Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantification and uncertainty of root growth stimulation by elevated CO2 in mature temperate deciduous forest

Increasing CO2 levels are a major global challenge, and the extent to which increasing anthropogenic CO2 emissions can be mitigated by natural carbon sinks remains poorly understood. The uptake of elevated CO2 (eCO2) by the terrestrial biosphere, and subsequent sequestration as biomass in ecosystems, may act as a negative feedback in the carbon budget, but remains hard to quantify in natural ecosystems. Here, we combine large-scale field observations of fine root stocks and flows, derived from belowground imaging and soil cores, with image analysis, stochastic modelling, and statistical inference, to elucidate belowground root dynamics in a mature temperate deciduous forest under free-air CO2 enrichment to 150ppm above ambient levels. Using over 67k frames of belowground observation, we observe that eCO2 leads to relatively faster root production (a peak volume fold change of 4.52 ± 0.44 eCO2 versus 2.58 ± 0.21 control). We identify an increase in existing root elongation relative to root mass decay as the likely causal mechanism for this acceleration. Direct physical analysis of biomass and width measurements from 552 root systems recovered from soil cores support this picture, with lengths and widths of fine roots significantly increasing under eCO2. We use dynamic measurements to estimate fine root contributions to net primary productivity, finding an increase under eCO2, with an estimated mean annual 204 ± 93 g dw m−2yr−1 eCO2 versus 140 ± 60 g dw m−2 yr−1 control. We also quantify and discuss the uncertainties in such productivity measurements. This multi-faceted approach thus sheds quantitative light on the challenging characterisation of the eCO2 response of root biomass in mature temperate forests.
Adaptive Subsets Limit the Anti-Tumoral NK-Cell Activity in Hepatocellular Carcinoma

Background and Aims Hepatocellular carcinoma (HCC) is a global health burden with increasing incidence, poor prognosis and limited therapeutic options. Natural killer (NK) cells exhibit potent anti-tumoral activity and therefore represent potential targets for immunotherapeutic approaches in HCC treatment. However, the human NK-cell repertoire is highly diverse including conventional and adaptive NK cells that differ in phenotype and effector function. Adaptive NK-cell frequencies are increased in association with HCMV (human cytomegalovirus) seropositivity that is also common in HCC patients. In this study, we aimed to gain a better understanding of the NK-cell repertoire and the associated anti-tumoral activity in HCC patients. Methods In-depth phenotypic and functional flow-cytometry analyses of the HCMV-associated NK cell-repertoire obtained from 57 HCC patients, 33 liver cirrhosis patients and 36 healthy donors (HD). Results First, adaptive subsets are present in all three cohorts with conserved characteristics in patients with liver cirrhosis and HCC. Second, adaptive NK cells can be isolated from HCC tissue however lack features of tissue-residency and thus probably represent circulating/infiltrating lymphocytes. Third, the anti-tumoral activity by adaptive NK cells is reduced compared to conventional NK-cell subsets, also in HCC. Lastly, frequencies of adaptive NK cells were increased in patients suffering from Hepatitis B virus-associated HCC providing a link between etiology and the NK-cell repertoire in HCC. Conclusion Adaptive NK cells limit the anti-tumoral activitity of NK cells in HCC, especially in association with HBV infection that is accompanied by an expansion of this NK cell subset. Lay summary In patients with liver cancer (HCC), a subset of natural killer cells, so called adaptive NK cells show a diminished anti-tumoral activity compared to other, called conventional NK cells. Adaptive NK cells are expanded in patients with HCC associated to Hepatitis B virus infection. Thus, presence of adaptive NK cells contributes to the immune escape in HCC.
Multifunctional RNA-binding proteins influence mRNA abundance and translational efficiency of distinct sets of target genes

RNA-binding proteins (RBPs) can regulate more than a single aspect of RNA metabolism. We searched for such previously undiscovered multifunctionality within a set of 143 RBPs, by defining the predictive value of RBP abundance for the transcription and translation levels of known RBP target genes across 80 human hearts. This led us to newly associate 27 RBPs with cardiac translational regulation in vivo. Of these, 21 impacted both RNA expression and translation, albeit for virtually independent sets of target genes. We highlight a subset of these, including G3BP1, PUM1, UCHL5, and DDX3X, where dual regulation is achieved through differential affinity for target length, by which separate biological processes are controlled. Similar to the RNA helicase DDX3X, the known splicing factors EFTUD2 and PRPF8 - all identified as multifunctional RBPs by our analysis - selectively influence target translation rates depending on 5’ UTR structure. Our analyses identify dozens of RBPs as being multifunctional and pinpoint potential novel regulators of translation, postulating unanticipated complexity of protein-RNA interactions at consecutive stages of gene expression.
Regulatory phosphorylation site tunes Phosphoglucomutase 1 as a metabolic valve to control mobilization of glycogen stores

Regulation of glycogen metabolism is of vital importance in organisms of all three kingdoms of life. Although the pathways involved in glycogen synthesis and degradation are well known, many regulatory aspects around the metabolism of this polysaccharide remain undeciphered. Here, we used the unicellular cyanobacterium Synechocystis as a model to investigate how glycogen metabolism is regulated in dormant nitrogen-starved cells, which entirely rely on glycogen catabolism to restore growth. We found that the activity of the enzymes involved in glycogen synthesis and degradation is tightly controlled at different levels via post-translational modifications. Phosphorylation of phosphoglucomutase 1 (Pgm1) on a peripheral residue (Ser63) regulates Pgm1 activity and controls the mobilization of the glycogen stores. Inhibition of Pgm1 activity via phosphorylation on Ser63 appears essential for survival of Synechocystis in the dormant state. Remarkably, this regulatory mechanism seems to be conserved from bacteria to humans. Moreover, phosphorylation of Pgm1 influences the formation of a metabolon, which includes Pgm1, oxidative pentose phosphate cycle protein (OpcA) and glucose-6-phosphate dehydrogenase (G6PDH). Analysis of the steady-state levels of the metabolic products of glycogen degradation together with protein-protein interaction studies revealed that the activity of G6PDH and the formation of this metabolon are under additional redox control, likely to ensure metabolic channeling of glucose-6-phosphate to the required pathways for each developmental stage. Significance statement In this study, we showed that post-translational modification of phosphoglucomutase 1 (Pgm1) via phosphorylation at a peripheral residue is a key, evolutionary-conserved regulatory mechanism that controls the utilization of the glycogen reserves. We identified Pgm1 as a central metabolic valve, associating with oxidative pentose phosphate cycle protein (OpcA) and glucose-6-phosphate dehydrogenase (G6PDH) into a metabolon. This interaction is regulated by the phosphorylation state of Pgm1 and the redox state of OpcA, and probably allows direction of the carbon flux into the required metabolic pathways.
Selective Prefrontal–Amygdala Circuit Interactions Underlie Social and Nonsocial Valuation in Rhesus Macaques

Lesion studies in macaques suggest dissociable functions of the orbitofrontal cortex (OFC) and medial frontal cortex (MFC), with OFC being essential for goal-directed decision-making and MFC supporting social cognition. Bilateral amygdala damage results in impairments in both of these domains. There are extensive reciprocal connections between these prefrontal areas and the amygdala; however, it is not known whether the dissociable roles of OFC and MFC depend on functional interactions with the amygdala. To test this possibility, we compared the performance of male rhesus macaques (Macaca mulatta) with crossed surgical disconnection of the amygdala and either MFC (MFC × AMY, n = 4) or OFC (OFC × AMY, n = 4) to a group of unoperated controls (CON, n = 5). All monkeys were assessed for their performance on two tasks to measure the following: (1) food-retrieval latencies while viewing videos of social and nonsocial stimuli in a test of social interest and (2) object choices based on current food value using reinforcer devaluation in a test of goal-directed decision-making. Compared with the CON group, the MFC × AMY group, but not the OFC × AMY group, showed significantly reduced food-retrieval latencies while viewing videos of conspecifics, indicating reduced social valuation and/or interest. By contrast, on the devaluation task, group OFC × AMY, but not group MFC × AMY, displayed deficits on object choices following changes in food value. These data indicate that the MFC and OFC must functionally interact with the amygdala to support normative social and nonsocial valuation, respectively. SIGNIFICANCE STATEMENT Ascribing value to conspecifics (social) versus objects (nonsocial) may be supported by distinct but overlapping brain networks. Here, we test whether two nonoverlapping regions of the prefrontal cortex, the medial frontal cortex and the orbitofrontal cortex, must causally interact with the amygdala to sustain social valuation and goal-directed decision-making, respectively. We found that these prefrontal-amygdala circuits are functionally dissociable, lending support for the idea that medial frontal and orbital frontal cortex make independent contributions to cognitive appraisals of the environment. These data provide a neural framework for distinct value assignment processes and may enhance our understanding of the cognitive deficits observed following brain injury or in the development of mental health disorders.
Switch-like and persistent memory formation in individual Drosophila larvae

Associative learning allows animals to use past experience to predict future events. The circuits underlying memory formation support immediate and sustained changes in function, often in response to a single example. Larval Drosophila is a genetic model for memory formation that can be accessed at molecular, synaptic, cellular, and circuit levels, often simultaneously, but existing behavioral assays for larval learning and memory do not address individual animals, and it has been difficult to form long lasting memories, especially those requiring synaptic re-organization. We demonstrate a new assay for learning and memory capable of tracking the changing preferences of individual larvae. We use this assay to explore how activation of a pair of reward neurons changes the response to the innately aversive gas Carbon Dioxide (CO2). We confirm that when coupled to odor presentation in appropriate temporal sequence, optogenetic reward reduces avoidance of CO2. We find that learning is switch-like: all-or-none and quantized in two states. Memories can be extinguished by repeated unrewarded exposure to CO2 but are stabilized against extinction by repeated training or overnight consolidation. Finally, we demonstrate long-lasting protein synthesis dependent and independent memory formation.
Pch2 orchestrates the meiotic recombination checkpoint from the cytoplasm

During meiosis, defects in critical events trigger checkpoint activation and restrict cell cycle progression. The budding yeast Pch2 AAA+ ATPase orchestrates the checkpoint response launched by synapsis deficiency; deletion of PCH2 or mutation of the ATPase catalytic sites suppress the meiotic block of the zip1Δ mutant lacking the central region of the synaptonemal complex. Pch2 action enables adequate levels of phosphorylation of the Hop1 axial component at threonine 318, which in turn promotes activation of the Mek1 effector kinase and the ensuing checkpoint response. In zip1Δ chromosomes, Pch2 is exclusively associated to the rDNA region, but this nucleolar fraction is not required for checkpoint activation, implying that another yet uncharacterized Pch2 population must be responsible for this function. Here, we have artificially redirected Pch2 to different subcellular compartments by adding ectopic NES or NLS sequences or by trapping Pch2 in an immobile extranuclear domain, and we have evaluated the effect on Hop1 chromosomal distribution and checkpoint activity. We have also deciphered the spatial and functional impact of Pch2 regulators including Orc1, Dot1 and Nup2. We conclude that the cytoplasmic pool of Pch2 is sufficient to support the meiotic recombination checkpoint involving the subsequent Hop1-Mek1 activation on chromosomes, whereas the nuclear accumulation of Pch2 has pathological consequences. We propose that cytoplasmic Pch2 provokes a conformational change in Hop1 that poises it for its chromosomal incorporation and phosphorylation. Our discoveries shed light into the intricate regulatory network controlling the accurate balance of Pch2 distribution among different cellular compartments, which is essential for proper meiotic outcomes.
Global mismatches between crop distributions and climate suitability

The selection of new crops and the migration of crop areas are two key strategies for agriculture to cope with climate change and ensure food security in the coming years. However, both rely on the assumption that climate is a major factor determining crop distributions worldwide. Here, we show that the current global distributions of nine of twelve major crops strongly diverge from their modelled climatic suitability for yields, after controlling for technology, agricultural management and soil conditions. Comparing the climatic niches of crops and their wild progenitors reveals that climate suitability is higher outside the native climatic range for six of these nine crops while all of them are farmed predominantly in their native ranges. These results show that agricultural strategies coping with climate change will be unsuccessful unless they fully consider the social, cultural, and ecological factors underpinning crop distributions.
A3D 2.0 update for the prediction and optimization of protein solubility

Protein aggregation propensity is a property imprinted in protein sequences and structures, being associated with the onset of human diseases and limiting the implementation of protein-based biotherapies. Computational approaches stand as cost-effective alternatives for reducing protein aggregation and increasing protein solubility. AGGRESCAN 3D (A3D) is a structure-based predictor of aggregation that takes into account the conformational context of a protein, aiming to identify aggregation-prone regions exposed in protein surfaces. Here we inspect the updated 2.0 version of the algorithm, which extends the application of A3D to previously inaccessible proteins and incorporates new modules to assist protein redesign. Among these features, the new server includes stability calculations and the possibility to optimize protein solubility using an experimentally validated computational pipeline. Finally, we employ defined examples to navigate the A3D RESTful service, a routine to handle extensive protein collections. Altogether, this work is conceived to train and assist A3D non-experts in the study of aggregation-prone regions and protein solubility redesign.
Adaptive Mossy Cell Circuit Plasticity after Status Epilepticus

Hilar mossy cells regulate network function in the hippocampus through both direct excitation and di-synaptic inhibition of dentate granule cells (DGCs). Substantial mossy cell loss accompanies hippocampal circuit changes in epilepsy. We examined the contribution of surviving mossy cells to network activity in the reorganized dentate gyrus after pilocarpine-induced status epilepticus (SE). To examine functional circuit changes, we optogenetically stimulated mossy cells in acute hippocampal slices from male mice. In control mice, activation of mossy cells produced monosynaptic excitatory and di-synaptic GABAergic currents in DGCs. In pilocarpine-treated mice, mossy cell density and excitation of DGCs were reduced in parallel, with only a minimal reduction in feedforward inhibition, enhancing the inhibition/excitation ratio. Surprisingly, mossy cell-driven excitation of parvalbumin-positive (PV+) basket cells, primary mediators of feed-forward inhibition, was maintained. Our results suggest that mossy cell outputs reorganize following seizures, increasing their net inhibitory effect in the hippocampus. SIGNIFICANCE STATEMENT Hilar mossy cell loss in epilepsy is associated with hippocampal hyperexcitability, potentially as a result of disrupted dentate microcircuit function. We used transgenic mice, translational mouse modeling, viral vectors, and optogenetics to selectively examine functional changes to mossy cell outputs following status epilepticus (SE). Interestingly, the outputs of surviving mossy cells exhibited adaptive plasticity onto target parvalbumin-positive (PV+) interneurons, resulting in a relative increase in their inhibitory control of dentate granule cells (DGCs). Our findings suggest that residual mossy cell outputs can reorganize in a homeostatic manner, which may provide clues for therapeutic targeting of this microcircuit.
Photon-free (s)CMOS camera characterization for artifact reduction in high- and super-resolution microscopy

Modern implementations of widefield fluorescence microscopy often rely on sCMOS cameras, but this camera architecture inherently features pixel-to-pixel variations. Such variations lead to image artifacts and render quantitative image interpretation difficult. Although a variety of algorithmic corrections exists, they require a thorough characterization of the camera, which typically is not easy to access or perform. Here, we developed a fully automated pipeline for camera characterization based solely on thermally generated signal, and implemented it in the popular open-source software Micro-Manager and ImageJ/Fiji. Besides supplying the conventional camera maps of noise, offset and gain, our pipeline also gives access to dark current and thermal noise as functions of the exposure time. This allowed us to avoid structural bias in single-molecule localization microscopy (SMLM), which without correction is substantial even for scientific-grade, cooled cameras. In addition, our approach enables high-quality 3D super-resolution as well as live-cell time-lapse microscopy with cheap, industry-grade cameras. As our approach for camera characterization does not require any user interventions or additional hardware implementations, numerous correction algorithms that rely on camera characterization become easily applicable. Pixel-to-pixel variations in sCMOS cameras lead to image artifacts in widefield fluorescence microscopy, and algorithmic corrections require thorough camera characterization. Here, the authors present an open source automated pipeline for camera characterization based solely on thermally generated signal.
Phenotypic divergence between the cultivated apple (Malus domestica) and its primary wild progenitor (Malus sieversii)

An understanding of the relationship between the cultivated apple (Malus domestica) and its primary wild progenitor species (M. sieversii) not only provides an understanding of how apples have been improved in the past, but may be useful for apple improvement in the future. We measured 10 phenotypes in over 1000 unique apple accessions belonging to M. domestica and M. sieversii from Canada’s Apple Biodiversity Collection. Using principal components analysis (PCA), we determined that M. domestica and M. sieversii differ significantly in phenotypic space and are nearly completely distinguishable as two separate groups. We found that M. domestica had a shorter juvenile phase than M. sieversii and that cultivated trees produced flowers and ripe fruit later than their wild progenitors. Cultivated apples were also 3.6 times heavier, 43% less acidic, and had 68% less phenolic content than wild apples. Using historical records, we found that apple breeding over the past 200 years has resulted in a trend towards apples that have higher soluble solids, are less bitter, and soften less during storage. Our results quantify the significant changes in phenotype that have taken place since apple domestication, and provide evidence that apple breeding has led to continued phenotypic divergence of the cultivated apple from its wild progenitor species.
Visual search for upright bigrams predicts reading fluency in children

Fluent reading is an important milestone in education, but we lack a clear understanding of why children vary so widely in attaining this milestone. Language-related factors such as rapid automatized naming (RAN) and phonological awareness have been identified as important factors that influence reading fluency. Of theoretical interest is also, however, whether aspects of visual processing influence reading fluency. To investigate this issue, we tested primary school children (n = 68) on four tasks: two reading fluency tasks (word reading and passage reading), a RAN task to measure naming speed, and a visual search task using letters and bigrams to measure visual processing. As expected, the RAN score was strongly correlated with reading fluency. In addition, visual processing of bigrams was correlated with reading fluency. Importantly, this association was specific to upright but not inverted bigrams, and to bigrams with normal but not large letter spacing. Thus, reading fluency in children is accompanied by specialized changes in upright bigram processing. We propose that bigram processing during visual search could complement existing measures of language processing to understand individual differences in reading fluency.
Enabling the execution of large scale workflows for molecular dynamics simulations

The usage of workflows has led to progress in many fields of science, where the need to process large amounts of data is coupled with difficulty in accessing and efficiently using High Performance Computing platforms. On the one hand, scientists are focused on their problem and concerned with how to process their data. On top of that, the applications typically have different parts and use different tools for each part, thus complicating the distribution and the reproducibility of the simulations. On the other hand, computer scientists concentrate on how to develop frameworks for the deployment of workflows on HPC or HTC resources; often providing separate solutions for the computational aspects and the data analytic ones. In this paper we present an approach to support biomolecular researchers in the development of complex workflows that i) allow them to compose pipelines of individual simulations built from different tools and interconnected by data dependencies, ii) run them seamlessly on different computational platforms, and iii) scale them up to the large number of cores provided by modern supercomputing infrastructures. Our approach is based on the orchestration of computational building blocks for Molecular Dynamics simulations through an efficient workflow management system that has already been adopted in many scientific fields to run applications on multitudes of computing backends. Results demonstrate the validity of the proposed solution through the execution of massively parallel runs in a supercomputer facility.