Univ.-Prof. Dr. Martin Polz

Microbes are the most abundant and diverse organisms on the planet. Yet how this diversity is structured in the environment remains poorly understood. Martin’s group is broadly interested in structure-function relationships within microbial communities. How do gene flow, environmental interactions, and selection structure populations? How does viral predation drive the ecology and evolution of microbes? How fast do microbes grow in environmental samples?

The group addresses these questions by a combination of in situ molecular approaches, environmental genomics, traditional physiological and genetic techniques, and modelling. They study patterns of diversity among co-occurring microbes from the level of the entire community to the individual genome and gene. Their model systems include marine microbes as well as animal microbiomes. Their latest projects focus on microbe-virus interactions and on growth dynamics under environmental conditions.

In many environments, the number of bacteria is relatively invariant irrespective of growth rates. This is due to the high predation rates that can rapidly adjust to changes in bacterial productivity. Hence predators exert strong selection on their prey yet very little is known how these processes affect bacterial population diversity and dynamics in the wild. To address this issue, we have recently carried out a highly resolved time series to explore the coupling of predator-prey dynamics on the population level. This has resulted in the largest, fully genome sequenced virus-host interaction network to date with over 300 and 600 sequenced viral and bacterial genomes. One of the most important results of this effort was the discovery of a novel type of virus that resembles double-beta barrel fold of many eukaryotic viruses in its capsid proteins but infects bacteria. Importantly, this viral type matches the dominant morphotype viruses in the ocean whose identity has to date remained enigmatic. In ongoing work, we are exploring how defense against viruses is structured in environmental populations and how this influences the eco-evolutionary dynamics of viruses and their hosts.

We are in the process of generalizing to other groups of microbes our previous insights into the evolution of population structure gained in our Vibrio model. We hypothesized that although genes in genomes have no consistent signal of common evolutionary descent due to a history of extensive horizontal gene transfer, recent gene flow should on average be higher within than between populations due to genetic and ecological similarity of individuals within populations. Using a novel measure to identify the most recent HGT events among genomes, we constructed gene flow networks for closely related genomes, and found that clusters in these networks match previously defined ecologically cohesive populations in diverse bacteria and archaea. Defining populations based on gene flow also provides a powerful 'reverse ecology’ framework where genomes of closely related, co-occurring microbes from environmental samples can be assayed for genetic cohesion as a rapid means to hypothesize population structure and hence ecological differentiation. Identifying and understanding such fine-scale structure among coexisting bacteria and archaea has implications for a broad species definition and will allow more facile linking genomic to ecological features in both environmental and health applications. In fact, we have recently applied the method to bacterial pathogens and discovered unrecognized population structure and speciation events.

Microbes are collectively responsible for much of primary and secondary production, are key drivers of biogeochemical cycles, and modulate the physiology of other organisms. In recent years, genomic and metagenomic efforts have also highlighted the enormous genetic and functional diversity co-existing within different types of microbiomes. However, although it is relatively easy with modern sequence techniques to determine the relative abundance of microbes in samples, fundamental questions remain on how microbes grow under varying spatial and temporal conditions, hampering our understanding of globally and locally important processes. For example, it is largely unknown how fast individual microbes grow under in situ conditions, how growth rates differ among groups of microbes and how they are modulated by ecological conditions. We are currently addressing this problem by coupling single cell estimates of biomass and growth rate with genomics, hence providing the full spectrum of measurements necessary to determine the importance of specific microbes within complex communities. The central element of our novel approach is the suspended microchannel resonator (SMR), which is a well-developed microfluidics-based mass-sensor that has sufficient resolution for measuring the natural range in size, biomass and growth rate of microbes. Single cell growth measurements will be the foundation of coupling of diversity estimates with biogeochemical activity or correlation to host physiology, and it will lead to a more quantitative estimate of microbial activity in global carbon cycle models.

Although it was recognized well over two decades ago that in most environments the diversity of genes used as markers for microbial taxa is vast, it was not clear how much of this diversity really matters when we want to estimate the number of ecologically distinct populations. We showed that thousands of 16S rRNA and protein-coding genes, which are used to survey microbial diversity, are retrieved from samples but that sequence diversity is organized into microdiverse clusters.  This observation led us to hypothesize that these clusters represent ecologically distinct populations. Using marine bacteria of the genus Vibrio as a model, we tested this hypothesis using a combination of fine-scale environmental sampling and mathematical modeling, and we showed that sequence clusters differentially partition environmental resources. This represented the first step towards defining population structure in natural environments by allowing categorization of co-existing diversity into distinct ecological units and was the starting point for development of our population genomics model.

How reproducibly microbial populations are associated with the same type of micro-environmental features in the wild remains poorly understood but is crucial for structure-function linkage.  Using our vibrio model, we showed that populations display reproducible environmental dynamics and characteristic distributions. We identified associations with different types of organic particles and organisms, and different ecological strategies from highly specialized to generalist. Our repeated sampling of the same microenvironments also demonstrated that associations are predictable at the population level but that genotypic diversity within populations is high, most conspicuously manifest as high gene content diversity. Importantly, these observations have allowed us to interpret gene types and frequencies within and between populations in terms of environmental selection.

Because horizontal gene transfer is common among microbes, species concepts developed for sexual eukaryotes have not been applicable to these organisms. One of the most puzzling observations is that individuals (clones), which are nearly identical in most of their genes, can have hundreds of genes that are differentially present or absent in their genomes. Our population model has yielded important insights into how populations differentiate in light of environmental selection and maintain such genomic diversity even during speciation events. A major breakthrough was the detailed genomic analysis of two recently speciated populations, that already showed differential ecological specialization. Counter to the most commonly cited model, which predicted genome-wide sweeps, we showed that genes can sweep in a population specific manner, i.e., akin to sexual eukaryotes where recombination allows high rates of gene flow. The observed ecological differentiation was accompanied by a competition-dispersal tradeoff as a potential explanation for microscale separation of gene pools during early speciation. Our population model has also allowed us to make progress in explaining gene content diversity within members of populations. For example, we have observed that cheater phenotypes often differ in gene content (rather than regulation) in public good dynamics. We are currently finding similar results in predator-prey interactions so that we are able to provide a more general understanding on how environmental selection causes such large gene content variation across closely related genomes.