Human milk cream alters intestinal microbiome of preterm infants: a prospective cohort study.

BACKGROUND: In very low birth weight (VLBW) infants, human milk cream added to standard human milk fortification is used to improve growth. This study aimed to evaluate the impact of cream supplement on the intestinal microbiome of VLBW infants. METHODS: Whole genome shotgun sequencing was performed on stool (n = 57) collected from a cohort of 23 infants weighing 500-1250 grams (control = 12, cream = 11). Both groups received an exclusive human milk diet (mother's own milk, donor human milk, and donor human milk-derived fortifier) with the cream group receiving an additional 2 kcal/oz cream at 100 mL/kg/day of fortified feeds and then 4 kcal/oz if poor growth. RESULTS: While there were no significant differences in alpha diversity, infants receiving cream significantly differed from infants in the control group in beta diversity. Cream group samples had significantly higher prevalence of Proteobacteria and significantly lower Firmicutes compared to control group. Klebsiella species dominated the microbiota of cream-exposed infants, along with bacterial pathways involved in lipid metabolism and metabolism of cofactors and amino acids. CONCLUSIONS: Cream supplementation significantly altered composition of the intestinal microbiome of VLBW infants to favor increased prevalence of Proteobacteria and functional gene content associated with these bacteria. IMPACT: We report changes to the intestinal microbiome associated with administration of human milk cream; a novel supplement used to improve growth rates of preterm very low birth weight infants. Since little is known about the impact of cream on intestinal microbiota composition of very low birth weight infants, our study provides valuable insight on the effects of diet on the microbiome of this population. Dietary supplements administered to preterm infants in neonatal intensive care units have the potential to influence the intestinal microbiome composition which may affect overall health status of the infant.

Tryptophan Metabolites And Their Predicted Microbial Sources In Fecal Samples From Healthy Individuals.

Gut microbiota produce tryptophan metabolites (TMs) important to homeostasis. However, measuring TM levels in stool and determining their microbial sources can be difficult. Here, we measured TMs from the indole pathway in fecal samples from 21 healthy adults with the goal to: 1) determine fecal TM concentrations in healthy individuals; 2) link TM levels to bacterial abundance using 16S and whole genome shotgun (WGS) sequencing data; and 3) predict likely bacterial sources of TM production. Within our samples, we identified 151 genera (16S) and 592 bacterial species (WGS). Eight TMs were found in ≥17 fecal samples, including four in all persons. To our knowledge, we are the first to report fecal levels for indole-3-lactate, indole-3-propionate, and 3-indoleacrylate levels in healthy persons. Overall, indole, indole-3-acetate (IAA), and skatole accounted for 86% of the eight TMs measured. Significant correlations were found between seven TMs and 29 bacterial species.  Predicted multiple TM sources support the notion of a complex network of TM production and regulation. Further, the data suggest key roles for Collinsella aerofaciens and IAA, a metabolite reported to maintain intestinal homeostasis through enhanced barrier integrity and anti-inflammatory/antioxidant activities. These findings extend our understanding of TMs and their relationship to the microbial species that act as effectors and/or regulators in the healthy intestine and may lead to novel strategies designed to manipulate tryptophan metabolism to prevent disease and/or restore health to the dysbiotic gut.

Wastewater sequencing reveals community and variant dynamics of the collective human virome.

Wastewater is a discarded human by-product, but its analysis may help us understand the health of populations. Epidemiologists first analyzed wastewater to track outbreaks of poliovirus decades ago, but so-called wastewater-based epidemiology was reinvigorated to monitor SARS-CoV-2 levels while bypassing the difficulties and pit falls of individual testing. Current approaches overlook the activity of most human viruses and preclude a deeper understanding of human virome community dynamics. Here, we conduct a comprehensive sequencing-based analysis of 363 longitudinal wastewater samples from ten distinct sites in two major cities. Critical to detection is the use of a viral probe capture set targeting thousands of viral species or variants. Over 450 distinct pathogenic viruses from 28 viral families are observed, most of which have never been detected in such samples. Sequencing reads of established pathogens and emerging viruses correlate to clinical data sets of SARS-CoV-2, influenza virus, and monkeypox viruses, outlining the public health utility of this approach. Viral communities are tightly organized by space and time. Finally, the most abundant human viruses yield sequence variant information consistent with regional spread and evolution. We reveal the viral landscape of human wastewater and its potential to improve our understanding of outbreaks, transmission, and its effects on overall population health.

Functional Genomics of Gastrointestinal Escherichia coli Isolated from Patients with Cancer and Diarrhea.

We describe the epidemiology and clinical characteristics of 29 patients with cancer and diarrhea in whom Enteroaggregative Escherichia coli (EAEC) was initially identified by GI BioFire panel multiplex. E. coli strains were successfully isolated from fecal cultures in 14 of 29 patients. Six of the 14 strains were identified as EAEC and 8 belonged to other diverse E. coli groups of unknown pathogenesis. We investigated these strains by their adherence to human intestinal organoids, cytotoxic responses, antibiotic resistance profile, full sequencing of their genomes, and annotation of their functional virulome. Interestingly, we discovered novel and enhanced adherence and aggregative patterns for several diarrheagenic pathotypes that were not previously seen when co-cultured with immortalized cell lines. EAEC isolates displayed exceptional adherence and aggregation to human colonoids compared not only to diverse GI E. coli , but also compared to prototype strains of other diarrheagenic E. coli . Some of the diverse E. coli strains that could not be classified as a conventional pathotype also showed an enhanced aggregative and cytotoxic response. Notably, we found a high carriage rate of antibiotic resistance genes in both EAEC strains and diverse GI E. coli isolates and observed a positive correlation between adherence to colonoids and the number of metal acquisition genes carried in both EAEC and the diverse E. coli strains. This work indicates that E. coli from cancer patients constitute strains of remarkable pathotypic and genomic divergence, including strains of unknown disease etiology with unique virulomes. Future studies will allow for the opportunity to re-define E. coli pathotypes with greater diagnostic accuracy and into more clinically relevant groupings.

Wastewater pandemic preparedness: Toward an end-to-end pathogen monitoring program.

Molecular analysis of public wastewater has great potential as a harbinger for community health and health threats. Long-used to monitor the presence of enteric viruses, in particular polio, recent successes of wastewater as a reliable lead indicator for trends in SARS-CoV-2 levels and hospital admissions has generated optimism and emerging evidence that similar science can be applied to other pathogens of pandemic potential (PPPs), especially respiratory viruses and their variants of concern (VOC). However, there are substantial challenges associated with implementation of this ideal, namely that multiple and distinct fields of inquiry must be bridged and coordinated. These include engineering, molecular sciences, temporal-geospatial analytics, epidemiology and medical, and governmental and public health messaging, all of which present their own caveats. Here, we outline a framework for an integrated, state-wide, end-to-end human pathogen monitoring program using wastewater to track viral PPPs.

Multiple Respiratory Syncytial Virus (RSV) Strains Infecting HEp-2 and A549 Cells Reveal Cell Line-Dependent Differences in Resistance to RSV Infection.

Respiratory syncytial virus (RSV) is a leading cause of pediatric acute respiratory infection worldwide. There are currently no approved vaccines or antivirals to combat RSV disease. A few transformed cell lines and two historic strains have been extensively used to study RSV. Here, we reported a thorough molecular and cell biological characterization of HEp-2 and A549 cells infected with one of four strains of RSV representing both major subgroups as well as historic and more contemporary genotypes (RSV/A/Tracy [GA1], RSV/A/Ontario [ON], RSV/B/18537 [GB1], and RSV/B/Buenos Aires [BA]) via measurements of viral replication kinetics and viral gene expression, immunofluorescence-based imaging of gross cellular morphology and cell-associated RSV, and measurements of host response, including transcriptional changes and levels of secreted cytokines and growth factors. IMPORTANCE Infection with the respiratory syncytial virus (RSV) early in life is essentially guaranteed and can lead to severe disease. Most RSV studies have involved either of two historic RSV/A strains infecting one of two cell lines, HEp-2 or A549 cells. However, RSV contains ample variation within two evolving subgroups (A and B), and HEp-2 and A549 cell lines are genetically distinct. Here, we measured viral action and host response in both HEp-2 and A549 cells infected with four RSV strains from both subgroups and representing both historic and more contemporary strains. We discovered a subgroup-dependent difference in viral gene expression and found A549 cells were more potently antiviral and more sensitive, albeit subtly, to viral variation. Our findings revealed important differences between RSV subgroups and two widely used cell lines and provided baseline data for experiments with model systems better representative of natural RSV infection.

Modeling nonsegmented negative-strand RNA virus (NNSV) transcription with ejective polymerase collisions and biased diffusion.

Infections by non-segmented negative-strand RNA viruses (NNSV) are widely thought to entail gradient gene expression from the well-established existence of a single promoter at the 3' end of the viral genome and the assumption of constant transcriptional attenuation between genes. But multiple recent studies show viral mRNA levels in infections by respiratory syncytial virus (RSV), a major human pathogen and member of NNSV, that are inconsistent with a simple gradient. Here we integrate known and newly predicted phenomena into a biophysically reasonable model of NNSV transcription. Our model succeeds in capturing published observations of respiratory syncytial virus and vesicular stomatitis virus (VSV) mRNA levels. We therefore propose a novel understanding of NNSV transcription based on the possibility of ejective polymerase-polymerase collisions and, in the case of RSV, biased polymerase diffusion.

Evidence of recombination in coronaviruses implicating pangolin origins of nCoV-2019.

A novel coronavirus (nCoV-2019) was the cause of an outbreak of respiratory illness detected in Wuhan, Hubei Province, China in December of 2019. Genomic analyses of nCoV-2019 determined a 96% resemblance with a coronavirus isolated from a bat in 2013 (RaTG13); however, the receptor binding motif (RBM) of these two genomes share low sequence similarity. This divergence suggests a possible alternative source for the RBM coding sequence in nCoV-2019. We identified high sequence similarity in the RBM between nCoV-2019 and a coronavirus genome reconstructed from a viral metagenomic dataset from pangolins possibly indicating a more complex origin for nCoV-2019.