Type 1 diabetes (T1D) is caused by autoimmune destruction of the insulin-producing β cells in the pancreatic islets, which are essentially mini-organs embedded in exocrine tissue. CTLs are considered to have a predominant role in the autoimmune destruction underlying T1D. Visualization of CTL-mediated killing of β cells would provide new insight into the pathogenesis of T1D, but has been technically challenging to achieve. Here, we report our use of intravital 2-photon imaging in mice to visualize the dynamic behavior of a virally expanded, diabetogenic CTL population in the pancreas at cellular resolution. Following vascular arrest and extravasation, CTLs adopted a random motility pattern throughout the compact exocrine tissue and displayed unimpeded yet nonlinear migration between anatomically nearby islets. Upon antigen encounter within islets, a confined motility pattern was acquired that allowed the CTLs to scan the target cell surface. A minority of infiltrating CTLs subsequently arrested at the β cell junction, while duration of stable CTL–target cell contact was on the order of hours. Slow-rate killing occurred in the sustained local presence of substantial numbers of effector cells. Collectively, these data portray the kinetics of CTL homing to and between antigenic target sites as a stochastic process at the sub-organ level and argue against a dominant influence of chemotactic gradients.
Ken Coppieters, Natalie Amirian, Matthias von Herrath
This article was first published December 1, 2011. Usage data is cumulative from June 2015 through June 2016.
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.