However, the evolutionary and ecological implications of satellites on helper viruses remain unclear. Here, using staphylococcal pathogenicity islands (SaPIs) as a model of virus satellites, we experimentally show that helper viruses rapidly evolve resistance to their virus satellites, preventing SaPI proliferation, and SaPIs in turn can readily evolve to overcome phage resistance. Genomic analyses of both these experimentally evolved strains as well as naturally occurring bacteriophages suggest that the SaPIs drive the coexistence of multiple alleles of the phage-coded SaPI inducing genes, as well as sometimes selecting for the absence of the SaPI depressing genes. We report similar  evolution of resistance to SaPIs in laboratory phages used for Staphylococcus aureus typing and also obtain the same qualitative results in both experimental evolution and phylogenetic studies of Enterococcus faecalis phages and their satellites viruses. In summary, our results suggest that helper and satellite viruses undergo rapid coevolution, which is likely to play a key role in the evolution and ecology of the viruses as well as their prokaryotic hosts.Virus satellites are widespread subcellular entities, present both in eukaryotic and in prokaryotic cells. Their  Staphylococcus aureus phages. Since SaPIs exploit the life cycle of their helper phages to enable their rapid replication and promiscuous spread, these strategies are mechanisms that reduce SaPI interference, thus facilitating the infectivity and dissemination of the helper phages in nature.Satellites are defined as viruses that have a life cycle dependent on a helper virus. Thus, they can be considered as parasites of parasites. In addition to their fascinating life cycle, these widespread infectious elements, present both in eukaryotic and prokaryotic cells, have a dramatic role in virulence by controlling the symptoms induced by their eukaryotic helper viruses or by encoding key bacterial virulence genes. While satellites can play an important role in the ecology of the viruses they parasitise, the evolutionary impact on their helper viruses is unclear. Here we show that staphylococcal pathogenicity islands (SaPIs), an example of a virus satellite, are a major selective force on the viruses (bacteriophages) they parasitise. Using both bioinformatic and experimental evolution data we have been able to confirm that pathogenicity islands are a major selective pressure enhancing the diversity of both genes and gene content in  Staphylococcus aureus pathogenicity islands (SaPIs), a type of satellite virus, reduces phage proliferation [Vibrio cholerae phage satellites control not only the expression of the clinically relevant CTX phage-coded cholera toxin, but also the transmission of their helper CTX phage [Satellites are defined as viruses which have a life cycle dependent on a helper virus, but lack extensive nucleotide sequence homology to the helper virus and are dispensable for helper virus proliferation –4. Theseferation ,6. Givenferation , satelliferation . Satelliferation ,10, VibrTX phage ,12.Interactions between hosts and their parasites frequently result in antagonistic coevolution, with host evolving defence and parasites evolving counter defence . Given tThe SaPIs are the prototypical members of a widespread family of highly mobile pathogenicity islands, the PICIs , that exploit the life cycle of their helper phages with elegant precision to enable their rapid replication and promiscuous spread ,10. In tstl-mutants that can be packaged and transferred by the evolved non-inducing phages, imposing a large transmission cost on the helper phages. Furthermore, bioinformatics data supports the view that SaPIs are an important selective pressure driving the diversity of both genes and gene content in S. aureus phages. Finally, to show the generality of this result we report similar experimental and bioinformatic results for Enterococcus faecalis phages. Taken together, our results suggest that helper and satellite viruses undergo extensive antagonistic coevolution.In previous work, we observed that different helper phages encoded allelic variants of the inducing genes with different affinity for the SaPI-encoded repressors . Moreovein vivo by calculating and comparing the dN−dS values of the representative SaPI inducer genes  and synonymous site (dS), is classically used as an indicator of selective pressure acting on a protein-coding gene. As is summarised in dN−dS comparisons were significantly lower than 0 (p < 0.005), indicating that the SaPI inducers are under purifying selection.To determine if SaPIs play an obvious role in phage evolution, we initially analysed the phage sequences deposited in GenBank and identified allelic variants of the phage-coded SaPIbov1, SaPI1 and SaPIbov2 inducing proteins, corresponding to the dUTPase (Dut), Sri and 80α ORF15-like proteins, respectively [er genes . The dNIt is assumed that the main consequence of the purifying selection is a reduction in the level of variation present in the locus under selection, produced by the removal from the population of less-adapted variants. However, the existence of multiple alleles in the phage-coded SaPI inducers suggests the existence of an evolutionary force operating in opposite direction that maintains the diversity observed in the SaPI inducer proteins. In previous studies, we demonstrated that variants of the SaPIbov1 and SaPIbov2 derepressing proteins differentially induce the SaPIbov1 and SaPIbov2 cycles, respectively . MoreoveTo test the hypothesis that phages are under strong selection to resist SaPIs, we experimentally determined if the interaction with the SaPIs resulted in the evolution of phages carrying variants in the SaPI inducing proteins. Phage 80α was used as a model because it induces three different SaPIs: SaPIbov1, SaPIbov2 and SaPI1. Strains RN4220  or JP1996 (RN4220 derivative carrying SaPIbov1) were initially infected with phage 80α  induced and the capacity of the different phages to induce the SaPIs cycle was analysed. As shown in We first determined growth of the ancestral and evolved phages. As observed in dut (dUTPase). This result was further confirmed by sequencing the dut gene from other 120 evolved phages (60 infecting RN4220 and 60 infecting JP1996), obtained from 3 independent experiments. As summarised in dut. By contrast, no mutations were observed either in the other SaPI inducer genes, corresponding to sri and ORF15, or in the phages infecting the SaPIbov1-negative strain  and 5 from the third passage on the RN4220 (SaPI-negative) branch were completely sequenced and analysed. Only phages that interacted with SaPIbov1 contained mutations in their genomes, which were in all cases located in the SaPIbov1 inducer gene n Tables .To determine the genetic basis of resistance to the other SaPIs, SaPIbov2 and SaPI1, the SaPI inducer genes from 120 evolved phages  were analysed. The SaPI inducer genes were also sequenced from 60 phages that had only infected the SaPI-negative RN4220 strain . As occudut genes from the evolved phages did not induce SaPIbov1, while the wild-type gene did. As the Dut protein levels produced from these constructs are comparable  induced and the islands transferred to the cognate recipient strains carrying the same phage that was present in the donor strain. After the transfer, the SaPI-positive strains were recollected and the procedure repeated 7 more times. After the eighth passage, the SaPI titre obtained was compared with that obtained with the original SaPIs. Remarkably, at the end of the experiment the SaPIs that interacted with the mutant phages increased their titres more than 104-fold  in the previous experiments . The SaP104-fold , suggeststl gene. These mutations, located in the coding or in the promoter region of the stl gene  from a reference laboratory, and isolated, from each of these samples, five single phages, which were amplified using the non-lysogenic RN4220 strain. We used both the amplified phages obtained from the single plaques as well as the original phage populations to infect the non-lysogenic strain RN4220, as well as derivatives of this strain carrying SaPI1, SaPIbov1 or SaPIbov2. The rationale for this experiment was to compare the interference observed with these different phage samples. We hypothesised that if both samples had the same plating efficiency (interference) rate when infecting any of the SaPI-positive strains, both phage populations would be genetically homogenous (related to the SaPI inducers). By contrast, if a different behaviour was observed, and one of the samples infected the SaPI-positive strain better than the other sample, this would imply that the original population contained a mixed phage population that probably had evolved in response to the SaPI interference. Although the analysis of the ϕ29 and ϕ52A phage populations did not reveal any difference between the purified phages and those present in the samples from the reference laboratory, 1% of the original ϕ55 phage population generated plaques in the SaPI1-positive strain. By contrast, only 0.001% (1000 x reduction) of the purified ϕ55 phages generated plaques in this strain. This result suggested that the original phage lysate contained at least two different phage populations, evolved from a common ancestor, carrying variants of the SaPI1 inducing gene.Given the likely importance of SaPI-imposed selection, we speculated simple amplification of phages to obtain high titers of phage stock may have itself resulted in significant SaPI-imposed evolution. Phage collections have been traditionally used to type Siphoviridae [S. aureus phages, one of many plausible explanations for the differences between these two phages is that recombination occurred between ϕ55–2 and a prophage residing in the propagating strains. To verify that the aforementioned changes observed in phage ϕ55–3 were not generated during the purification and amplification of the phage, PCR experiments with specific oligonucleotides for each of the phages were performed, using DNA samples obtained from the original phage population (without amplification).To test this, one of the previously purified phages infecting RN4220 but showing interference to the SaPI-positive strain was completely sequenced (ϕ55–2). One phage having no interference to SaPI1 was also purified and sequenced (ϕ55–3). The genome length of ϕ55–2 is 41,898 bp, containing the information for approximately 81 ORFs of 50 or more codons, and is deposited in GenBank under accession number KR709302. The genome length of ϕ55–3 is 42,309 bp, with approximately 83 ORFs, and is deposited in GenBank under accession number KR709303. Both ϕ55–2 and ϕ55–3 belong to a class of related staphylococcal oviridae . OverallTo confirm that the mutations present in phage ϕ55–3 conferred an advantage for the phage in the presence of a SaPI1-positive strain, competition experiments (in triplicate) were performed in which a SaPI1-negative or a SaPI1-positive strain were infected (phage:bacteria ratio 1:3) with a mixed population (1:1) of the ϕ55–2 and ϕ55–3 phages. The lysates obtained from each experiment were used to infect again the same strains, and after the third passage, the number of the ϕ55–2 and ϕ55–3 phages was evaluated by PCR using oligonucleotides that specifically recognise the different allelic variants of the phage coded SaPI1 inducers. While both phages were present in equal numbers after infecting the SaPI-negative strain , passages through the SaPI1-positve strain selected for ϕ55–3 (>95%).The previous results suggested that it would be possible to find closely related phages encoding different alleles of the SaPI inducers as a consequence of the phage interaction with the SaPIs. To address this, we initially performed a phylogenetic analysis of 33 randomly selected staphylococcal phages . Next, wsri was absent in phages ϕ11, ϕPVL or ϕNM3 and the SaPIbov2 inducer was not present in phages ϕ11, ϕNM2, ϕPVL-CN125, ϕPVL, ϕNM3 or ϕ52a, although closely related phages coded for the missing inducers  similarity to the 80α or ϕ11 Duts. Two promising candidate were the Dut proteins encoded by the prophages ϕSaov3 and B2 (accession numbers YP_005736587 and ERS400827), which have only 5 amino acid changes compared with the 80α and ϕ11 Duts, respectively . As showp < 0.01, Student’s t-test) their dUTPase activity  gene  gene . Remarka3 island .in vivo, we analysed whether related enterococcal phages encoded allelic variants of the EfCIV583 inducer, and if these variants are under purifying selection. As shown in Next, to test if this process is relevant S. aureus. We confirm previous results that parasitism by SaPIs, which exploit phages for their own transmission, impose a massive growth rate cost on the phages [S. aureus phages through bioinformatic analyses and in laboratory populations of S. aureus phages used in phage typing. Finally, we report comparable experimental and bioinformatics results in E. faecalis.The significance of coevolution between prokaryotes and their viruses ,24, and e phages –25. We ti) blocking of phage DNA packaging by expression of the SaPI-coded Ppi protein, which interferes with the phage coded TerS protein [ii) diversion of phage proteins to produce the SaPI-specific particles [iii) expression of the PtiA homologs [iv) carriage by the SaPIs of the phage cos or pac sites in order to compete with the inducing phages to be packaged in the phage particles [We have previously demonstrated that one of the key features of the SaPIs is to interfere with helper phage reproduction, using a variety of mechanisms. These include  protein ; ii) divarticles ; iii) exhomologs , which bhomologs ,27, direarticles ,29. In tarticles .stl gene severely affects bacterial physiology and growth, probably because of the uncontrolled replication of the stl mutant SaPIs [stl mutants. These costs of SaPI resistance presumably arise because the phage-coded SaPI inducers are proteins that perform their functions through protein-protein interactions with other phage- or bacterial-coded proteins [dut) and SaPIbov2 (80α ORF15) inducers, the Sri protein (SaPI1 inducer) interact with the cellular DnaI protein inhibiting staphylococcal replication [While our results show that coevolution between satellite and helper viruses can occur very rapidly, it opens up a number of key questions. Specifically, how is the intimate association between phages and SaPIs maintained given that SaPI adaptation resulted in the loss of the need of specific helper phages for induction? First, there are massive costs associated with loss of function of the SaPI global repressor. As previously reported, mutations in the nt SaPIs . This exproteins , and thaproteins . Althouglication .Based on this and previous in vitro results discussed above, one type of dynamic of continual phage-SaPI coevolution in nature may therefore be cycles of the following specific events: i) Phages evolve SaPI resistance by alteration or loss of the inducing protein, assuming that the short term benefits of SaPI resistance outweigh fitness costs (if any) associated with changes in the inducing protein; ii) SaPIs respond by loss of the need to be induced by a helper phage, again assuming benefits to the SaPI of being transmitted to new hosts outweigh the costs of reducing the fitness of hosts they infect; iii) As a result of the mutant SaPIs being able to exploit both the original and mutant “resistant” phages, phages with the original unaltered SaPI inducing proteins are able to outcompete mutant phages because of the costs associated with altered inducing proteins which no longer confer resistance; and iv) SaPIs that require induction by helper phage proteins can now outcompete SaPIs that do not require an inducer because there are large numbers of inducing phage present, starting the cycle again. This type of coevolutionary dynamic can be described as range fluctuating selection , and canThe high diversity of phage inducing protein alleles suggests however alternative coevolutionary dynamics are operating in nature in addition to or instead of the model described above. Specifically, SaPI-imposed selection may cause diversifying selection if SaPIs adapt to changes in inducing proteins by switching to exploit the modified or an alternative protein, rather than losing the need for specific helper phages, and hence evolving more general infectivity. Consistent with this model, SaPIs, encoding different Stl repressors, have acquired the ability to exploit entirely unrelated phage proteins as antirepressors, and SaPIs tend to be induced by single rather than multiple proteins . This coWe have also demonstrated that another member of the PICI family of mobile genetic elements, the EfCIV583 island, drives phage evolution. Since one of the key features of the PICI elements is to interfere with the phage biology, we anticipate that these elements will have developed multiple interference functions that will have to be overcome by the helper phages in order to prevent PICI interference. Since PICI elements have been found in most Gram-positive bacteria, we anticipate that the strategies reported here by which the phages evolve in response to the SaPIs are widespread in nature.S. aureus and E. faecalis can have important ecological and evolutionary implications on their helper viruses. Crucially, these findings add another layer of complexity to the increasingly recognised role of coevolution between viruses and their bacterial hosts in driving ecological and evolutionary dynamics of these organisms [Our work shows that virus satellites associated with both rganisms . For exaS. aureus, were performed essentially as previously described [E. faecalis lysates were obtained and prepared as previously indicated [The bacterial strains used in these studies are listed in escribed ,28,34. Endicated .General DNA manipulations were performed using standard procedures. The plasmids and oligonucleotides used in this study are listed in 7 cells of the SaPIbov1-positive strain JP1996 were initially infected with phage 80α (1:1 ratio). Once the culture lysed, which occurred normally 4–5 hours post-infection, the resulting phage population was titred and used to infect again the SaPIbov1-positive strain, using always the aforementioned cells:phage ratio. The phage lysates obtained after the third passage done in strain JP1996 were used to infect strain JP2129, an RN4220 derivative carrying SaPIbov2. After the third passage done in this strain (JP2129), the evolved phages were then used to infect JP2966, an RN4220 derivative carrying SaPI1. As a control, phages only infecting RN4220 were propagated and analysed through the experiment , and the resulting plasmids ; greater than zero supports positive directional selection, and lower than zero is taken as evidence of purifying (stabilising) selection. Substitution rates were computed using Nei-Gojobori modified method with Jukes-Cantor correction . Standard errors were estimated by a bootstrap procedure (1000 replicates). These analyses were done using MEGA5 [Selective pressures operating on SaPI or EfsCIV583 inducers were analysed using the average difference between substitution rates per nonsynonymous and synonymous sites, ng MEGA5 .www.datamonkey.org). No evidence for recombination was found for the SaPI1 (Sri), SaPIbov2 and EfsCIV583 inducers. However, a weak evidence was found by RDP4 for the SaPIbov1 inducers (Duts), but this was not supported by the other algorithms. Thus, we decided not to consider any Dut sequence as a truly recombinant.Sequence alignments were screened for the presence of recombination using all the algorithms implemented in the RDP4 program  as well The genome of selected phages was aligned using MAUVE version 2.3.1  with itsE. coli, using standard procedures. Enzyme assays were performed using the EnzCheck Pyrophosphate Assay Kit (Molecular Probes), as previously reported [dUTPase activity was assayed using His(6)-dUTPase proteins purified after expression in reported .S1 FigS. aureus phages and prophages, coloured according to relative sequence conservation at each position. Adapted from lineup generated by PRALINE. Accession numbers Dut proteins: 80 (YP_001285346); Rosa (YP_240373); 71 (YP_240446); ETA2 (YP_001004294); PVL108 (YP_918921); NM3 (YP_908820); 85 (YP_239795); 3A (YP_239989); PVL-CN125 (YP_002939700). SaPIbov2 inducers: ROSA (YP_240350); 85 (YP_239776); 80 (YP_001285329); Strain DAR390 (EXY00034); Strain PLAC6004 (EVF70071). Sri proteins: Strain A6300 (EEV76885); Strain Mu50 (BAB57032); 85 (YP_239784); Strain 21252 (EHO92899); Strain M79256 (EXP87181); 80 (YP_001285336); 55 (YP_240514). Phylogenetic network of the SaPI inducer coding genes generated by SplitsTree version 4.11.3 . Numbers in the branches indicate the bootstrap support for each bipartition. Branch lengths are proportional to genetic differences among phage-coded SaPI inducers. Shaded are the proteins characterised in this study.  Lineup of selected SaPI inducer protein sequences from different (PDF)Click here for additional data file.S2 Fig(PDF)Click here for additional data file.S3 FigS. aureus phages in the presence of possible recombination events and of parallel evolutionary changes is shown. Shaded are the proteins characterised in this study. Accession numbers phages: 80 (DQ517338); 53 (AY954952); 11 (AF424781); 85 (AY954953); 69 (AY954951); NM1 (DQ530359); NM2 (DQ530360); ETA2 (AP008953); 12 (AF424782); PVL (AB009866); PVL108 (AB243556); 42E (AY954955); 52A (AY954965); ROSA (AY954961); PVL-CN125 (FJ713816); 77 (AY508486); 47 (AY954957); P954 (GQ398772); NM3 (DQ530361); MR11 (AB370268); 187 (AY954950); SLT (AB045978); tp310-3 (EF462199); 29 (AY954964); 71 (AY954962); 2638A (AY954954); EW (AY954959); 37 (AY954958); PH15 (DQ834250); 13 (AF424783); 55 (AY954963); 80 (DQ908929); MR25 (AB370205). (B). Lineup of the SaPI inducer proteins selected in (A). Adapted from lineup generated by PRALINE. Accession numbers Dut proteins: SLT (NP_075491); 187 (YP_239558); 12 (NP_803328); 2638A (YP_239842); 29 (YP_240597); ROSA (YP_240373); PVL-CN125 (YP_002939700); tp310-3 (YP_001429990). SaPIbov2 inducers: EW (YP_240202); PH15 (YP_950707); 37 (YP_240124); 29 (YP_240582.1); ROSA (YP_240350); MR25 (YP_001949812); ETA2 (YP_001004275). Sri proteins: 52A (YP_240656); 55 (YP_240514); tp310-3 (ERS400827); PVL-CN125 (YP_002939693.1).(A) The genetic relatedness among the (PDF)Click here for additional data file.S4 Figt-test was used to compute p values for group comparisons; differences that are statistically significant are indicated by an asterisk (p < 0.01). All error bars show s.e.m.The graph shows the Vmax, expressed in nmoles of dUTP hydrolysed in one second for 1μg of protein, measured for Dut80α and mutants. In all cases, the experiments were done in triplicate. Student’s (PDF)Click here for additional data file.S5 Fig8 bacteria were infected with 400 p.f.u. of phage 1, plated on phage bottom agar, and incubated 24h at 32°C. Plates were stained with 0.1% TTC in TSB and photographed.Approximately 10(PDF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S3 Table(PDF)Click here for additional data file.S4 Table(PDF)Click here for additional data file.S5 Table(PDF)Click here for additional data file.S6 Table(PDF)Click here for additional data file.S7 Table(PDF)Click here for additional data file.S8 Table(PDF)Click here for additional data file.


In vitro and animal studies continue to elucidate the mechanisms of fibrosis and have led to advancements in treatment for idiopathic pulmonary fibrosis and cirrhosis, but the search for treatments for renal fibrosis has been more disappointing. Here, we will discuss homeodomain-interacting-protein kinase 2 (HIPK2), a novel regulator of fibrosis that acts upstream of major fibrosis signaling pathways. Its key role in renal fibrosis has been validated in vitro and in several murine models of chronic kidney diseases (CKD). Fibrosis is the final common pathway for chronic kidney diseases (CKD). Renal fibrosis occurs as an overwhelming response to tissue injury. The attempt to repair damage begins with the recruitment of inflammatory cells, but ends with an unchecked inflammatory response that activates matrix-producing cells leading to tubular cell apoptosis, irreversible scarring, loss of renal function, and ultimately end stage renal disease (ESRD)  which acts upstream of several pro-fibrosis pathways.Novel drugs targeting the signaling pathways of renal fibrosis have generally given mixed results and occasionally concerning side effects. The shortcomings of these experimental therapies are likely due to the fact that the pathogenesis of fibrosis is complex; blockade of one pathway may still leave open many others for promoting inflammation and fibrosis.A central mediator in renal fibrosis is transforming growth factor-β (TGF-β). TGF-β superfamily is highly conserved and plays a major role in a variety of cellular responses including cell proliferation, differentiation and apoptosis. TGF-β1, the predominant isoform, stimulates extracellular matrix production via Smad-dependent and Smad-independent mechanisms to inhibit extracellular matrix degradation and promote expression of pro-fibrosis genes in various cell types . These drugs are appealing because they block chronic inflammation in addition to decreasing aberrant wound healing. Pirfenidone has well-established anti-fibrotic and anti-inflammatory properties in various in-vitro studies show that it reduces collagen synthesis in fibroblasts, and inhibits the production of interleukin-6 in endothelial cells  is part of the TGF-β family and actually opposes the pro-fibrogenic effects of TGF-β1 by blocking transcriptional upregulation of plasminogen activator inhibitor-1 and antagonizing TGF-β-induced epithelial-mesenchymal transition  modulates TGF-β and BMP-7 activities. CTGF is not expressed in normal kidney but is upregulated in human kidney disease where it enhances TGFβ-1 signaling resulting in myofibroblast activation, fibronectin accumulation and tissue fibrosis  by genetic ablation of HIPK2. In all three separate models of CKD, loss of HIPK2 resulted in attenuation of renal fibrosis, consistent with the role of HIPK2 as a regulator of gene expressions involved in tubular injury and fibrosis.In renal tubular epithelial cells (RTEC), HIPK2 induced expression of pro-fibrosis markers and apoptosis in HIV-infected RTEC, likely due to its role in activating p53, TGF-β, and Wnt/Notch pathways, which are each known to increase expression of pro-fibrosis markers  mediated proteasomal degradation. However, oxidative stress, such as from HIV infection, decreased SIAH-1 mRNA and protein expression The above data suggest that inhibition of HIPK2 would mitigate renal fibrosis progression in kidney disease. Importantly, genetic ablation of HIPK2 does not result in a significant phenotype, as opposed to the detrimental effects seen with partial NF-κB inhibition, making HIPK2 an attractive target for therapy (Doi et al., One concern of using HIPK2 inhibitors as anti-fibrosis therapy is its tumor suppressive effects. HIPK2 suppresses tumor growth by activating p53 and inducing tumor cell apoptosis (Li et al., in vitro in cultured kidney cells and in vivo in animal models of kidney disease. However, currently, none of the drugs targeting these pathways have been proven to be effective anti-fibrosis therapy for kidney disease in large clinical trials. One potential reason is that renal fibrosis is mediated by a complex signaling network of several different pathways. Therefore, targeting one pathway is not enough to be effective. HIPK2 has been identified as a master regulator of kidney fibrosis and acts upstream of several major fibrosis-signaling pathways. Controlling HIPK2's activities might be an effective approach to reduce the progression of kidney fibrosis. However, it is important to note that HIPK2 also has some onco-suppressor functions and that loss of HIPK2 may also lead to neurodegenerative disease (Lanni et al., Several key signaling pathways that mediate renal fibrosis have been identified. This has been shown both The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Escherichia coli O157:H7 (EcO157) associated with the 2006 spinach outbreak appears to have persisted as the organism was isolated, three months after the outbreak, from environmental samples in the produce production areas of the central coast of California. Survival in harsh environments may be linked to the inherent fitness characteristics of EcO157. This study evaluated the comparative fitness of outbreak-related clinical and environmental strains to resist protozoan predation and survive in soil from a spinach field in the general vicinity of isolation of strains genetically indistinguishable from the 2006 outbreak strains. Environmental strains from soil and feral pig feces survived longer  with Vorticella microstoma and Colpoda aspera, isolated previously from dairy wastewater; these D-values correlated (P<0.05) negatively with protozoan growth. Similarly, strains from cow feces, feral pig feces, and bagged spinach survived significantly longer in soil compared to clinical isolates indistinguishable by 11-loci multi-locus variable-number tandem-repeat analysis. The curli-positive (C+) phenotype, a fitness trait linked with attachment in ruminant and human gut, decreased after exposure to protozoa, and in soils only C− cells remained after 7 days. The C+ phenotype correlated negatively with D-values of EcO157 exposed to soil , Vorticella  or Colpoda . In contrast, protozoan growth correlated positively with C+ phenotype  suggesting a preference for consumption of C+ cells, although they grew on C− strains also. We speculate that the C− phenotype is a selective trait for survival and possibly transport of the pathogen in soil and water environments. Escherichia coli O157:H7 (EcO157) responsible for over 200 infections in a large multi-state outbreak There are numerous habitats in the vicinity of produce production, each of which may affect survival of EcO157 differently. Although most EcO157 strains decrease rapidly in the soil and manure environments E. coli and other pathogenic bacteria is through proliferation within vacuoles A mechanism for increased survival of Colpoda aspera, Vorticella microstoma and Platyophrya sp. from dairy wastewater that consumed EcO157 in preference to native bacteria Direct evidence was reported for sequestration of EcO157 in vacuoles of protozoa isolated from store-bought spinach and lettuce csgA, are expressed in response to low temperature, low oxygen, low osmolarity, and nutrient limitation Survival of specific strains of EcO157 in sufficient numbers to cause infection is associated with their intrinsic fitness traits and genetic makeup − phenotype may confer a selective advantage in surviving austere environments. C− strains survive up to 10,000 times better than C+ strains under acidic conditions (pH 2.4) and this appears to occur by maintaining C− cells regardless of selection pressure Subpopulations of EcO157 have been reported to adapt to harsh environmental conditions V. microstoma and C. aspera of clinical and environmental strains of EcO157 that are highly related genotypically and associated with the 2006 spinach outbreak. In addition, we compared if specific phenotype subpopulations that evade protozoan predation are increased in fitness for survival in soil from produce field.We described differences in predation of EcO157 by different protozoa isolated from dairy wastewater in a previous study Soil samples were provided by the Western Center for Food Safety and Security, University of California at Davis. No special permits were required as the soils were collected under cooperative agreements with produce growers and the samplings did not involve any endangered or protected species.stx2 (Shiga-toxin), eae (intimin), and hly (hemolysin); and serotype specific genes, fliC (H7-antigen) and rfbE (O157-antigen) EcO157 strains  were selg for 5 min and washed twice in 0.01 M PBS (pH 7.0) and adjusted to OD600 of 0.3 prior to inoculations to Sonneborn medium  or soil. Enumeration of EcO157 from soils or protozoa media was carried out by plating 100 µl volumes of 10-fold serial dilutions in 0.01 M PBS onto Rainbow-NT agar and the bluish-grey colonies were counted after over-night incubation at 37°C. Some colonies were tested at random by real-time PCR to confirm the presence of O157-antigen specific gene rfbE, using a method described previously Isolated colonies from Rainbow-NT agar were grown over-night in 10% Luria broth  at 25°C and at 150 rpm on a gyratory shaker, cells were separated by centrifuging at 10,000×+ (red) and C− (white) colonies were tested at random to confirm the presence of rfbE The proportion of phenotypic variants of EcO157 strains, post-protozoan or soil exposure, expressing C was determined as described previously V. microstoma and C. aspera isolated previously pH 7.0) supplemented with 5% 3-µm filtered and heat-killed wastewater was inoculated with 1×108 CFU/ml of EcO157 and 2×103 cells of protozoa per ml . A 7-day old growth of protozoa in Sonneborn medium was used as inoculum. Overnight growth of EcO157 strains in 10% LB broth, centrifuged and resuspended in 0.01 M PBS was used as the bacterial food source for protozoa. The populations of both EcO157 and protozoa during a 7-day incubation without agitation at 25°C were determined using methods described previously Consumption of EcO157 strains was determined using 7 CFU of EcO157 cells in 160 µl and adjusted to moisture at 50% water holding capacity (26.1% moisture on dry weight basis) by adding 110 µl sterile distilled water. Vials containing the inoculated soils were capped loosely to allow aeration, incubated at 25°C and sampled at regular intervals for the enumeration of surviving EcO157 cells and for analyzing the proportion of C subpopulations as described above. The moisture loss at each sampling interval was monitored by weighing another set of vials containing un-inoculated soil. Soils were mixed thoroughly with sterile spatulas and ∼100 mg soil samples by weight were removed and used to make 10-fold serial dilutions for enumeration of EcO157. D-values were calculated based on the decreases in EcO157 populations during a 7-day incubation period. All the comparisons were in triplicates and the data was analyzed statistically as described above. In addition, Spearman rank order correlations were used to compare the fitness of EcO157 in soil with resistance to predation; growth increases of protozoa and the proportion of C subpopulations.Survival of nine EcO157 strains  was moniV. microstoma and C. aspera to determine if any strains resist predation or, alternatively, were consumed preferentially based on their genetic differences or source of isolation. Inter-strain differences in predation of EcO157 isolates were indicated by a wide range of D-values from 1 to 35 days in the presence of Vorticella and 4 to 26 days for Colpoda   . All strP<0.001; Colpoda compared to Vorticella (P<0.001) resulting from the consumption of EcO157 cells  than the clinical outbreak strains of MLVA 163. These results indicate that strains that are highly related by MLVA can have functional fitness differences depending upon the environment to which it was exposed.Tests with strains grouped based on MLVA typing  indicateP<0.001, + subpopulations decreased significantly (P = 0.006) during the 7-day incubation with both protozoa and even more significantly with strains RM6441, RM9993 and RM6331 and RM6553 (P<0.0001). However, C− strains . The proportion of C+ variants in the presence of protozoa was correlated negatively with D-values . Thus, log increases in protozoa correlated negatively with D-values of EcO157 strains  with the proportion of C variants. Only C− variants remained in soil after a 7-day exposure of 7 out of 9 strains. The proportions of C+ and C− variants of the other two strains  were not evaluated.The fate of EcO157 in soil was monitored to evaluate if strains that resist predation also survive longer in soil. Nine strains from fitness studies with protozoa  were useEcO157 is prevalent in agricultural environments  and has been detected frequently in environmental samples during and after the 2006 spinach outbreak EcO157 strains from environmental sources such as soil and feral pig feces, in particular, resisted predation by both protozoa significantly . These sVorticella consumed EcO157 cells more rapidly (P = 0.031) compared to Colpoda  with isolates that resisted predation and were from feral pig feces and soil. Similarly, protozoa that can feed and grow on EcO157 when released into dairy ponds might explain why EcO157 were not isolated in a previous study from dairy wastewater Protozoa grew as they consumed EcO157 strains rapidly and, as expected, protozoan growth was correlated negatively with D-values of EcO157 , Table 3ficantly  compared strains  that are+ to C− variants correlated negatively with D-values indicating significant consumption of EcO157 resulting in growth increases of both protozoa (+ variants were rapidly consumed by both protozoa and decreased the proportion of C+ variants very significantly (P<0.0001). In contrast, strains from feral pig feces and dry pasture soil were predominantly C−  in spinach field soil resulted in recovering only C− subpopulations. This previous environmental exposure is probably associated with extended survival in soil when it is re-inoculated into soil, and may be due to C− strains being isolated predominately from these environments; this is consistent with the proportion of C+ variant subpopulations correlating negatively  with soil D-values , and is consistent with significant acid stress-resistance reported for C− variants of EcO157 strains We hypothesize that EcO157 strains with increased percentage of CD-values . We spec− variants, predominately, surviving the exposure, a negative correlation of proportion of C+ variants with D-values of EcO157 and a positive correlation with growth of both predators. Since 8 of the 9 strains used in these tests are genetically indistinguishable from the 2006 spinach outbreak strain by MLVA (163), soil fitness or predation resistance of these isolates cannot be attributed to genetic differences. However, the naturally persistent, but genetically different, soil isolate (MLVA778), which was 87% C− variants, resisted predation by both protozoa and also survived longer in spinach field soil. Thus, it appears that most pathogenic EcO157 fail to survive in hostile soil and water environments, but selection and enrichment of C− variants is one survival strategy that may relate to contamination of produce.The fitness responses observed for survival of EcO157 under stressful conditions in soil and resisting predation by protozoa were quite similar. Both environments elicited a similar phenotypic response of C−. Thus, the presence of C− variants in a population of cells at some frequency appears to be a survival mechanism associated with EcO157 fitness in soil and on plant surfaces rpoS) and the role of C+ and C− variants in complex environments warrant further studies to determine whether selection of some variants are associated also with hypervirulent strains associated with outbreaks.In summary, these results indicate that the environmental persistence of pathogenic EcO157 is associated with the fitness of clonal subpopulations, although some generalizations can be made on survival in soil and resistance to predation based on isolation source. Whereas populations of clinical strains associated with the spinach outbreak decreased rapidly in soils or were consumed rapidly by protozoa, environmental strains  survived longer in soil and resisted predation. Our results suggest also that exposure of EcO157 strains to stress conditions (e.g. soil or protozoa) generally result in rapid die-off, but the subpopulations that do survive are usually CTable S1MLVA characteristics of EcO157 strains used. Number of tandem repeats at each of 11 loci are given.(DOCX)Click here for additional data file.Table S2Two-way ANOVA comparisons of strain differences in fitness of EcO157 to protozoan predation, protozoan growth response to EcO157 consumption and influence of protozoan exposure on proportion of curli subpopulations.(DOCX)Click here for additional data file.


SYN1, SYN2, and SYN3) are important players in the adult brain, given their involvement in synaptic transmission and plasticity, as well as in the developing brain through roles in axon outgrowth and synaptogenesis. We and others previously reported gene expression dysregulation, both as increases and decreases, of Synapsins in mood disorders, but little is known about the regulatory mechanisms leading to these differences. Thus, we proposed to study DNA methylation at theses genes’ promoter regions, under the assumption that altered epigenetic marks at key regulatory sites would be the cause of gene expression changes and thus part of the mood disorder etiology.The Synapsins (We performed CpG methylation mapping focusing on the three genes’ predicted CpG islands using the Sequenom EpiTYPER platform. DNA extracted from post-mortem brain tissue (BA10) from individuals who had lived with bipolar disorder (BD), major depressive disorder (MDD), as well as psychiatrically healthy individuals was used. Differences in methylation across all CpGs within a CpG island and between the three diagnostic groups were assessed by 2-way mixed model analyses of variance.SYN1 or SYN3, but there was a significant group difference in SYN2 methylation, as well as an overall pattern of hypomethylation across the CpG island. Furthermore, we found a significant inverse correlation of DNA methylation with SYN2a mRNA expression.We found no significant results for SYN2, in mood disorders and improve our understanding of the regulatory mechanisms that precipitate these changes likely leading to the BD or MDD phenotype.These findings contribute to previous work showing dysregulation of Synapsins, particularly The online version of this article (doi:10.1186/s12888-016-0989-0) contains supplementary material, which is available to authorized users. SYN1), Synapsin II (SYN2), and Synapsin III (SYN3) – are interesting candidates for the etiology of mood disorders due to their involvement in the adult brain in synaptic transmission and plasticity, as well as in brain development in axon outgrowth and synaptogenesis [SYN1 gene was shown to cause familial epilepsy; and some studies have suggested an association of SYN3 with schizophrenia [Reviewed in: [Synapsin genes – Synapsin I SYN, Synapsiin II SYN, and Synin II SYN, and SynSYN3 promoter [SYN1 transcription start site hypermethylation and related mRNA downregulation in the amygdala [Though the literature provides ample evidence for genetic associations and gene expression increases of Synapsins in mood disorders, little has been done to elucidate the regulatory mechanisms that lead to these disturbances. To date there is no evidence of altered DNA methylation of these genes in mood disorders; only one study of a single schizophrenia patient suggests potentially variably methylated sites in the distal amygdala .in silico predicted islands at the proximal promoters of SYN1 (845 bp) and SYN2 (975 bp), as well as at a distal promoter of SYN3 (613 bp) [Since we previously reported Synapsins mRNA up-regulation in mood disorders , we aimewww.douglasbrainbank.ca) as described elsewhere [n = 13) or MDD (n = 18) and who died primarily by suicide. Controls were White Caucasian individuals with neither current nor past psychiatric diagnoses who died suddenly and could not have undergone resuscitation or other medical intervention (n = 14). We found no significant group differences in gender, age, brain pH or refrigeration delay  brain tissue from Brodmann Area 10 used in this study was obtained from the Douglas Bell-Canada Brain Bank  and suggestive at p ≤ 0.1 (labeled #).Differences in methylation across all CpGs within a CpG island and between the three diagnostic groups were assessed by 2-way mixed model analyses of variance (ANOVA) with groups as the fixed factor and CpG dinucleotides percent methylation level as the repeated measure, followed by Fisher Least Significant Difference (LSD) post-hoc analyses. Since there was no difference between groups in regards to potential confounders: sex, brain pH, post-mortem delay, or age  we hypothesized that altered epigenetic marks at key regulatory sites would be in part responsible for this gene expression increase and thus part of the mood disorder etiology. We chose to work with the Brodmann Area 10 (BA10) given our previous findings regarding synapsin gene expression in this region, and more importantly its role in mood regulation shown through imaging studies as well as documented deficits in PFC-mediated working memory and executive function in BD [In this study we explored the role of DNA methylation at promoter-region CpG islands mapping to the three synapsin genes: on in BD , 8, 9. TSYN1 (p = 0.718) or SYN3 (p = 0.449)  . The most interesting locus was at chr3:12046417-12046478, where three consecutive CpGs were significantly hypomethylated in MDD and their methylation levels strongly correlated across individuals . This locus is part of a binding site for EZH2 , a catalyst of mono- di- or tri-methylation of histone H3 at lysine 27 [SYN2 gene expression. Furthermore, EZH2 has been shown to also serve as a recruitment platform for DNA methyltransferases within the context of the Polycomb repressive complexes 2 and 3, and its decreased binding would lead to reduced DNA methylation [We found no significant group differences for red Fig. . We founN3 p = 0.49  and a suggestive inverse correlation with SYN2b mRNA expression . This is the expected direction, as promoter and first exon hypomethylation have been associated with increased gene expression [Previous work from our group showed significant mRNA up-regulation of the m in MDD . Further3 in MDD . Since tpression . There wpression . On the SYN1 transcription start site hypermethylation and related mRNA downregulation in the amygdala [To our knowledge, this is the first study to show evidence of altered DNA methylation at any of the Synapsin genes in mood disorders; only one recent study in rats proposed that early life stress, a precipitant of depressive behavior, leads to amygdala . It woulamygdala –17.SYN2 in mood and other psychiatric disorders [Overall our current findings contribute to previous work showing dysregulation of isorders  and imprIn this work we showed evidence of decreased promoter DNA methylation which correlated with increased expression of Synapsin genes in mood disorders. This finding is important as it contributes to our understanding of the intricacies of mood disorder dysregulation at the genetic and epigenetic level in the brain.


It has become increasingly evident that chronic inflammation underpins the development of many chronic diseases including cancer, cardiovascular disease and type 2 diabetes. Oxidative stress is inherently a biochemical dysregulation of the redox status of the intracellular environment, which under homeostatic conditions is a reducing environment, whereas inflammation is the biological response to oxidative stress in that the cell initiates the production of proteins, enzymes, and other compounds to restore homeostasis. At the center of the day-to-day biological response to oxidative stress is the Keap1/Nrf2/ARE pathway, which regulates the transcription of many antioxidant genes that preserve cellular homeostasis and detoxification genes that process and eliminate carcinogens and toxins before they can cause damage. The Keap1/Nrf2/ARE pathway plays a major role in health resilience and can be made more robust and responsive by certain dietary factors. Transient activation of Nrf2 by dietary electrophilic phytochemicals can upregulate antioxidant and chemopreventive enzymes in the absence of actual oxidative stress inducers. Priming the Keap1/Nrf2/ARE pathway by upregulating these enzymes prior to oxidative stress or xenobiotic encounter increases cellular fitness to respond more robustly to oxidative assaults without activating more intense inflammatory NFκB-mediated responses. It has become increasingly evident that chronic inflammation underpins the development of many chronic diseases including cancer, cardiovascular disease, and type 2 diabetes . Reactiv−/− mice are more sensitive to inflammatory disease -like 2), is a transcription factor in the basic leucine zipper (bZIP) superfamily with a Cap‘n’Collar (CNC) structure. Nrf2 heterodimerizes with small Maf proteins in the nucleus; this complex can then bind its cognate response element, the antioxidant response element (ARE), which upregulates the transcription of ARE-responsive genes . In. InIKBKB2H, 2+) or sulfonic  acids, the reactions are not reversible, potentially leaving Keap1 unable to revert to a protein-binding conformation [When Nrf2 is released by oxidative triggers, there is an increase in the intracellular pool of unbound Keap1 available to capture more intracellular IKKβ, thus inhibiting the expression of NFκB target genes. Alkylation of Keap1 by electrophilic phytochemicals is reversible; the electrophile is released when the oxidative environment returns to homeostasis and the Nrf2-binding conformation of Keap1 is restored. Beyond a certain threshold in the intracellular oxidation status, Nrf2 can actually promote ROS generation . In trueormation ,64. ThisThere are innumerable phytochemicals that have Nrf2 activation abilities and can interact differently with Keap1 sensor thiols. Typically, the potency of an Nrf2 activator is directly related to the speed of its reaction with Keap1 sulfhydryl moieties ,65. AlkyMost diet-derived phytochemical Nrf2 inducers are Michael acceptors or can be metabolized as such . MichaelOrganosulfides are among the most potent Nrf2 activating phytochemicals. Plants in the Brassica family  are a particularly rich source of organosulfides, primarily glucosinolates and their derivatives. However, different Brassica species present diverse phytochemical profiles. Sulforaphane was the most bioavailable glucosinolate in a broccoli-based diet, while neoglucobrassicin was the main glucosinolate in a pak choi-based diet . Both diThe most well studied phytochemical among the glucosinolates is the isothiocyanate, sulforaphane. Nine of the ten current clinical trials evaluating compounds affecting the Nrf2 pathway are focused on sulforaphane . Acute s−/− mice, indicating that Nrf2 is essential for NQO1 induction [−/− cell lines [Broccoli seed, rich in various glucosinolates and isothiocyantes, increased the activity of NQO-1 and GST in the stomach, small intestine and liver of wild type, but not Nrf2nduction . GCLC prll lines . Mice fell lines . Radish ll lines . Oral adll lines . Sulforall lines  and skinll lines , as wellll lines .In vitro, the methanolic extract of acai berry protected against oxidative stress and lipid peroxidation by increasing the GSH:GSSG ratio and overall glutamate uptake into primary rat astrocytes [Organosulfide compounds are the most extensively studied, however a wide variety of other phytochemical compounds from whole foods interact with Keap1 to similar effect. Whole grape-based diet increased cardiac GSH and GSR activity in hypertensive rats experiencing heart failure . Grape-dtrocytes .In vivo, falcarindiol acts systemically to upregulate NQO1 and HO-1 in key tissues facing detoxification challenges: liver, kidney, lung, and small intestine [Carotenoids are polyenes that lack an electrophilic moiety, however oxidized carotenoid metabolites may have the capacity to upregulate the Nrf2/ARE pathway . Lycopenntestine .Diethylnitrosamine (DEN) causes hepatocarcinogenesis in rats. Lycopene consumption offered some protection against the severity of carcinogenesis and lipid peroxidation by increasing the production of Nrf2-target enzymes  and reducing the phosphorylation of NFκB resulting in the suppression of COX-2 and other targets . PolypheEven herbs, spices and other flavor enhancers used in food preparation can contribute to Nrf2 upregulation. Hydroxytyrosol, a component of olive oil, moderately increased the expression of Nrf2, GCLC and NQO1 in a dose dependent manner and dramatically upregulated HO-1 in human retinal pigment epithelial cells . NotablyTrace minerals are elements required by the body for normal function in amounts less than approximately 100 mg/day. Trace minerals seem to have a special relationship to non-essential amino acid, cysteine, and its essential precursor, methionine. Zinc and selenium have a special role in redox biology .The human body typically contains approximately 2–3 g of zinc and has a daily turnover rate of approximately 20–30 mg . Nearly However, protein association is not the only role for zinc in intracellular redox management. It is becoming increasingly clear that “zinc signaling”  by free zinc ions (free referring to the rapidly exchanging pool and not ligand-free) may play a role in intracellular signal transduction of the cellular redox state . In factTriterpenoids are potent Nrf2 activators. Pretreatment with Nrf2 activators upregulates ARE-responsive genes, but zinc treatment alone is sufficient to upregulate Nrf2 itself and many ARE-responsive genes. Microarray analysis of both mouse and rat livers after 4-day pretreatment with oleanolic acid (a triterpenoid) showed a dramatic increase in MT, as well as Nrf2 itself, and other ARE-responsive genes  . There wde novo GSH synthesis (increased GCL mRNA) resulting in a 70% increase in GSH [Administration of zinc alone to retinal pigment epithelial cells activated the Nrf2-ARE pathway, upregulating e in GSH . In a sie in GSH . Zinc dee in GSH . Zinc dee in GSH . In rat e in GSH . In stree in GSH . In the e in GSH . GSH leve in GSH . The effe in GSH .Both sulfur and selenium are group 16 elements, which are two electrons short of a complete outer shell. Selenium can sometimes displace sulfur in cysteine residues to form selenocysteine. Selenoproteins are key in biological redox systems; selenocysteine (−488 mV) has a higher reduction potential than cysteine (−233 mV) due to its lower pKa, therefore selenol residues a more powerful reducing agents than thiols . Selenoc2O2-induced apoptosis than either compound alone [Selenium intake is a limiting factor in GPx and TrxR synthesis since they both employ selenocysteines in their active sites (SH and SeH), however selenium deficiency also upregulates the expression of other Nrf2 target genes in a compensatory manner ,125. AOMnd alone .Nrf2 has been recognized as a hormetically regulated pathway in that it reflects a biphasic dose response ,128. EleThere is an incredible diversity of electrophilic dietary phytochemicals that interact with the Keap1/Nrf2/ARE pathway. Consuming a wide variety of fresh fruits and vegetables would help to optimize the collective role of Nrf2 regulated proteins: to restore homeostasis from a state of oxidative stress and xenobiotic insult, protecting the integrity of DNA, proteins, membrane and other lipids. Adequate dietary intake of sulfur and trace minerals such as zinc and selenium provide the building blocks necessary to optimize Nrf2-mediated resilience to oxidative stress. Management of the inflammatory and oxidative homeostasis of the body through proper diet may help to slow disease progression or prevent the development of chronic disorders altogether ,130.


Accumulating evidence suggests cortical circuits may contribute to control of human locomotion. Here, noninvasive electroencephalography (EEG) recorded from able-bodied volunteers during a novel treadmill walking paradigm was used to assess neural correlates of walking. A systematic processing method, including a recently developed subspace reconstruction algorithm, reduced movement-related EEG artifact prior to independent component analysis and dipole source localization. We quantified cortical activity while participants tracked slow and fast target speeds across two treadmill conditions: an active mode that adjusted belt speed based on user movements and a passive mode reflecting a typical treadmill. Our results reveal frequency specific, multi-focal task related changes in cortical oscillations elicited by active walking. Low γ band power, localized to the prefrontal and posterior parietal cortices, was significantly increased during double support and early swing phases, critical points in the gait cycle since the active controller adjusted speed based on pelvis position and swing foot velocity. These phasic γ band synchronizations provide evidence that prefrontal and posterior parietal networks, previously implicated in visuo-spatial and somotosensory integration, are engaged to enhance lower limb control during gait. Sustained μ and β band desynchronization within sensorimotor cortex, a neural correlate for movement, was observed during walking thereby validating our methods for isolating cortical activity. Our results also demonstrate the utility of EEG recorded during locomotion for probing the multi-regional cortical networks which underpin its execution. For example, the cortical network engagement elicited by the active treadmill suggests that it may enhance neuroplasticity for more effective motor training. There is mounting evidence of cortical involvement in walking facilitated by the advancement of mobile functional neuroimaging technologies, namely functional near infrared spectroscopy (fNIRS) and electroencephalography (EEG), which have allowed for the study of brain activation during gait. fNIRS uses infrared light to assess changes in oxygenated (HbO) and deoxygenated (HbR) hemoglobin levels in the outer layers of the cortex  and equivalent dipole fitting to reveal intra-stride changes in spectral power coupled to the gait cycle in anterior cingulate, posterior parietal, and sensorimotor cortices  treadmill and walking with a typical (passive) treadmill. We hypothesized that active control would increase cortical activity and voluntary drive compared to passive treadmill walking regardless of gait speed; a result that would elucidate supraspinal networks involved in limb coordination during walking and provide impetus to include such control in treadmill based rehabilitation.Ten healthy adults  with no history of neurological disease participated in this study. The experimental protocol was approved by the institutional review board of the National Institutes of Health. All subjects gave written consent prior to study participation. While all 10 subjects completed the protocol, a technical problem during data collection resulted in unusable data from one subject; thus the data analysis was performed on data from the nine remaining subjects. Prior to the experiment, each subject was fitted with a 64-channel, wireless, active electrode EEG system  with sensors placed according to the 5% 10–20 international system  with the reference placed at the FCz electrode location. Electrode impedance was maintained below 20 kΩ. EEG data were sampled at 500 Hz. Reflective markers placed on the right and left posterior superior iliac spines (PSIS) and on the right and left feet were tracked using a Vicon MX motion capture system  at 120 Hz.Participants walked at two command speeds: slow (0.9 m/s) and fast (1.5 m/s). Prior to walking, we assessed user comfort with each speed and for one subject gait speeds were adjusted down to 0.8 and 1.4 m/s. Each participant completed a total of six walking trials on a split belt treadmill , three each in two different modes: typical (passive) and user-driven (active) walking. The passive walking mode reflected a typical treadmill: belt speed was automatically adjusted to the target speed within each block (slow or fast) so that walking speed was dictated by the treadmill setting. In the active mode a combination of feedforward and feedback controllers were implemented to allow the user to drive the speed of the treadmill. Briefly, the desired gait speed of the user was estimated from the maximum foot swing velocity in the sagittal plane  containing functions from EEGLAB v13 . ICs greater than three standard deviations from a cluster centroid were relegated to an outlier cluster and subsequently omitted from analysis.After ASR, an adaptive mixture independent component analysis (AMICA)  for each epoch with a multitaper fast Fourier transform with discrete prolate sequences using the “pmtm” command in Matlab. The PSD was then averaged across all epochs for each IC for a given experimental condition. Cluster grand mean PSDs were computed by averaging across the ICs within each one. A within subjects, repeated measures Two-Way ANOVA with Bonferroni correction for multiple comparisons was used to assess significant effects of speed  and treadmill type  on area under the PSD curve of each cluster across five frequency bands of interest: Δ (1–4 Hz), θ (4–8 Hz), α/μ (8–13 Hz), β (14–30 Hz), and low γ (30–50 Hz). Shapiro-Wilk tests of normality on studentized residuals verified that PSD data within all bands and clusters were normally distributed.Each IC was then split into 2.2 s epochs surrounding the right heel-strike (RHS), starting from 200 ms before each RHS. Each epoch was labeled according to its corresponding walking command: slow, fast, slow-to-fast transition (acceleration), or fast-to-slow transition (deceleration) and treadmill type: passive or active. Transitions were identified as the six gait cycles—three before and three after—surrounding the change in command speed, a number that assured all subjects had reached steady state based on p < 0.05) were identified using a bootstrapping technique within EEGLAB  of each epoch was computed using a fast Fourier transform with a Hanning window taper. Within each cluster, single epoch spectrograms from each IC were linearly time-warped so that gait events (heel-strikes and toe-offs) occurred at the same median latency  condition. The mean baseline condition was then subtracted from the four walking conditions. Finally, these mean baseline subtracted spectrograms were averaged across all ICs in a cluster for each experimental condition. To ascertain significant differences between active and passive treadmill we transformed the time-frequency values to decibels (dB) and statistically compared spectrograms using a non-parametric bootstrapping technique with random shuffling  = 61.0; p < 0.01] for active compared to passive treadmill walking  = 19.4; p = 0.01] with less power for active compared to passive walking and one in the prefrontal (PF) region for speed  with increased power for fast compared to slow walking. The only significance for γ band PSD was a main effect for treadmill type in the PP cluster  with power increased for active compared to passive mode. There were no significant interactions or main effects on PSD for treadmill type or speed for the anterior cingulate (AC) or left premotor (LPM) regions in any frequency band.There was a significant interaction effect between speed and treadmill conditions on μ band PSD in the left motor (LM), right motor (RM), and posterior parietal (PP) cortex Table . Post-hoP Figure , Table 2sed [F1,  = 61.0; Amplitude modulations relative to the mean gait cycle activity were present in the μ and lower β band of LM, RM, and PP clusters with similar temporal patterns Figures . ERSPs sThe time-frequency analysis showed changes in spectral power at multiple frequency bands during steady walking compared to quiet standing Figure . We obseWe computed difference spectrograms between active and passive walking for both slow and fast speeds Figure . The difWe observed significantly less power—as indicated by area under the PSD curve Figure  and sustParticipants were asked to track slow and fast target speeds in both passive and active walking modes; in the passive mode, treadmill belt speed was externally set and maintained at the specified target speed, making the tracking task trivial. In active mode, intentional changes in the swing foot velocity and pelvis position of the participant caused the belt speed to react in real time, resulting in a more challenging tracking task. Data analysis focused only on periods of steady state tracking at slow and fast speeds. Our behavioral data reflect the difficulty disparity between treadmill modes as we observed more step-to-step variability in belt speed during active walking for both speeds Figure . HoweverPrevious work  which lowered the statistical power of tests on the mean PSD of each cluster due to the multiple comparison correction. The mean PSD collapses the time dimension to capture broad oscillatory changes between walking conditions. To limit the number of statistical comparisons, we chose to segment the PSD into broad frequency ranges at the risk of eliminating differences that may have been identified if smaller frequency bins had been employed. Future studies with more trials can empower more detailed analysis of frequency band specific power changes during walking. Yet, the emergence of μ and β band ERD for active relative to passive and for fast relative to slow walking in the motor and parietal cortices reflects enhanced activity during these tasks, an important result as it pertains to rehabilitation because activation of these motor areas plays a key role in neural plasticity for motor learning (Dayan and Cohen, Caution should be exercised when interpreting the location of the dipoles obtained from the finite element model which has been shown to have median errors of 5–8 mm (Akalin Acar and Makeig, We employed a systematic pre-processing strategy to isolate true electrocortical signals from artifact including, to the best of our knowledge, the first application of ASR (Mullen et al., While previous work has examined cortical activity during typical treadmill walking or walking in a robotic assisted gait training device, this study utilized a novel experimental paradigm to differentiate neural contributions to precision speed control during simulated overground walking. We observed significant task related differences in cortical activation patterns between active and passive treadmill walking across multiple regions. Specifically, μ and β band desynchronization was enhanced in the sensorimotor areas indicating increased cortical involvement in the active walking task. Phasic γ band synchronization was observed in the prefrontal and posterior parietal areas during simulated overground walking, providing evidence for γ band oscillations in control of bipedal locomotion. Prefrontal synchronizations were enhanced for the fast speed, suggesting executive control of sensorimotor areas is elevated to improve speed tracking performance. It is important to note that engagement of these cortical structures do not, in and of themselves, provide evidence for neuroplasticity or the efficacy of this active treadmill training approach. Careful assessment of functional outcomes via randomized controlled trials comparing these two different types of treadmill control is necessary to correlate these alterations in brain activity with improved therapeutic benefits. Such studies are planned in the future. Additionally, our results demonstrate the feasibility and sensitivity of non-invasive EEG for monitoring brain activity during gait, supporting its future role as a clinical tool for rehabilitation paradigm development and assessment.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Dear Editor,Drosophila, with easy accessibility to genetic, molecular, and behavioral analyses, was also employed in olfactory learning studies and many key genes underlying memory formation were identified in these studies , DCO , and AKAP Yu   insertion  Fig. A. Westersvr1021 in different time points after training. Memory of the svr mutant (svr1021) exhibited a significant impairment at both 3 min and 3 h after one-cycle training  had normal 3 min memory, such memory was impaired in double-heterozygote mutant (svr1021/svrKG02090) , but not at the restrictive temperature (30°C). The gene svr contains three carboxypeptidase domains, and has five endogenous transcriptional forms as a result of alternative splicing  effectively rescued the perturbed memory in svr mutant to a comparable level in the control group   and svr mutant group (svr1021/Y) was detected in un-induced conditions  rescued the memory deficiency in svr mutant , was not able to generate similar rescuing effect , which have analogous functions to insulin  in Drosophila. Carboxypeptidases and endopeptidases can turn precursors into peptides  system is similar to its human counterpart. It comprises a single insulin receptor (InR) that mediates the function of all eight insulin-like peptides (ILPs), from dilp1 to dilp8  partially rescued the memory impairment in svr mutant Below is the link to the electronic supplementary material.


Breast, lung, and pancreatic cancers collectively represent one third of all diagnosed tumors and are responsible for almost 40% of overall cancer mortality. Despite improvements in current treatments, efforts to develop more specific therapeutic options are warranted. Here we identify matrix metalloproteinase 3 (MMP3) as a potential target within all three of these tumor types. MMP3 has previously been shown to induce expression of Rac1b, a tumorigenic splice isoform of Rac1. In this study we find that MMP3 and Rac1b proteins are both strongly expressed by the tumor cells of all three tumor types and that expression of MMP3 protein is prognostic of poor survival in pancreatic cancer patients. We also find that MMP3 gene expression can serve as a prognostic marker for patient survival in breast and lung cancer. These results suggest an oncogenic MMP3-Rac1b signaling axis as a driver of tumor progression in three common poor prognosis tumor types, further suggesting that new therapies to target these pathways could have substantial therapeutic benefit. Lung cancer is the leading cause of death for both sexes with a 221,000 new cases and 158,000 deaths estimated for 2015 in the US  and imprInvestigations of the processes involved in cancer development and tumor metastasis have identified matrix metalloproteinases (MMPs) as key factors involved in the development of the tumor microenvironment and as drivers of cancer progression and metastasis –10. ThesMMPs are a family of 24 enzymes, some members of which are easier to detect by zymography methods and have been studied more extensively in the context of cancer progression and metastasis, while other members of the MMP family are more difficult to visualize. MMP3, classified as a stromelysin for its ability to cleave a variety of extracellular matrix protein substrates, is an example of an MMP family member that is more challenging to detect, and consequently has not been as widely studied as a potential biomarker for cancer prognosis as many other MMPs. While many studies using cultured cells or animal models have implicated MMP3 as a functional contributor to lung, breast, and pancreatic premalignancy and cancer –23, muchIn this study, we evaluate the stromal and epithelial cell expression of MMP3 in lung, breast, and pancreatic cancer. We extend our findings from a previously described tissue microarray study consisting of patients with pancreatic adenocarcinoma , and intPancreatic adenocarcinoma tissue microarrays (TMAs) were stained for MMP3, Rac1b Patient breast and lung cancer tissue biospecimens revealed epithelial staining patterns for MMP3 Figure , similarWe used the KM Plotter web utility (25) to analyze gene expression in breast cancer patients using endpoints of overall survival (OS), finding that patients with increased MMP3 did not show significantly different outcome  and genomic instability , 26. UsiOne unexpected finding of our study is the localization of MMP3 primarily to tumor cells; this is somewhat surprising since MMPs have been generally believed to derive mainly from the tumor stroma , where tOur identification of an oncogenic MMP3-Rac1b signaling axis as a driver of tumor growth and progression of multiple common poor prognosis cancers suggests that new therapies to target this pathway may hold substantial clinical promise. Direct targeting of Rac1b is anticipated to be challenging, since like other small GTPases , 61, itsAs the extracellular initiator of the oncogenic pathway, MMP3 may offer an even more tractable molecular target for drug development. While early oncology trials of nonselective small molecule MMP inhibitors proved disappointing –13, it iIf drugs can be developed to intervene in the oncogenic MMP3-Rac1b signaling axis, a parallel challenge will be to identify the patients most likely to respond to this therapeutic strategy. The present study suggests that some cancer subtypes may be more responsive than others, since, for example, MMP3 expression was significantly prognostic of outcome in lung adenocarcinoma but not in squamous cell carcinoma; further studies to validate our observations in additional clinical cohorts of breast, lung, and pancreatic cancers are warranted. Ultimately, implementation of a therapeutic strategy to intervene in the MMP3-Rac1b signaling axis may be best guided using companion biomarkers. Our studies to date of a large cohort of pancreatic cancer patients suggest that MMP3 staining may be useful as a prognostic tissue biomarker, and might be anticipated to predict response to therapies targeting this axis.Pancreatic adenocarcinoma formalin-fixed, paraffin-embedded (FFPE) tissue samples mounted as a tissue microarray (TMA) were obtained through the Mayo Clinic Pancreas Cancer SPORE. Each TMA slide contains up to 432 cores representing each patient with three spots (n=140) and 12 process controls. TMA slides were stained for human MMP3 , human Rac1b , and human Collagen-I . TMAs were deparaffinized and rehydrated in graded alcohol into water. Antigen retrieval was done in citrate buffer pH 6.0 for 25min at 100C. Followed by 3% H2O2 treatment for 5min and serum free protein block for 5min. Slides were then stained for 1 h at room temperature with the respective antibodies. Followed by 30 min with secondary anti-rabbit labeled polymer/horse radish peroxidase conjugate (Dako #K4003) and then color was developed for 5min using 3,3′-diaminobenzidine . Slides were counterstained with hemotoxin. The stained slides were analyzed using Image Scope Software application TMA-lab  with a color deconvolution. The stained slides were analyzed using Image Scope Software application TMA-lab  with a color deconvolution algorithm that generates an H-score  to allow non-biased interpretation of intensity and positivity of patient samples (score is acquired as follows: 1.0x(%weak positive)+2.0x(%median positive)+3.0x(%strong positive)). This scoring method has been widely used to objectively quantify receptor expression and different stains in lung, ovarian and prostate cancers . Spot scAdditional breast cancer and lung cancer human tissue samples were provided by Mayo Clinic Jacksonville Department of Cancer Biology histology and stained for human MMP3, human Rac1b, and human Collagen-I. The slides were subsequently analyzed for tumor and stroma staining and staining patterns for the individual markers were determined.Average patient expression level was calculated by taking the mean of the multiple core level H-scores for an individual. Overall survival was compared across quartiles of mean patient expression level using Kaplan-Meier methods and log-rank tests. A post-hoc analysis combining quartiles 1-3 compared to quartile 4 was considered to explore differences in survival for the subset of patients with the highest mean expression. Cox Proportional Hazards regression models were utilized to estimate Hazard Ratios and 95% Confidence Intervals. Statistical analysis related to the TMA scoring and relevant patient characteristics was performed using SAS/STAT software, version 9.2 of the SAS System for UNIX.http://www.kmplot.com; [The Kaplan-Meier Plotter results were obtained using the current release of Kaplan Meier Plotter  using t


Stat5ab in the liver as well Junb deletion in a T-cell lymphoma model. We quantified the expression of total or activated STAT5AB or JUNB protein in normal (+/+ or JunB+/+Stat5ab), hemizygous (+/ΔStat5ab or +/ΔJunB) or knockout (Δ/ΔStat5ab or Δ/ΔJunB) settings. Image analysis was able to accurately detect hemizygosity at the protein level. Moreover, nuclear signals were distinguished from cytoplasmic expression and translocation of the transcription factors from the cytoplasm to the nucleus was reliably detected and quantified using image analysis. We demonstrate that image analysis supported pathologists to score nuclear STAT5AB expression levels in immunohistologically stained human hepatocellular patient samples and decreased inter-observer variability.In targeted therapy, patient tumors are analyzed for aberrant activations of core cancer pathways, monitored based on biomarker expression, to ensure efficient treatment. Thus, diagnosis and therapeutic decisions are often based on the status of biomarkers determined by immunohistochemistry in combination with other clinical parameters. Standard evaluation of cancer specimen by immunohistochemistry is frequently impeded by its dependence on subjective interpretation, showing considerable intra- and inter-observer variability. To make treatment decisions more reliable, automated image analysis is an attractive possibility to reproducibly quantify biomarker expression in patient tissue samples. We tested whether image analysis could detect subtle differences in protein expression levels. Gene dosage effects generate well-graded expression patterns for most gene-products, which vary by a factor of two between wildtype and haploinsufficient cells lacking one allele. We used conditional mouse models with deletion of the transcription factors  Cancer genome studies revealed insights into molecular pathways, which are driving events for cancer development and progression. Targeting key signaling molecules, which define core cancer pathways, are a central theme in the modern cancer treatment. Some of these drugs are of great success; for example the kinase inhibitor imatinib, which blocks BCR-ABL tyrosine kinase activity in chronic myelogenous leukemia (CML) Targeted treatments become increasingly expensive and thus, correct biomarker quantification is also a critical economic factor. Computer assisted image analysis of IHC stained specimens AMY1) number, which can vary between populations due to copy number differences, is correlated linearly with Amylase protein amount Kip1+/−p27 mice were compared to their wildtype counterparts Gene dosage, either by the presence of one or two alleles or variation in gene copy number generally affects the corresponding protein levels. For example the human salivary amylase gene (Stat5ab) as well as JunB hemizygosity in different conditional knockout models translate to 50% of the corresponding protein levels as determined by Western blotting. This confirmed the results obtained from automatic quantitative assessment of STAT5AB and JUNB protein in IHC-stained paraffin embedded sections of the affected mouse tissues. Second, we demonstrate that image analysis can reliably distinguish cancer cells from the tumor stroma and allows individual analysis. Third, we had to rule out that detection and quantification of a nuclear signal e.g. a transcription factor (such as active STAT5 or STAT3) was not altered by the presence of the molecule in the cytoplasm. We used STAT5AB nuclear translocation upon activation in the mouse liver for verification. Fourth, we show that the inter-observer variability judging nuclear STAT5AB of human hepatocellular carcinoma (HCC) patient samples significantly decreased with the support of quantitative image analysis information. Therefore we conclude that image analysis will improve accuracy and reproducibility to score expression levels in immunohistologically stained patient samples.We tested quantitative image analysis tools and evaluated genetically engineered mouse models, which display well-defined and controlled differences of a specific protein levels associated with gene copy number. First, we demonstrate that signal transducer and activator of transcription 5ab  included the minimal CD4 enhancer, the minimal murine CD4 promoter, the transcription initiation site, part of the untranslated first exon and part of the first intron of the murine CD4 gene but lacked the CD8 silencer. JunB conditional knockouts in T-cells of NPM-ALK transgenic animals were obtained by crossing the NPM-ALK transgenes with mice carrying a floxed allele of JunB (f/fJunB) +/+JunB, NPM-ALK/+/ΔJunB and NPM-ALK/Δ/ΔJunB. Hepatocyte-specific Stat5ab hemizygous and homozygous knockout mice (+/ΔStat5ab and Δ/ΔStat5ab) were generated by crossing conditional Stat5ab mice to Alfp-Cre transgenic mice NPM-ALK transgenic mice were obtained from the lab of Prof. Inghirami Tyr705), STAT5AB and phospho-tyrosine 694 -STAT5AB (p-STAT5ABTyr694) stainings the sections were incubated at 56°C for 2 hours and rehydrated. Steamer pretreatment (95°C for 1 hour) in Tris/EDTA buffer  and cooling was done to retrieve antigens for JUNB, p-STAT3 Tyr705 and p-STAT5ABTyr694 stainings. For total STAT5AB antigen retrieval an autoclave pretreatment in citrate buffer  was performed. The endogenous peroxidase activity was quenched by incubation of the sections in 3% hydrogen peroxide in PBS for 10 minutes. After washing in PBS an avidin and biotin blocking  was performed done for 10 minutes. Rabbit polyclonal JUNB  antibody, rabbit monoclonal p-STAT3Tyr705 , rabbit polyclonal STAT5AB  antibody and rabbit monoclonal p-STAT5ABTyr694  antibody were used and incubated at 4°C overnight. Afterwards, the slides were washed in PBS and the signal was detected with the IDetect Super Stain System . Signal was amplified using 3-Amino-9-Ethylcarbazole  under visual control. Formalin fixed and paraffin embedded (FFPE) HCC patient samples were stained for STAT5AB as described above for the mouse samples.Mouse tissues from the above mentioned mice were fixed in 4% paraformaldehyde, embedded in paraffin and 5 µm sections were prepared. The sections of different genotypes were processed on same slides to warrant exactly the same treatment and incubation times. AEC color development was terminated as early as distinct signals were detected on the wildtype sections. For JUNB, phospho-tyrosine 705 -STAT3  provides tools to quantify protein expression levels on immunohistochemically (HistoQuest) stained tissue slides or cell preparations. The software programs are based on single cell detection by identification of nuclear structures For analysis with the HistoQuest software, hematoxylin staining was used as a master marker for cell identification on the basis of nuclear detection. Furthermore, the average nuclear size, discrimination area, discrimination gray and background threshold for the master marker was specified. The range of intensities of the master marker (hematoxylin) and the immunohistochemical stainings  were set by autodetection of the software. Regions of interest (ROIs) were defined as indicated, which were analyzed and quantified separately from the surrounding stromal areas. The general setups were done on a representative image. All images were analyzed with the same settings after adjustments. Forward and backward gating was routinely used for quality control of measurements. By clicking on high or low AEC staining intensity cells in the image, the forward gating tool shows the individual staining intensities of selected cells in the scattergram. Backward gating was used to verify data by visual inspection on the original image. The results are visualized in dot plot scattergrams and/or histograms. Cut-offs (to differentiate between positive and negative cells) and gates (to accentuate between cell populations) were set in the dot blots. For statistical analysis the raw data of the analysis were imported into GraphPad Prism, analyzed for significance and processed for data output as whisker box blots. All photomicrographs were taken with same settings . The images of the IHC photomicrographs were taken with a Zeiss Imager Z1 microscope.+/+Stat5ab, +/ΔStat5ab and Δ/ΔStat5ab mice were injected intraperitoneally with 2 mg/kg recombinant human GH  or with saline and sacrificed 30 min thereafter. For subsequent Western blot and immunohistochemical analysis liver tissues were immediately snap-frozen in liquid nitrogen or fixed in 4% phosphate-buffered formalin  for 48 hrs followed by embedding into paraffin using standard procedures as described For the analysis of growth hormone (GH)-dependent activation of STAT3 and STAT5AB in Tyr705 , p-STAT5Tyr694  and STAT5B  were subjected to sodium dodecyl sulphate-polyacrylamide electrophoresis (SDS-PAGE) and then transferred to a nitrocellulose membrane, and blocked in TBS-T/5% BSA for one hour. Blots were incubated with antibodies against JUNB , p-STAT3Stat5ab+/+Stat5ab), hemizygous (+/ΔStat5ab) and homozygous (Δ/ΔStat5ab) mice by Western blotting. , JunB hemizygous (NPM-ALK/+/ΔJunB) and lacked JunB completely (NPM-ALK/Δ/ΔJunB). JUNB is heterogeneously expressed in tissues due to cell cycle fluctuations of the protein level JunB gene dosage was directly translated into different protein levels by Western blot analysis . Due to the cell cycle dependent regulation of JUNB expression, the staining intensity varied between different cells of the same tumors from high to low expression levels to complete absence. Automated image analysis with the HistoQuest software revealed the quantitative differences in JUNB protein expression  driven T-cell lymphomas Tyr705 in the mouse liver model. The amount of phosphorylated STAT proteins is indicative for their transcriptional activity. STAT5AB phosphorylation in hepatocytes can be achieved by growth hormone administration in mice. As demonstrated earlier, hepatic STAT5AB is heavily phosphorylated upon GH treatment in +/+Stat5ab mice, whereas the p-STAT5ABTyr694 signal is absent in untreated mice as well as in GH induced Δ/ΔStat5ab mice +/ΔStat5ab hepatocytes displayed the same level of STAT5AB phosphorylation indicative for the full STAT5AB signaling capacity of hepatocytes containing only half the amount of STAT5AB  STAT5AB and STAT3 STAT5AB . IHC anan nuclei . Unspeciuisition . Importalot data . As alreoccurred . SurprisTaken together we provide a proof of concept study that STAT5AB and STAT3 activity, which can be assessed by the levels of tyrosine phosphorylated protein, can reliably be quantified in FFPE tissue sections using cell based image analysis software.+/+Stat5ab and +/ΔStat5ab mouse livers as evident by visual inspection whereas the cytoplasmic levels decreased  depends on their nuclear localization. Therefore, a proper distinction of nuclear versus cytoplasmic antigen expression is a prerequisite for consistent image analysis and quantification with a specific attribution to the respective cell type that is to be quantified. To test this, we used the GH induction of STAT5AB phosphorylation in the mouse liver, which is accompanied by a translocation of STAT5AB into the nucleus. Nuclear STAT5AB increased in GH treated ecreased . After aecreased , right. ecreased .Δ/ΔStat5ab liver cells a cut-off was defined , which uses color separation, as well as cell nuclear recognition algorithms (nuclear segmentation based on hematoxylin staining) to measure IHC staining intensities horseradish peroxidase or alkaline phosphatase based detection using e.g. AEC, 3,3′-diaminobenzidine as chromogenic substrates) in individual cells in the sections. We asked, whether this system is powerful enough to exactly quantify minor expression differences in tissue sections. It is of importance to notice that the tissue specimens were fixed for the same time period, arranged in the same block, cut, stained and analyzed on the same slides, in order to avoid differences in section thickness and staining time. This setup might be of relevance for the acquisition of quantitative data in clinical samples albeit it is difficult to achieve in routine diagnostics. To circumvent the drawbacks of individual preparation and staining of tissue samples, we suggest using an internal control standard, embedded next to the patient sample in the paraffin block to obtain an inter-sample reference for normalization or to use custom made tissue microarrays (TMA) of the samples to be compared.Stat5ab and JunB or the corresponding hemizygous alleles. Full knockouts of these genes were used as negative expression controls. The models offered exact and stable differences of protein expression resulting in relative expression levels of 2, 1 and 0 in vivo. The calculated ratio was indeed observed in the analyzed tissue samples, as indicated by the median staining intensities of STAT5AB and JUNB obtained from the automated image analysis. Since the measured expression levels were so close to the theoretical values and the overall protein levels as determined by Western blotting in the test system, we were confident to detect relative subtle differences in expression. The consequence of haploinsufficiency, accompanied by the reduction of protein levels due to loss of one allele, has been underscored in tumor suppressor studies KIP1+/−p27 animals the targeted protein was present at exactly half the expression level of wildtype mice as determined by Western blot analysis To obtain defined differences we made use of gene-dosage effects in two independent genetic mouse models, harboring either wildtype Stat5ab mice, was detected in the cytoplasm as well as in the nucleus of mock versus GH treated mice. However, arguably tumor cells might be very different and variable regarding their morphology. This might complicate the use of an automated system. In this respect we are confident that a major advantage of the image analysis used in this study is the segmentation of cells based on nuclear hematoxylin staining. The size and form of a nucleus can be measured and helps to distinguish different cell types within a tissue . This feature of nuclear recognition might also be exploited to detect and sub-select cell types of same origin but different morphology.In comparison to global analysis of protein expression in tissues by Western blotting, IHC of tissue sections provide major supplemental information. First, one can obtain the distribution of expression in different cell types of the tissue and the spatial variation of expression in a certain cell type. We clearly demonstrated that our approach could distinguish stroma from parenchyma and could provide quantification data of selected tissue substructures. This ensures a more reliable comparison between physiologic or therapeutic states, since the amount of stromal cells can often vary. Second, it is possible to analyze the intracellular localization of protein expression. Image analysis was able to distinguish nuclear versus cytoplasmic expression, calculate mean expression in the two compartments and cytoplasmic to nuclear translocation was also quantifiable. Convincingly, even the 2∶1.0 gene dosage ratio in the genetically different in vivo we proved that tyrosine phosphorylation of STAT3 and STAT5AB is consistently quantified in IHC-stained mouse liver tissue by the image analysis system. The result of p-STAT3Tyr705 activation upon GH injection of hepatic STAT5AB heterozygous or knockout mice is in line with an important tumor suppressor role of STAT5AB to prevent liver cancer development. STAT5AB protein levels are essential to saturate GH receptor binding sites to prevent mis-activation of p-STAT3Tyr705 by janus kinase 2 (JAK2) in a GH-induced way.The reliable detection and quantitative analysis of phospho-protein levels in biopsies is essential to identify malfunction of core cellular pathways in cancer In a pilot study analyzing 22 human hepatocellular carcinoma samples we show that the inter-rater variation in scoring nuclear STAT5AB significantly decreased with the aid of quantitative image analysis information. These results clearly demonstrated that the software–supported histopathological evaluation was beneficial for a more robust and comparable scoring. Detection of nuclear STAT5AB in cellular subpopulations is useful in predicting human liver cancer progression and drug treatment efficacy in the patients as previously demonstrated In the future the ultimate goal of automated analysis of IHC slides should facilitate large-scale, high throughput applications including prognostic marker validation, identification of novel targets and evaluation of targeted treatment efficacy. In general, we need to be aware of the fact that in human disease a lack of quantifiable internal control standards for IHC normalization makes all IHC stainings only to be semiquantitative and a well-trained pathologist is essential for proper diagnosis, since many aspects of histopathology cannot be recognized by a software tool. As we have demonstrated, automated image analysis can detect changes in protein expression in a reproducible manner, however, sometimes the area of expression is more important than the overall expression level. For instance, expression of certain factors at the invasion front of a certain tumor might have more impact than expression in the middle of the same tumor. This is another reason why evaluation by a pathologist is undispensable. However, we want to point out that small staining differences can be made more quantitative and help to reduce inter-pathologist/experimentator interpretation. Of note, we would also like to point out that these image analysis tools might help to better interpret animal experiments for non-pathologists in a preclinical setup.File S1(PDF)Click here for additional data file.