Genetic overlap study between idiopathic pulmonary fibrosis and COVID-19

Background/Objectives: Genetic factors influence COVID-19 susceptibility and outcomes, including the development of pulmonary fibrosis (i.e. lung scarring). Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease and the most common cause of pulmonary fibrosis in the general population. Genome-wide association studies (GWAS) of COVID-19 and IPF revealed genes associated with both diseases, suggesting these share genetic risk factors. Here we performed a genetic overlap study between COVID-19 and IPF. Method(s): Summary statistics from an IPF 5-way meta-GWAS and from the COVID-19 Host Genetics initiative GWAS metaanalysis (v6) were used. We performed genetic correlation analyses and assessed individual genetic signals to identify those variants shared between both traits. We conducted colocalisation analyses to determine whether the same causal variant was driving both traits. Finally, the association of overlapping variants with gene expression was assessed and a phenome-wide association study was performed. Result(s): There was a positive genetic correlation between severe COVID-19 and IPF. We found four genetic loci with likely shared causal variants between both traits, including one novel risk locus at 7q22.1 that colocalised with decreased ZKSCAN1 and TRIM4 expression in blood. The other three loci colocalised with MUC5B, ATP11A and DPP9 expression. The locus associated with increased ATP11A expression was also associated with higher Hb1AC levels, a biomarker used in diabetes. Conclusion(s): Results suggest there are shared biological processes driving IPF and severe COVID-19 phenotypes.

Microbiota shaping and bioburden monitoring of indoor antimicrobial surfaces

Indoor residents are constantly exposed to dynamic microbiota that have significant health effects. In addition to hand hygiene, cleaning, and disinfection, antimicrobial coatings (AMCs) can prevent the spread of infectious diseases in public areas. The sustainable use of antimicrobial-coated products requires an assessment of their pros and cons for human health and the environment. The toxicity and resistance risks of AMCs have been considered, but large-scale genetic studies on the microbial community compositions and resistomes of AMCs are scarce. The use of an AMC can reduce the total number of microbes on a surface but poses the risk of dysbiosis, microbial imbalance, such as the polarized growth of metallophilic, metal- and antimicrobial-resistant, and other survivor bacteria, and the overall reduction of microbial diversity. Loss of diversity may lead to the enrichment of harmful bacteria and an increased risk of communicable or immunological non-communicable inflammatory diseases (NCDs). In public buildings, such as kindergartens and nursing homes for the elderly, the use of AMCs is likely to increase due to epidemics and pandemics in recent years. Therefore, comprehensive metagenomic research is needed to monitor the effects of AMCs on indoor microbial community compositions and functions. Although the determination of good indoor microbiota and homeostasis is difficult, microbial communities that have health-protective or harmful effects can and should be identified using a metagenomic sequencing approach before the large-scale implementation of AMCs.

SARS-CoV-2 infection alters the gut microbiome in diabetes patients: A cross-sectional study from Bangladesh.

Populations of different South Asian nations including Bangladesh reportedly have a high risk of developing diabetes in recent years. This study aimed to investigate the differences in the gut microbiome of COVID-19-positive participants with or without type 2 diabetes mellitus (T2DM) compared with healthy control subjects. Microbiome data of 30 participants with T2DM were compared with 22 age-, sex-, and body mass index (BMI)-matched individuals. Clinical features were recorded while fecal samples were collected aseptically from the participants. Amplicon-based (16S rRNA) metagenome analyses were employed to explore the dysbiosis of gut microbiota and its correlation with genomic and functional features in COVID-19 patients with or without T2DM. Comparing the detected bacterial genera across the sample groups, 98 unique genera were identified, of which 9 genera had unique association with COVID-19 T2DM patients. Among different bacterial groups, Shigella (25%), Bacteroides (23.45%), and Megamonas (15.90%) had higher mean relative abundances in COVID-19 patients with T2DM. An elevated gut microbiota dysbiosis in T2DM patients with COVID-19 was observed while some metabolic functional changes correlated with bidirectional microbiome dysbiosis between diabetes and non-diabetes humans gut were also found. These results further highlight the possible association of COVID-19 infection that might be linked with alteration of gut microbiome among T2DM patients.

Assessment of residual chlorine in soil microbial community using metagenomics

Chlorine-containing disinfectants have been widely used around the world for the prevention and control of the COVID-19 pandemic. However, at present, little is known about the impact of residual chlorine on the soil micro-ecological environment. Herein, we treated an experimental soil-plant-microbiome microcosm system by continuous irrigation with a low concentration of chlorine-containing water, and then analyzed the influence on the soil microbial community using metagenomics. After 14-d continuous chlorine treatment, there were no significant lasting effect on soil microbial community diversity and composition either in the rhizosphere or in bulk soil. Although metabolic functions of the rhizosphere microbial community were affected slightly by continuous chlorine treatment, it recovered to the original status. The abundance of several resistance genes changed by 7 d and recovered by 14 d. According to our results, the chlorine residue resulting from daily disinfection may present a slight long-term effect on plant growth (shoot length and fresh weight) and soil micro-ecology. In general, our study assisted with environmental risk assessments relating to the application ofchlorine-containing disinfectants and minimization of risks to the environment during disease control, such as COVID-19. © 2022, Higher Education Press.

A Novel Coronavirus and a Broad Range of Viruses in Kenyan Cave Bats.

BACKGROUND AND METHODS: To investigate virus diversity in hot zones of probable pathogen spillover, 54 oral-fecal swabs were processed from five bat species collected from three cave systems in Kenya, using metagenome sequencing. RESULTS: Viruses belonging to the Astroviridae, Circoviridae, Coronaviridae, Dicistroviridae, Herpesviridae and Retroviridae were detected, with unclassified viruses. Retroviral sequences were prevalent; 74.1% of all samples were positive, with distinct correlations between virus, site and host bat species. Detected retroviruses comprised Myotis myotis, Myotis ricketti, Myotis daubentonii and Galidia endogenous retroviruses, murine leukemia virus-related virus and Rhinolophus ferrumequinum retrovirus (RFRV). A near-complete genome of a local RFRV strain with identical genome organization and 2.8% nucleotide divergence from the prototype isolate was characterized. Bat coronavirus sequences were detected with a prevalence of 24.1%, where analyses on the ORF1ab region revealed a novel alphacoronavirus lineage. Astrovirus sequences were detected in 25.9%of all samples, with considerable diversity. In 9.2% of the samples, other viruses including Actinidia yellowing virus 2, bat betaherpesvirus, Bole tick virus 4, Cyclovirus and Rhopalosiphum padi virus were identified. CONCLUSIONS: Further monitoring of bats across Kenya is essential to facilitate early recognition of possibly emergent zoonotic viruses.

[Composition of oropharyngeal microbiota in patients with COVID-19 of different pneumonia severity].

AIM: To identify features of the taxonomic composition of the oropharyngeal microbiota of COVID-19 patients with different disease severity. MATERIALS AND METHODS: The study group included 156 patients hospitalized with confirmed diagnosis of COVID-19 in the clinical medical center of Yevdokimov Moscow State University of Medicine and Dentistry between April and June 2021. There were 77 patients with mild pneumonia according to CT (CT1) and 79 patients with moderate to severe pneumonia (CT2 and CT3). Oropharyngeal swabs were taken when the patient was admitted to the hospital. Total DNA was isolated from the samples, then V3V4 regions of the 16s rRNA gene were amplified, followed by sequencing using Illumina HiSeq 2500 platform. DADA2 algorithm was used to obtain amplicon sequence variants (ASV). RESULTS: When comparing the microbial composition of the oropharynx of the patients with different forms of pneumonia, we have identified ASVs associated with the development of both mild and severe pneumonia outside hospital treatment. Based on the results obtained, ASVs associated with a lower degree of lung damage belong predominantly to the class of Gram-negative Firmicutes (Negativicutes), to various classes of Proteobacteria, as well as to the order Fusobacteria. In turn, ASVs associated with a greater degree of lung damage belong predominantly to Gram-positive classes of Firmicutes Bacilli and Clostridia. While being hospitalized, patients with severe pneumonia demonstrated negative disease dynamics during treatment significantly more often. CONCLUSION: We have observed differences in the taxonomic composition of the oropharyngeal microbiota in patients with different forms of pneumonia developed outside hospital treatment against COVID-19. Such differences might be due to the presumed barrier function of the oropharyngeal microbiota, which reduces the risk of virus titer increase.

In silico identification and exploration of a new non-toxic antimicrobial peptide of medicinal leech microbiome

Antimicrobial agents are demanded to treat infectious diseases, one of the leading causes of death worldwide. Longstanding thoughtless use of antibiotics has led to the development and spread of drug-resistant microorganisms. This problem has become especially acute within the Covid-19 pandemic. Antimicrobial peptides (AMPs) are considered as effective therapeutic agents that are less prone to the development of bacterial resistance than antibiotics. In the present study, we identified antimicrobial non-toxic peptides from the leech metagenome protein database using a gradient boosting approach (CatBoost). The antimicrobial activity of the peptides was tested against Grampositive and Gram-negative bacteria (Bacillus subtilis, Staphylococcus aureus, Staphylococcus haemolyticus, Escherichia coli, Mycobacterium smegmatis). One of the analyzed peptides, peptide HMAMP-2, showed the best antimicrobial activity against the tested bacteria at low concentrations. Viability and hemolysis evaluation of cells incubated with peptides demonstrated peptide HMAMP-2 did not affect cell viability at high concentrations. It was experimentally shown that the peptide killed pathogens due to the membranolytic mechanism of action. According to nuclear magnetic resonance analysis, the peptide adopted an a-helical structure in a membrane environment. In addition, we demonstrated that peptide Hm-AMP2 binds to LPS, which supported the immunomodulatory properties of the peptide. Thus, peptide Hm-AMP2 is characterized as a promising non-hemolytic and non-toxic antimicrobial compound. Peptide Hm-AMP2 is likely involved in the regulation of the inflammatory response of the innate immune system, which should be studied further. The developed algorithm for the identification of antimicrobial peptides with a reduced toxic effect can be used for the rational design of effective non-toxic antibacterial agents.

METAGENOMIC INTERROGATION OF RESPIRATORY AND GUT MICROBIAL COMMUNITIES, HOST IMMUNE RESPONSE, AND RISK OF SEVERE COVID-19

Background: Human-associated microbial communities have been linked to host immune response to respiratory viral infections. Prior investigations have observed shifts in the composition of the gut or respiratory microbiome in severe COVID-19. However, there has been no comprehensive metagenomic evaluation of the interaction between lower respiratory and gut microbiomes and host immune factors in COVID-19. Methods: From April 2020 to May 2021, we prospectively enrolled 153 hospitalized patients with mild (n=12), moderate (n=65), and severe (n=76) COVID-19 infection categorized using established clinical criteria. We longitudinally collected stool (n=270) for metagenomic profiling, and in a subset, we generated comprehensive host-microbiome-molecular profiles by collecting sputum metagenomes (n=87 participants with 212 samples) and blood cytokine levels (n=109 with 181 samples) weekly until hospital discharge. We performed omnibus testing of overall gut and respiratory community structure, species-level differential abundance testing using mixed effects modeling accounting for repeated sampling, hierarchical clustering of paired gut and respiratory metagenomic profiles, and multi-omic machine learning classification of disease severity. Results: Patients with severe COVID-19 tended to be older, were more frequently male, had higher rates of overweight/obesity, and a greater mean Charlson Comorbidity Index. Patients with severe COVID-19 infection had significantly decreased stool and respiratory microbiome a-diversity irrespective of antibiotic administration. COVID severity accounted for a small proportion of variance in stool (R2=2.4%, p=0.002) and sputum (R2=4.4%, p= 0.03) profiles. Hierarchical clustering of paired gut and respiratory samples from patients with severe COVID revealed the joint expansion of oral-typical taxa typically present during systemic inflammation (i.e., increases in Streptococcus and Peptostreptococus spp. in both gut and sputum). A pro-inflammatory milieu defined by a composite elevation of circulating plasma cytokines (e.g., IL-6, TNF-a, and IL-29 among others) were linked to broad microbial excursions in community structure for both stool and sputum as measured by Bray-Curtis distances. A random forest classifier incorporating either stool or sputum taxonomic features and accounting for age, sex, body mass index, and recent antibiotic use achieved excellent classification of biospecimens from patients with severe vs. non-severe COVID patients (AUROC > 0.80). Conclusions: Alterations of the gut and respiratory microbiome were associated with differences in host immune response and COVID-19 disease severity. Further studies are needed to identify the potential role of human-associated microbial communities as a biomarker for poor patient outcomes in COVID-19 who may warrant escalated levels of care.(Figure Presented) Fig. 1. (A) Using unsupervised feature selection (species abundance > 0.001) inclusive of taxa differentially abundant by non-parametric Wilcoxon rank-sum testing (nominal p-value < 0.05), (B) we performed random forest classification using a twice-repeated 5-fold crossvalidation scheme to predict COVID-19 disease severity from shotgun metagenomic stool profiles (C) yielding an AUROC of 0.91.

Microbiome Analysis for Wastewater Surveillance during COVID-19.

Wastewater surveillance (WS), when coupled with advanced molecular techniques, offers near real-time monitoring of community-wide transmission of SARS-CoV-2 and allows assessing and mitigating COVID-19 outbreaks, by evaluating the total microbial assemblage in a community. Composite wastewater samples (24 h) were collected weekly from a manhole between December 2020 and November 2021 in Maryland, USA. RT-qPCR results showed concentrations of SARS-CoV-2 RNA recovered from wastewater samples reflected incidence of COVID-19 cases. When a drastic increase in COVID-19 was detected in February 2021, samples were selected for microbiome analysis (DNA metagenomics, RNA metatranscriptomics, and targeted SARS-CoV-2 sequencing). Targeted SARS-CoV-2 sequencing allowed for detection of important genetic mutations, such as spike: K417N, D614G, P681H, T716I, S982A, and D1118H, commonly associated with increased cell entry and reinfection. Microbiome analysis (DNA and RNA) provided important insight with respect to human health-related factors, including detection of pathogens and their virulence/antibiotic resistance genes. Specific microbial species comprising the wastewater microbiome correlated with incidence of SARS-CoV-2 RNA, suggesting potential association with SARS-CoV-2 infection. Climatic conditions, namely, temperature, were related to incidence of COVID-19 and detection of SARS-CoV-2 in wastewater, having been monitored as part of an environmental risk score assessment carried out in this study. In summary, the wastewater microbiome provides useful public health information, and hence, a valuable tool to proactively detect and characterize pathogenic agents circulating in a community. In effect, metagenomics of wastewater can serve as an early warning system for communicable diseases, by providing a larger source of information for health departments and public officials. IMPORTANCE Traditionally, testing for COVID-19 is done by detecting SARS-CoV-2 in samples collected from nasal swabs and/or saliva. However, SARS-CoV-2 can also be detected in feces of infected individuals. Therefore, wastewater samples can be used to test all individuals of a community contributing to the sewage collection system, i.e., the infrastructure, such as gravity pipes, manholes, tanks, lift stations, control structures, and force mains, that collects used water from residential and commercial sources and conveys the flow to a wastewater treatment plant. Here, we profile community wastewater collected from a manhole, detect presence of SARS-CoV-2, identify genetic mutations of SARS-CoV-2, and perform COVID-19 risk score assessment of the study area. Using metagenomics analysis, we also detect other microorganisms (bacteria, fungi, protists, and viruses) present in the samples. Results show that by analyzing all microorganisms present in wastewater, pathogens circulating in a community can provide an early warning for contagious diseases.

Hi-C Metagenomics in the ICU: Exploring Clinically Relevant Features of Gut Microbiome in Chronically Critically Ill Patients.

Gut microbiome in critically ill patients shows profound dysbiosis. The most vulnerable is the subgroup of chronically critically ill (CCI) patients - those suffering from long-term dependence on support systems in intensive care units. It is important to investigate their microbiome as a potential reservoir of opportunistic taxa causing co-infections and a morbidity factor. We explored dynamics of microbiome composition in the CCI patients by combining "shotgun" metagenomics with chromosome conformation capture (Hi-C). Stool samples were collected at 2 time points from 2 patients with severe brain injury with different outcomes within a 1-2-week interval. The metagenome-assembled genomes (MAGs) were reconstructed based on the Hi-C data using a novel hicSPAdes method (along with the bin3c method for comparison), as well as independently of the Hi-C using MetaBAT2. The resistomes of the samples were derived using a novel assembly graph-based approach. Links of bacteria to antibiotic resistance genes, plasmids and viruses were analyzed using Hi-C-based networks. The gut community structure was enriched in opportunistic microorganisms. The binning using hicSPAdes was superior to the conventional WGS-based binning as well as to the bin3c in terms of the number, completeness and contamination of the reconstructed MAGs. Using Klebsiella pneumoniae as an example, we showed how chromosome conformation capture can aid comparative genomic analysis of clinically important pathogens. Diverse associations of resistome with antimicrobial therapy from the level of assembly graphs to gene content were discovered. Analysis of Hi-C networks suggested multiple "host-plasmid" and "host-phage" links. Hi-C metagenomics is a promising technique for investigating clinical microbiome samples. It provides a community composition profile with increased details on bacterial gene content and mobile genetic elements compared to conventional metagenomics. The ability of Hi-C binning to encompass the MAG's plasmid content facilitates metagenomic evaluation of virulence and drug resistance dynamics in clinically relevant opportunistic pathogens. These findings will help to identify the targets for developing cost-effective and rapid tests for assessing microbiome-related health risks.

The Human Virome: Viral Metagenomics, Relations with Human Diseases, and Therapeutic Applications.

The human body is colonized by a wide range of microorganisms. The field of viromics has expanded since the first reports on the detection of viruses via metagenomic sequencing in 2002. With the continued development of reference materials and databases, viral metagenomic approaches have been used to explore known components of the virome and discover new viruses from various types of samples. The virome has attracted substantial interest since the outbreak of the coronavirus disease 2019 (COVID-19) pandemic. Increasing numbers of studies and review articles have documented the diverse virome in various sites in the human body, as well as interactions between the human host and the virome with regard to health and disease. However, there have been few studies of direct causal relationships. Viral metagenomic analyses often lack standard references and are potentially subject to bias. Moreover, most virome-related review articles have focused on the gut virome and did not investigate the roles of the virome in other sites of the body in human disease. This review presents an overview of viral metagenomics, with updates regarding the relations between alterations in the human virome and the pathogenesis of human diseases, recent findings related to COVID-19, and therapeutic applications related to the human virome.

SARS-CoV-2 triggered oxidative stress and abnormal energy metabolism in gut microbiota.

Specific roles of gut microbes in COVID-19 progression are critical. However, the circumstantial mechanism remains elusive. In this study, shotgun metagenomic or metatranscriptomic sequencing was performed on fecal samples collected from 13 COVID-19 patients and controls. We analyzed the structure of gut microbiota, identified the characteristic bacteria, and selected biomarkers. Further, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotations were employed to correlate the taxon alterations and corresponding functions. The gut microbiota of COVID-19 patients was characterized by the enrichment of opportunistic pathogens and depletion of commensals. The abundance of Bacteroides spp. displayed an inverse relationship with COVID-19 severity, whereas Actinomyces oris, Escherichia coli, and Streptococcus parasanguini were positively correlated with disease severity. The genes encoding oxidoreductase were significantly enriched in gut microbiome of COVID-19 group. KEGG annotation indicated that the expression of ABC transporter was upregulated, while the synthesis pathway of butyrate was aberrantly reduced. Furthermore, increased metabolism of lipopolysaccharide, polyketide sugar, sphingolipids, and neutral amino acids were found. These results suggested the gut microbiome of COVID-19 patients was in a state of oxidative stress. Healthy gut microbiota may enhance antiviral defenses via butyrate metabolism, whereas the accumulation of opportunistic and inflammatory bacteria may exacerbate COVID-19 progression.

AI for the collective analysis of a massive number of genome sequences: various examples from the small genome of pandemic SARS-CoV-2 to the human genome.

In genetics and related fields, huge amounts of data, such as genome sequences, are accumulating, and the use of artificial intelligence (AI) suitable for big data analysis has become increasingly important. Unsupervised AI that can reveal novel knowledge from big data without prior knowledge or particular models is highly desirable for analyses of genome sequences, particularly for obtaining unexpected insights. We have developed a batch-learning self-organizing map (BLSOM) for oligonucleotide compositions that can reveal various novel genome characteristics. Here, we explain the data mining by the BLSOM: an unsupervised AI. As a specific target, we first selected SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) because a large number of viral genome sequences have been accumulated via worldwide efforts. We analyzed more than 0.6 million sequences collected primarily in the first year of the pandemic. BLSOMs for short oligonucleotides (e.g., 4-6-mers) allowed separation into known clades, but longer oligonucleotides further increased the separation ability and revealed subgrouping within known clades. In the case of 15-mers, there is mostly one copy in the genome; thus, 15-mers that appeared after the epidemic started could be connected to mutations, and the BLSOM for 15-mers revealed the mutations that contributed to separation into known clades and their subgroups. After introducing the detailed methodological strategies, we explain BLSOMs for various topics, such as the tetranucleotide BLSOM for over 5 million 5-kb fragment sequences derived from almost all microorganisms currently available and its use in metagenome studies. We also explain BLSOMs for various eukaryotes, including fishes, frogs and Drosophila species, and found a high separation ability among closely related species. When analyzing the human genome, we found enrichments in transcription factor-binding sequences in centromeric and pericentromeric heterochromatin regions. The tDNAs (tRNA genes) could be separated according to their corresponding amino acid.

Microbiological and Toxicological Hazards in Sewage Treatment Plant Bioaerosol and Dust.

Despite the awareness that work in the sewage treatment plant is associated with biological hazards, they have not been fully recognised so far. The research aims to comprehensively evaluate microbiological and toxicological hazards in the air and settled dust in workstations in a sewage treatment plant. The number of microorganisms in the air and settled dust was determined using the culture method and the diversity was evaluated using high-throughput sequencing. Endotoxin concentration was assessed with GC-MS (gas chromatography-mass spectrometry) while secondary metabolites with LC-MS/MS (liquid chromatography coupled to tandem mass spectrometry). Moreover, cytotoxicity of settled dust against a human lung epithelial lung cell line was determined with the MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay and UHPLC-Q-ToF-UHRMS (ultra-high-performance liquid chromatography-quadrupole time-of-flight ultrahigh-resolution mass spectrometry) analysis was performed to determine the source of cytotoxicity. The total dust concentration in the sewage treatment plant was low and ranged from 0.030 mg m-3 to 0.044 mg m-3. The highest microbiological contamination was observed in sludge thickening building and screenings storage. Three secondary metabolites were detected in the air and sixteen in the settled dust. They were dominated by compounds typical of lichen and plants and Aspergillus, Penicillium and Fusarium genera mould. The settled dust from the sludge thickening building revealed high cytotoxicity to human lung epithelial cells A-549 (IC50 = 6.98 after 72 h). This effect can be attributed to a biocidal compound-didecyldimethylammonium chloride (DDAC-C10) and seven toxic compounds: 4-hydroxynonenal, carbofuran, cerulenin, diethylphosphate, fenpropimorph, naphthalene and onchidal. The presence of DDAC-C10 and other biocidal substances in the sewage treatment plant environment may bring negative results for biological sewage treatment and the natural environment in the future and contribute to microorganisms' increasing antibiotics resistance. Therefore, the concentration of antibiotics, pesticides and disinfectants in sewage treatment plant workstations should be monitored.

Enriched Opportunistic Pathogens Revealed by Metagenomic Sequencing Hint Potential Linkages between Pharyngeal Microbiota and COVID-19.

As a respiratory tract virus, SARS-CoV-2 infected people through contacting with the upper respiratory tract first. Previous studies indicated that microbiota could modulate immune response against pathogen infection. In the present study, we performed metagenomic sequencing of pharyngeal swabs from eleven patients with COVID-19 and eleven Non-COVID-19 patients who had similar symptoms such as fever and cough. Through metagenomic analysis of the above two groups and a healthy group from the public data, there are 6502 species identified in the samples. Specifically, the Pielou index indicated a lower evenness of the microbiota in the COVID-19 group than that in the Non-COVID-19 group. Combined with the linear discriminant analysis (LDA) and the generalized linear model, eighty-one bacterial species were found with increased abundance in the COVID-19 group, where 51 species were enriched more than 8 folds. The top three enriched genera were Streptococcus, Prevotella and Campylobacter containing some opportunistic pathogens. More interestingly, through experiments, we found that two Streptococcus strains, S. suis and S. agalactiae, could stimulate the expression of ACE2 of Vero cells in vitro, which may promote SARS-CoV-2 infection. Therefore, these enriched pathogens in the pharynxes of COVID-19 patients may involve in the virus-host interactions to affect SARS-CoV-2 infection and cause potential secondary bacterial infections through changing the expression of the viral receptor ACE2 and/or modulate the host's immune system.

Advances in Microbiome Research for Animal Health.

Host-associated microbiomes contribute in many ways to the homeostasis of the metaorganism. The microbiome's contributions range from helping to provide nutrition and aiding growth, development, and behavior to protecting against pathogens and toxic compounds. Here we summarize the current knowledge of the diversity and importance of the microbiome to animals, using representative examples of wild and domesticated species. We demonstrate how the beneficial ecological roles of animal-associated microbiomes can be generally grouped into well-defined main categories and how microbe-based alternative treatments can be applied to mitigate problems for both economic and conservation purposes and to provide crucial knowledge about host-microbiota symbiotic interactions. We suggest a Customized Combination of Microbial-Based Therapies to promote animal health and contribute to the practice of sustainable husbandry. We also discuss the ecological connections and threats associated with animal biodiversity loss, microorganism extinction, and emerging diseases, such as the COVID-19 pandemic.

Protein Structure and Sequence Reanalysis of 2019-nCoV Genome Refutes Snakes as Its Intermediate Host and the Unique Similarity between Its Spike Protein Insertions and HIV-1.

As the infection of 2019-nCoV coronavirus is quickly developing into a global pneumonia epidemic, the careful analysis of its transmission and cellular mechanisms is sorely needed. In this Communication, we first analyzed two recent studies that concluded that snakes are the intermediate hosts of 2019-nCoV and that the 2019-nCoV spike protein insertions share a unique similarity to HIV-1. However, the reimplementation of the analyses, built on larger scale data sets using state-of-the-art bioinformatics methods and databases, presents clear evidence that rebuts these conclusions. Next, using metagenomic samples from Manis javanica, we assembled a draft genome of the 2019-nCoV-like coronavirus, which shows 73% coverage and 91% sequence identity to the 2019-nCoV genome. In particular, the alignments of the spike surface glycoprotein receptor binding domain revealed four times more variations in the bat coronavirus RaTG13 than in the Manis coronavirus compared with 2019-nCoV, suggesting the pangolin as a missing link in the transmission of 2019-nCoV from bats to human.