Kendra Pierre-Louis: For Scientific AmericanIt is Science quicklymy name is Kendra Pierre-Louis, I’m replacing Rachel Feltman. You are listening to our weekly summary of scientific news.
First, a new AI model could help expand our understanding of genetics. To get more information about this research, I spoke with Tanya Lewis, senior editor for the Health and Medicine Bureau here at SciAm. Here is that conversation.
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Ask Lewis: Of course, at any time.
Pierre-Louis: A massive study was therefore published [last] Wednesday in the newspaper Nature Google researchers, who said that using their AI model, which they call AlphaGenome, they could predict the function of certain pieces of DNA. And you know, I know most people at this point know that these are the building blocks of life, but what does that really mean and what are some of the gaps in our knowledge of DNA?
Louis: Okay, so DNA, as you said, is sort of the blueprint for life. Every cell in our body has this long genetic code made up of basically four letters, so A, T, G and C – the nucleotides – and then these nucleotides, or letters, link together in what are called base pairs. And it’s the order of these base pairs that actually determines the code for every protein in our body, and these are the proteins that carry out all the vital functions of our cells and also the problems that arise when we suffer from disease.
Pierre-Louis: You know, over the last few decades we have successfully sequenced the entire human genome. But it’s a bit like we now have all the words in a book of a language we don’t speak, and we’re now trying to figure out what the different codes really mean.
Louis: Yeah, that’s a great way to describe it. And so what Google DeepMind is trying to do with AlphaGenome, this latest AI model, is basically take long stretches of the genome that don’t do it coding proteins – this is called non-coding DNA – and trying to understand what these DNA fragments actually do to control gene activity.
So even though they are called non-coding, they are actually very important to how genes are expressed or made into proteins. So we want to understand these long sections of what we sometimes call the “dark matter” of DNA. So the way genes work is they have these instructions in our nucleus, and those instructions are then transcribed into what’s called RNA, which is similar to DNA, but basically they’re little messages that come out of the nucleus and say to the cell, “Okay, make this protein.” And these RNA instructions are translated into proteins. So that’s the part that I think AlphaGenome is really trying to unpack is this kind of more complicated regulatory stuff.
Pierre-Louis: Got it. I don’t know why in my head I imagine DNA as a royal person and RNA as a scribe. [Laughs.]
Louis: [Laughs.] Yeah, exactly. It’s a good analogy. It’s like up top, the DNA says, here’s what you should do, make these proteins, and then the RNA says, yes, sir. And there are all these intermediate steps where that message can be changed, and that’s where this regulatory DNA comes in, so – and particularly in disease. So when you have cancer, for example, it hijacks your cells and tells them to make more copies of themselves, and that’s not how the cell is supposed to work. So this is something we want to understand better.
Pierre-Louis: So with AlphaGenome, you know, if this is confirmed, and understand [these] regulatory pieces of DNA, we can understand how things like cancer can hijack this message; this could lead to better treatments. Is this that kind of hope?
Louis: I would say that, well downstream, that’s the goal, but at this point, AlphaGenome is really designed to help researchers and scientists test their hypotheses about how a gene might be regulated, like, “Oh, maybe this mutation has this effect.” And then they can go out and test that. And then, hopefully, that will lead to these treatments. And what’s exciting about a tool like this is that it can simplify a lot of the work that goes into testing all of these different hypotheses and basically streamline the process so that scientists can move forward more efficiently.
Pierre-Louis: To learn more about AlphaGenome, visit ScientificAmerican.com.
In other groundbreaking news, Northwestern University researchers accomplished an impressive feat: They kept a patient alive for 48 hours without lungs, according to a study published Thursday in the Cell Press newspaper With.
The patient was a 33-year-old man who arrived at the hospital with a life-threatening illness: acute respiratory distress syndrome, or ARDS. When a person has ARDS, their lungs are so inflamed that fluid fills the organs’ small air sacs. Oxygen has difficulty getting in, making it extremely difficult for the person to breathe. In this case, the respiratory distress was triggered by a flu infection exacerbated by a case of bacterial pneumonia. The disease was so severe that the man’s lungs, heart and kidneys eventually began to fail, researchers said.
Doctors already have ways to oxygenate the blood when the heart or lungs have difficulty giving these organs time to recover. Extracorporeal membrane oxygenation, or ECMO, for example, is a life-sustaining technique that involves connecting patients to an artificial heart-lung machine. The machine removes blood from the body to remove carbon dioxide and add oxygen. Then the machine heats the blood and returns it to the body. In this case, doctors felt the man’s lungs were so damaged that they were unlikely to heal. At the same time, they were a source of infection and so he was unlikely to recover once his lungs were in place. So they removed his lungs and installed a total artificial lung system to not only oxygenate the blood, but also to ensure it circulates regularly through the heart. After lung removal, the patient stabilized. Two days later he received a double lung transplant, and two years later he is still alive.
The study sheds light on an incredible piece of medical science and also serves as a reminder of how serious a flu infection can be.
Besides, anyone who has sent a baby to daycare knows that these adorable moppets are tiny germ factories. But a study published at the end of January in the review Nature suggests babies in daycare don’t just spread “bad” germs; they also share “good” germs.
The current thinking is that a baby’s microbiome usually begins to develop after birth, primarily through microbes passed on from the parent who gave birth to them. And while research has also shown that the exchange of microbial strains is common among people who live together, how the microbiota changes during the early stages of a child’s life is not well understood.
Italian researchers sought answers by tracking the microbiomes of 43 babies before, during and after their first year of care. The team analyzed fecal samples from the babies, nursery staff and members of the children’s households, including their parents, siblings and pets.
The study found that microbiome transmission between babies began just a month after they entered day care and continued to grow over the course of the year. At the same time, babies who had a sibling often had greater diversity in their overall microbiota. They also received more of their microbiome from their sibling than from their parents, while fewer bacterial strains were passed on from other babies in the nursery.
The study also mapped the transmission of individual microbial species between participants. For example, researchers discovered that a strain of bacteria called Akkermansia muciniphila, It is thought to have some metabolic benefits, passed from a mother to her baby, who passes it on to another baby at daycare, who then passes it on to their parents. What this means as a whole is not yet clear: after all, our understanding of microbiomes continues to expand. But this study at least gives a clearer picture of how bacteria move.
And finally, we turn to a little tropical flower that may very well upend what we thought we knew about plant evolution. This is what a published study reveals [last] Tuesday in the newspaper New plant scientist.
At the center of the mystery is a group of plants called lipstick vines. These plants get their common name from their large, tube-shaped red flowers that look, well, like as IIP key. This tubular shape attracts sunbirds, with their long, thin beaks. And yet, a type of lipstick vine, Aeschynanthus sharp do not bring up such makeup ideas. It has short yellowish-green flowers and grows not only in mainland Asia, where its fellow lipstick vines are found, but also on the island of Taiwan, which has no sunbirds. There, green lipstick vines are usually pollinated by generalist birds that are not particularly particular about where they get their food.
In botany, there has long been a theory known as the Grant-Stebbins model, which states that plants typically evolve when they move to a new location to attract pollinators in the area. The researchers wondered if this was the case for this unusual lipstick vine: had it simply adapted to life in sunbird-free Taiwan?
But a DNA analysis of this lipstick vine found in Taiwan, compared to its relatives in mainland Asia, suggested that no, the plant had evolved in mainland Asia and then made its way to Taiwan, contradicting the Grant-Stebbins model.
Jing-Yi Lu, lead author of the study, said in a statement, a quote, “It was really exciting to get these results because they don’t follow classical ideas about how we would have imagined the species evolved.”
In short, this isn’t the first time nature has found a way to foil our understanding of evolution – and it probably won’t be the last.
That’s all for the episode and today. See you on Wednesday to look at a curious phenomenon: not being able to burp.
But before we go, we’d like to ask for your help with an upcoming episode: it’s about kisses. Tell us about your most memorable kiss. What made him special? How did you feel? Record a voice memo on your phone or computer and send it to ScienceQuickly@sciam.com. Be sure to include your name and where you are from.
Science quickly is produced by me, Kendra Pierre-Louis, with Fonda Mwangi, Sushmita Pathak and Jeff DelViscio. This episode was edited by Alex Sugiura. Shayna Posses and Aaron Shattuck check in on our show. Our theme music was composed by Dominic Smith. Subscribe to Scientific American for more recent and in-depth scientific news.
For Scientific American, This is Kendra Pierre-Louis. Have a good week!
