Miracle-dz/UniFAR-FTUs huggingface dataset:
Two isoforms of the essential C. elegans Argonaute CSR-1 differentially regulate sperm and oocyte fertility

The C. elegans genome encodes nineteen functional Argonaute proteins that utilize 22G-RNAs, 26G-RNAs, miRNAs, or piRNAs to regulate their target transcripts. Only one of these proteins is essential under normal laboratory conditions: CSR-1. While CSR-1 has been studied in various developmental and functional contexts, nearly all studies investigating CSR-1 have overlooked the fact that the csr-1 locus encodes two isoforms. These isoforms differ by an additional 163 amino acids present in the N-terminus of CSR-1a. Using CRISPR-Cas9 genome editing to introduce GFP::3xFLAG epitopes into the long (CSR-1a) and short (CSR-1b) isoforms of CSR-1, we identified differential expression patterns for the two isoforms. CSR-1a is expressed specifically during spermatogenesis and in select somatic tissues, including the intestine. In contrast, CSR-1b, is expressed constitutively in the germline. Essential functions of csr-1 described in the literature coincide with CSR-1b. In contrast, CSR-1a plays tissue specific functions during spermatogenesis, where it integrates into a spermatogenesis sRNA regulatory network including ALG-3, ALG-4, and WAGO-10 that is necessary for male fertility. CSR-1a is also required in the intestine for the silencing of repetitive transgenes. Sequencing of small RNAs associated with each CSR-1 isoform reveals that CSR-1a engages with 22G- and 26G-RNAs, while CSR-1b interacts with only 22G-RNAs to regulate distinct groups of germline genes and regulate both sperm and oocyte-mediated fertility.
Deep Learning Neural Network Prediction Method Improves Proteome Profiling of Vascular Sap of Grapevines during Pierce’s Disease Development

Plant secretome studies have shown the importance of plant defense proteins in the vascular system against pathogens. Studies on Pierce’s disease of grapevines caused by the xylem-limited bacteria Xylella fastidiosa (Xf) have detected proteins and pathways associated to its pathobiology. Despite the biological importance of the secreted proteins in the extracellular space to plant survival and development, proteome studies are scarce due to technical and technological challenges. Deep learning neural network prediction methods can provide powerful tools for improving proteome profiling by data-independent acquisition (DIA). We aimed to explore the potential of this strategy by combining it with in silico spectral library prediction tool, Prosit, to analyze the proteome of vascular leaf sap of grapevines with Pierce’s disease. The results demonstrate that the combination of DIA and Prosit increased the total number of identified proteins from 145 to 360 for grapevines and 18 to 90 for Xf. The new proteins increased the range of molecular weight, assisted on the identification of more exclusive peptides per protein, and increased the identification of low abundance proteins. These increases allowed the identification of new functional pathways associated with cellular responses to oxidative stress to be further investigated.
Genome analysis of clinical pneumococcal isolates to decipher sequence types, antibiotic resistance mechanisms and virulence gene profiles

Introduction Streptococcus pneumoniae is a common cause of meningitis and pneumonia. Various studies have explored the relationship between genome and phenotypic characteristics like antibiotic resistance. Methods Four pneumococcal isolates from clinical specimens were included. DNA was extracted and genomes were sequenced in 2×101bp layout. Standard genome analysis tools and pipelines were employed to understand phenotypic characteristics. Results There was almost perfect agreement of genome-based predictions and phenotypic methods for antibiotic resistance. Novel sequence type (ST) was identified in one of the isolates. In total 29 virulence genes were common for all the isolates.
Ecological Load and Balancing Selection in Circumboreal Barnacles

Acorn barnacle adults experience environmental heterogeneity at various spatial scales of their circumboreal habitat, raising the question of how adaptation to high environmental variability is maintained in the face of strong juvenile dispersal and mortality. Here we show that 4% of genes in the barnacle genome experience balancing selection across the entire range of the species. Many of these genes harbor mutations maintained across 2 million years of evolution between the Pacific and Atlantic oceans. These genes are involved in ion regulation, pain reception, and heat tolerance, functions which are essential in highly variable ecosystems. The data also reveal complex population structure within and between basins, driven by the trans-Arctic interchange and the last glaciation. Divergence between Atlantic and Pacific populations is high, foreshadowing the onset of allopatric speciation, and suggesting that balancing selection is strong enough to maintain functional variation for millions of years in the face of complex demography.
Humic acids enrich the plant microbiota with bacterial candidates for the suppression of pathogens

Humic acids (HAs) stimulate the growth of several plant species by regulating their hormonal and redox metabolisms. Nevertheless, studies on the relationship of these substances with the plant-associated microbiota are almost nonexistent. Here, we hypothesized that the effect of HAs occurs in parallel with the regulation of the plant-associated bacterial community. Our results show the positive influence of HAs on the growth of rice and its stimulation of the root system. Metataxonomics revealed that the structure and composition of root bacterial communities were affected upon the application of HAs. Chitinophaga and Mucilaginibacter were the predominant genera in HA-treated roots. These bacteria produce enzymes that degrade compounds like those present in the wall of fungi, oomycetes, and nematode eggs. Pseudomonas and the Gp 1 group of Acidobacteria, both siderophore-producers and plant-growth promoters were also enriched, although with lower abundances. Given these results, we suggest that plants recruit these microorganisms in response to the stress caused by the HA-root interaction. For the first time, our findings indicate that HA-stimulated plants adopt the ecological strategy of recruiting members of the bacterial community that are candidates for the suppression of pathogens and, therefore, involved in plant defense.
V-ATPase controls tumor growth and autophagy in a Drosophila model of gliomagenesis

Glioblastoma (GBM), a very aggressive and incurable tumor, often results from constitutive activation of EGFR (epidermal growth factor receptor) and of PI3K (phosphoinositide 3-kinase). To understand the role of autophagy in the pathogenesis of glial tumors in vivo, we used an established Drosophila melanogaster model of glioma based on overexpression in larval glial cells of an active human EGFR and of the PI3K homolog Dp110. Interestingly, the resulting hyperplastic glia expresses high levels of ref(2)P (refractory to Sigma P), the Drosophila homolog of p62/SQSTM1. However, cellular clearance of autophagic cargoes appears inhibited upstream of autophagosome formation. Remarkably, downregulation of subunits of the vacuolar-H+-ATPase (V-ATPase) prevents overgrowth, reduces PI3K signaling and restores clearance. Consistent with evidence in flies, neurospheres from patients with high V-ATPase subunit expression show inhibition of autophagy. Altogether, our data suggest that autophagy is repressed during glial tumorigenesis and that V-ATPase could represent a therapeutic target against GBM.
Optogenetic activation of spinal microglia triggers chronic pain in mice

Spinal microglia are highly responsive to peripheral nerve injury and are known to be a key player in neuropathic pain. However, there has not been any direct evidence showing selective microglial activation in vivo is sufficient to induce chronic pain. Here we used optogenetic approaches in microglia to address this question employing CX3CR1creER/+: R26LSL-ReaChR/+ transgenic mice, in which red-activated channelrhodopsin (ReaChR) is inducibly and specifically expressed in microglia. We found that activation of ReaChR by red light in spinal microglia evoked reliable inward currents and membrane depolarization. In vivo optogenetic activation of microglial ReaChR in the spinal cord triggered chronic pain hypersensitivity lasting for 5-7 days. In addition, activation of microglial ReaChR upregulated neuronal c-fos expression and enhanced C-fiber responses. Mechanistically, ReaChR activation led to a reactive microglial phenotype with increased IL-1β production. IL-1 receptor antagonist was able to reverse the pain hypersensitivity and neuronal hyperactivity induced by microglial ReaChR activation. Therefore, our work demonstrates that optogenetic activation of spinal microglia is sufficient to trigger chronic pain phenotypes by increasing neuronal activity via IL-1 signaling.
Structural determination of Streptococcus pyogenes M1 protein interactions with human immunoglobulin G using integrative structural biology

Streptococcus pyogenes (Group A streptococcus; GAS) is an important human pathogen responsible for mild to severe, life-threatening infections. GAS expresses a wide range of virulence factors, including the M family proteins. The M proteins allow the bacteria to evade parts of the human immune defenses by triggering the formation of a dense coat of plasma proteins surrounding the bacteria, including IgGs. However, the molecular level details of the M1-IgG interaction have remained unclear. Here, we characterized the structure and dynamics of this interaction interface in human plasma on the surface of live bacteria using integrative structural biology, combining cross-linking mass spectrometry and molecular dynamics (MD) simulations. We show that the primary interaction is formed between the S-domain of M1 and the conserved IgG Fc-domain. In addition, we show evidence for a so far uncharacterized interaction between the A-domain and the IgG Fc-domain. Both these interactions mimic the protein G-IgG interface of group C and G streptococcus. These findings underline a conserved scavenging mechanism used by GAS surface proteins that block the IgG-receptor (FcγR) to inhibit phagocytic killing. We additionally show that we can capture Fab-bound IgGs in a complex background and identify the specific M1 epitopes targeted on live bacteria. Our results elucidate the M1-IgG interaction network involved in inhibition of phagocytosis and reveal important M1 peptides that can be further investigated as future vaccine targets.
Proprioceptive afferents differentially contribute to effortful perception of object heaviness and mass distribution

When humans handle a tool, such as a tennis racket or hammer, for the first time, they often wield it to determine its inertial properties, however, the mechanisms that contribute to perception of inertial properties are not fully understood. The goal of the present study was to investigate how proprioceptive afferents contribute to effortful perception of heaviness and mass distribution of a manually wielded object in the absence of vision. Blindfolded participants manually wielded a set of specially-designed experimental objects of different mass and mass distribution about the wrist at different wrist angles and wrist angular kinematics. By independently manipulating these variables, we aimed to elicit different levels of tonic and rhythmic activity in the muscle spindles of the wrist flexors and extensors and relate them to reported perceptual judgments of heaviness and length. Perception of heaviness and length were predominantly dependent on an object’s static moment and the moment of inertia, respectively. Manipulations of wrist angle and wrist angular kinematics affected perceptual judgments of heaviness and length in relatively opposite ways. As for wrist angle, ulnar deviation consistently resulted in an object being perceived heavier but shorter. Compared to static holding, wielding the object resulted in it being perceived heavier but wielding did not affect perceived length. These results suggest that proprioceptive afferents differentially contribute to effortful perception of object heaviness and mass distribution.
SARS-CoV2 spike protein displays biologically significant similarities with paramyxovirus surface proteins; a bioinformatics study

Recent emergence of SARS-CoV2 and associated COVID-19 pandemic has posed a great challenge for the scientific community. Understanding various aspects of SARS-CoV2 biology, virulence and pathogenesis as well as determinants of immune response have become a global research priority. In this study, we performed bioinformatic analyses on SAR-CoV2 protein sequences, trying to unravel biologically important similarities between this newly emerged virus with other RNA viruses. Comparing the proteome of SARS-CoV2 with major positive and negative strand ssRNA viruses showed significant homologies between SARS-CoV2 spike protein with pathogenic paramyxovirus fusion proteins. This ‘spike-fusion’ homology was not limited to SARS-CoV2 and it existed for some other pathogenic coronaviruses; nonetheless, SARS-CoV2 spike-fusion homology was orders of magnitude stronger than homologies observed for other known coronaviruses. Moreover, this homology did not seem to be a consequence of general ssRNA virus phylogenetic relations. We also explored potential immunological significance of this spike-fusion homology. Spike protein epitope analysis using experimentally verified data deposited in Immune Epitope Database (IEDB) revealed that the majority of spike’s T cell epitopes as well as many B cell and MHC binding epitopes map within the spike-fusion homology region. Overall, our data indicate that there might be a relation between SARS-CoV2 and paramyxoviruses at the level of their surface proteins and this relation could be of crucial immunological importance.
The Short- and Long-Range RNA-RNA Interactome of SARS-CoV-2

The Coronaviridae is a family of positive-strand RNA viruses that includes SARS-CoV-2, the etiologic agent of the COVID-19 pandemic. Bearing the largest single-stranded RNA genomes in nature, coronaviruses are critically dependent on long-distance RNA-RNA interactions to regulate the viral transcription and replication pathways. Here we experimentally mapped the in vivo RNA-RNA interactome of the full-length SARS-CoV-2 genome and subgenomic mRNAs. We uncovered a network of RNA-RNA interactions spanning tens of thousands of nucleotides. These interactions reveal that the viral genome and subgenomes adopt alternative topologies inside cells, and engage in different interactions with host RNAs. Notably, we discovered a long-range RNA-RNA interaction - the FSE-arch - that encircles the programmed ribosomal frameshifting element. The FSE-arch is conserved in the related MERS-CoV and is under purifying selection. Our findings illuminate RNA structure based mechanisms governing replication, discontinuous transcription, and translation of coronaviruses, and will aid future efforts to develop antiviral strategies.
Combinatorial Inference for Large-Scale Data Analysis

Problems of inferring the combinatorial structures of networks arise in many real applications ranging from genomic regulatory networks, brain networks to social networks. This poses new and challenging problems on the uncertainty assessment and replicability analysis for statistical methods inferring these network topological structures. This thesis develops combinatorial inference, a new inferential framework for networks, to conduct hypothesis tests and variable selection for combinatorial structures in large-scale graphs. In the first part of the thesis, we propose a unified inferential method to test hypotheses on the global combinatorial properties of graphical models. We showed that my method works for general monotone graph properties that can be preserved under edge deletion including bipartite, planar, k-colorable, etc. We develop a new combinatorial minimax theory to justify the optimality of the skip-down algorithm. We introduce a new notion of graph packing entropy to sharply characterize the complexity of combinatorial inference problems for graphical models. It can be viewed as the combinatorial counterpart of the famous metric entropy theory on parametric minimax lower bounds. In the second part of the thesis, we generalize the combinatorial inference for larger family of graphical models. We propose a novel class of dynamic nonparanormal graphical models, which allows us to model high dimensional heavy-tailed systems and the evolution of their latent network structures. Under this model we develop statistical tests for presence of edges both locally at a fixed index value and globally over a range of values. The tests are developed for a high-dimensional regime, are robust to model selection mistakes and do not require commonly assumed minimum signal strength. The testing procedures are based on a high dimensional, debiasing-free moment estimator, which uses a novel kernel smoothed Kendall’s tau correlation matrix as an input statistic.
Evaluation of diversity levels of the integrase gene sequences coming from HIV-1 virus, supporting the lack of target specificity of ivermectin versus the integrase-importin complex in SARS-CoV-2 infection

Therapies with new drugs have been appearing in tests worldwide as potential inhibitors of sars-cov-2 virus replication. Recently, one of these drugs, Ivermectin, was reported as an inhibitor of the nuclear import of HIV-1 proteins in vitro, soon becoming the target of an international prospecting work (not yet published), with patients tested for COVID-19. However, understanding the evolutionary aspects of the biological components involved in the complex drug-nuclear import helps in understanding how these relationships exist in the deactivation of viral infections. Thus, 153 sequences of the HIV-1 integrase gene were analyzed for their genetic structure and molecular diversity and the presence of two distinct groups for the Gene and not only one, was detected; As well as different degrees of structuring for each of these groups. These results support the interpretation of the lack of conservation of the HIV-1 gene and that the number of existing polymorphisms, only for this structure of the complex, implies the non-efficiency of a drug at population levels. Thus, the molecular diversity found in HIV-1 can be extrapolated to other viruses, such as Including, SARS-CoV-2 and the functionality of the drug, interacting with the integrase-importin complex, can be further decreased.
Programmable Digital Liquid Metal Droplets in Reconfigurable Magnetic Fields.

Gallium based liquid metal (LM) exhibits excellent locomotion and deformation capabilities under external stimuli and have presented potentials in developing intelligent robots. Programming the locomotion and morphology of LM to endow it with functionalities and intelligence as robots is charming but remains challenging. In this study, we develop a programmable digital liquid metal (PDLM) control platform that can realize versatile locomotion and morphological manipulation of magnetic LM (MLM) droplets using arrays of electromagnets. We demonstrate on-demand transportation, deformation, breakup and merging of multiple MLM droplets simultaneously and precisely. We find that the intriguing behaviors of MLM under magnetic field is owning to the interplay of surface tension and magnet forces. Furthermore, we present a functional cooperative droplet robot by equipping the MLM droplets with 3D printed micro-tool modules. We show that both position and orientation of a rod-shaped object can be precisely manipulated by the cooperation the MLM droplet robots. More interestingly, we explore the capability of the MLM droplet robots for cooperatively handling a copper wire to connect and disconnect electronic circuits. Finally, we demonstrate that the PDLM control platform is capable of programming a group of MLM droplets to accomplish a digital display task. We believe the PDLM control system presents a promising potential in developing LM based reconfigurable circuits, digital display systems, and biomimetic soft robotic systems with high controllability, multi-functionalities and intelligence.
Tiotropium Is Predicted to Be a Promising Drug for COVID-19 Through Transcriptome-Based Comprehensive Molecular Pathway Analysis

The coronavirus disease 2019 (COVID-19) outbreak caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) affects almost everyone in the world in many ways. We previously predicted antivirals (atazanavir, remdesivir and lopinavir/ritonavir) and non-antiviral drugs (tiotropium and rapamycin) that may inhibit the replication complex of SARS-CoV-2 using our molecular transformer–drug target interaction (MT–DTI) deep-learning-based drug–target affinity prediction model. In this study, we dissected molecular pathways upregulated in SARS-CoV-2-infected normal human bronchial epithelial (NHBE) cells by analyzing an RNA-seq data set with various bioinformatics approaches, such as gene ontology, protein–protein interaction-based network and gene set enrichment analyses. The results indicated that the SARS-CoV-2 infection strongly activates TNF and NFκB-signaling pathways through significant upregulation of the TNF, IL1B, IL6, IL8, NFKB1, NFKB2 and RELB genes. In addition to these pathways, lung fibrosis, keratinization/cornification, rheumatoid arthritis, and negative regulation of interferon-gamma production pathways were also significantly upregulated. We observed that these pathologic features of SARS-CoV-2 are similar to those observed in patients with chronic obstructive pulmonary disease (COPD). Intriguingly, tiotropium, as predicted by MT–DTI, is currently used as a therapeutic intervention in COPD patients. Treatment with tiotropium has been shown to improve pulmonary function by alleviating airway inflammation. Accordingly, a literature search summarized that tiotropium reduced expressions of IL1B, IL6, IL8, RELA, NFKB1 and TNF in vitro or in vivo, and many of them have been known to be deregulated in COPD patients. These results suggest that COVID-19 is similar to an acute mode of COPD caused by the SARS-CoV-2 infection, and therefore tiotropium may be effective for COVID-19 patients.
It’s about being the good parent: exploring attitudes and beliefs towards active school transportation

ABSTRACT In recent decades, there has been a decline in active school transportation (AST). Parents play an important role as the key decision-makers of children’s AST, and there is a need of more knowledge about the decision-making process and parents’ beliefs towards AST. The overall aim of this study was to explore parents’ attitudes and beliefs towards AST in the northern part of Sweden. Twenty parents participated in semi-structured interviews, which was based on the theory of planned behaviour. Qualitative content analysis was used to analyse the interviews. The analysis yielded one main theme, “Parenting and active school transportation – making route choices in a changed landscape” and four subthemes, “Knowing that it is beneficial while struggling with daily life”, “Considering barriers and solutions to enable AST”, “Parenting is challenging and about balancing”, and “Reflecting and contemplating about what we and others do”. Winter conditions affect parents’ decisions, and this needs to be considered when facilitating AST in these regions. Overall better health, increased physical activity, time spent outdoors, and free play were revealed as positive outcomes of AST. Decisions were also influenced by social norms and how the idea of parenting has changed through generations. The findings of this study are likely to be important when promoting AST.