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Single Nucleotide Polymorphisms-SNPs

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A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...

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Updated: Apr 14, 2026

Detection of Trypanosoma brucei Variant Surface Glycoprotein Switching by Magnetic Activated Cell Sorting and Flow Cytometry

Detection of Trypanosoma brucei Variant Surface Glycoprotein Switching by Magnetic Activated Cell Sorting and Flow Cytometry

Published on: October 19, 2016

Identifying SARS-CoV-2 Variants Using Single-Molecule Conductance Measurements.

Zahra Aminiranjbar¹, Caglanaz Akin Gultakti^2,3, Mashari Nasser Alangari^1,4

¹Department of Electrical and Computer Engineering, University of California Davis, Davis, California 95616, United States.

|May 22, 2024

Summary

This summary is machine-generated.

Single-molecule RNA conductance experiments can rapidly identify specific SARS-CoV-2 variants. This method uses machine learning to detect genetic changes, aiding in tracking new strains like Alpha, Beta, Delta, and Omicron.

Keywords:

SARS-CoV-2 variant detection XGBoost machine learning biosensors molecular electronics single-molecule break junction

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Published on: September 8, 2023

Area of Science:

Biophysics
Molecular Biology
Genomics

Background:

The COVID-19 pandemic necessitates rapid detection of biological agents and monitoring of viral genetic evolution.
Emergence of new SARS-CoV-2 variants requires advanced tools for identification and tracking.

Purpose of the Study:

To demonstrate RNA-based single-molecule conductance experiments for specific SARS-CoV-2 variant identification.
To develop a rapid, high-specificity, and high-sensitivity method for detecting short RNA sequences and genetic mutations.

Main Methods:

Selection of target RNA sequences specific to SARS-CoV-2 variants.
Single-molecule break junction measurements to generate conductance histograms.
XGBoost machine learning classifier for rapid identification of target molecules in solution.

Main Results:

Successful identification of SARS-CoV-2 variants B.1.1.7 (Alpha), B.1.351 (Beta), B.1.617.2 (Delta), and B.1.1.529 (Omicron).
Demonstrated high specificity and sensitivity for detecting RNA targets as short as 20 base pairs using complementary DNA probes.
Showcased sensitivity to nucleotide mismatches, enabling broader identification capabilities.

Conclusions:

RNA-based single-molecule conductance experiments provide a viable method for detecting specific SARS-CoV-2 variants.
The methodology can rapidly identify known variants and detect emerging new variants based on their unique genetic sequences.
This approach offers a powerful tool for real-time surveillance of viral evolution and public health monitoring.