Isolation of intact RNA from cytometrically sorted Saccharomyces cerevisiae for the analysis of intrapopulation diversity of gene expression

Digital models in biotechnology: Towards multi-scale integration and implementation

Industrial biotechnology encompasses a large area of multi-scale and multi-disciplinary research activities. With the recent megatrend of digitalization sweeping across all industries, there is an increased focus in the biotechnology industry on developing, integrating and applying digital models to improve all aspects of industrial biotechnology. Given the rapid development of this field, we systematically classify the state-of-art modelling concepts applied at different scales in industrial biotechnology and critically discuss their current usage, advantages and limitations. Further, we critically analyzed current strategies to couple cell models with computational fluid dynamics to study the performance of industrial microorganisms in large-scale bioprocesses, which is of crucial importance for the bio-based production industries. One of the most challenging aspects in this context is gathering intracellular data under industrially relevant conditions. Towards comprehensive models, we discuss how different scale-down concepts combined with appropriate analytical tools can capture intracellular states of single cells. We finally illustrated how the efforts could be used to develop digitals models suitable for both cell factory design and process optimization at industrial scales in the future.

Technical pipeline for screening microbial communities as a function of substrate specificity through fluorescent labelling

The study of specific glycan uptake and metabolism is an effective tool in aiding with the continued unravelling of the complexities in the human gut microbiome. To this aim fluorescent labelling of glycans may provide a powerful route towards this target. Here, we successfully used the fluorescent label 2-aminobenzamide (2-AB) to monitor and study microbial degradation of labelled glycans. Both single strain and co-cultured fermentations of microbes from the common human-gut derived Bacteroides genus, are able to grow when supplemented with 2-AB labelled glycans of different monosaccharide composition, degrees of acetylation and polymerization. Utilizing a multifaceted approach that combines chromatography, mass spectrometry, microscopy and flow cytometry techniques, it is possible to better understand the metabolism of labelled glycans in both supernatants and at a single cell level. We envisage this combination of complementary techniques will help further the understanding of substrate specificity and the role it plays within microbial communities.

A reductive amination-based fluorophore labelling of complex wood-derived glycans provides a proof-of-principle multi-modal platform for monitoring glycan uptake by bacteria.

Determination of elemental distribution and evaluation of elemental concentration in single Saccharomyces cerevisiae cells using single cell-inductively coupled plasma mass spectrometry

Single-cell analysis using inductively coupled plasma mass spectrometry (SC-ICP-MS) is a method to obtain qualitative and quantitative information of the elemental content and distribution of single cells. Six intrinsic target elements were analyzed in yeast cells at different cell growth phases cultured in medium with different phosphorus concentrations (0, 7, 14 mM) to study its effect on cell growth and composition. SC-ICP-MS results were compared with those obtained by the acid digestion and the average ratio was 0.81. The limits of detection of this method were 0.08, 2.54, 12.5, 0.02, 0.02, and 0.08 fg cell-1 for Mg, P, K, Mn, Cu, and Zn, respectively. During the exponential growth phase, the cells exhibited higher elemental contents, wider distribution for most elements, and larger cell size in comparison to the stationary growth phase. Phosphorus-free conditions reduced the average P content in single cells of stationary growth phase from 650 to 80 fg. Phosphorus deficiency led to decreasing intracellular concentrations not only of P but also of K and Cu, and to increasing Zn concentration after 48 h. Mg maintained its concentration at ∼0.11 fg µm-3 and did not change significantly under the three investigated conditions after 48 h. Accordingly, Mg content was successfully used to estimate the intracellular concentration of other intrinsic elements in single yeast cells. SC-ICP-MS is suited to determine target elements in single yeast cells, and allows the study of heterogeneity of cell composition and effects of stressors on the elemental content, distribution, and concentrations of intrinsic elements.

Single-Cell Technologies to Understand the Mechanisms of Cellular Adaptation in Chemostats

There is a growing interest in continuous manufacturing within the bioprocessing community. In this context, the chemostat process is an important unit operation. The current application of chemostat processes in industry is limited although many high yielding processes are reported in literature. In order to reach the full potential of the chemostat in continuous manufacture, the output should be constant. However, adaptation is often observed resulting in changed productivities over time. The observed adaptation can be coupled to the selective pressure of the nutrient-limited environment in the chemostat. We argue that population heterogeneity should be taken into account when studying adaptation in the chemostat. We propose to investigate adaptation at the single-cell level and discuss the potential of different single-cell technologies, which could be used to increase the understanding of the phenomena. Currently, none of the discussed single-cell technologies fulfill all our criteria but in combination they may reveal important information, which can be used to understand and potentially control the adaptation.

Cytometry meets next-generation sequencing - RNA-Seq of sorted subpopulations reveals regional replication and iron-triggered prophage induction in Corynebacterium glutamicum

Phenotypic diversification is key to microbial adaptation. Currently, advanced technological approaches offer insights into cell-to-cell variation of bacterial populations at a spatiotemporal resolution. However, the underlying molecular causes or consequences often remain obscure. In this study, we developed a workflow combining fluorescence-activated cell sorting and RNA-sequencing, thereby allowing transcriptomic analysis of 106 bacterial cells. As a proof of concept, the workflow was applied to study prophage induction in a subpopulation of Corynebacterium glutamicum. Remarkably, both the phage genes and flanking genomic regions of the CGP3 prophage revealed significantly increased coverage upon prophage induction - a phenomenon that to date has been obscured by bulk approaches. Genome sequencing of prophage-induced populations suggested regional replication at the CGP3 locus in C. glutamicum. Finally, the workflow was applied to unravel iron-triggered prophage induction in early exponential cultures. Here, an up-shift in iron levels resulted in a heterogeneous response of an SOS (PdivS) reporter. RNA-sequencing of the induced subpopulation confirmed induction of the SOS response triggering also activation of the CGP3 prophage. The fraction of CGP3-induced cells was enhanced in a mutant lacking the iron regulator DtxR suffering from enhanced iron uptake. Altogether, these findings demonstrate the potential of the established workflow to gain insights into the phenotypic dynamics of bacterial populations.

Population heterogeneity in microbial bioprocesses: origin, analysis, mechanisms, and future perspectives

Population heterogeneity is omnipresent in all bioprocesses even in homogenous environments. Its origin, however, is only so well understood that potential strategies like bet-hedging, noise in gene expression and division of labour that lead to population heterogeneity can be derived from experimental studies simulating the dynamics in industrial scale bioprocesses. This review aims at summarizing the current state of the different parts of single cell studies in bioprocesses. This includes setups to visualize different phenotypes of single cells, computational approaches connecting single cell physiology with environmental influence and special cultivation setups like scale-down reactors that have been proven to be useful to simulate large-scale conditions. A step in between investigation of populations and single cells is studying subpopulations with distinct properties that differ from the rest of the population with sub-omics methods which are also presented here. Moreover, the current knowledge about population heterogeneity in bioprocesses is summarized for relevant industrial production hosts and mixed cultures, as they provide the unique opportunity to distribute metabolic burden and optimize production processes in a way that is impossible in traditional monocultures. In the end, approaches to explain the underlying mechanism of population heterogeneity and the evidences found to support each hypothesis are presented. For instance, population heterogeneity serving as a bet-hedging strategy that is used as coordinated action against bioprocess-related stresses while at the same time spreading the risk between individual cells as it ensures the survival of least a part of the population in any environment the cells encounter.

One-step hot formamide extraction of RNA from Saccharomyces cerevisiae

Current methods for isolating RNA from budding yeast require lengthy and laborious steps such as freezing and heating with phenol, homogenization with glass beads, or enzymatic digestion of the cell wall. Here, extraction with a solution of formamide and EDTA was adapted to isolate RNA from whole yeast cells through a rapid and easily scalable procedure that does not require mechanical cell lysis, phenol, or enzymes. RNA extracted with formamide-EDTA can be directly loaded on gels for electrophoretic analysis without alcohol precipitation. A simplified protocol for downstream DNase treatment and reverse transcription reaction is also included. The formamide-EDTA extraction of yeast RNA is faster, safer, and more economical than conventional methods, outperforms them in terms of total yield, and greatly increases throughput.

Leishmania donovani Aurora kinase: A promising therapeutic target against visceral leishmaniasis

BACKGROUND

Aurora kinases are key mitotic kinases executing multiple aspects of eukaryotic cell-division. The apicomplexan homologs being essential for survival, suggest that the Leishmania homolog, annotated LdAIRK, may be equally important.

METHODS

Bioinformatics, stage-specific immunofluorescence microscopy, immunoblotting, RT-PCR, molecular docking, in-vitro kinase assay, anti-leishmanial activity assays, flow cytometry, fluorescence microscopy.

RESULTS

Ldairk expression is seen to vary as the cell-cycle progresses from G1 through S and finally G2M and cytokinesis. Kinetic studies demonstrate their enzymatic activity exhibiting a Km and Vmax of 6.12μM and 82.9pmoles·min(-1)mg(-1) respectively against ATP using recombinant Leishmania donovani H3, its physiological substrate. Due to the failure of LdAIRK-/+ knock-out parasites to survive, we adopted a chemical knock-down approach. Based on the conservation of key active site residues, three mammalian Aurora kinase inhibitors were investigated to evaluate their potential as inhibitors of LdAIRK activity. Interestingly, the cell-cycle progressed unhindered, despite treatment with GSK-1070916 or Barasertib, inhibitors with greater potencies for the ATP-binding pocket compared to Hesperadin, which at nanomolar concentrations, severely compromised viability at IC50s 105.9 and 36.4nM for promastigotes and amastigotes, respectively. Cell-cycle and morphological studies implicated their role in both mitosis and cytokinesis.

CONCLUSION

We identified an Aurora kinase homolog in L. donovani implicated in cell-cycle progression, whose inhibition led to aberrant changes in cell-cycle progression and reduced viability.

GENERAL SIGNIFICANCE

Human homologs being actively pursued drug targets and the observations with LdAIRK in both promastigotes and amastigotes suggest their potential as therapeutic-targets. Importantly, our results encourage the exploration of other proteins identified herein as potential novel drug targets.

Living Cell Microarrays: An Overview of Concepts

Living cell microarrays are a highly efficient cellular screening system. Due to the low number of cells required per spot, cell microarrays enable the use of primary and stem cells and provide resolution close to the single-cell level. Apart from a variety of conventional static designs, microfluidic microarray systems have also been established. An alternative format is a microarray consisting of three-dimensional cell constructs ranging from cell spheroids to cells encapsulated in hydrogel. These systems provide an in vivo-like microenvironment and are preferably used for the investigation of cellular physiology, cytotoxicity, and drug screening. Thus, many different high-tech microarray platforms are currently available. Disadvantages of many systems include their high cost, the requirement of specialized equipment for their manufacture, and the poor comparability of results between different platforms. In this article, we provide an overview of static, microfluidic, and 3D cell microarrays. In addition, we describe a simple method for the printing of living cell microarrays on modified microscope glass slides using standard DNA microarray equipment available in most laboratories. Applications in research and diagnostics are discussed, e.g., the selective and sensitive detection of biomarkers. Finally, we highlight current limitations and the future prospects of living cell microarrays.

Variability in subpopulation formation propagates into biocatalytic variability of engineered Pseudomonas putida strains

Pivotal challenges in industrial biotechnology are the identification and overcoming of cell-to-cell heterogeneity in microbial processes. While the development of subpopulations of isogenic cells in bioprocesses is well described (intra-population variability), a possible variability between genetically identical cultures growing under macroscopically identical conditions (clonal variability) is not. A high such clonal variability has been found for the recombinant expression of the styrene monooxygenase genes styAB from Pseudomonas taiwanensis VLB120 in solvent-tolerant Pseudomonas putida DOT-T1E using the alk-regulatory system from P. putida GPo1. In this study, the oxygenase subunit StyA fused to eGFP was used as readout tool to characterize the population structure in P. putida DOT-T1E regarding recombinant protein content. Flow cytometric analyses revealed that in individual cultures, at least two subpopulations with highly differing recombinant StyA-eGFP protein contents appeared (intra-population variability). Interestingly, subpopulation sizes varied from culture-to-culture correlating with the specific styrene epoxidation activity of cells derived from respective cultures (clonal variability). In addition, flow cytometric cell sorting coupled to plasmid copy number (PCN) determination revealed that detected clonal variations cannot be correlated to the PCN, but depend on the combination of the regulatory system and the host strain employed. This is, to the best of our knowledge, the first work reporting that intra-population variability (with differing protein contents in the presented case study) causes clonal variability of genetically identical cultures. Respective impacts on bioprocess reliability and performance and strategies to overcome respective reliability issues are discussed.

Analysis of aging in lager brewing yeast during serial repitching

Serial repitching of brewing yeast inoculates is an important economic factor in the brewing industry, as their propagation is time and resource intensive. Here, we investigated whether replicative aging and/or the population distribution status changed during serial repitching in three different breweries with the same brewing yeast strain but different abiotic backgrounds and repitching regimes with varying numbers of reuses. Next to bud scar numbers the DNA content of the Saccharomyces pastorianus HEBRU cells was analyzed. Gene expression patterns were investigated using low-density microarrays with genes for aging, stress, storage compound metabolism and cell cycle. Two breweries showed a stable rejuvenation rate during serial repitching. In a third brewery the fraction of virgin cells varied, which could be explained with differing wort aeration rates. Furthermore, the number of bud scars per cell and cell size correlated in all 3 breweries throughout all runs. Transcriptome analyses revealed that from the 6th run on, mainly for the cells positive gene expression could be seen, for example up-regulation of trehalose and glycogen metabolism genes. Additionally, the cells' settling in the cone was dependent on cell size, with the lowest and the uppermost cone layers showing the highest amount of dead cells. In general, cells do not progressively age during extended serial repitching.

Transcriptome analysis

Transcriptome analysis technologies are important systems-biology methods for the investigation and optimization of mammalian cell cultures concerning with regard to growth rates and productivity. For the production of recombinant proteins, knowledge of the expression conditions of the influencing genes is a major issue in the improvement of cell lines by means of genome engineering. This chapter presents two main techniques for transcriptome analysis: microarray technology and next-generation sequencing. Protein-based methods are also briefly outlined. Furthermore, the impact of these technologies on mammalian cell culture improvement is discussed.

Origin and analysis of microbial population heterogeneity in bioprocesses

Heterogeneity of industrial production cultures is accepted to a certain degree; however, the underlying mechanisms are seldom perceived or included in the development of new bioprocess control strategies. Population heterogeneity and its basics, perceptible in the diverse proficiency of cells, begins with asymmetric birth and is found to recess during the life cycle. Since inefficient subpopulations have significant impact on the productivity of industrial cultures, cellular heterogeneity needs to be detected and quantified by using high speed detection tools like flow cytometry. Possible origins of population heterogeneity, sophisticated fluorescent techniques for detection of individual cell states, and cutting-edge Omics-technologies for extended information beyond the resolution of fluorescent labelling are highlighted.

Analysis and modeling of growing budding yeast populations at the single cell level

Model organisms and in particular the budding yeast Saccharomyces cerevisiae have been instrumental in advancing our understanding of cell cycle progression. The asymmetric division of the budding yeast and the tight coupling between cell growth and division have challenged the theoretical understanding of the cell size structure of growing yeast populations. Past efforts have centered on modeling the steady-state theoretical age distribution for asymmetric division from which a cell size distribution can be derived assuming dispersion of cell size within each age class. Different developments, especially in the field of flow cytometry, allowed the determination of a number of cellular properties and their joint distributions for the entire population and the different subpopulations as well. A new rigorous framework for modeling directly the dynamics of size distributions of structured yeast populations has been proposed, which readily extends to modeling of more complex conditions, such as transient growth. Literature on the structure of growing yeast populations and modeling of cell cycle progression is reviewed.

Cytomics and nanobioengineering

The finding that an individual's genome differs as much as by many million variants from that of the human reference assembly diminished the great enthusiasm that every disease could be predicted based on nucleotide polymorphisms. Even individual cells of an organ may be specifically equipped to perform specific tasks and that the information of individual cells in a cell system is key information to understand function or dysfunction. Therefore, cytomics received great attention during the last years as it allows to quantitatively and qualitatively analyzing great number of individual cells, cell constituents, and of their intracellular and functional interactions in a cellular system and also giving the concept of analysis of these data.Exhaustive data extraction from multiparametric assays and multiple tests are the prerequisite for prediction of drug toxicity. Cytomics, as novel approach for unsupervised data analysis give a chance to find the most predictive parameters, which describe best the toxicity of a chemical. Cytomics is intrinsically connected to drug development and drug discovery.Focused on small structures, nanobioengineering is the ideal partner of cytomics, the systems biological discipline for cell population analysis. Realizing the idea "from the molecule to the patient" develops and offers chemical compounds, proteins, and other biomolecules, cells as well as tissues as instruments and products for a wide variety of biotechnological and biomedical applications.The integrative nanobioengineering combining different disciplines of nanotechnology will promote the development of innovative therapies and diagnostic methods. It can improve the precision of the measurements with focus on single cell analysis. By nanobioengineering and whole body imaging techniques, cytomics covers the field from molecules through bacterial cells, eukaryotic tissues, and organs to small animal live analysis. Toxicological testing and medical drug development are currently strongly broadening. It harbors the promise to substantially impact on various fields of biomedicine, drug discovery, and predictive medicine.As the number of scientific data is rising exponentially, new data analysis tools and strategies like cytomics and nanobioengineering take a lead and get closer to application. Bionanoengineering may strongly support the quantitative data supply, thus strengthening the rational for cytomics approach.