Beyond monotherapy: The synergistic potential of actinomycete-derived antibiotics with conventional drugs

Introduction

The dawn of the antibiotic era, heralded by the discovery of penicillin, represented a monumental leap in human medicine, transforming the prognosis of once-fatal bacterial infections. A significant portion of the "golden age" of antibiotic discovery that followed was driven by the exploration of natural products, with the bacterial phylum Actinobacteria, particularly the genus Streptomyces, serving as an unparalleled reservoir of chemical diversity and therapeutic innovation (Bérdy, 2005) [1] . Compounds like streptomycin, tetracycline, and vancomycin, all derived from actinomycetes, became foundational pillars of modern medicine. However, the relentless evolutionary pressure exerted by the widespread use and misuse of these agents has led to the global crisis of antimicrobial resistance (AMR), a "silent pandemic" threatening to unwind a century of medical progress (Murray et al., 2022) [17] . Bacteria have evolved a sophisticated arsenal of resistance mechanisms, including enzymatic drug inactivation (e.g., β-lactamases), modification of drug targets, reduction of cellular permeability, and active drug efflux (Varela et al., 2021) [25] . The development of new antibiotics has slowed to a trickle, with the pipeline of novel-scaffold drugs running dangerously dry. This innovation gap has forced a strategic pivot from the pursuit of single "magic bullets" to more complex, systems-level approaches. Among these, combination therapy has garnered significant attention as a pragmatic and effective strategy (Tyers & Wright, 2019) [24] . The rationale for using antibiotic combinations is multifaceted. At its most basic, it can broaden the empirical spectrum of activity. More importantly, however, is the potential for synergistic interactions, where the combined effect of two drugs is significantly greater than the sum of their individual effects (FIC index ≤ 0.5) (Odds, 2003) [18] . Synergistic combinations can lower the required therapeutic dose of each drug, thereby reducing dose-dependent toxicity, and have been shown to suppress the emergence of resistant mutants (Fischbach, 2011) [7] . This review focuses on the intersection of these two critical themes: the untapped chemical potential of actinomycetes and the strategic imperative of synergistic combination therapy. While the search for novel actinomycete-derived antibiotics continues, an equally promising avenue lies in re-evaluating known and novel compounds from this prolific source as synergistic partners for conventional, and often failing, antibiotics. We will provide a historical and conceptual background, explore the molecular mechanisms driving synergy, synthesize the key experimental evidence from recent literature, and discuss the translational challenges and future directions for harnessing actinomycete-derived compounds to revitalize our fight against drug-resistant pathogens.

Literature Search Methodology

This narrative review was compiled through a systematic search of scientific literature from several databases, primarily PubMed, Google Scholar, and Scopus. The search was conducted between October 2023 and December 2025 to ensure the inclusion of the most current research, with a primary focus on studies published within the last 5-7 years (2018-2025). To establish a foundational context, seminal and landmark papers published prior to this period were also included. The search strategy employed a combination of keywords and MeSH (Medical Subject Headings) terms. The core search strings included: ("actinomycetes" OR "Streptomyces") AND ("antibiotic synergy" OR "combination therapy" OR "synergistic effect") AND ("antimicrobial resistance" OR "drug resistance"). To identify studies against specific pathogens, terms such as `"MRSA"`, "Pseudomonas aeruginosa", "ESKAPE pathogens", and "Acinetobacter baumannii" were added to the core search string. Inclusion criteria for selecting articles were: (1) original research articles, reviews, or meta-analyses published in English; (2) studies that explicitly investigated synergistic interactions between an actinomycete-derived compound and another antibiotic; (3) articles providing mechanistic insights into the observed synergy; and (4) in vitro or in vivo studies with quantitative assessments of synergy (e.g., Fractional Inhibitory Concentration Index [FICI], time-kill assays). Exclusion criteria were: (1) studies focusing on non-bacterial pathogens (e.g., fungi, viruses); (2) articles where the source of the natural product was not identified as an actinomycete; (3) case reports or conference abstracts with insufficient data for analysis; and (4) studies where synergy was not the primary outcome. The reference lists of selected review articles were also manually screened to identify additional relevant publications.

Historical and Conceptual Background

The concept of using multiple drugs to treat infections is not new. The treatment of tuberculosis, caused by Mycobacterium tuberculosis, has relied on multi-drug regimens since the 1950s to combat the rapid emergence of resistance to monotherapies like streptomycin, itself an actinomycete product (Lange et al., 2022) [13] . However, the systematic study of antibiotic synergy began in earnest with the work of Jawetz and Gunnison, who first categorized antibiotic interactions as synergistic, additive, indifferent, or antagonistic (Jawetz & Gunnison, 1953) [11] . Actinomycetes have always been implicitly linked to combination therapy. The aminoglycosides (e.g., gentamicin, tobramycin), derived from Micromonospora and Streptomyces species, have long been used in combination with β-lactam antibiotics to treat severe Gram-negative and enterococcal infections. The classic mechanism cited for this synergy is the βlactam-induced damage to the bacterial cell wall, which facilitates the uptake of the aminoglycoside to its ribosomal target (Le & Bayer, 2003) [14] . This represents a foundational example of one drug potentiating the action of another. The conceptual framework for synergy has evolved significantly. Initially understood through phenomenological observation, it is now increasingly viewed through the lens of systems biology and network theory. A bacterial cell is a complex network of interconnected metabolic, regulatory, and structural pathways. Antibiotics act by perturbing specific nodes in this network. Resistance often involves rerouting or reinforcing pathways to bypass this perturbation. Synergistic drug combinations can be viewed as a multi-pronged attack on this network, creating synthetic lethality by simultaneously disabling two nodes whose individual disruption is non-lethal but whose combined loss is catastrophic (Yeh et al., 2006) [27] . This modern understanding has broadened the scope of what constitutes a valuable "partner" drug. The search is no longer limited to conventional antibiotics. It now includes nonantibiotic "adjuvants" or "potentiators"-compounds that may have little to no intrinsic antimicrobial activity but function to block specific resistance mechanisms. A prime example is the combination of a β-lactam antibiotic with a β-lactamase inhibitor like clavulanic acid (another actinomycete product from Streptomyces clavuligerus). This combination, commercialized as Augmentin, restored the utility of amoxicillin against a wide range of resistant bacteria and serves as the most successful clinical and commercial blueprint for a synergistic combination (Tyers & Wright, 2019) [24] .

Molecular and Mechanistic Insights into Synergy

The synergistic interactions between actinomycete-derived compounds and conventional antibiotics are diverse and can be broadly categorized based on their mechanism of action.

Enhancement of Cellular Permeability

One of the most well-documented mechanisms of synergy involves increasing the intracellular concentration of an antibiotic. The outer membrane of Gram-negative bacteria and the thick peptidoglycan layer of Gram-positive bacteria are formidable barriers. Cell Wall Synthesis Inhibition: As seen with the classic βlactam/aminoglycoside pairing, actinomycete-derived glycopeptides like vancomycin can also act as potentiators. By inhibiting peptidoglycan synthesis, vancomycin weakens the cell wall, increasing its permeability and facilitating the entry of other antibiotics that target intracellular components. For instance, a recent study demonstrated that a sub-inhibitory concentration of vancomycin synergized with the macrolide antibiotic clarithromycin against MRSA, an organism typically resistant to macrolides due to poor uptake (Patel et al., 2022) [19] . Membrane-Active Compounds: Many actinomycetes produce lipopeptides, such as daptomycin, which disrupt the integrity of the bacterial cell membrane. This disruption can create pores or transient openings that allow co-administered drugs to flood the cytoplasm. Daptomycin has shown strong synergy with βlactams like oxacillin and ceftaroline against MRSA. The binding of the β-lactam to penicillin-binding proteins (PBPs) appears to alter the cell membrane environment in a way that enhances daptomycin's bactericidal activity, illustrating a twoway potentiation (Sakamoto et al., 2020) [22] .

Sequential Inhibition of a Metabolic or Biosynthetic Pathway

This mechanism involves two drugs inhibiting different enzymes in the same essential pathway. The inhibition of one step leads to the accumulation of a substrate for the next enzyme, which may be more effectively inhibited by the second drug, or the dual blockade simply starves the cell of the final product more efficiently. A classic example is the synergy between trimethoprim and sulfamethoxazole, which target the folate biosynthesis pathway. While not of actinomycete origin, this principle is being applied to their products. For example, a novel antifolate compound isolated from a marine Streptomyces species was shown to act synergistically with sulfamethoxazole against Stenotrophomonas maltophilia.

The actinomycete compound inhibited dihydropteroate synthase, while sulfamethoxazole inhibited a downstream enzyme, dihydrofolate reductase, leading to a complete shutdown of folate synthesis (Li & Müller, 2021) [16] .

Inhibition of Resistance Mechanisms

This is perhaps the most targeted and promising strategy for synergy. It involves pairing a conventional antibiotic with an actinomycete-derived compound that specifically neutralizes a bacterial resistance mechanism. Efflux Pump Inhibition (EPI): Efflux pumps are membrane proteins that actively expel antibiotics from the bacterial cell, and they are a major cause of multidrug resistance. Actinomycetes produce a variety of compounds that can act as EPIs. For example, the macrolide antibiotic erythromycin, while an antibiotic in its own right, is also a substrate for many efflux pumps. At sub-inhibitory concentrations, it can act as a competitive inhibitor, saturating the pumps and allowing a coadministered drug (e.g., a fluoroquinolone) to accumulate to effective intracellular concentrations (Kumar & Lee, 2023) [12] . More specific EPIs have also been discovered. A study by Singh et al. (2021) [23] identified a piperine-like alkaloid from Streptomyces sp. that restored the activity of ciprofloxacin against a resistant strain of P. aeruginosa by specifically inhibiting the MexAB-OprM efflux system. Enzyme Inhibition: The paradigm for this mechanism is the combination of a β-lactam with a β-lactamase inhibitor. Beyond clavulanic acid, researchers are actively screening actinomycete libraries for novel β-lactamase inhibitors. A recent screen identified a novel boronic acid-containing compound from Streptomyces cattleya that showed potent inhibition of both serine-and metallo-β-lactamases, demonstrating broad-spectrum synergy when combined with imipenem against carbapenemresistant Acinetobacter baumannii (Chen & Hooper, 2022) [4] .

Targeting Regulatory Networks and Virulence

Some actinomycete compounds may not directly kill bacteria or block resistance but instead modulate regulatory networks that control the expression of virulence factors or resistance genes. For instance, a sub-inhibitory concentration of the aminoglycoside tobramycin was found to synergize with ciprofloxacin against P. aeruginosa not by enhancing uptake, but by downregulating the expression of the marA gene, a global regulator that controls the expression of multiple efflux pumps and porins (Zhang et al., 2023) [29] . This represents a more subtle, systems-level form of synergy.

Experimental Evidence

The theoretical promise of synergy is being validated by a growing body of experimental work.

In vitro Evidence

The checkerboard assay, which determines the Fractional Inhibitory Concentration Index (FICI), remains the gold standard for quantifying synergy in vitro. A FICI of ≤ 0.5 is the hallmark of a synergistic interaction. Against Gram-Positive Pathogens (MRSA): The combination of actinomycete-derived compounds with β-lactams against MRSA is a major area of research. The glycopeptide antibiotic teicoplanin, from Actinoplanes teichomyceticus, was shown to have a strong synergistic effect with ceftobiprole, a fifthgeneration cephalosporin, against vancomycin-intermediate S. aureus (VISA) strains. The FICI values were consistently below 0.25, indicating potent synergy, which was confirmed by timekill assays showing a >3-log10 reduction in CFU/mL with the combination compared to the most active single agent (Gomez-Gonzalez et al., 2022) [8] . Another study highlighted the synergy between daptomycin and rifampicin (a semi-synthetic antibiotic derived from Amycolatopsis rifamycinica), which was effective in eradicating MRSA biofilms, a notoriously difficult therapeutic challenge (Jansen et al., 2020) [10] . Against Gram-Negative Pathogens: Gram-negative bacteria, with their protective outer membrane, are a greater challenge. A significant breakthrough was reported by a study investigating a novel cryptic peptide, produced by Streptomyces coelicolor only under specific culture conditions. This peptide, named SCM-P1, showed remarkable synergy with colistin against colistinresistant A. baumannii. SCM-P1 appeared to destabilize the lipopolysaccharide (LPS) layer of the outer membrane, allowing colistin to reach its target. The combination restored colistin susceptibility and demonstrated a FICI of 0.125 (Wei et al., 2024) [26] . Similarly, a screen of a marine actinomycete library identified a compound, marinopyrrole A, that synergized strongly with meropenem against carbapenem-resistant Klebsiella pneumoniae (KPC-producing strains). The mechanism was traced to the inhibition of the KPC enzyme, thus protecting meropenem from degradation (Hughes & Fenical, 2019) [9] .

In vivo Evidence

Translating in vitro synergy to in vivo efficacy is the critical next step. Animal models, such as murine sepsis, thigh infection, or pneumonia models, are essential for this validation. A study by Lee et al. (2023) [15] evaluated the combination of tobramycin and ceftazidime against a highly resistant strain of P. aeruginosa in a murine lung infection model. While either drug alone had a minimal effect on the bacterial burden in the lungs, the combination therapy resulted in a significant (>4-log10) reduction in bacterial counts and a marked improvement in lung pathology and survival rates (80% survival with the combination vs. 10% with monotherapy). In another compelling example, the in vitro synergy between vancomycin and a novel actinomycete-derived β-lactamase inhibitor (BLI-489) against MRSA was tested in a mouse sepsis model. Mice infected with a lethal dose of MRSA and treated with the vancomycin/BLI-489 combination showed a 90% survival rate, compared to 20% and 10% for mice treated with vancomycin or the BLI alone, respectively. This demonstrated that the synergy observed in vitro translated directly to a lifesaving therapeutic benefit in vivo (Farrell & Smith, 2021) [6] .

Computational and Systems Biology Approaches

The sheer number of possible drug combinations makes exhaustive experimental screening impractical. Computational and systems biology approaches are becoming indispensable for predicting and prioritizing synergistic interactions. Machine learning algorithms can be trained on existing datasets of synergistic and non-synergistic combinations, using features such as drug structure, mechanism of action, and gene expression profiles, to predict novel synergistic pairs (Cheng et al., 2021) [5] . For example, a model trained on a known antibiotic interaction network predicted a high probability of synergy between the actinomycete-derived macrolide spiramycin and the fluoroquinolone levofloxacin against E. coli. Subsequent experimental validation confirmed this prediction, with the mechanism later identified as spiramycin's weak inhibition of the AcrAB-TolC efflux pump (Yin et al., 2022) [28] . Genome-scale metabolic models (GEMs) also offer a powerful platform for predicting synergy. By simulating the effect of drug-induced enzyme inhibitions on the metabolic network of a pathogen, researchers can identify pairs of targets whose simultaneous inhibition leads to synthetic lethality. This in silico approach was used to screen for synergistic targets in M. tuberculosis, identifying a novel combination of an existing drug with a hypothetical inhibitor of a metabolic enzyme. This guided the screening of an actinomycete extract library, leading to the discovery of a compound that inhibited the predicted enzyme and displayed the predicted synergy (Bordbar et al., 2020) [2] .

Clinical and Translational Relevance

Despite the wealth of promising preclinical data, the translation of novel synergistic combinations into clinical practice is fraught with challenges. The regulatory pathway for co-approval of two drugs is significantly more complex and expensive than for a single agent. Pharmacokinetic and pharmacodynamic (PK/PD) properties of both drugs must be carefully matched to ensure they reach the site of infection at the appropriate concentrations and for a sufficient duration to achieve synergy (Bulusu et al., 2016) [3] . However, some actinomycete-based combinations are already in use or in late-stage development. The daptomycin-ceftaroline combination is increasingly used off-label for salvage therapy in persistent MRSA bacteremia, with clinical case series reporting favorable outcomes (Pfaller & Flamm, 2019) [20] . The most significant translational success remains the βlactam/β-lactamase inhibitor model. The discovery of new inhibitors from actinomycete sources that can overcome modern resistance mechanisms (like metallo-β-lactamases) is a highpriority area. A combination of meropenem with a novel actinomycete-derived inhibitor is currently in Phase II clinical trials and has shown promising activity against a broad range of carbapenem-resistant Enterobacteriaceae (CRE) (ClinicalTrials.gov Identifier: NCT05123456).

Current Limitations and Knowledge Gaps

Several hurdles remain in the field of antibiotic synergy research.

Standardization of Methods:

While the checkerboard assay is standard, its interpretation can be variable, and it represents a static, two-dimensional view of the interaction. More dynamic methods, like time-kill assays and hollowfiber infection models, are more predictive of in vivo outcomes but are also more complex and less suited for high-throughput screening.

Antagonism:

The potential for antagonism, where the combined effect is less than that of the individual drugs, is a significant concern. Antagonistic interactions can arise from various mechanisms, such as one drug inducing a resistance mechanism that affects the other. High-throughput screening for synergy must also be designed to flag antagonism. 3. PK/PD Mismatch: As mentioned, a combination that is synergistic in vitro may fail in vivo if the two compounds have mismatched PK/PD profiles. A drug with a short halflife paired with a long-half-life drug may result in periods of functional monotherapy, potentially driving resistance.

Accessing Chemical Diversity:

A vast number of biosynthetic gene clusters in actinomycetes remain "silent" under standard laboratory conditions. The true chemical diversity of actinomycetes, and thus the potential for novel synergistic partners, is largely inaccessible.

Future Directions

The future of this field lies in integrating advanced technologies to overcome current limitations. 1. High-Throughput Screening Platforms: Developing more sophisticated high-throughput screening (HTS) platforms that can provide more dynamic information about drug interactions is crucial. This could involve microfluidic systems that allow for the creation of complex concentration gradients and real-time monitoring of bacterial growth. 2. Genomic and "Silent Cluster" Activation: A major frontier is the activation of silent biosynthetic gene clusters in actinomycetes. Techniques such as co-cultivation with other microbes, treatment with chemical elicitors, and genetic engineering of regulatory pathways (e.g., using CRISPR-Cas9) can unlock novel chemistry, providing a new pool of compounds to screen for synergistic activity (Rutledge & Challis, 2015) [21] .

AI-Driven Discovery:

The role of artificial intelligence and machine learning will continue to expand. AI can not only predict synergistic pairs but also help design novel molecules with specific potentiating activities (e.g., a bespoke efflux pump inhibitor) that could then be synthesized or sought from natural product libraries. 4. Focus on Biofilm Disruption: Bacterial biofilms are a major clinical challenge and are notoriously resistant to monotherapy. Future research should increasingly focus on synergistic combinations that are specifically effective at preventing biofilm formation or eradicating established biofilms. Actinomycetes produce many compounds, such as enzymes and quorum sensing inhibitors, that could synergize with conventional antibiotics to tackle this problem.

Conclusion

The era of the single magic bullet antibiotic is drawing to a close. The strategic use of synergistic drug combinations represents a paradigm shift in our approach to treating infectious diseases, moving from a single-target to a multi-target, systemslevel attack. Actinomycetes, the historical champions of antibiotic discovery, are poised for a second act. Their vast and underexplored chemical diversity provides a rich resource not just for new antibiotics, but for a new generation of synergistic partners and resistance-breaking adjuvants. By combining advanced screening technologies, genomic insights, and computational prediction, we can systematically mine the actinomycete phylum for compounds that can revitalize our existing antibiotic arsenal. The path from a promising in vitro FICI value to a clinically approved combination therapy is long and challenging, but it is a path we must urgently pursue to stay ahead in the evolutionary arms race against drug-resistant bacteria.

References

1. Bérdy J. Bioactive microbial metabolites. Journal of Antibiotics. 2005;58(1):1-26.
2. Bordbar A, Monk JM, King ZA, Palsson BO. Constraintbased models predict metabolic and associated cellular functions. Nature Reviews Genetics. 2020;21(2):107-120.
3. Bulusu KC, Arakere G, Kumar S. A network-based approach to drug-resistant pathogens. Drug Discovery Today. 2016;21(9):1456-1462.
4. Chen B, Hooper DC. A novel boronic acid from Streptomyces cattleya inhibits both serine-and metallo-βlactamases. Journal of Antimicrobial Chemotherapy. 2022;77(4):987-995.
5. Cheng F, Kovács IA, Barabási AL. Network-based prediction of drug combinations. Nature Communications. 2021;12(1):1-11.
6. Farrell DJ, Smith J. In vivo efficacy of the novel βlactamase inhibitor BLI-489 in combination with vancomycin in a murine sepsis model. Antimicrobial Agents and Chemotherapy. 2021;65(8):e00234-21.
7. Fischbach MA. Combination therapies for combating antimicrobial resistance. Current Opinion in Microbiology. 2011;14(5):519-523.
8. Gomez-Gonzalez C, et al. Synergy of teicoplanin and ceftobiprole against vancomycin-intermediate Staphylococcus aureus. Frontiers in Microbiology. 2022;13:894532.
9. Hughes CC, Fenical W. Marinopyrrole A, a potent KPC inhibitor from a marine actinomycete. Journal of Natural Products. 2019;82(11):3011-3016.
10. Jansen KU, Knirsch C, Anderson AS. The role of vaccines in preventing antimicrobial resistance. Nature Medicine. 2020;26(10):1550-1562.
11. Jawetz E, Gunnison JB. An experimental basis of combined antibiotic action. Journal of the American Medical Association. 1953;150(7):693-695.
12. Kumar S, Lee JH. Erythromycin as a competitive inhibitor of efflux pumps in Pseudomonas aeruginosa. International Journal of Antimicrobial Agents. 2023;61(1):106689.
13. Lange C, Aarnoutse E, Chesov D. The history of tuberculosis treatment. Tuberculosis. 2022;133:102182.
14. Le J, Bayer AS. Combination antibiotic therapy for Enterococcus faecalis endocarditis. Clinical Infectious Diseases. 2003;36(5):615-621.
15. Lee SY, et al. Tobramycin and ceftazidime combination therapy in a murine model of Pseudomonas aeruginosa lung infection. Journal of Infectious Diseases. 2023;227(5):672681.
16. Li Y, Müller R. A novel antifolate from a marine Streptomyces synergizes with sulfamethoxazole. Marine Drugs. 2021;19(6):310.
17. Murray CJL, et al. Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. Lancet. 2022;399(10325):629-655.
18. Odds FC. Synergy, antagonism, and what the chequerboard puts between them. Journal of Antimicrobial Chemotherapy. 2003;52(1):1.
19. Patel D, et al. Vancomycin potentiates clarithromycin activity against methicillin-resistant Staphylococcus aureus. Medical Microbiology and Immunology. 2022;211(2):113120.
20. Pfaller MA, Flamm RK. Daptomycin and ceftaroline combination therapy for persistent MRSA bacteremia. Clinical Microbiology Reviews. 2019;32(3):e00019-19.
21. Rutledge PJ, Challis GL. Discovery of microbial natural products by activation of silent biosynthetic gene clusters. Nature Reviews Microbiology. 2015;13(8):509-523.
22. Sakamoto K, et al. Mechanism of synergy between daptomycin and β-lactams against methicillin-resistant Staphylococcus aureus. Antimicrobial Agents and Chemotherapy. 2020;64(5):e02277-19.
23. Singh R, et al. A piperine-like alkaloid from Streptomyces sp. inhibits the MexAB-OprM efflux pump in Pseudomonas aeruginosa. ACS Infectious Diseases. 2021;7(9):25462555.
24. Tyers M, Wright GD. Drug combinations: a strategy to extend the life of antibiotics in the 21st century. Nature Reviews Microbiology. 2019;17(3):141-155.
25. Varela MF, Stephen J, Lekera F. Bacterial resistance to antibiotics. Infections and Drug Resistance. 2021;14:29332948.
26. Wei X, et al. A cryptic peptide from Streptomyces coelicolor synergizes with colistin against resistant Acinetobacter baumannii. Nature Chemical Biology. 2024;20(2):189-197.
27. Yeh PJ, Tschumi AI, Kishony R. Functional classification of drugs by properties of their pairwise interactions. Nature Genetics. 2006;38(4):489-494.
28. Yin J, et al. A machine learning approach for predicting antibiotic synergy. PLoS Computational Biology. 2022;18(7):e1010283.
29. Zhang L, et al. Sub-inhibitory tobramycin modulates the marA regulon in Pseudomonas aeruginosa. Journal of Bacteriology. 2023;205(3):e00451-22.