Individual and meta-immune networks

Why current quantitative serology is not quantitative and how systems immunology could provide solutions

Determination of the presence of antibodies against infectious agents, self-antigens, allogeneic antigens and environmental antigens is the goal of medical serology. Along with the standardization of these tests the community also started to use the expression “quantitative serology,” referring to the fact that arbitrary units are used for the expression of results. In this review I will argue against the use of the term quantitative serology for current tests. Because each test and each antibody isotype determination uses its own references, the term semiquantitative better describes these methods. The introduction of really quantitative serology could both benefit from and drive forward systems immunological approach to immunity.

Not by structures alone: Can the immune system recognize microbial functions?

A central question for immunology is: what does the immune system recognize and according to which principles does this kind of recognition work? Immunology has been dominated by the idea of recognizing molecular structures and triggering an appropriate immune response when facing non-self or danger. Recently, characterizations in terms of function have turned out to be more conserved and explanatory in microbiota research than taxonomic composition for understanding microbiota-host interactions. Starting from a conceptual analysis of the notions of structure and function, I raise the title question whether it is possible for the immune system to recognize microbial functions. I argue that this is indeed the case, making the claim that some function-associated molecular patterns are not indicative of the presence of certain taxa (''who is there'') but of biochemical activities and effects (''what is going on''). In addition, I discuss case studies which show that there are immunological sensors that can directly detect microbial activities, irrespective of their specific structural manifestation. At the same time, the discussed account puts the causal role notions of function on a more realist and objective basis.

Diagnostic Profiling of the Human Public IgM Repertoire With Scalable Mimotope Libraries

Specific antibody reactivities are routinely used as biomarkers, but the antibody repertoire reactivity (igome) profiles are still neglected. Here, we propose rationally designed peptide arrays as efficient probes for these system level biomarkers. Most IgM antibodies are characterized by few somatic mutations, polyspecificity, and physiological autoreactivity with housekeeping function. Previously, probing this repertoire with a set of immunodominant self-proteins provided a coarse analysis of the respective repertoire profiles. In contrast, here, we describe the generation of a peptide mimotope library that reflects the common IgM repertoire of 10,000 healthy donors. In addition, an appropriately sized subset of this quasi-complete mimotope library was further designed as a potential diagnostic tool. A 7-mer random peptide phage display library was panned on pooled human IgM. Next-generation sequencing of the selected phage yielded 224,087 sequences, which clustered in 790 sequence clusters. A set of 594 mimotopes, representative of the most significant sequence clusters, was shown to probe symmetrically the space of IgM reactivities in patients' sera. This set of mimotopes can be easily scaled including a greater proportion of the mimotope library. The trade-off between the array size and the resolution can be explored while preserving the symmetric sampling of the mimotope sequence and reactivity spaces. BLAST search of the non-redundant protein database with the mimotopes sequences yielded significantly more immunoglobulin J region hits than random peptides, indicating a considerable idiotypic connectivity of the targeted igome. The proof of principle predictors for random diagnoses was represented by profiles of mimotopes. The number of potential reactivity profiles that can be extracted from this library is estimated at more than 10⁷⁰. Thus, a quasi-complete IgM mimotope library and a scalable representative subset thereof are found to address very efficiently the dynamic diversity of the human public IgM repertoire, providing informationally dense and structurally interpretable IgM reactivity profiles.

A generalized quantitative antibody homeostasis model: antigen saturation, natural antibodies and a quantitative antibody network

In a pair of articles, we present a generalized quantitative model for the homeostatic function of clonal humoral immune system. In this second paper, we describe how antibody production controls the saturation of antigens and the network of antibody interactions that emerges in the epitome space with the establishment of the immune system. Efficient control of antigens, be it self or foreign, requires the maintenance of antibody concentrations that saturate antigen to relevant levels. Simple calculations suggest that the observed diverse recognition of antigens by natural antibodies is only possible by cross-reactivity whereby particular clones of antibodies bind to diverse targets and shared recognition of particular antigens by multiple antibody clones contribute to the maintenance of antigen control. We also argue that natural antibodies are none else than the result of thymus-independent responses against immunological self. We interpret and explain antibody production and function in a virtual molecular interaction space and as a network of interactions. Indeed, the general quantitative (GQM) model we propose is in agreement with earlier models, confirms some assumptions and presumably provides the theoretical basis for the construction of a real antibody network using the sequence and interaction database data.

Can the Immune System Perform a t-Test?

The self-nonself discrimination hypothesis remains a landmark concept in immunology. It proposes that tolerance breaks down in the presence of nonself antigens. In strike contrast, in statistics, occurrence of nonself elements in a sample (i.e., outliers) is not obligatory to violate the null hypothesis. Very often, what is crucial is the combination of (self) elements in a sample. The two views on how to detect a change seem challengingly different and it could seem difficult to conceive how immunological cellular interactions could trigger responses with a precision comparable to some statistical tests. Here it is shown that frustrated cellular interactions reconcile the two views within a plausible immunological setting. It is proposed that the adaptive immune system can be promptly activated either when nonself ligands are detected or self-ligands occur in abnormal combinations. In particular we show that cellular populations behaving in this way could perform location statistical tests, with performances comparable to t or KS tests, or even more general data mining tests such as support vector machines or random forests. In more general terms, this work claims that plausible immunological models should provide accurate detection mechanisms for host protection and, furthermore, that investigation on mechanisms leading to improved detection in “in silico” models can help unveil how the real immune system works.

The Hyper-Modular Associative Mind: A Computational Analysis of Associative Responses of Persons with Asperger Syndrome

Rigidity of thought is considered a main characteristic of persons with Asperger syndrome (AS). This rigidity may explain the poor comprehension of unusual semantic relations, frequently exhibited by persons with AS. Research indicates that such deficiency is related to altered mental lexicon organization, but has never been directly examined. The present study used computational network science tools to compare the mental lexicon structure of persons with AS and matched controls. Persons with AS and matched controls generated free associations, and network tools were used to extract and compare the mental lexicon structure of the two groups. The analysis revealed that persons with AS exhibit a hyper-modular semantic organization: their mental lexicon is more compartmentalized compared to matched controls. We argue that this hyper-modularity may be related to the rigidity of thought which characterizes persons with AS and discuss the clinical and more general cognitive implications of our findings.

Seroprofiling at the Candida albicans protein species level unveils an accurate molecular discriminator for candidemia

Serum antibodies to specific Candida proteins have been reported as potential diagnostic biomarkers for candidemia. However, their diagnostic usefulness at the protein species level has hardly been examined. Using serological proteome analysis, we explored the IgG-antibody responses to Candida albicans protein species in candidemia and control patients. We found that 87 discrete protein species derived from 34 unique proteins were IgG-targets, although only 43 of them were differentially recognized by candidemia and control sera. An increase in the speciation of the immunome, connectivity and modularity of antigenic species co-recognition networks, and heterogeneity of antigenic species recognition patterns was associated with candidemia. IgG antibodies to certain discrete protein species were better predictors of candidemia than those to their corresponding proteins. A molecular discriminator delineated from the combined fingerprints of IgG antibodies to two distinct species of phosphoglycerate kinase and enolase accurately classified candidemia and control patients. These results provide new insight into the anti-Candida IgG-antibody response development in candidemia, and demonstrate that an immunoproteomic signature at the molecular level may be useful for its diagnosis. Our study further highlights the importance of defining pathogen-specific antigens at the chemical and molecular level for their potential application as immunodiagnostic reagents or even vaccine candidates.

Semantic organization in children with cochlear implants: computational analysis of verbal fluency

PURPOSE

Cochlear implants (CIs) enable children with severe and profound hearing impairments to perceive the sensation of sound sufficiently to permit oral language acquisition. So far, studies have focused mainly on technological improvements and general outcomes of implantation for speech perception and spoken language development. This study quantitatively explored the organization of the semantic networks of children with CIs in comparison to those of age-matched normal hearing (NH) peers.

METHOD

Twenty seven children with CIs and twenty seven age- and IQ-matched NH children ages 7-10 were tested on a timed animal verbal fluency task (Name as many animals as you can). The responses were analyzed using correlation and network methodologies. The structure of the animal category semantic network for both groups were extracted and compared.

RESULTS

Children with CIs appeared to have a less-developed semantic network structure compared to age-matched NH peers. The average shortest path length (ASPL) and the network diameter measures were larger for the NH group compared to the CIs group. This difference was consistent for the analysis of networks derived from animal names generated by each group [sample-matched correlation networks (SMCN)] and for the networks derived from the common animal names generated by both groups [word-matched correlation networks (WMCN)].

CONCLUSIONS

The main difference between the semantic networks of children with CIs and NH lies in the network structure. The semantic network of children with CIs is under-developed compared to the semantic network of the age-matched NH children. We discuss the practical and clinical implications of our findings.