Since a few months, the manuscript entitled “Multiplexed biochemical imaging reveals caspase activation patterns underlying single cell fate“, and authored by Maximilian W Fries, Kalina T Haas, Suzan Ber, John Saganty, Emma K Richardson, Ashok R Venkitaraman, Alessandro Esposito, is available as pre-print at the bioRxiv repository. It has started its journey through the peer-review process, but here I wished to explain to students and young scientists what happened behind the scenes as, I believe, can be instructive.
The inception of the idea | I am unsure if it will be evident from the manuscript, but this is the culmination of a huge effort that started more than a decade ago. I was about to leave the Cell Biophysics Group led by Prof. Fred Wouters after I completed my PhD, on a train from Goettingen to Bonn where my partner used to work, thinking: “What should I do next? … something that while capitalizing on my training can make my work distinct from my mentors and others? Where can I have the highest impact?” Moment that stuck in my memory.
I believe I read Santos et al. (2007) “Growth factor-induced MAPK network topology shapes Erk response determining PC-12 cell fate.” in that period, a paper that influenced me significantly. It made me thinking of cells as if they were computational machines, interpreting various inputs from the extra- and intra- cellular environment to trigger appropriate outputs, cell states or transition between cell states, i.e. cellular (fate) decisions. Everyone working with microscopy knows that cells treated equally often behave differently and, therefore, I started to formulate ideas around the following question: “How does a network of biochemical reactions encodes for cellular decisions? Why do genetically identical cells take a different decision faced by a similar stimulus?” Basic principles, the science I love the most, but questions worth answering also to obtain mechanistic insights, questions also quite relevant to disease.
As a matter of fact, it is of fundamental importance to understand how cells trigger pathological states or if differences in biochemical networks can be used as diagnostic markers for patient stratification or targeted for therapy, concepts that I started to work only later. Certainly, I thought back then, with my unique blend of physics, engineering, mathematics, molecular and cell biology I can do, in this area, what others might not be able to. Therefore, since 2007, my aim is to image not just a biochemical reaction, but biochemical networks within intact living cells, while they undertake decisions.
Finding the resources, the initial success | Perhaps other students start less naïvely than me, but soon I would discover that having a good idea (let’s suppose it is a good idea) and having the right skills is only a tiny part of the job. First, aiming to coordinate my work with that of my partner (now wife), I accepted a job offer at the University of Cambridge to work with Prof. Clemens Kaminski and Dr. Virgilio Lew to study one exciting but quite unrelated project. While working on the homeostasis of P. falciparum infected red blood cells, I set up collaborations and wrote an EPSRC fellowship which was funded. Therefore, in 2009, two years after my first idea, I got the funding to work on biochemical multiplexing. With this fellowship, I was able to refine my expertise in biochemical multiplexing, permitting me to build advanced technologies for fluorescence sensing such as confocal spectro-polarimetry and fast SPAD-based spectral FLIM. This EPSRC fellowship, together with my expertise and vision, and the benefit to have already established my name in the community thanks to the work I had done with and the support of Prof. Fred Wouters and Prof. Hans Gerritsen, were an excellent platform that permitted me to do the next jump and accepted a senior position at the MRC Cancer Unit.
Finding the resources, the struggle | Rather than focusing just on technology, I then broaden my research to a research program that would require theoretical developments, engineering of new pairs of fluorescent proteins to achieve multiplexing, coding and, of course, biological applications. I recognize that expanding my research before seizing the appropriate resources was a significant mistake or at least a huge risk. Working within Prof. Ashok Venkitaraman group, I started to write ambitious EU grants. Some of them would receive excellent feedback (14 out of 15 points, first or second not funded…) but fall short of being funded. Hans once told me that “at this level of competition and quality, often it is just noise that decides the final outcome“. Probably true, even funny if you knew we worked together on photon-statistic (‘noise’). But great feedback does not replace funds, and thus I wrote an ERC grant.
I did not get ERC funding but, once again, ERC is very competitive and I was not sufficiently experienced, thus no drama. However, I started to notice one big issue. Physicists would judge my physics not great physics, biologists would judge my biology not great biology. Some colleagues would find my objectives impossible to reach. This is what I have then discovered to be the challenge of doing multi-disciplinary research (well, technically is called trans-disciplinary research, but this is the topic for another post). When your proposal is both trivial and impossible, you might have an issue that is not necessarily related only on your science. One referee commented that “A number of groups have being trying to improve the technologies for many years and although some of them have an enormous experience they are not anywhere close to where he intends to be in five years“. Around the same time, a renown scientist commented on the description of my work “It is impossible”, but then added in a wonderfully supportive and very appreciated manner “but if there is someone that could do it, it is Alessandro” – well, if funding-proposals could be judged with the human touch that people have when speaking in person knowing and respecting each others work… I’ll cut an even longer story short, but with significantly less resources than I was asking and struggling to increase my funding, with the financial backing of Prof. Ashok Venkitaraman, we did everything we wanted to do in… five years!
The great technical success (NyxBits and NyxSense) | I wished to tell you a story of great success in a broader sense, but this has to be still written… if it will ever be. I did waste significant amount of time in looking for resources in what I found an amazingly inefficient system. However, from the end of my EPSRC fellowship since this year (~6 years), we have done a huge amount of work to realize what it was thought not to be possible:
- Molecular Biology. I wished to develop two platforms, one based on spectrally multiplexed time-resolved anisotropy (open for collaborations here!) and one for spectral FLIM to manage the cross-talk between multiple FRET pairs and making biochemical multiplexing possible. With the limited resources I had, and initial help from Bryn Hardwick, Meredith Roberts-Thomson and David Perera in Ashok’s lab, we kick-started the project. The mole of work started to overwhelm me. Occupied with grant writing, training in a new field, engineering, software development and mathematics, I could not push this forward as fast as I wished. A great help then arrived from Max Fries who did 6 months with me as master student. Once he left, I was short of resources again, with the FRET pairs misbehaving and exhibiting aggregation or spurious signals, we abandoned one of the two sensing platforms. Emma Richardson then joined me as a Research Assistant dedicated to cloning and testing FRET pairs and then Max came back to work with me for another four years as a PhD student. Committed and skilled, he tested tens and tens of FRET pairs. The work was a huge task, but a couple of paragraphs in the manuscript. We even have better pairs then we used in this work, all described in the Supporting Information. Indeed, under the pressure for publishing on high impact journals, I decided (probably anoher mistake of mine) to progress to applications, settling for what we recently baptized as NyxBits: mTagBFP, sREACh, mAmetrine, msCP576, mKeima and tdNirFP, so to focus on biological applications. NyxBits and NyxSense? Well, I have explained the choice of names elsewhere.
- Mathematics and software. There is something I could not really write in the manuscript so explicitly and it is appreciated only by the experts in the field. There is something I also find impossible to communicate to review panels. As a testimony to this, I report here a comment I was once relayed to, something like: “Why do we need to offer him a carreer, once he has built the instruments we really need one person just clicking a button, no?” (I am sure I remember it much worst then it was. May be). The integration of technologies is so new and challenging, that we had to formulate new theoretical frameworks and write all new software, including how to acquire data, data format, and analysis. Also, some aspects of our work are difficult to appreciate. Let me tell you another small event that would push me in a particular direction. I really enjoy the conference Focus on Microscopy, even when criticized. Presenting new ideas, a colleague – respectfully – questioned the possibility for multiplexed imaging to be capable to measure several FRET pairs at the same time. This stimulated me to resume studying the Fisher information content in biochemical imaging. What is the biochemical resolution in microscopy? Can we enhance it? After years of thinking about this topic, in 2013 I cracked the problem, and published the mathematics in PLOS ONE where I formulate what I defined ‘the photon-partitioning theorem’. Then, with the increasing financial backing of my Director, Kalina Haas joined my growing team. Kalina implemented unmixing algorithms and complex data analysis pipelines. Max and Kalina then became my dream-team to progress the project to the shape you can read today.
- Technology. I mentioned some earlier technology platform that were designed for biochemical multiplexing. In my recent and first release of manuscripts on bioRxiv, we also published a full implementation of Hyper-Dimensional Imaging Microscopy (HDIM) with which we backed the photon-partitioning theorem with experimental evidence. We have done much more in that direction, but when we started biological applications, we realized the need for faster FLIM systems. Uncapable to wait for commercial solutions or to gain the benefits of other prototypes we had developed, I decided to build my own fast multiplexed electronics. This development was fostered by a negative criticism of a referee. During a PNAS submission of our spectral FLIM system, a referee mentioned we could do the same utilizing Hybrid PMTs. I disagreed, as achieving 64 channel spectral FLIM with the capability to run at hundreds of millions of photon-counts per second is all-together a very different application; however, there is merit in most referees’ criticisms, even the most negative ones. Only then I have realized PMT are now very fast and the bottleneck was just the electronics. Therefore, I got in touch with Surface Concept who supported me wonderfully and sold me one of their multi-hit TDC platforms. After several months of software development, we were then capable to run FLIM measurements with the quality of TCSPC and the speed of FD-FLIM. As usual, I presented this work at FoM where it was greatly received by colleagues and companies, but we did not publish the imaging platform as we were fully committed to pursue biological applications.
- The biology. The bottleneck of our experiments was and still is data analysis and, with tens of experiments, thousands of biochemical traces to be painfully manually curated, we moved ahead very slowly, but working hardly. Mostly Max, Kalina and myself, suffered years of hard work, the occasional worry when something stopped working, and the excitement of seeing things that others could not see, for the first time. In this manuscript, we reveal the extent of non-genetic heterogeneity that biochemical networks can exhibit and that eventually result into difference cellular decisions. Here, we focused on multiplexing simple biosensors for caspases as we aimed to de-risk and very ambitious project. We also decided to work with HeLa cells, again for the same reason. Despite the simplicity of the model system under study, we realized how complex and heterogeneous the response of biochemical pathways is, the cross-talk between enzymes, signaling pathways and cellular metabolism. All of this is, for me, fascinating and it shows that whenever we do ensemble measurements, we really see only the behavior of the average cell. It is then important to understand that the ‘average cell’, most of the times, does not really exist. If we are lucky, the bulk of the population responds with one phenotype and the measured ‘average cell’ will indeed represent the ‘most frequent cell’. However, in other instances when there are significant populations behaving in distinct ways, we would not just miss important information. The model inferred from the ‘average cell’ would be simply the wrong model of a non-existing cell. This is why it would be important to know, for any assay, if the sample behave synchronously with a stimulus and homogeneously. In this sense, single cell biochemistry, could bring not just an additional layer of information, but inform us if what the observations we obtain on a given model system with ensemble measurements can be reliable.
Enduring the struggle | I hope you did not mind I spoke so positvly about my own work. If you know me, you also know I am not so self-centered. However, I wished to let the younger scientists to know what there might be between a ‘good idea’ and its realization, passing through frequent failures and some success. Probably, one of the most precious quality of a scientist is resilience. We need thick skin to confront the constant failures that lead us to discoveries, the constant struggles in getting resources and eventually publishing good work in a highly competitive environment. Turning a negative event in something negative is part of this process. Understanding why one experiment did not work enables us to make troubleshooting, why an experiments falsified our hypothesis to build new and better models, why funding was not awarded or a manuscript was not published how we can improve our scientific proposals and reporting. Of course this is easier said than done.
The work we presented in bioRxiv is not the end of the story. The work, wonderfully-received in conferences, is still not peer-reviewed. Will colleagues appreciate and understand the vision of our work, its possible impact and the mole of work we had to do? Were we able to communicate properly? And even if we did it, we still have a long way in front of us. My dream is to establish a single cell systems biology of cell fate. A huge amount of work, from maths to biology, from biotechnology to physics, all still needed to be able to understand why cells do what they do, how physiological states are maintained and how pathological states emerge.