Heterogeneity of eukaryotic replicons, replicon clusters, and replication foci

According to the current paradigm, replication foci are discrete sites in the interphase nucleus where assemblies of DNA replication enzymes simultaneously elongate the replication forks of 10–100 adjacent replicons (each ∼100 kbp). Here we review new results and provide alternative interpretations for old results to show that the current paradigm is in need of further development. In particular, many replicons are larger than previously thought – so large that their complete replication takes much longer (several hours) than the measured average time to complete replication at individual foci (45–60 min). In addition to this large heterogeneity in replicon size, it is now apparent that there is also a corresponding heterogeneity in the size and intensity of individual replication foci. An important property of all replication foci is that they are stable structures that persist, with constant dimensions, during all cell cycle stages including mitosis, and therefore likely represent a fundamental unit of chromatin organization. With this in mind, we present a modified model of replication foci in which many of the foci are composed of clusters of small replicons as previously proposed, but the size and number of replicons per focus is extremely heterogeneous, and a significant proportion of foci are composed of single large replicons. We further speculate that very large replicons may extend over two or more individual foci and that this organization may be important in regulating the replication of such large replicons as the cell proceeds through S-phase. Received: 16 August 1999 / Accepted: 17 August 1999     

Rad51–Rad52 Mediated Maintenance of Centromeric Chromatin in Candida albicans

Specification of the centromere location in most eukaryotes is not solely dependent on the DNA sequence. However, the non-genetic determinants of centromere identity are not clearly defined. While multiple mechanisms, individually or in concert, may specify centromeres epigenetically, most studies in this area are focused on a universal factor, a centromere-specific histone H3 variant CENP-A, often considered as the epigenetic determinant of centromere identity. In spite of variable timing of its loading at centromeres across species, a replication coupled early S phase deposition of CENP-A is found in most yeast centromeres. Centromeres are the earliest replicating chromosomal regions in a pathogenic budding yeast Candida albicans. Using a 2-dimensional agarose gel electrophoresis assay, we identify replication origins (ORI7-LI and ORI7-RI) proximal to an early replicating centromere (CEN7) in C. albicans. We show that the replication forks stall at CEN7 in a kinetochore dependent manner and fork stalling is reduced in the absence of the homologous recombination (HR) proteins Rad51 and Rad52. Deletion of ORI7-RI causes a significant reduction in the stalled fork signal and an increased loss rate of the altered chromosome 7. The HR proteins, Rad51 and Rad52, have been shown to play a role in fork restart. Confocal microscopy shows declustered kinetochores in rad51 and rad52 mutants, which are evidence of kinetochore disintegrity. CENP-A^CaCse4 levels at centromeres, as determined by chromatin immunoprecipitation (ChIP) experiments, are reduced in absence of Rad51/Rad52 resulting in disruption of the kinetochore structure. Moreover, western blot analysis reveals that delocalized CENP-A molecules in HR mutants degrade in a similar fashion as in other kinetochore mutants described before. Finally, co-immunoprecipitation assays indicate that Rad51 and Rad52 physically interact with CENP-A^CaCse4 in vivo. Thus, the HR proteins Rad51 and Rad52 epigenetically maintain centromere functioning by regulating CENP-A^CaCse4 levels at the programmed stall sites of early replicating centromeres.     

Soluble cuticular phenoloxidase in the gypsy moth Lymantria dispar

The soluble enzyme phenoloxidase (tyrosinase) from the larval cuticle of Lymantria dispar has been partially purified using Ultrogel ACA 34, and the activity has been determined using phenolic substrates. The enzyme exhibited more activity toward O-diphenolic substrates and monophenolic substrates. The enzyme is inhibited by diethyl dithiocarbamate, phenylthiourea, and thiourea. The enzyme has been localized in the 7% slab and disc PAGE as an intense band. The enzyme is suggested to be involved in wound healing. © 1992 Wiley-Liss, Inc.     

A framework for considering prior information in network-based approaches to omics data analysis

For decades, molecular biologists have been uncovering the mechanics of biological systems. Efforts to bring their findings together have led to the development of multiple databases and information systems that capture and present pathway information in a computable network format. Concurrently, the advent of modern omics technologies has empowered researchers to systematically profile cellular processes across different modalities. Numerous algorithms, methodologies, and tools have been developed to use prior knowledge networks (PKNs) in the analysis of omics datasets. Interestingly, it has been repeatedly demonstrated that the source of prior knowledge can greatly impact the results of a given analysis. For these methods to be successful it is paramount that their selection of PKNs is amenable to the data type and the computational task they aim to accomplish. Here we present a five-level framework that broadly describes network models in terms of their scope, level of detail, and ability to inform causal predictions. To contextualize this framework, we review a handful of network-based omics analysis methods at each level, while also describing the computational tasks they aim to accomplish.     

Metabolic profiling for dissection of late leaf spot disease resistance mechanism in groundnut

Late leaf spot (LLS) caused by fungi Passalora personata is generally more destructive and difficult to control than early leaf spot. The aim of this study was to decipher biochemical defense mechanism in groundnut genotypes against P. personata by identifying resistance specific biomarkers and metabolic pathways induced during host–pathogen interaction. Metabolomics of non-infected and infected leaves of moderately resistant (GPBD4 and ICGV86590), resistant (KDG128 and RHRG06083) and susceptible (GG20, JL24 and TMV2) genotypes was carried out at 5 days after infection (65 days after sowing). Non-targeted metabolite analysis using GC–MS revealed total 77 metabolites including carbohydrates, sugar alcohols, amino acids, fatty acids, polyamines, phenolics, terpenes and sterols. Variable importance in projection (VIP) measure of partial least squares-discriminant analysis (PLS-DA) showed that resistant and moderately resistant genotypes possessed higher intensities of ribonic acid, cinnamic acid, malic acid, squalene, xylulose, galactose, fructose, glucose, β-amyrin and hydroquinone while susceptible genotypes had higher amount of gluconic acid 2-methoxime, ribo-hexose-3-ulose and gluconic acid. Heat map analysis showed that resistant genotypes had higher intensities of β-amyrin, hydroquinone in non-infected and malic acid, squalene, putrescine and 2,3,4-trihydroxybutyric acid in infected leaves. Dendrogram analysis further separated resistant genotypes in the same cluster along with infected moderately resistant genotypes. The most significant pathways identified are: linoleic acid metabolism, flavone and flavonol biosynthesis, cutin, suberin and wax biosynthesis, pentose and glucuronate interconversions, starch and sucrose metabolism, stilbenoid biosynthesis and ascorbate and aldarate metabolism. Targeted metabolite analysis further confirmed that resistant genotypes possessed higher content of primary metabolites sucrose, glucose, fructose, malic acid and citric acid. Moreover, resistant genotypes possessed higher content of salicylic, coumaric, ferulic, cinnamic, gallic acid (phenolic acids) and kaempferol, quercetin and catechin (flavonols). Thus metabolites having higher accumulation in resistant genotypes can be used as biomarkers for screening of LSS resistant germplasm. These results unravel that higher amount of primary metabolites leads to stimulate the accumulation of more amounts of secondary metabolites such as phenolic acid, flavanols, stilbenes and terpenoids (squalene and β-amyrin) biosynthesis which are ultimately involved in defense mechanism against LLS pathogen.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12298-021-00985-5.