Next Article in Journal
Evaluation of the Antibacterial Potential of Two Short Linear Peptides YI12 and FK13 against Multidrug-Resistant Bacteria
Previous Article in Journal
Characterising the Metabolomic Diversity and Biological Potentials of Extracts from Different Parts of Two Cistus Species Using UHPLC-MS/MS and In Vitro Techniques
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Pathogens
Volume 13
Issue 9
10.3390/pathogens13090796
pathogens-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Metabolic Footprint of Treponema phagedenis and Treponema pedis Reveals Potential Interaction Towards Community Succession and Pathogenesis in Bovine Digital Dermatitis

by
Hector M. Espiritu
1,
Edeneil Jerome P. Valete
1,
Lovelia L. Mamuad
1,
Myunghwan Jung
2,
Man-Jeong Paik
3,
Sang-Suk Lee
1 and
Yong-Il Cho
1,*
1
Department of Animal Science and Technology, Sunchon National University, Suncheon-si 57922, Jeollanam-do, Republic of Korea
2
Department of Microbiology, College of Medicine, Gyeongsang National University, Jinju 52727, Gyeongsangnam-do, Republic of Korea
3
College of Pharmacy, Sunchon National University, Suncheon-si 57922, Jeollanam-do, Republic of Korea
*
Author to whom correspondence should be addressed.
Pathogens 2024, 13(9), 796; https://doi.org/10.3390/pathogens13090796
Submission received: 16 August 2024 / Revised: 4 September 2024 / Accepted: 10 September 2024 / Published: 14 September 2024
(This article belongs to the Section Bacterial Pathogens)
Browse Figures
Versions Notes

Abstract

Bovine digital dermatitis (BDD) is a cattle infection causing hoof lesions and lameness, with treponemes as key pathogens. We analyzed the metabolic activity of Treponema phagedenis and Treponema pedis using gas chromatography–mass spectrometry for organic acids (OAs), amino acids (AAs), and fatty acids (FAs), and high-performance liquid chromatography for short-chain fatty acids (SCFAs). Key findings include a 61.5% reduction in pyruvic acid in T. pedis and 81.0% in T. phagedenis. 2-hydroxybutyric acid increased by 493.8% in T. pedis, while succinic acid increased by 31.3%, potentially supporting T. phagedenis. Among AAs, glycine was reduced by 97.4% in T. pedis but increased by 64.1% in T. phagedenis. Proline increased by 76.6% in T. pedis but decreased by 13.6% in T. phagedenis. Methionine and glutamic acid were competitively utilized, with methionine reduced by 41.8% in T. pedis and 11.9% in T. phagedenis. Both species showed significant utilization of palmitic acid (reduced by 82.8% in T. pedis and 87.2% in T. phagedenis). Butyric acid production increased by 620.2% in T. phagedenis, and propionic acid increased by 932.8% in T. pedis and 395.6% in T. phagedenis. These reveal metabolic interactions between the pathogens, contributing to disease progression and offering insights to BDD pathogenesis.

1. Introduction

Many microorganisms live in complex polymicrobial biofilm communities, as single-species planktonic microbes are not common [1]. These communities are composed of different species with specialized phenotypes performing distinct functions, and several species within the community can work together to carry out more complex processes. Some of these interactions can range from intense competition for nutrients and niches to highly evolved cooperative mechanisms that support cooperative growth between multiple species [2]. Such complex interactions between members of the polymicrobial biofilm may play a pivotal role in the pathogenesis of most known infections [3]. A growing awareness of these interactions, as well as a desire to better understand the processes governing them, has led to a transition from monomicrobial to polymicrobial biofilm studies in various disease models [4].
One of the major diseases that exhibits polybacterial etiology is bovine digital dermatitis (BDD). BDD is a major problem in the livestock and dairy sector because it reduces [both welfare and economic efficiency of animals globally. It is a cutaneous infection characterized by an ulcerative and proliferative lesion on the hoof that affects the weight-bearing distribution, gait, and posture of affected animals and often leads to lameness. Previous investigations have reported that this disease has a complex microbiome due to the dysbiosis caused by the overabundance of opportunistic pathogens which mainly include multiple Treponema species [5,6,7,8,9]. Despite five decades since its initial report, limited progress has been made in the study of the fundamental mechanisms underlying BDD pathogenesis. This is primarily due to the fastidious behavior exhibited by the anaerobic group of bacteria involved. Currently, four Treponema species have been successfully recovered from BDD lesions, three of which are considered as the main pathogens involved because of their high abundance level persistently found in most lesions, namely T. phagedenis, T. pedis, and T. medium [10,11,12,13,14]. The persistence of these treponemes in lesions has led to a series of investigations of their properties to decipher their role in the pathogenesis of BDD [7,15,16].
In the polybacterial consortium within BDD, the interactions among members of the community are undeniably complex. Competition for intermediates or products, or cooperative interactions, such as the beneficial metabolic exchange known as “cross-feeding”, may be at play [2]. Identification of the interactions among the bacteria responsible for BDD may offer important clues about its etiology. Exometabolomics, or metabolic footprinting, the study of small metabolite profiles in extracellular environments, is a method that is ideally suited for this. Insights into the metabolic activities of certain microbial strains or communities can be obtained by analyzing metabolites absorbed from or released into culture medium as individual bacterial strain preferences can be characterized to identify the likelihood of competing with other strains [1]. In this study, we aimed to elucidate the metabolic footprint profiles of two Treponema species, T. phagedenis and T. pedis, isolated from BDD in Korean dairy cattle. By analyzing their metabolic footprints in monocultures, we aimed to compare key metabolites, namely organic acids (OAs), amino acids (AAs), and fatty acids (FAs), measured using targeted techniques like gas chromatography–tandem mass spectrometry (GC-MS/MS) and high-performance liquid chromatography (HPLC). OAs are involved in energy production and basic metabolic processes, AAs are essential for protein synthesis and bacterial growth, and FAs are important for cell membranes and energy storage. This will provide us with clues about both the potential metabolic interactions between T. phagedenis and T. pedis and how these metabolites might affect the host tissues.

2. Materials and Methods

2.1. Isolates and Culture Medium

Bacterial cultures of T. phagedenis HNW1 [17] and T. pedis GNW45 [18] isolated previously were prepared using an optimized Treponema enrichment broth (OTEB, Anaerobe Systems, Morgan Hill, CA, USA) supplemented with 10% fetal bovine serum to provide necessary nutrients for anaerobic growth [17]. Each culture was prepared in triplicate, alongside a negative control consisting of the same OTEB medium with 10% FBS but without bacterial inoculum. This control was used to establish baseline levels of metabolites present in the medium, ensuring that any observed metabolic changes in the experimental cultures were attributable to bacterial activity. Post-incubation, all cultures, including the negative control, were examined microscopically for any bacterial growth or contamination. Following this, cultures were centrifuged at 4000 rpm for 10 min to harvest the supernatants. The supernatants were then sterile-filtered using a 0.2 µm filter to remove any remaining cells and stored at −80 °C for subsequent analysis.

2.2. Metabolomic Profiling

The quantification of OAs, AAs, and FAs in the culture supernatants was performed using GC-MS/MS which followed the methodology described by Kim et al. (2020) [19]. To prepare the samples for GC-MS/MS analysis, a derivatization protocol was employed to convert the metabolites into volatile and stable derivatives. The derivatization involved three key reactions: ethoxycarbonylation (EOC) to modify amine groups in AAs, methoximation (MO) to protect carbonyl groups, and tert-butyldimethylsilylation (TBDMS) to derivatize hydroxyl and carboxyl groups. These reactions were essential for converting the metabolites into forms suitable for GC-MS/MS analysis for precise detection and quantification. The GC-MS/MS analysis was conducted on a Shimadzu TQ 8040 triple quadrupole mass spectrometer (Kyoto, Japan) with an Ultra-2 capillary column. The instrument operated in split-injection mode with helium as the carrier gas and argon as the collision gas. Specific chromatographic conditions were applied to optimize the separation and detection of each metabolite class: For OAs, the GC oven temperature was initially set at 100 °C for 2 min, then ramped to 250 °C at 10 °C/min, followed by an increase to 300 °C at 20 °C/min. AAs were analyzed by maintaining the oven temperature at 140 °C for 3 min before increasing to 300 °C at 8 °C/min. FAs were measured by holding the temperature at 100 °C for 3 min, followed by a rise to 200 °C at 20 °C/min, then 260 °C at 1.5 °C/min, and finally 300 °C at 20 °C/min. The MS employed electron impact ionization at 70 eV and multiple reaction monitoring (MRM) mode, focusing on specific precursor and product ion transitions for accurate metabolite identification. Calibration curves were constructed using standards to ensure accurate quantification of metabolite concentrations in the samples.
Additional analysis for the determination of the concentration of short-chain fatty acids (SCFAs) was conducted using high-performance liquid chromatography (HPLC). The analysis utilized an Agilent 1200 Series HPLC System with a UV detector set at 210 and 220 nm. Samples were eluted isocratically with 0.0085 N H2SO4 at a flow rate of 0.6 mL/min and a column temperature of 35 °C, following a previous protocol [17].

2.3. Data Analysis

The data obtained from GC-MS/MS and HPLC analyses were subjected to statistical evaluation. Analysis of variance (ANOVA) followed by Duncan’s multiple range test were used to assess significant differences between metabolite concentrations in the different Treponema species. All statistical analyses were performed using SAS version 9.4. The results were normalized against baseline values obtained from the control using relative normalization. These normalized values were then visualized using radar plots created in Microsoft Excel (https://www.microsoft.com/en-au/microsoft-365/excel, accessed on 15 Ausgust 2024) to illustrate patterns of metabolite utilization and production.

3. Results

A total of 40 metabolites, which included 11 OAs, 19 AAs, six FAs, and five SCFAs, were analyzed. Out of these, a total of eight OAs, nine AAs, four FAs, and all SCFAs have significant differences based on the concentration between the isolates and the control.

3.1. Organic Acids (OAs)

The concentrations of OAs quantified in the culture medium are detailed in Table 1. Significant differences were observed for several OAs, including pyruvic acid, glycolic acid, 2-hydroxybutyric acid (2-HBA), 3-hydroxypropionic acid (3-HPA), succinic acid, fumaric acid, oxaloacetic acid, and α-ketoglutaric acid. Both T. pedis and T. phagedenis exhibited significant reductions in pyruvic acid levels, with decreases of 61.5% and 81.0%, respectively, compared to the control, suggesting competition for this metabolite. Glycolic acid levels were reduced by 21.8% in T. phagedenis but remained stable in T. pedis. There was a notable increase of 493.8% in 2-HBA in T. pedis, while T. phagedenis remained unchanged. 3-HPA levels decreased by 11.9% in T. pedis and 45.7% in T. phagedenis. Succinic acid levels increased by 31.3% in T. pedis but showed no significant change in T. phagedenis. Fumaric acid utilization increased by 36.7% in T. pedis and decreased by 48.4% in T. phagedenis, indicating possible cooperative interactions. Oxaloacetic acid increased slightly by 15.8% in T. pedis but decreased by 29.2% in T. phagedenis. α-Ketoglutaric acid decreased by 60.7% in T. phagedenis but remained stable in T. pedis. The normalized concentrations of these metabolites are depicted in Figure 1A through a radar plot, which illustrates whether each metabolite was utilized or produced by the bacteria. Figure 1B presents the percentage composition of each OA, offering a comparative view of their relative abundances across different conditions.

3.2. Amino Acids (AAs)

The concentration of AAs in the culture medium varied significantly, particularly for alanine, glycine, proline, methionine, serine, threonine, aspartic acid, glutamic acid, and glutamine, as detailed in Table 2. T. pedis showed a 40.9% increase in alanine levels compared to the control, while T. phagedenis exhibited a 20.8% increase. A significant reduction in glycine was observed for T. pedis, which showed a 97.4% decrease compared to the control, whereas T. phagedenis exhibited increased glycine levels, with a 64.1% increase. Proline concentrations were significantly higher in T. pedis, showing a 76.6% increase compared to the control, while T. phagedenis exhibited a 13.6% reduction. Significant reductions in methionine were noted across both bacterial species, with T. pedis showing a 41.8% decrease and T. phagedenis showing a 11.9% decrease compared to the control.
Threonine levels increased by 58.8% in T. pedis compared to the control, but T. phagedenis showed a 45.0% reduction. Aspartic acid levels decreased by 26.8% in T. pedis, while T. phagedenis exhibited a 49.4% increase compared to the control. Glutamic acid was not detected in T. phagedenis, indicating substantial utilization, while T. pedis showed a reduction of 28.2%. Glutamine levels were significantly reduced in T. phagedenis (100% utilization), and T. pedis showed a 19.2% decrease compared to the control.
This pattern of AA metabolism suggests potential metabolic cross-feeding between the treponemes for amino acids like proline and threonine, and metabolic competition for methionine, glutamic acid, and glutamine. Serine appears to be commensally shared between the two species, as it showed only a slight reduction in both.
The normalized concentrations of these metabolites are depicted in Figure 2A through a radar plot, which illustrates whether each amino acid was utilized or produced by the bacteria. Figure 2B presents the percentage composition of each AA, offering a comparative view of their relative abundances across different conditions.

3.3. Fatty Acids (FAs/SCFAs)

The Treponema species exhibited significant utilization of FAs, particularly cis-9-Hexadecenoic acid, palmitic acid, linoleic acid, and oleic acid, as evidenced by their reduced levels in both T. pedis and T. phagedenis compared to the control, as detailed in Table 3. Cis-9-Hexadecenoic acid levels were significantly reduced by about 80.4% in T. pedis and 87.3% in T. phagedenis compared to the control. Palmitic acid levels showed an 82.8% reduction in T. pedis and an 87.3% reduction in T. phagedenis. Linoleic acid levels decreased by 86.3% in T. pedis and 47.8% in T. phagedenis. Oleic acid levels were lower by 42.1% in T. pedis and 48.2% in T. phagedenis. Although octadecanoic acid was also utilized by both spirochetes, the changes were not statistically significant.
Distinct patterns of production and utilization were observed for metabolites measured through HPLC, including SCFAs and lactic acid, as shown in Table 3. Notably, there was a significant increase in butyric acid production, particularly in T. phagedenis, which exhibited a dramatic 620.1% increase, while T. pedis showed a 317.1% increase compared to the control, highlighting butyric acid as a key metabolite in BDD. Propionic acid production also showed striking differences. T. pedis exhibited a remarkable 932.8% increase compared to the control, while T. phagedenis showed a 395.6% increase. This suggests significant metabolic activity in both species due to higher levels of propionic acid produced. Formic acid production was exclusively observed in T. phagedenis, not detected in the control or T. pedis. In contrast, T. pedis exhibited higher production of acetic acid (130.8% increase) compared to T. phagedenis, which showed a lower increase of 20.5%. Lactic acid, though not an SCFA but are commonly produced by SCFA-producing bacteria, shows that its concentrations were significantly reduced in both T. pedis and T. phagedenis, with a reduction of 41.5% and 50.2%, respectively, indicating substantial utilization by these species.
The normalized concentrations of these metabolites are depicted in Figure 3A,C through a radar plot, which illustrates whether each fatty acid or SCFA was utilized or produced by the bacteria. Figure 3B,D presents the percentage composition of each FA and SCFA, offering a comparative view of their relative abundances across different conditions.

4. Discussion

In this study, we used exometabolomics, also known as metabolic footprinting, to examine how two Treponema species change small molecules in their environment by comparing culture media with and without the bacteria. This method examines how cells modify these molecules in their niche [20], helping us understand how these bacteria interact in the BDD bacterial community. By analyzing AAs, FAs, and OAs, we can see how the bacteria either cooperate or compete for resources. Our results showed that both Treponema species have unique metabolic patterns, using up many essential AAs and OAs while consuming key FAs, suggesting they have adapted to survive and thrive in their environment. The observed differences in metabolic profiles between T. phagedenis and T. pedis are expected given their distinct species identities, but these differences provide biologically significant insights into how each species adapts to and potentially influences the BDD microenvironment. For example, the production of butyric acid by T. phagedenis might contribute to its survival or affect the host’s immune response differently than T. pedis. These variations could play a role in how these bacteria interact with the host and with other microorganisms in the community, potentially impacting disease progression. It is also important to acknowledge certain limitations; for instance, the use of FBS as a nutrient source, though obtained from the same batch across all experiments, presents a level of complexity that may not fully replicate the natural environment within a bovine host. In vivo, Treponema species would interact with a range of host tissues, immune responses, and other members of the polymicrobial community, factors that our in vitro conditions cannot entirely mimic. This means that while our findings are robust within the context of the experimental setup, caution should be exercised when extrapolating these results to natural, in vivo conditions. Furthermore, BDD is known to be a polymicrobial infection, and our focus on monoculture analyses in this study was aimed at establishing baseline metabolic activities and understanding the differences between T. phagedenis and T. pedis. However, the complexity of BDD urges that future research would benefit from exploring mixed cultures, not only among Treponema spp. but also including other non-treponeme bacteria commonly found in lesions, such as Fusobacterium spp., Porphyromonas spp., and Dichelobacter spp. [7]. Analyzing a mixed metabolic profile could provide deeper insights into potential metabolic co-dependencies and interactions among these diverse microbial species. Such studies could reveal whether these bacteria exhibit metabolic cooperation or competition when coexisting within the same environment, offering a more comprehensive understanding of their roles within the BDD microbial community.
According to Freilich et al. [21], metabolic cooperation occurs when one bacterium produces a metabolite that another uses, while competition happens when both use the same metabolite. Our findings indicate both cooperative and competitive interactions between the species, providing insight into their roles in the BDD bacterial community. These results enhance our understanding of Treponema biology and suggest possible targets for treatments to disrupt these bacteria’s metabolic pathways and control disease progression.

4.1. Organic Acids

For the OAs presented in Table 1 and Figure 1, pyruvic acid is a key metabolic requirement for both T. pedis and T. phagedenis, as evidenced by their competitive interaction for this metabolite. Previous studies have established pyruvic acid as a crucial intermediate in bacterial carbohydrate metabolism [22]. As a monocarboxylic acid produced at the end of glycolysis, pyruvic acid can serve as the sole carbon source for some bacteria, such as E. coli [23]. Treponema species have also been documented to be pyruvate-dependent. For example, Nichols and Baseman demonstrated that the virulent T. pallidum selectively uses pyruvate as a carbon source, producing CO2 and acetate as degradation end products [24]. Additionally, the glutathione metabolism of T. denticola rapidly consumes pyruvate, enhancing bacterial colonization and producing volatile sulfur compounds (VSCs) like hydrogen sulfide (H2S), which plays a significant role in pathogenic changes in human periodontal tissues through hemoxidation and hemolysis [25]. The production of VSCs such as H2S and methyl mercaptan as metabolic byproducts could explain the strong malodor associated with BDD, as these compounds are highly toxic and contribute to host tissue damage.
Regarding glycolic acid, no interaction was observed between the two Treponema species. The significant reduction of glycolic acid by T. phagedenis suggests that this bacterium might utilize it as a carbon and energy source, potentially enhancing its colonization ability. A similar mechanism has been observed in other colonizing bacteria, such as Mycoplasma pneumoniae, which uses glycerol [26]—modulated by glycolic acid [27]—as a carbon and energy source, implicating its role in virulence.
Among the OAs, we observed an overproduction of 2-hydroxybutyric acid by T. pedis. Although limited information is available regarding this OA’s role in bacterial virulence in host tissues, it is related to butyrate, which has been shown to have both positive and negative effects depending on tissue localization. We also observed that 3-hydroxypropionic acid levels were lower, indicating competitive utilization between the treponemes. This suggests that 3-hydroxypropionic acid may play a pivotal role in bacterial community succession, potentially sourced from other propiogenic bacteria in BDD or from the host itself.
Succinic acid was uniquely produced by T. pedis. Similar to butyric acid, elevated levels of succinic acid have been associated with periodontitis, promoting dysbiosis, inflammation, and bone loss [28]. Historically, succinate produced by Bacteroides spp. in mixed intra-abdominal infections has been shown to impair host polymorphonuclear leukocyte function [29]. In periodontal disease, Tannerella forsythia, a member of the “red complex”, can produce succinate by reducing fumaric acid, thereby promoting the growth of other “red complex” bacteria, such as P. gingivalis [30]. A similar mechanism could be occurring in BDD, as we observed that both succinic acid and fumaric acid were produced by T. pedis, potentially promoting the growth of T. phagedenis.
For oxaloacetic acid and alpha-ketoglutaric acid, there is limited information on their involvement in tissue damage and virulence. However, oxaloacetic acid has been reported to support the anaerobic growth of Actinobacillus pleuropneumoniae, a porcine lung pathogen [31], while alpha-ketoglutaric acid is known to assimilate nitrogen in diverse bacterial communities in the gut [32]. This suggests that these metabolites may be more involved in cooperative metabolism for microbiome succession in BDD.

4.2. Amino Acids

Pathogens require AAs to support their physiological functions, and changes in the availability of AAs can significantly affect pathogen growth and expression of virulence factors [32]. In this study, we observed several AAs that are cooperatively regulated between T. pedis and T. phagedenis, as presented in Table 2 and in Figure 2. Alanine is crucial for bacterial growth and viability [33], and studies have shown that alanine levels are altered at infection sites, such as in periodontitis, where its levels are higher in patients before treatment [34,35].
Aspartic acid showed cooperative interaction between the two treponemes, suggesting its role in their survival within the microbiome. Szafranski et al. (2015) noted increased aspartate degradation in chronic periodontitis patients [36]. Glutamic acid and glutamine were undetectable in T. phagedenis, indicating complete utilization. Closely related treponemes, like the Reiter strain of T. pallidum, are known to degrade AAs such as arginine, histidine, serine, threonine, and glutamic acid [37]. T. phagedenis is closely related to T. pallidum, having been previously classified as one of the non-pathogenic strains of T. pallidum [38]. Although evidence of glutamine’s role as a virulence factor in treponemes is limited, it has been shown that oral supplementation of glutamine in rats reduces periodontitis progression [39]. The absence of glutamine at infection sites could be due to the utilization of the pathogen from the host, potentially causing tissue damage or toxic byproducts from glutamine metabolism. Glutamate levels were also lower in both treponemes. In chronic periodontitis patients, reduced glutamate is linked to its consumption by pathogens like P. gingivalis and F. nucleatum [40]. Glutamic acid is involved in vitamin B12 and porphyrin biosynthesis, promoting proinflammatory responses in skin diseases such as acne vulgaris [41]. Pyroglutamic acid, although utilized in modest levels by T. phagedenis and moderately produced by T. pedis, study suggests cooperation, and its excretion in periodontitis suggests disruptions in oxidative stress response and gluta-thione synthesis [42]. Similarly, T. denticola can convert glycine into serine using serine hydroxymethyltransferase, and further deaminates serine to produce pyruvate, which is metabolized into acetate or lactate [43].
Threonine production by T. pedis may be utilized by T. phagedenis. This interaction parallels those in periodontitis, where pathogens like P. gingivalis assimilate serine and threonine from culture media [44]. Threonine can also be synthesized from glycine or homoserine, as seen in Salmonella Typhimurium, aiding intra-host survival [45]. Proline utilization promotes biofilm growth, suggesting the cooperative regulation of proline by these treponemes enhances biofilm formation and colonization of BDD pathogens [46].
The significant reduction of methionine in the spirochetes might be due to the action of L-methionine-α-deamino-γ-mercaptomethane lyase (METase), which breaks down L-methionine into α-ketobutyrate, ammonia, and methyl mercaptan—another VSC [47]. This has been observed in human periodontitis with pathogens like P. gingivalis [48] and T. denticola [47] after supplementation with heat-inactivated fetal bovine serum. The absence of asparagine in the substrate reduces the formation rate of round bodies in T. denticola, highlighting its importance in forming bacterial persisters during stress or starvation [49].

4.3. Fatty Acids

The significant utilization of FAs by Treponema species has been supported by studies from the 1970s and 1980s on pathogenic treponemes, such as T. pallidum and T. denticola [50]; however, there has been less research on other Treponema species. Our study highlights that FAs are essential metabolic sources for T. pedis and T. phagedenis, with competitive interactions observed between them. FAs are crucial for biosynthesis of cellular membranes and serve as an energy source through catabolism [51]. Treponema species rely on FAs, which constitute a significant portion of their cell mass, primarily as phospholipids in their membranes that enclose the cell body and periplasmic space with peptidoglycan and endoflagellae [52]. Although there is limited evidence specific to BDD treponemes, competition within the microbiome may drive these bacteria to utilize host-derived FAs, similar to other pathogenic bacteria [53]. Previous studies have linked palmitic acid to periodontitis pathogenesis due to its ability to increase pro-inflammatory cytokines [54]. Other reports indicate that host-derived fatty acids serve as nutrient sources for pathogens, such as in Mycobacteria [55].
There are currently limited reports of SCFA production or utilization linked with T. pedis [56]. On the other hand, T. phagedenis has been reported to produce SCFAs and alcohol as fermentation end products [50]. Additionally, the T. phagedenis Reiter strain has been known to produce acetic and N-butyric acids as major fermentation end products, while propionic acid is less common [57]. In vitro trials involving Cutibacterium acnes (formerly Propionibacterium acnes), the causative agent of inflammatory skin disease acne, have shown that strains secrete propionic acid, which contributes to their pathogenicity by affecting keratinocyte cell growth and causing cytotoxicity in a strain-specific and dose-dependent manner [58]. Significant production of propionic acid could explain the glutamic acid utilization, as well as the hyperinflammatory lesions of BDD. In addition, a previous report found that T. phagedenis isolated from BDD produced formic, acetic, and butyric acids, although quantitative data were not provided [59]. The quantitative results for SCFAs obtained in this study are consistent with these earlier findings.
It is assumed that BDD forms through successive waves of bacterial colonization, where early colonizers create an environment favorable for later anaerobic colonizers. Previously, pathogenic treponemes were thought to colonize later once anaerobic conditions were established and mid-colonizers altered nutrient availability by providing SCFAs. However, our results suggest that treponemes themselves produce most SCFAs, particularly butyric acid and propionic acid. Numerous studies have explored butyrate’s role in periodontitis progression [60,61,62,63]. For example, Shirasugi et al. (2018) concluded that elevated butyrate levels are associated with increased periodontitis progression [60]. Although butyrate has beneficial functions in the gut and nervous system, it has detrimental effects in the oral cavity [63], which may be similar in BDD. Formic acid was observed to promote tumor progression by Fusobacterium nucleatum [64].
Treponemes are frequently detected in deeper parts of BDD lesions, where they utilize host-derived AAs and FAs, resulting in the production of SCFAs that may cause dysbiosis and host tissue damage. Recent studies on periodontitis have shown increased SCFA levels as the disease progresses [60,65]. Our findings suggest that BDD treponemes utilize medium- to long-chain FAs, producing polyamines like cadaverine and putrescine. SCFAs are produced from AA and carbohydrate metabolism, creating an acidic microenvironment favorable for treponemal growth and potentially triggering host pro-inflammatory immune responses.

5. Conclusions

This study represents the first detailed exploration of the metabolic footprint of T. phagedenis and T. pedis, two key pathogens associated with BDD. The results revealed significant interactions between these species, including both metabolic competition and cross-feeding. OAs like pyruvic acid and fumaric acid were competitively consumed, while 2-HBA and succinic acid were produced cooperatively by T. pedis, potentially supporting the growth of T. phagedenis. Among AAs, glycine, proline, and threonine were regulated cooperatively, while methionine and glutamic acid were competitively utilized, highlighting important metabolic dependencies that may affect bacterial persistence within BDD lesions. Both species demonstrated significant utilization of FAs such as palmitic acid and linoleic acid, which are essential for their survival and virulence. SCFAs were also central to their metabolic strategies, with T. phagedenis showing increased butyric acid production and both species exhibiting high levels of propionic acid, contributing to the damaging environment of BDD lesions. These insights not only enhance our understanding of the complex polybacterial community within BDD but also highlight potential metabolic targets for therapeutic intervention. Further research is necessary to explore these metabolic interactions in more complex polymicrobial settings that mimic the in vivo environment more closely.

Author Contributions

H.M.E., L.L.M. and Y.-I.C. were responsible for the study’s conceptualization and design. The experimentation was carried out by H.M.E., L.L.M., E.J.P.V. and M.-J.P. Data analysis was conducted by H.M.E. and E.J.P.V. Manuscript writing was completed by H.M.E. and E.J.P.V., with editing and revising performed by M.J., M.-J.P. and Y.-I.C. S.-S.L., M.-J.P. and Y.-I.C. supervised the research, while Y.-I.C. secured funding for the project. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported and funded by the National Research Foundation of Korea (NRF-2021R1I1A3043691).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All data included in this study are presented within the manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Lubbe, A.; Bowen, B.P.; Northen, T. Exometabolomic Analysis of Cross-Feeding Metabolites. Metabolites 2017, 7, 50. [Google Scholar] [CrossRef] [PubMed]
  2. Zelezniak, A.; Andrejev, S.; Ponomarova, O.; Mende, D.R.; Bork, P.; Patil, K.R. Metabolic Dependencies Drive Species Co-Occurrence in Diverse Microbial Communities. Proc. Natl. Acad. Sci. USA 2015, 112, 6449–6454. [Google Scholar] [CrossRef] [PubMed]
  3. Molina, C.A.; Vilchez, S. Cooperation and Bacterial Pathogenicity: An Approach to Social Evolution. Rev. Chil. Hist. Nat. 2014, 87, 14. [Google Scholar] [CrossRef]
  4. Gabrilska, R.A.; Rumbaugh, K.P. Biofilm Models of Polymicrobial Infection. Future Microbiol. 2015, 10, 1997. [Google Scholar] [CrossRef] [PubMed]
  5. Krull, A.C.; Shearer, J.K.; Gorden, P.J.; Cooper, V.L.; Phillips, G.J.; Plummera, P.J. Deep Sequencing Analysis Reveals Temporal Microbiota Changes Associated with Development of Bovine Digital Dermatitis. Infect. Immun. 2014, 82, 3359–3373. [Google Scholar] [CrossRef]
  6. Espiritu, H.M.; Mamuad, L.L.; Kim, S.; Jin, S.; Lee, S.; Kwon, S.; Cho, Y. Microbiome Shift, Diversity, and Overabundance of Opportunistic Pathogens in Bovine Digital Dermatitis Revealed by 16S RRNA Amplicon Sequencing. Animals 2020, 10, 1798. [Google Scholar] [CrossRef]
  7. Moreira, T.F.; Facury Filho, E.J.; Carvalho, A.U.; Strube, M.L.; Nielsen, M.W.; Klitgaard, K.; Jensen, T.K. Pathology and Bacteria Related to Digital Dermatitis in Dairy Cattle in All Year-Round Grazing System in Brazil. PLoS ONE 2018, 13, e0193870. [Google Scholar] [CrossRef]
  8. Bay, V.; Griffiths, B.; Carter, S.; Evans, N.J.; Lenzi, L.; Bicalho, R.C.; Oikonomou, G. 16S RRNA Amplicon Sequencing Reveals a Polymicrobial Nature of Complicated Claw Horn Disruption Lesions and Interdigital Phlegmon in Dairy Cattle. Sci. Rep. 2018, 8, 15529. [Google Scholar] [CrossRef]
  9. Zinicola, M.; Lima, F.; Lima, S.; Machado, V.; Gomez, M. Altered Microbiomes in Bovine Digital Dermatitis Lesions, and the Gut as a Pathogen Reservoir. PLoS ONE 2015, 10, e0120504. [Google Scholar] [CrossRef]
  10. Schrank, K.; Choi, B.K.; Grund, S.; Moter, A.; Heuner, K.; Nattermann, H.; Göbel, U.B. Treponema brennaborense sp. nov., a Novel Spirochaete Isolated from a Dairy Cow Suffering from Digital Dermatitis. Int. J. Syst. Bacteriol. 1999, 49, 43–50. [Google Scholar] [CrossRef]
  11. Nally, J.E.; Hornsby, R.L.; Alt, D.P.; Whitelegge, J.P. Phenotypic and Proteomic Characterization of Treponemes Associated with Bovine Digital Dermatitis. Vet. Microbiol. 2019, 235, 35–42. [Google Scholar] [CrossRef] [PubMed]
  12. Evans, N.J.; Brown, J.M.; Demirkan, I.; Murray, R.D.; Birtles, R.J.; Hart, C.A.; Carter, S.D. Treponema pedis sp. nov., a Spirochaete Isolated from Bovine Digital Dermatitis Lesions. Int. J. Syst. Evol. Microbiol. 2009, 59, 987–991. [Google Scholar] [CrossRef] [PubMed]
  13. Kuhnert, P.; Brodard, I.; Alsaaod, M.; Steiner, A.; Stoffel, M.H.; Jores, J. Treponema phagedenis (Ex Noguchi 1912) Brumpt 1922 sp. nov., nom. rev., Isolated from Bovine Digital Dermatitis. Int. J. Syst. Evol. Microbiol. 2020, 70, 2115–2123. [Google Scholar] [CrossRef] [PubMed]
  14. Staton, G.J.; Clegg, S.R.; Ainsworth, S.; Armstrong, S.; Carter, S.D.; Radford, A.D.; Darby, A.; Wastling, J.; Hall, N.; Evans, N.J. Dissecting the Molecular Diversity and Commonality of Bovine and Human Treponemes Identifies Key Survival and Adhesion Mechanisms. PLoS Pathog. 2021, 17, e1009464. [Google Scholar] [CrossRef]
  15. Nielsen, M.W.; Strube, M.L.; Isbrand, A.; Al-Medrasi, W.D.H.M.; Boye, M.; Jensen, T.K.; Klitgaard, K. Potential Bacterial Core Species Associated with Digital Dermatitis in Cattle Herds Identified by Molecular Profiling of Interdigital Skin Samples. Vet. Microbiol. 2016, 186, 139–149. [Google Scholar] [CrossRef]
  16. Demirkan, I.; Evans, N.J.; Singh, P.; Brown, J.M.; Getty, B.; Carter, S.D.; Timofte, D.; Hart, C.A.; Vink, W.D.; Birtles, R.J.; et al. Association of Unique, Isolated Treponemes with Bovine Digital Dermatitis Lesions. J. Clin. Microbiol. 2009, 47, 689–696. [Google Scholar] [CrossRef]
  17. Espiritu, H.M.; Mamuad, L.L.; Jin, S.; Kim, S.; Kwon, S.; Lee, S.; Lee, S.; Cho, Y. Genotypic and Phenotypic Characterization of Treponema phagedenis from Bovine Digital Dermatitis. Microorganisms 2020, 8, 1520. [Google Scholar] [CrossRef]
  18. Espiritu, H.; Mamuad, L.; Valete, E.J.; Jung, M.; Lee, S.S.; Cho, Y.L. Complete Genome Sequence of Treponema pedis GNW45 Isolated from Dairy Cattle with Active Bovine Digital Dermatitis in Korea. J. Anim. Sci. Technol. 2023. pISSN: 2055-0391, eISSN: 2672-0191. [Google Scholar] [CrossRef]
  19. Kim, Y.; Kim, S.H.; Oh, S.J.; Lee, H.S.; Ji, M.; Choi, S.; Lee, S.S.; Paik, M.J. Metabolomic Analysis of Organic Acids, Amino Acids, and Fatty Acids in Plasma of Hanwoo Beef on a High-Protein Diet. Metabolomics 2020, 16, 114. [Google Scholar] [CrossRef]
  20. Silva, L.P.; Northen, T.R. Exometabolomics and MSI: Deconstructing How Cells Interact to Transform Their Small Molecule Environment. Curr. Opin. Biotechnol. 2015, 34, 209–216. [Google Scholar] [CrossRef]
  21. Freilich, S.; Zarecki, R.; Eilam, O.; Segal, E.S.; Henry, C.S.; Kupiec, M.; Gophna, U.; Sharan, R.; Ruppin, E. Competitive and Cooperative Metabolic Interactions in Bacterial Communities. Nat. Commun. 2011, 2, 589. [Google Scholar] [CrossRef]
  22. Doelle, H.W. Carbohydrate Metabolism. In Bacterial Metabolism; Elsevier: Amsterdam, The Netherlands, 1975; pp. 208–311. [Google Scholar]
  23. Kreth, J.; Lengeler, J.W.; Jahreis, K. Characterization of Pyruvate Uptake in Escherichia Coli K-12. PLoS ONE 2013, 8, e67125. [Google Scholar] [CrossRef] [PubMed]
  24. Nichols, J.C.; Baseman, J.B. Carbon Sources Utilized by Virulent Treponema pallidum. Infect. Immun. 1975, 12, 1044–1050. [Google Scholar] [CrossRef] [PubMed]
  25. Chu, L.; Dong, Z.; Xu, X.; Cochran, D.L.; Ebersole, J.L. Role of Glutathione Metabolism of Treponema denticola in Bacterial Growth and Virulence Expression. Infect. Immun. 2002, 70, 1113–1120. [Google Scholar] [CrossRef] [PubMed]
  26. Blötz, C.; Stülke, J. Glycerol Metabolism and Its Implication in Virulence in Mycoplasma. FEMS Microbiol. Rev. 2017, 41, 640–652. [Google Scholar] [CrossRef] [PubMed]
  27. Sun, Z.J.; Wu, L.; Huang, W.; Chen, C.; Chen, Y.; Lu, X.L.; Zhang, X.L.; Yang, B.F.; Dong, D.L. Glycolic Acid Modulates the Mechanical Property and Degradation of Poly(Glycerol, Sebacate, Glycolic Acid). J. Biomed. Mater. Res. A 2010, 92, 332–339. [Google Scholar] [CrossRef]
  28. Guo, Y.; Xu, F.; Thomas, S.C.; Zhang, Y.; Paul, B.; Sakilam, S.; Chae, S.; Li, P.; Almeter, C.; Kamer, A.R.; et al. Targeting the Succinate Receptor Effectively Inhibits Periodontitis. Cell Rep. 2022, 40, 111389. [Google Scholar] [CrossRef]
  29. Rotstein, O.D.; Pruett, T.L.; Fiegel, V.D.; Nelson, R.D.; Simmons, R.L. Succinic Acid, a Metabolic by-Product of Bacteroides Species, Inhibits Polymorphonuclear Leukocyte Function. Infect. Immun. 1985, 48, 402. [Google Scholar] [CrossRef]
  30. Sharma, A. Virulence Mechanisms of Tannerella forsythia. Periodontol. 2000 2010, 54, 106. [Google Scholar] [CrossRef]
  31. Konze, S.A.; Abraham, W.R.; Goethe, E.; Surges, E.; Kuypers, M.M.M.; Hoeltig, D.; Meens, J.; Vogel, C.; Stiesch, M.; Valentin-Weigand, P.; et al. Link between Heterotrophic Carbon Fixation and Virulence in the Porcine Lung Pathogen Actinobacillus pleuropneumoniae. Infect. Immun. 2019, 87, 10–1128. [Google Scholar] [CrossRef]
  32. Pierzynowski, S.; Pierzynowska, K. Alpha-Ketoglutarate, a Key Molecule Involved in Nitrogen Circulation in Both Animals and Plants, in the Context of Human Gut Microbiota and Protein Metabolism. Adv. Med. Sci. 2022, 67, 142–147. [Google Scholar] [CrossRef]
  33. Sidiq, K.R.; Chow, M.W.; Zhao, Z.; Daniel, R.A. Alanine Metabolism in Bacillus Subtilis. Mol. Microbiol. 2020, 115, 739–757. [Google Scholar] [CrossRef] [PubMed]
  34. Ren, W.; Rajendran, R.; Zhao, Y.; Tan, B.; Wu, G.; Bazer, F.W.; Zhu, G.; Peng, Y.; Huang, X.; Deng, J.; et al. Amino Acids as Mediators of Metabolic Cross Talk between Host and Pathogen. Front. Immunol. 2018, 9, 319. [Google Scholar] [CrossRef] [PubMed]
  35. Citterio, F.; Romano, F.; Meoni, G.; Iaderosa, G.; Grossi, S.; Sobrero, A.; Dego, F.; Corana, M.; Berta, G.N.; Tenori, L.; et al. Changes in the Salivary Metabolic Profile of Generalized Periodontitis Patients after Non-Surgical Periodontal Therapy: A Metabolomic Analysis Using Nuclear Magnetic Resonance Spectroscopy. J. Clin. Med. 2020, 9, 3977. [Google Scholar] [CrossRef] [PubMed]
  36. Szafrański, S.P.; Deng, Z.L.; Tomasch, J.; Jarek, M.; Bhuju, S.; Meisinger, C.; Kühnisch, J.; Sztajer, H.; Wagner-Döbler, I. Functional Biomarkers for Chronic Periodontitis and Insights into the Roles of Prevotella nigrescens and Fusobacterium nucleatum; a Metatranscriptome Analysis. npj Biofilms Microbiomes 2015, 1, 15017. [Google Scholar] [CrossRef] [PubMed]
  37. Allen, S.L.; Johnson, R.C.; Peterson, D. Metabolism of Common Substrates by the Reiter Strain of Treponema pallidum. Infect. Immun. 1971, 3, 727–734. [Google Scholar] [CrossRef]
  38. Miao, R.; Fieldsteel, A.H. Genetics of Treponema: Relationship between Treponema pallidum and Five Cultivable Treponemes. J. Bacteriol. 1978, 133, 101–107. [Google Scholar] [CrossRef]
  39. Silva Junior, A.R.D.; Semenoff Segundo, A.; Semenoff, T.A.D.V.; Silva, N.F.D.; CoporossiI, C. Effect of Glutamine Ingestion on the Progression of Induced Periodontitis: Experimental Study in Rats. Rev. Odontol. UNESP 2018, 47, 119–123. [Google Scholar] [CrossRef]
  40. Téllez, N.; Aguilera, N.; Quiñónez, B.; Silva, E.; González, L.E.; Hernández, L. Arginine and Glutamate Levels in the Gingival Crevicular Fluid from Patients with Chronic Periodontitis. Braz. Dent. J. 2008, 19, 318–322. [Google Scholar] [CrossRef]
  41. Kang, D.; Shi, B.; Erfe, M.C.; Craft, N.; Li, H. Vitamin B12 Modulates the Transcriptome of the Skin Microbiota in Acne Pathogenesis. Sci. Transl. Med. 2015, 7, 293ra103. [Google Scholar] [CrossRef]
  42. Tsuchida, S.; Nakayama, T. Metabolomics Research in Periodontal Disease by Mass Spectrometry. Molecules 2022, 27, 2864. [Google Scholar] [CrossRef]
  43. Tan, K.H.; Seers, C.A.; Dashper, S.G.; Mitchell, H.L.; Pyke, J.S.; Meuric, V.; Slakeski, N.; Cleal, S.M.; Chambers, J.L.; McConville, M.J.; et al. Porphyromonas gingivalis and Treponema denticola Exhibit Metabolic Symbioses. PLoS Pathog. 2014, 10, e1003955. [Google Scholar] [CrossRef] [PubMed]
  44. Dashper, S.G.; Brownfield, L.; Slakeski, N.; Zilm, P.S.; Rogers, A.H.; Reynolds, E.C. Sodium Ion-Driven Serine/Threonine Transport in Porphyromonas gingivalis. J. Bacteriol. 2001, 183, 4142–4148. [Google Scholar] [CrossRef]
  45. Jelsbak, L.; Hartman, H.; Schroll, C.; Rosenkrantz, J.T.; Lemire, S.; Wallrodt, I.; Thomsen, L.E.; Poolman, M.; Kilstrup, M.; Jensen, P.R.; et al. Identification of Metabolic Pathways Essential for Fitness of Salmonella Typhimurium in Vivo. PLoS ONE 2014, 9, e101869. [Google Scholar] [CrossRef] [PubMed]
  46. Cleaver, L.M.; Moazzez, R.V.; Carpenter, G.H. Evidence for Proline Utilization by Oral Bacterial Biofilms Grown in Saliva. Front. Microbiol. 2021, 11, 619968. [Google Scholar] [CrossRef]
  47. Fukamachi, H.; Nakano, Y.; Okano, S.; Shibata, Y.; Abiko, Y.; Yamashita, Y. High Production of Methyl Mercaptan by L-Methionine-α-Deamino-γ-Mercaptomethane Lyase from Treponema denticola. Biochem. Biophys. Res. Commun. 2005, 331, 127–131. [Google Scholar] [CrossRef]
  48. Stephen, A.S.; Millhouse, E.; Sherry, L.; Aduse-Opoku, J.; Culshaw, S.; Ramage, G.; Bradshaw, D.J.; Burnett, G.R.; Allaker, R.P. In Vitro Effect of Porphyromonas gingivalis Methionine Gamma Lyase on Biofilm Composition and Oral Inflammatory Response. PLoS ONE 2016, 11, e0169157. [Google Scholar] [CrossRef]
  49. De Ciccio, A.; McLaughlin, R.; Chan, E.C.S. Factors Affecting the Formation of Spherical Bodies in the Spirochete Treponema denticola. Oral Microbiol. Immunol. 1999, 14, 384–386. [Google Scholar] [CrossRef]
  50. Van Horn, K.G.; Smibert, R.M. Fatty Acid Requirement of Treponema denticola and Treponema vincentii. Can. J. Microbiol. 1982, 28, 344–350. [Google Scholar] [CrossRef] [PubMed]
  51. Mitchell, M.K.; Ellermann, M. Long Chain Fatty Acids and Virulence Repression in Intestinal Bacterial Pathogens. Front. Cell. Infect. Microbiol. 2022, 12, 801. [Google Scholar] [CrossRef]
  52. Wyss, C. Fatty Acids Synthesized by Oral Treponemes in Chemically Defined Media. FEMS Microbiol. Lett. 2007, 269, 70–76. [Google Scholar] [CrossRef]
  53. Teoh, W.P.; Chen, X.; Laczkovich, I.; Alonzo, F. Staphylococcus aureus Adapts to the Host Nutritional Landscape to Overcome Tissue-Specific Branched-Chain Fatty Acid Requirement. Proc. Natl. Acad. Sci. USA 2021, 118, e2022720118. [Google Scholar] [CrossRef] [PubMed]
  54. Shikama, Y.; Kudo, Y.; Ishimaru, N.; Funaki, M. Possible Involvement of Palmitate in Pathogenesis of Periodontitis. J. Cell. Physiol. 2015, 230, 2981–2989. [Google Scholar] [CrossRef] [PubMed]
  55. Yang, H.; Wang, F.; Guo, X.; Liu, F.; Liu, Z.; Wu, X.; Zhao, M.; Ma, M.; Liu, H.; Qin, L.; et al. Interception of Host Fatty Acid Metabolism by Mycobacteria under Hypoxia to Suppress Anti-TB Immunity. Cell Discov. 2021, 7, 90. [Google Scholar] [CrossRef] [PubMed]
  56. Krieg, N.R.; Staley, J.T.; Brown, D.R.; Hedlund, B.P.; Paster, B.J.; Ward, N.L.; Ludwig, W.; Whitman, W.B.; Parte, A.C. Bergey’s Manual of Systematic Bacteriology Volume 4: The Bacteroidetes, Spirochaetes, Tenericutes (Mollicutes), Acidobacteria, Fibrobacteres, Fusobacteria, Dictyoglomi, Gemmatimonadetes, Lentisphaerae, Verrucomicrobia, Chlamydiae, and Planctomycetes; Springer: New York, NY, USA, 2011; ISBN 9780387950426. [Google Scholar]
  57. O’Leary, W. Practical Handbook of Microbiology; CRC Press: New York, NY, USA; Washington, DC, USA, 1989; ISBN 9781466587403. [Google Scholar]
  58. Tax, G.; Urbán, E.; Palotás, Z.; Puskás, R.; Kónya, Z.; Bíró, T.; Kemény, L.; Szabó, K. Propionic Acid Produced by Propionibacterium acnes Strains Contributes to Their Pathogenicity. Acta Derm. Venereol. 2016, 96, 43–49. [Google Scholar] [CrossRef]
  59. Wilson-Welder, J.H.; Elliott, M.K.; Zuerner, R.L.; Bayles, D.O.; Alt, D.P.; Stanton, T.B. Biochemical and Molecular Characterization of Treponema phagedenis-like Spirochetes Isolated from a Bovine Digital Dermatitis Lesion. BMC Microbiol. 2013, 13, 280. [Google Scholar] [CrossRef]
  60. Shirasugi, M.; Nakagawa, M.; Nishioka, K.; Yamamoto, T.; Nakaya, T.; Kanamura, N. Relationship between Periodontal Disease and Butyric Acid Produced by Periodontopathic Bacteria. Inflamm. Regen. 2018, 38, 23. [Google Scholar] [CrossRef]
  61. Zhao, Y.; Li, J.; Guo, W.; Li, H.; Lei, L. Periodontitis-Level Butyrate-Induced Ferroptosis in Periodontal Ligament Fibroblasts by Activation of Ferritinophagy. Cell Death Discov. 2020, 6, 119. [Google Scholar] [CrossRef]
  62. Hou, J.; Xu, J.; Liu, Y.; Zhang, H.; Wang, S.; Jiao, Y.; Guo, L.; Li, S. Sodium Butyrate Inhibits Osteogenesis in Human Periodontal Ligament Stem Cells by Suppressing Smad1 Expression. BMC Oral Health 2022, 22, 301. [Google Scholar] [CrossRef]
  63. Guan, X.; Li, W.; Meng, H. A Double-Edged Sword: Role of Butyrate in the Oral Cavity and the Gut. Mol. Oral Microbiol. 2021, 36, 121–131. [Google Scholar] [CrossRef]
  64. VanHook, A.M. Formate for Tumor Progression. Sci. Signal. 2022, 15, eadd1844. [Google Scholar] [CrossRef]
  65. Hatanaka, K.; Shirahase, Y.; Yoshida, T.; Kono, M.; Toya, N.; Sakasegawa, S.I.; Konishi, K.; Yamamoto, T.; Ochiai, K.; Takashiba, S. Enzymatic Measurement of Short-Chain Fatty Acids and Application in Periodontal Disease Diagnosis. PLoS ONE 2022, 17, e0268671. [Google Scholar] [CrossRef] [PubMed]
Pathogens 13 00796 g001
Figure 1. (A) Illustrates the normalized concentration values of OAs in the culture medium negative control (Con), T. pedis, and T. phagedenis, with each axis representing a different OA; (B) shows the percentage composition of each OA in the culture media. Each segment represents a different OA, indicating their relative abundance.
Figure 1. (A) Illustrates the normalized concentration values of OAs in the culture medium negative control (Con), T. pedis, and T. phagedenis, with each axis representing a different OA; (B) shows the percentage composition of each OA in the culture media. Each segment represents a different OA, indicating their relative abundance.
Pathogens 13 00796 g001
Pathogens 13 00796 g002
Figure 2. (A) Illustrates the normalized concentration values of AAs in the culture medium negative control (Con), T. pedis, and T. phagedenis, with each axis representing a different AA; (B) shows the percentage composition of each AA in the culture media. Each segment represents a different AA, indicating their relative abundance.
Figure 2. (A) Illustrates the normalized concentration values of AAs in the culture medium negative control (Con), T. pedis, and T. phagedenis, with each axis representing a different AA; (B) shows the percentage composition of each AA in the culture media. Each segment represents a different AA, indicating their relative abundance.
Pathogens 13 00796 g002
Pathogens 13 00796 g003
Figure 3. The radar plots show normalized concentration values of FAs (A) and SCFAs (B) between negative control (Con), T. pedis, and T. phagedenis in the culture medium. The column charts depict the percentage composition of each FA (C) and SCFA (D) in the culture media. Each segment represents a metabolite presenting their relative abundance.
Figure 3. The radar plots show normalized concentration values of FAs (A) and SCFAs (B) between negative control (Con), T. pedis, and T. phagedenis in the culture medium. The column charts depict the percentage composition of each FA (C) and SCFA (D) in the culture media. Each segment represents a metabolite presenting their relative abundance.
Pathogens 13 00796 g003
Table 1. Quantitative analysis of organic acid profiles in culture media of Treponema spp.
Table 1. Quantitative analysis of organic acid profiles in culture media of Treponema spp.
OA (ng/5 µL)ControlT. pedisT. phagedenisSEMp-Value
Pyruvic acid1258.4 a484.2 b239.6 b64.76<0.001
Glycolic acid1666.9 a1680.9 a1302.5 b48.0<0.001
2-Hydroxybutyric acid8.0 b47.5 a8.5 b0.69<0.001
3-Hydroxypropionic acid365.8 a322.3 a198.5 b28.690.019
Succinic acid217 b284.9 a213.1 b8.74<0.001
Fumaric acid12 b16.4 a6.2 c0.77<0.001
Oxaloacetic acid17.1 a19.8 a12.1 b0.85<0.001
α-Ketoglutaric acid34.1 a32.8 a13.4 b1.56<0.001
Malic acid95.6114.5132.710.890.205
2-Hydroxyglutaric acid82.2121.676.315.450.231
Different superscripts (a,b,c) within the same row indicate statistically significant differences between groups (control, T. pedis, T. phagedenis) based on one-way ANOVA and Duncan’s multiple range test (DMRT) (p < 0.05).
Table 2. Quantitative analysis of amino acid profiles in culture media of Treponema spp.
Table 2. Quantitative analysis of amino acid profiles in culture media of Treponema spp.
OA (ng/2 µL)ControlT. pedisT. phagedenisSEMp-Value
Alanine59.1 c83.3 a71.4 b52.09<0.001
Glycine23.4 b0.6 c38.4 a13.79<0.001
Valine62.368.764.446.390.556
Leucine86.992.487.360.690.188
Isoleucine112.5109.4107.877.060.933
Proline50.8 b89.7 a43.9 b46.78<0.001
Pyroglutamic acid39.241.726.324.730.060
Methionine24.4 a14.2 b21.5 ab12.50.047
Serine28.0 a29.1 a0.6 b12.170.004
Threonine24.0 b38.1 a13.2 b18.930.008
Phenylalanine47.046.148.60.750.165
Aspartic acid32.4 ab23.7 b48.4 a3.960.030
Glutamic acid205.8 a147.8 a0 b17.460.003
Asparagine21.416.48.62.290.078
Ornithine10.710.711.00.620.931
Glutamine12.5 a10.1 a0 b0.870.001
Lysine135.4133.4126.615.010.925
Tyrosine39.834.535.03.660.633
Tryptophan52.039.933.97.350.383
Different superscripts (a,b,c) within the same row indicate statistically significant differences between groups (control, T. pedis, T. phagedenis) based on one-way ANOVA and Duncan’s multiple range test (DMRT) (p < 0.05).
Table 3. Quantitative analysis of fatty acid (FA) and short-chain fatty acid (SCFA) profiles in culture media.
Table 3. Quantitative analysis of fatty acid (FA) and short-chain fatty acid (SCFA) profiles in culture media.
FA (ng/2 µL)ControlT. pedisT. phagedenisSEMp-Value
cis-9-Hexadecenoic acid (C16:1)146.9 a28.8 b18.6 c2.12<0.001
Palmitic acid (C16:0)1115.3 a191.4 b142.2 b79.98<0.001
Linoleic acid (C18:2)135.1 a18.5 c70.5 b2.29<0.001
Oleic acid (C18:1)745.1 a431.4 b386.2 b14.24<0.001
Octadecanoic acid (C18:0)730.9405.7228.4159.480.203
Octacosanoic acid (C28:0)257.093.4310.7100.560.523
SCFA (mM)
Lactic acid26.1 a15.28 b12.99 b2.150.002
Formic acid0 b0 b5.1 a0.85<0.001
Acetic acid22.08 b50.96 a26.59 b4.72<0.001
Propionic acid5.73 c59.18 a28.41 b7.79<0.001
Butyric acid16.19 c67.55 b116.58 a14.50<0.001
Different superscripts (a,b,c) within the same row indicate statistically significant differences between groups (control, T. pedis, T. phagedenis) based on one-way ANOVA and Duncan’s multiple range test (DMRT) (p < 0.05).
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Espiritu, H.M.; Valete, E.J.P.; Mamuad, L.L.; Jung, M.; Paik, M.-J.; Lee, S.-S.; Cho, Y.-I. Metabolic Footprint of Treponema phagedenis and Treponema pedis Reveals Potential Interaction Towards Community Succession and Pathogenesis in Bovine Digital Dermatitis. Pathogens 2024, 13, 796. https://doi.org/10.3390/pathogens13090796

AMA Style

Espiritu HM, Valete EJP, Mamuad LL, Jung M, Paik M-J, Lee S-S, Cho Y-I. Metabolic Footprint of Treponema phagedenis and Treponema pedis Reveals Potential Interaction Towards Community Succession and Pathogenesis in Bovine Digital Dermatitis. Pathogens. 2024; 13(9):796. https://doi.org/10.3390/pathogens13090796

Chicago/Turabian Style

Espiritu, Hector M., Edeneil Jerome P. Valete, Lovelia L. Mamuad, Myunghwan Jung, Man-Jeong Paik, Sang-Suk Lee, and Yong-Il Cho. 2024. "Metabolic Footprint of Treponema phagedenis and Treponema pedis Reveals Potential Interaction Towards Community Succession and Pathogenesis in Bovine Digital Dermatitis" Pathogens 13, no. 9: 796. https://doi.org/10.3390/pathogens13090796

APA Style

Espiritu, H. M., Valete, E. J. P., Mamuad, L. L., Jung, M., Paik, M.-J., Lee, S.-S., & Cho, Y.-I. (2024). Metabolic Footprint of Treponema phagedenis and Treponema pedis Reveals Potential Interaction Towards Community Succession and Pathogenesis in Bovine Digital Dermatitis. Pathogens, 13(9), 796. https://doi.org/10.3390/pathogens13090796

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop