CENP-A nucleosome clusters form rosette-like structures around HJURP during G1

Nanoscale cellular organization of viral RNA and proteins in SARS-CoV-2 replication organelles

The SARS-CoV-2 viral infection transforms host cells and produces special organelles in many ways, and we focus on the replication organelles, the sites of replication of viral genomic RNA (vgRNA). To date, the precise cellular localization of key RNA molecules and replication intermediates has been elusive in electron microscopy studies. We use super-resolution fluorescence microscopy and specific labeling to reveal the nanoscopic organization of replication organelles that contain numerous vgRNA molecules along with the replication enzymes and clusters of viral double-stranded RNA (dsRNA). We show that the replication organelles are organized differently at early and late stages of infection. Surprisingly, vgRNA accumulates into distinct globular clusters in the cytoplasmic perinuclear region, which grow and accommodate more vgRNA molecules as infection time increases. The localization of endoplasmic reticulum (ER) markers and nsp3 (a component of the double-membrane vesicle, DMV) at the periphery of the vgRNA clusters suggests that replication organelles are encapsulated into DMVs, which have membranes derived from the host ER. These organelles merge into larger vesicle packets as infection advances. Precise co-imaging of the nanoscale cellular organization of vgRNA, dsRNA, and viral proteins in replication organelles of SARS-CoV-2 may inform therapeutic approaches that target viral replication and associated processes.

Non-random spatial organization of telomeres varies during the cell cycle and requires LAP2 and BAF

Spatial genome organization within the nucleus influences major biological processes and is impacted by the configuration of linear chromosomes. Here, we applied 3D spatial statistics and modeling on high-resolution telomere and centromere 3D-structured illumination microscopy images in cancer cells. We found a multi-scale organization of telomeres that dynamically evolved from a mixed clustered-and-regular distribution in early G1 to a purely regular distribution as cells progressed through the cell cycle. In parallel, our analysis revealed two pools of peripheral and internal telomeres, the proportions of which were inverted during the cell cycle. We then conducted a targeted screen using MadID to identify the molecular pathways driving or maintaining telomere anchoring to the nuclear envelope observed in early G1. Lamina-associated polypeptide (LAP) proteins were found transiently localized to telomeres in anaphase, a stage where LAP2α initiates the reformation of the nuclear envelope, and impacted telomere redistribution in the next interphase together with their partner barrier-to-autointegration factor (BAF).

Nanoscale cellular organization of viral RNA and proteins in SARS-CoV-2 replication organelles

The SARS-CoV-2 viral infection transforms host cells and produces special organelles in many ways, and we focus on the replication organelle where the replication of viral genomic RNA (vgRNA) occurs. To date, the precise cellular localization of key RNA molecules and replication intermediates has been elusive in electron microscopy studies. We use super-resolution fluorescence microscopy and specific labeling to reveal the nanoscopic organization of replication organelles that contain vgRNA clusters along with viral double-stranded RNA (dsRNA) clusters and the replication enzyme, encapsulated by membranes derived from the host endoplasmic reticulum (ER). We show that the replication organelles are organized differently at early and late stages of infection. Surprisingly, vgRNA accumulates into distinct globular clusters in the cytoplasmic perinuclear region, which grow and accommodate more vgRNA molecules as infection time increases. The localization of ER labels and nsp3 (a component of the double-membrane vesicle, DMV) at the periphery of the vgRNA clusters suggests that replication organelles are enclosed by DMVs at early infection stages which then merge into vesicle packets as infection progresses. Precise co-imaging of the nanoscale cellular organization of vgRNA, dsRNA, and viral proteins in replication organelles of SARS-CoV-2 may inform therapeutic approaches that target viral replication and associated processes.

Dynamic interplay between human alpha-satellite DNA structure and centromere functions

Maintenance of genome stability relies on functional centromeres for correct chromosome segregation and faithful inheritance of the genetic information. The human centromere is the primary constriction within mitotic chromosomes made up of repetitive alpha-satellite DNA hierarchically organized in megabase-long arrays of near-identical higher order repeats (HORs). Centromeres are epigenetically specified by the presence of the centromere-specific histone H3 variant, CENP-A, which enables the assembly of the kinetochore for microtubule attachment. Notably, centromeric DNA is faithfully inherited as intact haplotypes from the parents to the offspring without intervening recombination, yet, outside of meiosis, centromeres are akin to common fragile sites (CFSs), manifesting crossing-overs and ongoing sequence instability. Consequences of DNA changes within the centromere are just starting to emerge, with unclear effects on intra- and inter-generational inheritance driven by centromere's essential role in kinetochore assembly. Here, we review evidence of meiotic selection operating to mitigate centromere drive, as well as recent reports on centromere damage, recombination and repair during the mitotic cell division. We propose an antagonistic pleiotropy interpretation to reconcile centromere DNA instability as both driver of aneuploidy that underlies degenerative diseases, while also potentially necessary for the maintenance of homogenized HORs for centromere function. We attempt to provide a framework for this conceptual leap taking into consideration the structural interface of centromere-kinetochore interaction and present case scenarios for its malfunctioning. Finally, we offer an integrated working model to connect DNA instability, chromatin, and structural changes with functional consequences on chromosome integrity.

Effects of Holliday Junction-Recognition Protein-Mediated C-Jun N-Terminal Kinase/ Signal Transducer and Activator of Transcription 3 Signaling Pathway on Cell Proliferation, Cell Cycle and Cell Apoptosis in Bladder Urothelial Carcinoma

The Holliday Junction-Recognition Protein (HJURP) was upregulated in several tumors, which was associated with poor outcome. This study investigated the effects of the HJURP-mediated c-Jun N-terminal kinase (JNK)/ signal transducer and activator of transcription 3 (STAT3) pathway on bladder urothelial carcinoma (BLUC). Online databases were used to analyze HJURP expression in BLUC and the correlation of HJURP to JNK1 [mitogen-activated protein kinase 8 (MAPK8)], JNK2 (MAPK9), STAT3, marker of proliferation Ki-67 (MKI67), proliferating cell nuclear antigen (PCNA), cyclin dependent kinase 2 (CDK2), CDK4 and CDK6. HJURP expression was detected in BLUC cells and human normal primary bladder epithelial cells (BdECs). BLUC cells were treated with HJURP lentivirus activation /shRNA lentivirus particles or JNK inhibitor SP600125. HJURP was upregulated in BLUC tissues and correlated with poor prognosis of patients (all P < 0.05). HJURP in tumor positively correlated with MAPK8 (R = 0.30), MAPK9 (R = 0.30), STAT3 (R = 0.15), MKI67 (R = 0.60), PCNA (R = 0.46), CDK2 (R = 0.39), CDK4 (R = 0.24) and CDK6 (R = 0.21). The JNK inhibitor SP600125 decreased p-JNK/JNK and p-STAT3/STAT3 in BLUC cells, which was reversed by HJURP overexpression (P < 0.05). The HJURP-mediated JNK/STAT3 pathway promoted BLUC cell proliferation and inhibited cell apoptosis (P < 0.05). HJURP reversed the arrested G0/G1 phase of BLUC cells by SP600125. HJURP acted as an oncogene to regulate BLUC cell proliferation, apoptosis and the cell cycle by mediating the JNK/STAT3 pathway. Therefore, HJURP targeting might be an attractive novel therapeutic target for early diagnosis and treatment in BLUC.

Semi-automated 3D fluorescence speckle analyzer (3D-Speckler) for microscope calibration and nanoscale measurement

The widespread use of fluorescence microscopy has prompted the ongoing development of tools aiming to improve resolution and quantification accuracy for study of biological questions. Current calibration and quantification tools for fluorescence images face issues with usability/user experience, lack of automation, and comprehensive multidimensional measurement/correction capabilities. Here, we developed 3D-Speckler, a versatile, and high-throughput image analysis software that can provide fluorescent puncta quantification measurements such as 2D/3D particle size, spatial location/orientation, and intensities through semi-automation in a single, user-friendly interface. Integrated analysis options such as 2D/3D local background correction, chromatic aberration correction, and particle matching/filtering are also encompassed for improved precision and accuracy. We demonstrate 3D-Speckler microscope calibration capabilities by determining the chromatic aberrations, field illumination uniformity, and response to nanometer-scale emitters above and below the diffraction limit of our imaging system using multispectral beads. Furthermore, we demonstrated 3D-Speckler quantitative capabilities for offering insight into protein architectures and composition in cells.

Machine learning framework to segment sarcomeric structures in SMLM data

Object detection is an image analysis task with a wide range of applications, which is difficult to accomplish with traditional programming. Recent breakthroughs in machine learning have made significant progress in this area. However, these algorithms are generally compatible with traditional pixelated images and cannot be directly applied for pointillist datasets generated by single molecule localization microscopy (SMLM) methods. Here, we have improved the averaging method developed for the analysis of SMLM images of sarcomere structures based on a machine learning object detection algorithm. The ordered structure of sarcomeres allows us to determine the location of the proteins more accurately by superimposing SMLM images of identically assembled proteins. However, the area segmentation process required for averaging can be extremely time-consuming and tedious. In this work, we have automated this process. The developed algorithm not only finds the regions of interest, but also classifies the localizations and identifies the true positive ones. For training, we used simulations to generate large amounts of labelled data. After tuning the neural network's internal parameters, it could find the localizations associated with the structures we were looking for with high accuracy. We validated our results by comparing them with previous manual evaluations. It has also been proven that the simulations can generate data of sufficient quality for training. Our method is suitable for the identification of other types of structures in SMLM data.

Nuclear envelope, chromatin organizers, histones, and DNA: The many achilles heels exploited across cancers

In eukaryotic cells, the genome is organized in the form of chromatin composed of DNA and histones that organize and regulate gene expression. The dysregulation of chromatin remodeling, including the aberrant incorporation of histone variants and their consequent post-translational modifications, is prevalent across cancers. Additionally, nuclear envelope proteins are often deregulated in cancers, which impacts the 3D organization of the genome. Altered nuclear morphology, genome organization, and gene expression are defining features of cancers. With advances in single-cell sequencing, imaging technologies, and high-end data mining approaches, we are now at the forefront of designing appropriate small molecules to selectively inhibit the growth and proliferation of cancer cells in a genome- and epigenome-specific manner. Here, we review recent advances and the emerging significance of aberrations in nuclear envelope proteins, histone variants, and oncohistones in deregulating chromatin organization and gene expression in oncogenesis.

Pan-cancer analysis based on epigenetic modification explains the value of HJURP in the tumor microenvironment

To analyze the expression levels, prognostic value and immune infiltration association of Holliday junction protein (HJURP) as well as its feasibility as a pan-cancer biomarker for different cancers. The Protter online tool was utilized to obtain the localization of HJURP, then the methylation of HJURP in tumors were further explored. Thereafter, the mRNA data and clinical characteristics of 33 tumor types from TCGA database were obtained to investigate the expression and prognostic relationship of HJURP in different tumor types. Finally, the composition pattern and immune infiltration of HJURP in different tumors were detected in Tumor Immune Estimation Resource. HJURP was abnormally expressed in most of the cancer types and subtypes in TCGA database. Also, it was associated with poor prognosis of different cohorts. At the same time, the results also showed that HJURP was related to tumor immune evasion through different mechanisms, including T cell rejection and methylation in different cancer types. Besides, the methylation of HJURP was inversely proportional to mRNA expression levels, which mediated the dysfunctional phenotypes of T cells and poor prognosis of different cancer types. Alternatively, our results indicated that HJURP expression was associated with immune cell infiltration in a variety of cancers. HJURP may serve as an oncogenic molecule, and its expression and immune infiltration characteristics can be used as a biomarker for cancer detection, prognosis, treatment design and follow-up.

splitSMLM, a spectral demixing method for high-precision multi-color localization microscopy applied to nuclear pore complexes

Single molecule localization microscopy (SMLM) with a dichroic image splitter can provide invaluable multi-color information regarding colocalization of individual molecules, but it often suffers from technical limitations. Classical demixing algorithms tend to give suboptimal results in terms of localization precision and correction of chromatic errors. Here we present an image splitter based multi-color SMLM method (splitSMLM) that offers much improved localization precision and drift correction, compensation of chromatic distortions, and optimized performance of fluorophores in a specific buffer to equalize their reactivation rates for simultaneous imaging. A novel spectral demixing algorithm, SplitViSu, fully preserves localization precision with essentially no data loss and corrects chromatic errors at the nanometer scale. Multi-color performance is further improved by using optimized fluorophore and filter combinations. Applied to three-color imaging of the nuclear pore complex (NPC), this method provides a refined positioning of the individual NPC proteins and reveals that Pom121 clusters act as NPC deposition loci, hence illustrating strength and general applicability of the method.

The development of an image splitter based multi-colour single-molecule localization microscopy method (splitSMLM) in combination with a spectral demixing algorithm improves localization accuracy as exemplified by three-colour imaging of nuclear pore complex proteins.

Centromere Identity and the Regulation of Chromosome Segregation

Eukaryotes segregate their chromosomes during mitosis and meiosis by attaching chromosomes to the microtubules of the spindle so that they can be distributed into daughter cells. The complexity of centromeres ranges from the point centromeres of yeast that attach to a single microtubule to the more complex regional centromeres found in many metazoans or holocentric centromeres of some nematodes, arthropods and plants, that bind to dozens of microtubules per kinetochore. In vertebrates, the centromere is defined by a centromere specific histone variant termed Centromere Protein A (CENP-A) that replaces histone H3 in a subset of centromeric nucleosomes. These CENP-A nucleosomes are distributed on long stretches of highly repetitive DNA and interspersed with histone H3 containing nucleosomes. The mechanisms by which cells control the number and position of CENP-A nucleosomes is unknown but likely important for the organization of centromeric chromatin in mitosis so that the kinetochore is properly oriented for microtubule capture. CENP-A chromatin is epigenetically determined thus cells must correct errors in CENP-A organization to prevent centromere dysfunction and chromosome loss. Recent improvements in sequencing complex centromeres have paved the way for defining the organization of CENP-A nucleosomes in centromeres. Here we discuss the importance and challenges in understanding CENP-A organization and highlight new discoveries and advances enabled by recent improvements in the human genome assembly.

CENP-B-mediated DNA loops regulate activity and stability of human centromeres

Chromosome inheritance depends on centromeres, epigenetically specified regions of chromosomes. While conventional human centromeres are known to be built of long tandem DNA repeats, much of their architecture remains unknown. Using single-molecule techniques such as AFM, nanopores, and optical tweezers, we find that human centromeric DNA exhibits complex DNA folds such as local hairpins. Upon binding to a specific sequence within centromeric regions, the DNA-binding protein CENP-B compacts centromeres by forming pronounced DNA loops between the repeats, which favor inter-chromosomal centromere compaction and clustering. This DNA-loop-mediated organization of centromeric chromatin participates in maintaining centromere position and integrity upon microtubule pulling during mitosis. Our findings emphasize the importance of DNA topology in centromeric regulation and stability.

Oncogenic lncRNAs alter epigenetic memory at a fragile chromosomal site in human cancer cells

Chromosome instability is a critical event in cancer progression. Histone H3 variant CENP-A plays a fundamental role in defining centromere identity, structure, and function but is innately overexpressed in several types of solid cancers. In the cancer background, excess CENP-A is deposited ectopically on chromosome arms, including 8q24/cMYC locus, by invading transcription-coupled H3.3 chaperone pathways. Up-regulation of lncRNAs in many cancers correlates with poor prognosis and recurrence in patients. We report that transcription of 8q24-derived oncogenic lncRNAs plays an unanticipated role in altering the 8q24 chromatin landscape by H3.3 chaperone-mediated deposition of CENP-A-associated complexes. Furthermore, a transgene cassette carrying specific 8q24-derived lncRNA integrated into a naïve chromosome locus recruits CENP-A to the new location in a cis-acting manner. These data provide a plausible mechanistic link between locus-specific oncogenic lncRNAs, aberrant local chromatin structure, and the generation of new epigenetic memory at a fragile site in human cancer cells.

Variation and Evolution of Human Centromeres: A Field Guide and Perspective

We are entering a new era in genomics where entire centromeric regions are accurately represented in human reference assemblies. Access to these high-resolution maps will enable new surveys of sequence and epigenetic variation in the population and offer new insight into satellite array genomics and centromere function. Here, we focus on the sequence organization and evolution of alpha satellites, which are credited as the genetic and genomic definition of human centromeres due to their interaction with inner kinetochore proteins and their importance in the development of human artificial chromosome assays. We provide an overview of alpha satellite repeat structure and array organization in the context of these high-quality reference data sets; discuss the emergence of variation-based surveys; and provide perspective on the role of this new source of genetic and epigenetic variation in the context of chromosome biology, genome instability, and human disease.

Diverse mechanisms of centromere specification

The centromere performs a universally conserved function, to accurately partition genetic information upon cell division. Yet, centromeres are among the most rapidly evolving regions of the genome and are bound by a varying assortment of centromere-binding factors that are themselves highly divergent at the protein-sequence level. A common thread in most species is the dependence on the centromere-specific histone variant CENP-A for the specification of the centromere site. However, CENP-A is not universally required in all species or cell types, making the identification of a general mechanism for centromere specification challenging. In this review, we examine our current understanding of the mechanisms of centromere specification in CENP-A-dependent and independent systems, focusing primarily on recent work.

CENP-A nucleosome-a chromatin-embedded pedestal for the centromere: lessons learned from structural biology

The centromere is a chromosome locus that directs equal segregation of chromosomes during cell division. A nucleosome containing the histone H3 variant CENP-A epigenetically defines the centromere. Here, we summarize findings from recent structural biology studies, including several CryoEM structures, that contributed to elucidate specific features of the CENP-A nucleosome and molecular determinants of its interactions with CENP-C and CENP-N, the only two centromere proteins that directly bind to it. Based on those findings, we propose a role of the CENP-A nucleosome in the organization of centromeric chromatin beyond binding centromeric proteins.

R-loops at centromeric chromatin contribute to defects in kinetochore integrity and chromosomal instability in budding yeast

R-loops, the byproduct of DNA–RNA hybridization and the displaced single-stranded DNA (ssDNA), have been identified in bacteria, yeasts, and other eukaryotic organisms. The persistent presence of R-loops contributes to defects in DNA replication and repair, gene expression, and genomic integrity. R-loops have not been detected at centromeric (CEN) chromatin in wild-type budding yeast. Here we used an hpr1∆ strain that accumulates R-loops to investigate the consequences of R-loops at CEN chromatin and chromosome segregation. We show that Hpr1 interacts with the CEN-histone H3 variant, Cse4, and prevents the accumulation of R-loops at CEN chromatin for chromosomal stability. DNA–RNA immunoprecipitation (DRIP) analysis showed an accumulation of R-loops at CEN chromatin that was reduced by overexpression of RNH1 in hpr1∆ strains. Increased levels of ssDNA, reduced levels of Cse4 and its assembly factor Scm3, and mislocalization of histone H3 at CEN chromatin were observed in hpr1∆ strains. We determined that accumulation of R-loops at CEN chromatin contributes to defects in kinetochore biorientation and chromosomal instability (CIN) and these phenotypes are suppressed by RNH1 overexpression in hpr1∆ strains. In summary, our studies provide mechanistic insights into how accumulation of R-loops at CEN contributes to defects in kinetochore integrity and CIN.

A Review of Super-Resolution Single-Molecule Localization Microscopy Cluster Analysis and Quantification Methods

Single-molecule localization microscopy (SMLM) is a relatively new imaging modality, winning the 2014 Nobel Prize in Chemistry, and considered as one of the key super-resolution techniques. SMLM resolution goes beyond the diffraction limit of light microscopy and achieves resolution on the order of 10-20 nm. SMLM thus enables imaging single molecules and study of the low-level molecular interactions at the subcellular level. In contrast to standard microscopy imaging that produces 2D pixel or 3D voxel grid data, SMLM generates big data of 2D or 3D point clouds with millions of localizations and associated uncertainties. This unprecedented breakthrough in imaging helps researchers employ SMLM in many fields within biology and medicine, such as studying cancerous cells and cell-mediated immunity and accelerating drug discovery. However, SMLM data quantification and interpretation methods have yet to keep pace with the rapid advancement of SMLM imaging. Researchers have been actively exploring new computational methods for SMLM data analysis to extract biosignatures of various biological structures and functions. In this survey, we describe the state-of-the-art clustering methods adopted to analyze and quantify SMLM data and examine the capabilities and shortcomings of the surveyed methods. We classify the methods according to (1) the biological application (i.e., the imaged molecules/structures), (2) the data acquisition (such as imaging modality, dimension, resolution, and number of localizations), and (3) the analysis details (2D versus 3D, field of view versus region of interest, use of machine-learning and multi-scale analysis, biosignature extraction, etc.). We observe that the majority of methods that are based on second-order statistics are sensitive to noise and imaging artifacts, have not been applied to 3D data, do not leverage machine-learning formulations, and are not scalable for big-data analysis. Finally, we summarize state-of-the-art methodology, discuss some key open challenges, and identify future opportunities for better modeling and design of an integrated computational pipeline to address the key challenges.

Deriving and refining atomic models in crystallography and cryo-EM: the latest Phenix tools to facilitate structure analysis

In structural biology, deriving and refining atomic models into maps obtained from X-ray crystallography or cryo electron microscopy (cryo-EM) is essential for the detailed interpretation of a structure and its functional implications through interactions so that for example hydrogen bonds, drug specificity and associated molecular mechanisms can be analysed. This commentary summarizes the latest features of the Phenix software and also highlights the fact that cryo-EM increasingly contributes to data depositions in the PDB and EMDB.