Measures of Anxiety in Zebrafish (Danio rerio): Dissociation of Black/White Preference and Novel Tank Test

The effects of wall color stimuli on diving, and the effects of depth stimuli on scototaxis, were assessed in zebrafish. Three groups of fish were confined to a black, a white, or a transparent tank, and tested for depth preference. Two groups of fish were confined to a deep or a shallow tank, and tested for black-white preference. As predicted, fish preferred the deep half of a split-tank over the shallow half, and preferred the black half of a black/white tank over the white half. Results indicated that the tank wall color significantly affected depth preference, with the transparent tank producing the strongest depth preference and the black tank producing the weakest preference. Tank depth, however, did not significantly affect color preference. Additionally, wall color significantly affected shuttling and immobility, while depth significantly affected shuttling and thigmotaxis. These results are consistent with previous indications that the diving response and scototaxis may reflect dissociable mechanisms of behavior. We conclude that the two tests are complementary rather than interchangeable, and that further research on the motivational systems underlying behavior in each of the two tests is needed

American Gut: an Open Platform for Citizen Science Microbiome Research

McDonald D, Hyde E, Debelius JW, et al. American Gut: an Open Platform for Citizen Science Microbiome Research. mSystems. 2018;3(3):e00031-18

Structure, function and diversity of the healthy human microbiome

Author Posting. © The Authors, 2012. This article is posted here by permission of Nature Publishing Group. The definitive version was published in Nature 486 (2012): 207-214, doi:10.1038/nature11234.Studies of the human microbiome have revealed that even healthy individuals differ remarkably in the microbes that occupy habitats such as the gut, skin and vagina. Much of this diversity remains unexplained, although diet, environment, host genetics and early microbial exposure have all been implicated. Accordingly, to characterize the ecology of human-associated microbial communities, the Human Microbiome Project has analysed the largest cohort and set of distinct, clinically relevant body habitats so far. We found the diversity and abundance of each habitat’s signature microbes to vary widely even among healthy subjects, with strong niche specialization both within and among individuals. The project encountered an estimated 81–99% of the genera, enzyme families and community configurations occupied by the healthy Western microbiome. Metagenomic carriage of metabolic pathways was stable among individuals despite variation in community structure, and ethnic/racial background proved to be one of the strongest associations of both pathways and microbes with clinical metadata. These results thus delineate the range of structural and functional configurations normal in the microbial communities of a healthy population, enabling future characterization of the epidemiology, ecology and translational applications of the human microbiome.This research was supported in part by National Institutes of Health grants U54HG004969 to B.W.B.; U54HG003273 to R.A.G.; U54HG004973 to R.A.G., S.K.H. and J.F.P.; U54HG003067 to E.S.Lander; U54AI084844 to K.E.N.; N01AI30071 to R.L.Strausberg; U54HG004968 to G.M.W.; U01HG004866 to O.R.W.; U54HG003079 to R.K.W.; R01HG005969 to C.H.; R01HG004872 to R.K.; R01HG004885 to M.P.; R01HG005975 to P.D.S.; R01HG004908 to Y.Y.; R01HG004900 to M.K.Cho and P. Sankar; R01HG005171 to D.E.H.; R01HG004853 to A.L.M.; R01HG004856 to R.R.; R01HG004877 to R.R.S. and R.F.; R01HG005172 to P. Spicer.; R01HG004857 to M.P.; R01HG004906 to T.M.S.; R21HG005811 to E.A.V.; M.J.B. was supported by UH2AR057506; G.A.B. was supported by UH2AI083263 and UH3AI083263 (G.A.B., C. N. Cornelissen, L. K. Eaves and J. F. Strauss); S.M.H. was supported by UH3DK083993 (V. B. Young, E. B. Chang, F. Meyer, T. M. S., M. L. Sogin, J. M. Tiedje); K.P.R. was supported by UH2DK083990 (J. V.); J.A.S. and H.H.K. were supported by UH2AR057504 and UH3AR057504 (J.A.S.); DP2OD001500 to K.M.A.; N01HG62088 to the Coriell Institute for Medical Research; U01DE016937 to F.E.D.; S.K.H. was supported by RC1DE0202098 and R01DE021574 (S.K.H. and H. Li); J.I. was supported by R21CA139193 (J.I. and D. S. Michaud); K.P.L. was supported by P30DE020751 (D. J. Smith); Army Research Office grant W911NF-11-1-0473 to C.H.; National Science Foundation grants NSF DBI-1053486 to C.H. and NSF IIS-0812111 to M.P.; The Office of Science of the US Department of Energy under Contract No. DE-AC02-05CH11231 for P.S. C.; LANL Laboratory-Directed Research and Development grant 20100034DR and the US Defense Threat Reduction Agency grants B104153I and B084531I to P.S.C.; Research Foundation - Flanders (FWO) grant to K.F. and J.Raes; R.K. is an HHMI Early Career Scientist; Gordon&BettyMoore Foundation funding and institutional funding fromthe J. David Gladstone Institutes to K.S.P.; A.M.S. was supported by fellowships provided by the Rackham Graduate School and the NIH Molecular Mechanisms in Microbial Pathogenesis Training Grant T32AI007528; a Crohn’s and Colitis Foundation of Canada Grant in Aid of Research to E.A.V.; 2010 IBM Faculty Award to K.C.W.; analysis of the HMPdata was performed using National Energy Research Scientific Computing resources, the BluBioU Computational Resource at Rice University

A framework for human microbiome research

A variety of microbial communities and their genes (the microbiome) exist throughout the human body, with fundamental roles in human health and disease. The National Institutes of Health (NIH)-funded Human Microbiome Project Consortium has established a population-scale framework to develop metagenomic protocols, resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomic data available to the scientific community. Here we present resources from a population of 242 healthy adults sampled at 15 or 18 body sites up to three times, which have generated 5,177 microbial taxonomic profiles from 16S ribosomal RNA genes and over 3.5 terabases of metagenomic sequence so far. In parallel, approximately 800 reference strains isolated from the human body have been sequenced. Collectively, these data represent the largest resource describing the abundance and variety of the human microbiome, while providing a framework for current and future studies

Frequency of shuttling (center-crossing).

<p>The effect of black, white, and transparent stimuli on shuttling is plotted in <b>panel a</b>; animals in transparent tanks shuttled less frequently than those in black or white tanks. The effect of deep and shallow stimuli on color preference is plotted in <b>panel b</b>; animals in shallow tanks shuttled less frequently than those in deep tanks.</p

Illustration of the apparatus.

<p>In <b>panels a–c</b> are the configurations used for examining the effect of color (black in <b>panel a</b>, white in <b>panel b</b>, transparent in <b>panel c</b>) on depth preference. In <b>panels d and e</b> are the configurations used for examining the effect of depth (deep in <b>panel d</b>, shallow in <b>panel e</b>) on color preference. Horizontal open areas represent the plexiglas partitions, while areas filled with grey represent the gravel substrate.</p

Mean distance from the walls.

<p>In the upper portion of <b>panel a</b> is the mean distance from the walls in the deep side of the tank, and in the lower portion of panel a is the mean distance from the walls in the shallow side of the tank. Black, white and transparent stimuli had no effect on distance from the walls. In the upper portion of <b>panel b</b> is the mean distance from the walls in the black side of the tank, and in the lower portion of panel b is the mean distance from the walls in the white side of the tank. Animals remained closer to the walls when the tank was shallow.</p

Immobility.

<p>In the upper portion of <b>panel a</b> is immobility in the deep side of the tank, and in the lower portion of panel a is immobility in the shallow side. Transparent stimuli produced more immobility than black or white stimuli, all of which was in the deep side. In the upper portion of <b>panel b</b> is immobility in the black side of the tank, and in the lower portion of panel b is immobility in the white side; there was no effect of depth on immobility.</p

Schematic representation of behavior.

<p>In <b>panels a–c</b> are the DP groups, and <b>panels d and e</b> are the CP groups. Circle size represents the duration of time in each side, and arrow size represents the frequency of shuttling between the two sides.</p

Duration of zebrafish on the less-preferred side.

<p>The effect of black, white, and transparent stimuli on depth preference is plotted in <b>panel a</b>; animals in black tanks spent more time in the shallow side than those in transparent tanks. The effect of deep and shallow stimuli on color preference is plotted in <b>panel b</b>; there was no effect of depth on color preference.</p