Yeast

Course-based undergraduate research experiences (CUREs) are widely recognized as a high-impact practice in biology education, yet most existing CURE frameworks treat the research organism as an interchangeable teaching prop rather than a genuine scientific contribution. We argue that place-based, community-embedded CUREs - in which students isolate, characterize, and publicly deploy a locally meaningful wild organism - constitute a qualitatively distinct model warranting broader adoption. As proof of concept, we present the Declaration of Fermentation project at Indiana University Bloomington: graduate researchers isolated a wild Saccharomyces cerevisiae strain from the bark of a campus landmark tree, confirmed its wild provenance by whole-genome sequencing and phylogenomics, and partnered with local craft breweries to produce a colonial-era inspired ale released publicly for the 250th anniversary of the Declaration of Independence. Volunteer sensory panels at two independent public tasting events (combined n = 33-34 per attribute) confirmed a fruity-funky profile consistent with wild-strain fermentation, with no significant differences between events (Mann-Whitney U, Benjamini-Hochberg-corrected p > 0.05 for all 11 attributes). We describe three design principles - genomically confirmed strain identity, mandatory community partnership, and place-based historical narrative - that distinguish this model from prior wild yeast brewing CUREs, discuss how these principles generalize to other institutions and fermentation vehicles, and identify next steps for formal learning assessment. Complete implementation protocols are provided as supplemental Appendices 1-6, and the bioinformatics pipeline is freely available at https://doi.org/10.5281/zenodo.20679384.

The yeast secreted proteome plays critical biological roles and influences product and production parameters in industrial fermentation. Systematic profiling of the response of the yeast secretome to intrinsic and extrinsic factors is therefore essential for understanding these functions and for optimizing manufacturing processes. Here, we characterized the yeast secretome under diverse proteosynthetic stress conditions, including glycosylation deficiency, oxidative, reductive, and thermal stresses. The secretome was predominantly composed of conventionally secreted proteins, while a subset of proteins appeared to be secreted via unconventional pathways. Distinct secretome profiles were observed in response to different stressors, driven by a combination of altered intracellular proteomes, altered canonical secretion, and altered cell lysis and unconventional protein secretion, while reflecting the underlying metabolic state of the cells. Heat stress did not impact protein glycosylation but did cause similar protein misfolding stress to N-glycosylation deficiency. Intriguingly, canonically intracellular chaperone BiP was abundant in the secretome in particular stress conditions where its activity would be beneficial. BiP interacted with probable extracellular client proteins in vitro, consistent with it acting as a functional extracellular chaperone/holdase in conditions such as reductive stress in which client proteins could be misfolded outside the cell.

Sinking marine particles is a key process regulating carbon export through the biological carbon pump, yet direct measurements of sinking dynamics remain limited in many coastal environments. One barrier is that most existing approaches require expensive instrumentation and large research platforms. Here, we present a low-cost, modular method for concentrating fast-sinking particles and measuring their individual sinking velocities under controlled conditions. This combines large settling tanks (110 L) for field-based particle fractionation with a video-based tracking system that quantifies the sinking behavior of natural marine particles. The particle sinking speed chamber is surrounded on three sides by a temperature-controlled water chamber, minimizing the problem of advection during measurements. The post-processing Python script delivers sinking velocity, particle size, circularity, and RGB-based properties for large numbers of particles. The method accuracy was validated using reference beads with known theoretical sinking velocities derived from Stokes law. Field deployments in the Baltic Sea demonstrated successful enrichment of fast-sinking particles and stable operation from both a research vessel and a small boat. Compared to existing methods, the approach substantially reduces logistical and financial barriers while maintaining particle-resolved measurements and compatibility with complementary biogeochemical analyses. This enables a broader observational coverage of sinking particle processes across environments that are currently underrepresented in carbon export studies.

Protein homeostasis - i.e., proteostasis - is the biological process by which the qualitative and quantitative balance of the proteome is conducted, either by preserving functionally relevant proteins or by degrading unnecessary ones. Stress conditions can modulate cellular proteostasis in order to promote cytoprotection and preserve the viability of living organisms. Among the cellular pathways already described that can play an important role in preserving biological functions by modulating proteostasis are the heat shock response and the ribosome quality control pathways. In this work, we show that the Rqc1p protein is necessary for the thermoadaptation of S. cerevisiae to heat shock, as RQC1-deficient yeast is sensitive to elevated temperatures. In silico approaches - such as multiple sequence alignment, structural analysis, and molecular dynamics simulations - confirmed earlier predictions that Rqc1p shares characteristics with the bHLH family of proteins. We also verified, through computational prediction of sub-cellular localization, that S. cerevisiae Rqc1p contains nuclear localization signals, suggesting that this protein can potentially be translocated toward the nucleus, thereby broadening its current range of recognized biological functions in this organism. Also, analysis of yeast transcriptomes subjected to heat shock showed that Rqc1p mRNA levels do not fluctuate in response to heat shock, suggesting that cellular concentrations of Rqc1p are already at optimal levels to elicit a rapid and effective response during thermal stress in S. cerevisiae.

Genetically identical cells grown in the same environment show variation in gene expression known as expression noise. Expression noise can be heritable and impact fitness, making it subject to natural selection. Increasing expression noise for the Saccharomyces cerevisiae TDH3 gene was shown to be beneficial in glucose-based media when mean TDH3 expression was far from the fitness optimum but deleterious when it was close to this optimum. Here, we show that growth on different carbon sources alters the effects of new mutations on TDH3 expression noise and examine the fitness effects of changing expression noise. In galactose-based media, we observed the same relationship between expression noise and fitness seen in glucose-based media, but in glycerol- and ethanol-based media, we observed the opposite relationship or no significant relationship, respectively. Using simulations of single-cell organisms, we found that these differences were most likely explained by environment-specific relationships between gene expression and fitness. We also found that, far from the optimum, the fitness effects of noise were greatest when expression was highly heritable between mother and daughter cells. The empirical observations and simulations reported in this study show how environments influence both the production of expression noise and its impacts on fitness.

Cancer, one of the worlds leading causes of death, is characterized by a complex metabolic reprogramming that features the Warburg effect as one of its hallmarks. The Warburg effect involves increased glucose and amino acid metabolism, which promotes tumor proliferation and progression. Although cancer has historically been attributed to genetic mutations, recent studies suggest a possible metabolic origin. However, a key characteristic of cancer cells is their greater adaptability than normal cells, as evidenced by their resistance to chemotherapy, which stems from their high mutability. This underscores the need to examine the relationship between metabolic reprogramming and cancer development from both metabolic and evolutionary perspectives. In this context, Saccharomyces cerevisiae snf1{Delta} strain has emerged as an ideal cellular model for studying the Warburg effect. This study aimed to determine whether deletion of the SNF1 gene in S. cerevisiae affects its chronological aging and competitiveness in a glucose and amino acid-dependent manner. Herein, we provide evidence that the snf1{Delta} strain changes the chronological aging depending on nutrimental condition, under low-nutrient levels shortens (0.1% glucose + 0.1x amino acids), and increases under high-nutrient levels (5% glucose + 3x amino acids). Competitiveness of the snf1{Delta} strain in co-cultivation with wild-type was also improved in 5% glucose + 3x amino acids, by approximately 2 Log10. These results indicate that snf1{Delta} strain aging and competitiveness are also sensitive to nutrimental status, as was observed in cancer cells.

Microbial metabolism can be represented as an energy-conserving process (catabolism) and a biomass-forming reaction (anabolism). Anabolism is traditionally measured through the turbidity of the culture, while catabolism is often assessed by the substrates consumed or the products formed. Standard measurements of biomass and products are intrusive and disrupt cultivation and headspace composition, potentially masking important analytical parameters and interactions. Online pressure and backscatter were combined in small-scale closed batch vials to obtain undisturbed real-time measurements of catabolic and anabolic rates, enabling mapping of metabolic phases throughout an entire batch cultivation cycle. The method identified discrete metabolic phases in yeast cultivation and thermophilic syngas fermentation. In nutrient-rich yeast cultivation, five metabolic phases were characterized, covering growth-associated and non-growth-associated gas formation. In a mixed community syngas fermentation, estimates of catabolic and anabolic rates distinguished early biomass increase from minimal net pressure change from two later gas-driven phases. An initial phase with a higher growth rate, linked to carboxydotrophy, followed by a phase with slightly lower growth and increased gas consumption, corresponding to hydrogenotrophic acetogenesis. The study demonstrates that a simple, affordable experimental setup with online pressure and backscatter measurements can be used to visualize phase-plane mapping of microbial metabolism. An additional advantage is the ability to detect sequential metabolic cascades in mixed microbial communities, which is not possible with gas-sparging bioreactor studies. Using a single simple batch culture, growth and maintenance data can be obtained, even when growth is low or absent, thereby yielding parameters applicable to phenotypic characterization and dynamic metabolic modelling.

Metabolomics enables the profiling of small-molecule metabolites and thereby captures the biochemical state of a living organism at a given moment and enables to monitor its cellular responses to stimuli. This technique has become a powerful tool in pharmaceutical research, the food industry, and microbial research. Metabolomics aims to obtain an unbiased metabolic profile; however, this is complicated by compound instability, complex and often extensive sample processing, and nonlinear responses in mass spectrometry. Therefore, correcting for metabolite loss and mass spectrometry-related artifacts is essential, typically achieved through relative quantification against an isotopically labelled internal standard for each metabolite of interest. This article describes how to produce 13C-labelled yeast extract and its use as internal standard for metabolomics. More specifically, it provides step-by-step protocols for the fed-batch fermentation, quenching, metabolite extraction, and LC-MS and GC-MS characterization of the internal standard. It also includes a protocol explaining how to use the internal standard for the quantification of metabolites in yeast samples.

Chitosan is an oligosaccharide derived from chitin that is protonated at acidic pH to form a polycation. Its positive charge promotes the interaction with negatively charged components of the yeast cell surface, which has been associated with increased cell permeability and growth inhibition. In this study, we investigated the interaction of chitosan with the cell surface and its permeabilizing capacity in three yeast species displaying distinct susceptibility profiles, Saccharomyces cerevisiae, Candida albicans and Debaryomyces hansenii. We evaluated the correlation between differential susceptibility and chitosan association at the cell surface, as well as cell permeabilization, by integrating growth analyses with surface-binding assays, including FITC-conjugated chitosan to monitor surface association and cellular integration over time, and ultrastructural examination by transmission electron microscopy (TEM). Our results showed that chitosan exhibited varying effects on the growth and permeability of each yeast strain, with D. hansenii being the most susceptible. Furthermore, we observed the incorporation of chitosan onto the cell surface and confirmed its role as a permeabilizing agent. Finally, we used chitosan-induced permeabilization as a method to measure the activity of selected enzymes in situ, demonstrating its potential for studying metabolic functions in permeabilized yeast cells. Overall, our findings establish chitosan as a strain-dependent antifungal agent and a useful tool for functional biochemical analyses in yeast.

Yeast responding to acute stress reallocate cellular resources, in part via the Environmental Stress Response (ESR) that induces stress-defense genes while repressing ribosome-biogenesis and growth genes. The purpose and regulation of coordinated induction and repression is incompletely understood, but both responses are influenced by ESR transcription factors Msn2 and Msn4 (Msn2/4). Here we used single-cell microscopy and transcriptomic analysis to investigate the role of upstream regulator Pde2 in ESR regulation and post-stress fitness. Loss of PDE2 weakened and shortened Msn2 activation following salt stress and produced muted induction of Msn2/4 targets, similar to a msn2{triangleup}msn4{triangleup} strain. In contrast, Pde2 had at most a minor impact on ESR repressor Dot6, yet was important for repression of its targets beyond Msn2/4 influence. Consistent with our recent resource-reallocation model, pde2{triangleup} cells had normal or faster post-stress growth rates, despite weaker activation of the ESR. We discuss implications for ESR regulation and function.

Automated platforms such as Chi.Bio enable simultaneous monitoring of optical density and fluorescent reporter expression in 20 ml reactor cultures with controllable pump systems. As such, they provide an appealing option for contemporary gene expression quantification, quantitative physiology, and laboratory evolution and ecology experiments. While optical density calibration for this device is well established, no equivalent calibration framework exists for fluorescence, making quantitative comparison with reference instruments unreliable. Here, we characterize Chi.Bio fluorescence capabilities using fluorescent calibration microspheres and fixed GFP-expressing S. cerevisiae and E. coli cells, compared with orthogonal plate-reader measurements. We show that microsphere fluorescence is detectable and scales linearly with concentration, whereas the GFP signal from both species falls below the device detection limit. Comparison of background-correction strategies indicates that direct subtraction of a non-fluorescent control measured within the same device yields more reliable fluorescence estimates than the commonly used on-line normalization method. Knowledge of these sensitivity boundaries of the device provides practical guidelines for experimental design of future studies.

Globally, heat waves (HWs) have become more frequent, intense, and prolonged, with extreme temperatures that reduce quality or result in crop loss in wine grapes. Irrigation prior to or during HWs is one of the most common means of mitigating damage to vines and berries. However, the effect of this practice on flavonoids is not well established. Red wine quality is directly impacted by phenolics, including anthocyanins and proanthocyanidins (PAs). This study was conducted over three vintages (2019-2021) in a commercial vineyard to evaluate the impact of supplemental irrigation - applied before and during HWs - on winegrape chemistry in Cabernet Sauvignon. Results demonstrated that supplemental irrigation significantly reduced anthocyanin loss compared to a control treatment maintained at 60% evapotranspiration (ET), and that pre-HW irrigation can mitigate some of the deleterious effects on classes of flavonoids important to red wine quality. Furthermore, applying excessive water (3x, or 180% ET) had no additional beneficial effects on flavonoids relative to a moderate supplemental application (2x, or 120% ET).

Endosymbiosis is widespread throughout the tree of life. Understanding how the transition of a bacterial endosymbiont from facultative to host-dependent obligate life occurs is an important question for defining the origin of endosymbiosis. A novel gram-positive bacillus, Brevibacillus sp. TJ4 was isolated from the nitrogen-fixing yeast Rhodotorula mucilaginosa JGTA-S1, which houses several endobacteria within its cells. TJ4 can survive independently of yeast but exhibits genomic and metabolic features characteristic of an evolving endosymbiont, slowly assuming a host-dependent, obligate lifestyle. The TJ4 genome contains several incomplete pathways for carbohydrate, amino acid, vitamin, and cofactor metabolism, which is reflected in its increased reliance on host-derived nutrients and auxotrophy compared with that of other Brevibacillus spp. Comparative genomics revealed widespread genome rearrangements, loss of synteny, and multiple cross-genus and inter-kingdom horizontal gene transfer (HGT) events in TJ4 compared to other Brevibacillus spp. These HGTs include the acquisition of genes from bacteriophages and co-resident endobacteria of JGTA-S1. One such horizontally acquired gene, Type II 3-dehydroquinate dehydratase (AroQ), appears to have originated from the Rhodotorula host itself. This acquisition functionally restores the shikimate pathway in strain TJ4, as evidenced by the phylogenetic placement of AroQ from TJ4 within the clade of fungal AroQ homologs. Potential exploitation of the host JGTA-S1 appears to be a probable mode of endosymbiosis of TJ4, an evolving endosymbiont that we named Brevibacillus rhodotorulae sp. nov.

Lipid peroxidation (LPO) is widely used as a biomarker of oxidative stress in coral bleaching research, yet its measurement remains poorly standardized across the field. A systematic review of the coral LPO literature reveals substantial variation in methodological approaches, including tissue fraction analysis, lysis protocols, assay choice, and normalization metrics, confounding cross-study comparison and obscuring the biological interpretation of results. We experimentally investigate two key sources of variation: the use of bulk holobiont vs separated host and algal symbiont fractions, and the choice of normalization metric. To do so, we used Montastraea cavernosa (n = 6 colonies) exposed to ambient (28C), heat stress (30.5C), and heat stress + artificial upwelling (AU; heat stress intermitted by daily pulses of cooler water, 30.5/27.5C) conditions in a controlled mesocosm experiment. Using a TBARS-based MDA assay with a lysis buffer optimized for coral tissue, we measured LPO separately in coral host and algal symbiont fractions across four time points throughout the day. Host MDA remained stable across all treatments and time points, consistent with either sufficient antioxidant buffering capacity or thermal acclimation over the experimental period. Algal symbiont MDA, in contrast, exhibited pronounced diel and treatment-specific dynamics, and the two fractions responses were decoupled from one another. Normalizing MDA to coral surface area instead of total protein content produced largely consistent diel and treatment patterns, but the two metrics diverged at specific time points, indicating that normalization choice is not interchangeable and can itself affect interpretation. Together, our literature review and empirical results demonstrate that host and algal symbiont LPO dynamics are not comparable when aggregated and argue for host-symbiont fraction separation and consistent, explicitly reported normalization as minimum standards for interpretable and cross-comparable coral LPO measurement.

Whole-genome sequencing identifies focal DNA amplifications with base-pair resolution but cannot determine whether amplified sequences reside on extrachromosomal DNA (ecDNA, also known as double minutes) or within chromosomally integrated homogeneously staining regions (HSRs). DNA fluorescence in situ hybridization (DNA-FISH) metaphase spreads remain the gold standard for distinguishing these amplification states at single-cell resolution. Here, we present a detailed protocol for DNA-FISH metaphase spreads using human cancer cell lines, encompassing cell culture, metaphase arrest, hypotonic treatment, fixation, chromosome spreading, fluorescent probe hybridization, and fluorescence imaging. The protocol incorporates intermediate quality-control steps to verify successful chromosome dispersion and optimize metaphase spread quality, making the workflow accessible to laboratories without specialized cytogenetics expertise. Results demonstrate clear visualization of ecDNA and HSR amplification states using locus-specific probes and illustrate common technical artifacts that can affect interpretation. This protocol provides a robust and reproducible approach for studying the structural organization of oncogene amplification in cancer cells.

Gene-by-environment (GxE) interactions play a major role in shaping both phenotypic and molecular variation, with important implications for human health and disease. In this study, we used the Doxycycline (Dox) regulated, tetracycline-responsive (Tet-Off) promoter system to sequentially reduce or titrate gene expression levels of the essential yeast transcription factor Repressor Activator Protein 1 (RAP1) similar to a hypomorph allele series, across three distinct environments: Yeast Peptone Dextrose (YPD) media, YPD media with Heat Shock (HS), and Yeast Peptone Acetate (YPAC) media. We then performed RNA sequencing (RNA Seq) to assess global transcriptional responses to RAP1 reduction in these different growth environments. Our analysis first focused on the independent effects of varying RAP1 expression levels within and across environments. We then explored GxE interactions, revealing a subset of genes with significant consequences of reduced levels of RAP1 and environment-specific expression patterns. Notably, many genes exhibited opposite effects of RAP1 titration on gene expression when yeast were grown in YPAC media compared to YPD media and/or HS, suggesting environment-dependent regulatory architecture. This design reveals how cells integrate internal transcriptional and regulatory changes with external environmental cues, providing a deeper view of GxE architecture. Using Weighted Gene Co-expression Network Analysis (WGCNA), we identified co-regulated gene modules, and by combining this with transcription factor motif enrichment tests, our study identified candidate regulators driving their dynamics. Our findings demonstrate that gene regulatory networks can vary dramatically depending on the environmental context an organism experiences, which can then influence the specific phenotypes produced by a particular genetic perturbation. This illustrates the complexity of genotype-environment interactions and the importance of studying gene function in multiple environments to gain a truly comprehensive understanding of a genes sometimes numerous and diverse functions.

LC/MS-based food lipidomics provides detailed information on intact lipid species, but the resulting datasets are often difficult to translate into concepts directly useful for food quality, processing, nutritional profiling and authenticity assessment. Here, we present Lipid Food Profile (LFP), a module of the LipidOne platform designed to convert annotated LC/MS lipidomics data into interpretable food-relevant lipid indices. LFP applies an in silico hydrolysis strategy to reconstruct acyl, alkyl and alkenyl chains from intact lipid species while preserving their lipid-class origin. The reconstructed information is then summarized into index categories related to food lipid quality, compositional balance, omega balance, oxidative stability, chain remodelling and ether-linked chain contribution. The interpretative value of LFP was evaluated using three published food lipidomics datasets addressing different analytical questions: X-ray-induced lipid remodelling in Chlorella vulgaris, spatial lipid heterogeneity in Mugil cephalus bottarga, and geographical-origin assessment of camel milk. Across these case studies, LFP recovered the main conclusions of the original lipidomics investigations, including treatment-associated lipid remodelling, inner-outer layer differences in bottarga and regional variation in camel milk. Importantly, LFP reorganized these findings into a smaller number of food-oriented indices, providing additional information on saturation balance, oxidative susceptibility, chain architecture and classification potential. Overall, LFP provides an interpretative layer for LC/MS food lipidomics that complement conventional fatty-acid analysis and molecular-species-based interpretation. By translating complex lipidomic tables into structured lipid index profiles, the module may support more accessible and chemically meaningful analysis of food composition, processing effects, lipid quality and exploratory traceability applications. LFP is freely accessible through the LipidOne web platform (LipidOne.eu). HighlightsO_LILipid Food Profile translates LC/MS food lipidomics into interpretable lipid indices. C_LIO_LIThe workflow preserves chain and lipid-class information without chemical hydrolysis. C_LIO_LIPublished case studies show that LFP recovers and extends previous interpretations. C_LIO_LILFP supports food quality, processing and exploratory origin/authenticity assessment. C_LIO_LIThe module complements conventional fatty-acid analysis and molecular lipidomics. C_LI

SummaryBiological growth curves are widely used but inconsistently analyzed due to fragmented workflows and limited quality control. We present growthcurves, a Python package for extracting growth parameters, and two open-source web applications, MicroGrowth and AutoGrowth, that combine automated fitting with interactive, human-in-the-loop inspection, selective refitting and traceable export for microplate reader and mini-bioreactor datasets in batch or turbidostat cultivation mode. Availability and Implementationgrowthcurves is implemented in Python and is freely available to non-commercial users at [https://github.com/biosustain/growthcurves.git] and through PyPI at [https://pypi.org/project/growthcurves/]. MicroGrowth and AutoGrowth are available at [https://biosustain.github.io/growthcurves_app/], and their source code is available at [https://github.com/biosustain/growthcurves_app.git]. Documentation, installation instructions, example datasets and tutorials are available at [https://growthcurves.readthedocs.io/en/latest/]. Contactstefdon@dtu.dk; cargac@dtu.dk Supplementary InformationSupplementary information and Supplementary Methods are available online.

Listeria monocytogenes causes listeriosis in humans and animals and contaminates prepared food by attaching to food processing environments. Therefore, closer monitoring of how the organism adheres to surfaces will help identify ways to prevent it from colonising food-processing environments. To develop new attachment assays, clinical and environmental strains of L. monocytogenes were transformed by inserting a plasmid containing lux, gfp reporter genes and an erythromycin-resistant gene into the parent cells. Transformed cells were grown for 48 hours on brain heart infusion agar plates containing 1-5{micro}g/ml of erythromycin, after which the cells were viewed under a molecular light imager and luminometer. Fluorescent cells containing the gfp, lux, and erythromycin-resistant genes were visible, whereas control cells without the plasmid were not. Transformation efficiency was highest with the environmental strains, and subsequent growth and hydrophobicity tests carried out with the transformed cells in different growth conditions showed that they were able to attach well to solvents when compared to the parent cells. However, the growth rate of the transformed cells was poor, indicating a disruption of cell metabolism. Results show the possibility of real-time monitoring of how cells attach to different surfaces and could lead to a better understanding of the initial colonisation of a surface by the organism.

Quantitative assessment of cellular oxidative stress requires simultaneous measurement of intracellular redox state and extracellular respiratory activity, yet integrated sensing approaches remain limited. Here, we present a dual-fluorescent sensing platform combining a genetically encoded redox biosensor (roGFP2{square}Tsa2{Delta}CR) with an optical oxygen sensor embedded in microwell plates for parallel, non-invasive quantification of intracellular reactive oxygen species (ROS) and oxygen consumption rates (OCR) in industrial yeast systems. The roGFP2-based sensor was stably expressed in Saccharomyces cerevisiae (S. cerevisiae) and Yarrowia lipolytica (Y. lipolytica), enabling dynamic monitoring of oxidative stress at population, single-cell, and subcellular levels, while oxygen-sensitive films provided real-time respiration measurements. Using this platform, we identified distinct redox-respiration phenotypes between the two yeasts. Crabtree-positive S. cerevisiae exhibited low OCR and mitochondrial ROS during glucose cultivation, whereas growth on glycerol increased OCR and mitochondrial ROS by ~2.5-fold and 12%, respectively. In contrast, the obligate respiratory yeast Y. lipolytica displayed 3-fold higher OCR and 16% lower mitochondrial ROS than respiring S. cerevisiae, indicating differences in respiratory oxidative burden. Antimycin A treatment reduced OCR by 60% in respiring S. cerevisiae while increasing mitochondrial ROS by 35%, whereas Y. lipolytica showed greater resistance to respiratory and oxidative perturbations. By integrating intracellular redox sensing with extracellular oxygen measurements, this platform enables quantitative coupling of redox state and respiration in living cells. The approach provides a scalable framework for evaluating cellular fitness, stress tolerance, and metabolic state in biomanufacturing and synthetic biology.