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A new study by the Cornall group provides new insights into the importance of zinc in human health.
Single-cell atlas of colonic CD8+ T cells in ulcerative colitis.
Colonic antigen-experienced lymphocytes such as tissue-resident memory CD8+ T cells can respond rapidly to repeated antigen exposure. However, their cellular phenotypes and the mechanisms by which they drive immune regulation and inflammation remain unclear. Here we compiled an unbiased atlas of human colonic CD8+ T cells in health and ulcerative colitis (UC) using single-cell transcriptomics with T-cell receptor repertoire analysis and mass cytometry. We reveal extensive heterogeneity in CD8+ T-cell composition, including expanded effector and post-effector terminally differentiated CD8+ T cells. While UC-associated CD8+ effector T cells can trigger tissue destruction and produce tumor necrosis factor (TNF)-α, post-effector cells acquire innate signatures to adopt regulatory functions that may mitigate excessive inflammation. Thus, we identify colonic CD8+ T-cell phenotypes in health and UC, define their clonal relationships and characterize terminally differentiated dysfunctional UC CD8+ T cells expressing IL-26, which attenuate acute colitis in a humanized IL-26 transgenic mouse model.
Structural Remodeling of the Human Colonic Mesenchyme in Inflammatory Bowel Disease.
Intestinal mesenchymal cells play essential roles in epithelial homeostasis, matrix remodeling, immunity, and inflammation. But the extent of heterogeneity within the colonic mesenchyme in these processes remains unknown. Using unbiased single-cell profiling of over 16,500 colonic mesenchymal cells, we reveal four subsets of fibroblasts expressing divergent transcriptional regulators and functional pathways, in addition to pericytes and myofibroblasts. We identified a niche population located in proximity to epithelial crypts expressing SOX6, F3 (CD142), and WNT genes essential for colonic epithelial stem cell function. In colitis, we observed dysregulation of this niche and emergence of an activated mesenchymal population. This subset expressed TNF superfamily member 14 (TNFSF14), fibroblastic reticular cell-associated genes, IL-33, and Lysyl oxidases. Further, it induced factors that impaired epithelial proliferation and maturation and contributed to oxidative stress and disease severity in vivo. Our work defines how the colonic mesenchyme remodels to fuel inflammation and barrier dysfunction in IBD.
In silico identification of vaccine targets for 2019-nCoV.
Background: The newly identified coronavirus known as 2019-nCoV has posed a serious global health threat. According to the latest report (18-February-2020), it has infected more than 72,000 people globally and led to deaths of more than 1,016 people in China. Methods: The 2019 novel coronavirus proteome was aligned to a curated database of viral immunogenic peptides. The immunogenicity of detected peptides and their binding potential to HLA alleles was predicted by immunogenicity predictive models and NetMHCpan 4.0. Results: We report in silico identification of a comprehensive list of immunogenic peptides that can be used as potential targets for 2019 novel coronavirus (2019-nCoV) vaccine development. First, we found 28 nCoV peptides identical to Severe acute respiratory syndrome-related coronavirus (SARS CoV) that have previously been characterized immunogenic by T cell assays. Second, we identified 48 nCoV peptides having a high degree of similarity with immunogenic peptides deposited in The Immune Epitope Database (IEDB). Lastly, we conducted a de novo search of 2019-nCoV 9-mer peptides that i) bind to common HLA alleles in Chinese and European population and ii) have T Cell Receptor (TCR) recognition potential by positional weight matrices and a recently developed immunogenicity algorithm, iPred, and identified in total 63 peptides with a high immunogenicity potential. Conclusions: Given the limited time and resources to develop vaccine and treatments for 2019-nCoV, our work provides a shortlist of candidates for experimental validation and thus can accelerate development pipeline.
Local Chromatin Features Including PU.1 and IKAROS Binding and H3K4 Methylation Shape the Repertoire of Immunoglobulin Kappa Genes Chosen for V(D)J Recombination.
V(D)J recombination is essential for the generation of diverse antigen receptor (AgR) repertoires. In B cells, immunoglobulin kappa (Igκ) light chain recombination follows immunoglobulin heavy chain (Igh) recombination. We recently developed the DNA-based VDJ-seq assay for the unbiased quantitation of Igh VH and DH repertoires. Integration of VDJ-seq data with genome-wide datasets revealed that two chromatin states at the recombination signal sequence (RSS) of VH genes are highly predictive of recombination in mouse pro-B cells. It is unknown whether local chromatin states contribute to Vκ gene choice during Igκ recombination. Here we adapt VDJ-seq to profile the Igκ VκJκ repertoire and present a comprehensive readout in mouse pre-B cells, revealing highly variable Vκ gene usage. Integration with genome-wide datasets for histone modifications, DNase hypersensitivity, transcription factor binding and germline transcription identified PU.1 binding at the RSS, which was unimportant for Igh, as highly predictive of whether a Vκ gene will recombine or not, suggesting that it plays a binary, all-or-nothing role, priming genes for recombination. Thereafter, the frequency with which these genes recombine was shaped both by the presence and level of enrichment of several other chromatin features, including H3K4 methylation and IKAROS binding. Moreover, in contrast to the Igh locus, the chromatin landscape of the promoter, as well as of the RSS, contributes to Vκ gene recombination. Thus, multiple facets of local chromatin features explain much of the variation in Vκ gene usage. Together, these findings reveal shared and divergent roles for epigenetic features and transcription factors in AgR V(D)J recombination and provide avenues for further investigation of chromatin signatures that may underpin V(D)J-mediated chromosomal translocations.
The rise and fall of machine learning methods in biomedical research.
In the era of explosion in biological data, machine learning techniques are becoming more popular in life sciences, including biology and medicine. This research note examines the rise and fall of the most commonly used machine learning techniques in life sciences over the past three decades.
A comparison of peak callers used for DNase-Seq data.
Genome-wide profiling of open chromatin regions using DNase I and high-throughput sequencing (DNase-seq) is an increasingly popular approach for finding and studying regulatory elements. A variety of algorithms have been developed to identify regions of open chromatin from raw sequence-tag data, which has motivated us to assess and compare their performance. In this study, four published, publicly available peak calling algorithms used for DNase-seq data analysis (F-seq, Hotspot, MACS and ZINBA) are assessed at a range of signal thresholds on two published DNase-seq datasets for three cell types. The results were benchmarked against an independent dataset of regulatory regions derived from ENCODE in vivo transcription factor binding data for each particular cell type. The level of overlap between peak regions reported by each algorithm and this ENCODE-derived reference set was used to assess sensitivity and specificity of the algorithms. Our study suggests that F-seq has a slightly higher sensitivity than the next best algorithms. Hotspot and the ChIP-seq oriented method, MACS, both perform competitively when used with their default parameters. However the generic peak finder ZINBA appears to be less sensitive than the other three. We also assess accuracy of each algorithm over a range of signal thresholds. In particular, we show that the accuracy of F-Seq can be considerably improved by using a threshold setting that is different from the default value.
Chromatin accessibility data sets show bias due to sequence specificity of the DNase I enzyme.
BACKGROUND: DNase I is an enzyme which cuts duplex DNA at a rate that depends strongly upon its chromatin environment. In combination with high-throughput sequencing (HTS) technology, it can be used to infer genome-wide landscapes of open chromatin regions. Using this technology, systematic identification of hundreds of thousands of DNase I hypersensitive sites (DHS) per cell type has been possible, and this in turn has helped to precisely delineate genomic regulatory compartments. However, to date there has been relatively little investigation into possible biases affecting this data. RESULTS: We report a significant degree of sequence preference spanning sites cut by DNase I in a number of published data sets. The two major protocols in current use each show a different pattern, but for a given protocol the pattern of sequence specificity seems to be quite consistent. The patterns are substantially different from biases seen in other types of HTS data sets, and in some cases the most constrained position lies outside the sequenced fragment, implying that this constraint must relate to the digestion process rather than events occurring during library preparation or sequencing. CONCLUSIONS: DNase I is a sequence-specific enzyme, with a specificity that may depend on experimental conditions. This sequence specificity is not taken into account by existing pipelines for identifying open chromatin regions. Care must be taken when interpreting DNase I results, especially when looking at the precise locations of the reads. Future studies may be able to improve the sensitivity and precision of chromatin state measurement by compensating for sequence bias.
Is DNA a worm-like chain in Couette flow? In search of persistence length, a critical review.
Persistence length is the foremost measure of DNA flexibility. Its origins lie in polymer theory which was adapted for DNA following the determination of BDNA structure in 1953. There is no single definition of persistence length used, and the links between published definitions are based on assumptions which may, or may not be, clearly stated. DNA flexibility is affected by local ionic strength, solvent environment, bound ligands and intrinsic sequence-dependent flexibility. This article is a review of persistence length providing a mathematical treatment of the relationships between four definitions of persistence length, including: correlation, Kuhn length, bending, and curvature. Persistence length has been measured using various microscopy, force extension and solution methods such as linear dichroism and transient electric birefringence. For each experimental method a model of DNA is required to interpret the data. The importance of understanding the underlying models, along with the assumptions required by each definition to determine a value of persistence length, is highlighted for linear dichroism data, where it transpires that no model is currently available for long DNA or medium to high shear rate experiments.
SARS-CoV-2 peptides bind to NKG2D and increase NK cell activity.
Immune dysregulation is commonly observed in patients with coronavirus disease 2019 (COVID-19). Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induces severe lung inflammation and innate immune cell dysregulation. However, the precise interaction between SARS-CoV-2 and the innate immune system is currently unknown. To understand the interaction between SARS-CoV-2 and natural killer (NK) cells, several SARS-CoV-2 S protein peptides capable of binding to the NKG2D receptor were screened by in silico analysis. Among them, two peptides, cov1 and cov2, bound to NK cells and NKG2D receptors. These cov peptides increased NK cytotoxicity toward lung cancer cells, stimulated interferon gamma (IFN-γ) production by NK cells, and likely mediated these responses through the phosphorylation of Vav1, a key downstream-signaling molecule of NKG2D and NK activation genes. The direct interaction between SARS-CoV-2 and NK cells is a novel finding, and modulation of this interaction has potential clinical application as a therapeutic target for COVID-19.
A new phosphate-starvation response in fission yeast requires the endocytic function of myosin I.
Endocytosis is essential for uptake of many substances into the cell, but how it links to nutritional signalling is poorly understood. Here, we show a new role for endocytosis in regulating the response to low phosphate in Schizosaccharomyces pombe. Loss of function of myosin I (Myo1), Sla2/End4 or Arp2, proteins involved in the early steps of endocytosis, led to increased proliferation in low-phosphate medium compared to controls. We show that once cells are deprived of phosphate they undergo a quiescence response that is dependent on the endocytic function of Myo1. Transcriptomic analysis revealed a wide perturbation of gene expression with induction of stress-regulated genes upon phosphate starvation in wild-type but not Δmyo1 cells. Thus, endocytosis plays a pivotal role in mediating the cellular response to nutrients, bridging the external environment and internal molecular functions of the cell.
Two Mutually Exclusive Local Chromatin States Drive Efficient V(D)J Recombination.
Variable (V), diversity (D), and joining (J) (V(D)J) recombination is the first determinant of antigen receptor diversity. Understanding how recombination is regulated requires a comprehensive, unbiased readout of V gene usage. We have developed VDJ sequencing (VDJ-seq), a DNA-based next-generation-sequencing technique that quantitatively profiles recombination products. We reveal a 200-fold range of recombination efficiency among recombining V genes in the primary mouse Igh repertoire. We used machine learning to integrate these data with local chromatin profiles to identify combinatorial patterns of epigenetic features that associate with active VH gene recombination. These features localize downstream of VH genes and are excised by recombination, revealing a class of cis-regulatory element that governs recombination, distinct from expression. We detect two mutually exclusive chromatin signatures at these elements, characterized by CTCF/RAD21 and PAX5/IRF4, which segregate with the evolutionary history of associated VH genes. Thus, local chromatin signatures downstream of VH genes provide an essential layer of regulation that determines recombination efficiency.
Genome organization and chromatin analysis identify transcriptional downregulation of insulin-like growth factor signaling as a hallmark of aging in developing B cells.
BACKGROUND: Aging is characterized by loss of function of the adaptive immune system, but the underlying causes are poorly understood. To assess the molecular effects of aging on B cell development, we profiled gene expression and chromatin features genome-wide, including histone modifications and chromosome conformation, in bone marrow pro-B and pre-B cells from young and aged mice. RESULTS: Our analysis reveals that the expression levels of most genes are generally preserved in B cell precursors isolated from aged compared with young mice. Nonetheless, age-specific expression changes are observed at numerous genes, including microRNA encoding genes. Importantly, these changes are underpinned by multi-layered alterations in chromatin structure, including chromatin accessibility, histone modifications, long-range promoter interactions, and nuclear compartmentalization. Previous work has shown that differentiation is linked to changes in promoter-regulatory element interactions. We find that aging in B cell precursors is accompanied by rewiring of such interactions. We identify transcriptional downregulation of components of the insulin-like growth factor signaling pathway, in particular downregulation of Irs1 and upregulation of Let-7 microRNA expression, as a signature of the aged phenotype. These changes in expression are associated with specific alterations in H3K27me3 occupancy, suggesting that Polycomb-mediated repression plays a role in precursor B cell aging. CONCLUSIONS: Changes in chromatin and 3D genome organization play an important role in shaping the altered gene expression profile of aged precursor B cells. Components of the insulin-like growth factor signaling pathways are key targets of epigenetic regulation in aging in bone marrow B cell precursors.
An alignment-free model for comparison of regulatory sequences.
MOTIVATION: Some recent comparative studies have revealed that regulatory regions can retain function over large evolutionary distances, even though the DNA sequences are divergent and difficult to align. It is also known that such enhancers can drive very similar expression patterns. This poses a challenge for the in silico detection of biologically related sequences, as they can only be discovered using alignment-free methods. RESULTS: Here, we present a new computational framework called Regulatory Region Scoring (RRS) model for the detection of functional conservation of regulatory sequences using predicted occupancy levels of transcription factors of interest. We demonstrate that our model can detect the functional and/or evolutionary links between some non-alignable enhancers with a strong statistical significance. We also identify groups of enhancers that are likely to be similarly regulated. Our model is motivated by previous work on prediction of expression patterns and it can capture similarity by strong binding sites, weak binding sites and even the statistically significant absence of sites. Our results support the hypothesis that weak binding sites contribute to the functional similarity of sequences. Our model fills a gap between two families of models: detailed, data-intensive models for the prediction of precise spatio-temporal expression patterns on the one side, and crude, generally applicable models on the other side. Our model borrows some of the strengths of each group and addresses their drawbacks. AVAILABILITY: The RRS source code is freely available upon publication of this manuscript: http://www2.warwick.ac.uk/fac/sci/systemsbiology/staff/ott/tools_and_software/rrs.
On finiteness of multiplication modules
Our main aim in this note, is a further generalization of a result due to D. D. Anderson, i.e., it is shown that if R is a commutative ring, and M a multiplication R-module, such that every prime ideal minimal over Ann (M) is finitely generated, then M contains only a finite number of minimal prime submodules. This immediately yields that if P is a projective ideal of R, such that every prime ideal minimal over Ann (P) is finitely generated, then P is finitely generated. Furthermore, it is established that if M is a multiplication R-module in which every minimal prime submodule is finitely generated, then R contains only a finite number of prime ideals minimal over Ann (M). © 2007 Springer Science + Business Media B.V.
Can we predict T cell specificity with digital biology and machine learning?
Recent advances in machine learning and experimental biology have offered breakthrough solutions to problems such as protein structure prediction that were long thought to be intractable. However, despite the pivotal role of the T cell receptor (TCR) in orchestrating cellular immunity in health and disease, computational reconstruction of a reliable map from a TCR to its cognate antigens remains a holy grail of systems immunology. Current data sets are limited to a negligible fraction of the universe of possible TCR-ligand pairs, and performance of state-of-the-art predictive models wanes when applied beyond these known binders. In this Perspective article, we make the case for renewed and coordinated interdisciplinary effort to tackle the problem of predicting TCR-antigen specificity. We set out the general requirements of predictive models of antigen binding, highlight critical challenges and discuss how recent advances in digital biology such as single-cell technology and machine learning may provide possible solutions. Finally, we describe how predicting TCR specificity might contribute to our understanding of the broader puzzle of antigen immunogenicity.
Discovery of a CD10-negative B-progenitor in human fetal life identifies unique ontogeny-related developmental programs.
Human lymphopoiesis is a dynamic lifelong process that starts in utero 6 weeks postconception. Although fetal B-lymphopoiesis remains poorly defined, it is key to understanding leukemia initiation in early life. Here, we provide a comprehensive analysis of the human fetal B-cell developmental hierarchy. We report the presence in fetal tissues of 2 distinct CD19+ B-progenitors, an adult-type CD10+ve ProB-progenitor and a new CD10-ve PreProB-progenitor, and describe their molecular and functional characteristics. PreProB-progenitors and ProB-progenitors appear early in the first trimester in embryonic liver, followed by a sustained second wave of B-progenitor development in fetal bone marrow (BM), where together they form >40% of the total hematopoietic stem cell/progenitor pool. Almost one-third of fetal B-progenitors are CD10-ve PreProB-progenitors, whereas, by contrast, PreProB-progenitors are almost undetectable (0.53% ± 0.24%) in adult BM. Single-cell transcriptomics and functional assays place fetal PreProB-progenitors upstream of ProB-progenitors, identifying them as the first B-lymphoid-restricted progenitor in human fetal life. Although fetal BM PreProB-progenitors and ProB-progenitors both give rise solely to B-lineage cells, they are transcriptionally distinct. As with their fetal counterparts, adult BM PreProB-progenitors give rise only to B-lineage cells in vitro and express the expected B-lineage gene expression program. However, fetal PreProB-progenitors display a distinct, ontogeny-related gene expression pattern that is not seen in adult PreProB-progenitors, and they share transcriptomic signatures with CD10-ve B-progenitor infant acute lymphoblastic leukemia blast cells. These data identify PreProB-progenitors as the earliest B-lymphoid-restricted progenitor in human fetal life and suggest that this fetal-restricted committed B-progenitor might provide a permissive cellular context for prenatal B-progenitor leukemia initiation.
Spatiotemporal analysis of human intestinal development at single-cell resolution.
Development of the human intestine is not well understood. Here, we link single-cell RNA sequencing and spatial transcriptomics to characterize intestinal morphogenesis through time. We identify 101 cell states including epithelial and mesenchymal progenitor populations and programs linked to key morphogenetic milestones. We describe principles of crypt-villus axis formation; neural, vascular, mesenchymal morphogenesis, and immune population of the developing gut. We identify the differentiation hierarchies of developing fibroblast and myofibroblast subtypes and describe diverse functions for these including as vascular niche cells. We pinpoint the origins of Peyer's patches and gut-associated lymphoid tissue (GALT) and describe location-specific immune programs. We use our resource to present an unbiased analysis of morphogen gradients that direct sequential waves of cellular differentiation and define cells and locations linked to rare developmental intestinal disorders. We compile a publicly available online resource, spatio-temporal analysis resource of fetal intestinal development (STAR-FINDer), to facilitate further work.
Predicting Cross-Reactivity and Antigen Specificity of T Cell Receptors.
Adaptive immune recognition is mediated by specific interactions between heterodimeric T cell receptors (TCRs) and their cognate peptide-MHC (pMHC) ligands, and the methods to accurately predict TCR:pMHC interaction would have profound clinical, therapeutic and pharmaceutical applications. Herein, we review recent developments in predicting cross-reactivity and antigen specificity of TCR recognition. We discuss current experimental and computational approaches to investigate cross-reactivity and antigen-specificity of TCRs and highlight how integrating kinetic, biophysical and structural features may offer valuable insights in modeling immunogenicity. We further underscore the close inter-relationship of these two interconnected notions and the need to investigate each in the light of the other for a better understanding of T cell responsiveness for the effective clinical applications.