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.Comment: 165 pages, review article for Rev. Mod. Phy

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SUMMARY How cells control their size and maintain size homeostasis is a fundamental open question. Cell-size homeostasis has been discussed in the context of two major paradigms: sizer, in which the cell actively monitors its size and triggers the cell cycle once it reaches a critical size, and timer, in which the cell attempts to grow for a specific amount of time before division. These paradigms, in conjunction with the “growth law” [1] and the quantitative bacterial cell cycle model [2], inspired numerous theoretical models [3-9] and experimental investigations from growth [10,11] to cell cycle and size control [12–15]. However, experimental evidence involved difficult-to-verify assumptions or population-averaged data, which allowed different interpretations [1–5,16–20] or limited conclusions [4–9]. In particular, population-averaged data and correlations are inconclusive as the averaging process masks causal effects at the cellular level. In this work, we extended a microfluidic “mother machine” [21] and monitored hundreds of thousands of Gram-negative Escherichia coli and Gram-positive Bacillus subtilis cells under a wide range of steady-state growth conditions. Our combined experimental results and quantitative analysis demonstrate that cells add a constant volume each generation irrespective of their newborn sizes, conclusively supporting the so-called constant Δ model. This model was introduced for E. coli [6,7] and recently revisited [9], but experimental evidence was limited to correlations. This “adder” principle quantitatively explains experimental data at both the population and single-cell levels, including the origin and the hierarchy of variability in the size-control mechanisms, and how cells maintain size homeostasis.

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.