First thought to be closely related to crabs, lobsters and other crustaceans, in 1881 evolutionary biologist E. Ray Lankester placed them solidly in a group more similar to spiders and scorpions. Horseshoe crabs have since been thought to be ancestors of the arachnids, but molecular sequence data have always been sparse enough to cast doubt.

University of Wisconsin-Madison evolutionary biologists Jesús Ballesteros and Prashant Sharma hope, then, that their recent study published in the journal Systematic Biology helps firmly plant ancient horseshoe crabs within the arachnid family tree.

By analyzing troves of genetic data and considering a vast number of possible ways to examine it, the scientists now have a high degree of confidence that horseshoe crabs do indeed belong within the arachnids.

“By showing that horseshoe crabs are part of the arachnid radiation, instead of a lineage closely related to but independent of arachnids, all previous hypotheses on the evolution of arachnids need to be revised,” says Ballesteros, a postdoctoral researcher in Sharma’s lab. “It’s a major shift in our understanding of arthropod evolution.”

Arthropods are often considered the most successful animals on the planet since they occupy land, water and sky and include more than a million species. This grouping includes insects, crustaceans and arachnids.

Horseshoe crabs have been challenging to classify within the arthropods because analysis of the animals’ genome has repeatedly shown them to be related to arachnids like spiders, scorpions, mites, ticks and lesser-known creatures such as vinegaroons. Yet, “scientists assumed it was an error, that there was a problem with the data,” says Ballesteros.

Moreover, horseshoe crabs possess a mix of physical characteristics observed among a variety of arthropods. They are hard-shelled like crabs but are the only marine animals known to breathe with book gills, which resemble the book lungs spiders and scorpions use to survive on land.

Only four species of horseshoe crabs are alive today, but the group first appeared in the fossil record about 450 million years ago, together with mysterious, extinct lineages like sea scorpions. These living fossils have survived major mass extinction events and today their blood is used by the biomedical industry to test for bacterial contamination.

Age is just one of the problems inherent in tracing their evolution, say Ballesteros and Sharma, since searching back through time to find a common ancestor is not easy to accomplish. And evidence from the fossil record and genetics indicates evolution happened quickly among these groups of animals, convoluting their relationships to one another.

“One of the most challenging aspects of building the tree of life is differentiating old radiations, these ancient bursts of speciation,” says Sharma, a professor of integrative biology. “It is difficult to resolve without large amounts of genetic data.”

Even then, genetic comparisons become tricky when looking at the histories of genes that can either unite or separate species. Some genetic changes can be misleading, suggesting relationships where none exist or dismissing connections that do. This is owed to phenomena such as incomplete lineage sorting or lateral gene transfer, by which assortments of genes aren’t cleanly made across the evolution of species.

Ballesteros tested the complicated relationships between the trickiest genes by comparing the complete genomes of three out of the four living horseshoe crab species against the genome sequences of 50 other arthropod species, including water fleas, centipedes and harvestmen.

Using a complex set of matrices, taking care not to introduce biases in his analysis, he painstakingly teased the data apart. Still, no matter which way Ballesteros conducted his analysis, he found horseshoe crabs nested within the arachnid family tree.

He says his approach serves as a cautionary tale to other evolutionary biologists who may be inclined to cherry-pick the data that seem most reliable, or to toss out data that don’t seem to fit. Researchers could, for example, “force” their data to place horseshoe crabs among crustaceans, says Sharma, but it wouldn’t be accurate. The research team tried this and found hundreds of genes supporting incorrect trees.

Ballesteros encourages others to subject their evolutionary data to this kind of rigorous methodology, because “evolution is complicated.”

Why horseshoe crabs are water dwellers while other arachnids colonized land remains an open question. These animals belong to a group called Chelicerata, which also includes sea spiders. Sea spiders are marine arthropods like horseshoe crabs, but they are not arachnids.

“What the study concludes is that the conquest of the land by arachnids is more complex than a single tradition event,” says Ballesteros.

It’s possible the common ancestor of arachnids evolved in water and only groups like spiders and scorpions made it to land. Or, a common ancestor may have evolved on land and then horseshoe crabs recolonized the sea.

“The big question we are after is the history of terrestrialization,” says Sharma.

For Ballesteros, who is now studying the evolution of blindness in spiders living deep within caves in Israel, his motivations get to the heart of human nature itself.

“I get to look with childish curiosity and ask: ‘How did all this diversity come to be?'” he says. “It’s incredible what exists, and I never thought I would have the privilege to be able to do this.”

The study was funded by the M. Guyer postdoctoral fellowship and supported by National Science Foundation grant IOS-1552610.

“People always laugh when I say that,” she adds. “But it’s true.”

Our rich new understanding of microbial communities and their influence on human health or crop productivity has led to the dream of changing these communities to produce benefits. In pursuit of that dream, millions of Americans now take probiotics, beneficial microbes they hope will improve their gut.

But the immense complexity and resiliency of these microbiomes leave researchers unsure how to produce predictable and long-lasting changes for the better.

New research by Handelsman and her collaborators addresses that complexity head-on. The team developed a community they named THOR, three species of bacteria isolated from soybean roots and grown together. The complex community of microbes developed new behaviors together that couldn’t be predicted from the individual members alone — they grew tougher structures known as biofilms, changed how they moved across their environment, and controlled the release of a novel antibiotic.

Each of the three members of THOR has a sequenced genome, and an array of tools are available to easily study the bacteria in isolation and together, which opens up opportunities to start unraveling the complexity of microbial communities like THOR and others. A better understanding of these microbiomes could help scientists figure out how to improve them.

The work is published March 5 in the journal mBio. The work was led by Handelsman lab postdoctoral researcher Gabriel Lozano with collaborators at the UW-Madison Department of Plant Pathology, Yale University and other institutions.

The thunderous name THOR stems from the members of the community: The Hitchhikers Of the Rhizosphere. Years ago, Handelsman’s lab noticed that several bacteria came along for the ride when members of common Bacillus bacteria were isolated from the microbiome of soybean roots, known as the rhizosphere. These hitchhikers only showed themselves when Bacillus bacteria were grown in the cold for several weeks.

Those tight associations between different species suggest they could serve as a model community to test how complex traits emerge when multiple species share the same space. The researchers settled on species from the Pseudomonas and Flavobacterium groups of bacteria to grow and study alongside Bacillus.

Combined, the members of THOR boasted some 15,000 genes and were capable of producing thousands of small molecules, creating “layers of complexity” over time and across space, says Handelsman.

When grown alone, the Pseudomonas member of THOR produces a biofilm, a hearty structure that protects the bacteria from its environment. Biofilms gum up implants used in medicine and make bacteria resistant to antibiotics. When all three members of THOR were grown together, the community produced two times as much biofilm and the biofilm lasted longer than when Pseudomonas was alone.

“Even when their populations are small, these other species are sparking larger biofilms,” says Handelsman.

Other complex traits emerged in THOR as well. The Bacillus member reduced the production of antibiotics made by Pseudomonas, protecting Flavobacterium from their effects. And the other members of THOR induced Bacillus colonies to grow out like the branches of a tree, spreading over and around the other bacteria in complex patterns.

Many efforts to manipulate microbiomes are focused on improving human health, and model communities like THOR could help scientists understand how complex microbial relationships can be altered to benefit us.

But THOR’s information about the microbiome of plant roots, the rhizosphere, is just as vital. The rhizosphere helps glue soil together, preventing erosion. And soil locks up three times more carbon than floats in the atmosphere, making it an important element in addressing climate change. Knowing how individual microbes come together to produce the rich, complex behavior of the soil microbiome may be a key to maximizing the benefit we derive from these unseen communities.

“It’s one of the most critical relationships we have,” says Handelsman.

2. Switzerland: 76.1

3. France: 76.0

4. Singapore: 76.0

5. Kuwait: 75.3

6. South Korea: 75.1

7. Spain: 75.1

8. Italy: 74.8

9. Puerto Rico: 74.6

10. Peru: 74.3

2. Marshall Islands: 51.0

3. Afghanistan: 51.6

4. Vanuatu: 52.2

5. Solomon Islands: 53.4

6. Central African Republic: 53.6

7. Lesotho: 53.6

8. Kiribati: 54.2

9. Guinea-Bissau: 54.5

10. Federated States of Micronesia: 55.0

2. Singapore: 108.3

3. South Korea: 110.1

4. Japan: 110.6

5. Italy: 115.2

6. Kuwait: 118.2

7. Spain: 119.2

8. France: 119.3

9. Israel: 120.2

10. Sweden: 122.1

2. Marshall Islands: 396.6

3. Vanuatu: 392.1

4. Afghanistan: 380.2

5. Solomon Islands: 368.0

6. Central African Republic: 364.6

7. Lesotho: 360.5

8. Kiribati: 347.5

9. Guinea-Bissau: 343.4

10. Eritrea: 325.7

Up until the last decade or so, scientists thought the Moon was arid, with any water existing mainly as pockets of ice in permanently shaded craters near the poles. More recently, scientists have identified surface water in sparse populations of molecules bound to the lunar soil, or regolith. The amount and locations vary based on the time of day. This water is more common at higher latitudes and tends to hop around as the surface heats up.

“This is an important new result about lunar water, a hot topic as our nation’s space program returns to a focus on lunar exploration,” said SwRI’s Dr. Kurt Retherford, the principal investigator of the LRO LAMP instrument. “We recently converted the LAMP’s light collection mode to measure reflected signals on the lunar dayside with more precision, allowing us to track more accurately where the water is and how much is present.”

Water molecules remain tightly bound to the regolith until surface temperatures peak near lunar noon. Then, molecules thermally desorb and can bounce to a nearby location that is cold enough for the molecule to stick or populate the Moon’s extremely tenuous atmosphere, or “exosphere,” until temperatures drop and the molecules return to the surface. SwRI’s Dr. Michael Poston, now a research scientist on the LAMP team, had previously conducted extensive experiments with water and lunar samples collected by the Apollo missions. This research revealed the amount of energy needed to remove water molecules from lunar materials, helping scientists understand how water is bound to surface materials.

“Lunar hydration is tricky to measure from orbit, due to the complex way that light reflects off of the lunar surface,” Poston said. “Previous research reported quantities of hopping water molecules that were too large to explain with known physical processes. I’m excited about these latest results because the amount of water interpreted here is consistent with what lab measurements indicate is possible. More work is needed to fully account for the complexities of the lunar surface, but the present results show that work is definitely worth doing!”

Scientists have hypothesized that hydrogen ions in the solar wind may be the source of most of the Moon’s surface water. With that in mind, when the Moon passes behind the Earth and is shielded from the solar wind, the “water spigot” should essentially turn off. However, the water observed by LAMP does not decrease when the Moon is shielded by the Earth and the region influenced by its magnetic field, suggesting water builds up over time, rather than “raining” down directly from the solar wind.

“These results aid in understanding the lunar water cycle and will ultimately help us learn about accessibility of water that can be used by humans in future missions to the Moon,” said Amanda Hendrix, a senior scientist at the Planetary Science Institute and lead author of the paper. “A source of water on the Moon could help make future crewed missions more sustainable and affordable. Lunar water can potentially be used by humans to make fuel or to use for radiation shielding or thermal management; if these materials do not need to be launched from Earth, that makes these future missions more affordable.”

The funding for this research came from NASA Goddard Space Flight Center’s LRO program office, including an LRO LAMP subcontract between SwRI and PSI, and the team received additional support from a NASA Solar System Exploration Research Virtual Institute (SSERVI) cooperative agreement.

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The discovery of the type II clustered regularly interspaced short palindromic repeats (CRISPR)-associated caspase 9 (Cas9) system has been a milestone in the field of targeted genome editing. Initially derived from the bacterium Streptococcus pyogenes, the RNA/protein-complex now is an established tool for targeted genome-editing in eukaryotes.

Whilst its scissor-like properties have yielded a broad range of applications, scientists from the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK Gatersleben) are now using CRISPR/Cas9 in a new cytogenetic method for shining a light into eukaryote genomes — RNA-guided endonuclease — in situ labelling (RGEN-ISL).

For the last 30 years, fluorescence in situ hybridization (FISH) has been the established and commonly used method for visualising in-situ DNA-sequences at chromosomal level. However, this method requires denaturation of the investigated DNA, thus often damaging the structure of the sample. By basing the RGEN-ISL method on CRISPR-Cas9, IPK researchers managed to bypass the denaturation-step of FISH whilst simultaneously integrating the desired fluorescent labelling properties of the conventional FISH-method. As the new cytogenetic tool preserves the structure of the sample, it opens up the option of investigating the spatio-temporal structure of the genome.

Further experimentation showed that RGEN-ISL outperforms conventional method combinations, such as FISH and immunohistochemistry, requiring less preparation and being comparatively quicker and cheaper. Additionally, the new method functions over a broad temperature-range of 4°C to 37°C and can also be combined with additional protein-detection and imaging methods. A further merit is that RGEN-ISL allows for real-time visualisation of the CRISPR/Cas9-mediated DNA-labelling, therefore revealing the kinetics of the reaction.

So far, the researchers have tested RGEN-ISL in plant samples, but also in human chromosomes, illustrating that their new method can likely be applied within all organisms. Currently, the use of method is limited to repetitive DNA-sequences, as often found in plant genomes. However, Dr Takayoshi Ishii, now working at Tottori University (Japan), who conceived the initial idea behind RGEN-ISL, assumes that this method could be adapted to visualise even single-copy sequences in the future.

The project around the new method, which was developed under research group leader Dr Andreas Houben, was made possible through a grant to CSIRO (Australia) by the Bill & Melinda Gates Foundation (USA) as well as thanks too additional funding by the German Research Foundation — DFG (Germany).

Given its properties and broad applicability, RGEN-ISL is a promising new cytogenetic tool for furthering the understanding of the spatial organisation of the genome and the connection between chromatin structure and function, as well as for advancing the knowledge within the wide field of chromosome biology.

The approach is similar to looking at the activities and interactions of all the individuals in a community and then selecting out the most meaningful interactions, some which may be very rare. The researchers are looking for the biological equivalent of two individuals who may be the only two in the entire community that participate in an important interaction.

Not only does this help researchers identify how proteins perform biological functions or carry out biological processes, the algorithm can be applied to previously generated biological data and potentially other areas of science to glean new information.

“It’s a form of big data analysis that we are applying to proteomics data to identify and understand protein interaction networks,” says Michael Washburn, PhD, director of the Stowers Proteomics Center. “It’s complementary to a lot of techniques already in use so it can be used to ask and answer new questions.”

Protein data sets can be challenging to examine for meaningful information because they are so large. “You have thousands of proteins to look at,” says Mihaela Sardiu, PhD, a senior research specialist at Stowers. Understanding how a wide variety of proteins come together to do something, like repair DNA, is a difficult problem. “We wanted to simplify the problem.”

That meant instead of taking an overall view of everything, they hunted for less common events. Researchers did this by looking for bait (proteins already known to be involved in processes of interest) and prey (proteins that could interact with bait proteins) to see how they interacted in human DNA repair and yeast chromatin remodeling complexes. Through TopS, data is analyzed in a parallel fashion, meaning that data from several biologically-related baits are considered at the same time. A key attribute of TopS is the ability to evaluate the preference of a prey protein for a bait relative to other baits. “Instead of calculating a score by concentrating only information of a single bait, we now aggregate information from the entire data set,” explains Sardiu.

Washburn and Sardiu believe that TopS can be applied to a wide range of data sets beyond proteomics, in both basic research and beyond. Sardiu sees potential in using it for healthcare data, where physicians might be able to compare a patient’s health to others, like being able to tell if a patient’s disease is “really advanced compared to others or not,” she says.

The team has also published these findings on Github, a computer code repository, because they want to offer other researchers the opportunity to test the algorithm and see how they can apply it to their own projects.

“We’re excited to see how far this can go. It’s a potentially high impact tool and we want to see what other creative and innovative people can come up with,” says Washburn. “We think this is a really valuable potential tool for a lot of people out there who struggle with the challenge of sorting through very large-scale data.”

Other contributors from the Stowers Institute included Joshua M. Gilmore, PhD, Brad D. Groppe, Arnob Dutta, PhD, and Laurence Florens, PhD. Dutta is currently an Assistant Professor at the University of Rhode Island, Groppe is now working at Thermo Fisher Scientific, and Gilmore is a scientist with Boehringer Ingelheim.

This research was funded by the Stowers Institute and a grant from the National Institute of General Medical Sciences of the National Institutes of Health under award number R01GM112639. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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