EmrR-Dependent Upregulation of the Efflux Pump EmrCAB Contributes to Antibiotic Resistance in Chromobacterium violaceum

Chromobacterium violaceum is an environmental Gram-negative bacterium that causes infections in humans. Treatment of C. violaceum infections is difficult and little is known about the mechanisms of antibiotic resistance in this bacterium. In this work, we identified mutations in the MarR family transcription factor EmrR and in the protein GyrA as key determinants of quinolone resistance in C. violaceum, and we defined EmrR as a repressor of the MFS-type efflux pump EmrCAB. Null deletion of emrR caused increased resistance to nalidixic acid, but not to other quinolones or antibiotics of different classes. Moreover, the ΔemrR mutant showed decreased production of the purple pigment violacein. Importantly, we isolated C. violaceum spontaneous nalidixic acid-resistant mutants with a point mutation in the DNA-binding domain of EmrR (R92H), with antibiotic resistance profile similar to that of the ΔemrR mutant. Other spontaneous mutants with high MIC values for nalidixic acid and increased resistance to fluoroquinolones presented point mutations in the gene gyrA. Using DNA microarray, Northern blot and EMSA assays, we demonstrated that EmrR represses directly a few dozen genes, including the emrCAB operon and other genes related to transport, oxidative stress and virulence. This EmrR repression on emrCAB was relieved by salicylate. Although mutation of the C. violaceum emrCAB operon had no effect in antibiotic susceptibility or violacein production, deletion of emrCAB in an emrR mutant background restored antibiotic susceptibility and violacein production in the ΔemrR mutant. Using a biosensor reporter strain, we demonstrated that the lack of pigment production in ΔemrR correlates with the accumulation of quorum-sensing molecules in the cell supernatant of this mutant strain. Therefore, our data revealed that overexpression of the efflux pump EmrCAB via mutation and/or derepression of EmrR confers quinolone resistance and alters quorum-sensing signaling in C. violaceum, and that point mutation in emrR can contribute to emergence of antibiotic resistance in bacteria

Microbiological and clinical profile of health care infections in a Pernambuco hospital / Perfil microbiológico e clínico de infecções relacionadas à assistência à saúde em um hospital de Pernambuco

Objetivo: descrever o perfil microbiológico e clínico de infecções relacionadas à assistência à saúde (IRAS). Métodos: estudo epidemiológico, descritivo e retrospectivo. Utilizou-se dados de 78 notificações de IRAS de pacientes internados entre agosto/2016 a junho/2018. A coleta de dados ocorreu entre agosto a dezembro de 2018, a partir das fichas de notificações e registro de prontuários. Resultados: parte dos diagnósticos de infecções foi no grupo neoplasias 23,0%. Klebsiella pneumoniae obteve maior taxa de infecção, e foi a mais prevalente nos pacientes em uso de dispositivos invasivos. O tempo de uso de antibióticos por mais de 10 dias foi prevalente na associação com o diagnóstico de infecção primária de corrente sanguínea. Conclusão: são necessários estudos que visem medidas preventivas e o uso racional de antibióticos para corroborar com uma menor prevalência de IRAS e resistência bacteriana.

HIV infections in youth: prevalence and associated factors

Objective: to estimate the prevalence and associated factors with Human Immunodeficiency Virus (HIV) infection in youths. Methods: cross-sectional study in two Centers for Testing and Counseling, with 279 youths from 15 to 24 years old. An anti-HIV test and a structured instrument were applied. We used bivariate analysis and logistic regression, with Bonferroni corrections, to investigate the association between the variables and the outcome. Results: the prevalence of HIV in the youth analyzed was 3.9% (Confidence interval - CI95%: 1.0-10.1). The association with the outcome of HIV was statistically significant in male youth (p=0.001), homosexuals (p<0.001), those who tested due to sexual exposure (p=0.034), perception of a high risk of acquiring HIV (p=0.002), and anal sex (p=0.004). Homosexual youth (odds ratio-OR=13.46; CI95%;1.14-15.84), with a perception of high risk of acquiring HIV (OR=18.11; CI95%: 2.28-143.69) had a higher chance of being HIV positive. Conclusion: the prevalence of HIV and associated factors in youth was ascertained. Contributions to practice: the information produced here shows evidence for those who aim to formulate policies, including health managers and workers. It can give support to the elaboration of strategies that involve perfecting preventive, coordinated actions, adjusted to behavioral contexts in the settings studied

Sifilis em pacientes sem HIV: revisão de literature / Syphilis in HIV-free patients: A review of the literature

Introdução: As manifestações clínicas dependem do estágio da doença. O T. pallidum pode iniciar a infecção onde quer que ocorra a inoculação. A sífilis é geralmente dividida em fases iniciais ou precoce e tardias. Objetivos: O objetivo desse estudo é revisar sobre o manejo da sífilis em pacientes sem HIV, compreendendo epidemiologia, fisiopatologia, manifestações clinicas, diagnóstico e tratamento. Métodos: Os bancos de dados Pubmed, Diretrizes e UpToDate foram pesquisados eletronicamente utilizando os descritores doenças sexualmente transmissíveis; infecções por treponema; sífilis congênita e treponema pallidum nos idiomas inglês e português. Discussão e Conclusão: Pacientes com sinais e sintomas compatíveis com sífilis devem ser submetidos a testes sorológicos para confirmar o diagnóstico. No entanto, alguns pacientes podem ser tratados empiricamente com base nos achados clínicos (por exemplo, pacientes com suspeita de câncer e exposição conhecida). A penicilina G administrada por via parenteral é o tratamento de escolha para todos os estágios da sífilis

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

The complete genome sequence of Chromobacterium violaceum reveals remarkable and exploitable bacterial adaptability

Chromobacterium violaceum is one of millions of species of free-living microorganisms that populate the soil and water in the extant areas of tropical biodiversity around the world. Its complete genome sequence reveals (i) extensive alternative pathways for energy generation, (ii) ≈500 ORFs for transport-related proteins, (iii) complex and extensive systems for stress adaptation and motility, and (iv) wide-spread utilization of quorum sensing for control of inducible systems, all of which underpin the versatility and adaptability of the organism. The genome also contains extensive but incomplete arrays of ORFs coding for proteins associated with mammalian pathogenicity, possibly involved in the occasional but often fatal cases of human C. violaceum infection. There is, in addition, a series of previously unknown but important enzymes and secondary metabolites including paraquat-inducible proteins, drug and heavy-metal-resistance proteins, multiple chitinases, and proteins for the detoxification of xenobiotics that may have biotechnological applications