Work was conducted via 3 main workpackages (WP). WP1 and WP2 have been dedicated to tackle the two objectives namely “How are transcriptional and metabolic changes coordinated over time during macrophage activation?” and “How are metabolic pathways co-opted to control signal-induced chromatin and transcriptional changes?” while WP3 aimed at the assembly of a database for the laboratory/institute first, and for dissemination upon publication of relevant articles.
WP1 comprised the main experimental and computational steps to relate transcriptional and metabolic changes. I was able to:
(WP1.1) Record transcriptional and metabolomic changes in activated macrophages in time. High-throughput metabolomics was conducted during the secondment in the lab of Prof. Nico Mitro at UNIMI. Interaction with the Mitro’s lab allowed the fellow to learn novel techniques and identifying more that 200 metabolites constitutive or changing across. Data integration was performed using Constrained-base reconstruction and analysis methods (COBRA). This strategy was adopted as it produces human interpretable models which I was able to appreciate during the Metabolic Pathway Analysis 2019 conference (Riga University, Aug 2019) and the advanced COBRA course (Leiden University, Nov 2019). Modelling metabolic changes using this strategy allowed the fellow to both learn new modelling strategies and produce a metabolic model of macrophage activation with unprecedent levels of accuracy. (WP1.2) Identifying transcriptional regulators directly controlling metabolic enzymes and nutrient transporters encoded within the model assembled in WP1.1. (WP1.3) Selection of Irf8 transcriptional regulator from a panel of candidates identified from WP1.2. Perturbation experiment were performed to assess the role of Irf8 in the metabolic regulation of activated macrophages.
WP2 was also structure into sub-workpackages and aimed at evaluating the impact of metabolic pathways onto transcriptional changes. Although a full screen of a panel of metabolic inhibitors have been impossible to achieve due to the limited laboratory-time caused by the COVID19 emergency, I was able to team up with members of the Natoli’s lab and assess the effects of nitric oxide on gene transcription in activated macrophage.
WP3 was dedicated to the assembly of computational resources developed during the action. To make these resources immediately available to potential users, together with the supervisor the researcher decided to make the data available to all the institute and train biologist of the lab to use these resources. In particular the fellow assembled a general workflow, which was developed and used for the analysis of all genomic datasets related to the objective of the action, into a flexible and versatile pipeline so that more data-sets could be easily analysed. This produced a valuable resource that speeded up the analysis of datasets of more that 15 different projects allowing direct transfer of knowledge to the about 20 members of the lab. Supporting the efficacy of this strategy three members of the lab started independent learning of both basic and advanced computational languages (learning R and Python) and are actively mentored by the fellow.
Key achievements transversal to all workpackages included: (i) the submission of a seminal review on macrophage metabolism (submitted); (ii) training of a PhD student and a master student dedicating individual tasks and WPs; (iii) dissemination of the action at two international conferences, an advanced workshop and a lecture at the University of Bologna; (iv) engage in productive scientific collaborations expanding the researcher scientific community.
