Ursolic acid (UA) is a pentacyclicterpenoid carboxylic acid that is present in a wide variety of plant foods. There are many beneficial health effects that are attributed to the properties of UA. However, the specific cellular targets of UA and the mechanism underlying downstream signal transduction processes linked to the anti‐inflammation pathway have not been thoroughly elucidated to date.Chemical biology strategies such as target fishing, click reaction synthesis of a UA probe and molecular imaging were used to identify potential target proteins of UA. Cysteinyl aspartate specific proteinase 3 (CASP3) and its downstream signaling pathway were verified as potential targets by molecular docking, intracellular enzyme activity evaluation and accurate pathway analysis. The results indicated that UA acted on CASP3, ERK1 and JNK2 targets, alleviated inflammation‐associated downstream multiple signal transduction factors, including ERK1, NF‐κB and STAT3, and exhibited anti‐inflammation activities.As a natural dietary supplement, UA demonstrated anti‐inflammation activity via inhibition of CASP3 and shows the potential to improve the therapy effect of several inflammation‐associated diseases. Given the rapid advances in chemical biology, effective chemical proteinomics methods have opened new avenues to probe compound‐target interactions. A Fishing‐rod strategy has been applied to verify that the target of indomethacin is GLO1 and that the anti‐inflammatory effects of the indomethacin were related to inhibition of GLO1 enzyme activity.In this study, we employed chemical biology methods to prepare a UA probe used for target capture from BEAS‐2B cells. Subsequently, molecule docking, cell co‐localization and downstream signaling pathway evaluation were applied to verify the key target. The results of the biochemical analysis and molecular biological detection methods demonstrated that UA affects the action of cysteinyl aspartate specific proteinase 3 (CASP3) on the MAPK signaling pathway, regulates STAT3 and NF‐κB transcription, and alleviates the inflammation‐associated transduction process.22.13‐tag (3‐azido‐7‐hydroxy‐2H‐chromen‐2‐one) was delegated to Wuxi App Tec . Fe3O4 amino magnetic microspheres (MMs) were purchased from Tianjin baseline Chromtech Research Center . Human TNF‐α was purchased from PeproTech . The NF‐κB luciferase reporter plasmid pGL4.32 and Renilla luciferase reporter vector plasmid pRL‐TK were obtained from Promega . The transfection reagent Lipofectamine 2000 was obtained from Invitrogen . Primary antibodies ERK1/2, JNK1/2, CASP3, NF‐κB (p65), STAT3, PARP, β‐actin, p‐STAT3S727, p‐ERK1/2, p‐JNK and secondary antibodies were purchased from Cell Signaling Technology . Fluorescent‐labeled anti‐rabbit IgG secondary antibodies were purchased from Abcam . Chemiluminescent HRP substrates were purchased from Millipore Corporation . CASP3 inhibitor Q‐VD‐Oph was purchased from Selleckchem . All cell culture reagents were purchased from Gibco BRL Life Technologies . All other chemicals and solvents used were of analytical grade.UA  and N, N‐Diisopropylethylamine (DIPEA) were purchased from Aladdin . Sodium1‐((3‐((4‐azidophenyl) disulfanyl) propanoyl) oxy)‐2, 5‐dioxopyrrolidine‐3‐sulfonate (Sulfo‐SADP) was purchased from Bioworld . The synthesis of N2.22 atmosphere in a humidified incubator. All cells were used at ≈75% confluency (cell density) in 6‐well plates or 25 cm2 culture flasks for western blot analysis and ≈60% confluency in 20 mm culture dish for immunocytochemical analysis.BEAS‐2B cell line, derived from human bronchial epithelial cells, was cultured in Dulbecco's Modified Eagle's medium 1640 medium supplemented with 10% fetal bovine serum. Chinese hamster ovary (CHO) cells were cultured in Dulbecco's Modified Eagle's medium/F12 supplemented with 10% fetal bovine serum. All cells were obtained from the American Type Culture Collection  and incubated at 37 °C in a 5% CO2.3Oxalyl chloride  was added dropwise to a solution of UA  in 10 mL of anhydrous dichloromethane. The mixture was stirred under argon at room temperature for 6 h. Subsequently, the solvent was evaporated under reduced pressure to afford the crude intermediate as a white solid. This crude product and mono‐propargylamine  were then dissolved in 10 mL of anhydrous dichloromethane and stirred at room temperature for 4 h. The mixture was concentrated in vacuo and purified by column chromatography on silica gel (dichloromethane: methanol = 30:1) to obtain alkynyl‐modified UA probe as a white solid. The yield of this reaction was 56% (179.6 mg). The detailed NMR data are described in the supporting information.2.4−5 mmol L−1 alkynyl‐modified UA probe for 6 h. BEAS‐2B cells were washed with PBS and fixed using 4% paraformaldehyde for 30 min and later treated with a 100 μL reaction solution . After 1 h incubation, the cells were washed with PBST. The fluorescence images were obtained with a confocal microscope . The excitation and emission wavelengths employed were 365 and 470 nm, respectively.BEAS‐2B cells were cultured in 20 mm culture dish with or without 102.52‐MMs (5 mg mL−1) was suspended in 5 mL borate buffer and Sulfo‐SADP  was added; then the mixture was reacted at room temperature for 12 h. Subsequently, the azide modified‐MMs were enriched via magnetic separation and first washed three times with water followed by three washes with methanol, respectively. The azide modified‐MMs were collected and used directly for the subsequent steps. CuBr  was dissolved in degassed methanol (3 mL) under argon atmosphere and DIPEA  was added. The resulting blue suspension was degassed for 30 min under a stream of argon in the dark. Alkynyl‐modified UA  was dissolved in degassed methanol (0.5 mL) and treated with 1 mL of the freshly prepared suspension of CuBr‐DIPEA and azide modified‐MMs . The reaction mixture was shaken at room temperature in the dark for 24 h. Next, the UA‐modified functionalized MMs were separated with a magnet and washed with methanol and water. The enriched MMs were reduced by DL‐ DTT (100 mmol L−1) and the released UA derivative was analyzed by LC‐MS . The details of UA‐modified functionalized MMs are shown in the supporting information.A total of 1 mL NH2.6http://59.78.96.61/phammapper) for target prediction. The pathways were carried out through KEGG . The interaction of proteins was analyzed using String9.1 (http://www.string-db.org/). The 3D structures of potential protein targets were obtained from the Protein Data Bank (http://www.rcsb.org/pdb). The structure of the molecules and potential targets were constructed and minimized using the SYBYL software , then, AutoDock version4.2  was applied for the docking study using a hybrid Lamarckian genetic algorithm (LGA). The number of LGA runs was set to 30. The step size parameters of quaternion and torsion were 30. In addition, a Molecular Operating Environment (MOE 2015.10) was also used for molecular docking. The triangle matcher algorithm of the MOE software packages was selected to dock the identified compounds into the protein active site. The scoring function must comply with the following parameters: (i) specifying ASE Scoring to rank the poses output by the placement stage; (ii) specifying Forcefield Refinement to relax the poses; (iii) specifying Affinity dG Scoring to rank the poses using the refinement stage. The free energy of binding was calculated from the contributions of the hydrophobic, ionic, hydrogen bond, and van der Waals interactions between the protein and the ligand, intramolecular hydrogen bonds and strains of the ligand. We observed that the docking poses were ranked by the binding free energy calculation in the S field.The three‐dimensional (3D) structure of UA was put into the PharmMapper database  for 30 min at 4 °C and collected with a cell scraper. The lysate was centrifuged and the protein content of the supernatant was quantified with a BCA protein assay kit . The UA‐modified functionalized MMs were added to the lysate and incubated for 10 h at 4 °C. The MMs were collected by magnetic separation and rinsed three times with precooled PBS. Bound proteins were released with 200 μL DTT (100 mmol L−1) at 4 °C for 30 min and the supernatants were collected for SDS‐PAGE.BEAS‐2B cells were plated in 25 cm2.8−5mmol L−1 alkynyl‐UA probe for 6 h. After washing with PBS, the cells were fixed with 4% paraformaldehyde for 15 min, and washed with PBS. After blocking with 10% goat serum for 1 h, cells were incubated with rabbit against CASP3 polyclonal antibodies (1:1000) overnight at 4 °C. After washing with PBST, anti‐rabbit secondary cy3 antibodies (1:1000) were added for 1 h at room temperature. After washed, the fixed cells were carried to the click chemistry reaction of N3‐tag according to the previously described bioorthogonal conditions. All fluorescence images were obtained with a confocal microscope. The excitation and emission wavelengths of Cy3 employed were 590 and 617 nm, respectively.BEAS‐2B cells were cultured in 20 mm culture dish. When cells reached approximately 60% confluence, they were treated with 102.9−1 TNF‐α stimulation and UA treatment, the levels of activity of CASP3 in the cell lysates were measured using commercial CASP3 activity kits  according to the manufacturer's instructions. The absorbance values were determined at 405 nm using a BioTek ELx800 microplate reader . CASP3 activity was expressed as the fold change in enzyme activity compared to the control group.After 20 ng mL2.10−1) for 6 h, and subsequently carried for the observation of NF‐κB (p65) and STAT3 nucleus translocation. The cells were washed three times with PBST, fixed in 4% paraformaldehyde for 15 min, then permeabilized with 0.1% Triton X‐100 for 5 min. After the permeabilization, the samples were washed with PBST adequately, and blocked in 10% goat serum for 1 h at room temperature. The cells were then sequentially incubated with anti‐NF‐κB p65 antibody (1:400) or anti‐P‐STAT3S727 antibody (1:500) overnight at 4 °C. On the next day, the cells were probed with an Alexa Fluor 594‐conjugated anti‐rabbit antibody (1:500) at room temperature for 1 h, then washed with PBST adequately. Additionally, the DAPI Fluoromount‐G was added for 5 min to stain the nuclei. Images were captured with a confocal microscope .BEAS‐2B cells were grown in 20 mm culture dish for 24 h and pretreated with drugs (UA or Q‐VD‐Oph) for 6 h. Then the cells were treated with TNF‐α  overnight at 4 °C. Membranes were rinsed with PBST three times, and then incubated with secondary antibody (1:1000) at room temperature for 1 h. Membranes were washed, incubated with chemiluminescent HRP substrates and exposed in a FluorChem E imager .2.12t‐test. p< 0.05 was considered to indicate significant differences. All data were processed using the GraphPad Prism statistical software, version 5.01.The results are expressed as the mean ± standard deviation (SD). Multiple comparisons were performed using an analysis of variance (ANOVA), followed by Bonferroni's post hoc test. For single comparisons, significant differences between the means were determined using Student's 33.1Figure3‐tag (group 2) were used to compare with the fluorescence intensity of the click product . As expected, the click product showed strong fluorescence, while the two substrates (groups 1 and 2) showed almost no fluorescence. The excitation and emission wavelengths of the click product were 365 and 470 nm, respectively  were analyzed using bioinformatics tools. As shown in 3.3To evaluate the collecting efficiency, SDS‐PAGE was performed, and proteins were detected using Coomassie Brilliant Blue Figure B. The re−1 UA.To verify the result of the above fishing‐rod strategy, the co‐localization of CASP3 and UA probe was investigated. As shown in Figure 3.4−1) was lower than that of Q‐VD‐Oph , and these findings were verified by the results of an enzyme activity detection kit. This technique indicated that hybrid Lamarckian genetic algorithm has a high probability to generate realistic‐binding poses. We then analyzed the top scoring poses of UA in all cases, which are displayed as 3D maps  using MOE software. We found that the binding energy of UA  and a histidine residue (His‐121) that act to stabilize the peptide bond cleavage of the target protein sequence to the carboxy‐terminal side of an aspartic acid when it is part of a particular 4‐amino acid sequence (Asp‐x‐x‐Asp).FigureAs we know, CASP3 can cleave MEKK1, then active Raf, and subsequent MAPK pathway involved in the signaling pathways that are associated with inflammation.Currently, there is a concern surrounding the use of natural compounds or products as daily dietary nutrition to prevent chronic inflammatory diseases. Moreover, daily supplements of UA have been shown to be safe and lead to a reduced risk of chronic inflammatory diseases. UA improves therapies for inflammation and inflammatory diseases, including cancer, type 2 diabetes mellitus and associated complications. Our findings suggest that the anti‐inflammatory effect of UA is due to the reduced expression of cytokines and alleviation inflammatory disorders via inhibition of CASP3. However, the targets of other effects, including improved type 2 diabetes mellitus, were not found in this study, and the identification of these targets requires further study. In summary, these results provide an increased understanding of UA, particularly regarding the molecular mechanism of anti‐inflammation as well as demonstrating the potential of UA as a therapeutic for the treatment of inflammation‐associated diseases.CASP3cysteinyl aspartate specific proteinase 3DIPEA, NN‐DiisopropylethylamineMMsmagnetic microspheresPARPpoly ADP‐ribose polymeraseUAursolic acidThe authors have declared no conflicts of interest.Supporting InformationClick here for additional data file.


Human T-cell leukemia virus-1 (HTLV-1) is the first pathogenic human retrovirus identified in 1979 by the Gallo group. HTLV-1 causes fatal T-cell leukemia (adult T cell leukemia) and a progressive myelopahy  and other disorders. Since the discovery of HTLV-1, several other microorganisms are demonstrated to cause cancer in humans. In this article, we investigated the oncogenic capacity of HTLV-1, in comparison with those of other oncoviruses and one oncobacterium  based on published literature. We conclude here that HTLV-1 is one of the most and may be the most carcinogenic among them and arguably one of the most potent of the known human carcinogens. This fact has not been noted before and is particularly important to justify why we need to study HTLV-1 as an important model of human viral oncogenesis. At the time of discovery of HTLV-1 , the incidence of nasopharyngeal carcinoma in association with EBV is at best 0.05% or less. Numbers for endemic Burkitt's lymphoma is more imprecise but estimated as 3~4/100,000 among Ugandan children  and a more special and very atypical form of lymphoma in collaboration with HIV, HHV-8 is very minimally oncogenic in the absence of HIV. We also note that in most of primary effusion lymphoma cases associated with HHV-8, EBV is detected along with HHV-8, another support that HHV-8 is not potently oncogenic on its own . That said, one study estimates that the HCC develops in 1~3% of HCV infected persons after 30 years and the mechanisms are obscure  Epidemiology studies  reported that gastric cancer develops in approximately 3% of H. pylori-infected patients, compared to none of the uninfected patients , a coalition of virologists on a global scale, as the result of the vote (16 vs. 5) supported the original name “leukemia”. Another vote conducted at the 18th International HTLV-1 meeting  again showed majority support (78 vs. 26) on the “leukemia” name. We believe that this most carcinogenic virus deserves the “leukemia” name.In summary, we note here that HTLV-1 is one of the most oncogenic entities known among human viruses and even among most known human carcinogens. The oncogenic mechanism of HTLV-1 is more direct compared with other entities and to date there is no evidence for any particular co-factor requirement. This striking characteristic of HTLV-1 seems overlooked because of its low prevalence in the U.S. and Europe. As discussed in an accompanying paper, we propose to revert the name of HTLV-1 back to the original, Human T-cell leukemia virus. This is also supported by a recent survey among 21 HTLV-1 experts from all over the world who belong to the HTLV-1 task-force of the Global Virus Network (GVN, YT and RG conceptualized the idea, conducted literature search and investigation, and wrote the manuscript.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.


This showed 22/113 (19.5%) of LBC’s from HIV+ve patients were positive for HTLV-1 compared to 4/111 (3.6%) of those from HIV−ve women  = 6.42 (2.07–26.56)). Only 1/37 (2.7%) of HIV+ve and none of the 44 HIV−ve ICC samples were positive for HTLV-1. There was also a significant correlation between HTLV-1 infection, numbers of sexual partners (p < 0.05) and smoking (p < 0.01). Using this unique method, these data suggest an unexpectedly high prevalence of HTLV-1 DNA in HIV+ve women in this geographical location. However, the low level of HTLV-1 detected in HIV+ve ICC samples was unexpected and the reasons for this are unclear.The oncogenic retrovirus human T-cell lymphotropic virus type 1 (HTLV-1) is endemic in some countries although its prevalence and relationship with other sexually transmitted infections in Sub-Saharan Africa is largely unknown. A novel endpoint PCR method was used to analyse the prevalence of HTLV-1 proviral DNA in genomic DNA extracted from liquid based cytology (LBC) cervical smears and invasive cervical carcinomas (ICCs) obtained from human immunodeficiency virus-positive (HIV+ve) and HIV-negative (HIV−ve) Kenyan women. Patient sociodemographic details were recorded by structured questionnaire and these data analysed with respect to HIV status, human papillomavirus (HPV) type (Papilocheck Human T-cell lymphotropic virus type 1 (HTLV-1) was the first pathogenic human retrovirus to be discovered and is known to be associated with various mild to severe pathologies resulting from chronic lifelong infection ,3,4. It Although HTLV-1 is reported to currently infect between 10 and 25 million people globally, the true prevalence in different geographical regions of the world is largely unknown ,7,10,11.Both HIV and HTLV-1 share similar risk factors since they are both transmitted through sexual contact, blood transfusion, sharing of needles among intravenous drug users and vertical transmission from mother to child via breast-feeding, ,10,16,17During the past 20 years, HIV type 1 (HIV-1)/HTLV-1 co-infection has emerged as a global health problem with increasing numbers of cases in South America and Africa . AlthougSeveral previous studies have attempted to link HTLV-1 infection with the aetiology of ICC and have produced inconsistent findings. For example, a study carried out in Yucatan (Mexico) where HTLV-1 prevalence is low but the incidence of ICC is high, found no statistical difference between these two groups . HoweverIn light of these previous observations, the objective of the current study was to evaluate the prevalence of HTLV-1 proviral DNA extracted from liquid based cytology (LBC) specimens from HIV positive and negative patients attending specialist referral clinics in Kenyatta National Hospital in Nairobi, Kenya. The same analysis was carried out on DNA extracted from biopsies obtained from patients with ICC in the same hospital.A cross-sectional study was carried out among women attending Kenyatta National Hospital (KNH), Nairobi, Kenya. Consecutive female patients attending a Specialist HIV Clinic and Family Planning Clinic were recruited between April 2008 and February 2009. Women aged between 21 and 52 years were included, while those who had prior destructive procedures for cervical disease and/or hysterectomy were excluded. A total of 224 patients were recruited, including 111 HIV negative  and 113 HIV positive  with 56 of these in receipt of highly active antiretroviral therapy (HAART). After undergoing voluntary counselling and testing for HIV, a structured questionnaire was administered and a blood sample was collected. During the same period, 37 HIV positive and 40 HIV negative women newly diagnosed with ICC at KNH were also randomly recruited. They underwent examination under anaesthesia (EUA), a biopsy was taken which was then formalin-fixed and paraffin-embedded (FFPE). FFPE samples were used for histopathology and DNA extractions.This study was approved by the Kenyatta National Hospital’s Ethics and Research Board (ERB), the University of Nairobi (No KNH-ERC/01/4988) and the University of Manchester, Oldham Research Ethics Committee amendment 5 project 07/Q1405/14. All patients gave written informed consent.All patients were examined with a speculum and cervical samples collected using a cervex brush, which was stirred into a vial of PreservCyt® transport solution . Cytology slides were prepared using a Cellspin Cytocentrifuge,  and were stained with Papanicolaou (pap) stain. All pap stained slides were independently examined by two different pathologists and the Bethesda 2001 criteria were used for slide interpretation .® test kit , and, if positive, this was confirmed by Uni-Gold® .HIV testing was done using Determine® M48  as described by the manufacturer. Approximately 4 × 10 µm FFPE ICC sections were used for DNA extraction using the Qiagen Qiacube®  according to the manufacturer’s instructions.All residual PreserveCyt® material was used for automated DNA extraction using BioRobot® test  as per the manufacturer’s instructions. This identifies 24 different HPV genotypes: six low-risk HPV types  and 18 high-risk HPV types .DNA was quantified using a Nanodrop UV spectrophotometer  and used for HPV genotyping with the PapilloCheck2. HTLV-1 Tax PCRs were optimized using a multiplex PCR kit (Qiagen) as recommended by the manufacturer. All reactions were carried out in duplicate, using a Veriti™ Thermal Cycler  with the conditions and primers indicated in GAPDH PCR was performed to assess the quality of input DNA using a 50 µL reaction mixture containing 2 µL of each DNA sample (50 ng), 2.5 units of BioTaq DNA polymerase , 0.2 mM dNTPs, and 0.2 µM of each primer in 10 mM Tris-HCl pH 8.3, 50 mM KCl and 2.5 mM MgClThe gel-separated DNA bands were excised, isolated, purified and sequenced using an ABI BigDye Cycle sequencing kit  as indicated by the manufacturer and a 3100 ABI sequencer .p-value of less than 0.05 was considered statistically significant.The data were captured in an Access database and exported to SPSS version 16.0 for analysis after cleaning and validation. Statistical tests of significance were done using Pearson’s chi-square with Yates correction or with Fisher’s test if the expected frequencies were less than five. Odds ratio (OR), adjusted OR (AOR) and the 95% confidence intervals (CI) were used to measure strengths of associations. Further, cross-tabulations were also used to assess the distribution between HTLV-1 and HIV status of the participants, and the 95% CI around the prevalence of virus infection was computed using R program version 3.2.2 package binom. A As indicated, PCR of glyceraldehyde 3-phosphate dehydrogenase (GAPDH) with GAPDH specific primers was used to assess the quality and integrity of all DNA samples prior to these being used for unknown test PCR’s with Tax specific primers as illustrated in As illustrated in The specificity of the single Tax amplimer product was confirmed by excision and DNA sequencing of the 264-bp PCR product and the identity verified by the use of National Center for Biotechnology Information (NCBI) Basic Local Alignment Search Tool (BLAST) .The HTLV-1 prevalence was four out of 111 (3.6%) (95% CI: 0.9%–8.9%) in HIV negative women, which indicates that the frequency of HTLV-1 infection is >5 times higher in HIV positive than negative patients, indicating that HTLV-1 infection is significantly associated with a HIV positive status (p = 0.231 using Pearson’s chi-square with Yates correction). Nevertheless, it was noted that all the HTLV-1 infections were in normal/LSIL and none were found in HSIL/ASCUS   clinical staging system, the 113 HIV positives were classified as stage I–IV, consisting of stage I in 24, II in 16, III in 38 and IV in 35 patients. There was no statistical significance between HTLV-1 positive and HIV clinical stages. Additionally, HTLV-1 positivity was not associated with increasing advancement of HIV disease or use of HAART (.05) See . WHO gui® system. Of the samples analysed, one sample had an invalid result, while 121  had at least one HPV subtype with the highest number of genotypes detected in any one individual being seven, covering 107 HR  and 14 LR  HPV subtypes. None of the HPV subtypes covered showed any association with HTLV-1 apart from HPV type 53 where there was a significant positive association (p < 0.05)  and 18 high-risk (HR) were identified in LBC specimens using the Papillocheck < 0.05) .LBC material for this study was obtained from women with an age range of 21 to 52 years and median or mean ages of 35 or 35.2 years, respectively. The median age of HTLV-1 negatives was 35 and HTLV-1 positives 31 years with no significant difference observed between the median age of HTLV-1 positives with respect to either HPV or HIV status . Within Among the 77 ICC study subjects, the median and mean ages were 42 and 44 years, respectively, with a range of 27–68 years. Any association between HTLV-1 infection and age could not be calculated since only one ICC sample was positive.Analysis of the relationship between HTLV-1 infection and patient’s life style shown in HTLV-1 DNA was only detected in one out of 77 ICC biopsies, of which 37 were HIV positive see . This eqAlthough HTLV-1 was discovered 35 years ago, information on its prevalence and associated risk factors in Sub-Saharan Africa countries have remained poorly defined. HIV, HTLV-1 and HPV can share the same sexual route of transmission and, to our knowledge, this is the first study carried out in Kenya to analyse the prevalence of HTLV-1 in LBC cervical specimens and formalin fixed and paraffin-embedded (FFPE) ICC biopsies from HIV positive and negative women. The most significant observation was the high prevalence of HTLV-1 proviral DNA found in LBC samples from HIV positive women, consistent with previous work carried out in Guinea-Bissau, showing that HIV infection is a potential risk factor for acquiring HTLV-1 . MoreoveA limitation of the current study is the lack of corroborating serological data on HTLV-1 prevalence. Although the PCR method is sensitive, it is very clear this may underestimate the true prevalence since it depends on the inclusion of sufficient numbers of infected cells in extracted material. Indeed, this could also provide an alternative explanation for the lower detection of HTLV-1 DNA found in ICC samples. However, another possibility is that HTLV-1 could suppress HPV mediated cervical carcinogenesis in HIV positive women, which raises the question: is there a potential mechanism for such an effect? Both HIV and HTLV-1 infect CD4+ cells and it has been previously shown that elevated numbers of CD4+ cells are associated with HPV-related dysplasia ,36,37. Mp = 0.01) but no associations were observed with any of the other cancers studied.With regard to other cancers, a protective role for HTLV-1 is not without precedent. Hirata et al. evaluated the relationship between HTLV-1 infection and the occurrence of several types of cancers namely biliary tract, pancreatic, esophageal, gastric, colorectal, liver, and lung cancers using logistic regression analysis adjusted for age and sex . CuriousAnother important question raised by the current study is that, given the high prevalence of HTLV-1 in HIV positive Kenyan women, is there a correspondingly higher incidence of HTLV-1 related pathologies in these women as observed in Japan ? HoweverOther noteworthy finding from our study was the significant association between HTLV-1 infection and increased numbers of direct and indirect sexual contacts in addition to smoking. Given that smoking is known to impair the function of cervical Langerhans cells, it is possible that the increased incidence of HTLV-1 in smokers could be related to impaired local immunity which contributes to increased rates of sexual transmission of the virus .In summary, it is known that the influence of HIV infection on the incidence of HPV related ICC seems to vary depending on the geographical location of the study . For exaAs discussed, there is a paucity of epidemiological data on HTLV-1 in Sub-Saharan Africa, which also bears the heaviest global HIV burden. The HTLV-1 prevalence found in LBC samples from HIV positive women (20.4%) suggests this could be higher than anticipated reinforcing the finding that Kenya may be endemic for HTLV-1 and also confirming the association between HTLV-1 and HIV. Clearly, there is an urgent need to conduct larger population based studies and to institute public health measures to curb the continued spread of HTLV-1. For example, addressing the issue of vertical transmission through breast-feeding (by considering safe replacement feeds for those whose mothers are carriers), increased condom use to curb sexual transmission and provision of universal HTLV-1 screening on all blood donations, tissue and organ donors. Currently, routine HTLV-1 screening is not carried out in most African countries including Kenya—a gap which may be promoting the spread of this virus. Furthermore, there is no curative treatment for HTLV-1 or its associated pathologies and an effective vaccine is equally unavailable which puts a heavy social and financial burden on sufferers, their families and the healthcare systems. Thus, public health interventions aimed at counselling and educating high-risk individuals and the public are of critical significance .


A country’s total fertility rate (TFR) depends on many factors. Attributing changes in TFR to changes of policy is difficult, as they could easily be correlated with changes in the unmeasured drivers of TFR. A case in point is Australia where both pronatalist effort and TFR increased in lock step from 2001 to 2008 and then decreased. The global financial crisis or other unobserved confounders might explain both the reducing TFR and pronatalist incentives after 2008. Therefore, it is difficult to estimate causal effects of policy using econometric techniques. The aim of this study is to instead look at the structure of the population to identify which subgroups most influence TFR. Specifically, we build a stochastic model relating TFR to the fertility rates of various subgroups and calculate elasticity of TFR with respect to each rate. For each subgroup, the ratio of its elasticity to its group size is used to evaluate the subgroup’s potential cost effectiveness as a pronatalist target. In addition, we measure the historical stability of group fertility rates, which measures propensity to change. Groups with a high effectiveness ratio and also high propensity to change are natural policy targets. We applied this new method to Australian data on fertility rates broken down by parity, age and marital status. The results show that targeting parity 3+ is more cost-effective than lower parities. This study contributes to the literature on pronatalist policies by investigating the targeting of policies, and generates important implications for formulating cost-effective policies. After a prolonged post-war fertility decline, many developed countries saw a recovery of fertility in the 1990s to early 2000s. Some of these countries introduced pronatalist incentives over the same period. Were these effective? Perhaps fertility would have recovered anyway even without policy intervention. Various alternative explanations of fertility recovery have been identified in the literature, including: tempo distortion ; economiendogenous. As just one example, in 2010 Japan introduced the universal child benefit but abolished it two years later, due to the financial effects of the 2011 tsunami [The key problem in estimating the effect of pronatalist policy on fertility is that other factors can drive them both, giving the illusion of causation. Economists would say that the policy change is  tsunami ,6. The r tsunami . A more In Australia, a strong pronatalist narrative began around 1995, presaging the introduction of the 1996 maternity allowance and increasing benefits over the ensuing 12 years. Existing studies suggest that the policies had a small positive impact on fertility in Australia, while being very costly –13. ThesFrejka  examinedNotwithstanding the difficulties of endogeneity, empirical studies suggest that policies had heterogeneous impacts on different population subgroups, especially groups defined by parity. In Hungary, child-related benefits had a positive effect on second and third births . Child aHow can we identify groups whose targeting will influence TFR in a cost effective way i.e. groups that give the largest “bang per buck” ? In the The plan of the paper is as follows. We begin by giving a brief history of pronatalist policies in Australia, since Australian data is used to illustrate the method. This data is broken down by mother’s age, marital status and parity, which has not been available previously. To estimate the impact of group fertility rate on TFR, we construct a simple stochastic model for TFR and calculate the elasticity with respect to each group fertility rate. We measure the likely changes in fertility rates of each group from their historical trends. Based on all this information, we calculate the benefit-cost ratio for targeting each group. A comparison of the benefit-cost ratio is made to provide a benchmark for policy makers to evaluate the cost-effectiveness of pronatalist programs.Faced with declining fertility in the 1990s, the Australian Government reintroduced the maternity allowance, a means-tested lump-sum payment of AUD$840 per child. The Child Care Benefit was introduced in 2000, whereby families that passed a means test could receive an hour rate up to 50 hours per week. In 2002, the First Child Tax Refund was available to parents following the birth of the first child and the payment amount depended on the income of the primary carer . Set agaThe untargeted nature of the Baby Bonus invited criticism ,13,29 anBudgetary limitations, especially after the recent financial crisis, call for a targeted policy which can cost-effectively influence the fertility rate. How do targeted policies fit with the changing childbearing patterns and age-parity composition of the female population in Australia? Unlike previous research, most of which directly examined the apparent impact of pronatalist actions, this study will try to explore the potential targeting of policies.Motivated by the cited research of Kippen  and ParrTo estimate group-specific fertility rates, we required the number of women in the population and the number of babies born, broken down by age, marital status and parity. Such data were not publically available, though recorded. The female population data were obtained from National Information Consultancy Services of the Australia Bureau of Statistics (ABS) for the census years 1996, 2006 and 2011. Based on censuses, numbers of female residents in Australia are cross-classified by marital status, 5-year age-groups and the number of children ever born (from 0 up to 6+). As parity information was not recorded in the 2001 census, the year 2001 is not included in the analysis.The national birth data was provided by the demography section of New South Wales section of ABS Information Consultancy Services. All recorded births in the years 1997, 2007, 2012 (i.e. one year later than the census data) are classified by marital status, 5-year age-groups and birth order . Instead of using the number of mothers giving birth, the number of babies is used in each cross-category (the difference between the two being attributed to multiple births), as this reflects actual rather than intended fertility rates. Though the data are of generally high quality, some data cleaning and adjustments were necessary and details are in The stochastic model we develop also requires age-specific marriage and divorce rates. The marriage rates are calculated by dividing registered marriages (including remarriages) by the number of unmarried females, broken down by 5-year age group. Age-specific marriage rates for 1997 were extracted directly from the Marriages and Divorces 1998 report. The numbers of marriages for 2007 and 2012 were provided by ABS. The age-specific divorce rates (the number of divorces per 1000 married women) for years 1996, 2006, and 2011, were extracted from ABS report 3310.0 Marriages and Divorces, Australia, 2012.A stochastic model is constructed for TFR, which tracks transitions in marital status and parity of women over her reproductive life. Unlike many Asian countries, marriage in Australia is not a social prerequisite to childbearing, and out-of-wedlock births currently account for 35% of all births  but lessA Markov chain is used to model the transition dynamics. Marital status has two states, namely unmarried  and married; parity has five states, namely 0 to 4+. Several simplifying assumptions are made: one woman can give birth to one child at most each year, but an appropriate adjustment is made to take account of multiple births; marriage (or divorce) and childbirth do not happen in the same year; the fertility rates of the remarried and first-married women are the same.nm denoting the probability of an unmarried woman marrying at age n and nd the probability of a married woman divorcing at age n. Horizontal arrows represent parity transitions. For married women, the probability of having a jth child at age n in a given year is denoted by pm,n(j) j = 1,…,4 and for unmarried women by pu,n(j). Together with the probabilities of marriage and divorce, there are 2+4+4 = 10 parameters governing transitions at any age. As women’s age is categorized into seven 5-year age groups (covering age 15–49), there are 10×7 = 70 parameters in all.θ1,…,θ70 denote the 70 marriage, divorce and group fertility parameters in the transition model, TFR is a function of these parameters.Based on this model, it is possible to write down an expression for the TFR in terms of these parameters. The formula is expressed in matrix notation  is a very complex function, derivatives are computed in Matlab. The focus of the analysis is on the 56 fertility parameters rather than the marriage and divorce rates. It should be emphasized that elasticity is more meaningful than a raw partial derivative, as the former consider the proportional change of the parameter rather than an absolute change. For example, the fertility rate for parity 2 of the 45–49 year-old unmarried women is at the level of 0.001 children per woman, so it is more reasonable to assume 1% increase than an absolute increase of 0.1 child per woman for this group.Elasticity, a concept in economics, is a measure of the percentage change of quantity demanded per 1% change in the price. Analogously, the elasticity of TFR with respect to parameter ηJ measures the change in TFR for a 1% change in the fertility rate of group J. But to compare different groups in their influence on TFR, we should try to estimate effect of a likely change in group fertility, rather than that induced by the same hypothetical change of 1% for each group.The fertility elasticity coefficient of variation (CV). The likely change in TFR from targeting group J is then estimated by multiplying the elasticity ηJ by the coefficient of variation CVJ. Therefore, the likely impact would be ηJ×CVJ.This is the only part of the methodology that requires historical rather than current data. By looking at historical variations in group fertility rates, we might estimate plausible future changes in these rates. In this paper, we will use a rather crude measure, namely the historical variability of each group fertility rate, for the current application across four time points 1997, 2002, 2007 and 2012. And since elasticity is concerned with proportional changes, it makes sense to measure variability in proportional terms i.e. to use the In using CVs of historical group fertility rates as a measure for their propensity to change, we are ignoring the direction of the historical variations. The implicit argument then is that if group fertility rates are increasing over time, policy might help facilitate this trend; if they are decreasing over time then policy might reverse that trend. This is indeed the typical purpose of pronatalist policy. Other more sophisticated measures for the propensity to change might be considered in future work.per child, it would be reasonable to argue that the cost of a policy for a particular group is proportional to the number of babies born in that group, which we denote by BJ.While it is not feasible to put a dollar value on marginal increases in fertility, it is practically important to compare the effect of pronatalist policies to their cost. The monetary cost of a pronatalist program is hard to measure, and depends on the details of the program. However, as the vast majority of such programs deliver benefits ηJ×CVJ/BJ. Since here we do not put a dollar value on likely impact on TFR (measured by ηJ×CVJ) and policy costs are only proportional to BJ, these ratios are on an arbitrary scale. Largely for cosmetic reasons, we do not use the absolute number of babies born to a certain group (i.e. BJ) but the proportion of babies in this group to the overall number of babies–denoted by bJ (= JB/∑JB).Different subgroups can be compared in their cost-effectiveness, via the ratio Fertility rates for all subgroups by marital status, age-group and parity  for the years 1996/1997, 2006/2007, and 2011/2012 were calculated and are displayed in There have been changes over time. Nearly all rates increased from 1997 to 2007, a period where the economy was prospering and pronatalist policy was introduced and strengthened . And oveJ, computed using Matlab, with respect to 70 parameters for the year 2012 only. Details of the elasticity calculations can be found in Here the focus is on the elasticities with respect to the 56 subgroup fertility rates. To visualize the pattern of elasticities, J of each group fertility rate over the four time periods using the same color scale as J×CVJ which measures the % change in TFR for a likely % change in the group fertility rate, rather than an arbitrary 1% change. The most influential groups are 35–39 year-old married women at parity 3 and parity 2. For unmarried mothers, the most influential segments are first births for mothers under 30, and second and third births for older mothers aged 25–39. If we imagine a completely untargeted pronatalist policy such as the universal Baby Bonus in Australia, the greener cells would tend to contribute more to any increase in TFR.In There are some important differences between Tables J×CVJ in J in each group. Those with relatively higher benefit-cost ratios are the oldest age-groups and those unmarried (aged over 30) at higher parities.As policies usually target parity, rather than the age or marital status of women, we calculated the benefit cost ratio for groups by parity. To do this, for each parity we divided the accumulation of the likely impact in Estimating the causal effects of pronatalist policy on TFR is difficult because policy changes are often endogenous. For instance, a positive national stance towards population growth may easily lead to both pronatalist incentives and increases in TFR that would have occurred anyway. So, policy effects tend to be over-estimated. At the same time, there is concern about the cost effectiveness of policy, which has motivated many countries to shift towards more targeted incentives. This highlights the need for research on how the TFR can be influenced in a cost-effective way. To fill this gap, this paper has made several contributions.We suggest a new method for identifying population subgroups that are better targets of pronatalist policy. It involves measuring three factors: (1) the sensitivity of TFR to changes in group fertility rates, (2) the propensity of each group fertility to change and (3) the total cost of the policy for that group. Our final measure is (1)×(2)/(3). Only mother and birth count data by group and minimal time series data is required. Modelling of causality is side-stepped by focusing on the structure of the population. In our illustration, groups are defined by age, marital status and parity of the mother and we used data at three time points. This level of data has not been previously available in Australia.To measure the sensitivity of TFR to changes in group fertility rates, we built a parity transition model that relates TFR to group fertility rates (as well as marriage and divorce rates) and calculated fertility elasticity which is originally an economic concept. It measures the percentage change in the TFR given 1% change in a certain group’s fertility rate and automatically takes account of the size and fertility rate of the group. However, it might reasonably be argued that changes in parity specific fertility rates could affect the timing of childbearing rather than desired family size. This is true in principle and if a particular parity fertility rate increased then later parity rates might decrease in response. The magnitude of this effect will surely depend on the public perceptions of whether the policy is going to persist over their planning horizon. So in order to realise the predictions of our elasticity model, long-term pronatalist policies should be adopted. Moreover, in reality only long-term policy, which is seen to be long term, will likely be effective anyway.Besides, it should also be emphasized that the change in timing risk will surely be less for higher parities, that is, an increase in say parity 4+ fertility is much more likely to represent an increase in fertility intention than a change in parity 1 fertility. In other words, the diluting effect of potential changes in timing changes will decrease with parity. Consequently, any bias in our method due to timing is towards lower parities. So, if our method identifies higher parities as better targets  then the real effect may in fact be larger. This is precisely what we found in our analysis of Australian data–support for targeting parities 3 and 4+. Finally, timing effects will surely be less for older mothers and most of the fertility gains for parities 3 and 4+ are from older mothers.bJ could be used.To measure the propensity of each group fertility to change, we looked at historical variation of group fertilities. One quite crude method is to use coefficient of variation, the idea being that historical fluctuations, either increase or decrease, or mixed, are predictive of the magnitude of changes that are likely to occur in the fertility rate of that group. More sophisticate methods could be used for this step in the future. To measure the total cost of the policy, we assumed that the cost for targeting each group is proportional to the proportion of births in that group. If there were economies of scale, then some power of Applying the method to Australian data, the results show that the TFR is most mathematically sensitive to changes in the following fertility rates: parity-1 for the 15–34 year-old unmarried women; parity 1, 2, and 3 among the 30–39 year-old married women see . But aftThere are some limitations in this study. Several minor assumptions are made to facilitate the computations, which consequently do not fully model the exact parity transition in real life. But the analysis can still shed light on Australia’s fertility trends, especially the roles of different subgroups in the group fertility rate . Among uSince it is unrealistic in Australia to directly target people by age-group or marital status, we calculated the benefit cost ratios for groups only by parity. We found that targeting parity 3 is the most cost-effective and four times more cost-effective than targeting parity 1 . This reS1 Appendix(DOCX)Click here for additional data file.S2 Appendix(DOCX)Click here for additional data file.S1 File(XLSX)Click here for additional data file.


Giardia duodenalis , is a significant zoonotic parasitic disease of animals and humans worldwide. Accurate genotyping of G. duodenalis is essential for efficient control and management of giardiasis. The objectives of the present study were to investigate the prevalence and assemblages of giardiasis in pigs in Shaanxi Province, northwestern China, and for the first time study multilocus genotypes (MLGs) in pigs using multilocus genotyping technology in this region.Giardiasis, caused by G. duodenalis and significant differences in prevalence were observed among different locations. Differences in prevalence were also detected in pigs of different age groups, with the highest prevalence in sows and the lowest in boars. Two assemblages, A and E, were identified, and a mixed infection of both A and E was identified in one faecal sample. Assemblage E was predominant and widely distributed in all investigated areas and age groups. Genetic viability was detected for both assemblages, and four different multi-locus genotypes (MLGs) within assemblage E were found, MLGE1-MLGE4.Of 560 faecal samples collected from five farms in Shaanxi Province, 45 were positive for Giardia duodenalis was detected in pigs from Shaanxi Province, northwestern China, and genetic diversity was observed in these infections. Both assemblages A and E were detected, and four distinct MLGs within assemblage E were identified. These findings provide new data for controlling G. duodenalis infection in pigs. Giardia duodenalis , an important parasitic protozoan, inhabits the gastrointestinal tracts of animals. It causes giardiasis, with clinical presentations ranging from chronic to acute diarrhea, dehydration, abdominal pain, nausea, vomiting, and weight loss [Giardia duodenalis has also been reported in a wide variety of other hosts worldwide, including sheep, goats, cattle, and non-human primates [ght loss , leadingght loss . Giardiaght loss . The pubght loss , 5. Giarprimates –20.G. duodenalis, assemblages A-H [Recent molecular analysis indicated eight major morphologically similar but genetically distinct assemblages of ages A-H . Among tages A-H , whereasages A-H , 22.G. duodenalis has been identified in sheep (4.3–6.6%) [Giardia duodenalis infection has been reported in pigs in many countries  , 16, goa.3–6.6%)  and catt.3–6.6%) –21. Alth.3–6.6%) . Pigs ar.3–6.6%) . GiardiaG. duodenalis used morphological methods or molecular technologies based on one or two gene loci , glutamate dehydrogenase (gdh), triosephosphate isomerase (tpi) and the small subunit ribosomal RNA (SSU rRNA), several multilocus genotypes (MLGs) and mixed genotypes were observed, including one MLGA and four MLGE in dairy calves [G. duodenalis in pigs in Shaanxi Province, northwestern China, and investigate the MLGs in pigs using multilocus genotyping tool.Previous studies to investigate ci Table . Morpholy calves , native y calves , sheep [y calves , raccoony calves , childrey calves , pet chiy calves , red deey calves  and othey calves . Using fy calves , one MLGy calves , one MLGy calves , three My calves , two MLGy calves , and twoy calves . The objG. duodenalis in pigs in Shaanxi Province, northwestern China, 560 faecal samples were collected from pigs (newborn to 2 years) from five different farms in Zhouzhi, Qishan, Mianxian, Lintong and Yuyang, between September 2016 and March 2017 , according to the manufacturer’s instructions. Extracted DNA samples were stored at -20 °C prior to PCR analysis.Each faecal sample was washed three times in distilled water with centrifugation at 13,000 G. duodenalis in pigs was initially determined by nested PCR targeting the bg gene fragment using primers described previously [Ex Taq Buffer (Mg2+ free), 2 mM MgCl2, 0.2 mM dNTP Mixture, 0.625 U of TaKaRa Ex Taq  and 0.4 μM of each primer  agarose gels with ethidium bromide staining.To investigate multi-locus genotypes (MLGs) of eviously , 35  using relevant internal nested primers for PCR amplification. Sequences obtained were aligned with sequences available on GenBank using Basic Local Alignment Search Tool (BLAST), and edited using DNAStar 5.0  and Clusχ2) analysis and 95% confidence intervals (CIs) were calculated using SPSS 19.0 for Windows  and used to analyze differences between different locations and age groups, with P < 0.05 considered statistically significant.Chi-square  GenBank database under the following accession numbers: KY989575–KY989579 for the Giardia duodenalis is one of the most common intestinal parasites in symptomatic and asymptomatic humans and livestock [G. duodenalis, they still shed infective G. duodenalis cysts into the environment which can survive for extended periods in cool, humid environments. Considering that exposure to infective cysts through contaminated water and food is the primary mechanism of G. duodenalis transmission to animals and humans [G. duodenalis infection in pigs has important implications for controlling giardiasis in humans and animals.Globally, ivestock ; this spd humans , 40, invG. duodenalis have been reported in livestock in China, e.g. 4.3–6.6% in sheep [G. duodenalis infection  prevalences were observed among different locations, with the highest  in Lintong district and the lowest   in Qishan county. Comparison of these results with results obtained from other pig farms showed that the prevalence of G. duodenalis in pigs in Shaanxi Province in China was lower than that in Australia (31.1%) [G. duodenalis was comparatively higher . These findings could suggest transmission between the different animals, which should be explored in future studies.Varying prevalence rates of in sheep –16, 2.9–in sheep  and 1.1–in sheep –20. In t (31.1%) , Ontario (31.1%) , Denmark (31.1%) –45, Pola (31.1%) , Lusaka, (31.1%) , and Pre (31.1%) , but hig (31.1%) , Preah V (31.1%) , Istanbu (31.1%) , Norway  (31.1%) . The dif (31.1%) . For exaG. duodenalis prevalence were detected in pigs of different age groups in this study, but these differences were not statistically significant . The highest prevalence  was detected in sow pigs, which was consistent with a study from Zambia (53.3%) [G. duodenalis infection should be further evaluated in future studies.Differences in  (53.3%) , but was (53.3%)  and one  (53.3%) , where t (53.3%) , in whic (53.3%) , the actG. duodenalis has been reported in pigs and five assemblages  have been reported [G. duodenalis-positive samples based on the bg gene, with assemblage E  being the predominant assemblage, which was detected in all investigated areas and age groups. These results were consistent with a study in Australia [Genetic variability of reported , 44–46. ustralia  and two  80%, 36/ being thustralia . While australia , 44, 45 G. duodenalis in pigs, the sequence characters of the tpi and gdh genes were analyzed for the 45 bg positive samples and the MLGs were characterized in pigs using combined data from these three gene loci. Of 45 bg-positive samples, 9 tpi and 11 gdh gene sequences were obtained. Sequence alignment identified different genotypes of assemblages E (Table gdh and SSU rRNA sequences [bg, gdh, tpi, and SSU rRNA sequences in dairy calves [G. duodenalis in animals as well as humans.To further illuminate the genetic diversity of  E Table . MLGE1 aequences  and othey calves , dairy cy calves , and shey calves . This suG. duodenalis in pigs from Shaanxi Province, northwestern China, were investigated in the present study. The total prevalence of G. duodenalis infection was 8% and the highest infection rate was observed in sow. Assemblage analysis indicated the presence of the animal-specific assemblage E and the potentially zoonotic assemblage A. Genetic diversity was found within both assemblages, and four assemblage E MLGs were discovered. To the best of our knowledge, this is the first investigation of G. duodenalis MLGs in pigs. The findings in our study provided basic data for understanding the molecular epidemiology of G. duodenalis in pigs, and highlighted the significance of multilocus genotyping for unraveling the intricate molecular epidemiology of giardiasis in animals and impact on livestock economics and human health. However, there were some limitations to the sampling strategies and study methodologies in our study. For example, no statistical analysis of prevalence in different seasons was conducted in our study. Therefore, additional factors should be included in future studies to accurately determine the infection status of G. duodenalis in pigs in Shaanxi Province as well as other geographical locations.The prevalence and MLGs of


The roles of autophagy in viral infection are complicated. While autophagy has been shown to function in host antiviral defense by eliminating intracellular viruses and regulating adaptive immunity, several viruses have evolved molecular mechanisms to get benefits from it. The deltaretrovirus human T-cell leukemia virus type-1 (HTLV-1) has been reported to profit its replication from enhancing autophagosome accumulation. Here, we reported that HLA-DMB , the beta chain of the non-classical MHC-II protein HLA-DM, had strong expression in HTLV-1-transformed T-cell lines and could be induced in Hela, PMA-differentiated THP1 (PMA-THP1) or primary human monocytes by HTLV-1 infection. Immunoblot and real-time PCR assays demonstrated that overexpression of DMB decreased HTLV-1 protein expression while the knockdown of DMB increased HTLV-1 protein expression. Immunoblot and confocal microscopy assays indicated that overexpression of DMB decreased HTLV-1 induced autophagosome accumulation while the knockdown of DMB yielded the opposite effects. Coimmunoprecipitation and immunoprecipitation experiments suggested DMB interacted with autophagy-related gene (ATG) 7 and increased the acetylation of ATG7. Taken together, these results suggested DMB modulated HTLV-1 protein expression through regulation of autophagosome accumulation and our findings suggested a new mechanism by which the host cells defended against HTLV-1 infection. While most infected individuals are asymptomatic carriers (ACs) of the virus, 3~5% of infected individuals develop a malignancy of CD4+ T cells known as Adult T cell leukemia (ATL) several decades after infection and less than 50% of the ATL patients survive more than one year5. HTLV-1 also causes a severe neurological disorder designated HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP) and other inflammatory diseases such as HTLV-1 uveitis6.Human T-cell leukemia virus type-1 (HTLV-1), the first retrovirus discovered to be linked with human diseases8. Autophagy is initiated at the isolation membrane, usually from endoplasmic reticulum (ER) membranes, and autophagosome formation is dependent on the so-called autophagy-related gene (ATG) products9. Till now, 40 ATG proteins have been identified in yeast and many mammalian homologs for these have been found10. However, only half of these are essential for formation of canonical autophagosomes, including ATG1-10, 12–14, 16–18, 29, and 3111. Central to canonical autophagy are two ubiquitination-like conjugation systems, ATG12 conjugation system and the microtubule-associated protein 1-light chain 3 (LC3)/ATG8 lipidation system. Both ATG12 and ATG8 are activated by the same E1-like enzymes called ATG712. In the ATG12 conjugation system, ATG7 facilitates the conjugation of ATG12 to ATG5, forming the ATG12-ATG5 conjugate13. In the LC3 lipidation system, activated LC3-I is transferred to ATG3 and finally conjugated to phosphatidylethanolamine (PE)14. This LC3-PE conjugate is known as LC3-II and is one of the most accepted markers of autophagy now15.Autophagy, characterized by the formation of double-membrane vesicles called autophagosomes and subsequent lysosome-based degradation of damaged or excess cellular components, plays an important role in maintaining homeostasis16. Importantly, it is becoming increasingly clear that autophagy is activated upon viral infection17. Depending on the virus and the host cell, autophagy can have different effects during viral infection, either as an innate host antiviral defense mechanism or as a pro-viral process18. As an integral part of immune system, autophagy has been shown to function in host antiviral defense by limiting viral replication, influencing viral antigens presentation or targeting virions and virus components for autophagic degradation22. Conversely, certain viruses have evolved diverse mechanisms to exploit the autophagy system for their replication26. For example, autophagy proteins  are proviral factors required for translation of incoming hepatitis C virus (HCV) RNA and, therefore, for establishment of productive infection27. In addition, recent work has demonstrated that HTLV-1 infection increases the accumulation of autophagosomes and that this accumulation benefits viral replication28, although detailed mechanisms remain to be clarified.Autophagy can be stimulated by nutrient deprivation, growth factor withdrawal, and other signals, including ER stress, oxidative stress, and immune cell activationHere we demonstrated that HLA-DMB , the beta chain of the non-classical MHC-II protein HLA-DM, was induced by HTLV-1 infection and suppressed HTLV-1 protein expression. We showed that DMΒ inhibited the accumulation of autophagosomes during HTLV-1 infection, which was important for HTLV-1 replication. Further study indicated that DMB was associated with ATG7, one of the core autophagy proteins essential for canonical autophagy, and increased its acetylation. Collectively, our findings may shed some new lights on autophagy regulation and contribute to our understanding of the host defenses against HTLV-1 infection.29, which are expressed constitutively in B cells and could be induced by some stimuli in other cell types such as monocytes and T cells30. All the above cell types could be infected by HTLV-131. Thus, it seemed reasonable for us to explore the relationship between DMΒ and HTLV-1 infection. We first examined DMΒ expression in HTLV-1 infected cells. We compared the expression of DMΒ in non-infected Jurkat T-cell line as well as in HTLV-1-transformed T-cell lines (C8166 and MT2). Immunoblot assays indicated that the HTLV-1-positive MT2 and C8166 cells showed strong expression of endogenous DMΒ protein, whereas the HTLV-1-negative Jurkat cells did not  of retroviruses could be recognized by DNA sensors, we speculated that DMB might be induced by cytosolic DNA sensor pathways. It has been clarified that HTLV-1 RTIs interact with STING and HTLV-1 infection triggers a robust anti-viral innate immune response in primary monocytesure Fig. , suggesture Fig. . Taken tThen we tried to determine the functions of DMΒ during HTLV-1 infection. Hela cells overexpressing DMB were co-cultured with MT2 cells and the expression levels of HTLV-1 proteins were investigated. Immunoblot assays demonstrated that the exogenous expression of DMB was associated with lower protein levels of HTLV-1 proteins Tax and p19 Fig. . ConsistNext, we examined whether endogenous DMΒ was involved in the regulation of HTLV-1 protein expression. We silenced endogenous DMB expression in MT2 cells by siRNA. We purchased three siRNA constructs and determined their effects on DMB expression. As shown in Fig. 28. Then we examined the effects of DMB on HTLV-1 induced autophagosome accumulation. DMB was silenced in MT2 cells and immunoblot assays were performed. We found that the knockdown of DMB increased the amount of LC3-II protein levels . Subsequent coimmunoprecipitation experiments were performed and the data suggested only ATG7 bound to DMB Fig. . To confConsidered that DMB usually forms a heterodimeric protein with DMA, we also examined the effects of DMA on HTLV-1 infection. Hela cells overexpressing DMA were co-cultured with MT2 cells and the expression levels of Tax and p19 were investigated. Both immunoblot and real-time PCR results suggested that DMA had no significant effect on the expression levels of Tax and p19  almost lost the ability to regulate autophagosome accumulation and HTLV-1 protein expression, suggesting that the interaction between DMB and ATG7 was essential to the regulatory role of DMB in autophagy and HTLV-1 infection.40. It has been reported that deacetylation of ATG5, ATG7 and ATG8 by the NAD-dependent deacetylase Sirt1 could stimulate autophagy36. Here, we showed that DMB affected the acetylation of ATG7, thereby playing an inhibitory role in autophagosome accumulation. The overexpression of DMB promoted the acetylation of ATG7 in both MT2-co-cultured Hela cells and untreated Hela cells, whereas the knockdown of DMB decreased the acetylation of ATG7 in MT2 cells. Although our data have suggested DMB might regulate the acetylation of ATG7 by inhibiting the interaction between Sirt1 and ATG7, further studies about the underlying molecular mechanism are needed.Acetylation is one of the important posttranslational modifications for the regulation of autophagy, which could affect ATG gene expression or activity28. One may think that the inhibition of autophagosome-lysosome fusion by Tax results in increased autophagosome accumulation and decreased degradation of HTLV-1 protein, leading to increased HTLV-1 proteins abundance. Interestingly, our data showed that the DMB expression inhibited autophagosome accumulation at the early phase of the autophagy pathway and resulted in impaired HTLV-1 protein expression. These results indicated that the autophagosome formation might provide convenience for HTLV-1 protein expression. It is possible that HTLV-1 infection promotes the autophagosome formation to benefit its replication. Meanwhile the Tax protein inhibits the degradation of autophagosome to make the best use of this benefit. Further studies are needed to clarify the detailed mechanisms.It is worth noting that the detailed mechanisms about how autophagosome accumulation can increase the abundance of HTLV-1 protein remain to be clarified. It has been revealed that HTLV-1 protein Tax, which plays an important role in regulating HTLV-1 replication, blocks the fusion of autophagosomes to lysosomes and prevented its degradation of HTLV-1 protein in the autophagy-lysosome pathwayTogether, our study demonstrated that DMB modulated autophagosome accumulation by regulating the acetylation of ATG7, thereby affecting the expression of HTLV-1 protein Fig. . Our resHuman HLA-DMB was amplified by PCR using cDNA from MT2 cells, and subsequently cloned into pcDNA3.1 vector. The deletion mutants of DMB were amplified by PCR and subcloned into pEGFP vector. Human ATG3, ATG4, ATG7, and Beclin1 were amplified by PCR using cDNA from Hela cells, and cloned into a pcDNA3.1-HA vector. ATG7 was subcloned into a pmCherry vector. pENTER-Flag-DMA plasmid was obtained from Vigene Biosciences. Myc-Sirt1 plasmid was a generous gift of Xiaofei Zhu . The 90-base-long HTLV-1 ssDNA90 is the reverse complement of the 5′UTR region (315–404) of complete HTLV-1 genome (NCBI) and was synthesized from the Sangon Biotech. The sequence was as follows: CTGTGTACTAAATTTCTCTCCTGGAGAGTGCTATAGAATGGGCTGTCGCTGGCTCCGAGCCAGCAGAGTTGCCGGTACTTGGCCGTGGGC.The following antibodies were used for immunoblot or immunoprecipitation analysis: anti-HA , anti-Flag , anti-DMB , anti-HTLV-1 p19 , anti-LAMP1 , anti-Tax , anti-IFI16 , anti-LC3A/B , anti-ATG5 , anti-ATG7 , anti-ATG12 , anti-Acetylated-Lysine , anti-Sirt1 , anti-GFP , anti-Myc , anti-cGAS (26416-1-AP), Proteintech) and anti-β-actin .The 3-MA (M9281) was obtained from Sigma-Aldrich. All the chemical inhibitors were obtained from Selleck. The PMA (S1819) was purchased from Beyotime Biotechnology.+ T cells were isolated from PBMCs by FACS screening, and cultured in RPMI 1640 in the presence of IL-2. All cells were supplemented with 10% FBS (Gibco), 4mM L-glutamine, 100U/ml penicillin, and 100U/ml streptomycin under humidified conditions with 5% CO2 at 37 °C. Transfection of HEK293T and Hela cells was performed with Lipofectamine 2000 (Invitrogen) according to the manufacturer’s instructions.HEK293T and Hela cells were cultured in DMEM. MT2, C8166, Jurkat and THP1 cells were grown in RPMI 1640. PBMCs were enriched from donor blood using Ficoll density gradient separation and human monocytes were separated by their adherence to the culture plate in RPMI 1640. Primary CD441. In short, HEK293T, Hela, THP1 or MT2 cells were transfected with various combinations of plasmids or siRNA. At 24 h after the transfection, the cell lysates were prepared in lysis buffer containing 1.0% (vol/vol) Nonidet P40, 20 mM Tris-HCl, pH 8.0, 10%(vol/vol) glycerol, 150 mM NaCl, 0.2 mM Na3VO4, 1 mM NaF, 0.1 mM sodium pyrophosphate and a protease inhibitor ‘cocktail’ (Roche). After centrifugation for 20 min at 14,000 g, supernatants were collected and incubated with the indicated antibody together with protein A/G Plus-agarose immunoprecipitation reagent  at 4 °C for 3 h or overnight. After three washes, the immunoprecipitants were boiled in SDS sample buffer for 10 min and analyzed by immunoblot. For endogenous coimmunoprecipitation experiments, the cell lysates of MT2 cells or THP1 cells were incubated with indicated antibodies and analyzed by immunoblot.Immunoprecipitation and immunoblot analysis were performed as described previously−△△Ct method. Gene-specific primer sequences were as described42 or as follow:Total RNA was extracted from the cultured cells with TRIzol reagent (Invitrogen) as described by the manufacturer. All gene transcripts were quantified by real-time PCR with SYBR Green qPCR Master Mix using a 7500 Fast real-time PCR system (Applied Biosystems). The relative fold induction was calculated using the 2p19,Forward, 5′-CACCCCTTTCCCTTTCATTCACGA-3′,Reverse, 5′- CCGGCCGGGGTATCCTTTT-3′,Env,Forward, 5′-CCATCGTTAGCGCTTCCAGCCCC-3′,Reverse, 5′- CGGGATCCTAGCGTGGGAACAGGT-3′;px,Forward, 5′- CAAAGTTAACCATGCTTATTATCAGC-3′,Reverse, 5′-ACACGTAGACTGGGTATCCGAA-3′HBZ,Forward, 5′- AACTGTCTAGTATAGCCATCA -3′;Reverse, 5′- CAAGGAGGAGGAGGAAGCTGTGC -3′ISG15,Forward, 5′- ATGGGCTGGGACCTGACCGG -3′;Reverse, 5′- TTAGCTCCGCCCGCCAGGCT -3′IP-10,Forward, 5′- TTCCTGCAAGCCAATTTTGTC -3′;Reverse, 5′- TCTTCTCACCCTTCTTTTTCATTGT -3′RANTES,Forward, 5′- TACACCAGTGGCAAGTGCTC -3′;Reverse, 5′- ACACACTTGGCGGTTCTTTC -3′HLA-DMB-Stealth-RNA interference was designed by the Invitrogen BLOCKiT RNAi Designer. The small interfering RNA (siRNA) sequences used were as follows:H1,Forward, 5′-UCCUUCAACAAGGAUCUGCUGACCU-3′,Reverse, 5′-AGGUCAGCAGAUCCUUGUUGAAGGA-3′;H2,Forward, 5′-GGACAUACCAGACCCUCUCCCAUUU-3′,Reverse, 5′-AAAUGGGAGAGGGUCUGGUAUGUCC-3′;H3,Forward, 5′-ACUCCUCUUCCUGGGUCCAAUUAUU-3′,Reverse, 5′-AAUAAUUGGACCCAGGAAGAGGAGU-3′.The negative control siRNA was purchased from Invitrogen .STING-Stealth-RNA interference was designed by the Invitrogen BLOCKiT RNAi Designer. The small interfering RNA (siRNA) sequences used were as follows:Forward, 5′-GGCCCGGAUUCGAACUUACAAUCAG-3′;Reverse, 5′-CUGAUUGUAAGUUCGAAUCCGGGCC-3′.Ku70-Silencer Select Pre-designed siRNA was obtained from Invitrogen. The small interfering RNA (siRNA) sequences used were as follows:Forward, 5′-GACAUAUCCUUGUUCUACATT-3′;Reverse, 5′-UGUAGAACAAGGAUAUGUCAA-3′;cGAS-Stealth-RNA interference was designed by the Invitrogen BLOCKiT RNAi Designer. The small interfering RNA (siRNA) sequences used were as follows:Forward, 5′-GCACGUGAAGAUUUCUGCACCUAAU-3′;Reverse, 5′-AUUAGGUGCAGAAAUCUUCACGUGC-3′.IFI16-Stealth-RNA interference was designed by the Invitrogen BLOCKiT RNAi Designer. The small interfering RNA (siRNA) sequences used were as follows:Forward, 5′-UCAAUCAGCUUUGCUCACAAACUAA-3′;Reverse, 5′-UUAGUUUGUGAGCAAAGCUGAUUGA-3′+ T cells or primary human monocytes were transfected with siRNA using Lipofectamine 2000 according to the manufacturer’s instructions. At 24 h after transfection, the cells were used for further experiments.THP1, Hela, MT2, Jurkat, primary CDHela cells were transfected with the indicated plasmids. At 24 h after transfection, cells were fixed with 4% PFA in PBS and permeabilized with Triton X-100 and then blocked with 1% BSA in PBS. Nuclei were stained with DAPI.p < 0.05 was considered statistically significant.The data were presented as the means ± SD from at least three independent experiments. The statistical comparisons between the different treatments were performed using the unpaired Student t test, and Supplemental materials


In the vertebrate CNS, afferent sensory inputs are targeted to specific depths or layers of their target neuropil. This patterning exists ab initio, from the very beginning, and therefore has been considered an activity-independent process. However, here we report that, during circuit development, the subcellular segregation of the visual and mechanosensory inputs to specific regions of tectal neuron dendrites in the tadpole optic tectum requires NMDA receptor activity. Blocking NMDARs during the formation of these sensory circuits, or removing the visual set of inputs, leads to less defined segregation, and suggests a correlation-based mechanism in which correlated inputs wire to common regions of dendrites. This can account for how two sets of inputs form synapses onto different regions of the same dendrite. Blocking NMDA receptors during later stages of circuit development did not disrupt segregation, indicating a critical period for activity-dependent shaping of patterns of innervation.DOI:http://dx.doi.org/10.7554/eLife.20502.001 In most regions of the vertebrate CNS, afferent axonal inputs form topographic maps within specific layers of their target region. This laminar patterning of maps allows for multiple sets of afferent inputs to coexist across the same two dimensional plane of a common target, conducive to integration. This patterning motif is found in many brain structures that receive multiple sets of afferent input. For example, the different sensory inputs that are received and processed by the optic tecta of birds , fish X, and ampXenopus tadpole optic tectum as a model system, a relatively simple and well-studied multisensory integration center. The optic tectum receives direct visual input from the retinal ganglion cells in the eye and mechanosensory input that enters the tectum via the brainstem. Both sets of afferent sensory inputs form topographic maps parallel with the surface of the neuropil,  region of the laminar axis while the non-visual mechanosensory inputs that enter the tectum via the hindbrain (HB), and so called ‘HB inputs’, target the proximal  region ; Figure functional pattern of synaptic input. To address this, we used a modified whole brain preparation that allows direct access to the entire distal-proximal axis of the neuropil while, like the traditional whole brain preparation, retaining both the RGC and HB inputs. It was previously established that the pattern and strength of RGC and HB-evoked responses recorded from tectal neurons of the modified preparation do not differ from that recorded in the traditional preparation, indicating that RGC and HB inputs are not severed in the modified brain preparation  into the intact eye and DiI (red) into both sides of the HB. As predicted by the CSD and FP data, we observed that HB axonal inputs in the DCR tecta appeared less focused in space and extended into the vacant dendritic region that is normally occupied by RGC axons, whereas the control tectum showed a typical confined band of HB axons along the proximal part of the laminar axis . Figure It has been established that blocking NMDARs during the formation of the retinotectal projection prevents refinement of the topographic map  and the Chronic NMDAR blockade caused both sets of afferent inputs to shift closer to one another across the laminar axis, with a portion of the inputs moving outside the boundaries of their lamina and forming synapses where they normally would not. Overall, this resulted in a greater amount of spatial overlap of inputs at the border region. Besides appearing less confined to a specific lamina, the spatial pattern of synaptic connections displayed by both sets of inputs appeared less defined, lacking an obvious peak region of synaptic input.maintenance of this organization is also NMDAR-dependent. To address this, tadpoles were exposed to MK-801 at a later stage in development (stage 45), after both the visual and non-visual inputs have established their postsynaptic targets. Once tadpoles reached stage 49, the same set of experiments as previously described were carried out to characterize the degree of functional and structural segregation. The RGC- and HB-evoked spatial profile of peak FP amplitudes of the MK-801-exposed tecta resemble control profiles  versus late (stage 45) NMDAR blockade on the spatial pattern of functional synaptic input made by the RGC and HB inputs  is mirrored by the pattern of axonal terminations across the neuropil, DiD (green) and DiI (red) was injected into the eyes and HBs, respectively, of control and MK-801-reared tadpoles to visualize RGC and HB axon terminals in the neuropil. In addition to measuring the distance between the peak fluorescence of RGC and HB axons, the amount of overlap between inputs was also calculated by measuring the area of neuropil that was common to both inputs. We found that early and late NMDAR blockade significantly increased the total amount of overlap of RGC and HB axons compared to control  Similarly, chronic blockade of NMDA receptors during circuit development desegregates the two different sets of sensory inputs, showing that the subcellular targeting of the different afferent inputs to specific regions of a common tectal dendrite requires NMDAR activation (The major findings of this study are (1) During the development of the tivation . (3) BloWe observed that removing the contralateral RGC inputs before they reached the tectum caused the entire spatial pattern of mechanosensory (HB) synaptic input to shift distally. A portion of the HB inputs extended beyond their normal proximal lamina into a more distal lamina, and formed synapses onto more distal regions of dendrite that are normally synaptic targets for RGC axons, suggesting that the sensory-dependent segregation of afferent inputs across the neuropil, and in this case, across the distal-proximal axis of individual dendrites, requires their physical presence. If the input is absent during the development of the circuit, its target region becomes ectopically innervated by the remaining neighboring afferent input. Similar monocular enucleation studies in the axolotl  and the only in an EphrinA2/A5 double knockout mouse. The shift was not observed in wild type mice because Ephrin expression between the LGN and MGN inhibits the remaining input from crossing over into vacant territory. Therefore, because we observe a shift in mechanosensory inputs to the more distant dendrites by just removing the RGC input indicates that, in this case, segregation is not under the sole control of molecular cues. Nevertheless, the possibility that the absence of the RGC input somehow altered the expression pattern of some putative molecular signal cannot be ruled out, and it is interesting to note that a differential pattern of ephrin expression across the laminar axis of both the Rana pipiens  MK-801 exposure was not observed to alter the spatial position of peak field potential amplitudes, peak CSD sinks, nor peak HB and RGC axon fluorescence, it did appear to significantly increase the overall amount of overlap between these two sets of axons. This increase in overlap in response to late MK801 exposure could reflect a subpopulation of relatively immature axons that have more recently entered the tectum and are still undergoing NMDAR-dependent correlation-based processes. In addition, the HB axons, specifically, appeared to be more affected by late MK-801 exposure than the RGC axons .Why may the segregation of inputs involve an activity-dependent component while many other examples of lamination appear to be hard wired? One important aspect of the tadpole optic tectum that sets it apart from most other integration centers is that the tectal neuron dendrites span the entire laminar axis and receive input from both sensory modalities. Thus, in the tadpole optic tectum, inputs are segregated to the distal and proximal regions of a common dendrite, while in zebrafish, and chick, inputs form onto specific cell types . The subThis study does not address the function of subcellular segregation of inputs. We have not yet been able to address this because the chronic blockade of NMDARs – which disrupts the segregation – also disrupts the refinement of the RGC topographic map . In ordeDuring development of many sensory circuits in the vertebrate CNS, molecular cues guide sensory inputs to form a course topographic map across the 2-dimensional surface of their target regions. The course topographic map is refined via NMDAR-dependent fire-together-wire-together rules . Our resXenopus laevis tadpoles were raised in Steinberg’s solution at 25°C on a 12:12 hr light-dark cycle, and developmental stages were identified according to 2, 3 MgCl2, 5 HEPES, and 10 glucose, pH 7.25, osmolarity 255 mosM). Next, the skin overlying the brain was peeled away and the brain and brainstem were filleted open along the dorsal midline, and the most lateral 1/4th of the tectum  is excised. Next, the preparation is pinned onto the side of a piece of submerged silicone, positioned such that the sliced side is on the surface and readily accessible for recording, and also so that bipolar stimulation electrodes can be placed onto the optic chiasm and hindbrain to stimulate the visual (RGC) and non-visual (HB) inputs, respectively . Wildtype ectively . TypicalMonocular enucleations were done at stage 34 using a sterile 26-gauge syringe needle. Tadpoles were first anesthetized using 0.02% MS-222 and the entire eye, from lens to choroid, was removed. The animals recovered from the operation in Steinberg’s solution. Post-surgery, tadpoles displayed normal swimming and schooling behaviors, similar to controls. Electrophysiological experiments and axonal dye fills were performed approximately ten days after the operation.To chronically block NMDA receptors, tadpoles were reared in Steinberg’s solution containing 25 µM (+)-MK-801 (Tocris) starting at stage 39 for 8–10 days, and the drug-containing media was refreshed every three days . Electro+-gluconate internal recording saline . Electrophysiological recordings were carried out using an Axon Instruments 700B Multipatch amplifier , digitized at 10 kHz using a Digidata 1322A digitizer, and recorded using pCLAMP software.Tectal neurons were visualized using a Zeiss light microscope equipped with a 60X water-immersion objective and a Hamamatsu infrared charge-coupled device camera. For whole-cell recordings, we used glass micropipettes with 8–12 MΩ resistance filled with KAll field potential (FP) recordings were done as described in FP amplitudes reflect the peak deflection that occurred within 4 ms of the time of stimulus since the monosynaptic response is known to occur within this time frame . Peak FPTo reveal more precisely the spatial pattern of the major sites of synaptic activity, we calculated the current-source density (CSD) profile of visual and mechanosensory inputs along the neuropil as described in To image axons, DiI  and DiD  were dissolved into 5% ethanol for injection. Xenopus tadpoles were anesthetized in 0.01% MS-222, DiI was injected into both sides of the hindbrain, and DiD was injected into both eyes, then tadpoles were fixed in 4% paraformaldehyde (PFA) for six days. Prior to imaging, samples were rinsed three times in 0.1 M phosphate buffer (PB: pH 7.4), mounted onto a customized slide for in vivo imaging, and then imaged using a laser scanning confocal microscope (Carl Zeiss LSM 710).ImageJ software was used to quantify the pixel intensity of RGC and HB axon terminations in the laminar axis. For this, a single line was drawn parallel to the laminar axis at a point along the rostrocaudal axis where the neuropil is the widest. The fluorescent profile along this line was generated. We identified the distance from the distal edge of the laminar axis at which the peak pixel intensity, corresponding to the bulk of axonal input, of RGC and HB axons occurred and measured the distance (i.e. the gap) between the two peaks. The merged RGC and HB axon fluorescent profiles were also used to measure the amount of overlap between the two sets of axons by quantifying the area of each profile that was common to both inputs. In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.eLife. Your article has been reviewed by three peer reviewers, one of whom, Ronald Calabrese, is a member of our Board of Reviewing Editors and the evaluation has been overseen by Eve Marder as the Senior Editor.Thank you for submitting your article "An NMDA receptor-dependent mechanism for subcellular segregation of sensory inputs in the tadpole optic tectum" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.Summary:Xenopus tadpoles. The study confirms that these inputs are segregated onto the more distal and more proximal portions respectively of the same dendrites of tectal neurons. It is particularly clearly shown that they form functional synapses on these specific portions of the dendrites. The authors then show that elimination of the visual input causes spread of the somatosensory inputs and that normal segregation is compromised if the tadpoles are reared from the stage of initial synapse formation in the presence of NMDR blocker (MK-801) but not if the blockade is initiated at a later stage. Because the inputs are segregated initially during development, the results suggest a progression of activity-independent, then -dependent mechanisms that together result in the segregation of inputs across tectal neuron dendrites. Activity – specifically NMDAR-dependent activity – segregates the different inputs, implicating a correlation-based mechanism. This work thus adds to our knowledge about how inputs are segregated onto dendrites during development.This study combines neuronal labeling and electrophysiology  to study the segregation of visual and somatosensory inputs in the tectum of Essential revisions:There are some concerns that must be addressed, but overall this appears to be a strong study of general significance.1) The examples of anatomical data presented seem to support the conclusions, but the results must be quantified and comparisons made across a number of animals to test whether the differences seen in the examples presented do indeed stand up. Such analysis is necessary for the data in 2) The analysis of CSD sinks should be more thorough or this measure dropped and the physiological analysis restricted LFP. This concern is fleshed out more in the attached comments of reviewer #2.Xenopus compared to other species. This makes the findings interesting, but also means that the cellular mechanism is an important one to hash out.3) A weakness of the paper is that the MK801 effect is the only direct evidence implicating NMDARs. Without evidence showing that disrupting NMDAR function specifically in tectal cells is sufficient to replicate the MK801 results the exact site of action is not clear. There are several reports of presynaptic NMDARs playing important roles, so the experiments provided do not exclude other NMDAR-dependent mechanisms being at play. Furthermore, in the discussion much attention is given to the fact that the data suggest a fundamentally different mechanism for the sorting of visual/non-visual input in At the minimum this should be addressed in the discussion as a limitation of the preparation and something that should be addressed in the future. This would also be a good opportunity to provide any evidence (references or unpublished data) supporting a model in which NMDAR activity in tectal neurons is, in fact, the cellular mechanism mediating this phenomenon.Reviewer #2:While the interpretation is interesting, the data analysis is incomplete, decreasing confidence in the conclusions.There are two principal concerns with the data analysis:1) The anatomical pattern of innervation from the retina and the HB to the tectum, and the effect of eye enucleation and pharmacological treatment, are described anecdotally (a couple of examples). It is possible and probably essential to quantify (and summarize) the effect of enucleation and MK-801 on tectal innervation using some kind of laminar area measure or segregation measure . This would put on much more solid ground the apparent effect of enucleation or MK-801 on HB projection 'segregation'.2) The presentation of CSD and FP is a little confusing. Both are presented in the figures. It is argued that the CSD shows the site of sources and sinks (concentrated synaptic contacts occur at sinks if the structure is laminar in nature). However, only the FP amplitude is quantified, not the amplitude of the CSD sinks. In my opinion, the authors should also quantify the location (and spread as a result of enucleation) of the CSD sinks. If this is altered by the enucleation and/or MK-801, it would strengthen their arguments about the NMDA-receptor dependent 'competitive' segregation process. If quantification of the CSD pattern (and it's changes) is not possible, then this should be explained (and probably the CSD data should be de-emphasized or removed).eLife. Your article has been reviewed by one peer reviewer, and the evaluation has been overseen by a Reviewing Editor and Eve Marder as the Senior Editor. The reviewer has opted to remain anonymous.Thank you for submitting your article "An NMDA receptor-dependent mechanism for subcellular segregation of sensory inputs in the tadpole optic tectum" for consideration by The reviewer has discussed the reviews with the Reviewing Editor and the Reviewing Editor has drafted this decision to help you prepare a revised submission.Summary:The revision is very complete with most points forthrightly addressed. One more point remains. This revision should be quick and will not necessitate re-review. See comments of Reviewer #2Reviewer #2:The authors nicely included a quantification of the anatomical patterns of projection from the retina and HB to the tectum. This was done primarily by identifying the location of the peak of flourescence of the HB or retinal inputs to the tectum. While this measure does show a shift that is consistent with the interpretation of the authors, it would have been better to also include a measure of OVERLAP of the HB and retinal input to the tectum. That is, to what degree do the 'red' and 'green' signals from the retinal and HB axons overlap in the tectum with and without manipulation . Such an OVERLAP index (instead of a measure of the location of the peak flourescence) more closely conforms to the interpretation of the anatomical and functional data the authors are presenting. I don't think this is an essential omission, but including an OVERLAP index would have been better. If an OVERLAP index does not show an effect consistent with their interpretation, perhaps the authors can comment on this in the discussion. Essential revisions:There are some concerns that must be addressed, but overall this appears to be a strong study of general significance.1) The examples of anatomical data presented seem to support the conclusions, but the results must be quantified and comparisons made across a number of animals to test whether the differences seen in the examples presented do indeed stand up. Such analysis is necessary for the data in See reviewer 2 #1 below.2) The analysis of CSD sinks should be more thorough or this measure dropped and the physiological analysis restricted LFP. This concern is fleshed out more in the attached comments of reviewer #2.See reviewer 2 #2 below.3) A weakness of the paper is that the MK801 effect is the only direct evidence implicating NMDARs. Without evidence showing that disrupting NMDAR function specifically in tectal cells is sufficient to replicate the MK801 results the exact site of action is not clear. There are several reports of presynaptic NMDARs playing important roles, so the experiments provided do not exclude other NMDAR-dependent mechanisms being at play. Furthermore, in the discussion much attention is given to the fact that the data suggest a fundamentally different mechanism for the sorting of visual/non-visual input in Xenopus compared to other species. This makes the findings interesting, but also means that the cellular mechanism is an important one to hash out.At the minimum this should be addressed in the discussion as a limitation of the preparation and something that should be addressed in the future. This would also be a good opportunity to provide any evidence (references or unpublished data) supporting a model in which NMDAR activity in tectal neurons is, in fact, the cellular mechanism mediating this phenomenon.Whether segregation of visual and mechanosensory inputs relies specifically on postsynaptic NMDA receptors, presynaptic NMDA receptors, or both is not determined in this study, but will be addressed in the future. The following has been added to the Discussion:“Exposing tadpoles to MK-801 blocks all NMDARs, so the possibility that presynaptic NMDARs could play a role in axon segregation cannot be ruled out. […] In addition, this will be an especially interesting experiment given that postsynaptic activation of CaMKII in cultured cortical neurons has been shown to remodel inputs such that the strongest inputs are kept and strengthened while other inputs are completely lost .”We do not suggest a different mechanism in tadpole compared to other species, but a different situation. In the tadpole tectum it is well established that single tectal neurons receive visual and mechanosensory input. Thus, our findings suggest a classic NMDAR-dependent correlation-driven mechanism underlies this subcellular segregation of inputs. This does not mean that NMDAR-dependent mechanisms are not involved in axon segregation in the optic tectum of Zebrafish or chick where axons are segregated, to the best of our knowledge, at the cellular (not subcellular) level. Indeed, NMDARs have been shown to be required for the proper segregation of RGC input onto different cells of the LGN, and for refinement of many circuits .Reviewer #2:While the interpretation is interesting, the data analysis is incomplete, decreasing confidence in the conclusions.There are two principal concerns with the data analysis:1) The anatomical pattern of innervation from the retina and the HB to the tectum, and the effect of eye enucleation and pharmacological treatment, are described anecdotally (a couple of examples). It is possible and probably essential to quantify (and summarize) the effect of enucleation and MK-801 on tectal innervation using some kind of laminar area measure or segregation measure . This would put on much more solid ground the apparent effect of enucleation or MK-801 on HB projection 'segregation'.The manuscript now includes analysis of the spatial fluorescence intensity profiles of the HB and RGC axon projections across the tectum. ImageJ was used to generate the fluorescence intensity profiles . For the enucleation experiment, the peak fluorescence of HB inputs – which presumably reflects the peak in axon density – was measured and reported as the distance from the distal edge of the tectum. For the MK801 experiments, the distance from distal edge of peak fluorescence for both HB and RGC axons was measured as well as the distance (gap) separating these peaks. These data have been added to the figures and the text. The anatomical data are (strikingly) consistent with the FP and CSD data.2) The presentation of CSD and FP is a little confusing. Both are presented in the figures. It is argued that the CSD shows the site of sources and sinks (concentrated synaptic contacts occur at sinks if the structure is laminar in nature). However, only the FP amplitude is quantified, not the amplitude of the CSD sinks. In my opinion, the authors should also quantify the location (and spread as a result of enucleation) of the CSD sinks. If this is altered by the enucleation and/or MK-801, it would strengthen their arguments about the NMDA-receptor dependent 'competitive' segregation process. If quantification of the CSD pattern (and it's changes) is not possible, then this should be explained (and probably the CSD data should be de-emphasized or removed).The location of the major CSD sink along the laminar axis has been quantified and this data has been added to the figures and text. The CSD data is in accordance with the FP data. The amount of shift observed in the major CSD sink due to NMDAR blockade is the same amount of shift observed with the FPs. Identifying the major CSD sink was straightforward. We did not include the quantification of the amount of spread of the CSD sinks, however, as we did not observe such a pattern, probably because the CSDs reflect only δ. So for example if there was a big string of depolarization across the axis (i.e. a spread of depolarization) – this would not be reflected in the CSDs since a persistent depolarization (across space) would not be detected as a change in potential.Reviewer #2:The authors nicely included a quantification of the anatomical patterns of projection from the retina and HB to the tectum. This was done primarily by identifying the location of the peak of flourescence of the HB or retinal inputs to the tectum. While this measure does show a shift that is consistent with the interpretation of the authors, it would have been better to also include a measure of OVERLAP of the HB and retinal input to the tectum. That is, to what degree do the 'red' and 'green' signals from the retinal and HB axons overlap in the tectum with and without manipulation . Such an OVERLAP index (instead of a measure of the location of the peak flourescence) more closely conforms to the interpretation of the anatomical and functional data the authors are presenting. I don't think this is an essential omission, but including an OVERLAP index would have been better. If an OVERLAP index does not show an effect consistent with their interpretation, perhaps the authors can comment on this in the discussion.The amount of OVERLAP between the RGC and HB axons was calculated by measuring the area of the spatial fluorescent profile that was common to both sets of axons. These data are summarized in