrinsically more elastic than their canonical counterparts. Furthermore, binding proteins, which discriminate between histone variant nucleosomes, suppress this innate elasticity and also compact chromatin. Interestingly, when we overexpress the binding proteins in vivo, we also observe increased compaction of chromatin enriched for histone variant nucleosomes, correlating with diminished access. Taken together, these data suggest a plausible link between innate mechanical properties possessed by histone variant nucleosomes, the adaptability of chromatin states in vivo, and the epigenetic plasticity of the underlying locus.

scholarly journals Cooperation between PDGF and FGF converts slowly dividing O-2Aadult progenitor cells to rapidly dividing cells with characteristics of O-2Aperinatal progenitor cells.

1992 ◽  
Vol 118 (4) ◽  
pp. 889-900 ◽  
Author(s):  
G Wolswijk ◽  
M Noble
Keyword(s):  
Progenitor Cells ◽  
Adult Brain ◽  
High Rate ◽  
Adult Rat ◽  
Large Numbers ◽  
Dividing Cells ◽  
Rapid Generation ◽  
And Migration

We have shown previously that oligodendrocyte-type-2 astrocyte (O-2A) progenitor cells isolated from adult rat optic nerves can be distinguished in vitro from their perinatal counterparts on the basis of their much slower rates of division, differentiation, and migration when grown in the presence of cortical astrocytes or PDGF. This behavior is consistent with in vivo observations that there is only a modest production of oligodendrocytes in the adult CNS. As such a behavior is inconsistent with the likely need for a rapid generation of oligodendrocytes following demyelinating damage to the mature CNS, we have been concerned with identifying in vitro conditions that allow O-2Aadult progenitor cells to generate rapidly large numbers of progeny cells. We now provide evidence that many slowly dividing O-2Aadult progenitor cells can be converted to rapidly dividing cells by exposing adult optic nerve cultures to both PDGF and bFGF. In addition, these O-2Aadult progenitor cells appear to acquire other properties of O-2Aperinatal progenitor cells, such as bipolar morphology and high rate of migration. Although many O-2Aadult progenitor cells in cultures exposed to bFGF alone also divide rapidly, these cells are multipolar and migrate little in vitro. Oligodendrocytic differentiation of O-2Aadult progenitor cells, which express receptors for bFGF in vitro, is almost completely inhibited in cultures exposed to bFGF or bFGF plus PDGF. As bFGF and PDGF appear to be upregulated and/or released after injury to the adult brain, this particular in vitro response of O-2Aadult progenitor cells to PDGF and bFGF may be of importance in the generation of large numbers of new oligodendrocytes in vivo following demyelination.

scholarly journals Diamond Nanoparticles Downregulate Expression of CycD and CycE in Glioma Cells

Molecules ◽  
2019 ◽  
Vol 24 (8) ◽  
pp. 1549 ◽  
Author(s):  
Marta Grodzik ◽  
Jaroslaw Szczepaniak ◽  
Barbara Strojny-Cieslak ◽  
Anna Hotowy ◽  
Mateusz Wierzbicki ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Glioma Cells ◽  
Migration And Invasion ◽  
Control Group ◽  
Ki 67 ◽  
Normal Cells ◽  
Diamond Nanoparticles ◽  
Dividing Cells

Our previous studies have shown that diamond nanoparticles (NDs) exhibited antiangiogenic and proapoptotic properties in vitro in glioblastoma multiforme (GBM) cells and in tumors in vivo. Moreover, NDs inhibited adhesion, leading to the suppression of migration and invasion of GBM. In the present study, we hypothesized that the NDs might also inhibit proliferation and cell cycle in glioma cells. Experiments were performed in vitro with the U87 and U118 lines of GBM cells, and for comparison, the Hs5 line of stromal cells (normal cells) after 24 h and 72 h of treatment. The analyses included cell morphology, cell death, viability, and cell cycle analysis, double timing assay, and gene expression (Rb, E2F1, CycA, CycB, CycD, CycE, PTEN, Ki-67). After 72 h of ND treatment, the expression level of Rb, CycD, and CycE in the U118 cells, and E2F1, CycD, and CycE in the U87 cells were significantly lower in comparison to those in the control group. We observed that decreased expression of cyclins inhibited the G1/S phase transition, arresting the cell cycle in the G0/G1 phase in glioma cells. The NDs did not affect the cell cycle as well as PTEN and Ki-67 expression in normal cells (Hs5), although it can be assumed that the NDs reduced proliferation and altered the cell cycle in fast dividing cells.

scholarly journals Multi-scale modeling of drug binding kinetics to predict drug efficacy

2019 ◽  
Vol 77 (3) ◽  
pp. 381-394 ◽  
Author(s):  
Fabrizio Clarelli ◽  
Jingyi Liang ◽  
Antal Martinecz ◽  
Ines Heiland ◽  
Pia Abel zur Wiesch
Keyword(s):  
Mathematical Models ◽  
Drug Efficacy ◽  
Drug Binding ◽  
Binding Kinetics ◽  
Multi Scale ◽  
Drug Concentrations ◽  
Body Compartments ◽  
Target Binding

AbstractOptimizing drug therapies for any disease requires a solid understanding of pharmacokinetics (the drug concentration at a given time point in different body compartments) and pharmacodynamics (the effect a drug has at a given concentration). Mathematical models are frequently used to infer drug concentrations over time based on infrequent sampling and/or in inaccessible body compartments. Models are also used to translate drug action from in vitro to in vivo conditions or from animal models to human patients. Recently, mathematical models that incorporate drug-target binding and subsequent downstream responses have been shown to advance our understanding and increase predictive power of drug efficacy predictions. We here discuss current approaches of modeling drug binding kinetics that aim at improving model-based drug development in the future. This in turn might aid in reducing the large number of failed clinical trials.

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