Raman Spectroscopy and Its Modifications Applied to Biological and Medical Research

Development of a cost-effective confocal Raman microscopy with high sensitivity

Confocal Raman microscopy is a powerful technique for identifying materials and molecular species; however, the signal from Raman scattering is extremely weak. Typically, handheld Raman instruments are cost-effective but less sensitive, while high-end scientific-grade Raman instruments are highly sensitive but extremely expensive. This limits the widespread use of Raman technique in our daily life. To bridge this gap, we explored and developed a cost-effective yet highly sensitive confocal Raman microscopy system. The key components of the system include an excitation laser based on readily available laser diode, a lens-grating-lens type spectrometer with high throughput and image quality, and a sensitive detector based on a linear charge-coupled device (CCD) that can be cooled down to -30 °C. The developed compact Raman instrument can provide high-quality Raman spectra with good spectral resolution. The 3rd order 1450 cm-1 peak of Si (111) wafer shows a signal-to-noise ratio (SNR) better than 10:1, demonstrating high sensitivity comparable to high-end scientific-grade Raman instruments. We also tested a wide range of different samples (organic molecules, minerals and polymers) to demonstrate its universal application capability.

High-Throughput Metabolite Analysis of Unicellular Microalgae by Orthogonal Hybrid Ionization Label-Free Mass Cytometry

Microalgae metabolite analysis is fundamental for the rational design of metabolic engineering strategies for the biosynthesis of high-value products. Mass spectrometry (MS) has been utilized for single-cell microalgae analysis. However, limitations in the detection throughput and polarities of detectable substances make it difficult to realize high-throughput screening of high-performance microalgae. Herein, a plasma-assisted label-free mass cytometry, named as PACyESI-MS, was proposed combining the advantages of orthogonal hybrid ionization and high-throughput MS analysis, which realized rapid metabolite detection of single microalgae. The cell detection throughput of PACyESI-MS was up to 52 cells/min. Dozens of the critical primary and secondary metabolites within single microalgae were detected simultaneously, including pigments, lipids, and energy metabolites. Furthermore, metabolite changes of Chlamydomonas reinhardtii and Haematococcus pluvialis under nitrogen deficiency stress were studied. Discrimination of Chlamydomonas under different nutrient conditions was realized using single-cell metabolite profiles obtained by PACyESI-MS. The relationships between the accumulation of bioactive astaxanthin and changes in functional primary metabolites of Haematococcus were investigated. It was demonstrated that PACyESI-MS can detect the flexible change of metabolites in single microalgae cells under different nutritional conditions and during the synthesis of high-value products, which is expected to become an important tool for the design of metabolic engineering-based high-performance microalgae factories.

Ante- and Post-Mortem Fracture Identification Protocol Based on Low- and High-Level Fusion Using Fourier Transform Infrared Spectroscopy and Raman Spectroscopy Association

In this study, the application of low-level fusion (LLF) and high-level fusion (HLF) strategies using a combination of Fourier transform infrared spectroscopy (FT-IR) and Raman spectroscopy in the identification of antemortem and postmortem fracture at different postmortem intervals (PMIs) was investigated. On a technical level, the same hard tissue sample can be detected using a mix of FT-IR and Raman techniques. At the method level, two cutting-edge chemometrics approaches (LLF and HLF) combining FT-IR and Raman spectroscopic data are explored. The models were ranked in accordance with their parametric quality as follows: HLF and LLF + HLF models > LLF single model > Raman single model > FT-IR single model. The LLF model performed marginally better than the Raman model, however, when compared to other models, the HLF model performed considerably better. The HLF model achieved the best performance, with both cross-validation accuracy and test data set accuracy of 0.88. The importance of the feature wavelengths in the model construction process was subsequently evaluated by intersection fusion, and it was found that the absorbance bands of amide I, PO43- ν1 ν3, and CH2 in FT-IR and phenylalanine, CO32- ν1- PO43- ν3, and amide III in Raman have outstanding contributions to the construction of antemortem and postmortem fractures identification models. Overall, the combination of FT-IR and Raman with the HLF strategy is a novel and promising approach for developing antemortem and postmortem fracture identification models at different PMIs.

Multi-branch attention Raman network and surface-enhanced Raman spectroscopy for the classification of neurological disorders

Surface-enhanced Raman spectroscopy (SERS), a rapid, low-cost, non-invasive, ultrasensitive, and label-free technique, has been widely used in-situ and ex-situ biomedical diagnostics questions. However, analyzing and interpreting the untargeted spectral data remains challenging due to the difficulty of designing an optimal data pre-processing and modelling procedure. In this paper, we propose a Multi-branch Attention Raman Network (MBA-RamanNet) with a multi-branch attention module, including the convolutional block attention module (CBAM) branch, deep convolution module (DCM) branch, and branch weights, to extract more global and local information of characteristic Raman peaks which are more distinctive for classification tasks. CBAM, including channel and spatial aspects, is adopted to enhance the distinctive global information on Raman peaks. DCM is used to supplement local information of Raman peaks. Autonomously trained branch weights are applied to fuse the features of each branch, thereby optimizing the global and local information of the characteristic Raman peaks for identifying diseases. Extensive experiments are performed for two different neurological disorders classification tasks via untargeted serum SERS data. The results demonstrate that MBA-RamanNet outperforms commonly used CNN methods with an accuracy of 88.24% for the classification of healthy controls, mild cognitive impairment, Alzheimer's disease, and Non-Alzheimer's dementia; an accuracy of 90% for the classification of healthy controls, elderly depression, and elderly anxiety.

Raman Characterization of Plastics: A DFT Study of Polystyrene

Plastic materials are ubiquitous and raise concerns about their impact on health and the environment. To address these concerns, it is crucial to characterize the structural, size, and textural properties of plastics throughout their lifecycle from production to degradation. Raman spectroscopy appears as a valuable tool for this purpose, offering speed, robustness, and sensitivity to nanoscale and amorphous particles. In order to be properly used for plastics, the Raman response of reference materials needs to be carefully assessed, with the literature on such assessments being scarce. This study addresses this gap by using theoretical calculations to generate ab initio spectra for polystyrene, a reference material. The aim is to explain the origins of the spectral peaks and their consistency across various compositions and structures using linear ordered polymeric and finite amorphous models. The CRYSTAL package is employed to obtain full Raman spectra based on a careful benchmark of computational settings. While some peaks are present across all spectra and can serve for calibration, others exhibit structure-dependent behavior, enabling polymer identification. We conclude that Raman spectroscopy is a well-suited technique for plastics characterization provided that a careful analysis of signal origin is conducted to fully interpret the spectra and deploy applications.

Early diagnosis of thyroid-associated ophthalmopathy using label-free Raman spectroscopy and multivariate analysis

Thyroid-associated ophthalmopathy (TAO) is the most common orbital disease in adults, with complex clinical manifestations and significant impacts on the life quality of patients. The current diagnosis of TAO lacks reliable biomarkers for early and non-invasive screening and detection, easily leading to poor prognosis. Therefore, it is essential to explore new methods for accurately predicting TAO development in its early stage. In this study, Raman spectroscopy, with non-destructive, label-free, and high-sensitivity characteristics, was used to analyze the differences in biochemical components of orbital adipocyte and tear samples between TAO and control groups. Furthermore, a multivariate analysis method (i.e., Principal Component Analysis-Linear Discriminant Analysis (PCA-LDA)) was applied for data processing and analysis. Compared with controls, PCA-LDA yielded TAO diagnostic accuracies of 72.7% and 75.0% using orbital adipocytes and tears, respectively. Our proof-of-concept results suggest that Raman spectroscopy holds potential for exploring the underlying pathogenesis of TAO, and its potential application in early screening of other thyroid-associated diseases can be further expanded.

Spectral insights: Navigating the frontiers of biomedical and microbiological exploration with Raman spectroscopy

Raman spectroscopy (RS), a powerful analytical technique, has gained increasing recognition and utility in the fields of biomedical and biological research. Raman spectroscopic analyses find extensive application in the field of medicine and are employed for intricate research endeavors and diagnostic purposes. Consequently, it enjoys broad utilization within the realm of biological research, facilitating the identification of cellular classifications, metabolite profiling within the cellular milieu, and the assessment of pigment constituents within microalgae. This article also explores the multifaceted role of RS in these domains, highlighting its distinct advantages, acknowledging its limitations, and proposing strategies for enhancement.

Topical delivery of extracted curcumin as curcumin loaded spanlastics anti-aging gel: Optimization using experimental design and ex-vivo evaluation

Objective

This study aimed to extract and separate the organic coloring agent known as Curcumin from the rhizomes of Curcuma longa, and then to create Spanlastics that were loaded with curcumin using the ethanol injection technique. The optimized Spanlastic dispersions were then incorporated into a gel preparation for topical anti-aging use. The Spanlastic dispersions were analyzed for particle size, zeta potential, drug loading efficiency, and in vitro release profile. Furthermore, the rheological properties of the gel preparation were assessed, and a skin penetration study was conducted using confocal microscopy.

Methods

Twelve different Curcumin-loaded Spanlastic dispersions using the ethanol injection method with Span® 60 as a surfactant and Tween® 80 as an edge activator in varying ratios. The dispersions were then subjected to various tests, such as particle size analysis, zeta potential measurement, drug entrapment efficiency assessment, and in vitro release profiling. The optimized formula was selected using Design-Expert® software version 13, then used to create a gel preparation, which utilized 2% HPMC E50 as a gelling polymer. The gel was evaluated for its rheological properties and analyzed using confocal microscopy. Additionally, Raman analysis was performed to ensure that the polymers used in the gel were compatible with the drug substance.

Results

F5 formula, (that contains 10 mg Curcumin, and mixture 5 of span-tween mixtures that consist of 120 mg Span® 60 with 80 mg Tween® 80) was selected as the optimized formula with a desirability produced by Design Expert® software equal to 0.761, based on its particle size (212.8 ± 4.76), zeta potential (-29.4 ± 2.11), drug loading efficiency (99.788 ± 1.34), and in vitro release profile evaluations at Q 6hr equal to almost 100 %. Statistical significance (P < 0.05) was obtained using one-way ANOVA. Then F5 was used to formulate HPMC E50 gel-based preparations. The gel formula that was created and analyzed using Raman spectroscopy demonstrated no signs of incompatibility between the Curcumin and the polymers that were utilized.The confocal spectroscopy found that the anti-aging gel preparation showed promising results in terms of skin penetration. Also, images revealed that the gel could penetrate the layers of the skin (reached a depth of about 112.5 μm), where it could potentially target and reduce the appearance of fine lines and wrinkles. The gel also appeared to be well-tolerated by the skin, with no signs of irritation or inflammation observed in the images.

Conclusion

The obtained results successfully confirmed the potential of the promising (F5) formula to produce sustained release action and its ability to be incorporated into 2% HPMC E50 anti-aging gel. The confocal microscopy study suggested that the anti-aging gel had the potential to be an effective and safe topical treatment for aging skin.

Strategies and Progress of Raman Technologies for Cellular Uptake Analysis of the Drug Delivery Systems

Nanoparticle (NP)-based drug delivery systems have the potential to significantly enhance the pharmacological and therapeutic properties of drugs. These systems enhance the bioavailability and biocompatibility of pharmaceutical agents via enabling targeted delivery to specific tissues or organs. However, the efficacy and safety of these systems are largely dependent on the cellular uptake and intracellular transport of NPs. Thus, it is crucial to monitor the intracellular behavior of NPs within a single cell. Yet, it is challenging due to the complexity and size of the cell. Recently, the development of the Raman instrumentation offers a versatile tool to allow noninvasive cellular measurements. The primary objective of this review is to highlight the most recent advancements in Raman techniques (spontaneous Raman scattering, bioorthogonal Raman scattering, coherence Raman scattering, and surface-enhanced Raman scattering) when it comes to assessing the internalization of NP-based drug delivery systems and their subsequent movement within cells.

Machine learning applications for multi-source data of edible crops: A review of current trends and future prospects

The quality and safety of edible crops are key links inseparable from human health and nutrition. In the era of rapid development of artificial intelligence, using it to mine multi-source information on edible crops provides new opportunities for industrial development and market supervision of edible crops. This review comprehensively summarized the applications of multi-source data combined with machine learning in the quality evaluation of edible crops. Multi-source data can provide more comprehensive and rich information from a single data source, as it can integrate different data information. Supervised and unsupervised machine learning is applied to data analysis to achieve different requirements for the quality evaluation of edible crops. Emphasized the advantages and disadvantages of techniques and analysis methods, the problems that need to be overcome, and promising development directions were proposed. To monitor the market in real-time, the quality evaluation methods of edible crops must be innovated.

Spectroscopic techniques for monitoring stem cell and organoid proliferation in 3D environments for therapeutic development

Spectroscopic techniques for monitoring stem cell and organoid proliferation have gained significant attention in therapeutic development. Spectroscopic techniques such as fluorescence, Raman spectroscopy, and infrared spectroscopy offer noninvasive and real-time monitoring of biochemical and biophysical changes that occur during stem cell and organoid proliferation. These techniques provide valuable insight into the underlying mechanisms of action of potential therapeutic agents, allowing for improved drug discovery and screening. This review highlights the importance of spectroscopic monitoring of stem cell and organoid proliferation and its potential impact on therapeutic development. Furthermore, this review discusses recent advances in spectroscopic techniques and their applications in stem cell and organoid research. Overall, this review emphasizes the importance of spectroscopic techniques as valuable tools for studying stem cell and organoid proliferation and their potential to revolutionize therapeutic development in the future.

Accessing Properties of Molecular Compounds Involved in Cellular Metabolic Processes with Electron Paramagnetic Resonance, Raman Spectroscopy, and Differential Scanning Calorimetry

In this work, we review some physical methods of macroscopic experiments, which have been recently argued to be promising for the acquisition of valuable characteristics of biomolecular structures and interactions. The methods we focused on are electron paramagnetic resonance spectroscopy, Raman spectroscopy, and differential scanning calorimetry. They were chosen since it can be shown that they are able to provide a mutually complementary picture of the composition of cellular envelopes (with special attention paid to mycobacteria), transitions between their molecular patterning, and the response to biologically active substances (reactive oxygen species and their antagonists-antioxidants-as considered in our case study).

A Review on Photonic Sensing Technologies: Status and Outlook

In contemporary science and technology, photonic sensors are essential. They may be made to be extremely resistant to some physical parameters while also being extremely sensitive to other physical variables. Most photonic sensors may be incorporated on chips and operate with CMOS technology, making them suitable for use as extremely sensitive, compact, and affordable sensors. Photonic sensors can detect electromagnetic (EM) wave changes and convert them into an electric signal due to the photoelectric effect. Depending on the requirements, scientists have found ways to develop photonic sensors based on several interesting platforms. In this work, we extensively review the most generally utilized photonic sensors for detecting vital environmental parameters and personal health care. These sensing systems include optical waveguides, optical fibers, plasmonics, metasurfaces, and photonic crystals. Various aspects of light are used to investigate the transmission or reflection spectra of photonic sensors. In general, resonant cavity or grating-based sensor configurations that work on wavelength interrogation methods are preferred, so these sensor types are mostly presented. We believe that this paper will provide insight into the novel types of available photonic sensors.

Plasmonic Nanopillars-A Brief Investigation of Fabrication Techniques and Biological Applications

Nanopillars (NPs) are submicron-sized pillars composed of dielectrics, semiconductors, or metals. They have been employed to develop advanced optical components such as solar cells, light-emitting diodes, and biophotonic devices. To integrate localized surface plasmon resonance (LSPR) with NPs, plasmonic NPs consisting of dielectric nanoscale pillars with metal capping have been developed and used for plasmonic optical sensing and imaging applications. In this study, we studied plasmonic NPs in terms of their fabrication techniques and applications in biophotonics. We briefly described three methods for fabricating NPs, namely etching, nanoimprinting, and growing NPs on a substrate. Furthermore, we explored the role of metal capping in plasmonic enhancement. Then, we presented the biophotonic applications of high-sensitivity LSPR sensors, enhanced Raman spectroscopy, and high-resolution plasmonic optical imaging. After exploring plasmonic NPs, we determined that they had sufficient potential for advanced biophotonic instruments and biomedical applications.

Detecting nanoparticles by "listening"

In the macroscopic world, we can obtain some important information through the vibration of objects, that is, listening to the sound. Likewise, we can also get some information of the nanoparticles that we want to know by the means of "listening" in the microscopic world. In this review, we will introduce two sensing methods (cavity optomechanical sensing and surface-enhanced Raman scattering sensing) which can be used to detect the nanoparticles. The cavity optomechanical systems are mainly used to detect sub-gigahertz nanoparticle or cavity vibrations, while surface-enhanced Raman scattering is a well-known technique to detect molecular vibrations whose frequency generally exceeds terahertz. Therefore, the vibrational information of nanoparticles from low-frequency to high-frequency could be obtained by these two methods. The size of the viruses is at the nanoscale and we can regard it as a kind of nanoparticles. Rapid and ultrasensitive detection of the viruses is the key strategies to break the spread of the viruses in the community. Cavity optomechanical sensing enables rapid, ultrasensitive detection of nanoparticles through the interaction of light and mechanical oscillators and surface-enhanced Raman scattering is an attractive qualitatively analytical technique for chemical sensing and biomedical applications, which has been used to detect the SARS-CoV-2 infected. Hence, investigation in these two fields is of vital importance in preventing the spread of the virus from affecting human's life and health.

Technological aspects of manufacturing and analytical control of biological nanoparticles

Extracellular vesicles (EVs) are cell-derived biological nanoparticles that gained great interest for drug delivery. EVs have numerous advantages compared to synthetic nanoparticles, such as ideal biocompatibility, safety, ability to cross biological barriers and surface modification via genetic or chemical methods. On the other hand, the translation and the study of these carriers resulted difficult, mostly because of significant issues in up-scaling, synthesis and impractical methods of quality control. However, current manufacturing advances enable EV packaging with any therapeutic cargo, including DNA, RNA (for RNA vaccines and RNA therapeutics), proteins, peptides, RNA-protein complexes (including gene-editing complexes) and small molecules drugs. To date, an array of new and upgraded technologies have been introduced, substantially improving EV production, isolation, characterization and standardization. The used-to-be "gold standards" of EV manufacturing are now outdated, and the state-of-art requires extensive revision. This review re-evaluates the pipeline for EV industrial production and provides a critical overview of the modern technologies required for their synthesis and characterization.

Vibrational Spectroscopy as a Tool for Bioanalytical and Biomonitoring Studies

The review briefly describes various types of infrared (IR) and Raman spectroscopy methods. At the beginning of the review, the basic concepts of biological methods of environmental monitoring, namely bioanalytical and biomonitoring methods, are briefly considered. The main part of the review describes the basic principles and concepts of vibration spectroscopy and microspectrophotometry, in particular IR spectroscopy, mid- and near-IR spectroscopy, IR microspectroscopy, Raman spectroscopy, resonance Raman spectroscopy, Surface-enhanced Raman spectroscopy, and Raman microscopy. Examples of the use of various methods of vibration spectroscopy for the study of biological samples, especially in the context of environmental monitoring, are given. Based on the described results, the authors conclude that the near-IR spectroscopy-based methods are the most convenient for environmental studies, and the relevance of the use of IR and Raman spectroscopy in environmental monitoring will increase with time.

Stimulated Raman Scattering Imaging Sheds New Light on Lipid Droplet Biology

A lipid droplet (LD) is a dynamic organelle closely associated with cellular functions and energy homeostasis. Dysregulated LD biology underlies an increasing number of human diseases, including metabolic disease, cancer, and neurodegenerative disorder. Commonly used lipid staining and analytical tools have difficulty providing the information regarding LD distribution and composition at the same time. To address this problem, stimulated Raman scattering (SRS) microscopy uses the intrinsic chemical contrast of biomolecules to achieve both direct visualization of LD dynamics and quantitative analysis of LD composition with high molecular selectivity at the subcellular level. Recent developments of Raman tags have further enhanced sensitivity and specificity of SRS imaging without perturbing molecular activity. With these advantages, SRS microscopy has offered great promise for deciphering LD metabolism in single live cells. This article overviews and discusses the latest applications of SRS microscopy as an emerging platform to dissect LD biology in health and disease.

Raman Spectroscopy on Brain Disorders: Transition from Fundamental Research to Clinical Applications

Brain disorders such as brain tumors and neurodegenerative diseases (NDs) are accompanied by chemical alterations in the tissues. Early diagnosis of these diseases will provide key benefits for patients and opportunities for preventive treatments. To detect these sophisticated diseases, various imaging modalities have been developed such as computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). However, they provide inadequate molecule-specific information. In comparison, Raman spectroscopy (RS) is an analytical tool that provides rich information about molecular fingerprints. It is also inexpensive and rapid compared to CT, MRI, and PET. While intrinsic RS suffers from low yield, in recent years, through the adoption of Raman enhancement technologies and advanced data analysis approaches, RS has undergone significant advancements in its ability to probe biological tissues, including the brain. This review discusses recent clinical and biomedical applications of RS and related techniques applicable to brain tumors and NDs.

Photosynthesis under Biotic and Abiotic Environmental Stress

Photosynthesis is a unique process that has shaped life on our planet and created the conditions for all known life forms [...].

Effect of Laser-Induced Optical Breakdown on the Structure of Bsa Molecules in Aqueous Solutions: An Optical Study

The influence of laser radiation of a typical surgical laser on the physicochemical properties of the Bovine Serum Albumin (BSA) protein was studied. It was established that the physicochemical characteristics of optical breakdown weakly depend on the concentration of protein molecules. At the same time, the patterns observed for an aqueous solution of BSA irradiated with a laser for different time periods were extremely similar to the classical ones. It was established that after exposure to laser radiation, the optical density of protein solutions increases. At the same time, the intensity of BSA fluorescence due to aromatic amino acid residues decreases insignificantly after exposure to laser radiation. In this case, the position of the excitation and emission maximum does not change, and the shape of the fluorescence spot on 3D maps also does not change significantly. On the Raman spectrum after exposure to laser radiation, a significant decrease in 1570 cm⁻¹ was observed, which indicates the degradation of α-helices and, as a result, partial denaturation of BSA molecules. Partial denaturation did not significantly change the total area of protein molecules, since the refractive index of solutions did not change significantly. However, in BSA solutions, after exposure to laser radiation, the viscosity increased, and the pseudoplasticity of aqueous solutions decreased. In this case, there was no massive damage to the polypeptide chain; on the contrary, when exposed to optical breakdown, intense aggregation was observed, while aggregates with a size of 400 nm or more appeared in the solution. Thus, under the action of optical breakdown induced by laser radiation in a BSA solution, the processes of partial denaturation and aggregation prevail, aromatic amino acid residues are damaged to a lesser extent, and fragmentation of protein molecules is not observed.

Gold Nanocone Array with Extensive Electromagnetic Fields for Highly Reproducible Surface-Enhanced Raman Scattering Measurements

Surface-enhanced Raman scattering (SERS) is a technique used to distinguish the constitution of disease-related biomarkers in liquid biopsies, such as exosomes and circulating tumor cells, without any recognition elements. Previous studies using metal nanoparticle aggregates and angular nanostructures have achieved the detection of various biomarkers owing to strong hot spots and electromagnetic (EM) fields by localized surface plasmon resonance (LSPR). Although these SERS platforms enable significant enhancement of Raman signals, they still have some problems with the fabrication reproducibility of platforms in obtaining reproducible SERS signals. Therefore, highly reproducible fabrication of SERS platforms is required. Here, we propose the application of a polymer-based gold (Au) nanocone array (Au NCA), which extensively generates an enhanced EM field near the Au NCA surface by LSPR. This approach was experimentally demonstrated using a 785 nm laser, typically used for SERS measurements, and showed excellent substrate-to-substrate reproducibility (relative standard deviation (RSD) < 6%) using an extremely simple fabrication procedure and very low laser energy. These results proved that a Au NCA can be used as a highly reproducible SERS measurement to distinguish the constitution of biomarkers.

Influence of Mo and Fe on Photosynthetic and Nitrogenase Activities of Nitrogen-Fixing Cyanobacteria under Nitrogen Starvation

The potential of cyanobacteria to perform a variety of distinct roles vital for the biosphere, including nutrient cycling and environmental detoxification, drives interest in studying their biodiversity. Increasing soil erosion and the overuse of chemical fertilizers are global problems in developed countries. The option might be to switch to organic farming, which entails largely the use of biofertilisers. Cyanobacteria are prokaryotic, photosynthetic organisms with considerable potential, within agrobiotechnology, to produce biofertilisers. They contribute significantly to plant drought resistance and nitrogen enrichment in the soil. This study sought, isolated, and investigated nitrogen-fixing cyanobacterial strains in rice fields, and evaluated the effect of Mo and Fe on photosynthetic and nitrogenase activities under nitrogen starvation. Cyanobacterial isolates, isolated from rice paddies in Kazakhstan, were identified as Trichormus variabilis K-31 (MZ079356), Cylindrospermum badium J-8 (MZ079357), Nostoc sp. J-14 (MZ079360), Oscillatoria brevis SH-12 (MZ090011), and Tolypothrix tenuis J-1 (MZ079361). The study of the influence of various concentrations of Mo and Fe on photosynthetic and nitrogenase activities under conditions of nitrogen starvation revealed the optimal concentrations of metals that have a stimulating effect on the studied parameters.