The Innovator Blog Series celebrates research conducted by 10x Genomics customers who have demonstrated scientific ingenuity by adapting Chromium Single Cell or Visium Spatial sequencing-based assays. These innovations are distinguished by their originality and potential impact on scientific discovery, including providing access to novel analytes, advancing multiomic analysis techniques, and demonstrating critical applications to human health and disease research. These techniques are customer developed, meaning they are not officially supported by 10x Genomics.

Why single cell for bacteria

Whatever your perception of bacteria may be, these tiny, squirming, ciliated buggers are, nonetheless, cells. They have a transcriptome, too, which can be measured (now, at the single cell level) to understand cellular identity and cell-to-cell heterogeneity.

Antimicrobial resistance (AMR) is currently growing at an unprecedented scale, raising a major concern to the global health public. According to a 2019 global analysis of antimicrobial resistance, 1.27 million people died as a direct result of drug-resistant infections, far surpassing the mortality rates of HIV/AIDS and malaria, which accounted for 864,000 and 643,000 lives, respectively (1,2). In Vietnam, the level of antimicrobial resistance has been recorded at an alarming rate, among the highest in Asia, due to irrational antibiotic use without prescription and insufficient antibiotic stewardship.

Traditionally, antimicrobial susceptibility testing (AST) is performed in vivo to assess the efficacy of a wide range of antibiotics against certain bacteria. However, the long turnaround time for results often resort patients to empiric treatment (broad-spectrum antibiotics) to prevent disease progression. This practice can exacerbate antibiotic resistance, especially to the extent that bacteria become resistant to empirical treatments, leaving no other options to cure patients. As a result, the underlying mechanisms of drug resistance have drawn significant attention from the scientific community for decades.

A fact sheet that describes how antibiotic resistance spreads. CREDIT: Centers for Disease Control and Prevention (2022). https://www.cdc.gov/drugresistance/about/how-resistance-happens.html

But what exactly is the mechanism behind this formidable resistance in bacteria? One of the key players is a type of mobile genetic element known as insertion sequences (IS elements) which have long been known to contribute to both microevolutionary and macroevolutionary processes in bacteria.

Insertion sequences (IS elements) are short DNA sequences that function as simple transposable elements, capable of randomly migrating from one position to another within the bacterial genome. Microevolution may initiate with small-scale alterations introduced by these elements, such as random insertions, deletions, and gene repetitions, which can accumulate over time. When these changes reach their culmination point, they result in macroevolution, leading to the emergence of completely new species or, in this context, irreversible antibiotic-resistant bacteria. 

Bulk RNA sequencing is the most prevalent method to sequence the bacterial transcriptome; however, it can easily overlook subtle cell-to-cell heterogeneity that may contribute to bacterial persister formation. Ignoring rare resistant cell subtypes can lead to poor management of microevolution, paving the way for multi-drug resistant bacteria to sneak into bacterial populations and aggressively complicate antibiotic resistance.

This challenge has motivated scientists from different research groups to develop a method built on the Chromium Single Cell platform, enabling highly scalable single-cell analysis of bacterial cells. Two recent methods, BacDrop and M3-seq, are modified from Chromium Single Cell ATAC for applications in AMR studies. By identifying open and accessible chromatin regions for transcription factors and other regulatory proteins, researchers can pinpoint how IS elements and other MGEs (Mobile Genetic Elements) interact with the bacterial genome to fuel resistance.

Keep reading to explore their innovative methods, which overcome numerous challenges to accessing mRNA in bacterial cells, and offer new insights into the role of mobile genetic elements in driving antibiotic resistance.

In-cell reactions solve the mRNA access problem

While eukaryotic cells have been tested and validated extensively on single cell sequencing platforms, prokaryotic cells (in this case, bacteria) don’t follow the eukaryotic norms. For example, one crucial difference between mammalian and bacterial cells is in the composition and accessibility of their messenger RNA (mRNA) molecules, or transcripts. These molecules carry the coding sequences for protein synthesis (4) and are quantified in gene expression profiling experiments.

Bacterial cells are also heavily dominated by ribosomal RNA (rRNA) and genomic DNA (gDNA). Accessing bacterial mRNA is also difficult because their cell walls require harsher lysis conditions than most eukaryotic cells, which risks damaging RNA integrity (3).

Two parallel studies from Broad Institute and Lewis-Sigler Institute were conceived to effectively handle two challenges. Briefly, during the sample preparation, they simultaneously removed rRNA, whether in situ or in post-library amplification step, and “tail” cDNA molecules using terminal transferase, which involves the addition of deoxynucleotides to the 3′ end of bacterial transcripts since they lack poly-A tails. 

Now, all cDNA molecules would have a poly-A tail, making it possible to perform second-strand cDNA synthesis using oligo-dT primers (a cDNA enrichment step that happens inside droplets on the Chromium platform), and subsequently to attach a round 2 droplet barcode to double-stranded cDNA. Using this approach, each unique cell would be identified by the combination of the round 1 plate barcode and round 2 droplet barcode, allowing researchers to load each droplet with multiple cells and, therefore, increase the throughput of the assay (3).

If you thought all of that was cool, here, the true wildcard of their experiment: the team prepared cells for droplet generation on the Chromium platform, but specifically using the Single Cell ATAC Library and Gel Bead Kit. This kit is technically designed to barcode DNA fragments from single nuclei. However, in this case, the researchers hacked it to capture cDNA fragments from single bacteria cells (pause, as your mind is blown). Using this high-throughput, microfluidics platform—including hundreds of thousands of unique droplet barcodes provided in the single cell ATAC kit—allowed the team to reduce plate-based combinatorial index steps and increase the efficiency and scale of their single cell analysis workflow.

After running bacterial cells through the assay, the team purified and enriched cDNA content, then constructed sequencing-ready libraries, completing an innovative and unexpected experiment to capture and quantify the bacterial transcriptome at single cell resolution.

BacDrop overcomes bulk RNA-seq to reveal a key factor of bacterial cell heterogeneity

Putting BacDrop to the test was next on the researchers’ agenda—in particular, assessing its ability to distinguish bacterial heterogeneity at the transcriptional level between different species, within the same population, and under different antibiotic treatment conditions (3).

The team first validated BacDrop by successfully distinguishing four different bacterial species—K. pneumoniae, P. aeruginosa, gram-negative E. coli, and gram-positive E. faecium—in single cell RNA-seq data. They also tested the molecular sensitivity and coverage of their method by generating a one-million-cell library of K. pneumoniae, sequenced at 5,000 reads per cell. They recovered 60,000 cells with at least 15 mRNA genes per cell and, combining analysis of all cells, detected expression for 96% of the genes in the entire genome, which validated BacDrop’s sensitivity (3).

Their next experiments honed in on the identification of heterogeneous subpopulations within a cultured clinical isolate of K. pneumoniae MGH66 under antibiotic-treated and untreated conditions. One MGH66 culture was split into four cultures: one was left untreated, while the remaining three were treated with antibiotics (meropenem, ciprofloxacin, and gentamicin) of varying mechanisms of action. Each of the four samples were first barcoded with round 1 plate barcodes separately, then pooled together for single cell analysis. Cell clustering was dictated by the unique gene expression changes induced by each of the antibiotic treatment conditions, confirming BacDrop’s ability to disentangle both heterogeneous populations within the same bacterial species and transcriptional programs induced by treatment.

Bulk RNA-seq was performed in parallel on biological replicates sharing the same treatment scheme and, generally, bulk data showed alignment to the gene expression changes seen in single cell analysis of the ciprofloxacin- and gentamicin-treated samples. However, this alignment diverged in the meropenem sample: bulk RNA-seq showed minimal transcriptional changes as a result of treatment; however, single cell analysis revealed four subpopulations with distinct molecular responses characterised by upregulation of genes involved in the stress response, cell wall synthesis, DNA replication, and cold shock response (3).

Bulk RNA-seq also could not reveal a small but important population within the untreated K. pneumoniae sample. The team identified two major subpopulations by single cell analysis: a large homogeneous subpopulation and a much smaller subpopulation (comprising about 4.5% of cells) showing increased expression of the IS903B transposase gene, a mobile genetic element (MGE) that can move around and duplicate itself (and has 83 times) within the MGH66 genome (3). This small MGE population could explain the K. pneumoniae strain’s tendency to acquire antibiotic resistance (3).

To test this hypothesis, the research team used BacDrop to study a carbapenem-resistant K. pneumoniae clinical isolate (BIDMC35). This class of bacteria are a serious threat to public health, because, in some cases, they are resistant to all available antibiotics (5). Single cell analysis of 9,748 bacteria cells again revealed MGE-driven subpopulations: in this case, three unique cell clusters defined by expression of three different transposon genes, IS4321 family transposase (195 cells, 2%), insH transposase (146 cells, 1.5%), and IS110 family transposase (133 cells, 1.4%). With this high-resolution view of rare subpopulations, the team confirmed the role of MGEs in driving heterogeneity and likely in antibiotic resistance as well (3).

M3-seq reveals transcriptional variations in bacteria exposed to bacteriostatic antibiotics.

M3-seq is short for massively parallel, multiplexed, microbial sequencing, allowing transcriptome-scale single-cell RNA sequencing (scRNA-seq) at massive cell numbers and across multiple conditions. In this study, E. coli were exposed to eight different types of antibiotics, including both narrow-spectrum and broad-spectrum classifications. Among these antibiotics, tetracycline and chloramphenicol are widely known as broad-spectrum, bacteriostatic antibiotics, which combat a wide range of bacteria by preventing bacterial cell growth. Therefore, the effectiveness of these antibiotics plays a vital role in treating a wide array of infections in global healthcare. However, their mode of action merely halts bacterial growth rather than directly killing the bacteria. This poses a challenge to studying bacteriostatic effects at the single-cell level because they do not produce readily measurable persistence and tolerance phenotypes. The rapidly evolving resistant bacterial strains reduce their efficacy, limiting treatment options and posing a significant threat to public health worldwide.

This modified protocol of Chromium ATAC helps researchers delve deeper into various transcriptional states of tetracycline- and chloramphenicol-treated E. coli, revealing 14 and 8 clusters, respectively. The results exhibited several rare clusters—never before determined—with cells from both samples expressing genes encoding mobile genetic elements (MGEs). These rare populations may help cultures persist and thrive even  in bacteriostatic environments through mechanisms such as activating genes implicated in cold shock, like ydfK. Understanding these mechanisms can be a key to adopting more effective antibiotic treatments and managing resistance (6).

Transforming microbiology with cellular resolution

What could microbiologists and infectious disease researchers do with full access to the bacterial transcriptome at single cell resolution? BacDrop offers a tool to answer that and opens a door to a new world of research. Scientists are empowered to delve deeper into the biological heterogeneity of pathogenic bacterial species, environment species, and even the microbiome—and to understand how antibiotic treatments work, or why they don’t. Given this huge potential, BacDrop is fully qualified to stand among the other customer-developed methods featured in the Innovator Series.

Want to read more Innovator Series posts? Learn about a method to measure viral RNA in single cells and in spatially resolved tissue sections here.

Looking for other infectious disease resources? Check out our page!

Summary

Antimicrobial resistance (AMR) is a major global health issue that requires transformative discoveries to elucidate underlying mechanisms and improve treatment options. In bacteria, the acquisition of AMR genes carried on mobile genetic elements (MGEs) can lead to microevolution and, ultimately, macroevolution, resulting in multidrug-resistant bacteria. Traditional approaches such as bulk RNA sequencing and ChIP sequencing have limitations in scalability and their capacity to capture cell-to-cell heterogeneity.

This is where single-cell technology, including Chromium ATAC, comes into play. However, bacteria pose unique challenges compared to eukaryotes, including the absence of polyadenylated tails, the heavy dominance of ribosomal RNA (rRNA) and genomic DNA (gDNA), and a rigid cell wall. To address these challenges, two independent research teams have developed modified Chromium ATAC protocols, namely BacDrop and M3-seq, to advance single-cell applications in revealing various bacterial resistance phenotypes.

References:

1. Murray C, et al. Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. The Lancet 399: P629–655 (2022). doi: 10.1016/S0140-6736(21)02724-0

2. Thompson T. The staggering death toll of drug-resistant bacteria. Nature (2022). doi: 10.1038/d41586-022-00228-x

3. Ma P, et al. Bacterial droplet-based single-cell RNA-seq reveals antibiotic-associated heterogeneous cellular states. Cell 186: 1–15 (2023). doi: 10.1016/j.cell.2023.01.002

4. Ribosomes, Transcription, and Translation. Scitable by Nature Education (2014).

5. https://www.cdc.gov/hai/organisms/cre

6. Wang, B., Lin, A.E., Yuan, J. et al. Single-cell massively-parallel multiplexed microbial sequencing (M3-seq) identifies rare bacterial populations and profiles phage infection. Nat Microbiol 8, 1846–1862 (2023). doi: 10.1038/s41564-023-01462-3

7. Olivia Habern. Bacterial single cell RNA-seq reveals antibiotic resistance mechanisms. 10x Genomics Blog (2023). https://www.10xgenomics.com/blog/bacterial-single-cell-rna-seq-reveals-antibiotic-resistance-mechanisms

Source: Bacterial single cell RNA-seq reveals antibiotic resistance mechanisms