Understanding tissue migration

We have an exciting new bioRxiv story that just went live! This one takes a computational immunology approach to understanding tissue-resident lymphocytes. The story highlights the extra value mathematical modelling can bring to biology.

It starts with a large multi-tissue multi-timepoint parabiosis experiment we ran to understand tissue Tregs. Václav Gergelits, lead author on the study, saw greater potential in this dataset to understand the kinetics of lymphocyte migration broadly.

We extracted turnover data for CD4, CD8, Treg, B cells and NK cells from 17 tissue sources, and generated a sophisticated model of migration, activation and death for each lineage and tissue. The Markov chain modelling found high-confidence solutions that matched the empirical data beautifully.

This tells us a probabilistic model and three distinct states (resting/activated/resident) are sufficient to recapitulate the complex migratory and tissue-residency behaviour of these cells. The cell states change probabilities, but the behaviour is still *probabilistic*.

This means lymphocytes do not have a residency "clock". We can measure the average dwell times for resident cells, but if this average residency time is 3 weeks, it does not mean cells have a 3-week timer. It means the cells have a daily probability of leaving that gives a 3 week average. The dice roll comes up earlier for some cells than for others, within those cells being intrinsically different. Like radioactive decay of atoms, it is just probability - there is nothing intrinsically different about the uranium atoms that decay after a week vs those that decay after a million years, they just had different rolls of the dice.

This approach can explain much of the variation in cell fate without needing to invoke cellular heterogeneity! Two identical cells can have highly divergent outcomes simply because of probability, without different underlying biology. In fact, we can create thousands of identical "digital cells", model them with these simple rules, and we get the empirically-observed range of dwell-times. There is no need to invoke TCR clonality or the like - it is simply an emergent property of cells with probabilistic kinetics!

A great example of applied mathematics informing biology!

Take a read of the pre-print here.

Understanding vaccination in transplant patients

We have a new systems vaccinology paper out at npj Vaccines!

The study tackles the problematic question of why transplant patients responded so poorly to the COVID vaccine. While most people had great antibodies from a single dose, only half of transplant patients have responded even after three!

We took blood from 20 healthy, 31 lung transplant and 59 kidney transplant patients prior to vaccination, and profiled 444 immunological parameters, to get a comprehensive systems immunology profile. We then followed who did and didn't respond to the vaccine, to find the immunological associates.

First up, there are clinical effects: Vaccine response was especially poor soon after transplantation, and in patients on immunosuppressive cocktails, especially those including MMF. Even taking this into account, there were immunological drivers associated with poor response.

As you might predict, the patients that responded best were those with an immune profile that had returned closer to normal post-transplantation. In fact, you could predict vaccine response with 93% accuracy just based on 10 immune parameters.

 

Oddly though, some patients were able to hobble together a poor but detectable response after two shots. These patients didn't have a more normal immune profile, and had quite unusual relationships between immune populations, suggesting that they had put together a poor-but-functional "kludge".

This study was a joint initiative from our lab, Arnaud Marchant's lab at at ULB and Stephanie Humblet-Baron's lab at KU Leuven. 

Huge thanks to all team members, especially Nicolas Gemander, Julika Neumann, Rafael Veiga and Isabelle Etienne for their leadership roles.

Biggest thanks of all to the patients who volunteered for the study!

Read the full paper here

Lab punting

ALBA-IBRO Diversity podcast

The ALBA Network has a great program on enhancing diversity in neurosciences, including some fascinating podcasts hosted by The Lonely Pipette. I was honoured to be able to take part in the latest episode, together with Denise Fitzgerald, Dorieke Grijseels and Angeline Dukes.

Take a listen for a great discussion on how an inclusive working environment is the true fuel of a productive research team. We talk team dynamics, lab values, and inclusive leadership, as well as practice advise on how and when to incorporate positive research culture practices into your science!

Mothers in Science

My interview with Mothers in Science is now out!

PRIDE: Challenges, Champions and Change

Creating settings on the Aurora

From the talented Oliver Burton:

Athenaeum Club

A short talk on diversity in the immune system that I gave at the Athenaeum Club. 

As was noted by the Club members, there is a striking parallel with the value of diversity in ideas: education and exposure to multiple different approaches to intellectualism inoculate us from destructive ideologies such as fascism. To what degree is this pure coincidence? Could it be because the same asymmetry that exists in evolutionary speeds between humans and pathogens is also found in the evolutionary speeds of humans and ideas? Could the protective effect of diversity in shielding against pathogens and ideology both be the mathematical consequences of the laws of evolution?

International women in STEM day

Diversity in Science, KU Leuven

It was my pleasure to be at the "Diversity in Science" symposium today at KU Leuven! If you weren't able to attend, you missed a lot of great talks and round-table discussions, but here is a chance to see my own contribution to the event: