TATA binding proteins can recognize nontraditional DNA sequences

Identifying promoter sequence architectures via a chunking-based algorithm using non-negative matrix factorisation

Core promoters are stretches of DNA at the beginning of genes that contain information that facilitates the binding of transcription initiation complexes. Different functional subsets of genes have core promoters with distinct architectures and characteristic motifs. Some of these motifs inform the selection of transcription start sites (TSS). By discovering motifs with fixed distances from known TSS positions, we could in principle classify promoters into different functional groups. Due to the variability and overlap of architectures, promoter classification is a difficult task that requires new approaches. In this study, we present a new method based on non-negative matrix factorisation (NMF) and the associated software called seqArchR that clusters promoter sequences based on their motifs at near-fixed distances from a reference point, such as TSS. When combined with experimental data from CAGE, seqArchR can efficiently identify TSS-directing motifs, including known ones like TATA, DPE, and nucleosome positioning signal, as well as novel lineage-specific motifs and the function of genes associated with them. By using seqArchR on developmental time courses, we reveal how relative use of promoter architectures changes over time with stage-specific expression. seqArchR is a powerful tool for initial genome-wide classification and functional characterisation of promoters. Its use cases are more general: it can also be used to discover any motifs at near-fixed distances from a reference point, even if they are present in only a small subset of sequences.

Solid-Phase Optical Sensing Techniques for Sensitive Virus Detection

Viral infections can pose a major threat to public health by causing serious illness, leading to pandemics, and burdening healthcare systems. The global spread of such infections causes disruptions to every aspect of life including business, education, and social life. Fast and accurate diagnosis of viral infections has significant implications for saving lives, preventing the spread of the diseases, and minimizing social and economic damages. Polymerase chain reaction (PCR)-based techniques are commonly used to detect viruses in the clinic. However, PCR has several drawbacks, as highlighted during the recent COVID-19 pandemic, such as long processing times and the requirement for sophisticated laboratory instruments. Therefore, there is an urgent need for fast and accurate techniques for virus detection. For this purpose, a variety of biosensor systems are being developed to provide rapid, sensitive, and high-throughput viral diagnostic platforms, enabling quick diagnosis and efficient control of the virus's spread. Optical devices, in particular, are of great interest due to their advantages such as high sensitivity and direct readout. The current review discusses solid-phase optical sensing techniques for virus detection, including fluorescence-based sensors, surface plasmon resonance (SPR), surface-enhanced Raman scattering (SERS), optical resonators, and interferometry-based platforms. Then, we focus on an interferometric biosensor developed by our group, the single-particle interferometric reflectance imaging sensor (SP-IRIS), which has the capability to visualize single nanoparticles, to demonstrate its application for digital virus detection.

The highly diverse TATA box-binding proteins among protists: A review

Transcription is the first step of gene expression regulation and is a fundamental mechanism for establishing the viability and development of a cell. The TATA box-binding protein (TBP) interaction with a TATA box in a promoter is one of the best studied mechanisms in transcription initiation. TBP is a transcription factor that is highly conserved from archaea to humans and is essential for the transcription initiated by each of the three RNA polymerases. In addition, the discovery of TBP-related factor 1 (TRF1) and other factors related to TBP shed light on the variability among transcription initiation complexes, thus demonstrating that the compositions of these complexes are, in fact, more complicated than originally believed. Despite these facts, the majority of studies on transcription have been performed on animal, plant and fungal cells, which serve as canonical models, and information regarding protist cells is relatively scarce. The aim of this work is to review the diversity of the TBPs that have been documented in protists and describe some of the specific features that differentiate them from their counterparts in higher eukaryotes.

Interferometric Reflectance Imaging Sensor (IRIS)--A Platform Technology for Multiplexed Diagnostics and Digital Detection

Over the last decade, the growing need in disease diagnostics has stimulated rapid development of new technologies with unprecedented capabilities. Recent emerging infectious diseases and epidemics have revealed the shortcomings of existing diagnostics tools, and the necessity for further improvements. Optical biosensors can lay the foundations for future generation diagnostics by providing means to detect biomarkers in a highly sensitive, specific, quantitative and multiplexed fashion. Here, we review an optical sensing technology, Interferometric Reflectance Imaging Sensor (IRIS), and the relevant features of this multifunctional platform for quantitative, label-free and dynamic detection. We discuss two distinct modalities for IRIS: (i) low-magnification (ensemble biomolecular mass measurements) and (ii) high-magnification (digital detection of individual nanoparticles) along with their applications, including label-free detection of multiplexed protein chips, measurement of single nucleotide polymorphism, quantification of transcription factor DNA binding, and high sensitivity digital sensing and characterization of nanoparticles and viruses.

Multiple novel promoter-architectures revealed by decoding the hidden heterogeneity within the genome

An important question in biology is how different promoter-architectures contribute to the diversity in regulation of transcription initiation. A step forward has been the production of genome-wide maps of transcription start sites (TSSs) using high-throughput sequencing. However, the subsequent step of characterizing promoters and their functions is still largely done on the basis of previously established promoter-elements like the TATA-box in eukaryotes or the -10 box in bacteria. Unfortunately, a majority of promoters and their activities cannot be explained by these few elements. Traditional motif discovery methods that identify novel elements also fail here, because TSS neighborhoods are often highly heterogeneous containing no overrepresented motif. We present a new, organism-independent method that explicitly models this heterogeneity while unraveling different promoter-architectures. For example, in five bacteria, we detect the presence of a pyrimidine preceding the TSS under very specific circumstances. In tuberculosis, we show for the first time that the spacing between the bacterial 10-motif and TSS is utilized by the pathogen for dynamic gene-regulation. In eukaryotes, we identify several new elements that are important for development. Identified promoter-architectures show differential patterns of evolution, chromatin structure and TSS spread, suggesting distinct regulatory functions. This work highlights the importance of characterizing heterogeneity within high-throughput genomic data rather than analyzing average patterns of nucleotide composition.

A high-throughput method to examine protein-nucleotide interactions identifies targets of the bacterial transcriptional regulatory protein fur

The Ferric uptake regulatory protein (Fur) is a transcriptional regulatory protein that functions to control gene transcription in response to iron in a number of pathogenic bacteria. In this study, we applied a label-free, quantitative and high-throughput analysis method, Interferometric Reflectance Imaging Sensor (IRIS), to rapidly characterize Fur-DNA interactions in vitro with predicted Fur binding sequences in the genome of Neisseria gonorrhoeae, the causative agent of the sexually transmitted disease gonorrhea. IRIS can easily be applied to examine multiple protein-protein, protein-nucleotide and nucleotide-nucleotide complexes simultaneously and demonstrated here that seventy percent of the predicted Fur boxes in promoter regions of iron-induced genes bound to Fur in vitro with a range of affinities as observed using this microarray screening technology. Combining binding data with mRNA expression levels in a gonococcal fur mutant strain allowed us to identify five new gonococcal genes under Fur-mediated direct regulation.

Genome-wide organization of eukaryotic preinitiation complex is influenced by nonconsensus protein-DNA binding

Genome-wide binding preferences of the key components of eukaryotic preinitiation complex (PIC) have been recently measured at high resolution in Saccharomyces cerevisiae by Rhee and Pugh. However, the rules determining the PIC binding specificity remain poorly understood. In this study, we show that nonconsensus protein-DNA binding significantly influences PIC binding preferences. We estimate that such nonconsensus binding contributes statistically at least 2-3 kcal/mol (on average) of additional attractive free energy per protein per core-promoter region. The predicted attractive effect is particularly strong at repeated poly(dA:dT) and poly(dC:dG) tracts. Overall, the computed free-energy landscape of nonconsensus protein-DNA binding shows strong correlation with the measured genome-wide PIC occupancy. Remarkably, statistical PIC preferences of binding to both TFIID-dominated and SAGA-dominated genes correlate with the nonconsensus free-energy landscape, yet these two groups of genes are distinguishable based on the average free-energy profiles. We suggest that the predicted nonconsensus binding mechanism provides a genome-wide background for specific promoter elements, such as transcription-factor binding sites, TATA-like elements, and specific binding of the PIC components to nucleosomes. We also show that nonconsensus binding has genome-wide influence on transcriptional frequency.

High-throughput label-free detection of DNA hybridization and mismatch discrimination using interferometric reflectance imaging sensor

Optical label-free biosensors have demonstrated advantages over fluorescent-based detection methods by allowing accurate quantification while also being capable of measuring dynamic bimolecular interactions. A simple, high-throughput, solid-phase, and label-free technique, interferometric reflectance imaging sensor (IRIS), can quantify the mass density of DNA with pg/mm(2) sensitivity by measuring the optical path difference. We present the design of the IRIS instrument and complementary microarrays that can be used to perform a quantitative analysis of DNA microarrays. Finally, we present methods to accurately calculate the hybridization efficiency and identify SNPs from dynamic measurements, as well as supporting software algorithms needed for robust data processing.