Insights Unveiled: A Case Study with VITA GutMicrobiome
Over the last two decades, the gut microbiome has emerged as a prominent research field, revealing its pivotal role in human physiology and its significant association with various diseases [1-3]. However, our understanding of the intricate functional mechanisms within the gut microbiome remains incomplete and current applied methodologies often rely on bulked analyses, offering only insights based on averaged data and lack sensitivity to detect nuanced dynamics and diverse functions present within complex microbial communities.
In November 2023, we launched VITA GutMicrobiome, our pioneering single-bacterial transcriptome product designed for the gut microbiome. Our cutting-edge solution enables accurate barcoding of each individual bacterium in gut microbiome samples, improving the efficiency and accuracy of of bacterial transcriptome analysis by clearly identifying the cellular origin of each sequenced fragment and eliminating the need for culture processes. Moreover, the high-resolution data for single bacterial transcriptomes offer an advantage in resolving functional heterogeneity even within homogeneous populations, serving as a powerful analytical tool at the single-cell level.
Here, we showcase the exceptional performance of our VITA GutMicrobiome product through single-bacteria transcriptome analysis on a fecal sample from a healthy human individual.
Practical Application and Performance Assessment of VITA GutMicrobiome
The workflow commenced with the preparation of a single-cell suspension from the sample, followed by the fixation and permeabilization of bacterial cells. Subsequently, in situ reverse transcription was conducted using the VITA GutMicrobiome Kit. Following this step, cell partitioning and barcoding were carried out using the VITAcruize Single-Cell Partitioning Instrument. Next, cDNA amplification and library construction were conducted with the same kit. Finally, the libraries were sequenced on an Illumina Novaseq6000 platform (Figure 1)
Figure 1: VITA GutMicrobiome workflow
Library Quality and Metrics
The sequencing resulted in 54.8 G of high-quality raw data, capturing an estimated 7,020 cells. With a Q30 score of 89.3%, indicating a high level of accuracy, a sequencing saturation rate of 67.7% was achieved, reflecting robust data acquisition. Additionally, the median gene count stood at 105 per cell, while the median UMI count reached 307 per cell (Table 1). These results underscore the effectiveness of VITA GutMicrobiome in delivering high-quality data output.
Table 1: Library metrics of data obtained from the analysis of a human fecal sample conducted using the VITA GutMicrobiome platform and a Illumina Novaseq6000 platform.
Microbial Diversity and Functional Pathways
The bioinformatic analysis was performed using the advanced VITAseer software. Sequences were filtered for uniquely identifiable cellular barcodes, enabling precise species annotation of each cell thereafter. Remarkably, we identified over 60 species in the sequencing data derived from a human fecal sample. Through quantifying the cell barcodes associated with each bacterial species, we gained detailed insights into the abundance of species within the sample (Figure 2).
Figure 2: Species abundance in a human fecal sample (species with an abundance of <1% are displayed in white)
Species with an abundance exceeding 1% were subjected to Uniform Manifold Approximation and Projection (UMAP) dimensionality reduction analysis. Through visualization of their 2D data based on by their transcriptomic profiles, distinct identifiable clusters corresponding to each species emerged (Figure 3).
Figure 3: UMAP clustering diagram of the most abundant species (abundance >1%) in a human fecal sample.
To explore the datasets in greater depth, we conducted Gene Set Enrichment Analysis (GSEA) of differentially expressed genes for the most abundant species. The enriched pathways associated with each bacterial species are visually presented in a heatmap diagram (Figure 4). Our analysis unveiled the enrichment of distinct gene sets associated with diverse functional pathways across different bacterial species, providing insights into their functional roles and interconnections within the gut microbial community.
Figure 4: Heatmap generated from the GSEA performed on the most abundant species in a human fecal sample (horizontal axis represents the bacterial species, vertical axis illustrates the enriched pathways).
Identification of Intraspecific Supopulations
We expanded our data analysis by conducting an in-depth exploration of the functional diversity within the two predominant species, Neobittarella massiliensis and Phocaeicola coprocola. This process entailed identifying several intraspecific subpopulations through UMAP clustering in both species (Figure 5).
Figure 5: UMAP clustering diagram of predominant bacterial species in a human fecal sample.
Following this, we applied Gene Set Enrichment Analysis (GSEA) to identify functional gene groups exhibiting significant alterations in expression. Notably, we observed a distinct enrichment in the expression of numerous functional pathways across the subpopulations within both species (Figure 6).
Figure 6: Heatmap of GSEA conducted for each subpopulation of Neobittarella massiliensis (left) and Phocaeicola coprocola (right) populations in a human fecal sample.
We identified significant enrichment in pathways related to galactose metabolism, aminosugar and nucleotide sugar metabolism, various amino acid metabolisms, and sphingolipid biosynthesis in subpopulation 0 of Neobittarella massiliensis. In contrast, subpopulation 1 of Neobittarella massiliensis exhibited an increased expression of pathways associated with ABC transporter proteins, porphyrin metabolism, protein processing, and CAMP resistance-related mechanisms.
Furthermore, we observed significant enrichment of specific functional pathways in various subpopulations of Phocaeicola coprocola. Subpopulation 5 exhibited a notable enrichment of genes involved in the biosynthesis of secondary metabolites, cyanoamino acid metabolism, degradation of flavonoids, and starch and sucrose metabolism. In contrast, subpopulation 3 showed enrichment for genes involved in Salmonella infection, shigellosis, flagellar assembly, and nod-like receptor signaling. These observations suggest the presence of functional heterogeneity and a specialization or adaptation of subpopulations to specific gut environments. Our results underscore the capability of VITA GutMicrobiome to explore and characterize the functional heterogeneity of intraspecific subpopulations.
Revolutionizing Gut Microbiome Research with VITA GutMicrobiome: Unveiling Microbial Complexity at Single-Cell Resolution
Through our evaluation of VITA GutMicrobiome using a human fecal sample, we showcase its exceptional performance and unveil the diverse array of research opportunities it presents. Our case study illustrates how VITA GutMicrobiome provides accurate insights into microbial composition and abundance in fecal samples. Additionally, it demonstrates the product's capability to pinpoint enriched functional pathways across different species and homogeneous subpopulations. These features hold the potential to unravel the intricate functional network within complex microbial communities with single-cell resolution.
As the sole high-throughput single-bacteria transcriptome solution designed for microbiome samples, VITA GutMicrobiome presents unparalleled opportunities for groundbreaking advancements of gut microbiome research. The user-friendly nature of VITA GutMicrobiome provides researchers with an accessible solution, enabling them to delve into the intricate nuances of the gut microbiome with precision and efficiency.
References:
[1] Fan Y, et al. Gut microbiota in human metabolic health and disease. Nat Rev Microbiol. 2021;19:55–71.
[2] Sorboni SG, et al. A Comprehensive Review on the Role of the Gut Microbiome in Human Neurological Disorders. Clin Microbiol Rev. 2022;35(1):e0033820.
[3] de Vos WM, et al. Gut microbiome and health: mechanistic insights. Gut. 2022;71(5):1020-1032.
