The vertebrate retina is comprised of seven major cell types that are generated in overlapping but well-defined intervals. To identify genes that might regulate retinal development, gene expression in the developing retina was profiled at multiple time points using serial analysis of gene expression (SAGE). The expression patterns of 1,051 genes that showed developmentally dynamic expression by SAGE were investigated using in situ hybridization. A molecular atlas of gene expression in the developing and mature retina was thereby constructed, along with a taxonomic classification of developmental gene expression patterns. Genes were identified that label both temporal and spatial subsets of mitotic progenitor cells. For each developing and mature major retinal cell type, genes selectively expressed in that cell type were identified. The gene expression profiles of retinal Müller glia and mitotic progenitor cells were found to be highly similar, suggesting that Müller glia might serve to produce multiple retinal cell types under the right conditions. In addition, multiple transcripts that were evolutionarily conserved that did not appear to encode open reading frames of more than 100 amino acids in length (“noncoding RNAs”) were found to be dynamically and specifically expressed in developing and mature retinal cell types. Finally, many photoreceptor-enriched genes that mapped to chromosomal intervals containing retinal disease genes were identified. These data serve as a starting point for functional investigations of the roles of these genes in retinal development and physiology. Spatial and temporal patterns of expression for over 1000 genes in identified retinal cells invites functional investigations into the role of these genes in development and physiology The vertebrate retina is a model system for studying both the development and function of the central nervous system (CNS). Only six major types of neurons develop within the retina, along with a single type of glial cell . These cThese birthdating studies, together with heterochronic coculture experiments , heterocDrosophila CNS development  to profile gene expression during the development of the mouse retina . SAGE, wBy employing both SAGE-based expression profiling and large-scale ISH analysis to determine cellular expression of developmentally dynamic transcripts, we aim to combine the strengths of these two approaches and obtain a detailed picture of molecular events taking place during development of the retina. The laminar structure of the retina, which allows identification of the major cell types expressing a transcript under examination, makes large-scale ISH particularly informative relative to many other regions of the nervous system.http://134.174.53.82/Cepko/, that is searchable by gene name, SAGE tag sequence, accession number, genome location, or UniGene number. It displays all SAGE tags and their levels, as well as ISH images (see below).SAGE was conducted on mouse retinal tissue taken at 2-d intervals from near the start of neurogenesis at embryonic day 12.5 (E12.5) to nearly the end of neurogenesis at postnatal day 6.5 (P6.5). In addition, libraries were made from P10 wild-type mice and the adult retina. Previously generated SAGE data from the microdissected outer nuclear layer (ONL) of the retina, which comprises roughly 97% rod photoreceptors, from retinal tissue from mice that were deficient for Crx (littermates of the wild-type P10 mice), and from adult hypothalamus were also incorporated into the analysis . All of The accuracy of the SAGE data was assessed by comparing the 15,268 SAGE tags from E14.5 retina to an unnormalized and unsubtracted set of 15,268 ESTs generated by another research group from E14.5 mouse retina of a different strain . An r-vak-means algorithm designed specifically for SAGE data  consists almost entirely of mitotic progenitor cells, while newborn neurons (mostly consisting of amacrine and ganglion cells) reside in the inner neuroblastic layer (INBL). The position of mitotic progenitors within the ONBL varies depending upon their progress through the cell cycle, with S phase cells being found on the vitreal side of the ONBL near the border with the INBL and M-phase cells being found on the scleral side of the ONBL abutting the retinal pigment epithelium a, 1985b.In the developing retina, expression in the scleral and vitreal portions of both the ONBL and INBL were scored separately, along with whether the gene in question was expressed in all or only a subset of cells in the layer in question. In the case of the adult retina, cell identity in wild-type animals could be scored readily by laminar position of the cells expressing the gene of interest , and thuExtracting order from the diversity of gene expression patterns observed in the developing nervous system can be a daunting task. It is not obvious how best to generate a useful taxonomy of these expression patterns. In tackling this problem, we found it useful to classify cellular expression patterns of genes both by eye and by clustering software. Both methods have specific advantages—user classification more readily identifies rare but distinct patterns, while machine-based clustering allows more flexibility with respect to cluster number and appears to better accommodate classification of intermediate patterns. All classifications were based on the location of the ISH signal within the retinal layers over time during development. TRAP2-like, and Nlk-like  were highly likely to be expressed in developing rods. In the case of early-onset gene expression patterns, which would likely be expressed in retinal progenitor cells, comparison to a microarray-based study could be made. Microarray profiling data of 4N progenitor enriched versus 2N cells has led to the identification of a number of these genes as being enriched in 4N progenitor cells . These gIn general, the temporal expression pattern observed in a given SAGE tag cluster was accurately reflected by the ISH data, although precise prediction of cellular expression patterns based on cluster data were not achieved. Clusters that showed postnatal peaks in expression, such as cluster 6, could contain a great diversity of cellular expression patterns, yet still be enriched for genes that showed strong expression in specific cell types that were differentiating. The expression clusters—whether generated by user annotation or clustering software—at best represent a lower limit to the number of distinct expression patterns within the developing retina. Although the number of distinct types of cells in the developing retina is not known, it is undoubtedly high . ParticuRPGRIP showing comparatively early onset of expression, followed by the progressively later onset timesof rod arrestin, rhodopsin, and, finally, Gα1 and GCAP1 (see http://134.174.53.82/cepko/ for the full set of ISH data). Such profiles could be explored for the possibility of control by cascades of transcription factors.One interesting and potentially useful finding from the SAGE cluster data is that genes known to have highly selective cell-specific expression within a single retinal cell type could show different times of onset of expression. For instance, there is heterogeneity in the time of onset of expression among the genes that mediate rod phototransduction, a feature that has previously been reported in ferret retina . PhototrCAP1 see . This heDrosophila neuroblast specification and the specification of neural-crest-derived cells , a number of genes that are expressed in broad but temporally restricted subsets of mitotic progenitor cells were identified A. sFrp2 e retina —and BrdUor cells .3H thymidine labeling at E14, E16, and P0 , along with many genes of other functional classes. Particularly intriguing is the early and transient expression of Pum1, a mammalian homolog of the pumilio gene, which has been shown to mediate asymmetric mRNA distribution in Drosophila  as well as signal transduction components. These intrinsically acting factors represent potential candidates for regulating developmental competence and, by analogy with the Drosophila retina, may act combinatorially to help specify cell fate , which was expressed throughout the ONBL during early development and which was later restricted to Müller glia. It was transcribed in a head-to-head fashion, and largely coexpressed, with Six3. This transcript showed extensive alternative splicing, and while one splice form contained a potential ORF of greater than 100 amino acids, no mouse/human conservation of this putative protein was observed, while high similarity was observed at the nucleotide level in other regions of the transcript. RNCR2 , on the other hand, was expressed in a large subset of cells in both the ONBL and INBL prenatally, with expression restricted to the INL and GCL postnatally. ISH signal for RNCR2 was strongly concentrated in what appeared to be nuclear or perinuclear regions of expressing cells. RNCR3 was expressed in a steadily increasing subset of cells in the ONBL from E14 and gradually resolved to an adult pattern that was photoreceptor-enriched but present in the inner retina at lower levels.A number of RNA transcripts that do not appear to encode proteins were strongly expressed in the developing retina . These tXist and H19 in mammals and Rox1 and Rox2 in Drosophila have been implicated in a variety of epigenetic processes , P8 cerebellar granule precursor cells maintained in culture for 24 h , P8 cerebellar granule precursor cells maintained in culture and treated with Shh for 24 h , freshly harvested P8 cerebellar granule precursor cells . Libraries from E15 and P1 cerebral cortex were obtained from http://www.ncbi.nlm.nih.gov/SAGE.Isolation of mouse brain and retinal tissue, as well as construction of all SAGE libraries derived from retinal and hypothalamic tissue, was conducted as previously described . Publiclhttp://www.ncbi.nlm.nih.gov/SAGE). UniGene Build 131 of Mus musculus (http://www.ncbi.nlm.nih.gov/UniGene) was used for the mappings. In cases where ISH results for genes matching a “reliable” tag did not match the temporal expression profile for the tag in question, along with all cases of unknown tags (i.e., tags which had no “reliable” tag to gene assignment) that were present at greater than 0.1% of total tags in any one SAGE library, the genes were tested via NCBI BLASTN searching (http://www.ncbi.nlm.nih.gov/BLAST/) against the nr and dbest databases, with Expect threshold set to 100  was used to extract SAGE tags and eliminate duplicate ditags. Identity of SAGE tags was obtained from the National Center for Biotechnology Information (NCBI) “reliable” tag map set for UniGene (available at t to 100 . A tag wt to 100 . If no st to 100  were conhttp://genome.ucsc.edu). In cases where no curated ortholog was present in the database, BLASTN analysis against nr, dbest, and htgs databases was used to identify transcripts that showed over 85% sequence conservation over 100 bp and did not match any repeat sequence. The University of California at Santa Cruz genome browser using the October 2003 freeze (http://genome.ucsc.edu/cgi-bin/hgGateway) was used to determine if any transcripts with no obvious coding sequence mapped within 5 kb of the 3′ end of an identified gene and were transcribed in the sense orientation relative to that gene. If so, these were considered to represent novel 3′ ends of that gene. All other data analysis and curation was conducted with Microsoft Excel and Microsoft Access.Human orthologs of mouse genes were identified through the use of the Homologene data set and verified by BLASTN and/or BLASTX analysis using the NCBI server, or BLAT analysis using the University of California at Santa Cruz genome server  in Hank's balanced salt solution (HBSS) containing 10 mM HEPES (pH 7.6), 2.5 mM cysteine, and 0.5 mM EDTA. The suspensions were then gently triturated and incubated with 0.1 mg/ml DNase I for 10 min at 37 °C. The cells were pelleted, washed twice in HBSS, and plated on polyD-lysine-coated glass slides for 15 min at room temperature. Cells were fixed to the slides in 4% paraformaldehyde for 5 min at room temperature, washed twice in PBS, and dehydrated in 100% methanol. For acetylation, probe incubation, and subsequent washings, the in situ protocol detailed herein for tissue sections was used. A tyramide signal amplification system (TSA Plus, PerkinElmer, Wellesey, Massachusetts, United States) combined with an anti-digoxigenin-HRP antibody (Roche) was used according to the manufacturer's instructions to detect the signal. Autoradiographic processing was performed in emulsion (NTB2, Eastman Kodak, Rochester, New York, United States) exactly as previously described  of cellular expression patterns  generated a presumptive minimal classification of expression patterns following visual inspection of each hybridization pattern .k groups. Second, a cluster center, which led to the expected expression pattern of each tag, was calculated for each cluster. Chi-square test statistics were used to measure the distance between the observed expression pattern and the expected expression pattern of a tag in a cluster. Third, using an iterative method, tags were moved between clusters, and intra- and intercluster distances were measured with each move. Tags were allowed to remain in the new cluster only if they were closer to it than to their previous cluster. Fourth, after each move, the expression vectors for each cluster were recalculated. Last, the shuffling proceeded until moving any more tags made the clusters more variable, increasing intracluster distances and decreasing intercluster dissimilarity . Information on the measurement values for the SAGE libraries and ISH images can be accessed at http://134.174.53.82/cepko/. The database was developed to provide up-to-date mapping of SAGE tags to UniGene clusters. Since a single sequence tag can represent different genes and, conversely, an individual UniGene cluster can be represented by more than one tag, both “full” and “reliable” tag-to-UniGene mappings (http://www.ncbi.nlm.nih.gov/SAGE). For the database reported herein, UniGene Build 131 of Mus musculus and Build 164 of Homo sapiens (http://www.ncbi.nlm.nih.gov/UniGene) were used for the mappings. However, the database at http://134.174.53.82/cepko/ includes up-to-date mapping data. For each UniGene cluster, all measurement values and ISH images of associated tags are provided. Measurement values can also be segregated and summed up for each library if more than one SAGE tag is mapped to a given UniGene cluster. A plot of measurement values was also created to visualize patterns across the SAGE libraries. Additionally, for each UniGene cluster, links to gene functions using GO, accession numbers for annotated human orthologs, and LocusLink IDs have been provided.Data from 21 SAGE libraries and ISH images were gathered and stored in a MySQL relational database .Click here for additional data file.Figure S2rod arrestin, PrCdh, Gγ1, rod PDEγ, rhodopsin, peripherin 2, Gα1, and GCAP1.The genes shown are (26.9 MB TIF).Click here for additional data file.Figure S3Otx2, RORβ, Yboxbp1, Mm.38347, Mm.11660, BTF3, H2Ax, Ppp1r14b, Grb10, Mm.158631, HMG-AT1, Mm.24141, KIAA1411, Mm.25018, IAP5, and Chaf1b.Sections were from central retina. The genes shown are (25.7 MB TIF).Click here for additional data file.Figure S4PDK3, Giα2, β-catenin, LRC8, Nrarp, Foxn4, and HMG-17.The genes shown are (27.4 MB TIF).Click here for additional data file.Figure S5FABP7, BMP7, NTT7, Inhibin βB, and Sal3.The genes shown are (20.8 MB TIF).Click here for additional data file.Figure S6NeuroD1, Crx, Nrl, and NR2E3.These data are shown to allow direct comparison with the data in (24.9 MB TIF).Click here for additional data file.Figure S7Cpx2, TRABID, Fln29, Mak, Mm.24642, Nlk, Hrs, Tnfsf13, and Arip2.The genes shown are (18.3 MB TIF).Click here for additional data file.Figure S8Chx10, Gli5, Dbp, Lhx4, Mm.41284, Prkcl, SEZ-6, and Zfh4.The genes shown are (21.4 MB TIF).Click here for additional data file.Figure S9Borg4.The gene shown is (11.0 MB TIF).Click here for additional data file.Figure S10Unc-51-like-1, ArfGAP, robo3, necdin, SAK, Mm.6393, Mm.34130, Nhlh2, NPY, Mm.21657, Mm.215653, and Mm.41638.The genes shown are (19.1 MB TIF).Click here for additional data file.Figure S11KIAA0937, Mm.157502, Slc38a3, Nkd1, Dsp8, carbonic anhydrase 2, and cyclin D1.The genes shown are (40.1 MB TIF).Click here for additional data file.Figure S12MEG3, Xist, and Tsix.The genes shown are (13.6 MB TIF).Click here for additional data file.Protocol S1(52 KB DOC).Click here for additional data file.Table S1−/−crx animals, and the library from microdissected ONL of adult animals) is shown. The number of tags, and the fraction of total tags, that do not show any reliable match for any gene (data from NCBI) are also shown.The total cumulative number of tags found at each abundance level in all 12 retinal libraries .Click here for additional data file.Table S2This list includes not only all libraries made from retinal tissue, but also nonretinal SAGE libraries made by this group, and other mouse libraries that are publicly available. Raw, unnormalized tag counts are shown. See (17.9 MB TXT).Click here for additional data file.Table S3http://www.ncbi.nlm.nih.gov/SAGE) is shown, along with the confidence level of that assignment. Mouse UniGene number is shown for each tag-to-gene match, along with LocusLink ID, where available. In each case where a gene was analyzed by ISH in developing retina, that fact is indicated in the final column. In some cases, a gene that matched the tag with a lower confidence level was tested. In these cases, the UniGene number of the gene tested by ISH differs from that of the most probable tag match.All tag abundance levels were normalized to 100,000. Tags present at greater than 0.1% in one or more of the ten wild-type total retina libraries were considered. The single most probable “reliable” tag-to-gene match ((1.0 MB XLS).Click here for additional data file.Table S4Gene names and LocusLink IDs for these genes are also shown(225 KB XLS).Click here for additional data file.Table S5The SAGE tag matching each gene tested is given, as well as the accession number of the cDNA used to generate each probe used for ISH. Cellular expression is scored on a 0–5 point scale for each time point tested, as well as for E16 embryo and P6 head cut in horizontal section. A, amacrine cells; Ast, astrocytes; B, bipolar cells; Bv, blood vessels; Cb, cerebellum; CM, ciliary margin; CP, cortical plate; Ctx, cerebral cortex; DG, dentate gyrus of hippocampus; DRG, dorsal root ganglia; EGL, external granule layer of developing cerebellum; EOM, extraocular muscles; G, ganglion cells; H, horizontal cells; Hippo, hippocampus; I, inner neuroblastic layer; In, inner nuclear layer; MG, Müller glia; MGE, medial ganglionic eminence; ND, not determined; O, outer neuroblastic layer; OB, olfactory bulb; OE, olfactory epithelium; ORN, olfactory receptor neurons; P, panretinal; PC, Purkinje cells; PNS, peripheral nervous system; Pr, photoreceptors; Pr(is), inner segments of photoreceptors; sA, subset of amacrine cells; sB, subset of bipolar cells; SC, spinal cord; sG, subset of ganglion cells; sI, subset of cells in INBL; sIn, subset of cells in INL; scI, scleral INBL; sscI, subset of cells in scleral INBL; svI, subset of cells in vitreal INBL; sO, subset of cells in outer neuroblastic layer; scO, scleral ONBL; sscO, subsets of cells in scleral ONBL; svO, subset of cells in vitreal ONBL; sPr, subset of photoreceptors; SVZ, subventricular zone; vI, vitreal INBL; vO, vitreal ONBL; VRN, vomeronasal receptor neurons; VZ, ventricular zone.(381 KB XLS).Click here for additional data file.Table S6Here, data from (261 KB XLS).Click here for additional data file.Table S7To obtain these numbers, data from (266 KB XLS).Click here for additional data file.Table S8The fraction listed notes the fraction of genes in the machine-generated cluster that were found in a given user-curated cellular expression cluster. The presumptive cellular expression pattern of each user-curated cellular expression cluster is also listed (following (86 KB XLS).Click here for additional data file.Table S9Shown is the percentage of tags that matched genes enriched in 4N retinal progenitor cells found in a given SAGE tag cluster.(14 KB XLS).Click here for additional data file.Table S10Values indicate the fraction of all tags found in a given SAGE tag cluster that were found in a specific user-curated cellular expression cluster. The presumptive cellular expression pattern of each cellular expression cluster is also listed (following (209 KB XLS).Click here for additional data file.Table S11Tags in each library are expressed as the fraction of all tags that match the gene in question that were found in the ten libraries considered.(15 KB XLS).Click here for additional data file.Table S12P-values for BLASTN and BLASTX mouse/human comparisons are shown. Transcripts that show high BLASTN, but low BLASTX, matches to human may represent the best candidates for noncoding mRNAs of functional importance and are indicated as likely to be genuine noncoding RNAs. NS, not significant.The SAGE tag corresponding to the transcript in question is listed, along with UniGene numbers, and accession numbers of the probes used for ISH for each candidate noncoding RNA. (17 KB XLS).Click here for additional data file.Table S13http://www.sph.uth.tmc.edu/Retnet/disease.htm). User-curated cellular expression data of the genes in question .Click here for additional data file.Table S14k-means clusters over all variables. Euclidian mean distance–directed clustering is used (Ni − N(i – 5))/Ni, where N is the average within-cluster distance and i is cluster number.The values shown here are the average sum-of-squares within  is used . The pro is used . For thi(14 KB XLS).Click here for additional data file.Table S15k-means clusters for each number of clusters is shown. The PRE, given by (Ni − N(i – 5))/Ni, is also shown.Tags present at greater than 0.1% in one or more of the ten wild-type total retina libraries were considered and were normalized to 100,000 for this analysis. The average sum-of-squares within (14 KB XLS).Click here for additional data file.www.ncbi.nlm.nih.gov) accession numbers for the genes discussed in this paper are β-catenin (NM_007614), ArfGAP (BC030682), Arip2 (NM_025292), BMP7 (NM_007557), Borg4 (NM_012121), brain fatty acid binding protein 7 (NM_021272), BTF3 (NM_145455), carbonic anhydrase 2 (NM_009801), cdk4 (NM_009870), Chaf1b (NM_028083), Chx10 (NM_007701), Cpx2 (NM_007756), Crx (NM_007770), Dbp (NM_016974), Drosophila castor gene (BC035954), Dsp8 (XM_181424), FABP7 (NM_021272), Fln29 (NM_172275), Foxn4 (NM_148935), GCAP1 (NM_008189), Giα2 (NM_008138), Gli5 (NM_031184), Grb10 (NM_010345), Gα1 (NM_008140), Gγ1 (NM_010314), H2Ax (NM_010436), HMG-17 (NM_016957), HMG-AT1 (NM_016660), Hrs (NM_008244), IAP5 (NM_009689), inhibin βB (BC048845), KIAA0937 (NM_172442), KIAA1411 (NM_026604), Lhx4 (NM_010712), LRC8 (NM_172736), Mak (NM_008547), MEG3 (NM_144513), Mm.103742/Cdc42GAP (NM_020260), Mm.11660 (AK034313), Mm.11738/Ark-1 (BC005425), Mm.142856/Lhx2 (NM_010710), Mm.150838/RNCR1 (AK044330), Mm.157502 (NM_026592), Mm.158631 (XM_132295), Mm.1635/PIAS3 (NM_018812), Mm.18789/Sox4 (NM_009238), Mm.19155/sFrp2 (NM_009144), Mm.193526/Yboxbp4 (NM_007705), Mm.194050/RNCR3 (AK044422), Mm.200608/clusterin (NM_013492), Mm.20465/GPCR37 (NM_010338), Mm.213213/HK-R (NM_145419), Mm.215653 (NM_183191), Mm.21657 (BC038057), Mm.2214/septin 4 (NM_011129), Mm.22288/cyclin D1 (NM_007631), Mm.2229/Eya2 (NM_010165), Mm.235550/ERRβ (NM_011934), Mm.23916 (AK009781), Mm.24141 (NM_025615), Mm.24642 (NM_146168), Mm.25018 (BC010304), Mm.26062/AD024 (NM_025565), Mm.27953/glycine decarboxylase (NM_138595), Mm.29067/Mbtd1 (NM_134012), Mm.29496/Zf-1 (AK004085), Mm.29729/Tweety1 (NM_021324), Mm.29924/Arl6ip1 (BC010196), Mm.34130 (AK012601), Mm.34701/Pum1 (NM_030722), Mm.3499/Rax homeodomain factor (NM_013833), Mm.35817 (NM_145940), Mm.35829/Edr (NM_133362), Mm.38347 (XM_126644), Mm.3904/Fgf15 (NM_008003), Mm.40321/Pgrmc2 (XM_130859), Mm.41284 (NM_153137), Mm.41638 (NM_029530), Mm.44854/RNCR2 (AK028326), Mm.4541/Sox2 (NM_011443), Mm.45753/KIAA0013 (NM_181416), Mm.4605/Tbx2 (NM_009324), Mm.5021/DDR1 (NM_007584), Mm.55143/Dkk3 (NM_015814), Mm.6393 (NM_010045), Mm.89623/mCas ( BC035954), Mm.9114/mu-crystallin (NM_016669), necdin (NM_010882), NeuroD1 (NM_010894 , Neuropeptide Y (NM_023456), Nhlh2 (NM_178777), Nkd1 (NM_027280), Nlk (NM_008702), NPY (NM_023456), NR2E3 (NM_013708), Nrarp (NM_025980), Nrl (NM_008736), NTT7 (NM_175328), Otx2 (NM_144841), PDK3 (NM_005391), peripherin 2 (NM_008938), Ppp1r14b (NM_008889), PrCdh (NM_130878), Prkcl (NM_008857), RGPRIP (NM_023879), rhodopsin (NM_145383), robo3 (NM_011248), rod arrestin (NM_009118), rod PDEγ (NM_012065), RORβ (NM_146095), SAK (NM_019945), Sal3 (NM_026528), SEZ-6 (NM_021286), Slc38a3 (NM_023805), syntrophin-associated kinase (NM_019945), Tnfsf13 (NM_023517), TRABID (AK005926), Tsix (AF138745), Unc-51-like-1 (NM_009469), Xist (AK011511), Yboxbp1 (NM_011732), and Zfh4 (NM_030708).The GenBank (


The genetics of plumage of Japanese quail is of interest both from a biological standpoint, for comparative studies between avian species, and from a zootechnical standpoint, for identifying commercial selection lines or crosses. There are only few plumage mutations reported in quail, and the present work describes a new color variant "rusty" and a new feather structure "curly", and their heredity from an F1 and F2 segregation experiment.Curly feathers result from abnormal early growth caused by transient joining of follicle walls of adjacent feathers around 10 days of age, but the expression of the trait is variable. Rusty plumage color results from the replacement of the wild-type plumage pattern on the tip of the feather by a reddish coloration, but the pigmentation of the bottom part of the feather is not affected. Two lines breeding true for the curly or the rusty phenotype were developed. Both characters are determined by autosomal recessive mutations which are independent. The curly mutation has also a positive effect on body weight at 5 weeks of age.The curly line is a new model which may be used for further work on the growth of the feather, and the rusty mutation is a new addition to the panel of plumage mutations available for comparative studies in poultry, and more generally among avian species. Japanese quail is both a model animal in biology and a bird used for meat and egg production under a large variety of settings . In the In the present work, a new feather structure phenotype (curly) and a new plumage color (rusty) were described, and their mode of inheritance and linkage were studied in two successive generations (F1 and F2) from an F0 made of eight quail with curly feathering and eight birds with rusty plumage. Growth of the F2 quail was also monitored and compared according to their phenotype for the two plumage mutations.The quail line with the curly feathers was developed in 2001 from group mating 6 founding (G0) curly quail. Starting in G3, only quail for which the curly phenotype observed at 10 days of age was expressed most strongly were kept for breeding. No differential survival was observed in curly quail after hatching, but the hatching rate in the fixed line at G5 under pool mating was only 34%, mainly because some females did not get mated under this type of mating. In curly chicks, the calamus of the growing wing feathers are not independent from one another, but they are connected through the follicle walls which appear to be joined together. This phenomenon is best observed around 10 days of age and is associated with the curly growth  made of a single rusty female bred to a wild-type male from another origin. It was followed by sib mating of the all wild-type G1 quail to produce G2 and G3 pedigreed progeny and selection of the few rusty G4 birds. Survival rate to sexual maturity of the rusty descendance of the early generations was poor, and reproductive performance was low (hatched/incubated = 31%) in the fixed line under pool mating at G6, because of the mating system but also of inbreeding derived from having a single rusty ancestor. The plumage of the mutant chicks was rusty, but the down underneath retained the usual wild-type dark-slaty color. A similar color pattern was maintained in rusty adults: their contour and flight feathers had dark barbs on the bottom and rusty colored barbs on the top third of their length which produced the overall rusty look  in Table 2s were high enough (p > 0.05 and p > 0.1, respectively). The maximum likelihood estimation of the penetrance parameter (± SE) was 1-λ = 0.83 (± 0.07) which indicates that 17% of F2 curly quail might have been misclassified as wild-type birds. This result is consistent with the observation that the expression of the curly trait was variable, and it would account for the relative deficit of curly birds in the F2. Overall, however, the segregation of the F2 results fits a simple two-locus Mendelian inheritance of two autosomal recessive and independent mutations.All 68 F1 quail were wild-type birds, confirming that both mutations should be recessive, and not sex-linked. Four phenotypes were obtained in the 531 F2 progeny: 326"wild-type", 95 "rusty", 79 "curly" and 31 "rusty and curly"  were set up with G5 rusty and G4 curly quail from the two pure lines to produce the F1. Then, 531 F2 birds were produced in three consecutive hatches from 17 single pair matings of F1 birds. Sib-mating was avoided, and the hatching rate across all pair matings and hatches was 81%. All chicks were pedigreed, and they were phenotyped for plumage color at hatching and for feather structure at 10 days of age. F2 quail from the first two hatches were raised in two group pens (one per hatch) with free access to ad libitum commercial feed and drinking water, and they were weighed weekly until 5 weeks of age.Gene nomenclature used in this paper followed recommendations published for chicken genes , with a 2 test [3) + bd/(b+d)3, derived for misclassification of phenotypes due to "partial manifestation" [Analysis of the segregation in the F2 to test for linkage was carried out using maximum likelihood methodology and the χ2 test . Penetrastation" . In the Five-way analyses of variance of individual body weights (BW) between hatching and 5 weeks of age were carried out by the GLM procedure  for the FM coordinated the study and wrote the paper, DG and CM participated in the design of the study and carried out the the data collection.


Bombyx mori to produce textiles. In contrast, despite the more promising properties of their silk, spiders have not been domesticated for large-scale or even industrial applications, since farming the spiders is not commercially viable due to their highly territorial and cannibalistic nature. Before spider silks can be copied or mimicked, not only the sequence of the underlying proteins but also their functions have to be resolved. Several attempts to recombinantly produce spider silks or spider silk mimics in various expression hosts have been reported previously. A new protein engineering approach, which combines synthetic repetitive silk sequences with authentic silk domains, reveals proteins that closely resemble silk proteins and that can be produced at high yields, which provides a basis for cost-efficient large scale production of spider silk-like proteins.Since thousands of years humans have utilized insect silks for their own benefit and comfort. The most famous example is the use of reeled silkworm silk from  Spiders and silks always go together. Currently there are over 34,000 described species of spiders, all of which have a varied tool kit of task-specific silks with divergent mechanical properties -6. Altho9 N/m2) coupled with a reasonable viscoelasticity (dragline 35 %, Kevlar 5 %). Spiders use dragline silk as a strong yet flexible structural element in the web, providing a framework to which other silks are attached, and as a life line when a spider is dropping off to escape an enemy. Minor ampullate (MI) silk, used for structural reinforcement in construction of the web, has a similar high tensile strength in comparison to major ampullate silk but has little elasticity [Among the various spider silks the major ampullate (MA) silk, which forms the primary dragline, is extremely tough. MA silk reveals a tensile strength that is comparable to Kevlar  and from Araneus diadematus ADF-3 and ADF-4 (Araneus Diadematus Fibroin). The dragline silk proteins have apparent molecular masses between 180 kDa and 720 kDa depending on the conditions of analysis [Spider silks are protein polymers that display extraordinary physical properties -4,8, butproteins ,10-13 ananalysis -16. It ianalysis ,17.n or (GA)n), GGX, and spacers  Figure . The smas Figure . A fifths Figure , often rNephila clavipes n motif. Interestingly, this motif is not found in flagelliform silks. A glycine-rich 31-helix is adopted by the GGX motif forming an amorphous matrix that connects crystalline regions and that provides elasticity [On the basis of several studies, the major categories of peptide motifs in spider silk proteins have been assigned structural roles -28. The asticity ,33,34. Tasticity ,35,36. Tasticity . Recent asticity ,36,38.in vivo is a remarkable process. For instance, dragline silk proteins are stored at concentrations up to 50 % (w/v) in the respective glands [Silk assembly e glands . This hie glands -42. There glands ,43,44.Thread assembly is initiated during a passage of the silk dope through the spinning duct accompanied by extraction of water, sodium and chloride ,46. SimuAraneus diadematus, ADF-3 and ADF-4, revealed that, although their amino acid sequences are rather similar [While some aspects of spider silk assembly have been unraveled, the contribution of the individual silk proteins to the assembly process still needs to be resolved in more detail. Comparative studies of the two major dragline silk proteins of  similar , they di similar , ADF-4 i similar . At a cl similar .Laboratory-scale production of spider silk would initiate a new generation of ecological materials. Spider silk is for instance a promising tool with broad usability in medical devices. In the middle ages spider webs were used as wound dressing – some reports are even dated back to ancient Greek and Roman cultures. Silkworm silk does not cause allergic reactions and it is thought that spider silk behaves similarly . The unmgc-content, by the length of the constructs, and by the specific codon usage of spiders. In first studies, in vitro translation of mRNA from excised major ampullate glands of Nephila clavipes was performed using tRNA from E. coli, but translation was discontinuous [Nephila clavipes and Araneus diadematus and other spiders have been reported [E. coli [Spodoptera frugiperda using the baculovirus expression system [Recombinant production of spider silk proteins has been complicated by the highly repetitive nature of the underlying genes, by their high ntinuous ,54. In treported ,11,20-22[E. coli , in MAC-[E. coli , or in in system . The mosPichia pastoris and mainly E. coli have been utilized as expression hosts for synthetic genes yielding proteins with up to 150 kDa [Cloning strategies for designing genes for bacterial, yeast or plant expression have been developed to produce recombinant silk-like proteins closely resembling natural dragline ,36,56-62 150 kDa ,56-62. U 150 kDa . Althoug 150 kDa , large l 150 kDa ,56,59,60 150 kDa ].Araneus diadematus were chosen as templates for the synthetic constructs. A seamless cloning strategy [In a recent study, genes coding for spider silk-like proteins were generated using a cloning strategy, which was based on a combination of synthetic DNA modules and PCR-amplified authentic gene sequences Figure  36]. Th. Th36]. strategy  allowed gg (sense) and cc (antisense) were used for connecting two modules . Glycine is naturally abundant in spider silk proteins (~30%), therefore modules could be designed to match authentic amino acid sequences. Since the arrangement of the cloning cassette's elements remained unchanged upon cloning, repeat units could be multimerized to generate synthetic genes coding for the repetitive proteins (rep-proteins) (AQ)12 and (QAQ)8 . Therefore, the established bacterial expression system provides the basis for cost-efficient large scale production of spider silk-like proteins.A-values [Sf9 cells  used for producing ADF-4 corresponds to the pH in the spinning dope prior to silk thread assembly [Sf9 cells [adf-4 expressing cells revealed filaments that coiled throughout the cytoplasm, whereby most of the cells contained only one or few filaments. In contrast, Sf9 cells infected with control viruses or the adf-3 encoding virus never produced such filaments. The diameter of the ADF-4 filaments (0.2 – 1.5 μm) was in the range of native dragline silks (1.0 – 4.0 μm), but length of the filaments formed in the Sf9 cells seemed to be constrained by the volume of the cells, making them too short for mechanical force measurements. Strikingly, the purified ADF-4 filaments  in the dope without apparent aggregation or assembly. However, spider silk proteins can rapidly assemble into highly stable fibers when needed. The determination of solubility and self-assembly of recombinant spider silk proteins is therefore important to create commercially available silk fibers. For instance, pH-shifts are involved in natural silk assembly, but the exact function of acidification during spider silk assembly has not yet been determined. It seems likely that negatively charged groups are protonated reducing the net charge of spider silk proteins. Phosphoryl groups of phosphorylated amino acid residues, which have been detected in dragline silk , displayA-values  near theA-values . Interes% w/v in s Figure  showed aPhosphate, like other lyotropic ions, is known to increase the surface tension of water, promoting hydrophobic interactions . In the in vitro several aspects have to be taken into account to gain materials with expected properties.A remaining critical step concerning commercial production of silk fibers is the successful spinning of recombinant proteins into fibers resembling the natural silks in their microstructure and in their mechanical properties, which are outstanding by any measure. Besides the chemical parameters discussed above, several mechanical parameters play important roles in generating silk. To draw silk under natural spinning conditions, spiders attach their dragline to an object with glue from the piriform glands, before drawing the silk out by moving away or by descending and using their weight to draw the silk. It is common practice to take advantage of the drawing process by the forced silking of captive animals to collect silk for experiments. Analysis of the differences between naturally and forcibly spun dragline silk provided evidence for discrepancies in their material properties ,68,69. FBombyx mori [Nephila clavipes was wet-spun [Nephila fibers [Several attempts are reported in the literature and even more have been performed to wet-spin recombinant spider silk proteins. In a first attempt, microfabricated spinnerets were constructed using silicon microfabrication methods -73. Thesbyx mori , before wet-spun . The diawet-spun . Other awet-spun ,74. Theswet-spun . Howevera fibers , but lowa fibers .The future objective might not be to prepare identical copies of natural silk fibers, but rather to capture its key structural and functional features in designs that could be useful for engineering applications Figure . Using "Since the physical and chemical properties of bio-polymers and their assembly processes depend on the amino acid composition of the underlying polypeptide, engineering "synthetic" proteins with specific structural features will create a new class of fibrous proteins. However, to design new biomaterials based on spider silk, all properties of the underlying proteins have to be analyzed and in the best case successfully mimicked . Therefo


The inferior colliculus, which receives almost all ascending and descending auditory signals, plays a crucial role in the processing of auditory information. While the majority of the recorded activities in the inferior colliculus are attributed to GABAergic and glutamatergic signalling, other neurotransmitter systems are expressed in this brain area including opiate peptides and their receptors which may play a modulatory role in neuronal communication.3H]GABA from rat inferior colliculus slices. DAMGO ([D-Ala(2), N-Me-Phe(4), Gly(5)-ol]-enkephalin) but not DADLE ([D-Ala2, D-Leu5]-enkephalin or U69593 has the same effect as morphine indicating that μ rather than δ or κ opioid receptors mediate this action. [3H]GABA release was diminished by 16%, and this was not altered by the protein kinase C inhibitor bisindolylmaleimide I. Immunostaining of inferior colliculus cryosections shows extensive staining for glutamic acid decarboxylase, more limited staining for μ opiate receptors and relatively few neurons co-stained for both proteins.Using a perfusion protocol we demonstrate that morphine can inhibit KCl-induced release of [The results suggest that μ-opioid receptor ligands can modify neurotransmitter release in a sub population of GABAergic neurons of the inferior colliculus. This could have important physiological implications in the processing of hearing information and/or other functions attributed to the inferior colliculus such as audiogenic seizures and aversive behaviour. Sounds are first converted into neuronal signals in the inner ear and then conveyed to the cerebral cortex via a number of discrete brain areas including the inferior colliculus. Each of these areas receives ascending pathways carrying signals from one or both ears and descending pathways from higher brain centres. The current knowledge of the neurochemical events occurring at each of these brain centres is limited ,2. In thThe neuronal communication occurring in the inferior colliculus is likely to be influenced by modulatory systems such as those of peptidergic neurotransmitters. Opiate receptor gene expression, immunoreactivity and activity in the inferior colliculus have been described -10 althoThree classes of opiate peptides endorphins, dynorphins and enkephalins activate μ, κ and δ-opiate receptors subtypes respectively . Recentl3H]GABA from inferior colliculus slicesIn previous work we have established the presence and distribution of opiate receptors in the adult and developing rat cochlea suggesting that the opiate system has a role in hearing function ,18. In o3H]GABA were perfused for 30 min and stimulated twice with 25 mM KCl to elicit neurotransmitter release. The eluate was collected in 1 ml fractions and the released radioactivity was assessed by scintillation counting. Figure Inferior colliculus slices pre-incubated with [3H]GABA release is shown in Figure 3H]GABA release from the inferior colliculus slices. The effect of 1 μM morphine was antagonised by the antagonist naloxone (10 μM) which was perfused from one fraction before the addition of morphine. The perfusion of naloxone alone did not cause a significant effect on [3H]GABA release. These data strongly indicate that morphine modulates the release of [3H]GABA via activation of opiate receptors. The reduction in [3H]GABA release calculated as the change in S2/S1 ratios in the presence and absence of morphine during S2 was 16% (p < 0.01). These data agree with previous reports on the presence of both GABA neurons and opiate receptors and peptides in the inferior colliculus [The effect of different concentrations of morphine on KCl-induced [lliculus . In addi3H]GABA release, morphine was substituted by either 1 μM DAMGO, DADLE or U69593 which specifically activate μ, δ and κ opiate receptors respectively  indicating that only μ opioid receptors participate in the regulation of GABA release. Higher concentrations of DAMGO (5 μM) did not have greater effects on [3H]GABA release (not shown). Data from our lab (unpublished) and from others [In order to establish which of the opiate receptor subtypes are involved in the modulation of the HGABA relm others  indicate3H]GABA release (16%) could be that during the exposure to opiate agonists, down-regulation of the opiate receptors may occur [3H]GABA release. While there is no direct proof that BIM had its reported effect on the tissue, the data indicate that receptor desensitisation may not be the cause of the relatively low percentage effect of morphine.A possible explanation for the relatively low effect of opiate agonist on [ay occur . To addray occur ,21 and tay occur ,23. Beca3H]GABA release by opiate agonists may be the limited number of GABAergic neurons that express opiate receptors. To address this question inferior colliculi slices were double labelled with guinea pig antibodies against μ-opioid receptors and with rabbit antibodies against glutamic acid decarboxylase (the enzyme uniquely responsible for the synthesis of GABA) Species specific secondary antibodies conjugated to red and green fluorochromes allowed the detection of both antigens on the same slide  reduction of [ide Fig. . Althoug3H]GABA release via activation of the μ-opiate receptor subtype. The amount of [3H]GABA released in presence of opiate agonists was 16% lower than in control slices. This relatively low level of decrease is probably not due to receptor desensitization occurring during the assay but rather to a relatively small population of GABAergic neurons in the inferior colliculus expressing μ-opiate receptors. The small effect of the opiate compounds could also indicate that modulation of GABA release is not their major role, but it could still be of physiological significance.This study has demonstrated that in the rat inferior colliculus slices opiate agonists can inhibit KCl-induced [Together with its reported role in audiogenic seizures and aversive behaviour, the inferior colliculus is an important neuronal centre for auditory processing containing both ascending and descending fibres. The identification of the role of opiate peptides and possibly other modulatory system in the inferior colliculus and other areas of the auditory pathway may allow a better understanding of the mechanism of the hearing system and possibly offer a target for therapeutic intervention in hearing dysfunction. Alternatively, elucidation of the role opiate peptides in the inferior colliculus could provide information about regulation of audiogenic seizures and aversive behaviour.) Krebs carbonate buffer: NaCl 118 mM, KCl 4.84 mM, CaCl2 2.4 mM, NaHCO3 25 mM, MgSO4 1.8 mM KH2PO4 1.2 glucose 9.5 mM.Opiate agonist and antagonists, (Morphine, DAMGO [d-Ala(2), N-Me-Phe(4), Gly(5)-ol]-enkephalin, DADLE [D-Ala2, D-Leu5]-enkephalin, U69593 and naloxone were purchased from SIGMA, UK. Antibodies against μ-opiate receptor AB1774  and glutamic acid decarboxylase AB1511  and species specific pre-absorbed secondary antibodies (donkey anti rabbit IgG FITC and donkey anti guinea pig IgG rhodamine) were purchased from Chemicon UK. Both antibodies were raised against synthetic peptides, and have been used in several immunocytochemical investigations of rat tissue. ,25 AB151Sprague Dawley rats, approximately 200 g, were obtained from UCL Biological Services. All animal experiments were carried out in accordance to the Animal (Scientific Procedure) Act 1986, UK.Rats were stunned and killed by cervical dislocation. The skull was opened and the whole brain removed. The inferior colliculus was dissected out by two coronal transections, the first between the cerebellum and the inferior colliculus and the second between the inferior colliculus and the superior coliculus. The slice was placed horizontally and medullar tissue ventral to the inferior colliculus was removed. The inferior colliculus was then placed on a tissue chopper and sliced into 250 μm coronal sections. Individual slices were separated under a dissecting microscope in Krebs buffer.2 / 5% CO2) Krebs buffer containing GABA transaminase inhibitor aminooxyacetic acid (100 μM) at 32°C for 5 min [3H]GABA was added to give a final concentration of 11 nM and incubated in a shaking water bath for 30 min. Slices were distributed into 6 superfusion chambers between filter papers (Brandel Superfusion System) and perfused at 0.5 ml/min with oxygenated Krebs buffer. Following a 30 min perfusion required to reach a steady state (non-stimulated) [3H]GABA release, 2 min fractions (1 ml) were collected. In order to evoke sub-maximal GABA release the slices were perfused for 2 min with 25 mMKCl at 6–8 min and 22–24 min of the fractionation time (fraction 4 and 12). At the end of each experiment (17 fractions) the tissue and the filter papers were collected and incubated with 500 μl Soluene-350 for 20 min and neutralised with 200 μl of glacial acetic acid. Scintillant (Packard, Ultima Gold, 3 ml) was added to all tissue samples and eluted fractions and the radioactivity was measured by scintillation counting . Each drug treament was repeated in several experiments as indicated in the figures and the ratios of the S2/S1 peaks were averaged. Statistical significance of the effect of treatments was analysed by one way ANOVA using Excel (Microsoft, USA)As previously described, slices were incubated in 5 ml oxygenated (95% 0or 5 min . [3H]GAB2HPO4.7H2O, 1.4 mM KH2PO4 pH 7.3) for 1 hour, washed 3 times in PBS and incubated overnight at 4°C in 30%sucrose in PBS. Coronal sections (20 μm) were cut with a cryostat and collected on poly-lysine coated glass slides and allowed to dry. The sections were blocked in 10% normal donkey serum diluted in PBS containing 0.25% bovine serum albumin and 0.1% Triton X-100 (PBS-A) for 30 min at room temperature. Subsequently, they were incubated for 12 hours at 4°C with the combination of primary antibodies (rabbit anti GAD and guinea pig anti mu opioid receptor) diluted 1:500 in PBS containing 1% bovine serum albumin and 0.3% Triton X-100 (PBS-B).. Slides were washed 3 × 10 min with PBS-B and incubated with secondary antibodies diluted 1:200 in PBS-B, for 2 hours at room temperature. The secondary antibodies used were donkey anti rabbit conjugated with fluorescein (AP182F) and donkey anti guinea pig conjugated with rhodamine (AP182R). Finally, the sections were rinsed in PBS-B for 10 min and in PBS for 2 × 10 min and then mounted in Citifluor (Agar). The immunoreactivity was visualized under the confocal microscopy (LSM 510 META Carl Zeiss, Germany).Inferior colliculi were dissected as decribed above and fixed in 4% paraformaldehyde in phosphate buffer saline (PBS: 137 mM NaCl, 2.7 mM KCl, 4.3 mM NaWT carried out the majority of the experiments, NJ carried out initial experiments and established assay conditions, JC provided expertise in neurotransmitter release studies and participated in the design of the study and analysis of the data, PP provided expertise in the double labelling studies, HD, AF and PG participated in the design of the study and analysis of the data, SOC conceived of the study and participated in its design and coordination. All authors read and approved the final manuscript.


What Is Life?, Erwin Schroedinger concluded that life depends in large part on storing and processing information. For genetic material to carry the diverse instructions required for living processes, he proposed, it must be stored in an aperiodic crystal. Just nine years later, it was clear that DNA is indeed an aperiodic crystal and that genetic information is conveyed through this irregular pattern. Much like computers, biological systems are programmed to follow a precise set of rules, or algorithms, to store information and solve problems. These biological algorithms direct all manner of biochemical processes to create complex patterns and structures by chemically modifying and assembling individual components.In his seminal exploration of the properties of living organisms, Of course, cells use biochemical circuits not electronic circuits. Single tubulin proteins, for example, follow precise rules of chemistry and physics to spontaneously self-assemble, or polymerize, into the microtubules essential for cell transport and motility. The proteins' binding interactions effect rules that specify how the pieces fit together to form the resulting structure. They also specify when and how tubulins assemble from a nucleation complex—a molecular algorithm governing the logic of polymerization. These complex structures self-assemble with remarkably few mistakes. Though considered quite simple, little is understood about the principles that govern programmable structural order underlying this type of spontaneous self-assembly.In crystals, the simplest example of spontaneous self-assembly, subunits of the whole are arranged in a repeating pattern that extends indefinitely in all directions. If you know the position of one unit in the pattern, you can tell the exact position of every other unit. In a new study, Rothemund and colleagues use DNA to show that crystal growth can be programmed to create specific aperiodic patterns. Inspired by a model of crystal growth as a computational process, they have programmed DNA molecules to act as molecular building blocks, arranging themselves according to local rules that in turn create a complex global pattern. The resulting two-dimensional structures, which self-assemble from knotted DNA complexes , grow to create a fractal pattern known as a Sierpinski triangle. These DNA structures—neither periodic (as in quartz), nor random (as in glass), nor pseudorandom —demonstrate a form of self organization in crystalline materials determined by programmable growth rules, and are hence dubbed “algorithmic crystals.”How can such growth algorithms be encoded in biological molecules? The rules of chemical base-pairing follow regular, predictable patterns, allowing the authors to use DNA to determine the tiles' binding interactions.Desired binding interactions between tiles were programmed by endowing each tile with single-stranded “sticky ends” whose sequence was complementary to the sticky ends of tiles it should stick to. Each tile was either white (0) or black (1): a black tile can fit at any site where the two neighboring tiles are opposite colors, while a white tile can fit at any site where the two neighboring tiles are the same color. Logically, the new tile's color is the exclusive-or (XOR) of the tiles in the previous layer.That such logical layer-by-layer iteration of XOR computations will produce the Sierpinski triangle is well known. What's remarkable is that DNA molecules can be programmed to grow according to this logic. With this programmable algorithmic crystal, Rothemund and colleagues demonstrate a method for designing DNA molecules capable of implementing any pattern of abstract logical tiles. What's more, the authors argue, any algorithmic crystal growth process can, in principle, be experimentally investigated using DNA self-assembly.So how is algorithmic self-assembly related to biology? Like the algorithmic crystals, many of the self-assembled structures in biology are ordered but aperiodic. The hope is that the theoretical insights of computer science—well-honed for describing, analyzing, and programming computational systems—can direct investigations of biochemical self-assembly and information processing. And with a method for demonstrating how simple chemical and physical elements can create complex organization, Rothemund and colleagues have added a concrete experimental framework to bolster that work. (For more on DNA and complexity, see “The Emergence of Complexity: Lessons from DNA” by Chengde Mao.)


The lysophospholipid ligands of these receptors are structurally similar, however recognition of these lipids by these receptors is highly selective. A single residue present within the third transmembrane domain (TM) of S1P receptors is thought to determine ligand selectivity; replacement of the naturally occurring glutamic acid with glutamine (present at this position in the LPA receptors) has previously been shown to be sufficient to change the specificity of S1P4. This mutation severely affected the response of S1P4 to S1P in a [35S]GTPγS binding assay, and imparted sensitivity to LPA species in the order 14:0 LPA > 16:0 LPA > 18:1 LPA. These results indicate a length restriction for activation of this receptor and demonstrate the utility of using LPA-responsive S1P receptor mutants to probe binding pocket length using readily available LPA species. Computational modelling of the interactions between these ligands and both wild type and mutant S1P4 receptors showed excellent agreement with experimental data, therefore confirming the fundamental role of this residue in ligand recognition by S1P receptors.We tested whether mutation of this "ligand selectivity" residue to glutamine could confer LPA-responsiveness to the related S1P receptor, S1P1 receptor.Glutamic acid in the third transmembrane domain of the S1P receptors is a general selectivity switch regulating response to S1P over the closely related phospholipids, LPA. Mutation of this residue to glutamine confers LPA responsiveness with preference for short-chain species. The preference for short-chain LPA species indicates a length restriction different from the closely related S1P These lipids elicit diverse responses from a wide range of cell types, including enhanced cell survival, cell proliferation, induction of cytoskeletal changes and chemotaxis ) with glutamine conferred LPA-responsiveness to the S1P4 receptor and hence determine the role of this residue in this lower-affinity S1P receptor. To achieve this, we expressed wild type and E3.29(122)Q mutant S1P4 receptors in CHO-K1 cells and studied responses to lysophospholipids using a [35S]GTPγS binding assay. Since CHO-K1 cells respond to LPA, we utilised fusion proteins constructed between the S1P4 receptor and a pertussis toxin-insensitive Gαi1(C351I) G protein. Expression of these proteins in CHO-K1 cells followed by treatment with pertussis toxin prior to harvest allowed elimination of any signal due to stimulation of endogenous LPA receptors. Within this study, we also examined how the length of the LPA acyl chain affected potency at the mutant S1P4 receptor, using a panel of naturally occurring LPA analogues. Computational models of complexes between the wild type or mutant S1P4 receptor and S1P and LPA species were used to provide a molecular interpretation of the experimental findings.In the present study, the role of this residue in determining ligand selectivity for the S1Preceptor . We ther4 was mutated at position 122 to replace the naturally occurring glutamic acid with glutamine. The mutant and wild type receptors were stably expressed in CHO-K1 cells as in-frame GPCR-G protein fusions with pertussis toxin-insensitive Gαi1(C351I). Western blotting was used to detect expression of these fusion proteins. Membranes from HA-S1P4-Gαi1(C351I)- or HA-S1P4(E3.29(122)Q)-Gαi1(C351I)-transfected cells contained a polypeptide with an apparent molecular mass of approximately 110 kDa, which reacted with anti-HA and anti-SG1 antibodies  and HA-S1P4(E3.29(122)Q)-Gαi1(C351I) to S1P was assessed using membranes from cells transfected to express these proteins and treated with pertussis toxin prior to harvest. S1P promoted dose-dependent increase in [35S]GTPγS binding to membranes containing HA-S1P4-Gαi1(C351I) with an EC50 of 355 nM ± 155 nM (n = 3); in contrast, membranes from HA-S1P4(E3.29(122)Q)-Gαi1(C351I)-expressing cells demonstrated severely impaired response to S1P  was not statistically significantly different from that obtained using the unfused HA-S1P4 receptor Q mutant using S1P and LPA species with 14:0, 16:0 and 18:1 acyl chains at a single (10 μM) concentration. Of the lysophospholipids tested, only S1P induced a strong response over basal levels (approximately 48% ± 5%) in membranes containing HA-S1P4-Gαi1 . In contrast, membranes containing HA-S1P4(E3.29(122)Q)-Gαi1(C351I) showed at least weak response to each ligand Q mutant S1P4 receptor was 18:1 LPA, which produced only 14% ± 2% stimulation over basal. S1P and 16:0 LPA gave approximately 21% ± 4% and 19% ± 4% stimulation over basal response, respectively. The best agonist for the E3.29(122)Q mutant was 14:0 LPA, which gave a 40% ± 2% enhancement over basal levels. The stimulation promoted by 14:0 LPA was statistically different from that produced by 18:1 LPA (p < 0.01). Sensitivity of the receptor to stimulation by each form of LPA, and particularly 14:0 LPA, was markedly increased after introduction of the E3.29(122)Q mutation and indicated that this position was important in influencing HA-S1P4 ligand preference.Structure activity relationships were determined by the [1 Figure , whilst d Figure . The wea3.29(122)Q mutation in the S1P4 receptor confers LPA-responsiveness, and that a short form of LPA was a more effective agonist than the intermediate and longer forms, when tested at this single concentration. Dose response curves were constructed for ligand-induced activation of the E3.29(122)Q S1P4 mutant by the 14:0 and 18:1 forms of LPA as well as S1P Q)-Gαi1(C351I) was calculated to be 3.8 ± 1.4 μM. However, since a plateau of maximal stimulation was not achieved, interpretation of this EC50 value needs caution. This result clearly showed that 14:0 LPA was a weak agonist of HA-S1P4(E3.29(122)Q)-Gαi1(C351I) and hence confirmed the involvement of residue 122 in S1P4 ligand preference. Similar results were obtained using a second CHO-K1 clone expressing this fusion protein (not shown).These results indicate that introduction of the EP Figure . An EC504 receptor identifies the best S1P binding site within the TM with the phosphate group at the extracellular end  and K5.38(202). An additional ion pair occurs between the cationic ammonium of S1P and E3.29(122). Hydrophobic residues from TM2, TM3, TM5 and TM6 line the binding pocket and surround the alkyl chain of S1P.Computational modelling of the S1P complex with the wild type S1Pd Figure . Ion pai3.29(122)Q S1P4 mutant receptor model has striking similarity to the best complex of S1P in the wild type S1P4 receptor model  and K5.38(202). Each ligand interacts with the amino acid at position 3.29(122), S1P by an ion pair with the carboxylate of the wild type glutamate and 14:0 LPA by a hydrogen bond with the mutated glutamine. Multiple hydrophobic residues surround the nonpolar tails of the lipid ligands. The superimposition of the two complexes Q S1P4 and S1P with wild type S1P4, the remaining complexes show much less common volume Q S1P4 and S1P with wild type S1P4. Of particular interest is the observation that the best complexes generated by Autodock for the 18:1 LPA species with wild type S1P4 has a very high positive van der Waals interaction energy, > 3000 kcal/mol, compared to values well under 200 kcal/mol for every other complex studied. In the best complexes found for 16:0 LPA and 18:1 LPA in both constructs, the terminal six to eight carbons of the hydrophobic tails fold into L-shaped conformations quite different from the extended conformations observed in the S1P complex with wild type S1P4 or the 14:0 LPA complex with the E3.29(122)Q S1P4 mutant. The terminal carbons in several complexes curl out of the receptor between TM5 and TM6 Q S1P4 mutant, have complementary interactions with the residue at position 3.29(122). These strong complexes give the most robust activation. Weak complexes are formed for other combinations due to mismatched interactions with position 3.29(122) or excessive length of the hydrophobic tail. The presence of hydrophobic tails of 16:0 or 18:1 LPA between transmembrane domains may additionally impair the conformational change necessary for full agonist responses.In contrast to the complexes of 14:0 LPA with Ee Figure . Most co6 Figure  due to t1 . For this reason, fusion proteins between wild type or mutant HA-S1P4 and the pertussis toxin-insensitive Gαi1(C351I) G protein were used in these studies. Expression of these proteins in CHO-K1 cells followed by treatment with pertussis toxin prior to harvest allowed elimination of any signal due to stimulation of endogenous LPA receptors. McAllister et al. [1 receptor.Parental CHO-K1 cells respond to LPA in functional assays, reflecting expression of endogenous LPAr et al.  (.(adopt3.29(122) in controlling S1P4 ligand selectivity using functional and computational methods. This residue, which is conserved throughout the S1P receptors, has been shown to control ligand specificity for the related S1P1 receptor [3.29(122)Q mutation severely affected the response of S1P4 to S1P: in dose-response experiments S1P caused minimal stimulation at only the highest concentration of ligand used. This is in agreement with published observations for activation of the equivalent S1P1 mutant [4(E3.29(122)Q) with an EC50 of approximately 3.8 μM but only promoted minimal stimulation of the wild type S1P4 receptor. The modelled complexes of 14:0 LPA with E3.29(122)Q S1P4 and S1P with wild type S1P4 demonstrate nearly identical volumes occupied by the two ligands and very similar interactions between these ligands and their respective receptors. Of particular importance are amino acid residues at positions 3.28(121), 3.29(122) and 5.38(202), which either ion pair with the phosphate or interact with the 2-amino or 2-hydroxyl group in S1P and 14:0 LPA, respectively. The importance of interactions with amino acids at positions 3.28 and 3.29 has been previously noted for the S1P1 [1,2,3 [We examined the role of residue Ereceptor . Introdu1 mutant . 14:0 LPthe S1P1 ,7 and LP3.292 in cont4 receptor exhibits marked constitutive (agonist-independent) activity Q mutation (data not shown). This indicates that the mutation perturbs S1P recognition without affecting the ability of the receptor to spontaneously adopt an active conformation. Similar observations have been reported for the β2AR, where a mutation in the sixth transmembrane domain abolished agonist activation but not constitutive activity [The S1Py Figure  which waactivity .in vivo, the term LPA actually refers to a family of molecules that take the general form 1-o-acyl-2-hydroxy-sn-glyceryl-3-phosphate. Naturally occurring forms of LPA contain acyl chains of differing lengths, with differing degrees of saturation. Investigations into the effect of the length and degree of saturation of the acyl chain of LPA have been undertaken for the LPA receptors [3.29(122)Q S1P4 mutant facilitates structure activity relationship (SAR) studies due to the greater availability of LPA analogs relative to S1P analogs. Comparison of space-filling models of the structures of S1P and three analogues of LPA  is larger than the valine found in the other four S1P receptors, LPA1 and LPA3. Finally, I7.51(305) corresponds to the smaller valine in S1P2 and S1P3 and the much smaller alanine in LPA2. These findings provide a molecular explanation for a similar SAR observed using para-alkyl amide analogs of S1P [4 mutant are in contrast to that shown by LPA receptors, which exhibit the general trend of 18:1 ≥ 16:0 > 14:0 for potency and maximal stimulation [Unlike S1P, which exists as a single species eceptors ,15, but A Figure  revealed4 receptor from the naturally occurring glutamic acid to glutamine conferred responsiveness to 14:0 LPA and severely affected responses to S1P, our observations support the hypothesis that this conserved residue in the third transmembrane domain of the S1P receptors is involved in ligand recognition. This is in contrast to a recent paper describing models of several GPCRs, including S1P4, which had been generated using novel first principle methods [4, interactions between S1P and residues T7.34(127) and W7.37(291) and E7.30(284) were observed. Interaction of E7.30(284) with the ammonium group of S1P appeared to control ligand selectivity since the other residues appeared to interact with the phosphate group, which is present on both LPA and S1P. It is therefore surprising that none of these residues are conserved throughout the S1P or LPA receptor families. The data presented here support the assertion that glutamic acid residue 3.29 present in the third transmembrane domain of the S1P receptors controls ligand selectivity and suggest that the S1P4 model described by Vaidehi et al. [Since mutation of residue 122 in the S1P methods . In thisi et al.  is inacc4 receptor. On the other hand, the activation of the S1P1-E3.29(121)Q mutant by 18:1 LPA [1 receptor. S1P receptor agonists with differing selectivity profiles will be useful tools to more completely map the physiological and pathophysiological roles of these receptors.The current study provides new information for the development of more selective S1P receptor agonists. In particular, an S1P analog with its hydrophobic chain extended by either 2 or 4 carbons would be a very poor agonist of the S1P18:1 LPA  indicate4 receptor is stimulated most strongly by LPA 14:0 and is not activated by the longer LPA 18:1, in contrast with a previous report on the analogous S1P1 receptor mutant that responded to LPA 18:1. Thus the S1P4 receptor ligand binding pocket is shorter in length than the S1P1 ligand binding pocket.These studies confirm that glutamic acid residue 3.29, present in the third transmembrane domain of the S1P receptors is important for the selective recognition of S1P, versus the closely related lipid, LPA. Mutation of E3.29 to glutamine diminished response to S1P and allowed structure activity studies using the diverse available LPA species. The mutant S1P4 can be assigned index positions to facilitate comparison between receptors with different numbers of amino acids, as described by Weinstein and coworkers [Amino acids within the TM of S1Poworkers . An indeoworkers .Materials for tissue culture were supplied by Invitrogen Ltd. (Paisley, Scotland, U.K.). Foetal bovine serum was obtained from Helena Biosciences Ltd., (Sunderland, U.K.) or PAA Labs GmbH., (Linz, Austria). Pertussis toxin was purchased from CN Biosciences Ltd., (Nottingham, U.K.). Lysophosphatidic acid (18:1, 16:0 and 14:0) and S1P were from Avanti Polar Lipids Inc., (Alabaster, AL., U.S.A.). The SG1 antiserum was produced previously [4 coding sequence was cloned from a human PBMC cDNA library using the sense primer 5'-GAGAGAGCGGCCGCCACCATGTATCCATATGATGTTCCAGATTATGCTAACGCCACGGGGACCCCGGTG-3', which contains a NotI restriction site (bold) and the haemagglutinin HA epitope tag (YPYDVPVYA, underlined) immediately after the initiator methionine, and the antisense primer 5'-GAGAGAGAATTCGGCGATGCTCCGCACGCTGGAGATG-3', which contains an EcoRI restriction site (bold) and changes the S1P4 stop codon to alanine (underlined). A C351I mutant of the Gαi1 G protein (previously produced, [GAATTCGCCA CCATGGGCTGCACACTGAGCG-3', which contains the EcoRI restriction site (bold), and the antisense cloning primer 5'-GAGAGAGGATCCTTAGAAGAGACCGATGTCTTTTA G-3', which contains a BamHI restriction site (bold). After digestion of each PCR product with the appropriate restriction enzymes, fragments were ligated into the pIRESpuro mammalian expression vector (Invitrogen Ltd.) to generate an in-frame fusion between HA-S1P4 and Gαi1(C351I).The S1Produced, ) was amp3.29(122)Q mutation was introduced into the S1P4 sequence in parallel PCR reactions. Complementary oligonucleotides were designed across the residue which was to be mutated such that each primer contained the necessary base change to mutate residue 122 to glutamine (underlined in each primer): sense mutational primer: 5'-CAGTGGTTCCTACGGCAGGGCCTGCTCTTCAC-3'; antisense mutational primer: 5'-GTGAAGAGCAGGCCCTGCCGTAGGAACCACTG-3'. Mutational sense or antisense primers were used in parallel PCR reactions with the appropriate antisense or sense cloning primer, with HA-S1P4 plasmid DNA as template. Equimolar amounts of each purified PCR product were mixed and amplified in a further reaction, using the cloning primers described above. The resultant product was digested with the appropriate restriction enzymes and ligated with the Gαi1 sequence in the pIRESpuro expression vector to generate an in-frame fusion between HA-S1P4(E3.29(122)Q) and Gαi1(C351I).The E2 in Dulbecco's modified Eagle's medium (DMEM), supplemented with 10% foetal bovine serum (FBS), 2 mM L-glutamine and non-essential amino acids. Sub-confluent cell monolayers were stably transfected to express either HA-S1P4-Gαi1(C351I) or HA-S1P4(E3.29(122)Q)-Gαi1(C351I) fusion proteins using Lipofectamine reagent (Invitrogen). 72 hours post-transfection, cells were seeded in media supplemented with 7.5 μg/mL puromycin and the resultant clones examined for expression of cell surface receptor using FACS analysis. Clonal cell lines were expanded in complete DMEM containing 7.5 μg/mL puromycin and were transferred to serum free DMEM approximately 24 hours prior to harvesting. Where indicated, 100 ng/mL pertussis toxin was included in the serum free medium.CHO-K1 cells were maintained at 37°C with 5% CO4 in RH7777 cells, which are unresponsive to S1P and LPA and have been commonly used for studies of Edg family receptors [4 expressed in these cells using a variety of functional assays were unsuccessful. Therefore, we used CHO-K1 cells as an alternative host in these studies; expression of functional S1P4 in CHO-K1 cells has also been reported by Mandala et al. [It should be noted that we initially expressed S1Peceptors . Unfortua et al. .3) then stained with the 3F10 antibody (or an isotype matched control) for 40 minutes at 4°C in the dark. After washing with FACS buffer, cells were analysed using a FACScalibur flow cytometer (BD Biosciences, Oxon., U.K.).The amino-terminal HA-epitope tag was detected using a fluorescein conjugate of the anti-HA antibody, clone 3F10 . Cells were harvested non-enzymatically and washed with FACS buffer (PBS containing 3% FBS and 0.1% NaN2, 100 mM NaCl), supplemented with "complete" protease inhibitors . Cells were homogenised in a nitrogen cavitation chamber (500 psi for 15 minutes). Unbroken cells and nuclei were pelleted by centrifugation (500 × g, 10 minutes, 4°C) and the supernatant fraction was centrifuged at 45,000 × g for 45 minutes at 4°C. Membrane pellets were resuspended in assay buffer, titurated through a fine gauge needle and stored at -80°C until required.Cells were harvested non-enzymatically, washed with PBS and resuspended in "assay buffer" (20 mM Hepes, pH 7.4, 3 mM MgClαi1 antibody (Autogen Bioclear Ltd., Wilts., U.K.) was diluted 1 in 1000. Immunoreactivity was detected using an appropriate horseradish peroxidase-conjugated secondary antibody, diluted 1 in 10,000 in PBS/0.1% Tween-20 containing 1% Marvel, followed by detection using SuperSignal reagents (Perbio Science Ltd., Cheshire, U.K.).Samples were resolved by SDS-Page on 4–20% Tris-Glycine gels (Invitrogen) and were transferred to Immobilon-P membrane (Millipore Ltd., Herts., U.K.). The membrane was blocked using 2.5% Marvel in PBS before incubating with primary antibodies which had been diluted in PBS/0.1% Tween-20 containing 1% Marvel. The high affinity rat anti-HA antibody was diluted 1 in 500; the anti-G35S]GTPγS binding experiments were performed essentially as described previously [35S]GTPγS (100 nCi/point), saponin (20 μg/point) and 0.1 μM GDP. 18:1 LPA was prepared as a 2 mM DMSO stock whilst 16:0 and 14:0 LPA were prepared as 2 mM stock solutions in 1:1 ethanol:water per supplier recommendation due to their poor solubility in DMSO. S1P had previously been dispensed as thin film aliquots (dissolved in MeOH and the solvent evaporated under nitrogen) in brown glass vials and stored at -70°C prior to use. Lipids (S1P or LPA forms) were diluted in assay buffer containing 1% fatty acid free BSA, such that the final concentration of BSA in the assay was 0.1%. Following incubation, membrane protein was solubilised with 1.25% NP-40 and 0.4% SDS and after pre-clearance using non-immune serum, Gαi1/2 subunits were immunoprecipitated with SG1 antiserum, used at a dilution of 1 in 200. Non-specific binding was determined by the addition of 100 μM GTPγS. Bound radioactivity was measured using liquid scintillation counting.[eviously . BrieflyNumerical data are expressed as means ± standard error, shown as error bars in the appropriate figures. Statistical comparisons were made using one-way ANOVA with Dunnett's multiple comparison post test.4 (GenBank™ accession number AAP84350) was developed by homology to the experimentally-validated model of S1P1 [et al., unpublished data). A preliminary model was generated by homology modelling using default parameters and subsequently manually refined to optimise interhelical hydrogen bonding. Cis-amide bonds present in the loop regions were converted to the trans conformation by manual rotation followed by the minimisation of two residues on either side of the amide linkage to a root mean square (RMS) gradient of 0.1 kcal/mol·Å using the MMFF94 forcefield [A model of human S1P of S1P1 . Alignmercefield . After t4 with the E3.29(122)Q mutation was developed by performing the appropriate mutation in MOE, and saturating the residue with hydrogen atoms. To allow the sidechains of the other residues in the binding pocket to adapt to the presence of the new moiety, the backbone atoms of the receptor were fixed and the receptor was optimised to an RMS gradient of 0.1 kcal/mol·Å using the MMFF94 forcefield [A model of S1Prcefield .Computational models of the naturally-occurring stereoisomers of 14:0 LPA, 16:0 LPA, 18:1 LPA, and S1P were built using the MOE software package. The -1 ionization state for the phosphate functionality was chosen for all ligands, and the +1 ionization state was chosen for the amine moiety of S1P. Previous docking studies using the -2 ionization state for phosphate in related systems yield essentially identical geometries as studies using the -1 ionization state. These ligands were geometry optimised using the MMFF94 force field .4 wild type and S1P4 E3.29(122)Q mutant receptor models. Each docking box was centered near F3.33(126) with dimensions of 30.75 × 23.25 × 23.25 or 32.25 × 23.25 × 23.25 Å for shorter (S1P and 14:0 LPA) or longer (16:0 and 18:1 LPA) ligands, respectively. At least 20 putative complexes were generated for each receptor:ligand pair using docking parameters at default values with the exception of the number of energy evaluations (2.5 × 108), generations (10000) and maximum iterations (3000). Resultant complexes were evaluated based on final docked energy, Van der Waals interaction energies from the MMFF94 forcefield as well as visual analysis. The complexes with the lowest final docked energies and others of interest were geometry optimised using the MMFF94 force field [Using the AUTODOCK 3.0 software package , 14:0 LPce field , and theCHO, Chinese hamster ovary; Edg, endothelial differentiation gene; ERK, extracellularly regulated kinase; FACS, fluorescence activated cell sorter; G protein, guanine nucleotide-binding protein; GPCR, G protein-coupled receptor; HA, haemagglutinin; LPA, lysophosphatidic acid; MAP, mitogen-activated protein kinase; PBMC, peripheral blood mononuclear cell; PTx, pertussis toxin; SIP, sphingosine-1-phosphate; TM, transmembrane domain4 fusion proteins and drafted the manuscript. D Osborne performed and interpreted docking studies to generate all mutant complexes with all LPA species and S1P and all wild type complexes with LPA species. TC Pham generated the homology model of the human S1P4 receptor. J Fells performed docking studies of S1P with the wild type S1P4 receptor. G Hutchinson and G Milligan participated in the design and coordination of the experimental studies with S1P4 fusion proteins. A Parrill participated in the design and coordination of the modelling studies and edited the manuscript.G Holdsworth performed and interpreted all studies with experimental S1P


Drosophila melanogaster challenged with Salmonella enterica serovartyphimurium (S. typhimurium). We demonstrate that wild-type S. typhimurium causes a lethal systemic infection when injected into the hemocoel of D. melanogaster. Deletion of the gene encoding the secreted bacterial effector Salmonella leucine-rich (PslrP) changes an acute and lethal infection to one that is persistent and less deadly. We propose a model in which Salmonella secreted effectors stimulate the fly and thus cause an immune response that is damaging both to the bacteria and, subsequently, to the host. In support of this model, we show that mutations in the fly gene eiger, a TNF homolog, delay the lethality of Salmonella infection. These results suggest that S. typhimurium-infected flies die from a condition that resembles TNF-induced metabolic collapse in vertebrates. This idea provides us with a new model to study shock-like biology in a genetically manipulable host. In addition, it allows us to study the difference in pathways followed by a microbe when producing an acute or persistent infection.Death by infection is often as much due to the host's reaction as it is to the direct result of microbial action. Here we identify genes in both the host and microbe that are involved in the pathogenesis of infection and disease in  A lethal infection of Drosophila is abrogated by removing a secreted Salmonella effector, demonstrating that the fly's immune system, which although initially protective, is subsequently harmful to the host A hallmark of pathogens is their ability to manipulate their hosts at both a cellular and organismal level. This exploitation of the host can involve the production of specific toxins, secretion of virulence effectors into host cells via type III and type IV secretion apparatuses, or mimicry of host signaling molecules . The hosSalmonella enterica serovar typhimurium (S. typhimurium) is naturally infectious to mice through an oral route and causes a systemic disease resembling human typhoid fever  that translocate effector proteins across both bacterial and host membranes into the host cell cytoplasm. One TTSA encoded by Salmonella pathogenicity island 1 (SPI1) plays an important role in cell entry, whereas a second TTSA, SPI2, alters the intracellular environment of the host cell to permit Salmonella growth. Salmonella likely does not find itself in the hemolymph of Drosophila in nature, but by placing it there we can ask some questions that are difficult to approach using other techniques.id fever . S. typhThe fly is able to fight invading microorganisms via an innate immune response that is composed of at least three arms . First, Drosophila phagocytes affect the course of infections. It has been demonstrated that these cells act in concert with the humoral immune response to destroy invading bacteria , encoded by the eiger gene, is involved in this process. Flies homozygous for mutations in eiger outlive wild-type flies infected with Salmonella.To focus attention on the cellular immune response, we have been characterizing the interaction between  the fly . In thisDrosophila with S. typhimurium by feeding bacteria to flies and by injecting bacteria into the hemocoel. Flies were resistant to feeding (unpublished data), but direct injection of approximately 10,000 bacterial cells resulted in an infection that caused death in 7–9 d, while injection of sterile medium led to a mean time of death of approximately 20 d . Circulating bacteria were not seen in wild-type flies. In contrast to imd homozygotes, flies homozygous for a mutation in Dif, a transcription factor in the Toll pathway, did not die rapidly   D. Under 6 bacteria per fly. This is the case for infections both of wild-type flies with pathogens such as Pseudomonas aeruginosa and L. monocytogenes . Bacteria carrying the plasmid containing the macrophage-inducible gene (pmig-1)  , which i(pmig-1) , which cd larvae A–2D. Hemd larvae . Salmonese cells E–2H. TheS. typhimurium carrying mutations in a gene encoding a regulator of virulence, phosphatase P(phoP)  instead of the average of 40,000 cfu per fly found in wild-type infections  , or blocP(phoP)  or SPI2 P(phoP) , were infections B. In confections D and 3B.Salmonella carrying in-frame deletions of these genes as well as several others we suspected might be involved in virulence in the fly , sseB, sseC, and sseD all resembled a SPI2 knockout as expected because the proteins encoded by these genes are implicated in building the SPI2 translocation machinery  produced a phenotype similar to that of the knockout of the entire SPI2 TTSA in terms of fly death -labeled dead E. coli were injected into flies and incubated for 60 min to allow time for phagocytosis to occur. Trypan blue was then injected into the flies to quench the fluorescence of extracellular bacteria. Uptake of the E. coli was then monitored by observing the flies under FITC illumination with a dissecting microscope. At day 1 post-Salmonella infection, hemocytes infected with wild-type, SPI1-mutant, SPI2-mutant, and SlrP bacteria showed similar phagocytic activities (unpublished data). Following 7 d of infection, flies infected with wild-type or slrP-mutant bacteria had greatly reduced numbers of phagocytic cells -injected controls . The needle was placed in the anterior abdomen on the ventrolateral surface. One-week-old male flies were used for all experiments. All experiments were performed in triplicate with at least 20 flies in each replicate. Oregon R flies were used as our wild-type strain.Infected flies were homogenized in LB containing 1% Triton X-100. Three infected flies were homogenized together either with a small pestle or by shaking with 0.4 mm glass beads. Diluted homogenates were plated on LB-agar with 50 μg/ml streptomycin.E. coli (Molecular Probes, Eugene, Oregon, United States) and incubated for 1 h at 25 °C to permit phagocytosis of the bacteria. Trypan blue (4%) was then injected into the flies. Enough dye was injected to turn the entire fly blue. Flies were observed under a Leica MZ3 fluorescent dissecting microscope (Leica, Wetzlar, Germany) using GFP epifluorescence optics, and photographed with an ORCA camera (Hamamatsu, Osaka, Japan) using Openlab software (Improvision, Coventry, UK).This assay was performed essentially as described previously . InfecteSalmonella strain 14028s/pKD46  and 5′-CGCGGATCCTGGGTTAAGCCCGTTTAC-3′ (slrP 3′ BamHI)  .th polymerase  and the following eiger primers: 5′-GATGGTCTGGATTCCATTGC-3′ (5′ oligo), 5′-TAGTCTGCGCCAACATCATC-3′ (3′ oligo) and 5′-6FAM-GACGACGAGGACGACGACGTTAGCT-TAMRA-3′ (hybridization oligo). Concentrations of eiger transcripts were normalized to the expression of the D. melanogaster ribosomal protein 15a transcript in each sample . Quantitative real-time RT-PCR was performed with rTh sample . All exp


Not all devices that measure the same property do it in the same way—a clock might use a spring system or it might be digitally synchronized to a transmitted signal. Although both have the same goal of reporting accurate time, each is subject to different errors. Sometimes even the same device uses different systems to measure the same property. A relatively simple device like a camera will use one sensor system to capture light intensity for an image and a second sensor to capture light intensity for making automatic adjustments of aperture and flash. It does not seem outlandish, therefore, that the brain might also have developed multiple sensory systems to achieve different goals. Indeed, an influential hypothesis has argued that people use two separate visual processing systems in much the same way as a camera—one for creating our perception of the world and another for guiding our actions within it.One line of evidence supporting this dual hypothesis comes from an illusion known as Roelofs effect. Usually, people are pretty good at judging the location of even a small object. But if the small object is surrounded by a large frame and the frame itself is not centered in front of the person who is judging it, the viewer will perceive the object as shifted in a direction opposite that of the frame. This may not in itself be surprising, but the same person who perceives an offset of the object where none exists is nonetheless able to grasp it without difficulties.PLoS Biology, Paul Dassonville and his colleagues reexamine the seeming dissociation of visual analysis for perception and action, and call it into question. Through a careful quantitative analysis of the conditions under which the Roelofs effect occurs, they find that it traces not to an illusory perception of the object location but to an illusory perception of self. The large frame, presented under experimental conditions in which subjects sit in darkness without access to a normal rich sensory environment, actually causes people to incorrectly perceive their own centers as rotated towards the frame and therefore to conclude that the small object is offset with respect to themselves. This may seem like a subtle distinction, and yet, since it is the observer's frame of reference that is altered, that same distorted frame of reference will be used to guide movement. Thus, the error in movement planning should cancel the error in perception, and people should have no trouble reaching for the object despite their misperception, which is indeed what is observed.In this issue of Others have questioned the hypothesis that two separable neural systems process the visual world for perception and action, but this study removes one of the strongest pieces of evidence in its favor with a precise alternative explanation. No two brains may see the world identically, but the authors suggest that it may be time to concede that a single brain, at least, has the same world view.