Molecular Mechanisms Underlying Mucosal Attachment and Colonization by \u3ci\u3eClostridioides difficile\u3c/i\u3e

Clostridioides difficile is a Gram-positive, spore-forming, anaerobic bacterium which causes gastrointestinal disease and is a leading cause of nosocomial infections. Although infection typically occurs following antibiotic therapy, in recent years there has been an increase in infections which are not preceded by antibiotic use. Additionally, community-associated infections and rates of disease recurrence have increased. While it is understood that a healthy gastrointestinal microbiota provides protection against infection, the molecular mechanisms which underly C. difficile\u27s ability to colonize and persist in the gut are mostly unknown. Building on work from others that suggests C. difficile associates with the outer mucus layer during infection, we utilized an in vitro mucus layer model to probe attachment and colonization mechanisms. Using gene-interruption mutants of the major subunits of type IV pili and flagella, two extracellular appendages implicated in adhesion, we observed that the presence of flagella facilitates initial mucus attachment. Adhesion was variable across multiple strains of C. difficile and was also dependent on the source of mucin derivation. When mucin glycans were modified by mucin-degrading bacteria, C. difficile attachment decreased in our model. Collectively, our findings suggest that adherence to mucin likely influences C. difficile\u27s ability to colonize and may offer novel strategies for future therapeutics once the underlying mechanisms are better understood. Advisor: Kurt H. Piepenbrin

Recognition of extracellular DNA by type IV pili promotes biofilm formation by \u3ci\u3eClostridioides difficile\u3c/i\u3e

Clostridioides difficile is a Gram-positive bacillus, which is a frequent cause of gastrointestinal infections triggered by the depletion of the gut microbiome. Because of the frequent recurrence of these infections after antibiotic treatment, mechanisms of C. difficile persistence and recurrence, including biofilm formation, are of increasing interest. Previously, our group and others found that type IV pili, filamentous helical appendages polymerized from protein subunits, promoted microcolony and biofilm formation in C. difficile. In Gram-negative bacteria, the ability of type IV pili to mediate bacterial self-association has been explained through interactions between the pili of adjacent cells, but type IV pili from several Gram-negative species are also required for natural competence through DNA uptake. Here, we report the ability of two C. difficile pilin subunits, PilJ and PilW, to bind to DNA in vitro, as well as the defects in biofilm formation in the pilJ and pilW gene-interruption mutants. Additionally, we have resolved the X-ray crystal structure of PilW, which we use to model possible structural mechanisms for the formation of C. difficile biofilm through interactions between type IV pili and the DNA of the extracellular matrix. Taken together, our results provide further insight into the relationship between type IV pilus function and biofilm formation in C. difficile and, more broadly, suggest that DNA recognition by type IV pili and related structures may have functional importance beyond DNA uptake for natural competence

Are You Still With Me? Continuous Engagement Assessment From a Robot's Point of View

Continuously measuring the engagement of users with a robot in a Human-Robot Interaction (HRI) setting paves the way toward in-situ reinforcement learning, improve metrics of interaction quality, and can guide interaction design and behavior optimization. However, engagement is often considered very multi-faceted and difficult to capture in a workable and generic computational model that can serve as an overall measure of engagement. Building upon the intuitive ways humans successfully can assess situation for a degree of engagement when they see it, we propose a novel regression model (utilizing CNN and LSTM networks) enabling robots to compute a single scalar engagement during interactions with humans from standard video streams, obtained from the point of view of an interacting robot. The model is based on a long-term dataset from an autonomous tour guide robot deployed in a public museum, with continuous annotation of a numeric engagement assessment by three independent coders. We show that this model not only can predict engagement very well in our own application domain but show its successful transfer to an entirely different dataset (with different tasks, environment, camera, robot and people). The trained model and the software is available to the HRI community, at https://github.com/LCAS/engagement_detector, as a tool to measure engagement in a variety of settings

A Pilot Study with a Novel Setup for Collaborative Play of the Humanoid Robot KASPAR with children with autism

This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.This article describes a pilot study in which a novel experimental setup, involving an autonomous humanoid robot, KASPAR, participating in a collaborative, dyadic video game, was implemented and tested with children with autism, all of whom had impairments in playing socially and communicating with others. The children alternated between playing the collaborative video game with a neurotypical adult and playing the same game with the humanoid robot, being exposed to each condition twice. The equipment and experimental setup were designed to observe whether the children would engage in more collaborative behaviours while playing the video game and interacting with the adult than performing the same activities with the humanoid robot. The article describes the development of the experimental setup and its first evaluation in a small-scale exploratory pilot study. The purpose of the study was to gain experience with the operational limits of the robot as well as the dyadic video game, to determine what changes should be made to the systems, and to gain experience with analyzing the data from this study in order to conduct a more extensive evaluation in the future. Based on our observations of the childrens’ experiences in playing the cooperative game, we determined that while the children enjoyed both playing the game and interacting with the robot, the game should be made simpler to play as well as more explicitly collaborative in its mechanics. Also, the robot should be more explicit in its speech as well as more structured in its interactions. Results show that the children found the activity to be more entertaining, appeared more engaged in playing, and displayed better collaborative behaviours with their partners (For the purposes of this article, ‘partner’ refers to the human/robotic agent which interacts with the children with autism. We are not using the term’s other meanings that refer to specific relationships or emotional involvement between two individuals.) in the second sessions of playing with human adults than during their first sessions. One way of explaining these findings is that the children’s intermediary play session with the humanoid robot impacted their subsequent play session with the human adult. However, another longer and more thorough study would have to be conducted in order to better re-interpret these findings. Furthermore, although the children with autism were more interested in and entertained by the robotic partner, the children showed more examples of collaborative play and cooperation while playing with the human adult.Peer reviewe