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1.
ISME J ; 18(1)2024 Jan 08.
Article in English | MEDLINE | ID: mdl-38519103

ABSTRACT

Deadwood provides habitat for fungi and serves diverse ecological functions in forests. We already have profound knowledge of fungal assembly processes, physiological and enzymatic activities, and resulting physico-chemical changes during deadwood decay. However, in situ detection and identification methods, fungal origins, and a mechanistic understanding of the main lignocellulolytic enzymes are lacking. This study used metaproteomics to detect the main extracellular lignocellulolytic enzymes in 12 tree species in a temperate forest that have decomposed for 8 ½ years. Mainly white-rot (and few brown-rot) Basidiomycota were identified as the main wood decomposers, with Armillaria as the dominant genus; additionally, several soft-rot xylariaceous Ascomycota were identified. The key enzymes involved in lignocellulolysis included manganese peroxidase, peroxide-producing alcohol oxidases, laccase, diverse glycoside hydrolases (cellulase, glucosidase, xylanase), esterases, and lytic polysaccharide monooxygenases. The fungal community and enzyme composition differed among the 12 tree species. Ascomycota species were more prevalent in angiosperm logs than in gymnosperm logs. Regarding lignocellulolysis as a function, the extracellular enzyme toolbox acted simultaneously and was interrelated (e.g. peroxidases and peroxide-producing enzymes were strongly correlated), highly functionally redundant, and present in all logs. In summary, our in situ study provides comprehensive and detailed insight into the enzymatic machinery of wood-inhabiting fungi in temperate tree species. These findings will allow us to relate changes in environmental factors to lignocellulolysis as an ecosystem function in the future.


Subject(s)
Ascomycota , Basidiomycota , Wood/microbiology , Ecosystem , Trees , Basidiomycota/physiology , Peroxides/metabolism , Fungi
2.
Sci Rep ; 12(1): 13187, 2022 08 01.
Article in English | MEDLINE | ID: mdl-35915148

ABSTRACT

The interactions of microalgae and their associated microbiomes have come to the fore of applied phycological research in recent years. However, the functional mechanisms of microalgal interactions remain largely unknown. Here, we examine functional protein patterns of the microalgae Scenedesmus vacuolatus and its associated bacterial community during algal infection by the endoparasite Amoeboaphelidium protococcarum. We performed metaproteomics analyses of non-infected (NI) and aphelid-infected (AI) S. vacuolatus cultures to investigate underlying functional and physiological changes under infectious conditions. We observed an increase in bacterial protein abundance as well as a severe shift of bacterial functional patterns throughout aphelid-infection in comparison to NI treatment. Most of the bacterial proteins (about 55%) upregulated in AI were linked to metabolism and transport of amino acids, lipids, coenzymes, nucleotides and carbohydrates and to energy production. Several proteins associated with pathogenic bacterial-plant interactions showed higher protein abundance levels in AI treatment. These functional shifts indicate that associated bacteria involved in commensalistic or mutualistic interactions in NI switch to opportunistic lifestyles and facilitate pathogenic or saprotrophic traits in AI treatment. In summary, the native bacterial microbiome adapted its metabolism to algal host die off and is able to metabolize nutrients from injured cells or decompose dead cellular material.


Subject(s)
Microalgae , Microbiota , Scenedesmus , Bacteria , Biomass , Eukaryota , Microalgae/metabolism , Scenedesmus/metabolism
3.
Data Brief ; 29: 105285, 2020 Apr.
Article in English | MEDLINE | ID: mdl-32123712

ABSTRACT

Wood-decomposition in terrestrial ecosystems is a very important process with huge ecologic consequences. This decomposition process is a combination of biological respiration, leaching and fragmentation, mainly triggered by organismic activities. In order to gain a deeper insight into these microbial communities and their role in deadwood decay, we used metaproteomics. Metaproteomics is an important tool and offers the ability to characterize the protein complement of environmental microbiota at a given point in time. In this dataset, we provide data of an exemplary beech wood log and applied different extraction methods to provide the proteome profile of beech dead wood and their corresponding fungal-bacterial community.

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