Differential immunoglobulin and complement levels in leprosy prior to development of reversal reaction and erythema nodosum leprosum

Background Leprosy is a treatable infectious disease caused by Mycobacterium leprae. However, there is additional morbidity from leprosy-associated pathologic immune reactions, reversal reaction (RR) and erythema nodosum leprosum (ENL), which occur in 1 in 3 people with leprosy, even with effective treatment of M. leprae. There is currently no predictive marker in use to indicate which people with leprosy will develop these debilitating immune reactions. Our peripheral blood mononuclear cell (PBMC) transcriptome analysis revealed that activation of the classical complement pathway is common to both RR and ENL. Additionally, differential expression of immunoglobulin receptors and B cell receptors during RR and ENL support a role for the antibody-mediated immune response during both RR and ENL. In this study, we investigated B-cell immunophenotypes, total and M. leprae-specific antibodies, and complement levels in leprosy patients with and without RR or ENL. The objective was to determine the role of these immune mediators in pathogenesis and assess their potential as biomarkers of risk for immune reactions in people with leprosy. Methodology/findings We followed newly diagnosed multibacillary leprosy cases (n = 96) for two years for development of RR or ENL. They were compared with active RR (n = 35), active ENL (n = 29), and healthy household contacts (n = 14). People with leprosy who subsequently developed ENL had increased IgM, IgG1, and C3d-associated immune complexes with decreased complement 4 (C4) at leprosy diagnosis. People who developed RR also had decreased C4 at leprosy diagnosis. Additionally, elevated anti-M. leprae antibody levels were associated with subsequent RR or ENL. Conclusions Differential co-receptor expression and immunoglobulin levels before and during immune reactions intimate a central role for humoral immunity in RR and ENL. Decreased C4 and elevated anti-M. leprae antibodies in people with new diagnosis of leprosy may be risk factors for subsequent development of leprosy immune reactions

Leishmania chagasi T-Cell Antigens Identified through a Double Library Screen

Control of human visceral leishmaniasis in regions where it is endemic is hampered in part by limited accessibility to medical care and emerging drug resistance. There is no available protective vaccine. Leishmania spp. protozoa express multiple antigens recognized by the vertebrate immune system. Since there is not one immunodominant epitope recognized by most hosts, strategies must be developed to optimize selection of antigens for prevention and immunodiagnosis. For this reason, we generated a cDNA library from the intracellular amastigote form of Leishmania chagasi, the cause of South American visceral leishmaniasis. We employed a two-step expression screen of the library to systematically identify T-cell antigens and T-dependent B-cell antigens. The first step was aimed at identifying the largest possible number of clones producing an epitope-containing polypeptide by screening with a pool of sera from Brazilians with documented visceral leishmaniasis. After removal of clones encoding heat shock proteins, positive clones underwent a second-step screen for their ability to cause proliferation and gamma interferon responses in T cells from immune mice. Six unique clones were selected from the second screen for further analysis. The corresponding antigens were derived from glutamine synthetase, a transitional endoplasmic reticulum ATPase, elongation factor 1γ, kinesin K39, repetitive protein A2, and a hypothetical conserved protein. Humans naturally infected with L. chagasi mounted both cellular and antibody responses to these proteins. Preparations containing multiple antigens may be optimal for immunodiagnosis and protective vaccines

Design and in silico validation of polymerase chain reaction primers to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)

Abstract Accurate designing of polymerase chain reaction (PCR) primers targeting conserved segments in viral genomes is desirable for preventing false-negative results and decreasing the need for standardization across different PCR protocols. In this work, we designed and described a set of primers and probes targeting conserved regions identified from a multiple sequence alignment of 2341 Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) genomes from the Global Initiative on Sharing All Influenza Data (GISAID). We subsequently validated those primers and probes in 211,833 SARS-CoV-2 whole-genome sequences. We obtained nine systems (forward primer + reverse primer + probe) that potentially anneal to highly conserved regions of the virus genome from these analyses. In silico predictions also demonstrated that those primers do not bind to nonspecific targets for human, bacterial, fungal, apicomplexan, and other Betacoronaviruses and less pathogenic sub-strains of coronavirus. The availability of these primer and probe sequences will make it possible to validate more efficient protocols for identifying SARS-CoV-2

Comparison of methods to account for relatedness in genome-wide association studies with family-based data.

Approaches based on linear mixed models (LMMs) have recently gained popularity for modelling population substructure and relatedness in genome-wide association studies. In the last few years, a bewildering variety of different LMM methods/software packages have been developed, but it is not always clear how (or indeed whether) any newly-proposed method differs from previously-proposed implementations. Here we compare the performance of several LMM approaches (and software implementations, including EMMAX, GenABEL, FaST-LMM, Mendel, GEMMA and MMM) via their application to a genome-wide association study of visceral leishmaniasis in 348 Brazilian families comprising 3626 individuals (1972 genotyped). The implementations differ in precise details of methodology implemented and through various user-chosen options such as the method and number of SNPs used to estimate the kinship (relatedness) matrix. We investigate sensitivity to these choices and the success (or otherwise) of the approaches in controlling the overall genome-wide error-rate for both real and simulated phenotypes. We compare the LMM results to those obtained using traditional family-based association tests (based on transmission of alleles within pedigrees) and to alternative approaches implemented in the software packages MQLS, ROADTRIPS and MASTOR. We find strong concordance between the results from different LMM approaches, and all are successful in controlling the genome-wide error rate (except for some approaches when applied naively to longitudinal data with many repeated measures). We also find high correlation between LMMs and alternative approaches (apart from transmission-based approaches when applied to SNPs with small or non-existent effects). We conclude that LMM approaches perform well in comparison to competing approaches. Given their strong concordance, in most applications, the choice of precise LMM implementation cannot be based on power/type I error considerations but must instead be based on considerations such as speed and ease-of-use

Concordance between top SNPs identified by different methods.

a<p>See <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004445#pgen-1004445-t002" target="_blank">Table 2</a> for description of methods.</p

Genomic control factors obtained using different software packages and different strategies for modelling kinships.

<p>PLINK =  analysis in PLINK with no adjustment made for relatedness. Other methods/software packages are listed in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004445#pgen-1004445-t001" target="_blank">Table 1</a> (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004445#pgen-1004445-t002" target="_blank">Table 2</a> for abbreviated names of methods). Pedigree  =  theoretical kinships based on known pedigree relationships used to adjust for relatedness. Thinned  =  kinships based on 1900 ‘thinned’ SNPs used to adjust for relatedness. Pruned  =  kinships based on 50,129 ‘pruned’ SNPs used to adjust for relatedness. Full  =  kinships based on 545,433 SNPs used to adjust for relatedness.</p

Summary of methods/software packages investigated.

<p>Summary of methods/software packages investigated.</p