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Bacillus subtilis Pathway Optimization

Accelerate Production Strain Development from Pathway Design to Pre-Pilot Scale.

Iterative design-build-test-learn cycles to engineer Bacillus subtilis for enhanced production of target compounds.

  • Custom pathway design for the target compound
  • Iterative optimization cycles with quantitative metabolite data.
  • Scalable from shake-flask R&D to pre-pilot bioreactor evaluation

End-to-End Bacillus subtilis Metabolic Engineering

Our service covers the complete pathway optimization workflow: in silico modeling, gene synthesis, strain construction, cultivation, and metabolite quantification—all under a single project manager. Each project is tailored to the target molecule and includes iterative rounds of optimization.

  • Design-Build-Test-Learn cycle for systematic improvement
  • HPLC/LC-MS metabolite profiling for flux monitoring
  • Strain stability assessment over multiple passages
Design & Model
Build & Transform
Quantify & Iterate
Our Approach

Systematic Pathway Optimization in Bacillus subtilis

We apply a structured design-build-test-learn methodology tailored to your target molecule and production goals. Each project begins with in silico pathway design and progresses through iterative cycles of genetic engineering and fermentation evaluation.

Pathway Design & In Silico Modeling

Retrosynthetic analysis and flux balance modeling to identify optimal gene combinations and regulatory nodes for the target product.

  • Target molecule pathway mapping using genome-scale metabolic models
  • Gene selection from B. subtilis or heterologous sources
  • Promoter and RBS design for balanced expression

Strain Construction & Screening

Iterative rounds of DNA assembly, transformation, and shake-flask screening to identify high-producing variants.

  • Synthetic gene construction and plasmid assembly
  • B. subtilis competent cell transformation and selection
  • Shake-flask cultivation with optical density and metabolite sampling

Custom Pathway Construction

Design and assemble biosynthetic gene clusters or individual pathway modules tailored to B. subtilis codon usage and regulatory context.

Fermentation Parameter Tuning

Optimization of media composition, induction conditions, and feeding strategy to evaluate yield and productivity.

Analytical Characterization

HPLC and LC-MS quantification of target metabolite and key intermediates, with optional byproduct profiling.

Deliverables

What You Receive

Each project delivers a clearly documented engineered B. subtilis strain alongside quantitative performance data and standard operating procedures.

Engineered Strain & Data

  • Final engineered B. subtilis strain (glycerol stock, verified by sequencing)
  • Production titer, yield, and productivity data from shake-flask runs
  • Documented pathway design and genetic construct map
  • Summary of fermentation parameters evaluated

Supporting Documentation

  • DNA sequence files (GenBank format) of all constructs
  • Metabolite quantification reports (HPLC/LC-MS chromatograms)
  • Stability assessment data (passaging and re-scoring)
  • Project report including iterative improvement history
Service Scope

Parameters and Customization

Projects are scoped per target molecule and project-scoped attributes assessed analytically. Below are typical parameters discussed during initial consultation.

Parameter Typical project scope
Target Molecule Class Small molecules, amino acids, organic acids, polyketides, peptides, or heterologous proteins
Pathway Design Strategy Retrosynthetic modeling, heterologous pathway assembly, or existing pathway optimization
Genetic Modification Approach Plasmid-based expression, chromosomal integration, promoter engineering, or gene knockouts
Evaluation Scale Shake-flask (scale scoped per project–scale scoped per project) to bench-top bioreactor (scale
Quantification Method HPLC-UV/RI, LC-MS/MS, or bioassay for target metabolite; byproduct profile as needed
Number of Improvement Cycles Determined per project; typically 3–5 iterative rounds with interim data review
Workflow

How We Execute Bacillus subtilis Pathway Optimization

Our standard workflow follows five phases from initial design to final strain validation.

Pathway Design & In Silico Modeling

We perform retrosynthetic analysis and flux balance modeling to select enzyme candidates and design synthetic operons. Target molecule pathways are mapped using B. subtilis genome-scale models to identify flux bottlenecks.

Gene Synthesis & Plasmid Construction

Custom DNA fragments are synthesized and assembled into B. subtilis expression vectors with appropriate promoters, RBS, and terminators. Constructs are sequence-verified before transformation.

Transformation & Strain Construction

Competent B. subtilis cells are transformed with the pathway plasmids. Positive clones are selected on antibiotics and confirmed by colony PCR and sequencing.

Shake-Flask Cultivation & Screening

Multiple clones are cultivated in shake flasks under controlled conditions. Optical density and metabolite concentrations are monitored to rank production performance.

Analytical Metabolite Quantification & Iteration

Culture supernatants are analyzed by HPLC or LC-MS for target and intermediate quantification. Top-performing strains are selected for the next round of engineering or final characterization.

Applications

Where Bacillus subtilis Pathway Optimization Delivers Value

Our service supports a wide range of industrial biotechnology applications where B. subtilis is a preferred host.

Production of Organic Acids and Alcohols

Engineer B. subtilis for high-yield production of lactic acid, succinic acid, butanol, and other platform chemicals using renewable feedstocks.

  • Pathway design for homofermentative production
  • Co-factor balancing to minimize byproducts
  • Scale-up demonstration in bench bioreactors

Heterologous Protein and Enzyme Production

Evaluate secretion pathways and expression systems in B. subtilis for industrial enzymes, therapeutic proteins, or diagnostic reagents.

  • Signal peptide optimization for secretion
  • Promoter tuning for expression level control
  • Fed-batch cultivation to boost volumetric productivity

Biosynthesis of Antimicrobials and Pigments

Reconstitute and evaluate biosynthetic gene clusters from actinomycetes or fungi in B. subtilis for novel natural product discovery and production.

  • Heterologous expression of silent BGCs
  • Precursor supply enhancement
  • Post-PKS tailoring enzyme co-expression
FAQ

Frequently Asked Questions

Common questions about our Bacillus subtilis pathway optimization service.

  • We work with a broad range of product classes including organic acids, amino acids, polyketides, terpenoids, and heterologous proteins. The pathway complexity is evaluated during initial consultation to investigate feasibility and scoping.

  • The number of design-build-test-learn cycles is project-dependent, typically ranging from two to five rounds depending on pathway complexity and target yield. Interim milestones are defined at project start to assess progress and decide on additional cycles.

  • Yes, we can use customer-provided strains as starting hosts. Alternatively, we offer common laboratory strains optimized for transformation and protein secretion. All work is performed under a material transfer agreement to protect your IP.

  • Project timelines are determined during scoping and depend on the number of engineering cycles, pathway length, and analytical requirements. A typical single-cycle project may take a timeline confirmed during project scoping, while multi-cycle projects can extend to a timeline confirmed during project scoping. We provide a detailed timeline with milestones at the proposal stage.

Scientific Literature

References

  1. Put H, Gerstmans H, Vande Capelle H, et al. Bacillus subtilis as a host for natural product discovery and engineering of biosynthetic gene clusters. Natural product reports. 2024;41(7):1113-1151. View on PubMed
  2. Ye JW, Chen GQ. Halomonas as a chassis. Essays in biochemistry. 2021;65(2):393-403. View on PubMed
  3. Tibocha-Bonilla JD, Zuñiga C, Lekbua A, et al. Predicting stress response and improved protein overproduction in Bacillus subtilis. NPJ systems biology and applications. 2022;8(1):50. View on PubMed

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