Metagenomic SNV-Based Strain Tracking
We leverage deep shotgun metagenomics to ensure sufficient coverage for variant calling. By aligning post-administration reads against the reference genome of your administered strain, our pipelines identify unique Single Nucleotide Variants (SNVs). We compare these signatures against pre-treatment baseline samples to differentiate the administered strain from endogenous background strains, enabling the estimation of engraftment events and relative strain dominance over time.
Long-Read Strain Resolution
When strains exhibit high genomic similarity or contain extensive mobile genetic elements, SNVs alone may be insufficient. Creative Biolabs utilizes long-read sequencing technologies (such as PacBio HiFi or Oxford Nanopore) to capture complete structural variants, large insertions/deletions, and intact operons. This allows us to characterize strains based on larger genomic architecture, offering a robust layer of evidence for strain-level colonization assessment, especially in complex competitive environments in vivo.
Pre- and Post-Dosing Comparative Analysis
A fundamental component of our service is the robust comparison of longitudinal sample sets. By analyzing samples taken before treatment, during the dosing regimen, and across multiple follow-up time points, we establish the baseline microbial landscape. We then track the specific introduction, peak abundance, and gradual decline or persistence of the LBP, helping inform dosing intervals and evaluating the therapeutic window.
Engraftment Likelihood and Persistence Assessment
Where study design and data quality permit, we can model engraftment likelihood, persistence trajectories, and time-to-loss patterns across cohorts. We assess persistence kinetics to help inform dosing frequency and clinical trial design, estimating whether colonization is transient or sustained.
Competitive Microbiome Dynamics
LBPs interact within a dense, adapted ecosystem. Concurrently with tracking your strain, we monitor the dynamic shifts in the surrounding microbiome. We identify which endogenous taxa are displaced or which taxa co-expand synergistically with your therapy, providing evidence-based ecological insights into the potential mechanism of action.
