Nanomechanics of Platelet Contractility

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 2202-2202
Author(s):  
David R Myers ◽  
Todd Sulchek ◽  
Wilbur Lam

Abstract Abstract 2202 Background: Blood clots are composed of fibrin, platelets, and other blood cells and proteins, which interact to prevent hemorrhage. Previous studies on clot formation have shown that the mechanical properties of clots have direct effects on hemostasis and thrombosis, and alterations of those clot mechanics are associated with disease. For example, clots are 50% stiffer and more resistant to dissolution in young patients with post-myocardial infarction (Collet, et al., Arterioscler Thromb Vasc Biol, 2006) than clots from healthy controls. Conversely, clots are softer and more prone to dissolution in patients with bleeding disorders (Hvas, et al., J. Thrombosis and Haemostasis, 2007). As such, understanding the mechanical properties of clots is vital to understand hemostasis and thrombosis. As platelets drive this contraction phenomenon, single platelet measurements are required to obtain a mechanistic understanding of the retraction process and to identify specific therapeutic targets for disease states in which platelet/clot retraction is pathologically altered. In addition, as fibrin has recently been shown to have extremely complex material and mechanical properties (Brown, et al., Science, 2009), single platelet studies would decouple the effects of fibrin from platelets when examining clot mechanics. However, few studies have focused on the biomechanical role of platelets in clot formation and clot mechanics, especially at the single cell level. The key barrier which has prevented the study of single platelets has been the lack of technology with the sufficient precision and sensitivity to both manipulate and measure individual platelets. To that end, we recently published the first study investigating platelet contractility at the single cell level using an atomic force microscope (AFM) (Lam, et al., Nat Mater, 2011) Results: An AFM enables precise measurements of force down to the pico-newton level. A mechanically well-defined, fibrinogen-coated cantilever is brought into contact with a platelet and then brought to a fibrinogen-coated surface as shown in Figure 1A. The platelet will contract and the resulting deflection of the cantilever is measured with high accuracy to determine the force applied by the platelet. From AFM studies, it was found that both the loading rate (Fig 1B) and maximum contraction force exerted by single platelets (Fig 1C) were a function of the mechanical stiffness of the cantilever. Furthermore, preliminary data using the same techniques is indicating that there may be a unique subpopulation of platelets which exhibit high-amplitude, oscillatory contraction as shown in Figure 1D. Conclusions and Ongoing Effort: Ours is the first reported data measuring platelet contraction at the single cell level and reveals that platelets are extremely “strong” contractile machines, especially when taking account their small size. In addition, we discovered that platelets can “sense” their mechanical microenvironment, adjusting their contractility accordingly. Based on this research, the overall theme of this proposed work is to quantitatively investigate how the biophysics interacts with the molecular biology of platelet contraction. However, our initial work and past research have shown that platelets within a given population exhibit varied behavior, and to truly obtain meaningful data, studies on large populations are necessary. We are developing a high-throughput device that is capable of individually measuring the contractility of thousands of platelets using the same principles as AFM. As this “biomechanical flow cytometer” leverages microfabrication techniques, it offers new capabilities to manipulate the platelet microenvironment while making contractility measurements. This device will use massively parallel sets of polymer cantilevers to measure individual platelet contractility with an integrated microfluidic delivery system (Figure 2). Platelets flowing in the microfluidic channel will be captured by a set of fibrinogen-coated cantilevers. As the platelet contracts, the deflection of the cantilever tip can be measured optically, which is correlated to the force with the cantilever spring constant. Leveraging the capabilities of this system to test multiple conditions simultaneously, we will vary shear stresses and expose platelet to different doses of different agonists and determine how these parameters affect contraction. Disclosures: No relevant conflicts of interest to declare.

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 785-785
Author(s):  
Paul S. Hole ◽  
Sara Davies ◽  
Chinmay R Munje ◽  
Sandra Kreuser ◽  
Robert K. Hills ◽  
...  

Abstract The serine/ threonine kinase, p38MAPK is activated by phosphorylation in response to a variety of cellular stresses including oxidative stress. Prolonged p38MAPK activation drives cell-cycle arrest and apoptosis; and in HSC activation of p38MAPK leads to a loss of reconstituting capacity (Ito et al, Nat.Med. 2006;12:446-451). In cancer, p38MAPK responses are often attenuated and cancer models suggest that this is a necessary adaptation for transformation (Dolado et al, Cancer Cell 2007;11:191-205). Previously we have shown that 60% of acute myeloid leukemia (AML) patients constitutively generate significantly more extracellular reactive oxygen species (ROS) than normal hematopoietic CD34+ cells (Hole et al, Blood 2013;122:3322-3330). Despite this, AML blasts showed low or absent p38MAPK phosphorylation; even in patients generating high levels of ROS. Here we examine p38MAPK activation at the single cell level in primary AML blasts using flow cytometry. We challenged AML blasts with a dose of hydrogen peroxide (H2O2) sufficient to completely activate p38MAPK in normal CD34+ cells (1 mM for 30 min), where the threshold for activation was defined as the 95th percentile of basal p38MAPK activation in unstimulated cells. Attenuated responses to H2O2 were seen in 14/15 (93%) of patients; where 16-95% of the total blast population failed to activate p38MAPK. These non-responding cells are hereafter termed “Δpp38MAPK cells” and were absent in normal CD34+ cells (p < 0.01; Figure 1). Examination of a panel of 6 AML cell lines showed that each of the lines contained Δpp38MAPK cells at different frequencies: MV4-11 (10%); HL60 (10%); KG-1 (15%), U937 (30%), NB4 (50%), THP-1 (65%). Further analysis showed that Δpp38MAPK cells were not distinguished by cell cycle phase, immunophenotype or reduced viability in either cell lines or AML blasts. These data suggest that nearly all AML patients harbor a population of blasts which have developed resistance to p38MAPK activation. We reasoned that failure to respond could arise either through defective p38MAPK signaling or because of enhanced anti-oxidative protection in a subpopulation of cells. To investigate the latter, we labelled cells with the lipophilic oxidation probe, C11 -BODIPY or the cytosolic oxidant probe, CM-DCFDA and monitored the oxidative response to H2O2 at the single cell level in the AML cell lines: KG-1, MV4-11 and THP-1. In each case C11 -BODIPY oxidation exactly matched the heterogeneous profile of p38MAPK activation in these cells, whereas CM-DCFDA showed only homogeneous responses to H2O2 induction. These data show that Δpp38MAPK cells are defined by an enhanced membrane-associated anti-oxidant capacity and we are currently analyzing this resistant subpopulation to identify the molecules responsible. To examine whether p38MAPK responsiveness influenced responsiveness to pro-oxidant drugs, we selected KG-1 and THP-1 cells (as representative examples of strong and weak p38MAPK responses respectively) and tested their sensitivity to the pro-oxidant drugs, phenethyl isothiocyanate (PEITC) and buthionine sulfoximine (BSO). We found that the IC50 was higher for THP-1 for both PEITC (KG-1 = 0.6µM; THP-1 = 7.5µM) and BSO (KG-1 = 50µM; THP-1 = 70µM), indicating that the p38MAPK responsiveness limits the effectiveness of pro-oxidant drugs. We next examined whether promoting p38MAPK activation could augment the effects of these pro-oxidants. We used the p38MAPK activator 2-benzylidene-3-(cyclohexylamino)-1-indanone (BCI), which promotes activation of p38MAPK via inhibition of a p38MAPK phosphatase, DUSP1. This compound weakly promoted phosphorylation of p38MAPK in THP-1 cells and consistent with this, had no effect on the efficacy of these compounds in these cells. However, BCI potently activated p38MAPK in KG-1 cells and showed synergy with BSO in this context (CI = 0.3; Figure 2) indicating that where BCI is effective in activating p38MAPK it can promote the effectiveness of pro-oxidant drugs. In summary, we show for the first time that AML patients almost universally display attenuated p38MAPK responses in all or part of the blast population and we suggest that this trait may be selected for to maintain self-renewing potential under the pro-oxidative conditions found in the leukemic marrow. Further we show that by manipulating p38MAPK activity, we can augment the potency of the pro-oxidant compound BSO. Figure 1 Figure 1. Figure 2 Figure 2. Disclosures No relevant conflicts of interest to declare.


Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 31-32
Author(s):  
Hongqiang Jiang ◽  
Honglei Tu ◽  
Yanxia Jin ◽  
Xianjin Wu ◽  
Ziyi Luo ◽  
...  

Abstract Background: Multiple myeloma (MM) is a hematology malignant disease originated from B-cell line and still incurable. Compound Kushen Injection (CKI) as a Traditional Chinese Medicines are promising agents in our previous research for treating cancer. The effect of CKI on multiple myeloma was still unknown. Methods: In vitro experiment, flow cytometry was used to evaluate effect of CKI on multiple myeloma cells. Optofluidic chip was applied to detect effect at single-cell level. And in vivo RPMI-8226 GFP+ B-NSG mouse model was built to assess the role of CKI in multiple myeloma treatment. Results: CKI inhibited MM cells proliferation of and increased its apoptosis rate. And the cell cycle of MM cells was also arrested by CKI treatment. In contrast, CKI has few toxic effects on mesenchymal stem cells (MSCs) and MC3T3 cells. At the single-cell level, MM cells was died in time and dose dependent manner. Transcriptome find that the expression of MYC and TERT in CKI-treated RPMI-8226 cells was significantly down-regulated and confirmed by qRT-PCR and Western blot. Overexpression of TERT can partly reverse the inhibition effect of CKI on RPMI-8226 cells. B-NSG mouse was injected with GFP+ RPMI-8226 cells through caudal vein, and the disease was partially alleviated by decreased tumor burden in the CKI-treated group. Furthermore, it is surprising that in animal models with myeloma bone disease, the bone mass was higher in CKI treatment group than control. Conclusions: CKI inhibits MM cells through the MYC/TERT signaling pathway and improve the quality of life of MM mouse. Our findings provide preclinical evidence to show that CKI could be a promising candidate in human MM therapy. Disclosures No relevant conflicts of interest to declare.


2019 ◽  
Author(s):  
Ruixin Wang ◽  
Dongni Wang ◽  
Dekai Kang ◽  
Xusen Guo ◽  
Chong Guo ◽  
...  

BACKGROUND In vitro human cell line models have been widely used for biomedical research to predict clinical response, identify novel mechanisms and drug response. However, one-fifth to one-third of cell lines have been cross-contaminated, which can seriously result in invalidated experimental results, unusable therapeutic products and waste of research funding. Cell line misidentification and cross-contamination may occur at any time, but authenticating cell lines is infrequent performed because the recommended genetic approaches are usually require extensive expertise and may take a few days. Conversely, the observation of live-cell morphology is a direct and real-time technique. OBJECTIVE The purpose of this study was to construct a novel computer vision technology based on deep convolutional neural networks (CNN) for “cell face” recognition. This was aimed to improve cell identification efficiency and reduce the occurrence of cell-line cross contamination. METHODS Unstained optical microscopy images of cell lines were obtained for model training (about 334 thousand patch images), and testing (about 153 thousand patch images). The AI system first trained to recognize the pure cell morphology. In order to find the most appropriate CNN model,we explored the key image features in cell morphology classification tasks using the classical CNN model-Alexnet. After that, a preferred fine-grained recognition model BCNN was used for the cell type identification (seven classifications). Next, we simulated the situation of cell cross-contamination and mixed the cells in pairs at different ratios. The detection of the cross-contamination was divided into two levels, whether the cells are mixed and what the contaminating cell is. The specificity, sensitivity, and accuracy of the model were tested separately by external validation. Finally, the segmentation model DialedNet was used to present the classification results at the single cell level. RESULTS The cell texture and density were the influencing factors that can be better recognized by the bilinear convolutional neural network (BCNN) comparing to AlexNet. The BCNN achieved 99.5% accuracy in identifying seven pure cell lines and 86.3% accuracy for detecting cross-contamination (mixing two of the seven cell lines). DilatedNet was applied to the semantic segment for analyzing in single-cell level and achieved an accuracy of 98.2%. CONCLUSIONS This study successfully demonstrated that cell lines can be morphologically identified using deep learning models. Only light-microscopy images and no reagents are required, enabling most labs to routinely perform cell identification tests.


RSC Advances ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 5384-5392
Author(s):  
Abd Alaziz Abu Quba ◽  
Gabriele E. Schaumann ◽  
Mariam Karagulyan ◽  
Doerte Diehl

Setup for a reliable cell-mineral interaction at the single-cell level, (a) study of the mineral by a sharp tip, (b) study of the bacterial modified probe by a characterizer, (c) cell-mineral interaction, (d) subsequent check of the modified probe.


2021 ◽  
Vol 22 (11) ◽  
pp. 5988
Author(s):  
Hyun Kyu Kim ◽  
Tae Won Ha ◽  
Man Ryul Lee

Cells are the basic units of all organisms and are involved in all vital activities, such as proliferation, differentiation, senescence, and apoptosis. A human body consists of more than 30 trillion cells generated through repeated division and differentiation from a single-cell fertilized egg in a highly organized programmatic fashion. Since the recent formation of the Human Cell Atlas consortium, establishing the Human Cell Atlas at the single-cell level has been an ongoing activity with the goal of understanding the mechanisms underlying diseases and vital cellular activities at the level of the single cell. In particular, transcriptome analysis of embryonic stem cells at the single-cell level is of great importance, as these cells are responsible for determining cell fate. Here, we review single-cell analysis techniques that have been actively used in recent years, introduce the single-cell analysis studies currently in progress in pluripotent stem cells and reprogramming, and forecast future studies.


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