Researchers developed a custom gene sequencing technology to precisely quantify a biochemical DNA tagging mechanism that turns genes on and off. They were able to analyze the system in a variety of cell types, including human, plant, and bacterial cells, as a result of this. While the findings supported the hypothesis that this system may exist in non-bacterial cells in nature, the levels were significantly lower than those reported in prior research and were readily biased by bacterial contamination or existing experimental procedures. Human brain cancer cells were used in the experiments, and the findings were identical.
A tiny group of cutting-edge medical experts has been researching a biochemical DNA tagging system that turns genes on or off for decades. Many researchers have looked at it in bacteria, and now some have discovered traces of it in plants, insects, and even human brain tumors. However, there may be a snag, according to a recent study from Mount Sinai’s Icahn School of Medicine: most of the evidence of its existence in higher species might be due to bacterial contamination, which is difficult to detect using existing experimental techniques.
To combat this, the researchers developed a custom gene sequencing approach that uses a novel machine learning algorithm to precisely determine the source and quantities of tagged DNA. They were able to differentiate bacterial DNA from that of human and non-bacterial cells as a result of this. While the findings published in Science supported the hypothesis that this system may exist naturally in non-bacterial cells, the levels were far lower than those reported in prior research and were readily biased by bacterial contamination or current experimental procedures. Human brain cancer cells were used in the experiments, and the findings were identical.
“It might be difficult to push the frontiers of medical study. We have to rethink the experimental techniques we employ to test out some of the theories since they are so innovative “Icahn Mount Sinai’s Gang Fang, PhD, is an Associate Professor of Genetics and Genomic Sciences. “We devised a novel approach for quantifying this DNA mark in a broad range of species and cell types in this work. We expect that by doing so, scientists will be able to learn more about the myriad roles that these processes may play in evolution and human illness.”
The research focused on DNA adenine methylation, a biological procedure in which a methyl group is attached to an adenine, one of the four building blocks molecules used to make long DNA strands and encode genes. Without actually changing DNA sequences, this may “epigenetically” activate or mute genes. For example, adenine methylation is known to play a key role in how certain bacteria protect themselves against viruses.
For decades, scientists assumed that adenine methylation only occurred in bacteria, and that methylation of a separate building component, cytosine, was used to control genes in human and other non-bacterial organisms. Then, about 2015, this viewpoint shifted. High quantities of adenine methylation were found in plant, fly, mouse, and human cells, indicating that the reaction has played a larger role throughout evolution.
The scientists who carried out the early trials, on the other hand, had to make tough trade-offs. Others relied on methods that can recognize methylation in various cell types but may overstate response levels, while others employed techniques that can accurately quantify adenine methylation levels from any cell type but lack the ability to identify which cell each piece of DNA originated from.
Dr. Fang’s team devised a technique dubbed 6mASCOPE to address these trade-offs in this work. It involves extracting DNA from a sample of tissue or cells and chopping it up into little strands using enzymes. The strands are put in minuscule wells and treated with enzymes that cause each strand to replicate itself. The pace at which each nucleotide building block is introduced to a new strand is subsequently measured in real time by a sophisticated sequencing equipment. Methylated adenines slow down the process somewhat. The information is then entered into a machine learning system that the researchers developed to predict methylation levels from sequencing data.
“The DNA sequences enabled us to determine which cells — human or bacterial — methylation happened in, while the machine learning algorithm assessed methylation levels in each species individually,” stated Dr. Fang.
The 6mASCOPE approach seemed to be helpful in detecting changes between two species that both had significant levels of adenine methylation in early trials on basic, single-cell organisms like green algae.
In complex organisms, the approach seemed to be successful in quantifying adenine methylation. Previous research has revealed that high levels of methylation may play a role in the fruit fly Drosophila melanogaster and the flowering plant Arabidopsis thaliana’s early development. The researchers discovered that these high levels of methylation were largely caused by bacterial DNA contamination in this investigation. In truth, only negligible quantities of methylation were found in the DNA of the fly and plant in these investigations.
Experiments on human cells also shown that methylation takes place at extremely low levels in both healthy and diseased states. Only small quantities of methylation were found in immune cell DNA extracted from patient blood samples.
DNA extracted from glioblastoma brain tumor samples yielded similar findings. This was in contrast to a recent research that found much greater levels of adenine methylation in tumor cells. However, as the authors point out, additional study is required to understand how much of the variation is attributable to tumor subtype differences or other possible methylation causes.
Finally, the researchers discovered that plasmid DNA, a common tool for manipulating genes, may be contaminated with high amounts of methylation from bacteria, suggesting that this DNA might be a source of contamination in future investigations.
“Our findings suggest that the method used to quantify adenine methylation has a significant impact on the outcome of an experiment. We don’t rule out the potential that certain human tissues or disease subtypes have high levels of DNA adenine methylation, but we think that 6mASCOPE can enable scientists in conducting a thorough investigation of this topic by removing the bias caused by bacterial contamination “Dr. Gang said. “We’ve made the 6mASCOPE analysis software and a full operation manual readily accessible to other researchers to assist with this.”
The National Institutes of Health (GM139655, HG011095, AG071291), the Icahn Institute for Genomics and Multiscale Biology, the Irma T. Hirschl/Monique Weill-Caulier Trust, the Nash Family Foundation, and the Department of Scientific Computing at Mount Sinai all contributed to this research. Collaborations at the Chinese Academy of Sciences (XDPB2004) and the National Natural Science Foundation of China enabled the validation of methods utilizing mass spectrometry (22021003).