bluuebunny/crossref_metadata_2025_split huggingface dataset:
Associative white matter tracts selectively predict sensorimotor learning
Authors: Vinci-Booher S. , McDonald D.J. , Berquist E. , Pestilli F. 
Published: January 2023

AbstractHuman learning is a complex phenomenon that varies greatly among individuals and is related to the microstructure of major white matter tracts in several learning domains, yet the impact of the existing myelination of white matter tracts on future learning outcomes remains unclear. We employed a machine-learning model selection framework to evaluate whether existing microstructure might predict individual differences in the potential for learning a sensorimotor task, and further, if the mapping between the microstructure of major white matter tracts and learning was selective for learning outcomes. We used diffusion tractography to measure the mean fractional anisotropy (FA) of white matter tracts in 60 adult participants who then underwent training and subsequent testing to evaluate learning. During training, participants practiced drawing a set of 40 novel symbols repeatedly using a digital writing tablet. We measured drawing learning as the slope of draw duration over the practice session and visual recognition learning as the performance accuracy in an old/new 2-AFC recognition task. Results demonstrated that the microstructure of major white matter tracts selectively predicted learning outcomes, with left hemisphere pArc and SLF 3 tracts predicting drawing learning and the left hemisphere MDLFspl predicting visual recognition learning. These results were replicated in a repeat, held-out data set and supported with complementary analyses. Overall, results suggest that individual differences in the microstructure of human white matter tracts may be selectively related to future learning outcomes and open avenues of inquiry concerning the impact of existing tract myelination in the potential for learning.Significance statementA selective mapping between tract microstructure and future learning has been demonstrated in the murine model and, to our knowledge, has not yet been demonstrated in humans. We employed a data-driven approach that identified only two tracts, the two most posterior segments of the arcuate fasciculus in the left hemisphere, to predict learning a sensorimotor task (drawing symbols) and this prediction model did not transfer to other learning outcomes (visual symbol recognition). Results suggest that individual differences in learning may be selectively related to the tissue properties of major white matter tracts in the human brain.
Comprehensive approach to study branched ubiquitin chains reveals roles for K48-K63 branches in VCP/p97-related processes
Authors: Lange Sven M. , McFarland Matthew R. , Lamoliatte Frederic , Kwaśna Dominika , Shen Linnan , Wallace Iona , Cole Isobel , Armstrong Lee A. , Knebel Axel , Johnson Clare , De Cesare Virginia , Kulathu Yogesh 
Published: January 2023

Branched ubiquitin (Ub) chains make up a significant proportion of Ub polymers in human cells and are formed when two or more sites on a single Ub molecule are modified with Ub creating bifurcated architectures. Despite their abundance, we have a poor understanding of the cellular functions of branched Ub signals that stems from a lack of facile tools and methods to study them. Here we develop a comprehensive pipeline to define branched Ub function, using K48-K63-branched chains as a case study. We discover branch-specific binders and, by developing a method that monitors cleavage of linkages within complex polyUb, we discover the VCP/p97-associated ATXN3, and MINDY family deubiquitinases to act as debranching enzymes. By engineering and utilizing a branched K48-K63-Ub chain-specific nanobody, we reveal roles for these chains in VCP/p97-related processes. In summary, we provide a blueprint to investigate branched Ub function that can be readily applied to study other branched chain types.HighlightsAssembly of defined branched ubiquitin chains enables identification of specific binding proteinsDevelopment of quantitative DUB assay monitoring cleavage of individual Ub linkages within complex ubiquitin chains identifies debranching enzymesEngineering specific, high-affinity nanobody against branched K48-K63 ubiquitin reveals roles in VCP/p97 related processes and DNA damage responsesGeneral blueprint of new methods and tools for in-depth characterization of branched ubiquitin chains and their underlying biology
Uncovering the Dynamics of Precise Repair at CRISPR/Cas9-induced Double-Strand Breaks
Authors: Ben-Tov Daniela , Mafessoni Fabrizio , Cucuy Amit , Honig Arik , Melamed-Bessudo Cathy , Levy Avraham A. 
Published: January 2023

SummaryCRISPR/Cas9-mediated genome editing relies on error-prone repair of targeted DNA double-strand breaks (DSBs). Understanding CRISPR/Cas9-mediated DSB induction and subsequent repair dynamics requires measuring the rate of cutting and that of precise repair, a hidden-variable of the repair machinery. Here, we present a molecular and computational toolkit for multiplexed quantification of DSB intermediates and repairproducts by single-molecule sequencing. Using this approach, we characterized the dynamics of DSB induction, processing and repair at endogenous loci along a 72-hour time-course in tomato protoplasts. Combining this data with kinetic modeling reveals that indel accumulation is not an accurate reflection of DSB induction efficiency due to prominent precise re-ligation, accounting for 40-70% of all repair events. Altogether, this system exposes previously unseen flux in the DSB repair process, decoupling induction and repair dynamics, and suggesting an essential role of high-fidelity repair in limiting CRISPR editing efficiency in somatic cells.
miRCurator: A rapid curation and analysis tool for plant microRNA studies
Authors: Avşar Bihter , Aliabadi Danial Esmaeili 
Published: January 2023

AbstractPlant microRNAs (miRNAs) are tiny, non-coding RNAs that regulate the biological pathways either by inducing translational repression or messenger RNA decay. The advent of sequencing technologies increases the number of biological tools and computational methods to identify miRNAs with their targets inside the genome and transcriptome. In this study, we present a rapid curation software tool, the so-calledmiRCurator, which filters out unwanted microRNA candidates based on three significant criteria: (1) the pre-miRNA sequence should be deprived of multi-branched loops; (2) less than four mismatches on between mature miRNA and miRNA* strand are allowed; (3) no mismatches at DICER cut points are permitted on a mature miRNA strand.miRCuratoris a stand-alone user-friendly package that does not rely on cutting-edge computing platforms. We have examined our tool on different organisms, which are shown as case studies, and it was able to successfully identify all the unwanted miRNA candidates. The developed tool helps to identify genuine miRNAs and provides reliable outcomes in an automated fashion by eliminating false-positive predictions.
Evidence for an RNAi-independent role of DICER-LIKE2 in conferring growth inhibition and basal antiviral resistance
Authors: Nielsen Carsten Poul Skou , Arribas-Hernández Laura , Han Lijuan , Andersen Stig Uggerhøj , Pumplin Nathan , Brodersen Peter 
Published: January 2023

ABSTRACTHigher plants encode four DICER-LIKE (DCL) enzymes responsible for the production of small non-coding RNAs which function in RNA interference (RNAi). Different RNAi pathways in plants effect transposon silencing, antiviral defense and endogenous gene regulation.DCL2acts genetically redundantly withDCL4to confer basal antiviral defense, but in other settings,DCL2has the opposite function ofDCL4, at least in formal genetic terms. For example, knockout ofDCL4causes growth defects that are suppressed by inactivation ofDCL2. Current models maintain that the biochemical basis of both of these effects is RNAi via DCL2-dependent small interfering RNAs (siRNAs). Here, we report that neither DCL2-mediated antiviral resistance nor growth defects can be explained by silencing effects of DCL2-dependent siRNAs. Both functions are defective in genetic backgrounds that maintain high levels of DCL2-dependent siRNAs, either through specific point mutations in DCL2 or simply by reducing DCL2 dosage in plants heterozygous fordcl2knockout alleles. Intriguingly, however, all functions of DCL2 depend on it having some level of catalytic activity. We discuss this requirement for catalytic activity, but not for the resulting siRNAs, in the light of recent findings that reveal a function of DCL2 in activation of innate immunity in response to cytoplasmic double-stranded RNA.
Natural stimuli drive concerted nonlinear responses in populations of retinal ganglion cells
Authors: Karamanlis Dimokratis , Khani Mohammad H. , Schreyer Helene M. , Zapp Sören J. , Mietsch Matthias , Gollisch Tim 
Published: January 2023

AbstractThe role of the vertebrate retina in early vision is generally described by the efficient coding theory, which predicts that the retina discards spatiotemporal correlations in natural scenes. It is unclear, however, whether the predicted decorrelation in the activity of ganglion cells, the retina’s output neurons, holds under gaze shifts, which dominate the natural visual input. We here show that species-specific gaze patterns in natural stimuli can drive strong and correlated spiking responses both within and across distinct types of ganglion cells in marmoset as well as mouse retina. These concerted responses violate efficient coding and signal fixation periods with locally high spatial contrast. Finally, novel model-based analyses of ganglion cell responses to natural stimuli reveal that the observed response correlations follow from nonlinear pooling of ganglion cell inputs. Our results reveal how concerted population activity can surpass efficient coding to detect gaze-related stimulus features.
Navigation and the Efficiency of Spatial Coding: Insights from Closed-Loop Simulations
Authors: Ghazinouri Behnam , Nejad Mohammadreza Mohagheghi , Cheng Sen 
Published: January 2023

AbstractSpatial learning is critical for survival and its underlying neuronal mechanisms have been studied extensively. These studies have revealed a wealth of information about the neural representations of space, such as place cells and boundary cells. While many studies have focused on how these representations emerge in the brain, their functional role in driving spatial learning and navigation has received much less attention. We extended an existing computational modeling tool-chain to study the functional role of spatial representations using closed-loop simulations of spatial learning. At the heart of the model agent was a spiking neural network that formed a ring attractor. This network received inputs from place and boundary cells and the location of the activity bump in this network was the output. This output determined the movement directions of the agent. We found that the navigation performance depended on the parameters of the place cell input, such as their number, the place field sizes, and peak firing rate, as well as, unsurprisingly, the size of the goal zone. The dependence on the place cell parameters could be accounted for by just a single variable, the overlap index, but this dependence was nonmonotonic. By contrast, performance scaled monotonically with the Fisher information of the place cell population. Our results therefore demonstrate that efficiently encoding spatial information is critical for navigation performance.
Arabidopsis TRB proteins function in H3K4me3 demethylation by recruiting JMJ14
Authors: Wang Ming , Zhong Zhenhui , Gallego-Bartolomé Javier , Feng Suhua , Shih Yuan-Hsin , Liu Mukun , Zhou Jessica , Richey John Curtis , Ng Charmaine , Jami-Alahmadi Yasaman , Wohlschlegel James , Wu Keqiang , Jacobsen Steven E. 
Published: January 2023

AbstractArabidopsis telomeric repeat binding factors (TRBs) can bind telomeric DNA sequences to protect telomeres from degradation. TRBs can also recruit Polycomb Repressive Complex 2 (PRC2) to deposit tri-methylation of H3 lysine 27 (H3K27me3) over certain target loci. Here, we demonstrate that TRBs also associate and colocalize with JUMONJI14 (JMJ14) and trigger H3K4me3 demethylation at some loci. Thetrb1/2/3triple mutant and thejmj14-1mutant show an increased level of H3K4me3 over TRB and JMJ14 binding sites, resulting in up-regulation of their target genes. Furthermore, tethering TRBs to the promoter region of genes with an artificial zinc finger (TRB-ZF) successfully triggers target gene silencing, as well as H3K27me3 deposition, and H3K4me3 removal. Interestingly, JMJ14 is predominantly recruited to ZF off-target sites with low levels of H3K4me3, which is accompanied with TRB-ZFs triggered H3K4me3 removal at these loci. These results suggest that TRB proteins coordinate PRC2 and JMJ14 activities to repress target genes via H3K27me3 deposition and H3K4me3 removal.
Modeling and Analysis of a Cell-Free Gluconate Responsive Biosensor
Authors: Adhikari Abhinav , Murti Abhishek , Narayanan Anirudh M. , Lim Ha Eun , Varner Jeffrey D. 
Published: January 2023

AbstractCell-free synthetic systems are composed of the parts required for transcription and translation processes in a buffered solution. Thus, unlike living cells, cell-free systems are amenable to rapid adjustment of the reaction composition and easy sampling. Further, because cellular growth and maintenance requirements are absent, all resources can go toward synthesizing the product of interest. Recent improvement in key performance metrics, such as yield, reaction duration, and portability, has increased the space of possible applications open to cell-free systems and lowered the time required to design-build-test new circuitry. One promising application area is biosensing. This study describes developing and modeling a D-gluconate biosensor circuit operating in a reconstituted cell-free system. Model parameters were estimated using time-resolved measurements of the mRNA and protein concentration with and without the addition of D-gluconate. Sensor performance was predicted using the model for D-gluconate concentrations not used in model training. The model predicted the transcription and translation kinetics and the dose response of the circuit over several orders of magnitude of D-gluconate concentration. Global sensitivity analysis of the model parameters gave detailed insight into the operation of the sensor circuit. Taken together, this study reported an in-depth, systems-level analysis of a D-gluconate biosensor circuit operating in a reconstituted cell-free system. This circuit could be used directly to estimate D-gluconate or as a subsystem in a more extensive synthetic gene expression program.
Branched chain amino acid synthesis is coupled to TOR activation early in the cell cycle in yeast
Authors: Blank Heidi M. , Reuse Carsten , Schmidt-Hohagen Kerstin , Hammer Staci E. , Hiller Karsten , Polymenis Michael 
Published: January 2023

ABSTRACTHow cells coordinate their metabolism with division determines the rate of cell proliferation. Dynamic patterns of metabolite synthesis during the cell cycle are unexplored. We report the first isotope tracing analysis in synchronous, growing budding yeast cells. Synthesis of leucine, a branched-chain amino acid (BCAA), increased through the G1 phase of the cell cycle, peaking later during DNA replication. Cells lacking Bat1, a mitochondrial aminotransferase that synthesizes BCAAs, grew slower, were smaller, and were delayed in the G1 phase, phenocopying cells in which the growth-promoting kinase complex TORC1 was moderately inhibited. Loss of Bat1 lowered the levels of BCAAs and reduced TORC1 activity. Exogenous provision of BCAAs to cells lacking Bat1 promoted cell division and increased TORC1 activity. In wild-type cells, TORC1 activity was dynamic in the cell cycle, starting low in early G1 but increasing later in the cell cycle. These results suggest a link between BCAA synthesis from glucose to TORC1 activation in the G1 phase of the cell cycle.
Hypoxia-inducing cryogels uncover key cancer-immune cell interactions in an oxygen-deficient tumor microenvironment
Authors: Colombani Thibault , Rogers Zachary J. , Bhatt Khushbu , Sinoimeri James , Gerbereux Lauren , Hamrangsekachaee Mohammad , Bencherif Sidi A. 
Published: January 2023

AbstractHypoxia, an important feature of solid tumors, is a major factor shaping the immune landscape, and several cancer models have been developed to emulate hypoxic tumors. However, to date, they still have several limitations, such as the lack of reproducibility, inadequate biophysical cues, limited immune cell infiltration, and poor oxygen (O2) control, leading to non-pathophysiological tumor responses. As a result, it is essential to develop new and improved cancer models that mimic key features of the tumor extracellular matrix and recreate tumor-associated hypoxia while allowing cell infiltration and cancer-immune cell interactions. Herein, hypoxia-inducing cryogels (HICs) have been engineered using hyaluronic acid (HA) as macroporous scaffolds to fabricate three-dimensional microtissues and model a hypoxic tumor microenvironment. Specifically, tumor cell-laden HICs have been designed to deplete O2locally and induce long-standing hypoxia. This state of low oxygen tension, leading to HIF-1α stabilization in tumor cells, resulted in changes in hypoxia-responsive gene expression and phenotype, a metabolic adaptation to anaerobic glycolysis, and chemotherapy resistance. Additionally, HIC-supported tumor models induced dendritic cell (DC) inhibition, revealing a phenotypic change in plasmacytoid B220+DC (pDC) subset and an impaired conventional B220−DC (cDC) response in hypoxia. Lastly, our HIC-based melanoma model induced CD8+ T cell inhibition, a condition associated with the downregulation of pro-inflammatory cytokine secretion, increased expression of immunomodulatory factors, and decreased degranulation and cytotoxic capacity of T cells. Overall, these data suggest that HICs can be used as a tool to model solid-like tumor microenvironments and identify a phenotypic transition from cDC to pDC in hypoxia and the key contribution of HA in retaining cDC phenotype and inducing their hypoxia-mediated immunosuppression. This technology has great potential to deepen our understanding of the complex relationships between cancer and immune cells in low O2conditions and may pave the way for developing more effective therapies.
Virome analyses by next-generation sequencing (NGS) in chilli (Capsicum anuumL.) presented with diverse symptoms phenotype revealed the association of seven plant viruses
Authors: Reddy Netla Vamsidhar , Hiremath Shridhar , Muttappagol Mantesh , Vinay Kumar H. D. , Prasanna S. Koti , Mohan Kumar T. L , Jahir Basha C. R. , Shankarappa K. S. , Venkataravanappa V. , Lakshminarayana Reddy C. N. 
Published: January 2023

ABSTRACTChilli is an important vegetable and spice crop, is known to be infected by several viruses. Techniques used in diagnosis of plant viral diseases before Next-generation sequencing (NGS) are having limitation of identifying the only known viruses. In the present study, virome analyses in infected chilli leaf samples was carried out using NGS to know the diversity of both known and unknown viruses associated with diseased symptoms. For virome profiling, samples from 19 fields were collected from chilli plants showing leaf curling, vein banding, mosaic, mottling, shoestring/rat tail/filiform/leathery and dull coloured leaves. Viral disease incidence in the surveyed fields varied from 26.66% to 47.50%. Total RNA was extracted from the 19 chilli leaf samples collected from fields and were pooled at equimolar concentration for virome profiling. From the rRNA-depleted pooled total RNA, mRNA and sRNA libraries were prepared and sequenced using Illumina NOVASEQ 6000 platform. Raw sequence data obtained wasde novoassembled using three approaches; mRNAome with Trinity, sRNAome with Velvet and whole transcriptome (WT) with SPAdes assembly. Chilli virome, pairwise sequence identity and phylogenetic analyses revealed the presence of seven different viruses; chilli leaf curl virus (ChiLCV) along with its associated alpha and betasatellites, cucumber mosaic virus (CMV), groundnut bud necrosis orthotospovirus (GBNV), pepper cryptic virus-2 (PCV-2), pepper vein yellows virus (PeVYV), bell pepper alphaendornavirus (BPEV) and tobacco vein clearing virus (TVCV). From the virus associated contigs, complete/near-complete genomes for ChiLCV, CMV, PCV-2, PeVYV and BPEV and, partial genomes for GBNV and TVCV were reconstructed from the RNAome. Recombination breakpoint analyses revealed presence of recombination breakpoints in ChiLCV (coat protein and AC4 regions), CMV RNA2 (2a protein region) and P0, P3 and P5 protein regions of PeVYV. viruses identified in the current study are known to be originated from intra and interspecific recombination. Further, all the viruses detected in the pooled RNA sample were validated by PCR and loop mediated isothermal amplification (LAMP) using specific primers designed. Among the seven viruses identified in the study in chilli, PeVYV and BPEV are the first reports from India.
Organisms use mode-switching to solve the explore-vs-exploit problem
Authors: Biswas Debojyoti , Lamperski Andrew , Yang Yu , Hoffman Kathleen , Guckenheimer John , Fortune Eric S. , Cowan Noah J. 
Published: January 2023

AbstractThe inescapable link between sensing and movement generates a conflict between producing costly movements for gathering information (“explore”) versus using previously acquired information to achieve a goal (“exploit”). Determining the optimal balance between explore and exploit is a computationally intractable problem, necessitating the use of heuristics. We looked to nature to measure and model the solutions used by organisms. Here we show that the electric fishEigenmannia virescensuses a salience-dependent mode-switching strategy to solve the explore–exploit conflict during a refuge tracking task. The fish produced distinctive non-Gaussian (i.e., non-normal) distributions of movement velocities characterized by sharp peaks for slower, task-oriented “exploit” movements and broad shoulders for faster, “explore” movements. The measures of non-normality increased in relation to increased sensory salience. Data from ten phylogenetically diverse organisms, from amoebae to humans, revealed the same distinctive distribution of movement velocities that were also modulated in relation to sensory salience. We propose a state-uncertainty based mode-switching heuristic that (1) reproduces the distinctive velocity distribution, (2) rationalizes modulation by sensory salience, and (3) outperforms the classic persistent excitation approach while using less energy. This mode-switching heuristic provides insights to purposeful exploratory behaviors in organisms as well as a framework for more efficient state estimation and control of robots.