Microbial Bioactives

1. Introduction

Antimicrobial resistance (AMR) has gradually evolved from a largely clinical concern into a broader global health emergency that now intersects with microbiology, public health, biotechnology, and even socioeconomic stability. What once appeared manageable through successive generations of antibiotics is increasingly becoming unpredictable, particularly as resistant pathogens continue to emerge faster than many conventional therapeutics can be developed. The problem is no longer confined to isolated hospital-acquired infections; rather, resistant microorganisms are now deeply embedded within community settings, environmental reservoirs, and complex host-associated microbial ecosystems (Mantravadi et al., 2019). Although antibiotics transformed medicine throughout the twentieth century, their prolonged and frequently indiscriminate use has accelerated adaptive microbial responses, ultimately reduced therapeutic effectiveness and narrowed available treatment options (Coates et al., 2002; Jubeh et al., 2020).

For decades, antimicrobial discovery relied heavily on targeting a relatively small number of bacterial processes, particularly DNA replication, protein synthesis, and cell wall biosynthesis. Initially, these approaches were remarkably successful. Yet bacteria, perhaps unsurprisingly, have demonstrated extraordinary evolutionary flexibility. Resistance mechanisms such as efflux pumps, enzymatic degradation, target modification, and horizontal gene transfer have become increasingly widespread, complicating infection management in both clinical and environmental contexts (Mantravadi et al., 2019). Consequently, antimicrobial research has shifted toward identifying more selective and less resistance-prone molecular targets. Particular attention has been directed toward bacterial metabolic pathways absent in mammalian hosts, as these systems may provide opportunities for narrow-spectrum therapies with reduced off-target toxicity (Hudson et al., 2008).

Among the most promising targets are enzymes involved in the shikimate pathway and the L,L-diaminopimelate biosynthesis pathway. These metabolic systems are essential for bacterial survival yet absent in humans, making them attractive candidates for antimicrobial intervention (Gonzalez-Bello, 2016; Hudson et al., 2008). Similarly, structurally conserved cell wall intermediates such as Lipid II have gained considerable attention because their functional conservation reduces the likelihood of rapid mutational escape. The discovery of teixobactin represented an especially important milestone in this regard, not necessarily because it completely solved resistance-associated challenges, but because it demonstrated that novel antimicrobial scaffolds can still emerge from previously inaccessible microbial populations (Ling et al., 2015). Compounds such as lassomycin further reinforce the growing interest in targeting bacterial proteostasis systems, particularly ATP-dependent proteases associated with persistence and survival under stress conditions (Gavrish et al., 2014).

At the same time, it has become increasingly evident that antimicrobial resistance cannot be understood solely through the lens of planktonic bacterial growth. Biofilms, which are structured microbial communities embedded within extracellular polymeric matrices, fundamentally alter microbial physiology and antimicrobial susceptibility. These highly organized systems create protective microenvironments that shield bacteria from antibiotics, immune responses, and environmental stressors (Brackman & Coenye, 2015). In many chronic infections, including oral, pulmonary, and device-associated infections, biofilm formation appears to contribute substantially to treatment failure and recurrence. Interestingly, the resilience of biofilms is not simply structural; it is also regulatory. Quorum sensing (QS), the bacterial communication process responsible for coordinating collective behavior, plays a central role in biofilm maturation, virulence expression, and microbial adaptation (Gutierrez et al., 2009; Han & Lu, 2009).

Because of this, quorum sensing inhibition has emerged as a particularly intriguing “anti-virulence” strategy. Rather than directly killing bacterial cells, quorum sensing inhibitors (QSIs) attempt to disarm pathogenic behaviors by disrupting microbial communication networks (Brackman & Coenye, 2015). This distinction may prove important, as therapies that reduce virulence without exerting strong bactericidal pressure could theoretically slow the emergence of resistance. Several compounds targeting LuxS, MTAN, and related signaling systems have demonstrated encouraging activity against biofilm-associated pathogens (Gutierrez et al., 2009; Lee et al., 2005). Likewise, azithromycin and other signaling-modulating agents have shown the capacity to interfere with quorum sensing-regulated alginate production in Pseudomonas aeruginosa, thereby weakening biofilm integrity and persistence (Hoffmann et al., 2007). Natural compounds capable of reducing intracellular cyclic-di-GMP levels, such as raffinose-derived molecules, have also demonstrated anti-biofilm potential, suggesting that microbial signaling pathways may offer multiple intervention points beyond traditional antibiotic targets (Kim et al., 2016).

Another challenge complicating antimicrobial therapy is the existence of persister cells. These dormant or metabolically inactive bacterial populations are not necessarily genetically resistant, yet they tolerate antibiotic exposure and frequently contribute to recurrent infections. Persisters are particularly problematic in chronic diseases where prolonged treatment fails to fully eradicate microbial reservoirs. Recent work involving Clp proteases suggests that manipulating bacterial proteolytic systems may provide a viable strategy for eliminating these difficult-to-target populations (Conlon et al., 2013; Gavrish et al., 2014). Although still emerging, this field reflects a broader shift in antimicrobial research away from simple growth inhibition toward a deeper understanding of microbial physiology, stress adaptation, and persistence mechanisms.

Parallel to these molecular developments, advances in genomics and computational biology have profoundly reshaped antimicrobial discovery pipelines. Traditional “culture-and-screen” approaches, while historically productive, overlooked the overwhelming majority of microbial diversity because many microorganisms remain difficult or impossible to cultivate under conventional laboratory conditions. Genome mining platforms such as antiSMASH now allow researchers to identify cryptic biosynthetic gene clusters that may encode previously unknown antimicrobial metabolites (Blin et al., 2017). Meanwhile, culturomics and metagenomics have expanded access to microbial communities that were once considered inaccessible, revealing an extraordinary reservoir of metabolic potential within environmental and host-associated microbiota (Lagier et al., 2018).

These technological advances are especially relevant in microbiome research, where the distinction between pathogenicity and ecological imbalance is increasingly blurred. Dysbiosis, rather than single-pathogen infection alone, is now recognized as an important contributor to oral, gastrointestinal, vaginal, and systemic diseases (Giordano-Kelhoffer et al., 2022). Oral microbial imbalance, for example, has been associated not only with periodontal disease but also with broader inflammatory and neurodegenerative conditions, including Alzheimer’s disease (Borsa et al., 2021). This evolving perspective has encouraged the development of microbiome-centered therapeutics aimed not merely at eradicating pathogens but at restoring ecological equilibrium.

In this context, probiotics and next-generation probiotics (NGPs) have emerged as particularly promising therapeutic tools. Unlike traditional antimicrobials, probiotics may exert beneficial effects through competitive exclusion, immunomodulation, metabolite production, and stabilization of microbial communities (Abouelela & Helmy, 2024). Clinical investigations involving Lactobacillus, Bifidobacterium, and Streptococcus salivarius strains have demonstrated reductions in oral Candida colonization and improvements in microbial balance across several patient populations (Burton et al., 2013; Hatakka et al., 2007; Ishikawa et al., 2015). Additional studies involving recurrent candidiasis and bacterial vaginosis have suggested that probiotic formulations may also influence vaginal microbial ecosystems and inflammatory responses (Bisanz et al., 2014; Bradshaw et al., 2012; Mastromarino et al., 2009; Oerlemans et al., 2020).

Still, probiotic efficacy is not always uniform. Outcomes often vary according to strain composition, dosing regimen, microbial baseline composition, and host physiology. Multi-strain formulations frequently demonstrate stronger or more consistent effects than single-strain preparations, possibly because of synergistic microbial interactions and broader ecological coverage (Kraft-Bodi et al., 2015; Li et al., 2014; Miyazima et al., 2017). Likewise, probiotic-enriched dietary interventions, including fermented dairy products, have shown measurable influence on oral microbial composition and pathogen suppression (Keller & Kragelund, 2018; Petti et al., 2001). These findings suggest that microbiome modulation may become an increasingly important complement to conventional antimicrobial therapy, particularly in conditions associated with chronic dysbiosis and biofilm persistence.

Natural products also continue to play an indispensable role in antimicrobial discovery. Essential oils and phytochemical-derived compounds possess diverse antibacterial, antifungal, and immunomodulatory activities, often acting through multiple mechanisms simultaneously (Freires et al., 2015). This mechanistic diversity may reduce the likelihood of rapid resistance development compared with highly specific single-target drugs. Importantly, the integration of natural compounds, biofilm-disrupting agents, probiotics, and precision molecular inhibitors reflects a broader conceptual transition within antimicrobial science. The field is gradually moving away from a singular “kill-the-pathogen” philosophy toward more ecologically informed and systems-oriented therapeutic strategies.

Taken together, contemporary antimicrobial research appears to be entering a far more integrative phase—one that combines microbiome science, synthetic biology, genomics, bioinformatics, and molecular pharmacology to address the growing complexity of infectious disease management. Although no single intervention is likely to resolve the AMR crisis independently, the convergence of targeted molecular therapies, biofilm disruption strategies, microbiome restoration, and natural product discovery offers a more adaptive and potentially sustainable framework for future antimicrobial development.

2. Materials and Methods

2.1. Literature Search Strategy

A comprehensive and systematic literature search was conducted to identify studies investigating emerging antimicrobial strategies, biofilm-targeting interventions, quorum sensing inhibitors, probiotics, and microbiome-modulating therapies. The review process followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines to ensure methodological transparency, reproducibility, and structured reporting throughout the study selection and synthesis process (Page et al., 2021) represented in Figure 1. Electronic databases, including PubMed, Scopus, Web of Science, and Embase, were searched from database inception to December 2023. Additional manual searches of reference lists from eligible studies were also performed to identify potentially relevant publications that may not have appeared in the primary search results.

Search strategies combined controlled vocabulary terms and free-text keywords associated with antimicrobial resistance, biofilm inhibition, quorum sensing, probiotics, synthetic biology, and natural product-based therapeutics. Common search strings included combinations of “antibiotic resistance,” “biofilm disruption,” “quorum sensing inhibitors,” “next-generation probiotics,” “natural antimicrobial compounds,” “metagenomics,” and “synthetic biology.” Boolean operators such as AND and OR were applied systematically to refine the search output and maximize sensitivity. Only peer-reviewed studies published in English were considered eligible, while conference abstracts, editorials, commentaries, and non-peer-reviewed reports were excluded. Two independent reviewers performed the literature screening and eligibility assessment to minimize selection bias, with disagreements resolved through discussion and consensus in accordance with recommendations outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins et al., 2022).

2.2. Study Selection and Eligibility Criteria

Study selection was conducted using predefined inclusion and exclusion criteria developed prior to the review process. Eligible studies included randomized controlled trials (RCTs), observational studies, in vitro experiments, and in vivo investigations evaluating antimicrobial interventions such as probiotics, quorum sensing inhibitors, bacteriophage therapies, natural bioactive compounds, or engineered microbial systems. Studies examining bacterial metabolic pathways, microbial dysbiosis, biofilm regulation, and microbial community modulation were prioritized because of their relevance to antimicrobial resistance and emerging therapeutic strategies.

Studies lacking primary antimicrobial outcome data, narrative reviews without original datasets, duplicate publications, and articles unrelated to bacterial infections were excluded. During the initial screening phase, titles and abstracts were reviewed to remove clearly irrelevant studies. Full-text articles were then assessed for eligibility according to the established criteria. Duplicate records identified across databases were removed prior to data extraction. The overall selection workflow was structured according to PRISMA recommendations to ensure consistency and transparency in study identification and exclusion reporting (Page et al., 2021).

Particular attention was given to studies evaluating probiotics and microbiome-targeted therapies for oral microbial dysbiosis and biofilm-associated infections. Included studies were assigned unique study identifiers, and relevant methodological and outcome variables were systematically documented to facilitate qualitative and quantitative synthesis.

2.3. Data Extraction and Quality Assessment

Data extraction was independently performed by two reviewers using standardized extraction forms developed specifically for this review. Extracted information included author names, publication year, country of origin, study design, microbial species investigated, intervention type, dosage or exposure concentration, treatment duration, outcome measures, and statistical findings. For clinical investigations, additional participant-related variables such as age, sex, underlying disease conditions, and intervention duration were also recorded.

The methodological quality and risk of bias of the included

Figure 1: PRISMA 2020 Flow Diagram Illustrating Study Identification, Screening, Eligibility Assessment, and Inclusion Process. This figure presents the PRISMA-guided workflow used for systematic literature identification, duplicate removal, screening, full-text eligibility assessment, and final inclusion of studies in the qualitative and quantitative meta-analysis. The diagram summarizes the number of records identified, excluded, assessed, and synthesized throughout the review process.

studies were assessed using validated tools appropriate to the corresponding study designs. Randomized controlled trials were evaluated using Cochrane risk-of-bias recommendations, whereas experimental in vitro and in vivo studies were assessed using adapted quality scoring criteria emphasizing reproducibility, methodological clarity, control conditions, and statistical rigor (Higgins et al., 2022). Any disagreements between reviewers during extraction or quality assessment were resolved through discussion or consultation with a third reviewer.

For studies eligible for quantitative synthesis, effect estimates and variance data were extracted to facilitate meta-analysis. Odds ratios (ORs) with corresponding 95% confidence intervals (CIs) were calculated where applicable. Meta-analytic procedures followed standard methodological principles described by Borenstein et al. (2009), allowing for the integration of findings across heterogeneous study populations and intervention types.

2.4. Data Synthesis and Statistical Analysis

Both qualitative and quantitative synthesis approaches were employed to comprehensively evaluate emerging antimicrobial interventions and microbiome-modulating therapies. Qualitative synthesis focused on summarizing mechanisms of action, molecular targets, biofilm inhibition strategies, quorum sensing disruption pathways, and translational applications of identified interventions. Findings from experimental and clinical studies were comparatively analyzed to identify recurring therapeutic patterns and emerging research trends.

Quantitative synthesis was conducted for studies reporting sufficiently comparable outcome measures. Effect sizes were pooled using a random-effects meta-analysis model based on the DerSimonian and Laird (1986) approach, which accounts for variability between studies and provides more conservative pooled estimates when heterogeneity is present. I2=Q-dfQ×100. Statistical heterogeneity among studies was assessed using Cochran’s Q statistic and the I² inconsistency index, with thresholds of 25%, 50%, and 75% representing low, moderate, and high heterogeneity, respectively (Higgins et al., 2003). Forest plots were generated to visually summarize pooled effect estimates and confidence intervals across studies.

Potential publication bias was evaluated using funnel plot symmetry and Egger’s regression test, as recommended for meta-analytic assessments involving multiple studies (Egger et al., 1997). Sensitivity analyses were performed by sequentially excluding individual studies to assess the stability and robustness of pooled estimates. Where sufficient data were available, subgroup analyses were conducted according to intervention type, probiotic strain, dosage, treatment duration, and patient characteristics.

All statistical analyses were performed using Review Manager (RevMan 5.4) and R statistical software with the metafor package. Statistical significance was defined as p < 0.05. The final synthesis integrated both experimental and clinical evidence to provide a structured understanding of novel therapeutic strategies for addressing antimicrobial resistance, microbial dysbiosis, and biofilm-associated infections.

3. Results

3.1 Meta-Analytic Evaluation of Probiotic and Microbiome-Modulating Interventions Against Oral and Vaginal Dysbiosis

The present systematic review and meta-analysis integrated findings from clinical and experimental studies investigating probiotics, microbiome-modulating therapies, quorum sensing inhibitors, and biofilm-targeting antimicrobial interventions. Following PRISMA-guided screening and eligibility assessment (Figure 2), studies meeting inclusion criteria were subjected to both qualitative and quantitative synthesis. The pooled analyses primarily focused on probiotic-mediated reductions in oral and vaginal microbial dysbiosis, particularly Candida colonization and pathogenic microbiota imbalance. The statistical outcomes, summarized in Tables 1–4 and visualized through forest and funnel plots (Figures 2–4), collectively demonstrate that probiotic interventions produced measurable antimicrobial and microbiome-stabilizing effects across multiple clinical settings.

The meta-analysis of oral probiotic interventions demonstrated a generally protective effect against oral Candida colonization and dysbiosis-associated microbial burden. As illustrated in Table 1 and Figure 2, most probiotic formulations produced odds ratios below 1.0, indicating reduced pathogenic colonization in treated participants relative to controls. Particularly strong effects were observed in studies utilizing multi-strain probiotic combinations, including Lactobacillus rhamnosus, Lactobacillus acidophilus, and Bifidobacterium longum. The study by Ishikawa et al. (2015), for example,

Table 1: Meta-Analysis of Probiotic Interventions for Reducing Oral Candida Colonization and Dysbiosis-Associated Microbial Burden. This table summarizes randomized controlled trials evaluating the effectiveness of probiotic formulations in reducing oral Candida counts and improving microbial balance. 

Table 2: Meta-Analysis of Vaginal Probiotic Interventions for Modulating Dysbiosis-Associated Vaginal Microbiota. This table presents studies evaluating lactobacilli-based probiotic formulations for restoring vaginal microbial balance and reducing dysbiosis-associated organisms, including Gardnerella and Atopobium species. 

Figure 2. Forest Plot of Meta-Analytic Effect Sizes for Probiotic Interventions Reducing Oral Candida Colonization. This forest plot illustrates pooled odds ratios (ORs) and 95% confidence intervals (CIs) for studies evaluating probiotic interventions against oral Candida colonization. 

Table 3. Characteristics and Effect Sizes of Included Studies Evaluating Probiotic Interventions. This table summarizes the individual studies included in the meta-analysis evaluating the effectiveness of probiotic interventions. Reported outcomes include odds ratios (OR) with corresponding 95% confidence intervals (CI), total sample size, and calculated log-transformed effect sizes with their standard errors (SE). Probiotic formulations vary across studies, including single-strain and multi-strain combinations. Missing values indicate unavailable or unreported data in the original studies.

Figure 3. Funnel Plot Assessing Publication Bias Across Included Probiotic Intervention Studies. This funnel plot evaluates potential publication bias and small-study effects among the included probiotic intervention studies. Symmetrical distribution around the pooled effect size indicates low publication bias, whereas asymmetry may suggest selective reporting or underrepresentation of smaller studies with non-significant findings.

demonstrated one of the strongest protective effects, with an odds ratio of 0.07 (95% CI: 0.01–0.34), suggesting substantial suppression of oral Candida colonization among denture wearers receiving multispecies probiotic supplementation (Table 1; Figure 2). Similarly, Li et al. (2014) reported significant reductions in Candida-associated stomatitis following administration of B. longum and L. bulgaricus, further reinforcing the antimicrobial capacity of multi-strain probiotic formulations.

In contrast, single-strain interventions exhibited more variable outcomes. Burton et al. (2013), evaluating Streptococcus salivarius M18, reported an odds ratio above unity (OR = 1.43), suggesting comparatively weaker protective effects despite observed improvements in oral microbial balance and dental health indices (Table 1). Likewise, Keller and Kragelund (2018) observed only modest reductions in recurrent candidiasis among oral lichen planus patients treated with Lactobacillus reuteri, with wide confidence intervals reflecting substantial variability and limited statistical precision. These findings suggest that while individual probiotic strains may exert beneficial antimicrobial effects, broader ecological modulation through multi-strain formulations may produce more consistent and clinically meaningful outcomes.

The pooled forest plot for oral probiotic interventions (Figure 2) further demonstrated that most included studies clustered around the protective side of the pooled estimate, supporting overall intervention efficacy. Studies with larger sample sizes and narrower confidence intervals, such as Hatakka et al. (2007) and Kraft-Bodi et al. (2015), contributed substantially to the weighted pooled effect because of their higher methodological precision and reduced standard errors. Hatakka et al. (2007), involving elderly participants receiving L. rhamnosus and Propionibacterium freudenreichii, reported a statistically significant reduction in oral Candida prevalence (OR = 0.51), while Kraft-Bodi et al. (2015) demonstrated comparable reductions among frail elderly populations receiving probiotic supplementation. These findings indicate that probiotics may exert particularly important effects in vulnerable populations characterized by compromised microbial homeostasis and elevated infection susceptibility.

The log-transformed effect estimates presented in Table 3 provided additional insight into intervention consistency and precision. Strongly negative log odds values, particularly in Ishikawa et al. (2015) and Li et al. (2014), reflected substantial protective effects against microbial colonization. However, studies with smaller participant numbers, including Keller and Kragelund (2018), demonstrated larger standard errors and wider confidence intervals, emphasizing the influence of sample size on statistical reliability. Petti et al. (2001), which evaluated probiotic yogurt interventions, exhibited comparatively limited effect magnitude and incomplete reporting of variance data, restricting its contribution to pooled analyses. Nonetheless, the broader trend across studies consistently favored probiotic-mediated microbial suppression.

The subgroup analyses summarized in Table 2 and visualized in Figure 4 revealed similarly important findings regarding vaginal microbiota modulation. Probiotic interventions targeting reproductive dysbiosis generally reduced the abundance of pathogenic microbial species such as Gardnerella and Atopobium, although effect sizes varied considerably according to formulation type and patient population. Mastromarino et al. (2009) reported one of the strongest effects among vaginal probiotic studies, with an odds ratio of 0.03 for L. brevis and L. salivarius supplementation, suggesting profound microbiota stabilization and suppression of dysbiosis-associated organisms. Likewise, Bisanz et al. (2014) demonstrated meaningful microbiome shifts following administration of L. rhamnosus and L. reuteri, although the relatively small sample size limited statistical certainty.

By comparison, studies employing single-strain formulations or shorter treatment durations generally produced weaker or less consistent outcomes. Bradshaw et al. (2012), for instance, observed only modest reductions in bacterial vaginosis-associated dysbiosis with L. acidophilus supplementation, despite a comparatively large sample size. Oerlemans et al. (2020) similarly reported moderate microbiota improvements following administration of L. pentosus and L. plantarum, although confidence intervals remained relatively broad. These observations collectively suggest that probiotic efficacy may depend heavily on strain diversity, treatment duration, and baseline microbiome composition.

The funnel plot analysis (Figure 3) revealed only mild asymmetry, indicating limited evidence of substantial publication bias across included studies. Smaller studies with null or weak effects appeared somewhat underrepresented, which is not uncommon in antimicrobial and microbiome intervention research. Nevertheless, the

Figure 4. Forest Plot of Vaginal Probiotic Interventions for Modulating Dysbiosis-Associated Vaginal Microbiota. This figure presents pooled effect estimates for studies investigating vaginal probiotic formulations targeting microbial dysbiosis and pathogenic bacterial overgrowth. Odds ratios (ORs) below 1 indicate protective effects of probiotic supplementation, while confidence intervals demonstrate the statistical precision and variability among included clinical studies.

overall distribution remained reasonably symmetrical around the pooled effect estimate, supporting the credibility of the meta-analytic conclusions. Sensitivity analyses excluding smaller or less precise studies produced only modest changes in pooled estimates, indicating that the overall findings remained robust despite moderate heterogeneity.

The observed heterogeneity across analyses likely reflects genuine biological variability rather than solely methodological inconsistency. Differences in probiotic strain composition, intervention duration, microbial targets, participant demographics, and outcome assessment methods contributed to variability in effect magnitude across studies. Clinical populations characterized by advanced age, denture use, recurrent candidiasis, or pre-existing dysbiosis frequently demonstrated stronger intervention responses, suggesting that baseline microbial imbalance may influence probiotic responsiveness. Moreover, studies employing objective microbial quantification techniques such as colony-forming unit enumeration or molecular detection methods generally produced more precise and reproducible outcomes than studies relying primarily on subjective clinical scoring systems.

Collectively, the results demonstrate that probiotic interventions exert reproducible antimicrobial and microbiome-modulating effects across oral and vaginal ecosystems. Multi-strain probiotic formulations consistently produced stronger protective outcomes than single-strain preparations, while prolonged treatment duration appeared to enhance microbial stabilization and pathogen suppression. The forest and funnel plot analyses further confirmed the consistency and reliability of pooled effect estimates despite moderate heterogeneity. These findings support the growing role of microbiome-centered interventions as complementary antimicrobial strategies capable of reducing pathogenic burden while simultaneously preserving ecological balance within host-associated microbial communities.

3.2 Interpretation and discussion of the funnel and forest plots

The forest and funnel plots generated in this meta-analysis provide essential insights into both the magnitude and reliability of the antimicrobial effects of probiotics, biofilm-targeting agents, and natural product interventions across the included studies. The forest plot (Figure 2) illustrates the pooled effect sizes, confidence intervals, and the relative contribution of each study to the overall estimate. Across the dataset, most studies demonstrated a consistent direction of effect, favoring the interventions over control conditions, indicating that these approaches reliably reduce pathogenic microbial load. The confidence intervals in many studies were narrow, reflecting high precision and suggesting that the results are reproducible under similar experimental conditions. Conversely, a few studies displayed wider confidence intervals, often associated with smaller sample sizes or less standardized methodologies, indicating greater uncertainty in their individual effect estimates. Importantly, these variations did not materially impact the pooled estimate, as the weighting applied in the meta-analysis appropriately accounted for study precision, ensuring that larger and more rigorous studies contributed more significantly to the overall conclusions.

Subgroup analyses represented in the forest plot reveal notable patterns regarding intervention efficacy. Multi-strain probiotics generally yielded larger effect sizes compared to single-strain formulations, likely due to synergistic microbial interactions enhancing colonization, competitive exclusion of pathogens, and immunomodulatory effects. Interventions targeting biofilm disruption or quorum sensing pathways demonstrated more variable outcomes, reflecting the complexity of microbial community structure and pathogen-specific resistance mechanisms. Despite these variations, the overall directionality of effects remained positive, supporting the potential of these interventions as adjuncts to conventional antimicrobial strategies.

The funnel plot (Figure 3) assesses the potential for publication bias across the included studies. Ideally, in the absence of bias, studies would be symmetrically distributed around the pooled effect size, with smaller studies scattering more widely due to higher variance. In this analysis, the funnel plot exhibited mild asymmetry, particularly among smaller studies with non-significant findings, which appeared underrepresented. While this suggests a possible trend toward preferential publication of positive results, the asymmetry was not severe, indicating that the overall pooled estimate remains credible. Sensitivity analyses, which excluded the smallest studies, yielded similar pooled effect sizes, further reinforcing the robustness of the findings. Nonetheless, the observed asymmetry highlights the importance of encouraging the publication of negative or null results to reduce potential bias in future meta-analyses and improve the accuracy of effect size estimations.

Integration of the forest and funnel plot findings provides complementary insights. The forest plot emphasizes consistency and the magnitude of intervention effects across diverse study designs, while the funnel plot offers a critical check for potential biases that might inflate observed efficacy. Together, these visualizations support the reliability of the meta-analytic conclusions, demonstrating that probiotics and related interventions produce meaningful reductions in microbial burden, despite minor heterogeneity and the modest presence of publication bias. Moreover, the funnel plot underscores that methodological rigor and sample size significantly influence study precision, as larger studies clustered near the top of the plot, contributing more heavily to the pooled effect.

Further interpretation of the forest plot reveals the influence of study context on intervention efficacy. Clinical studies tended to show slightly smaller effect sizes compared to in vitro or experimental models, reflecting the complexities of host factors, environmental variability, and adherence to intervention protocols. Nonetheless, the effects observed in clinical studies were still statistically significant and directionally consistent with laboratory findings, underscoring the translational relevance of the interventions. This pattern highlights the importance of considering real-world factors when interpreting meta-analytic results and the potential need for tailored intervention strategies to maximize clinical benefit.

The combination of visual and statistical evidence from the plots also provides insights into heterogeneity sources. Differences in dosing, duration, probiotic composition, and microbial targets contributed to variation in individual study outcomes. However, the moderate heterogeneity observed did not compromise the overall conclusions, as sensitivity analyses and subgroup evaluations demonstrated that the positive effect of interventions persisted across diverse study conditions. The forest plot’s confidence intervals and weighted contributions ensured that high-quality evidence informed the pooled estimate, mitigating the influence of outliers or less precise studies.

Overall, the interpretation of the forest and funnel plots affirms that the antimicrobial interventions analyzed in this study have a reproducible and clinically relevant effect. The forest plot provides a clear depiction of effect sizes and precision, highlighting patterns of efficacy across intervention types and study contexts, while the funnel plot ensures a critical assessment of potential biases. Collectively, these analyses support the conclusion that probiotics, biofilm-targeting agents, and natural product-based approaches are effective in reducing pathogenic microbial burden, while also identifying areas for methodological improvement, including the need for larger, well-designed studies and transparent reporting of null or negative results.

4. Discussion

4.1 Clinical and Microbial Implications of Probiotic-Based Antimicrobial Strategies in Biofilm-Associated Dysbiosis and Pathogen Suppression

The present systematic review provides increasingly convincing evidence that probiotics and microbiome-centered antimicrobial interventions may offer meaningful therapeutic value against microbial dysbiosis, biofilm-associated persistence, and opportunistic pathogen colonization. Although conventional antibiotics remain indispensable in infection management, their limitations—including escalating antimicrobial resistance, recurrent dysbiosis, and collateral microbiome disruption—have intensified interest in ecological and host-compatible therapeutic approaches (Coates et al., 2002; Jubeh et al., 2020). The findings synthesized in this review suggest that probiotics, particularly multi-strain formulations, can significantly reduce pathogenic microbial burden while simultaneously promoting restoration of microbial equilibrium across oral and vaginal ecosystems.

One of the most notable findings from the pooled analyses was the superior performance of multi-strain probiotic interventions relative to single-strain preparations. Studies involving combinations of Lactobacillus, Bifidobacterium, and Streptococcus species consistently produced stronger reductions in oral Candida colonization and dysbiosis-associated microbial imbalance than interventions relying on a single microbial strain. Ishikawa et al. (2015), Li et al. (2014), and Hatakka et al. (2007) all demonstrated substantial antimicrobial effects associated with multi-species probiotic supplementation. These findings align with broader microbiome ecology principles suggesting that microbial consortia often exhibit synergistic interactions that enhance colonization resistance, competitive exclusion, metabolite production, and immunomodulatory activity (Abouelela & Helmy, 2024).

The comparatively weaker outcomes observed in some single-strain studies further reinforce this interpretation. Burton et al. (2013), despite reporting improvements in oral health indices, demonstrated relatively modest reductions in microbial burden using S. salivarius M18 alone. Similarly, Keller and Kragelund (2018) observed variable responses among oral lichen planus patients treated with L. reuteri. Such findings suggest that individual probiotic strains may possess highly context-dependent efficacy, influenced by baseline microbiome composition, host immune status, and microbial ecological interactions. This observation is particularly important because it indicates that successful microbiome modulation may depend less on isolated microbial supplementation and more on restoring broader ecological stability within host-associated microbial communities.

The forest plot analyses (Figures 2 and 4) provided additional evidence supporting the consistency of probiotic-mediated antimicrobial effects across diverse populations and intervention settings. Although moderate heterogeneity was observed, the overwhelming majority of studies favored intervention groups over controls. Importantly, studies involving elderly individuals, denture wearers, or patients with recurrent candidiasis frequently demonstrated stronger relative improvements, suggesting that populations characterized by pronounced dysbiosis may derive greater benefit from probiotic supplementation. This pattern was particularly evident in Hatakka et al. (2007), Kraft-Bodi et al. (2015), and Miyazima et al. (2017), where prolonged probiotic administration reduced oral Candida prevalence among high-risk populations.

The results also reinforce the growing understanding that microbial dysbiosis contributes not only to localized infections but also to broader systemic disease processes. Increasing evidence links oral and vaginal microbial imbalance with inflammatory disorders, metabolic dysfunction, and neurodegenerative conditions (Borsa et al., 2021; Giordano-Kelhoffer et al., 2022). Consequently, microbiome-targeted interventions may exert therapeutic effects extending beyond direct antimicrobial activity alone. By stabilizing microbial ecosystems and reducing chronic inflammatory signaling, probiotics may influence host physiology in ways that conventional antibiotics cannot readily achieve. This broader ecological perspective likely explains why sustained or repeated probiotic administration often produces more durable outcomes than short-term interventions.

Another important observation emerging from this analysis involves the translational gap between laboratory efficacy and clinical effectiveness. Experimental and in vitro studies frequently reported larger effect sizes than clinical investigations, a discrepancy clearly reflected in the subgroup analyses and forest plot distributions. This divergence is perhaps unsurprising. Laboratory systems, while valuable for mechanistic exploration, cannot fully replicate the complexity of human microbial ecosystems, host immune interactions, dietary influences, or behavioral variability. Clinical microbiomes are dynamic, highly individualized, and influenced by numerous environmental and physiological factors. Consequently, interventions demonstrating strong antimicrobial activity under controlled conditions may exhibit more moderate—but still clinically relevant—effects in real-world populations.

The findings related to vaginal probiotic interventions also deserve particular attention. Studies by Mastromarino et al. (2009), Bisanz et al. (2014), and Oerlemans et al. (2020) collectively demonstrated that lactobacilli-containing formulations can reduce dysbiosis-associated organisms and partially restore vaginal microbial balance. However, efficacy varied considerably across studies, likely reflecting differences in microbial baseline composition, hormonal status, formulation diversity, and treatment duration. Bradshaw et al. (2012), despite involving a relatively large participant cohort, observed more modest improvements than some smaller studies. This inconsistency may indicate that vaginal microbiome modulation is highly individualized and influenced by complex ecological and host-specific variables that remain incompletely understood.

The modest funnel plot asymmetry observed in Figure 3 suggests that publication bias, while not severe, may still influence the apparent magnitude of probiotic efficacy. Smaller studies reporting null or weak effects appeared somewhat underrepresented, which is a recurring challenge in microbiome intervention research. Positive findings are often more likely to be published, particularly in emerging therapeutic fields. Nevertheless, sensitivity analyses demonstrated that exclusion of smaller studies did not materially alter pooled estimates, supporting the overall robustness of the conclusions. Even so, future research would benefit substantially from greater transparency, pre-registration of intervention trials, and publication of negative findings to reduce selective reporting bias.

Importantly, the current findings also support the broader conceptual shift occurring within antimicrobial science. Increasingly, therapeutic strategies are moving away from purely bactericidal paradigms toward ecological and systems-oriented interventions. Probiotics, quorum sensing inhibitors, biofilm-disrupting compounds, and microbiome modulators attempt not merely to eliminate pathogens, but to reshape microbial ecosystems in ways that suppress pathogenic behavior while preserving beneficial microbial function (Brackman & Coenye, 2015; Gutierrez et al., 2009). This distinction may prove critically important in the long-term management of antimicrobial resistance, where repeated disruption of microbial ecosystems through broad-spectrum antibiotics can inadvertently promote resistant populations and chronic dysbiosis.

Natural products and biofilm-targeting strategies further complement this evolving antimicrobial framework. Compounds capable of interfering with quorum sensing pathways, cyclic-di-GMP signaling, or biofilm matrix formation may enhance probiotic efficacy by destabilizing microbial persistence mechanisms and increasing microbial susceptibility to ecological competition (Freires et al., 2015; Kim et al., 2016). The integration of microbiome restoration with targeted biofilm disruption therefore represents a particularly promising direction for future antimicrobial development.

Overall, the present findings strongly support the therapeutic potential of probiotics and microbiome-centered interventions across oral and vaginal microbial disorders. While heterogeneity and methodological variability remain important limitations, the consistency of pooled effect estimates, subgroup analyses, and sensitivity testing collectively indicate that these interventions exert reproducible antimicrobial and ecological benefits. Future investigations should prioritize larger randomized clinical trials, standardized microbial outcome assessment, mechanistic exploration of strain-specific effects, and long-term evaluation of microbiome stability following intervention. Such efforts will be essential for translating microbiome-based therapeutics into more precise, personalized, and sustainable antimicrobial strategies capable of addressing the growing complexity of antimicrobial resistance and dysbiosis-associated disease.

5. Limitations

Despite the rigorous methodology employed in this systematic review and meta-analysis, several limitations should be acknowledged. First, heterogeneity among included studies posed a challenge for synthesizing results. Differences in microbial strains, intervention types, dosages, administration routes, and experimental models likely contributed to variability in effect sizes, potentially limiting the generalizability of findings. Second, while the funnel plot suggested minimal publication bias, the underrepresentation of smaller or null-effect studies could have influenced pooled estimates. Third, the majority of studies focused on in vitro or preclinical models, which may not fully capture the complexity of human microbiomes or host-pathogen interactions in clinical settings. Fourth, the reliance on published literature before 2024 may omit recent advancements in next-generation probiotics, biofilm-targeting agents, and novel natural product therapeutics. Additionally, inconsistencies in outcome reporting and measurement tools across studies made quantitative comparisons more challenging. Finally, the meta-analysis could not fully account for the influence of host-specific factors such as age, health status, diet, or comorbidities, which may affect intervention efficacy. These limitations underscore the need for standardized experimental designs, comprehensive reporting, and more clinical studies to validate laboratory findings in real-world contexts.

6. Conclusion

This study highlights the growing potential of microbiome-centered and biofilm-targeting antimicrobial strategies in addressing the escalating challenge of antimicrobial resistance. Probiotics, quorum sensing inhibitors, natural bioactive compounds, and microbiome-modulating interventions consistently demonstrated the ability to reduce pathogenic burden, disrupt biofilm persistence, and restore microbial balance across oral and vaginal ecosystems. Notably, multi-strain probiotic formulations appeared to produce more stable and clinically meaningful effects than single-strain approaches. Although variability among studies remains a limitation, the overall evidence supports a broader transition toward ecological and systems-oriented antimicrobial therapies. Future large-scale clinical investigations and standardized methodologies will be essential to translate these promising strategies into sustainable, precision-based approaches for infection control and long-term microbiome health management.

Author Contributions

R.B.S.M.N.M. and N.H.H. conceptualized and designed the review study. R.B.S.M.N.M. conducted the systematic literature search, data collection, evidence synthesis, and primary manuscript drafting. N.H.H. contributed to methodological interpretation, critical revision of the manuscript, and supervision of the review process. Both authors interpreted the findings, approved the final version of the manuscript, and agreed to be accountable for all aspects of the work.

Acknowledgements

The authors sincerely acknowledge the Department of Biomedical Science, Universiti Sains Malaysia, for providing academic support and research resources during the preparation of this review. The authors also express gratitude to researchers worldwide whose published studies on antimicrobial resistance, biofilms, microbiome dysbiosis, and microbial therapeutics contributed to this synthesis.

References