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Related Concept Videos

Ion Channels01:19

Ion Channels

The movement of ions like sodium, potassium, and calcium into and out of the cell is essential to maintain the electrochemical gradient in living cells. The ion channels—a class of membrane transport proteins—help maintain this ionic gradient for the smooth functioning of physiological activities such as maintaining cell size and volume, conducting nerve impulses, and gas and nutrient exchange.
Ion channels are specialized integral membrane proteins on the plasma membrane that allow specific...
Non-gated Ion Channels01:24

Non-gated Ion Channels

Ion channels are specialized proteins on the plasma membrane that allow charged ions to pass down their electrochemical gradient. Their main function is to maintain the membrane potential which is critical for cell viability. These channels are either gated or non-gated and can transport more than a thousand ions within milliseconds for the cellular event to occur.
Compared to the gated ion channels, the non-gated channels, also known as leakage or passive channels, have no gating mechanism.
The Role of Ion Channels in Neuronal Computation01:19

The Role of Ion Channels in Neuronal Computation

A postsynaptic neuron usually receives numerous impulses from several other presynaptic neurons. The axon hillock of the postsynaptic neuron integrates all these signals and determines the likelihood of firing an action potential.
Sometimes a single EPSP is strong enough to induce an action potential in the postsynaptic neuron. However, multiple presynaptic inputs must often create EPSPs around the same time for the postsynaptic neuron to be sufficiently depolarized to fire an action potential.
Non-gated Ion Channels01:24

Non-gated Ion Channels

Ion channels are specialized proteins on the plasma membrane that allow charged ions to pass down their electrochemical gradient. Their main function is to maintain the membrane potential which is critical for cell viability. These channels are either gated or non-gated and can transport more than a thousand ions within milliseconds for the cellular event to occur.
Compared to the gated ion channels, the non-gated channels, also known as leakage or passive channels, have no gating mechanism.
Insensitive Nuclei Enhanced by Polarization Transfer (INEPT)01:15

Insensitive Nuclei Enhanced by Polarization Transfer (INEPT)

Insensitive Nuclei Enhanced by Polarization Transfer (INEPT) is an advanced Nuclear Magnetic Resonance (NMR) technique specifically designed to detect and enhance the signals of low-abundance nuclei, such as carbon-13 and nitrogen-15, in small molecules. The fundamental principle behind INEPT is the transfer of polarization from a more abundant and highly polarizable nucleus, typically hydrogen-1, to the low-abundance nucleus of interest. This process effectively boosts the NMR signal of the...
Pore Transport and Ion-Pair Transport01:17

Pore Transport and Ion-Pair Transport

Pore transport and ion-pair formation are critical mechanisms for the absorption and distribution of drugs in the body.
Pore transport, also known as convective transport, is a process where small molecules like urea, water, and sugars rapidly cross cell membranes as though there were channels or pores in the membrane. Although direct microscopic evidence is limited  but the concept of pores or channels is widely accepted based on physiological evidence. Despite the lack of direct microscopic...

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Updated: May 11, 2026

On-chip Isotachophoresis for Separation of Ions and Purification of Nucleic Acids
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On-chip Isotachophoresis for Separation of Ions and Purification of Nucleic Acids

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tRNA isodecoder analysis using Nanopore ionic current signals and deep learning.

Stuart Akeson1, Pooria Daneshvar Kakhaki2, Neda Ghohabi Esfahani1

  • 1Department of Bioengineering, Northeastern University, Boston, MA 02115, USA.

Biorxiv : the Preprint Server for Biology
|January 7, 2026
PubMed
Summary
This summary is machine-generated.

We developed a deep learning method using Nanopore sequencing and ionic current signals for accurate transfer RNA (tRNA) analysis. This approach improves isodecoder identification and alignment in bacteria and yeast, advancing biological discovery.

Keywords:
Deep learningIonic current analysisIsodecoder classificationNanopore direct tRNA sequencingtRNA modifications

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Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Transfer RNA (tRNA) plays a crucial role in protein synthesis and cellular regulation.
  • Accurate analysis of tRNA sequences and their modifications is essential for understanding biological processes.
  • Current methods for tRNA analysis face limitations in resolution and accuracy, particularly for isodecoder-level distinctions.

Purpose of the Study:

  • To develop and validate a novel computational strategy for high-resolution tRNA analysis using Nanopore direct sequencing.
  • To leverage deep learning and ionic current signals for precise isodecoder identification in bacterial and yeast tRNA.
  • To enhance tRNA sequence alignment accuracy and explore the potential of ionic current data for detecting tRNA modifications.

Main Methods:

  • Application of Nanopore direct sequencing technology for capturing ionic current signals from tRNA molecules.
  • Development of deep learning models to predict tRNA isodecoders directly from raw nanopore ionic current data.
  • Integration of ionic current analysis with pairwise sequence alignment to improve tRNA read alignment and identity.

Main Results:

  • Achieved improved alignment rates for *E. coli* (2.6%) and *S. cerevisiae* (13.1%) tRNA reads compared to existing Nanopore strategies.
  • Demonstrated a significant increase in alignment identity, indicating higher accuracy in tRNA sequence determination.
  • Successfully used ionic current models to confirm enrichment of specific tRNA isotypes and fractions in experimental samples.
  • Showcased the information-rich nature of raw ionic current signals for deconvoluting complex molecular features, including chemical modifications.

Conclusions:

  • Nanopore direct tRNA sequencing combined with deep learning and ionic current analysis offers a powerful tool for isodecoder-level tRNA characterization.
  • This advanced methodology significantly improves the accuracy and efficiency of tRNA analysis in prokaryotes and lower eukaryotes.
  • The findings have broad implications for advancing tRNA research in discovery biology and human health applications.