bluuebunny/crossref_metadata_2025_split huggingface dataset:
Allosteric inactivation of an engineered optogenetic GTPase
Authors: Jain Abha , Dokholyan Nikolay V. , Lee Andrew L. 
Published: May 2022

AbstractOptogenetics is a technique for establishing direct spatiotemporal control over molecular function within living cells using light. Light application induces conformational changes within targeted proteins that produce changes in function. One of the applications of optogenetic tools is an allosteric control of proteins via light-sensitive LOV2 domain, which allows direct and robust control of protein function. Computational studies supported by cellular imaging demonstrated that application of light allosterically controlled signaling proteins Vav2, ITSN, and Rac1, but the structural and dynamic basis of such control has yet to be elucidated by experiment. Here, using NMR spectroscopy, we discover principles of action of allosteric control of cell division control protein 42 (CDC42), a small GTPase involved in cell signaling. Both LOV2 and Cdc42 employ flexibility in their function to switch between “dark”/ “lit” or active/inactive states, respectively. By conjoining Cdc42 and LOV2 domains into the bi-switchable fusion Cdc42Lov, application of light – or alternatively, mutation in LOV2 to mimic light absorption – allosterically inhibits Cdc42 downstream signaling. The flow and patterning of allosteric transduction in this flexible system is well-suited to observation by NMR. Close monitoring of the structural and dynamic properties of dark versus lit states of Cdc42Lov revealed lit-induced allosteric perturbations. Chemical shift perturbations for lit mimic, I539E, have distinct regions of sensitivity and both the domains are coupled together leading to bi-directional interdomain signaling. Insights gained from this optoallosteric design will increase our ability to control response sensitivity in future designs.Significance StatementControl of cell signaling activity in proteins by light is one of the primary goals of optogenetics. The hybrid light-receptor/cell-signaling protein Cdc42Lov was engineered recently as an optogenetic tool, employing a novel allosteric strategy that results in photoinhibition. In contrast to previous activation designs, the mechanism of inhibition of GTPase signaling activity in Cdc42 is only apparent at a detailed structural and dynamic level. NMR characterization of dark and mutationally “lit” forms reveals the allosteric interdomain perturbations, knowledge of which will enhance future applications of this design strategy.
Optimal balancing of xylem efficiency and safety explains plant vulnerability to drought
Authors: Franklin Oskar , Fransson Peter , Hofhansl Florian , Joshi Jaideep 
Published: May 2022

SummaryIn vast areas of the world, the growth of forests and vegetation is water-limited and plant survival depends on the ability to avoid catastrophic hydraulic failure. Therefore, it is remarkable that plants take high hydraulic risks by operating at water potentials (ψ) that induce partial failure of the water conduits (xylem). Here we present an eco-evolutionary optimality principle for xylem conduit design that explains this phenomenon.Based on the hypothesis that conductive efficiency and safety are optimally co-adapted to the environment, we derive a simple relationship between the intrinsic tolerance to negative water potential (ψ50) and the environmentally dependent minimum xylem ψ.This relationship is constrained by a physiological tradeoff between xylem conductivity and safety, which is relatively strong at the level of individual conduits although it may be weak at the whole sapwood level. The model explains observed variation in ψ50 both across a large number of species, and along the xylem path in two species. The larger hydraulic safety margin in gymnosperms compared to angiosperms is explained as an adaptation to the gymnosperms’ lower capacity to recover from conductivity loss.The constant xylem safety factor provides a powerful principle for simplifying and improving plant and vegetation models.
A systematic evaluation of deep learning methods for the prediction of drug synergy in cancer
Authors: Baptista Delora , Ferreira Pedro G. , Rocha Miguel 
Published: May 2022

AbstractOne of the main obstacles to the successful treatment of cancer is the phenomenon of drug resistance. A common strategy to overcome resistance is the use of combination therapies. However, the space of possibilities is huge and efficient search strategies are required. Machine Learning (ML) can be a useful tool for the discovery of novel, clinically relevant anti-cancer drug combinations. In particular, deep learning (DL) has become a popular choice for modeling drug combination effects. Here, we set out to examine the impact of different methodological choices on the performance of multimodal DL-based drug synergy prediction methods, including the use of different input data types, preprocessing steps and model architectures. Focusing on the NCI ALMANAC dataset, we found that feature selection based on prior biological knowledge has a positive impact on performance. Drug features appeared to be more predictive of drug response. Molecular fingerprint-based drug representations performed slightly better than learned representations, and gene expression data of cancer or drug response-specific genes also improved performance. In general, fully connected feature-encoding subnetworks outperformed other architectures, with DL outperforming other ML methods. Using a state-of-the-art interpretability method, we showed that DL models can learn to associate drug and cell line features with drug response in a biologically meaningful way. The strategies explored in this study will help to improve the development of computational methods for the rational design of effective drug combinations for cancer therapy.Author summaryCancer therapies often fail because tumor cells become resistant to treatment. One way to overcome resistance is by treating patients with a combination of two or more drugs. Some combinations may be more effective than when considering individual drug effects, a phenomenon called drug synergy. Computational drug synergy prediction methods can help to identify new, clinically relevant drug combinations. In this study, we developed several deep learning models for drug synergy prediction. We examined the effect of using different types of deep learning architectures, and different ways of representing drugs and cancer cell lines. We explored the use of biological prior knowledge to select relevant cell line features, and also tested data-driven feature reduction methods. We tested both precomputed drug features and deep learning methods that can directly learn features from raw representations of molecules. We also evaluated whether including genomic features, in addition to gene expression data, improves the predictive performance of the models. Through these experiments, we were able to identify strategies that will help guide the development of new deep learning models for drug synergy prediction in the future.
Design and construction of 3D-printed devices to investigate active and passive bacterial dispersal on hydrated surfaces
Authors: Kuhn Thierry , Buffi Matteo , Bindschedler Saskia , Chain Patrick S. , Gonzalez Diego , Stanley Claire , Wick Lukas Y. , Junier Pilar , Richter Xiang-Yi Li 
Published: May 2022

AbstractTo disperse in water-unsaturated environments, such as the soil, bacteria rely on the availability and structure of water films forming on biotic and abiotic surfaces, and, especially, along fungal mycelia. Dispersal along such “fungal highways” is driven both by mycelial physical properties and by interactions between bacteria and fungi. To understand the role of abiotic elements, we designed and 3D-printed two devices establishing stable liquid films that support bacteria dispersal in the absence of biotic interactions. The thickness of the liquid film determined the presence of hydraulic flow capable of carrying non-motile cells. In the absence of flow, only motile cells can disperse in the presence of an energy source. Non-motile cells could not disperse autonomously without flow, but dispersed when co-inoculated with motile cells. By teasing apart the abiotic and biotic dimensions, these 3D-printed devices will stimulate further research on microbial dispersal in soil and other water-unsaturated environments.
Two independent loss-of-function mutations in anthocyanidin synthase homeologous genes make sweet basil all green
Authors: Gonda Itay , Abu-Abied Mohamad , Adler Chen , Milavsky Renana , Tal Ofir , Davidovich-Rikanati Rachel , Faigenboim Adi , Kahane-Achinoam Tali , Shachter Alona , Chaimovitsh David , Dudai Nativ 
Published: May 2022

AbstractSweet basil, Ocimum basilicum L., is an important culinary herb grown worldwide. Although basil is green, many landraces, breeding lines and exotic cultivars have purple stems and flowers. This anthocyanins pigmentation is unacceptable in the traditional Italian basil. We used the recently published sweet basil genome to map quantitative trait loci (QTL) for flower and stem color in a bi-parental F2 population. It was found that the pigmentation is governed by a single QTL, harboring an anthocyanidin synthase (ANS) gene. Further analysis revealed that the basil genome harbors two homeologous ANS genes, each carrying a loss-of-function mutation. ObANS1 carries a 1-bp insertion, and ObANS2 carries a missense mutation within the active site. In the purple-flower parent, ANS1 is functional and ANS2 carries a nonsense mutation. The functionality of the active allele was validated by complementation in an Arabidopsis ANS mutant. Moreover, we have restored the functionality of the missense-mutated ANS2 using site-directed activation. We found that the non-functional alleles were expressed to similar levels as the functional allele, suggesting polyploids invest futile effort in expressing non-functional genes, harming their superior redundancy. We show here we can harness basil’s genomics and genetics to understand the basic mechanism of metabolic traits.
Mammary Tissue-Derived Extracellular Matrix Hydrogels Reveal the Role of Irradiation in Driving a Pro-Tumor and Immunosuppressive Microenvironment
Authors: Zhu Tian , Alves Steven M. , Adamo Arianna , Wen Xiaona , Corn Kevin C. , Shostak Anastasia , Johnson Shereena , Shaub Nicholas D. , Martello Shannon E. , Hacker Benjamin C. , D’Amore Antonio , Bardhan Rizia , Rafat Marjan 
Published: May 2022

AbstractRadiation therapy (RT) is essential for triple negative breast cancer (TNBC) treatment. However, patients with TNBC continue to experience recurrence after RT. The role of the extracellular matrix (ECM) of irradiated breast tissue in tumor recurrence is still unknown. In this study, we evaluated the structure, molecular composition, and mechanical properties of irradiated murine mammary fat pads (MFPs) and developed ECM hydrogels from decellularized tissues (dECM) to assess the effects of RT-induced ECM changes on breast cancer cell behavior. Irradiated MFPs were characterized by increased ECM deposition and fiber density compared to unirradiated controls, which may provide a platform for cell invasion and proliferation. ECM component changes in collagens I, IV, and VI, and fibronectin were observed following irradiation in both MFPs and dECM hydrogels. Encapsulated TNBC cell proliferation and invasive capacity was enhanced in irradiated dECM hydrogels. In addition, TNBC cells co-cultured with macrophages in irradiated dECM hydrogels induced M2 macrophage polarization and exhibited further increases in proliferation. Our study establishes that the ECM in radiation-damaged sites promotes TNBC invasion and proliferation as well as an immunosuppressive microenvironment. This work represents an important step toward elucidating how changes in the ECM after RT contribute to breast cancer recurrence.
Evolution of a Plastic Surgery Summer Research Program
Authors: Alfonso Allyson R. , Berman Zoe P. , Diep Gustave K. , Lee Jasmine , Ramly Elie P. , Diaz-Siso J. Rodrigo , Rodriguez Eduardo D. , Rabbani Piul S. 
Published: May 2022

ABSTRACTBackgroundEarly surgical exposure and research fellowships have been independently shown to influence medical students’ specialty choice, increase academic productivity, and impact residency match. However, to our knowledge there is no published guidance on the implementation of formal plastic surgery summer research programs for first year medical students. We present our institutional experience developing a plastic surgery summer research program over seven years (2013-2020) in an effort to inform program development at other institutions. We hypothesized that this early, formal exposure could spark interest in pursuing research activities throughout medical school and residency.MethodsFrom 2013 to 2016, a sole basic science research arm existed. In 2017, a clinical research arm was introduced, with several supplemental activities including structured surgical skills sessions. A formalized selection process was instituted in 2014. Participant feedback was analyzed on a yearly basis. Long-term outcomes included continued research commitment, productivity, and residency match.ResultsThe applicant pool has reached 96 applicants in 2019, with 85% from outside institutions. Acceptance rate reached 7% in 2020. With adherence to a scoring rubric for applicant evaluation, good to excellent interrater reliability was achieved (ICC = 0.75). Long-term outcomes showed that on average per year, 28% of participants continued departmental research activities and 29% returned for dedicated research. Upon finishing medical school, participants had a mean of 6.9±4.0 peer-reviewed publications. 62% of participants matched into a surgical residency program, with 54% in integrated plastic surgery.ConclusionsA research program designed for first year medical students interested in plastic surgery can achieve academic goals. Students are provided with mentorship, networking opportunities, and tools for self-guided learning and career development.
Ptr1 and ZAR1 immune receptors confer overlapping and distinct bacterial pathogen effector specificities
Authors: Ahn Ye Jin , Kim Haseong , Choi Sera , Mazo-Molina Carolina , Prokchorchik Maxim , Zhang Ning , Kim Boyoung , Mang Hyunggon , Yoon Hayeon , Segonzac Cécile , Martin Gregory B. , Schultink Alex , Sohn Kee Hoon 
Published: May 2022

SUMMARYNucleotide-binding and leucine-rich repeat receptors (NLRs) detect pathogen effectors inside the plant cell. To identify Nicotiana benthamiana NLRs (NbNLRs) with novel effector recognition specificity, we designed an NbNLR VIGS library and conducted a rapid reverse genetic screen. During the NbNLR VIGS library screening, we identified that N. benthamiana homolog of Ptr1 (PSEUDOMONAS SYRINGAE PV. TOMATO RACE 1 RESISTANCE) recognizes the Pseudomonas effectors AvrRpt2, AvrRpm1, and AvrB.We demonstrated that recognition of the Xanthomonas effector AvrBsT and the Pseudomonas effector HopZ5 in N. benthamiana is conferred independently by N. benthamiana homolog of Ptr1 and ZAR1 (HOPZ-ACTIVATED RESISTANCE 1). In addition, we showed that the RLCK XII family protein JIM2 (XOPJ4 IMMUNITY 2) physically interacts with AvrBsT and HopZ5 and is required for the NbZAR1-dependent recognition of AvrBsT and HopZ5. The recognition of multiple bacterial effectors by Ptr1 and ZAR1 in N. benthamiana demonstrates a convergent evolution of effector recognition across plant species. Identification of key components involved in Ptr1 and ZAR1 mediated immunity would reveal unique mechanisms of expanded effector recognition and be useful for engineering resistance in solanaceous crops.
Simulation of the effect of the randomness of climbing fiber input on the relationship between motor learning and Focal Task-Specific Dystonia
Authors: Muramatsu Kaito , Yuki Shoko , Kori Hiroshi , Yanagihara Dai 
Published: May 2022

AbstractFocal Task-Specific Dystonia (FTSD) is an intractable neurological disorder with no clear prevention or treatment that affects more than 1% of classical musicians and threatens the active lives of experts due to its task-specific tremor symptoms. In the present study, we focused on the motor learning function of the cerebellum, which has not been the focus of much attention in the past. We numerically simulated the firing of cerebellar Purkinje cells and cerebellar nuclei during eyeblink conditioning as a typical example of cerebellar-related timing motor learning, with the aim to find the principle of the pathogenesis of FTSD at the level of individual neurons. The results showed the sustained firing of cerebellar nuclei after the learning condition in which the climbing fiber input to Purkinje cells was continued randomly. Therefore, the present study claims a suggestive factor regarding the neural mechanism of the cerebellum in the motor learning-induced task-specific tremor, which is a symptom of FTSD. We also proposed a motor learning paradigm, “undesirable motor learning,” in which the motor goal is too advanced to be achieved by repetitions alone and converges to a different result than the desired.
Alteration of Soil Bacteriome by Prolonged Exposure to Metal Oxide Nanoparticles
Authors: Egboluche Nzube Prisca , Yu Hongtao , Wachira James 
Published: May 2022

AbstractMetal oxide nanoparticles (MONPs) have found applications in many industrial and consumer products and are inevitably released into the environment, including soil. Soils host diverse microorganisms that are integral to ecosystem function including regulating plant growth. In this study, the influence of Cu2O, Fe3O4and Ag2O NPs on soil microbial communities was assessed. Microbial community diversity and compositional structure was characterized using quantitative PCR and 16S rRNA gene sequencing. MONPs altered soil bacteria community composition by causing significant reduction in bacterial diversity and change in bacterial abundance. Soils with Cu2O and Ag2O NPs treatments significantly reduce bacterial diversity accompanied by shifts at the Class and Phylum taxonomic levels toward bacteria groups responsible for chitin degradation (Bacteriodetes) and nitrogen fixation (alpha-Proteobacteria). Response of bacterial communities to MONPs exposure is dependent on the exposure time and type of MONPs used. While the mechanisms underlying these observations remain to be elucidated, it is proposed that the known antimicrobial properties of Cu2O and Ag2O NPscause reduced growth and viability of some bacteria taxa.ImportanceNanoparticles are finding many applications in society and as such there is the need to gain a better understanding of their potential effects on microorganisms in soil and other environmental niches. Soil contains a large diversity of microorganisms that play many essential roles in organic matter recycling and plant growth. Metagenomics has become an essential tool for understanding the functional diversity of microbiomes and in this study, it was used to assess the diversity of soil bacteria communities in the presence of selected metal oxide nanoparticles. The reported changes in bacterial community structure suggest that nanoparticles have the potential to alter soil microbiomes. However, the effects depend on the composition of the nanoparticles suggesting that environmental impacts of different nanoparticle formulations are necessary.
CHIP ubiquitin ligase is involved in the nucleolar stress management
Authors: Piechota Malgorzata , Biriczova Lilla , Kowalski Konrad , Szulc Natalia A. , Pokrzywa Wojciech 
Published: May 2022

ABSTRACTThe nucleolus is a dynamic nuclear biomolecular condensate involved in cellular stress response. Under proteotoxic stress, the nucleolus can store damaged proteins for refolding or degradation. HSP70 chaperone is a well-documented player in the recovery process of proteins accumulated in the nucleolus after heat shock. However, little is known about the involvement of the ubiquitin-proteasome system in the turnover of its nucleolar clients. Here we show that HSP70, independently of its ATPase activity, promotes migration of the CHIP (carboxyl terminus of HSC70-interacting protein) ubiquitin ligase into the granular component of the nucleolus, specifically after heat stress. We show that while in the nucleolus, CHIP retains mobility that depends on its ubiquitination activity. Furthermore, after prolonged exposure to heat stress, CHIP self-organizes into large, intra-nucleolar droplet-like structures whose size is determined by CHIP ubiquitination capacity. Using a heat-sensitive nucleolar protein luciferase, we show that excess CHIP impairs its regeneration, probably through deregulation of HSP70. Our results demonstrate a novel role for CHIP in managing nucleolar proteostasis in response to stress.
Re-direction of phagosomes to the recycling expulsion pathway by a fungal pathogen
Authors: Jia Lei-Jie , Rafiq Muhammad , Radosa Lukáš , Hortschansky Peter , Cunha Cristina , Cseresnyés Zoltán , Krüger Thomas , Schmidt Franziska , Heinekamp Thorsten , Straßburger Maria , Löffler Bettina , Doenst Torsten , Lacerda João F. , Campos António , Figge Marc Thilo , Carvalho Agostinho , Kniemeyer Olaf , Brakhage Axel A. 
Published: May 2022

SummaryThe analysis of host-pathogen interactions bears the potential to discover novel pathogenicity mechanisms and to obtain novel insights into basic mechanisms of cell biology. Here, we obtained unprecedented insight into both. We discovered that the HscA protein on the conidial surface of the clinically important human-pathogenic fungusAspergillus fumigatusacts as an effector protein. It inhibits phagosome maturation and reprograms phagosomes for expulsion of conidia. HscA anchors the human p11 protein to phagosomes. p11 is a decisive factor for targeting phagosomes either to the degradative or secretory pathway. The relevance of our findings is indicated by the identification of an SNP in the non-coding region of the human p11 gene that affects its translation and is associated with heightened susceptibility to invasive pulmonary aspergillosis.
The fuzzy PD control for combined energy and attitude control system
Authors: Aslam Sohaib , Chak Yew-Chung , Jaffery Mujtaba Hussain , Varatharajoo Renuganth 
Published: May 2022

Purpose
The satellite pointing accuracy plays a crucial role in ensuring a successful satellite mission itself. Therefore, this paper aims to enhance the attitude pointing accuracy of the combined energy and attitude control system (CEACS) in a satellite in the presence of external disturbance torques through a robust controller, which can produce high pointing accuracies with smaller control torques.

Design/methodology/approach
To improve the CEACS attitude pointing accuracy, a maiden fuzzy proportional derivative (PD)-based CEACS architecture is proposed. The mathematical models along with its numerical treatments of the fuzzy PD-based CEACS attitude control architecture are presented. In addition, a comparison between the PD and fuzzy PD controllers in terms of the CEACS pointing accuracies and control torques is provided.

Findings
Numerical results show that the fuzzy PD controller produces a considerable CEACS pointing accuracy improvement for a lower control torque compartment.

Practical implications
CEACS has gained a renew interest because of significant increase in the projected onboard power requirements for future space missions. Therefore, it is of paramount importance to improve the CEACS pointing accuracy itself with a minimum control torque compartment. In fact, this proposed fuzzy PD controller is shown to be a potential CEACS attitude controller.

Originality/value
The fuzzy PD-based CEACS architecture not only provides a better attitude pointing accuracy but also ensures a lower control torque compartment, which corresponds to a lower onboard power consumption.