ABSTRACT
The soils of the Amazon are complex environments with different organisms cohabiting in continuous adaptation processes; this changes significantly when these environments are modified for the development of agricultural activities that alter the chemical, macro, and microbiological compositions. The metagenomic variations and the levels of the environmental impact of four different soil samples from the Amazon region were evaluated, emphasizing the resistome. Soil samples from the organic phase from the different forest, pasture, and transgenic soybean monocultures of 2-14 years old were collected in triplicate at each site. The samples were divided into two groups, and one group was pre-treated to obtain genetic material to perform sequencing for metagenomic analysis; another group carried out the chemical characterization of the soil, determining the pH, the content of cations, and heavy metals; these were carried out in addition to identifying with different databases the components of the microbiological communities, functional genes, antibiotic and biocide resistance genes. A greater diversity of antibiotic resistance genes was observed in the forest soil. In contrast, in monoculture soils, a large number of biocide resistance genes were evidenced, highlighting the diversity and abundance of crop soils, which showed better resistance to heavy metals than other compounds, with a possible dominance of resistance to iron due to the presence of the acn gene. For up to 600 different genes for resistance to antibiotics and 256 genes for biocides were identified, most of which were for heavy metals. The most prevalent was resistance to tetracycline, cephalosporin, penam, fluoroquinolone, chloramphenicol, carbapenem, macrolide, and aminoglycoside, providing evidence for the co-selection of these resistance genes in different soils. Furthermore, the influence of vegetation cover on the forest floor was notable as a protective factor against the impact of human contamination. Regarding chemical characterization, the presence of heavy metals, different stress response mechanisms in monoculture soils, and the abundance of mobile genetic elements in crop and pasture soils stand out. The elimination of the forest increases the diversity of genes for resistance to biocides, favoring the selection of genes for resistance to antibiotics in soils.
ABSTRACT
Peperomia pellucida L. Kunth is a herb well-known for its secondary metabolites (SM) with biological potential. In this study, the variations in the SM of P. pellucida during association with rhizobacteria were evaluated. Plants were inoculated with Enterobacter asburiae and Klebsiella variicola, which were identified by sequencing of the 16S rRNA gene. The data were evaluated at 7, 21, and 30-day post inoculation (dpi). Plant-bacteria symbiosis improved plant growth and weight. Total phenolic content and phenylalanine ammonia lyase enzyme activity had a significant increase mainly at 30 dpi. P. pellucida was mainly composed of phenylpropanoids (37.30-52.28%) and sesquiterpene hydrocarbons (39.28-49.42%). The phenylpropanoid derivative 2,4,5-trimethoxy-styrene (ArC2), the sesquiterpene hydrocarbon ishwarane, and the phenylpropanoid dillapiole were the major compounds. Principal component analysis (PCA) of the classes and compounds ≥ 2.0% indicated that plants colonized by E. asburiae had a reduction in the content of sesquiterpene hydrocarbons and an increase in phenylpropanoids and derivatives. Plants treated with this bacterium also had an increase in the content of 2,4,5-trimethoxystyrene at 30 dpi. Plants inoculated with K. variicola had significant increases only in the content of the classes monoterpene hydrocarbons and 'other compounds' (hydrocarbons, esters, ketones, etc.). These data suggest that the production of plant secondary metabolites can be modified depending on the type of rhizobacteria inoculated.
Subject(s)
Peperomia/growth & development , Enterobacter/genetics , Klebsiella/genetics , Peperomia/metabolism , Peperomia/microbiology , Phenols/metabolism , Phenylalanine Ammonia-Lyase/metabolism , Phylogeny , Principal Component Analysis , RNA, Ribosomal, 16S/genetics , Rhizosphere , Secondary Metabolism , Volatile Organic Compounds/metabolismABSTRACT
OBJECTIVE: To report the university extension research result entitled 'The COVID-PA Bulletin', which presented forecasts on the behavior of the pandemic in the state of Pará, Brazil. METHODS: The artificial intelligence technique also known as 'artificial neural networks' was used to generate 13 bulletins with short-term forecasts based on historical data from the State Department of Public Health information system. RESULTS: After eight months of predictions, the technique generated reliable results, with an average accuracy of 97% (observed for147 days) for confirmed cases, 96% (observed for 161 days) for deaths and 86% (observed for 72 days) for Intensive Care Unit bed occupancy. CONCLUSION: These bulletins have become a useful decision-making tool for public managers, assisting in the reallocation of hospital resources and optimization of COVID-19 control strategies in various regions of the state of Pará.
Subject(s)
COVID-19 , Pandemics , Adaptation, Psychological , Artificial Intelligence , Brazil/epidemiology , Humans , SARS-CoV-2ABSTRACT
Objective: Report the university research and extension product denominated 'Boletim COVID-PA' which presented projections about the pandemic in the State of Pará, Brazil, with practical, mathematically rigorous and computationally efficient approaches. Methods: The artificial intelligence technique known as Artificial Neural Networks was used to generate thirteen bulletins with short-term projections based on historical data from the State Department of Public Health system. Results: After eight months of projections, the technique generated reliable results with an average accuracy of 97% (147 days observed) for confirmed cases, 96% (161 observed days) for deaths and 86% (72 days observed) for occupancy of intensive care unit beds. Conclusion: These bulletins have become a useful tool for decision making by public managers, assisting in reallocating hospital resources and optimizing COVID-19 control strategies for the various regions of the State of Pará.
Objetivo: Relatar o produto de pesquisa e extensão universitária denominado Boletim COVID-PA, que apresentou projeções sobre o comportamento da pandemia no estado do Pará, Brasil. Métodos: Utilizou-se da técnica de inteligência artificial conhecida como 'redes neurais artificiais', para gerar 13 boletins com projeções de curto prazo baseadas nos dados históricos do sistema da Secretaria de Estado de Saúde Pública. Resultados: Após oito meses de projeções, a técnica gerou resultados confiáveis, com precisão média de 97% (147 dias observados) para casos confirmados, 96% (161 dias observados) para óbitos e 86% (72 dias observados) para ocupação de leitos de unidade de terapia intensiva. Conclusão: Esses boletins tornaram-se um instrumento útil para a tomada de decisão de gestores públicos, auxiliando na realocação de recursos hospitalares e otimização das estratégias de controle da COVID-19 nas diversas regiões do estado do Pará.
ABSTRACT
The first case of the novel coronavirus in Brazil was notified on February 26, 2020. After 21 days, the first case was reported in the second largest State of the Brazilian Amazon. The State of Pará presented difficulties in combating the pandemic, ranging from underreporting and a low number of tests to a large territorial distance between cities with installed hospital capacity. Due to these factors, mathematical data-driven short-term forecasting models can be a promising initiative to assist government officials in more agile and reliable actions. This study presents an approach based on artificial neural networks for the daily and cumulative forecasts of cases and deaths caused by COVID-19, and the forecast of demand for hospital beds. Six scenarios with different periods were used to identify the quality of the generated forecasting and the period in which they start to deteriorate. Results indicated that the computational model adapted capably to the training period and was able to make consistent short-term forecasts, especially for the cumulative variables and for demand hospital beds.
Subject(s)
COVID-19/epidemiology , Beds , Brazil/epidemiology , COVID-19/mortality , Forecasting , Hospitalization , Humans , Models, Statistical , Neural Networks, Computer , Pandemics , SARS-CoV-2/isolation & purificationABSTRACT
Objetivo: Relatar o produto de pesquisa e extensão universitária denominado Boletim COVID-PA, que apresentou projeções sobre o comportamento da pandemia no estado do Pará, Brasil. Métodos: Utilizou-se da técnica de inteligência artificial conhecida como 'redes neurais artificiais', para geração de 13 boletins com projeções de curto prazo baseadas nos dados históricos do sistema da Secretaria de Estado de Saúde Pública. Resultados: Após oito meses de projeções, a técnica gerou resultados confiáveis, com precisão média de 97% (147 dias observados) para casos confirmados, 96% (161 dias observados) para óbitos e 86% (72 dias observados) para ocupação de leitos de unidade de terapia intensiva. Conclusão: Esses boletins tornaram-se um instrumento útil para a tomada de decisão de gestores públicos, auxiliando na realocação de recursos hospitalares e otimização das estratégias de controle da COVID-19 nas diversas regiões do estado do Pará.
Objetivo: Reporte el resultado de la investigación y extensión universitaria denominada 'Boletim COVID-PA' que presentó proyecciones sobre el comportamiento de la pandemia en el estado de Pará, con un enfoque práctico y computacionalmente eficiente. Métodos: Fue utilizada una técnica de inteligencia artificial denominadas Redes Neurales para generar trece boletines con proyecciones basado en datos históricos del sistema de la Secretaría de Salud Pública. Resultados: Después de ocho meses de previsiones, la técnica genero resultados confiables con una precisión promedio de 97% (147 días observados) para casos confirmados, 96% (161 días observados) para los fallecimientos y 86% (72 días observados) para la ocupación de camas en las unidades de cuidados intensivos. Conclusión: Estos boletines se convirtieron en una herramienta para la toma de decisiones, auxiliando en la redistribución de recursos en los hospitales en el estado de Pará.
Objective: To report the university extension research result entitled 'The COVID-PA Bulletin', which presented forecasts on the behavior of the pandemic in the state of Pará, Brazil. Methods: The artificial intelligence technique also known as 'artificial neural networks' was used to generate 13 bulletins with short-term forecasts based on historical data from the State Department of Public Health information system. Results: After eight months of predictions, the technique generated reliable results, with an average accuracy of 97% (observed for147 days) for confirmed cases, 96% (observed for 161 days) for deaths and 86% (observed for 72 days) for Intensive Care Unit bed occupancy. Conclusion: These bulletins have become a useful decision-making tool for public managers, assisting in the reallocation of hospital resources and optimization of COVID-19 control strategies in various regions of the state of Pará.
Subject(s)
Artificial Intelligence , Decision Making , COVID-19/epidemiology , Brazil/epidemiology , Neural Networks, ComputerABSTRACT
The genus Psychrobacter includes Gram-negative coccobacilli that are non-pigmented, oxidase-positive, non-motile, psychrophilic or psychrotolerant, and halotolerant. Psychrobacter strain ENNN9_III was isolated from water in a polluted temperate estuarine system, contaminated with hydrocarbons and heavy metals. The genome has a G + C content of 42.7%, 2618 open reading frames (ORFs), three copies of the rRNAs operon, and 29 tRNA genes. Twenty-five sequences related to the degradation of aromatic compounds were predicted, as well as numerous genes related to resistance to metals or metal(loid)s. The genome sequence of Psychrobacter strain ENNN9_III provides the groundwork for further elucidation of the mechanisms of metal resistance and aromatic compounds degradation. Future studies are needed to confirm the usefulness of this strain for bioremediation proposes.
ABSTRACT
The species Corynebacterium renale, Corynebacterium pilosum, and Corynebacterium cystitidis were initially thought to be the same species C. renale, but with different immunological types. These bacteria are the causative agent of cystitis, urethritis and pyelonephritis and are found usually as constituents of the normal flora in the lower urogenital tract of cattle. Therefore, we present the draft genome sequences of two pathogenic Corynebacterium species: C. renale CIP 52.96 and C. pilosum CIP 103422. The genome sequences of these species have 2,322,762 bp with 2,218 protein encoding genes and 2,548,014 bp with 2,428 protein encoding genes, respectively. These genomes can help clarify the virulence mechanisms of these unknown bacteria and enable the development of more effective methods for control.
ABSTRACT
Vibrio fluvialis is a halophilic bacterium found in many environments and is mainly associated with sporadic cases and outbreaks of gastroenteritis in humans. Here, we describe the genome sequences of environmental strains of V. fluvialis 560 (Vf560) and V. fluvialis 539 (Vf539) possessing a variant of the integrative and conjugative element (ICE) SXT for the first time in Brazil and South America.
ABSTRACT
Vibrio cholerae O1 is the causative agent of cholera and is ubiquitous in the aquatic environment, while V. cholerae strains non-O1 and non-O139 are recognized as causative agents of sporadic and localized outbreaks of diarrhea. Here, we report the complete sequence of a non-O1 and non-O139 V. cholerae strain (VCC19), which was isolated from the environment in Brazil. The sequence includes the integrative conjugative element (ICE). This paper is the first report of the presence of such an element in a V. cholerae strain isolated in Brazil.
ABSTRACT
Corynebacterium ulcerans is a bacterial species with high importance because it causes infections in animals and, rarely, in humans. Its virulence mechanisms remain unclear. The current study describes the draft genome of C. ulcerans FRC58, which was isolated from the bronchitic aspiration of a patient in France.
ABSTRACT
An epidemic of surgical-site infections by a single strain of Mycobacterium abscessus subsp. bolletii affected >1,700 patients in Brazil from 2004 to 2008. The genome of the epidemic prototype strain M. abscessus subsp. bolletii INCQS 00594, deposited in the collection of the National Institute for Health Quality Control (INCQS), was sequenced.
ABSTRACT
Serratia fonticola is a Gram-negative bacterium with a wide distribution in aquatic environments. On some occasions, it has also been regarded as a significant human pathogen. In this work, we report the first draft genome sequence of an S. fonticola strain (LMG 7882(T)), which was isolated from freshwater.
ABSTRACT
Serratia fonticola UTAD54 is an environmental isolate that is resistant to carbapenems due to the presence of a class A carbapenemase and a metallo-ß-lactamase that are unique to this strain. Its draft genome sequence was obtained to clarify the molecular basis of its carbapenem resistance and identify the genomic context of its carbapenem resistance determinants.
ABSTRACT
Streptococcus agalactiae (Lancefield group B; GBS) is the causative agent of meningoencephalitis in fish, mastitis in cows, and neonatal sepsis in humans. Meningoencephalitis is a major health problem for tilapia farming and is responsible for high economic losses worldwide. Despite its importance, the genomic characteristics and the main molecular mechanisms involved in virulence of S. agalactiae isolated from fish are still poorly understood. Here, we present the genomic features of the 1,820,886 bp long complete genome sequence of S. agalactiae SA20-06 isolated from a meningoencephalitis outbreak in Nile tilapia (Oreochromis niloticus) from Brazil, and its annotation, consisting of 1,710 protein-coding genes (excluding pseudogenes), 7 rRNA operons, 79 tRNA genes and 62 pseudogenes.
ABSTRACT
With the advent of high-throughput DNA sequencing platforms, there has been a reduction in the cost and time of sequencing. With these advantages, new challenges have emerged, such as the handling of large amounts of data, quality assessment, and the assembly of short reads. Currently, benchtop high-throughput sequencers enable the genomes of prokaryotic organisms to be sequenced within two hours with a reduction in coverage compared with the SOLiD, Illumina and 454 FLX Titanium platforms, making it necessary to evaluate the efficiency of less expensive benchtop instruments for prokaryotic genomics. In the present work, we evaluate and propose a methodology for the use of the Ion Torrent PGM platform for decoding the gram-positive bacterium Corynebacterium pseudotuberculosis, for which 15 complete genome sequences have already been deposited based on fragment and mate-paired libraries with a 3-kb insert size. Despite the low coverage, a single sequencing run using a mate-paired library generated 39 scaffolds after de novo assembly without data curation. This result is superior to that obtained by sequencing using libraries generated from fragments marketed by the equipment's manufacturer, as well as that observed for mate-pairs sequenced by SOLiD. The generated sequence added an extra 91kb to the genome available at NCBI.
Subject(s)
Corynebacterium pseudotuberculosis/genetics , Genomics/methodsABSTRACT
Methylobacterium mesophilicum strain SR1.6/6 is an endophytic bacterium isolated from a surface-sterilized Citrus sinensis branch. Ecological and biotechnological aspects of this bacterium, such as the genes involved in its association with the host plant and the primary oxidation of methanol, were annotated in the draft genome.
ABSTRACT
Vibrio cholerae is the causal organism of the cholera epidemic, which is mostly prevalent in developing and underdeveloped countries. However, incidences of cholera in developed countries are also alarming. Because of the emergence of new drug-resistant strains, even though several generic drugs and vaccines have been developed over time, Vibrio infections remain a global health problem that appeals for the development of novel drugs and vaccines against the pathogen. Here, applying comparative proteomic and reverse vaccinology approaches to the exoproteome and secretome of the pathogen, we have identified three candidate targets (ompU, uppP and yajC) for most of the pathogenic Vibrio strains. Two targets (uppP and yajC) are novel to Vibrio, and two targets (uppP and ompU) can be used to develop both drugs and vaccines (dual targets) against broad spectrum Vibrio serotypes. Using our novel computational approach, we have identified three peptide vaccine candidates that have high potential to induce both B- and T-cell-mediated immune responses from our identified two dual targets. These two targets were modeled and subjected to virtual screening against natural compounds derived from Piper betel. Seven compounds were identified first time from Piper betel to be highly effective to render the function of these targets to identify them as emerging potential drugs against Vibrio. Our preliminary validation suggests that these identified peptide vaccines and betel compounds are highly effective against Vibrio cholerae. Currently we are exhaustively validating these targets, candidate peptide vaccines, and betel derived lead compounds against a number of Vibrio species.
Subject(s)
Cholera/drug therapy , Drug Discovery , Piper betle/chemistry , Vibrio cholerae/drug effects , Cholera/immunology , Cholera/microbiology , Epitopes, T-Lymphocyte/immunology , Humans , Ligands , Proteome , Small Molecule Libraries/chemistry , Small Molecule Libraries/pharmacology , Vaccines, Subunit/chemistry , Vaccines, Subunit/pharmacology , Vibrio cholerae/immunology , Vibrio cholerae/pathogenicityABSTRACT
Corynebacterium pseudotuberculosis equi is a Gram-positive pathogenic bacterium which affects a variety of hosts. Besides the great economic losses it causes to horse-breeders, this organism is also known to be an important infectious agent to cattle and buffaloes. As an outcome of the efforts in characterizing the molecular basis of its virulence, several complete genome sequences were made available in recent years, enabling the large-scale assessment of genes throughout distinct isolates. Meanwhile, the RNA-seq stood out as the technology of choice for comprehensive transcriptome studies, which may bring valuable information regarding active genomic regions, despite of the still impeditive associated costs. In an attempt to increase the use of generated reads per instrument run, by effectively eliminating unwanted rRNAs from total RNA samples without relying on any commercially available kits, we applied denaturing high-performance liquid chromatography (DHPLC) as an alternative method to assess the transcriptional profile of C. pseudotuberculosis. We have found that the DHPLC depletion method, allied to Ion Torrent sequencing, allows mapping of transcripts in a comprehensive way and identifying novel transcripts when a de novo approach is used. These data encourage us to use DHPLC in future transcriptional evaluations in C. pseudotuberculosis.
Subject(s)
Chromatography, High Pressure Liquid/methods , Corynebacterium pseudotuberculosis/metabolism , High-Throughput Nucleotide Sequencing/methods , Nucleic Acid Denaturation/genetics , RNA, Ribosomal/chemistry , Transcriptome , Animals , Bacterial Proteins/genetics , Bacterial Proteins/metabolism , Corynebacterium Infections/microbiology , Corynebacterium Infections/veterinary , Corynebacterium pseudotuberculosis/classification , Corynebacterium pseudotuberculosis/genetics , Horse Diseases/microbiology , Horses/microbiology , RNA, Bacterial/genetics , RNA, Bacterial/metabolism , RNA, Ribosomal/genetics , RNA, Ribosomal/metabolism , Species SpecificityABSTRACT
New sequencing platforms have enabled rapid decoding of complete prokaryotic genomes at relatively low cost. The Ion Torrent platform is an example of these technologies, characterized by lower coverage, generating challenges for the genome assembly. One particular problem is the lack of genomes that enable reference-based assembly, such as the one used in the present study, Corynebacterium pseudotuberculosis biovar equi, which causes high economic losses in the US equine industry. The quality treatment strategy incorporated into the assembly pipeline enabled a 16-fold greater use of the sequencing data obtained compared with traditional quality filter approaches. Data preprocessing prior to the de novo assembly enabled the use of known methodologies in the next-generation sequencing data assembly. Moreover, manual curation was proved to be essential for ensuring a quality assembly, which was validated by comparative genomics with other species of the genus Corynebacterium. The present study presents a modus operandi that enables a greater and better use of data obtained from semiconductor sequencing for obtaining the complete genome from a prokaryotic microorganism, C. pseudotuberculosis, which is not a traditional biological model such as Escherichia coli.
