To decipher the complexity and improve the understanding of host-pathogen interactions, biologists must adopt new system level approaches in which the hierarchy of biological interactions and dynamics can be studied. This paper presents the application of systems biology for the cross-comparative analysis and interactome modeling of three different infectious agents, leading to the identification of novel, unique and common molecular host responses (biosignatures).Brucella melitensis (BMEL), Salmonella enterica Typhimurium (STM) and Mycobacterium avium paratuberculosis (MAP). A bovine ligated ileal loop biological model was employed to capture the host gene expression response at four time points post infection. New methods based on Dynamic Bayesian Network (DBN) machine learning were employed to conduct a systematic comparative analysis of pathway and Gene Ontology category perturbations.A computational systems biology method was utilized to create interactome models of the host responses to A cross-comparative assessment of 219 pathways and 1620 gene ontology (GO) categories was performed on each pathogen-host condition. Both unique and common pathway and GO perturbations indicated remarkable temporal differences in pathogen-host response profiles. Highly discriminatory pathways were selected from each pathogen condition to create a common system level interactome model comprised of 622 genes. This model was trained with data from each pathogen condition to capture unique and common gene expression features and relationships leading to the identification of candidate host-pathogen points of interactions and discriminatory biosignatures.Our results provide deeper understanding of the overall complexity of host defensive and pathogen invasion processes as well as the identification of novel host-pathogen interactions. The application of advanced computational methods for developing interactome models based on DBN has proven to be instrumental in conducting multi-conditional cross-comparative analyses. Further, this approach generates a fully simulateable model with capabilities for predictive analysis as well as for diagnostic pattern recognition. The resulting biosignatures may represent future targets for identification of emerging pathogens as well as for development of antimicrobial drugs, immunotherapeutics, or vaccines for prevention and treatment of diseases caused by known, emerging/re-emerging infectious agents. The complexity of host-pathogen interactions requires a system level understanding of the entire hierarchy of biological interactions and dynamics. A systems biology approach can provide systematic insights into the dynamic/temporal difference in gene regulation, interaction, and function, and thereby deliver an improved understanding and more comprehensive hypotheses of the underlying mechanisms ,2. Moreoin vivo perinatal calf ligated ileal loop model, in conjunction with custom bovine microarrays, was used to study the early temporal changes in the host response to a previously optimized dosage of 1 x 109 colony forming units of STM, BMEL, or MAP at four common sampling time-points post infection  conducted under approved protocols by the Texas A&M University Institutional Animal Use and Care Committee. Gene expression data was collected by Dr. Adams’ lab at Texas A&M College of Veterinary Medicine following a surgical and sample collection methodology described elsewhere [An established lsewhere -6. For elsewhere . Brieflylsewhere .™). Its core tools are based on Dynamic Bayesian Networks (DBN) [™ is used to identify groups and individual genes that capture the perturbation in a pathway or biological process over time. This technique is named Dynamic Bayesian Gene Group Activation (DBGGA). DBGGA employs Dynamic Bayesian network (DBN) models that are trained using gene expression data replicates from the condition considered as controls. The other experimental condition expression data replicates are then used as evidence to test the goodness-of-fit of these data against the trained DBN control model. Goodness-of-fit is determined by Bayesian likelihood ratio tests that are subsequently transformed to a z-score test statistic (Bayesian z-score) to permit comparison of scores across all pathways and biological processes. The DBGGA computational method scores and rank groups of interrelated genes within a given pathway or gene ontology group across all time points in lieu of just one gene in a single time point  and thus determines the differences and commonalities between experimental and control conditions. DBGGA can also determine which genes are the significant sources of the perturbation. Such genes are designated as “candidate mechanistic genes”, a term we coined to describe those genes within a pathway that individually contributed significantly to the overall pathway Bayesian z-scores and thus are considered mechanistic candidates that may play key roles in governing the host response. Only those genes which are associated with a given pathway or biological process (GO group) were examined using the DBGGA modeling approach.Computational analysis and modeling was completed by Dr. Drake at Seralogix using an integrated platform enabling a systems biology computational pipeline for multi-conditional analysis and modeling, termed the BioSignature Discovery System (BioSignatureDSks (DBN) , an adva™ utilizes the significantly perturbed pathways, GO groups and the “mechanistic genes” as building blocks to construct system level network model of the disease/condition. Encapsulating global time-course patterns and multi-conditional behaviors of a large group of genes/proteins, the systems level model has great discriminating power even when the effects of individual genes are small. Thus, the disease models can be used for more efficient comparative modeling, pattern recognition (diagnostics) and simulations (prognostics). Further, proteomic data can be integrated into the models as an overlay to individual pathway and system-level models to both confirm the presence of proteins for their encoding genes as well as to visualize the temporal patterns of protein abundance.BioSignatureDS™ modeled and scored 219 known metabolic and signaling pathways and 1620 biological processes (gene groups associated with Gene Ontology (GO) terms) at four time points. DBGGA was employed to identify the perturbations between pathogen conditions for pathways, GO categories, and genes. The DBGGA method generates Bayesian log likelihood scores that are normalized and transformed to a z-score equivalent (hereafter Bayesian z-score) so that all pathways and GO groups across all host/pathogen conditions can be equivalently compared and assessed for significance.For each host/pathogen interaction condition, BioSignatureDSOf the 219 signaling/metabolic pathways scored, we focused on a subset of immune response related pathways as listed in Figure Salmonella enterica serovar Typhimurium [Yersinia spp.[Listeriamonocytogenes[Mycobacterium spp. [IL1A, which encodes interleukin 1 protein involved in various immune responses, inflammatory processes, and hematopoiesis; and 2) RASGRP1, which encodes a protein characterized by the presence of a Ras superfamily guanine nucleotide exchange factor (GEF) domain that activates the Erk/MAP kinase cascade and regulates T-cell and B-cell development, homeostasis and differentiation. The perturbation of IL1A and RASGRP1 is consistent with genes involved in immune response, but the expression patterns for these two genes vary significantly between pathogens.Significant divergent responses between conditions were observed for MAPK Signaling. For MAP, the MAPK pathway reversed from induced to suppressed, while STM increased induction and BMEL maintained a suppressed state. The MAPK Signaling Pathway was implicated in bacterial pathogenesis for a number of pathogens such as himurium , Yersiniinia spp., Listericytogenes, and Mycium spp. . This paSimply comparing and contrasting the expression patterns of perturbed genes was inadequate for deciphering the MAPK pathway response dynamics. Clearly, the uniqueness of the MAPK pathway responses suggested that very different invasion/evasion mechanisms have evolved for each pathogen. More sophisticated methods are needed to identify potential points of host response disruptions. This is done by interrogating the trained DBN model for the MAPK Pathway for genes that exceed threshold Bayesian z-scores>|2.24| (“mechanistic genes”) and gene-gene network relationships (arcs). For example, Figure TRAF2->FLNA had a strong positive weight (correlated) for STM-Host (0.241) and for the BMEL-Host (0.204) while MAP-Host had a large negative weight (anti-correlated) of -0.17. The reversal of gene-to-gene arc weight of MAP-Host may indicate a disruption of either TRAF or FLNA gene by virulent factors of the pathogens, identifying potential novel points of interaction. TRAF2 encodes a protein that is a member of the TNF receptor associated factor (TRAF) protein family. This protein is required for TNF-alpha-mediated activation of MAPK8/JNK and NF-κB. It has a binding relationship with the filamin-A protein encoded by the FLNA gene. FLNA participates in the anchoring of membrane proteins to the actin cytoskeleton. This type of interaction analysis can be done for every pathway and used to identify novel differences between pathogen conditions. The visualization of mechanistic genes and arc weight enables an efficient identification of the differences between pathogenic influences.In Table A DBGGA analysis was also conducted for gene GO categories. For each pathogen condition, 1620 biological process GO categories were scored. Each condition produced its own unique set of highly scored GO functions, but for comparison purposes, we chose a small subset of highly perturbed categories to illustrate the different temporal responses as shown in Figure ™, the significantly perturbed pathways and gene groups from DBGGA were integrated to construct a plausible system level model of the disease/condition. The system model encompasses whole time-course patterns and multi-conditional behaviors of a large group of genes/proteins. The system model can be used for more efficient comparative modeling, pattern recognition and simulation supporting “what-if” type of analyses. The system model is constructed from a method based on merging of pathways with known gene/protein relationships and produces a trained and optimized network model similar to the pathway network shown in Figure Utilizing BioSignatureDSa prior biological interactions and cross-species PPI predictions. The model identified a set of 34 known and novel STM-Host protein interactions. These predicted interactions will be employed in guiding future biological experiments for their confirmation as host-pathogen virulence factors and are candidates for points of intervention. PPI interactome models will be developed for BMEL-Host and MAP-Host and full results reported in future publications.Ultimately, the goal is to develop interactome models between the pathogen and the host to make predictions of protein-protein interactions (PPIs). A preliminary STM-Host model (model not shown herein) was created using BioSignatureDS™ augmented with new computational methods to learn PPIs between the pathogen and the host. Model PPI structure learning utilized (host and STM) microarray gene expressions and mass spec protein levels  guidWe analyzed the set of system model genes (622) looking for strong differential expressions (99% confidence) between the three conditions . In this manner we were able to identify sets of genes that were uniquely different from the other two pathogen responses. We found 69 unique genes in the BMEL-Host, 253 genes in the STM-Host, and 64 genes in the MAP-host. Listing of these genes is not provided herein, but will be made publically available in a forthcoming publication. The results of our analysis and modeling identified common and uniquely perturbed genes and biosignatures. A cross-species interactome model identified 34 PPIs that was learned from STM-Host co-expressed gene and protein data. More importantly, these models produce gene networks that can be used to identify novel targets for intervention, as well as the overall improved understanding of the underlying pathogenicity of each pathogen.  Dr. Drake, Dr. Wylie, and Dr. Bai participated in the analysis and modeling presented in this paper. They all work for Seralogix, a private business that is developing the analysis and modeling software for commercial purposes.


Distance index to indicate the qualities of iPS cells, which based on the projection distance of iPSCs-ESCs and iPSCs-fibroblasts. The results indicated that the “Differentiation-index coordinate” can distinguish differentiation states of the different cells types. Furthermore, by applying this method to the analysis of expression profiles in the tetraploid complementation assay, we showed that the Distance index which reflected spatial distributions correlated the pluripotency of iPSCs. We also analyzed the significantly changed gene sets of “developing lines”. The results suggest that the method presented here is not only suitable for the estimation of the quality of iPS cells based on expression profiles, but also is a new approach to analyze time-resolved experimental data.Somatic cells can be reprogrammed to a pluripotent state by over-expression of defined factors, and pluripotency has been confirmed by the tetraploid complementation assay. However, especially in human cells, estimating the quality of Induced Pluripotent Stem Cell(iPSC) is still difficult. Here, we present a novel supervised method for the assessment of the quality of iPSCs by estimating the gene expression profile using a 2-D “Differentiation-index coordinate”, which consists of two “developing lines” that reflects the directions of ES cell differentiation and the changes of cell states during differentiation. By applying a novel liner model to describe the differentiation trajectory, we transformed the ES cell differentiation time-course expression profiles to linear “developing lines”; and use these lines to construct the 2-D “Differentiation-index coordinate” of mouse and human. We compared the published gene expression profiles of iPSCs, ESCs and fibroblasts in mouse and human “Differentiation-index coordinate”. Moreover, we defined the  As a promising technology, induced pluripotent stem cells (iPSCs) are playing important roles in many fields, including personal therapy and scientific research. Both human and mouse fibroblast cells have been reprogrammed to a pluripotent cell state by the over-expression of several transcription factors (TF) that appear in embryonic stem cells Similar to ES cells, the pluripotency of iPS cells evoke expectation and enthusiasm. Different experimental and theoretical approaches have been applied to estimate the similarity between iPSCs and ESCs. Among these approaches, microarray technology and clustering analysis are widely used to detect expression patterns during the reprogramming process. Mark Distance index, which reflects a spatial distance, to measure the similarity of each sample to ESCs. This method not only provided an estimation of the quality of iPSCs based on similarities between iPSCs-ESCs and iPSCs-fibroblasts at the transcriptional level but was also a novel approach for the analysis of time-resolved experimental data.Here, we introduce a new supervised method to estimate the quality of iPSCs based on gene expression profiles from the perspective of ES cell differentiation ability. Inspired by the description of differentiation trajectories in a high-dimensional state space, time-resolved expression profiles of ESC differentiation processes were transformed into linear scales, which were named “developing lines” and represent differentiation directions and the changes in gene expression over time. Here, these developing lines were used to measure the transcription profiles of iPSCs and undifferentiated ESCs. If the iPSCs are similar to ESCs, they should have the similar projection positions on these “developing lines”. Moreover, we defined the concept of the To construct the mouse “Differentiation-index Coordinate”, dataset GSE10970, which contains a series of time-resolved differentiation gene expression profiles for ESC-derived cardiac precursor cells (CPCs), and dataset GSE3653, which contains a series of time-resolved differentiation gene expression profiles for ESC-derived pancreatic islets (PIs), were transformed to a CPC developing line and PI developing line as described in the The mouse Differentiation-index coordinate accurately distinguished between the distributions of different cell types and clearly showed the cell state changes during the reprogramming process. The mouse embryonic fibroblast cells were located the largest distance from the ESCs. The partially reprogrammed cells were located in the middle between the ESC region and fibroblast region. iPSCs were located close to the ESC region and partly overlapped with it. Meanwhile, neuronal progenitor cells were located more closely to the ESC region than the fibroblast cells, which indicated a greater similarity between neuronal progenitor cells and ESCs. Recent studies have indicated that compared with the four factors  required to induce fibroblast cells, neuronal progenitor cells could be induced into a pluripotent state by only Oct4 (Pou5f1) expressionWe also included dataset GSE16925, which was generated with the tetraploid complementation assay Then, we selected the GSE9940 dataset of human ES cell-derived neural rosette differentiation expression profiles to generate a human neuronal developing line. The GSE8884 dataset of human ES cell-derived blast cell differentiation expression profiles was used to generate the second axis, a blast cell developing line . Thus, the two-dimensional human “Differentiation-index coordinate” was obtained.All collected expression profiles of human iPSCs, ESCs and fibroblast cells were estimated using the human Differentiation-index coordinate . The resDistance index (Di), which reflected the distance ratio of iPS cells to ES cells and fibroblast cells. A smaller Distance index  for all collected ESCs  and 60% (12 of 20) of mouse ESCs were under the threshold.We calculated the ted ESCs , S2 and ted ESCs , S4 for Distance indices of iPSCs reflected their distinct abilities to generate live pups . However, the three replicates of IP14D-101 had larger variances than the other two cell lines.We compared the three strains of iPSCs used in the tetraploid complementation assay ive pups . All thrThe methods presented here are not limited to the estimation of the similarities between different cell types; they could also be applied to the analysis of time-resolved experimental data. When calculating the developing lines, we also defined a weight for each gene to represent the expression change, and then calculated P and FDR values based on distribution of weights. With a P-value cut-off of <0.01 and an FDR of <0.1, we selected the most significantly changed genes in four different ESC differentiation processes. For assessing the functions of these significantly changed genes, we performed GO analysis using the DAVID bioinformatics resource Furthermore, we compared the significantly changed genes between the two experiments and generated a list of “common genes” in both human and mouse , S24. ThTo better understand the relationship and function of these genes, we searched for their protein binding partners using protein-protein interaction data . Interestingly, we found a new model that consisted of three components: down-regulated genes, up-regulated genes, and insignificantly changed genes and named it the “Seesaw module” . The expThe induced pluripotent stem (iPS) cell technology is an enormously promising approach for personal therapy and scientific research. However, how the cell state alteration process happens from terminal differentiation to pluripotency is unclear. The similarities and differences in the transcriptomes of iPSCs and ES cells have been estimated Distance index of dataset GSE16925 indicated that low quality iPS cells (IP20D-3) distinctly have bigger Di then the high quality iPS cells (IP14D-1), and this disparity is also clearly reflected by the success of live pups. We believe that the Distance index, as a more accurate and reasonable measurement, have the potential to become an easy standard to estimate the quality of iPSCs at molecular level.The value of iPSCs is their pluripotency. From this perspective, pluripotency should be a gold standard for estimating the quality of iPSCs Distance index by this supervised method is based on a large number of expression profiles from different laboratories, and these existing datasets give our method greater robustness and accuracy. Such characteristics enable us to compare expression profiles of different sources more easily. Moreover, this method gives a simple and direct description of different cell state distributions. The dynamic changes in cell states induced by reprogramming were also clearly indicated by the “Differentiation-index coordinate”. These dynamic changes of cell states would help us to understand more about the movement trajectories of the ES cells differentiation and the reprogramming process of somatic cells.The similarity defined by hierarchical clustering method severely depends on the mathematical characteristics of expression profiles. The system error of ES cells expression profiles would affect the clustering results. In our model, the “developing lines” generated by time-ordered linear model have distinct biological meaning: such lines are projection of ES cells differentiation trajectories. Meanwhile, the calculation of As shown, the time-order linear model was also a novel method to analyze time-resolved experimental data. This method generated lists of the significantly up/down regulated genes during the time-resolved experiment. Based on the Protein-protein interaction network and significantly changed genes during human ES cell differentiation, we identified some interesting “seesaw” modules. One of these modules directly regulates the epigenetic changes that occur during the ESC differentiation process: ZBTB16--DNMT3B. DNMT3B encodes a DNA methyltransferase that is thought to function in genome DNA de novo methylation. HADC1 encodes a histone deacetylase that is responsible for the deacetylation of lysine residues on the N-terminal tails of the core histones . By SUMO1 modification, DNMT3B modulates its interaction with HDAC1 to repress the transcription of target genes In this work, we constructed developing lines of some differentiation fates determinations in mouse and human. Theoretically, the developing line had the best resolving power for estimating the cell state of the corresponding cells, i.e, using fibroblast developing line to estimate iPSCs originated from fibroblasts, using the neuronal developing line to estimate iPSCs originated from neurons. However, for the limited number of successful ESC differentiation events in vitro, it is still difficult for us to construct developing lines that represent all directions of every ESC differentiation process. Here, we used two developing lines to estimate the pluripotency of iPSCs and other cells, and the promising results encouraged us to improve this method. Although the resolution powers of the different developing lines still need to assess, we expect that these “Differentiation-index coordinates” could reflect all of cell fates, fit all expression data, or even distinguish all cell types accurately in the future.The approach presented here could also contribute to the construction of a “Cell type coordinate”, which would reflect the relationship between different cell types and describe the cell type-specific differences at different levels . Recently, the fibroblast cell have been directly reprogrammed to functional neurons and Cardiomyocytes http://www.ncbi.nlm.nih.gov/geo/). To construct linear scales that represent the changes in gene expression over differentiation time, we analyzed two datasets that contained the expression profiles of human ESCs differentiating into neural rosettes and blast cells  if possible (before Oct. 2009). All of the expression profile datasets of human iPSCs and ESCs are listed in We also constructed mouse ES cell differentiation developing lines to estimate the relationship between mouse iPSCs and mouse ESCs. All of the expression profiles were based on the Affymetrix Mouse Genome 430 2.0 chip (GEO platform: GPL1226). Two datasets containing the expression profiles of mouse ES cells differentiating to cardiac precursor cells and pancreatic islets were used to generate two differentiation developing lines .As described above, we collected the expression profiles of mouse iPS cells and mouse ESCs where possible (before Oct. 2009) and analyzed these expression profiles as described in the method .Probe signal estimates were derived from the SOFT files. Each probe was treated as an independent transcript. The log-transformed values of the expression data were then median-normalized independently for each dataset.To construct developing lines that represent ESC differentiation processes, we used a time-ordered linear model algorithm to transform time-resolved ESC's differentiation expression profiles into the Octave environment.Inspiriting from Clustering the line could preserve the time order of the projected pointsthe line could preserve the distance ratio of joint sample points in the microarray spaceN), a series of unlooped, head-to-tail joint vectors  have one co-bisector. Because the angles between each vector and co-bisector are the same, after each vector is projected onto the co-bisector, the strict order and length ratio of every vector is preserved perfectly. Naturally, the co-bisector of a series of vectors has the longest length among all bisectors  vectors For the purpose of preserving the strict order of the projected points of Then, we defined the co-bisector as Naturally, after the points of To simplify our calculations, we set With equations (2), (3), (4), and (5), the parameters Thus i of each sample is calculated by: When the expression profiles of other samples are projected onto the vector , http://david.abcc.ncifcrf.gov). We performed a functional analysis on the significantly changed genes on the DAVID bioinformatics resource By applying multiple testing, we calculated the P-value and Benjamini-Hochberg FDR for the weight of each probe in vector Figure S1Estimates of Human ES cell and neuron rosettes in the Human Differentiation Coordinate. The X-axis is the blast cell developing line; the Y-axis is the neuronal developing line. Ellipses were generated by the mean values and standard variances.(PDF)Click here for additional data file.Figure S2Maximizing the projection of each vector on the angle-bisector. Vector(PDF)Click here for additional data file.Figure S3Noise Random permutation testing to developing line (GSE13149): The Projection location of Dataset GSE6998.(PDF)Click here for additional data file.Table S1Distance-index of Human Embryonic Stem Cells.(PDF)Click here for additional data file.Table S2Distance-index of Mouse Embryonic Stem Cells.(PDF)Click here for additional data file.Table S3Distance-index of Human Induced Pluripotent Stem Cells.(PDF)Click here for additional data file.Table S4Distance-index of Mouse Induced Pluripotent Stem Cells.(PDF)Click here for additional data file.Table S5GO analysis of negative regulated genes in ES cell-derived Cardiac precursors cells Differentiation (GSE10970).(PDF)Click here for additional data file.Table S6GO analysis of positive regulated genes in ES cell-derived Cardiac precursors cells Differentiation (GSE10970).(PDF)Click here for additional data file.Table S7GO analysis of negative regulated genes in ES cell-derived Pancreatic islets cells Differentiation (GSE3653).(PDF)Click here for additional data file.Table S8GO analysis of positive regulated genes in ES cell-derived Pancreatic islets cells Differentiation (GSE3653).(PDF)Click here for additional data file.Table S9GO analysis of negative regulated genes in ES cell-derived blast cells Differentiation (GSE8884).(PDF)Click here for additional data file.Table S10GO analysis of positive regulated genes in ES cell-derived blast cells Differentiation (GSE8884).(PDF)Click here for additional data file.Table S11GO analysis of negative regulated genes in ES cell-derived neuron rosettes Differentiation (GSE9940).(PDF)Click here for additional data file.Table S12GO analysis of positive regulated genes in ES cell-derived neuron rosettes Differentiation (GSE9940).(PDF)Click here for additional data file.Table S13Positive regulated genes in ES cell-derived blast cell differentiation (GSE8884).(PDF)Click here for additional data file.Table S14Negative regulated genes in ES cell-derived blast cell differentiation (GSE8884).(PDF)Click here for additional data file.Table S15Positive regulated genes in ES cells-derived neuron rosette differentiation (GSE9940).(PDF)Click here for additional data file.Table S16Positive regulated genes in ES cells-derived neuron rosette differentiation (GSE9940).(PDF)Click here for additional data file.Table S17Negative regulated genes in ES cell-derived Cardiac precursors cells Differentiation (GSE10970).(PDF)Click here for additional data file.Table S18Positive regulated genes in ES cell-derived Cardiac precursors cells Differentiation (GSE10970).(PDF)Click here for additional data file.Table S19Negative regulated genes in ES cell-derived Pancreatic islets cells Differentiation (GSE3653).(PDF)Click here for additional data file.Table S20Positive regulated genes in ES cell-derived Pancreatic islets cells Differentiation (GSE3653).(PDF)Click here for additional data file.Table S21Significant Up-regulated Common Genes in GSE8884 and GSE9940.(PDF)Click here for additional data file.Table S22Significant Down-regulated Common Genes in GSE8884 and GSE9940.(PDF)Click here for additional data file.Table S23Significant Up-regulated Common Genes in GSE10970 and GSE3653.(PDF)Click here for additional data file.Table S24Significant Down-regulated Common Genes in GSE10970 and GSE3653.(PDF)Click here for additional data file.Table S25Noise Random permutation testing to developing line (GSE13149): The Projection location of Dataset GSE6998.(PDF)Click here for additional data file.


Protein interactions control the regulatory networks underlying developmental processes. The understanding of developmental complexity will, therefore, require the characterization of protein interactions within their proper environment. The bimolecular fluorescence complementation (BiFC) technology offers this possibility as it enables the direct visualization of protein interactions in living cells. However, its potential has rarely been applied in embryos of animal model organisms and was only performed under transient protein expression levels.Drosophila embryo. Importantly, all BiFC parameters were established with constructs that were stably expressed under the control of endogenous promoters. Under these physiological conditions, we showed that BiFC is specific and sensitive enough to analyse dynamic protein interactions. We next used BiFC in a candidate interaction screen, which led to the identification of several Hox protein partners.Using a Hox protein partnership as a test case, we investigated the suitability of BiFC for the study of protein interactions in the living Drosophila embryonic development.Our results establish the general suitability of BiFC for revealing and studying protein interactions in their physiological context during the rapid course of  Aequorea victoria has become a potent tool in biology. GFP has been manipulated and modified and a set of derived fluorescent proteins showing different spectral properties and stabilities are now available. GFP proteins can tolerate peptide insertions without perturbing its fluorescence characteristics   or from Xenopus laevis and Danio rerio to visualize the nuclear translocation of a Smad2/Smad4 complex in embryonic explants [Caenorabditis elegans and between odorant receptors [Drosophila melanogaster. Importantly, these latter studies were only undertaken in adults.BiFC is by now a widely used assay for testing the protein interaction status in cultured cells  and planexplants ,16 or emexplants , respectexplants  or betweexplants  in Caenoeceptors , actin neceptors  or transeceptors  in DrosoThe absence of BiFC applications in the embryos of these model organisms might appear somewhat surprising, given that they have been extensively used to address questions relating to mechanisms underlying developmental control, and that protein interactions are central to the developmental processes. Among the reasons that may explain this are technical constraints, such as the short time window characterizing worm and fly embryogenesis, and the sensitivity of the technique when fusion proteins are expressed at the same level as the endogenous proteins of interest, a prerequisite for drawing physiologically relevant conclusions.Drosophila embryo, using the partnership between the Hox protein AbdominalA (AbdA) and the PBC class Extradenticle (Exd) protein as a paradigm. Hox proteins are present in all bilaterians and play major roles during embryonic development by controlling diversified morphogenesis along the anteroposterior axis [cis-regulatory sequences of target genes [In this work, we question the suitability of the BiFC technology in conditions where proteins are expressed at physiological levels in the ior axis . Hox andet genes .Drosophila embryogenesis. Our work demonstrates that BiFC is a specific and sensitive method which allows the visualization of spatial interaction dynamics between AbdA and Exd. The technology was further used for assessing the in vivo interaction status between AbdA and several candidate partners, including non-HD containing transcription factors. Results indicate that the methodology is generally suited for the study of interactions between different types of transcription factors.Here, we establish experimental parameters that make BiFC compatible with both the physiological levels of protein expression and the short time window characterizing The DNA fragments coding for the N-terminal (VN: 1-173) and C-terminal (VC: 155-238) moieties of Venus were generated by polymerase chain reaction (PCR) and cloned into EcoRI-XhoI or XhoI-XbaI restriction sites of the pUAST  and pUASCerulean N-terminal CN: 1-173) and C-terminal (CC:155-238) coding fragments 3 and C-t N-terminAll constructs were sequence-verified before fly transformation and transgenic lines were established either by the ΦC-31 integrase  UltrabitabdAGal4 line was generated by replacing a P-lacZ insertion -Gal4, paired(prd)-Gal4, engrailed (en)-Gal4, 24B-Gal4, breathless (btl)-Gal4 and Ubx-Gal4M1 [UAS-abdA, UAS-Bip2, UAS-β-Galactosidase and exd XP11 lines were obtained from the Bloomington Stock Centre ; the UAS-Tsh line was kindly provided by S Kerridge.The e HC7JA1 ) by a P- element . Other Gx-Gal4M1  drivers.Embryo collections, cuticle preparations and immunodetections were performed according to standard procedures ,30. The arm-Gal4 driver at different temperatures. The anti-AbdA fluorescent immunostaining was compared between the A2 segment of wild-type embryos and the T2 segment of embryos ectopically expressing VC-AbdA. Pictures of at least 10 different embryos were taken with a LSM510 Zeiss confocal microscope under fixed parameters of acquisition and average levels of pixel intensities were determined with the ImageJ software. The ratio between the experimentally induced AbdA protein levels in T2 and the wild-type AbdA protein levels in A2 was determined, allowing the selection of the temperature for which the induced AbdA expression with arm-Gal4 was close to the endogenous AbdA expression levels found normally in A2.Experimental conditions allowing physiological levels of protein expression were established by two steps. First, the VC-AbdA construct was expressed with the abdAGal4 driver. This was performed with the VC-AbdA construct: intensities of the GFP fluorescent immunostaining were measured and compared to embryos expressing VC-AbdA with the arm-Gal4 driver in order to adjust the physiological conditions of expression. In our conditions, abdA-Gal4 is 20% more expressed than arm-Gal4. Since arm-Gal4 led to 80% of the AbdA endogenous expression levels in the A2 segment, we concluded that our experimental conditions with abdA-Gal4 are close to physiological levels of expression.Secondly, we established experimental conditions for using the Fly crosses for BiFC analyses were set up at the defined temperature over night. After the removal of the flies, the embryos were kept at 4°C for 28 h before live imaging. In order to visualize the complementation between split Venus fragments, living embryos were dechorionated and mounted in the halocarbon oil 10S . In order to quantify the BiFC signals, unsaturated images of ectodermal fluorescence were taken in embryos of the desired stage (with a minimum of 10 embryos by condition) using a LSM510 confocal microscope . For Venus fluorescence, filters were adjusted at 500 nm for excitation and 535 nm for emission. Identical parameters of acquisition were applied between the different genotypes. The number and intensity of the all pixels (for each embryo) were measured using the histogram function of the ImageJ Software. The quantification of fluorescence complementation was shown for each condition by boxplot representation using R-Software. Boxplot depicts: the smallest value, lower quartile, median (green line), upper quartile and largest value for each condition. Black points correspond to individual measures. Cerulean and mCherry BiFC signals were taken after identical maturation times of 28 h with the AxioImagerZ1 microscope (Zeiss), using specific filters for excitation and emission wavelengths .A fixed number of 100 embryos were collected over a 1h period at room temperature and left to develop for 4h, which allows having a high proportion of stage 9/10 embryos. Embryos were next placed at 4°C for different times before being returned to resume and complete development at room temperature. The embryonic lethality rate was deduced by counting the number of hatching embryos that gave rise to first instar larvae. For each incubation time the experiments were repeated twice and the results were stably reproduced.in vitro transcription/translation system (Promega). Production yields of AbdA and Exd fusion proteins were estimated by 35S-methionine labelling. The amount of Hox proteins used in the band shift assays is indicated in the figure legends. EMSAs were performed as described previously [con 5'-TATTTGGGCCATAAATCATTCCCGCGGACAGTT-3' [The fusion constructs were subcloned in the PcDNA3 vector and sequence-verified. Proteins were produced with the TNT T7-coupled eviously . We usedCAGTT-3'  and PRS CAGTT-3' . The rabin vitro approach based on EMSAs could help in predicting the best appropriate choice of fusion proteins for in vivo analyses.The identity , corresponds to a consensus Hox-Exd DNA binding site for the AbdA monomer and the AbdA-Exd heterodimer [PRS (for Pbx1 recognition sequence), corresponds to a monomer binding site for PBC proteins in vitro [Indeed, EMSAs allow one to measure both DNA binding and protein interactions. Each of the split fragments of the Venus fluorescent protein was fused to the N-terminus or the C-terminus of AbdA and Exd Figure . Importaerodimer . The secin vitro . TogetheDllcon  fragment strongly inhibits monomer DNA binding while the VC fragment has minor effects Figure . For exain vitro analysis highlights the fact that the topology of the fusions can drastically affect complex formation between AbdA and Exd. Although this was expected in general, it was not possible to predict which topology would actually be the most neutral to protein activity. Therefore, EMSA may constitute a valuable rapid assay for choosing the best match of fusion proteins for BiFC analysis in the case of DNA binding transcription factors.Our extensive in vivo functions and BiFC efficiency, we selected combinations which showed weak (VC-AbdA/VN-Exd), medium (VN-AbdA-VC-Exd) or strong (VN-AbdA/Exd-VC) impairments for complex assembly in vitro . This was performed by quantifying the activity of the armadillo (arm)-Gal4 driver  target gene. Through its DME enhancer, this gene is normally repressed by AbdA in the abdomen [paired-Gal4 driver leads to complete repression of DME in the T2 thoracic segment . As a control, we found that embryos have a normal rate of lethality around 12% when development occurred at room temperature only  on the property of the spontaneous association of split fragments when brought together upon protein interactions . This prDrosophila embryo, we first expressed the VN and VC moieties as such. As expected, when expressed together, these two fragments led to strong BiFC signals which were visible after short incubation times at 4°C . The effect of HD mutations was next analysed on BiFC in the Drosophila embryo. We verified that HD-mutated fusion proteins were properly expressed, at levels equivalent to the wild type fusion proteins -Gal4 driver , which is a zinc finger transcription factor. Tsh has been genetically described to act with Antennapedia (Antp) and Hox proteins of the Bithorax complex for specifying the embryonic trunk region . More reosophila . We obseThe second putative partner analysed is a tissue-specific transcription factor, Biniou (Bin), which contains a forkhead DNA-binding domain. Bin has been proposed to act as a Hox cofactor for the regulation of several target genes in the visceral mesoderm . BiFC, iFinally, we tested the interaction potential of AbdA with two candidate proteins belonging to the basal transcriptional machinery, TFIIbeta and BIP2. TFIIbeta has been shown to interact with Ubx in a yeast two-hybrid assay , while BOur results raised two limits of the BiFC for a candidate interaction screening. First, even if we observed that BIP2-VN was able to produce strong BiFC signals with VC-Ubx Figure , the absIn order to validate the observed BiFC between AbdA and Tsh, we co-expressed VC-AbdA and VN-AbdA with wild-type Tsh, which we designed as a 'cold' competitive partner (not fused to a Venus fragment). We observed that this co-expression led to a drastic loss of BiFC Figure , which cThe same type of experiment was performed with BIP2 to validate absence of BiFC between AbdA and BIP2. We observed that co-expressing the cold wild-type BIP2 protein led to a strong decrease of BiFC resulting from the VC-AbdA/VN-AbdA complex assembly Figure . We concDrosophila embryo. Our extensive analysis highlights the need for careful selection of fusion topologies, which is of particular importance when considering that absence of BiFC signal can simply result of an unfavourable fusion topology. There is no simple rule for predicting the arrangement of fusion topologies that will produce maximal signals, even when the protein interaction domains are known. For example, in the case of Hth, the N-terminus Exd interaction domain was paradoxically more affected by fusions at the C-terminus of the protein. Similarly, the best fusion topologies in AbdA and Exd cannot be predicted, although Hox/PBC interfaces have been well characterized by structural studies. Since these structures were obtained with portions of proteins, it can simply not be informative in the context of the three dimensional arrangements of the full length protein. Appropriate fusion constructs can, however, be rapidly identified with the help of in vitro interaction assays, limiting the number of Drosophila transgenic lines that need to be generated. In the case of AbdA and Exd, we showed that EMSA provides a mean to select the best suited fusion proteins for subsequent BiFC analysis in the Drosophila embryo. The impact of fusion topologies on BiFC also underlines the need of using the same fusion topology when comparing protein interaction efficiencies.By using Hox partnership as a paradigm, we have demonstrated the suitability of BiFC for the study of transcription factors interactions in the Drosophila embryo. This includes the extremely weak tendency of VN and VC fragments to self-associate when one fragment is fused to AbdA, the destabilization of complex formation through protein competition, the absence of BiFC signals in absence of interactions, the spatial restriction of BiFC in the tracheal system or absence of BiFC between AbdA and BIP2.We showed that the VN and VC fragments were able to self assemble with a typical kinetic when expressed as single peptides. Although this property was expected for a visualisation method based on complementation, it also emphasized the need of control experiments for validating BiFC results. Here, we provided several evidences demonstrating the specificity of BiFC for the study of protein interactions in the Drosophila embryonic development and suggests that the methodology could be generally suited for the study of protein interactions in the context of other rapid developmental processes. Finally, we showed that multicolour BiFC is applicable to the Drosophila embryo, extending further the potential of the methodology for in vivo simultaneous study of multiple protein interactions.We found that the time required for visualizing BiFC signals can be provided by keeping embryos at 4°C, ideally for a period no longer than 28 h. This procedure allows the visualization of protein interactions within the short time window of Drosophila.BiFC is a commonly used method in cultured cells and in plants for studying protein interactions. Surprisingly, this method remains rarely used in living animal embryos. In contrast, the visualization method based on fluorescence resonance energy transfer (FRET) has been more thoroughly used in animal models, although it requires complex instrumentation and data processing. FRET analysis is based on energy transfer between two fluorophores placed in close proximity, allowing real time detection of complex formation and dissociation. The detection of this energy transfer usually requires high levels of protein expression  and is cin vivo protein functions. In order to validate BiFC as a unique visualization method for measuring physiologically relevant protein interactions, we have generated a P-Gal4 driver by replacing a P-lacZ insertion in abdA cis-regulatory sequences. This driver reproduces the abdA expression profile and we selected experimental conditions allowing expression levels close to endogenous AbdA. Importantly, this insertion affects endogenous abdA expression, which offers the advantage of performing BiFC in cells containing normal doses of AbdA. Loss of the endogenous competitive protein can also be crucial for visualising weak protein interactions by BiFC. The huge number of genomic P insertions in Drosophila are thus of great utility for performing BiFC under physiological conditions.In this work, we establish BiFC as a complementary approach to FRET. We show that the sensitivity of BiFC enables it to work at physiological levels of expression. This is a crucial property of the methodology, since quantitative differences in protein interactions play important roles in controlling Given the sensitivity, specificity and simplicity of BiFC, the method should in principle be suited for the identification of interacting protein partners. We investigated the suitability of the method for revealing protein interactions of different natures, using a candidate gene approach. Although the expression level of all candidate cofactors was not systematically verified, several transgenic lines were tested in each case. This includes: Hox-Hox interactions that do not involve a TALE (three amino acids loop extension) homeodomain as in the case of AbdA/Exd interactions; interactions with proteins of the basal transcription machinery; and interactions with zinc-finger or forkhead transcription factors. The nature of these interacting partners, involved in different transcriptional processes, illustrates the potential of Hox proteins to accommodate interactions with various classes of transcription factors.in vivo. It also illustrates the difficulty of validating BiFC observations by using mutated proteins when the molecular cues required for the complex assembly are not known. We showed that an alternative way to validate BiFC observations is through competition experiments. This was achieved by co-expressing the candidate partner as a 'cold' protein with the VC-AbdA and VN-AbdA fusion proteins. In the context of specific interactions, the titration of AbdA fusion proteins by the cold competitive partner will affect BiFC resulting from the VC-AbdA/VN-AbdA complex assembly, as observed with Tsh. The same approach can also be instructive in absence of BiFC, as shown with BIP2, revealing an unfavourable arrangement of fusion topologies for visualising protein interactions.We tried to validate the specificity of these interactions by using a DNA-binding deficient form of AbdA. We observed that this mutation abolished interactions with Exd or Bin but had no effect on interactions with Ubx, Tsh or TFIIbeta. This result stresses that the DNA binding of Hox proteins is not a mandatory step for recruiting protein partners Interestingly, interactions between AbdA and candidate partners have distinct and typical nuclear localisations, suggesting that the nuclear architecture has important roles in controlling Hox protein interactions and functions. It also illustrates the power of BiFC for deciphering unanticipated mechanisms regulating protein interactions within a proper physiological context.Drosophila genetics.Finally, the variety of protein interactions visualized through BiFC indicates that the methodology could be used more globally  for screDrosophila embryo. We provided experimental procedures to circumvent the limitations of BiFC and we designed control experiments to validate BiFC results. We also revealed the importance of choosing the best match of fusion proteins, which can be rapidly achieved with transcription factors through EMSA experiments. Finally, we described how to use BiFC for finding novel cofactors through a candidate gene approach. Altogether, our work demonstrates that BiFC is not only a physiologically relevant protein interaction test but also a powerful method for studying protein interaction dynamics during Drosophila embryogenesis.We have explained how to perform multicolour BiFC with physiological levels of protein expression in the live AbdA: abdominalA; BiFC: bimolecular fluorescence complementation; CC: C-terminal fragment of Cerulean; CFP: cyan fluorescent protein; CN: N-terminal fragment of Cerulean; dt: dorsal trunk; EMSA: electrophoretic mobility shift assay; Exd: extradenticle; FRET: fluorescence resonance energy transfer; GFP: green FP; HD: homeodomain; Hth: homothorax; TALE: three amino acids insertion; PCR: polymerase chain reaction; Tsh: Teashirt; Bin: biniou; Ubx: ultrabithorax; YFP: yellow FP; VN: Venus; VN: N-terminal fragment of venus; VC: C-terminal fragment of Venus; mCN: N-terminal fragment of mCherry; mCC: C-terminal fragment of mCherryBH performed most of the experiments. SM conceived the project, designed most of the experiments and performed some of them. SV helped in the performance of some of the experiments. BH, YG and SM wrote the paper together.ultrabithorax (Ubx)-Gal4 driverEstablishing physiological levels of protein expression with the . (A) The Ubx-Gal4 driver was used to express the green fluorescent protein (GFP) reporter protein (red), showing an expression profile similar to endogenous Ubx protein (grey) in a stage 10 embryo. (B) Establishing physiological levels of VC-Ubx (VCU) expression with the armadillo (arm)-Gal4 driver. The average level of VCU was quantified in the T2 thoracic segment and compared to the level of endogenous Ubx in the A1 segment of a wild type embryo (red-dotted circles). Fluorescent immunostainings were similarly performed with an anti-Ubx antibody (grey). Graph on the right is a boxplot representation of the statistical quantification of the surface and intensity of the fluorescent Ubx immunostaining. It shows that VCU is expressed at around 80% of endogenous Ubx under these conditions. (C) Establishing physiological levels of expression with the Ubx-Gal4 driver. Quantifications were measured with an anti-GFP that recognizes the VC fragment of VCU. Fluorescent immunostainings (grey) were performed in embryos expressing VCU either with arm-Gal4 or Ubx-Gal4 at 29°C. Graph on the right indicates that Ubx-Gal4 led to a slightly better expression than armGal4 (around 20% more). From (B) and (C), we concluded that using Ubx-Gal4 at 29°C allows expression levels comparable to endogenous Ubx levels found in the A1 segment of a wild type embryo.Click here for fileAdditional File 2. Live imaging of a developing embryo expressing the VC-abdominalA (AbdA) and VN-extradenticle (Exd) fusion proteins with the abdA-Gal4 driver. Live imaging was acquired from stage 10 to stage 14 of embryogenesis.Click here for fileInfluence of fusion topologies on bimolecular fluorescence complementation (BiFC) resulting from extradenticle (Exd)/homothorox (Hth) complex assembly. (A) Schematic representation of Exd and Hth fusion proteins. Interacting domains  are indicated. (B) BiFC with the indicated fusion proteins which were expressed with the engrailed (en)-Gal4 driver. No signal can be visualized between Hth-VN and VC-Exd. (C) The VC-Hth and Hth-VN fusion proteins are expressed at similar levels with the en-Gal4 driver. Fusion proteins expression was revealed with a polyclonal anti-green fluorescent protein antibody (grey) that recognizes both fragments of Venus. Images were acquired with identical confocal parameters.Click here for fileDrosophila embryoSelf-assembly properties of the VN and VC fragments in the . (A) The VN and VC fragments were expressed with the abdA-Gal4 driver, either as isolated peptides, or in the context of an abdominalA fusion protein, as indicated above pictures. Bimolecular fluorescence complementation (BiFC) was visualized in stage 11 or stage 14 embryos, after 28 h of incubation at 4°C. BiFC resulting from the assembly of isolated Venus (VN) and VC fragments was already visible after a short incubation time of 2 h, but the intensity of the fluorescence did not increase with longer times of incubation . (B) Expression level of the VN and VC fragments, as revealed with a polyclonal anti-green fluorescent protein antibody (grey) that recognizes both fragments. Images were acquired with identical confocal parameters. Note that the VN fragment is more specifically addressed to the nucleus than the VC fragment, due to the addition of a nuclear localization signal (see Methods).Click here for fileThe mutation in the homeodomain (HD) of abdominalA (AbdA) and extradenticle (Exd) does not affect their expression profile and abolishes bimolecular fluorescence complementation (BiFC). (A) The wild-type (VCA) and homeodomain (HD)-mutated (VCAHD) forms of the VC-AbdA fusion protein are expressed at comparable levels in the embryo. Quantifications were performed with an anti-green fluorescent protein antibody (grey) in embryos heterozygous for the PabdAGal4 driver. (B) The wild-type (VNE) and HD-mutated forms (VNEHD) of the HA-tagged VN-Exd fusion proteins are expressed at comparable levels in the embryo. Quantifications were performed with an anti-HA antibody (grey) in embryos heterozygous for the PabdAGal4 driver. Graphs on the right illustrate the statistical quantification as boxplot. (C) The VCAHD and VNEHD fusion proteins did not produced BiFC in vivo. Fusion proteins were expressed with the engrailed (en)-Gal4 driver at 18°C or 29°C. High levels of fusion proteins expression were confirmed by the AbdA (magenta) and Exd  immunostainings. Despite these high levels of protein expression, no BiFC can be visualized (upper images), highlighting the specificity of the methodology.Click here for file


The actions of cell adhesion molecules, in particular, cadherins during embryonic development and morphogenesis more generally, regulate many aspects of cellular interactions, regulation and signaling. Often, a gradient of cadherin expression levels drives collective and relative cell motions generating macroscopic cell sorting. Computer simulations of cell sorting have focused on the interactions of cells with only a few discrete adhesion levels between cells, ignoring biologically observed continuous variations in expression levels and possible nonlinearities in molecular binding. In this paper, we present three models relating the surface density of cadherins to the net intercellular adhesion and interfacial tension for both discrete and continuous levels of cadherin expression. We then use then the Glazier-Graner-Hogeweg (GGH) model to investigate how variations in the distribution of the number of cadherins per cell and in the choice of binding model affect cell sorting. We find that an aggregate with a continuous variation in the level of a single type of cadherin molecule sorts more slowly than one with two levels. The rate of sorting increases strongly with the interfacial tension, which depends both on the maximum difference in number of cadherins per cell and on the binding model. Our approach helps connect signaling at the molecular level to tissue-level morphogenesis. Experimental measurements of cadherin binding employing a variety of approaches have obtained widely differing estimates of the per-cadherin pair-binding force, cell-cell adhesion force and surface tension at the tissue level linear-zipper model (LZM) based on experiments on N-cadherin cis-dimer model (CDM) (equation (8)) based on experiments on E-cadherin trans-homophilic-bond model (THBM) (equation (9)) based on experiments on C-cadherin saturation model (SM) (equation (10)), based on the observation that, for both the CDM and THBM models, when the cadherin binding between cells saturates, the number of bonds depends on the cell with the minimum cadherin concentration.Multiple transcriptional and post-translational signaling cascades can regulate cadherin expression levels, localization and per-cadherin binding strengths i.e., we assume no conformational changes in molecular structure during a simulation). We then explore how the sorting configuration and rate depend on a few essential parameters in our models. Compared to the rate of sorting for an aggregate with two levels of a single cadherin, simulations with more intermediate levels sort more slowly but the sorting rate is similar for aggregates with the same number of cadherin levels for all binding models. The speed of sorting increases strongly with the interfacial tension, which depends both on the maximum difference in number of cadherins per cell and on the binding model.This paper therefore proposes a simple framework to explore how homotypic cadherin binding at the molecular level could produce intercellular adhesion and eventually determine cell sorting at the tissue level. We neglect complex spatial and temporal changes in cadherin behavior, assuming that cadherin distributions are uniform and constant on the cell membrane and that adhesion-strength per molecular bond is also time-independent (CDM), the trans-homophilic-bond (THBM), and the saturation (SM) models to relate the cells' cadherin surface densities to the cell-cell adhesion energy.The nature of cadherin-cadherin binding determines the way the cell-cell adhesion energy, depends on cells' cadherin surface densities, and thus the correct binding model to use in simulations of cell sorting. Since more recent mutagenesis studies do not support the linear-zipper model CDM) The cis-dimer model  effective equilibrium constant and the surface  Finally, for the saturation model (SM), which applies for strong clustering of cadherins, or large differences in the number of molecules per cell, the concentration of bound cadherin pairs is given byintercellular adhesion energy density due to cadherin binding via the relation:energy density due to adhesion unrelated to cadherinsWe relate the concentration of cadherin pairs to the cell-cell interfacial-tension density over the contact area between two cells expressing different numbers of a single type of cadherin is defined The Glazier-Graner-Hogeweg model (GGH) Cellular Potts Modeleffective energy, H, to describe the behavior of cells, for instance, due to cell-cell adhesion. GGH simulations agree quantitatively with simple cell-sorting and other experiments To simulate cell sorting due to cell-cell adhesion, we used the cell index, intrinsic cell motility corresponding to membrane fluctuations resulting from cytoskeleton fluctuations. If the lattice has Monte Carlo Step (MCS) to be Cells in the GGH are extended domains of pixels  The effective energy between cells is due to cell-cell adhesion. (2) The cells have fixed and identical target volumes, membrane areas, and intrinsic motilities. (3) Cells do not grow, divide or die. (4) Cells are isotropic, so cadherins are uniformly distributed on the cell membrane and the cadherin concentration is constant in time. With these assumptions, the effective energy is:Each cell expresses a specific number of cadherins. The cell-cell adhesion energy relates to The relative strengths of cell-cell adhesions result in net forces which act on each cell. Depending on the relative hierarchy of cell-cell adhesive interactions the generated forces can either drive or suppress cell sorting. Equation (13) is the condition for the sorting to occur.e.g., during limb outgrowth, in which cells maintain both their antero-posterior and proximo-distal positions through differential adhesion.Why does sorting occur for most of the conditions that we consider in this paper? For two cadherin levels with eriphery , with a HBL), the total contact length between cells with different cadherin levels, measured in pixels:In an ideal, fully-sorted configuration, cells expressing the higher levels of cadherins will cluster together and round up into a solid sphere, surrounded by successive spherical shells of cells expressing successively lower levels of cadherins. To monitor the progress of cell sorting in our simulations, we define the heterotypic boundary length (WHBL) is simply the total interfacial tension (equations (8–10)) multiplied by the lengths:If cells express multiple cadherin levels, t. sorting relaxation time, Different aggregates may have different maximum  and minimum heterotypic boundary lengths (HBL) or weighted heterotypic boundary lengths (WHBL). To compare sorting in different aggregates, we normalize these lengths using the transformation:sorting rate, The We first investigated sorting completeness for the trans-homophilic-bond model ), with http://www.compucell3d.org/) which allows rapid translation of biological models into simulations using a combination of CC3DML and Python scripting. We presented our simulation codes in We implemented our simulations using the open-source software package CompuCell3D /weighted heterotypic boundary length (WHBL) for the THBM (equation (16)) in three cases:Cells with different numbers of levels of cadherin expression, but the same range between maximum and minimum expression number.Cells with different ranges between maximum and minimum expression number but with the same number of levels .Cells with different motilities, but with the same cadherin levels.We also investigated:Cells with different cadherin binding models, but the same range between maximum and minimum expression number for two, five, nine and continuous levels.NWHBL) for the cell aggregates in  to sort .According to the theory of phase separation in liquids, the sorting rate for simple fluids is proportional to the interfacial tension divided by the viscosity' In For different models with the same cadherin expression levels, for two-level aggregates , sortingt faster . Howevercomplete .When cells' expression of cadherin varies continuously, sorting still occurs, but more slowly than for discrete expression levels. The final configuration is imperfectly sorted since the intrinsic cell motility can overcome small differences in adhesion energy due to local missorting. The sorting rate depends on the interfacial tension rather than directly on the expression levels or the cadherin-binding model. Again, insufficient or excessive motility prevents complete sorting.From the considerations above we can say that, although individually the sorting kinetics in aggregates with each binding model are sensitive to the number of cadherin levels and the energy range, all models have similar global behaviors. For each model, sorting is always faster for smaller numbers of cadherin levels, independent of the energy expression range. The dependence of sorting time and completeness on the number of cadherin levels is also similar for the three models, although the SM model seems to sort slightly faster and more completely for large numbers of cadherin levels. In the absence of experiments determining the model to use, the SM is computationally more efficient for larger aggregates.E.g. we could transfect a GFP-cadherin plasmid construct into normally non-adherent CHO cells, so the amount of cadherin in each cell would be proportional to its fluorescence intensity. For discrete levels we could use multiple fluorescent tags. Cotransformation with a nuclear-targeted fluorescent protein of a different color would allow real-time cell tracking to determine cell motilities and positions.Our results could be checked by experiments controlling cadherin expression. Using the interfacial boundary length as a measure of sorting is experimentally inconvenient because current automated image segmentation cannot accurately extract the interfacial lengths from a stack of images. Instead, measuring the autocorrelation of the intensity in experimental and simulation image stacks would be much simpler. To represent a nuclear-targeted label in our simulations we could place a dot at each cell's center of mass with an intensity proportional to the cell's the number of cadherins. To represent cytoplasmic labeling, we could fill the entire cell volume with an intensity corresponding to the cadherin level and similarly for membrane labeling, we could label the cell's contour.log-log graph at right. Mean and error bars for these graphs are calculated from six simulation replicas.An alternative measure of sorting would use a clustering algorithm to track the number and size of homotypic cell clusters. This approach is straightforward in CC3D and relatively easy to implement in experiments using K-Means or K-Median clustering algorithms, as described in Comparing any of these bulk cell-sorting measures for experiments and simulations would allow us to infer the specific binding mechanism in a particular experiment, information otherwise difficult to obtain.et al. 2008 et al. 2009 At the beginning of a particular developmental phase, patterns of gene expression are often fuzzy initially, then gradually become distinct. Both changing cell identity and cell movement are possible mechanisms for refining initially fuzzy expression patterns or for fixing transient patterns of morphogens. Glazier etc…. Therefore future measurements should concentrate on dynamics of intra and inter-cellular mechanisms  related to cellular adhesion To provide better links/interplay between computer simulations and biological experiments, we would suggest carrying out measurements of the following key parameters Our studies based on the Glazier-Graner-Hogeweg model, investigated how homotypic cadherin binding at the molecular level affects cell-cell adhesion and determines cell sorting speeds at the tissue level. We have used three different microscopic models of cadherin-binding for discrete and continuous levels. The three binding mechanisms lead to similar cell-sorting behavior, although the saturation binding model is somewhat faster for larger aggregates with more cadherin levels. Sorting speed decreases with increasing numbers of cadherin levels. For classical sorting with two cadherin levels, sorting speed increases with the ratio between the two levels. Additionally, in each case a single optimum value for the cell motility results in the fastest sorting. Cell motilities above or below the optimum sort more slowly.Codes S1XML configuration file and python scripts for the simulations presented in the text.(BZ2)Click here for additional data file.Movie S1Sorting of cells expressing two cadherin levels - .(WMV)Click here for additional data file.Movie S2Sorting of cells expressing three cadherin levels - .(WMV)Click here for additional data file.Movie S3Sorting of cells expressing five cadherin levels - .(WMV)Click here for additional data file.Movie S4Sorting of cells expressing nine cadherin levels - .(WMV)Click here for additional data file.Movie S5Sorting of cells expressing five cadherin levels (as above) and motility = 5.(WMV)Click here for additional data file.Movie S6Same five cadherin levels but motility = 10.(WMV)Click here for additional data file.Movie S7Same five cadherin levels but motility = 40.(WMV)Click here for additional data file.Movie S8Same five cadherin levels but motility = 60.(WMV)Click here for additional data file.Movie S9Same five cadherin levels but motility = 80.(WMV)Click here for additional data file.


Bipolar Disorder (BD) is a debilitating syndrome that is often undiagnosed and under-treated. Population surveys show that persons with BD often self-medicate with complementary, alternative medicine (CAM) or integrative therapies in spite of limited research evidence supporting their use. To date no review has focused specifically on non-conventional treatments for BD. Our objective was to present a comprehensive review of non-conventional (complementary and integrative) interventions examined in clinical trials on BD, and to offer provisional guidelines for the judicious integrative use of CAM in the management of BD.PubMed, CINAHL, Web of Science and Cochrane Library databases were searched for human clinical trials in English during mid 2010 using Bipolar Disorder and CAM therapy and CAM medicine search terms. Effect sizes (Cohen’s d) were also calculated where data were available.Several positive high-quality studies on nutrients in combination with conventional mood stabilizers and antipsychotic medications in BD depression were identified, while branched-chain amino acids and magnesium were effective  in attenuating mania in BD. In the treatment of bipolar depression evidence was mixed regarding omega-3 fatty acids, while isolated studies provide provisional support for a multi-nutrient formula, n-acetyl cysteine, and L-tryptophan. In one study acupuncture was found to have favorable, but non-significant effects on mania and depression outcomes.Current evidence supports the integrative treatment of BD using combinations of mood stabilizers and select nutrients. Other CAM or integrative modalities used to treat BD have not been adequately explored to date, however some early findings are promising. Select CAM and integrative interventions add to established conventional treatment of BD and may be considered when formulating a treatment plan for patients diagnosed with BD. It is hoped that the safety issues and clinical considerations addressed in this paper may encourage the practice of safety-conscious and evidence-based integrative treatment of BD.


Apostichopus japonicus . By analysing transcriptome sequence data, here the protein precursors of six of these myoactive peptides  have been identified, providing novel insights on neuropeptide and endocrine-type signalling systems in echinoderms. The A. japonicus SALMFamide precursor comprises eight putative neuropeptides including both L-type and F-type SALMFamides, which contrasts with previous findings from the sea urchin Strongylocentrotus purpuratus where L-type and F-type SALMFamides are encoded by different genes. The NGIWYamide precursor contains five copies of NGIWYamide but, unlike other NG peptide-type neuropeptide precursors in deuterostomian invertebrates, the NGIWYamide precursor does not have a C-terminal neurophysin domain, indicating loss of this character in holothurians. NGIWYamide was originally discovered as a muscle contractant, but it also causes stiffening of mutable connective tissue in the body wall of A. japonicus, whilst holokinins (PLGYMFR and derivative peptides) cause softening of the body wall. However, the mechanisms by which these peptides affect the stiffness of body wall connective tissue are unknown. Interestingly, analysis of the A. japonicus transcriptome reveals that the only protein containing the holokinin sequence PLGYMFR is an alpha-5 type collagen. This suggests that proteolysis of collagen may generate peptides (holokinins) that affect body wall stiffness in sea cucumbers, providing a novel perspective on mechanisms of mutable connective tissue in echinoderms.Peptides that cause muscle relaxation or contraction or that modulate electrically-induced muscle contraction have been discovered in the sea cucumber  Peptides are evolutionarily ancient mediators of intercellular communication. In the animal kingdom, the use of secreted peptides as intercellular signalling molecules has probably been exploited most extensively in nervous systems. Thus, neurons release “neuropeptide” signalling molecules, which act as neurotransmitters, neuromodulators or neurohormones and have important roles in co-ordination of physiological processes and whole-animal behaviour Research on neuropeptide signalling systems has, of course, largely focused on mammals and other vertebrates. However, early on it was recognised that invertebrates are attractive as model systems for neuropeptide studies because of the relative simplicity of their nervous systems Echinoderms  are of particular interest for phylogenetic studies because they are one of only three non-chordate phyla that are deuterostomes Asterias rubens and Asterias forbesi on account of their immunoreactivity with antibodies to a molluscan FMRFamide-related neuropeptide pQDPFLRFamide. Subsequently, two SALMFamide neuropeptides (GFSKLYFamide and SGYSVLYFamide) were isolated from another echinoderm species, the sea cucumber Holothuria glaberrimain vitro pharmacological studies have revealed that SALMFamide neuropeptides are widely expressed in echinoderm nervous systems and act as inhibitory neurotransmitters, causing relaxation of a variety of different echinoderm muscle preparations Research on neuropeptides in echinoderms is still in its infancy, but opportunities for rapid progress are being provided by sequencing of the genomes and/or transcriptomes of echinoderm species Apostichopus japonicus for peptides that affect the in vitro contractility of the radial longitudinal muscle (RLM) from this species A. japonicus by incorporating the use of intestine preparations as a bioassay system alongside the RLM An alternative functional-based strategy for identification of echinoderm neuropeptides was used by Iwakoshi et al. to screen extracts of the sea cucumber A. japonicus. Analysis of the sequences of these peptides revealed that they are structurally similar to the SALMFamide neuropeptides previously identified in the sea cucumber H. glaberrima (GFSKLYFamide and SGYSVLYFamide). However, the A. japonicus peptides have a phenylalanine (F) residue in the position occupied by a leucine (L) residue in the H. glaberrima peptides, broadening the structural characteristics of SALMFamide neuropeptides to SxF/LxFamide Amongst the peptides identified by Ohtani et al. (1999) were two peptides (GYSPFMFamide or “Sticho-MFamide-1” and FKSPFMFamide or “Sticho-MFamide-2”) that cause relaxation of the intestine in A. japonicus intestine, a peptide that causes contraction of both the intestine and the RLM was identified as NGIWYamide A. japonicus and in nerve fibres innervating the tube feet, tentacles, intestine and body wall dermis In addition to the SALMFamide peptides that cause relaxation of the A. japonicus as myoactive peptides also affect the stiffness of collagenous body wall preparations from this species. Thus, NGIWYamide causes stiffening of the body wall, whereas holokinin-1 and holokinin-2 both cause softening of the body wall. The peptide stichopin, which inhibits electrically induced contractions of the RLM, also exerts an inhibitory effect on body wall preparations, blocking acetylcholine induced stiffening of the body wall. Accordingly, it was proposed that these peptides act in vivo as neuropeptides that control the stiffness of connective tissue in the body wall in vitro, are also neuropeptides that are released by nerve fibres innervating the body wall.Interestingly, four of the peptides originally identified in A. japonicus, there is at present no such evidence available for any of the other eighteen myoactive peptides shown in A. japonicus, with identification of 29,666 transcripts (isotigs) A. japonicus that are shown in Whilst there is immunocytochemical evidence that both NGIWYamide and stichopin are realeased by neurons and therefore act as neuropeptide signalling molecules in A. japonicus isotigs in FASTA format was downloaded from the supporting information section (Dataset S1) of the online paper by Du et al. http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0033311). The data was then subject to BLAST analysis http://www.sequenceserver.com/), which is freely available to academic users A file containing the sequences of 29,666 http://web.expasy.org/translate). Proteins were assessed as potential precursors of secreted bioactive peptides by investigating a). the presence of putative monobasic or dibasic cleavage sites on the N-terminal and C-terminal side of the sequence of the bioactive peptide and b). the presence of a putative N-terminal signal peptide sequence, using the SignalP 3.0 server at http://www.cbs.dtu.dk/services/SignalP-3.0/To search for transcripts encoding putative precursor proteins for the myoactive peptides listed in http://www.ncbi.nlm.nih.gov/sra/) under the accession number SRA046386.For some of the isotigs identified as cDNAs enoding putative precursor proteins it was necessary to perform additional analysis of raw sequence data, which can be downloaded from the NCBI Short Read Archive (SRA) database (A. japonicus isotigs using a query comprising sequences of the two F-type SALMFamides previously identified in this species bounded by putative dibasic cleavage sites (KRGYSPFMFGKRFKSPFMFGKR) resulted in the identification of isotig 12925 as a putative SALMFamide precursor cDNA. However, translation of the 900 base sequence of isotig 12925 revealed that the FKSPFMFG and GYSPFMFG sequences were encoded on different reading frames. Therefore, raw sequence data was analysed and assembled manually to identify a full-length open reading frame encoding a 290-residue precursor protein, which comprises an N-terminal signal peptide and eight putative amidated neuropeptides bounded by dibasic cleavage sites  as a cDNA encoding the NGIWYamide precursor. The 238-residue NGIWYamide precursor comprises an N-terminal signal peptide and five copies of the sequence NGIWYG, which are located in the C-terminal half of the protein from residues 169 to 226  resulted in the identification of isotig 26630 (449 bases) as a cDNA encoding the stichopin precursor. Isotig 26630 contains an open reading frame encoding a 39 residue protein comprising an N-terminal signal peptide (residues 1–22) followed by the 17 residue sequence DRQGWPACYDSNGNYKC, which is identical to stichopin in all but two amino acid residues   . AnalysiA. japonicus isotigs using a query comprising the sequence of GN-19 (GGRLPNYAGPPRMPWLIHN) resulted in the identification of isotig 23619 (582 bases) as a cDNA encoding the GN-19 precursor. Isotig 23619 contains an open reading frame encoding a 82 residue protein comprising an N-terminal signal peptide (residues 1–24) and the GN-19 peptide sequence, which is located from residues 52 to 80 bounded by putative dibasic cleavage sites  resulted in the identification of isotig 12170 (429 bases) as a cDNA encoding the GLRFA precursor. Isotig 12170 contains an open reading frame encoding a 62 residue protein comprising an N-terminal signal peptide (residues 1–19) and the GLRFA peptide sequence, which is located from residues 30 to 34 bounded N-terminally by a putative dibasic cleavage site and bounded C-terminally by a putative monobasic cleavage site  as a partial cDNA encoding a protein sequence comprising 298 residues, with the sequence PLGYMFR located between residues 35 and 41  and SWYG-2 (SWYGTLG) did not reveal any transcripts encoding proteins containing these sequences. However, a transcript (isotig 11737) encoding a protein containing the sequence of SWYG-3 (SWYGSLA) was identified. Analysis of isotig 11737 revealed that it contains an open reading frame encoding 137 residues with the sequence SWYGSLA located from residues 125 to 131 (Aquifex aeolicus (NP_214225.1 GI:15606845), ii). a curvibacterial putative symbiont of the cnidarian Hydra magnipapillata (CBA26623.1 GI:260219765), iii) the bacterium Hydrogenivirga sp. 128-5-R1-1 (ZP_02177525.1 GI:163782528), iv). the bacterium Prevotella sp. oral taxon 472 str. F0295 (ZP_05918427.1 GI:260911861) and v). the bacterium Hydrogenobaculum sp. Y04AAS1 (YP_002121272.1 GI:195952982). Therefore, the 137-residue protein containing the sequence SWYGSLA may in fact be derived from a bacterial species associated with A. japonicus.BLAST analysis of the 5 to 131 . A putatA. japonicus isotigs using a query comprising the GYI sequence bounded by putative dibasic cleavage sites (KRGYIKR) revealed two isotigs encoding potential precursor proteins for this peptide: isotigs 09011 and 09012. Analysis of the sequences of these isotigs revealed that they both encode the same protein, with a single copy of the sequence GYI bounded by a lysine residue N-terminally and the sequence KRR C-terminally. Furthermore, submission the sequence of the protein encoded by isotigs 09011 and 09012 as a query in a BLAST analysis of the GenBank protein database revealed that it is a sea cucumber homolog of human UFM1-specific ligase 1  did not reveal any isotigs encoding proteins contain these sequences.BLAST analysis of the A. japonicusin vitro effects of these peptides on connective tissue and/or muscle is largely unknown. Here this issue was addressed by investigating the identity and properties of the proteins that these peptides are derived from. Six of the peptides  are derived from proteins that have an N-terminal signal peptide, indicating that these peptides are secreted as neuropeptide and/or endocrine-type signalling molecules. Furthermore, holokinins (PLGYMFR and related peptides), peptides that cause softening of the body wall in A. japonicus, appear to be derived from proteolysis of collagen, which provides an important new insight on the mechanisms of mutable connective tissue in sea cucumbers and possibly other echinoderms.Twenty peptides that affect the mechanical activity of connective tissue and/or muscle have been identified in the sea cucumber A. japonicusGYSPFMFamide (Sticho-MFamide-1) and FKSPFMFamide (Sticho-MFamide-2) were originally discovered as peptides that cause relaxation of the intestine in A. japonicus SALMFamide precursor, however, is that in addition to containing F-type SALMFamides, it also contains two putative L-type SALMFamide neuropeptides, GGYSALYFamide and VPELAESDGGQSKLYFamide, which appear to be homologs of the two L-type SALMFamides  that were originally discovered in the H. glaberrimaS. purpuratus revealed that in this species F-type and L-type SALMFamide neuropeptides are encoded by different genes, with seven F-type SALMFamides (SpurS1 – SpurS7) derived from one precursor protein and two L-type SALMFamides (SpurS8 and SpurS9) derived from a second precursor protein A. japonicus containing both F-type and L-type SALMFamides may reflect conservation of a characteristic of the common ancestor of sea cucumbers and sea urchins. Accordingly, the existence of separate precursors for F-type and L-type SALMFamides in S. purpuratus is presumably a consequence of duplication of a single SALMFamide gene in an ancestor of sea urchins, with subsequent loss of L-type and F-type SALMFamides in the gene copies that gave rise to genes encoding F-type and L-type SALMFamide precursors in S. purpuratus, respectively. Thus far, F-type SALMFamides have only been found in sea cucumbers and sea urchins, whereas L-type SALMFamides have been found in all echinoderms for which peptide sequence data are available  Perhaps the most interesting feature of the A. japonicusS. purpuratus, a protein containing two copies of a putative neuropeptide with the sequence NGFFFamide was identified in vitro pharmacological effects of NGFFFamide revealed that it causes contraction of sea urchin muscle preparations, consistent with the muscle-contracting action of NGIWYamide in A. japonicus. Interestingly, analysis of the sequence of the NGFFFamide precursor revealed the presence of a C-terminal neurophysin-like domain. Neurophysins are polypeptides that hitherto were thought to be uniquely associated with the precursors of vasopressin/oxytocin-type neuropeptides and which are required for biosynthesis of these neuropeptides Saccoglossus kowalevskii encodes a protein with a C-terminal neurophysin domain and five copies of the putative neuropeptide NGFWNamide and one copy of NGFYNamide, whereas in the cephalochordate Branchiostoma floridae there is a NG peptide precursor with a C-terminal neurophysin domain and two copies of the putative neuropeptide SFRNGVamide. Discovery of these genes demonstrated that the origin of neurophysin-containing NG peptide precursors could be traced back at least as far as the common ancestor of the deuterostomes. Therefore, it was anticipated that the precursor of NGIWYamide, the prototype of the NG peptide family, would also have a neurophysin domain. However, the identification of the NGIWYamide precursor in A. japonicus, as reported here, has revealed that it contains five copies of NGIWYamide but lacks a C-terminal neurophysin domain. Therefore, presumably the neurophysin domain has been lost from NG peptide precursors in the sea cucumber lineage that gave rise to A. japonicus.NGIWYamide is a pleiotropic neuropeptide because although it was originally discovered on account of its myoactivity B. floridae NG peptide SFRNGVamide is identical to the N-terminal region of a vertebrate neuropeptide named “neuropeptide S” or NPS B. floridae, the NPS precursor does not have a C-terminal neurophysin domain A. japonicus may be examples of NG peptide precursors that have lost their neurophysin domain. This suggests that the neurophysin domain is dispensable and may not be essential for NG peptide biosynthesis. However, if this is the case then why has it been retained in other lineages? Experimental studies that investigate the role of neurophysin in NG peptide biosynthesis are now required to address this issue.It is noteworthy that the A. japonicus on account of its inhibitory modulating effect on electrically induced contractions of radial longitudinal muscle (RLM) preparations A. japonicusA. japonicusThe peptide stichopin (DRQGWPACYDSKGNYLC) was originally isolated from A. stichopus that was used for peptide purification and sequencing The discovery of the 39 amino acid residue stichopin precursor, as reported here, supports the hypothesis that stichopin acts as a neuropeptide-type signalling molecule and as a peptide hormone in sea cucumbers. In particular, the presence of an N-terminal signal peptide is consistent with targeting of stichopin to the regulated secretory pathway. A noteworthy feature of the stichopin precursor is that it consists solely of a signal peptide (residues 1–22) followed by the stichopin peptide (residues 23–39), which is the simplest type of precursor protein for neuropeptides and peptide hormones. Furthermore, determination of the sequence of the stichopin precursor has revealed polymorphisms in the sequence of stichopin at residues 12 and 16, which may reflect differences between the population of A. japonicus body wall extracts that causes contraction or relaxation of intestine preparations from this species, but has no effect on the radial longitudinal muscle A. japonicus and investigation of its physiological roles as a putative neuropeptide or endocrine-type signalling molecule.The peptide GN-19 (GGRLPNYAGPPRMPWLIHN) was originally identified as peptide derived from A. japonicus body wall extracts that causes contraction of intestine preparations from this species and that potentiates electrically induced contraction of radial longitudinal muscle preparations A. japonicus will facilitate investigation of its physiological roles as a putative neuropeptide or endocrine-type signalling molecule.The peptide GLRFA was originally identified as a peptide derived from A. japonicus: holokinin-1 (PLGYMFR) and derivatives of holokinin-1 with either an oxidised methionine residue (PLGYM(O)FR, holokinin-2) or with a brominated tyrosine residue (PLGY(Br)MFR, holokinin-3) or with N-terminal truncation ). All four peptides cause inhibition of electrically induced contraction of radial longitudinal muscle (RLM) preparations and contraction of intestine preparations A. japonicusA. stichopus.Four holokinins have been isolated from in vitro (e.g. NGIWYamide and stichopin) are present in nerve process and/or endocrine-type cells located within the collagenous dermis of the body wall in vitro, may be derived from proteolysis of an alpha-5 type collagen in A. stichopus suggests other mechanisms by which the stiffness of dermis may be regulated. Whilst the possibility remains that the softening effect of holokinins in vitro is a pharmacological phenomenon that has no relevance to physiological control mechanisms, if proteolytic generation of holokinins from alpha-5 type collagen does occur in vivo then potential mechanisms by which these peptides exert their effects physiologically can be envisaged. For example, holokinins might cause softening of mutable connective tissue in the body wall dermis by competitively blocking interaction between the PLGYMFR sequence located in fibrils that contain alpha-5 type collagen and putative PLGYMFR-binding sites on other adjacent fibrils. Interestingly, previous studies on the endoskeleton of the sea urchin Paracentrotus lividus have revealed that in this collagenous tissue alpha-5 type collagen chains form heteromeric molecules with two alpha-1 type collagen chains. Furthermore, alpha-5 N-terminal propeptides are found at the surface of collagen fibrils and it has been suggested that these proteins may link collagen fibrils and therefore “might be of importance in the unique properties of mutable collagenous tissues” Mutable connective tissue in echinoderms changes between stiff and pliant states and the collagenous body wall of sea cucumbers is one of the best-studied examples of this A. japonicus  no putative precursor proteins were identified based on BLAST analysis of the A. japonicus transcriptome sequence data, which may indicate that the precursors of these peptides are encoded by low abundance transcripts or that mRNAs encoding precursors of these peptides are not expressed in the tissues/organs that were used for production of cDNA libraries for sequencing For six of the myoactive peptides isolated from A. japonicus UFM1-specific ligase 1 is bounded by basic amino acid residues that could serve as substrates for endopeptidases. However, it is possible that the proteolysis of A. japonicus UFM1-specific ligase 1 that putatively gives rise to the GYI peptide is simply an artifact of peptide extraction in vitro and not a physiological phenomenon.A putative precursor for the myoactive peptide GYI was identified as the sea cucumber homolog of human UFM1-specific ligase 1, but the physiological relevance of this is uncertain. The GYI sequence in Apostichopus SWYG peptides revealed a potential precursor for SWYG-3 but not for SWYG-1 and SWYG-2. However, analysis of the sequence of the protein containing the sequence of SWYG-3 (SWYGSLA) indicates that it may in fact be derived from a bacterial species that is associated with A. japonicus.Analysis of the transciptome data for putative precursors of the three in vitro proteolysis of proteins derived from the tissues/organs analysed or from commensal/symbiotic bacterial species associated with the study organism. The utilization of transcriptome sequence data, as employed here, is a valuable complementary approach in discovery of peptide signalling molecules because by identifying the precursor proteins of bioactive peptides it is possible to determine which peptides are likely to be utilized as signalling molecules in vivo. Here precursor proteins for SALMFamide neuropeptides, NGIWYamide, stichopin, GN-19 and GLRFA have been identified in the A. japonicus. For SALMFamides, NGIWYamide and stichopin, there was already evidence from immunocytochemical studies that these peptides act as secreted neuropeptide or endocrine-type signalling molecules A. japonicus. Lastly, whilst it appears that the holokinins may not act as conventional neuronal or endocrine-type secreted peptide signalling molecules in A. japonicus, the discovery that these peptides may be derived from collagen proteolysis has provided a potentially important new insight on the physiological mechanisms that mediate regulation of the mechanical properties of connective tissue and muscle in echinoderms.The GYI and SWYG-3 peptides highlight the difficulties associated with using extracts of organs or other body parts for discovery of putative peptide signalling molecules. Some of the peptides identified as bioactive molecules biochemically may be generated artifactually as a consequence of Figure S1Putative protein from which the peptide SWGSLA is derived.(PDF)Click here for additional data file.Figure S2Putative protein from which the peptide GYI is derived.(PDF)Click here for additional data file.


Even though, Highly Active Antiretroviral Therapy (HAART) has resulted in significant reduction in mortality associated with Acquired Immune Deficiency Syndrome (AIDS), the side-effects and difficulties in patient compliance warrants the search for new therapeutic options. One potential strategy is to design chemokine analogues that will prevent the entry of human immunodeficiency virus-1 (HIV-1) into the target cell by competitively blocking its interaction with CC chemokine-5 (CCR5) receptor. The objective of the present study is to design and validate the efficacy of chemokine analogues based on the viral macrophage inflammatory protein-II (vMIP-II) core as putative anti-HIV agents.In the present study we have synthesized the chemokine analogues by Fmoc solid phase peptide synthesis and were purified to homogeneity by semi preparative RP-HPLC. Molecular mass of the analogues were confirmed by MALDI-TOF MS. Structural characterization was done by CD spectroscopy. Their interaction with CCR5 receptor was analyzed by calcium release studies.The analogues designed were obtained in high purity and correct identity and they displayed similar patterns on the CD spectra to their parent template vMIP-II. The analogues displayed significantly lower toxicity in MTT assays. The interactive nature of the analogues was evident in calcium release studies where, the calcium flux varies with the type of the grafted N-terminus.The findings in this study highlight the potential of vMIP-II to serve as a valuable target in designing chemokine analogues, which have the efficiency to serve as putative anti HIV- 1 agents.