Proposing a new focus for the study of natural and artificial cognitive systems

In the study of systems the function of the system is often a good hint to how it works. In the following paper I would like to suggest that in studying or modeling a cognitive system our pre-knowledge of their functions should be treated carefully. We should focus on the statistical distribution of the system's environment and the ways this distribution affects the behavior and development of the cognitive system. I will show an example of how such a focus changes the view of the immune system. I would also like to show how this new outlook on the study of cognitive systems could affect attempts at creating artifcial cognitive system

The immune system and other cognitive systems

In the following pages we propose a theory on cognitive systems and the common strategies of perception, which are at the basis of their function. We demonstrate that these strategies are easily seen to be in place in known cognitive systems such as vision and language. Furthermore we show that taking these strategies into consideration implies a new outlook on immune function calling for a new appraisal of the immune system as a cognitive system

ImmuneDB, a Novel Tool for the Analysis, Storage, and Dissemination of Immune Repertoire Sequencing Data

ImmuneDB is a system for storing and analyzing high-throughput immune receptor sequencing data. Unlike most existing tools, which utilize flat-files, ImmuneDB stores data in a well-structured MySQL database, enabling efficient data queries. It can take raw sequencing data as input and annotate receptor gene usage, infer clonotypes, aggregate results, and run common downstream analyses such as calculating selection pressure and constructing clonal lineages. Alternatively, pre-annotated data can be imported and analyzed data can be exported in a variety of common Adaptive Immune Receptor Repertoire (AIRR) file formats. To validate ImmuneDB, we compare its results to those of another pipeline, MiXCR. We show that the biological conclusions drawn would be similar with either tool, while ImmuneDB provides the additional benefits of integrating other common tools and storing data in a database. ImmuneDB is freely available on GitHub at https://github.com/arosenfeld/immunedb, on PyPi at https://pypi.org/project/ImmuneDB, and a Docker container is provided at https://hub.docker.com/r/arosenfeld/immunedb. Full documentation is available at http://immunedb.com

Computational Evaluation of B-Cell Clone Sizes in Bulk Populations

B cell clones expand and contract during adaptive immune responses and can persist or grow uncontrollably in lymphoproliferative disorders. One way to monitor and track B cell clones is to perform large-scale sampling of bulk cell populations, amplifying, and sequencing antibody gene rearrangements by next-generation sequencing (NGS). Here, we describe a series of computational approaches for estimating B cell clone size in NGS immune repertoire profiling data of antibody heavy chain gene rearrangements. We define three different measures of B cell clone size—copy numbers, instances, and unique sequences—and show how these measures can be used to rank clones, analyze their diversity, and study their distribution within and between individuals. We provide a detailed, step-by-step procedure for performing these analyses using two different data sets of spleen samples from human organ donors. In the first data set, 19 independently generated biological replicates from a single individual are analyzed for B cell clone size, diversity and sampling sufficiency for clonal overlap analysis. In the second data set, B cell clones are compared in eight different organ donors. We comment upon frequently encountered pitfalls and offer practical advice with alternative approaches. Overall, we provide a series of pragmatic analytical approaches and show how different clone size measures can be used to study the clonal landscape in bulk B cell immune repertoire profiling data

AIRR Community Standardized Representations for Annotated Immune Repertoires

Increased interest in the immune system's involvement in pathophysiological phenomena coupled with decreased DNA sequencing costs have led to an explosion of antibody and T cell receptor sequencing data collectively termed “adaptive immune receptor repertoire sequencing” (AIRR-seq or Rep-Seq). The AIRR Community has been actively working to standardize protocols, metadata, formats, APIs, and other guidelines to promote open and reproducible studies of the immune repertoire. In this paper, we describe the work of the AIRR Community's Data Representation Working Group to develop standardized data representations for storing and sharing annotated antibody and T cell receptor data. Our file format emphasizes ease-of-use, accessibility, scalability to large data sets, and a commitment to open and transparent science. It is composed of a tab-delimited format with a specific schema. Several popular repertoire analysis tools and data repositories already utilize this AIRR-seq data format. We hope that others will follow suit in the interest of promoting interoperable standards

Reconstruction of regulatory networks through temporal enrichment profiling and its application to H1N1 influenza viral infection

BACKGROUND: H1N1 influenza viruses were responsible for the 1918 pandemic that caused millions of deaths worldwide and the 2009 pandemic that caused approximately twenty thousand deaths. The cellular response to such virus infections involves extensive genetic reprogramming resulting in an antiviral state that is critical to infection control. Identifying the underlying transcriptional network driving these changes, and how this program is altered by virally-encoded immune antagonists, is a fundamental challenge in systems immunology. RESULTS: Genome-wide gene expression patterns were measured in human monocyte-derived dendritic cells (DCs) infected in vitro with seasonal H1N1 influenza A/New Caledonia/20/1999. To provide a mechanistic explanation for the timing of gene expression changes over the first 12 hours post-infection, we developed a statistically rigorous enrichment approach integrating genome-wide expression kinetics and time-dependent promoter analysis. Our approach, TIme-Dependent Activity Linker (TIDAL), generates a regulatory network that connects transcription factors associated with each temporal phase of the response into a coherent linked cascade. TIDAL infers 12 transcription factors and 32 regulatory connections that drive the antiviral response to influenza. To demonstrate the generality of this approach, TIDAL was also used to generate a network for the DC response to measles infection. The software implementation of TIDAL is freely available at http://tsb.mssm.edu/primeportal/?q=tidal_prog. CONCLUSIONS: We apply TIDAL to reconstruct the transcriptional programs activated in monocyte-derived human dendritic cells in response to influenza and measles infections. The application of this time-centric network reconstruction method in each case produces a single transcriptional cascade that recapitulates the known biology of the response with high precision and recall, in addition to identifying potentially novel antiviral factors. The ability to reconstruct antiviral networks with TIDAL enables comparative analysis of antiviral responses, such as the differences between pandemic and seasonal influenza infections

Chickens, more than humans, focus the diversity of their immunoglobulin genes on the complementarity-determining region but utilise amino acids, indicative of a more cross-reactive antibody repertoire

The mechanisms of B-cell diversification differ greatly between aves and mammals, but both produce B cells and antibodies capable of supporting an effective immune response. To see how differences in the generation of diversity might affect overall repertoire diversity, we have compared the diversity characteristics of immunoglobulin genes from domestic chickens to those from humans. Both use V(D)J gene rearrangement and somatic hypermutation, but only chickens use somatic gene conversion. A range of diversity analysis tools were used to investigate multiple aspects of amino acid diversity at both the germline and repertoire levels. The effect of differing amino acid usages on antibody characteristics was assessed. At both the germline and repertoire levels, chickens exhibited lower amino acid diversity in comparison to the human immunoglobulin genes, especially outside of the complementarity-determining region (CDR). Chickens were also found to possess much larger and more hydrophilic CDR3s with a higher predicted protein binding potential, suggesting that the antigen-binding site in chicken antibodies is more flexible and more polyreactive than that seen in human antibodies