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Bee-collected pollen (BCP) and bee bread (BB) are honey bee products known for their beneficial biological properties. The main goal of this study was to investigate BB microbiota and its contribution to bioactivity exerted by BB. The microbiota of BB samples collected at different maturation stages was investigated via culture-independent (Next Generation Sequencing, NGS) and culture-dependent methods. Microbial communities dynamically fluctuate during BB maturation, ending in a stable microbial community structure in mature BB. Bee bread bacterial isolates were tested for phenotypes and genes implicated in the production and secretion of enzymes as well as antibacterial activity. Out of 309 bacterial isolates, 41 secreted hemicellulases, 13 cellulases, 39 amylases, 132 proteinases, 85 Coomassie brilliant blue G or R dye-degrading enzymes and 72 Malachite Green dye-degrading enzymes. Furthermore, out of 309 bacterial isolates, 42 exhibited antibacterial activity against Staphylococcus aureus, 34 against Pseudomonas aeruginosa, 47 against Salmonella enterica ser. Typhimurium and 43 against Klebsiella pneumoniae. Artificially fermented samples exerted higher antibacterial activity compared to fresh BCP, strongly indicating that BB microbiota contribute to BB antibacterial activity. Our findings suggest that BB microbiota is an underexplored source of novel antimicrobial agents and enzymes that could lead to new applications in medicine and the food industry.

The causal relationship between HPV and cervical cancer in association with the high prevalence of high risk HPV genotypes led to the design of HPV vaccines based on the major capsid L1 protein. In recent years, capsid protein L2 has also become a focal point in the field of vaccine research. The present review focuses on the variability of HPV16 L1 and L2 genes, emphasizing the distribution of specific amino acid changes in the epitopes of capsid proteins. Moreover, a substantial bioinformatics analysis was conducted to describe the worldwide distribution of amino acid substitutions throughout HPV16 L1, L2 proteins. Five amino acid changes (T176N, N181T; EF loop), (T266A; FG loop), (T353P, T389S; HI loop) are frequently observed in the L1 hypervariable surface loops, while two amino acid substitutions (D43E, S122P) are adjacent to L2 specific epitopes. These changes have a high prevalence in certain geographic regions. The present review suggests that the extensive analysis of the amino acid substitutions in the HPV16 L1 immunodominant loops may provide insights concerning the ability of the virus in evading host immune response in certain populations. The genetic variability of the HPV16 L1 and L2 epitopes should be extensively analyzed in a given population.

Honey bees face new challenges, ranging from climate crisis to emerging pathogens such as Vairimorpha (Nosema) ceranae that synergistically cause a syndrome designated as colony collapse disorder (CCD). This study employed a metataxonomic approach in order to investigate if V. ceranae affects gut microbiota (bacteria and fungi) of adult A. mellifera honey bees as well as microbiota of bee bread (BB) stored in colonies demonstrating severe V. ceranae infection (spore counts >2,500,000 per bee) as compared with colonies exhibiting very low spore counts (Podosphaera spp. were absent in BB samples collected from colonies with high spore counts, while relative abundance of Blumeria spp. was significantly decreased. Interestingly, relative abundance of Rosenbergiella spp. was increased in BB samples collected from colonies with high spore counts. The reason for these findings remains elusive. Although further research is warranted, overall reduced microbial diversity and relative abundance of certain microbial groups may serve as biomarkers of colony collapse.

Previous analyses have identified certain but limited evidence of recombination among HPV16 genomes, in accordance with a general perception that DNA viruses do not frequently recombine. In this evolutionary/bioinformatics study we have analyzed more than 3600 publicly available complete and partial HPV16 genomes. By studying the phylogenetic incongruence, similarity plots and the distribution patterns of lineage-specific SNPs, we identify several potential recombination events between the two major HPV16 evolutionary clades. These two clades comprise the (widely considered) phenotypically more benign (lower risk) lineage A and the (widely considered) phenotypically more aggressive (higher risk) non-European lineages B, C and D. We observe a frequency of potential recombinant sequences ranging between 0.3 and 1.2% which is low, but nevertheless considerable. Our findings have clinical implications and highlight that HPV16 genotyping and risk assessment based only on certain genomic regions and not the entire genome may provide a false genotype and, therefore, its associated risk estimate. Finally, based on this analysis, we have developed a bioinformatics tool that automates the entire process of HPV16 lineage genotyping, recombination detection and further identifies, within the submitted sequences, SNPs that have been reported in the literature to increase the risk of cancer.

It has been suggested that microorganisms present in honey are a potential source of antimicrobial compounds. This study aimed to isolate and characterize bacteria from 46 Greek honey samples of diverse botanical and geographical origin and to determine whether these bacteria demonstrate antibacterial activity against five important nosocomial and foodborne pathogens. In total, 2014 bacterial isolates were obtained and screened for antibacterial activity. Overall, 16% of the isolates inhibited the growth of Staphylococcus aureus, 11.2% inhibited the growth of Pseudomonas aeruginosa and Acinetobacter baumannii, 10.2% inhibited the growth of Salmonella Typhimurium and 12.4% of the isolates affected the growth of Citrobacter freundii. In total, 316 isolates that inhibited the growth of more than two of the tested pathogens were grouped by restriction fragment length polymorphisms (RFLP) analysis of the 16S rRNA gene amplicon. Fifty of them were identified by 16S rRNA gene sequencing. The majority, 62% of the isolates, belonged to the genus Bacillus. Only 10% of the isolates were identified as Gram-negative bacteria. Furthermore, in several bacterial isolates, genes encoding polyketide synthases and nonribosomal peptide synthetases that catalyze the biosynthesis of secondary metabolites which might contribute to the exerted antimicrobial activity, were detected. This study demonstrates that honey microbiota exerts antimicrobial activity and is a putative source of secondary metabolites against important nosocomial and food pathogens that warrants further investigation.

Bee bread is the only fermented product of the beehive. It constitutes the main source of proteins, lipids, vitamins, and macro- and microelements in honeybee nutrition and it exerts antioxidant and antimicrobial properties, though research on these aspects has been limited so far. In this study 18 samples of Greek bee bread, two of which were monofloral, were collected during different seasons from diverse locations such as Crete and Mount Athos and were tested for their bioactivity. Samples were analyzed for their antibacterial properties, antioxidant activity, total phenolic content (TPC), and total flavonoid content (TFC). The antimicrobial activity of each sample was tested against Staphylococcus aureus, Pseudomonas aeruginosa, Klebsiella pneumoniae, and Salmonella typhimurium. Our data demonstrate that all samples exert inhibitory and most of them bactericidal activity against at least two pathogens. Furthermore, all samples exert significant antioxidant activity, where the monofloral Castanea Sativa sample demonstrated superior antioxidant activity. Nevertheless, the antioxidant and antimicrobial activity were not strongly correlated. Furthermore, machine learning methods demonstrated that the palynological composition of the samples is a good predictor of their TPC and ABTS activity. This is the first study that focuses on the biological properties of Greek bee bread and demonstrates that bee bread can be considered a functional food and a possible source of novel antimicrobial compounds.

Pine honey is a unique type of honeydew honey produced exclusively in Eastern Mediterranean countries like Greece and Turkey. Although the antioxidant and anti-inflammatory properties of pine honey are well documented, few studies have investigated so far its antibacterial activity. This study investigates the antibacterial effects of pine honey against P. aeruginosa PA14 at the molecular level using a global transcriptome approach via RNA-sequencing. Pine honey treatment was applied at sub-inhibitory concentration and short exposure time (0.5× of minimum inhibitory concentration –MIC- for 45 min). Pine honey induced the differential expression (>two-fold change and p ≤ 0.05) of 463 genes, with 274 of them being down-regulated and 189 being up-regulated. Gene ontology (GO) analysis revealed that pine honey affected a wide range of biological processes (BP). The most affected down-regulated BP GO terms were oxidation-reduction process, transmembrane transport, proteolysis, signal transduction, biosynthetic process, phenazine biosynthetic process, bacterial chemotaxis, and antibiotic biosynthetic process. The up-regulated BP terms, affected by pine honey treatment, were those related to the regulation of DNA-templated transcription, siderophore transport, and phosphorylation. Pathway analysis revealed that pine honey treatment significantly affected two-component regulatory systems, ABC transporter systems, quorum sensing, bacterial chemotaxis, biofilm formation and SOS response. These data collectively indicate that multiple mechanisms of action are implicated in antibacterial activity exerted by pine honey against P. aeruginosa.

The aim of the present study was to compare the efficiency of targeted and untargeted breath analysis in the discrimination of lung cancer (Ca+) patients from healthy people (HC) and patients with benign pulmonary diseases (Ca−). Exhaled breath samples from 49 Ca+ patients, 36 Ca− patients and 52 healthy controls (HC) were analyzed by an SPME–GC–MS method. Untargeted treatment of the acquired data was performed with the use of the web-based platform XCMS Online combined with manual reprocessing of raw chromatographic data. Machine learning methods were applied to estimate the efficiency of breath analysis in the classification of the participants. Results: Untargeted analysis revealed 29 informative VOCs, from which 17 were identified by mass spectra and retention time/retention index evaluation. The untargeted analysis yielded slightly better results in discriminating Ca+ patients from HC (accuracy: 91.0%, AUC: 0.96 and accuracy 89.1%, AUC: 0.97 for untargeted and targeted analysis, respectively) but significantly improved the efficiency of discrimination between Ca+ and Ca− patients, increasing the accuracy of the classification from 52.9 to 75.3% and the AUC from 0.55 to 0.82. Conclusions: The untargeted breath analysis through the inclusion and utilization of newly identified compounds that were not considered in targeted analysis allowed the discrimination of the Ca+ from Ca− patients, which was not achieved by the targeted approach.

Considering that 70% of our planet’s surface is covered by oceans, it is likely that undiscovered biodiversity is still enormous. A large portion of marine biodiversity consists of microbiomes. They are very attractive targets of bioprospecting because they are able to produce a vast repertoire of secondary metabolites in order to adapt in diverse environments. In many cases secondary metabolites of pharmaceutical and biotechnological interest such as nonribosomal peptides (NRPs) and polyketides (PKs) are synthesized by multimodular enzymes named nonribosomal peptide synthetases (NRPSes) and type-I polyketide synthases (PKSes-I), respectively. Novel findings regarding the mechanisms underlying NRPS and PKS evolution demonstrate how microorganisms could leverage their metabolic potential. Moreover, these findings could facilitate synthetic biology approaches leading to novel bioactive compounds. Ongoing advances in bioinformatics and next-generation sequencing (NGS) technologies are driving the discovery of NRPs and PKs derived from marine microbiomes mainly through two strategies: genome-mining and metagenomics. Microbial genomes are now sequenced at an unprecedented rate and this vast quantity of biological information can be analyzed through genome mining in order to identify gene clusters encoding NRPSes and PKSes of interest. On the other hand, metagenomics is a fast-growing research field which directly studies microbial genomes and their products present in marine environments using culture-independent approaches. The aim of this review is to examine recent developments regarding discovery strategies of bioactive compounds synthesized by NRPS and type-I PKS derived from marine microbiomes and to highlight the vast diversity of NRPSes and PKSes present in marine environments by giving examples of recently discovered bioactive compounds.