Por décadas, um pequeno grupo de pesquisadores médicos de ponta vem estudando um sistema bioquímico de marcação de DNA, que liga ou desliga os genes. Muitos o estudaram em bactérias e agora alguns viram sinais disso em plantas, moscas e até tumores cerebrais humanos. No entanto, de acordo com um novo estudo realizado por pesquisadores da Escola de Medicina Icahn em Mount Sinai, pode haver um problema:grande parte da evidência de sua presença em organismos superiores pode ser devido à contaminação bacteriana, que foi difícil de detectar usando testes experimentais atuais. métodos.
Para resolver isso, os cientistas criaram um método de sequenciamento de genes sob medida que se baseia em um novo algoritmo de aprendizado de máquina para medir com precisão a fonte e os níveis de DNA marcado. Isso os ajudou a distinguir o DNA bacteriano do humano e de outras células não bacterianas. Enquanto os resultados publicados na Science apoiaram a ideia de que este sistema pode ocorrer naturalmente em células não bacterianas, os níveis foram muito mais baixos do que alguns estudos anteriores relatados e foram facilmente distorcidos por contaminação bacteriana ou métodos experimentais atuais. Experimentos com células cancerígenas do cérebro humano produziram resultados semelhantes.

"Empurrar os limites da pesquisa médica pode ser desafiador. Às vezes, as idéias são tão novas que temos que repensar os métodos experimentais que usamos para testá-las", disse Gang Fang, Ph.D., Professor Associado de Genética e Ciências Genômicas da Icahn Monte Sinai. "Neste estudo, desenvolvemos um novo método para medir efetivamente essa marca de DNA em uma ampla variedade de espécies e tipos de células. Esperamos que isso ajude os cientistas a descobrir os muitos papéis que esses processos podem desempenhar na evolução e nas doenças humanas".

O estudo se concentrou na metilação da adenina do DNA, uma reação bioquímica que liga um produto químico, chamado grupo metil, a uma adenina, uma das quatro moléculas de bloco de construção usadas para construir longas fitas de DNA e codificar genes. Isso pode ativar ou silenciar genes "epigeneticamente" sem realmente alterar as sequências de DNA. Por exemplo, sabe-se que a metilação da adenina desempenha um papel crítico na forma como algumas bactérias se defendem contra vírus.

Durante décadas, os cientistas pensaram que a metilação da adenina acontecia estritamente nas bactérias, enquanto as células humanas e outras não bacterianas dependiam da metilação de um bloco de construção diferente – citosina – para regular os genes. Then, starting around 2015, this view changed. Scientists spotted high levels of adenine methylation in plant, fly, mouse, and human cells, suggesting a wider role for the reaction throughout evolution.

However, the scientists who performed these initial experiments faced difficult trade-offs. Some used techniques that can precisely measure adenine methylation levels from any cell type but do not have the capacity to identify which cell each piece of DNA came from, while others relied on methods that can spot methylation in different cell types but may overestimate reaction levels.

In this study, Dr. Fang's team developed a method called 6mASCOPE which overcomes these trade-offs. In it, DNA is extracted from a sample of tissue or cells and chopped up into short strands by proteins called enzymes. The strands are placed into microscopic wells and treated with enzymes that make new copies of each strand. An advanced sequencing machine then measures in real time the rate at which each nucleotide building block is added to a new strand. Methylated adenines slightly delay this process. The results are then fed into a machine learning algorithm which the researchers trained to estimate methylation levels from the sequencing data.

"The DNA sequences allowed us to identify which cells—human or bacterial—methylation occurred in while the machine learning model quantified the levels of methylation in each species separately," said Dr. Fang,

Initial experiments on simple, single-cell organisms, such as green algae, suggested that the 6mASCOPE method was effective in that it could detect differences between two organisms that both had high levels of adenine methylation.

The method also appeared to be effective at quantifying adenine methylation in complex organisms. For example, previous studies had suggested that high levels of methylation may play a role in the early growth of the fruit fly Drosophila melanogaster and of the flowering weed Arabidopsis thaliana . In this study, the researchers found that these high levels of methylation were mostly the result of contaminating bacterial DNA. In reality, the fly and the plant DNA from these experiments only had trace amounts of methylation.

Likewise, experiments on human cells suggested that methylation occurs at very low levels in both healthy and disease conditions. Immune cell DNA obtained from patient blood samples had only trace amounts of methylation.

Similar results were also seen with DNA isolated from glioblastoma brain tumor samples. This result was different than a previous study, which reported much higher levels of adenine methylation in tumor cells. However, as the authors note, more research may be needed to determine how much of this discrepancy may be due to differences in tumor subtypes as well as other potential sources of methylation.

Finally, the researchers found that plasmid DNA, a tool that scientists use regularly to manipulate genes, may be contaminated with high levels of methylation that originated from bacteria, suggesting this DNA could be a source of contamination in future experiments.

"Our results show that the manner in which adenine methylation is measured can have profound effects on the result of an experiment. We do not mean to exclude the possibility that some human tissues or disease subtypes may have highly abundant DNA adenine methylation, but we do hope 6mASCOPE will help scientists fully investigate this issue by excluding the bias from bacterial contamination," said Dr. Gang. "To help with this we have made the 6mASCOPE analysis software and a detailed operating manual widely available to other researchers."