bluuebunny/crossref_metadata_2025_split huggingface dataset:
Age-related neurodegeneration and cognitive impairments of NRMT1 knockout mice are preceded by misregulation of RB and expansion of the neural stem cell population
Authors: Catlin James , Marziali Leandro N. , Rein Benjamin , Yan Zhen , Feltri M. Laura , Schaner Tooley Christine E. 
Published: March 2021

AbstractN-terminal methylation is an important post-translational modification that regulates protein/DNA interactions and plays a role in many cellular processes, including DNA damage repair, mitosis, and transcriptional regulation. Our generation of a constitutive knockout mouse for the N-terminal methyltransferase NRMT1, demonstrated its loss results in severe developmental abnormalities and premature aging. As premature aging is often accompanied by neurodegeneration, we more specifically examined how NRMT1 loss affects neural pathology and cognitive behaviors. Here we find thatNrmt1-/-mice exhibit postnatal enlargement of the lateral ventricles, age-dependent striatal and hippocampal neurodegeneration, memory impairments, and hyperactivity. These morphological and behavior abnormalities are preceded by alterations in neural stem cell (NSC) development. Depletion of quiescent NSC pools inNrmt1-/-mice is concurrent with expansion of intermediate progenitor and neuroblast pools. These phenotypes are similar to those seen with loss of the NRMT1 target retinoblastoma protein (RB), and we see that NRMT1 loss leads to derepression of RB target genes and abnormal RB phosphorylation and degradation. As also seen with RB loss, neurons inNrmt1-/-mice fail to exit cell cycle and ultimately undergo NOXA-mediated apoptosis, indicating that early misregulation of RB inNrmt1-/-mice promotes premature NSC proliferation and contributes to subsequent neurodegenerative phenotypes.
Functional development of a V3-specific broadly neutralizing antibody isolated from a case of HIV superinfection
Authors: Shipley Mackenzie M. , Prasad Vidya Mangala , Doepker Laura E. , Dingens Adam , Ralph Duncan , Harkins Elias , Dhar Amrit , Arenz Dana , Chohan Vrasha , Weight Haidyn , Mandaliya Kishor , Bloom Jesse D. , Matsen Frederick A. , Lee Kelly K. , Overbaugh Julie M. 
Published: March 2021

AbstractStimulating broadly neutralizing antibodies (bnAbs) directly from germline remains a barrier for HIV vaccines. HIV superinfection elicits bnAbs more frequently than single infection, providing clues of how to elicit such responses. We used longitudinal antibody sequencing and structural studies to characterize bnAb development from a superinfection case. Mature bnAb QA013.2 bound both initial transmitted and superinfecting virus, but its inferred naïve bound only the superinfecting strain and was not neutralizing. QA013.2 requires residues spanning FWRH1-CDRH1 to attain breadth, which is uncommon for V3-specific bnAbs. A 4.15 Å cryo-EM structure of QA013.2 bound to heterologous native-like trimer showed recognition of V3 signatures (N301, N332, and GDIR). Antigenic profiling revealed that viral escape was achieved not only by changes in the structurally-defined epitope, but also by mutations in V1. These results highlight shared and distinct properties of QA013.2 relative to other V3-specific bnAbs in the setting of sequential, diverse antigenic variants.
Super interactive promoters provide insight into cell type-specific regulatory networks in blood lineage cell types
Authors: Lagler Taylor M. , Yang Yuchen , Harigaya Yuriko , Sankaran Vijay G. , Hu Ming , Reiner Alexander P. , Raffield Laura M. , Wen Jia , Li Yun 
Published: March 2021

AbstractExisting studies of chromatin conformation have primarily focused on potential enhancers interacting with gene promoters. By contrast, the interactivity of promotersper se, while equally critical to understanding transcriptional control, has been largely unexplored, particularly in a cell type-specific manner for blood lineage cell types. In this study, we leverage promoter capture Hi-C data across a compendium of blood lineage cell types to identify and characterize cell type-specific super-interactive promoters (SIPs). Notably, promoter-interacting regions (PIRs) of SIPs are more likely to overlap with cell type-specific ATAC-seq peaks and GWAS variants for relevant blood cell traits than PIRs of non-SIPs. Further, SIP genes tend to express at a higher level in the corresponding cell type, and show enriched heritability of relevant blood cell trait(s). Importantly, this analysis shows the potential of using promoter-centric analyses of chromatin spatial organization data to identify biologically important genes and their regulatory regions.
Alternative LC-MS/MS Platforms and Data Acquisition Strategies for Proteomic Genotyping of Human Hair Shafts
Authors: Goecker Zachary C. , Legg Kevin M. , Salemi Michelle R. , Herren Anthony W. , Phinney Brett S. , McKiernan Heather E. , Parker Glendon J. 
Published: March 2021

AbstractProtein is a major component of all biological evidence. Proteomic genotyping is the use of genetically variant peptides that contain single amino acid polymorphisms to infer the genotype of matching non-synonymous single nucleotide polymorphisms for the individual who originated the protein sample. This can be used to statistically associate an individual to evidence found at a crime scene. The utility of the inferred genotype increases as the detection of genetically variant peptides increases, which is the direct result of technology transfer to mass spectrometry platforms typically available. Digests of single (2 cm) human hair shafts from three European and two African subjects were analyzed using data dependent acquisition on a Q-Exactive™ Plus Hybrid Quadrupole-Orbitrap™ system, data independent acquisition and a variant of parallel reaction monitoring on a Orbitrap Fusion™ Lumos™ Tribrid™ system, and multiple reaction monitoring on an Agilent 6495 triple quadrupole system. In our hands, average genetically variant peptide detection from a selected 24 genetically variant peptide panel increased from 6.5 ± 1.1 and 3.1 ± 0.8 using data dependent and independent acquisition to 9.5 ± 0.7 and 11.7 ± 1.7 using parallel reaction monitoring and multiple reaction monitoring (p < 0.05). Parallel reaction monitoring resulted in a 1.3-fold increase in detection sensitivity, and multiple reaction monitoring resulted in a 1.6-fold increase in detection sensitivity. This increase in biomarker detection has a functional impact on the statistical association of a protein sample and an individual. Increased biomarker sensitivity, using Markov Chain Monte Carlo modeling, produced a median estimated random match probability of over 1 in 10 trillion from a single hair using targeted proteomics. For parallel reaction monitoring and multiple reaction monitoring, detected genetically variant peptides were validated by the inclusion of stable isotope labeled peptides in each sample, which served also as a detection trigger. This research accomplishes two aims: the demonstration of utility for alternative analytical platforms in proteomic genotyping, and the establishment of validation methods for the evaluation of inferred genotypes.HighlightsTest four mass spectrometry configurations to optimize detection of genetically variant peptidesTechnology transfer of proteomic genotyping assaysImproved sensitivity results in higher level of forensic discrimination for human identification using multiple reaction monitoringGraphical Abstract
Retinal factors of visual sensitivity in the human fovea
Authors: Domdei Niklas , Reiniger Jenny L. , Holz Frank G. , Harmening Wolf 
Published: March 2021

AbstractHumans direct their gaze towards visual objects of interest such that the retinal images of fixated objects fall onto the fovea, a small anatomically and physiologically specialized region of the retina displaying highest visual fidelity. One striking anatomical feature of the fovea is its non-uniform cellular topography, with a steep decline of cone photoreceptor density and outer segment length with increasing distance from its center. We here assessed in how far the specific cellular organization of the foveola is reflected in visual function. Increment sensitivity to small spot visual stimuli (1 x 1 arcmin, 543 nm light) was recorded psychophysically in 4 human participants at 17 locations placed concentric within a 0.2-degree diameter around the preferred retinal locus of fixation with adaptive optics scanning laser ophthalmoscopy based microstimulation. While cone density as well as maximum outer segment length differed significantly among the four tested participants, the range of observed threshold was similar, yielding an average increment threshold of 3.3 ± 0.2 log10 photons at the cornea. Thresholds were correlated with retinal eccentricity, as well as cone density and outer segment length. Biophysical simulation allowed to develop a model of foveal sensitivity based on these parameters, explaining at least 37% of the observed threshold variability. Based on high reproducibility in replicate testing, the residual variability is assumed to be caused by individual cone and bipolar cell weighting at the specific target locations.
Spatial representation by ramping activity of neurons in the retrohippocampal cortex
Authors: Tennant Sarah A. , Clark Harry , Hawes Ian , Tam Wing Kin , Hua Junji , Yang Wannan , Gerlei Klara Z. , Wood Emma R. , Nolan Matthew F. 
Published: March 2021

SummaryNeurons in the retrohippocampal cortices play crucial roles in spatial memory. Many retrohippocampal neurons have firing fields that are selectively active at specific locations, with memory for rewarded locations associated with reorganisation of these firing fields. Whether this is the sole strategy for representing spatial memories is unclear. Here, we demonstrate that during a spatial memory task retrohippocampal neurons encode location through ramping activity that extends within segments of a linear track approaching and following a reward, with the rewarded location represented by offsets or switches in the slope of the ramping activity. These ramping representations could be maintained independently of trial outcome and cues that mark the reward location, indicating that they result from recall of the track structure. During recordings in an open arena, neurons that generated ramping activity during the spatial memory task were more numerous than grid or border cells, with a majority showing spatial firing that did not meet criteria for classification as grid or border representations. Encoding of rewarded locations through offsets and switches in the slope of ramping activity also emerged in recurrent neural networks trained to solve a similar location memory task. Impaired performance of these networks following disruption of outputs from ramping neurons is consistent with this coding strategy supporting navigation to recalled locations of behavioural significance. We hypothesise that retrohippocampal ramping activity mediates readout of learned models for goal-directed navigation.
Predicting Cellular Drug Sensitivity using Conditional Modulation of Gene Expression
Authors: Connell Will , Keiser Michael 
Published: March 2021

AbstractSelecting drugs most effective against a tumor’s specific transcriptional signature is an important challenge in precision medicine. To assess oncogenic therapy options, cancer cell lines are dosed with drugs that can differentially impact cellular viability. Here we show that basal gene expression patterns can be conditioned by learned small molecule structure to better predict cellular drug sensitivity, achieving anR2of 0.7190±0.0098 (a 5.61% gain). We find that 1) transforming gene expression values by learned small molecule representations outperforms raw feature concatenation, 2) small molecule structural features meaningfully contribute to learned representations, and 3) an affine transformation best integrates these representations. We analyze conditioning parameters to determine how small molecule representations modulate gene expression embeddings. This ongoing work formalizesin silicocellular screening as a conditional task in precision oncology applications that can improve drug selection for cancer treatment.
The brown algaeSaccharina japonicaandSargassum horneriexhibit species-specific responses to synergistic stress of ocean acidification and eutrophication
Authors: Liu Yuxin , Cao Jiazhen , Chu Yaoyao , Liu Yan , Wang Qiaohan , Gong Qingli , Li Jingyu 
Published: March 2021

AbstractOcean acidification and eutrophication are two important environmental stressors. They inevitably impact marine macroalgae, and hence the coastal ecosystem of China.Saccharina japonica, as the main culture species in China, is suffering the harmful golden tide caused bySargassum horneri. However, it remains unclear whether the detrimental effects ofS. hornerionS. japonicacultivation become more severe in future acidified and eutrophic scenario. In this study, we respectively investigated the effects ofpCO2(400 μatm and 1000 μatm) and nutrients (non-enriched and enriched seawater) on the growth, photosynthesis, respiration, chlorophyll contents, and tissue nitrogen ofS. japonicaandS. horneri. Results indicated that enrichment of nutrients contributedS. hornerito utilize HCO3-. The carbon acquisition pathway shifted from HCO3-to CO2inS. japonica, whileS. horneriremained using HCO3-regulated by nutrient enrichment.S. horneriexhibited better photosynthetic traits thanS. japonica, with a higher level of net photosynthetic rate and chlorophyll contents at elevatedpCO2and enriched nutrients. Tissue nitrogen also accumulated richly in the thalli ofS. horneriunder higherpCO2and nutrients. Significant enhancement in growth was only detected inS. horneriunder synergistic stress. Together,S. hornerishowed competitive dominance in current study. These findings suggest that increasing risk of golden tide in acidified and eutrophic ocean can most likely result in great damage toS. japonicacultivation.
Machine learning methods trained on simple models can predict critical transitions in complex natural systems
Authors: Deb Smita , Sidheekh Sahil , Clements Christopher F. , Krishnan Narayanan C. , Dutta Partha S. 
Published: March 2021

Abstract1. Sudden transitions from one stable state to a contrasting state occur in complex systems ranging from the collapse of ecological populations to climatic change, with much recent work seeking to develop methods to predict these unexpected transitions from signals in time series data. However, previously developed methods vary widely in their reliability, and fail to classify whether an approaching collapse might be catastrophic (and hard to reverse) or non-catastrophic (easier to reverse) with significant implications for how such systems are managed.2. Here we develop a novel detection method, using simulated outcomes from a range of simple mathematical models with varying nonlinearity to train a deep neural network to detect critical transitions - the Early Warning Signal Network (EWSNet).3. We demonstrate that this neural network (EWSNet), trained on simulated data with minimal assumptions about the underlying structure of the system, can predict with high reliability observed real-world transitions in ecological and climatological data. Importantly, our model appears to capture latent properties in time series missed by previous warning signals approaches, allowing us to not only detect if a transition is approaching but critically whether the collapse will be catastrophic or non-catastrophic.4. The EWSNet can flag a critical transition with unprecedented accuracy, overcoming some of the major limitations of traditional methods based on phenomena such as Critical Slowing Down. These novel properties mean EWSNet has the potential to serve as a universal indicator of transitions across a broad spectrum of complex systems, without requiring information on the structure of the system being monitored. Our work highlights the practicality of deep learning for addressing further questions pertaining to ecosystem collapse and have much broader management implications.
Pyrolyzed substrates induce aromatic compound metabolism in the post-fire fungus,Pyronema domesticum
Authors: Fischer Monika S. , Stark Frances Grace , Berry Timothy D. , Zeba Nayela , Whitman Thea , Traxler Matthew F. 
Published: March 2021

ABSTRACTWildfires represent a fundamental and profound disturbance in many ecosystems, and their frequency and severity are increasing in many regions of the world. Fire affects soil by removing carbon in the form of CO2and transforming remaining surface carbon into pyrolyzed organic material (PyOM). Fires also generate substantial necromass at depths where the heat kills soil organisms but does not catalyze the formation of PyOM.Pyronemaspecies strongly dominate soil fungal communities within weeks to months after fire. However, the carbon pool (i.e. necromass or PyOM) that fuels their rise in abundance is unknown. We used aPyronema domesticumisolate from the catastrophic 2013 Rim Fire (CA, USA) to ask ifP. domesticumis capable of metabolizing PyOM.P. domesticumgrew readily on agar media where the sole carbon source was PyOM (specifically, pine wood PyOM produced at 750 °C). Using RNAseq, we investigated the response ofP. domesticumto PyOM and observed a comprehensive induction of genes involved in the metabolism and mineralization of aromatic compounds, typical of those found in PyOM. Lastly, we used13C-labeled 750 °C PyOM to demonstrate thatP. domesticumis capable of mineralizing PyOM to CO2. Collectively, our results indicate a robust potential forP. domesticumto liberate carbon from PyOM in post-fire ecosystems and return it to the bioavailable carbon pool.IMPORTANCEFires are increasing in frequency and severity in many regions across the world. Thus, it’s critically important to understand how our ecosystems respond to inform restoration and recovery efforts. Fire transforms the soil, removing many nutrients while leaving behind both nutritious necromass and complex pyrolyzed organic matter, which is often recalcitrant. Filamentous fungi of the genusPyronemastrongly dominate soil fungal communities soon after fire. While Pyronema are key pioneer species in post-fire environments, the nutrient source that fuels their rise in abundance is unknown. In this manuscript, we used a P. domesticum isolate from the catastrophic 2013 Rim Fire (CA, USA) to demonstrate thatP. domesticummetabolizes pyrolyzed organic material, effectively liberating this complex pyrolyzed carbon and returning it to the bioavailable carbon pool. The success of Pyronema in post-fire ecosystems has the potential to kick-start growth of other organisms and influence the entire trajectory of post-fire recovery.
Overexpression of the RNA-binding protein NrdA affects global gene expression and secondary metabolism inAspergillusspecies
Authors: Kadooka Chihiro , Izumitsu Kosuke , Asai Teigo , Mori Kazuki , Okutsu Kayu , Yoshizaki Yumiko , Takamine Kazunori , Goto Masatoshi , Tamaki Hisanori , Futagami Taiki 
Published: March 2021

ABSTRACTRNA-binding protein Nrd1 plays a role in RNA polymerase II transcription termination. In this study, we showed that the orthologous NrdA is important in global mRNA expression and secondary metabolism inAspergillusspecies. We constructed annrdAconditional expression strain using the Tet-On system inAspergillus luchuenesismut.kawachii. Downregulation ofnrdAcaused a severe growth defect, indicating that NrdA is essential for the proliferation ofA. kawachii. Parallel RNA-sequencing and RNA immunoprecipitation-sequencing analysis identified potential NrdA-interacting transcripts, corresponding to 32% of the predicted protein coding genes ofA. kawachii. Subsequent gene ontology analysis suggested that overexpression of NrdA affects the production of secondary metabolites. To clarify this, we constructed NrdA-overexpressing strains ofAspergillus nidulans,Aspergillus fumigatus, andAspergillus oryzae. Overexpression of NrdA reduced the production of sterigmatocystin and penicillin inA. nidulans, as well as that of helvolic acid and pyripyropene A inA. fumigatus. Moreover, it increased the production of kojic acid and reduced production of penicillin inA. oryzae. These effects were accompanied by almost consistent transcriptional changes in the relevant genes. Collectively, these results suggest that NrdA is the essential RNA-binding protein, which plays a significant role in global gene expression and secondary metabolism inAspergillusspecies.IMPORTANCENrd1, a component of the Nrd1–Nab3–Sen1 complex, is an essential RNA-binding protein involved in transcriptional termination in yeast. However, its role in filamentous fungi has not been studied. In this study, we characterized an orthologous NrdA in theAspergillusspecies, identified potential NrdA-interacting mRNA, and investigated the effect of overexpression of NrdA on mRNA expression inAspergillus luchuensismut.kawachii. The results indicated that NrdA controls global gene expression involved in versatile metabolic pathways, including the secondary metabolic process. We demonstrated that NrdA overexpression significantly affected the production of secondary metabolites inAspergillus nidulans,Aspergillus oryzae, andAspergillus fumigatus. Our findings are of importance to the fungal research community because the secondary metabolism is an industrially and clinically important aspect for theAspergillusspecies.
Faecal shedding models for SARS-CoV-2 RNA among hospitalised patients and implications for wastewater-based epidemiology
Authors: Hoffmann Till , Alsing Justin 
Published: March 2021

SummaryThe concentration of SARS-CoV-2 RNA in faeces is not well established, posing challenges for wastewater-based surveillance of COVID-19 and risk assessments of environmental transmission. We develop versatile hierarchical models for faecal RNA shedding and apply them to data collected in six studies. We find that the mean number of gene copies per mL of faeces is 1.9 × 106(2.3 × 105–2.0 × 10895% credible interval) among unvaccinated hospitalised patients. Using Bayesian model comparison, we find no evidence for a subpopulation of patients who do not shed RNA: limits of quantification can account for negative stool samples. Our models indicate that hospitalised patients represent the tail of the shedding profile with a half-life of 34 hours (28–43 95% credible interval), suggesting that wastewater-based surveillance signals are more indicative of incidence than prevalence and can be a leading indicator of clinical presentation. Shedding among inpatients cannot explain high RNA concentrations observed in wastewater, consistent with more abundant shedding during the early infection course. We show that the models generalise and can predict summary statistics of held-out clinical datasets. However, shedding prior to hospitalisation cannot be constrained due to lack of samples, and information on viral variants was not available.