Subtractive phage display selection from canine visceral leishmaniasis identifies novel epitopes that mimic leishmania infantum antigens with potential serodiagnosis applications

Visceral leishmaniasis (VL) is a zoonotic disease that is endemic to Brazil, where dogs are the main domestic parasite reservoirs, and the percentages of infected dogs living in regions where canine VL (CVL) is endemic have ranged from 10% to 62%. Despite technological advances, some problems have been reported with CVL serodiagnosis. The present study describes a sequential subtractive selection through phage display technology from polyclonal antibodies of negative and positive sera that resulted in the identification of potential bacteriophage-fused peptides that were highly sensitive and specific to antibodies of CVL. A negative selection was performed in which phage clones were adhered to purified IgGs from healthy and Trypanosoma cruzi-infected dogs to eliminate cross-reactive phages. The remaining supernatant nonadhered phages were submitted to positive selection against IgG from the blood serum of dogs that were infected with Leishmania infantum. Phage clones that adhered to purified IgGs from the CVL-infected serum samples were selected. Eighteen clones were identified and their reactivities tested by a phage enzyme-linked immunosorbent assay (phage-ELISA) against the serum samples from infected dogs (n 31) compared to those from vaccinated dogs (n 21), experimentally infected dogs with cross-reactive parasites (n 23), and healthy controls (n 17). Eight clones presented sensitivity, specificity, and positive and negative predictive values of 100%, and they showed no crossreactivity with T. cruzi- or Ehrlichia canis-infected dogs or with dogs vaccinated with two different commercial CVL vaccines in Brazil. Our study identified eight mimotopes of L. infantum antigens with 100% accuracy for CVL serodiagnosis. The use of these mimotopes by phage-ELISA proved to be an excellent assay that was reproducible, simple, fast, and inexpensive, and it can be applied in CVL-monitoring programsThis work was supported by grants from the Pró-Reitoria de Pesquisa of UFMG (supported 03/2013), the Instituto Nacional de Ciência e Tecnologia em Nano-Biofarmacêutica (INCT Nano-Biofar), Rede Nanobiotec/Brasil-UFU (CAPES), PRONEX-FAPEMIG (APQ-01019- 09), FAPEMIG (APQ-00496-11 and APQ-00819-12), and CNPq (APQ- 472090/2011-9 and APQ-482976/2012-8). E.A.F.C. and L.R.G. are recipients of grants from CNPq. M.A.C.-F. is the recipient of a grant from FAPEMIG/CAPE

Sensitive and specific serodiagnosis of Leishmania infantum infection in dogs by using peptides selected from hypothetical proteins identified by an immunoproteomic approach

In Brazil, the percentage of infected dogs living in areas where canine visceral leishmaniasis (CVL) is endemic ranges from 10 to 62%; however, the prevalence of infection in dogs is probably higher than figures reported from serological studies. In addition, problems with the occurrence of false-positive or false-negative results in the serodiagnosis of CVL have been reported. The present work analyzed the potential of synthetic peptides mapped from hypothetical proteins for improvement of the serodiagnosis of Leishmania infantum infection in dogs. From 26 identified leishmanial proteins, eight were selected, considering that no homologies between these proteins and others from trypanosomatide sequence databases were encountered. The sequences of these proteins were mapped to identify linear B-cell epitopes, and 17 peptides were synthesized and tested in enzyme-linked immunosorbent assays (ELISAs) for the serodiagnosis of L. infantum infection in dogs. Of these, three exhibited sensitivity and specificity values higher than 75% and 90%, respectively, to differentiate L. infantum-infected animals from Trypanosoma cruziinfected animals and healthy animals. Soluble Leishmania antigen (SLA) showed poor sensitivity (4%) and specificity (36%) to differentiate L. infantum-infected dogs from healthy and T. cruzi-infected dogs. Lastly, the three selected peptides were combined in different mixtures and higher sensitivity and specificity values were obtained, even when sera from T. cruzi-infected dogs were used. The study’s findings suggest that these three peptides can constitute a potential tool for more sensitive and specific serodiagnosis of L. infantum infection in dogsThis work was supported by grants from the Pró-Reitoria de Pesquisa from UFMG (Edital 07/2012), Instituto Nacional de Ciência e Tecnologia em Nano-biofarmacêutica (INCT-NANOBIOFAR, Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG) (CBB-APQ-02364-08, CBB-APQ-00356-10, CBB-APQ-00496-11, and CBB-APQ-00819-12), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) (APQ-472090/2011-9), and the Instituto Nacional de Ciência e Tecnologia em Vacinas (INCT-V). E.A.F.C. and A.P.F. are CNPq grant recipients. M.A.C.-F. is a FAPEMIG/CAPES grant recipient. This study was supported in Spain, in part, by grants from the Ministerio de Ciencia e Innovación (FIS/PI1100095)

Candidate gene prioritization by network analysis of differential expression using machine learning approaches

<p>Abstract</p> <p>Background</p> <p>Discovering novel disease genes is still challenging for diseases for which no prior knowledge - such as known disease genes or disease-related pathways - is available. Performing genetic studies frequently results in large lists of candidate genes of which only few can be followed up for further investigation. We have recently developed a computational method for constitutional genetic disorders that identifies the most promising candidate genes by replacing prior knowledge by experimental data of differential gene expression between affected and healthy individuals.</p> <p>To improve the performance of our prioritization strategy, we have extended our previous work by applying different machine learning approaches that identify promising candidate genes by determining whether a gene is surrounded by highly differentially expressed genes in a functional association or protein-protein interaction network.</p> <p>Results</p> <p>We have proposed three strategies scoring disease candidate genes relying on network-based machine learning approaches, such as kernel ridge regression, heat kernel, and Arnoldi kernel approximation. For comparison purposes, a local measure based on the expression of the direct neighbors is also computed. We have benchmarked these strategies on 40 publicly available knockout experiments in mice, and performance was assessed against results obtained using a standard procedure in genetics that ranks candidate genes based solely on their differential expression levels (<it>Simple Expression Ranking</it>). Our results showed that our four strategies could outperform this standard procedure and that the best results were obtained using the <it>Heat Kernel Diffusion Ranking </it>leading to an average ranking position of 8 out of 100 genes, an AUC value of 92.3% and an error reduction of 52.8% relative to the standard procedure approach which ranked the knockout gene on average at position 17 with an AUC value of 83.7%.</p> <p>Conclusion</p> <p>In this study we could identify promising candidate genes using network based machine learning approaches even if no knowledge is available about the disease or phenotype.</p

Network Analysis of Differential Expression for the Identification of Disease-Causing Genes

Genetic studies (in particular linkage and association studies) identify chromosomal regions involved in a disease or phenotype of interest, but those regions often contain many candidate genes, only a few of which can be followed-up for biological validation. Recently, computational methods to identify (prioritize) the most promising candidates within a region have been proposed, but they are usually not applicable to cases where little is known about the phenotype (no or few confirmed disease genes, fragmentary understanding of the biological cascades involved). We seek to overcome this limitation by replacing knowledge about the biological process by experimental data on differential gene expression between affected and healthy individuals. Considering the problem from the perspective of a gene/protein network, we assess a candidate gene by considering the level of differential expression in its neighborhood under the assumption that strong candidates will tend to be surrounded by differentially expressed neighbors. We define a notion of soft neighborhood where each gene is given a contributing weight, which decreases with the distance from the candidate gene on the protein network. To account for multiple paths between genes, we define the distance using the Laplacian exponential diffusion kernel. We score candidates by aggregating the differential expression of neighbors weighted as a function of distance. Through a randomization procedure, we rank candidates by p-values. We illustrate our approach on four monogenic diseases and successfully prioritize the known disease causing genes

Recent updates and perspectives on approaches for the development of vaccines against visceral leishmaniasis

All rights reserved. Visceral leishmaniasis (VL) is one of the most important tropical diseases worldwide. Although chemotherapy has been widely used to treat this disease, problems related to the development of parasite resistance and side effects associated with the compounds used have been noted. Hence, alternative approaches for VL control are desirable. Some methods, such as vector control and culling of infected dogs, are insufficiently effective, with the latter not ethically recommended. The development of vaccines to prevent VL is a feasible and desirable measure for disease control, for example, some vaccines designed to protect dogs against VL have recently been brought to market. These vaccines are based on the combination of parasite fractions or recombinant proteins with adjuvants that are able to induce cellular immune responses, however, their partial efficacy and the absence of a vaccine to protect against human leishmaniasis underline the need for characterization of new vaccine candidates. This review presents recent advances in control measures for VL based on vaccine development, describing extensively studied antigens, as well as new antigenic proteins recently identified using immuno-proteomic techniquesThis work was supported by grants from Instituto Nacional de Ciência e Tecnologia em Nano-Biofarmacêutica, Rede Nanobiotec/Brasil-Universidade Federal de Uberlândia/CAPES, PRONEX-FAPEMIG (APQ-01019-09), FAPEMIG (CBB-APQ-00819-12 and CBB-APQ-01778-2014), and CNPq (APQ-482976/2012-8, APQ-488237/2013-0, and APQ-467640/2014-9). EAFC and LRG are recipients of the grant from CNPq. MACF is the recipient of grants from FAPEMIG/CAPE

New insights into the genetic etiology of Alzheimer's disease and related dementias

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele

Multiancestry analysis of the HLA locus in Alzheimer’s and Parkinson’s diseases uncovers a shared adaptive immune response mediated by HLA-DRB1*04 subtypes

Across multiancestry groups, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson’s disease (PD) and Alzheimer’s disease (AD) versus controls. We demonstrate that the two diseases share the same protective association at the HLA locus. HLA-specific fine-mapping showed that hierarchical protective effects of HLA-DRB1*04 subtypes best accounted for the association, strongest with HLA-DRB1*04:04 and HLA-DRB1*04:07, and intermediary with HLA-DRB1*04:01 and HLA-DRB1*04:03. The same signal was associated with decreased neurofibrillary tangles in postmortem brains and was associated with reduced tau levels in cerebrospinal fluid and to a lower extent with increased Aβ42. Protective HLA-DRB1*04 subtypes strongly bound the aggregation-prone tau PHF6 sequence, however only when acetylated at a lysine (K311), a common posttranslational modification central to tau aggregation. An HLA-DRB1*04-mediated adaptive immune response decreases PD and AD risks, potentially by acting against tau, offering the possibility of therapeutic avenues

Identification of differentially expressed proteins from Leishmania amazonensis associated with the loss of virulence of the parasites.

BACKGROUND: The present study analyzed whether or not the in vitro cultivation for long periods of time of pre-isolated Leishmania amazonensis from lesions of chronically infected BALB/c mice was able to interfere in the parasites' infectivity using in vivo and in vitro experiments. In addition, the proteins that presented a significant decrease or increase in their protein expression content were identified applying a proteomic approach. METHODOLOGY/PRINCIPAL FINDINGS: Parasites were cultured in vitro for 150 days. Aliquots were collected on the day 0 of culture (R0), as well as after ten (R10; 50 days of culture), twenty (R20; 100 days of culture), and thirty (R30; 150 days of culture) passages, and were used to analyze the parasites' in vitro and in vivo infectivity, as well as to perform the proteomic approach. Approximately 837, 967, 935, and 872 spots were found in 2-DE gels prepared from R0, R10, R20, and R30 samples, respectively. A total of 37 spots presented a significant decrease in their intensity of expression, whereas a significant increase in protein content during cultivation could be observed for 19 proteins (both cases >2.0 folds). Some of these identified proteins can be described, such as diagnosis and/or vaccine candidates, while others are involved in the infectivity of Leishmania. It is interesting to note that six proteins, considered hypothetical in Leishmania, showed a significant decrease in their expression and were also identified. CONCLUSIONS/SIGNIFICANCE: The present study contributes to the understanding that the cultivation of parasites over long periods of time may well be related to the possible loss of infectivity of L. amazonensis. The identified proteins that presented a significant decrease in their expression during cultivation, including the hypothetical, may also be related to this loss of parasites' infectivity, and applied in future studies, including vaccine candidates and/or immunotherapeutic targets against leishmaniasis