The use of omics technologies in creating LBP and postbiotics based on the Limosilactobacillus fermentum U-21.

In recent years, there has been an increasing tendency to create drugs based on certain commensal bacteria of the human microbiota and their ingredients, primarily focusing on live biotherapeutics (LBPs) and postbiotics. The creation of such drugs, termed pharmacobiotics, necessitates an understanding of their mechanisms of action and the identification of pharmacologically active ingredients that determine their target properties. Typically, these are complexes of biologically active substances synthesized by specific strains, promoted as LBPs or postbiotics (including vesicles): proteins, enzymes, low molecular weight metabolites, small RNAs, etc. This study employs omics technologies, including genomics, proteomics, and metabolomics, to explore the potential of Limosilactobacillus fermentum U-21 for innovative LBP and postbiotic formulations targeting neuroinflammatory processes. Proteomic techniques identified and quantified proteins expressed by L. fermentum U-21, highlighting their functional attributes and potential applications. Key identified proteins include ATP-dependent Clp protease (ClpL), chaperone protein DnaK, protein GrpE, thioredoxin reductase, LysM peptidoglycan-binding domain-containing protein, and NlpC/P60 domain-containing protein, which have roles in disaggregase, antioxidant, and immunomodulatory activities. Metabolomic analysis provided insights into small-molecule metabolites produced during fermentation, revealing compounds with anti-neuroinflammatory activity. Significant metabolites produced by L. fermentum U-21 include GABA (γ-aminobutyric acid), niacin, aucubin, and scyllo-inositol. GABA was found to stabilize neuronal activity, potentially counteracting neurodegenerative processes. Niacin, essential for optimal nervous system function, was detected in vesicles and culture fluid, and it modulates cytokine production, maintaining immune homeostasis. Aucubin, an iridoid glycoside usually secreted by plants, was identified as having antioxidant properties, addressing issues of bioavailability for therapeutic use. Scyllo-inositol, identified in vesicles, acts as a chemical chaperone, reducing abnormal protein clumps linked to neurodegenerative diseases. These findings demonstrate the capability of L. fermentum U-21 to produce bioactive substances that could be harnessed in the development of pharmacobiotics for neurodegenerative diseases, contributing to their immunomodulatory, anti-neuroinflammatory, and neuromodulatory activities. Data of the HPLC-MS/MS analysis are available via ProteomeXchange with identifier PXD050857.

Komagataella phaffii as a Platform for Heterologous Expression of Enzymes Used for Industry.

In the 1980s, Escherichia coli was the preferred host for heterologous protein expression owing to its capacity for rapid growth in complex media; well-studied genetics; rapid and direct transformation with foreign DNA; and easily scalable fermentation. Despite the relative ease of use of E. coli for achieving the high expression of many recombinant proteins, for some proteins, e.g., membrane proteins or proteins of eukaryotic origin, this approach can be rather ineffective. Another microorganism long-used and popular as an expression system is baker's yeast, Saccharomyces cerevisiae. In spite of a number of obvious advantages of these yeasts as host cells, there are some limitations on their use as expression systems, for example, inefficient secretion, misfolding, hyperglycosylation, and aberrant proteolytic processing of proteins. Over the past decade, nontraditional yeast species have been adapted to the role of alternative hosts for the production of recombinant proteins, e.g., Komagataella phaffii, Yarrowia lipolytica, and Schizosaccharomyces pombe. These yeast species' several physiological characteristics (that are different from those of S. cerevisiae), such as faster growth on cheap carbon sources and higher secretion capacity, make them practical alternative hosts for biotechnological purposes. Currently, the K. phaffii-based expression system is one of the most popular for the production of heterologous proteins. Along with the low secretion of endogenous proteins, K. phaffii efficiently produces and secretes heterologous proteins in high yields, thereby reducing the cost of purifying the latter. This review will discuss practical approaches and technological solutions for the efficient expression of recombinant proteins in K. phaffii, mainly based on the example of enzymes used for the feed industry.

The Molecular Aspects of Functional Activity of Macrophage-Activating Factor GcMAF.

Group-specific component macrophage-activating factor (GcMAF) is the vitamin D3-binding protein (DBP) deglycosylated at Thr420. The protein is believed to exhibit a wide range of therapeutic properties associated with the activation of macrophagal immunity. An original method for GcMAF production, DBP conversion to GcMAF, and the analysis of the activating potency of GcMAF was developed in this study. Data unveiling the molecular causes of macrophage activation were obtained. GcMAF was found to interact with three CLEC10A derivatives having molecular weights of 29 kDa, 63 kDa, and 65 kDa. GcMAF interacts with high-molecular-weight derivatives via Ca2+-dependent receptor engagement. Binding to the 65 kDa or 63 kDa derivative determines the pro- and anti-inflammatory direction of cytokine mRNA expression: 65 kDa-pro-inflammatory (TNF-α, IL-1ß) and 63 kDa-anti-inflammatory (TGF-ß, IL-10). No Ca2+ ions are required for the interaction with the canonical 29 kDa CLEC10A. Both forms, DBP protein and GcMAF, bind to the 29 kDa CLEC10A. This interaction is characterized by the stochastic mRNA synthesis of the analyzed cytokines. Ex vivo experiments have demonstrated that when there is an excess of GcMAF ligand, CLEC10A forms aggregate, and the mRNA synthesis of analyzed cytokines is inhibited. A schematic diagram of the presumable mechanism of interaction between the CLEC10A derivatives and GcMAF is provided. The principles and elements of standardizing the GcMAF preparation are elaborated.

Accurate noise-robust classification of Bacillus species from MALDI-TOF MS spectra using a denoising autoencoder.

Bacillus strains are ubiquitous in the environment and are widely used in the microbiological industry as valuable enzyme sources, as well as in agriculture to stimulate plant growth. The Bacillus genus comprises several closely related groups of species. The rapid classification of these remains challenging using existing methods. Techniques based on MALDI-TOF MS data analysis hold significant promise for fast and precise microbial strains classification at both the genus and species levels. In previous work, we proposed a geometric approach to Bacillus strain classification based on mass spectra analysis via the centroid method (CM). One limitation of such methods is the noise in MS spectra. In this study, we used a denoising autoencoder (DAE) to improve bacteria classification accuracy under noisy MS spectra conditions. We employed a denoising autoencoder approach to convert noisy MS spectra into latent variables representing molecular patterns in the original MS data, and the Random Forest method to classify bacterial strains by latent variables. Comparison of the DAE-RF with the CM method using the artificially noisy test samples showed that DAE-RF offers higher noise robustness. Hence, the DAE-RF method could be utilized for noise-robust, fast, and neat classification of Bacillus species according to MALDI-TOF MS data.

A GC-MS Chemotaxonomic Study on Lipophilic Compounds in the Bark of S. aucuparia subsp. sibirica Trees from the Population Growing in Akademgorodok, Novosibirsk (Russia).

Determination of chemotypes and of their role in the polymorphism of populations is an important field in the research on secondary metabolites of plants. In the present study, by gas chromatography coupled with mass spectrometry, the composition of bark extracts from rowan S. aucuparia subsp. sibirica was determined for 16 trees growing within Akademgorodok of Novosibirsk, with bark samples collected both in winter and summer. Among 101 fully or partially identified metabolites, there are alkanes, alkenes, linear alcohols, fatty acids and their derivatives, phenols and their derivatives, prunasin and its parent and derivative compounds, polyprenes and their derivatives, cyclic diterpenes, and phytosterols. These compounds were grouped according to their biosynthesis pathways. Cluster analysis revealed two groups among the bark samples collected in winter and three groups among bark samples collected in summer. The key determinants of this clustering are the biosynthesis of metabolites via the cyanogenic pathway (especially potentially toxic prunasin) and their formation via the phytosterol pathway (especially potentially pharmacologically useful lupeol). It follows from the results that the presence of chemotypes having sharply different profiles of metabolites in a population from a small geographic area invalidates the practice of general sampling to obtain averaged data when a population is described. From the standpoint of possible industrial use or plant selection based on metabolomic data, it is possible to select specific sets of samples containing a minimal amount of potentially toxic compounds and the largest amount of potentially useful substances.