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Brown, T.

Publications and source records attributed to Brown, T..

62 records · Page 4Linked to original sources

Optimising DNA-Coated Gold Nanoparticles to Enrich Skeletal Stem Cells from Human Bone Marrow Samples

Human bone marrow (BM) derived stromal cells contain a population of skeletal stem cells (SSCs), with the capacity to differentiate along the osteogenic, adipogenic and chondrogenic lineages enabling their application to clinical therapies. However, current methods, to isolate and enrich SSCs from human tissues remain, at best, challenging in the absence of a specific SSC marker. Unfortunately, none of the current proposed markers, alone, can isolate a homogenous cell population with the ability to form bone, cartilage, and adipose tissue in humans. Here, we have designed DNA-gold nanoparticles able to identify and sort SSCs displaying specific mRNA signatures. The current approach demonstrates the significant enrichment attained in the isolation of SSCs, with potential therein to enhance our understanding of bone cell biology and translational applications. TABLE OF CONTENTS O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/882563v3_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@48c5acorg.highwire.dtl.DTLVardef@1a9d096org.highwire.dtl.DTLVardef@1bd4da2org.highwire.dtl.DTLVardef@133dd1d_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

Dissection of the 4D chromatin structure of the α-globin locus through in vivo erythroid differentiation with extreme spatial and temporal resolution

Mammalian gene expression patterns are controlled by regulatory elements, which interact within Topologically Associating Domains (TADs). The relationship between activation of regulatory elements, formation of structural chromatin interactions and gene expression during development is unclear. We developed Tiled-C, a low-input Chromosome Conformation Capture (3C) approach, to study chromatin architecture at high spatial and temporal resolution through in vivo mouse erythroid differentiation. Integrated analysis of matched chromatin accessibility and single-cell expression data shows that regulatory elements gradually become accessible within pre-existing TADs during early differentiation. This is followed by structural re-organization within the TAD and formation of specific contacts between enhancers and promoters. In contrast to previous reports, our high-resolution data show that these enhancer-promoter interactions are not established prior to gene expression, but formed gradually during differentiation, concomitant with progressive upregulation of gene activity. Together, these results provide new insight into the close, interdependent relationship between chromatin architecture and gene regulation during development.

genomics↗

H3K4me3 is neither instructive for, nor informed by, transcription.

H3K4me3 is a near-universal histone modification found predominantly at the 5 region of genes, with a well-documented association with gene activity. H3K4me3 has been ascribed roles as both an instructor of gene expression and also a downstream consequence of expression, yet neither has been convincingly proven on a genome-wide scale. Here we test these relationships using a combination of bioinformatics, modelling and experimental data from budding yeast in which the levels of H3K4me3 have been massively ablated. We find that loss of H3K4me3 has no effect on the levels of nascent transcription or transcript in the population. Moreover, we observe no change in the rates of transcription initiation, elongation, mRNA export or turnover, or in protein levels, or cell-to-cell variation of mRNA. Loss of H3K4me3 also has no effect on the large changes in gene expression patterns that follow galactose induction. Conversely, loss of RNA polymerase from the nucleus has no effect on the pattern of H3K4me3 deposition and little effect on its levels, despite much larger changes to other chromatin features. Furthermore, large genome-wide changes in transcription, both in response to environmental stress and during metabolic cycling, are not accompanied by corresponding changes in H3K4me3. Thus, despite the correlation between H3K4me3 and gene activity, neither appear to be necessary to maintain levels of the other, nor to influence their changes in response to environmental stimuli. When we compare gene classes with very different levels of H3K4me3 but highly similar transcription levels we find that H3K4me3-marked genes are those whose expression is unresponsive to environmental changes, and that their histones are less acetylated and dynamically turned-over. Constitutive genes are generally well-expressed, which may alone explain the correlation between H3K4me3 and gene expression, while the biological role of H3K4me3 may have more to do with this distinction in gene class.

genomics↗

Complexity matching: brain signals mirror environment information patterns during music listening and reward

Understanding how the human brain integrates information from the environment with ongoing, internal brain signals in order to produce individual perspective is an essential element of understanding the human mind. Brain signal complexity, measured with multiscale entropy, has been employed as a measure of information processing in the brain (Carpentier et al., 2016), and we propose that it can also be used to measure the information available from a stimulus. We can directly assess the correspondence, or functional isomorphism, between brain signal complexity and stimulus complexity as an indication of how well the brain reflects the content of the environment in an analysis that we termed complexity matching. Music makes an ideal stimulus input because it is a multidimensional, complex signal, and because of its emotion and reward-inducing potential. We found that electroencephalography (EEG) complexity was lower and more closely resembled the musical complexity when participants performed a perceptual task that required them to closely track the acoustics, compared to an emotional task that asked them to think about how the music made them feel. Music-derived reward scores on the Barcelona Music Reward Questionnaire (Mas-Herrero et al., 2013) correlated with worse complexity matching and higher EEG complexity. Compared to perceptual-level processing, emotional and reward responses are associated with additional internal information processes above and beyond those in the external stimulus.\n\nSignificance StatementExperience of our world is combination of the input from the environment, our expectations, and individual responses. For example, the same piece of music can elict happiness in one person and sadness in another. We researched this by measuring the information in pieces of music and whether listeners brain more closely followed that, or whether additional information was added by the brain. We noted when listeners were reacting to how music made them feel, their brains added more information and the degree to which this occurred related to how much they find music rewarding. Thus, we were able to provide clues as to how the brain integrates incoming information, adding to it to provide a richer perceptual and emotional experience.

neuroscience↗

Diffeomorphic registration with intensity transformation and missing data: Application to 3D digital pathology of Alzheimer’s disease

This paper examines the problem of diffeomorphic image mapping in the presence of differing image intensity profiles and missing data. Our motivation comes from the problem of aligning 3D brain MRI with 100 micron isotropic resolution, to histology sections with 1 micron in plane resolution. Multiple stains, as well as damaged, folded, or missing tissue are common in this situation. We overcome these challenges by introducing two new concepts. Cross modality image matching is achieved by jointly estimating polynomial transformations of the atlas intensity, together with pose and deformation parameters. Missing data is accommodated via a multiple atlas selection procedure where several atlases may be of homogeneous intensity and correspond to \"background\" or \"artifact\". The two concepts are combined within an Expectation Maximization algorithm, where atlas selection posteriors and deformation parameters are updated iteratively, and polynomial coefficients are computed in closed form. We show results for 3D reconstruction of digital pathology and MRI in standard atlas coordinates. In conjunction with convolutional neural networks, we quantify the 3D density distribution of tauopathy throughout the medial temporal lobe of an Alzheimers disease postmortem specimen.\n\nAuthor summaryOur work in Alzheimers disease (AD) is attempting to connect histopathology at autopsy and longitudinal clinical magnetic resonance imaging (MRI), combining the strengths of each modality in a common coordinate system. We are bridging this gap by using post mortem high resolution MRI to reconstruct digital pathology in 3D. This image registration problem is challenging because it combines images from different modalities in the presence of missing tissue and artifacts. We overcome this challenge by developing a new registration technique that simultaneously classifies each pixel as \"good data\" / \"missing tissue\" / \"artifact\", learns a contrast transformation between modalities, and computes deformation parameters. We name this technique \"(D)eformable (R)egistration and (I)ntensity (T)ransformation with (M)issing (D)ata\", pronounced as \"Dr. It, M.D.\". In conjunction with convolutional neural networks, we use this technique to map the three dimensional distribution of tau tangles in the medial temporal lobe of an AD postmortem specimen.

neuroscience↗

Molecular flexibility of DNA as a major determinant of RAD51 recruitment

The timely activation of homologous recombination is essential for the maintenance of genome stability, in which the RAD51 recombinase plays a central role. Biochemically, human RAD51 polymerises faster on single-stranded DNA (ssDNA) compared to double-stranded DNA (dsDNA), raising a key conceptual question: how does it discriminate between them? In this study, we tackled this problem by systematically assessing RAD51 binding kinetics on ssDNA and dsDNA differing in length and flexibility using surface plasmon resonance. By fitting detailed polymerisation models informed by our experimental datasets, we show that RAD51 is a mechano-sensor that exhibits a larger polymerisation rate constant on flexible ssDNA compared to rigid ssDNA or dsDNA. This model presents a new general framework suggesting that the flexibility of DNA, which may increase locally as a result of DNA damage, plays an important role in rapidly recruiting repair factors that multimerise at sites of DNA damage.

biochemistry↗

Antisense transcription-dependent chromatin signature modulates sense transcription and transcript dynamics

Antisense transcription is widespread in genomes. Despite large differences in gene size and architecture, we find that yeast and human genes share a unique, antisense transcription-associated chromatin signature. We asked whether this signature is related to a biological function for antisense transcription. Using quantitative RNA-FISH, we observed changes in sense transcript distributions in nuclei and cytoplasm as antisense transcript levels were altered. To determine the mechanistic differences underlying these distributions, we developed a mathematical framework describing transcription from initiation to transcript degradation. At GAL1, high levels of antisense transcription alters sense transcription dynamics, reducing rates of transcript production and processing, while increasing transcript stability, which is also a genome-wide association. Establishing the antisense transcription-associated chromatin signature through disruption of the Set3C histone deacetylase activity is sufficient to similarly change these rates even in the absence of antisense transcription. Thus, antisense transcription alters sense transcription dynamics in a chromatin-dependent manner.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=198 HEIGHT=200 SRC=\"FIGDIR/small/187237_fig8.gif\" ALT=\"Figure 8\">\nView larger version (52K):\norg.highwire.dtl.DTLVardef@4f872corg.highwire.dtl.DTLVardef@1339662org.highwire.dtl.DTLVardef@1d62cc2org.highwire.dtl.DTLVardef@148f24_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract\n\nC_FIG In this work, Brown et al. provide a mechanistic understanding of the effect of antisense transcription on the production and fate of sense transcripts. Antisense transcription buffers genes against the action of the Set3 lysine deacetylase, thus altering rates of transcript production, processing and stability. O_LIConserved antisense transcription-dependent chromatin architecture near promoters\nC_LIO_LIAntisense transcription alters sense transcription dynamics and transcript stability\nC_LIO_LIAntisense transcription functions in a chromatin-dependent manner\nC_LIO_LIIncreased acetylation by set3{Delta} mimics high antisense transcriptional dynamics\nC_LI

systems biology↗

CRISPRi is not strand-specific and redefines the transcriptional landscape

CRISPRi, an adapted CRISPR-Cas9 system, is proposed to act as a strand-specific roadblock to repress transcription in eukaryotic cells using guide RNAs (sgRNAs) to target catalytically inactive Cas9 (dCas9) and offers an alternative to genetic interventions for studying pervasive antisense transcription. Here we successfully use click chemistry to construct DNA templates for sgRNA expression and show, rather than acting simply as a roadblock, binding of sgRNA/dCas9 creates an environment that is permissive for transcription initiation and termination, thus generating novel sense and antisense transcripts. At HMS2 in Saccharomyces cerevisiae, sgRNA/dCas9 targeting to the non-template strand results in antisense transcription termination, premature termination of a proportion of sense transcripts and initiation of a novel antisense transcript downstream of the sgRNA/dCas9 binding site. This redefinition of the transcriptional landscape by CRISPRi demonstrates that it is not strand-specific and highlights the controls and locus understanding required to properly interpret results from CRISPRi interventions.

genetics↗