Instruction Tools for Signal Processing and Machine Learning for Ion-Channel Sensors

Instruction Tools for Signal Processing and Machine Learning for Ion-Channel Sensors

Prasanna Sattigeri, Jayaraman Thiagarajan, Karthikeyan Ramamurthy, Andreas Spanias, Mahesh Banavar, Abhinav Dixit, Jie Fan, Mohit Malu, Kristen Jaskie, Sunil Rao, Uday Shanthamallu, Vivek Narayanaswamy, Sameeksha Katoch
DOI: 10.4018/IJVPLE.285601
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Abstract

Ion Channel sensors have several applications including DNA sequencing, biothreat detection, and medical applications. Ion-channel sensors mimic the selective transport mechanism of cell membranes and can detect a wide range of analytes at the molecule level. Analytes are sensed through changes in signal patterns. Papers in the literature have described different methods for ion channel signal analysis. In this paper, we describe a series of new graphical tools for ion channel signal analysis which can be used for research and education. The paper focuses on the utility of this tools in biosensor classes. Teaching signal processing and machine learning for ion channel sensors is challenging because of the multidisciplinary content and student backgrounds which include physics, chemistry, biology and engineering. The paper describes graphical ion channel analysis tools developed for an on-line simulation environment called J-DSP. The tools are integrated and assessed in a graduate bio-sensor course through computer laboratory exercises.
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1. Introduction

In this paper, we introduce the subject of biological ion-channels and motivate their importance in modern biology, medicine, detection of biothreats and DNA sequence analysis. There have been several efforts to build sensors that are based on ion channels which promise to detect analytes at the molecule level (Wilk et al 2004). The motivation for using signal processing in analyzing ion-channel signals stems from the fact that ion-channel currents are very small and noise in acquiring data can be significant. We briefly describe the electrical signals that characterize ion-channels and discuss the signal processing techniques needed to denoise and classify these signals. Pre-processing and transform methods are described to segment and extract appropriate features to identify ion-channel events of interest. We introduce J-DSP - a high-level web-based software tool for simulating and teaching signal processing concepts without requiring a substantial background in programming. We use J-DSP to teach the signal processing aspects of ion-channel studies to an interdisciplinary bioelectronics class and evaluate its effectiveness using objective and subjective student assessments. In the sub-sections below, we provide background and motivation for this endeavor and we describe the basics of J-DSP.

1.1 Importance of the Study of Ion-Channels

The study of ion-channels is embedded in several undergraduate and graduate-level bioscience, bio-engineering, and medical science curricula (Demir. 2006). Understanding ion-channels helps in understanding living systems at the cellular level. Cellular membranes are inherently non-permeable to ions. Ion-channel proteins form gated pores across these cell membranes and regulate the flow of ions (Miller 1992, Purves et.al., 2008). They are formed by proteins in living cells and are important in physiological functions such as transport of nutrients, nerve excitation, muscle contraction, and hormonal secretion (Chrispeels et. al., 1999, Goodman 2008). Disorders in the functioning of ion-channels can lead to several diseases (Hatta et.al., 2002) and mutation of the ion-channel proteins. These are the primary causes of abnormal excitation of cells. Mutations can occur in the promoter region (Chakravarthy et. al., 2004, Cooper and Jan, 1999, Ravichandran et.al., 2011) which leads to over-expression or under-expression of the channel protein. Mutations in the coding region can lead to gain or loss of channel function. Abnormalities in the ion transport across channels can cause diseases such as Bartter syndrome. In addition, certain ion-channel forming proteins can act as lethal agents and are often part of the venom of snakes. Ion channels, and their close relative nanopores, are also very useful in DNA sequencing (Ali et.al 2010). More recently, research efforts have demonstrated the utility of ion channels in detecting the SARS-CoV-2 virus that causes COVID-19 (McClenaghan et. al., 2020). The study of ion-channels can provide substantial insight into the cause of several diseases.

As computation models for ion-channel analysis continue to improve, interactions with new molecules and compounds have been discovered and used in fields such as bioengineering and pharmacology. The utility of biologically engineered ion-channels for sensing has been studied in (Braha et.al., 2000, Gu et.al., 1999). Ion-channel proteins have been used to analyze pharmaceutically important substances and to aid in the detection of harmful elements potentially released by chemical weapons.

Due to switching or gating properties, ion-channel proteins produce characteristic current signals (Catterall, 2010). These current signals can be evaluated and analyzed using standard signal processing methods. In (Spanias et. al., 2007a, Konnanath et al., 2009a), the authors describe several statistical signal analysis tools to analyze ion channel currents and ion channel noise.

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