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Thorsen, J.

Publications and source records attributed to Thorsen, J..

9 recordsLinked to original sources

Evolutionary history and microbial cross-feeding shape lifestyle-stratified dominance of Bifidobacterium longum subspecies in infants

Bifidobacterium longum (Bl.) is a key early-life gut symbiont, yet its evolutionary origin and mechanisms underlying the global biogeographic distribution of its subspecies remain poorly resolved. Here, we compiled a global genomic atlas of >7,000 MAGs/genomes from infants, domesticated animals, non-human primates, and ancient humans. High-resolution phylogenomic and functional analyses expanded infant-associated subspecies to five. Compared with non-human primates, B. longum was more prevalent in domesticated animals and ancient humans dating from 150 to 1,500 years ago. Moreover, human- and livestock-derived lineages from the same geographic regions clustered together, suggesting potential host-associated transmission. Ecologically, Bl. infantis and Bl. longum predominated in non-Western and Western infants, respectively, independent of breastfeeding, delivery mode, or antibiotic exposure. Instead, their distribution was associated with co-occurring microbes and HMO-driven cross-feeding interactions. These findings explain subspecies differentiation in the gut microbiota of Western and non-Western infants and provide a framework for community-mediated interventions in early life.

microbiology↗

Extracting host-specific developmental signatures from longitudinal microbiome data

Longitudinal microbiome studies provide critical insights into microbial community dynamics and their relation to host health. Tensor decompositions offer a powerful framework for the unsupervised analysis of such data, yielding interpretable low-dimensional temporal patterns. However, existing approaches based on the CANDECOMP/PARAFAC (CP) model assume common temporal dynamics for all subjects and therefore cannot capture subject-specific trajectories. To address this limitation, we introduce a novel analytical framework based on PARAFAC2 to explicitly model subject-specific variations, such as shifts and delays in temporal patterns. Through systematic comparisons on simulated and real-world datasets--including studies of infant gut maturation and dietary interventions--we demonstrate that PARAFAC2 outperforms CP in capturing subject-specific temporal trajectories, and enables the discovery of biologically relevant patterns that are overlooked by CP. Furthermore, we introduce replicability as a robust criterion for selecting the number of components and demonstrate that the extracted patterns are replicable. Author summaryLongitudinal microbiome datasets are complex, consisting of repeated high-dimensional compositions that track changes in microbial abundance across individuals over time. While tensor decompositions are powerful tools for unraveling structure in these data, standard models like CANDECOMP/PARAFAC (CP) impose a critical limitation: they assume that temporal dynamics are identical across all individuals. This assumption often fails to capture the heterogeneity of biological processes, such as the varying pace of gut microbiome maturation or distinct individual responses to dietary changes. In this work, we introduce a novel analytical framework leveraging the PARAFAC2 model to overcome these constraints. By explicitly modeling subject-specific temporal variations, our PARAFAC2-based approach allows for the detection of individual time shifts and delays. We validated this framework using both simulation and real-world cohorts, demonstrating its ability to recover personalized trajectories that CP obscures. Additionally, we implemented a robust criterion to guide model selection, ensuring that the discovered patterns are replicable.

bioinformatics↗

MAGinator enables strain-level quantification of de novo MAGs

MotivationMetagenomic sequencing has provided great advantages in the characterization of microbiomes, but currently available analysis tools lack the ability to combine strain-level taxonomic resolution and abundance estimation with functional profiling of assembled genomes. In order to define the microbiome and its associations with human health, improved tools are needed to enable comprehensive understanding of the microbial composition and elucidation of the phylogenetic and functional relationships between the microbes. ResultsHere, we present MAGinator, a freely available tool, tailored for the profiling of shotgun metagenomics datasets. MAGinator provides de novo identification of subspecies-level microbes and accurate abundance estimates of metagenome-assembled genomes (MAGs). MAGinator utilises the information from both gene- and contig-based methods yielding insight into both taxonomic profiles and the origin of genes as well as genetic content, used for inference of functional content of each sample by host organism. Additionally, MAGinator facilitates the reconstruction of phylogenetic relationships between the MAGs, providing a framework to identify clade-level differences within subspecies MAGs. Availability and implementationMAGinator is available as a Python module at https://github.com/Russel88/MAGinator ContactTrine Zachariasen, trine_zachariasen@hotmail.com

bioinformatics↗

The influence of early life exposures on the infant gut virome

Large cohort studies have contributed significantly to our understanding of the factors that influence the development of the bacterial component of the gut microbiome (GM) during the first years of life. However, the factors that shape the colonization by other important GM members such as the viral fraction remain more elusive. Most gut viruses are bacteriophages (phages), i.e., viruses attacking bacteria in a host specific manner, and to a lesser extent, but also widely present, eukaryotic viruses, including viruses attacking human cells. Here, we utilize the deeply phenotyped COPSAC2010 birth cohort consisting of 700 infants to investigate how social, pre-, peri- and postnatal factors may influence the gut virome composition at one year of age, where fecal virome data was available from 645 infants. Among the different exposures studied, having older siblings and living in an urban vs. rural area had the strongest impact on gut virome composition. Differential abundance analysis from a total of 16,118 viral operational taxonomic units (vOTUs) (mainly phages, but also 6.1% eukaryotic viruses) identified 2,105 vOTUs varying with environmental exposures, of which 5.9% were eukaryotic viruses and the rest was phages. Bacterial hosts for these phages were mainly predicted to be within the Bacteroidaceae, Prevotellaceae, and Ruminococcaceae families, as determined by CRISPR spacer matches. Spearman correlation coefficients indicated strong co-abundance trends of vOTUs and their targeted bacterial host, which underlined the predicted phage-host connections. Further, our findings show that some gut viruses encode important metabolic functions and how the abundance of genes encoding these functions is influenced by environmental exposures. Genes that were significantly associated with early life exposures were found in a total of 42 vOTUs. 18 of these vOTUs had their life styles predicted, with 17 of them having a temperate lifestyle. These 42 vOTUs carried genes coding for enzymes involved in alanine, aspartate and glutamate metabolism, glycolysis-gluconeogenesis, as well as fatty acid biosynthesis. The latter implies that these phages could be involved in the utilization and degradation of major dietary components and affect infant health by influencing the metabolic capacity of their bacterial host. Given the importance of the GM in early life for maturation of the immune system and maintenance of metabolic health, these findings provide a valuable source of information for understanding early life factors that predispose for autoimmune and metabolic disorders.

microbiology↗

Co-localization of antibiotic resistance genes is widespread in the infant gut microbiome and associates with an immature gut microbial composition

Even in the absence of antibiotic exposure, the gut microbiome of infants has been shown to contain numerous antibiotic resistance genes (ARGs), but the mechanism for this remains unclear. In environmental bacteria, the selective advantage of ARGs can be increased through co-localization with genes such as other ARGs, biocide resistance genes, metal resistance genes, and virulence genes. However, this phenomenon is unknown from the human gut microbiome during early life despite frequent exposures to biocides and metals from an early age. Here, we conducted a comprehensive analysis of genetic co-localization of resistance genes in a cohort of 662 Danish children and examined the association between such co-localization and environmental factors as well as gut microbial maturation. Our study showed that co-localization of ARGs with other resistance and virulence genes is common in the early gut microbiome and is associated with gut bacteria that are indicative of low maturity, especially E. coli. The most common forms of co-localization involved tetracycline and fluoroquinolone resistance genes located near other ARGs, and, on plasmids, co-localization predominantly occurred in the form of class 1 integrons. Antibiotic use caused a short-term increase in mobile ARGs, while non-mobile ARGs showed no significant change. Finally, we found that a high abundance of virulence genes was associated with low gut microbial maturity and that virulence genes showed even higher potential for mobility than ARGs. Our study highlights important constraints that need to be considered when developing strategies to combat ARG dissemination.

microbiology↗

Manual resolution of virome dark matter uncovers hundreds of viral families in the infant gut

The gut microbiome (GM) is shaped through infancy and plays a major role in determining susceptibility to chronic inflammatory diseases later in life. Bacteriophages (phages) are known to modulate bacterial populations in numerous ecosystems, including the gut. However, virome data is difficult to analyse because it mostly consists of unknown viruses, i.e. viral dark matter. Here, we manually resolved the viral dark matter in the largest human virome study published to date. Fecal viromes from a cohort of 647 infants at 1 year of age were deeply sequenced and analysed through successive rounds of clustering and curation. We uncovered more than ten thousand viral species distributed over 248 viral families falling within 17 viral order-level clades. Most of the defined viral families and orders were novel and belonged to the Caudoviricetes viral class. Bacterial hosts were predicted for 79% of the viral species using CRISPR spacers, including those in metagenomes from the same fecal samples. While Bacteroides-infecting Crassphages were present, novel viral families were more predominant, including phages infecting Clostridiales and Bifidobacterium. Phage lifestyles were determined for more than three thousand caudoviral species. Lifestyles were homogeneous at the family level for 149 Caudoviricetes families, including 32 families that were found to be virulent, while 117 were temperate. Virulent phage families were more abundant but temperate ones were more diverse and widespread. Together, the viral families found in this study represent a major expansion of existing bacteriophage taxonomy.

microbiology↗

Prophages in the infant gut are largely induced, and may be functionally relevant to their hosts.

BackgroundBacteriophages are the most abundant biological entity on the planet, and are key components of any ecosystem they are present in. The gut virome is increasingly being implicated in disease states although these studies largely focus on lytic phages in adults. Here we identify prophages from a large infant cohort and investigate their potential functions. ResultsWe identified 10645 vOTUs from 662 metagenomes. No core virome was found: the most prevalent vOTU was identified in 70% of the samples. The most abundant and prevalent group of phages are a novel group closely related to Bacteroides phage Hanky p00. Functional annotation of this group revealed the presence of genes in the dDTP-L-rhamnose pathway, possibly involved in the production of capsular polysaccharides. We also found an abundance of diversity generating retroelements in the phages. Additionally, paired virome data allowed us to show that the majority of prophages are induced in at least one sample and that this is not affected by the use of antibiotics in the 4 weeks prior to sampling. ConclusionsProphages in the infant gut are largely unique to the individual and not shared. Most of them appear to be induced and so may be key drivers in shaping the bacterial microbiome. The most abundant group of phages are novel, and possess elements that may allow them to maintain differentially susceptible subpopulations of their host bacterium; whilst also containing diversity generating retroelements that could expand their host range. Prophages are important components of the infant gut that may have far reaching influences on the composition and function of the microbiome.

microbiology↗

Stability of the vaginal microbiota during pregnancy and its importance for early infant colonization

Early life microbiota has been linked to the development of chronic inflammatory diseases. It has been hypothesized that maternal vaginal microbiota is an important initial seeding source and therefore can have lifelong effects on disease risk. To understand maternal vaginal microbiotas role in seeding the childs microbiota and the extent of delivery mode-dependent transmission, we studied 700 mother-child dyads from the COPSAC2010 cohort. The maternal vaginal microbiota was evaluated in the third trimester and compared with the childrens fecal and airway microbiota. The vaginal samples displayed known stable community state types and only 1:6 changed over time. Only one OTU was significantly transferred to childrens fecal compartment, but an inflated number had positive transfer odds. A few taxonomic families showed early transfer enrichment to vaginally-born children, indicating vertical transfer, while half of the observed transfer effects were delivery mode independent enrichment with attenuating strength over time, indicating a common reservoir.

bioinformatics↗

DAtest: a framework for choosing differential abundance or expression method

DAtest is an R package for directly comparing different statistical methods for differential abundance and expression analysis on a dataset of interest; be it data from RNA-seq, proteomics, metabolomics or a microbial marker-gene survey. A myriad of statistical methods exists for conducting these analyses, and with this tool we give the analyst an empirical foundation for choosing a method suitable for a specific dataset. The package supports categorical and quantitative variables, paired/block experimental designs, and the inclusion of covariates. It is freely available at GitHub: https://github.com/Russel88/DAtest along with detailed instructions.

bioinformatics↗