Narrowing Signal Distribution by Adamantane Derivatization for Amino Acid Identification Using an α-Hemolysin Nanopore.

The rapid progress in nanopore sensing has sparked interest in protein sequencing. Despite recent notable advancements in amino acid recognition using nanopores, chemical modifications usually employed in this process still need further refinements. One of the challenges is to enhance the chemical specificity to avoid downstream misidentification of amino acids. By employing adamantane to label proteinogenic amino acids, we developed an approach to fingerprint individual amino acids using the wild-type α-hemolysin nanopore. The unique structure of adamantane-labeled amino acids (ALAAs) improved the spatial resolution, resulting in distinctive current signals. Various nanopore parameters were explored using a machine-learning algorithm and achieved a validation accuracy of 81.3% for distinguishing nine selected amino acids. Our results not only advance the effort in single-molecule protein characterization using nanopores but also offer a potential platform for studying intrinsic and variant structures of individual molecules.

Engineering Biological Nanopore Approaches toward Protein Sequencing.

Biotechnological innovations have vastly improved the capacity to perform large-scale protein studies, while the methods we have for identifying and quantifying individual proteins are still inadequate to perform protein sequencing at the single-molecule level. Nanopore-inspired systems devoted to understanding how single molecules behave have been extensively developed for applications in genome sequencing. These nanopore systems are emerging as prominent tools for protein identification, detection, and analysis, suggesting realistic prospects for novel protein sequencing. This review summarizes recent advances in biological nanopore sensors toward protein sequencing, from the identification of individual amino acids to the controlled translocation of peptides and proteins, with attention focused on device and algorithm development and the delineation of molecular mechanisms with the aid of simulations. Specifically, the review aims to offer recommendations for the advancement of nanopore-based protein sequencing from an engineering perspective, highlighting the need for collaborative efforts across multiple disciplines. These efforts should include chemical conjugation, protein engineering, molecular simulation, machine-learning-assisted identification, and electronic device fabrication to enable practical implementation in real-world scenarios.

In vitro and ex vivo proteomics of Mycobacterium marinum biofilms and the development of biofilm-binding synthetic nanobodies.

The antibiotic-tolerant biofilms present in tuberculous granulomas add an additional layer of complexity when treating mycobacterial infections, including tuberculosis (TB). For a more efficient treatment of TB, the biofilm forms of mycobacteria warrant specific attention. Here, we used Mycobacterium marinum (Mmr) as a biofilm-forming model to identify the abundant proteins covering the biofilm surface. We used biotinylation/streptavidin-based proteomics on the proteins exposed at the Mmr biofilm matrices in vitro to identify 448 proteins and ex vivo proteomics to detect 91 Mmr proteins from the mycobacterial granulomas isolated from adult zebrafish. In vitro and ex vivo proteomics data are available via ProteomeXchange with identifiers PXD033425 and PXD039416, respectively. Data comparisons pinpointed the molecular chaperone GroEL2 as the most abundant Mmr protein within the in vitro and ex vivo proteomes, while its paralog, GroEL1, with a known role in biofilm formation, was detected with slightly lower intensity values. To validate the surface exposure of these targets, we created in-house synthetic nanobodies (sybodies) against the two chaperones and identified sybodies that bind the mycobacterial biofilms in vitro and those present in ex vivo granulomas. Taken together, the present study reports a proof-of-concept showing that surface proteomics in vitro and ex vivo proteomics combined is a valuable strategy to identify surface-exposed proteins on the mycobacterial biofilm. Biofilm surface-binding nanobodies could be eventually used as homing agents to deliver biofilm-targeting treatments to the sites of persistent biofilm infection. IMPORTANCE With the currently available antibiotics, the treatment of TB takes months. The slow response to treatment is caused by antibiotic tolerance, which is especially common among bacteria that form biofilms. Such biofilms are composed of bacterial cells surrounded by the extracellular matrix. Both the matrix and the dormant lifestyle of the bacterial cells are thought to hinder the efficacy of antibiotics. To be able to develop faster-acting treatments against TB, the biofilm forms of mycobacteria deserve specific attention. In this work, we characterize the protein composition of Mmr biofilms in bacterial cultures and in mycobacteria extracted from infected adult zebrafish. We identify abundant surface-exposed targets and develop the first sybodies that bind to mycobacterial biofilms. As nanobodies can be linked to other therapeutic compounds, in the future, they can provide means to target therapies to biofilms.

A recyclable thermoset with built-in thermocleavable group developed from a cis-cyclobutane-1,2-dicarboxylic acid.

A novel class of recyclable thermoset has been developed from cis-3,4-diphenylcyclobutane-1,2-dicarboxylic acid (CBDA-4) due to its thermocleavability at high temperature. This key CBDA-4 building block was synthesized from ß-trans-cinnamic acid using a [2+2] photocycloaddition reaction. CBDA-4 was subsequently linked with glycerol via esterification to give a thermoset with Tg of 68 °C. The thermoset was heated to 300 °C to analyze its degradation. A key intermediate was successfully obtained after purification of the degraded polymer. NMR, FT-IR, HRMS, and single crystal X-ray diffraction confirmed the intermediate was glycerol cinnamate, which was the result of splitting cyclobutane in the polymer backbone at high temperature. Glycerol cinnamate was readily hydrolyzed reforming the starting materials glycerol and trans-cinnamic acid to complete the recycling loop.

Nanopore sensing: A physical-chemical approach.

Protein nanopores have emerged as an important class of sensors for the understanding of biophysical processes, such as molecular transport across membranes, and for the detection and characterization of biopolymers. Here, we trace the development of these sensors from the Coulter counter and squid axon studies to the modern applications including exquisite detection of small volume changes and molecular reactions at the single molecule (or reactant) scale. This review focuses on the chemistry of biological pores, and how that influences the physical chemistry of molecular detection.

Laser-based temperature control to study the roles of entropy and enthalpy in polymer-nanopore interactions.

Single-molecule approaches for probing the free energy of confinement for polymers in a nanopore environment are critical for the development of nanopore biosensors. We developed a laser-based nanopore heating approach to monitor the free energy profiles of such a single-molecule sensor. Using this approach, we measure the free energy profiles of two distinct polymers, polyethylene glycol and water-soluble peptides, as they interact with the nanopore sensor. Polyethylene glycol demonstrates a retention mechanism dominated by entropy with little sign of interaction with the pore, while peptides show an enthalpic mechanism, which can be attributed to physisorption to the nanopore (e.g., hydrogen bonding). To manipulate the energetics, we introduced thiolate-capped gold clusters [Au25(SG)18] into the pore, which increases the charge and leads to additional electrostatic interactions that help dissect the contribution that enthalpy and entropy make in this modified environment. These observations provide a benchmark for optimization of single-molecule nanopore sensors.

A cell competition-based small molecule screen identifies a novel compound that induces dual c-Myc depletion and p53 activation.

Breakpoint Cluster Region-Abelson kinase (BCR-Abl) is a driver oncogene that causes chronic myeloid leukemia and a subset of acute lymphoid leukemias. Although tyrosine kinase inhibitors provide an effective treatment for these diseases, they generally do not kill leukemic stem cells (LSCs), the cancer-initiating cells that compete with normal hematopoietic stem cells for the bone marrow niche. New strategies to target cancers driven by BCR-Abl are therefore urgently needed. We performed a small molecule screen based on competition between isogenic untransformed cells and BCR-Abl-transformed cells and identified several compounds that selectively impair the fitness of BCR-Abl-transformed cells. Interestingly, systems-level analysis of one of these novel compounds, DJ34, revealed that it induced depletion of c-Myc and activation of p53. DJ34-mediated c-Myc depletion occurred in a wide range of tumor cell types, including lymphoma, lung, glioblastoma, breast cancer, and several forms of leukemia, with primary LSCs being particularly sensitive to DJ34. Further analyses revealed that DJ34 interferes with c-Myc synthesis at the level of transcription, and we provide data showing that DJ34 is a DNA intercalator and topoisomerase II inhibitor. Physiologically, DJ34 induced apoptosis, cell cycle arrest, and cell differentiation. Taken together, we have identified a novel compound that dually targets c-Myc and p53 in a wide variety of cancers, and with particularly strong activity against LSCs.

Desumoylation of RNA polymerase III lies at the core of the Sumo stress response in yeast.

Post-translational modification by small ubiquitin-like modifier (Sumo) regulates many cellular processes, including the adaptive response to various types of stress, referred to as the Sumo stress response (SSR). However, it remains unclear whether the SSR involves a common set of core proteins regardless of the type of stress or whether each particular type of stress induces a stress-specific SSR that targets a unique, largely nonoverlapping set of Sumo substrates. In this study, we used MS and a Gene Ontology approach to identify differentially sumoylated proteins during heat stress, hyperosmotic stress, oxidative stress, nitrogen starvation, and DNA alkylation in Saccharomyces cerevisiae cells. Our results indicate that each stress triggers a specific SSR signature centered on proteins involved in transcription, translation, and chromatin regulation. Strikingly, whereas the various stress-specific SSRs were largely nonoverlapping, all types of stress tested here resulted in desumoylation of subunits of RNA polymerase III, which correlated with a decrease in tRNA synthesis. We conclude that desumoylation and subsequent inhibition of RNA polymerase III constitutes the core of all stress-specific SSRs in yeast.

High Resolution Physical Characterization of Single Metallic Nanoparticles.

Individual molecules can be detected and characterized by measuring the degree by which they reduce the ionic current flowing through a single nanometer-scale pore. The signal is characteristic of the molecule's physicochemical properties and its interactions with the pore. We demonstrate that the nanopore formed by the bacterial protein exotoxin Staphylococcus aureus alpha hemolysin (αHL) can detect polyoxometalates (POMs, anionic metal oxygen clusters), at the single molecule limit. Moreover, multiple degradation products of 12-phosphotungstic acid POM (PTA, H3PW12O40) in solution are simultaneously measured. The single molecule sensitivity of the nanopore method allows for POMs to be characterized at significantly lower concentrations than required for nuclear magnetic resonance (NMR) spectroscopy. This technique could serve as a new tool for chemists to study the molecular properties of polyoxometalates or other metallic clusters, to better understand POM synthetic processes, and possibly improve their yield. Hypothetically, the location of a given atom, or the rotation of a fragment in the molecule, and the metal oxidation state could be investigated with this method. In addition, this new technique has the advantage of allowing the real-time monitoring of molecules in solution.

A comparison of ion channel current blockades caused by individual poly(ethylene glycol) molecules and polyoxometalate nanoclusters.

Proteinaceous nanometer-scale pores have been used to detect and physically characterize many different types of analytes at the single-molecule limit. The method is based on the ability to measure the transient reduction in the ionic channel conductance caused by molecules that partition into the pore. The distribution of blockade depth amplitudes and residence times of the analytes in the pore are used to physically and chemically characterize them. Here we compare the current blockade events caused by flexible linear polymers of ethylene glycol (PEGs) and structurally well-defined tungsten polyoxymetallate nanoparticles in the nanopores formed by Staphylococcus aureusα-hemolysin and Aeromonas hydrophila aerolysin. Surprisingly, the variance in the ionic current blockade depth values for the relatively rigid metallic nanoparticles is much greater than that for the flexible PEGs, possibly because of multiple charged states of the polyoxymetallate clusters.

Predicting drug-resistant epilepsy - A machine learning approach based on administrative claims data.

Patients with drug-resistant epilepsy (DRE) are at high risk of morbidity and mortality, yet their referral to specialist care is frequently delayed. The ability to identify patients at high risk of DRE at the time of treatment initiation, and to subsequently steer their treatment pathway toward more personalized interventions, has high clinical utility. Here, we aim to demonstrate the feasibility of developing algorithms for predicting DRE using machine learning methods. Longitudinal, intersected data sourced from US pharmacy, medical, and adjudicated hospital claims from 1,376,756 patients from 2006 to 2015 were analyzed; 292,892 met inclusion criteria for epilepsy, and 38,382 were classified as having DRE using a proxy measure for drug resistance. Patients were characterized using 1270 features reflecting demographics, comorbidities, medications, procedures, epilepsy status, and payer status. Data from 175,735 randomly selected patients were used to train three algorithms and from the remainder to assess the trained models' predictive power. A model with only age and sex was used as a benchmark. The best model, random forest, achieved an area under the receiver operating characteristic curve (95% confidence interval [CI]) of 0.764 (0.759, 0.770), compared with 0.657 (0.651, 0.663) for the benchmark model. Moreover, predicted probabilities for DRE were well-calibrated with the observed frequencies in the data. The model predicted drug resistance approximately 2 years before patients in the test dataset had failed two antiepileptic drugs (AEDs). Machine learning models constructed using claims data predicted which patients are likely to fail ≥3 AEDs and are at risk of developing DRE at the time of the first AED prescription. The use of such models can ensure that patients with predicted DRE receive specialist care with potentially more aggressive therapeutic interventions from diagnosis, to help reduce the serious sequelae of DRE.

Cdk1 gates cell cycle-dependent tRNA synthesis by regulating RNA polymerase III activity.

tRNA genes are transcribed by RNA polymerase III (RNAPIII). During recent years it has become clear that RNAPIII activity is strictly regulated by the cell in response to environmental cues and the homeostatic status of the cell. However, the molecular mechanisms that control RNAPIII activity to regulate the amplitude of tDNA transcription in normally cycling cells are not well understood. Here, we show that tRNA levels fluctuate during the cell cycle and reveal an underlying molecular mechanism. The cyclin Clb5 recruits the cyclin dependent kinase Cdk1 to tRNA genes to boost tDNA transcription during late S phase. At tDNA genes, Cdk1 promotes the recruitment of TFIIIC, stimulates the interaction between TFIIIB and TFIIIC, and increases the dynamics of RNA polymerase III in vivo. Furthermore, we identified Bdp1 as a putative Cdk1 substrate in this process. Preventing Bdp1 phosphorylation prevented cell cycle-dependent recruitment of TFIIIC and abolished the cell cycle-dependent increase in tDNA transcription. Our findings demonstrate that under optimal growth conditions Cdk1 gates tRNA synthesis in S phase by regulating the RNAPIII machinery, revealing a direct link between the cell cycle and RNAPIII activity.

The Utility of Nanopore Technology for Protein and Peptide Sensing.

Resistive pulse nanopore sensing enables label-free single-molecule analysis of a wide range of analytes. An increasing number of studies have demonstrated the feasibility and usefulness of nanopore sensing for protein and peptide characterization. Nanopores offer the potential to study a variety of protein-related phenomena that includes unfolding kinetics, differences in unfolding pathways, protein structure stability, and free-energy profiles of DNA-protein and RNA-protein binding. In addition to providing a tool for fundamental protein characterization, nanopores have also been used as highly selective protein detectors in various solution mixtures and conditions. This review highlights these and other developments in the area of nanopore-based protein and peptide detection.

GRP94 rewires and buffers the FLT3-ITD signaling network and promotes survival of acute myeloid leukemic stem cells.

Internal tandem duplications in the tyrosine kinase receptor FLT3 (FLT3-ITD) are among the most common lesions in acute myeloid leukemia and there exists a need for new forms of treatment. Using ex vivo drug sensitivity screening, we found that FLT3-ITD+ patient cells are particularly sensitive to HSP90 inhibitors. While it is well known that HSP90 is important for FLT3-ITD stability, we found that HSP90 family members play a much more complex role in FLT3-ITD signaling than previously appreciated. First, we found that FLT3-ITD activates the unfolded protein response, leading to increased expression of GRP94/HSP90B1. This results in activation of a nefarious feedback loop, in which GRP94 rewires FLT3-ITD signaling by binding and retaining FLT3-ITD in the endoplasmic reticulum, leading to aberrant activation of downstream signaling pathways and further inducing the unfolded protein response. Second, HSP90 family proteins protect FLT3-ITD+ acute myeloid leukemia cells against apoptosis by alleviating proteotoxic stress, and treatment with HSP90 inhibitors results in proteotoxic overload that triggers unfolded protein response-induced apoptosis. Importantly, leukemic stem cells are strongly dependent upon HSP90 for their survival, and the HSP90 inhibitor ganetespib causes leukemic stem cell exhaustion in patient-derived mouse xenograft models. Taken together, our study reveals a molecular basis for HSP90 addiction of FLT3-ITD+ acute myeloid leukemia cells and provides a rationale for including HSP90 inhibitors in the treatment regime for FLT3-ITD+ acute myeloid leukemia.

Determining the Physical Properties of Molecules with Nanometer-Scale Pores.

Nanometer-scale pores have been developed for the detection, characterization, and quantification of a wide range of analytes (e.g., ions, polymers, proteins, anthrax toxins, neurotransmitters, and synthetic nanoparticles) and for DNA sequencing. We describe the key requirements that made this method possible and how the technique evolved. Finally, we show that, despite sound theoretical work, which advanced both the conceptual framework and quantitative capability of the method, there are still unresolved questions that need to be addressed to further improve the technique.

Single Molecule Nanopore Spectrometry for Peptide Detection.

Sensing and characterization of water-soluble peptides is of critical importance in a wide variety of bioapplications. Single molecule nanopore spectrometry (SMNS) is based on the idea that one can use biological protein nanopores to resolve different sized molecules down to limits set by the blockade duration and noise. Previous work has shown that this enables discrimination between polyethylene glycol (PEG) molecules that differ by a single monomer unit. This paper describes efforts to extend SMNS to a variety of biologically relevant, water-soluble peptides. We describe the use of Au25(SG)18 clusters, previously shown to improve PEG detection, to increase the on- and off-rate of peptides to the pore. In addition, we study the role that fluctuations play in the single molecule nanopore spectrometry (SMNS) methodology and show that modifying solution conditions to increase peptide flexibility (via pH or chaotropic salt) leads to a nearly 2-fold reduction in the current blockade fluctuations and a corresponding narrowing of the peaks in the blockade distributions. Finally, a model is presented that connects the current blockade depths to the mass of the peptides, which shows that our enhanced SMNS detection improves the mass resolution of the nanopore sensor more than 2-fold for the largest cationic peptides studied.

Novel nanofluidic chemical cells based on self-assembled solid-state SiO2 nanotubes.

Novel nanofluidic chemical cells based on self-assembled solid-state SiO2 nanotubes on silicon-on-insulator (SOI) substrate have been successfully fabricated and characterized. The vertical SiO2 nanotubes with a smooth cavity are built from Si nanowires which were epitaxially grown on the SOI substrate. The nanotubes have rigid, dry-oxidized SiO2 walls with precisely controlled nanotube inner diameter, which is very attractive for chemical-/bio-sensing applications. No dispersion/aligning procedures were involved in the nanotube fabrication and integration by using this technology, enabling a clean and smooth chemical cell. Such a robust and well-controlled nanotube is an excellent case of developing functional nanomaterials by leveraging the strength of top-down lithography and the unique advantage of bottom-up growth. These solid, smooth, clean SiO2 nanotubes and nanofluidic devices are very encouraging and attractive in future bio-medical applications, such as single molecule sensing and DNA sequencing.