Approximately 537 million people suffered from diabetes in 2021. This number is projected to be 643 million by 2030 and 783 million by 2045, and related healthcare costs may rise to 40% of the total healthcare budget in high incidence countries (Source: International Diabetes Federation). Despite these daunting numbers, our knowledge about the pathophysiology of the disease remains limited and many questions about the relation of the β-cell mass, β-cell function and the metabolism of different tissues remain unanswered, largely due to insufficient technology.
In our research we combine powerful techniques for optical 3D imaging with classic molecular biology approaches to study the mechanisms underlying diabetes. In particular, we are working with mesoscopic imaging platforms, in particular optical projection tomography (OPT) and light sheet fluorescence microscopy, to study how different pancreatic cell types are affected during development of diabetes. With these technologies, individual islets, or other cell volumes, and their spatial 3D coordinates can be derived in large cohorts of animals, informing about various aspects of pancreas biology ranging from normal pancreatic anatomy to e.g., b-cell: establishment and proliferation, destruction/reduction and preservation, immune cell infiltration, cellular/identity/maturity etc., difficult (or even impossible) to obtain by other existing technology (For review see Alanentalo et al., Frontiers in endocrinology, 2021). As an example of the added value of the “mesoscopic perspective” we could based on OPT data advocate for a new nomenclature for how the lobular compartments of the rodent pancreas should be designated.
By adaptations of our original OPT-protocols, we recently devised a method by which any volume of human (pancreatic) tissue can be studied in 3D with mm-resolution and with highly specific contrast (using principally any antibody targeted epitope of choice). The possibility to study the entire pancreas in all angles and through its entire depth (with known 3D coordinates for all labelled objects), provide a unique opportunity to identify features that would be extremely challenging to recognize using other techniques. We are currently investing several aspects of diabetes (T1D & T2D) disease aetiology using these techniques and to this end we have obtained a large collection of intact pancreata from diseased donors with various disease histories.
We are currently looking for a Post-doc to join our team. Please contact Ulf.Ahlgren@umu.se for further information.
Insulin producing islets of Langerhans in the human pancreas (red), visualized by OPT. The image illustrate an approach to visualise antibody labelled cells throughout the volume of the human pancreas (See Hahn et al., 2021 https://www.nature.com/articles/s42003-021-02589-x).
Our research is/was funded by: The Swedish Research Council, The Juvenile Diabetes Foundation, The Kempe Foundations, Umeå University, Diabetesfonden, NovoNordisk, The diabetes Wellness foundation, Barndiabetesfonden and the European Union.