A Randomized Trial of Mesenchymal Stromal Cells for Moderate to Severe Acute Respiratory Distress Syndrome from COVID-19.

Rationale: There are limited therapeutic options for patients with coronavirus disease (COVID-19)-related acute respiratory distress syndrome with inflammation-mediated lung injury. Mesenchymal stromal cells offer promise as immunomodulatory agents. Objectives: Evaluation of efficacy and safety of allogeneic mesenchymal cells in mechanically-ventilated patients with moderate or severe COVID-19-induced respiratory failure. Methods: Patients were randomized to two infusions of 2 million cells/kg or sham infusions, in addition to the standard of care. We hypothesized that cell therapy would be superior to sham control for the primary endpoint of 30-day mortality. The key secondary endpoint was ventilator-free survival within 60 days, accounting for deaths and withdrawals in a ranked analysis. Measurements and Main Results: At the third interim analysis, the data and safety monitoring board recommended that the trial halt enrollment as the prespecified mortality reduction from 40% to 23% was unlikely to be achieved (n = 222 out of planned 300). Thirty-day mortality was 37.5% (42/112) in cell recipients versus 42.7% (47/110) in control patients (relative risk [RR], 0.88; 95% confidence interval, 0.64-1.21; P = 0.43). There were no significant differences in days alive off ventilation within 60 days (median rank, 117.3 [interquartile range, 60.0-169.5] in cell patients and 102.0 [interquartile range, 54.0-162.5] in control subjects; higher is better). Resolution or improvement of acute respiratory distress syndrome at 30 days was observed in 51/104 (49.0%) cell recipients and 46/106 (43.4%) control patients (odds ratio, 1.36; 95% confidence interval, 0.57-3.21). There were no infusion-related toxicities and overall serious adverse events over 30 days were similar. Conclusions: Mesenchymal cells, while safe, did not improve 30-day survival or 60-day ventilator-free days in patients with moderate and/or severe COVID-19-related acute respiratory distress syndrome.

Host-microbe interactions and outcomes in multiple myeloma and hematopoietic stem cell transplantation.

Microbiota are essential to normal immune development and there is growing recognition of its importance to human health and disease and deepening understanding of the complexity of host-microbe interactions in the human gut and other tissues. Commensal microbes not only can influence host immunity locally through impacts of bioactive microbial metabolites and direct interactions with epithelial cells and innate immune receptors but also can exert systemic immunomodulatory effects via impacts on host immune cells capable of trafficking beyond the gut. Emerging data suggest microbiota influence the development of multiple myeloma (MM), a malignancy of the immune system derived from immunoglobulin-producing bone marrow plasma cells, through the promotion of inflammation. Superior treatment outcomes for MM correlate with a higher abundance of commensal microbiota capable of influencing inflammatory responses through the production of butyrate. In patients with hematologic malignancies, higher levels of diversity of the gut microbiota correlate with superior outcomes after hematopoietic stem cell transplantation. Correlative data support the impact of commensal microbiota on survival, risk of infection, disease relapse, and graft-versus-host disease (GVHD) after transplant. In this review, we will discuss the current understanding of the role of host-microbe interactions and the inflammatory tumor microenvironment of multiple myeloma, discuss data describing the key role of microbiota in hematopoietic stem cell transplantation for treatment of hematologic malignancies, and highlight several possible concepts for interventions directed at the gut microbiota to influence treatment outcomes.

Signal Versus Noise: How to Analyze the Microbiome and Make Progress on Antimicrobial Resistance.

Antimicrobial resistance has become a worldwide medical challenge [1], so impactful that vancomycin-resistant Enterococcus (VRE) and methicillin-resistant Staphylococcus aureus (MRSA) have entered the common vernacular. We have attempted to reduce the selective pressure through antimicrobial stewardship, curtail the spread by identifying and isolating carriers and individuals with symptomatic infection, and treat antibiotic-resistant organisms (AROs) by developing novel antimicrobials. Despite these extraordinary measures, the challenge of AROs continues to grow. The gut microbiome, the ecosystem of microbes (ie, the microbiota) and metabolites present upon and within all humans, is an emerging target for both the risk for colonization and defense against infection with AROs. Here, informed from experiences and successes with understanding the role of the microbiome in mediating risk of Clostridioides difficile infection (CDI), we (1) review our understanding of the risk from ARO acquisition; (2) review our current understanding of the gut microbiome's ability to resist colonization with AROs; (3) describe how experimental model systems can test these initial, global insights to arrive at more granular, mechanistic ones; and (4) suggest a path forward to make further progress in the field.

Genetic Variation in Toll-Like Receptor 5 and Colonization with Flagellated Bacterial Vaginosis-Associated Bacteria.

Bacterial vaginosis (BV) is a vaginal dysbiotic condition linked to negative gynecological and reproductive sequelae. Flagellated bacteria have been identified in women with BV, including Mobiluncus spp. and BV-associated bacterium-1 (BVAB1), an uncultivated, putatively flagellated species. The host response to flagellin mediated through Toll-like receptor 5 (TLR5) has not been explored in BV. Using independent discovery and validation cohorts, we examined the hypothesis that TLR5 deficiency-defined by a dominant negative stop codon polymorphism, rs5744168-is associated with an increased risk for BV and increased colonization with flagellated bacteria associated with BV (BVAB1, Mobiluncus curtisii, and Mobiluncus mulieris). TLR5 deficiency was not associated with BV status, and TLR5-deficient women had decreased colonization with BVAB1 in both cohorts. We stimulated HEK-hTLR5-overexpressing NF-κB reporter cells with whole, heat-killed M. mulieris or M. curtisii and with partially purified flagellin from these species; as BVAB1 is uncultivated, we used cervicovaginal lavage (CVL) fluid supernatant from women colonized with BVAB1 for stimulation. While heat-killed M. mulieris and CVL fluid from women colonized with BVAB1 stimulate a TLR5-mediated response, heat-killed M. curtisii did not. In contrast, partially purified flagellin from both Mobiluncus species stimulated a TLR5-mediated response in vitro We observed no correlation between vaginal interleukin 8 (IL-8) and flagellated BVAB concentrations among TLR5-sufficient women. Interspecies variation in accessibility of flagellin recognition domains may be responsible for these observations, as reflected in the potentially novel flagellin products encoded by Mobiluncus species versus those encoded by BVAB1.

Tocilizumab for Treatment of Mechanically Ventilated Patients With COVID-19.

BACKGROUND: Severe coronavirus disease 2019 (COVID-19) can manifest in rapid decompensation and respiratory failure with elevated inflammatory markers, consistent with cytokine release syndrome for which IL-6 blockade is an approved treatment. METHODS: We assessed effectiveness and safety of IL-6 blockade with tocilizumab in a single-center cohort of patients with COVID-19 requiring mechanical ventilation. The primary endpoint was survival probability postintubation; secondary analyses included an ordinal illness severity scale integrating superinfections. Outcomes in patients who received tocilizumab compared with tocilizumab-untreated controls were evaluated using multivariable Cox regression with propensity score inverse probability of treatment weighting (IPTW). RESULTS: 154 patients were included, of whom 78 received tocilizumab and 76 did not. Median follow-up was 47 days (range, 28-67). Baseline characteristics were similar between groups, although tocilizumab-treated patients were younger (mean: 55 vs 60 years), less likely to have chronic pulmonary disease (10% vs 28%), and had lower D-dimer values at time of intubation (median: 2.4 vs 6.5 mg/dL). In IPTW-adjusted models, tocilizumab was associated with a 45% reduction in hazard of death (HR, .55; 95% CI, .33-.90) and improved status on the ordinal outcome scale [OR per 1-level increase, .58; .36-.94). Although tocilizumab was associated with an increased proportion of patients with superinfections (54% vs 26%; P < .001), there was no difference in 28-day case fatality rate among tocilizumab-treated patients with versus without superinfection (22% vs 15%; P = .42). Staphylococcus aureus accounted for ~50% of bacterial pneumonia. CONCLUSIONS: In this cohort of mechanically ventilated COVID-19 patients, tocilizumab was associated with lower mortality despite higher superinfection occurrence.

Graft-Derived Reconstitution of Mucosal-Associated Invariant T Cells after Allogeneic Hematopoietic Cell Transplantation.

Mucosal-associated invariant T (MAIT) cells express a semi-invariant Vα7.2+ T cell receptor (TCR) that recognizes ligands from distinct bacterial and fungal species. In neonates, MAIT cells proliferate coincident with gastrointestinal (GI) bacterial colonization. In contrast, under noninflammatory conditions adult MAIT cells remain quiescent because of acquired regulation of TCR signaling. Effects of inflammation and the altered GI microbiota after allogeneic hematopoietic cell transplantation (HCT) on MAIT cell reconstitution have not been described. We conducted an observational study of MAIT cell reconstitution in myeloablative (n = 41) and nonmyeloablative (n = 66) allogeneic HCT recipients and found that despite a rapid and early increase to a plateau at day 30 after HCT, MAIT cell numbers failed to normalize for at least 1 year. Cord blood transplant recipients and those who received post-HCT cyclophosphamide for graft versus host disease (GVHD) prophylaxis had profoundly impaired MAIT cell reconstitution. Sharing of TCRß gene sequences between MAIT cells isolated from HCT grafts and blood of recipients after HCT showed early MAIT cell reconstitution was due at least in part to proliferation of MAIT cells transferred in the HCT graft. Inflammatory cytokines were required for TCR-dependent MAIT cell proliferation, suggesting that bacterial Vα7.2+ TCR ligands might promote MAIT cell reconstitution after HCT. Robust MAIT cell reconstitution was associated with an increased GI abundance of Blautia spp. MAIT cells suppressed proliferation of conventional T cells consistent with a possible regulatory role. Our data identify modifiable factors impacting MAIT cell reconstitution that could influence the risk of GVHD after HCT.

Antibiotic Exposure Prior to Respiratory Viral Infection Is Associated with Progression to Lower Respiratory Tract Disease in Allogeneic Hematopoietic Cell Transplant Recipients.

Recent publications note an association between antibiotic exposure and respiratory viral infections (RVIs). Antibiotics affect microbiota and impair immune response against RVIs in mice, and low microbiome diversity is associated with pulmonary complications including viral lower respiratory tract disease (LRTD) in hematopoietic cell transplantation (HCT) recipients. In this study, we examined whether antibiotic exposure was associated with increased risk of disease progression in RVIs post-transplantation. We analyzed patients who underwent allogeneic HCT (June 2008 to February 2016) and had their first RVI due to parainfluenza virus (PIV), respiratory syncytial virus (RSV), or human metapneumovirus (MPV) during the initial 100 days post-transplantation. Antibiotic exposure in the 3 weeks before RVI onset was defined as (1) use of specific antibiotics versus none of these antibiotics and (2) number of antibiotic-days. Cox proportional hazards models were used to examine associations between antibiotic exposures and risk of viral disease progression to proven/probable/possible LRTD. Ninety HCT recipients (84 adults, 6 children) fulfilled study criteria; 33 progressed to LRTD. The number of antibiotic-days was associated with progression to LRTD after adjusting for neutropenia, steroid use, and either lymphopenia (hazard ratio, 1.41 [95% confidence interval, 1.04 to 1.92], P = .027) or monocytopenia (hazard ratio, 1.46 [95% confidence interval, 1.11 to 1.91], P = .006). Specific antibiotic classes was not associated with the outcome. Cumulative antibiotic exposure immediately before RVI onset is a risk factor for disease progression following PIV, RSV, and MPV infections post-transplantation. Larger cohort studies are needed to determine the impact of specific antibiotics or antibiotic classes on disease severity.

Evaluating the accuracy of amplicon-based microbiome computational pipelines on simulated human gut microbial communities.

BACKGROUND: Microbiome studies commonly use 16S rRNA gene amplicon sequencing to characterize microbial communities. Errors introduced at multiple steps in this process can affect the interpretation of the data. Here we evaluate the accuracy of operational taxonomic unit (OTU) generation, taxonomic classification, alpha- and beta-diversity measures for different settings in QIIME, MOTHUR and a pplacer-based classification pipeline, using a novel software package: DECARD. RESULTS: In-silico we generated 100 synthetic bacterial communities approximating human stool microbiomes to be used as a gold-standard for evaluating the colligative performance of microbiome analysis software. Our synthetic data closely matched the composition and complexity of actual healthy human stool microbiomes. Genus-level taxonomic classification was correctly done for only 50.4-74.8% of the source organisms. Miscall rates varied from 11.9 to 23.5%. Species-level classification was less successful, (6.9-18.9% correct); miscall rates were comparable to those of genus-level targets (12.5-26.2%). The degree of miscall varied by clade of organism, pipeline and specific settings used. OTU generation accuracy varied by strategy (closed, de novo or subsampling), reference database, algorithm and software implementation. Shannon diversity estimation accuracy correlated generally with OTU-generation accuracy. Beta-diversity estimates with Double Principle Coordinate Analysis (DPCoA) were more robust against errors introduced in processing than Weighted UniFrac. The settings suggested in the tutorials were among the worst performing in all outcomes tested. CONCLUSIONS: Even when using the same classification pipeline, the specific OTU-generation strategy, reference database and downstream analysis methods selection can have a dramatic effect on the accuracy of taxonomic classification, and alpha- and beta-diversity estimation. Even minor changes in settings adversely affected the accuracy of the results, bringing them far from the best-observed result. Thus, specific details of how a pipeline is used (including OTU generation strategy, reference sets, clustering algorithm and specific software implementation) should be specified in the methods section of all microbiome studies. Researchers should evaluate their chosen pipeline and settings to confirm it can adequately answer the research question rather than assuming the tutorial or standard-operating-procedure settings will be adequate or optimal.

Stool Microbiota at Neutrophil Recovery Is Predictive for Severe Acute Graft vs Host Disease After Hematopoietic Cell Transplantation.

BACKGROUND: Graft-versus-host disease (GVHD) is common after allogeneic hematopoietic cell transplantation (HCT). Risk for death from GVHD has been associated with low bacterial diversity in the stool microbiota early after transplant; however, the specific species associated with GVHD risk remain poorly defined. METHODS: We prospectively collected serial weekly stool samples from 66 patients who underwent HCT, starting pre-transplantation and continuing weekly until 100 days post-transplant, a total of 694 observations in HCT recipients. We used 16S rRNA gene polymerase chain reaction with degenerate primers, followed by high-throughput sequencing to assess the relative abundance of sequence reads from bacterial taxa in stool samples over time. RESULTS: The gut microbiota was highly dynamic in HCT recipients, with loss and appearance of taxa common on short time scales. As in prior studies, GVHD was associated with lower alpha diversity of the stool microbiota. At neutrophil recovery post-HCT, the presence of oral Actinobacteria and oral Firmicutes in stool was positively correlated with subsequent GVHD; Lachnospiraceae were negatively correlated. A gradient of bacterial species (difference of the sum of the relative abundance of positive correlates minus the sum of the relative abundance of negative correlates) was most predictive (receiver operator characteristic area under the curve of 0.83) of subsequent severe acute GVHD. CONCLUSIONS: The stool microbiota around the time of neutrophil recovery post-HCT is predictive of subsequent development of severe acute GVHD in this study.

Acarbose Impairs Gut Bacteroides Growth by Targeting Intracellular GH97 Enzymes.

Acarbose is a type-2 diabetes medicine that inhibits dietary starch breakdown into glucose by inhibiting host amylase and glucosidase enzymes. Numerous gut species in the Bacteroides genus enzymatically break down starch and change in relative abundance within the gut microbiome in acarbose-treated individuals. To mechanistically explain this observation, we used two model starch-degrading Bacteroides, Bacteroides ovatus (Bo) and Bacteroides thetaiotaomicron (Bt). Bt growth is severely impaired by acarbose whereas Bo growth is not. The Bacteroides use a starch utilization system (Sus) to grow on starch. We hypothesized that Bo and Bt Sus enzymes are differentially inhibited by acarbose. Instead, we discovered that although acarbose primarily targets the Sus periplasmic GH97 enzymes in both organisms, the drug affects starch processing at multiple other points. Acarbose competes for transport through the Sus beta-barrel proteins and binds to the Sus transcriptional regulators. Further, Bo expresses a non-Sus GH97 (BoGH97D) when grown in starch with acarbose. The Bt homolog, BtGH97H, is not expressed in the same conditions, nor can overexpression of BoGH97D complement the Bt growth inhibition in the presence of acarbose. This work informs us about unexpected complexities of Sus function and regulation in Bacteroides, including variation between related species. Further, this indicates that the gut microbiome may be a source of variable response to acarbose treatment for diabetes.

Discovery of sparse, reliable omic biomarkers with Stabl.

Adoption of high-content omic technologies in clinical studies, coupled with computational methods, has yielded an abundance of candidate biomarkers. However, translating such findings into bona fide clinical biomarkers remains challenging. To facilitate this process, we introduce Stabl, a general machine learning method that identifies a sparse, reliable set of biomarkers by integrating noise injection and a data-driven signal-to-noise threshold into multivariable predictive modeling. Evaluation of Stabl on synthetic datasets and five independent clinical studies demonstrates improved biomarker sparsity and reliability compared to commonly used sparsity-promoting regularization methods while maintaining predictive performance; it distills datasets containing 1,400-35,000 features down to 4-34 candidate biomarkers. Stabl extends to multi-omic integration tasks, enabling biological interpretation of complex predictive models, as it hones in on a shortlist of proteomic, metabolomic and cytometric events predicting labor onset, microbial biomarkers of pre-term birth and a pre-operative immune signature of post-surgical infections. Stabl is available at https://github.com/gregbellan/Stabl .

Microbiome preterm birth DREAM challenge: Crowdsourcing machine learning approaches to advance preterm birth research.

Every year, 11% of infants are born preterm with significant health consequences, with the vaginal microbiome a risk factor for preterm birth. We crowdsource models to predict (1) preterm birth (PTB; <37 weeks) or (2) early preterm birth (ePTB; <32 weeks) from 9 vaginal microbiome studies representing 3,578 samples from 1,268 pregnant individuals, aggregated from public raw data via phylogenetic harmonization. The predictive models are validated on two independent unpublished datasets representing 331 samples from 148 pregnant individuals. The top-performing models (among 148 and 121 submissions from 318 teams) achieve area under the receiver operator characteristic (AUROC) curve scores of 0.69 and 0.87 predicting PTB and ePTB, respectively. Alpha diversity, VALENCIA community state types, and composition are important features in the top-performing models, most of which are tree-based methods. This work is a model for translation of microbiome data into clinically relevant predictive models and to better understand preterm birth.

Human Microbiomes and Disease for the Biomedical Data Scientist.

The human microbiome is complex, variable from person to person, essential for health, and related to both the risk for disease and the efficacy of our treatments. There are robust techniques to describe microbiota with high-throughput sequencing, and there are hundreds of thousands of already-sequenced specimens in public archives. The promise remains to use the microbiome both as a prognostic factor and as a target for precision medicine. However, when used as an input in biomedical data science modeling, the microbiome presents unique challenges. Here, we review the most common techniques used to describe microbial communities, explore these unique challenges, and discuss the more successful approaches for biomedical data scientists seeking to use the microbiome as an input in their studies.

MaLiAmPi enables generalizable and taxonomy-independent microbiome features from technically diverse 16S-based microbiome studies.

For studies using microbiome data, the ability to robustly combine data from technically and biologically distinct microbiome studies is a crucial means of supporting more robust and clinically relevant inferences. Formidable technical challenges arise when attempting to combine data from technically diverse 16S rRNA gene variable region amplicon sequencing (16S) studies. Closed operational taxonomic units and taxonomy are criticized as being heavily dependent upon reference sets and with limited precision relative to the underlying biology. Phylogenetic placement has been demonstrated to be a promising taxonomy-free manner of harmonizing microbiome data, but it has lacked a validated count-based feature suitable for use in machine learning and association studies. Here we introduce a phylogenetic-placement-based, taxonomy-independent, compositional feature of microbiota: phylotypes. Phylotypes were predictive of clinical outcomes such as obesity or pre-term birth on technically diverse independent validation sets harmonized post hoc. Thus, phylotypes enable the rigorous cross-validation of 16S-based clinical prognostic models and associative microbiome studies.

Feasibility of a dietary intervention to modify gut microbial metabolism in patients with hematopoietic stem cell transplantation.

Evaluation of the impact of dietary intervention on gastrointestinal microbiota and metabolites after allogeneic hematopoietic stem cell transplantation (HCT) is lacking. We conducted a feasibility study as the first of a two-phase trial. Ten adults received resistant potato starch (RPS) daily from day -7 to day 100. The primary objective was to test the feasibility of RPS and its effect on intestinal microbiome and metabolites, including the short-chain fatty acid butyrate. Feasibility met the preset goal of 60% or more, adhering to 70% or more doses; fecal butyrate levels were significantly higher when participants were on RPS than when they were not (P < 0.0001). An exploratory objective was to evaluate plasma metabolites. We observed longitudinal changes in plasma metabolites compared to baseline, which were independent of RPS (P < 0.0001). However, in recipients of RPS, the dominant plasma metabolites were more stable compared to historical controls with significant difference at engraftment (P < 0.05). These results indicate that RPS in recipients of allogeneic HCT is feasible; in this study, it was associated with significant alterations in intestinal and plasma metabolites. A phase 2 trial examining the effect of RPS on graft-versus-host disease in recipients of allogeneic HCT is underway. ClinicalTrials.gov registration: NCT02763033 .

Microbiome Preterm Birth DREAM Challenge: Crowdsourcing Machine Learning Approaches to Advance Preterm Birth Research.

Globally, every year about 11% of infants are born preterm, defined as a birth prior to 37 weeks of gestation, with significant and lingering health consequences. Multiple studies have related the vaginal microbiome to preterm birth. We present a crowdsourcing approach to predict: (a) preterm or (b) early preterm birth from 9 publicly available vaginal microbiome studies representing 3,578 samples from 1,268 pregnant individuals, aggregated from raw sequences via an open-source tool, MaLiAmPi. We validated the crowdsourced models on novel datasets representing 331 samples from 148 pregnant individuals. From 318 DREAM challenge participants we received 148 and 121 submissions for our two separate prediction sub-challenges with top-ranking submissions achieving bootstrapped AUROC scores of 0.69 and 0.87, respectively. Alpha diversity, VALENCIA community state types, and composition (via phylotype relative abundance) were important features in the top performing models, most of which were tree based methods. This work serves as the foundation for subsequent efforts to translate predictive tests into clinical practice, and to better understand and prevent preterm birth.

Exposure to antibiotics with anaerobic activity before respiratory viral infection is associated with respiratory disease progression after hematopoietic cell transplant.

We examined associations between specific antibiotic exposures and progression to lower respiratory tract disease (LRTD) following individual respiratory viral infections (RVIs) after hematopoietic cell transplantation (HCT). We analyzed allogeneic HCT recipients of all ages with their first RVI during the first 100 days post-HCT. For the 21 days before RVI onset, we recorded any receipt of specific groups of antibiotics, and the cumulative sum of the number of antibiotics received for each day (antibiotic-days). We used Cox proportional hazards models to assess the relationship between antibiotic exposure and progression to LRTD. Among 469 patients with RVI, 124 progressed to LRTD. Compared to no antibiotics, use of antibiotics with broad anaerobic activity in the prior 21 days was associated with progression to LRTD after adjusting for age, virus type, hypoalbuminemia, neutropenia, steroid use, and monocytopenia (HR 2.2, 95% CI 1.1-4.1). Greater use of those antibiotics (≥7 antibiotic days) was also associated with LRTD in adjusted models (HR 2.2, 95% CI 1.1-4.3). Results were similar after adjusting for lymphopenia instead of monocytopenia. Antibiotic use is associated with LRTD after RVI across different viruses in HCT recipients. Prospective studies using anaerobe-sparing antibiotics should be explored to assess impact on LRTD in patients undergoing HCT.

Mucolytic bacteria license pathobionts to acquire host-derived nutrients during dietary nutrient restriction.

Pathobionts employ unique metabolic adaptation mechanisms to maximize their growth in disease conditions. Adherent-invasive Escherichia coli (AIEC), a pathobiont enriched in the gut mucosa of patients with inflammatory bowel disease (IBD), utilizes diet-derived L-serine to adapt to the inflamed gut. Therefore, the restriction of dietary L-serine starves AIEC and limits its fitness advantage. Here, we find that AIEC can overcome this nutrient limitation by switching the nutrient source from the diet to the host cells in the presence of mucolytic bacteria. During diet-derived L-serine restriction, the mucolytic symbiont Akkermansia muciniphila promotes the encroachment of AIEC to the epithelial niche by degrading the mucus layer. In the epithelial niche, AIEC acquires L-serine from the colonic epithelium and thus proliferates. Our work suggests that the indirect metabolic network between pathobionts and commensal symbionts enables pathobionts to overcome nutritional restriction and thrive in the gut.

SARS-CoV-2 vaccines: a triumph of science and collaboration.

Roughly 1 year after the first case of COVID-19 was identified and less than 1 year after the sequencing of SARS-CoV-2, multiple SARS-CoV-2 vaccines with demonstrated safety and efficacy in phase III clinical trials are available. The most promising vaccines have targeted the surface glycoprotein (S-protein) of SARS-CoV-2 and achieved an approximate 85%-95% reduction in the risk of symptomatic COVID-19, while retaining excellent safety profiles and modest side effects in the phase III clinical trials. The mRNA, replication-incompetent viral vector, and protein subunit vaccine technologies have all been successfully employed. Some novel SARS-CoV-2 variants evade but do not appear to fully overcome the potent immunity induced by these vaccines. Emerging real-world effectiveness data add evidence for protection from severe COVID-19. This is an impressive first demonstration of the effectiveness of the mRNA vaccine and vector vaccine platforms. The success of SARS-CoV-2 vaccine development should be credited to open science, industry partnerships, harmonization of clinical trials, and the altruism of study participants. The manufacturing and distribution of the emergency use-authorized SARS-CoV-2 vaccines are ongoing challenges. What remains now is to ensure broad and equitable global vaccination against COVID-19.

Comparative Analysis of Public RNA-Sequencing Data from Human Intestinal Enteroid (HIEs) Infected with Enteric RNA Viruses Identifies Universal and Virus-Specific Epithelial Responses.

Acute gastroenteritis (AGE) has a significant disease burden on society. Noroviruses, rotaviruses, and astroviruses are important viral causes of AGE but are relatively understudied enteric pathogens. Recent developments in novel biomimetic human models of enteric disease are opening new possibilities for studying human-specific host-microbe interactions. Human intestinal enteroids (HIE), which are epithelium-only intestinal organoids derived from stem cells isolated from human intestinal biopsy tissues, have been successfully used to culture representative norovirus, rotavirus, and astrovirus strains. Previous studies investigated host-virus interactions at the intestinal epithelial interface by individually profiling the epithelial transcriptional response to a member of each virus family by RNA sequencing (RNA-seq). Despite differences in the tissue origin, enteric virus used, and hours post infection at which RNA was collected in each data set, the uniform analysis of publicly available datasets identified a conserved epithelial response to virus infection focused around "type I interferon production" and interferon-stimulated genes. Additionally, transcriptional changes specific to only one or two of the enteric viruses were also identified. This study can guide future explorations into common and unique aspects of the host response to virus infections in the human intestinal epithelium and demonstrates the promise of comparative RNA-seq analysis, even if performed under different experimental conditions, to discover universal and virus-specific genes and pathways responsible for antiviral host defense.