bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gene expression signature for predicting homologous recombination deficiency in triple-negative breast cancer
Authors: Pan Jia-Wern , Tan Zi-Ching , Ng Pei-Sze , Zabidi Muhammad Mamduh Ahmad , Nur Fatin Putri , Teo Jie-Ying , Hasan Siti Norhidayu , Islam Tania , Teoh Li-Ying , Jamaris Suniza , See Mee-Hoong , Yip Cheng-Har , Rajadurai Pathmanathan , Looi Lai-Meng , Taib Nur Aishah Mohd , Rueda Oscar M. , Caldas Carlos , Chin Suet-Feung , Lim Joanna , Teo Soo-Hwang 
Published: June 2022

AbstractTriple-negative breast cancers (TNBCs) are a subset of breast cancers that have remained difficult to treat. Roughly 1 in 10 of TNBCs arise in individuals with pathogenic variants inBRCA1orBRCA2, and treating BRCA-associated TNBCs with PARP inhibitors results in improved survival. A proportion of TNBCs arising in non-carriers ofBRCApathogenic variants have genomic features that are similar toBRCAcarriers, and we postulated that gene expression may identify individuals with such features who might also benefit from PARP inhibitor treatment. Using genomic data from 129 TNBC samples from the Malaysian Breast Cancer (MyBrCa) cohort, we classified tumours as having high or low homologous recombination deficiency (HRD) and developed a gene expression-based machine learning classifier for HRD in TNBCs. The classifier identified samples with HRD mutational signature at an AUROC of 0.94 in the MyBrCa validation dataset, and strongly segregated HRD-associated genomic features in TNBCs from TCGA and METABRIC. Further validation of the classifier using the NanoString nCounter platform showed that the RNA-seq results correlated strongly with NanoString results (r= 0.90) from fresh frozen tissue as well as NanoString results from FFPE tissue (r= 0.84). Thus, our gene expression classifier may identify triple-negative breast cancer patients with homologous recombination deficiency, suggesting an alternative method to identify individuals who may benefit from treatment with PARP inhibitors or platinum chemotherapy.Novelty/Impact statementWe developed a gene expression-based classifier for homologous recombination deficiency (HRD) in breast cancer patients using WES and RNA-seq data obtained from 129 TNBC samples from a Malaysian hospital-based cohort (MyBrCa). This classifier was able to predict for HRD status at an AUC of 0.94 in the MyBrCa cohort, and was also able to segregate HRD-associated features in TNBCs from TCGA. We also validated the classifier on a NanoString platform with both fresh frozen and FFPE tissue.
Matrin3 regulates cell proliferation and spindle dynamics by regulating CDC14B alternative splicing
Authors: Muys Bruna R. , Shrestha Roshan L. , Anastasakis Dimitrios G. , Pongor Lorinc , Li Xiao Ling , Grammatikakis Ioannis , Polash Ahsan , Harris Curtis C , Aladjem Mirit I. , Basrai Munira A. , Hafner Markus , Lal Ashish 
Published: June 2022

AbstractMatrin3 is an RNA-binding protein that affects diverse RNA-related processes, including mRNA splicing. While Matrin3 has been intensively studied in neurodegenerative diseases, its function in cancer remains unclear. Here, we discovered Matrin3-mediated regulation of mitotic spindle dynamics in colorectal cancer (CRC) cells. We identified bound and regulated Matrin3-target RNAs transcriptome-wide in CRC cells and found that Matrin3 broadly modulates mRNA splicing patterns. Among the top Matrin3 targets, we focused on CDC14B and found that Matrin3 loss increased inclusion of an exon containing a premature termination codon into the CDC14B transcript and simultaneous down-regulation of the standard CDC14B transcript. Selective knockdown of the CDC14B standard transcript phenocopied Matrin3 knockdown and exhibited reduced proliferation and defects in mitotic spindle formation, suggesting that CDC14B is a key downstream effector of Matrin3. Collectively, these data reveal an important role for the Matrin3/CDC14B axis in control of CRC cell proliferation and mitotic spindle formation.
Proposal and extensive test of a calibration protocol for crop phenology models
Authors: Wallach Daniel , Palosuo Taru , Thorburn Peter , Mielenz Henrike , Buis Samuel , Hochman Zvi , Gourdain Emmanuelle , Andrianasolo Fety , Dumont Benjamin , Ferrise Roberto , Gaiser Thomas , Garcia Cecile , Gayler Sebastian , Harrison Matthew , Hiremath Santosh , Horan Heidi , Hoogenboom Gerrit , Jansson Per-Erik , Jing Qi , Justes Eric , Kersebaum Kurt-Christian , Launay Marie , Lewan Elisabet , Liu Ke , Mequanint Fasil , Moriondo Marco , Nendel Claas , Padovan Gloria , Qian Budong , Schütze Niels , Seserman Diana-Maria , Shelia Vakhtang , Souissi Amir , Specka Xenia , Srivastava Amit Kumar , Trombi Giacomo , Weber Tobias K.D. , Weihermüller Lutz , Wöhling Thomas , Seidel Sabine J. 
Published: June 2022

AbstractA major effect of environment on crops is through crop phenology, and therefore, the capacity to predict phenology for new environments is important. Mechanistic crop models are a major tool for such predictions, but calibration of crop phenology models is difficult and there is no consensus on the best approach. Here we propose an original, detailed approach, a protocol, for calibration of such models. The protocol covers all the steps in the calibration work-flow, namely choice of default parameter values, choice of objective function, choice of parameters to estimate from the data, calculation of optimal parameter values and diagnostics. The major innovation is in the choice of which parameters to estimate from the data, which combines expert knowledge and data-based model selection. First, almost additive parameters are identified and estimated. This should make bias (average difference between observed and simulated values) nearly zero. These are “obligatory” parameters, that will definitely be estimated. Then candidate parameters are identified, which are parameters likely to explain the remaining discrepancies between simulated and observed values. A candidate is only added to the list of parameters to estimate if it leads to a reduction in BIC (Bayesian Information Criterion), which is a model selection criterion. A second original aspect of the protocol is the specification of documentation for each stage of the protocol. The protocol was applied by 19 modeling teams to three data sets for wheat phenology. All teams first calibrated their model using their “usual” calibration approach, so it was possible to compare usual and protocol calibration. Evaluation of prediction error was based on data from sites and years not represented in the training data. Compared to usual calibration, calibration following the new protocol reduced the variability between modeling teams by 22% and significantly reduced prediction error.
A circular zone of attachment to the extracellular matrix provides directionality to the motility ofToxoplasma gondiiin 3D
Authors: Stadler Rachel V. , Nelson Shane R. , Warshaw David M. , Ward Gary E. 
Published: June 2022

AbstractToxoplasma gondiiis a protozoan parasite that infects 30-40% of the world’s population. Infections are typically subclinical but can be severe and, in some cases, life threatening. Central to the virulence ofT. gondiiis an unusual form of substrate-dependent motility that enables the parasite to invade cells of its host and to disseminate throughout the body. A hetero-oligomeric complex of proteins that functions in motility has been characterized, but how these proteins work together to drive forward motion of the parasite remains controversial. A key piece of information needed to understand the underlying mechanism(s) is the directionality of the forces that a moving parasite exerts on the external environment. The linear motor model of motility, which has dominated the field for the past two decades, predicts continuous anterior-to-posterior force generation along the length of the parasite. We show here using three-dimensional traction force mapping that the predominant forces exerted by a moving parasite are instead periodic and directed in towards the parasite at a fixed circular location within the extracellular matrix. These highly localized forces, which are generated by the parasite pulling on the matrix, create a visible constriction in the parasite’s plasma membrane. We propose that the ring of inward-directed force corresponds to a circumferential attachment zone between the parasite and the matrix, through which the parasite propels itself to move forward. The combined data suggest a closer connection between the mechanisms underlying parasite motility and host cell invasion than previously recognized. In parasites lacking the major surface adhesin, TgMIC2, neither the inward-directed forces nor the constriction of the parasite membrane are observed. The trajectories of the TgMIC2-deficient parasites are less straight than those of wild-type parasites, suggesting that the annular zone of TgMIC2-mediated attachment to the extracellular matrix normally constrains the directional options available to the parasite as it migrates through its surrounding environment.
Hallucinating protein assemblies
Authors: Wicky B. I. M. , Milles L. F. , Courbet A. , Ragotte R. J. , Dauparas J. , Kinfu E. , Tipps S. , Kibler R. D. , Baek M. , DiMaio F. , Li X. , Carter L. , Kang A. , Nguyen H. , Bera A. K. , Baker D. 
Published: June 2022

AbstractDeep learning generative approaches provide an opportunity to broadly explore protein structure space beyond the sequences and structures of natural proteins. Here we use deep network hallucination to generate a wide range of symmetric protein homo-oligomers given only a specification of the number of protomers and the protomer length. Crystal structures of 7 designs are very close to the computational models (median RMSD: 0.6 Å), as are 3 cryoEM structures of giant rings with up to 1550 residues, C33 symmetry, and 10 nanometer in diameter; all differ considerably from previously solved structures. Our results highlight the rich diversity of new protein structures that can be created using deep learning, and pave the way for the design of increasingly complex nanomachines and biomaterials.One-sentence summaryDeep network-based protein design enables the generation of cyclic homo-oligomers across the nanoscopic scale.
Bacteriophage anti-defense genes that neutralize TIR and STING immune responses
Authors: Ho Peiyin , Chen Yibu , Biswas Subarna , Canfield Ethan , Feldman Douglas E. 
Published: June 2022

SummaryProgrammed cell suicide of infected bacteria, known as abortive infection (Abi), serves as a central immune defense strategy to prevent the spread of bacteriophage viruses and other invasive genetic elements across a population. Many Abi systems utilize bespoke cyclic nucleotide immune messengers generated upon infection to rapidly mobilize cognate death effectors. Here, we identify a large family of bacteriophage nucleotidyltransferases (NTases) that synthesize competitor cyclic dinucleotide (CDN) ligands, inhibiting NAD-depleting TIR effectors activated by a linked STING CDN sensor domain. Virus NTase genes are positioned within genomic regions containing other anti-defense genes, and through a functional screen, we uncover candidate anti-TIR defense (Atd) genes that confer protection against TIR-STING cytotoxicity. We show that a virus MazG-like nucleotide pyrophosphatase identified in the screen, Atd1, depletes the starvation alarmone (p)ppGpp, revealing a role for the alarmone-activated host toxin MazF as a key executioner of TIR-directed abortive infection. Phage NTases and counter-defenses like Atd1 preserve host viability to ensure virus propagation, and may be exploited as tools to modulate TIR and STING immune responses.
Ribosome display ofN-linked glycoproteins in cell-free extracts
Authors: Chung Sean S. , Bidstrup Erik J. , Hershewe Jasmine M. , Warfel Katherine F. , Jewett Michael C. , DeLisa Matthew P. 
Published: June 2022

ABSTRACTRibosome display is a powerfulin vitromethod for the selection and directed evolution of proteins expressed from combinatorial libraries. However, because ribosome display is typically performed with standardin vitrotranslation reagents, the ability to display proteins with complex post-translational modifications such as glycosylation is limited. To address this technological gap, here we developed a set of complementary methods for producing stalled ribosome complexes that displayed asparagine-linked (N-linked) glycoproteins in conformations amenable to downstream functional and glyco-structural interrogation. The ability to generate glycosylated ribosome-nascent chain (glycoRNC) complexes was enabled by integrating SecM-mediated translation arrest with methods for cell-free synthesis ofN-glycoproteins. This integration yielded a novel capability for translating and displaying target proteins modified efficiently and site-specifically with differentN-glycan structures. Moreover, the encoding mRNAs remained stably attached to stalled ribosomes both before and after biopanning, thereby providing the genotype– glycophenotype link between an arrested glycoprotein and its RNA message. We anticipate that our method will enable selection and evolution ofN-linked glycoproteins with advantageous biological and biophysical properties.
PKC isoforms activate LRRK1 kinase by phosphorylating conserved residues (Ser1064, Ser1074 and Thr1075) within the CORBGTPase domain
Authors: Malik Asad U , Karapetsas Athanasios , Nirujogi Raja S. , Chatterjee Deep , Phung Toan K. , Wightman Melanie , Gourlay Robert , Morrice Nick , Mathea Sebastian , Knapp Stefan , Alessi Dario R 
Published: June 2022

AbstractLeucine-rich-repeat-kinase 1 (LRRK1) and its homologue LRRK2 are multidomain kinases possessing a ROC-CORA-CORBcontaining GTPase domain and phosphorylate distinct Rab proteins. LRRK1 loss of function mutations cause the bone disorder osteosclerotic metaphyseal dysplasia, whereas LRRK2 missense mutations that enhance kinase activity cause Parkinson’s disease. Previous work suggested that LRRK1 but not LRRK2, is activated via a Protein Kinase C (PKC)-dependent mechanism. Here we demonstrate that phosphorylation and activation of LRRK1 in HEK293 cells is blocked by PKC inhibitors including LXS-196 (Darovasertib), a compound that has entered clinical trials. We show multiple PKC isoforms phosphorylate and activate recombinant LRRK1 in a manner reversed by phosphatase treatment. PKCα unexpectedly does not activate LRRK1 by phosphorylating the kinase domain, but instead phosphorylates a cluster of conserved residues (Ser1064, Ser1074 and Thr1075) located within a region of the CORBdomain of the GTPase domain. These residues are positioned at the equivalent region of the LRRK2 DK helix reported to stabilize the kinase domain αC-helix in the active conformation. Thr1075 represents an optimal PKC site phosphorylation motif and its mutation to Ala, blocked PKC-mediated activation of LRRK1. A triple Glu mutation of Ser1064/Ser1074/Thr1075 to mimic phosphorylation, enhanced LRRK1 kinase activity ~3-fold. From analysis of available structures, we postulate that phosphorylation of Ser1064, Ser1074 and Thr1075 activates LRRK1 by promoting interaction and stabilization of the aC-helix on the kinase domain. This study provides new fundamental insights into the mechanism controlling LRRK1 activity and reveals a novel unexpected activation mechanism.
Anopheles albimanus is a potential alphavirus vector in the Americas
Authors: Terradas Gerard , Novelo Mario , Metz Hillery C. , Brustolin Marco , Rasgon Jason L. 
Published: June 2022

AbstractDespite its ecological flexibility and geographical co-occurrence with human pathogens, little is known about the ability for Anopheles albimanus to transmit arboviruses. To address this gap, we challenged An. albimanus females with four alphaviruses and one flavivirus and monitored progression of infections. We found this species is an efficient vector of the alphaviruses Mayaro virus, O’nyong-nyong virus, and Sindbis virus, though the latter two do not currently exist in its habitat range. An. albimanus was able to become infected with Chikungunya virus, but virus dissemination was rare (indicating the presence of a midgut escape barrier), and no mosquito transmitted. Mayaro virus rapidly established disseminated infections in An. albimanus females and was detected in the saliva of a substantial proportion of infected mosquitoes. Consistent with previous work in other anophelines, we find that An. albimanus is refractory to infection with flaviviruses, a phenotype that did not depend on midgut-specific barriers. Our work demonstrates that An. albimanus may be a vector of neglected emerging human pathogens and adds to recent evidence that anophelines are competent vectors for diverse arboviruses.
Nanotopography modulates intracellular excitable systems through cytoskeleton actuation
Authors: Yang Qixin , Miao Yuchuan , Banerjee Parijat , Hourwitz Matt J. , Hu Minxi , Qing Quan , Iglesias Pablo A. , Devreotes Peter N. , Fourkas John T. , Losert Wolfgang 
Published: June 2022

AbstractCellular sensing of most environmental cues involves receptors that affect a signal-transduction excitable network (STEN), which is coupled to a cytoskeletal excitable network (CEN). We show that the mechanism of sensing of nanoridges is fundamentally different. CEN activity occurs preferentially on nanoridges, whereas STEN activity is constrained between nanoridges. In the absence of STEN, waves disappear, but long-lasting F-actin puncta persist along the ridges. When CEN is suppressed, wave propagation is no longer constrained by nanoridges. A computational model reproduces these experimental observations. Our findings indicate that nanotopography is sensed directly by CEN, whereas STEN is only indirectly affected due to a CEN-STEN feedback loop. These results explain why texture sensing is robust, and acts cooperatively with multiple other guidance cues in complex microenvironments.One-Sentence SummaryCells sense nanotopography directly through their cytoskeletal dynamics, in a reversal of traditional signaling pathway hierarchies.
Hybridization kinetics of out-of-equilibrium mixtures of short RNA oligonucleotides
Authors: Todisco Marco , Szostak Jack W. 
Published: June 2022

ABSTRACTHybridization and strand displacement kinetics determine the evolution of the base-paired configurations of mixtures of oligonucleotides over time. Although much attention has been focused on the thermodynamics of DNA and RNA base pairing in the scientific literature, much less work has been done on the time dependence of interactions involving multiple strands, especially in RNA. Here we provide a study of oligoribonucleotide interaction kinetics and show that it is possible to calculate the association, dissociation and strand displacement rates displayed by short oligonucleotides (5nt – 12nt) as simple functions of oligonucleotide length, CG content, ΔG of hybridization and ΔG of toehold binding. We then show that the resultant calculated kinetic parameters are consistent with the experimentally observed time dependent changes in concentrations of the different species present in mixtures of multiple competing RNA strands. We show that by changing the mixture composition, it is possible to create and tune kinetic traps that extend by orders of magnitude the typical sub-second hybridization timescale of two complementary oligonucleotides. We suggest that the slow equilibration of complex oligonucleotide mixtures may have facilitated the nonenzymatic replication of RNA during the origin of life.
Systematic investigation of synthetic operon designs enables prediction and control of expression levels of multiple proteins
Authors: Gerngross Daniel , Beerenwinkel Niko , Panke Sven 
Published: June 2022

AbstractControlling the expression levels of multiple recombinant proteins for optimal performance is crucial for synthetic biosystems but remains difficult given the large number of DNA-encoded factors that influence the process of gene expression from transcription to translation. In bacterial hosts, biosystems can be economically encoded as operons, but the sequence requirements for exact tuning of expression levels in an operon remain unclear. Here, we demonstrate the extent and predictability of protein-level variation using diverse arrangements of twelve genes to generate 88 synthetic operons with up to seven genes at varying inducer concentrations. The resulting 2772 protein expression measurements allowed the training of a sequence-based machine learning model that explains 83% of the variation in the data with a mean absolute error of 9% relative to reference constructs, making it a useful tool for protein expression prediction. Feature importance analysis indicates that operon length, gene position and gene junction structure are of major importance for protein expression.
Analysis of damage characteristics of an aeroelastic model for air-breathing hypersonic vehicles
Authors: Guo Zhongge , Li Yunxin , Wang Yuhui 
Published: June 2022

Purpose
To suppress fatigue damage and ensure structural safety, this paper aims to analyze the effect of the damage accumulation on the aeroelastic model of an air-breathing hypersonic flight vehicle (AHFV).

Design/methodology/approach
Initially, by constructing the modified longitudinal elastic model of an AHFV, the stress condition of the fuselage is analyzed, and the model differences with the rigid body are studied. Then, a new damage dynamic model is presented to describe the damage dynamic evolution. Finally, combining the damage model and the longitudinal model of the AHFV, the key variables affecting the damage accumulation are determined.

Findings
It is demonstrated that the elastic deformation must be considered when analyzing the damage characteristics of the fuselage and to determine the key variables that affect the damage accumulation, which provides a more accurate reference for improving the structural reliability and lifespan of AHFVs.

Originality/value
The novelty of this paper comes from the application of the force and stress models for the damage evolution of the AHFV and the development of a new damage model for the entire body with the elastic dynamics of AHFVs.