Secretome analysis and virulence assessment in Abiotrophia defectiva

Abstract

Background

Abiotrophia defectiva, although infrequently occurring, is a notable cause of culture-negative infective endocarditis with limited research on its virulence. Associated with oral infections such as dental caries, exploring its secretome may provide insights into virulence mechanisms. Our study aimed to analyze and characterize the secretome of A. defectiva strain CCUG 27639.

Methods

Secretome of A. defectiva was prepared from broth cultures and subjected to mass spectrometry and proteomics for protein identification. Inflammatory potential of the secretome was assessed by ELISA.

Results

Eighty-four proteins were identified, with diverse subcellular localizations predicted by PSORTb. Notably, 20 were cytoplasmic, 12 cytoplasmic membrane, 5 extracellular, and 9 cell wall-anchored proteins. Bioinformatics tools revealed 54 proteins secreted via the ‘Sec’ pathway and 8 via a non-classical pathway. Moonlighting functions were found in 23 proteins, with over 20 exhibiting potential virulence properties, including peroxiredoxin and oligopeptide ABC transporter substrate-binding protein. Gene Ontology and KEGG analyses categorized protein sequences in various pathways. STRING analysis revealed functional protein association networks. Cytokine profiling demonstrated significant proinflammatory cytokine release (IL-8, IL-1β, and CCL5) from human PBMCs.

Conclusions

Our study provides a comprehensive understanding of A. defectiva‘s secretome, laying the foundation for insights into its pathogenicity.

Keywords:

• Abiotrophia defectiva
• infective endocarditis
• secretome
• proteomics
• oral infections

Introduction

Abiotrophia defectiva, is part of the normal human oral microbiota, and urogenital &intestinal tracts [1]. Although a commensal, the pathogenic potential of A. defectiva has been reported [2]. It is a species of clinical significance, contributing to infective endocarditis with potentially devastating consequences albeit occurring infrequently [3–6] and has also been involved in various disease processes such as cerebral abscess, pancreatic abscess, corneal ulcer, sinusitis, osteomyelitis, scrotal abscess [1] and aortitis [7]. Its pathogenic role in oral diseases also, like caries [8,9] and orthodontic infections [10,11] cannot be overlooked. This relatively unknown bacterium is frequently associated with infections resulting from dental procedures [3]. It is pleomorphic on Gram stain [12], difficult to isolate, and characterized by its growth requiring complex media enriched with pyridoxal (vitamin B6) or cysteine or as small satellite colonies supported by helper bacteria [3]. These characteristics of A. defectiva contribute to some cases of culture-negative endocarditis and underestimate its pathogenic role [13].

Protein secretion is an essential mechanism utilized by bacteria for their growth and survival. It also serves multiple functions in enhancing its virulence, including facilitating attachment to host cells, acquiring resources from the environment, and directly disrupting the functions of the target cells. The pathogens employ dedicated protein secretion systems for the extracellular transfer of their cytosolic virulence factors into the host cell or host environment. Due to distinct cell wall structures, Gram-positive and Gram-negative bacteria possess different mechanisms for extracellular protein secretion. Gram-positive bacteria mainly employ both, the general secretory system (Sec) and the Twin-arginine transport (Tat) pathways to transport proteins across the cytoplasmic membrane while Gram-negative bacteria use more complex secretory systems (Type I to Type VIII). However, in many cases, these transport mechanisms alone are insufficient to deliver proteins to their final destinations. Consequently, pathogens employ conserved mechanisms of protein secretion to transport important virulence factors extracellularly during an infection [14].

The protein secretion mechanisms of Abiotrophia species are not well understood. However, a closely related species, Granulicatella elegans has been reported to secrete arginine deiminase, which inhibits the proliferation of human peripheral blood mononuclear cells (PBMCs) in vitro through citrullination [15] and impede the surface attachment of certain dental plaque bacteria in biofilms [16], suggesting a potential association of G. elegans with the pathogenesis of dental and certain systemic diseases. It is a well-established fact that the bacteria causing endocarditis interact with proteins of the extracellular matrix (ECM) during adhesion and colonization of damaged heart valves [17,18]. In vitro studies have investigated the ability of Abiotrophia and Granulicatella isolates to bind to certain ECM proteins, such as, fibrinogen, fibronectin, collagen and laminin, aiming to explore if variations in binding abilities could explain differences in clinical behavior of these strains [19]. In our recently published similar kind of investigation, the secretome of G. adiacens was analyzed and functionally characterized in addition to obtaining a preliminary information on the induction of immunoinflammatory response [20]. The findings have generated interest in exploring similar secretome analyses in close phylogenetic relative like A. defectiva to understand the possible pathogenic mechanisms in such bacteria.

Here, we investigated and functionally characterized the secretome of extracellularly released proteins from A. defectiva. Further, we examined the cytokine production and immune-stimulatory effect of these extracellular proteins on human peripheral blood mononuclear cells (PBMCs).

Methods

The procedures employed in this study for the methods described under sections 2.1, 2.2, 2.3, 2.4, 2.7, 2.9, 2.11, and Gene Ontology Analysis in 2.10, adhered closely to the protocols outlined in the prior work [20]. An overview of these methods is presented here.

Bacterial culture

A. defectiva CCUG 27,639 was cultured on chocolate blood agar for 48 hours at 37°C with 5% CO₂ in the air. The medium was supplemented with 0.001% pyridoxal hydrochloride [21].

Extracellular protein (ECP) release

A. defectiva grown on chocolate blood agar was inoculated into 5 ml of brucella broth supplemented with 0.001% pyridoxal hydrochloride and incubated at 37°C with 5% CO₂ in air, alongside a no-bacteria control. After 24 hours of incubation, the broth culture was centrifuged (5000 ×g, 5 min), separating ECP-containing supernatant which was subsequently filtered through a sterile 0.2 µm filter to remove residual bacterial cells.

Preparation of the secretome

The ECP (secretome) obtained in broth culture supernatant were isolated by tri-chloroacetic acid (TCA) precipitation method as described earlier [22]. Briefly, 100% w/v TCA was mixed with the secretome-containing supernatant in 1:4 ratio and incubated at −20°C for 30 minutes. Ultracentrifugation at 14,000 ×g for 20 minutes at 4°C yielded the secretome pellet which was subjected to two acetone washes (0.5 ml each) and air-drying in a fume hood. The protein samples were then diluted to 0.5 ml with lysis buffer for desalting, washed thrice by ultrafiltration (14,000 ×g for 15 minutes at 4°C), and finally eluted by centrifugation at 1000 ×g for 2 min at 4°C.

Preparation of the whole cell protein (WCP)

A. defectiva colonies from chocolate blood agar plates were PBS-washed and centrifuged at 5000 ×g for 5 minutes. The resulting pellet was resuspended in lysis buffer (1 mg/ml lysozyme and 1 mM phenyl methyl sulfonyl fluoride) and incubated for 4 h at 4–8°C. Subsequently, the sample was subjected to eight cycles of sonication at a pulse rate 40 in Omni Ruptor, followed by centrifugation at 10,000 ×g for 10 minutes at 4°C. This WCP of A. defectiva was used as a comparative control in western blot analysis against the ECP extract.

SDS-PAGE and gel image analysis

Samples for SDS-PAGE were prepared by denaturing proteins in 2× loading buffer at 100°C for 5 min, followed by centrifugation at 5000 ×g for 5 min. Five µg protein samples loaded in each well of the gel were separated on 12% SDS-PAGE at a constant 120 V and detected by both, coomassie blue and silver staining (Pierce Silver Stain Kit). Gel pictures were captured on Syngene G: Box Imaging System. Protein banding patterns and molecular weights of the bands were determined using GeneSys tools software. Duplicate SDS-PAGE gel was prepared in parallel for western blot analysis.

Western blot analysis

To validate that A. defectiva cells were not lysed and that the cellular proteins were not released in the secretome (ECP) preparations, we conducted western blot analysis on both ECP and WCP preparations. Briefly, the protein transfer from the gel to a PVDF membrane was achieved using Trans-Blot® Turbo^TM transfer system (Bio-Rad). Subsequently, the membrane was blocked overnight at 4°C with 5% skimmed milk to prevent any non-specific binding. The primary antibody targeting the cytoplasmic marker protein, Ftsz (Filamenting temperature sensitive mutant z) (Agrisera AB, Sweden), was employed followed by enzyme conjugated secondary antibody and chemiluminescent substrate. The images were captured using the G:Box Imaging System (Syngene).

Protein analyses & identification

Extracellular protein samples were lyophilized, and proteomics analysis was done by using a nanoLC-ESI-MS/MS mass spectrometer (Proteome Factory AG, Germany). MS/MS ion search of the Mascot search engine (Matrix Science, England) and NCBI-nr (National Centre for Biotechnology Information, USA) protein database were used for identification of proteins.

Nano-liquid chromatography-electrospray ionization-tandem mass spectrometry (nanoLC-ESI-MS/MS)

The composition of proteins in the A. defectiva secretome was determined using nanoLC-ESI-MS/MS by Proteome Factory (Proteome Factory AG, Berlin, Germany). With an Agilent 1100 nanoHPLC system (Agilent, Waldbronn, Germany) interfaced to an Orbitrap Velos (Thermo Scientific, Bremen, Germany) via a nanoelectrospray ion source. After pooling replicate samples from preparations, proteins were reduced, alkylated and digested by trypsin (Promega, Mannheim, Germany). Then, 400 ng of the resulting peptides were subjected to the nanoLC-ESI-MS/MS. 1% acetonitrile/0.5% formic acid was used as eluent for 5 minutes to trap and desalt the peptides on the enrichment column (Zorbax 300SB-C18, 0.3 × 5 mm, Agilent). A water/acetonitrile (both supplemented with 0.1% formic acid) gradient from 5% to 40% acetonitrile was then used within 120 minutes to separate the peptides on a Zorbax 300SB-C18, 75 µm x 150 mm column (Agilent). The mass spectrometer automatically recorded mass spectra, and tandem mass spectra were data-dependently acquired for multiply charged ions. Protein identification was made using the Mascot search engine (Matrix Science, London, England) against the bacterial subset of the RefSeq protein database (National Center for Biotechnology Information), (downloaded on NaN Invalid Date , 49867978 entries, NCBI, Bethesda, USA) and a database with common protein contaminants. For MS/MS spectra where assignment of the precursor ion’s charge state was missing, search parameters for ions from ESI-MS/MS data acquisition was set to ‘2+, 3+ or 4+’ according to the instrument’s and method’s standard charge state distribution. The search parameters were: Fixed modifications: Carbamidomethyl (C); variable modifications: Deamidated (NQ), Oxidation (M); Peptide Mass Tolerance: ±3 ppm; Fragment Mass Tolerance: ±0.6 Da; Missed Cleavages: 2. The inclusion criterion was: peptides that match with a score of 20 or above. Mass spectrometry data has been submitted to ‘PRIDE Archive’ (https://www.ebi.ac.uk/pride/archive/) repository with the project accession number PXD015631. The data files can be accessed with the username [email protected] and password: gCB24pty.

Bioinformatics analyses of the secreted proteins

Protein sequences of the secreted proteins obtained from Liquid Chromatography-Mass Spectrometer (LC-MS) analysis of the A. defectiva secretome were analyzed by an in silico 2-dimensional electrophoresis (2-DE) tool. For this, a theoretical (2-DE) image was obtained by using the software JVirGel, version 2.0 (http://www.jvirgel.de/index.html) [22]. The software creates and visualizes virtual two-dimensional (2D) protein gels based on the migration behavior of proteins in dependence of their theoretical molecular weights in combination with their calculated isoelectric points.

The signal peptides, transmembrane topology and subcellular localization of the secreted proteins were determined by using SignalP version 5.0 (http://www.cbs.dtu.dk/services/SignalP/) [23], Phobius (http://phobius.sbc.su.se/) [24], and PSORTb version 3.0.2 (http://www.psort.org/psortb/) [25]. Interpretation of results was done based on a most-votes approach. SignalP was utilized to predict proteins secreted via the general Secretion route (Sec-pathway) [26]. Proteins secreted via Twin-arginine translocation (Tat) pathway were predicted by TatP (http://www.cbs.dtu.dk/services/TatP/) [27] and TatFind (http://signalfind.org/tatfind.html) [28] tools. To identify proteins secreted via non-classical secretory system, SecretomeP 2.0 was used (http://www.cbs.dtu.dk/services/SecretomeP/) [29] and Proteins that were positive for signal peptides were not taken into account. To identify lipoproteins, lipoboxes were searched using the prediction tools LipoP (http://www.cbs.dtu.dk/services/LipoP/) and PRED-LIPO (http://bioinformatics.biol.uoa.gr/PRED-LIPO/input.jsp) [30]. Transmembrane alpha helices were predicted combining the tools TMHMM v2.0 (http://www.cbs.dtu.dk/services/TMHMM/) [31], SVMtm (http://ccb.imb.uq.edu.au/svmtm/) [32], and SOSUI (http://harrier.nagahama-i-bio.ac.jp/sosui/sosuiG/sosuigsubmit.html) [33]. MultitaskProtDB (http://wallace.uab.es/multitask) and Moonprot (http://www.moonlightingproteins.org/) were used for identifying ‘moonlighting proteins’ in the A. defectiva secretome [34]. Proteins identified as hypothetical by nr protein database (National Center for Biotechnology Information, USA) were further analysed by using NCBI Conserved Domains Database (CDD) [35].

Functional annotation of the secreted proteins were checked by assigning Gene Ontology (GO) IDs and protein names using ‘WEGO’ (http://wego.genomics.org.cn/) tool [36] and the Blast2GO program. KEGG Pathway Database (http://www.genome.jp/kegg/pathway.html) and KEGG Mapper (http://www.genome.jp/kegg/mapper.html) were used to predict the proteins with enzymatic functions that are possibly linked to metabolic pathways. Potential virulence proteins were predicted using ‘VirulentPred’ software (http://203.92.44.117/virulent/) [37], and the Virulece Factor DataBase (VFDB) (http://www.mgc.ac.cn/VFs/) [38]. Further, the functional protein association networks were used to group the secreted proteins through STRING (https://string-db.org/) [39].

Stimulation of PBMCs with extracellular (ECPs) and whole cell proteins (WCPs)

PBMCs were isolated using Ficoll-Paque density gradient centrifugation method [40]. Isolated PBMCs were stimulated with different concentrations (10, 25, 50, and 100 µg/ml) of extracellular and whole-cell proteins of A. defectiva for 24 h. For this, 0.45 ml of PBMCs (10⁶ mL⁻¹) in RPMI medium were added to 0.05 ml extracellular/whole cell proteins of A. defectiva in each well and incubated for 24 h at 37°C in 5% CO₂ in air for stimulation. Well containing PBS without protein samples and with PBMCs in RPMI medium was used as negative control.

ELISA based quantification of selected cytokines

Proinflammatory cytokines Human IL-8, IL-1β/1F2, CCL5/RANTES were quantified in extracellular and whole-cell protein stimulated PBMC samples using cytokine specific ELISA immunoassay kits (Quantikine® ELISA R&D systems). A cytokine specific monoclonal antibody pre-coated ELISA plate employing the quantitative sandwich enzyme immunosorbent assay (ELISA) technique was used. Standards, samples and controls were pipetted into the wells of ELISA plate and to allow the specific cytokine in the sample to be bound by the specific immobilized antibody on the bottom of the well, the plate was incubated at room temperature for 2 hours. Wells were washed with wash buffer to remove unbound substances (ImmunoWash^TM 1575 microplate washer) and an enzyme-linked polyclonal antibody specific for cytokine of interest was added to the wells. Washing steps were followed to remove any unbound antibody-enzyme reagent and then a substrate solution was added to the wells. The color development was stopped by terminating the enzyme-substrate reaction using stop solution and the intensity of the color developed in proportion to the amount of bound cytokine of interest was measured in microplate reader (iMark^TM, Biorad).

Statistics

Data from cytokine quantification was tested for normal distribution by Skewness and Kurtosis values, Shapiro Wilkins p values and histograms. Student t-test was used to compare the means between the groups. SPSS vs 23 for Windows used for the analysis.

Results

Analysis of the secretome of A. defectiva

By subjecting the secretome of A. defectiva to analysis by LC-MS/MS and conducting a database search in NCBI-nr, a total of 84 proteins were identified (Figure 1a, Table S1). Theoretical mapping of these secretome proteins onto a 2DE map shown in Figure 1b indicated a molecular weight distribution ranging from 11.04 kDa to 105.08 kDa, with clustering based on predicted isoelectric points (pI). Most proteins were clustered within a pI range of 3.94 to 9.44. To ascertain that the identified proteins in the secretome preparation did not originate from bacterial cell lysis, a western blot analysis was performed, wherein Fts-Z protein was utilized as a cytoplasmic lysis marker. The results, as depicted in Figure 1c, clearly demonstrated the presence of Fts-Z protein in the whole-cell protein (WCP) and not in the secretome/extracellular protein (ECP). Additionally, bacterial viability was confirmed by plating a 24-hour broth culture during the experiment. The prediction tools, SignalIP and TatP were employed to get insights into the protein secretion pathways. The SignalIP predicted that 54 out of 84 secreted proteins possessed signal sequence, indicating the ‘Sec’ pathway for their secretion while TatP predicted three sequences with TatP signal sequences, suggesting alternative secretion mechanisms for those proteins. However, no lipoproteins were detected (Pred-Lipo, LipoP) in the secretome.

Figure 1.  Analysis of the proteome of A. defectiva secretome. (a) SDS-PAGE gel showing protein bands from secretome/extracellular proteins (ECP) and whole cell protein preparations (WCP). (b) Protein sequences from LC-MS analysis of the secretome were analyzed by an in silico 2DE tool and (c) Western blot analysis showing the absence of the cytoplasmic marker protein FtsZ in the secretome and whole cell protein preparations.

Using SecretomeP 2.0 as another prediction tool, initially, 59 sequences were predicted to utilize non-classical pathway for their secretion. However, upon further analysis, as 51 of them possessed signal sequences, suggesting secretion via Sec pathway, only eight proteins (9.5%) were finally considered to be utilizing non-classical pathway for their secretion.According to the PSORTb subcellular localization prediction tool analysis, A.defectiva secretome of 84 secreted proteins detected with LC-MS/MS was predicted to contain 20 cytoplasmic proteins (23.8%), 12 cytoplasmic membrane proteins (14.3%), 5 extracellular proteins (5.95%), 9 cell wall anchored proteins (10.71%), whereas the localization of 38 proteins (45.24%) could not be predicted.

For predicting the presence of transmembrane alpha helices TMHMM, SOUSIG and SVMtm tools were used. SOSUIG analyzed that out of total 84 proteins, 21 were membrane proteins (25%) and rest 63 were soluble proteins (75%). TMHMM tool analysis predicted transmembrane alpha helices in 18 proteins. Two of the 18 protein sequences that were predicted to have at least 2 transmembrane domains were considered as putatively membrane attached and therefore not included in further analyses. Multitask Prot DB tool for detecting moonlighting proteins identified 23 proteins with moonlighting functions in the secretome of A. defectiva (Table 1). Four hypothetical proteins (>gi|554771335|gb|ESK65778.1| hypothetical protein GCWU000182_00843 [Abiotrophia defectiva ATCC 49,176]; >gi|736332351|ref|WP_034358940.1| hypothetical protein [Herbaspirillum rubrisubalbicans]; >gi|949021501|gb|KRO30945.1| hypothetical protein ABR60_00340 [Actinobacteria bacterium BACL2 MAG-120802-bin41]; >gi|736332376|ref|WP_034358964.1| hypothetical protein [Herbaspirillum rubrisubalbicans]) were observed to have conserved domains.

Table 1. List of A. defectiva secretome proteins with a predicted moonlighting function.

S.no.	GI #	Name
1	gi|557369311	peptide ABC transporter substrate-binding protein
2	gi|554771431	ABC transporter, solute-binding protein
3	gi|557369709	maltodextrin-binding protein MdxE/extracellular solute-binding protein
4	gi|554770501	putative fumarate reductase flavoprotein subunit
5	gi|557369146	ABC transporter solute-binding protein
6	gi|557370056	peptidase S41/PDZ domain-containing protein
7	gi|557369427	D-methionine-binding lipoprotein MetQ
8	gi|557368903	type I glyceraldehyde-3-phosphate dehydrogenase
9	gi|557370233	ErfK/YbiS/YcfS/YnhG
10	gi|557368618	ABC transporter substrate-binding protein
11	gi|557369034	LysM domain-containing protein
12	gi|557369704	peptidase
13	gi|557370108	serine protease do-like protein/PDZ domain-containing protein
14	gi|554772095	LysM domain protein
15	gi|557368864	glycerol dehydrogenase
16	gi|488760879	Adenosyl homo cysteinase
17	gi|554770293	fructose-1,6-bisphosphate aldolase, class II
18	gi|554771016	LysM domain protein
19	gi|553304592	ATP-dependent Clp protease ATP-binding subunit ClpX
20	gi|554770463	peroxiredoxin, Ohr subfamily
21	gi|557370264	ABC transporter solute-binding protein
22	gi|557368899	enolase/MULTISPECIES: phosphopyruvate hydratase
23	gi|1027884671	ShlB/FhaC/HecB family hemolysin secretion/activation protein

Gene ontology analysis for predicting functional annotation of secreted proteins

The amino acid FASTA sequences of A. defectiva secretome were subjected to Gene Ontology (GO) analysis using Blast2GO and WEGO tools. For WEGO, the InterPro analysis XML file was utilized (Figure 2). Overall, 41 of the 84 sequences were assigned as annotated genes. The proteins were grouped based on GO terms: 31 in ‘biological process’, 15 in ‘cellular component’, and 31 in ‘molecular function’ groups.

Figure 2.  Gene ontology analysis of A. defectiva secreted proteins. Gene ontology annotation was achieved using Blast2GO and an online software ‘WEGO’. Protein sequences were grouped into 3 categories based on their properties and functions.

KEGG pathway analysis for predicting enzymatic functions involved in metabolic pathways

All the detected protein sequences from the A. defectiva secretome were subjected to KEGG pathway annotation and analysis using KEGG mapper software tool (Figure 3). Total 28 of the 84 protein sequences were annotated and detected to be involved in various biological pathways. Proteins involved in environmental information processing were found to be predominant (11 proteins/39%) followed by carbohydrate metabolism (5 proteins/18%) and protein families involved in signaling and cellular processing (4 proteins/14%). Three proteins (11%) were found to be involved in genetic information processing while other two in Protein families: Genetic information processing (7%). Proteins categorized in energy metabolism, cellular processes and protein families: metabolism were found to be one each (3.6%).

Figure 3.  KEGG pathway analysis of the A. defectiva secretome. all protein sequences from the secretome were analyzed by KEGG pathway tool.

Potential virulence proteins in A. defectiva secretome

A total of 20 proteins were predicted to be virulent in A. defectiva secretome based on in silico prediction using the online tools ‘VirulentPred’ and ‘VFDB’ (Virulence Factor DataBase). The results were further supported by the evidence from the literature (Table 2). Manual search for investigating the associations with virulence activities in other species helped in assessing the virulence potential of the A. defectiva secretome. The major proteins evidenced having virulence properties in other bacterial species were NlpC/P60 family protein, SEC10/PgrA surface exclusion domain-containing protein, DUF1002 domain-containing protein, ErfK/YbiS/YcfS/YnhG, Tat pathway signal sequence domain protein, ubiquitin-ribosomal protein fusion S27a, W×G100family type VII secretion target ubiquitin, peroxiredoxin, Ohr subfamily, signal peptide protein-YSIRK family, LysM domain protein, oligopeptide ABC transporter substrate-binding protein, PDZ domain-containing protein, MULTISPECIES: 50S ribosomal protein L7/L12, D-alanyl-D-alanine carboxypeptidase, DNA starvation/stationary phase protection protein, and LysM peptidoglycan-binding domain-containing protein.

Table 2. Putative virulence factors identified in A. defectiva secretome.

S.No.	GI Number	Protein	In silico prediction	Literature evidence
1	gi|557370330|	NlpC/P60 family protein		[1,2]
2	gi|557369880|	SEC10/PgrA surface exclusion domain-containing protein		[41]
3	gi|557368815|	DUF1002 domain-containing protein		[42,43]
4	gi|557370233|	ErfK/YbiS/YcfS/YnhG		[44,45]
5	gi|554770642|	Tat pathway signal sequence domain protein		[46–48]
6	gi|68481104|	ubiquitin-ribosomal protein fusion S27a		[49,50]
7	gi|557369257|	WXG100 family type VII secretion target		[51–53]
8	gi|315447814|	ubiquitin		[54,55]
9	gi|554770463|	peroxiredoxin, Ohr subfamily		[56]
10	gi|554771681|	signal peptide protein, YSIRK family		[57,58]
11	gi|554772095|	LysM domain protein		[59]
12	gi|554771016|	LysM domain protein		[59]
13	gi|554771335|	hypothetical protein		[60]
14	gi|557368619|	oligopeptide ABC transporter substrate-binding protein		[61–63]
15	gi|557370108|	PDZ domain-containing protein		[64–66]
16	gi|557370394|	MULTISPECIES: 50S ribosomal protein L7/L12		[67,68]
17	gi|949021501|	hypothetical protein ABR60_00340		[69]
18	gi|557369052|	D-alanyl-D-alanine carboxypeptidase		[70,71]
19	gi|557369594|	DNA starvation/stationary phase protection protein		[72,73]
20	gi|557369034|	LysM peptidoglycan-binding domain-containing protein		[74]
21	gi|557369429|	MULTISPECIES: MetQ/NlpA family ABC transporter substrate-binding protein		[75,76]
22	gi|553304592|	ATP-dependent Clp protease ATP-binding subunit ClpX		[77]
23	gi|557368688|	MULTISPECIES: HU family DNA-binding protein		[78,79]
24	gi|505265440|	F0F1 ATP synthase subunit alpha		[80,81]
25	gi|557369704|	peptidase		[82–84]
26	gi|557370108|	PDZ domain-containing protein
27	gi|557370264|	extracellular solute-binding protein		[85–87]

STRING for functional protein association network analysis

The functional protein association network analysis of A. defectiva (Figure 4) was demonstrated using tool STRING. As evident in Figure 4, secretome proteins formed three distinct protein groups based on molecular action, i.e, carbohydrate metabolism proteins, ribosomal proteins, and ATP synthase proteins. Proteins network involved in carbohydrate metabolism were Pyruvate kinase, ATP-dependent 6-phosphofructokinase, glucose-6-phosphate isomerase, Pyruvate, Enolase, Fructose-1,6-bisphosphate aldolase, 2,3-bisphosphoglycerate-independent phosphoglycerate mutase, Triosephosphate isomerase, glyceraldehyde 3-phosphate dehydrogenase. The ribosomal protein group was mainly consisted of secreted 50S ribosomal proteins (L4, L5, L6, L7/12, L10, L11, L13, L14, L19 and L20). The third protein network of extracellular ATPases (or ATP synthases) involved in ATP synthesis and/or hydrolysis were ATP synthase subunits alpha, a, b, gamma chain and epsilon chain.

Figure 4.  Functional protein association networks of A. defectiva secretome. The online tool STRING was used for grouping the secreted proteins on the basis of functional networks. Minimum interaction scores were set at a strong confidence level of 0.7. The three major network groups formed are shown in dotted circles. Seven different colored link a number of nodes and represent seven types of evidence used in predicting associations. A red line indicates the presence of fusion evidence; a green line represents neighborhood evidence; a blue line represents co-occurrence evidence; a purple line represents experimental evidence; a yellow line represents text mining evidence; a light blue line represents database evidence and a black line represents co-expression evidence.

ELISA quantification of selected cytokines produced from stimulated human PBMCs with A. defectiva secretome (ECPs) and whole cell proteins (WCPs)

Various concentrations (10, 25, 50, and 100 µg/ml) of A. defectiva secretome triggered the production of proinflammatory cytokines IL-8, IL-1β and CCL 5 from PBMCs as compared to the controls (0 µg/ml). The secretome induced significantly higher levels of IL-1β production (p < 0.05) compared to WCPs of A. defectiva while IL-8 levels were significantly higher from the WCPs. In the case of CCL5, large amounts of upto 5000 pg/ml were also induced at 0 mg/ml protein concentration (Figure 5).

Figure 5.  Cytokine induction from human PBMCs by A. defectiva secretome preparation.

Fractionated human PBMCs were stimulated by A. defectiva secretome (ECPs) and whole-cell preparation (WCPs) for 24 h (10, 25, 50, and 100 µg/ml). The cytokines produced were quantified using specific ELISA immunoassay kits (Quantikine® ELISA R&D systems). The data presented are mean (SD).

Discussion

Understanding the ability of bacteria to secrete extracellular proteins is crucial for comprehending their role in biofilm formation and pathogenesis, which aid the bacteria in developing defensive strategies against host and mount infection. Recent discoveries in protein secretome in several other oral bacteria have prompted us to consolidate the information on the secretome of A. defectiva [15,20,88,89]. The secretion of extracellular proteins is a fundamental aspect of bacterial physiology, with a remarkable clinical importance. Bacterial pathogens transport various virulence-associated proteins to the extracellular space, strategically deploying them in host locations to facilitate colonization and subsequent infection. In the case of oral bacteria, these secreted virulence proteins may promote bacterial proliferation at specific oral sites, potentially contributing to dysbiosis.

In the current investigation, a broad proteomics-based analysis of the A. defectiva secretome was performed and found a large number of putative virulence factors. We accomplished the characterization of most of the secretome proteins ‘in silico’ by using various bioinformatics tools. Proteins belonging to several secretion systems, like the sec-dependent Tat pathway and a non-classical secretory system, were found to be part of the secretome. The possibility of contamination of the secretome with subcellular proteins was ruled out by using an established cytoplasmic marker protein, Fts-Z [90], which remained absent in all A. defectiva secretome preparations but was detected in whole-cell protein lysate.

We found more than 20 possible virulence-associated proteins in the A. defectiva secretome using in silico analysis. These results were backed up by experiments and published research. Virulence factors have been found in the secretomes of other oral bacteria that have been studied a lot, like Aggregatibacter actinomycetemcomitans [88], Porphyromonas gingivalis [89] and less-studied G. adiacens [20]. Several well-known virulence factors in other bacteria (such as NlpC/P60 family protein, SEC10/PgrA, ErfK, ubiquitin-ribosomal protein fusion S27a, peroxiredoxin, signal peptide protein-YSIRK family, LysM domain protein, 50S ribosomal protein L7/L12, DNA starvation/stationary phase protection protein, and LysM peptidoglycan-binding domain-containing protein) were also detected in the A. defectiva secretome. Such virulence factors are believed to enhance bacterial colonization, promote inflammation, disrupt host cellular homeostasis, and modulate host immune responses [91].

Several proteins in the A. defectiva secretome were categorized under the multifunctional group ‘moonlighting proteins’ [91,92], which have a known function inside the bacterial cell but also participate in different biological processes in the extracellular medium after their secretion. Because of their well-known function in bacterial pathogenicity, the moonlighting proteins in the secretome of A. defectiva are of great significance [93,94]. Secretion of 50S ribosomal proteins was noticed in the secretome of A. defectiva. Interestingly, ribosomal protein L7/L12 is highly antigenic and immunogenic [95,96] in other bacteria. Some of the glycolytic enzymes possess moonlighting properties, e.g. they function as adhesins [97], receptors for transferrin [98], neutrophil evasion proteins [99], immunomodulators [100] and participate in extracellular polysaccharide synthesis [101]. The versatile functionality of moonlighting proteins may facilitate the growth of A. defectiva in both its native habitats and sterile anatomical regions.

While predicting the functional annotation of secreted proteins, more than 75 A. defectiva secretome proteins were grouped into biological process, cellular component, and molecular function ontology groups.

Predicting enzymatic functions involved in metabolic pathways by KEGG, 28 of the total protein sequences were annotated and detected to be involved in various biological pathways. Proteins involved in environmental information processing were found to be predominant, followed by carbohydrate metabolism and protein families involved in signaling and cellular processing. Others were found to be involved in genetic information processing and energy metabolism. The secretome proteins are aligned with various KEGG pathways.

Several secretome proteins aligned with various KEGG pathways, notably the antibiotic biosynthesis and glycolysis pathways. The antibiotic biosynthesis pathway consisted of key enzymes, including hydratase, dehydrogenase, and aldolase, known for their essential roles in antibiotic biosynthesis [102,103]. Other significant pathways were cysteine & methionine metabolism, methane metabolism, and purine metabolism. These findings indicate that extracellular proteins of A. defectiva with metabolic functions might assist the bacterium in utilizing the available extracellular nutrients [104]. The functional protein association network analysis (STRING) of A. defectiva demonstrated three distinct protein groups based on molecular action, i.e. carbohydrate metabolism, ribosomal proteins, and ATP synthase proteins. The protein network involved in carbohydrate metabolism consisted of pyruvate kinase, phosphofructokinase, isomerases, pyruvate, enolase, aldolase, phosphoglycerate mutase, and a dehydrogenase. Several glycolytic enzymes seemed to have overlapping functions, i.e. they were also involved in antibiotic biosynthesis, as predicted by KEGG. The ribosomal protein group mainly consisted of secreted 50S ribosomal proteins L4, L5, L6, etc. The third protein network of extracellular ATPases (or ATP synthases) involved in ATP synthesis and/or hydrolysis were the ATP synthase subunits alpha, gamma chain and epsilon chain. Living organisms generate ATP through respiration and subsequently utilize ATP to carry out cellular functions that are necessary for their survival, growth and replication. In addition to its intracellular roles in storing and supplying energy in metabolism and enzymatic reactions, ATP also has signaling functions. ATPases (or ATP synthases) are membrane-bound enzyme complexes or ion transporters that combine ATP synthesis and/or hydrolysis with the transport of protons across a membrane. In previous studies, Escherichia coli and Salmonella were shown to actively deplete the extracellular ATP and an ATP supplement in culture media, enhancing their own stationary survival. Recently, ATP was also shown to regulate virulence gene mgtC in Salmonella [105]. Extracellular ATP was also observed in a variety of other bacterial species including human pathogens such as Acinetobacter, Pseudomonas, Klebsiella and Staphylococcus [106]. Extracellular ATP interact with P2 receptors to modulate immune response by stimulating cell migration and cytokine secretion [104,107]. These findings suggest ATP as a more versatile molecule than a mere source of energy.

The secretome of A. defectiva was examined to assess its ability to stimulate cytokines and explore the immune response of the host. Stimulation of human PBMCs with various concentrations of A. defectiva secretome and whole-cell proteins triggered the production of proinflammatory cytokines IL-8, IL-1β, and CCL 5. Significant levels of IL-1β and IL-8 (p < 0.05) were induced by A. defectiva secretome. Previous studies have demonstrated that several bacterial species possess secreted components that can induce an inflammatory response in host cells [108–111]. In our previous study of cytokine induction in human PBMCs upon stimulation with biofilms and biofilm supernatants of Granulicatella and Abiotrophia spp., supernatants from A. defectiva biofilms were observed to be the strongest inducing among Granulicatella elegans, Granulicatella adiacens, and A. defectiva [112].

This study has certain limitations. We did not validate the proteomic in silico detection of proteins through laboratory methods. Additionally, the mass spectrometry approach we utilized offers only qualitative information about the proteins and obtaining quantitative data on the secreted proteins could provide more profound insights into their significance. The secretion of proteins into the extracellular space is influenced by numerous factors, such as growth conditions, including medium composition, and atmospheric conditions. In a prior investigation of the periodontitis-associated bacterium A. actinomycetecomitans, when specific conditions mimicking those encountered in the host were replicated, significant differences in protein secretion were observed in this species [113]. Likewise, exploring the secretome of A. defectiva under the in vivo conditions that the species may encounter would be of considerable interest.

In conclusion, elucidation of the secretome has revealed the role of various secreted proteins of A. defectiva, an oral bacterium well-documented in infective endocarditis and shown to be involved in oral infections. Putative virulence factors and several multifunctional ‘moonlighting’ proteins, which in other species are known to function as virulence factors, were detected [114,115]. Hence, the output of the present study is a foundation stone for investigating the role of secreted proteins of A. defectiva at deeper levels in oral infections as well as in infective endocarditis.

Ethics statement

This study was carried out in accordance with the recommendations of the Ethical Committee of Health Sciences Center (HSC), Kuwait University. Written informed consent was obtained from the human volunteer and the consent was in accordance with the Declaration of Helsinki. The protocol was approved by the Ethical Committee of the HSC, Kuwait University.

Author contribution statement

MK: Conceived and designed the study, bioinformatics analyses

RGB, MEK, MK: Performed the laboratory experiments, bioinformatics analyses

MK, RGB, MEK: Wrote the manuscript

Acknowledgments

This study was supported by Kuwait University Grant SRUL 01/14. We thank Dr. Nupur Sharma for critical reading and commenting on the manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

The raw data supporting the conclusions of this manuscript has been submitted to ‘PRIDE Archive’ (https://www.ebi.ac.uk/pride/archive/) repository with the project accession number PXD015631. The data files can be accessed with the username [email protected] and password: gCB24pty.

Additional information

Funding

This study was funded by Kuwait University Grant SRUL 01/14.