Predicting protein subcellular locations using hierarchical ensemble of Bayesian classifiers based on Markov chains

BACKGROUND: The subcellular location of a protein is closely related to its function. It would be worthwhile to develop a method to predict the subcellular location for a given protein when only the amino acid sequence of the protein is known. Although many efforts have been made to predict subcellular location from sequence information only, there is the need for further research to improve the accuracy of prediction. RESULTS: A novel method called HensBC is introduced to predict protein subcellular location. HensBC is a recursive algorithm which constructs a hierarchical ensemble of classifiers. The classifiers used are Bayesian classifiers based on Markov chain models. We tested our method on six various datasets; among them are Gram-negative bacteria dataset, data for discriminating outer membrane proteins and apoptosis proteins dataset. We observed that our method can predict the subcellular location with high accuracy. Another advantage of the proposed method is that it can improve the accuracy of the prediction of some classes with few sequences in training and is therefore useful for datasets with imbalanced distribution of classes. CONCLUSION: This study introduces an algorithm which uses only the primary sequence of a protein to predict its subcellular location. The proposed recursive scheme represents an interesting methodology for learning and combining classifiers. The method is computationally efficient and competitive with the previously reported approaches in terms of prediction accuracies as empirical results indicate. The code for the software is available upon request

Control of the specificity of T cell-mediated anti-idiotype immunity by natural regulatory T cells

The idiotypes of B cell lymphomas represent tumor-specific antigens. T cell responses induced by idiotype vaccination in vivo are directed predominantly against CDR peptides, whereas in vitro T cells also recognize framework-derived epitopes. To investigate the mechanisms regulating the specificity of idiotype-specific T cells, BALB/c or B10.D2 mice were immunized with mature dendritic cells loaded with H-2Kd-restricted peptides from influenza hemagglutinin, or from shared (J region) or unique (CDR3) structures of the A20 lymphoma idiotype. Antigen-specific T cells were induced in vivo by the CDR3 and influenza epitopes, but not by the J peptide. Gene expression profiling of splenic regulatory T cells revealed vaccination-induced Treg activation and proliferation. Treg activity involved J epitope-dependent IL-10 secretion and functional suppression of peptide-specific effector T cells. Vaccination-induced in vivo proliferation of transgenic hemagglutinin-specific T cells was suppressed by co-immunization with the J peptide and was restored in CD25-depleted animals. In conclusion, Treg induced by a shared idiotype epitope can systemically suppress T cell responses against idiotype-derived and immunodominant foreign epitopes in vivo. The results imply that tumor vaccines should avoid epitopes expressed by normal cells in the draining lymph node to achieve optimal anti-tumor efficacy

Assessing the Functional Relevance of Variants in the IKAROS Family Zinc Finger Protein 1 (IKZF1) in a Cohort of Patients With Primary Immunodeficiency

Common variable immunodeficiency (CVID) is the most frequent symptomatic primary immunodeficiency. Patients with CVID are prone to recurrent bacterial infection due to the failure of adequate immunoglobulin production. Monogenetic defects have been identified in ~25% of CVID patients. Recently, mutations in IKZF1, encoding the zinc-finger transcription factor IKAROS which is broadly expressed in hematopoietic cells, have been associated with a CVID-like phenotype. Herein we describe 11 patients with heterozygous IKZF1 variants from eight different families with autosomal dominant CVID and two siblings with an IKZF1 variant presenting with inflammatory bowel disease (IBD). This study shows that mutations affecting the DNA binding domain of IKAROS can impair the interaction with the target DNA sequence thereby preventing heterochromatin and pericentromeric localization (HC-PC) of the protein. Our results also indicate an impairment of pericentromeric localization of IKAROS by overexpression of a truncated variant, caused by an immature stop codon in IKZF1. We also describe an additional variant in TNFSF10, encoding Tumor Necrosis Factor Related Apoptosis Inducing Ligand (TRAIL), additionally presented in individuals of Family A. Our results indicate that this variant may impair the TRAIL-induced apoptosis in target cell lines and prohibit the NFκB activation by TRAIL and may act as a modifier in Family A.Fil: Eskandarian, Zoya. Albert Ludwigs University of Freiburg; AlemaniaFil: Fliegauf, Manfred. Albert Ludwigs University of Freiburg; AlemaniaFil: Bulashevska, Alla. Albert Ludwigs University of Freiburg; AlemaniaFil: Proietti, Michele. Albert Ludwigs University of Freiburg; AlemaniaFil: Hague, Rosie. Royal Hospital For Children; Reino UnidoFil: Smulski, Cristian Roberto. Albert Ludwigs University of Freiburg; Alemania. Comisión Nacional de Energía Atómica. Centro Atómico Bariloche; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte; ArgentinaFil: Schubert, Desirée. Albert Ludwigs University of Freiburg; AlemaniaFil: Warnatz, Klaus. Albert Ludwigs University of Freiburg; AlemaniaFil: Grimbacher, Bodo. Albert Ludwigs University of Freiburg; Alemania. University College London; Reino Unid

Artificial intelligence and neoantigens: paving the path for precision cancer immunotherapy

Cancer immunotherapy has witnessed rapid advancement in recent years, with a particular focus on neoantigens as promising targets for personalized treatments. The convergence of immunogenomics, bioinformatics, and artificial intelligence (AI) has propelled the development of innovative neoantigen discovery tools and pipelines. These tools have revolutionized our ability to identify tumor-specific antigens, providing the foundation for precision cancer immunotherapy. AI-driven algorithms can process extensive amounts of data, identify patterns, and make predictions that were once challenging to achieve. However, the integration of AI comes with its own set of challenges, leaving space for further research. With particular focus on the computational approaches, in this article we have explored the current landscape of neoantigen prediction, the fundamental concepts behind, the challenges and their potential solutions providing a comprehensive overview of this rapidly evolving field

Assessing the Functional Relevance of Variants in the IKAROS Family Zinc Finger Protein 1 (IKZF1) in a Cohort of Patients With Primary Immunodeficiency

Common variable immunodeficiency (CVID) is the most frequent symptomatic primary immunodeficiency. Patients with CVID are prone to recurrent bacterial infection due to the failure of adequate immunoglobulin production. Monogenetic defects have been identified in ~25% of CVID patients. Recently, mutations in IKZF1, encoding the zinc-finger transcription factor IKAROS which is broadly expressed in hematopoietic cells, have been associated with a CVID-like phenotype. Herein we describe 11 patients with heterozygous IKZF1 variants from eight different families with autosomal dominant CVID and two siblings with an IKZF1 variant presenting with inflammatory bowel disease (IBD). This study shows that mutations affecting the DNA binding domain of IKAROS can impair the interaction with the target DNA sequence thereby preventing heterochromatin and pericentromeric localization (HC-PC) of the protein. Our results also indicate an impairment of pericentromeric localization of IKAROS by overexpression of a truncated variant, caused by an immature stop codon in IKZF1. We also describe an additional variant in TNFSF10, encoding Tumor Necrosis Factor Related Apoptosis Inducing Ligand (TRAIL), additionally presented in individuals of Family A. Our results indicate that this variant may impair the TRAIL-induced apoptosis in target cell lines and prohibit the NFκB activation by TRAIL and may act as a modifier in Family A

Bayesian statistical modelling of human protein interaction network incorporating protein disorder information

<p>Abstract</p> <p>Background</p> <p>We present a statistical method of analysis of biological networks based on the exponential random graph model, namely p2-model, as opposed to previous descriptive approaches. The model is capable to capture generic and structural properties of a network as emergent from local interdependencies and uses a limited number of parameters. Here, we consider one global parameter capturing the density of edges in the network, and local parameters representing each node's contribution to the formation of edges in the network. The modelling suggests a novel definition of important nodes in the network, namely <it>social</it>, as revealed based on the local <it>sociality </it>parameters of the model. Moreover, the sociality parameters help to reveal organizational principles of the network. An inherent advantage of our approach is the possibility of hypotheses testing: <it>a priori </it>knowledge about biological properties of the nodes can be incorporated into the statistical model to investigate its influence on the structure of the network.</p> <p>Results</p> <p>We applied the statistical modelling to the human protein interaction network obtained with Y2H experiments. Bayesian approach for the estimation of the parameters was employed. We deduced <it>social </it>proteins, essential for the formation of the network, while incorporating into the model information on protein disorder. <it>Intrinsically disordered </it>are proteins which lack a well-defined three-dimensional structure under physiological conditions. We predicted the fold group (ordered or disordered) of proteins in the network from their primary sequences. The network analysis indicated that protein disorder has a positive effect on the connectivity of proteins in the network, but do not fully explains the interactivity.</p> <p>Conclusions</p> <p>The approach opens a perspective to study effects of biological properties of individual entities on the structure of biological networks.</p

Characterization of the clinical and immunologic phenotype and management of 157 individuals with 56 distinct heterozygous NFKB1 mutations

Background: An increasing number of NFKB1 variants are being identified in patients with heterogeneous immunologic phenotypes. Objective: To characterize the clinical and cellular phenotype as well as the management of patients with heterozygous NFKB1 mutations. Methods: In a worldwide collaborative effort, we evaluated 231 individuals harboring 105 distinct heterozygous NFKB1 variants. To provide evidence for pathogenicity, each variant was assessed in silico; in addition, 32 variants were assessed by functional in vitro testing of nuclear factor of kappa light polypeptide gene enhancer in B cells (NF-kappa B) signaling. Results: We classified 56 of the 105 distinct NFKB1 variants in 157 individuals from 68 unrelated families as pathogenic. Incomplete clinical penetrance (70%) and age-dependent severity of NFKB1-related phenotypes were observed. The phenotype included hypogammaglobulinemia (88.9%), reduced switched memory B cells (60.3%), and respiratory (83%) and gastrointestinal (28.6%) infections, thus characterizing the disorder as primary immunodeficiency. However, the high frequency of autoimmunity (57.4%), lymphoproliferation (52.4%), noninfectious enteropathy (23.1%), opportunistic infections (15.7%), autoinflammation (29.6%), and malignancy (16.8%) identified NF-kappa B1-related disease as an inborn error of immunity with immune dysregulation, rather than a mere primary immunodeficiency. Current treatment includes immunoglobulin replacement and immunosuppressive agents. Conclusions: We present a comprehensive clinical overview of the NF-kappa B1-related phenotype, which includes immunodeficiency, autoimmunity, autoinflammation, and cancer. Because of its multisystem involvement, clinicians from each and every medical discipline need to be made aware of this autosomal-dominant disease. Hematopoietic stem cell transplantation and NF-kappa B1 pathway-targeted therapeutic strategies should be considered in the future.Peer reviewe

Clinical and Immunological Phenotype of Patients With Primary Immunodeficiency Due to Damaging Mutations in NFKB2

Non-canonical NF-κB-pathway signaling is integral in immunoregulation. Heterozygous mutations in NFKB2 have recently been established as a molecular cause of common variable immunodeficiency (CVID) and DAVID-syndrome, a rare condition combining deficiency of anterior pituitary hormone with CVID. Here, we investigate 15 previously unreported patients with primary immunodeficiency (PID) from eleven unrelated families with heterozygous NFKB2-mutations including eight patients with the common p.Arg853* nonsense mutation and five patients harboring unique novel C-terminal truncating mutations. In addition, we describe the clinical phenotype of two patients with proximal truncating mutations. Cohort analysis extended to all 35 previously published NFKB2-cases revealed occurrence of early-onset PID in 46/50 patients (mean age of onset 5.9 years, median 4.0 years). ACTH-deficiency occurred in 44%. Three mutation carriers have deceased, four developed malignancies. Only two mutation carriers were clinically asymptomatic. In contrast to typical CVID, most patients suffered from early-onset and severe disease manifestations, including clinical signs of T cell dysfunction e.g., chronic-viral or opportunistic infections. In addition, 80% of patients suffered from (predominately T cell mediated) autoimmune (AI) phenomena (alopecia &gt; various lymphocytic organ-infiltration &gt; diarrhea &gt; arthritis &gt; AI-cytopenia). Unlike in other forms of CVID, auto-antibodies or lymphoproliferation were not common hallmarks of disease. Immunophenotyping showed largely normal or even increased quantities of naïve and memory CD4+ or CD8+ T-cells and normal T-cell proliferation. NK-cell number and function were also normal. In contrast, impaired B-cell differentiation and hypogammaglobinemia were consistent features of NFKB2-associated disease. In addition, an array of lymphocyte subpopulations, such as regulatory T cell, Th17-, cTFH-, NKT-, and MAIT-cell numbers were decreased. We conclude that heterozygous damaging mutations in NFKB2 represent a distinct PID entity exceeding the usual clinical spectrum of CVID. Impairment of the non-canonical NF-κB pathways affects function and differentiation of numerous lymphocyte-subpopulations and thus causes a heterogeneous, more severe form of PID phenotype with early-onset. Further characteristic features are multifaceted, primarily T cell-mediated autoimmunity, such as alopecia, lymphocytic organ infiltration, and in addition frequently ACTH-deficiency