Towards Sequence-Based DNA Flexibility Analysis

In this poster, we present an extension to our freely available KINARI-Web server to identify rigid and flexible regions of nucleic acids and protein-nucleic acid complexes contained in the Protein Data Bank (PDB). The goal is to explore the effect of DNA and RNA on the rigidity and stability of these structures. We also propose an approach for determining DNA rigidity based solely on sequence. Currently, only the rigidity of DNA molecules whose structures have been deposited in the PDB (approx. \u3c4,000 files) can be analyzed. Once fine-tuned and validated, this new coordinate-free method for investigating DNA flexibility could be applied to the more than 135 million sequences in GenBank, and to nanostructure design

Revisiting the anomalous bending elasticity of sharply bent DNA

Several recent experiments suggest that sharply bent DNA has a surprisingly high bending flexibility, but the cause of this flexibility is poorly understood. Although excitation of flexible defects can explain these results, whether such excitation can occur with the level of DNA bending in these experiments remains unclear. Intriguingly, the DNA contained preexisting nicks in most of these experiments but whether nicks might play a role in flexibility has never been considered in the interpretation of experimental results. Here, using full-atom molecular dynamics simulations, we show that nicks promote DNA basepair disruption at the nicked sites, which drastically reduces DNA bending energy. In addition, lower temperatures suppress the nick-dependent basepair disruption. In the absence of nicks, basepair disruption can also occur but requires a higher level of DNA bending. Therefore, basepair disruption inside B-form DNA can be suppressed if the DNA contains preexisting nicks. Overall, our results suggest that the reported mechanical anomaly of sharply bent DNA is likely dependent on preexisting nicks, therefore the intrinsic mechanisms of sharply bent nick-free DNA remain an open question.Comment: 39 pages, 11 figures, 1 supporting materia

Social Fingerprinting: detection of spambot groups through DNA-inspired behavioral modeling

Spambot detection in online social networks is a long-lasting challenge involving the study and design of detection techniques capable of efficiently identifying ever-evolving spammers. Recently, a new wave of social spambots has emerged, with advanced human-like characteristics that allow them to go undetected even by current state-of-the-art algorithms. In this paper, we show that efficient spambots detection can be achieved via an in-depth analysis of their collective behaviors exploiting the digital DNA technique for modeling the behaviors of social network users. Inspired by its biological counterpart, in the digital DNA representation the behavioral lifetime of a digital account is encoded in a sequence of characters. Then, we define a similarity measure for such digital DNA sequences. We build upon digital DNA and the similarity between groups of users to characterize both genuine accounts and spambots. Leveraging such characterization, we design the Social Fingerprinting technique, which is able to discriminate among spambots and genuine accounts in both a supervised and an unsupervised fashion. We finally evaluate the effectiveness of Social Fingerprinting and we compare it with three state-of-the-art detection algorithms. Among the peculiarities of our approach is the possibility to apply off-the-shelf DNA analysis techniques to study online users behaviors and to efficiently rely on a limited number of lightweight account characteristics

Genetic affinities within a large global collection of pathogenic <i>Leptospira</i>: implications for strain identification and molecular epidemiology

Leptospirosis is an important zoonosis with widespread human health implications. The non-availability of accurate identification methods for the individualization of different Leptospira for outbreak investigations poses bountiful problems in the disease control arena. We harnessed fluorescent amplified fragment length polymorphism analysis (FAFLP) for Leptospira and investigated its utility in establishing genetic relationships among 271 isolates in the context of species level assignments of our global collection of isolates and strains obtained from a diverse array of hosts. In addition, this method was compared to an in-house multilocus sequence typing (MLST) method based on polymorphisms in three housekeeping genes, the rrs locus and two envelope proteins. Phylogenetic relationships were deduced based on bifurcating Neighbor-joining trees as well as median joining network analyses integrating both the FAFLP data and MLST based haplotypes. The phylogenetic relationships were also reproduced through Bayesian analysis of the multilocus sequence polymorphisms. We found FAFLP to be an important method for outbreak investigation and for clustering of isolates based on their geographical descent rather than by genome species types. The FAFLP method was, however, not able to convey much taxonomical utility sufficient to replace the highly tedious serotyping procedures in vogue. MLST, on the other hand, was found to be highly robust and efficient in identifying ancestral relationships and segregating the outbreak associated strains or otherwise according to their genome species status and, therefore, could unambiguously be applied for investigating phylogenetics of Leptospira in the context of taxonomy as well as gene flow. For instance, MLST was more efficient, as compared to FAFLP method, in clustering strains from the Andaman island of India, with their counterparts from mainland India and Sri Lanka, implying that such strains share genetic relationships and that leptospiral strains might be frequently circulating between the islands and the mainland

Biophysical and electrochemical studies of protein-nucleic acid interactions

This review is devoted to biophysical and electrochemical methods used for studying protein-nucleic acid (NA) interactions. The importance of NA structure and protein-NA recognition for essential cellular processes, such as replication or transcription, is discussed to provide background for description of a range of biophysical chemistry methods that are applied to study a wide scope of protein-DNA and protein-RNA complexes. These techniques employ different detection principles with specific advantages and limitations and are often combined as mutually complementary approaches to provide a complete description of the interactions. Electrochemical methods have proven to be of great utility in such studies because they provide sensitive measurements and can be combined with other approaches that facilitate the protein-NA interactions. Recent applications of electrochemical methods in studies of protein-NA interactions are discussed in detail