Fluctuation-Based Super-Resolution Traction Force Microscopy

Abstract

Cellular mechanics play a crucial role in tissue morphogenesis and homeostasis and are often misregulated in disease. Traction force microscopy (TFM) is one of the key methods that has enabled researchers to study fundamental aspects of mechanobiology; however, the power of TFM is limited by poor resolution and low throughput. Here, we propose a simplified protocol and imaging strategy, relying on super-resolution microscopy enabled by fluorophore fluctuation analysis, to enhance the output of TFM, by increasing both bead density as well as the accuracy of bead tracking in TFM gels. Our analysis pipeline can be used on either camera-based confocal or widefield microscopes and is fully compatible with available TFM analysis software. In addition, we demonstrate that our workflow can be used to gain biologically relevant information and is suitable for longterm live measurement of traction forces even in light-sensitive cells. Finally, we propose that our strategy could be used to considerably simplify the implementation of TFM screens. Our streamlined protocol can be performed with minimal hardware and software investment, and has the potential to standardize high-resolution TFM. Fluctuation-based super-resolution microscopy | SACD, LiveSRRF | Traction force microscopy | Live imaging | Mechanobiology Correspondence: guillaume.jacquemet@abo.fi or johanna.ivaska@utu.fi Stubb et al. | bioRχiv |

ZeroCostDL4Mic: an open platform to use Deep-Learning in Microscopy

“…U-251 glioma cells were grown in DMEM/F-12 (Dulbecco’s Modified Eagle’s Medium/Nutrient Mixture F-12; Life Technologies, 10565-018) supplemented with 10 % fetal bovine serum (FCS) (Biowest, S1860). U-251 glioma cells expressing endogenously tagged paxillin-GFP were generated using CRISPR / Cas9 and were described previously (1). MCF10 DCIS.COM (DCIS.COM) lifeact-RFP cells were cultured in a 1:1 mix of DMEM (Sigma-Aldrich) and F12 (Sigma-Aldrich) supplemented with 5% horse serum (16050-122; GIBCO BRL), 20 ng/ml human EGF (E9644; Sigma-Aldrich), 0.5 mg/ml hydrocortisone (H0888-1G; Sigma-Aldrich), 100 ng/ml cholera toxin (C8052-1MG; Sigma-Aldrich), 10 μg/ml insulin (I9278-5ML; Sigma-Aldrich), and 1% (vol/vol) penicillin/streptomycin (P0781-100ML; Sigma-Aldrich).…”

“…Therefore, no specific training datasets are required, only noisy images and even one noisy image is sufficient to train the network. The 2D dataset provided with our notebooks was generated by plating U-251 glioma cells expressing endogenously tagged paxillin-GFP on fibronectin-coated poly-acrylamide gels (stiffness 9.6 kPa) (1). Cells were then recorded live using a spinning disk confocal microscope equipped with a long working distance 63x (NA 1.15 water, LD C-Apochromat) objective (Zeiss).…”