bluuebunny/crossref_metadata_2025 huggingface dataset:
A near-complete genome sequence of einkorn wheat provides insight into the evolution of wheat A subgenomes
Authors: Wang Xiangfeng , Li Hongna , Shen Tao , Wang Xinrui , Yi Shu , Meng Tan , Sun Jie , Wang Xiaoliang , Qu Xiaojian , Chen Shisheng , Guo Li
Published: May 2023

Einkorn wheat (Triticum monococcum) is one of the oldest cereal crops to be domesticated by human beings, playing essential role in early agriculture development. Today, it is considered an important genomic resource for modern wheat improvement, especially for resistance against pests and diseases. However, the exploration and utilization of useful genes fromT. monococcumis limited due to the lack of a reference genome and annotation for this species. Here, we report a near-complete genome assembly forT. monococcumwith a total length of 5.11 Gb with a contig N50 of 131.2Mb and scaffold N50 of 728.66Mb, representing a genome assembly of highest quality for any wheat genome reported. Phylogenomic analysis confirmedT. monococcumis closely-related toT. urartu, the progenitor of wheat A subgenomes. A 4AL/5AL terminal translocation is present in the diploid speciesT. urartuandT. monococcum, taking place before wheat polyploidization.T. monococcumhas significantly expanded and unique gene families involved in DNA damage repair and heat stress tolerance, reflecting its adaptive evolution to cope with historical harsh climate in its natural habitat, South East Turkey. The genome sequence confirmed the introgression ofT. monococcumrust resistance genes at 5AmL into modern bread wheat varieties. This near-complete reference genome ofT. monococcumwill be an essential resource for wheat functional and evolutionary genomic studies and expedite the cloning of useful genes inT. monococcumfor future wheat improvement.
TBX2 driven switch from Androgen Receptor to Glucocorticoid Receptor signaling confers therapeutic resistance in Prostate Cancer
Authors: Dutta Sayanika , Patel Girijesh Kumar , Khedmatgozar Hamed , Latour Daniel , Tripathi Manisha , Nandana Srinivas
Published: May 2023

Recent studies have highlighted that androgen receptor (AR) signaling can be bypassed via activation of the glucocorticoid receptor (GR), and that this bypass drives enzalutamide resistance in advanced prostate cancer (PCa). However, the molecular mechanism(s) that drive the switch from AR to GR signaling remain unknown. We have previously reported that TBX2, a developmental T-box transcription factor (TF), is over-expressed in castrate resistant prostate cancer (CRPC) and that TBX2 drives the CRPC phenotype via cell-intrinsic and exosome-mediated paracrine modes. Our current study demonstrates that TBX2, a TF with known repressor and activator functions, may be the molecular switch that represses AR on one hand while activating GR expression on the other to drive CRPC. Mechanistically, our studies revealed a two-tiered mechanism of AR repression by TBX2 wherein TBX2 directly binds to the promoters of AR and GATA2, an AR coregulator, thereby resulting in the repression of AR as well as GATA2. Conversely, our results demonstrate that TBX2 mediates increased expression of GR via directly binding to the GR promoter, and through TBX2-GR functional protein-protein interaction. Our results demonstrate that the TBX2 driven switch from AR to GR signaling results in enzalutamide resistance since GR inhibition in the context of TBX2 over-expression attenuates enzalutamide resistance. Further, we present evidence that SP2509 based allosteric inhibition of Lysine Specific Demethylase 1 (LSD1), a protein that interacts with TBX2 as part of the Co-repressor of RE1-Silencing Transcription Factor (COREST) complex, is able to disrupt TBX2-GR interaction. Taken together, our study has identified TBX2 as the molecular switch that drives AR to GR signaling and thereby confers enzalutamide resistance in CRPC. Furthermore, our study provides key insights into a potential therapeutic strategy of targeting the AR to GR switch wherein SP2509-based allosteric inhibition of TBX2-LSD1 could be harnessed to target the TBX2-GR interaction, thereby resulting in the inhibition of enzalutamide resistance in CRPC.
Nitrogen starvation causes lipid remodeling inRhodotorula toruloides
Authors: Mishra Shekhar , Deewan Anshu , Zhao Huimin , Rao Christopher V.
Published: May 2023

The oleaginous yeastRhodotorula toruloidesis a promising chassis organism for the biomanufacturing of value-added bioproducts. It can accumulate lipids at a high fraction of biomass. However, metabolic engineering efforts in this organism have progressed at a slower pace than those in more extensively studied yeasts. Few studies have investigated the lipid accumulation phenotype exhibited byR. toruloidesunder nitrogen limitation conditions. Consequently, there have been only a few studies exploiting the lipid metabolism for higher product titers. Here, we present a multi-omic investigation of the lipid accumulation phenotype under nitrogen limitation. Through an integrative lens of transcriptomic and lipidomic analysis, we identify thatR. toruloidesundergoes lipid remodeling during nitrogen limitation, wherein the pool of phospholipids gets remodeled to mostly storage lipids. This insight into the mechanisms of lipid accumulation can lead to the success of future metabolic engineering strategies for overproduction of oleochemicals.

Highlights

The oleaginous yeastR. toruloidesdisplays enhanced lipid accumulation during nitrogen starvation.

A multi-omic investigation of the lipid accumulation phenotype was carried out.

Lipid remodeling was observed during the accumulation phase, wherein carbon was transferred from phospholipids to storage lipids.

Multi-omic analysis suggested that selective regulation within lipid biosynthesis controls for the specific increase of storage lipids.
High-resolution spatial multi-omics reveals cell-type specific nuclear compartments
Authors: Takei Yodai , Yang Yujing , White Jonathan , Yun Jina , Prasad Meera , Ombelets Lincoln J , Schindler Simone , Cai Long
Published: May 2023

The mammalian nucleus is compartmentalized by diverse subnuclear structures. These subnuclear structures, marked by nuclear bodies and histone modifications, are often cell-type specific and affect gene regulation and 3D genome organization1–3. Understanding nuclear organization requires identifying the molecular constituents of subnuclear structures and mapping their associations with specific genomic loci in individual cells, within complex tissues. Here, we introduce two-layer DNA seqFISH+, which allows simultaneous mapping of 100,049 genomic loci, together with nascent transcriptome for 17,856 genes and a diverse set of immunofluorescently labeled subnuclear structures all in single cells in cell lines and adult mouse cerebellum. Using these multi-omics datasets, we showed that repressive chromatin compartments are more variable by cell type than active compartments. We also discovered a single exception to this rule: an RNA polymerase II (RNAPII)-enriched compartment was associated with long, cell-type specific genes (> 200kb), in a manner distinct from nuclear speckles. Further, our analysis revealed that cell-type specific facultative and constitutive heterochromatin compartments marked by H3K27me3 and H4K20me3 are enriched at specific genes and gene clusters, respectively, and shape radial chromosomal positioning and inter-chromosomal interactions in neurons and glial cells. Together, our results provide a single-cell high-resolution multi-omics view of subnuclear compartments, associated genomic loci, and their impacts on gene regulation, directly within complex tissues.
Persistent humoral immunity in children and adolescents throughout the COVID-19 pandemic (June 2020 to July 2022): a prospective school-based cohort study (Ciao Corona) in Switzerland
Authors: Raineri Alessia , Radtke Thomas , Rueegg Sonja , Haile Sarah R. , Menges Dominik , Ballouz Tala , Ulyte Agne , Fehr Jan , Cornejo Daniel L. , Pantaleo Giuseppe , Pellaton Céline , Fenwick Craig , Puhan Milo A. , Kriemler Susi
Published: May 2023

Objectives

To assess the longitudinal development of humoral immunity in children and adolescents during the COVID-19 pandemic, with a particular focus on how anti-spike IgG antibodies and neutralising response changed during the first Omicron peak (December 2021 to May 2022).

Design

Prospective school-based study during the COVID-19 pandemic (June 2020 to July 2022) including five testing rounds with corresponding cross-sectional cohorts and a longitudinal cohort who participated in at least four rounds.

Setting

55 randomly selected schools in the Canton of Zurich, Switzerland.

Participants

Between 1875 to 2500 children and adolescents per testing round and 751 in the longitudinal cohort.

Main outcome measures

Development of SARS-CoV-2 seroprevalence, anti-spike IgG antibodies and neutralising antibody response over time, persistence of antibodies and variation of antibody levels in individuals only infected, vaccinated or with hybrid immunity during the early Omicron period.

Results

By July 2022 96.9% (95% credible interval [CrI] 95.2 to 98.1%) of children and adolescents had anti-spike IgG antibodies against SARS-CoV-2. The substantial increase in seroprevalence during the first peak of the Omicron wave was largely driven by primary infections in mostly unvaccinated children under the age of 12 (28.4% [95% CrI 24.2 to 33.2%] in December 2021, to 95.7% [95% CrI 93.4 to 97.4%] in July 2022). This stands in contrast to adolescents aged 12 years and older (69.4% [95% CrI 64.0 to 75.4%] in December 2021 to 98.4% [95% CrI 97.3 to 99.2%] in July 2022), who were eligible for vaccination since June 2021. Children and adolescents with hybrid immunity or immunity from vaccination had high anti-spike IgG titres (median Mean Fluorescence Intensity (MFI) ratio of 136.2 [Inter Quartile Range [IQR]: 121.9 to 154.3] and 127.6 [IQR: 114.1 to 151.0]) and strong neutralising responses (e.g., anti-Omicron 98.9% [95% Confidence Interval [CI] 96.0 to 99.7%] and 81.6% [95% CI 74.9 to 86.9%]). Meanwhile, infected but unvaccinated children and adolescents had substantially lower anti-spike IgG titres (median MFI ratio of 54.8 [IQR: 22.8 to 89.8]) and neutralising responses (e.g., anti-Omicron 64.9% [95% CI 59.8 to 69.7%]).

Conclusion

These findings show that the Omicron wave and the rollout of vaccines led to almost 100% seropositivity and boosted anti-spike IgG titres and neutralising capacity in children and adolescents. This was particularly driven by unvaccinated children (<12 years), who became seropositive due to the highly infectious Omicron variant. Nevertheless, during the entire study period parents of only one adolescent reported hospital stay of less than 24 hours related to a possible acute infection.
Neuromodulation for peripheral arterial disease of lower extremities: A 10-year analysis
Authors: Kretzschmar Michael , Okaro Udoka , Schwarz Marcus , Reining Marco , Lesser Thomas
Published: May 2023

Introduction

Spinal cord stimulation (SCS) or Dorsal root ganglion stimulation (DRG-S) can improve limb salvage, microcirculatory blood flow, and pain relief in patients with peripheral arterial disease (PAD) who are not candidates for revascularization or who have persistent ischemic-related pain after revascularization This retrospective analysis presents 10-year data on the effectiveness and safety outcomes of neuromodulation for PAD at a single center.

Objective

This study evaluated the survival and amputation outcome of subjects who received neuromodulation therapy for the management of PAD. Descriptive outcomes such as Walking distance (m), pain intensity (NRS), opioid consumption (MME [morphine milligram equivalents]/d), and self-rated health (EQ-VAS) were also analysed.

Methods

This study retrospectively reviews the health data of a single cohort of 51 patients who received an SCS or DRG-S from 2007 to 2022 in a single German center. Survival rate was determined using the Kaplan Meier (KM) curve and major amputation was determined as the amputation of a major limb above the ankle. Patients who received a toe amputation were excluded from the amputation analysis. Two patients were excluded (2 patients died at 3 and 5 months after implantation. Pain, quality of life, walking distance, and opioid usage were assessed before implantation (baseline), 1, 6, and 12 months after implantation, and then annually (during a follow-up visit). Implant-related complications were also documented.)

Results

51 patients (37 men [mean age 68.9± 10.2], 14 women [mean age (68.7 ± 14.6]) underwent SCS (n = 49) or DRG-S (n = 2) implantation due to persistent ischemic pain. The follow-up mean years ± SD is 4.04 ± 2.73 with a range of 1 – 10 years. Atherosclerosis (40.4%) and diabetic vascular disease (48.9%) were the most common pathologies with 48.9% of patients depending on nicotine. At baseline, patients were classified as Rutherford’s Category 3 (n = 23), Category 4 (n = 15), or Category 5 (n = 9). At 24M, 42/47 patients did not require a major amputation following the implant. All patients reported complete pain relief from pain at rest, and 93.3% reported no pain from walking. A total of 75% of patients were able to walk more than 200m and 87% of patients who used opioids at baseline were off this medication at 24 months. Overall, 93% of patients reported an improvement in their overall health assessment. These improved outcomes were sustained through years 3-10 for patients who have reported outcomes.

Conclusions

Our single center data supports the efficacy of spinal neuromodulation for improvements in limb salvage, pain relief, mobility, and quality of life. Also, the data show that neuromodulative therapy has a long-term therapeutic effect in patients with chronic limb pain with Rutherford class 3, 4, and 5 peripheral arterial disease (both reconstructable and non-reconstructable).
A machine learning model for predicting out-of-hospital cardiac arrest incidence using meteorological, chronological, and geographical data from the United States
Authors: Nakashima Takahiro , Ogata Soshiro , Kiyoshige Eri , Al-Hamdan Mohammad Z , Wang Yifan , Noguchi Teruo , Shields Theresa A , Al-Araji Rabab , McNally Bryan , Nishimura Kunihiro , Neumar Robert W
Published: May 2023

Background

Despite advances in pre- and post-resuscitation care, percentage of survival to hospital discharge after out-of-hospital cardiac arrest (OHCA) was extremely low. Development of an accurate system to predict the daily incidence of OHCA might provide a significant public health benefit. Here, we developed and validated a machine learning (ML) predictive model for daily OHCA incidence using high-resolution meteorological, chronological, and geographical data.

Methods

We analyzed a dataset from the United States that combined an OHCA nationwide registry, high-resolution meteorological data, chronological data, and geographical data. We developed a model to predict daily OHCA incidence with a training dataset for 2013–2017 using the eXtreme Gradient Boosting algorithm. A dataset for 2018–2019 was used to test the predictive model. The main outcome was the predictive accuracy for the number of daily OHCA events, based on root mean squared error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). In general, a model with MAPE less than 10% is considered highly accurate.

Results

Among the 446,830 OHCAs of non-traumatic cause where resuscitative efforts were initiated by a 911 responder, 264,916 in the training dataset and 181,914 in the testing dataset were included in the analysis. The ML model with combined meteorological, chronological, and geographical data had high predictive accuracy in relation to nationwide incidence rate per 100,000 at the nationwide level) in the training dataset (RMSE, 0.016; MAE, 0.013; and MAPE, 7.61%) and in the testing dataset (RMSE, 0.018; MAE, 0.014; and MAPE, 6.52%).

Conclusions

A ML predictive model using comprehensive daily meteorological, chronological, and geographical data allows for highly precise estimates of OHCA incidence in the United States.

Clinical Perspective

What is new?

A machine learning predictive model developed with a high-resolution meteorological dataset and chronological and geographical variables predicted the daily incidence of out-of-hospital cardiac arrest (OHCA) in the U.S. population with high precision. The predictive accuracy at the state level was greater in medium and high-temperature areas than in the low-temperature area.

What are the clinical implications?

This predictive model revealed complex associations between meteorological, chronological, and geographic variables in relation to predicting daily incidence of OHCA. It might be useful for public health strategies in temperate regions, for example, by providing a warning system for citizens and emergency medical services agencies on high-risk days.
Early recanalization among patients undergoing bridging therapy with tenecteplase or alteplase
Authors: Checkouri Thomas , Gerschenfeld Gaspard , Seners Pierre , Yger Marion , Hassen Wagih Ben , Chausson Nicolas , Olindo Stéphane , Caroff Jildaz , Marnat Gaultier , Clarençon Frédéric , Baron Jean-Claude , Turc Guillaume , Alamowitch Sonia
Published: May 2023

Background

Intravenous thrombolysis (IVT) with alteplase or tenecteplase prior to mechanical thrombectomy (MT) is the recommended treatment for large-vessel occlusion acute ischemic stroke (LVOS). There are divergent data on whether these agents differ in terms of early recanalization (ER) rates before MT, and little data on their potential differences in terms of established ER predictors such as time elapsed between IVT and ER evaluation (IVT-to-ERevaltime), occlusion site and thrombus length.

Methods

We compared the likelihood of ER after IVT with tenecteplase or alteplase in anterior circulation LVOS patients from the PREDICT-RECANAL (alteplase) and TETRIS (tenecteplase) French multicenter registries. ER was defined as a modified thrombolysis in cerebral infarction score 2b-3 on first angiographic run or non–invasive vascular imaging (magnetic resonance or computed tomography angiography) in patients with early neurological improvement. Analyses were based on propensity score overlap weighting (PSOW, leading to an exact balance in baseline characteristics between the treatment groups) and confirmed with adjusted logistic regression (sensitivity analysis).

Results

A total of 1865 patients were included. ER occurred in 156/787 (19.8%) and 199/1078 (18.5%) patients treated with tenecteplase or alteplase, respectively (odds ratio, 1.09 [95%CI 0.83–1.44];P=0.52). A differential effect of tenecteplasevsalteplase on the probability of ER according to thrombus length was observed (Pinteraction=0.003), with tenecteplase being associated with higher odds of ER in thrombi > 10 mm (odds ratio, 2.43 [95% CI 1.02-5.81];P=0.04). There was no differential effect of tenecteplasevsalteplase on the likelihood of ER according to the IVT-to-ERevaltime (Pinteraction=0.40) or occlusion site (Pinteraction=0.80).

Conclusion

Both thrombolytics achieved ER in a fifth of LVOS patients, with potentially greater effect of tenecteplase in larger thrombi. There was no significant differential influence of IVT-to-ERevaltime or occlusion site on likelihood of ER.
Modelling cell adaptation using internal variables: accounting for cell plasticity in continuum mathematical biology
Authors: Pérez-Aliacar Marina , Ayensa-Jiménez Jacobo , Doblaré Manuel
Published: May 2023

Abstract

Cellular adaptation is the ability of cells to change in response to different stimuli and environmental conditions. It occurs via phenotypic plasticity, that is, changes in gene expression derived from changes in the physiological environment. This phenomenon is important in many biological processes, in particular in cancer evolution and its treatment. Therefore, it is crucial to understand the mechanisms behind it. Specifically, the emergence of the cancer stem cell phenotype, showing enhanced proliferation and invasion rates, is an essential process in tumour progression.

We present a mathematical framework to simulate phenotypic heterogeneity in different cell populations as a result of their interaction with chemical species in their microenvironment, through a continuum model using the well-known concept of internal variables to model cell phenotype. The resulting model, derived from conservation laws, incorporates the relationship between the phenotype and the history of the stimuli to which cells have been subjected, together with the inheritance of that phenotype. To illustrate the model capabilities, it is particularised for glioblastoma adaptation to hypoxia. A parametric analysis is carried out to investigate the impact of each model parameter regulating cellular adaptation, showing that it permits reproducing different trends reported in the scientific literature. The framework can be easily adapted to any particular problem of cell plasticity, with the main limitation of having enough cells to allow working with continuum variables. With appropriate calibration and validation, it could be useful for exploring the underlying processes of cellular adaptation, as well as for proposing favorable/unfavourable conditions or treatments.
Anatomical registration of intracranial electrodes. Robust model-based localization and deformable smooth brain-shift compensation methods
Authors: Blenkmann Alejandro Omar , Leske Sabine Liliana , Llorens Anaïs , Lin Jack J. , Chang Edward , Brunner Peter , Schalk Gerwin , Ivanovic Jugoslav , Larsson Pål Gunnar , Knight Robert Thomas , Endestad Tor , Solbakk Anne-Kristin
Published: May 2023

Precise electrode localization is important for maximizing the utility of intracranial EEG data. Electrodes are typically localized from post-implantation CT artifacts, but algorithms can fail due to low signal-to-noise ratio, unrelated artifacts, or high-density electrode arrays. Minimizing these errors usually requires time-consuming visual localization and can still result in inaccurate localizations. In addition, surgical implantation of grids and strips typically introduces non-linear brain deformations, which result in anatomical registration errors when post-implantation CT images are fused with the pre-implantation MRI images. Several projection methods are currently available, but they either fail to produce smooth solutions or do not account for brain deformations.

To address these shortcomings, we propose two novel algorithms for the anatomical registration of intracranial electrodes that are almost fully automatic and provide highly accurate results. We first presentGridFit,an algorithm that simultaneously localizes all contacts in grids, strips, or depth arrays by fitting flexible models to the electrodes’ CT artifacts. We observed localization errors of less than one millimeter (below 8% relative to the inter-electrode distance) and robust performance under the presence of noise, unrelated artifacts, and high-density implants when we ran ∼6000 simulated scenarios. Furthermore, we validated the method with real data from 20 intracranial patients.

As a second registration step, we introduceCEPA,a brain-shift compensation algorithm that combines orthogonal-based projections, spring-mesh models, and spatial regularization constraints. When tested with real data from 15 patients, anatomical registration errors were smaller than those obtained for well-established alternatives. Additionally,CEPAaccounted simultaneously for simple mechanical deformation principles, which is not possible with other available methods. Inter-electrode distances of projected coordinates smoothly changed across neighbor electrodes, while changes in inter-electrode distances linearly increased with projection distance. Moreover, in an additional validation procedure, we found that modeling resting-state high-frequency activity (75-145 Hz) in five patients further supported our new algorithm.

Together,GridFitandCEPAconstitute a versatile set of tools for the registration of subdural grid, strip, and depth electrode coordinates that provide highly accurate results even in the most challenging implantation scenarios. The methods presented here are implemented in the iElectrodes open-source toolbox, making their use simple, accessible, and straightforward to integrate with other popular toolboxes used for analyzing electrophysiological data.
Estimating the mean in the space of ranked phylogenetic trees
Authors: Berling Lars , Collienne Lena , Gavryushkin Alex
Published: May 2023

Reconstructing evolutionary histories of biological entities, such as genes, cells, organisms, populations, and species, from phenotypic and molecular sequencing data is central to many biological, palaeontological, and biomedical disciplines. Typically, due to uncertainties and incompleteness in data, the true evolutionary history (phylogeny) is challenging to estimate. Statistical modelling approaches address this problem by introducing and studying probability distributions over all possible evolutionary histories. In practice, computational methods are deployed to learn those distributions typically by sampling them. This approach, however, is fundamentally challenging as it requires designing and implementing various statistical methods over a space of phylogenetic trees (or treespace).

Although the problem of developing statistics over a treespace has received substantial attention in the literature and numerous breakthroughs have been made, it remains largely unsolved. The challenge of solving this problem is two-fold: a treespace has non-trivial often counter-intuitive geometry implying that much of classical Euclidean statistics does not immediately apply; many parametrisations of treespace with promising statistical properties are computationally hard, so they cannot be used in data analyses. As a result, there is no single conventional method for estimating even the most fundamental statistics over any treespace, such as mean and variance, and various heuristics are used in practice. Despite the existence of numerous tree summary methods to approximate means of probability distributions over a treespace based on its geometry, and the theoretical promise of this idea, none of the attempts resulted in a practical method for summarising tree samples.

In this paper we present such a method along with useful properties of our chosen treespace while focusing on its impact on phylogenetic analyses of real datasets. We perform an extensive benchmark study and demonstrate that our method outperforms currently most popular methods with respect to a number of important “quality” statistics. Further, we apply our method to three real datasets ranging from cancer evolution to linguistics and find novel insights into corresponding evolutionary problems in all of them. We hence conclude that this treespace is a promising candidate to serve as a foundation for developing statistics over phylogenetic trees analytically, as well as new computational tools for evolutionary data analyses.
NRF2 connects Src tyrosine kinase to ferroptosis resistance in glioblastoma
Authors: Cirotti Claudia , Taddei Irene , Contadini Claudia , Pepe Gerardo , Bardi Marco De , Borsellino Giovanna , Helmer-Citterich Manuela , Barilà Daniela
Published: May 2023

Glioblastoma (GBM) is a severe brain tumor characterized by an extremely poor survival rate of patients. GBM cancer cells escape to standard therapeutic protocols consisting of combination of ionizing radiation (IR) and alkylating drugs that trigger DNA damage, by rewiring of signaling pathways. In recent years, the upregulation of factors that counteract ferroptosis has been highlighted as a major driver of cancer resistance to IR, although the molecular connection between the activation of oncogenic signaling and the modulation of ferroptosis has not been clarified yet.

Here we provide the first evidence for a molecular connection between the constitutive activation of tyrosine kinases and resistance to ferroptosis. Src tyrosine kinase, a central hub on which Receptor Tyrosine Kinases deregulated signaling converge in cancer, leads to the stabilization and activation of NRF2 pathway, thus promoting resistance to IR-induced ferroptosis. These data suggest that the upregulation of Src-NRF2 axis may represent a vulnerability for combined strategies that, by targeting ferroptosis resistance, enhance radiation sensitivity in glioblastoma.
Comprehensive characterization of the neurogenic and neuroprotective action of a novel TrkB agonist using mouse and human stem cell models of Alzheimer’s Disease
Authors: Charou Despoina , Rogdakis Thanasis , Latorrata Alessia , Valcarcel Maria , Papadogiannis Vasileios , Athanasiou Christina , Tsengenes Alexandros , Papadopoulou Maria Anna , Lypitkas Dimitrios , Lavigne Matthieu D. , Katsila Theodora , Wade Rebecca C. , Cader M. Zameel , Calogeropoulou Theodora , Gravanis Achille , Charalampopoulos Ioannis
Published: May 2023

Neural stem cell (NSC) proliferation and differentiation in the mammalian brain decreases to minimal levels postnatally. Nevertheless, neurogenic niches persist in the adult cortex and hippocampus in rodents, primates and humans, with adult NSC differentiation sharing key regulatory mechanisms with development. Adult neurogenesis impairments have been linked to Alzheimer’s Disease (AD) pathology. Addressing these impairments is a promising new avenue for therapeutic intervention based on neurogenesis. However, this possibility has been hindered by technical difficulties of using in-vivo models to conduct screens, including working with scarce NSCs in the adult brain and differences between human and mouse models or ethical limitations. In our study, we use a combination of mouse and human stem cell models to circumvent these issues and perform comprehensive characterization of a novel neurogenic compound usingin vitroscreening. Our work focuses on the brain-derived neurotrophic factor (BDNF) pathway, a pivotal neurotrophin in the regulation of neuronal growth and differentiation via its receptor tyrosine receptor kinase B (TrkB). We describe the design, chemical synthesis and biological characterization of ENT-A011, a steroidal dehydroepiandrosterone (DHEA) derivative and BDNF mimetic with neuroprotective and neurogenic actions. The compound is able to increase proliferation of mouse primary adult hippocampal NSCs and embryonic cortical NSCs, in the absence of EGF/FGF, while reducing Amyloid-β (Aβ) induced cell death, acting specifically through TrkB activation. The compound is also able to increase astrocytic gene markers involved in NSC maintenance, protect hippocampal neurons from Αβ toxicity and prevent synapse loss after Aβ treatment. To provide a translational link to human cells, we also used neural progenitor cells (NPCs) differentiated from three human induced pluripotent stem cell lines from healthy and AD donors. Our findings suggest that ENT-A011 successfully induces proliferation and prevents cell death after Aβ toxicity of human NPCs. Additionally, using RNAseq profiling, we demonstrate that the compound acts through a core gene network shared with BDNF. Our work characterizes a novel synthetic BDNF mimetic with potential neurogenic and neuroprotective actions in Alzheimer’s disease via stem cell-based screening, demonstrating the promise of stem cell systems for short-listing competitive candidates for further testing.
Metastatic potentials classified with hypoxia-inducible factor 1 downstream gene in pan-cancer cell lines
Authors: Nakamichi Kazuya , Semba Kentaro , Nakayama Jun
Published: May 2023

Hypoxia-inducible factor 1 (HIF1) gene codes a transcription factor that is stabilized under hypoxia conditions via post-translational modifications. HIF1 regulates tumor malignancy and metastasis by gene transcriptions, such as Warburg effect- and angiogenesis-related genes, in cancer cells. However, the HIF1 downstream genes show varied expressional patterns in different cancer types. Herein, we performed the hierarchical clustering based on the HIF1 downstream gene expression patterns using 1,406 cancer cell lines crossing 30 types of cancer to understand the relationship between HIF1 downstream genes and the metastatic potential of cancer cell lines. Four types of cancer were classified by HIF1 downstream genes with significantly altered metastatic potentials. Furthermore, different HIF1 downstream gene subsets were extracted to discriminate each subtype for the four cancer types. HIF1 downstream subtyping classification will help understand the novel insight into tumor malignancy and metastasis in each cancer type.

Funding

This work was supported by Project for JSPS KAKENHI (Grant-in-Aid for Scientific Research (C): JP23K06665 to JN, Grant-in-Aid for Early-Carrier Scientists: JP21K15562 to JN), and in part by translational research program from Fukushima Prefecture (KS).

Competing Interests statement

The authors have declared that no conflict of interest exists.
CoCoNat: a novel method based on deep-learning for coiled-coil prediction
Authors: Madeo Giovanni , Savojardo Castrense , Manfredi Matteo , Martelli Pier Luigi , Casadio Rita
Published: May 2023

Motivation

Coiled-coil domains (CCD) are widespread in all organisms performing several crucial functions. Given their relevance, the computational detection of coiled-coil domains is very important for protein functional annotation. State-of-the art prediction methods include the precise identification of coiled-coil domain boundaries, the annotation of the typical heptad repeat pattern along the coiled-coil helices as well as the prediction of the oligomerization state.

Results

In this paper we describe CoCoNat, a novel method for predicting coiled-coil helix boundaries, residue-level register annotation and oligomerization state. Our method encodes sequences with the combination of two state-of-the-art protein language models and implements a three-step deep learning procedure concatenated with a Grammatical-Restrained Hidden Conditional Random Field (GRHCRF) for CCD identification and refinement. A final neural network (NN) predicts the oligomerization state. When tested on a blind test set routinely adopted, CoCoNat obtains a performance superior to the current state-of-the-art both for residue-level and segment-level coiled-coil detection. CoCoNat significantly outperforms the most recent state-of-the art method on register annotation and prediction of oligomerization states.

Availability

CoCoNat is available athttps://coconat.biocomp.unibo.it.

Contact

pierluigi.martelli@unibo.it
Progressive Senescence Programs Induce Intrinsic Vulnerability to Aging-related Breast Cancer
Authors: Bai Huiru , Liu Xiaoqin , Lin Meizhen , Meng Yuan , Li Nan , Clarke Michael F. , Cai Shang
Published: May 2023

Cancer incidence escalates exponentially with advancing age; however, the underlying mechanism remains unclear. In this study, we built a chronological molecular clock at the single-cell transcription level with a mammary stem cell-enriched population to depict physiological aging dynamics in mice. We found that the mammary aging process was asynchronous and progressive, initiated by an early senescence program with elevated NF-kB and P53 signaling, succeeded by an entropic late senescence program with reduced NF-kB and P53 signaling and enhanced PI3K-Akt-mTOR, Wnt, Notch and pluripotent activity, vulnerable to cancer predisposition. The transition towards senescence program was governed by the master stem cell factorBcl11b, loss of which accelerated mammary ageing with enhanced DMBA-induced tumor formation. We identified a drug TPCA-1 that can elevateBcl11b, rejuvenate mammary cells and significantly reduce aging-related cancer incidence. Our findings established a molecular portrait of progressive mammary cell aging and elucidated the transcriptional regulatory network bridging mammary aging and cancer predisposition, which can be modulated to control cancer initiation; therefore, this study has potential implications for the management of cancer prevalence in the aged.
Increase of cell surface vimentin (CSV) is associated with vimentin network disruption and subsequent stress-induced premature senescence (SIPS) in human chondrocytes
Authors: Riegger Jana , Brenner Rolf E.
Published: May 2023

Accumulation of dysfunctional chondrocytes has detrimental consequences on the cartilage homeostasis and is thus thought to play a crucial role during the pathogenesis of osteoarthritis (OA). However, the underlying mechanisms of phenotypical alteration in chondrocytes are incompletely understood.

Here, we provide evidence that disruption of the intracellular vimentin network and consequent phenotypical alteration in human chondrocytes results in an externalization of the intermediate filament. The presence of so-called cell surface vimentin (CSV) on chondrocytes was associated with the severity of tissue degeneration in clinical OA samples and was enhanced after mechanical injury of cartilage tissue. By means of a doxorubicine-based in vitro model of stress-induced premature senescence (SIPS), we could confirm the connection between cellular senescence and amount of CSV. Although siRNA-mediated silencing ofCDKN2Aclearly reduced the senescent phenotype as well as CSV levels of human chondrocytes, cellular senescence could not be completely reversed. Interestingly, knockdown of vimentin resulted in a SIPS-like phenotype and consequently increased CSV. Therefore, we concluded that the integrity of the intracellular vimentin network is crucial to maintain cellular function in chondrocytes. This assumption could be confirmed by chemically-induced collapse of the vimentin network, which resulted in cellular stress and enhanced CSV expression. Regarding its biological function, CSV was found to be associated with enhanced chondrocyte adhesion and plasticity. While osteogenic capacities seemed to be enhanced in chondrocytes expressing high levels of CSV, the chondrogenic potential was clearly compromised.

Overall, our study reinforces the importance of the vimentin network in maintenance of the chondrogenic phenotype and introduces CSV as a novel membrane-bound marker of dysfunctional chondrocytes.
Gene networks reveal stem-cell state convergence during preneoplasia and progression to malignancy in multistage skin carcinogenesis
Authors: Taylor Mark A. , Kandyba Eve , Halliwill Kyle , Delrosario Reyno , Koroshkin Matvei , Goodarzi Hani , Quigley David , Li Yun Rose , Wu Di , Bollam Saumya , Mirzoeva Olga , Akhurst Rosemary J. , Balmain Allan
Published: May 2023

Adult mammalian stem cells play critical roles in normal tissue homeostasis, as well as in tumor development, by contributing to cell heterogeneity, plasticity, and development of drug resistance. The relationship between different types of normal and cancer stem cells is highly controversial and poorly understood. Here, we carried out gene expression network analysis of normal and tumor samples from genetically heterogeneous mice to create network metagenes for visualization of stem-cell networks, rather than individual stem-cell markers, at the single-cell level during multistage carcinogenesis. We combined this approach with lineage tracing and single-cell RNASeq of stem cells and their progeny, identifying a previously unrecognized hierarchy in whichLgr6+ stem cells from tumors generate progeny that express a range of other stem-cell markers includingSox2, Pitx1, Foxa1, Klf5, andCd44. Our data identify a convergence of multiple stem-cell and tumor-suppressor pathways in benign tumor cells expressing markers of lineage plasticity and oxidative stress. This same single-cell population expresses network metagenes corresponding to markers of cancer drug resistance in human tumors of the skin, lung and prostate. Treatment of mouse squamous carcinomasin vivowith the chemotherapeuticcis-platin resulted in elevated expression of the genes that mark this cell population. Our data have allowed us to create a simplified model of multistage carcinogenesis that identifies distinct stem-cell states at different stages of tumor progression, thereby identifying networks involved in lineage plasticity, drug resistance, and immune surveillance, providing a rich source of potential targets for cancer therapy.

One-Sentence Summary

Genes act in networks to drive cancer, and we identify these groups of genes from bulk-tissue and trace them at single-cell resolution.
The dynamic hypoosmotic response ofVibrio choleraerelies on the mechanosensitive channel MscS
Authors: Ramsey Kristen , Britt Madolyn , Maramba Joseph , Ushijima Blake , Moller Elissa , Anishkin Andriy , Häse Claudia , Sukharev Sergei
Published: May 2023

Like other intestinal bacteria, the facultative pathogenVibrio choleraeadapts to a wide range of osmotic environments. Under drastic osmotic down-shifts,Vibrioavoids mechanical rupture by rapidly releasing excessive metabolites through mechanosensitive (MS) channels that belong to two major types, low-threshold MscS and high-threshold MscL. To investigate each channel’s individual contribution toV. cholerae’sosmotic permeability response, we generated individualΔmscS, ΔmscL, and doubleΔmscL ΔmscSmutants inV. choleraeO395 and characterized their tension-dependent activation in patch-clamp experiments, as well as their millisecond-scale osmolyte release kinetics using a stopped-flow light scattering technique. We additionally generated numerical models reflecting the kinetic competition of osmolyte release with water influx. Both mutants lacking MscS exhibited delayed osmolyte release kinetics and decreased osmotic survival rates compared to WT. TheΔmscLmutant showed comparable release kinetics to WT, but a higher osmotic survival, while ΔmscShad low survival, comparable to the doubleΔmscLΔmscSmutant. By analyzing release kinetics following rapid medium dilution, we illustrate the sequence of events and define the set of parameters that characterize discrete phases of the osmotic response. Osmotic survival rates are directly correlated to the extent and duration of cell swelling, the rate of osmolyte release and the onset time, and the completeness of the post-shock membrane resealing. Not only do the two channels interact functionally during the resealing phase, but there is also a compensatory up-regulation of MscS in theΔmscLstrain suggesting some transcriptional crosstalk. The data reveal the advantage of the low-threshold MscS channel in curbing tension surges, without which MscL becomes toxic, and the role of MscS in the proper termination of the osmotic permeability response inVibrio.
Dynamics of Single-Base Editing: Theoretical Analysis
Authors: Vardanyan Vardan Hoviki , Wang Qian , Kolomeisky Anatoly B.
Published: May 2023

Recent experimental advances led to the development of DNA base editors (BEs) with a single-nucleotide precision that is critical for future progress in various scientific and technological fields. The molecular mechanisms of single-base discrimination, however, remain not well understood. Using a recently developed stochastic approach, we theoretically investigated the dynamics of single-base editing. More specifically, transient and mean times to edit “TC” motifs by cytosine BEs are explicitly evaluated for correct (target) and incorrect (bystander) locations on DNA. In addition, the effect of mutations on the dynamics of the single-base edition is also analyzed. It is found that for most ranges of parameters, it is possible to temporarily separate target and bystander products of base editing, supporting the idea of dynamic selectivity as a method of improving the precision of single-base editing. We conclude that to improve the efficiency of single-base editing, selecting the probability or selecting the time requires different strategies. Physical-chemical arguments to explain the observed dynamic properties are presented. The theoretical analysis clarifies some important aspects of molecular mechanisms of selective base editing.
MscS inactivation and recovery are slow voltage-dependent processes sensitive to interactions with lipids
Authors: Britt Madolyn , Moller Elissa , Maramba Joseph , Anishkin Andriy , Sukharev Sergei
Published: May 2023

Mechanosensitive channel MscS, the major bacterial osmolyte release valve, shows a characteristic adaptive behavior. With a sharp onset of activating tension, the channel population readily opens, but under prolonged action of moderate near-threshold tension, it inactivates. The inactivated state is non-conductive and tension-insensitive, which suggests that the gate gets uncoupled from the lipid-facing domains. The kinetic rates for tension-driven opening-closing transitions are 4-6 orders of magnitude higher than the rates for inactivation and recovery. Here we show that inactivation is augmented and recovery is slowed down by depolarization. Hyperpolarization, conversely, impedes inactivation and speeds up recovery. We then address the question of whether protein-lipid interactions may set the rates and influence voltage dependence of inactivation and recovery. Mutations of conserved arginines 46 and 74 anchoring the lipid-facing helices to the inner membrane leaflet to tryptophans do not change the closing transitions, but instead change the kinetics of both inactivation and recovery and essentially eliminate their voltage-dependence. Uncharged polar substitutions (S or Q) for these anchors produce functional channels but increase the inactivation and reduce the recovery rates. The data suggest that it is not the activation and closing transitions, but rather the inactivation and recovery pathways that involve substantial rearrangements of the protein-lipid boundary associated with the separation of the lipid-facing helices from the gate. The discovery that hyperpolarization robustly assists MscS recovery indicates that membrane potential can regulate osmolyte release valves by putting them either on the ‘ready’ or ‘standby’ mode depending on the cell’s metabolic state.
STUSC: selection tests under size change
Authors: Wooding Stephen
Published: May 2023

Natural selection leaves signatures in genetic diversity. A challenge in detecting these signatures is that demographic history can shape genetic variation in ways similar to selection, making their effects difficult to disentangle. STUSC takes a simulation based approach to the problem. It performs five widely used tests for natural selection, Tajima’s D, Fu and Li’s F and F*, and Fu and Li’s D and D*, which ordinarily require the assumption of constant population size, under any size history. It also provides methods for generating their statistical distributions, allowing their responses to demography to be studied and past results to be evaluated.

Availability and implementation

STUSC is written in Java, and is freely available at the author’s website,woodinglab.org/stusc

Contact

swooding@ucmerced.edu