γH2AX has emerged in the last 20 years as a central player in the DDR (DNA damage response), with specificity for DSBs (double-strand breaks). Upon the generation of DSBs, γ-phosphorylation extends along megabase-long domains in chromatin, both sides of the damage. The significance of this mechanism is of great importance; it depicts a biological amplification mechanism where one DSB induces the γ-phosphorylation of thousands of H2AX molecules along megabaselong domains of chromatin, that are adjusted to the sites of DSBs. A sequential recruitment of signal transduction factors that interact to each other and become activated to further amplify the signal that will travel to the cytoplasm take place on the γ-phosphorylated chromatin. γ-phosphorylation is an early event in the DSB damage response, induced in all phases of the cell cycle, and participates in both DSB repair pathways, the HR (homologous recombination) and NHEJ (non-homologous end joining). Today, numerous studies support the notion that γH2AX functions as a guardian of the genome by preventing misrepaired DSB that increase the mutation load of the cells and may further lead to genome instability and carcinogenesis.

Sfela is a white brined Greek cheese of protected designation of origin (PDO) produced in the Peloponnese region from ovine, caprine milk, or a mixture of the two. Despite the PDO status of Sfela, very few studies have addressed its properties, including its microbiology. For this reason, we decided to investigate the microbiome of two PDO industrial Sfela cheese samples along with two non-PDO variants, namely Sfela touloumotiri and Xerosfeli. Matrix-assisted laser desorption/ionization–time of flight mass spectrometry (MALDI-TOF MS), 16S rDNA amplicon sequencing and shotgun metagenomics analysis were used to identify the microbiome of these traditional cheeses. Cultured-based analysis showed that the most frequent species that could be isolated from Sfela cheese were Enterococcus faecium, Lactiplantibacillus plantarum, Levilactobacillus brevis, Pediococcus pentosaceus and Streptococcus thermophilus. Shotgun analysis suggested that in industrial Sfela 1, Str. thermophilus dominated, while industrial Sfela 2 contained high levels of Lactococcus lactis. The two artisanal samples, Sfela touloumotiri and Xerosfeli, were dominated by Tetragenococcus halophilus and Str. thermophilus, respectively. Debaryomyces hansenii was the only yeast species with abundance > 1% present exclusively in the Sfela touloumotiri sample. Identifying additional yeast species in the shotgun data was challenging, possibly due to their low abundance. Sfela cheese appears to contain a rather complex microbial ecosystem and thus needs to be further studied and understood. This might be crucial for improving and standardizing both its production and safety measures.

Cystathionine β-synthase (CBS) is a key enzyme in the production of the signaling molecule hydrogen sulfide, deregulation of which is known to contribute to a range of serious pathological states. Involvement of hydrogen sulfide in pathways of paramount importance for cellular homeostasis renders CBS a promising drug target. An in-house focused library of heteroaromatic compounds was screened for CBS modulators by the methylene blue assay and a pyrazolopyridine derivative with a promising CBS inhibitory potential was discovered. The compound activity was readily comparable to the most potent CBS inhibitor currently known, aminoacetic acid, while a promising specificity over the related cystathionine γ-lyase was identified. To rule out any possibility that the inhibitor may bind the enzyme regulatory domain due to its high structural similarity with cofactor s-adenosylmethionine, differential scanning fluorimetry was employed. A sub-scaffold search guided follow-up screening of related compounds, providing preliminary structure-activity relationships with respect to requisites for efficient CBS inhibition by this group of heterocycles. Subsequently, a hypothesis regarding the exact binding mode of the inhibitor was devised on the basis of the available structure-activity relationships (SAR) and a deep neural networks analysis and further supported by induced-fit docking calculations.