19 research outputs found
Zika virus disrupts gene expression in human myoblasts and myotubes: Relationship with susceptibility to infection
The tropism of Zika virus (ZIKV) has been described in the nervous system, blood, placenta, thymus, and skeletal muscle. We investigated the mechanisms of skeletal muscle susceptibility to ZIKV using an in vitro model of human skeletal muscle myogenesis, in which myoblasts differentiate into myotubes. Myoblasts were permissive to ZIKV infection, generating productive viral particles, while myotubes controlled ZIKV replication. To investigate the underlying mechanisms, we used gene expression profiling. First, we assessed gene changes in myotubes compared with myoblasts in the model without infection. As expected, we observed an increase in genes and pathways related to the contractile muscle system in the myotubes, a reduction in processes linked to proliferation, migration and cytokine production, among others, confirming the myogenic capacity of our system in vitro. A comparison between non-infected and infected myoblasts revealed more than 500 differentially expressed genes (DEGs). In contrast, infected myotubes showed almost 2,000 DEGs, among which we detected genes and pathways highly or exclusively expressed in myotubes, including those related to antiviral and innate immune responses. Such gene modulation could explain our findings showing that ZIKV also invades myotubes but does not replicate in these differentiated cells. In conclusion, we showed that ZIKV largely (but differentially) disrupts gene expression in human myoblasts and myotubes. Identifying genes involved in myotube resistance can shed light on potential antiviral mechanisms against ZIKV infection
Molecular epidemiological investigation of Mayaro virus in febrile patients from Goiania City, 2017-2018.
Mayaro virus (MAYV) has historically been associated with sylvatic transmission; however, urban outbreaks have been reported in Brazil, including cases of co-detection with dengue virus (DENV). Therefore, we performed a molecular survey to investigate MAYV circulation and cocirculation with DENV within Goiania, a major city in Central-West Brazil. Among 375 subjects with arbovirus-like symptoms, 259 were positive for DENV and 26 for MAYV. Of these, 17 were coinfected with DENV-2, suggesting co-transmission of the viruses. The most common complaints at the time of inclusion were myalgia, headache, fever, arthralgia, retro-orbital pain, and skin rash. No specific symptoms were associated with MAYV when either detected alone or co-detected with DENV, compared to that when DENV was detected alone. Most MAYV-infected subjects were women with no recent travel history to rural/sylvatic areas. Phylogenetic reconstruction indicated that the MAYV identified in this study is closely related with a lineage observed in Peru, belonging to genotype D. Our results corroborate the growing circulation of MAYV in urban environments in Brazil and reinforce the need to implement laboratory diagnosis in the Unified Health System, considering that the clinical manifestations of Mayaro fever are similar to those of other arboviruses, particularly dengue. Furthermore, most cases occurred in association with DENV-2. Further phylogenetic studies are needed to evaluate MAYV, which has not been widely examined
Dynamics of Early Establishment of SARS-CoV-2 VOC Omicron Lineages in Minas Gerais, Brazil
Brazil is one of the nations most affected by Coronavirus disease 2019 (COVID-19). The introduction and establishment of new virus variants can be related to an increase in cases and fatalities. The emergence of Omicron, the most modified SARS-CoV-2 variant, caused alarm for the public health of Brazil. In this study, we examined the effects of the Omicron introduction in Minas Gerais (MG), the second-most populous state of Brazil. A total of 430 Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) samples from November 2021 to June 2022 from Belo Horizonte (BH) city were sequenced. These newly sequenced genomes comprise 72% of all previously available SARS-CoV-2 genomes for the city. Evolutionary analysis of novel viral genomes reveals that a great diversity of Omicron sublineages have circulated in BH, a pattern in-keeping with observations across Brazil more generally. Bayesian phylogeographic reconstructions indicate that this diversity is a product of a large number of international and national importations. As observed previously, São Paulo state is shown as a significant hub for viral spread throughout the country, contributing to around 70% of all viral Omicron introductions detected in MG
Data and R code used in epidemiological analyses.
Since 2014, Brazil has experienced an unprecedented epidemic caused by chikungunya virus (CHIKV), with several waves of East-Central-South-African (ECSA) lineage transmission reported across the country. In 2018, Rio de Janeiro state, the third most populous state in Brazil, reported 41% of all chikungunya cases in the country. Here we use evolutionary and epidemiological analysis to estimate the timescale of CHIKV-ECSA-American lineage and its epidemiological patterns in Rio de Janeiro. We show that the CHIKV-ECSA outbreak in Rio de Janeiro derived from two distinct clades introduced from the Northeast region in mid-2015 (clade RJ1, n = 63/67 genomes from Rio de Janeiro) and mid-2017 (clade RJ2, n = 4/67). We detected evidence for positive selection in non-structural proteins linked with viral replication in the RJ1 clade (clade-defining: nsP4-A481D) and the RJ2 clade (nsP1-D531G). Finally, we estimate the CHIKV-ECSA’s basic reproduction number (R0) to be between 1.2 to 1.6 and show that its instantaneous reproduction number (Rt) displays a strong seasonal pattern with peaks in transmission coinciding with periods of high Aedes aegypti transmission potential. Our results highlight the need for continued genomic and epidemiological surveillance of CHIKV in Brazil, particularly during periods of high ecological suitability, and show that selective pressures underline the emergence and evolution of the large urban CHIKV-ECSA outbreak in Rio de Janeiro.</div
Fig 2 -
Symptoms distribution, RT-qPCR Ct values dynamics and their correlation with genome sequencing coverage. (A) Distribution of symptoms exhibited by all CHIKV positive patients in the Duque de Caxias cohort. (B) The time lag between symptoms onset and sample collection dates exhibits correlation with RT-qPCR Ct values. As infection proceeds, viral loads decrease (Cts increase) likely due to immunological response. (C) Negative correlation between RT-qPCR Cts and genome sequencing coverage. Sequences characterized from samples with higher viral load (lower Cts) tend to exhibit higher coverage, although no strong statistical correlation was inferred on a linear model (p = 0.08).</p
<i>R</i><sub><i>0</i></sub> estimates and sensitivity analysis.
R0 estimates obtained with epidemiological data under different generation time distributions (gamma distributions with means 10, 14 and 20, and constant standard deviation: 6.4 days). (TIFF)</p
<i>R</i><sub><i>t</i></sub> estimates and sensitivity analysis.
(A)Rt estimate performed with different generation time (GT) distributions (gamma distributions with means 10, 14 and 20, and constant standard deviation: 6.4 days). Colors indicate estimates for different GTs (10: gray, 14: yellow, 20: blue). (B) Rt estimates performed with different sliding window lengths (3 to 8 weeks). Colors indicate estimates for different window lengths (3: salmon, 4: yellow, 5: green, 6: blue, 7: purple, 8: pink). Solid lines indicate mean values and ribbons indicate the 95% confidence intervals. The dashed lines denote the critical epidemic threshold (Rt = 1). (TIFF)</p
BEAST xml files and outputs generated in this study.
BEAST xml files and outputs generated in this study.</p
Input and output files of selection analysis with Datamonkey.
Input and output files of selection analysis with Datamonkey.</p
Maximum likelihood phylogenetic analysis of global and ECSA-American datasets.
(A) Phylogenetic tree inferred from the global dataset. All new characterized genomes clustered within the ECSA-Br clade. Names of lineages and relevant clades are indicated. SH-aLRT statistical support values for these clades are shown close to their defining nodes (colored in red). (B) Phylogeny inferred from the filtered ECSA-American dataset. Tip shapes are colored according to sampling location (Centre-West region: purple, North region: yellow, Northeast region: red, Rio de Janeiro state: green). Sequences generated in this study are highlighted with red circles around the tip shapes. Clades composed mostly by RJ sequences are indicated along their SH-aLRT support values. (C) The root-to-tip regression plot, which indicates a strong temporal signal (R2 = 0.72, slope = 5.19 x 10−4). Scale bars represent substitutions per site (s/s).</p