SARS-CoV-2 reinfections with BA.1 (Omicron) variant among fully vaccinated individuals in northeastern Brazil.

BACKGROUND: The first case of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection in Rio Grande do Norte, northeastern Brazil, was diagnosed on March 12, 2020; thereafter, multiple surges of infection occurred, similar to what was seen elsewhere. These surges were mostly due to SARS-CoV-2 mutations leading to emergence of variants of concern (VoC). The introduction of new VoCs in a population previously exposed to SARS-CoV-2 or after vaccination has been a challenge to understanding the kinetics of the protective immune response against this virus. The aim of this study was to investigate the outbreak of SARS-CoV-2 reinfections observed in mid-January 2022 in Rio Grande do Norte state, Brazil. It describes the clinical and genomic characteristics of nine cases of reinfection that occurred coincident with the introduction of the omicron variant. METHODOLOGY/PRINCIPAL FINDINGS: Of a total of 172,965 individuals with upper respiratory symptoms tested for SARS-CoV-2, between March 2020 through mid-February 2022, 58,097 tested positive. Of those, 444 had documented a second SARS-CoV-2 infection and nine reinfection cases were selected for sequencing. Genomic analysis revealed that virus lineages diverged between primary infections and the reinfections, with the latter caused by the Omicron (BA.1) variant among individuals fully vaccinated against SARS-CoV-2. CONCLUSIONS/SIGNIFICANCE: Our findings suggest that the Omicron variant is able to evade both natural and vaccine-induced immunity, since all nine cases had prior natural infection and, in addition, were fully vaccinated, emphasizing the need to develop effective blocking vaccines.

Improved reverse transcription-polymerase chain reaction assay for the detection of flaviviruses with semi-nested primers for discrimination between dengue virus serotypes and Zika virus.

BACKGROUND The genus Flavivirus includes a variety of medically important viruses, including dengue virus (DENV) and Zika virus (ZIKV), which are most prevalent in Brazil. Because the clinical profile of patients affected by different DENV serotypes or ZIKV may be similar, the development of new methods that facilitate a rapid and accurate diagnosis is crucial. OBJECTIVES The current study aimed to develop an improved reverse transcription-polymerase chain reaction (RT-PCR) protocol for universal detection of flaviviruses by using semi-nested primers that discriminate between DENV serotypes and ZIKV. METHODS The bioinformatics workflow adopted for primer design included: (1) alignment of 1,442 flavivirus genome sequences, (2) characterisation of 27 conserved regions, (3) generation of a primer set comprising 77 universal primers, and (4) selection of primer pairs with greatest coverage and specificity. Following primer design, the reaction was validated in vitro. The same approach was applied to the design of primers specific for DENV and ZIKV, using a species-specific sequence database. FINDINGS The new assay amplified an 800-806 nt variable region of the NS5 gene and allowed discrimination of virtually all flavivirus species using reference-sequence comparison. The 800-806 nt fragment was validated as a template for a semi-nested multiplex PCR using five additional primers for the detection of DENV and ZIKV. These primers were designed to generate amplicons of different sizes, allowing differentiation of the four serotypes of DENV, and ZIKV using agarose gel electrophoresis. MAIN CONCLUSIONS The bioinformatics pipeline allowed efficient primer design, making it possible to identify the best targets within the coding region of the NS5 protein. The multiplex system proved effective in differentiation of DENV1-4 and ZIKV on a 2% agarose gel. The possibility of discriminating DENV serotypes and ZIKV in the same reaction provided a faster result consuming less sample. In addition, this simplified approach ensured the reduction of the cost per analysis.

Improved reverse transcription-polymerase chain reaction assay for the detection of flaviviruses with semi-nested primers for discrimination between dengue virus serotypes and Zika virus

BACKGROUND The genus Flavivirus includes a variety of medically important viruses, including dengue virus (DENV) and Zika virus (ZIKV), which are most prevalent in Brazil. Because the clinical profile of patients affected by different DENV serotypes or ZIKV may be similar, the development of new methods that facilitate a rapid and accurate diagnosis is crucial. OBJECTIVES The current study aimed to develop an improved reverse transcription-polymerase chain reaction (RT-PCR) protocol for universal detection of flaviviruses by using semi-nested primers that discriminate between DENV serotypes and ZIKV. METHODS The bioinformatics workflow adopted for primer design included: (1) alignment of 1,442 flavivirus genome sequences, (2) characterisation of 27 conserved regions, (3) generation of a primer set comprising 77 universal primers, and (4) selection of primer pairs with greatest coverage and specificity. Following primer design, the reaction was validated in vitro. The same approach was applied to the design of primers specific for DENV and ZIKV, using a species-specific sequence database. FINDINGS The new assay amplified an 800-806 nt variable region of the NS5 gene and allowed discrimination of virtually all flavivirus species using reference-sequence comparison. The 800-806 nt fragment was validated as a template for a semi-nested multiplex PCR using five additional primers for the detection of DENV and ZIKV. These primers were designed to generate amplicons of different sizes, allowing differentiation of the four serotypes of DENV, and ZIKV using agarose gel electrophoresis. MAIN CONCLUSIONS The bioinformatics pipeline allowed efficient primer design, making it possible to identify the best targets within the coding region of the NS5 protein. The multiplex system proved effective in differentiation of DENV1-4 and ZIKV on a 2% agarose gel. The possibility of discriminating DENV serotypes and ZIKV in the same reaction provided a faster result consuming less sample. In addition, this simplified approach ensured the reduction of the cost per analysis.