M20 Genomics

Decoding Heterogeneity in Mixed Bacterial Samples with VITA MscRNA-seq

2024-11  /  View: 27

Bacterial infections are on the rise, presenting increasingly complex challenges to human health. The mechanisms of infection often involve complex interactions between various species. The synergistic interactions within and between bacterial populations can enhance pathogenicity, antibiotic resistance, and evasion of host immune responses. Understanding how different bacterial species interact within these mixed populations is crucial for developing preventive stategies and treatments for infections and to combat cirtical phenomena such as antibiotic resitance.

In 2022, M20 Genomics introduced VITApilote MscRNA-seq, a revolutionary technology in high-throughput single-species single-bacterium transcriptome analysis. By leveraging random primers for RNA capture, this innovative platform not only enables precise single-cell transcriptome profiling across a wide spectrum of bacterial species—such as Escherichia coli, Acinetobacter baumannii, Streptococcus pneumoniae, Pseudomonas aeruginosa, Bacillus subtilis, Staphylococcus aureus, Lactobacillus, and Clostridium difficile—but also extends its application to mixed bacterial samples.

Unlike traditional methods such as bulk RNA-seq, which provide averaged data across samples, VITApilote MscRNA-seq offers single-cell resolution. This capability reveals the functional and phenotypic heterogeneity within mixed bacterial populations. By uncovering the intricate functional states and interations, researchers can unravel mechanisms of pathogenicity, identify cooperative or competitive behaviors, and understand how antibiotic resistance develops across different cells.

Figure 1: VITA MscRNA-seq product

Single-Bacterium Transcriptome Analysis of a Mixed Bacterial Sample

One of our customers successfully leveraged VITA MscRNA-seq for advanced single-cell transcriptome profiling in a mixed sample of Klebsiella pneumoniae and Escherichia coli, highlighting the technologies’ ability to obtain precise data from mixed bacterial samples. The sequencing process generated 35.9 GB of raw data, detecting an estimated 3,150 valid bacterial cells (Table 1). A total of 5,464 genes were identified, with a median gene count of 215 and a median UMI count of 611 per cell (Table 1 and Figure 2).

Raw Reads [M]107.7
Q30 Bases in RNA read [%]89.6
Sequencing Saturation [%]66.0
Estimated Number of Cells3,150
Mean UMI per Cell823
Median UMI per Cell611
Mean Genes per Cell230
Median Genes per Cells215
Total Genes5,464

Table 1: Data metrics derived from a mixed culture of Klebsiella pneumoniae and Escherichia coli

Figure 2: Distribution of detected genes in a mixed culture of Klebsiella pneumoniae and Escherichia coli

Unsupervised clustering based on transcriptomic profiles was conducted on the obtained dataset. The results unveiled two distinct clusters within the sample, that were annotated as Klebsiella pneumoniae and Escherichia coli, respectively (Figure 3).

Figure 3: UMAP clustering identifying different bacterial species within the mixed culture of Klebsiella pneumoniae and Escherichia coli

The data analysis was further expanded to the subspecies level. Unsupervised clustering identified six distinct subpopulations within the K. pneumoniae population (Figure 4) revealing the heterogeneity within one species. 

Figure 4: Unsupervised clustering within the Klebsiella pneumonia population reveals six subpopulations

Furthermore, VITA MscRNA-seq facilitates precise analysis of differential gene expression, unveiling significant heterogeneity across the distinct subpopulations within the Klebsiella pneumoniae population (Figure 5).

Figure 5: Differential gene expression within the population of Klebsiella pneumonia.

VITA MscRNA-Seq: Single-Cell Resolution for Mixed Bacterial Samples

Analyzing mixed bacterial cultures is essential for unraveling the intricate interactions and functions within mixed populations. Understanding these dynamics is crucial for addressing challenges such as infections, antibiotic resistance, and adaptive responses. VITA MscRNA overcomes the limitations of traditional methods in capturing the heterogeneity within bacterial populations.

VITA MscRNA-seq transforms microbiology by facilitating single-cell transcriptomic profiling within mixed populations. This groundbreaking technology allows researchers to uncover the diverse transcriptional states of thousands of individual bacterial cells in one sample. VITA MscRNA-seq offers unprecedented precision in analysing the mechanisms behind microbial functions.

Join us in advancing the frontiers of microbial research with VITA MscRNA-seq. Explore the microbial universe with unmatched detail and drive transformative discoveries!

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