Welcome

The Biophysics and Biophotonics Group is based at the Department of Physics at Umeå University and is led by Professor Magnus Andersson, who also serves as Head of the Department. Our research focuses on developing and applying advanced optical, biophysical, and computational methods to investigate biological systems, from single molecules and cells to complex microbial communities.

For more than two decades, we have pioneered the development of optical tweezers for micromanipulation, force spectroscopy, and Raman spectroscopy. We combine these experimental approaches with advanced image analysis, machine learning, and tracking algorithms to gain new insights into biological processes and organism behavior.

In addition to optical techniques, we develop innovative microfluidic platforms enabled by 3D-printing technologies, advanced imaging methods, and biosensors for the detection of foodborne pathogens. Our interdisciplinary research spans physics, biology, chemistry, medicine, and engineering, and is strengthened by close collaborations with both academic partners and industry.

The group is an active member of the Umeå Centre for Microbial Research (UCMR) and IceLab, contributing to collaborative research at the interface of biology, physics, and data science.

We welcome inquiries from students, postdoctoral researchers, industrial partners, and academic collaborators. If you are interested in a research project, collaboration, or simply want to learn more about our work, we would be delighted to hear from you.

Using optical tweezers, we characterize the biomechanical properties of bacterial adhesion pili to better understand how pathogenic bacteria are able to stick to host surfaces. So far we have assessed typical uropathogenic-related pili such as; type 1, P, S1, S2, F1C and enterotoxic, CFA/I, CS2, CS20. Read our latest PNAS 2021 paper here, the latest Nature 2022 paper here, and the latest Nature Communication 2023 paper here.

We are developing new methods for creating flow devices in silicone rubber by using 3D printing techniques. Here we demonstrate the capability of our method by recreating the cerebral vascular network as a patient-specific phantom model. This technology can help advance research in the field of e.g. neurological disorders by allowing invasive measurement techniques not previously possible when working on patients. This work is explained in-depth in this paper.

Analysis of numerous filamentous structures in an image is often limited by the ability of algorithms to accurately segment complex structures or structures within a dense population. To overcome these issues we present DSeg; an image analysis program designed to process time-series image data, as well as single images, to segment filamentous structures. DSeg includes automatic segmentation, tools for analysis, and drift correction, and outputs statistical data such as persistence length, growth rate, and growth direction. The program is available here: Sourceforge.