bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quantification of genetic variants in bacterial cultures by Sanger sequencing
Authors: Prakash Satya , Racovita Adrian , Petrucci Teresa , Galizi Roberto , Jaramillo Alfonso 
Published: July 2022

AbstractGenetic variations such as mutations and recombinations arise spontaneously in all cultured organisms. Although it is possible to identify non-neutral mutations by selection or counter- selection, neutral mutations usually require DNA sequencing to be identified in a population, which are normally expensive and time-consuming. Neutral mutations could even become dominant under changing environmental conditions enforcing transitory selection or counter- selection. We propose a novel methodology to quantify DNA using Sanger sequencing, that we validated experimentally with specially-engineered plasmids both in vitro and in co-transformed E. coli by and assessing our predictions with qPCR and fluorescence quantifications. The method relies on the alignment of the electropherograms from the query and reference samples, where we quantify the DNA concentration from the amplitude ratio of aligned electropherogram peaks. Our DNA quantification will allow quantifying genetic variants, including single-base natural polymorphisms or de novo mutations, from mixed Sanger sequencing reads, with consistent reduction of costs compared to canonical approaches such as qPCR.
Architecture of the NADH:ferredoxin oxidoreductase RNF that drives Biological Nitrogen Fixation
Authors: Zhang Lin , Einsle Oliver 
Published: July 2022

Biological nitrogen fixation requires substantial metabolic energy in form of ATP, as well as low-potential electrons that must derive from central metabolism. During aerobic growth, the free-living soil diazotrophAzotobacter vinelandiitransfers electrons from the key metabolite NADH to the low-potential ferredoxin FdxA that serves as a direct electron donor to the dinitrogenase reductases. This process is mediated by the RNF complex that exploits the proton motive force over the cytoplasmic membrane to lower the midpoint potential of the transferred electron. Here we report the cryo-EM structure of the nitrogenase-associated RNF complex ofA. vinelandii, a seven-subunit membrane protein assembly that contains four flavin cofactors and six iron-sulfur centers. Its function requires the strict coupling of electron and proton transfer but also involves major conformational changes within the assembly that can be traced with a combination of electron microscopy and modeling.One Sentence SummaryBiological nitrogen fixation requires electrons with a negative redox potential, and the diazotrophAzotobacter vinelandiican provide these through the evolutionarily ancient RNF complex that bridges the energy difference between NADH and a low-potential ferredoxin by exploiting the transmembrane proton gradient.
Random folding drives the emergence of topologically associating domains in chromatin three-dimensional structure
Authors: Meng Luming , Luo Qiong 
Published: July 2022

AbstractDomains are units of genome organization. Due to the seemingly irreconcilable difference between topologically associating domains (TADs) revealed by population-based biochemical studies and domains (sTADs) by single-cell imaging, finding a mechanism that simultaneously shape TADs and sTADs is challenging. Here we propose that TADs and sTADs are underlied by random folding of chromatin fiber heterogeneous in DNA density. On the hypothesis, we develop a model, termed RCHC, to yield chromatin structure ensemble from chromatin accessibility data. Calculated ensemble enables our hypothesis to be validated by population-based and single-cell experiments. Our simulation confirms the independence between domain and compartment structures in genome organization and shows that RCHC can predict the chromatin reorganization during differentiation. We mechanistically prove that genome is organized randomly with biases introduced by DNA-encoded information.One-Sentence SummaryThe TADs emergence is underlied by random folding of heterogeneous chromatin fiber carrying nucleosome occupancy information.
Noncanonical circRNA biogenesis driven by alpha and gamma herpesviruses
Authors: Dremel Sarah E. , Koparde Vishal N. , Arbuckle Jesse H. , Hogan Chad H. , Kristie Thomas M. , Krug Laurie T. , Conrad Nicholas K , Ziegelbauer Joseph M. 
Published: July 2022

ABSTRACTHerpesviruses rely on the host transcriptional machinery for expression of their >100 different transcripts. To prioritize viral transcripts, herpesviruses affect significant changes in all stages of gene expression. Herein, we examined how herpesviruses alter circular RNA (circRNA) synthesis resulting in distinct characteristics for those expressed from the host or viral genome. CircRNA were identified with our Circrnas in Host And viRuses anaLysis pIpEline (CHARLIE) capable ofde novoannotation using aggregated calls from five distinct tools. Comparative profiling for Herpes Simplex Virus-1, Kaposi sarcoma-associated herpesvirus, and murine gammaherpesvirus 68 identified thousands of back splicing variants, including circRNA species commonly expressed in all phases of infection. CircRNA expression was highest during lytic infection, with a transcriptional density 500-fold greater than the host. We characterized cis- and trans-elements controlling back splicing and found viral circRNAs are generally resistant to spliceosome inhibition or depletion, with >90% lacking canonical splice donor-acceptor sites. Using eCLIP and 4sU-Sequencing, we determined that the viral RNA binding protein, ORF57, enhanced synthesis for a subset of viral and host circRNAs. Our work elucidates a unique splicing mechanism driven by late lytic replication and identifies a class of transcripts with potential to function in replication, persistence, or tumorigenesis.
IKKα promotes lung adenocarcinoma growth through activation of ERK signaling via DARPP-32-mediated inhibition of PP1 activity
Authors: Alam Sk. Kayum , Wang Li , Zhu Zhu , Hoeppner Luke H. 
Published: July 2022

AbstractNon–small cell lung cancer (NSCLC) accounts for 80-85% cases of lung cancer cases. Diagnosis at advanced stages is common, after which therapy-refractory disease progression frequently occurs. Therefore, a better understanding of the molecular mechanisms that control NSCLC progression is necessary to develop new therapies. Overexpression of IκB kinase α (IKKα) in NSCLC correlates with poor patient survival. IKKα is an NF-κB-activating kinase that is important in cell survival and differentiation, but its regulation of oncogenic signaling is not well understood. We recently demonstrated that IKKα promotes NSCLC cell migration by physically interacting with dopamine- and cyclic AMP-regulated phosphoprotein, Mr 32000 (DARPP-32), and its truncated splice variant, t-DARPP. Here, we show that IKKα phosphorylates DARPP-32 at threonine 34, resulting in DARPP-32-mediated inhibition of protein phosphatase 1 (PP1), subsequent PP1-mediated dephosphorylation of ERK, and activation of ERK signaling to promote lung oncogenesis. Correspondingly, DARPP-32 ablation in human lung adenocarcinoma cells reduced their anchorage-independent growth in soft agar. Mice challenged with IKKα-ablated HCC827 cells exhibited less lung tumor growth than mice orthotopically administered control HCC827 cells. Our findings suggest that IKKα drives NSCLC growth through activation of ERK signaling via DARPP-32-mediated inhibition of PP1 activity.
Stochastic modelling of cell differentiation networks from partially-observed clonal tracking data
Authors: Del Core L. , Pellin D. , Grzegorczyk M. A. , Wit E. C. 
Published: July 2022

AbstractMotivationClarifying how hematopoietic stem cells differentiate into mature cell types is important for understanding how they attain specific functions and offers the potential for therapeutic manipulation. Over the past decades, clonal tracking has proven to be capable of unveiling population dynamics and hierarchical relationships in vivo. For this reason, clonal tracking studies are required for safety and long-term efficacy assessment in gene therapy. However, many standard clonal tracking studies consider only a subset of cell-types and are subject to noise.ResultsIn this work, we propose a stochastic framework that investigates the dynamics of cell differentiation from typical clonal tracking data subject to measurement noise, false-negative errors, and systematically unobserved cell types. Our framework is based on stochastic reaction networks combined with extended Kalman filtering and Rauch-Tung-Striebel smoothing. Our tool can provide statistical support to biologists in gene therapy clonal tracking studies to better understand clonal reconstitution dynamics.AvailabilityThe stochastic framework is implemented in the package Karen which is available for download at https://github.com/delcore-luca/Karen. The code that supports the findings of this study is openly available at https://github.com/delcore-luca/CellDifferentiationNetworks.Contactl.del.core@rug.nl
Bayesian Inference of RNA Velocity from Multi-Lineage Single-Cell Data
Authors: Gu Yichen , Blaauw David , Welch Joshua D. 
Published: July 2022

AbstractExperimental approaches for measuring single-cell gene expression can observe each cell at only one time point, requiring computational approaches for reconstructing the dynamics of gene expression during cell fate transitions. RNA velocity is a promising computational approach for this problem, but existing inference methods fail to capture key aspects of real data, limiting their utility. To address these limitations, we developed VeloVAE, a Bayesian model for RNA velocity inference. VeloVAE uses variational Bayesian inference to estimate the posterior distribution of latent time, latent cell state, and kinetic rate parameters for each cell. Our approach addresses key limitations of previous methods by inferring a global time and cell state value for each cell; explicitly modeling the emergence of multiple cell types; incorporating prior information such as time point labels; using scalable minibatch optimization; and quantifying parameter uncertainty. We show that VeloVAE significantly outperforms previous approaches in terms of data fit and accuracy of inferred differentiation directions. VeloVAE can also capture qualitative features of expression dynamics neglected by previous methods, including late induction, early repression, transcriptional boosts, and bifurcations. These improvements allow VeloVAE to accurately model gene expression dynamics in complex biological systems, including hematopoiesis, induced pluripotent stem cell reprogramming, neurogenesis, and organogenesis. We find that the latent time automatically inferred using all cells can even outperform pseudotime inferred using manually chosen cell subsets and root cells. We further use the inferred parameters to construct cell type transition graphs and fit branching differential equation models that describe the effects of cell type bifurcations on kinetic rate parameters.
Interplay between MYZUS PERSICAE-INDUCED LIPASE 1 and OPDA signaling in controlling green peach aphid infestation on Arabidopsis thaliana
Authors: Archer Lani , Mondal Hossain A. , Behera Sumita , Twayana Moon , Louis Joe , Nalam Vamsi J. , Keereetaweep Jantana , Chowdhury Zulkarnain , Shah Jyoti 
Published: July 2022

AbstractMYZUS PERSICAE-INDUCED LIPASE1 (MPL1) encodes a lipase in Arabidopsis thaliana that is required for controlling infestation by the green peach aphid (GPA; Myzus persicae), an important phloem sap-consuming insect pest. Previously, we demonstrated that MPL1 expression was upregulated in response to GPA infestation, and GPA fecundity was higher on the mpl1 mutant, compared to the wild-type (WT), and lower on 35S:MPL1 plants that constitutively expressed MPL1 from the 35S promoter. Here, we show that the MPL1 promoter is active in the phloem and expression of the MPL1 coding sequence from the phloem-specific SUC2 promoter is sufficient to restore resistance to the GPA in the mpl1 mutant. The GPA infestation-associated upregulation of MPL1 requires CYCLOPHILIN 20-3 (CYP20-3), which encodes a 12-oxo- phytodienoic acid (OPDA)-binding protein that is involved in OPDA signaling and is required for controlling GPA infestation. OPDA promotes MPL1 expression to limit GPA fecundity, a process that requires CYP20-3 function. These results along with our observation that constitutive expression of MPL1 from the 35S promoter restores resistance to the GPA in the cyp20-3 mutant, and MPL1 feedbacks to limit OPDA levels in GPA-infested plants, suggest that an interplay between MPL1, OPDA, and CYP20-3 contributes to resistance to the GPA.HighlightInteraction between MYZUS PERSICAE-INDUCED LIPASE 1 function in the phloem, and 12-oxo-phytodienoic acid (OPDA) and CYCLOPHILIN 20-3, which encodes an OPDA-binding protein that is involved in OPDA signaling, is involved in controlling green peach aphid infestation on Arabidopsis thaliana.
The rostral zona incerta: a subcortical integrative hub and potential DBS target for OCD
Authors: Haber Suzanne N. , Lehman Julia , Maffei Chiara , Yendiki Anastasia 
Published: July 2022

AbstractBackgroundThe zona incerta (ZI) is involved in mediating survival behaviors and is connected to a wide range of cortical and subcortical structures, including key basal ganglia nuclei. Based on these connections and their links to behavioral modulation, we propose the ZI is a connectional hub for in mediating between top-down and bottom-up control and a possible target for deep brain stimulation for obsessive compulsive disorder.MethodsWe analyzed the trajectory of cortical fibers to the ZI in nonhuman and human primates, based on tracer injections in monkeys and high-resolution diffusion MRI in humans. The organization of cortical and subcortical connections with the ZI were identified in the nonhuman primate studies.ResultsMonkey anatomic data and human dMRI data showed a similar trajectory of fibers/streamlines to the ZI. PFC/ACC terminals all converge within the rostral ZI (ZIr), with dorsal and lateral areas most prominent. Motor areas terminate caudally. Dense subcortical reciprocal connections included the thalamus, medial hypothalamus, substantia nigra/ventral tegmental area, reticular formation, and pedunculopontine nucleus and a dense nonreciprocal projection to the lateral habenula (LHb). Additional connections included amygdala, dorsal raphe nucleus, and periaqueductal grey.ConclusionsDense connections with dorsal and lateral PFC/ACC cognitive control areas and LHb and SN/VTA coupled with inputs from the amygdala, hypothalamus, and brainstem, suggests that the ZIr is a subcortical hub positioned to modulate between top-down and bottom-up control. A DBS electrode placed in the ZIr would involve both connections common to other DBS sites, but also would capture several critically distinctive connections.
Gene Trajectory Inference for Single-cell Data by Optimal Transport Metrics
Authors: Qu Rihao , Cheng Xiuyuan , Sefik Esen , Stanley Jay S. , Landa Boris , Strino Francesco , Platt Sarah , Garritano James , Odell Ian D. , Coifman Ronald , Flavell Richard A. , Myung Peggy , Kluger Yuval 
Published: July 2022

AbstractSingle-cell RNA-sequencing has been widely used to investigate cell state transitions and gene dynamics of biological processes. Current strategies to infer the sequential dynamics of genes in a process typically rely on constructing cell pseudotime through cell trajectory inference. However, the presence of concurrent gene processes in the same group of cells and technical noise can obscure the true progression of the processes studied. To address this challenge, we present GeneTrajectory, an approach that identifies trajectories of genes rather than trajectories of cells. Specifically, optimal-transport distances are calculated between gene distributions across the cell-cell graph to extract gene programs and define their gene pseudotemporal order. Here, we demonstrate that GeneTrajectory accurately extracts progressive gene dynamics in myeloid lineage maturation. Moreover, we show that GeneTrajectory deconvolves key gene programs underlying mouse skin hair follicle dermal condensate differentiation that could not be resolved by cell trajectory approaches. GeneTrajectory facilitates discovery of gene programs that control the changes and activities of biological processes.
Human mtRF1 terminates COX1 translation and its ablation induces mitochondrial ribosome-associated quality control
Authors: Nadler Franziska , Lavdovskaia Elena , Krempler Angelique , Cruz-Zaragoza Luis Daniel , Dennerlein Sven , Richter-Dennerlein Ricarda 
Published: July 2022

AbstractTranslation termination requires release factors that read a STOP codon in the decoding center and subsequently facilitate the hydrolysis of the nascent peptide chain from the peptidyl tRNA within the ribosome. In human mitochondria eleven open reading frames terminate in the standard UAA or UAG STOP codon, which can be recognized by mtRF1a, the proposed major mitochondrial release factor. However, two transcripts encoding for COX1 and ND6 terminate in the non-conventional AGA or AGG codon, respectively. How translation termination is achieved in these two cases is not known. We solve this long-standing open question by showing that the non-canonical release factor mtRF1 is a specialized release factor that triggers COX1 translation termination, while mtRF1a terminates the majority of other mitochondrial translation events including the non-canonical ND6. Loss of mtRF1 leads to isolated COX deficiency and activates the mitochondrial ribosome-associated quality control accompanied by the degradation of COX1 mRNA to prevent an overload of the ribosome rescue system. Taken together, these results establish the role of mtRF1 in mitochondrial translation, which had been a mystery for almost 25 years, and lead to a comprehensive picture of translation termination in human mitochondria.
CeDAR: incorporating cell type hierarchy improves cell type specific differential analyses in bulk omics data
Authors: Chen Luxiao , Li Ziyi , Wu Hao 
Published: July 2022

AbstractThe bulk high-throughput omics data contain signals from a mixture of cell types. Recent developments of deconvolution methods facilitate cell-type-specific inferences from bulk data. Our real data exploration suggests that the differential expression or methylation status are often correlated among cell types. Based on this observation, we develop a novel statistical method named CeDAR to incorporate the cell type hierarchy in cell-type-specific differential analyses in bulk data. Extensive simulation and real data analyses demonstrate that this approach significantly improves the accuracy and power in detecting cell-type-specific differential signals compared with existing methods, especially in low abundance cell types.
Development of genome-driven, lifestyle-informed primers for identification of the cereal-infecting pathogens Xanthomonas translucens pathovars undulosa and translucens
Authors: Román-Reyna Verónica , Curland Rebecca D. , Velez-Negron Yesenia , Ledman Kristi E. , Gutierrez Diego , Beutler Jonathan , Butchacas Jules , Brar Gurcharn Singh , Roberts Robyn , Dill-Macky Ruth , Jacobs Jonathan M. 
Published: July 2022

ABSTRACTBacterial leaf streak, blight and black chaff caused by Xanthomonas translucens pathovars are major diseases affecting small grains. Xanthomonas translucens pv. translucens and X. translucens pv. undulosa are seedborne pathogens that cause similar symptoms on barley, but only X. translucens pv. undulosa causes bacterial leaf streak of wheat. Recent outbreaks of X. translucens have been a concern for wheat and barley growers in the Northern Great Plains and Upper Midwest; however, there are limited diagnostic tools for pathovar differentiation. We developed a multiplex PCR based on whole-genome differences to distinguish X. translucens pv. translucens and X. translucens pv. undulosa. We validated the primers across different Xanthomonas and non-Xanthomonas strains. To our knowledge, these are the first multiplex PCR to distinguish X. translucens pv. translucens and X. translucens pv. undulosa. These molecular tools will support disease management strategies enabling detection and pathovar incidence analysis of X. translucens.
Conservation of three-dimensional structure in Lepidoptera and Trichoptera L-fibroins for 290 million years
Authors: Stewart Russell J. , Frandsen Paul B. , Pauls Steffen U. , Heckenhauer Jacqueline 
Published: July 2022

ABSTRACTThe divergence of sister orders, Trichoptera (caddisflies) and Lepidoptera (moths and butterflies), from a silk-spinning ancestor occurred around 290 million years ago. Trichoptera larvae are mainly aquatic and Lepidoptera larvae are almost entirely terrestrial, distinct habitats that required molecular adaptation of their silk for deployment in water versus air. The major protein components of their silks are Heavy chain and Light chain fibroins. In an effort to identify molecular changes in L-fibroins that may have contributed to the divergent use of silk in water versus air, we used the ColabFold implementation of AlphaFold2 to predict three-dimensional structures of L-fibroins from both orders. Comparison of the structures revealed that despite the ancient divergence, profoundly different habitats, and low sequence conservation, a 10-helix core structure was strongly conserved in L-fibroins from both orders. Previously known intra- and intermolecular disulfide linkages were accurately predicted. Structure variations observed outside of the core may represent molecular changes that contributed to the evolution of silks adapted to water or air. The distributions of electrostatic potential, for example, are not conserved and present distinct order-specific surfaces for potential interactions with or modulation by external factors. Also, the interactions of L-fibroins with the H-fibroin C-termini are different between the orders; lepidopteran L-fibroins have N-terminal insertions, not present in trichopteran L-fibroins, which form an unstructured ribbon in isolation but become part of an intermolecular β-sheet when folded with their corresponding H-fibroin C-termini. The results may serve as another example of protein structure prediction from deep sequence data of understudied proteins made possible by AlphaFold2.
Machine learning reveals conserved chromatin patterns determining meiotic recombination sites in plants
Authors: Wang Minghui , Shilo Shay , Zhou Adele , Zelkowski Mateusz , Olson Mischa A. , Azuri Ido , Shoshani-Hechel Nurit , Melamed-Bessudo Cathy , Marand Alexandre P. , Jiang Jiming , Schnable James C. , Underwood Charles J. , Henderson Ian R. , Sun Qi , Pillardy Jaroslaw , Kianian Penny M.A. , Kianian Shahryar F. , Chen Changbin , Levy Avraham A. , Pawlowski Wojciech P. 
Published: July 2022

ABSTRACTDistribution of meiotic recombination events in plants has been associated with local chromatin and DNA characteristics, chromosome landmark proximity, and other features1-7. However, relative importance of these characteristics is unclear and it is unknown if they are sufficient to unambiguously determine recombination landscape8. Here, we analyzed over 40 DNA sequence, chromatin, and chromosome location features of maize andArabidopsisrecombination sites using machine learning9,10. We discovered that a combination of just three features, CG methylation, CHG methylation, and nucleosome occupancy, enabled identification of exact crossover site with 90% accuracy. These results imply redundancy of most recombination site characteristics. Recombination takes place in a small fraction of the genome with chromatin features distinct from those of genome at large. Surprisingly, crossover sites show elevated heterochromatin histone marks despite low DNA methylation. Crossover site features show broad evolutionary conservation, which will enable creating genetic maps in species where conventional mapping is unfeasible.