bluuebunny/crossref_metadata_2025 huggingface dataset:
How socio-ecological factors influence the differentiation of social relationships: an integrated conceptual framework
Authors: Moscovice Liza R. , Sueur Cédric , Aureli Filippo
Published: September 2020

The extent of differentiation of social relationships within groups is a means to assess social complexity, with greater differentiation indicating greater social complexity. Socio-ecological factors are likely to influence social complexity, but no attempt has been made to explain the differentiation of social relationships using multiple socio-ecological factors. Here, we propose a conceptual framework based on four components underlying multiple socio-ecological factors that influence the differentiation of social relationships: the extent of within-group contest competition to access resources, the extent to which individuals differ in their ability to provide a variety of services, the need for group-level cooperation and the constraints on social interactions. We use the framework to make predictions about the degree of relationship differentiation that can be expected within a group according to the cumulative contribution of multiple socio-ecological factors to each of the four components. The framework has broad applicability, since the four components are likely to be relevant to a wide range of animal taxa and to additional socio-ecological factors not explicitly dealt with here. Hence, the framework can be used as the basis for the development of novel and testable hypotheses about intra- and interspecific differences in relationship differentiation and social complexity.
Make or break it: boundary conditions for integrating multiple elements in episodic memory
Authors: James Emma , Ong Gabrielle , Henderson Lisa M. , Horner Aidan J.
Published: September 2020

Event memories are characterized by the holistic retrieval of their constituent elements. Studies show that memory for individual event elements (e.g. person, object and location) are statistically related to each other, and that the same associative memory structure can be formed by learning all pairwise associations across separated encoding contexts (person–object, person–location, object–location). Counter to previous studies that have shown no differences in holistic retrieval between simultaneously and separately encoded event elements, adults did not show evidence of holistic retrieval from separately encoded event elements when using a similar paradigm adapted for children (Experiment 1). We conducted a further five online experiments to explore the conditions under which holistic retrieval emerges following separated encoding of within-event associations, testing for influences of trial length (Experiment 2), the number of events learned (Experiment 3a) and stimulus presentation format (Experiments 3b, 4a, 4b). Presentation of written words was optimal for integrating elements across encoding trials, whereas the addition of spoken words disrupted integration across separately presented associations. The use of picture stimuli also produced effect sizes smaller than those of previously published research. We discuss the ways in which memory integration processes may be disrupted by these differences in presentation format. The findings have practical implications for the utility of this paradigm across research and learning contexts.
Degradation and detoxification of azo dyes with recombinant ligninolytic enzymes from
Aspergillus
sp. with secretory overexpression in
Pichia pastoris
Authors: Liu Siqi , Xu Xiaolin , Kang Yanshun , Xiao Yingtian , Liu Huan
Published: September 2020

Ligninolytic enzymes, including laccase (Lac), manganese peroxidase (MnP) and lignin peroxidase (LiP), have attracted much attention in the degradation of contaminants. Genes of Lac (1827 bp), MnP (1134 bp) and LiP (1119 bp) were cloned from
Aspergillus
sp. TS-A, and the recombinant Lac (69 kDa), MnP (45 kDa) and LiP (35 kDa) were secretory expressed in
Pichia pastoris
GS115, with enzyme activities of 34, 135.12 and 103.13 U l
−1
, respectively. Dyes of different structures were treated via the recombinant ligninolytic enzymes under the optimal degradation conditions, and the result showed that the decolourization rate of Lac on Congo red (CR) in 5 s was 45.5%. Fourier-transform infrared spectroscopy, gas chromatography–mass spectrometry analysis and toxicity tests further proved that the ligninolytic enzymes could destroy the dyes, both those with one or more azo bonds, and the degradation products were non-toxic. Moreover, the combined ligninolytic enzymes could degrade CR more completely compared with the individual enzyme. Remarkably, besides azo dyes, ligninolytic enzymes could also degrade triphenylmethane and anthracene dyes. This suggests that ligninolytic enzymes from
Aspergillus
sp. TS-A have the potential for application in the treatment of contaminants.
Designing of cytotoxic and helper T cell epitope map provides insights into the highly contagious nature of the pandemic novel coronavirus SARS-CoV-2
Authors: Mishra Seema
Published: September 2020

Novel coronavirus, SARS-CoV-2, has emerged as one of the deadliest pathogens of this century, creating an unprecedented pandemic. Belonging to the betacoronavirus family, it primarily spreads through human contact via symptomatic and asymptomatic transmission. Despite several attempts since it emerged, there is no known treatment in the form of drugs or vaccines. Hence, work on developing a potential multi-subunit vaccine is the need of the hour. In this study, attempts have been made to find globally conserved epitopes from the entire set of SARS-CoV-2 proteins as there is as yet, no clear information on the immunogenicity of these proteins. Using diverse computational tools, a ranked list of probable immunogenic, promiscuous epitopes generated through all the three main stages of antigen processing and presentation pathways has been prioritized. Moreover, several useful insights were gleaned during these analyses. One of the most important insights is that all of the proteins in this pathogen present unique epitopes, so that the targeting of a few specific viral proteins is not likely to result in an effective immune response in humans. Due to the presence of these unique epitopes in all of the SARS-CoV-2 proteins, stronger immune responses generated by T cell hyperactivation may lead to cytokine storm and immunopathology and consequently, remote chances of human survival. These epitopes, after due validation
in vitro
, may thus need to be presented to the human body in that form of multi-subunit epitope-based vaccine that avoids such immunopathologies.
Feeding specialization and longer generation time are associated with relatively larger brains in bees
Authors: Sayol Ferran , Collado Miguel Á. , Garcia-Porta Joan , Seid Marc A. , Gibbs Jason , Agorreta Ainhoa , San Mauro Diego , Raemakers Ivo , Sol Daniel , Bartomeus Ignasi
Published: September 2020

Despite their miniature brains, insects exhibit substantial variation in brain size. Although the functional significance of this variation is increasingly recognized, research on whether differences in insect brain sizes are mainly the result of constraints or selective pressures has hardly been performed. Here, we address this gap by combining prospective and retrospective phylogenetic-based analyses of brain size for a major insect group, bees (superfamily Apoidea). Using a brain dataset of 93 species from North America and Europe, we found that body size was the single best predictor of brain size in bees. However, the analyses also revealed that substantial variation in brain size remained even when adjusting for body size. We consequently asked whether such variation in relative brain size might be explained by adaptive hypotheses. We found that ecologically specialized species with single generations have larger brains—relative to their body size—than generalist or multi-generation species, but we did not find an effect of sociality on relative brain size. Phylogenetic reconstruction further supported the existence of different adaptive optima for relative brain size in lineages differing in feeding specialization and reproductive strategy. Our findings shed new light on the evolution of the insect brain, highlighting the importance of ecological pressures over social factors and suggesting that these pressures are different from those previously found to influence brain evolution in other taxa.
The relationship between a combinatorial processing rule and a continuous mate preference function in an insect
Authors: Desjonquères Camille , Holt Rebecca R. , Speck Bretta , Rodríguez Rafael L.
Published: September 2020

Mate choice involves processing signals that can reach high levels of complexity and feature multiple components, even in small animals with tiny brains. This raises the question of whether and how such organisms deal with this complexity. One solution involves combinatorial processing, whereby different signal elements are processed as single units. Combinatorial processing has been described in several mammals and birds, and recently in a vibrationally signalling insect,
Enchenopa
treehoppers. Here, we ask about the relationship between combinatorial rules and mate preferences for continuously varying signal features.
Enchenopa
male advertisement signals are composed of two elements: a ‘whine’ followed by a set of pulses. The dominant frequency of the whine and element combination both matter to females. We presented synthetic signals varying in element order (natural [whine-pulses], reverse [pulses-whine]) and in frequency to
Enchenopa
females and recorded their responses. The reverse combination resulted in a decrease in attractiveness of the signals, and also slightly changed the shape of the preference for frequency. We found that females could be classified into three ‘types’: females with both a strong preference and a strong combinatorial rule, females with both a weak preference and weak rule, and females with a strong preference but a weak rule. Our results suggest that in
Enchenopa
signal processing, the mate preference for a continuous signal feature ‘takes precedence’ over, but also interacts with, the combinatorial rule. The relationship between the preference and the rule could evolve to take different forms according to selection on mate choice decisions. We suggest that exploring the relationship between such preferences and rules in species with more complex signals will bring insight into the evolution of the multi-component communication systems.
Reactivation of latent infections with migration shapes population-level disease dynamics
Authors: Becker Daniel J. , Ketterson Ellen D. , Hall Richard J.
Published: September 2020

Annual migration is common across animal taxa and can dramatically shape the spatial and temporal patterns of infectious disease. Although migration can decrease infection prevalence in some contexts, these energetically costly long-distance movements can also have immunosuppressive effects that may interact with transmission processes in complex ways. Here, we develop a mechanistic model for the reactivation of latent infections driven by physiological changes or energetic costs associated with migration (i.e. ‘migratory relapse’) and its effects on disease dynamics. We determine conditions under which migratory relapse can amplify or reduce infection prevalence across pathogen and host traits (e.g. infectious periods, virulence, overwinter survival, timing of relapse) and transmission phenologies. We show that relapse at either the start or end of migration can dramatically increase prevalence across the annual cycle and may be crucial for maintaining pathogens with low transmissibility and short infectious periods in migratory populations. Conversely, relapse at the start of migration can reduce the prevalence of highly virulent pathogens by amplifying culling of infected hosts during costly migration, especially for highly transmissible pathogens and those transmitted during migration or the breeding season. Our study provides a mechanistic foundation for understanding the spatio-temporal patterns of relapsing infections in migratory hosts, with implications for zoonotic surveillance and understanding how infection patterns will respond to shifts in migratory propensity associated with environmental change. Further, our work suggests incorporating within-host processes into population-level models of pathogen transmission may be crucial for reconciling the range of migration–infection relationships observed across migratory species.
BBB07 contributes to, but is not essential for, Borrelia burgdorferi infection in mice
Authors: Hahn Beth , Anderson Phillip , Lu Zouyan , Danner Rebecca , Zhou Zhipeng , Hyun Noorie , Gao Lihui , Lin Tao , Norris Steven J. , Coburn Jenifer
Published: September 2020

Borrelia burgdorferi, a causative agent of Lyme disease, encodes a protein BBB07 on the genomic plasmid cp26. BBB07 was identified as a candidate integrin ligand based on the presence of an RGD tripeptide motif, which is present in a number of mammalian ligands for β1 and β3 integrins . Previous work demonstrated that BBB07 in recombinant form binds to β1 integrins and induces inflammatory responses in synovial cells in culture. Several transposon mutants in bbb07 were attenuated in an in vivo screen of the transposon library in mice. We therefore tested individual transposon mutant clones in single-strain infections in mice and found that they were attenuated in terms of ID50 but did not have significantly reduced tissue burdens in mice. Based on data presented here we conclude that BBB07 is not essential for, but does contribute to,

B. burgdorferi

infectivity in mice.
The impact of COVID-19 in diabetic kidney disease and chronic kidney disease: A population-based study
Authors: Leon-Abarca Juan A. , Memon Roha S. , Rehan Bahar , Iftikhar Maimoona , Chatterjee Antara
Published: September 2020

Background

The spectrum of pre-existing renal disease is known as a risk factor for severe COVID-19 outcomes. However, little is known about the impact of COVID-19 on patients with diabetic nephropathy in comparison to patients with chronic kidney disease.

Methods

We used the Mexican Open Registry of COVID-19 patients 11 to analyze anonymized records of those who had symptoms related to COVID-19 to analyze the rates of SARS-CoV-2 infection, development of COVID-19 pneumonia, admission, intubation, Intensive Care Unit admission and mortality. Robust Poisson regression was used to relate sex and age to each of the six outcomes and find adjusted prevalences and adjusted prevalence ratios. Also, binomial regression models were performed for those outcomes that had significant results to generate probability plots to perform a fine analysis of the results obtained along age as a continuous variable.

Results

The adjusted prevalence analysis revealed that that there was a a 87.9% excess probability of developing COVID-19 pneumonia in patients with diabetic nephropathy, a 5% excess probability of being admitted, a 101.7% excess probability of intubation and a 20.8% excess probability of a fatal outcome due to COVID-19 pneumonia in comparison to CKD patients (p< 0.01).

Conclusions

Patients with diabetic nephropathy had nearly a twofold rate of COVID-19 pneumonia, a higher probability of admission, a twofold probability of intubation and a higher chance of death once admitted compared to patients with chronic kidney disease alone. Also, both diseases had higher COVID-19 pneumonia rates, intubation rates and case-fatality rates compared to the overall population.
Testing an analogue game to promote peer support and person-centredness in education for people with type 2 diabetes: a realist evaluation
Authors: Stenov Vibeke , Lindgreen Pil , Willaing Ingrid , Basballe Henning Grubb , Joensen Lene Eide
Published: September 2020

Aim

To explore the outcomes of testing an analogue game to incorporate person-centredness and peer dialogues in group-based diabetes education targeting people with type 2 diabetes

Design

A quasi-experimental design inspired by realistic evaluation focusing on context, mechanisms and outcomes of the intervention

Methods

In March-July 2019, the game was tested among 76 people with type 2 diabetes and 17 healthcare professionals in 19 settings across nine Danish municipalities. Data consisted of audio recordings, individual and group interviews and questionnaires. Data were analysed using systematic text condensation and descriptive statistics.

Results

Outcomes of using the analogue game in diabetes education were: 1) a playful and relaxed atmosphere; 2) active engagement 3) reflections on diabetes-specific experiences; 4) structured and focused dialogues; 5) healthcare professionals gaining insight into the preferences and needs of participants; and 6) healthcare professionals experiencing peer dialogue as important to incorporate into education. Questionnaire responses showed that 92% of people with type 2 diabetes and 94% of healthcare professionals found that the game incorporated person-centredness and peer dialogues into diabetes education.

Conclusion

Implementing the analogue game as part of patient education facilitated peer support and person-centredness in a fun and playful way. Lack of time in diabetes education programmes and complicated game rules inhibited person-centeredness and peer dialogue.

Impact

The study provides novel insights into gaming as a method for promoting peer dialogue and person-centredness in diabetes education targeting people with type 2 diabetes.

The game proved feasible as a structured tool to implement in group-based diabetes education.

Implementing the game in diabetes education can help healthcare professionals provide diabetes education and support, which may improve quality of life and diabetes self-management skills.
CIAlign - A highly customisable command line tool to clean, interpret and visualise multiple sequence alignments
Authors: Tumescheit Charlotte , Firth Andrew E. , Brown Katherine
Published: September 2020

Background

Throughout biology, multiple sequence alignments (MSAs) form the basis of much investigation into biological features and relationships. These alignments are at the heart of many bioinformatics analyses. However, sequences in MSAs are often incomplete or very divergent, which leads to poorly aligned regions or large gaps in alignments. This slows down computation and can impact conclusions without being biologically relevant. Therefore, cleaning the alignment by removing these regions can substantially improve analyses. Manual editing of MSAs is very widespread but is time-consuming and difficult to reproduce.

Results

We present a comprehensive, user-friendly MSA trimming tool with multiple visualisation options. Our highly customisable command line tool aims to give intervention power to the user by offering various options, and outputs graphical representations of the alignment before and after processing to give the user a clear overview of what has been removed.

The main functionalities of the tool include removing regions of low coverage due to insertions, removing gaps, cropping poorly aligned sequence ends and removing sequences that are too divergent or too short. The thresholds for each function can be specified by the user and parameters can be adjusted to each individual MSA. CIAlign is designed with an emphasis on solving specific and common alignment problems and on providing transparency to the user.

Conclusion

CIAlign effectively removes problematic regions and sequences from MSAs and provides novel visualisation options. This tool can be used to refine alignments for further analysis and processing. The tool is aimed at anyone who wishes to automatically clean up parts of an MSA and those requiring a new, accessible way of visualising large MSAs.
SARS-CoV-2 protein Nsp1 alters actomyosin cytoskeleton and phenocopies arrhythmogenic cardiomyopathy-related PKP2 mutant
Authors: Márquez-López Cristina , Roche-Molina Marta , García-Quintáns Nieves , Sacristán Silvia , Siniscalco David , González-Guerra Andrés , Camafeita Emilio , Lytvyn Mariya , Guillen María I. , Sanz-Rosa David , Martín-Pérez Daniel , Sánchez-Ramos Cristina , García Ricardo , Bernal Juan A.
Published: September 2020

Mutations in desmosomalPlakophilin-2 (PKP2)are the most prevalent drivers of arrhythmogenic cardiomyopathy (ACM) and a common cause of sudden cardiac death in young athletes. However, partner proteins that elucidate PKP2 cellular mechanism to understand cardiac dysfunction in ACM are mostly unknown. Here we identify the actin-based motor proteins Myh9 and Myh10 as key PKP2 interactors, and demonstrate that the expression of the ACM-related PKP2 mutant R735X alters actin fiber organization and cell mechanical stiffness. We also show that SARS-CoV-2 Nsp1 protein acts similarly to this known pathogenic R735X mutant, altering the actomyosin component distribution on cardiac cells. Our data reveal that the viral Nsp1 hijacks PKP2 into the cytoplasm and mimics the effect of delocalized R735X mutant. These results demonstrate that cytoplasmic PKP2, wildtype or mutant, induces the collapse of the actomyosin network, since shRNA-PKP2knockdown maintains the cell structure, validating a critical role of PKP2 localization in the regulation of actomyosin architecture. The fact that Nsp1 and PKP2 mutant R735X share similar phenotypes also suggests that direct SARS-CoV-2 heart infection could induce a transient ACM-like disease in COVID-19 patients, which may contribute to right ventricle dysfunction, observed in patients with poor survival prognosis.

Highlights

The specific cardiac isoform Plakophilin-2a (PKP2) interacts with Myh9 and Myh10.

PKP2 delocalization alters actomyosin cytoskeleton component organization. SARS-CoV-2 Nsp1 protein hijacks PKP2 from the desmosome into the soluble fraction where it is downregulated.

Viral Nsp1 collapses the actomyosin cytoskeleton and phenocopies the arrhythmogenic cardiomyopathy-related mutant R735X.
Identification of hsa-miR-106a-5p as an impact agent on promotion of multiple sclerosis using multi-step data analysis
Authors: Rahimirad Samira , Navaderi Mohammad , Alaei Shokoofeh , Sanati Mohammad Hossein
Published: September 2020

Multiple Sclerosis (MS) is a chronic, demyelinating disease in which the neuron myelin sheath is disrupted and leading to signal transductions disabilities. The evidence demonstrated that gene expression patterns and their related regulating factors are the most critical agents in Multiple Sclerosis demyelinating process. A miRNA is a small non-coding RNA which functions in post-transcriptional regulation of gene expression. Identification of specific miRNA dysregulation patterns in multiple sclerosis blood samples compared to healthy control can be used as a diagnostic and prognostic agent. Through the literature review and bioinformatics analysis, it was found that the hsa-miR-106a-5p can be considered as a significant MS pathogenic factor, which seems has an abnormal expression pattern in patients’ blood. Experimental validation using Real-Time PCR assay was carried to verifying the miR-106a-5p expression in Multiple Sclerosis and healthy control blood samples. The obtained results proved the miR-106a dysregulation in MS patients. The expression levels of miR-106a-5p were significantly down-regulated (Fold change=0.44) in patient blood samples compared to controls (p=0.059). Our study suggested that miR-106a-5p may have a biomarker potential to the diagnosis of MS patients based on its dysregulation patterns in Multiple Sclerosis blood.
Ligation bias is a major contributor to nonstoichiometric abundances of secondary siRNAs and impacts analyses of microRNAs
Authors: Baldrich Patricia , Tamim Saleh , Mathioni Sandra , Meyers Blake
Published: September 2020

Plant small RNAs are a diverse and complex set of molecules, ranging in length from 21 to 24 nt, involved in a wide range of essential biological processes. High-throughput sequencing is used for the discovery and quantification of small RNAs. However, several biases can occur during the preparation of small RNA libraries, especially using low input RNA. We used two stages of maize anthers to evaluate the performance of seven commercially-available methods for small RNA library construction, using different RNA input amounts. We show that when working with plant material, library construction methods have differing capabilities to capture small RNAs, and that different library construction methods provide better results when applied to the detection of microRNAs, phasiRNAs, or tRNA-derived fragment. We also observed that ligation bias occurs at both ends of miRNAs and phasiRNAs, suggesting that the biased compositions observed in small RNA populations, including nonstoichiometric levels of phasiRNAs within a locus, may reflect a combination of biological and technical influences.
CROssBAR: Comprehensive Resource of Biomedical Relations with Deep Learning Applications and Knowledge Graph Representations
Authors: Doğan Tunca , Atas Heval , Joshi Vishal , Atakan Ahmet , Rifaioglu Ahmet Sureyya , Nalbat Esra , Nightingale Andrew , Saidi Rabie , Volynkin Vladimir , Zellner Hermann , Cetin-Atalay Rengul , Martin Maria , Atalay Volkan
Published: September 2020

Systemic analysis of available large-scale biological and biomedical data is critical for developing novel and effective treatment approaches against both complex and infectious diseases. Owing to the fact that different sections of the biomedical data is produced by different organizations/institutions using various types of technologies, the data are scattered across individual computational resources, without any explicit relations/connections to each other, which greatly hinders the comprehensive multi-omics-based analysis of data. We aimed to address this issue by constructing a new biological and biomedical data resource, CROssBAR, a comprehensive system that integrates large-scale biomedical data from various resources and store them in a new NoSQL database, enrich these data with deep-learning-based prediction of relations between numerous biomedical entities, rigorously analyse the enriched data to obtain biologically meaningful modules and display them to users via easy-to-interpret, interactive and heterogenous knowledge graph (KG) representations within an open access, user-friendly and online web-service athttps://crossbar.kansil.org. As a use-case study, we constructed CROssBAR COVID-19 KGs (available at:https://crossbar.kansil.org/covid_main.php) that incorporate relevant virus and host genes/proteins, interactions, pathways, phenotypes and other diseases, as well as known and completely new predicted drugs/compounds. Our COVID-19 graphs can be utilized for a systems-level evaluation of relevant virus-host protein interactions, mechanisms, phenotypic implications and potential interventions.
Contrasting beta diversity and functional composition of aquatic insect communities across local to regional scales in Amazonian streams
Authors: Nicacio Gilberto , Cunha Erlane José , Hamada Neusa , Juen Leandro
Published: September 2020

We investigated how components of beta diversity (i.e., the turnover and nestedness and functional compositional) aquatic insect assemblages change among sites and are influenced by environmental and spatial drivers. For this, we analyzed beta-diversity and functional composition of Ephemeroptera, Plecoptera, and Trichoptera in 16 streams in two Amazonian basins with distinct environmental conditions (the Carajás and Tapajós regions). We performed Multiple regression on dissimilarity matrices (MRM) and Procrustes analysis to test spatial and environmental influences on the taxonomic and functional composition of communities. Community dissimilarity was most related to variations in geographic distance and topography, which highlighted the environmental distances shaping the communities. Variation in functional composition could be mostly attributed to the replacement of species by those with similar traits, indicating trait convergence among communities. Environmental predictors best-explained species replacement and trait congruence within and between the regions evaluated. In summary, among communities with different taxonomic compositions, the high species replacement observed appears to be leading them to have similar community structure, with species having the same functional composition, even in communities separated by both small and large geographic distances.
GP96 drives exacerbation of secondary bacterial pneumonia following influenza A virus infection
Authors: Sumitomo Tomoko , Nakata Masanobu , Nagase Satoshi , Takahara Yuki , Honda-Ogawa Mariko , Mori Yasushi , Yamaguchi Masaya , Okamoto Shigefumi , Kawabata Shigetada
Published: September 2020

Influenza A virus (IAV) infection predisposes the host to secondary bacterial pneumonia, known as a major cause of morbidity and mortality during influenza epidemics. Analysis of interactions between IAV-infected human epithelial cells andStreptococcus pneumoniaerevealed that infected cells ectopically exhibited the endoplasmic reticulum chaperon GP96 on the surface. Importantly, efficient pneumococcal adherence to epithelial cells was imparted by interactions with extracellular GP96 and integrin αV, with the surface expression mediated by GP96 chaperone activity. Furthermore, abrogation of adherence was gained by chemical inhibition or genetic knockout of GP96, as well as addition of RGD peptide. Direct binding of extracellular GP96 and pneumococci was shown to be mediated by pneumococcal oligopeptide permease components. Additionally, IAV infection induced activation of calpains and Snail1, which are responsible for degradation and transcriptional repression of junctional proteins in the host, respectively, indicating increased bacterial translocation across the epithelial barrier. Notably, treatment of IAV-infected mice with the GP96 inhibitor enhanced pneumococcal clearance from lung tissues and ameliorated lung pathology. Taken together, the present findings indicate a viral-bacterial synergy in relation to disease progression and suggest a paradigm for developing novel therapeutic strategies tailored to inhibit pneumococcal colonization in an IAV-infected respiratory tract.
COPB2haploinsufficiency causes a coatopathy with osteoporosis and developmental delay
Authors: Marom Ronit , Burrage Lindsay C. , Clément Aurélie , Blanco-Sánchez Bernardo , Venditti Rossella , Jain Mahim , Grafe Ingo , Scott Daryl A. , Rosenfeld Jill A. , Sutton V. Reid , Shinawi Marwan , Mirzaa Ghayda , DeVile Catherine , Roberts Rowenna , Calder Alistair D , Allgrove Jeremy , Lanza Denise G. , Li Xiaohui , Joeng Kyu Sang , Lee Yi-Chien , Song I-Wen , Sliepka Joseph M. , Batkovskyte Dominyka , Jin Zixue , Dawson Brian C. , Chen Shan , Chen Yuqing , Jiang Ming-Ming , Munivez Elda M. , Tran Alyssa A. , Emrick Lisa T. , Murdock David R. , Hanchard Neil A. , Zapata Gladys E. , Mehta Nitesh R. , Weis Mary Ann , Kuzawa Cole , Scott Abbey , Tremp Brenna A. , Phillips Jennifer B. , Wegner Jeremy , Taylor-Miller Tashunka , Gibbs Richard A. , Muzny Donna M. , Jhangiani Shalini N. , Stottmann Rolf W. , Dickinson Mary E. , Seavitt John R. , Heaney Jason D. , Eyre David R. , Ambrose Catherine G. ,   Undiagnosed Diseases Network Monte Westerfield, De Matteis Maria Antonella , Lee Brendan
Published: September 2020

Coatomer complexes function in the sorting and trafficking of proteins between subcellular organelles. Pathogenic variants in coatomer subunits or associated factors have been reported in multi-systemic disorders, i.e., coatopathies, that can affect the skeletal and central nervous systems. We have identified loss-of-function variants inCOPB2, a component of the coatomer complex I (COPI), in individuals presenting with osteoporosis, fractures and developmental delay of variable severity. Because the role of COPB2 in bone has not been characterized, we studied the effect ofCOPB2deficiency on skeletal development in mice and zebrafish.Copb2+/−mice showed low bone mass and decreased bone strength. In zebrafish, larvae carrying acopb2heterozygous frameshift variant showed delayed mineralization.copb2-null embryos showed endoplasmic reticulum (ER) and Golgi disorganization, and embryonic lethality.COPB2siRNA-treated fibroblasts showed delayed collagen trafficking with retention of type I collagen in the ER and Golgi, and altered distribution of Golgi markers. Our data suggest thatCOPB2haploinsufficiency leads to disruption of intracellular collagen trafficking and osteoporosis, which may improve with ascorbic acid supplementation. This work highlights the role of COPI complex as a critical regulator of bone mass and identifies a new form of coatopathy due toCOPB2deficiency.
Sustained attention and spatial attention distinctly influence long-term memory encoding
Authors: deBettencourt Megan T. , Williams Stephanie D. , Vogel Edward K. , Awh Edward
Published: September 2020

Our attention is critically important for what we remember. Prior measures of the relationship between attention and memory, however, have largely treated “attention” as a monolith. Here, across three experiments, we provide evidence for two dissociable aspects of attention that influence encoding into long-term memory. Using spatial cues together with a sensitive continuous report procedure, we find that long-term memory response error is affected by both trial-by-trial fluctuations of sustained attention and prioritization via covert spatial attention. Furthermore, using multivariate analyses of EEG, we track both sustained attention and spatial attention prior to stimulus onset. Intriguingly, even during moments of low sustained attention, there is no decline in the representation of the spatially attended location, showing that these two aspects of attention have robust but independent effects on long term memory encoding. Finally, sustained and spatial attention predicted distinct variance in long-term memory performance across individuals. That is, the relationship between attention and long-term memory suggests a composite model, wherein distinct attentional subcomponents influence encoding into long-term memory. These results point towards a taxonomy of the distinct attentional processes that constrain our memories.
Dragonfly visual neurons selectively attend to features in naturalistic scenes
Authors: Evans BJE , Fabian JM , O’Carroll DC , Wiederman SD
Published: September 2020

Aerial predators, such as the dragonfly, determine the position and movement of their prey even when embedded in natural scenes. This task is likely supported by a group of optic lobe neurons with responses selective for moving targets of less than a few degrees. These Small Target Motion Detector (STMD) neurons are tuned to target velocity and show profound facilitation in responses to targets that move along continuous trajectories. When presented with a pair of targets, some STMDs competitively select one of the alternatives as if the other does not exist.

Here we describe intracellular responses of STMD neurons to the visual presentation of many potential alternatives within cluttered environments comprised of natural scenes. We vary both target contrast and the background scene, across a range of target and background velocities. We find that background motion affects STMD responses indirectly, via the competitive selection of background features. We find that robust target discrimination is limited to scenarios when the target velocity is matched to, or greater than, background velocity. Furthermore, STMD target discriminability is modified by background direction. Backgrounds that move in the neuron’s anti-preferred direction result in the least performance degradation.

Significance Statement

Biological brains solve the difficult problem of visually detecting and tracking moving features in cluttered environments. We investigated this neuronal processing by recording intracellularly from dragonfly visual neurons that encode the motion of small moving targets subtending less than a few degrees (e.g. prey and conspecifics). However, dragonflies live in a complex visual environment where background features may interfere with tracking by reducing target contrast or providing competitive cues. We find that selective attention towards features drives much of the neuronal response, with background clutter competing with target stimuli for selection. Moreover, the velocity of features is an important component in determining the winner in these competitive interactions.
leADS: improved metabolic pathway inference based on active dataset subsampling
Authors: Basher Abdur Rahman M. A. , Nallan Aditi N. , McLaughlin Ryan J. , Anstett Julia , Hallam Steven J.
Published: September 2020

Metabolic pathways are composed of reaction sequences catalyzed by enzymes. The set of reactions within and between cells comprises a reactome. Pathways and reactomes can be predicted from organismal or multi-organismal genomes using rule-based or machine learning methods. While machine learning methods overcome issues of probability and scale associated with rule-based methods, several complications remain that can degrade performance including inadequately labeled training data, missing feature information, and inherent imbalances in the distribution of pathways within a dataset. Here, we present leADS (multi-label learning based onactivedatasetsubsampling), a machine learning method, that uses subsampling to reduce the negative impact of training loss due to class imbalance. We demonstrate leADs performance using organismal and multi-organismal datasets in relation to other machine learning pathway prediction methods.

Availability and implementation

leADS is available under the GNU license at github.com/hallamlab/leADS. A wiki, including a tutorial, is available at github.com//hallamlab/leADS/wiki

Contact

shallam@mail.ubc.ca
Fate of the M-phase-assembled centrioles during the cell cycle in theTP53;PCNT;CEP215-deleted cells
Authors: Jung Gee In , Rhee Kunsoo
Published: September 2020

Cancer cells frequently include supernumerary centrioles. Here, we generatedTP53;PCNT;CEP215triple knockout cell lines and observed precocious separation and amplification of the centrioles at M phase. Many of the triple KO cells maintained supernumerary centrioles throughout the cell cycle. The M-phase-assembled centrioles lack an ability to function as templates for centriole assembly during S phase. They also lack an ability to organize microtubules in interphase. However, we found that a fraction of them acquired an ability to organize microtubules during M phase. Our works provide an example how supernumerary centrioles behave in dividing cells.
Mapping Brain-Behavior Space Relationships Along the Psychosis Spectrum
Authors: Ji Jie Lisa , Helmer Markus , Fonteneau Clara , Burt Joshua B. , Tamayo Zailyn , Demšar Jure , Adkinson Brendan , Savić Aleksandar , Preller Katrin H. , Moujaes Flora , Vollenweider Franz X. , Martin William J. , Repovš Grega , Murray John D. , Anticevic Alan
Published: September 2020

Difficulties in advancing effective patient-specific therapies for psychiatric disorders highlight a need to develop a stable neurobiologically-grounded mapping between neural and symptom variation. This gap is particularly acute for psychosis-spectrum disorders (PSD). Here, in a sample of 436 cross-diagnostic PSD patients, we derived and replicated a dimensionality-reduced symptom space across hallmark psychopathology symptoms and cognitive deficits. In turn, these symptom axes mapped onto distinct, reproducible brain maps. Critically, we found that multivariate brain-behavior mapping techniques (e.g. canonical correlation analysis) do not produce stable results. Instead, we show that a univariate brain-behavioral space (BBS) can resolve stable individualized prediction. Finally, we show a proof-of-principle framework for relating personalized BBS metrics with molecular targets via serotonin and glutamate receptor manipulations and gene expression maps. Collectively, these results highlight a stable and data-driven BBS mapping across PSD, which offers an actionable path that can be iteratively optimized for personalized clinical biomarker endpoints.
Refactoring the formicamycin biosynthetic gene cluster to make high-level producing strains and new molecules
Authors: Devine Rebecca , McDonald Hannah , Qin Zhiwei , Arnold Corinne , Noble Katie , Chandra Govind , Wilkinson Barrie , Hutchings Matthew I.
Published: September 2020

The formicamycins are promising antibiotics with potent activity against Gram-positive pathogens including VRE and MRSA and display a high barrier to selection of resistant isolates. They were first identified inStreptomyces formicaeKY5, which produces the formicamycins at low levels on solid agar but not in liquid culture, thus hindering further investigation of these promising antibacterial compounds. We hypothesised that by understanding the organisation and regulation of theforbiosynthetic gene cluster, we could rationally refactor the cluster to increase production levels. Here we report that theforbiosynthetic gene cluster consists of 24 genes expressed on nine transcripts. Seven of these transcripts, including those containing all the major biosynthetic genes, are repressed by the MarR-regulator ForJ which also controls the expression of the ForGF two-component system that initiates biosynthesis. A third cluster-situated regulator, ForZ, autoregulates and controls production of the putative MFS transporter ForAA. Consistent with these findings, deletion offorJincreased formicamycin biosynthesis 5-fold, while over-expression offorGFin the ΔforJbackground increased production 10-fold compared to the wild-type. De-repression by deletingforJalso switched on biosynthesis in liquid-culture and induced the production of two novel formicamycin congeners. By combining mutations in regulatory and biosynthetic genes, six new biosynthetic precursors with antibacterial activity were also isolated. This work demonstrates the power of synthetic biology for the rational redesign of antibiotic biosynthetic gene clusters both to engineer strains suitable for fermentation in large scale bioreactors and to generate new molecules.

Importance

Antimicrobial resistance is a growing threat as existing antibiotics become increasingly ineffective against drug resistant pathogens. Here we determine the transcriptional organisation and regulation of the gene cluster encoding biosynthesis of the formicamycins, promising new antibiotics with activity against drug resistant bacteria. By exploiting this knowledge, we construct stable mutant strains which over-produce these molecules in both liquid and solid culture whilst also making some new compound variants. This will facilitate large scale purification of these molecules for further study including in vivo experiments and the elucidation of their mechanism of action. Our work demonstrates that understanding the regulation of natural product biosynthetic pathways can enable rational improvement of the producing strains.
Rational design of a new class of protease inhibitors for the potential treatment of coronavirus diseases
Authors: Westberg Michael , Su Yichi , Zou Xinzhi , Ning Lin , Hurst Brett , Tarbet Bart , Lin Michael Z.
Published: September 2020

The coronavirus main protease, Mpro, is a key protein in the virus life cycle and a major drug target. Based on crystal structures of SARSCoV2 Mprocomplexed with peptidomimetic inhibitors, we recognized a binding characteristic shared with proline-containing inhibitors of hepatitis C virus protease. Initial tests showed that this subclass of HCV protease inhibitors indeed exhibited activity against Mpro. Postulating a benefit for a preorganized backbone conformation, we designed new ketoamide-based Mproinhibitors based on central proline rings. One of the designed compounds, ML1000, inhibits Mprowith low-nanomolar affinity and suppresses SARSCoV2 viral replication in human cells at sub-micromolar concentrations. Our findings identify ML1000 as a promising new pre-organized scaffold for the development of anti-coronavirus drugs.
Transcription Factors STAT5A and SPI1 Reveals RHBDD2 as a Potential Biomarker in Sepsis and Septic Shock
Authors: Ali Arslan , Shehwana Huma , Hanif Ayesha , Fatima Abeera , Shabbir Maria , Rafiq Mehak
Published: September 2020

Sepsis is a serious health situation caused by uncontrolled infection and septic shock is a severe condition of sepsis. RHBDD2 is a member of the rhomboid superfamily which is overexpressed in different types of cancer and associated with ER stress and estrogen receptor. Using microarray gene expression data and using different computational techniques this study investigated the role of RHBDD2 in sepsis and septic shock. Finds functional annotation of RHBDD2 using co-expression analysis and identified the deregulation of RHBDD2 in sepsis using differential expression analysis. Results show that RHBDD2 is overexpressed in sepsis and septic shock. The GO enrichment analysis, KEGG pathways, and biological functions of the RHBDD2 co-expressed genes module show that it is involved in most of the sepsis-related biological functions and also plays a role in most of the infection-related pathways which lead to sepsis and septic shock. RHBDD2 is regulated by STAT5A and SPI1 transcription factors in sepsis and septic shock. The identification of the RHBDD2 as a biomarker may facilitate in septic shock diagnosis, treatment, and prognosis.
Accuracy of predicting chemical body composition of growing pigs using dual-energy X-ray absorptiometry
Authors: Kasper Claudia , Schlegel Patrick , Ruiz-Ascacibar Isabel , Stoll Peter , Bee Giuseppe
Published: September 2020

Abstract

Studies in animal science assessing nutrient and energy efficiency or determining nutrient requirements necessitate gathering exact measurements of body composition or body nutrient contents. Wet chemical analysis methods or standardized dissection are commonly applied, but both are destructive. Harnessing human medical imaging techniques for animal science can enable repeated measurements of individuals over time and reduce the number of individuals required for research. Among imaging techniques, dual-energy X-ray absorptiometry (DXA) is particularly promising. However, the measurements obtained with DXA do not perfectly match dissections or chemical analyses, requiring the adjustment of the DXA via calibration equations. Several calibration regressions have been published, but comparative studies are pending. Thus, it is currently not clear whether existing regression equations can be directly used to convert DXA measurements into chemical values or whether each individual DXA device will require its own calibration. Our study builds prediction equations that relate body composition to the content of single nutrients in growing entire male pigs (body weight range 20-100 kg) as determined by both DXA and chemical analyses, with R2ranging between 0.89 for ash and 0.99 for water and crude protein. Moreover, we show that the chemical composition of the empty body can be satisfactorily determined by DXA scans of carcasses, with the prediction error rCV ranging between 4.3% for crude protein and 12.6% for ash. Finally, we compare existing prediction equations for pigs of a similar range of body weights with the equations derived from our DXA measurements and evaluate their fit with our chemical analyses data. We found that existing equations for absolute contents that were built using the same DXA beam technology predicted our data more precisely than equations based on different technologies and percentages of fat and lean mass. This indicates that the creation of generic regression equations that yield reliable estimates of body composition in pigs of different growth stages, sexes and genetic breeds could be achievable in the near future. DXA may be a promising tool for high-throughput phenotyping for genetic studies, because it efficiently measures body composition in a large number and wide array of animals.