Durante décadas, un pequeño grupo de investigadores médicos de vanguardia ha estado estudiando un sistema bioquímico de marcado de ADN que activa o desactiva los genes. Muchos lo han estudiado en bacterias y ahora algunos han visto signos de él en plantas, moscas e incluso en tumores cerebrales humanos. Sin embargo, según un nuevo estudio realizado por investigadores de la Escuela de Medicina Icahn en Mount Sinai, puede haber un problema:gran parte de la evidencia de su presencia en organismos superiores puede deberse a la contaminación bacteriana, que fue difícil de detectar con los métodos experimentales actuales. métodos.

Para abordar esto, los científicos crearon un método de secuenciación de genes hecho a medida que se basa en un nuevo algoritmo de aprendizaje automático para medir con precisión la fuente y los niveles de ADN marcado. Esto les ayudó a distinguir el ADN bacteriano del humano y de otras células no bacterianas. Mientras que los resultados publicados en Science apoyó la idea de que este sistema puede ocurrir naturalmente en células no bacterianas, los niveles fueron mucho más bajos que los informados en algunos estudios anteriores y fueron fácilmente sesgados por la contaminación bacteriana o los métodos experimentales actuales. Los experimentos con células de cáncer de cerebro humano produjeron resultados similares.

"Ampliar los límites de la investigación médica puede ser un desafío. A veces, las ideas son tan novedosas que tenemos que repensar los métodos experimentales que usamos para probarlas", dijo Gang Fang, Ph.D., Profesor Asociado de Genética y Ciencias Genómicas en Icahn Monte Sinaí. "En este estudio, desarrollamos un nuevo método para medir de manera efectiva esta marca de ADN en una amplia variedad de especies y tipos de células. Esperamos que esto ayude a los científicos a descubrir las muchas funciones que estos procesos pueden desempeñar en la evolución y las enfermedades humanas".

El estudio se centró en la metilación de la adenina del ADN, una reacción bioquímica que une una sustancia química, llamada grupo metilo, a una adenina, una de las cuatro moléculas de bloques de construcción utilizadas para construir cadenas largas de ADN y codificar genes. Esto puede activar o silenciar "epigenéticamente" genes sin alterar realmente las secuencias de ADN. Por ejemplo, se sabe que la metilación de la adenina juega un papel fundamental en la forma en que algunas bacterias se defienden contra los virus.

For decades, scientists thought that adenine methylation strictly happened in bacteria whereas human and other non-bacterial cells relied on the methylation of a different building block—cytosine—to regulate 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."