South Korea has the lowest fertility rate in the world despite considerable governmental efforts to boost it. Increasing the fertility rate and achieving the desired outcomes of any implemented policies requires reliable data on the ongoing trends in fertility and preparations for the future based on these trends.The aims of this study were to (1) develop a determinants-of-fertility ontology with terminology for collecting and analyzing social media data; (2) determine the description logics, content coverage, and structural and representational layers of the ontology; and (3) use the ontology to detect future signals of fertility issues.An ontology was developed using the Ontology Development 101 methodology. The domain and scope of the ontology were defined by compiling a list of competency questions. The terms were collected from Korean government reports, Korea’s Basic Plan for Low Fertility and Aging Society, a national survey about marriage and childbirth, and social media postings on fertility issues. The classes and their hierarchy were defined using a top-down approach based on an ecological model. The internal structure of classes was defined using the entity-attribute-value model. The description logics of the ontology were evaluated using Protégé (version 5.5.0), and the content coverage was evaluated by comparing concepts extracted from social media posts with the list of ontology classes. The structural and representational layers of the ontology were evaluated by experts. Social media data were collected from 183 online channels between January 1, 2011, and June 30, 2015. To detect future signals of fertility issues, 2 classes of the ontology, the socioeconomic and cultural environment, and public policy, were identified as keywords. A keyword issue map was constructed, and the defined keywords were mapped to identify future signals. R software (version 3.5.2) was used to mine for future signals.A determinants-of-fertility ontology comprised 236 classes and terminology comprised 1464 synonyms of the 236 classes. Concept classes in the ontology were found to be coherently and consistently defined. The ontology included more than 90% of the concepts that appeared in social media posts on fertility policies. Average scores for all of the criteria for structural and representations layers exceeded 4 on a 5-point scale. Violence and abuse  and flexible working arrangement (fertility policy) were weak signals, suggesting that they could increase rapidly in the future.The determinants-of-fertility ontology developed in this study can be used as a framework for collecting and analyzing social media data on fertility issues and detecting future signals of fertility issues. The future signals identified in this study will be useful for policy makers who are developing policy responses to low fertility. South Korea has the lowest fertility rate in the world. According to the Organization for Economic Cooperation and Development (OECD), the total fertility rate (TFR) in South Korea peaked in 1970 at 4.53 and subsequently declined to 1.30 in 2001 [In an attempt to increase the TFR, in 2005 the Korean government enacted the Basic Law on Low Fertility and Aging Society, and the Ministry of Health and Welfare in collaboration with other government agencies established 5-year plans. The First Basic Plan for Low Fertility and Aging Society 2006-2010) was initiated to establish a foundation for the government from which to proactively respond to the low fertility and aging population. The second and third of these plans (2011-2020) were pursued with the aim of increasing the TFR and successfully responding to the increasingly aging society -5. Howev-2010 wasGovernments around the world are increasingly seeking ways to detect future signals of policy implications so they can respond to the various challenges that countries face in a timely and effectively manner . GovernmOne approach to predicting future signals is to harness intuitive judgment by experts; however, this is both time-consuming and costly ,12. SincSocial media data are written in various forms and are both unstructured and noisy . AnalyziAn ontology expresses shared concepts and their relationships in a specific domain , and it This study aimed to (1) develop an ontology with terminology for collecting and analyzing social media data on the determinants of fertility, (2) determine the description logics (DL), content coverage, and structural and representational layers of the ontology, and (3) use the ontology with terminology to detect future signals of fertility issues in social data posted in Korean.An ontology for describing the determinants of fertility, called the determinants-of-fertility ontology, was developed based on the Ontology Development 101 methodology  in 5 steThe aim of the determinants-of-fertility ontology developed in this study was to analyze social media data posted by consumers, not by health care professionals. Thus, we limited the scope of the ontology to the individual, social, economic, cultural, and policy factors of fertility in the domain of the consumer. The physiological, clinical, and therapeutic factors of fertility in the domain of health care professionals were excluded. The specific domain and scope of this ontology was determined by creating competency questions (CQs) that the ontology must be able to answer . Since fWe identified existing ontologies and conceptual frameworks representing fertility by searching PubMed, Google Scholar, and BioPortal  using thWe extracted terms from the literature that were consistent with the domain and scope of the ontology. The literature reviewed included reports on fertility, determinants of fertility, low fertility, and policy responses to low fertility published by the OECD , United The classes of the ontology and their hierarchy were defined using a top-down approach. The superclasses of the ontology and their relationships were constructed by integrating an ecological model .The internal structure of the ontology classes was defined by adding the properties of the classes, the value of the properties, and the value type using the entity-attribute-value (EAV) model. Entities refer to the concepts covered in the determinants of fertility, attributes are characteristics of entities, and value sets comprise the set of values that an attribute can have. Attributes and values were extracted from the questionnaires of the Korean National Survey on Dynamics of Marriage and Fertility  and the The available methods for evaluating the quality of an ontology include those proposed by Brank et al , Obrst ehasIndividual relationship, and subclasses  of the individual were related to the individual class through an is-a relationship, we could obtain the result of a DL query.We tested the DL of the ontology by applying the ontology debugger Protégé plug-in. We also tested the DL using the DL-reasoner Protégé plug-in to determine whether the ontology generates the correct answers to the previously developed CQs. For example, the CQ “What are the personal factors that influence a women’s decision to have a child?” was converted to a DL query “IsIndividualOf some Determinants_of_fertility.” After entering this query into Protégé, we tested whether the answers to the CQ were correct. Since the determinant of the fertility class (domain) was related to the subclasses of individual (range) through the The content coverage of the ontology was examined by comparing terms extracted from the bulletin board of the Korean Ministry of Health and Welfare with a list of classes and synonyms of the ontology. Both the general public and public servants are allowed to post their opinions or concerns on fertility issues and policies regarding low fertility on this bulletin board. In total, 1387 documents posted on the website by the general public and 63 posted by public servants were collected. Relevant terms in the documents were extracted using the Korean Natural Language Processing package in R software . Unique concepts were extracted based on the meaning of the terms and then mapped onto the ontology classes. The mapping results were reviewed by 3 experts in health informatics who had experience in ontology development . Any newThe structural and representational layers of the ontology were evaluated by 3 experts in health informatics who had previous experience in ontology design and 2 experts in maternity nursing who had previous experience in ontology evaluation. The evaluation tool developed by Jung et al  was usedThe ontology with terminology was used to detect future signals of fertility issues from social media data. Future signals were analyzed based on the text-mining–based weak-signal detection method of Yoon , as follWe collected posts on fertility issues written in Korean from the following 183 online channels between January 1, 2011, and June 30, 2015: 159 channels of online news, 17 message boards, 1 social networking service (Twitter), 4 internet blogs, and 2 online community services. “Low fertility” was used as a major search keyword, together with synonyms of “fertility rate decline,” “sharp decline in fertility rate,” “avoiding childbirth,” “no kids,” and “childless family.” Social media data were collected using the SK telecom’s big-data analytics platform . The datAfter extracting terms from each document, we identified the terms related to fertility issues such as socioeconomic and cultural factors and fertility policies. The future signals of fertility issues were detected using the keywords representing socioeconomic and cultural factors and fertility policies. The keywords that were semantically similar but expressed using different terms  were groSocioeconomic and cultural factors:Population agingEconomic problemsNuclearization of the familyChanging perspectives about marriageConservative valuesViolence and abuseEmployment problemsGender inequalityFertility policies:Financial support for childbirthChild-safety protection systemInfrastructure for childcare supportMaternity-leave systemPolicy public relationsFinancial support for employment securityFlexible working arrangementFamily-friendly work environmentSmart work centerFuture signals  show abnormal patterns due to current oddities . Future The DoD is the growth rate of the term occurrence expressed as a time-weighted coefficient and is also important for detecting future signals. The DoD represents how the diffusion of a term across different documents varies over time. Since the recent appearance of a term is more important than its past appearance, the DoD puts more weight on recent occurrences:ij is the DF of keyword i during period j, NNj is the total number of documents identified for period j, n is the number of periods, and tw is a time weight .The KIM was generated by plotting the average DF on the x-axis and the average growth rate of the DoD on the y-axis. The quadrants of the plot were divided by the medians of the respective values, and so each quadrant of the KIM represented different information about present and future keywords.Future signals were identified according to where keywords were located in the quadrants of the KIM. Keywords in the first quadrant, which represent strong signals, have a trend toward a high average DF and a high average DoD growth rate. Keywords in the second quadrant, which represent weak signals, have a low average DF but a high average DoD growth rate, and so they may increase rapidly in the future. Keywords in the third quadrant, which represent latent signals, have a low average DF and a low average DoD growth rate and are not yet significantly noticeable. Keywords in the fourth quadrant, which represent not-strong-but-well-known signals, have a high average DF but a low average DoD growth rate, and so currently exhibit a slow growth rate.A list of 10 CQs was compiled  that refWhat are the personal factors that influence a woman’s decision to have a child?What are the family factors that influence the decision to have a child?What are the childcare factors that influence the decision to have a child?What are the educational factors that influence the decision to have a child?What are the workplace factors that influence the decision to have a child?What are the sociocultural factors that influence the decision to have a child?What are the economic factors that influence the decision to have a child?What is the Korean government’s policy for overcoming low fertility?What are the policy tasks for addressing low fertility in South Korea?What are the policy targets for low fertility in South Korea?In total, 1659 terms covering the domain and scope of the ontology were collected, and 236 unique class concepts were extracted from these terms. We defined hierarchical and attribute relationships of the classes based on the ecological model. The determinants of fertility were organized into the following levels: individual, family, workplace, childcare and educational environment, socioeconomic and cultural environment, and public policy. These 6 levels of the ontology were defined by adding not only the workplace, but also childcare and educational environment to institutional factors, which constitute the third level of the ecological model. Due to the increasing participation of women in the labor market, the workplace and childcare and educational environment are important factors influencing decisions about childbirth among women who are working ,32,42,43contraceptive use had attributes of hasType and hasLengthOfUse, where the values of the hasType attribute were condoms, contraceptive injection, contraceptive patch, pill, intrauterine device, diaphragm, and sterilization and hasLengthOfUse had the value of number of months. We also developed a terminology linking synonyms for classes, attributes, and values: 90 synonyms for 236 classes, 9 synonyms for 54 attributes, and 501 synonyms for 772 values.We developed EAV models for the 139 lowest level class concepts. For example, The Protégé ontology debugger program revealed that concept classes in the ontology were coherently and consistently defined. The DL reasoner showed that the ontology correctly answered all 10 CQs.The content coverage of the ontology is presented in Average scores for all of the criteria for structural and representations layers exceeded 4 on a 5-point scale. The experts rated the hierarchy breadth, density, overall complexity, and connectivity criteria as strongly agree (score 5). The criterion with the lowest score was accuracy of the representation layers, with a score of 4.33 .Violence and abuse  and flexible working arrangement (fertility policy) had a low DF and high DoD growth rates. Economic problems, population aging, and nuclearization of the family  and child-safety protection system (fertility policy) had a high DF and high DoD growth rates.violence and abuse  and flexible working arrangement and financial support for employment security (fertility policies). The keywords classified as strong signals were economic problems, nuclearization of the family, and population aging , and child-safety protection system and maternity-leave system (fertility policies). The keywords classified as latent signals were gender inequality, employment problems, and changing perspectives about marriage , and policy public relations, family-friendly work environment, and smart work center (fertility policies). The keywords classified as not-strong-but-well-known signals were conservative values  and financial support for childbirth and infrastructure for childcare support (fertility policies).We have developed a determinants-of-fertility ontology as a framework for collecting and analyzing social media data. The ontology was evaluated in terms of the DL, content coverage, and structural and representational layers. We applied the ontology with terminology to detect future signals of fertility issues from social media data.The developed determinants-of-fertility ontology has 6 main characteristics. First, it is the first ontology to describe the multilevel factors that affect fertility. Various factors and the complex interactions between them determine fertility ,26,27, aSecond, this ontology contains factors related to fertility issues that are unique to South Korea. In most cases, childbirth does not occur until after marriage in South Korea, and delaying marriage is an important factor affecting the decision to have a child ,42,43. Tfinancial support for childbirth, various terms such as childbirth celebration money, childbirth grant, subsidy, baby bonus, and childbirth incentive are used on social media postings. Since the developed ontology includes these terms, it can be used to collect and analyze consumer terms in social media data.Third, the developed ontology includes terminology with synonyms for classes such as consumer terms and abbreviations, which makes it suitable for analyzing social media data. For example, regarding Fourth, each class of this ontology was modeled using the EAV model and included the attributes of each class and the values of those attributes. Like previous research ,21, valuFifth, we ensured quality of the ontology by using a variety of evaluation methods, including the application-based, data-driven, and user-based approaches proposed by Brank et al . Applicaeconomic problems, child-safety protection system, violence and abuse, and flexible working arrangement.Finally, the ontology with terminology developed in this study was used as a framework to detect future signals of fertility issues from social media data. The ontology allowed us to use social media data to identify the current trends and future changes in fertility issues related to the effective implementation of policies to increase the fertility rate. These trends were Economic problems and child-safety protection system were strong signals of fertility issues. Economic problems were noted to be an important topic in a survey about public perceptions of the low fertility phenomenon [enomenon . In a stenomenon . Therefochild-safety protection system needs to be implemented as another investment toward avoiding low fertility in future generations [child-safety protection system.A erations . In ordeerations ,4,45-47.erations ,47. Sincerations ,47. Howeerations , and reserations ,49. The Violence and abuse and flexible working arrangement were weak signals that could develop into strong signals in the future. Violence and abuse were previously reported as important factors for low fertility, with experts identifying changes in the social environment as being important [mportant ,49,50. Tflexible working arrangement is a policy that allows workers to balance work and life [A and life ,51. Bothand life . Long woand life . TherefoThe determinants-of-fertility ontology developed in this study comprehensively covers fertility issues relevant to the low fertility phenomenon in South Korea and will be useful for analyzing social media data. However, it is also subject to several limitations.First, the direct and indirect effects of employment stability, job creation, housing supply, and public education on fertility  were notSecond, the synonyms of the ontology developed in this study may not include all the terms used by the general public on social media. Many of the terms used on social media are highly transient—rapidly appearing, spreading, and then disappearing ,55. The Third, future signals of fertility issues were detected during the second phases of the policy on low fertility. Low fertility is a demographic issue that requires a long-term approach, and the policy responses of the government should be periodically reviewed and evaluated to ensure that the policies in place at a particular time point are consistent with any changes in the population and the socioeconomic and cultural environment . This siFinally, only the KIM that uses the DF of keywords was used to detect future signals. Since future signals are generally subjective , even a violence and abuse  and flexible working arrangement (fertility policy) were weak signals that might increase rapidly in the future. The findings of this study will help policy makers to develop effective policies for responding to the low fertility rate in South Korea based on examinations of the present and future trends.A determinants-of-fertility ontology was developed in this study that comprised 6 superclasses, 230 subclasses, and 41 relationships with terminology that comprised 1464 synonyms for the 236 classes. Class concepts of the ontology were included as an EAV model and contained synonyms of the ontology classes such as consumer terms and abbreviations. The ontology can be used to analyze social media data on fertility issues. The DL, content coverage, and structural and representational layers of the ontology were evaluated. The ontology and its terminology were used to detect future signals of fertility issues in South Korea. Our novel determinants-of-fertility ontology provides a framework for collecting and analyzing social media data toward understanding which socioeconomic and cultural factors and fertility policies should be focused on in the future. The analysis of future signals revealed that


Viral induced signaling through the Epidermal Growth Factor Receptor (EGFR) and other receptors such as integrins are key control points for viral-induced cellular changes and productive and latent infection in host organ systems. This review will explore the current understanding of HCMV strategies utilized to hijack cellular signaling pathways, such as EGFR, to promote the wide-spread dissemination and the classic life-long herpesvirus persistence.Viruses have evolved diverse strategies to manipulate cellular signaling pathways in order to promote infection and/or persistence. Human cytomegalovirus (HCMV) possesses a number of unique properties that allow the virus to alter cellular events required for infection of a diverse array of host cell types and long-term persistence. Of specific importance is infection of bone marrow derived and myeloid lineage cells, such as peripheral blood monocytes and CD34 Human cytomegalovirus (HCMV) infection is a significant public health threat worldwide . HCMV is+ hematopoietic progenitor cells (HPCs). The CD34+ HPCs during reactivation differentiate along myeloid lineage development pathways to become monocytes allowing organ dissemination and additional host to host spread , gH (UL75)/gL (UL115)/gO (ULl74), which make up the gH/gL/gO complex or the trimer, and the gH/gL/UL128-131 complex or the pentamer, and gM (UL100)/gN (UL73) interact with cellular receptors that in turn lead to the activation of various signal molecules in the infected host cells . There a+ HPCs in this review. Both cell types are important targets for HCMV infection and are critical to life-long persistence and dissemination within an individual infected host and the general human population. Monocytes are essential for hematogenous dissemination of HCMV to multiple organ systems following primary infection . HCMV gB, like all herpesvirus gBs, is essential for viral membrane fusion with cellular surface or vesicular membranes /UL116]  to the k+ HPCs and in cell signaling remain unresolved. Overall, viral glycoproteins are an indispensable cell type specific strategic weapon for successful viral infection via their receptor binding capabilities, their ability to induce cellular signaling in host cells and to allow viral entry into that target cell. Further studies are needed to determine the precise mechanisms by which the many HCMV glycoproteins and the many receptors together or independently alters host signaling pathways in the many cells that HCMV infects.There are both shared and unique features of the gH/gL glycoprotein complexes among the different herpesviruses. For example, gH/gL  comprise the central herpesvirus membrane fusion machinery . However+ HPCs K and Akt. When considering other peripheral blood cell types, such as T cell and B cells, EGFR expression seems to be involved in the select myeloid tropism of the virus . This HCThe HCMV gB engages EGFR and then rapidly and directly activates downstream signaling via its intrinsic tyrosine kinase . gB mainThe HCMV infection elicits a robust immune response . HoweverWe previously described that viral engagement of β1 and β3 integrins are essential for infection of human peripheral monocytes via the interaction of the HCMV gH/gL/UL128-131 complex with these two integrin families [The HCMV binding to host cell receptors induces signals in a distinct manner for each cell type. In monocytes, this receptor-ligand engagement results in cellular differentiation and long-term cellular survival ; but howIt is important to note that both the gB/EGFR and the pentamer/integrin signaling axes drive independent events, as well as cooperate to modify the infected cell. For example, as discussed briefly in this review, integrins activate paxillin through integrin/c-Src activation , and EGF+ cells (trans-Golgi network (TGN) and then finally to recycling endosomes in monocytes, where de-envelopment occurs  and interleukin-6 (IL-6), by targeting multiple members of the endocytic secretory pathway . In addi+ HPCs , has been documented to signal through a number of pathways and this chemokine receptor has a number of biological functions . US28 bispecific . US28 caspecific . US28 haspecific  and to bspecific . US28 isspecific , reactivspecific , and in nfection . Overallnfection  demonstr+ HPCs, two critical cell types required for persistence and dissemination, where data emphasizes that what is seen in other cell types such as fibroblasts and epithelial and endothelial cells is not seen during infection of these two cell types and vice versa. Overall, we believe that by defining the HCMV signaling pathway activated during infection, it will be possible to develop new treatment options for viral diseases.The HCMV has evolved a complicated strategy to disrupt biological pathways in infected host cells. The understanding of the relationship between viral infection and cellular signaling helps provide clues for how viral proteins and other regulators (whether they control primary infection or latency) hijack host cellular signaling pathways and control the pathways to the virus’ advantage. Deciphering the impact of cellular receptor engagement during viral entry and the corresponding exploitation of downstream host cellular signaling is vital to understanding viral dissemination and life-long viral persistence in individual hosts and in the human population in general. HCMV gB and gH complexes are critical for initiating these events through their binding to cognate host cell receptors during primary infection, while a number of viral proteins and miRNAs are critical to controlling the signaling associated with maintenance and reactivation from latency. Because each signaling event in each cell type is likely different, it is important to study the multiple cell types and how each event dictates the unique biology and infection characteristics within each cell. We argue this last point is evident during infection of monocytes and CD34All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.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.


S. cerevisiae. A number of experimental findings demonstrated a close relationship between these pathways: Both are responsive to glucose availability. Both regulate ribosome production on the transcriptional level and repress autophagy and the cellular stress response. Sch9, a major downstream effector of TORC1 presumably shares its kinase consensus motif with PKA, and genetic rescue and synthetic defects between PKA and Sch9 have been known for a long time. Further, studies in the first decade of this century have suggested direct regulation of PKA by TORC1. Nonetheless, the contribution of a potential direct cross-talk vs. potential sharing of targets between the pathways has still not been completely resolved. What is more, other findings have in contrast highlighted an antagonistic relationship between the two pathways. In this review, I explore the association between TOR and PKA signaling, mainly by focusing on proteins that are commonly referred to as shared TOR and PKA targets. Most of these proteins are transcription factors which to a large part explain the major transcriptional responses elicited by TOR and PKA upon nutrient shifts. I examine the evidence that these proteins are indeed direct targets of both pathways and which aspects of their regulation are targeted by TOR and PKA. I further explore if they are phosphorylated on shared sites by PKA and Sch9 or when experimental findings point towards regulation via the PP2ASit4/PP2A branch downstream of TORC1. Finally, I critically review data suggesting direct cross-talk between the pathways and its potential mechanism.TOR and PKA signaling are the major growth-regulatory nutrient-sensing pathways in  Protein kinase A (PKA) and TOR signaling are two highly conserved signaling pathways that respond to nutrient and stress signals and regulate various responses that govern cellular growth. Numerous findings indicate a strong connection between the pathways, but no clear picture of the nature of this interplay has emerged. This work aims to critically review the literature on shared targets and direct cross-talk and to point out gaps in current knowledge that hinder a better understanding. Beyond providing a resource about specifics of the signaling systems discussed, the described modes of interaction are intended to serve as examples relevant for understanding signaling interplay in a wider context. I will first provide a brief introduction to the PKA and TOR pathways to introduce the main players referred to subsequently. Then, I will give an overview of genetic data that link the pathways, before describing their major shared functions and substrates. Finally, I will discuss proposed direct cross-talk.TOR signaling is one of the most central mechanisms that allows cells to adapt their growth to nutrient availability and also functions as a stress sensor. TOR signaling has been reviewed elsewhere ,9,10,11 S. cerevisiae expresses a PP2A-like phosphatase (referred to as PP2ASit4), consisting of catalytic subunit Sit4 and either Sap155, Sap185 or Sap190 x[S/T] motifs on Tod6 and four sites in R[R/K]x[S/T] and one in an Rxx[S/T] motif on Dot6 caused a decrease, but not complete abrogation of phosphorylation by Sch9 in vitro . The ideignaling . Furtherignaling . Furtherreatment . In contreatment . TherefoBCY1 deletion strain and the presence of the Rap1 binding site in its promoter was sufficient to confer an increase in a reporter transcript in a bcy1∆ strain compared to wt x[S/T] motif x[S/T] ,162 was T] motif ,120. ,in Pfk26 , Nth1 [5in Pfk26 ,165, Ckiin Pfk26 , Adr1 [1in Pfk26  and Ssn2in Pfk26 . If diffin Pfk26 ,170 and in Pfk26 . As discgln3Δ gat1Δ background and several genetic manipulations hyperactivating PKA signaling  were found to further increase rapamycin resistance [SCH9 deletion resembles the effect of rapamycin treatment in this respect [Having explored how PKA and TOR signaling interact via shared targets, we will now return to discussing a potential more direct cross-talk between the pathways. As pointed out in an earlier section, the regulation of one pathway by the other is not sufficient to explain experimental observations. However, this does not rule out that such cross-talk may exist in addition to convergence on shared substrates. TOR was initially discovered by the Hall lab via a genetic screen for spontaneous rapamycin-insensitive mutants, leading to the identification of the target-of-rapamycin kinases Tor1 and Tor2 . In subssistance . Based oYAK1 deletion is equivalent to PKA hyperactivation with respect to overcoming Gat1-Gln3-independent rapamycin effects [cyr1∆ strain with cAMP [The model of TORC1 regulating PKA gained support through a subsequent study: Martin et al. showed that hyperactivation of PKA prohibited rapamycin-induced nuclear translocation of the RP gene repressor Crf1 and that PKA inactivation led to nuclear translocation without the need for rapamycin  (see abo effects . The fac effects ,65,173,  effects . Additio effects  and a po effects ,174,175. effects ,175 resuith cAMP . A modelith cAMP ,177,178,ith cAMP ,179,180.ith cAMP ,47. WhilSit4, in other cases the phospho sites are shared between PKA and Sch9 which exhibit similar substrate specificity. The mechanistic basis for some substrates being shared between the two AGC kinases and others being unique to PKA remains an important question to resolve. The review of each of these individual targets also points out that much remains to be learned about how TOR and PKA regulate even these best-understood common targets. In addition, some observations have led to the proposal of a more direct cross-talk between the pathways. While TOR signaling appears like an upstream regulator of PKA based on nucleo-cytoplasmic localization of PKA subunits and on the regulation of Yak1, a better understanding of the mechanism of this proposed cross-talk is required to lend credibility to its existence. Finally, we understand little about the physiological role of the interplay between the two major growth-regulatory pathways. The simple model, according to which PKA solely responds to carbon source availability and TOR to amino acid and nitrogen availability, has increasingly eroded in recent years. Instead, it now becomes important to ask how and why different environmental conditions impact the output of each individual pathway and their interplay. There exists compelling evidence for a tight interplay between TOR and PKA signaling, based on genetic findings and the phosphorylation state of known targets. However, genetic evidence also clearly demonstrates that the pathways are not purely epistatic. Based on the best-understood shared targets presented in this review, it is apparent that each point of convergence between the pathways needs to be considered individually. While in some cases the phospho sites targeted by the two pathways are distinct, with TORC1-dependent sites sometimes dephosphorylated by PP2A/PP2A


Bovine viral diarrhea virus (BVDV) infection during early gestation results in persistently infected (PI) immunotolerant calves that are the primary reservoirs of the virus. Pathologies observed in PI cattle include congenital defects of the brain, heart, and bone as well as marked functional defects in their immune system. It was hypothesized that fetal BVDV infection alters T cell activation and signaling genes by epigenetic mechanisms. To test this, PI and control fetal splenic tissues were collected on day 245 of gestation, 170 days post maternal infection. DNA was isolated for reduced representation bisulfite sequencing, protein was isolated for proteomics, both were analyzed with appropriate bioinformatic methods. Within set parameters, 1951 hypermethylated and 691 hypomethylated DNA regions were identified in PI compared to control fetuses. Pathways associated with immune system, neural, cardiac, and bone development were associated with heavily methylated DNA. The proteomic analysis revealed 12 differentially expressed proteins in PI vs. control animals. Upregulated proteins were associated with protein processing, whereas downregulated proteins were associated with lymphocyte migration and development in PI compared to control fetal spleens. The epigenetic changes in DNA may explain the immune dysfunctions, abnormal bone formation, and brain and heart defects observed in PI animals. Flaviviridae and Pestivirus genus, discovered in 1946 [Bovine viral diarrhea virus (BVDV) is a single stranded RNA virus in the family  in 1946 ,3,4,5. B in 1946 . The ncp in 1946 ,9,10,11. in 1946 ,13,14. T in 1946 ,13,14. I in 1946 ,16. Feta in 1946 ,18,19,20 in 1946 .Our group previously developed an in vivo model of BVDV PI fetal infection by inoculating pregnant BVDV naïve heifers with BVDV on day 75 of gestation ,22. FetuThe present study aimed to determine if the inhibition of the immune system following the initial immune response and PI pathologies were due to epigenetic changes in the PI fetal DNA. It was hypothesized that spleens from PI fetuses would have increased methylation of genes and decreased abundance of proteins associated with the adaptive immune response. Spleens from PI and control fetuses collected on gestational day 245 were examined because spleens are secondary lymphoid organs which survey the blood for pathogens; the day 245 time point was chosen for its proximity to parturition (283-day gestation in the bovine) and would provide epigenetic data similar to what would be expected in postnatal animals. Reduced representation bisulfite sequencing (RRBS) and liquid chromatography and mass spectrometry (LC-MS) proteomics and bioinformatic analyses were performed on these samples to determine epigenetic changes to genes and effects of DNA methylation on protein expression. Differentially methylated regions and protein abundances were found in PI fetuses compared to controls affecting pathways associated with compromised immune, neural, cardiac, and bone development.10 TCID50/mL to generate PI fetuses. Infected and control animals were confirmed infected or noninfected, respectively, by RT-qPCR and serum neutralization assay throughout gestation [All animal experiments were approved by the Institutional Animal Care and Use Committee 08-16A-01 (11/01/09) at Colorado State University and by the Colorado State University Biosafety Committee . Viral infections and fetal sample collections are described in previous studies ,29. Brieestation .Seven fetuses were collected  by cesarean section on gestational day 245. Originally, 4 PI fetuses were generated; however, one fetus was aborted for reasons unrelated to BVDV infection. Control fetuses were collected prior to the collection of PI fetuses to avoid any cross-contamination of infected tissues. Standard surgical practices were used, and sterile surgical packs were replaced between each animal. Splenic tissue was sampled from the middle of the organ to ensure the inclusion of both red and white pulps. Samples were dissected into halves; one half was snap frozen in liquid nitrogen and stored at −80 °C for later DNA and protein extraction for this study.MspI  and purified with DNA Clean & Concentrator-5 . Fragments were ligated to preannealed adapters with cytosine replaced with 5′-methyl-cytosine according to Illumina’s guidelines. Ligated fragments greater than 50 base pairs were recovered with the DNA Clean & Concentrator-5  then bisulfite treated with the EZ DNA Methylation-Lightning Kit . Samples were subjected to PCR with Illumina indices and products were then purified with DNA Clean & Concentrator-5 . Size and concentrations were confirmed with the Agilent 2200 TapeStation and libraries were sequenced on an Illumina platform.One milligram of splenic tissue was homogenized and subjected to the Qiagen DNeasy Blood and Tissue Kit  according to the manufacturer’s instructions for DNA extraction. Extracted DNA (~300 ng) was sent to Zymo Research  for genome-wide classic reduced representation bisulfite sequencing (RRBS/methyl-seq). The following methods were provided by Zymo Research. Samples were digested with 30 units of p < 0.05 and a 25% or greater difference in methylation patterns. Gene IDs were identified using the genomation R package [Raw BAM files received from Zymo Research were analyzed in R using the methylKit R package and the Colorado State University’s CVMRIT03 server, which identified differentially methylated regions (DMRs) . DMRs we package . Quality package ,35,36. B package . Raw filOne hundred milligrams of frozen splenic tissue from day 245 fetuses was subjected to protein extraction via RIPA Lysis and Extraction Buffer  and Halt Protease and Phosphatase Inhibitor Cocktail  according to the manufacturer’s instructions. Protein was quantified using a Pierce BCA Assay . Detergents were removed from the protein samples using the Pierce Detergent Removal Spin Columns . Cleaned samples were submitted to the CSU Analytical Resources Core Bioanalysis and Omics for protein quantification, trypsin digestion, and protein identification via liquid chromatography and mass spectrometry (LC-MS). The following methods were provided by the CSU Analytical Resources Core Bioanalysis and Omics. Aliquots of samples were diluted 1:2 in 2 M urea, 2% SDS and measured with the Pierce BCA Protein Assay . Fifty micrograms total protein was aliquoted and processed for in-solution trypsin digestion as previously described . Absorbam/z range of 400–2000 under positive mode ionization. Ions with charge state +2 or +3 were accepted for MS/MS using a dynamic exclusion limit of 2 MS/MS spectra of a given m/z value for 30 s (exclusion duration of 90 s). The instrument was operated in FT mode for MS detection  and ion trap mode for MS/MS detection with a normalized collision energy set to 35%. Compound lists of the resulting spectra were generated using Xcalibur 3.0 software  with an S/N threshold of 1.5 and 1 scan/group.The following methods were provided by the CSU Analytical Resources Core Bioanalysis and Omics. Reverse phase chromatography was performed using water with 0.1% formic acid (A) and acetonitrile with 0.1% formic acid (B). One micrograms of peptides was purified and concentrated using an on-line enrichment column . Chromatographic separation was performed on a reverse phase nanospray column  using a 90 min gradient: 5–30% B over 85 min followed by 30–45% B over 5 min at a flow rate of 350 nL/min. Peptides were eluted directly into the mass spectrometer  equipped with a Nanospray Flex ion source  and spectra were collected over an The following methods were provided by the CSU Analytical Resources Core Bioanalysis and Omics. Tandem mass spectra were extracted, charge state deconvoluted, and deisotoped by ProteoWizard MsConvert (version 3.0). Spectra from all samples were searched using Mascot  against reverse concatenated Uniprot_Bovine_rev_102819 and cRAP_rev_100518 databases  assuming the digestion enzyme trypsin. Mascot was searched with a fragment ion mass tolerance of 0.80 Da and a parent ion tolerance of 20 PPM. Carboxymethylation of cysteine was specified in Mascot as a fixed modification. Deamidation of asparagine and glutamine and oxidation of methionine were specified in Mascot as variable modifications.Search results from all samples were imported and combined using the probabilistic protein identification algorithms implemented in the Scaffold software  ,41. Peptt-test was applied to determine protein species that were significantly different in abundance between groups . Pseudo values were added (+1) prior to fold change calculations to eliminate zero values.Relative quantitation was determined using spectral counting (SpC) . A StudeInstrument suitability was monitored through analysis of commercially purchased BSA standard digest and automated monitoring using PanormaQC. Metrics  were monitored and flagged as outliers if results were outside +/− 3 standard deviations of the guide set . Values for all metrics were within normal limits throughout the duration of the experiment, indicating instrument stability and data robustness.Classic RRBS indicated no significant changes in whole genome global methylation levels between control and PI animals. At the regional level, there were 2641 DMRs between control and PI animals. Of those DMRs, 1951 regions were hypermethylated in PI animals compared to controls while 691 regions were hypomethylated in PIs compared to controls. Due to the expansive results of the methyl-seq, results will be focused on significantly impacted pathways. All DMRs can be found in Wnt/b-Catenin signaling, protein kinase A signaling, PI3K/AKT signaling, calcium signaling (predicted upregulation), STAT3 signaling, mTOR signaling, phospholipase C signaling, and Wnt-Ca signaling. Pathways associated with immune development and activation include the role of macrophages, fibroblasts, and endothelial cells in rheumatoid arthritis, CCR5 signaling in macrophages (predicted upregulation), IL8 signaling, IL15 production, regulation of IL2 expression in activated and anergic T lymphocytes, IL1 signaling, B cell activating factor signaling, CXCR4 signaling, PKCθ signaling in T lymphocytes, leukocyte extravasation signaling, and CD27 signaling in lymphocytes (predicted upregulation). Pathways associated with neural development include axonal guidance signaling, synaptogenesis signaling pathway (predicted upregulation), CREB signaling in neurons, alpha adrenergic signaling, and synaptic long-term depression. Pathways associated with cardiac development include factors promoting cardiogenesis in vertebrates, role of NFAT in cardiac hypertrophy (predicted upregulation), and cardiac hypertrophy signaling. Pathways associated with bone development or bone disease include the role of osteoblasts, osteoclasts and chondrocytes in rheumatoid arthritis, osteoarthritis pathway, and actin cytoskeleton signaling. When considering both hypo- and hypermethylated regions of PI fetuses, the nuclear factor of activated T cells (NFAT) family and signaling pathway stood out. Within that signaling cascade, calcium channel ORAI, calmodulin 1 (CALM1), and NFATc2 were hypomethylated while co-stimulatory molecules CD247, VAV1, NFATc1, and NFATc4 were hypermethylated in PIs compared to controls. Significantly different genes associated with these pathways can be found in The pathways reported are predicted to be downregulated, due to hypermethylation of genes, unless otherwise stated. Several pathways associated with general biological signaling were shown to be significantly affected, as predicted by IPA. In order of higher significance to lower significance, these pathways include but are not limited to: signaling by Rho family GTPases, human embryonic stem cell pluripotency, Proteomic analysis from LC-MS identified 12 significantly different proteins, with a 1.5-fold cutoff, in PI fetuses vs. controls. Increased proteins were translation machinery associated protein 7 (TMA7), peptidase d (PEPD), nuclear migration protein nudc (NUDC), tropomodulin 3 (TMOD3), and small nuclear ribonucleoprotein F (SNRPF). Proteins decreased in PI fetuses compared to controls include Thy-1 cell surface antigen (THY1), heterogenous nuclear ribonucleoprotein c (HNRPC), cysteine and glycine rich protein 1 (CSRP1), vesicle associated membrane protein associated protein B (VAPB), cystatin B (CSTB), AKAP2 c domain containing protein (AKAP2), and calponin 2 (CNN2).Day 245 fetal spleen samples are an imperfect but unique sample set for this study. As the developing fetus has a constantly changing epigenome, the fetuses on day 245, as opposed to early timepoints, provide epigenetic data most similar to what we would expect to see in postnatal animals. When discussing methylation data, it is important to understand its limitations without RNA expression data. Unfortunately, the data presented in this study do not contain RNA expression due to RNA from splenic tissue degrading over time at −80 °C; however, this leaves opportunities for future studies. Additionally, the epigenetic changes found in PI fetal spleens were not completely reflected in protein abundance. However, changes in methylation are rarely reflected in gene expression at one given time. Changes in gene expression due to methylation of specific genes may have occurred prior to day 245 or may occur postnatally, as discussed below. Despite these limitations to interpretation, the data discussed below are still highly valuable in understanding the effects BVDV PI has on fetal development.Fetal BVDV PI spleens contained 2641 DMRs and differences in the expression of 12 proteins compared to controls. Hyper- and hypomethylated genes were found in pathways related to the immune system, osteoclastogenesis in bone, and the developing neural system and heart in PI fetal spleens.Previously, it had been hypothesized that the dramatic attenuation of BVDV PI fetal immune responses and, specifically, the inactivation/lack of response from lymphocytes were due to fetal Treg cells identifying BVDV as self . This imInterleukin 2 (IL2) is an important cytokine in the development and activation of T cells promoting both the activation and anergy of T cells as well as Treg development. Genes within the IL2 pathways involved in the regulation of IL2 action and PKC signaling in T cells were heavily hypermethylated. For example, CD247 , part of a critical T cell receptor co-stimulatory molecule, was hypermethylated. Reduced expression of CD247 would reduce the release of IL2. IL2 is a potent stimulator of FOXP3 expression in Treg development, potentially causing an increase in Treg cell development through increased FOXP3 expression [IL2, causing apoptosis of effector cells [IL2 knockout mice exhibit lymphoproliferation and lethal autoimmunity which is prevented by adoptive transfer of normal Treg cells [IL2 signaling pathway of CD4 Th cells are hypermethylated , shifting the IL2 signaling towards the maintenance of Treg cells while hindering Th cell development. Methylation of these genes was not reflected in proteomic data. Thus, the changes in protein levels may have occurred earlier or later in gestation or postnatally.pression ,46. Tregor cells ,47. IL2 eg cells ,49. In avav guanine nucleotide exchange factor 1 (VAV1), integrin subunit alpha M (ITGAM), THY1, and others. The effects of hypermethylation of THY1 were reflected in decreased THY1 protein in PI fetal spleens compared to controls. THY1 is expressed in fibroblasts, neurons, and hematopoietic stem cells and has several functions including mediating the binding of leukocytes to ECs and triggering neutrophil effector functions. THY1 knockout mice have decreased extravasated leukocytes and altered cytokines released at sites of inflammation [TMOD not being differentially methylated, other mediators involved in the pathway have affected its expression.Leukocyte extravasation is the movement of cells from the blood stream across blood vessel walls to infected tissues in response to release of cytokines and chemokines as a part of the innate immune response. Recruitment of leukocytes requires gene products that stimulate leukocyte migration and adhesion to endothelial cells (ECs). Several signaling genes within this pathway were hypermethylated in fetal PI spleens including ammation . TMOD, aammation . DespiteC-X-C motif chemokine receptor 4 (CXCR4) was previously shown to be decreased for several months in maternal peripheral blood mononuclear cells (PBMCs) in the dams carrying PI fetuses and in postnatal PI animals compared to control animals [CXCR4 was not differentially methylated or expressed as a protein, its signaling pathways, including G proteins and Rho signaling, were hypermethylated in the data from the current experiment [CXCR4 inhibition in PI animals, possibly contributing to dysfunctional leukocyte and lymphocyte development in PI animals. These genes were not reflected in the proteomics data, indicating that their differential expression may occur at an earlier time point during fetal development. animals . Moreove animals . CXCR4 h animals . Althougperiment . InhibitIL35 stimulation, suggesting a role for AKAP2 in the differentiation of CD8 T cells [AKAP2 protein was decreased in fetal BVDV PI spleens compared to controls. AKAP family members anchor and compartmentalize PKA for regulation of cAMP signaling . More re T cells . AKAP2 w T cells . The litCNN2 has been associated with the development of immune cells of myeloid lineage. Peripheral blood neutrophils and monocytes were decreased in CNN2 interrupted mice, concurrently with increased proliferation and migration of neutrophils and monocytes, and increased macrophage phagocytic activity. In contrast, increased CNN2 was associated with the adhesion dependent maturation of macrophages. In this study, CNN2 was decreased in BVDV PI fetal spleens, which could cause a decrease in mature macrophages/leukocytes while increasing the proliferation and migration of immature monocytes in PI animals. These effects could be due to direct effects on macrophage development, or due to osteopetrosis resulting in the migration of immature leukocytes from bone marrow to the spleen and increased extramedullary splenic hematopoiesis.macrophage colony stimulating factor (CSF1 or M-CSF), receptor activator of nuclear factor kappa B ligand (RANKL), and others [CSF1 and RANKL, NFATc1 is considered the master transcription factor for osteoclastogenesis [IL1 and IL6, secreted by antigen stimulated immune cells [IL1 inhibitor from monocytes, direct viral changes to bone marrow derived cells, and inhibition of osteoclastogenesis by type I IFNs [Three hundred and eighty-five million years ago, the vertebrate skeletal system and immune system evolved together as aquatic vertebrates became terrestrial . The evod others . Althougogenesis ,62,63,64ne cells . Osteopene cells ,65,66. Pne cells ,65,66. Pne cells ,20,26,28ne cells . The calne cells . Additione cells . Increasne cells . Anotherne cells . At 13 mne cells . All thre I IFNs ,65,66. Se I IFNs ,69,70,71Wnt/b-Catenin signaling, protein kinase A signaling, PI3K/AKT signaling, calcium signaling, STAT3 signaling, phospholipase C signaling, and Wnt-Ca signaling pathways contained the same differentially methylated genes affecting osteoclastogenesis in PI fetal spleens compared to controls. Changes in signaling due to DNA methylation may explain the decreased number of osteoclasts observed in PI animals  formation/AP1 gene expression. The AP1 transcription complex includes the cFos and Jun family proteins. The cFos proteins are stimulated by not only Rho family GTPases, but also nuclear factor kappa B (NFKB). NFKB is expected to be inhibited due to hypomethylation of inhibitor of NFKB subunit beta and peroxisome proliferator activated receptor gamma (PPARG), and hypermethylation of PPARG coactivator 1 beta (PGCA1B), and CCAAT/enhancer binding protein alpha (C/EBP1A) [AP1 complexes are thought to be decreased and, thus, unable to stimulate osteoclastogenesis. In mouse studies, mice lacking cFos proteins developed osteopetrosis due to impaired osteoclastogenesis [Several pathways identified by IPA including signaling by Rho family GTPases, C/EBP1A) ,74,75,76ogenesis ,73,77.Wnt signaling pathway is important for both osteoclast and osteoblast differentiation, and the role of Wnt signaling depends on which Wnt molecule binds to the Frizzled receptor (hypermethylated). Normally, Wnt2b expression is higher in mature osteoblasts compared to osteoblast progenitors, however, its direct role in osteoblast differentiation is unknown. Wnt2b was hypermethylated in our data, possibly inhibiting not only its signaling pathway, but also affecting osteoblast maturation [Wnt7a was also hypermethylated in our data. Previous studies have shown Wnt7 conditional knockout causes a decrease in bone formation and chondrocyte differentiation [dickkopf WNT signaling pathway inhibitor 1 (DKK1), a Wnt inhibitor, is also hypermethylated which may compensate for a decreased osteoclastogenesis. Phospholipase C signaling contains the same signals as the Rho family GTPases pathway with direct effects on nuclear factor of activated T cells (NFATc1) expression. The hypermethylation of the G proteins and Rho is expected to decrease the signal for calcium mediated gene expression.The turation . Wnt7a wntiation . The metntiation ,28. OsteWnt signaling pathway being present in all bone related pathways. Colony stimulating factor 1  is hypermethylated and a large inducer of osteoclastogenesis, macrophage differentiation, and osteoclast survival. CSF1 is produced by osteoblasts and activated T cells to induce differentiation of macrophages or dendritic cells into osteoclasts [CSF1 would greatly inhibit osteoclastogenesis from monocytic cells. Mice lacking CSF1 exhibit severe osteopetrosis due to a decrease in osteoclastogenesis [IL1 and IL6 receptors, both inducers of osteoclastogenesis, are hypomethylated. IL6 is secreted by bone marrow stromal cells, osteoblasts, and macrophages to induce an inflammatory response as well as osteoclastogenesis through the STAT3 (hypermethylated) pathway [IL6 from bone marrow derived cells, the actual expression of IL6 may be hindered due to the osteopetrotic pathologies of BVDV PI animals lacking bone marrow and, thus, bone marrow derived cells. In response to such a decrease, IL6R may be hypomethylated to amplify the signal for downstream targets if IL6 does happen to bind. Despite the attempted amplification, the hypermethylation of STAT3 would further hinder the IL6 signaling for osteoclastogenesis. However, IL6 is also known to be antiosteoclastogenic but, because STAT3 is hypermethylated, the signaling will be hindered no matter the reason [IL1 is another proinflammatory cytokine that is pro-osteoclastogenic. One study has determined that BVDV PI animals have inhibited IL1 expression through the expression of an IL1 inhibitor from infected cells [IL1 may be an indirect cause of the hypomethylation of its receptor, for the same proposed reasons as the hypomethylation of IL6R discussed above.The pathways significantly affected by methylation, identified by IPA, which were associated with osteoarthritis and bone development, had overlapping genes and signaling pathways, with the eoclasts . Therefoogenesis ,82. Inte pathway ,84. Due ed cells . This inNFATc1 has been identified as the master transcription factor for osteoclast differentiation [RANKL induces calcium oscillations in the bone marrow cells, activates calcineurin, then induces NFATc1 expression via TNF receptor associated factor (TRAF) 6 and cFos signaling [NFATc1 autoamplifies and, with the assistance of the AP1 transcription complex, stimulates transcription of genes for osteoclastogenesis [NFATc1 was both hypo- and hypermethylated. Although the interpretation of this data is difficult, differing methylation patterns on a gene have been associated with carcinogenesis [NFATc1 expression would be altered and would cause an imbalance in osteoclast differentiation signaling. Interestingly, an upstream regulator to NFATc1, calmodulin, was hypomethylated. Calmodulin is a regulator for all NFAT family members and is involved with general calcium signaling. The hypomethylation of the calmodulin gene could be an attempt to stimulate other NFAT family members or amplify the calcium signaling pathway discussed above.ntiation . In healignaling . NFATc1 ogenesis . In the ogenesis . One stuogenesis . DespiteCSTB has several biological functions including chemotaxis, stimulation of cytokine secretion, release of nitric oxide, regulation of apoptosis, protection of neurons, cell cycle regulation, and bone resorption. CSTB was identified as a decreased protein in PI animals compared to controls. CSTB knockout mice mimic the progressive myoclonus epilepsy of Unverricht–Lundborg type (EPM1) epileptic phenotype in humans, characterized by inflammation in the brain [CSTB is also thought to protect osteoclasts from apoptosis in vitro through the inhibition of cathepsin K [CSTB knockouts would be an increase in osteoclasts, due to a lack of available inhibition of cathepsin K; however, that is not the case in vivo for CSTB deficient or knockout mice. In addition to epileptic phenotypes, CSTB knockout mice showed a significant decrease in osteoclasts and increased bone mineral densities [CSTB has been shown in mice infected with ectromelia virus, which is hypothesized to enhance viral replication [CSTB in dendritic cells to increase its own replication and contribute to the inhibition of osteoclastogenesis.he brain . In normhepsin K . A normaensities . A direclication . SimilarNFATc1 decreases along with osteoclastogenesis [VAPB is a vesicle associated protein which can form dimers with itself or VAPA for vesicle transport. VAPB protein was decreased in PI animals compared to controls. VAPB has been shown to enhance hepatitis C virus (another flavivirus) replication through the binding of the viral protein NS5B to intracellular vesicles. If VAPB also enhances BVDV replication, then the amount of VAPB protein would not be expected to be decreased and VAPB bound to BVDV would have been counted and possibly increased in PIs. Despite this potential link between BVDV replication and VAPB, the decreased VAPB protein is thought to be reflective of its function in osteoclastogenesis and cardiac development, or because it is directly targeted by the virus. VAPB has a role in osteoclastogenesis, by controlling the activation of the phospholipase C (PLCG)-Ca-NFATc1 signaling pathway . With deogenesis . The speogenesis . In humaogenesis . Throughogenesis . BVDV anogenesis . AlthougAlthough these epigenetic and proteomic data were procured from the fetal spleen, they most likely reflect pathologies observed in the bone. Hematopoietic stem cells are produced in the bone prior to migration into peripheral lymphoid organs such as the spleen ,65,66. IBVDV directly infects fetal neuronal tissues and is associated with a variety of neural defects including cerebellar hypoplasia, hydranencephaly, hydrocephalus, and retinal dysplasia ,95,96,97THY1 is expressed on neurons and is an inhibitor of neurite outgrowth. While THY1 knockout mice do not have structural neural abnormalities, they exhibit alterations in spatial learning and a lack of social cues, possibly reflecting abnormal neurite connections [CSTB knockout mice exhibit alterations in GABAergic signaling, possibly contributing to neuronal degeneration [The most significantly methylated canonical pathway identified by IPA was the axonal guidance signaling pathway with 60 differentially methylated genes, with 43 genes hypermethylated (72%), including G protein receptors, transcriptional regulators, enzymes, growth factors, kinases, and others. The affected genes/pathway are predictive of alterations in actin filament reorganization, microtubule assembly, axon attraction, and adhesion. In addition, genes within the synaptogenesis pathway were differentially methylated with most regions being hypermethylated. These genes are involved in neuron adhesion, microtubule stabilization, and axonal guidance signaling. In addition to the epigenetic changes, proteins VAPB, THY1, and CSTB , which were significantly decreased in PI fetal spleens, are associated with altered neural development. CSTB mutations are associated with EPM1 while VAPB genetic mutations have been associated with ALS in humans ,98. A stnections ,103,104.Wnt signaling, G proteins, and calcium signaling. Several hypermethylated genes promoting the cardiogenesis in vertebrates pathway contribute to a dysfunctional cell cycle of cardiocytes and cardiomyocyte differentiation, including transcription factors/T cell factors 4 and 7 (TCF), t-box transcription factor 5 (TBX5), cyclin D1, and myocardin. In the pathway for the role of NFAT in cardiac hypertrophy, histone deacetylase 7 and NFATc4 were both hypermethylated. Mice with attenuated NFAT (specific NFAT not identified) in late gestation showed a thinning of the myocardium [myocyte enhancer factor 2D (MEF2D). Interestingly, VEGF was also hypermethylated. VEGF is needed in the developing fetus for the organization of the vascular system and its predicted decreased expression may alter said organization [IPA identified several heavily methylated pathways associated with cardiac development, summarized in ocardium . The carnization . The metnization ,108.TMA7; however, it has been shown to be increased in influenza viral infections [NUDC has a role in cell migration, hematopoiesis, and spindle formation, and as a regulator of inflammation [NUDC may be contributing to PI immune evasion by regulating inflammatory responses or may be an indication of malignant proliferation of hematopoietic stem cells in the spleen.Several of the increased proteins in PI animals, compared to controls, have a link to viral replication. Not much is known about fections . In a STfections . NUDC haammation ,112. ItsNFATc2 , CD247 , VAV1 , ITGAM , and CSTB  [BVDV viral proteins have been shown to inhibit and evade several immune functions in vitro, including IFN responses ,116,117.day 245) . These dday 245) .IFNB, IFNG, and ISG15 in day 97 PI fetuses  [ISG15 are known inhibitors of osteoclastogenesis, and their expression of these IFNs early in fetal development may not only inhibit ongoing osteoclastogenesis, but also cause the inhibition of osteoclastogenesis through hypermethylation of genes in most pathways affecting bone development and immune cell development [Methylation of genes and the impact on protein expression may help explain the pathologies in multiple organ systems associated with early BVDV transplacental infections. We suggest that the inflammation and cytokines associated with the early fetal response to BVDV infection, along with Treg suppression of the immune system during immunotolerance, inhibit proper osteoclastogenesis and bone formation (summarized in fection) ,29. Theselopment ,118,119.BVDV is an important economic problem for cattle industries worldwide. While this research enhances our understanding of viral repercussions in PI animals, it also provides insight into potential epigenetic changes due to maternal and fetal viral infections in humans. Maternal infection with Zika virus (ZIKV) and other viruses causes severe defects of the fetal brain . OsteopeToxoplasma gondii, HIV, parvovirus, Listeria monocytogenes, Treponema pallidum, varicella zoster virus, rubella virus, CMV, herpesviruses (HSVs) 1 and 2, and ZIKV causes significant detrimental effects on the fetus [Maternal factors contributing to fetal programming and health as an adult are a concept described as the developmental origin of adult health and disease; originally a hypothesis by Barker and Osmond (1986) based on the effects of maternal heart disease on fetal growth ,125. Fethe fetus . Althoug


Receptor-bound β-arrestins also initiate a second wave of signaling by scaffolding mitogen-activated protein kinase (MAPK) signaling components, MAPK kinase kinase, MAPK kinase, and MAPK. In particular, β-arrestins facilitate ERK1/2 or JNK3 activation by scaffolding signal cascade components such as ERK1/2-MEK1-cRaf or JNK3-MKK4/7-ASK1. Understanding the precise molecular and structural mechanisms of β-arrestin-mediated MAPK scaffolding assembly would deepen our understanding of GPCR-mediated MAPK activation and provide clues for the selective regulation of the MAPK signaling cascade for therapeutic purposes. Over the last decade, numerous research groups have attempted to understand the molecular and structural mechanisms of β-arrestin-mediated MAPK scaffolding assembly. Although not providing the complete mechanism, these efforts suggest potential binding interfaces between β-arrestins and MAPK signaling components and the mechanism for MAPK signal amplification by β-arrestin-mediated scaffolding. This review summarizes recent developments of cellular and molecular works on the scaffolding mechanism of β-arrestin for MAPK signaling cascade. However, GRK5 and GRK6 phosphorylate receptors to induce β-arrestin-mediated ERK1/2 activation. Moreover, different ligands induced different receptor conformations and different phosphorylation patterns, resulting in different β-arrestin activation [Long before the barcode theory was suggested, it was reported that β-arrestin-mediated ERK1/2 activation is dependent on the GRK isoforms that phosphorylate the receptor ,77. GRK2tivation ,79. The tivation , and mortivation ,76,80,81In this review, we discussed the molecular and structural mechanisms of β-arrestin-mediated scaffolding of ERK1/2 and JNK3 signaling components. In both cases, β-arrestin must be activated to complete the scaffolding assembly. Furthermore, it has been suggested that, upon activation, both ERK1/2 and JNK3, the most downstream kinase of MAPK signaling cascade, leave the β-arrestin-mediated scaffolding assembly so that inactive MAPK can be recruited, which results in signal amplification. However, the binding interfaces within the β-arrestin-mediated scaffolding assemblies seem to differ; cRaf, MEK1, and ERK1/2 have distinct binding interfaces to interact with β-arrestin, while ASK1, MKK4/7, and JNK3 share a similar binding interface to interact with β-arrestin. The binding interfaces with β-arrestin are different between cRaf and ASK1, MEK1 and MKK4/7, and ERK1/2 and JNK3. Thus, defining the precise interacting residues in the different β-arrestin-mediated scaffolding assemblies could pave the way for the selective regulation of arrestin-mediated ERK or JNK signaling.


Background: As a member of the atypical thiol oxidase family, quiescin sulfhydryl oxidase 2 (QSOX2) has been reported to play an important role in several biological processes, but the expression and function of QSOX2 in colorectal cancer (CRC) remains elusive.Methods: The difference of QSOX2 expression, and its relationship with clinicopathological features and prognosis in CRC, was analyzed by bioinformatic analysis and validated by clinical CRC specimen cohort. The functional characterization of QSOX2 was detected via in vitro and vivo experiments in CRC cell lines, while the potential signaling pathways were predicted by Gene Set Enrichment Analysis (GSEA).Results: Our data based on bioinformatical analysis and clinical validation demonstrated that the expression of QSOX2 in CRC tissues was significantly upregulated. Additionally, the chi-square test, logistic regression analysis, and Fisher’s exact test showed that QSOX2 overexpression was significantly correlated with advanced clinicopathological parameters, such as pathological stage and lymph node metastasis. The Kaplan–Meier curves and univariate Cox regression model showed that QSOX2 overexpression predicts poor overall survival (OS) and disease-free survival (DFS) in CRC patients. More importantly, multivariate Cox regression model showed that QSOX2 overexpression could serve as an independent factor for CRC patients. In vitro and vivo data showed that the proliferation and metastasis ability of CRC cells were suppressed on condition of QSOX2 inhibition. In addition, GSEA showed that the QSOX2 high expression phenotype has enriched multiple potential cancer-related signaling pathways.Conclusion: QSOX2 overexpression is strongly associated with malignant progression and poor oncological outcomes in CRC. QSOX2 might act as a novel biomarker for prognosis prediction and a new target for biotherapy in CRC. Colorectal cancer, including colon cancer and rectal cancer, has leaped from the third leading cause of cancer death to the second cause in the world, which poses a more serious threat to the health of the people . In the Genes that contribute to oncogenicity has the potential to be explored for identifying cancer biomarkers and discovering new drug targets . The atyin vitro and in vivo were conducted to detect the biological function of QSOX2 in cell proliferation and metastasis of CRC. Furthermore, the QSOX2-related signaling pathways involved in CRC, which may support further investigation into the molecular mechanism underlying CRC, were analyzed by GSEA and verified by GEPIA correlation analysis and Western blotting analysis. Our results demonstrated that QSOX2 can be a promising biomarker for prognosis prediction in CRC.In this study, we first evaluate the mRNA and protein expression and asses the prognostic significance of QSXO2 in CRC based on bioinformatic analysis and clinical traits. In addition, experiments 1 and TIMER2.0,2 were used to observe the expression of QSOX2 in human pan-cancer in mRNA and protein level , the random effect model was used. The results are visualized by forest plots.A search of RNA sequencing and the microarray data, which met the requirements from the Gene Expression Omnibus (GEO) dataset, was conducted, and a total of seven datasets  were obtained, including 291 adjacent non-tumor tissues (adjacent NTTs), 661 CRC tissues, and original QSOX2 mRNA expression data . The difA cohort of 568 formalin-fixed paraffin-embedded CRC cases was collected to conduct the tissue microarrays (TMAs) for IHC analysis. Details about the TMAs has been previously described . The othIHC staining was performed on TMAs consisting of 568 formalin-fixed paraffin-embedded sections following a standard streptavidin–peroxidase (SP) method that has been previously described . Anti-QSThe evaluation of the immunohistochemical reaction product has been previously described . The staTrizol reagent (Invitrogen) was used to extract the total RNA from fresh frozen CRC tumor and adjacent NCTs according to the instructions of the manufacturer, and then the Trans Script one-step guide DNA removal and complementary DNA synthesis super mix (Trans Gen Biotech) was used for the reverse transcription reaction. The sequences of all the primers amplified for quantitative real-time PCR (qRT-PCR) were listed after: 5′-TCCCTTCTTGACAACCGTGG-3′ (forward) and 5′-AAATGCTTTGTCCCCGTCCA-3′ (reverse) for QSOX2; 5′-TTTCTCTCGGCTCCCCATGT-3′ (forward) and 5′-GCTGTATATTCAGCATTGTGGG-3′ (reverse) for p21; 5′-ACGGGAGCCCTAGCCTGGAGC-3′ (forward) and 5′-TGCCCTTCTCCACCTCTTGCC-3′ (reverse) for p27; 5′-TGAGGGACGCTTTGTCTGTC-3′ (forward) and 5′-CTTCTGCTGGAAACATGCCG-3′ (reverse) for cyclin D1; 5′-TAGCTGGTCTGGCGAGGTTT-3′ (forward) and 5′-ACAGGTGGCCAACAATTCCT-3′ (reverse) for cyclin E2; 5′-AAGGTCGGAGTCAACGGATTTG-3′ (forward) and 5′-CCATGGGTGGAATCATATTGGAA-3′ (reverse) for GAPDH; 5′-ATGGAGAACTTCCAAAAGGTGG-3′ (forward) and 5′-TCAGAGTCGAAGATGGGGTAC-3′ (reverse) for CDK2; 5′-ATGGCTACCTCTCGATATGAGC-3′ (forward) and 5′-CATTGGGGACTCTCACACTCT-3′ (reverse) for CDK4.2. The small interfering RNAs (siRNAs) against human QSOX2 and non-specific siRNA used as negative controls were gained from Gene pharma Technology  and transfected into the CRC cells by SilenFect reagent . All the experiments were performed according to the protocol of the manufacturer. The sequences of siRNAs were described as follows: siQSOX2#1 sense: GCAGCCAUUACGUGGCUAUTT; siQSOX2#2 sense: GGUACGUUCACACCUUCUUTT; siCtrl sense: UUCUCCGAACGUGUCACGUTT.HCT116 and LoVo, two types of human CRC cell lines, were gained from the Chinese Academy of Sciences Cell Bank. HCT116 and LoVo were cultured in DMEM Medium and RPMI 1640 medium, respectively, both supplemented with 10% fetal bovine serum (FBS) . All cell lines were incubated in a 37°C humidified incubator with 5% CO2 for 24–48 h, the migration and invasion cells were fixed and stained before calculation. In wound healing assay, CRC cells at a density of 1 × 106 cell/well were seeded onto six-well plates and cultured to a density of about 80%. Then artificial scratches were formed by sterile 10-μl pipette tips for each well. The suspended cells were cultured in a medium with 1% FBS after washing away with PBS. An inverted light microscope  was used to photograph cell migration distance at 0 and 48 h.Transwell filter inserts with a pore size of 8 μm  were used to detect cell migration and invasion, which were carried out using invasion assay. The modified two-chamber plates were coated with Matrigel , while in the migration assay, they was not. After serum starvation overnight, cells were seeded in the top chamber accompanied by complete medium added to the bottom chambers. After incubation at 37°C with 5% CO2 for 0, 24, 48, and 72 h. At specified time-points, the cells in each well will be added to 10 μl of cell counting kit (CCK)-8 solutions  and continued to be cultured under the original conditions for 2 h. Absorbance was measured at 450 nm at the specified time-points. All experiments were performed in triplicate. For EdU (5-ethynyl-2′-deoxyuridine) assay, the cells were laid in a 96-well plate with 4,000 cells per well and cultured at 37°C in 5% CO2 for 20 h. Then, the cells were treated with 50 μmol/L of EdU assay kit  according to the protocol of the manufacturer and incubated at 37°C in 5% CO2 for 2 h. Finally, 4% paraformaldehyde was used to fix the cells for 20 min, 0.5% Triton X-100 was used to permeabilize the cells for another 20 min, 100 μl of 1 × Apollo reaction cocktail was used to incubate the cells for 30 min at room temperature.HCT116 and LoVo cells were transfected with Ctrl siRNA or QSOX2 siRNA. For cell counting kit (CCK)-8 assay, the cells were counted before laying in a 96-well plate with 2,000 cells per well and continued to be cultured at 37°C in 5% COa priori set of genes , and false discovery rate (FDR) q-value.As a computational method, the Gene Set Enrichment Analysis (GSEA) was performed to analyze the statistically significant and concordant differences between two different biological states based on of genes . AccordiProteins were extracted from HCT116 and LoVo cells with RIPA buffer  supplemented with protease inhibitor cocktail and quantified by bicinchoninic acid (BCA) analysis . The prepared protein was loaded into a 10% SDS-PAGE gel with a content of 30 μg per well, then transferred to PVDF membranes, and blocked with 5% skimmed milk. Then, the PVDF membranes were incubated at 4° with antibodies against QSOX2 , p21 , p27 , Cyclin D1 , Notch1 , GAPDH  for one night. The next day, the PVDF membranes were washed with TBST three times and then incubated with the secondary antibody for 2 h at room temperature. Finally, ECL substrate  was used to visualize the blots.6) were injected subcutaneously into the flanks of mice. From the fifth day after the injection of cells, tumor volume (V) was calculated every 3 days by the following formula: V = (long axis × short axis2)/2. The mice were sacrificed at 24 days, and the tumors were used for HE and IHC staining after dissected and weighted.The ethical approval of animal experiments was approved by the Animal Care and Use Committee of Xuzhou Medical University. Four to 6-week-old BALB/c nude mice  were obtained from the Vital River Laboratory Animal Technology Co., Ltd.  and housed under specific pathogen-free conditions. The lentiviral against human QSOX2 (shQSOX2 group) and non-specific lentiviral (shCtrl group) were transfected into HCT116 cells according to the instructions of the manufacturer. The stable HCT116 cell line including shCtrl and shQSOX2 groups were selected with puromycin and verified by Western blot. In order to construct models of xenograft tumor, 200 μl of serum-free DMEM containing groups of HCT116- shCtrl and HCT116–shQSOX2 cells (5 × 102) test was used to analyze the relationship between QSOX2 expression and clinicopathological parameters. The survival rate differences between QSOX2 high and low groups, including OS and DFS rates, was analyzed by Kaplan–Meier analysis and log rank test. The univariate Cox proportional hazard regression model combined with multivariate Cox proportional hazard regression model were used for determining the effects of QSOX2 or other clinicopathological parameters on survival. SPSS statistical software (version 23.0) and R software (version 2.15.3) were used for statistical analyses. For all tests, p < 0.05 was defined as statistically significance.The difference in QSOX2 expression between non-paired cases was tested by Wilcoxon rank-sum test, while paired cases was tested by Wilcoxon matched-pairs signed-rank test. Kruskal–Wallis test was used to analyze the differences in QSOX2 expression among multiple clinical characteristic groups. Chi-square  (p < 0.001) (p < 0.001), according to the random effects model (95% CI:0.25–0.61), the final combined SMD of QSOX2 was 0.43. The data are statistically significant, thus, suggesting that QSOX2 expression was upregulated in CRC based on the GEO database  . Finally< 0.001) . To furt< 0.001) . Additio< 0.001) . The datdatabase .p = 0.004), T classification (p < 0.001), N classification (p =0.009), and M classification (p < 0.001) (p = 0.003) and lymph node metastasis (p = 0.003). Logistic regression analysis indicated that the QSOX2 overexpression was observed to be positively correlated with pathological stage , lymph node metastasis   . To furt= 0.001) .p = 0.048), TNM stage progression (p < 0.001), tumor diameter (p = 0.017), and distant metastasis (p = 0.008). On the other hand, there was no striking relationship between QSOX2 expression and age, gender, differentiation, or depth of invasion.Consistent with the analysis results of TCGA cohort, QSOX2 mRNA expression in the CRC cohort containing 50 pairs of fresh frozen tissue specimens was also different in groups classified according to TNM stage, lymph node metastasis, depth of invasion, and distant metastasis . To furtp = 0.006), age , pathological stage , T classification , N classification , and M classification  were important risk factors for survival (p = 0.033) was an independent risk factor for survival  and DFS (p < 0.001) (p < 0.001) and DFS  in CRC patients  . To furt< 0.001) . Finallypatients .Since the results of bioinformatic analysis and clinical specimens showed that QSOX2 overexpression was associated with the malignant progression of CRC patients, we will focus on the biological function of QSOX2 in CRC. The expression of QSOX2 was reduced by small interfering RNAs (siRNAs) and detected by Western blotting and qRT-PCR analysis, respectively . Given tp-value, and FDR q-value, 15 signaling pathways enriched in the QSOX2 high group were selected, including cell cycle, homologous recombination, pyrimidine metabolism, spliceosome, purine metabolism, nucleotide excision repair, notch signaling pathway, glyoxylate, dicarboxylate metabolism, ubiquitin-mediated proteolysis, DNA replication, mTOR signaling pathway, p53 signaling pathway, ERBB signaling pathway, threonine metabolism, glycine serine, and basal transcription factors  and surgical methods. Second, the specimens used in this study were limited to one hospital, and lack of multicenter research. Finally, the deeper molecular mechanisms of QSOX2 in CRC are not detected by experiments In summary, based on bioinformatics analysis and clinical verification, our study demonstrated that QSOX2 is upregulated in CRC, and the upregulation of QSOX2 is closely correlated with clinical aggressive progression and poor survival in TCGA clinical and two independent specimen cohorts. We also found that QSOX2 facilitates the proliferation and metastasis ability of CRC cells, and these results suggest that QSOX2 plays a vital part in the initiation and progression of CRC. In conclusion, QSOX2 might act as a novel biomarker for prognosis prediction and a new target for biotherapy in CRC.https://portal.gdc.cancer.gov/.Publicly available datasets were analyzed in this study. This data can be found here: The studies involving human participants were reviewed and approved by the Ethnic Committee of the Affiliated Hospital of Xuzhou Medical University. The patients/participants provided their written informed consent to participate in this study. The animal study was reviewed and approved by the Animal Care and Use Committee of Xuzhou Medical University. All standard biosecurity and institutional safety procedures have been adhered to in all the experiment procedures in this study.in vitro. All authors have read and discussed the manuscript and agreed with the final manuscript.TJ, JS, and RW designed the study and drafted the manuscript. LZ and XL analyzed the data, prepared the figures, and they contributed equally with TJ. HS and YX collected the surgical specimens and associated clinical data. JL assisted in the IHC staining and assessment. HW and SW helped to downloading the database from TCGA and GEO. CD and LL performed the experiments 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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.