Explorative characterization and taxonomy-aligned comparison of alterations in lipids and other biomolecules in Antarctic bacteria grown at different temperatures.

Temperature significantly impacts bacterial physiology, metabolism and cell chemistry. In this study, we analysed lipids and the total cellular biochemical profile of 74 fast-growing Antarctic bacteria grown at different temperatures. Fatty acid diversity and temperature-induced alterations aligned with bacterial classification-Gram-groups, phylum, genus and species. Total lipid content, varied from 4% to 19% of cell dry weight, was genus- and species-specific. Most bacteria increased lipid content at lower temperatures. The effect of temperature on the profile was complex and more species-specific, while some common for all bacteria responses were recorded. Gram-negative bacteria adjusted unsaturation and acyl chain length. Gram-positive bacteria adjusted methyl branching (anteiso-/iso-), chain length and unsaturation. Fourier transform infrared spectroscopy analysis revealed Gram-, genus- and species-specific changes in the total cellular biochemical profile triggered by temperature fluctuations. The most significant temperature-related alterations detected on all taxonomy levels were recorded for mixed region 1500-900 cm-1 , specifically the band at 1083 cm-1 related to phosphodiester groups mainly from phospholipids (for Gram-negative bacteria) and teichoic/lipoteichoic acids (for Gram-positive bacteria). Some changes in protein region were detected for a few genera, while the lipid region remained relatively stable despite the temperature fluctuations.

Raman spectroscopy online monitoring of biomass production, intracellular metabolites and carbon substrates during submerged fermentation of oleaginous and carotenogenic microorganisms.

BACKGROUND: Monitoring and control of both growth media and microbial biomass is extremely important for the development of economical bioprocesses. Unfortunately, process monitoring is still dependent on a limited number of standard parameters (pH, temperature, gasses etc.), while the critical process parameters, such as biomass, product and substrate concentrations, are rarely assessable in-line. Bioprocess optimization and monitoring will greatly benefit from advanced spectroscopy-based sensors that enable real-time monitoring and control. Here, Fourier transform (FT) Raman spectroscopy measurement via flow cell in a recirculatory loop, in combination with predictive data modeling, was assessed as a fast, low-cost, and highly sensitive process analytical technology (PAT) system for online monitoring of critical process parameters. To show the general applicability of the method, submerged fermentation was monitored using two different oleaginous and carotenogenic microorganisms grown on two different carbon substrates: glucose fermentation by yeast Rhodotorula toruloides and glycerol fermentation by marine thraustochytrid Schizochytrium sp. Additionally, the online FT-Raman spectroscopy approach was compared with two at-line spectroscopic methods, namely FT-Raman and FT-infrared spectroscopies in high throughput screening (HTS) setups. RESULTS: The system can provide real-time concentration data on carbon substrate (glucose and glycerol) utilization, and production of biomass, carotenoid pigments, and lipids (triglycerides and free fatty acids). Robust multivariate regression models were developed and showed high level of correlation between the online FT-Raman spectral data and reference measurements, with coefficients of determination (R2) in the 0.94-0.99 and 0.89-0.99 range for all concentration parameters of Rhodotorula and Schizochytrium fermentation, respectively. The online FT-Raman spectroscopy approach was superior to the at-line methods since the obtained information was more comprehensive, timely and provided more precise concentration profiles. CONCLUSIONS: The FT-Raman spectroscopy system with a flow measurement cell in a recirculatory loop, in combination with prediction models, can simultaneously provide real-time concentration data on carbon substrate utilization, and production of biomass, carotenoid pigments, and lipids. This data enables monitoring of dynamic behaviour of oleaginous and carotenogenic microorganisms, and thus can provide critical process parameters for process optimization and control. Overall, this study demonstrated the feasibility of using FT-Raman spectroscopy for online monitoring of fermentation processes.

Sparse wavelengths data in mid-infrared spectroscopy: Modelling approaches and channel sampling.

Infrared instruments with smaller and cost-effective components such as bandpass filters, single channel detectors, and laser-based light sources are being developed to provide cheaper and faster analysis of biological samples. Such instruments often provide measurements in form of sparse data, which include a collection of single-frequency channels or a collection of channels covering very narrow spectral ranges, called here multi-frequency channels. To keep costs low, the number of channels needs to be kept at a minimum. However, modelling and preprocessing of sparse data needs enough channels to perform the task. The aim of this study therefore was to understand the effect of channels sampling on data modelling results and find optimal modelling algorithm for different type of sparse data. The sparse data was simulated using Fourier Transform Infrared spectra of milk and fungi. Regression models were established to predict fatty acid composition by partial least squares regression (PLSR), multiple linear regression (MLR) and random forest (RF) methods. We observe that PLSR algorithm is very well suited for sparse data such as multi-frequency channels: excellent calibration models were obtained with only three channels comprising three wavenumbers each. The results were comparable to results obtained with full spectra. MLR and RF in turn provided similarly good results using data with single-frequency channels requiring nine channels in total.

Production of docosahexaenoic acid from spruce sugars using Aurantiochytrium limacinum.

In this study lignocellulosic sugars from Norway spruce were used for production of docosahexaenoic acid (DHA) by the marine thraustochytrid Aurantiochytrium limacinum SR21. Enzymatically prepared spruce hydrolysate was combined with a complex nitrogen source and different amounts of salts. Shake flask batch cultivations revealed that addition of extra salts was not needed for optimal growth. Upscaling to fed-batch bioreactors yielded up to 55 g/L cell dry mass and a total fatty acid content of 44% (w/w) out of which 1/3 was DHA. Fourier transform infrared spectroscopy was successfully applied as a rapid method for monitoring lipid accumulation in A. limacinum SR21. Thus, this proof-of-principle study clearly demonstrates that crude spruce hydrolysates can be directly used as a novel and sustainable resource for production of DHA.

Towards high-throughput screening (HTS) of polyhydroxyalkanoate (PHA) production via Fourier transform infrared (FTIR) spectroscopy of Halomonas sp. R5-57 and Pseudomonas sp. MR4-99.

High-throughput screening (HTS) methods for characterization of microbial production of polyhydroxyalkanoates (PHA) are currently under investigated, despite the advent of such systems in related fields. In this study, phenotypic microarray by Biolog PM1 screening of Halomonas sp. R5-57 and Pseudomonas sp. MR4-99 identified 49 and 54 carbon substrates to be metabolized by these bacteria, respectively. Growth on 15 (Halomonas sp. R5-57) and 14 (Pseudomonas sp. MR4-99) carbon substrates was subsequently characterized in 96-well plates using medium with low nitrogen concentration. Bacterial cells were then harvested and analyzed for putative PHA production using two different Fourier transform infrared spectroscopy (FTIR) systems. The FTIR spectra obtained from both strains contained carbonyl-ester peaks indicative of PHA production. Strain specific differences in the carbonyl-ester peak wavenumber indicated that the PHA side chain configuration differed between the two strains. Confirmation of short chain length PHA (scl-PHA) accumulation in Halomonas sp. R5-57 and medium chain length PHA (mcl-PHA) in Pseudomonas sp. MR4-99 was done using Gas Chromatography-Flame Ionization Detector (GC-FID) analysis after upscaling to 50 mL cultures supplemented with glycerol and gluconate. The strain specific PHA side chain configurations were also found in FTIR spectra of the 50 mL cultures. This supports the hypothesis that PHA was also produced in the cells cultivated in 96-well plates, and that the HTS approach is suitable for analysis of PHA production in bacteria. However, the carbonyl-ester peaks detected by FTIR are only indicative of PHA production in the small-scale cultures, and appropriate calibration and prediction models based on combining FTIR and GC-FID data needs to be developed and optimized by performing more extensive screenings and multivariate analyses.

High-throughput vibrational spectroscopy methods for determination of degree of acetylation for chitin and chitosan.

The rising demand for chitin and chitosan in chemical, agro-food, and healthcare industries is creating a need for rapid and high-throughput analysis. The physicochemical properties of these biopolymers are greatly dependent on the degree of acetylation (DA). Conventional methods for DA determination, such as LC-MS and 1H NMR, are time-consuming when performed on many samples, and therefore efficient methods are needed. Here, high-throughput microplate-based FTIR and FT-Raman methods were compared with their manual counterparts. Partial least squares regression models were based on 30 samples of chitin and chitosan with reference DA values obtained by LC-MS and 1H NMR, and the models were validated on an independent test set of 16 samples. The overall predictive accuracy of the high-throughput methods was at the same level as the manual methods and the well-established LC-MS and 1H NMR methods. Therefore, high-throughput FTIR and FT-Raman DA determination methods have great potential to serve as fast and economical substitutes for traditional methods.

Optimizing extraction solvents for deoxynivalenol analysis in maize via infrared attenuated total reflection spectroscopy and chemometric methods.

Farmers, cereal suppliers and processors demand rapid techniques for the assessment of mould-associated contamination. Deoxynivalenol (DON) is among the most important Fusarium toxins and related to human and animal diseases besides causing significant economic losses. Routine analytical techniques for the analysis of DON are either based on chromatographic or immunoanalytical techniques, which are time-consuming and frequently rely on hazardous consumables. The present study evaluates the feasibility of infrared attenuated total reflection spectroscopy (IR-ATR) for the analysis of maize extracts via different solvents optimized for the determination of DON contamination along the regulatory requirements by the European Union (EU) for unprocessed maize (1750 µg kg-1). Reference analysis was done by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). The studied maize samples were either naturally infected or had been artificially inoculated in the field with Fusarium graminearum, Fusarium culmorum or Fusarium verticillioides. Principal component analysis demonstrated that water and methanol-water (70 : 30% v) were optimum solvents for differentiating DON contamination levels. Supervised partial least squares discriminant analysis resulted in excellent classification accuracies of 86.7% and 90.8% for water and methanol-water extracts, respectively. The IR spectra of samples with fungal infection and high DON contamination had distinct spectral features, which could be related to carbohydrates, proteins and lipid content within the investigated extracts.

Isolation, Physiological Characterization, and Antibiotic Susceptibility Testing of Fast-Growing Bacteria from the Sea-Affected Temporary Meltwater Ponds in the Thala Hills Oasis (Enderby Land, East Antarctica).

In this study, for the first time, we report the identification and characterization of culturable fast-growing bacteria isolated from the sea-affected temporary meltwater ponds (MPs) in the East Antarctica area of the Vecherny region (-67.656317, 46.175058) of the Thala Hills Oasis, Enderby Land. Water samples from the studied MPs showed alkaline pH (from 8.0 to 10.1) and highly varied total dissolved solids (86-94,000 mg/L). In total, twenty-nine bacterial isolates were retrieved from the studied MPs. The phylogenetic analysis based on 16S rRNA gene sequence similarities showed that the isolated bacteria belong to the phyla Proteobacteria, Actinobacteria, Firmicutes, and Bacteroidetes and the twelve genera Pseudomonas, Shewanella, Acinetobacter, Sporosarcina, Facklamia, Carnobacterium, Arthrobacter, Brachybacterium, Micrococcus, Agrococcus, Leifsonia, and Flavobacterium. Most of the isolated bacteria were psychrotrophs and showed the production of one or more extracellular enzymes. Lipolytic and proteolytic activities were more prevalent among the isolates. Five isolates from the Actinobacteria phylum and one isolate from the Bacteroidetes phylum had strong pigmentation. Antibiotic susceptibility testing revealed that most of the isolates are resistant to at least one antibiotic, and seven isolates showed multi-resistance.

Temperature- and Nutrients-Induced Phenotypic Changes of Antarctic Green Snow Bacteria Probed by High-Throughput FTIR Spectroscopy.

Temperature fluctuations and nutrient composition are the main parameters influencing green snow microbiome. In this study we investigated the influence of temperature and nutrient conditions on the growth and cellular chemical profile of bacteria isolated from green snow. Chemical profiling of the green snow bacteria was done by high-throughput FTIR spectroscopy combined with multivariate data analysis. We showed that temperature and nutrients fluctuations strongly affect growth ability and chemical profile of the green snow bacteria. The size of colonies for green snow bacteria grown at higher (25 °C) and lower (4 °C and 10 °C) than optimal temperature (18 °C) was smaller. All isolates grew on rich medium, and only 19 isolates were able to grow on synthetic minimal media. Lipid and mixed spectral regions showed to be phylogeny related. FTIR fingerprinting indicates that lipids are often affected by the temperature fluctuations. Growth on different media resulted in the change of the whole chemical profile, where lipids showed to be more affected than proteins and polysaccharides. Correlation analysis showed that nutrient composition is clearly strongly influencing chemical changes in the cells, followed by temperature.

SmdA is a Novel Cell Morphology Determinant in Staphylococcus aureus.

Cell division and cell wall synthesis in staphylococci need to be precisely coordinated and controlled to allow the cell to multiply while maintaining its nearly spherical shape. The mechanisms ensuring correct placement of the division plane and synthesis of new cell wall have been studied intensively. However, hitherto unknown factors and proteins are likely to play key roles in this complex interplay. Here, we identified and investigated a protein with a major influence on cell morphology in Staphylococcus aureus. The protein, named SmdA (for staphylococcal morphology determinant A), is a membrane protein with septum-enriched localization. By CRISPRi knockdown and overexpression combined with different microscopy techniques, we demonstrated that proper levels of SmdA were necessary for cell division, including septum formation and cell splitting. We also identified conserved residues in SmdA that were critical for its functionality. Pulldown and bacterial two-hybrid interaction experiments showed that SmdA interacted with several known cell division and cell wall synthesis proteins, including penicillin-binding proteins (PBPs) and EzrA. Notably, SmdA also affected susceptibility to cell wall targeting antibiotics, particularly in methicillin-resistant S. aureus (MRSA). Together, our results showed that S. aureus was dependent on balanced amounts of membrane attached SmdA to carry out proper cell division. IMPORTANCE Staphylococcus aureus is an important human and animal pathogen. Antibiotic resistance is a major problem in the treatment of staphylococcal infections, and cell division and cell wall synthesis factors have previously been shown to modulate susceptibility to antibiotics in this species. Here, we investigated the function of a protein named SmdA, which was identified based on its septal localization and knockdown phenotype resulting in defective cellular morphologies. We demonstrated that this protein was critical for normal cell division in S. aureus. Depletion of SmdA sensitized resistant staphylococci to ß-lactam antibiotics. This work revealed a new staphylococcal cell division factor and a potential future target for narrow-spectrum antimicrobials or compounds to resensitize antibiotic-resistant staphylococcal strains.

The Use of Constituent Spectra and Weighting in Extended Multiplicative Signal Correction in Infrared Spectroscopy.

Extended multiplicative signal correction (EMSC) is a widely used preprocessing technique in infrared spectroscopy. EMSC is a model-based method favored for its flexibility and versatility. The model can be extended by adding constituent spectra to explicitly model-known analytes or interferents. This paper addresses the use of constituent spectra and demonstrates common pitfalls. It clarifies the difference between analyte and interferent spectra, and the importance of orthogonality between model spectra. Different normalization approaches are discussed, and the importance of weighting in the EMSC is demonstrated. The paper illustrates how constituent analyte spectra can be estimated, and how they can be used to extract additional information from spectral features. It is shown that the EMSC parameters can be used in both regression tasks and segmentation tasks.

Mucoromycota fungi as powerful cell factories for modern biorefinery.

Biorefinery employing fungi can be a strategy for valorizing low-cost rest materials, by-products and wastes into several valuable bioproducts through the fungal fermentation. Mucoromycota fungi are soil fungi with a highly versatile metabolic system that positions them as powerful microbial cell factories for biorefinery applications. Lipids, pigments, chitin/chitosan, polyphosphates, ethanol, organic acids and enzymes are main Mucoromycota products that can be refined from the fermentation process and applied in nutrition, chemical or biofuel industries. In addition, Mucoromycota biomass can be used as it is for specific purposes, such as feed. Mucoromycota fungi can be employed in developing co-production processes, whereby several intra- and extracellular products are simultaneously formed in a single fermentation process, and, thus, economic viability of the process can be improved. This mini review provides a comprehensive overview over the recent advances in the production of valuable metabolites by Mucoromycota fungi and fermentation strategies which could be potentially applied in the industrial biorefinery settings. KEY POINTS: • Biorefineries utilizing Mucoromycota fungi as production cell factories can provide a wide range of bioproducts. • Mucoromycota fungi are able to perform co-production of various metabolites in a single fermentation process. • Versatile metabolism of Mucoromycota allows valorization of a various low-cost substrates such as wastes and rest materials.

Deep learning-enabled Inference of 3D molecular absorption distribution of biological cells from IR spectra.

Infrared spectroscopy delivers abundant information about the chemical composition, as well as the structural and optical properties of intact samples in a non-destructive manner. We present a deep convolutional neural network which exploits all of this information and solves full-wave inverse scattering problems and thereby obtains the 3D optical, structural and chemical properties from infrared spectroscopic measurements of intact micro-samples. The proposed model encodes scatter-distorted infrared spectra and infers the distribution of the complex refractive index function of concentrically spherical samples, such as many biological cells. The approach delivers simultaneously the molecular absorption, sample morphology and effective refractive index in both the cell wall and interior from a single measured spectrum. The model is trained on simulated scatter-distorted spectra, where absorption in the distinct layers is simulated and the scatter-distorted spectra are estimated by analytic solutions of Maxwell's equations for samples of different sizes. This allows for essentially real-time deep learning-enabled infrared diffraction micro-tomography, for a large subset of biological cells.

A robust metabolomics approach for the evaluation of human embryos from in vitro fertilization.

The identification of the most competent embryos for transfer to the uterus constitutes the main challenge of in vitro fertilization (IVF). We established a metabolomic-based approach by applying Fourier transform infrared (FTIR) spectroscopy on 130 samples of 3-day embryo culture supernatants from 26 embryos that implanted and 104 embryos that failed. On examining the internal structure of the data by unsupervised multivariate analysis, we found that the supernatant spectra of nonimplanted embryos constituted a highly heterogeneous group. Whereas ∼40% of these supernatants were spectroscopically indistinguishable from those of successfully implanted embryos, ∼60% exhibited diverse, heterogeneous metabolic fingerprints. This observation proved to be the direct result of pregnancy's multifactorial nature, involving both intrinsic embryonic traits and external characteristics. Our data analysis strategy thus involved one-class modelling techniques employing soft independent modelling of class analogy that identified deviant fingerprints as unsuitable for implantation. From these findings, we could develop a noninvasive Fourier-transform-infrared-spectroscopy-based approach that represents a shift in the fundamental paradigm for data modelling applied in assisted-fertilization technologies.

Assessment of Biotechnologically Important Filamentous Fungal Biomass by Fourier Transform Raman Spectroscopy.

Oleaginous filamentous fungi can accumulate large amount of cellular lipids and biopolymers and pigments and potentially serve as a major source of biochemicals for food, feed, chemical, pharmaceutical, and transport industries. We assessed suitability of Fourier transform (FT) Raman spectroscopy for screening and process monitoring of filamentous fungi in biotechnology. Six Mucoromycota strains were cultivated in microbioreactors under six growth conditions (three phosphate concentrations in the presence and absence of calcium). FT-Raman and FT-infrared (FTIR) spectroscopic data was assessed in respect to reference analyses of lipids, phosphorus, and carotenoids by using principal component analysis (PCA), multiblock or consensus PCA, partial least square regression (PLSR), and analysis of spectral variation due to different design factors by an ANOVA model. All main chemical biomass constituents were detected by FT-Raman spectroscopy, including lipids, proteins, cell wall carbohydrates, and polyphosphates, and carotenoids. FT-Raman spectra clearly show the effect of growth conditions on fungal biomass. PLSR models with high coefficients of determination (0.83-0.94) and low error (approximately 8%) for quantitative determination of total lipids, phosphates, and carotenoids were established. FT-Raman spectroscopy showed great potential for chemical analysis of biomass of oleaginous filamentous fungi. The study demonstrates that FT-Raman and FTIR spectroscopies provide complementary information on main fungal biomass constituents.

Rhodotorula kratochvilovae CCY 20-2-26-The Source of Multifunctional Metabolites.

Multifunctional biomass is able to provide more than one valuable product, and thus, it is attractive in the field of microbial biotechnology due to its economic feasibility. Carotenogenic yeasts are effective microbial factories for the biosynthesis of a broad spectrum of biomolecules that can be used in the food and feed industry and the pharmaceutical industry, as well as a source of biofuels. In the study, we examined the effect of different nitrogen sources, carbon sources and CN ratios on the co-production of intracellular lipids, carotenoids, ß-glucans and extracellular glycolipids. Yeast strain R. kratochvilovae CCY 20-2-26 was identified as the best co-producer of lipids (66.7 ± 1.5% of DCW), exoglycolipids (2.42 ± 0.08 g/L), ß-glucan (11.33 ± 1.34% of DCW) and carotenoids (1.35 ± 0.11 mg/g), with a biomass content of 15.2 ± 0.8 g/L, by using the synthetic medium with potassium nitrate and mannose as a carbon source. It was shown that an increased C/N ratio positively affected the biomass yield and production of lipids and ß-glucans.

Oleaginous yeasts respond differently to carbon sources present in lignocellulose hydrolysate.

BACKGROUND: Microbial oils, generated from lignocellulosic material, have great potential as renewable and sustainable alternatives to fossil-based fuels and chemicals. By unravelling the diversity of lipid accumulation physiology in different oleaginous yeasts grown on the various carbon sources present in lignocellulose hydrolysate (LH), new targets for optimisation of lipid accumulation can be identified. Monitoring lipid formation over time is essential for understanding lipid accumulation physiology. This study investigated lipid accumulation in a variety of oleaginous ascomycetous and basidiomycetous strains grown in glucose and xylose and followed lipid formation kinetics of selected strains in wheat straw hydrolysate (WSH). RESULTS: Twenty-nine oleaginous yeast strains were tested for their ability to utilise glucose and xylose, the main sugars present in WSH. Evaluation of sugar consumption and lipid accumulation revealed marked differences in xylose utilisation capacity between the yeast strains, even between those belonging to the same species. Five different promising strains, belonging to the species Lipomyces starkeyi, Rhodotorula glutinis, Rhodotorula babjevae and Rhodotorula toruloides, were grown on undiluted wheat straw hydrolysate and lipid accumulation was followed over time, using Fourier transform-infrared (FTIR) spectroscopy. All five strains were able to grow on undiluted WSH and to accumulate lipids, but to different extents and with different productivities. R. babjevae DVBPG 8058 was the best-performing strain, accumulating 64.8% of cell dry weight (CDW) as lipids. It reached a culture density of 28 g/L CDW in batch cultivation, resulting in a lipid content of 18.1 g/L and yield of 0.24 g lipids per g carbon source. This strain formed lipids from the major carbon sources in hydrolysate, glucose, acetate and xylose. R. glutinis CBS 2367 also consumed these carbon sources, but when assimilating xylose it consumed intracellular lipids simultaneously. Rhodotorula strains contained a higher proportion of polyunsaturated fatty acids than the two tested Lipomyces starkeyi strains. CONCLUSIONS: There is considerable metabolic diversity among oleaginous yeasts, even between closely related species and strains, especially when converting xylose to biomass and lipids. Monitoring the kinetics of lipid accumulation and identifying the molecular basis of this diversity are keys to selecting suitable strains for high lipid production from lignocellulose.

Calcium Affects Polyphosphate and Lipid Accumulation in Mucoromycota Fungi.

Calcium controls important processes in fungal metabolism, such as hyphae growth, cell wall synthesis, and stress tolerance. Recently, it was reported that calcium affects polyphosphate and lipid accumulation in fungi. The purpose of this study was to assess the effect of calcium on the accumulation of lipids and polyphosphate for six oleaginous Mucoromycota fungi grown under different phosphorus/pH conditions. A Duetz microtiter plate system (Duetz MTPS) was used for the cultivation. The compositional profile of the microbial biomass was recorded using Fourier-transform infrared spectroscopy, the high throughput screening extension (FTIR-HTS). Lipid content and fatty acid profiles were determined using gas chromatography (GC). Cellular phosphorus was determined using assay-based UV-Vis spectroscopy, and accumulated phosphates were characterized using solid-state 31P nuclear magnetic resonance spectroscopy. Glucose consumption was estimated by FTIR-attenuated total reflection (FTIR-ATR). Overall, the data indicated that calcium availability enhances polyphosphate accumulation in Mucoromycota fungi, while calcium deficiency increases lipid production, especially under acidic conditions (pH 2-3) caused by the phosphorus limitation. In addition, it was observed that under acidic conditions, calcium deficiency leads to increase in carotenoid production. It can be concluded that calcium availability can be used as an optimization parameter in fungal fermentation processes to enhance the production of lipids or polyphosphates.

Evaluation and optimisation of direct transesterification methods for the assessment of lipid accumulation in oleaginous filamentous fungi.

BACKGROUND: Oleaginous filamentous fungi can accumulate large amount of cellular lipids and potentially serve as a major source of oleochemicals for food, feed, chemical, pharmaceutical, and transport industries. Transesterification of microbial oils is an essential step in microbial lipid production at both laboratory and industrial scale. Direct transesterification can considerably reduce costs, increase sample throughput and improve lipid yields (in particular fatty acid methyl esters, FAMEs). There is a need for the assessment of the direct transesterification methods on a biomass of filamentous fungi due to their unique properties, specifically resilient cell wall and wide range of lipid content and composition. In this study we have evaluated and optimised three common direct transesterification methods and assessed their suitability for processing of fungal biomass. RESULTS: The methods, based on hydrochloric acid (Lewis method), sulphuric acid (Wahlen method), and acetyl chloride (Lepage method), were evaluated on six different strains of Mucoromycota fungi by using different internal standards for gas chromatography measurements. Moreover, Fourier transform infrared (FTIR) spectroscopy was used for the detection of residual lipids in the biomass after the transesterification reaction/extraction, while transesterification efficiency was evaluated by nuclear magnetic resonance spectroscopy. The results show that the majority of lipids, in particular triglycerides, were extracted for all methods, though several methods had substandard transesterification yields. Lewis method, optimised with respect to solvent to co-solvent ratio and reaction time, as well as Lepage method, offer precise estimate of FAME-based lipids in fungal biomass. CONCLUSIONS: The results show that Lepage and Lewis methods are suitable for lipid analysis of oleaginous filamentous fungi. The significant difference in lipid yields results, obtained by optimised and standard Lewis methods, indicates that some of the previously reported lipid yields for oleaginous filamentous fungi must be corrected upwards. The study demonstrates value of biomass monitoring by FTIR, importance of optimal solvent to co-solvent ratio, as well as careful selection and implementation of internal standards for gas chromatography.

Animal Fat as a Substrate for Production of n-6 Fatty Acids by Fungal Solid-State Fermentation.

The method of solid-state fermentation (SSF) represents a powerful technology for the fortification of animal-based by-products. Oleaginous Zygomycetes fungi are efficient microbial cell factories used in SSF to valorize a wide range of waste and rest cereal materials. The application of this fermentation technique for utilization and biotransformation of animal-based materials represents a distinguished step in their treatment. In this study, for the first time, the strain Umbelopsis isabellina CCF2412 was used for the bioconversion of animal fat by-products to the fermented bioproducts enriched with n-6 polyunsaturated fatty acids, mainly γ-linolenic acid (GLA). Bioconversion of both cereals and the animal fat by-product resulted in the production of fermented bioproducts enriched with not just GLA (maximal yield was 6.4 mg GLA/g of fermented bioproduct), but also with high yields of glucosamine. Moreover, the fermentation on the cornmeal matrix led to obtaining bioproduct enriched with ß-carotene. An increased amount of ß-carotene content improved the antioxidant stability of obtained fermented bioproducts. Furthermore, the application of Fourier-transform infrared spectroscopy for rapid analysis and characterization of the biochemical profile of obtained SSF bioproducts was also studied.