Diversity, composition, and networking of saliva microbiota distinguish the severity of COVID-19 episodes as revealed by an analysis of 16S rRNA variable V1-V3 region sequences.

Studies on the role of the oral microbiome in SARS-CoV-2 infection and severity of the disease are limited. We aimed to characterize the bacterial communities present in the saliva of patients with varied COVID-19 severity to learn if there are differences in the characteristics of the microbiome among the clinical groups. We included 31 asymptomatic subjects with no previous COVID-19 infection or vaccination; 176 patients with mild respiratory symptoms, positive or negative for SARS-CoV-2 infection; 57 patients that required hospitalization because of severe COVID-19 with oxygen saturation below 92%, and 18 fatal cases of COVID-19. Saliva samples collected before any treatment were tested for SARS-CoV-2 by PCR. Oral microbiota in saliva was studied by amplification and sequencing of the V1-V3 variable regions of 16S gene using an Illumina MiSeq platform. We found significant changes in diversity, composition, and networking in saliva microbiota of patients with COVID-19, as well as patterns associated with severity of disease. The presence or abundance of several commensal species and opportunistic pathogens were associated with each clinical stage. Patterns of networking were also found associated with severity of disease: a highly regulated bacterial community (normonetting) was found in healthy people whereas poorly regulated populations (disnetting) were characteristic of severe cases. Characterization of microbiota in saliva may offer important clues in the pathogenesis of COVID-19 and may also identify potential markers for prognosis in the severity of the disease. IMPORTANCE SARS-CoV-2 infection is the most severe pandemic of humankind in the last hundred years. The outcome of the infection ranges from asymptomatic or mild to severe and even fatal cases, but reasons for this remain unknown. Microbes normally colonizing the respiratory tract form communities that may mitigate the transmission, symptoms, and severity of viral infections, but very little is known on the role of these microbial communities in the severity of COVID-19. We aimed to characterize the bacterial communities in saliva of patients with different severity of COVID-19 disease, from mild to fatal cases. Our results revealed clear differences in the composition and in the nature of interactions (networking) of the bacterial species present in the different clinical groups and show community-patterns associated with disease severity. Characterization of the microbial communities in saliva may offer important clues to learn ways COVID-19 patients may suffer from different disease severities.

Dominance of Three Sublineages of the SARS-CoV-2 Delta Variant in Mexico.

In this study, we analyzed the sequences of SARS-CoV-2 isolates of the Delta variant in Mexico, which has completely replaced other previously circulating variants in the country due to its transmission advantage. Among all the Delta sublineages that were detected, 81.5 % were classified as AY.20, AY.26, and AY.100. According to publicly available data, these only reached a world prevalence of less than 1%, suggesting a possible Mexican origin. The signature mutations of these sublineages are described herein, and phylogenetic analyses and haplotype networks are used to track their spread across the country. Other frequently detected sublineages include AY.3, AY.62, AY.103, and AY.113. Over time, the main sublineages showed different geographical distributions, with AY.20 predominant in Central Mexico, AY.26 in the North, and AY.100 in the Northwest and South/Southeast. This work describes the circulation, from May to November 2021, of the primary sublineages of the Delta variant associated with the third wave of the COVID-19 pandemic in Mexico and highlights the importance of SARS-CoV-2 genomic surveillance for the timely identification of emerging variants that may impact public health.

[Coinfections by SARS-CoV-2 and other respiratory viruses and their clinical outcome]. / Coinfecciones por SARS-CoV-2 y otros virus respiratorios y su desenlace clínico.

Background: SARS-CoV-2 is a coronavirus described for the first time in China, in December 2019. This virus can cause a disease with a very variable spectrum that ranges from asymptomatic cases to deaths. The most severe cases are normally associated with comorbidities and with the age of the patient. However, there are patients who are not part of these risk groups and develop severe cases. Objetive: To determine the association between coinfections by SARS-CoV-2 and other respiratory viruses and their clincal outcome. Material and methods: RT-qPCR was performed to determine the presence of 16 respiratory viruses in 103 confirmed COVID-19 cases. Demographic and comorbid data were collected, and statistical analyzes were performed to determine associations with severity. Results: Of the 103 analyzed cases, 14 (13.6%) presented a coinfection, of these, 92% did not require hospitalization, even in those cases in which the patient presented advanced age and some comorbidities. Conclusions: These results suggest that coinfection of SARS-CoV-2 and other respiratory viruses is not related to a more severe form of COVID-19 and, in some cases, depending on the virus involved, it could even lead to a better prognosis. These findings lay the foundations for the development of new studies that could determine the biological mechanism of this phenomenon.

Introducción: el SARS-CoV-2 es un coronavirus que fue descrito por primera vez en diciembre de 2019 en Wuhan, China. Este virus causa una enfermedad que varía en un espectro de severidad que va desde casos asintomáticos hasta defunciones. Los casos más severos se asocian normalmente con algunas comorbilidades y con la edad del paciente. Sin embargo, existen pacientes que no son parte de estos grupos de riesgo y aun así desarrollan casos graves. Objetivo: determinar la asociación entre las coinfecciones por SARS-CoV-2 y otros virus respiratorios y su desenlace clínico. Material y métodos: se realizó RT-qPCR para determinar la presencia de 16 virus respiratorios en 103 casos confirmados de COVID-19. Se recolectaron datos demográficos y de comorbilidades, y se realizaron análisis estadísticos para determinar asociaciones con gravedad. Resultados: el 13.6% de los casos (14/103) presentaron alguna coinfección, de estos, el 92% nunca requirió ingreso hospitalario, aun en aquellos casos en los que el paciente presentara comorbilidades y edad avanzada. Conclusiones: estos resultados sugieren que la coinfección no está relacionada con un COVID-19 más grave y que, dependiendo del virus involucrado, incluso podría conducir a un mejor pronóstico. Estos hallazgos sientan las bases para nuevos estudios dirigidos a determinar el mecanismo biológico por el cual ocurre este fenómeno y a proponer las estrategias correspondientes para limitar la progresión a casos severos de COVID-19.

Differential Detection of Enterovirus and Herpes Simplex Virus in Cerebrospinal Fluid by Real-Time RT-PCR.

BACKGROUND: Enterovirus (EV) and herpes simplex virus 1 and 2 (HSV1 and HSV2) are the main etiologic agents of central nervous system infections. Early laboratory confirmation of these infections is performed by viral culture of the cerebrospinal fluid (CSF), or the detection of specific antibodies in serum (e.g., HSV). The sensitivity of viral culture ranges from 65 to 75%, with a recovery time varying from 3 to 10 days. Serological tests are faster and easy to carry out, but they exhibit cross-reactivity between HSV1 and HSV2. Although molecular techniques are more sensitive (sensitivity >95%), they are more expensive and highly susceptible to cross-contamination. METHODS: A real-time RT-PCR for the detection of EV, HSV1, and HSV2 was compared with end-point nested PCR. RESULTS: We tested 87 CSF samples of patients with a clinical diagnosis of viral meningitis or encephalitis. Fourteen samples were found to be positive by RT-PCR, but only 8 were positive by end-point PCR. The RT-PCR showed a specificity range of 94-100%, the negative predictive value was 100%, and the positive predictive value was 62, 100, and 28% for HSV1, HSV2, and EV, respectively. CONCLUSION: Real-time RT-PCR detected EV, HSV1, and HSV2 with a higher sensitivity and specificity than end-point nested RT-PCR.

Prevalence of non-influenza respiratory viruses in acute respiratory infection cases in Mexico.

BACKGROUND: Acute respiratory infections are the leading cause of morbidity and mortality worldwide. Although a viral aetiological agent is estimated to be involved in up to 80% of cases, the majority of these agents have never been specifically identified. Since 2009, diagnostic and surveillance efforts for influenza virus have been applied worldwide. However, insufficient epidemiological information is available for the many other respiratory viruses that can cause Acute respiratory infections. METHODS: This study evaluated the presence of 14 non-influenza respiratory viruses in 872 pharyngeal exudate samples using RT-qPCR. All samples met the operational definition of a probable case of an influenza-like illness or severe acute respiratory infection and had a previous negative result for influenza by RT-qPCR. RESULTS: The presence of at least one non-influenza virus was observed in 312 samples (35.8%). The most frequent viruses were rhinovirus (RV; 33.0%), human respiratory syncytial virus (HRSV; 30.8%) and human metapneumovirus (HMPV; 10.6%). A total of 56 cases of co-infection (17.9%) caused by 2, 3, or 4 viruses were identified. Approximately 62.5% of all positive cases were in children under 9 years of age. CONCLUSION: In this study, we identified 13 non-influenza respiratory viruses that could occur in any season of the year. This study provides evidence for the prevalence and seasonality of a wide range of respiratory viruses that circulate in Mexico and constitute a risk for the population. Additionally, our data suggest that including these tests more widely in the diagnostic algorithm for influenza may reduce the use of unnecessary antibiotics, reduce the hospitalisation time, and enrich national epidemiological data with respect to the infections caused by these viruses.