Role of Acetic Acid Bacteria in Food and Beverages.

Acetic acid bacteria (AAB) are microorganisms widely distributed in nature. Although this group is involved in the spoilage of some foods, AAB are of great industrial interest, and their functionality is still poorly understood. AAB convert ethanol, sugars and polyols into various organic acids, aldehydes and ketones via oxidative fermentation. These metabolites are produced during a succession of biochemical reactions in various fermented foods and beverages, such as vinegar, kombucha, water kefir, lambic and cocoa. Furthermore, important products such as gluconic acid and ascorbic acid precursors can be produced industrially from their metabolism. The development of new AAB-fermented fruit drinks with healthy and functional properties is an interesting niche for research and the food industry to explore, as it can meet the needs of a wide range of consumers. Exopolysaccharides such as levan and bacterial cellulose have unique properties, but they need to be produced on a larger scale to expand their applications in this area. This work emphasizes the importance and applications of AAB during the fermentation of various foods, their role in the development of new beverages as well as numerous applications of levan and bacterial cellulose.

Diagnosis and prognosis of COVID-19 employing analysis of patients' plasma and serum via LC-MS and machine learning.

OBJECTIVE: To implement and evaluate machine learning (ML) algorithms for the prediction of COVID-19 diagnosis, severity, and fatality and to assess biomarkers potentially associated with these outcomes. MATERIAL AND METHODS: Serum (n = 96) and plasma (n = 96) samples from patients with COVID-19 (acute, severe and fatal illness) from two independent hospitals in China were analyzed by LC-MS. Samples from healthy volunteers and from patients with pneumonia caused by other viruses (i.e. negative RT-PCR for COVID-19) were used as controls. Seven different ML-based models were built: PLS-DA, ANNDA, XGBoostDA, SIMCA, SVM, LREG and KNN. RESULTS: The PLS-DA model presented the best performance for both datasets, with accuracy rates to predict the diagnosis, severity and fatality of COVID-19 of 93%, 94% and 97%, respectively. Low levels of the metabolites ribothymidine, 4-hydroxyphenylacetoylcarnitine and uridine were associated with COVID-19 positivity, whereas high levels of N-acetyl-glucosamine-1-phosphate, cysteinylglycine, methyl isobutyrate, l-ornithine and 5,6-dihydro-5-methyluracil were significantly related to greater severity and fatality from COVID-19. CONCLUSION: The PLS-DA model can help to predict SARS-CoV-2 diagnosis, severity and fatality in daily practice. Some biomarkers typically increased in COVID-19 patients' serum or plasma (i.e. ribothymidine, N-acetyl-glucosamine-1-phosphate, l-ornithine, 5,6-dihydro-5-methyluracil) should be further evaluated as prognostic indicators of the disease.

Influence of foods and nutrients on COVID-19 recovery: A multivariate analysis of data from 170 countries using a generalized linear model.

BACKGROUND & AIMS: COVID-19 is an emergency public health problem of global importance. This study aimed to investigate the effect of foods and nutrients as complementary approaches on the recovery from COVID-19 in 170 countries, especially considering the complexity of the disease and the current scarcity of active treatments. METHODS: A retrospective study was performed using the Kaggle database, which links the consumption of various foods with recovery from COVID-19 in 170 countries, using multivariate analysis based on a generalized linear model. RESULTS: The results showed that certain foods had a positive effect on recovery from COVID-19: eggs, fish and seafood, fruits, meat, milk, starchy roots, stimulants, vegetable products, nuts, vegetable oil and vegetables. In general, consumption of higher levels of proteins and lipids had a positive effect on COVID-19 recovery, whereas high consumption of alcoholic beverages had a negative effect. In developed countries, where hunger had been eradicated, the effect of food on recovery from COVID-19 had a greater magnitude than in countries with a higher global hunger index (GHI), where there was almost no identifiable effect. CONCLUSION: Several foods had a positive effect on COVID-19 recovery in developed countries, especially food groups with a higher content of lipids, proteins, antioxidants and micronutrients (e.g., selenium and zinc). In countries with extreme poverty (high GHI), foods presented little effect on recovery from COVID-19.

Diagnosis and prediction of COVID-19 severity: can biochemical tests and machine learning be used as prognostic indicators?

OBJECTIVE: This study aimed to implement and evaluate machine learning based-models to predict COVID-19' diagnosis and disease severity. METHODS: COVID-19 test samples (positive or negative results) from patients who attended a single hospital were evaluated. Patients diagnosed with COVID-19 were categorised according to the severity of the disease. Data were submitted to exploratory analysis (principal component analysis, PCA) to detect outlier samples, recognise patterns, and identify important variables. Based on patients' laboratory tests results, machine learning models were implemented to predict disease positivity and severity. Artificial neural networks (ANN), decision trees (DT), partial least squares discriminant analysis (PLS-DA), and K nearest neighbour algorithm (KNN) models were used. The four models were validated based on the accuracy (area under the ROC curve). RESULTS: The first subset of data had 5,643 patient samples (5,086 negatives and 557 positives for COVID-19). The second subset included 557 COVID-19 positive patients. The ANN, DT, PLS-DA, and KNN models allowed the classification of negative and positive samples with >84% accuracy. It was also possible to classify patients with severe and non-severe disease with an accuracy >86%. The following were associated with the prediction of COVID-19 diagnosis and severity: hyperferritinaemia, hypocalcaemia, pulmonary hypoxia, hypoxemia, metabolic and respiratory acidosis, low urinary pH, and high levels of lactate dehydrogenase. CONCLUSION: Our analysis shows that all the models could assist in the diagnosis and prediction of COVID-19 severity.

Chemical composition, cytotoxicity, and antibacterial activity of propolis from Africanized honeybees and three different Meliponini species.

ETHNOPHARMACOLOGICAL RELEVANCE: Propolis extracts are widely used in traditional folk medicine and exhibit several properties such as antitumor, anti-inflammatory, and antimicrobial. However, these products have not been investigated in combination with medicines used in clinical practice. AIM OF THE STUDY: This study aimed to evaluate the chemical composition of propolis extracts from Apis mellifera scutellata and different Meliponini species and characterize their cytotoxicity against tumor cells, antibacterial effects, and interference with the actions of doxorubicin and gentamicin. MATERIALS AND METHODS: Chromatographic and spectrometric analyses were performed using ultra-high-performance liquid chromatography (UPLC)-tandem mass spectrometry (MS/MS). Propolis extracts were evaluated for cytotoxicity and synergism using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and the antimicrobial activity was examined using the broth microdilution technique and synergism was investigated using checkerboard and time-kill assays. RESULTS: The chemical characterization revealed the presence of 63 compounds, and the extracts showed selective cytotoxicity against tumor cell lines. Propolis extracts of mandaçaia and mirim exerted selective synergistic cytotoxicity in combination with doxorubicin. Except for the tubuna extract, all evaluated extracts exhibited antibacterial effects on gram-positive strains. Mandaçaia and mirim extracts exerted a synergistic effect with gentamicin; however, only mandaçaia extract exerted a selective effect. CONCLUSION: Propolis could be a source of antineoplastics and antibiotics. These natural products may reduce the occurrence of doxorubicin and gentamicin related adverse effects, resistance, or both.

Occurrence of antibiotics and antibiotic resistant bacteria in subtropical urban rivers in Brazil.

The occurrence of antibiotics in the natural environment has been a growing issue and correlations between this presence and developing resistance bacteria are explored. The purpose of this study was to investigate the presence of antibiotics of different classes and associated resistant bacteria, in water samples taken from urban river waters in Curitiba, Brazil. A method for the quantification of antibiotics (azithromycin, amoxicillin, norfloxacin ciprofloxacin, doxycycline and sulfamethoxazole) was developed and validated using liquid chromatography coupled with mass spectrometry. To investigate and identify coliforms resistant to these antibiotics, we performed selective microbiological culturing techniques. We detected antibiotics in our water samples; concentrations ranged from 0.13 to 4.63 µg L-1, with the highest being amoxicillin at 4.63 µg L-1. In all water samples this study, antibiotic resistant bacteria were detected. Escherichia coli was resistant to amoxicillin, norfloxacin, ciprofloxacin, doxycycline and sulfamethoxazole. Strains producing ß-lactamase with extended spectrum (ESBL and AmpC) were also found in these isolates. Enterococcus spp. displayed resistance to norfloxacin and ciprofloxacin, and some isolates were resistant to vancomycin, gentamicin and streptomycin (complementary tests). No P. aeruginosa resistant strains were observed. It is possible these antibiotics came from domestic effluents and may be contributing to the spread of bacterial resistance.

Characteristics of an Aeromonas trota strain isolated from cerebrospinal fluid.

Aeromonas are ubiquitous in aquatic habitats. However some species can cause infections in humans, but rarely meningitis. Here we describe the isolation and characterization of an Aeromonas strain from cerebrospinal fluid of a meningitis patient. The isolate, identified as A. trota by biochemical and molecular methods, was susceptible to ampicillin but resistant to cephalothin and cefazolin. Genome sequencing revealed virulence factor genes such as type VI secretion system, aerolysin and lateral flagella. The isolate exhibited swarming motility, hemolytic activity and adhesion and cytotoxicity on HeLa cells. This is the first report of A. trota associated with meningitis and its virulence characteristics.

Utilization of carbon sources by clinical isolates of Aeromonas.

Bacteria in the genus Aeromonas are primarily aquatic organisms; however, some species can cause diseases in humans, ranging from wound infections to septicemia, of which diarrhea is the most common condition. The ability to use a variety of carbon substrates is advantageous for pathogenic bacteria. Therefore, we used Biolog GN2 microplates to analyze the ability of 103 clinical, predominantly diarrheal, isolates of Aeromonas to use various carbon sources, and we verified whether, among the substrates metabolized by these strains, there were some endogenous to the human intestine. The results indicate that Aeromonas present great diversity in the utilization of carbon sources, and that they preferentially use carbohydrates and amino acids as carbon sources. Among the carbon sources metabolized by Aeromonas in vitro, some were found to be components of intestinal mucin, including aspartic acid, glutamic acid, l-serine, galactose, N-acetyl-glucosamine, and glucose, which were used by all strains tested. Additionally, mannose, d-serine, proline, threonine, and N-acetyl-galactosamine were used by several strains. The potential to metabolize substrates endogenous to the intestine may contribute to Aeromonas' capacity to grow in and colonize the intestine. We speculate that this may help explain the ability of Aeromonas to cause diarrhea.

Biochemical characteristics, adhesion, and cytotoxicity of environmental and clinical isolates of Herbaspirillum spp.

Herbaspirillum bacteria are best known as plant growth-promoting rhizobacteria but have also been recovered from clinical samples. Here, biochemical tests, matrix-assisted laser deionization-time of flight (MALDI-TOF) mass spectrometry, adherence, and cytotoxicity to eukaryotic cells were used to compare clinical and environmental isolates of Herbaspirillum spp. Discrete biochemical differences were observed between human and environmental strains. All strains adhered to HeLa cells at low densities, and cytotoxic effects were discrete, supporting the view that Herbaspirillum bacteria are opportunists with low virulence potential.

Impact of Aeromonas and diarrheagenic Escherichia coli screening in patients with diarrhea in Paraná, southern Brazil.

INTRODUCTION: A wide diversity of bacterial agents may cause diarrhea, presenting challenges to clinical laboratories to define a diagnosis. Considering that most stool cultures are negative, we screened stool samples from patients with diarrhea for the presence of 14 bacterial enteropathogens, aiming to establish which of them should be included in routine stool analysis. METHODOLOGY: Stool samples from 400 patients with diarrhea were analyzed for the presence of Salmonella, Shigella, Campylobacter, Aeromonas, Plesiomonas shigelloides, Vibrio, Yersinia enterocolitica, and diarrheagenic Escherichia coli using conventional microbiological methods and PCR. Two distinct samples were studied; one included predominantly patients involved in outbreaks, and the other patients of low socioeconomic status presenting sporadic cases of diarrhea. RESULTS: In total, 86 cultures (21.5%) were positive. Mixed infections were found in five patients, leading to recovery of 91 strains of enteropathogenic bacteria: Salmonella Enteritidis (9.2%), Aeromonas (7.2%), diarrheagenic E. coli (5.2%), and C. jejuni (1%). However, Salmonella predominated, with 11.5% frequency in diarrhea outbreaks, while Aeromonas predominated among patients of low socioeconomic status, with 14.6% frequency. CONCLUSION: Aeromonas and diarrheagenic E. coli, which are not routinely screened for, deserve to be included in laboratory screening panels.

Detection of diarrheagenic Escherichia coli using a two-system multiplex-PCR protocol.

BACKGROUND: Diarrheagenic Escherichia coli (DEC) strains are important causes of diarrhea. However, they cannot be distinguished from E. coli of the intestinal microbiota by conventional microbiological tests. METHODS: This work presents a two-system multiplex PCR for detection of DEC. Primers for 16S rRNA gene were added as internal amplification control to validate negative reactions. The multiplex-PCR system 1 contains primers for detection of Shiga toxin producing E. coli (STEC; stx1, stx2), enteropathogenic E. coli (EPEC; eae, bfpA), atypical enteropathogenic E. coli (aEPEc; eae), enteroinvasive E. coli (ETEC; lt, st), enteroinvasive E. coli (EIEC; ial), and the internal amplification control 16S rRNA. The system 2 contains primers for EIEC (ipaH), enteroaggregative E. coli (CVD432), diffusely adherent E. coli (daaE), and 16S rRNA. The protocol was tested with E. coli reference strains, and also with cultures of fecal specimens of people with diarrhea and healthy controls. RESULTS: The protocol correctly identified the DEC reference strains. No DEC marker was amplified for negative controls; these results were validated by the amplification of a fragment of the 16S rRNA gene. The frequency of DEC was 7.6% for both patients and healthy controls; two Shigella sonnei strains were detected in the group with diarrhea. The identity of the amplicons was confirmed by DNA sequencing. CONCLUSION: The protocol is specific for DEC Shigella and is suitable for clinical laboratories.