As DNA research has developed, in this Special Issue of DNA, we aimed to explore recent advancements, with an emphasis on the DNA damage-induced alteration of cellular functions [...]
Human genomic DNA contains a number of diverse repetitive sequence motifs, often identified as fragile sites leading to genetic instability. Among them, expansion events occurring at triplet repeats have been extensively studied due to their association with neurological disorders, including Huntington’s disease (HD). In the case of HD, expanded CAG triplet repeats in the HTT gene are thought to cause the onset. The expansion of CAG triplet repeats is believed to be triggered by the emergence of stem-loops composed of CAG triplet repeats, while the underlying molecular mechanisms are largely unknown. Therefore, identifying proteins recruited on such stem loops would be useful to understand the molecular mechanisms leading to the genetic instability of CAG triplet repeats. We previously developed a plasmid DNA pull-down methodology that captures proteins specifically assembled on any sequence of interest using nuclear extracts. Analysis by Mass Spectrometry revealed that among the proteins specifically bound to a stem-loop composed of CAG triplet repeats, many turned out to belong to DNA repair pathways. We expect our data set to represent a useful entry point for the design of assays allowing the molecular mechanisms of genetic instability at CAG triplet repeats to be explored.
Both the number of cells and the collective genome of the gut microbiota outnumber their mammalian hosts, and the metabolic and physiological interactions of the gut microbiota with the host have not yet been fully characterized. Cancer remains one of the leading causes of death, and more research into the critical events that can lead to cancer and the importance of the gut microbiota remains to be determined. The gut microbiota can release microbial molecules that simulate host endogenous processes, such as inflammatory responses, or can alter host metabolism of ingested substances. Both of these reactions can be beneficial or deleterious to the host, and some can be genotoxic, thus contributing to cancer progression. This review focused on the molecular evidence currently available on the mechanistic understanding of how the gut microbiota are involved in human carcinogenesis. We first reviewed the key events of carcinogenesis, especially how DNA damage proceeds to tumor formulation. Then, the current knowledge on host DNA damage attributed to the gut microbiota was summarized, followed by the genotoxic endogenous processes the gut microbiota can induce. Finally, we touched base on the association between specific gut microbiota dysbiosis and different types of cancer and concluded with the up-to-date knowledge as well as future research direction for advancing our understanding of the relationship between the gut microbiota and cancer development.
DNA G-quadruplexes (G4s) are non-canonical secondary structures formed in guanine-rich sequences. Within the human genome, G4s are found in regulatory regions such as gene promoters and telomeres to control replication, transcription, and telomere lengthening. In the cellular context, there are several proteins named as G4-binding proteins (G4BPs) that interact with G4s, either anchoring upon, stabilizing, and/or unwinding them. These proteins may play different key roles in the regulation of the endogenous G4 landscape and its associated functions. The present review summarizes the current literature on G4BPs in terms of their targets and functions, providing updated insights into the regulation of G4s in living organisms.
DNA methyltransferase 1 (DNMT1) is the enzyme primarily responsible for propagation of the methylation pattern in cells. Mutations in DNMT1 have been linked to the development of adult-onset neurodegenerative disorders; these disease-associated mutations occur in the regulatory replication foci-targeting sequence (RFTS) domain of the protein. The RFTS domain is an endogenous inhibitor of DNMT1 activity that binds to the active site and prevents DNA binding. Here, we examine the impact of the disease-associated mutation A554V on normal RFTS-mediated inhibition of DNMT1. Wild-type and mutant proteins were expressed and purified to homogeneity for biochemical characterization. The mutation increased DNA binding affinity ~8-fold. In addition, the mutant enzyme exhibited increased DNA methylation activity. Circular dichroism (CD) spectroscopy revealed that the mutation does not significantly impact the secondary structure or relative thermal stability of the isolated RFTS domain. However, the mutation resulted in changes in the CD spectrum in the context of the larger protein; a decrease in relative thermal stability was also observed. Collectively, this evidence suggests that A554V disrupts normal RFTS-mediated autoinhibition of DNMT1, resulting in a hyperactive mutant enzyme. While the disease-associated mutation does not significantly impact the isolated RFTS domain, the mutation results in a weakening of the interdomain stabilizing interactions generating a more open, active conformation of DNMT1. Hyperactive mutant DNMT1 could be responsible for the increased DNA methylation observed in affected individuals.
Preimplantation genetic testing for structural rearrangements (PGT-SR) was one of the first applications of PGT, with initial cases being worked up in the Delhanty lab. It is the least well-known of the various forms of PGT but nonetheless provides effective treatment for many carrier couples. Structural chromosomal rearrangements (SRs) lead to infertility, repeated implantation failure, pregnancy loss, and congenitally affected children, despite the balanced parent carrier having no obvious phenotype. A high risk of generating chromosomally unbalanced gametes and embryos is the rationale for PGT-SR, aiming to select for those that are chromosomally normal, or at least balanced like the carrier parent. PGT-SR largely uses the same technology as PGT-A, i.e., initially FISH, superseded by array CGH, SNP arrays, Karyomapping, and, most recently, next-generation sequencing (NGS). Trophectoderm biopsy is now the most widely used sampling approach of all PGT variants, though there are prospects for non-invasive methods. In PGT-SR, the most significant limiting factor is the availability of normal or balanced embryo(s) for transfer. Factors directly affecting this are rearrangement type, chromosomes involved, and sex of the carrier parent. De novo aneuploidy, especially for older mothers, is a common limiting factor. PGT-SR studies provide a wealth of information, much of which can be useful to genetic counselors and the patients they treat. It is applicable in the fundamental study of basic chromosomal biology, in particular the purported existence of an interchromosomal effect (ICE). An ICE means essentially that the existence of one chromosomal defect (e.g., brought about by malsegregation of translocation chromosomes) can perpetuate the existence of others (e.g., de novo aneuploidy). Recent large cohort studies of PGT-SR patients seem, however, to have laid this notion to rest, at least for human embryonic development. Unless new evidence comes to light, this comprehensive review should serve as a requiem.
In preimplantation testing for monogenic disease (PGT-M), we are used to specific and directed diagnoses. Preimplantation testing for polygenic disease (PGT-P), however, represents a further level of complexity in that multiple genes are tested for with an associated polygenic risk score (PRS), usually established by a genome-wide association study (GWAS). PGT-P has a series of pros and cons and, like many areas of genetics in reproductive medicine, there are vocal proponents and opponents on both sides. As with all things, the question needs to be asked, how much benefit does PGT-P provide in comparison to the risks involved? For each disease, a case will need to be made for PGT-P, as will a justification that the family involved will actually benefit; the worry is that this might be more work than the cost justifies.
WRKY transcription factors play a pivotal role in regulating stress signaling pathways, including those associated with salt stress response. The present work characterized the effects of two WRKY genes from Vigna unguiculata, namely VuWRKY21 and VuWRKY87, on enhancing plant salinity tolerance. Under salt stress conditions, Arabidopsis lines expressing VuWRKY21 or VuWRKY87 showed elevated expression of genes participating in saline stress response pathways and reduced oxidative stress induced by reactive oxygen species (ROS). Among the salt-responsive genes in Arabidopsis, AtP5CS1, AtNHX1, AtRD29A, AtSOS3, AtSOS2, and AtSOS1 exhibited modulated expression levels after stress imposition. Furthermore, compared to wild-type plants, at most evaluated times, transgenic lines, on average, presented lower H2O2 content while displaying higher content of SOD (EC: 1.15.1.1) and CAT (EC: 1.11.1.6) at early stages of salt stress. These findings suggest that the expression of both VuWRKY genes in Arabidopsis, particularly VuWRKY21, activated genes involved in salinity tolerance.
The DNA photocleavage effect of halogenated O-carbamoyl derivatives of 4-MeO-benzamidoxime under UVB and UVA irradiation was studied in order to identify the nature, position, and number of halogens on the carbamoyl moiety that ensure photoactivity. F, Cl, and Br-phenyl carbamate esters (PCME) exhibited activity with the p-Cl-phenyl derivative to show excellent photocleavage against pBR322 plasmid DNA. m-Cl-PCME has diminished activity, whereas the presence of two halogen atoms reduced DNA photocleavage. The substitution on the benzamidoxime scaffold was irrelevant to the activity. The mechanism of action indicated function in the absence of oxygen, probably via radicals derived from the N-O bond homolysis of the carbamates and in air via hydroxyl radicals and partially singlet oxygen. The UVA-vis area of absorption of the nitro-benzamidoxime p-Cl-PCMEs allowed for the investigation of their potential efficacy as photopesticides under UVA irradiation against the whitefly Bemisia tabaci, a major pest of numerous crops. The m-nitro derivative exhibited a moderate specificity against the adult population. Nymphs were not affected. The compound was inactive in the dark. This result may allow for the development of lead compounds for the control of agricultural insect pests that can cause significant economic damage in crop production.
The mummy of a seven-year-old child that was discovered in 1985 in Cerro Aconcagua (Mendoza, Argentina) was likely part of an Inka sacrificial religious practice known as capacocha. Previous uniparental DNA marker studies conducted by some scholars have suggested that the mummified child may be related to the southern Andean population of Peru. However, autosome genome-wide analysis performed by others has indicated that the child was more closely related to the population along the northern Peruvian coast than to that of the southern Andes. In this study, we aimed to determine possible genealogical connections in the male lineage of the mummified child. To achieve this, we compared the genetic profile of the mummy with an extensive database of contemporary individuals from the northern Peruvian coastal and southern Andean regions. We used single nucleotide polymorphisms and short tandem repeats from the nonrecombining region of the Y-chromosome for our analysis. Our results confirmed that the Inka child mummy was closely related to individuals from the north coast of Peru. This suggests that the child was likely descended from the Muchik–Chimor-speaking people.
Nucleic acid methylations are important genetic and epigenetic biomarkers. The formation and removal of these markers is related to either methylation or demethylation. In this review, we focus on the demethylation or oxidative modification that is mediated by the 2-oxoglutarate (2-OG)/Fe(II)-dependent AlkB/TET family enzymes. In the catalytic process, most enzymes oxidize 2-OG to succinate, in the meantime oxidizing methyl to hydroxymethyl, leaving formaldehyde and generating demethylated base. The AlkB enzyme from Escherichia coli has nine human homologs (ALKBH1-8 and FTO) and the TET family includes three members, TET1 to 3. Among them, some enzymes have been carefully studied, but for certain enzymes, few studies have been carried out. This review focuses on the kinetic properties of those 2-OG/Fe(II)-dependent enzymes and their alkyl substrates. We also provide some discussions on the future directions of this field.
Teratozoospermia, a complex male fertility disorder affecting sperm morphology, has been linked to AURKC, SPATA16, and SUN5 gene defects. However, the sheer volume of SNPs in these genes necessitates prioritization for comprehensive analysis. This study focuses on the often-overlooked untranslated region (UTR) variants in these genes, aiming to assess their association with teratozoospermia and prioritize them. We employed a multi-step filtering process, including functional significance assessment (RegulomeDB, 3DSNP v2.0, SNPinfo (FuncPred)), evaluation of gene expression impacts in testis tissue using GTEx, and assessment of miRNA binding site effects (PolymiRTS Database 3.0, miRNASNP v3). Additionally, we used SNPnexus to evaluate their conservation and association with diseases. In AURKC, we identified six UTR SNPs (rs11084490, rs58264281, rs35582299, rs533889458, rs2361127, rs55710619), two of which influenced gene expression in testis, while others affected the binding sites of 29 miRNAs or were located in transcription-factor binding sites. Three of these SNPs were also found to be associated with spermatogenic failure according to previous studies indicating a potential regulatory role in teratozoospermia, too. For SPATA16, two 3′ UTR variants, rs146640459 and rs148085657, were prioritized, with the latter impacting miRNA binding sites. In SUN5, three 3′ UTR variants (rs1485087675, rs762026146, rs1478197315) affected miRNA binding sites. It should be noted that none of the above variants was identified in a conserved region. Our findings shed light on the potential regulatory roles of these SNPs in teratozoospermia and lay the foundation for future research directions in this area.
Molecular computation involving promiscuous, or non-orthogonal, binding interactions between system components is found commonly in natural biological systems, as well as some proposed human-made molecular computers. Such systems are characterized by the fact that each computational unit, such as a domain within a DNA strand, may bind to several different partners with distinct, prescribed binding strengths. Unfortunately, implementing systems of molecular computation that incorporate non-orthogonal binding is difficult, because researchers lack a robust, general-purpose method for designing molecules with this type of behavior. In this work, we describe and demonstrate a process for the rational design of DNA sequences with prescribed non-orthogonal binding behavior. This process makes use of a model that represents large sets of non-orthogonal DNA sequences using fixed-length binary strings, and estimates the differential binding affinity between pairs of sequences through the Hamming distance between their corresponding binary strings. The real-world applicability of this model is supported by simulations and some experimental data. We then select two previously described systems of molecular computation involving non-orthogonal interactions, and apply our sequence design process to implement them using DNA strand displacement. Our simulated results on these two systems demonstrate both digital and analog computation. We hope that this work motivates the development and implementation of new computational paradigms based on non-orthogonal binding.
Nucleic acid strands, which react by forming and breaking Watson-Crick base pairs, can be designed to form complex nanoscale structures or devices. Controlling such systems requires accurate predictions of the reaction rate and of the folding pathways of interacting strands. Simulators such as Multistrand model these kinetic properties using continuous-time Markov chains (CTMCs), whose states and transitions correspond to secondary structures and elementary base pair changes, respectively. The transient dynamics of a CTMC are determined by a kinetic model, which assigns transition rates to pairs of states, and the rate of a reaction can be estimated using the mean first passage time (MFPT) of its CTMC. However, use of Multistrand is limited by its slow runtime, particularly on rare events, and the quality of its rate predictions is compromised by a poorly-calibrated and simplistic kinetic model. The former limitation can be addressed by constructing truncated CTMCs, which only include a small subset of states and transitions, selected either manually or through simulation. As a first step to address the latter limitation, Bayesian posterior inference in an Arrhenius-type kinetic model was performed in earlier work, using a small experimental dataset of DNA reaction rates and a fixed set of manually truncated CTMCs, which we refer to as Assumed Pathway (AP) state spaces. In this work we extend this approach, by introducing a new prior model that is directly motivated by the physical meaning of the parameters and that is compatible with experimental measurements of elementary rates, and by using a larger dataset of 1105 reactions as well as larger truncated state spaces obtained from the recently introduced stochastic Pathway Elaboration (PE) method. We assess the quality of the resulting posterior distribution over kinetic parameters, as well as the quality of the posterior reaction rates predicted using AP and PE state spaces. Finally, we use the newly parameterised PE state spaces and Multistrand simulations to investigate the strong variation of helix hybridization reaction rates in a dataset of Hata et al. While we find strong evidence for the nucleation-zippering model of hybridization, in the classical sense that the rate-limiting phase is composed of elementary steps reaching a small “nucleus” of critical stability, the strongly sequence-dependent structure of the trajectory ensemble up to nucleation appears to be much richer than assumed in the model by Hata et al. In particular, rather than being dominated by the collision probability of nucleation sites, the trajectory segment between first binding and nucleation tends to visit numerous secondary structures involving misnucleation and hairpins, and has a sizeable effect on the probability of overcoming the nucleation barrier.
We present an abstract model of self-assembly of systems composed of “crisscross slats”, which have been experimentally implemented as a single-stranded piece of DNA [21] or as a complete DNA origami structure [28]. We then introduce a more physically realistic “kinetic” model and show how important constants in the model were derived and tuned, and compare simulation-based results to experimental results [21,28]. Using these models, we show how we can apply optimizations to designs of slat systems in order to lower the numbers of unique slat types required to build target structures. In general, we apply two types of techniques to achieve greatly reduced numbers of slat types. Similar to the experimental work implementing DNA origami-based slats, in our designs the slats oriented in horizontal and vertical directions are each restricted to their own plane and sets of them overlap each other in square regions which we refer to as macrotiles . Our first technique extends their previous work of reusing slat types within macrotiles and requires analyses of binding domain patterns to determine the potential for errors consisting of incorrect slat types attaching at undesired translations and reflections. The second technique leverages the power of algorithmic self-assembly to efficiently reuse entire macrotiles which self-assemble in patterns following designed algorithms that dictate the dimensions and patterns of growth. Using these designs, we demonstrate that in kinetic simulations the systems with reduced numbers of slat types self-assemble more quickly than those with greater numbers. This provides evidence that such optimizations will also result in greater assembly speeds in experimental systems. Furthermore, the reduced numbers of slat types required have the potential to vastly reduce the cost and number of lab steps for crisscross assembly experiments.
Transcription factor A, mitochondrial (TFAM) is a key player in mitochondrial DNA (mtDNA) transcription and replication [...]
Rapid and modular assembly of DNA parts is crucial to many synthetic biologists. This can be achieved through Golden Gate assembly, which often requires purchase and delivery of new primers for each part and assembly configuration. Here, we report on a small set of primers that can be used to amplify any DNA from the Registry of Standard Biological Parts for Golden Gate assembly. These primers bind to regions common to the backbone plasmid for these parts, but pair imperfectly and introduce type IIS restriction enzyme sites in a way that minimizes assembly scars. This approach makes redesign of assembly strategies faster and less expensive and can help expand access to synthetic biology to a wider group of scientists and students.
Discrete chemical reaction networks formalize the interactions of molecular species in a well-mixed solution as stochastic events. Given their basic mathematical and physical role, the computational power of chemical reaction networks has been widely studied in the molecular programming and distributed computing communities. While for Turing-universal systems there is a universal measure of optimal information encoding based on Kolmogorov complexity, chemical reaction networks are not Turing universal unless error and unbounded molecular counts are permitted. Nonetheless, here we show that the optimal number of reactions to generate a specific count $x \in \mathbb{N}$ with probability $1$ is asymptotically equal to a ``space-aware'' version of the Kolmogorov complexity of $x$, defined as $\mathrm{\widetilde{K}s}(x) = \min_p\left\{\lvert p \rvert / \log \lvert p \rvert + \log(\texttt{space}(\mathcal{U}(p))) : \mathcal{U}(p) = x \right\}$, where $p$ is a program for universal Turing machine $\mathcal{U}$. This version of Kolmogorov complexity incorporates not just the length of the shortest program for generating $x$, but also the space usage of that program. Probability $1$ computation is captured by the standard notion of stable computation from distributed computing, but we limit our consideration to chemical reaction networks obeying a stronger constraint: they ``know when they are done'' in the sense that they produce a special species to indicate completion. As part of our results, we develop a module for encoding and unpacking any $b$ bits of information via $O(b/\log{b})$ reactions, which is information-theoretically optimal for incompressible information. Our work provides one answer to the question of how succinctly chemical self-organization can be encoded -- in the sense of generating precise molecular counts of species as the desired state.
