Live cell imaging of low- and non-repetitive chromosome loci using CRISPR-Cas9.

Imaging chromatin dynamics is crucial to understand genome organization and its role in transcriptional regulation. Recently, the RNA-guidable feature of CRISPR-Cas9 has been utilized for imaging of chromatin within live cells. However, these methods are mostly applicable to highly repetitive regions, whereas imaging regions with low or no repeats remains as a challenge. To address this challenge, we design single-guide RNAs (sgRNAs) integrated with up to 16 MS2 binding motifs to enable robust fluorescent signal amplification. These engineered sgRNAs enable multicolour labelling of low-repeat-containing regions using a single sgRNA and of non-repetitive regions with as few as four unique sgRNAs. We achieve tracking of native chromatin loci throughout the cell cycle and determine differential positioning of transcriptionally active and inactive regions in the nucleus. These results demonstrate the feasibility of our approach to monitor the position and dynamics of both repetitive and non-repetitive genomic regions in live cells

Shelterin Protects Chromosome Ends by Compacting Telomeric Chromatin

Telomeres, repetitive DNA sequences at chromosome ends, are shielded against the DNA damage response (DDR) by the shelterin complex. To understand how shelterin protects telomere ends, we investigated the structural organization of telomeric chromatin in human cells using super-resolution microscopy. We found that telomeres form compact globular structures through a complex network of interactions between shelterin subunits and telomeric DNA, but not by DNA methylation, histone deacetylation, or histone trimethylation at telomeres and subtelomeric regions. Mutations that abrogate shelterin assembly or removal of individual subunits from telomeres cause up to a 10-fold increase in telomere volume. Decompacted telomeres accumulate DDR signals and become more accessible to telomere-associated proteins. Recompaction of telomeric chromatin using an orthogonal method displaces DDR signals from telomeres. These results reveal the chromatin remodeling activity of shelterin and demonstrate that shelterin-mediated compaction of telomeric chromatin provides robust protection of chromosome ends against the DDR machinery

Validation of a machine learning approach to estimate Systemic Lupus Erythematosus Disease Activity Index score categories and application in a real-world dataset

Objective Use of the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) in routine clinical practice is inconsistent, and availability of clinician-recorded SLEDAI scores in real-world datasets is limited. This study aimed to validate a machine learning model to estimate SLEDAI score categories using clinical notes and to apply the model to a large, real-world dataset to generate estimated score categories for use in future research studies.Methods A machine learning model was developed to estimate an individual patient’s SLEDAI score category (no activity, mild activity, moderate activity or high/very high activity) for a specific encounter date using clinical notes. A training cohort of 3504 encounters and a separate validation cohort of 1576 encounters were created from the OM1 SLE Registry. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), calculated using a binarised version of the outcome that sets the positive class to be those records with clinician-recorded SLEDAI scores >5 and the negative class to be records with scores ≤5. Model performance was evaluated by categorising the scores into the four disease activity categories and by calculating the Spearman’s R value and Pearson’s R value.Results The AUC for the two categories was 0.93 for the development cohort and 0.91 for the validation cohort. The model had a Spearman’s R value of 0.7 and a Pearson’s R value of 0.7 when calculated using the four disease activity categories.Conclusion The model performs well when estimating SLEDAI score categories using unstructured clinical notes