Abstracts
Rosalind J. Allen - FSU Jena - Theoretical Microbial Ecology
Modelling microbial growth: from cells to populations to ecosystems
An overview of the work of theoretical microbial ecology group
Dennis De Bakker - Leibniz Institute on Aging FLI Jena - Evolution and ecology of aging
Microbiota transplantation can mitigate age-related brain inflammation and functional decline in a model of spontaneous Alzheimer’s-like pathology
Neurodegenerative diseases such as Alzheimer’s disease are correlated with an imbalance of the microbial community of the gut. However, whether the gut microbiota plays a causal role in the etiology of neurodegenerative diseases remains to be elucidated. Here, we investigate whether microbiota transfer can mitigate age-related phenotypes of Alzheimers-like pathology. To address the aim of this study, we employ the turquoise killifish (Nothobranchius furzeri). Turquoise killifish are naturally short-lived vertebrates which spontaneously develop age-related changes in their gut microbiota which shares characteristics with those observed in Alzheimer’s patients. In addition, turquoise killifish have been reported to spontaneously develop key phenotypes described in human neurodegenerative diseases, such as neuronal degeneration, protein aggregation, microgliosis, astrogliosis and learning capacity. First, we successfully validated the spontaneous and age-related onset of neuronal degeneration, protein aggregation, microgliosis, astrogliosis and learning capacity. Furthermore, we investigated the accumulation of amyloid beta (Aβ), a key hallmark of Alzheimer’s disease. We found that pyroglutamated-Aβ, a highly toxic and aggregation-prone form of Aβ, accumulated throughout the killifish brain which directly correlated with poor learning performance. Heterochronic microbiome transplant in killifish extends lifespan. However, we have no insights as to whether it reduces organ-specific inflammation. Our hypothesis is that reducing brain-specific inflammation by targeting the gut microbiota could mitigate Alzheimer’s-like pathology. To test our hypothesis, we transplanted gut microbiota from young to aged turquoise killifish and observed that the fish which received young microbiota display significantly less microgliosis and astrogliosis, indicating reduced inflammation. Furthermore, although no differences were detected in the number of actively degenerating neurons at 6 months of age, we did observe a mitigation of the age-related decline in learning performance. Together, these findings indicate that microbiota transplantation can reduce age-related brain inflammation and mitigates functional decline in a model of spontaneous Alzheimer’s-like pathology.
Hilje Doekers - Wageningen University & Research - Plant Sciences - Laboratory of Genetics
Modelling microbial evolution in spatially structured environments
In microbial communities, bacteria compete and otherwise interact with many others. Oftentimes, interactions between community members happen over short distances only. Spatial structures that emerge from such local interactions are key determinants of microbial evolution. In the first part of my talk, I will discuss how local interactions and spatial structure influence selection on two microbial traits: density-dependent production of anticompetitor toxins and antibiotic resistance. Then, in the second part, I will present a mathematical framework for multiscale selection. This extension of Price’s equation allows one to decomposes selection into local selection acting within environments and interlocal selection acting among environments for any length scale defining “localness”. I will show how this framework can be used to analyse the effects of spatial structure on selection in simulated populations.
Bas E. Dutilh - FSU Jena - Viral Ecology and Omics
Quantifying the impact of Human Leukocyte Antigen on the human gut microbiota
Jacopo Grilli - ICTP Trieste - Quantitative Ecology and Evolution
Non-catastrophic shifts in the human gut microbiome
Aristeidis Litos - FSU Jena - Viral Ecology and Omics
Encoding and Decoding the Microverse
Complex dynamics and co-occurrence patterns transpire throughout the Microverse and are reflected in the composition of microbial communities. These dynamics, which could be stochastic, universal, niche-specific, or even sample-specific, play a crucial role in determining the structure and function of microbial communities. However, discerning the relative contribution of universal and context-specific processes in shaping the composition of microbial communities remains a challenge. If microbial communities are largely shaped by a set of conserved and universal processes, then the information needed to reconstruct their composition is minimal, which signifies a large level of compressibility in community composition. Conversely, if communities are shaped by context-specific rules, making each community essentially unique, a comprehensive understanding of the entire community would be necessary to reconstruct its composition, indicating that compositions are largely incompressible.
Intrinsic dynamics on the global scale are still understudied, whereas the volume of available data increases. Here, we introduce a neural network-based framework to unravel intrinsic dynamics in microbial communities and its concepts. To achieve that we utilize all the data in MGnify database and develop a neural network with an autoencoder architecture for microbial compositions.
Autoencoders learn compressed representations of data by reducing dimensions and reconstructing them. In our implementation we further introduce taxonomic information, by projecting the composition to a universal taxonomy tree. Hyperparameters regarding the model’s architecture, training procedure and preprocessing of the data are tuned based on the beta-diversity between predictions and samples along with other metrics. All samples are assigned with a compressibility score that considers the performance.
High compressibility scores indicate wider-spread intrinsic patterns in the composition, while low scores suggest uniqueness. Therefore, with our generative model, we can classify microbial taxonomic profiles in a gradient from universal to context-specific dynamic patterns. Universal patterns throughout the Microverse can be revealed with models trained and tested on datasets from different biomes.
Shared patterns of intrinsic dynamics encrypted in the composition between samples of different biomes can emerge and further our understanding of microbial communities, their structures, functions and role in nature.
Sascha Schaeuble - Leibniz Institute for Natural Product Research and Infection Biology HKI Jena - Microbiome Dynamics
Fungal pathogenicity and the influence of the microbiome - an in silico modeling perspective
Candida albicans and Aspergillus fumigatus have been identified by the WHO as top-priority fungal pathogens recently. These fungi reside next to the human microbiome in the lung or gut, interacting with bacterial communities for nutrition and survival. Investigating the impact of interaction on host, fungal, and bacterial metabolism at the systems level is pivotal to understand infection progression and associated disease. Towards this aim, we developed genome-scale fungal metabolic models and conducted data-driven simulations alone or in conjunction with bacterial models. We predict metabolite uptake, secretion, and their effects on fungal growth. Our in silico approach complements traditional research, enables focussed downstream experiments and offers new insights into combating emerging fungal pathogens and identifying potential therapeutic strategies.
Stefan Schuster, Lukas Korn, Suman Chakraborty - FSU Jena - Dept. of Bioinformatics
Optimizing biochemical defence and counter-counter defence in parasitic interactions. Steady-state analysis
In many interactions between parasites (including pathogens) and their hosts, defense and counter-adaptation mechanisms in the form of defense chemicals and enzymes degrading those chemicals can be observed. An example is provided by antimicrobial peptides (e.g. defensins) and multidrug resistance pumps. Some of these enzymes are subject to counter-counter defense mechanisms of the parasite such as efflux pump inhibitors.
We consider a defense chemical that is produced at a constant rate and degraded by a Michaelis-Menten enzyme. The enzyme is inhibited by a substance that is produced by the same pathogen at a constant rate as well and degraded or removed according to a linear kinetics. The sum of the two production rates is assumed to be constant because the capacity (resource) of the cell to invest into that system is certainly limited. However, the capacity can slowly increase upon induction. The maximization problem is to find the optimal allocation of the resource to the two rates, that is, to defense and counter-counter defense, respectively. Here, we solve the problem under steady-state conditions in an analytical way.
Optimal resource allocation can be expressed as a function of the capacity and of the inhibition constant. For values of the inhibition constant above a certain threshold (weak binding of the inhibitor), it does not pay off anymore to invest into the counter-counter defense; rather the resource should be invested fully into the defense. Bifurcation points also exist in the dependence on the capacity. Our analysis is promising in view of optimizing pharmaceutical treatments of infection diseases.
Bram van Dijk - Utrecht University - Theoretical Biology
Distinct distributions of transposons across E. coli strains hint at lifestyles reminiscent of lysis and lysogeny
Transposable elements (TEs) are without a doubt the smallest Darwinian entity we know to date. They exhibit replication, mutation, and variation in survival rates. While larger organisms typically compete for tangible resources, TEs have a different kind of "resource" – non-essential DNA. In my presentation, I'll demonstrate that for simple TEs like insertion-sequence (IS) elements, the balance between non-essential and essential DNA is pivotal in determining their fate. Assuming TEs insert randomly in the genome, I'll explore how this balance impacts their evolution, particularly in the context of transferring to new hosts via Horizontal Gene Transfer (HGT). Next, I will allow TEs to evolve their own site-specificity to avoid inserting into essential DNA. Interestingly, when HGT is infrequent, TEs tend to become highly specific about their insertion sites. This specificity initially incurs a direct fitness penalty due to the difficulty of finding suitable sites, but is beneficial in the long run as it prevents rapid host extinction. This behaviour parallels the concept of phage lysogeny, albeit on a vastly different timescale, and results in distinct copy-number distributions compared to less specific TEs. I'll back these findings with an analysis of multiple IS-element families, demonstrating that these distinct patterns are indeed observable in real-world data. Thus, even in the smallest Darwinian entities like TEs, we observe the classic ecological strategies of r-selection (producing many offspring with few surviving) and K-selection (producing fewer offspring with a higher survival probability). In summary, despite their slower replication and slower exploitation of hosts compared to phages, TEs exhibit surprising similarities, offering valuable insights into evolutionary strategies and ecological dynamics.
Lin Lin Xu - Leibniz Institute for Natural Product Research and Infection Biology HKI Jena - Microbiome Dynamics
Sediment microbiome mediates the effect of pollution on benthic macro-organisms
Coastal marine ecosystems serve as vital sources of food security, cultural heritage, and means of subsistence for millions of people globally. Despite their essential role, over the past several decades coastal ecosystems have been under continued decline worldwide with reported local extinctions of mollusks, followed by cnidarians, fish, and macroalgae. Microbial communities in marine sediments contribute significantly to marine ecosystems' overall health and resiliency. While several studies have provided substantial evidence that the sedimental microbiome is impacted by pollution in the last few years, there has been no integrative comprehensive analysis of macro- and micro-organisms under pollution stress. Therefore, a comprehensive understanding of the complex relationships between micro- and macro-organisms is crucial for improving coastal marine ecosystem biodiversity and will benefit humankind in the long term.
Considering macro-organisms and microbiomes’ work as a synergistic ecological unit, we combined deep shotgun metagenomic sequencing and DNA metabarcoding analysis of samples collected from an urbanized coastal city (Hong Kong) across a pollution gradient. Environmental factors, including water and sediment quality indexes, accounted for more than 50% of the observed variance in marine sediment microbial communities and benthic macro-organisms, with heavy metals, total carbon, and total nitrogen having the greatest explanatory power. Our findings revealed that pollution gradients are associated with continuous shifts in functional diversity, characterized by increased alpha diversity of functional profiles and significant changes in microbial pathways abundance, resulting in a unique metabolic landscape for other organisms to thrive. We found that both the biodiversity and functional profile richness of the bacterial community was positively correlated with the richness of benthic macro-organisms. Interestingly, mediation analysis suggested that microbial species and functions accounted for 11% and 14% of the total effect of pollution on the benthic macro-organisms, respectively. By bi-directional mediation analyses, we noticed that microbes involved in marine pollution biogeochemistry and microbial mechanisms associated with energy synthesis and conservation play a key role in mediating the impact of pollution on benthic macro-organisms. Moreover, the mediation effect from specific microbial taxa (Rhodopirellula and Nitrospina gracilis) and functions to benthic macro-organisms could be up to 85%.
Our study introduces a novel multi-level perspective for future studies in urbanized coastal areas to explore marine ecosystems, revealing the impact of pollution stress on microbiome communities and their critical biogeochemical functions, which in turn may influence the macrofaunal composition.