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The continuity of life and its evolution, we proposed, emerge from an interactive group process manifested in networks of interaction. We term this process \textit{survival-of-the-fitted}. Here, we reason that survival of the fitted results from a natural computational process we term \textit{natural autoencoding}. Natural autoencoding works by retaining repeating biological interactions while non-repeatable interactions disappear. (1) We define a species by its \textit{species interaction code}, which consists of a compact description of the repeating interactions of species organisms with their external and internal environments. Species interaction codes are descriptions recorded in the biological infrastructure that enables repeating interactions. Encoding and decoding are interwoven. (2) Evolution proceeds by natural autoencoding of sustained changes in species interaction codes. DNA is only one element in natural autoencoding. (3) Natural autoencoding accounts for the paradox of genome randomization in sexual reproduction -- recombined genomes are analogous to the diversified inputs required for artificial autoencoding. The increase in entropy generated by genome randomization compensates for the decrease in entropy generated by organized life. (4) Natural autoencoding and artificial autoencoding algorithms manifest defined similarities and differences. Recognition of the importance of fittedness could well serve the future of a humanly livable biosphere., Comment: In version 7 we added various clarifications including to terminology, definitions, and to the reference to the second law of thermodynamics

COVID-19 infection tends to be more lethal in older persons than in the young; death results from an overactive inflammatory response, leading to cytokine storm and organ failure. Here we describe immune regulation of the inflammatory response phenotype as emerging from a process that is analogous to machine-learning algorithms used in computers. We briefly describe some strategic similarities between immune learning and computer machine learning. We reason that a balanced response to COVID-19 infection might be induced by treating the elderly patient with a wellness repertoire of antibodies obtained from healthy young people. We propose that a beneficial training set of such antibodies might be administered in the form of intravenous immunoglobulin (IVIg).

An association between T‐cell lymphopenia and autoimmunity has long been proposed, but it remains to be elucidated whether T‐cell lymphopenia affects B‐cell responses to autoantigens. Human neonatal thymectomy (Tx) results in a decrease in T‐cell numbers and we used this model to study the development of autoreactivity. Two cohorts of neonatally thymectomized individuals were examined, a cohort of young (1–5 years post‐Tx, n = 10–27) and older children (>10 years, n = 26), and compared to healthy age‐matched controls. T‐cell and B‐cell subsets were assessed and autoantibody profiling performed. Early post‐Tx, a decrease in T‐cell numbers (2.75 × 109/L vs. 0.71 × 109/L) and an increased proportion of memory T cells (19.72 vs. 57.43%) were observed. The presence of autoantibodies was correlated with an increased proportion of memory T cells in thymectomized children. No differences were seen in percentages of different B‐cell subsets between the groups. The autoantigen microarray showed a skewed autoantibody response after Tx. In the cohort of older individuals, autoantibodies were present in 62% of the thymectomized children, while they were found in only 33% of the healthy controls. Overall, our data suggest that neonatal Tx skews the autoantibody profile. Preferential expansion and preservation of Treg (regulatory T) cell stability and function, may contribute to preventing autoimmune disease development after Tx.

Living organisms are composed of cells and all living cells contain a genome, the organism's stock of deoxyribonucleic acid (DNA). The role of the genome has been likened to a program that encodes the organism's development and its subsequent response to the environment. This computer metaphor teaches that the organism – the hardware – is controlled by the software – the genome. Thus, the organism and its fate can be explained by genetics, the plans written into the sequence of genomic DNA; the Genome Project was devised to decipher this program. However, it is now clear that the genome does not directly program the organism; the computer program metaphor has misled us. The genome is only one class of vital information that serves the organism. Metaphorically, the genome can be likened to a vocabulary of words that can be deployed to make meaningful sentences, or to a toolbox for accomplishing specific tasks. Key concepts: The genome does not function as a master plan or computer program for controlling the organism; the genome is the organism's servant, not its master. The genome is a reservoir of DNA sequence information and a vehicle for transmitting this information; the meaning of DNA emerges from the cellular processing of this raw information into proteins and other functional molecules. DNA is only one class of vital information that serves the organism; the organism epigenetically uses, manipulates, regulates and, in the case of the immune system, creates genes. The effects of a gene vary with the organism's environment; the interactions between genes and environment are not linear and, in most cases, not additive. Therefore, one cannot compute with certainty the relative contributions of genes and environment to an organism's observed features – its phenotype. Metaphorically, we can think of the genome as akin to a list of words, a vocabulary, which can be used to build and express a meaningful language; like a vocabulary, a genome by itself has no functional meaning. The genome is thus akin to a toolbox of DNA sequences that provide molecular tools as requested by the internal state of the organism and the state of the environment. One's genes cannot explain one's being: an organism is the expression of a dynamic and ongoing interaction between the state of its environment and its internal state, which includes its past history and its toolbox of DNA sequences. Keywords: genetics; computer program; evolution; information; complexity

Objective To address whether a targeted modulation of the abnormal expression of Hsp70 and autoantibodies against this molecule in systemic lupus erythematosus can influence disease. Methods Lupus-prone (NZB × NZW)F1 mice that had been DNA-vaccinated with plasmids encoding Hsp70 and controls were monitored for lupus disease parameters including anti-double stranded DNA (anti-dsDNA) autoantibodies and cytokines using enzyme-linked immunosorbent assay, and for kidney function and pathology. The phenotypic and numerical changes in relevant immune cells were evaluated by flow cytometry, and cell function was assessed. Results Mice that had been DNA-vaccinated with Hsp70 displayed marked suppression of anti-dsDNA antibody production, reduced renal disease, and antiinflammatory responses that are associated with a significantly extended survival, compared to controls. These protective effects in Hsp70-vaccinated mice were associated with an induction of tolerogenic immune responses and an expansion of functional Treg cells. Conclusion DNA vaccination with Hsp70 suppresses murine lupus by inducing tolerogenic immune responses and antiinflammatory immune responses associated with reduced disease manifestations and increased mouse survival.

Here, we outline an overview of the mammalian immune system that updates and extends the classical clonal selection paradigm. Rather than focusing on strict self-not-self discrimination, we propose that the system orchestrates variable inflammatory responses that maintain the body and its symbiosis with the microbiome while eliminating the threat from pathogenic infectious agents and from tumors. The paper makes four points: The immune system classifies healthy and pathologic states of the body-including both self and foreign elements-by deploying individual lymphocytes as cellular computing machines; immune cells transform input signals from the body into an output of specific immune reactions.Rather than independent clonal responses, groups of individually activated immune-system cells co-react in lymphoid organs to make collective decisions through a type of self-organizing swarm intelligence or crowd wisdom.Collective choices by swarms of immune cells, like those of schools of fish, are modified by relatively small numbers of individual regulators responding to shifting conditions-such collective inflammatory responses are dynamically responsive.Self-reactive autoantibody and T-cell receptor (TCR) repertoires shared by healthy individuals function in a biological version of experience-based supervised machine learning. Immune system decisions are primed by formative experience with training sets of self-antigens encountered during lymphocyte development; these initially trained T cell and B cell repertoires form a Wellness Profile that then guides immune responses to test sets of antigens encountered later. This experience-based machine learning strategy is analogous to that deployed by supervised machine-learning algorithms. We propose experiments to test these ideas. This overview of the immune system bears clinical implications for monitoring wellness and for treating autoimmune disease, cancer, and allograft reactions.

Alzheimer's disease (AD) is a neurodegenerative disorder which is the most prevalent cause of dementia in the western world. Currently, it is the most expensive disease in America, costing more than heart diseases and cancer and as the world population is getting older it is expected to become the most expensive medical disorder in the world. AD is characterized by three core pathologies: accumulation of amyloid β (Aβ) plaques, neurofibrillary tangles (NFT) and sustained inflammation. It is now believed that inflammation provides the link between Aβ and NFT. The immune system is therefore, a major player in the pathogenesis of AD. Here we propose that Bacillus Calmette-Guerin (BCG) could affect the incidence of AD. Bacillus Calmette-Guerin (BCG) is a live attenuated Mycobacterium bovis preparation first developed as a vaccine against M. tuberculosis. It has been shown to be moderately effective in preventing tuberculosis, while noted to induce modifications in inflammatory response and to regulate the immune system. Intra-vesical administration of BCG is used successfully in the past four decades to prevent recurrence of non-muscle invasive bladder cancer. In this manuscript we investigate the hypothesis that exposure to BCG decreases the prevalence of AD in elderly population and that this occurs through modulation of the immune system. Our hypothesis is based on several lines of evidence: lower prevalence of AD in countries with high BCG coverage, ability of BCG to ameliorate several conditions involving the immune system like type 1 diabetes mellitus and multiple sclerosis, animal models of AD in which BCG shows therapeutic potential and a plausible molecular mechanism which may be the basis for this hypothesis. Namely, elevated systemic levels of IL-2 (as found when BCG is given intra-vesically) that amplify Treg cells that inhibit AD associated inflammation, decreased plaque formation and restore cognitive function. To test this hypothesis one may study cognition in the large available "natural adult population" exposed to high dose of BCG through the bladder. Bladder cancer survivors not given BCG can serve as control group. This population can be used without adding any medical intervention.

We describe here the development, verification and validation of the SLE-key ® rule-out test for a definitive rule-out of a diagnosis of systemic lupus erythematosus (SLE). The test uses the proprietary iCHIP ® micro-array technology platform (Fattal et al., 2010) to identify discriminating patterns of circulating autoantibodies among SLE patients compared with self-declared healthy individuals. Given the challenges associated with the diagnosis of SLE and the healthcare costs of delayed diagnosis and misdiagnosis, a definitive rule-out test can provide significant clinical benefits to patients and potentially major cost savings to healthcare systems.

To enable microbial colonization of the gut mucosa, the intestinal immune system must not only react to danger signals but also recognize cues that indicate safety. Recognition of safety, paradoxically, is mediated by the same environmental sensors that are involved in signaling danger. Indeed, in addition to their well-established role in inducing inflammation in response to stress signals, pattern recognition receptors and a variety of metabolic sensors also promote gut-microbiota symbiosis by responding to "microbial symbiosis factors", "resolution-associated molecular patterns", markers of energy extraction and other signals indicating the absence of pathogenic infection and tissue damage. Here we focus on how the paradoxical roles of immune receptors and other environmental sensors define the microbiota signature of an individual.

The evolution of multicellular eukaryotes expresses two sorts of adaptations: local adaptations like fur or feathers, which characterize species in particular environments, and universal adaptations like microbiomes or sexual reproduction, which characterize most multicellulars in any environment. We reason that the mechanisms driving the universal adaptations of multicellulars should themselves be universal, and propose a mechanism based on properties of matter and systems: energy, entropy, and interaction. Energy from the sun, earth and beyond creates new arrangements and interactions. Metabolic networks channel some of this energy to form cooperating, interactive arrangements. Entropy, used here as a term for all forces that dismantle ordered structures (rather than as a physical quantity), acts as a selective force. Entropy selects for arrangements that resist it long enough to replicate, and dismantles those that do not. Interactions, energy-charged and dynamic, restrain entropy and enable survival and propagation of integrated living systems. This fosters survival-of-the-fitted – those entities that resist entropic destruction – and not only of the fittest – the entities with the greatest reproductive success. The “unit” of evolution is not a discrete entity, such as a gene, individual, or species; what evolves are collections of related interactions at multiple scales. Survival-of-the-fitted explains universal adaptations, including resident microbiomes, sexual reproduction, continuous diversification, programmed turnover, seemingly wasteful phenotypes, altruism, co-evolving environmental niches, and advancing complexity. Indeed survival-of-the-fittest may be a particular case of the survival-of-the-fitted mechanism, promoting local adaptations that express reproductive advantages in addition to resisting entropy. Survival-of-the-fitted accounts for phenomena that have been attributed to neutral evolution: in the face of entropy, there is no neutrality; all variations are challenged by ubiquitous energy and entropy, retaining those that are “fit enough”. We propose experiments to test predictions of the survival-of-the-fitted theory, and discuss implications for the wellbeing of humans and the biosphere.

Background Alzheimer’s disease (AD) affects one in ten people older than 65 years. Thus far, there is no cure or even disease-modifying treatment for this disease. The immune system is a major player in the pathogenesis of AD. Bacillus Calmette-Guerin (BCG), developed as a vaccine against tuberculosis, modulates the immune system and reduces recurrence of non-muscle invasive bladder cancer. Theoretical considerations suggested that treatment with BCG may decrease the risk of AD. We tested this hypothesis on a natural population of bladder cancer patients. Methods and findings After removing all bladder cancer patients presenting with AD or developing AD within one-year following diagnosis of bladder cancer, we collected data on a total of 1371 patients (1134 males and 237 females) who were followed for at least one year after the diagnosis of bladder cancer. The mean age at diagnosis of bladder cancer was 68.1 years (SD 13.0). Adjuvant post-operative intra-vesical treatment with BCG was given to 878 (64%) of these patients. The median period post-operative follow-up was 8 years. During follow-up, 65 patients developed AD at a mean age of 84 years (SD 5.9), including 21 patients (2.4%) who had been treated with BCG and 44 patients (8.9%) who had not received BCG. Patients who had been treated with BCG manifested more than 4-fold less risk for AD than those not treated with BCG. The Cox proportional hazards regression model and the Kaplan-Meier analysis of AD free survival both indicated high significance: patients not treated with BCG had a significantly higher risk of developing AD compared to BCG treated patients (HR 4.778, 95%CI: 2.837–8.046, p = 4.08x10-9 and Log Rank Chi-square 42.438, df = 1, p = 7.30x10-11, respectively). Exposure to BCG did not modify the prevalence of Parkinson’s disease, 1.9% in BCG treated patients and 1.6% in untreated (Fisher’s Exact Test, p = 1). Conclusions Bladder cancer patients treated with BCG were significantly less likely to develop AD at any age than patients who were not so treated. This finding of a retrospective study suggests that BCG treatment might also reduce the incidence of AD in the general population. Confirmation of such effects of BCG in other retrospective studies would support prospective studies of BCG in AD.

In this work, we studied autoantibody repertoires and Ig isotypes in 71 mothers and their 104 healthy newborns (including twins and triplets delivered term or premature). Newborns receive maternal IgG Abs via the placenta before birth, but developing infants must produce their own IgM and IgA Abs. We used an Ag microarray analysis to detect binding to a selection of 295 self-Ags, compared with 27 standard foreign Ags. The magnitude of binding to specific self-Ags was found to be not less than that to the foreign Ags. As expected, each newborn shared with its mother a similar IgG repertoire—manifest as early as the 24th week of gestation. IgM and IgA autoantibody repertoires in cord sera were highly correlated among the newborns and differed from their mothers’ repertoires; the latter differed in sera and milk. The autoantibodies bound to self-Ags known to be associated with tumors and to autoimmune diseases. Thus, autoantibody repertoires in healthy humans—the immunological homunculus—arise congenitally, differ in maternal milk and sera, and mark the potential of the immune system to attack tumors, beneficially, or healthy tissues, harmfully; regulation of the tissue site, the dynamics, and the response phenotype of homuncular autoimmunity very likely affects health.

Background The SLE-key® RuleOut iCHIP® antigen microarray-based test rules out a diagnosis of SLE with a sensitivity of 94%1. Objectives Here we report the use of the iCHIP® platform and a set of synthetic oligonucleotide antigens to distinguish between SLE subjects and those with a diagnosis of Rheumatoid Arthritis (RA), Scleroderma (SSc), Sjogren9s syndrome (SS), or healthy individuals (HC). Methods We examined IgM and IgG antibody binding to 22 synthetic oligonucleotides (44 features) in the sera of HC subjects (N=40); SLE (N=30); SSc (N=40); SS (N=20); or RA (N=30) patients. Univariate analysis (FDR adjusted p-values) was used to determine the ability of each feature to separate between SLE and the different classes of subjects. Results Table 1 shows that multiple oligonucleotides successfully distinguished SLE patients from all other groups. All significant features were IgG antibodies, except for 1 IgM. Table 2 shows the impact of single nucleotide change on autoantibody binding. PolyG (G17) separates SLE from all but SS. T1G16 separates SLE from HC subjects, while G16T1 gave no significant separation. The addition of a G to the 59 and 39 end of T16 enhanced IgG antibody binding and improved separation between SLE and other autoimmune diseases with at least 10-fold improved significance as compared to T20. PolyG sequence length impacts the ability of the oligonucleotides to separate between SLE and the other groups (Fig. 1A). Unexpectedly, sequences either shorter or longer than G14 were effective in separating SLE from HC, RA, and SSc, while G14 was not effective. Furthermore, none of the polyG homopolymers could separate SLE from SS. Sequences rich in C or T were more effective at separating between SLE and SS patients (Fig. 1B). Conclusions Autoantibody binding to oligonucleotides can be used to differentiate SLE from other autoimmune conditions and healthy subjects. The structural basis for the differences in binding of antibodies from disease sera to the various oligonucleotides is not yet understood, but may be due to immunologically unique conformations and secondary structures of oligonucleotides of defined length and sequence. SSc can be differentiated from SLE based on particular antibody binding to epitopes of oligonucleotides containing C and T. RA can be differentiated from SLE more significantly than the other autoimmune conditions. The iCHIP® microarray technology is being further developed to generate a clinically useful test to rule in a diagnosis of SLE relative to other related autoimmune diseases. References Putterman et al., J Immunol Methods 2016. Fattal et al., Immunology, 2010. Fattal et al., Immunology, 2015. Acknowledgements Authors wish to acknowledge Cohen-Gindi O, Lerner M, Tarnapolski O, Blumenstein Y, Javaherian A, Pitts J, Barton M and Wong E. and the Innovative Medicines Initiative Joint Undertaking under grant agreement n° 115308 BIOVACSAFE. Disclosure of Interest C. Putterman Consultant for: ImmunArray, A. Gabrielli: None declared, A. Balbir-Gurman: None declared, P. Safer Employee of: ImmunArray, K. Jakobi-Brook: None declared, R. Sorek Employee of: ImmunArray, I. Gluzman Employee of: ImmunArray, S. Wallace Employee of: ImmunArray, I. Cohen Shareholder of: ImmunArray, Consultant for: ImmunArray

Background We previously described the SLE-key® RuleOut test1,2 to rule out the presence of systemic lupus erythematosus (SLE) with 94% sensitivity, 75% specificity, and 93% negative predictive value. We also reported that the SLE-key® signature appeared to be independent of disease activity or duration3 suggesting4 that that the SLE-key® signature might persist over time in the same subject. Objectives Here we report that the SLE-key® signature remains stable over time in paired samples drawn from most individual subjects, regardless of disease activity. Methods We determined the SLE-key® RuleOut scores for 113 paired serum samples submitted by clinics specializing in SLE. SLEDAI scores at the time of the blood draw ranged from 0 to 22. The mean SLEDAI difference within the pairs was 2.7±6.3. Samples were collected from subjects with a T1-T2 time difference that ranged from 0 to 11.5 years (mean =2±2.6 years). Results The SLE-Key® RuleOut test identifies an SLE-specific signature based on a profile of autoantibodies to a combination of nucleic acids (complex ssDNA and a defined oligonucleotide) and protein biomarkers. Patients with an SLE-key® score of >0.18 are considered not ruled out for a diagnosis of SLE. In 84% of paired samples, patients9 SLE-key® scores remained essentially the same (Figure 1, closed circles). The scores for these subjects were stable, persistent, and independent of SLEDAI score or time between sampling. Significant changes in the SLE-key® scores of 18/113 patient pairs (open circles) appear to be independent of time between blood draws and change in SLEDAI score. In 7 cases there was a change in Rule Out status of the patients. In 3 cases, both scores were close to the 0.18 threshold and the change was deemed not significant. In 4 cases, patients9 status changed from RuledOut to Not Ruled Out, but with no correlation to change in SLEDAI score or time between sampling dates. Records of patients with changing SLE-key® scores are being studied to determine the reasons and the clinical implications of the change. Conclusions The SLE-key® RuleOut test detects a serologic signature which remains stable between sampling dates and over a long period of time after diagnosis in 84% of subjects. Subjects who were ruled out at T1 were generally ruled out at T2. Patients not ruled out at T1 remained not ruled out at T2. The clinical implications of a changing SLE-key® RuleOut score in the remaining 16% of patients may be meaningful, and are currently being carefully investigated. References Fattal et al; Immunology 2010. Putterman et al., J Immunol Methods, 2016. Putterman et al., Lupus 2016. Cohen IR, Lupus Open Access 2016. Acknowledgements The authors wish to acknowledge the invaluable contributions of Cohen-Gindi O, Lerner M, Tarnapolski O, Blumenstein Y, Javaherian A, Pitts J, Barton M and Wong E and Innovative Medicines Initiative Joint Undertaking under grant agreement n° 115308 BIOVACSAFE. Disclosure of Interest C. Putterman Consultant for: ImmunArray, M. Petri: None declared, R. Caricchio: None declared, P. Safer Employee of: ImmunArray, K. Jakobi Employee of: ImmunArray, R. Sorek Employee of: ImmunArray, I. Gluzman Employee of: ImmunArray, S. Wallace Employee of: ImmunArray, I. Cohen Shareholder of: ImmunArray, Consultant for: ImmunArray

Cell stress of various kinds can lead to the induction of cell death and a damaging inflammatory response. Hence, a goal of therapeutic cell-stress management is to develop agents that might effectively regulate undesirable cell death and inflammation. To that end, we developed a synthetic peptide of seven amino acids based on structural mimicry to a functional domain of p53, a key factor in the responses of cells to stressful stimuli. This heptapeptide, which we term Stressin-1, was found to inhibit both cell death and the secretion of inflammatory mediators by various cell types in response to different stressful agents in vitro. The combined anti-inflammatory and anti-apoptotic activities of Stressin-1 were associated with a cellular signalling cascade that induced activation of Akt kinase and activation of the cAMP response element-binding protein (CREB) transcription factor. These immediate signalling events led to the inhibition of the signal transducer and activator of transcription and nuclear factor-κB pathways 24 hr later. Unexpectedly, we found no evidence for a direct involvement of p53 in the effects produced by Stressin-1. Intraperitoneal administration of 100 μg of Stressin-1 to lethally irradiated mice significantly protected them from death. These findings show that activating the Akt-CREB axis with Stressin-1 can counteract some of the undesirable effects of various cell stresses. Stressin-1 may have clinical usefulness.

The T-cell receptor (TCR) repertoire is formed by random recombinations of genomic precursor elements; the resulting combinatorial diversity renders unlikely extensive TCR sharing between individuals. Here, we studied CDR3β amino acid sequence sharing in a repertoire-wide manner, using high-throughput TCR-seq in 28 healthy mice. We uncovered hundreds of public sequences shared by most mice. Public CDR3 sequences, relative to private sequences, are two orders of magnitude more abundant on average, express restricted V/J segments, and feature high convergent nucleic acid recombination. Functionally, public sequences are enriched for MHC-diverse CDR3 sequences that were previously associated with autoimmune, allograft, and tumor-related reactions, but not with anti-pathogen-related reactions. Public CDR3 sequences are shared between mice of different MHC haplotypes, but are associated with different, MHC-dependent, V genes. Thus, despite their random generation process, TCR repertoires express a degree of uniformity in their post-genomic organization. These results, together with numerical simulations of TCR genomic rearrangements, suggest that biases and convergence in TCR recombination combine with ongoing selection to generate a restricted subset of self-associated, public CDR3 TCR sequences, and invite reexamination of the basic mechanisms of T-cell repertoire formation.

Recent findings have provided evidence for the existence of non-vertebrate acquired immunity. We survey these findings and propose that all living organisms must express both innate and acquired immunity. This is opposed to the paradigm that only vertebrates manifest the two forms of immune mechanism; other species are thought to use innate immunity alone. We suggest new definitions of innate and acquired immunity, based on whether immune recognition molecules are encoded in the inherited genome or are generated through somatic processes. We reason that both forms of immunity are similarly ancient, and have co-evolved in response to lifestyle, cost-benefit tradeoffs and symbiosis versus parasitism. However, different species have evolved different immune solutions that are not necessarily genetically related, but serve a similar general function - allowing individuals to learn from their own immune experience; survival of species is contingent on the acquired immune experience of its individuals.

Diversity of T cell receptor (TCR) repertoires, generated by somatic DNA rearrangements, is central to immune system function. However, the level of sequence similarity of TCR repertoires within and between species has not been characterized. Using network analysis of high-throughput TCR sequencing data, we found that abundant CDR3-TCRβ sequences were clustered within networks generated by sequence similarity. We discovered a substantial number of public CDR3-TCRβ segments that were identical in mice and humans. These conserved public sequences were central within TCR sequence-similarity networks. Annotated TCR sequences, previously associated with self-specificities such as autoimmunity and cancer, were linked to network clusters. Mechanistically, CDR3 networks were promoted by MHC-mediated selection, and were reduced following immunization, immune checkpoint blockade or aging. Our findings provide a new view of T cell repertoire organization and physiology, and suggest that the immune system distributes its TCR sequences unevenly, attending to specific foci of reactivity. DOI: http://dx.doi.org/10.7554/eLife.22057.001

Aberrant inflammation appears to be a pathogenic factor in autoimmune diseases and other noxious inflammatory conditions in which the inflammatory process is misapplied, exaggerated, recurrent or chronic. The protein molecules involved in pathogenic inflammation—disease-associated proteins (DAP)—which include chemokines, cytokines, and growth factors and their receptors, appear normal; their networks of interaction are at fault. Here we demonstrate a new approach to network regulation of inflammation based on peptide sequence motifs shared by the second extra-cellular loop (ECL2) of different chemokine receptors; previously known chemokine receptor binding sites have not involved the ECL2 loop. These motifs of 9 amino acids, which we detected by sequence alignment, manifest very low E-values compared with slightly modified sequence variations, indicating that they were not likely to have evolved by chance. To test whether this shared sequence network (SSN) might serve a regulatory function, we synthesized...

Here we review T-cell vaccination (TCV), a cell-based, generic approach to immune regulation. We describe TCV clinical trials in multiple sclerosis and other autoimmune diseases; we analyze the immune regulatory mechanisms activated by TCV; we examine the potential of public T cells as TCV mediators, and we discuss the physiology of immune regulation in the light of TCV.

In October of 2015, the startup company ImmunArray announced the launch of a microarray platform – the iChip® – to profile repertoires of serum antibodies and autoantibodies. The first iChip® product – the SLE-key® RuleOut test – is designed to help the physician rule out a diagnosis of systemic lupus erythematosus (SLE) in suspected patients. The aim of this review is threefold: the first aim is to describe how basic observations and a philosophical notion led me to undertake the development of what has turned out to be a clinically useful aid in dealing with complex diseases; the second aim is to describe the role of a company in overcoming the technological and informatics challenges involved in translating basic research into patient welfare; the third aim is to discuss why SLE, like other complex medical problems, can be better managed using immune profiling. Basic scientist readers might learn here about the path to clinical application; clinician readers might learn here about the complicated origins of seemingly simple tests.

In his pioneering 1952 paper, “The chemical basis of morphogenesis”, Alan Turing introduced, perhaps for the first time, a model of the morphogenesis of embryo development. Central to his theory is the concept of cells with chemical entities that interact with morphogens to drive embryonic development through changes in what he termed ‘the state of the system’. Turing's concepts have inspired many mathematical and computational models proposed since then. Here we discuss the way Turing's ideas inspired our approach to the state-based modeling of morphogenesis, which results in a fully executable program for the interactions between chemical entities and morphogens. As a representative example we describe our modeling of pancreatic organogenesis, a complex developmental process that develops from a flat sheet of cells into a 3D cauliflower-like shape. We show how we constructed the model and tested the relations between morphogens and cells, and illustrate the analysis of the model against experimental data. Finally, we discuss a variant of the original Turing-Test for a machine's ability to demonstrate intelligence as a future means to validate computerized biological models, like the one presented here.

Gliomas that grow uninhibited in the brain almost never metastasize outside the CNS. The rare occurrences of extracranial metastasis are usually associated with a suppressed immune system. This observation raises the possibility that some gliomas might not grow outside the CNS due to an inherent immune response, We report in this study that the highly malignant F98 Fischer rat undifferentiated glioma, which grows aggressively in the brain, spontaneously regresses when injected live s.c. We found that this regression is immune-mediated and that it markedly enhances the survival or cures rats challenged with the same tumor intracranially either before or after the s.c. live-cell treatment. Adoptive transfer experiments showed the effect was immune-mediated and that the CD8 T cell fraction, which exhibited direct tumor cytotoxicity, was more effective than the CD4 T cell fraction in mediating resistance to intracranial challenge of naive rats. Brain tumors from treated rats exhibited enhanced CD3+CD8+CD4− and CD3+CD4+CD8− T cell infiltration and IFN-γ secretion. The results in the F98 glioma were corroborated in the Lewis rat CNS-1 astrocytoma. In both tumor models, s.c. treatment with live cells was significantly better than immunization with irradiated cells. We propose in this study a location-based immunotherapeutic phenomenon we term “split immunity”: a tumor that thrives in an immune-privileged site may be inhibited by injecting live, unmodified tumor cells into a site that is not privileged, generating protective immunity that spreads back to the privileged site. Split immunity could explain several long-standing paradoxes regarding the lack of overt extracranial metastasis in patients with primary brain tumors.

Heat shock proteins (HSPs) were initially discovered as participants in the cellular response to stress. It is now clear, however, that self and microbial HSPs also play an important role in the control of the immune response. Here, we focus on HSP60 and its interactions with both the innate and adaptive immune system in mammals. We also consider that circulating HSP60 and the quantities and specificities of serum antibodies to HSP60 provide a biomarker to monitor the immune status of the individual. Thus, the dual role of HSP60 as an immune modulator and a biomarker, provides an opportunity to modulate immunity for therapeutic purposes, and to monitor the immune response in health and disease.

Over the past decade, multi-level complex behavior and reactive nature of biological systems, has been a focus point for the biomedical community. We have developed a computational approach, termed Reactive Animation (RA) for simulating such complex biological systems. RA is an approach for describing the dynamic characteristics of biological systems based on facts collected from experiments. These data are integrated bottom-up by computational tools and methods for reactive systems development and are simulated concomitantly to a front-end user friendly visualization and reporting systems. Using RA, the experimenter may intervene mid-simulation, suggest new hypotheses for cellular and molecular interactions, apply them to the simulation and observe their resulting outcomes "on-line". Several RA models have been developed including models of T cell activation, thymocyte development and pancreatic organogenesis, which are describe in the in this review.

Up to one in four lung-transplanted patients develop pulmonary infiltrates and impaired oxygenation within the first days after lung transplantation. Known as primary graft dysfunction (PGD), this condition increases mortality significantly. Complex interactions between donor lung and recipient immune system are the suspected cause. We took an integrative, systems-level approach by first exploring whether the recipient's immune response to PGD includes the development of long-lasting autoreactivity. We next explored whether proteins displaying such differential autoreactivity also display differential gene expression in donor lungs that later develop PGD compared with those that did not. We evaluated 39 patients from whom autoantibody profiles were already available for PGD based on chest radiographs and oxygenation data. An additional nine patients were evaluated for PGD based on their medical records and set aside for validation. From two recent donor lung gene expression studies, we reanalysed and paired gene profiles with autoantibody profiles. Primary graft dysfunction can be distinguished by a profile of differentially reactive autoantibodies binding to 17 proteins. Functional analysis showed that 12 of these proteins are part of a protein-protein interaction network (P=3 x 10⁻⁶) involved in proliferative processes. A nearest centroid classifier assigned correct PGD grades to eight out of the nine patients in the validation cohort (P=0·048). We observed significant positive correlation (r=0·63, P=0·011) between differences in IgM reactivity and differences in gene expression levels. This connection between donor lung gene expression and long-lasting recipient IgM autoantibodies towards a specific set of proteins suggests a mechanism for the development of autoimmunity in PGD.

Patients with systemic lupus erythematosus (SLE) produce antibodies to many different self-antigens. Here, we investigated antibodies in SLE sera using an antigen microarray containing many hundreds of antigens, mostly self-antigens. The aim was to detect sets of antibody reactivities characteristic of SLE patients in each of various clinical states – SLE patients with acute lupus nephritis, SLE patients in renal remission, and SLE patients who had never had renal involvement. The analysis produced two novel findings: (i) an SLE antibody profile persists independently of disease activity and despite long-term clinical remission, and (ii) this SLE antibody profile includes increases in four specific immunoglobulin G (IgG) reactivities to double-stranded DNA (dsDNA), single-stranded DNA (ssDNA), Epstein–Barr virus (EBV) and hyaluronic acid; the profile also includes decreases in specific IgM reactivities to myeloperoxidase (MPO), CD99, collagen III, insulin-like growth factor binding protein 1 (IGFBP1) and cardiolipin. The reactivities together showed high sensitivity (> 93%) and high specificity for SLE (> 88%). A healthy control subject who had the SLE antibody profile was later found to develop clinical SLE. The present study did not detect antibody reactivities that differentiated among the various subgroups of SLE subjects with statistical significance. Thus, SLE is characterized by an enduring antibody profile irrespective of clinical state. The association of SLE with decreased IgM natural autoantibodies suggests that these autoantibodies might enhance resistance to SLE.

Obliterative bronchiolitis (OB) continues to be the major limitation to long-term survival after lung transplantation. The specific aetiology and pathogenesis of OB are not well understood. To explore the role of autoreactivity in OB, we spotted 751 different self molecules onto glass slides, and used these antigen microarrays to profile 48 human serum samples for immunoglobulin G (IgG) and IgM autoantibodies; 27 patients showed no or mild bronchiolitis obliterans syndrome (BOS; a clinical correlate of OB) and 15 patients showed medium to severe BOS. We now report that these BOS grades could be differentiated by a profile of autoantibodies binding to 28 proteins or their peptides. The informative autoantibody profile included down-regulation as well as up-regulation of both IgM and IgG specific reactivities. This profile was evaluated for robustness using a panel of six independent test patients. Analysis of the functions of the 28 informative self antigens showed that eight of them are connected in an interaction network involved in apoptosis and protein metabolism. Thus, a profile of autoantibodies may reflect pathological processes in the lung allograft, suggesting a role for autoimmunity in chronic rejection leading to OB.

Complex biological systems involve incorporated behaviors of numerous processes, mechanisms and objects. However, experimental analysis, by its nature, divides biological systems into static interactions with little dynamics. To bridge the gap between experimental data and the underlying behavior, our group has been formalizing biological findings into mathematically and algorithmically rigorous specifications, which are then compiled into reactive models. To realistically animate our models, we designed a generic architecture for the earlier idea of reactive animation, in a way that allows it to link up reactive models with animation tools. Here, we describe the reactive animation approach and some of the benefits of employing it to simulate and analyze complex biological systems. We illustrate our approach with a model of pancreatic development, a highly complex system with a unique 3D structure, and also mention more recent work on adding animation to the generic cell project (GemCell).

An experimental autoimmune multiple sclerosis-like disease (EAMSD) was induced in rabbits by immunizing them with bovine brain gangliosides. Forebrain myelin was isolated and fractionated on a discontinuous sucrose gradient into light myelin (LM, buoyant density less than or equal to 0.625 M), and heavy myelin (HM, buoyant density greater than 0.625 M). No abnormalities in either protein or lipid composition of EAMSD myelin fractions were observed. However, the EAMSD tissue yielded 31% less light and 39% more heavy myelin compared to the control brains. Thus, the HL/LM ratio was two-fold greater in experimental than in control myelin. This pathological pattern is similar to that which has been observed in myelin obtained from the brains of multiple sclerosis patients and from the optic nerves of rabbits with experimentally-induced demyelination.

Organogenesis, the process by which organs develop from individual precursor stem cells, requires that the precursor cells proliferate, differentiate, and aggregate to form a functioning structure. This process progresses through changes in 4 dimensions: time and 3 dimensions of space—4D. Experimental analysis of organogenesis, by its nature, cuts the 4D developmental process into static, 2D histological images or into molecular or cellular markers and interactions with little or no spatial dimensionality and minimal dynamics. Understanding organogenesis requires integration of the piecemeal experimental data into a running, realistic and interactive 4D simulation that allows experimentation and hypothesis testing in silico. Here, we describe a fully executable, interactive, visual model for 4D simulation of organogenic development using the mouse pancreas as a representative case. Execution of the model provided a dynamic description of pancreas development, culminating in a structure that remarkably recapitulated morphologic features seen in the embryonic pancreas. In silico mutations in key signaling molecules resulted in altered patterning of the developing pancreas that were in general agreement with in vivo data. The modeling approach described here thus typifies a useful platform for studying organogenesis as a phenomenon in 4 dimensions.

Lymph nodes are organs in which lymphocytes respond to antigens to generate, among other cell types, plasma cells that secrete specific antibodies and memory lymphocytes for enhanced future responses to the antigen. To achieve these ends, the lymph node (LN) has to orchestrate the meeting and interactions between the antigen and various cell types including the rare clones of B cells and T cells bearing receptors for the antigen. The process is dynamic in essence and involves chemotaxis of responding cells through various anatomical compartments of the LN and selective cell differentiation, proliferation and programmed death. Understanding the LN requires a dynamic integration of the mass of data generated by extensive experimentation. Here, we present a fully executable, bottom-up computerized model of the LN using the visual language of Statecharts and the technology of reactive animation (RA) to create a dynamic front-end. We studied the effects of amount of antigen and LN size on the emergent properties of lymphocyte dynamics, differentiation and anatomic localization. The dynamic organization of the LN visualized by RA sheds new light on how the immune system transforms antigen stimulation into a highly sensitive, yet buffered response.

HIV infection is initiated by the fusion of the viral membrane with the target T-cell membrane. The HIV envelope glycoprotein, gp41, contains a fusion peptide (FP) in the N terminus that functions together with other gp41 domains to fuse the virion with the host cell membrane. We recently reported that FP co-localizes with CD4 and T-cell receptor (TCR) molecules, co-precipitates with TCR, and inhibits antigen-specific T-cell proliferation and pro-inflammatory cytokine secretion. Molecular dynamic simulation implicated an interaction between an alpha-helical transmembrane domain (TM) of the TCRalpha chain (designated CP) and the beta-sheet 5-13 region of the 16 N-terminal amino acids of FP (FP(1-16)). To correlate between the theoretical prediction and experimental data, we synthesized a series of mutants derived from the interacting motif GALFLGFLG stretch (FP(5-13)) and investigated them structurally and functionally. The data reveal a direct correlation between the beta-sheet structure of FP(5-13) and its mutants and their ability to interact with CP and induce immunosuppressive activity; the phenylalanines play an important role. Furthermore, studies with fluorescently labeled peptides revealed that this interaction leads to penetration of the N terminus of FP and its active analogues into the hydrophobic core of the membrane. A detailed understanding of the molecular interactions mediating the immunosuppressive activity of the FP(5-13) motif should facilitate evaluating its contribution to HIV pathology and its exploitation as an immunotherapeutic tool.

The mass and complexity of biological information requires computer-aided simulation and analysis to help scientists achieve understanding and guide experimentation. Although living organisms are composed of cells, actual genomic and proteomic data have not yet led to a satisfactory model of working cell in silico. We have set out to devise a user-friendly generic platform, GemCell, for Generic Executable Modeling of Cells, based on whole, functioning cells. Starting with the cell simplifies life, because all cells expresses essentially five generic types of behavior: replication, death, movement (including change of shape and adherence), export (secretion, signaling, etc.) and import (receiving signals, metabolites, phagocytosis, etc.). The details of these behaviors are specified in GemCell for particular kinds of cells as part of a database of biological specifics (the DBS), which specifies the cell properties and functions that depend on the cell’s history, state, environment, etc. The DBS is designed in an intuitive fashion, so users are able to easily insert their data of interest. The generic part of GemCell, built using Statecharts, is a fully dynamic model of a cell, its interactions with the environment and its resulting behavior, individually and collectively. Model specificity emerges from the DBS, so that model execution is carried out by the statecharts executing with the aid of specific data extracted from the DBS dynamically. Our long term goal is for GemCell to serve as a broadly applicable platform for biological modeling and analysis, supporting user-friendly in silico experimentation, animation, discovery of emergent properties, and hypothesis testing, for a wide variety of biological systems.

Modeling natural systems is a complicated task that involves the concurrent behavior of various processes, mechanisms and objects. Here, we describe an approach that we have been taking in our group for several years, whereby the complexity of the problem is reduced by decomposing a natural system into its basic elements, which are then reassembled and combined to form a comprehensive, simulatable model of the system. Our modeling approach allows one to view a natural system at various levels of abstraction, in a way that makes it possible to zoom in and out between levels. Using statecharts, a high level visual formalism, we specify the behavior of the basic elements of each level and compile these into executable code, which is then linked to an animated front-end. At run-time, the concurrent execution of the basic elements is continuously displayed and provides a dynamic description of the system. We illustrate this approach by modeling aspects of three biological systems: development of the mammalian pancreas; the differentiation of T cells in the thymus; and the dynamic architecture of a lymph node. We compared each model's behavior with experimental data and also reproduced genetic experiments in silico. Interestingly, certain behavioral properties that were not explicitly programmed into the model emerge from concurrent execution and correspond well with the experimental observations.

The notion of the immunological homunculus arose from the observations (1) that the healthy adaptive immune system is inclined to respond (T cell reactivity and autoantibodies) to particular sets of body molecules (self-antigens) and (2) that autoimmune diseases are characterized by sets of autoimmune reactivity to some of the very same self-antigens recognized by healthy subjects - with an obvious difference in outcome. I termed this natural autoimmune structuring of the immune system, the immunological homunculus - the immune system's representation of the body. What might be the selective advantage of an immune system expressing patterns of built-in autoimmunity to particular sets of self-molecules? To better characterize the homunculus, we have used informatic tools to study patterns of antibodies to many hundreds of self-molecules arrayed on glass slides - an antigen chip of our design. Results using the antigen chip suggest that the particular self-reactivities comprising the homunculus could serve as a set of biomarkers that help the immune system initiate and regulate the inflammatory processes that maintain the body.

A recent workshop discussed the recognition of multiple distinct ligands by individual T cell and B cell receptors and the implications of this discovery for lymphocyte biology. The workshop recommends general use of the term polyspecificity because it emphasizes two fundamental aspects, the inherent specificity of receptor recognition and the ability to recognize multiple ligands. Many different examples of polyspecificity and the structural mechanisms were discussed, and the group concluded that polyspecificity is a general, inherent feature of TCR and antibody recognition. This review summarizes the relevance of polyspecificity for lymphocyte development, activation and disease processes.

Here I present the idea that the immune system uses a computational strategy to carry out its many functions in protecting and maintaining the body. Along the way, I define the concepts of computation, Turing machines and system states. I attempt to show that reframing our view of the immune system in computational terms is worth our while.

LPS, a molecule produced by Gram-negative bacteria, is known to activate both innate immune cells such as macrophages and adaptive immune B cells via TLR4 signaling. Although TLR4 is also expressed on T cells, LPS was observed not to affect T cell proliferation or cytokine secretion. We now report, however, that LPS can induce human T cells to adhere to fibronectin via TLR4 signaling. This response to LPS was confirmed in mouse T cells; functional TLR4 and MyD88 were required, but T cells from TLR2 knockout mice could respond to LPS. The human T cell response to LPS depended on protein kinase C signaling and involved the phosphorylation of the proline-rich tyrosine kinase (Pyk-2) and p38. LPS also up-regulated the T cell expression of suppressor of cytokine signaling 3, which led to inhibition of T cell chemotaxis toward the chemokine stromal cell-derived factor 1α (CXCL12). Thus, LPS, through TLR4 signaling, can affect T cell behavior in inflammation.

Type 1 diabetes mellitus (T1DM) results from a specific autoimmune mediated destruction of the pancreatic beta-cells. PDX-1 induced developmentally redirected liver cells were suggested to restore the ablated pancreatic function in chemically induced diabetes. However, developmentally redirected liver cells, may have acquired along with the desired beta-cell characteristics and functions, also undesired sensitivity to autoimmune attack and therefore may be inefficient in ameliorating T1DM. This study analyzes whether subjects with beta-cell autoimmunity could benefit from Ad-CMV-PDX-1 gene therapy. Using the model of cyclophosphamide-accelerated diabetes in non-obese diabetic (CAD-NOD) mice, we report that recombinant adenovirus mediated PDX-1 gene therapy, ameliorates hyperglycemia in CAD-NOD mice. Our data demonstrate that 43% of the overtly diabetic CAD-NOD mice treated with Ad-CMV-PDX-1 became normoglycemic and maintained a stable body weight. Ectopic PDX-1 expression induced pancreatic gene expression and insulin production in the mice livers. The amelioration of hyperglycemia, in PDX-1 treated diabetic mice was associated with an immune modulation manifested by Th1 to Th2 shift in the autoimmune T-cell response to antigens associated with NOD diabetes. Thus, liver-to-pancreas transdifferentiation ameliorates T1DM in a process which is associated with a concomitant modulation of the autoimmune attack. Our findings suggest a beneficial therapeutic effect of the PDX-1 gene therapy for treating autoimmune type 1 diabetes mellitus (T1DM).

Autoimmune diseases are often marked by autoantibodies binding to self antigens. However, many healthy persons also manifest autoantibodies that bind to self antigens, known as natural autoantibodies. In order to characterize natural autoantibodies present at birth, we used an antigen microarray (antigen chip) to analyze informatically (with clustering algorithms and correlation mapping) the natural IgM, IgA, and IgG autoantibody repertoires present in 10 pairs of sera from healthy mothers and the cords of their newborn babies. These autoantibodies were found to bind to 305 different, mostly self, molecules. We report that in utero, humans develop IgM and IgA autoantibodies to relatively uniform sets of self molecules. The global patterns of maternal IgM autoantibodies significantly diverged from those at birth, although certain reactivities remained common to both maternal and cord samples. Because maternal IgG antibodies (unlike IgM and IgA) cross the placenta, maternal and cord IgG autoantibodies showed essentially identical reactivities. We found that some self antigens that bind cord autoantibodies were among the target self antigens associated with autoimmune diseases later in life. Thus, the obviously benign autoimmunity prevalent at birth may provide the basis for the emergence of some autoimmune diseases relatively prevalent later in life.

Treatment with DiaPep277, a peptide derived from HSP60, has been shown to preserve beta-cell function in non-obese diabetic mouse (NOD) mice and in a trial with newly diagnosed human patients with type 1 diabetes treated over a 10-month period. This article extends the clinical trial observations to a total of 20 months of treatment to determine the safety and the effects of repeated doses of DiaPep277 on endogenous insulin secretion, metabolic control, and exogenous insulin requirements.Thirty-five male patients (aged 16-58) with a basal C-peptide greater than 0.1 nmol/L were assigned to periodic treatment with DiaPep277 (1 mg) or placebo for a 12-month treatment and 18-month observation protocol, later extended to an additional year of treatment. Stimulated C-peptide, HbA1c, and an exogenous insulin dose were the clinical endpoints.At 18 months, stimulated C-peptide concentrations had fallen in the placebo group (p = 0.0005) but were maintained in the DiaPep277 group. The need for exogenous insulin was higher in the placebo group than in the DiaPep277 group. Mean HbA1c concentrations were similar in both groups. After extension of the study, patients continuing treatment with DiaPep277 and those switched from placebo to DiaPep277 manifested a trend towards a greater preservation of beta-cell function compared to patients maintained on or switched to placebo. The safety profile of DiaPep277 was similar between the treatment and placebo groups, and no drug-related adverse events occurred.Periodic treatment of subjects with DiaPep277 over 2 years was safe and associated preservation of endogenous insulin secretion up to 18 months was observed.

To enable microbial colonization of the gut mucosa, the intestinal immune system must not only react to danger signals but also recognize cues that indicate safety. Recognition of safety, paradoxically, is mediated by the same environmental sensors that are involved in signaling danger. Indeed, in addition to their well-established role in inducing inflammation in response to stress signals, pattern recognition receptors and a variety of metabolic sensors also promote gut-microbiota symbiosis by responding to "microbial symbiosis factors", "resolution-associated molecular patterns", markers of energy extraction and other signals indicating the absence of pathogenic infection and tissue damage. Here we focus on how the paradoxical roles of immune receptors and other environmental sensors define the microbiota signature of an individual.