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opencc-zeroOct 2023View details →

Divergent molecular networks program functionally distinct CD8+ skin-resident memory T cells

Skin-resident CD8+ T cells comprise distinct IFN-γ- (TRM1) and IL-17-producing (TRM17) subsets that differentially contribute to immune responses. However, whether these populations employ common mechanisms to establish tissue residence is unknown. Here, we show that TRM1 and TRM17 cells navigate divergent trajectories to acquire tissue residency in skin. While TRM1 cells depend on a T-bet-Hobit-IL-15 axis, TRM17 cells develop independently of these factors. Instead, c-Maf commands a tissue-resident program in TRM17 cells parallel to that induced by Hobit in TRM1 cells, with an ICOS-c-Maf-IL-7 axis pivotal to TRM17 cell commitment. Accordingly, targeting this pathway enables ablation of skin TRM17 cells without compromising their TRM1 counterparts. Thus, skin-resident T cells rely on distinct molecular circuitries, which can be exploited to strategically modulate local immunity.

opencc-by-4.0Jul 2021View details →

Multi-taxa environmental DNA inventories reveal distinct taxonomic and functional diversity in urban tropical forest fragments

Urban expansion and associated habitat transformation drives shifts in biodiversity, with declines in taxonomic and functional diversity. Forests fragments within urban landscapes offer a number of ecosystem services, and help to maintain biodiversity and ecosystem functions. Here, we focus on a tropical forest environment, and on the soil biota. Using eDNA metabarcoding, we compare forest fragments within the city of Cayenne, French Guiana, with a neighbouring continuous undisturbed forest. We wished to determine if urban forest fragments conserve high levels of alpha and beta diversity as well as similar functional composition for plants, soil animals, fungi and bacteria. We found that alpha diversity is similar across habitats for plants and fungi, lower in urban forests for metazoans and higher for bacteria. We also found that urban forests communities differ from undisturbed forests in their taxonomic composition, with urban forests exhibiting greater turnover between fragments potentially caused by ecological drift and limited dispersal. However, their functional composition exhibited limited differences, with an enrichment of palms, arbuscular mycorrhizal fungi and bacteria and a depletion of climber plants and termites. Thus, although urban forest fragments do shelter soil biodiversity that differs from native forests, the losses of soil functions may be relatively limited. This study demonstrates the strong potential of a multi-taxa eDNA approach for rapid inventories across taxonomic kingdoms, in particular for cryptic soil diversity. It also demonstrates the key role of urban forest fragments in conserving biodiversity and ecosystem function, and points to a need for more systematic monitoring of these areas in urban management plans. For each of the 16 samples per plot, 15 g of soil was used for eDNA analyses. Extracellular DNA was extracted as described previously (Zinger et al., 2016; 2019), where each soil sample is added to 15ml of saturated phosphate buffer (Na2HPO4; 0.12m; pH ≈8) in 50ml Falcon tubes. This is placed in an agitator for 15 minutes, before a 2ml aliquot of the soil/phosphate buffer mixture is pipetted into an Eppendorf tube and centrifuged for five minutes at 13000 rcf. 500μL of the resulting supernatant is then recovered and used for the next extraction steps that are carried out with a commercial kit for soil DNA (NucleoSpin® Soil; Macherey-Nagel, Düren, Germany), skipping the lysis step and following manufacturer’s instructions. The DNA extract was recovered in 100 μL and diluted 10 times before being used as PCR template.  For each plot one DNA extraction negative control was performed adding up 17 extractions per plot. PCR amplifications were then conducted for four DNA molecular markers, with primers targeting either Viridiplantae (subsequently referred to as plants), Eukaryotes, Fungi or Bacteria (Table 1). For each marker, PCR amplification of samples occurred across 12 plates. Each PCR reaction was performed in a total volume of 20 μl and comprised 10 μl of AmpliTaq Gold Master Mix (Life Technologies, Carlsbad, CA, USA), 5.84 μl of Nuclease-Free Ambion Water (Thermo Fisher Scientific, Massachusetts, USA), 0.25 μM of each primer, 3.2 μg of BSA (Roche Diagnostic, Basel, Switzerland), and 2 μl of DNA template that was before 10-fold diluted to reduce the amounts of PCR inhibitors. Thermocycling conditions for each primer pair are indicated in Table 1.  A negative extraction control per site and a negative PCR control per PCR plate were amplified and sequenced in parallel with the regular samples. Positive controls were also included and consisted of mock communities of plants and fungi DNA (no mock communities were built for bacteria or eukaryotes here), which were used to guide choices in our data curation process. Two PCR replicates were performed for each sample and control. Amplification was conducted using a double indexing system strategy (Binladen et al. 2007) using a system of 32 by 36 octamers with at least five differences between them located at the 5’ end of each primer (Coissac 2012). In doing so, each PCR product had a unique combination of tags for both forward and reverse primers, allowing for the retrieval of sequence data for each sample. Ten wells per PCR plate were left empty to act as sequencing controls (non-used tag combinations) for downstream data curation (see below). PCR products were pooled and sequencing libraries were constructed using the Illumina TruSeq NanoPCRFree kit following the supplier’s instructions (Illumina Inc., San Diego, California, USA), except that the ligation product was not PCR amplified to limit tag-jump biases (Taberlet et al 2018). The libraries were then sequenced on different Illumina platforms (San Diego, CA, USA) depending on the marker considered (Table S1), using the paired-end technology. Bioinformatic analyses were performed on the GenoToul bioinformatics platform (Toulouse, France), with the OBITOOLS package (Boyer et al. 2016). First, ‘illuminapairedend’ was used to assemble paired-end reads. This algorithm is based on an exact alignment algorithm that considers the quality scores at all positions during the assembly process. Subsequently, we used the ‘ngsfilter’ command to identify and remove the primers and tags on each read, and assign reads to their respective samples. This program was used with its default parameters tolerating two mismatches for each of the two primers and no mismatch for the tags. Following this, sequencing reads were dereplicated using the ‘obiuniq’ command. Sequences of low quality (containing Ns or with paired-end alignment scores below 50) were excluded using the ‘obigrep’ command. The same command was used to exclude sequences represented by only one read (singletons) as they are more likely to be molecular artefacts (Taberlet et al. 2018). Sequences outside of the preset range were also discarded (Table 1). To remove PCR/sequencing errors as well as intraspecific variability, we built OTUs (Operational Taxonomic Units) using the ‘sumaclust’ clustering algorithm (Mercier et al. 2013), which considers the most abundant sequence of each cluster as the cluster representative.  OTUs were set at a sequence similarity threshold of 97% for eukaryotes, fungi and bacteria following the standards in microbial ecology, but this was lowered to 95% for plants since the eDNA target region is shorter (typically around 50 base pairs), where one mismatch inherently results in a lower percentage of similarity. To assign a taxon to plant and fungal OTUs, we built two reference sequence databases, one global, using the ecoPCR programme (Ficetola et al. 2010) and the plant / fungi specific markers on the European Molecular Biology Laboratory (EMBL; release 141), a second local, generated from specimens of fungi (Jaouen et al. 2019) and plants (see Zinger et al. 2019) collected in French Guiana. OTUs were then assigned a taxonomy, using OBITOOL’s ecotag programme (Boyer et al. 2016), which performs a global alignment of each OTU sequence (the query) against each reference. The reference taxon assigned to each OTU corresponds to the Last Common Ancestor of all the best-match sequences for the query. For taxonomic assignment of bacteria and eukaryote OTUs, the SILVA taxonomic database was used (version 1.3; Quast et al., 2012). Classification was performed by a local nucleotide BLAST search against the non-redundant version of the SILVA SSU Ref dataset (release 132; http://www.arb-silva.de) using blastn (version 2.2.30+; http://blast.ncbi.nlm.nih.gov/Blast.cgi) with standard settings (Camacho et al., 2009).  Eukaryote derived metazoan OTUs were then further assigned a taxonomy for Phyla identified at the Arthropoda, Annelida and Nematoda level using reference sequence databases built as above for these groups using the ecoPCR programme on EMBL release 141. Datasets were subsequently filtered to remove contaminants as well as artefacts such as PCR chimeras and remaining sequencing errors, following Zinger et al. (2019) and using routines now implemented in the metabaR R package (Zinger et al 2020b), in R version 3.6.1 (R Development Core Team, 2013). The filtering process consisted of four steps: (i) a negative control-based filtering. OTUs whose maximum abundance was found in extraction/PCR negative controls were removed from the dataset, as they were likely to be reagent/aerosol contaminants, better amplified in the absence of competing DNA fragments as it is the case in biological samples. (ii) a reference-based filtering. OTUs which are too dissimilar from sequences available in reference databases are potential chimeras generated during sequencing and amplification. In this study, we chose to set similarity thresholds at 95% for plants, 80% for bacteria and eukaryotes and due to the marker being more polymorphic, 65% for fungi. For plants and fungi, the remaining assignment was then verified with the local database, to confirm if assigned taxa also occurred in the local dataset, with preference given to local assignment. In addition, we removed all taxa that are not targeted by the primer used. (iii) an abundance-based filtering. This procedure targets incorrect assignment of a few numbers of sequences corresponding to true OTUs occurring to the wrong sample, a phenomenon called “tag-switching” (Esling et al. 2015), “tag jumps” (Schnell et al. 2015) or “cross-talk” (Edgar 2018). It consists in setting OTUs abundances to 0 in samples where their abundance represents < 0.03% of the total OTU abundance in the entire dataset. (iv) Finally, we conducted a PCR-based filtering by considering any PCR reaction that yielded less than 100 reads for plants, 1000 reads for fungi, bacteria and eukaryotes as non-functional, and removed them from the dataset. Data provided consists of 4 x OTU tables for each of the markers used to target different components of the soil biota, with rows representing each OTU, and columns the features of the OTU within the dataset, namely their id code, the number of read counts in the analysed dataset, their similarity score against the taxonomic dataset used to identify them, and when possible, a functional group assignment used in the manuscript. Details of these can be found above and in the manuscript and supplementary information. For each of the four datasets, we also provide a .rds file, corresponding to the processed dataset used in manuscript preparation. This is in the format of a metabaR list which includes PCR, Sample, Read count and the seperately provided OTU datasets. To facilitate interpretation, please refer to Zinger, L., Lionnet, C., Benoiston, A.S., Donald, J., Mercier, C. and Boyer, F., 2021. metabaR: an R package for the evaluation and improvement of DNA metabarcoding data quality. Methods in Ecology and Evolution, 12(4), pp.586-592. For the fungal (ITS) data, we also provide :  - the R1/R2 raw fastq files of the samples used in the paper + experimental controls - a tsv file containing the tag combinations corresponding to the samples/PCR replicates, to enable demultiplexing of data. - a csv file containing the description of each sample.

opencc-by-4.0May 2024View details →

Data from: Mouse α-synuclein fibrils are structurally and functionally distinct from human fibrils associated with Lewy body diseases

Tabular raw data corresponding to figure sets used in the study.  Fig. 1 Mouse α-syn fibrils are structurally similar to human E46K-mutated and MSA-amplified α-syn fibrils Chemical structure and binding curves of ThT (J), Nile Red (K), and FSB (L) to mouse and human sonicated α-syn fibrils (average radii: 16.68±1.44 nm and 15.14±4.02 nm, respectively). Data points indicate means from three independent experiments and error bars are S.E.M.  ****p<0.0001 and ***p<0.01 from 2-tailed t-tests. Fig. 2 Distinct β-fold stacking arrangements in mouse α-syn fibrils contribute to low tensile strength and resilience (C) Representation of proposed model of fibril fragmentation for tensile strength estimation used to simulate the MMGBSA energy of α-syn fibrils rupture and group analysis of MMGBSA energy required to disrupt a stack of six rungs. Error bars represent S.D. from 100 independent simulations. (D) Group comparison of fibril breakage under sonication conditions shown as the percent of size population of 10-100 nm (e.g., short fibrils) at 0, 2, and 30 minutes, measured by DLS. Error bars indicate S.E.M of three independent experiments with 30 acquisition measurements corresponding to each experiment. (E) Filter-trap slot-blot analysis of sonicated fibrils (i.e., PFFs) exposed to different concentrations of guanidinium chloride (GuHCl), and then remaining fibrils detected with the fibril-selective antibody MJFR14-6-4-2. Error bars indicate S.E.M from three independent experiments. (F) DLS analysis of PFFs after incubation with GuHCL. Error bars indicate S.E.M of three independent experiments with 10 acquisition measurements for each biological sample. Curves in (E) and (F) show asymmetric sigmoidal models with a goodness of fit >0.96, and  **p<0.01, **p<0.001, ****p < 0.0001 from unpaired 2-tailed t-tests. Fig. 3 Mouse α-syn fibrils fail to elicit robust cytokine and lysosome damage in macrophages (B) Internalized Alexa-647-PFFs (%area) inside cells and (C) % of LAMP1-positive vesicles positive for PFFs. Each data point represents the means of cells analyzed from at least eight images from three independent experiments. (D) ELISA analysis of the extracellular IL-6 and (E) CCL5 from MDM cultures treated with PFFs (1 μg/mL) for 3 and 24 hours. Each data point represents the mean from two technical replicates from four independent experiments. (F) % of Gal3-positive vesicles calculated per mm² of cell surface area in PFF-treated MDM cultures after 24 hours of incubation and (G) % of Gal3-positive vesicles also positive for DQ-PFFs after 48 hours of PFF incubation. Data points show the mean values from cells imaged across three independent experiments with at least eight images analyzed per group. (H) Representative images of Gal3 immunostaining after 24-hours treatment with Alexa-647- or DQ- labeled PFFs. Orthogonal views of sequential z-stacks are shown. Side left image = x,y plane, side right image = y,z plane; top image = x,z plane. Scale bar is 5 um. Error bars represent S.E.M and  ***p<0.001, *p<0.05 and ns for not significant from unpaired 2-tailed t-tests (panels B, C, F, G) or from Tukey’s post-hoc test after ANOVA (panels D,E). Fig. 4. Mouse and human α-syn fibril uptake in neurons is similar and clathrin-dependent (A) Time-dependent dynamics of pHrodo-labeled mouse or human PFF (1 µg/mL) internalization over 24 hours into human-PAC-wt-SNCA+/+/Snca-/- hippocampal primary neuronal cultures at DIV7, with normalized pHrodo-channel intensity to DAPI counts at the indicated time point. Each dot represents mean values from four images each from three independent neuronal cultures. (D)  Alexa-568 intensity in dopaminergic neurons and (E) intensity exclusively in the perinuclear area 8 hours post PFF incubation. Each dot represents the mean value of one image with at least 20 images collected from three independent experiments. (F) Calculated uptake of pHrodo-labeled α-syn PFFs at 24 hours in the presence of endocytosis inhibitors with signals normalized to vehicle only controls. Each dot in panel F represents the mean value of four images evaluated per condition from three independent experiments. Error bars for each group analysis represent S.E.M., and ns is not-significant from 2-tailed t tests. Fig. 5. Mouse α-syn fibrils pathology propagation is more efficient than human α-syn in primary neurons.  (A) Levels of pS129-α-syn signal assessed relative to the number of neurons in the corresponding cultures cultured from human-PAC-wt-SNCA+/+/Snca-/- hippocampal primary neuron culture treated with 1 µg/mL of α-syn PFFs for 14 days, or equivalent amounts of monomer as indicated, and stained against pS129-α-syn, Tau and NeuN. (B) To ensure the specificity of pS129-α-syn signals, control groups show the lack of signal in neurons cultured from Snca-/- mice following 14 days of incubation with α-syn PFFs or monomer as shown. (D) Abundance of distinct pS129-α-syn signals in cell bodies or neuritic morphology in neuronal cells treated with 1 µg/mL of mouse or human α-syn PFFs. (E) Proportion of pS129-α-syn occupancy in cell body and neurites in primary hippocampal cultures incubated with mouse or human α-syn PFFs for 14 days. (F) ELISA quantification of α-syn aggregate levels in cell lysates from human-PAC-wt-SNCA+/+/Snca-/-  or Snca-/- neuronal cultures treated with fibril PFFs or monomeric protein for 14 days. (G) Group analysis of NeuN-positive nuclei abundance normalized to DAPI count. Each data point in a group in the graphs represents the mean of signal from an individual litter with two technical replicates per litter and at least 25 images analyzed for each replicate, with error bars indicating S.E.M. Significance was determined by 2-tailed t-tests; **p<0.001, ****p < 0.0001, ns for not significant. Fig. 6. Mouse PFF induced α-syn pathology spreads through the mouse brain to seed human α-syn pathology more efficiently than human α-syn PFFs (B) Group analysis of α-syn pathology propagation ratio to contralateral side in piriform cortex, (C) thalamus, and (D) dorsal striatum, quantified as proportion of pSyn neuronal inclusion spread between Ipsi and Contr. areas. (E) Analysis of pS129-α-syn pathology near the injection site within the ipsilateral dorsal striatum. Each data point (n=5 per group) in group analysis plots represents the mean of the signal from 20-25 sections from an individual animal, and error bars indicate S.E.M. Significance was determined by 2-tailed t-tests; *p<0.05, ns for not significant. Fig. 7. Recruitment of human α-syn monomer into mouse PFFs leads to the generation of mouse-like fibrils. (A) Representative aggregation assays showing mouse and human PFF-templated aggregation with human α-syn monomer, with (B) the calculated lag phase. Data points represent normalized ThT fluorescence from three independent experiments with error bars indicating S.E.M. (C) Representative filter-trap slot-blot membranes stained with MJFR14-6-4-2 α-syn aggregate-specific antibodies for the detection of aggregated α-syn in corroboration of aggregation kinetics without amyloid dyes.  (E) Group analysis of ThT binding (fluorescence units, F.U.) from chimeric or homogenous-sequence extracted, monomer-free, sonicated α-syn fibril (PFF) products, as well as (F) Nile Red binding. Each data point in panels E and F represents a mean from an individual experiment measured in duplicate with three independent experiments.E<a name="_Hlk173655145"></a>rror bars indicate S.E.M.,  **p<0.01, from a 2-tailed t-test, and ***p<0.001 from Tukey’s post-hoc test after ANOVA. fig. S2. High resolution estimation of the cryo-EM map of mouse and human recombinant α-syn fibrils Fourier shell correlation (FSC) resolution estimation and validation for the 3D reconstruction of the cryo-EM collected images of procured  mouse fibrils generated by Duke (a) and EPFL (b) research groups. (c) FSC estimation plot of human α-syn fibrils collected and generated at Duke University.   fig. S7. Generation and validation of mouse and human α-syn PFFs (c) Group analysis of the size population proportions of sonicated mouse and human α-syn preparations, (e) representative average radii of human α-syn,(f) UV absorbance spectra and (g) coefficient extinction adjusted concentration. Each data point or S.E.M in panel c, e and g are extracted from a single acquisition from three independent experiments with ten measurements analyzed per group. Each dot in panel f is the mean of two technical replicates from three independent batches. Significance was assessed via 2-tailed t-tests with ns for not significant.   fig. S9. Mouse α-syn PFFs are highly susceptible to sarkosyl denaturation. (a) Filter-trap slot-blot analysis of sonicated fibrils (PFFs) exposed to different concentrations of sarkosyl (left) and the remaining fibrils detected with the fibril-selective antibody MJFR14-6-4-2 in a dose-response curve (middle), with group analysis between two PFF variants at 1% Sarkosyl compared (right). Error bars indicate S.E.M from three independent experiments. (b) DLS analysis of sonicated fibrils (PFFs) exposed to sarkosyl concentrations in a dose-response curve. Error bars indicate S.E.M of three independent experiments with 10 acquisition measurements for each biological sample.  *p<0.05 from unpaired 2-tailed t-tests.   fig. S11. Evaluation of α-syn aggregation ELISA using control recombinant mouse and human α-syn fibril PFFs. Standard curves generated from mouse and human PFFs in a pan-α-syn aggregate-specific ELISA. The ELISA approach was utilized to quantify the level of aggregates present in lysates derived from the neuronal cultures. The standard curve, along with the indicated goodness of fit and corresponding r² values, provides reliable measures at physiological ranges. Each data point represents the mean from three technical replicates from two independent experiments with errors bars indicating S.E.M.   fig. S9. Evaluation of α-syn ELISA using control recombinant mouse and human α-syn fibril PFFs Standard curve generated from mouse and human PFFs in a pan-α-syn aggregate ELISA. The ELISA was utilized to quantify the level of aggregates present in the cell lysates. The standard curve, along with the indicated goodness of fit and corresponding r² values, provides a reliable measure for interpreting the results. Each data point represents the mean from three technical replicates from two independent experiments with errors bars indicating S.E.M.   fig. S12. Elevated p-S129-α-syn levels in iPSC-derived dopaminergic neurons following treatment with mouse α-syn PFFs (b) Levels of pS129-α-syn in the β-III-tubulin area in iPSC-derived DA neurons after 7 days of treatment with 10 μg/mL of PFFs or control. (c) The quantity of pS129-α-syn puncta relative to the β-III-tubulin area measured in each image and compared across conditions. (d) Proportion of abundance of pS129-α-syn puncta localized in cell bodies and neurites in group analysis between mouse and human α-syn PFF treatments. Each data point in c and d represent the mean value of the images from one well (n=4) and errors bars indicate S.E.M with **p<0.01 from 2-tailed t-tests.    fig. S13. Evaluation of kinetic properties in aggregation assays with cross-seeded chimeric fibrils show that the chimeric fibrils largely replicate the functional properties of their parental seeds, despite different amino acid sequences between the fibril preparations. (a) Representative RT-QuIC (real-time quaking induced)  assays of normalized relative fluorescence values (RFUs) with mouse monomer templating on different PFF seeds in the creation of new fibrils. The lack of formation of spontaneous fibrils (gray color, no PFFs added “no template”) indicate that spontaneous aggregation is not occurring under the given aggregation conditions within the specified timeframes. Line graphs show corresponding lag in amplification (in hours, or time to initial fluorescence threshold) of the different reactions combined with different PFF concentrations added and analyzed to a linear regression model. Data points represent normalized ThT fluorescence to their maximal fluorescence in the individual reactions, accounting for differential ThT binding to different fibril structures. (b) Comparable reactions as above but with human instead of mouse monomer templating with the indicated PFF seed.

opencc-by-4.0Oct 2024View details →

Dataset for: Dopamine neurons that inform Drosophila olfactory memory have distinct, acute functions driving attraction and aversion

The brain must guide immediate responses to beneficial and harmful stimuli while simultaneously writing memories for future reference. While both immediate actions and reinforcement learning are instructed by dopamine, how dopaminergic systems maintain coherence between these two reward functions is unknown. Through optogenetic activation experiments, we showed that the dopamine neurons that inform olfactory memory in Drosophila have a distinct, parallel function driving attraction and aversion (valence). Sensory neurons required for olfactory memory were dispensable to dopaminergic valence. A broadly projecting set of dopaminergic cells had valence that was dependent on dopamine, glutamate, and octopamine. Similarly, a more restricted dopaminergic cluster with attractive valence was reliant on dopamine and glutamate; flies avoided opto-inhibition of this narrow subset, indicating the role of this cluster in controlling ongoing behavior. Dopamine valence was distinct from output-neuron opto-valence in locomotor pattern, strength, and polarity. Overall our data suggest that dopamine’s acute effect on valence provides a mechanism by which a dopaminergic system can coherently write memories to influence future responses while guiding immediate attraction and aversion.

opencc-by-4.0Feb 2023View details →

dataset relate to article: "Functional Characterization of Two Variants at the Intron 6-Exon 7 Boundary of the KCNQ2 Potassium Channel Gene Causing Distinct Epileptic Phenotypes"

Sequencing Analysis performed at Fondazione Besta and carried out as part of the study mentioned at title

opencc-zeroJul 2023View details →

Beyond trait distances: Functional distinctiveness captures the outcome of plant competition

Functional trait distances between coexisting organisms reflect not only complementarity in the way they use resources, but also differences in their competitive abilities. Accordingly, absolute and relative trait distances have been widely used to capture the effects of niche dissimilarity and competitive hierarchies, respectively, on the performance of plants in competition. However, multiple dimensions of the plant phenotype are involved in these plant-plant interactions (PPI), challenging the use of relative trait distances to predict their outcomes. Furthermore, estimating the effects of competitive hierarchy on the performance of a group of coexisting plants remains particularly difficult since relative trait distances relate to the effects of a focal plant on another. We argue that trait distinctiveness, an emerging facet of functional diversity that characterizes the eccentric position of a species (or genotype) in a phenotypic space, can reveal the unique role played by a given individual plant in a group of competing plants . We used the model crop species Oryza sativa spp. japonica to evaluate the ability of trait distances and trait distinctiveness to predict the outcome of intraspecific PPI on the performance of single genotype and genotype mixtures. We performed a screening experiment to characterize the phenotypic space of 49 rice genotypes based on 11 aboveground and root traits. We selected nine genotypes with contrasting positions in the phenotypic space and grew them in pots following a complete pairwise interaction design. Relative distances and distinctiveness based on traits associated with light competition were by far the best predictors of the performance of single genotypes - taller genotypes that acquired resource faster being the best competitors - while absolute trait distances had no effect. These results indicate that competitive hierarchy for light dominates PPI in this experiment. Consistently, trait distinctiveness in plant height and age at flowering had the strongest, positive effects on mixture performance, confirming that functional distinctiveness captures the effects of trait hierarchies and asymmetric PPI at this scale. Our findings shed new light on the role of trait diversity in regulating PPI and ecosystem processes and call for a greater consideration of functional distinctiveness in studies of coexistence mechanisms.

publicJul 2023View details →

Beyond trait distances: Functional distinctiveness captures the outcome of plant competition

Open the record for dataset details and reuse information.

publicOct 2023View details →

Divergent molecular networks program functionally distinct CD8+ skin-resident memory T cells

Open the record for dataset details and reuse information.

opencc-by-4.0Jul 2020View details →

Data set for "Anatomically and functionally distinct thalamocortical inputs to primary and secondary mouse whisker somatosensory cortices"

Data set for: El-Boustani S, Sermet BS, Foustoukos G, Oram TB, Yizhar O, Petersen CCH (2020) Anatomically and functionally distinct thalamocortical inputs to primary and secondary mouse whisker somatosensory cortices. Nature Communications 11: 3342. doi: 10.1038/s41467-020-17087-7 There are 4 files in this upload: 1. The file named "2020_El-Boustani_NCOMMS.pdf" is the Open Access pdf file of the manuscript published in Nature Communications. 2. The file named "2020_El-Boustani_NCOMMS_SupMovie1.avi" is Supplementary Movie 1 in .avi format, accompanying the Nature Communications publication. 2. The file named "2020_El-Boustani_NCOMMS_SupMovie2.avi" is Supplementary Movie 2 in .avi format, accompanying the Nature Communications publication. 4. The file named "El-Boustani_data_code.zip" (~36 GB) is a zipped version of a folder "El-Boustani_data_code" (~45 GB), which contains the data analysed in the study along with the Matlab code used to generate the published figures. To access the data and the code, first unzip the file. In the main folder, data for all experiments are stored within folders starting by the prefix “SB”. The code for generating population data and plotting figures from the paper are in the folder “Matlab_code”. In this folder, several Matlab scripts are named after the panels or figures they will plot such as “Plot_Fig3d_Axon_GCaMP6s_traces_example.m”. After opening each file, executing the script will automatically plot the panels and name them accordingly. In some files, the type of data to plot should be specified at the very beginning of the script: “VPM” for VPM data, “POMf” for POm-FO data and “Layer1” for POm-HO data in layer 1. For figure 2, the code is located in a dedicated folder where a Matlab file “Plot_Fig2d_g_Populatin_Plot_POm_FO_HO.m” is used to generate the figures. Finally, other Matlab files are included that are used to create population .mat files or for additional analysis related to the manuscript.

opencc-zeroJun 2022View details →

Raw data for the article: A Cryptochrome adopts distinct moon- and sunlight states and functions as sun- versus moonlight interpreter in monthly oscillator entrainment

The moon's monthly cycle synchronizes reproduction in countless marine organisms. The mass-spawning bristle worm Platynereis dumerilii uses an endogenous monthly oscillator to phase reproduction to specific days. Classical work showed that this oscillator is set by full moon. But how do organisms recognize such a specific moon phase? We uncover that the light receptor L-Cryptochrome (L-Cry) is able to discriminate between different moonlight durations, as well as between sun- and moonlight. Consistent with L-Cry's function as light valence interpreter, its genetic loss leads to a faster re-entrainment under artificially strong nocturnal light. This suggests that L-Cry blocks "wrong" light from impacting on the monthly oscillator. A biochemical characterization of purified L-Cry protein, exposed to naturalistic sun- or moonlight, reveals the formation of distinct sun- and moonlight states characterized by different photoreduction- and recovery kinetics of L-Cry's co-factor Flavin Adenine Dinucleotide. In vivo, L-Cry's sun- versus moonlight states correlate with distinct sub-cellular localizations, indicating different signalling. In contrast, r-Opsin1, the most abundant ocular opsin, is not required for monthly oscillator entrainment. Our work reveals a new concept for correct moonlight interpretation involving a "valence interpreter" that provides entraining photoreceptor(s) with light source and moon phase information. These findings advance our mechanistic understanding of a fundamental biological phenomenon: moon-controlled monthly timing. Such level of understanding is also an essential prerequisite to tackle anthropogenic threats on marine ecology.

opencc-by-4.0Aug 2024View details →

Aging is associated with functional and molecular changes in distinct hematopoietic stem cell subsets

Contains the input data used in the analysis of the paper: Aging is associated with functional and molecular changes in distinct hematopoietic stem cell subsets (Su, Hauenstein, Somuncular et al., Nature Communications, 2024).

opencc-zeroJul 2021View details →

Distinct synaptic transfer functions in same-type photoreceptors

Many sensory systems use ribbon-type synapses to transmit their signals to downstream circuits. The properties of this synaptic transfer fundamentally dictate which aspects in the original stimulus will be accentuated or suppressed, thereby partially defining the detection limits of the circuit. Accordingly, sensory neurons have evolved a wide variety of ribbon geometries and vesicle pool properties to best support their diverse functional requirements. However, the need for diverse synaptic functions does not only arise across neuron types, but also within. Here we show that UV-cones, a single type of photoreceptor of the larval zebrafish eye, exhibit striking differences in their synaptic ultrastructure and consequent calcium to glutamate transfer function depending on their location in the eye. We arrive at this conclusion by combining serial section electron microscopy and simultaneous "dual-colour" 2-photon imaging of calcium and glutamate signals from the same synapse in vivo. We further use the functional dataset to fit a cascade-like model of the ribbon synapse with different vesicle pool sizes, transfer rates and other synaptic properties. Exploiting recent developments in simulation-based inference, we obtain full posterior estimates for the parameters and compare these across different retinal regions. The model enables us to extrapolate to new stimuli and to systematically investigate different response behaviours of various ribbon configurations. We also provide an interactive, easy-to-use version of this model as an online tool. Overall, we show that already on the synaptic level of single neuron types there exist highly specialized mechanisms which are advantageous for the encoding of different visual features.

opencc-by-4.0Jul 2021View details →

Functionally distinct tree species support long-term productivity in extreme environments

Dataset used for the article "Functionally distinct tree species support long-term productivity in extreme environments", submitted to Proceedings of the Royal society B. Contains raw output of simulations performed with the ForCEEPS forest gap model (http://capsis.cirad.fr/capsis/help_en/forceeps). For a description of the simulations performed and the dataset, see the associated GitHub (https://github.com/LDelalandre/Project-1_Distinct-sp_BEF) and the article. Simulations are grouped in 11 folders corresponding to the 11 environmental conditions used for simulating community dynamics. Subfolders group outputs by species richness gradients (30 random orders, plus "decreasing" order, which is from the most functionally distinct to the least functioonally distinct species, and "increasing, which is the other way around, and monocultures). For each species richness level (from 1: all the species, to 30, the last species of the richness gradient), four different files were generated: - biomass data: 'complete' (every individual); 'mean' (aggregated at the community level each year); - productivity data: productivity (every individual); productitity_scene (aggregated at the species level each year).

opencc-by-4.0Jul 2023View details →

A triple distinction of cerebellar function for oculomotor learning and fatigue compensation

This depository contains the data and modeling code of the publication  Masselink J., Cheviet, A., Froment-Tilikete, C., Pélisson, D., & Lappe, M. (2023). A triple distinction of cerebellar function for oculomotor learning and fatigue compensation. PLoS Comput Biol Please see the publication for detailed description of experimental and modeling methods. Data are provided in a mat-file, modeling code is provided in m-files (Matlab).

opencc-zeroSep 2023View details →

A trait-based approach to assess niche overlap and functional distinctiveness between non-indigenous and native species

Our understanding of the community assembly processes acting on non-indigenous species (NIS), as well as the relationship with native species is limited, especially in marine ecosystems. To overcome this knowledge gap we here develop a trait-based approach based on the functional distinctiveness metric to assess niche overlap between NIS and native species, using high-resolution data on benthic invertebrate communities in the Baltic Sea. Our results show that NIS retain a certain degree of similarity with native species, but display one or a few singular unique traits (e.g., bioturbation ability). Furthermore, we demonstrate that community assembly processes, including both environmental filtering and limiting similarity affect NIS establishment, but that their effects may be highly context dependent, as illustrated by pronounced spatial patterns in distinctiveness. Finally, our trait-based approach provides a generic framework applicable to other areas and organisms, to better understand and address biological invasions.

publicJul 2020View details →

Data from: Flexibility of fetal tolerance: Immune function during pregnancy varies between ecologically distinct populations

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publicMay 2024View details →

Similar Enzymatic Functions in Distinct Bioluminescence Systems: Evolutionary Recruitment of Sulfotransferases in Ostracod Light Organs

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