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.

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.

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.

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.

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.

Metal and Phosphate Ions Show Remarkable Influence on the Biomass Production and Lipid Accumulation in Oleaginous Mucor circinelloides.

The biomass of Mucor circinelloides, a dimorphic oleaginous filamentous fungus, has a significant nutritional value and can be used for single cell oil production. Metal ions are micronutrients supporting fungal growth and metabolic activity of cellular processes. We investigated the effect of 140 different substrates, with varying amounts of metal and phosphate ions concentration, on the growth, cell chemistry, lipid accumulation, and lipid profile of M. circinelloides. A high-throughput set-up consisting of a Duetz microcultivation system coupled to Fourier transform infrared spectroscopy was utilized. Lipids were extracted by a modified Lewis method and analyzed using gas chromatography. It was observed that Mg and Zn ions were essential for the growth and metabolic activity of M. circinelloides. An increase in Fe ion concentration inhibited fungal growth, while higher concentrations of Cu, Co, and Zn ions enhanced the growth and lipid accumulation. Lack of Ca and Cu ions, as well as higher amounts of Zn and Mn ions, enhanced lipid accumulation in M. circinelloides. Generally, the fatty acid profile of M. circinelloides lipids was quite consistent, irrespective of media composition. Increasing the amount of Ca ions enhanced polyphosphates accumulation, while lack of it showed fall in polyphosphate.

Deep convolutional neural network recovers pure absorbance spectra from highly scatter-distorted spectra of cells.

Infrared spectroscopy of cells and tissues is prone to Mie scattering distortions, which grossly obscure the relevant chemical signals. The state-of-the-art Mie extinction extended multiplicative signal correction (ME-EMSC) algorithm is a powerful tool for the recovery of pure absorbance spectra from highly scatter-distorted spectra. However, the algorithm is computationally expensive and the correction of large infrared imaging datasets requires weeks of computations. In this paper, we present a deep convolutional descattering autoencoder (DSAE) which was trained on a set of ME-EMSC corrected infrared spectra and which can massively reduce the computation time for scatter correction. Since the raw spectra showed large variability in chemical features, different reference spectra matching the chemical signals of the spectra were used to initialize the ME-EMSC algorithm, which is beneficial for the quality of the correction and the speed of the algorithm. One DSAE was trained on the spectra, which were corrected with different reference spectra and validated on independent test data. The DSAE outperformed the ME-EMSC correction in terms of speed, robustness, and noise levels. We confirm that the same chemical information is contained in the DSAE corrected spectra as in the spectra corrected with ME-EMSC.

The influence of phosphorus source and the nature of nitrogen substrate on the biomass production and lipid accumulation in oleaginous Mucoromycota fungi.

Oleaginous filamentous fungi grown under the nitrogen limitation, accumulate high amounts of lipids in the form of triacylglycerides (TAGs) with fatty acid profiles similar to plant and fish oils. In this study, we investigate the effect of six phosphorus source concentrations combined with two types of nitrogen substrate (yeast extract and ammonium sulphate), on the biomass formation, lipid production, and fatty acid profile for nine oleaginous Mucoromycota fungi. The analysis of fatty acid profiles was performed by gas chromatography with flame ionization detector (GC-FID) and the lipid yield was estimated gravimetrically. Yeast extract could be used as both nitrogen and phosphorus source, without additional inorganic phosphorus supplementation. The use of inorganic nitrogen source (ammonium sulphate) requires strain-specific optimization of phosphorus source amount to obtain optimal lipid production regarding quantity and fatty acid profiles. Lipid production was decreased in ammonium sulphate-based media when phosphorus source was limited in all strains except for Rhizopus stolonifer. High phosphorus source concentration inhibited the growth of Mortierella fungi. The biomass (22 g/L) and lipid (14 g/L) yield of Umbelopsis vinacea was the highest among all the tested strains. KEY POINTS: • The strain specific P requirements of Mucoromycota depend on the nature of N source. • Yeast extract leads to consistent biomass and lipid yield and fatty acids profiles. • Umbelopsis vinacea showed the highest biomass (22 g/L) and lipid (14 g/L) yield. • High P source amounts inhibit the growth of Mortierella fungi.

Microcultivation and FTIR spectroscopy-based screening revealed a nutrient-induced co-production of high-value metabolites in oleaginous Mucoromycota fungi.

Mucoromycota fungi possess a versatile metabolism and can utilize various substrates for production of industrially important products, such as lipids, chitin/chitosan, polyphosphates, pigments, alcohols and organic acids. However, as far as commercialisation is concerned, establishing industrial biotechnological processes based on Mucoromycota fungi is still challenging due to the high production costs compared to the final product value. Therefore, the development of co-production concept is highly desired since more than one valuable product could be produced at the time and the process has a potentially higher viability. To develop such biotechnological strategy, we applied a high throughput approach consisting of micro-titre cultivation and FTIR spectroscopy. This approach allows single-step biochemical fingerprinting of either fungal biomass or growth media without tedious extraction of metabolites. The influence of two types of nitrogen sources and different levels of inorganic phosphorus on the co-production of lipids, chitin/chitosan and polyphosphates for nine different oleaginous Mucoromycota fungi was evaluated. FTIR analysis of biochemical composition of Mucoromycota fungi and biomass yield showed that variation in inorganic phosphorus had higher effect when inorganic nitrogen source-ammonium sulphate-was used. It was observed that: (1) Umbelopsis vinacea reached almost double biomass yield compared to other strains when yeast extract was used as nitrogen source while phosphorus limitation had little effect on the biomass yield; (2) Mucor circinelloides, Rhizopus stolonifer, Amylomyces rouxii, Absidia glauca and Lichtheimia corymbifera overproduced chitin/chitosan under the low pH caused by the limitation of inorganic phosphorus; (3) Mucor circinelloides, Amylomyces rouxii, Rhizopus stolonifer and Absidia glauca were able to store polyphosphates in addition to lipids when high concentration of inorganic phosphorus was used; (4) the biomass and lipid yield of high-value lipid producers Mortierella alpina and Mortierella hyalina were significantly increased when high concentrations of inorganic phosphorus were combined with ammonium sulphate, while the same amount of inorganic phosphorus combined with yeast extract showed negative impact on the growth and lipid accumulation. FTIR spectroscopy revealed the co-production potential of several oleaginous Mucoromycota fungi forming lipids, chitin/chitosan and polyphosphates in a single cultivation process.