Compartment-specific immunity in the human gut: Properties and functions of dendritic cells in the colon versus the ileum

© 2015 The Authors. Published by BMJ. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: http://dx.doi.org/10.1136/gutjnl-2014-307916Objective Dendritic cells (DC) mediate intestinal immune tolerance. Despite striking differences between the colon and the ileum both in function and bacterial load, few studies distinguish between properties of immune cells in these compartments. Furthermore, information of gut DC in humans is scarce. We aimed to characterise human colonic versus ileal DC. Design Human DC from paired colonic and ileal samples were characterised by flow cytometry, electron microscopy or used to stimulate T cell responses in a mixed leucocyte reaction. Results A lower proportion of colonic DC produced pro-inflammatory cytokines (tumour necrosis factor-a and interleukin (IL)-1ß) compared with their ileal counterparts and exhibited an enhanced ability to generate CD4+FoxP3+IL-10+ (regulatory) T cells. There were enhanced proportions of CD103+Sirpa- DC in the colon, with increased proportions of CD103+Sirpa+ DC in the ileum. A greater proportion of colonic DC subsets analysed expressed the lymph-node-homing marker CCR7, alongside enhanced endocytic capacity, which was most striking in CD103+Sirpa+ DC. Expression of the inhibitory receptor ILT3 was enhanced on colonic DC. Interestingly, endocytic capacity was associated with CD103+ DC, in particular CD103+Sirpa+ DC. However, expression of ILT3 was associated with CD103- DC. Colonic and ileal DC differentially expressed skin-homing marker CCR4 and small-bowel-homing marker CCR9, respectively, and this corresponded to their ability to imprint these homing markers on T cells. Conclusions The regulatory properties of colonic DC may represent an evolutionary adaptation to the greater bacterial load in the colon. The colon and the ileum should be regarded as separate entities, each comprising DC with distinct roles in mucosal immunity and imprinting.This research was funded by St. Mark's Foundation (Harrow, UK), The Biotechnology and Biological Sciences Research Council (BBSRC; BB/J004529/1) and The National Institutes of Health (NIH; US) including The National Institute of Diabetes and Digestive and Kidney Diseases (NIH/NIDDK; T32-DK07632 and P01-DK072084) and The National Institute of Allergy and Infectious Disease (NIH/NIAID; R21-AI094033). We also gratefully acknowledge funding support from The Harvey M. and Lyn P. Meyerhoff Inflammatory Bowel Disease Centre at The Johns Hopkins Hospital, Baltimore, US.Published versio

Optimal Compensation for Temporal Uncertainty in Movement Planning

Motor control requires the generation of a precise temporal sequence of control signals sent to the skeletal musculature. We describe an experiment that, for good performance, requires human subjects to plan movements taking into account uncertainty in their movement duration and the increase in that uncertainty with increasing movement duration. We do this by rewarding movements performed within a specified time window, and penalizing slower movements in some conditions and faster movements in others. Our results indicate that subjects compensated for their natural duration-dependent temporal uncertainty as well as an overall increase in temporal uncertainty that was imposed experimentally. Their compensation for temporal uncertainty, both the natural duration-dependent and imposed overall components, was nearly optimal in the sense of maximizing expected gain in the task. The motor system is able to model its temporal uncertainty and compensate for that uncertainty so as to optimize the consequences of movement

A Forward-Genetic Screen and Dynamic Analysis of Lambda Phage Host-Dependencies Reveals an Extensive Interaction Network and a New Anti-Viral Strategy

Latently infecting viruses are an important class of virus that plays a key role in viral evolution and human health. Here we report a genome-scale forward-genetics screen for host-dependencies of the latently-infecting bacteriophage lambda. This screen identified 57 Escherichia coli (E. coli) genes—over half of which have not been previously associated with infection—that when knocked out inhibited lambda phage's ability to replicate. Our results demonstrate a highly integrated network between lambda and its host, in striking contrast to the results from a similar screen using the lytic-only infecting T7 virus. We then measured the growth of E. coli under normal and infected conditions, using wild-type and knockout strains deficient in one of the identified host genes, and found that genes from the same pathway often exhibited similar growth dynamics. This observation, combined with further computational and experimental analysis, led us to identify a previously unannotated gene, yneJ, as a novel regulator of lamB gene expression. A surprising result of this work was the identification of two highly conserved pathways involved in tRNA thiolation—one pathway is required for efficient lambda replication, while the other has anti-viral properties inhibiting lambda replication. Based on our data, it appears that 2-thiouridine modification of tRNAGlu, tRNAGln, and tRNALys is particularly important for the efficient production of infectious lambda phage particles

A nonlinear updating algorithm captures suboptimal inference in the presence of signal-dependent noise

Bayesian models have advanced the idea that humans combine prior beliefs and sensory observations to optimize behavior. How the brain implements Bayes-optimal inference, however, remains poorly understood. Simple behavioral tasks suggest that the brain can flexibly represent probability distributions. An alternative view is that the brain relies on simple algorithms that can implement Bayes-optimal behavior only when the computational demands are low. To distinguish between these alternatives, we devised a task in which Bayes-optimal performance could not be matched by simple algorithms. We asked subjects to estimate and reproduce a time interval by combining prior information with one or two sequential measurements. In the domain of time, measurement noise increases with duration. This property takes the integration of multiple measurements beyond the reach of simple algorithms. We found that subjects were able to update their estimates using the second measurement but their performance was suboptimal, suggesting that they were unable to update full probability distributions. Instead, subjects’ behavior was consistent with an algorithm that predicts upcoming sensory signals, and applies a nonlinear function to errors in prediction to update estimates. These results indicate that the inference strategies employed by humans may deviate from Bayes-optimal integration when the computational demands are high

Towards a synergy framework across neuroscience and robotics: Lessons learned and open questions. Reply to comments on: "Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands"

We would like to thank all commentators for their insightful commentaries. Thanks to their diverse and complementary expertise in neuroscience and robotics, the commentators have provided us with the opportunity to further discuss state-of-the-art and gaps in the integration of neuroscience and robotics reviewed in our article. We organized our reply in two sections that capture the main points of all commentaries [1–9]: (1) Advantages and limitations of the synergy approach in neuroscience and robotics, and (2) Learning and role of sensory feedback in biological and robotics synergies