Tobacco use has been implicated as an immunomodulator in the oral cavity and contributes to the development of oral cancer. In the present study, we investigated the effects of cigarette smoking on bacterial diversity and host responses compared to healthy nonsmoking controls. Saliva samples were collected from eighteen smokers and sixteen nonsmoking individuals by passive drool. The 16S rRNA gene was used to characterize the salivary microbiome by using the Illumina MiSeq platform. Cytokine and chemokine expression analyses were performed to evaluate the host response. Significant differences in cytokine and chemokine expression levels of MDC, IL-10, IL-5, IL-2, IL-4, IL-7, adrenocorticotropic hormone (ACTH), insulin, and leptin were observed between smokers and nonsmokers. Taxonomic analyses revealed differences between the two groups, and some bacterial genera associated with the smokers group had correlations with hormones and cytokines identified as statistically different between smokers and nonsmokers. These factors have been associated with inflammation and carcinogenesis in the oral cavity. The data obtained may aid in the identification of the interactions between the salivary microbiome, host inflammatory responses, and metabolism in smokers.

The implementation of antiretroviral treatment combined with the monitoring of drug resistance mutations improves the quality of life of HIV-1 positive patients. The drug resistance mutation patterns and viral genotypes are currently analyzed by DNA sequencing of the virus in the plasma of patients. However, the virus compartmentalizes, and different T cell subsets may harbor distinct viral subsets. In this study, we compared the patterns of HIV distribution in cell-free (blood plasma) and cell-associated viruses (peripheral blood mononuclear cells, PBMCs) derived from ART-treated patients by using Sanger sequencing- and Next-Generation sequencing-based HIV assay. CD4⁺CD45RA⁻RO⁺ memory T-cells were isolated from PBMCs using a BD FACSAria instrument. HIV pol (protease and reverse transcriptase) was RT-PCR or PCR amplified from the plasma and the T-cell subset, respectively. Sequences were obtained using Sanger sequencing and Next-Generation Sequencing (NGS). Sanger sequences were aligned and edited using RECall software (beta v3.03). The Stanford HIV database was used to evaluate drug resistance mutations. Illumina MiSeq platform and HyDRA Web were used to generate and analyze NGS data, respectively. Our results show a high correlation between Sanger sequencing and NGS results. However, some major and minor drug resistance mutations were only observed by NGS, albeit at different frequencies. Analysis of low-frequency drugs resistance mutations and virus distribution in the blood compartments may provide information to allow a more sustainable response to therapy and better disease management.

Alcohol-related disorders (ARD) are highly prevalent among Latin American-Caribbean countries. Mental disorders are common comorbidities in individuals with ARD. However, the etiology of the association between ARD and mental disorders remains unclear. We examined the association of inflammatory cytokines, microbiome, and other biomakers with measures of depression, social anxiety, and executive functions. We observed a significant increase in cytokine and chemokine expression levels in saliva and plasma in the alcohol group (AG) samples. Also, the salivary bacterial composition in the AG revealed an abundance of Prevotella. Depression symptomatology was markedly higher in the AG, but social anxiety levels were negligible. AG also exhibited executive dysfunctions, which negatively correlated with increased plasma levels of pro-inflammatory cytokines and increased salivary concentrations of Prevotella bacteria. Our study suggests that chronic alcohol use correlates with executive dysfunction, immune system dysregulation, and dysbiosis of the salivary microbiota. Additional studies are needed to understand the role of the microbiome and inflammation in alcohol use and mental comorbidities.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an RNA virus that evolves over time, leading to new variants. In the current study, we assessed the genomic epidemiology of SARS-CoV-2 in the Dominican Republic. A total of 1149 SARS-CoV-2 complete genome nucleotide sequences from samples collected between March 2020 and mid-February 2022 in the Dominican Republic were obtained from the Global Initiative on Sharing All Influenza Data (GISAID) database. Phylogenetic relationships and evolution rates were analyzed using the maximum likelihood method and the Bayesian Markov chain Monte Carlo (MCMC) approach. The genotyping details (lineages) were obtained using the Pangolin web application. In addition, the web tools Coronapp, and Genome Detective Viral Tools, among others, were used to monitor epidemiological characteristics. Our results show that the most frequent non-synonymous mutation over the study period was D614G. Of the 1149 samples, 870 (75.74%) were classified into 8 relevant variants according to Pangolin/Scorpio. The first Variants Being Monitored (VBM) were detected in December 2020. Meanwhile, in 2021, the variants of concern Delta and Omicron were identified. The mean mutation rate was estimated to be 1.5523 × 10⁻³ (95% HPD: 1.2358 × 10⁻³, 1.8635 × 10⁻³) nucleotide substitutions per site. We also report the emergence of an autochthonous SARS-CoV-2 lineage, B.1.575.2, that circulated from October 2021 to January 2022, in co-circulation with the variants of concern Delta and Omicron. The impact of B.1.575.2 in the Dominican Republic was minimal, but it then expanded rapidly in Spain. A better understanding of viral evolution and genomic surveillance data will help to inform strategies to mitigate the impact on public health.

HIV-1 epidemics in Caribbean countries, including Puerto Rico, have been reported to be almost exclusively associated with the subtype B virus (HIV-1B). However, while HIV infections associated with other clades have been only sporadically reported, no organized data exist to accurately assess the prevalence of non-subtype B HIV-1 infection. We analyzed the nucleotide sequence data of the HIV pol gene associated with HIV isolates from Puerto Rican patients. The sequences (n = 945) were obtained from our “HIV Genotyping” test file, which has been generated over a period of 14 years (2001–2014). REGA subtyping tool found the following subtypes: B (90%), B-like (3%), B/D recombinant (6%), and D/B recombinant (0.6%). Though there were fewer cases, the following subtypes were also found (in the given proportions): A1B (0.3%), BF1 (0.2%), subtype A (01-AE) (0.1%), subtype A (A2) (0.1%), subtype F (12BF) (0.1%), CRF-39 BF-like (0.1%), and others (0.1%). Some of the recombinants were identified as early as 2001. Although the HIV epidemic in Puerto Rico is primarily associated with HIV-1B virus, our analysis uncovered the presence of other subtypes. There was no indication of subtype C, which has been predominantly associated with heterosexual transmission in other parts of the world.

The HIV-1 integrase viral protein is responsible for incorporating the viral DNA into the genomic DNA. The inhibition of viral integration into host cell DNA is part of recent therapeutic procedures. Combination therapy with protease and reverse transcriptase inhibitors has demonstrated good synergistic results in reducing viral replication. The purpose of this study is to assess the occurrence of integrase drug resistance mutations from the period comprising 2013 through 2018 in Puerto Rico (PR). We analyzed 131 nucleotide sequences available in our HIV genotyping database, and we performed drug resistance mutation analyses using the Stanford HIV Drug Resistance Database. Twenty-one sequences (16.03%) harbored major or resistance-associated mutations. We identified the Q148HKR, G140S, Y143R, N155H, S147G, and E138EA major drug resistance mutations and the D232DN, T97TA, E157Q, G163GART accessory mutations. We detected high-level drug resistance to Elvitegravir and Raltegravir (76.19% and 85.71%). Moreover, we identified sequences harboring drug resistance mutations that could provide resistance to Dolutegravir. The transmission of strains with integrase antiretroviral resistance has been previously documented in treatment naïve patients. Given the increase of patients treated with integrase inhibitors, surveillance of drug resistance mutations is an essential aspect of PR’s clinical management of HIV infection.