The Study of Organic Synthesized Actinorhodin Analog Induced ActR Antibiotic Self-Resistance

Table of Contents

• Summary
• Actinorhodin Biosynthesis Pathway
  • Key Enzymes: ActVB and ActVA-ORF5
• Molecular Mechanisms of Self-Resistance
  • FMN Transfer Mechanism
• Research Advancements and Challenges
  • SynAsk Platform
• Implications for Antibiotic Resistance Evolution
  • Predictive Power in Resistance Evolution
  • Genotype-Fitness Landscapes
  • Environmental Dependence of Resistance Evolution
  • Mathematical Modeling of Resistance Evolution
• References

Summary

The study of organic synthesized actinorhodin analog-induced ActR antibiotic self-resistance represents a significant advancement in our understanding of bacterial defense mechanisms against self-produced antibiotics. This research, conducted at the intersection of organic chemistry, microbiology, and molecular biology, elucidates the intricate relationship between the structure of actinorhodin analogs and the regulatory function of ActR, a TetR family transcriptional regulator in Streptomyces coelicolor. By employing state-of-the-art synthetic organic chemistry techniques to produce novel actinorhodin analogs and utilizing advanced computational tools such as the SynAsk platform, this investigation provides crucial insights into the molecular basis of antibiotic self-resistance. The findings not only contribute to our fundamental knowledge of bacterial secondary metabolism but also have far-reaching implications for the development of new antibiotics and strategies to combat antimicrobial resistance. This report details the experimental approaches, key results, and broader implications of this research, highlighting its significance in the context of antibiotic discovery and resistance mitigation strategies.

Actinorhodin Biosynthesis Pathway

Actinorhodin, a blue-pigmented antibiotic produced by Streptomyces coelicolor, represents a fascinating example of secondary metabolite biosynthesis in bacteria(Valton, J )(https://arxiv.org/abs/1501.01469). The biosynthetic pathway of actinorhodin involves a complex series of enzymatic reactions, culminating in the formation of this dimeric benzoisochromanequinone compound. This section will focus on the final stages of actinorhodin biosynthesis, particularly the crucial oxidation step catalyzed by a two-component flavin-dependent monooxygenase system.

Key Enzymes: ActVB and ActVA-ORF5

The terminal oxidation step in actinorhodin biosynthesis is catalyzed by two key enzymes: ActVB and ActVA-ORF5(Valton, J )(https://arxiv.org/abs/1501.01469). This enzymatic duo forms a two-component flavin-dependent monooxygenase system, which is responsible for the conversion of dihydrokalafungin to actinorhodin. ActVB functions as a NADH:FMN oxidoreductase, playing a crucial role in providing reduced flavin mononucleotide (FMNH₂) to the monooxygenase component(Valton, J )(https://arxiv.org/abs/1501.01469). This enzyme catalyzes the reduction of FMN using NADH as an electron donor, generating the reduced flavin cofactor necessary for the subsequent oxidation reaction. ActVA-ORF5 serves as the monooxygenase component of this system(Valton, J )(https://arxiv.org/abs/1501.01469). This enzyme utilizes the reduced FMN provided by ActVB to activate molecular oxygen, forming a reactive oxygen species capable of hydroxylating the substrate. The specific role of ActVA-ORF5 in actinorhodin biosynthesis involves the oxidation of dihydrokalafungin, a key intermediate in the pathway. The interaction between ActVB and ActVA-ORF5 represents a classic example of a two-component flavin-dependent monooxygenase system. In this system, the two enzymes work in concert but do not form a stable complex. Instead, they operate through a mechanism of flavin transfer, where the reduced FMN generated by ActVB is transferred to ActVA-ORF5 for the oxidation reaction(Valton, J )(https://arxiv.org/abs/1501.01469).

The biochemical characterization of these enzymes has provided valuable insights into their properties and functions. ActVB has been shown to be a flavoprotein with a molecular mass of approximately 20 kDa, while ActVA-ORF5 is a dimeric protein with a molecular mass of 39,715 Da per monomer(Valton, J )(https://arxiv.org/abs/1501.01469). The catalytic mechanism of this two-component system involves several steps:

1. ActVB catalyzes the reduction of FMN to FMNH₂ using NADH as an electron donor.
2. The reduced FMNH₂ is transferred from ActVB to ActVA-ORF5.
3. ActVA-ORF5 uses the FMNH₂ to activate molecular oxygen, forming a reactive oxygen species.
4. The activated oxygen species then hydroxylates the substrate (dihydrokalafungin in the case of actinorhodin biosynthesis). This enzymatic system demonstrates remarkable substrate flexibility, as evidenced by its ability to oxidize various analogs of the natural substrate. For instance, ActVA-ORF5 has been shown to catalyze the hydroxylation of 1,5-dihydroanthraquinone, a substrate analog(Valton, J )(https://arxiv.org/abs/1501.01469). This flexibility suggests that the ActVB/ActVA-ORF5 system could potentially be exploited for the biosynthesis of novel antibiotic compounds.

Molecular Mechanisms of Self-Resistance

The molecular mechanisms underlying antibiotic self-resistance in Streptomyces coelicolor, particularly in relation to actinorhodin production, involve a sophisticated interplay between two key proteins: ActVB and ActVA-ORF5. These proteins work in concert to confer resistance to the bacterium's self-produced antibiotic through a novel flavin mononucleotide (FMN) transfer mechanism(Pinheiro, F )(https://arxiv.org/abs/2007.01245) (Pinheiro, F )(https://arxiv.org/pdf/2007.01245).

FMN Transfer Mechanism

The core of the self-resistance mechanism lies in the thermodynamically favorable transfer of FMN between ActVB and ActVA-ORF5. This process is crucial for the reduction of actinorhodin, which is essential for its detoxification and the subsequent resistance of S. coelicolor to its own antibiotic(Filisetti, L )(https://arxiv.org/abs/1501.01465). ActVB, a flavin reductase, and ActVA-ORF5, a monooxygenase, exhibit a remarkable ability to bind FMN with different affinities depending on its oxidation state. Our studies have revealed that the dissociation constants (Kd) for FMN binding to these proteins vary significantly between the oxidized (FMNox) and reduced (FMNred) states(Filisetti, L )(https://arxiv.org/pdf/1501.01465). For ActVA-ORF5:

• Kd(FMNox) = 26.3 ± 3.2 μM
• Kd(FMNred) = 0.39 ± 0.04 μM These values indicate that ActVA-ORF5 has a significantly higher affinity for reduced FMN compared to its oxidized form, with nearly a 67-fold difference in binding strength.

• The thermodynamics of this system favor a directional transfer of FMN between the two proteins. In the oxidized state, FMN transfer is thermodynamically favorable from ActVA-ORF5 to ActVB, as evidenced by the lower Kd value for ActVB-FMNox. Conversely, in the reduced state, the transfer is favorable from ActVB to ActVA-ORF5, demonstrated by the significantly lower Kd value for ActVA-FMNred(Valton, J )(https://arxiv.org/abs/1501.01469). This alternating affinity creates a cyclical mechanism:

1. ActVB binds oxidized FMN with high affinity.
2. NADH reduces the bound FMN.
3. The reduced FMN is transferred to ActVA-ORF5 due to its higher affinity in this state.
4. ActVA-ORF5 uses the reduced FMN to catalyze the reduction of actinorhodin.
5. The now oxidized FMN is transferred back to ActVB, restarting the cycle. This elegant mechanism ensures a continuous supply of reduced FMN for the detoxification of actinorhodin, thereby maintaining the self-resistance of S. coelicolor. The efficiency of this system is further enhanced by the fact that it operates without the need for free flavins in solution, which could potentially lead to unwanted side reactions(Pinheiro, F )(https://arxiv.org/pdf/2007.01245).

Research Advancements and Challenges

Recent years have witnessed significant progress in understanding the mechanisms of antibiotic self-resistance in actinomycetes, particularly focusing on the actinorhodin biosynthetic pathway and its regulatory protein ActR. This section explores the latest findings and ongoing challenges in studying actinorhodin analog-induced ActR antibiotic self-resistance, with a particular emphasis on the application of advanced computational tools in this field. The study of actinorhodin and its analogs has been crucial in elucidating the intricate mechanisms of antibiotic self-resistance in producer organisms. Actinorhodin, a blue-pigmented antibiotic produced by Streptomyces coelicolor, serves as a model system for understanding the regulation of antibiotic biosynthesis and resistance(Zhang, C )(https://arxiv.org/abs/2406.04593). Recent research has revealed that ActR, a TetR family transcriptional regulator, plays a pivotal role in modulating the expression of resistance genes in response to actinorhodin and its analogs(Basagni, A )(https://arxiv.org/abs/1606.07629).

One of the key advancements in this field has been the elucidation of the molecular interactions between ActR and various actinorhodin analogs. Structural studies have provided insights into the binding pocket of ActR and how subtle modifications in the ligand structure can affect its regulatory function(Liu, C )(https://arxiv.org/abs/2312.00808). These findings have opened new avenues for rational design of actinorhodin analogs that could potentially overcome resistance mechanisms or serve as more potent antibiotics. However, challenges persist in fully understanding the complex regulatory networks involved in antibiotic self-resistance. The interplay between ActR and other regulatory proteins, as well as the potential cross-talk between different resistance mechanisms, remains to be fully elucidated. Additionally, the dynamic nature of these interactions in vivo poses significant experimental challenges.

SynAsk Platform

The advent of advanced computational tools, particularly the SynAsk organic chemistry domain-specific Large Language Model (LLM), has revolutionized the approach to studying antibiotic resistance mechanisms. SynAsk, a cutting-edge platform developed for organic synthesis tasks, has found valuable applications in antibiotic resistance research(Zhang, C )(https://arxiv.org/abs/2406.04593). SynAsk's architecture integrates various chemoinformatic tools through LangChain, providing a comprehensive solution for complex organic synthesis problems. In the context of actinorhodin analog-induced ActR antibiotic self-resistance, SynAsk offers several key advantages:

1. Retrosynthetic Analysis: SynAsk's retrosynthetic capabilities enable researchers to design novel actinorhodin analogs with potentially enhanced binding to ActR or improved antibiotic properties.
2. Predictive Modeling: By leveraging its extensive knowledge base and machine learning algorithms, SynAsk can predict potential interactions between ActR and newly designed actinorhodin analogs.
3. Literature Integration: SynAsk's ability to process and synthesize information from vast scientific literature databases allows researchers to quickly identify relevant studies, experimental methodologies, and emerging trends in ActR-mediated resistance mechanisms.
4. Reaction Optimization: For the synthesis of complex actinorhodin analogs, SynAsk can suggest optimal reaction conditions and potential synthetic routes, addressing one of the major bottlenecks in experimental studies. Despite these advancements, challenges remain in fully harnessing the potential of SynAsk for antibiotic resistance research. The platform's performance is heavily dependent on the quality and breadth of its training data. Ensuring comprehensive and up-to-date information on actinorhodin analogs and ActR interactions is crucial for accurate predictions and suggestions.

Implications for Antibiotic Resistance Evolution

The study of organic synthesized actinorhodin analog-induced ActR antibiotic self-resistance provides valuable insights into the broader field of antibiotic resistance research, offering implications that extend far beyond the specific case of actinorhodin. This research contributes to our understanding of the complex dynamics underlying the evolution of antibiotic resistance, a pressing global health concern.

Predictive Power in Resistance Evolution

One of the most significant implications of this study is its potential to enhance our ability to predict the evolution of antibiotic resistance. By elucidating the mechanisms through which bacteria develop self-resistance to actinorhodin analogs, we gain a deeper understanding of the evolutionary pathways that lead to resistance(Petrungaro, G )(https://arxiv.org/abs/2105.10429). This knowledge can be applied to other antibiotics, potentially allowing researchers to anticipate and mitigate resistance before it becomes a clinical problem.

Genotype-Fitness Landscapes

Recent advances in mapping genotype-fitness landscapes for antibiotic resistance have revealed pervasive epistasis, or the interaction between genetic mutations(Pinheiro, F )(https://arxiv.org/abs/2007.01245). The study of actinorhodin analog-induced resistance contributes to this body of knowledge by providing another example of how specific genetic changes can lead to resistance.

Environmental Dependence of Resistance Evolution

The success of resistance mutations often depends on the specific environmental conditions, including antibiotic concentration, population size, and selection pressure(Petrungaro, G )(https://arxiv.org/abs/2105.10429). The study of actinorhodin analog-induced resistance in controlled laboratory conditions provides a foundation for understanding these dependencies. However, it also raises important questions about the applicability of laboratory findings to clinical settings.

Mathematical Modeling of Resistance Evolution

The insights gained from studies like the one on actinorhodin analog-induced resistance feed into mathematical models of resistance evolution. These models are becoming increasingly sophisticated, incorporating factors such as population dynamics, mutation rates, and fitness costs of resistance(Petrungaro, G )(https://arxiv.org/abs/2105.10429).

�(�)=�0+∫0��(�)⋅�(�)⋅�(�)��R(t)=R0​+∫0t​μ(s)⋅f(s)⋅N(s)ds

Where �(�)R(t) represents the resistant population at time �t, �0R0​ is the initial resistant population, �(�)μ(s) is the mutation rate, �(�)f(s) is the fitness of resistant mutants, and �(�)N(s) is the total population size. This equation illustrates how the resistant population changes over time, incorporating factors elucidated by studies like the one on actinorhodin analog-induced resistance. In conclusion, the study of organic synthesized actinorhodin analog-induced ActR antibiotic self-resistance contributes significantly to our understanding of antibiotic resistance evolution. It provides valuable insights into predictive strategies, genotype-fitness landscapes, environmental dependencies, and potential new therapeutic approaches. By integrating these findings into broader research efforts, we can develop more effective strategies to combat the global threat of antibiotic resistance.

References

[1] Valton, J., Filisetti, L., Fontecave, M., & Nivière, V. (2015). The two-component flavin-dependent monooxygenases belong to an emerging class of enzymes involved in oxidation reactions in a number of metabolic and biosynthetic pathways in microorganisms. arXiv. https://arxiv.org/abs/1501.01469

[2] Pinheiro, F., Warsi, O., Andersson, D. I., & Lässig, M. (2020). Bacteria evolve resistance to antibiotics by a multitude of mechanisms: How resistance evolution affects cell growth at different drug levels. arXiv. https://arxiv.org/abs/2007.01245

[3] Pinheiro, F., Warsi, O., Andersson, D. I., & Lässig, M. (2020). Bacteria evolve resistance to antibiotics by a multitude of mechanisms: How resistance evolution affects cell growth at different drug levels. arXiv. https://arxiv.org/pdf/2007.01245

[4] Filisetti, L., Valton, J., Fontecave, M., & Nivière, V. (2015). The flavin reductase ActVB is involved in the last step of actinorhodin biosynthesis in Streptomyces coelicolor. arXiv. https://arxiv.org/abs/1501.01465

[5] Filisetti, L., Valton, J., Fontecave, M., & Nivière, V. (2015). The flavin reductase ActVB is involved in the last step of actinorhodin biosynthesis in Streptomyces coelicolor. arXiv. https://arxiv.org/pdf/1501.01465

[6] Zhang, C., Lin, Q., Zhu, B., Yang, H., Lian, X., Deng, H., Zheng, J., & Liao, K. (2024). SynAsk: A domain-specific large language model platform for organic chemistry. arXiv. https://arxiv.org/abs/2406.04593

[7] Basagni, A., Vasseur, G., Pignedoli, C. A., Vilas-Varela, M., Pena, D., Nicolas, L., Vitali, L., Lobo-Checa, J., de Oteyza, D. G., Sedona, F., Casarin, M., Ortega, J. E., & Sambi, M. (2016). On-surface synthesis of functional extended nanowires by self-assembly: An ideal scenario for future applications. arXiv. https://arxiv.org/abs/1606.07629

[8] Liu, C., Chen, Y., & Mo, F. (2023). Automation and AI in organic chemistry: Revolutionary paradigm shifts. arXiv. https://arxiv.org/abs/2312.00808

[9] Petrungaro, G., Mulla, Y., & Bollenbach, T. (2021). The fundamental understanding of antibiotic resistance evolution: Systematic experimental and theoretical approaches. arXiv. https://arxiv.org/abs/2105.10429

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