Outer Membrane Structural Defects in Salmonella enterica Serovar Typhimurium Affect Neutrophil Chemokinesis but Not Chemotaxis.

Neutrophils, the first line of defense against pathogens, are critical in the host response to acute and chronic infections. In Gram-negative pathogens, the bacterial outer membrane (OM) is a key mediator of pathogen detection; nonetheless, the effects of variations in its molecular structure on the neutrophil migratory response to bacteria remain largely unknown. Here, we developed a quantitative microfluidic assay that precludes physical contact between bacteria and neutrophils while maintaining chemical communication, thus allowing investigation of both transient and steady-state responses of neutrophils to a library of Salmonella enterica serovar Typhimurium OM-related mutants at single-cell resolution. Using single-cell quantitative metrics, we found that transient neutrophil chemokinesis is highly gradated based upon OM structure, while transient and steady-state chemotaxis responses differ little between mutants. Based on our finding of a lack of correlation between chemokinesis and chemotaxis, we define "stimulation score" as a metric that comprehensively describes the neutrophil response to pathogens. Complemented with a killing assay, our results provide insight into how OM modifications affect neutrophil recruitment and pathogen survival. Altogether, our platform enables the discovery of transient and steady-state migratory responses and provides a new path for quantitative interrogation of cell decision-making processes in a variety of host-pathogen interactions.IMPORTANCE Our findings provide insights into the previously unexplored effects of Salmonella envelope defects on fundamental innate immune cell behavior, which advance the knowledge in pathogen-host cell biology and potentially inspire the rational design of attenuated strains for vaccines or immunotherapeutic strains for cancer therapy. Furthermore, the microfluidic assay platform and analytical tools reported herein enable high-throughput, sensitive, and quantitative screening of microbial strains' immunogenicity in vitro This approach could be particularly beneficial for rapid in vitro screening of engineered microbial strains (e.g., vaccine candidates) as the quantitative ranking of the overall strength of the neutrophil response, reported by "stimulation score," agrees with in vivo cytokine response trends reported in the literature.

Data-driven statistical modeling of the emergent behavior of biohybrid microrobots.

Multi-agent biohybrid microrobotic systems, owing to their small size and distributed nature, offer powerful solutions to challenges in biomedicine, bioremediation, and biosensing. Synthetic biology enables programmed emergent behaviors in the biotic component of biohybrid machines, expounding vast potential benefits for building biohybrid swarms with sophisticated control schemes. The design of synthetic genetic circuits tailored toward specific performance characteristics is an iterative process that relies on experimental characterization of spatially homogeneous engineered cell suspensions. However, biohybrid systems often distribute heterogeneously in complex environments, which will alter circuit performance. Thus, there is a critically unmet need for simple predictive models that describe emergent behaviors of biohybrid systems to inform synthetic gene circuit design. Here, we report a data-driven statistical model for computationally efficient recapitulation of the motility dynamics of two types of Escherichia coli bacteria-based biohybrid swarms-NanoBEADS and BacteriaBots. The statistical model was coupled with a computational model of cooperative gene expression, known as quorum sensing (QS). We determined differences in timescales for programmed emergent behavior in BacteriaBots and NanoBEADS swarms, using bacteria as a comparative baseline. We show that agent localization and genetic circuit sensitivity strongly influence the timeframe and the robustness of the emergent behavior in both systems. Finally, we use our model to design a QS-based decentralized control scheme wherein agents make independent decisions based on their interaction with other agents and the local environment. We show that synergistic integration of synthetic biology and predictive modeling is requisite for the efficient development of biohybrid systems with robust emergent behaviors.

Integrating nanofibers with biochemical gradients to investigate physiologically-relevant fibroblast chemotaxis.

Persistent cell migration can occur due to anisotropy in the extracellular matrix (ECM), the gradient of a chemo-effector, or a combination of both. Through a variety of in vitro platforms, the contributions of either stimulus have been extensively studied, while the combined effect of both cues remains poorly described. Here, we report an integrative microfluidic chemotaxis assay device that enables the study of single cell chemotaxis on ECM-mimicking, aligned, and suspended nanofibers. Using this assay, we evaluated the effect of fiber spacing on the morphology and chemotaxis response of embryonic murine NIH/3T3 fibroblasts in the presence of temporally invariant, linear gradients of platelet-derived growth factor-BB (PDGF-BB). We found that the strength of PDGF-mediated chemotaxis response depends on not only the gradient slope but also the cell morphology. Low aspect ratio (3.4 ± 0.2) cells on flat substrata exhibited a chemotaxis response only at a PDGF-BB gradient of 0-10 ng mL-1. However, high aspect ratio (19.1 ± 0.7) spindle-shaped cells attached to individual fibers exhibited maximal chemotaxis response at a ten-fold shallower gradient of 0-1 ng mL-1, which was robustly maintained up to 0-10 ng mL-1. Quadrilateral-shaped cells of intermediate aspect ratio (13.6 ± 0.8) attached to two fibers exhibited a weaker response compared to the spindle-shaped cells, but still stronger compared to cells attached to 2D featureless substrata. Through pharmacological inhibition, we show that the mesenchymal chemotaxis pathway is conserved in cells on fibers. Altogether, our findings show that chemotaxis on ECM-mimicking fibers is modulated by fiber spacing-driven cell shape and can be significantly different from the behavior observed on flat 2D substrata. We envisage that this microfluidic platform will have wide applicability in understanding the combined role of ECM architecture and chemotaxis in physiological and pathological processes.

Quantitative Investigation of the Role of Intra-/Intercellular Dynamics in Bacterial Quorum Sensing.

Bacteria utilize diffusible signals to regulate population density-dependent coordinated gene expression in a process called quorum sensing (QS). While the intracellular regulatory mechanisms of QS are well-understood, the effect of spatiotemporal changes in the population configuration on the sensitivity and robustness of the QS response remains largely unexplored. Using a microfluidic device, we quantitatively characterized the emergent behavior of a population of swimming E. coli bacteria engineered with the lux QS system and a GFP reporter. We show that the QS activation time follows a power law with respect to bacterial population density, but this trend is disrupted significantly by microscale variations in population configuration and genetic circuit noise. We then developed a computational model that integrates population dynamics with genetic circuit dynamics to enable accurate (less than 7% error) quantitation of the bacterial QS activation time. Through modeling and experimental analyses, we show that changes in spatial configuration of swimming bacteria can drastically alter the QS activation time, by up to 22%. The integrative model developed herein also enables examination of the performance robustness of synthetic circuits with respect to growth rate, circuit sensitivity, and the population's initial size and spatial structure. Our framework facilitates quantitative tuning of microbial systems performance through rational engineering of synthetic ribosomal binding sites. We have demonstrated this through modulation of QS activation time over an order of magnitude. Altogether, we conclude that predictive engineering of QS-based bacterial systems requires not only the precise temporal modulation of gene expression (intracellular dynamics) but also accounting for the spatiotemporal changes in population configuration (intercellular dynamics).