Saccharomyces cerevisiae biofactory to produce naringenin using a systems biology approach and a bicistronic vector expression strategy in flavonoid production.

IMPORTANCE: Flavonoids are a group of compounds generally produced by plants with proven biological activity, which have recently beeen recommended for the treatment and prevention of diseases and ailments with diverse causes. In this study, naringenin was produced in adequate amounts in yeast after in silico design. The four genes of the involved enzymes from several organisms (bacteria and plants) were multi-expressed in two vectors carrying each two genes linked by a short viral peptide sequence. The batch kinetic behavior of the product, substrate, and biomass was described at lab scale. The engineered strain might be used in a more affordable and viable bioprocess for industrial naringenin procurement.

Genome-Scale Metabolic Reconstruction, Non-Targeted LC-QTOF-MS Based Metabolomics Data, and Evaluation of Anticancer Activity of Cannabis sativa Leaf Extracts.

Over the past decades, Colombia has suffered complex social problems related to illicit crops, including forced displacement, violence, and environmental damage, among other consequences for vulnerable populations. Considerable effort has been made in the regulation of illicit crops, predominantly Cannabis sativa, leading to advances such as the legalization of medical cannabis and its derivatives, the improvement of crops, and leaving an open window to the development of scientific knowledge to explore alternative uses. It is estimated that C. sativa can produce approximately 750 specialized secondary metabolites. Some of the most relevant due to their anticancer properties, besides cannabinoids, are monoterpenes, sesquiterpenoids, triterpenoids, essential oils, flavonoids, and phenolic compounds. However, despite the increase in scientific research on the subject, it is necessary to study the primary and secondary metabolism of the plant and to identify key pathways that explore its great metabolic potential. For this purpose, a genome-scale metabolic reconstruction of C. sativa is described and contextualized using LC-QTOF-MS metabolic data obtained from the leaf extract from plants grown in the region of Pesca-Boyaca, Colombia under greenhouse conditions at the Clever Leaves facility. A compartmentalized model with 2101 reactions and 1314 metabolites highlights pathways associated with fatty acid biosynthesis, steroids, and amino acids, along with the metabolism of purine, pyrimidine, glucose, starch, and sucrose. Key metabolites were identified through metabolomic data, such as neurine, cannabisativine, cannflavin A, palmitoleic acid, cannabinoids, geranylhydroquinone, and steroids. They were analyzed and integrated into the reconstruction, and their potential applications are discussed. Cytotoxicity assays revealed high anticancer activity against gastric adenocarcinoma (AGS), melanoma cells (A375), and lung carcinoma cells (A549), combined with negligible impact against healthy human skin cells.

Omics approaches to understand cocoa processing and chocolate flavor development: A review.

The global market of chocolate has increased worldwide during the last decade and is expected to reach a value of USD 200 billion by 2028. Chocolate is obtained from different varieties of Theobroma cacao L, a plant domesticated more than 4000 years ago in the Amazon rainforest. However, chocolate production is a complex process requiring extensive post-harvesting, mainly involving cocoa bean fermentation, drying, and roasting. These steps have a critical impact on chocolate quality. Standardizing and better understanding cocoa processing is, therefore, a current challenge to boost the global production of high-quality cocoa worldwide. This knowledge can also help cocoa producers improve cocoa processing management and obtain a better chocolate. Several recent studies have been conducted to dissect cocoa processing via omics analysis. A vast amount of data has been produced regarding omics studies of cocoa processing performed worldwide. This review systematically analyzes the current data on cocoa omics using data mining techniques and discusses opportunities and gaps for cocoa processing standardization from this data. First, we observed a recurrent report in metagenomics studies of species of the fungi genus Candida and Pichia as well as bacteria from the genus Lactobacillus, Acetobacter, and Bacillus. Second, our analyzes of the available metabolomics data showed clear differences in the identified metabolites in cocoa and chocolate from different geographical origin, cocoa type, and processing stage. Finally, our analysis of peptidomics data revealed characteristic patterns in the gathered data including higher diversity and lower size distribution of peptides in fine-flavor cocoa. In addition, we discuss the current challenges in cocoa omics research. More research is still required to fill gaps in central matter in chocolate production as starter cultures for cocoa fermentation, flavor evolution of cocoa, and the role of peptides in the development of specific flavor notes. We also offer the most comprehensive collection of multi-omics data in cocoa processing gathered from different research articles.

Design and Assembly of a Biofactory for (2S)-Naringenin Production in Escherichia coli: Effects of Oxygen Transfer on Yield and Gene Expression.

The molecule (2S)-naringenin is a scaffold molecule with several nutraceutical properties. Currently, (2S)-naringenin is obtained through chemical synthesis and plant isolation. However, these methods have several drawbacks. Thus, heterologous biosynthesis has emerged as a viable alternative to its production. Recently, (2S)-naringenin production studies in Escherichia coli have used different tools to increase its yield up to 588 mg/L. In this study, we designed and assembled a bio-factory for (2S)-naringenin production. Firstly, we used several parametrized algorithms to identify the shortest pathway for producing (2S)-naringenin in E. coli, selecting the genes phenylalanine ammonia lipase (pal), 4-coumarate: CoA ligase (4cl), chalcone synthase (chs), and chalcone isomerase (chi) for the biosynthetic pathway. Then, we evaluated the effect of oxygen transfer on the production of (2S)-naringenin at flask (50 mL) and bench (4 L culture) scales. At the flask scale, the agitation rate varied between 50 rpm and 250 rpm. At the bench scale, the dissolved oxygen was kept constant at 5% DO (dissolved oxygen) and 40% DO, obtaining the highest (2S)-naringenin titer (3.11 ± 0.14 g/L). Using genome-scale modeling, gene expression analysis (RT-qPCR) of oxygen-sensitive genes was obtained.

Lipidomic profiling of bioactive lipids during spontaneous fermentations of fine-flavor cocoa.

The impact of cocoa lipid content on chocolate quality has been extensively described. Nevertheless, few studies have elucidated the cocoa lipid composition and their bioactive properties, focusing only on specific lipids. In the present study the lipidome of fine-flavor cocoa fermentation was analyzed using LC-MS-QTOF and a Machine Learning model to assess potential bioactivity was developed. Our results revealed that the cocoa lipidome, comprised mainly of fatty acyls and glycerophospholipids, remains stable during fine-flavor cocoa fermentations. Also, several Machine Learning algorithms were trained to explore potential biological activity among the identified lipids. We found that K-Nearest Neighbors had the best performance. This model was used to classify the identified lipids as bioactive or non-bioactive, nominating 28 molecules as potential bioactive lipids. None of these compounds have been previously reported as bioactive. Our work is the first untargeted lipidomic study and systematic effort to investigate potential bioactivity in fine-flavor cocoa lipids.

Theobroma cacao L. cultivar CCN 51: a comprehensive review on origin, genetics, sensory properties, production dynamics, and physiological aspects.

Many decades of improvement in cacao have aided to obtain cultivars with characteristics of tolerance to diseases, adaptability to different edaphoclimatic conditions, and higher yields. In Ecuador, as a result of several breeding programs, the clone CCN 51 was obtained, which gradually expanded through the cacao-production regions of Ecuador, Colombia, Brazil and Peru. Recognized for its high yield and adaptability to different regions and environments, it has become one of the most popular clones for breeding programs and cultivation around the world. This review aims to summarize the current evidence on the origin, genetics, morphological, volatile compounds, and organoleptic characteristics of this clone. Physiological evidence, production dynamics, and floral biology are also included to explain the high yield of CCN 51. Thus, characteristics such as osmotic adjustment, long pollen longevity, and fruit formation are further discussed and associated with high production at the end of the dry period. Finally, the impact of this popular clone on the current and future cacao industry will be discussed highlighting the major challenges for flavor enhancement and its relevance as a platform for the identification of novel genetic markers for cultivar improvement in breeding programs.

Dissecting fine-flavor cocoa bean fermentation through metabolomics analysis to break down the current metabolic paradigm.

Cocoa fermentation plays a crucial role in producing flavor and bioactive compounds of high demand for food and nutraceutical industries. Such fermentations are frequently described as a succession of three main groups of microorganisms (i.e., yeast, lactic acid, and acetic acid bacteria), each producing a relevant metabolite (i.e., ethanol, lactic acid, and acetic acid). Nevertheless, this view of fermentation overlooks two critical observations: the role of minor groups of microorganisms to produce valuable compounds and the influence of environmental factors (other than oxygen availability) on their biosynthesis. Dissecting the metabolome during spontaneous cocoa fermentation is a current challenge for the rational design of controlled fermentations. This study evaluates variations in the metabolic fingerprint during spontaneous fermentation of fine flavor cocoa through a multiplatform metabolomics approach. Our data suggested the presence of two phases of differential metabolic activity that correlate with the observed variations on temperature over fermentations: an exothermic and an isothermic phase. We observed a continuous increase in temperature from day 0 to day 4 of fermentation and a significant variation in flavonoids and peptides between phases. While the second phase, from day four on, was characterized for lower metabolic activity, concomitant with small upward and downward fluctuations in temperature. Our work is the first to reveal two phases of metabolic activity concomitant with two temperature phases during spontaneous cocoa fermentation. Here, we proposed a new paradigm of cocoa fermentation that considers the changes in the global metabolic activity over fermentation, thus changing the current paradigm based only on three main groups of microorganism and their primary metabolic products.

Dissecting industrial fermentations of fine flavour cocoa through metagenomic analysis.

The global demand for fine-flavour cocoa has increased worldwide during the last years. Fine-flavour cocoa offers exceptional quality and unique fruity and floral flavour attributes of high demand by the world's elite chocolatiers. Several studies have highlighted the relevance of cocoa fermentation to produce such attributes. Nevertheless, little is known regarding the microbial interactions and biochemistry that lead to the production of these attributes on farms of industrial relevance, where traditional fermentation methods have been pre-standardized and scaled up. In this study, we have used metagenomic approaches to dissect on-farm industrial fermentations of fine-flavour cocoa. Our results revealed the presence of a shared core of nine dominant microorganisms (i.e. Limosilactobacillus fermentum, Saccharomyces cerevisiae, Pestalotiopsis rhododendri, Acetobacter aceti group, Bacillus subtilis group, Weissella ghanensis group, Lactobacillus_uc, Malassezia restricta and Malassezia globosa) between two farms located at completely different agro-ecological zones. Moreover, a community metabolic model was reconstructed and proposed as a tool to further elucidate the interactions among microorganisms and flavour biochemistry. Our work is the first to reveal a core of microorganisms shared among industrial farms, which is an essential step to process engineering aimed to design starter cultures, reducing fermentation times, and controlling the expression of undesirable phenotypes.

New Therapeutic Candidates for the Treatment of Malassezia pachydermatis -Associated Infections.

The opportunistic pathogen Malassezia pachydermatis causes bloodstream infections in preterm infants or individuals with immunodeficiency disorders and has been associated with a broad spectrum of diseases in animals such as seborrheic dermatitis, external otitis and fungemia. The current approaches to treat these infections are failing as a consequence of their adverse effects, changes in susceptibility and antifungal resistance. Thus, the identification of novel therapeutic targets against M. pachydermatis infections are highly relevant. Here, Gene Essentiality Analysis and Flux Variability Analysis was applied to a previously reported M. pachydermatis metabolic network to identify enzymes that, when absent, negatively affect biomass production. Three novel therapeutic targets (i.e., homoserine dehydrogenase (MpHSD), homocitrate synthase (MpHCS) and saccharopine dehydrogenase (MpSDH)) were identified that are absent in humans. Notably, L-lysine was shown to be an inhibitor of the enzymatic activity of MpHCS and MpSDH at concentrations of 1 mM and 75 mM, respectively, while L-threonine (1 mM) inhibited MpHSD. Interestingly, L- lysine was also shown to inhibit M. pachydermatis growth during in vitro assays with reference strains and canine isolates, while it had a negligible cytotoxic activity on HEKa cells. Together, our findings form the bases for the development of novel treatments against M. pachydermatis infections.

Rational Design of Photo-Electrochemical Hybrid Devices Based on Graphene and Chlamydomonas reinhardtii Light-Harvesting Proteins.

Dye-sensitized solar cells (DSSCs) have been highlighted as the promising alternative to generate clean energy based on low pay-back time materials. These devices have been designed to mimic solar energy conversion processes from photosynthetic organisms (the most efficient energy transduction phenomenon observed in nature) with the aid of low-cost materials. Recently, light-harvesting complexes (LHC) have been proposed as potential dyes in DSSCs based on their higher light-absorption efficiencies as compared to synthetic dyes. In this work, photo-electrochemical hybrid devices were rationally designed by adding for the first time Leu and Lys tags to heterologously expressed light-harvesting proteins from Chlamydomonas reinhardtii, thus allowing their proper orientation and immobilization on graphene electrodes. The light-harvesting complex 4 from C. reinhardtii (LHC4) was initially expressed in Escherichia coli, purified via affinity chromatography and subsequently immobilized on plasma-treated thin-film graphene electrodes. A photocurrent density of 40.30 ± 9.26 µA/cm2 was measured on devices using liquid electrolytes supplemented with a phosphonated viologen to facilitate charge transfer. Our results suggest that a new family of graphene-based thin-film photovoltaic devices can be manufactured from rationally tagged LHC proteins and opens the possibility to further explore fundamental processes of energy transfer for biological components interfaced with synthetic materials.

Insights into the behavior of six rationally designed peptides based on Escherichia coli's OmpA at the water-dodecane interface.

The Escherichia coli's membrane protein OmpA has been identified as a potential biosurfactant due to their amphiphilic nature, and their capacity to stabilize emulsions of dodecane in water. In this study, the influence of surfactant type, concentration, preservation time and droplet size on the crystallization of n-dodecane and water, in oil-in-water emulsions stabilized with six rationally designed Escherichia coli's OmpA-based peptides was investigated. A differential scanning calorimetry (DSC) protocol was established using emulsions stabilized with Tween 20® and Tween 80®. A relationship between the surfactant concentration and the crystallization temperatures of n-dodecane and water was observed, where the crystallization temperatures seem to be dependent on the preservation time. A deconvolution analysis shows that the peak morphology possibly depends on the interactions at the interface because the enthalpic contributions of each Gaussian peak remained similar in emulsions stabilized with the same peptide. Adsorption results show that the main driver for adsorption and thus stabilization of emulsions is polar interactions (e.g. H-bonding) through the hydrophilic parts of the peptides. Those peptides with a preponderance of polar interaction groups distribution (i.e. NH2, COOH, imidazole) showed the highest interfacial activity under favorable pH conditions. This suggests that custom-made peptides whose hydrophilic/hydrophobic regions can be fine-tuned depending on the application can be easily produced with the additional advantage of their biodegradable nature.

Identification of novel genes involved in acetic acid tolerance of Saccharomyces cerevisiae using pooled-segregant RNA sequencing.

Acetic acid tolerance of the yeast Saccharomyces cerevisiae is manifested in several quantifiable parameters, of which the duration of the latency phase is one of the most studied. It has been shown recently that the latter parameter is mostly determined by a fraction of cells within the population that resumes proliferation upon exposure to acetic acid. The aim of the current study was to identify genetic determinants of the difference in this parameter between the highly tolerant strain MUCL 11987-9 and the laboratory strain CEN.PK113-7D. To this end, a combination of genetic mapping and pooled-segregant RNA sequencing was applied as a new approach. The genetic mapping data revealed four loci with a strong linkage to strain MUCL 11987-9, each containing still a large number of genes making the identification of the causal ones by traditional methods a laborious task. The genes were therefore prioritized by pooled-segregant RNA sequencing, which resulted in the identification of six genes within the identified loci showing differential expression. The relevance of the prioritized genes for the phenotype was verified by reciprocal hemizygosity analysis. Our data revealed the genes ESP1 and MET22 as two, so far unknown, genetic determinants of the size of the fraction of cells resuming proliferation upon exposure to acetic acid.

Development of a Chlamydomonas reinhardtii metabolic network dynamic model to describe distinct phenotypes occurring at different CO2 levels.

The increase in atmospheric CO2 due to anthropogenic activities is generating climate change, which has resulted in a subsequent rise in global temperatures with severe environmental impacts. Biological mitigation has been considered as an alternative for environmental remediation and reduction of greenhouse gases in the atmosphere. In fact, the use of easily adapted photosynthetic organisms able to fix CO2 with low-cost operation is revealing its high potential for industry. Among those organism, the algae Chlamydomonas reinhardtii have gain special attention as a model organism for studying CO2 fixation, biomass accumulation and bioenergy production upon exposure to several environmental conditions. In the present study, we studied the Chlamydomonas response to different CO2 levels by comparing metabolomics and transcriptomics data with the predicted results from our new-improved genomic-scale metabolic model. For this, we used in silico methods at steady dynamic state varying the levels of CO2. Our main goal was to improve our capacity for predicting metabolic routes involved in biomass accumulation. The improved genomic-scale metabolic model presented in this study was shown to be phenotypically accurate, predictive, and a significant improvement over previously reported models. Our model consists of 3726 reactions and 2436 metabolites, and lacks any thermodynamically infeasible cycles. It was shown to be highly sensitive to environmental changes under both steady-state and dynamic conditions. As additional constraints, our dynamic model involved kinetic parameters associated with substrate consumption at different growth conditions (i.e., low CO2-heterotrophic and high CO2-mixotrophic). Our results suggest that cells growing at high CO2 (i.e., photoautotrophic and mixotrophic conditions) have an increased capability for biomass production. In addition, we have observed that ATP production also seems to be an important limiting factor for growth under the conditions tested. Our experimental data (metabolomics and transcriptomics) and the results predicted by our model clearly suggest a differential behavior between low CO2-heterotrophic and high CO2-mixotrophic growth conditions. The data presented in the current study contributes to better dissect the biological response of C. reinhardtii, as a dynamic entity, to environmental and genetic changes. These findings are of great interest given the biotechnological potential of this microalga for CO2 fixation, biomass accumulation, and bioenergy production.

A synthetic multi-cellular network of coupled self-sustained oscillators.

Engineering artificial networks from modular components is a major challenge in synthetic biology. In the past years, single units, such as switches and oscillators, were successfully constructed and implemented. The effective integration of these parts into functional artificial self-regulated networks is currently on the verge of breakthrough. Here, we describe the design of a modular higher-order synthetic genetic network assembled from two independent self-sustained synthetic units: repressilators coupled via a modified quorum-sensing circuit. The isolated communication circuit and the network of coupled oscillators were analysed in mathematical modelling and experimental approaches. We monitored clustering of cells in groups of various sizes. Within each cluster of cells, cells oscillate synchronously, whereas the theoretical modelling predicts complete synchronization of the whole cellular population to be obtained approximately after 30 days. Our data suggest that self-regulated synchronization in biological systems can occur through an intermediate, long term clustering phase. The proposed artificial multicellular network provides a system framework for exploring how a given network generates a specific behaviour.

The potential of synthetic biology for improving environmental quality and human health in developing countries / Biología Sintética: un nuevo potencial para mejorar la calidad ambiental y la salud humana en países en desarrollo

ABSTRACT Environmental quality is a major factor in global health that mainly affects the poorest populations. Vector- borne diseases, climate change, pollution and unintentional poisonings are recognized as the primary causes of environmental diseases burden in developing countries. The development and implementation of new technologies to reduce the impact of these risk factors on health in developing countries is a priority in the current research. In this regard, synthetic biology, a nearly new research area, has initiated a big revolution through the de novo design or rewiring of biological components, organisms, and functions with the aim to reduce the adverse effects of environmental risk factors on human health. Despite synthetic biology is well recognized for being a multidisciplinary area where biotechnologist, biologist, physicists, mathematicians and engineers play together, its integration with public health and other social sciences seems to be of relevance to apply these technologies into a practical context. In this review, we discuss the major advances in synthetic biology with potential to improve environmental quality and human health in developing countries.

RESUMEN La calidad ambiental es reconocida como uno de los factores con mayor impacto sobre la salud humana principalmente en los países en vías de desarrollo. Las enfermedades transmitidas por vectores, el cambio climático, la contaminación y las intoxicaciones no intencionales han sido reportados como las principales causas de enfermedades ambientales en estos países. El desarrollo y la implementación de nuevas tecnologías encaminadas a reducir el impacto de estos factores ambientales en la salud es una prioridad de la investigación actual. En ese sentido, la biología sintética ha iniciado una gran revolución al permitir el diseño de novo y el mejoramiento de diversos componentes biológicos, organismos y funciones biológicas que tienen el potencial de reducir los efectos adversos de estos factores en la salud humana de una manera más eficiente y económica. A pesar de que la biología sintética es reconocida como un área multidisciplinaria donde biotecnólogos, biólogos, físicos, matemáticos e ingenieros unen sus esfuerzos, su integración con el área de la salud pública y las ciencias sociales es muy importante para llevar estas tecnologías a la práctica. En esta revisión, nosotros discutimos los más importantes avances en biología sintética y su potencial para mejorar la calidad ambiental y la salud humana en países en vías de desarrollo.

The Cytosolic pH of Individual Saccharomyces cerevisiae Cells Is a Key Factor in Acetic Acid Tolerance.

It was shown recently that individual cells of an isogenic Saccharomyces cerevisiae population show variability in acetic acid tolerance, and this variability affects the quantitative manifestation of the trait at the population level. In the current study, we investigated whether cell-to-cell variability in acetic acid tolerance could be explained by the observed differences in the cytosolic pHs of individual cells immediately before exposure to the acid. Results obtained with cells of the strain CEN.PK113-7D in synthetic medium containing 96 mM acetic acid (pH 4.5) showed a direct correlation between the initial cytosolic pH and the cytosolic pH drop after exposure to the acid. Moreover, only cells with a low initial cytosolic pH, which experienced a less severe drop in cytosolic pH, were able to proliferate. A similar correlation between initial cytosolic pH and cytosolic pH drop was also observed in the more acid-tolerant strain MUCL 11987-9. Interestingly, a fraction of cells in the MUCL 11987-9 population showed initial cytosolic pH values below the minimal cytosolic pH detected in cells of the strain CEN.PK113-7D; consequently, these cells experienced less severe drops in cytosolic pH. Although this might explain in part the difference between the two strains with regard to the number of cells that resumed proliferation, it was observed that all cells from strain MUCL 11987-9 were able to proliferate, independently of their initial cytosolic pH. Therefore, other factors must also be involved in the greater ability of MUCL 11987-9 cells to endure strong drops in cytosolic pH.

The fraction of cells that resume growth after acetic acid addition is a strain-dependent parameter of acetic acid tolerance in Saccharomyces cerevisiae.

High acetic acid tolerance of Saccharomyces cerevisiae is a relevant phenotype in industrial biotechnology when using lignocellulosic hydrolysates as feedstock. A screening of 38 S. cerevisiae strains for tolerance to acetic acid revealed considerable differences, particularly with regard to the duration of the latency phase. To understand how this phenotype is quantitatively manifested, four strains exhibiting significant differences were studied in more detail. Our data show that the duration of the latency phase is primarily determined by the fraction of cells within the population that resume growth. Only this fraction contributed to the exponential growth observed after the latency phase, while all other cells persisted in a viable but non-proliferating state. A remarkable variation in the size of the fraction was observed among the tested strains differing by several orders of magnitude. In fact, only 11 out of 10(7)  cells of the industrial bioethanol production strain Ethanol Red resumed growth after exposure to 157 mM acetic acid at pH 4.5, while this fraction was 3.6 × 10(6) (out of 10(7)  cells) in the highly acetic acid tolerant isolate ATCC 96581. These strain-specific differences are genetically determined and represent a valuable starting point to identify genetic targets for future strain improvement.