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1.
Front Public Health ; 12: 1378413, 2024.
Artículo en Inglés | MEDLINE | ID: mdl-39076419

RESUMEN

Introduction: Infections acquired during healthcare setting stay pose significant public health threats. These infections are known as Healthcare-Associated Infections (HAI), mostly caused by pathogenic bacteria, which exhibit a wide range of antimicrobial resistance. Currently, there is no knowledge about the global cleaning process of hospitals and the bacterial diversity found in ICUs of Brazilian hospitals contributing to HAI. Objective: Characterize the microbiome and common antimicrobial resistance genes present in high-touch Intensive Care Unit (ICU) surfaces, and to identify the potential contamination of the sanitizers/processes used to clean hospital surfaces. Methods: In this national, multicenter, observational, and prospective cohort, bacterial profiles and several antimicrobial resistance genes from 41 hospitals across 16 Brazilian states were evaluated. Using high-throughput 16S rRNA amplicon sequencing and real-time PCR, the bacterial abundance and resistance genes presence were analyzed in both ICU environments and cleaning products. Results: We identified a wide diversity of microbial populations with a recurring presence of HAI-related bacteria among most of the hospitals. The median bacterial positivity rate in surface samples was high (88.24%), varying from 21.62 to 100% in different hospitals. Hospitals with the highest bacterial load in samples were also the ones with highest HAI-related abundances. Streptococcus spp., Corynebacterium spp., Staphylococcus spp., Bacillus spp., Acinetobacter spp., and bacteria from the Flavobacteriaceae family were the microorganisms most found across all hospitals. Despite each hospital particularities in bacterial composition, clustering profiles were found for surfaces and locations in the ICU. Antimicrobial resistance genes mecA, bla KPC-like, bla NDM-like, and bla OXA-23-like were the most frequently detected in surface samples. A wide variety of sanitizers were collected, with 19 different active principles in-use, and 21% of the solutions collected showed viable bacterial growth with antimicrobial resistance genes detected. Conclusion: This study demonstrated a diverse and spread pattern of bacteria and antimicrobial resistance genes covering a large part of the national territory in ICU surface samples and in sanitizers solutions. This data should contribute to the adoption of surveillance programs to improve HAI control strategies and demonstrate that large-scale epidemiology studies must be performed to further understand the implications of bacterial contamination in hospital surfaces and sanitizer solutions.


Asunto(s)
Infección Hospitalaria , Farmacorresistencia Bacteriana , Unidades de Cuidados Intensivos , ARN Ribosómico 16S , Brasil , Humanos , ARN Ribosómico 16S/genética , Infección Hospitalaria/microbiología , Estudios Prospectivos , Farmacorresistencia Bacteriana/genética , Bacterias/genética , Bacterias/efectos de los fármacos , Bacterias/aislamiento & purificación , Bacterias/clasificación , Hospitales , Reacción en Cadena en Tiempo Real de la Polimerasa , Antibacterianos/farmacología
2.
Front Cell Infect Microbiol ; 12: 879656, 2022.
Artículo en Inglés | MEDLINE | ID: mdl-35860383

RESUMEN

Antimicrobial resistance is a major threat to public health. Antimicrobial use in animal husbandry is a major concern since it can favor an increase in antimicrobial resistance among farms. Herein, we aim to better understand and characterize the main resistome profiles in microbial communities found in pig farms. Sampling of swine manure was performed in two different timepoints (October 2019 and January 2020) in each of the 14 different swine farms, located in the mesoregion of Western Santa Catarina state in Brazil, a pole of swine product production of worldwide importance. Samples were divided into three groups: farms with the opened regimen and no usage of antimicrobials (F1; n = 10), farms with the closed regimen and usage of antimicrobials (F2; n = 16), and farms with the closed regimen and no usage of antimicrobials (F3; n = 2). The metagenomic evaluation was performed to obtain and identify genetic elements related to antimicrobial resistance using nanopore sequencing. We used ResistoXplorer software to perform composition, alpha and beta diversity, and clustering analysis. In addition, PCR reactions were performed to confirm the presence or absence of seven different beta-lactamase family genes and five phosphoethanolamine transferase gene variants clinically relevant. Our findings based on the identification of resistance genes at the mechanism level showed a prevalence of alteration of the drug target (72.3%) profile, followed by drug inactivation (17.5%) and drug efflux (10.1%). We identified predominantly aminoglycosides (45.3%), tetracyclines (15.9%), and multiclass (11,2%) resistance genes. PCoA analysis indicates differences between F1 and F2 profiles. F2 samples showed increased diversity when compared to the F1 group. In addition, herein we first report the identification of mcr-4 in a slurry sample (C1F1.1) in Santa Catarina State. In general, our findings reinforce that many factors on the practices of animal husbandry are involved in the resistome profile at the mechanism and class levels. Further studies to better understand microbiome and mobilome aspects of these elements are necessary to elucidate transmission pathways between different bacteria and environments.


Asunto(s)
Antiinfecciosos , Estiércol , Animales , Antibacterianos/farmacología , Farmacorresistencia Bacteriana/genética , Granjas , Estiércol/microbiología , Porcinos
3.
Rev. biol. trop ; Rev. biol. trop;69(4)dic. 2021.
Artículo en Español | LILACS, SaludCR | ID: biblio-1387685

RESUMEN

Resumen Introducción: La disciplina científica de la bioinformática tiene el potencial de generar aplicaciones innovadoras para las sociedades humanas. Costa Rica, pequeña en tamaño y población en comparación con otros países de América Latina, ha ido adoptando la disciplina de manera progresiva. El reconocer los avances permite determinar hacia dónde puede dirigirse el país en este campo, así como su contribución a la región latinoamericana. Objetivo: En este manuscrito se reporta evidencia de la evolución de la bioinformática en Costa Rica, para identificar debilidades y fortalezas que permitan definir acciones a futuro. Métodos: Se realizaron búsquedas en bases de datos de publicaciones científicas y repositorios de secuencias, así como información de actividades de capacitación, redes, infraestructura, páginas web y fuentes de financiamiento. Resultados: Se observan avances importantes desde el 2010, incluyendo un aumento en oportunidades de entrenamiento y número de publicaciones, aportes significativos a las bases de datos de secuencias y conexiones por medio de redes. Sin embargo, ciertas áreas, como la masa crítica y la financiación requieren más desarrollo. La comunidad científica y sus patrocinadores deben promover la investigación basada en bioinformática, invertir en la formación de estudiantes de posgrado, aumentar la formación de profesionales, crear oportunidades laborales para carreras en bioinformática y promover colaboraciones internacionales a través de redes. Conclusiones: Se sugiere que para experimentar los beneficios de las aplicaciones de la bioinformática se deben fortalecer tres aspectos clave: la comunidad científica, la infraestructura de investigación y las oportunidades de financiamiento. El impacto de tal inversión sería el desarrollo de proyectos ambiciosos pero factibles y colaboraciones extendidas dentro de la región latinoamericana. Esto permitiría realizar contribuciones significativas para abordar los desafíos globales y la aplicación de nuevos enfoques de investigación, innovación y transferencia de conocimiento para el desarrollo de la economía, dentro de un marco de ética de la investigación.


Abstract Introduction: The scientific discipline of bioinformatics has the potential to generate innovative applications for human societies. Costa Rica, small in size and population compared to other Latin American countries, has been progressively adopting the discipline. Recognizing progress makes it possible to determine where the country can go in this field, as well as its contribution to the Latin American region. Objective: This manuscript reports evidence of the evolution of bioinformatics in Costa Rica, to identify weaknesses and strengths allowing future actions plans. Methods: We searched databases of scientific publications and sequence repositories, as well as information on training activities, networks, infrastructure, web pages and funding sources. Results: Important advances have been observed since 2010, such as increases in training opportunities and the number of publications, significant contributions to the sequence databases and connections through networks. However, areas such as critical mass and financing require further development. The scientific community and its sponsors should promote bioinformatics-based research, invest in graduate student training, increase professional training, create career opportunities in bioinformatics, and promote international collaborations through networks. Conclusions: It is suggested that in order to experience the benefits of bioinformatics applications, three key aspects must be strengthened: the scientific community, the research infrastructure, and funding opportunities. The impact of such investment would be the development of ambitious but feasible projects and extended collaborations within the Latin American region and abroad. This would allow significant contributions to address global challenges and the implementation of new approaches to research, innovation and knowledge transfer for the development of the economy, within an ethics of research framework.


Asunto(s)
Biología Computacional/tendencias , Manejo de Datos , Costa Rica
4.
Microbiol Res (Pavia) ; 11(2): 45-55, 2020 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-39175946

RESUMEN

Understanding the different factors shaping the spatial and temporal distribution of marine microorganisms is fundamental in predicting their responses to future environmental disturbances. There has been, however, little effort to characterize the microbial diversity including the microbiome dynamics among regions in the Caribbean Sea. Toward this end, this study was designed to gain some critical insights into microbial diversity within the coastal marine ecosystem off the coast of Puerto Rico. Using Illumina MiSeq, the V4 region of the 16S rRNA gene was sequenced with the goal of characterizing the microbial diversity representative of different coastal sites around the island of Puerto Rico. This study provided valuable insights in terms of the local bacterial taxonomic abundance, α and ß diversity, and the environmental factors shaping microbial community composition and structure. The most dominant phyla across all 11 sampling sites were the Proteobacteria, Bacteroidetes, and Planctomycetes, while the least dominant taxonomic groups were the NKB19, Tenericutes, OP3, Lentisphaerae, and SAR406. The geographical area (Caribbean and Atlantic seas) and salinity gradients were the main drivers shaping the marine microbial community around the island. Despite stable physical and chemical features of the different sites, a highly dynamic microbiome was observed. This highlights Caribbean waters as one of the richest marine sources for a microbial biodiversity hotspot. The data presented here provide a basis for further temporal evaluations aiming at deciphering microbial taxonomic diversity around the island, while determining how microbes adapt to changes in the climate.

5.
Acta biol. colomb ; 20(2): 23-35, mayo-ago. 2015. ilus, tab
Artículo en Inglés | LILACS | ID: lil-743843

RESUMEN

RNA Sequencing (RNA-Seq) is a newly born tool that has revolutionized the post-genomic era. The data produced by RNA-Seq, sequencing technologies and use of bioinformatics are exploding rapidly. In recent years, RNA-Seq has been the method of choice for profiling dynamic transcriptome taking advantage of high throughput sequencing technologies. RNA-Seq studies have shown the transcriptome magnitude, notion and complexity. From 2008, as its introduction year, the relevant reports on RNA-Seq have been multiplied by more than 2822 times just in 6 years. RNA-Seq also contributes a more accurate gene expression and transcript isoform estimation than other methods. Furthermore, some of the potential applications for RNA-Seq cannot be conducted by other methods and as yet are unique to RNA-Seq. As RNA-Seq approaches increase in speed and decrease in cost, more distinct researches are applied and become more common and accurate. RNA-Seq is a cross and interdisciplinary method that interconnects biology to other scientific topics. This article describes RNA-Seq approach, technologies, methodologies, implementation, and methods done so far in characterizing and profiling transcriptomes.


En los últimos años, la técnica RNA-Seq ha tenido un desarrollo acelerado y se ha convertido en el método de elección para el estudio y la caracterización de los transcriptomas dinámicos, aprovechando las tecnologías de secuenciación de alto rendimiento. Estudios aplicando RNA-Seq han mostrado la magnitud, noción y complejidad del transcripotma. A partir de 2008, año de introducción de la técnica, los estudios con RNA-Seq se han multiplicados por más de 2822 veces sólo en 6 años. Al compararse con otros métodos, los estudios empleando RNA-Seq contribuyen a una estimación más precisa de la expresión génica y de las isoformas de los transcriptos. Además, algunas de las aplicaciones potenciales de RNA-Seq no se pueden llevar a cabo con otros métodos. El uso de RNA-Seq aumenta la velocidad de obtención de información y disminuye los costos, logrando con su uso, que investigaciones diversas se vuelvan más frecuentes y precisas. RNA-Seq es un método interdisciplinario que interconecta la biología a otros temas científicos. En este artículo se describe el planteamiento de la tecnología RNA-Seq, metodologías y los métodos realizados en la caracterización de transcriptomas.

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