A classic problem in microbiology is that bacteria display two types of growth behavior when cultured on a mixture of two carbon sources: in certain mixtures the bacteria consume the two carbon sources sequentially (diauxie) and in other mixtures the bacteria consume both sources simultaneously (co-utilization). The search for the molecular mechanism of diauxie led to the discovery of the lac operon and gene regulation in general. However, questions remain as why microbes would bother to have different strategies of taking up nutrients and in the case of co-utilization what determines the partition and distribution of carbon sources in the cell. Here we show that diauxie versus co-utilization can be understood from the topological features of the metabolic network. A model of optimal allocation of protein resources quantitatively explains why and how the cell makes the choice when facing multiple carbon sources. When two carbon sources are being co-utilized, the model predicts…

Modeling large multi-molecular assemblies at atomic resolution is a key task in elucidating cell function.   Since for most assemblies there is no single experimental method, that can deliver atomic resolution structures of such large molecules, hybrid methods, which integrate data from various experimental modalities, are being developed for this task. We have developed an integrative method, which combines atomic resolution models of individual assembly components with an intermediate resolution electron microscopy map of the full assembly.  It can also naturally accommodate available chemical cross link (Xlink) data. From a purely geometric viewpoint, this task can be viewed as an assembly of a three dimensional large multiple piece puzzle, where we have relatively accurate models of the individual subcomponents, and a rough, low resolution scan of the full puzzle volume. This is joint work with my M.Sc. students Dan Cohen and Naama Amir.

The three-dimensional (3D) organization of chromatin within the cell nucleus is crucial for regulating genome functionality. The knowledge of its role has greatly advanced thanks to the development of novel imaging and molecular biology techniques. In particular, chromosome conformation capture (3C) and its high-throughput derivatives, based on next generation sequencing, allow investigating chromatin architecture on a genome-wide scale. My research group is focused on the use of 3D chromatin organization data to gain mechanistic insights into transcription and epigenetic regulation at different levels. On a large scale, we investigate mechanisms for the coordinated regulation of large chromatin domains in physiological and disease conditions. These involve, for example, the organization of the genome in distinct structural domains, such as Topologically Associating Domains (TADs), or Lamina Associated Domains (LADs). On a finer scale, instead, we study distal regulatory elements (enhancers) and their epigenetic or genetic alterations in genetics diseases and cancer. In this context,…

The binding of transcription factors (TFs) to their specific motifs in genomic regulatory regions is commonly studied in isolation. However, in order to elucidate the mechanisms of transcriptional regulation, it is essential to determine which TFs bind DNA cooperatively as dimers and to infer the precise nature of these interactions. We will discuss an algorithm for predicting cell-type–specific TF–TF dimerization on DNA on a large scale, using DNase I hypersensitivity cell-type-specific data

Computational approaches are nowadays a full, self-standing branch of chemistry, both for their quantum-based (“ab initio”) accuracy, and for its multiscale extent. In prebiotic chemistry, however, due to the instrinsic complexity of the chemical problems, ab initio atomistic simulations have so far had a limited impact, with the exception of a few relevant studies, including the elucidation of the chemical interactions between biomolecules with surfaces, such as ice and minerals, or the simulation of the effect of the pressure/temperature shock waves induced by meteorite impacts in the early Earth. Surprisingly, even the celebrated Miller experiments, which historically reported on the spontaneous formation of amino-acids from a mixture of simple molecules reacting under an electric discharge, have never been studied at the quantum atomistic level. Here we set the general problem of chemical networks within new topology-based concepts, using search algorithms and social network data analysis. This allows a very efficient definition of reaction coordinates…

In our group at The Institute of Cancer Research, we use massive parallel sequencing to study genomic features of malignant tumours. Among other things, we work on detection of tumour DNA in liquid biopsies, analysis of patients’ human gut microbiomes and identification of tumour neoantigens for cancer immunotherapies. In this talk, I will first provide an introduction to cancer genomics and then I will focus on our in silico studies of cancer resistance mutations’ immunogenicity in the context of cancer vaccines.

The genetic component of the molecular phenotypes has been studied extensively in the last decade. Multiple results show that the donor identity accounts for a significant part of transcriptome variation and identified thousands of cis expression Quantitative Trait Loci (eQTLs). While gene expression is informative for understanding mechanisms of gene regulation, most cellular phenotypes are occuring at the protein level and variation in transcript levels may not be reflected at the protein level and vice versa. Yet, the degree in which the proteome is affected is still poorly understood. To examine the proteome variation and its coordination with gene expression, we generated matched proteomic (TMT Mass Spectrometry), transcriptomic (RNA-seq) and genomic datasets for 202 iPSC lines derived from 151 different donors as part of the Human Induced Pluripotent Stem Cells Initiative (HipSci). Our data revealed significant effects of the donor identity on abundance variation across lines for more than 900 proteins and several protein…