Alternative splicing is a major gene expression regulatory process that increases the diversity of the transcriptome and the proteome encoded by a limited number of genes. For example, 95% of human genes generates different splicing variants encoding different protein isoforms. While tremendous progress has been made in elucidating the molecular mechanisms of alternative splicing regulation (relying on RNA biding proteins or splicing factors), two important related issues have been poorly addressed. The first issue concerns the biological information encoded by coregulated alternative exons (e.g., exons regulated by the same splicing factor). To date, it has been assumed that splicing factor-coregulated exons are diverse and unrelated in terms of coding information features. A second major issue concerns the relationship between coding and exonic splicing regulatory sequences. So far, it has been assumed that coding sequences can accommodate splicing regulatory sequences because of the redundancy of the genetic code (a same amino acid is…

Vaccination has saved more lives than any other medical procedure. But, some pathogens have evolved which have defied successful vaccination using the empirical paradigms pioneered by Pasteur and Jenner. I will describe how bringing together theoretical/computational approaches from statistical physics, with immunology is beginning to confront this challenge by developing some of the principles necessary for rational design of vaccines that may eliminate these scourges. One characteristic of many pathogens for which successful vaccines do not exist is that they present themselves in various guises. HIV is an extreme example because of its high mutability, and it continues to wreak havoc, especially in developing countries. I will describe how we developed models to translate data on HIV protein sequences to knowledge of the HIV fitness landscape, and tested the resulting predictions against in vitro and clinical data (with collaborators). Based on these studies, a therapeutic T cell-based vaccine was designed, which is…

The co-transcriptional assembly of mRNAs into messenger ribonucleoparticles (mRNPs) is pivotal for both genome expression and integrity: indeed, the combinatorial association of RNA-binding proteins (RBPs) to mRNAs does not only define their cellular fate, but also counteracts the accumulation of genotoxic DNA:RNA hybrids, or R-loops. To further understand how these processes are coordinated, especially for functionally related mRNAs, we systematically analyzed genome-wide maps of RBP association and R-loop formation in the budding yeast S. cerevisiae. On the one hand, we have investigated whether specific mRNP biogenesis pathways could take place for mRNAs encoding the subunits of multiprotein complexes. Focusing on the Nuclear Pore, we highlighted a trans-acting mechanism that collectively target the mRNAs encoding the components of this complex, and prevent the accumulation of unassembled subunits. On the other hand, we have searched for cis-acting genomic features regulating R-loop formation. Surprisingly, we found that the presence of introns mitigates the accumulation of…

Considered as the dark matter of genomes, the non-protein coding DNA portion of eukaryotic genomes has, in the last decade, been shown to be much bigger than what was thought. Furthermore, with the advent of deep sequencing it became clear that genomes are pervasively transcribed and that the noncoding fraction generates huge amounts of transcripts that cannot be accounted for as simple “junk” or transcriptional noise. This challenges the central dogma of molecular biology where, for over 50 years, proteins have been considered to be the sole drivers of biological processes. Recent evidence strongly supports that noncoding (nc)RNAs are indeed functional and responsible for a multitude of regulatory processes such as gene regulation, nucleus organization and post-transcriptional regulation. In Phaeodactylum tricornutum over ∼1,500 long intergenic (li)ncRNAs and ∼3,300 natural antisense lncRNAs (NATs) have been identified. These are polyadenylated bona fide discrete transcripts that are expressed under specific physiological states. A ‘guilt by…

The co-evolutive landmarks left by the evolutionary process in protein multiple sequence alignments can be used, among other things, to detect pairs of proteins physically interacting or functionally related. Over time, we have developed different approaches that exploit this idea with the aim of extracting protein interaction networks from the deluge of sequence data that characterizes modern Biology. Current “high-throughput sequencing” technologies have the potential to revolutionize these methods as they generate protein sequences in a fast and cheap way. Nevertheless, more than blindly using all available sequences, it looks like the future will be characterized by a careful selection of those to use, and even the “a-la-carte” re-sequencing of the more suitable species/strains for a particular family/system of interest.

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.