Summary Predicting host health status based on microbial community structure is a major goal of microbiome research. An implicit assumption of microbiome profiling for diagnostic purposes is that the proportional representation of different taxa determine host phenotypes. To test this assumption, we colonized gnotobiotic zebrafish with zebrafish-derived bacterial isolates and measured bacterial abundance and host neutrophil responses. Surprisingly, combinations of bacteria elicited immune responses that do not reflect the numerically dominant species. These data are consistent with a quantitative model in which the host responses to commensal species are additive, but where various species have different per capita immunostimulatory effects. For example, one species has a high per capita immunosuppression that is mediated through a potent secreted factor. We conclude that the proportional representation of bacteria in a community does not necessarily predict its functional capacities; however, characterizing specific properties of individual species offers predictive insights into multi-species community function.

Ion channel localization to specific cell surface regions is essential for proper neuronal function. The Kv2.1 K ϩ channel forms large clusters on the plasma membrane of hippocampal neurons and transfected human embryonic kidney (HEK) cells. Using live cell imaging, we address mechanisms underlying this Kv2.1 clustering in both HEK cells and cultured hippocampal neurons. The Kv2.1-containing surface clusters have properties unlike those expected for a scaffolding protein bound channel. After channel is delivered to the plasma membrane via intracellular transport vesicles, it remains localized at the insertion site. Fluorescence recovery after photobleaching (FRAP) and quantum dot tracking experiments indicate that channel within the surface cluster is mobile (FRAP, ϭ 14.1 Ϯ 1.5 and 11.5 Ϯ 6.1 s in HEK cells and neurons, respectively). The cluster perimeter is not static, because after fusion of adjacent clusters, green fluorescent protein (GFP)-Kv2.1 completely exchanged between the two domains within 60 s. Treatment of hippocampal neurons expressing GFP-Kv2.1 with 5 M latrunculin A resulted in a significant increase in average cluster size from 0.89 Ϯ 0.16 m 2 to 12.15 Ϯ 1.4 m 2 with a concomitant decrease in cluster number. Additionally, Kv2.1 was no longer restricted to the cell body, suggesting a role for cortical actin in both cluster maintenance and localization. Thus, Kv2.1 surface domains likely trap mobile Kv2.1 channels within a well defined, but fluid, perimeter rather than being tightly bound to a scaffolding protein-containing complex. Channel moves directly into these clusters via trafficking vesicles. Such domains allow for efficient trafficking to the cell surface while sequestering channel with signaling proteins.Key words: Kv channel; restricted diffusion; membrane insertion; quantum dot tracking; fluorescence microscopy; hippocampal neurons IntroductionVoltage-gated ion channels are often highly localized in electrically excitable cells such as nerve and muscle. Voltage-gated Na ϩ channels form high-density arrays within the axon node of Ranvier, and voltage-gated K ϩ channels localize in the paranodal region (Rasband and Trimmer, 2001). In smooth muscle, Ca 2ϩ -dependent K ϩ channels are found adjacent to the ryanodine receptors of the sarcoplasmic reticulum (Wellman and Nelson, 2003). L-type voltage-gated Ca 2ϩ channels are exclusively localized to the T-tubule/sarcoplasmic reticulum triad junction in skeletal muscle (Dirksen, 2002). Whereas scaffolding proteins are known to cluster some neurotransmitter receptors (Kim and Sheng, 2004), the exact mechanisms underlying most ion channel localization remain unknown.The delayed rectifier Kv2.1 regulates somato-dendritic excitability in the mammalian CNS where it forms unique cell surface clusters on the soma and proximal dendrites of hippocampal neurons both in situ and in culture (Misonou et al., , 2005. Kv2.1 represents the predominant delayed rectifier current in these cells (Du et al., 2000). This clustering has been proposed to be attributa...

The vertebrate intestine is home to microbial ecosystems that play key roles in host development and health. Little is known about the spatial and temporal dynamics of these microbial communities, limiting our understanding of fundamental properties, such as their mechanisms of growth, propagation, and persistence. To address this, we inoculated initially germ-free zebrafish larvae with fluorescently labeled strains of an Aeromonas species, representing an abundant genus in the zebrafish gut. Using light sheet fluorescence microscopy to obtain three-dimensional images spanning the gut, we quantified the entire bacterial load, as founding populations grew from tens to tens of thousands of cells over several hours. The data yield the first ever measurements of the growth kinetics of a microbial species inside a live vertebrate intestine and show dynamics that robustly fit a logistic growth model. Intriguingly, bacteria were nonuniformly distributed throughout the gut, and bacterial aggregates showed considerably higher growth rates than did discrete individuals. The form of aggregate growth indicates intrinsically higher division rates for clustered bacteria, rather than surface-mediated agglomeration onto clusters. Thus, the spatial organization of gut bacteria both relative to the host and to each other impacts overall growth kinetics, suggesting that spatial characterizations will be an important input to predictive models of host-associated microbial community assembly.

The Kv2.1 delayed-rectifier channel trafficks to 1-3 μm2 clusters on the surface of neurons and transfected HEK cells. Single quantum dot (Qdot) tracking and FRAP approaches were used to quantify the diffusion of GFP-labeled Kv2.1 channels on the cell surface and address the mechanisms underlying the formation of these unique membrane structures. Mean square displacement analysis of single Kv2.1 channel tracks inside or outside the surface clusters yielded mean diffusion coefficients of 0.03±0.02 μm2/second and 0.06±0.05 μm2/second, respectively. Kv2.1 channels outside the clusters effectively ignore the cluster boundary, readily diffusing through these microdomains. However, in 5% of the tracks analyzed, single, non-clustered channels were observed to cross into a cluster and become corralled within the cluster perimeter. Alexa Fluor 594-labelled phalloidin staining and mCherry-Kv2.1 co-expression with GFP-actin indicated that the Kv2.1 surface clusters form where the cortical actin cytoskeleton is reduced. Kv2.1 channels lacking the C-terminus do not form clusters, freely diffusing over the cell surface with a mean diffusion coefficient of 0.07±0.04 μm2/second. These data support a model whereby the Kv2.1 clusters are formed by sub-membrane cytoskeletal structures that limit the lateral diffusion of only the sub-population of Kv2.1 channels carrying the appropriate modifications on the Kv2.1 C-terminus.

ABSTRACTDifferent disease outcomes ofHelicobacter pyloriinfection correlate with distinct inflammation patterns. These different inflammatory distributions may be initiated by differences in bacterial localization. OneH. pyloriproperty known to affect murine stomach localization is chemotaxis, the ability to move in response to chemical cues. In this report, we used nonchemotactic mutants (Che−) to analyze whether chemotaxis is required for initial colonization of particular stomach regions or for subsequent growth therein. We found thatH. pyloribehaves differently in the corpus, antrum, and corpus-antrum transition zone subregions of the stomach. This outcome suggests that these regions contain unique chemotactic signals. In the corpus,H. pyloriutilizes chemotaxis for initial localization but not for subsequent growth. In contrast, in the antrum and the corpus-antrum transition zone, chemotaxis does not help initial colonization but does promote subsequent proliferation. To determine which chemoreceptor is responsible for the corpus-antrum phenotypes, we infected mice with strains lacking each chemoreceptor. Strains lacking TlpA, TlpB, or TlpC displayed only modest deviations from the wild-type phenotype, while strains lacking TlpD resembled the Che−mutant in their antral colonization defect and fared even worse than the Che−mutant in the corpus. Additional analysis showed that inflammation is worse in the antrum than in the corpus in both wild-type and Che−mutant infections. These results suggest that chemotaxis, specifically, that controlled by TlpD, is necessary forH. pylorito survive or grow in the environment of increased inflammation in the antrum.

The diverse collections of microorganisms associated with humans and other animals, collectively referred to as their "microbiome," are critical for host health, but the mechanisms that govern their assembly are poorly understood. This has made it difficult to identify consistent host factors that explain variation in microbiomes across hosts, despite large-scale sampling efforts. While ecological theory predicts that the movement, or dispersal, of individuals can have profound and predictable consequences on community assembly, its role in the assembly of animal-associated microbiomes remains underexplored. Here, we show that dispersal of microorganisms among hosts can contribute substantially to microbiome variation, and is able to overwhelm the effects of individual host factors, in an experimental test of ecological theory. We manipulated dispersal among wild-type and immune-deficient knockout zebrafish and observed that interhost dispersal had a large effect on the diversity and composition of intestinal microbiomes. Interhost dispersal was strong enough to overwhelm the effects of host factors, largely eliminating differences between wild-type and immune-deficient hosts, regardless of whether dispersal occurred within or between genotypes, suggesting dispersal can independently alter the ecology of microbiomes. Our observations are consistent with a predictive model that assumes metacommunity dynamics and are likely mediated by dispersal-related microbial traits. These results illustrate the importance of microbial dispersal to animal microbiomes and motivate its integration into the study of host-microbe systems.

Sustaining a balanced intestinal microbial community is critical for maintaining intestinal health and preventing chronic inflammation. The gut is a highly dynamic environment, subject to periodic waves of peristaltic activity. We hypothesized that this dynamic environment is a prerequisite for a balanced microbial community and that the enteric nervous system (ENS), a chief regulator of physiological processes within the gut, profoundly influences gut microbiota composition. We found that zebrafish lacking an ENS due to a mutation in the Hirschsprung disease gene, sox10, develop microbiota-dependent inflammation that is transmissible between hosts. Profiling microbial communities across a spectrum of inflammatory phenotypes revealed that increased levels of inflammation were linked to an overabundance of pro-inflammatory bacterial lineages and a lack of anti-inflammatory bacterial lineages. Moreover, either administering a representative anti-inflammatory strain or restoring ENS function corrected the pathology. Thus, we demonstrate that the ENS modulates gut microbiota community membership to maintain intestinal health.

The efficacy of cancer immunotherapy is limited, in part, by the multitude of immunosuppressive mechanisms present within the tumor microenvironment (TME). Galectin-3 (Gal-3) is a lectin that contributes to TME immunosuppression and regulates diverse functions including cellular homeostasis and cancer biology. Increased Gal-3 expression during cancer progression augments tumor growth, invasiveness, metastatic potential, and immune suppression, which highlights the potential use of Gal-3 as a therapeutic target capable of modulating anti-tumor immunity. Here, we discuss the mechanisms by which Gal-3 regulates lymphocytes, the role of Gal-3 in lung and prostate tumors, and the contribution of Gal-3 to TME immunosuppression.