SARS-CoV-2 detection status associates with bacterial community composition in patients and the hospital environment

The indoors microbiome and human health

Indoor environments serve as habitat for humans and are replete with various reservoirs and niches for microorganisms. Microorganisms enter indoor spaces with their human and non-human hosts, as well as via exchange with outdoor sources, such as ventilation and plumbing. Once inside, many microorganisms do not survive, especially on dry, barren surfaces. Even reduced, this microbial biomass has critical implications for the health of human occupants. As urbanization escalates, exploring the intersection of the indoor environment with the human microbiome and health is increasingly vital. The indoor microbiome, a complex ecosystem of microorganisms influenced by human activities and environmental factors, plays a pivotal role in modulating infectious diseases and fostering healthy immune development. Recent advancements in microbiome research shed light on this unique ecological system, highlighting the need for innovative approaches in creating health-promoting living spaces. In this Review, we explore the microbial ecology of built environments - places where humans spend most of their lives - and its implications for immune, endocrine and neurological health. We further propose strategies to harness the indoor microbiome for better health outcomes.

IL-22 resolves MASLD via enterocyte STAT3 restoration of diet-perturbed intestinal homeostasis

The exponential rise in metabolic dysfunction-associated steatotic liver disease (MASLD) parallels the ever-increasing consumption of energy-dense diets, underscoring the need for effective MASLD-resolving drugs. MASLD pathogenesis is linked to obesity, diabetes, "gut-liver axis" alterations, and defective interleukin-22 (IL-22) signaling. Although barrier-protective IL-22 blunts diet-induced metabolic alterations, inhibits lipid intake, and reverses microbial dysbiosis, obesogenic diets rapidly suppress its production by small intestine-localized innate lymphocytes. This results in STAT3 inhibition in intestinal epithelial cells (IECs) and expansion of the absorptive enterocyte compartment. These MASLD-sustaining aberrations were reversed by administration of recombinant IL-22, which resolved hepatosteatosis, inflammation, fibrosis, and insulin resistance. Exogenous IL-22 exerted its therapeutic effects through its IEC receptor, rather than hepatocytes, activating STAT3 and inhibiting WNT-β-catenin signaling to shrink the absorptive enterocyte compartment. By reversing diet-reinforced macronutrient absorption, the main source of liver lipids, IL-22 signaling restoration represents a potentially effective interception of dietary obesity and MASLD.

Planning and Analyzing a Low-Biomass Microbiome Study: A Data Analysis Perspective

As investigations of low-biomass microbial communities have become more common, so too has the recognition of major challenges affecting these analyses. These challenges have been shown to compromise biological conclusions and have contributed to several controversies. Here, we review some of the most common and influential challenges in low-biomass microbiome research. We highlight key approaches to alleviate these potential pitfalls, combining experimental planning strategies and data analysis methods.

The impact of breastfeeding on the preterm infant's microbiome and metabolome: a pilot study

BACKGROUND

Human milk is unquestionably beneficial for preterm infants. We investigated how the transition from tube to oral/breastfeeding impacts the preterm infants' oral and gut microbiome and metabolome.

METHODS

We analyzed stool, saliva, and milk samples collected from a cohort of preterm infants enrolled in the MAP Study, a prospective observational trial. The microbiome and metabolome of the samples were analyzed from 4 longitudinal sample time points, 2 during tube feeds only and 2 after the initiation of oral/breastfeeding.

RESULTS

We enrolled 11 mother-infant dyads (gestational age = 27.9 (23.4-32.2)) and analyzed a total of 39 stool, 44 saliva, and 43 milk samples over 4 timepoints. In saliva samples, there was a shift towards increased Streptococcus and decreased Staphylococcus after oral feeding/breastfeeding initiation (p < 0.05). Milk sample metabolites were strongly influenced by the route of feeding and milk type (p < 0.05) and represented the pathways of Vitamin E metabolism, Vitamin B12 metabolism, and Tryptophan metabolism.

CONCLUSION

Our analysis demonstrated that the milk and preterm infant's saliva microbiome and metabolome changed over the course of the first four to 5 months of life, coinciding with the initiation of oral/breastfeeds.

IMPACT

The microbiome and metabolome is altered in the infant's saliva but not their stool, and in mother's milk when feeds are transitioned from tube to oral/breastfeeding. We assessed the relationship between the gut and oral microbiome/metabolome with the milk microbiome/metabolome over a longitudinal period of time in preterm babies. Metabolites that changed in the infants saliva after the initiation of oral feeds have the potential to be used as biomarkers for disease risk.

Intra-hospital microbiome variability is driven by accessibility and clinical activities

The hospital environmental microbiome, which can affect patients' and healthcare workers' health, is highly variable and the drivers of this variability are not well understood. In this study, we collected 37 surface samples from the neonatal intensive care unit (NICU) in an inpatient hospital before and after the operation began. Additionally, healthcare workers collected 160 surface samples from five additional areas of the hospital. All samples were analyzed using 16S rRNA gene amplicon sequencing, and the samples collected by healthcare workers were cultured. The NICU samples exhibited similar alpha and beta diversities before and after opening, which indicated that the microbiome there was stable over time. Conversely, the diversities of samples taken after opening varied widely by area. Principal coordinate analysis (PCoA) showed the samples clustered into two distinct groups: high alpha diversity [the pediatric intensive care unit (PICU), pathology lab, and microbiology lab] and low alpha diversity [the NICU, pediatric surgery ward, and infection prevention and control (IPAC) office]. Least absolute shrinkage and selection operator (LASSO) classification models identified 156 informative amplicon sequence variants (ASVs) for predicting the sample's area of origin. The testing accuracy ranged from 86.37% to 100%, which outperformed linear and radial support vector machine (SVM) and random forest models. ASVs of genera that contain emerging pathogens were identified in these models. Culture experiments had identified viable species among the samples, including potential antibiotic-resistant bacteria. Though area type differences were not noted in the culture data, the prevalences and relative abundances of genera detected positively correlated with 16S sequencing data. This study brings to light the microbial community temporal and spatial variation within the hospital and the importance of pathogenic and commensal bacteria to understanding dispersal patterns for infection control.

IMPORTANCE

We sampled surface samples from a newly built inpatient hospital in multiple areas, including areas accessed by only healthcare workers. Our analysis of the neonatal intensive care unit (NICU) showed that the microbiome was stable before and after the operation began, possibly due to access restrictions. Of the high-touch samples taken after opening, areas with high diversity had more potential external seeds (long-term patients and clinical samples), and areas with low diversity and had fewer (short-term or newborn patients). Classification models performed at high accuracy and identified biomarkers that could be used for more targeted surveillance and infection control. Though culturing data yielded viability and antibiotic-resistance information, it disproportionately detected the presence of genera relative to 16S data. This difference reinforces the utility of 16S sequencing in profiling hospital microbiomes. By examining the microbiome over time and in multiple areas, we identified potential drivers of the microbial variation within a hospital.

Dietary iron intake has long-term effects on the fecal metabolome and microbiome

Iron is essential for life, but its imbalances can lead to severe health implications. Iron deficiency is the most common nutrient disorder worldwide, and iron dysregulation in early life has been found to cause long-lasting behavioral, cognitive, and neural effects. However, little is known about the effects of dietary iron on gut microbiome function and metabolism. In this study, we sought to investigate the impact of dietary iron on the fecal metabolome and microbiome by using mice fed with three diets with different iron content: an iron deficient, an iron sufficient (standard), and an iron overload diet for 7 weeks. Additionally, we sought to understand whether any observed changes would persist past the 7-week period of diet intervention. To assess this, all feeding groups were switched to a standard diet, and this feeding continued for an additional 7 weeks. Analysis of the fecal metabolome revealed that iron overload and deficiency significantly alter levels of peptides, nucleic acids, and lipids, including di- and tri-peptides containing branched-chain amino acids, inosine and guanosine, and several microbial conjugated bile acids. The observed changes in the fecal metabolome persist long after the switch back to a standard diet, with the cecal gut microbiota composition and function of each group distinct after the 7-week standard diet wash-out. Our results highlight the enduring metabolic consequences of nutritional imbalances, mediated by both the host and gut microbiome, which persist after returning to the original standard diets.

Evaluation of the safety and efficacy of fecal microbiota transplantations in bottlenose dolphins (Tursiops truncatus) using metagenomic sequencing

AIMS

Gastrointestinal disease is a leading cause of morbidity in bottlenose dolphins (Tursiops truncatus) under managed care. Fecal microbiota transplantation (FMT) holds promise as a therapeutic tool to restore gut microbiota without antibiotic use. This prospective clinical study aimed to develop a screening protocol for FMT donors to ensure safety, determine an effective FMT administration protocol for managed dolphins, and evaluate the efficacy of FMTs in four recipient dolphins.

METHODS AND RESULTS

Comprehensive health monitoring was performed on donor and recipient dolphins. Fecal samples were collected before, during, and after FMT therapy. Screening of donor and recipient fecal samples was accomplished by in-house and reference lab diagnostic tests. Shotgun metagenomics was used for sequencing. Following FMT treatment, all four recipient communities experienced engraftment of novel microbial species from donor communities. Engraftment coincided with resolution of clinical signs and a sustained increase in alpha diversity.

CONCLUSION

The donor screening protocol proved to be safe in this study and no adverse effects were observed in four recipient dolphins. Treatment coincided with improvement in clinical signs.

Development and management of gastrointestinal symptoms in long-term COVID-19

Background

Emerging evidence reveals that SARS-CoV-2 possesses the capability to disrupt the gastrointestinal (GI) homeostasis, resulting in the long-term symptoms such as loss of appetite, diarrhea, gastroesophageal reflux, and nausea. In the current review, we summarized recent reports regarding the long-term effects of COVID-19 (long COVID) on the gastrointestine.

Objective

To provide a narrative review of abundant clinical evidence regarding the development and management of long-term GI symptoms in COVID-19 patients.

Results

Long-term persistent digestive symptoms are exhibited in a majority of long-COVID patients. SARS-CoV-2 infection of intestinal epithelial cells, cytokine storm, gut dysbiosis, therapeutic drugs, psychological factors and exacerbation of primary underlying diseases lead to long-term GI symptoms in COVID-19 patients. Interventions like probiotics, prebiotics, fecal microbiota transplantation, and antibiotics are proved to be beneficial in preserving intestinal microecological homeostasis and alleviating GI symptoms.

Conclusion

Timely diagnosis and treatment of GI symptoms in long-COVID patients hold great significance as they may contribute to the mitigation of severe conditions and ultimately lead to the improvement of outcomes of the patients.

Contamination source modeling with SCRuB improves cancer phenotype prediction from microbiome data

Sequencing-based approaches for the analysis of microbial communities are susceptible to contamination, which could mask biological signals or generate artifactual ones. Methods for in silico decontamination using controls are routinely used, but do not make optimal use of information shared across samples and cannot handle taxa that only partially originate in contamination or leakage of biological material into controls. Here we present Source tracking for Contamination Removal in microBiomes (SCRuB), a probabilistic in silico decontamination method that incorporates shared information across multiple samples and controls to precisely identify and remove contamination. We validate the accuracy of SCRuB in multiple data-driven simulations and experiments, including induced contamination, and demonstrate that it outperforms state-of-the-art methods by an average of 15-20 times. We showcase the robustness of SCRuB across multiple ecosystems, data types and sequencing depths. Demonstrating its applicability to microbiome research, SCRuB facilitates improved predictions of host phenotypes, most notably the prediction of treatment response in melanoma patients using decontaminated tumor microbiome data.

Mild SARS-CoV-2 infection results in long-lasting microbiota instability

Viruses targeting mammalian cells can indirectly alter the gut microbiota, potentially compounding their phenotypic effects. Multiple studies have observed a disrupted gut microbiota in severe cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection that require hospitalization. Yet, despite demographic shifts in disease severity resulting in a large and continuing burden of non-hospitalized infections, we still know very little about the impact of mild SARS-CoV-2 infection on the gut microbiota in the outpatient setting. To address this knowledge gap, we longitudinally sampled 14 SARS-CoV-2-positive subjects who remained outpatient and 4 household controls. SARS-CoV-2 cases exhibited a significantly less stable gut microbiota relative to controls. These results were confirmed and extended in the K18-humanized angiotensin-converting enzyme 2 mouse model, which is susceptible to SARS-CoV-2 infection. All of the tested SARS-CoV-2 variants significantly disrupted the mouse gut microbiota, including USA-WA1/2020 (the original variant detected in the USA), Delta, and Omicron. Surprisingly, despite the fact that the Omicron variant caused the least severe symptoms in mice, it destabilized the gut microbiota and led to a significant depletion in Akkermansia muciniphila. Furthermore, exposure of wild-type C57BL/6J mice to SARS-CoV-2 disrupted the gut microbiota in the absence of severe lung pathology. IMPORTANCE Taken together, our results demonstrate that even mild cases of SARS-CoV-2 can disrupt gut microbial ecology. Our findings in non-hospitalized individuals are consistent with studies of hospitalized patients, in that reproducible shifts in gut microbial taxonomic abundance in response to SARS-CoV-2 have been difficult to identify. Instead, we report a long-lasting instability in the gut microbiota. Surprisingly, our mouse experiments revealed an impact of the Omicron variant, despite producing the least severe symptoms in genetically susceptible mice, suggesting that despite the continued evolution of SARS-CoV-2, it has retained its ability to perturb the intestinal mucosa. These results will hopefully renew efforts to study the mechanisms through which Omicron and future SARS-CoV-2 variants alter gastrointestinal physiology, while also considering the potentially broad consequences of SARS-CoV-2-induced microbiota instability for host health and disease.

CRISPR arrays as high-resolution markers to track microbial transmission during influenza infection

BACKGROUND

Disruption of the microbial community in the respiratory tract due to infections, like influenza, could impact transmission of bacterial pathogens. Using samples from a household study, we determined whether metagenomic-type analyses of the microbiome provide the resolution necessary to track transmission of airway bacteria. Microbiome studies have shown that the microbial community across various body sites tends to be more similar between individuals who cohabit in the same household than between individuals from different households. We tested whether there was increased sharing of bacteria from the airways within households with influenza infections as compared to control households with no influenza.

RESULTS

We obtained 221 respiratory samples that were collected from 54 individuals at 4 to 5 time points across 10 households, with and without influenza infection, in Managua, Nicaragua. From these samples, we generated metagenomic (whole genome shotgun sequencing) datasets to profile microbial taxonomy. Overall, specific bacteria and phages were differentially abundant between influenza positive households and control (no influenza infection) households, with bacteria like Rothia, and phages like Staphylococcus P68virus that were significantly enriched in the influenza-positive households. We identified CRISPR spacers detected in the metagenomic sequence reads and used these to track bacteria transmission within and across households. We observed a clear sharing of bacterial commensals and pathobionts, such as Rothia, Neisseria, and Prevotella, within and between households. However, due to the relatively small number of households in our study, we could not determine if there was a correlation between increased bacterial transmission and influenza infection.

CONCLUSION

We observed that airway microbial composition differences across households were associated with what appeared to be different susceptibility to influenza infection. We also demonstrate that CRISPR spacers from the whole microbial community can be used as markers to study bacterial transmission between individuals. Although additional evidence is needed to study transmission of specific bacterial strains, we observed sharing of respiratory commensals and pathobionts within and across households. Video Abstract.

A microbiome-targeting fibre-enriched nutritional formula is well tolerated and improves quality of life and haemoglobin A1c in type 2 diabetes: A double-blind, randomized, placebo-controlled trial

AIMS

To investigate a prebiotic fibre-enriched nutritional formula on health-related quality of life and metabolic control in type 2 diabetes.

MATERIALS AND METHODS

This was a 12-week, double-blind, placebo-controlled study with an unblinded dietary advice only comparator arm. Participants were randomized 2:1:1 to a prebiotic fibre-enriched nutritional formula (Active), a placebo fibre-absent nutritional formula (Placebo), or non-blinded dietary advice alone (Diet). Primary endpoint was change in core Type 2 Diabetes Distress Assessment System (cT2-DDAS) at week 12. Glycated haemoglobin (HbA1c) change was a key secondary endpoint.

RESULTS

In total, 192 participants were randomized. Mean age was 54.3 years, HbA1c 7.8%, and body mass index 35.9 kg/m2 . At week 12, cT2-DDAS reduced significantly in Active versus Placebo (-0.4, p = .03), and HbA1c was reduced significantly in Active vs Placebo (-0.64%, p = .01). Gut microbiome sequencing revealed that the relative abundance of two species of butyrate-producing bacteria (Roseburia faecis and Anaerostipes hadrus) increased significantly in Active vs. Placebo.

CONCLUSIONS

A microbiome-targeting nutritional formula significantly improved cT2-DDAS and HbA1c, suggesting the potential for prebiotic fibre as a complement to lifestyle and/or pharmaceutical interventions for managing type 2 diabetes.

Understanding the Relationship of the Human Bacteriome with COVID-19 Severity and Recovery

The Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) first emerged in 2019 in China and has resulted in millions of human morbidities and mortalities across the globe. Evidence has been provided that this novel virus originated in animals, mutated, and made the cross-species jump to humans. At the time of this communication, the Coronavirus disease (COVID-19) may be on its way to an endemic form; however, the threat of the virus is more for susceptible (older and immunocompromised) people. The human body has millions of bacterial cells that influence health and disease. As a consequence, the bacteriomes in the human body substantially influence human health and disease. The bacteriomes in the body and the immune system seem to be in constant association during bacterial and viral infections. In this review, we identify various bacterial spp. In major bacteriomes (oral, nasal, lung, and gut) of the body in healthy humans and compare them with dysbiotic bacteriomes of COVID-19 patients. We try to identify key bacterial spp. That have a positive effect on the functionality of the immune system and human health. These select bacterial spp. Could be used as potential probiotics to counter or prevent COVID-19 infections. In addition, we try to identify key metabolites produced by probiotic bacterial spp. That could have potential anti-viral effects against SARS-CoV-2. These metabolites could be subject to future therapeutic trials to determine their anti-viral efficacies.

Shaping the subway microbiome through probiotic-based sanitation during the COVID-19 emergency: a pre-post case-control study

BACKGROUND

The COVID-19 pandemic has highlighted the extent to which the public transportation environment, such as in subways, may be important for the transmission of potential pathogenic microbes among humans, with the possibility of rapidly impacting large numbers of people. For these reasons, sanitation procedures, including massive use of chemical disinfection, were mandatorily introduced during the emergency and remain in place. However, most chemical disinfectants have temporary action and a high environmental impact, potentially enhancing antimicrobial resistance (AMR) of the treated microbes. By contrast, a biological and eco-sustainable probiotic-based sanitation (PBS) procedure was recently shown to stably shape the microbiome of treated environments, providing effective and long-term control of pathogens and AMR spread in addition to activity against SARS-CoV-2, the causative agent of COVID-19. Our study aims to assess the applicability and impact of PBS compared with chemical disinfectants based on their effects on the surface microbiome of a subway environment.

RESULTS

The train microbiome was characterized by both culture-based and culture-independent molecular methods, including 16S rRNA NGS and real-time qPCR microarray, for profiling the train bacteriome and its resistome and to identify and quantify specific human pathogens. SARS-CoV-2 presence was also assessed in parallel using digital droplet PCR. The results showed a clear and significant decrease in bacterial and fungal pathogens (p < 0.001) as well as of SARS-CoV-2 presence (p < 0.01), in the PBS-treated train compared with the chemically disinfected control train. In addition, NGS profiling evidenced diverse clusters in the population of air vs. surface while demonstrating the specific action of PBS against pathogens rather than the entire train bacteriome.

CONCLUSIONS

The data presented here provide the first direct assessment of the impact of different sanitation procedures on the subway microbiome, allowing a better understanding of its composition and dynamics and showing that a biological sanitation approach may be highly effective in counteracting pathogens and AMR spread in our increasingly urbanized and interconnected environment. Video Abstract.

Characterization of SARS-CoV-2 Distribution and Microbial Succession in a Clinical Microbiology Testing Facility during the SARS-CoV-2 Pandemic

The exchange of microbes between humans and the built environment is a dynamic process that has significant impact on health. Most studies exploring the microbiome of the built environment have been predicated on improving our understanding of pathogen emergence, persistence, and transmission. Previous studies have demonstrated that SARS-CoV-2 presence significantly correlates with the proportional abundance of specific bacteria on surfaces in the built environment. However, in these studies, SARS-CoV-2 originated from infected patients. Here, we perform a similar assessment for a clinical microbiology lab while staff were handling SARS-CoV-2 infected samples. The goal of this study was to understand the distribution and dynamics of microbial population on various surfaces within different sections of a clinical microbiology lab during a short period of 2020 Coronavirus disease (COVID-19) pandemic. We sampled floors, benches, and sinks in 3 sections (bacteriology, molecular microbiology, and COVID) of an active clinical microbiology lab over a 3-month period. Although floor samples harbored SARS-CoV-2, it was rarely identified on other surfaces, and bacterial diversity was significantly greater on floors than sinks and benches. The floors were primarily colonized by bacteria common to natural environments (e.g., soils), and benchtops harbored a greater proportion of human-associated microbes, including Staphylococcus and Streptococcus. Finally, we show that the microbial composition of these surfaces did not change over time and remained stable. Despite finding viruses on the floors, no lab-acquired infections were reported during the study period, which suggests that lab safety protocols and sanitation practices were sufficient to prevent pathogen exposures. IMPORTANCE For decades, diagnostic clinical laboratories have been an integral part of the health care systems that perform diagnostic tests on patient's specimens in bulk on a regular basis. Understanding their microbiota should assist in designing and implementing disinfection, and cleaning regime in more effective way. To our knowledge, there is a lack of information on the composition and dynamics of microbiota in the clinical laboratory environments, and, through this study, we have tried to fill that gap. This study has wider implications as understanding the makeup of microbes on various surfaces within clinical laboratories could help identify any pathogenic bacterial taxa that could have colonized these surfaces, and might act as a potential source of laboratory-acquired infections. Mapping the microbial community within these built environments may also be critical in assessing the reliability of laboratory safety and sanitation practices to lower any potential risk of exposures to health care workers.

Safer at school early alert: an observational study of wastewater and surface monitoring to detect COVID-19 in elementary schools

Background

Schools are high-risk settings for SARS-CoV-2 transmission, but necessary for children's educational and social-emotional wellbeing. Previous research suggests that wastewater monitoring can detect SARS-CoV-2 infections in controlled residential settings with high levels of accuracy. However, its effective accuracy, cost, and feasibility in non-residential community settings is unknown.

Methods

The objective of this study was to determine the effectiveness and accuracy of community-based passive wastewater and surface (environmental) surveillance to detect SARS-CoV-2 infection in neighborhood schools compared to weekly diagnostic (PCR) testing. We implemented an environmental surveillance system in nine elementary schools with 1700 regularly present staff and students in southern California. The system was validated from November 2020 to March 2021.

Findings

In 447 data collection days across the nine sites 89 individuals tested positive for COVID-19, and SARS-CoV-2 was detected in 374 surface samples and 133 wastewater samples. Ninety-three percent of identified cases were associated with an environmental sample (95% CI: 88%-98%); 67% were associated with a positive wastewater sample (95% CI: 57%-77%), and 40% were associated with a positive surface sample (95% CI: 29%-52%). The techniques we utilized allowed for near-complete genomic sequencing of wastewater and surface samples.

Interpretation

Passive environmental surveillance can detect the presence of COVID-19 cases in non-residential community school settings with a high degree of accuracy.

Funding

County of San Diego, Health and Human Services Agency, National Institutes of Health, National Science Foundation, Centers for Disease Control.

Wastewater and surface monitoring to detect COVID-19 in elementary school settings: The Safer at School Early Alert project

Background

Schools are high-risk settings for SARS-CoV-2 transmission, but necessary for children's educational and social-emotional wellbeing. Previous research suggests that wastewater monitoring can detect SARS-CoV-2 infections in controlled residential settings with high levels of accuracy. However, its effective accuracy, cost, and feasibility in non-residential community settings is unknown.

Methods

The objective of this study was to determine the effectiveness and accuracy of community-based passive wastewater and surface (environmental) surveillance to detect SARS-CoV-2 infection in neighborhood schools compared to weekly diagnostic (PCR) testing. We implemented an environmental surveillance system in nine elementary schools with 1700 regularly present staff and students in southern California. The system was validated from November 2020 - March 2021.

Findings

In 447 data collection days across the nine sites 89 individuals tested positive for COVID-19, and SARS-CoV-2 was detected in 374 surface samples and 133 wastewater samples. Ninety-three percent of identified cases were associated with an environmental sample (95% CI: 88% - 98%); 67% were associated with a positive wastewater sample (95% CI: 57% - 77%), and 40% were associated with a positive surface sample (95% CI: 29% - 52%). The techniques we utilized allowed for near-complete genomic sequencing of wastewater and surface samples.

Interpretation

Passive environmental surveillance can detect the presence of COVID-19 cases in non-residential community school settings with a high degree of accuracy.

Funding

County of San Diego, Health and Human Services Agency, National Institutes of Health, National Science Foundation, Centers for Disease Control.

The spatial and temporal distribution of SARS-CoV-2 from the built environment of COVID-19 patient rooms: A multicentre prospective study

BACKGROUND

SARS-CoV-2 can be detected from the built environment (e.g., floors), but it is unknown how the viral burden surrounding an infected patient changes over space and time. Characterizing these data can help advance our understanding and interpretation of surface swabs from the built environment.

METHODS

We conducted a prospective study at two hospitals in Ontario, Canada between January 19, 2022 and February 11, 2022. We performed serial floor sampling for SARS-CoV-2 in rooms of patients newly hospitalized with COVID-19 in the past 48 hours. We sampled the floor twice daily until the occupant moved to another room, was discharged, or 96 hours had elapsed. Floor sampling locations included 1 metre (m) from the hospital bed, 2 m from the hospital bed, and at the room's threshold to the hallway (typically 3 to 5 m from the hospital bed). The samples were analyzed for the presence of SARS-CoV-2 using quantitative reverse transcriptase polymerase chain reaction (RT-qPCR). We calculated the sensitivity of detecting SARS-CoV-2 in a patient with COVID-19, and we evaluated how the percentage of positive swabs and the cycle threshold of the swabs changed over time. We also compared the cycle threshold between the two hospitals.

RESULTS

Over the 6-week study period we collected 164 floor swabs from the rooms of 13 patients. The overall percentage of swabs positive for SARS-CoV-2 was 93% and the median cycle threshold was 33.4 (interquartile range [IQR]: 30.8, 37.2). On day 0 of swabbing the percentage of swabs positive for SARS-CoV-2 was 88% and the median cycle threshold was 33.6 (IQR: 31.8, 38.2) compared to swabs performed on day 2 or later where the percentage of swabs positive for SARS-CoV-2 was 98% and the cycle threshold was 33.2 (IQR: 30.6, 35.6). We found that viral detection did not change with increasing time (since the first sample collection) over the sampling period, Odds Ratio (OR) 1.65 per day (95% CI 0.68, 4.02; p = 0.27). Similarly, viral detection did not change with increasing distance from the patient's bed (1 m, 2 m, or 3 m), OR 0.85 per metre (95% CI 0.38, 1.88; p = 0.69). The cycle threshold was lower (i.e., more virus) in The Ottawa Hospital (median quantification cycle [Cq] 30.8) where floors were cleaned once daily compared to the Toronto hospital (median Cq 37.2) where floors were cleaned twice daily.

CONCLUSIONS

We were able to detect SARS-CoV-2 on the floors in rooms of patients with COVID-19. The viral burden did not vary over time or by distance from the patient's bed. These results suggest floor swabbing for the detection of SARS-CoV-2 in a built environment such as a hospital room is both accurate and robust to variation in sampling location and duration of occupancy.

Evaluation of the gut microbiome associated with COVID-19

Introduction

In 2019, a new virus from the coronavirus family called SARS-CoV-2, infected populations throughout the world. Coronavirus disease 2019 (COVID-19), an illness induced by this virus, attacks vital organs in the body, such as the respiratory system and the gastrointestinal tract. Recent studies have confirmed changes in the gut microbiome caused by the COVID-19 disease. We examined the alteration of the gut microbiome in COVID-19 patients compared to healthy individuals.

Materials and methods

in this study, the 16s metagenomics dataset, publicly available in the Sequence Read Archive (SRA) database, was used for analysis (accession number PRJNA636824). The analysis processes were performed using the CLC Microbial Genomics Module 20.1.1 (Qiagen). At first, the sequence reads of samples were trimmed and classified into operational taxonomic units (OTUs) with 97% similarity and then assigned to the Greengenes reference database (v138). Differential abundance analysis was used to determine statistically significant differences in OTUs between COVID-19 and healthy groups. Next, biodiversity analyses including the alpha diversity (intragroup diversity) and beta diversity (intergroup diversity) using defined indexes were estimated. Then, the co-occurrence network at the species level was constructed using the Pearson correlation coefficient calculation between pairs of OTUs in R software and visualized using Cytoscape software. Ultimately, the hub OTUs at the species level were identified using the cytoHubba plugin of Cytoscape based on Maximal Clique Centrality (MCC) algorithm.

Results

The results of the metagenomic analysis revealed that the intestinal microbiome in healthy individuals has a higher biodiversity compared to COVID-19 patients. Indeed, healthy people also have a higher percentage of beneficial bacteria such as bifidobacteria adolescentis compared to COVID-19 patients; in contrast, COVID-19 patients have higher levels of opportunistic and pathogenic bacteria such as Streptococcus anginosus than healthy people. Also, by constructing a co-occurrence network at the species level, Bifidobacterium longum in the healthy group and Veillonella parvulain the COVID-19 group were found as hub species.

Conclusion

The results of this study shed light on the relationship between the gut microbiome and COVID-19. These results could be helpful for understanding the pathogenesis, clinical features, and treatment of COVID-9.

Mild SARS-CoV-2 infection results in long-lasting microbiota instability

Viruses targeting mammalian cells can indirectly alter the gut microbiota, potentially compounding their phenotypic effects. Multiple studies have observed a disrupted gut microbiota in severe cases of SARS-CoV-2 infection that require hospitalization. Yet, despite demographic shifts in disease severity resulting in a large and continuing burden of non-hospitalized infections, we still know very little about the impact of mild SARS-CoV-2 infection on the gut microbiota in the outpatient setting. To address this knowledge gap, we longitudinally sampled 14 SARS-CoV-2 positive subjects who remained outpatient and 4 household controls. SARS-CoV-2 cases exhibited a significantly less stable gut microbiota relative to controls, as long as 154 days after their positive test. These results were confirmed and extended in the K18-hACE2 mouse model, which is susceptible to SARS-CoV-2 infection. All of the tested SARS-CoV-2 variants significantly disrupted the mouse gut microbiota, including USA-WA1/2020 (the original variant detected in the United States), Delta, and Omicron. Surprisingly, despite the fact that the Omicron variant caused the least severe symptoms in mice, it destabilized the gut microbiota and led to a significant depletion in Akkermansia muciniphila . Furthermore, exposure of wild-type C57BL/6J mice to SARS-CoV-2 disrupted the gut microbiota in the absence of severe lung pathology.

IMPORTANCE

Taken together, our results demonstrate that even mild cases of SARS-CoV-2 can disrupt gut microbial ecology. Our findings in non-hospitalized individuals are consistent with studies of hospitalized patients, in that reproducible shifts in gut microbial taxonomic abundance in response to SARS-CoV-2 have been difficult to identify. Instead, we report a long-lasting instability in the gut microbiota. Surprisingly, our mouse experiments revealed an impact of the Omicron variant, despite producing the least severe symptoms in genetically susceptible mice, suggesting that despite the continued evolution of SARS-CoV-2 it has retained its ability to perturb the intestinal mucosa. These results will hopefully renew efforts to study the mechanisms through which Omicron and future SARS-CoV-2 variants alter gastrointestinal physiology, while also considering the potentially broad consequences of SARS-CoV-2-induced microbiota instability for host health and disease.

Influenza and Pneumococcal Vaccination and the Risk of COVID-19: A Systematic Review and Meta-Analysis

A number of studies have investigated the potential on-specific effects of some routinely administered vaccines (e.g., influenza, pneumococcal) on COVID-19 related outcomes, with contrasting results. In order to elucidate this discrepancy, we conducted a systematic review and meta-analysis to assess the association between seasonal influenza vaccination and pneumococcal vaccination with SARS-CoV-2 infection and its clinical outcomes. PubMed and medRxiv databases were searched up to April 2022. A random effects model was used in the meta-analysis to pool odds ratio (OR) and adjusted estimates with 95% confidence intervals (CIs). Heterogeneity was quantitatively assessed using the Cochran's Q and the I2 index. Subgroup analysis, sensitivity analysis and assessment of publication bias were performed for all outcomes. In total, 38 observational studies were included in the meta-analysis and there was substantial heterogeneity. Influenza and pneumococcal vaccination were associated with lower risk of SARS-CoV-2 infection (OR: 0.80, 95% CI: 0.75-0.86 and OR: 0.70, 95% CI: 0.57-0.88, respectively). Regarding influenza vaccination, it seems that the majority of studies did not properly adjust for all potential confounders, so when the analysis was limited to studies that adjusted for age, gender, comorbidities and socioeconomic indices, the association diminished. This is not the case regarding pneumococcal vaccination, for which even after adjustment for such factors the association persisted. Regarding harder endpoints such as ICU admission and death, current data do not support the association. Possible explanations are discussed, including trained immunity, inadequate matching for socioeconomic indices and possible coinfection.

The role of multi-omics in the diagnosis of COVID-19 and the prediction of new therapeutic targets

The global pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus causing COVID-19, has led to more than 170 million confirmed cases in 223 countries and regions, claiming 3,872,457 lives. Some patients with COVID-19 have mild clinical symptoms despite severe respiratory failure, which greatly increases the difficulty of diagnosis and treatment. It is therefore necessary to identify biological characteristics of SARS-CoV-2, screen novel diagnostic and prognostic biomarkers, as well as to explore potential therapeutic targets for COVID-19. In this comprehensive review, we discuss the current published literature on COVID-19. We find that the comprehensive application of genomics, transcriptomics, proteomics and metabolomics is becoming increasingly important in the treatment of COVID-19. Multi-omics analysis platforms are expected to revolutionize the diagnosis and classification of COVID-19. This review aims to provide a reference for diagnosis, surveillance and clinical decision making related to COVID-19.

Persistence of SARS-CoV-2 on surfaces and relevance to the food industry

Determining the prevalence and persistence of viruses outside the human host aids our ability to characterize exposure risk across multiple transmission pathways. Since 2020, the Coronavirus Disease 2019 pandemic has resulted in a surge of research regarding severe acute respiratory syndrome-coronavirus-type 2 (SARS-CoV-2) and its potential to spread via direct and indirect contact transmission routes. Here, the authors discuss the current state of the science concerning SARS-CoV-2 transmission via contaminated surfaces and its persistence on environmental surfaces. This review aims to provide the reader with an overview of the currently published SARS-CoV-2 persistence studies, factors impacting persistence, guidelines for performing persistence studies, limitation of current data, and future directions for assessing SARS-CoV-2 persistence on fomites.

Simultaneous monitoring of SARS-CoV-2 and bacterial profiles from the air of hospital environments with COVID-19-affected patients

The SARS-CoV-2 presence and the bacterial community profile in air samples collected at the Intensive Care Unit (ICU) of the Operational Unit of Infectious Diseases of Santa Caterina Novella Hospital in Galatina (Lecce, Italy) have been evaluated in this study. Air samplings were performed in different rooms of the ICU ward with and without COVID-19 patients. No sample was found positive to SARS-CoV-2, according to Allplex 2019-nCoV Assay. The airborne bacterial community profiles determined by the 16S rRNA gene metabarcoding approach up to the species level were characterized by richness and biodiversity indices, Spearman correlation coefficients, and Principal Coordinate Analysis. Pathogenic and non-pathogenic bacterial species, also detected in outdoor air samples, were found in all collected indoor samples. Staphylococcus pettenkoferi, Corynebacterium tuberculostearicum, and others coagulase-negative staphylococci, detected at high relative abundances in all the patients' rooms, were the most abundant pathogenic species. The highest mean relative abundance of S. pettenkoferi and C. tuberculostearicum suggested that they were likely the main pathogens of COVID-19 patients at the ICU ward of this study. The identification of nosocomial pathogens representing potential patients' risks in ICU COVID-19 rooms and the still controversial airborne transmission of the SARS-CoV-2 are the main contributions of this study.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10453-022-09754-7.

Teaching genomics to life science undergraduates using cloud computing platforms with open datasets

The final year of a biochemistry degree is usually a time to experience research. However, laboratory-based research projects were not possible during COVID-19. Instead, we used open datasets to provide computational research projects in metagenomics to biochemistry undergraduates (80 students with limited computing experience). We aimed to give the students a chance to explore any dataset, rather than use a small number of artificial datasets (~60 published datasets were used). To achieve this, we utilized Google Colaboratory (Colab), a virtual computing environment. Colab was used as a framework to retrieve raw sequencing data (analyzed with QIIME2) and generate visualizations. Setting up the environment requires no prior experience; all students have the same drive structure and notebooks can be shared (for synchronous sessions). We also used the platform to combine multiple datasets, perform a meta-analysis, and allowed the students to analyze large datasets with 1000s of subjects and factors. Projects that required increased computational resources were integrated with Google Cloud Compute. In future, all research projects can include some aspects of reanalyzing public data, providing students with data science experience. Colab is also an excellent environment in which to develop data skills in multiple languages (e.g., Perl, Python, Julia).

The Relationship Between Pediatric Gut Microbiota and SARS-CoV-2 Infection

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.

SARS-CoV-2 Distribution in Residential Housing Suggests Contact Deposition and Correlates with Rothia sp

Monitoring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on surfaces is emerging as an important tool for identifying past exposure to individuals shedding viral RNA. Our past work demonstrated that SARS-CoV-2 reverse transcription-quantitative PCR (RT-qPCR) signals from surfaces can identify when infected individuals have touched surfaces and when they have been present in hospital rooms or schools. However, the sensitivity and specificity of surface sampling as a method for detecting the presence of a SARS-CoV-2 positive individual, as well as guidance about where to sample, has not been established. To address these questions and to test whether our past observations linking SARS-CoV-2 abundance to Rothia sp. in hospitals also hold in a residential setting, we performed a detailed spatial sampling of three isolation housing units, assessing each sample for SARS-CoV-2 abundance by RT-qPCR, linking the results to 16S rRNA gene amplicon sequences (to assess the bacterial community at each location), and to the Cq value of the contemporaneous clinical test. Our results showed that the highest SARS-CoV-2 load in this setting is on touched surfaces, such as light switches and faucets, but a detectable signal was present in many untouched surfaces (e.g., floors) that may be more relevant in settings, such as schools where mask-wearing is enforced. As in past studies, the bacterial community predicts which samples are positive for SARS-CoV-2, with Rothia sp. showing a positive association. IMPORTANCE Surface sampling for detecting SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), is increasingly being used to locate infected individuals. We tested which indoor surfaces had high versus low viral loads by collecting 381 samples from three residential units where infected individuals resided, and interpreted the results in terms of whether SARS-CoV-2 was likely transmitted directly (e.g., touching a light switch) or indirectly (e.g., by droplets or aerosols settling). We found the highest loads where the subject touched the surface directly, although enough virus was detected on indirectly contacted surfaces to make such locations useful for sampling (e.g., in schools, where students did not touch the light switches and also wore masks such that they had no opportunity to touch their face and then the object). We also documented links between the bacteria present in a sample and the SARS-CoV-2 virus, consistent with earlier studies.

Fomite Transmission Follows Invasion Ecology Principles

The invasion ecology principles illustrated in many ecosystems have not yet been explored in the context of fomite transmission. We hypothesized that invaders in fomite transmission are trackable, are neutrally distributed between hands and environmental surfaces, and exhibit a proximity effect. To test this hypothesis, a surrogate invader, Lactobacillus delbrueckii subsp. bulgaricus, was spread by a root carrier in an office housing more than 20 participants undertaking normal activities, and the microbiotas on skin and environmental surfaces were analyzed before and after invasion. First, we found that the invader was trackable. Its identity and emission source could be determined using microbial-interaction networks, and the root carrier could be identified using a rank analysis. Without prior information, L. bulgaricus could be identified as the invader emitted from a source that exclusively contained the invader, and the probable root carrier could be located. In addition to the single-taxon invasion by L. bulgaricus, multiple-taxon invasion was observed, as genera from sputum/saliva exhibited co-occurrence relationships on skin and environmental surfaces. Second, the invader had a below-neutral distribution in a neutral community model, suggesting that hands accrued heavier invader contamination than environmental surfaces. Third, a proximity effect was observed on a surface touch network. Invader contamination on surfaces decreased with increasing geodesic distance from the hands of the carrier, indicating that the carrier’s touching behaviors were the main driver of fomite transmission. Taken together, these results demonstrate the invasion ecology principles in fomite transmission and provide a general basis for the management of ecological fomite transmission.

IMPORTANCE Fomite transmission contributes to the spread of many infectious diseases. However, pathogens in fomite transmission typically are either investigated individually without considering the context of native microbiotas or investigated in a nondiscriminatory way from the dispersal of microbiotas. In this study, we adopted an invasion ecology framework in which we considered pathogens as invaders, the surface environment as an ecosystem, and human behaviors as the driver of microbial dispersal. With this approach, we assessed the ability of quantitative ecological theories to track and forecast pathogen movements in fomite transmission. By uncovering the relationships between the invader and native microbiotas and between human behaviors and invader/microbiota dispersal, we demonstrated that fomite transmission follows idiosyncratic invasion ecology principles. Our findings suggest that attempts to manage fomite transmission for public health purposes should focus on the microbial communities and anthropogenic factors involved, in addition to the pathogens.

Fungal, parasitological, and bacterial coinfection in a severely ill COVID-19 patient in Peru

COVID-19 patients are prone to coinfections during their hospitalization. These coinfections are challenging as they involve longer hospital stays, high costs, and higher risk of mortality. Here, we present a case of a patient with multi-infection by resistant parasites, fungi, and bacteria during his hospitalization in a hospital in Lima, Peru.

Respiratory tract infections and gut microbiome modifications: A systematic review

Respiratory tract infections (RTIs) are extremely common and can cause gastrointestinal tract symptoms and changes to the gut microbiota, yet these effects are poorly understood. We conducted a systematic review to evaluate the reported evidence of gut microbiome alterations in patients with a RTI compared to healthy controls (PROSPERO: CRD42019138853). We systematically searched Medline, Embase, Web of Science, Cochrane and the Clinical Trial Database for studies published between January 2015 and June 2021. Studies were eligible for inclusion if they were human cohorts describing the gut microbiome in patients with an RTI compared to healthy controls and the infection was caused by a viral or bacterial pathogen. Dual data screening and extraction with narrative synthesis was performed. We identified 1,593 articles and assessed 11 full texts for inclusion. Included studies (some nested) reported gut microbiome changes in the context of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) (n = 5), influenza (H1N1 and H7N9) (n = 2), Tuberculosis (TB) (n = 4), Community-Acquired Pneumonia CAP (n = 2) and recurrent RTIs (rRTI) (n = 1) infections. We found studies of patients with an RTI compared to controls reported a decrease in gut microbiome diversity (Shannon) of 1.45 units (95% CI, 0.15-2.50 [p, <0.0001]) and a lower abundance of taxa (p, 0.0086). Meta-analysis of the Shannon value showed considerable heterogeneity between studies (I2, 94.42). Unbiased analysis displayed as a funnel plot revealed a depletion of Lachnospiraceae, Ruminococcaceae and Ruminococcus and enrichment of Enterococcus. There was an important absence in the lack of cohort studies reporting gut microbiome changes and high heterogeneity between studies may be explained by variations in microbiome methods and confounder effects. Further human cohort studies are needed to understand RTI-induced gut microbiome changes to better understand interplay between microbes and respiratory health.

SARS-CoV-2 detection from the built environment and wastewater and its use for hospital surveillance

Patients hospitalized with SARS-CoV-2 infections are major contributors to morbidity and mortality in health care settings. Our understanding of the distribution of this virus in the built health care environment and wastewater, and relationship to disease burden, is limited. We performed a prospective multi-center study of environmental sampling of SARS-CoV-2 from hospital surfaces and wastewater and evaluated their relationships with regional and hospital COVID-19 burden. We validated a qPCR-based approach to surface sampling and collected swab samples weekly from different locations and surfaces across two tertiary care hospital campuses for a 10-week period during the pandemic, along with wastewater samples. Over the 10-week period, 963 swab samples were collected and analyzed. We found 61 (6%) swabs positive for SARS-CoV-2, with the majority of these ( n = 51) originating from floor samples. Wards that actively managed patients with COVID-19 had the highest frequency of positive samples. Detection frequency in built environment swabs was significantly associated with active cases in the hospital throughout the study. Wastewater viral signal changes appeared to predate change in case burden. Our results indicate that environment sampling for SARS-CoV-2, in particular from floors, may offer a unique and resolved approach to surveillance of COVID-19.

Analysis of SARS-CoV-2 RNA Persistence across Indoor Surface Materials Reveals Best Practices for Environmental Monitoring Programs

Environmental monitoring in public spaces can be used to identify surfaces contaminated by persons with coronavirus disease 2019 (COVID-19) and inform appropriate infection mitigation responses. Research groups have reported detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on surfaces days or weeks after the virus has been deposited, making it difficult to estimate when an infected individual may have shed virus onto a SARS-CoV-2-positive surface, which in turn complicates the process of establishing effective quarantine measures. In this study, we determined that reverse transcription-quantitative PCR (RT-qPCR) detection of viral RNA from heat-inactivated particles experiences minimal decay over 7 days of monitoring on eight out of nine surfaces tested. The properties of the studied surfaces result in RT-qPCR signatures that can be segregated into two material categories, rough and smooth, where smooth surfaces have a lower limit of detection. RT-qPCR signal intensity (average quantification cycle [Cq]) can be correlated with surface viral load using only one linear regression model per material category. The same experiment was performed with untreated viral particles on one surface from each category, with essentially identical results. The stability of RT-qPCR viral signal demonstrates the need to clean monitored surfaces after sampling to establish temporal resolution. Additionally, these findings can be used to minimize the number of materials and time points tested and allow for the use of heat-inactivated viral particles when optimizing environmental monitoring methods. IMPORTANCE Environmental monitoring is an important tool for public health surveillance, particularly in settings with low rates of diagnostic testing. Time between sampling public environments, such as hospitals or schools, and notifying stakeholders of the results should be minimal, allowing decisions to be made toward containing outbreaks of coronavirus disease 2019 (COVID-19). The Safer At School Early Alert program (SASEA) (https://saseasystem.org/), a large-scale environmental monitoring effort in elementary school and child care settings, has processed >13,000 surface samples for SARS-CoV-2, detecting viral signals from 574 samples. However, consecutive detection events necessitated the present study to establish appropriate response practices around persistent viral signals on classroom surfaces. Other research groups and clinical labs developing environmental monitoring methods may need to establish their own correlation between RT-qPCR results and viral load, but this work provides evidence justifying simplified experimental designs, like reduced testing materials and the use of heat-inactivated viral particles.

SARS-CoV-2 Distribution in Residential Housing Suggests Contact Deposition and Correlates with Rothia sp

Monitoring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on surfaces is emerging as an important tool for identifying past exposure to individuals shedding viral RNA. Our past work has demonstrated that SARS-CoV-2 reverse transcription-quantitative PCR (RT-qPCR) signals from surfaces can identify when infected individuals have touched surfaces such as Halloween candy, and when they have been present in hospital rooms or schools. However, the sensitivity and specificity of surface sampling as a method for detecting the presence of a SARS-CoV-2 positive individual, as well as guidance about where to sample, has not been established. To address these questions, and to test whether our past observations linking SARS-CoV-2 abundance to Rothia spp. in hospitals also hold in a residential setting, we performed detailed spatial sampling of three isolation housing units, assessing each sample for SARS-CoV-2 abundance by RT-qPCR, linking the results to 16S rRNA gene amplicon sequences to assess the bacterial community at each location and to the Cq value of the contemporaneous clinical test. Our results show that the highest SARS-CoV-2 load in this setting is on touched surfaces such as light switches and faucets, but detectable signal is present in many non-touched surfaces that may be more relevant in settings such as schools where mask wearing is enforced. As in past studies, the bacterial community predicts which samples are positive for SARS-CoV-2, with Rothia sp. showing a positive association.

IMPORTANCE

Surface sampling for detecting SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), is increasingly being used to locate infected individuals. We tested which indoor surfaces had high versus low viral loads by collecting 381 samples from three residential units where infected individuals resided, and interpreted the results in terms of whether SARS-CoV-2 was likely transmitted directly (e.g. touching a light switch) or indirectly (e.g. by droplets or aerosols settling). We found highest loads where the subject touched the surface directly, although enough virus was detected on indirectly contacted surfaces to make such locations useful for sampling (e.g. in schools, where students do not touch the light switches and also wear masks so they have no opportunity to touch their face and then the object). We also documented links between the bacteria present in a sample and the SARS-CoV-2 virus, consistent with earlier studies.

SARS-CoV-2 Distribution in Residential Housing Suggests Contact Deposition and Correlates with Rothia sp

Monitoring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on surfaces is emerging as an important tool for identifying past exposure to individuals shedding viral RNA. Our past work has demonstrated that SARS-CoV-2 reverse transcription-quantitative PCR (RT-qPCR) signals from surfaces can identify when infected individuals have touched surfaces such as Halloween candy, and when they have been present in hospital rooms or schools. However, the sensitivity and specificity of surface sampling as a method for detecting the presence of a SARS-CoV-2 positive individual, as well as guidance about where to sample, has not been established. To address these questions, and to test whether our past observations linking SARS-CoV-2 abundance to Rothia spp. in hospitals also hold in a residential setting, we performed detailed spatial sampling of three isolation housing units, assessing each sample for SARS-CoV-2 abundance by RT-qPCR, linking the results to 16S rRNA gene amplicon sequences to assess the bacterial community at each location and to the Cq value of the contemporaneous clinical test. Our results show that the highest SARS-CoV-2 load in this setting is on touched surfaces such as light switches and faucets, but detectable signal is present in many non-touched surfaces that may be more relevant in settings such as schools where mask wearing is enforced. As in past studies, the bacterial community predicts which samples are positive for SARS-CoV-2, with Rothia sp. showing a positive association.

IMPORTANCE

Surface sampling for detecting SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), is increasingly being used to locate infected individuals. We tested which indoor surfaces had high versus low viral loads by collecting 381 samples from three residential units where infected individuals resided, and interpreted the results in terms of whether SARS-CoV-2 was likely transmitted directly (e.g. touching a light switch) or indirectly (e.g. by droplets or aerosols settling). We found highest loads where the subject touched the surface directly, although enough virus was detected on indirectly contacted surfaces to make such locations useful for sampling (e.g. in schools, where students do not touch the light switches and also wear masks so they have no opportunity to touch their face and then the object). We also documented links between the bacteria present in a sample and the SARS-CoV-2 virus, consistent with earlier studies.

Dysbiosis and structural disruption of the respiratory microbiota in COVID-19 patients with severe and fatal outcomes

The COVID-19 outbreak has caused over three million deaths worldwide. Understanding the pathology of the disease and the factors that drive severe and fatal clinical outcomes is of special relevance. Studying the role of the respiratory microbiota in COVID-19 is especially important as the respiratory microbiota is known to interact with the host immune system, contributing to clinical outcomes in chronic and acute respiratory diseases. Here, we characterized the microbiota in the respiratory tract of patients with mild, severe, or fatal COVID-19, and compared it to healthy controls and patients with non-COVID-19-pneumonia. We comparatively studied the microbial composition, diversity, and microbiota structure between the study groups and correlated the results with clinical data. We found differences in the microbial composition for COVID-19 patients, healthy controls, and non-COVID-19 pneumonia controls. In particular, we detected a high number of potentially opportunistic pathogens associated with severe and fatal levels of the disease. Also, we found higher levels of dysbiosis in the respiratory microbiota of patients with COVID-19 compared to the healthy controls. In addition, we detected differences in diversity structure between the microbiota of patients with mild, severe, and fatal COVID-19, as well as the presence of specific bacteria that correlated with clinical variables associated with increased risk of mortality. In summary, our results demonstrate that increased dysbiosis of the respiratory tract microbiota in patients with COVID-19 along with a continuous loss of microbial complexity structure found in mild to fatal COVID-19 cases may potentially alter clinical outcomes in patients. Taken together, our findings identify the respiratory microbiota as a factor potentially associated with the severity of COVID-19.

Acute SARS-CoV-2 infection is associated with an increased abundance of bacterial pathogens, including Pseudomonas aeruginosa in the nose

Research conducted on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pathogenesis and coronavirus disease 2019 (COVID-19) generally focuses on the systemic host response, especially that generated by severely ill patients, with few studies investigating the impact of acute SARS-CoV-2 at the site of infection. We show that the nasal microbiome of SARS-CoV-2-positive patients (CoV⁺, n = 68) at the time of diagnosis is unique when compared to CoV⁻ healthcare workers (n = 45) and CoV⁻ outpatients (n = 21). This shift is marked by an increased abundance of bacterial pathogens, including Pseudomonas aeruginosa, which is also positively associated with viral RNA load. Additionally, we observe a robust host transcriptional response in the nasal epithelia of CoV⁺ patients, indicative of an antiviral innate immune response and neuronal damage. These data suggest that the inflammatory response caused by SARS-CoV-2 infection is associated with an increased abundance of bacterial pathogens in the nasal cavity that could contribute to increased incidence of secondary bacterial infections.

Altered oral and gut microbiota and its association with SARS-CoV-2 viral load in COVID-19 patients during hospitalization

The human oral and gut commensal microbes play vital roles in the development and maintenance of immune homeostasis, while its association with susceptibility and severity of SARS-CoV-2 infection is barely understood. In this study, we investigated the dynamics of the oral and intestinal flora before and after the clearance of SARS-CoV-2 in 53 COVID-19 patients, and then examined their microbiome alterations in comparison to 76 healthy individuals. A total of 140 throat swab samples and 81 fecal samples from these COVID-19 patients during hospitalization, and 44 throat swab samples and 32 fecal samples from sex and age-matched healthy individuals were collected and then subjected to 16S rRNA sequencing and viral load inspection. We found that SARS-CoV-2 infection was associated with alterations of the microbiome community in patients as indicated by both alpha and beta diversity indexes. Several bacterial taxa were identified related to SARS-CoV-2 infection, wherein elevated Granulicatella and Rothia mucilaginosa were found in both oral and gut microbiome. The SARS-CoV-2 viral load in those samples was also calculated to identify potential dynamics between COVID-19 and the microbiome. These findings provide a meaningful baseline for microbes in the digestive tract of COVID-19 patients and will shed light on new dimensions for disease pathophysiology, potential microbial biomarkers, and treatment strategies for COVID-19.

Altered oral and gut microbiota and its association with SARS-CoV-2 viral load in COVID-19 patients during hospitalization

The human oral and gut commensal microbes play vital roles in the development and maintenance of immune homeostasis, while its association with susceptibility and severity of SARS-CoV-2 infection is barely understood. In this study, we investigated the dynamics of the oral and intestinal flora before and after the clearance of SARS-CoV-2 in 53 COVID-19 patients, and then examined their microbiome alterations in comparison to 76 healthy individuals. A total of 140 throat swab samples and 81 fecal samples from these COVID-19 patients during hospitalization, and 44 throat swab samples and 32 fecal samples from sex and age-matched healthy individuals were collected and then subjected to 16S rRNA sequencing and viral load inspection. We found that SARS-CoV-2 infection was associated with alterations of the microbiome community in patients as indicated by both alpha and beta diversity indexes. Several bacterial taxa were identified related to SARS-CoV-2 infection, wherein elevated Granulicatella and Rothia mucilaginosa were found in both oral and gut microbiome. The SARS-CoV-2 viral load in those samples was also calculated to identify potential dynamics between COVID-19 and the microbiome. These findings provide a meaningful baseline for microbes in the digestive tract of COVID-19 patients and will shed light on new dimensions for disease pathophysiology, potential microbial biomarkers, and treatment strategies for COVID-19.

Comparison of heat-inactivated and infectious SARS-CoV-2 across indoor surface materials shows comparable RT-qPCR viral signal intensity and persistence

Environmental monitoring in public spaces can be used to identify surfaces contaminated by persons with COVID-19 and inform appropriate infection mitigation responses. Research groups have reported detection of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) on surfaces days or weeks after the virus has been deposited, making it difficult to estimate when an infected individual may have shed virus onto a SARS-CoV-2 positive surface, which in turn complicates the process of establishing effective quarantine measures. In this study, we determined that reverse transcription-quantitative polymerase chain reaction (RT-qPCR) detection of viral RNA from heat-inactivated particles experiences minimal decay over seven days of monitoring on eight out of nine surfaces tested. The properties of the studied surfaces result in RT-qPCR signatures that can be segregated into two material categories, rough and smooth, where smooth surfaces have a lower limit of detection. RT-qPCR signal intensity (average quantification cycle (Cq)) can be correlated to surface viral load using only one linear regression model per material category. The same experiment was performed with infectious viral particles on one surface from each category, with essentially identical results. The stability of RT-qPCR viral signal demonstrates the need to clean monitored surfaces after sampling to establish temporal resolution. Additionally, these findings can be used to minimize the number of materials and time points tested and allow for the use of heat-inactivated viral particles when optimizing environmental monitoring methods.