Protocol for the isolation, sequencing, and analysis of the gut phageome from human fecal samples

The phage-bacteria interactions in the gut microbiome are critical for health and disease, but viruses of the human gut microbiome are poorly understood. Here, we present a simple and cost-efficient protocol for collecting viral-like particles (VLPs) from human fecal samples. We describe VLPs quantification using epifluorescence and TEM microscopy, followed by DNA sequencing and bioinformatics analysis. This protocol characterizes the gut phageome in normal-weight and obese children with metabolic syndrome. It is also suitable to conduct high-throughput studies for other diseases.

For complete details on the use and execution of this profile, please refer to Bikel et al. (2021).

•

Protocol for collecting, sequencing, and bioinformatics of viral-like particles (VLPs)

•

Simple, reproducible, and cost-efficient protocol to characterize the VLPs of phages

•

Revealing the number of VLPs in human fecal samples by epifluorescence and TEM microscopy

•

Revealing bacteriophage abundance with functional and taxonomical analysis of VLPs

Gut dsDNA virome shows diversity and richness alterations associated with childhood obesity and metabolic syndrome

Changes in the human gut microbiome are associated with obesity and metabolic syndrome, but the role of the gut virome in both diseases remains largely unknown. We characterized the gut dsDNA virome of 28 school-aged children with healthy normal-weight (NW, n = 10), obesity (O, n = 10), and obesity with metabolic syndrome (OMS, n = 8), using metagenomic sequencing of virus-like particles (VLPs) from fecal samples. The virome classification confirmed the bacteriophages' dominance, mainly composed of Caudovirales. Notably, phage richness and diversity of individuals with O and OMS tended to increase, while the VLP abundance remained the same among all groups. Of the 4,611 phage contigs composing the phageome, 48 contigs were highly prevalent in ≥80% of individuals, suggesting high inter-individual phage diversity. The abundance of several contigs correlated with gut bacterial taxa; and with anthropometric and biochemical parameters altered in O and OMS. To our knowledge, this gut phageome represents one of the largest datasets and suggests disease-specific phage alterations.

A novel approach for human whole transcriptome analysis based on absolute gene expression of microarray data

Background

In spite of the emergence of RNA sequencing (RNA-seq), microarrays remain in widespread use for gene expression analysis in the clinic. There are over 767,000 RNA microarrays from human samples in public repositories, which are an invaluable resource for biomedical research and personalized medicine. The absolute gene expression analysis allows the transcriptome profiling of all expressed genes under a specific biological condition without the need of a reference sample. However, the background fluorescence represents a challenge to determine the absolute gene expression in microarrays. Given that the Y chromosome is absent in female subjects, we used it as a new approach for absolute gene expression analysis in which the fluorescence of the Y chromosome genes of female subjects was used as the background fluorescence for all the probes in the microarray. This fluorescence was used to establish an absolute gene expression threshold, allowing the differentiation between expressed and non-expressed genes in microarrays.

Methods

We extracted the RNA from 16 children leukocyte samples (nine males and seven females, ages 6-10 years). An Affymetrix Gene Chip Human Gene 1.0 ST Array was carried out for each sample and the fluorescence of 124 genes of the Y chromosome was used to calculate the absolute gene expression threshold. After that, several expressed and non-expressed genes according to our absolute gene expression threshold were compared against the expression obtained using real-time quantitative polymerase chain reaction (RT-qPCR).

Results

From the 124 genes of the Y chromosome, three genes (DDX3Y, TXLNG2P and EIF1AY) that displayed significant differences between sexes were used to calculate the absolute gene expression threshold. Using this threshold, we selected 13 expressed and non-expressed genes and confirmed their expression level by RT-qPCR. Then, we selected the top 5% most expressed genes and found that several KEGG pathways were significantly enriched. Interestingly, these pathways were related to the typical functions of leukocytes cells, such as antigen processing and presentation and natural killer cell mediated cytotoxicity. We also applied this method to obtain the absolute gene expression threshold in already published microarray data of liver cells, where the top 5% expressed genes showed an enrichment of typical KEGG pathways for liver cells. Our results suggest that the three selected genes of the Y chromosome can be used to calculate an absolute gene expression threshold, allowing a transcriptome profiling of microarray data without the need of an additional reference experiment.

Discussion

Our approach based on the establishment of a threshold for absolute gene expression analysis will allow a new way to analyze thousands of microarrays from public databases. This allows the study of different human diseases without the need of having additional samples for relative expression experiments.

Combining metagenomics, metatranscriptomics and viromics to explore novel microbial interactions: towards a systems-level understanding of human microbiome

The advances in experimental methods and the development of high performance bioinformatic tools have substantially improved our understanding of microbial communities associated with human niches. Many studies have documented that changes in microbial abundance and composition of the human microbiome is associated with human health and diseased state. The majority of research on human microbiome is typically focused in the analysis of one level of biological information, i.e., metagenomics or metatranscriptomics. In this review, we describe some of the different experimental and bioinformatic strategies applied to analyze the 16S rRNA gene profiling and shotgun sequencing data of the human microbiome. We also discuss how some of the recent insights in the combination of metagenomics, metatranscriptomics and viromics can provide more detailed description on the interactions between microorganisms and viruses in oral and gut microbiomes. Recent studies on viromics have begun to gain importance due to the potential involvement of viruses in microbial dysbiosis. In addition, metatranscriptomic combined with metagenomic analysis have shown that a substantial fraction of microbial transcripts can be differentially regulated relative to their microbial genomic abundances. Thus, understanding the molecular interactions in the microbiome using the combination of metagenomics, metatranscriptomics and viromics is one of the main challenges towards a system level understanding of human microbiome.