Biology subjects

Stokholm, J.

Publications and source records attributed to Stokholm, J..

11 recordsLinked to original sources

bioRxiv2026

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↗

bioRxiv2025

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↗

bioRxiv2025

Harnessing systemic glycolysis-TCA cycle axis to boost the host defense against newborn infection

Energy metabolism and immune response are tightly connected, but it is poorly understood how this interplay is regulated in early life to dictate host defense strategy, infection risks and severity. This interplay is particularly relevant for preterm, low birthweight or otherwise immunocompromised infants, who have poor metabolic control and increased risks of sepsis. Here, we utilized data from the COPSAC2010 cohort with 700 mother-child pairs and showed that plasma levels of TCA cycle metabolites in early life were associated with reduced childhood risk of bacterial infection and an attenuated systemic inflammatory response. Next, we explored how two distinct nutritional strategies, which were aimed at boosting TCA cycle activity instead of glycolysis, impacted neonatal host defense against a serious bloodstream infection in preterm piglets. Substituting galactose for glucose in parenteral nutrition enhanced disease tolerance in early phase of infection and overall glucose homeostasis, improving survival. Further, combining glucose restriction with supplementation of glucogenic amino acids conferred glycemic control and completely prevented sepsis and abnormal changes of organ injury markers. Mechanistically, this intervention enhanced both disease resistance and tolerance, accompanied by metabolic rewiring from glycolysis towards gluconeogenesis, TCA cycle activity and oxidative phosphorylation. Thus, optimized nutritional strategies controlling the interplay of energy metabolism and host defense may be lifesaving for infected infants. In briefNewborns rely on two distinct defense strategies to combat infections in early life. Disease resistance, fueled by aerobic glycolysis, seeks to actively eliminate microorganisms while disease tolerance, fueled by mitochondrial oxidative phosphorylation, seeks to reduce collateral tissue damage during infections. We found that in healthy human newborns, increased plasma levels of metabolites from the tricarboxylic acid (TCA) cycle were associated with lower burden of childhood infections and reduced pro-inflammatory status. In a newborn animal model of bloodstream infection, nutritional strategies boosting systemic TCA cycle activity, while reducing aerobic glycolysis, enhanced both host disease tolerance and resistance, thereby improving survival. These findings could pave a path for improved infection management in human newborns. HighlightsO_LIIn healthy children, higher plasma levels of TCA cycle metabolites are associated with lower infection risks and systemic inflammation. C_LIO_LIIn a neonatal infection model, the supply of galactose, instead of glucose, improves host glucose homeostasis and TCA cycle activity, improving disease tolerance and survival. C_LIO_LIA combination of glucose restriction and glucogenic amino acid supply also improves TCA cycle activity, enhancing both disease resistance and tolerance and completely preventing lethal sepsis. C_LI

immunology↗

bioRxiv2023

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↗

bioRxiv2023

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↗

bioRxiv2023

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↗

bioRxiv2021

Genome binning of viral entities from bulk metagenomics data

Despite the accelerating number of uncultivated virus sequences discovered in metagenomics and their apparent importance for health and disease, the human gut virome and its interactions with bacteria in the gastrointestinal are not well understood. In addition, a paucity of whole-virome datasets from subjects with gastrointestinal diseases is preventing a deeper understanding of the viromes role in disease and in gastrointestinal ecology as a whole. By combining a deep-learning based metagenomics binning algorithm with paired metagenome and metavirome datasets we developed the Phages from Metagenomics Binning (PHAMB) approach for binning thousands of viral genomes directly from bulk metagenomics data. Simultaneously our methodology enables clustering of viral genomes into accurate taxonomic viral populations. We applied this methodology on the Human Microbiome Project 2 (HMP2) cohort and recovered 6,077 HQ genomes from 1,024 viral populations and explored viral-host interactions. We show that binning can be advantageously applied to existing and future metagenomes to illuminate viral ecological dynamics with other microbiome constituents.

genomics↗

bioRxiv2021

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↗

bioRxiv2021

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↗

bioRxiv2020

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↗

bioRxiv2020

Kernel integration by Graphical LASSO

Integration of unstructured and very diverse data is often required for a deeper understanding of complex biological systems. In order to uncover communalities between heterogeneous data, the data is often harmonized by constructing a kernel and numerical integration is performed. In this study we propose a method for data integration in the framework of an undirected graphical model, where the nodes represent individual data sources of varying nature in terms of complexity and underlying distribution, and where the edges represent the partial correlation between two blocks of data. We propose a modified GLASSO for estimation of the graph, with a combination of cross-validation and extended Bayes Information Criterion for sparsity tuning. Furthermore, hierarchical clustering on the weighted consensus kernels from a fixed network is used to partitioning the samples into different classes. Simulations show increasing ability to uncover true edges with increasing sample size and signal to noise. Likewise, identification of non existing edges towards disconnected nodes is feasible. The framework is demonstrated for integration of longitudinal symptom burden data from the 2nd and 3rd year of life with 21 diseases precursors as well as the development of asthma and eczema at the age of 6 years from 403 children from the COPSAC2010 mother-child cohort, suggesting that maternal predisposition as well as being born preterm indirectly lead to higher risk of asthma via increased respiratory symptom burden.

bioinformatics↗