Spatiotemporal transmission of SARS-CoV-2 lineages during 2020-2021 in Pernambuco-Brazil.

SARS-CoV-2 virus emerged as a new threat to humans and spread around the world, leaving a large death toll. As of January 2023, Brazil is among the countries with the highest number of registered deaths. Nonpharmacological and pharmacological interventions have been heterogeneously implemented in the country, which, associated with large socioeconomic differences between the country regions, has led to distinct virus spread dynamics. Here, we investigate the spatiotemporal dispersion of SARS-CoV-2 lineages in the Pernambuco state (Northeast Brazil) throughout the distinct epidemiological scenarios that unfolded in the first 2 years of the pandemic. We generated a total of 1,389 new SARS-CoV-2 genomes from June 2020 to August 2021. This sampling captured the arrival, communitary transmission, and the circulation of the B1.1, B.1.1.28, and B.1.1.33 lineages; the emergence of the former variant of interest P.2; and the emergence and fast replacement of all previous variants by the more transmissible variant of concern P.1 (Gamma). Based on the incidence and lineage spread pattern, we observed an East-to-West to inner state pattern of transmission, which is in agreement with the transmission of more populous metropolitan areas to medium- and small-size country-side cities in the state. Such transmission patterns may be partially explained by the main routes of traffic across municipalities in the state. Our results highlight that the fine-grained intrastate analysis of lineages and incidence spread can provide actionable insights for planning future nonpharmacological intervention for air-borne transmissible human pathogens.IMPORTANCEDuring the COVID-19 pandemic, Brazil was one of the most affected countries, mainly due its continental-size, socioeconomic differences among regions, and heterogeneous implementation of intervention methods. In order to investigate SARS-CoV-2 dynamics in the state of Pernambuco, we conducted a spatiotemporal dispersion study, covering the period from June 2020 to August 2021, to comprehend the dynamics of viral transmission during the first 2 years of the pandemic. Throughout this study, we were able to track three significant epidemiological waves of transmission caused by B1.1, B.1.1.28, B.1.1.33, P.2, and P.1 lineages. These analyses provided valuable insights into the evolution of the epidemiological landscape, contributing to a deeper understanding of the dynamics of virus transmission during the early years of the pandemic in the state of Pernambuco.

High prevalence of GR2 and GR4 plasmids in Acinetobacter baumannii strains from Brazil.

Acinetobacter baumannii is Gram-negative pathogen with extensive role in healthcare-associated infections (HAIs). Plasmids in this species are important carriers of antimicrobial resistance genes. In this work, we investigated the plasmids of 227 Brazilian A. baumannii genomes. A total of 389 plasmid sequences with 424 Rep proteins typed to 22 different homology groups (GRs) were identified. The GR2 plasmid group was the most predominant (40.6%), followed by the GR4 group (16.7%), representing ∼57% of all plasmids. There is a wide distribution of plasmids among the isolates and most strains carry more than one plasmid. Our analyses revealed a significant prevalence of GR4 plasmids in Brazilian A. baumannii genomes carrying several antimicrobial resistance genes, notably to carbapenem (39.43%). These plasmids harbor a MOBQ relaxase that might confer increased spreading potential in the environment. Most plasmids of the predominant groups belong to the same plasmid taxonomic unit (PTU-Pse7) and have a AbkA/AbkB toxin-antitoxin system that has a role in plasmid stability and dissemination of carbapenem resistance genes. The results of this work should contribute to our understanding of the molecular content of plasmids in a large and populous country, highlighting the importance of genomics for enhanced epidemiological surveillance.

Multiple introductions and country-wide spread of DENV-2 genotype II (Cosmopolitan) in Brazil.

Dengue virus serotype 2, genotype Cosmopolitan (DENV-2-GII), is one of the most widespread DENV strains globally. In the USA, DENV-2 epidemics have been dominated by DENV-2 genotype Asian-American (DENV-2-GIII), and the first cases of DENV-2-GII were only described in 2019, in Peru, and in 2021 in Brazil. To gain new information about the circulation of DENV-2-GII in Brazil, we sequenced 237 DENV-2 confirmed cases sampled between March 2021 and March 2023 and revealed that DENV-2-GII is already present in all geographic regions of Brazil. The phylogeographic analysis inferred that DENV-2-GII was introduced at least four times in Brazil, between May 2020 and August 2022, generating multiple clades that spread throughout the country with different success. Despite multiple introductions of DENV-2-GII, analysis of the country-wide laboratory surveillance data showed that the Brazilian dengue epidemic in 2022 was dominated by DENV-1 in most states. We hypothesize that massive circulation of DENV-2-GIII in previous years in Brazil might have created a population immune barrier against symptomatic homotypic reinfections by DENV-2-GII, leading to sustained cryptic circulation in asymptomatic cases and localized outbreaks of this new genotype. In summary, our study stresses the importance of arboviral genomic surveillance to close monitoring and better understanding the potential impact of DENV-2-GII in the coming years.

ViralFlow: A Versatile Automated Workflow for SARS-CoV-2 Genome Assembly, Lineage Assignment, Mutations and Intrahost Variant Detection.

The COVID-19 pandemic is driven by Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) that emerged in 2019 and quickly spread worldwide. Genomic surveillance has become the gold standard methodology used to monitor and study this fast-spreading virus and its constantly emerging lineages. The current deluge of SARS-CoV-2 genomic data generated worldwide has put additional pressure on the urgent need for streamlined bioinformatics workflows. Here, we describe a workflow developed by our group to process and analyze large-scale SARS-CoV-2 Illumina amplicon sequencing data. This workflow automates all steps of SARS-CoV-2 reference-based genomic analysis: data processing, genome assembly, PANGO lineage assignment, mutation analysis and the screening of intrahost variants. The pipeline is capable of processing a batch of around 100 samples in less than half an hour on a personal laptop or in less than five minutes on a server with 50 threads. The workflow presented here is available through Docker or Singularity images, allowing for implementation on laptops for small-scale analyses or on high processing capacity servers or clusters. Moreover, the low requirements for memory and CPU cores and the standardized results provided by ViralFlow highlight it as a versatile tool for SARS-CoV-2 genomic analysis.

In silico predictions of protein interactions between Zika virus and human host.

BACKGROUND: The ZIKA virus (ZIKV) belongs to the Flaviviridae family, was first isolated in the 1940s, and remained underreported until its global threat in 2016, where drastic consequences were reported as Guillan-Barre syndrome and microcephaly in newborns. Understanding molecular interactions of ZIKV proteins during the host infection is important to develop treatments and prophylactic measures; however, large-scale experimental approaches normally used to detect protein-protein interaction (PPI) are onerous and labor-intensive. On the other hand, computational methods may overcome these challenges and guide traditional approaches on one or few protein molecules. The prediction of PPIs can be used to study host-parasite interactions at the protein level and reveal key pathways that allow viral infection. RESULTS: Applying Random Forest and Support Vector Machine (SVM) algorithms, we performed predictions of PPI between two ZIKV strains and human proteomes. The consensus number of predictions of both algorithms was 17,223 pairs of proteins. Functional enrichment analyses were executed with the predicted networks to access the biological meanings of the protein interactions. Some pathways related to viral infection and neurological development were found for both ZIKV strains in the enrichment analysis, but the JAK-STAT pathway was observed only for strain PE243 when compared with the FSS13025 strain. CONCLUSIONS: The consensus network of PPI predictions made by Random Forest and SVM algorithms allowed an enrichment analysis that corroborates many aspects of ZIKV infection. The enrichment results are mainly related to viral infection, neuronal development, and immune response, and presented differences among the two compared ZIKV strains. Strain PE243 presented more predicted interactions between proteins from the JAK-STAT signaling pathway, which could lead to a more inflammatory immune response when compared with the FSS13025 strain. These results show that the methodology employed in this study can potentially reveal new interactions between the ZIKV and human cells.

High-resolution genome-wide analysis is essential for the identification of ambiguous Aeromonas strains.

Aeromonads are mainly opportunistic pathogens; however, many species are emerging as important human pathogens. Therefore, monitoring these bacteria and their accurate characterization of its species is highly important. Aeromonas Aer593 strain was recovered from a diarrhoea outbreak and did not group with any previously described Aeromonas species by housekeeping gene sequencing. To clarify the taxonomic position of Aer593, its genome was sequenced and analysed by multilocus phylogenetic analysis (MLPA), in silico DNA-DNA hybridization (isDDH), average nucleotide identity (ANI) and core genome-based phylogenetic analyzes. The MLPA with the housekeeping genes gyrB, rpoD, recA, dnaJ, gyrA and dnaX ranked the Aer593 isolate into an independent branch suggesting that it could represent a new species. However, the identity percentages of Aer593 to A. caviae strains using robust genomic analysis by isDDH and ANI were at least 81.3% and 97.8%, respectively, defining Aer593 as A. caviae. Multilocus sequence typing (MLST) presented an exact match against only a single allele (groL96) and the novel ST648 was assigned for this strain. The core genome-based phylogenetic analyses with a total of 863 orthologous genes also grouped the Aer593 isolate with A. caviae reference strains. These findings warn about the possibility of misidentification of some Aeromonas strains by MLPA and show that high-resolution genome-wide analysis is essential for the correct identification of ambiguous Aeromonas strains.

Genome sequencing reveals coinfection by multiple chikungunya virus genotypes in a recent outbreak in Brazil.

Chikungunya virus (CHIKV) is an RNA virus from the Togaviridae family transmitted by mosquitoes in both sylvatic and urban cycles. In humans, CHIKV infection leads to a febrile illness, denominated Chikungunya fever (CHIKF), commonly associated with more intense and debilitating outcomes. CHIKV arrived in Brazil in 2014 through two independent introductions: the Asian/Caribbean genotype entered through the North region and the African ECSA genotype was imported through the Northeast region. Following their initial introduction, both genotypes established their urban cycle among large naive human populations causing several outbreaks in the Americas. Here, we sequenced CHIKV genomes from a recent outbreak in the Northeast region of Brazil, employing an in-house developed Next-Generation Sequencing (NGS) protocol capable of directly detecting multiple known CHIKV genotypes from clinical positive samples. Our results demonstrate that both Asian/Caribbean and ECSA genotypes expanded their ranges, reaching cocirculation in the Northeast region of Brazil. In addition, our NGS data supports the findings of simultaneous infection by these two genotypes, suggesting that coinfection might be more common than previously thought in highly endemic areas. Future efforts to understand CHIKV epidemiology should thus take into consideration the possibility of coinfection by different genotypes in the human population.

Revisiting Key Entry Routes of Human Epidemic Arboviruses into the Mainland Americas through Large-Scale Phylogenomics.

The rapid worldwide spread of chikungunya (CHIKV), dengue (DENV), and Zika (ZIKV) viruses have raised great international concern. Knowledge about the entry routes and geographic expansion of these arboviruses to the mainland Americas remain incomplete and controversial. Epidemics caused by arboviruses continue to cause socioeconomic burden globally, particularly in countries where vector control is difficult due to climatic or infrastructure factors. Understanding how the virus circulates and moves from one country to another is of paramount importance to assist government and health officials in anticipating future epidemics, as well as to take steps to help control or mitigate the spread of the virus. Through the analyses of the sequences of arbovirus genomes collected at different locations over time, we identified patterns of accumulated mutations, being able to trace routes of dispersion of these viruses. Here, we applied robust phylogenomic methods to trace the evolutionary dynamics of these arboviruses with special focus on Brazil, the epicenter of these triple epidemics. Our results show that CHIKV, DENV-1-4, and ZIKV followed a similar path prior to their first introductions into the mainland Americas, underscoring the need for systematic arboviral surveillance at major entry points of human population movement between countries such as airports and seaports.

HTT-DB: new features and updates.

Horizontal Transfer (HT) of genetic material between species is a common phenomenon among Bacteria and Archaea species and several databases are available for information retrieval and data mining. However, little attention has been given to this phenomenon among eukaryotic species mainly due to the lower proportion of these events. In the last years, a vertiginous amount of new HT events involving eukaryotic species was reported in the literature, highlighting the need of a common repository to keep the scientific community up to date and describe overall trends. Recently, we published the first HT database focused on HT of transposable elements among eukaryotes: the Horizontal Transposon Transfer DataBase (http://lpa.saogabriel.unipampa.edu.br: 8080/httdatabase/). Here, we present new features and updates of this unique database: (i) its expansion to include virus-host exchange of genetic material, which we called Horizontal Virus Transfer (HVT) and (ii) the availability of a web server for HT detection, where we implemented the online version of vertical and horizontal inheritance consistence analysis (VHICA), an R package developed for HT detection. These improvements will help researchers to navigate through known HVT cases, take data-informed decision and export figures based on keywords searches. Moreover, the availability of the VHICA as an online tool will make this software easily reachable even for researchers with no or little computation knowledge as well as foster our capability to detect new HT events in a wide variety of taxa. (Database URL: http://lpa.saogabriel.unipampa.edu.br:8080/httdatabase/).