Metabolites Potentially Determine the High Antioxidant Properties of Limosilactobacillus fermentum U-21.

Many kinds of Lactobacillus are common occupants of humans' digestive tract that support the preservation of a balanced microbial environment that benefits host health. In this study, the unique lactic acid bacterium strain Limosilactobacillus fermentum U-21, which was isolated from the feces of a healthy human, was examined for its metabolite profile in order to compare it to that of the strain L. fermentum 279, which does not have antioxidant (AO) capabilities. By using GC × GC-MS, the metabolite fingerprint of each strain was identified, and the data were then subjected to multivariate bioinformatics analysis. The L. fermentum U-21 strain has previously been shown to possess distinctive antioxidant properties in in vivo and in vitro studies, positioning it as a drug candidate for the treatment of Parkinsonism. The production of multiple distinct compounds is shown by the metabolite analysis, demonstrating the unique characteristics of the L. fermentum U-21 strain. According to reports, some of the L. fermentum U-21 metabolites found in this study have health-promoting properties. The GC × GC-MS-based metabolomic tests defined strain L. fermentum U-21 as a potential postbiotic with significant antioxidant potential.

Kanamycin and Ofloxacin Activate the Intrinsic Resistance to Multiple Antibiotics in Mycobacterium smegmatis.

Drug resistance (DR) in Mycobacterium tuberculosis is the main problem in fighting tuberculosis (TB). This pathogenic bacterium has several types of DR implementation: acquired and intrinsic DR. Recent studies have shown that exposure to various antibiotics activates multiple genes, including genes responsible for intrinsic DR. To date, there is evidence of the acquisition of resistance at concentrations well below the standard MICs. In this study, we aimed to investigate the mechanism of intrinsic drug cross-resistance induction by subinhibitory concentrations of antibiotics. We showed that pretreatment of M. smegmatis with low doses of antibiotics (kanamycin and ofloxacin) induced drug resistance. This effect may be caused by a change in the expression of transcriptional regulators of the mycobacterial resistome, in particular the main transcriptional regulator whiB7.

Using the Software DeepWings© to Classify Honey Bees across Europe through Wing Geometric Morphometrics.

DeepWings© is a software that uses machine learning to automatically classify honey bee subspecies by wing geometric morphometrics. Here, we tested the five subspecies classifier (A. m. carnica, Apis mellifera caucasia, A. m. iberiensis, Apis mellifera ligustica, and A. m. mellifera) of DeepWings© on 14,816 wing images with variable quality and acquired by different beekeepers and researchers. These images represented 2601 colonies from the native ranges of the M-lineage A. m. iberiensis and A. m. mellifera, and the C-lineage A. m. carnica. In the A. m. iberiensis range, 92.6% of the colonies matched this subspecies, with a high median probability (0.919). In the Azores, where the Iberian subspecies was historically introduced, a lower proportion (85.7%) and probability (0.842) were observed. In the A. m mellifera range, only 41.1 % of the colonies matched this subspecies, which is compatible with a history of C-derived introgression. Yet, these colonies were classified with the highest probability (0.994) of the three subspecies. In the A. m. carnica range, 88.3% of the colonies matched this subspecies, with a probability of 0.984. The association between wing and molecular markers, assessed for 1214 colonies from the M-lineage range, was highly significant but not strong (r = 0.31, p < 0.0001). The agreement between the markers was influenced by C-derived introgression, with the best results obtained for colonies with high genetic integrity. This study indicates the good performance of DeepWings© on a realistic wing image dataset.

Genetic Structure of Apis cerana Populations from South Korea, Vietnam and the Russian Far East Based on Microsatellite and Mitochondrial DNA Polymorphism.

In this article, we present the results of the genetic analysis of Apis cerana samples from the Russian Far East, South Korea and Vietnam. An analysis of the polymorphism of seven microsatellite loci and an assessment of the haplotype diversity of the mtDNA tRNAleu-COII locus were performed. A fragment of about 431 bp in tRNAleu-COII was sequenced. The analysis showed the presence of 14 haplotypes, while the predominant haplotype was Japan1. Microsatellite data revealed two differentiated clusters. The first cluster contained tropical climate A. cerana samples from Vietnam, and the second cluster combined temperate climate A. cerana samples from the Russian Far East and South Korea.

Genetic Relationships and Signatures of Adaptation to the Climatic Conditions in Populations of Apis cerana Based on the Polymorphism of the Gene Vitellogenin.

Apis cerana and Apis mellifera are important honey bee species in Asia. A. cerana populations are distributed from a cold, sharply continental climate in the north to a hot, subtropical climate in the south. Due to the Sacbrood virus, almost all A. cerana populations in Asia have declined significantly in recent decades and have recovered over the past five years. This could lead to a shift in the gene pool of local A. cerana populations that could affect their sustainability and adaptation. It was assumed that adaptation of honey bees could be observed by comparative analysis of the sequences of genes involved in development, labor division, and caste differentiation, such as the gene Vitellogenin VG. The VG gene nucleotide sequences were used to assess the genetic structure and signatures of adaptation of local populations of A. cerana from Korea, Russia, Japan, Nepal, and China. A. mellifera samples from India and Poland were used as the outgroup. The signatures of adaptive selection were found in the local population of A. cerana using VG gene sequence analysis based on Jukes−Cantor genetic distances, cluster analysis, dN/dS ratio evaluation, and Tajima's D neutrality test. Based on analysis of the VG gene sequences, Apis cerana koreana subspecies in the Korean Peninsula were subdivided into three groups in accordance with their geographic localization from north to south. The VG gene sequences are acceptable tools to study the sustainability and adaptation of A. cerana populations.

Common Inflammatory Mechanisms in COVID-19 and Parkinson's Diseases: The Role of Microbiome, Pharmabiotics and Postbiotics in Their Prevention.

In the last decade, metagenomic studies have shown the key role of the gut microbiome in maintaining immune and neuroendocrine systems. Malfunction of the gut microbiome can induce inflammatory processes, oxidative stress, and cytokine storm. Dysfunction of the gut microbiome can be caused by short-term (virus infection and other infectious diseases) or long-term (environment, nutrition, and stress) factors. Here, we reviewed the inflammation and oxidative stress in neurodegenerative diseases and coronavirus infection (COVID-19). Here, we reviewed the renin-angiotensin-aldosterone system (RAAS) involved in the processes of formation of oxidative stress and inflammation in viral and neurodegenerative diseases. Moreover, the coronavirus uses ACE2 receptors of the RAAS to penetrate human cells. The coronavirus infection can be the trigger for neurodegenerative diseases by dysfunction of the RAAS. Pharmabiotics, postbiotics, and next-generation probiotics, are considered as a means to prevent oxidative stress, inflammatory processes, neurodegenerative and viral diseases through gut microbiome regulation.

Authoritative subspecies diagnosis tool for European honey bees based on ancestry informative SNPs.

BACKGROUND: With numerous endemic subspecies representing four of its five evolutionary lineages, Europe holds a large fraction of Apis mellifera genetic diversity. This diversity and the natural distribution range have been altered by anthropogenic factors. The conservation of this natural heritage relies on the availability of accurate tools for subspecies diagnosis. Based on pool-sequence data from 2145 worker bees representing 22 populations sampled across Europe, we employed two highly discriminative approaches (PCA and FST) to select the most informative SNPs for ancestry inference. RESULTS: Using a supervised machine learning (ML) approach and a set of 3896 genotyped individuals, we could show that the 4094 selected single nucleotide polymorphisms (SNPs) provide an accurate prediction of ancestry inference in European honey bees. The best ML model was Linear Support Vector Classifier (Linear SVC) which correctly assigned most individuals to one of the 14 subspecies or different genetic origins with a mean accuracy of 96.2% ± 0.8 SD. A total of 3.8% of test individuals were misclassified, most probably due to limited differentiation between the subspecies caused by close geographical proximity, or human interference of genetic integrity of reference subspecies, or a combination thereof. CONCLUSIONS: The diagnostic tool presented here will contribute to a sustainable conservation and support breeding activities in order to preserve the genetic heritage of European honey bees.

A revision of subspecies structure of western honey bee Apis mellifera.

The taxonomy of honey bee A. mellifera contains a lot of issues due to the specificity of population structure, features of biology and resolutions of honey bee subspecies discrimination methods. There are a lot of transition zones between ranges of subspecies which led to the gradual changes of characteristics among neighbor subspecies. The modern taxonomic pattern of honey bee Apis mellifera is given in this paper. Thirty-three distinct honey bee subspecies are distributed across all Africa (11 subspecies), Western Asia and the Middle East (9 subspecies), and Europe (13 subspecies). All honey bee subspecies are subdivided into 5 evolutionary lineages: lineage A (10 subspecies) and its sublineage Z (3 subspecies), lineage M (3 subspecies), lineage C (10 subspecies), lineage O (3 subspecies), lineage Y (1 subspecies), lineage C or O (3 subspecies).

Estimation of C-derived introgression into A. m. mellifera colonies in the Russian Urals using microsatellite genotyping.

BACKGROUND: Marker-assisted selection is well established in animal breeding method of selecting individuals with desirable traits in a breeding scheme based on DNA molecular marker patterns. OBJECTIVE: Genetic diversity and C-derived admixture into local purebred gene pool of A. m. mellifera colonies was assessed using polymorphism of nine microsatellite loci in order to provide further marker-assisted selection of desired honey bee colonies. METHODS: The genetic diversity and the level of C-derived introgression into A. m. mellifera colonies in the Shulgan-Tash Nature Reserve (Russia) was assessed based on nine microsatellite loci (ap243, 4a110, A24, A8, A43, A113, A88, Ap049, A28), which were analized using the fragment analysis of the PCR products in Applied Biosystems 3130 DNA Analyzer. Phylogenetic relationship of colonies was evaluated using Neighbor-Joining methods with Cavalli-Sforza and Edwards genetic distance using the PHYLIP 3.68. The model-based Bayesian clustering algorithm implemented in STRUCTURE 2.3.3 was employed to infer membership and introgression proportions (Q-value). RESULTS: In the Shulgan-Tash Nature Reserve colonies of A. m. mellifera subdivided into four groups by level of C-derived introgression. Only five colonies of A. m. mellifera had C-derived introgression which varied from 0.5 to 2%. The genetic diversity in colonies of A. m. mellifera varied from 0.12 to 0.40. The Neighbor-Joining tree demonstrates the genetic relationship of A. m. mellifera colonies, which subdivided into three groups with different levels of C-derived introgression. Group 1 combined five honey bee colonies Bort_1, Bort_2, Bort_3, Baisalyan_1, and Kush_7 with a fraction of introgression close to 0.000 and genetic diversity from 0.20 to 0.25. CONCLUSION: The results showed the excellence of nine microsatellite loci genotyping in estimation of genetic diversity, distinguishing the two European evolutionary lineages M and C and estimating C-derived introgression. These genetic parameters can be applied further to perform the marker-assisted selection of purebred dark European honey bees.

Abdominal contact of fluvalinate induces olfactory deficit in Apis mellifera.

τ-Fluvalinate (fluvalinate) is a highly selective pyrethroid insecticide compound used for controlling ectoparasitic mites that cause major damages in honey bee colonies. Although honey bees have resistance and low toxicity to this xenobiotic chemical, little is known about the effects of this chemical on sensory modulation and behaviors in honey bees. Here we addressed the effect on olfactory cognition at the behavioral, molecular, and neurophysiological levels. First, we found that topical application of fluvalinate to honeybee abdomen elicited somewhat severe toxicity to honey bees. Furthermore, honeybees treated with sublethal doses of fluvalinate showed a significant decrease in olfactory responses. At the molecular level, there was no change in gene expression levels of odorant receptor co-receptor (Orco), which is important for electrical conductivity induced by odorant binding in insects. Rather, small neuropeptide F (sNPF) signaling pathway was involved in olfactory fluctuation after treatment of fluvalinate. This indicates that olfactory deficits by abdominal contact of fluvalinate may stem from various internal molecular pathways in honey bees.

Author Correction: Characterization and its implication of a novel taste receptor detecting nutrients in the honey bee, Apis mellifera.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Characterization and its implication of a novel taste receptor detecting nutrients in the honey bee, Apis mellifera.

Umami taste perception indicates the presence of amino acids, which are essential nutrients. Although the physiology of umami perception has been described in mammals, how insects detect amino acids remains unknown except in Drosophila melanogaster. We functionally characterized a gustatory receptor responding to L-amino acids in the western honey bee, Apis mellifera. Using a calcium-imaging assay and two-voltage clamp recording, we found that one of the honey bee's gustatory receptors, AmGr10, functions as a broadly tuned amino acid receptor responding to glutamate, aspartate, asparagine, arginine, lysine, and glutamine, but not to other sweet or bitter compounds. Furthermore, the sensitivity of AmGr10 to these L-amino acids was dramatically enhanced by purine ribonucleotides, like inosine-5'-monophosphate (IMP). Contact sensory hairs in the mouthpart of the honey bee responded strongly to glutamate and aspartate, which house gustatory receptor neurons expressing AmGr10. Interestingly, AmGr10 protein is highly conserved among hymenopterans but not other insects, implying unique functions in eusocial insects.