Introduction
Escherichia coli (E. coli) is a paradoxical bacterial species—essential for human digestion yet a major contributor to the global antibiotic resistance crisis. While most strains of E. coli reside harmlessly in the intestines, some pathogenic variants can cause severe illnesses, including urinary tract infections, sepsis, and diarrhea. This dual nature underscores its significance in microbiology and medicine.
The urgency of studying E. coli only intensifies as multidrug-resistant (MDR) strains emerge, complicating treatment and endangering lives worldwide. In this article, we explore E. coli's biology, its role in antibiotic resistance, and how advanced single-cell technologies are reshaping our understanding of this microbial frontier.
Biological Overview
E. coli is a Gram-negative, rod-shaped bacterium that thrives in warm-blooded animals' intestines under optimal conditions of 37°C and pH 6.0–8.0. As a facultative anaerobe, it can survive in both oxygen-rich and oxygen-deprived environments. It is important to note that not all E. coli strains are harmful. Commensal strains play a vital role in gut health by aiding digestion and synthesizing essential vitamins. However, pathogenic strains like Shiga toxin-producing E. coli (STEC) can cause severe diseases such as hemolytic uremic syndrome (HUS). The genetic diversity of E. coli allows it to adapt to various environments and evolve mechanisms for survival and virulence.
Global Impact
Pathogenic E. coli spreads through contaminated food, water, or direct contact with infected individuals or animals. Poor sanitation exacerbates its transmission. Infections caused by E. coli are prevalent worldwide, with seasonal spikes linked to foodborne outbreaks during warmer months. These infections impose significant public health and economic burdens not helped by the rise in antibiotic resistance in bacteria.
Antibiotic-resistant E. coli, particularly MDR strains, are increasingly reported in clinical and environmental settings globally. Resistance rates to commonly used antibiotics like ampicillin and ciprofloxacin exceed 60% in many regions.
E. coli’s antibiotic resistance mechanisms include:
These mechanisms are classified into intrinsic resistance (genetically determined) and acquired resistance (resulting from gene mutations or horizontal transfer of resistance factors). Acquired resistance is considered the primary driver of antibiotic resistance in E. coli.
However, traditional research methods have significant limitations in studying E. coli antibiotic resistance. For example, they lack effective approaches for investigating heteroresistance. This is because conventional bulk sequencing masks the gene expression heterogeneity of minor subpopulations associated with resistance, leading to the loss of critical information and posing challenges for heteroresistance research. Using single cell sequencing tools, researchers can investigate how these mechanisms enable E. coli to withstand antibiotics across multiple classes and pose a significant challenge to public health. Single-bacterium transcriptome tools, such as M20 Genomics’ MscRNA-seq technology (commercially available as the VITA single-cell transcriptome platform), overcomes these limitations and can analyse individual cells with high resolution. The VITA platform leverages random primers and is thereby able to obtain a more complete RNA transcriptome.
Case Study – E. coli Single Cell Analysis
Number of Reads (M) | 189.3 |
Sequencing Saturation% | 60.3 |
Q30 Bases in RNA read% | 92.7 |
Total Genes Detected | 4,443 |
Number of Valid Cells | 4,360 |
Median UMI per Valid Cells | 683 |
Median Genes per Valid Cell | 188 |
Table 1. Summary of sequencing and analysis metrics
Figure 1: 8 subpopulations were distinguished based on gene expression profiling in the E. coli Sample
Utilizing the VITA platform on a pure culture sample, researchers achieved 189.3 million reads and detected 4,443 cells with a median gene of 188 per cell (Table 1), which allows researchers to investigate the mechanisms that are only visible with gene detention on the single cell level. Based on their gene expression profile, 8 distinct subpopulations were distinguished in this E. coli sample (Figure 1). These subpopulations can be explored for the upregulation of specific genes to determine the phenotypic heterogeneity and discover functional differences.
Figure 2: UMAP visualization of E. coli clustering under antibiotic treatment time points. The left panel shows cells colored by treatment duration (0h, AMP 1h, AMP 2h, and AMP 4h), while the right panel displays clusters labeled 0–10.
In another example, researchers studied antibiotic resistance in E. coli by treating a sample with ampicillin and collecting samples at 0, 1, 2, and 4 hours (Figure 2). This allowed the team to investigate the effects of the antibiotic treatment on the bacterial population. Transcriptome sequencing via the VITA platform was able to further characterize the heterogeneous response of the E. coli population into subpopulations within each sample cluster.
Differential gene analysis is able to identify the heterogeneity within the E. coli samples of each treatment group and color them into 11 subclusters. These clustered breakdowns of the E. coli under antibiotic treatment reveal a great deal of gene expression heterogeneity between and within each treatment duration sample, and potentially offer insight into the survival mechanisms that the bacteria employ to resist treatment. Experiments like this, using the innovative technology of the VITA platform, provide a window into the developmental processes behind antimicrobial resistance (AMR). With this key advantage, researchers can identify mechanisms of resistant subpopulations, map gene regulatory networks driving resistance, and eventually develop targeted antimicrobial therapies. This level of insight is crucial for understanding bacterial adaptation under antibiotic pressure.
Conclusion
The dualistic nature of E. coli—as both a beneficial gut bacterium and a public health threat—underscores the complexity of microbial ecosystems. The rise of MDR strains highlights the urgent need for innovative research approaches.
Single-cell technologies like VITA single-cell technology are transforming microbiology by providing unprecedented insights into bacterial behavior at the cellular level. By leveraging these tools, researchers can develop targeted strategies to mitigate antibiotic resistance and safeguard global health.
For more on how M20 Genomics is advancing microbiological research with cutting-edge technology, visit our website and products page.
References:
1. Asmare Z, Erkihun M, Abebe W, Tamrat E. Antimicrobial resistance and ESBL production in uropathogenic Escherichia coli: a systematic review and meta-analysis in Ethiopia. JAC-Antimicrobial Resistance. 2024.
2. Islam, Md. Saiful, Hossain, Md. Jannat, Sobur, Md. Abdus, Punom, Sadia Afrin, Rahman, A. M. M. Taufiquer, Rahman, Md. Tanvir, A Systematic Review on the Occurrence of Antimicrobial-Resistant Escherichia coli in Poultry and Poultry Environments in Bangladesh between 2010 and 2021, BioMed Research International. 2023.
3. Kaper, J., Nataro, J. & Mobley, H. Pathogenic Escherichia coli. Nat Rev Microbiol 2. 2004.
4. Kasanga M, Shempela DM, Daka V, Mwikisa MJ, Sikalima J, Chanda D, Mudenda S. Antimicrobial resistance profiles of Escherichia coli isolated from clinical and environmental samples: findings and implications. JAC Antimicrob Resist. 2024.
5. Liu C, Sun S, Sun Y, et al. Antibiotic resistance of Escherichia coli isolated from food and clinical environment in China from 2001 to 2020. Sci Total Environ. 2024, 939:173498.
6. Matussek A, Mernelius S, Chromek M, Zhang J, Frykman A, Hansson S, Georgieva V, Xiong Y, Bai X. Genome-wide association study of hemolytic uremic syndrome causing Shiga toxin-producing Escherichia coli from Sweden, 1994-2018. Eur J Clin Microbiol Infect Dis. 2023.
7. Mueller M, Tainter CR. Escherichia coli Infection. National Library of Medicine. 2023.
8. Nasrollahian S, Graham JP, Halaji M. A review of the mechanisms that confer antibiotic resistance in pathotypes of E. coli. Front Cell Infect Microbiol. 2024.
9. Poirel L, Madec JY, Lupo A, Schink AK, Kieffer N, Nordmann P, Schwarz S. Antimicrobial Resistance in Escherichia coli. Microbiol Spectr. 2018.
10. Sina Nasrollahian, Jay P. Graham, Mehrdad Halaji. A review of the mechanisms that confer antibiotic resistance in pathotypes of E. coli. Front. Cell. Infect. Microbiol. 2024, 2024.1387497.
11. Xu, Z., Wang, Y., Sheng, K. et al. Droplet-based high-throughput single microbe RNA sequencing by smRandom-seq. Nat Commun 14, 5130 (2023).