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PreprintCited by 6vaccines and immunoinformatics approachesProtein Structure and DynamicsBiochemical and Structural Characterization

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Identification of potential molecular mimicry in pathogen-host interactions

Open access
Rich, Kaylee D., Srivastava, Shruti, Muthye, Viraj, Wasmuth, James D.·2023·PeerJ
DOI 10.1101/2023.06.14.544818PMC PMC10637249

Preprint — published as 10.7717/peerj.16339

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Abstract

Pathogens have evolved sophisticated strategies to manipulate host signaling pathways, including the phenomenon of molecular mimicry, where pathogen-derived biomolecules imitate host biomolecules. In this study, we used a sequence-based bioinformatics pipeline to identify potential molecular mimicry candidates between humans and 32 pathogenic species—bacteria, fungi, protozoa, and helminths—of global health importance. We observed considerable variation in the number of mimicry candidates across pathogenic species, with pathogenic bacteria exhibiting fewer candidates compared to fungi and protozoans. Further analysis revealed that the candidate mimicry regions were enriched in solvent-accessible regions, highlighting their potential functional relevance. We identified a total of 1878 mimicked regions in 1439 human proteins, and clustering analysis indicated diverse target proteins across pathogen species. The human proteins containing mimicked regions revealed significant associations between these proteins and various biological processes, with an emphasis on host extracellular matrix organization and cytoskeletal processes. However, immune-related proteins were underrepresented as targets of mimicry. Our findings provide insights into the broad range of host-pathogen interactions mediated by molecular mimicry and highlight potential targets for further investigation. This comprehensive analysis contributes to our understanding of the complex mechanisms employed by pathogens to subvert host defenses and promotes the development of novel therapeutic strategies.

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Figures

Figure 1 The mimicry identification pipeline used in our analysis. Descriptions for each step are included in the blue boxes.
Figure 1 The mimicry identification pipeline used in our analysis. Descriptions for each step are included in the blue boxes.CC BY · PubMed Central
Figure 2 Example of MPRs and MHRs, and how they relate to each other. Each region from a pathogen protein is paired with a region from a host protein: region A is paired with region E. A mimicking pathogen region (MPR) is the region comprised of all overlapping 14-mers from a single pathogen protein that aligned to any host protein during pathogen-host sequence filtering: MPR-1 is comprised of regions A and B. A mimicked host region (MHR) is all merged corresponding regions on a host protein and multiple regions may overlap on the same protein: MHR-2 is made up of regions F, G, and H. Mimicry regions can be shared between one or more proteins: MPR-1 is shared between two MHRs on one host protein. MHRs can also be shared between pathogen species: MHR-2 is shared between three pathogen proteins and two pathogen species.
Figure 2 Example of MPRs and MHRs, and how they relate to each other. Each region from a pathogen protein is paired with a region from a host protein: region A is paired with region E. A mimicking pathogen region (MPR) is the region comprised of all overlapping 14-mers from a single pathogen protein that aligned to any host protein during pathogen-host sequence filtering: MPR-1 is comprised of regions A and B. A mimicked host region (MHR) is all merged corresponding regions on a host protein and multiple regions may overlap on the same protein: MHR-2 is made up of regions F, G, and H. Mimicry regions can be shared between one or more proteins: MPR-1 is shared between two MHRs on one host protein. MHRs can also be shared between pathogen species: MHR-2 is shared between three pathogen proteins and two pathogen species.CC BY · PubMed Central
Figure 3 Illustration of Gene Ontology assignment between host and pathogen proteins. Each host protein assigned to a given GO term may contain an MHR which aligns to MPRs in proteins from one or more pathogen species. The number of associated pathogen species is obtained through identifying the pathogen proteins paired to each host protein mapped to the given term.
Figure 3 Illustration of Gene Ontology assignment between host and pathogen proteins. Each host protein assigned to a given GO term may contain an MHR which aligns to MPRs in proteins from one or more pathogen species. The number of associated pathogen species is obtained through identifying the pathogen proteins paired to each host protein mapped to the given term.CC BY · PubMed Central
Figure 4 Number of 14-mers with a hit to a human protein for each species coloured by group and number of identical amino acid residues.
Figure 4 Number of 14-mers with a hit to a human protein for each species coloured by group and number of identical amino acid residues.CC BY · PubMed Central
Figure 5 Number of paired pathogen-host regions before (blue) and after (red) QSASA filtering, coloured by alignment percent identity.
Figure 5 Number of paired pathogen-host regions before (blue) and after (red) QSASA filtering, coloured by alignment percent identity.CC BY · PubMed Central
Figure 6 Solvent accessibility of potential mimicry regions for selected pathogens. Histograms/KDE plots for average solvent accessibility of potential mimicry candidates from select pathogen species (A) and human proteins (B) with equivalent-length regions randomly selected from the complete pathogen proteome (grey) and from full-length protein HSPs (hatched). Vertical grey lines indicate 0.75 QSASA threshold. The plots for all pathogen-host pairs are shown in Figs. S1 and S2, and at https://github.com/Kayleerich/molecularmimicry/.
Figure 6 Solvent accessibility of potential mimicry regions for selected pathogens. Histograms/KDE plots for average solvent accessibility of potential mimicry candidates from select pathogen species (A) and human proteins (B) with equivalent-length regions randomly selected from the complete pathogen proteome (grey) and from full-length protein HSPs (hatched). Vertical grey lines indicate 0.75 QSASA threshold. The plots for all pathogen-host pairs are shown in Figs. S1 and S2, and at https://github.com/Kayleerich/molecularmimicry/.CC BY · PubMed Central
Figure 7 The proportion of host protein clusters associated with more than one pathogen species does not change with increased clustering. A cluster is considered associated with a pathogen species if a protein sequence from the species paired to at least one human sequence in the cluster. (A) Total number of host protein clusters associated with one or more pathogen species at each percent identity clustering value. Clustering increases from left to right. (B) Proportion of total clusters associated with one or more pathogen species for each clustering value. The dashed line represents an example of expected proportions for increased clustering if multiple pathogens were mimicking similar host proteins.
Figure 7 The proportion of host protein clusters associated with more than one pathogen species does not change with increased clustering. A cluster is considered associated with a pathogen species if a protein sequence from the species paired to at least one human sequence in the cluster. (A) Total number of host protein clusters associated with one or more pathogen species at each percent identity clustering value. Clustering increases from left to right. (B) Proportion of total clusters associated with one or more pathogen species for each clustering value. The dashed line represents an example of expected proportions for increased clustering if multiple pathogens were mimicking similar host proteins.CC BY · PubMed Central
Figure 8 Example of low complexity in mimicry regions. The MHR from Q9BVH7 overlaps an LCR by 60% and the LCR overlap is not necessarily equal length between pathogen and human proteins. Proteins are referred to by Uniprot ID, mismatched residues from MPR to MHR are coloured grey.
Figure 8 Example of low complexity in mimicry regions. The MHR from Q9BVH7 overlaps an LCR by 60% and the LCR overlap is not necessarily equal length between pathogen and human proteins. Proteins are referred to by Uniprot ID, mismatched residues from MPR to MHR are coloured grey.CC BY · PubMed Central
Figure 9 Removing MHRs comprised of more than 50% LCR removes most MHRs which were aligned to MPRs from more than one pathogen species. In these examples, the human proteins contain multiple MHRs. O60346 contains three MHRs which pair with up to ten MPRs from five pathogen species, Q8WUF5 contains two MHRs paired with up to five MPRs from five pathogen species, and Q99700 contains three MHRs paired with up to eight MPRs from seven pathogen species. After filtering out MHRs comprised of 50% or more LCR, the number of MHRs drops to one for all human proteins and eliminates all MHRs paired to more than two MPRs.
Figure 9 Removing MHRs comprised of more than 50% LCR removes most MHRs which were aligned to MPRs from more than one pathogen species. In these examples, the human proteins contain multiple MHRs. O60346 contains three MHRs which pair with up to ten MPRs from five pathogen species, Q8WUF5 contains two MHRs paired with up to five MPRs from five pathogen species, and Q99700 contains three MHRs paired with up to eight MPRs from seven pathogen species. After filtering out MHRs comprised of 50% or more LCR, the number of MHRs drops to one for all human proteins and eliminates all MHRs paired to more than two MPRs.CC BY · PubMed Central
Figure 10 Alignments of select mimicry candidates. (A) Alignment of identified MPRs from four P. falciparum PfEMP1 proteins to the MHR of vitronectin. (B) Alignment of identified MPRs from two T. cruzi proteins to human ADAM15. Dashed boxes indicate the individual pathogen regions identified.
Figure 10 Alignments of select mimicry candidates. (A) Alignment of identified MPRs from four P. falciparum PfEMP1 proteins to the MHR of vitronectin. (B) Alignment of identified MPRs from two T. cruzi proteins to human ADAM15. Dashed boxes indicate the individual pathogen regions identified.CC BY · PubMed Central

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Cites

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Metadata

Authors
Rich, K. D., Srivastava, S., Muthye, V., & Wasmuth, J. D.
Affiliations
University of Calgary (CA)
Corresponding author
Wasmuth, James D.
ORCID
Venue
PeerJ
Publisher
openRxiv
Published
2023-06-15
Volume
11
Pages
e16339-e16339
ISSN
2167-8359 (ISSN-L)
DOI
10.1101/2023.06.14.544818
PMC
PMC10637249
OpenAlex
W4388458284
Cited by
6
References
2
Citations by year
2026: 2 · 2025: 2 · 2024: 1 · 2023: 1
FWCI
0.53
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • PeerJ (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • University of Calgary
  • Natural Sciences and Engineering Research Council of Canada (#04589-2020)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biochemical and Structural Characterization
Keywords
molecular mimicry, host-pathogen interaction, protein structure prediction, extracellular matrix organization, immune evasion, therapeutic target, bioinformatics pipeline
MeSH terms
Bacteria, Humans, Molecular Mimicry, Computational Biology, Proteome, Host-Pathogen Interactions

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