Showing papers by "Institute for Systems Biology published in 2021"
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French Institute of Health and Medical Research1, University of Paris2, Rockefeller University3, Hiroshima University4, Autonomous University of Barcelona5, University of Tartu6, University of Franche-Comté7, Jean Monnet University8, Lyon College9, Centre national de la recherche scientifique10, Aix-Marseille University11, National Institutes of Health12, Tokyo Medical and Dental University13, Paris Diderot University14, Academy of Athens15, Institute for Systems Biology16, University of Antioquia17, Del Rosario University18, Carlos III Health Institute19, Canadian Real Estate Association20
TL;DR: In this paper, the authors found that auto-antibodies neutralizing high concentrations (10 ng/mL, in plasma diluted 1 to 10) of IFN-α and/or -ω are found in about 10% of patients with critical COVID-19 pneumonia, but not in subjects with asymptomatic infections.
Abstract: Circulating autoantibodies (auto-Abs) neutralizing high concentrations (10 ng/mL, in plasma diluted 1 to 10) of IFN-α and/or -ω are found in about 10% of patients with critical COVID-19 pneumonia, but not in subjects with asymptomatic infections. We detect auto-Abs neutralizing 100-fold lower, more physiological, concentrations of IFN-α and/or -ω (100 pg/mL, in 1/10 dilutions of plasma) in 13.6% of 3,595 patients with critical COVID-19, including 21% of 374 patients > 80 years, and 6.5% of 522 patients with severe COVID-19. These antibodies are also detected in 18% of the 1,124 deceased patients (aged 20 days-99 years; mean: 70 years). Moreover, another 1.3% of patients with critical COVID-19 and 0.9% of the deceased patients have auto-Abs neutralizing high concentrations of IFN-β. We also show, in a sample of 34,159 uninfected subjects from the general population, that auto-Abs neutralizing high concentrations of IFN-α and/or -ω are present in 0.18% of individuals between 18 and 69 years, 1.1% between 70 and 79 years, and 3.4% >80 years. Moreover, the proportion of subjects carrying auto-Abs neutralizing lower concentrations is greater in a subsample of 10,778 uninfected individuals: 1% of individuals 80 years. By contrast, auto-Abs neutralizing IFN-β do not become more frequent with age. Auto-Abs neutralizing type I IFNs predate SARS-CoV-2 infection and sharply increase in prevalence after the age of 70 years. They account for about 20% of both critical COVID-19 cases in the over-80s, and total fatal COVID-19 cases.
269 citations
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18 Feb 2021
TL;DR: In this paper, the authors leverage three independent cohorts comprising over 9,000 individuals and find that compositional uniqueness is strongly associated with microbially produced amino acid derivatives circulating in the bloodstream.
Abstract: The gut microbiome has important effects on human health, yet its importance in human ageing remains unclear. In the present study, we demonstrate that, starting in mid-to-late adulthood, gut microbiomes become increasingly unique to individuals with age. We leverage three independent cohorts comprising over 9,000 individuals and find that compositional uniqueness is strongly associated with microbially produced amino acid derivatives circulating in the bloodstream. In older age (over ~80 years), healthy individuals show continued microbial drift towards a unique compositional state, whereas this drift is absent in less healthy individuals. The identified microbiome pattern of healthy ageing is characterized by a depletion of core genera found across most humans, primarily Bacteroides. Retaining a high Bacteroides dominance into older age, or having a low gut microbiome uniqueness measure, predicts decreased survival in a 4-year follow-up. Our analysis identifies increasing compositional uniqueness of the gut microbiome as a component of healthy ageing, which is characterized by distinct microbial metabolic outputs in the blood.
211 citations
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TL;DR: Dfam as mentioned in this paper is an open access database of repetitive DNA families, sequence models, and genome annotations, which includes 266,740 new de novo generated transposable element families from 336 species contributed by the EBI.
Abstract: Dfam is an open access database of repetitive DNA families, sequence models, and genome annotations. The 3.0–3.3 releases of Dfam (
https://dfam.org
) represent an evolution from a proof-of-principle collection of transposable element families in model organisms into a community resource for a broad range of species, and for both curated and uncurated datasets. In addition, releases since Dfam 3.0 provide auxiliary consensus sequence models, transposable element protein alignments, and a formalized classification system to support the growing diversity of organisms represented in the resource. The latest release includes 266,740 new de novo generated transposable element families from 336 species contributed by the EBI. This expansion demonstrates the utility of many of Dfam’s new features and provides insight into the long term challenges ahead for improving de novo generated transposable element datasets.
181 citations
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University of Copenhagen1, Massachusetts Institute of Technology2, Chief Dull Knife College3, University of Washington4, Institute for Systems Biology5, Paris Diderot University6, Institut de recherche pour le développement7, University of the Witwatersrand8, Université de Montréal9, Laval University10, Finnish Environment Institute11, University of Helsinki12, Broad Institute13, University of Auckland14, Tumaini University Makumira15, University of Dar es Salaam16, University of Alcalá17, Karolinska Institutet18, Korle Bu Teaching Hospital19, University of Cape Coast20, Mayo Clinic21, Catholic University College, Kensington22, Kwame Nkrumah University of Science and Technology23, Lagos State University24
TL;DR: This paper investigated the extent to which the rates and targets of horizontal gene transfer vary across thousands of bacterial strains from 15 human populations spanning a range of industrialization and found that industrialized lifestyles are associated with higher HGT rates and the functions of HGTs are related to the level of host industrialization.
119 citations
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TL;DR: In this article, the authors performed a detailed characterization of natural killer (NK) cells in 205 patients (403 samples; days 2 to 41 after symptom onset) from four independent cohorts using single-cell transcriptomics and proteomics together with functional studies.
111 citations
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National Institutes of Health1, University of California, San Diego2, Saint Petersburg State University3, University of Washington4, University of California, Berkeley5, Johns Hopkins University6, University of Connecticut7, University of California, Santa Cruz8, University of Geneva9, Stowers Institute for Medical Research10, Harvard University11, Wellcome Trust Sanger Institute12, University of Cambridge13, Howard Hughes Medical Institute14, Washington University in St. Louis15, University of Tennessee Health Science Center16, Yale University17, Pacific Biosciences18, University of Düsseldorf19, National Institute of Standards and Technology20, Max Planck Society21, Baylor College of Medicine22, University of California, Davis23, Institute for Systems Biology24, Duke University25, University of Pittsburgh26, Russian Academy of Sciences27
TL;DR: The T2T-CHM13 reference as mentioned in this paper contains gapless assemblies for all 22 autosomes plus Chromosome X, corrected numerous errors, and introduced nearly 200 million bp of novel sequence containing 2,226 paralogous gene copies, 115 of which are predicted to be protein coding.
Abstract: In 2001, Celera Genomics and the International Human Genome Sequencing Consortium published their initial drafts of the human genome, which revolutionized the field of genomics. While these drafts and the updates that followed effectively covered the euchromatic fraction of the genome, the heterochromatin and many other complex regions were left unfinished or erroneous. Addressing this remaining 8% of the genome, the Telomere-to-Telomere (T2T) Consortium has finished the first truly complete 3.055 billion base pair (bp) sequence of a human genome, representing the largest improvement to the human reference genome since its initial release. The new T2T-CHM13 reference includes gapless assemblies for all 22 autosomes plus Chromosome X, corrects numerous errors, and introduces nearly 200 million bp of novel sequence containing 2,226 paralogous gene copies, 115 of which are predicted to be protein coding. The newly completed regions include all centromeric satellite arrays and the short arms of all five acrocentric chromosomes, unlocking these complex regions of the genome to variational and functional studies for the first time.
108 citations
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Center for Biologics Evaluation and Research1, Institute for Systems Biology2, National Institutes of Health3, University of Illinois at Urbana–Champaign4, St. John's University5, University of Southern California6, Harborview Medical Center7, University of Vermont Medical Center8, New York University9, Memorial Sloan Kettering Cancer Center10
84 citations
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TL;DR: The B.1.2 variant of SARS-CoV-2 is emerging as the dominant variant in England, evidenced by sustained local transmission as mentioned in this paper, with a doubling time between 5-14 days.
Abstract: The rapid emergence of SARS-CoV-2 mutants with new phenotypic properties is a critical challenge to the control of the ongoing pandemic. B.1.1.7 was monitored in the UK through routine testing and S-gene target failures (SGTF), comprising over 90% of cases by March 2021. Now, the reverse is occurring: SGTF cases are being replaced by an S-gene positive variant, which we associate with B.1.617.2. Evidence from the characteristics of S-gene positive cases demonstrates that, following importation, B.1.617.2 is transmitted locally, growing at a rate higher than B.1.1.7 and a doubling time between 5-14 days. S-gene positive cases should be prioritised for sequencing and aggressive control in any countries in which this variant is newly detected. One-Sentence Summary The B.1.617.2 variant of SARS-CoV-2 is replacing B.1.1.7 and emerging as the dominant variant in England, evidenced by sustained local transmission.
65 citations
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TL;DR: In this article, metabolic changes associated with the peripheral immune response of 198 individuals with COVID-19 through an integrated analysis of plasma metabolite and protein levels as well as single-cell multiomics analyses from serial blood draws collected during the first week after clinical diagnosis.
Abstract: A better understanding of the metabolic alterations in immune cells during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection may elucidate the wide diversity of clinical symptoms experienced by individuals with coronavirus disease 2019 (COVID-19). Here, we report the metabolic changes associated with the peripheral immune response of 198 individuals with COVID-19 through an integrated analysis of plasma metabolite and protein levels as well as single-cell multiomics analyses from serial blood draws collected during the first week after clinical diagnosis. We document the emergence of rare but metabolically dominant T cell subpopulations and find that increasing disease severity correlates with a bifurcation of monocytes into two metabolically distinct subsets. This integrated analysis reveals a robust interplay between plasma metabolites and cell-type-specific metabolic reprogramming networks that is associated with disease severity and could predict survival.
64 citations
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University of California, San Francisco1, Lawrence Berkeley National Laboratory2, Beckman Research Institute3, Qatar Computing Research Institute4, Lebanese University5, Institute for Systems Biology6, Qatar Airways7, Khalifa University8, Leiden University Medical Center9, Barcelona Supercomputing Center10, Cornell University11, New York University12, University of Chicago13, University of Calgary14, University of Sannio15, Ontario Institute for Cancer Research16, University of Naples Federico II17, University of Paris18, University of Genoa19
TL;DR: In this article, the authors investigated the effect of common and rare germline variants on 139 well-defined immune traits in ∼9000 cancer patients enrolled in TCGA and found that high heritability was observed for estimates of NK cell and T-cell subset infiltration and for interferon signaling.
64 citations
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TL;DR: Zafra et al. as mentioned in this paper established the first human forward genetic modeling of a commonly mutated tumor suppressor gene, ARID1A, by integrating diverse modalities including CRISPR/Cas9 genome editing, organoid culture, systems biology, and small-molecule screening to derive novel insights into early transformation mechanisms of ARID 1A-deficient gastric cancers.
Abstract: Mutations in ARID1A rank among the most common molecular aberrations in human cancer. However, oncogenic consequences of ARID1A mutation in human cells remain poorly defined due to lack of forward genetic models. Here, CRISPR/Cas9-mediated ARID1A knockout (KO) in primary TP53-/- human gastric organoids induced morphologic dysplasia, tumorigenicity, and mucinous differentiation. Genetic WNT/β-catenin activation rescued mucinous differentiation, but not hyperproliferation, suggesting alternative pathways of ARID1A KO-mediated transformation. ARID1A mutation induced transcriptional regulatory modules characteristic of microsatellite instability and Epstein-Barr virus-associated subtype human gastric cancer, including FOXM1-associated mitotic genes and BIRC5/survivin. Convergently, high-throughput compound screening indicated selective vulnerability of ARID1A-deficient organoids to inhibition of BIRC5/survivin, functionally implicating this pathway as an essential mediator of ARID1A KO-dependent early-stage gastric tumorigenesis. Overall, we define distinct pathways downstream of oncogenic ARID1A mutation, with nonessential WNT-inhibited mucinous differentiation in parallel with essential transcriptional FOXM1/BIRC5-stimulated proliferation, illustrating the general utility of organoid-based forward genetic cancer analysis in human cells. SIGNIFICANCE: We establish the first human forward genetic modeling of a commonly mutated tumor suppressor gene, ARID1A. Our study integrates diverse modalities including CRISPR/Cas9 genome editing, organoid culture, systems biology, and small-molecule screening to derive novel insights into early transformation mechanisms of ARID1A-deficient gastric cancers.See related commentary by Zafra and Dow, p. 1327.This article is highlighted in the In This Issue feature, p. 1307.
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TL;DR: In this article, the authors determined thermal tolerance thresholds of GoA versus central Red Sea (CRS) Stylophora pistillata corals using multi-temperature acute thermal stress assays to determine thermal thresholds.
Abstract: Corals from the northern Red Sea, in particular the Gulf of Aqaba (GoA), have exceptionally high bleaching thresholds approaching >5℃ above their maximum monthly mean (MMM) temperatures. These elevated thresholds are thought to be due to historical selection, as corals passed through the warmer Southern Red Sea during recolonization from the Arabian Sea. To test this hypothesis, we determined thermal tolerance thresholds of GoA versus central Red Sea (CRS) Stylophora pistillata corals using multi-temperature acute thermal stress assays to determine thermal thresholds. Relative thermal thresholds of GoA and CRS corals were indeed similar and exceptionally high (~7℃ above MMM). However, absolute thermal thresholds of CRS corals were on average 3℃ above those of GoA corals. To explore the molecular underpinnings, we determined gene expression and microbiome response of the coral holobiont. Transcriptomic responses differed markedly, with a strong response to the thermal stress in GoA corals and their symbiotic algae versus a remarkably muted response in CRS colonies. Concomitant to this, coral and algal genes showed temperature-induced expression in GoA corals, while exhibiting fixed high expression (front-loading) in CRS corals. Bacterial community composition of GoA corals changed dramatically under heat stress, whereas CRS corals displayed stable assemblages. We interpret the response of GoA corals as that of a resilient population approaching a tipping point in contrast to a pattern of consistently elevated thermal resistance in CRS corals that cannot further attune. Such response differences suggest distinct thermal tolerance mechanisms that may affect the response of coral populations to ocean warming.
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University of California, San Francisco1, University of California, Los Angeles2, University of Texas MD Anderson Cancer Center3, Fred Hutchinson Cancer Research Center4, Memorial Sloan Kettering Cancer Center5, University of Pennsylvania6, University of Florida7, National Institutes of Health8, Northwestern University9, Heidelberg University10, Institute for Systems Biology11, Johns Hopkins University12, City of Hope National Medical Center13, Harvard University14, Duke University15, Washington University in St. Louis16, German Cancer Research Center17
TL;DR: The 2019 Immuno-Oncology Think Tank Meeting was held during the 2019 Annual Society for Neuro Oncology Scientific Conference as mentioned in this paper, which focused on topics such as the tumor microenvironment, myeloid cells and T-cell dysfunction, cellular engineering, and translational aspects that are critical and unique challenges inherent with primary brain tumors.
Abstract: Cancer immunotherapy has made remarkable advances with over fifty separate Food and Drug Administration (FDA) approvals as first or second line indications since 2015. These include immune checkpoint blocking antibodies, chimeric antigen receptor-transduced T-cells and bispecific T-cell-engaging antibodies. While multiple cancer types now benefit from these immunotherapies, notable exceptions thus far include brain tumors, such as glioblastoma. As such, it seems critical to gain a better understanding of unique mechanistic challenges underlying the resistance of malignant gliomas to immunotherapy, as well as to acquire insights in the development of future strategies. An Immuno-Oncology Think Tank Meeting was held during the 2019 Annual Society for Neuro-Oncology Scientific Conference. Discussants in the fields of neuro-oncology, neurosurgery, neuro-imaging, medical oncology, and cancer immunology participated in the meeting. Sessions focused on topics such as the tumor microenvironment, myeloid cells and T-cell dysfunction, cellular engineering, and translational aspects that are critical and unique challenges inherent with primary brain tumors. In this review, we summarize the discussions and the key messages from the meeting, which may potentially serve as a basis for advancing the field of immune neuro-oncology in a collaborative manner.
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TL;DR: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Abstract: DNA methylation patterns at specific cytosine-phosphate-guanine (CpG) sites predictably change with age and can be used to derive “epigenetic age”, an indicator of biological age, as opposed to merely chronological age. A relatively new estimator, called “DNAm GrimAge”, is notable for its superior predictive ability in older populations regarding numerous age-related metrics like time-to-death, time-to-coronary heart disease, and time-to-cancer. PTSD is associated with premature mortality and frequently has comorbid physical illnesses suggestive of accelerated biological aging. This is the first study to assess DNAm GrimAge in PTSD patients. We investigated the acceleration of GrimAge relative to chronological age, denoted “AgeAccelGrim” in combat trauma-exposed male veterans with and without PTSD using cross-sectional and longitudinal data from two independent well-characterized veteran cohorts. In both cohorts, AgeAccelGrim was significantly higher in the PTSD group compared to the control group (N = 162, 1.26 vs −0.57, p = 0.001 and N = 53, 0.93 vs −1.60 Years, p = 0.008), suggesting accelerated biological aging in both cohorts with PTSD. In 3-year follow-up study of individuals initially diagnosed with PTSD (N = 26), changes in PTSD symptom severity were correlated with AgeAccelGrim changes (r = 0.39, p = 0.049). In addition, the loss of CD28 cell surface markers on CD8 + T cells, an indicator of T-cell senescence/exhaustion that is associated with biological aging, was positively correlated with AgeAccelGrim, suggesting an immunological contribution to the accelerated biological aging. Overall, our findings delineate cellular correlates of biological aging in combat-related PTSD, which may help explain the increased medical morbidity and mortality seen in this disease.
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TL;DR: The Human Extracellular Vesicle Peptide Atlas (HPPP) as mentioned in this paper was built in 2011 and contains 4395 canonical and 1482 additional nonredundant human proteins detected in 240 mass-spectrometry (MS)-based experiments.
Abstract: The study of proteins circulating in blood offers tremendous opportunities to diagnose, stratify, or possibly prevent diseases. With recent technological advances and the urgent need to understand the effects of COVID-19, the proteomic analysis of blood-derived serum and plasma has become even more important for studying human biology and pathophysiology. Here we provide views and perspectives about technological developments and possible clinical applications that use mass-spectrometry(MS)- or affinity-based methods. We discuss examples where plasma proteomics contributed valuable insights into SARS-CoV-2 infections, aging, and hemostasis and the opportunities offered by combining proteomics with genetic data. As a contribution to the Human Proteome Organization (HUPO) Human Plasma Proteome Project (HPPP), we present the Human Plasma PeptideAtlas build 2021-07 that comprises 4395 canonical and 1482 additional nonredundant human proteins detected in 240 MS-based experiments. In addition, we report the new Human Extracellular Vesicle PeptideAtlas 2021-06, which comprises five studies and 2757 canonical proteins detected in extracellular vesicles circulating in blood, of which 74% (2047) are in common with the plasma PeptideAtlas. Our overview summarizes the recent advances, impactful applications, and ongoing challenges for translating plasma proteomics into utility for precision medicine.
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University of Luxembourg1, Institute for Systems Biology2, Indiana University3, Translational Genomics Research Institute4, Harvard University5, George Washington University6, Northern Arizona University7, Katholieke Universiteit Leuven8, University of California, Los Angeles9, University of Strasbourg10
TL;DR: In this paper, the authors analyzed generation-resolved iMGE-host dynamics spanning one and a half years in a microbial consortium from a biological wastewater treatment plant using integrated meta-omics.
Abstract: Viruses and plasmids (invasive mobile genetic elements (iMGEs)) have important roles in shaping microbial communities, but their dynamic interactions with CRISPR-based immunity remain unresolved. We analysed generation-resolved iMGE–host dynamics spanning one and a half years in a microbial consortium from a biological wastewater treatment plant using integrated meta-omics. We identified 31 bacterial metagenome-assembled genomes encoding complete CRISPR–Cas systems and their corresponding iMGEs. CRISPR-targeted plasmids outnumbered their bacteriophage counterparts by at least fivefold, highlighting the importance of CRISPR-mediated defence against plasmids. Linear modelling of our time-series data revealed that the variation in plasmid abundance over time explained more of the observed community dynamics than phages. Community-scale CRISPR-based plasmid–host and phage–host interaction networks revealed an increase in CRISPR-mediated interactions coinciding with a decrease in the dominant ‘Candidatus Microthrix parvicella’ population. Protospacers were enriched in sequences targeting genes involved in the transmission of iMGEs. Understanding the factors shaping the fitness of specific populations is necessary to devise control strategies for undesirable species and to predict or explain community-wide phenotypes. CRISPR-based immunity and microbial community dynamics in a wastewater treatment plant over one and a half years.
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TL;DR: In this paper, the authors illustrate how metabolically distinct species of Clostridia protect against or worsen Clostrichioides difficile infection in mice by modulating the pathogen's colonization, growth, and virulence to impact host survival.
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TL;DR: In this article, three COVID-19 epidemic waves have been observed in Kenya and the first two distinct waves were explained by differences in contact rates in high and low social-economic groups, and the third wave by the introduction of higher transmissibility variants.
Abstract: Policy decisions on COVID-19 interventions should be informed by a local, regional and national understanding of SARS-CoV-2 transmission. Epidemic waves may result when restrictions are lifted or poorly adhered to, variants with new phenotypic properties successfully invade, or when infection spreads to susceptible sub-populations. Three COVID-19 epidemic waves have been observed in Kenya. Using a mechanistic mathematical model, we explain the first two distinct waves by differences in contact rates in high and low social-economic groups, and the third wave by the introduction of higher-transmissibility variants. Reopening schools led to a minor increase in transmission between the second and third waves. Socio-economic and urban/rural population structure are critical determinants of viral transmission in Kenya.
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TL;DR: The authors reviewed recent evidence for non-genetic mechanisms of progression, explain the theoretical foundation of attractor transitions behind treatment-induced increase of aggressiveness, and provide a framework for unifying genetic and nongenetic dynamics in tumor progression.
Abstract: Post-treatment progression of tumors is commonly explained by somatic Darwinian evolution (ie, selection of cells carrying genetic mutations that create more aggressive cell traits) But cancer genome and transcriptome analyses now paint a picture far more complex, prompting us to see beyond the Darwinian scheme: non-genetic cell phenotype plasticity explained by alternative stable gene expression states ('attractors'), may also produce aggressive phenotypes that can be selected for, without mutations Worse, treatment may even induce cell state transitions into more malignant attractors We review recent evidence for non-genetic mechanisms of progression, explain the theoretical foundation of attractor transitions behind treatment-induced increase of aggressiveness, and provide a framework for unifying genetic and non-genetic dynamics in tumor progression
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TL;DR: The first animal mitochondrial genomes to be sequenced were of several vertebrates and model organisms, and the consistency of genomic features found has led to a 'textbook description'.
Abstract: The first animal mitochondrial genomes to be sequenced were of several vertebrates and model organisms, and the consistency of genomic features found has led to a 'textbook description'. However, a more broad phylogenetic sampling of complete animal mitochondrial genomes has found many cases where these features do not exist, and the phylum Mollusca is especially replete with these exceptions. The characterization of full mollusc mitogenomes required considerable effort involving challenging molecular biology, but has created an enormous catalogue of surprising deviations from that textbook description, including wide variation in size, radical genome rearrangements, gene duplications and losses, the introduction of novel genes, and a complex system of inheritance dubbed 'doubly uniparental inheritance'. Here, we review the extraordinary variation in architecture, molecular functioning and intergenerational transmission of molluscan mitochondrial genomes. Such features represent a great potential for the discovery of biological history, processes and functions that are novel for animal mitochondrial genomes. This provides a model system for studying the evolution and the manifold roles that mitochondria play in organismal physiology, and many ways that the study of mitochondrial genomes are useful for phylogeny and population biology. This article is part of the Theo Murphy meeting issue 'Molluscan genomics: broad insights and future directions for a neglected phylum'.
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TL;DR: In this article, the authors compared eight strategies for reopening primary and secondary schools in England and found that while any school reopening will result in increased mixing and infection amongst children and the wider population, reopening schools alone in June 2020 was unlikely to push R above one.
Abstract: By mid-May 2020, cases of COVID-19 in the UK had been declining for over a month; a multi-phase emergence from lockdown was planned, including a scheduled partial reopening of schools on 1 June 2020. Although evidence suggests that children generally display mild symptoms, the size of the school-age population means the total impact of reopening schools is unclear. Here, we present work from mid-May 2020 that focused on the imminent opening of schools and consider what these results imply for future policy. We compared eight strategies for reopening primary and secondary schools in England. Modifying a transmission model fitted to UK SARS-CoV-2 data, we assessed how reopening schools affects contact patterns, anticipated secondary infections and the relative change in the reproduction number, R. We determined the associated public health impact and its sensitivity to changes in social distancing within the wider community. We predicted that reopening schools with half-sized classes or focused on younger children was unlikely to push R above one. Older children generally have more social contacts, so reopening secondary schools results in more cases than reopening primary schools, while reopening both could have pushed R above one in some regions. Reductions in community social distancing were found to outweigh and exacerbate any impacts of reopening. In particular, opening schools when the reproduction number R is already above one generates the largest increase in cases. Our work indicates that while any school reopening will result in increased mixing and infection amongst children and the wider population, reopening schools alone in June 2020 was unlikely to push R above one. Ultimately, reopening decisions are a difficult trade-off between epidemiological consequences and the emotional, educational and developmental needs of children. Into the future, there are difficult questions about what controls can be instigated such that schools can remain open if cases increase. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.
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TL;DR: In this paper, the authors integrated 4,780 blood transcriptome profiles from patients aged 0 to 90 years infected with one of 16 viruses, including SARS-CoV-2, Ebola, chikungunya, and influenza, across 34 cohorts from 18 countries, and single-cell RNA sequencing profiles of 702,970 immune cells from 289 samples across three cohorts.
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Icahn School of Medicine at Mount Sinai1, Life Sciences Institute2, Tulane University3, Institute for Systems Biology4, Zhejiang University5, Johns Hopkins University School of Medicine6, Institute of Ecosystem Studies7, VCU Medical Center8, Bard College9, Northeastern University10, Yale University11, North Carolina State University12, Indiana University13, University of California, Los Angeles14, University of California, Davis15, Columbia University16
TL;DR: In this paper, a review article summarizes progress over the past 5 years in understanding of Lyme and tick-borne diseases in the United States and highlights remaining challenges, highlighting the urgent need for more support.
Abstract: Lyme disease (also known as Lyme borreliosis) is the most common vector-borne disease in the United States with an estimated 476,000 cases per year. While historically, the long-term impact of Lyme disease on patients has been controversial, mounting evidence supports the idea that a substantial number of patients experience persistent symptoms following treatment. The research community has largely lacked the necessary funding to properly advance the scientific and clinical understanding of the disease, or to develop and evaluate innovative approaches for prevention, diagnosis, and treatment. Given the many outstanding questions raised into the diagnosis, clinical presentation and treatment of Lyme disease, and the underlying molecular mechanisms that trigger persistent disease, there is an urgent need for more support. This review article summarizes progress over the past 5 years in our understanding of Lyme and tick-borne diseases in the United States and highlights remaining challenges.
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Institute for Systems Biology1, European Bioinformatics Institute2, University of Montana3, Toyama University of International Studies4, Ghent University5, University of Lausanne6, Thermo Fisher Scientific7, University of Antwerp8, National Institute of Standards and Technology9, Boston University10, Protein Sciences11, Hong Kong University of Science and Technology12
TL;DR: The Universal Spectrum Identifier (USI) as mentioned in this paper provides a standardized mechanism for encoding a virtual path to any mass spectrum contained in datasets deposited to public proteomics repositories, enabling greater transparency of spectral evidence, with over 1 billion USI identifications from over 3 billion spectra already available through ProteomeXchange repositories.
Abstract: Mass spectra provide the ultimate evidence to support the findings of mass spectrometry proteomics studies in publications, and it is therefore crucial to be able to trace the conclusions back to the spectra. The Universal Spectrum Identifier (USI) provides a standardized mechanism for encoding a virtual path to any mass spectrum contained in datasets deposited to public proteomics repositories. USI enables greater transparency of spectral evidence, with more than 1 billion USI identifications from over 3 billion spectra already available through ProteomeXchange repositories.
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TL;DR: In this paper, the authors evaluated the sociodemographic and clinical characteristics of patients across racial/ethnic groups and assessed their associations with COVID-19 outcomes with multivariate logistic regression.
Abstract: Background Data on the characteristics of COVID-19 patients disaggregated by race/ethnicity remain limited. We evaluated the sociodemographic and clinical characteristics of patients across racial/ethnic groups and assessed their associations with COVID-19 outcomes. Methods This retrospective cohort study examined 629,953 patients tested for SARS-CoV-2 in a large health system spanning California, Oregon, and Washington between March 1 and December 31, 2020. Sociodemographic and clinical characteristics were obtained from electronic health records. Odds of SARS-CoV-2 infection, COVID-19 hospitalization, and in-hospital death were assessed with multivariate logistic regression. Results 570,298 patients with known race/ethnicity were tested for SARS-CoV-2, of whom 27.8% were non-White minorities. 54,645 individuals tested positive, with minorities representing 50.1%. Hispanics represented 34.3% of infections but only 13.4% of tests. While generally younger than White patients, Hispanics had higher rates of diabetes but fewer other comorbidities. 8,536 patients were hospitalized and 1,246 died, of whom 56.1% and 54.4% were non-White, respectively. Racial/ethnic distributions of outcomes across the health system tracked with state-level statistics. Increased odds of testing positive and hospitalization were associated with all minority races/ethnicities. Hispanic patients also exhibited increased morbidity, and Hispanic race/ethnicity was associated with in-hospital mortality (OR: 1.39 [95% CI: 1.14-1.70]). Conclusion Major healthcare disparities were evident, especially among Hispanics who tested positive at a higher rate, required excess hospitalization and mechanical ventilation, and had higher odds of in-hospital mortality despite younger age. Targeted, culturally-responsive interventions and equitable vaccine development and distribution are needed to address the increased risk of poorer COVID-19 outcomes among minority populations.
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TL;DR: The COVID-19 Disease Map (C19DMap) as mentioned in this paper is a large-scale community effort to build an open access, interoperable and computable repository of COVID19 molecular mechanisms.
Abstract: We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.
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TL;DR: In this article, a review of the evolution of mathematical biology and pharmacology models is presented, highlighting some of the gaps and challenges in developing and applying systems pharmacology model and providing a vision for an integrated strategy that leverages advances in adjacent fields to overcome these challenges.
Abstract: Mathematical biology and pharmacology models have a long and rich history in the fields of medicine and physiology, impacting our understanding of disease mechanisms and the development of novel therapeutics. With an increased focus on the pharmacology application of system models and the advances in data science spanning mechanistic and empirical approaches, there is a significant opportunity and promise to leverage these advancements to enhance the development and application of the systems pharmacology field. In this paper, we will review milestones in the evolution of mathematical biology and pharmacology models, highlight some of the gaps and challenges in developing and applying systems pharmacology models, and provide a vision for an integrated strategy that leverages advances in adjacent fields to overcome these challenges.
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Chongqing University of Posts and Telecommunications1, European Bioinformatics Institute2, Free University of Berlin3, Zuse Institute Berlin4, Russian Academy of Sciences5, Moscow Institute of Physics and Technology6, University of Freiburg7, Northeastern University8, Medical University of Vienna9, University of Bergen10, University of Copenhagen11, Ruhr University Bochum12, Ghent University13, University of Southern Denmark14, University of Pennsylvania15, University of Toulouse16, Technische Universität München17, Genentech18, University of Montana19, University of Tübingen20, Institute for Systems Biology21, Protein Sciences22
TL;DR: In this article, the authors propose a standard representation for proteomics sample metadata, called MAGE-TAB-Proteomics, which is used to describe the sample metadata and their relationship with the dataset files in a way that fully supports their understanding or reanalysis.
Abstract: The amount of public proteomics data is rapidly increasing but there is no standardized format to describe the sample metadata and their relationship with the dataset files in a way that fully supports their understanding or reanalysis. Here we propose to develop the transcriptomics data format MAGE-TAB into a standard representation for proteomics sample metadata. We implement MAGE-TAB-Proteomics in a crowdsourcing project to manually curate over 200 public datasets. We also describe tools and libraries to validate and submit sample metadata-related information to the PRIDE repository. We expect that these developments will improve the reproducibility and facilitate the reanalysis and integration of public proteomics datasets.
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Institut national des sciences Appliquées de Lyon1, Pompeu Fabra University2, University of Valencia3, University of Lyon4, Cornell University5, McGill University6, Katholieke Universiteit Leuven7, French Institute for Research in Computer Science and Automation8, SupAgro9, University of Paris10, École normale supérieure de Lyon11, Institute for Systems Biology12, University of Melbourne13, École Polytechnique Fédérale de Lausanne14, University of Rennes15, University of Mainz16
TL;DR: In this article, the rice weevil Sitophilus oryzae was sequenced using a combination of short and long reads to produce the best assembly for a Curculionidae species to date.
Abstract: Background The rice weevil Sitophilus oryzae is one of the most important agricultural pests, causing extensive damage to cereal in fields and to stored grains. S. oryzae has an intracellular symbiotic relationship (endosymbiosis) with the Gram-negative bacterium Sodalis pierantonius and is a valuable model to decipher host-symbiont molecular interactions. Results We sequenced the Sitophilus oryzae genome using a combination of short and long reads to produce the best assembly for a Curculionidae species to date. We show that S. oryzae has undergone successive bursts of transposable element (TE) amplification, representing 72% of the genome. In addition, we show that many TE families are transcriptionally active, and changes in their expression are associated with insect endosymbiotic state. S. oryzae has undergone a high gene expansion rate, when compared to other beetles. Reconstruction of host-symbiont metabolic networks revealed that, despite its recent association with cereal weevils (30 kyear), S. pierantonius relies on the host for several amino acids and nucleotides to survive and to produce vitamins and essential amino acids required for insect development and cuticle biosynthesis. Conclusions Here we present the genome of an agricultural pest beetle, which may act as a foundation for pest control. In addition, S. oryzae may be a useful model for endosymbiosis, and studying TE evolution and regulation, along with the impact of TEs on eukaryotic genomes.