Germination and Growth Analysis of Streptomyces lividans at the Single-Cell Level Under Varying Medium Compositions

Koepff J, Sachs CC, Wiechert W, et al. Germination and Growth Analysis of Streptomyces lividans at the Single-Cell Level Under Varying Medium Compositions. FRONTIERS IN MICROBIOLOGY. 2018;9: 2680.Quantitative single-cell cultivation has provided fundamental contributions to our understanding of heterogeneity among industrially used microorganisms. Filamentous growing Streptomyces species are emerging platform organisms for industrial production processes, but their exploitation is still limited due to often reported high batch-to-batch variations and unexpected growth and production differences. Population heterogeneity is suspected to be one responsible factor, which is so far not systematically investigated at the single-cell level. Novel microfluidic single-cell cultivation devices offer promising solutions to investigate these phenomena. In this study, we investigated the germination and growth behavior of Streptomyces lividans TK24 under varying medium compositions on different complexity levels (i.e., mycelial growth, hyphal growth and tip elongation) on single-cell level. Our analysis reveals a remarkable stability within growth and germination of spores and early mycelium development when exposed to constant and defined environments. We show that spores undergo long metabolic adaptation processes of up to > 30 h to adjust to new medium conditions, rather than using a "persister" strategy as a possibility to cope with rapidly changing environments. Due to this uniform behavior, we conclude that S. lividans can be cultivated quite robustly under constant environmental conditions as provided by microfluidic cultivation approaches. Failure and non-reproducible cultivations are thus most likely to be found in less controllable larger-scale cultivation workflows and as a result of environmental gradients within large-scale cultivations

Germination and Growth Analysis of Streptomyces lividans at the Single-Cell Level Under Varying Medium Compositions

Quantitative single-cell cultivation has provided fundamental contributions to our understanding of heterogeneity among industrially used microorganisms. Filamentous growing Streptomyces species are emerging platform organisms for industrial production processes, but their exploitation is still limited due to often reported high batch-to-batch variations and unexpected growth and production differences. Population heterogeneity is suspected to be one responsible factor, which is so far not systematically investigated at the single-cell level. Novel microfluidic single-cell cultivation devices offer promising solutions to investigate these phenomena. In this study, we investigated the germination and growth behavior of Streptomyces lividans TK24 under varying medium compositions on different complexity levels (i.e., mycelial growth, hyphal growth and tip elongation) on single-cell level. Our analysis reveals a remarkable stability within growth and germination of spores and early mycelium development when exposed to constant and defined environments. We show that spores undergo long metabolic adaptation processes of up to > 30 h to adjust to new medium conditions, rather than using a “persister” strategy as a possibility to cope with rapidly changing environments. Due to this uniform behavior, we conclude that S. lividans can be cultivated quite robustly under constant environmental conditions as provided by microfluidic cultivation approaches. Failure and non-reproducible cultivations are thus most likely to be found in less controllable larger-scale cultivation workflows and as a result of environmental gradients within large-scale cultivations

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.Peer reviewe

The uncertain climate footprint of wetlands under human pressure

Significant climate risks are associated with a positive carbon–temperature feedback in northern latitude carbon-rich ecosystems,making an accurate analysis of human impacts on the net greenhouse gas balance of wetlands a priority. Here, we provide a coherent assessment of the climate footprint of a network of wetland sites based on simultaneous and quasi-continuous ecosystem observations of CO2 and CH4 fluxes. Experimental areas are located both in natural and in managed wetlands and cover a wide range of climatic regions, ecosystem types, and management practices. Based on direct observations we predict that sustained CH4 emissions in natural ecosystems are in the long term (i.e., several centuries) typically offset by CO2 uptake, although with large spatiotemporal variability. Using a space-for-time analogy across ecological and climatic gradients, we represent the chronosequence from natural to managed conditions to quantify the “cost” of CH4 emissions for the benefit of net carbon sequestration. With a sustained pulse– response radiative forcing model, we found a significant increase in atmospheric forcing due to land management, in particular for wetland converted to cropland. Our results quantify the role of human activities on the climate footprint of northern wetlands and call for development of active mitigation strategies for managed wetlands and new guidelines of the Intergovernmental Panel on Climate Change (IPCC) accounting for both sustained CH4 emissions and cumulative CO2 exchange

Online High Throughput Microfluidic Single Cell Analysis for Feed-Back Experimentation

Unraveling heterogeneity remains a major challenge to overcome when advancing our understanding of bio(techno)logical processes. Microfluidic single cell cultivation combined with live cell imaging has become a powerful technology to elucidate cellular heterogeneities temporally resolved on the single cell level. In this context, within recent years, versatile cultivation devices as well as image analysis tools have been developed, tailored to microbial single-cell studies. At the current state, acquired image data are typically analyzed after experimentation has been finished, resulting in static offline approaches and long cycles of insight generation. To shorten these cycles and to allow novel types of experiments extended by interacting with the biological system, the experimental setup needs live analysis with joint automated experimental control. This work develops software-based online capable techniques for feed-back experimentation: The application and development of image analysis pipelines suitable therefor, as well as the establishment of a new automated experimental control platform, HiMiCs, for microfluidic live cell experiments: An existing image analysis pipeline is described, aiming at one dimensional microfluidic growth channels. It is applied and connected into the platform. A new image analysis pipeline specifically aiming at filamentous growing microorganisms in cultivation chambers was developed and applied. Furthermore, a machine learning based approach for segmenting rod-shaped bacteria has been investigated. The experimental control platform connects high-level microscope control specifically tailored to the necessities of microfluidic experimentation, that is, hardware control of the microscope and additional peripherals, image acquisition and remote storage in centralized infrastructure, jointly with connectivity protocols for image analysis routines. This allows for direct, automated analysis of the image data, as it is acquired, presenting the user with results and remote control. By passing the results to a simple yet powerful scripting interface, model based steering of the experiment at a high abstraction level becomes possible. Furthermore, a simulation based image generation system is described, for in silico end-to-end testing scenarios of the platform, as well to gather insight towards microcolony growth by modeling. As a proof-of-concept experiment facilitating feed-back control, growth of the biotechnologically relevant organism Corynebacterium glutamicum is automatically controlled via nutrient availability. With that, the experimental control platform HiMiCs lays the foundation to new classes of experiments while reducing the “time to insight”: Based upon biological behavior, experimental conditions can be adapted automatically, thereby closing the cycle of data generation and experiment parameter decision within a single experiment