Peptide-PAINT Enables Investigation of Endogenous Talin with Molecular Scale Resolution in Cells and Tissues.

Talin is a cell adhesion molecule that is indispensable for the development and function of multicellular organisms. Despite its central role for many cell biological processes, suitable methods to investigate the nanoscale organization of talin in its native environment are missing. Here, we overcome this limitation by combining single-molecule resolved PAINT (points accumulation in nanoscale topography) imaging with the IRIS (image reconstruction by integrating exchangeable single-molecule localization) approach, enabling the quantitative analysis of genetically unmodified talin molecules in cells. We demonstrate that a previously reported peptide can be utilized to specifically label the two major talin isoforms expressed in mammalian tissues with a localization precision of <10 nm. Our experiments show that the methodology performs equally well as state-of-the-art single-molecule localization techniques, and the first applications reveal a thus far undescribed cell adhesion structure in differentiating stem cells. Furthermore, we demonstrate the applicability of this peptide-PAINT technique to mouse tissues paving the way to single-protein imaging of endogenous talin proteins under physiologically relevant conditions.

Molecular Force Measurement with Tension Sensors.

The ability of cells to generate mechanical forces, but also to sense, adapt to, and respond to mechanical signals, is crucial for many developmental, postnatal homeostatic, and pathophysiological processes. However, the molecular mechanisms underlying cellular mechanotransduction have remained elusive for many decades, as techniques to visualize and quantify molecular forces across individual proteins in cells were missing. The development of genetically encoded molecular tension sensors now allows the quantification of piconewton-scale forces that act upon distinct molecules in living cells and even whole organisms. In this review, we discuss the physical principles, advantages, and limitations of this increasingly popular method. By highlighting current examples from the literature, we demonstrate how molecular tension sensors can be utilized to obtain access to previously unappreciated biophysical parameters that define the propagation of mechanical forces on molecular scales. We discuss how the methodology can be further developed and provide a perspective on how the technique could be applied to uncover entirely novel aspects of mechanobiology in the future.

Quantitative single-protein imaging reveals molecular complex formation of integrin, talin, and kindlin during cell adhesion.

Single-molecule localization microscopy (SMLM) enabling the investigation of individual proteins on molecular scales has revolutionized how biological processes are analysed in cells. However, a major limitation of imaging techniques reaching single-protein resolution is the incomplete and often unknown labeling and detection efficiency of the utilized molecular probes. As a result, fundamental processes such as complex formation of distinct molecular species cannot be reliably quantified. Here, we establish a super-resolution microscopy framework, called quantitative single-molecule colocalization analysis (qSMCL), which permits the identification of absolute molecular quantities and thus the investigation of molecular-scale processes inside cells. The method combines multiplexed single-protein resolution imaging, automated cluster detection, in silico data simulation procedures, and widely applicable experimental controls to determine absolute fractions and spatial coordinates of interacting species on a true molecular level, even in highly crowded subcellular structures. The first application of this framework allowed the identification of a long-sought ternary adhesion complex-consisting of talin, kindlin and active ß1-integrin-that specifically forms in cell-matrix adhesion sites. Together, the experiments demonstrate that qSMCL allows an absolute quantification of multiplexed SMLM data and thus should be useful for investigating molecular mechanisms underlying numerous processes in cells.