An Efficient Extraction Method Allowing the Genetic Evaluation of Host DNA from Samples Collected for Virus Infection Diagnosis in Viral Transport Medium.

Introduction: During the COVID-19 pandemic, an extraordinary number of nasopharyngeal secretion samples inoculated in viral transport medium (VTM) were collected and analyzed to detect SARS-CoV-2 infection. In addition to viral detection, those samples can also be a source of host genomic material, providing excellent opportunities for biobanking and research. Objective: To describe a simple, in-house-developed DNA extraction method to obtain high yield and quality genomic DNA from VTM samples for host genetic analysis and assess its relative efficiency by comparing its yield and suitability to downstream applications to two different commercial DNA extraction kits. Methods: In this study, 13 VTM samples were processed by two commercial silica-based kits and compared with an in-House-developed protocol for host DNA extraction. An additional 452 samples were processed by the in-House method. The quantity and quality of the differentially extracted DNA samples were assessed by Qubit and spectrophotometric measurements. The suitability of extracted samples for downstream applications was tested by polymerase chain reaction (PCR) amplification followed by amplicon sequencing and allelic discrimination in real-time PCR. Results: The in-House method provided greater median DNA yield (0.81 µg), being significantly different from the PureLink® method (0.14 µg, p < 0.001), but not from the QIAamp® method (0.47 µg, p = 0.980). Overall satisfactory results in DNA concentrations and purity, in addition to cost, were observed using the in-House method, whose samples were able to produce clear amplification in PCR and sequencing reads, as well as effective allelic discrimination in real-time PCR TaqMan® assay. Conclusion: The described in-House method proved to be suitable and economically viable for genomic DNA extraction from VTM samples for biobanking purposes. These results are extremely valuable for the study of the COVID-19 pandemic and other emergent infectious diseases, allowing host genetic studies to be performed in samples initially collected for diagnosis.

Investigation of the impact of AXL, TLR3, and STAT2 in congenital Zika syndrome through genetic polymorphisms and protein-protein interaction network analyses.

INTRODUCTION: Zika virus (ZIKV) is a human teratogen that causes congenital Zika syndrome (CZS). AXL, TLR3, and STAT2 are proteins involved in the ZIKV's entry into cells (AXL) and host's immune response (TLR3 and STAT2). In this study, we evaluated the role of genetic polymorphisms in these three genes as risk factors to CZS, and highlighted which proteins that interact with them could be important for ZIKV infection and teratogenesis. MATERIALS AND METHODS: We evaluate eighty-eight children exposed to ZIKV during the pregnancy, 40 with CZS and 48 without congenital anomalies. The evaluated polymorphisms in AXL (rs1051008), TLR3 (rs3775291), and STAT2 (rs2066811) were genotyped using TaqMan® Genotyping Assays. A protein-protein interaction network was created in STRING database and analyzed in Cytoscape software. RESULTS: We did not find any statistical significant association among the polymorphisms and the occurrence of CZS. Through the analyses of the network composed by AXL, TLR3, STAT2 and their interactions targets, we found that EGFR and SRC could be important proteins for the ZIKV infection and its teratogenesis. CONCLUSION: In summary, our results demonstrated that the evaluated polymorphisms do not seem to represent risk factors for CZS; however, EGFR and SRC appear to be important proteins that should be investigated in future studies.

Downregulation of Microcephaly-Causing Genes as a Mechanism for ZIKV Teratogenesis: A Meta-analysis of RNA-Seq Studies.

Zika virus (ZIKV) is a neurotropic teratogen that causes congenital Zika syndrome (CZS), characterized by brain and eye anomalies. Impaired gene expression in neural cells after ZIKV infection has been demonstrated; however, there is a gap in the literature of studies comparing whether the differentially expressed genes in such cells are similar and how it can cause CZS. Therefore, the aim of this study was to compare the differential gene expression (DGE) after ZIKV infection in neural cells through a meta-analysis approach. Through the GEO database, studies that evaluated DGE in cells exposed to the Asian lineage of ZIKV versus cells, of the same type, not exposed were searched. From the 119 studies found, five meet our inclusion criteria. Raw data of them were retrieved, pre-processed, and evaluated. The meta-analysis was carried out by comparing seven datasets, from these five studies. We found 125 upregulated genes in neural cells, mainly interferon-stimulated genes, such as IFI6, ISG15, and OAS2, involved in the antiviral response. Furthermore, 167 downregulated, involved with cellular division. Among these downregulated genes, classic microcephaly-causing genes stood out, such as CENPJ, ASPM, CENPE, and CEP152, demonstrating a possible mechanism by which ZIKV impairs brain development and causes CZS.

Search for DQ2 5 and DQ8 alleles using a lower cost technique in patients with type 1 diabetes and celiac disease in a population of southern Brazil

ABSTRACT Objective To evaluate the frequency of DQ2.5 and DQ8 alleles using the Tag-single-nucleotide polymorphism (Tag-SNP) technique in individuals with type 1 diabetes mellitus (T1DM) and celiac disease (CD) in southern Brazil. Materials and methods In a prospective design, we performed the search for DQA1*0501 and DQB1*0201 alleles for DQ2.5 and DQB1*0302 for DQ8 through Real-Time Polymerase Chain Reaction (RT-PCR) technique, using TaqMan Genotyping Assays (Applied Biosystems, USA). The diagnosis of CD was established by duodenal biopsy and genotypic determination performed by StepOne Software v2.3. Allelic and genotypic frequencies were compared between groups using Chi-square and Fisher's exact tests and the multiple comparisons using Finner's adjustment. Results Three hundred and sixty two patients with a median age of 14 years were divided into 3 groups: T1DM without CD (264); T1DM with CD (32) and CD without T1DM (66). In 97% of individuals with T1DM and CD and 76% of individuals with CD without T1DM, respectively, the alleles DQ2.5 and/or DQ8 were identified (p < 0.001). DQ2.5 was more common in individuals with CD (p = 0.004) and DQ8 was more common in individuals with type 1 diabetes (p = 0.008). Conclusions The evaluation of the alleles for DQ2.5 and DQ8 by Tag-SNP technique showed a high negative predictive value among those with T1DM, similar to that described by the conventional technique. The high frequency of DQ8 alleles in individuals with T1DM did not allow differentiating those at higher risk of developing T1DM.

Search for DQ2.5 and DQ8 alleles using a lower cost technique in patients with type 1 diabetes and celiac disease in a population of southern Brazil.

OBJECTIVE: To evaluate the frequency of DQ2.5 and DQ8 alleles using the Tag-single-nucleotide polymorphism (Tag-SNP) technique in individuals with type 1 diabetes mellitus (T1DM) and celiac disease (CD) in southern Brazil. MATERIALS AND METHODS: In a prospective design, we performed the search for DQA1*0501 and DQB1*0201 alleles for DQ2.5 and DQB1*0302 for DQ8 through Real-Time Polymerase Chain Reaction (RT-PCR) technique, using TaqMan Genotyping Assays (Applied Biosystems, USA). The diagnosis of CD was established by duodenal biopsy and genotypic determination performed by StepOne Software v2.3. Allelic and genotypic frequencies were compared between groups using Chi-square and Fisher's exact tests and the multiple comparisons using Finner's adjustment. RESULTS: Three hundred and sixty two patients with a median age of 14 years were divided into 3 groups: T1DM without CD (264); T1DM with CD (32) and CD without T1DM (66). In 97% of individuals with T1DM and CD and 76% of individuals with CD without T1DM, respectively, the alleles DQ2.5 and/or DQ8 were identified (p < 0.001). DQ2.5 was more common in individuals with CD (p = 0.004) and DQ8 was more common in individuals with type 1 diabetes (p = 0.008). CONCLUSIONS: The evaluation of the alleles for DQ2.5 and DQ8 by Tag-SNP technique showed a high negative predictive value among those with T1DM, similar to that described by the conventional technique. The high frequency of DQ8 alleles in individuals with T1DM did not allow differentiating those at higher risk of developing T1DM.