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Biology subjects

Korshoj, L. E.

Publications and source records attributed to Korshoj, L. E..

3 recordsLinked to original sources

Bacterial single-cell RNA sequencing captures biofilm transcriptional heterogeneity and differential responses to immune pressure

Biofilm formation is an important mechanism of survival and persistence for many bacterial pathogens. These multicellular communities contain subpopulations of cells that display vast metabolic and transcriptional diversity along with high recalcitrance to antibiotics and host immune defenses. Investigating the complex heterogeneity within biofilm has been hindered by the lack of a sensitive and high-throughput method to assess stochastic transcriptional activity and regulation between bacterial subpopulations, which requires single-cell resolution. We have developed an optimized bacterial single-cell RNA sequencing method, BaSSSh-seq, to study Staphylococcus aureus diversity during biofilm growth and transcriptional adaptations following immune cell exposure. We validated the ability of BaSSSh-seq to capture extensive transcriptional heterogeneity during biofilm compared to planktonic growth. Application of new computational tools revealed transcriptional regulatory networks across the heterogeneous biofilm subpopulations and identification of gene sets that were associated with a trajectory from planktonic to biofilm growth. BaSSSh-seq also detected alterations in biofilm metabolism, stress response, and virulence that were tailored to distinct immune cell populations. This work provides an innovative platform to explore biofilm dynamics at single-cell resolution, unlocking the potential for identifying biofilm adaptations to environmental signals and immune pressure.

microbiology↗

Diagnostic optical sequencing

Advances in precision medicine require high-throughput, inexpensive, point-of-care diagnostic methods with multi-omics capability for detecting a wide range of biomolecules and their molecular variants. Optical techniques have offered many promising advances towards such diagnostics. However, the inability to squeeze light with several hundred-nanometer wavelengths into angstrom-scale volume for single nucleotide measurements has hindered further progress. Recently, a block optical sequencing (BOS) method has been shown for determining relative nucleobase content in DNA k-mer blocks with Raman spectroscopy, and a block optical content scoring (BOCS) algorithm was developed for robust content-based genetic biomarker database searching. Here, we performed BOS measurements on positively-charged silver nanoparticles to achieve 93.3% accuracy for predicting nucleobase content in DNA k-mer blocks (where k=10), as well as measurements on RNA and chemically-modified nucleobases for extensions to transcriptomic and epigenetic studies. Our high-accuracy BOS measurements were then used with BOCS to correctly identify a {beta}-lactamase gene from the MEGARes antibiotic resistance database and confirm the Pseudomonas aeruginosa pathogen of origin from <12 content measurements (<15% coverage) of the gene. These results prove the integration of BOS/BOCS as a diagnostic optical sequencing platform. With the versatile range of available plasmonic substrates offering simple data acquisition, varying resolution (single-molecule to ensemble), and multiplexing, this optical sequencing platform has potential as the rapid, cost-effective method needed for broad-spectrum biomarker detection.

bioengineering↗

BOCS: DNA k-mer content and scoring for rapid genetic biomarker identification at low coverage

A single, inexpensive diagnostic test capable of rapidly identifying a wide range of genetic biomarkers would prove invaluable in precision medicine. Previous work has demonstrated the potential for high-throughput, label-free detection of A-G-C-T content in DNA k-mers, providing an alternative to single-letter sequencing while also having inherent lossy data compression and massively parallel data acquisition. Here, we apply a new bioinformatics algorithm - block optical content scoring (BOCS) - capable of using the high-throughput content k-mers for rapid, broad-spectrum identification of genetic biomarkers. BOCS uses content-based sequence alignment for probabilistic mapping of k-mer contents to gene sequences within a biomarker database, resulting in a probability ranking of genes on a content score. Simulations of the BOCS algorithm reveal high accuracy for identification of single antibiotic resistance genes, even in the presence of significant sequencing errors (100% accuracy for no sequencing errors, and > 90% accuracy for sequencing errors at 20%), and at well below full coverage of the genes. Simulations for detecting multiple resistance genes within a methicillin-resistant Staphylococcus aureus (MRSA) strain showed 100% accuracy at an average gene coverage of merely 0.515, when the k-mer lengths were variable and with 4% sequencing error within the k-mer blocks. Extension of BOCS to cancer and other genetic diseases met or exceeded the results for resistance genes. Combined with a high-throughput content-based sequencing technique, the BOCS algorithm potentiates a test capable of rapid diagnosis and profiling of genetic biomarkers ranging from antibiotic resistance to cancer and other genetic diseases.

bioinformatics↗