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Article ; Online: Peptide Hamming Graphs: A network representation of peptides presented through specific HLAs to identify potential epitope clusters.

Santoni, Daniele

2023 Volume 517, Page(s) 113474

Abstract: Background: Class I Major Histocompatibility Complex plays a critical role in the adaptive immune response by binding to peptides processed by Proteasome and Transporter associated with antigen processing complex and presenting them on the cell surface ... ...

Abstract	Background: Class I Major Histocompatibility Complex plays a critical role in the adaptive immune response by binding to peptides processed by Proteasome and Transporter associated with antigen processing complex and presenting them on the cell surface to cytotoxic T-cells. Understanding the process of peptide presentation and studying how presented peptides are distributed in the huge space of all potential epitopes could have a dramatic impact in the context of vaccine design, transplantation, autoimmunity, and cancer development. Methods: In the present work we propose a graph-driven approach to investigate the landscape of both self (human) and viral (254 organisms) peptides presented on cell surface through class I Major Histocompatibility Complex considering specific HLAs. For each considered HLA (N = 89) we designed a network, namely Peptide Hamming Graph, where nodes are peptides predicted to be presented by a given HLA and an edge is set when the Hamming distance between two peptides is equal or smaller than 2 (i.e. the same amino acid occurs in at least 7 positions of the two sequences). Results: Through the analysis of Peptide Hamming Graphs we studied how predicted presented peptides are distributed in the whole configurational space for different HLAs, identifying sets of viral peptides that can constitute a potential target for the immune system. In particular we selected connected components of the graph made exclusively of viral peptides and sets of viral peptides with high node degree interacting exclusively with viral neighbours. Conclusions: This work constitutes an innovative approach to study potential cytotoxic T-cell epitopes relying on a network approach, overcoming the classical paradigm based on the identification of potential epitopes only considering their features as single peptides. T-cell cross-reactivity plays a focal role for the efficacy of this strategy increasing the probability of recognition, and consequently a stronger immune response, of presented peptides far from self, sharing a common pattern in terms of sequence similarity.
MeSH term(s)	Humans ; HLA Antigens ; Peptides ; Antigen Presentation ; Histocompatibility Antigens ; Epitopes, T-Lymphocyte
Chemical Substances	HLA Antigens ; Peptides ; Histocompatibility Antigens ; Epitopes, T-Lymphocyte
Language	English
Publishing date	2023-04-15
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	120142-6
ISSN	1872-7905 ; 0022-1759
ISSN (online)	1872-7905
ISSN	0022-1759
DOI	10.1016/j.jim.2023.113474
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Article ; Online: Peptide Hamming Graphs: A network representation of peptides presented through specific HLAs to identify potential epitope clusters

Santoni, Daniele

Journal of Immunological Methods. 2023 June, v. 517 p.113474-

2023

Abstract: Class I Major Histocompatibility Complex plays a critical role in the adaptive immune response by binding to peptides processed by Proteasome and Transporter associated with antigen processing complex and presenting them on the cell surface to cytotoxic ... ...

Abstract	Class I Major Histocompatibility Complex plays a critical role in the adaptive immune response by binding to peptides processed by Proteasome and Transporter associated with antigen processing complex and presenting them on the cell surface to cytotoxic T-cells. Understanding the process of peptide presentation and studying how presented peptides are distributed in the huge space of all potential epitopes could have a dramatic impact in the context of vaccine design, transplantation, autoimmunity, and cancer development. In the present work we propose a graph-driven approach to investigate the landscape of both self (human) and viral (254 organisms) peptides presented on cell surface through class I Major Histocompatibility Complex considering specific HLAs. For each considered HLA (N = 89) we designed a network, namely Peptide Hamming Graph, where nodes are peptides predicted to be presented by a given HLA and an edge is set when the Hamming distance between two peptides is equal or smaller than 2 (i.e. the same amino acid occurs in at least 7 positions of the two sequences). Through the analysis of Peptide Hamming Graphs we studied how predicted presented peptides are distributed in the whole configurational space for different HLAs, identifying sets of viral peptides that can constitute a potential target for the immune system. In particular we selected connected components of the graph made exclusively of viral peptides and sets of viral peptides with high node degree interacting exclusively with viral neighbours. This work constitutes an innovative approach to study potential cytotoxic T-cell epitopes relying on a network approach, overcoming the classical paradigm based on the identification of potential epitopes only considering their features as single peptides. T-cell cross-reactivity plays a focal role for the efficacy of this strategy increasing the probability of recognition, and consequently a stronger immune response, of presented peptides far from self, sharing a common pattern in terms of sequence similarity.
Keywords	T-lymphocytes ; adaptive immunity ; amino acids ; autoimmunity ; carcinogenesis ; cross reaction ; cytotoxicity ; epitopes ; humans ; landscapes ; major histocompatibility complex ; peptides ; probability ; proteasome endopeptidase complex ; sequence homology ; vaccine development ; Viral peptides ; MHC class I ; Immunoinformatics ; Self/non-self ; TAP transport ; Proteasome cleavage
Language	English
Dates of publication	2023-06
Publishing place	Elsevier B.V.
Document type	Article ; Online
ZDB-ID	120142-6
ISSN	1872-7905 ; 0022-1759
ISSN (online)	1872-7905
ISSN	0022-1759
DOI	10.1016/j.jim.2023.113474
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Article ; Online: The impact of flanking sequence features on DNA CpG methylation.

Santoni, Daniele

Computational biology and chemistry

2021 Volume 92, Page(s) 107480

Abstract: Epigenetics and DNA methylation play a pivotal role in many processes of the cell and we often observe that an aberrant methylation pattern characterizes pathologies. In this work we investigate the role that the flanking sequences of CGs play in the ... ...

Abstract	Epigenetics and DNA methylation play a pivotal role in many processes of the cell and we often observe that an aberrant methylation pattern characterizes pathologies. In this work we investigate the role that the flanking sequences of CGs play in the methylation process in human. We built four different CG datasets: methylated, unmethylated, and two randomly extracted ones. We evaluated features associated to the flanking sequences of those CG sets, for different size around the CG, through five measures accounting for different aspects of sequence composition complexity and structure. The analysis performed through those measures revealed evident different behaviors between methylated and unmethylated probe sets. Major differences were observed for GC content and CG dinucleotide frequency in a window size of 300-400 bp and for CG self-attraction in 3K bp. It is remarkable as the effect of methylated CG lasts much more than expected far from the CG.
MeSH term(s)	CpG Islands/genetics ; DNA/genetics ; DNA/metabolism ; DNA Methylation/genetics ; Entropy ; Humans
Chemical Substances	DNA (9007-49-2)
Language	English
Publishing date	2021-03-30
Publishing country	England
Document type	Journal Article
ISSN	1476-928X
ISSN (online)	1476-928X
DOI	10.1016/j.compbiolchem.2021.107480
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Article ; Online: The impact of codon choice on translation process in Saccharomyces cerevisiae: folding class, protein function and secondary structure.

Santoni, Daniele

Journal of theoretical biology

2021 Volume 526, Page(s) 110806

Abstract: The genetic code consists in a set of rules used by living organisms to translate genomic information, contained in genes, into proteins; every amino acid is coded by a set of nucleotide triplets or codons. We refer to codon choice as the choice of a ... ...

Abstract	The genetic code consists in a set of rules used by living organisms to translate genomic information, contained in genes, into proteins; every amino acid is coded by a set of nucleotide triplets or codons. We refer to codon choice as the choice of a given codon, among the synonymous available ones, to code a given amino acid occurrence. The aim of this work is to shed light on the pivotal role that codon choice plays in regulating the timing of translation process, through patterns of low and high translation efficiency codons. A translation efficiency value, namely codon score, was associated to each codon through a formula based on the number of tRNAs gene copies able to translate the given codon. By using codon scores, those k-mers of the proteome of Saccharomyces cerevisiae, showing low and high average scores associated to the correspondent codons, were computed. The analysis of distribution of both low and high average score k-mers clearly showed that, in particular for higher k-mer size, they occur much more than expected, strongly suggesting a functional role. Moreover performed analysis highlighted that significant k-mers preferentially occur in some protein folding classes, such as those containing alpha helices, and in some functional classes mainly involved in transcription process while codon choice seems to have a very low impact in proteins associated to energy production and metabolism. The relationship between secondary structures and significant k-mers was investigated, revealing that low score k-mers tend to preferentially occur in coil or close to coil regions and almost never in beta sheets, while high score k-mers preferentially occur in alpha helices, avoiding beta sheets, and close to coil regions for high k-mer sizes. Finally the analysis of distribution of significant codon patterns along the proteins highlighted a relevant enrichment of low average score k-mers at the 5' end of protein-coding sequences in the region from 5th to 25th amino acid.
MeSH term(s)	Codon/genetics ; Protein Biosynthesis/genetics ; Protein Folding ; Protein Structure, Secondary ; Proteins/genetics ; Saccharomyces cerevisiae/genetics
Chemical Substances	Codon ; Proteins
Language	English
Publishing date	2021-06-07
Publishing country	England
Document type	Journal Article
ZDB-ID	2972-5
ISSN	1095-8541 ; 0022-5193
ISSN (online)	1095-8541
ISSN	0022-5193
DOI	10.1016/j.jtbi.2021.110806
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Article ; Online: An Integer Linear Programming Model to Optimize Coding DNA Sequences By Joint Control of Transcript Indicators.

Arbib, Claudio / D'ascenzo, Andrea / Rossi, Fabrizio / Santoni, Daniele

Journal of computational biology : a journal of computational molecular cell biology

2024

Language	English
Publishing date	2024-04-30
Publishing country	United States
Document type	Journal Article
ZDB-ID	2030900-4
ISSN	1557-8666 ; 1066-5277
ISSN (online)	1557-8666
ISSN	1066-5277
DOI	10.1089/cmb.2023.0166
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Article ; Online: Viral peptides-MHC interaction: Binding probability and distance from human peptides.

Santoni, Daniele

Journal of immunological methods

2018 Volume 459, Page(s) 35–43

Abstract: Identification of peptides binding to MHC class I complex can play a crucial role in retrieving potential targets able to trigger an immune response. Affinity binding of viral peptides can be estimated through effective computational methods that in the ... ...

Abstract	Identification of peptides binding to MHC class I complex can play a crucial role in retrieving potential targets able to trigger an immune response. Affinity binding of viral peptides can be estimated through effective computational methods that in the most of cases are based on machine learning approach. Achieving a better insight into peptide features that impact on the affinity binding rate is a challenging issue. In the present work we focused on 9-mer peptides of Human immunodeficiency virus type 1 and Human herpes simplex virus 1, studying their binding to MHC class I. Viral 9-mers were partitioned into different classes, where each class is characterized by how far (in terms of mutation steps) the peptides belonging to that class are from human 9-mers. Viral 9-mers were partitioned in different classes, based on the number of mutation steps they are far from human 9-mers. We showed that the overall binding probability significantly differs among classes, and it typically increases as the distance, computed in terms of number of mutation steps from the human set of 9-mers, increases. The binding probability is particularly high when considering viral 9-mers that are far from all human 9-mers more than three mutation steps. A further evidence, providing significance to those special viral peptides and suggesting a potential role they can play, comes from the analysis of their distribution along viral genomes, as it revealed they are not randomly located, but they preferentially occur in specific genes.
MeSH term(s)	Epitopes, T-Lymphocyte/immunology ; Genome, Viral ; HIV-1/immunology ; Herpesvirus 1, Human/immunology ; Histocompatibility Antigens Class I/immunology ; Humans ; Oligopeptides/immunology ; Probability ; Protein Binding ; Viral Proteins/immunology
Chemical Substances	Epitopes, T-Lymphocyte ; Histocompatibility Antigens Class I ; MHC binding peptide ; Oligopeptides ; Viral Proteins
Language	English
Publishing date	2018-05-23
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	120142-6
ISSN	1872-7905 ; 0022-1759
ISSN (online)	1872-7905
ISSN	0022-1759
DOI	10.1016/j.jim.2018.05.009
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Article ; Online: An immunological glimpse of human virus peptides: Distance from self, MHC class I binding, proteasome cleveage, TAP transport and sequence composition entropy.

Santoni, Daniele / Felici, Giovanni

Virus research

2022 Volume 317, Page(s) 198814

Abstract: Adaptive immune response is triggered when specific pathogen peptides called epitopes are recognised as exogenous according to the paradigm of self/non-self. To be recognized by immune cells, epitopes have to be exposed (presented) on the surface of the ... ...

Abstract	Adaptive immune response is triggered when specific pathogen peptides called epitopes are recognised as exogenous according to the paradigm of self/non-self. To be recognized by immune cells, epitopes have to be exposed (presented) on the surface of the cell. Predicting if a peptide is exposed is important to shed light on the rules that govern immune response and, thus, identify potential targets and design vaccine and drugs. We focused on peptides exposed on cell surface and made accessible to immune system through the MHC Class I complex. Before this can happen, three successive selection steps have to take place: a) Proteasome cleveage, b) TAP Transport, and c) binding to MHC-class I. Starting from a set of 211 host human reference viruses, we computed the set of unique peptides occurring in the correspondent proteomes. Then, we obtained the probability values of Proteasome Cleveage, TAP Transport and Binding to MHC Class I associated to those peptides through established prediction software tools. Such values were analysed in conjunction with two other features that could play a major role: the distance from self, strictly linked to the concept of nullomers, and the sequence entropy, measuring the complexity of the peptide amino acid composition. The analysis confirmed and extended previous results on a larger, more significant and consistent data set; we showed that the higher the distances from self, the higher the score of TAP Transport and binding to MHC class I; no significant association was instead found between distance from self and Proteasome Cleveage. Additionally, amino acid peptide composition entropy was significantly associated with the other features. In particular, higher entropies were linked with higher scores of Proteasome Cleveage, TAP Transport, Binding to MHC Class I, and higher distance from self. The relationship among the three selection steps provided evidence of a tight inter-correlation, clearly suggesting it could be the product of a co-evolutive process. We believe that these results give new insights on the complex processes that regulate peptide presentation through MHC class I, and unveil the mechanisms the allow the immune system to distinguish self and viral non-self peptides.
MeSH term(s)	ATP-Binding Cassette Transporters/genetics ; Amino Acids ; Antigen Presentation ; Entropy ; Epitopes ; Histocompatibility Antigens Class I/metabolism ; Humans ; Peptides ; Proteasome Endopeptidase Complex/metabolism ; Viruses/metabolism
Chemical Substances	ATP-Binding Cassette Transporters ; Amino Acids ; Epitopes ; Histocompatibility Antigens Class I ; Peptides ; Proteasome Endopeptidase Complex (EC 3.4.25.1)
Language	English
Publishing date	2022-05-16
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	605780-9
ISSN	1872-7492 ; 0168-1702
ISSN (online)	1872-7492
ISSN	0168-1702
DOI	10.1016/j.virusres.2022.198814
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Article ; Online: Network homophily via tail inequalities.

Apollonio, Nicola / Franciosa, Paolo G / Santoni, Daniele

Physical review. E

2023 Volume 108, Issue 5-1, Page(s) 54130

Abstract: Homophily is the principle whereby "similarity breeds connections." We give a quantitative formulation of this principle within networks. Given a network and a labeled partition of its vertices, the vector indexed by each class of the partition, whose ... ...

Abstract	Homophily is the principle whereby "similarity breeds connections." We give a quantitative formulation of this principle within networks. Given a network and a labeled partition of its vertices, the vector indexed by each class of the partition, whose entries are the number of edges of the subgraphs induced by the corresponding classes, is viewed as the observed outcome of the random vector described by picking labeled partitions at random among labeled partitions whose classes have the same cardinalities as the given one. This is the recently introduced random coloring model for network homophily. In this perspective, the value of any homophily score Θ, namely, a nondecreasing real-valued function in the sizes of subgraphs induced by the classes of the partition, evaluated at the observed outcome, can be thought of as the observed value of a random variable. Consequently, according to the score Θ, the input network is homophillic at the significance level α whenever the one-sided tail probability of observing a value of Θ at least as extreme as the observed one is smaller than α. Since, as we show, even approximating α is an NP-hard problem, we resort to classical tails inequality to bound α from above. These upper bounds, obtained by specializing Θ, yield a class of quantifiers of network homophily. Computing the upper bounds requires the knowledge of the covariance matrix of the random vector, which was not previously known within the random coloring model. In this paper we close this gap. Interestingly, the matrix depends on the input partition only through the cardinalities of its classes and depends on the network only through its degrees. Furthermore all the covariances have the same sign, and this sign is a graph invariant. Plugging this structure into the bounds yields a meaningful, easy to compute class of indices for measuring network homophily. As demonstrated in real-world network applications, these indices are effective and reliable, and may lead to discoveries that cannot be captured by the current state of the art.
Language	English
Publishing date	2023-12-19
Publishing country	United States
Document type	Journal Article
ZDB-ID	2844562-4
ISSN	2470-0053 ; 2470-0045
ISSN (online)	2470-0053
ISSN	2470-0045
DOI	10.1103/PhysRevE.108.054130
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Article ; Online: Transcription Factor Driven Gene Regulation in COVID-19 Patients.

Santoni, Daniele / Ghosh, Nimisha / Derelitto, Carlo / Saha, Indrajit

Viruses

2023 Volume 15, Issue 5

Abstract: SARS-CoV-2 and its many variants have caused a worldwide emergency. Host cells colonised by SARS-CoV-2 present a significantly different gene expression landscape. As expected, this is particularly true for genes that directly interact with virus ... ...

Abstract	SARS-CoV-2 and its many variants have caused a worldwide emergency. Host cells colonised by SARS-CoV-2 present a significantly different gene expression landscape. As expected, this is particularly true for genes that directly interact with virus proteins. Thus, understanding the role that transcription factors can play in driving differential regulation in patients affected by COVID-19 is a focal point to unveil virus infection. In this regard, we have identified 19 transcription factors which are predicted to target human proteins interacting with Spike glycoprotein of SARS-CoV-2. Transcriptomics RNA-Seq data derived from 13 human organs are used to analyse expression correlation between identified transcription factors and related target genes in both COVID-19 patients and healthy individuals. This resulted in the identification of transcription factors showing the most relevant impact in terms of most evident differential correlation between COVID-19 patients and healthy individuals. This analysis has also identified five organs such as the blood, heart, lung, nasopharynx and respiratory tract in which a major effect of differential regulation mediated by transcription factors is observed. These organs are also known to be affected by COVID-19, thereby providing consistency to our analysis. Furthermore, 31 key human genes differentially regulated by the transcription factors in the five organs are identified and the corresponding KEGG pathways and GO enrichment are also reported. Finally, the drugs targeting those 31 genes are also put forth. This in silico study explores the effects of transcription factors on human genes interacting with Spike glycoprotein of SARS-CoV-2 and intends to provide new insights to inhibit the virus infection.
MeSH term(s)	Humans ; COVID-19/genetics ; SARS-CoV-2 ; Transcription Factors/genetics ; Transcription Factors/metabolism ; Gene Expression Regulation ; Glycoproteins/genetics
Chemical Substances	Transcription Factors ; Glycoproteins
Language	English
Publishing date	2023-05-18
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2516098-9
ISSN	1999-4915 ; 1999-4915
ISSN (online)	1999-4915
ISSN	1999-4915
DOI	10.3390/v15051188
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Article: An immunological glimpse of human virus peptides: Distance from self, MHC class I binding, proteasome cleveage, TAP transport and sequence composition entropy

Santoni, Daniele / Felici, Giovanni

Virus research. 2022 Aug., v. 317

2022

Abstract	Adaptive immune response is triggered when specific pathogen peptides called epitopes are recognised as exogenous according to the paradigm of self/non-self. To be recognized by immune cells, epitopes have to be exposed (presented) on the surface of the cell. Predicting if a peptide is exposed is important to shed light on the rules that govern immune response and, thus, identify potential targets and design vaccine and drugs. We focused on peptides exposed on cell surface and made accessible to immune system through the MHC Class I complex. Before this can happen, three successive selection steps have to take place: a) Proteasome cleveage, b) TAP Transport, and c) binding to MHC-class I. Starting from a set of 211 host human reference viruses, we computed the set of unique peptides occurring in the correspondent proteomes. Then, we obtained the probability values of Proteasome Cleveage, TAP Transport and Binding to MHC Class I associated to those peptides through established prediction software tools. Such values were analysed in conjunction with two other features that could play a major role: the distance from self, strictly linked to the concept of nullomers, and the sequence entropy, measuring the complexity of the peptide amino acid composition. The analysis confirmed and extended previous results on a larger, more significant and consistent data set; we showed that the higher the distances from self, the higher the score of TAP Transport and binding to MHC class I; no significant association was instead found between distance from self and Proteasome Cleveage. Additionally, amino acid peptide composition entropy was significantly associated with the other features. In particular, higher entropies were linked with higher scores of Proteasome Cleveage, TAP Transport, Binding to MHC Class I, and higher distance from self. The relationship among the three selection steps provided evidence of a tight inter-correlation, clearly suggesting it could be the product of a co-evolutive process. We believe that these results give new insights on the complex processes that regulate peptide presentation through MHC class I, and unveil the mechanisms the allow the immune system to distinguish self and viral non-self peptides.
Keywords	adaptive immunity ; amino acid composition ; amino acids ; computer software ; data collection ; entropy ; epitopes ; humans ; immune response ; immune system ; peptides ; prediction ; probability ; proteasome endopeptidase complex ; proteome ; research ; vaccines ; vertebrate viruses ; viruses
Language	English
Dates of publication	2022-08
Publishing place	Elsevier B.V.
Document type	Article
ZDB-ID	605780-9
ISSN	1872-7492 ; 0168-1702
ISSN (online)	1872-7492
ISSN	0168-1702
DOI	10.1016/j.virusres.2022.198814
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