Anaerobic Antibiotics and the Risk of Graft-versus-Host Disease after Allogeneic Hematopoietic Stem Cell Transplantation.

Certain anaerobic bacteria are important for maintenance of gut barrier integrity and immune tolerance and may influence the risk of graft-versus-host disease (GVHD) after allogeneic hematopoietic stem cell transplantation (HSCT). We conducted a single-center retrospective cohort study of allogeneic HSCT recipients to evaluate associations between receipt of antibiotics with an anaerobic spectrum of activity and GVHD outcomes. We identified 1214 children and adults who developed febrile neutropenia between 7 days before and 28 days after HSCT and compared GVHD risk and mortality among patients who received anaerobic antibiotics (piperacillin-tazobactam or carbapenems; n = 491) to patients who received only antibiotics with minimal activity against anaerobes (aztreonam, cefepime, or ceftazidime; n = 723). We performed metagenomic sequencing of serial fecal samples from 36 pediatric patients to compare the effects of specific antibiotics on the gut metagenome. Receipt of anaerobic antibiotics was associated with higher hazards of acute gut/liver GVHD (hazard ratio [HR], 1.26; 95% confidence interval [CI], 1.03 to 1.54) and acute GVHD mortality (HR, 1.63; 95% CI, 1.08 to 2.46), but not chronic GVHD diagnosis (HR, 1.04; 95% CI: .84 to 1.28) or chronic GVHD mortality (HR, .88; 95% CI, .53 to 1.45). Anaerobic antibiotics resulted in decreased gut bacterial diversity, reduced abundances of Bifidobacteriales and Clostridiales, and loss of bacterial genes encoding butyrate biosynthesis enzymes from the gut metagenome. Acute gut/liver GVHD was preceded by a sharp decline in bacterial butyrate biosynthesis genes with antibiotic treatment. Our findings demonstrate that exposure to anaerobic antibiotics is associated with increased risks of acute gut/liver GVHD and acute GVHD mortality after allogeneic HSCT. Use of piperacillin-tazobactam or carbapenems should be reserved for febrile neutropenia cases in which anaerobic or multidrug-resistant infections are suspected.

Gut Colonization Preceding Mucosal Barrier Injury Bloodstream Infection in Pediatric Hematopoietic Stem Cell Transplantation Recipients.

The gastrointestinal tract is the predicted reservoir for most bloodstream infections (BSIs) after hematopoietic stem cell transplantation (HSCT). Whole-genome sequencing and comparative genomics have the potential to improve our understanding of the dynamics of gut colonization that precede BSI in HSCT recipients. Within a prospective cohort study of children (age <18 years) undergoing HSCT, 9 subjects met criteria for mucosal barrier injury BSI. We performed whole-genome sequencing of the blood culture isolate and weekly fecal samples preceding the BSI to compare the genetic similarity of BSI isolates to fecal strains. We evaluated temporal associations between antibiotic exposures and the abundances of BSI strains in the gut microbiota and correlated the detection of antibiotic resistance genes with the phenotypic antibiotic resistance of these strains. The median patient age was 2.6 years, and 78% were male. BSIs were caused by Escherichia coli (n = 5), Enterococcus faecium (n = 2), Enterobacter cloacae (n = 1), and Rothia mucilaginosa (n = 1). In the 6 BSI episodes with evaluable comparative genomics, the fecal strains were identical to the blood culture isolate (>99.99% genetic similarity). Gut domination by these strains preceded only 4 of 7 E. coli or E. faecium BSIs by a median of 17 days (range, 6 to 21 days). Increasing abundances of the resulting BSI strains in the gut microbiota were frequently associated with specific antibiotic exposures. E. cloacae and R. mucilaginosa were not highly abundant in fecal samples preceding BSIs caused by these species. The detection of antibiotic resistance genes for ß-lactam antibiotics and vancomycin predicted phenotypic resistance in BSI strains. Bacterial strains causing mucosal barrier injury BSI in pediatric HSCT recipients were observed in the gut microbiota before BSI onset, and changes in the abundances of these strains within the gut preceded most BSI episodes. However, frequent sampling of the gut microbiota and sampling of other ecological niches is likely necessary to effectively predict BSI in HSCT recipients.

Strain-level microbial epidemiology and population genomics from shotgun metagenomics.

Identifying microbial strains and characterizing their functional potential is essential for pathogen discovery, epidemiology and population genomics. We present pangenome-based phylogenomic analysis (PanPhlAn; http://segatalab.cibio.unitn.it/tools/panphlan), a tool that uses metagenomic data to achieve strain-level microbial profiling resolution. PanPhlAn recognized outbreak strains, produced the largest strain-level population genomic study of human-associated bacteria and, in combination with metatranscriptomics, profiled the transcriptional activity of strains in complex communities.

Recovery of ethanol-induced Akkermansia muciniphila depletion ameliorates alcoholic liver disease.

OBJECTIVE: Alcoholic liver disease (ALD) is a global health problem with limited therapeutic options. Intestinal barrier integrity and the microbiota modulate susceptibility to ALD. Akkermansia muciniphila, a Gram-negative intestinal commensal, promotes barrier function partly by enhancing mucus production. The aim of this study was to investigate microbial alterations in ALD and to define the impact of A. muciniphila administration on the course of ALD. DESIGN: The intestinal microbiota was analysed in an unbiased approach by 16S ribosomal DNA (rDNA) sequencing in a Lieber-DeCarli ALD mouse model, and faecal A. muciniphila abundance was determined in a cohort of patients with alcoholic steatohepatitis (ASH). The impact of A. muciniphila on the development of experimental acute and chronic ALD was determined in a preventive and therapeutic setting, and intestinal barrier integrity was analysed. RESULTS: Patients with ASH exhibited a decreased abundance of faecal A. muciniphila when compared with healthy controls that indirectly correlated with hepatic disease severity. Ethanol feeding of wild-type mice resulted in a prominent decline in A. muciniphila abundance. Ethanol-induced intestinal A. muciniphila depletion could be restored by oral A. muciniphila supplementation. Furthermore, A. muciniphila administration when performed in a preventive setting decreased hepatic injury, steatosis and neutrophil infiltration. A. muciniphila also protected against ethanol-induced gut leakiness, enhanced mucus thickness and tight-junction expression. In already established ALD, A. muciniphila used therapeutically ameliorated hepatic injury and neutrophil infiltration. CONCLUSION: Ethanol exposure diminishes intestinal A. muciniphila abundance in both mice and humans and can be recovered in experimental ALD by oral supplementation. A. muciniphila promotes intestinal barrier integrity and ameliorates experimental ALD. Our data suggest that patients with ALD might benefit from A. muciniphila supplementation.

Prophages of the genus Bifidobacterium as modulating agents of the infant gut microbiota.

Phage predation is one of the key forces that shape genetic diversity in bacterial genomes. Phages are also believed to act as modulators of the microbiota composition and, consequently, as agents that drive bacterial speciation in complex bacterial communities. Very little is known about the occurrence and genetic variability of (pro)phages within the Bifidobacterium genus, a dominant bacterial group of the human infant microbiota. Here, we performed cataloguing of the predicted prophage sequences from the genomes of all currently recognized bifidobacterial type strains. We analysed their genetic diversity and deduced their evolutionary development, thereby highlighting an intriguing origin. Furthermore, we assessed infant gut microbiomes for the presence of (pro)phage sequences and found compelling evidence that these viral elements influence the composition of bifidobacterial communities in the infant gut microbiota.

16S community profiling identifies proton pump inhibitor related differences in gastric, lung, and oropharyngeal microflora.

OBJECTIVES: To test the hypothesis that proton pump inhibitor (PPI) use results in changes in gastric microflora which, through full column reflux, results in lung and oropharyngeal microflora changes. STUDY DESIGN: We performed a prospective, cross-sectional cohort study of 116 children (57 off and 59 on PPIs) undergoing simultaneous bronchoscopy and upper endoscopy for the evaluation of chronic cough. We performed 16S sequencing on gastric, bronchoalveolar lavage, and oropharyngeal fluid. Fifty patients also underwent multichannel intraluminal impedance testing. RESULTS: Streptococcus was more abundant in the gastric fluid of patients taking PPIs, and there was a significant correlation with PPI dose (mg/kg/d) and abundance of gastric Streptococcus (P = .01). There was also a significant difference in the abundance of oropharyngeal Streptococcus in patients treated with PPI. Eight unique bacterial genera were found in the gastric and lung fluid but not in the oropharyngeal suggesting exchange between the 2 sites and 2 of the 8 (Lactococcus, Acinetobacter) were more abundant in patients with more full column reflux, suggesting direct aspiration. Principal component analysis revealed greater overlap between gastric and lung than oropharyngeal microflora. CONCLUSIONS: PPI use was associated with differences in gastric, lung, and oropharyngeal microflora. Although microflora exchange can occur between all 3 sites, gastric and lung microflora are more closely related, and the mechanism of exchange between sites may be aspiration of full column reflux.

Comparative phylogenomics and evolution of the Brucellae reveal a path to virulence.

Brucella species include important zoonotic pathogens that have a substantial impact on both agriculture and human health throughout the world. Brucellae are thought of as "stealth pathogens" that escape recognition by the host innate immune response, modulate the acquired immune response, and evade intracellular destruction. We analyzed the genome sequences of members of the family Brucellaceae to assess its evolutionary history from likely free-living soil-based progenitors into highly successful intracellular pathogens. Phylogenetic analysis split the genus into two groups: recently identified and early-dividing "atypical" strains and a highly conserved "classical" core clade containing the major pathogenic species. Lateral gene transfer events brought unique genomic regions into Brucella that differentiated them from Ochrobactrum and allowed the stepwise acquisition of virulence factors that include a type IV secretion system, a perosamine-based O antigen, and systems for sequestering metal ions that are absent in progenitors. Subsequent radiation within the core Brucella resulted in lineages that appear to have evolved within their preferred mammalian hosts, restricting their virulence to become stealth pathogens capable of causing long-term chronic infections.

Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons.

Bacterial diversity among environmental samples is commonly assessed with PCR-amplified 16S rRNA gene (16S) sequences. Perceived diversity, however, can be influenced by sample preparation, primer selection, and formation of chimeric 16S amplification products. Chimeras are hybrid products between multiple parent sequences that can be falsely interpreted as novel organisms, thus inflating apparent diversity. We developed a new chimera detection tool called Chimera Slayer (CS). CS detects chimeras with greater sensitivity than previous methods, performs well on short sequences such as those produced by the 454 Life Sciences (Roche) Genome Sequencer, and can scale to large data sets. By benchmarking CS performance against sequences derived from a controlled DNA mixture of known organisms and a simulated chimera set, we provide insights into the factors that affect chimera formation such as sequence abundance, the extent of similarity between 16S genes, and PCR conditions. Chimeras were found to reproducibly form among independent amplifications and contributed to false perceptions of sample diversity and the false identification of novel taxa, with less-abundant species exhibiting chimera rates exceeding 70%. Shotgun metagenomic sequences of our mock community appear to be devoid of 16S chimeras, supporting a role for shotgun metagenomics in validating novel organisms discovered in targeted sequence surveys.

Early empiric antibiotic use in preterm infants is associated with lower bacterial diversity and higher relative abundance of Enterobacter.

OBJECTIVES: To determine the impact of empiric ampicillin and gentamicin use in the first week of life on microbial colonization and diversity in preterm infants. STUDY DESIGN: The 16s ribosomal DNA community profiling was used to compare the microbiota of 74 infants born ≤32 weeks gestational age by degree of antibiotic use in the first week of life. The degree of antibiotic use was classified as 0 days, 1-4 days, and 5-7 days of antibiotic administration. All of the antibiotic use was empiric, defined as treatment based solely on clinical suspicion of infection without a positive culture result. RESULTS: Infants who received 5-7 days of empiric antimicrobial agents in the first week had increased relative abundance of Enterobacter (P = .016) and lower bacterial diversity in the second and third weeks of life. Infants receiving early antibiotics also experienced more cases of necrotizing enterocolitis, sepsis, or death than those not exposed to antibiotics. CONCLUSIONS: Early empiric antibiotics have sustained effects on the intestinal microbiota of preterm infants. Intestinal dysbiosis in this population has been found to be associated with elevated risk of necrotizing enterocolitis, sepsis, or death.

The effects of antibiotic exposures on the gut resistome during hematopoietic cell transplantation in children.

Antibiotic resistance is a global threat driven primarily by antibiotic use. We evaluated the effects of antibiotic exposures on the gut microbiomes and resistomes of children at high risk of colonization by antibiotic-resistant bacteria. We performed shotgun metagenomic sequencing of 691 serially collected fecal samples from 80 children (<18 years) undergoing hematopoietic cell transplantation. We evaluated the effects of aerobic (cefepime, vancomycin, fluoroquinolones, aminoglycosides, macrolides, and trimethoprim-sulfamethoxazole) and anaerobic (piperacillin-tazobactam, carbapenems, metronidazole, and clindamycin) antibiotic exposures on the diversity and composition of the gut microbiome and resistome. We identified 372 unique antibiotic resistance genes (ARGs); the most frequent ARGs identified encode resistance to tetracyclines (n = 88), beta-lactams (n = 84), and fluoroquinolones (n = 79). Both aerobic and anaerobic antibiotic exposures were associated with a decrease in the number of bacterial species (aerobic, ß = 0.71, 95% CI: 0.64, 0.79; anaerobic, ß = 0.66, 95% CI: 0.53, 0.82) and the number of unique ARGs (aerobic, ß = 0.81, 95% CI: 0.74, 0.90; anaerobic, ß = 0.73, 95% CI: 0.61, 0.88) within the gut metagenome. However, only antibiotic regimens that included anaerobic activity were associated with an increase in acquisition of new ARGs (anaerobic, ß = 1.50; 95% CI: 1.12, 2.01) and an increase in the relative abundance of ARGs in the gut resistome (anaerobic, ß = 1.62; 95% CI: 1.15, 2.27). Specific antibiotic exposures were associated with distinct changes in the number and abundance of ARGs for individual antibiotic classes. Our findings detail the impact of antibiotics on the gut microbiome and resistome and demonstrate that anaerobic antibiotics are particularly likely to promote acquisition and expansion of antibiotic-resistant bacteria.

Microbiota encoded fatty-acid metabolism expands tuft cells to protect tissues homeostasis during Clostridioides difficile infection in the large intestine.

Metabolic byproducts of the intestinal microbiota are crucial in maintaining host immune tone and shaping inter-species ecological dynamics. Among these metabolites, succinate is a driver of tuft cell (TC) differentiation and consequent type 2 immunity-dependent protection against invading parasites in the small intestine. Succinate is also a growth enhancer of the nosocomial pathogen Clostridioides difficile in the large intestine. To date, no research has shown the role of succinate in modulating TC dynamics in the large intestine, or the relevance of this immune pathway to C. difficile pathophysiology. Here we reveal the existence of a three-way circuit between commensal microbes, C. difficile and host epithelial cells which centers around succinate. Through selective microbiota depletion experiments we demonstrate higher levels of type 2 cytokines leading to expansion of TCs in the colon. We then demonstrate the causal role of the microbiome in modulating colonic TC abundance and subsequent type 2 cytokine induction using rational supplementation experiments with fecal transplants and microbial consortia of succinate-producing bacteria. We show that administration of a succinate-deficient Bacteroides thetaiotaomicron knockout (Δfrd) significantly reduces the enhanced type 2 immunity in mono-colonized mice. Finally, we demonstrate that mice prophylactically administered with the consortium of succinate-producing bacteria show reduced C. difficile-induced morbidity and mortality compared to mice administered with heat-killed bacteria or the vehicle. This effect is reduced in a partial tuft cell knockout mouse, Pou2f3+/-, and nullified in the tuft cell knockout mouse, Pou2f3-/-, confirming that the observed protection occurs via the TC pathway. Succinate is an intermediary metabolite of the production of short-chain fatty acids, and its concentration often increases during dysbiosis. The first barrier to enteric pathogens alike is the intestinal epithelial barrier, and host maintenance and strengthening of barrier integrity is vital to homeostasis. Considering our data, we propose that activation of TC by the microbiota-produced succinate in the colon is a mechanism evolved by the host to counterbalance microbiome-derived cues that facilitate invasion by intestinal pathogens.

Serine/threonine phosphatase Stp1 contributes to reduced susceptibility to vancomycin and virulence in Staphylococcus aureus.

The genetic mechanisms that contribute to reduced susceptibility to vancomycin in Staphylococcus aureus are complex and heterogeneous. In addition, debate is emerging as to the true effect of reduced susceptibility to vancomycin on staphylococcal virulence. To investigate this, comparative genomics was performed on a collection of vancomycin-exposed isogenic S. aureus pairs (14 strains in total). Previously described mutations were observed in genes such as vraG, agrA, yvqF, and rpoB; however, a new mechanism was identified involving a serine/threonine phosphatase, Stp1. After constructing an stp1 deletion mutant, we showed that stp1 is important in vancomycin susceptibility and cell wall biosynthesis. Gene expression studies showed that stp1 also regulates virulence genes, including a hemolysin, superantigen-like protein, and phenol-soluble modulin, and that the deletion mutant is attenuated in virulence in vivo. Stp1 provides a new link between vancomycin susceptibility and virulence in S. aureus.

Evolved bacterial resistance to the chemotherapy gemcitabine modulates its efficacy in co-cultured cancer cells.

Drug metabolism by the microbiome can influence anticancer treatment success. We previously suggested that chemotherapies with antimicrobial activity can select for adaptations in bacterial drug metabolism that can inadvertently influence the host's chemoresistance. We demonstrated that evolved resistance against fluoropyrimidine chemotherapy lowered its efficacy in worms feeding on drug-evolved bacteria (Rosener et al., 2020). Here, we examine a model system that captures local interactions that can occur in the tumor microenvironment. Gammaproteobacteria-colonizing pancreatic tumors can degrade the nucleoside-analog chemotherapy gemcitabine and, in doing so, can increase the tumor's chemoresistance. Using a genetic screen in Escherichia coli, we mapped all loss-of-function mutations conferring gemcitabine resistance. Surprisingly, we infer that one third of top resistance mutations increase or decrease bacterial drug breakdown and therefore can either lower or raise the gemcitabine load in the local environment. Experiments in three E. coli strains revealed that evolved adaptation converged to inactivation of the nucleoside permease NupC, an adaptation that increased the drug burden on co-cultured cancer cells. The two studies provide complementary insights on the potential impact of microbiome adaptation to chemotherapy by showing that bacteria-drug interactions can have local and systemic influence on drug activity.

The intestinal microbiota predicts COVID-19 severity and fatality regardless of hospital feeding method.

SARS-CoV-2-positive patients exhibit gut and oral microbiome dysbiosis, which is associated with various aspects of COVID-19 disease (1-4). Here, we aim to identify gut and oral microbiome markers that predict COVID-19 severity in hospitalized patients, specifically severely ill patients compared to moderately ill ones. Moreover, we investigate whether hospital feeding (solid versus enteral), an important cofounder, influences the microbial composition of hospitalized COVID-19 patients. We used random forest classification machine learning models with interpretable secondary analyses. The gut, but not the oral microbiota, was a robust predictor of both COVID-19-related fatality and severity of hospitalized patients, with a higher predictive value than most clinical variables. In addition, perturbations of the gut microbiota due to enteral feeding did not associate with species that were predictive of COVID-19 severity. IMPORTANCE SARS-CoV-2 infection leads to wide-ranging, systemic symptoms with sometimes unpredictable morbidity and mortality. It is increasingly clear that the human microbiome plays an important role in how individuals respond to viral infections. Our study adds to important literature about the associations of gut microbiota and severe COVID-19 illness during the early phase of the pandemic before the availability of vaccines. Increased understanding of the interplay between microbiota and SARS-CoV-2 may lead to innovations in diagnostics, therapies, and clinical predictions.

The microbiota of pregnant women with SARS-CoV-2 and their infants.

BACKGROUND: Infants receive their first bacteria from their birthing parent. This newly acquired microbiome plays a pivotal role in developing a robust immune system, the cornerstone of long-term health. RESULTS: We demonstrated that the gut, vaginal, and oral microbial diversity of pregnant women with SARS-CoV-2 infection is reduced, and women with early infections exhibit a different vaginal microbiota composition at the time of delivery compared to their healthy control counterparts. Accordingly, a low relative abundance of two Streptococcus sequence variants (SV) was predictive of infants born to pregnant women with SARS-CoV-2 infection. CONCLUSIONS: Our data suggest that SARS-CoV-2 infections during pregnancy, particularly early infections, are associated with lasting changes in the microbiome of pregnant women, compromising the initial microbial seed of their infant. Our results highlight the importance of further exploring the impact of SARS-CoV-2 on the infant's microbiome-dependent immune programming. Video Abstract.

Tracking insertion mutants within libraries by deep sequencing and a genome-wide screen for Haemophilus genes required in the lung.

Rapid genome-wide identification of genes required for infection would expedite studies of bacterial pathogens. We developed genome-scale "negative selection" technology that combines high-density transposon mutagenesis and massively parallel sequencing of transposon/chromosome junctions in a mutant library to identify mutants lost from the library after exposure to a selective condition of interest. This approach was applied to comprehensively identify Haemophilus influenzae genes required to delay bacterial clearance in a murine pulmonary model. Mutations in 136 genes resulted in defects in vivo, and quantitative estimates of fitness generated by this technique were in agreement with independent validation experiments using individual mutant strains. Genes required in the lung included those with characterized functions in other models of H. influenzae pathogenesis and genes not previously implicated in infection. Genes implicated in vivo have reported or potential roles in survival during nutrient limitation, oxidative stress, and exposure to antimicrobial membrane perturbations, suggesting that these conditions are encountered by H. influenzae during pulmonary infection. The results demonstrate an efficient means to identify genes required for bacterial survival in experimental models of pathogenesis, and this approach should function similarly well in selections conducted in vitro and in vivo with any organism amenable to insertional mutagenesis.

The Urinary Microbiome of Older Adults Residing in a Nursing Home Varies With Duration of Residence and Shows Increases in Potential Pathogens.

The community of bacteria that colonize the urinary tract, the urinary microbiome, is hypothesized to influence a wide variety of urinary tract conditions. Older adults who reside in nursing homes are frequently diagnosed and treated for urinary tract conditions such as urinary tract infection. We investigated the urinary microbiome of older adults residing in a nursing home to determine if there are features of the urinary microbiome that are associated with specific conditions and exposure in this population. We were also interested in the stability of urinary microbiome over time and in similarities between the urinary and gastrointestinal microbiome. Urine samples were prospectively collected over a period of 10 months from a cohort of 26 older adults (aged >65 years) residing in a single nursing home located in Central Massachusetts. Serial samples were obtained from 6 individuals over 10 months and 5 participants were concurrently enrolled in a study of the gastrointestinal microbiome. Information collected on participants included demographics, medical history, duration of residence in the nursing home, frailty, dementia symptoms, urinary symptoms, antibiotic treatment, urinary catheterization, and hospitalizations over a 10-month period. Clean catch, midstream urine samples were collected and stored at -80°C. DNA was extracted and 16S rRNA gene sequencing was performed. The length of stay in the nursing facility and the Clinical Frailty Scale correlated with significant changes in microbiome composition. An increase in the relative abundance of a putative urinary pathogen, Aerococcus urinae, was the largest factor influencing change that occurred over the duration of residence.

COVID-19 Variant Surveillance and Social Determinants in Central Massachusetts: Development Study.

BACKGROUND: Public health scientists have used spatial tools such as web-based Geographical Information System (GIS) applications to monitor and forecast the progression of the COVID-19 pandemic and track the impact of their interventions. The ability to track SARS-CoV-2 variants and incorporate the social determinants of health with street-level granularity can facilitate the identification of local outbreaks, highlight variant-specific geospatial epidemiology, and inform effective interventions. We developed a novel dashboard, the University of Massachusetts' Graphical user interface for Geographic Information (MAGGI) variant tracking system that combines GIS, health-associated sociodemographic data, and viral genomic data to visualize the spatiotemporal incidence of SARS-CoV-2 variants with street-level resolution while safeguarding protected health information. The specificity and richness of the dashboard enhance the local understanding of variant introductions and transmissions so that appropriate public health strategies can be devised and evaluated. OBJECTIVE: We developed a web-based dashboard that simultaneously visualizes the geographic distribution of SARS-CoV-2 variants in Central Massachusetts, the social determinants of health, and vaccination data to support public health efforts to locally mitigate the impact of the COVID-19 pandemic. METHODS: MAGGI uses a server-client model-based system, enabling users to access data and visualizations via an encrypted web browser, thus securing patient health information. We integrated data from electronic medical records, SARS-CoV-2 genomic analysis, and public health resources. We developed the following functionalities into MAGGI: spatial and temporal selection capability by zip codes of interest, the detection of variant clusters, and a tool to display variant distribution by the social determinants of health. MAGGI was built on the Environmental Systems Research Institute ecosystem and is readily adaptable to monitor other infectious diseases and their variants in real-time. RESULTS: We created a geo-referenced database and added sociodemographic and viral genomic data to the ArcGIS dashboard that interactively displays Central Massachusetts' spatiotemporal variants distribution. Genomic epidemiologists and public health officials use MAGGI to show the occurrence of SARS-CoV-2 genomic variants at high geographic resolution and refine the display by selecting a combination of data features such as variant subtype, subject zip codes, or date of COVID-19-positive sample collection. Furthermore, they use it to scale time and space to visualize association patterns between socioeconomics, social vulnerability based on the Centers for Disease Control and Prevention's social vulnerability index, and vaccination rates. We launched the system at the University of Massachusetts Chan Medical School to support internal research projects starting in March 2021. CONCLUSIONS: We developed a COVID-19 variant surveillance dashboard to advance our geospatial technologies to study SARS-CoV-2 variants transmission dynamics. This real-time, GIS-based tool exemplifies how spatial informatics can support public health officials, genomics epidemiologists, infectious disease specialists, and other researchers to track and study the spread patterns of SARS-CoV-2 variants in our communities.

Oropharyngeal Microbiome Profiled at Admission is Predictive of the Need for Respiratory Support Among COVID-19 Patients.

The clinical course of infection due to respiratory viruses such as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2), the causative agent of Coronavirus Disease 2019 (COVID-19) is thought to be influenced by the community of organisms that colonizes the upper respiratory tract, the oropharyngeal microbiome. In this study, we examined the oropharyngeal microbiome of suspected COVID-19 patients presenting to the Emergency Department and an inpatient COVID-19 unit with symptoms of acute COVID-19. Of 115 enrolled patients, 74 were confirmed COVID-19+ and 50 had symptom duration of 14 days or less; 38 acute COVID-19+ patients (76%) went on to require respiratory support. Although no microbiome features were found to be significantly different between COVID-19+ and COVID-19-patients, when we conducted random forest classification modeling (RFC) to predict the need of respiratory support for the COVID-19+ patients our analysis identified a subset of organisms and metabolic pathways whose relative abundance, when combined with clinical factors (such as age and Body Mass Index), was highly predictive of the need for respiratory support (F1 score 0.857). Microbiome Multivariable Association with Linear Models (MaAsLin2) analysis was then applied to the features identified as predicative of the need for respiratory support by the RFC. This analysis revealed reduced abundance of Prevotella salivae and metabolic pathways associated with lipopolysaccharide and mycolic acid biosynthesis to be the strongest predictors of patients requiring respiratory support. These findings suggest that composition of the oropharyngeal microbiome in COVID-19 may play a role in determining who will suffer from severe disease manifestations. Importance: The microbial community that colonizes the upper airway, the oropharyngeal microbiome, has the potential to affect how patients respond to respiratory viruses such as SARS-CoV2, the causative agent of COVID-19. In this study, we investigated the oropharyngeal microbiome of COVID-19 patients using high throughput DNA sequencing performed on oral swabs. We combined patient characteristics available at intake such as medical comorbidities and age, with measured abundance of bacterial species and metabolic pathways and then trained a machine learning model to determine what features are predicative of patients needing respiratory support in the form of supplemental oxygen or mechanical ventilation. We found that decreased abundance of some bacterial species and increased abundance of pathways associated bacterial products biosynthesis was highly predictive of needing respiratory support. This suggests that the oropharyngeal microbiome affects disease course in COVID-19 and could be targeted for diagnostic purposes to determine who may need oxygen, or therapeutic purposes such as probiotics to prevent severe COVID-19 disease manifestations.

Oropharyngeal microbiome profiled at admission is predictive of the need for respiratory support among COVID-19 patients.

The oropharyngeal microbiome, the collective genomes of the community of microorganisms that colonizes the upper respiratory tract, is thought to influence the clinical course of infection by respiratory viruses, including Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the causative agent of Coronavirus Infectious Disease 2019 (COVID-19). In this study, we examined the oropharyngeal microbiome of suspected COVID-19 patients presenting to the Emergency Department and an inpatient COVID-19 unit with symptoms of acute COVID-19. Of 115 initially enrolled patients, 50 had positive molecular testing for COVID-19+ and had symptom duration of 14 days or less. These patients were analyzed further as progression of disease could most likely be attributed to acute COVID-19 and less likely a secondary process. Of these, 38 (76%) went on to require some form of supplemental oxygen support. To identify functional patterns associated with respiratory illness requiring respiratory support, we applied an interpretable random forest classification machine learning pipeline to shotgun metagenomic sequencing data and select clinical covariates. When combined with clinical factors, both species and metabolic pathways abundance-based models were found to be highly predictive of the need for respiratory support (F1-score 0.857 for microbes and 0.821 for functional pathways). To determine biologically meaningful and highly predictive signals in the microbiome, we applied the Stable and Interpretable RUle Set to the output of the models. This analysis revealed that low abundance of two commensal organisms, Prevotella salivae or Veillonella infantium (< 4.2 and 1.7% respectively), and a low abundance of a pathway associated with LPS biosynthesis (< 0.1%) were highly predictive of developing the need for acute respiratory support (82 and 91.4% respectively). These findings suggest that the composition of the oropharyngeal microbiome in COVID-19 patients may play a role in determining who will suffer from severe disease manifestations.