What does the LC-MS bile acid panel include, and how does it support NASH screening decisions?

The panel typically quantifies >15 major bile acids across primary/secondary and conjugated/free pools. Deliverables include analyte tables, summarized class shifts, and transformation mapping that connects BSH-linked deconjugation steps to downstream changes, enabling prioritization for follow-up assays.

Can you rank multiple strains in one project and provide a simple decision table?

Yes. We screen strain panels and report tiered BSH activity grades alongside bile acid shift summaries, and we can format a decision table to match your internal gating criteria.

Do you provide evidence of FXR/TGR5 receptor activation?

No, we provide hypothesis generation based on chemical shifts. We map bile acid patterns to likely biological pathways to guide your choice of cell-based or in vivo models for functional validation.

How should I combine this service with downstream models?

A common approach is to screen strains with BSH activity plus bile acid profiling, shortlist candidates based on transformation patterns, and validate with appropriate host-response models.

BSH Activity & Bile Acid Transformation Profiling by LC-MS

Why bile acid modulation is a high-value screening metric

In NASH and fatty liver programs, mechanistic validation often faces a bottleneck: teams can observe a phenotype, but cannot demonstrate whether a candidate strain can shift bile acid pools in a direction consistent with FXR/TGR5-linked pathways. Without a quantitative bile acid panel, it is difficult to compare strains, prioritize MoA experiments, or defend a go/no-go decision.

Uncertain BSH strength

Genomic annotation alone does not guarantee functional BSH activity. You need an in vitro measurement that ranks strains by intensity under controlled conditions.

Unclear transformation route

Bile acid metabolism is network-like: deconjugation can unlock downstream transformations. A strain can be active but still fail to generate the bile acid shifts you need.

Hard-to-compare datasets

Programs often mix readouts (growth, pH, single-analyte LC, or qualitative MS), producing results that are not comparable across strains or studies.

Missing MoA cues

Even with a bile acid panel, teams need interpretable outputs that suggest which FXR/TGR5-relevant hypotheses are plausible and worth validating in vivo or ex vivo.

Service Scope: What's included in the package

This service couples a standardized BSH activity assay with a quantitative LC-MS bile acid panel to produce a cohesive, strain-comparable dataset. You can submit single strains or a screening panel. Outputs are packaged for internal decision-making and partner diligence.

Sample Input Requirements

Strains & Cultures

We accept pure single-strain isolates or defined microbial consortia. Live cultures are required for the functional enzyme activity assay.

Sample Matrix

Compatible with bacterial culture suspensions, cell lysates, culture supernatants, or defined reaction mixtures. (Note: Complex fecal communities or in vivo samples require custom scoping).

Module A: BSH activity assay (in vitro)

We quantify bile salt deconjugation capacity using defined substrates (e.g., typical conjugated bile acids like TCA or GCA) and controlled incubation conditions. The readout measures the released free bile acids or amino acids (via LC-MS or targeted colorimetric methods based on design).

•Standardized activity readout suitable for cross-strain comparison.
•Optional normalization strategies (e.g., biomass/OD or protein) when appropriate for your design.
•BSH intensity grading (e.g., low/medium/high) for decision support.

Note: Grading is provided under standardized assay conditions with defined substrates; cross-project comparability depends on matched conditions.

Module B: LC-MS bile acid panel (quantitative)

We quantify a targeted bile acid panel to capture class-level shifts and specific analyte changes. The panel is designed to inform gut–liver axis hypotheses and to enable transformation mapping from conjugated to free and from primary to secondary pools.

Panel dimension	What is quantified	Why it matters
Primary vs secondary	Class distribution and key representatives	Supports hypotheses on downstream receptor engagement
Conjugated vs free	Deconjugation-linked shifts	Connects directly to BSH-dependent gating steps
Total bile acids	Aggregate concentration trends	Enables normalization across conditions

Coverage: Analyte list available on request or in a downloadable panel sheet (typically covering major primary/secondary BAs such as CA, CDCA, DCA, LCA, and their taurine/glycine conjugates).

Follow-up assay suggestions (FXR/TGR5-related)

We provide a pattern-to-hypothesis mapping based on the data. We first outline the observed shifts, map them to the most likely microbial conversion steps, and finally suggest the recommended readouts in host cell models.
Note: This is designed to guide next-step in vivo/ex vivo validation choices, and is not evidence of receptor activation by itself.

1

Observed Shifts

Quantify significant changes in specific BA ratios (e.g., Free vs. Conjugated, Primary vs. Secondary).

2

Transformation Map

Provide an interpretable route diagram showing likely deconjugation and downstream microbial conversion steps.

3

What you receive: decision-ready deliverables

Your package is built for comparison, reporting, and downstream MoA planning—so the data can be used immediately in internal reviews or partner discussions.

Standard deliverables

•BSH activity results with strain grading (tiered intensity classification).
•LC-MS bile acid quantification table (raw values, normalized formats as applicable).
•Primary/secondary and conjugated/free summaries with clear visualization.
•Transformation pathway diagram inferred from the observed bile acid shifts.
•Mechanism prompts mapping patterns to suggested FXR/TGR5-relevant follow-ups.
•Methods summary and QC notes suitable for documentation and audit trails.

Ready to start?

Share your strain list, sample matrix, and decision questions. We will recommend a fit-for-purpose design that keeps your screening aligned to NASH-relevant endpoints.

Optional add-ons to strengthen the dataset

Add-on	Best for	Output
Condition screening	Strains sensitive to medium, pH, or incubation time	Comparative panels across selected conditions
Replicate expansion	Programs requiring stronger statistics	Higher-confidence ranking and variance estimates
Follow-up hypothesis mapping	Teams planning receptor or host-response assays	Short MoA plan aligned to your target model system

How it works: a practical workflow for strain screening

The workflow is optimized for clarity and repeatability. You can run a small pilot to validate feasibility, then expand to a full screening panel.

1

Project scoping

Confirm strain list, substrates, incubation design, and reporting format aligned to your go/no-go criteria.

2

Sample handling

Standardized handling and documentation to preserve comparability across strains and runs.

3

BSH activity assay

Run the in vitro BSH activity module and assign intensity grades with QC checks.

4

LC-MS bile acid panel

Quantify bile acids, summarize class-level shifts, and generate visualization-ready outputs.

5

Interpretation package

Deliver transformation route mapping and mechanism prompts aligned to FXR/TGR5 follow-up options.

Published Data: Bile salt hydrolases in the gut–liver axis

A peer-reviewed overview discusses how microbial bile salt hydrolases act as key “gatekeeping” enzymes that deconjugate bile acids in the gut, influencing the composition of circulating bile acid pools and shaping host–microbiome signaling. The article highlights conceptual links between deconjugation steps and downstream bile acid transformations, which are often used to frame FXR- and TGR5-relevant mechanism hypotheses.

This service operationalizes that concept into a measurable dataset: we quantify BSH activity directly and pair it with an LC-MS bile acid panel so you can see which strains are most likely to modulate bile acid pools in a way that justifies targeted follow-up experiments.

Bile salt hydrolases deconjugate circulating bile acids along the gut–liver axis. (Creative Biolabs Authorized) — Fig.1 Bile salt hydrolases act on circulating conjugated bile acids in the gut-liver axis.¹

Why teams choose us for bile acid mechanism screening

Our execution is research-grade: rigorous traceable workflows, robust analytical chemistry, and reporting structures that support IND-enabling data expectations.

Targeted LC-MS via internal standards

We utilize isotope-labeled internal standards to ensure precise, reproducible absolute quantification across complex matrices.

Calibration & QC embedded

Every analytical batch includes rigorous calibration curves and QC sample sets to guarantee data integrity for down-selection.

Standardized BSH grading rubric

Assays are evaluated against defined thresholds, allowing reliable intra-project benchmarking of weak vs. strong deconjugators.

Traceable reporting

Methods summary, QC notes, and structured tables designed for internal documentation and partner review.

Actionable hypothesis generation

We map bile acid shifts into practical next-step ideas for FXR/TGR5 host-response validation.

Clear data ownership

You receive structured raw and summarized outputs that integrate directly into your existing bioinformatics pipelines.

Recommended services to extend your gut–liver mechanism package

Bile acid profiling is often most valuable when combined with broader metabolite and functional datasets. The services below are frequently selected to build an integrated gut–liver mechanism package that supports translational decisions and partner discussions.

Fast-start checklist

•Strain IDs and matrix (cultures/lysates)
•Decision question (rank, MoA, comparability, or route mapping)
•Preferred reporting format (tables, figures, or both)

Frequently Asked Questions

The panel is designed to quantify typically >15 major bile acids across primary/secondary and conjugated/free pools (e.g., CA, CDCA, DCA, LCA, and their conjugates) so you can compare strains on the same scale. For screening, the most useful outputs are (1) a quantitative table of analytes, (2) summarized class shifts, and (3) a transformation mapping view that connects deconjugation (BSH-linked) steps to downstream changes. Together, these help you prioritize strains for targeted follow-up assays.

Yes. We can screen panels and deliver an intensity-grade summary for BSH activity (using defined substrates like TCA/GCA) alongside bile acid shift summaries. A decision table can be formatted to match your internal gating criteria (e.g., top-tier BSH activity plus the most informative bile acid pattern changes).

No, we provide hypothesis generation based on chemical shifts. We translate bile acid pool changes into practical next-step ideas (e.g., highlighting patterns that strongly correlate with known FXR/TGR5 activation pathways). These recommendations guide your choice of cell-based or in vivo models for functional validation, rather than serving as standalone therapeutic claims.

We routinely accept pure isolates (live cultures required for BSH activity), defined consortia, bacterial lysates, and culture supernatants. Complex matrices like fecal samples or tissue require a custom scoping discussion. During setup, we confirm matrix handling needs to maintain strict cross-strain comparability.

A common sequence is: (1) screen strains with BSH activity plus bile acid profiling, (2) pick a shortlist based on the transformation pattern you need, and (3) validate with host-response models that match your program (e.g., gut–liver interfaces or liver-relevant readouts). If you share your decision question, we can recommend a staged design.

Resources

Creative Biolabs' Live Biotherapeutics - Brochure

Probiotic Strain Products for NGP Research - Brochure

Custom Small-scale Probiotic Production - Brochure

Live Biotherapeutics - Creative Biolabs - Video

References

Foley, Matthew H., et al. "Bile salt hydrolases: Gatekeepers of bile acid metabolism and host-microbiome crosstalk in the gastrointestinal tract." PLoS Pathogens 15.3 (2019): e1007581. https://doi.org/10.1371/journal.ppat.1007581
Distributed under Open Access license CC BY 4.0, without modification.