the time of writing, the NCBI database provides more than
200,000 entries for prokaryote genomic sequence data at different
assembly levels, covering almost 7000 species and including multiple strains of nearly all important pathogens (https://www.ncbi.
nlm.nih.gov/genome/microbes/). A clear example of that is the
causative agent of tuberculosis Mycobacterium tuberculosis, for
which more than 6000 assemblies can be accessed through public
databases, representing a significant global collection of circulating
strains. This flood of freely available genomic information provides
a powerful tool for large-scale genome analyses and pangenome
approaches to identify conserved vaccine antigens [2]. The term
pangenome refers to the entire genomic repertoire of a given
species or higher taxa and it includes both the genes shared by the
genomes of all strains (core genome) and the genes present only in
some strains of a species (accessory genome) [3, 4]. Consequently,
the panproteome is the full set of proteins that might be expressed
by a group of related organisms.
The process of conceiving vaccines starting from a pathogen’s
sequenced genome is largely known as reverse vaccinology
[5]. Nearly 20 years after the first reverse vaccinology study (Neisseria meningitidis serogroup B [6]), this approach has evolved with
a pangenome perspective toward the discovery of universal antigens
[2]. In pangenomic reverse vaccinology, high-throughput in silico
analyses of multiple genomic or proteomic data sets are performed
to identify features that might be predictive of conserved vaccine
candidates [7, 8]. A similar approach may also be applied to identify
vaccine candidates discriminating pathogenic and nonpathogenic
members of a same species or of related species, by performing a
subtractive proteomic analysis on the two groups [7, 9, 10]. The
panproteome of the pathogenic bacteria can also be compared to
the human proteome to exclude antigens that could lead to an
autoimmune cross-reaction [11]. Subtractive genomics and proteomics analyses along with reverse vaccinology approaches not only
enable the identification of pathogen-specific antigens but may also
support drug-target discovery projects [12]. The design and production of vaccines based on reverse vaccinology has been validated
by the introduction of a successful vaccine against Meningococcus
B strains [13]. This multicomponent vaccine contains three main
surface-associated protein antigens discovered by mining the
genome of N. meningitidis with a classical reverse vaccinology
approach. The antigens were initially selected in silico based on
their subcellular localization and validated in vivo for their ability
to elicit bactericidal antibodies and induce protection in an animal
model [6, 14].
With the progress of immunoinformatics [15], the shortlisting
of proteins on the basis of cellular localization and conservation has
been complemented with their screening for B- and/or T-cell
epitopes by various prediction algorithms. Many reverse
44
Daniel Yero et al.
200,000 entries for prokaryote genomic sequence data at different
assembly levels, covering almost 7000 species and including multiple strains of nearly all important pathogens (https://www.ncbi.
nlm.nih.gov/genome/microbes/). A clear example of that is the
causative agent of tuberculosis Mycobacterium tuberculosis, for
which more than 6000 assemblies can be accessed through public
databases, representing a significant global collection of circulating
strains. This flood of freely available genomic information provides
a powerful tool for large-scale genome analyses and pangenome
approaches to identify conserved vaccine antigens [2]. The term
pangenome refers to the entire genomic repertoire of a given
species or higher taxa and it includes both the genes shared by the
genomes of all strains (core genome) and the genes present only in
some strains of a species (accessory genome) [3, 4]. Consequently,
the panproteome is the full set of proteins that might be expressed
by a group of related organisms.
The process of conceiving vaccines starting from a pathogen’s
sequenced genome is largely known as reverse vaccinology
[5]. Nearly 20 years after the first reverse vaccinology study (Neisseria meningitidis serogroup B [6]), this approach has evolved with
a pangenome perspective toward the discovery of universal antigens
[2]. In pangenomic reverse vaccinology, high-throughput in silico
analyses of multiple genomic or proteomic data sets are performed
to identify features that might be predictive of conserved vaccine
candidates [7, 8]. A similar approach may also be applied to identify
vaccine candidates discriminating pathogenic and nonpathogenic
members of a same species or of related species, by performing a
subtractive proteomic analysis on the two groups [7, 9, 10]. The
panproteome of the pathogenic bacteria can also be compared to
the human proteome to exclude antigens that could lead to an
autoimmune cross-reaction [11]. Subtractive genomics and proteomics analyses along with reverse vaccinology approaches not only
enable the identification of pathogen-specific antigens but may also
support drug-target discovery projects [12]. The design and production of vaccines based on reverse vaccinology has been validated
by the introduction of a successful vaccine against Meningococcus
B strains [13]. This multicomponent vaccine contains three main
surface-associated protein antigens discovered by mining the
genome of N. meningitidis with a classical reverse vaccinology
approach. The antigens were initially selected in silico based on
their subcellular localization and validated in vivo for their ability
to elicit bactericidal antibodies and induce protection in an animal
model [6, 14].
With the progress of immunoinformatics [15], the shortlisting
of proteins on the basis of cellular localization and conservation has
been complemented with their screening for B- and/or T-cell
epitopes by various prediction algorithms. Many reverse
44
Daniel Yero et al.