Schizophrenia is a mental disorder marked by an evolutionarily puzzling combination of high heritability, reduced reproductive success, and a remarkably stable prevalence. Recently, it has been proposed that sexual selection may be crucially involved in the evolution of schizophrenia. In the sexual selection model (SSM) of schizophrenia and schizotypy, schizophrenia represents the negative extreme of a sexually selected indicator of genetic fitness and condition. Schizotypal personality traits are hypothesized to increase the sensitivity of the fitness indicator, thus conferring mating advantages on high-fitness individuals but increasing the risk of schizophrenia in low-fitness individuals; the advantages of successful schzotypy would be mediated by enhanced courtship-related traits such as verbal creativity. Thus, schizotypy-increasing alleles would be maintained by sexual selection, and could be selectively neutral or even beneficial, at least in some populations. However, most empirical studies find that the reduction in fertility experienced by schizophrenic patients is not compensated for by increased fertility in their unaffected relatives. This finding has been interpreted as indicating strong negative selection on schizotypy-increasing alleles, and providing evidence against sexual selection on schizotypy.A simple mathematical model is presented, showing that reduced fertility in the families of schizophrenic patients can coexist with selective neutrality of schizotypy-increasing alleles, or even with positive selection on schizotypy in the general population. If the SSM is correct, studies of patients' families can be expected to underestimate the true fertility associated with schizotypy.This paper formally demonstrates that reduced fertility in the families of schizophrenic patients does not constitute evidence against sexual selection on schizotypy-increasing alleles. Futhermore, it suggests that the fertility estimates derived from extant studies may be biased to an unknown extent. These results have important implications for the evolutionary genetics of psychosis. Schizophrenia presents researchers with a complex evolutionary puzzle. The features of schizophrenia include a lifetime prevalence of about 1% worldwide  that reveals to potential mates an individual's underlying genetic quality  and condition . This hypothetical fitness indicator would comprise a number of “verbal courtship” traits including creativity, emotional sensitivity, and expressiveness. It is important to stress that, in the fitness indicator model by Shaner and colleagues, there are at least two distinct classes of genetic variants contributing to increased risk for schizophrenia: (a) deleterious mutations in the many brain-expressed genes that contribute to the fitness indicator, which by definition are under negative selection and are maintained by mutation-selection balance; and (b) schizotypy-increasing alleles that enhance the sensitivity of the fitness indicator itself. Schizotypy would then act as an “amplifier” of individual differences in genetic fitness and condition: high-schizotypy individuals would be more likely to achieve outstanding mating success when they have high genetic fitness and/or grow up in good environmental conditions, but also more likely to develop schizophrenia (and to suffer reduced mating success) when they have low genetic fitness and/or grow up in poor conditions. Thus, schizotypy itself can be sexually selected, possibly more strongly so in populations characterized by high levels of mating competition and short-term mating patterns, where displays of good genetic quality are more critical to successful courtship Later, Shaner and colleagues sexual selection model (SSM) of schizophrenia and schizotypy. The fitness indicator model by Shaner and colleagues can be easily integrated with Nettle's original proposal: schizotypy-increasing alleles could affect brain processes so as to increase verbal and artistic creativity , but the outcomes may be either beneficial (mating success) or deleterious (schizophrenia), depending in part on the individual's genetic fitness and condition The low fertility observed in families of schizophrenic patients is a potential stumbling block for the SSM. Individuals with a diagnosis of schizophrenia tend to show low reproductive success relative to controls (about .3 to .8 on average); furthermore, the reduction in fertility is more severe in male patients Although these results are statistically robust and based on very large samples, it is still possible that fertility estimates in patients and their relatives are artificially deflated by unrecognized sources of bias. If, for example, schizotypal males had an increased likelihood of extra-pair conceptions, studies based on census and self-report data would easily miss this component of fertility, leading to systematically deflated estimates. This is not an unlikely possibility, given that schizotypal personality traits specifically predict increased engagement in short-term mating and casual sex The finding of reduced fertility in schizophrenic patients' families has been interpreted as indicating strong negative selection on “susceptibility alleles” that increase the risk of schizophrenia. Furthermore, several researchers have argued that reduced fertility in schizophrenics' relatives supports a strict mutation-selection model in which schizotypy-increasing alleles are not maintained nor favored by selection In conclusion, the evolutionary implications of reduced fertility in schizophrenic patients' families are not clear in the literature, and many researchers seem to believe that the empirical findings in this area undermine the SSM The aim of this paper is to provide a simple mathematical model showing that reduced fertility in the families of schizophrenic patients is fully consistent with the SSM, and can coexist with selective neutrality of schizotypy, or even with positive selection on schizotypy in a given population. It can be shown that, if the assumptions of the SSM hold, empirical studies of patients and their relatives can be expected to underestimate the true fertility associated with schizotypy in the general population.The argument can be stated verbally as follows. If the SSM is correct, individuals who become schizophrenic patients will tend, on average, to have lower genetic fitness  and poorer developmental conditions  compared with those who do not. Their close relatives will share not only their schizotypy-increasing alleles, but also their fitness-reducing mutations and their poor environments. Thus, the families of schizophrenic patients will include a disproportionate proportion of low-fitness individuals, who can expected to suffer reduced fertility compared with high-fitness individuals – and especially with those who enjoy outstanding mating success thanks to their schizotypy-increasing alleles. This sampling artifact will result in a downward-biased estimate of the true fertility associated with schizotypy in the whole population. Under some circumstances, such bias can be strong enough to turn a positive selection pressure on schizotypy into a negative one.A simple but useful mathematical model can be constructed by treating families in a given population as the main unit of analysis. Of course, demarcating families from one another necessarily involves a degree of arbitrariness; however, any reasonable criterion would work for the purpose of this simplified model. Each family can be assigned to one of four classes according to the average level of schizotypy of its members and their average genetic fitness. Families whose members, on average, display comparatively high schizotypy are labeled “schizotypal families”; the remaining families are labeled “non-schizotypal families.” Likewise, “high-fitness families” and “low-fitness families” can be defined as those families whose members' average genetic fitness is (respectively) higher and lower than the population mean. Note that this classification is purely descriptive, and can be applied to any population once families are identified and their members measured on the traits of interest.P(D) of being diagnosed with schizophrenia is higher against a background of low fitness (L) than against a background of high fitness (H). For simplicity, let us further assume that (a) in non-schizotypal families, the probability of developing a diagnosable condition is negligibly small; and (b) in the population as a whole as well as in schizotypal families, genetic fitness is symmetrically distributed across families  be a family member's probability of being diagnosed with schizophrenia. In high-fitness schizotypal families, a member's probability of receiving a diagnosis is P(D|H). The relative risk of schizophrenia based on family fitness is thusLet us first consider low-fitness schizotypal families and let P(L|D) that a randomly selected schizophrenic patient comes from a family with low average fitness can be easily found with Bayes' theorem:The probability R in equation 3 gives:Substituting It follows that:HW be the average fertility of members of high-fitness schizotypal families, and LW the average fertility of members of low-fitness schizotypal families (relative to the population mean). The expected relative fertility W of a random member of a schizotypal family is then:What happens when fertility in schizophrenic patients and their relatives is used as a proxy for the fertility of schizotypal individuals? Let However, when only diagnosed patients and their relatives are sampled, the expected proportion of high- versus low-fitness families in the sample will no longer reflect that in the population, as low-fitness families will be over-represented (eq. 4) and high-fitness families will be under-represented (eq. 5). Since, on average, members of low-fitness families (both patients and their relatives) are expected to suffer a decrease in fertility because of diminished mating success, the disproportionate inclusion of low-fitness families will lead to a negative bias on estimated fertility.In particular, the estimated relative fertility d be the difference Let Since r = 3, and the overall difference in relative fertility between members of high- and low-fitness schizotypal families is d = 1 . In this case,For example, imagine a population where the relative risk of schizophrenia in low- versus high-fitness schizotypal families is d and r; but high values of d and r are exactly what one expects under the assumptions of the SSM. Indeed, if schizotypy-increasing alleles act as “amplifiers” of differences in fitness and condition, and if schizophrenia corresponds to the low-fitness extreme of a sexually selected fitness indicator, both d and r should be large, as they directly reflect the hypothesized effects of schizotypy. Although the model presented here is too coarse to permit accurate quantification of the underestimation bias, the qualitative insights it yields should be taken into account in the evolutionary study of psychosis.In summary, if the SSM is correct, it follows that studies of schizophrenic patients and their relatives consistently underestimate the true fertility associated with schizotypy in the general population (eq. 10). This underestimation bias can lead to infer negative selection even when schizotypy is in fact selectively neutral , or even under positive selection (eq. 11). Moreover, equation 10 shows that the underestimation bias becomes more severe with higher values of In this paper, it was shown that reduced fitness in the families of schizophrenic patients is fully consistent with the sexual selection model (SSM) of schizophrenia and schizotypy; indeed, if the assumptions of the SSM hold, studies of patients' families can be predicted to underestimate the true fertility associated with schizotypy in the general population. In a sense, this result is not completely novel; the consistency of the SSM with low fertility in patients' families was already implicit in the papers by Shaner and colleagues In future work on the evolutionary genetics of schizophrenia, it will be crucial to discriminate between two distinct genetic sources of schizophrenia risk: deleterious mutations and schizotypy-increasing alleles. Whereas mutation-selection balance is the most likely explanation for the maintenance of the former, very different selection regimes can apply to the latter


Plasmodium falciparum elicits host inflammatory responses that cause the symptoms and severe manifestations of malaria. One proposed mechanism involves formation of immunostimulatory uric acid (UA) precipitates, which are released from sequestered schizonts into microvessels. Another involves hypoxanthine and xanthine, which accumulate in parasitized red blood cells (RBCs) and may be converted by plasma xanthine oxidase to UA at schizont rupture. These two forms of ‘parasite-derived’ UA stimulate immune cells to produce inflammatory cytokines in vitro.We measured plasma levels of soluble UA and inflammatory cytokines and chemokines  in 470 Malian children presenting with uncomplicated malaria (UM), non-cerebral severe malaria (NCSM) or cerebral malaria (CM). UA levels were elevated in children with NCSM  and CM  compared to those with UM . In children with UM, parasite density and plasma creatinine levels correlated with UA levels. These UA levels correlated with the levels of seven cytokines . In 39 children, UA levels were 1.49-fold  higher during their malaria episode [geometric mean titer (GMT) 4.67 mg/dl] than when they were previously healthy and aparasitemic (GMT 3.14 mg/dl).P. falciparum malaria by activating immune cells to produce inflammatory cytokines. While this study cannot identify the cause of elevated UA levels, their association with parasite density and creatinine levels suggest that parasite-derived UA and renal function may be involved. Defining pathogenic roles for parasite-derived UA precipitates, which we have not directly studied here, requires further investigation.Elevated UA levels may contribute to the pathogenesis of NCT00669084ClinicalTrials.gov  Plasmodium falciparum causes an estimated 655 million episodes of malaria worldwide and 1 million deaths, mostly in young children living in sub-Saharan Africa P. falciparum malaria is complex, involving multiple parasite and human factors that, in combination, produce varying levels of immune stimulation and microvascular inflammation P. falciparum-derived factors have been shown to activate immune cells to produce the inflammatory responses associated with malaria. These include glycosylphosphatidylinositol (GPI) anchors and DNA-laden hemozoin (a polymer of heme moieties derived from digested hemoglobin), which are released into circulation when sequestered P. falciparum-infected red blood cells (RBCs) rupture in microvessels in vitro to elicit some of the same cytokine responses associated with human malaria syndromes.Each year, et al. showed that soluble UA and ROS, derived from the degradation of hypoxanthine and xanthine accumulated in P. yoelii–infected RBCs, activate murine dendritic cells in vitro to produce TNFα P. falciparum-infected RBCs was significantly reduced in the presence of allopurinol (an inhibitor of xanthine oxidase) or uricase (an enzyme which degrades UA) P. falciparum requires hypoxanthine and xanthine for de novo synthesis of purines en masse and may rupture synchronously, transient high levels of soluble UA may directly stimulate PBMCs. In the third study, van de Hoef et al. found that UA precipitates accumulate in the cytosol and parasitophorous vacuole of intraerythrocytic parasites as they mature in vitro. Whether the inflammatory potential of these parasite-derived UA precipitates in vivo is similar to that of UA crystals, which cause gout Uric acid (UA) is produced in humans and higher primates as the final product of purine metabolism P. falciparum malaria and correlated them with parasite densities, plasma creatinine levels , disease severity and plasma cytokine levels. We found that UA levels (i) increase during episodes of uncomplicated malaria; (ii) increase further during episodes of severe malaria; (iii) correlate with parasite densities and creatinine levels; and (iv) correlate with levels of seven cytokines associated with disease severity in our patient population. These data support a model of malaria pathogenesis in which elevated levels of UA, resulting in part from the combined effects of rupturing P. falciparum-infected RBCs and subclinical renal insufficiency, stimulate the production of inflammatory cytokines.We hypothesized that UA contributes to the pathology of human malaria by stimulating the production of cytokines from immune cells. To explore this hypothesis, we measured plasma UA levels in Malian children with All protocol activities were approved by the Ethics Committee of the Faculty of Medicine, Pharmacy and Odontostomatology at the University of Bamako, Mali, and the Institutional Review Board of the National Institute of Allergy and Infectious Diseases at the National Institutes of Health, United States. The parent or guardian of each child gave written informed consent. The protocol is registered at clinicaltrials.gov (NCT00669084).P. falciparum transmission is seasonal (June–December) and intense. Only children with treatment-seeking behavior for symptoms of malaria were evaluated for the disease; that is, no active case detection was conducted. We used the findings from history taking and physical examination, along with measurements of hemoglobin and glucose , to diagnose each child with uncomplicated or severe malaria. Parasite densities were quantified from thick blood films by counting the number of ring-stage parasites until 300 leukocytes were also counted, then multiplying this number by 25 (which assumes an average number of 7500 leukocytes per µl whole blood). Hemoglobin levels were measured again 72 hours later.To evaluate the effects of human genetic polymorphisms on the incidence of falciparum malaria, we enrolled 1257 children into a prospective longitudinal cohort study in May 2008. Nearly all children aged 6 months–17 years from three neighboring villages  participated. In these villages, located approximately 75 km southwest of Bamako, P. falciparum density with no symptoms or signs of severe malaria or other etiologies of febrile illness discernible by history taking and physical examination. We treated these children with artesunate 4 mg/kg plus amodiaquine 10 mg/kg, given orally, for 3 consecutive days  and confirmed they were aparasitemic on day 3. Children with uncomplicated malaria and P. falciparum density ≥100,000/µl whole blood were treated as for severe malaria.Uncomplicated falciparum malaria was defined by fever  in the presence of any asexual P. falciparum malaria was defined by the presence of any parasite density plus any one of the following: coma (defined as Blantyre coma score ≤2), convulsions (witnessed by the study investigator), severe prostration, severe anemia (hemoglobin ≤5 g/dl), respiratory distress (deep acidotic breathing), hypoglycemia (serum glucose ≤40 mg/dl), jaundice/icterus, shock , cessation of eating and drinking, and repetitive vomiting. All children diagnosed with cerebral malaria met the criterion of coma, had neither hypoglycemia nor convulsions, and responded clinically to antimalarial therapy alone; ocular fundoscopy was not performed. Children with severe malaria were treated with artesunate, given intravenously, followed by the drug regimen for uncomplicated malaria when the child was able to take oral medication.Severe P. falciparum). During the 2008 malaria season, we obtained 2–10 ml venous blood from all children in the cohort who developed malaria, at each episode and prior to antimalarial drug administration. We collected all blood samples into sodium heparin Vacutainers® , separated plasma by centrifugation (2500 rpm×10 min) within 4–6 hours of the blood draw, and immediately stored aliquots at −80°C until use.In May 2008, before the malaria season, we obtained 2–10 ml venous blood from a sub-cohort of 162 children aged 2–14 years who were healthy and aparasitemic  at 4°C. Using polystyrene bead-based multiplex assay kits  according to the manufacturer's instructions, we quantified the levels of IL-6, IL-10, sTNFRII, MCP-1, IL-8, TNFα, IP-10, IFNγ, GM-CSF and IL-1β. We tested samples at a 1∶3 dilution. We read the plates using a Luminex LX100 instrument  and interpolated the results from five-parameter-fit standard curves generated by Xponent 3.1 software (Luminex Corp.). We changed all cytokine or chemokine values = “0.0” to half the next largest value. We replaced IP-10 values = “>380” with the median of all the rest greater than 380 (median = 560), and changed all cytokine values “<X” to “X/2”.We tested plasma samples in triplicate using QuantiChrom™ Uric Acid Assay Kit . This method utilizes 2,4,6-tripyridyl-s-triazine which forms a blue-colored complex specifically with iron in the presence of UA. The colorimetric reaction was read at 590 nm using a plate reader . The method has a linear detection range between 0.22–30 mg/dl (13–80 µM) UA. We used the mean of triplicate values for UA levels in subsequent analyses.Plasma creatinine levels were determined using the Enzymatic Creatinine Flex® Reagent cartridge . In this method, hydrogen peroxide and chromogens  form an amount of colored end product that is proportional to the amount of creatinine in the sample. The colored end product was measured at 540 and 700 nm using the Dimension Vista® System . The analytical measurement range of this method in plasma is 0.14–20 mg/dl.10 UA levels, log10 parasite densities, log10 cytokine levels and log10 creatinine levels by Pearson's correlation coefficient, and tested whether they were different from 0 using the t-distribution. To determine how parasite density and creatinine level predict UA level, we used a linear model with log10 UA level as a response. Analyses were done in either GraphPad version 5.01  or R version 2.13.0 .We compared the values for continuous variables  between groups of children with uncomplicated and cerebral or non-cerebral severe malaria using the Mann-Whitney test with the associated fold-change confidence intervals calculated using the Hodges-Lehmann method on the log-transformed values. The geometric mean titers of UA and creatinine in paired plasma samples were compared using the Paired t test on log-transformed values. We evaluated the relationship between login vitroin vivo, we measured plasma UA levels, parasite densities and plasma cytokine levels in a cohort of Malian children who developed P. falciparum malaria. Plasma samples were available for 90% (501/557) of children who developed a first episode of malaria in 2008. Of these samples, 473, 24 and 4 were from children with uncomplicated malaria (UM), non-cerebral severe malaria (NCSM) and cerebral malaria (CM), respectively. We included in this study an additional 5 plasma samples from children who developed CM in the 2009 malaria season, giving a total of 9 CM samples.Parasite-derived UA stimulates the production of inflammatory cytokines from human PBMCs andvs. 4.67 mg/dl)  and CM  compared to those in children with UM (median 4.60 mg/dl) andFig. 1a10 UA levels correlated significantly with log10 parasite densities  but not age . Since UA levels are known to be affected by renal function  10 UA levels correlated significantly with log10 creatinine levels . In the 39 baseline plasma samples, we found that baseline creatinine levels increased 1.13-fold  during a malaria episode (GMT 0.352 mg/dl vs. 0.398 mg/dl). While these data support the possibility that parasite-derived UA contributes to the elevated UA levels in children with UM, they suggest that subclinical renal insufficiency may contribute as well.To explore the cause of elevated UA levels during a malaria episode, we performed a series of univariate analyses on data obtained from children with UM. We found that log10 UA levels and the log10 levels of seven cytokines, listed here from strongest to weakest: IL-6 , IL-10 , sTNFRII , MCP-1 , IL-8 , TNFα  and IP-10 . These seven correlations remained significant at the 0.05 level even after correcting for the fact that we tested ten cytokines using Holm's multiple comparison correction To investigate a potential role for UA in malaria pathogenesis, we first measured the levels of ten cytokines  that other studies 10 UA level as a response. The model predicts that for a fixed level of creatinine, there is a significant 1.06-fold  increase in UA for each log10 increase in parasite density. Further, for a fixed level of parasitemia, there is a 1.50-fold  increase in UA for each log10 increase in creatinine.To explore how parasite density and creatinine level predict UA level, we used a linear model with logHere we report data from a large number of Malian children who developed uncomplicated or severe malaria in the 2008 malaria season. We found that baseline plasma UA levels increase in UM and further increase in NCSM and CM. In children with UM, UA levels correlated with parasite densities and creatinine levels, suggesting that parasite-derived UA and subclinical renal insufficiency contribute in part to elevating UA levels. UA levels also correlated with IL-6, IL-10, sTNFRII, MCP-1, IL-8, TNFα and IP-10 levels, all of which were elevated in children with severe malaria. These data suggest a model of malaria pathogenesis in which elevated levels of UA stimulate immune and possibly other host cells to produce excessive levels of inflammatory cytokines.P. falciparum-derived UA precipitates activate immune cells via this mechanism has not yet been investigated. Recent work suggests that UA functions as a danger signal to the immune system when it is released from necrotic cells P. falciparum and P. vivax-infected RBCs obtained directly from Peruvian patients with P. falciparum and P. vivax malaria P. vivax malaria, they may also contribute to the pathogenesis of this disease, for example, by stimulating the production of cytokines that induce fever and dyserythropoiesis. Elucidating the pathways by which Plasmodium-derived soluble and precipitated UA stimulate host cells may improve our understanding of the pathogenesis of other diseases in which elevated levels of soluble or insoluble UA are present Studies of non-malaria diseases have shown that crystalline forms of UA are proinflammatory, and have begun to elucidate the mechanisms by which they induce inflammation. In gout, for example, UA crystals have been shown to induce IL-1β production through the NALP3 inflammasome pathway P. falciparum malaria in African children, but also raises the possibility that the UA level may serve as a useful biomarker for severe disease. In addition, our findings may help to explain those of Sarma et al.P. falciparum malaria. Our data also provide some evidence to support the need for clinical trials to investigate whether allopurinol, which has been safely administered at UA-lowering doses to patients with severe P. falciparum malaria Our findings not only support the hypothesis that UA contributes to the pathogenesis of P. falciparum densities in patients with malaria. Bertrand et al. et al.This study reports data from a relatively large number of Malian children of all ages who presented with malaria syndromes that were clinically well-defined. To our knowledge, this is the first study to specifically investigate associations between UA and inflammatory cytokines during episodes of human malaria. Before making these correlations, we confirmed that the cytokines we measured increase with disease severity, thus implicating them in the pathogenesis of severe malaria in our Malian study population. Previous studies that measured UA levels in patients with malaria tested the hypothesis that UA is an indirect marker of oxidative stress et al.in vitro.Our study has several limitations. First, we are unable to identify the cause of elevated UA levels in our patients. During a malaria episode, excess soluble UA may be produced by a variety of processes, including the dissolution of parasite-derived UA precipitates, the conversion of parasite-accumulated hypoxanthine and xanthine to UA by plasma xanthine oxidase, and the hemolysis of both parasitized and non-parasitized RBCs. The levels of UA produced by any of these processes may correlate with parasite density. More detailed studies of renal function in children with malaria are needed to determine whether subclinical renal insufficiency also helps to increase the concentration of UA in plasma. Second, we are unable to quantify the ‘local’ levels of parasite-derived UA in microvessels. UA and cytokine levels may be considerably higher in the post-capillary venules where schizonts rupture than in the large veins from which we obtain plasma. We are also unable to quantify the amount of parasite-derived UA precipitates that may be present as un-dissolved, yet immunostimulatory, material in microvessels. Third, the correlations between UA and cytokine levels cannot definitively establish that UA is directly stimulating immune cells to produce the cytokines we measured. In support of this possibility, however, we found that UA levels correlate significantly with IL-6, TNFα and IL-10 levels. These findings are consistent with those of Orengo P. falciparum malaria, may provide direct proof that parasite-derived UA precipitates are localized to microvessels and in contact with immune or other host cells  that produce the cytokines we measured.In summary, the present study provides clear evidence that baseline UA levels increase in malaria and that UA levels correlate with the levels of multiple cytokines implicated in the pathogenesis of this disease. Confirming a role for soluble UA in causing the symptoms and complications of malaria may require clinical trials of allopurinol or uricosuric drugs as adjunctive therapies. Immunohistochemical staining of autopsy specimens, or biopsies of muscle and dermis in live patients with uncomplicated


The seroprevalence of human T-cell leukemia virus type 1 (HTLV-1) is very high among Brazilians (∼1∶200). HTLV-1 associated myelopathy or tropical spastic paraparesis (HAM/TSP) is the most common neurological complication of HTLV-1 infection. HAM/TSP can present with an acute/subacute form of longitudinally extensive myelitis, which can be confused with lesions seen in aquaporin-4 antibody (AQP4-Ab) positive neuromyelitis optica spectrum disorders (NMOSD) on MRI. Moreover, clinical attacks in patients with NMOSD have been shown to be preceded by viral infections in around 30% of cases.To evaluate the frequency of AQP4-Ab in patients with HAM/TSP. To evaluate the frequency of HTLV-1 infection in patients with NMOSD.23 Brazilian patients with HAM/TSP, 20 asymptomatic HTLV-1+ serostatus patients, and 34 with NMOSD were tested for AQP4-Ab using a standardized recombinant cell based assay. In addition, all patients were tested for HTLV-1 by ELISA and Western blotting.20/34 NMOSD patients were positive for AQP4-Ab but none of the HAM/TSP patients and none of the asymptomatic HTLV-1 infected individuals. Conversely, all AQP4-Ab-positive NMOSD patients were negative for HTLV-1 antibodies. One patient with HAM/TSP developed optic neuritis in addition to subacute LETM; this patient was AQP4-Ab negative as well. Patients were found to be predominantly female and of African descent both in the NMOSD and in the HAM/TSP group; Osame scale and expanded disability status scale scores did not differ significantly between the two groups.Our results argue both against a role of antibodies to AQP4 in the pathogenesis of HAM/TSP and against an association between HTLV-1 infection and the development of AQP4-Ab. Moreover, the absence of HTLV-1 in all patients with NMOSD suggests that HTLV-1 is not a common trigger of acute attacks in patients with AQP4-Ab positive NMOSD in populations with high HTLV-1 seroprevalence. NMO, LETM, and ON are often referred to as ‘NMO spectrum disorders’ (NMOSD) Neuromyelitis optica (NMO) is an inflammatory disease of the central nervous system (CNS) of putative autoimmune aetiology, which is characterized by severe attacks of myelitis and optic neuritis (ON) It is estimated that 15 to 20 million individuals are infected with the human T-cell leukemia virus type 1 (HTLV-1) worldwide There are few population-based epidemiological studies of NMOSD, but it seems that the disease is more prevalent in peoples of Asian, African-American or Hispanic background when compared with those of Northern European descent As testing for aquaporin-4 antibodies (AQP4-Ab) became available only few years ago, cases of AQP4-Ab positive LETM occurring in the context of HTLV-1 seropositivity might thus have been misdiagnosed as acute HAM/TSP in a subset of patients in the past. Furthermore, AQP4-Ab positive NMO was shown to be frequently preceded by viral or bacterial infections and HTLV-1 infection may act as a trigger of NMO in some cases This study aimed to determine the seroprevalence of antibodies to AQP4 in patients with HTLV-1 associated myelopathy (HAM/TSP) and that of HTLV-1 antibodies in patients with neuromyelitis optica spectrum disorders (NMOSD) and to compare the clinical characteristics of a HAM/TSP and NMOSD in Brazilian patients.This is a cross-sectional study that included along with regular visits NMOSD patients who were followed-up at the neurological outpatient unit of the University of Campinas (UNICAMP) Hospital as well as HTLV-1 seropositive asymptomatic and HAM/TSP patients attending the outpatient clinic at the Emilio Ribas State Reference Institute of Infectious Diseases and at the UNICAMP Hospital, São Paulo, Brazil, during the period of January 2011 to January 2012.Schistosoma mansoni, which is endemic in northeast Brazil) At each appointment, demographic and clinical data were collected and the neurological statuses were evaluated by different scales, including the EDSS Peripheral blood samples were collected from patients diagnosed with HAM/TSP as defined by World Health Organization (WHO) criteria UNICAMP and Emilio Ribas Institute of Infectious Diseases Ethics Committees for Research approved the study and all patients provided informed written consent. On the behalf of the minors/children participants involved in our study, we obtained informed written consent from one of their parents.p values <0.05.We tested all peripheral blood samples for AQP4-Ab in a standardized cell based immunofluorescence assay  employinSerum AQP4-Ab were detected in 20 out of 34 (59%) patients in the NMOSD group, which included patients with NMO (positive in 14/17 cases) and patients with syndromes considered to confer a high risk for conversion to NMO   revealed an elevated spontaneous proliferative response when compared with a healthy control. After cells were cultured for 48h and pulsed with thymidine during 18h, the proliferative response were determinated by the mean incorporation of thymidine in DNA, and indicated as counts per minute (cpm). This spontaneous proliferation of PBMC in vitro is an immunopathologic characteristic of HTLV-1–infected individuals, driven by the HTLV-1-encoded TAX protein and indicate the exaggerated proinflammatory cellular immune response One patient developed an atypical form of HAM/TSP with relapsing subacute LETM and ON. HTLV-1 antibodies were detectable in serum and in the cerebrospinal fluid (CSF) of this patient by western blot analysis; by contrast, serum AQP4-Ab were negative. Moreover, In the NMOSD group, no difference regarding gender was found between AQP4-Ab positive and negative patients . 15 out 32 (47%) patients self-reported their ethic origin as afrodescendant in the NMOSD group, 9 out of 17 (53%) in the HAM/TSP group, and 7 out 15 (47%) in the HTLV-1+ group.Regarding the median degree of disability, as measured by Osame scale (p = 0.47) and EDSS (p = 0.52), there were no statistically significant differences between the three groups . An OsamOur findings are relevant not only from a diagnostic but also from a pathophysiological point of view. HTLV-1 infection is highly prevalent among Brazilians, and patients with HAM/TSP can present with an acute/subacute form of longitudinally extensive myelitis, which can be confused with LETM lesions seen in NMOSD on MRI. Our results argue both against a role of antibodies to AQP4 in the pathogenesis of HAM/TSP and against an association between HTLV-1 infection and the development of AQP4-Ab. Moreover, the fact that antibodies to HTLV-1 were absent in all patients with NMOSD suggests that HTLV-1 is not a common trigger of acute attacks in patients with AQP4-Ab positive NMOSD, a disorder in which relapses are often preceded by infection, in populations with high HTLV-1 seroprevalence.NMOSD and HAM/TSP are both highly prevalent in some global areas. In Japan and in Martinique, for example, NMOSD accounts for around 40% and 17.3% of cases of CNS demyelinating diseases, respectively, and these areas also feature a high prevalence of HTLV-1 infection Regarding the patients’ epidemiological data, we found an older median age at onset in the HAM/TSP group compared to the NMOSD group in accordance with the literature, possibly reflecting the long latency of HTLV-1 infection The relative high EDSS and Osame scores in the NMOSD group as compared to the HAM/TSP group despite a shorter disease duration reflects the attack severity in NMOSD with poor recovery In conclusion, our findings indicate that misdiagnosis of NMOSD as HAM/TSP is rare and support the view that LETM associated to either HAM/TSP or NMO are distinct disorders, which are likely to be pathogenetically unrelated.


It has been recently demonstrated that serum uric acid (UA) is associated with metabolic syndrome (MetS) or its related clinical indications based on cross-sectional or prospective cohort studies. Nonetheless, due to the fact that UA level constantly fluctuates from time to time even for the person, using a single measure of UA level at baseline of those studies may not be sufficient for estimating the UA-Mets association.To further estimate this time-dependent association, we fitted a generalized estimating equation (GEE) regression model with data from a large-scale 6-year longitudinal study, which included 2222 participants aged > =25 years with an average of 3.5 repeated measures of UA per person in the Health Management Center of Shandong Provincial Hospital, Shandong, China.p < 0.0001). It was found that UA level was positively associated with obesity, hypertension, and dyslipidemia, but was inversely associated with hyperglycemia.After adjusting for other potential confounding factors , it was verified that time-dependent UA level was an independent risk factor for MetS (OR = 1.6920, Serum UA level may serve as an important risk factor of MetS. Additionally, our study suggested that UA level be an independent risk factor to obesity, hypertension and dyslipidemia, but a protective factor to hyperglycemia. These findings are concordant with results from other studies on Asian populations, and jointly provide a basis to further develop a risk assessment model for predicting MetS using UA levels and other factors in China. Metabolic syndrome (MetS) refers to a combination of medical disorders ,including obesity, dyslipidemia, hypertension and insulin resistance. When ocIn our longitudinal study, participants include 2222 male residents of Shandong Province who visited HMCSPH (an affiliate of organization of Shandong University) at least three times for annual physical examinations between 2005 and 2010. During the 6 year follow-up, each participant on average had 3.63 ± 0.016 measures including serum UA levels. For this study, we only included participants who had not been diagnosed as having MetS at baseline. They were all Chinese Han with baseline age between 25 and 91 years, all belong to middle and upper socioeconomic classes. This study was approved by the Ethics Committee of School of Public Health, Shandong University, and all participants gave informed written consent.Blood samples were collected from participants after an overnight fast of at least 12 hours. Height and weight were measured on participants wearing light clothing without shoes, and body mass index (BMI) was calculated as weight (kg) divided by squared height (m). Blood pressure was measured on right upper arm with participants in sitting position after 5 minutes rest. Peripheral blood samples was obtained for measuring the following parameters: glucose, total cholesterol (CHOL), low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides, uric acid (UA), gamma-glutamyltranspeptidase (GGT), serum albumin (ALB), serum globulins (GLO), blood urea nitrogen (BUN), serum creatinine (CREA), hemoglobin (Hb), hematokrit (HCT), mean corpuscular volume(MCV), mean corpuscular hemoglobin (MCH), Red blood cell distribution width (RDW), white blood count (WBC), platelet distribution width (PDW), mean platelet volume (MPV), and thrombocytocrit (PCT). Data on smoking habits, alcohol intake, diet habits, sleeping quality, exercise frequency, and other variables were obtained using standardized questionnaire.Considering the physiological characteristics of our target population, the diagnostic criteria recommended by Diabetes Branch of the Chinese Medical Association (CDS)  was usedIn our longitudinal study, there were some variables  as cut-off values. As seen in Table Before fitting a GEE model, the original continuous serum UA measure was categorized into 4 levels using the 3 quartiles . To study the association between UA levels and MetS, we first fitted simple GEE models, each with a single predictor . We finally fitted a multiple GEE regression model. A covariate was added to the final multiple regression model only if it was found significant (p < 0.05) in the single-predictor model. Note that the GEE modelling strategy is capable of describing time-dependent relationship between UA levels and the MetS status (yes or no), after adjusting potential confounders. All these variables are repeatedly measured during the 6-year follow-up. Age at baseline was also added to the multiple GEE analysis procedure to adjust for the age effect. In each GEE model, ‘Logit’ was chosen as the link function of GEE, because either MetS status is a binary dependent variable. Following the same procedure, we studied the association between UA levels and each one of the four medical disorders in defining MetS , which were all defined as binary variables. All statistical analysis was performed by SAS 9.1.3.Additional file Table p < 0.0001). Although not significant, the ORs for Q2 and Q3 were all larger than 1.0, and an increasing trend was seen in OR from Q2 to Q4.Table The results on association of UA levels with each single MetS component, are shown in Table 4, 5, 6 and 7 of the Supplemental Materials, respectively for overweight/obesity, hypertension dyslipidemia and hyperglycemia. Table 4 shows that UA was a strong independent risk factor to overweight/obesity; and an obvious increasing trend in OR is seen from Q2 to Q4 after adjusting the other three components of MetS and potential confounding factors. Table The relationship among UA, MetS and cardiovascular diseases has received much attention in recent years. The findings from a nationwide representative sample of US adults indicate that the prevalence of the MetS increases substantially with increasing levels of UA . UA as aAs an essential component of MetS, obesity was regarded as a main contributor of the increasing prevalence of MetS, because obesity was proved as a risk factor of hypertension, dyslipidemia and hyperuricemia . The posThe association between hyperglycemia and UA, however, still remained controversy. Most researches suggested that hyperglycemia and UA should be the pathophysiological underpinning of MetS a long time ago , and a nUA was first demonstrated to be associated with hypertension by Mohamed in 1870 s , and in Finally, it has been well received that elevated UA level would increase the risk of dyslipidemia ,30. Our Association between UA and cardiovascular diseases has been reported frequently recent years. Many research confirmed that UA was a strong risk factor for cardiovascular diseases, especially MetS -35. Our There were several limitations in the present study. Due to the fact that participants of the study who came to the hospitals mainly for physical examinations, they were mandatorily asked to report histories on medication for treating MetS or related medical disorders . Thus we did not have data on medication in our GEE regression analyses in studying the UA–MetS association. Also considering that our study contains only local males from relatively rich and educated families in Shandong province, and the fact that our analyses only covered a follow-up period of 6 years and no genetic information was included, it is expected a large scale longitudinal study is expected for a better and fully understanding of the target relationships.There is no conflict of interest for any of the authors. All authors had access to the data and were involved in drafting the article and revising it critically for important intellectual content.In our work, FX and CZ designed the study and directed its implementation, including quality assurance and control. XS, FT, HL and DZ did the clinical exam and collected the data. WM, YZ and ZZ helped analyzing the data. LL provided scientific comments and advice. XY worked on writing of the paper. QZ participated much of the above work and led the writing of the paper. All authors read and approved the final manuscriptThe pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/12/419/prepubTable S1. The distribution of UA levels and other potential confounding factors. Table S2 Numbers Participants at Each Year of the Study Click here for file


The bZIP factor (HBZ) is an HTLV-1 regulatory protein encoded by anti-sense transcription of the HTLV-1 genome. HBZ mRNA expression correlates with clinical disability in HAM/TSP patients – and can be reversed by interferon (IFN) therapy. Sporadic evidence suggests that HBZ may have a negative role on interferon signalling. Activation of IRF3-dependent IFN signalling – either direct induction of IFNβ, viral restriction factors or interferon stimulated genes (ISGs) – is crucial for TLR and RLR mediated antiviral response. Thus, we sought to determine whether HBZ can impair IRF3-mediated innate immune responses. Over-expression of active forms of RIG-I, MAVS, TBK1, IKKε or IRF3 alone drive an antiviral response – however, in the presence of an HBZ expression vector, IFNβ responses were abrogated by 50-70%. In contrast, HBZ enhanced IRF7-dependent responses. In confirmation, both PBMC and human astrocytes transfected with HBZ and subsequently stimulated with IFN-triggering ligands , exhibited impaired IRF3-dependent signalling as compared with controls. As IRF3 is known to bind other bZIP proteins, further studies are underway to delineate the nature of IRF-HBZ interactions. Identifying such a mechanism may explain an enhanced risk of neurologic infection, as we show that chronically HTLV-1 infected astrocytes gradually increase and maintain long-term HBZ expression. Defining the immunomodulatory properties of HTLV-1 HBZ protein will provide a vital contribution toward understanding clinical outcome and risk of opportunistic infection associated with HTLV-1 infection.


Human T-cell leukemia virus type 1 (HTLV-1) causes adult T-cell leukemia (ATL) and HTLV-I-associated myelopathy/tropical spastic paraparesis (HAM/TSP) in a small percentage of infected individuals. ATL is often associated with general immune suppression and an impaired HTLV-1-specific T cell response. We previously found that a small fraction of asymptomatic HTLV-1-carriers (AC) also showed impaired T cell responses against the major target antigen Tax. However, it is unclear whether the impaired HTLV-1-specific T cell response in these individuals is an HTLV-1-specific phenomenon, or merely reflects general immune suppression. In this study, we investigated the function of Tax-specific cytotoxic T lymphocytes (CTLs) using tetramers consisting of major CTL epitopes and HLA-A0201, A2402, or A1101 in various HTLV-1-infected individuals possessing these HLAs. Tax-specific CTLs were detected in 33.3% (n=7/21), 100% (n=18/18), and 86.4% (n=19/22) of chronic ATL (cATL) patients, HAM/TSP patients, and AC, respectively. Tax-specific CTLs of all HAM/TSP patients tested proliferated well in culture and produced IFN-γ when stimulated with Tax peptides, while Tax-specific CTLs detected in cATL patients did not. In ACs, the Tax-specific CTL responses were retained in most cases. However, Tax-specific CTLs in one AC hardly produced IFN-γ and failed to proliferate or express a degranulation (CD107a) marker upon Tax peptide stimulation. In contrast, cytomegalovirus (CMV) pp65-specific CTLs in the same donor could be fully activated by pp65 peptide stimulation. These findings indicated that HTLV-1-specific T cell function is impaired in a limited population in an HTLV-1-specific manner during an asymptomatic stage.


KRAS mutations are frequent in colorectal cancer (CRC) and have the potential to activate proliferation and inhibit cell death through effects on MAPK/ERK and PI3K/Akt signaling pathways. Because diet is one of the most important determinants of CRC incidence and progression, we studied the effects of the dietary triterpenoid ursolic acid (UA) on proliferation and cell death induction in human CRC derived KRAS mutated cell lines.Our results show that UA decreases cell proliferation and induces cell death while decreasing signaling through KRAS as indicated by a decrease in ERK and Akt phosphorylation (western blot). UA also induced cell death.TP53 mutated cells are known to be resistant to the chemotherapeutic drug 5-FU. Caspase independent apoptosis (Tunel assay), was increased 6 fold by co-incubation of UA with 5-FU. However, apoptosis was only a small percentage of the total cell death induced by UA. In order to explain these observations, we looked into effects on autophagy. Autophagy is emerging as a promising therapeutic target for drug resistant tumors. UA modulated autophagy by inducing the accumulation of LC3 II and p62 levels an effect dependent on JNK activation.In conclusion, this study shows UA’s anticancer potential as a modulator of KRAS signaling and cell death mechanisms increasing sensitivity to the chemotherapeutic drug 5-FU.


Yersinia pestis and E. coli infections identified the key perturbation in the network and potential drug targets. Thus, our analyses of TLR4 signaling highlights the role of phosphatases as key regulatory factors in determining the global interdependencies among the network elements; uncovers novel signaling connections; identifies potential drug targets for infections.Among the 13 TLRs in the vertebrate systems, only TLR4 utilizes both Myeloid differentiation factor 88 (MyD88) and Toll/Interleukin-1 receptor (TIR)-domain-containing adapter interferon-β-inducing Factor (TRIF) adaptors to transduce signals triggering host-protective immune responses. Earlier studies on the pathway combined various experimental data in the form of one comprehensive map of TLR signaling. But in the absence of adequate kinetic parameters quantitative mathematical models that reveal emerging systems level properties and dynamic inter-regulation among the kinases/phosphatases of the TLR4 network are not yet available. So, here we used reaction stoichiometry-based and parameter independent logical modeling formalism to build the TLR4 signaling network model that captured the feedback regulations, interdependencies between signaling kinases and phosphatases and the outcome of simulated infections. The analyses of the TLR4 signaling network revealed 360 feedback loops, 157 negative and 203 positive; of which, 334 loops had the phosphatase PP1 as an essential component. The network elements' interdependency (positive or negative dependencies) in perturbation conditions such as the phosphatase knockout conditions revealed interdependencies between the dual-specific phosphatases MKP-1 and MKP-3 and the kinases in MAPK modules and the role of PP2A in the auto-regulation of Calmodulin kinase-II. Our simulations under the specific kinase or phosphatase gene-deficiency or inhibition conditions corroborated with several previously reported experimental data. The simulations to mimic  Toll-Like Receptors (TLRs), thirteen in vertebrates, are the members of pattern recognition receptor family (PRRs) and recognize the pathogen-associated molecular patterns (PAMPs) In such complex biological systems of signal processing and integration, understanding the inter-regulation between the signaling elements by computational reconstruction of the signaling networks enables one to systematically investigate the regulatory principles associated with the network and thus to build hypothesis that can subsequently be tested through experiments. For capturing the quantitative system level properties of signaling network dynamic modeling approaches Escherichia coli and Yersinia pestis. The model at its current state is open to experimental tests and thus further fine-tuning; as it was observed that training such logical models with high throughput experimental data remarkably increases its predictive power Here, we have constructed a logical model of TLR4 signaling utilizing information derived from hundreds of independent experimental reports. The preliminary information was gathered from the comprehensive map of TLR signaling We started the model building by extracting the information on the TLR4-specific interactions from the comprehensive map of TLR signaling In the logical model the state 1 and 0 represents on (active) and off (inactive) state, respectively.In the simplest kind of interaction where an upstream directly activates its downstream, activation state 1 of the upstream activator is transferred to the downstream, representing the signal flow. Consider for example, a set of molecules X, Y and Z; 1] if activation of Z requires activation of both X and Y simultaneously, then the logic gate AND connects A, B to C as: X AND Y = Z; 2] If Z is activated when any of its upstream X or Y are active, then the Boolean gate OR connects X, Y, Z as: X OR Y = Z; 3] If Z is active only when X is active but Y is NOT active then the NOT gate connects the elements as X+NOT Y = Z. The TLR4 model comprised of 40 input nodes. These inputs correspond to TLR4 receptor; TLR4 ligand, co-receptor CD14 and lipopolysaccharide binding protein (LBP) and the rest 36 are the intermediates for which direct activators or inhibitors are not know clearly. In biological system activation of signaling elements in a pathway is temporal in nature which is determined by the hierarchy of signal flow from membrane to nucleus. To mimic the dynamicity (or pseudo dynamics) of signal flow like a real system we have opted time scale scenario formulation by selectively assigning different time scale to different signaling elements in a hierarchical manner Time scale 0: Formation of ligand receptor complex and activation of housekeeping species.Timescale 2: Activation of the all-cytoplasmic reactions taking place after recruitment of ligand to the receptor.Time scale 4: Activation of reactions corresponding to the nuclear translocation of specific cytoplasmic kinases that leads to triggering of transcription factors or activation of other target molecules/genes.Time scale 7: In this time scale signaling events in the nucleus that are triggered by the MyD88 dependent pathways were activated. List of the reactions involved in the MyD88 dependent pathway is given in Time scale 7.1: Activation of the TRIF dependent pathway was assumed to occur at later as suggested by experimental studies Time scale 8: Finally in the time scale 8 the cytoplasmic and nuclear phosphatases and inhibitors of the TLR4 signaling were activated. This leads to complete shutdown of information flow in the system.In the in-vivo settings, the cytoplasmic/nuclear phosphatases can be activated earlier to the time required for the signal to reach the nucleus or they remain constitutively active causing an attenuation/suppression of the signal strength, thus imparting dynamically achieved finer regulations Feedback loops are pivotal for the functioning of almost all the signal transduction networks. Various dynamic analyses of signaling systems show that positive feedback loops lead to signal amplification, multi-stability and hysteresis or tolerance An important element in the feedback loops are the phosphatase of the network When all the phosphatases of the system were knocked out, 25 feedback loops remained. These 25 feedback loops owed their origin purely to kinase-mediated interactions of which 5 were negative and 20 were positive feedback loops. The interactions that gave rise to the 25 feedbacks were next extracted and shown; 11 reactions were found to comprise the 5 negative feedback loops and 31 reactions comprised the 20 positive feedback loops, respectively . RelativAs interdependencies among the signaling intermediates characterizes cell signaling Typically in large-scale networks a remote downstream kinase could be an activator/inhibitor of an upstream molecule and the process of activation/inhibition comprises multiple intermediates The model of the TLR4 signaling network contained 181 species, so the size of the dependency matrix is 181×181; making its visual comprehension and representation inconvenient. We thus selected a subset of the total elements of the complete dependency matrix comprising molecules such as the MAP kinases , Akt, NIK, IKK and CAMKII which are representative of distinct signaling pathways activated during TLR4 signaling, together with the phosphatases MKP-1, MKP-3, PP1, PP2A. The chosen kinases are also pivotal biologically, as they carry out growth, differentiation, and proliferation and are involved in several diseased conditions −/−, PP2A−/−, MKP-1−/−, PP1−/−, (MKP-3+ MKP-1)−/−, (MKP-3+PP2A)−/−, (MKP-3+PP1)−/−, (MKP-1+PP2A)−/−, (MKP-1+PP1)−/−, (PP1+PP2A)−/−, (MKP-3+MKP-1+PP2A)−/−, (MKP-3+PP2A+PP1)−/−, (MKP-1+PP2A+PP1)−/− and (MKP-3+MKP-1+PP2A+PP1)−/−. Several interesting behaviors were observed in the knockout conditions all of which cannot be discussed due to the volume of the information. So, we state some interesting regulatory behaviors exhibited by the system in different knockout conditions that can be easily tested experimentally.Effects of various in-silico phosphatases' knockout and resultant alterations of the positive/negative dependencies among species are detailed . The com> ERK-1/2 acted as an ambivalent factor of MEKK3 and IKK in the wild type condition but in the MKP-3 knock out condition, ERK-1/2 become an activator of MEKK3 and IKK; this suggests that the negative effect from ERK-1/2 to MEKK3 and IKK is mediated in an MKP-3 dependent manner. In addition, in the MKP-3 knockout condition ERK-1/2 becomes an inhibitor of PP2A and p38MAPK whereas in the wild type condition ERK-1/2 is ambivalent to both. ERK-1/2 becomes an activator of CAMKII and inhibitor of Akt in MKP-3 knock out condition whereas in wild type condition ERK-1/2 is ambivalent to both  whereas in the wild type condition CAMKII ambivalently affects itself and Akt. Thus the positive self-regulatory loop of CAMKII must have PP2A as an essential element. Also PP2A has a dual role (positive and negative) in CAMKII mediated regulation of Akt in the wild type condition. Further, knockout studies in the model show that the positive loop from CAMKII to Akt is abolished when MKP-1+PP1 is knocked out .> All the signaling paths from MKP-1 to MEKK3, CAMKII and Akt have PP2A as an essential element as in the PP2A knock out condition MKP-1 is no longer connected to these kinases . Such coIndependent experiments show that in TLR4 signaling ERK-1/2 regulates IL-10 production both positively Logical steady state analysis (LSSA) was performed to understand the characteristics of signal flow through the TLR4 network. In LSSA the state 1 means an on state and a state 0 means off state. In LSSA, the state of each model element is consistent with the value of its associated Boolean function, and therefore, once a Boolean network has moved into a logical steady state, it will stop to switch and then retain this state −/− mice phosphorylation of the MAPKs'  and I-κB is reduced  = 0. We found 6 positive signaling paths that connect TRADD to MAPKs' and 110 signaling path that connects TRADD to I-κB. The signaling paths unravel the plausible intermediates involved in transmitting the signal from TRADD to the affected molecules, which is open to experimental validation.As demonstrated earlier E.coli and Yersinia pestis and investigated whether the model predictions fall in the same lines as the experimental reports on the same.Several pathogens are known to perturb TLR4 signaling during their host invasion. We tested two cases of infection; infection by uropathogenic Yersinia pestis is a Gram-negative bacterium that causes bubonic plague. YopJ protein found in Yersinia inhibits MKK6 and IKK by acetylation Yersinia Yopj protein also inhibits MKK6 and IKK Yersinia plausibly uses this strategy to overcome the defense mechanism of the immune system by selective inhibition of the pro-inflammatory cytokines' production and allowing only the production of anti-inflammatory cytokine such as IL-10. IL-10 production in the infection condition is ERK1.2 dependent, which is activated through a path comprising Rac.GTPase. To alter the infection condition one strategy would be to suppress the ERK-1/2 activation which in our model would mean ERK-1/2 = 0. We thus calculated the MIS  the network elements that correspond to parasitic infections where our simulations reproduced the experimentally reported inhibition of cytokines. The therapeutic utility of the model was examined by predicting the potential drug targets through MIS analysis. In addition, SHP1-mediated regulation of TLR4 signaling was simulated by adding three additional reactions in our model as SHP1 inhibits TLR4-mediated IRAK1 activation Taken together, this study helps in understanding the structural organization based working principles governing the whole cell level TLR4 signaling and poses a number of conjectures that can be experimentally verified. As proposed earlier For qualitative analysis of the TLR4 signal transduction pathway, we have used a Boolean logic based modeling approaches for modeling signaling networks, implemented in the MATLAB toolbox CellNetAnalyzer nd row, 2nd column). Biologically it is possible to form a ligand receptor complex [TLR4.L] only when both ligand and receptor comes together. Using the Boolean gate AND  we could implement such biological relations where the function AND allows the TLR4.L to be active (state = 1) only when TLR4 = 1 and LIGAND = 1.For example, TLR4 receptor and ligand binding steps are represented by two interaction graphs  the OR gate is appropriate to capture the situation . When any one of ERK-1/2 or p38MAPK = 1, the activation state of Mnk1 = 1.On the contrary, there are situations where any one activator  is sufficient for triggering activation of a substrate. For example Mnk1 can be phosphorylated either by ERK-1/2 or p38MAPK. So . Boolean representation of such situations is shown  where AND NOT gate captured the biological relation between these three species.In another scenario, elements like Elk1 requires p38MAPK = 1 and PP2B = 0 for its activation state to become 1  making the analysis process complicated. However the information of influence of one species on rest of the model elements could be extracted from the dependency matrix using CNA Minimal intervention set (MIS) in an interaction networks is the  sets of elements that are to be removed or to be added in order to achieve a certain goal such as activation or inhibition of a target molecule Logical steady state shows the activation state of a set of molecules on assigned time scale for given input signal. For computation of the logical steady state in a particular situation, for example, in a Myd88 knockout situation, values = 1 or 0 were assigned to the respective species and then the LSS were computed at time scale 7.1. Time scale 7.1 was selected for analyzing the effect of a knockout or addition of inhibitors in the system because at time scale 7.1 the signal was allowed to flow through the entire span of the network. During the calculation of the LSS few interactions were not considered. For example, p38MAPK and TAK.TAB1 which are activated at the same time scale are connected though a NOT gate, blocking the downstream flow of signal. As the p38aMAPK activation and the TAK.TAB1 activation occur in the time scale 2, and as p38aMAPK inhibits the TAK.TAB1, calculation of LSS at any further time scale above 2 calculates the downstream signaling effect considering TAK.TAB1 = 0. Hence the LSS calculations were carried out without including the feedback loop from p38MAPK to TAK.TAB1. A total of five interactions  were removed during the calculation of logical steady stateshown in .As discussed above in the We implemented results of various experiments in the logical model aiming to validate its predictive power. For example, experimental data shows that in Myd88 knockout mice production of inflammatory cytokine is down regulated. We knocked out My88 in the model by assigning it a 0 value and computed the LSS at time scale 7.1 which qualitatively reproduced the experimental observations. Several such examples are shown.Figure S1(A–Q) Dependency matrix in different conditions of phosphatases knockout. In addition, screenshot of the model LSS for E.coli and Yersinia infection is shown.(PDF)Click here for additional data file.Table S1Supplementary table S1 shows the list of all reaction involved in the TLR4 signal transduction.(DOC)Click here for additional data file.Table S2List of all species of the TLR4 logical model.(XLS)Click here for additional data file.Table S3Relative participation of different reactions in positive and negative feedback loops in (MKP3+MKP1+PP2A+PP1) knockout condition.(XLS)Click here for additional data file.Table S4Dependency matrix showing influence of a particular kinase  on other kinases (elements of different rows in the matrix), in different conditions of phosphatases knockout alone or in combinations.(XLS)Click here for additional data file.Table S5Logical steady state of all output species on different time scale and in knock in condition of individual inhibitor in a full activated system .(XLS)Click here for additional data file.Table S6Logical steady state of the output species in infection condition of Yersinia and Uropathogenic E. coli.(XLS)Click here for additional data file.Table S7Validation of Model through comparison of Logical Steady State Analysis (LSSA) results to various experimentally reported results.(DOC)Click here for additional data file.Table S8MISs for the production of the TNF-α in the E. coli infection condition.(XLS)Click here for additional data file.Table S9List of the reactions, which are eliminated during the calculation of the logical steady state analysis of model.(XLSX)Click here for additional data file.Model S1Logical models of the TLR4 signal transduction pathway is presented. The file contains two folders. The model TLR4_LSSA_Complete was used for the feedback loop analysis. TLR4_LSSA was used for the logical steady state analysis of the TLR4 signal transduction pathway. The MATLAB toolbox CellNetAnalyzer was used for both the analysis.(RAR)Click here for additional data file.


Mycobacterium tuberculosis. Here, we examined the role of STPK pknE, using a deletion mutant ΔpknE in the modulation of intracellular signaling events that favor M. tuberculosis survival. Phosphorylation kinetics of MAPK  was defective in ΔpknE compared to wild-type infected macrophages. This defective signaling dramatically delayed and reduced the phosphorylation kinetics of transcription factors ATF-2 and c-JUN in ΔpknE infected macrophages. MAPK inhibitors instead of reducing the phosphorylation in ΔpknE infected macrophages, revealed crosstalks with Erk½ signaling influenced by SAPK/JNK and p38 pathways independently. Modulations in intra cellular signaling altered the expression of coreceptors CCR5 and CXCR4 in ΔpknE infected macrophages. In conclusion, pknE plays a role in MAPK crosstalks that enables intracellular survival of M. tuberculosis. This survival strategy also impacts HIV/TB coinfection.Serine threonine protein kinases (STPK) play a major role in the pathogenesis of  Mycobacterium tuberculosis (MTB) has increased due to the emergence of drug resistant strains and HIV coinfection pknE, pknG, pknH, pknI and pknK play a role in its intracellular survival The global incidence of tuberculosis (TB) caused by eis and mPTPB were reported to play a role in the modulation of host intracellular signaling STPKs are prime targets for new drug discovery and share only 30% homology with their human counterparts Mycobacterium have shown the suppression of MAPK signaling as a mechanism to prevent macrophage activation Mitogen activated protein kinase (MAPK) cascades are evolutionarily conserved signaling pathways in eukaryotes that play a role in cell proliferation, cell differentiation, cell movement and cell death pknE expressed under nitric oxide (NO) stress suppresses multiple apoptotic pathways thereby supporting intracellular survival of MTB and that purified PknE cross-reacts with SAPK/JNK antibody TB predominates in HIV-infected individuals due to weakened immune functions that lead to reactivation of latent MTB. Disease progression in HIV/TB coinfected individuals is accelerated by both MTB and HIV pknE on intracellular signaling that favors MTB survival and its impact on the outcome of HIV/TB coinfection were studied. Our data shows that pknE of MTB influences the crosstalk between the MAPK pathways to regulate inflammation and HIV/TB coinfection.In the present study, the influence of 37Rv , H37RvpknE::hyg  and complemented H37RvpknE strain (CΔE) were grown in Middlebrook 7H9 broth as reported earlier with 50 µg/ml of hygromycin and 20 µg/ml of kanamycin when required MTB Hω-Hydroxy-nor-L-arginine diacetate, 100 µM), caspase-8 , caspase-9 , Erk½ , p38 , SAPK/JNK  and TP53  purchased from Calbiochem, USA, and infected with MTB strains. For nitrate stress experiments, post-infection with MTB, the cells were treated with 10 mM sodium nitroprusside (SNP) as reported earlier THP-1 cells were maintained, differentiated and infected as reported earlier Cell lysates were prepared as reported earlier 6 THP-1 macrophages were lysed using 300 µl of buffer A , centrifuged for 10 s at 15,000 g and the supernatants were labeled as cytosolic fraction. The cell pellet was resuspended in 200 µl of icecold buffer B , centrifuged at 15,000 g for 10 s and the supernatants were stored at −80°C until use. The concentration of proteins was quantified using bicinchoninic acid method (Sigma).Nuclear factors were isolated using the procedure reported earlier Trans-AM ATF-2, c-JUN and NF-kB kit from Active Motif  were used to determine the levels of ATF-2, c-JUN and p65NF-kB in nuclear extract. 2 µg of nuclear extract was added to wells coated with oligonucleotides containing the consensus binding site for the respective nuclear factors, followed by addition of primary antibody, horseradish peroxidase-conjugated secondary antibody and the substrate. The absorbance was read at 450 nm (with a reference wavelength at 650 nm). The specificity of the assay was monitored using competitive binding of wild-type or mutated consensus oligonucleotides before the addition of nuclear extracts.50 of CCR5 (92UG005) and CXCR4 (92UG024)-tropic HIV-1 virus for 2 h at 37°C. Post infection extracellular virus was removed by wash using serum-free RPMI and replenished with RPMI containing 10% FBS. The supernatant was harvested on day 4 to estimate the viral p24 levels by sandwich ELISA (Perkin Elmer). Similarly, monocyte derived macrophages (MDM) were isolated from the blood received from healthy volunteers  after written informed consent approved by institutional ethics committee review board (NIRT IEC protocol number 2006 006) and the coinfection experiment was carried out as described above.24 h post-infection with MTB, THP-1 cells were infected with 500TCIDStatistical analysis was carried out using graph pad prism v5.0. One way and Two way ANOVA were used depending on the data and p value<0.05 was considered statistically significant.pknE and CΔE (complemented ΔpknE). Control cells and Lipopolysaccharide (LPS) were used as appropriate controls.The phosphorylation kinetics of Erk½, p38MAPK and SAPK/JNK were compared in THP-1-derived macrophages infected with MTB strains Rv, ΔpknE-infected macrophages abrogated the phosphorylation of Erk½ at 240 min , reduced the phosphorylation of p38MAPK at 60 min (p<0.0001) and selectively inhibited the phosphorylation of p46 subunit of SAPK/JNK at 120 min (p<0.0001) post infection compared to Rv-infected macrophages .The inhibition of MAPK signaling by ΔpknE-infected macrophages suggests two plausible facts; either ΔpknE induces phosphatases of MAPK differentially or that it initiates a crosstalk response. We chose to analyze Erk½ crosstalk based on its reduced expression in ΔpknE-infected macrophages and its role in cellular survival.The absence of inhibition in the presence of MAPK and Akt inhibitors observed in ΔpknE-infected macrophages as compared to Rv-infected macrophages   , survival  and apoptosis  were studied. While Erk½ inhibitor almost inhibited production of TNF-α and IL-6 in Rv-infected macrophages, increased production of these cytokines in Δor both) . ΔpknE-iophages) . Secretihibitors .pknE-infected macrophages produced reduced amounts of TNF-α and IL-6 in the presence of Akt inhibitor (p<0.05 and p<0.0001 respectively), and arginase inhibitor had a reciprocal effect on their secretion . IL-6 was modestly increased in ΔpknE-infected macrophages in the presence of caspase-8/9 and TP53 inhibitors, of which only caspase-9 inhibition was significant (p<0.05)  inhibitors did not have any effect on the secretion of TNF-α or IL-6 secretion in Rv-infected macrophages . However(p<0.05) . CΔE-infpknE has a role in nitrate stress response suppressing the host cell apoptosis. The role of pknE in modulating intracellular signaling in response to nitrate stress was studied using an exogenous NO donor, sodium nitroprusside.From our previous observations pknE-infected macrophages while Erk½ and SAPK/JNK were reduced in ΔpknE-infected macrophages, similar to that observed in the absence of NO donor . Phosphorylation of NF-kB was reduced in ΔpknE-infected as compared to Rv-infected macrophages (p<0.05)  . CΔE-infpknE in the modulation of CCR5 and CXCR4 receptors involved in HIV entry was investigated based on our observation that ΔpknE has defective MAPK signaling, and the knowledge that MAPK signaling influences modulation of coreceptors.The role of pknE-infected macrophages as compared to Rv-infected macrophages on both days , SAPK/JNK inhibitors increased the expression of CCR5 in comparison with Rv-infected cells   . TP53 inrophages . CΔE-infpknE and CΔE) and a CCR5 (R5) or CXCR4 (X4)-tropic HIV strain to examine the effect of coreceptor modulation on HIV entry and infection, by measuring HIV-1 p24 antigen levels in infected culture supernatants. While THP-1 macrophages coinfected with ΔpknE and R5-tropic virus had reduced p24 levels, cells coinfected with X4 virus had increased p24 levels  and iNOS pknE results in deactivation of survival pathways inside the host. This underlines the role for pknE in modulating host intracellular cascades.This defective MAPK signaling could be a reason for the ΔpknE-infected macrophages did not reverse the effects. However, the secretion of TNF-α and IL-6 were modulated by inhibitors to various intracellular pathways. Observations from the inhibitor studies suggested the probability of crosstalk responses and ΔpknE infected macrophages had cross talk responses between Erk½ and SAPK/JNK, and p38MAPK and Erk½ pathways. This is in concordance with earlier studies where crosstalks within MAPK signaling were reported pknE in crosstalk responses essential for the intracellular survival of MTB.Use of pathway specific inhibitors to confirm the defective MAPK signaling in ΔpknE was found to respond NO stress that results in suppression of apoptosis pknE in modulating intracellular signaling in response to the NO stress of the host was examined using SNP as NO donor that mimics in vivo situations of NO stress pknE-infected macrophages had reduced phosphorylation of MAPKs that confirms pknE in modulating intracellular signaling during NO stress of the host.In our earlier observations pknE increases Erk½ signaling thereby suppressing apoptosis which favors the survival of MTB. This is analogous with a previous report where Erk½ was shown to suppress apoptotic signals Our findings suggest that pknE in the co-pathogenesis of HIV. This was investigated since the data about mycobacterial genes involved in HIV coinfection remains unexplored. Nevertheless earlier reports have shown MAPKs, Akt, chemokines, apoptosis, IL-12 and MTB to modulate CCR5 and CXCR4 coreceptors involved in HIV entry In the next part of the study we endeavored to analyze the significance of pknE suppressed CCR5 but increased CXCR4 expression as compared to the wild-type strain. This finding was further confirmed by coinfection studies with MTB and HIV-1 tropic strains. Next we examined various intracellular pathways that could influence this modulation. MAPK and arginase signaling were found to play an important role in the expression of CCR5 and CXCR4 in macrophages infected with ΔpknE.Here we found that THP-1 macrophages infected with ΔpknE induces apoptosis and down modulates intracellular events that suppress CCR5 expression. This concurs with a previous study where CCR5 was shown to induce antiapoptotic signals via Akt and Erk½ pknE increased the levels of p24 antigen upon coinfection with either R5 or X4 tropic HIV-1 strains. Among the MAPK and arginase signaling, SAPK/JNK was chosen for further validation. Inhibition of the SAPK/JNK signaling and coinfection with either R5 or X4 tropic HIV-1 strains increased the p24 antigen levels in ΔpknE coinfected macrophages. However inhibition of SAPK/JNK signaling markedly reduced the p24 levels in macrophages coinfected with either R5 or X4 tropic HIV-1 strains and Rv. These data suggests SAPK/JNK signaling as one among the cascade that regulates CCR5/CXCR4 expression. This is in concordance with an earlier report where inhibition of SAPK/JNK was shown to reduce CCR5 expression For the first time, we show that ΔpknE contributes to the intracellular survival of MTB by initiating crosstalks within the intracellular signaling of the host. This protective strategy employed by MTB provides a favorable niche for HIV infection.In conclusion, our previous Table S1ΔpknE coinfected with CCR5 has reduced while with CXCR4 have increased p24 levels in THP-1 model of coinfection. THP-1 derived macrophages were infected with M. tuberculosis strains followed by coinfection with a CCR5 and CXCR4 tropic virus. The p24 antigen levels were estimated using ELISA on day 4. *, ** denotes p<0.05 and p<0.001 (one way – Anova) when ΔpknE was compared to Rv infected macrophages.(DOC)Click here for additional data file.


High prevalence rates of HTLV-2 have been found among injecting drug users (IDU) in several European countries. In studies in early 1990s among IDUs in Stockholm, HTLV-2 prevalence rates of 2.3% and 3.2 % were found, while HTLV-1 was rare (1-2). We have now, in 2007-8, performed a new study in a similar population in Stockholm, Sweden.To study if HTLV-2 is still prevalent among IDUs in Stockholm. If so, to see if epidemiological characteristics and risk factors are similar as in 1994.Serum samples from IDUs in Stockholm, during the years 2007-8 (N=1079) were collected and investigated for HTLV-1/2 antibodies. Data regarding age, sex, current drug use, country of origin, detention and homelessness were collected.Among 1079 investigated subjects, 35 were found to be positive for antibodies to HTLV-1 and/or HTLV-2, giving an overall HTLV-prevalence of 3.2%. Of these, 2 (0.2%) had antibodies to HTLV-1, 28 to HTLV-2 (2.6%) and 5 (0.5%) had non-typeable antibodies to HTLV. The overall study group had similar age and sex distribution as in 1995. However, the HTLV-positive individuals were 10 years older than the HTLV-negative group (mean age) and compared to the cases studied in 1995.The HTLV prevalence among IVDUs in Stockholm, Sweden, 2007-8 was comparable to the rates found in the early 1990s. As back then, the HTLV-positive IVDUs were significantly older than the HTLV-negative persons. However, in the present study the age difference was more pronounced, 10 years vs 4 years mean difference. The higher age of HTLV cases indicates either a spread of HTLV mainly among older individuals, little spread to the younger persons or possibly limited spread of HTLV in general, since the HTLV-infected cases are now more than 10 years older than in 1995.


The recent discovery of HBZ, an antisense protein, encoded by HTLV-1 allowed a new way of understanding how HTLV-1 induces the development of adult T cell leukemia/lymphoma (ATLL). HBZ mRNA is expressed in all HTLV-1 patients tested regardless of their clinical status. Furthermore HBZ mRNA level is positively correlated to the HTLV-1 proviral load and it involved in infected T cell proliferation. The HTLV-2 homolog of HBZ, APH-2, also represses the viral transcription from the 5' LTR. We therefore quantified APH-2 and Tax mRNA levels as well as proviral load in a series of 51 blood samples obtained from the HTLV Outcomes Study (HOST) cohort. These samples were divided in low, intermediate and high proviral load (PVL) groups. We first show that APH-2 was expressed in most (94%) samples, while Tax was expressed mostly in the high PVL group. A positive correlation was observed between PVL and Tax and between PVL and APH-2. Although lymphocytosis is commonly observed among HTLV-2 carriers, we also demonstrate that APH2, contrary to HBZ does not promote cell proliferation in vitro. These results were confirmed in vivo since we did not observe a correlation between APH-2 level and the lymphocyte count. Our results therefore demonstrate that APH-2 is frequently expressed in vivo in HTLV-2 carriers. However, and contrary to HBZ, APH-2 does not promote cell proliferation.


Computational design of protein function involves a search for amino acids with the lowest energy subject to a set of constraints specifying function. In many cases a set of natural protein backbone structures, or “scaffolds”, are searched to find regions where functional sites  can be placed, and the identities of the surrounding amino acids are optimized to satisfy functional constraints. Input native protein structures almost invariably have regions that score very poorly with the design force field, and any design based on these unmodified structures may result in mutations away from the native sequence solely as a result of the energetic strain. Because the input structure is already a stable protein, it is desirable to keep the total number of mutations to a minimum and to avoid mutations resulting from poorly-scoring input structures. Here we describe a protocol using cycles of minimization with combined backbone/sidechain restraints that is Pareto-optimal with respect to RMSD to the native structure and energetic strain reduction. The protocol should be broadly useful in the preparation of scaffold libraries for functional site design. There has been recent progress in the computational design of functional proteins and in the prediction of biomolecular interactions across a wide range of problems: ligand-protein Most crystal structures will have regions of high energy as evaluated in Rosetta or other design programs, which will lead to sequence changes in design if they are not addressed. However most minimization protocols will lead to too much deviation from the original wild-type crystal structure. The question is how to properly balance energy minimization with reduction of structural deviation from the starting structure. The concept of optimizing a structure to the energy function in use has a long precedent – for example the equilibration of structures in molecular dynamics prior to a production run Here we carry out a systematic examination of a number of structure refinement methods, evaluating them for optimality (minimization of Rosetta energy and RMSD from the starting structure simultaneously) and for their influence on subsequent sequence re-design. We found that a combination of harmonic backbone and sidechain coordinate restraints minimizes all-atom RMSD and Rosetta energy together, and reduces the number of sequence changes in subsequent design. Because the restrained relax protocol examined here results in fewer sequence alterations in design, it also minimizes the amount of human intervention required in the overall design process.primum non nocere, or “first do no harm”) while also minimizing the Rosetta energy. One possibility in preparing structures for Rosetta is to re-refine the structure using an energy function incorporating standard Rosetta score terms as well as the correspondence to electron density Our goal in evaluating structure minimization protocols was first to minimize RMSD to the native  to understand energetic changes effected by the protocol at a residue-by-residue level. The high-energy residues about 5 REU are all moved to lower energy by the protocol; residues in the 1–5 REU range are largely moved to lower energy; residues with negative energy remain mostly unchanged . The design protocol on the native places a glutamate at the position 14, in place of native tyrosine . Briefly, these structures were prepared for Rosetta by removal of waters and non-canonical amino acids and preparation of Rosetta parameter files for the ligands. Structure selection is described fully in Nivón and Bjelic.The 41 protein monomer sequence recovery set has been described elsewhere min on one core of a mixed Intel-Xeon-L5335-2GHz/AMD-Opteron-2.2GHz cluster and roughly doubling in time for each additional 100 residues.The fast relax protocol in Rosetta is described elsewhere Harmonic coordinate restraints take the form f(x)  =  (d/sd)?2, where d is the distance of the atom from the desired coordinate, and sd is a parameter related to the strength of the restraint. Bounded coordinate restraints take a zero value within WIDTH of the desired coordinate, followed by a small harmonic segment to transition (from WIDTH to WIDTH +0.5*sd) and a linear value of slope set at 1/sd for the rest. Sidechain-sidechain restraint runs have harmonic distance restraints of sd = 2.0 for all sidechain atom pairs within the specified cutoff distance, and backbone heavy atom harmonic coordinate restraints of sd = 0.5.Parameter scans were performed with the flags:“-no_optH false -flip_HNQ -use_input_sc -correct -no_his_his_pairE -linmem_ig 10 -nblist_autoupdate true”Harmonic runs added flags “-constrain_relax_to_start_coords -relax:ramp_constraints false -relax:coord_constrain_sidechains -relax:coord_cst_stdev <SD>”, where SD ranged from 0.000001 to 5.0Bounded runs added flags “-constrain_relax_to_start_coords -relax:ramp_constraints false -relax:coord_constrain_sidechains -relax:coord_cst_stdev <SD> -relax:coord_cst_width <WIDTH>”, where SD ranged from 0.1 to 5.0, and WIDTH ranged from 0 to 1.0.Sidechain-sidechain runs added flags “-constrain_relax_to_start_coords-relax:ramp_constraints false -relax:sc_cst_maxdist <DIST>” where DIST ranged from 3 to 8.Unrestrained runs had no additional flags.RMSD values were computed in pymol with the command “align relaxed and not hydro, reference and not hydro, cycles = 0”. The median per-residue energy and RMSD of 10 replicates of the relax procedure were taken as the value for that protein, and the mean value across the 51 proteins in the input set were computed for each of the different parameter runs.Design was performed with the Rosetta enzyme design program, using the default parameters from the enzdes scientific test in rosetta (rosetta/rosetta_tests/scientific/biweekly/tests/enzdes_benchmark). Briefly, a design shell of 6 Å, with a 12 Å shell of repackable  residues was used. One cycle of design with a “soft” Lennard Jones repulsive term was followed by one with the standard repulsive term. Extra rotamers were included based on the Dunbrack rotamer distribution, and recent updates to the Rosetta score function were also included –l./inputs/pdb.list–enzdes::detect_design_interface–enzdes::cut1 6.0–enzdes::cut2 8.0–enzdes::cut3 10.0–enzdes::cut4 12.0–enzdes::cst_design–enzdes::design_min_cycles 2–enzdes::cst_min–enzdes::chi_min–ex1–ex2–ex1aro–ex2aro–extrachi_cutoff 1–soft_rep_design–flip_HNQ–correct–no_his_his_pairE–score::hbond_params correct_params–lj_hbond_hdis 1.75–lj_hbond_OH_donor_dis 2.6–dun08 false–nstruct 1–enzdes::no_unconstrained_repack–linmem_ig 10–nblist_autoupdate true–enzdes::lig_packer_weight 1.8–docking::ligand::old_estat true–extra_res_fa inputs/2b3b.params inputs/2ifb.params inputs/1sw1.params inputs/2FQX.params inputs/2p0d.params inputs/2DRI.params inputs/1fby.params inputs/1ZHX.params inputs/2RDE.params inputs/1db1.params inputs/2h6b.params inputs/1z17.params inputs/2FME.params inputs/1y3n.params inputs/1urg.params inputs/1FZQ.params inputs/1y52.params inputs/1POT.params inputs/1XT8.params inputs/2FR3.params inputs/2UYI.params inputs/1USK.params inputs/1n4h.params inputs/2qo4.params inputs/2GM1.params inputs/2rct.params inputs/2HZQ.params inputs/1hsl.params inputs/1A99.params inputs/1uw1.params inputs/1l8b.params inputs/3B50.params inputs/1H6H.params inputs/2Q2Y.params inputs/1hmr.params inputs/1OPB.params inputs/1x7r.params inputs/2Q89.params inputs/1nl5.params inputs/1TYR.params inputs/2e2r.params inputs/1LKE.params inputs/2PFY.params inputs/1wdn.params inputs/1nq7.params inputs/1y2u.params inputs/2ioy.params inputs/1J6Z.params inputs/1RBP.params inputs/1XZX.params inputs/2f5t.params–chemical:exclude_patches LowerDNA UpperDNA Cterm_amidation SpecialRotamerVirtualBB ShoveBB VirtualDNAPhosphate VirtualNTerm CTermConnect sc_orbitalspro_hydroxylated_case1 pro_hydroxylated_case2 ser_phosphorylatedthr_phosphorylated tyr_phosphorylated tyr_sulfated lys_dimethylatedlys_monomethylated lys_trimethylated lys_acetylated glu_carboxylatedcys_acetylated tyr_diiodinated N_acetylated C_methylamidatedMethylatedProteinCtermFile S1Supporting figures and tables. Table S1. Energy comparison between input and restrained-relax structures. Average over all energy terms for the input set (INPUT) and the set relaxed with sidechain coordinate restraints at sd = 0.5 (COORD). Values are sorted by the difference in each score term. Energy terms fa_dun (sidechain rotamer probability-based energy) and fa_rep (Lennard-Jones repulsive term) are the largest contributors to lower energy after the relax. Table S2. The top-10 most-improved residues after the relax protocol for 1A99. Score term changes are shown for fa_dun and fa_rep score terms only. INPUT is for the original wild-type crystal structure. COORD is for the coordinate restrained relax structures. Delta is the difference between INPUT and COORD for the specified score term and residue. Table S3. Residue 14 energies for 2ifb.pdb before/after restrained relax and before/after design. Note that after the restrained relax the total energy for residue 14 (−1.17) is much lower, even slightly lower than the energy after enzyme design on an unrelaxed input structure (−1.14). Figure S1. Per-residue score comparison between an input and restrained-relax structure. Histogram of individual residue Rosetta scores for the putrescine receptor (1A99.pdb) unmodified (blue) and after the coordinate-restrained relax protocol (red), with overlap in purple. Figure S2. Example of improved design after restrained relax. 2ifb position 14 example, native in green, design on the unmodified native in cyan, and design on the restrained-relax native in purple. The wild-type identity at position 14 is mutated from tyrosine to glutamate in the run on an unmodified structure (cyan), but remains the original tyrosine in the run on the restrained-relax structure (purple).(DOCX)Click here for additional data file.