Are scientists being fooled by bacteria?
Previous studies of a genetic on/off switch may have been confounded by contamination

Date:
February 3, 2022
Source:
The Mount Sinai Hospital / Mount Sinai School of Medicine
Summary:
Researchers created a tailor-made gene sequencing method to
accurately measure a biochemical, DNA tagging system, which
switches genes on or off. This helped them study the system in any
cell type, including human, plant and bacterial cells. While the
results supported the idea that this system may occur naturally in
non-bacterial cells, the levels were much lower than some previous
studies reported and were easily skewed by bacterial contamination
or current experimental methods. Experiments on human brain cancer
cells produced similar results.



FULL STORY ==========================================================================
For decades, a small group of cutting-edge medical researchers have
been studying a biochemical, DNA tagging system, which switches genes
on or off.

Many have studied it in bacteria and now some have seen signs of it in,
plants, flies, and even human brain tumors. However, according to a new
study by researchers at the Icahn School of Medicine at Mount Sinai,
there may be a hitch: much of the evidence of its presence in higher
organisms may be due to bacterial contamination, which was difficult to
spot using current experimental methods.


==========================================================================
To address this, the scientists created a tailor-made gene sequencing
method which relies on a new machine learning algorithm to accurately
measure the source and levels of tagged DNA. This helped them distinguish bacterial DNA from that of human and other non-bacterial cells. While
the results published in Science supported the idea that this system
may occur naturally in non- bacterial cells, the levels were much lower
than some previous studies reported and were easily skewed by bacterial contamination or current experimental methods. Experiments on human
brain cancer cells produced similar results.

"Pushing the boundaries of medical research can be challenging. Sometimes
the ideas are so novel that we have to rethink the experimental methods
we use to test them out," said Gang Fang, PhD, Associate Professor of
Genetics and Genomic Sciences at Icahn Mount Sinai. "In this study,
we developed a new method for effectively measuring this DNA mark
in a wide variety of species and cell types. We hope this will help
scientists uncover the many roles these processes may play in evolution
and human disease." The study focused on DNA adenine methylation, a biochemical reaction which attaches a chemical, called a methyl group,
to an adenine, one of the four building block molecules used to construct lengthy DNA strands and encode genes. This can "epigenetically" activate
or silence genes without actually altering DNA sequences. For instance,
it is known that adenine methylation plays a critical role in how some
bacteria defend themselves against viruses.

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." This work
was supported by 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 the Icahn School of Medicine
at Mount Sinai. Methods validation using Mass Spectrometry was supported
by the collaborators at the Chinese Academy of Sciences (XDPB2004)
and the National Natural Science Foundation of China (22021003).

special promotion Explore the latest scientific research on sleep and
dreams in this free online course from New Scientist -- Sign_up_now_>>> ========================================================================== Story Source: Materials provided by The_Mount_Sinai_Hospital_/_Mount_Sinai_School_of Medicine. Note: Content
may be edited for style and length.


========================================================================== Journal Reference:
1. Yimeng Kong, Lei Cao, Gintaras Deikus, Yu Fan, Edward A. Mead,
Weiyi Lai,
Yizhou Zhang, Raymund Yong, Robert Sebra, Hailin Wang, Xue-Song
Zhang, Gang Fang. Critical assessment of DNA adenine methylation
in eukaryotes using quantitative deconvolution. Science, 2022;
375 (6580): 515 DOI: 10.1126/science.abe7489 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2022/02/220203160551.htm

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