Microbiome

The source inoculum of gastrointestinal tract (GIT) microbes is largely influenced by delivery mode in full-term infants, but these influences may be decoupled in very low birth weight (VLBW, <1,500 g) neonates via conventional broad-spectrum antibiotic treatment. We hypothesize the built environment (BE), specifically room surfaces frequently touched by humans, is a predominant source of colonizing microbes in the gut of premature VLBW infants. Here, we present the first matched fecal-BE time series analysis of two preterm VLBW neonates housed in a neonatal intensive care unit (NICU) over the first month of life.

Fresh fecal samples were collected every 3 days and metagenomes sequenced on an Illumina HiSeq2000 device. For each fecal sample, approximately 33 swabs were collected from each NICU room from 6 specified areas: sink, feeding and intubation tubing, hands of healthcare providers and parents, general surfaces, and nurse station electronics (keyboard, mouse, and cell phone). Swabs were processed using a recently developed ‘expectation maximization iterative reconstruction of genes from the environment’ (EMIRGE) amplicon pipeline in which full-length 16S rRNA amplicons were sheared and sequenced using an Illumina platform, and short reads reassembled into full-length genes. Over 24,000 full-length 16S rRNA sequences were produced, generating an average of approximately 12,000 operational taxonomic units (OTUs) (clustered at 97% nucleotide identity) per room-infant pair. Dominant gut taxa, including Staphylococcus epidermidis, Klebsiella pneumoniae, Bacteroides fragilis, and Escherichia coli, were widely distributed throughout the room environment with many gut colonizers detected in more than half of samples. Reconstructed genomes from infant gut colonizers revealed a suite of genes that confer resistance to antibiotics (for example, tetracycline, fluoroquinolone, and aminoglycoside) and sterilizing agents, which likely offer a competitive advantage in the NICU environment.

We have developed a high-throughput culture-independent approach that integrates room surveys based on full-length 16S rRNA gene sequences with metagenomic analysis of fecal samples collected from infants in the room. The approach enabled identification of discrete ICU reservoirs of microbes that also colonized the infant gut and provided evidence for the presence of certain organisms in the room prior to their detection in the gut.

The deep mechanisms (deterministic and/or stochastic processes) underlying community assembly are a central challenge in microbial ecology. However, the relative importance of these processes in shaping riverine microeukaryotic biogeography is still poorly understood. Here, we compared the spatiotemporal and biogeographical patterns of microeukaryotic community using high-throughput sequencing of 18S rRNA gene and multivariate statistical analyses from a subtropical river during wet and dry seasons.

Our results provide the first description of biogeographical patterns of microeukaryotic communities in the Tingjiang River, the largest river in the west of Fujian province, southeastern China. The results showed that microeukaryotes from both wet and dry seasons exhibited contrasting community compositions, which might be owing to planktonic microeukaryotes having seasonal succession patterns. Further, all components of the microeukaryotic communities (including total, dominant, always rare, and conditionally rare taxa) exhibited a significant distance-decay pattern in both seasons, and these communities had a stronger distance-decay relationship during the dry season, especially for the conditionally rare taxa. Although several variables had a significant influence on the microeukaryotic communities, the environmental and spatial factors showed minor roles in shaping the communities. Importantly, these microeukaryotic communities were strongly driven by stochastic processes, with 89.9%, 88.5%, and 89.6% of the community variation explained by neutral community model during wet, dry, and both seasons, respectively. The neutral community model also explained a large fraction of the community variation across different taxonomic groups and levels. Additionally, the microeukaryotic taxa, which were above and below the neutral prediction, were ecologically and taxonomically distinct groups, which might be interactively structured by deterministic and stochastic processes.

This study demonstrated that stochastic processes are sufficient in shaping substantial variation in river microeukaryotic metacommunity across different hydrographic regimes, thereby providing a better understanding of spatiotemporal patterns, processes, and mechanisms of microeukaryotic community in waters.