bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dissecting Light Sensing and Metabolic Pathways on the Millimeter Scale in High-Altitude Modern Stromatolites
Authors: Alonso-Reyes Daniel Gonzalo , Galván Silvina , Irazoqui José Matías , Amadio Ariel , Tschoeke Diogo , Thompson Fabiano , Albarracín Virginia Helena , Farias María Eugenia 
Published: February 2022

ABSTRACTModern non-lithifying stromatolites (STs) on the shore of the volcanic lake Socompa in the Puna are affected by several extreme conditions. Although STs were proposed as ecologic models for understanding stress response and resilience in microbial ecosystems constituting a window into the past, our knowledge of ST function is still nascent. The present study assesses for the first time light utilization and functional metabolic stratification of STs on a millimeter scale through shotgun metagenomics. In addition, a scanning-electron-microscopy approach was used to explore the community. Our results demonstrated that Bacteroidetes and Cyanobacteria play major roles as ST builders and primary producers to sustain a diverse community of heterotrophs. STs manifest a high occurrence of genes for the synthesis of UV-protecting pigments, the cryptochrome-photolyase family (CPF), and rhodopsins in the surface layers. Three different ecologic niches involving the use of light in energy production were defined. Calvin-Benson and Wood-Ljungdahl pathways were proposed as the main mechanisms for carbon fixation. Several genes account for the microelectrode chemical data and pigment measurements performed in previous publications. We also provide here an explanation for the vertical microbial mobility within the ST described previously. Finally, our study points to STs as ideal modern analogues of ancient STs.
A network-based approach for isolating the chronic inflammation gene signatures underlying complex diseases towards finding new treatment opportunities
Authors: Hickey Stephanie L , McKim Alexander , Mancuso Christopher A , Krishnan Arjun 
Published: February 2022

AbstractComplex diseases are associated with a wide range of cellular, physiological, and clinical phenotypes. To advance our understanding of disease mechanisms and our ability to treat these diseases, it is critical to delineate the molecular basis and therapeutic avenues of specific disease phenotypes, especially those that are associated with multiple diseases. Inflammatory processes constitute one such prominent phenotype, being involved in a wide range of health problems including ischemic heart disease, stroke, cancer, diabetes mellitus, chronic kidney disease, non-alcoholic fatty liver disease, and autoimmune and neurodegenerative conditions. While hundreds of genes might play a role in the etiology of each of these diseases, isolating the genes involved in the specific phenotype (e.g., inflammation “component”) could help us understand the genes and pathways underlying this phenotype across diseases and predict potential drugs to target the phenotype. Here, we present a computational approach that integrates gene interaction networks, disease-/trait-gene associations, and drug-target information to accomplish this goal. We apply this approach to isolate gene signatures of complex diseases that correspond to chronic inflammation and prioritize drugs to reveal new therapeutic opportunities.
Clostridia isolated from helminth-colonized humans promote hatching of Trichuris muris
Authors: Sargsian Shushan , Chen Ze , Lee Soo Ching , Robertson Amicha , Sproch Julia , Devlin Joseph C. , Tee Mian Zi , Er Yi Xian , Copin Richard , Heguy Adriana , Pironti Alejandro , Torres Victor J. , Ruggles Kelly V. , Lim Yvonne A.L. , Loke P’ng , Cadwell Ken 
Published: February 2022

AbstractSoil transmitted intestinal worms known as helminths colonize over 1.5 billion people worldwide. Although helminth colonization has been associated with altered composition of the gut microbiota, such as increases in Clostridia, individual species have not been isolated and characterized. Here, we isolated and sequenced the genome of 13 Clostridia from the Orang Asli, an indigenous population in Malaysia with high prevalence of helminth infections. Metagenomic analysis of 650 fecal samples from urban and rural Malaysians revealed higher prevalence and abundance of these isolates compared to individuals in the United States, with Peptostreptococcaceae family members displaying a specific association with helminth colonization. Remarkably, Peptostreptococcaceae isolated from the Orang Asli displayed superior capacity to induce hatching of eggs from the murine helminth Trichuris muris. These findings support a model in which helminths select for gut colonization of microbes that in turn support their life cycle by promoting egg hatching.
Temporal and sequential transcriptional dynamics define lineage shifts in corticogenesis
Authors: Mukhtar Tanzila , Breda Jeremie , Boareto Marcelo , Grobecker Pascal , Karimaddini Zahra , Grison Alice , Eschbach Katja , Chandrasekhar Ramakrishnan , Vermeul Swen , Okoniewski Michal , Pachkov Mikhail , Atanasoski Suzana , Beisel Christian , Iber Dagmar , van Nimwegen Erik , Taylor Verdon 
Published: February 2022

AbstractThe cerebral cortex contains billions of neurons, and their disorganization or misspecification leads to neurodevelopmental disorders. Understanding how the plethora of projection neuron subtypes are generated by cortical neural stem cells (NSCs) is a major challenge. Here, we focused on elucidating the transcriptional landscape of murine embryonic NSCs, basal progenitors (BPs) and newborn neurons (NBNs) throughout cortical development. We uncover dynamic shifts in transcriptional space over time, and heterogeneity within each progenitor population. We identified signature hallmarks of NSC, BP and NBN clusters, and predict active transcriptional nodes and networks that contribute to neural fate specification. We find that the expression of receptors, ligands and downstream pathway components is highly dynamic over time and throughout the lineage implying differential responsiveness to signals. Thus, we provide an expansive compendium of gene expression during cortical development that will be an invaluable resource for studying neural developmental processes and neurodevelopmental disorders.
TP53 knockout in MCF7 breast cancer cells induces sensitivity to fluoropyrimidine drugs
Authors: Warrington JM , Mehta S , Moy VF , Patel JR , Liu C , Rago AR , McTighe C , Delgado I , Banister CE , Gmeiner WH , Buckhaults PJ 
Published: February 2022

AbstractTP53 mutations are present in all molecular subtypes of breast cancer and often correlate with decreased survival; however, few therapeutic options exist for patients with TP53-mutant breast cancers. To discover therapeutic strategies for these patients, we investigated the sensitivity of 129 FDA-approved chemotherapies to TP53-KO and TP53-WT MCF7 breast adenocarcinoma cells and found p53 loss to confer sensitivity to 5-fluorouracil (5-FU). We then treated the p53-null cells and isogenic controls with F10, a second-generation polymeric fluoropyrimidine, and found this preferential cytotoxicity of TP53-KO cells to be significantly magnified. F10 killing could only minimally be rescued by addition of exogenous uridine, whereas it was completely abrogated by addition of exogenous thymidine, suggesting DNA incorporation to be central to the cytotoxic mechanism of action. Furthermore, F10 killing of p53-null cells was persistent even in heterogeneous cellular mixtures more reflective of natural tumor evolution. Together, our results suggest F10 may widen the therapeutic window for TP53-mutant breast cancer by enhancing genotoxicity in cells resistant to apoptosis.
CaSee: A lightning transfer-learning model directly used to discriminate cancer/normal cells from scRNA-seq
Authors: Sh Yuan , Guo Caixia , Shi Fanghao , Jia Fei , Hu Zhiyuan , Zhang Xiuli 
Published: February 2022

AbstractSingle-cell RNA sequencing (scRNA-seq) is one of the most efficient technologies for human tumor research. However, data analysis is still faced with some technical challenges, especially the difficulty in efficiently and accurately discriminate cancer/normal cells in the scRNA-seq expression matrix. In this study, we developed a cancer/normal cell discrimination pipeline called pan-cancer seeker (CaSee) devoted to scRNA-seq expression matrix, which is based on the traditional high-quality pan-cancer bulk sequencing data using transfer learning. It is compatible with mainstream sequencings technology platforms, 10x Genomics Chromium, Smart-seq2, and Microwell-seq. Here, CaSee pipeline exhibited excellent performance in the multicenter data evaluation of 11 retrospective cohorts and one independent dataset, with an average discrimination accuracy of 96.69%. In general, the development of a deep-learning based, pan-cancer cell discrimination model, CaSee, to distinguish cancer cells from normal cells will be compelling to researchers working in the genomics, cancer, and single-cell fields.
PP1 inhibitor-2 promotes PP1γ positive regulation of synaptic transmission
Authors: Foley Karl , Altimimi Haider , Hou Hailong , Zhang Yu , McKee Cody , Papasergi-Scott Makaía M. , Yang Hongtian , Mayer Abigail , Ward Nancy , MacLean David M. , Nairn Angus C. , Stellwagen David , Xia Houhui 
Published: February 2022

AbstractInhibitor-2 (I-2) is a prototypic inhibitor of protein phosphatase-1 (PP1), a major serine-threonine phosphatase that regulates synaptic plasticity and learning and memory. Although I-2 is a potent inhibitor of PP1 in vitro, our previous work has elucidated that, in vivo, I-2 may act as a positive regulator of PP1. Here we show that I-2 and PP1γ, but not PP1α, positively regulate synaptic transmission in hippocampal neurons. Moreover, we demonstrated that I-2 enhances PP1γ interaction with its major synaptic scaffold, neurabin, by Förster resonance energy transfer (FRET)/Fluorescence lifetime imaging microscopy (FLIM) studies, while having a limited effect on PP1 autoinhibitory phosphorylation. Furthermore, our study indicates that the effect of I-2 on PP1 activity in vivo is dictated by I-2 threonine-72 phosphorylation. Our work thus demonstrates a molecular mechanism by which I-2 positively regulates PP1 function in synaptic transmission.
Structure, dynamics and assembly of the ankyrin complex on human red blood cell membrane
Authors: Xia Xian , Liu Shiheng , Zhou Z. Hong 
Published: February 2022

SummaryThe cytoskeleton of red blood cell (RBC) is anchored to cell membrane by the ankyrin complex. This complex is assembled during RBC genesis and comprises primarily band 3, protein 4.2 and ankyrin, whose mutations contribute to numerous human inherited diseases. High-resolution structures of the ankyrin complex have been long sought-after to understand its assembly and disease-causing mutations. Here, we analyzed native complexes on human RBC membrane by stepwise fractionation. Cryo-electron microscopy structures of nine band 3-associated complexes reveal that protein 4.2 stabilizes the cytoplasmic domain of band 3 dimer. In turn, the superhelix-shaped ankyrin binds to this protein 4.2 via ankyrin repeats (ARs) 6-13 and to another band 3 dimer via ARs 17-20, bridging two band 3 dimers in the ankyrin complex. Integration of these structures with both prior and our biochemical data supports a model of ankyrin complex assembly during erythropoiesis and identifies interactions essential for mechanical stability of RBC.
Low-cost sample preservation methods for high-throughput processing of rumen microbiomes
Authors: Budel Juliana C. C. , Hess Melanie K. , Bilton Timothy P. , Henry Hannah , Dodds Ken G. , Janssen Peter H. , McEwan John C. , Rowe Suzanne J. 
Published: February 2022

AbstractBackgroundThe use of rumen microbial community (RMC) profiles to predict methane emissions has driven interest in ruminal DNA preservation and extraction protocols that can be processed cheaply while also maintaining or improving DNA quality for RMC profiling. Our standard approach for preserving rumen samples, as defined in the Global Rumen Census (GRC), requires time-consuming pre-processing steps of freeze drying and grinding prior to international transportation and DNA extraction. This impedes researchers unable to access sufficient funding or infrastructure. To circumvent these pre-processing steps, we investigated three methods of preserving rumen samples for subsequent DNA extraction, based on existing lysis buffers Tris-NaCl-EDTA-SDS (TNx2) and guanidine hydrochloride (GHx2), or 100% ethanol.ResultsRumen samples were collected via stomach intubation from 151 sheep at two time-points two weeks apart. Each sample was separated into four subsamples and preserved using the three preservation methods and the GRC method (n = 4×302). DNA was extracted and sequenced using Restriction Enzyme-Reduced Representation Sequencing to generate RMC profiles. Differences in DNA yield, quality and integrity, and sequencing metrics were observed across the methods (p < 0.0001). Ethanol exhibited poorer quality DNA (A260/A230 < 2) and more failed samples compared to the other methods. Samples preserved using the GRC method had smaller relative abundances in gram-negative genera Anaerovibrio, Bacteroides, Prevotella, Selenomonas, and Succiniclasticum, but larger relative abundances in the majority of 56 additional genera compared to TNx2 and GHx2. However, log10 relative abundances across all genera and time-points for TNx2 and GHx2 were on average consistent (R2 > 0.99) but slightly more variable compared to the GRC method. Relative abundances were moderately to highly correlated (0.68 ± 0.13) between methods for samples collected within a time-point, which was greater than the average correlation (0.17 ± 0.11) between time-points within a preservation method.ConclusionsThe two modified lysis buffers solutions (TNx2 and GHx2) proposed in this study were shown to be viable alternatives to the GRC method for RMC profiling in sheep. Use of these preservative solutions reduces cost and improves throughput associated with processing and sequencing ruminal samples. This development could significantly advance implementation of RMC profiles as a tool for breeding ruminant livestock.
Barrier-free liquid condensates of nanocatalysts as effective concentrators of catalysis
Authors: Bedi Silky , Kumar Gaurav , Rose S M , Rakshit Sabyasachi , Sinha Sharmistha 
Published: February 2022

AbstractMolecular confinement of catalysts enhances the catalytic activity significantly. However, physicochemical barriers in traditional confinements restrict the free-passage of substrates/products. To obtain a barrier-free confinement of catalysts, here we explored the liquid-liquid phase separation. Using favourable ionic strength and crowding agents, we recruit the protein-inorganic-composites in phase separated liquid condensates from a solution. The phase separation propensity of these nanocomposites was seen to be independent of the native conformation of the component protein. Using standard catalytic oxidation-reduction reactions, we show that the close-proximity yet diffusive nature of catalysts in solution amplifies the homogeneous catalytic-efficiency of metal particles significantly. Overall, our work demonstrates the roadmap of using inorganic catalysts in homogeneous homogenous solution phase with amplified efficiency and longevity.
Sequence- and chemical specificity define the functional landscape of intrinsically disordered regions
Authors: Langstein-Skora Iris , Schmid Andrea , Huth Frauke , Shabani Drin , Spechtenhauser Lorenz , Likhodeeva Mariia , Kunert Franziska , Metzner Felix J. , Emenecker Ryan J. , Richardson Mary O.G. , Aftab Wasim , Götz Maximilian J. , Payer Sarah K. , Pietrantoni Niccoló , Sjeničić Valentina , Ravichandran Sakthi K. , Bartke Till , Hopfner Karl-Peter , Gerland Ulrich , Korber Philipp , Holehouse Alex S. 
Published: February 2022

AbstractIntrinsically disordered protein regions (IDRs) pervasively engage in essential molecular functions, yet they are often poorly conserved as assessed by sequence alignment. To understand the seeming paradox of how sequence variability is compatible with persistent function, we examined the functional determinants for a poorly conserved but essential IDR. We show that IDR function depends on two distinct but related properties: sequence- and chemical specificity. While sequence-specificity works via linear binding motifs, chemical specificity reflects the sequence-encoded chemistry of multivalent interactions through amino acids across an IDR. Unexpectedly, a binding motif that is essential in the wild-type IDR can be removed if compensatory changes to the sequence chemistry are made, highlighting the orthogonality and interoperability of both properties and providing a much deeper sequence space compatible with function. Our results provide a general framework to understand the functional constraints on IDR sequence evolution.
Ecological Observations Based on Functional Gene Sequencing Are Sensitive to the Amplicon Processing Method
Authors: Cholet Fabien , Lisik Agata , Agogué Hélène , Ijaz Umer Z , Pineau Philippe , Lachaussée Nicolas , Smith Cindy J 
Published: February 2022

AbstractUntil recently, the de-facto method for short read-based amplicons reconstruction is a sequence similarity threshold approach (Operational taxonomic Units OTUs). This assumption was relaxed by shifting to Amplicon Sequencing Variants (ASVs) where distributions are fitted to abundance profiles of individual genes using a noise-error model. Whilst OTUs-based approach is still useful for 16SrRNA/18S rRNA regions, where typically 97-99% thresholds are used, their utility to functional genes is still debatable as there is no consensus on how to cluster the sequences together. Here, we compare OTUs- and ASVs-based reconstruction approaches as well as taxonomy assignment methods, Naïve Bayesian Classifier (NBC) and Bayesian Lowest Common Ancestor Algorithm (BLCA), using functional genes dataset from the microbial nitrogen-cycling community in the Brouage mudflat (France). A range of OTU similarity thresholds and ASV were used to compare amoA (AOA and AOB), nxrB, nirS, nirK and nrfA communities between differing sedimentary structures. We show that for AOA-amoA and nrfA, the use of ASV led to differences in the communities between sedimentary structures whereas the use of OTUs didn’t. Conversely, significant differences were detected when using OTU (97%) for AOB-amoA but not with ASV or OTUs at other similarity thresholds. Interestingly, conclusions drawn from the other three functional genes were consistent between amplicon reconstruction methods. We also show that, when the sequences in the reference-database are related to the environment in question, BLCA leads to more phylogenetically relevant classifications. However, when the reference database contains sequences more dissimilar to the ones retrieved, NBC helps obtain more information.ImportanceSeveral analysis pipelines are available to microbial ecologists to process amplicon sequencing data yet to-date, there is no consensus as to the most appropriate method, and it becomes more difficult for genes that encode a specific function (functional genes). Standardised approaches need to be adopted to increase reliability and reproducibility of environmental amplicon sequencing-based datasets. In this paper, we argue that the recently developed ASV approach offers a better opportunity to achieve such standardisation compared to OTUs for functional genes. We also propose a comprehensive framework for quality filtering of the sequencing reads based on protein sequence verification and merging.
Global Force-of-Infection Trends for Human Taenia solium Taeniasis/Cysticercosis
Authors: Dixon Matthew A. , Winskill Peter , Harrison Wendy E. , Whittaker Charles , Schmidt Veronika , Flórez Sánchez Astrid Carolina , Cucunubá Zulma M. , Edia-Asuke Agnes U. , Walker Martin , Basáñez Maria-Gloria 
Published: February 2022

AbstractInfection by Taenia solium poses a major burden across endemic countries. The World Health Organization (WHO) 2021–2030 Neglected Tropical Diseases roadmap has proposed that 30% of endemic countries achieve intensified T. solium control in hyperendemic areas by 2030. Understanding geographical variation in age-prevalence profiles and force-of-infection (FoI) estimates will inform intervention designs across settings.Human taeniasis (HTT) and human cysticercosis (HCC) age-prevalence data from 16 studies in Latin America, Africa and Asia were extracted through a systematic review. Catalytic models, incorporating diagnostic performance uncertainty, were fitted to the data using Bayesian methods, to estimate rates of antibody (Ab)-seroconversion, infection acquisition and Ab-seroreversion or infection loss. HCC FoI and Ab-seroreversion rates were also estimated across 23 departments in Colombia from 28,100 individuals.Across settings, there was extensive variation in all-ages seroprevalence. Evidence for Ab- seroreversion or infection loss was found in most settings for both HTT and HCC and for HCC Ab- seroreversion in Colombia. The average duration until humans became Ab-seropositive/infected decreased as all-age (sero)prevalence increased. There was no clear relationship between the average duration humans remain Ab-seropositive and all-age seroprevalence.Marked geographical heterogeneity in T. solium transmission rates indicate the need for setting- specific intervention strategies to achieve the WHO goals.
Predictive Machine Learning for Personalised Medicine in Major Depressive Disorder
Authors: Gountouna Viktoria-Eleni , Bermingham Mairead L. , Kuznetsova Ksenia , Muñoz Daniel Urda , Agakov Felix , Robson Siân E. , Meijsen Joeri J. , Campbell Archie , Hayward Caroline , Wigmore Eleanor M. , Clarke Toni-Kim , Fernandez Ana Maria , MacIntyre Donald J. , McKeigue Paul , Porteous David J. , Nicodemus Kristin K. 
Published: February 2022

AbstractDepression is a common psychiatric disorder with substantial recurrence risk. Accurate prediction from easily collected data would aid in diagnosis, treatment and prevention. We used machine learning in the Generation Scotland cohort to predict lifetime risk of depression and, among cases, recurrent depression. Rank aggregation was used to combine results across ten different algorithms and identify highly predictive variables. The model containing all but the cardiometabolic predictors had the highest predictive ability on independent data. Rank aggregation produced a reduced set of predictors without decreasing predictive performance (lifetime: 20 out of 154 predictors and Receiver Operating Characteristic area under the curve (AUC)=0·84, recurrent: 10 out of 180 predictors and AUC=0·76). Here we develop a pipeline which leads to a small set of highly predictive variables. This information can be easily collected with a smartphone ‘application’ to help diagnosis and treatment, while longitudinal tracking may help patients in self-management.SignificanceDepression is the most common psychiatric disorder and a leading cause of disability worldwide. Patients are often diagnosed and treated by non-specialist clinicians who have limited time available to assess them. We present a novel methodology which allowed us to identify a small set of highly predictive variables for a diagnosis of depression, or recurrent depression in patients. This information can easily be collected using a tablet or smartphone application in the clinic to aid diagnosis.