## 1 Introduction  
Organ-on-chip platforms have rapidly gained recognition as highly predictive and physiologically relevant tools for modeling human tissues and diseases in vitro, offering enhanced translational potential compared to conventional cell culture methods. To fully characterize these microphysiological systems, it is critical to assess both nuclear and mitochondrial genetic integrity, as well as epigenetic modifications that can influence cellular responses to drugs or environmental stimuli. While profiling absorption, distribution, metabolism, and excretion (ADME) genes remains central to understanding pharmacokinetics and toxicity in organ-on-chip setups, investigating mitochondrial genome perturbations--including sequence variations and methylation patterns--provides a more comprehensive picture of cellular metabolism and stress responses. The integrity of the mitochondrial genome (mtDNA) is crucial for cellular energy production, metabolism [1; 2; 3; 4], and overall cell health [5; 6; 7; 8; 9; 10]. Unlike the nuclear genome, mtDNA exists in multiple copies per cell and is particularly susceptible to accumulating sequence variations and molecular damage [1; 2; 3; 4; 11; 12; 13; 14; 15] leading to heteroplasy (the coexistence of different mtDNA types within a cell) and epigenetic modifications such as DNA methylation [16; 17; 18]. Accurately characterizing these mtDNA features is vital for understanding cellular function, aging, and disease pathogenesis, but it poses significant technical challenges [15]. The human mitochondrial genome is circular, consisting of 37 genes, has no introns, and is represented by naked double-stranded DNA, more susceptible to molecular modification and damage [13; 14; 15]. MtDNA defects were mainly studied using Sanger sequencing, Southern blot, and long and quantitative PCR. However, these technologies are expensive and limited in speed, throughput, and sensitivity. Recently, next-generation sequencing (NGS) has been more and more explored to study mtDNA defects. In this study, we employed third-generation sequencing technology from Oxford Nanopore, which utilizes flow cells containing arrays of nanopores embedded in an electro-resistant membrane. Each nanopore is coupled to an electrode connected to a channel and sensor chip that continuously monitors the ionic current passing through the pore. As a DNA or RNA molecule translocates through the nanopore, characteristic disruptions in the current produce a so-called \"squiggle\" signal. This signal is then deciphered by real-time base-calling algorithms to reconstruct the nucleotide sequence. Unlike short-read sequencing methods, which constrain analyses to limited read lengths, nanopore sequencing accommodates continuous, long-read data. Such extended read lengths enable complete resolution of repetitive regions, identification of structural variants, and discrimination between different isoforms, thereby offering a more comprehensive genomic characterization. Long-read sequencing is based on a simplified protocol that requires nanopore adaptor ligation of the sequenced DNA strand. Therefore, opening the circular mitochondrial DNA is crucial for this protocol to work. DNA shearing is one way to produce many linearized strands of DNA, but unless ultrasound or enzyme approaches are applied, it results in non-uniform length of the future sequencing reads. To avoid amplification-related biases and to enable the simultaneous detection of base modifications (e.g., methylation) alongside the nucleotide sequence, we employed another ONT technology referred to as _Adaptive Sampling_. This software-controlled method is unique to nanopore sequencing and selectively enriches the desired region without PCR amplification. By providing a FASTA file specifying the target region, the adaptive sampling algorithm examines the first 400-500 bp of each DNA fragment as it enters the nanopore.