Solution Hybrid Selection Capture for the Recovery of Functional Full-Length Eukaryotic cDNAs From Complex Environmental Samples

Eukaryotic microbial communities play key functional roles in soil biology and potentially represent a rich source of natural products including biocatalysts. Culture-independent molecular methods are powerful tools to isolate functional genes from uncultured microorganisms. However, none of the methods used in environmental genomics allow for a rapid isolation of numerous functional genes from eukaryotic microbial communities. We developed an original adaptation of the solution hybrid selection (SHS) for an efficient recovery of functional complementary DNAs (cDNAs) synthesized from soil-extracted polyadenylated mRNAs. This protocol was tested on the Glycoside Hydrolase 11 gene family encoding endo-xylanases for which we designed 35 explorative 31-mers capture probes. SHS was implemented on four soil eukaryotic cDNA pools. After two successive rounds of capture, >90% of the resulting cDNAs were GH11 sequences, of which 70% (38 among 53 sequenced genes) were full length. Between 1.5 and 25% of the cloned captured sequences were expressed in Saccharomyces cerevisiae. Sequencing of polymerase chain reaction-amplified GH11 gene fragments from the captured sequences highlighted hundreds of phylogenetically diverse sequences that were not yet described, in public databases. This protocol offers the possibility of performing exhaustive exploration of eukaryotic gene families within microbial communities thriving in any type of environment

Can arbuscular mycorrhizal fungi be used as bioindicators of land use ?

National audienceBeing abundant in nearly all soils and less diverse than other soil organisms, Arbuscular Mycorrhizal Fungi (AMF) are potential indicators of land management legacies and soil quality degradation. It has been pointed out that these are critical factors for understanding and supporting the sustainable use of soils, but can be difficult to measure directly (Jansa et al. 2014). To serve as broadly applicable bioindicators, AMF should exhibit consistent patterns in a range of soils. In the framework of the EcoFINDERS project, soil AMF assemblages were described in four European long term observatories (mainly grasslands), located in different climatic and geological zones, subjected to either low or high management intensity. AMF communities were described, in both spring and autumn, by means of high-throughput metabarcoding targeting the ITS2 region. AMF community structures were related to soil properties, land management intensity and geographic distances to address the relative importance of these factors in shaping the composition of AMF communities. As expected, our results indicate significant effects of management type (p=0.000999), soil chemical and physical properties (such as pH, soil texture, organic carbon content and available phosphorus), and among-site geographic distances on community composition (Mantel tests). Indicator species analysis (presence/absence data) retrieved some taxa (or their combinations) characteristic of specific land uses (or their combinations) in both seasons. Jansa J. et al. 2014 - Soil and geography are more important determinants of indigenous arbuscular mycorrhizal communities than management practices in Swiss agricultural soils. Molecular Ecology 23: 2118–213

Arbuscular mycorrhizal fungal community differences among European long-term observatories

Arbuscular mycorrhizal fungal (AMF) communities have been demonstrated to respond to a variety of biotic and abiotic factors, including various aspects of land management. Numerous studies have specifically addressed the impact of land use on AMF communities, but usually have been confined to one or a few sites. In this study, soil AMF assemblages were described in four different long-term observatories (LTOs) across Europe, each of which included a site-specific high-intensity and a low-intensity land use. AMF communities were characterized on the basis of 454 sequencing of the internal transcribed spacer 2 (ITS2) rDNA region. The primary goals of this study were (i) to determine the main factors that shape AMF communities in differentially managed sites in Europe and (ii) to identify individual AMF taxa or combinations of taxa suitable for use as biomarkers of land use intensification. AMF communities were distinct among LTOs, and we detected significant effects of management type and soil properties within the sites, but not across all sites. Similarly, indicator species were identified for specific LTOs and land use types but not universally for high- or low-intensity land uses. Different subsets of soil properties, including several chemical and physical variables, were found to be able to explain an important fraction of AMF community variation alone or together with other examined factors in most sites. The important factors were different from those for other microorganisms studied in the same sites, highlighting particularities of AMF biology

ORF Capture-Seq as a versatile method for targeted identification of full-length isoforms

Most human protein-coding genes are expressed as multiple isoforms, which greatly expands the functional repertoire of the encoded proteome. While at least one reliable open reading frame (ORF) model has been assigned for every coding gene, the majority of alternative isoforms remains uncharacterized due to (i) vast differences of overall levels between different isoforms expressed from common genes, and (ii) the difficulty of obtaining full-length transcript sequences. Here, we present ORF Capture-Seq (OCS), a flexible method that addresses both challenges for targeted full-length isoform sequencing applications using collections of cloned ORFs as probes. As a proof-of-concept, we show that an OCS pipeline focused on genes coding for transcription factors increases isoform detection by an order of magnitude when compared to unenriched samples. In short, OCS enables rapid discovery of isoforms from custom-selected genes and will accelerate mapping of the human transcriptome. © 2020, The Author(s)