bluuebunny/crossref_metadata_2025_split huggingface dataset:
Novel regulation of the transcription factor ZHX2 by N-terminal methylation
Authors: Conner Meghan M. , Parker Haley V. , Falcone Daniela R. , Chung Gehoon , Schaner Tooley Christine E. 
Published: October 2021

AbstractN-terminal methylation (Nα-methylation) by the methyltransferase NRMT1 is an important post-translational modification that regulates protein-DNA interactions. Accordingly, its loss impairs functions that are reliant on such interactions, including DNA repair and transcriptional regulation. Global loss of Nα-methylation results in severe developmental and premature aging phenotypes, but given over 300 predicted substrates, it is hard to discern which physiological substrates contribute to each phenotype. One of the most striking phenotypes in NRMT1 knockout (Nrmt1-/-) mice is early liver degeneration. To identify the disrupted signaling pathways leading to this phenotype and the NRMT1 substrates involved, we performed RNA-sequencing analysis of control and Nrmt1-/- adult mouse livers. We found both a significant upregulation of transcripts in the cytochrome P450 (CYP) family and downregulation of transcripts in the major urinary protein (MUP) family. Interestingly, transcription of both families is inversely regulated by the transcription factor zinc fingers and homeoboxes 2 (ZHX2). ZHX2 contains a non-canonical NRMT1 consensus sequence, indicating its function could be directly regulated by Nα-methylation. We confirmed misregulation of CYP and MUP mRNA and protein levels in Nrmt1-/- livers and verified NRMT1 can methylate ZHX2 in vitro. In addition, we used mutants of ZHX2 that cannot be methylated to directly demonstrate Nα-methylation promotes ZHX2 transcription factor activity. Finally, we show Nrmt1-/- mice also exhibit early postnatal de-repression of ZHX2 targets involved in fetal liver development. Taken together, these data implicate continual ZHX2 misregulation as a driving force behind the liver phenotype seen in Nrmt1-/- mice.
Drift on holey landscapes as a dominant evolutionary process
Authors: Dochtermann Ned A. , Klock Brady , Roff Derek A. , Royauté Raphaël 
Published: October 2021

AbstractAn organism’s phenotype has been shaped by evolution but the specific processes have to be indirectly inferred for most species. For example, correlations among traits imply the historical action of correlated selection and, more generally, the expression and distribution of traits is expected to be reflective of the adaptive landscapes that have shaped a population. However, our expectations about how quantitative traits—like most behaviors, physiological processes, and life-history traits—should be distributed under different evolutionary processes is not clear. Here we show that genetic variation in quantitative traits is not distributed as would be expected under dominant evolutionary models. Instead, we found that genetic variation in quantitative traits across 6 phyla and 60 species (including both Plantae and Animalia) is consistent with evolution across high dimensional “holey landscapes”. This suggests that the leading conceptualizations and modeling of the evolution of trait integration fail to capture how phenotypes are shaped and that traits are integrated in a manner contrary to predictions of dominant evolutionary theory. Our results demonstrate that our understanding of how evolution has shaped phenotypes remains incomplete and these results provide a starting point for reassessing the relevance of existing evolutionary models.Significance StatementWe found that empirical estimations of how quantitative genetic variation is distributed do not correspond to typical Gaussian representations of fitness landscapes. These Gaussian landscapes underpin major areas of evolutionary biology and how selection is estimated in natural populations. Rather than being consistent with evolution on Gaussian landscapes, empirical estimates of genetic variation are, instead, consistent with evolution on high-dimensional “holey” landscapes. These landscapes represent situations where specific combinations of trait values are either viable or not and populations randomly drift among the viable combinations. This finding suggests that we have substantially misunderstood how selection actually shapes populations and thus how evolution typically proceeds.
Optimal confidence for unaware visuomotor deviations
Authors: Pereira Michael , Skiba Rafal , Cojan Yann , Vuilleumier Patrik , Bègue Indrit 
Published: October 2021

AbstractNumerous studies have shown that humans can successfully correct deviations to ongoing movements without being aware of them, suggesting limited conscious monitoring of visuomotor performance. Here, we ask whether such limited monitoring impairs the capacity to judiciously place confidence ratings to reflect decision accuracy (metacognitive sensitivity). To this end, we recorded functional magnetic resonance imaging data while thirty-one participants reported visuomotor cursor deviations and rated their confidence retrospectively. We show that participants use a summary statistic of the unfolding visual feedback (the maximum cursor error) to detect deviations but that this information alone is insufficient to explain detection performance. The same summary statistics is used by participants to optimally adjust their confidence ratings, even for unaware deviations. At the neural level, activity in the ventral striatum tracked high confidence, whereas a broad network including the anterior prefrontal cortex encoded cursor error but not confidence, shedding new light on a role of the anterior prefrontal cortex for action monitoring rather than confidence. Together, our results challenge the notion of limited action monitoring and uncover a new mechanism by which humans optimally monitor their movements as they unfold, even when unaware of ongoing deviations.
Melanoma Addiction to GCDH is Mediated by NRF2 Tumor Suppressor Function
Authors: Verma Sachin , Crawford David , Khateb Ali , Feng Yongmei , Sergienko Eduard , Pathria Gaurav , Ma Chen-Ting , Olson Steven H , Scott David , Murad Rabi , Ruppin Eytan , Jackson Michael , Ronai Ze’ev A 
Published: October 2021

AbstractTumor dependency on specific metabolic signals has guided numerous therapeutic approaches. Here we identify melanoma addiction to the mitochondrial protein Glutaryl-CoA dehydrogenase (GCDH), a component in lysine metabolism which controls protein glutarylation. GCDH knockdown promoted apoptotic Unfolded Protein Response signaling and cell death in melanoma cells, an activity blocked by knockdown of the upstream lysine catabolism enzyme DHTKD1. Correspondingly, reduced GCDH expression correlated with improved survival of melanoma patients. A key mediator of GCDH-dependent melanoma cell death programs is the transcription factor NRF2, which induces ATF3, CHOP, and CHAC1 transcription linking lysine catabolism with the UPR signaling. NRF2 glutarylation upon GCDH KD increased its stability and DNA binding activity, which coincided with increased transcriptional activity, promoting apoptotic UPR signaling and tumor suppression. In vivo, genetic GCDH inhibition effectively inhibited melanoma tumor growth. Overall, these findings demonstrate an addiction of melanoma cells to GCDH, which by controlling NRF2 glutarylation limits apoptotic UPR signaling. Inhibiting the GCDH pathway could represent a novel therapeutic modality to treat melanoma.
selscan 2.0: scanning for sweeps in unphased data
Authors: Szpiech Zachary A. 
Published: October 2021

AbstractSummarySeveral popular haplotype-based statistics for identifying recent or ongoing positive selection in genomes require knowledge of haplotype phase. Here we provide an update to selscan which implements a re-definition of these statistics for use in unphased data.Availability and ImplementationSource code and binaries freely available athttps://github.com/szpiech/selscan, implemented in C/C++ and supported on Linux, Windows, and MacOS.Contactszpiech@psu.eduSupplemental InformationOnline supplemental information available
NanoSplicer: Accurate identification of splice junctions using Oxford Nanopore sequencing
Authors: You Yupei , Clark Michael B. , Shim Heejung 
Published: October 2021

AbstractMotivationLong read sequencing methods have considerable advantages for characterising RNA isoforms. Oxford nanopore sequencing records changes in electrical current when nucleic acid traverses through a pore. However, basecalling of this raw signal (known as a squiggle) is error prone, making it challenging to accurately identify splice junctions. Existing strategies include utilising matched short-read data and/or annotated splice junctions to correct nanopore reads but add expense or limit junctions to known (incomplete) annotations. Therefore, a method that could accurately identify splice junctions solely from nanopore data would have numerous advantages.ResultsWe developed “NanoSplicer” to identify splice junctions using raw nanopore signal (squiggles). For each splice junction the observed squiggle is compared to candidate squiggles representing potential junctions to identify the correct candidate. Measuring squiggle similarity enables us to compute the probability of each candidate junction and find the most likely one. We tested our method using 1. synthetic mRNAs with known splice junctions 2. biological mRNAs from a lung-cancer cell-line. The results from both datasets demonstrate NanoSplicer improves splice junction identification, especially when the basecalling error rate near the splice junction is elevated. Our method is implemented in the software package NanoSplicer, available at https://github.com/shimlab/NanoSplicer.
Spatiotemporal transcriptome at single-cell resolution reveals key radial glial cell population in axolotl telencephalon development and regeneration
Authors: Wei Xiaoyu , Fu Sulei , Li Hanbo , Liu Yang , Wang Shuai , Feng Weimin , Yang Yunzhi , Liu Xiawei , Zeng Yan-Yun , Cheng Mengnan , Lai Yiwei , Qiu Xiaojie , Wu Liang , Zhang Nannan , Jiang Yujia , Xu Jiangshan , Su Xiaoshan , Peng Cheng , Han Lei , Lou Wilson Pak-Kin , Liu Chuanyu , Yuan Yue , Ma Kailong , Yang Tao , Pan Xiangyu , Gao Shang , Chen Ao , Esteban Miguel A. , Yang Huanming , Wang Jian , Fan Guangyi , Liu Longqi , Chen Liang , Xu Xun , Fei Ji-Feng , Gu Ying 
Published: October 2021

SUMMARYBrain regeneration requires a precise coordination of complex responses in a time- and region-specific manner. Identifying key cell types and molecules that direct brain regeneration would provide potential targets for the advance of regenerative medicine. However, progress in the field has been hampered largely due to limited regeneration capacity of the mammalian brain and understanding of the regeneration process at both cellular and molecular level. Here, using axolotl brain with extrodinary regeneration ability upon injury, and the SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq), we reconstructed the first architecture of axolotl telencephalon with gene expression profiling at single-cell resolution, and fine cell dynamics maps throughout development and regeneration. Intriguingly, we discovered a marked heterogeneity of radial glial cell (RGC) types with distinct behaviors. Of note, one subtype of RGCs is activated since early regeneration stages and proliferates while other RGCs remain dormant. Such RGC subtype appears to be the major cell population involved in early wound healing response and gradually covers the injured area before presumably transformed into the lost neurons. Altogether, our work systematically decoded the complex cellular and molecular dynamics of axolotl telencephalon in development and regeneration, laying the foundation for studying the regulatory mechanism of brain regeneration in the future.
Retraction ATPase motors from three orthologous type IVa pilus systems support promiscuous retraction of the Vibrio cholerae competence pilus
Authors: Couser Evan , Chlebek Jennifer L. , Dalia Ankur B. 
Published: October 2021

ABSTRACTBacterial surface appendages called type IVa pili (T4aP) promote diverse activities including DNA uptake, twitching motility, and virulence. These activities rely on the ability of T4aP to dynamically extend and retract from the cell surface. Dynamic extension relies on a motor ATPase commonly called PilB. Most T4aP also rely on specific motor ATPases, commonly called PilT and PilU, to dynamically and forcefully retract. Here, we systematically assess whether motor ATPases from three orthologous T4aP can functionally complement Vibrio cholerae mutants that lack their endogenous motors. We found that the PilT and PilU retraction ATPases from the three T4aP systems tested are promiscuous and promote retraction of the V. cholerae competence T4aP despite a high degree of sequence divergence. In contrast, the orthologous extension ATPases from the same T4aP systems were not able to mediate extension of the V. cholerae competence T4aP despite exhibiting a similar degree of sequence divergence. Also, we show that one of the PilT orthologs characterized does not support PilU-dependent retraction and provide some data to indicate that the C-terminus of PilT is important for PilU-dependent retraction. Together, our data suggest that retraction ATPases may have maintained a high degree of promiscuity for promoting retraction of T4aP, while extension ATPases may have evolved to become specific for their cognate systems.IMPORTANCEOne way that bacteria interact with their environments is via hair-like appendages called type IVa pili (T4aP). These appendages dynamically extend and retract from the cell surface via the action of distinct ATPase motors. T4aP are present in diverse bacterial species. Here, we demonstrate that retraction motors from three T4aP are promiscuous, and capable of promoting retraction of a heterologous T4aP system. By contrast, the extension ATPase motors from these same T4aP systems are specific and cannot promote extension of a heterologous T4aP. Thus, these results suggest that T4aP extension may be more tightly regulated compared to T4aP retraction.
Loss-of-function, gain-of-function and dominant-negative mutations have profoundly different effects on protein structure: implications for variant effect prediction
Authors: Gerasimavicius Lukas , Livesey Benjamin J , Marsh Joseph A. 
Published: October 2021

AbstractMost known pathogenic mutations occur in protein-coding regions of DNA and change the way proteins are made. Taking protein structure into account has therefore provided great insight into the molecular mechanisms underlying human genetic disease. While there has been much focus on how mutations can disrupt protein structure and thus cause a loss of function (LOF), alternative mechanisms, specifically dominant-negative (DN) and gain-of-function (GOF) effects, are less understood. Here, we have investigated the protein-level effects of pathogenic missense mutations associated with different molecular mechanisms. We observe striking differences between recessive vs dominant, and LOF vs non-LOF mutations, with dominant, non-LOF disease mutations having much milder effects on protein structure, and DN mutations being highly enriched at protein interfaces. We also find that nearly all computational variant effect predictors underperform on non-LOF mutations, even those based solely on sequence conservation. However, we do find that non-LOF mutations could potentially be identified by their tendency to cluster in three-dimensional space. Overall, our work suggests that many pathogenic mutations that act via DN and GOF mutations are likely being missed by current variant prioritisation strategies, but that there is considerable scope to improve computational predictions through consideration of molecular disease mechanisms.
Benchmarking AlphaFold for protein complex modeling reveals accuracy determinants
Authors: Yin Rui , Feng Brandon Y. , Varshney Amitabh , Pierce Brian G. 
Published: October 2021

AbstractHigh resolution experimental structural determination of protein-protein interactions has led to valuable mechanistic insights, yet due to the massive number of interactions and experimental limitations there is a need for computational methods that can accurately model their structures. Here we explore the use of the recently developed deep learning method, AlphaFold, to predict structures of protein complexes from sequence. With a benchmark of 152 diverse heterodimeric protein complexes, multiple implementations and parameters of AlphaFold were tested for accuracy. Remarkably, many cases had highly accurate models generated as top-ranked predictions, greatly surpassing the performance of unbound protein-protein docking, whereas antibody-antigen docking was largely unsuccessful. While AlphaFold-generated accuracy predictions were able to discriminate near-native models, previously developed scoring protocols improved performance. Our study demonstrates that end-to-end deep learning can accurately model transient protein complexes, and identifies areas for improvement to guide future developments to reliably model any protein-protein interaction of interest.
MRGM: a mouse reference gut microbiome reveals a large functional discrepancy for gut bacteria of the same genus between mice and humans
Authors: Kim Nayeon , Kim Chan Yeong , Yang Sunmo , Park Dongjin , Ha Sang-Jun , Lee Insuk 
Published: October 2021

ABSTRACTThe gut microbiome is associated with human diseases and interacts with dietary components and drugs. In vivo mouse models may be effective for studying diet and drug effects on the gut microbiome. We constructed a mouse reference gut microbiome (MRGM, https://www.mbiomenet.org/MRGM/) that includes newly-assembled genomes from 878 metagenomes. Leveraging samples with ultra-deep metagenomic sequencing (>130 million read pairs), we demonstrated quality improvement in assembled genomes for mouse gut microbes as sequencing depth increased. MRGM provides a catalog of 46,267 non-redundant genomes with ≥70% completeness and ≤5% contamination comprising 1,689 representative bacterial species and 15.2 million non-redundant proteins. Importantly, MRGM significantly improved the taxonomic classification rate of sequencing reads from mouse fecal samples compared to previous databases. Using MRGM, we determined that reliable low-abundance taxa profiles of the mouse gut microbiome require sequencing >10 million reads. Despite the high overall functional similarity of the mouse and human gut microbiomes, only ~10% of MRGM species are shared with the human gut microbiome. Although ~80% of MRGM genera are present in the human gut microbiome, ~70% of the shared genera have <40% of core gene content for the respective genus with human counterparts. These suggest that although metabolic processes of the human gut microbiome largely occur in the mouse gut microbiome, functional translations between them according to genus-level taxonomic commonality require caution.Key PointsMRGM provides 46,267 genomes comprising 1,689 bacterial species of mouse gut microbiome.Despite high overlap of genera, functional discrepancy between mouse and human gut microbiota is large.Lineage-specific markers underestimate the completeness of assembled genomes for uncharacterized taxa.
Allele and genotype frequencies of CYP3A4, CYP3A5, CYP3A7, and GSTP1 gene polymorphisms among mainland Tibetan, Mongolian, Uyghur, and Han Chinese populations
Authors: Qi Guangzhao , Han Chao , Zhou Yubing , Wang Xin 
Published: October 2021

AbstractOver 50% prescribed drugs are metabolised by cytochrome P450 3A (CYP3A) and glutathione S‐transferase pi (GSTP1) adds a glutathione to the oxidative products by CYP3A, which increases the hydrophilic property of metabolites and facilitates the excretion. Single nucleotide polymorphisms (SNPs) of CYP3A and GSTP1 show a diverse allele and genotype frequencies distribution among the world populations. The present study aimed to investigate the genotype and allele frequency distribution patterns of CYP3A4, CYP3A5, CYP3A7 and GSTP1 polymorphisms among healthy participants in mainland Tibetan, Mongolian, Uyghur, and Han Chinese populations. Blood samples were collected from 842 unrelated healthy subjects (323 Tibetan, 134 Mongolian, 162 Uyghur, and 223 Han) for genotyping analysis. Variant allele frequencies of CYP3A4 rs2242480, CYP3A5 rs776746, CYP3A7 rs2257401, and GSTP1 Ile105Val were observed in Han (0.253, 0.686, 0.312 and 0.188), Tibetan (0.186, 0.819, 0.192 and 0.173), Mongolian (0.198, 0.784, 0.228 and 0.235) and Uyghur (0.179, 0.858, 0.182 and 0.250) respectively. The allele frequency of CYP3A7*1C in Uyghur (0.019) was higher than that in Tibetan (0.002, p < 0.01). There was a strong linkage disequilibrium between CYP3A4 rs2242480, CYP3A5 rs776746, and CYP3A7 rs2257401 among the four ethnic groups. The results might be useful for the precise medication in the Chinese populations.
Ultrastructural observation of filtration membrane in cell‐free and concentrated ascites reinfusion therapy for malignant ascites
Authors: Koga Kenichi , Ishihara Takeshi , Doi Yohei , Suzuki Ryota , Komatsu Masakazu , Abe Kosei , Tanaka Takahiro , Iwaki Ryuji , Hashi Hiroyuki , Sugawara Akira 
Published: October 2021

AbstractIntroductionCell‐free and concentrated ascites reinfusion therapy (CART) is used for the treatment of diuretic‐resistant ascites. An increase in circuit pressure and clogging of the filtration membrane often occur in CART for malignant ascites.MethodsTo clarify the precise mechanism of filter clogging, we performed an ultrastructural observation study of the filtration membrane after the filtration of malignant ascites.ResultsThe deposition on the filtration membrane was composed of blood cells, fibrin, or both. Cellular deposition was associated with a greater number of blood cells in the original ascites fluid. In contrast, fibrin deposition was associated with higher levels of interleukin‐6, α1‐antitrypsin, haptoglobin, and fibrinogen/fibrin degradation products.ConclusionOur results suggest that the specific pathophysiologies of malignancy (such as inflammation or coagulation/fibrinolysis) and characteristics of malignant ascites (highly concentrated and cell‐rich) are associated with clogging of the filtration membrane during CART.
Chromosome‐scale genome assembly of Castanopsis tibetana provides a powerful comparative framework to study the evolution and adaptation of Fagaceae trees
Authors: Sun Ye , Guo Jianling , Zeng Xiaorong , Chen Risheng , Feng Yi , Chen Shuang , Yang Kai 
Published: October 2021

AbstractFagaceae species are increasingly used as models to elucidate the process and mechanism of adaptation and speciation by integrating ecology, evolution and genomics. The genus Castanopsis belongs to the family Fagaceae and is mainly distributed across subtropical and tropical Asia. In the present study, we reported the first chromosome‐scale genome assembly of Castanopsis tibetana, a common species of evergreen broadleaved forests in subtropical China. The combination of Nanopore sequencing and Hi‐C technologies enabled a high‐quality genome assembly. The final assembled genome size of C. tibetana was 878.6 Mb (97.6% of the estimated genome size), consisting of 477 contigs with an N50 length of 3.3 Mb. The benchmarking universal single‐copy orthologue (BUSCO) assessment indicated a completeness of 93.0%. Hi‐C scaffolding generated 12 pseudochromosomes, representing 98.7% of the assembled genome. Subsequently, 40,937 protein‐coding genes were predicted and 90.04% of them were functionally annotated. More than 476.9 Mb of repetitive sequences (54.3% of the genome) were identified, and the percentage of the genome covered by TE elements was 39.98%. Comparative genomics analysis revealed that C. tibetana was most closely related to Castanea mollissima and diverged at 18.48 Ma, and that C. tibetana has undergone considerable gene family expansion and contraction. Evidence of positive selection was detected in 53 genes, which showed different arrangement pattern compared to Quercus robur. The chromosome‐scale genome assembly of C. tibetana will expand Fagaceae genome resources across the family and provide a powerful comparative framework to study the adaptation and evolution of Fagaceae trees.