Fungi of the genus Trichoderma are economically important due to their plant growth- and performance-promoting effects, such as improved nutrient supply, mycoparasitism of plant-pathogens and priming of plant defense. Due to their mycotrophic lifestyle, however, they might also be antagonistic to other plant-beneficial fungi, such as mycorrhiza-forming species. Trichoderma spp. release a high diversity of volatile organic compounds (VOCs), which likely play a decisive role in the inter-species communication. It has been shown that Trichoderma VOCs can inhibit growth of some plant pathogens, but their inhibition potentials during early interactions with mutualistic fungi remain unknown. Laccaria bicolor is a common ectomycorrhizal fungus which in symbiotic relationship is well known to facilitate plant performance. Here, we investigated the VOC profiles of three strains of Trichoderma species, Trichoderma harzianum, Trichoderma Hamatum , and Trichoderma velutinum , as well as L. bicolor by stir bar sorptive extraction and gas chromatography – mass spectrometry (SBSE-GC-MS). We further examined the fungal performance and the VOC emission profiles during confrontation of the Trichoderma species with L. bicolor in different co-cultivation scenarios. The VOC profiles of the three Trichoderma species were highly species-dependent. T. harzianum was the strongest VOC emitter with the most diverse compound pattern, followed by T. hamatum and T. velutinum . Co-cultivation of Trichoderma spp. and L. bicolor altered the VOC emission patterns dramatically in some scenarios. The co-cultivations also revealed contact degree-dependent inhibition of one of the fungal partners. Trichoderma growth was at least partially inhibited when sharing the same headspace with L. bicolor . In direct contact between both mycelia, however, L. bicolor growth was impaired, indicating that Trichoderma and L. bicolor apply different effectors when defending their territory. Multivariate analysis demonstrated that all examined individual fungal species in axenic cultures, as well as their co-cultivations were characterized by a distinct VOC emission pattern. The results underline the importance of VOCs in fungal interactions and reveal unexpected adjustability of the VOC emissions according to the specific biotic environments.

We present a high-quality de novo genome assembly (rheMacS) of the Chinese rhesus macaque (Macaca mulatta) using long-read sequencing and multiplatform scaffolding approaches. Compared to the current Indian rhesus macaque reference genome (rheMac8), rheMacS increases sequence contiguity 75-fold, closing 21,940 of the remaining assembly gaps (60.8 Mbp). We improve gene annotation by generating more than two million full-length transcripts from ten different tissues by long-read RNA sequencing. We sequence resolve 53,916 structural variants (96% novel) and identify 17,000 ape-specific structural variants (ASSVs) based on comparison to ape genomes. Many ASSVs map within ChIP-seq predicted enhancer regions where apes and macaque show diverged enhancer activity and gene expression. We further characterize a subset that may contribute to ape- or great-ape-specific phenotypic traits, including taillessness, brain volume expansion, improved manual dexterity, and large body size. The rheMacS genome assembly serves as an ideal reference for future biomedical and evolutionary studies.

Volatile organic compounds (VOCs) play vital roles in the interaction of fungi with plants and other organisms. A systematic study of the global fungal VOC profiles is still lacking, though it is a prerequisite for elucidating the mechanisms of VOC-mediated interactions. Here we present a versatile system enabling a high-throughput screening of fungal VOCs under controlled temperature. In a proof-of-principle experiment, we characterized the volatile metabolic fingerprints of four Trichoderma spp. over a 48 h growth period.The developed platform allows automated and fast detection of VOCs from up to 14 simultaneously growing fungal cultures in real time. The comprehensive analysis of fungal odors is achieved by employing proton transfer reaction-time of flight-MS and GC-MS. The data-mining strategy based on multivariate data analysis and machine learning allows the volatile metabolic fingerprints to be uncovered.Our data revealed dynamic, development-dependent and extremely species-specific VOC profiles from the biocontrol genus Trichoderma. The two mass spectrometric approaches were highly complementary to each other, together revealing a novel, dynamic view to the fungal VOC release.This analytical system could be used for VOC-based chemotyping of diverse small organisms, or more generally, for any in vivo and in vitro real-time headspace analysis.