Here is a list of my main recent projects. More details can be found in my publications.


Machine Learning the impact of Genomic Variants (PRISMR)

prismr.png prismr_val.png

Large genomic mutations (Structural Variants, SVs) can change the activity of genes by altering their contact network with enhancers. Linked to diseases such as congenital disorders or cancer, their effects remain difficult to predict. We developed PRISMR, a method combining Machine Learning and Polymer Physics, to model 3D chromatin folding. Trained on wild-type data, upon a mutation it successfully predicts how chromatin refolds, and enhancer-promoter contacts rewire. Validated across mutations in mice and human cells, PRISMR can highlight for single individuals the disease-causing potential of SVs genome-wide.

Selected references:
B.K. Kragesteen, et al., "Dynamic 3D chromatin architecture contributes to enhancer specificity and limb morphogenesis", Nature Genetics 50, 1463 (2018)
S. Bianco et al., "Polymer Physics Predicts the Effects of Structural Variants on Chromatin Architecture", Nature Genetics 50, 662 (2018)

Genome Architecture Mapping (GAM) technology

gam_mellon.png gam_data.png

Genome Architecture Mapping (GAM) is a ligation-free technology to map genome-wide chromosome interactions, beyond pairwise contacts, alternative to 3C based methods. Developed in collaboration with A. Pombo, its concept is simple: in slices extracted from the cell nucleus, spatially closer sites are found to co-segregate more frequently, and maths can dissect real contacts from random encounters. We find, for instance, that highly transcribed regions or super-enhancers tend to form more frequently three-way or multiple contacts.

Selected references:
R.A. Beagrie et al., "Complex multi-enhancer contacts captured by genome architecture mapping", Nature 543, 519 (2017)

Polymer physics of chromatin 3D organization (SBS model)

stringsbinders.jpg sbs_model_vs_hic.jpg

Polymer physics can help dissecting the molecular mechanisms underlying the complex 3D organisation of chromosomes and its functional role. Our Strings&Binders (SBS) model represents the scenario where binding molecules produce loops by bridging distal DNA sites, such as genes and their regulators. It was shown to explain with high accuracy Hi-C, GAM and FISH data, and the 3D structure of genomic loci across chromosomes and cell types. Its predictions on the effects of genomic rearrangements are confirmed by experiments, opening to new diagnostic tools for diseases linked to chromatin misfolding, such as congenital disorders and cancer.

Selected references:
M. Barbieri et al., "Active and poised promoter states drive folding of the extended HoxB locus in mouse embryonic stem cells" , Nature Struct. Mol. Bio. 24, 515 (2017)
A.M. Chiariello et al., "Polymer physics of chromosome large-scale 3D organisation", Nature Scientific Reports 6, 29775 (2016)
M. Barbieri et al., "Complexity of chromatin folding is captured by the strings and binders switch model" , PNAS 109, 16173 (2012)
M. Nicodemi et al., "Thermodynamic pathways to genome spatial organization in the cell nucleus" , Biophys.Jou. 96, 2168 (2009)

Higher-order chromatin structures (metaTADs)

metatads1.png metatads2.png

Genome-wide mapping of chromatin architecture by Hi-C and GAM in mouse and human cells reveals a hierarchical 3D organization of chromatin in higher-order domains (metaTADs) extending across chromosomal scales. The topology of MetaTAD reflects epigenomic features and is relatively conserved through differentiation, while its rewiring relates to changes in gene expression. The molecular mechanisms of metaTAD self-assembly are well explained by microphase separation within the SBS polymer model.

Selected references:
J. Fraser et al., "Hierarchical folding and reorganization of chromosomes are linked to transcriptional changes during cellular differentiation", Mol. Sys. Bio. 11, 852 (2015)
A. Pombo and M. Nicodemi, "Models of chromosome structure", Curr. Opin. Cell Bio. 28, 90 (2014)

Symmetry Breaking at X-Chromosome Inactivation

symbreak.png sbdiag.png

In the female mammalian embryo, X-Chromosome Inactivation is the vital process whereby each cell inactivates one, randomly selected X to equalise X products w.r.t. males. It is unknown how the X's undergo random, yet opposite fates during such a stochastic regulatory process. We proposed a possible physical explanation: a Symmetry Breaking mechanism whereby a set of interacting molecules self-assemble, by a phase separation mechanism, into a single X-linked 'blocking factor'. This scenario is supported by current experiments.

Selected references:
M. Nicodemi and A. Prisco, "A Symmetry Breaking Model for X Chromosome Inactivation", Phys. Rev. Lett. 98, 108104 (2007)
A. Scialdone and M. Nicodemi, "Mechanics and Dynamics of X-Chromosome Pairing at X Inactivation", PLoS Comp.Bio. 4, e1000244 (2008)
A. Scialdone et al., "Conformation Regulation of the X Chromosome Inactivation Center: A Model" , PLoS Comp. Bio. 7, e1002229 (2011)

Single-cell states in cell transition processes

singlecellmodel.png sc_profiles.png

Differentiation, reprogramming and disease transformations involve transitions of cells through distinct states. Yet, accessing the key properties of such single-cell states can be extremely challenging. We introduced a stochastic model where the dynamics of a cell is described as a sequence of transitions within a network of different states. By fitting genome-wide time-course data, the network of states and their profiles can be reconstructed. The state structure predicted by our approach, e.g., in MEF reprogramming to pluripotency or in CD4+ T-cell differentiation, was supported by independent single-cell experiments.

Selected references:
V. Proserpio, et al. "Single-cell analysis of CD4+ T-cell differentiation reveals three major cell states and progressive acceleration of proliferation", Genome Biology 17, 103 (2016)
J.W. Armond, et al. "A stochastic model dissects cell states in biological transition processes", Nature Scientific Reports 4, 3692 (2014)


Statistical Mechanics of Granular Media

scaling.jpg gmpd.jpg

Granular media are the second most dealt with material in human activities after water. As they are non-thermal systems (can have zero kinetic energy at room temperature), standard thermodynamics does not apply and a first principles theory for their description is still missing. We showed that they can be described via a generalized Statistical Mechanics approach via suitable ensemble averages (with an effective thermodynamic parameter, T), and derived the system phase diagram. That's confirmed by recent experiments and computer simulations.

Selected references:
M. Nicodemi, "Dynamical response functions in models of vibrated granular media", Phys. Rev. Lett. 82, 3734 (1999)
P. Richard, M. Nicodemi, R. Delannay, P. Ribiere, D. Bideau, "Slow relaxation and compaction of granular systems", Nature Materials 4, 121 (2005)
M. Pica Ciamarra, A. Coniglio, and M. Nicodemi,"Thermodynamics and Statistical Mechanics of Dense Granular Media", Phys. Rev. Lett. 97, 158001 (2006)

Rheology of Granular Media

img1.jpg, 3.8kB img1.jpg, 3.8kB

The rheology of non-thermal systems such as granular suspensions is currently focus of intense research for both fundamental science and practical applications. We explored the nature of the system flow diagram and found that its different regimes are separated by sharp, yet stochastic transitions: (a) disordered grain flow, (b) ordered grain flow and (c) grain jamming. We discovered that disordered flow has an Ostwald-de Waele-type power-law shear-stress constitutive relation, while a nearly solid plug appears in ordered flow.

Selected references:
D.S. Grebenkov, M. Pica Ciamarra, M. Nicodemi, A. Coniglio, "Flow, ordering, and jamming of sheared granular suspensions" , Phys. Rev. Lett. 100, 078001 (2008)
M. Pica Ciamarra, A. Coniglio, and M. Nicodemi,"Shear instabilities in granular mixtures", Phys. Rev. Lett. 94, 188001 (2005)