bluuebunny/crossref_metadata_2025_split huggingface dataset:
Automated community ecology using deep learning: a case study of planktonic foraminifera
Authors: Hsiang Allison Y. , Hull Pincelli M. 
Published: November 2022

AbstractThe development of deep learning methods using convolutional neural networks (CNNs) has revolutionised the field of computer vision in recent years. The automation of taxonomic identification using CNNs leads naturally to the use of such technology for rapidly generating large organismal datasets in order to study the evolutionary and ecological dynamics of biological communities across time and space. While CNNs have been used to train machine learning classifiers that can identify organisms to the species level for several groups, this vision of automated community ecology has yet to be thoroughly tested or fulfilled. Here, we present a case study of automated community ecology using a large dataset of Atlantic planktonic foraminifera for which the generation of species labels and morphometric measurements was completely automated. We compare standard community diversity metrics between the fully automated dataset and a “traditional” dataset with human-identified specimens. We show that there is high congruence between the results, and that machine classifications help avoid biases that can result in the inference of misleading biodiversity patterns. Our study demonstrates the viability and potential of fully automated community ecology and sets the stage for a new era of ecological and evolutionary inquiry driven by artificial intelligence.
Landscape heterogeneity and soil biota are central to multi-taxa diversity for landscape restoration
Authors: Montoya-Sánchez Vannesa , Kreft Holger , Arimond Isabelle , Ballauff Johannes , Berkelmann Dirk , Brambach Fabian , Daniel Rolf , Grass Ingo , Hines Jes , Hölscher Dirk , Irawan Bambang , Krause Alena , Polle Andrea , Potapov Anton , Sachsenmaier Lena , Scheu Stefan , Sundawati Leti , Tscharntke Teja , Zemp Delphine Clara , Guerrero-Ramírez Nathaly R. 
Published: November 2022

AbstractHow to enhance biodiversity in monoculture-dominated landscapes is a key sustainability question that requires considering the spatial organization of ecological communities (beta diversity). Here, we experimentally tested if increasing landscape heterogeneity – through tree islands – is a suitable landscape restoration strategy when aiming to enhance multi-taxa diversity. We found that multi-taxa diversity resulted from islands fostering unique species (turnover: between 0.18 - 0.73) rather than species losses and gains (nestedness: between 0.03 - 0.34), suggesting that tree islands enhance diversity at the landscape scale. Through partial correlation networks, we revealed that landscape heterogeneity is associated with multi-taxa diversity (strength = 0.84). Soil biota were also central to the overall community by connecting beta diversity patterns across taxa. Our results show that increasing landscape heterogeneity enhances multi-taxa diversity in monoculture-dominant landscapes. Furthermore, we highlight that strategies aiming to enhance multi-taxa diversity should consider that spatial distributions of above- and below-ground communities are associated.
In vivoCharacterization of the Critical Interaction between the RNA Exosome and the Essential RNA Helicase Mtr4 inSaccharomyces cerevisiae
Authors: Sterrett Maria C. , Farchi Daniela , Strassler Sarah E. , Boise Lawrence H. , Fasken Milo B. , Corbett Anita H. 
Published: November 2022

ABSTRACTThe RNA exosome is a conserved molecular machine that processes/degrades numerous coding and non-coding RNAs. The 10-subunit complex is composed of three S1/KH cap subunits (human EXOSC2/3/1; yeast Rrp4/40/Csl4), a lower ring of six PH-like subunits (human EXOSC4/7/8/9/5/6; (yeast Rrp41/42/43/45/46/Mtr3), and a singular 3’-5’ exo/endonuclease DIS3/Rrp44. Recently, several disease-linked missense mutations have been identified in genes encoding the structural cap and core subunits of the RNA exosome. In this study, we characterize a rare multiple myeloma patient missense mutation that was identified in the cap subunit geneEXOSC2. This missense mutation results in a single amino acid substitution, p.Met40Thr, in a highly conserved domain of EXOSC2. Structural studies suggest this Met40 residue makes direct contact with the essential RNA helicase, MTR4, and may help stabilize the critical interaction between the RNA exosome complex and this cofactor. To assess this interactionin vivo, we utilized theSaccharomyces cerevisiaesystem and modeled theEXOSC2patient mutation into the orthologous yeast geneRRP4, generating the variantrrp4 M68T. Therrp4 M68Tcells have accumulation of certain RNA exosome target RNAs and show sensitivity to drugs that impact RNA processing. Additionally, we identified robust negative genetic interactions therrp4 M68Tvariant and RNA exosome cofactor mutants, particularlymtr4mutant variants. This study suggests that theEXOC2mutation identified in a multiple myeloma patient may impact the function of the RNA exosome and provides anin vivoassessment of a critical interface between the RNA exosome and Mtr4.
A multivariate regressor of patterned dopamine release predicts relapse to cocaine
Authors: Luján Miguel Á. , Young-Morrison Reana , Engi Sheila A. , Oliver Brandon L. , Zhang Lan-Yuan , Wenzel Jennifer M. , Li Yulong , Zlebnik Natalie E. , Cheer Joseph F. 
Published: November 2022

AbstractDrug addiction is characterized by a sustained vulnerability to relapse even after long periods of abstinence. A deeper understanding of the brain systems underlying this state could inform therapeutic strategies with novel prognostic biomarkers aimed at preventing renewed drug seeking. Most drugs of abuse, in particular psychostimulants such as cocaine, lead to long-lasting mesolimbic dopamine system adaptations, that ultimately facilitate drug seeking following exposure to drug-paired cues. This “dopaminergic hypothesis” of relapse has been previously addressed, but technical limitations in measuringin vivodopamine release have precluded the assessment of its sufficiency without introducing pharmacological, electrical, or optogenetic confounds. Using a dopamine receptor-based fluorescent sensor in freely moving mice, we show that long-lasting dopamine recordings in the nucleus accumbens (NAc), throughout the animal’s entire history of cocaine self-administration, are strong predictors of relapse as well as the time it takes an animal to extinguish its drug seeking behavior. Moreover, we reveal previously unseen sex-specific trajectories of cocaine-related phasic dopamine responses from acquisition to relapse. We show that males exhibit higher-amplitude phasic dopamine responses, a trait accompanied by a greater resistance to extinguish their cocaine seeking, compared to females. Furthermore, we show that a semi-parametric model of the transition to extinction – using only multivariate patterns of dopamine release and sex as covariates – faithfully recapitulates male-specific vulnerability to persistent cocaine seeking. In conclusion, we present a predictive model of reinstatement behavior that uses information exclusively conveyed by NAc phasic dopamine responses, thus confirming, and actuating the sufficiency of the dopaminergic hypothesis of relapse.
A Biophysical Basis for Learning and Transmitting Sensory Predictions
Authors: Muller Salomon Z. , Abbott LF , Sawtell Nathaniel B. 
Published: November 2022

AbstractHomeostatic (anti-Hebbian) forms of synaptic are effective at eliminating “prediction errors” that signal the differences between predicted and actual sensory input. However, such mechanisms appear to preclude the possibility of transmitting the resulting predictions to downstream circuits, severely limiting their utility. Using modeling and recordings from the electrosensory lobe of mormyrid fish, we reveal interactions between axonal and dendritic spikes that support both the learningandtransmission of predictions. We find that sensory input modulates the rate of dendritic spikes by adjusting the amplitude of backpropagating axonal action potentials. Homeostatic plasticity counteracts these effects through changes in the underlying membrane potential, allowing the dendritic spike rate to be restored to equilibrium while simultaneously transmitting predictions through modulation of the axonal spike rate. These results reveal how two types of spikes dramatically enhance the computational power of single neurons in support of an ethologically relevant multi-layer computation.
A method for polyclonal antigen-specific T cell-targeted genome editing (TarGET) for adoptive cell therapy applications
Authors: Palianina Darya , Di Roberto Raphaël B. , Castellanos-Rueda Rocío , Schlatter Fabrice , Reddy Sai T. , Khanna Nina 
Published: November 2022

ABSTRACTAdoptive cell therapy of donor-derived, antigen-specific T cells expressing native T cell receptors (TCRs) is a powerful strategy to fight viral infections in immunocompromised patients. Determining the fate of T cells following patient infusion hinges on the ability to track themin vivo. While this is possible by genetic labeling of parent cells, the applicability of this approach has been limited by the non-specificity of the edited T cells.Here, we devised a method for CRISPR-targeted genome integration of a barcoded gene into Epstein-Barr virus-antigen-stimulated T cells and demonstrated its use for exclusively identifying expanded virus-specific cell lineages. Our method facilitated the enrichment of antigen-specific T cells, which then mediated improved cytotoxicity against EBV-transformed target cells. Single-cell and deep sequencing for lineage tracing revealed the expansion profile of specific T cell clones and their corresponding gene expression signature. This method has the potential to enhance the traceability and the monitoring capabilities during immunotherapeutic T cell regimens.
A representative Performance Assessment of Maximum Likelihood based Phylogenetic Inference Tools
Authors: Höhler Dimitri , Haag Julia , Kozlov Alexey M. , Stamatakis Alexandros 
Published: November 2022

AbstractSummaryThe evaluation of phylogenetic inference tools is commonly conducted on simulated and empirical sequence data alignments. An open question is how representative these alignments are with respect to those, commonly analyzed by users. Based upon the RAxMLGrove database, it is now possible to simulate DNA sequences based on more than 70, 000 representative RAxML and RAxML-NG tree inferences on empirical datasets conducted on the RAxML web servers. This allows to assess the phylogenetic tree inference accuracy of various inference tools based on realistic and representative simulated DNA alignments. We simulated 20, 000 MSAs based on representative datasets (in terms of signal strength) from RAxMLGrove, and used 5, 000 datasets from the TreeBASE database, to assess the inference accuracy of FastTree2, IQ-TREE2, and RAxML-NG. We find that on quantifiably difficult-to-analyze MSAs all of the analysed tools perform poorly, such that the quicker FastTree2, can constitute a viable alternative to infer trees. We also find, that there are substantial differences between accuracy results on simulated and empirical data, despite the fact that a substantial effort was undertaken to simulate sequences under as realistic as possible settings.ContactDimitri Höhler,dimitri.hoehler@h-its.org
ALaSCA: a computational platform for quantifying the effect of proteins using Pearlian causal inference, with an example application in Alzheimer’s disease
Authors: Truter Nina , Jansen van Rensburg Zuné , Oudrhiri Radouane , Van Niekerk David D. , Loos Ben , Singh Raminderpal , Louw Carla 
Published: November 2022

AbstractIntroductionAn urgent need to delay the onset of aging-associated diseases has arisen due to increasing human lifespan. A dramatic surge in the number of identified potential molecular targets that could promote successful aging, has led to the challenge of prioritizing these targets for further research and drug development. In our previous work, we prioritized genes associated with aging processes based on their similarity to known aging-related genes and dysfunction marker genes inC. elegans. The goal of this study was to demonstrate the ability of our computational platform to identify molecular drivers of neuronal aging using specialized causal inference techniques. S6K was highly ranked in the previous study and here the nearby neighbors in its protein interaction network were selected to explore ALaSCA’s (Adaptable Large-Scale Causal Analysis) ability to identify possible drivers of Alzheimer’s disease.MethodsUtilizing head and brain proteome data, two of ALaSCA’s capabilities were used to understand how protein changes over the lifespan ofDrosophila melanogasteraffect a feature of neuronal aging, namely climbing ability:Pearson correlation analysis was used to assess the relationship between the changes in abundance of specific proteins associated (through protein-protein interactions) with S6K and climbing ability.Pearlian causal inference, required to achieve formal causal analysis, was used to determine which pathway, associated with proteins linked to S6K, has the largest effect on climbing ability and therefore to what degree these specific proteins are driving neuronal aging.Results and discussionBased on the correlation results, the proteins associated withfz, a gene encoding for the fz family of receptors that are involved in Wnt signaling, display an increase in abundance as climbing ability declines over time. When viewed together with thefzproteins’ strong negative causal value, it seems that their increased abundance over the lifespan ofDrosophilais an important driver of the observed decrease in climbing ability. Additionally, expression of the genes FZD1 and FZD7 (fzorthologs) is altered in the hippocampus early on in Alzheimer’s disease human samples and in an amyloid precursor protein mouse model.ConclusionWe have demonstrated the potential of the ALaSCA platform to identify and provide evidence behind molecular mechanisms. This capability enables identification of possible drivers of Alzheimer’s disease - as the human orthologs of the proteins identified here, through its Pearlian causal inference capability, have been linked to Alzheimer’s disease progression.
Druggable Growth Dependencies and Tumor Evolution Analysis in Patient-Derived Organoids of Neuroendocrine Cancer
Authors: Dayton Talya L. , Alcala Nicolas , Moonen Laura , den Hartigh Lisanne , Mangiante Lise , Lap Lisa , Dost Antonella F. M. , Beumer Joep , Levy Sonja , van Leeuwaarde Rachel S. , Hackeng Wenzel M. , Samsom Kris , Voegele Catherine , Sexton-Oates Alexandra , Begthel Harry , Korving Jeroen , Hillen Lisa , Brosens Lodewijk A. A. , Lantuejoul Sylvie , Jaksani Sridevi , Kok Niels F.M. , Hartemink Koen J. , Klomp Houke M. , Rinkes Inne H.M. Borel , Dingemans Anne-Marie , Valk Gerlof D. , Vriens Menno R. , Buikhuisen Wieneke , van den Berg José , Tesselaar Margot , Derks Jules , Speel Ernst Jan , Foll Matthieu , Fernández-Cuesta Lynnette , Clevers Hans 
Published: November 2022

SUMMARYNeuroendocrine neoplasms (NENs) comprise well-differentiated neuroendocrine tumors and poorly-differentiated carcinomas. Treatment options for patients with NENs are limited, in part due to lack of accurate models. To address this need we established the first patient-derived tumor organoids (PDTOs) from pulmonary neuroendocrine tumors and derived PDTOs from an understudied NEN subtype, large cell neuroendocrine carcinoma (LCNEC). PDTOs maintain the gene expression patterns, intra-tumoral heterogeneity, and evolutionary processes of parental tumors. Through drug sensitivity analyses, we uncover therapeutic sensitivities to an inhibitor of NAD salvage biosynthesis and to an inhibitor of BCL-2. Finally, we identify a dependency on EGF in pulmonary neuroendocrine tumor PDTOs. Consistent with these findings, analysis of an independent cohort showed that approximately 50% of pulmonary neuroendocrine tumors expressed EGFR. This study identifies a potentially actionable vulnerability for a subset of NENs, and further highlights the utility of these novel PDTO models for the study of NENs.Graphical abstractHighlightsPDTOs of pulmonary NETs and LCNEC were establishedPDTOs recapitulate intra-tumoral heterogeneity and evolution of parental tumorsDrug assays reveal therapeutic vulnerabilities and biomarkersPulmonary NET PDTOs are dependent on EGF
Generation of Unfolded Outer Membrane Protein Ensembles Targeted by Hydrodynamic Properties
Authors: Devlin Taylor , Fleming Patrick J. , Loza Nicole , Fleming Karen G. 
Published: November 2022

AbstractOuter membrane proteins (OMPs) must exist as an unfolded ensemble while interacting with a chaperone network in the periplasm of Gram-negative bacteria. Here, we developed a method to model unfolded OMP (uOMP) conformational ensembles using experimental properties of two well-studied OMPs. The overall size and shape of the unfolded ensembles in water were experimentally defined by measuring the sedimentation coefficient as a function of urea concentration. We used these data to model a full range of unfolded conformations by parameterizing a targeted coarse-grained simulation protocol. The ensemble members were further refined by short molecular dynamics simulations to reflect proper torsion angles. The final conformational ensembles reveal inherent differences in the unfolded states that necessitate further investigation. Building these uOMP ensembles advances the understanding of OMP biogenesis and produces essential information for interpreting structures of uOMP-chaperone complexes.
Nascent-Chain Interaction Networks and Their Effect on the Bacterial Ribosome
Authors: Masse Meranda M. , Guzman-Luna Valeria , Varela Angela E. , Hutchinson Rachel B. , Srivastava Aniruddha , Wei Wanting , Fuchs Andrew M , Cavagnero Silvia 
Published: November 2022

AbstractIn order to become bioactive, proteins need to be biosynthesized and protected from aggregation during translation. The ribosome and molecular chaperones contribute to both of these tasks. While it is known that some ribosomal proteins (r-proteins) interact with ribosome-bound nascent chains (RNCs), specific interaction networks and their role within the ribosomal machinery remain poorly characterized and understood. Here, we find that RNCs of variable sequence and length (beyond the 1stC-terminal reside) do not modify the apparent stability of the peptidyl-transferase center (PTC) and r-proteins. Thus, RNC/r-protein interaction networks close to the PTC have no effect on the apparent stability of ribosome-RNC complexes. Further, fluorescence anisotropy decay, chemical-crosslinking and Western blots show that RNCs of the foldable protein apoHmp1-140have an N-terminal compact region (63–94 residues) and interact specifically with r-protein L23 but not with L24 or L29, at the ribosomal-tunnel exit. Longer RNCs bear a similar compact region and interact either with L23 alone or with L23 and another unidentified r-protein, or with molecular chaperones. The apparent strength of RNC/r-protein interactions does not depend on RNC sequence. Taken together, our findings show that RNCs encoding foldable protein sequences establish an expanding specific interaction network as they get longer, including L23, another r-protein and chaperones. Interestingly, the ribosome alone (i.e., in the absence of chaperones) provides indiscriminate support to RNCs bearing up to ca. 190 residues, regardless of nascent-chain sequence and foldability. In all, this study highlights the unbiased features of the ribosome as a powerful nascent-protein interactor.Significance StatementThe presence of interactions between nascent chains bearing a foldable amino-acid sequence (with no signal or arrest tags) and specific ribosomal proteins has never been experimentally demonstrated, up to now. Here, we identify the ribosomal protein L23 as a specific nascent-chain interacting partner. We show that L23 establishes noncovalent contacts with nascent chains of the multi-domain foldable model protein apoHmp, which lacks signal/arrest sequences. Interactions with another ribosomal protein and with the trigger-factor and Hsp70 chaperones were also detected. Interestingly, ribosomal-protein/nascent-chain complexes have similar apparent stability, in the case of nascent chains of variable sequence and degree of foldability. These findings are significant because they advance our knowledge on ribosome-mediated nascent-protein interaction networks and suggest avenues to prevent undesirable aggregation.
Genomic Selection Pressure Discovery using Site-Frequency Spectrum & Reduced Local-Variability Statistics in Pakistani Dera-Din-Panah Goat
Authors: Saif Rashid , Mahmood Tania , Ejaz Aniqa , Zia Saeeda 
Published: November 2022

AbstractPopulation geneticists have long sought to comprehend various selection traces present in the goat genome due to natural or human-driven selection and breeding practices. As a step forward to pinpoint the selection signals in the Pakistani Dera-Din-Panah (DDP) goat breed, whole-genome pooled-sequencing (n=12) was performed and 618,236,192 clean paired-end reads were mapped against ARS1 reference goat assembly. Five different selection signal statistics were applied here using four Site-Frequency Spectrum (SFS) methods (Tajima’s D (TD), Fay & Wu’s H (H), Zeng’s E (E),Pool – HMM) and one Reduced Local-Variability approach named pooled-heterozygosity (Hp). The under-selection regions were annotated with significant threshold values of –ZTD≥4.7, –ZH≥6, –ZE≥2.5, Pool-HMM≥12, and –ZHp≥5, which resulted in accumulative 364 candidate gene hits, while the highest signals were observed on Chr. 4, 6, 10, 12, 15, 16, 18, 20, 27 harborADAMTS6, CWC27genes associated with body-height,RELN, MYCBP2, FGF14, STIM1, CFAP74, GNB1, CALML6, TMEM52, FAM149A, NADK, MMP23B, OPN3with body-weight/meat production,FH, MFHAS1, KLKB1with milk production,RRM1, KMO, SPEF2, F11with fecundity rate/reproduction,ATP8B4with immunity,KIT, KMOwith pigmentation,ERI1with olfaction andRHOGwith wool production traits. Furthermore, we accentuate to highlight the putative windows that were captured commonly by any of the five statistical methods applied which harbor meat production, immunity and reproduction-associated genes validating the genotype-phenotype relationship of aforementioned traits private to this goat breed. Current insight into the genomic architecture of DDP goat provides a better understanding to improve its genetic potential and other vested traits of large body size and fiber production by updating the breeding strategies to boost the livestock-based agricultural economy of the country.
Excitatory amino acid transporter 1 supports adult hippocampal neural stem cell self-renewal
Authors: Rieskamp Joshua D. , Rosado-Burgos Ileanexis , Christofi Jacob E. , Ansar Eliza , Einstein Dalia , Walters Ashley E. , Valentini Valentina , Bruno John P. , Kirby Elizabeth D. 
Published: November 2022

SummaryWithin the adult mammalian dentate gyrus (DG) of the hippocampus, glutamate stimulates neural stem cell (NSC) self-renewing proliferation, providing a link between adult neurogenesis and local circuit activity. Here, we show that glutamate-induced self-renewal of adult DG NSCs requires glutamate transport via excitatory amino acid transporter 1 (EAAT1) to stimulate lipogenesis. Loss of EAAT1 prevented glutamate-induced self-renewing proliferation of NSCs in vitro and in vivo, with little role evident for canonical glutamate receptors. Transcriptomics and further pathway manipulation revealed that glutamate simulation of NSCs relied on EAAT1 transport-stimulated lipogenesis. Our findings demonstrate a critical, direct role for EAAT1 in stimulating NSCs to support neurogenesis in adulthood, thereby providing insights into a non-canonical mechanism by which NSCs sense and respond their niche.