Biology subjects

Solomon, O.

Publications and source records attributed to Solomon, O..

9 recordsLinked to original sources

bioRxiv2022

Loss of allosteric regulation in α-isopropylmalate synthase identified as an antimicrobial resistance mechanism

Despite our best efforts to discover new antimicrobials, bacteria have evolved mechanisms to become resistant. Resistance to antimicrobials can be attributed to innate, inducible, and acquired mechanisms. Mycobacterium abscessus is one of the most antimicrobial resistant bacteria and is known to cause chronic pulmonary infections within the cystic fibrosis community. Previously, we identified epetraborole as an inhibitor against M. abscessus with in vitro and in vivo activities and that the efficacy of epetraborole could be improved with the combination of the non-proteinogenic amino acid norvaline. Norvaline demonstrated activity against the M. abscessus epetraborole resistant mutants thus, limiting resistance to epetraborole in wild type populations. Here we show M. abscessus mutants with resistance to epetraborole can acquire resistance to norvaline in a leucyl-tRNA synthetase (LeuRS) editing-independent manner. After showing that the membrane hydrophobicity and efflux activity are not linked to norvaline resistance, whole-genome sequencing identified a mutation in the allosteric regulatory domain of -isopropylmalate synthase (-IPMS). We found that mutants with the -IPMSA555V variant incorporated less norvaline in the proteome and produced more leucine than the parental strain. Furthermore, we found that leucine can rescue growth inhibition from norvaline challenge in the parental strain. Our results demonstrate that M. abscessus can modulate its metabolism through mutations in an allosteric regulatory site to upregulate the biosynthesis of the natural LeuRS substrate and outcompete norvaline. These findings emphasize the antimicrobial resistant nature of M. abscessus and describe a unique mechanism of substrate-inhibitor competition. Significance StatementCystic fibrosis patients and individuals undergoing plastic surgery are at risk for acquiring chronic infections from Mycobacterium abscessus. Current antibiotics are not adequate and require increased drug discovery efforts to identify better treatments for these patients. The benzoxaborole, epetraborole has been shown by our group and others to be a promising candidate against M. abscessus but the emergence of resistance to epetraborole in a clinical trial for complicated urinary tract infections has hindered its development. Previously, we identified the combination of epetraborole and norvaline as a potential means to limit resistance against epetraborole. Our results here demonstrate that M. abscessus can acquire resistance to both epetraborole and norvaline. These results may help develop combination therapies to reduce the risk of resistance to benzoxaboroles and non-proteinogenic amino acids.

microbiology↗

bioRxiv2021

Doppler Slicing for Ultrasound Super-Resolution Without Contrast Agents

Much of the information needed for diagnosis and treatment monitoring of diseases like cancer and cardiovascular disease is found at scales below the resolution limit of classic ultrasound imaging. Recently introduced vascular super-localization methods provide more than a ten-fold improvement in spatial resolution by precisely estimating the positions of microbubble contrast agents. However, most vascular ultrasound scans are currently performed without contrast agents due to the associated cost, training, and post-scan monitoring. Here we show that super-resolution ultrasound imaging of dense vascular structures can be achieved using the natural contrast of flowing blood cells. Instead of relying on separable targets, we used Fourier-based decomposition to separate signals arising from the different scales of vascular structures while removing speckle noise using multi-ensemble processing. This approach enabled the use of compressed sensing for super-resolution imaging of the underlying vascular structures, improving resolution by a factor of four. Reconstruction of ultrafast mouse brain scans revealed details that could not be resolved in regular Doppler images, agreeing closely with bubble-based super-localization microscopy of the same fields of view. By combining multi-ensemble Doppler acquisitions with narrowband Fourier decomposition and computational super-resolution imaging, this approach opens new opportunities for affordable and scalable super-resolution ultrasound imaging.

bioengineering↗

bioRxiv2021

Electrochemical biosensors based on peptide-kinase interactions at the kinase docking site

Kinases are important cancer biomarkers and are conventionally detected based on their catalytic activity. Kinases regulate cellular activities by phosphorylation of motif-specific multiple substrate proteins, resulting in lack of selectivity of activity-based kinase biosensors. We present an alternative approach of sensing kinases based on the interactions of their allosteric docking sites with a specific partner protein. The new approach was demonstrated for the ERK2 kinase and its substrate ELK-1. A peptide derived from ELK-1 was bound to a gold electrode and ERK2 sensing was performed by electrochemical impedance spectroscopy. The sensors showed high level of target selectivity for ERK2 when compared with p38{gamma} kinase and BSA. ERK2 was detected in its cellular concentration range, 0.2-8.0 M. Using the flexibility of peptide design, our method is generic for developing sensitive and substrate-specific biosensors and other disease-related enzymes based on their interactions. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/468793v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@277550org.highwire.dtl.DTLVardef@870467org.highwire.dtl.DTLVardef@32098aorg.highwire.dtl.DTLVardef@1104840_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2020

Deep-learning based fully automatic segmentation of the globus pallidus interna and externa using ultra-high 7 Tesla MRI

Deep brain stimulation (DBS) surgery has been shown to dramatically improve the quality of life for patients with various motor dysfunctions, such as those afflicted with Parkinsons disease (PD), dystonia, and essential tremor (ET), by relieving motor symptoms associated with such pathologies. The success of DBS procedures is directly related to the proper placement of the electrodes, which requires the ability to accurately detect and identify relevant target structures within the subcortical basal ganglia region. In particular, accurate and reliable segmentation of the globus pallidus (GP) interna is of great interest for DBS surgery for PD and dystonia. In this work, we present a deep-learning based neural network, which we term GP-net, for the automatic segmentation of both the external and internal segments of the globus pallidus. High resolution 7 Tesla images from 101 subjects were used in this study; GP-net is trained on a cohort of 58 subjects, containing patients with movement disorders as well as healthy control subjects. GP-net performs 3D inference in a patient-specific manner, alleviating the need for atlas-based segmentation. GP-net was extensively validated, both quantitatively and qualitatively over 43 test subjects including patients with movement disorders and healthy control and is shown to consistently produce improved segmentation results compared with state-of-the-art atlas-based segmentations. We also demonstrate a post-operative lead location assessment with respect to a segmented globus pallidus obtained by GP-net.

neuroscience↗

bioRxiv2019

Identifying triplex binding rules in vitro leads to creation of a new synthetic regulatory tool in vivo

Nature provides a rich toolbox of dynamic nucleic acid structures that are widespread in cells and affect multiple biological processes1. Recently, non-canonical structures gained renewed scientific and biotechnological interest2,3. One particularly intriguing form of such structures are triplexes4 in which a single-stranded nucleic acid molecule interacts via Hoogsteen bonds with a DNA/RNA double helix5. Despite extensive research in vitro6-9, the underlying rules for triplex formation remain debated and evidence for triplexes in vivo is circumstantial10-12. Here, we demonstrate the development of a deep-sequencing platform termed Triplex-Seq to systematically refine the DNA triplex code and identify high affinity triplex forming oligo (TFO) variants. We identified a preference for short G-rich motifs using an oligo-library with a mix of all four bases. These high-information content motifs formed specific high-affinity triplexes in a pH-independent manner and stability was increased with G-rich double-stranded molecules. We then conjugated one high-affinity and one low-affinity variant to a VP48 peptide and studied these synthetic biomolecules in mammalian cells. Using these peptide-oligo constructs (POCs), we demonstrated possible triplex-induced down-regulation activity in 544 differentially expressed genes. Our results show that deep-sequencing platforms can substantially expand our understanding of triplex binding rules, which in turn has led to the development of a functional non-genetically encoded regulatory tool for in vivo applications.

synthetic biology↗

bioRxiv2018

Model-Aware Deep Learning Based Strategies for Clutter Suppression in Contrast Enhanced Ultrasound

Contrast enhanced ultrasound is a radiation-free imaging modality which uses encapsulated gas microbubbles for improved visualization of the vascular bed deep within the tissue. It has recently been used to enable imaging with unprecedented subwavelength spatial resolution by relying on super-resolution techniques. A typical preprocessing step in super-resolution ultrasound is to separate the microbubble signal from the cluttering tissue signal. This step has a crucial impact on the final image quality. Here, we propose a new approach to clutter removal based on robust principle component analysis (PCA) and deep learning. We begin by modeling the acquired contrast enhanced ultrasound signal as a combination of a low rank and sparse components. This model is used in robust PCA and was previously suggested in the context of ultrasound Doppler processing and dynamic magnetic resonance imaging. We then illustrate that an iterative algorithm based on this model exhibits improved separation of microbubble signal from the tissue signal over commonly practiced methods. Next, we apply the concept of deep unfolding to suggest a deep network architecture tailored to our clutter filtering problem which exhibits improved convergence speed and accuracy with respect to its iterative counterpart. We compare the performance of the suggested deep network on both simulations and in-vivo rat brain scans, with a commonly practiced deep-network architecture and the fast iterative shrinkage algorithm, and show that our architecture exhibits better image quality and contrast.

bioengineering↗

bioRxiv2017

Synthetic protein-sensing riboswitches

We study translational regulation by a 5 UTR sequence encoding the binding site of an RNA-binding protein (RBP) in bacteria, using a reporter assay and Selective 2-hydroxyl acylation analysed by primer extension sequencing (SHAPE-Seq). We tested constructs containing a single hairpin, based on the binding sites of the coat RBPs of bacteriophages GA, MS2, PP7, and Q{beta}, positioned in the 5 UTR of a reporter gene. With specifically-bound RBP present, either weak repression or up-regulation is observed, depending on the binding site and its flanking sequence. SHAPE-Seq data for a representative construct exhibiting up-regulation, indicates a partially-folded hairpin and non-reactive upstream and downstream flanking region, which we attribute to intermediate structures that apparently blocks translation. RBP binding stabilizes the fully-folded hairpin state and thus facilitates translation, suggesting that the up-regulating constructs are RBP-sensing riboswitches. This finding is further supported by lengthening the binding-site stem, which in turn destabilizes the translationally-inactive state, and abolishes the up-regulating behavior. Finally, we found that the combination of two binding sites, positioned in the 5 UTR and gene-header of the same transcript, can yield a cooperative regulatory response. Together, we show that the interaction of an RBP with its RNA target facilitates structural changes in the RNA, which is reflected by a controllable range of binding affinities and dose response behaviors. Thus, demonstrating that RNA-RBP interactions can provide a platform for constructing gene regulatory networks that are based on translational, rather than transcriptional, regulation.

synthetic biology↗

bioRxiv2017

An in vivo binding assay for RNA-binding proteins based on repression of a reporter gene

We employ a reporter assay and Selective 2'-hydroxyl acylation analysed by primer extension sequencing (SHAPE-seq) to study translational regulation by RNA-binding proteins, in bacteria. We designed 82 constructs, each with a single hairpin based on the binding sites of the RNA-binding coat proteins of phages MS2, PP7, GA, and Q{beta}, at various positions within the N-terminus of a reporter gene. In the absence of RNA-binding proteins, the translation level depends on hairpin location, and exhibits a three-nucleotide periodicity. For hairpin positions within the initiation region, we observe strong translational repression in the presence of its cognate RNA-binding protein. In vivo SHAPE-seq results for a representative construct indicate that the repression phenomenon correlates with a wide-swath of protection, including the hairpin and extending past the ribosome binding site. Consequently, our data suggest that the protection provided by the RBP-hairpin complex inhibits ribosomal initiation. Finally, utilizing the repression phenomenon for quantifying protein-RNA binding affinity in vivo, we both observe partially contrasting results to previous in vitro and in situ studies, and additionally, show that this method can be used in a high-throughput assay for a quantitative study of protein-RNA binding in vivo.

synthetic biology↗

bioRxiv2016

Short CT-rich motifs can trigger context-specific silencing of gene expression in bacteria

We use an oligonucleotide library of over 10000 variants together with a synthetic biology approach to identify an insulation mechanism encoded within a subset of {sigma}54 promoters. Insulation manifests itself as dramatically reduced protein expression for a downstream gene that may be expressed by transcriptional read-through. The insulation we observe is strongly associated with the presence of short CT-rich motifs (3-5 bp), positioned within 25 bp upstream of the Shine-Dalgarno (SD) motif of the silenced gene. We hypothesize that insulation is effected by binding of the RBS to the upstream CT-rich motif. We provide evidence to support this hypothesis using mutations to the CT-rich motif and gene expression measurements on multiple sequence variants. Modelling is also consistent with this hypothesis. We show that the strength of the silencing, effected by insulation, depends on the location and number of CT-rich motifs encoded within the promoters. Finally, we show that in E.coli these insulator sequences are preferentially encoded within {sigma}54 promoters as compared to other promoter types, suggesting a regulatory role for these sequences in natural contexts. Our findings suggest that context-related regulatory effects may often be due to sequence-specific interactions encoded sparsely by short motifs that are not easily detected by lower throughput studies. Such short sequence-specific phenomena can be uncovered with a focused OL design that filters out the sequence noise, as exemplified herein.

systems biology↗