麻豆淫院

When a tree dies, it forms the foundation for new life: In a slow, invisible process, leaves, wood and roots are gradually decomposed鈥攏ot by wind or weather, but by millions and millions of tiny organisms.

Fungi thread their way through the dead wood and degrade cell walls. Tiny animals such as insect larvae and mites gnaw through the tissue. And something very important happens in the process: the carbon stored in the plant is released, ultimately placing it at the disposal of plants again for the purpose of photosynthesis.

But what exactly is responsible for performing this task in the global carbon cycle? And which molecular tools do the organisms use for it?

To answer these questions, the researchers have developed a new bioinformatics-based method, which they present in .

18,000 species in the spotlight

The method, called fDOG (Feature architecture-aware directed ortholog search), makes it possible to search in the genetic material of various organisms for genes that have evolved from the same precursor gene. It is assumed that these genes, known as "orthologs," encode proteins with similar functions.

For the current study, the scientists searched for the genes of plant cell wall-degrading enzymes (PCDs). Unlike previous methods, fDOG not only searches through masses of genomic information but also analyzes the architecture of the proteins found鈥攊.e. their structural composition, which reveals a lot about an enzyme's function.

"We start with a gene from one species, referred to as the seed, and then trawl through tens of thousands of species in the search for orthologous genes," explains Ingo Ebersberger, Professor of Applied Bioinformatics at Goethe University Frankfurt.

"In the process, we constantly monitor whether the genes we find perhaps differ from the seed in terms of function and structure鈥攆or example, through the loss or gain of individual areas relevant for function."

The research team used this method to search for more than 200 potential PCD candidates in over 18,000 species from all three domains of life鈥攂acteria, archaea and eukaryotes (plants, animals, fungi). The result is a detailed global map鈥攚ith unprecedented accuracy鈥攐f enzymes capable of degrading plant cell walls.

Surprising discoveries among fungi and animals

The researchers devised special visualization methods to analyze the vast amounts of data and detect patterns. This revealed characteristic changes in the enzyme repertoire of the fungi under study, indicating a change in lifestyle of certain fungal species: from a decomposing lifestyle鈥攊.e. the degradation of dead plants鈥攖o a parasitic lifestyle in which they infest living animals.

Such evolutionary transitions are mirrored in characteristic patterns of enzyme loss.

A special surprise in the animal kingdom was the discovery that some arthropods possess an unexpectedly wide range of plant cell wall-degrading enzymes.

These enzymes presumably originated from fungi and bacteria and entered the genome of invertebrates via direct gene transfer between different organisms鈥攊.e. horizontal gene transfer. This suggests that they might be able to degrade plant material independently and are not reliant on the bacteria in their intestines, as was previously assumed.

In another case, however, it emerged that the potential PCD genes in the analyzed sequence could be ascribed to microbial contamination鈥攁n important sign that such data need to be checked very carefully.

New insights into the global carbon cycle

The study shows how fDOG can be used to systematically map biological capabilities across the entire tree of life鈥攆rom broad-scale overviews to detailed investigations of individual species. With this method, it is possible both to track evolutionary trajectories and to identify players previously overlooked in the global carbon cycle.

Since soils contain large amounts of dead plant material and therefore constitute the largest terrestrial carbon sink, the decomposition of plant material is an important driver of the global carbon cycle.

"Our method gives us a fresh view of how metabolic capacities are distributed across the tree of life," says Ebersberger. "We can now conduct multi-scale analyses and in the process detect both recent evolutionary changes and large patterns."