Gall-formers are parasitic organisms manipulating plant traits for their own benefit. Gall-formers of many domains are known, including more than 1,440 gall-forming insect species from at least five different orders. Insect's galls have been shown to protect their inhabitants from natural enemies such as predators and parasitoids by various chemical and mechanical means, but much less attention has been given to defence against microbial pathogens likely to grow in the humid and nutrient-rich gall environment. The large, cauliflower-shaped, galls formed by Slavum wertheimae on buds of Pistacia atlantica have been shown to host thousands of aphids, and their sugar rich secretion for up to 8 month, suggesting such protection could be of benefit to the inhabiting aphids. We have if S. wertheimae galls do indeed have antimicrobial properties using plate diffusion assay and essential oils testes on bacteria and filamentous fungi. Our results suggest that indeed those galls do express antibacterial and antifungal activities distinct from those found in non-galled leaves. Antibacterial activity was especially profound against Bacillus spp. (known insect pathogen) and against Pseudomonas aeruginosa (known plant pathogen). Antifungal activity was demonstrated against multiple filamentous fungi. Our results provide experimental evidence for a new protective antimicrobial role of galls. These results suggest not only S. wertheimae galls as a possible source for antimicrobial compounds but also call for an exmination of other gall systems as a possible source for such compounds.

Streptomyces spp. are known producer of therapeutically important secondary metabolites with diversity in structure and function. Optimization of different bioprocess parameters towards the improved productivity and activity profile is always considered to be of high significance. Peptone is an acclaimed source of nutrients that had been studied for its effect on the bioactivity of metabolites produced during media development. In the present communication we report remarkable variation on the profile and anti-Candida activity of metabolites produced by Streptomyces chrestomyceticus strain ADP4 in response to variation in the source of peptone. It was found that peptone procured from different manufactures (Himedia, CDH and Diffco) have shown noteworthy variation when used as a component of Sabouraud Dextrose Broth (SDB). The zone of inhibition, values of minimum inhibitory concentration (MIC₉₀) against C. krusei and yield of the metabolites varied significantly when the metabolites were produced in SDB medium using peptones from above mentioned sources. CDH-peptone was found to be the best for anti-Candida activity with highest zone of inhibition of 38 ± 2.0 mm and MIC₉₀ value of 2.877± 0.22 µg/mL against C. krusei ATCC 6258. Activity against C. albicans ATCC 10231, C. tropicalis ATCC 750, C. parapsilosis ATCC 90028 and C. auris CBS 12372 was also better as compared to the activities obtained using other peptones. The yield of the metabolite extract was noted to be twice in CDH-peptone as compared to those from HiMedia and Diffco when grown under same conditions like pH, temperature and carbon source. Analyses of the metabolites by using TLC and HPLC demonstrated a clear and significant difference in the metabolite-profile of S. chrestomyceticus strain ADP4. Since peptone is a major nitrogen source, it may be inferred that nitrogen source may play a critical role in regulation of biosynthetic gene clusters associated with synthesis of anti-Candida compounds.

The human pathogen of Mycobacterium tuberculosis (MTB) is indeed one of the renowned important longtime infectious diseases, tuberculosis (TB). Interestingly, MTB infection has become one of the world's leading causes of human death. In trehalose synthase, the protein NCGM 946K2 146 found in MTB has an important role. For carbohydrate transport and metabolism, trehalose synthase is required. The protein isn't clarified yet, though. In this research, an in silico approach was therefore formulated for functional and structural documentation of the uncharacterized protein NCGM946K2 146.Three distinct servers, including Modeller, Phyre2, and Swiss Model were used to evaluate the predicted tertiary structure. The top materials are selected using structural evaluations conducted with the analysis of Ramachandran Plot, Swiss-Model Interactive Workplace, Prosa-web, Verify 3D, and Z scores. This analysis aimed to uncover the value of the NCGM946K2 146 protein of MTB. This research will, therefore, improve our pathogenesis awareness and give us a chance to target the protein compound.

Bacteria of the Rhizobum genus form a group of microorganisms existing in the environment in two forms: symbiotic - in the root nodules of Fabaceae sp. plants and free-living, saprophytic in the soil environment. The basic function of Rhizobum sp. in a symbiosis is to reduce nitrogen to ammonia directly assimilated by the plant.

The subject of study was genetic identification and characterization of metabolic activity Rhizobium genus bacteria. The study was conducted on the 16 bacteria strains from the collection of Department of Agricultural Microbiology, Institute of Soil Science and Plant Cultivation in Puławy, Poland. Bacteria strains were isolated from root nodules derived from plans of the genus Trifolium.

Based on the sequencing of PCR products, we found that all strains belong to one species - Rhizobium leguminosarum. The study of metabolic activity was performed using the GEN III BIOLOG system method (Biolog Inc., Hayward, CA, USA). The GEN III microplate contains 94 phenotypic tests: 71 carbon source utilization assays and 23 chemical sensitivity assays. Tetrazolium dyes from the wells of the microplate are used to indicate the use of carbon sources or resistance to inhibitory chemicals by microorganisms. The cell suspensions were inoculated into the GEN III and incubated for 7 days. The subject of the study was to evaluate the ability of strains of Rhizobium leguminosarum bacteria to metabolize three groups of compounds: carbohydrates (CH), amino acids (AA) and fatty acids (FA).

Based on results the heat maps were made and the cluster analysis according to Ward’s method conducted thus illustrating the diversity of strains in terms of the intensity and pace of the individual compounds consumption. Metabolism analysis of all R. leguminosarum strains with the use of GEN III™ plates showed that carbohydrates (CH) were the most intensively utilised group of substrates. Between the Rhizobium leguminosarum strains, there are metabolic differences in terms of the studied features. That may indicate the adaptive capacity of microorganisms to the environmental conditions in which they currently live.

Sourdoughs represent an awesome example of ecosystem in which yeasts and lactic acid bacteria (LAB) interact with each other, defining the characteristics of the final product in terms of composition, texture, taste and flavor. Therefore, the identification of dominant yeasts and LAB involved in the fermentation process can lead to the selection of starters with good fermentation aptitude and capable of producing desired aromas and/or aromatic precursors.

In this work, two sourdoughs samples (A and B) for Panettone production were collected from an artisan bakery. Yeasts and bacteria were isolated at different fermentation steps on selective agar media. A total of 120 isolates were obtained and firstly characterized by conventional microbiology methods. Afterward, genomic DNA was extracted from the cultures, and (GTG)₅-MSP-PCR fingerprinting analysis was carried out to reduce the redundance among the isolates. Representative yeasts and LAB strains, having a unique profile, were identified by sequencing the D1/D2 domain of the 26S rRNA and the 16S rRNA genes, respectively. The results highlighted the occurrence of Kazachstania humilis and Fructilactobacillus sanfranciscensis in both sourdoughs. Among LAB also some other strains belonging to Lactobacillus genus were found. Moreover, Saccharomyces cerevisiae and Staphylococcus spp. strains were detected in sample B. In this study, a pool of yeasts and LAB strains for producing starter cultures with specific technological traits for sourdough productions was obtained.

The wine fermentation process is very complex and involves different types of yeasts. While the predominant one is Saccharomyces cerevisiae, it has long been known that other non- Saccharomyces yeasts also play an important role. Their action is mainly known in the early stages of fermentation. However, one should not overlook the processes and changes that non-Saccharomyces yeast populations may have undergone during previous stages of grape berry ripening. The whole process is conditioned by several environmental factors as well as the possibility that they have been subjected to some antifungal treatment. In our study we controlled the dynamics of non- Saccharomyces yeast populations during the ripening process, using biochemical identification systems (API 20C AUX and API ID 32C) as well as molecular techniques (RFLP-PCR) and enzymatic analysis. Some yeasts not usually found in wine fermentation (Aureobasidium pullulans, Cryptococcus sp., Metschnikowia pulcherrima and Rodotorula mucilaginosa) have been identified. These yeasts could be affected by antifungal treatments used in wineries, and this fact could explain the novelty of their isolation and identification. After their extensive characterization, these yeasts can be used to implement new biotechnological processes.

The enterobacteria that produce β-lactamases are the main focus of infections in the healthcare environment. This is due to the difficulty they present in terms of treatment, their ease of transmission, and the impact they represent at the economic and personal level. The bacteria of greatest clinical relevance are those with resistance to third and fourth generation cephalosporins, extended spectrum β-lactamase and AmpC. Currently, carbapenemics are one of the few antimicrobials effective against multi-drug resistant organisms. However, the emergence of carbapenem-resistant enterobacteria has increased health concerns. These microorganisms include K. pneumoniae, a pan-resistant bacteria with high morbidity and mortality rates in public health facilities. In this work we have carried out a review on the antimicrobial resistance genes found in its genome, as well as the resistance mechanisms involved. Finally, we will focus on the main outbreaks causing nosocomial infections during the last years.

Machine learning can be used as an alternative to similarity algorithms such as BLAST when the latter fail to identify highly dissimilar antimicrobial resistance (AMR) genes in bacteria; however, determining the most informative characteristics, known as features, for AMR is essential in order to obtain accurate predictions. In this paper we introduce a feature selection algorithm called symmetrical uncertainty-qualitative mutual information (SU-QMI) which selects features based on estimates of their relevance, redundancy, and interdependency. We use the concepts of symmetrical uncertainty and qualitative mutual information in addition to graph theory to derive a feature selection method for identifying putative AMR genes in Gram-negative bacteria. First we extract physicochemical, evolutionary, and structural features from the protein sequences of five genera of Gram-negative bacteria-Acinetobacter, Klebsiella, Campylobacter, Salmonella, and Escherichia-which confer resistance to acetyltransferase (aac), beta-lactamase (bla), and dihydrofolate reductase (dfr). Our SU-QMI algorithm is then used to find the best subset of features, and a support vector machine (SVM) model is trained for AMR prediction using this feature subset. We evaluate the performance using an independent set of protein sequences from three Gram-negative bacterial genera-Pseudomonas, Vibrio, and Enterobacter-and achieve prediction accuracy ranging from 88% to 100%. Compared to the SU-QMI method, BLASTp requires similarity as low as 53% for comparable classification results. Thus, our results indicate the effectiveness of the SU-QMI method for selecting the best protein features for AMR prediction in Gram-negative bacteria.

Antimicrobial resistance is driving pharmaceutical companies to investigate different therapeutic approaches. One approach that has garnered growing consideration in drug development is the use of antimicrobial peptides (AMPs). Antibacterial peptides (ABPs), which occur naturally as part of the immune response, can serve as powerful, broad-spectrum antibiotics. However, conventional laboratory procedures for screening and discovering ABPs are expensive and time-consuming. Identification of ABPs can be significantly improved using computational methods. In this paper, we introduce a machine learning method for the fast and accurate prediction of ABPs. We gathered more than 6000 peptides from publicly available datasets and extracted 1209 features (peptide characteristics) from these sequences. We selected the optimal features by applying correlation-based and random forest feature selection techniques. Finally, we designed an ensemble gradient boosting model (GBM) to predict putative ABPs. We evaluated our model using ROC curves, calculating the area under the curve (AUC) for several different models for comparison, including a recurrent neural network, a support vector machine, and iAMPpred. The AUC for the GBM was∼0.98, more than 2.5% better than any of the other models. We also present an algorithm which artificially generates potential ABPs based on the frequency of amino acid occurrence in more than 3000 ABPs and their frequency of length. The algorithm uses a random function to produce sets of amino acid sequences in which the probability of inclusion of amino acids is based on the calculated frequencies. After generating the artificial sequences, we use the GBM to predict whether they are ABPs.

H. pylori is one of the major human pathogens infecting approximately 50% of the world's population. Its treatment is based on the combined use of different antibiotics. In recent years, the number of antibiotic resistant strains have been increased. Therefore, new alternative therapies are required for H. pylori treatment. The aim of the present work was to evaluate the antibacterial, anti-inflammatory and antioxidant effect of olive leaf extracts against antibiotics resistant H. pylori strains. Two olive leaf extracts were used: E1, enriched in hydroxytyrosol (10%); and E2, enriched in oleuropein (20%). E1 extract showed a bactericidal effect for all evaluated H. pylori strains (7/7), while the E2 extract was bactericidal for three of the studied strains (3/7) and caused a decrease of around 1 log in colony forming units (CFU) for the rest of the strains. About antioxidant activity, both extracts reduced up to 33% the production of intracellular reactive oxygen species in human gastric AGS cells infected by H. pylori, being the antioxidant activity of the E2 extract higher than E1. Finally, E1 and E2 extracts showed anti-inflammatory activity, reducing IL-8 pro-inflammatory factor secretion by infected-AGS cells in a range of 20-74% and 71-93%, respectively. Therefore, the olive leaf extracts could be consider as a potential new candidate for H. pylori treatment, providing an alternative for the 20% of infected people with symptoms for whom antibiotic treatments are not effective. Furthermore, the recycling of olive industry by-products could also contribute to its revalorization, reducing also the environmental impact.