Single cell assessment of yeast metabolic engineering for enhanced lipid production using Raman and AFM-IR imaging

Exploring engineering strategies that enhance de novo production of exotic cyclopropane fatty acids in Saccharomyces cerevisiae

Cycloalkanes have broad applications as specialty fuels, lubricants, and pharmaceuticals but are not currently available from renewable sources, whereas, production of microbial cycloalkanes such as cyclopropane fatty acids (CFA) has bottlenecks. Here, a systematic investigation was undertaken into the biosynthesis of CFA in Saccharomyces cerevisiae heterologously expressing bacterial CFA synthase. The enzyme catalyzes formation of a 3-membered ring in unsaturated fatty acids. Monounsaturated fatty acids in phospholipids (PL) are the site of CFA synthesis; precursor cis-Δ9 C16 and C18 fatty acids were enhanced through OLE1 and SAM2 overexpression which enhanced CFA in PL. CFA turnover from PL to storage in triacylglycerols (TAG) was achieved by phospholipase PBL2 overexpression and acyl-CoA synthase to increase flux to TAG. Consequently, CFA storage as TAG reached 12 mg g-1 DCW, improved 3-fold over the base strain and >22% of TAG was CFA. Our research improves understanding of cycloalkane biosynthesis in yeast and offers insights into processing of other exotic fatty acids.

Quantitative Raman chemical imaging of intracellular drug-membrane aggregates and small molecule drug precipitates in cytoplasmic organelles

Raman confocal microscopes have been used to visualize the distribution of small molecule drugs within different subcellular compartments. This visualization allows the discovery, characterization, and detailed analysis of the molecular transport phenomena underpinning the Volume of Distribution - a key parameter governing the systemic pharmacokinetics of small molecule drugs. In the specific case of lipophilic small molecules with large Volumes of Distribution, chemical imaging studies using Raman confocal microscopes have revealed how weakly basic, poorly soluble drug molecules can accumulate inside cells by forming stable, supramolecular complexes in association with cytoplasmic membranes or by precipitating out within organelles. To study the self-assembly and function of the resulting intracellular drug inclusions, Raman chemical imaging methods have been developed to measure and map the mass, concentration, and ionization state of drug molecules at a microscopic, subcellular level. Beyond the field of drug delivery, Raman chemical imaging techniques relevant to the study of microscopic drug precipitates and drug-lipid complexes which form inside cells are also being developed by researchers with seemingly unrelated scientific interests. Highlighting advances in data acquisition, calibration methods, and computational data management and analysis tools, this review will cover a decade of technological developments that enable the conversion of spectral signals obtained from Raman confocal microscopes into new discoveries and information about previously unknown, concentrative drug transport pathways driven by soluble-to-insoluble phase transitions occurring within the cytoplasmic organelles of eukaryotic cells.

Morphological and lipid metabolism alterations in macrophages exposed to model environmental nanoplastics traced by high-resolution synchrotron techniques

The release of nanoplastics (NPs) in the environment is a significant health concern for long-term exposed humans. Although their usage has certainly revolutionized several application fields, at nanometer size, NPs can easily interact at the cellular level, resulting in potential harmful effects. Micro/Nanoplastics (M/NPs) have a demonstrated impact on mammalian endocrine components, such as the thyroid, adrenal gland, testes, and ovaries, while more investigations on prenatal and postnatal exposure are urgently required. The number of literature studies on the NPs' presence in biological samples is increasing. However, only a few offer a close study on the model environmental NP-immune system interaction exploited by advanced microscopy techniques. The present study highlights substantial morphological and lipid metabolism alterations in human M1 macrophages exposed to labeled polypropylene and polyvinyl chloride nanoparticles (PP and PVC NPs) (20 μg/ml). The results are interpreted by advanced microscopy techniques combined with standard laboratory tests and fluorescence microscopy. We report the accurate detection of polymeric nanoparticles doped with cadmium selenide quantum dots (CdSe-QDs NPs) by following the Se (L line) X-ray fluorescence emission peak at higher sub-cellular resolution, compared to the supportive light fluorescence microscopy. In addition, scanning transmission X-ray microscopy (STXM) imaging successfully revealed morphological changes in NP-exposed macrophages, providing input for Fourier transform infrared (FTIR) spectroscopy analyses, which underlined the chemical modifications in macromolecular components, specifically in lipid response. The present evidence was confirmed by quantifying the lipid droplet (LD) contents in PP and PVC NPs-exposed macrophages (0-100 μg/ml) by Oil Red O staining. Hence, even at experimental NPs' concentrations and incubation time, they do not significantly affect cell viability; they cause an evident lipid metabolism impairment, a hallmark of phagocytosis and oxidative stress.

Towards multi-molecular surface-enhanced infrared absorption using metal plasmonics

Surface-enhanced infrared absorption (SEIRA) leads to a largely improved detection of polar molecules, compared to standard infrared absorption. The enhancement principle is based on localized surface plasmon resonances of the substrate, which match the frequency of molecular vibrations in the analyte of interest. Therefore, in practical terms, the SEIRA sensor needs to be tailored to each specific analyte. We review SEIRA sensors based on metal plasmonics for the detection of biomolecules such as DNA, proteins, and lipids. We further focus this review on chemical SEIRA sensors, with potential applications in quality control, as well as on the improvement in sensor geometry that led to the development of multiresonant SEIRA substrates as sensors for multiple analytes. Finally, we give an introduction into the integration of SEIRA sensors with surface-enhanced Raman scattering (SERS).

Metabolic Engineering Strategies for Improved Lipid Production and Cellular Physiological Responses in Yeast Saccharomyces cerevisiae

Microbial lipids have been a hot topic in the field of metabolic engineering and synthetic biology due to their increased market and important applications in biofuels, oleochemicals, cosmetics, etc. This review first compares the popular hosts for lipid production and explains the four modules for lipid synthesis in yeast, including the fatty acid biosynthesis module, lipid accumulation module, lipid sequestration module, and fatty acid modification module. This is followed by a summary of metabolic engineering strategies that could be used for enhancing each module for lipid production. In addition, the efforts being invested in improving the production of value-added fatty acids in engineered yeast, such as cyclopropane fatty acid, ricinoleic acid, gamma linoleic acid, EPA, and DHA, are included. A discussion is further made on the potential relationships between lipid pathway engineering and consequential changes in cellular physiological properties, such as cell membrane integrity, intracellular reactive oxygen species level, and mitochondrial membrane potential. Finally, with the rapid development of synthetic biology tools, such as CRISPR genome editing tools and machine learning models, this review proposes some future trends that could be employed to engineer yeast with enhanced intracellular lipid production while not compromising much of its cellular health.

Imaging Dynamic Processes in Multiple Dimensions and Length Scales

Optical microscopy has become an invaluable tool for investigating complex samples. Over the years, many advances to optical microscopes have been made that have allowed us to uncover new insights into the samples studied. Dynamic changes in biological and chemical systems are of utmost importance to study. To probe these samples, multidimensional approaches have been developed to acquire a fuller understanding of the system of interest. These dimensions include the spatial information, such as the three-dimensional coordinates and orientation of the optical probes, and additional chemical and physical properties through combining microscopy with various spectroscopic techniques. In this review, we survey the field of multidimensional microscopy and provide an outlook on the field and challenges that may arise. Expected final online publication date for the Annual Review of Physical Chemistry, Volume 73 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Cowpea NAC Transcription Factors Positively Regulate Cellular Stress Response and Balance Energy Metabolism in Yeast via Reprogramming of Biosynthetic Pathways

Yeast is a dominant host for recombinant production of heterologous proteins, high-value biochemical compounds, and microbial fermentation. During bioprocess operations, pH fluctuations, organic solvents, drying, starvation, osmotic pressure, and often a combination of these stresses cause growth inhibition or death, markedly limiting its industrial use. Thus, stress-tolerant yeast strains with balanced energy-bioenergetics are highly desirous for sustainable improvement of quality biotechnological production. We isolated two NAC transcription factors (TFs), VuNAC1 and VuNAC2, from a wild cowpea genotype, improving both stress tolerance and growth when expressed in yeast. The GFP-fused proteins were localized to the nucleus. Y2H and reporter assay demonstrated the dimerization and transactivation abilities of the VuNAC proteins having structural folds similar to rice SNAC1. The gel-shift assay indicated that the TFs recognize an "ATGCGTG" motif for DNA-binding shared by several native TFs in yeast. The heterologous expression of VuNAC1/2 in yeast improved growth, biomass, lifespan, fermentation efficiency, and altered cellular composition of biomolecules. The transgenic strains conferred tolerance to multiple stresses such as high salinity, osmotic stress, freezing, and aluminum toxicity. Analysis of the metabolome revealed reprogramming of major pathways synthesizing nucleotides, vitamin B complex, amino acids, antioxidants, flavonoids, and other energy currencies and cofactors. Consequently, the transcriptional tuning of stress signaling and biomolecule metabolism improved the survival of the transgenic strains during starvation and stress recovery. VuNAC1/2-based synthetic gene expression control may contribute to designing robust industrial yeast strains with value-added productivity.

Recent developments in Raman spectral analysis of microbial single cells: Techniques and applications

The conventional microbial cell analyses are mostly population-averaged methods that conceal the characteristics of single-cell in the community. Single-cell analysis can provide information on the functional and structural variation of each cell, resulting in the elimination of long and tedious microbial cultivation techniques. Raman spectroscopy is a label-free, noninvasive, and in-vivo method ideal for single-cell measurement to obtain spatially resolved chemical information. In the current review, recent developments in Raman spectroscopic techniques for microbial characterization at the single-cell level are presented, focusing on Raman imaging of single cells to study the intracellular distribution of different components. The review also discusses the limitation and challenges of each technique and put forward some future outlook for improving Raman spectroscopy-based techniques for single-cell analysis. Raman spectroscopic methods at the single-cell level have potential in precision measurements, metabolic analysis, antibiotic susceptibility testing, resuscitation capability, and correlating phenotypic information to genomics for cells, the integration of Raman spectroscopy with other techniques such as microfluidics, stable isotope probing (SIP), and atomic force microscope can further improve the resolution and provide extensive information. Future focuses should be given to advance algorithms for data analysis, standardized reference libraries, and automated cell isolation techniques in future.

Quantum-enhanced nonlinear microscopy

The performance of light microscopes is limited by the stochastic nature of light, which exists in discrete packets of energy known as photons. Randomness in the times that photons are detected introduces shot noise, which fundamentally constrains sensitivity, resolution and speed¹. Although the long-established solution to this problem is to increase the intensity of the illumination light, this is not always possible when investigating living systems, because bright lasers can severely disturb biological processes^2-4. Theory predicts that biological imaging may be improved without increasing light intensity by using quantum photon correlations^1,5. Here we experimentally show that quantum correlations allow a signal-to-noise ratio beyond the photodamage limit of conventional microscopy. Our microscope is a coherent Raman microscope that offers subwavelength resolution and incorporates bright quantum correlated illumination. The correlations allow imaging of molecular bonds within a cell with a 35 per cent improved signal-to-noise ratio compared with conventional microscopy, corresponding to a 14 per cent improvement in concentration sensitivity. This enables the observation of biological structures that would not otherwise be resolved. Coherent Raman microscopes allow highly selective biomolecular fingerprinting in unlabelled specimens^6,7, but photodamage is a major roadblock for many applications^8,9. By showing that the photodamage limit can be overcome, our work will enable order-of-magnitude improvements in the signal-to-noise ratio and the imaging speed.

Effect of Selenium on the Growth and Lipid Accumulation of Yarrowia lipolytica Yeast

Nowadays, there is an increase attention on the effect of selenium (Se) on metabolic processes of microorganisms. Strains belonging to the genus of Yarrowia are of great biotechnological interest for various industries. In this study, we evaluated the effect of 10 mg/L of Se on the growth and lipid production of two Yarrowia lipolytica strains: the ACA DC 50109 and one more with increased oleagenicity, derived after ALE methodology (referred here as Y. lipolytica ALE_70). The presence of Se in the growth medium negatively affected both cell mass production and total lipid accumulation, for both Y. lipolytica strains. Fractionation of total lipids showed an inhibition on neutral lipid (NL) synthesis and consequently, an increase of polar lipids (glycolipids plus sphingolipids, and phospholipids) on the lipids of the Se-enriched ACA DC 50109 strain; however, the NL/polar ratio of the Se-enriched ALE_70 indicated that Se, apart from the inhibition of NL synthesis, provoked also the accumulation of polar lipids in this strain. In addition, the fatty acid (FA) composition was differently affected by Se. Se-enriched total lipids of the ALE_70 strain were enriched in linoleic acid (C18:2 n-6), which resulted in increase of the unsaturated index. On the other hand, Se-enriched lipids of the ACA DC 50109 strain were more saturated, as the percentage of palmitic (C16:0) and stearic (C18:0) acids increased in the total FAs. Moreover, it seems that Se influenced the activity or the expression of desaturases and elongase in both strains. Finally, the supplementation of growth medium with Se affected cell morphology, as well as the size and distribution of lipid droplets inside the yeast cells. According to our opinion, Se caused stress conditions and the consequence of that was the occurrence of metabolic disorders that affected cell mass, lipid content, and/or morphological structures. The results of the present study suggest that further research should be carried out to understand the background of the lipogenesis process in yeast cells cultured under stress conditions.

Recent advances in lipid metabolic engineering of oleaginous yeasts

With the increasing demand to develop a renewable and sustainable biolipid feedstock, several species of non-conventional oleaginous yeasts are being explored. Apart from the platform oleaginous yeast Yarrowia lipolytica, the understanding of metabolic pathway and, therefore, exploiting the engineering prospects of most of the oleaginous species are still in infancy. However, in the past few years, enormous efforts have been invested in Rhodotorula, Rhodosporidium, Lipomyces, Trichosporon, and Candida genera of yeasts among others, with the rapid advancement of engineering strategies, significant improvement in genetic tools and techniques, generation of extensive bioinformatics and omics data. In this review, we have collated these recent progresses to make a detailed and insightful summary of the major developments in metabolic engineering of the prominent oleaginous yeast species. Such a comprehensive overview would be a useful resource for future strain improvement and metabolic engineering studies for enhanced production of lipid and lipid-derived chemicals in oleaginous yeasts.

Non-invasive Raman spectroscopy for time-resolved in-line lipidomics

Oil-producing yeast cells are a valuable alternative source for palm oil production and, hence, may be one important piece of the puzzle for a more sustainable future.

Comparison between high definition FT-IR, Raman and AFM-IR for subcellular chemical imaging of cholesteryl esters in prostate cancer cells

The family of vibrational spectroscopic imaging techniques grows every few years and there is a need to compare and contrast new modalities with the better understood ones, especially in the case of demanding biological samples. Three vibrational spectroscopy techniques (high definition Fourier-transform infrared [FT-IR], Raman and atomic force microscopy infrared [AFM-IR]) were applied for subcellular chemical imaging of cholesteryl esters in PC-3 prostate cancer cells. The techniques were compared and contrasted in terms of image quality, spectral pattern and chemical information. All tested techniques were found to be useful in chemical imaging of cholesterol derivatives in cancer cells. The results obtained from FT-IR and Raman imaging showed to be comparable, whereas those achieved from AFM-IR study exhibited higher spectral heterogeneity. It confirms AFM-IR method as a powerful tool in local chemical imaging of cells at the nanoscale level. Furthermore, due to polarization effect, p-polarized AFM-IR spectra showed strong enhancement of lipid bands when compared to FT-IR.

Nanoscale AFM-IR spectroscopic imaging of lipid heterogeneity and effect of irradiation in prostate cancer cells

The recent development of the AFM-IR technique, which combines nanoscale imaging with chemical contrast through infrared spectroscopy, opened up new fields for exploration, which were out of reach for other modalities, e.g. Raman spectroscopy. Lipid droplets (LDs) are key organelles, which are associated with stress response mechanisms in cells and their size falls into that niche. LDs composition is heterogeneous and varies depending on cancer cell type and the tumor microenvironment. Prostate cancer cells show a unique lipid metabolism manifested by an increased requirement for lipid accumulation in cytosolic LDs. In the current work, AFM-IR nanoimaging was undertaken to analyze lipids in untreated and x-ray irradiated PC-3 prostate cancer cells. Cells poor in LDs showed slightly increased lipid signal in cytoplasm close to the nucleus. On the other hand, high lipid signal coming from LDs accumulation could be found in any part of the cytoplasmic region. The observed behavior was found to be independent from irradiation and its dose. According to the band assignment of the collected AFM-IR spectra, the main components of LDs were assigned to cholesteryl esters. The size of LDs present in cells poor in lipids was found to be of less than 1 μm, whereas LDs aggregates spread out over a few microns. Analysis of AFM-IR spectra shows relative homogeneity of LDs composition in single cells and heterogeneity of LDs content within the PC-3 cell population.

Comparison of malachite green adsorption by two yeast strains using Raman microspectroscopy

Malachite green (MG), as a triarylmethane compound, poses a health hazard and causes considerable environmental concern. In this work, batch biosorption experiments were conducted under different operational conditions such as pH, contact time and adsorption dose to assess the optimal parameters of MG dye removal by yeast biomass from aqueous solutions. Then, the conventional biochemical assay was used to evaluate MG removal efficiency (75.18 and 95.85%) by Saccharomyces cerevisiae and Candida utilis. In addition, Fourier-transform infrared spectroscopy in combination with Raman microspectroscopy was employed to scrutinize the differences of dye removal between two types of yeast strains. This study demonstrates that Raman microspectroscopy may serve as a useful and powerful tool to quantitatively measure the content of MG dye on yeast cell surfaces in situ, and even offer an alternative new technique to seek potentially proper adsorbents for the removal of toxic dyes from industrial effluents.

Whole-Organism Analysis by Vibrational Spectroscopy

Vibrational spectroscopy has contributed to the understanding of biological materials for many years. As the technology has advanced, the technique has been brought to bear on the analysis of whole organisms. Here, we discuss advanced and recently developed infrared and Raman spectroscopic instrumentation to whole-organism analysis. We highlight many of the recent contributions made in this relatively new area of spectroscopy, particularly addressing organisms associated with disease with emphasis on diagnosis and treatment. The application of vibrational spectroscopic techniques to entire organisms is still in its infancy, but new developments in imaging and chemometric processing will likely expand in the field in the near future.

Raman spectroscopy as a tool for tracking cyclopropane fatty acids in genetically engineered Saccharomyces cerevisiae

Cyclopropane fatty acids (CFAs) are a group of lipids with unique physical and chemical properties between those of saturated and monounsaturated fatty acids. The distinctive physicochemical characteristics of CFAs (e.g. oxidative stability, self-polymerization at high temperatures, etc.) results from the presence of a cyclopropane ring within their structure making them highly useful in industrial applications. CFAs are present in several species of plants and bacteria and are typically detected with standard lipid profiling techniques, such as gas or liquid chromatography. In this work we investigated several strains of S. cerevisiae, genetically modified to introduce the production of CFAs, in comparison to control strain using confocal Raman spectroscopy (CRS). The aim of our work was to demonstrate the potential of CRS not only to detect changes introduced due to the CFAs presence, but also to track CFAs within the cells. We present for the first time Raman and IR spectra of CFA standard (cis-9,10-methyleneoctadecanoic acid), completed with quantum chemical calculations and band assignment. We identified marker bands of CFA (e.g. 2992, 1222, 942 cm-1) attributed to the vibrations of the cyclopropyl ring. Furthermore, we analysed lipid bodies (LBs) from modified and control yeast using CRS imaging and identified multiple changes in size, number and composition of LBs from engineered strains. We observed a significant reduction in the degree of unsaturation of LBs using the ratio of bands located at 1660 cm-1 (ν(C[double bond, length as m-dash]C)) and 1448 cm-1 (δ(CH2)) in the modified cell lines. In addition, we were able to detect the presence of CFAs in LBs, using the established marker bands. CRS shows tremendous potential as technique to identify CFAs in lipid bodies providing a new way to track lipid production in genetically modified single yeast cells.

Visualizing wax ester fermentation in single Euglena gracilis cells by Raman microspectroscopy and multivariate curve resolution analysis

BACKGROUND

Global demand for energy is on the rise at a time when limited natural resources are fast depleting. To address this issue, microalgal biofuels are being recommended as a renewable and eco-friendly substitute for fossil fuels. Euglena gracilis is one such candidate that has received special interest due to their ability to synthesize wax esters that serve as precursors for production of drop-in jet fuel. However, to realize economic viability and achieve industrial-scale production, development of novel methods to characterize algal cells, evaluate its culture conditions, and construct appropriate genetically modified strains is necessary. Here, we report a Raman microspectroscopy-based method to visualize important metabolites such as paramylon and ester during wax ester fermentation in single Euglena gracilis cells in a label-free manner.

RESULTS

We measured Raman spectra to obtain intracellular biomolecular information in Euglena under anaerobic condition. First, by univariate approach, we identified Raman markers corresponding to paramylon/esters and constructed their time-lapse chemical images. However, univariate analysis is severely limited in its ability to obtain detailed information as several molecules can contribute to a Raman band. Therefore, we further employed multivariate curve resolution analysis to obtain chain length-specific information and their abundance images of the produced esters. Accumulated esters in Euglena were particularly identified to be myristyl myristate (C28), a wax ester candidate suitable to prepare drop-in jet fuel. Interestingly, we found accumulation of two different forms of myristyl myristate for the first time in Euglena through our exploratory multivariate analysis.

CONCLUSIONS

We succeeded in visualizing molecular-specific information in Euglena during wax ester fermentation by Raman microspectroscopy. It is obvious from our results that simple univariate approach is insufficient and that multivariate curve resolution analysis is crucial to extract hidden information from Raman spectra. Even though we have not measured any mutants in this study, our approach is directly applicable to other systems and is expected to deepen the knowledge on lipid metabolism in microalgae, which eventually leads to new strategies that will help to enhance biofuel production efficiency in the future.

Correlated Materials Characterization via Multimodal Chemical and Functional Imaging

Multimodal chemical imaging simultaneously offers high-resolution chemical and physical information with nanoscale and, in select cases, atomic resolution. By coupling modalities that collect physical and chemical information, we can address scientific problems in biological systems, battery and fuel cell research, catalysis, pharmaceuticals, photovoltaics, medicine, and many others. The combined systems enable the local correlation of material properties with chemical makeup, making fundamental questions of how chemistry and structure drive functionality approachable. In this Review, we present recent progress and offer a perspective for chemical imaging used to characterize a variety of samples by a number of platforms. Specifically, we present cases of infrared and Raman spectroscopies combined with scanning probe microscopy; optical microscopy and mass spectrometry; nonlinear optical microscopy; and, finally, ion, electron, and probe microscopies with mass spectrometry. We also discuss the challenges associated with the use of data originated by the combinatorial hardware, analysis, and machine learning as well as processing tools necessary for the interpretation of multidimensional data acquired from multimodal studies.

Enhanced Production of High-Value Cyclopropane Fatty Acid in Yeast Engineered for Increased Lipid Synthesis and Accumulation

The unique strained ring structure in cyclopropane fatty acids (CFA) conveys oxidative stability and lubricity to lipids. These attributes are highly valuable for industrial applications such as cosmetics and specialist lubrication but there is currently no commercial source of the lipid. Here, built on recently engineered strains of Saccharomyces cerevisiae, the authors have developed an efficient strategy for CFA production. Expression of the Escherichia coli cyclopropane fatty acid synthetase (Ec.CFAS) in the engineered yeast resulted in formation of cis-9,10-methylene-hexadecanoic and octadecanoic acids in both the phospholipid (PL) and triacylglycerol (TAG) fractions. CFA concentration in TAG of engineered yeast is 12 mg CFA g^-1 DCW (fourfold above the strain expressing CFAS only). The yield of CFA increases from 13.2 to 68.3 mg L^-1 , the highest reported in yeast, using a two-stage bioprocess strategy that separated cell growth from the lipid modification stage. Strategies for further improvement of this valuable lipid are proposed.