Miracle-dz/UniFAR-FTUs huggingface dataset:
Inactivation of posterior but not anterior dorsomedial caudate-putamen impedes learning with self-administered nicotine stimulus

The rodent caudate-putamen is a large heterogeneous neural structure with distinct anatomical connections that differ in their control of learning processes. Previous research suggests that the anterior and posterior dorsomedial caudate-putamen (a- and p-dmCPu) differentially regulate associative learning with a non-contingent nicotine stimulus. The current study used bilateral NMDA-induced excitotoxic lesions to the a-dmCPu and p-dmCPu to determine the functional involvement of a-dmCPu and p-dmCPu in appetitive learning with contingent nicotine stimulus. Rats with a-dmCPu, p-dmCPu, or sham lesions were trained to lever-press for intravenous nicotine (0.03 mg/kg/inf) followed by access to sucrose 30 s later. After 1, 3, 9, and 20 nicotine-sucrose training sessions, appetitive learning in the form of a goal-tracking response was assessed using a non-contingent nicotine-alone test. All rats acquired nicotine self-administration and learned to retrieve sucrose from a receptacle at equal rates. However, rats with lesions to p-dmCPu demonstrated blunted learning of the nicotine-sucrose association. Our primary findings show that rats with lesions to p-dmCPu had a blunted goal-tracking response to a non-contingent nicotine administration after 20 consecutive days of nicotine-sucrose pairing. Our findings extend previous reports to a contingent model of nicotine self-administration and show that p-dmCPu is involved in associative learning with nicotine stimulus using a paradigm where rats voluntarily self-administer nicotine infusions that are paired with access to sucrose—a paradigm that closely resembles learning processes observed in humans.
Maintaining robust size across environmental conditions is achieved through plastic growth dynamics in the central nervous system of Drosophila melanogaster

Organ growth is tightly regulated across environmental conditions to generate appropriate final size. While the size of some organs is free to vary, others need to maintain constant size to function properly. This poses a unique problem: how is robust final size achieved when environmental conditions alter the rates and the duration of growth? Brain growth is known to be “spared” from the effects of the environment from humans to fruit flies. Here, we explore how this robustness in brain size is achieved by examining differences in growth dynamics between the larval body, the brain, and the mushroom bodies – a brain compartment – in Drosophila melanogaster across thermal and nutritional conditions. We identify key differences in patterns of growth between the whole brain and mushroom bodies, as well as differences in the signalling pathways implicated, that are likely to underlie robustness of final organ shape. Further, we show that these differences produce distinct brain shapes across environments.
Identifying seaweeds species of Chlorophyta, Ochrophyta and Rhodophyta using DNA barcodes

Strengthening the DNA barcode database is important for a species level identification, which was lacking for seaweeds. We made an effort to collect and barcode seaweeds occurring along Southeast coast of India. We barcoded 31 seaweeds species belonging to 21 genera, 14 family, 12 order of 3 phyla (viz., Chlorophyta, Ochrophyta and Rhodophyta). We found 10 species in 3 phyla and 2 genera (Anthophycus and Chnoospora) of Ochrophyta were barcoded for the first time. Uncorrected p-distance calculated using K2P, nucleotide diversity and Tajima’s test statistics reveals highest values among the species of Chlorophyta. Over all K2P distance was 0.36. The present study revealed the potentiality of rbcL gene sequences in identification of all 3 phyla of seaweeds. We also found that the present barcode reference libraries (GenBank and BOLD) were insufficient in seaweeds identification and more efforts were needed for strengthening local seaweed barcode library to benefit rapids developing field such as environmental DNA barcoding. We also show that the constructed barcode library could aid various industrial experts involved in seaweed bio-resource exploration and taxonomy/non-taxonomic researches involved in climate, agriculture and epigenetics research in precise seaweed identification. Since the rise of modern high-throughput sequencing technologies is significantly altering bio-monitoring applications and surveys, reference datasets such as ours will become essential in ecosystem’s health assessment and monitoring.
The rhizosphere metabolome triggers species-specific and context-dependent root responses in later arriving plants

Priority effects can have long-lasting consequences for the structure and functioning of plant communities. Currently, it is poorly understood to what extent the rhizo-sphere metabolome of plant communities is conditioned by its species composition and whether these changes affect subsequent species during assembly. We collected soil solutions from plant communities differing in species and functional group composition (forbs or grasses). We evaluated the effect of the rhizosphere metabolome found in the soil solutions on the growth, biomass allocation, and functional traits of a forb (Dianthus deltoides) and a grass species (Festuca rubra). The rhizosphere metabolome of forb and grass communities differed in composition and chemical diversity. While F. rubra did not respond to different rhizosphere solutions, soil exploration by D. deltoides roots decreased when plants received the rhizosphere solution from a grass or a forb community. Structural equation modelling showed that reduced soil exploration by D. deltoides arose via either a root growth-dependent pathway (forb metabolome) or a root trait-dependent pathway (grass metabolome). Reduced soil exploration was not connected to a decrease in total N uptake. Our findings reveal that rhizosphere chemical cues can affect later arriving plants and create belowground priority effects in grasslands.
Gains and Losses Differentially Regulate Attentional Efficacy and Learning at Low and High Attentional Load

Visual attention involves both enhancing the processing of stimuli that may lead to reward and avoiding the processing of stimuli that may lead to loss. But compared to reward expectancy little is known how loss-avoidance mediates attention. One hypothesis holds that attention is more efficiently deployed when expecting larger gains and larger losses as both increase motivational saliency. Alternatively, expecting larger penalties might reduce attentional efficacy and ‘loom’ larger than gains. Here, we tested these opposing views in four monkeys with a feature-token learning task that quantifies attentional efficacy by increasing distractor load from multidimensional objects. During learning the number of token rewards gained for correct choices and lost for incorrect choices were varied. We found that expecting larger gains improves attentional efficacy and learning speed as long as distractor load was low. In contrast, expecting larger losses impairs attentional efficacy and this impairment increases with distractor load and uncertainty about the relevance of visual features. These findings functionally dissociate the contributions of expecting gains and losses on attentional learning, suggesting that they operate via separate control pathways. One pathway is linked to avoiding loss by slowing down learning and disrupting attention non-selectively, while the second pathway enhances learning selectively for higher valued target features up to a limited distractor load. These results illustrate the strength and the limitation of motivational regulation of attentional efficacy during learning. Significance statement Visual attention is biased to objects promising higher expected gains, but it should likewise be biased to avoid processing objects associated with incurring a loss. Clarifying the roles of gains and losses to modulate attention is critical for understanding the possible neuronal processes that determine how efficient attention is deployed in real-world learning scenarios. This study clarifies that gains and losses have surprisingly strong, opposite effects on the efficacy of attentional deployment in environments with low and high distractor load. Attentional efficacy is enhanced with increased gains primarily when there are few distractors, while attentional efficacy is impaired with increased loss expectancy particularly when there are many distractors. These results clarify that avoiding loss and striving for gains affect attentional efficacy via partly distinct mechanisms.
Genomic analyses of two Italian oyster mushroom Pleurotus pulmonarius strains

Pleurotus mushrooms are among the most cultivated fungi in the world and are highly valuable for food, medicine and biotechnology industries. Furthermore, Pleurotus species are carnivorous fungi; they can rapidly paralyze and kill nematodes when nutrient-deprived. The predator-prey interactions between Pleurotus and nematodes are still widely unexplored. Moreover, the molecular mechanisms and the genes involved in the carnivorous behavior of Pleurotus mushrooms remain a mystery. We are attempting to understand the interactions between Pleurotus mushrooms and their nematode prey through genetic and genomic analyses. Two single spores (ss2 and ss5) isolated from a fruiting body of Pleurotus pulmonarius exhibited significant differences in growth and toxicity against nematodes. Thus, using PacBio long reads, we assembled and annotated two high-quality genomes for these two isolates of Pleurotus pulmonarius. Each of these assemblies contains 23 scaffolds, including 6 (ss2) and 8 (ss5) telomere-to-telomere scaffolds, and they are among the most complete assembled genomes of the Pleurotus species. Comparative analyses identified the genomic differences between the two P. pulmonarius strains. In sum, this work provides a genomic resource that will be invaluable for better understanding the Italian oyster mushroom P. pulmonarius.
Genome-wide signatures of plastid-nuclear coevolution point to repeated perturbations of plastid proteostasis systems across angiosperms

Nuclear and plastid (chloroplast) genomes experience different mutation rates, levels of selection, and transmission modes, yet key cellular functions depend on coordinated interactions between proteins encoded in both genomes. Functionally related proteins often show correlated changes in rates of sequence evolution across a phylogeny (evolutionary rate covariation or ERC), offering a means to detect previously unidentified suites of coevolving and cofunctional genes. We performed phylogenomic analyses across angiosperm diversity, scanning the nuclear genome for genes that exhibit ERC with plastid genes. As expected, the strongest hits are highly enriched for plastid-targeted proteins, providing evidence that cytonuclear interactions affect rates of molecular evolution at genome-wide scales. Many identified nuclear genes function in post-transcriptional regulation and the maintenance of protein homeostasis (proteostasis), including protein translation (in both the plastid and cytosol), import, quality control and turnover. We also identified nuclear genes that exhibit strong signatures of coevolution with the plastid genome but lack organellar-targeting annotations, making them candidates for having previously undescribed roles in plastids. In sum, our genome-wide analyses reveal that plastid- nuclear coevolution extends beyond the intimate molecular interactions within chloroplast enzyme complexes and may be driven by frequent rewiring of the machinery responsible for maintenance of plastid proteostasis in angiosperms.
A novel microcosm for recruiting inherently competitive biofertilizer-candidate microorganisms from soil environments

Fertilizer phosphorus (P) is both a necessary crop nutrient and finite resource, necessitating the development of innovative solutions for P fertilizer efficiency and recycling in agricultural systems. Myo-inositol hexakisphosphate (phytate) and its lower order derivatives constitute the majority of identified organic P in many soil types and has been shown to accumulate with increasing application of P fertilizer. Phytate is only poorly available to plants, and in alkaline soils it often precipitated as even more unavailable calcium (Ca)-phytate. Incorporating phytase-producing biofertilizers (i.e., microbial-based products with capacity to mineralize phytate) into soil presents a viable and environmentally acceptable way of utilizing P from phytate, whilst reducing the need for mineral P application. Here we present an in-soil microcosm that utilizes precipitated Ca-phytate to recruit microorganisms with degradation activity towards phytate in solum. Our results show both direct and indirect evidence for Ca-phytate mineralization in vitro and in solum. Furthermore, the abundance of bacteria recruited was measured via 16S rRNA gene copy number, as was three genes relating to organic P degradation; phoX and phoD phosphatases and the BPP (β-propeller phytase) gene. Amplicon sequencing as well as BioLog catabolism studies show that microcosm treatments containing the ‘bait’ Ca-phytate, recruited a different set of microorganisms when compared to controls. These Ca-phytate microcosms recruited mainly Actinobacteria, Firmicutes, and Proteobacteria, and the genus Streptomyces was specifically enriched. We conclude that our microcosm presents an innovative approach for isolating soil microorganisms with the potential to degrade precipitated phytate in solum and represents a new isolation method with the potential to isolate inherently robust biofertilizer candidates directly from target soils.
Prophylactic Application of Tailocins Prevents Infection by Pseudomonas syringae

Tailocins are phage-derived bacteriocins that demonstrate great potential as agricultural antimicrobials given their high killing efficiency and their precise strain-specific targeting ability. Our group has recently categorized and characterized tailocins produced by and tailocin sensitivities of the phytopathogen Pseudomonas syringae, and here we extend these experiments to test whether prophylactic tailocin application can prevent infection of Nicotiana benthamiana by P. syringae pv. syringae B728a. Specifically, we demonstrate that multiple strains can produce tailocins that prevent infection by strain B728a and engineer a deletion mutant to prove that tailocin targeting is responsible for this protective effect. Lastly, we provide evidence that heritable resistance mutations do not explain the minority of cases where tailocins fail to prevent infection. Our results extend previous reports of prophylactic use of tailocins against phytopathogens, and establish a model system with which to test and optimize tailocin application for prophylactic treatment to prevent phytopathogen infection.
Crucial Role of ppGpp in the Resilience of Escherichia coli to Growth Disruption

The capacity of microbes to resist and overcome environmental insults, known as resilience, allows them to survive in changing environments but also to resist antibiotic and biocide treatments and immune system responses. Although the role of the stringent response in bacterial resilience to nutritional stresses has been well studied, little is known about its importance in the ability of the bacteria to not just resist but also recover from these disturbances. ABSTRACT Bacteria grow in constantly changing environments that can suddenly become completely depleted of essential nutrients. The stringent response, a rewiring of the cellular metabolism mediated by the alarmone (p)ppGpp, plays a crucial role in adjusting bacterial growth to the severity of the nutritional stress. The ability of (p)ppGpp to trigger a slowdown of cell growth or induce bacterial dormancy has been widely investigated. However, little is known about the role of (p)ppGpp in promoting growth recovery after severe growth inhibition. In this study, we performed a time-resolved analysis of (p)ppGpp metabolism in Escherichia coli as it recovered from a sudden slowdown in growth. The results show that E. coli recovers by itself from the growth disruption provoked by the addition of serine hydroxamate, the serine analogue that we used to induce the stringent response. Growth inhibition was accompanied by a severe disturbance of metabolic activity and, more surprisingly, a transient overflow of valine and alanine. Our data also show that ppGpp is crucial for growth recovery since in the absence of ppGpp, E. coli’s growth recovery was slower. In contrast, an increased concentration of pppGpp was found to have no significant effect on growth recovery. Interestingly, the observed decrease in intracellular ppGpp levels in the recovery phase correlated with bacterial growth, and the main effect involved in the return to the basal level was identified by flux calculation as growth dilution. This report thus significantly expands our knowledge of (p)ppGpp metabolism in E. coli physiology. IMPORTANCE The capacity of microbes to resist and overcome environmental insults, known as resilience, allows them to survive in changing environments but also to resist antibiotic and biocide treatments and immune system responses. Although the role of the stringent response in bacterial resilience to nutritional stresses has been well studied, little is known about its importance in the ability of the bacteria to not just resist but also recover from these disturbances. To address this important question, we investigated growth disruption resilience in the model bacterium Escherichia coli and its dependence on the stringent response alarmone (p)ppGpp by quantifying ppGpp and pppGpp levels as growth was disrupted and then recovered. Our findings may thus contribute to understanding how ppGpp improves E. coli’s resilience to nutritional stress and other environmental insults.
Assessing the Inflation Hedging Ability of Timberland Assets in the United States

: Inflation hedging is one of the unique features of timberland assets that attract timberland investors. This study uses Fisher hypothesis and capital asset pricing model under inflation to analyze how effectively private- and public-equity timberland assets hedge actual, expected, and unexpected inflation in the United States over 1987 to 2009. Rolling regression is used to evaluate whether timberland assets can persistently hedge inflation, whereas the state space model is used to examine the time-varying inflation hedging ability. Empirical results suggest that private-equity timberland assets do hedge actual, expected, and unexpected inflation, whereas public-equity timberland assets are not consistent in hedging actual, expected, or unexpected inflation. Hedging effectiveness depends on the state of the economy. We find that private-equity timberland assets are effective in hedging inflation during the boom and less effective during the recession. Investment horizon also plays a significant role in timberland inflation hedging. The longer people invest in the private-equity timberland assets, the stronger and more consistent the hedging ability holds. F OR . S CI . 59(1):93–104.
Support for the Adaptive Decoupling Hypothesis from Whole-Transcriptome Profiles of a Hypermetamorphic and Sexually Dimorphic Insect, Neodiprion lecontei

Though seemingly bizarre, the dramatic post-embryonic transformation that occurs during metamorphosis is one of the most widespread and successful developmental strategies on the planet. The adaptive decoupling hypothesis (ADH) proposes that metamorphosis is an adaptation for optimizing expression of traits across life stages that experience opposing selection pressures. Similarly, sex-biased expression of traits is thought to evolve in response to sexually antagonistic selection. Both hypotheses predict that traits will be genetically decoupled among developmental stages and sexes, but direct comparisons between stage-specific and sex-specific decoupling are rare. Additionally, tests of the ADH have been hampered by a lack of suitable traits for among-stage comparisons and by uncertainties regarding how much decoupling is to be expected. To fill these voids, we characterize transcriptome-wide patterns of gene-expression decoupling in the hypermetamorphic and sexually dimorphic insect, Neodiprion lecontei. This species has three ecologically and morphologically distinct larval stages separated by molts, as well as a complete metamorphic transition that produces dimorphic adult males and females. Consistent with the ADH, we observe that: (1) the decoupling of gene expression becomes more pronounced as the ecological demands of developmental stages become more dissimilar and (2) gene-expression traits that mediate changing ecological interactions show stronger and more variable decoupling than expression traits that are likely to experience more uniform selection. We also find that gene-expression decoupling is more pronounced among major life stages than between the sexes. Overall, our results demonstrate that patterns of gene-expression decoupling can be predicted based on gene function and organismal ecology.
NECo: A node embedding algorithm for multiplex heterogeneous networks

Complex diseases such as hypertension, cancer, and diabetes cause nearly 70% of the deaths in the U.S. and involve multiple genes and their interactions with environmental factors. Therefore, identification of genetic factors to understand and decrease the morbidity and mortality from complex diseases is an important and challenging task. With the generation of an unprecedented amount of multi-omics datasets, network-based methods have become popular to represent the multilayered complex molecular interactions. Particularly node embeddings, the low-dimensional representations of nodes in a network are utilized for gene function prediction. Integrated network analysis of multi-omics data alleviates the issues related to missing data and lack of context-specific datasets. Most of the node embedding methods, however, are unable to integrate multiple types of datasets from genes and phenotypes. To address this limitation, we developed a node embedding algorithm called Node Embeddings of Complex networks (NECo) that can utilize multilayered heterogeneous networks of genes and phenotypes. We evaluated the performance of NECo using genotypic and phenotypic datasets from rat (Rattus norvegicus) disease models to classify hypertension disease-related genes. Our method significantly outperformed the state-of-the-art node embedding methods, with AUC of 94.97% compared 85.98% in the second-best performer, and predicted genes not previously implicated in hypertension. Availability and implementation The source code is available on GitHub at https://github.com/bozdaglab/NECo.
Two voltage-dependent currents can explain the functional diversity of embryonic Renshaw cells

Spontaneous neuronal activity occurs at the onset of the synaptogenesis in the central Nervous System and plays a major role in shaping developing neural networks. How intrinsic properties of neurons evolve during this critical developmental period remains largely unknown. We studied the Renshaw cells because they participate to the early-synchronized neuronal activity in the embryonic spinal cord. We found that these interneurons are subdivided into several functional clusters at the onset of the synaptogenesis and then display a transitory involution process during which they lose their ability to sustain tonic firing. This complex developmental trajectory results from the synergy between a persistent sodium inward current and a delayed rectifier potassium outward current, which are present in most neurons during development and in the adult. Taken together, our results reveal a core mechanism producing functional hetereogeneity in embryonic neurons and likely shaping the ongoing of early spontaneous neuronal activity.