# Improved strain-level metagenome assembly for modern long reads

Riccardo Vicedomini, Rayan Chikhi

► To cite this version:

Riccardo Vicedomini, Rayan Chikhi. Improved strain-level metagenome assembly for modern long reads. SeqBIM 2025 - Journées sur les Séquences en Bioinformatique, Informatique et Mathématiques, Nov 2025, Nantes, France. hal-05424057

HAL Id: hal-05424057

https://hal.science/hal-05424057v1

Submitted on 18 Dec 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
Abstract

# Improved strain-level metagenome assembly for modern long reads

Riccardo Vicedomini¹,*, Rayan Chikhi²

¹Univ Rennes, CNRS, Inria, IRISA - UMR 6074, Rennes, France

²Institut Pasteur, Université Paris Cité, CNRS UMR 3525, Paris, France

*Corresponding author: riccardo.vicedomini@irisa.fr

## Abstract

Advances in long-read sequencing technologies from PacBio and Oxford Nanopore Technologies (ONT) have paved the way for the development of methods that significantly improve the quality of metagenome assemblies, particularly with the modern PacBio HiFi and ONT R10.4 technologies. Nevertheless, standard metagenome assemblers [1, 2, 3, 4, 5], while providing high-quality species-level reconstructions, are often unable to distinguish and accurately reconstruct genomes of highly similar bacterial strains (i.e., with > 99% sequence identity). Moreover, several long-read-based methods have been recently proposed to address the challenge of reconstructing bacterial strain genomes (or haplotypes) from metagenomic data [6, 7, 8].

In this work we show that existing metagenome assembly tools either produce highly fragmented assemblies or generate longer contigs at the expense of numerous strain-level misassemblies. We also present Strainberry2, an improved version of Strainberry [6], specifically designed for PacBio HiFi and ONT R10.4 sequencing data, aimed at providing a better balance between contiguity and strain-level accuracy. As is common for strain-separation methods, Strainberry2 takes as input a strain-oblivious metagenome assembly (i.e., a species-level assembly) together with a set of accurate long reads. It produces an augmented assembly that recovers strain diversity – absent in the input assembly – by generating strain-specific sequences. Strainberry2 distinguishes itself from competing methods by introducing an upstream dereplication step and a novel strain-phasing algorithm. The dereplication step is aimed at reducing ambiguous read mappings, which are critical for reliably detecting single-nucleotide and structural variants. The strain-phasing algorithm uses an iterative approach that leverages an implicit variant graph constructed from co-occurring single-nucleotide variants in the reads. At each iteration, candidate bacterial haplotypes are defined, while retaining only those supported by a sufficient number of reads.

We ran Strainberry2 and state-of-the-art standard and strain-aware metagenome assemblers on 64 simulated datasets from [7], covering different sequencing technologies, varying numbers of strains (up to 5), multiple bacterial species, and either uniform or staggered strain abundances. We further ran these tools with real sequencing data on the ZymoBIOMICS Gut Microbiome Standard mock community, which includes five highly similar strains of *Escherichia coli* and for which both PacBio HiFi and ONT R10.4 reads are publicly available. The resulting assemblies
were evaluated with MetaQUAST [9]. To overcome the limitations of MetaQUAST in assessing assemblies against highly similar reference genomes, we complemented the evaluation with a k-mer-based approach. In particular, we adapted several of the metrics introduced in [10] to the strain-aware context to provide a more fine-grained evaluation of completeness, duplication, and strain-switch errors.

On the 64 simulated datasets, Strainberry2 achieved, on average, comparable or significantly better results across all qualitative metrics (e.g., 2-7× fewer misassemblies according to MetaQUAST and at least 10× fewer k-mer-based strain-switch errors). On the real-data mock community, Strainberry2 showed the same trend, particularly with ONT R10.4 data. With PacBio HiFi reads, Strainberry2 delivered results on par with the state-of-the-art hifiasm-meta, providing slightly higher accuracy across qualitative metrics. While hifiasm-meta reached greater contiguity (4× higher NGA50), this came at the cost of 20% more duplicated sequences, highlighting the more balanced trade-off achieved by Strainberry2.

Strainberry2 is an open-source software, implemented in Rust, and publicly available at https://github.com/rvicedomini/rust-strainberry.

## References

[1] Mikhail Kolmogorov et al. metaFlye: scalable long-read metagenome assembly using repeat graphs. *Nature methods*, 17(11):1103–1110, 2020.

[2] Xiaowen Feng et al. Metagenome assembly of high-fidelity long reads with hifiasm-meta. *Nature methods*, 19(6):671–674, 2022.

[3] Gaëtan Benoit et al. High-quality metagenome assembly from long accurate reads with metaMDBG. *Nature Biotechnology*, 42(9):1378–1383, 2024.

[4] Gaëtan Benoit et al. High-quality metagenome assembly from nanopore reads with nanoMDBG. *bioRxiv*, pages 2025–04, 2025.

[5] Jim Shaw et al. High-resolution metagenome assembly for modern long reads with myloasm. *bioRxiv*, pages 2025–09, 2025.

[6] Riccardo Vicedomini et al. Strainberry: automated strain separation in low-complexity metagenomes using long reads. *Nature Communications*, 12(1):4485, 2021.

[7] Ekaterina Kazantseva et al. Strainy: phasing and assembly of strain haplotypes from long-read metagenome sequencing. *Nature Methods*, 21(11):2034–2043, 2024.

[8] Roland Faure et al. HairSplitter: haplotype assembly from long, noisy reads. *Peer Community Journal*, 4, 2024.

[9] Alla Mikheenko, Vladislav Saveliev, and Alexey Gurevich. MetaQUAST: evaluation of metagenome assemblies. *Bioinformatics*, 32(7):1088–1090, 2016.

[10] Wenjuan Yu et al. Comprehensive assessment of 11 de novo HiFi assemblers on complex eukaryotic genomes and metagenomes. *Genome Research*, 34(2):326–340, 2024.