bluuebunny/crossref_metadata_2025_split huggingface dataset:
mEos4b photoconversion efficiency depends on laser illumination conditions used in PALM
Authors: Wulffele Jip , Thedié Daniel , Glushonkov Oleksandr , Bourgeois Dominique 
Published: April 2022

Green-to-red photoconvertible fluorescent proteins (PCFPs) are widely employed as markers in photoactivated localization microscopy (PALM). However, their highly complex photophysical behavior complicates their usage. The fact that only a limited fraction of a PCFP ensemble can form the photoconverted state upon near-UV light illumination, termed photoconversion efficiency (PCE), lowers the achievable spatial resolution in PALM and creates undercounting errors in quantitative counting applications. Here, we show that the PCE of mEos4b is not a fixed property of this PCFP, but strongly depends on illumination conditions. Attempts to reduce long-lived blinking in red mEos4b by application of 488 nm light leads to a reduction of the PCE. Furthermore, the PCE of mEos4b strongly depends on the applied 405-nm power density. A refined photophysical model of mEos4b accounts for the observed effects, involving nonlinear green-state photobleaching upon violet light illumination favored by photon absorption by a putative radical dark state.TOC GRAPHICS
Fundamental trade-off between speed of switching and robustness of genetic switches limits dynamic control of metabolism
Authors: Raj Kaushik , Wong William T. Z. , Zhang Beini , Mahadevan Radhakrishnan 
Published: April 2022

1AbstractBi-stable gene regulatory motifs are found in a wide variety of natural gene regulatory networks and effect transcriptional switching between stable phenotypic states in cells. In synthetic gene regulatory circuits, these architectures can be leveraged to dynamically switch between distinct metabolic states for metabolic engineering and therapeutic applications. However, the lack of modularity and predictability of these motifs in varying environments has limited widespread application, especially since the factors that affect switching characteristics are still unclear. In this work, we use a mathematical model along with a newly developed dynamical modeling and continuity analysis framework to analyze the dynamics and robustness of bi-stable switches over a range of biologically relevant model parameter values. We identify a hitherto undiscovered fundamental trade-off between the robustness of the motif - the parameter ranges over which it retains bi-stable function, and the speed at which it effects a phenotypic change. Further, usingE. colias a model host, we constructed a large library (100) of transcriptional switches that show a wide range of switching speeds, to experimentally demonstrate the presence of this trade-off. The presence of this trade-off has significant implications on the design of transcriptional switches for diverse applications and explains the circuit architecture of naturally occurring transcriptional switches as well. Additionally, we anticipate that our diverse library of experimentally validated robust bi-stable switches will be valuable to effect phenotypic changes with differing switching speed requirements for metabolic engineering applications.2Significance statementThe ability to switch genes on and off in response to spatio-temporal stimuli is critical to the survival of all organisms. At the cellular level, such switching is effected by regulatory motifs such as the bi-stable genetic toggle switch. Bi-stable motifs also serve as a primitive mode of cellular memory - “remembering” the last environment to which the cells have been exposed. In this work, we uncover a fundamental trade-off between the robust functioning of these switches and the speed at which they can effect a change in the gene expression landscape. These findings have a broad impact on the design and use of such synthetic gene regulatory devices across several fields such as industrial biotechnology, healthcare, etc.
Aberrant MYCN expression drives oncogenic hijacking of EZH2 as a transcriptional activator in peripheral T cell lymphoma
Authors: Vanden Bempt Marlies , Debackere Koen , Demeyer Sofie , Van Thillo Quentin , Meeuws Nienke , Provost Sarah , Mentens Nicole , Jacobs Kris , Gielen Olga , Nittner David , Ogawa Seishi , Kataoka Keisuke , Graux Carlos , Tousseyn Thomas , Cools Jan , Dierickx Daan 
Published: April 2022

AbstractPeripheral T cell lymphoma (PTCL) is a heterogeneous group of hematological cancers arising from the malignant transformation of mature T cells. In a cohort of 28 PTCL cases, we identified recurrent overexpression of MYCN, a member of the MYC family of oncogenic transcription factors. Approximately half of all PTCL cases was characterized by a MYC expression signature. Inducible expression of MYCN in lymphoid cells in a mouse model caused T cell lymphoma that recapitulated human PTCL with a MYC expression signature. Integration of mouse and human expression data identified EZH2 as a key downstream target of MYCN. Remarkably, EZH2 was found to be an essential co-factor for the transcriptional activation of the MYCN-driven gene expression program, which was independent of methyltransferase activity, but dependent on phosphorylation by CDK1. MYCN-driven T cell lymphoma was sensitive to EZH2 degradation or CDK1 inhibition, which displayed synergy with FDA-approved HDAC inhibitors.Key points- Transcriptomic analysis of PTCL tumors reveals recurrent MYCN overexpression and the presence of a MYC signature in 50% of PTCL cases- EZH2 is a transcriptional cofactor for the MYCN-driven gene expression program, which confers sensitivity to HDAC inhibition
Small molecules from Bacopa monneiri as potent inhibitors against Neurodegenerative disorders
Authors: Sangeet Satyam , Khan Arshad 
Published: April 2022

AbstractAlzheimer’s is characterized by the formation of senile plaques and fibril tangles. Several methodologies have been employed to treat the disease. Albeit engineered medications which are accessible for the treatment of Alzheimer’s, due to their numerous side-effects, it becomes imperative to formulate and synthesize novel drug candidates. Plants could be utilized as an alternative for these manufactured medications because of their low incidental effects in contrast with the engineered drugs. Bacopa monneiri (BM) is a therapeutic plant which is accounted for to be utilized to treat NDs. Therefore, in current study an in-silico approach was carried out to evaluate the pharmacological effect of BM. Molecular Docking was carried out to screen the active phytochemicals of BM which can act as potential drug candidates against amyloid-β plaques. A total of 8 biologically active phytochemicals from BM were docked against p75NTR receptor. Based on molecular docking study it was observed that the phytocompounds Bacopasaponin D and Bacopasaponin G of BM significantly fits to the active site of p75NTR. Further Molecular Dynamics simulation study was performed to examine the stability of the binding of these phytochemicals with the selected targets. Our findings suggested that the phytocompounds Bacopasaponin D and Bacopasaponin G significantly binds with p75NTR and thus might have a potential to inhibit the natural binding activity of amyloid-b plaques and act as a potential anti-neurodegenerative drug.
Targeted Proteomics of Plasma Extracellular Vesicles Uncovers MUC1 as Combinatorial Biomarker for the Early Detection of High-grade Serous Ovarian Cancer
Authors: Cooper Tyler T. , Dieters-Castator Dylan Z. , Liu Jiahui , Siegers Gabrielle M. , Pink Desmond , Veliz Lorena , Lewis John D. , Lagugné-Labarthet François , Fu Yangxin , Steed Helen , Lajoie Gilles A. , Postovit Lynne-Marie 
Published: April 2022

AbstractPurposeThe five-year prognosis for patients with late-stage high-grade serous carcinoma (HGSC) remains dismal, underscoring the critical need for identifying early-stage biomarkers. This study explores the potential of extracellular vesicles (EVs) circulating in blood, which are believed to harbor proteomic cargo reflective of the HGSC microenvironment, as a source for biomarker discovery.Experimental DesignWe conducted a comprehensive proteomic profiling of EVs isolated from blood plasma, ascites, and cell lines of patients, employing both data-dependent (DDA) and data-independent acquisition (DIA) methods to construct a spectral library tailored for targeted proteomics. Our investigation aimed at uncovering novel biomarkers for the early detection of HGSC by comparing the proteomic signatures of EVs from women with HGSC to those with benign gynecological conditions. The initial cohort, comprising 9-10 donors, utilized DDA proteomics for spectral library development. The subsequent cohort, involving 30 HGSC patients and 30 control subjects, employed DIA proteomics for a similar purpose. Support vector machine (SVM) classification was applied in both cohorts to identify combinatorial biomarkers with high specificity and sensitivity (ROC-AUC > 0.90).ResultsNotably, MUC1 emerged as a significant biomarker in both cohorts when used in combination with additional biomarkers. Validation through an ELISA assay on a subset of benign (n=18), Stage I (n=9), and stage II (n=9) plasma samples corroborated the diagnostic utility of MUC1 in the early-stage detection of HGSC.ConclusionsThis study highlights the value of EV-based proteomic analysis in the discovery of combinatorial biomarkers for early ovarian cancer detection.
A computational method for Cell type-specific Expression Quantitative Trait Loci mapping using bulk RNA-seq data
Authors: Little Paul , Liu Si , Zhabotynsky Vasyl , Li Yun , Lin Danyu , Sun Wei 
Published: April 2022

AbstractMapping cell type-specific gene expression quantitative trait loci (ct-eQTLs) is a powerful way to investigate the genetic basis of complex traits. A popular method for ct-eQTL mapping is to assess the interaction between the genotype of a genetic locus and the abundance of a specific cell type using a linear model. However, this approach requires transforming RNA-seq count data, which distorts the relation between gene expression and cell type proportions and results in reduced power and/or inflated type I error. To address this issue, we have developed a statistical method called CSeQTL that allows for ct-eQTL mapping using bulk RNA-seq count data while taking advantage of allele-specific expression. We validated the results of CSeQTL through simulations and real data analysis, comparing CSeQTL results to those obtained from purified bulk RNA-seq data or single cell RNA-seq data. Using our ct-eQTL findings, we were able to identify cell types relevant to 21 categories of human traits.
Protons in gating the Kv1,2 channel: a calculated conformational change in response to addition of a proton, and a proposed path from voltage sensing domain to gate
Authors: Kariev Alisher M. , Green Michael E 
Published: April 2022

ABSTRACTWe have in the past proposed that protons constitute the gating current in the potassium channel Kv1.2. Here we present a quantum calculation of a protonation change in a 311 atom section of intracellular S4-S5 linker, together with part of the T1 intracellular moiety of the channel. This proton shift leads to a hinge rotation in the linker, which in turn produces a separation of two amino acids, K312 and R326 (using the numbering of the 3Lut pdb structure). Two complete proton wires can then be proposed that would fully account for the gating mechanism with protons; the proton wires have as yet not been completely calculated. However, the path seems reasonably evident, based on the amino acids in the S4-S5 linker, which connects to the pore transmembrane S6 segment as well, and the T1 moiety of the channel, which is part of one proton path. This therefore also accounts for the T1 effect on gating. We had earlier shown how a proton could be generated from the VSD. Taken together the paths from the VSD to the gate show how the VSD can couple to the gating mechanism by having protons move between the VSD and the gate, closing the channel by both producing the hinge rotation and providing electrostatic repulsion to an incoming K+ ion. The protons move under the influence of membrane polarization/depolarization. Taken together, this makes our previous model much more detailed, specifying the role of particular amino acids.
Long-range inhibition synchronizes and updates prefrontal task activity
Authors: Cho Kathleen K.A. , Shi Jingcheng , Sohal Vikaas S. 
Published: April 2022

AbstractChanges in patterns of activity within the medial prefrontal cortex enable rodents, non-human primates, and humans to update their behavior to adapt to changes in the environment, e.g., during cognitive tasks1–5. Within medial prefrontal cortex, inhibitory neurons expressing parvalbumin are important for updating strategies in a rule shift task6–8. Nevertheless, causal mechanisms through which parvalbumin neurons recruit specific circuits to produce prefrontal network dynamics that switch from maintaining to updating task-related patterns of activity remain unknown. Here we identify a new long-range inhibitory projection from prefrontal parvalbumin neurons to the contralateral cortex that mediates this process. Whereas nonspecifically inhibiting all callosal projections does not prevent mice from learning rule shifts, selectively inhibiting these callosal parvalbumin projections disrupts rule shift learning, desynchronizes gamma-frequency activity that is necessary for learning8, and suppresses changes in prefrontal activity patterns that normally accompany rule shifts. Thus, callosal parvalbumin projections switch prefrontal circuits from maintaining to updating behavioral strategies by synchronizing callosal communication and preventing it from inappropriately maintaining outdated neural representations. These findings may explain how deficits in prefrontal parvalbumin neurons and gamma synchrony cause impaired behavioral flexibility in schizophrenia9–10, and identify long-range projections from prefrontal parvalbumin neurons as a key circuit locus for understanding and treating these deficits.
Small Molecules Restore Azole Activity Against Drug-Tolerant and Drug-ResistantCandidaIsolates
Authors: Alabi Philip E. , Gautier Cécile , Murphy Thomas P. , Gu Xilin , Lepas Mathieu , Aimanianda Vishukumar , Sello Jason K. , Ene Iuliana V. 
Published: April 2022

ABSTRACTEach year, fungi cause more than 1.5 billion infections worldwide and have a devastating impact on human health, particularly in immunocompromised individuals or patients in intensive care units. The limited antifungal arsenal and emerging multidrug resistant species necessitate the development of new therapies. One strategy for combating drug resistant pathogens is the administration of molecules that restore fungal susceptibility to approved drugs. Accordingly, we carried out a screen to identify small molecules that could restore the susceptibility of pathogenicCandidaspecies to azole antifungals. This screening effort led to the discovery of novel 1,4-benzodiazepines that restore fluconazole susceptibility in resistant isolates ofCandida albicans, as evidenced by 100-1000-fold potentiation of fluconazole activity. This potentiation effect was also observed in azole-tolerant strains ofC. albicansand in other pathogenicCandidaspecies. The 1,4-benzodiazepines selectively potentiated different azoles, but not other approved antifungals. A remarkable feature of the potentiation was that the combination of the compounds with fluconazole was fungicidal, whereas fluconazole alone is fungistatic. Interestingly, the potentiators were not toxic toC. albicansin the absence of fluconazole, but inhibited virulence-associated filamentation of the fungus. We found that the combination of the potentiators and fluconazole significantly enhanced host survival in aGalleria mellonellamodel of systemic fungal infection. Taken together, these observations validate a strategy wherein small molecules can restore the activity of highly used anti-infectives that have lost potency.IMPORTANCEIn the last decade, we have been witnessing a higher incidence of fungal infections, due to an expansion of the fungal species capable of causing disease (e.g.,Candida auris), as well as increased antifungal drug resistance. Among human fungal pathogens,Candidaspecies are a leading cause of invasive infections and are associated with high mortality rates. Infections by these pathogens are commonly treated with azole antifungals, yet the expansion of drug-resistant isolates have reduced their clinical utility. In this work, we describe the discovery and characterization of small molecules that potentiate fluconazole and restore the susceptibility of azole-resistant and azole-tolerantCandidaisolates. Interestingly, the potentiating 1,4-benzodiazepines were not toxic to fungal cells but inhibited their virulence-associated filamentous growth. Furthermore, combinations of the potentiators and fluconazole decreased fungal burdens and enhanced host survival in aGalleria mellonellamodel of systemic fungal infections. Accordingly, we propose the use of novel antifungal potentiators as a powerful strategy for addressing the growing resistance of fungi to clinically approved drugs.
An untargeted metabolomics analysis of exogenous chemicals in human milk and transfer to the infant
Authors: Thomas Sydney , Gauglitz Julia M. , Tripathi Anupriya , Vargas Fernando , Bertrand Kerri , Kim Jae H. , Chambers Christina , Dorrestein Pieter C. , Tsunoda Shirley 
Published: April 2022

AbstractHuman milk is the optimal infant nutrition. However, while human-derived metabolites such as lipids and oligosaccharides in human milk are regularly reported, the presence of exogenous chemicals (such as drugs, food, and synthetic compounds) are often not addressed. To understand the types of exogenous compounds that might be present, human milk (n=996) was analyzed by untargeted metabolomics. This analysis revealed that lifestyle molecules such as medications and their metabolites, food, industrial sources such as plasticizers, cosmetics, microbial molecules, and other personal care products are found in human milk. We provide further evidence that some of these lifestyle molecules are also detectable in the newborn’s stool. Thus, this study gives important insight into the types of exposures infants receiving human milk might ingest due to the lifestyle choices, exposure, or medical status of the lactating parent.
Development of a long-read NGS workflow for improved characterization of fastidious respiratory mycoplasmas
Authors: Framst Isaac , D’Andrea Cassandra , Baquero Monica , Maboni Grazieli 
Published: April 2022

AbstractMycoplasmas are respiratory pathogens in humans and animals and due to their fastidious nature, they have been historically underdiagnosed. Lack of standardised diagnostic, typing and antimicrobial susceptibility testing methods makes clinical management and epidemiological studies challenging. The aim of this study was to develop a cost-effective and accurate sequencing workflow for genotypic characterization of clinical isolates of respiratory mycoplasmas using a rapid long-read sequencing platform. Critical aspects of bacterial whole genome sequencing were explored using fastidious respiratory Mycoplasma (M. felis and M. cynos) isolated from animals including: (i) four solid and liquid-based media based on a specialized formulation for Mycoplasma culture, (ii) three DNA extraction methods modified for sequencing purposes, and (iii) two de novo assembly platforms as key components of a bioinformatic pipeline including Flye and Canu assemblers. DNA quality and quantity compatible with long-read sequencing requirements were obtained with culture volumes of 160ml in modified Hayflick’s broth incubated for 96 hours. The other three culture approaches investigated did not meet the DNA quality criteria required for long-read sequencing. The use of bead-beating bacterial cell lysis in the extraction protocol resulted in smaller fragments and shorter reads compared to enzymatic lysis methods. Overall, Flye generated more contiguous assemblies than the Canu assembler. This novel study provides a step-by-step sequencing workflow including mycoplasma culture, DNA extraction and de novo assembly approaches for the characterization of highly fastidious respiratory mycoplasmas. This workflow will provide diagnosticians, epidemiologists, and researchers with a more comprehensive tool than the laborious conventional methods for a complete genomic characterization of respiratory mycoplasmas.
Impact of 100 LRRK2 variants linked to Parkinson’s Disease on kinase activity and microtubule binding
Authors: Kalogeropulou Alexia F , Purlyte Elena , Tonelli Francesca , Lange Sven M , Wightman Melanie , Prescott Alan R , Padmanabhan Shalini , Sammler Esther , Alessi Dario R 
Published: April 2022

AbstractMutations enhancing the kinase activity of LRRK2 cause Parkinson’s disease (PD) and therapies that reduce LRRK2 kinase activity are being tested in clinical trials. Numerous rare variants of unknown clinical significance have been reported, but how the vast majority impact on LRRK2 function is unknown. Here, we investigate 100 LRRK2 variants linked to PD, including previously described pathogenic mutations. We identify 23 LRRK2 variants that robustly stimulate kinase activity, including variants within the N-terminal non-catalytic regions [ARM (E334K, A419V), ANK(R767H), LRR (R1067Q, R1325Q)], as well as variants predicted to destabilise the ROC:CORB interface [ROC (A1442P, V1447M), CORA (R1628P) CORB (S1761R, L1795F)] and COR:COR dimer interface [CORB (R1728H/L)]. Most activating variants decrease LRRK2 biomarker site phosphorylation (pSer935/pSer955/pSer973), consistent with the notion that the active kinase conformation blocks their phosphorylation. We conclude that the impact of variants on kinase activity is best evaluated by deploying a cellular assay of LRRK2-dependent Rab10 substrate phosphorylation, compared to a biochemical kinase assay, as only a minority of activating variants [CORB (Y1699C, R1728H/L, S1761R) and kinase (G2019S, I2020T, T2031S)], enhance in vitro kinase activity of immunoprecipitated LRRK2. Twelve variants including several that activate LRRK2 and have been linked to PD, suppressed microtubule association in the presence of a Type I kinase inhibitor [ARM(M712V), LRR(R1320S), ROC (A1442P, K1468E, S1508R), CORA(A1589S), CORB (Y1699C, R1728H/L) and WD40(R2143M, S2350I, G2385R)]. Our findings will stimulate work to better understand the mechanisms by which variants impact biology and provide rationale for variant carrier inclusion or exclusion in ongoing and future LRRK2 inhibitor clinical trials.
X-ray reflectivity from curved surfaces as illustrated by a graphene layer on molten copper
Authors: Konovalov Oleg V. , Belova Valentina , La Porta Francesco , Saedi Mehdi , Groot Irene M. N. , Renaud Gilles , Snigireva Irina , Snigirev Anatoly , Voevodina Maria , Shen Chen , Sartori Andrea , Murphy Bridget M. , Jankowski Maciej 
Published: April 2022

The X-ray reflectivity technique can provide out-of-plane electron-density profiles of surfaces, interfaces, and thin films, with atomic resolution accuracy. While current methodologies require high surface flatness, this becomes challenging for naturally curved surfaces, particularly for liquid metals, due to the very high surface tension. Here, the development of X-ray reflectivity measurements with beam sizes of a few tens of micrometres on highly curved liquid surfaces using a synchrotron diffractometer equipped with a double crystal beam deflector is presented. The proposed and developed method, which uses a standard reflectivity θ–2θ scan, is successfully applied to study in situ the bare surface of molten copper and molten copper covered by a graphene layer grown in situ by chemical vapor deposition. It was found that the roughness of the bare liquid surface of copper at 1400 K is 1.25 ± 0.10 Å, while the graphene layer is separated from the liquid surface by a distance of 1.55 ± 0.08 Å and has a roughness of 1.26 ± 0.09 Å.