dataesr/scientific-paragraphs-categorization huggingface dataset:
After liquid extraction, the amount of radioactivity incorporated in organic solvent-extractable material, resulting from the phosphorylation of PI, was counted. A significant level of radioactivity, corresponding to the production of  2 µM PI(4)P was measured, if PI4K was attached to liposomes containing MPB-PE (Fig. 1F ). In comparison, a negligible amount of radioactivity was measured both in experiments with liposomes devoid of MPB-PE and mixed with PI4K, or in the absence of PI4K. Jointly these data confirmed that the PI4K construct, attached to PIrich liposomes, generated PI(4)P.
The fluorescence was recorded with measurement settings identical to those used to follow PI(4)P synthesis. By plotting the intensity of NBD signal as a function of PI(4)P concentration, we obtained a binding curve that could be easily fitted assuming a 1:1 protein-ligand interaction model (Fig. 2A ). Then, using the obtained parameters (F0, Fmax, KD) and considering that a PI-to-PI(4)P conversion occurred following a pseudo first-order reaction, we fitted the data points of fluorescence traces measured in the presence of liposomes (200 µM lipids, 10 µM PI), decorated with 0. 25, 5 or 1 µM PI4K (Fig. 2B , Fig. S2A ) to estimate the synthesis of PI(4)P over time as a function of PI4K density on liposome surface (see Methods). The amount of PI(4)P synthesized after 1 hour was found to be proportional to this factor and to reach a maximum of 2.
Acknowledgments We wish to thank  Dr. Chang Chen  for providing the plasmid coding for GST-PI4KIIα SSPSS C construct and  Dr. Jeffrey Atkinson  for the plasmid coding for GST-Sec14p. This work was supported by a " Défi Modélisation du vivant-2019 " grant from  CNRS  and " ANR-16-CE13-0006 " and " ANR-15-IDEX-0 " grants from the  Agence Nationale de la Recherche. A. S. acknowledges support from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme  (grant agreement No  101002724 RIDING ), the  Air Force Office of Scientific Research  under award number  FA8655-20-1-7028 , and the  National Institutes of Health (NIH)  under award number  R01DC018789.
FiguresFigure 1. 1 Figures Figure 1. PI(4)P synthesis on liposome surface by membrane-associated PI 4-kinase (A)Tridimensional structure of PI4KIIα SSPSS C protein (PDB ID: 4HNE (51)). The solvent-exposed serine S178 in the SSPSS sequence was replaced by a cysteine residue (in sphere mode, with carbon in grey, nitrogen in blue, oxygen in red and sulfur in yellow). The molecule of ATP bound to the PI 4kinase in the crystal is shown (in sphere mode, with carbon in green, nitrogen in blue, oxygen in red and phosphorus in orange). The orientation of the PI 4-kinase relative to the plane of the membrane (dashed line) has been suggested by molecular dynamics simulations (51). A molecule of MPB-PE is represented in sphere mode with carbon in grey (glycerol and acyl chain) or dark blue (headgroup), oxygen in red, nitrogen in blue, phosphate in orange and hydrogen in white.
Protists are major actors of soil communities and play key roles in shaping food webs, community assembly, and ecosystem processes, yet their functional diversity is understudied. High-throughput sequencing data have revealed their ubiquity and diversity, but lack of standardized traits has hampered the integration of functional information, limiting our understanding of soil ecosystems. Here, we propose a functional framework for soil protists, identify a set of common traits to characterize their functional diversity, and apply the framework on a broad-scale, real-world dataset. We reviewed studies on soil protists to identify the traits used in the literature, and define a framework based on 10 key traits that satisfy two criteria: availability of information, and applicability to most taxa.
The framework was tested on a dataset of environmental DNA metabarcoding data from 1123 soil samples collected in 48 glacier forelands worldwide. Traits were assigned to the 570 Molecular Operational Taxonomic Units (MOTUs) detected in our dataset, leading to the production of a global trait-based dataset from glacier forelands. We estimated the functional space of protist communities and evaluated if the selected traits were effective in describing protist diversity. The functional space of protist communities showed that the MOTUs are clustered in three regions, mainly reflecting different nutritional and habitat preferences. The proposed framework is appropriate for multiple applications, including estimation of functional diversity and food web analyses, and provides a basis for ecological studies on soil protists, enabling the functional characterization of this essential but often neglected component of soil biodiversity.
, 2012; Naeem et al. , 2012; Briones, 2014; Geisen et al. , 2023). Functional diversity represents the variety of morphological, ecological, behavioral, and physiological traits exhibited by different species  (Hooper et al. , 2005; Cadotte et al. , 2011). Despite preliminary efforts to define a functional classification for soil protists and identify functional groups  (Coûteaux et al. , 1998) , functional studies on soil protists remain scarce (Fig. 1 ). This can be related to the complexity of the study of protists ecology  (Geisen et al. , 2023) , but also to the lack of a conceptual framework and comprehensive databases covering key functional traits  (Dumack et al. , 2020). So far, publicly available datasets are mostly restricted to a few major taxa such as Cercozoa and Endomyxa  (Fiore-Donno et al.
, 2019; Dumack et al. , 2020 ), phytoplankton (Laplace-Treyture et al. , 2021) , or a subset of Ciliophora and amoeboid protists  (Gulin et al. , 2022). Furthermore, the few datasets covering phylogenetically diverse taxa are generally limited to a single functional trait, usually the trophic level  (Seppey et al. , 2020; Mazel et al. , 2022; Singer et al. , 2021). Nonetheless, a wealth of functional information on protists is available but spread across various sources of the existing literature, including taxonomic articles, functional datasets, and monographs/atlases spanning different taxonomic levels, from phylum  (Bahls et al. , 2018; Lynn et al. , 2018) , to family level  (Berger, 1999 (Berger, , 2007 (Berger, , 2011;; Foissner and Xu, 2007). Still, the absence of standard guidelines or established key functional traits hampers the extraction of information from existing literature.
The aim of this study is to propose a framework for developing a comprehensive database on the functional traits of soil protists that is designed to i) facilitate the retrieval of functional information, ii) accommodate most of soil protist diversity, iii) be exploitable in ecological studies and iv) use consistent terminology. To achieve this, we followed a standardized approach developed for soil fauna  (Hedde et al. , 2022)  and reviewed the literature to define a common set of readily accessible traits to characterize the functional diversity of soil protists, akin to the framework proposed for terrestrial invertebrates  (Moretti et al. , 2017). To illustrate the efficacy of the proposed framework, we applied it to a dataset containing 570 molecular operational taxonomic units (MOTUs) of protists obtained from the environmental DNA metabarcoding of 1123 soil samples covering a broad range of environmental conditions and geographic regions.
From the retained literature, we extracted information on article type, year of publication, research topic, location and geographical scale, sampling method, sampling environment, taxa considered, the functional traits and functional categories used, and the source of the functional data (Table  S1 ). The functional traits found through the review were classified into six broad types  (Moretti et al. , 2017; Dumack et al. , 2020) : nutrition, morphology, life-history, physiology, behavior, and habitat. From those traits, we selected for our functional framework the ones that satisfied two main criteria: a) information availability, b) broad applicability. Information availability was evaluated considering the possibility to retrieve functional information in the literature (e. g. , availability of trait datasets), while the applicability to a broad range of soil protists was assessed by checking if the traits can be used to characterize multiple protist lineages (Table  S2 ).
Application: functional traits of protists from glacier forelands To illustrate the application of the selected functional traits, we used a dataset containing 570 molecular operational taxonomic units (MOTUs) of protists detected using environmental DNA metabarcoding from 1123 soil samples collected along 48 glacier forelands around the world (Fig. S1 ). The 48 glacier forelands range from 48 • S to 79 • N and encompass five continents. Each glacier foreland represents a sequence of dated sites starting from 1 to a maximum of 483 years after glacier retreat  (Marta et al. , 2021)  with a general habitat shift from bare ground to fully vegetated ecosystems  (Cantera et al. , 2023). MOTUs were derived from the amplification of the eukaryotic marker Euka02  (Guardiola et al. , 2015; Taberlet et al.
, 2018)  which amplifies a ~123 bp fragment of the V7 region of the 18S rDNA gene. For details on sample collection, DNA extraction, amplification, sequencing and bioinformatic analyses, see Supplementary Methods 2. After clustering similar sequences (97% threshold;  Bonin et al. , 2023) , a total of 2008 MOTUs belonging to different kingdoms in the Eukaryota domain were detected (Fig. 2 ). Taxonomy was defined through the NCBI Taxonomy database  (Schoch et al. , 2020). We then applied our framework to functionally characterize protist communities in proglacial soils. To assign functional traits, we searched for information on nutrition, morphology, behavior, life-history, and habitat preferences for MOTUs belonging to 27 phyla/clades and to six supergroups (i. e. , Alveolata, Amoebozoa, Archaeplastida, Opisthokonta, Rhizaria, Stramenopiles; Fig.
2 ). In so doing, we conducted an extensive literature search for each taxon included in the dataset using references obtained through our review, plus additional specific searches in Google, Google Scholar and Web of Science. We gathered information from a total of 197 references (176 scientific articles including 17 datasets, 15 books/guides/atlas, and six websites; Table  S1 ). The taxonomic level of identification of MOTUs varied, with some MOTUs identified at fine taxonomic resolution (e. g. , Vorticella sphaeroidalis or Euglypha rotunda), and others identified at coarser resolution (e. g. , Cercozoa or Bacillariophyta). Therefore, the assignment of functional traits depended on the taxonomic level of identification of each MOTU. MOTUs that could not be characterized by a unique functional category due to the lack of taxonomic resolution (e.
g. , MOTU identified as Cercomonadidae), were described using two or more functional categories separated by "or" (e. g. , for Cercomonadidae, feeding mode: bacterivore_or_omnivore). To visualize how the traits proposed in our framework describe the community of protists from the proglacial soil dataset, we estimated the functional space through a principal coordinates analysis (PCoA) using the R package "ape"  (Paradis and Schliep, 2019). To build the functional space, we merged MOTUs with the same taxonomic identification, and excluded MOTUs with a taxonomic assignment coarser than family. The remaining MOTUs were characterized by every trait defined in our framework. Categorical traits were coded as dummy variables  (de Bello et al. , 2021). Length was log-transformed and scaled between 0 and 1.
Dissimilarities among MOTUs were estimated using the Gower distance weighted through the "gawdis" R function to uniform the contribution of different traits  (de Bello et al. , 2021). Finally, we tested the correlation between the first two PCoA axes and functional traits through the function envfit() from the R package "vegan"  (Oksanen et al. , 2022). Data manipulation and statistical analyses were done using the R platform v. 4. 2. 2.
Review of functional traits The Web of Science search resulted in 51 scientific articles, but only 22 actually focused on protists. Inspection of articles and of references therein yielded 10 additional references focusing on functional traits of soil protists. Of the 32 studies, one presents a functional database  (Dumack et al. , 2020) , while the remaining ones are primary research. All retained studies were published between 2015 and 2022, with an increase in publication rate during the last three years (77% of studies published between 2020 and 2022). Studies encompassed different approaches, such as tests of relationships between functional traits and environmental factors (21 studies), network analyses (eight), identification of community assembly processes (four), microcosm experiments (four), and one comparative analysis.
Three main trophic categories are generally considered  (Oliverio et al. , 2020; Seppey et al. , 2020; Mazel et al. , 2022; Singer et al. , 2021) : a) Consumer: heterotrophic protists feeding through phagocytosis. b) Parasite: heterotrophic protists living at the expense of another organism. c) Autotroph: a non-heterotrophic protist, typically a phototrophic organism that produces energy through photosynthesis. 3. 1. 1. 1. 4. Availability in the literature. A comprehensive dataset reporting trophic levels of all protist taxa can be found in  Singer et al. (2021) , whereas Laplace-Treyture et al. (  2021 ) published a detailed functional dataset for phytoplankton. 3. 1. 1. 1. 5. Critical aspects. Due to its coarse characterization, the trophic level is not appropriate for detailed analyses of the trophic composition of communities, or to infer specific biotic interactions.
h) Saprotroph: protist feeding on decaying organic matter. i)  Autotroph. 3. 1. 1. 2. 4. Availability in literature. The feeding mode is one of the most widely used functional traits for soil protists. It can be found in available functional datasets  (Adl et al. , 2019; Dumack et al. , 2020; Calderón-Sanou et al. , 2022; Gulin et al. , 2022) , and can be deducted from monographies or original description articles reporting the food sources exploited by a species or higher taxonomic groups. A synopsis of feeding habits of protists is also found in a recent review on feeding habits of soil consumers  (Potapov et al. , 2022). 3. 1. 1. 2. 5. Critical aspects. Although a good amount of data is available concerning feeding preference of soil protists, for many taxa uncertainty remains regarding their actual food sources and further analyses are needed.
, 1998; Potapov, 2022). Size differences can also reflect a vertical stratification of the composition of soil communities, with larger species often limited to the surface soil horizons  (Geisen and Bonkowski, 2018; Fiore-Donno et al. , 2022; Potapov, 2022). 3. 1. 2. 1. 3. Availability in literature. Although measures of body length and width are usually reported in articles describing taxa, databases gathering this information remain scarce (but see  Luan et al. , 2020; Laplace-Treyture et al. , 2021). 3. 1. 2. 1. 4. Critical aspects. Length and width measurements are often available but highly dispersed in literature, making it timeconsuming to obtain this information, especially if the aim is the functional characterization of many taxa. Furthermore, information on length is almost always available, whereas measures of width can be lacking.
Availability in literature. The occurrence of a protective shell and its composition are reported in original description articles. Datasets reporting information on shell structure include Fiore-Donno et al. (  2019 ) and  Dumack et al. (2020)  for Cercozoa and Endomyxa; some data on amoeboid protists are available in  Gulin et al. (2022) , while for phytoplankton see  Laplace-Treyture et al. (2021). 3. 1. 2. 2. 5. Critical aspects. Some taxa exhibit protective structures like spicules or spines that morphologically cannot be considered as a true shell (e. g. , members of the family Heterophryidae and Raphidiophryidae; Cavalier-Smith and von der Heyden, 2007). 3. 1. 2. 3. 5. Critical aspects. While for major soil protist groups data are easily available (i. e. , Cercozoa, Ameobozoa, Ciliophora), for other taxa extensive literature research is needed.
Availability in literature Information about lifestyle is often present in original descriptions articles. Datasets containing information on lifestyle include Fiore-Donno et al. (  2019 ) and  Dumack et al. (2020)  for  Cercozoa and Endomyxa, and Laplace-Treyture et al. (2021) for phytoplankton. 3. 1. 2. 4. 1. 4. Critical aspects Several protists have multiple life stages exhibiting different lifestyles. Many endoparasites, such as dinoflagellates belonging to the Amoebophryaceae family, present a free-living life stage in which they move throughout the environment to find a host  (Archibald et al. , 2017). 3. 1. 2. 5. Life form 3. 1. 2. 5. 1. Definition. Life form identifies the level of organization of an organism in life. Most protists are solitary cells, but some can form colonies composed of multiple unicellular individuals, and some algae develop into truly multicellular organisms.
3. 1. 2. 5. 3. Availability in literature. Information about life forms is often indicated in original description articles but datasets reporting this information are scarce (but see  Laplace-Treyture et al. , 2021 for phytoplankton; Gulin et al. , 2022 for Ciliophora). 3. 1. 2. 5. 4. Critical aspects. Even though the definition of a solitary unicellular protist is generally unambiguous, some taxa can create large multinucleate structures (e. g. , plasmodia of Myxomycetes;  Archibald et al. , 2017). Here we considered these taxa as "solitary" since they are neither colonial nor multicellular.
Habitat preferences 3. 1. 4. 1. 1. Definition. Type of environments in which the species have been sampled  (Burki et al. , 2021). 3. 1. 4. 1. 2. Functional categories. a) Terrestrial: found exclusively in terrestrial environments. b) Freshwater: found exclusively in freshwater environments. c) Marine: found exclusively in marine environments. d) Ubiquitous: found in both terrestrial and aquatic environments. 3. 1. 4. 1. 3. Availability in literature. Information on the typical habitat is usually present in taxonomic articles and has been summarized in some datasets  (Dumack et al. , 2020; Gulin et al. , 2022). 3. 1. 4. 1. 4. Critical aspects. Data on the type of exploited habitats typically refers to where a specific taxon has been historically found, thus information available in the literature is probably incomplete  (Simon et al.
A common framework to describe the functional diversity of soil protists To address the need for more accessible and standardized functional information, we proposed a framework consisting of a set of 10 key traits that summarize current knowledge on soil protist functional diversity (Table  1 ). The aim of this framework is to promote reproducibility and comparability across existing datasets and repositories, representing a first step toward the development of a common trait database for soil protists. Given that protists are an extremely heterogeneous group, it is debatable whether one comprehensive framework can effectively describe such diverse organisms or, alternatively, a specific functional characterization would be required for each clade/group (e. g. , Ciliophora, Cercozoa, testate amoebae).
, 2022). Clade-specific approaches are also used in palaeoecological studies to reconstruct past environmental conditions  (Fournier et al. , 2015; Marcisz et al. , 2020). However, the clade-specific approach lacks the potential to perform multi-taxa analyses and is not appropriate for datasets with broad taxonomic scope (i. e. , high-throughput sequencing data based on generalist markers). In this case, a common set of key traits can facilitate a multi-taxa approach which is essential to explain community assembly  (Calderón-Sanou et al. , 2022) , to reveal the functions and services provided by soil ecosystems  (Donald et al. , 2021)  and to construct ecological networks such as belowground food webs  (Potapov, 2022). A multi-taxa approach is frequent in metabarcoding studies (69% of reviewed studies; Table  S1 ), which often use generalist markers providing an overall characterization of protist communities but often show limited taxonomic resolution.
A common framework is thus pivotal to exploit the full potential of these datasets and will facilitate relating detected organisms with ecosystem processes and functions  (de Bello et al. , 2010; Brousseau et al. , 2018). The generality and flexibility of this approach can also encourage studies in less investigated areas of the world, reducing the observed geographical bias. Along with the multi-taxa approach, the common set of traits proposed in our framework enables us to investigate the multifaceted variation of traits in soil protist communities. This is particularly helpful to identify patterns of co-variation in functional traits across taxa (i. e. , trait syndromes;  Raffard et al. , 2017) , favouring the discrimination between traits constrained by phylogeny and those related to local environmental conditions and ecological trade-offs  (Ellers et al.
For instance, considering a single trait such as "life-form", which discriminates between solitary and colonial protists, leads to grouping phylogenetically distant protists with differing ecological functions. The integration of multiple traits like feeding mode, morphology, lifestyle, and habitat preferences enables to construct a functional space in which protist communities are well discriminated into distinct clusters. These clusters may suggest that a few traits can effectively summarize the functional diversity of protist communities but could also reflect a strong phylogenetic signal of traits  (Goberna and Verdú, 2016). The application of the framework to a metabarcoding dataset provided a practical example of how these traits can be suitable for highthroughput sequencing data. Nonetheless, characterizing a MOTU identified only to the genus or the family level requires specific adjustments to apply functional information defined at the species level.
Such a process is different between trait types. Continuous traits, such as body size, can be defined by averaging the values (e. g. , mean length) from the multiple species belonging to high-level MOTUs (e. g. , genus or family), whereas categorical traits can be transformed in fuzzy dummy variables  (de Bello et al. , 2021)  to account for the functional variability across species composing the MOTU (i. e. , species from the same taxonomic unit exhibiting diverse ecological features). Due to the lack of a common trait repository, trait assignment required an extensive literature search. The search was particularly challenging for body size data, which are usually only found in taxonomic articles where the species or genus is described or revised. To facilitate data retrieval in future studies, we report the main datasets available for different traits and taxonomic groups, highlighting the ecological relevance and potential issues for each trait (see Results section 3.
1). Despite these challenges, the framework allowed us to develop a functional dataset on proglacial soils, representing a starting point toward the creation of a common trait repository. However, the use of a single generic eukaryotic marker limited the ability to target specific taxonomic groups (e. g. , Amoebozoa or Heterolobosea;  Geisen et al. , 2023)  and, therefore, the dataset presented is not complete, as widespread soil protist taxa are missing.