High-throughput single-cell analysis for the proteomic dynamics study of the yeast osmotic stress response

Quantitative Characterization of Gene Regulatory Circuits Associated With Fungal Secondary Metabolism to Discover Novel Natural Products

Microbial genetic circuits are vital for regulating gene expression and synthesizing bioactive compounds. However, assessing their strength and timing, especially in multicellular fungi, remains challenging. Here, an advanced microfluidic platform is combined with a mathematical model enabling precise characterization of fungal gene regulatory circuits (GRCs) at the single-cell level. Utilizing this platform, the expression intensity and timing of 30 transcription factor-promoter combinations derived from two representative fungal GRCs, using the model fungus Aspergillus nidulans are determined. As a proof of concept, the selected GRC combination is utilized to successfully refactor the biosynthetic pathways of bioactive molecules, precisely control their production, and activate the expression of the silenced biosynthetic gene clusters (BGCs). This study provides insights into microbial gene regulation and highlights the potential of platform in fungal synthetic biology applications and the discovery of novel natural products.

Instantaneous extracellular solution exchange for concurrent evaluation of membrane permeability of single cells

The osmotic stress imposed on microorganisms by hypotonic conditions is perceived to regulate water and solute flux via cell membranes, which are crucial for survival. Some cells that fail to perceive osmotic stress die because this results in the rupture of the cell membrane. The flux through the membrane is characterized by the membrane permeability, which is measured using a stopped-flow apparatus in response to a millisecond-order osmolarity change. However, the obtained data are an ensemble average of each cell response. Additionally, the measurement of permeability, considering cellular viability, contributes to a more accurate evaluation of osmoadaptation. Here, we present a novel on-chip instantaneous extracellular solution exchange method using an air-liquid interface. The presented method provides a concurrent evaluation at the single-cell level in response to a millisecond-order osmotic shock, considering cellular viability by solution exchange. This method utilizes a liquid bridge with a locally formed droplet on the surface of a micropillar fabricated inside a microchannel. We evaluated a solution exchange time of 3.6 ms and applied this method to Synechocystis PCC 6803 under two different osmolarity conditions. The live/dead ratio of 1 M to 0.5 M osmotic down shock condition was 78.8/21.2% while that of 1 M to 0.25 M osmotic down shock condition was 40.0/60.0%. We evaluated the water permeability of two groups: cells that were still live before and after osmotic shock (hereafter named cell type 1), and cells that were live before but were dead 10 minutes after osmotic shock (hereafter named cell type 2). The results indicated that the water permeability of cell type 2 was higher than that of cell type 1. The results obtained using the presented methods confirmed that the effect of osmotic stress can be accurately evaluated using single-cell analysis.

Food yeasts: occurrence, functions, and stress tolerance in the brewing of fermented foods

With the rapid development of systems biology technology, there is a deeper understanding of the molecular biological mechanisms and physiological characteristics of microorganisms. Yeasts are widely used in the food industry with their excellent fermentation performances. While due to the complex environments of food production, yeasts have to suffer from various stress factors. Thus, elucidating the stress mechanisms of food yeasts and proposing potential strategies to improve tolerance have been widely concerned. This review summarized the recent signs of progress in the variety, functions, and stress tolerance of food yeasts. Firstly, the main food yeasts occurred in fermented foods, and the taxonomy levels are demonstrated. Then, the main functions of yeasts including aroma enhancer, safety performance enhancer, and fermentation period reducer are discussed. Finally, the stress response mechanisms of yeasts and the strategies to improve the stress tolerance of cells are reviewed. Based on sorting out these related recent researches systematically, we hope that this review can provide help and approaches to further exert the functions of food yeasts and improve food production efficiency.

Two-Layered Microfluidic Devices for High-Throughput Dynamic Analysis of Synthetic Gene Circuits in E. coli

Escherichia coli is a common chassis for synthetic gene circuit studies. In addition to the dose-response of synthetic gene circuits, the analysis of dynamic responses is also an important part of the future design of more complicated synthetic systems. Recently, microfluidic-based methods have been widely used for the analysis of gene expression dynamics. Here, we established a two-layered microfluidic platform for the systematic characterization of synthetic gene circuits (eight strains in eight different culture environments could be observed simultaneously with a 5 min time resolution). With this platform, both dose responses and dynamic responses with a high temporal resolution could be easily derived for further analysis. A controlled environment ensures the stability of the bacterial growth rate, excluding changes in gene expression dynamics caused by changes of the growth dilution rate. The precise environmental switch and automatic micrograph shooting ensured that there was nearly no time lag between the inducer addition and the data recording. We studied four four-node incoherent-feedforward-loop (IFFL) networks with different operators using this device. The experimental results showed that as the effect of inhibition increased, two of the IFFL networks generated pulselike dynamic gene expressions in the range of the inducer concentrations, which was different from the dynamics of the two other circuits with only a simple pattern of rising to the platform. Through fitting the dose-response curves and the dynamic response curves, corresponding parameters were derived and introduced to a simple model that could qualitatively explain the generation of pulse dynamics.

The regulatory mechanism of the yeast osmoresponse under different glucose concentrations

Cells constantly respond to environmental changes by modulating gene expression programs. These responses may demand substantial costs and, thus, affect cell growth. Understanding the regulation of these processes represents a key question in biology and biotechnology. Here, we studied the responses to osmotic stress in glucose-limited environments. By analyzing seventeen osmotic stress-induced genes and stress-activated protein kinase Hog1, we found that cells exhibited stronger osmotic gene expression response and larger integral of Hog1 nuclear localization during adaptation to osmotic stress under glucose-limited conditions than under glucose-rich conditions. We proposed and verified that in glucose-limited environment, glycolysis intermediates (representing "reserve flux") were limited, which required cells to express more glycerol-production enzymes for stress adaptation. Consequently, the regulatory mechanism of osmoresponse was derived in the presence and absence of such reserve flux. Further experiments suggested that this reserve flux-dependent stress-defense strategy may be a general principle under nutrient-limited environments.

Microfluidic-Enabled Multi-Cell-Densities-Patterning and Culture Device for Characterization of Yeast Strains’ Growth Rates under Mating Pheromone

Yeast studies usually focus on exploring diversity in terms of a specific trait (such as growth rate, antibiotic resistance, or fertility) among extensive strains. Microfluidic chips improve these biological studies in a manner of high throughput and high efficiency. For a population study of yeast, it is of great significance to set a proper initial cell density for every strain under specific circumstances. Herein, we introduced a novel design of chip, which enables users to load cells in a gradient order (six alternatives) of initial cell density within one channel. We discussed several guidelines to choose the appropriate chamber to ensure successful data recording. With this chip, we successfully studied the growth rate of yeast strains under a mating response, which is crucial for yeasts to control growth behaviors for prosperous mating. We investigated the growth rate of eight different yeast strains under three different mating pheromone levels (0.3 μM, 1 μM, and 10 μM). Strains with, even, a six-fold in growth rate can be recorded, with the available data produced simultaneously. This work has provided an efficient and time-saving microfluidic platform, which enables loading cells in a pattern of multi-cell densities for a yeast population experiment, especially for a high-throughput study. Besides, a quantitatively analyzed growth rate of different yeast strains shall reveal inspiring perspectives for studies concerning yeast population behavior with a stimulated mating pheromone.

Yeast cell fate control by temporal redundancy modulation of transcription factor paralogs

Recent single-cell studies have revealed that yeast stress response involves transcription factors that are activated in pulses. However, it remains unclear whether and how these dynamic transcription factors temporally interact to regulate stress survival. Here we show that budding yeast cells can exploit the temporal relationship between paralogous general stress regulators, Msn2 and Msn4, during stress response. We find that individual pulses of Msn2 and Msn4 are largely redundant, and cells can enhance the expression of their shared targets by increasing their temporal divergence. Thus, functional redundancy between these two paralogs is modulated in a dynamic manner to confer fitness advantages for yeast cells, which might feed back to promote the preservation of their redundancy. This evolutionary implication is supported by evidence from Msn2/Msn4 orthologs and analyses of other transcription factor paralogs. Together, we show a cell fate control mechanism through temporal redundancy modulation in yeast, which may represent an evolutionarily important strategy for maintaining functional redundancy between gene duplicates.

Age-dependent decline in stress response capacity revealed by proteins dynamics analysis

The aging process is regarded as the progressive loss of physiological integrity, leading to impaired biological functions and the increased vulnerability to death. Among various biological functions, stress response capacity enables cells to alter gene expression patterns and survive when facing internal and external stresses. Here, we explored changes in stress response capacity during the replicative aging of Saccharomyces cerevisiae. To this end, we used a high-throughput microfluidic device to deliver intermittent pulses of osmotic stress and tracked the dynamic changes in the production of downstream stress-responsive proteins, in a large number of individual aging cells. Cells showed a gradual decline in stress response capacity of these osmotic-related downstream proteins during the aging process after the first 5 generations. Among the downstream stress-responsive genes and unrelated genes tested, the residual level of response capacity of Trehalose-6-Phosphate Synthase (TPS2) showed the best correlation with the cell remaining lifespan. By monitor dynamics of the upstream transcription factors and mRNA of Tps2, it was suggested that the decline in downstream stress response capacity was caused by the decline of translational rate of these proteins during aging.

Metabolic cost of rapid adaptation of single yeast cells

Cells can rapidly adapt to changing environments through nongenetic processes; however, the metabolic cost of such adaptation has never been considered. Here we demonstrate metabolic coupling in a remarkable, rapid adaptation process (1 in 1,000 cells adapt per hour) by simultaneously measuring metabolism and division of thousands of individual Saccharomyces cerevisiae cells using a droplet microfluidic system: droplets containing single cells are immobilized in a two-dimensional (2D) array, with osmotically induced changes in droplet volume being used to measure cell metabolism, while simultaneously imaging the cells to measure division. Following a severe challenge, most cells, while not dividing, continue to metabolize, displaying a remarkably wide diversity of metabolic trajectories from which adaptation events can be anticipated. Adaptation requires a characteristic amount of energy, indicating that it is an active process. The demonstration that metabolic trajectories predict a priori adaptation events provides evidence of tight energetic coupling between metabolism and regulatory reorganization in adaptation. This process allows S. cerevisiae to adapt on a physiological timescale, but related phenomena may also be important in other processes, such as cellular differentiation, cellular reprogramming, and the emergence of drug resistance in cancer.

Robotic Cell Printing for Constructing Living Yeast Cell Microarrays in Microfluidic Chips

Living cell microarrays in microfluidic chips allow the non-invasive multiplexed molecular analysis of single cells. Here, we developed a simple and affordable perfusion microfluidic chip containing a living yeast cell array composed of a population of cell variants (green fluorescent protein (GFP)-tagged Saccharomyces cerevisiae clones). We combined mechanical patterning in 102 microwells and robotic piezoelectric cell dispensing in the microwells to construct the cell arrays. Robotic yeast cell dispensing of a yeast collection from a multiwell plate to the microfluidic chip microwells was optimized. The developed microfluidic chip and procedure were validated by observing the growth of GFP-tagged yeast clones that are linked to the cell cycle by time-lapse fluorescence microscopy over a few generations. The developed microfluidic technology has the potential to be easily upscaled to a high-density cell array allowing us to perform dynamic proteomics and localizomics experiments.

Genome-scale transcriptional dynamics and environmental biosensing

Genome-scale technologies have enabled mapping of the complex molecular networks that govern cellular behavior. An emerging theme in the analyses of these networks is that cells use many layers of regulatory feedback to constantly assess and precisely react to their environment. The importance of complex feedback in controlling the real-time response to external stimuli has led to a need for the next generation of cell-based technologies that enable both the collection and analysis of high-throughput temporal data. Toward this end, we have developed a microfluidic platform capable of monitoring temporal gene expression from over 2,000 promoters. By coupling the "Dynomics" platform with deep neural network (DNN) and associated explainable artificial intelligence (XAI) algorithms, we show how machine learning can be harnessed to assess patterns in transcriptional data on a genome scale and identify which genes contribute to these patterns. Furthermore, we demonstrate the utility of the Dynomics platform as a field-deployable real-time biosensor through prediction of the presence of heavy metals in urban water and mine spill samples, based on the the dynamic transcription profiles of 1,807 unique Escherichia coli promoters.

Applications of Microfluidics in Quantitative Biology

Quantitative biology is dedicated to taking advantage of quantitative reasoning and advanced engineering technologies to make biology more predictable. Microfluidics, as an emerging technique, provides new approaches to precisely control fluidic conditions on small scales and collect data in high-throughput and quantitative manners. In this review, the authors present the relevant applications of microfluidics to quantitative biology based on two major categories (channel-based microfluidics and droplet-based microfluidics), and their typical features. We also envision some other microfluidic techniques that may not be employed in quantitative biology right now, but have great potential in the near future.