Massimo Vergassola

The Lattice Boltzmann equation: Theory and applications

The basic elements of the theory of the lattice Boltzmann equation, a special lattice gas kinetic model for hydrodynamics, are reviewed. Applications are also presented together with some generalizations which allow one to extend the range of applicability of the method to a number of fluid dynamics related problems.

The Listeria transcriptional landscape from saprophytism to virulence

The bacterium Listeria monocytogenes is ubiquitous in the environment and can lead to severe food-borne infections. It has recently emerged as a multifaceted model in pathogenesis. However, how this bacterium switches from a saprophyte to a pathogen is largely unknown. Here, using tiling arrays and RNAs from wild-type and mutant bacteria grown in vitro, ex vivo and in vivo, we have analysed the transcription of its entire genome. We provide the complete Listeria operon map and have uncovered far more diverse types of RNAs than expected: in addition to 50 small RNAs (<500 nucleotides), at least two of which are involved in virulence in mice, we have identified antisense RNAs covering several open-reading frames and long overlapping 5′ and 3′ untranslated regions. We discovered that riboswitches can act as terminators for upstream genes. When Listeria reaches the host intestinal lumen, an extensive transcriptional reshaping occurs with a SigB-mediated activation of virulence genes. In contrast, in the blood, PrfA controls transcription of virulence genes. Remarkably, several non-coding RNAs absent in the non-pathogenic species Listeria innocua exhibit the same expression patterns as the virulence genes. Together, our data unravel successive and coordinated global transcriptional changes during infection and point to previously unknown regulatory mechanisms in bacteria.

Particles and fields in fluid turbulence

The understanding of fluid turbulence has considerably progressed in recent years. The application of the methods of statistical mechanics to the description of the motion of fluid particles, i.e. to the Lagrangian dynamics, has led to a new quantitative theory of intermittency in turbulent transport. The first analytical description of anomalous scaling laws in turbulence has been obtained. The underlying physical mechanism reveals the role of statistical integrals of motion in non-equilibrium systems. For turbulent transport, the statistical conservation laws are hidden in the evolution of groups of fluid particles and arise from the competition between the expansion of a group and the change of its geometry. By breaking the scale-invariance symmetry, the statistically conserved quantities lead to the observed anomalous scaling of transported fields. Lagrangian methods also shed new light on some practical issues, such as mixing and turbulent magnetic dynamo.

Infotaxis as a strategy for searching without gradients

Chemotactic bacteria rely on local concentration gradients to guide them towards the source of a nutrient. Such local cues pointing towards the location of the source are not always available at macroscopic scales because mixing in a flowing medium breaks up regions of high concentration into random and disconnected patches. Thus, animals sensing odours in air or water detect them only intermittently as patches sweep by on the wind or currents. A macroscopic searcher must devise a strategy of movement based on sporadic cues and partial information. Here we propose a search algorithm, which we call ‘infotaxis’, designed to work under such conditions. Any search process can be thought of as acquisition of information on source location; for infotaxis, information plays a role similar to concentration in chemotaxis. The infotaxis strategy locally maximizes the expected rate of information gain. We demonstrate its efficiency using a computational model of odour plume propagation and experimental data on mixing flows. Infotactic trajectories feature ‘zigzagging’ and ‘casting’ paths similar to those observed in the flight of moths. The proposed search algorithm is relevant to the design of olfactory robots, but the general idea of infotaxis can be applied more broadly in the context of searching with sparse information.

Computational detection of genomic cis- regulatory modules applied to body patterning in the early Drosophila embryo

BackgroundRegulation of gene transcription is crucial for the function and development of all organisms. While gene prediction programs that identify protein coding sequence are used with remarkable success in the annotation of genomes, the development of computational methods to analyze noncoding regions and to delineate transcriptional control elements is still in its infancy.ResultsHere we present novel algorithms to detect cis- regulatory modules through genome wide scans for clusters of transcription factor binding sites using three levels of prior information. When binding sites for the factors are known, our statistical segmentation algorithm, Ahab, yields about 150 putative gap gene regulated modules, with no adjustable parameters other than a window size. If one or more related modules are known, but no binding sites, repeated motifs can be found by a customized Gibbs sampler and input to Ahab, to predict genes with similar regulation. Finally using only the genome, we developed a third algorithm, Argos, that counts and scores clusters of overrepresented motifs in a window of sequence. Argos recovers many of the known modules, upstream of the segmentation genes, with no training data.ConclusionsWe have demonstrated, in the case of body patterning in the Drosophila embryo, that our algorithms allow the genome-wide identification of regulatory modules. We believe that Ahab overcomes many problems of recent approaches and we estimated the false positive rate to be about 50%. Argos is the first successful attempt to predict regulatory modules using only the genome without training data. Complete results and module predictions across the Drosophila genome are available at http://uqbar.rockefeller.edu/~siggia/.

Identification of new noncoding RNAs in Listeria monocytogenes and prediction of mRNA targets

To identify noncoding RNAs (ncRNAs) in the pathogenic bacterium Listeria monocytogenes, we analyzed the intergenic regions (IGRs) of strain EGD-e by in silico-based approaches. Among the twelve ncRNAs found, nine are novel and specific to the Listeria genus, and two of these ncRNAs are expressed in a growth-dependent manner. Three of the ncRNAs are transcribed in opposite direction to overlapping open reading frames (ORFs), suggesting that they act as antisense on the corresponding mRNAs. The other ncRNA genes appear as single transcription units. One of them displays five repeats of 29 nucleotides. Five of these new ncRNAs are absent from the non-pathogenic species L. innocua, raising the possibility that they might be involved in virulence. To predict mRNA targets of the ncRNAs, we developed a computational method based on thermodynamic pairing energies and known ncRNA–mRNA hybrids. Three ncRNAs, including one of the putative antisense ncRNAs, were predicted to have more than one mRNA targets. Several of them were shown to bind efficiently to the ncRNAs suggesting that our in silico approach could be used as a general tool to search for mRNA targets of ncRNAs.

VirR, a response regulator critical for Listeria monocytogenes virulence

Signature‐tagged mutagenesis (STM) was used to identify new genes involved in the virulence of the Gram‐positive intracellular pathogen Listeria monocytogenes. One of the mutants isolated by this technique had the transposon inserted in virR, a gene encoding a putative response regulator of a two‐component system. Deletion of virR severely decreased virulence in mice as well as invasion in cell‐culture experiments. Using a transcriptomic approach, we identified 12 genes regulated by VirR, including the dlt‐operon, previously reported to be important for L. monocytogenes virulence. However, a strain lacking dltA, was not as impaired in virulence as the ΔvirR strain, suggesting a role in virulence for other members of the vir regulon. Another VirR‐regulated gene is homologous to mprF, which encodes a protein that modifies membrane phosphatidyl glycerol with l‐lysine and that is involved in resistance to human defensins in Staphylococcus aureus. VirR thus appears to control virulence by a global regulation of surface components modifications. These modifications may affect interactions with host cells, including components of the innate immune system. Surprisingly, although controlling the same set of genes as VirR, the putative cognate histidine kinase of VirR, VirS, encoded by a gene located three genes downstream of virR, was shown not to be essential for virulence. By monitoring the activity of VirR with a GFP reporter construct, we showed that VirR can be activated independently of VirS, for example through a mechanism involving variations in the level of intracellular acetyl phosphate. In silico analysis of the VirR‐regulated promoters revealed a VirR DNA‐binding consensus site and specific interaction between purified VirR protein and this consensus sequence was demonstrated by gel mobility shift assays. This study identifies a second key virulence regulon in L. monocytogenes, after the prfA regulon.

CovS/CovR of group B streptococcus: a two-component global regulatory system involved in virulence

In this study, we carried out a detailed structural and functional analysis of a Streptococcus agalactiae (GBS) two‐component system which is orthologous to the CovS/CovR (CsrS/CsrR) regulatory system of Streptococcus pyogenes. In GBS, covR and covS are part of a seven gene operon transcribed from two promoters that are not regulated by CovR. A ΔcovSR mutant was found to display dramatic phenotypic changes such as increased haemolytic activity and reduced CAMP activity on blood agar. Adherence of the ΔcovSR mutant to epithelial cells was greatly increased and analysis by transmission electron microscopy revealed the presence at its surface of a fibrous extracellular matrix that might be involved in these intercellular interactions. However, the ΔcovSR mutant was unable to initiate growth in RPMI and its viability in human normal serum was greatly impaired. A major finding of this phenotypic analysis was that the CovS/CovR system is important for GBS virulence, as a 3 log increase of the LD50 of the mutant strain was observed in the neonate rat sepsis model. The pleiotropic phenotype of the ΔcovSR mutant is in full agreement with the large number of genes controlled by CovS/CovR as seen by expression profiling analysis, many of which encode potentially secreted or cell surface‐associated proteins: 76 genes are repressed whereas 63 were positively regulated. CovR was shown to bind directly to the regulatory regions of several of these genes and a consensus CovR recognition sequence was proposed using both DNase I footprinting and computational analyses.

An evolutionary and functional assessment of regulatory network motifs

BackgroundCellular functions are regulated by complex webs of interactions that might be schematically represented as networks. Two major examples are transcriptional regulatory networks, describing the interactions among transcription factors and their targets, and protein-protein interaction networks. Some patterns, dubbed motifs, have been found to be statistically over-represented when biological networks are compared to randomized versions thereof. Their function in vitro has been analyzed both experimentally and theoretically, but their functional role in vivo, that is, within the full network, and the resulting evolutionary pressures remain largely to be examined.ResultsWe investigated an integrated network of the yeast Saccharomyces cerevisiae comprising transcriptional and protein-protein interaction data. A comparative analysis was performed with respect to Candida glabrata, Kluyveromyces lactis, Debaryomyces hansenii and Yarrowia lipolytica, which belong to the same class of hemiascomycetes as S. cerevisiae but span a broad evolutionary range. Phylogenetic profiles of genes within different forms of the motifs show that they are not subject to any particular evolutionary pressure to preserve the corresponding interaction patterns. The functional role in vivo of the motifs was examined for those instances where enough biological information is available. In each case, the regulatory processes for the biological function under consideration were found to hinge on post-transcriptional regulatory mechanisms, rather than on the transcriptional regulation by network motifs.ConclusionThe overabundance of the network motifs does not have any immediate functional or evolutionary counterpart. A likely reason is that motifs within the networks are not isolated, that is, they strongly aggregate and have important edge and/or node sharing with the rest of the network.

Bacterial strategies for chemotaxis response

Regular environmental conditions allow for the evolution of specifically adapted responses, whereas complex environments usually lead to conflicting requirements upon the organism’s response. A relevant instance of these issues is bacterial chemotaxis, where the evolutionary and functional reasons for the experimentally observed response to chemoattractants remain a riddle. Sensing and motility requirements are in fact optimized by different responses, which strongly depend on the chemoattractant environmental profiles. It is not clear then how those conflicting requirements quantitatively combine and compromise in shaping the chemotaxis response. Here we show that the experimental bacterial response corresponds to the maximin strategy that ensures the highest minimum uptake of chemoattractants for any profile of concentration. We show that the maximin response is the unique one that always outcompetes motile but nonchemotactic bacteria. The maximin strategy is adapted to the variable environments experienced by bacteria, and we explicitly show its emergence in simulations of bacterial populations in a chemostat. Finally, we recast the contrast of evolution in regular vs. complex environments in terms of minimax vs. maximin game-theoretical strategies. Our results are generally relevant to biological optimization principles and provide a systematic possibility to get around the need to know precisely the statistics of environmental fluctuations.