A comparative analysis of transcriptomics of newly diagnosed multiple myeloma: exploring drug repurposing.

Multiple myeloma (MM) is an incurable malignant plasma cell disorder characterized by the infiltration of clonal plasma cells in the bone marrow compartment. Gene Expression Profiling (GEP) has emerged as a powerful investigation tool in modern myeloma research enabling the dissection of the molecular background of MM and allowing the identification of gene products that could potentially serve as targets for therapeutic intervention. In this study we investigated shared transcriptomic abnormalities across newly diagnosed multiple myeloma (NDMM) patient cohorts. In total, publicly available transcriptomic data of 7 studies from CD138+ cells from 281 NDMM patients and 44 healthy individuals were integrated and analyzed. Overall, we identified 28 genes that were consistently differentially expressed (DE) between NDMM patients and healthy donors (HD) across various studies. Of those, 9 genes were over/under-expressed in more than 75% of NDMM patients. In addition, we identified 4 genes (MT1F, PURPL, LINC01239 and LINC01480) that were not previously considered to participate in MM pathogenesis. Meanwhile, by mining three drug databases (ChEMBL, IUPHAR/BPS and DrugBank) we identified 31 FDA-approved and 144 experimental drugs that target 8 of these 28 over/under-expressed MM genes. Taken together, our study offers new insights in MM pathogenesis and importantly, it reveals potential new treatment options that need to be further investigated in future studies.

pyPGCF: A Python Software for Phylogenomic Analysis, Species Demarcation, Identification of Core, and Fingerprint Proteins of Bacterial Genomes That Are Important for Plants.

This computational protocol describes how to use pyPGCF, a python software package that runs in the linux environment, in order to analyze bacterial genomes and perform: (i) phylogenomic analysis, (ii) species demarcation, (iii) identification of the core proteins of a bacterial genus and its individual species, (iv) identification of species-specific fingerprint proteins that are found in all strains of a species and, at the same time, are absent from all other species of the genus, (v) functional annotation of the core and fingerprint proteins with eggNOG, and (vi) identification of secondary metabolite biosynthetic gene clusters (smBGCs) with antiSMASH. This software has already been implemented to analyze bacterial genera and species that are important for plants (e.g., Pseudomonas, Bacillus, Streptomyces). In addition, we provide a test dataset and example commands showing how to analyze 165 genomes from 55 species of the genus Bacillus. The main advantages of pyPGCF are that: (i) it uses adjustable orthology cut-offs, (ii) it identifies species-specific fingerprints, and (iii) its computational cost scales linearly with the number of genomes being analyzed. Therefore, pyPGCF is able to deal with a very large number of bacterial genomes, in reasonable timescales, using widely available levels of computing power.

A panoramic view of the genomic landscape of the genus Streptomyces.

We delineate the evolutionary plasticity of the ecologically and biotechnologically important genus Streptomyces, by analysing the genomes of 213 species. Streptomycetes genomes demonstrate high levels of internal homology, whereas the genome of their last common ancestor was already complex. Importantly, we identify the species-specific fingerprint proteins that characterize each species. Even among closely related species, we observed high interspecies variability of chromosomal protein-coding genes, species-level core genes, accessory genes and fingerprints. Notably, secondary metabolite biosynthetic gene clusters (smBGCs), carbohydrate-active enzymes (CAZymes) and protein-coding genes bearing the rare TTA codon demonstrate high intraspecies and interspecies variability, which emphasizes the need for strain-specific genomic mining. Highly conserved genes, such as those specifying genus-level core proteins, tend to occur in the central region of the chromosome, whereas those encoding proteins with evolutionarily volatile species-level fingerprints, smBGCs, CAZymes and TTA-codon-bearing genes are often found towards the ends of the linear chromosome. Thus, the chromosomal arms emerge as the part of the genome that is mainly responsible for rapid adaptation at the species and strain level. Finally, we observed a moderate, but statistically significant, correlation between the total number of CAZymes and three categories of smBGCs (siderophores, e-Polylysin and type III lanthipeptides) that are related to competition among bacteria.

Impact of Mt. Olympus Honeys on Virulence Factors Implicated in Pathogenesis Exerted by Pseudomonas aeruginosa.

The aim of this study was to examine the impact of twenty honey samples, harvested in Mt. Olympus (Greece), on the virulence factors implicated in P. aeruginosa pathogenesis. Six key virulence factors (protease and elastase activity, pyocyanin and pyoverdine concentration, biofilm formation, and swimming motility) were selected in order to assess the effect of the tested honeys compared with Manuka honey. All tested honeys demonstrated a significant inhibition of protease and elastase activity compared with the control. Six and thirteen honeys exerted superior protease (no inhibition zone) and elastase (values lower than 55%) activity, respectively, compared with Manuka honey. Seventeen tested honeys exhibited reduced pyoverdine production compared with the control; all tested honeys, except for one, showed an inhibitory effect on pyocyanin production compared with the control. Regarding swimming motility, nine tested honeys demonstrated significantly higher inhibition compared with Manuka honey. Honey concentrations (6% v/v and 8% v/v) had the most profound impact, as they reduced biofilm formation to less than 20% compared with the control. Overall, our data demonstrate a significant inhibition of the virulence factors in the tested Mt. Olympus honeys, highlighting the strong antimicrobial activity against P. aeruginosa, an antibiotic-resistant pathogen of growing concern, which is implicated in severe nosocomial infections globally.

Transcriptional Response to Hypoxia: The Role of HIF-1-Associated Co-Regulators.

The Hypoxia Inducible Factor 1 (HIF-1) plays a major role in the cellular response to hypoxia by regulating the expression of many genes involved in adaptive processes that allow cell survival under low oxygen conditions. Adaptation to the hypoxic tumor micro-environment is also critical for cancer cell proliferation and therefore HIF-1 is also considered a valid therapeutical target. Despite the huge progress in understanding regulation of HIF-1 expression and activity by oxygen levels or oncogenic pathways, the way HIF-1 interacts with chromatin and the transcriptional machinery in order to activate its target genes is still a matter of intense investigation. Recent studies have identified several different HIF-1- and chromatin-associated co-regulators that play important roles in the general transcriptional activity of HIF-1, independent of its expression levels, as well as in the selection of binding sites, promoters and target genes, which, however, often depends on cellular context. We review here these co-regulators and examine their effect on the expression of a compilation of well-characterized HIF-1 direct target genes in order to assess the range of their involvement in the transcriptional response to hypoxia. Delineating the mode and the significance of the interaction between HIF-1 and its associated co-regulators may offer new attractive and specific targets for anticancer therapy.

Antioxidant Activity and Inhibition of Liver Cancer Cells' Growth of Extracts from 14 Marine Macroalgae Species of the Mediterranean Sea.

Macroalgae exhibit beneficial bioactivities for human health. Thus, the aim of the present study was to examine the antioxidant and anticancer potential of 14 macroalgae species' extracts, namely, Gigartina pistillata, Gigartina teedei, Gracilaria gracilis, Gracilaria sp., Gracilaria bursa pastoris, Colpomenia sinuosa, Cystoseira amentacea, Cystoseira barbata, Cystoseira compressa, Sargassum vulgare, Padina pavonica, Codium fragile, Ulva intestinalis, and Ulva rigida, from the Aegean Sea, Greece. The antioxidant activity was assessed using DPPH, ABTS•+, •OH, and O2•- radicals' scavenging assays, reducing power (RP), and protection from ROO•-induced DNA plasmid damage assays. Moreover, macroalgae extracts' total polyphenol contents (TPCs) were assessed. Extracts' inhibition against liver HepG2 cancer cell growth was assessed using the XTT assay. The results showed that G. teedei extract's IC50 was the lowest in DPPH (0.31 ± 0.006 mg/mL), ABTS•+ (0.02 ± 0.001 mg/mL), •OH (0.10 ± 0.007 mg/mL), O2•- (0.05 ± 0.003 mg/mL), and DNA plasmid breakage (0.038 ± 0.002 mg/mL) and exhibited the highest RP (RP0.5AU 0.24 ± 0.019 mg/mL) and TPC (12.53 ± 0.88 mg GAE/g dw). There was also a significant correlation between antioxidant activity and TPC. P. pavonica (IC50 0.93 ± 0.006 mg/mL) exhibited the highest inhibition against HepG2 cell growth. Conclusively, some of the tested extracts exhibited significant chemopreventive properties, and so they may be used for food products.

The Dynamic and Crucial Role of the Arginine Methylproteome in Myoblast Cell Differentiation.

Protein arginine methylation is an extensive and functionally significant post-translational modification. However, little is known about its role in differentiation at the systems level. Using stable isotope labeling by amino acids in cell culture (SILAC) proteomics of whole proteome analysis in proliferating or five-day differentiated mouse C2C12 myoblasts, followed by high-resolution mass spectrometry, biochemical assays, and specific immunoprecipitation of mono- or dimethylated arginine peptides, we identified several protein families that were differentially methylated on arginine. Our study is the first to reveal global changes in the arginine mono- or dimethylation of proteins in proliferating myoblasts and differentiated myocytes and to identify enriched protein domains and novel short linear motifs (SLiMs). Our data may be crucial for dissecting the links between differentiation and cancer growth.

Prediction and Ranking of Biomarkers Using multiple UniReD.

Protein-protein interactions (PPIs) are of key importance for understanding how cells and organisms function. Thus, in recent decades, many approaches have been developed for the identification and discovery of such interactions. These approaches addressed the problem of PPI identification either by an experimental point of view or by a computational one. Here, we present an updated version of UniReD, a computational prediction tool which takes advantage of biomedical literature aiming to extract documented, already published protein associations and predict undocumented ones. The usefulness of this computational tool has been previously evaluated by experimentally validating predicted interactions and by benchmarking it against public databases of experimentally validated PPIs. In its updated form, UniReD allows the user to provide a list of proteins of known implication in, e.g., a particular disease, as well as another list of proteins that are potentially associated with the proteins of the first list. UniReD then automatically analyzes both lists and ranks the proteins of the second list by their association with the proteins of the first list, thus serving as a potential biomarker discovery/validation tool.

A Comparative Analysis of the Core Proteomes within and among the Bacillus subtilis and Bacillus cereus Evolutionary Groups Reveals the Patterns of Lineage- and Species-Specific Adaptations.

By integrating phylogenomic and comparative analyses of 1104 high-quality genome sequences, we identify the core proteins and the lineage-specific fingerprint proteins of the various evolutionary clusters (clades/groups/species) of the Bacillus genus. As fingerprints, we denote those core proteins of a certain lineage that are present only in that particular lineage and absent in any other Bacillus lineage. Thus, these lineage-specific fingerprints are expected to be involved in particular adaptations of that lineage. Intriguingly, with a few notable exceptions, the majority of the Bacillus species demonstrate a rather low number of species-specific fingerprints, with the majority of them being of unknown function. Therefore, species-specific adaptations are mostly attributed to highly unstable (in evolutionary terms) accessory proteomes and possibly to changes at the gene regulation level. A series of comparative analyses consistently demonstrated that the progenitor of the Cereus Clade underwent an extensive genomic expansion of chromosomal protein-coding genes. In addition, the majority (76-82%) of the B. subtilis proteins that are essential or play a significant role in sporulation have close homologs in most species of both the Subtilis and the Cereus Clades. Finally, the identification of lineage-specific fingerprints by this study may allow for the future development of highly specific vaccines, therapeutic molecules, or rapid and low-cost molecular tests for species identification.

The Notable Achievements and the Prospects of Bacterial Pathogen Genomics.

Throughout the entirety of human history, bacterial pathogens have played an important role and even shaped the fate of civilizations. The application of genomics within the last 27 years has radically changed the way we understand the biology and evolution of these pathogens. In this review, we discuss how the short- (Illumina) and long-read (PacBio, Oxford Nanopore) sequencing technologies have shaped the discipline of bacterial pathogen genomics, in terms of fundamental research (i.e., evolution of pathogenicity), forensics, food safety, and routine clinical microbiology. We have mined and discuss some of the most prominent data/bioinformatics resources such as NCBI pathogens, PATRIC, and Pathogenwatch. Based on this mining, we present some of the most popular sequencing technologies, hybrid approaches, assemblers, and annotation pipelines. A small number of bacterial pathogens are of very high importance, and we also present the wealth of the genomic data for these species (i.e., which ones they are, the number of antimicrobial resistance genes per genome, the number of virulence factors). Finally, we discuss how this discipline will probably be transformed in the near future, especially by transitioning into metagenome-assembled genomes (MAGs), thanks to long-read sequencing.

Comparative Analysis of SARS-CoV-2 Variants of Concern, Including Omicron, Highlights Their Common and Distinctive Amino Acid Substitution Patterns, Especially at the Spike ORF.

In order to gain a deeper understanding of the recently emerged and highly divergent Omicron variant of concern (VoC), a study of amino acid substitution (AAS) patterns was performed and compared with those of the other four successful variants of concern (Alpha, Beta, Gamma, Delta) and one closely related variant of interest (VoI-Lambda). The Spike ORF consistently emerges as an AAS hotspot in all six lineages, but in Omicron this enrichment is significantly higher. The progenitors of each of these VoC/VoI lineages underwent positive selection in the Spike ORF. However, once they were established, their Spike ORFs have been undergoing purifying selection, despite the application of global vaccination schemes from 2021 onwards. Our analyses reject the hypothesis that the heavily mutated receptor binding domain (RBD) of the Omicron Spike was introduced via recombination from another closely related Sarbecovirus. Thus, successive point mutations appear as the most parsimonious scenario. Intriguingly, in each of the six lineages, we observed a significant number of AAS wherein the new residue is not present at any homologous site among the other known Sarbecoviruses. Such AAS should be further investigated as potential adaptations to the human host. By studying the phylogenetic distribution of AAS shared between the six lineages, we observed that the Omicron (BA.1) lineage had the highest number (8/10) of recurrent mutations.

The Remarkable Evolutionary Plasticity of Coronaviruses by Mutation and Recombination: Insights for the COVID-19 Pandemic and the Future Evolutionary Paths of SARS-CoV-2.

Coronaviruses (CoVs) constitute a large and diverse subfamily of positive-sense single-stranded RNA viruses. They are found in many mammals and birds and have great importance for the health of humans and farm animals. The current SARS-CoV-2 pandemic, as well as many previous epidemics in humans that were of zoonotic origin, highlights the importance of studying the evolution of the entire CoV subfamily in order to understand how novel strains emerge and which molecular processes affect their adaptation, transmissibility, host/tissue tropism, and patho non-homologous genicity. In this review, we focus on studies over the last two years that reveal the impact of point mutations, insertions/deletions, and intratypic/intertypic homologous and non-homologous recombination events on the evolution of CoVs. We discuss whether the next generations of CoV vaccines should be directed against other CoV proteins in addition to or instead of spike. Based on the observed patterns of molecular evolution for the entire subfamily, we discuss five scenarios for the future evolutionary path of SARS-CoV-2 and the COVID-19 pandemic. Finally, within this evolutionary context, we discuss the recently emerged Omicron (B.1.1.529) VoC.

The Neighborhood of the Spike Gene Is a Hotspot for Modular Intertypic Homologous and Nonhomologous Recombination in Coronavirus Genomes.

Coronaviruses (CoVs) have very large RNA viral genomes with a distinct genomic architecture of core and accessory open reading frames (ORFs). It is of utmost importance to understand their patterns and limits of homologous and nonhomologous recombination, because such events may affect the emergence of novel CoV strains, alter their host range, infection rate, tissue tropism pathogenicity, and their ability to escape vaccination programs. Intratypic recombination among closely related CoVs of the same subgenus has often been reported; however, the patterns and limits of genomic exchange between more distantly related CoV lineages (intertypic recombination) need further investigation. Here, we report computational/evolutionary analyses that clearly demonstrate a substantial ability for CoVs of different subgenera to recombine. Furthermore, we show that CoVs can obtain-through nonhomologous recombination-accessory ORFs from core ORFs, exchange accessory ORFs with different CoV genera, with other viruses (i.e., toroviruses, influenza C/D, reoviruses, rotaviruses, astroviruses) and even with hosts. Intriguingly, most of these radical events result from double crossovers surrounding the Spike ORF, thus highlighting both the instability and mobile nature of this genomic region. Although many such events have often occurred during the evolution of various CoVs, the genomic architecture of the relatively young SARS-CoV/SARS-CoV-2 lineage so far appears to be stable.

Effect of polyphenols from coffee and grape on gene expression in myoblasts.

Coffee and grape contain various bioactive compounds like polyphenols that may exert beneficial effects, especially antioxidant activity, on human health upon consumption. However, the molecular mechanisms through which these effects are achieved are not fully elucidated. Thus, in the present study in order to investigate these mechanisms, a whole genome expression DNA microarray analysis was carried out in myoblasts treated with polyphenols of coffee and grape pomace at concentrations that improved the redox status. Grape was composed of catechin, epicatechin, cyanidin, malvidin, delphinidin, petunidin, myrtillin, kuromanin, oenin, peonidin, quercetin, gallic acid and caftaric acid as LC-MS revealed, with a total polyphenolic content (TPC) of 648 mg of gallic acid equivalents/g of dry matter. Coffee had a TPC of 42.61 mg GAE/g coffee and was composed of 3-chlorogenic acid (16.61 mg/g), 4- and 5-chlorogenic acids (13.62 mg/g), as UHPLC-HRMS revealed. According to the results, grape polyphenols altered mainly the expression of cytoskeleton and differentiation-associated genes, while coffee compounds had a more profound effect, on the expression levels of many metabolic and antioxidant genes possibly through the nuclear factor (erythroid-derived 2) like-2 (Nrf2) pathway.

The Pivotal Role of Protein Phosphorylation in the Control of Yeast Central Metabolism.

Protein phosphorylation is the most frequent eukaryotic post-translational modification and can act as either a molecular switch or rheostat for protein functions. The deliberate manipulation of protein phosphorylation has great potential for regulating specific protein functions with surgical precision, rather than the gross effects gained by the over/underexpression or complete deletion of a protein-encoding gene. In order to assess the impact of phosphorylation on central metabolism, and thus its potential for biotechnological and medical exploitation, a compendium of highly confident protein phosphorylation sites (p-sites) for the model organism Saccharomyces cerevisiae has been analyzed together with two more datasets from the fungal pathogen Candida albicans Our analysis highlights the global properties of the regulation of yeast central metabolism by protein phosphorylation, where almost half of the enzymes involved are subject to this sort of post-translational modification. These phosphorylated enzymes, compared to the nonphosphorylated ones, are more abundant, regulate more reactions, have more protein-protein interactions, and a higher fraction of them are ubiquitinated. The p-sites of metabolic enzymes are also more conserved than the background p-sites, and hundreds of them have the potential for regulating metabolite production. All this integrated information has allowed us to prioritize thousands of p-sites in terms of their potential phenotypic impact. This multi-source compendium should enable the design of future high-throughput (HTP) mutation studies to identify key molecular switches/rheostats for the manipulation of not only the metabolism of yeast, but also that of many other biotechnologically and medically important fungi and eukaryotes.

The complex evolutionary history of aminoacyl-tRNA synthetases.

Aminoacyl-tRNA synthetases (AARSs) are a superfamily of enzymes responsible for the faithful translation of the genetic code and have lately become a prominent target for synthetic biologists. Our large-scale analysis of >2500 prokaryotic genomes reveals the complex evolutionary history of these enzymes and their paralogs, in which horizontal gene transfer played an important role. These results show that a widespread belief in the evolutionary stability of this superfamily is misconceived. Although AlaRS, GlyRS, LeuRS, IleRS, ValRS are the most stable members of the family, GluRS, LysRS and CysRS often have paralogs, whereas AsnRS, GlnRS, PylRS and SepRS are often absent from many genomes. In the course of this analysis, highly conserved protein motifs and domains within each of the AARS loci were identified and used to build a web-based computational tool for the genome-wide detection of AARS coding sequences. This is based on hidden Markov models (HMMs) and is available together with a cognate database that may be used for specific analyses. The bioinformatics tools that we have developed may also help to identify new antibiotic agents and targets using these essential enzymes. These tools also may help to identify organisms with alternative pathways that are involved in maintaining the fidelity of the genetic code.