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This is the first study on gut microbiota (GM) in children affected by coronavirus disease 2019 (COVID-19). Stool samples from 88 patients with suspected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and 95 healthy subjects were collected (admission: 3–7 days, discharge) to study GM profile by 16S rRNA gene sequencing and relationship to disease severity. The study group was divided in COVID-19 (68), Non–COVID-19 (16), and MIS-C (multisystem inflammatory syndrome in children) (4). Correlations among GM ecology, predicted functions, multiple machine learning (ML) models, and inflammatory response were provided for COVID-19 and Non–COVID-19 cohorts. The GM of COVID-19 cohort resulted as dysbiotic, with the lowest α-diversity compared with Non–COVID-19 and CTRLs and by a specific β-diversity. Its profile appeared enriched in Faecalibacterium, Fusobacterium, and Neisseria and reduced in Bifidobacterium, Blautia, Ruminococcus, Collinsella, Coprococcus, Eggerthella, and Akkermansia, compared with CTRLs (p < 0.05). All GM paired-comparisons disclosed comparable results through all time points. The comparison between COVID-19 and Non–COVID-19 cohorts highlighted a reduction of Abiotrophia in the COVID-19 cohort (p < 0.05). The GM of MIS-C cohort was characterized by an increase of Veillonella, Clostridium, Dialister, Ruminococcus, and Streptococcus and a decrease of Bifidobacterium, Blautia, Granulicatella, and Prevotella, compared with CTRLs. Stratifying for disease severity, the GM associated to “moderate” COVID-19 was characterized by lower α-diversity compared with “mild” and “asymptomatic” and by a GM profile deprived in Neisseria, Lachnospira, Streptococcus, and Prevotella and enriched in Dialister, Acidaminococcus, Oscillospora, Ruminococcus, Clostridium, Alistipes, and Bacteroides. The ML models identified Staphylococcus, Anaerostipes, Faecalibacterium, Dorea, Dialister, Streptococcus, Roseburia, Haemophilus, Granulicatella, Gemmiger, Lachnospira, Corynebacterium, Prevotella, Bilophila, Phascolarctobacterium, Oscillospira, and Veillonella as microbial markers of COVID-19. The KEGG ortholog (KO)–based prediction of GM functional profile highlighted 28 and 39 KO-associated pathways to COVID-19 and CTRLs, respectively. Finally, Bacteroides and Sutterella correlated with proinflammatory cytokines regardless disease severity. Unlike adult GM profiles, Faecalibacterium was a specific marker of pediatric COVID-19 GM. The durable modification of patients’ GM profile suggested a prompt GM quenching response to SARS-CoV-2 infection since the first symptoms. Faecalibacterium and reduced fatty acid and amino acid degradation were proposed as specific COVID-19 disease traits, possibly associated to restrained severity of SARS-CoV-2–infected children. Altogether, this evidence provides a characterization of the pediatric COVID-19–related GM.

The dynamics of human immunodeficiency virus type 1 (HIV-1) transcription was analyzed in vitro and in vivo by using a specific molecular approach which allows accurate quantitation of the different classes of viral mRNAs. Unspliced (US) and multiply spliced (MS) HIV-1 transcripts were assayed by competitive reverse transcription (cRT)-PCR, using a single competitor RNA bearing in tandem internally deleted sequences of both template species. Acute HIV-1 infection of primary peripheral blood mononuclear cells (PBMCs), monocytes/macrophages cells, and the A3.01 T-lymphocyte-derived cell line was studied; both classes of HIV-1 mRNAs increased exponentially (r 2 > 0.98) at days 1 to 3 and 1 to 4 postinfection in HIV IIIB -infected A3.01 cells and PBMCs, respectively, whereas monocytes/macrophages infected with monocytotropic HIV BaL exhibited a linear (r 2 ‫؍‬ 0.81 to 0.94) accumulation of US and MS transcripts. Following induction of chronically infected ACH-2 cells, MS transcripts increased 2 h postinduction and peaked at 5 h (doubling time, 58 min), while at 24 h, US mRNAs increased 3,053-fold compared with basal time (doubling time, 137 min). To address the biopathological significance of HIV-1 expression pattern during infection progression, pilot cross-sectional and longitudinal analyses were carried out with samples from untreated and treated HIV-1-infected patients. In almost all untreated (recently infected, long-term nonprogressor, and progressor) patients, MS transcript levels followed the general trend of systemic HIV-1 activity. In patients under treatment with powerful antiretroviral compounds, viral MS transcripts rapidly fell to undetectable levels, indicating that in vivo, levels of MS mRNAs in PBMCs are closely associated with the number of newly infected cells and suggesting a new role for the quantitative analysis of HIV-1 transcription in infected patients.

From February to April, 2020, Lombardy (Italy) was the area who worldwide registered the highest numbers of SARS-CoV-2 infection. By extensively analyzing 346 whole SARS-CoV-2 genomes, we demonstrated the simultaneous circulation in Lombardy of two major viral lineages, likely derived from multiple introductions, occurring since the second half of January. Seven single nucleotide polymorphisms (five of them non-synonymous) characterized the SARS-CoV-2 sequences, none of them affecting N-glycosylation sites. These two lineages, and the presence of two well defined clusters inside Lineage 1, revealed that a sustained community transmission was ongoing way before the first COVID-19 case found in Lombardy.