Enabling a systems biology approach to immunology: focus on innate immunity

Transcriptome profiling of immune rejection mechanisms in a porcine vascularized composite allotransplantation model

Background

Vascularized composite allotransplantation (VCA) offers the potential for a biological, functional reconstruction in individuals with limb loss or facial disfigurement. Yet, it faces substantial challenges due to heightened immune rejection rates compared to solid organ transplants. A deep understanding of the genetic and immunological drivers of VCA rejection is essential to improve VCA outcomes.

Methods

Heterotopic porcine hindlimb VCA models were established and followed until reaching the endpoint. Skin and muscle samples were obtained from VCA transplant recipient pigs for histological assessments and RNA sequencing analysis. The rejection groups included recipients with moderate pathological rejection, treated locally with tacrolimus encapsulated in triglycerol-monostearate gel (TGMS-TAC), as well as recipients with severe end-stage rejection presenting evident necrosis. Healthy donor tissue served as controls. Bioinformatics analysis, immunofluorescence, and electron microscopy were utilized to examine gene expression patterns and the expression of immune response markers.

Results

Our comprehensive analyses encompassed differentially expressed genes, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes pathways, spanning various composite tissues including skin and muscle, in comparison to the healthy control group. The analysis revealed a consistency and reproducibility in alignment with the pathological rejection grading. Genes and pathways associated with innate immunity, notably pattern recognition receptors (PRRs), damage-associated molecular patterns (DAMPs), and antigen processing and presentation pathways, exhibited upregulation in the VCA rejection groups compared to the healthy controls. Our investigation identified significant shifts in gene expression related to cytokines, chemokines, complement pathways, and diverse immune cell types, with CD8 T cells and macrophages notably enriched in the VCA rejection tissues. Mechanisms of cell death, such as apoptosis, necroptosis and ferroptosis were observed and coexisted in rejected tissues.

Conclusion

Our study provides insights into the genetic profile of tissue rejection in the porcine VCA model. We comprehensively analyze the molecular landscape of immune rejection mechanisms, from innate immunity activation to critical stages such as antigen recognition, cytotoxic rejection, and cell death. This research advances our understanding of graft rejection mechanisms and offers potential for improving diagnostic and therapeutic strategies to enhance the long-term success of VCA.

Recent trends in next generation immunoinformatics harnessed for universal coronavirus vaccine design

The ongoing pandemic of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has globally devastated public health, the economies of many countries and quality of life universally. The recent emergence of immune-escaped variants and scenario of vaccinated individuals being infected has raised the global concerns about the effectiveness of the current available vaccines in transmission control and disease prevention. Given the high rate mutation of SARS-CoV-2, an efficacious vaccine targeting against multiple variants that contains virus-specific epitopes is desperately needed. An immunoinformatics approach is gaining traction in vaccine design and development due to the significant reduction in time and cost of immunogenicity studies and increasing reliability of the generated results. It can underpin the development of novel therapeutic methods and accelerate the design and production of peptide vaccines for infectious diseases. Structural proteins, particularly spike protein (S), along with other proteins have been studied intensively as promising coronavirus vaccine targets. Numbers of promising online immunological databases, tools and web servers have widely been employed for the design and development of next generation COVID-19 vaccines. This review highlights the role of immunoinformatics in identifying immunogenic peptides as potential vaccine targets, involving databases, and prediction and characterization of epitopes which can be harnessed for designing future coronavirus vaccines.

Analysis of Persian Bioinformatics Research with Topic Modeling

Purpose

As a scientific field, bioinformatics has drawn remarkable attention from various fields, such as information technology, mathematics, and modern biological sciences, in recent years. The topic models originating from the field of natural language processing have become the focus of attention with the rapid accumulation of biological datasets. Thus, this research is aimed at modeling the topic content of the bioinformatics literature presented by Iranian researchers in the Scopus Citation Database. Methodology. This research was a descriptive-exploratory study, and the studied population included 3899 papers indexed in the Scopus database, which had been indexed in this database until March 9, 2022. The topic modeling was then performed on the abstracts and titles of the papers. A combination of LDA and TF-IDF was utilized for topic modeling. Findings. The data analysis with topic modeling resulted in identifying seven main topics "Molecular Modeling," "Gene Expression," "Biomarker," "Coronavirus," "Immunoinformatics," "Cancer Bioinformatics," and "Systems Biology." Moreover, "Systems Biology" and "Coronavirus" had the largest and smallest clusters, respectively.

Conclusion

The present investigation demonstrated an acceptable performance for the LDA algorithm in classifying the topics included in this field. The extracted topic clusters indicated excellent consistency and topic connection with each other.

A transcriptomic analysis of the effects of macrophage polarization and endotoxin tolerance on the response to Salmonella

Salmonella is an intracellular pathogen causing significant morbidity and mortality. Its ability to grow inside macrophages is important to virulence, and is dependent on the activation state of the macrophages. Classically activated M1 macrophages are non-permissive for Salmonella growth, while alternatively activated M2 macrophages are permissive for Salmonella growth. Here we showed that endotoxin-primed macrophages (MEP), such as those associated with sepsis, showed similar levels of Salmonella resistance to M1 macrophages after 2 hr of intracellular infection, but at the 4 hr and 24 hr time points were susceptible like M2 macrophages. To understand this mechanistically, transcriptomic sequencing, RNA-Seq, was performed. This showed that M1 and MEP macrophages that had not been exposed to Salmonella, demonstrated a process termed here as primed activation, in expressing relatively higher levels of particular anti-infective genes and pathways, including the JAK-STAT (Janus kinase-signal transducer and activator of transcription) pathway. In contrast, in M2 macrophages these genes and pathways were largely expressed only in response to infection. Conversely, in response to infection, M1 macrophages, but not MEP macrophages, modulated additional genes known to be associated with susceptibility to Salmonella infection, possibly contributing to the differences in resistance at later time points. Application of the JAK inhibitor Ruxolitinib before infection reduced resistance in M1 macrophages, supporting the importance of early JAK-STAT signalling in M1 resistance to Salmonella.

Mesenchymal Stem Cell-Derived Antimicrobial Peptides as Potential Anti-Neoplastic Agents: New Insight into Anticancer Mechanisms of Stem Cells and Exosomes

Mesenchymal stem cells (MSCs), as adult multipotent cells, possess considerable regenerative and anti-neoplastic effects, from inducing apoptosis in the cancer cells to reducing multidrug resistance that bring them up as an appropriate alternative for cancer treatment. These cells can alter the behavior of cancer cells, the condition of the tumor microenvironment, and the activity of immune cells that result in tumor regression. It has been observed that during inflammatory conditions, a well-known feature of the tumor microenvironment, the MSCs produce and release some molecules called “antimicrobial peptides (AMPs)” with demonstrated anti-neoplastic effects. These peptides have remarkable targeted anticancer effects by attaching to the negatively charged membrane of neoplastic cells, disrupting the membrane, and interfering with intracellular pathways. Therefore, AMPs could be considered as a part of the wide-ranging anti-neoplastic effects of MSCs. This review focuses on the possible anti-neoplastic effects of MSCs-derived AMPs and their mechanisms. It also discusses preconditioning approaches and using exosomes to enhance AMP production and delivery from MSCs to cancer cells. Besides, the clinical administration of MSCs-derived AMPs, along with their challenges in clinical practice, were debated.

Computational Immune Proteomics Approach to Target COVID-19

Progress of the omics platforms widens their application to diverse fields, including immunology. This enables a deeper level of knowledge and the provision of a huge amount of data for which management and fruitful integration with the past evidence requires a steadily growing computational effort. In light of this, immunoinformatics emerges as a new discipline placed in between the traditional lab-based investigations and the computational analysis of the biological data. Immunoinformatics make use of tailored bioinformatics tools and data repositories to facilitate the analysis of data from a plurality of disciplines and help drive novel research hypotheses and in silico screening investigations in a fast, reliable, and cost-effective manner. Such computational immunoproteomics studies may as well prepare and guide lab-based investigations, representing valuable technology for the investigation of novel pathogens, to tentatively evaluate specificity of diagnostic products, to forecast on potential adverse effects of vaccines and to reduce the use of animal models. The present manuscript provides an overview of the COVID-19 pandemic and reviews the state of the art of the omics technologies employed in fighting SARS-CoV-2 infections. A comprehensive description of the immunoinformatics approaches and its potential role in contrasting COVID-19 pandemics is provided.

Elucidating host-microbe interactions in vivo by studying population dynamics using neutral genetic tags

Host–microbe interactions are highly dynamic in space and time, in particular in the case of infections. Pathogen population sizes, microbial phenotypes and the nature of the host responses often change dramatically over time. These features pose particular challenges when deciphering the underlying mechanisms of these interactions experimentally, as traditional microbiological and immunological methods mostly provide snapshots of population sizes or sparse time series. Recent approaches – combining experiments using neutral genetic tags with stochastic population dynamic models – allow more precise quantification of biologically relevant parameters that govern the interaction between microbe and host cell populations. This is accomplished by exploiting the patterns of change of tag composition in the microbe or host cell population under study. These models can be used to predict the effects of immunodeficiencies or therapies (e.g. antibiotic treatment) on populations and thereby generate hypotheses and refine experimental designs. In this review, we present tools to study population dynamics in vivo using genetic tags, explain examples for their implementation and briefly discuss future applications.

Systems Biology Approaches to Understanding the Human Immune System

Systems biology is an approach to interrogate complex biological systems through large-scale quantification of numerous biomolecules. The immune system involves >1,500 genes/proteins in many interconnected pathways and processes, and a systems-level approach is critical in broadening our understanding of the immune response to vaccination. Changes in molecular pathways can be detected using high-throughput omics datasets (e.g., transcriptomics, proteomics, and metabolomics) by using methods such as pathway enrichment, network analysis, machine learning, etc. Importantly, integration of multiple omic datasets is becoming key to revealing novel biological insights. In this perspective article, we highlight the use of protein-protein interaction (PPI) networks as a multi-omics integration approach to unravel information flow and mechanisms during complex biological events, with a focus on the immune system. This involves a combination of tools, including: InnateDB, a database of curated interactions between genes and protein products involved in the innate immunity; NetworkAnalyst, a visualization and analysis platform for InnateDB interactions; and MetaBridge, a tool to integrate metabolite data into PPI networks. The application of these systems techniques is demonstrated for a variety of biological questions, including: the developmental trajectory of neonates during the first week of life, mechanisms in host-pathogen interaction, disease prognosis, biomarker discovery, and drug discovery and repurposing. Overall, systems biology analyses of omics data have been applied to a variety of immunology-related questions, and here we demonstrate the numerous ways in which PPI network analysis can be a powerful tool in contributing to our understanding of the immune system and the study of vaccines.

Effects of cannabis oil extract on immune response gene expression in human small airway epithelial cells (HSAEpC): implications for chronic obstructive pulmonary disease (COPD)

Background

Chronic obstructive pulmonary disease (COPD) is commonly associated with both a pro-inflammatory and a T-helper 1 (Th1) immune response. It was hypothesized that cannabis oil extract can alleviate COPD symptoms by eliciting an anti-inflammatory Th2 immune response. Accordingly, the effects of cannabis oil extract on the expression of 84 Th2 and related immune response genes in human small airways epithelial cells (HSAEpC) were investigated.

Methods

HSAEpC from a single donor were treated with three dilutions of a standardized cannabis oil extract (1:400, 1:800 and 1:1600) along with a solvent control (0.25% [2.5 ul/ml] ethanol) for 24 h. There were four replicates per treatment dilution, and six for the control. RNA isolated from cells were employed in pathway-focused quantitative polymerase chain reaction (qPCR) microarray assays.

Results

The extract induced significant (P < 0.05) changes in expression of 37 tested genes. Six genes (CSF2, IL1RL1, IL4, IL13RA2, IL17A and PPARG) were up-regulated at all three dilutions. Another two (CCL22 and TSLP) were up-regulated while six (CLCA1, CMA1, EPX, LTB4R, MAF and PMCH) were down-regulated at the 1:400 and 1:800 dilutions. The relationship of differentially-expressed genes of interest to biologic pathways was explored using the Database for Annotation, Visualization and Integrated Discovery (DAVID).

Conclusions

This exploratory investigation indicates that cannabis oil extract may affect expression of specific airway epithelial cell genes that could modulate pro-inflammatory or Th1 processes in COPD. These results provide a basis for further investigations and have prompted in vivo studies of the effects of cannabis oil extract on pulmonary function.

Trial registration

NONE (all in vitro experiments).

Coordinated Activity of Transcriptional Networks Responding to the Pattern of Action Potential Firing in Neurons

Transcriptional responses to the appropriate temporal pattern of action potential firing are essential for long-term adaption of neuronal properties to the functional activity of neural circuits and environmental experience. However, standard transcriptome analysis methods can be too limited in identifying critical aspects that coordinate temporal coding of action potential firing with transcriptome response. A Pearson correlation analysis was applied to determine how pairs of genes in the mouse dorsal root ganglion (DRG) neurons are coordinately expressed in response to stimulation producing the same number of action potentials by two different temporal patterns. Analysis of 4728 distinct gene-pairs related to calcium signaling, 435,711 pairs of transcription factors, 820 pairs of voltage-gated ion channels, and 86,862 pairs of calcium signaling genes with transcription factors indicated that genes become coordinately activated by distinct action potential firing patterns and this depends on the duration of stimulation. Moreover, a measure of expression variance revealed that the control of transcripts abundances is sensitive to the pattern of stimulation. Thus, action potentials impact intracellular signaling and the transcriptome in dynamic manner that not only alter gene expression levels significantly (as previously reported) but also affects the control of their expression fluctuations and profoundly remodel the transcriptional networks.

PBMCs transcriptome profiles identified breed-specific transcriptome signatures for PRRSV vaccination in German Landrace and Pietrain pigs

Porcine reproductive and respiratory syndrome (PRRS) is a devastating viral disease affecting the swine industry worldwide. Genetic variation in host immunity has been considered as one of the potential determinants to improve the immunocompetence, thereby resistance to PRRS. Therefore, the present study aimed to investigate the breed difference in innate immune response to PRRSV vaccination between German Landrace (DL) and Pietrain (Pi) pigs. We analyzed microarray-based transcriptome profiles of peripheral blood mononuclear cells (PBMCs) collected before (0 h) and 24 h after PRRSV vaccination from purebred DL and Pi pigs with three biological replicates. In total 4,269 transcripts were identified to be differentially expressed in PBMCs in at least any of four tested contrast pairs (i.e. DL-24h vs. DL-0h, Pi-24h vs. Pi-0h, DL-0h vs. Pi-0h and DL-24h vs. Pi-24h). The number of vaccine-induced differentially expressed genes (DEGs) was much higher (2,459) in DL pigs than that of Pi pigs (291). After 24 h of PRRSV vaccination, 1,046 genes were differentially expressed in PMBCs of DL pigs compared to that of Pi (DL-24h vs. Pi-24h), indicating the breed differences in vaccine responsiveness. The top biological pathways significantly affected by DEGs of both breeds were linked to immune response functions. The network enrichment analysis identified ADAM17, STAT1, MMS19, RPA2, BAD, UCHL5 and APC as potential regulatory genes for the functional network of PRRSV vaccine response specific for DL; while FOXO3, IRF2, ADRBK1, FHL3, PPP2CB and NCOA6 were found to be the most potential hubs of Pi specific transcriptome network. In conclusion, our data provided insights of breed-specific host transcriptome responses to PRRSV vaccination which might contribute in better understanding of PPRS resistance in pigs.

Epitope Prediction by Novel Immunoinformatics Approach: A State-of-the-art Review

Immunoinformatics is a science that helps to create significant immunological information using bioinformatics softwares and applications. One of the most important applications of immunoinformatics is the prediction of a variety of specific epitopes for B cell recognition and T cell through MHC class I and II molecules. This method reduces costs and time compared to laboratory tests. In this state-of-the-art review, we review about 50 papers to find the latest and most used immunoinformatic tools as well as their applications for predicting the viral, bacterial and tumoral structural and linear epitopes of B and T cells. In the clinic, the main application of prediction of epitopes is for designing peptide-based vaccines. Peptide-based vaccines are a considerably potential alternative to low-cost vaccines that may reduce the risks related to the production of common vaccines.

Landscape of innate immune system transcriptome and acute T cell-mediated rejection of human kidney allografts

Acute rejection of human allografts has been viewed mostly through the lens of adaptive immunity, and the intragraft landscape of innate immunity genes has not been characterized in an unbiased fashion. We performed RNA sequencing of 34 kidney allograft biopsy specimens from 34 adult recipients; 16 were categorized as Banff acute T cell-mediated rejection (TCMR) and 18 as normal. Computational analysis of intragraft mRNA transcriptome identified significantly higher abundance of mRNA for pattern recognition receptors in TCMR compared with normal biopsies, as well as increased expression of mRNAs for cytokines, chemokines, interferons, and caspases. Intragraft levels of calcineurin mRNA were higher in TCMR biopsies, suggesting underimmunosuppression compared with normal biopsies. Cell-type-enrichment analysis revealed higher abundance of dendritic cells and macrophages in TCMR biopsies. Damage-associated molecular patterns, the endogenous ligands for pattern recognition receptors, as well markers of DNA damage were higher in TCMR. mRNA expression patterns supported increased calcium flux and indices of endoplasmic, cellular oxidative, and mitochondrial stress were higher in TCMR. Expression of mRNAs in major metabolic pathways was decreased in TCMR. Our global and unbiased transcriptome profiling identified heightened expression of innate immune system genes during an episode of TCMR in human kidney allografts.

Transcriptome Modifications in Porcine Adipocytes via Toll-Like Receptors Activation

Adipocytes are the most important cell type in adipose tissue playing key roles in immunometabolism. We previously reported that nine members of the Toll-like receptor (TLR) family are expressed in an originally established porcine intramuscular pre-adipocyte (PPI) cell line. However, the ability of TLR ligands to modulate immunometabolic transcriptome modifications in porcine adipocytes has not been elucidated. Herein, we characterized the global transcriptome modifications in porcine intramuscular mature adipocytes (pMA), differentiated from PPI, following stimulation with Pam3csk4, Poly(I:C) or LPS which are ligands for TLR2, TLR3, and TLR4, respectively. Analysis of microarray data identified 530 (218 up, 312 down), 520 (245 up, 275 down), and 525 (239 up, 286 down) differentially expressed genes (DEGs) in pMA following the stimulation with Pam3csk4, Poly(I:C), and LPS, respectively. Gene ontology classification revealed that DEGs are involved in several biological processes including those belonging to immune response and lipid metabolism pathways. Functionally annotated genes were organized into two groups for downstream analysis: immune response related genes (cytokines, chemokines, complement factors, adhesion molecules, and signal transduction), and genes involved with metabolic and endocrine functions (hormones and receptors, growth factors, and lipid biosynthesis). Differential expression analysis revealed that EGR1, NOTCH1, NOS2, TNFAIP3, TRAF3IP1, INSR, CXCR4, PPARA, MAPK10, and C3 are the top 10 commonly altered genes of TLRs induced transcriptional modification of pMA. However, the protein-protein interaction network of DEGs identified EPOR, C3, STAR, CCL2, and SAA2 as the major hub genes, which were also exhibited higher centrality estimates in the Gene-Transcription factor interaction network. Our results provide new insights of transcriptome modifications associated with TLRs activation in porcine adipocytes and identified key regulatory genes that could be used as biomarkers for the evaluation of treatments having immunomodularoty and/or metabolic functional beneficial effects in porcine adipocytes.

Metabolic regulation protects mice against Klebsiella pneumoniae lung infection

PURPOSE

Klebsiella pneumoniae-caused pneumonia is a risk factor for development of lung injury. However, the current clinical isolates of K. pneumoniae are mostly multidrug-resistance and thus must be addressed with new treatments. One ideal approach is to enhance the innate immunity of the infected host through metabolic modulators.

MATERIALS AND METHODS

We used GC/MS-based metabolomics to profile the metabolomes among Control, Dead and Survival groups. The key metabolites were administrated in mice, and the bacterial loads in lung and survival were measured. The effect of the key metabolites on macrophage phagocytosis was determined by flow cytometry.

RESULTS

Compared with the mice that compromised from K. pneumoniae lung infection, mice that survived the infection displayed the varied metabolomic profile. The differential analysis of metabolome showed D-Glucose, Glutamine, L-Serine, Myo-inositol, Ethanedioic acid and Lactic acid related to the host surviving a K. pneumoniae lung infection. Further pathway enrichment analysis proposed that valine, leucine and isoleucine biosynthesis involved in outcome of lung infection. The follow-up data showed that exogenous L-Serine, L-Valine and L-Leucine could decline the load of K. pneumoniae in infected lung and increases the mouse survival. More interestingly, L-Serine, L-Valine and L-Leucine also were able to promote macrophage phagocytosis that is the natural way to promote hosts to clear lung pathogens.

CONCLUSIONS

Our study establishes a novel strategy of identifying metabolic modulator from surviving host and emphasizes the feasibility of employing the metabolic modulator as a therapy for K. pneumoniae lung infection.

Systems-synthetic biology in understanding the complexities and simple devices in immunology

Systems and synthetic biology in the coming era has the ability to manipulate, stimulate and engineer cells to counteract the pathogenic immune response. The inherent biological complexities associated with the creation of a device allow capitalizing the biotechnological resources either by simply administering a recombinant cytokine or just reprogramming the immune cells. The strategy outlined, adopted and discussed may mark the beginning with promising therapeutics based on the principles of synthetic immunology.

PBMC transcriptome profiles identifies potential candidate genes and functional networks controlling the innate and the adaptive immune response to PRRSV vaccine in Pietrain pig

The porcine reproductive and respiratory syndrome (PRRS) is a devastating viral disease affecting swine production, health and welfare throughout the world. A synergistic action of the innate and the adaptive immune system of the host is essential for mounting a durable protective immunity through vaccination. Therefore, the current study aimed to investigate the transcriptome profiles of peripheral blood mononuclear cells (PBMCs) to characterize the innate and the adaptive immune response to PRRS Virus (PRRSV) vaccination in Pietrain pigs. The Affymetrix gene chip porcine gene 1.0 ST array was used for the transcriptome profiling of PBMCs collected at immediately before (D0), at one (D1) and 28 days (D28) post PRRSV vaccination with three biological replications. With FDR <0.05 and log2 fold change ±1.5 as cutoff criteria, 295 and 115 transcripts were found to be differentially expressed in PBMCs during the stage of innate and adaptive response, respectively. The microarray expression results were technically validated by qRT-PCR. The gene ontology terms such as viral life cycle, regulation of lymphocyte activation, cytokine activity and inflammatory response were enriched during the innate immunity; cytolysis, T cell mediated cytotoxicity, immunoglobulin production were enriched during adaptive immunity to PRRSV vaccination. Significant enrichment of cytokine-cytokine receptor interaction, signaling by interleukins, signaling by the B cell receptor (BCR), viral mRNA translation, IFN-gamma pathway and AP-1 transcription factor network pathways were indicating the involvement of altered genes in the antiviral defense. Network analysis revealed that four network modules were functionally involved with the transcriptional network of innate immunity, and five modules were linked to adaptive immunity in PBMCs. The innate immune transcriptional network was found to be regulated by LCK, STAT3, ATP5B, UBB and RSP17. While TGFß1, IL7R, RAD21, SP1 and GZMB are likely to be predictive for the adaptive immune transcriptional response to PRRSV vaccine in PBMCs. Results of the current immunogenomics study advances our understanding of PRRS in term of host-vaccine interaction, and thereby contribute to design a rationale for disease control strategy.

Stress responses sculpt the insect immune system, optimizing defense in an ever-changing world

A whole organism, network approach can help explain the adaptive purpose of stress-induced changes in immune function. In insects, mediators of the stress response (e.g. stress hormones) divert molecular resources away from immune function and towards tissues necessary for fight-or-flight behaviours. For example, molecules such as lipid transport proteins are involved in both the stress and immune responses, leading to a reduction in disease resistance when these proteins are shifted towards being part of the stress response system. Stress responses also alter immune system strategies (i.e. reconfiguration) to compensate for resource losses that occur during fight-or flight events. In addition, stress responses optimize immune function for different physiological conditions. In insects, the stress response induces a pro-inflammatory state that probably enhances early immune responses.

Contribution of Mass Spectrometry-Based Proteomics to the Understanding of TNF-α Signaling

NF-κB is a family of ubiquitous dimeric transcription factors that play a role in a myriad of cellular processes, ranging from differentiation to stress response and immunity. In inflammation, activation of NF-κB is mediated by pro-inflammatory cytokines, in particular the prototypic cytokines IL-1β and TNF-α, which trigger the activation of complex signaling cascades. In spite of decades of research, the system level understanding of TNF-α signaling is still incomplete. This is partially due to the limited knowledge at the proteome level. The objective of this review is to summarize and critically evaluate the current status of the proteomic research on TNF-α signaling. We will discuss the merits and flaws of the existing studies as well as the insights that they have generated into the proteomic landscape and architecture connected to this signaling pathway. Besides delineating past and current trends in TNF-α proteomic research, we will identify research directions and new methodologies that can further contribute to characterize the TNF-α associated proteome in space and time.

Using biological networks to integrate, visualize and analyze genomics data

Network biology is a rapidly developing area of biomedical research and reflects the current view that complex phenotypes, such as disease susceptibility, are not the result of single gene mutations that act in isolation but are rather due to the perturbation of a gene’s network context. Understanding the topology of these molecular interaction networks and identifying the molecules that play central roles in their structure and regulation is a key to understanding complex systems. The falling cost of next-generation sequencing is now enabling researchers to routinely catalogue the molecular components of these networks at a genome-wide scale and over a large number of different conditions. In this review, we describe how to use publicly available bioinformatics tools to integrate genome-wide ‘omics’ data into a network of experimentally-supported molecular interactions. In addition, we describe how to visualize and analyze these networks to identify topological features of likely functional relevance, including network hubs, bottlenecks and modules. We show that network biology provides a powerful conceptual approach to integrate and find patterns in genome-wide genomic data but we also discuss the limitations and caveats of these methods, of which researchers adopting these methods must remain aware.

How does our increased understanding of the role of inflammation and innate immunity in acne impact treatment approaches?

A supplement article recently published in the Journal of the European Academy of Dermatology and Venereology by Dréno et al., members of the Global Alliance to Improve Outcomes in Acne group, summarized the data for the emerging concept that inflammation in general and the innate immune system specifically play a central role in the pathogenesis of acne. This review, entitled "Understanding innate immunity and inflammation in acne: implications for management", also discusses the impact of different treatment options on the innate immune response and inflammation. The aim of the present summary is to provide a synopsis of the key points made in the paper, from the members of the Global Alliance, as relevant to the main article within this supplement: "Recent advances in the use of adapalene 0.1%/benzoyl peroxide 2.5% to treat acne patients with moderate to severe acne".

Modeling-Enabled Systems Nutritional Immunology

This review highlights the fundamental role of nutrition in the maintenance of health, the immune response, and disease prevention. Emerging global mechanistic insights in the field of nutritional immunology cannot be gained through reductionist methods alone or by analyzing a single nutrient at a time. We propose to investigate nutritional immunology as a massively interacting system of interconnected multistage and multiscale networks that encompass hidden mechanisms by which nutrition, microbiome, metabolism, genetic predisposition, and the immune system interact to delineate health and disease. The review sets an unconventional path to apply complex science methodologies to nutritional immunology research, discovery, and development through “use cases” centered around the impact of nutrition on the gut microbiome and immune responses. Our systems nutritional immunology analyses, which include modeling and informatics methodologies in combination with pre-clinical and clinical studies, have the potential to discover emerging systems-wide properties at the interface of the immune system, nutrition, microbiome, and metabolism.

Immunity comes first: the effect of parasite genotypes on adaptive immunity and immunization in three-spined sticklebacks

Adaptive immunity in vertebrates can confer increased resistance against invading pathogens upon re-infection. But how specific parasite genotypes affect the temporal transition from innate to adaptive immunity under continual exposure to parasites is poorly understood. Here, we investigated the effects of homologous and heterologous exposures of genetically distinct parasite lineages of the eye fluke Diplostomum pseudospathaceum on gene expression patterns of adaptive immunity in sticklebacks (Gasterosteus aculeatus). Observable differences in gene expression were largely attributable to final exposures while there was no transcription pattern characteristic for a general response to repeated infections with D. pseudospathaceum. None of the final exposure treatments was able to erase the distinct expression patterns resulting from a heterologous pre-exposed fish. Interestingly, heterologous final exposures showed similarities between different treatment groups subjected to homologous pre-exposure. The observed pattern was supported by parasite infection rates and suggests that host immunization was optimized towards an adaptive immune response that favored effectiveness against parasite diversity over specificity.

Integrative Genomics-Based Discovery of Novel Regulators of the Innate Antiviral Response

The RIG-I-like receptor (RLR) pathway is essential for detecting cytosolic viral RNA to trigger the production of type I interferons (IFNα/β) that initiate an innate antiviral response. Through systematic assessment of a wide variety of genomics data, we discovered 10 molecular signatures of known RLR pathway components that collectively predict novel members. We demonstrate that RLR pathway genes, among others, tend to evolve rapidly, interact with viral proteins, contain a limited set of protein domains, are regulated by specific transcription factors, and form a tightly connected interaction network. Using a Bayesian approach to integrate these signatures, we propose likely novel RLR regulators. RNAi knockdown experiments revealed a high prediction accuracy, identifying 94 genes among 187 candidates tested (~50%) that affected viral RNA-induced production of IFNβ. The discovered antiviral regulators may participate in a wide range of processes that highlight the complexity of antiviral defense (e.g. MAP3K11, CDK11B, PSMA3, TRIM14, HSPA9B, CDC37, NUP98, G3BP1), and include uncharacterized factors (DDX17, C6orf58, C16orf57, PKN2, SNW1). Our validated RLR pathway list (http://rlr.cmbi.umcn.nl/), obtained using a combination of integrative genomics and experiments, is a new resource for innate antiviral immunity research.

Genomewide effects of peroxisome proliferator-activated receptor gamma in macrophages and dendritic cells--revealing complexity through systems biology

BACKGROUND

Systems biology approaches have become indispensable tools in biomedical and basic research. These data integrating bioinformatic methods gained prominence after high-throughput technologies became available to investigate complex cellular processes, such as transcriptional regulation and protein-protein interactions, on a scale that had not been studied before. Immunology is one of the medical fields that systems biology impacted profoundly due to the plasticity of cell types involved and the accessibility of a wide range of experimental models.

MATERIALS AND METHODS

In this review, we summarize the most important recent genomewide studies exploring the function of peroxisome proliferator-activated receptor γ in macrophages and dendritic cells. PPARγ ChIP-seq experiments were performed in adipocytes derived from embryonic stem cells to complement the existing data sets and to provide comparators to macrophage data. Finally, lists of regulated genes generated from such experiments were analysed with bioinformatics and system biology approaches.

RESULTS

We show that genomewide studies utilizing high-throughput data acquisition methods made it possible to gain deeper insights into the role of PPARγ in these immune cell types. We also demonstrate that analysis and visualization of data using network-based approaches can be used to identify novel genes and functions regulated by the receptor.

CONCLUSIONS

The example of PPARγ in macrophages and dendritic cells highlights the crucial importance of systems biology approaches in establishing novel cellular functions for long-known signaling pathways.

Current transcriptomics in pig immunity research

Swine performance in the face of disease challenge is becoming progressively more important. To improve the pig’s robustness and resilience against pathogens through selection, a better understanding of the genetic and epigenetic factors in the immune response is required. This review highlights results from the most recent transcriptome research, and the meta-analyses performed, in the context of pig immunity. A technological overview is given including wholegenome microarrays, immune-specific arrays, small-scale high-throughput expression methods, high-density tiling arrays, and next generation sequencing (NGS). Although whole genome microarray techniques will remain complementary to NGS for some time in domestic species, research will transition to sequencing-based methods due to cost-effectiveness and the extra information that such methods provide. Furthermore, upcoming high-throughput epigenomic studies, which will add greatly to our knowledge concerning the impact of epigenetic modifications on pig immune response, are listed in this review. With emphasis on the insights obtained from transcriptomic analyses for porcine immunity, we also discuss the experimental design in pig immunity research and the value of the newly published porcine genome assembly in using the pig as a model for human immune response. We conclude by discussing the importance of establishing community standards to maximize the possibility of integrative computational analyses, such as was clearly beneficial for the human ENCODE project.

A lack of synergy between membrane-permeabilizing cationic antimicrobial peptides and conventional antibiotics

The rapid rise in morbidity and mortality from drug-resistant pathogenic bacteria has generated elevated interest in combination therapy using antimicrobial agents. Antimicrobial peptides (AMPs) are a candidate drug class to advance the development of combination therapies. Although the literature is ambiguous, the generic membrane disrupting activity of AMPs could enable them to synergize with conventional small molecule antibiotics by increasing access to the cell and by triggering membrane damage mediators. We used a novel assay to measure interactions, expressed as fractional inhibitory concentration (FIC), between four conventional antibiotics in combination with four well-characterized, membrane permeabilizing AMPs, against three species of Gram negative and Gram positive bacteria, giving 40 total pair-wise measurements of FIC with statistical uncertainties. We chose a set of AMPs that are known to dramatically disrupt the membranes of both Gram negative and Gram positive bacteria. Yet none of the membrane permeabilizing antimicrobial peptides interacted synergistically with any of the conventional antibiotic drugs in any organism. Large-scale membrane disruption and permeabilization by AMPs is not sufficient to drive them to act synergistically with chemical antibiotics in either Gram negative or Gram positive microbes.

Differential protein network analysis of the immune cell lineage

Recently, the Immunological Genome Project (ImmGen) completed the first phase of the goal to understand the molecular circuitry underlying the immune cell lineage in mice. That milestone resulted in the creation of the most comprehensive collection of gene expression profiles in the immune cell lineage in any model organism of human disease. There is now a requisite to examine this resource using bioinformatics integration with other molecular information, with the aim of gaining deeper insights into the underlying processes that characterize this immune cell lineage. We present here a bioinformatics approach to study differential protein interaction mechanisms across the entire immune cell lineage, achieved using affinity propagation applied to a protein interaction network similarity matrix. We demonstrate that the integration of protein interaction networks with the most comprehensive database of gene expression profiles of the immune cells can be used to generate hypotheses into the underlying mechanisms governing the differentiation and the differential functional activity across the immune cell lineage. This approach may not only serve as a hypothesis engine to derive understanding of differentiation and mechanisms across the immune cell lineage, but also help identify possible immune lineage specific and common lineage mechanism in the cells protein networks.

WITHDRAWN: Systems Biology and Immune Aging

The Publisher regrets that this article is an accidental duplication of anarticle that has already been published, http://dx.doi.org/10.1016/j.imlet.2014.09.009. The duplicate article has therefore been withdrawn.

Computational vaccinology and epitope vaccine design by immunoinformatics

Human immune system includes variety of different cells and molecules correlating with other body systems. These instances complicate the analysis of the system; particularly in postgenomic era by introducing more amount of data, the complexity is increased and necessity of using computational approaches to process and interpret them is more tangible.Immunoinformatics as a subset of bioinformatics is a new approach with variety of tools and databases that facilitate analysis of enormous amount of immunologic data obtained from experimental researches. In addition to directing the insight regarding experiment selections, it helps new thesis design which was not feasible with conventional methods due to the complexity of data. Considering this features immunoinformatics appears to be one of the fields that accelerate the immunological research progression.In this study we discuss advances in genomics and vaccine design and their relevance to the development of effective vaccines furthermore several division of this field and available tools in each item are introduced.

A systems biology approach to the analysis of subset-specific responses to lipopolysaccharide in dendritic cells

Dendritic cells (DCs) are critical for regulating CD4 and CD8 T cell immunity, controlling Th1, Th2, and Th17 commitment, generating inducible Tregs, and mediating tolerance. It is believed that distinct DC subsets have evolved to control these different immune outcomes. However, how DC subsets mount different responses to inflammatory and/or tolerogenic signals in order to accomplish their divergent functions remains unclear. Lipopolysaccharide (LPS) provides an excellent model for investigating responses in closely related splenic DC subsets, as all subsets express the LPS receptor TLR4 and respond to LPS in vitro. However, previous studies of the LPS-induced DC transcriptome have been performed only on mixed DC populations. Moreover, comparisons of the in vivo response of two closely related DC subsets to LPS stimulation have not been reported in the literature to date. We compared the transcriptomes of murine splenic CD8 and CD11b DC subsets after in vivo LPS stimulation, using RNA-Seq and systems biology approaches. We identified subset-specific gene signatures, which included multiple functional immune mediators unique to each subset. To explain the observed subset-specific differences, we used a network analysis approach. While both DC subsets used a conserved set of transcription factors and major signalling pathways, the subsets showed differential regulation of sets of genes that ‘fine-tune’ the network Hubs expressed in common. We propose a model in which signalling through common pathway components is ‘fine-tuned’ by transcriptional control of subset-specific modulators, thus allowing for distinct functional outcomes in closely related DC subsets. We extend this analysis to comparable datasets from the literature and confirm that our model can account for cell subset-specific responses to LPS stimulation in multiple subpopulations in mouse and man.

Genetic associations with micronutrient levels identified in immune and gastrointestinal networks

The discovery of vitamins and clarification of their role in preventing frank essential nutrient deficiencies occurred in the early 1900s. Much vitamin research has understandably focused on public health and the effects of single nutrients to alleviate acute conditions. The physiological processes for maintaining health, however, are complex systems that depend upon interactions between multiple nutrients, environmental factors, and genetic makeup. To analyze the relationship between these factors and nutritional health, data were obtained from an observational, community-based participatory research program of children and teens (age 6–14) enrolled in a summer day camp in the Delta region of Arkansas. Assessments of erythrocyte S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH), plasma homocysteine (Hcy) and 6 organic micronutrients (retinol, 25-hydroxy vitamin D3, pyridoxal, thiamin, riboflavin, and vitamin E), and 1,129 plasma proteins were performed at 3 time points in each of 2 years. Genetic makeup was analyzed with 1 M SNP genotyping arrays, and nutrient status was assessed with 24-h dietary intake questionnaires. A pattern of metabolites (met_PC1) that included the ratio of erythrocyte SAM/SAH, Hcy, and 5 vitamins were identified by principal component analysis. Met_PC1 levels were significantly associated with (1) single-nucleotide polymorphisms, (2) levels of plasma proteins, and (3) multilocus genotypes coding for gastrointestinal and immune functions, as identified in a global network of metabolic/protein–protein interactions. Subsequent mining of data from curated pathway, network, and genome-wide association studies identified genetic and functional relationships that may be explained by gene–nutrient interactions. The systems nutrition strategy described here has thus associated a multivariate metabolite pattern in blood with genes involved in immune and gastrointestinal functions.

Barriers to the effective treatment of sepsis: antimicrobial agents, sepsis definitions, and host-directed therapies

Sepsis is a complex clinical syndrome involving both infection and a deleterious host immune response. Antimicrobial agents are key elements of sepsis treatment, yet despite great strides in antimicrobial development in the last decades, sepsis continues to be associated with unacceptably high mortality (~30%). This is the result, on one hand, of the rise of antimicrobial resistant organisms and, on the other hand, of the dearth of effective host-directed immune therapies. A major obstacle to the development of good host-directed therapies is the lack of understanding of the host immune response. The problem is exacerbated by poor nonspecific clinical definitions of disease. Poor definitions have had a profound impact on sepsis research, from epidemiologic studies to the failed clinical trials of host-directed therapies. Therefore, better definitions must be developed to enable advancement in the field.

Protein biomarkers of periodontitis in saliva

Periodontitis is a chronic inflammatory condition of the tissues that surround and support the teeth and is initiated by inappropriate and excessive immune responses to bacteria in subgingival dental plaque leading to loss of the integrity of the periodontium, compromised tooth function, and eventually tooth loss. Periodontitis is an economically important disease as it is time-consuming and expensive to treat. Periodontitis has a worldwide prevalence of 5-15% and the prevalence of severe disease in western populations has increased in recent decades. Furthermore, periodontitis is more common in smokers, in obesity, in people with diabetes, and in heart disease patients although the pathogenic processes underpinning these links are, as yet, poorly understood. Diagnosis and monitoring of periodontitis rely on traditional clinical examinations which are inadequate to predict patient susceptibility, disease activity, and response to treatment. Studies of the immunopathogenesis of periodontitis and analysis of mediators in saliva have allowed the identification of many potentially useful biomarkers. Convenient measurement of these biomarkers using chairside analytical devices could form the basis for diagnostic tests which will aid the clinician and the patient in periodontitis management; this review will summarise this field and will identify the experimental, technical, and clinical issues that remain to be addressed before such tests can be implemented.

A systems biological approach reveals multiple crosstalk mechanism between gram-positive and negative bacterial infections: an insight into core mechanism and unique molecular signatures

Background

Bacterial infections remain a major threat and a leading cause of death worldwide. Most of the bacterial infections are caused by gram-positive and negative bacteria, which are recognized by Toll-like receptor (TLR) 2 and 4, respectively. Activation of these TLRs initiates multiple pathways that subsequently lead to effective immune response. Although, both the TLRs share common signaling mechanism yet they may exhibit specificity as well, resulting in the release of diverse range of inflammatory mediators which could be used as candidate biomolecules for bacterial infections.

Results

We adopted systems biological approach to identify signaling pathways mediated by TLRs to determine candidate molecules associated with bacterial infections. We used bioinformatics concepts, including literature mining to construct protein-protein interaction network, prioritization of TLRs specific nodes using microarray data and pathway analysis. Our constructed PPI network for TLR 2 (nodes: 4091 and edges: 66068) and TLR 4 (node: 4076 and edges: 67898) showed 3207 common nodes, indicating that both the TLRs might share similar signaling events that are attributed to cell migration, MAPK pathway and several inflammatory cascades. Our results propose the potential collaboration between the shared signaling pathways of both the receptors may enhance the immune response against invading pathogens. Further, to identify candidate molecules, the TLRs specific nodes were prioritized using microarray differential expressed genes. Of the top prioritized TLR 2 molecules, 70% were co-expressed. A similar trend was also observed within TLR 4 nodes. Further, most of these molecules were preferentially found in blood plasma for feasible diagnosis.

Conclusions

The analysis reveals the common and unique mechanism regulated by both the TLRs that provide a broad perspective of signaling events in bacterial infections. Further, the identified candidate biomolecules could potentially aid future research efforts concerning the possibility in differential diagnosis of gram-positive and negative bacterial infections.

Human genome-wide RNAi screen identifies an essential role for inositol pyrophosphates in Type-I interferon response

The pattern recognition receptor RIG-I is critical for Type-I interferon production. However, the global regulation of RIG-I signaling is only partially understood. Using a human genome-wide RNAi-screen, we identified 226 novel regulatory proteins of RIG-I mediated interferon-β production. Furthermore, the screen identified a metabolic pathway that synthesizes the inositol pyrophosphate 1-IP7 as a previously unrecognized positive regulator of interferon production. Detailed genetic and biochemical experiments demonstrated that the kinase activities of IPPK, PPIP5K1 and PPIP5K2 (which convert IP5 to1-IP7) were critical for both interferon induction, and the control of cellular infection by Sendai and influenza A viruses. Conversely, ectopically expressed inositol pyrophosphate-hydrolases DIPPs attenuated interferon transcription. Mechanistic experiments in intact cells revealed that the expression of IPPK, PPIP5K1 and PPIP5K2 was needed for the phosphorylation and activation of IRF3, a transcription factor for interferon. The addition of purified individual inositol pyrophosphates to a cell free reconstituted RIG-I signaling assay further identified 1-IP7 as an essential component required for IRF3 activation. The inositol pyrophosphate may act by β-phosphoryl transfer, since its action was not recapitulated by a synthetic phosphonoacetate analogue of 1-IP7. This study thus identified several novel regulators of RIG-I, and a new role for inositol pyrophosphates in augmenting innate immune responses to viral infection that may have therapeutic applications.

The innate immune system is critical for viral infection control by host organisms. The type I interferons are a family of major antiviral cytokines produced upon the activation of innate immune pattern recognition receptors (PRRs) by viruses. The RIG-I is a major PRR that uniquely detects RNA viruses within the cytoplasm. In this study, we aimed to discover cellular genes and pathways that play regulatory roles in the transcriptional induction of type I interferon-β (IFNβ). Using a human genome wide RNA interference (RNAi) screening, we identified 226 genes whose expression is important for proper IFNβ production. Through bioinformatics-based mining of the RNAi screen results, we identified that the cellular pathway synthesizing inositol pyrophosphates, a class of inositol phosphates with high-energy diphosphates, is a key positive regulator of RIG-I mediated IFNβ production. The kinases IPPK, PPIP5K1 and PPIP5K2, that synthesize inositol pyrophosphate 1-IP7, regulated IFNβ response in a catalytically dependent manner. Mechanistic studies identified that 1-IP7 synthesis pathway was needed for efficient phosphorylation of IRF3. The DIPP family of inositol pyrophosphate hydrolases negatively regulated the IFNβ response, upon ectopic expression. In summary, this study generated a global view of the regulation of RIG-I signaling, and identified inositol pyrophosphates as important regulators of antiviral response.

The role of low-grade inflammation and metabolic flexibility in aging and nutritional modulation thereof: a systems biology approach

Aging is a biological process characterized by the progressive functional decline of many interrelated physiological systems. In particular, aging is associated with the development of a systemic state of low-grade chronic inflammation (inflammaging), and with progressive deterioration of metabolic function. Systems biology has helped in identifying the mediators and pathways involved in these phenomena, mainly through the application of high-throughput screening methods, valued for their molecular comprehensiveness. Nevertheless, inflammation and metabolic regulation are dynamical processes whose behavior must be understood at multiple levels of biological organization (molecular, cellular, organ, and system levels) and on multiple time scales. Mathematical modeling of such behavior, with incorporation of mechanistic knowledge on interactions between inflammatory and metabolic mediators, may help in devising nutritional interventions capable of preventing, or ameliorating, the age-associated functional decline of the corresponding systems.

Consensus statement understanding health and malnutrition through a systems approach: the ENOUGH program for early life

Nutrition research, like most biomedical disciplines, adopted and often uses experimental approaches based on Beadle and Tatum's one gene-one polypeptide hypothesis, thereby reducing biological processes to single reactions or pathways. Systems thinking is needed to understand the complexity of health and disease processes requiring measurements of physiological processes, as well as environmental and social factors, which may alter the expression of genetic information. Analysis of physiological processes with omics technologies to assess systems' responses has only become available over the past decade and remains costly. Studies of environmental and social conditions known to alter health are often not connected to biomedical research. While these facts are widely accepted, developing and conducting comprehensive research programs for health are often beyond financial and human resources of single research groups. We propose a new research program on essential nutrients for optimal underpinning of growth and health (ENOUGH) that will use systems approaches with more comprehensive measurements and biostatistical analysis of the many biological and environmental factors that influence undernutrition. Creating a knowledge base for nutrition and health is a necessary first step toward developing solutions targeted to different populations in diverse social and physical environments for the two billion undernourished people in developed and developing economies.

Immunoinformatics: a brief review

A large volume of data relevant to immunology research has accumulated due to sequencing of genomes of the human and other model organisms. At the same time, huge amounts of clinical and epidemiologic data are being deposited in various scientific literature and clinical records. This accumulation of the information is like a goldmine for researchers looking for mechanisms of immune function and disease pathogenesis. Thus the need to handle this rapidly growing immunological resource has given rise to the field known as immunoinformatics. Immunoinformatics, otherwise known as computational immunology, is the interface between computer science and experimental immunology. It represents the use of computational methods and resources for the understanding of immunological information. It not only helps in dealing with huge amount of data but also plays a great role in defining new hypotheses related to immune responses. This chapter reviews classical immunology, different databases, and prediction tool. Further, it briefly describes applications of immunoinformatics in reverse vaccinology, immune system modeling, and cancer diagnosis and therapy. It also explores the idea of integrating immunoinformatics with systems biology for the development of personalized medicine. All these efforts save time and cost to a great extent.

Proteomic characterization of the hemolymph of Octopus vulgaris infected by the protozoan parasite Aggregata octopiana

The immune system of cephalopods is poorly known to date. The lack of genomic information makes difficult to understand vital processes like immune defense mechanisms and their interaction with pathogens at molecular level. The common octopus Octopus vulgaris has a high economic relevance and potential for aquaculture. However, disease outbreaks provoke serious reductions in production with potentially severe economic losses. In this study, a proteomic approach is used to analyze the immune response of O. vulgaris against the coccidia Aggregata octopiana, a gastrointestinal parasite which impairs the cephalopod nutritional status. The hemocytes and plasma proteomes were compared by 2-DE between sick and healthy octopus. The identities of 12 differentially expressed spots and other 27 spots without significant alteration from hemocytes, and 5 spots from plasma, were determined by mass spectrometry analysis aided by a six reading-frame translation of an octopus hemocyte RNA-seq database and also public databases. Principal component analysis pointed to 7 proteins from hemocytes as the major contributors to the overall difference between levels of infection and so could be considered as potential biomarkers. Particularly, filamin, fascin and peroxiredoxin are highlighted because of their implication in octopus immune defense activity. From the octopus plasma, hemocyanin was identified. This work represents a first step forward in order to characterize the protein profile of O. vulgaris hemolymph, providing important information for subsequent studies of the octopus immune system at molecular level and also to the understanding of the basis of octopus tolerance-resistance to A. octopiana.

BIOLOGICAL SIGNIFICANCE

The immune system of cephalopods is poorly known to date. The lack of genomic information makes difficult to understand vital processes like immune defense mechanisms and their interaction with pathogens at molecular level. The study herein presented is focused to the comprehension of the octopus immune defense against a parasite infection. Particularly, it is centered in the host-parasite relationship developed between the octopus and the protozoan A. octopiana, which induces severe gastrointestinal injuries in octopus that produce a malabsorption syndrome. The common octopus is a commercially important species with a high potential for aquaculture in semi-open systems, and this pathology reduces the condition of the octopus populations on-growing in open-water systems resulting in important economical loses. This is the first proteomic approach developed on this host-parasite relationship, and therefore, the contribution of this work goes from i) ecological, since this particular relationship is tending to be established as a model of host-parasite interaction in natural populations; ii) evolutionary, due to the characterization of immune molecules that could contribute to understand the functioning of the immune defense in these highly evolved mollusks; and iii) to economical view. The results of this study provide an overview of the octopus hemolymph proteome. Furthermore, proteins influenced by the level of infection and implicated in the octopus cellular response are also showed. Consequently, a set of biomarkers for disease resistance is suggested for further research that could be valuable for the improvement of the octopus culture, taken into account their high economical value, the declining of landings and the need for the diversification of reared species in order to ensure the growth of the aquaculture activity. Although cephalopods are model species for biomedical studies and possess potential in aquaculture, their genomes have not been sequenced yet, which limits the application of genomic data to research important biological processes. Similarly, the octopus proteome, like other non-model organisms, is poorly represented in public databases. Most of the proteins were identified from an octopus' hemocyte RNA-seq database that we have performed, which will be the object of another manuscript in preparation. Therefore, the need to increase molecular data from non-model organisms is herein highlighted. Particularly, here is encouraged to expand the knowledge of the genomic of cephalopods in order to increase successful protein identifications. This article is part of a Special Issue entitled: Proteomics of non-model organisms.

Systems biology: a biologist's viewpoint

The debate over reductionism and antireductionism in biology is very old. Even the systems approach in biology is more than five decades old. However, mainstream biology, particularly experimental biology, has broadly sidestepped those debates and ideas. Post-genome data explosion and development of high-throughput techniques led to resurfacing of those ideas and debates as a new incarnation called Systems Biology. Though experimental biologists have co-opted systems biology and hailed it as a paradigm shift, it is practiced in different shades and understood with divergent meanings. Biology has certain questions linked with organization of multiple components and processes. Often such questions involve multilevel systems. Here in this essay we argue that systems theory provides required framework and abstractions to explore those questions. We argue that systems biology should follow the logical and mathematical approach of systems theory and transmogrification of systems biology to mere collection of higher dimensional data must be avoided. Therefore, the questions that we ask and the priority of those questions should also change. Systems biology should focus on system-level properties and investigate complexity without shying away from it.

Technical note: proteomic approaches to fundamental questions about neutrophil biology

Proteomics is one of a group of technologies that generates high-throughput, large-scale datasets that can be used to understand cell or organ functions at a systems level. This review will focus on the application of proteomics to the understanding of neutrophil biology. The strengths and weaknesses of common proteomic methods and their application to neutrophils are reviewed, with the goal of evaluating whether the technology is ready to advance our understanding of neutrophil biology.

A global "imaging'' view on systems approaches in immunology

The immune system exhibits an enormous complexity. High throughput methods such as the "-omic'' technologies generate vast amounts of data that facilitate dissection of immunological processes at ever finer resolution. Using high-resolution data-driven systems analysis, causal relationships between complex molecular processes and particular immunological phenotypes can be constructed. However, processes in tissues, organs, and the organism itself (so-called higher level processes) also control and regulate the molecular (lower level) processes. Reverse systems engineering approaches, which focus on the examination of the structure, dynamics and control of the immune system, can help to understand the construction principles of the immune system. Such integrative mechanistic models can properly describe, explain, and predict the behavior of the immune system in health and disease by combining both higher and lower level processes. Moving from molecular and cellular levels to a multiscale systems understanding requires the development of methodologies that integrate data from different biological levels into multiscale mechanistic models. In particular, 3D imaging techniques and 4D modeling of the spatiotemporal dynamics of immune processes within lymphoid tissues are central for such integrative approaches. Both dynamic and global organ imaging technologies will be instrumental in facilitating comprehensive multiscale systems immunology analyses as discussed in this review.

A strategy to study pathway cross-talks of cells under repetitive exposure to stimuli

Background

Cells are subject to fluctuating and multiple stimuli in their natural environment. The signaling pathways often crosstalk to each other and give rise to complex nonlinear dynamics. Specifically repetitive exposure of a cell to a same stimulus sometime leads to augmented cellular responses. Examples are amplified proinflammatory responses of innate immune cells pretreated with a sub-threshold then a high dose of endotoxin or cytokine stimulation. This phenomenon, called priming effect in the literature, has important pathological and clinical significances.

Results

In a previous study, we enumerated possible mechanisms for priming using a three-node network model. The analysis uncovered three mechanisms. Based on the results, in this work we developed a straightforward procedure to identify molecular candidates contributing to the priming effect and the corresponding mechanisms. The procedure involves time course measurements, e.g., gene expression levels, or protein activities under low, high, and low + high dose of stimulant, then computational analysis of the dynamics patterns, and identification of functional roles in the context of the regulatory network. We applied the procedure to a set of published microarray data on interferon-γ-mediated priming effect of human macrophages. The analysis identified a number of network motifs possibly contributing to Interferon-γ priming. A further detailed mathematical model analysis further reveals how combination of different mechanisms leads to the priming effect.

Conclusions

One may perform systematic screening using the proposed procedure combining with high throughput measurements, at both transcriptome and proteome levels. It is applicable to various priming phenomena.