Diamond nanoparticles modity curcumin activity:<i>in vitro</i> studies on cancer and normal cells and <i>in ovo</i> studies on chicken embryo model

Curcumin has been studied broadly for its wide range of biological activities, including anticancer properties. The major problem with curcumin is its poor bioavailability, which can be improved by the addition of carriers, such as diamond nanoparticles (DN). They are carbon allotropes, and are therefore biocompatible and easily taken up by cells. DN are non-toxic and have antiangiogenic properties with potential applications in cancer therapy. Their large surface makes them promising compounds in a drug delivery system for bioactive agents, as DN create bio-complexes in a fast and simple process of self-organisation. We investigated the cytotoxicity of such bio-complexes against liver cancer cells and normal fibroblasts, revealing that conjugation of curcumin with DN significantly improves its activity. The experiment performed in a chicken embryo model demonstrated that neither curcumin nor DN nor bio-complexes affect embryo development, even though DN can form deposits in tissues. Preliminary results confirmed the applicability of DN as an efficient carrier of curcumin, which improves its performance against cancer cells in vitro, yet is not toxic to an organism, which makes the bio-complex a promising anticancer agent

Cytoskeletal vimentin regulates cell size and autophagy through mTORC1 signaling

The nutrient-activated mTORC1 (mechanistic target of rapamycin kinase complex 1) signaling pathway determines cell size by controlling mRNA translation, ribosome biogenesis, protein synthesis, and autophagy. Here, we show that vimentin, a cytoskeletal intermediate filament protein that we have known to be important for wound healing and cancer progression, determines cell size through mTORC1 signaling, an effect that is also manifested at the organism level in mice. This vimentin-mediated regulation is manifested at all levels of mTOR downstream target activation and protein synthesis. We found that vimentin maintains normal cell size by supporting mTORC1 translocation and activation by regulating the activity of amino acid sensing Rag GTPase. We also show that vimentin inhibits the autophagic flux in the absence of growth factors and/or critical nutrients, demonstrating growth factor-independent inhibition of autophagy at the level of mTORC1. Our findings establish that vimentin couples cell size and autophagy through modulating Rag GTPase activity of the mTORC1 signaling pathway

Cytoskeletal vimentin regulates cell size and autophagy through mTORC1 signaling

The nutrient-activated mTORC1 (mechanistic target of rapamycin kinase complex 1) signaling pathway determines cell size by controlling mRNA translation, ribosome biogenesis, protein synthesis, and autophagy. Here, we show that vimentin, a cytoskeletal intermediate filament protein that we have known to be important for wound healing and cancer progression, determines cell size through mTORC1 signaling, an effect that is also manifested at the organism level in mice. This vimentin-mediated regulation is manifested at all levels of mTOR downstream target activation and protein synthesis. We found that vimentin maintains normal cell size by supporting mTORC1 translocation and activation by regulating the activity of amino acid sensing Rag GTPase. We also show that vimentin inhibits the autophagic flux in the absence of growth factors and/or critical nutrients, demonstrating growth factor-independent inhibition of autophagy at the level of mTORC1. Our findings establish that vimentin couples cell size and autophagy through modulating Rag GTPase activity of the mTORC1 signaling pathway. © 2022 Mohanasundaram et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</p

Single-cell mechanical phenotyping across timescales and cell state transitions

Mechanical properties of cells and their environment have an undeniable impact on physiological and pathological processes such as tissue development or cancer metastasis. Hence, there is a pressing need for establishing and validating methodologies for measuring the mechanical properties of cells, as well as for deciphering the molecular underpinnings that govern the mechanical phenotype. During my doctoral research, I addressed these needs by pushing the boundaries of the field of single-cell mechanics in four projects, two of which were method-oriented and two explored important biological questions. First, I consolidated real-time deformability cytometry as a method for high-throughput single-cell mechanical phenotyping and contributed to its transformation into a versatile image-based cell characterization and sorting platform. Importantly, this platform can be used not only to sort cells based on image-derived parameters, but also to train neural networks to recognize and sort cells of interest based on raw images. Second, I performed a cross-laboratory study comparing three microfluidics-based deformability cytometry approaches operating at different timescales in two standardized assays of osmotic shock and actin disassembly. This study revealed that while all three methods are sensitive to osmotic shock-induced changes in cell deformability, the method operating at the shortest timescale is not suited for detection of actin cytoskeleton changes. Third, I demonstrated changes in cell mechanical phenotype associated with cell fate specification on the example of differentiation and de-differentiation along the neural lineage. In the process of reprogramming to pluripotency, neural precursor cells acquired progressively stiffer phenotype, that was reversed in the process of neural differentiation. The stiff phenotype of induced pluripotent stem cells was equivalent to that of embryonic stem cells, suggesting that mechanical properties of cells are inherent to their developmental stage. Finally, I identified and validated novel target genes involved in the regulation of mechanical properties of cells. The targets were identified using machine learning-based network analysis of transcriptomic profiles associated with mechanical phenotype change, and validated computationally as well as in genetic perturbation experiments. In particular, I showed that the gene with the best in silico performance, CAV1, changes the mechanical properties of cells when silenced or overexpressed. Identification of novel targets for mechanical phenotype modification is crucial for future explorations of physiological and pathological roles of cell mechanics. Together, this thesis encompasses a collection of contributions at the frontier of single-cell mechanical characterization across timescales and cell state transitions, and lays ground for turning cell mechanics from a correlative phenomenological parameter to a controllable property.:Abstract Kurzfassung List of Publications Contents Introduction Chapter 1 — Background 1.1. Mechanical properties as a marker of cell state in health and disease 1.2. Functional relevance of single-cell mechanical properties 1.3. Internal structures determining mechanical properties of cells 1.4. Cell as a viscoelastic material 1.5. Methods to measure single-cell mechanical properties Aims and scope of this thesis Chapter 2 — RT-DC as a versatile method for image-based cell characterization and sorting 2.1. RT-DC for mechanical characterization of cells 2.1.1. Operation of the RT-DC setup 2.1.2. Extracting Young’s modulus from RT-DC data 2.2. Additional functionalities implemented to the RT-DC setup 2.2.1. 1D fluorescence readout in three spectral channels 2.2.2. SSAW-based active cell sorting 2.3. Beyond assessment of cell mechanics — emerging applications 2.3.1. Deformation-assisted population separation and sorting 2.3.2. Brightness-based identification and sorting of blood cells 2.3.3. Transferring molecular specificity into label-free cell sorting 2.4. Discussion 2.5. Key conclusions 2.6. Materials and experimental procedures 2.7. Data analysis Chapter 3 — A comparison of three deformability cytometry classes operating at different timescales 3.1. Results 3.1.1. Representatives of the three deformability cytometry classes 3.1.2. Osmotic shock-induced deformability changes are detectable in all three methods 3.1.3. Ability to detect actin disassembly is method-dependent 3.1.4. Strain rate increase decreases the range of deformability response to actin disassembly in sDC 3.2. Discussion 3.3. Key conclusions 3.4. Materials and methods Chapter 4 — Mechanical journey of neural progenitor cells to pluripotency and back 4.1. Results 4.1.1. fNPCs become progressively stiffer during reprogramming to pluripotency 4.1.2. Transgene-dependent F-class cells are more compliant than ESC-like iPSCs 4.1.3. Surface markers unravel mechanical subpopulations at intermediate reprogramming stages 4.1.4. Neural differentiation of iPSCs mechanically mirrors reprogramming of fNPCs 4.1.5. The closer to the pluripotency, the higher the cell stiffness 4.2. Discussion 4.3. Key conclusions 4.4. Materials and methods Chapter 5 — Data-driven approach for de novo identification of cell mechanics regulators 5.1. Results 5.1.1. An overview of the mechanomics approach 5.1.2. Model systems characterized by mechanical phenotype changes 5.1.3. Discriminative network analysis on discovery datasets 5.1.4. Conserved functional network module comprises five genes 5.1.5. CAV1 performs best at classifying soft and stiff cell states in validation datasets 5.1.6. Perturbing expression levels of CAV1 changes cells stiffness 5.2. Discussion 5.3. Key conclusions 5.4. Materials and methods Conclusions and Outlook Appendix A Appendix B Supplementary Tables B.1 – B.2 Supplementary Figures B.1 – B.9 Appendix C Supplementary Tables C.1 – C.2. Supplementary Figures C.1 – C.5 Appendix D Supplementary Tables D.1 – D.6 Supplementary Figures D.1 – D.7 List of Figures List of Tables List of Abbreviations. List of Symbols References Acknowledgement

Cfap91-Dependent Stability of the RS2 and RS3 Base Proteins and Adjacent Inner Dynein Arms in Tetrahymena Cilia

Motile cilia and eukaryotic flagella are specific cell protrusions that are conserved from protists to humans. They are supported by a skeleton composed of uniquely organized microtubules&mdash;nine peripheral doublets and two central singlets (9 &times; 2 + 2). Microtubules also serve as docking sites for periodically distributed multiprotein ciliary complexes. Radial spokes, the T-shaped ciliary complexes, repeat along the outer doublets as triplets and transduce the regulatory signals from the cilium center to the outer doublet-docked dynein arms. Using the genetic, proteomic, and microscopic approaches, we have shown that lack of Tetrahymena Cfap91 protein affects stable docking/positioning of the radial spoke RS3 and the base of RS2, and adjacent inner dynein arms, possibly due to the ability of Cfap91 to interact with a molecular ruler protein, Ccdc39. The localization studies confirmed that the level of RS3-specific proteins, Cfap61 and Cfap251, as well as RS2-associated Cfap206, are significantly diminished in Tetrahymena CFAP91-KO cells. Cilia of Tetrahymena cells with knocked-out CFAP91 beat in an uncoordinated manner and their beating frequency is dramatically reduced. Consequently, CFAP91-KO cells swam about a hundred times slower than wild-type cells. We concluded that Tetrahymena Cfap91 localizes at the base of radial spokes RS2 and RS3 and likely plays a role in the radial spoke(s) positioning and stability

Highly-Parallel Microfluidics-Based Force Spectroscopy on Single Cytoskeletal Motors

Cytoskeletal motors transform chemical energy into mechanical work to drive essential cellular functions. Optical trapping experiments have provided crucial insights into the operation of these molecular machines under load. However, the throughput of such force spectroscopy experiments is typically limited to one measurement at a time. Here, a highly-parallel, microfluidics-based method that allows for rapid collection of force-dependent motility parameters of cytoskeletal motors with two orders of magnitude improvement in throughput compared to currently available methods is introduced. Tunable hydrodynamic forces to stepping kinesin-1 motors via DNA-tethered beads and utilize a large field of view to simultaneously track the velocities, run lengths, and interaction times of hundreds of individual kinesin-1 molecules under varying resisting and assisting loads are applied. Importantly, the 16 µm long DNA tethers between the motors and the beads significantly reduces the vertical component of the applied force pulling the motors away from the microtubule. The approach is readily applicable to other molecular systems and constitutes a new methodology for parallelized single-molecule force studies on cytoskeletal motors