bluuebunny/crossref_metadata_2025 huggingface dataset:
Reconstruction of the cell pseudo-space from single-cell RNA sequencing data with scSpace
Authors: Liao Jie , Qian Jingyang , Liu Ziqi , Chi Ying , Zheng Yanrong , Shao Xin , Cheng Junyun , Cui Yongjin , Guo Wenbo , Yang Penghui , Hu Yining , Bao Hudong , Chen Qian , Li Mingxiao , Zhang Bing , Fan Xiaohui
Published: May 2022

Tissues are highly complicated with spatial heterogeneity in gene expression. However, the cutting-edge single-cell RNA-seq technology eliminates the spatial information of individual cells, which contributes to the characterization of cell identities. Herein, we propose single-cell spatial position associated co-embeddings (scSpace), an integrative algorithm to distinguish spatially variable cell subclusters by reconstructing cells onto a pseudo-space with spatial transcriptome references (Visium, STARmap, Slide-seq, etc.). We demonstrated that scSpace can define biologically meaningful cell subpopulations neglected by single-cell RNA-seq or spatially resolved transcriptomics. The use of scSpace to uncover the spatial association within single-cell data, reproduced, the hierarchical distribution of cells in the brain cortex and liver lobules, and the regional variation of cells in heart ventricles and the intestinal villus. scSpace identified cell subclusters in intratelencephalic neurons, which were confirmed by their biomarkers. The application of scSpace in melanoma and Covid-19 exhibited a broad prospect in the discovery of spatial therapeutic markers.
Limited overlap of eQTLs and GWAS hits due to systematic differences in discovery
Authors: Mostafavi Hakhamanesh , Spence Jeffrey P. , Naqvi Sahin , Pritchard Jonathan K.
Published: May 2022

Most signals in genome-wide association studies (GWAS) of complex traits point to noncoding genetic variants with putative gene regulatory effects. However, currently identified expression quantitative trait loci (eQTLs) explain only a small fraction of GWAS signals. By analyzing GWAS hits for complex traits in the UK Biobank, and cis-eQTLs from the GTEx consortium, we show that these assays systematically discover different types of genes and variants: eQTLs cluster strongly near transcription start sites, while GWAS hits do not. Genes near GWAS hits are enriched in numerous functional annotations, are under strong selective constraint and have a complex regulatory landscape across different tissue/cell types, while genes near eQTLs are depleted of most functional annotations, show relaxed constraint, and have simpler regulatory landscapes. We describe a model to understand these observations, including how natural selection on complex traits hinders discovery of functionally-relevant eQTLs. Our results imply that GWAS and eQTL studies are systematically biased toward different types of variants, and support the use of complementary functional approaches alongside the next generation of eQTL studies.
Chemical structures of cyclic ADP ribose (cADPR) isomers and the molecular basis of their production and signaling
Authors: Manik Mohammad K. , Shi Yun , Li Sulin , Zaydman Mark A. , Damaraju Neha , Eastman Samuel , Smith Thomas G. , Gu Weixi , Masic Veronika , Mosaiab Tamim , Weagley James S. , Hancock Steven J. , Vasquez Eduardo , Hartley-Tassell Lauren , Maruta Natsumi , Lim Bryan Y. J. , Burdett Hayden , Lansdberg Michael J. , Schembri Mark A. , Prokes Ivan , Song Lijiang , Grant Murray , DiAntonio Aaron , Nanson Jeffrey D. , Guo Ming , Milbrandt Jeffrey , Ve Thomas , Kobe Bostjan
Published: May 2022

Cyclic ADP ribose (cADPR) isomers are important signaling molecules produced by bacterial and plant Toll/interleukin-1 receptor (TIR) domains via NAD+ hydrolysis, yet their chemical structures are unknown. We show that v-cADPR (2’cADPR) and v2-cADPR (3’cADPR) isomers are cyclized by O-glycosidic bond formation between the ribose moieties in ADPR. Structures of v-cADPR (2’cADPR)-producing TIR domains reveal that conformational changes are required for the formation of the active assembly that resembles those of Toll-like receptor adaptor TIR domains, and mutagenesis data demonstrate that a conserved tryptophan is essential for cyclization. We show that v2-cADPR (3’cADPR) is a potent activator of ThsA effector proteins from Thoeris anti-phage defence systems and is responsible for suppression of plant immunity by the effector HopAM1. Collectively, our results define new enzymatic activities of TIR domains, reveal the molecular basis of cADPR isomer production, and establish v2-cADPR (3’cADPR) as an antiviral signaling molecule and an effector-mediated signaling molecule for plant immunity suppression.

One-Sentence Summary

The chemical structures of two O-glycosidic bond-containing cyclic ADP ribose isomers, the molecular basis of their production, and their function in antiviral and plant immunity suppression by bacteria are reported.
Dynamic emergence of relational structure network in human brains
Authors: Ren Xiangjuan , Zhang Hang , Luo Huan
Published: May 2022

Reasoning the hidden relational structure from sequences of events is a crucial ability humans possess, which help them to predict the future and make inferences. Besides simple statistical properties, humans also excel in learning more complex relational networks. Several brain regions are engaged in the process, yet the time-resolved neural implementation of relational structure learning and its behavioral relevance remains unknown. Here human subjects performed a probabilistic sequential prediction task on image sequences generated from a transition graph-like network, with their brain activities recorded using electroencephalography (EEG). We demonstrate the emergence of two key aspects of relational knowledge – lower-order transition probability and higher-order community structure, which arise around 840 msec after image onset and well predict behavioral performance. Furthermore, computational modeling suggests that the formed higher-order community structure, i.e., compressed clusters in the network, could be well characterized by a successor representation operation. Overall, human brains are constantly computing the temporal statistical relationship among discrete inputs, based on which new abstract knowledge could be inferred.
Multi-policy models of interregional communication in the human connectome
Authors: Betzel Richard F. , Faskowitz Joshua , Mišić Bratislav , Sporns Olaf , Seguin Caio
Published: May 2022

Network models of communication, e.g. shortest paths, diffusion, navigation, have become useful tools for studying structure-function relationships in the brain. These models generate estimates of communication efficiency between all pairs of brain regions, which can then be linked to the correlation structure of recorded activity, i.e. functional connectivity (FC). At present, however, communication models have a number of limitations, including difficulty adjudicating between models and the absence of a generic framework for modeling multiple interacting communication policies at the regional level. Here, we present a framework that allows us to incorporate multiple region-specific policies and fit them to empirical estimates of FC. Briefly, we show that many communication policies, including shortest paths and greedy navigation, can be modeled as biased random walks, enabling these policies to be incorporated into the same multi-policy communication model alongside unbiased processes, e.g. diffusion. We show that these multi-policy models outperform existing communication measures while yielding neurobiologically interpretable regional preferences. Further, we show that these models explain the majority of variance in time-varying patterns of FC. Collectively, our framework represents an advance in network-based communication models and establishes a strong link between these patterns and FC. Our findings open up many new avenues for future inquiries and present a flexible framework for modeling anatomically-constrained communication.
Pupil size as a robust marker of attentional bias toward nicotine-related stimuli in smokers
Authors: Blini Elvio , Zorzi Marco
Published: May 2022

Spatial attention can be magnetically attracted by behaviorally salient stimuli. This phenomenon occasionally conflicts with behavioral goals, leading to maladaptive consequences, as in the case of addiction, in which attentional biases have been described and linked with clinically meaningful variables, such as craving level or dependence intensity. Here, we sought to probe the markers of attentional priority in smokers through eye-tracking measures, by leveraging the established link between eye movements and spatial attention. We were particularly interested in potential markers related to pupil size, because pupil diameter reflects a range of autonomic, affective, and cognitive/attentional reactions to behaviorally significant stimuli and is a robust marker of appetitive and aversive learning. We found that changes in pupil size to nicotine-related visual stimuli could reliably predict, in crossvalidated logistic regression, the smoking status of young smokers (showing pupil constriction) better than more traditional proxy measures. The possibility that pupil constriction may reflect a bias toward central vision, e.g. attentional capture, is discussed in terms of sensory tuning with respect to nicotine-related stimuli. Pupil size was more sensitive at lower nicotine dependence levels, and at increased abstinence time (though these two variables were collinear). We conclude that pupillometry can provide a robust marker for attentional priority computation and useful indications regarding motivational states and individual attitudes toward conditioned stimuli.
FIB-SEM analysis on three-dimensional structures of growing organelles in wild Chlorella pyrenoidosa cells
Authors: Feng Lingchong , Guo Wangbiao , Guo Jiansheng , Zhang Xing , Zou Xiangbo , Rao Mumin , Ye Ji , Kuang Cao , Chen Gongda , Chen Chuangting , Qin Shiwei , Yang Weijuan , Cheng Jun
Published: May 2022

To clarify dynamic changes of organelle microstructures in Chlorella pyrenoidosa cells during photosynthetic growth with CO2 fixation, three-dimensional organelle microstructures in three growth periods of meristem, elongation and maturity were quantitatively determined and comprehensively reconstructed with focused ion beam scanning electron microscopy (FIB-SEM). The single round-pancake mitochondria in each cell split into a dumbbell and then into a circular ring, while barycenter distance of mitochondria to chloroplast and nucleus was reduced to 45.5% and 88.3% to strengthen energy transfer, respectively. The single pyrenoid consisting of a large part and another small part in each chloroplast gradually developed to a mature state in which the two parts were nearly equal in size. The nucleolus progressively became larger with euchromatin replication. The number of starch grains gradually increased, but average grain volume remained nearly unchanged.
On the limits of fitting complex models of population history to genetic data
Authors: Maier Robert , Flegontov Pavel , Flegontova Olga , Changmai Piya , Reich David
Published: May 2022

Our understanding of human population history in deep time has been assisted by fitting “admixture graphs” to data: models that specify the ordering of population splits and mixtures which is the only information needed to capture the patterns of allele frequency correlation among populations. Not needing to specify population size changes, split times, or whether admixture events were sudden or drawn out simplifies the space of models that need to be searched. However, the space of possible admixture graphs relating populations is vast and cannot be sampled fully, and thus most published studies have identified fitting admixture graphs through a manual process driven by prior hypotheses, leaving the vast majority of alternative models unexplored. Here, we develop a method for systematically searching the space of all admixture graphs that can incorporate non-genetic information in the form of topology constraints. We implement this findGraphs tool within a software package, ADMIXTOOLS 2, which is a reimplementation of the ADMIXTOOLS software with new features and large performance gains. We apply this methodology to identify alternative models to admixture graphs that played key roles in eight published studies and find that graphs modeling more than six populations and two or three admixture events are often not unique, with many alternative models fitting nominally or significantly better than the published one. Our results suggest that strong claims about population history from admixture graphs should only be made when all well-fitting and temporally plausible models share common topological features. Our re-evaluation of published data also provides insight into the population histories of humans, dogs, and horses, identifying features that are stable across the models we explored, as well as scenarios of populations relationships that differ in important ways from models that have been highlighted in the literature, that fit the allele frequency correlation data, and that are not obviously wrong.
Chromosome-scale assembly of the lablab genome - A model for inclusive orphan crop genomics
Authors: Njaci Isaac , Waweru Bernice , Kamal Nadia , Muktar Meki Shehabu , Fisher David , Gundlach Heidrun , Muli Collins , Muthui Lucy , Maranga Mary , Kiambi Davies , Maass Brigitte L , Emmrich Peter MF , Entfellner Jean-Baka Domelevo , Spannagl Manuel , Chapman Mark A , Shorinola Oluwaseyi , Jones Chris S
Published: May 2022

Orphan crops (also described as underutilised and neglected crops) hold the key to diversified and climate-resilient food systems. After decades of neglect, the genome sequencing of orphan crops is gathering pace, providing the foundations for their accelerated domestication and improvement. Recent attention has however turned to the gross under-representation of researchers in Africa in the genome sequencing efforts of their indigenous orphan crops. Here we report a radically inclusive approach to orphan crop genomics using the case of Lablab purpureus (L.) Sweet (syn. Dolichos lablab, or hyacinth bean) – a legume native to Africa and cultivated throughout the tropics for food and forage. Our Africa-led South-North plant genome collaboration produced a high-quality chromosomescale assembly of the lablab genome – the first chromosome-scale plant genome assembly locally sequenced in Africa. We also re-sequenced cultivated and wild accessions of lablab from Africa confirming two domestication events and examined the genetic diversity in lablab germplasm conserved in Africa. Our approach provides a valuable resource for lablab improvement and also presents a model that could be explored by other researchers sequencing indigenous crops particularly from Low and middle income countries (LMIC).
Attention-wise masked graph contrastive learning for predicting molecular property
Authors: Liu Hui , Huang Yibiao , Liu Xuejun , Deng Lei
Published: May 2022

Motivation

Accurate and efficient prediction of the molecular property is one of the fundamental problems in drug research and development. Recent advancements in representation learning have been shown to greatly improve the performance of molecular property prediction. However, due to limited labeled data, supervised learning-based molecular representation algorithms can only search limited chemical space and suffer from poor generalizability.

Results

In this work, we proposed a self-supervised learning method, ATMOL, for molecular representation learning and properties prediction. We developed a novel molecular graph augmentation strategy, referred to as attention-wise graph masking, to generate challenging positive samples for contrastive learning. We adopted the graph attention network (GAT) as the molecular graph encoder, and leveraged the learned attention weights as masking guidance to generate molecular augmentation graphs. By minimization of the contrastive loss between original graph and augmented graph, our model can capture important molecular structure and higher-order semantic information. Extensive experiments showed that our attention-wise graph mask contrastive learning exhibited state-of-the-art performance in a couple of downstream molecular property prediction tasks. We also verified that our model pretrained on larger scale of unlabeled data improved the generalization of learned molecular representation. Moreover, visualization of the attention heatmaps showed meaningful patterns indicative of atoms and atomic groups important to specific molecular property.
Adversarial interspecies relationships facilitate population suppression by gene drive in spatially explicit models
Authors: Liu Yiran , Teo WeiJian , Yang Haochen , Champer Jackson
Published: May 2022

Suppression gene drives are designed to bias their inheritance and increase in frequency in a population, disrupting an essential gene in the process. When the frequency is high enough, the population will be unable to reproduce above the replacement level and could be eliminated. CRISPR suppression drives based on the homing mechanism have already seen success in the laboratory, particularly in malaria mosquitoes. However, several models predict that the use of these drives in realistic populations with spatial structure may not achieve complete success. This is due to the ability of wild-type individuals to escape the drive and reach empty areas with reduced competition, allowing them to achieve high reproductive success and leading to extinction-recolonization cycles across the landscape. Here, we extend our continuous space gene drive framework to include two competing species or predator-prey species pairs. We find that in both general and mosquito-specific models, the presence of a competing species or predator can greatly facilitate drive-based suppression, even for drives with modest efficiency. However, the presence of a competing species also substantially increases the frequency of outcomes in which the drive is lost before suppression is achieved. These results are robust in models with seasonal population fluctuations that mosquito populations often experience. We also found that suppression can be somewhat more difficult if targeting a predator with strong predator-prey interactions. Our results illustrate the difficulty of predicting outcomes of interventions that could substantially affect populations of interacting species in complex ecosystems. However, our results are also potentially promising for the prospects of less powerful suppression gene drives for achieving successful elimination of target mosquito and other pest populations.
m6A epitranscriptomic modification regulates neural progenitor-to-glial cell transition in the retina
Authors: Xin Yanling , He Qinghai , Liang Huilin , Guo Jingyi , Zhong Qi , Zhang Ke , Li Jinyan , Liu Yizhi , Chen Shuyi
Published: May 2022

N6-methyladenosine (m6A) is the most prevalent mRNA internal modification and has been shown to regulate the development, physiology and pathology of various tissues. However, the functions of the m6A epitranscriptome in the visual system remain unclear. In this study, using a retina-specific conditional knockout mouse model, we show that retinas deficient in Mettl3, the core component of the m6A methyltransferase complex, exhibit structural and functional abnormalities beginning at the end of retinogenesis. Immunohistological and scRNA-seq analyses of retinogenesis processes reveal that retinal progenitor cells (RPCs) and Müller glial cells are the two cell types primarily affected by Mettl3 deficiency. Integrative analyses of scRNA-seq and MeRIP-seq data suggest that m6A fine-tunes the transcriptomic transition from RPCs to Müller cells by promoting the degradation of RPC transcripts, the disruption of which leads to abnormalities in late retinogenesis and compromises the glial functions of Müller cells. Finally, overexpression of m6A-regulated RPC-enriched transcripts in late RPCs partially recapitulates the Mettl3-deficient retinal phenotype. Collectively, our study reveals an epitranscriptomic mechanism governing progenitor-to-glial cell transition during late retinogenesis, which is essential for the homeostasis of the mature retina. The mechanism revealed in this study might also apply to other nervous systems.
Single-particle studies of the effects of RNA-protein interactions on the self-assembly of RNA virus particles
Authors: Garmann Rees F. , Goldfain Aaron M. , Tanimoto Cheylene R. , Beren Christian E. , Vasquez Fernando F. , Knobler Charles M. , Gelbart William M. , Manoharan Vinothan N.
Published: May 2022

Understanding the pathways by which simple RNA viruses self-assemble from their coat proteins and RNA is of practical and fundamental interest. Although RNA-protein interactions are thought to play a critical role in the assembly, our understanding of their effects is limited because the assembly process is difficult to observe directly. We address this problem by using interferometric scattering microscopy, a sensitive optical technique with high dynamic range, to follow the in vitro assembly kinetics of over 500 individual particles of brome mosaic virus (BMV)—for which RNA-protein interactions can be controlled by varying the ionic strength of the buffer. We find that when RNA-protein interactions are weak, BMV assembles by a nucleation-and-growth pathway in which a small cluster of RNA-bound proteins must exceed a critical size before additional proteins can bind. As the strength of RNA-protein interactions increases, the nucleation time becomes shorter and more narrowly distributed until the assembly kinetics become indistinguishable from diffusion-limited adsorption. In contrast, the time to grow a capsid after nucleation varies weakly with both salt and protein concentration. These results show that the nucleation rate is controlled by RNA-protein interactions, while the growth process is driven less by RNA-protein interactions and more by protein-protein interactions and intra-protein forces. The nucleated pathway observed with the plant virus BMV is strikingly similar to that previously observed with bacteriophage MS2, a phylogenetically distinct virus with a different host kingdom. These results raise the possibility that nucleated assembly pathways might be common to other RNA viruses.

RNA viruses first inspired the term “self-assembly.” Yet much is still not understood about how even the simplest such viruses assemble or if different viruses assemble in similar ways. Theoretical models suggest many possible assembly pathways, with many different roles for the RNA, but until recently measuring these pathways has not been possible. We use a sensitive microscopy technique to follow the assembly of individual particles of BMV, a plant virus. We find evidence of an RNA-mediated nucleation-and-growth pathway that is strikingly similar to that of MS2, a bacterial virus. The last common ancestor of BMV and MS2 existed only in ancient times, suggesting that their assembly pathway might be evolutionarily conserved and other viruses might follow a similar pathway.
Role of intraluteal and intrauterine prostaglandin signaling in LH-induced luteolysis in pregnant rats
Authors: Vashistha Akshi , Rudraiah Medhamurthy
Published: May 2022

Luteal dysfunctions lead to fertility disorders and pregnancy complications. Normal luteal function is regulated by many factors, including luteinizing hormone (LH). The luteotropic roles of LH have been widely investigated but its role in the process of luteolysis has received little attention. LH has been shown to have luteolytic effects during pregnancy in rats. Stocco et al. have demonstrated the role of intraluteal prostaglandins (PGs) in LH-mediated luteolysis. However, the status of PG signaling in the uterus during LH-mediated luteolysis remains unexplored. In this study, we have examined the effect of LH-mediated luteolysis on luteal and uterine PG synthesis machinery and genes associated with activated luteal PGF2α signalling and uterine activation during different stages (mid and late) of pregnancy. Further, we analysed the effect of overall PG synthesis machinery blockage on LH-mediated luteolysis during late-pregnancy. Unlike the mid-stage of pregnancy, the expression of genes involved in PG synthesis and responsivity in late-stage pregnant rats’ luteal and uterine tissue increase post repeated administration of LH. Since the cAMP/PKA pathway mediates LH-mediated luteolysis, we analyzed the effect of inhibition of endogenous PG synthesis on the cAMP/PKA/CREB pathway, followed by the analysis of the expression of markers of luteolysis. Inhibition of endogenous PG synthesis did not affect the cAMP/PKA/CREB pathway. However, in the absence of endogenous PGs, luteolysis could not be activated to the full extent. Our results suggest that endogenous PGs may contribute to LH-mediated luteolysis, but this dependency on endogenous PGs is pregnancy stage dependent. These findings advance our understanding of the molecular pathways that regulate luteolysis.
Meta-analysis of transcriptomes in insects showing density-dependent polyphenism
Authors: Toga Kouhei , Yokoi Kakeru , Bono Hidemasa
Published: May 2022

With increasing public data, a statistical analysis approach called meta-analysis, which combines transcriptome results obtained from multiple studies, has succeeded in providing novel insights into targeted biological processes. Locusts and aphids are representative of insect groups that exhibit density-dependent plasticity. Although the physiological mechanisms underlying density-dependent polyphenism have been identified in aphids and locusts, the underlying molecular mechanisms remain largely unknown. In this study, we performed a meta-analysis of public transcriptomes to gain additional insights into the molecular underpinning of density-dependent plasticity. We collected RNA sequencing data of aphids and locusts from public databases and detected differentially expressed genes (DEGs) between crowded and isolated conditions. Gene set enrichment analysis was performed to reveal the characteristics of the DEGs. DNA replication (GO:0006260), DNA metabolic processes (GO:0006259), and mitotic cell cycle (GO:0000278) were enriched in response to crowded conditions. To date, these processes have scarcely been the focus of research. The importance of the oxidative stress response and neurological system modifications under isolated conditions has been highlighted. These biological processes, clarified by meta-analysis, are thought to play key roles in the regulation of density-dependent plasticity.

Simple Summary

Population density can be an environmental cue to induce modification of insect morphology, physiology, and behavior. This phenomenon is called density-dependent plasticity. Aphids and locusts exhibit textbook examples of density-dependent plasticity but there is a lack of integrative understanding for insect density-dependent plasticity. To address this problem, we combined public gene expression data obtained from multiple studies and re-analyzed them (this process is called meta-analysis). The present study provides additional insight into the regulatory mechanisms of density-dependent plasticity, demonstrating the effectiveness of meta-analyses of public transcriptomes.
Integrative multi-omics analysis reveals molecular subtypes and tumor evolution of synovial sarcoma
Authors: Chen Yi , Su Yanhong , Leo Isabelle Rose , Siavelis Ioannis , Zeng Jianming , Cao Xiaofang , Tsagkozis Panagiotis , Hesla Asle C , Papakonstantinou Andri , Liu Xiao , Huang Wen-Kuan , Ehnman Monika , Johansson Henrik , Lin Yingbo , Lehtiö Janne , Zhang Yifan , Larsson Olle , Haglund de Flon Felix
Published: May 2022

Synovial sarcomas (SS) are malignant mesenchymal tumors characterized by the SS18-SSX fusion gene, which drives tumorigenesis by altering the composition of the BAF complex. Secondary genomic alterations that determine variations in tumor phenotype or clinical presentation are largely unknown. Herein, we present transcriptome, targeted DNA-sequencing, and proteomics analysis of 91 synovial sarcomas from 55 patients. We identified three SS clusters (SSCs) characterized by distinct histology, tumor microenvironments, genomic complexities, therapeutic effects, and clinical outcomes. Eight BAF complex components are differentially expressed among SSCs, and their role in mesenchymal-epithelial-transition is supported by single cell sequencing. The epithelial cells of biphasic tumors are more susceptible to developing copy number alterations, including amplification of PDCD1 and TMPRSS2. Our findings explain broad concepts in SS biology and imply that the BAF composition at the start of the tumorigenesis (i.e. the cellular linage) may determine the SS subtype, providing a rationale for individualized treatment strategies.
Multi-color live-cell STED nanoscopy of mitochondria with a gentle inner membrane stain
Authors: Liu Tianyan , Stephan Till , Chen Peng , Chen Jingting , Riedel Dietmar , Yang Zhongtian , Jakobs Stefan , Chen Zhixing
Published: May 2022

Capturing mitochondria’s intricate and dynamic structure poses a daunting challenge for optical nanoscopy. Different labeling strategies have been demonstrated for live-cell stimulated emission depletion (STED) microscopy of mitochondria, but orthogonal strategies are yet to be established, and image acquisition has suffered either from photodamage to the organelles or from rapid photobleaching. Therefore, live-cell nanoscopy of mitochondria has been largely restricted to 2D single-color recordings of cancer cells. Here, by conjugation of cyclooctatetraene to a benzo-fused cyanine dye, we report a mitochondrial inner-membrane (IM) fluorescent marker, PK Mito Orange (PKMO), featuring efficient STED at 775 nm, strong photostability and markedly reduced phototoxicity. PKMO enables super-resolution recordings of inner-membrane dynamics for extended periods in immortalized mammalian cell lines, primary cells, and organoids. Photostability and reduced phototoxicity of PKMO open the door to live-cell 3D STED nanoscopy of mitochondria for three-dimensional analysis of the convoluted IM. PKMO is optically orthogonal with green and far-red markers allowing multiplexed recordings of mitochondria using commercial STED microscopes. Using multi-color STED, we demonstrate that imaging with PKMO can capture the sub-mitochondrial localization of proteins, or interactions of mitochondria with different cellular components, such as the ER or the cytoskeleton at sub-100 nm resolution. Thereby, this work offers a versatile tool for studying mitochondrial inner-membrane architecture and dynamics in a multiplexed manner.
The synergistic effects of plants and nitrogen on microbial hitchhiking
Authors: Liu Zhibin , Wang Ziyuan , Xia Qini , Zhou Qin , Wu Xiaobo , Kong Wenqing , Lei Wenyan , Zeng Jiayi , Liu Chao , Wang Yongfeng , Chang Wei , Li Zhi , Yang Yi , Yang Liang , Tan Xiao
Published: May 2022

Microbial hitchhiking demonstrates that some nonmotile microbes utilize trans-species motility to traverse their environment; however, whether driving forces, such as plants and nitrogen, affect microbial hitchhiking is not clear. In our study, we explored the effects of plants and nitrogen fertilizer on Bacillus-hitchhiking by setting filter membranes and different nitrogen fertilizer concentration gradients. In the experimental treatment, we added a filter membrane to the soil to prevent hitchhiking. In the absence of plants, nitrogen alone had little influence on motile bacteria and hitchhiking. However, Bacillus contents were significantly impacted by the nitrogen concentration when the plants were rooted, leading to a great variation in cell motility function according to the functional analysis in the soil microbial community. After applying the filter membrane, there were no significant differences in Bacillus contents, microbial community structure or cell motility functional abundance, which illustrated that hitchhiking impacted the microbial community. Our analysis of co-occurrence between bulk soil motile bacteria (Bacillus) and rhizosphere bacteria also confirmed this. The correlation between bulk soil motile bacteria and the rhizosphere microbial community was strong in the groups with suitable nitrogen concentrations without filter membranes and was weak at all nitrogen levels in the no-membrane treatments. Thus, we concluded that plants and different nitrogen doses synergistically altered the soil microbiome by hitchhiking, whose effect depends on nitrogen.
In-silico identification of Tyr232 in AMPKα2 as a dephosphorylation site for the protein tyrosine phosphatase PTP-PEST
Authors: Manikandan Amrutha , Sreevidya T S , Manoj Narayanan , Vemparala Satyavani , Dixit Madhulika
Published: May 2022

The AMP-activated protein kinase (AMPK) is known to be activated by the protein tyrosine phosphatase non-receptor type 12 (PTP-PEST) under hypoxic conditions. This activation is mediated by tyrosine dephosphorylation of the AMPKα subunit. However, the identity of the phosphotyrosine residues remains unknown. In this study we first predicted the structure of the complex of the AMPKα2 subunit and PTP-PEST catalytic domain using bioinformatics tools and further confirm the stability of the complex using molecular dynamics simulations. Evaluation of the protein-protein interfaces indicates that residue Tyr232 is the most likely site of dephosphorylation on AMPKα2. In addition, we explored the effect of phosphorylation of PTP-PEST residue Tyr64 on the stability of the complex. The phosphorylation of Tyr64, an interface residue, enhances the stability of the complex via the rearrangement of a network of electrostatic interactions in conjunction with conformational changes in the catalytic WPD loop. Our findings present a plausible structural basis of AMPK regulation mediated by PTP-PEST and shows how phosphorylation of PTP-PEST could be involved in its activation.
Cell-type specific transcriptomics reveals roles for root hairs and endodermal barriers in interaction with beneficial rhizobacterium
Authors: Verbon Eline H. , Liberman Louisa M. , Zhou Jiayu , Yin Jie , Pieterse Corné M.J. , Benfey Philip N. , Stringlis Ioannis A. , de Jonge Ronnie
Published: May 2022

Growth-promoting bacteria can boost crop productivity in a sustainable way. Pseudomonas simiae WCS417 is a well-studied bacterium that promotes growth of many plant species. Upon colonization, WCS417 affects root system architecture resulting in an expanded root system. Both immunity and root system architecture, are controlled by root-cell-type specific biological mechanisms, but it is unknown how WCS417 affects these mechanisms. Therefore, here, we transcriptionally profiled five Arabidopsis thaliana root cell types following WCS417 colonization. The cortex and endodermis displayed the most differentially expressed genes, even though they were not in direct contact with this epiphytic bacterium. Many of these genes are associated with reduced cell wall biogenesis, possibly facilitating the root architectural changes observed in WCS417-colonized roots. Comparison of the transcriptome profiles in the two epidermal cell types that were in direct contact with WCS417 – trichoblasts that form root hairs and atrichoblasts that don’t – imply functional specialization. Whereas basal expression levels of nutrient uptake-related genes and defense-related genes are highest in trichoblasts and atrichoblasts, respectively, upon exposure to WCS417 these roles revert. This suggests that root hairs participate in the activation of root immunity, further supported by attenuation of immunity in a root hairless mutant. Furthermore, we observed elevated expression of suberin biosynthesis genes and increased deposition of suberin in the endodermis in WCS417-colonized roots. Using an endodermal barrier mutant we show the importance of endodermal barrier integrity for optimal plant-beneficial bacterium association. Altogether, we highlight the strength of cell-type-specific transcriptional profiling to uncover “masked” biological mechanisms underlying successful plant-microbe associations.
Netrin-1 regulates the balance of glutamatergic connectivity in the adult ventral tegmental area
Authors: Cline Marcella M , Juarez Barbara , Hunker Avery C. , Regiarto Ernesto G. , Hariadi Bryan , Soden Marta E. , Zweifel Larry S.
Published: May 2022

The axonal guidance cue netrin-1 serves a critical role in neural circuit development by promoting growth cone motility, axonal branching, and synaptogenesis. Within the adult mouse brain, expression of the gene encoding netrin-1 (Ntn1) is highly enriched in the ventral midbrain where it is expressed in both GABAergic and dopaminergic neurons, but its function in these cell types in the adult system remains largely unknown. To address this, we performed viral-mediated, cell-type specific CRISPR-Cas9 mutagenesis of Ntn1 in the ventral tegmental area (VTA) of adult mice. Ntn1 loss-of-function in either cell type resulted in a significant reduction in excitatory postsynaptic connectivity. In dopamine neurons, reduced excitatory tone had a minimal phenotypic behavioral outcome; however, reduced glutamatergic tone on VTA GABA neurons induced behaviors associated with a hyperdopaminergic phenotype. Loss of Ntn1 function in both cell types simultaneously largely rescued the phenotype observed in the GABA-only mutagenesis. These findings demonstrate an important role for netrin-1 in maintaining excitatory connectivity in the adult midbrain and that a balance in this connectivity within two of the major cell types of the VTA is critical for the proper functioning of the mesolimbic system.
Epitope-Evaluator: an interactive web application to study predicted T-cell epitopes
Authors: Soto Luis Fernando , Requena David , Fuxman Bass Juan Ignacio
Published: May 2022

Multiple immunoinformatic tools have been developed to predict T-cell epitopes from protein amino acid sequences for different major histocompatibility complex (MHC) alleles. These prediction tools output hundreds of potential peptide candidates which require further processing; however, these tools are either not graphical or not friendly for non-programming users. We present Epitope-Evaluator, a web tool developed in the Shiny/R framework to interactively analyze predicted T-cell epitopes. This includes providing the distribution of epitopes across a selected set of MHC alleles, the promiscuity and conservation of epitopes, and their density and location within antigens. Epitope-Evaluator requires as input the fasta file of protein sequences and the output prediction file coming out from any predictor. By choosing different cutoffs and parameters, users can produce several interactive plots and tables that can be downloaded as JPG and text files, respectively. Epitope-Evaluator removes the programming barrier and provides intuitive tools, allowing a straightforward interpretation and graphical representations that facilitate the selection of candidate epitopes for experimental evaluation.

Author Summary

With the advent of the COVID-19 pandemic as well as past pandemics and epidemics, scientists have focused on immunological studies to develop better vaccines as well as understand immune responses. Many of the questions are centered on studying T-cell epitopes, and peptide sequences that can be presented to immune cells to elicit responses against pathogens. Although current software can produce hundreds of predictions, they are generally not user-friendly nor graphical. In order to remove the existing programming barrier, we developed a Web tool to allow scientists to analyze and filter T-cell epitopes in an easy, intuitive, interactive, and versatile way. We have included two biological cases identifying new biological insights and showing the importance of having this type of toolset, especially for nonprogrammer researchers in the immunology field.
TSC2 regulates tumor susceptibility to TRAIL-mediated T cell killing by orchestrating mTOR signaling
Authors: Lin Chun-Pu , Traets Joleen J.H. , Vredevoogd David W. , Visser Nils L. , Peeper Daniel S.
Published: May 2022

Resistance to cancer immunotherapy continues to impair common clinical benefit. Here, we uncover an important role for Tuberous Sclerosis Complex 2 (TSC2) in determining tumor susceptibility to cytotoxic T lymphocytes (CTL) killing, bothin vitroandin vivo.TSC2-depleted tumor cells showed disrupted mTOR regulation upon CTL attack, which was associated with enhanced cell death. Tumor cells adapted to CTL attack by shifting their mTOR signaling balance toward increased mTORC2 activity to circumvent apoptosis and necroptosis. TSC2 critically protected tumor cells as its ablation strongly augmented tumor cell sensitivity to CTL attack. Mechanistically, TSC2 inactivation caused elevation of TRAIL receptors expression, cooperating with mTORC1-S6 signaling to induce tumor cell death. Clinically, we found a negative correlation betweenTSC2expression and TRAIL signaling in TCGA patient cohorts. Moreover, a lower TSC2 immune response signature was observed in melanomas from patients responding to immune checkpoint blockades. Our study uncovers a pivotal role for TSC2 in the cancer immune response by governing crosstalk between TSC2-mTOR and TRAIL signaling, aiding future therapeutic exploration of this pathway in immuno-oncology.
The endothelial-specific LINC00607 mediates endothelial angiogenic function
Authors: Boos Frederike , Oo James A. , Warwick Timothy , Günther Stefan , Ponce Judit Izquierdo , Buchmann Giulia , Li Tianfu , Seredinski Sandra , Haydar Shaza , Kashefiolasl Sepide , Baker Andrew H. , Boon Reinier A. , Schulz Marcel H. , Miller Francis J. , Brandes Ralf P. , Leisegang Matthias S.
Published: May 2022

Long non-coding RNAs (lncRNAs) can act as regulatory RNAs which, by altering the expression of target genes, impact on the cellular phenotype and cardiovascular disease development. Endothelial lncRNAs and their vascular functions are largely undefined. Deep RNA-Seq and FANTOM5 CAGE analysis revealed the lncRNA LINC00607 to be highly enriched in human endothelial cells. LINC00607 was induced in response to hypoxia, arteriosclerosis regression in non-human primates and also in response to propranolol used to induce regression of human arteriovenous malformations. siRNA knockdown or CRISPR/Cas9 knockout of LINC00607 attenuated VEGF-A-induced angiogenic sprouting. LINC00607 knockout in endothelial cells also integrated less into newly formed vascular networks in an in vivo assay in SCID mice. Overexpression of LINC00607 in CRISPR knockout cells restored normal endothelial function. RNA- and ATAC-Seq after LINC00607 knockout revealed changes in the transcription of endothelial gene sets linked to the endothelial phenotype and in chromatin accessibility around ERG-binding sites. Mechanistically, LINC00607 interacted with the SWI/SNF chromatin remodeling protein BRG1. CRISPR/Cas9-mediated knockout of BRG1 in HUVEC followed by CUT&RUN revealed that BRG1 is required to secure a stable chromatin state, mainly on ERG-binding sites. In conclusion, LINC00607 is an endothelial-enriched lncRNA that maintains ERG target gene transcription by interacting with the chromatin remodeler BRG1.
Efficient inference of evolutionary and progressive dynamics on hypercubic transition graphs
Authors: Moen Marcus T. , Johnston Iain G.
Published: May 2022

The progression of cancer and other diseases, the evolution of organismal features in biology, and a wide range of broader questions can often be viewed as the sequential stochastic acquisition of binary traits (for example, genetic changes, symptoms, or characters). Using potentially noisy or incomplete data to learn the sequences by which such traits are acquired is a problem of general interest. The problem is complicated for large numbers of traits which may, individually or synergistically, influence the probability of further acquisitions both positively and negatively. Hypercubic inference approaches, based on hidden Markov models on a hypercubic transition network, address these complications, but previous Bayesian instances can consume substantial time for converged results, limiting their practical use. Here we introduce HyperHMM, an adapted Baum-Welch (expectation maximisation) algorithm for hypercubic inference with resampling to quantify uncertainty, and show that it allows orders-of-magnitude faster inference while making few practical sacrifices compared to existing approaches. We apply this approach to synthetic and biological datasets and discuss its more general application in learning evolutionary and progressive pathways.
Ubiquitous bacterial polyketides induce cross-kingdom microbial interactions
Authors: Krespach Mario K. C. , Stroe Maria C. , Netzker Tina , Rosin Maira , Zehner Lukas M. , Komor Anna J. , Beilmann Johanna M. , Krüger Thomas , Kniemeyer Olaf , Schroeckh Volker , Hertweck Christian , Brakhage Axel A.
Published: May 2022

Although the interaction of prokaryotic and eukaryotic microorganisms is critical for the functioning of ecosystems, knowledge of the processes driving microbial interactions within communities is in its infancy. We previously reported that the soil bacteriumStreptomyces iranensisspecifically triggers the production of natural products in the fungusAspergillus nidulans.Here, we discovered that arginine-derived polyketides serve as the bacterial signals for this induction. Arginine-derived polyketide-producing bacteria occur world wide. These producer bacteria and the fungi that decode and respond to this signal can be co-isolated from the same soil sample. Arginine-derived polyketides impact surrounding microorganisms both directly as well as indirectly, by inducing the production of natural products in fungi that further influence the composition of microbial consortia.

One-Sentence Summary

Ubiquitous bacterial polyketides are universal components of the chemical network for microbial communication
Deep Reinforcement Learning for Optimal Experimental Design in Biology
Authors: Treloar Neythen J. , Braniff Nathan , Ingalls Brian , Barnes Chris P.
Published: May 2022

The field of optimal experimental design uses mathematical techniques to determine experiments that are maximally informative from a given experimental setup. Here we apply a technique from artificial intelligence—reinforcement learning—to the optimal experimental design task of maximizing confidence in estimates of model parameter values. We show that a reinforcement learning approach performs favourably in comparison with a one-step ahead optimisation algorithm and a model predictive controller for the inference of bacterial growth parameters in a simulated chemostat. Further, we demonstrate the ability of reinforcement learning to train over a distribution of parameters, indicating that this approach is robust to parametric uncertainty.

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Author summary

Biological systems are often complex and typically exhibit non-linear behaviour, making accurate model parametrisation difficult. Optimal experimental design tools help address this problem by identifying experiments that are predicted to provide maximally accurate parameter estimates. In this work we use reinforcement learning, an artificial intelligence method, to determine such experiments. Our simulation studies show that this approach allows uncertainty in model parameterisation to be directly incorporated into the search for optimal experiments, opening a practical avenue for training an experimental controller without confident knowledge of the system’s parameter values. We present this method as complementary to existing optimisation approaches and we anticipate that artificial intelligence has a fundamental role to play in the future of optimal experimental design.