3. Results and discussion
3.1. The approach
To explore and determine the variety of post-translational modifications
(PTMs) present on proteins in human dry blood spots, a comprehensive
analysis was conducted. The dataset consisted of a large number of scans
(95516) and features (262910) obtained from the samples. Table 2
provides an overview of the data statistics, showcasing the abundance of
information captured in the analysis.
The results show that a total of approximately 3,374 unique peptides
were identified in the study. Of the 3,374 peptides identified, they
corresponded to approximately 354 different protein groups corresponding
to 151 unique proteins ( Sup Table 2).The list of 151 proteins includes
various molecules involved in important biological processes such as
neutrophil aggregation, fibrinolysis, and complement activation via the
alternative pathway. Neutrophil aggregation refers to the process by
which neutrophils, a type of white blood cell, come together and form
aggregates. This process plays a crucial role in the immune response,
particularly in the context of inflammation and host defense against
pathogens. The proteins in this list likely contribute to the molecular
mechanisms underlying neutrophil aggregation, facilitating their proper
function in immune responses.
Fibrinolysis is the process of breaking down fibrin, a protein involved
in blood clot formation, to prevent excessive clotting and promote the
dissolution of existing clots. The proteins in this list are likely
involved in regulating the fibrinolysis process, which is essential for
maintaining proper hemostasis and preventing thrombotic disorders.
Complement activation via the alternative pathway is one of the pathways
through which the complement system, a part of the immune system, can be
activated. The alternative pathway provides an immediate response to
invading pathogens and contributes to the elimination of microbial
infections. The proteins in this list likely participate in the
activation and regulation of the alternative pathway, enabling effective
immune responses against pathogens.
In total, 976 modified peptides were identified across the samples. Each
PTM was further manually validated through PTM-specific neutral loss and
a, b and/or y fragmentation ions series. Notably, Carbamidomethylation
emerged as the most prevalent PTM, which is expected given the sample
preparation method involving derivatization for trypsin digestion. The
identification of numerous Carbamidomethylation peptides reinforces the
robustness of the analysis. Interestingly, it was found that half of the
proteins exhibited more than one modification, indicating the complexity
and diversity of PTMs in the human dry blood spot proteome (Sup Table
3). Figure 2 illustrates that approximately 46% of the proteins showed
additional modifications, including formylation or deamidation. These
findings highlight the presence of multiple layers of protein
modifications in the analyzed samples, suggesting intricate regulatory
mechanisms at play.
The characterization of PTMs in the human dry blood spot proteome not
only provides valuable insights into the complexity of protein
modifications but also offers potential avenues for understanding their
functional implications and their association with various physiological
and pathological processes. Further investigations are warranted to
elucidate the specific roles and clinical relevance of these PTMs,
paving the way for their potential application as biomarkers and
therapeutic targets in the future.
3.2. PTMs in the samples
The analysis of PTMs in the samples revealed a diverse array of
modifications present on proteins. Among the identified PTMs, several
were found to be highly representative across all samples (Sup Table).
These PTMs contribute to the functional diversity and complexity of the
proteome in the human dry blood spot. One of the prominent PTMs observed
was Carbamidomethylation, which was consistently detected in the
majority of proteins. This modification involves the addition of a
carbamidomethyl group to cysteine residues, thereby stabilizing the
protein structure and preventing oxidation. Carbamidomethylation in
conjunction with other PTMs such as Acetylation (K), Deamidation (NQ),
and Oxidation (M) was also observed, indicating the presence of complex
modification patterns on the proteins. Another notable PTM observed was
Formylation, which involves the addition of a formyl group to certain
amino acid residues. This modification has been associated with various
biological processes, including protein degradation and immune
responses. Additionally, Deamidation (NQ) was found to be prevalent,
which results in the conversion of asparagine (N) and glutamine (Q)
residues to aspartic acid (D) and glutamic acid (E), respectively. Other
PTMs identified in the analysis included Methylation (KR), Acetylation
(N-term), Pyro-glu from E and Q, Oxidation (HW and M), Tryptophan
oxidation to kynurenin, and various other modifications such as
Acetaldehyde, Carboxyethyl, Propionaldehyde, Sulphone, and Quinone (Sup
Table). These PTMs contribute to the structural and functional diversity
of proteins, potentially influencing their stability, enzymatic
activity, and molecular interactions.
The presence of multiple modifications on proteins, as well as the
variety of PTMs observed, underscores the intricate nature of protein
regulation and signaling in the human dry blood spot proteome. Further
exploration of these modifications and their functional implications
will deepen our understanding of their roles in physiological and
pathological processes, and may lead to the discovery of novel
biomarkers and therapeutic targets.
Citrullination, for example, is a PTM known as deamidation, which is
observed in ~11% of cases and involves the conversion
of the amino acid arginine to citrulline by the hydrolysis of nitrogen
atoms in one of its side chains. In this irreversible PTM, the guanidium
group of the arginine residue is converted to a ureido group.
The reaction leads to the production of the non-standard amino acid
citrulline, ammonia release and the loss of a positive charge with a
monoisotopic mass contrast of +0.984016, lowering the overall charge of
the protein each time the reaction takes place
[17]. This irreversible modification
leads to the loss of a positive charge and the production of a
non-standard amino acid, citrulline. Tandem analysis MS (MS /MS) was
used to verify the presence of deamidation in the identified peptides.
By examining the fragmentation pattern of the peptide ions,
characteristic fragments indicative of deamidation can be identified.
Manual inspection also revealed that the Cit effect was the most
prominent fragmentation pathway when Cit was followed by a His or Pro
residue, which is due to an additive His and Pro effect leading to
suppressed fragment ion intensity for other ions
[18]. The enzymatic reaction
responsible for citrullination is catalyzed by a group of enzymes called
peptidylarginine deiminases (PADs), which are calcium-dependent and
include PAD 1-4 and PAD 6 in the human body
[19]. The conversion of arginine to
citrulline during citrullination has significant implications for
protein properties. Citrullination reduces the overall charge of the
protein and affects its isoelectric point, hydrogen bonding capacity,
and charge distribution. Additionally, citrullination can increase the
local and global hydrophobicity of the modified peptide, potentially
influencing protein folding, polarity, and susceptibility to enzymatic
degradation [20]. Physiologically,
citrullination is involved in various processes such as gene regulation,
apoptosis, epidermal terminal differentiation, immune system functions,
and skin physiology. It has been implicated in several diseases,
including multiple sclerosis, rheumatoid arthritis, Alzheimer’s disease,
cancer, central nervous system disorders, and cardiovascular disease.
Citrullinated proteins have been identified in cellular proteins like
histones, vimentin, and filaggrin, as well as extracellular matrix
proteins such as collagens. The association between citrullination and
these diseases highlights the role of this PTM in disease pathogenesis
[21,
22]. Furthermore, emerging research
suggests that citrullination may have implications in epigenetic
regulation, as it can directly modify histones or interact with
citrullinated histone-modifying enzymes and coactivators
[23]. The physiological significance
and involvement of citrullination in both normal and pathological
conditions underscore its importance in cellular processes and disease
mechanisms. Ongoing research continues to explore the biological roles
of citrullinated proteins, the pathologies associated with
citrullination, and the methodologies employed for their enrichment and
detection [19,
24-27].
In this study, we aimed to demonstrate the effectiveness of our strategy
by analyzing samples from patients with coronary arterial disease (CAD).
By focusing on scientific research, we identified several genes, namely
TGM2, PON1, APEH, ANK1, HSPA8, APOC1, YWHAZ, NME1, and FBXO7, that have
been implicated in various aspects of CAD. TGM2 is associated with CAD
due to its involvement in the formation of advanced glycation end
products (AGEs) and the remodeling of the extracellular matrix. These
processes are linked to atherosclerosis and plaque
stability[28].
In addition, HSPA8, also known as Hsc70, is a heat shock protein
involved in protein folding. Its association with CAD stems from its
involvement in cellular stress responses, as well as its potential roles
in inflammation and plaque formation. The presence of HSPA8 in CAD
suggests that it may play a role in the pathogenesis of the disease.
Furthermore, FBXO7 is another gene associated with CAD. It is linked to
CAD risk factors such as blood pressure regulation and inflammation,
indicating its potential involvement in the development and progression
of CAD[29]. Moreover, APOC1, a
component of lipoproteins, has also been linked to CAD. Its involvement
in lipid metabolism, inflammation, and regulation of cholesterol
transport suggests that it may contribute to the development of
atherosclerosis and the progression of CAD. These genes, including
HSPA8, FBXO7, and APOC1, highlight the multifactorial nature of CAD and
emphasize the complex interplay of various biological processes in the
pathogenesis of the disease. Further research is needed to fully
elucidate the specific mechanisms by which these genes contribute to CAD
and to explore their potential as therapeutic
targets[30],[31].Additionally,
PON1, an enzyme associated with HDL particles, has been linked to CAD
due to its crucial role in the metabolism of oxidized lipids. This
metabolic process contributes to the development of atherosclerosis, a
key factor in CAD progression.
Moreover, APEH (Acylpeptide hydrolase) has been suggested to play a
significant role in CAD. It exerts its influence by influencing peptide
metabolism and modifying the stability and accumulation of
atherosclerotic plaques[32]. APEH’s
involvement in these processes highlights its potential contribution to
the pathogenesis of CAD.
The inclusion of PON1[33] and APEH in
the list of implicated genes emphasizes the diverse molecular mechanisms
underlying CAD development. These findings underscore the complex
interplay of lipid metabolism, peptide metabolism, and plaque formation
in the pathophysiology of CAD. Further research is necessary to deepen
our understanding of the precise roles of PON1 and APEH and their
potential as therapeutic targets for CAD management.
Furthermore, variants of ANK1 have been linked to CAD risk factors,
including elevated levels of LDL cholesterol and triglycerides. The
alterations in ANK1 can also have an impact on red blood cell
morphology, which has the potential to affect blood flow. These
associations highlight the significance of ANK1 in the pathogenesis of
CAD, shedding light on the influence of lipid metabolism and blood cell
characteristics in the development of the
disease[34]. In addition, YWHAZ has
been implicated in CAD due to its involvement in signaling pathways
associated with vascular smooth muscle cell proliferation and migration.
These cellular processes play a crucial role in the development of
atherosclerosis, a hallmark of CAD. The participation of YWHAZ in these
signaling pathways underscores its potential contribution to the
pathogenesis of CAD[35].
The inclusion of ANK1 and YWHAZ among the genes implicated in CAD
emphasizes the multifaceted nature of the disease, involving lipid
metabolism, blood cell characteristics, and cellular signaling.
Understanding the precise mechanisms by which ANK1 and YWHAZ contribute
to CAD progression can provide valuable insights for the development of
targeted therapies and interventions. Further research is warranted to
uncover the full extent of their roles in CAD and their potential as
therapeutic targets. It is important to note that while these genes have
demonstrated associations with CAD, the specific mechanisms through
which they contribute to the disease are still under investigation.
Further research is necessary to fully comprehend their roles and
potential therapeutic implications in CAD.
Glycosylation, as a major posttranslational modification (PTM), plays a
critical role in shaping protein function, stability, and interactions
and is therefore an interesting area for disease-related studies.
Previous successes in identifying different glycosylation patterns, such
as monosaccharides linked to different sugars (topoisomers, e.g.,
triantennary GlcNAc or bisecting GlcNAc), and variations in linkage
positions (linkage isomers, e.g., α2-3-sialic acid versus α2-6-sialic
acid), have highlighted their potential importance in proteomic
studies[36]. However, despite efforts
to look for such glycosylation patterns in this study, the results did
not yield positive results. It is possible that the use of a relatively
small volume of DBS (10 μl) may have contributed to the lack of
glycosylation results[37].
To investigate the potential effects of PTMs and their relevance to CAD,
volcano plot analysis was performed, as shown in Table 3 and Figure 4.
The aim of volcano plot analysis was to identify proteins that showed
changes in abundance in the DBS samples associated with CAD. These
scatter plots were generated by plotting the log2 fold change in protein
abundance against the negative logarithm (base 10) of the p value, which
allowed visualization of statistically significant changes in a large
proteomic dataset (Figure 4). Considering fold-change variations with a
p-value of less than 0.05, a total of 42 peptides were identified that
differed significantly in abundance. These peptides, along with their
corresponding proteins, are detailed in Table 3. Volcano plot analysis
provided valuable insights into the differential expression of proteins
in DBS samples with CAD, which may shed light on the involvement of PTMs
in disease development. The statistically significant changes observed
in these proteins highlight their potential as candidates for further
investigation as biomarkers or mechanistic players associated with CAD.
These results highlight the power of volcano diagram analysis in
proteomic studies, particularly with large data sets, and underscore the
importance of understanding PTMs in the context of disease processes.
Further studies and validation efforts are warranted to confirm and
explore the functional implications of these identified PTMs in the
context of CAD and their potential clinical relevance.
In our study, we observed the presence of deamidation in the peptide
serotransferrin at the peptide K.IMN(+.98)GEADAMSLDGGFVYIAGK.C. This
finding is consistent with the phenomenon of asparagine deamidation
known to occur during protein aging and/or oxidative stress. During
asparagine deamidation, asparagine residues are converted to aspartic
acid or isoaspartic acid, resulting in changes in the overall charge
states of proteins [38]. In
particular, deamidation of specific residues, such as Asn-943 in protein
Cp (ceruloplasmin), has been associated with oxidative stress-induced
changes that may affect its ferroxidase activity. This highlights the
potential functional implications of deamidation events in proteins
[39].
While the clinical and diagnostic application of mass spectrometry (MS)
for post-translational modification (PTM) detection has experienced
significant advancements [40], it is
important to acknowledge the existing caveats and recognize the
opportunities for further progress in mass spectrometry-based clinical
investigations. One major caveat is the challenge posed by sample
preparation, which remains a labor-intensive process prone to variations
in concentration and matrix background. These variations introduce
complexity and potential bias into the analysis, limiting the
reliability and reproducibility of results. Additionally, a considerable
amount of operating time for mass spectrometers is dedicated to
maintenance tasks such as cleaning and regenerating high-performance
liquid chromatography (HPLC) columns. This maintenance requirement
reduces instrument productivity and hampers the throughput of mass
spectrometry-based clinical investigations. Moreover, the data analysis
of mass spectrometric spectra is a highly complex and time-consuming
task that demands the expertise of experienced operators. Current
biostatistical tools available for PTM-centric mass spectrometric data
analysis are primarily designed for scientific applications and lack
universal applicability, reproducibility, automation, and high
throughput [41]. This limitation
impedes the clinical translation of mass spectrometry-based diagnostic
approaches, as it hinders the efficient and standardized analysis of
data. However, these caveats also present opportunities for improvement
and advancement in mass spectrometry-based clinical investigations.
Significant efforts should be directed towards the automation of sample
preparation processes, reducing labor intensity and enhancing the
reproducibility of results. Furthermore, the development of standardized
protocols and regulatory adaptations can optimize mass spectrometer
instrument usage, minimizing idle time and increasing overall
productivity. To address the challenges associated with data analysis,
there is a need for the development of advanced biostatistical tools
specifically tailored for PTM-centric mass spectrometric data analysis
in clinical settings. These tools should prioritize universal
applicability, reproducibility, automation, and high throughput
capabilities. By streamlining and standardizing the data analysis
process, the clinical translation of mass spectrometry-based diagnostic
approaches can be facilitated.