Evolution Under Process Pressure

Adaptive Laboratory Evolution Service

Let sustained selection deliver the traits that rational design cannot reach — solvent tolerance, low-pH survival, growth on a new feedstock. Part of our Microbial Strain Engineering & Fermentation Optimization Platform.

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100–1,000+

generations per campaign

4 modes

batch · chemostat · turbidostat · auxostat

9 stress axes

applied alone or combined

Schematic of an adaptive laboratory evolution workflow showing serial batch passaging, continuous culture vessels, online monitoring, and endpoint genome resequencing of an adapted strain.

Batch → Continuous

one adaptation engine

Selection, not design — no mechanistic model required

Pressure that matches the process, not a single lab variable

Endpoint clones resequenced with causal mutations mapped

Overview

When The Trait Has No Blueprint, Use Selection

Tolerance, robustness, and feedstock flexibility are polygenic and poorly mapped. Adaptive evolution reaches them anyway.

Surviving a lignocellulosic hydrolysate, holding productivity at low pH, or growing on a substrate the organism never encountered are traits distributed across dozens of loci. No target list exists to edit, and rational design stalls before it starts. Adaptive Laboratory Evolution sidesteps the problem: apply the pressure the process will apply, keep the population dividing, and let the fittest lineages emerge over hundreds of generations.

Creative BioMart Microbe integrates serial batch, continuous culture, automated, and specialized selection strategies into a unified adaptive evolution platform. Each campaign is assembled from a cultivation mode, a selection pressure, and a monitoring strategy chosen to match your target trait and process conditions.

Campaigns close with whole-genome resequencing of endpoint clones and populations, so you receive not only an improved strain but the mutations behind it. Those variants can then be moved into a clean production background through our Strain Directed Evolution service, or verified against a wider variant set built by Mutant Library Construction.

The result is a strain selected under the conditions it will actually face — and a documented genetic explanation for why it performs.

Services

Four Modules, One Continuous Selection Engine

Every campaign is assembled from a cultivation mode, a selection pressure, and a monitoring strategy. The three choices are made together, because the wrong pairing either kills the population or lets it coast.

Service Modules

Illustration of serial batch adaptive evolution showing repeated transfer of an exponential-phase culture into fresh medium under selection pressure.

Serial Batch Evolution

Cultures are transferred at exponential phase into fresh selective medium, returning the population repeatedly to unrestricted growth. Growth-based transfer timing maintains synchronized physiological states across parallel lineages. Best for: tolerance traits and parallel replicate lineages.

Continuous Culture Evolution

Chemostat, turbidostat, and auxostat operation hold the population under uninterrupted selection at a steady state you define. A chemostat fixes growth rate through the dilution rate and selects on nutrient affinity; a turbidostat lets cells grow at their maximum specific growth rate under steady-state selection; an auxostat ties feed to a measured variable such as pH. Best for: substrate limitation and growth-rate maximization.

Illustration of an automated evolution platform with integrated online monitoring and feedback control for adaptive selection.

Automated Evolution Platforms

Integrated online monitoring tracks culture performance throughout the run, with feedback control adjusting selection pressure to maintain evolutionary momentum. Pressure is modulated based on population response, keeping lineages away from both extinction and stagnation across extended campaigns. Best for: long campaigns and reproducible ramp control.

Specialized Selection Strategies

The pressure itself is the design variable. We apply substrate limitation, product tolerance, temperature, pH, osmotic, oxidative and solvent stress, co-culture evolution, and multi-factor gradients that ramp two or more pressures together. Combining stresses is what separates a strain that survives one laboratory variable from one that holds up in the real fermentation. Best for: industrial robustness under combined conditions.

Cultivation Mode Comparison

Mode selection determines what the population is actually competing on. The table below is the starting point for that decision during consultation.

Mode	Operating Principle	Growth Rate	What It Selects For
Serial batch	Periodic transfer at exponential phase into fresh medium containing the selection pressure	Fluctuating — repeated lag, growth, and depletion	Fastest recovery and growth under the applied stress
Chemostat	Continuous feed at a fixed dilution rate; one nutrient held growth-limiting	Fixed by the dilution rate	Highest affinity for the limiting substrate
Turbidostat	Feed regulated by optical density feedback; nutrients kept in excess	Maximal and self-selected	Maximum specific growth rate under steady-state selection
Auxostat	Feed controlled by a measured culture variable such as pH or dissolved oxygen	Set by the controlled variable	Adaptation to a defined physiological set point

Selection Pressure Library

Pressure	How It Is Applied	Target Trait
Substrate limitation	Growth-limiting feed of the target carbon or nitrogen source in continuous culture	Uptake affinity, non-native substrate utilization
Product tolerance	Stepwise increase of the accumulating product in the medium	Higher end titer, reduced product inhibition
Temperature stress	Gradual ramp above or below the growth optimum across successive passages	Thermotolerance, reduced cooling demand at scale
pH stress	Progressive acidification or alkalization under buffered or auxostat control	Low-pH organic acid production, acid-resistant probiotics
Osmotic stress	High sugar or salt loading raised in defined increments	High-gravity fermentation, dehydration survival
Oxidative stress	Controlled peroxide exposure or elevated dissolved oxygen	Redox robustness, aerobic process stability
Solvent tolerance	Rising concentrations of alcohols, organic solvents, or hydrolysate inhibitors	Biofuel and biorefinery robustness
Co-culture evolution	Paired or consortium cultivation with a partner organism	Cross-feeding, community stability, syntrophic productivity
Multi-factor stress gradient	Two or more pressures ramped simultaneously across the campaign	Combined robustness under real process conditions

Campaign Workflow

Six stages, from initial consultation to delivering the adapted clone with its mutation list.

Consultation & Scoping

Define target trait and pressure

Baseline Phenotyping

Find the current tolerance ceiling

Campaign Design

Mode, ramp profile, replicates

Evolution Run

Monitored passaging or continuous run

Isolation & Validation

Clone picking, stability testing

Characterization & Delivery

Mutation report + stocks

Campaign Specifications & Monitoring

01 · Platform Capability

Automated serial passaging with growth-based transfer timing.
Chemostat, turbidostat, and auxostat vessels with defined dilution control.
Integrated online culture monitoring and feedback control.
Adaptive stress ramping responsive to population performance.
Parallel replicate lineages to separate reproducible adaptation from drift.
Whole-genome resequencing of endpoint clones and populations with variant-frequency tracking.
Reverse engineering of candidate mutations in a clean background to confirm causality.

02 · Typical Campaign Metrics

Campaign duration	4–16 weeks, pressure-dependent
Generations accumulated	100–1,000+
Parallel lineages	3–8 per condition
Endpoint clones characterized	5–20 per lineage
Host coverage	Bacteria, yeast, fungi, microalgae

03 · Deliverables & Documentation

Adapted strain	Glycerol stocks of endpoint clones
Population archive	Frozen intermediate passages
Phenotype report	Growth, tolerance ceiling, productivity
Mutation report	Variant list with frequencies
Campaign record	Mode, ramp profile, monitoring traces

Sample Requirements

What To Send Us

An evolution campaign is only as good as its starting point. Alongside the culture, we need to know where your strain currently stops performing.

Required	Optional	Not Accepted
Pure, axenic starting culture with its documented growth medium Strain name and taxonomic identification Biosafety classification (e.g., BSL-1) and known sensitivities Target trait and the stress that defines it Current performance ceiling — the condition at which growth stops	Genome sequence or assembly of the parent strain Prior evolution, mutagenesis, or screening history Process medium or hydrolysate sample for realistic pressure Acceptable trade-offs, such as growth rate against product yield Preferred cultivation mode	Contaminated or mixed cultures, unless a co-culture project is declared Uncharacterized pathogens (BSL-2 or above without clearance) Strains under material transfer or export restrictions Cultures that cannot be revived from a frozen stock

Baseline Data That Shortens A Campaign

Growth curve in your reference medium	Sets the unstressed control and doubling time
Inhibitory concentration of the target stress	Defines where the ramp begins
Parent genome sequence	Separates evolved mutations from pre-existing variants
Product or reporter assay	Tracks productivity alongside growth
Process medium sample	Allows evolution under the actual downstream condition

Storage & Shipping: Ship glycerol stocks on dry ice, or send stabilized agar slants at ambient temperature with cushioning. Send at least two independent vials so a campaign can be restarted without a second shipment, and avoid temperature excursions that reduce viability before the run begins. If a hydrolysate or process medium is supplied, ship it separately and note any preservative added. Contact our team via the contact form before dispatch for biosafety clearance.

Advantages

Why Teams Run ALE Campaigns With Us

No Target List Required

Polygenic traits such as tolerance and feedstock flexibility are reached through selection, so a campaign can start before anyone knows which genes are involved.

All Four Cultivation Modes

Serial batch, chemostat, turbidostat, and auxostat operation run on the same platform, so the mode follows the trait rather than the equipment on hand.

Pressure Matched To Your Process

Campaigns can be run in your own hydrolysate or process medium, so the strain adapts to the conditions it will meet downstream instead of a simplified laboratory proxy.

Ramping That Responds To The Culture

Stress levels are adjusted from live monitoring data rather than a fixed calendar, keeping lineages between the two ways campaigns fail — extinction and stagnation.

Replicate Lineages, Not Single Winners

Running several lineages in parallel shows whether an adaptation is reproducible, and mutations recurring across independent lines are the ones worth transferring.

Mutations Mapped, Not Just Strains

Endpoint resequencing and optional reverse engineering identify the causal variants, turning an evolved isolate into a defined edit you can reapply to other backgrounds.

Customer Reviews

Trusted by Research Teams Worldwide

"We sent our own hydrolysate along with the strain, and the campaign was run in that medium rather than a synthetic substitute. The adapted isolate performed on the first attempt in our pilot fermentation, which almost never happens."

Dr. E. L.

Bioprocess Engineer

USA

"The chemostat campaign on a limiting carbon source gave us the uptake improvement we had failed to engineer for two years. Being able to read the dilution-rate history alongside the sequencing data made the result easy to defend internally."

Dr. T. N.

Metabolic Engineer

USA

"Six parallel lineages under the same solvent ramp told us far more than a single line would have. Two independent lineages converged on the same locus, and that convergence is what convinced us to build the edit into our production host."

Dr. C. A.

Synthetic Biologist

USA

"Our previous attempt at adaptive evolution died out twice because the stress steps were too aggressive. Here the ramp was driven by the growth signal, and the culture stayed viable through the entire ascent."

Dr. N. H.

Principal Scientist

USA

"Combining thermal and osmotic pressure in one gradient produced a starter culture that holds up in high-gravity conditions. Testing the two stresses separately had never reproduced that behavior."

Dr. M. B.

Fermentation Specialist

Germany

"The frozen archive of intermediate passages turned out to be the most useful deliverable. When we wanted to understand when the phenotype appeared, we could go back and re-test the population at each stage."

Dr. A. V.

Research Director

USA

Applications

Where Adaptive Evolution Creates Value

Lignocellulosic Biorefining

Furfural, HMF, acetate tolerance

Illustration representing organic acid fermentation at low pH.

Organic Acids

Low-pH titer and survival

Illustration representing biofuel production and solvent tolerance.

Biofuels & Solvents

Alcohol and solvent tolerance

Non-Native Substrates

Methanol, glycerol, xylose uptake

Illustration representing probiotic and starter culture robustness.

Probiotics & Starters

Acid, bile, drying survival

Illustration representing high-gravity industrial fermentation.

High-Gravity Fermentation

Osmotic and thermal load

Case Study

Automated Campaigns And Long-Term Gradients

Automated Evolution: Robotics-Assisted ALE Lifts HMF Tolerance In Pseudomonas taiwanensis

An oxidation-deficient derivative of Pseudomonas taiwanensis VLB120 was evolved under HMF selection pressure using robotics-assisted adaptive laboratory evolution. Passaging was automated in microtiter-scale cultures and triggered whenever scattered-light intensity crossed a fixed threshold, giving seven serial passages across roughly one week and about 40 generations. Final cultures reached the transfer threshold in a mean of 14.7 h, more than twice as fast as the starting cultures, and isolated clones grew in the presence of 8 mM HMF where the unevolved parent did not grow at all. Whole-genome sequencing found loss-of-function mutations in the transcriptional regulator mexT in every evolved clone, and reverse engineering of mexT variants reproduced the tolerance, tracing the benefit to shutdown of the mexEF-oprN efflux pump. The study shows how automated passaging, online growth monitoring, and endpoint resequencing turn a short campaign into a causally explained trait.

Growth comparison of evolved clones, unevolved GRC1 ROX, and oxidation-positive GRC1 in absence or presence of HMF. — Figure 1. Analysis of isolated clones from the ALE. (Lechtenberg, *et al.* 2024)

Multi-Factor Gradient: Thermotolerant Candida tropicalis Adapted For High-Glucose Fermentation

A thermotolerant Candida tropicalis isolate was put through repetitive long-term cultivation with a gradual temperature increase in medium containing 200 g/L glucose, so heat and osmotic load acted together. Seven-day passages carried the culture from 40°C up to 44.5°C, and the single surviving lineage yielded the adapted strain X-17.2b. Fermenting 160 g/L glucose at 37°C, the adapted strain reached 60.7 g/L ethanol against 46.5 g/L for the parent — a 30.7% gain accompanied by 15.6% higher glucose consumption — and it still produced 27.8 g/L at 42°C where the parent managed 14.9 g/L. Tolerance to ethanol, furfural, and HMF improved as well. This is the multi-factor stress gradient strategy in practice: stacking two industrially relevant pressures in one campaign yields a strain fit for the process rather than for a single laboratory variable.

Growth and metabolite profiles of parental Candida tropicalis X-17, the adapted strain X-17.2b, and Kluyveromyces marxianus DMKU 3-1042 in medium containing 160 g/L glucose. — Figure 2. Growth and metabolite profiles of C. tropiclis X-17 (filled circles), adapted strain C. tropicalis X-17.2b (filled squares) and K. marxianus DMKU 3-1042 (filled triangles). (Phommachan, *et al.* 2022)

Turn Evolved Mutations Into Defined Edits

Variants recovered from a campaign can be rebuilt in a clean production background through directed evolution and targeted engineering, so the gain travels with the strain.

Explore Directed Evolution →

FAQs

Common Questions

Q: Which cultivation mode should I choose for my trait?

Serial batch suits tolerance traits and stress ramps because the population repeatedly re-enters exponential growth. A chemostat is the right choice when the goal is affinity for a limiting substrate, a turbidostat when you want maximum specific growth rate under steady-state selection, and an auxostat when selection should track a controlled variable such as pH. We confirm the mode after baseline phenotyping.

Q: How do you keep the selection pressure from wiping out the culture?

Stress is raised in steps rather than set at a target value from the outset, and each step is gated on the measured growth response. If a lineage slows beyond a defined margin, the pressure is held or reduced until growth recovers. Parallel lineages provide additional insurance, since losing one line does not end the campaign.

Q: How long does a campaign run, and how many generations does that give?

Most campaigns run 4–16 weeks and accumulate 100–1,000 or more generations, depending on doubling time and how steeply the pressure rises. Short automated campaigns can produce measurable tolerance gains in a week when the selection is strong, while substrate-affinity work in continuous culture generally needs longer.

Q: How do you confirm the improvement is genetic rather than a temporary physiological adjustment?

Endpoint clones are isolated, passaged without the selection pressure, and re-tested to confirm the phenotype persists. Whole-genome resequencing then identifies the underlying mutations, and candidate variants can be reverse engineered into the parent background to demonstrate that they alone reproduce the trait.

Q: Can the campaign be run against my actual process medium or hydrolysate?

Yes, and it usually gives a better outcome than a synthetic proxy. Real hydrolysates and process media contain inhibitor mixtures that no single-compound challenge reproduces. Send a representative sample with the culture and note any preservative, and we will characterize it before designing the ramp.

Q: Can several stresses be applied at the same time?

They can, through multi-factor stress gradient evolution. Two or more pressures — for example temperature together with high sugar loading — are ramped in parallel so the population adapts to the combination. Strains selected this way often outperform strains evolved against each stress separately when placed in a real fermentation.

Q: What can be done with the campaign results afterwards?

The mutation report is the bridge to the rest of the platform. Causal variants can be rebuilt in a clean host through our Strain Directed Evolution service, explored more broadly with Mutant Library Construction, or ranked across many isolates by High-Throughput Screening.

Ready To Put Your Strain Under Pressure?

Tell us the condition where your strain currently stops performing—our team will design the cultivation mode, the stress ramp, and the readout around it.

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Mutant Library Construction

Diversity generation

High-Throughput Screening

Million-scale discovery

Strain Directed Evolution

Iterative enhancement

Adaptive Laboratory Evolution

Industrial robustness

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References:

Lechtenberg, T., et al. (2024). Improving 5-(hydroxymethyl)furfural (HMF) tolerance of Pseudomonas taiwanensis VLB120 by automated adaptive laboratory evolution (ALE). Metabolic Engineering Communications, 18, e00235.
Phommachan, K., et al. (2022). Adaptive laboratory evolution for multistress tolerance, including fermentability at high glucose concentrations in thermotolerant Candida tropicalis. Energies, 15(2), 561.

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