PEPMatch: a tool to identify short peptide sequence matches in large sets of proteins

BACKGROUND

Numerous tools exist for biological sequence comparisons and search. One case of particular interest for immunologists is finding matches for linear peptide T cell epitopes, typically between 8 and 15 residues in length, in a large set of protein sequences. Both to find exact matches or matches that account for residue substitutions. The utility of such tools is critical in applications ranging from identifying conservation across viral epitopes, identifying putative epitope targets for allergens, and finding matches for cancer-associated neoepitopes to examine the role of tolerance in tumor recognition.

RESULTS

We defined a set of benchmarks that reflect the different practical applications of short peptide sequence matching. We evaluated a suite of existing methods for speed and recall and developed a new tool, PEPMatch. The tool uses a deterministic k-mer mapping algorithm that preprocesses proteomes before searching, achieving a 50-fold increase in speed over methods such as the Basic Local Alignment Search Tool (BLAST) without compromising recall. PEPMatch's code and benchmark datasets are publicly available.

CONCLUSIONS

PEPMatch offers significant speed and recall advantages for peptide sequence matching. While it is of immediate utility for immunologists, the developed benchmarking framework also provides a standard against which future tools can be evaluated for improvements. The tool is available at https://nextgen-tools.iedb.org , and the source code can be found at https://github.com/IEDB/PEPMatch .

Coronavirus Immunotherapeutic Consortium Database

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has seen multiple anti-SARS-CoV-2 antibodies being generated globally. It is difficult, however, to assemble a useful compendium of these biological properties if they are derived from experimental measurements performed at different sites under different experimental conditions. The Coronavirus Immunotherapeutic Consortium (COVIC) circumvents these issues by experimentally testing blinded antibodies side by side for several functional activities. To collect these data in a consistent fashion and make it publicly available, we established the COVIC database (COVIC-DB, https://covicdb.lji.org/). This database enables systematic analysis and interpretation of this large-scale dataset by providing a comprehensive view of various features such as affinity, neutralization, in vivo protection and effector functions for each antibody. Interactive graphs enable direct comparisons of antibodies based on select functional properties. We demonstrate how the COVIC-DB can be utilized to examine relationships among antibody features, thereby guiding the design of therapeutic antibody cocktails. Database URL  https://covicdb.lji.org/.

IEDB and CEDAR: Two Sibling Databases to Serve the Global Scientific Community

Various methodologies have been utilized to analyze epitope-specific responses in the context of non-self-antigens, such as those associated with infectious diseases and allergies, and in the context of self-antigens, such as those associated with transplantation, autoimmunity, and cancer. Further to this, epitope-specific data, and its associated immunological context, are crucial to training and developing predictive algorithms and pipelines for the development of specific vaccines and diagnostics. In this chapter, we describe the methodology utilized to derive two sibling resources, the Immune Epitope Database (IEDB) and Cancer Epitope Database and Analysis Resource (CEDAR), to specifically host this data, and make them freely available to the scientific community.

The Cancer Epitope Database and Analysis Resource (CEDAR)

We established The Cancer Epitope Database and Analysis Resource (CEDAR) to catalog all epitope data in the context of cancer. The specific molecular targets of adaptive T cell and B cell immune responses are referred to as epitopes. Epitopes derived from cancer antigens are of high relevance as they are recognized by anti-cancer immune cells. Detailed knowledge of the molecular characteristic of cancer epitopes and associated metadata is relevant to understanding and planning prophylactic and therapeutic applications and accurately characterizing naturally occurring immune responses and cancer immunopathology. CEDAR provides a freely accessible, comprehensive collection of cancer epitope and receptor data curated from the literature and serves as a companion site to the Immune Epitope Database (IEDB), which is focused on infectious, autoimmune, and allergic diseases. CEDAR is freely accessible at https://cedar.iedb.org/.

Phenotypes of disease severity in a cohort of hospitalized COVID-19 patients: Results from the IMPACC study

BACKGROUND

Better understanding of the association between characteristics of patients hospitalized with coronavirus disease 2019 (COVID-19) and outcome is needed to further improve upon patient management.

METHODS

Immunophenotyping Assessment in a COVID-19 Cohort (IMPACC) is a prospective, observational study of 1164 patients from 20 hospitals across the United States. Disease severity was assessed using a 7-point ordinal scale based on degree of respiratory illness. Patients were prospectively surveyed for 1 year after discharge for post-acute sequalae of COVID-19 (PASC) through quarterly surveys. Demographics, comorbidities, radiographic findings, clinical laboratory values, SARS-CoV-2 PCR and serology were captured over a 28-day period. Multivariable logistic regression was performed.

FINDINGS

The median age was 59 years (interquartile range [IQR] 20); 711 (61%) were men; overall mortality was 14%, and 228 (20%) required invasive mechanical ventilation. Unsupervised clustering of ordinal score over time revealed distinct disease course trajectories. Risk factors associated with prolonged hospitalization or death by day 28 included age ≥ 65 years (odds ratio [OR], 2.01; 95% CI 1.28-3.17), Hispanic ethnicity (OR, 1.71; 95% CI 1.13-2.57), elevated baseline creatinine (OR 2.80; 95% CI 1.63- 4.80) or troponin (OR 1.89; 95% 1.03-3.47), baseline lymphopenia (OR 2.19; 95% CI 1.61-2.97), presence of infiltrate by chest imaging (OR 3.16; 95% CI 1.96-5.10), and high SARS-CoV2 viral load (OR 1.53; 95% CI 1.17-2.00). Fatal cases had the lowest ratio of SARS-CoV-2 antibody to viral load levels compared to other trajectories over time (p=0.001). 589 survivors (51%) completed at least one survey at follow-up with 305 (52%) having at least one symptom consistent with PASC, most commonly dyspnea (56% among symptomatic patients). Female sex was the only associated risk factor for PASC.

INTERPRETATION

Integration of PCR cycle threshold, and antibody values with demographics, comorbidities, and laboratory/radiographic findings identified risk factors for 28-day outcome severity, though only female sex was associated with PASC. Longitudinal clinical phenotyping offers important insights, and provides a framework for immunophenotyping for acute and long COVID-19.

FUNDING

NIH.

Towards the prediction of non-peptidic epitopes

In-silico methods for the prediction of epitopes can support and improve workflows for vaccine design, antibody production, and disease therapy. So far, the scope of B cell and T cell epitope prediction has been directed exclusively towards peptidic antigens. Nevertheless, various non-peptidic molecular classes can be recognized by immune cells. These compounds have not been systematically studied yet, and prediction approaches are lacking. The ability to predict the epitope activity of non-peptidic compounds could have vast implications; for example, for immunogenic risk assessment of the vast number of drugs and other xenobiotics. Here we present the first general attempt to predict the epitope activity of non-peptidic compounds using the Immune Epitope Database (IEDB) as a source for positive samples. The molecules stored in the Chemical Entities of Biological Interest (ChEBI) database were chosen as background samples. The molecules were clustered into eight homogeneous molecular groups, and classifiers were built for each cluster with the aim of separating the epitopes from the background. Different molecular feature encoding schemes and machine learning models were compared against each other. For those models where a high performance could be achieved based on simple decision rules, the molecular features were then further investigated. Additionally, the findings were used to build a web server that allows for the immunogenic investigation of non-peptidic molecules (http://tools-staging.iedb.org/np_epitope_predictor). The prediction quality was tested with samples from independent evaluation datasets, and the implemented method received noteworthy Receiver Operating Characteristic-Area Under Curve (ROC-AUC) values, ranging from 0.69–0.96 depending on the molecule cluster.

Small molecules found in cosmetics, foodstuffs, dyes, and industrial materials, but also those produced by plants, bacteria, and animals can trigger strong reactions of the human immune system and can therefore be hazardous to health. In the present work, several thousand immune-reactive small molecules (so-called non-peptidic epitopes) were classified by molecular structure and studied with the aim of identifying specific parts of the molecules responsible for such immune responses. Using a machine-learning approach (random forests and neural networks), we identified some substructures that appear strikingly often in non-peptidic epitopes and which may be responsible for the hazardous immune response. Such knowledge may help to explain allergic reactions to chemicals and also to minimize the health risks of new chemicals in industrial production. To support this endeavor, we have implemented the method in a publicly available web application. This can be used for the prediction and identification of non-peptidic epitopes and their underlying substructures.

Minimal Information about MHC Multimers (MIAMM)

With the goal of improving the reproducibility and annotatability of MHC multimer reagent data, we present the establishment of a new data standard: Minimal Information about MHC Multimers (https://miamm.lji.org/). Multimers are engineered reagents composed of a ligand and a MHC, which can be represented in a standardized format using ontology terminology. We provide an online Web site to host the details of the standard, as well as a validation tool to assist with the adoption of the standard. We hope that this publication will bring increased awareness of Minimal Information about MHC Multimers and drive acceptance, ultimately improving the quality and documentation of multimer data in the scientific literature.

OBO Foundry in 2021: operationalizing open data principles to evaluate ontologies

Biological ontologies are used to organize, curate and interpret the vast quantities of data arising from biological experiments. While this works well when using a single ontology, integrating multiple ontologies can be problematic, as they are developed independently, which can lead to incompatibilities. The Open Biological and Biomedical Ontologies (OBO) Foundry was created to address this by facilitating the development, harmonization, application and sharing of ontologies, guided by a set of overarching principles. One challenge in reaching these goals was that the OBO principles were not originally encoded in a precise fashion, and interpretation was subjective. Here, we show how we have addressed this by formally encoding the OBO principles as operational rules and implementing a suite of automated validation checks and a dashboard for objectively evaluating each ontology’s compliance with each principle. This entailed a substantial effort to curate metadata across all ontologies and to coordinate with individual stakeholders. We have applied these checks across the full OBO suite of ontologies, revealing areas where individual ontologies require changes to conform to our principles. Our work demonstrates how a sizable, federated community can be organized and evaluated on objective criteria that help improve overall quality and interoperability, which is vital for the sustenance of the OBO project and towards the overall goals of making data Findable, Accessible, Interoperable, and Reusable (FAIR).

Database URL http://obofoundry.org/

SARS-CoV-2 human T cell epitopes: Adaptive immune response against COVID-19

Over the past year, numerous studies in the peer reviewed and preprint literature have reported on the virological, epidemiological and clinical characteristics of the coronavirus, SARS-CoV-2. To date, 25 studies have investigated and identified SARS-CoV-2-derived T cell epitopes in humans. Here, we review these recent studies, how they were performed, and their findings. We review how epitopes identified throughout the SARS-CoV2 proteome reveal significant correlation between number of epitopes defined and size of the antigen provenance. We also report additional analysis of SARS-CoV-2 human CD4 and CD8 T cell epitope data compiled from these studies, identifying 1,400 different reported SARS-CoV-2 epitopes and revealing discrete immunodominant regions of the virus and epitopes that are more prevalently recognized. This remarkable breadth of epitope repertoire has implications for vaccine design, cross-reactivity, and immune escape by SARS-CoV-2 variants.

Standardization of assay representation in the Ontology for Biomedical Investigations

The Ontology for Biomedical Investigations (OBI) underwent a focused review of assay term annotations, logic and hierarchy with a goal to improve and standardize these terms. As a result, inconsistencies in W3C Web Ontology Language (OWL) expressions were identified and corrected, and additionally, standardized design patterns and a formalized template to maintain them were developed. We describe here this informative and productive process to describe the specific benefits and obstacles for OBI and the universal lessons for similar projects.

An immunologically friendly classification of non-peptidic ligands

The Immune Epitope Database (IEDB) freely provides experimental data regarding immune epitopes to the scientific public. The main users of the IEDB are immunologists who can easily use our web interface to search for peptidic epitopes via their simple single-letter codes. For example, 'A' stands for 'alanine'. Similarly, users can easily navigate the IEDB's simplified NCBI taxonomy hierarchy to locate proteins from specific organisms. However, some epitopes are non-peptidic, such as carbohydrates, lipids, chemicals and drugs, and it is more challenging to consistently name them and search upon, making access to their data more problematic for immunologists. Therefore, we set out to improve access to non-peptidic epitope data in the IEDB through the simplification of the non-peptidic hierarchy used in our search interfaces. Here, we present these efforts and their outcomes. Database URL:  http://www.iedb.org/.

TCRMatch: Predicting T-Cell Receptor Specificity Based on Sequence Similarity to Previously Characterized Receptors

The adaptive immune system in vertebrates has evolved to recognize non-self antigens, such as proteins expressed by infectious agents and mutated cancer cells. T cells play an important role in antigen recognition by expressing a diverse repertoire of antigen-specific receptors, which bind epitopes to mount targeted immune responses. Recent advances in high-throughput sequencing have enabled the routine generation of T-cell receptor (TCR) repertoire data. Identifying the specific epitopes targeted by different TCRs in these data would be valuable. To accomplish that, we took advantage of the ever-increasing number of TCRs with known epitope specificity curated in the Immune Epitope Database (IEDB) since 2004. We compared seven metrics of sequence similarity to determine their power to predict if two TCRs have the same epitope specificity. We found that a comprehensive k-mer matching approach produced the best results, which we have implemented into TCRMatch, an openly accessible tool (http://tools.iedb.org/tcrmatch/) that takes TCR β-chain CDR3 sequences as an input, identifies TCRs with a match in the IEDB, and reports the specificity of each match. We anticipate that this tool will provide new insights into T cell responses captured in receptor repertoire and single cell sequencing experiments and will facilitate the development of new strategies for monitoring and treatment of infectious, allergic, and autoimmune diseases, as well as cancer.

A behind-the-scenes tour of the IEDB curation process: an optimized process empirically integrating automation and human curation efforts

The Immune Epitope Database and Analysis Resource (IEDB) provides the scientific community with open access to epitope data, as well as epitope prediction and analysis tools. The IEDB houses the most extensive collection of experimentally validated B‐cell and T‐cell epitope data, sourced primarily from published literature by expert curation. The data procurement requires systematic identification, categorization, curation and quality‐checking processes. Here, we provide insights into these processes, with particular focus on the dividends they have paid in terms of attaining project milestones, as well as how objective analyses of our processes have identified opportunities for process optimization. These experiences are shared as a case study of the benefits of process implementation and review in biomedical big data, as well as to encourage idea‐sharing among players in this ever‐growing space.

The Immune Epitope Database (IEDB): 2018 update

The Immune Epitope Database (IEDB, iedb.org) captures experimental data confined in figures, text and tables of the scientific literature, making it freely available and easily searchable to the public. The scope of the IEDB extends across immune epitope data related to all species studied and includes antibody, T cell, and MHC binding contexts associated with infectious, allergic, autoimmune, and transplant related diseases. Having been publicly accessible for >10 years, the recent focus of the IEDB has been improved query and reporting functionality to meet the needs of our users to access and summarize data that continues to grow in quantity and complexity. Here we present an update on our current efforts and future goals.

A structured model for immune exposures

An Immune Exposure is the process by which components of the immune system first encounter a potential trigger. The ability to describe consistently the details of the Immune Exposure process was needed for data resources responsible for housing scientific data related to the immune response. This need was met through the development of a structured model for Immune Exposures. This model was created during curation of the immunology literature, resulting in a robust model capable of meeting the requirements of such data. We present this model with the hope that overlapping projects will adopt and or contribute to this work.

ImmunomeBrowser: a tool to aggregate and visualize complex and heterogeneous epitopes in reference proteins

Motivation

Datasets that are derived from different studies (e.g. MHC ligand elution, MHC binding, B/T cell epitope screening etc.) often vary in terms of experimental approaches, sizes of peptides tested, including partial and or nested overlapping peptides and in the number of donors tested.

Results

We present a customized application of the Immune Epitope Database’s ImmunomeBrowser tool, which can be used to effectively aggregate and visualize heterogeneous immunological data. User provided peptide sets and associated response data is mapped to a user-provided protein reference sequence. The output consists of tables and figures representing the aggregated data represented by a Response Frequency score and associated estimated confidence interval. This allows the user to visualizing regions associated with dominant responses and their boundaries. The results are presented both as a user interactive javascript based web interface and a tabular format in a selected reference sequence.

Availability and implementation

The ‘ImmunomeBrowser’ has been a longstanding feature of the IEDB (http://www.iedb.org). The present application extends the use of this tool to work with user-provided datasets, rather than the output of IEDB queries. This new server version of the ImmunomeBrowser is freely accessible at http://tools.iedb.org/immunomebrowser/.

Identifying antibodies and T-cell receptors with known specificity in repertoire sequencing data

The adaptive immune system in vertebrates has evolved to recognize an immense number of pathogens. B and T cells play important role in the antigen recognition by expressing a substantially diverse repertoire of antigen-specific receptors. The recent advances in the high-throughput immune repertoire sequencing has led to a tremendous increase in the antibody and T-cell receptor information. Identification of specific epitopes recognized by the receptors is vital in analyzing the repertoire sequencing data. Here, we present a tool that examines data from an immune receptor repertoire experiment, and identifies receptors (or highly related variants) that are present in the Immune Epitope Database (IEDB). The IEDB is a free resource which compiles experiments characterizing immune epitopes. IEDB also captures the epitope-specific immune receptor sequences and groups them based on their epitope specificity. IEDB currently has information on over 26,000 receptor groups. Users can provide receptor repertoire sequence data in multiple formats, and specify different CDR sequence identity cutoffs to restrict or broaden the receptor search. We expect that this tool will provide new insights into B and T cell responses captured in the receptor repertoire experiments by identifying specific epitopes, and facilitate development of new strategies for monitoring and treating of infectious, allergic and autoimmune diseases.

The Immune Epitope Database enables and accelerates research

The Immune Epitope Database and Analysis Project (IEDB) is a freely available resource funded by the National Institute of Allergy and Infectious Diseases, to advance immunology research. The database allows easy searching of all published experimental data characterizing antibody and T cell epitopes studied in humans, non-human primates, and other animal species. Epitopes involved in infectious disease, allergy, autoimmunity, and transplant are included. The data were derived from more than 19,000 publications. The IEDB also hosts tools that assist in the prediction and analysis of B cell and T cell epitopes. In recent years, the IEDB has updated its search interface and added highly sought after data, such and antibody and TCR sequence information. We will detail how the IEDB can be used to facilitate immunological research.

Reporting and connecting cell type names and gating definitions through ontologies

Background

Human immunology studies often rely on the isolation and quantification of cell populations from an input sample based on flow cytometry and related techniques. Such techniques classify cells into populations based on the detection of a pattern of markers. The description of the cell populations targeted in such experiments typically have two complementary components: the description of the cell type targeted (e.g. ‘T cells’), and the description of the marker pattern utilized (e.g. CD14−, CD3+).

Results

We here describe our attempts to use ontologies to cross-compare cell types and marker patterns (also referred to as gating definitions). We used a large set of such gating definitions and corresponding cell types submitted by different investigators into ImmPort, a central database for immunology studies, to examine the ability to parse gating definitions using terms from the Protein Ontology (PRO) and cell type descriptions, using the Cell Ontology (CL). We then used logical axioms from CL to detect discrepancies between the two.

Conclusions

We suggest adoption of our proposed format for describing gating and cell type definitions to make comparisons easier. We also suggest a number of new terms to describe gating definitions in flow cytometry that are not based on molecular markers captured in PRO, but on forward- and side-scatter of light during data acquisition, which is more appropriate to capture in the Ontology for Biomedical Investigations (OBI). Finally, our approach results in suggestions on what logical axioms and new cell types could be considered for addition to the Cell Ontology.

Epitope Specific Antibodies and T Cell Receptors in the Immune Epitope Database

The Immune Epitope Database (IEDB) is a free public resource which catalogs experiments characterizing immune epitopes. To accommodate data from next generation repertoire sequencing experiments, we recently updated how we capture and query epitope specific antibodies and T cell receptors. Specifically, we are now storing partial receptor sequences sufficient to determine CDRs and VDJ gene usage which are commonly identified by repertoire sequencing. For previously captured full length receptor sequencing data, we have calculated the corresponding CDR sequences and gene usage information using IMGT numbering and VDJ gene nomenclature format. To integrate information from receptors defined at different levels of resolution, we grouped receptors based on their host species, receptor type and CDR3 sequence. As of August 2018, we have cataloged sequence information for more than 22,510 receptors in 18,292 receptor groups, shown to bind to more than 2,241 distinct epitopes. These data are accessible as full exports and through a new dedicated query interface. The later combines the new ability to search by receptor characteristics with previously existing capability to search by epitope characteristics such as the infectious agent the epitope is derived from, or the kind of immune response involved in its recognition. We expect that this comprehensive capture of epitope specific immune receptor information will provide new insights into receptor-epitope interactions, and facilitate the development of novel tools that help in the analysis of receptor repertoire data.

FAIR principles and the IEDB: short-term improvements and a long-term vision of OBO-foundry mediated machine-actionable interoperability

The Immune Epitope Database (IEDB), at www.iedb.org, has the mission to make published experimental data relating to the recognition of immune epitopes easily available to the scientific public. By presenting curated data in a searchable database, we have liberated it from the tables and figures of journal articles, making it more accessible and usable by immunologists. Recently, the principles of Findability, Accessibility, Interoperability and Reusability have been formulated as goals that data repositories should meet to enhance the usefulness of their data holdings. We here examine how the IEDB complies with these principles and identify broad areas of success, but also areas for improvement. We describe short-term improvements to the IEDB that are being implemented now, as well as a long-term vision of true 'machine-actionable interoperability', which we believe will require community agreement on standardization of knowledge representation that can be built on top of the shared use of ontologies.

Identification of errors in the IEDB using ontologies

The Immune Epitope Database (IEDB) is a free online resource that has manually curated over 18 500 references from the scientific literature. Our database presents experimental data relating to the recognition of immune epitopes by the adaptive immune system in a structured, searchable manner. In order to be consistent and accurate in our data representation across many different journals, authors and curators, we have implemented several quality control measures, such as curation rules, controlled vocabularies and links to external ontologies and other resources. Ontologies and other resources have greatly benefited the IEDB through improved search interfaces, easier curation practices, interoperability between the IEDB and other databases and the identification of errors within our dataset. Here, we will elaborate on how ontology mapping and usage can be used to find and correct errors in a manually curated database.

Database URL: www.iedb.org

Better living through ontologies at the Immune Epitope Database

The Immune Epitope Database (IEDB) project incorporates independently developed ontologies and controlled vocabularies into its curation and search interface. This simplifies curation practices, improves the user query experience and facilitates interoperability between the IEDB and other resources. While the use of independently developed ontologies has long been recommended as a best practice, there continues to be a significant number of projects that develop their own vocabularies instead, or that do not fully utilize the power of ontologies that they are using. We describe how we use ontologies in the IEDB, providing a concrete example of the benefits of ontologies in practice.

Database URL:www.iedb.org

Favorable effects of myo-inositol, selenomethionine or their combination on the hydrogen peroxide-induced oxidative stress of peripheral mononuclear cells from patients with Hashimoto's thyroiditis: preliminary in vitro studies

OBJECTIVE

The aim of this study was to assess whether blood mononuclear cells (PBMC) from Hashimoto's thyroiditis (HT) and control women, were protected from in vitro H2O2-induced oxidative stress after addition of antioxidants.

PATIENTS AND METHODS

PBMC, from 8 HT women and 3 healthy women (controls), were cultured in the presence of 200 µM H2O2 alone, with subsequent addition of myo-inositol (Myo) (0.25, 0.5, 1.0 µM), selenomethionine (SelMet) (0.25, 0.5, 1.0 µM), or their combination (0.25+0.25, 0.5+0.5, 1.0+1.0 µM). PBMC proliferation, vitality, genotoxicity (Comet score) and secretion in the medium of the chemokines CXCL10 [IP10], CCL2 e CXCL9 [MIG] were the indices measured.

RESULTS

PBMC proliferation was decreased by H2O2 alone, and it decreased further and dose-dependently in either group (greatest decrease with Myo+SelMet in HT). H2O2 alone decreased vitality by 5% in controls and 10% in the HT group, but vitality was rescued by the three additions. The addition of H2O2 alone increased the Comet score at +505% above baseline in controls and +707% in HT women. In either group, each addition dose-dependently contrasted genotoxicity. Concentrations of chemokines in the medium were increased by H2O2 alone, and in HT women more than in controls. Each addition dose-dependently decreased these concentrations in either group, and often below baseline levels, with Myo+SelMet being the most potent addition (up to approximately -80% of baseline).

CONCLUSIONS

The tested antioxidants exert beneficial effects on PBMC exposed in vitro to H2O2-induced oxidative stress in both control and HT women. Particularly, the association Myo+SelMet is the most effective. After the demonstration of a favorable in vitro outcomes in a large cohort of HT patients, we could predict favorable in vivo outcomes given by the same supplement. Thus, one can select HT patients with a high chance of benefit from supplementation.

Myo-inositol and selenium reduce the risk of developing overt hypothyroidism in patients with autoimmune thyroiditis

OBJECTIVE

The beneficial effects obtained by myo-inositol in association with seleno-methionine in patients affected by subclinical hypothyroidism have been recently demonstrated. Here, we evaluate the immune-modulating effect of myo-inositol in association with seleno-methionine in patients with euthyroid autoimmune thyroiditis (AT).

PATIENTS AND METHODS

Twenty-one consecutive Caucasian patients with newly diagnosed euthyroid chronic AT were evaluated. All subjects were treated with myo-inositol in association with selenium (600 mg/83 mg) tablets, twice per day, for six months. A complete thyroid assessment was done before the treatment, and after six months.

RESULTS

After the treatment thyroid-stimulating hormone (TSH) levels significantly declined with respect to basal values, overall in patients with an initial TSH value in the high normal range (2.1<TSH<4.0), suggesting that the combined treatment can reduce the risk of a progression to hypothyroidism in subjects with autoimmune thyroid diseases (AITD). We found that after the treatment antithyroid autoantibodies levels declined. Moreover, the immune-modulatory effect was first confirmed by the fact that after the treatment CXCL10 levels declined, too.

CONCLUSIONS

We first show an immune-modulatory effect of myo-inositol in association with seleno-methionine in patients with euthyroid AT. Further studies are needed to extend the observations in a large population, to evaluate the effect on the quality of life, and to study the mechanism of the effect on chemokines.

Gly972Arg of IRS-1 and Lys121Gln of PC-1 polymorphisms act in opposite way in polycystic ovary syndrome

PURPOSE

Polycystic ovary syndrome (PCOS) was associated with a number of polymorphisms of genes involved in insulin signaling. So far, they have been studied separately. The aim of this study was to verify the impact of the coexistence of two polymorphisms of insulin signaling.

METHODS

One hundred consecutive PCOS women (diagnosed by Rotterdam criteria) and 45 age-matched healthy women were genotyped for two polymorphisms: Gly972Arg of IRS-1 and Lys121Gln of PC-1. Also, they underwent clinical evaluation, blood sampling for measurement of metabolic and hormonal indices, and a 75-g oral glucose tolerance test (OGTT).

RESULTS

Comparing PCOS women with controls, the rate of homo-/heterozygosity was significantly greater (50 vs. 24.5%, P = 0.004) for IRS-1 polymorphism, but insignificantly greater (20 vs. 13.3%, P = 0.33) for PC-1 polymorphism. In PCOS women, compared with controls, the genotypes IRS-1 hetero/PC-1 wild type (WT) (36 vs. 17.8%, P = 0.03) and IRS-1 hetero/PC-1 hetero (14 vs. 6.7%, P = 0.20) were overrepresented at the expense of IRS-1 WT/PC-1 WT (44 vs. 68.8%, P = 0.005), while IRS-1 WT/PC-1 hetero was similarly represented (6 vs. 6.7%). Based on genotype, metabolic and hormonal indices changed significantly. For instance, six indices (HOMA-IR, fasting insulin, insulin area under the curve at OGTT, triglycerides, total and calculated free testosterone) were the highest in IRS-1 hetero/PC-1 WT women.

CONCLUSIONS

Genetic variations in insulin signaling contribute to the extent and the variability of metabolic and hormonal derangement.

Sequence conservation predicts T cell reactivity against ragweed allergens

BACKGROUND

Ragweed is a major cause of seasonal allergy, affecting millions of people worldwide. Several allergens have been defined based on IgE reactivity, but their relative immunogenicity in terms of T cell responses has not been studied.

OBJECTIVE

We comprehensively characterized T cell responses from atopic, ragweed-allergic subjects to Amb a 1, Amb a 3, Amb a 4, Amb a 5, Amb a 6, Amb a 8, Amb a 9, Amb a 10, Amb a 11, and Amb p 5 and examined their correlation with serological reactivity and sequence conservation in other allergens.

METHODS

Peripheral blood mononuclear cells (PBMCs) from donors positive for IgE towards ragweed extracts after in vitro expansion for secretion of IL-5 (a representative Th2 cytokine) and IFN-γ (Th1) in response to a panel of overlapping peptides spanning the above-listed allergens were assessed.

RESULTS

Three previously identified dominant T cell epitopes (Amb a 1 176-191, 200-215, and 344-359) were confirmed, and three novel dominant epitopes (Amb a 1 280-295, 304-319, and 320-335) were identified. Amb a 1, the dominant IgE allergen, was also the dominant T cell allergen, but dominance patterns for T cell and IgE responses for the other ragweed allergens did not correlate. Dominance for T cell responses correlated with conservation of ragweed epitopes with sequences of other well-known allergens.

CONCLUSIONS AND CLINICAL RELEVANCE

These results provide the first assessment of the hierarchy of T cell reactivity in ragweed allergens, which is distinct from that observed for IgE reactivity and influenced by T cell epitope sequence conservation. The results suggest that ragweed allergens associated with lesser IgE reactivity and significant T cell reactivity may be targeted for T cell immunotherapy, and further support the development of immunotherapies against epitopes conserved across species to generate broad reactivity against many common allergens.

The Ontology for Biomedical Investigations

The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed in association with OBI. The current release of OBI is available at http://purl.obolibrary.org/obo/obi.owl.

Reproducibility and conflicts in immune epitope data

The Immune Epitope Database is uniquely positioned to assess the body of research related to immune epitopes, we have manually curated all such published data. Thus, we are able to make observations on the state of these fields of research, as well as aggregate the individual data points to present a clearer picture of the immune response to specific antigens in all studied hosts. Additionally, we are able to identify where conflicts in the literature exist and where publications fall short in terms of identifiable methods and in reproducibility. Here we present guidelines to improve the quality of immune epitope data, which will benefit journals and researchers alike.

An ontology for major histocompatibility restriction

BACKGROUND

MHC molecules are a highly diverse family of proteins that play a key role in cellular immune recognition. Over time, different techniques and terminologies have been developed to identify the specific type(s) of MHC molecule involved in a specific immune recognition context. No consistent nomenclature exists across different vertebrate species.

PURPOSE

To correctly represent MHC related data in The Immune Epitope Database (IEDB), we built upon a previously established MHC ontology and created an ontology to represent MHC molecules as they relate to immunological experiments.

DESCRIPTION

This ontology models MHC protein chains from 16 species, deals with different approaches used to identify MHC, such as direct sequencing verses serotyping, relates engineered MHC molecules to naturally occurring ones, connects genetic loci, alleles, protein chains and multi-chain proteins, and establishes evidence codes for MHC restriction. Where available, this work is based on existing ontologies from the OBO foundry.

CONCLUSIONS

Overall, representing MHC molecules provides a challenging and practically important test case for ontology building, and could serve as an example of how to integrate other ontology building efforts into web resources.

The immune epitope database (IEDB) 3.0

The IEDB, www.iedb.org, contains information on immune epitopes—the molecular targets of adaptive immune responses—curated from the published literature and submitted by National Institutes of Health funded epitope discovery efforts. From 2004 to 2012 the IEDB curation of journal articles published since 1960 has caught up to the present day, with >95% of relevant published literature manually curated amounting to more than 15 000 journal articles and more than 704 000 experiments to date. The revised curation target since 2012 has been to make recent research findings quickly available in the IEDB and thereby ensure that it continues to be an up-to-date resource. Having gathered a comprehensive dataset in the IEDB, a complete redesign of the query and reporting interface has been performed in the IEDB 3.0 release to improve how end users can access this information in an intuitive and biologically accurate manner. We here present this most recent release of the IEDB and describe the user testing procedures as well as the use of external ontologies that have enabled it.

Hepatitis C virus infection and type 2 diabetes

Hepatitis C virus (HCV) infection and Type 2 diabetes mellitus (T2DM) are two worldwide, major public health problems with increasing complication and mortality rates. Many epidemiological studies have demonstrated the significant association between T2DM and chronic HCV infection. In this paper we have reviewed the increasing evidence linking HCV infection and DM in more than one field (epidemiology, pathogenesis, clinical aspects, prevention and treatment). We have considered T2DM, acute and chronic HCV infection, and cirrhotic patients. Moreover, we have considered some particular populations, solid organ transplant recipients or HCV/human immunodeficiency virus (HIV) coinfected patients. In the final part we have analyzed the potential effect of the association between HCV infection and the development of DM in term of outcome and possibilities for prevention and treatment.

Antibody informatics for drug discovery

More and more antibody therapeutics are being approved every year, mainly due to their high efficacy and antigen selectivity. However, it is still difficult to identify the antigen, and thereby the function, of an antibody if no other information is available. There are obstacles inherent to the antibody science in every project in antibody drug discovery. Recent experimental technologies allow for the rapid generation of large-scale data on antibody sequences, affinity, potency, structures, and biological functions; this should accelerate drug discovery research. Therefore, a robust bioinformatic infrastructure for these large data sets has become necessary. In this article, we first identify and discuss the typical obstacles faced during the antibody drug discovery process. We then summarize the current status of three sub-fields of antibody informatics as follows: (i) recent progress in technologies for antibody rational design using computational approaches to affinity and stability improvement, as well as ab-initio and homology-based antibody modeling; (ii) resources for antibody sequences, structures, and immune epitopes and open drug discovery resources for development of antibody drugs; and (iii) antibody numbering and IMGT. Here, we review "antibody informatics," which may integrate the above three fields so that bridging the gaps between industrial needs and academic solutions can be accelerated. This article is part of a Special Issue entitled: Recent advances in molecular engineering of antibody.

Query enhancement through the practical application of ontology: the IEDB and OBI

Ontologies categorize entities, express relationships between them, and provide standardized definitions. Thus, they can be used to present and enforce the specific relationships between database components. The Immune Epitope Database (IEDB, http://www.iedb.org) utilizes the Ontology for Biomedical Investigations (OBI) and several additional ontologies to represent immune epitope mapping experiments. Here, we describe our experiences utilizing this representation in order to provide enhanced database search functionality. We applied a simple approach to incorporate the benefits of the information captured in a formal ontology directly into the user web interface, resulting in an improved user experience with minimal changes to the database itself. The integration is easy to maintain, provides standardized terms and definitions, and allows for subsumption queries. In addition to these immediate benefits, our long-term goal is to enable true semantic integration of data and knowledge in the biomedical domain. We describe our progress towards that goal and what we perceive as the main obstacles.

T cell responses to known allergen proteins are differently polarized and account for a variable fraction of total response to allergen extracts

A panel of 133 allergens derived from 28 different sources, including fungi, trees, grasses, weeds, and indoor allergens, was surveyed utilizing prediction of HLA class II-binding peptides and ELISPOT assays with PBMC from allergic donors, resulting in the identification of 257 T cell epitopes. More than 90% of the epitopes were novel, and for 14 allergen sources were the first ever identified to our knowledge. The epitopes identified in the different allergen sources summed up to a variable fraction of the total extract response. In cases of allergens in which the identified T cell epitopes accounted for a minor fraction of the extract response, fewer known protein sequences were available, suggesting that for low epitope coverage allergen sources, additional allergen proteins remain to be identified. IL-5 and IFN-γ responses were measured as prototype Th2 and Th1 responses, respectively. Whereas in some cases (e.g., orchard grass, Alternaria, cypress, and Russian thistle) IL-5 production greatly exceeded IFN-γ, in others (e.g., Aspergillus, Penicillum, and alder) the production of IFN-γ exceeded IL-5. Thus, different allergen sources are associated with variable polarization of the responding T cells. The present study represents the most comprehensive survey to date of human allergen-derived T cell epitopes. These epitopes might be used to characterize T cell phenotype/T cell plasticity as a function of seasonality, or as a result of specific immunotherapy treatment or varying disease severity (asthma or rhinitis).

The immune epitope database 2.0

The Immune Epitope Database (IEDB, www.iedb.org) provides a catalog of experimentally characterized B and T cell epitopes, as well as data on Major Histocompatibility Complex (MHC) binding and MHC ligand elution experiments. The database represents the molecular structures recognized by adaptive immune receptors and the experimental contexts in which these molecules were determined to be immune epitopes. Epitopes recognized in humans, nonhuman primates, rodents, pigs, cats and all other tested species are included. Both positive and negative experimental results are captured. Over the course of 4 years, the data from 180 978 experiments were curated manually from the literature, which covers ∼99% of all publicly available information on peptide epitopes mapped in infectious agents (excluding HIV) and 93% of those mapped in allergens. In addition, data that would otherwise be unavailable to the public from 129 186 experiments were submitted directly by investigators. The curation of epitopes related to autoimmunity is expected to be completed by the end of 2010. The database can be queried by epitope structure, source organism, MHC restriction, assay type or host organism, among other criteria. The database structure, as well as its querying, browsing and reporting interfaces, was completely redesigned for the IEDB 2.0 release, which became publicly available in early 2009.

The curation guidelines of the immune epitope database and analysis resource

The IEDB houses antibody and T cell epitope data and makes them accessible and searchable. The curation of literature references requires explicit guidelines in order to capture the data in an objective and consistent manner. Description of these guidelines ensures transparency of the database and facilitates direct submissions to the database.

Curation of complex, context-dependent immunological data

Background

The Immune Epitope Database and Analysis Resource (IEDB) is dedicated to capturing, housing and analyzing complex immune epitope related data .

Description

To identify and extract relevant data from the scientific literature in an efficient and accurate manner, novel processes were developed for manual and semi-automated annotation.

Conclusion

Formalized curation strategies enable the processing of a large volume of context-dependent data, which are now available to the scientific community in an accessible and transparent format. The experiences described herein are applicable to other databases housing complex biological data and requiring a high level of curation expertise.

Clustering of T cell ligands on artificial APC membranes influences T cell activation and protein kinase C theta translocation to the T cell plasma membrane

T cell activation is associated with active clustering of relevant molecules in membrane microdomains defined as the supramolecular activation cluster. The contact area between these regions on the surface of T cells and APC is defined as the immunological synapse. It has been recently shown that preclustering of MHC-peptide complexes in membrane microdomains on the APC surface affects the efficiency of immune synapse formation and the related T cell activation. Disruption of such clusters may reduce the efficiency of stimulation. We describe here an entirely artificial system for Ag-specific, ex vivo stimulation of human polyclonal T cells (artificial APC (aAPC)). aAPC are based on artificial membrane bilayers containing discrete membrane microdomains encompassing T cell ligands (i.e., appropriate MHC-peptide complexes in association with costimulatory molecules). We show here that preclustering of T cell ligands triggered a degree of T cell activation significantly higher than the one achieved when we used either soluble tetramers or aAPC in which MHC-peptide complexes were uniformly distributed within artificial bilayer membranes. This increased efficiency in stimulation was mirrored by increased translocation from the cytoplasm to the membrane of protein kinase theta, a T cell signaling molecule that colocalizes with the TCR within the supramolecular activation cluster, thus indicating efficient engagement of T cell activation pathways. Engineered aAPC may have immediate application for basic and clinical immunology studies pertaining to modulation of T cells ex vivo.

SPAK kinase is a substrate and target of PKCtheta in T-cell receptor-induced AP-1 activation pathway

Protein kinase C-theta (PKCtheta) plays an important role in T-cell activation via stimulation of AP-1 and NF-kappaB. Here we report the isolation of SPAK, a Ste20-related upstream mitogen-activated protein kinase (MAPK), as a PKCtheta-interacting kinase. SPAK interacted with PKCtheta (but not with PKCalpha) via its 99 COOH-terminal residues. TCR/CD28 costimulation enhanced this association and stimulated the catalytic activity of SPAK. Recombinant SPAK was phosphorylated on Ser-311 in its kinase domain by PKCtheta, but not by PKCalpha. The magnitude and duration of TCR/CD28-induced endogenous SPAK activation were markedly impaired in PKCtheta-deficient T cells. Transfected SPAK synergized with constitutively active PKCtheta to activate AP-1, but not NF-kappaB. This synergistic activity, as well as the receptor-induced SPAK activation, required the PKCtheta-interacting region of SPAK, and Ser-311 mutation greatly reduced these activities of SPAK. Conversely, a SPAK-specific RNAi or a dominant-negative SPAK mutant inhibited PKCtheta- and TCR/CD28-induced AP-1, but not NF-kappaB, activation. These results define SPAK as a substrate and target of PKCtheta in a TCR/CD28-induced signaling pathway leading selectively to AP-1 (but not NF-kappaB) activation.

IGF-I/BP-3 administration preserves hepatic homeostasis after thermal injury which is associated with increases in no and hepatic NF-kappa B

After a severe trauma, such as a cutaneous thermal injury, an increase in hepatocyte apoptosis has been associated with hepatocyte damage and impairment in hepatic function. Insulinlike growth factor-I (IGF-I) exerts antiapoptotic effects in several organs, thus improving organ homeostasis. The purpose of the present study was to determine whether IGF-I in combination with its principle binding protein-3 (BP-3) attenuates liver damage after a burn and whether this attenuation is through signals of the apoptotic-proliferative axis of hepatocytes. Sprague-Dawley rats (56 males) received a 60% total body surface area third-degree scald burn and were randomly divided to receive either rhlGF-I/BP3 (10 mg/kg/day s.c.) or saline (control). Serum aspartate transaminase (AST) and nitric oxide (NO), and hepatocyte proliferation and apoptosis, were measured on postburn days 1, 2, 5, and 7. Hepatic interleukin-1 beta (IL-1 beta) and tumor necrosis factor-alpha (TNF-alpha) mRNA and hepatic nuclear-factor kappa B (NF-kappa B) were determined at 1 and 2 days postburn. IGF-I/BP-3 decreased serum AST and increased serum NO at 1, 2, and 5 days after burn when compared with controls (P < 0.05). IGF-I/BP-3 increased hepatocyte proliferation on the first day after burn and decreased hepatocyte apoptosis at day 7 postburn when compared with controls (P < 0.05). IGF-I/BP-3 decreased hepatic IL-1 beta and TNF-alpha mRNA 1 day after burn (P < 0.05). IGF-I/BP-3 further increased hepatic NF-kappa B concentration 1 and 2 days postburn when compared with controls (P < 0.05). Recombinant hIGF-I in combination with its principle binding protein conserves hepatic homeostasis, which is associated with a transient increase in hepatocyte proliferation and decrease in hepatocyte apoptosis possibly through NO and hepatic NF-kappa B.

The functional role of rho and rho-associated coiled-coil forming protein kinase in eotaxin signaling of eosinophils

The CC chemokine eotaxin plays a pivotal role in local accumulation of eosinophils. Very little is known about the eotaxin signaling in eosinophils except the activation of the mitogen-activated protein (MAP) kinase family. The p21 G protein Rho and its substrate Rho-associated coiled-coil forming protein kinase (ROCK) regulate the formation of stress fibers and focal adhesions. In the present study, we studied the functional relevance of Rho and ROCK in eosinophils using the ROCK inhibitor (Y-27632) and exoenzyme C3, a specific Rho inhibitor. Eotaxin stimulates activation of Rho A and ROCK II in eosinophils. Exoenzyme C3 almost completely inhibited the ROCK activity, indicating that ROCK is downstream of Rho. We then examined the role of Rho and ROCK in eosinophil chemotaxis. The eotaxin-induced eosinophil chemotaxis was significantly inhibited by exoenzyme C3 or Y-27632. Because extracellular signal-regulated kinase (ERK)1/2 and p38 MAP kinases are activated by eotaxin and are critical for eosinophil chemotaxis, we investigated whether Rho and ROCK are upstream of these MAP kinases. C3 partially inhibited eotaxin-induced phosphorylation of ERK1/2 but not p38. In contrast, neither ERK1/2 nor p38 phosphorylation was abrogated by Y-27632. Both C3 and Y-27632 reduced reactive oxygen species production from eosinophils. We conclude that both Rho and ROCK are important for eosinophil chemotaxis and reactive oxygen species production. There is a dichotomy of downstream signaling pathways of Rho, namely, Rho-ROCK and Rho-ERK pathways. Taken together, eosinophil chemotaxis is regulated by multiple signaling pathways that involve at least ROCK, ERK, and p38 MAP kinase.

Cell proliferation, apoptosis, NF-kappaB expression, enzyme, protein, and weight changes in livers of burned rats

Thermal injury has been shown to alter gut epithelium and heart myocyte homeostasis by inducing programmed cell death. The effect of thermal injury on hepatocyte apoptosis and proliferation, however, has not been established. The purpose of this study was to determine whether a large thermal injury increases liver cell apoptosis and proliferation and whether these changes were associated with alterations in hepatic nuclear factor kappaB (NF-kappaB) expression and changes in liver enzymes and amount of protein. Sprague-Dawley rats received a 40% total body surface area scald burn or sham burn. Rats were killed and livers were harvested at 1, 2, 5, and 7 days after burn. Liver cell apoptosis was determined by terminal deoxyuridine nick end labeling (TUNEL) assay and cell proliferation by immunohistochemistry for proliferating cell nuclear antigen. Hepatic NF-kappaB expression was determined by Western blot, and total hepatic protein content was determined by protein assay. Protein concentration decreased after burn compared with sham controls (P < 0.05). Liver cell apoptosis, proliferation, and NF-kappaB expression in hepatocytes increased in burned rats compared with controls (P < 0.05). It was concluded that thermal injury induces hepatic cell apoptosis and proliferation associated with an increase in hepatic NF-kappaB expression and a decrease in hepatic protein concentration.

Interleukin 15 is produced by endothelial cells and increases the transendothelial migration of T cells In vitro and in the SCID mouse-human rheumatoid arthritis model In vivo

The capacity of endothelial cells (EC) to produce IL-15 and the capacity of IL-15 to influence transendothelial migration of T cells was examined. Human umbilical vein endothelial cells expressed both IL-15 mRNA and protein. Moreover, endothelial-derived IL-15 enhanced transendothelial migration of T cells as evidenced by the inhibition of this process by blocking monoclonal antibodies to IL-15. IL-15 enhanced transendothelial migration of T cells by activating the binding capacity of the integrin adhesion molecule LFA-1 (CD11a/CD18) and also increased T cell motility. In addition, IL-15 induced expression of the early activation molecule CD69. The importance of IL-15 in regulating migration of T cells in vivo was documented by its capacity to enhance accumulation of adoptively transferred human T cells in rheumatoid arthritis synovial tissue engrafted into immune deficient SCID mice. These results demonstrate that EC produce IL-15 and imply that endothelial IL-15 plays a critical role in stimulation of T cells to extravasate into inflammatory tissue.

Phenotypic characterization of CD4+ T cells that exhibit a transendothelial migratory capacity

The phenotype of CD4+ T cells capable of transendothelial migration was determined using an in vitro model system, in which cells migrate through a monolayer of endothelial cells (EC) on collagen gels. A specific subset of resting CD4+ memory T cells was found to migrate. T cells within this subset can be defined by the bright expression of CD11a, CD26, CD44, and CD49d. Additionally, the migratory CD4+ T cell population is largely CD58bright, CD31-, CD62L-, and is also enriched in cells that brightly express CD49c, CD49e, and CD49f. Only a minority of the cells are activated, as indicated by expression of CD69. The EC were found to play a central role in facilitating migration of this subset because selective enrichment of CD11abright, CD26bright, CD44bright, CD4+ T cells was not observed when cells migrated in the absence of EC. Activation of the T cells induced a modest degree of migration of an additional subset of CD45RA+, CD31+ naive T cells. In contrast, TNF-alpha activation of the EC increased the transendothelial migration of an additional subset of activated memory T cells that expressed CD69 and CD62L. Neither activation of the T cells, stimulation of the EC, nor the presence of macrophage inflammatory protein-1 alpha (MIP-1 alpha) or RANTES, however, altered the phenotype of the majority of the migratory CD4+ T cell population, which is characteristic of a particular stage of memory cell differentiation. These results suggest that CD4+ T cells acquire the capacity for transendothelial migration at a specific phase of maturation that is only minimally altered by the activation of either the T cell or the EC, or by the presence of specific chemokines in the subendothelial matrix.