Biology subjects

Bittner, L.

Publications and source records attributed to Bittner, L..

8 recordsLinked to original sources

bioRxiv2024

Single-cell transcriptomics highlights sexual cues among reproductive life stages of uncultivated Acantharia (Radiolaria)

As an innate property of life, the ability to reproduce is a key process for the perpetuation of organisms. Along the evolution of protist reproductive strategies, the molecular machinery of sexual recombination is estimated to have been inherited from the last eukaryotic common ancestor (LECA). Nevertheless, unraveling the sexual cycles of extant free-living protist lineages remains challenging, given the enigmatic roles of many uncultivated life stages. Among the uncultivated planktonic group of Acantharia (Radiolaria), a hypothetical sexual cycle has been proposed since the late 19th century, including the existence of a gamete-like life stage of undetermined ploidy, referred to as swarmers. In order to investigate the sexual nature of acantharian reproductive stages, we conducted single-cell transcriptomic analysis across various acantharian life stages. Our results show distinct functional profiles for reproductive and vegetative life stages, while revealing the expression of the reference eukaryotic genes involved in gamete fusion, HAP2/GCS1 and GEX1-KAR5, in swarmers and pre-swarmer stages. Annotation of differentially expressed life stage-specific genes, also highlights putative meiosis-related functions among swarmers, while suggesting the existence of a potential swarmer/vegetative intermediate stage expressing putative growth-related genes. This original life stage-specific genetic data is coherent with morphological evidence supporting the existence of an acantharian sexual cycle, with swarmers acting as gametes. Moreover, it paves the way for a deeper understanding of radiolarian cell biology and ecology at a single-cell scale. HighlightsO_LIAcantharia demonstrate both morphological and genetic evidence of a sexual cycle C_LIO_LIAcantharian reproductive stages are enriched in functions related to cell division C_LIO_LINuclear fusion gene family GEX1-KAR5 is up-regulated in putative acantharian gametes C_LIO_LIMost expressed genes specific to acantharian reproductive stages are unassigned C_LIO_LIReproduction-specific unassigned genes include putative sex-related functions C_LI

microbiology↗

bioRxiv2023

Picoeukaryotic photosynthetic potential is functionally redundant but taxonomically structured at global scale

Primary production, performed by RUBISCO, and often associated with carbon concentration mechanisms, is of major importance in the oceans. Thanks to growing metagenomic resources (e.g., eukaryotic Metagenome-Assembled-Genomes; MAGs), we provide the first reproducible machine-learning-based framework to derive the potential biogeography of a given function, through the multi-output regression of the standardized number of reads of the associated genes on environmental climatologies. We use it to study the genomic potential of C4-photosynthesis of picoeukaryotes, a diverse and abundant group of marine unicellular photosynthetic organisms. We show that the genomic potential supporting C4-enzymes and RUBISCO exhibit strong functional redundancy and an important affinity towards tropical oligotrophic waters. This redundancy is then structured taxonomically by the dominance of Mamiellophyceae and Prymnesiophyceae in mid and high latitudes. Finally, unlike the genomic potential related to most C4-enzymes, the one of RUBISCO showed a clear pattern affinity for temperate waters.

ecology↗

bioRxiv2023

SENSE-PPI reconstructs protein-protein interactions of various complexities, within, across, and between species, with sequence-based evolutionary scale modeling and deep learning

Ab initio computational reconstructions of protein-protein interaction (PPI) networks will provide invaluable insights on cellular systems, enabling the discovery of novel molecular interactions and elucidating biological mechanisms within and between organisms. Leveraging latest generation protein language models and recurrent neural networks, we present SENSE-PPI, a sequence-based deep learning model that efficiently reconstructs ab initio PPIs, distinguishing partners among tens of thousands of proteins and identifying specific interactions within functionally similar proteins. SENSE-PPI demonstrates high accuracy, limited training requirements, and versatility in cross-species predictions, even with non-model organisms and human-virus interactions. Its performance decreases for phylogenetically more distant model and non-model organisms, but signal alteration is very slow. SENSE-PPI is state-of-the-art, outperforming all existing methods. In this regard, it demonstrates the important role of parameters in protein language models. SENSE-PPI is very fast and can test 10,000 proteins against themselves in a matter of hours, enabling the reconstruction of genome-wide proteomes. Graphical abstractSENSE-PPI is a general deep learning architecture predicting protein-protein interactions of different complexities, between stable proteins, between stable and intrinsically disordered proteins, within a species, and between species. Trained on one species, it accurately predicts interactions and reconstructs complete specialized subnetworks for model and non-model organisms, and trained on human-virus interactions, it predicts human-virus interactions for new viruses. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=187 SRC="FIGDIR/small/558413v3_ufig1.gif" ALT="Figure 1"> View larger version (63K): org.highwire.dtl.DTLVardef@106d345org.highwire.dtl.DTLVardef@11883a6org.highwire.dtl.DTLVardef@6b07d9org.highwire.dtl.DTLVardef@d07138_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2022

Beyond the limits of the unassigned protist microbiome: inferring large-scale spatio-temporal patterns of marine parasites

Marine protists are major components of the oceanic microbiome that remain largely unrepresented in culture collections and genomic reference databases. The exploration of this uncharted protist diversity in oceanic communities relies essentially on studying genetic markers from the environment as taxonomic barcodes. Here we report that across 6 large scale spatio-temporal planktonic surveys, half of the genetic barcodes remain taxonomically unassigned at the genus level, preventing a fine ecological understanding for numerous protist lineages. Among them, parasitic Syndiniales (Dinoflagellata) appear as the least described protist group. We have developed a computational workflow, integrating diverse 18S rDNA gene metabarcoding datasets, in order to infer large-scale ecological patterns at 100% similarity of the genetic marker, overcoming the limitation of taxonomic assignment. From a spatial perspective, we identified 2 171 unassigned clusters exclusively shared between the Tropical/Subtropical Ocean and the Mediterranean Sea among all Syndiniales orders and 25 ubiquitous clusters shared within all the studied marine regions. From a temporal perspective, over 3 time-series, we highlighted 38 unassigned clusters that follow rhythmic patterns of recurrence and are the best indicators of parasite communitys variation. These clusters withhold potential as ecosystem change indicators, mirroring their associated host community responses. Our results underline the importance of Syndiniales in structuring planktonic communities through space and time, raising questions regarding host-parasite association specificity and the trophic mode of persistent Syndiniales, while providing an innovative framework for prioritizing unassigned protist taxa for further description.

genomics↗

bioRxiv2019

Stereoscopic Rendering in a Head Mounted Display Elicits Higher Functional Connectivity During Virtual Reality

Virtual reality (VR) simulates real world scenarios by creating a presence in users. Such immersive scenarios lead to more similar behaviour to that displayed in real world settings, which may facilitate the transfer of knowledge and skills acquired in VR to real world situations. VR has already been used in education, psychotherapy, rehabilitation and it is an appealing choice for training intervention. The aim was to investigate to what extend VR technology can be used in a magnetic resonance imaging scanner(MRI), addressing the question of whether brain connectivity differs between VR and screen via mirror projection presentations. Moreover, we investigate whether stereoscopic goggle stimulation, where eyes receive different input, would elicit more brain connectivity than stimulation where both eyes receive the same input (monoscopic). To our knowledge, there is no previous research addressing this question. Multiple analyses were performed to cover different aspects of brain connectivity: fractional low frequency fluctuation, independent component analysis, seed-based functional connectivity and graph analysis. In goggles (mono and stereoscopic) vs. screen, we found connectivity differences in cerebellum and postcentral gyrus and in visual and frontal inferior cortex in visual/default-mode networks. Considering specific areas, we found higher connectivity between superior frontal cortex and temporal lobe, as well as inferior parietal cortex with calcarine and lingual. Furthermore, superior frontal cortex and insula/putamen were more strongly connected in stereoscopic, in line with our hypothesis. We assume that conditions eliciting most connectivity should be suited for long-term interventions as extended training under these conditions could permanently improve functional/structural connectivity.

neuroscience↗

bioRxiv2018

Evaluation of FlowVR: a virtual reality game for improvement of depressive mood

ObjectiveThis study evaluated the efficacy of FlowVR, a virtual reality (VR) game designed to improve mood and reduce feelings of depression. The aim is to contribute to the question of whether and how VR could be used for depression therapy, as research in this area is quite rare.\n\nMethod18 healthy participants (9 female; Mage = 25.9) underwent three conditions, playing FlowVR in VR with a head-mounted display, playing FlowVR on a tablet or reading a text on a tablet. For each condition, they were tested on a separate day at the same time of day within a two-week period. Before and after every condition participants completed the Becks Depression Inventory II (BDI-II), the state part of the State-Trait-Anxiety-Depression-Inventory (STADI(S)) and the Positive Affect Negative Affect Schedule-Expanded Form (PANAS-X).\n\nResultsWhile the participants showed only a reduction in acute anxiety in the control and the tablet conditions, they showed improved affectivity in all variables measured in the VR condition. In addition, VR had significantly better results than the control condition in improving positive affectivity, negative affectivity and acute feelings of depression. Using a less conservative statistical approach, these significant differences could also be found between the tablet and the VR condition. There were no significant differences between the tablet and the control condition.\n\nConclusionThe results indicate that due to its immersive nature, VR can be used effectively to improve mood and temporarily reduce feelings of depression. Long-term effects of FlowVR on participants with depression must be investigated in consecutive research.

neuroscience↗

bioRxiv2017

A de novo approach to disentangle partner identity and function in holobiont systems

BackgroundStudy of meta-transcriptomic datasets involving non-model organisms represents bioinformatic challenges. The production of chimeric sequences and our inability to distinguish the taxonomic origins of the sequences produced are inherent and recurrent difficulties in de novo assembly analyses. The study of holobiont transcriptomes shares similarities with meta-transcriptomic, and hence, is also affected by challenges invoked above. Here we propose an innovative approach to tackle such difficulties which was applied to the study of marine holobiont models as a proof of concept.\n\nResultsWe considered three holobionts models, of which two transcriptomes were previously assembled and published, and a yet unpublished transcriptome, to analyze their raw reads and assign them to the host and/or to the symbiont(s) using Short Read Connector, a k-mer based similarity method. We were able to define four distinct categories of reads for each holobiont transcriptome: host reads, symbiont reads, shared reads and unassigned reads. The result of the independent assemblies for each category within a transcriptome led to a significant diminution of de novo assembled chimeras compared to classical assembly methods. Combining independent functional and taxonomic annotations of each partners transcriptome is particularly convenient to explore the functional diversity of an holobiont. Finally, our strategy allowed to propose new functional annotations for two well-studied holobionts and a first transcriptome from a planktonic Radiolaria-Dinophyta system forming widespread symbiotic association for which our knowledge is limited. Conclusions\n\nIn contrast to classical assembly approaches, our bioinformatic strategy not only allows biologists to studying separately host and symbiont data from a holobiont mixture, but also generates improved transcriptome assemblies. The use of Short Read Connector has proven to be an effective way to tackle meta-transcriptomic challenges to study holobiont systems composed of either well-studied or poorly characterized symbiotic lineages such as the newly sequenced marine plankton Radiolaria-Dinophyta symbiosis and ultimately expand our knowledge about these marine symbiotic associations.

genomics↗

bioRxiv2017

Analysis Of The Genomic Basis Of Functional Diversity In Dinoflagellates Using A Transcriptome-Based Sequence Similarity Network

Dinoflagellates are one of the most abundant and functionally diverse groups of eukaryotes. Despite an overall scarcity of genomic information for dinoflagellates, constantly emerging high-throughput sequencing resources can be used to characterize and compare these organisms. We assembled de novo and processed 46 dinoflagellate transcriptomes and used a sequence similarity network (SSN) to compare the underlying genomic basis of functional features within the group. This approach constitutes the most comprehensive picture to date of the genomic potential of dinoflagellates. A core proteome composed of 252 connected components (CCs) of putative conserved protein domains (pCDs) was identified. Of these, 206 were novel and 16 lacked any functional annotation in public databases. Integration of functional information in our network analyses allowed investigation of pCDs specifically associated to functional traits. With respect to toxicity, sequences homologous to those of proteins involved in toxin biosynthesis pathways (e.g. sxtA1-4 and sxtG) were not specific to known toxin-producing species. Although not fully specific to symbiosis, the most represented functions associated with proteins involved in the symbiotic trait were related to membrane processes and ion transport. Overall, our SSN approach led to identification of 45,207 and 90,794 specific and constitutive pCDs of respectively the toxic and symbiotic species represented in our analyses. Of these, 56% and 57% respectively (i.e. 25,393 and 52,193 pCDs) completely lacked annotation in public databases. This stresses the extent of our lack of knowledge, while emphasizing the potential of SSNs to identify candidate pCDs for further functional genomic characterization.

genomics↗