View all of my publications on Google Scholar.

Highlights

2024

Geographical variation in the incidence of colorectal cancer and urinary tract cancer is associated with population exposure to colibactin-producing Escherichia coli

Tommi Mäklin, Aurora Taira, Sergio Arredondo-Alonso, Yan Shao, Michael R Stratton, Trevor D Lawley, Lauri A Aaltonen, and Jukka Corander

Lancet Microbe, 2024

We show that the geographical variation in population prevalence of colibactin-producing E. coli lineages ST95 and ST73 in healthy carriage largely explains the variation in colorectal cancer incidence globally. Since ST95 and ST73 are are also major causes of UTIs, a similar link might also exist in some urinary tract cancers via exposure to colibactin during infection. Our study provides a potential vaccine target for reducing the burden from colibactin associated cancers by pinpointing the exact E. coli lineages responsible in humans.

Deep sequencing of Escherichia coli exposes colonisation diversity and impact of antibiotics in Punjab, Pakistan

Tamim Khawaja°, Tommi Mäklin°, Teemu Kallonen°, Rebecca A Gladstone, Anna K Pöntinen, Sointu Mero, Harry A Thorpe, Ørjan Samuelsen, Julian Parkhill, Mateen Izhar, Waheed M Akhtar, Jukka Corander, and Anu Kantele
° joint first authors

Nature Communications, 2024

We investigated the impact of antimicrobial usage on the diversity of E. coli strain carriage in a cross-sectional cohort from the Punjab province of Pakistan. Our results highlight notable differences in E. coli competition and carriage compared to genomic cohorts from western and northen Europe. In particular the European-endemic non-MDR clinical strains ST73 and ST95 are nearly completely absent in Pakistan, and the prevalence of the MDR clinical strains ST69 and ST131 is highly reduced and modulated by recent antibiotic intake.

2023

Themisto: a scalable colored k-mer index for sensitive pseudoalignment against hundreds of thousands of bacterial genomes

Jarno N Alanko, Jaakko Vuohtoniemi, Tommi Mäklin, and Simon Puglisi

Bioinformatics, 2023

Themisto is a method for both building and querying colored de Bruijn graphs that was originally introduced in my mGEMS paper in 2021. The 2023 version of Themisto implements an order of magnitude faster build and query algorithms than the state-of-the-art at the time, and introduces a new hybrid method of pseudoalignment that combines ideas from existing algorithms.

2022

Strong pathogen competition in neonatal gut colonisation

Tommi Mäklin, Harry A Thorpe, Anna K Pöntinen, Rebecca A Gladstone, Yan Shao, Maiju Pesonen, Alan McNally, Pål J Johnsen, Ørjan Samuelsen, Trevor D Lawley, Antti Honkela, and Jukka Corander

Nature Communications, 2022

We applied the mSWEEP and mGEMS methods to study colonization dynamics of Escherichia coli, Klebsiella pneumoniae, and Enterococcus faecalis at the lineage-level. Our results highlighted a strong competitive advantage for the first strain to colonize the gut of a newborn but found no selection for hospital-adapted or disease-associated lineages. For more information, please see the press release by the Wellcome Sanger Institute.

2021

Bacterial genomic epidemiology with mixed samples

Tommi Mäklin, Teemu Kallonen, Jarno N Alanko, Ørjan Samuelsen, Kristin Hegstad, Veli Mäkinen, Jukka Corander, Eva Heinz, and Antti Honkela

Microbial Genomics, 2021

This article introduces the mGEMS pipeline for deconvoluting short-read sequencing data from samples containing multiple lineages of the same bacterial species. mGEMS assigns each read to one or more reference lineage(s) and produces an assignment of the reads that can replace isolate sequencing data in standard epidemiological analyses applied to metagenomic data. mGEMS has been used in study of within-host diversity of Streptococcus pneumoniae and Enterobacteriaceae colonization dynamics.

High-resolution sweep metagenomics using fast probabilistic inference

Tommi Mäklin, Teemu Kallonen, Sophia David, Christine J Boinett, Ben Pascoe, Guillaume Méric, David M Aanensen, Edward J Feil, Stephen Baker, Julian Parkhill, Samuel K Sheppard, Jukka Corander, and Antti Honkela

Wellcome Open Research, 2021

This article describes the mSWEEP method for estimating the relative abundances of lineages of a bacterial species in a set of short-read sequencing data. mSWEEP is closely tied with the mGEMS tool and the two are typically used together.