scholarly journals High resolution AKT signaling in individual cells

2018 ◽  
Author(s):  
Sean M. Gross ◽  
Mark A. Dane ◽  
Elmar Bucher ◽  
Laura M. Heiser

AbstractCells sense and respond to their environment by activating distinct intracellular signaling pathways, however an individual cell’s ability to faithfully transmit and discriminate environmental signals is thought to be limited. To assess the fidelity of signal transmission in the PI3K-AKT signaling pathway, we first developed an optimized genetically encoded sensor that had an increased dynamic range and reduced variation under basal conditions. We then used this reporter to track responses to varying doses of IGF-I in live cells and found that signaling responses from individual cells overlapped across a wide range of IGF-I doses, suggesting limited transmission accuracy. However, further analysis of individual cell traces revealed that responses were constant over time without stochastic fluctuations. We devised a new information theoretic approach to calculate the channel capacity using variance of the single cell time course data‐‐rather than population-level variance as has been previously used—and predicted that cells were capable of discriminating multiple growth factor doses. We validated these predictions by tracking individual cell responses to multiple IGF-I doses and found that cells can accurately distinguish at least four different IGF-I concentrations, as demonstrated by their distinct responses. Furthermore, we found a similar discriminatory ability to pathway inhibition, as assessed by responses to the PI3K inhibitor alpelisib. Our studies indicate that cells can faithfully transmit an IGF-I input into a down-stream signaling response and that heterogeneous responses result from variation in the input-output relation across the population. These observations reveal the importance of viewing each cell as having its own communication channel and underscore the importance of understanding responses at the single cell level.

2018 ◽  
Vol 96 (2) ◽  
pp. 102-109 ◽  
Author(s):  
Man Chung Gilbert Lee ◽  
Bingyun Sun

Protein nonspecific adsorption that occurred at the solid–liquid interface has been subjected to intense physical and chemical characterizations due to its crucial role in a wide range of applications, including food and pharmaceutical industries, medical implants, biosensing, and so on. Protein-adsorption caused sample loss has largely hindered the studies of single-cell proteomics; the prevention of such loss requires the understanding of protein–surface adsorption at the proteome level, in which the competitive adsorption of thousands and millions of proteins with vast dynamic range occurs. To this end, we feel the necessity to review current methodologies on their potentials to characterize — more specifically to quantify — the proteome-wide adsorption. We hope this effort can help advancing single-cell proteomics and trace proteomics.


2017 ◽  
Author(s):  
Mayank Sharma ◽  
Huipeng Li ◽  
Debarka Sengupta ◽  
Shyam Prabhakar ◽  
Jayadeva

AbstractRecent advances in single cell RNA-seq technologies have provided researchers with unprecedented details of transcriptomic variation across individual cells. However, it has not been straightforward to infer differentiation trajectories from such data, due to the parameter-sensitivity of existing methods. Here, we present Finding Orderings Robustly using k-means and Steiner trees (FORKS), an algorithm that pseudo-temporally orders cells and thereby infers bifurcating state trajectories. FORKS, which is a generic method, can be applied to both single-cell and bulk differentiation data. It is a semi-supervised approach, in that it requires the user to specify the starting point of the time course. We systematically benchmarked FORKS and eight other pseudo-time estimation algorithms on six benchmark datasets, and found it to be more accurate, more reproducible, and more memory-efficient than existing methods for pseudo-temporal ordering. Another major advantage of our approach is its robustness – FORKS can be used with default parameter settings on a wide range of datasets.


Author(s):  
John Henningsen ◽  
Matthaeus Schwarz-Schilling ◽  
Andreas Leibl ◽  
Joaquin A. M. Guttierez ◽  
Sandra Sagredo ◽  
...  

AbstractGenetic networks that generate oscillations in gene expression activity are found in a wide range of organisms throughout all kingdoms of life. Oscillatory dynamics facilitates the temporal orchestration of metabolic and growth processes inside cells and organisms, as well as the synchronization of such processes with periodically occurring changes in the environment. Synthetic oscillator gene circuits such as the ‘repressilator’ can perform similar functions in bacteria. Until recently, such circuits were mainly based on a relatively small set of well-characterized transcriptional repressors and activators. A promising, sequence-programmable alternative for gene regulation is given by CRISPR interference (CRISPRi), which enables transcriptional repression of nearly arbitrary gene targets directed by short guide RNA molecules. In order to demonstrate the use of CRISPRi in the context of dynamic gene circuits, we here replaced one of the nodes of a repressilator circuit by the RNA-guided dCas9 protein. Using single cell experiments in microfluidic reactors we show that this system displays robust relaxation oscillations over multiple periods and over the time course of several days. Through statistical analysis of the single cell data, the potential for the circuit to act as a synthetic pacemaker for cellular processes is evaluated. The use of CRISPRi in the context of an oscillator circuit is found to have profound effects on its dynamics. Specifically, irreversible binding of dCas9-sgRNA appears to prolong the period of the oscillator. Further, we demonstrate that the oscillator affects cellular growth, leading to variations in growth rate with the oscillator’s frequency.


2020 ◽  
Vol 20 (12) ◽  
pp. 1074-1092 ◽  
Author(s):  
Rammohan R.Y. Bheemanaboina

Phosphoinositide 3-kinases (PI3Ks) are a family of ubiquitously distributed lipid kinases that control a wide variety of intracellular signaling pathways. Over the years, PI3K has emerged as an attractive target for the development of novel pharmaceuticals to treat cancer and various other diseases. In the last five years, four of the PI3K inhibitors viz. Idelalisib, Copanlisib, Duvelisib, and Alpelisib were approved by the FDA for the treatment of different types of cancer and several other PI3K inhibitors are currently under active clinical development. So far clinical candidates are non-selective kinase inhibitors with various off-target liabilities due to cross-reactivities. Hence, there is a need for the discovery of isoform-selective inhibitors with improved efficacy and fewer side-effects. The development of isoform-selective inhibitors is essential to reveal the unique functions of each isoform and its corresponding therapeutic potential. Although the clinical effect and relative benefit of pan and isoformselective inhibition will ultimately be determined, with the development of drug resistance and the demand for next-generation inhibitors, it will continue to be of great significance to understand the potential mechanism of isoform-selectivity. Because of the important role of type I PI3K family members in various pathophysiological processes, isoform-selective PI3K inhibitors may ultimately have considerable efficacy in a wide range of human diseases. This review summarizes the progress of isoformselective PI3K inhibitors in preclinical and early clinical studies for anticancer and other various diseases.


Plants ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1443
Author(s):  
Yoshiaki Kamiyama ◽  
Sotaro Katagiri ◽  
Taishi Umezawa

Reversible phosphorylation is a major mechanism for regulating protein function and controls a wide range of cellular functions including responses to external stimuli. The plant-specific SNF1-related protein kinase 2s (SnRK2s) function as central regulators of plant growth and development, as well as tolerance to multiple abiotic stresses. Although the activity of SnRK2s is tightly regulated in a phytohormone abscisic acid (ABA)-dependent manner, recent investigations have revealed that SnRK2s can be activated by group B Raf-like protein kinases independently of ABA. Furthermore, evidence is accumulating that SnRK2s modulate plant growth through regulation of target of rapamycin (TOR) signaling. Here, we summarize recent advances in knowledge of how SnRK2s mediate plant growth and osmotic stress signaling and discuss future challenges in this research field.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ibtissame Khaoua ◽  
Guillaume Graciani ◽  
Andrey Kim ◽  
François Amblard

AbstractFor a wide range of purposes, one faces the challenge to detect light from extremely faint and spatially extended sources. In such cases, detector noises dominate over the photon noise of the source, and quantum detectors in photon counting mode are generally the best option. Here, we combine a statistical model with an in-depth analysis of detector noises and calibration experiments, and we show that visible light can be detected with an electron-multiplying charge-coupled devices (EM-CCD) with a signal-to-noise ratio (SNR) of 3 for fluxes less than $$30\,{\text{photon}}\,{\text{s}}^{ - 1} \,{\text{cm}}^{ - 2}$$ 30 photon s - 1 cm - 2 . For green photons, this corresponds to 12 aW $${\text{cm}}^{ - 2}$$ cm - 2 ≈ $$9{ } \times 10^{ - 11}$$ 9 × 10 - 11 lux, i.e. 15 orders of magnitude less than typical daylight. The strong nonlinearity of the SNR with the sampling time leads to a dynamic range of detection of 4 orders of magnitude. To detect possibly varying light fluxes, we operate in conditions of maximal detectivity $${\mathcal{D}}$$ D rather than maximal SNR. Given the quantum efficiency $$QE\left( \lambda \right)$$ Q E λ of the detector, we find $${ \mathcal{D}} = 0.015\,{\text{photon}}^{ - 1} \,{\text{s}}^{1/2} \,{\text{cm}}$$ D = 0.015 photon - 1 s 1 / 2 cm , and a non-negligible sensitivity to blackbody radiation for T > 50 °C. This work should help design highly sensitive luminescence detection methods and develop experiments to explore dynamic phenomena involving ultra-weak luminescence in biology, chemistry, and material sciences.


Genes ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 311
Author(s):  
Zhenqiu Liu

Single-cell RNA-seq (scRNA-seq) is a powerful tool to measure the expression patterns of individual cells and discover heterogeneity and functional diversity among cell populations. Due to variability, it is challenging to analyze such data efficiently. Many clustering methods have been developed using at least one free parameter. Different choices for free parameters may lead to substantially different visualizations and clusters. Tuning free parameters is also time consuming. Thus there is need for a simple, robust, and efficient clustering method. In this paper, we propose a new regularized Gaussian graphical clustering (RGGC) method for scRNA-seq data. RGGC is based on high-order (partial) correlations and subspace learning, and is robust over a wide-range of a regularized parameter λ. Therefore, we can simply set λ=2 or λ=log(p) for AIC (Akaike information criterion) or BIC (Bayesian information criterion) without cross-validation. Cell subpopulations are discovered by the Louvain community detection algorithm that determines the number of clusters automatically. There is no free parameter to be tuned with RGGC. When evaluated with simulated and benchmark scRNA-seq data sets against widely used methods, RGGC is computationally efficient and one of the top performers. It can detect inter-sample cell heterogeneity, when applied to glioblastoma scRNA-seq data.


2021 ◽  
Vol 7 (2) ◽  
pp. 205521732110227
Author(s):  
Friederike Held ◽  
Sudhakar Reddy Kalluri ◽  
Achim Berthele ◽  
Ana-Katharina Klein ◽  
Markus Reindl ◽  
...  

Background Myelin oligodendrocyte glycoprotein (MOG) antibody disease (MOG-AD) is recognized as a distinct nosological entity. IgG antibodies against MOG (MOG-Ab) overlap with neuromyelitis optica spectrum disorders (NMOSD) phenotype in adults. However, an increasing number of clinical phenotypes have been reported to be associated with MOG-Ab. Objective To investigate the seroprevalence of MOG-Ab under consideration of demographics, disease entities and time course in a large cohort of unselected neurological patients. Methods Blood samples of 2.107 consecutive adult neurologic patients admitted to our department between 2016-2017 were tested for MOG-Ab using a cell-based assay. MOG-Ab persistence was analyzed in follow-up samples. External validation was performed in two independent laboratories. Results We found MOG-Ab in 25 of 2.107 (1.2%) patients. High antibody ratios were mostly associated with NMOSD and MOG-AD phenotype (5/25). Low ratios occurred in a wide range of neurological diseases, predominantly in other demyelinating CNS diseases (5/25) and stroke (6/25). MOG-Ab persistence over time was not confined to NMOSD and MOG-AD phenotype. Conclusion The present study demonstrates the occurrence of MOG-Ab in a wide range of neurological diseases. Only high MOG-Ab ratios were associated with a defined clinical phenotype, but low MOG-Ab ratios were not. The diagnostic value of low MOG-Ab is thus highly limited.


2021 ◽  
Vol 10 (3) ◽  
pp. 506
Author(s):  
Hans Binder ◽  
Maria Schmidt ◽  
Henry Loeffler-Wirth ◽  
Lena Suenke Mortensen ◽  
Manfred Kunz

Cellular heterogeneity is regarded as a major factor for treatment response and resistance in a variety of malignant tumors, including malignant melanoma. More recent developments of single-cell sequencing technology provided deeper insights into this phenomenon. Single-cell data were used to identify prognostic subtypes of melanoma tumors, with a special emphasis on immune cells and fibroblasts in the tumor microenvironment. Moreover, treatment resistance to checkpoint inhibitor therapy has been shown to be associated with a set of differentially expressed immune cell signatures unraveling new targetable intracellular signaling pathways. Characterization of T cell states under checkpoint inhibitor treatment showed that exhausted CD8+ T cell types in melanoma lesions still have a high proliferative index. Other studies identified treatment resistance mechanisms to targeted treatment against the mutated BRAF serine/threonine protein kinase including repression of the melanoma differentiation gene microphthalmia-associated transcription factor (MITF) and induction of AXL receptor tyrosine kinase. Interestingly, treatment resistance mechanisms not only included selection processes of pre-existing subclones but also transition between different states of gene expression. Taken together, single-cell technology has provided deeper insights into melanoma biology and has put forward our understanding of the role of tumor heterogeneity and transcriptional plasticity, which may impact on innovative clinical trial designs and experimental approaches.


2021 ◽  
Vol 22 (2) ◽  
pp. 677
Author(s):  
Tausif Altamash ◽  
Wesam Ahmed ◽  
Saad Rasool ◽  
Kabir H. Biswas

Intracellular ionic strength regulates myriad cellular processes that are fundamental to cellular survival and proliferation, including protein activity, aggregation, phase separation, and cell volume. It could be altered by changes in the activity of cellular signaling pathways, such as those that impact the activity of membrane-localized ion channels or by alterations in the microenvironmental osmolarity. Therefore, there is a demand for the development of sensitive tools for real-time monitoring of intracellular ionic strength. Here, we developed a bioluminescence-based intracellular ionic strength sensing strategy using the Nano Luciferase (NanoLuc) protein that has gained tremendous utility due to its high, long-lived bioluminescence output and thermal stability. Biochemical experiments using a recombinantly purified protein showed that NanoLuc bioluminescence is dependent on the ionic strength of the reaction buffer for a wide range of ionic strength conditions. Importantly, the decrease in the NanoLuc activity observed at higher ionic strengths could be reversed by decreasing the ionic strength of the reaction, thus making it suitable for sensing intracellular ionic strength alterations. Finally, we used an mNeonGreen–NanoLuc fusion protein to successfully monitor ionic strength alterations in a ratiometric manner through independent fluorescence and bioluminescence measurements in cell lysates and live cells. We envisage that the biosensing strategy developed here for detecting alterations in intracellular ionic strength will be applicable in a wide range of experiments, including high throughput cellular signaling, ion channel functional genomics, and drug discovery.


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