Our next interviewee for our ‘Young PI’ series is Dr Velia Siciliano, Principal Investigator at the Italian Institute of Technology and Honorary Research Fellow at the Department of Medicine of Imperial College London.
Stefano Donati: In your work you have focused on engineered circuits in mammalian cells in different ways, either using miRNAs and proteases-associated cascades. What would you say are the biggest challenges in this field?
Velia Siciliano: The biggest challenge is still in developing circuits whose behavior is really predictable. The beauty and importance of mammalian cells is that they are very robust to external perturbations! This is what makes us very robust machines adapting to different environments. So, the idea that we can simply modify cells is not that straight-forward: it requires a lot of build and test re-iterations. In our work, we tend to use a lot of mathematical models which are useful to predict and understand how these circuits are going to work.
Another important challenge is to understand how much we can overload mammalian cells when using synthetic circuits. I refer for example to Francesca Ceroni’s work on burden of synthetic circuits in bacteria. Something very similar happens also in mammalian cells. I think we should take a step back and first understand how to optimize synthetic circuits such that we do not impair its physiology.
Another important thing is trying to connect the expression of our circuits to some physiological or pathological events, leading to possible applications of our circuits.
Stefano: So what are the most promising applications of using such tools in mammalian cells?
Velia: There are two types of applications for mammalian synthetic biology: the first one is to create orthogonal synthetic pathways that do not have crosstalk with the endogenous pathways. This can allow to better understand biological mechanisms. A second kind of application is to give cells novel functions. For example, in the CAR T-cell approach, T-cells are engineered to express unnatural receptors to target specifically leukemia cells.
My specific interest lies in the design of new therapies. We propose to design “smart interfaces”, which sense disease inputs and express some therapeutic output.
Stefano: Can you tell us a bit about your career? What did you study?
Velia: I am from Naples and I studied medical biotechnology. Soon after my MSc I started my PhD at TIGEM (Telethon Institute of Genetics and Medicine) in collaboration with the Open University. My PhD supervisor (Prof. Di Bernardo) was an electronic engineer and he introduced me for the first time to synthetic biology. I was very fascinated by the field and the idea of working together with engineers, mathematicians and computational biologists. I started to work on mammalian synthetic biology studying different network motifs which are recurrent in biological pathways: at that point my research was about building to understand. My PhD was a first key moment: my PhD supervisor was pushing us to attend conferences, be very outward looking and increase our ambition.
Stefano: How did you choose your PostDoc?
Velia: In a conference I met Ron Weiss (MIT), and I was very motivated to join his lab, as I was very interested in what they were doing. I refused other offers until I could move there. I spent 3 years in his lab. The MIT is one of the best possible environment, where everything moves very fast around you and this shaped a lot my mindset about becoming a PI. It’s not that you are born with the idea of becoming a PI! It’s a stepwise process to realize this.
Stefano: So how did the transition actually happen?
Velia: I met Prof. Paul Freemont from Imperial College during a summer school. He mentioned that at Imperial there are fellowship to become an independent young investigator, and encouraged me to apply. I won the fellowship and eventually moved there for two years as an independent group leader. I then was offered a tenure track position at the Italian Institute for Technology (IIT), and decided to move back to Italy, first briefly in Genova and then relocating at the IIT center in Naples. I am lucky to have a good network of collaborators: I still collaborate with Ron Weiss, with people at the Imperial College, ETH and immunology labs in Italy.
Stefano: What is the Italian Institute for Technology?
Velia: The idea of the IIT is to develop technologies that can help society. There are different research lines, from robotics to life sciences, biomaterials, computational biology, nano-medicine.
Stefano: What is the state of Synthetic Biology in Italy? Is it that this kind of research is not pursued, or more that people are calling it differently?
Velia: The Italian Synthetic Biology scene is quite heterogenous and dispersed. Synthetic Biology can be declined in many different ways: the first approaches of gene therapy or immunotherapy which rely on expression of chimeric receptors on the surface of T cells are also approaches of Synthetic Biology. I think there is still no conception of Synthetic Biology as a branch of research in Italy: many researchers use a Synthetic Biology approaches but they don’t know it.
Stefano: What are the key skills to train to be a successful PI?
Velia: The one thing you really need is to be resilient! It is not easy to be a scientist and there are many frustrating moments. Often, we do not appreciate that in every failure we also learn a lot of useful skills!
Learning to manage your time effectively is a key skill.
Another thing that helped me a lot to was to keep my research interest broad, without focusing on just one thing. I always kept a backup strategy for every project I pursued. Moreover, in a long-term perspective it can be very helpful to have some side projects. This is important because it can allow you to move from a project that you were asked to develop, to a project you are actually proposing to develop. This should happen when you work as a PostDoc, and this is when you start realizing that you are becoming independent.
Next advice: be open-minded. Even the weirdest ideas can be groundbreaking and feasible.
Building collaborations and networking are also very important things: the idea that we can do everything on our own is outdated: you work much better when you can discuss with other people. Science would be much better if we would trust and respect each other more.
Stefano: So to sum it up, be resilient, organized, have always a plan B up your sleeve, be open-minded and keep in touch with other scientists. Do you want to add something else?
Velia: Yes! I was recently awarded with the ERC starting grant! If you are interested in my work and would like to move to join my lab, there will be opening soon, and we are already looking for a PostDoc! Stay tuned!
Velia Siciliano received her Bachelor degree in Health Biotechnology and her Master Degree in Medical Biotechnology from the University of Naples Federico II. In 2012 she obtained her PhD in Human Genetics from Open University UK in a joint program with the Telethon Institute of Genetics and Medicine Naples (TIGEM), and she then moved to Massachusetts Institute of Technology where she worked as postdoctoral fellow at the Synthetic Biology Center and Biological Engineering Department. She was awarded with the Junior Research Fellowship from Imperial College London where she moved in 2015 to conduct her independent research in the Department of Medicine. In 2017 she won the Proof of Concept grant from SynbiCITE London and she is a partner of a H2020 consortium grant led by Prof. diBernardo (TIGEM, Naples). Velia joined IIT in September 2017 where she leads the System and Synthetic Biology lab for biomedicine. She is also Honorary Research Fellow at the Department of Medicine of Imperial College London. In 2018 Velia won the MIT Young Innovator Award and the Galileo Galilei Award. She was also selected as one of the 150 "Unstoppable Women" for Science and Innovation. In 2019 Velia was selected as member of the Global Young Academy. Velia is a reviewer for a number of scientific journals, including Nature Communication, Nucleic Acid Research, BMC Systems Biology, etc.