Regulation of bistability in the std fimbrial operon of Salmonella enterica by DNA adenine methylation and transcription factors HdfR, StdE and StdF

Bistable expression of the Salmonella enterica std operon is controlled by an AND logic gate involving three transcriptional activators: the LysR-type factor HdfR and the StdE and StdF regulators encoded by the std operon itself. StdE activates transcription of the hdfR gene, and StdF activates std transcription together with HdfR. Binding of HdfR upstream of the std promoter is hindered by methylation of GATC sites located within the upstream activating sequence (UAS). Epigenetic control by Dam methylation thus antagonizes formation of the StdE-StdF-HdfR loop and tilts the std switch toward the StdOFF state. In turn, HdfR binding hinders methylation of the UAS, permitting activation of the StdE-StdF-HdfR loop and concomitant formation of StdON cells. Bistability is thus the outcome of competition between DNA adenine methylation and the StdE-StdF-HdfR activator loop.Ministerio de Ciencia, Innovación y Universidades [BIO2016–75235-P

Dynamical Synapses Enhance Neural Information Processing: Gracefulness, Accuracy and Mobility

Experimental data have revealed that neuronal connection efficacy exhibits two forms of short-term plasticity, namely, short-term depression (STD) and short-term facilitation (STF). They have time constants residing between fast neural signaling and rapid learning, and may serve as substrates for neural systems manipulating temporal information on relevant time scales. The present study investigates the impact of STD and STF on the dynamics of continuous attractor neural networks (CANNs) and their potential roles in neural information processing. We find that STD endows the network with slow-decaying plateau behaviors-the network that is initially being stimulated to an active state decays to a silent state very slowly on the time scale of STD rather than on the time scale of neural signaling. This provides a mechanism for neural systems to hold sensory memory easily and shut off persistent activities gracefully. With STF, we find that the network can hold a memory trace of external inputs in the facilitated neuronal interactions, which provides a way to stabilize the network response to noisy inputs, leading to improved accuracy in population decoding. Furthermore, we find that STD increases the mobility of the network states. The increased mobility enhances the tracking performance of the network in response to time-varying stimuli, leading to anticipative neural responses. In general, we find that STD and STP tend to have opposite effects on network dynamics and complementary computational advantages, suggesting that the brain may employ a strategy of weighting them differentially depending on the computational purpose.Comment: 40 pages, 17 figure

Std fimbriae-fucose interaction increases Salmonella-induced intestinal inflammation and prolongs colonization

Author summary The intestinal epithelium is a crucial biological interface, interacting with both commensal and pathogenic microorganisms. It’s lined with heavily glycosylated proteins and glycolipids which can act as both attachment sites and energy sources for intestinal bacteria. Fut2, the enzyme governing epithelial α1,2-fucosylation, has been implicated in the interaction between microbes and intestinal epithelial cells. Salmonella is one of the most important bacterial gastrointestinal pathogens affecting millions of people worldwide. Salmonella possesses fimbrial and non-fimbrial adhesins which can be used to adhere to host cells. Here we show that Salmonella expresses Std fimbriae in the gastrointestinal tract in vivo and exploit Std fimbriae to bind fucosylated structures in the mucus and on the intestinal epithelium. Furthermore, we demonstrate that the Std fimbriae-fucose interaction is necessary for bacterial colonization of the intestine and for triggering intestinal inflammation. These data lend new insights into bacterial adhesion-epithelial interactions which are essential for bacterial pathogenesis and key factors in determining tissue tropism and host susceptibility to infectious disease

Symmetric Tensor Decomposition Description of Fermionic Many-Body Wavefunctions

The configuration interaction (CI) is a versatile wavefunction theory for interacting fermions but it involves an extremely long CI series. Using a symmetric tensor decomposition (STD) method, we convert the CI series into a compact and numerically tractable form. The converted series encompasses the Hartree-Fock state in the first term and rapidly converges to the full-CI state, as numerically tested using small molecules. Provided that the length of the STD-CI series grows only moderately with the increasing complexity of the system, the new method will serve as one of the alternative variational methods to achieve full-CI with enhanced practicability.Comment: 10 pages, 6 figure