Biology subjects

Firek, B. A.

Publications and source records attributed to Firek, B. A..

7 recordsLinked to original sources

bioRxiv2023

Infant gut bacteriophage strain persistence during the first three years of life

Bacteriophages are key components of gut microbiomes, yet the phage colonization process in the infant gut remains uncertain. Here, we established a large phage sequence database and used strain-resolved analyses to investigate phage succession in infants throughout the first three years of life. Analysis of 819 fecal metagenomes collected from 28 full-term and 24 preterm infants and their mothers revealed that early-life phageome richness increased over time and reached adult-like complexity by age three. Approximately 9% of early phage colonizers, mostly maternally transmitted and infecting Bacteroides, persisted for three years and were more prevalent in full-term than in preterm infants. Although rare, phages with stop codon reassignment were more likely to persist than non-recoded phages and generally displayed an increase in in-frame re-assigned stop codons over three years. Overall, maternal seeding, stop codon reassignment, host CRISPR-Cas locus prevalence, and diverse phage populations contribute to stable viral colonization.

microbiology↗

bioRxiv2022

Using strain-resolved analysis to identify contamination in metagenomics data

Metagenomics analyses can be negatively impacted by DNA contamination. While external sources of contamination such as DNA extraction kits have been widely reported and investigated, contamination originating within the study itself remains underreported. Here we applied high-resolution strain-resolved analyses to identify contamination in two large-scale clinical metagenomics datasets. By mapping strain sharing to DNA extraction plates, we identified well-to-well contamination in both negative controls and biological samples in one dataset. Such contamination is more likely to occur among samples that are on the same or adjacent columns or rows of the extraction plate than samples that are far apart. Our strain-resolved workflow also reveals the presence of externally derived contamination, primarily in the other dataset. Overall in both datasets, contamination is more significant in samples with lower biomass. Our work demonstrates that genome-resolved strain tracking, with its essentially genome-wide nucleotide-level resolution, can be used to detect contamination in sequencing-based microbiome studies. Our results underscore the value of strain-specific methods to detect contamination and the critical importance of looking for contamination beyond negative and positive controls.

microbiology↗

bioRxiv2021

Infant gut strain persistence is associated with maternal origin, phylogeny, and functional potential including surface adhesion and iron acquisition

Gut microbiome succession impacts infant development. However, it remains unclear what factors promote persistence of initial bacterial colonists in the developing gut. Here, we performed strain-resolved metagenomic analyses to compare gut colonization of preterm and full-term infants throughout the first year of life and evaluated links between strain persistence and strain origin as well as genetic potential. Analysis of 206 fecal metagenomes collected from full-term and preterm infants and their mothers revealed that infants initially distinct microbial communities converged by age one. Approximately 11% of early colonists, primarily Bacteroides and Bifidobacterium, persisted during the first year of life, and these were more prevalent in full-term compared to preterm infants. Gut-associated strains from mothers were significantly more likely to persist in the infant gut than other strains. Enrichment in genes for surface adhesion, iron acquisition and carbohydrate degradation may explain persistence of some strains through the first year of life.

microbiology↗

bioRxiv2020

Genetic and behavioral adaptation of Candida parapsilosis to the microbiome of hospitalized infants revealed by in situ genomics, transcriptomics and proteomics

Candida parapsilosis is a common cause of invasive candidiasis, especially in newborn infants, and infections have been increasing over the past two decades. C. parapsilosis has been primarily studied in pure culture, leaving gaps in understanding of its function in microbiome context. Here, we reconstructed five unique C. parapsilosis genomes from premature infant fecal samples and analyzed their genome structure, population diversity and in situ activity relative to reference strains in pure culture. All five genomes contain hotspots of single nucleotide variants, some of which are shared by strains from multiple hospitals. A subset of environmental and hospital-derived genomes share variants within these hotspots suggesting derivation of that region from a common ancestor. Four of the newly reconstructed C. parapsilosis genomes have four to sixteen copies of the gene RTA3, which encodes a lipid translocase and is implicated in antifungal resistance, potentially indicating adaptation to hospital antifungal use. Time course metatranscriptomics and metaproteomics on fecal samples from a premature infant with a C. parapsilosis blood infection revealed highly variable in situ expression patterns that are distinct from those of similar strains in pure cultures. For example, biofilm formation genes were relatively less expressed in situ, whereas genes linked to oxygen utilization were more highly expressed, indicative of growth in a relatively aerobic environment. In gut microbiome samples, C. parapsilosis coexisted with Enterococcus faecalis that shifted in relative abundance over time, accompanied by changes in bacterial and fungal gene expression and proteome composition. The results reveal potentially medically relevant differences in Candida function in gut vs. laboratory environments, and constrain evolutionary processes that could contribute to hospital strain persistence and transfer into premature infant microbiomes.

microbiology↗

bioRxiv2019

Necrotizing enterocolitis is preceded by increased gut bacterial replication, Klebsiella, and fimbriae-encoding bacteria that may stimulate TLR4 receptors

Necrotizing enterocolitis (NEC) is a devastating intestinal disease that occurs primarily in premature infants. We performed genome-resolved metagenomic analysis of 1,163 fecal samples from premature infants to identify microbial features predictive of NEC. Features considered include genes, bacterial strain types, eukaryotes, bacteriophages, plasmids and growth rates. A machine learning classifier found that samples collected prior to NEC diagnosis harbored significantly more Klebsiella, bacteria encoding fimbriae, and bacteria encoding secondary metabolite gene clusters related to quorum sensing and bacteriocin production. Notably, replication rates of all bacteria, especially Enterobacteriaceae, were significantly higher two days before NEC diagnosis. The findings uncover biomarkers that could lead to early detection of NEC and targets for microbiome-based therapeutics.

microbiology↗

bioRxiv2018

Strain-level overlap between infant and hospital fungal microbiomes revealed through de novo assembly of eukaryotic genomes from metagenomes

Eukaryotes are a leading cause of nosocomial infections in neonates, but their diversity and population heterogeneity are rarely investigated. This has led to an incomplete understanding of eukaryotic strains that colonize infants and of the neonatal intensive care unit (NICU) as a possible source of these strains. Analysis of 1,174 time-series metagenomes from 161 premature infants revealed fungal colonization of 13 infants, primarily in the first two weeks of life. Nearly all 24 NICU samples contained eukaryotes, and the most diverse communities were in NICU sinks. Five of fourteen newly-assembled eukaryotic genomes derived from genomically undescribed species. Purpureocillium lilacinum genomes from infant and NICU samples shared 99.999% average nucleotide identity, highlighting the potential of hospital-associated fungi to colonize hospitalized infants. We quantified zygosity and within-population variation associated with the diploid eukaryotes, and thus defined the genetic reservoirs of eukaryotes in room environments and infants.

microbiology↗

bioRxiv2018

The developing premature infant gut microbiome is a major factor shaping the microbiome of neonatal intensive care unit rooms

1.1BackgroundThe neonatal intensive care unit (NICU) contains a unique cohort of patients with underdeveloped immune systems and nascent microbiome communities. Patients often spend several months in the same room and it has been previously shown that the gut microbiomes of these infants often resemble the microbes found in the NICU. Little is known, however, about the identity, persistence and absolute abundance of NICU room-associated bacteria over long stretches of time. Here we couple droplet digital PCR (ddPCR), 16S rRNA gene surveys, and recently published metagenomics data from infant gut samples to infer the extent to which the NICU microbiome is shaped by its room occupants.\n\nResultsOver 2,832 swabs, wipes, and air samples were collected from sixteen private-style NICU rooms housing very low birthweight (<1,500 g), premature (<31 weeks gestation) infants. For each infant, room samples were collected daily, Monday through Friday, for one month. The first samples from the first infant and last samples from the last infant were collected 383 days apart. Twenty-two NICU locations spanning room surfaces, hands, electronics, sink basins, and air were collected. Results point to an incredibly simple room community where 5-10 taxa, mostly skin associated, account for over 50% of 16S reads. Biomass estimates reveal 4-5 orders of magnitude difference between the least to the most dense microbial communities, air and sink basins, respectively. Biomass trends from bioaerosol samples and petri dish dust collectors suggest occupancy to be a main driver of suspended biological particles within the NICU. Using a machine learning algorithm to classify the origin of room samples, we show that each room has a unique microbial fingerprint. Several important taxa driving this model were dominant gut colonizers of infants housed within each room.\n\nConclusionsDespite regular cleaning of hospital surfaces, bacterial biomass was detectable at varying densities. A room specific microbiome signature was detected, suggesting microbes seeding NICU surfaces are sourced from reservoirs within the room and that these reservoirs contain actively dividing cells. Collectively, the data suggests that hospitalized infants, in combination with their caregivers, shape the microbiome of NICU rooms.

microbiology↗