Background/Objectives: Human cytomegalovirus (HCMV) DNAemia remains a significant concern for transplant recipients, largely due to mutations in the viral genome that may lead to antiviral-resistant strains. Mutations in the UL97 gene are frequently associated with resistance to ganciclovir (GCV), highlighting the importance of early mutation detection to effectively manage viremia. This study aimed to optimize a Sanger sequencing protocol for analyzing GCV resistance-linked mutations in the HCMV UL97 gene from plasma samples of transplant patients treated at Hospital de Clínicas de Porto Alegre, Rio Grande do Sul, Brazil. Methods: A nested-PCR approach combined with a touchdown PCR method was employed to enhance the sensitivity and specificity of the sequencing analysis. Results: The study sample included various transplants, encompassing solid organ and bone marrow recipients. Among 16 sequenced samples, 8 exhibited nucleotide substitutions resulting in amino acid changes. Notably, the A594V and C603W mutations, associated with GCV resistance, were identified in four samples. Additionally, three mutations with unknown phenotypic impact (P509L, A628T, and H662Y) and two viral polymorphisms (N510S and D605E) were detected. Furthermore, double peaks in the Sanger electropherograms, indicative of mixed viral populations of HCMV were observed in seven samples. Conclusions: The optimized Sanger sequencing protocol provides a cost-effective solution for detecting GCV resistance mutations in HCMV UL97 among transplant recipients. This approach could improve the understanding of HCMV strain dynamics and serve as a valuable tool for long-term patient monitoring, particularly within resource-constrained settings such as the public health systems of middle-income countries.

The P1104A variant in the TYK2 gene is recognized as the first common monogenic cause of tuberculosis, and recent studies also suggest a potential role in COVID-19 severity. However, its frequency and impact in admixed Latin American populations remain underexplored. Therefore, we investigated the P1104A/TYK2 variant in a cohort comprising 1826 RT-PCR-confirmed COVID-19 patients from Southern Brazil. Cases were stratified by severity into non-severe (n = 1190) and severe (n = 636). Three homozygous individuals were identified—one non-severe and two severe cases—although no statistically significant association with disease severity was observed. The frequency of the C allele in the COVID-19 cohort (2.85%) was significantly higher than in Brazilian population databases, including “DNA do Brasil” (1.81%, p < 0.001) and ABraOM (2.34%, p = 0.03), but lower than in the multi-ancestry gnomAD database (3.71%, p = 0.01), possibly reflecting ancestry bias. We also observed associations between COVID-19 severity and sex (p = 0.003), age (p < 0.001), obesity (p < 0.001), diabetes (p < 0.001), and hypertension (p < 0.001). Future studies in larger and more diverse cohorts are needed to characterize the prevalence of the variant in admixed populations and assess its contribution to COVID-19 susceptibility.

Acute myeloid leukemia (AML) is a heterogeneous hematologic malignancy. AML classification is currently based on cytogenetic and molecular alterations as well as immunophenotyping, although risk stratification still relies primarily on cytogenetic findings. However, approximately 45% of AML patients present with a normal karyotype, which makes accurate risk classification and treatment stratification more challenging. Therefore, the identification of molecular prognostic markers described in the literature has become essential in routine diagnostic laboratories, enabling the more precise categorization of patients into risk groups. In this study, we present a simple, rapid, step-by-step multiplex PCR protocol combined with capillary electrophoresis for the detection of two of the most prevalent molecular alterations in AML: nucleophosmin 1 (NPM1) mutations and Fms-like tyrosine kinase 3 internal tandem duplications (FLT3/ITD). This protocol provides a practical workflow that can assist diagnostic laboratories in implementing and optimizing multiplex mutation detection in routine practice.