Aptamers for Infectious Disease Diagnosis

Aptamers are in vitro-selected, nucleic acids with unique abilities to bind strongly and specifically to their selective targets (ligands) based on their three-dimensional structures. Target binding is generally associated with a change in aptamer structure, which provides a means of linking many output signals to the binding event. Being synthetic, aptamers are less expensive compared to antibodies. Aptamers are also more easily modified chemically or their sequence changed to optimize properties such target specificity, storability and stability. In this chapter we will discuss the potential benefits of applying aptamers to diagnostics with a focus on infectious disease and the unique challenges posed by aptamers for their successful incorporation into reliable aptasensors

Correcting Model Misspecification via Generative Adversarial Networks

Machine learning models are often misspecified in the likelihood, which leads to a lack of robustness in the predictions. In this paper, we introduce a framework for correcting likelihood misspecifications in several paradigm agnostic noisy prior models and test the model's ability to remove the misspecification. The "ABC-GAN" framework introduced is a novel generative modeling paradigm, which combines Generative Adversarial Networks (GANs) and Approximate Bayesian Computation (ABC). This new paradigm assists the existing GANs by incorporating any subjective knowledge available about the modeling process via ABC, as a regularizer, resulting in a partially interpretable model that operates well under low data regimes. At the same time, unlike any Bayesian analysis, the explicit knowledge need not be perfect, since the generator in the GAN can be made arbitrarily complex. ABC-GAN eliminates the need for summary statistics and distance metrics as the discriminator implicitly learns them and enables simultaneous specification of multiple generative models. The model misspecification is simulated in our experiments by introducing noise of various biases and variances. The correction term is learnt via the ABC-GAN, with skip connections, referred to as skipGAN. The strength of the skip connection indicates the amount of correction needed or how misspecified the prior model is. Based on a simple experimental setup, we show that the ABC-GAN models not only correct the misspecification of the prior, but also perform as well as or better than the respective priors under noisier conditions. In this proposal, we show that ABC-GANs get the best of both worlds

Effect of phosphorylation on the structure and fold of transactivation domain of p53

Several phosphorylations are known to occur in the N-terminal transactivation domain of human p53. To explore the structural effects of these phosphorylations, we have chemically synthesized the unphosphorylated p53-(1-39) and its three phosphorylated analogs, phosphorylated at Ser-15, Thr-18, and Ser-20. p53-(1-39) and its Ser-15 and Thr-18 phosphorylated analogs were tested for interaction with p300. The order of binding affinities was similar to that derived from biochemical experiments with the whole protein, indicating functional integrity of the domain. Differences in chemical shifts and coupling constants indicate significant structural changes upon phosphorylations. The single tryptophan in the unphosphorylated domain has an emission maximum and a Stern-Volmer constant that are characteristics of tryptophans situated in protein interiors. The diffusion constant is monomer-like, with an axial ratio of 1:7.5, indicating a significant degree of compaction. Upon phosphorylations, the emission maximum and diffusion constant change significantly toward values that indicate more open conformations. Binding of the hydrophobic probe bis-1-anilino-8-naphthalenesulfonate to the unphosphorylated and one of the phosphorylated domains is also significantly different, suggesting different conformations. We propose that phosphorylations switch the largely folded transactivation domain to more open conformations that interact with transcription factors such as p300/cAMP- responsive element-binding protein-binding protein, leading to enhancement of gene expression

A Rare HBV Subgenotype D4 with Unique Genomic Signatures Identified in North-Eastern India –An Emerging Clinical Challenge?

BACKGROUND/AIMS: HBV has been classified into ten genotypes (A-J) and multiple subgenotypes, some of which strongly influence disease outcome and their distribution also correlate with human migration. HBV infection is highly prevalent in India and its diverse population provides an excellent opportunity to study the distinctiveness of HBV, its evolution and disease biology in variegated ethnic groups. The North-East India, having international frontiers on three sides, is one of the most ethnically and linguistically diverse region of the country. Given the paucity of information on molecular epidemiology of HBV in this region, the study aimed to carry out an in-depth genetic characterization of HBV prevailing in North-East state of Tripura. METHODS: From sera of chronically HBV infected patients biochemical/serological tests, HBV DNA quantification, PCR-amplification, sequencing of PreS/S or full-length HBV genomes were done. HBV genotype/subgenotype determination and sequence variability were assessed by MEGA5-software. The evolutionary divergence times of different HBV subgenotypes were estimated by DNAMLK/PHYLIP program while jpHMM method was used to detect any recombination event in HBV genomes. RESULTS: HBV genotypes D (89.5%), C (6.6%) and A (3.9%) were detected among chronic carriers. While all HBV/A and HBV/C isolates belonged to subgenotype-A1 and C1 respectively, five subgenotypes of HBV/D (D1-D5) were identified including the first detection of rare D4. These non-recombinant Indian D4 (IndD4) formed a distinct phylogenetic clade, had 2.7% nucleotide divergence and recent evolutionary radiation than other global D4. Ten unique amino acids and 9 novel nucleotide substitutions were identified as IndD4 signatures. All IndD4 carried T120 and R129 in ORF-S that may cause immune/vaccine/diagnostic escape and N128 in ORF-P, implicated as compensatory Lamivudine resistance mutation. CONCLUSIONS: IndD4 has potential to undermine vaccination programs or anti-viral therapy and its introduction to North-East India is believed to be linked with the settlement of ancient Tibeto-Burman migrants from East-Asia

Mph1p promotes gross chromosomal rearrangement through partial inhibition of homologous recombination

Gross chromosomal rearrangement (GCR) is a type of genomic instability associated with many cancers. In yeast, multiple pathways cooperate to suppress GCR. In a screen for genes that promote GCR, we identified MPH1, which encodes a 3′–5′ DNA helicase. Overexpression of Mph1p in yeast results in decreased efficiency of homologous recombination (HR) as well as delayed Rad51p recruitment to double-strand breaks (DSBs), which suggests that Mph1p promotes GCR by partially suppressing HR. A function for Mph1p in suppression of HR is further supported by the observation that deletion of both mph1 and srs2 synergistically sensitize cells to methyl methanesulfonate-induced DNA damage. The GCR-promoting activity of Mph1p appears to depend on its interaction with replication protein A (RPA). Consistent with this observation, excess Mph1p stabilizes RPA at DSBs. Furthermore, spontaneous RPA foci at DSBs are destabilized by the mph1Δ mutation. Therefore, Mph1p promotes GCR formation by partially suppressing HR, likely through its interaction with RPA