Metagenomics of gut microbiome for migratory seagulls in Kunming city revealed the potential public risk to human health.

BACKGROUND: Seagull as a migratory wild bird has become most popular species in southwest China since 1980s. Previously, we analyzed the gut microbiota and intestinal pathogenic bacteria configuration for this species by using 16S rRNA sequencing and culture methods. To continue in-depth research on the gut microbiome of migratory seagulls, the metagenomics, DNA virome and RNA virome were both investigated for their gut microbial communities of abundance and diversity in this study. RESULTS: The metagenomics results showed 99.72% of total species was bacteria, followed by viruses, fungi, archaea and eukaryota. In particular, Shigella sonnei, Escherichia albertii, Klebsiella pneumonia, Salmonella enterica and Shigella flexneri were the top distributed taxa at species level. PCoA, NMDS, and statistics indicated some drug resistant genes, such as adeL, evgS, tetA, PmrF, and evgA accumulated as time went by from November to January of the next year, and most of these genes were antibiotic efflux. DNA virome composition demonstrated that Caudovirales was the most abundance virus, followed by Cirlivirales, Geplafuvirales, Petitvirales and Piccovirales. Most of these phages corresponded to Enterobacteriaceae and Campylobacteriaceae bacterial hosts respectively. Caliciviridae, Coronaviridae and Picornaviridae were the top distributed RNA virome at family level of this migratory animal. Phylogenetic analysis indicated the sequences of contigs of Gammacoronavirus and Deltacoronavirus had highly similarity with some coronavirus references. CONCLUSIONS: In general, the characteristics of gut microbiome of migratory seagulls were closely related to human activities, and multiomics still revealed the potential public risk to human health.

The causal links between gut microbiota and COVID-19: A Mendelian randomization study.

Several studies have shown a possible correlation between gut microbiota and COVID-19. However, the cause-and-effect relationship between the two has not been investigated. We conducted a two-sample Mendelian randomization study (MR) study using publicly available GWAS data. Inverse variance weighted (IVW) analysis was the main MR analysis technique and was supplemented with other sensitivity analyses. Forty-two bacterial genera were associated with COVID-19 susceptibility, hospitalization, and severity in the IVW method. Among these gut microbiota, five gut microbiota (genus unknowngenus [id.1000005472], family unknownfamily [id.1000005471], genus Tyzzerella3, order MollicutesRF9.id.11579, and phylum Actinobacteria) were significantly associated with COVID-19 hospitalization and severity. Three gut microbiota (class Negativicutes, order Selenomonadales, and class Actinobacteria) were significantly associated with COVID-19 hospitalization and susceptibility, while two microbiota (class Negativicutes and order Selenomonadales) were significantly associated with COVID-19 hospitalization and severity, and susceptibility. Sensitivity analysis did not detect any heterogeneity and horizontal pleiotropy. Our findings demonstrated that several microorganisms were causally linked to COVID-19, and improved our understanding of the relationship between gut microbiota and COVID-19 pathology.

A high-risk gut microbiota configuration associates with fatal hyperinflammatory immune and metabolic responses to SARS-CoV-2.

Protection against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and associated clinical sequelae requires well-coordinated metabolic and immune responses that limit viral spread and promote recovery of damaged systems. However, the role of the gut microbiota in regulating these responses has not been thoroughly investigated. In order to identify mechanisms underpinning microbiota interactions with host immune and metabolic systems that influence coronavirus disease 2019 (COVID-19) outcomes, we performed a multi-omics analysis on hospitalized COVID-19 patients and compared those with the most severe outcome (i.e. death, n = 41) to those with severe non-fatal disease (n = 89), or mild/moderate disease (n = 42), that recovered. A distinct subset of 8 cytokines (e.g. TSLP) and 140 metabolites (e.g. quinolinate) in sera identified those with a fatal outcome to infection. In addition, elevated levels of multiple pathobionts and lower levels of protective or anti-inflammatory microbes were observed in the fecal microbiome of those with the poorest clinical outcomes. Weighted gene correlation network analysis (WGCNA) identified modules that associated severity-associated cytokines with tryptophan metabolism, coagulation-linked fibrinopeptides, and bile acids with multiple pathobionts, such as Enterococcus. In contrast, less severe clinical outcomes are associated with clusters of anti-inflammatory microbes such as Bifidobacterium or Ruminococcus, short chain fatty acids (SCFAs) and IL-17A. Our study uncovered distinct mechanistic modules that link host and microbiome processes with fatal outcomes to SARS-CoV-2 infection. These features may be useful to identify at risk individuals, but also highlight a role for the microbiome in modifying hyperinflammatory responses to SARS-CoV-2 and other infectious agents.

Ecology and Machine Learning-Based Classification Models of Gut Microbiota and Inflammatory Markers May Evaluate the Effects of Probiotic Supplementation in Patients Recently Recovered from COVID-19.

Gut microbiota (GM) modulation can be investigated as possible solution to enhance recovery after COVID-19. An open-label, single-center, single-arm, pilot, interventional study was performed by enrolling twenty patients recently recovered from COVID-19 to investigate the role of a mixed probiotic, containing Lactobacilli, Bifidobacteria and Streptococcus thermophilus, on gastrointestinal symptoms, local and systemic inflammation, intestinal barrier integrity and GM profile. Gastrointestinal Symptom Rating Scale, cytokines, inflammatory, gut permeability, and integrity markers were evaluated before (T0) and after 8 weeks (T1) of probiotic supplementation. GM profiling was based on 16S-rRNA targeted-metagenomics and QIIME 2.0, LEfSe and PICRUSt computational algorithms. Multiple machine learning (ML) models were trained to classify GM at T0 and T1. A statistically significant reduction of IL-6 (p < 0.001), TNF-α (p < 0.001) and IL-12RA (p < 0.02), citrulline (p value < 0.001) was reported at T1. GM global distribution and microbial biomarkers strictly reflected probiotic composition, with a general increase in Bifidobacteria at T1. Twelve unique KEGG orthologs were associated only to T0, including tetracycline resistance cassettes. ML classified the GM at T1 with 100% score at phylum level. Bifidobacteriaceae and Bifidobacterium spp. inversely correlated to reduction of citrulline and inflammatory cytokines. Probiotic supplementation during post-COVID-19 may trigger anti-inflammatory effects though Bifidobacteria and related-metabolism enhancement.

Relationship Functioning and Gut Microbiota Composition among Older Adult Couples.

An emerging area of research extends work on couple functioning and physical health to gut health, a critical marker of general health and known to diminish with age. As a foray into this area, we conducted a pilot study to (1) determine the feasibility of remote data collection, including a fecal sample, from older adult couples, (2) examine within-couple concordance in gut microbiota composition, and (3) examine associations between relationship functioning and gut microbiota composition. Couples (N = 30) were recruited from the community. The participants' demographic characteristics were as follows: M (SD) age = 66.6 (4.8), 53% female, 92% White, and 2% Hispanic. Two of the couples were same-sex. All 60 participants completed self-report measures and supplied a fecal sample for microbiome analysis. Microbial DNA was extracted from the samples, and the 16S rRNA gene V4 region was amplified and sequenced. The results indicated that individuals shared more similar gut microbial composition with their partners than with others in the sample, p < 0.0001. In addition, individuals with better relationship quality (greater relationship satisfaction and intimacy and less avoidant communication) had greater microbial diversity, p < 0.05, a sign of healthier gut microbiota. Further research with a larger and more diverse sample is warranted to elucidate mechanisms.

Gut Microbiota Dysbiosis Correlates With Long COVID-19 at One-Year After Discharge.

BACKGROUND: Long coronavirus disease 2019 (COVID-19) in recovered patients (RPs) is gradually recognized by more people. However, how long it will last and the underlining mechanism remains unclear. METHODS: We conducted a prospective follow-up study to evaluate the long-term symptoms and clinical indices of RPs at one-year after discharge from Union Hospital, Wuhan, China between December 2020 to May 2021. We also performed the 16S rRNA sequencing of stool samples from RPs and healthy controls (HCs) and analyzed the correlation between the gut microbiota and long COVID-19. RESULTS: In total, 187 RPs were enrolled, among them, 84 (44.9%) RPs reported long COVID-19 symptoms at one-year after discharge. The most common long-term symptoms were cardiopulmonary symptoms, including chest tightness after activity (39/187, 20.9%), palpitations on exercise (27/187, 14.4%), sputum (21/187, 11.2%), cough (15/187, 8.0%) and chest pain (13/187, 7.0%), followed by systemic symptoms including fatigue (34/187, 18.2%) and myalgia (20/187, 10.7%), and digestive symptoms including constipation (14/187, 7.5%), anorexia (13/187, 7.0%), and diarrhea (8/187, 4.3%). Sixty-six (35.9%) RPs presented either anxiety or depression (42/187 [22.8%] and 53/187 [28.8%] respectively), and the proportion of anxiety or depression in the long symptomatic group was significantly higher than that in the asymptomatic group (41/187 [50.6%] vs. 25/187 [24.3%]). Compared with the asymptomatic group, scores of all nine 36-Item Short Form General Health Survey domains were lower in the symptomatic group (all P < 0.05). One hundred thirty RPs and 32 HCs (non-severe acute respiratory syndrome coronavirus 2 infected subjects) performed fecal sample sequencing. Compared with HCs, symptomatic RPs had obvious gut microbiota dysbiosis including significantly reduced bacterial diversities and lower relative abundance of short-chain fatty acids (SCFAs)-producing salutary symbionts such as Eubacterium_hallii_group, Subdoligranulum, Ruminococcus, Dorea, Coprococcus, and Eubacterium_ventriosum_group. Meanwhile, the relative abundance of Eubacterium_hallii_group, Subdoligranulum, and Ruminococcus showed decreasing tendencies between HCs, the asymptomatic group, and the symptomatic group. CONCLUSION: This study demonstrated the presence of long COVID-19 which correlates with gut microbiota dysbiosis in RPs at one-year after discharge, indicating gut microbiota may play an important role in long COVID-19.

Altered infective competence of the human gut microbiome in COVID-19.

BACKGROUND: Infections with SARS-CoV-2 have a pronounced impact on the gastrointestinal tract and its resident microbiome. Clear differences between severe cases of infection and healthy individuals have been reported, including the loss of commensal taxa. We aimed to understand if microbiome alterations including functional shifts are unique to severe cases or a common effect of COVID-19. We used high-resolution systematic multi-omic analyses to profile the gut microbiome in asymptomatic-to-moderate COVID-19 individuals compared to a control group. RESULTS: We found a striking increase in the overall abundance and expression of both virulence factors and antimicrobial resistance genes in COVID-19. Importantly, these genes are encoded and expressed by commensal taxa from families such as Acidaminococcaceae and Erysipelatoclostridiaceae, which we found to be enriched in COVID-19-positive individuals. We also found an enrichment in the expression of a betaherpesvirus and rotavirus C genes in COVID-19-positive individuals compared to healthy controls. CONCLUSIONS: Our analyses identified an altered and increased infective competence of the gut microbiome in COVID-19 patients. Video Abstract.

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.

Guild-Level Microbiome Signature Associated with COVID-19 Severity and Prognosis.

Coronavirus disease 2019 (COVID-19) severity has been associated with alterations of the gut microbiota. However, the relationship between gut microbiome alterations and COVID-19 prognosis remains elusive. Here, we performed a genome-resolved metagenomic analysis on fecal samples from 300 in-hospital COVID-19 patients, collected at the time of admission. Among the 2,568 high quality metagenome-assembled genomes (HQMAGs), redundancy analysis identified 33 HQMAGs which showed differential distribution among mild, moderate, and severe/critical severity groups. Co-abundance network analysis determined that the 33 HQMAGs were organized as two competing guilds. Guild 1 harbored more genes for short-chain fatty acid biosynthesis, and fewer genes for virulence and antibiotic resistance, compared with Guild 2. Based on average abundance difference between the two guilds, the guild-level microbiome index (GMI) classified patients from different severity groups (average AUROC [area under the receiver operating curve] = 0.83). Moreover, age-adjusted partial Spearman's correlation showed that GMIs at admission were correlated with 8 clinical parameters, which are predictors for COVID-19 prognosis, on day 7 in hospital. In addition, GMI at admission was associated with death/discharge outcome of the critical patients. We further validated that GMI was able to consistently classify patients with different COVID-19 symptom severities in different countries and differentiated COVID-19 patients from healthy subjects and pneumonia controls in four independent data sets. Thus, this genome-based guild-level signature may facilitate early identification of hospitalized COVID-19 patients with high risk of more severe outcomes at time of admission. IMPORTANCE Previous reports on the associations between COVID-19 and gut microbiome have been constrained by taxonomic-level analysis and overlook the interaction between microbes. By applying a genome-resolved, reference-free, guild-based metagenomic analysis, we demonstrated that the relationship between gut microbiota and COVID-19 is genome-specific instead of taxon-specific or even species-specific. Moreover, the COVID-19-associated genomes were not independent but formed two competing guilds, with Guild 1 potentially beneficial and Guild 2 potentially more detrimental to the host based on comparative genomic analysis. The dominance of Guild 2 over Guild 1 at time of admission was associated with hospitalized COVID-19 patients at high risk for more severe outcomes. Moreover, the guild-level microbiome signature is not only correlated with the symptom severity of COVID-19 patients, but also differentiates COVID-19 patients from pneumonia controls and healthy subjects across different studies. Here, we showed the possibility of using genome-resolved and guild-level microbiome signatures to identify hospitalized COVID-19 patients with a high risk of more severe outcomes at the time of admission.

The gut-microbiota-brain axis in a Spanish population in the aftermath of the COVID-19 pandemic: microbiota composition linked to anxiety, trauma, and depression profiles.

The prevalence of anxiety and depression soared following the COVID-19 pandemic. To effectively treat these conditions, a comprehensive understanding of all etiological factors is needed. This study investigated fecal microbial features associated with mental health outcomes (symptoms of anxiety, depression, or posttraumatic stress disorder (PTSD)) in a Spanish cohort in the aftermath of the COVID-19 pandemic. Microbial communities from stool samples were profiled in 198 individuals who completed validated, self-report questionnaires. 16S ribosomal RNA gene V3-4 amplicon sequencing was performed. Microbial diversity and community structure were analyzed, together with relative taxonomic abundance. In our cohort of N=198, 17.17% reported depressive symptoms, 37.37% state anxiety symptoms, 40.90% trait anxiety symptoms, and 8.08% PTSD symptoms, with high levels of comorbidity. Individuals with trait anxiety had lower Simpson's diversity. Fusicatenibacter saccharivorans was reduced in individuals with comorbid PTSD + depression + state and trait anxiety symptoms, whilst an expansion of Proteobacteria and depletion of Synergistetes phyla were noted in individuals with depressive symptoms. The relative abundance of Anaerostipes was positively correlated with childhood trauma, and higher levels of Turicibacter sanguinis and lower levels of Lentisphaerae were found in individuals who experienced life-threatening traumas. COVID-19 infection and vaccination influenced the overall microbial composition and were associated with distinct relative taxonomic abundance profiles. These findings will help lay the foundation for future studies to identify microbial role players in symptoms of anxiety, depression, and PTSD and provide future therapeutic targets to improve mental health outcomes.

Correlation between postmortem microbial signatures and substance abuse disorders.

The microbiota gut-brain-axis is a bidirectional circuit that links the neural, endocrine, and immunological systems with gut microbial communities. The gut microbiome plays significant roles in human mind and behavior, specifically pain perception, learning capacity, memory, and temperament. Studies have shown that disruptions in the gut microbiota have been associated with substance use disorders. The interplay of gut microbiota in substance abuse disorders has not been elucidated; however, postmortem microbiome profiles may produce promising avenues for future forensic investigations. The goal of the current study was to determine gut microbiome composition in substance abuse disorder cases using transverse colon tissues of 21 drug overdose versus 19 non-overdose-related cases. We hypothesized that postmortem samples of the same cause of death will reveal similar microbial taxonomic relationships. We compared microbial diversity profiles using amplicon-based sequencing of the 16S rRNA gene V4 hypervariable region. The results demonstrated that the microbial abundance in younger-aged cases were found to have significantly more operational taxonomic units than older cases. Using weighted UniFrac analysis, the influence of substances in overdose cases was found to be a significant factor in determining microbiome similarity. The results also revealed that samples of the same cause of death cluster together, showing a high degree of similarity between samples and a low degree of similarity among samples of different causes of death. In conclusion, our examination of human transverse colon microflora in decomposing remains extends emerging literature on postmortem microbial communities, which will ultimately contribute to advanced knowledge of human putrefaction.

Multi-kingdom gut microbiota analyses define COVID-19 severity and post-acute COVID-19 syndrome.

Our knowledge of the role of the gut microbiome in acute coronavirus disease 2019 (COVID-19) and post-acute COVID-19 is rapidly increasing, whereas little is known regarding the contribution of multi-kingdom microbiota and host-microbial interactions to COVID-19 severity and consequences. Herein, we perform an integrated analysis using 296 fecal metagenomes, 79 fecal metabolomics, viral load in 1378 respiratory tract samples, and clinical features of 133 COVID-19 patients prospectively followed for up to 6 months. Metagenomic-based clustering identifies two robust ecological clusters (hereafter referred to as Clusters 1 and 2), of which Cluster 1 is significantly associated with severe COVID-19 and the development of post-acute COVID-19 syndrome. Significant differences between clusters could be explained by both multi-kingdom ecological drivers (bacteria, fungi, and viruses) and host factors with a good predictive value and an area under the curve (AUC) of 0.98. A model combining host and microbial factors could predict the duration of respiratory viral shedding with 82.1% accuracy (error ± 3 days). These results highlight the potential utility of host phenotype and multi-kingdom microbiota profiling as a prognostic tool for patients with COVID-19.

Meta-analysis of 16S rRNA microbial data identified alterations of the gut microbiota in COVID-19 patients during the acute and recovery phases.

BACKGROUND: Dozens of studies have demonstrated gut dysbiosis in COVID-19 patients during the acute and recovery phases. However, a consensus on the specific COVID-19 associated bacteria is missing. In this study, we performed a meta-analysis to explore whether robust and reproducible alterations in the gut microbiota of COVID-19 patients exist across different populations. METHODS: A systematic review was conducted for studies published prior to May 2022 in electronic databases. After review, we included 16 studies that comparing the gut microbiota in COVID-19 patients to those of controls. The 16S rRNA sequence data of these studies were then re-analyzed using a standardized workflow and synthesized by meta-analysis. RESULTS: We found that gut bacterial diversity of COVID-19 patients in both the acute and recovery phases was consistently lower than non-COVID-19 individuals. Microbial differential abundance analysis showed depletion of anti-inflammatory butyrate-producing bacteria and enrichment of taxa with pro-inflammatory properties in COVID-19 patients during the acute phase compared to non-COVID-19 individuals. Analysis of microbial communities showed that the gut microbiota of COVID-19 recovered patients were still in unhealthy ecostates. CONCLUSIONS: Our results provided a comprehensive synthesis to better understand gut microbial perturbations associated with COVID-19 and identified underlying biomarkers for microbiome-based diagnostics and therapeutics.

MicrobiomeCensus estimates human population sizes from wastewater samples based on inter-individual variability in gut microbiomes.

The metagenome embedded in urban sewage is an attractive new data source to understand urban ecology and assess human health status at scales beyond a single host. Analyzing the viral fraction of wastewater in the ongoing COVID-19 pandemic has shown the potential of wastewater as aggregated samples for early detection, prevalence monitoring, and variant identification of human diseases in large populations. However, using census-based population size instead of real-time population estimates can mislead the interpretation of data acquired from sewage, hindering assessment of representativeness, inference of prevalence, or comparisons of taxa across sites. Here, we show that taxon abundance and sub-species diversisty in gut-associated microbiomes are new feature space to utilize for human population estimation. Using a population-scale human gut microbiome sample of over 1,100 people, we found that taxon-abundance distributions of gut-associated multi-person microbiomes exhibited generalizable relationships with respect to human population size. Here and throughout this paper, the human population size is essentially the sample size from the wastewater sample. We present a new algorithm, MicrobiomeCensus, for estimating human population size from sewage samples. MicrobiomeCensus harnesses the inter-individual variability in human gut microbiomes and performs maximum likelihood estimation based on simultaneous deviation of multiple taxa's relative abundances from their population means. MicrobiomeCensus outperformed generic algorithms in data-driven simulation benchmarks and detected population size differences in field data. New theorems are provided to justify our approach. This research provides a mathematical framework for inferring population sizes in real time from sewage samples, paving the way for more accurate ecological and public health studies utilizing the sewage metagenome.

Antibiotics and probiotics impact gut antimicrobial resistance gene reservoir in COVID-19 patients.

Dysbiosis of gut microbiota is well-described in patients with coronavirus 2019 (COVID-19), but the dynamics of antimicrobial resistance genes (ARGs) reservoir, known as resistome, is less known. Here, we performed longitudinal fecal metagenomic profiling of 142 patients with COVID-19, characterized the dynamics of resistome from diagnosis to 6 months after viral clearance, and reported the impact of antibiotics or probiotics on the ARGs reservoir. Antibiotic-naive patients with COVID-19 showed increased abundance and types, and higher prevalence of ARGs compared with non-COVID-19 controls at baseline. Expansion in resistome was mainly driven by tetracycline, vancomycin, and multidrug-resistant genes and persisted for at least 6 months after clearance of SARS-CoV-2. Patients with expanded resistome exhibited increased prevalence of Klebsiella sp. and post-acute COVID-19 syndrome. Antibiotic treatment resulted in further increased abundance of ARGs whilst oral probiotics (synbiotic formula, SIM01) significantly reduced the ARGs reservoir in the gut microbiota of COVID-19 patients during the acute infection and recovery phase. Collectively, these findings shed new insights on the dynamic of ARGs reservoir in COVID-19 patients and the potential role of microbiota-directed therapies in reducing the burden of accumulated ARGs.

Downregulation of ACE, AGTR1, and ACE2 genes mediating SARS-CoV-2 pathogenesis by gut microbiota members and their postbiotics on Caco-2 cells.

INTRODUCTION: Coronavirus disease-2019 (COVID-19) is a complex infection caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that can cause also gastrointestinal symptoms. There are various factors that determine the host susceptibility and severity of infection, including the renin-angiotensin system, the immune response, and the gut microbiota. In this regard, we aimed to investigate the gene expression of ACE, AGTR1, ACE2, and TMPRSS2, which mediate SARS-CoV-2 pathogenesis by Akkermansia muciniphila, Faecalibacterium prausnitzii, Bacteroides thetaiotaomicron, and Bacteroides fragilis on Caco-2 cells. Also, the enrichment analysis considering the studied genes was analyzed on raw data from the microarray analysis of COVID-19 patients. MATERIALS AND METHODS: Caco-2 cells were treated with live, heat-inactivated form and cell free supernatants of A. muciniphila, F. prausnitzii, B. thetaiotaomicron and B. fragilis for overnight. After RNA extraction and cDNA synthesis, the expression of studied genes was assessed by RT-qPCR. DNA methylation of studied genes was analyzed by Partek® Genomics Suite® software on the GSE174818 dataset. We used GSE164805 and GSE166552 datasets from COVID-19 patients to perform enrichment analysis by considering the mentioned genes via GEO2R, DAVID. Finally, the related microRNAs to GO terms concerned on the studied genes were identified by miRPath. RESULTS: The downregulation of ACE, AGTR1, and ACE2 genes by A. muciniphila, F. prausnitzii, B. thetaiotaomicron, and B. fragilis in live, heat-inactivated, and cell-free supernatants was reported for the first time. These genes had hypomethylated DNA status in COVID-19 patients' raw data. The highest fold enrichment in upregulated RAS pathways and immune responses belonged to ACE, AGTR1, and ACE2 by considering the protein-protein interaction network. The common miRNAs targeting the studied genes were reported as miR-124-3p and miR-26b-5p. CONCLUSION: In combination with our experimental data and bioinformatic analysis, we showed the potential of A. muciniphila, F. prausnitzii, B. thetaiotaomicron, and B. fragilis and their postbiotics to reduce ACE, ATR1, and ACE2 expression, which are essential genes that drive upregulated biological processes in COVID-19 patients. Accordingly, due to the potential of studied bacteria on the alteration of ACE, AGTR1, ACE2 genes expression, understanding their correlation with demonstrated miRNAs expression could be valuable. These findings suggest the importance of considering targeted gut microbiota intervention when designing the possible therapeutic strategy for controlling the COVID-19.

SARS-CoV-2-associated gut microbiome alteration; A new contributor to colorectal cancer pathogenesis.

The emergence of a novel coronavirus, COVID-19, in December 2019 led to a global pandemic with more than 170 million confirmed infections and more than 6 million deaths (by July 2022). Studies have shown that infection with SARS-CoV-2 in cancer patients has a higher mortality rate than in people without cancer. Here, we have reviewed the evidence showing that gut microbiota plays an important role in health and is linked to colorectal cancer development. Studies have shown that SARS-CoV-2 infection leads to a change in gut microbiota, which modify intestinal inflammation and barrier permeability and affects tumor-suppressor or oncogene genes, proposing SARS-CoV-2 as a potential contributor to CRC pathogenesis.

Identification of trypsin-degrading commensals in the large intestine.

Increased levels of proteases, such as trypsin, in the distal intestine have been implicated in intestinal pathological conditions1-3. However, the players and mechanisms that underlie protease regulation in the intestinal lumen have remained unclear. Here we show that Paraprevotella strains isolated from the faecal microbiome of healthy human donors are potent trypsin-degrading commensals. Mechanistically, Paraprevotella recruit trypsin to the bacterial surface through type IX secretion system-dependent polysaccharide-anchoring proteins to promote trypsin autolysis. Paraprevotella colonization protects IgA from trypsin degradation and enhances the effectiveness of oral vaccines against Citrobacter rodentium. Moreover, Paraprevotella colonization inhibits lethal infection with murine hepatitis virus-2, a mouse coronavirus that is dependent on trypsin and trypsin-like proteases for entry into host cells4,5. Consistently, carriage of putative genes involved in trypsin degradation in the gut microbiome was associated with reduced severity of diarrhoea in patients with SARS-CoV-2 infection. Thus, trypsin-degrading commensal colonization may contribute to the maintenance of intestinal homeostasis and protection from pathogen infection.

The Entero-Mammary Pathway and Perinatal Transmission of Gut Microbiota and SARS-CoV-2.

COVID-19 is a severe respiratory disease threatening pregnant women, which increases the possibility of adverse pregnancy outcomes. Several recent studies have demonstrated the ability of SARS-CoV-2 to infect the mother enterocytes, disturbing the gut microbiota diversity. The aim of this study was to characterize the entero-mammary microbiota of women in the presence of the virus during delivery. Fifty mother-neonate pairs were included in a transversal descriptive work. The presence of SARS-CoV-2 RNA was detected in nasopharyngeal, mother rectal swabs (MRS) and neonate rectal swabs (NRS) collected from the pairs, and human colostrum (HC) samples collected from mothers. The microbiota diversity was characterized by high-throughput DNA sequencing of V3-16S rRNA gene libraries prepared from HC, MRS, and NRS. Data were analyzed with QIIME2 and R. Our results indicate that several bacterial taxa are highly abundant in MRS positive for SARS-CoV-2 RNA. These bacteria mostly belong to the Firmicutes phylum; for instance, the families Bifidobacteriaceae, Oscillospiraceae, and Microbacteriaceae have been previously associated with anti-inflammatory effects, which could explain the capability of women to overcome the infection. All samples, both positive and negative for SARS-CoV-2, featured a high abundance of the Firmicutes phylum. Further data analysis showed that nearly 20% of the bacterial diversity found in HC was also identified in MRS. Spearman correlation analysis highlighted that some genera of the Proteobacteria and Actinobacteria phyla were negatively correlated with MRS and NRS (p < 0.005). This study provides new insights into the gut microbiota of pregnant women and their potential association with a better outcome during SARS-CoV-2 infection.

Dissecting the role of the human microbiome in COVID-19 via metagenome-assembled genomes.

Coronavirus disease 2019 (COVID-19), primarily a respiratory disease caused by infection with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is often accompanied by gastrointestinal symptoms. However, little is known about the relation between the human microbiome and COVID-19, largely due to the fact that most previous studies fail to provide high taxonomic resolution to identify microbes that likely interact with SARS-CoV-2 infection. Here we used whole-metagenome shotgun sequencing data together with assembly and binning strategies to reconstruct metagenome-assembled genomes (MAGs) from 514 COVID-19 related nasopharyngeal and fecal samples in six independent cohorts. We reconstructed a total of 11,584 medium-and high-quality microbial MAGs and obtained 5403 non-redundant MAGs (nrMAGs) with strain-level resolution. We found that there is a significant reduction of strain richness for many species in the gut microbiome of COVID-19 patients. The gut microbiome signatures can accurately distinguish COVID-19 cases from healthy controls and predict the progression of COVID-19. Moreover, we identified a set of nrMAGs with a putative causal role in the clinical manifestations of COVID-19 and revealed their functional pathways that potentially interact with SARS-CoV-2 infection. Finally, we demonstrated that the main findings of our study can be largely validated in three independent cohorts. The presented results highlight the importance of incorporating the human gut microbiome in our understanding of SARS-CoV-2 infection and disease progression.