bluuebunny/crossref_metadata_2025 huggingface dataset:
Kinase regulators evolved into two families by gain and loss of ability to bind plant steroid receptors
Authors: Wei Qiang , Liu Jing , Guo Feimei , Wang Zhuxia , Zhang Xinzhen , Yuan Lei , Ali Khawar , Qiang Fanqi , Wen Yueming , Li Wenjuan , Zheng Bowen , Bai Qunwei , Li Guishuang , Ren Hongyan , Wu Guang
Published: December 2022

All biological functions evolve by fixing beneficial mutations and removing deleterious ones. Therefore, continuously fixing and removing the same essential function to separately diverge monophyletic gene families sounds improbable. Yet, here we report that brassinosteroid insensitive1 kinase inhibitor1 (BKI1)/membrane-associated kinase regulators (MAKRs) regulating a diverse function evolved into BKI1 and MAKR families from a common ancestor by respectively enhancing and losing ability to bind brassinosteroid receptor brassinosteroid insensitive1 (BRI1). The BKI1 family includes BKI1, MAKR1/BKI1-like (BKL) 1, and BKL2, while the MAKR family contains MAKR2-6. Seedless plants contain only BKL2. In seed plants, MAKR1/BKL1 and MAKR3, duplicates of BKL2, gained and lost the ability to bind BRI1, respectively. In angiosperms, BKL2 lost the ability to bind BRI1 to generate MAKR2, while BKI1 and MAKR6 were duplicates of MAKR1/BKL1 and MAKR3, respectively. In dicots, MAKR4 and MAKR5 were duplicates of MAKR3 and MAKR2, respectively. Importantly, BKI1 localized in the plasma membrane, but BKL2 localized to the nuclei while MAKR1/BKL1 localized throughout the whole cell. Importantly, BKI1 strongly and MAKR1/BKL1 weakly inhibited plant growth, but BKL2 and the MAKR family did not inhibit plant growth. Functional study of the chimeras of their N- and C-termini showed that only the BKI1 family was partially reconstructable, supporting stepwise evolution by a seesaw mechanism between their C- and N-termini to alternately gain an ability to bind and inhibit BRI1, respectively. Nevertheless, the C-terminal BRI1-interacting motif best defines the divergence of BKI1/MAKRs. Therefore, BKI1 and MAKR families evolved by gradually gaining and losing the same function, respectively, extremizing divergent evolution and adding insights into gene (BKI1/MAKR) duplication and divergence.
The double flower variant of yellowhorn is due to a LINE1 transposon-mediated insertion
Authors: Wang Hanhui , Lu Yanan , Zhang Tianxu , Liu Zhi , Cao Li , Chang Qiaoying , Liu Yueying , Lu Xin , Yu Song , Li Huiyu , Jiang Jing , Liu Guifeng , Sederoff Heike W , Sederoff Ronald R , Zhang Qingzhu , Zheng Zhimin
Published: December 2022

As essential organs of reproduction in angiosperms, flowers, and the genetic mechanisms of their development have been well characterized in many plant species but not in the woody tree yellowhorn (Xanthoceras sorbifolium). Here, we focused on the double flower phenotype in yellowhorn, which has high ornamental value. We found a candidate C-class gene, AGAMOUS1 (XsAG1), through Bulked Segregant Analysis (BSA) sequencing and genetics analysis with a Long Interpersed Nuclear Elements 1 (LINE1) transposable element fragment (Xsag1-LINE1-1) inserted into its second intron that caused a loss-of-C-function and therefore the double flower phenotype. In situ hybridization of XsAG1 and analysis of the expression levels of other ABC genes were used to identify differences between single- and double-flower development processes. These findings enrich our understanding of double flower formation in yellowhorn and provide evidence that transposon insertions into genes can reshape plant traits in forest trees.
Pharmacological potentiators of the calcium signaling cascade identified by high-throughput screening
Authors: Genovese Michele , Guidone Daniela , Buccirossi Martina , Borrelli Anna , Rodriguez-Gimeno Alejandra , Bertozzi Fabio , Bandiera Tiziano , Galietta Luis J V
Published: December 2022

Pharmacological modulators of the Ca2+ signaling cascade are important research tools and may translate into novel therapeutic strategies for a series of human diseases. We carried out a screening of a maximally diverse chemical library using the Ca2+-sensitive Cl− channel TMEM16A as a functional readout. We found compounds that were able to potentiate UTP-dependent TMEM16A activation. Mechanism of action of these compounds was investigated by a panel of assays that looked at intracellular Ca2+ mobilization triggered by extracellular agonists or by caged-IP3 photolysis, PIP2 breakdown by phospholipase C, and ion channel activity on nuclear membrane. One compound appears as a selective potentiator of inositol triphosphate receptor type 1 (ITPR1) with a possible application for some forms of spinocerebellar ataxia. A second compound is instead a potentiator of the P2RY2 purinergic receptor, an activity that could promote fluid secretion in dry eye and chronic obstructive respiratory diseases.
Risky cascading transitions in international relationships
Authors: Zhang Mingyuan , Chen Shenwen , Du Wenbo , Cao Xianbin , Li Daqing , Zhang Jun , Havlin Shlomo
Published: December 2022

Changing attitudes in diplomatic relations is a common feature of international politics. However, such changes may trigger risky domino-like cascades of “friend-to-enemy” transitions among other counties and yielding catastrophic damage that could reshape the global network of international relationships. While previous attention has been focused on studying single pairs of international relationships, due to the lack of a systematic framework, it remains still unknown whether, and how, a single transition of attitude between two countries could trigger a cascade of attitude transitions among other countries. Here, we develop such a framework and construct a global evolving network of relations between country pairs based on 70,756,728 international events between 1,225 country pairs from January 1995 to March 2020. Our framework can identify and quantify the cascade of transitions following a given original transition. Surprisingly, weaker transitions are found to initiate most of the largest cascades. We also find that transitions are not only related to the balance of the local environment, but also global network properties such as betweenness centrality. Our results suggest that these transitions have a substantial impact on bilateral trade volumes and scientific collaborations. Our results reveal reaction chains of international relations, which could be helpful for designing early warning signals and mitigation methods for global international conflicts.
Paxillin tunes the relationship between cell–matrix and cell–cell adhesions to regulate stiffness-dependent dentinogenesis
Authors: Bai Mingru , Zhang Zhaowei , Chen Huiyu , Liu Xiaoyu , Xie Jing
Published: December 2022

Mechanical stiffness is recognized as a key physical factor and directs cell function via a mechanotransduction process, from extracellular physical cues to intracellular signaling cascades that affect transcriptional activity. Cells continually receive mechanical signals from both the surrounding matrix and adjacent cells. However, how mechanical stiffness cue at cell–substrate interfaces coordinates cell–cell junctions in guiding mesenchymal stem cell behaviors is poorly understood. Here, polydimethylsiloxane substrates with different stiffnesses were used to study mechanosensation/transduction mechanisms in controlling odontogenic differentiation of dental papilla cells (DPCs). DPC phenotypes (morphology and differentiation) changed in response to the applied force derived from stiff substrates. Significantly, higher expression of paxillin on stiffer substrates promoted DPC dentinogenesis. Upon treatment with siRNA to knockdown paxillin, N-cadherin increased mainly in the cytomembrane at the area of cell–cell contacts, whereas β-catenin decreased in the nuclei. The result of a double luciferase reporter assay showed that stiffness promoted β-catenin binding to TCF, which could coactivate the target genes associated with odontogenic differentiation, as evidenced by bioinformatics analysis. Finally, we determined that the addition of a β-catenin inhibitor suppressed DPC mineralization in all the stiffness groups. Thus, our results indicated that a mechanotransduction process from cell–substrate interactions to cell–cell adhesions was required for DPC odontogenic differentiation under the stimulation of substrate stiffness. This finding suggests that stem cell fate specification under the stimulus of stiffness at the substrates is based on crosstalk between substrate interactions and adherens junctions, which provides an essential mechanism for cell-based tissue engineering.
The PICC in Chinese Courts
Authors: Liu Qiao
Published: December 2022

This article offers, for the first time, a comprehensive survey of all accessible (28) Chinese cases in which Chinese judges or lawyers invoked the Unidroit Principles of International Commercial Contracts (PICC) as applicable law or otherwise made a reference to the PICC. The survey has a particular focus on the use of the PICC to interpret or supplement domestic law, which is widely assumed to have no direct impact on the decisions of local courts. Through a detailed analysis that explores the often-times subtle connection between the PICC and judicial reasoning in Chinese courtrooms, the survey rebuts the ‘no direct impact’ thesis and demonstrates and expounds a range of significant roles the PICC may play in this respect. In doing so, this article also illustrates the case-guiding effect of previously little-known case comments—the dominant vehicle by which Chinese judges presently make the above use of the PICC.
Polymorphisms predicting phylogeny in hepatitis B virus
Authors: Lourenço José , McNaughton Anna L , Pley Caitlin , Obolski Uri , Gupta Sunetra , Matthews Philippa C
Published: December 2022

Hepatitis B viruses (HBVs) are compact viruses with circular genomes of ∼3.2 kb in length. Four genes (HBx, Core, Surface, and Polymerase) generating seven products are encoded on overlapping reading frames. Ten HBV genotypes have been characterised (A–J), which may account for differences in transmission, outcomes of infection, and treatment response. However, HBV genotyping is rarely undertaken, and sequencing remains inaccessible in many settings. We set out to assess which amino acid (aa) sites in the HBV genome are most informative for determining genotype, using a machine learning approach based on random forest algorithms (RFA). We downloaded 5,496 genome-length HBV sequences from a public database, excluding recombinant sequences, regions with conserved indels, and genotypes I and J. Each gene was separately translated into aa, and the proteins concatenated into a single sequence (length 1,614 aa). Using RFA, we searched for aa sites predictive of genotype and assessed covariation among the sites with a mutual information–based method. We were able to discriminate confidently between genotypes A–H using ten aa sites. Half of these sites (5/10) sites were identified in Polymerase (Pol), of which 4/5 were in the spacer domain and one in reverse transcriptase. A further 4/10 sites were located in Surface protein and a single site in HBx. There were no informative sites in Core. Properties of the aa were generally not conserved between genotypes at informative sites. Among the highest co-varying pairs of sites, there were fifty-five pairs that included one of these ‘top ten’ sites. Overall, we have shown that RFA analysis is a powerful tool for identifying aa sites that predict the HBV lineage, with an unexpectedly high number of such sites in the spacer domain, which has conventionally been viewed as unimportant for structure or function. Our results improve ease of genotype prediction from limited regions of HBV sequences and may have future applications in understanding HBV evolution.
De NovoVariants inMRTFBhave gain of function activity inDrosophilaand are associated with a novel neurodevelopmental phenotype with dysmorphic features
Authors: Andrews Jonathan C. , Mok Jung-Wan , Kanca Oguz , Jangam Sharayu , Tifft Cynthia , Macnamara Ellen F. , Russell Bianca , Wang Lee-kai ,   Undiagnosed Diseases Network, Nelson Stanley F. , Bellen Hugo J. , Yamamoto Shinya , Malicdan May , Wangler Michael F.
Published: December 2022

Myocardin-Related Transcription Factor B (MRTFB) is an important transcriptional regulator which promotes the activity of an estimated 300 genes during different stages of development. Here we report two pediatric probands withde novovariants inMRTFB(R104G and A91P) and mild dysmorphic features, intellectual disability, global developmental delays, speech apraxia, and impulse control issues. As theMRTFBprotein is highly conserved between vertebrate and invertebrate model organisms, we generated a humanizedDrosophilamodel expressing the humanMRTFBprotein in the same spatial and temporal pattern as the fly gene. Expression of the humanMRTFBR104Gvariant using amrtf-T2A-GAL4line proved to be embryonic lethal. Additional phenotypes were also identified by expressing theMRTFBR104GandMRTFBA91Pvariant in a subset ofDrosophilatissues. Notably, expression within wing tissues resulted in an expansion of intervein tissue, wing vein thickening, shortening or loss of wing veins, and blistering. TheMRTFBR104GandMRTFBA91Pvariants also display a decreased level of actin binding within critical RPEL domains, resulting in increased transcriptional activity and changes in the organization of the Actin cytoskeleton. These changes were not observed in flies expressing two additional candidate variants,MRTFBN95SandMRTFBR109Q, highlighting that the location of the mutation within the 2nd RPEL domain is critical to the pathogenicity of the variant. These changes suggest that theMRTFBR104GandMRTFBA91Palleles we have identified affect the regulation of the protein and that these variants inMRTFBunderly a novel neurodevelopmental disorder.
Integrated Single-Dose Kinome Profiling Data is Predictive of Cancer Cell Line Sensitivity to Kinase Inhibitors
Authors: Joisa Chinmaya U. , Chen Kevin A. , Berginski Matthew E. , Golitz Brian T. , Jenner Madison R. , Herrera Loeza Silvia G. , Yeh Jen Jen , Gomez Shawn M.
Published: December 2022

Protein kinase activity forms the backbone of cellular information transfer, acting both individually and as part of a broader network, the kinome. Correspondingly, their central role in signaling implicates kinome dysfunction as a common driver of cancer, where numerous kinases have been identified as having a causal or modulating role in cancer development and progression. Driven by their importance, the development of therapies targeting kinases has rapidly grown, with over 70 kinase inhibitors approved for use in the clinic and over double this number currently in clinical trials. Given the growing importance of kinase-targeted therapies, linking the relationship between kinase inhibitor treatment and their effects on downstream cellular phenotype is of clear importance for understanding treatment mechanisms and streamlining compound screening in therapy development. In this work, we combine two large-scale kinome profiling data sets and use them to link inhibitor-kinome interactions with cell line treatment responses (AUC/IC50). We then built computational models on this data set that achieve a high degree of prediction accuracy (R2of 0.7 and RMSE of 0.9), and were able to identify a set of well-characterized and understudied kinases that significantly affect cell responses. Further, we validated these models experimentally by testing predicted effects in breast cancer cell lines, and extended the model scope by performing additional validation in patient-derived pancreatic cancer cell lines. Overall, these results demonstrate that broad quantification of kinome inhibition state is highly predictive of downstream cellular phenotypes.
Whole slide image representation in bone marrow cytology
Authors: Mu Youqing , Tizhoosh H.R. , Dehkharghanian Taher , Campbell Clinton JV
Published: December 2022

One of the goals of AI-based computational pathology is to generate compact WSI representations, identifying the essential information required for diagnosis. While such approaches have been applied to histopathology, few applications have been reported in cytology. Bone marrow aspirate cytology is the basis for key clinical decisions in hematology. However, visual inspection of aspirate specimens is a tedious and complex process subject to variation in interpretation, and hematopathology expertise is scarce. The ability to generate a compact representation of an aspirate specimen may form the basis for clinical decision support tools in hematology. We have previously published an end-to-end AI-based system for counting and classifying cells from bone marrow aspirate WSI. Using deep embeddings from this model, we construct bags of individual cell features from each WSI, and apply multiple instance learning to extract vector representations for each WSI. Using these representations in vector search, we achieved 0.58 ± 0.02 mAP@10 in WSI-level image retrieval, which outperforms the Random baseline (0.39 ± 0.1). Using a weighted k-nearest-neighbours (k-NN) model on these slide vectors, we predict five broad diagnostic labels on individual aspirate WSI with a weighted-macro-average F1 score of 0.57 ± 0.03 on the test set of 278 randomly sampled WSIs, which outperforms a classifier using empirical class prior probabilities (0.26 ± 0.02). We present the first example of exploring trainable mechanisms to generate compact, slide-level representations in bone marrow cytology with deep learning. This method has the potential to summarize complex semantic information in WSIs toward improved diagnostics in hematology, and may eventually support AI-assisted computational pathology approaches.
Cell projection plots: a novel visualization of bone marrow aspirate cytology
Authors: Dehkharghanian Taher , Mu Youqing , Ross Catherine , Sur Monalisa , Tizhoosh H.R. , Campbell Clinton JV
Published: December 2022

Deep models for cell detection have demonstrated utility in bone marrow cytology, showing impressive results in terms of accuracy and computational efficiency. However, these models have yet to be implemented in the clinical diagnostic workflow. Additionally, the metrics used to evaluate cell detection models are not necessarily aligned with clinical goals and targets. In order to address these issues, we introduce cell projection plots (CPPs), which are novel, automatically generated visual summaries of bone marrow aspirate specimens. CPPs provide a compact summary of bone marrow aspirate cytology, and encompass relevant biological patterns such as neutrophil maturation. To gauge clinical relevance, CPPs were shown to three hematopathologists, who decided whether shown diagnostic synopses matched with generated CPPs. Pathologists were able to match CPPs to the correct synopsis with 85% accuracy. Our finding suggests CPPs can compactly represent clinically relevant information from bone marrow aspirate specimens, and may be used to efficiently summarize bone marrow cytology to pathologists. CPP could be a step toward human-centered implementation of artificial intelligence (AI) in hematopathology, and a basis for a diagnostic support tool for digital pathology workflows.
Inhibition of LATS Kinases in Ovarian Cancer Activates Cyclin D1/CDK4 and Decreases DYRK1A Activity
Authors: Sesay Fatmata , Saini Siddharth , Pajimola Angel H , Witt Austin , Hu Bin , Koblinski Jennifer , Litovchick Larisa
Published: December 2022

The controlled division of cells requires a coordination of multiple cellular pathways. Hippo pathway controls the organ size and restricts cell proliferation in response to the signals from cell surface receptors, and genetic alterations in the components of this pathway are common in cancer. LATS1 and LATS2 are homologous protein kinases that relay the signals from the environment to the Hippo effector YAP by direct phosphorylation that promotes its degradation. The genes encoding these kinases undergo frequent genetic losses in human cancers, with particularly high rates in high grade serous ovarian carcinoma (HGSOC), a highly lethal cancer with poorly understood mechanisms of pathogenesis and progression. We hypothesized that loss of LATS kinases could be a driver in this cancer and investigated signaling pathways downstream of LATS that could influence the ovarian cancer tumorigenic phenotypes. Depletion of both LATS1 and LATS2 was required to increase cell proliferation and disrupt the assembly of the cell-cycle regulatory DREAM complex. LATS-depleted human ovarian cancer cells formed bigger tumors in the immunocompromised mice, consistent with their tumor suppressor role. DREAM assembly depends on the activity of DYRK1A protein kinase, which was decreased in the LATS1/2-depleted cells. Furthermore, loss of LATS kinases increased the inhibitory phosphorylation of the retinoblastoma (Rb) family proteins, further promoting the DREAM disassembly that was rescued by CDK4 inhibitor palbociclib. Our study describes a crosstalk between the Hippo pathway and the cell cycle regulatory machinery converging on cyclin D1, a major regulator of the Rb tumor suppressor family, and highlights cellular pathways that could contribute to ovarian cancer pathogenesis and progression.
Discovery and biological evaluation of a potent small molecule CRM1 inhibitor for its selective ablation of extranodal NK/T cell lymphoma
Authors: Liu He , Liu Meishuo , Tian Xibao , Wang Haina , Gao Jiujiao , Li Hanrui , Zhao Zhehuan , Liu Yu , Liu Caigang , Chen Xuan , Yang Yongliang
Published: December 2022

Background

The overactivation of NF-κB signaling is a key hallmark for the pathogenesis of extranodal natural killer/T cell lymphoma (ENKTL), a very aggressive subtype of non-Hodgkin’s lymphoma yet with rather limited control strategies. Previously, we found that the dysregulated exportin-1 (also known as CRM1) is mainly responsible for tumor cells to evade apoptosis and promote tumor-associated pathways such as NF-κB signaling.

Methods

Herein we reported the discovery and biological evaluation of a potent small molecule CRM1 inhibitor, LFS-1107. We validated that CRM1 is a major cellular target of LFS-1107 by biolayer interferometry assay (BLI) and the knockdown of CRM1 conferred tumor cells with resistance to LFS-1107.

Results

We found that LFS-1107 can strongly suppresses the growth of ENKTL cells at low-range nanomolar concentration yet with minimal effects on human platelets and healthy peripheral blood mononuclear cells. Treatment of ENKTL cells with LFS-1107 resulted in the nuclear retention of IkBαand consequent strong suppression of NF-κB transcriptional activities, NF-κB target genes downregulation and attenuated tumor cell growth and proliferation. Furthermore, LFS-1107 exhibited potent activities when administered to immunodeficient mice engrafted with human ENKTL cells.

Conclusions

Therefore, LFS-1107 holds great promise for the treatment of ENKTL and may warrant translation for use in clinical trials.
Farmer’s perspectives of rodent pests’ damage and management practices in Wenchi highlands, central Ethiopia
Authors: Legese Kabeta , Bekele Afework
Published: December 2022

A study was conducted to obtain information about the knowledge, attitudes and practices (KAP) of farmers in Wenchi highlands on rodent damage and their management practices. Farmers (n=395) from four highland villages of Wenchi District were randomly selected and interviewed using a semi-structured questionnaire. Rodents were identified as major pests, and perceived negatively among farmers. There were significant variations in the type of damage (χ2=112.698, df= 3, p < 0.05) and crop types susceptibility to rodent pest attack (χ2= 143.26, df = 3, P < 0.05). Crop damage (38.7%) and damage to human properties (27.9%) were the two dominant rodent related problems in the area. Barley was the most susceptible crop to rodent attack (57.5%). The occurrence of frequency of rodent pests and crop damage between the cropping stages also varied significantly. Most damage on barley crop (42.5%) occurred during the maturation stage. Farmers assessed and detected rodents damage by observing damaged seeds, damaged stores and rodent droppings in the storage, and stem cut of standing crops in the crop fields. None of the farmers have employed any management strategy in barley crop fields stating that this is practically impossible. In storage, farmers mainly use cats (53.73%) and trapping (22.64%) to control rodents. Detailed off-field rodent damage assessment, and community education for rodent management are recommended.
Is niche divergence more likely in parapatry? A test inSclerurus mexicanussensu lato (Aves: Furnariidae)
Authors: Cooper Jacob C. , Barragán Diego
Published: December 2022

Aim

While species’ niches are understood to diverge through time, the mode of these divergences is not fully understood. The null hypothesis of niche divergence in the present is that of conservatism; that species are likely to occur in the same environment as their ancestors and, therefore, as allopatric sister species. Alternatively, species are expected to diverge when selective pressure, such as parapatry with a congener, occurs. Here, we analyse niche divergence in a mosaic of allo- and parapatricSclerurus mexicanussensu lato populations to determine if niche divergence is more likely in parapatry.

Location

Neotropics.

Methods

We created a dataset of 1,100 vetted localities forS. mexicanussensu lato, and assigned each point to each of the seven described populations. We created individual dispersal areas for each species in Maxent following: 1) a broad approach in which training areas where allowed to overlap with parapatric congeners; and 2) a narrow approach in which species dispersal areas adhered to strict parapatry and there was no overlap in training areas. We complemented these ENMs with ‘random’ models drawn from points within each training area, thus creating ‘null’ ENMs against which we could test niche divergence using the metric Schoener’s D.

Results

There was no significant difference in the performance of broad and narrow training areas. Few significant divergences were found, and all of those that were found consisted of allopatric populations. Partial divergences were frequently recovered when comparing parapatric taxa.

Main conclusions

In contrast to our expectation, we found no significant evidence for increased niche divergence in parapatric versus allopatric species. Possible explanations for these findings include true conservatism even among parapatric lineages (e.g., additional environmental or biological factors may delimit distributions) or artefactual errors inherent to model creation. We discuss the implications of these findings, and discuss ways to improve upon tests of niche divergence in the future, especially when dealing with cases of parapatry.
The Role of 1-O-Acylceramide NP in Structural Organization and Permeability of the Stratum Corneum Lipid Matrix
Authors: Yang Moon Young , Lee Eun Ok , Park Chang Seo , Nam Yoon Sung
Published: December 2022

The extracellular lipid matrix in the stratum corneum (SC) is crucial for generating a skin barrier (permeability) function. The lipid matrix contains three major components; ceramides, cholesterol, and free fatty acids. The broad diversity of ceramides depends on their molecular structures (e.g., hydroxylations and chain lengths) and plays a critical role in maintaining the structural integrity of the lipid matrix. Although recent studies identified a new subclass of ceramide, 1-O-acylceramide NP (CerENP), its precise role in the lipid matrix of SC is still elusive. Herein, we investigate the role of CerENP on the structure and permeability of the SC by molecular dynamics simulations. Our results suggest that the CerENP molecules induce a denser lipid matrix in the lateral dimension in the long periodicity phase model with a bilayer-slab- bilayer structure. Moreover, ethanol permeability analysis indicates that CerENP can suppress molecular permeability through the lipid matrix. This study provides insight into the role of a new subclass of ceramide in the SC, which can lead to our better understanding of skin organization and disease-related barrier dysfunction.
pH - responsive, reversible A-motif based DNA hydrogels: synthesis and biosensing applications
Authors: Morya Vinod , Shukla Ashish Kumar , Ghoroi Chinmay , Bhatia Dhiraj
Published: December 2022

Functional DNA hydrogels using various motifs and functional groups require perfect sequence designing to avoid cross-bonding interference with self or other structural sequences. The present work reports an A-motif functional DNA hydrogel that does not require any sequence design. A-motif DNA is a non-canonical parallel DNA duplex structure comprises homopolymeric deoxyadenosines (poly-dA) strands that undergo conformational changes from single strands at neutral pH to a parallel duplex DNA helix at acidic pH. Despite many advantages over other DNA motifs like no sequence, design is required and no cross-bonding interference with other structural sequences, A-motif has not been explored much. We successfully synthesized DNA hydrogel utilizing A-motif as a reversible handle to polymerize DNA three-way junction (3WJ). The composed A-motif hydrogel was first characterized by EMSA, & DLS, which shows the formation of higher-order structures. Further, we utilized imaging techniques like atomic force microscopy (AFM) and scanning electron microscope (SEM) validating its hydrogel like highly branched morphology. pH-induced conformational transformation from monomers to gel is quick and reversible, and was analysed for multiple acid-base cycles. The sol-to-gel transitions and gelation properties is further examined using rheological studies. The use of A-motif hydrogel in the visual detection of pathogenic target nucleic acid sequence is demonstrated for the first time using the capillary assay. Moreover, the pH-induced hydrogel formation is observedin-situas a layer over the mammalian cells. The proposed A-motif DNA scaffold has enormous potential in designing stimuli-responsive nanostructures that can be utilized for many biological applications.
Baseline Acute Myeloid Leukemia Prognosis Models using Transcriptomic and Clinical Profiles by Studying the Impacts of Dimensionality Reductions and Gene Signatures on Cox-Proportional Hazard
Authors: Sauvé Léonard , Hébert Josée , Sauvageau Guy , Lemieux Sébastien
Published: December 2022

Gene marker extraction to evaluate risk in cancer can refine the diagnosis process and lead to adapted therapies and better survival. These survival analyses can be done through computer systems and Machine Learning (ML) algorithms such as the Cox-Proportional-Hazard model from gene expression (GE) RNA-Seq data. However, optimal tuning of CPH from genome-wide GE data is challenging and poorly assessed so far. In this work we propose to interrogate an Acute Myeloid Leukemia (AML) dataset (Leucegene) to derive key components of the CPH driving down its performance and discovering its sensitivity to various factors in hoping to ameliorate the system. In this study, we compare the projection and selection data reduction techniques, mainly the PCA and LSC17 gene signature in combination with the CPH in a ML framework. Results reveals that CPH performs better with a combination of clinical and genetic expression features. We determine that projections performs better than selections without clinical information. We ascertain that CPH is affected by overfitting and that this overfitting is linked to the number and the content of input covariables. We show that PCA links clinical features via ability to learn from the input data directly and generalizes better than LSC17 on Leucegene. We postulate that projection are preferred than selection on harder task such as assessing risk in the intermediate subset of Leucegene. We extrapolate that these findings apply in the more general context of risk detection via machine learning in cancer. We see that higher capacity models such as CPH-DNNs systems can be improved via survival-derived projections and combat overfitting through heavy regularization.

Author summary

This study aims to investigate the feasibility of using gene expression to evaluate risk in cancer, and to compare the projection and selection data reduction techniques. The study used the Leucegene dataset to compare the PCA method and a previously published 17 genes signature in combination with the Cox-Proportional-Hazard model in a machine learning framework. Results showed that CPH was affected by overfitting and that this overfitting was linked to the number and the content of input covariables. The study found that PCA links clinical features via ability to learn from the input data directly and generalizes better than LSC17 on Leucegene. The study concluded that projections are preferred than selection on harder task such as assessing risk in the intermediate subset of Leucegene and can be tuned to improve their performance.

Data availability statement

Source code for pipelines and algorithms, as well as gene expression matrices, are available here:https://github.com/lemieux-lab/dimensions_coxph. Access to the Leucegene cohort’s survival times can be granted upon request and following ethical review.
Improving prediction of drug-target interactions based on fusing multiple features with data balancing and feature selection techniques
Authors: Khojasteh Hakimeh , Pirgazi Jamshid
Published: December 2022

Predicting drug-target interaction (DTI) is an important research area in the field of drug discovery. It means identifying the interaction between chemical compounds and protein targets. Wet lab experiments to explore these interactions are expensive as well as time-consuming. On the contrary, a dry lab environment focusing more on computational methods of interaction prediction can be helpful to limit the search space for the wet lab experiments and give clues before developing a new medicine. This paper proposes a novel drug-target interaction prediction method called SRX-DTI. First, we extract various descriptors from protein sequences, and the drug is encoded as FP2 fingerprint. Besides, we present the One-SVM-US technique to deal with imbalanced data. We also developed the FFS-RF algorithm, a forward feature selection algorithm, and coupled it with a random forest (RF) classifier to maximize the predictive performance. This feature selection algorithm removes the irrelevant features to obtain the best optimal features. Finally, the balanced dataset with optimal features is given to the XGBoost classifier to identify DTIs. The experimental results demonstrate that our proposed approach SRX-DTI achieves significantly higher performance than other existing methods in predicting DTIs. The experimental results demonstrate that our proposed approach SRX-DTI achieves significantly higher performance than other existing methods in predicting DTIs. The datasets and source code are available at:https://github.com/Khojasteh-hb/SRX-DTI.
DNA damage-induced lncRNA MEG9 impacts angiogenesis
Authors: Fraile-Bethencourt Eugenia , Khou Sokchea , Wilson RaeAnna , Baris Adrian , Ruhl Rebecca , Espinosa-Diez Cristina , Anand Sudarshan
Published: December 2022

Endothelial cells are highly responsive to environmental changes that allow them to adapt to intrinsic and extrinsic stimuli and switch their transcriptome accordingly to go back to vascular homeostasis. Our previous data demonstrated that small non-coding-RNAs respond quickly to genotoxic stressors and determined endothelial cell fate and DNA damage response. To further understand the contribution of non-coding-RNAs, we profiled differentially expressed long non-coding RNAs in response to genotoxic stress and compared them to pro-angiogenic growth factor signaling. We identified the Maternally expressed gene 9 (MEG9) as a cytoprotective lncRNA in the endothelium. Gain and Loss-of-function studies indicate that MEG9 prevents endothelial cells from cell death, suggesting that MEG9 responses to genotoxic stress can be an adaptive and protective mechanism. Consistent with this phenotype, the knockdown of MEG9 decreases growth factor-dependent angiogenesis in a 3D fibrin gel angiogenesis assay. Deletion of the MEG9 ortholog, Mirg, in mice results in increased vascular leak in Matrigel plugs and a sex and age-dependent decrease in platelets. Mechanistically, we observed that both MEG9 knockdown in vitro andMirg-deleted mice in vivo activated common pathways, including apoptosis, clotting, and inflammation. Indeed, the proinflammatory adhesion molecule ICAM1 was significantly increased in human and mouse endothelial cells in a MEG9-dependent manner, supporting the increased vascular permeability observed on MEG9 deficient cells. Taken together, our findings illustrate how genotoxic stress responses through dynamic modulation of lncRNAs, such as MEG9, trigger adaptive mechanisms to maintain endothelial function, while loss of these molecules contributes to maladaptive responses and endothelial cell dysfunction.
TWAS coupled with eQTL analysis reveals the genetic connection between gene expression and flowering time in Arabidopsis
Authors: Chien Pei-Shan , Chen Pin-Hua , Lee Cheng-Ruei , Chiou Tzyy-Jen
Published: December 2022

Genome-wide association study (GWAS) has improved our understanding of complex traits, but challenges exist in distinguishing causation versus association caused by linkage disequilibrium. Instead, the transcriptome-wide association study (TWAS) detects direct associations between expression levels and phenotypic variations, providing an opportunity to better prioritize candidate genes. To assess the feasibility of TWAS, we investigated the association among transcriptomes, genomes, and various traits, including flowering time inArabidopsis. First, the associated genes formerly known to regulate growth allometry or metabolite production were identified by TWAS. Then, for flowering time, six TWAS-newly identified genes were functionally validated. Analysis of expression quantitative trait locus (eQTL) further revealed atrans-regulatory hotspot affecting the expression of several TWAS-identified genes. The hotspot covers theFRIGIDA(FRI) gene body, which possesses multiple haplotypes differentially affecting the expression of downstream genes, such asFLOWERING LOCUS C(FLC) andSUPPRESSOR OF OVEREXPRESSION OF CO 1(SOC1). We also revealed multiple independent paths towards the loss ofFRIfunction in natural accessions. Altogether, this study demonstrates the potential of combining TWAS with eQTL analysis to identify important regulatory modules of theFRI-FLC-SOC1for quantitative traits in natural populations.

Highlight

Combining TWAS with eQTL analyses identifies haplotypes connecting flowering genes with their physiological trait, strengthening the importance ofFRI-FLC-SOC1regulatory module on flowering time among the Arabidopsis natural population.
Reactive myelopoiesis and FX-expressing monocyte-derived macrophages triggered by chemotherapy promote cancer lung metastasis
Authors: Wu Caijun , Zhong Qian , Shrestha Rejeena , Wang Jingzhi , Hu Xiaoling , Li Hong , Rouchka Eric C. , Yan Jun , Ding Chuanlin
Published: December 2022

Chemotherapy offers long-term clinical benefits to many cancer patients. However, several pre-clinical studies have demonstrated that certain cytotoxic drugs enhance metastasis via multiple mechanisms. These studies have mainly focused on tumor cell-derived inflammation. The importance of host responses triggered by chemotherapy in regulating cancer metastasis has not been fully explored. Here, we showed that multi-dose Gemcitabine (GEM) treatment promoted breast cancer lung metastasis in a transgenic spontaneous breast cancer animal model. Both CCR2+macrophages and monocytes were increased in the lungs of GEM-treated mice. Further, the increase of CCR2+macrophages and monocytes were observed in naïve (tumor-free) mice after GEM treatment. These changes were largely caused by chemotherapy-induced reactive myelopoiesis that are biased toward monocyte development. Mechanistically, enhanced production of mitochondrial ROS (mtROS) was observed in GEM-treated BM LSK cells and monocytes. Treatment with the mitochondrial targeted antioxidant abrogated GEM induced hyper differentiation of BM progenitors. In addition, GEM treatment induced up-regulation of host cell-derived CCL2, and CCL2/CCR2 axis played essential role in the pro-metastatic host response induced by chemotherapy. Further, GEM and Paclitaxel (PTX) in combination with Doxorubicin (DOX) treatment resulted in up-regulation of coagulation factor X (FX) in lung interstitial macrophages. Targeting activated FX (FXa) using FXa inhibitor or F10 gene knockdown reduced pro-metastatic effect of chemotherapy-triggered host response. Together, these studies suggest a novel mechanism for chemotherapy induced metastasis via the host response-induced accumulation of monocytes/macrophages and interplay between coagulation and inflammation in the lungs.
scEvoNet: a gradient boosting-based method for prediction of cell state evolution
Authors: Kotov Aleksandr , Zinovyev Andrei , Monsoro-Burq Anne-Helene
Published: December 2022

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Background

Exploring the function or the developmental history of cells in various organisms provides insights into a given cell type’s core molecular characteristics and putative evolutionary mechanisms. Numerous computational methods now exist for analyzing single-cell data and identifying cell states. These methods mostly rely on the expression of genes considered as markers for a given cell state. Yet, there is a lack of scRNA-seq computational tools to study the evolution of cell states, particularly how cell states change their molecular profiles. This can include novel gene activation or the novel deployment of programs already existing in other cell types, known as co-option.

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Results

Here we present scEvoNet, a Python tool for predicting cell type evolution in crossspecies or cancer-related scRNA-seq datasets. ScEvoNet builds the confusion matrix of cell states and a bipartite network connecting genes and cell states. It allows a user to obtain a set of genes shared by the characteristic signature of two cell states even between distantly-related datasets. These genes can be used as indicators of either evolutionary divergence or co-option occurring during organism or tumor evolution. Our results on cancer and developmental datasets indicate that scEvoNet is a helpful tool for the initial screening of such genes as well as for measuring cell state similarities.

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Conclusions

The scEvoNet package is implemented in Python and is freely available fromhttps://github.com/monsoro/scEvoNet. Utilizing this framework and exploring the continuum of transcriptome states between developmental stages and species will help explain cell state dynamics.
Genome comparison reveals inversions and alternative evolutionary history of nutritional endosymbionts in planthoppers (Hemiptera: Fulgoromorpha)
Authors: Deng Junchen , Bennett Gordon M. , Franco Diego C. , Prus-Frankowska Monika , Stroiński Adam , Michalik Anna , Łukasik Piotr
Published: December 2022

The evolutionary success of sap-feeding hemipteran insects in the suborder Auchenorrhyncha was enabled by nutritional contributions from their heritable endosymbiotic bacteria. However, the symbiont diversity, functions, and evolutionary origins in this large insect group have not been broadly characterized using genomic tools. In particular, the origins and relationships among ancient betaproteobacterial symbiontsVidania(in Fulgoromorpha) andNasuia/Zinderia(in Cicadomorpha) are uncertain. Here, we characterized the genomes ofVidaniaandSulciafrom threePyropsplanthoppers (family Fulgoridae) to understand their metabolic functions and evolutionary histories. Like in previously characterized planthoppers, these symbionts share nutritional responsibilities, withVidaniaproviding seven out of ten essential amino acids.Sulcialineages across the Auchenorrhyncha have a highly conserved genome but with multiple independent rearrangements occurring in an early ancestor of Cicadomorpha or Fulgoromorpha and in a few succeeding lineages. Genomic synteny was also observed within each of the betaproteobacterial symbiont generaNasuia,Zinderia, andVidania, but not across them, which challenges the expectation of a shared ancestry for these symbionts. The further comparison of other biological traits strongly suggests an independent origin ofVidaniaearly in the planthopper evolution and possibly ofNasuiaandZinderiain their respective host lineages.

Originality-Significance Statement

We sequenced and characterized the genomes of two ancient nutritional symbionts,SulciaandVidania, in three species from the genusPyropsin the species- and symbiont-rich but understudied insect clade, Fulgoromorpha (planthoppers). We describe—for the first time—several independent genome rearrangements inSulcia, which is often cited as a premier example of extreme genome stability spanning hundreds of millions of years. We also show a global lack of synteny across the genomes of the Auchenorrhynchan betaproteobacterial symbionts (Vidania,Nasuia, andZinderia). This result is unexpected given previous hypotheses of a common origin for these symbionts >250 million years ago alongsideSulcia. Taken together, we suggest an independent origin ofVidaniaand possibly ofNasuiaandZinderiasymbiont lineages as well. This hypothesis further links the potential acquisition of novel nutritional endosymbiont lineages with the emergence of auchenorrhyncham superfamilies.
TranceptEVE: Combining Family-specific and Family-agnostic Models of Protein Sequences for Improved Fitness Prediction
Authors: Notin Pascal , Van Niekerk Lood , Kollasch Aaron W , Ritter Daniel , Gal Yarin , Marks Debora S.
Published: December 2022

Modeling the fitness landscape of protein sequences has historically relied on training models on family-specific sets of homologous sequences called Multiple Sequence Alignments. Many proteins are however difficult to align or have shallow alignments which limits the potential scope of alignment-based methods. Not subject to these limitations, large protein language models trained on non-aligned sequences across protein families have achieved increasingly high predictive performance – but have not yet fully bridged the gap with their alignment-based counterparts. In this work, we introduce TranceptEVE – a hybrid method between family-specific and family-agnostic models that seeks to build on the relative strengths from each approach. Our method gracefully adapts to the depth of the alignment, fully relying on its autoregressive transformer when dealing with shallow alignments and leaning more heavily on the family-specific models for proteins with deeper alignments. Besides its broader application scope, it achieves state-of-the-art performance for mutation effects prediction, both in terms of correlation with experimental assays and with clinical annotations from ClinVar.