Enhancing Sensory Quality of Coffee: The Impact of Fermentation Techniques on Coffea arabica cv. Catiguá MG2.

Fermentation, a critical post-harvest process, can be strategically manipulated to augment coffee quality. This enhancement is achieved through the activity of microorganisms, which generate metabolites instrumental in the formation of distinct sensory profiles. This study investigated the impact of different fermentation methods on the quality of coffee beverages, specifically utilizing the Catiguá MG2 variety. The experimental setup involved fermenting the coffee in 200 L bioreactors, employing both natural and pulped coffee beans. The fermentation process utilized was self-induced anaerobic fermentation (SIAF), conducted in either a solid-state or submerged medium over a 96 h period. Analytical sampling was conducted initially and at 24 h intervals thereafter to quantify the concentration of sugars, alcohols, and organic acids. Sensory evaluation was performed using the established protocols of the Specialty Coffee Association (SCA). The outcomes of this investigation reveal that fermentation substantially enhances the quality of coffee, with each treatment protocol yielding divergent profiles of acids and alcohols, thereby influencing the sensory characteristics of the resulting beverage. Notably, superior quality beverages were produced from naturally processed coffee subjected to solid-state fermentation for durations exceeding 24 h. These findings underscore the significant influence of fermentation techniques and duration on the sensory attributes and overall quality of coffee.

Evaluation of Arabica Coffee Fermentation Using Machine Learning.

This study explores the variances in the organic, chemical, and sensory attributes of fermented coffee beans, specifically examining how post-harvest processes influence cup quality. Coffee fruits from the Catuaí IAC-144 variety were processed using both natural coffee (NC) and pulped coffee (PC) methods. The fruits were then subjected to self-induced anaerobic fermentation (SIAF) using one of the following fermentation methods: solid-state fermentation (SSF) or submerged fermentation (SMF). Within these methods, either spontaneous fermentation (SPF) or starter culture fermentation (SCF) was applied. Each method was conducted over periods of 24, 48, and 72 h. For this purpose, two-hundred-liter bioreactors were used, along with two control treatments. Numerous parameters were monitored throughout the fermentation process. A comprehensive chemical profiling and sensory analysis, adhering to the guidelines of the Specialty Coffee Association, were conducted to evaluate the influence of these fermentation processes on the flavor, aroma, and body characteristics of the coffee beverage across multiple dimensions. Data analysis and predictive modeling were performed using machine learning techniques. This study found that NC exhibited a higher production of acids (citric, malic, succinic, and lactic) compared to PC, resulting in distinct chemical and sensory profiles. The decision tree showed that fructose and malic and succinic acids were identified as the main factors enhancing sensory notes during cupping. SMF promoted higher concentrations of lactic acid, while SSF led to increased ethanol content. Consequently, the SIAF process enhances the sensory quality of coffee, adding value to the product by generating diverse sensory profiles.

State of the art in protein-protein interactions within the fungi kingdom.

Proteins rarely exert their function by themselves. Protein-protein interactions (PPIs) regulate virtually every biological process that takes place in a cell. Such interactions are targets for new therapeutic agents against all sorts of diseases, through the screening and design of a variety of inhibitors. Here we discuss several aspects of PPIs that contribute to prediction of protein function and drug discovery. As the high-throughput techniques continue to release biological data, targets for fungal therapeutics that rely on PPIs are being proposed worldwide. Computational approaches have reduced the time taken to develop new therapeutic approaches. The near future brings the possibility of developing new PPI and interaction network inhibitors and a revolution in the way we treat fungal diseases.

Proteomic identification of metabolic changes in Paracoccidioides brasiliensis induced by a nitroheteroarylchalcone.

Aim: To access the metabolic changes caused by a chalcone derivative (LabMol-75) through a proteomic approach. Methods: Proteomic analysis was performed after 9 h of Paracoccidioides brasiliensis yeast (Pb18) cell incubation with the LabMol-75 at MIC. The proteomic findings were validated through in vitro and in silico assays. Results: Exposure to the compound led to the downregulation of proteins associated with glycolysis and gluconeogenesis, ß-oxidation, the citrate cycle and the electron transport chain. Conclusion: LabMol-75 caused an energetic imbalance in the fungus metabolism and deep oxidative stress. Additionally, the in silico molecular docking approach pointed to this molecule as a putative competitive inhibitor of DHPS.

3-phenacylideneoxindoles as a new class of antifungal compounds against Paracoccidioides spp.

Aims: Considering the need to identify new compounds with antifungal action, the activity of five 3-phenacylideneoxindoles compounds was evaluated. Materials & methods: The compounds were synthesized, and their antifungal activity was elucidated through minimum inhibitory concentration tests and interaction assay with other antifungals. Potential targets of compounds were predicted in silico. Results: 3-phenacylideneoxindoles compounds inhibited fungal growth with minimum inhibitory concentration and minimum fungicidal concentration ranging from 3.05 to 12.26 µM. The compounds demonstrated high selectivity index and presented a synergistic effect with itraconazole. In silico prediction revealed the pentafunctional AROM polypeptide, enolase, superoxide dismutase, catalase and kinases as proteins targets of the compound 4a. Conclusion: The results demonstrate that 3-phenacylideneoxindoles is a potential new class of antifungal compounds for paracoccidioidomycosis treatment.

Patients affected by paracoccidioidomycosis (PCM) require long-term treatment, which commonly influences their adherence. In addition, only three drugs are in clinical use, which indicates the relevance of research in identifying new drugs for treating PCM. Thus, five drugs were tested in the laboratory to verify whether they could prevent the growth of the fungus without being toxic to humans. In addition, whether these compounds in combination with drugs used to treat PCM could be even more potent was evaluated. All compounds tested efficiently inhibited the growth of Paracoccidioides, the fungus that causes PCM. One drug was identified that, combined with itraconazole, decreased the required dose of both the discovered compound and itraconazole needed to inhibit fungal growth. Using computational tools, this work suggests how the new drug could act against the fungus. The results demonstrate a potential new treatment option, but more studies are needed to confirm the safety of these drugs.

Computer-aided identification of novel anti-paracoccidioidomycosis compounds.

AIM: The shape-based virtual screening was used for the identification of new compounds anti-paracoccidioidomycosis (PCM). MATERIALS & METHODS: The study was performed according to the following steps: collection and curation of a dataset of quinolinyl N-oxide chalcones with anti-PCM activity, development and validation of shape-based models, application of the best model for virtual screening, and experimental validation. RESULTS & CONCLUSION: Among 31 computational hits, eight compounds showed potent antifungal activity and low cytotoxicity for mammalian cells. The checkerboard assay showed that most promising hit (compound 3) displayed additive effects with the antifungal cotrimoxazole and amphotericin B. Therefore, the shape-based virtual screening allowed us to discover promising compounds in prospective hit-to-lead optimization studies for tackling PCM.

Ammonium removal from high-salinity oilfield-produced water: assessing the microbial community dynamics at increasing salt concentrations.

Water generated during oil exploration is chemically complex and contains high concentrations of ammonium and, in some cases, high salinity. The most common way to remove ammonium from effluent is a biological process, which can be performed by different routes and different groups of microorganisms. However, the presence of salts in the effluents could be an inhibiting factor for biological processes, interfering directly with treatment. This study aimed to evaluate changes in the profile of a microbial community involved in the process of ammonium removal when subjected to a gradual increase of salt (NaCl), in which the complete inhibition of the ammonium removal process occurred at 125 g L-1 NaCl. During the sludge acclimatization process, samples were collected and submitted to denaturing gradient gel electrophoresis (DGGE) and massive sequencing of the 16S ribosomal RNA (rRNA) genes. As the salt concentration increased in the reactor, a change in the microbial community was observed by the DGGE band profiles. As a result, there was a reduction in the presence of bacterial populations, and an increase in archaeal populations was found. The sequencing data suggested that ammonium removal in the reactor was carried out by different metabolic routes by autotrophic nitrifying bacteria, such as Nitrosococcus, Nitrosomonas, Nitrosovibrio, Nitrospira, and Nitrococcus; ammonium-oxidizing archaea Candidatus nitrosoarchaeum; ANAMMOX microorganisms, such as Candidatus brocadia, Candidatus kuenenia, and Candidatus scalindua; and microorganisms with the potential to be heterotrophic nitrifying, such as Paracoccus spp., Pseudomonas spp., Bacillus spp., Marinobacter sp., and Alcaligenes spp.

Proteomic profile response of Paracoccidioides lutzii to the antifungal argentilactone.

The dimorphic fungi Paracoccidioides spp. are the etiological agents of paracoccidioidomycosis (PCM), a mycosis of high incidence in Brazil. The toxicity of drug treatment and the emergence of resistant organisms have led to research for new candidates for drugs. In this study, we demonstrate that the natural product argentilactone was not cytotoxic or genotoxic to MRC5 cells at the IC50 concentration to the fungus. We also verified the proteomic profile of Paracoccidioides lutzii after incubation with argentilactone using a label free quantitative proteome nanoUPLC-MS(E). The results of this study indicated that the fungus has a global metabolic adaptation in the presence of argentilactone. Enzymes of important pathways, such as glycolysis, the Krebs cycle and the glyoxylate cycle, were repressed, which drove the metabolism to the methylcytrate cycle and beta-oxidation. Proteins involved in cell rescue, defense and stress response were induced. In this study, alternative metabolic pathways adopted by the fungi were elucidated, helping to elucidate the course of action of the compound studied.

Identification of genes and pathways related to phenol degradation in metagenomic libraries from petroleum refinery wastewater.

Two fosmid libraries, totaling 13,200 clones, were obtained from bioreactor sludge of petroleum refinery wastewater treatment system. The library screening based on PCR and biological activity assays revealed more than 400 positive clones for phenol degradation. From these, 100 clones were randomly selected for pyrosequencing in order to evaluate the genetic potential of the microorganisms present in wastewater treatment plant for biodegradation, focusing mainly on novel genes and pathways of phenol and aromatic compound degradation. The sequence analysis of selected clones yielded 129,635 reads at an estimated 17-fold coverage. The phylogenetic analysis showed Burkholderiales and Rhodocyclales as the most abundant orders among the selected fosmid clones. The MG-RAST analysis revealed a broad metabolic profile with important functions for wastewater treatment, including metabolism of aromatic compounds, nitrogen, sulphur and phosphorus. The predicted 2,276 proteins included phenol hydroxylases and cathecol 2,3- dioxygenases, involved in the catabolism of aromatic compounds, such as phenol, byphenol, benzoate and phenylpropanoid. The sequencing of one fosmid insert of 33 kb unraveled the gene that permitted the host, Escherichia coli EPI300, to grow in the presence of aromatic compounds. Additionally, the comparison of the whole fosmid sequence against bacterial genomes deposited in GenBank showed that about 90% of sequence showed no identity to known sequences of Proteobacteria deposited in the NCBI database. This study surveyed the functional potential of fosmid clones for aromatic compound degradation and contributed to our knowledge of the biodegradative capacity and pathways of microbial assemblages present in refinery wastewater treatment system.

Listeria monocytogenes: Occurrence in beef and identification of the main contamination points in processing plants.

This study aimed to establish the occurrence of Listeria spp., especially L. monocytogenes and its main serotypes, in beef and processing plants. A total of 443 samples were obtained from equipment, installations and products from 11 meat processing establishments from Paraná state, Brazil. All samples were analyzed using USDA methodology for Listeria spp. detection, followed by species identification. The occurrence of Listeria spp. in the samples was 38.1% of which 51.4% were from equipment, 35.4% from installations and 30.2% from products. The identified species were: L. monocytogenes (12.6%), L. innocua (78.4%), L. seeligeri (1.2%), L. welshimeri (7.2%) and L. grayi (0.6%). The identified serotypes of L. monocytogenes were 1/2a and 4b. The results demonstrate the significance of equipment and installations as sources of contamination by Listeria spp. and L. monocytogenes in the processing of beef and meat products.