Targeting of proteins to chromatin in Drosophila melanogaster

Dosage compensation of sex chromosomes in Drosophila melanogaster is an excellent model system to study various aspects of targeting of protein factors to chromatin. Dosage compensation prevents male lethality by up regulating transcription from the single male X chromosome in the ~2 fold range to match the two active X chromosomes in females [reviewed in e.g. (Ferrari et al., 2014; Kuroda et al., 2016; Samata and Akhtar, 2018)]. This up regulation is facilitated by the male specific lethal (MSL) dosage compensation complex (DCC). The DCC binds selectively to ~300 high affinity sites (HAS) on the X chromosome, containing a low complexity GAGA rich sequence motif, the MSL recognition element (MRE) (Alekseyenko et al., 2008; Straub et al., 2008). However, the DCC neglects thousands of other similar sequences in the genome outside of HAS. The DNA binding subunit MSL2 alone can enrich X chromosomal MREs in vitro, although MSL2 misses most MREs within HAS (Villa et al., 2016). The Chromatin Linked Adaptor for MSL Proteins (CLAMP) binds thousands of MREs genome wide and contributes to DCC targeting to HAS (Kaye et al., 2018; Soruco et al., 2013). The role of CLAMP in facilitating MSL2 targeting to HAS was investigated by several approaches. Monitoring MSL2 chromatin binding in vivo by chromatin immunoprecipitation with high throughput sequencing (ChIP seq) showed the requirement of CLAMP for HAS targeting. Next, the interplay between CLAMP and MSL2 in genome wide in vitro DNA binding was studied by DNA immunoprecipitation with high throughput sequencing (DIP seq) (Gossett and Lieb, 2008; Liu et al., 2005; Villa et al., 2016). The data revealed mutual recruitment of both factors to each other’s binding sites and cooperative binding to novel sites. This DNA binding cooperativity extended each other’s binding repertoire to facilitate robust binding of MREs located within HAS, although increased binding to other non functional sites was observed. Both factors interacted directly with each other in co IP experiments, providing an explanation for cooperative DNA binding. Whether CLAMP and MSL2 are required for keeping HAS nucleosome free was studied by assay for transposase accessibly chromatin with high throughput sequencing (ATAC seq) (Buenrostro et al., 2013; Buenrostro et al., 2015). Both factors cooperate to stabilize each other’s binding and to compete with nucleosome positioning at HAS. After successful binding of the DCC to HAS, it interacts with neighboring target genes, which are marked by trimethylation of histone H3K36 (H3K36me3). There, the DCC catalyzes acetylation of H4K16 (H4K16ac) to boost transcription (Akhtar and Becker, 2000; Gelbart et al., 2009; Larschan et al., 2007; Prestel et al., 2010). The DCC employs the chromosome 3D organization, which seems to be invariant between males and females, to transfer from HAS to active genes (Ramirez et al., 2015; Ulianov et al., 2016). The contribution of HAS to the chromosome interaction network was studied by using different chromosome conformation capture techniques. Hi C analysis on sex sorted embryos showed that, H4K16ac and H3K36me3 correlate well with the active compartments (Sexton et al., 2012). Interestingly, compartment switching on the X chromosome between males and females was correlated with H4K16ac and therefore attributed to dosage compensation. The involvement of the Pioneering sites on the X (PionX), a special sub-class of HAS, in chromosome architecture was studied by high resolution 4C seq in male and female cells. Chromosomal segments containing PionX made frequent contact with many loci within the active compartment and even looped over large domains of the inactive compartment (Ghavi-Helm et al., 2014). These long range interactions between PionX with other PionX/HAS were more robust in males compared to females, indicating that the dosage compensation machinery reinforced them. Moreover, de novo induction of DCC assembly in female cells showed that the DCC uses long range interaction within the active compartment to transfer from PionX to target genes marked by H3K36me3 for up regulation of transcription. The chromosomal kinase JIL 1, which catalyzes phosphorylation of histone H3S10, localizes also to actively transcribed genes marked by H3K36me3 and is two fold enriched on the male X chromosome (Jin et al., 2000; Regnard et al., 2011; Wang et al., 2001). JIL 1 is implicated in maintaining overall chromosome organization and preventing the spreading of heterochromatin into the euchromatic part of the X chromosome in both sexes (Cai et al., 2014; Ebert et al., 2004; Jin et al., 1999). Furthermore, JIL 1 localizes to the non LTR retrotransposon arrays of the telomeres to positively regulate their expression (Andreyeva et al., 2005; Silva-Sousa and Casacuberta, 2013; Silva-Sousa et al., 2012). The role of JIL 1 in regulating gene expression was studied using various methods. JIL 1 formed a stable complex with the novel PWWP domain containing protein, JIL 1 Anchoring and Stabilizing Protein (JASPer). The JIL 1 JASPer (JJ) complex specifically enriched H3K36me3 modified nucleosomes in vitro via JASPer’s PWWP domain from a nucleosome library containing 115 different nucleosome types. Consistently, ChIP seq experiments showed that the JJ complex localizes to H3K36me3 chromatin at active gene bodies and at telomeric transposons in vivo. As previously described, the JJ complex is also enriched on the male X chromosome relative to autosomes. Loss of JIL 1 resulted in loss of JASPer enrichment, a small increase in H3K9me2 and a decrease in H4K16ac on the X chromosome shown by spike in ChIP seq. Gene expression analysis by RNA seq showed that the JJ complex positively regulates expression of genes, in particular of genes from the male X chromosome, and of telomeric transposons. Furthermore, the JJ complex associated with the Set1/COMPASS complex and with other remodelling complexes as shown by co IP coupled to mass spectrometry analysis

Incommensurate 2kF2k_F density wave quantum criticality in two dimensional metals

We revisit the problem of two dimensional metals in the vicinity of a quantum phase transition to incommensurate $\mathbf{Q}=2k_F$ charge density wave order, where the order parameter wave vector $\mathbf{Q}$ connects two hot spots on the Fermi surface with parallel tangents. Earlier theoretical works argued that such critical points are potentially unstable, if the Fermi surface at the hot spots is not sufficiently flat. Here we perform a controlled, perturbative renormalization group analysis and find a stable fixed point corresponding to a continuous quantum phase transition, which exhibits a strong dynamical nesting of the Fermi surface at the hot spots. We derive scaling forms of correlation functions at the critical point and discuss potential implications for experiments with transition metal dichalcogenides and rare-earth tellurides.Comment: 11 pages, 3 figures; journal versio

TDP-43 Proteinopathy Specific Biomarker Development

TDP-43 is the primary or secondary pathological hallmark of neurodegenerative diseases, such as amyotrophic lateral sclerosis, half of frontotemporal dementia cases, and limbic age-related TDP-43 encephalopathy, which clinically resembles Alzheimer's dementia. In such diseases, a biomarker that can detect TDP-43 proteinopathy in life would help to stratify patients according to their definite diagnosis of pathology, rather than in clinical subgroups of uncertain pathology. For therapies developed to target pathological proteins that cause the disease a biomarker to detect and track the underlying pathology would greatly enhance such undertakings. This article reviews the latest developments and outlooks of deriving TDP-43-specific biomarkers from the pathophysiological processes involved in the development of TDP-43 proteinopathy and studies using biosamples from clinical entities associated with TDP-43 pathology to investigate biomarker candidates

Clustering of B -> D(*)tau- nu(tau) kinematic distributions with ClusterKinG

New Physics can manifest itself in kinematic distributions of particle decays. The parameter space defining the shape of such distributions can be large which is chalenging for both theoretical and experimental studies. Using clustering algorithms, the parameter space can however be dissected into subsets (clusters) which correspond to similar kinematic distributions. Clusters can then be represented by benchmark points, which allow for less involved studies and a concise presentation of the results. We demonstrate this concept using the Python package ClusterKinG, an easy to use framework for the clustering of distributions that particularly aims to make these techniques more accessible in a High Energy Physics context. As an example we consider B over bar -> D) (tau-nu over bar tau distributions and discuss various clustering methods and possible implications for future experimental analyses

The MOF-containing NSL complex associates globally with housekeeping genes, but activates only a defined subset

The MOF (males absent on the first)-containing NSL (non-specific lethal) complex binds to a subset of active promoters in Drosophila melanogaster and is thought to contribute to proper gene expression. The determinants that target NSL to specific promoters and the circumstances in which the complex engages in regulating transcription are currently unknown. Here, we show that the NSL complex primarily targets active promoters and in particular housekeeping genes, at which it colocalizes with the chromatin remodeler NURF (nucleosome remodeling factor) and the histone methyltransferase Trithorax. However, only a subset of housekeeping genes associated with NSL are actually activated by it. Our analyses reveal that these NSL-activated promoters are depleted of certain insulator binding proteins and are enriched for the core promoter motif ‘Ohler 5’. Based on these results, it is possible to predict whether the NSL complex is likely to regulate a particular promoter. We conclude that the regulatory capacity of the NSL complex is highly context-dependent. Activation by the NSL complex requires a particular promoter architecture defined by combinations of chromatin regulators and core promoter motifs

Exclusive b → s ν ν induced transitions in the RSc model

We study a set of exclusive B and Bs decay modes induced by the rare (Formula presented.) transition in the RSc model, an extra-dimensional extension of the standard model with warped 5D metric and extended gauge group. We discuss the role of correlations among the observables, and their importance for detecting the predicted small deviations from the standard model expectations

Exclusive b→sνν¯ induced transitions in the RS c model

We study a set of exclusive B and Bs decay modes induced by the rare b→sνν¯ transition in the RS c model, an extra-dimensional extension of the standard model with warped 5D metric and extended gauge group. We discuss the role of correlations among the observables, and their importance for detecting the predicted small deviations from the standard model expectations

Dissemination in time and space in presymptomatic granulin mutation carriers: a GENFI spatial chronnectome study

The presymptomatic brain changes of granulin (GRN) disease, preceding by years frontotemporal dementia, has not been fully characterized. New approaches focus on the spatial chronnectome can capture both spatial network configurations and their dynamic changes over time. To investigate the spatial dynamics in 141 presymptomatic GRN mutation carriers and 282 noncarriers from the Genetic Frontotemporal dementia research Initiative cohort. We considered time-varying patterns of the default mode network, the language network, and the salience network, each summarized into 4 distinct recurring spatial configurations. Dwell time (DT) (the time each individual spends in each spatial state of each network), fractional occupacy (FO) (the total percentage of time spent by each individual in a state of a specific network) and total transition number (the total number of transitions performed by each individual in a specifict state) were considered. Correlations between DT, FO, and transition number and estimated years from expected symptom onset (EYO) and clinical performances were assessed. Presymptomatic GRN mutation carriers spent significantly more time in those spatial states characterised by greater activation of the insula and the parietal cortices, as compared to noncarriers (p < 0.05, FDR-corrected). A significant correlation between DT and FO of these spatial states and EYO was found, the longer the time spent in the spatial states, the closer the EYO. DT and FO significantly correlated with performances at tests tapping processing speed, with worse scores associated with increased spatial states’ DT. Our results demonstrated that presymptomatic GRN disease presents a complex dynamic reorganization of brain connectivity. Change in both the spatial and temporal aspects of brain network connectivity could provide a unique glimpse into brain function and potentially allowing a more sophisticated evaluation of the earliest disease changes and the understanding of possible mechanisms in GRN disease

Disease-related cortical thinning in presymptomatic granulin mutation carriers

© 2020 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license.Mutations in the granulin gene (GRN) cause familial frontotemporal dementia. Understanding the structural brain changes in presymptomatic GRN carriers would enforce the use of neuroimaging biomarkers for early diagnosis and monitoring. We studied 100 presymptomatic GRN mutation carriers and 94 noncarriers from the Genetic Frontotemporal dementia initiative (GENFI), with MRI structural images. We analyzed 3T MRI structural images using the FreeSurfer pipeline to calculate the whole brain cortical thickness (CTh) for each subject. We also perform a vertex-wise general linear model to assess differences between groups in the relationship between CTh and diverse covariables as gender, age, the estimated years to onset and education. We also explored differences according to TMEM106B genotype, a possible disease modifier. Whole brain CTh did not differ between carriers and noncarriers. Both groups showed age-related cortical thinning. The group-by-age interaction analysis showed that this age-related cortical thinning was significantly greater in GRN carriers in the left superior frontal cortex. TMEM106B did not significantly influence the age-related cortical thinning. Our results validate and expand previous findings suggesting an increased CTh loss associated with age and estimated proximity to symptoms onset in GRN carriers, even before the disease onset.The authors thank all the volunteers for their participation in this study. SBE is a recipient of the Rio-Hortega post-residency grant from the Instituto de Salud Carlos III, Spain. This study was partially funded by Fundació Marató de TV3, Spain (grant no. 20143810 to RSV). The GENFI study has been supported by the Medical Research Council UK, the Italian Ministry of Health and the Canadian Institutes of Health Research as part of a Centres of Excellence in Neurodegeneration grant, as well as other individual funding to investigators. KM has received funding from an Alzheimer’s Society PhD studentship. JDR acknowledges support from the National Institute for Health Research (NIHR) Queen Square Dementia Biomedical Research Unit and the University College London Hospitals Biomedical Research Centre, the Leonard Wolfson Experimental Neurology Centre, the UK Dementia Research Institute, Alzheimer’s Research UK, the Brain Research Trust and the Wolfson Foundation. JCvS was supported by the Dioraphte Foundation grant 09-02-03-00, the Association for Frontotemporal Dementias Research Grant 2009, The Netherlands Organization for Scientific Research (NWO) grant HCMI 056-13-018, ZonMw Memorabel (Deltaplan Dementie, project number 733 051 042), Alzheimer Nederland and the Bluefield project. CG have received funding from JPND-Prefrontals VR Dnr 529-2014-7504, VR: 2015-02926, and 2018-02754, the Swedish FTD Initiative-Schörling Foundation, Alzheimer Foundation, Brain Foundation and Stockholm County Council ALF. DG has received support from the EU Joint Programme – Neurodegenerative Disease Research (JPND) and the Italian Ministry of Health (PreFrontALS) grant 733051042. JBR is funded by the Wellcome Trust (103838) and the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre. MM has received funding from a Canadian Institutes of Health Research operating grant and the Weston Brain Institute and Ontario Brain Institute. RV has received funding from the Mady Browaeys Fund for Research into Frontotemporal Dementia. EF has received funding from a CIHR grant #327387. JDR is an MRC Clinician Scientist (MR/M008525/1) and has received funding from the NIHR Rare Diseases Translational Research Collaboration (BRC149/NS/MH), the Bluefield Project and the Association for Frontotemporal Degeneration. MS was supported by a grant 779257 “Solve-RD” from the Horizon 2020 research and innovation programme.info:eu-repo/semantics/publishedVersio