Zigui Chen

We present an expansion of the classification of the family Papillomaviridae, which now contains 29 genera formed by 189 papillomavirus (PV) types isolated from humans (120 types), non-human mammals, birds and reptiles (64, 3 and 2 types, respectively). To accommodate the number of PV genera exceeding the Greek alphabet, the prefix "dyo" is used, continuing after the Omega-PVs with Dyodelta-PVs. The current set of human PVs is contained within five genera, whereas mammalian, avian and reptile PVs are contained within 20, 3 and 1 genera, respectively. We propose standardizations to the names of a number of animal PVs. As prerequisite for a coherent nomenclature of animal PVs, we propose founding a reference center for animal PVs. We discuss that based on emerging species concepts derived from genome sequences, PV types could be promoted to the taxonomic level of species, but we do not recommend implementing this change at the current time.

Background & AimsAlthough severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infects gastrointestinal tissues, little is known about the roles of gut commensal microbes in susceptibility to and severity of infection. We investigated changes in fecal microbiomes of patients with SARS-CoV-2 infection during hospitalization and associations with severity and fecal shedding of virus.MethodsWe performed shotgun metagenomic sequencing analyses of fecal samples from 15 patients with Coronavirus Disease 2019 (COVID-19) in Hong Kong, from February 5 through March 17, 2020. Fecal samples were collected 2 or 3 times per week from time of hospitalization until discharge; disease was categorized as mild (no radiographic evidence of pneumonia), moderate (pneumonia was present), severe (respiratory rate ≥30/min, or oxygen saturation ≤93% when breathing ambient air), or critical (respiratory failure requiring mechanical ventilation, shock, or organ failure requiring intensive care). We compared microbiome data with those from 6 subjects with community-acquired pneumonia and 15 healthy individuals (controls). We assessed gut microbiome profiles in association with disease severity and changes in fecal shedding of SARS-CoV-2.ResultsPatients with COVID-19 had significant alterations in fecal microbiomes compared with controls, characterized by enrichment of opportunistic pathogens and depletion of beneficial commensals, at time of hospitalization and at all timepoints during hospitalization. Depleted symbionts and gut dysbiosis persisted even after clearance of SARS-CoV-2 (determined from throat swabs) and resolution of respiratory symptoms. The baseline abundance of Coprobacillus, Clostridium ramosum, and Clostridium hathewayi correlated with COVID-19 severity; there was an inverse correlation between abundance of Faecalibacterium prausnitzii (an anti-inflammatory bacterium) and disease severity. Over the course of hospitalization, Bacteroides dorei, Bacteroides thetaiotaomicron, Bacteroides massiliensis, and Bacteroides ovatus, which downregulate expression of angiotensin-converting enzyme 2 (ACE2) in murine gut, correlated inversely with SARS-CoV-2 load in fecal samples from patients.ConclusionsIn a pilot study of 15 patients with COVID-19, we found persistent alterations in the fecal microbiome during the time of hospitalization, compared with controls. Fecal microbiota alterations were associated with fecal levels of SARS-CoV-2 and COVID-19 severity. Strategies to alter the intestinal microbiota might reduce disease severity. Although severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infects gastrointestinal tissues, little is known about the roles of gut commensal microbes in susceptibility to and severity of infection. We investigated changes in fecal microbiomes of patients with SARS-CoV-2 infection during hospitalization and associations with severity and fecal shedding of virus. We performed shotgun metagenomic sequencing analyses of fecal samples from 15 patients with Coronavirus Disease 2019 (COVID-19) in Hong Kong, from February 5 through March 17, 2020. Fecal samples were collected 2 or 3 times per week from time of hospitalization until discharge; disease was categorized as mild (no radiographic evidence of pneumonia), moderate (pneumonia was present), severe (respiratory rate ≥30/min, or oxygen saturation ≤93% when breathing ambient air), or critical (respiratory failure requiring mechanical ventilation, shock, or organ failure requiring intensive care). We compared microbiome data with those from 6 subjects with community-acquired pneumonia and 15 healthy individuals (controls). We assessed gut microbiome profiles in association with disease severity and changes in fecal shedding of SARS-CoV-2. Patients with COVID-19 had significant alterations in fecal microbiomes compared with controls, characterized by enrichment of opportunistic pathogens and depletion of beneficial commensals, at time of hospitalization and at all timepoints during hospitalization. Depleted symbionts and gut dysbiosis persisted even after clearance of SARS-CoV-2 (determined from throat swabs) and resolution of respiratory symptoms. The baseline abundance of Coprobacillus, Clostridium ramosum, and Clostridium hathewayi correlated with COVID-19 severity; there was an inverse correlation between abundance of Faecalibacterium prausnitzii (an anti-inflammatory bacterium) and disease severity. Over the course of hospitalization, Bacteroides dorei, Bacteroides thetaiotaomicron, Bacteroides massiliensis, and Bacteroides ovatus, which downregulate expression of angiotensin-converting enzyme 2 (ACE2) in murine gut, correlated inversely with SARS-CoV-2 load in fecal samples from patients. In a pilot study of 15 patients with COVID-19, we found persistent alterations in the fecal microbiome during the time of hospitalization, compared with controls. Fecal microbiota alterations were associated with fecal levels of SARS-CoV-2 and COVID-19 severity. Strategies to alter the intestinal microbiota might reduce disease severity.

Objectives We aimed to characterise the microbial changes associated with histological stages of gastric tumourigenesis. Design We performed 16S rRNA gene analysis of gastric mucosal samples from 81 cases including superficial gastritis (SG), atrophic gastritis (AG), intestinal metaplasia (IM) and gastric cancer (GC) from Xi’an, China, to determine mucosal microbiome dysbiosis across stages of GC. We validated the results in mucosal samples of 126 cases from Inner Mongolia, China. Results We observed significant mucosa microbial dysbiosis in IM and GC subjects, with significant enrichment of 21 and depletion of 10 bacterial taxa in GC compared with SG (q<0.05). Microbial network analysis showed increasing correlation strengths among them with disease progression (p<0.001). Five GC-enriched bacterial taxa whose species identifications correspond to Peptostreptococcus stomatis , Streptococcus anginosus , Parvimonas micra , Slackia exigua and Dialister pneumosintes had significant centralities in the GC ecological network (p<0.05) and classified GC from SG with an area under the receiver-operating curve (AUC) of 0.82. Moreover, stronger interactions among gastric microbes were observed in Helicobacter pylori -negative samples compared with H. pylori -positive samples in SG and IM. The fold changes of selected bacteria, and strengths of their interactions were successfully validated in the Inner Mongolian cohort, in which the five bacterial markers distinguished GC from SG with an AUC of 0.81. Conclusions In addition to microbial compositional changes, we identified differences in bacterial interactions across stages of gastric carcinogenesis. The significant enrichments and network centralities suggest potentially important roles of P. stomatis , D. pneumosintes , S. exigua , P. micra and S. anginosus in GC progression.

BACKGROUND: Vaccines for COVID-19 are anticipated to be available by 2021. Vaccine uptake rate is a crucial determinant for herd immunity. We examined factors associated with acceptance of vaccine based on (1). constructs of the Health Belief Model (HBM), (2). trust in the healthcare system, new vaccine platforms and manufacturers, and (3). self-reported health outcomes. METHODS: A population-based, random telephone survey was performed during the peak of the third wave of COVID-19 outbreak (27/07/2020 to 27/08/2020) in Hong Kong. All adults aged ≥ 18 years were eligible. The survey included sociodemographic details; self-report health conditions; trust scales; and self-reported health outcomes. Multivariable regression analyses were applied to examine independent associations. The primary outcome is the acceptance of the COVID-19 vaccine. RESULTS: We conducted 1200 successful telephone interviews (response rate 55%). The overall vaccine acceptance rate after adjustment for population distribution was 37.2% (95% C.I. 34.5-39.9%). The projected acceptance rates exhibited a "J-shaped" pattern with age, with higher rates among young adults (18-24 years), then increased linearly with age. Multivariable regression analyses revealed that perceived severity, perceived benefits of the vaccine, cues to action, self-reported health outcomes, and trust in healthcare system or vaccine manufacturers were positive correlates of acceptance; whilst perceived access barriers and harm were negative correlates. Remarkably, perceived susceptibility to infection carried no significant association, whereas recommendation from Government (aOR = 10.2, 95% C.I. 6.54 to 15.9, p < 0.001) was as the strongest driving factor for acceptance. Other key obstacles of acceptance included lack of confidence on newer vaccine platforms (43.4%) and manufacturers without track record (52.2%), which are of particular relevance to the current context. CONCLUSIONS: Governmental recommendation is an important driver, whereas perceived susceptibility is not associated with acceptance of COVID-19 vaccine. These HBM constructs and independent predictors inform evidence-based formulation and implementation of vaccination strategies.

Alterations of gut microbiota are associated with colorectal cancer (CRC) in different populations and several bacterial species were found to contribute to the tumorigenesis. The potential use of gut microbes as markers for early diagnosis has also been reported. However, cohort specific noises may distort the structure of microbial dysbiosis in CRC and lead to inconsistent results among studies. In this regard, our study targeted at exploring changes in gut microbiota that are universal across populations at species level. Based on the combined analysis of 526 metagenomic samples from Chinese, Austrian, American, and German and French cohorts, seven CRC-enriched bacteria (Bacteroides fragilis, Fusobacterium nucleatum, Porphyromonas asaccharolytica, Parvimonas micra, Prevotella intermedia, Alistipes finegoldii, and Thermanaerovibrio acidaminovorans) have been identified across populations. The seven enriched bacterial markers classified cases from controls with an area under the receiver-operating characteristics curve (AUC) of 0.80 across the different populations. Abundance correlation analysis demonstrated that CRC-enriched and CRC-depleted bacteria respectively formed their own mutualistic networks, in which the latter was disjointed in CRC. The CRC-enriched bacteria have been found to be correlated with lipopolysaccharide and energy biosynthetic pathways. Our study identified potential diagnostic bacterial markers that are robust across populations, indicating their potential universal use for non-invasive CRC diagnosis. We also elucidated the ecological networks and functional capacities of CRC-associated microbiota.