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Giralt-Zuniga, M.

Publications and source records attributed to Giralt-Zuniga, M..

3 recordsLinked to original sources

Regulatory memory and growth-coupled inheritance shape nutrient-dependent flagella number variation in Salmonella

Bacteria must balance the advantage of movement against the cost of building flagella, yet how nutrient availability shapes variation in flagellar number across single cells remains unclear. Here, we combine time-resolved basal-body measurements in Salmonella enterica with a mechanistically constrained stochastic model of flagellar remodeling. The model separates two routes from nutrient availability to flagellar number: an RflP-dependent regulatory memory that sets a synthesis target via a latent sensing-memory variable, and a physical inheritance process in which synthesis, binomial partitioning, and division reshape the flagellar-number distribution. Coarse-graining this process yields leaky-integrator dynamics in which the mean flagellar number tracks a regulatory target, while the latent correlation follows acquisition-decay dynamics. In wild-type cells, nutrient-dependent acquisition raises the target and increases flagellar investment; in {Delta}rflP cells, loss of acquisition produces a transient overshoot that isolates the intrinsic decay (memory) timescale of the regulatory state. The fitted model predicts a held-out nutrient condition and reveals which parameter combinations are identifiable from the data. Analysis of the fitted dynamics suggests that precision is tuned primarily by sensing-dependent signal amplitude, rather than integration time, with an apparent [~]1.7-fold increase in effective wild-type noise amplitude after mean normalization, consistent with a precision cost of active regulation relative to the mutant. A model-free, information-geometric (Cramer-Rao) speed limit further shows that active remodeling approaches the statistical speed allowed by the observed distributional variability. Together, these results reveal how Salmonella cells couple regulatory memory with growth-dependent inheritance to record recent nutrient history in their flagellar number.

systems biology↗

First genome-based characterization of Listeria monocytogenes in Costa Rica

Genomic data on the foodborne pathogen Listeria monocytogenes from Central America are scarse. We analysed 92 isolates collected in Costa Rica over a decade from different regions, compared them to publicly available genomes and identified unnoticed outbreaks. This study calls for mandatory reporting of listeriosis to improve pathogen surveillance.

genomics↗

SPI-1 virulence gene expression modulates motility of Salmonella Typhimurium in a proton motive force- and adhesins-dependent manner

Both the bacterial flagellum and the evolutionary related injectisome encoded on the Salmonella pathogenicity island 1 (SPI-1) play crucial roles during the infection cycle of Salmonella species. The interplay of both is highlighted by the complex cross-regulation that includes transcriptional control of the flagellar master regulatory operon flhDC by HilD, the master regulator of SPI-1 gene expression. Contrary to the HilD-dependent activation of flagellar gene expression, we report here that activation of HilD resulted in a dramatic loss of motility, which was dependent on the presence of SPI-1. Single cell analyses revealed that HilD-activation results in a SPI-1-dependent induction of the stringent response and a pronounced decrease of proton motive force (PMF), while flagellation was not affected. We further found that activation of HilD enhanced the adhesion of Salmonella to epithelial cells. A transcriptome analysis revealed a concomitant upregulation of several adhesin systems, which when overproduced, phenocopied the HilD-induced motility defect. We propose that a combination of SPI-1-dependent depletion of the PMF and upregulation of adhesins upon HilD-activation allows flagellated Salmonella to rapidly modulate their motility during infection, thereby enabling efficient adhesion to host cells and delivery of effector proteins.

microbiology↗