Two rapid assays for screening of patulin biodegradation

Artículo sobre distintos ensayos para comprobar la biodegradación de la patulinaThe mycotoxin patulin is produced by the blue mould pathogen Penicillium expansum in rotting apples during postharvest storage. Patulin is toxic to a wide range of organisms, including humans, animals, fungi and bacteria. Wash water from apple packing and processing houses often harbours patulin and fungal spores, which can contaminate the environment. Ubiquitous epiphytic yeasts, such as Rhodosporidium kratochvilovae strain LS11 which is a biocontrol agent of P. expansum in apples, have the capacity to resist the toxicity of patulin and to biodegrade it. Two non-toxic products are formed. One is desoxypatulinic acid. The aim of the work was to develop rapid, high-throughput bioassays for monitoring patulin degradation in multiple samples. Escherichia coli was highly sensitive to patulin, but insensitive to desoxypatulinic acid. This was utilized to develop a detection test for patulin, replacing time-consuming thin layer chromatography or high-performance liquid chromatography. Two assays for patulin degradation were developed, one in liquid medium and the other in semi-solid medium. Both assays allow the contemporary screening of a large number of samples. The liquid medium assay utilizes 96-well microtiter plates and was optimized for using a minimum of patulin. The semisolid medium assay has the added advantage of slowing down the biodegradation, which allows the study and isolation of transient degradation products. The two assays are complementary and have several areas of utilization, from screening a bank of microorganisms for biodegradation ability to the study of biodegradation pathways

Genotype by environment interaction in Nelore cattle from five Brazilian states

Records from 75,941 Nelore cattle were used to determine the importance of genotype by environment interaction (GEI) in five Brazilian states. (Co)variance components were estimated by single-trait analysis (with yearling weight, W450, considered to be the same trait in all states) and multiple-trait analysis (with the record from each state considered to be a different trait). The direct heritability estimates for yearling weight were 0.51, 0.39, 0.44, 0.37 and 0.41 in the states of Goiás, Mato Grosso, São Paulo, Mato Grosso do Sul and Minas Gerais, respectively. The across-state genetic correlation estimates between Goiás and Mato Grosso, Goiás and Minas Gerais, São Paulo and Minas Gerais, and Mato Grosso do Sul and Minas Gerais ranged from 0.67 to 0.75. These estimates indicate that GEIs are biologically important. No interactions were observed between Goiás and São Paulo, Goiás and Mato Grosso do Sul, Mato Grosso and São Paulo, Mato Grosso and Mato Grosso do Sul, Mato Grosso and Minas Gerais, or São Paulo and Mato Grosso do Sul (0.82 to 0.97). Comparison of single and multiple-trait analyses showed that selection based on the former was less efficient in the presence of GEI, with substantial losses (up to 10%) during selection

Dynamic model to predict the association between air quality, COVID-19 cases, and level of lockdown

Studies have reported significant reductions in air pollutant levels due to the COVID-19 outbreak worldwide due to global lockdowns. Nevertheless, all of the reports are limited compared to data from the same period over the past few years, providing mainly an overview of past events, with no future predictions. Lockdown level can be directly related to the number of new COVID-19 cases, air pollution, and economic restriction. As lockdown status varies considerably across the globe, there is a window for mega-cities to determine the optimum lockdown flexibility. To that end, firstly, we employed four different Artificial Neural Networks (ANN) to examine the compatibility to the original levels of CO, O3, NO2, NO, PM2.5, and PM10, for São Paulo City, the current Pandemic epicenter in South America. After checking compatibility, we simulated four hypothetical scenarios: 10%, 30%, 70%, and 90% lockdown to predict air pollution levels. To our knowledge, ANN have not been applied to air pollution prediction by lockdown level. Using a limited database, the Multilayer Perceptron neural network has proven to be robust (with Mean Absolute Percentage Error ∼ 30%), with acceptable predictive power to estimate air pollution changes. We illustrate that air pollutant levels can effectively be controlled and predicted when flexible lockdown measures are implemented. The models will be a useful tool for governments to manage the delicate balance among lockdown, number of COVID-19 cases, and air pollution

A computational method for the identification of dengue, zika and chikungunya virus species and genotypes

In recent years, an increasing number of outbreaks of Dengue, Chikungunya and Zika viruses have been reported in Asia and the Americas. Monitoring virus genotype diversity is crucial to understand the emergence and spread of outbreaks, both aspects that are vital to develop effective prevention and treatment strategies. Hence, we developed an efficient method to classify virus sequences with respect to their species and sub-species (i.e. serotype and/or genotype). This tool provides an easy-to-use software implementation of this new method and was validated on a large dataset assessing the classification performance with respect to whole-genome sequences and partial-genome sequences.publishersversionpublishe

In Vitro Evaluation of Enterococcus faecalis Adhesion on Various Endodontic Medicaments

E. faecalis in endodontic infection represents a biofilm type of disease, which explains the bacteria’s resistance to various antimicrobial compounds and the subsequent failure after endodontic treatment. The purpose of this study was to compare antimicrobial activities and bacteria kinetic adhesion in vitro for three endodontic medicaments with a clinical isolate of E. faecalis. We devised a shake culture which contained the following intracanalar preparations: CPD, Endoidrox (EIX), PulpCanalSealer (PCS); these were immersed in a liquid culture medium inoculated with the microorganism. The shake system velocity was able to prevent non-specific bacteria adhesion and simulated the salivary flow. Specimens were collected daily (from both the medium and medicaments) for 10 days; the viable cells were counted by plate count, while the adhesion index AI° [E. faecalis fg DNA] /mm2 was evaluated in the pastes after DNA extraction, by quantitative real time PCR for the 16S rRNA gene. A partial growth inhibition, during the first 24 hours, was observed in the liquid medium and on the medicaments for EIX and subsequently for CPD (six logs). EIX showed the lowest adhesion coefficient (5*102 [fg DNA]/mm2) for nine days and was similar to the control. PCS showed no antimicrobial/antibiofilm properties. This showed that “calcium oxide” base compounds could be active against biofilm progression and at least in the short term (2-4 days) on E. faecalis cells growing in planktonic cultures

The Dynamics of Plant Cell-Wall Polysaccharide Decomposition in Leaf-Cutting Ant Fungus Gardens

The degradation of live plant biomass in fungus gardens of leaf-cutting ants is poorly characterised but fundamental for understanding the mutual advantages and efficiency of this obligate nutritional symbiosis. Controversies about the extent to which the garden-symbiont Leucocoprinus gongylophorus degrades cellulose have hampered our understanding of the selection forces that induced large scale herbivory and of the ensuing ecological footprint of these ants. Here we use a recently established technique, based on polysaccharide microarrays probed with antibodies and carbohydrate binding modules, to map the occurrence of cell wall polymers in consecutive sections of the fungus garden of the leaf-cutting ant Acromyrmex echinatior. We show that pectin, xyloglucan and some xylan epitopes are degraded, whereas more highly substituted xylan and cellulose epitopes remain as residuals in the waste material that the ants remove from their fungus garden. These results demonstrate that biomass entering leaf-cutting ant fungus gardens is only partially utilized and explain why disproportionally large amounts of plant material are needed to sustain colony growth. They also explain why substantial communities of microbial and invertebrate symbionts have evolved associations with the dump material from leaf-cutting ant nests, to exploit decomposition niches that the ant garden-fungus does not utilize. Our approach thus provides detailed insight into the nutritional benefits and shortcomings associated with fungus-farming in ants