Shared IgG Infection Signatures vs. Hemorrhage-Restricted IgA Clusters in Human Dengue: A Phenotype of Differential Class-Switch via TGFβ1

Abstract

Phenotypic manifestations of infectious diseases are closely related to individual immune responses. Methods to extract information from patients’ own immune reactions would be of great use for both diagnosis and treatment. Dengue fever is one of the diseases that clinical aggravations could occur paradoxically after humoral immunity appears. This property makes dengue fever an excellent disease model to explore. A principal component analyses (PCAs)-based framework derived from a prior vaccination study was developed. The framework was verified by successful demonstrations of known IgG signatures from a Mexico Dengue data set. Afterward the pipeline was tested upon de novo IgG and IgA libraries of Dengue patients from southern Taiwan. We discovered four infection signatures within IgG repertoires, two of which were identical to previous reports. However, it was IgA but not IgG that could differentiate hemorrhagic from non-hemorrhagic patients. IgA repertoires were found more diversified among bleeders, from whom seven signature clusters were characterized. The expressions of transforming growth factor beta 1 ( TGFβ1 ) and accordingly mediated class-switch activity of IgA were distinct only among the PCA-segregated bleeding group. In sum, intercontinental sharing of IgG signatures in dengue fever was demonstrated via a unified working flow. Differential regulation of IgA class-switch with associated diversity expansion plus existences of hemorrhage-restricted clusters were shown. The ability of the framework to find common IgG signatures would implicate applications to infections even from unknown pathogens. The clusters within IgA repertoires could offer perspectives to other IgA-related bleeding disorders such as Henoch-Schönlein purpura or IgA nephropathy. Substantiated grounds for IgA-specific effector function via TGFβ1 -mediated class-switch would be a new factor to consider for infectious diseases.

A need to raise the bar — A systematic review of temporal trends in diagnostics for Japanese encephalitis virus infection, and perspectives for future research

“…During the past three years, with the international focus on emerging flaviviruses following the chikungunya virus and theZika virus global epidemics, there have been intensified efforts to reduce cost, increase throughput, and improve specificity. These include the analysis of IgA (Amaro et al, 2019;Warnecke et al, 2019;Colonetti et al, 2018;Nascimento et al, 2018;Rockstroh et al, 2017;Zhang et al, 2017;Huang et al, 2017;Balmaseda et al, 2008;Balmaseda et al, 2003;Yap et al, 2011) and IgG subclasses (Nascimento et al, 2018), antibody avidity (Amaro et al, 2019;de Vasconcelos et al, 2018;Ronnberg et al, 2017;Tsai et al, 2018;Shen et al, 2017), incorporation of blocking agents, IgG depletion (Calvert et al, 2018) and production of specific monoclonal antibodies for identification of specific viral epitopes (Zhu et al, 2018;Lebani et al, 2017;Piyasena et al, 2017;Kim et al, 2018b;Frietze et al, 2017). This recent work highlights the inherent challenges of serological techniques for JE identification.…”

Prospective Artificial Intelligence to Dissect the Dengue Immune Response and Discover Therapeutics

“…Appanna and colleagues report a dataset of dengue-specific B-cell CDR3 sequences from dengue patients in Singapore ( 84 ). Another dengue antibody sequence data source is the work by Huang and colleagues ( 127 ), who sequenced the IgG immune repertoire from 15 patients in Taiwan. CDR3 sequences of reported antibodies would play a key role in immune repertoire mining, due to their antigen specificity.…”

Machine Learning Detects Anti-DENV Signatures in Antibody Repertoire Sequences

“…This and the promising results of machine learning-based analysis of HTS data have intensified efforts also in the field of dengue. Recently, scientists have started to sequence dengue and dengue-related antibody repertoires directly from human samples, leading to a tremendous amount of genomic data and an increased understanding of the genetic composition and diversity of the virus and its elicited antibodies (Parameswaran et al, 2013;Galson et al, 2014;Appanna et al, 2016;Huang et al, 2017).…”

“…Dataset 3: Huang et al (2017) analyzed dengue antibody heavy-chain IgG/IgA signatures of 14 hemorrhagic, simple and healthy samples from Taiwan available as BioProject with ID PRJEB13768 (IgG and IgA antibodies). Since several repertoires were taken from each patient throughout the progress of the disease, a total of 59 repertoires were available.…”