Pluripotent stem cells are uniquely capable of differentiating into somatic cell derivatives of all three germ lineages, therefore holding tremendous promise for developmental biology studies and regenerative medicine therapies. Although temporal patterns of phenotypic gene expression have been relatively well characterized during the course of differentiation, coincident patterns of endogenous extracellular matrix (ECM) and growth factor expression that accompany pluripotent stem cell differentiation remain much less well-defined. Thus, the objective of this study was to examine the global dynamic profiles of ECM and growth factor genes associated with early stages of pluripotent mouse embryonic stem cell (ESC) differentiation. Gene expression analysis of ECM and growth factors by ESCs differentiating as embryoid bodies for up to 14 days was assessed using PCR arrays , and the results were examined using a variety of data mining methods. As expected, decreases in the expression of genes regulating pluripotent stem cell fate preceded subsequent increases in morphogen expression associated with differentiation. Pathway analysis generated solely from ECM and growth factor gene expression highlighted morphogenic cell processes within the embryoid bodies, such as cell growth, migration, and intercellular signaling, that are required for primitive tissue and organ developmental events. In addition, systems analysis of ECM and growth factor gene expression alone identified intracellular molecules and signaling pathways involved in the progression of pluripotent stem cell differentiation that were not contained within the array data set. Overall, these studies represent a novel framework to dissect the complex, dynamic nature of the extracellular biochemical milieu of stem cell microenvironments that regulate pluripotent cell fate decisions and morphogenesis. In vitro, ESCs are commonly induced to differentiate via the spontaneous assembly of cell aggregates in suspension referred to as “embryoid bodies” (EBs) For three decades, embryonic stem cells (ESCs) have been used as a model of mammalian developmental morphogenesis in order to define and characterize mechanisms of self-renewal and differentiation of pluripotent cells in vitro to specific cell phenotypes by precisely controlling the biochemical composition of the cell microenvironment. This strategy, often inspired by principles of developmental biology, has been successfully employed to direct pluripotent stem cell differentiation to certain cell types Exogenous administration of ECM and growth factor molecules in different combinations and sequences has been used to direct the differentiation of stem cells The objective of this study was to globally assess the dynamics of ECM and growth factor expression associated with the differentiation of ESCs within the EB microenvironment using PCR arrays for gene expression and pathway analyses. Gene expression of EB differentiation focused on ECM components, including cell adhesion molecules, matricellular proteins, integrins, and proteases, as well as growth factors, including members of the BMP, FGF, transforming growth factor β (TGFβ), and interleukin (IL) families. Gene expression profiles were contrasted using hierarchical clustering, k-means clustering, and statistical mapping to identify different global patterns of expression, as well as shared profiles of independent molecules; the combination of these approaches enabled the identification of groups of molecules expressing either coincident or divergent expression patterns. Subsequent pathway analyses highlighted key signaling pathways capable of acting on transcription factors regulating ESC phenotype at different stages of differentiation that were reconstructed solely from ECM and growth factor gene expression data. Characterizing the dynamic relationships between ECM/growth factor expression and EB differentiation using the quantitative analytical framework described provides new insights into the composition of the extracellular microenvironment regulating pluripotent stem cell biology and associated with early morphogenic differentiation events.3 U/mL leukemia inhibitory factor (LIF) (ESGRO). ES cells were passaged every two to three days before reaching ∼70% confluence. To initiate EB culture, adherent ESCs were detached from the gelatin-coated dishes using 0.05% Trypsin/0.53 mM EDTA (Mediatech) and 100 mm bacteriological grade polystyrene Petri dishes (Corning) were inoculated with 10 mL of a suspension of ESCs (4×105 cells/mL) in differentiation media (ESC media without LIF). EB suspension cultures were maintained on rotary orbital shakers  at 40 rpm at 37°C in 5% CO2 for the entire duration of suspension culture. Previous work from our lab has demonstrated that rotary orbital suspension culture methods result in greater yields of homogeneous populations of EBs Mouse embryonic stem cells  were initially expanded on a feeder layer of mouse embryonic fibroblasts and subsequently cultured feeder-free on 0.1% gelatin-coated polystyrene cell culture dishes (Corning) with Dulbecco's modified eagle medium (Mediatech), supplemented with 15% fetal bovine serum (HyClone), 2 mM L-glutamine (Mediatech), 1× MEM non-essential amino acid solution (Mediatech), antibiotic/antimycotics (Mediatech), 0.1 mM β-mercaptoethanol , and 10EB morphology was monitored daily by phase microscopy for up to 14 days of differentiation using a TE2000 microscope (Nikon) and a Spot Flex camera . For histological analysis, EBs collected at different stages of differentiation  were fixed with 10% formalin for 30 minutes and embedded in Histogel® (Richard-Allan Scientific). Histogel®-embedded samples were dehydrated through a series of alcohol and xylene rinses prior to paraffin embedding. Sections of EB samples (5 µm each) were obtained using a Microm HM 355S rotary microtome and stained with hematoxylin and eosin (H&E) using a Leica AutoStainer XL. Stained slides were coverslipped using low viscosity mounting medium  and imaged on a Nikon 80i microscope equipped with a SPOT Flex Camera (Diagnostic Instruments).Gapdh), which were each independently validated with appropriate positive cell controls. Relative levels of pluripotent gene expression were calculated compared to undifferentiated ESC samples and normalized to Gapdh using the ΔΔCt method Gapdh expression levels.RNA was extracted from undifferentiated ESCs and EBs at days 4, 7, 10, and 14 of differentiation (n≥3 for each sample) using the RNeasy Mini Kit (Qiagen). Complimentary DNA was reverse transcribed from 1 µg of total RNA using the iScript cDNA synthesis kit (Bio-Rad), and real-time RT-PCR was performed using SYBR Green technology with a MyiQ cycler (Bio-Rad). Beacon Designer software was used to design forward and reverse primers for pluripotency and differentiation markers as well as for the housekeeping gene glyceraldehyde-3-phosphate dehydrogenase . Genomic DNA was eliminated by mixing 0.5 µg RNA with 5× gDNA Elimination Buffer and RNase-free water before being incubating at 42°C for 5 minutes. The RT cocktail  was prepared and added to the elimination buffer mixture. Each cDNA sample was synthesized in an iCycler Thermal Cycler (Bio-Rad)  and diluted with RNase-free water after synthesis was complete. RT-PCR was performed by first preparing the experimental cocktail  and then equally distributing the cocktail (25 µL) into all of the individual wells of the PCR 96-well array (Mouse Extracellular Matrix and Adhesion Molecules array or Mouse Growth Factors array). Only one gene, secreted phosphoprotein 1 (Spp1), overlapped between both arrays besides the housekeeping genes and internal controls. Each array was tightly sealed with optical thin-wall 8-cap strips and amplified in a MyiQ cycler (Bio-Rad) with a two-step cycling program . Fold changes in gene expression were analyzed using the ΔΔCt method of quantitation, whereby samples of EBs from different time points  were compared relative to undifferentiated ESC values after individual sample values were normalized to internal Gapdh levels.For SuperArray RTGapdh as the normalization gene as described above. Initially, the results of the independent ECM and Growth Factor PCR arrays were separately analyzed by Genesis (Release 1.7.5) array analysis software. Two-dimensional hierarchical clustering of the log2-transformed data sets was performed across the different genes and time points using Euclidean distance and average linkage clustering. The clustering results were represented visually by a heat map dendrogram, with green indicating decreased expression and red indicating increased expression relative to undifferentiated ESCs. The relative color intensity values corresponding to the magnitude of fold change (either an increase or a decrease) were set between −7.0 and 7.0 to provide a distinct color range for all log-transformed magnitudes.Gene expression differences by differentiating EBs were calculated as fold change increases or decreases at the different time points examined compared to ESCs, using Prior to all further analysis, the ECM and Growth Factor array data sets were combined and examined together. The average fold-change values of ESCs and EBs for each gene from the entire time course were analyzed using k-means clustering analysis in Genesis software (version 1.7.5). In order to determine the optimal number of k-means clusters that sufficiently captured the different distinct profiles of the entire data set, the cluster number was varied between 4 and 20 and evaluated for a maximum of 300 iterations. Analysis with fewer clusters (4–8) did not distinguish different patterns of expression as clearly, whereas larger numbers of clusters (>12) yielded some independent groups with as a few as 1–2 genes; therefore, subsequent k-means analysis was performed using 12 clusters.p<0.05). Significant differences in expression fold-change between consecutive time points were depicted with a branch schematic for all genes from the array, with increasing or decreasing slopes representing positive or negative fold differences, respectively, while non-significant differences were represented as horizontal lines.Significance testing was conducted using SYSTAT (Version 12) software. For individual genes, expression fold change comparisons across time points were evaluated using a one-way analysis of variance (ANOVA) with subsequent post-hoc Tukey analysis to determine significance (p<0.01) using the Benjamini-Hochberg (B–H) multiple testing correction method to account for false-positives and were then ranked in decreasing order of significance ). Based on published literature reports, IPA generated networks that included interactions between the focused sets of array molecules as well as other molecules present in the IPA database. Each of the networks generated by IPA, which included up to 25 focus genes, was assigned a relative score reflecting the probability that any given gene in a particular network was present by chance; higher scores indicate a lower likelihood .Pathway analysis of genes that exhibited significant changes over time was performed using Ingenuity Pathway Analysis  to examine the biological functions and signaling pathways that were implicated in EB development. For each time point , fold-changes (−46.25 to −1 and 1 to +513.58) were filtered in IPA using a minimum 2-fold change threshold; from these genes, a list of “focus” genes was generated that contained molecules present in IPA's knowledge database (78% of eligible molecules). The top biological functions and networks for each time point were assessed based on the resulting eligible genes from the array (“focus genes”) and IPA's database containing gene associations . Biological functions were tested for significance  was expressed at significantly increased levels by day 14 compared to all other time points examined  and mesoderm differentiation  increased over time (data not shown), thus further confirming the expected time course of differentiation. The coincident decrease in pluripotency and increase in germ lineage marker expression, as well as the EB morphological changes that occurred over 14 days of suspension culture were consistent with previous studies from our laboratory The time course of EB differentiation was examined by morphology and phenotypic markers prior to performing semi-global gene expression analysis. Using rotary orbital suspension culture, the formation of EBs and maintenance of the EB population remained relatively uniform over the time course examined , similarn factor , decreast marker . ConversIn order to visualize the global gene expression patterns exhibited by EBs and to identify any subsets of molecules undergoing coincident expression changes over time, two-dimensional hierarchical clustering was performed independently for the Extracellular Matrix and Adhesion Molecules array  consistently increased between each of the different time points examined . In the Although hierarchical and k-means clustering analysis enabled the identification of subgroups of genes that were similarly expressed over the course of differentiation, the correlative relationships were based upon the magnitudes of fold-change relative to the starting state (ESCs), but didn't account for statistical changes occurring between each of the discrete time points examined. Parallel independent ANOVA analysis for each gene was therefore performed to evaluate significant changes in gene expression over time . In geneFgf2, matrix metalloproteinase 2 (Mmp2), and the housekeeping genes heat shock protein 90 kDa alpha, class B member 1 (Hsp90ab1) and β-actin (Actb). In the previous analyses, hierarchical and k-means clustering results similarly indicated that expression of both Hsp90ab1 , fibroblast growth factors (6/17 genes), interleukins (10/10 genes), and matrix metalloproteinases (4/12 genes) all appeared within the group of genes that did not change significantly between consecutive time points , whereasNetwork analysis was performed using only the genes that changed significantly over the course of differentiation and exhibited more than two-fold expression changes compared to undifferentiated ESCs. Using the IPA database, biological functions reflected by these genes were generated and ranked (only the 10 highest- (A) and 10 lowest-ranked (B) functions are shown in Fn1; day 4), Mmp9 (day 7), Vegfa (day 10), and insulin-like growth factor 1 . At day 4 . Many of the molecules included in the top day 4 network were related to the p53 transcription factor that acts to suppress the pluripotent marker Nanog and thereby induce differentiation p53; however, several growth factors that act on p53 in the day 4 network were not present at day 7, indicating an emergence of different roles for growth factors by day 7. Along with the greater number of genes significantly increasing over time, the number of genes included in the networks at later time points also grew such that the top networks for days 10 (Fli1), TATA box binding protein-associated factor 4B (Taf4b), and cell division cycle 73 (Cdc73), linked to extracellular factors, but their connectivity was low (2–3 connections) compared to the number of connections formed to p53 at days 4 and 7. This increase in the number of nuclear factors present in the day 10 network is suggestive of fewer commonly shared nuclear targets by the population of differentiating cells, which is consistent with the onset of diverging cell phenotypes within EBs to different germ lineages. Overall, the physical and biological network connections generated using statistically significant array data highlight the ability of ECM and growth factor expression patterns alone to elucidate global trends in cell growth and differentiation as a function of time.The networks generated from the gene expression data highlighted the transition of the differentiating ESCs away from a pluripotent state . Through this analysis, functional relationships based on unrelated previous studies emerge from the data that allow for new hypothesis generation and testing regarding exogenous molecules capable of affecting ESC differentiation.Complementary information provided from different forms of gene expression analysis yields an overall more comprehensive characterization of the temporal dynamics of EB differentiation than individual analyses alone. Some molecules appear consistently throughout the time course and change their molecular interactions with time, while others are unique to certain stages of differentiation. As an illustrative example, or array  and was  Emilin1  when the Emilin1 . When viin Vegfa  that emeFn1 as an important molecule in the examined EB system, due to the fact that it didn't exhibit large fold changes over the time course examined. Further analysis using parallel ANOVAs indicates that Fn1 expression increases significantly by day 14 , although it was present in the top network at day 4 with a single connection. Analysis displayed a relationship between Spock1 with Col18A1, a hub gene not included in the arrays, but highly connected to several ECM and growth factor genes contained in the arrays , as well as other highly connected genes (p53 and Fn1). The aforementioned examples of Fn1 and Spock1 demonstrate that a combination of analytical tools can identify potential key regulators in the differentiation system that would have otherwise been overlooked by single forms of analysis alone.Just as each individual analysis lends insight when examining specific molecules, the range of analyses presented is critical for extracting a more global perspective of EB morphogenesis from the array data. Researchers often rely on a single method for assessing large data sets, typically either hierarchical clustering or pathway analysis, which can potentially result in overlooking molecules important to the system. For example, performing clustering  alone did not result in the identification of y day 14 , along wostn/Vtn , while Aostn/Vtn . HoweverExtracellular factors, including matrix molecules and growth factors which are typically not highlighted so much as transcription factors to examine differentiation patterns, exhibited different dynamic signatures during EB differentiation that accompany changes in ESCs, such as decreased pluripotency and the onset of tissue morphogenesis. Semi-global transcriptional network analysis of extracellular factors expressed by pluripotent cells in dynamic environments highlighted the potential importance of such endogenous molecules and their utility in assessing the temporal shifts in tissue morphogenesis of the system. In order to analyze the wide spectrum of matrix molecules in this study, multiple methods were used that highlighted differences in expression patterns through clustering tools and focused on the relationships between the molecules via network analysis. Subsets of genes with diverging expression values (i.e. groups that exhibited opposing signatures over time) emerged from k-means and statistical analyses. The simultaneous increase and decrease of different sets of molecules is likely necessary for the onset of many differentiation events, and the identification of these sub-groups could be critical for further understanding the coincident cell phenotype specification. This study also demonstrates the potential caveats of examining individual molecules in a one-dimensional fashion and neglecting the global systems view that contributes considerably to the fundamental understanding of emergent biology. In contrast, the combination of clustering/statistical analyses with network mapping provides a multi-faceted approach that enables a more in-depth understanding of the dynamic nature and processes of the EB microenvironment. Overall, these insights provide a better understanding of the transcriptional changes for ECM molecules and growth factors that accompany embryonic morphogenesis and thereby enable novel routes to consider engineering the differentiation of ESCs to specific lineages within EBs.Figure S1Embryoid differentiation. (A–D) Histological examination of EB differentiation with H&E staining. (E) Gene expression of Oct-4, marker of pluripotency, during EB differentiation decreases at later time points of differentiation. ANOVA: # p<0.05 compared to ESCs (day 0), † p<0.05 compared to days 4 and 7.(DOCX)Click here for additional data file.Table S1Genes in each cluster represented in . Hierarchical clustering identified five gene groups based on relative expression over time. Clusters I and IV increased over time, clusters II and V decreased over time, and cluster III maintained relatively unchanged gne expression levels over time.(DOCX)Click here for additional data file.Table S2Genes in each k-means plot represented in . K-means analysis defines temporal gene expression, refining patterns of expression and separating hierarchical clusters. Clusters B–E correspond to clusters II and V; clusters F–I correspond to clusters I and IV; clusters J–M correspond to cluster III.(DOCX)Click here for additional data file.Table S3Genes represented in . Liste of genes separated by ANOVA analysis that do change statistically over time (4C–F) as well as those that do not change statistically over time (4B).(DOCX)Click here for additional data file.


One important aim in cancer treatment is to kill cancer cells to control tumor growth and achieve remission. However, cancer cells have strong capability to adapt to hostile environment and evolve under stress. This posts a major challenge to the treatment as most of current therapeutic strategies fail to address how to prevent cancer cells from evolution while trying to kill them. The outcome of such therapeutic strategies is the emergence of harder-to-treat malignancies once they relapse. This has been clearly recognized in targeted cancer therapy using tyrosine kinase inhibitors . For insSIRT1 is a key player promoting acquisition of genetic mutations for CML drug resistance [SIRT1 encodes a protein deacetylase that deacetylates histones and non-histone proteins for diverse cellular functions including DNA damage repair. In the model system the authors used, BCR-ABL mutations are acquired through a de novo process that is dependent on BCR-ABL expression [de novo acquisition of BCR-ABL mutations in blast crisis CML cells and prevents CML cell relapse from imatinib treatment. Two more recent reports have shown that SIRT1 is activated by BCR-ABL in both kinase dependent and independent manners, and that SIRT1 activation promotes BCR-ABL mediated leukemogenesis and CML stem/progenitor cell survival from imatinib treatment [de novo mutation acquisition of HPRT (hypoxanthine phosphoribosyl transferase) gene in CML and prostate cancer cells when they are treated with the chemotherapeutic agent camptothecin. Interestingly, the authors showed that the role of SIRT1 in promoting mutation acquisition is associated with its ability to enhance aberrant DNA damage repair, in particular, the error-prone non-homologous end joining (NHEJ) repair.In a recent study, Wang et al showed that mammalian stress response gene sistance . SIRT1 epression . SIRT1 ireatment , 5. The SIRT1−/− embryonic stem cells [SIRT1−/− mouse embryonic fibroblasts [SIRT1−/− mice, once survive from early developmental defect, do not exhibit the increased incidence of spontaneous tumors [The findings by Wang et al apparently contrast with previous reports that SIRT1 maintains genome integrity , 7, whicem cells , 7, imparoblasts . Furtherroblasts  and prevroblasts . Therefos tumors  and refes tumors , new gens tumors . Interess tumors . It is pAlthough molecular details how therapeutic stress signals mutation acquisition and cancer evolution are yet to be worked out, the findings by Wang et al have clear translational implication. Given the roles of SIRT1 in CML molecular pathobiology and drug resistance, SIRT1 inhibition in combination with BCR-ABL inhibitors may not only help eradicate residual CML stem cells but also prevent them from acquiring resistant mutations and evolution. Such a strategy may benefit treatment of other types of malignancies as well.


Breast cancer genomes have revealed a novel form of mutation showers (kataegis) in which multiple same-strand substitutions at C:G pairs spaced one to several hundred nucleotides apart are clustered over kilobase-sized regions, often associated with sites of DNA rearrangement. We show kataegis can result from AID/APOBEC-catalysed cytidine deamination in the vicinity of DNA breaks, likely through action on single-stranded DNA exposed during resection. Cancer-like kataegis can be recapitulated by expression of AID/APOBEC family deaminases in yeast where it largely depends on uracil excision, which generates an abasic site for strand breakage. Localized kataegis can also be nucleated by an I-SceI-induced break. Genome-wide patterns of APOBEC3-catalyzed deamination in yeast reveal APOBEC3B and 3A as the deaminases whose mutational signatures are most similar to those of breast cancer kataegic mutations. Together with expression and functional assays, the results implicate APOBEC3B/A in breast cancer hypermutation and give insight into the mechanism of kataegis.DOI:http://dx.doi.org/10.7554/eLife.00534.001 The genomes of cancer cells contain mutations that are not present in normal cells. Some of these prevent cells from repairing their DNA, while others give rise to tumours by causing cells to multiply uncontrollably. Moreover, some of the mutations in breast cancer cells occur in clusters—a phenomenon known as kataegis (from the Greek for ‘thunderstorm’).Kataegic mutations occur almost exclusively at a cytosine preceded by a thymine. This suggests that a family of proteins called AID/APOBEC enzymes—which remove amine groups from cytosines—may be involved in generating these mutations. In this study, Taylor et al. confirm this possibility by showing that expressing individual members of the AID/APOBEC family of enzymes in yeast cells increases the mutation frequency and induces kataegis.The kataegis triggered by the AID/APOBEC enzymes could be localised through the introduction of double-stranded breaks into the DNA: Taylor et al. suggest that this might happen because repairing the breaks exposes single-stranded DNA, which the AID/APOBEC enzymes then act upon. By comparing the mutations induced in the yeast cells with those observed in breast cancer cells, Taylor et al. identified APOBEC3B as the enzyme most likely to be responsible for kataegis in breast cancer . Moreover, they showed that APOBEC3B was highly expressed in breast cancer cell lines, and that APOBEC3B and APOBEC3A can also cause DNA damage in human cells.Taken together, the findings provide key insights into the mechanism by which kataegis arises, and identify two proteins likely to contribute to the mutations seen in breast cancer. Further work is now required to determine whether these enzymes also give rise to mutations in other forms of cancer.DOI:http://dx.doi.org/10.7554/eLife.00534.002 Whole genome sequencing of 21 breast cancers recently revealed the presence in more than half the cancers of a novel form of localised hypermutation (termed kataegis) in which clusters of multiple same-strand mutations at C:G pairs are focused on multikilobase-long genomic regions with adjacent mutations within each cluster separated by one to several hundred base pairs . AlthougMembers of the AID/APOBEC family of enzymes   during the period of AID/APOBEC induction and clonal expansion  . Genome xpansion . A hyperxpansion  gave a sThe distances between neighbouring mutations in the AID* yeast transformants are displayed as rainfall plots . While tThe overwhelming majority of the proximal mutations in the AID* transformants do not occur as isolated mutational pairs but, rather, are found in clusters. Thus, if we define proximal mutations as a pair of mutations that are located <8.5 kb apart (a distance that excludes 99% of the singlet mutations) and define a cluster as a stretch of DNA containing ≥5 proximal mutations, we find that 75% of the AID*-induced proximal mutations are actually parts of clusters. These clusters typically extend over 6–15 kb (with the full range detected being 1.8–30 kb) and contain anything up to 26 mutations . This clExploring the mutational spectra, we find that the majority (76%) of the mutations in the yeast AID* transformants are C→T transitions, although transversions do occur and these are preferentially associated with the kataegic stretches . TransveWhereas C→T transitions will likely arise through direct replication over uracils generated by cytidine deamination, transversions are presumably due to replication over abasic sites created through uracil excision by uracil-DNA glycosylase (UNG). The transversions exhibit a strong (4- to 10-fold) bias for C→G rather than C→A substitutions  suggestiung1Δ transformants was accompanied by a dramatic shift away from mutational clustering , 274 of the 1064 mutations observed in AID* wild type transformants are found within clusters compared to 28 of the 2088 mutations in the AID* ung1Δ transformants  or by the frequency of kataegic events (26 kataegic stretches in 40 AID* transformants in the wild type background vs 4 kataegic stretches in 19 AID* transformants in ung1Δ background)  . Thus, ikground) .CAN1 locus, and asked whether co-expression of I-SceI together with the APOBEC3G* deaminase increased the likelihood of kataegis in the vicinity. We chose to use APOBEC3G* for this experiment since it gave a good mutation load but a lower proportion of kataegic mutations than AID*  has been shown to exhibit a preference that accords with the breast cancer kataegic mutations. Their flanking sequence preferences  whilst allowing more precise quantitation of the degree of preference. With regard to APOBEC3A and APOBEC3B, the results reveal that  . InteresAlthough APOBEC3A has been shown to be capable of causing genomic damage in mammalian cells , the samAlthough kataegis could easily have resulted from a transient spike in deaminase expression during tumour development, it was interesting to ascertain whether APOBEC3A or APOBEC3B expression could be detected or induced in breast cancer-derived cells. RNA analysis revealed that although several APOBEC3s can be expressed in individual breast cancer cell-lines, the highest and broadest pattern of expression was evident with APOBEC3B . ConsistExpression of AID/APOBECs cytidine deaminases in yeast generates mutations across the genome, a proportion of which are found in clusters. Since completing this work, two other groups have also demonstrated that cytidine deaminases can generate such clustered mutations . Here weThe stimulation of local kataegis in yeast by the induction of an I-SceI break indicates that the process occurs during DNA break repair, most likely by AID/APOBEC-catalysed deamination of cytidines exposed on single-stranded DNA during the resection phase of homology-mediated repair. The lengths of the kataegic stretches (mostly in the range 6–15 kb) are in the same order as the extent of resection observed during yeast DNA break repair ; the C→T transition mutations would be the result of direct replication over the non-excised uracil. In contrast, the action of UNG on uracil in a stretch of exposed single-stranded DNA may yield an abasic site that is replicated over by a translesion polymerase rather than repaired.The yeast experiments indicate that kataegis can be triggered by DNA breaks, whether generated through the joint action of the deaminase and UNG or by other processes. The same likely holds true for the breast cancer kataegis. However, there is no reason why kataegis should be restricted to such initiating triggers. One can well imagine that other processes that cause significant exposure of single-stranded DNA  can lead to mutation of human papilloma viral DNA  as well Thus, APOBEC3B and/or APOBEC3A are the deaminases likely responsible for the breast cancer hypermutation although it remains possible that other APOBEC3s might contribute to genome mutation in other tumours. With regard specifically to kataegis, given that double strand breaks are a common feature of tumour development, it will obviously be interesting to discover whether whole genome sequencing of other tumour types also reveals evidence of kataegic hypermutation and whether, in light of the fact that the AID/APOBEC family has undergone considerable expansion in primates, such kataegic hypermutation might also have contributed more generally to recent genome evolution.MATa; his3Δ1; leu2Δ0; met15Δ0; ura3Δ0) and the ung1Δ::kanMX4 derivative were from Euroscarf . The rev1Δ::LEU2 derivative was generated by homologous recombination to remove the open reading frame of REV1 using a LEU2 cassette generated by PCR using 157-bp 5′ homology arm and 200-bp 3′ homology arm. The CAN1::KanMX-ISceIRS strain was generated by inserting a 1.4-kb module containing the I-SceI-recognition site and the KanMX selection cassette  that had been grown overnight in glucose medium to repress expression from the GAL1 promoter were diluted 1:100 into galactose-containing medium and grown for 2 days at 30°C before serial dilutions were plated onto canavanine-selection or viability plates. Colonies were counted after 3 days growth. For I-SceI-break induction, individual colonies were grown overnight in glucose medium before dilution 1:10 into raffinose-containing medium. After 4 hr growth, galactose was added to 2% and cells were cultured for a further 2 days before serial dilution and plating as above. APOBEC3G* was used in the I-SceI experiments as it gave a good mutation load but a lower proportion of kataegic mutations than AID* . InductiR colonies selected as above were subcloned by streaking out on selective plates, grown for 3 days in canavanine selection media (10 ml) and DNA prepared using Gentra Puregene Yeast/Bact. Kit  following manufacturers instructions.For genome sequence determination, individual CanShort insert 500-bp library construction, flowcell preparation and cluster generation was in accordance with the Illumina no-PCR library protocol . 100-bp A bespoke substitution-calling algorithm, CaVEMan (manuscript in preparation) was used for calling somatic substitutions where these were identified as alleles present in an AID/APOBEC-transformant genome but absent in the parental BY4741 genome. All high-confidence mutations included in this analysis were present in more than 0.5 variant allele fractions but were more frequently present in all reads reporting that genomic position. Post-processing filters were developed to improve the specificity of substitution calling. These filters removed false positive variants that were generated by genomic features resulting in mapping errors or systematic sequencing artefacts. All substitutions were visually assessed using a genome browser in order to ensure a high specificity of mutation-calling.K-cluster analysis  was usedhttp://tools.genouest.org/tools/meme/cgi-bin/tomtom.cgi) and are displayed as p-values.Sequence contexts were compared in pairwise fashion with the Tomtom motif comparison tool using Sandelin-Wasserman similarity -IRES-GFP (pMX-IG) cassette into the BglII- and 3′LTR XbaI site of pMSCVpuro. The tetracycline transactivator  was cloned into a modified pMSCVpuro (Clontech) which contained an IRES-mCherry cassette at the BglII–ClaI site, to generate pTET-ON-ImC. A derivative of the KBM7 human myelocytic leukemia line that stably expressed TET-ON protein was established by retroviral infection with virus particles produced from 293 cells that had been co-transformed with pTET-ON-ImC and packaging vectors using GeneJuice  according to manufacturers instructions. This KBM7[pTET-ON-ImC] cell-line was then superinfected with pMSCV/APOBEC retrovirus to yield derivatives expressing the AID/APOBEC proteins under doxycyclin-inducible control. Expression of the FLAG-tagged AID/APOBEC proteins in the KBM7 transfectants was monitored by Western blot analysis of whole cell lysates after 24 hr of doxycyclin induction using HRP-conjugated anti-FLAG antibody M2 , probing with anti-lamin antibody  as a loading control.Stable derivatives of KBM7 cells harbouring regulatable APOBEC proteins were induced for 72 hr with doxycyclin (inducer) and viability measured by flow cytometry by DAPI exclusion. γH2AX and 53BP1 induction and localisation was analysed by flow cytometry and confocal immunofluorescence after 24hr induction with doxycyclin; caspase inhibitor  was included in the cultures for γH2AX expression analysis to maintain cell viability. For γH2AX staining, ethanol-fixed cells were stained sequentially for 1 hr with anti-γH2AX  and Alexa568-conjugated anti-mouse IgG  prior to resuspension in PBS containing 5 μg/ml DAPI and flow cytometry. For 53BP1 staining, cells were allowed to adhere to poly-L-lysine-coated cover slips and stained using anti-53BP1  and Alexa 568-conjugated anti-rabbit IgG  prior to mounting with DAPI. 20-30 fields per sample were imaged with a Bio-Rad Radiance 2100 confocal microscope using a 63x oil immersion objective. Images were processed using ImageJ (default settings), and cells were scored as exhibiting either diffuse or punctate staining with punctate cells further scored for the number of foci.Breast cancer cell lines were kindly provided by Dr Kerstin Meyer  and RNA extracted using RNeasy Plus Mini Kit (Qiagen). cDNA was prepared using GoScript Reverse Transcription System (Promega) prior to APOBEC expression quantification by qPCR using QuantiFast SYBR Green PCR Kit using an ABI ViiA-7 system . The primers  are given in  review process). Similarly, the author response typically shows only responses to the major concerns raised by the reviewers.eLife posts the editorial decision letter and author response on a selection of the published articles . An edited version of the letter sent to the authors after peer review is shown, indicating the substantive concerns or comments; minor concerns are not usually shown. Reviewers have the opportunity to discuss the decision before the letter is sent . Although the conclusions of these two studies overlap, it is clear that the manuscript by Taylor et al offers important additional mechanistic insight into the kataegic process through the key UNG deletion experiment. The findings from this experiment expose the fundamental role of base excision within kataegis and demonstrate the utility of the yeast system the authors have created.One arising issue is the recently published study by Burns et al in As you will see below, the revisions requested, while important for a final submission and publication decision, are relatively minor. Given the recent emergence of a competing manuscript of which you are aware, we ask that you make these revisions without delay.1. In the text the authors refer to the clustered mutations as showing a “strong tendency towards strand polarity .” We are assuming that this reference is to the observation that one tends to see either all red ticks (clustered Gs) or black ticks (clustered Cs) together in a single cluster. However, it would be good to clarify this in either the text or figure legends.2. Was the stability of the AID and APOBEC proteins in yeast measured? Is the amount of protein produced equivalent?3. For the canavanine resistance assays, cells were grown in glucose medium, diluted, and then grown in galactose. For the I-SceI break assays, cells are transferred from glucose medium to raffinose medium for 4 hr, and then to galactose medium. Why the difference? Also, wouldn't the induction of both the human deaminases and I-SceI be better if, instead of using glucose medium at all, cells were grown in the non-inducing/non-repressing mediums of either raffinose or 3% glycerol 3% lactate, followed by the addition of galactose?CAN1 mutations in a rev1-null background . In that work, a temperature sensitive mutant of polymerase delta (pol3-t) was shown to lead to an increase in canavanine resistance that was almost completely suppressed in the absence of REV1, without significant changes to the number of transitions or transversions. Also the absence of REV1 suppressed the increased frequencies of chromosome loss, interhomolog exchange, and direct repeat recombination measured in pol3-t.4. The absence of REV1 could have pleiotropic effects not related to its deoxycytidyl transferase activity. For example, you may want to note previous work sequencing not APOBEC3G. This would add greatly to the paper because it would indicate how much of the mutation localization is due to APOBEC3G (after I-SceI).5. In Figure 2D, the authors might also want to show the condition; here I-SceI is present but 6. The authors infer long zones of end resection, but this is only an indirect inference based on AID and Apobec action. The single-strandedness could arise from increased breathing in zones of “opened up” chromatin due to the repair at the DSB. The authors should acknowledge this additional interpretation. 1) In the text the authors refer to the clustered mutations as showing a “strong tendency towards strand polarity .” We are assuming that this reference is to the observation that one tends to see either all red ticks (clustered Gs) or black ticks (clustered Cs) together in a single cluster. However, it would be good to clarify this in either the text or figure legends.We agree that this is an essential point that should be heavily emphasised. We have amended the paragraph to read: “Like the cancer kataegis, the clustered mutations in the various yeast transformants showed a strong tendency towards strand polarity; mutations within a cluster occur predominantly at either a C residue or a G residue with over 88% of mutations being strand coordinated .”2) Was the stability of the AID and APOBEC proteins in yeast measured? Is the amount of protein produced equivalent?We have measured proteins levels and there is little correlation between protein levels and the extent of deamination. We have confirmed that all AID/APPOBEC proteins are expressed in yeast. We find that AID and AID* are expressed at substantially lower levels in the yeast transformants than the APOBECs and we have included an extra panel in Figure 1–figure supplement 1 to show this.We suspect that the number of mutations is dependent more on the specific activity of each protein rather than on its abundance, which is in keeping with observations that we have previously made using AID upmutants in mammalian cell transfectants .3) For the canavanine resistance assays, cells were grown in glucose medium, diluted, and then grown in galactose. For the I-SceI break assays, cells are transferred from glucose medium to raffinose medium for 4 hr, and then to galactose medium. Why the difference? Also, wouldn't the induction of both the human deaminases and I-SceI be better if, instead of using glucose medium at all, cells were grown in the non-inducing/non-repressing mediums of either raffinose or 3% glycerol 3% lactate, followed by the addition of galactose?We were concerned that low levels of expression of AID/APOBEC proteins might result in selection for inactivating mutations on the AID/APOBEC plasmids. We therefore wanted to ensure limited and controlled exposure of the genomes to the exogenous mutators; hence the choice of glucose repressive media for culture during periods of clonal expansion. The difference in induction between experiments is historical. We have since tested both induction methods and found them to produce similar results, and we have added a comment in the Materials and methods section to reflect this: “Induction of protein expression both with and without the raffinose step gave similar mutation rates.”However, we appreciate the reviewers' comments and we can certainly use their suggestions for growth conditions in future experiments.4) The absence of REV1 could have pleiotrophic effects not related to its deoxycytidyl transferase activity. For example, you may want to note previous work sequencing CAN1 mutations in a rev1-null background  In that work, a temperature sensitive mutant of polymerase delta (pol3-t) was shown to lead to an increase in canavanine resistance that was almost completely suppressed in the absence of REV1, without significant changes to the number of transitions or transversions. Also the absence of REV1 suppressed the increased frequencies of chromosome loss, interhomolog exchange, and direct repeat recombination measured in pol3-t.The reason that we suspect that the effect of REV1 deficiency reflects its deoxycytidyl transferase activity is that the transversion mutations in REV1 sufficient cells are heavily biased towards C:G substitutions. While we fully accept that we cannot exclude indirect effects of REV1 deficiency, addressing the details and mechanistic function for REV1 in kataegis is beyond the scope of this paper, and will require extensive additional work. We have modified the text to reflect the possibility of a non-catalytic role for REV1 adding in the Results section: “This presumably reflects diminished repair of the AID/APOBEC-generated uracils. There was an overall decrease in average total mutation load in AID* transformants of REV1 deficient yeast, that might reflect the possible non-catalytic roles of REV1 during DNA damage repair .”5) In Figure 2D, the authors might also want to show the condition; here I-SceI is present but not APOBEC3G. This would add greatly to the paper because it would indicate how much of the mutation localization is due to APOBEC3G (after I-SceI).We agree that such a control would help emphasise the point; unfortunately we have not sequenced these genomes. The signatures of the detected mutations do, however, make this point as the vast majority occur at the APOBEC3G consensus, indicating they are caused by the activity of APOBEC3G and not other repair processes as we highlight in the figure legend. To further emphasise this, we have added the following sentence to the Discussion: “In our experiments, the signatures of the mutations associated with the I-SceI break  implicate APOBEC3 activity rather than error-prone polymerases as the source of mutations during the double-strand break repair.”6) The authors infer long zones of end resection, but this is only an indirect inference based on AID and Apobec action. The single-strandedness could arise from increased breathing in zones of “opened up” chromatin due to the repair at the DSB. The authors should acknowledge this additional interpretation.We do not favour an explanation based on breathing since breathing suggests a transient melting of the DNA, which would allow the unmutated DNA strand to act as a template upon strand reannealing, thereby resulting in non-mutagenic repair. Furthermore, the lengths of the observed kataegic tracts are not really compatible with measurements of DNA dynamics that suggest that fluctuations in base pairing are a relatively local phenomenon . However, we fully admit that we cannot definitively exclude it; we acknowledge in the Discussion a variety of mechanisms that promote single stranded DNA could generate kataegis. In the interests of brevity, we included in the Discussion a selective but not exhaustive list of possible alternative mechanisms.


Disease genes that interact cooperatively play crucial roles in the process of complex diseases, yet how to analyze and represent their associations is still an open problem. Traditional methods have failed to represent direct biological evidences that disease genes associate with each other in the pathogenesis of complex diseases. Molecular networks, assumed as ‘a form of biological systems’, consist of a set of interacting biological modules  and this notion could provide a promising insight into deciphering this topic.In this paper, we hypothesized that disease genes might associate by virtue of the associations between biological modules in molecular networks. Then we introduced a novel disease gene interaction pathway representation and analysis paradigm, and managed to identify the disease gene interaction pathway for 61 known disease genes of coronary artery disease (CAD), which contained 46 disease-risk modules and 182 interaction relationships. As demonstrated, disease genes associate through prescribed communication protocols of common biological functions and pathways.Our analysis was proved to be coincident with our primary hypothesis that disease genes of complex diseases interact with their neighbors in a cooperative manner, associate with each other through shared biological functions and pathways of disease-risk modules, and finally cause dysfunctions of a series of biological processes in molecular networks. We hope our paradigm could be a promising method to identify disease gene interaction pathways for other types of complex diseases, affording additional clues in the pathogenesis of complex diseases. Complex diseases are caused by disease risk genes in the form of biological modules or pathways in molecular networks e.g. the Alzheimer’s disease pathway, have been determined from experiments in vivo methods are too time-consuming and laborious for discovering a large number of pathways. With the development of genomics, functional proteomics and metabolomics, many computational algorithms have been generated to identify biological modules or pathways in the context of biological molecular networks. For example, literature searches are used to discover signal transduction pathways Many biological pathways have been derived experimentally Previous studies demonstrated that neighborhood similarity is an effective measurement for evaluating the likelihood of two proteins in a network sharing a number of interacting neighbors PPIN is an intuitive form of a set of interacting biological modules. The underlying rationale is that disease genes might associate by virtue of associations between biological modules in molecular networks. In this study, we introduced a novel disease gene interaction pathway representation and analysis paradigm to demonstrate disease gene association mechanisms. First, we clustered proteins using hierarchical clustering method, constructed a hierarchical tree of biological modules according to their neighborhood similarities in a PPIN and obtained different lossless network representations. Then, we searched for disease-risk modules that contained disease proteins and other proteins with similar functions, and linked these modules to form disease gene interaction pathways. This connected disease genes that did not interact directly in the network. We applied this algorithm to extract disease gene interaction pathways of coronary artery disease (CAD), hypertension (HT), and type 2 diabetes (T2D), and evaluated our results by functional annotations, pathway-wide analyses and randomization tests.http://www.hprd.org/) Human protein-protein interaction data were derived from Human Protein Reference Database  http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=OMIM) http://geneticassociationdb.nih.gov/) Disease genes for CAD, HT and T2D were the union of disease genes in Disease Ontology ; // raise to a higher hierarchycompute neighborhood similarity values between every module pairs in choose module pairs with the maximum value of neighborhood similarity;merge modules into discard modules from  and add  to calculate number of all the modules in current hierarchy;discard interactions between modules in search for new module interactions according to module interactions in output module interactions;Algorithm 1 and the resulting hierarchical tree and interacting modules in each hierarchy are in As an example, a sample PPIN composed of 10 proteins  was clustered hierarchically with Algorithm 2.We first marked disease genes and disease-risk modules that contained disease proteins in the hierarchical tree. Then, the disease gene interaction pathway was searched according to interaction relationships between disease-risk modules in each hierarchy of the hierarchical tree using a bottom-up approach. If a pair of proteins in two modules interacted with each other, the two modules interacted. The process is illustrated in Algorithm 2, In Algorithm 2 is shown here:input: all disease proteins in the protein set output: disease gene interaction pathway searchPath  comparing with random networks; and ii) validating of disease-risk modules and their interaction relationships.In this paper, based on the neighborhood similarities, we represented a primary PPIN as a hierarchical tree of biological modules generated in a bottom-up way. The disease gene interaction pathway for CAD was derived according to our proposed algorithms. This disease gene interaction pathway contained 46 disease-risk modules and 182 interaction relationships between these modules. The results of disease gene interaction pathways for HT and T2D are shown in We constructed a hierarchical tree using a bottom-up approach based on the neighborhood similarity of every two proteins or modules in the largest connected component of the PPIN . Proteins with large neighborhood similarities were organized into modules in lower hierarchies of the hierarchical tree, which were grouped into modules in higher hierarchies until all proteins are clustered into one module.Algorithm 1. Each hierarchy was a different presentation of the largest connected component of the PPIN, and clustered the proteins into modules of various sizes. Every module comprised two or more submodules or proteins.We obtained a hierarchical tree with 86 hierarchies using http://david.abcc.ncifcrf.gov/) To evaluate the function consistency of each module, we used the online toolkit, Functional Annotation Tool in Database for Annotation, Visualization and Integrated Discovery (DAVID) Bioinformatics Resources 6.7 . Then, we used the proposed pathway searching algorithm (see Searching disease gene interaction pathway in Methods section) to search for a CAD disease gene interaction pathway. In the pathway, CAD disease genes associated by the mechanism that disease-risk modules interacted with each other. This led to multiple dysfunctions of biological processes in CAD pathogenesis. Finally, we derived a CAD disease gene interaction pathway containing 46 disease-risk modules and 182 interaction relationships. This data arrangement is in http://www.geneontology.org/) functions VWF (geneID: 7450) and F12 (geneID: 2161), and COL3A1 (geneID: 1281) and SERPINE1 (geneID: 5054) are scattered in human PPIN. Notably, we found genes VWF and F12 associated via the shared function “blood coagulation” for interacting disease-risk modules “3895” and “4944”, while genes COL3A1 and SERPINE1 associated through the “fibrinolysis” process shared by interacting disease-risk modules “4287” and “5219” in the resulting pathway we derived  pathways To verify the associations between the resulting disease gene interaction pathway and CAD, we tested for cross-validations of CAD in disease-risk modules under the framework of Kyoto Encyclopedia of Genes and Genomes , apolipoprotein B, altered cholesterol levels, particularly high levels of low-density lipoproteins together with low levels of high-density lipoproteins Of all enriched pathways, 61 were validated to be CAD-related by a literature retrieval . For exaIL1R2+ESR2+coronary artery disease). Verified were 107 interactions (58.8%) related to the pathogenesis of CAD (IL1R2 (GeneID: 7850) and ESR2 (GeneID: 2100) in interacting modules 6116 and 5033 and IL1R2 and PLA2G7 (GeneID: 7941) in interacting modules 6116 and 638 were related to CAD by MVK (GeneID: 4598), LDLR (GeneID: 300438) and APOA1 (GeneID: 335) in disease-risk modules 638, 4945, and 6433 that interact with each other LRP1 (GeneID: 4035) and MTHFR (GeneID: 4524) in interacting disease-risk modules 4945 and 638, and LRP1 and SELP (Gene ID: 6403) in interacting modules 4945 and 4393 LDLR, SELP, and IL6 (GeneID: 3569) in disease-risk modules 4945, 4393, and 5982, which interact with each other TMEM57 (GeneID: 55219) and CTCF (GeneID: 10664) in interacting disease-risk modules 638 and 6433 is also recognized LDLR and APOA1 in interacting disease-risk modules 4945 and 6433 The CAD disease gene interaction pathway covered 182 interaction relationships between 46 disease-risk modules. To further evaluate the reliability of interaction relationships between disease-risk modules, we used the NCBI PubMed module to retrieve correlations between gene pairs and CAD with the term “GENE symbol 1+GENE symbol 2+coronary artery disease” , our method also allows inferring biological pathways in molecular networks when a set of source and/or target proteins are given. As for FASPAD and Pandora, our method is similar to these approaches at the aspect of taking into account of ‘similarity’ features of neighboring proteins in the background of biological molecular networks. It must be noted that our method has the following advantages. First, using the disease gene interaction pathway reveals potential associations between disease genes or proteins that do not connect directly. Second, representing biological networks as combinations of multiple modules is a lossless, compact, and less redundant representation of the PPIN that preserves the connectivity information between modules. Finally, our novel disease gene interaction pathway representation and analysis paradigm could elucidate that disease genes can associate by the mechanism of disease-risk modules with mutual functions interacting with each other. This leads to multiple dysfunctions of biological processes in the pathogenesis of complex diseases.Our method also has some limitations. For example, constructing a hierarchical tree and searching for underlying associations between disease genes based on the high-throughput biological network is time-consuming. Another limiting factor is that upstream or downstream relationships could not be identified in disease gene interaction pathways using our analysis.As demonstrated, the disease genes of CAD, HT, and T2D associated by virtue of associations between biological modules in the PPIN. We hypothesize that if the interaction relationships between disease-risk modules were blocked, communications would break down, preventing disease-risk modules from associating with each other. This might provide additional insights into the pathogenesis of CAD, HT, and T2D. Therefore, the interactions between disease-risk modules might be informational for CAD, HT, and T2D treatment and even in fields such as drug target analysis.We used the examples of CAD, HT, and T2D to determine the feasibility of this method. Once disease genes are determined in the PPIN, our proposed method can be used to identify disease gene interaction pathways for other types of complex diseases, yielding additional clues in the pathogenesis of complex diseases.Figure S1The resulting HT disease gene interaction pathway derived from the PPIN by our method. 87 nodes in pink are disease-risk modules that contain HT disease proteins (purple dots) and other proteins with similar functions, and the labels beside the nodes are their module IDs. The sizes of the nodes are directly proportional to the log number of proteins  they contain. 306 edges are the interaction relationships between disease-risk modules they connect.(TIF)Click here for additional data file.Figure S2The resulting T2D disease gene interaction pathway derived from the PPIN by our method. 123 nodes in pink are disease-risk modules that contain T2D disease proteins (orange dots) and other proteins with similar functions, and the labels beside the nodes are their module IDs. The sizes of the nodes are directly proportional to the log number of proteins  they contain. 579 edges are the interaction relationships between disease-risk modules they connect.(TIF)Click here for additional data file.Figure S3The distribution of four network metrics of disease gene interaction pathways from random networks. Boxes are values for disease gene interaction pathways from random networks, and blue diamonds are values for those from HPRD PPIN.(TIF)Click here for additional data file.Table S1GO functions enriched for disease-risk modules for CAD.(DOC)Click here for additional data file.Table S2Common GO functions shared by interacting terms in the CAD disease gene interaction pathway.(DOC)Click here for additional data file.Table S3PubMed ID in which KEGG pathways enriched have been proved to be correlated with CAD.(DOC)Click here for additional data file.Table S4PubMed ID in which gene pairs between interacting disease-risk terms have been proved to be correlated with CAD.(DOC)Click here for additional data file.Table S5PubMed ID in which KEGG pathways enriched have been proved to be correlated with HT.(DOC)Click here for additional data file.Table S6PubMed ID in which gene pairs between interacting disease-risk terms have been proved to be correlated with HT.(DOC)Click here for additional data file.Table S7PubMed ID in which KEGG pathways enriched have been proved to be correlated with T2D.(DOC)Click here for additional data file.Table S8PubMed ID in which gene pairs between interacting disease-risk terms have been proved to be correlated with T2D.(DOC)Click here for additional data file.


Reactive oxygen species (ROS) are involved in amplifying the radiation-induced damage to macromolecules as well as in downstream early responses leading to DNA repair or cell death and in delayed responses leading to tissue damage and/or tumorigenesis. We found in immortalized normal human bronchial epithelial cells (HBEC-3KT) following exposure to 1 Gy low (X-rays) or high (Fe ions) LET radiation that ROS levels persist elevated for up to eight population doublings (2 weeks) in the progeny of cells that repaired the radiation-induced damage and survived. To evaluate the function of persistently elevated ROS levels, we interrogated cells over the same period for genomic instability, proliferation and senescence biomarkers and evaluated whether ROS are functionally related to any of these phenotypes. We found that increased ROS production overlapped temporally with the persistence of reporters for genomic instability, increased micronucleus frequency and the presence of γH2AX-53BP1 positive ionizing radiation-induced foci. Although low LET radiation at high doses and high LET radiation induced a senescence-like phenotype dependent on ATM and p38 MAPK activity, this pathway was not a causative factor in ROS generation and did not affect cell proliferation rates at day 7 post-irradiation. On the contrary, when this pathway was inhibited, ROS levels increased further and micronucleus formation frequency was reduced. Because these results suggest a positive effect for increased ROS levels in the resolution of persistent micronucleus formation, their role was further confirmed by exposure to exogenous hydrogen peroxide, which resulted in a reduced micronucleus frequency. These results implicate ROS as an effector in the resolution of genomic instability and suggest that the senescence phenotype induced by high LET radiation or high low LET radiation dose promotes genomic instability by interfering with the cellular mechanism regulating ROS levels or the DNA repair machinery.


Drosophila SLC6 gene, Neurotransmitter transporter-like (Ntl), is expressed only in the male germline. Mobilization of a transposon inserted near the 3′ end of the Ntl coding region yields male-sterile mutants defining a single complementation group. Germline transformation with Ntl cDNAs under control of male germline-specific control elements restores Ntl/Ntl homozygotes to normal fertility, indicating that Ntl is required only in the germ cells. In mutant males, sperm morphogenesis appears normal, with elongated, individualized and coiled spermiogenic cysts accumulating at the base of the testes. However, no sperm are transferred to the seminal vesicle. The level of polyglycylation of Ntl mutant sperm tubulin appears to be significantly lower than that of wild type controls. Glycine transporters are the most closely related SLC6 transporters to Ntl, suggesting that Ntl functions as a glycine transporter in developing sperm, where augmentation of the cytosolic pool of glycine may be required for the polyglycylation of the massive amounts of tubulin in the fly's giant sperm. The male-sterile phenotype of Ntl mutants may provide a powerful genetic system for studying the function of an SLC6 transporter family in a model organism.The SLC6 class of membrane transporters, known primarily as neurotransmitter transporters, is increasingly appreciated for its roles in nutritional uptake of amino acids and other developmentally specific functions. A  Drosophila male-sterile mutations are isolated indicates that a large number of genes must contribute information required for spermatogenesis DrosophilaThe ease with which Drosophila, numerous mutations identified in genetic screens for behavioral abnormalities, or through targeting of fly homologues of human genes implicated in neurological disease states have yielded male-sterile mutations. The former include pushover (poe)tilBuncyurigishDmfr1, the Drosophila homologue of the Fragile X protein, dfxr parkinpinkGuo et al Neurotransmitter Sodium Symporter (NSS) family includes serotonin, dopamine, and GABA transporters, as well as amino acid and osmolyte transporters in both prokaryotes and eukaryotes Neurotransmitter Symporter Family), comprise the largest subfamily of neurotransmitter transporters. NSS family members are an ancient group of highly conserved integral membrane proteins with characteristic twelve transmembrane pass domains. They are crucial for transporting neurotransmitters, amino acids and osmolytes across the plasma membrane. They are generally referred to as the neurotransmitter transporter family because the classical members were transporters for GABA, norephinephrine, serotonin, and dopamine. However, additional family members are now known to mediate the cellular uptake of amino acids and their derivatives in a number of tissues The highly-conserved The NSS/SLC6 family is notable for the number of psychological/neurological disorders that have been linked to changes in their activities, and for the remarkable number of pharmacological agents that target them, including psychostimulants, antidepressants, and neurotoxins Drosophila melanogaster. Thus far five out of a total twenty two predicted Drosophila members of this family have been characterized, including the serotonin transporter homolog (SerT) DAT) inebriated (ine) gene Drosophila family members characterized are bloated tubules (blot) DrosophilaDespite their significance in mammalian physiology, relatively little is known about these transporters in the model organism Drosophila gene encoding a testis-specific member of the NSS family, which they named Neurotransmitter transporter-like (Ntl). Using an Ntl-LacZ fusion construct, Bigler showed that Ntl was expressed in developing sperm, and that the cellular distribution of Ntl protein exhibited dynamic reorganization during spermiogenesis. Here we report the isolation of male-sterile mutants in the Drosophila gene Neurotransmitter transporter-like (Ntl), a member of the NSS/SLC6 family, and confirm that the gene is expressed only in male germline cells. Sperm produced by individuals homozygous for a null mutation in Ntl are morphologically mature, but are immotile and fail to be transferred to the seminal vesicle. The massive posttranslational glycylation of sperm tubulin observed late in spermiogenesis is consistently reduced in Ntl mutants. This is in accord with the suggestion that glycylation is important for stability and/or motility of microtubule-based machinery Ntl to known glycine transporters suggests that it functions to augment the cytosolic glycine pool in male germ cells.Previous studies by R. Dörig and D. Bigler Ntl mutants are perfectly viable but completely male-sterile, they present an outstanding opportunity for the study of an NSS transporter function in a well-defined but complex cellular morphogenesis pathway. The very high conservation of Ntl homologues in mosquito vectors and the highly developed pharmacology of the NSS/SLC6 family also suggest a potential route to vector population control.Because +w or +y males were mated with yw females, with the recovery of +y or +wdaughters in the F1 generation confirming fertility. Genetic constructions were carried out using standard Drosophila genetics as in Greenspan Flies were raised on standard cornmeal molasses agar at 25°C Drosophila males carrying dj-GFP were withheld from females for eight days before dissecting their testes to check for dj-GFP expression. Lines expressing β tubulin-GFP were a kind gift from S. Goto via Karen Hales.For fluorescence microscopy of sperm individualization, wild type and mutant freshly eclosed Drosophila chromosome. The P{EPgy2}Ey05549 transposon insertion was generated by the Drosophila Genome P element disruption project +w and/or +y markers carried by the P element were recovered using standard Drosophila genetics, then screened for new male-sterile mutations expected from the deletions produced by imprecise excision of the P element The Ntl transcript/CDR is in the 28C region on the 2L arm of the Total RNA was isolated using TRI reagent (Sigma) according to the manufacturer's recommendations. RNA was extracted from males, females, ovaries, testes, heads and carcasses and concentration was determined by measuring its absorbance at 260 nm. 1–2 µg of total RNA was used after normalizing for all samples.Ntl gene specific primers were designed to span an intron/exon boundary to avoid genomic DNA amplification in case of contamination.Two-step RT-PCR was performed using SuperScript ™III Reverse Transcriptase (Invitrogen) according to the manufacturer's recommendations. During first strand synthesis incubation with gene specific primers were carried out at 55°C for 60 min. The Thermocycler (MJ Research Gradient cycler) was programmed as follows: 95°C for 5 min followed by the amplification steps of 94°C for 1 min, 57°C for 1 min, 72°C for 1 min. 30 cycles of PCR was run for all samples followed by 10 min at 72°C and held at 4°C overnight. Ntl primers amplified a 629 bp fragment, while rp49 control primers amplified a 405 bp fragment. Primers for this and all subsequent PCR-based molecular biology are specified in http://www.fruitfly.org/about/methods/inverse.pcr.html). 6 pairs of genome specific primers were used to span the entire coding sequence of Ntl. The thermocycler (MJ Research gradient cycler) was programmed as follows: 95°C for 5 min followed by the 30 cycles of: 94°C for 1 min, 57°C for 1 min, 72°C for 1 min. After a final 10′ at 72°C, samples were held at 4°C until gel analysis.Genomic DNA was isolated from males according to the Berkeley Drosophila Genome Project's protocol . The 6003 bp fragment was recovered by digesting with KpnI, gel purified and ligated into pCaSpeR4 vector (DGRC).To generate pCaSpeR4-Ntl; Ntl reading frame. The missing “G” was inserted at position 961 of AT20383 by site-directed mutagenesis  and the change confirmed by sequencing. The sequences of other cDNAs since deposited in the databases confirm that the missing base was a cloning artifact. Long Range PCR was done on the repaired clone (AT20383) using PfuTurbo DNA Polymerase (Stratagene) to attach NotI sites at either end for ligating into pTMR vector EcoRI digestion.To generate pTMR-Ntl, full-length cDNA clone AT20383 was obtained from the Drosophila Genome Research Center. Comparison of the AT20383 sequence with the predicted sequence in the NCBI database suggested a single base pair deletion in AT20383 leading to a frameshift mutation and premature termination of the http://stratagene.com/sdmdesigner/).Primers were designed using the Vector NTI software. Primers for SDM were designed using the QuikChange Primer Design Program , transferred to a drop of fixative  on poly-lysine coated slides for 10 minutes, then rinsed three times with PBT (0.1% Triton X in PBS), blocked in 1.5% BSA in PBT for 20 min and stained with 1 µg/ml TRITC-phalloidin  in PBT for 1 hour at room temperature. Slides were then rinsed three times in PBS and mounted in 10%(w/v) Mowiol  4–88, 25% glycerol, 100 mM Tris-HCl, pH 8.5. Slides were stored overnight at 4°C before imaging. Fluorescence images were captured by confocal microscopy .Don-juan-GFP (dj-GFP) was expressed in the testes by crossing a dj-GFP/TM3, Sb line into Ntl/SM6a mutant background to generate a stock. Testes were dissected from 0–1 day old young male Drosophila (unless mentioned otherwise) in 1X PBS buffer and gently squashed with a cover slip before taking fluorescence and phase images with Leica DM 4500B.Testes were dissected from 1–3 day-old males, fixed and embedded in Epon/Araldite. Thin sections were stained and photographed by TEM as previously described yw) flies. Therefore, whole abdomens were used to prepare protein samples. Six fly abdomens worth of protein (∼4–5 µg) were loaded in each lane.Samples were prepared from male fly abdomens for each genotype. The males were withheld from females for 4–6 days. Dissection of the testes sometimes leads to loss of seminal vesicle, which contain significant amounts of glycylated tubulin in wildtype  vortexed and boiled for 5 minutes. Samples were then spun at 15,800 g for 5 minutes, and supernatants were separated in a 15% SDS-Polyacrylamide gel and transferred to a PVDF membrane  using a Trans-Blot Semi-Dry transfer apparatus .Membranes were incubated with Poly-G, (gift of M.Gorovsky) and anti-α-tubulin antibody (1∶5000), .Protein bands were visualized with HRP-labelled anti rabbit or anti-mouse  followed by detection with ECL immunoblot detection kit . Loading control was α-tubulin from duplicate lanes.http://rsb.info.nih.gov/ij/, 1997–2009).All statistical analyses were done using Microsoft Excel. The average values of relative intensity (poly-G intensity/anti-tubulin) were plotted for each genotype. Intensities were calculated using Image J software .Clustal W alignment of the predicted Ntl mutants were generated by mobilizing a P element (P {EPgy2} CG7075 EY05549) at the 3′ end of the Ntl gene by crossing it into genetic background in which transposase is constitutively expressed in all tissues yellow+ (+y) and/or + (w+)white markers associated with the P element were recovered and established in balanced genetic stocks. P element excision is imprecise and deletions of varying size spanning the insertion site or extending from the insertion site in either direction are often recovered at significant frequencies Ntl locus showing the starting insertion, the mating scheme used to mobilize the transposon and identify new male-sterile mutations, and the location of primer pairs used to assay for deletions in the resulting male-sterile stocks is shown in Ntl gene and extending further into one or more essential genes.Of 150 chromosomes that were observed to have lost the P element, 8 were found to carry new male sterile mutations defining a single complementation group. Several homozygous lethal mutations were also recovered. These fail to complement the male-sterile alleles and are likely to be larger deletions including a functionally essential portion of the Ntl129A is a null mutant, as none of the primer pairs tested using 129A/Ntl129ANtl DNA as template yielded a PCR fragment corresponding to that obtained from the wild-type control  from the Drosophila Genomics Research Center, modified it as described in Drosophila transformation vector pTMR rd chromosome pTMR insertion lines rescued the Ntl mutant male sterile phenotype. Results from one of the rescued lines are presented in Ntl transcript to 519 bp beyond its 3′end also rescued the Ntl mutant phenotype . Rescue by the genomic construct indicates that all cis-acting control sequences required for functional Ntl expression lie within 2.7 kb upstream  of the gene. Results from one of the rescued lines are also presented in 129A/CyNtl stocks carrying the P insertions are stable, with fertility of homozygous mutant males segregating consistently with the +w marker of the P element. The male-sterile complementation group recovered after mobilization of the P element therefore corresponds to the Ntl gene.To confirm that the male sterile phenotype in our mutants is caused solely due to disruption of Ntl expression is male-specific and limited to the testes . In a genetic background expressing ic cysts  but we hDrosophila testes carrying dj-GFP were counterstained with TRITC conjugated phalloidin, we observed normal formation and movement of the actin cones of the individualization complex . In summary, morphogenesis of ntl mutant sperm appears quite normal at both optical and ultrastructural resolution, but the apparently immobile end products of spermiogenesis are not transferred to the seminal vesicle.Transmission electron micrographs of cross-sections through pre and post-individualized cysts (through the base of the testes) do not show any obvious defect in the individualization process nor the axoneme structure . ExaminaDrosophila sperm axonemes and many other eukaryotic cilia, has been shown to be modified via polyglycylation, the addition of glycine chains through the γ-carboxyl group of glutamate residues near the C-terminus of tubulin Drosophila glycylase, dmTTLL3B, results in male sterility Ntl is most similar to known human glycine transporter GLYT2 (P = 9 e−134 in BLASTP against nonredundant database with default parameters), we assayed Ntl mutant males for tubulin glycylation using anti Poly-G antiserum Ntl mutant was never observed to be higher than that of the wild-type. The semi-quantitative nature of this assay and variation between individuals sampled for the experiments could account for this variation. More quantitative biochemical approaches should resolve this issue.The tubulin of Ntl is the first member of the SLC6/NSS family shown to provide a function essential for male fertility in any animal. Ntl orthologues in the Dipteran disease vectors A. gambiae and A. aegypti are highly conserved Ntl function may be present among compounds already screened for their effects on other NSS family members.To our knowledge, Ntl with a human gene product is with the human glycine transporter type 2 (GLYT2), also known as SLC6A5. This is a presynaptic glycine transporter, mutations in which are associated with autosomal recessive hyperekplexia and life threatening episodes of neonatal apnea. Individuals with mutations in SLC6A5 present with hypertonia, an exaggerated startle response to tactile or acoustic stimuli. SLC6A5 mutations result in defective subcellular localization of glycine transporter-2, decreased glycine uptake, or both, with selected mutations affecting predicted glycine and Na+ binding sites The most significant BLAST score for Ntl gene product is unlikely to function as a neurotransmitter transporter. Presence of an aspartate or glycine in TM1 of a SLC6 transporter is thought to be partially responsible to distinguish between monoamine neurotransmitter transporters or amino acid transporters respectively Ntl amino acid sequence which further supports the claim for Ntl being an amino acid transporter. Recently, evidence has been accumulating that most of the orphan transporters of this class function as transporters of amino acids or their derivatives Since neither the germ cells nor the somatic cyst cells encasing them are known to be enervated, the Ntl sperm suggests that the Ntl gene product is a spermatid-specific glycine transporter. This would rationalize the similarity of Ntl to known glycine transporters, the requirement of polyglycylation for stability and motility of microtubule-based structures in numerous species Drosophila. However, complete loss of glycylation results in the breakdown of the individualization complex as it translocates along the cyst Ntl mutants is sufficient for sperm individualization, but not for later transitions required for transfer to the seminal vesicle and/or sperm motility, consistent with previous observations that sperm individualization and polyglycylation are tightly coordinated Drosophila sperm axonemes Ntl to accommodate this demand.The apparent reduction in glycylation of Ntl sperm suggests a potentially parallel role for Ntl in the activation of Drosophila sperm motility. Further understanding of the mechanisms controlling the activation of sperm motility, transfer to the seminal vesicle, and how these two phenomena may be linked, might therefore be informed by future studies of Ntl.Enomoto


Neuropsychiatric disorders (including dementia) have high personal, family, and social costs. Although many neuropsychiatric disorders share common patterns of symptoms and treatments, there are no validated biomarkers that define the underlying molecular mechanisms in the central nervous system (CNS). We hypothesize that there are early and common molecular changes in the CNS that will serve as sensitive indicators of CNS molecular stress and that will be predictive of neuropathological changes resulted in increasing the risk for neuropsychiatric diseases. Using the rodent model, we showed that systemic exposure to three diverse CNS stressors with different mechanisms of action  induced the expression of troponin T1 (Tnnt 1) within hours in adult mouse brain tissue. Tnnt 1 expression was induced in neuronal  cells, the hippocampal zone of neurogenesis, cerebral cortex, amygdale, and choroid plexus, which are important CNS locations in behavior and mental health. We also identified nine neural signaling pathways that showed a high degree of concordance in their transcriptional response in mouse brain tissue for hours after low-dose irradiation, in the aging human brain (unirradiated), and in brain tissue from patients with Alzheimer’s disease. Our studies provide new molecular information on shared mechanisms and expression profiles of diverse neuropsychiatric disorders. This knowledge will be fundamental for developing molecular signatures of early CNS stress biomarker for early diagnosis and treatment of neuropsychiatric diseases. The prevalence of major neuropsychiatric disorders such as schizophrenia, bipolar disorder, major depressive disorders and dementia is high, with little insight into underlying causes and molecular defects. Severe forms of depression affect 2-5% of the U.S. population, and up to 20% suffer from milder forms of this illness. Approximately 1%–2% of the populations are afflicted by bipolar disorder . The majThe treatment of major neuropsychiatric diseases was revolutionized by the introduction of several classes of medications  anti-depressants, and Memantine for dementia). Yet, our progress in understanding the genetic and neurobiological mechanisms underlying neuropsychiatric diseases has been disappointing . At bestet al. (2009) pr., (2008) reportedin situ hybridization techniques and fluorescence immunohistostaining Fig. (2) to search for candidate common early CNS stress response markers using mice treated with each of three different CNS stressors: ketamine, ionizing radiation and IFN-α that may produce symptoms that resemble various aspects of neuropsychiatric diseases and mimic the pathophysiologic conditions of diseases in the brain.For the current study, we utilized genome-wide expression profiling, RNA 137Cs source with a dose rate of 0.64 Gy min-1), and to IFN-α (by a single i.p. injection at 1 x 105 IU/kg ). RNA was isolated from the mouse brains tissues at various early times post treatment and hybridized to Affymetrix microarrays (MGU-74 av2 GeneChips®) Fig. (2). Several bioinformatics tools were used: GeneOntology (GO) enrichment analysis, Ingenuity Pathways Analysis (IPA 5.0), and L2L microarray analysis tool. GO analyses were performed using GO tree machine [We utilized genome-wide expression profiling to characterize the response of 8-10 week-old B6C3F1 male mice brain exposed to ketamine  injection at 80 mg/kg), ionizing radiation  in the CNS that are induced after exposures to a broad variety of environmental stress/insults, and that these mechanisms are associated with increased risks for a broad range of neuropsychiatric diseases.S1). Gene Ontology (GO) analyses showed that ketamine exposure of brain tissue induced significant biological processes, molecular functions and cellular components that were distinctly different from those treated with distilled water. Fig. (3) showed that ketamine-induced modulated genes were preferentially associated with metabolism, cell organization and biogenesis, intracellular signaling cascade and transcription in biological process analysis. The ketamine-induced signatures were significantly associated with protein and nucleotide binding in molecular function analysis Fig. (S1), and with the nucleus, cellular, membrane and cytoplasm component in cellular component analysis Fig. (S2). These GO analysis findings indicate that ketamine-induced damage responses in the brain are complex and functionally diverse and are significantly different from those of the controls. Troponin T1 (Tnnt1) gene showed consistent elevation (2- to 4-fold) across of the group of ketamine-treated mice. Tnnt1 nucleotides (GenBank accession number: AV213431 and AJ131711) showed ~ 4-fold increases for AV213431 (p <0.001) and ~ 2-fold increases for AJ131711(p< 0.03). Ingenuity Pathways Analysis (IPA) and network analysis were applied to the differentially expressed transcriptome profiles induced by ketamine exposure. Fig. (4) revealed that Tnnt 1  is associated with calcium canonical pathway (rectangle) and is regulated by FoxO1 (circle). Calcium metabolism plays a significant role in neuropsychiatric diseases in the CNS [Approximately 50 genes were differentially expressed in ketamine-treated mouse brains compared with control mice that received i.p. injection with distilled water,  containing mostly down-regulated genes involving ion channels, long term potentiation and depression, vascular damage, and other functions [Analyses of transcriptome profiles of mouse brain tissue 4 hours after whole body irradiation showed that low-dose exposures (10 cGy) induced genes not affected by high-dose radiation (200 cGy) and that low-dose genes were associated with unique pathways and functions. The low-dose response had two major components: pathways that are consistently seen across tissues and pathways that were specific for brain tissue. Low-dose genes clustered into a saturated network . Analyses of transcriptional profiles of mouse brain tissue one hour post IFN-α treatment showed no significant differentially expression between the IFN-α treated and distilled water treated mice  has been used routinely in emergency rooms for diagnosis and monitoring acute myocardial stress and infarction , 30. We 5 IU/kg). Brain issues were isolated at 30 min post ketamine treatment and at 4 hours post IFN-α and irradiation treatment Fig. (2). Patterns of Tnnt 1 transcript expression were compared in various CNS regions after ketamine, radiation and IFN-α treatments. The control mice showed unique regional expression patterns for the Tnnt 1 gene (Table 1): i.e., positive but weakly expression in the choroid plexus epithelium cells, ependymal lining of ventricles, and in the Ammon’s horn of hippocampus region and no detectable expression (negative) in pyramidal neurons and other regions. Tnnt 1 was induced in Purkinje cells of cerebellum after ionizing radiation and ketamine treatment; but not after IFN-α treatment. Tnnt 1 expression was consistently induced in pyramidal neurons of cerebral cortex, amygdale and hippocampal zone of neurogenesis after all three treatment regimens including 10 cGy of ionizing radiation (Table 1). Tnnt 1 was consistently enhanced in the choroid plexus after all three exposures (Table 1). Since the choroid plexus produces the majority of cerebral-spinal fluid (CSF), in the future, one might assess the status of Tnnt 1 modulation through CSF sampling.Adult B6C3F1 male mice were treated with either ketamine (a single i.p. injection at 80 mg/kg), whole body gamma-radiation  or human IFN-α , which is regulated by Fox O1 (circle) and involved in the Calcium signaling pathway (rectangle). Dark gray color: up-regulated genes. Light gray color: down-regulated genes. White color: genes that were not differentially expressed after ketamine treatment.5). We found that protein expression of Tnnt 1 was induced in mice treated with ketamine in the Purkinje cells, pyramidal neurons and in hippocampus region as shown in Fig. (5A). The patterns of protein expression of Tnnt 1 in CNS were consistent with those of RNA expression of Tnnt 1 Fig. (5B) [5)[Ketamine-induced Tnnt1 RNA expression was validated and characterized using fluorescence immunohistostaining in paraffin embedded brain tissue sections Fig. (ig. (5B) . The hig (5B) [5) indicatiin situ hybridization) and the level of protein expression (by fluorescence immunohistostaining). There were some notable discrepancies among these endpoints in tissues. This may be due to the different animals, different sections of brain tissues and different sampling times were used. Microarray analysis did not show the induced-expression of Tnnt 1 after 4 hours irradiation treatment whereas we found increased RNA expression using RNA in situ hybridization. This discrepancy between microarray and RNA in-situ hybridization endpoints may be related to a difference in sampling site used for the microarray analysis where the entire coronal section was used [insitu hybridization where the specific regions were used [2). For IFN-α treatment, the disagreement in results between the microarray and RNA in situ hybridization may be due to the different sampling time, where one hour post-treatment was used in microarray and four hour post treatment was used in RNA in situ hybridization analysis. In addition, the discrepancies may also arise from the less sensitivity of microarray assay when compared to RNA in situ hybridization assay, as the evidence that Tnnt 1 expression that was about 4 fold increased detected by microarray while about 20 fold increased in Purkinje cells of mice treated by Ketamine (Table 1).Our studies allow us to compare the effects of treatment at the level of RNA expression 2+ affinity as compared with other subunits in peripheral tissues [et al., (2005)[Troponin T is the subunit of troponin complex and interacts with tropomyosin, troponin C, troponin I and F-actin; and troponin T1 (Tnnt 1) has higher Ca tissues . Schevzo., (2005) reported., (2005).in situ hybridizations, we confirmed that RNA expression of Tnnt 1 was induced in mouse brain tissue after exposures to ketamine, ionizing radiation and IFN-α [Fig. (6). We believe that the induced expression of Tnnt 1 and co-modulated biomarkers of calcium signaling/other neuronal pathways in adult CNS will serve as a sensitive early indicator of CNS molecular stress that is predictive of neuropathological changes in the hippocampal zone of neurogenesis and the amygdala. Future studies to investigate the temporal expression relationship between the Tnnt 1 and calcium signaling markers and the temporal expression relationship between the calcium signaling pathway and neurogenesis are warranted Fig. (6).Using RNA nd IFN-α . We specIt is naïve to expect that any single gatekeeper function and biomarker will be sufficiently robust to identify all CNS stress mechanisms underlying neuropsychiatric diseases. A growing body of evidence suggests that neuropsychiatric disorders are the consequences of dysregulation of complex intracellular signaling cascades and neuronal networks, rather than the consequences of deficits or excesses of individual neurotransmitters . To captin vivo systems approach, we compared the CNS transcriptional profiles of mice exposed to the stress exposure of low-dose ionizing radiation versus published CNS signatures associated with normal aging and Alzheimer’s disease. Specifically, we compared our set of radiation response genes against a compendium of data sets of transcriptional profiles of various genetic and disease conditions including those from individuals with diminished cognitive function . As an example of our on 2007.1) to idenon 2007.1 and pation 2007.1. IPA wason 2007.1, and to on 2007.1. Compari2) and the integrin signaling pathway was the only pathway that was consistently up-regulated. In addition, three pathways  were significantly affected in all three data sets, but they differed somewhat in the direction of their effects (up- or downregulation)[Six pathways that are known to be associated with neuropsychiatric diseases were in full agreement among all data sets. Five out of six showed consistent down-regulation (Table gulation).Our findings suggest that low-dose irradiation modulates the expression of gene pathways that are also involved in human cognitive dysfunction associated with normal aging and Alzheimer’s disease. These findings support our hypothesis that there may be common mechanisms of CNS stress response, independent of the nature of the stressor. Future studies are warranted to determine whether other CNS stressors show similar responses and to characterize the time course of induction, duration, and persistence of stress responses in relation to the onset of neuropsychiatric illnesses.in vivo exposures to ketamine, ionizing radiation and IFN-α, all of which are known to increase the risks of neuropsychiatric diseases. The involvement of the choroid plexus which produces CSF raising the interesting possibility that CNS stress biomarkers may be detected in CSF in the future. Using a systems biology approach, we demonstrated that six neural signaling pathways associated with neuropsychiatric diseases were concordantly modulated in mouse brain tissue after low-dose (10 cGy) irradiation, in normal aging of the human brain (unirradiated), and in brain tissue from patients with Alzheimer’s disease. This suggests that diverse CNS stressors and pathologies can share common molecular stress response mechanisms.We demonstrated that the expression of Tnnt 1 was significantly induced in mouse brain tissue, including in the choroid plexus, after Our systems approach addresses a critical challenge of how to identify candidate biomarkers of early CNS stress for validation studies towards applications for preclinical diagnoses and for monitoring the treatments of neuropsychiatric diseases. Effective biomarkers of the CNS stress responses will open doors to urgently needed advances in the development and testing of new diagnostic and treatment strategies for neuropsychiatric disorders. Our studies provide several specific insights into the mechanisms of CNS stress-responses that may become useful for developing early diagnostics for CNS stress (as examples: (1) the association with Calcium signaling may lead to the development of brain imaging methods base on calcium ligands, and (2) choroid plexus secretions associated with stress responses may be detectable in the CSF as protein biomarkers or as other molecular signatures). CNS stress response biomarkers and molecular stress signatures hold the promise to enable rapid advances in early diagnosis and, hopefully, to provide mechanism-based treatments options of neuropsychiatric diseases in the future. Supplementary material is available on the publishers Web site along with the published article.