The intestinal microbiota is a complex community of bacteria, archaea, viruses, protists and fungi
. Although the composition of bacterial constituents has been linked to immune homeostasis and ...infectious susceptibility
, the role of non-bacterial constituents and cross-kingdom microbial interactions in these processes is poorly understood
. Fungi represent a major cause of infectious morbidity and mortality in immunocompromised individuals, although the relationship of intestinal fungi (that is, the mycobiota) with fungal bloodstream infections remains undefined
. We integrated an optimized bioinformatics pipeline with high-resolution mycobiota sequencing and comparative genomic analyses of fecal and blood specimens from recipients of allogeneic hematopoietic cell transplant. Patients with Candida bloodstream infection experienced a prior marked intestinal expansion of pathogenic Candida species; this expansion consisted of a complex dynamic between multiple species and subspecies with a stochastic translocation pattern into the bloodstream. The intestinal expansion of pathogenic Candida spp. was associated with a substantial loss in bacterial burden and diversity, particularly in the anaerobes. Thus, simultaneous analysis of intestinal fungi and bacteria identifies dysbiosis states across kingdoms that may promote fungal translocation and facilitate invasive disease. These findings support microbiota-driven approaches to identify patients at risk of fungal bloodstream infections for pre-emptive therapeutic intervention.
is a foodborne pathogen that causes septicemia, meningitis and chorioamnionitis and is associated with high mortality. Immunocompetent humans and animals, however, can tolerate high doses of
without ...developing systemic disease. The intestinal microbiota provides colonization resistance against many orally acquired pathogens, and antibiotic-mediated depletion of the microbiota reduces host resistance to infection. Here we show that a diverse microbiota markedly reduces
colonization of the gut lumen and prevents systemic dissemination. Antibiotic administration to mice before low dose oral inoculation increases
growth in the intestine. In immunodeficient or chemotherapy-treated mice, the intestinal microbiota provides nonredundant defense against lethal, disseminated infection. We have assembled a consortium of commensal bacteria belonging to the Clostridiales order, which exerts in vitro antilisterial activity and confers in vivo resistance upon transfer into germ free mice. Thus, we demonstrate a defensive role of the gut microbiota against
infection and identify intestinal commensal species that, by enhancing resistance against this pathogen, represent potential probiotics.
Intestinal commensal bacteria can inhibit dense colonization of the gut by vancomycin-resistant Enterococcus faecium (VRE), a leading cause of hospital-acquired infections
. A four-strained ...consortium of commensal bacteria that contains Blautia producta BP
can reverse antibiotic-induced susceptibility to VRE infection
. Here we show that BP
reduces growth of VRE by secreting a lantibiotic that is similar to the nisin-A produced by Lactococcus lactis. Although the growth of VRE is inhibited by BP
and L. lactis in vitro, only BP
colonizes the colon and reduces VRE density in vivo. In comparison to nisin-A, the BP
lantibiotic has reduced activity against intestinal commensal bacteria. In patients at high risk of VRE infection, high abundance of the lantibiotic gene is associated with reduced density of E. faecium. In germ-free mice transplanted with patient-derived faeces, resistance to VRE colonization correlates with abundance of the lantibiotic gene. Lantibiotic-producing commensal strains of the gastrointestinal tract reduce colonization by VRE and represent potential probiotic agents to re-establish resistance to VRE.
As of 10 April 2020, New York State had 180,458 cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and 9,385 reported deaths. Patients with cancer comprised 8.4% of deceased ...individuals
. Population-based studies from China and Italy suggested a higher coronavirus disease 2019 (COVID-19) death rate in patients with cancer
, although there is a knowledge gap as to which aspects of cancer and its treatment confer risk of severe COVID-19
. This information is critical to balance the competing safety considerations of reducing SARS-CoV-2 exposure and cancer treatment continuation. From 10 March to 7 April 2020, 423 cases of symptomatic COVID-19 were diagnosed at Memorial Sloan Kettering Cancer Center (from a total of 2,035 patients with cancer tested). Of these, 40% were hospitalized for COVID-19, 20% developed severe respiratory illness (including 9% who required mechanical ventilation) and 12% died within 30 d. Age older than 65 years and treatment with immune checkpoint inhibitors (ICIs) were predictors for hospitalization and severe disease, whereas receipt of chemotherapy and major surgery were not. Overall, COVID-19 in patients with cancer is marked by substantial rates of hospitalization and severe outcomes. The association observed between ICI and COVID-19 outcomes in our study will need further interrogation in tumor-specific cohorts.
Respiratory viral infections are frequent in patients undergoing allogeneic hematopoietic stem cell transplantation (allo-HCT) and can potentially progress to lower respiratory tract infection ...(LRTI). The intestinal microbiota contributes to resistance against viral and bacterial pathogens in the lung. However, whether intestinal microbiota composition and associated changes in microbe-derived metabolites contribute to the risk of LRTI following upper respiratory tract viral infection remains unexplored in the setting of allo-HCT. Fecal samples from 360 allo-HCT patients were collected at the time of stem cell engraftment and subjected to deep, 16S ribosomal RNA gene sequencing to determine microbiota composition, and short-chain fatty acid levels were determined in a nested subset of fecal samples. The development of respiratory viral infections and LRTI was determined for 180 days following allo-HCT. Clinical and microbiota risk factors for LRTI were subsequently evaluated using survival analysis. Respiratory viral infection occurred in 149 (41.4%) patients. Of those, 47 (31.5%) developed LRTI. Patients with higher abundances of butyrate-producing bacteria were fivefold less likely to develop viral LRTI, independent of other factors (adjusted hazard ratio = 0.22, 95% confidence interval 0.04-0.69). Higher representation of butyrate-producing bacteria in the fecal microbiota is associated with increased resistance against respiratory viral infection with LRTI in allo-HCT patients.
•Butyrate-producing bacteria abundance is correlated with protection against viral LRTI following allo-HCT.
Display omitted
Pulmonary complications (PCs) cause significant morbidity and mortality after allogeneic hematopoietic stem cell transplantation (HCT). Shifts in gut microbiota have been linked to HCT outcomes; ...however, their effect on PCs is unknown.
To investigate whether changes in gut microbiota are associated with PCs after HCT.
A single-center observational study was performed on 94 patients who underwent HCT from 2009 to 2011 and who were previously enrolled in a protocol for 16S ribosomal RNA sequencing of fecal microbiota. The primary endpoint, PC, was defined by new abnormal parenchymal findings on chest imaging in the setting of respiratory signs and/or symptoms. Outcomes were collected up to 40 months after transplant. Clinical and microbiota risk factors for PCs and mortality were evaluated using survival analysis.
One hundred twelve PCs occurred in 66 (70.2%) subjects. A high comorbidity index (hazard ratio HR, 2.30; 95% confidence interval CI, 1.30-4.00; P = 0.004), fluoroquinolones (HR, 2.29, 95% CI, 1.32-3.98; P = 0.003), low baseline diversity (HR, 2.63; 95% CI, 1.22-5.32; P = 0.015), and γ-proteobacteria domination of fecal microbiota (HR, 2.64; 95% CI, 1.10-5.65; P = 0.031), which included common respiratory pathogens, predicted PCs. In separate analyses, low baseline diversity was associated with PCs that occurred preengraftment (HR, 6.30; 95% CI, 1.42-31.80; P = 0.016), whereas γ-proteobacteria domination predicted PCs postengraftment (HR, 3.68; 95% CI, 1.49-8.21; P = 0.006) and overall mortality (HR, 3.52; 95% CI, 1.28-9.21; P = 0.016). Postengraftment PCs were also independent predictors of death (HR, 2.50; 95% CI, 1.25-5.22; P = 0.009).
This is the first study to demonstrate prospective changes in gut microbiota associated with PCs after HCT. Postengraftment PCs and γ-proteobacteria domination were predictive of mortality. This suggests an adverse relationship between the graft and lung, which is perhaps mediated by bacterial composition in the gut. Further study is warranted.
Highly diverse bacterial populations inhabit the gastrointestinal tract and modulate host inflammation and promote immune tolerance. In allogeneic hematopoietic stem cell transplantation (allo-HSCT), ...the gastrointestinal mucosa is damaged, and colonizing bacteria are impacted, leading to an impaired intestinal microbiota with reduced diversity. We examined the impact of intestinal diversity on subsequent mortality outcomes following transplantation. Fecal specimens were collected from 80 recipients of allo-HSCT at the time of stem cell engraftment. Bacterial 16S rRNA gene sequences were characterized, and microbial diversity was estimated using the inverse Simpson index. Subjects were classified into high, intermediate, and low diversity groups and assessed for differences in outcomes. Mortality outcomes were significantly worse in patients with lower intestinal diversity; overall survival at 3 years was 36%, 60%, and 67% for low, intermediate, and high diversity groups, respectively (P = .019, log-rank test). Low diversity showed a strong effect on mortality after multivariate adjustment for other clinical predictors (transplant related mortality: adjusted hazard ratio, 5.25; P = .014). In conclusion, the diversity of the intestinal microbiota at engraftment is an independent predictor of mortality in allo-HSCT recipients. These results indicate that the intestinal microbiota may be an important factor in the success or failure in allo-HSCT.
•Intestinal diversity is predictive of mortality in allo-HSCT.
Antibiotic treatment can deplete the commensal bacteria of a patient's gut microbiota and, paradoxically, increase their risk of subsequent infections. In allogeneic hematopoietic stem cell ...transplantation (allo-HSCT), antibiotic administration is essential for optimal clinical outcomes but significantly disrupts intestinal microbiota diversity, leading to loss of many beneficial microbes. Although gut microbiota diversity loss during allo-HSCT is associated with increased mortality, approaches to reestablish depleted commensal bacteria have yet to be developed. We have initiated a randomized, controlled clinical trial of autologous fecal microbiota transplantation (auto-FMT) versus no intervention and have analyzed the intestinal microbiota profiles of 25 allo-HSCT patients (14 who received auto-FMT treatment and 11 control patients who did not). Changes in gut microbiota diversity and composition revealed that the auto-FMT intervention boosted microbial diversity and reestablished the intestinal microbiota composition that the patient had before antibiotic treatment and allo-HSCT. These results demonstrate the potential for fecal sample banking and posttreatment remediation of a patient's gut microbiota after microbiota-depleting antibiotic treatment during allo-HSCT.
Dramatic microbiota changes and loss of commensal anaerobic bacteria are associated with adverse outcomes in hematopoietic cell transplantation (HCT) recipients. In this study, we demonstrate these ...dynamic changes at high resolution through daily stool sampling and assess the impact of individual antibiotics on those changes. We collected 272 longitudinal stool samples (with mostly daily frequency) from 18 patients undergoing HCT and determined their composition by multiparallel 16S rRNA gene sequencing as well as the density of bacteria in stool by quantitative PCR (qPCR). We calculated microbiota volatility to quantify rapid shifts and developed a new dynamic systems inference method to assess the specific impact of antibiotics. The greatest shifts in microbiota composition occurred between stem cell infusion and reconstitution of healthy immune cells. Piperacillin-tazobactam caused the most severe declines among obligate anaerobes. Our approach of daily sampling, bacterial density determination, and dynamic systems modeling allowed us to infer the independent effects of specific antibiotics on the microbiota of HCT patients.
Accurately predicting outcomes for cancer patients with COVID-19 has been clinically challenging. Numerous clinical variables have been retrospectively associated with disease severity, but the ...predictive value of these variables, and how multiple variables interact to increase risk, remains unclear.
We used machine learning algorithms to predict COVID-19 severity in 348 cancer patients at Memorial Sloan Kettering Cancer Center in New York City. Using only clinical variables collected on or before a patient's COVID-19 positive date (time zero), we sought to classify patients into one of three possible future outcomes: Severe-early (the patient required high levels of oxygen support within 3 days of being tested positive for COVID-19), Severe-late (the patient required high levels of oxygen after 3 days), and Non-severe (the patient never required oxygen support).
Our algorithm classified patients into these classes with an area under the receiver operating characteristic curve (AUROC) ranging from 70 to 85%, significantly outperforming prior methods and univariate analyses. Critically, classification accuracy is highest when using a potpourri of clinical variables - including basic patient information, pre-existing diagnoses, laboratory and radiological work, and underlying cancer type - suggesting that COVID-19 in cancer patients comes with numerous, combinatorial risk factors.
Overall, we provide a computational tool that can identify high-risk patients early in their disease progression, which could aid in clinical decision-making and selecting treatment options.
PDF
