258: Correcting GC bias in metagenomes

Holcik L et al., Nature Communications, doi:10.1038/s41467-025-65530-4 - GuaCAMOLE is an alignment-free algorithm that estimates and removes genomic GC-content-dependent sequencing bias to produce more accurate species abundance estimates from single metagenomic samples. Key terms: GC bias, metagenomics, species abundance, GuaCAMOLE, colorectal cancer. Study Highlights:GuaCAMOLE combines Kraken2/Bracken read assignment with per-taxon GC binning and a regularized least-squares estimator to infer GC-dependent sequencing efficiencies and bias-corrected abundances from a single sample. On simulations and mock communities across 28 library protocols it produced near-unbiased estimates and outperformed Bracken and MetaPhlAn4 when GC bias was present. Application to 3,435 gut microbiomes from 33 colorectal cancer studies revealed four distinct protocol-specific GC-bias shapes and systematic underestimation of GC-poor taxa. The tool also filters false-positive taxa by comparing observed and expected GC distributions and can apply inferred efficiencies to correct other tools' outputs. Conclusion:Per-sample GC-bias correction with GuaCAMOLE improves accuracy and comparability of metagenomic species abundance estimates across diverse protocols Music:Enjoy the music based on this article at the end of the episode. Article title:Genomic GC bias correction improves species abundance estimation from metagenomic data First author:Holcik L Journal:Nature Communications, doi:10.1038/s41467-025-65530-4 DOI:10.1038/s41467-025-65530-4 Reference:Holcik L., von Haeseler A., Pflug F. G. Genomic GC bias correction improves species abundance estimation from metagenomic data. Nature Communications. 2025;16:10523. https://doi.org/10.1038/s41467-025-65530-4 License:This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/ Support:Base by Base – Stripe donations: https://donate.stripe.com/7sY4gz71B2sN3RWac5gEg00 Official website https://basebybase.com On PaperCast Base by Base you’ll discover the latest in genomics, functional genomics, structural genomics, and proteomics. Episode link: https://basebybase.com/episodes/gc-bias-correction-metagenomics QC:This episode was checked against the original article PDF and publication metadata for the episode release published on 2026-01-13. QC Scope:- article metadata and core scientific claims from the narration- excludes analogies, intro/outro, and music- transcript coverage: Audited the transcript content for core scientific claims and results described in the article, including GC bias problems in metagenomics, the GuaCAMOLE algorithm, GC-bin strategy and QC, benchmarking results (simulated and mock data), CRC meta-analysis findings, and limitations/future work.- transcript topics: GC bias in metagenomic sequencing; GuaCAMOLE algorithm overview and alignment-free design; GC-bin read counting and abundance estimation; False-positive taxon filtering and QC; Benchmarking on simulated data and mock communities; Four GC-bias shapes across colorectal cancer gut microbiomes QC Summary:- factual score: 10/10- metadata score: 10/10- supported core claims: 8- claims flagged for review: 0- metadata checks passed: 4- metadata issues found: 0 Metadata Audited:- article_doi- article_title- article_journal- license Factual Items Audited:- GC content affects sequencing efficiency and biases vary by protocol- GuaCAMOLE is alignment-free and uses Kraken2/Bracken for initial taxon assignment with GC-bin stratification- Abundances and GC-dependent sequencing efficiencies are solved simultaneously via lea...