bluuebunny/crossref_metadata_2025_split huggingface dataset:
Graph-Based Reconstruction and Analysis of Disease Transmission Networks using Viral Genomic Data
Authors: Ke Ziqi , Vikalo Haris 
Published: August 2022

ABSTRACTUnderstanding the patterns of viral disease transmissions helps establish public health policies and aids in controlling and ending a disease outbreak. Classical methods for studying disease transmission dynamics that rely on epidemiological data, such as times of sample collection and duration of exposure intervals, struggle to provide desired insight due to limited informativeness of such data. A more precise characterization of disease transmissions may be acquired from sequencing data that reveals genetic distance between viral populations in patient samples. Indeed, genetic distance between viral strains present in hosts contains valuable information about transmission history, thus motivating the design of methods that rely on genomic data to reconstruct a directed disease transmission network, detect transmission clusters, and identify significant network nodes (e.g., super-spreaders). In this paper, we present a novel end-to-end framework for the analysis of viral transmissions utilizing viral genomic (sequencing) data. The proposed framework groups infected hosts into transmission clusters based on reconstructed viral quasispecies; the genetic distance between a pair of hosts is calculated using Earth Mover’s Distance, and further used to infer transmission direction between the hosts. To quantify the significance of a host in the transmission network, the importance score is calculated by a graph convolutional auto-encoder. The viral transmission network is represented by a directed minimum spanning tree utilizing the Edmond’s algorithm modified to incorporate constraints on the importance scores of the hosts. Results on realistic synthetic as well as experimental data demonstrate that the proposed framework outperforms state-of-the-art techniques for the analysis of viral transmission dynamics.CCS CONCEPTSApplied computing → Bioinformatics.ACM Reference FormatZiqi Ke and Haris Vikalo. 2022. Graph-Based Reconstruction and Analysis of Disease Transmission Networks using Viral Genomic Data. In Proceedings of The Seventh International Workshop on Computational Network Biology (CNB-MAC 2022). ACM, New York, NY, USA, 10 pages. https://doi.org/XXXXXXX.XXXXXXX
Ubigen: Interactive Ranking and Enrichment Test for Ubiquitously Expressed Genes
Authors: Projahn Elias , Möller Steffen 
Published: August 2022

SummaryWe provide an interactive web service to score and rank human genes by their abundance and invariance of expression across all samples in the GTEx database. Users may provide a list of genes to have these scored and ranked accordingly. A one-sided Wilcoxon rank sum test determines a p-value to indicate if the genes from the list score higher than expected by chance. It is possible to interactively control the parameters and instantly observe the effects on the ranking for each of the submitted genes of interest. A genome-wide sliding-window analysis finds that the genes with both the highest and the lowest ranks feature more GO term annotations, indicating that the scoring carries biological relevance.Availability and Implementationhttps://ubigen.uni-rostock.deContactelias.projahn@uni-rostock.de
Collective invasion of the basement membrane in breast cancer driven by forces from cell volume expansion and local contractility
Authors: Chang Julie , Saraswathibhatla Aashrith , Song Zhaoqiang , Varma Sushama , Sanchez Colline , Srivastava Sucheta , Liu Katherine , Bassik Michael C. , Marinkovich M. Peter , Hodgson Louis , Shenoy Vivek , West Robert B. , Chaudhuri Ovijit 
Published: August 2022

AbstractBreast cancer becomes invasive when carcinoma cells collectively invade through the basement membrane (BM), a nanoporous layer of matrix that physically separates the primary tumor from the stroma, in a first step towards metastasis. Single cells can invade through nanoporous three-dimensional (3D) matrices via protease-mediated degradation or, when the matrix exhibits sufficient mechanical plasticity, force-mediated widening of pores. However, how cells invade collectively through physiological BM layers in cancer remains unclear. Here, we developed a 3D in vitro model of collective invasion of the BM during breast cancer. We show that cells utilize both proteases and forces to breach the BM. Forces are generated from a combination of global cell volume expansion that stretch the BM with local contractile forces that act in the plane of the BM to breach it, allowing invasion. These results uncover a mechanism by which cells collectively interact to overcome a critical barrier to metastasis.
Drug-gene interaction screens coupled to tumour data analyses identify the most clinically-relevant cancer vulnerabilities driving sensitivity to PARP inhibition
Authors: Jamal Kunzah , Galbiati Alessandro , Armenia Joshua , Illuzzi Giuditta , Hall James , Bentouati Sabrina , Barrell Daniel , Ahdesmäki Miika ,   Functional Genomics Centre, O’Connor Mark J. , Leo Elisabetta , Forment Josep V. 
Published: August 2022

AbstractPoly(ADP-ribose) polymerase (PARP) inhibitors (PARPi) are currently indicated for the treatment of ovarian, breast, pancreatic and prostate cancers harbouring mutations in the tumour suppressor genes BRCA1 or BRCA2. In the case of ovarian and prostate cancers, their classification as homologous recombination repair (HRR) deficient (HRD) or mutated (HRRm) also makes PARPi an available treatment option beyond BRCA1 or BRCA2 mutational status. However, identification of the most relevant genetic alterations driving the HRD phenotype has proven difficult and recent data have shown that other genetic alterations not affecting HRR are also capable of driving PARPi responses. To gain insight into the genetics driving PARPi sensitivity, we performed CRISPR-Cas9 loss-of-function screens in 6 PARPi-insensitive cell lines and combined the output with published PARPi datasets from 8 additional cell lines. Ensuing exploration of the data identified 110 genes whose inactivation is strongly linked to sensitivity to PARPi. Parallel cell line generation of isogenic gene knockouts in ovarian and prostate cancer cell lines identified that inactivation of core HRR factors is required for driving in vitro PARPi responses comparable to the ones observed for BRCA1 or BRCA2 mutations. Moreover, pan-cancer genetic, transcriptomic and epigenetic data analyses of these 110 genes highlight the ones most frequently inactivated in tumours, making this study a valuable resource for prospective identification of potential PARPi-responsive patient populations. Importantly, our investigations uncover XRCC3 gene silencing as a potential new prognostic biomarker of PARPi sensitivity in prostate cancer.Statement of significanceThis study identifies tumour genetic backgrounds where to expand the use of PARP inhibitors beyond mutations in BRCA1 or BRCA2. This is achieved by combining the output of unbiased genome-wide loss-of-function CRISPR-Cas9 genetic screens with bioinformatics analysis of biallelic losses of the identified genes in public tumour datasets, unveiling loss of the DNA repair gene XRCC3 as a potential biomarker of PARP inhibitor sensitivity in prostate cancer.
Tracking multiple conformations occurring on angstrom-and-millisecond scales in single amino-acid-transporter molecules
Authors: Zhou Yufeng , Lewis John H. , Lu Zhe 
Published: August 2022

AbstractThe AdiC transporter facilitates the movement of arginine and its metabolite across the membrane of pathogenic enterobacteria, enabling them to evade a host’s highly acidic gastric defense barrier to reach the intestines. Like other transporters, AdiC undergoes a series of necessary conformational changes. Detection of these changes, which occur on angstrom-and- millisecond scales, remains extremely challenging. Here, using a high-resolution polarization-microscopic method, we have successfully resolved AdiC’s four conformations by monitoring the emission-polarization changes of a fluorophore attached to an α-helix that adopts conformation-specific orientations and, furthermore, quantified their probabilities in a series of arginine concentrations. The KD values determined for arginine in four individual conformations are statistically comparable to the previously reported overall KD determined using isothermal titration calorimetry. This demonstrated strong resolving power of the present polarization-microscopy method will enable an acquisition of the quantitative information required for understanding the expected complex conformational mechanism underlying the transporter’s function, as well as those of other membrane proteins.
Inference of evolutionary transitions to self-fertilization using whole-genome sequences
Authors: Struett Stefan , Sellinger Thibaut , Glémin Sylvain , Tellier Aurélien , Laurent Stefan 
Published: August 2022

AbstractThe evolution from outcrossing to selfing is a transition that occurred recurrently throughout the eukaryote tree of life, in plants, animals, fungi and algae. Despite some short-term advantages, selfing is supposed to be an evolutionary dead-end reproductive strategy on the long-term and its tippy distribution on phylogenies suggests that most selfing species are of recent origin. However, dating such transitions is challenging while it is central for this hypothesis. We develop two methods making use of full genome polymorphism data to 1) test if a transition from outcrossing to selfing occurred, and 2) infer its age. The sequentially Markov coalescent based (teSMC) and the Approximate Bayesian Computation (tsABC) methods use a common framework based on a transition matrix summarizing the distribution of times to the most recent common ancestor along the genome, allowing to estimate changes in the ratio of population recombination and mutation rates in time. We first demonstrate that our methods can disentangle between past change in selfing rate from past changes in demographic history. Second, we assess the accuracy of our methods and show that transitions to selfing as old as approximatively 2.5Ne generations can be identified from polymorphism data. Third, our estimates are robust to the presence of linked negative selection on coding sequences. Finally, as a proof of principle, we apply both methods to three populations from Arabidopsis thaliana, recovering a transition to selfing which occurred approximately 600,000 years ago. Our methods pave the way to study recent transitions to predominant self-fertilization in selfing organisms.Significance statementSelf-fertilization evolved recurrently from outcrossing in many groups of organisms. When, why, and at what pace such transitions occurred are central to understand the evolution of reproductive systems but dating them remains highly challenging. While experimental work can be conducted in ecological set-ups, it is difficult to reconstruct and empirically test the past ecological conditions which could have driven transitions from outcrossing to self-fertilizing reproduction. We suggest here to use full genome data of several individuals per population to estimate if and when a transition in reproductive strategy occurred. We develop two methods which can be applied to estimate the age of such transitions jointly with the species demographic history.
Overexpression profiling reveals cellular requirements in context of genetic backgrounds and environments
Authors: Saeki Nozomu , Yamamoto Chie , Eguchi Yuichi , Sekito Takayuki , Shigenobu Shuji , Yoshimura Mami , Yashiroda Yoko , Boone Charles , Moriya Hisao 
Published: August 2022

AbstractOverexpression due to copy number variation, promoter mutation, or aneuploidy is often observed, but its adaptive role is not clearly understood. Using a novel “overexpression profiling” method designated ADOPT, we systematically obtained genes whose overexpression was functionally adaptive (GOFAs) under stress conditions in budding yeast to elucidate the nature of adaptive overexpression. GOFAs obtained under heat, salt, and oxidative stress were unique genes that differed from known stress response genes. GOFAs under salt (NaCl) stress were genes involved in calcium homeostasis, reflecting the calcium deficiency of the medium. GOFAs from different genetic backgrounds and co-overexpressing strains revealed that calcium and potassium requirements in salt stress tolerance differ among strains, which is reflected. Profiling of the knockout collection suggested that the effect of calcium was to prevent mitochondrial outbursts. Mitochondria-enhancing GOFAs were adaptive only when calcium was sufficient and conversely non-adaptive in calcium deficiency, supporting the above hypothesis. Adaptive overexpression, thus, reflects the cellular requirements for maximizing the organism’s adaptive capacity within a given environmental and genetic context.
Probabilistic Edge Inference of Gene Networks with Bayesian Markov Random Field Modelling
Authors: Huang Yu-Jyun , Mukherjee Rajarshi , Hsiao Chuhsing Kate 
Published: August 2022

AbstractGaussian graphical models (GGMs), also known as Gaussian Markov random field (MRF) models, are commonly used for gene regulatory network construction. Most current approaches to estimating network structure via GGMs can be categorized into a binary decision that determines if an edge exists through penalized optimization and a probabilistic approach that incorporates graph uncertainty. Analyses in the first category usually adopt the perspective of variable (edge) selection without consideration of probabilistic interpretation. Methods in the second group, particularly the Bayesian approach, often quantify the uncertainty in the network structure with a stochastic measure on the precision matrix. Nevertheless, these methods overlook the existence probability of an edge and its strength related to the dependence between nodes. This study simultaneously investigates the existence and intensity of edges for network structure learning. We propose a method that combines the Bayesian MRF model and conditional autoregressive model for the relationship between gene nodes. This analysis can evaluate the relative strength of the edges and further prioritize the edges of interest. Simulations and a glioblastoma cancer study were carried out to assess the proposed model’s performance and compare it with existing methods. The proposed approach shows stable performance and may identify novel structures with biological insights.
Quantitative comparison of manuka and clover honey proteomes with royal jelly
Authors: Paget B.W. , Kleffmann T. , Whiteman K.E. , Thomas M.F. , McMahon C.D. 
Published: August 2022

AbstractRoyal jelly and honey are two substances produced successively by the worker bee caste. Sequential window acquisition of all theoretical fragment-ion spectra mass spectrometry (SWATH-MS) was used to compare protein quantities of bee origin in manuka and clover honey to royal jelly. Two analysis techniques identified 75 proteins in total. Peptide intensity was directly compared for a subset of 32 proteins that were identified with high confidence, and the relative changes in protein abundance were compared between each honey and royal jelly. A total of 16 proteins were found only in honey, 9 of which were common to manuka and clover honeys, and 7 found only in manuka honey. None of the identified proteins were unique to clover honey, while four proteins were unique to royal jelly. Major Royal Jelly Proteins (MRJPs) had similar profiles in both honeys, except MRJP6, which was significantly more abundant in clover honey.Quantitative data suggests changes of the protein composition as bees develop through the worker caste, with subtle changes in MRJP amounts, and extensive changes in proteins with enzymatic function. Metabolism enzymes were more abundant in honey than in royal jelly, where the trend revealed a potential catalytic role for two uncharacterised proteins (MRJP6 and LOC408608). Differences in the proteomes of the two types of honey probably reflects differences in the type of nectar foraged.
Arabidopsis LSH10 transcription factor interacts with the co-repressor histone deubiquitinase OTLD1 to recruit it to the target promoters
Authors: Vo Phan Mi Sa , Keren Ido , Tran Phu Tri , Lapidot Moshe , Citovsky Vitaly 
Published: August 2022

AbstractHistone ubiquitylation/deubiquitylation plays a major role in the epigenetic regulation of gene expression. In plants, OTLD1, a member of the ovarian tumor (OTU) deubiquitinase family, deubiquitylates monoubiquitylated histone 2B and represses the expression of genes involved in growth, cell expansion, and hormone signaling. Like many other histone-modifying enzymes, OTLD1 lacks the intrinsic ability to bind DNA. How OTLD1, as well as most other known plant histone deubiquitinases, is recruited specifically to the promoters of its target genes remains unknown. Here, we show that Arabidopsis transcription factor LSH10, a member of the ALOG protein family, interacts with OTLD1 in living plant cells. Loss-of-function LSH10 mutations relieve the OTLD1-promoted transcriptional repression of the target genes, resulting in their elevated expression, whereas recovery of the LSH10 function results in down-regulated transcription of the same genes. We then show that LSH10 associates directly with the target gene chromatin as well as with the specific DNA sequence motifs in the promoter regions of the target genes. Furthermore, in the absence of LSH10, the degree of H2B monoubiquitylation in the target promoter chromatin increases. Hence, our data suggest that OTLD1-LSH10 acts as a co-repressor complex, in which LSH1 recruits OTLD1 to the target gene promoters, potentially representing a general mechanism for recruitment of plant histone deubiquitinases to the target chromatin.
Reduced γ-glutamyl hydrolase activity likely contributes to high folate levels in Periyakulam-1 tomato
Authors: Tyagi Kamal , Sunkum Anusha , Gupta Prateek , Kilambi Himabindu Vasuki , Sreelakshmi Yellamaraju , Sharma Rameshwar 
Published: August 2022

AbstractTomato cultivars show wide variation in nutraceutical folate in ripe fruits, yet the loci regulating folate levels in fruits remain unexplored. To decipher regulatory points, we compared two contrasting tomato cultivars: Periyakulam-1 (PKM-1) with high folate and Arka Vikas (AV) with low folate. The progression of ripening in PKM-1 was nearly similar to AV but had substantially lower ethylene emission. In parallel, the levels of phytohormones salicylic acid, ABA, and jasmonic acid were substantially lower than AV. The fruits of PKM-1 were also metabolically distinct from AV, with upregulation of several amino acids. Consistent with higher °Brix levels, the red ripe fruits also showed upregulation of sugars and sugar-derived metabolites. In parallel with higher folate, PKM-1 fruits also had higher carotenoid levels, especially lycopene and β-carotene. Transcript levels of genes encoding folate biosynthesis did not show a perceptible difference in relative expression. The proteome analysis showed upregulation of carotenoid sequestration and folate metabolism-related proteins in PKM-1. The deglutamylation pathway mediated by γ-glutamyl hydrolase (GGH) was substantially reduced in PKM-1 at the red-ripe stage. The red-ripe fruits had reduced transcript levels of GGHs and lower GGH activity than AV. Conversely, the percent polyglutamylation of folate was much higher in PKM-1. Our analysis indicates the regulation of GGH activity as a potential target to elevate folate levels in tomato fruits.
InterClone: Store, Search and Cluster Adaptive Immune Receptor Repertoires
Authors: Wilamowski Jan , Xu Zichang , Ismanto Hendra S , Li Songling , Teraguchi Shunsuke , Llamas- Covarrubias Mara Anais , Lu Xiuyuan , Yamasaki Sho , Standley Daron M 
Published: August 2022

AbstractB and T cell receptor repertoire data has the potential to fundamentally change the way we diagnose and treat a wide range of diseases. However, there are few resources for storing or analyzing repertoire data. InterClone provides tools for storing, searching, and clustering repertoire datasets. Efficiency is achieved by encoding the complementarity-determining regions of sequences as mmseqs2 databases. Single chain search or cluster results can be merged into paired (alpha-beta or heavy-light) results for analysis of single-cell sequencing data. We illustrate the use of InterClone with two recently reported examples: 1) searching for SARS-CoV-2 infection-enhancing antibodies in bulk COVID-19 and healthy donor repertoires; 2) identification of SARS-CoV-2 specific TCRs by clustering paired and bulk sequences from COVID-19, BNT162b2 vaccinated and healthy unvaccinated donors. The core functions of InterClone have been implemented as a web server and integrated database (https://sysimm.org/interclone). All source code is available upon request.
Expansion Sequencing of RNA Barcoded Neurons in the Mammalian Brain: Progress and Implications for Molecularly Annotated Connectomics
Authors: Goodwin Daniel R. , Vaughan Alex , Leible Daniel , Alon Shahar , Henry Gilbert L. , Cheng Anne , Chen Xiaoyin , Zhang Ruihan , Xue Andrew G. , Wassie Asmamaw T. , Sinha Anubhav , Bando Yosuke , Kajita Atsushi , Marblestone Adam H. , Zador Anthony M. , Boyden Edward S. , Church George M. , Kohman Richie E. 
Published: August 2022

AbstractMapping and molecularly annotating mammalian neural circuits is challenging due to the inability to uniquely label cells while also resolving subcellular features such as synaptic proteins or fine cellular processes. We argue that an ideal technology for connectomics would have the following characteristics: the capacity for robustdistance-independent labeling, synaptic resolution, molecular interrogation, and scalable computational methods. The recent development of high-diversity cellular barcoding with RNA has provided a way to overcome the labeling limitations associated with spectral dyes, however performing all-optical circuit mapping has not been demonstrated because no method exists to image barcodes throughout cells at synaptic-resolution. Here we show ExBarSeq, an integrated method combining in situ sequencing of RNA barcodes, immunostaining, and Expansion Microscopy coupled with an end-to-end software pipeline that automatically extracts barcode identities from large imaging datasets without data processing bottlenecks. As a proof of concept, we applied ExBarSeq to thick tissue sections from mice virally infected with MAPseq viral vectors and demonstrated the extraction of 50 barcoded cells in the visual cortex as well as cell morphologies uncovered via immunostaining. The current work demonstrates high resolution multiplexing of exogenous barcodes and endogenous synaptic proteins and outlines a roadmap for molecularly annotated connectomics at a brain-wide scale.