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.

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.

Preclassification of Broadband and Sparse Infrared Data by Multiplicative Signal Correction Approach.

Preclassification of raw infrared spectra has often been neglected in scientific literature. Separating spectra of low spectral quality, due to low signal-to-noise ratio, presence of artifacts, and low analyte presence, is crucial for accurate model development. Furthermore, it is very important for sparse data, where it becomes challenging to visually inspect spectra of different natures. Hence, a preclassification approach to separate infrared spectra for sparse data is needed. In this study, we propose a preclassification approach based on Multiplicative Signal Correction (MSC). The MSC approach was applied on human and the bovine knee cartilage broadband Fourier Transform Infrared (FTIR) spectra and on a sparse data subset comprising of only seven wavelengths. The goal of the preclassification was to separate spectra with analyte-rich signals (i.e., cartilage) from spectra with analyte-poor (and high-matrix) signals (i.e., water). The human datasets 1 and 2 contained 814 and 815 spectra, while the bovine dataset contained 396 spectra. A pure water spectrum was used as a reference spectrum in the MSC approach. A threshold for the root mean square error (RMSE) was used to separate cartilage from water spectra for broadband and the sparse spectral data. Additionally, standard noise-to-ratio and principle component analysis were applied on broadband spectra. The fully automated MSC preclassification approach, using water as reference spectrum, performed as well as the manual visual inspection. Moreover, it enabled not only separation of cartilage from water spectra in broadband spectral datasets, but also in sparse datasets where manual visual inspection cannot be applied.

Preprocessing Strategies for Sparse Infrared Spectroscopy: A Case Study on Cartilage Diagnostics.

The aim of the study was to optimize preprocessing of sparse infrared spectral data. The sparse data were obtained by reducing broadband Fourier transform infrared attenuated total reflectance spectra of bovine and human cartilage, as well as of simulated spectral data, comprising several thousand spectral variables into datasets comprising only seven spectral variables. Different preprocessing approaches were compared, including simple baseline correction and normalization procedures, and model-based preprocessing, such as multiplicative signal correction (MSC). The optimal preprocessing was selected based on the quality of classification models established by partial least squares discriminant analysis for discriminating healthy and damaged cartilage samples. The best results for the sparse data were obtained by preprocessing using a baseline offset correction at 1800 cm-1, followed by peak normalization at 850 cm-1 and preprocessing by MSC.

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.

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.

Discrimination of grass pollen of different species by FTIR spectroscopy of individual pollen grains.

Fourier-transform infrared (FTIR) spectroscopy enables the chemical characterization and identification of pollen samples, leading to a wide range of applications, such as paleoecology and allergology. This is of particular interest in the identification of grass (Poaceae) species since they have pollen grains of very similar morphology. Unfortunately, the correct identification of FTIR microspectroscopy spectra of single pollen grains is hindered by strong spectral contributions from Mie scattering. Embedding of pollen samples in paraffin helps to retrieve infrared spectra without scattering artifacts. In this study, pollen samples from 10 different populations of five grass species (Anthoxanthum odoratum, Bromus inermis, Hordeum bulbosum, Lolium perenne, and Poa alpina) were embedded in paraffin, and their single grain spectra were obtained by FTIR microspectroscopy. Spectra were subjected to different preprocessing in order to suppress paraffin influence on spectral classification. It is shown that decomposition by non-negative matrix factorization (NMF) and extended multiplicative signal correction (EMSC) that utilizes a paraffin constituent spectrum, respectively, leads to good success rates for the classification of spectra with respect to species by a partial least square discriminant analysis (PLS-DA) model in full cross-validation for several species. PLS-DA, artificial neural network, and random forest classifiers were applied on the EMSC-corrected spectra using an independent validation to assign spectra from unknown populations to the species. Variation within and between species, together with the differences in classification results, is in agreement with the systematics within the Poaceae family. The results illustrate the great potential of FTIR microspectroscopy for automated classification and identification of grass pollen, possibly together with other, complementary methods for single pollen chemical characterization.

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.

Fossil pollen and spores as a tool for reconstructing ancient solar-ultraviolet irradiance received by plants: an assessment of prospects and challenges using proxy-system modelling.

Ultraviolet-B radiation (UV-B, 280-315 nm) constitutes less than 1% of the total solar radiation that reaches the Earth's surface but has a disproportional impact on biological and ecological processes from the individual to the ecosystem level. Absorption of UV-B by ozone is also one of the primary heat sources to the stratosphere, so variations in UV-B have important relationships to the Earth's radiation budget. Yet despite its importance for understanding atmospheric and ecological processes, there is limited understanding about the changes in UV-B radiation in the geological past. This is because systematic measurements of total ozone and surface UV-B only exist since the 1970s, so biological or geochemical proxies from sediment archives are needed to reconstruct UV-B irradiance received at the Earth surface beyond the experimental record. Recent developments have shown that the quantification of UV-B-absorbing compounds in pollen and spores have the potential to provide a continuous record of the solar-ultraviolet radiation received by plants. There is increasing interest in developing this proxy in palaeoclimatic and palaeoecological research. However, differences in interpretation exist between palaeoecologists, who are beginning to apply the proxy under various geological settings, and UV-B ecologists, who question whether a causal dose-response relationship of pollen and spore chemistry to UV-B irradiance has really been established. Here, we use a proxy-system modelling approach to systematically assess components of the pollen- and spore-based UV-B-irradiance proxy to ask how these differences can be resolved. We identify key unknowns and uncertainties in making inferences about past UV-B irradiance, from the pollen sensor, the sedimentary archive, and through the laboratory and experimental procedures in order to target priority areas of future work. We argue that an interdisciplinary approach, modifying methods used by plant ecologists studying contemporary responses to solar-UV-B radiation specifically to suit the needs of palaeoecological analyses, provides a way forward in developing the most reliable reconstructions for the UV-B irradiance received by plants across a range of timescales.

Elevated air humidity increases UV mediated leaf and DNA damage in pea (Pisum sativum) due to reduced flavonoid content and antioxidant power.

Growth in high relative air humidity (RH, >85%) affects plant morphology and causes diminished response to stomatal closing signals. Many greenhouses are prone to high RH conditions, which may negatively affect production and post-harvest quality. UV radiation induces stomatal closure in several species, and facilitates disease control. We hypothesised that UV exposure may trigger stomatal closure in pea plants (Pisum sativum) grown in high RH, thereby restoring stomatal function. The effects of UV exposure were tested on plants grown in moderate (60%) or high (90%) RH. UV exposure occurred at night, according to a disease control protocol. Lower stomatal conductance rates were found in UV-exposed plants, though UV exposure did not improve the rate of response to closing stimuli or desiccation tolerance. UV-exposed plants showed leaf curling, chlorosis, necrosis, and DNA damage measured by the presence of cyclobutane pyrimidine dimers (CPD), all of which were significantly greater in high RH plants. These plants also had lower total flavonoid content than moderate RH plants, and UV-exposed plants had less than controls. Plants exposed to UV had a higher content of cuticular layer uronic compounds than control plants. However, high RH plants had a higher relative amount of cuticular waxes, but decreased proteins and uronic compounds. Plants grown in high RH had reduced foliar antioxidant power compared to moderate RH. These results indicate that high RH plants were more susceptible to UV-induced damage than moderate RH plants due to reduced flavonoid content and oxidative stress defence.

Extended Multiplicative Signal Correction Based Model Transfer for Raman Spectroscopy in Biological Applications.

The chemometric analysis of Raman spectra of biological materials is hampered by spectral variations due to the instrumental setup that overlay the subtle biological changes of interest. Thus, an established statistical model may fail when applied to Raman spectra of samples acquired with a different device. Therefore, model transfer strategies are essential. Herein we report a model transfer approach based on extended multiplicative signal correction (EMSC). As opposed to existing model transfer methods, the EMSC based approach does not require group information on the secondary data sets, thus no extra measurements are required. The proposed model-transfer approach is a preprocessing procedure and can be combined with any method for regression and classification. The performance of EMSC as a model transfer method was demonstrated with a data set of Raman spectra of three Bacillus bacteria spore species ( B. mycoides, B. subtilis, and B. thuringiensis), which were acquired on four Raman spectrometers. A three-group classification by partial least-squares discriminant analysis (PLS-DA) with leave-one-device-out external cross-validation (LODCV) was performed. The mean sensitivities of the prediction on the independent device were considerably improved by the EMSC method. Besides the mean sensitivity, the model transferability was additionally benchmarked by the newly defined numeric markers: (1) relative Pearson's correlation coefficient and (2) relative Fisher's discriminant ratio. We show that these markers have led to consistent conclusions compared to the mean sensitivity of the classification. The advantage of our defined markers is that the evaluation is more effective and objective, because it is independent of the classification models.

Chemical characterization and identification of Pinaceae pollen by infrared microspectroscopy.

MAIN CONCLUSION: FTIR microspectroscopy, in combination with spectral averaging procedure, enables precise analysis of pollen grains for chemical characterization and identification studies of fresh and fossilised pollen in botany, ecology and palaeosciences. Infrared microspectroscopy (µFTIR) of Pinaceae pollen can provide valuable information on plant phenology, ecophysiology and paleoecology, but measurements are challenging, resulting in unreproducible spectra. The comparative analysis of µFTIR spectra belonging to morphologically different Pinaceae pollen, namely bisaccate Pinus and monosaccate Tsuga pollen, was conducted. The study shows that the main cause of spectral variability is non-radial symmetry of bisaccate pollen grains, while additional variation is caused by Mie scattering. Averaging over relatively small number of single pollen grain spectra (approx. 5-10) results with reproducible data on pollen chemical composition. The practical applicability of the µFTIR spectral averaging method has been demonstrated by the partial least-squares regression-based differentiation of the two closely related Pinus species with morphologically indistinguishable pollen: Pinus mugo (mountain pine) and Pinus sylvestris (Scots pine). The study has demonstrated that the µFTIR approach can be used for identification, differentiation and chemical characterization of pollen with complex morphology. The methodology enables analysis of fresh pollen, as well as fossil pollen from sediment core samples, and can be used in botany, ecology and paleoecology for study of biotic and abiotic effects on plants.

Assessment of the scalability of a microtiter plate system for screening of oleaginous microorganisms.

Recent developments in molecular biology and metabolic engineering have resulted in a large increase in the number of strains that need to be tested, positioning high-throughput screening of microorganisms as an important step in bioprocess development. Scalability is crucial for performing reliable screening of microorganisms. Most of the scalability studies from microplate screening systems to controlled stirred-tank bioreactors have been performed so far with unicellular microorganisms. We have compared cultivation of industrially relevant oleaginous filamentous fungi and microalga in a Duetz-microtiter plate system to benchtop and pre-pilot bioreactors. Maximal glucose consumption rate, biomass concentration, lipid content of the biomass, biomass, and lipid yield values showed good scalability for Mucor circinelloides (less than 20% differences) and Mortierella alpina (less than 30% differences) filamentous fungi. Maximal glucose consumption and biomass production rates were identical for Crypthecodinium cohnii in microtiter plate and benchtop bioreactor. Most likely due to shear stress sensitivity of this microalga in stirred bioreactor, biomass concentration and lipid content of biomass were significantly higher in the microtiter plate system than in the benchtop bioreactor. Still, fermentation results obtained in the Duetz-microtiter plate system for Crypthecodinium cohnii are encouraging compared to what has been reported in literature. Good reproducibility (coefficient of variation less than 15% for biomass growth, glucose consumption, lipid content, and pH) were achieved in the Duetz-microtiter plate system for Mucor circinelloides and Crypthecodinium cohnii. Mortierella alpina cultivation reproducibility might be improved with inoculation optimization. In conclusion, we have presented suitability of the Duetz-microtiter plate system for the reproducible, scalable, and cost-efficient high-throughput screening of oleaginous microorganisms.

FTIR spectroscopy as a unified method for simultaneous analysis of intra- and extracellular metabolites in high-throughput screening of microbial bioprocesses.

BACKGROUND: Analyses of substrate and metabolites are often bottleneck activities in high-throughput screening of microbial bioprocesses. We have assessed Fourier transform infrared spectroscopy (FTIR), in combination with high throughput micro-bioreactors and multivariate statistical analyses, for analysis of metabolites in high-throughput screening of microbial bioprocesses. In our previous study, we have demonstrated that high-throughput (HTS) FTIR can be used for estimating content and composition of intracellular metabolites, namely triglyceride accumulation in oleaginous filamentous fungi. As a continuation of that research, in the present study HTS FTIR was evaluated as a unified method for simultaneous quantification of intra- and extracellular metabolites and substrate consumption. As a proof of concept, a high-throughput microcultivation of oleaginous filamentous fungi was conducted in order to monitor production of citric acid (extracellular metabolite) and triglyceride lipids (intracellular metabolites), as well as consumption of glucose in the cultivation medium. RESULTS: HTS FTIR analyses of supernatant samples was compared with an attenuated total reflection (ATR) FTIR, which is an established method for bioprocess monitoring. Glucose and citric acid content of growth media was quantified by high performance liquid chromatography (HPLC). Partial least square regression (PLSR) between HPLC glucose and citric acid data and the corresponding FTIR spectral data was used to set up calibration models. PLSR results for HTS measurements were very similar to the results obtained with ATR methodology, with high coefficients of determination (0.91-0.98) and low error values (4.9-8.6%) for both glucose and citric acid estimates. CONCLUSIONS: The study has demonstrated that intra- and extracellular metabolites, as well as nutrients in the cultivation medium, can be monitored by a unified approach by HTS FTIR. The proof-of-concept study has validated that HTS FTIR, in combination with Duetz microtiter plate system and chemometrics, can be used for high throughput screening of microbial bioprocesses. It can be anticipated that the approach, demonstrated here on single-cell oil production by filamentous fungi, can find general application in screening studies of microbial bioprocesses, such as production of single-cell proteins, biopolymers, polysaccharides, carboxylic acids, and other type of metabolites.

Microtiter plate cultivation of oleaginous fungi and monitoring of lipogenesis by high-throughput FTIR spectroscopy.

BACKGROUND: Oleaginous fungi can accumulate lipids by utilizing a wide range of waste substrates. They are an important source for the industrial production of omega-6 polyunsaturated fatty acids (gamma-linolenic and arachidonic acid) and have been suggested as an alternative route for biodiesel production. Initial research steps for various applications include the screening of fungi in order to find efficient fungal producers with desired fatty acid composition. Traditional cultivation methods (shake flask) and lipid analysis (extraction-gas chromatography) are not applicable for large-scale screening due to their low throughput and time-consuming analysis. Here we present a microcultivation system combined with high-throughput Fourier transform infrared (FTIR) spectroscopy for efficient screening of oleaginous fungi. RESULTS: The microcultivation system enables highly reproducible fungal fermentations throughout 12 days of cultivation. Reproducibility was validated by FTIR and HPLC data. Analysis of FTIR spectral ester carbonyl peaks of fungal biomass offered a reliable high-throughput at-line method to monitor lipid accumulation. Partial least square regression between gas chromatography fatty acid data and corresponding FTIR spectral data was used to set up calibration models for the prediction of saturated fatty acids, monounsaturated fatty acids, polyunsaturated fatty acids, unsaturation index, total lipid content and main individual fatty acids. High coefficients of determination (R2 = 0.86-0.96) and satisfactory residual predictive deviation of cross-validation (RPDCV = 2.6-5.1) values demonstrated the goodness of these models. CONCLUSIONS: We have demonstrated in this study, that the presented microcultivation system combined with rapid, high-throughput FTIR spectroscopy is a suitable screening platform for oleaginous fungi. Sample preparation for FTIR measurements can be automated to further increase throughput of the system.

Vibrational microspectroscopy enables chemical characterization of single pollen grains as well as comparative analysis of plant species based on pollen ultrastructure.

MAIN CONCLUSION: Chemical imaging of pollen by vibrational microspectroscopy enables characterization of pollen ultrastructure, in particular phenylpropanoid components in grain wall for comparative study of extant and extinct plant species. A detailed characterization of conifer (Pinales) pollen by vibrational microspectroscopy is presented. The main problems that arise during vibrational measurements were scatter and saturation issues in Fourier transform infrared (FTIR), and fluorescence and penetration depth issues in Raman. Single pollen grains larger than approx. 15 µm can be measured by FTIR microspectroscopy using conventional light sources, while smaller grains may be measured by employing synchrotron light sources. Pollen grains that were larger than 50 µm were too thick for FTIR imaging since the grain constituents absorbed almost all infrared light. Chemical images of pollen were obtained on sectioned samples, unveiling the distribution and concentration of proteins, carbohydrates, sporopollenins and lipids within pollen substructures. The comparative analysis of pollen species revealed that, compared with other Pinales pollens, Cedrus atlantica has a higher relative amount of lipid nutrients, as well as different chemical composition of grain wall sporopollenin. The pre-processing and data analysis, namely extended multiplicative signal correction and principal component analysis, offer simple estimate of imaging spectral data and indirect estimation of physical properties of pollen. The vibrational microspectroscopy study demonstrates that detailed chemical characterization of pollen can be obtained by measurement of an individual grain and pollen ultrastructure. Measurement of phenylpropanoid components in pollen grain wall could be used, not only for the reconstruction of past environments, but for assessment of diversity of plant species as well. Therefore, analysis of extant and extinct pollen species by vibrational spectroscopies is suggested as a valuable tool in biology, ecology and palaeosciences.

Study of thermal stability of (3-aminopropyl)trimethoxy silane-grafted titanate nanotubes for application as nanofillers in polymers.

Protonated titanate nanotubes (TiNT-H) were surface-modified with (3-aminopropyl)trimethoxy silane (APTMS) by a novel method suitable for the syntheses of large amounts of materials at a low cost. The usage of prepared nanotubes for polymer reinforcement was studied. Since the thermal stability of the nanofiller was important to preserve its functional properties, its stability was studied by in situ high-temperature measurements. The most thermally stable nanotubes were silanized for 20 min and used for the preparation of epoxy-based nanocomposites. The nanofiller formed smaller (a few hundred nm) and larger (a few µm) aggregates in the polymer matrix, and the amount of aggregates increased as the nanofiller content increased. The APTMS-modified titanate nanotubes bonded well with the epoxy matrix since amine groups on the TiNT's surface can react with an epoxy group to form covalent bonds between the matrix and the nanofiller. A very small addition (0.19-1.52 wt%) of the nanotubes significantly increased the glass transition temperature and the modulus in the rubbery state of the epoxy-based polymer. Smaller nanofiller content leads to a larger increase in these parameters and therefore better dynamic mechanical properties due to the smaller amount of large aggregates. APTMS-modified titanate nanotubes have proven to be a promising nanofiller in epoxy-based nanocomposites.

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.

Comment on "Dying in the Sun: Direct evidence for elevated UV-B radiation at the end-Permian mass extinction".

Liu et al. present evidence of increased abundance of UV-B-absorbing compounds in fossilized sporomorphs at the end-Permian mass extinction based on Fourier transform infrared (FTIR) spectroscopy. Their approach assumes that UV-B-absorbing compounds are present in the fossilized sporomorphs spanning the extinction interval and that they can be quantified using FTIR. However, further analysis reveals that the signal that they aim to focus on is weak and poorly resolved against nonrandom background interference most likely associated with water vapor. We also show that the peak detection methods that they use are inappropriate for use on these fossil sporomorphs because their methods select only 3.9% of the spectra at the target waveband of interest. The reconstruction that they present is based on baseline variations in the spectra and cannot be confidently attributed to variations in UV-B-absorbing compounds. "Direct" evidence for UV-B radiation at the end-Permian mass extinction cannot be claimed to have been observed in this record.

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.