I don't like this article style. I've read halfway through it and the purported real reason is constantly advertised but never revealed. I've come to expect this from clickbait youtube videos that try to make you watch to the end for the one bit of information you're looking for, but to see this in an article that presumably is not monetised in the same way is just weird.
For the record, I would have gladly read the full article if it hadn't annoyed me so much with this attempt to make sure I read to the end, which, let's be fair, nobody is going to do unless they're a nerd with an insatiable curiosity and a manic compulsion to read every bit of text on the page; but then that's the audience this article targets anyway, so why make it annoying to read? Either you find the subject fascinating and you'll read the entire article anyway, or you don't and you won't get past the title.
For the impatient goblins - " Vibrio pectenicida, a saltwater-loving bacterium that works its way into sea star fluids, as the likely “dominant pathogen responsible for sea star wasting disease.”
Thanks from us, the impatient goblins who are spoiled by all these tasty abstracts when reading papers on arxiv.
I see that human publications strive for engagement, not citations, so they try to suspend the answer on the longest string that fits on the page. Pictures are nice though!
I was very irritated by tease yet no reveal style of the article until mid, asked, asked LLM (Leo in brave) to summarise, then ctrl+f and read the actual point myself.
My coworkers worked on this research! I wasn't involved in this project, but I'm so stoked to see this making the rounds. Everyone involved is deservedly proud of this one.
A big part of what makes me happy is that this seems quite niche to me, but it's getting a ton of attention which suggests people care about this more than I realized. That feels good! This is a huge deal for biodiversity in a huge swath of the Pacific Ocean.
It’s been really sad to watch the decline of sea stars the past 10+ years. Tide-pooling just hasn’t been the same at Cannon Beach or the San Juan Islands. It’s very encouraging to pin down the culprit.
I recall seeing a good amount of ochre stars the last time I was over at Pacific City a few months back. I took it as a good sign. Didn't see any sun stars, but those tend to be further out anyway - need to have a really low tide.
Gehman's colleague Melanie Prentice, also with the Hakai Institute and UBC, had begun reviewing the sequencing analysis. Scrolling through data on her laptop, an unmistakable pattern jumped out. Of the hundreds of microorganisms in the samples, enormous quantities of bacteria from the genus Vibrio seemed present in sick stars. The pattern was so strong, Prentice tells me, that she assumed she'd bungled the analysis.
I'm not familiar with sequencing much, but would feeding these to models similar to or purpose built like AlphaFold shorten the research time drastically [0]? If not, what other recent technological advancements do you reckon that'd help here? Thanks.
Do you mean it could be faster to analyze sequences using models rather than scrolling through them on a laptop?
Yes, we could get some broad strokes of what's present by using analytical tools, and we do. A lot of our researchers use R and Python to write simple tools to find patterns and perform simple aggregations.
We're in the process of discovering how AI can assist us, and we've had plenty of success in creating models to aid with processing and detecting things like mussel and kelp beds in aerial imagery (drone, plane, and satellite), but I suspect in this case the data can't actually tell the full story to begin with so what we're actually looking for is more like clues, not answers. When answers are present, we tend to be simply presenting findings like which organisms were present and, to some extent, their apparent population density. This is really easy to do without AI. Some models might find interesting patterns, but it's hard to tell which ones or why, or how we'd train that ourselves. It's an interesting question.
I work on the genomics team so it's something I should be actively considering. The work is certainly more manual than it needs to be, so there's work to be done here for sure.
It's tricky to identify the caustive agent from sequencing data. Sometimes it sticks out like a sore thumb. Eg I recently worked on samples from a patient who died, it was very easy to identify the cause because it was in the same at massive quantities (reads).
But usually, it's trawling through a hundred hits across all domains of life deciding is it consensual, contamination, pathogenic or database error. It's usually inconclusive.
Oddly enough, llm bots seem to be quiet good at this task without even fine tuning.
Well that’s fun. The seastars are ravaged by Vibrio pectenicida in the same genus that includes human pathogens like the bacteria that causes cholera and various flesh eating bacteria that can infect through undercooked seafood. The latter have even begun to eat plastic and multiply in sargassum [1] so watch those cuts when swimming in Florida!
No, I believe his necrotising fasciitis was caused by an infection from a skin biopsy so likely a different bacteria.
(Flesh eating bacteria don’t literally eat the tissue, they release toxins that kill the tissue so there’s many different kinds that can cause necrotising fasciitis).
For anyone else irritated by continuous teasing style of the article, it reveals the reason a bit past midway.
> Now, in August 2025, after another year-and-a-half of work confirming and reviewing their findings, Gehman and her team have published a peer-reviewed study in the journal Nature Ecology & Evolution identifying Vibrio pectenicida, a saltwater-loving bacterium that works its way into sea star fluids, as the likely “dominant pathogen responsible for sea star wasting disease.” Gehman’s team has tracked down the killer.
There is a major carbon credit opportunity that I hope is financially engineered by the right people.
Restoring the kelp forest would sequester more than €1.5B worth of carbon every year. That’s because the kelp grows so rapidly and then is sucked down into the deep sea. Ideally the ecosystem itself would somehow receive money for its services—but short of that, some foundation on behalf of the ecosystem —and short of that, some organization that’d be prepared to use the money to reinvest in other ecosystems.
I don't like this article style. I've read halfway through it and the purported real reason is constantly advertised but never revealed. I've come to expect this from clickbait youtube videos that try to make you watch to the end for the one bit of information you're looking for, but to see this in an article that presumably is not monetised in the same way is just weird.
For the record, I would have gladly read the full article if it hadn't annoyed me so much with this attempt to make sure I read to the end, which, let's be fair, nobody is going to do unless they're a nerd with an insatiable curiosity and a manic compulsion to read every bit of text on the page; but then that's the audience this article targets anyway, so why make it annoying to read? Either you find the subject fascinating and you'll read the entire article anyway, or you don't and you won't get past the title.
For the impatient goblins - " Vibrio pectenicida, a saltwater-loving bacterium that works its way into sea star fluids, as the likely “dominant pathogen responsible for sea star wasting disease.”
https://www.nature.com/articles/s41559-025-02797-2
Thank you for being kind and considerate of the little goblins :)
Thanks from us, the impatient goblins who are spoiled by all these tasty abstracts when reading papers on arxiv.
I see that human publications strive for engagement, not citations, so they try to suspend the answer on the longest string that fits on the page. Pictures are nice though!
Maybe someone can write a browser extension that reads the article and answers its main question.
I was very irritated by tease yet no reveal style of the article until mid, asked, asked LLM (Leo in brave) to summarise, then ctrl+f and read the actual point myself.
My coworkers worked on this research! I wasn't involved in this project, but I'm so stoked to see this making the rounds. Everyone involved is deservedly proud of this one.
A big part of what makes me happy is that this seems quite niche to me, but it's getting a ton of attention which suggests people care about this more than I realized. That feels good! This is a huge deal for biodiversity in a huge swath of the Pacific Ocean.
It’s been really sad to watch the decline of sea stars the past 10+ years. Tide-pooling just hasn’t been the same at Cannon Beach or the San Juan Islands. It’s very encouraging to pin down the culprit.
I recall seeing a good amount of ochre stars the last time I was over at Pacific City a few months back. I took it as a good sign. Didn't see any sun stars, but those tend to be further out anyway - need to have a really low tide.
TFA goes
I'm not familiar with sequencing much, but would feeding these to models similar to or purpose built like AlphaFold shorten the research time drastically [0]? If not, what other recent technological advancements do you reckon that'd help here? Thanks.[0] Trying to make sense of the hype around some of these: https://fortune.com/2025/07/06/deepmind-isomorphic-labs-cure...
Do you mean it could be faster to analyze sequences using models rather than scrolling through them on a laptop?
Yes, we could get some broad strokes of what's present by using analytical tools, and we do. A lot of our researchers use R and Python to write simple tools to find patterns and perform simple aggregations.
We're in the process of discovering how AI can assist us, and we've had plenty of success in creating models to aid with processing and detecting things like mussel and kelp beds in aerial imagery (drone, plane, and satellite), but I suspect in this case the data can't actually tell the full story to begin with so what we're actually looking for is more like clues, not answers. When answers are present, we tend to be simply presenting findings like which organisms were present and, to some extent, their apparent population density. This is really easy to do without AI. Some models might find interesting patterns, but it's hard to tell which ones or why, or how we'd train that ourselves. It's an interesting question.
I work on the genomics team so it's something I should be actively considering. The work is certainly more manual than it needs to be, so there's work to be done here for sure.
No. Drug discovery is a different beast.
It's tricky to identify the caustive agent from sequencing data. Sometimes it sticks out like a sore thumb. Eg I recently worked on samples from a patient who died, it was very easy to identify the cause because it was in the same at massive quantities (reads).
But usually, it's trawling through a hundred hits across all domains of life deciding is it consensual, contamination, pathogenic or database error. It's usually inconclusive.
Oddly enough, llm bots seem to be quiet good at this task without even fine tuning.
Well that’s fun. The seastars are ravaged by Vibrio pectenicida in the same genus that includes human pathogens like the bacteria that causes cholera and various flesh eating bacteria that can infect through undercooked seafood. The latter have even begun to eat plastic and multiply in sargassum [1] so watch those cuts when swimming in Florida!
[1] https://news.ycombinator.com/item?id=36129757
Fascinating! Wasn't this the diseases that ate part of Peter Watts? The marine biology coming for the marine biologist!
No, I believe his necrotising fasciitis was caused by an infection from a skin biopsy so likely a different bacteria.
(Flesh eating bacteria don’t literally eat the tissue, they release toxins that kill the tissue so there’s many different kinds that can cause necrotising fasciitis).
Thanks TIL
For anyone else irritated by continuous teasing style of the article, it reveals the reason a bit past midway.
> Now, in August 2025, after another year-and-a-half of work confirming and reviewing their findings, Gehman and her team have published a peer-reviewed study in the journal Nature Ecology & Evolution identifying Vibrio pectenicida, a saltwater-loving bacterium that works its way into sea star fluids, as the likely “dominant pathogen responsible for sea star wasting disease.” Gehman’s team has tracked down the killer.
There is a major carbon credit opportunity that I hope is financially engineered by the right people.
Restoring the kelp forest would sequester more than €1.5B worth of carbon every year. That’s because the kelp grows so rapidly and then is sucked down into the deep sea. Ideally the ecosystem itself would somehow receive money for its services—but short of that, some foundation on behalf of the ecosystem —and short of that, some organization that’d be prepared to use the money to reinvest in other ecosystems.
Vibrio infections are also lethal for humans.
Some are able to easily overpower our immune systems.
https://en.m.wikipedia.org/wiki/Vibriosis
Study link
https://www.nature.com/articles/s41559-025-02797-2
Couldn't they just do the initial test with 5? Maybe 10.. Why we gotta disintegrate 19 more of these fuzzy little guys? :|
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