Assessment of growth phases of the diatom Ditylum brightwellii by FT-IR and Raman spectroscopy

Mineralogical characterization of biosilicas versus geological analogs

Non-crystalline silica mineraloids are essential to life on Earth as they provide architectural structure to dominant primary producers, such as plants and phytoplankton, as well as to protists and sponges. Due to the difficulty in characterizing and quantifying the structure of highly disordered X-ray amorphous silica, relatively little has been done to understand the mineralogy of biogenic silica and how this may impact the material properties of biogenic silica, such as hardness and strength, or how biosilica might be identified and differentiated from its inorganic geological counterparts. Typically, geologically formed opal-A and hyalite opal-A_N are regarded as analogs to biogenic silica, however, some spectroscopic and imaging studies suggest that this might not be a reasonable assumption. In this study, we use a variety of techniques (X-ray diffraction, Raman spectroscopy, and scanning electron microscopy) to compare differences in structural disorder and bonding environments of geologically formed hydrous silicas (Opal-A, hyalite, geyserite) and silica glass versus biogenic silicas from an array of organisms. Our results indicate differences in the levels of structural disorder and the Raman-observed bonding environments of the SiO₂ network modes (D₁ mode) and the Q-species modes (~1015 cm^-1 ) between varieties of biogenic silicas and geologically formed silicas, which aligns with previous studies that suggest fundamental differences between biogenic and geologically formed silica. Biosilicas also differ structurally from one another by species of organism. Our mineralogical approach to characterizing biosilicas and differentiating them from other silicas may be expanded to future diagenesis studies, and potentially applied to astrobiology studies of Earth and other planets.

Label-free and noninvasive analysis of microorganism surface epistructures at the single-cell level

Cell surface properties of microorganisms provide abundant information for their physiological status and fate choice. However, current methods for analyzing cell surface properties require labeling or fixation, which can alter the cell activity. This study establishes a label-free, rapid, noninvasive, and quantitative analysis of cell surface properties, including the presence and the dimension of epistructure, down to the single-cell level and at the nanometer scale. Simultaneously, electrorotation provides dielectric properties of intracellular contents. With the combined information, the growth phase of microalgae cells can be identified. The measurement is based on electrorotation of single cells, and an electrorotation model accounting for the surface properties is developed to properly interpret experimental data. The epistructure length measured by electrorotation is validated by scanning electron microscopy. The measurement accuracy is satisfactory in particular in the case of microscale epistructures in the exponential phase and nanoscale epistructures in the stationary phase. However, the measurement accuracy for nanoscale epistructures on cells in the exponential phase is offset by the effect of a thick double layer. Lastly, a diversity in epistructure length distinguishes exponential phase from stationary phase.

Novel Approach to Freshwater Diatom Profiling and Identification Using Raman Spectroscopy and Chemometric Analysis

(1) An approach with great potential for fast and cost-effective profiling and identification of diatoms in lake ecosystems is presented herein. This approach takes advantage of Raman spectroscopy. (2) The study was based on the analysis of 790 Raman spectra from 29 species, belonging to 15 genera, 12 families, 9 orders and 4 subclasses, which were analysed using chemometric methods. The Raman data were first analysed by a partial least squares regression discriminant analysis (PLS-DA) to characterise the diatom species. Furthermore, a method was developed to streamline the integrated interpretation of PLS-DA when a high number of significant components is extracted. Subsequently, an artificial neural network (ANN) was used for taxa identification from Raman data. (3) The PLS interpretation produced a Raman profile for each species reflecting its biochemical composition. The ANN models were useful to identify various taxa with high accuracy. (4) Compared to studies in the literature, involving huge datasets one to four orders of magnitude larger than ours, high sensitivity was found for the identification of Achnanthidium exiguum (67%), Fragilaria pararumpens (67%), Amphora pediculus (71%), Achnanthidium minutissimum (80%) and Melosira varians (82%).

Response to nutrient variation on lipid productivity in green microalgae captured using second derivative FTIR and Raman spectroscopy

Two green microalgae species Monoraphidium contortum (M. contortum) and Chlamydomonas sp. that were identified to accumulate lipids were subjected to four different nutrient treatments (NP1-NP4), ranging in nitrate (0.05-5 mM N) and phosphate (2.8-264 μM P) concentrations, at a fixed N:P ratio of ∼18. The effect of nutrient variation on lipid productivity in the species was investigated using second derivative (SD) FTIR and Raman spectroscopy of algal biomass. SD spectral analysis revealed high production of lipid in the form of hydrocarbons (CH) (3000-2800 cm^-1), triacylglycerides (TAGs)(∼1740 cm^-1), saturated (SFA)(∼1440 cm^-1), and unsaturated fatty acids (UFA)(∼3010 cm^-1) for the nutrient deplete condition (NP1) in both species. Changes in signals attributed to lipids in proportion to other biochemical components were consistent with physiological changes expected from nutrient depletion. Relative signal intensities for lipids showed a significant increase in NP1, in particular, CH, TAGs in relation to protein signals (in SD-FTIR), and SFA, UFA in relation to carotenoid signals (in SD-Raman). PCA performed on the negative spectral values of the SD-FTIR and SD-Raman data for the four NP treatments enabled discrimination not only between the species but also between the NP treatments and the timing of harvest. M. contortum was found to contain a relatively higher proportion of CH, TAGs, SFA, and UFA compared to Chlamydomonas sp. Peak areas from the negative SD spectra, informed by PCA analysis, enabled capturing quantifiable changes in a manner that is consistent with known microalgal physiology. SD-FTIR and SD-Raman spectroscopy have been shown to possess superior potential to capture relevant microalgal physiological changes.

Environmental diagnosis with Raman Spectroscopy applied to diatoms

Freshwater quality has been changing due to the ever greater use of water resources and the contamination load resulting from human activities. Management of these systems, thus, requires constant diagnose of water quality with fast and efficient methodologies. The conventional methods adopted are, however, time-consuming, often very expensive, and require specialised expertise. Raman spectroscopy (RS) is a simple, fast and label-free technique that can be applied to environmental diagnosis using diatoms. Here, we developed a diagnostic method based on Raman spectroscopy applied to freshwater diatoms. For this, Raman spectra were recorded from diatoms of three lakes of a natural city park. The data acquired was analysed by chemometrics methods to describe the data (Partial Least Squares Regression), infer relationships in the dataset (Cluster Analysis) and produce classification models (Artificial Neural Network). The classification models developed diagnosed the lakes with excellent accuracy (89%) without requiring taxonomic information about the diatom species recorded. This study provides a proof-of-concept for the application of diatom Raman spectroscopy to diagnosing water quality, laying an important foundation for future environmental studies aiming at assessing freshwater systems, to be replicated at larger scales and to varied geographic settings.

Differential Membrane Lipid Profiles and Vibrational Spectra of Three Edaphic Algae and One Cyanobacterium

The membrane glycerolipids of four phototrophs that were isolated from an edaphic assemblage were determined by UPLC-MS after cultivation in a laboratory growth chamber. Identification was carried out by 18S and 16S rDNA sequencing. The algal species were Klebsormidium flaccidum (Charophyta), Oocystis sp. (Chlorophyta), and Haslea spicula (Bacillariophyta), and the cyanobacterium was Microcoleus vaginatus (Cyanobacteria). The glycerolipid profile of Oocystis sp. was dominated by monogalactosyldiacylglycerol (MGDG) species, with MGDG(18:3/16:4) accounting for 68.6%, whereas MGDG(18:3/16:3) was the most abundant glycerolipid in K. flaccidum (50.1%). A ratio of digalactosyldiacylglycerol (DGDG) species to MGDG species (DGDG/MGDG) was shown to be higher in K. flaccidum (0.26) than in Oocystis sp. (0.14). This ratio increased under high light (HL) as compared to low light (LL) in all the organisms, with its highest value being shown in cyanobacterium (0.38-0.58, LL-HL). High contents of eicosapentaenoic acid (EPA, C20:5) and hexadecenoic acid were observed in the glycerolipids of H. spicula. Similar Fourier transform infrared (FTIR) and Raman spectra were found for K. flaccidum and Oocystis sp. Specific bands at 1629.06 and 1582.78 cm-1 were shown by M. vaginatus in the Raman spectra. Conversely, specific bands in the FTIR spectrum were observed for H. spicula at 1143 and 1744 cm-1. The results of this study point out differences in the membrane lipid composition between species, which likely reflects their different morphology and evolutionary patterns.

The Fusion of Microfluidics and Optics for On-Chip Detection and Characterization of Microalgae

It has been demonstrated that microalgae play an important role in the food, agriculture and medicine industries. Additionally, the identification and counting of the microalgae are also a critical step in evaluating water quality, and some lipid-rich microalgae species even have the potential to be an alternative to fossil fuels. However, current technologies for the detection and analysis of microalgae are costly, labor-intensive, time-consuming and throughput limited. In the past few years, microfluidic chips integrating optical components have emerged as powerful tools that can be used for the analysis of microalgae with high specificity, sensitivity and throughput. In this paper, we review recent optofluidic lab-on-chip systems and techniques used for microalgal detection and characterization. We introduce three optofluidic technologies that are based on fluorescence, Raman spectroscopy and imaging-based flow cytometry, each of which can achieve the determination of cell viability, lipid content, metabolic heterogeneity and counting. We analyze and summarize the merits and drawbacks of these micro-systems and conclude the direction of the future development of the optofluidic platforms applied in microalgal research.

Raman spectroscopy applied to diatoms (microalgae, Bacillariophyta): Prospective use in the environmental diagnosis of freshwater ecosystems

Diatom species are good pollution bioindicators due to their large distribution, fast response to changes in environmental parameters and different tolerance ranges. These organisms are used in ecological water assessment all over the world using autoecological indices. Such assessments commonly rely on the taxonomic identification of diatom species-specific shape and frustule ornaments, from which cell counts, species richness and diversity indices can be estimated. Taxonomic identification is, however, time-consuming and requires years of expertise. Additionally, though the diatom autoecological indices are region-specific, they are often applied indiscriminately across regions. Raman spectroscopy is a simpler, fast and label-free technique that can be applied to environmental diagnosis with diatoms. However, this approach has been poorly explored. This work reviews Raman spectroscopy studies involving the structure, location and conformation of diatom cell components and their variation under different conditions. A critical appreciation of the pros and cons of its application to environmental diagnosis is also given. This knowledge provides a strong foundation for the development of environmental protocols using Raman spectroscopy in diatoms. Our work aims at stimulating further research on the application of Raman spectroscopy as a tool to assess physiological changes and water quality under a changing climate.

Biomolecular transitions and lipid accumulation in green microalgae monitored by FTIR and Raman analysis

Fourier transform infrared (FTIR) and Raman spectroscopic techniques were employed to analyze the biomolecular transitions and lipid accumulation in three freshwater green microalgal species, Monoraphidium contortum (M. contortum), Pseudomuriella sp. and Chlamydomonas sp. during various phases of their growth. Biomolecular transitions and lipid [hydrocarbons, triacylglycerides (TAGs)] accumulation within the microalgal cells were identified using second derivatives of the FTIR absorption spectroscopy. Second derivative analysis normalized and resolved the original spectra and led to the identification of smaller, overlapping bands. Both relative and absolute content of lipids were determined using the integrated band area. M. contortum exhibited higher accumulation of lipids than the other two species. The integrated band area of the vibrations from saturated (SFA) and unsaturated lipids (UFA) enabled quantification of fatty acids. The percentage of SFA and UFA was determined using GC, FTIR and Raman spectroscopy. From the spectral data, the order of increasing concentration of SFA among the three microalgal species was M. contortum > Chlamydomonas sp. >Pseudomuriella sp. The spectral results on fatty acids were consistent with the separation of lipids by gas chromatography. The results emphasized the significance of FTIR and Raman spectroscopic methods in monitoring the biomolecular transitions and rapid quantification of lipids, without the need for extraction of lipids.

Probing the Adhesion of the Common Freshwater Diatom Nitzschia palea at Nanoscale

Freshwater biofilms play an essential ecological role, but they also adversely affect human activities through undesirable biofouling of artificial submerged structures. They form complex aggregates of microorganisms that colonize any type of substratum. In phototrophic biofilms, diatoms dominate in biomass and produce copious amount of extracellular polymeric substances (EPSs), making them efficient early colonizers. Therefore, a better understanding of diatoms adhesive properties is essential to develop new anti-biofouling strategies. In this context, we used atomic force microscopy (AFM) to decipher the topography and adhesive mechanisms of the common freshwater diatom Nitzschia palea. Images taken in physiological conditions revealed typical ultrastructural features with a few nanometers resolution. Using single-cell force spectroscopy, we showed that N. palea strongly adheres to hydrophobic surfaces as compared to hydrophilic ones. Chemical force spectroscopy with hydrophobic tips further confirmed that the adhesion is governed by surface-associated hydrophobic EPS distributed in clusters at the frustule surface, and mostly composed of (glyco)-lipids as revealed by Raman spectroscopy. Collectively, our results demonstrate that AFM-based nanoscopy, combined with Raman spectroscopy, is a powerful tool to provide new insights into the adhesion mechanisms of diatoms.

High-throughput screening Raman microspectroscopy for assessment of drug-induced changes in diatom cells

High-throughput screening Raman spectroscopy (HTS-RS) with automated localization algorithms offers unsurpassed speed and sensitivity to investigate the effect of dithiothreitol on the diatom Phaedactylum tricornutum. The HTS-RS capability that was demonstrated for this model system can be transferred to unmet analytical applications such as kinetic in vivo studies of microalgal assemblages.

Optimal cultivation towards enhanced biomass and floridean starch production by Porphyridium marinum

Optimal conditions for maximal biomass and starch production by the marine red microalgae Porphyridium marinum were investigated. Box-Behnken Design was used to model the effect of light intensity, NaNO₃ concentration and salinity on the growth of microalgae but also on their starch and protein contents. These three factors increased biomass production by 13.6% in optimized conditions. A maximum starch production (140.21 μg·mL^-1), 30.6% higher than that of the control, was attained at a light intensity of 100 μmol photons·m^-2·s^-1, a NaNO₃ concentration of 1 g·L^-1 and a NaCl concentration of 20 g·L^-1. FT-IR spectroscopy was used to estimate the biochemical composition (carbohydrate accumulation) of P. marinum and revealed significant changes (P < 0.05) depending on culture conditions. FT-IR analysis highlighted also that the culture conditions leading to highest starch production by P. marinum corresponded to lowest sulfated polysaccharide and protein contents.

Windows into Microbial Seascapes: Advances in Nanoscale Imaging and Application to Marine Sciences

Geochemical cycles of all nonconservative elements are mediated by microorganisms over nanometer spatial scales. The pelagic seascape is known to possess microstructure imposed by heterogeneous distributions of particles, polymeric gels, biologically important chemicals, and microbes. While indispensable, most traditional oceanographic observational approaches overlook this heterogeneity and ignore subtleties, such as activity hot spots, symbioses, niche partitioning, and intrapopulation phenotypic variations, that can provide a deeper mechanistic understanding of planktonic ecosystem function. As part of the movement toward cultivation-independent tools in microbial oceanography, techniques to examine the ecophysiology of individual populations and their role in chemical transformations at spatial scales relevant to microorganisms have been developed. This review presents technologies that enable geochemical and microbiological interrogations at spatial scales ranging from 0.02 to a few hundred micrometers, particularly focusing on atomic force microscopy, nanoscale secondary ion mass spectrometry, and confocal Raman microspectroscopy and introducing promising approaches for future applications in marine sciences.

Assessment of physiological responses and growth phases of different microalgae under environmental changes by Raman spectroscopy with chemometrics

The assessment for cell physiology and growth phases of microalgae plays important roles in ecological and environmental fields since it can be used to forecast water eutrophication level worldwidely. Herein, growth phases and environmental conditions of microalgae were assessed by combining resonance Raman mapping spectroscopy with multivariate analysis methods. And, primary Raman characteristic peaks of microalgae were mined with two-dimensional synchronous spectra. Thereafter, algal growth phases and environmental conditions of microalgae were preliminary classified with different tendencies of characteristic Raman peaks by unsupervised principal component analysis (PCA) and support vector machine (SVM) methods. Our results demonstrated that resonance Raman mapping spectroscopy with PCA and SVM classification models can be used to assess algal growth phases and preliminary predict environmental conditions with characteristic Raman spectra of microalgae in water bodies.