bluuebunny/crossref_metadata_2025 huggingface dataset:
Signal, bias, and the role of transcriptome assembly quality in phylogenomic inference
Authors: Spillane Jennifer L , LaPolice Troy M , MacManes Matthew D , Plachetzki David C
Published: July 2020

The empirical details of whole transcriptome sequencing and assembly have been thoroughly evaluated, but few studies have addressed how user-defined aspects of the assembly process may influence performance in phylogenomic analyses. Errors in transcriptome assembly could affect ortholog prediction, alignment quality, and phylogenetic signal. Here we investigate the impacts of transcriptome assembly quality in phylogenomic studies by constructing phylogenomic data matrices from alternative transcriptome assemblies representing high-quality and intentionally low-quality assembly outcomes. We leveraged a well-resolved topology for craniates to apply a topological constraint to our analyses, providing a way to quantify phylogenetic signal. Craniates are amply represented in publicly available raw RNA-seq repositories, allowing us to control for transcriptome tissue type as well. By studying the performance of phylogenomic datasets derived from these alternative high- and low-quality inputs in a controlled experiment, we show that high-quality transcriptomes produce richer phylogenomic datasets with partitions that have lower alignment ambiguity, less compositional bias, and stronger phylogenetic signal than low-quality transcriptome assemblies. Our findings demonstrate the importance of transcriptome assembly in phylogenomic analyses and suggest that a portion of the uncertainty observed in phylogenomic studies could be alleviated at the assembly stage.
Co-expression of Mitochondrial Genes and ACE2 in Cornea Involved in COVID-19 Infection
Authors: Yuan Jian , Fan Dandan , Xue Zhengbo , Qu Jia , Su Jianzhong
Published: July 2020

The Coronavirus disease 2019 (COVID-19) pandemic severely challenges public health and necessitates the need for increasing our understanding of COVID-19 pathogenesis, especially host factors facilitating virus infection and propagation. Here, the co-expression network was constructed by mapping the well-known ACE2, TMPRSS2 and host susceptibility genes implicated in COVID-19 GWAS onto a cornea, retinal pigment epithelium and lung. We found a significant co-expression module of these genes in the cornea, revealing that cornea is potential extra-respiratory entry portal of SARS-CoV-2. Strikingly, both co-expression and interaction networks show a significant enrichment in mitochondrial function, which are the hub of cellular oxidative homeostasis, inflammation and innate immune response. We identified a corneal mitochondrial susceptibility module (CMSM) of 14 mitochondrial genes by integrating ACE2 co-expression cluster and SARS-CoV-2 interactome. Gene ECSIT, as a cytosolic adaptor protein involved in inflammatory responses, exhibits the strongest correlation with ACE2 in CMSM, which has shown to be an important risk factor for SARS-CoV-2 infection and prognosis. Our co-expression and protein interaction network analysis uncover that the mitochondrial function related genes in cornea contribute to the dissection of COVID-19 susceptibility and potential therapeutic interventions.
Wireless AI-Powered IoT Sensors for Laboratory Mice Behavior Recognition
Authors: Chen Meng , Liu Yifan , Tam John Chung , Chan Ho-yin , Li Xinyue , Chan Chishing , Li Wen J.
Published: July 2020

According to the U.S. Department of Agriculture in 2018, there are more than 100 million animals used in research, education, and testing per year. Of the laboratory animals used for research, 95 percent are mice and rats as reported by the Foundation for Biomedical Research (FBR). We present here our work in developing wireless Artificial Intelligent (AI)-powered IoT Sensors (AIIS) for laboratory mice motion recognition utilizing embedded micro-inertial measurement units (uIMUs). Based on the AIIS, we have demonstrated a small-animal motion tracking and recognition system that could recognize 5 common behaviors of mice in cages with accuracy of ~76.23%. The key advantage of this AIIS-based system is to enable high throughput behavioral monitoring of multiple to a large group of laboratory animals, in contrast to traditional video tracking systems that usually track only single or a few animals at a time. The system collects motion data (i.e., three axes linear accelerations and three axes angular velocities) from the IoT sensors attached to different mice, and classifies these data into different behaviors using machine learning algorithms. One of the challenging problems for data analysis is that the distribution of behavior samples is extremely imbalanced. Behaviors such assleepingandwalkingdominate the entire sample set from different mice. However, machine learning algorithms often require a balanced sample set to achieve optimal performance. Thus, several methods are proposed to solve the imbalanced sample problem. Data processing methods for data segmentation, feature extraction, feature selection, imbalanced learning, and machine learning are explored to process motion data includingsleeping, walking, rearing, digging, shaking, grooming, drinking and scratching. For example, by tuning the parameters of a machine-learning algorithm (i.e., Support Vector Machine (SVM)), the average accuracy of classifying five behaviors (i.e., sleeping, walking, rearing, digging and shaking) is 48.07% before solving the imbalance sample issue. To address this problem, an iteration of sample and feature selection is applied to improve the SVM performance. A combination of oversampling and undersampling is used to handle imbalanced classes, and feature selection provides the optimal number of features. The accuracy increases from 48.07% to 76.23% when the optimized combination is used. We further obtained an average accuracy of 86.46% by removingshaking, which is proved to have a negative effect on the overall performance, out of these five behaviors. Furthermore, we were able to classify less frequent behaviors includingrearing, digging, grooming, drinkingandscratchingat an average accuracy of 96.35%.
Single-cell landscape of immunological responses in COVID-19 patients
Authors: Zhang Ji-Yuan , Wang Xiang-Ming , Xing Xudong , Xu Zhe , Zhang Chao , Song Jin-Wen , Fan Xing , Xia Peng , Fu Jun-Liang , Wang Si-Yu , Xu Ruo-Nan , Dai Xiao-Peng , Shi Lei , Huang Lei , Jiang Tian-Jun , Shi Ming , Zhang Yuxia , Zumla Alimuddin , Maeurer Markus , Bai Fan , Wang Fu-Sheng
Published: July 2020

In COVID-19 caused by SARS-CoV-2 infection, the relationship between disease severity and the host immune response is not fully understood. Here we performed single-cell RNA sequencing in peripheral blood samples of five healthy donors and 13 COVID-19 patients including moderate, severe and convalescent cases. Through determining the transcriptional profiles of immune cells, coupled with assembled T cell receptor and B cell receptor sequences, we analyzed the functional properties of immune cells. Most cell types in COVID-19 patients showed a strong interferon-alpha response, and an overall acute inflammatory response. Moreover, intensive expansion of highly cytotoxic effector T cell subsets, such as CD4+Effector-GNLY (Granulysin), CD8+Effector-GNLY and NKT CD160, was associated with convalescence in moderate patients. In severe patients, the immune landscape featured a deranged interferon response, profound immune exhaustion with skewed T cell receptor repertoire and broad T cell expansion. These findings illustrate the dynamic nature of immune responses during the disease progression.
A hacked kitchen scale-based system for quantification of grip strength in rodents
Authors: Homolak Jan , Virag Davor , Kodvanj Ivan , Matak Ivica , Perhoc Ana Babic , Knezovic Ana , Barilar Jelena Osmanovic , Trkulja Vladimir , Salkovic-Petrisic Melita
Published: July 2020

Assessment of neuromuscular function is critical for understanding pathophysiological changes related to motor system dysfunction in many rodent disease models. Among methods used for quantification of grip performance in rodents, gauge-based grip strength meters provide the most reliable results, however, such instruments are unaffordable by many laboratories. Here we demonstrate how to build a rodent grip strength apparatus from scratch using a digital kitchen scale, an empty cage, and a microcontroller, with both hardware and software being completely open-source to enable maximal modularity and flexibility of the instrument in concordance with the principles of open-source bioinstrumentation. Furthermore, we test the griPASTA system for assessment of increased muscular rigidity in the proof-of-concept experiment in the rat model of Parkinson’s disease induced by intrastriatal administration of 6-hydroxydopamine (6-OHDA). Finally, the importance of bioinstrumental customization is demonstrated by utilizing griPASTA for assessment of trial speed from initial-to-maximal deflection time segments and controlling for its potential confounding effects on the grip strength.

Significance Statement

Neuromuscular function analyzed by grip strength performance tests is an integral part of motor system neuroscience and neurotoxicology. Strain gauge-based grip strength meters provide the most reliable results, however, commercial solutions are unaffordable by many. Consequently, cheap semi-quantitative tests are often used at the expense of precision and reliability. We propose griPASTA – a simple and robust open-source grip strength platform made from an ordinary kitchen scale. griPASTA could improve the quality and reproducibility of grip strength experiments by enabling researchers to obtain quantitative grip strength data in high resolution using a highly customizable platform.
Macroscopic cortical dynamics: Spatially uncorrelated but temporally coherent rich-club organisations in source-space resting-state EEG
Authors: Mehrkanoon Steve
Published: July 2020

Synchronous oscillations of neuronal populations support resting-state cortical activity. Recent studies indicate that resting-state functional connectivity is not static, but exhibits complex dynamics. The mechanisms underlying the complex dynamics of cortical activity have not been well characterised. Here, we directly apply singular value decomposition (SVD) in source-reconstructed electroencephalography (EEG) in order to characterise the dynamics of spatiotemporal patterns of resting-state functional connectivity. We found that changes in resting-state functional connectivity were associated with distinct complex topological features, “Rich-Club organisation”, of the default mode network, salience network, and motor network. Rich-club topology of the salience network revealed greater functional connectivity between ventrolateral prefrontal cortex and anterior insula, whereas Rich-club topologies of the default mode networks revealed bilateral functional connectivity between fronto-parietal and posterior cortices. Spectral analysis of the dynamics underlying Rich-club organisations of these source-space network patterns revealed that resting-state cortical activity exhibit distinct dynamical regimes whose intrinsic expressions contain fast oscillations in the alpha-beta band and with the envelope-signal in the timescale of < 0.1 Hz. Our findings thus demonstrated that multivariate eigen-decomposition of source-reconstructed EEG is a reliable computational technique to explore how dynamics of spatiotemporal features of the resting-state cortical activity occur that oscillate at distinct frequencies.
Comparing DNA Extraction and 16s Amplification Methods for Plant-Associated Bacterial Communities
Authors: Giangacomo Cecelia , Mohseni Mohsen , Kovar Lynsey , Wallace Jason G.
Published: July 2020

Plant-associated microbes play important roles in global ecology and agriculture. The most common method to profile these microbial communities is amplicon sequencing of the bacterial 16s rRNA gene. Both the DNA extraction and PCR amplification steps of this process are subject to bias, especially since the latter requires some way to exclude DNA from plant organelles, which would otherwise dominate the sample. We compared several common DNA extraction kits and 16s rRNA amplification protocols to determine the relative biases of each and to make recommendations for plant microbial researchers. For DNA extraction, we found that, as expected, kits optimized for soil were the best for soil, though each still included a distinct “fingerprint” of its own biases. Plant samples were less clear, with different species having different “best” options. For 16s amplification, we find that using peptide nucleic acid (PNA) clamps provides the least taxonomic distortion, while chloroplast-discriminating primers are easy and inexpensive but present significant bias in the results. We do not recommend blocking oligos, as they involved a more complex protocol and showed significant taxonomic bias in the results. Further methods development will hopefully result in protocols that are even more reliable and less biased.
Spectrum of pathogenic variants and multiple founder effects in amelogenesis imperfecta associated withMMP20
Authors: Nikolopoulos Georgios , Smith Claire E. L. , Poulter James A. , Murillo Gina , Silva Sandra , Brown Catriona J. , Day Peter F. , Soldani Francesca , Al-Bahlani Suhaila , Harris Sarah A. , O’Connell Mary J. , Inglehearn Chris F. , Mighell Alan J.
Published: July 2020

Amelogenesis imperfecta (AI) describes a heterogeneous group of developmental enamel defects that typically have Mendelian inheritance. Exome sequencing of ten families with recessive hypomaturation AI revealed 4 novel and 1 known variants in the matrix metallopeptidase 20 (MMP20) gene that were predicted to be pathogenic.MMP20encodes a protease that cleaves the developing extracellular enamel matrix and is necessary for normal enamel crystal growth during amelogenesis. New homozygous missense changes were shared between four families of Pakistani heritage (c.625G>C; p.(E209Q)) and two of Omani origin (c.710C>A; p.(S237Y)). In two families of UK origin and one from Costa Rica, affected individuals were homozygous for the previously reported c.954-2A>T; p.(I319Ffs*19) variant. For each of these variants, microsatellite haplotypes appeared to exclude a recent founder effect, but elements of haplotype were conserved, suggesting more distant founding ancestors. New compound heterozygous changes were identified in one family of European heritage; c.809_811+12delACGgtaagattattainsCCAG; p.(?) and c.1122A>C; p.(Q374H). All four new variants are within the zinc dependant peptidase domain. This report further elucidates the mutation spectrum ofMMP20and the probable impact on protein function, confirms a consistent hypomaturation phenotype and shows that mutations inMMP20are a common cause of autosomal recessive AI in some communities.

Data Availability

The data that support the findings of this study are openly available in ClinVar athttps://www.ncbi.nlm.nih.gov/clinvar/, accession numbers: SCV001338799 - SCV001338802 and in the AI Leiden Open Variation Database (LOVD) athttp://dna2.leeds.ac.uk/LOVD/with reference numbers: 0000000313 – 0000000317.
Characterization of a novel amastin-like surface protein (ALSP) ofLeishmania donovani, a probable lipase
Authors: Biswas Bapi , Laha Bhakti , Sengupta Pratyay , Das Koushik , Ghosh Monidipa
Published: July 2020

In the current study, a novel putative protein ofLeishmania donovani, amastin-like surface protein (ALSP) has been characterized. The gene was cloned in a bacterial system and the protein was overexpressed. A polyclonal antibody was developed against the protein, which detected a 10 kDa band in theL. donovaniamastigote. ALSP mRNA was detected inL. donovaniamastigote, which was not expressed in the promastigote. ALSP mRNA was not expressed in either morphological forms ofLeishmania major. MALDI-TOF confirmed the molecular weight of ALSP as 10 kDa. I-TASSER predicted the function of ALSP as a lipase, which was confirmed by preliminaryin-vitroexperiments using amastigotes ofL. donovani. ALSP has GAS amino acid sequences, which might act as the active site for its lipase activity. The selective expression of ALSP in amastigotes probably makes it important in virulence mechanisms such as survival in the phagolysosome and modulation of its membrane and other metabolic functions, necessary for parasite survival in the human host. ALSP can act as a peptide vaccine target and maybe detected in the peripheral blood or urine as a molecular biomarker of active disease in visceral leishmaniasis.
The essential role of Dnmt1 in gametogenesis in the large milkweed bug Oncopeltus fasciatus
Authors: Washington Joshua T. , Cavender Katelyn R. , Amukamara Ashley U. , McKinney Elizabeth C. , Schmitz Robert J. , Moore Patricia J.
Published: July 2020

Given the importance of DNA methylation in protection of the genome against transposable elements and transcriptional regulation in other taxonomic groups, the diversity in both levels and patterns of DNA methylation in the insects raises questions about its function and evolution. We show that the maintenance DNA methyltransferase, DNMT1, affects meiosis and is essential to fertility in milkweed bugs, Oncopeltus fasciatus, while DNA methylation is not required in somatic cells. Our results support the hypothesis that Dnmt1 is required for the transition of germ cells to gametes in O. fasciatus and that this function is conserved in male and female gametogenesis. They further suggest that DNMT1 has a function independent of DNA methylation in germ cells. Our results raise the question of how a gene so critical in fitness across multiple insect species can have diverged widely across the insect tree of life.
Host transcriptional responses and SARS-CoV-2 isolates from the nasopharyngeal samples of Bangladeshi COVID-19 patients
Authors: Islam Abul Bashar Mir Md. Khademul , Khan Md. Abdullah-Al-Kamran , Ahmed Rasel , Hossain Md. Sabbir , Kabir Shah Md. Tamim , Islam Md. Shahidul , Siddiki A.M.A.M. Zonaed
Published: July 2020

As the COVID-19 pandemic progresses, fatality and cases of new infections are also increasing at an alarming rate. SARS-CoV-2 follows a highly variable course and it is becoming more evident that individual’s immune system has a decisive influence on the progression of the disease. However, the detailed underlying molecular mechanisms of the SARS-CoV-2 mediate disease pathogenesis are largely unknown. Only a few host transcriptional responses in COVID-19 have been reported so far from the Western world, but no such data has been generated from the South-Asian region yet to correlate the conjectured lower fatality around this part of the globe. In this context, we aimed to perform the transcriptomic profiling of the COVID-19 patients from Bangladesh along with the reporting of the SARS-CoV-2 isolates from these patients. Moreover, we performed a comparative analysis to demonstrate how differently the various SARS-CoV-2 infection systems are responding to the viral pathogen. We detected a unique missense mutation at 10329 position of ORF1ab gene, annotated to 3C like proteinase, which is found in 75% of our analyzed isolates; but is very rare globally. Upon the functional enrichment analyses of differentially modulated genes, we detected a similar host induced response reported earlier; this response was mainly mediated by the innate immune system, interferon stimulation, and upregulated cytokine expression etc. in the Bangladeshi patients. Surprisingly, we did not perceive the induction of apoptotic signaling, phagosome formation, antigen presentation and production, hypoxia response within these nasopharyngeal samples. Furthermore, while comparing with the other SARS-CoV-2 infection systems, we spotted that lung cells trigger the more versatile immune and cytokine signaling which was several folds higher compared to our reported nasopharyngeal samples. We also observed that lung cells did not expressACE2in a very high amount as suspected, however, the nasopharyngeal cells are found overexpressingACE2. But the amount ofDPP4expression within the nasal samples was significantly lower compared to the other cell types. Surprisingly, we observed that lung cells express a very high amount of integrins compared to the nasopharyngeal samples, which might suggest the putative reasons for an increased amount of viral infections in the lungs. From the network analysis, we got clues on the probable viral modulation for the overexpression of these integrins. Our data will provide valuable insights in developing potential studies to elucidate the roles of ethnicity effect on the viral pathogenesis, and incorporation of further data will enrich the search of an effective therapeutics.
A psychometric platform to collect somatosensory sensations for neuroprosthetic use
Authors: Valle Giacomo , Iberite Francesco , Strauss Ivo , D’Anna Edoardo , Granata Giuseppe , Stieglitz Thomas , Raspopovic Stanisa , Petrini Francesco M. , Rossini Paolo M. , Micera Silvestro
Published: July 2020

Somatosensory neuroprostheses exploit invasive and non-invasive feedback technologies to restore sensorimotor functions lost to disease or trauma. These devices use electrical stimulation to communicate sensory information to the brain. A sensation characterization procedure is thus necessary to determine the appropriate stimulation parameters and to establish a clear personalized map of the sensations that can be restored. Several questionnaires have been described in the literature to collect the quality, type, location and intensity of the evoked sensations, but there is still no standard psychometric platform. Here we propose a new psychometric system containing previously validated questionnaires on evoked sensations, which can be applied to any kind of somatosensory neuroprosthesis. The platform collects stimulation parameters used to elicit sensations; records subjects’ percepts in terms of sensation location, type, quality, perceptual threshold, and intensity. It further collects data using standardized assessment questionnaires and scales, performs measurements over time, and collects phantom limb pain syndrome data. The psychometric platform is user-friendly and provides clinicians with all the information needed to assess the sensory feedback. The psychometric platform was validated with three trans-radial amputees. They platform was used to assess intraneural sensory feedback provided through implanted peripheral nerve interfaces. The proposed platform could act as a new standardized assessment toolbox to homogenize the reporting of results obtained with different technologies in the field of somatosensory neuroprosthetics.
Modulation of Individual Alpha Frequency with tACS shifts Time Perception
Authors: Mioni G. , Shelp A. , Stanfield-Wiswell C. T. , Gladhill K. A. , Bader F. , Wiener M.
Published: July 2020

Previous studies have linked brain oscillation and timing, with evidence suggesting that alpha oscillations (10Hz) may serve as a “sample rate” for the visual system. However, direct manipulation of alpha oscillations and time perception has not yet been demonstrated. Eighteen subjects performed a time generalization task with visual stimuli. Participants first learned the standard intervals (600 ms) and then were required to judge the new temporal intervals if they were equal or different compared to the standard. Additionally, we had previously recorded resting-state EEG from each subject and calculated their Individual Alpha Frequency (IAF), estimated as the peak frequency from the mean spectrum over posterior electrodes between 8 and 13 Hz. After learning the standard interval, participants performed the time generalization task while receiving occipital transcranial Alternating Current Stimulation (tACS). Crucially, for each subject, tACS was administered at their IAF or at off-peak alpha frequencies (IAF±2 Hz). Results demonstrated a linear shift in the psychometric function indicating a modification of perceived duration, such that progressively “faster” alpha stimulation led to longer perceived intervals. These results provide the first evidence that direct manipulations of alpha oscillations can shift perceived time in a manner consistent with a clock speed effect.
A termination-independent role of Rat1 in cotranscriptional splicing
Authors: Dhoondia Zuzer , Elewa Hesham , Malik Marva , Arif Zahidur , Pique-Regi Roger , Ansari Athar
Published: July 2020

The yeast termination factor Rat1, and its human homolog Xrn2, have been implicated in multiple nuclear processes. Here we report a novel role of Rat1 in mRNA splicing. Rat1 mutants display increased levels of unspliced transcripts. Accumulation of unspliced transcripts was not due to a failure to degrade unspliced mRNA, disruption of termination or an increased elongation rate in Rat1 mutants. ChIP-Seq analysis revealed Rat1 crosslinking to the introns of a subset of yeast genes. Mass spectrometry and coimmunoprecipitation revealed interaction of Rat1 with the Clf1, Isy1, Yju2, Prp43, and Sub2 splicing factors. Furthermore, recruitment of the Prp2 splicing factor on the intron was compromised in the Rat1 mutant. Based on these findings we propose that Rat1 has a novel role in splicing of a subset of mRNA in budding yeast.
Lineage specific transcription factor waves reprogram neuroblastoma from self-renewal to differentiation
Authors: Banerjee Deblina , Gryder Berkley , Bagchi Sukriti , Liu Zhihui , Chen Hsien-Chao , Xu Man , Sun Ming , Vaksman Zalman , Diskin Sharon J. , Khan Javed , Thiele Carol J
Published: July 2020

Temporal regulation of super-enhancer (SE) driven lineage specific transcription factors (TFs) underlies normal developmental programs. Neuroblastoma (NB) arises from an inability of sympathoadrenal progenitors to exit a self-renewal program and terminally differentiate. To identify critical SEs driving TF regulators of NB, we utilized NB cells in which all-trans retinoic acid (ATRA) induces growth arrest and differentiation. H3K27ac ChIP-seq paired with RNA-seq over a time course of ATRA treatment revealed SEs moving in a coordinated manner with four distinct temporal patterns (clusters). SEs that decreased with ATRA linked to 24 TFs involved in stem cell development/specialization (MYCN, GATA3, SOX11)along withLMO1, a transcriptional coregulator and oncogene identified via a genome-wide association study (GWAS) of NB. H3K27ac levels and GATA3 binding at the NB-associated rs2168101 site of the LMO1 SE were reduced with ATRA treatment, resulting in 1.46 fold decreasedLMO1expression. The SOX11 SE was lost coincident with a 50% decrease in mRNA after 8 days of ATRA treatment. CRISPR-Cas9 screening and siRNA inhibition showed a dependency on SOX11 for cell growth in NB cell lines. Silencing of the SOX11 SE using dCAS9-KRAB targeted guides caused a 40% decrease inSOX11mRNA and inhibited cell growth. Three other TF SE clusters had sequential waves of activation at 2, 4 and 8 days of ATRA treatment and involved TFs regulating neural development (GATA2andSOX4). Silencing of the gained SOX4 SE using dCAS9-KRAB targeting, caused a 50% decrease in SOX4 expression and attenuated expression of ATRA-induced differentiation genes. Our study has identified candidate oncogenic lineage drivers of NB self-renewal and TFs critical for implementing a differentiation program.
Immuno-informatics approach for multi-epitope vaccine designing against SARS-CoV-2
Authors: Banerjee Souvik , Majumder Kaustav , Gutierrez Gerardo Jose , Gupta Debkishore , Mittal Bharti
Published: July 2020

The novel Corona Virus Disease 2019 (COVID-19) pandemic has set the fatality rates ablaze across the world. So, to combat this disease, we have designed a multi-epitope vaccine from various proteins of Severe Acute Respiratory Syndrome Corona virus 2 (SARS-CoV-2) with an immuno-informatics approach, validated in silico to be stable, non-allergic and antigenic. Cytotoxic T-cell, helper T-cell, and B-cell epitopes were computationally predicted from six conserved protein sequences among four viral strains isolated across the world. The T-cell epitopes, overlapping with the B-cell epitopes, were included in the vaccine construct to assure the humoral and cell-mediated immune response. The beta-subunit of cholera toxin was added as an adjuvant at the N-terminal of the construct to increase immunogenicity. Interferon-gamma inducing epitopes were even predicted in the vaccine. Molecular docking and binding energetics studies revealed strong interactions of the vaccine with immune-stimulatory toll-like receptors (TLR) −2, 3, 4. Molecular dynamics simulation of the vaccine ensured in vivo stability in the biological system. The immune simulation of vaccine evinced elevated immune response. The efficient translation of the vaccine in an expression vector was assured utilizing in silico cloning approach. Certainly, such a vaccine construct could reliably be effective against COVID-19.
Annotation of Chromatin States in 66 Complete Mouse Epigenomes During Development
Authors: van der Velde Arjan , Fan Kaili , Tsuji Junko , Moore Jill , Purcaro Michael , Pratt Henry , Weng Zhiping
Published: July 2020

The morphologically and functionally distinct cell types of a multicellular organism are maintained by epigenomes and gene expression programs. Phase III of the ENCODE Project profiled 66 mouse epigenomes across twelve tissues at daily intervals from embryonic day 10.5 to birth. Applying the ChromHMM algorithm to these epigenomes, we annotated eighteen chromatin states with characteristics of promoters, enhancers, transcribed regions, repressed regions, and quiescent regions throughout the developmental time course. Our integrative analyses delineate the tissue specificity and developmental trajectory of the loci in these chromatin states. Approximately 0.3% of each epigenome is assigned to a bivalent chromatin state, which harbors both active marks and the repressive mark H3K27me3. Highly evolutionarily conserved, these loci are enriched in silencers bound by Polycomb Repressive Complex proteins and the transcription start sites of their silenced target genes. This collection of chromatin state assignments provides a useful resource for studying mammalian development.
Decreasing alertness modulates perceptual decision-making
Authors: Jagannathan Sridhar R. , Bareham Corinne A. , Bekinschtein Tristan A.
Published: July 2020

The ability to make decisions based on external information, prior knowledge and evidence, is a crucial aspect of cognition and may determine the success and survival of an organism. Despite extensive work on decision-making mechanisms/models, understanding the effects of alertness on neural and cognitive processes remain limited. Here we use electroencephalography and behavioural modelling to characterise cognitive and neural dynamics of perceptual decision-making in awake/low alertness periods in humans (14 male, 18 female) and characterise the compensatory mechanisms as alertness decreases. Well-rested human participants, changing between full-wakefulness and low alertness, performed an auditory tone-localisation task and its behavioural dynamics was quantified with psychophysics, signal detection theory and drift-diffusion modelling, revealing slower reaction times, inattention to the left side of space, and a lower rate of evidence accumulation in periods of low alertness. Unconstrained multivariate pattern analysis (decoding) showed a ~280ms delayed onset driven by low alertness of the neural signatures differentiating between left and right decision, with a spatial reconfiguration from centro-parietal to lateral frontal regions 150-360ms. To understand the neural compensatory mechanisms with decreasing alertness, we connected the evidence-accumulation behavioural parameter to the neural activity, showing in the early periods (125-325ms) a shift in the associated patterns from right parietal regions in awake, to right fronto-parietal during low alertness. This change in the neurobehavioural dynamics for central accumulation related cognitive processes define a clear reconfiguration of the brain networks’ regions and dynamics needed for the implementation of decision-making, revealing mechanisms of resilience of cognition when challenged by decreased alertness.

Significance statement

Most living organisms make multiple daily decisions and these require a degree of evidence from both the environment and the internal milieu. Such decisions are usually studied under sequential sampling models and involve making a behavioural choice based on sensory encoding, central accumulation, and motor implementation processes. Since there is little research on how decreasing alertness affects such cognitive processes, this study has looked at the cognitive and neural dynamics of perceptual decision-making in people while fully awake and in drowsy periods. Using computational modelling of behaviour and neural dynamics on human participants performing an auditory tone-localisation task, we reveal how low alertness modulates evidence accumulation related processes and its corresponding compensatory neural signatures.
Vast amounts of encoded items nullify but do not reverse the effect of sleep on declarative memory
Authors: Kolibius Luca D. , Born Jan , Feld Gordon B.
Published: July 2020

Sleep strengthens memories by repeatedly reactivating associated neuron ensembles. Our studies show that although long-term memory for a medium number of word-pairs (160) benefits from sleep, a large number (320) does not. This suggest an upper limit to the amount of information that has access to sleep-dependent declarative memory consolidation, which is possibly linked to the availability of reactivation opportunities. Due to competing processes of global forgetting that are active during sleep, we hypothesised that even larger amounts of information would enhance the proportion of information that is actively forgotten during sleep. In the present study, we aimed to induce such forgetting by challenging the sleeping brain with vast amounts of to be remembered information. For this, 80 participants learned a very large number of 640 word-pairs over the course of an entire day and then either slept or stayed awake during the night. Recall was tested after another night of regular sleep. Results revealed comparable retention rates between the sleep and wake groups. Although this null-effect can be reconciled the concept of limited capacities available for sleep-dependent consolidation, it contradicts our hypothesis that sleep would increase forgetting compared to the wake group. Additional exploratory analyses relying on equivalence testing and Bayesian statistics reveal that there is evidence against sleep having a detrimental effect on the retention of declarative memory at high information loads. We argue that forgetting occurs in both wake and sleep states through different mechanisms, i.e., through increased interference and through global synaptic downscaling, respectively. Both of these processes might scale similarly with information load.
ZNF416 is a pivotal transcriptional regulator of fibroblast mechano-activation
Authors: Jones Dakota L. , Meridew Jeffrey A. , Ducharme Merrick T. , Lydon Katherine L. , Choi Kyoung Moo , Caporarello Nunzia , Tan Qi , Link Patrick A. , Espinosa Ana Maria Diaz , Xiong Yuning , Lee Jeong-Heon , Ye Zhenqing , Yan Huihuang , Ordog Tamas , Ligresti Giovanni , Varelas Xaralabos , Tschumperlin Daniel J.
Published: July 2020

Matrix stiffness is a central regulator of fibroblast function. However, the transcriptional mechanisms linking matrix stiffness to changes in fibroblast phenotype are incompletely understood. Here, we evaluated the effect of matrix stiffness on genome-wide chromatin accessibility in freshly-isolated lung fibroblasts using assay for transposase-accessible chromatin followed by sequencing (ATAC-seq). We found higher matrix stiffness profoundly increased global chromatin accessibility relative to lower matrix stiffness, and these alterations were in close genomic proximity to known pro-fibrotic gene programs. Motif analysis of these regulated genomic loci identified ZNF416 as a putative mediator of fibroblast stiffness responses. Similarly, motif analysis of the promoters of differentially expressed genes observed in freshly sorted fibroblasts from an experimental bleomycin lung fibrosis model also identified ZNF416 as a putative mediator ofin vivofibroblast activation. Genome occupancy analysis using chromatin-immunoprecipitation followed by sequencing (ChIP-seq) confirmed that ZNF416 occupies a broad range of genes implicated in fibroblast activation and tissue-fibrosis, with relatively little overlap in genomic occupancy with other mechanoresponsive and pro-fibrotic transcriptional regulators. Using loss and gain of function studies we demonstrated that ZNF416 plays a critical role in fibroblast proliferation, extracellular matrix synthesis and contractile function. Together these observations identify ZNF416 as novel mechano-activated transcriptional regulator of fibroblast biology.
Reconstructing feedback representations in ventral visual pathway with a generative adversarial autoencoder
Authors: Al-Tahan Haider , Mohsenzadeh Yalda
Published: July 2020

While vision evokes a dense network of feedforward and feedback neural processes in the brain, visual processes are primarily modeled with feedforward hierarchical neural networks, leaving the computational role of feedback processes poorly understood. Here, we developed a generative autoencoder neural network model and adversarially trained it on a categorically diverse data set of images. We hypothesized that the feedback processes in the ventral visual pathway can be represented by reconstruction of the visual information performed by the generative model. We compared representational similarity of the activity patterns in the proposed model with temporal (magnetoencephalography) and spatial (functional magnetic resonance imaging) visual brain responses. The proposed generative model identified two segregated neural dynamics in the visual brain. A temporal hierarchy of processes transforming low level visual information into high level semantics in the feedforward sweep, and a temporally later dynamics of inverse processes reconstructing low level visual information from a high level latent representation in the feedback sweep. Our results append to previous studies on neural feedback processes by presenting a new insight into the algorithmic function and the information carried by the feedback processes in the ventral visual pathway.

Author summary

It has been shown that the ventral visual cortex consists of a dense network of regions with feedforward and feedback connections. The feedforward path processes visual inputs along a hierarchy of cortical areas that starts in early visual cortex (an area tuned to low level features e.g. edges/corners) and ends in inferior temporal cortex (an area that responds to higher level categorical contents e.g. faces/objects). Alternatively, the feedback connections modulate neuronal responses in this hierarchy by broadcasting information from higher to lower areas. In recent years, deep neural network models which are trained on object recognition tasks achieved human-level performance and showed similar activation patterns to the visual brain. In this work, we developed a generative neural network model that consists of encoding and decoding sub-networks. By comparing this computational model with the human brain temporal (magnetoencephalography) and spatial (functional magnetic resonance imaging) response patterns, we found that the encoder processes resemble the brain feedforward processing dynamics and the decoder shares similarity with the brain feedback processing dynamics. These results provide an algorithmic insight into the spatiotemporal dynamics of feedforward and feedback processes in biological vision.
Development of non-transgenic glyphosate tolerant wheat by TILLING
Authors: Moehs Charles P. , Austill William J. , Facciotti Daniel , Holm Aaron , Loeffler Dayna , Lu Zhongjin , Mullenberg Jessica C. , Slade Ann J. , Steine Michael N. , van Boxtel Jos , McGuire Cate
Published: July 2020

Glyphosate (N-phosphonomethyl-glycine) is the world’s most widely used broad spectrum, post-emergence herbicide. It inhibits the chloroplast-targeted enzyme 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS; EC 2.5.1.19), a component of the plant and microorganism-specific shikimate pathway and a key catalyst in the production of aromatic amino acids. Variants of EPSPS that are not inhibited by glyphosate due to particular amino acid alterations in the active site of the enzyme are known. Some of these variants have been identified in weed species that have developed resistance to glyphosate because of the strong selective pressure of continuous, heavy glyphosate use. We have used TILLING (Targeting Induced Local Lesions in Genomes), a non-transgenic, target-selected, reverse genetics mutation breeding technique, and conventional genetic crosses, to identify and combine, through two rounds of mutagenesis, wheat lines having both T102I and P106S (so-called TIPS enzyme) mutations in both the A and the D sub-genome homoeologous copies of the wheat EPSPS gene. The combined effects of the T102I and P106S mutations are known from previous work in multiple species to minimize the binding of the herbicide while maintaining the affinity of the catalytic site for its native substrates. These novel wheat lines exhibit substantial tolerance to commercially relevant levels of glyphosate.
Protein sequence design by explicit energy landscape optimization
Authors: Norn Christoffer , Wicky Basile I. M. , Juergens David , Liu Sirui , Kim David , Koepnick Brian , Anishchenko Ivan , Players Foldit , Baker David , Ovchinnikov Sergey
Published: July 2020

The protein design problem is to identify an amino acid sequence which folds to a desired structure. Given Anfinsen’s thermodynamic hypothesis of folding, this can be recast as finding an amino acid sequence for which the lowest energy conformation is that structure. As this calculation involves not only all possible amino acid sequences but also all possible structures, most current approaches focus instead on the more tractable problem of finding the lowest energy amino acid sequence for the desired structure, often checking by protein structure prediction in a second step that the desired structure is indeed the lowest energy conformation for the designed sequence, and discarding the in many cases large fraction of designed sequences for which this is not the case. Here we show that by backpropagating gradients through the trRosetta structure prediction network from the desired structure to the input amino acid sequence, we can directly optimize over all possible amino acid sequences and all possible structures, and in one calculation explicitly design amino acid sequences predicted to fold into the desired structure and not any other. We find that trRosetta calculations, which consider the full conformational landscape, can be more effective than Rosetta single point energy estimations in predicting folding and stability of de novo designed proteins. We compare sequence design by landscape optimization to the standard fixed backbone sequence design methodology in Rosetta, and show that the results of the former, but not the latter, are sensitive to the presence of competing low-lying states. We show further that more funneled energy landscapes can be designed by combining the strengths of the two approaches: the low resolution trRosetta model serves to disfavor alternative states, and the high resolution Rosetta model, to create a deep energy minimum at the design target structure.

Significance

Computational protein design has primarily focused on finding sequences which have very low energy in the target designed structure. However, what is most relevant during folding is not the absolute energy of the folded state, but the energy difference between the folded state and the lowest lying alternative states. We describe a deep learning approach which captures the entire folding landscape, and show that it can enhance current protein design methods.
Implicit auditory perception of local and global irregularities in passive listening condition
Authors: Liaukovich Krystsina , Ukraintseva Yulia , Martynova Olga
Published: July 2020

The auditory system detects differences in sounds at an implicit level, but data on this difference might not be sufficient to make explicit discrimination. The biomarkers of implicit auditory memory of ambiguous stimuli could shed light on unconscious auditory processing and implicit auditory learning. Mismatch negativity (MMN) and P3a, components of event-related potentials (ERPs) reflecting stimuli discrimination without direct attention, were previously detected in response to the local (short-term) irregularity in the auditory sequence even in an unconscious state. At the same time, P3b was elicited only in case of direct attention in response to the global (long-term) irregularity. In this study, we applied the local-global auditory paradigm to obtain possible electrophysiological signatures of implicit detection of hardly distinguishable auditory stimuli. ERPs were recorded from 20 healthy volunteers during active discrimination of deviant sounds in the old-ball sequence and passive listening of the same sounds in the sequence with local-global irregularity. The discrimination task consisted of two blocks with different deviant sounds targeted to respond. The sound discrimination accuracy was at an average of 40 %, implying the difficulty of explicit sound recognition. Comparing ERPs to standard and deviant sounds, we found posterior negativity in ERP around 450-600 ms in response to targeted deviant sounds. MMN was significant only in response to non-target deviants. In the passive local-global paradigm, we observed an anterior positivity (284-412 ms), compatible with P3a, in response to a violation of local regularity. Violation of global regularity elicited an anterior negative response (228-586 ms), resembling the N400 component of ERPs. Importantly, the other indexes of auditory discrimination, such as MMN and P3b, were insignificant in ERPs to both regularity violations. The observed P3a and N400 components of ERPs may reflect prediction error signals in the implicit perception of sound patterns even if behavioral recognition was poor.

Highlights

Processing of hardly distinguishable harmonic tones differs from processing of complex patterns, which consist of these tones

Implicit perception of local and global irregularities differs

In passive listening, local irregularity elicits frontal positivity that is associated with an involuntary switch of attention

In passive listening, global irregularity elicits late negativity that might reflect prediction error signals