Miracle-dz/UniFAR-FTUs huggingface dataset:
Why species richness of plants and herbivorous insects do or do not correlate

Unraveling the determinants of herbivorous insect diversity has been a major challenge in ecology. Despite the strong association between insect and plant species, previous studies conducted in natural systems have shown great variation in the strength of the correlation between their species richness. Such variation can be attributed to the proportion of generalist insect species (generality), though both higher and lower generality may weaken the correlation because 1) generalist insect species are less dependent on the number of plant species and 2) specialist insect species utilize only a part of the total plant species. To explore these opposing effects, we studied plant and herbivorous insect communities in semi-natural grasslands in Japan. Plant–insect interactions were evaluated in a unique way with a particular focus on the staying and herbivory behaviors of insects, which reflect their habitat use as well as host use. We fousnd that generality of insect communities negatively affected the correlation between species richness of plants and insects. However, such negative effect was significant only when the insect species richness was related with the number of plant species interacted with some insect species, instead of with that of total plant species. The results suggest that considering either of the opposing effects of insect generality is insufficient and they should be inclusively interpreted to understand the relationship between plant and insect species richness.
Volatile allosteric antagonists of mosquito odorant receptors inhibit normal odor-dependent behaviors

Odorant-dependent behaviors in insects are triggered by the binding of odorant ligands to the variable subunits of heteromeric olfactory receptors. Previous studies have shown, however, that specific odor binding to ORco, the common subunit of odorant receptor heteromers, may alter allosterically olfactory receptor function and affect profoundly subsequent behavioral responses. Here we report on the identification of several antagonists of the odorant receptor co-receptor of the African malaria vector Anopheles gambiae, AgamORco, in a small collection of natural volatile organic compounds (VOCs) using a relevant insect cell-based screening platform. Because some of the identified antagonists were previously shown to strongly repel Anopheles and Culex mosquitoes, here we examined the bioactivities of the identified antagonists against Aedes, the third major genus of the Culicidae family. The tested antagonists were found to inhibit the function of Ae. aegypti ORco ex vivo and repel Asian tiger, Ae. albopictus, adult mosquitoes. Specific antagonist binary mixtures elicited higher repellency than single antagonists. Binding competition assays suggested antagonist binding to distinct ORco sites as a likely cause for the enhanced repellence of the blends. These findings demonstrate that a simple screening assay may be used for the identification of allosteric modifiers of olfactory-driven behaviors capable of providing enhanced indoor and outdoor protection against multiple mosquito borne infectious diseases.
Developmental co-emergence of cardiac and gut tissues modeled by human iPSC-derived organoids

During embryogenesis, paracrine signaling between tissues in close proximity contributes to the determination of their respective cell fate(s) and development into functional organs. Organoids are in vitro models that mimic organ formation and cellular heterogeneity, but lack the paracrine input of surrounding tissues. Here, we describe a human multilineage iPSC-derived organoid that recapitulates cooperative cardiac and gut development and displays extensive cellular and structural complexity of both tissues. We demonstrate that the presence of endoderm tissue (gut/intestine) in multilineage organoids contributed to the development of the cardiac tissue, specifically cardiomyocyte expansion, compartmentalization, enrichment of atrial/nodal cells, myocardial compaction and functional fetal-like maturation. Overall, this study demonstrates the ability to generate specific cooperative tissues originating from different germ lineages within a single organoid model, an advance that will further the examination of multi-tissue interactions during development and disease.
Structural and functional alterations associated with the LRRK2 G2019S mutation revealed in structured human neural networks

Mutations in the LRRK2 gene have been widely linked to Parkinson’s disease. The G2019S variant has been shown to contribute uniquely to both familial and sporadic forms of the disease. LRRK2-related mutations have been extensively studied, yet the wide variety of cellular and network events directly or indirectly related to these mutations remain poorly understood. In this study, we structured multi-nodal human neural networks carrying the G2019S mutation using custom-designed microfluidic chips coupled to microelectrode-arrays. By applying live imaging approaches, immunocytochemistry and computational modelling, we have revealed alterations in both the structure and function of the resulting neural networks when compared to controls. We provide first evidence of increased neuritic density associated with the G2019S LRRK2 mutation, while previous studies have found either a strong decrease, or no change, compared to controls. Additionally, we corroborate previous findings regarding increased baseline network activity compared to control neural networks. Furthermore, we can reveal additional network alterations attributable to the specific mutation by selectively inducing transient overexcitation to confined parts of the structured multi-nodal networks. These alterations, which we were able to capture both at the micro- and mesoscale manifested as differences in relative network activity and correlation, as well as in mitochondria activation, neuritic remodelling, and synaptic alterations. Our study thus provides important new insights into early signs of neural network pathology significantly expanding upon the current knowledge relating to the G2019S Parkinson’s disease mutation.
A model explaining mRNA level fluctuations based on activity demands and RNA age

Cellular RNA levels are usually fluctuated and are affected by many factors. However, knowledge on the fundamental relationships between RNA abundance, environmental stimuli, and RNA activities is lacking, and the effects of RNA age on RNA levels remain unknown. A model based on activity demands and RNA age was developed to explore the mechanisms of RNA level fluctuations. With single cell time-series gene expression experimental data, we could assess transcription rates, RNA degradation rates, RNA life spans, RNA demands, accumulated transcription amounts, and accumulated RNA degradation amounts by this model. The model could also predict RNA levels under simulation backgrounds, such as stimuli leading to regular oscillations in RNA abundance, stable RNA levels over time being resulted from the long shortage of total RNA activity or uncontrollable transcription, and relationship between RNA levels and protein levels. Given explaining partly mechanisms of some RNA level fluctuations by the present model, further proves and suitable applications are expected.
The prolyl hydroxylase PHD3 maintains β-cell glucose metabolism during fatty acid excess

The alpha ketoglutarate-dependent dioxygenase, prolyl-4-hydroxylase 3 (PHD3), is a hypoxia-inducible factor target that uses molecular oxygen to hydroxylate proline. While PHD3 has been reported to influence cancer cell metabolism and liver insulin sensitivity, relatively little is known about effects of this highly conserved enzyme in insulin-secreting β-cells. Here, we show that deletion of PHD3 specifically in β-cells (βPHD3KO) is associated with impaired glucose homeostasis in mice fed high fat diet. In the early stages of dietary fat excess, βPHD3KO islets energetically rewire, leading to defects in the management of pyruvate fate and a shift away from glycolysis. However, βPHD3KO islets are able to maintain oxidative phosphorylation and insulin secretion by increasing utilization of fatty acids to supply the tricarboxylic acid cycle. This nutrient-sensing switch cannot be sustained and βPHD3KO islets begin to show signs of failure in response to prolonged metabolic stress, including impaired glucose-stimulated ATP/ADP rises, Ca2+ fluxes and insulin secretion. Thus, PHD3 might be a pivotal component of the β-cell glucose metabolism machinery by suppressing the use of fatty acids as a primary fuel source, under obesogenic and insulin resistant states. SIGNIFICANCE STATEMENT Prolyl-4-hydroxylase 3 (PHD3) is involved in the oxygen-dependent regulation of cell phenotype. A number of recent studies have shown that PHD3 might operate at the interface between oxygen availability and metabolism. To understand how PHD3 influences insulin secretion, which depends on intact glucose metabolism, we generated mice lacking PHD3 specifically in pancreatic β-cells. These mice, termed βPHD3KO, are apparently normal until fed high fat diet at which point their β-cells switch to fatty acids as a fuel source. This switch cannot be tolerated and β-cells in βPHD3KO mice eventually fail. Thus, PHD3 maintains glucose-stimulated insulin secretion in β-cells during states of fatty acid excess, such as diabetes and obesity.
Cortical and subcortical hemodynamic changes during human sleep slow waves

EEG slow waves, the hallmarks of NREM sleep, are closely linked to the restorative function of sleep and their regional cortical distribution reflects plasticity- and learning-related processes. Here we took advantage of simultaneous EEG-fMRI recordings to map cortical and subcortical hemodynamic (BOLD) fluctuations time-locked to sleep slow waves. Recordings were performed in twenty healthy adults during an afternoon nap. Slow waves were associated with BOLD-signal increases in the brainstem and in portions of thalamus and cerebellum characterized by preferential functional connectivity with limbic and somatomotor areas, respectively. At the cortical level, significant BOLD-signal decreases were found in several areas, including insula and somatomotor cortex, and were preceded by slow signal increases that peaked around slow-wave onset. EEG slow waves and BOLD fluctuations showed similar cortical propagation patterns, from centro-frontal to temporo-occipital cortices. These regional patterns of hemodynamic-electrical coupling are consistent with theoretical accounts of the functions of sleep slow waves.
Inside-out regulation of E-cadherin conformation and adhesion

Significance Cadherin cell–cell adhesion proteins play key roles in the formation and maintenance of tissues. Their adhesion is carefully regulated to orchestrate complex movement of cells. While cadherin ectodomains bind in two conformations with different adhesive properties, the mechanisms by which cells regulate the conformation (and consequently adhesion) of individual cadherins are unknown. Here, we demonstrate that the association of intracellular vinculin with the cadherin cytoplasmic region regulates cadherin adhesion by switching ectodomains from a weak binding to the strongly adhesive conformation. In contrast to the prevailing view which suggests that vinculin regulates adhesion solely by remodeling the cytoskeleton, we show that vinculin can directly modulate single cadherin ectodomain conformation and this process is mediated by changes in cytoskeletal tension. Cadherin cell–cell adhesion proteins play key roles in tissue morphogenesis and wound healing. Cadherin ectodomains bind in two conformations, X-dimers and strand-swap dimers, with different adhesive properties. However, the mechanisms by which cells regulate ectodomain conformation are unknown. Cadherin intracellular regions associate with several actin-binding proteins including vinculin, which are believed to tune cell–cell adhesion by remodeling the actin cytoskeleton. Here, we show at the single-molecule level, that vinculin association with the cadherin cytoplasmic region allosterically converts weak X-dimers into strong strand-swap dimers and that this process is mediated by myosin II–dependent changes in cytoskeletal tension. We also show that in epithelial cells, ∼70% of apical cadherins exist as strand-swap dimers while the remaining form X-dimers, providing two cadherin pools with different adhesive properties. Our results demonstrate the inside-out regulation of cadherin conformation and establish a mechanistic role for vinculin in this process.
Gliding motility of Plasmodium merozoites

Significance Plasmodium malaria parasites use a unique substrate-dependent locomotion, termed gliding motility, to migrate through tissues and invade cells. Previously, it was thought that the small labile invasive stages that invade erythrocytes, merozoites, use this motility solely to penetrate target erythrocytes. Here we reveal that merozoites use gliding motility for translocation across host cells prior to invasion. This forms an important preinvasion step that is powered by a conserved actomyosin motor and is regulated by a complex signaling pathway. This work broadens our understanding of the role of gliding motility and invasion in the blood and will have a significant impact on our understanding of blood stage host–pathogen interactions and parasite biology, with implications for interventions targeting erythrocyte invasion. Plasmodium malaria parasites are obligate intracellular protozoans that use a unique form of locomotion, termed gliding motility, to move through host tissues and invade cells. The process is substrate dependent and powered by an actomyosin motor that drives the posterior translocation of extracellular adhesins which, in turn, propel the parasite forward. Gliding motility is essential for tissue translocation in the sporozoite and ookinete stages; however, the short-lived erythrocyte-invading merozoite stage has never been observed to undergo gliding movement. Here we show Plasmodium merozoites possess the ability to undergo gliding motility in vitro and that this mechanism is likely an important precursor step for successful parasite invasion. We demonstrate that two human infective species, Plasmodium falciparum and Plasmodium knowlesi, have distinct merozoite motility profiles which may reflect distinct invasion strategies. Additionally, we develop and validate a higher throughput assay to evaluate the effects of genetic and pharmacological perturbations on both the molecular motor and the complex signaling cascade that regulates motility in merozoites. The discovery of merozoite motility provides a model to study the glideosome and adds a dimension for work aiming to develop treatments targeting the blood stage invasion pathways.
Temporal Dysbiosis of Infant Nasal Microbiota Relative to Respiratory Syncytial Virus Infection

Rationale Respiratory Syncytial Virus (RSV) infection is a leading cause of infant respiratory disease and hospitalization. Infant airway microbiota occupying the nasopharynx have been associated with respiratory disease risk and severity. The extent to which interactions between RSV and microbiota occur in the airway, and their impact on respiratory disease severity and infection susceptibility, are not well understood. Objectives To characterize associations between the nasal microbiota and RSV infection before, during, and after infants’ first respiratory illness. Methods Nasal 16S rRNA microbial community profiling of two cohorts of infants in the first year of life: 1) a cross-sectional cohort of 89 RSV infected infants sampled during illness and 102 population matched healthy controls, and 2) an individually matched longitudinal cohort of 12 infants who developed RSV infection and 12 who did not, sampled at time points before, during, and after infection. Measurements and Main Results We identified 12 taxa significantly associated with RSV infection. All 12 were differentially abundant during infection, with seven differentially abundant prior to infection, and eight differentially abundant after infection. Eight of these taxa were associated with disease severity. Nasal microbiota composition was more discriminative of healthy vs. infected than of disease severity. Conclusions Our findings elucidate the chronology of nasal microbiota dysbiosis and suggest an altered developmental trajectory associated with first-time RSV infection. Microbial temporal dynamics reveal indicators of disease risk, correlates of illness and severity, and the impact of RSV infection on microbiota composition. Identified taxa represent appealing targets for additional translationally-oriented research.
Comparative Transcriptome Analysis Reveals the Intensive Early Stage Responses of Host Cells to SARS-CoV-2 Infection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a widespread outbreak of highly pathogenic COVID-19. It is therefore important and timely to characterize interactions between the virus and host cell at the molecular level to understand its disease pathogenesis. To gain insights, we performed high-throughput sequencing that generated time-series data simultaneously for bioinformatics analysis of virus genomes and host transcriptomes implicated in SARS-CoV-2 infection. Our analysis results showed that the rapid growth of the virus was accompanied by an early intensive response of host genes. We also systematically compared the molecular footprints of the host cells in response to SARS-CoV-2, SARS-CoV and MERS-CoV. Upon infection, SARS-CoV-2 induced hundreds of up-regulated host genes hallmarked by a significant cytokine production followed by virus-specific host antiviral responses. While the cytokine and antiviral responses triggered by SARS-CoV and MERS-CoV were only observed during the late stage of infection, the host antiviral responses during the SARS-CoV-2 infection were gradually enhanced lagging behind the production of cytokine. The early rapid host responses were potentially attributed to the high efficiency of SARS-CoV-2 entry into host cells, underscored by evidence of a remarkably up-regulated gene expression of TPRMSS2 soon after infection. Taken together, our findings provide novel molecular insights into the mechanisms underlying the infectivity and pathogenicity of SARS-CoV-2.
Scarless Removal of Large Resistance Island AbaR Results in Antibiotic Susceptibility and Increased Natural Transformability in Acinetobacter baumannii

With a great diversity in gene composition, including multiple putative antibiotic resistance genes, AbaR islands are potential contributors to multidrug resistance in Acinetobacter baumannii. However, the effective contribution of AbaR to antibiotic resistance and bacterial physiology remains elusive. To address this, we sought to accurately remove AbaR islands and restore the integrity of their insertion site. To this end, we devised a versatile scarless genome editing strategy. ABSTRACT With a great diversity in gene composition, including multiple putative antibiotic resistance genes, AbaR islands are potential contributors to multidrug resistance in Acinetobacter baumannii. However, the effective contribution of AbaR to antibiotic resistance and bacterial physiology remains elusive. To address this, we sought to accurately remove AbaR islands and restore the integrity of their insertion site. To this end, we devised a versatile scarless genome editing strategy. We performed this genetic modification in two recent A. baumannii clinical strains: the strain AB5075 and the nosocomial strain AYE, which carry AbaR11 and AbaR1 islands of 19.7 kbp and 86.2 kbp, respectively. Antibiotic susceptibilities were then compared between the parental strains and their AbaR-cured derivatives. As anticipated by the predicted function of the open reading frame (ORF) of this island, the antibiotic resistance profiles were identical between the wild type and the AbaR11-cured AB5075 strains. In contrast, AbaR1 carries 25 ORFs, with predicted resistance to several classes of antibiotics, and the AYE AbaR1-cured derivative showed restored susceptibility to multiple classes of antibiotics. Moreover, curing of AbaRs restored high levels of natural transformability. Indeed, most AbaR islands are inserted into the comM gene involved in natural transformation. Our data indicate that AbaR insertion effectively inactivates comM and that the restored comM is functional. Curing of AbaR consistently resulted in highly transformable and therefore easily genetically tractable strains. Emendation of AbaR provides insight into the functional consequences of AbaR acquisition.
Pharmacological evaluation of Dactyloctenium aegyptium : An indigenous plant used to manage gastrointestinal ailments

Crude extract of Dactylotenium aegyptium and its fractions were evaluated to rationalize its folkloric use in gastrointestinal ailments. In spontaneous contracting rabbit jejunum preparation, D. aegyptium exert concentration-dependent spasmogenic effect (0.01-0.1 mg/mL) followed by spasmolytic effect at higher doses (0.3-3.0 mg/mL). Pretreatment of the tissue preparations with atropine resulted in suppression of the spasmogenic response. Furthermore, D. aegyptium (1.0 mg/mL) caused relaxation of K + (80 mM)-induced spastic contractions in isolated rabbit jejunum preparations and there was non-parallel shift in Ca ++ dose response curves towards right (0.1-0.3 mg/mL). These findings were found to be comparable with verapamil, a standard Ca ++ channel blocker. The solvent-solvents fractionation reflected segregations of spasmogenic and spasmolytic effects in respective aqueous and dichloromethane fractions. The above-mentioned findings reflected, presence of cholinergic as well as Ca ++ channel blocking activity in ethanolic extract of D. aegyptium thus providing scientific basis for its folkloric use in constipation and diarrhea.
RootNet: A Convolutional Neural Networks for Complex Plant Root Phenotyping from High-Definition Datasets

Plant phenotyping using machine learning and computer vision approaches is a challenging task. Deep learning-based systems for plant phenotyping is more efficient for measuring different plant traits for diverse genetic discoveries compared to the traditional image-based phenotyping approaches. Plant biologists have recently demanded more reliable and accurate image-based phenotyping systems for assessing various features of plants and crops. The core of these image-based phenotyping systems is structural classification and features segmentation. Deep learning-based systems, however, have shown outstanding results in extracting very complicated features and structures of above-ground plants. Nevertheless, the below-ground part of the plant is usually more complicated to analyze due to its complex arrangement and distorted appearance. We proposed a deep convolutional neural networks (CNN) model named “RootNet” that detects and pixel-wise segments plant roots features. The feature of the proposed method is detection and segmentation of very thin (1-3 pixels wide roots). The proposed approach segment high definition images without significantly sacrificing pixel density, it leads to more accurate root type detection and segmentation results. It is hard to train CNNs with high definition images due to GPU memory limitations. The proposed patch-based CNN training setup makes use of the entire image (with maximum pixel desisity) to recognize and segment give root system efficiently. We have used wheat (Triticum aestivum L.) seedlings dataset, which consists of wheat roots grown in visible pouches. The proposed system segments are given root systems and save it to the Root System Markup Language (RSML) for future analysis. RootNet trained on the dataset mentioned above along with popular semantic segmentation architectures, and it achieved a benchmark accuracy.