Pål Trosvik

Convergent temporal dynamics of the human infant gut microbiota

Temporal dynamics of the human gut microbiota is of fundamental importance for the development of proper gut function and maturation of the immune system. Here we present a description of infant gut ecological dynamics using a combination of nonlinear data modeling and simulations of the early infant gut colonization processes. Principal component analysis of infant microbiota 16S rRNA gene microarray data showed that the main directions of variation were defined by three phylum-specific probes targeting Bacteroides, Proteobacteria and Firmicutes. Nonlinear regression analysis identified several dynamic interactions between these three phyla. Simulations of the early phylum-level colonization process showed the relatively rapid establishment of an equilibrium community after an unstable initial phase. In general, varying the initial composition of phyla in the simulations had little bearing on the final equilibrium. The dynamic interaction model was found to maintain its predictive ability for Proteobacteria and Firmicutes well into the simulation, whereas Bacteroides densities tended to be underestimated, possibly due to host top-down selection for Bacteroides. In accordance with our model, initial perturbation of the microbiota by different mode of delivery (vaginal and C-section) did not affect the later phylum composition in the infants investigated. Considering the predictive ability and convergence of our phylum-level model, we now propose that deterministic bacterial–bacterial interactions are more important for shaping the human infant gut microbiota than previously anticipated.

Web of ecological interactions in an experimental gut microbiota

The dynamics of all ecosystems are dictated by intrinsic, density-dependent mechanisms and by density-independent environmental forcing. In spite of the importance of the gastrointestinal microbiota in health and disease, the ecology of this system remains largely unknown. Here, we take an ecological approach to gut microbial community analysis, with statistical modelling of time series data from chemostats. This approach removes effects of host forcing, allowing us to describe a network of intrinsic interactions determining the dynamic structure of an experimental gut microbiota. Surprisingly, the main colonization pattern in this simplified model system resembled that of the human infant gut, suggesting a potentially important role of density-dependent interactions in the early gut microbiota. Knowledge of ecological structures in microbial systems may provide us with a means of controlling such systems by modifying the strength and nature of interactions among microbes and between the microbes and their environment.

Prevention of intestinal Campylobacter jejuni colonization in broilers by combinations of in‐feed organic acids

Aim:  We have tested the effect of various combinations of formic acid and sorbate on Campylobacter jejuni colonization in broiler chickens to reduce the colonization of this zoonotic pathogen in broiler chicken flocks.

Multivariate Analysis of Complex DNA Sequence Electropherograms for High-Throughput Quantitative Analysis of Mixed Microbial Populations

ABSTRACT High-throughput quantification of genetically coherent units (GCUs) is essential for deciphering population dynamics and species interactions within a community of microbes. Current techniques for microbial community analyses are, however, not suitable for this kind of high-throughput application. Here, we demonstrate the use of multivariate statistical analysis of complex DNA sequence electropherograms for the effective and accurate estimation of relative genotype abundance in cell samples from mixed microbial populations. The procedure is no more labor-intensive than standard automated DNA sequencing and provides a very effective means of quantitative data acquisition from experimental microbial communities. We present results with the Campylobacter jejuni strain-specific marker gene gltA, as well as the 16S rRNA gene, which is a universal marker across bacterial assemblages. The statistical models computed for these genes are applied to genetic data from two different experimental settings, namely, a chicken infection model and a multispecies anaerobic fermentation model, demonstrating collection of time series data from model bacterial communities. The method presented here is, however, applicable to any experimental scenario where the interest is quantification of GCUs in genetically heterogeneous DNA samples.

Co-Infection Dynamics of a Major Food-Borne Zoonotic Pathogen in Chicken

A major bottleneck in understanding zoonotic pathogens has been the analysis of pathogen co-infection dynamics. We have addressed this challenge using a novel direct sequencing approach for pathogen quantification in mixed infections. The major zoonotic food-borne pathogen Campylobacter jejuni, with an important reservoir in the gastrointestinal (GI) tract of chickens, was used as a model. We investigated the co-colonisation dynamics of seven C. jejuni strains in a chicken GI infection trial. The seven strains were isolated from an epidemiological study showing multiple strain infections at the farm level. We analysed time-series data, following the Campylobacter colonisation, as well as the dominant background flora of chickens. Data were collected from the infection at day 16 until the last sampling point at day 36. Chickens with two different background floras were studied, mature (treated with Broilact, which is a product consisting of bacteria from the intestinal flora of healthy hens) and spontaneous. The two treatments resulted in completely different background floras, yet similar Campylobacter colonisation patterns were detected in both groups. This suggests that it is the chicken host and not the background flora that is important in determining the Campylobacter colonisation pattern. Our results showed that mainly two of the seven C. jejuni strains dominated the Campylobacter flora in the chickens, with a shift of the dominating strain during the infection period. We propose a model in which multiple C. jejuni strains can colonise a single host, with the dominant strains being replaced as a consequence of strain-specific immune responses. This model represents a new understanding of C. jejuni epidemiology, with future implications for the development of novel intervention strategies.

Characterizing mixed microbial population dynamics using time-series analysis.

Due to a general shortage of temporal population data, dynamic structures in microbial communities remain largely unexplored. Knowledge of community dynamics is, however, essential for understanding the mechanisms by which microbes interact. Here, we have used a computational approach for quantification of bacteria in multispecies populations, generating data for time-series modeling. Moreover, we have used online FR-IR spectroscopy to monitor the main metabolic processes. The approach enabled us to provide a functional description of the parameters governing the population dynamics in a three-species model bacterial community, demonstrating density-dependent regulation, interspecies competition and even a case of cooperation between two species. Since the field of microbial ecology has yet to embrace many of the concepts and methods developed for the study of ecology of higher plants and animals, the realization that microbial systems can be analyzed within the same conceptual framework as other ecosystems is of fundamental importance.

Biotic interactions and temporal dynamics of the human gastrointestinal microbiota

The human gastrointestinal (GI) microbiota is important to human health and imbalances or shifts in the gut microbial community have been linked to many diseases. Most studies of the GI microbiota only capture snapshots of this dynamic community at one or a few time points. Although this is valuable in terms of providing knowledge of community composition and variability between individuals, it does not provide the foundation for going beyond descriptive studies and toward truly predictive ecological models. In order to achieve this goal, we need longitudinal data of appropriate temporal and taxonomic resolution, so that established time series analysis tools for identifying and quantifying putative interactions among community members can be used. Here, we present new analyses of existing data to illustrate the potential usefulness of this approach. We discuss challenges related to sampling and data processing, as well as analytical approaches and considerations for future studies of the GI microbiota and other complex microbial systems.

Context-Dependent Competition in a Model Gut Bacterial Community

Understanding the ecological processes that generate complex community structures may provide insight into the establishment and maintenance of a normal microbial community in the human gastrointestinal tract, yet very little is known about how biotic interactions influence community dynamics in this system. Here, we use natural strains of Escherichia coli and a simplified model microbiota to demonstrate that the colonization process on the strain level can be context dependent, in the sense that the outcome of intra-specific competition may be determined by the composition of the background community. These results are consistent with previous models for competition between organisms where one competitor has adapted to low resource environments whereas the other is optimized for rapid reproduction when resources are abundant. The genomic profiles of E. coli strains representing these differing ecological strategies provide clues for deciphering the genetic underpinnings of niche adaptation within a single species. Our findings extend the role of ecological theory in understanding microbial systems and the conceptual toolbox for describing microbial community dynamics. There are few, if any, concrete examples of context-dependent competition on a single trophic level. However, this phenomenon can have potentially dramatic effects on which bacteria will successfully establish and persist in the gastrointestinal system, and the principle should be equally applicable to other microbial ecosystems.

Comparisons of infant Escherichia coli isolates link genomic profiles with adaptation to the ecological niche.

BackgroundDespite being one of the most intensely studied model organisms, many questions still remain about the evolutionary biology and ecology of Escherichia coli. An important step toward achieving a more complete understanding of E.coli biology entails elucidating relationships between gene content and adaptation to the ecological niche.ResultsHere, we present genome comparisons of 16 E.coli strains that represent commensals and pathogens isolated from infants during a specific time period in Trondheim, Norway. Using differential gene content, we characterized enrichment profiles of the collection of strains relating to phylogeny, early vs. late colonization, pathogenicity and growth rate. We found clear gene content distinctions relating to the various grouping criteria. We also found that different categories of strains use different genetic elements for similar biological processes. The sequenced genomes included two pairs of strains where each pair was isolated from the same infant at different time points. One pair, in which the strains were isolated four months apart, showed maintenance of an early colonizer genome profile but also gene content and codon usage changes toward the late colonizer profile. Lastly, we placed our sequenced isolates into a broader genomic context by comparing them with 25 published E.coli genomes that represent a variety of pathotypes and commensal strains. This analysis demonstrated the importance of geography in shaping strain level gene content profiles.ConclusionsOur results indicate a general pattern where alternative genetic pathways lead toward a consistent ecological role for E.coli as a species. Within this framework however, we saw selection shaping the coding repertoire of E.coli strains toward distinct ecotypes with different phenotypic properties.

Large-scale genetic structuring of a widely distributed carnivore--the Eurasian lynx (Lynx lynx).

Over the last decades the phylogeography and genetic structure of a multitude of species inhabiting Europe and North America have been described. The flora and fauna of the vast landmasses of north-eastern Eurasia are still largely unexplored in this respect. The Eurasian lynx is a large felid that is relatively abundant over much of the Russian sub-continent and the adjoining countries. Analyzing 148 museum specimens collected throughout its range over the last 150 years we have described the large-scale genetic structuring in this highly mobile species. We have investigated the spatial genetic patterns using mitochondrial DNA sequences (D-loop and cytochrome b) and 11 microsatellite loci, and describe three phylogenetic clades and a clear structuring along an east-west gradient. The most likely scenario is that the contemporary Eurasian lynx populations originated in central Asia and that parts of Europe were inhabited by lynx during the Pleistocene. After the Last Glacial Maximum (LGM) range expansions lead to colonization of north-western Siberia and Scandinavia from the Caucasus and north-eastern Siberia from a refugium further east. No evidence of a Berinigan refugium could be detected in our data. We observed restricted gene flow and suggest that future studies of the Eurasian lynx explore to what extent the contemporary population structure may be explained by ecological variables.