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.

Background. Cystic echinococcosis (CE) is a chronic, clinically complex, and neglected disease. Its prevalence in Italy, a country of medium to high endemicity, remains poorly defined, as notification has long ceased to be mandatory. Methods. We set up a retrospective cohort study involving all CE patients followed at our institute between January 2005 and December 2012. Demographical and clinical features were recorded and analyzed. Results. CE was found in 28 patients (64.3%), mostly Italians from the central regions (50%), followed by subjects from the islands (33.3%) and Southern Italy (16.7%). Their median age was 45 years (IQR: 38.5–66.5), with Eastern Europeans being significantly younger (28 years, IQR: 19–39) than other patients (P ≤ 0.0001). A total of 149 cysts, mostly with hepatic localization (96%), were described. Based on the WHO classification, the cysts were mainly small (80.5%) and active (CE1 (73.8%); CE2 (7.4%)). Active cysts were more common in Eastern Europeans (85.7%) than Italians (66.7%). Conclusion. Our data confirm CE occurrence in Italy. We emphasize the importance to have a national CE registry, opportunely recently introduced. This is essential to assess CE prevalence in this country, implement appropriate control measures, and improve patient management.

Anisakiasis is nowadays a well-known infection, mainly caused by the accidental ingestion of Anisakis larvae, following the consumption of raw or undercooked fishes and cephalopods. Due to the similarity of symptoms with those of common gastrointestinal disorders, this infection is often underestimated, and the need for new specific diagnostic tools is becoming crucial. Given the remarkable impact that MALDI–TOF MS biotyping had in the last decade in clinical routine practice for the recognition of bacterial and fungi strains, a similar scenario could be foreseen for the identification of parasites, such as nematodes. In this work, a MALDI–TOF MS profiling of Anisakis proteome was pursued with a view to constructing a first spectral library for the diagnosis of Anisakis infections. At the same time, a shotgun proteomics approach by LC–ESI–MS/MS was performed on the two main fractions obtained from protein extraction, to evaluate the protein species enriched by the protocol. A set of MALDI–TOF MS signals associated with proteins originating in the ribosomal fraction of the nematode extract was selected as a potential diagnostic tool for the identification of Anisakis spp.

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