Quantum Electronics

Contains reports on three research projects.U. S. Air Force Office of Scientific Research (Contract F44620-71-C-0051)Joint Services Electronics Program (Contract DAAB07-71-C-0300)University of California, Livermore (Subcontract No. 7877409)U. S. Army Research Office - Durham (Contract DAHC04-72-C-0044

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

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

Genetics ignite focus on microglial inflammation in Alzheimer’s disease

In the past five years, a series of large-scale genetic studies have revealed novel risk factors for Alzheimer’s disease (AD). Analyses of these risk factors have focused attention upon the role of immune processes in AD, specifically microglial function. In this review, we discuss interpretation of genetic studies.  We then focus upon six genes implicated by AD genetics that impact microglial function: TREM2, CD33, CR1, ABCA7, SHIP1, and APOE. We review the literature regarding the biological functions of these six proteins and their putative role in AD pathogenesis. We then present a model for how these factors may interact to modulate microglial function in AD

Rapid learning of magnetic compass direction by C57BL/6 mice in a 4-armed 'plus' water maze.

Magnetoreception has been demonstrated in all five vertebrate classes. In rodents, nest building experiments have shown the use of magnetic cues by two families of molerats, Siberian hamsters and C57BL/6 mice. However, assays widely used to study rodent spatial cognition (e.g. water maze, radial arm maze) have failed to provide evidence for the use of magnetic cues. Here we show that C57BL/6 mice can learn the magnetic direction of a submerged platform in a 4-armed (plus) water maze. Naïve mice were given two brief training trials. In each trial, a mouse was confined to one arm of the maze with the submerged platform at the outer end in a predetermined alignment relative to magnetic north. Between trials, the training arm and magnetic field were rotated by 180(°) so that the mouse had to swim in the same magnetic direction to reach the submerged platform. The directional preference of each mouse was tested once in one of four magnetic field alignments by releasing it at the center of the maze with access to all four arms. Equal numbers of responses were obtained from mice tested in the four symmetrical magnetic field alignments. Findings show that two training trials are sufficient for mice to learn the magnetic direction of the submerged platform in a plus water maze. The success of these experiments may be explained by: (1) absence of alternative directional cues (2), rotation of magnetic field alignment, and (3) electromagnetic shielding to minimize radio frequency interference that has been shown to interfere with magnetic compass orientation of birds. These findings confirm that mice have a well-developed magnetic compass, and give further impetus to the question of whether epigeic rodents (e.g., mice and rats) have a photoreceptor-based magnetic compass similar to that found in amphibians and migratory birds

Ectosymbionts alter spontaneous responses to the Earth’s magnetic field in a crustacean

Magnetic sensing is used to structure every-day, non-migratory behaviours in many animals. We show that crayfish exhibit robust spontaneous magnetic alignment responses. These magnetic behaviours are altered by interactions with Branchiobdellidan worms, which are obligate ectosymbionts. Branchiobdellidan worms have previously been shown to have positive effects on host growth when present at moderate densities, and negative effects at relatively high densities. Here we show that crayfish with moderate densities of symbionts aligned bimodally along the magnetic northeast-southwest axis, similar to passive magnetic alignment responses observed across a range of stationary vertebrates. In contrast, crayfish with high symbiont densities failed to exhibit consistent alignment relative to the magnetic field. Crayfish without symbionts shifted exhibited quadramodal magnetic alignment and were more active. These behavioural changes suggest a change in the organization of spatial behaviour with increasing ectosymbiont densities. We propose that the increased activity and a switch to quadramodal magnetic alignment may be associated with the use of systematic search strategies. Such a strategy could increase contact-rates with conspecifics in order to replenish the beneficial ectosymbionts that only disperse between hosts during direct contact. Our results demonstrate that crayfish perceive and respond to magnetic fields, and that symbionts influence magnetically structured spatial behaviour of their hosts

The experimental chamber.

<p>Turtles were tested in a Pyrex bowl with water that was ~1 cm deep so the turtle’s shell was not completely submerged. The Pyrex bowl, PVC surround, and overhead diffuser provided uniform visual surroundings.</p

C57BL/6 mice rapidly learn the magnetic direction of a submerged platform in the plus water maze (data in Table S2).

<p>Directional responses from mice given two training trails in the late afternoon (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0073112#pone-0073112-g001" target="_blank">Figure 1A & B</a>), and then tested the following morning (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0073112#pone-0073112-g001" target="_blank">Figure 1C</a>). A) The distribution of topographic bearings, i.e., deviations from the north arm of the maze (topN), was indistinguishable from random (p > 0.10, Rayleigh test). B) The same was true of the distribution of magnetic bearings, i.e., deviations from the alignment of magnetic north in testing (magN). C) In contrast, the distribution of bearings relative to the trained magnetic direction (black triangle) was non-randomly distributed, and the 95% confidence interval for the mean vector bearing contained the trained direction. Each data point is the directional response of a single mouse tested in one of the four magnetic field alignments (see Methods & Methods). Arrow in the center of (C) is the mean vector for distributions of bearings that are non-randomly distributed. The length of the arrow is proportional to the mean vector length (r), a measure of the clustering of bearings ranging from 0 to 1; radius of the circle corresponds to r = 1. Dashed lines show the 95% confidence interval for the mean vector bearing [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0073112#B52" target="_blank">52</a>]. ‘n.s.’- not significant (p > 0.10; Rayleigh Test).</p