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Proteomic features predict seroreactivity against leptospiral antigens in leptospirosis patients.

Lessa-Aquino C, Wunder EA, Lindow JC, Rodrigues CB, Pablo J, Nakajima R, Jasinskas A, Liang L, Reis MG, Ko AI, Medeiros MA, Felgner PL - J. Proteome Res. (2014)

Bottom Line: Together, this group of 14 enriched categories accounts for just 25% of the leptospiral proteome but contains 50% of the immunoreactive antigens.These findings are consistent with our previous studies of other Gram-negative bacteria.This genome-wide approach provides an empirical basis to predict and classify antibody reactive antigens based on structural, physical-chemical, and functional proteomic features and a framework for understanding the breadth and specificity of the immune response to L. interrogans.

View Article: PubMed Central - PubMed

Affiliation: Fiocruz, Bio-Manguinhos, Brazilian Ministry of Health , Avenida Brasil, 4365 - Manguinhos, Rio de Janeiro, RJ 21040-900, Brazil.

ABSTRACT
With increasing efficiency, accuracy, and speed we can access complete genome sequences from thousands of infectious microorganisms; however, the ability to predict antigenic targets of the immune system based on amino acid sequence alone is still needed. Here we use a Leptospira interrogans microarray expressing 91% (3359) of all leptospiral predicted ORFs (3667) and make an empirical accounting of all antibody reactive antigens recognized in sera from naturally infected humans; 191 antigens elicited an IgM or IgG response, representing 5% of the whole proteome. We classified the reactive antigens into 26 annotated COGs (clusters of orthologous groups), 26 JCVI Mainrole annotations, and 11 computationally predicted proteomic features. Altogether, 14 significantly enriched categories were identified, which are associated with immune recognition including mass spectrometry evidence of in vitro expression and in vivo mRNA up-regulation. Together, this group of 14 enriched categories accounts for just 25% of the leptospiral proteome but contains 50% of the immunoreactive antigens. These findings are consistent with our previous studies of other Gram-negative bacteria. This genome-wide approach provides an empirical basis to predict and classify antibody reactive antigens based on structural, physical-chemical, and functional proteomic features and a framework for understanding the breadth and specificity of the immune response to L. interrogans.

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Representativehistograms showing the criteria for selecting reactiveantigens. An antigen was considered to be reactive if either the groupaverage signal intensity or at least 33% of the samples within a groupshowed signal intensity above 2.5 standard deviations of the NoDNAcontrol reactions. The histogram plots the average signal intensity(Y axis) and the number of responsive individuals(secondary Y axis) for each reactive antigen selected(X axis) for IgM (A) or IgG (B) probing of convalescent-phasesamples from severe patients. Dotted lines correspond to the controlreactions cutoff (black) or the minimum number of responsive individuals(orange) included using this criteria.
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fig1: Representativehistograms showing the criteria for selecting reactiveantigens. An antigen was considered to be reactive if either the groupaverage signal intensity or at least 33% of the samples within a groupshowed signal intensity above 2.5 standard deviations of the NoDNAcontrol reactions. The histogram plots the average signal intensity(Y axis) and the number of responsive individuals(secondary Y axis) for each reactive antigen selected(X axis) for IgM (A) or IgG (B) probing of convalescent-phasesamples from severe patients. Dotted lines correspond to the controlreactions cutoff (black) or the minimum number of responsive individuals(orange) included using this criteria.

Mentions: We probed leptospiral proteinarrays with a collection of 188 serum samples, composed of longitudinalsamples from patients with mild and severe clinical presentationsof leptospirosis, at different phases of the disease, as well as patientsthat died from acute leptospirosis infection. Analyzing longitudinalsamples increased the likelihood of detecting an antigen with transientseroreactivity. In Figure 1, we show representativehistograms of the number of reactive antigens selected from the convalescenttime point for the severe patient group (n = 30)using the inclusion criteria (described in the Materialsand Methods). For some antigens, the high average signal intensityis due to the strong reactivity of a few patients, as observed bythe five orange dots below the orange dotted line in Figure 1B. We also observed that antigens with lower averagesignal intensity show positive reactivity in a few patients, as observedby the last 17 antigens in Figure 1A.


Proteomic features predict seroreactivity against leptospiral antigens in leptospirosis patients.

Lessa-Aquino C, Wunder EA, Lindow JC, Rodrigues CB, Pablo J, Nakajima R, Jasinskas A, Liang L, Reis MG, Ko AI, Medeiros MA, Felgner PL - J. Proteome Res. (2014)

Representativehistograms showing the criteria for selecting reactiveantigens. An antigen was considered to be reactive if either the groupaverage signal intensity or at least 33% of the samples within a groupshowed signal intensity above 2.5 standard deviations of the NoDNAcontrol reactions. The histogram plots the average signal intensity(Y axis) and the number of responsive individuals(secondary Y axis) for each reactive antigen selected(X axis) for IgM (A) or IgG (B) probing of convalescent-phasesamples from severe patients. Dotted lines correspond to the controlreactions cutoff (black) or the minimum number of responsive individuals(orange) included using this criteria.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4286151&req=5

fig1: Representativehistograms showing the criteria for selecting reactiveantigens. An antigen was considered to be reactive if either the groupaverage signal intensity or at least 33% of the samples within a groupshowed signal intensity above 2.5 standard deviations of the NoDNAcontrol reactions. The histogram plots the average signal intensity(Y axis) and the number of responsive individuals(secondary Y axis) for each reactive antigen selected(X axis) for IgM (A) or IgG (B) probing of convalescent-phasesamples from severe patients. Dotted lines correspond to the controlreactions cutoff (black) or the minimum number of responsive individuals(orange) included using this criteria.
Mentions: We probed leptospiral proteinarrays with a collection of 188 serum samples, composed of longitudinalsamples from patients with mild and severe clinical presentationsof leptospirosis, at different phases of the disease, as well as patientsthat died from acute leptospirosis infection. Analyzing longitudinalsamples increased the likelihood of detecting an antigen with transientseroreactivity. In Figure 1, we show representativehistograms of the number of reactive antigens selected from the convalescenttime point for the severe patient group (n = 30)using the inclusion criteria (described in the Materialsand Methods). For some antigens, the high average signal intensityis due to the strong reactivity of a few patients, as observed bythe five orange dots below the orange dotted line in Figure 1B. We also observed that antigens with lower averagesignal intensity show positive reactivity in a few patients, as observedby the last 17 antigens in Figure 1A.

Bottom Line: Together, this group of 14 enriched categories accounts for just 25% of the leptospiral proteome but contains 50% of the immunoreactive antigens.These findings are consistent with our previous studies of other Gram-negative bacteria.This genome-wide approach provides an empirical basis to predict and classify antibody reactive antigens based on structural, physical-chemical, and functional proteomic features and a framework for understanding the breadth and specificity of the immune response to L. interrogans.

View Article: PubMed Central - PubMed

Affiliation: Fiocruz, Bio-Manguinhos, Brazilian Ministry of Health , Avenida Brasil, 4365 - Manguinhos, Rio de Janeiro, RJ 21040-900, Brazil.

ABSTRACT
With increasing efficiency, accuracy, and speed we can access complete genome sequences from thousands of infectious microorganisms; however, the ability to predict antigenic targets of the immune system based on amino acid sequence alone is still needed. Here we use a Leptospira interrogans microarray expressing 91% (3359) of all leptospiral predicted ORFs (3667) and make an empirical accounting of all antibody reactive antigens recognized in sera from naturally infected humans; 191 antigens elicited an IgM or IgG response, representing 5% of the whole proteome. We classified the reactive antigens into 26 annotated COGs (clusters of orthologous groups), 26 JCVI Mainrole annotations, and 11 computationally predicted proteomic features. Altogether, 14 significantly enriched categories were identified, which are associated with immune recognition including mass spectrometry evidence of in vitro expression and in vivo mRNA up-regulation. Together, this group of 14 enriched categories accounts for just 25% of the leptospiral proteome but contains 50% of the immunoreactive antigens. These findings are consistent with our previous studies of other Gram-negative bacteria. This genome-wide approach provides an empirical basis to predict and classify antibody reactive antigens based on structural, physical-chemical, and functional proteomic features and a framework for understanding the breadth and specificity of the immune response to L. interrogans.

Show MeSH
Related in: MedlinePlus