Beyond the bulk: disclosing the life of single microbial cells

Application and research progress of ARTP mutagenesis in actinomycetes breeding

Atmospheric and room temperature plasma (ARTP) is an emerging artificial mutagenesis breeding technology. In comparison to traditional physical and chemical methods, ARTP technology can induce DNA damage more effectively and obtain mutation strains with stable heredity more easily after screening. It possesses advantages such as simplicity, safety, non-toxicity, and cost-effectiveness, showing high application value in microbial breeding. This article focuses on ARTP mutagenesis breeding of actinomycetes, specifically highlighting the application of ARTP mutagenesis technology in improving the performance of strains and enhancing the biosynthetic capabilities of actinomycetes. We analyzed the advantages and challenges of ARTP technology in actinomycetes breeding and summarized the common features, specific mutation sites and metabolic pathways of ARTP mutagenic strains, which could give guidance for genetic modification. It suggested that the future research work should focus on the establishment of high throughput rapid screening methods and integrate transcriptomics, proteomics, metabonomics and other omics to delve into the genetic regulations and synthetic mechanisms of the bioactive substances in ARTP mutated actinomycetes. This article aims to provide new perspectives for actinomycetes breeding through the establishment and application of ARTP mutagenesis technology, thereby promoting source innovation and the sustainable industrial development of actinomycetes.

Starch granules in algal cells play an inherent role to shape the popular SSC signal in flow cytometry

OBJECTIVE

Flow cytometry (FC) is probably the most important technique for single-cell analysis. It's precisely, rapid, and suitable for multidimensional single-cell analysis. The commonly used side scatter (SSC) intensity determined by FC is often interpreted as a measure of the internal cellular complexity of cells. In simple terms, the more structured a cell is, the higher the SSC intensity quantified by FC. Nevertheless, most of the studies that support this interpretation are based on data derived from animal or human cell lines and while it is assumed that the results can also be transferred to plant or algal cell lines, the details remain unclear. The objective of the recent work is to clarify the interpretation of the SSC signal from algal cells.

RESULTS

Algal lipid droplets and their starch play an inherent role to shape the popular SSC signal derived from FC. This was shown by a theoretical approach based on Lorenz-Mie theory. These results were supported by experiments with different model cultures of Chlamydomonas reinhardtii in which a high linear correlation was observed between the SSC signal and the 'physical' starch quantity.

Bacterial single-cell transcriptomics: Recent technical advances and future applications in dentistry

Metagenomics and metatranscriptomics have enhanced our understanding of the oral microbiome and its impact on oral health. However, these approaches have inherent limitations in exploring individual cells and the heterogeneity within mixed microbial communities, which restricts our current understanding to bulk cells and species-level information. Fortunately, recent technical advances have enabled the application of single-cell RNA sequencing (scRNA-seq) for studying bacteria, shedding light on cell-to-cell diversity and interactions between host-bacterial cells at the single-cell level. Here, we address the technical barriers in capturing RNA from single bacterial cells and highlight pioneering studies from the past decade. We also discuss recent achievements in host-bacterial dual transcriptional profiling at the single-cell level. Bacterial scRNA-seq provides advantages in various research fields, including the investigation of phenotypic heterogeneity within genetically identical bacteria, identification of rare cell types, detection of antibiotic-resistant or persistent cells, analysis of individual gene expression patterns and metabolic activities, and characterization of specific microbe-host interactions. Integrating single-cell techniques with bulk approaches is essential to gain a comprehensive understanding of oral diseases and develop targeted and personalized treatment in dentistry. The reviewed pioneering studies are expected to inspire future research on the oral microbiome at the single-cell level.

Microbial single-cell mass spectrometry: status, challenges, and prospects

Single-cell analysis uncovers phenotypic differences between cells in a population and dissects their individual physiological states and differences on all omics levels from genome to phenome. Spectrometric observation allows label-free analysis of the metabolome and proteome of individual cells, but is still mainly limited to the analysis of mammalian single cells. Recent progress in mass spectrometry approaches now enables the analysis of microbial single cells - mainly by miniaturizing cell handling, incubation, and improving chip-coupling concepts for analyte ionization by interfacing microfluidic chips and mass spectrometers. This review aims at distilling the enabling principles behind microbial single-cell mass spectrometry and puts them into perspective for the future of the field.

Advances in automated and reactive flow cytometry for synthetic biotechnology

Automated flow cytometry (FC) has been initially considered for bioprocess monitoring and optimization. More recently, new physical and software interfaces have been made available, facilitating the access to this technology for labs and industries. It also comes with new capabilities, such as being able to act on the cultivation conditions based on population data. This approach, known as reactive FC, extended the range of applications of automated FC to bioprocess control and the stabilization of cocultures, but also to the broad field of synthetic and systems biology for the characterization of gene circuits. However, several issues must be addressed before automated and reactive FC can be considered standard and modular technologies.

Prokaryotic and eukaryotic microbial diversity from three soda lakes in the East African Rift Valley determined by amplicon sequencing

Soda lakes are unique poly-extreme environments with high alkalinity and salinity that support diverse microbial communities despite their extreme nature. In this study, prokaryotic and eukaryotic microbial diversity in samples of the three soda lakes, Lake Abijata, Lake Chitu and Lake Shala in the East African Rift Valley, were determined using amplicon sequencing. Culture-independent analysis showed higher diversity of prokaryotic and eukaryotic microbial communities in all three soda lakes than previously reported. A total of 3,603 prokaryotic and 898 eukaryotic operational taxonomic units (OTUs) were found through culture-independent amplicon sequencing, whereas only 134 bacterial OTUs, which correspond to 3%, were obtained by enrichment cultures. This shows that only a fraction of the microorganisms from these habitats can be cultured under laboratory conditions. Of the three soda lakes, samples from Lake Chitu showed the highest prokaryotic diversity, while samples from Lake Shala showed the lowest diversity. Pseudomonadota (Halomonas), Bacillota (Bacillus, Clostridia), Bacteroidota (Bacteroides), Euryarchaeota (Thermoplasmata, Thermococci, Methanomicrobia, Halobacter), and Nanoarchaeota (Woesearchaeia) were the most common prokaryotic microbes in the three soda lakes. A high diversity of eukaryotic organisms were identified, primarily represented by Ascomycota and Basidiomycota. Compared to the other two lakes, a higher number of eukaryotic OTUs were found in Lake Abijata. The present study showed that these unique habitats harbour diverse microbial genetic resources with possible use in biotechnological applications, which should be further investigated by functional metagenomics.

Material Engineering in Gut Microbiome and Human Health

Tremendous progress has been made in the past decade regarding our understanding of the gut microbiome's role in human health. Currently, however, a comprehensive and focused review marrying the two distinct fields of gut microbiome and material research is lacking. To bridge the gap, the current paper discusses critical aspects of the rapidly emerging research topic of "material engineering in the gut microbiome and human health." By engaging scientists with diverse backgrounds in biomaterials, gut-microbiome axis, neuroscience, synthetic biology, tissue engineering, and biosensing in a dialogue, our goal is to accelerate the development of research tools for gut microbiome research and the development of therapeutics that target the gut microbiome. For this purpose, state-of-the-art knowledge is presented here on biomaterial technologies that facilitate the study, analysis, and manipulation of the gut microbiome, including intestinal organoids, gut-on-chip models, hydrogels for spatial mapping of gut microbiome compositions, microbiome biosensors, and oral bacteria delivery systems. In addition, a discussion is provided regarding the microbiome-gut-brain axis and the critical roles that biomaterials can play to investigate and regulate the axis. Lastly, perspectives are provided regarding future directions on how to develop and use novel biomaterials in gut microbiome research, as well as essential regulatory rules in clinical translation. In this way, we hope to inspire research into future biomaterial technologies to advance gut microbiome research and gut microbiome-based theragnostics.

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.

Growth-Associated Droplet Shrinkage for Bacterial Quantification, Growth Monitoring, and Separation by Ultrahigh-Throughput Microfluidics

Microbiology still relies on en masse cultivation for selection, isolation, and characterization of microorganisms of interest. This constrains the diversity of microbial types and metabolisms that can be investigated in the laboratory also because of intercellular competition during cultivation. Cell individualization by droplet-based microfluidics prior to experimental analysis provides an attractive alternative to access a larger fraction of the microbial biosphere, miniaturizing the required equipment and minimizing reagent use for increased and more efficient analytical throughput. Here, we show that cultivation of a model two-strain bacterial community in droplets significantly reduces representation bias in the grown culture compared to batch cultivation. Further, and based on the droplet shrinkage observed upon cell proliferation, we provide proof-of-concept for a simple strategy that allows absolute quantification of microbial cells in a sample as well as selective recovery of microorganisms of interest for subsequent experimental characterization.

Multiple timescales in bacterial growth homeostasis

In balanced exponential growth, bacteria maintain many properties statistically stable for a long time: cell size, cell cycle time, and more. As these are strongly coupled variables, it is not a-priori obvious which are directly regulated and which are stabilized through interactions. Here, we address this problem by separating timescales in bacterial single-cell dynamics. Disentangling homeostatic set points from fluctuations around them reveals that some variables, such as growth-rate, cell size and cycle time, are "sloppy" with highly volatile set points. Quantifying the relative contribution of environmental and internal sources, we find that sloppiness is primarily driven by the environment. Other variables such as fold-change define "stiff" combinations of coupled variables with robust set points. These results are manifested geometrically as a control manifold in the space of variables: set points span a wide range of values within the manifold, whereas out-of-manifold deviations are constrained. Our work offers a generalizable data-driven approach for identifying control variables in a multidimensional system.

Combining microscopy assays of bacteria-surface interactions to better evaluate antimicrobial polymer coatings

Validation of the antimicrobial performance of contact-killing polymer surfaces through experimental determination of bacterial adhesion or viability is essential for their targeted development and application. However, there is not yet a consensus on a single most appropriate evaluation method or procedure. Combining and benchmarking previously reported assays could reduce the significant variation and misinterpretation of efficacy data obtained from different methods. In this work, we systematically investigated the response of bacteria cells to anti-adhesive and antiseptic polymer coatings by combining (i) bulk solution-based, (ii) thin-film spacer-based and (iii) direct contact assays. In addition, we evaluated the studied assays using a five-point scoring framework that highlights key areas for improvement. Our data suggest that combined microscopy assays provide a more comprehensive representation of antimicrobial performance, thereby helping to identify effective types of antibacterial polymer coatings. Importance We present and evaluate a combination of methods for validating the efficacy of antimicrobial surfaces. Antimicrobial surfaces/coatings based on contact-killing components can be instrumental to functionalise a wide range of products. However, there is not yet a consensus on a single, most appropriate method to evaluate their performance. By combining three microscopy methods, we were able to discern contact killing effects at the single cell level that were not detectable by conventional bulk microbiological analyses. The developed approach is considered advantageous for the future targeted development of robust and sustainable antimicrobial surfaces.

Droplet-based microfluidics platform for antifungal analysis against filamentous fungi

Fungicides are extensively used in agriculture to control fungal pathogens which are responsible for significant economic impact on plant yield and quality. The conventional antifungal screening techniques, such as water agar and 96-well plates, are based on laborious protocols and bulk analysis, restricting the analysis at the single spore level and are time consuming. In this study, we present a droplet-based microfluidic platform that enables antifungal analysis of single spores of filamentous fungus Alternaria alternata. A droplet-based viability assay was developed, allowing the germination and hyphal growth of single A. alternata spores within droplets. The viability was demonstrated over a period of 24 h and the antifungal screening was achieved using Kunshi/Tezuma as antifungal agent. The efficacy results of the droplet-based antifungal analysis were compared and validated with the results obtained from conventional protocols. The percentage inhibitions assessed by the droplet-based platform were equivalent with those obtained by the other two methods, and the Pearson correlation analysis showed high correlation between the three assays. Taken together, this droplet-based microfluidic platform provides a wide range of potential applications for the analysis of fungicide resistance development as well as combinatorial screening of other antimicrobial agents and even antagonistic fungi.

Faster, better, and cheaper: harnessing microfluidics and mass spectrometry for biotechnology

High-throughput screening technologies are widely used for elucidating biological activities. These typically require trade-offs in assay specificity and sensitivity to achieve higher throughput. Microfluidic approaches enable rapid manipulation of small volumes and have found a wide range of applications in biotechnology providing improved control of reaction conditions, faster assays, and reduced reagent consumption. The integration of mass spectrometry with microfluidics has the potential to create high-throughput, sensitivity, and specificity assays. This review introduces the widely-used mass spectrometry ionization techniques that have been successfully integrated with microfluidics approaches such as continuous-flow system, microchip electrophoresis, droplet microfluidics, digital microfluidics, centrifugal microfluidics, and paper microfluidics. In addition, we discuss recent applications of microfluidics integrated with mass spectrometry in single-cell analysis, compound screening, and the study of microorganisms. Lastly, we provide future outlooks towards online coupling, improving the sensitivity and integration of multi-omics into a single platform.

Dimension-reduction simplifies the analysis of signal crosstalk in a bacterial quorum sensing pathway

Many pheromone sensing bacteria produce and detect more than one chemically distinct signal, or autoinducer. The pathways that detect these signals are typically noisy and interlocked through crosstalk and feedback. As a result, the sensing response of individual cells is described by statistical distributions that change under different combinations of signal inputs. Here we examine how signal crosstalk reshapes this response. We measure how combinations of two homoserine lactone (HSL) input signals alter the statistical distributions of individual cell responses in the AinS/R- and LuxI/R-controlled branches of the Vibrio fischeri bioluminescence pathway. We find that, while the distributions of pathway activation in individual cells vary in complex fashion with environmental conditions, these changes have a low-dimensional representation. For both the AinS/R and LuxI/R branches, the distribution of individual cell responses to mixtures of the two HSLs is effectively one-dimensional, so that a single tuning parameter can capture the full range of variability in the distributions. Combinations of crosstalking HSL signals extend the range of responses for each branch of the circuit, so that signals in combination allow population-wide distributions that are not available under a single HSL input. Dimension reduction also simplifies the problem of identifying the HSL conditions to which the pathways and their outputs are most sensitive. A comparison of the maximum sensitivity HSL conditions to actual HSL levels measured during culture growth indicates that the AinS/R and LuxI/R branches lack sensitivity to population density except during the very earliest and latest stages of growth respectively.

Growth Response and Recovery of Corynebacterium glutamicum Colonies on Single-Cell Level Upon Defined pH Stress Pulses

Bacteria respond to pH changes in their environment and use pH homeostasis to keep the intracellular pH as constant as possible and within a small range. A change in intracellular pH influences enzyme activity, protein stability, trace element solubilities and proton motive force. Here, the species Corynebacterium glutamicum was chosen as a neutralophilic and moderately alkali-tolerant bacterium capable of maintaining an internal pH of 7.5 ± 0.5 in environments with external pH values ranging between 5.5 and 9. In recent years, the phenotypic response of C. glutamicum to pH changes has been systematically investigated at the bulk population level. A detailed understanding of the C. glutamicum cell response to defined short-term pH perturbations/pulses is missing. In this study, dynamic microfluidic single-cell cultivation (dMSCC) was applied to analyze the physiological growth response of C. glutamicum to precise pH stress pulses at the single-cell level. Analysis by dMSCC of the growth behavior of colonies exposed to single pH stress pulses (pH = 4, 5, 10, 11) revealed a decrease in viability with increasing stress duration w. Colony regrowth was possible for all tested pH values after increasing lag phases for which stress durations w were increased from 5 min to 9 h. Furthermore, single-cell analyses revealed heterogeneous regrowth of cells after pH stress, which can be categorized into three physiological states. Cells in the first physiological state continued to grow without interruption after pH stress pulse. Cells in the second physiological state rested for several hours after pH stress pulse before they started to grow again after this lag phase, and cells in the third physiological state did not divide after the pH stress pulse. This study provides the first insights into single-cell responses to acidic and alkaline pH stress by C. glutamicum.

Adhesion heterogeneity of individual bacterial cells in an axenic culture studied by atomic force microscopy

The evaluation of bacterial adhesive properties at a single-cell level is critical for under standing the role of phenotypic heterogeneity in bacterial attachment and community formation. Bacterial population exhibits a wide variety of adhesive properties at the single-cell level, suggesting that bacterial adhesion is a rather complex process and some bacteria are prone to phenotypic heterogeneity. This heterogeneity was more pronounced for Escherichia coli, where two subpopulations were detected. Subpopulations exhibiting higher adhesion forces may be better adapted to colonize a new surface, especially during sudden changes in environmental conditions. Escherichia coli was characterized by a higher adhesion force, a stronger ability to form biofilm and larger heterogeneity index calculated in comparison with Bacillus subtilis. Higher adhesion forces are associated with a more efficient attachment of bacteria observed in an adhesion assay and might provide a basis for successful colonization, survival and multiplications in changing environment. The atomic force microscopy provides a platform for investigation of the adhesion heterogeneity of individual cells within a population, which may be expected to underpin further elucidation of the adaptive significance of phenotypic heterogeneity in a natural environment.

Opening up the Single-Cell Toolbox for Microbial Natural Products Research

The diverse microbes that produce natural products represent an important source of novel therapeutics, drug leads, and scientific tools. However, the vast majority have not been grown in axenic culture and are members of complex communities. While meta-'omic methods such as metagenomics, -transcriptomics, and -proteomics reveal collective molecular features of this "microbial dark matter", the study of individual microbiome members can be challenging. To address these limits, a number of techniques with single-bacterial resolution have been developed in the last decade and a half. While several of these are embraced by microbial ecologists, there has been less use by researchers interested in mining microbes for natural products. In this review, we discuss the available and emerging techniques for targeted single-cell analysis with a particular focus on applications to the discovery and study of natural products.

Reflections on the Predictability of Evolution: Toward a Conceptual Framework

Evolution is generally considered to be unpredictable because genetic variations are known to occur randomly. However, remarkable patterns of repeated convergent evolution are observed, for instance, loss of pigments by organisms living in caves. Analogous phenotypes appear in similar environments, sometimes in response to similar constraints. Alongside randomness, a certain evolutionary determinism also exists, for instance, the selection of particular phenotypes subjected to particular environmental constraints in the “evolutionary funnel.” We pursue the idea that eco-evolutionary specialization is in some way determinist. The conceptual framework of phenotypic changes entailing specialization presented in this essay explains how evolution can be predicted. We also discuss how the predictability of evolution could be tested using the case of metabolic specialization through gene losses. We also put forward that microorganisms could be key models to test and possibly make headway evolutionary predictions and knowledge about evolution.

Next-generation physiology approaches to study microbiome function at single cell level

The function of cells in their native habitat often cannot be reliably predicted from genomic data or from physiology studies of isolates. Traditional experimental approaches to study the function of taxonomically and metabolically diverse microbiomes are limited by their destructive nature, low spatial resolution or low throughput. Recently developed technologies can offer new insights into cellular function in natural and human-made systems and how microorganisms interact with and shape the environments that they inhabit. In this Review, we provide an overview of these next-generation physiology approaches and discuss how the non-destructive analysis of cellular phenotypes, in combination with the separation of the target cells for downstream analyses, provide powerful new, complementary ways to study microbiome function. We anticipate that the widespread application of next-generation physiology approaches will transform the field of microbial ecology and dramatically improve our understanding of how microorganisms function in their native environment.

Reproduction of Large-Scale Bioreactor Conditions on Microfluidic Chips

Microbial cells in industrial large-scale bioreactors are exposed to fluctuating conditions, e.g., nutrient concentration, dissolved oxygen, temperature, and pH. These inhomogeneities can influence the cell physiology and metabolism, e.g., decelerate cell growth and product formation. Microfluidic systems offer new opportunities to study such effects in great detail by examining responses to varying environmental conditions at single-cell level. However, the possibility to reproduce large-scale bioreactor conditions in microscale cultivation systems has not yet been systematically investigated. Hence, we apply computational fluid dynamics (CFD) simulations to analyze and compare three commonly used microfluidic single-cell trapping and cultivation devices that are based on (i) mother machines (MM), (ii) monolayer growth chambers (MGC), and (iii) negative dielectrophoresis (nDEP). Several representative time-variant nutrient concentration profiles are applied at the chip entry. Responses to these input signals within the studied microfluidic devices are comparatively evaluated at the positions of the cultivated cells. The results are comprehensively presented in a Bode diagram that illustrates the degree of signal damping depending on the frequency of change in the inlet concentration. As a key finding, the MM can accurately reproduce signal changes that occur within 1 s or slower, which are typical for the environmental conditions observed by single cells in large-scale bioreactors, while faster changes are levelled out. In contrast, the nDEP and MGC are found to level out signal changes occurring within 10 s or faster, which can be critical for the proposed application.

The Role of the Host in Driving Phenotypic Heterogeneity in Salmonella

The complex infection environment within hosts exerts unique stresses across tissues and cell types, selecting for phenotypic heterogeneity in bacterial populations. Pathogens maintain variability during infection as a strategy to cope with fluctuating host immune conditions, leading to diversification of virulence phenotypes. Recent improvements in single-cell analyses have revealed that distinct bacterial subpopulations contribute unique colonization and growth strategies across infection sites. We discuss several examples of host-driven phenotypic heterogeneity in Salmonella populations throughout the course of infection, highlighting how variation in gene expression, growth rate, immune evasion, and metabolic activity contribute to overall bacterial success at the population level. We additionally focus our discussion on the implications of diversity within bacterial communities for antimicrobial efficacy.

Viability Assessment Following Anticancer Treatment Requires Single-Cell Visualization

A subset of cells within solid tumors become highly enlarged and enter a state of dormancy (sustained proliferation arrest) in response to anticancer treatment. Although dormant cancer cells might be scored as “dead” in conventional preclinical assays, they remain viable, secrete growth-promoting factors, and can give rise to progeny with stem cell-like properties. Furthermore, cancer cells exhibiting features of apoptosis (e.g., caspase-3 activation) following genotoxic stress can undergo a reversal process called anastasis and survive. Consistent with these observations, single-cell analysis of adherent cultures (solid tumor-derived cell lines with differing p53 status) has demonstrated that virtually all cells—irrespective of their size and morphology—that remain adherent to the culture dish for a long time (weeks) after treatment with anticancer agents exhibit the ability to metabolize 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl- tetrazolium bromide (MTT). The purpose of this commentary is to briefly review these findings and discuss the significance of single-cell (versus population averaged) observation methods for assessment of cancer cell viability and metabolic activity.

Go with the flow or solitary confinement: a look inside the single-cell toolbox for isolation of rare and uncultured microbes

With the vast majority of the microbial world still considered unculturable or undiscovered, microbiologists not only require more fundamental insights concerning microbial growth requirements but also need to implement miniaturized, versatile and high-throughput technologies to upscale current microbial isolation strategies. In this respect, single-cell-based approaches are increasingly finding their way to the microbiology lab. A number of recent studies have demonstrated that analysis and separation of free microbial cells by flow-based sorting as well as physical stochastic confinement of individual cells in microenvironment compartments can facilitate the isolation of previously uncultured species and the discovery of novel microbial taxa. Still, while most of these methods give immediate access to downstream whole genome sequencing, upscaling to higher cell densities as required for metabolic readouts and preservation purposes can remain challenging. Provided that these and other technological challenges are addressed in future innovation rounds, integration of single-cell tools in commercially available benchtop instruments and service platforms is expected to trigger more targeted explorations in the microbial dark matter at a depth comparable to metagenomics.

Real-time monitoring of the budding index in Saccharomyces cerevisiae batch cultivations with in situ microscopy

BACKGROUND

The morphology of yeast cells changes during budding, depending on the growth rate and cultivation conditions. A photo-optical microscope was adapted and used to observe such morphological changes of individual cells directly in the cell suspension. In order to obtain statistically representative samples of the population without the influence of sampling, in situ microscopy (ISM) was applied in the different phases of a Saccharomyces cerevisiae batch cultivation. The real-time measurement was performed by coupling a photo-optical probe to an automated image analysis based on a neural network approach.

RESULTS

Automatic cell recognition and classification of budding and non-budding cells was conducted successfully. Deviations between automated and manual counting were considerably low. A differentiation of growth activity across all process stages of a batch cultivation in complex media became feasible. An increased homogeneity among the population during the growth phase was well observable. At growth retardation, the portion of smaller cells increased due to a reduced bud formation. The maturation state of the cells was monitored by determining the budding index as a ratio between the number of cells, which were detected with buds and the total number of cells. A linear correlation between the budding index as monitored with ISM and the growth rate was found.

CONCLUSION

It is shown that ISM is a meaningful analytical tool, as the budding index can provide valuable information about the growth activity of a yeast cell, e.g. in seed breeding or during any other cultivation process. The determination of the single-cell size and shape distributions provided information on the morphological heterogeneity among the populations. The ability to track changes in cell morphology directly on line enables new perspectives for monitoring and control, both in process development and on a production scale.

Analysis of population structures of the microalga Acutodesmus obliquus during lipid production using multi-dimensional single-cell analysis

Microalgae bear a great potential to produce lipids for biodiesel, feed, or even food applications. To understand the still not well-known single-cell dynamics during lipid production in microalgae, a novel single-cell analytical technology was applied to study a well-established model experiment. Multidimensional single-cell dynamics were investigated with a non-supervised image analysis technique that utilizes data from epi-fluorescence microscopy. Reliability of this technique was successfully proven via reference analysis. The technique developed was used to determine cell size, chlorophyll amount, neutral lipid amount, and deriving properties on a single-cellular level in cultures of the biotechnologically promising alga Acutodesmus obliquus. The results illustrated a high correlation between cell size and chlorophyll amount, but a very low and dynamic correlation between cell size, lipid amount, and lipid density. During growth conditions under nitrogen starvation, cells with low chlorophyll content tend to start the lipid production first and the cell suspension differentiated in two subpopulations with significantly different lipid contents. Such quantitative characterization of single-cell dynamics of lipid synthesizing algae was done for the first time and the potential of such simple technology is highly relevant to other biotechnological applications and to deeper investigate the process of microalgal lipid accumulation.

Dark matter in host-microbiome metabolomics: Tackling the unknowns-A review

The "dark matter" in metabolomics (unknowns) represents an exciting frontier with significant potential for discovery in relation to biochemistry, yet it also presents one of the largest challenges to overcome. This focussed review takes a close look at the current state-of-the-art and future challenges in tackling the unknowns with specific focus on the human gut microbiome and host-microbe interactions. Metabolomics, like metabolism itself, is a very dynamic discipline, with many workflows and methods under development, both in terms of chemical analysis and post-analysis data processing. Here, we look at developments in the mutli-omic analyses and the use of mass spectrometry to investigate the exchange of metabolites between the host and the microbiome as well as the environment within the microbiome. A case study using HuMiX, a microfluidics-based human-microbial co-culture system that enables the co-culture of human and microbial cells under controlled conditions, is used to highlight opportunities and current limitations. Common definitions, approaches, databases and elucidation techniques from both the environmental and metabolomics fields are covered, with perspectives on how to merge these, as the boundaries blur between the fields. While reflecting on the number of unknowns remaining to be conquered in typical complex samples measured with mass spectrometry (often orders of magnitude above the "knowns"), we provide an outlook on future perspectives and challenges in elucidating the relevant "dark matter".