Katharina Gaus

image - Kat Research

How do T cells make decisions?

We want to know how T cells initiate an immune response.

The decision of a T cell to activate or not to activate is determined by a complex signalling network within the cells. In this network, information is encoded not only in the components, but also by the frequency and duration of their interactions.

Studying how individual molecules within the cell control the actions of T cells is a fundamental single molecule problem.

The Gaus group is using new single molecule microscopes to understand the molecular basis of T cell decision-making, using strategies that combine mouse models with molecular biology, microscopy and mathematics (the 4 Ms).

Our research focuses on developing new super-resolution fluorescence microscopes and analysis routines to understand the decision-making processes of T cells. Single molecule data provide a unique ‘bottom up’ perspective to T cell signalling networks in intact and live cells. With new analysis strategies, we can map where signalling begins and how signals spread through the cells. We also use nanotechnology to control where and when T cells are stimulated.

T cells can distinguish between peptides derived from damaged and infected cells such as cancer cells, and benign ‘self’ peptides derived from healthy cells. The T cell receptor binds to peptides bound to major histocompatibility complexes, so-called peptide-MHC (pMHC) complexes, on the surface of antigen presenting cells. Despite the relatively weak T cell receptor-pMHC binding affinity, T cells can sense and respond to even a single antigenic peptide. This can lead to effector functions including secretion of potent mediators and killing of infected or cancerous cells. However, there are many more self peptides than foreign peptides presented to T cells and in this case, the correct decision for the T cell is to do nothing at all.

Despite extensive experimental and mathematical work, we do not understand how pMHC recognition by the T cell receptor initiates intracellular signalling and how the signalling network processes information ultimately leading to T cell fate decisions. This is a central question in peptide-mediated immunity and vaccine development and could help us to identify new avenues for drug design to combat autoimmune diseases and agents for cancer immunotherapy.

“With new single molecule tools, and our formidable team, the only limit to what we can achieve is our imagination,” says Kat.

About Katharina Gaus

Scientia Professor Katharina Gaus is an NHMRC Senior Research Fellow at the University of New South Wales and Head of the EMBL Australia Node in Single Molecule Science. She received her PhD from the University of Cambridge in 1999 and has led an independent research group since 2005. Her group investigates signal transduction processes with advanced fluorescence microscopy approaches. She was awarded the Young Investigator Award from the Australia and New Zealand Society for Cell and Developmental Biology(2010), the Gottschalk Medal from the Australian Academy of Science (2012) and the New South Wales Science and Engineering Award for Excellence in Biological Sciences (2013).


Rossy J. Owen DM, Williamson D, Yang Z, Gaus K. (2013) Conformational states of Lck regulate clustering in early T cell signalling. Nat Immunol, 14, 82-9.

Owen DM, Williamson D, Magenau A, Gaus K. (2012) Sub-resolution lipid domains exist in the plasma membrane and regulate protein diffusion and distribution. Nat Commun. 4;3:1256

Williamson D, Owen DM, Rossy J, Magenau A, Wehrmann M, Gooding JJ, Gaus K.(2011) Pre-existing clusters of the adaptor Lat do not participate in early T cell signaling events. Nat Immunol, 12, 655-662.

Gaus K, Chklovskaia E, Fazekas B, Jessup W, Harder T. (2005) Condensation of the plasma membrane at the site of T lymphocyte activation. J Cell Biol. 171. 121-131.

Gaus K, Gratton E, Kable EPW, Jones AS, Gelissen I, Kritharides L, Jessup W. (2003) Visualizing lipid structure and raft domains in living cells with 2-photon microscopy. Proc. Natl. Acad. Sci. U. S. A. 100, 15554-9.

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More Information

Career Highlights

  • NHMRC Senior Research Fellowship (2014)
  • NHMRC Achievement Award – Elisabeth Blackburn Fellowship (Biomedical) (2013)
  • NSW Science and Engineering Award for Excellence in Biological Sciences (2013)
  • Gottschalk Medal from the Australian Academy of Science (2012)
  • Wakefield Award for Higher Degree Research Supervision, The University of New South Wales (2012)


How does a T cell distinguish between peptides derived from “self” and “non-self”? T cells can sense and respond to a single copy of an antigenic peptide. Yet self-peptides presented to a T cell far out-number the antigenic peptides presented. So how does a T cell find the antigenic ‘needle in the haystack’? This question is particularly puzzling since adults have ~107 different T cell antigen receptors (TCR). Do structurally different receptors have a common basis for antigen recognition? What is the role of co-receptors in antigen discrimination? How does the membrane organisation influence T cell triggering and signal initiation? Can we engineer better receptors and give cytotoxic T cells better tools to fight cancers? We have begun to collect single molecule images of the TCR in which we can distinguish signalling (antigen-bound) from non-signalling (self-peptide-bound) receptors and, thus, map the TCR signalling efficiency. Only single molecule data can help us to understand the mechanisms that confer single molecule sensitivity to T cells.

How does a single antigen recognition event lead to T cell activation? Antigen binding triggers intracellular signalling cascades that involve 100s of proteins and 1000s of different interactions with time scales from seconds to hours. Somehow the signals initiated by the TCR must be amplified, verified and travel through the cellular architecture and arrive at the nucleus to result in gene transcription. Each step in the network is a single molecule problem–each step requires individual molecules to interact with each other, trigger a chemical reaction, and dissociate again.  We are developing new methods and analyses to decipher the language of signalling networks. Better understanding of the T cell signalling network will improve drug development to desensitise over-active T cells in autoimmune disease, or to stimulate under-active T cells for cancer immunotherapy. We provide a single molecule perspective of signalling networks to ultimately understand why and how information processing works so efficiently in T cells.

Which antigen recognition event leads to immunological memory? In addition to killing the target cells, an immune response also creates memory T cells. Immunological memory protects us throughout our lives. The basis for efficient vaccines is to understand the signalling events that lead to development of immunological memory. This would allow us to identify a way to activate T cells in a manner that promotes immunological memory. In addition to the nature of the antigen, the spatial arrangement of antigen presentation is likely to influence T cell receptor clustering, the quantity and quality of intracellular signals and thus the type of activation response that is achieved. In collaboration with Professor Justin Gooding from the Australian Centre of NanoMedicine (ACN) and the School of Chemistry at UNSW, we are developing nano- and micro-patterned surfaces to test this hypothesis. Spatial arrangements may link antigen recognition to intracellular signals and the formation of memory T cells.

How do mechanical forces influence T cell receptor signalling? In addition to sensing the chemical nature of antigens, T cells also respond to mechanical forces. Indeed, it has been proposed that the TCR is a mechanosensor. But how are chemical cues and mechanical forces integrated into the signalling network? We are developing and using a range of tools such as optical tweezers to both mechanical manipulate T cells and measure mechanical forces during T cell activation. This may be particularly important for the transition from migrating T cells to activated T cells. In collaboration with other SMS researchers, we aim to contribute to a conceptual framework of T cell activation that integrates chemical cues and mechanical forces.

Better images, better science, better health. To fully understand how T cells integrate the dynamic behaviour and molecular interactions on the nanometre scale into cellular outcomes, we also need to expand our toolbox. For example, we know relatively little about the 3-D architecture of the immunological synapse on the molecular scale, since many super-resolution images only generate 2-D images. This is important because membrane topography could influence how signalling proteins interact. We also need faster microscopes to track single molecules in live cells and microscopes that can perform single molecule imaging in tissues or even in a living animal. And of course, we need smarter analyses to visualise and interpret the data for a seamless transition from single molecule to systems immunology. We are looking for talented students and postdocs with a background in mathematics/image analysis, physics/optics and engineering/nanotechnology to help us build the next-generation of single molecule microscopes and analyses.

Lab Members

  • Thibault Tabarin (Postdoctoral fellow)
  • Enrico Klotzsch (ARC DECRA Fellow)
  • Sophie Pageon (Postdoctoral fellow)
  • Eldad Ben-Ishay (Postdoctoral fellow)
  • Philip Nicovich (Senior Scientist)
  • Jiegiong Lou (Postdoctoral fellow)
  • Daniel Nieves (Postdoctoral fellow)
  • Gabriela Segal (Postdoctoral fellow)
  • Melanie Chabaud (UNSW Vice-Chancellor Postdoctoral Fellow)
  • Joanna Kwiatek (PhD Student)
  • Mahdie Mollazade (PhD Student)
  • Yuanging Ma (PhD Student)
  • Yui Yamamoto (PhD Student)
  • Jason Tran (PhD Student)
  • Geva Hilzenrat (PhD Student)
  • Stephen Parker (PhD Student : joint and co-supervisor)
  • Xun Lu (PhD Student: joint and co-supervisor)
  • Yong (Jerry) Lu (PhD Student: joint and co-supervisor)
  • Quill Bowden (PhD Student : joint and co-supervisor)
  • Joyce Meiring (PhD Student : joint and co-supervisor)

Current funding sources

  • Australian Research Council
  • National Health and Medical Research Council
  • UNSW Australia
  • National Heart Foundation of Australia