Solid-State Single-Molecule Sensing with the Electronic Life-Detection Instrument for Enceladus/Europa (ELIE).

Growing evidence of the potential habitability of Ocean Worlds across our solar system is motivating the advancement of technologies capable of detecting life as we know it-sharing a common ancestry or physicochemical origin with life on Earth-or don't know it, representing a distinct emergence of life different than our one known example. Here, we propose the Electronic Life-detection Instrument for Enceladus/Europa (ELIE), a solid-state single-molecule instrument payload that aims to search for life based on the detection of amino acids and informational polymers (IPs) at the parts per billion to trillion level. As a first proof-of-principle in a laboratory environment, we demonstrate the single-molecule detection of the amino acid L-proline at a 10 µM concentration in a compact system. Based on ELIE's solid-state quantum electronic tunneling sensing mechanism, we further propose the quantum property of the HOMO-LUMO gap (energy difference between a molecule's highest energy-occupied molecular orbital and lowest energy-unoccupied molecular orbital) as a novel metric to assess amino acid complexity. Finally, we assess the potential of ELIE to discriminate between abiotically and biotically derived α-amino acid abundance distributions to reduce the false positive risk for life detection. Nanogap technology can also be applied to the detection of nucleobases and short sequences of IPs such as, but not limited to, RNA and DNA. Future missions may utilize ELIE to target preserved biosignatures on the surface of Mars, extant life in its deep subsurface, or life or its biosignatures in a plume, surface, or subsurface of ice moons such as Enceladus or Europa. One-Sentence Summary: A solid-state nanogap can determine the abundance distribution of amino acids, detect nucleic acids, and shows potential for detecting life as we know it and life as we don't know it.

Single-Molecule Identification of Nucleotides Using a Quantum Computer.

Genomic information is essential for human health. Due to its large volume, genomic information can be potentially computed using quantum computers, which are rapidly developing. Genome analysis using quantum computers can accelerate the development of personalized medicine, innovative drugs, and novel diagnostics based on genomic information. However, genomic analysis, including nucleotide identification, has not yet been performed using quantum computers. Here, we demonstrate single-molecule identification of nucleotides using a quantum computer. We have designed a quantum gate that explains the single-molecule conductance of adenosine electronically bonded between electrodes. The quantum circuit consists of a reverse and an encoding quantum gate that can strongly distinguish adenosine among the four nucleotides. Our results are the first step toward the realization of genome analysis using quantum computers.

Direct biomolecule discrimination in mixed samples using nanogap-based single-molecule electrical measurement.

In single-molecule measurements, metal nanogap electrodes directly measure the current of a single molecule. This technique has been actively investigated as a new detection method for a variety of samples. Machine learning has been applied to analyze signals derived from single molecules to improve the identification accuracy. However, conventional identification methods have drawbacks, such as the requirement of data to be measured for each target molecule and the electronic structure variation of the nanogap electrode. In this study, we report a technique for identifying molecules based on single-molecule measurement data measured only in mixed sample solutions. Compared with conventional methods that require training classifiers on measurement data from individual samples, our proposed method successfully predicts the mixing ratio from the measurement data in mixed solutions. This demonstrates the possibility of identifying single molecules using only data from mixed solutions, without prior training. This method is anticipated to be particularly useful for the analysis of biological samples in which chemical separation methods are not applicable, thereby increasing the potential for single-molecule measurements to be widely adopted as an analytical technique.

Quantitative Microscopic Observation of Base-Ligand Interactions via Hydrogen Bonds by Single-Molecule Counting.

Chemical properties have been based on statistical averages since the introduction of Avogadro's number. The lack of suitable methods for counting identified single molecules has posed challenges to counting statistics. The selectivity, affinity, and mode of hydrogen bonding between base and small molecules that make up DNA, which is vital for living organisms, have not yet been revealed at the single molecule level. Here, we show the quantitation of the above-mentioned parameters via single-molecule counting based on the combination of single-molecule electrical measurements and AI. The binding selectivity values of five ligands to four different base molecules were evaluated quantitatively by determining the ratio of the number of aggregates in a solution mixture of base molecules and a ligand. In addition, we show the ligand dependence of the mode and number of microscopic hydrogen bonds via single-molecule counting and quantum chemical calculations.

Establishment of a reference single-cell RNA sequencing dataset for human pancreatic adenocarcinoma.

Single-cell RNA sequencing (scRNAseq) has been used to assess the intra-tumor heterogeneity and microenvironment of pancreatic ductal adenocarcinoma (PDAC). However, previous knowledge is not fully universalized. Here, we built a single cell atlas of PDAC from six datasets containing over 70 samples and >130,000 cells, and demonstrated its application to the reanalysis of the previous bulk transcriptomic cohorts and inferring cell-cell communications. The cell decomposition of bulk transcriptomics using scRNAseq data showed the cellular heterogeneity of PDAC; moreover, high levels of tumor cells and fibroblasts were indicative of poor-prognosis. Refined tumor subtypes signature indicated the tumor cell dynamics in intra-tumor and their specific regulatory network. We further identified functionally distinct tumor clusters that had close interaction with fibroblast subtypes via different signaling pathways dependent on subtypes. Our analysis provided a reference dataset for PDAC and showed its utility in research on the microenvironment of intra-tumor heterogeneity.

Single-Molecule Classification of Aspartic Acid and Leucine by Molecular Recognition through Hydrogen Bonding and Time-Series Analysis.

Amino acid detection/identification methods are important for understanding biological systems. In this study, we developed single-molecule measurements for investigating quantum tunneling enhancement by chemical modification and carried out machine learning-based time series analysis for developing accurate amino acid discrimination. We performed single-molecule measurement of L-aspartic acid (Asp) and L-leucine (Leu) with a mercaptoacetic acid (MAA) chemical modified nano-gap. The measured current was investigated by a machine learning-based time series analysis method for accurate amino acid discrimination. Compared to measurements using a bare nano-gap, it is found that MAA modification improves the difference in the conductance-time profiles between Asp and Leu through the hydrogen bonding facilitated tunneling phenomena. It is also found that this method enables determination of relative concentration. even in the mixture of Asp and Leu. It improves selective analysis for amino acids and therefore would be applicable in medicine, diagnosis, and single-molecule peptide sequencing.

Direct observation of DNA alterations induced by a DNA disruptor.

DNA alterations, such as base modifications and mutations, are closely related to the activity of transcription factors and the corresponding cell functions; therefore, detection of DNA alterations is important for understanding their relationships. Particularly, DNA alterations caused by exposure to exogenous molecules, such as nucleic acid analogues for cancer therapy and the corresponding changes in cell functions, are of interest in medicine for drug development and diagnosis purposes. However, detection of comprehensive direct evidence for the relationship of DNA modifications/mutations in genes, their effect on transcription factors, and the corresponding cell functions have been limited. In this study, we utilized a single-molecule electrical detection method for the direct observation of DNA alterations on transcription factor binding motifs upon exposure to a nucleic acid analogue, trifluridine (FTD), and evaluated the effects of the DNA alteration on transcriptional activity in cancer cell line cells. We found ~ 10% FTD incorporation at the transcription factor p53 binding regions in cancer cells exposed to FTD for 5 months. Additionally, through single-molecule analysis of p53-enriched DNA, we found that the FTD incorporation at the p53 DNA binding regions led to less binding, likely due to weaken the binding of p53. This work suggests that single-molecule detection of DNA sequence alterations is a useful methodology for understanding DNA sequence alterations.

Review of the use of nanodevices to detect single molecules.

The development of methodologies to identify single molecules and/or to detect/monitor molecular behavior at the single-molecule level is one of the important research topics in chemistry and biology. In this review, we summarized the state-of-the-art of single molecule measurement methods and its latest applications using nanodevices integrated with molecular-size functional nanostructures, nanopores, nanogaps, and nanofluidic channels, which detect differences in chemical species, presence or absence of translational modifications, changes in steric structure, and changes in interactions between molecules. Besides these fundamental analytical achievements of molecular identification abilities, the latest applications include the single-molecule electrical sequencing, disease diagnosis, viral testing, single-molecule drug screening, and environmental monitoring. Finally, we added some discussion on the current status of single-molecule measurement as a method and technology to solve the problems to expand the future application needs of single-molecule measurement.

Single-molecule RNA sequencing for simultaneous detection of m6A and 5mC.

Epitranscriptomics is the study of RNA base modifications involving functionally relevant changes to the transcriptome. In recent years, epitranscriptomics has been an active area of research. However, a major issue has been the development of sequencing methods to map transcriptome-wide RNA base modifications. We have proposed a single-molecule quantum sequencer for mapping RNA base modifications in microRNAs (miRNAs), such as N6-methyladenosine (m6A) or 5-methylcytidine (5mC), which are related to cancer cell propagation and suppression. Here, we investigated 5mC and m6A in hsa-miR-200c-5p extracted from colorectal cancer cells and determined their methylation sites and rates; the data were comparable to those determined by mass spectrometry. Furthermore, we evaluated the methylation ratio of cytidine and adenosine at each site in the sequences and its relationship. These results suggest that the methylation ratio of cytidine and adenosine is facilitated by the presence of vicinal methylation. Our work provides a robust new tool for sequencing various types of RNA base modifications in their RNA context.

Development of Single-Molecule Electrical Identification Method for Cyclic Adenosine Monophosphate Signaling Pathway.

Cyclic adenosine monophosphate (cAMP) is an important research target because it activates protein kinases, and its signaling pathway regulates the passage of ions and molecules inside a cell. To detect the chemical reactions related to the cAMP intracellular signaling pathway, cAMP, adenosine triphosphate (ATP), adenosine monophosphate (AMP), and adenosine diphosphate (ADP) should be selectively detected. This study utilized single-molecule quantum measurements of these adenosine family molecules to detect their individual electrical conductance using nanogap devices. As a result, cAMP was electrically detected at the single molecular level, and its signal was successfully discriminated from those of ATP, AMP, and ADP using the developed machine learning method. The discrimination accuracies of a single cAMP signal from AMP, ADP, and ATP were found to be 0.82, 0.70, and 0.72, respectively. These values indicated a 99.9% accuracy when detecting more than ten signals. Based on an analysis of the feature values used for the machine learning analysis, it is suggested that this discrimination was due to the structural difference between the ribose of the phosphate site of cAMP and those of ATP, ADP, and AMP. This method will be of assistance in detecting and understanding the intercellular signaling pathways for small molecular second messengers.

Length Discrimination of Homo-oligomeric Nucleic Acids with Single-molecule Measurement.

Single-molecule DNA/RNA sequencing based on single-molecule measurement is a prominent method for higher throughput sequencing. In a previous report, the single-molecule DNA/RNA sequencing method has applied to detect each base-conductance difference in the tunneling current time profiles, and determined the sequence. However, discrimination of identical base lengths has not yet been achieved. The number of the identical contiguous bases has importance in biology because some homopolymers of nucleic acid control gene expression. In this study, we aimed to develop a method for discriminating the length of homopolymer of nucleic acids of adenosine monophosphate (AMP) using a single-molecule sequencing technique. We carried out single-molecule conductance measurements of adenine pentamer, hexamer and heptamer. The single-molecule signals of the oligomers are not distinguishable from current and duration time histograms. The three oligomers were discriminated by our developed machine learning-based analysis with accuracy of 0.54 for a single signal, and 99% for 40 signals. This method will be applied to the single signals and identify the contiguous bases in the sequence and provide new biological insights.

Single-Molecule Counting of Nucleotide by Electrophoresis with Nanochannel-Integrated Nano-Gap Devices.

We utilized electrophoresis to control the fluidity of sample biomolecules in sample aqueous solutions inside the nanochannel for single-molecule detection by using a nanochannel-integrated nanogap electrode, which is composed of a nano-gap sensing electrode, nanochannel, and tapered focusing channel. In order to suppress electro-osmotic flow and thermal convection inside this nanochannel, we optimized the reduction ratios of the tapered focusing channel, and the ratio of inlet 10 µm to outlet 0.5 µm was found to be high performance of electrophoresis with lower concentration of 0.05 × TBE (Tris/Borate/EDTA) buffer containing a surfactant of 0.1 w/v% polyvinylpyrrolidone (PVP). Under the optimized conditions, single-molecule electrical measurement of deoxyguanosine monophosphate (dGMP) was performed and it was found that the throughput was significantly improved by nearly an order of magnitude compared to that without electrophoresis. In addition, it was also found that the long-duration signals that could interfere with discrimination were significantly reduced. This is because the strong electrophoresis flow inside the nanochannels prevents the molecules' adsorption near the electrodes. This single-molecule electrical measurement with nanochannel-integrated nano-gap electrodes by electrophoresis significantly improved the throughput of signal detection and identification accuracy.

Detection of an alcohol-associated cancer marker by single-molecule quantum sequencing.

Alcoholic beverages are a well-known risk factor for cancer. N2-Ethyl-2'-deoxyguanosine (N2-Et-dG) is a promising biomarker for alcohol-associated cancers. However, the lack of a convenient detection method for N2-Et-dG hinders the development of practical DNA damage markers. Herein, we develop a detection method for N2-Et-dG using a single-molecule quantum sequencing (SMQS) method and machine learning analysis. Our method succeeded in discriminating between N2-Et-dG and dG with an accuracy of 99%, using 20 signals. Our developed method quantified the mixing ratio of N2-Et-dG from a mixed solution of N2-Et-dG and dG. It is shown that our method has the potential to facilitate the development of DNA damage markers, and thus the early detection and prevention of cancers.

Time-resolved neurotransmitter detection in mouse brain tissue using an artificial intelligence-nanogap.

The analysis of neurotransmitters in the brain helps to understand brain functions and diagnose Parkinson's disease. Pharmacological inhibition experiments, electrophysiological measurement of action potentials, and mass analysers have been applied for this purpose; however, these techniques do not allow direct neurotransmitter detection with good temporal resolution by using nanometre-sized electrodes. Hence, we developed a method for direct observation of a single neurotransmitter molecule with a gap width of ≤ 1 nm and on the millisecond time scale. It consists of measuring the tunnelling current that flows through a single-molecule by using nanogap electrodes and machine learning analysis. Using this method, we identified dopamine, serotonin, and norepinephrine neurotransmitters with high accuracy at the single-molecule level. The analysis of the mouse striatum and cerebral cortex revealed the order of concentration of the three neurotransmitters. Our method will be developed to investigate the neurotransmitter distribution in the brain with good temporal resolution.

Key aurophilic motif for robust quantum-tunneling-based characterization of a nucleoside analogue marker.

A quantum sequencer offers a scalable electrical platform for single-molecule analysis of genomic events. A thymidine (dT) analog exhibiting uniquely high single-molecule conductance is a key element in capturing DNA synthesis dynamics by serving as a decodable marker for enzymatic labeling of nascent strands. However, the current design strategies of dT analogs that focus on their molecular orbital energy levels require bulky chemical modifications to extend the π-conjugation, which hinders polymerase recognition. We report herein a polymerase-compatible dT analog that is highly identifiable in quantum sequencing. An ethynyl group is introduced as a small gold-binding motif to differentiate the nucleobase-gold electronic coupling, which has been an overlooked factor in modifying nucleobase conductance. The resulting C5-ethynyl-2'-deoxyuridine exhibits characteristic signal profiles that allowed its correct identification at a 93% rate while maintaining polymerase compatibility. This study would expand the applicability of quantum sequencing by demonstrating a robust nucleoside marker with high identifiability.

Chemical-Labeling-Assisted Detection of Nucleobase Modifications by Quantum-Tunneling-Based Single-Molecule Sensing.

Quantum-tunneling-based DNA sensing is a single-molecule technique that promises direct mapping of nucleobase modifications. However, its applicability is seriously limited because of the small difference in conductivity between modified and unmodified nucleobases. Herein, a chemical labeling strategy is presented that facilitates the detection of modified nucleotides by quantum tunneling. We used 5-Formyl-2'-deoxyuridine as a model compound and demonstrated that chemical labeling dramatically alters its molecular conductance compared with that of canonical nucleotides; thus, facilitating statistical discrimination, which is impeded in the unlabeled state. This work introduces a chemical strategy that overcomes the intrinsic difficulty in quantum-tunneling-based modification analysis-the similarity of the molecular conductance of the nucleobases of interest.

Highly Conductive Nucleotide Analogue Facilitates Base-Calling in Quantum-Tunneling-Based DNA Sequencing.

Quantum-tunneling-based DNA sequencing is a single molecular technology that has great potential for achieving facile and high-throughput DNA sequencing. In principle, the sequence of DNA could be read out by the time trace of the tunnel current that can be changed according to molecular conductance of nucleobases passing through nanosized gap electrodes. However, efficient base-calling of four genetic alphabets has been seriously impeded due to the similarity of molecular conductance among canonical nucleotides. In this article, we demonstrate that replacement of canonical 2'-deoxyadenosine (dA) with a highly conductive dA analogue, 7-deaza dA, could expand the difference of molecular conductance between four genetic alphabets. Additionally, systematic evaluation of molecular conductance using a series of dA and dG analogues revealed that molecular conductance of the nucleotide is highly dependent on the HOMO level. Thus, the present study demonstrating that signal characteristics of the nucleotide can be modulated based on the HOMO level provides a widely applicable chemical approach and insight for facilitation of single molecular sensing as well as DNA sequencing based on quantum tunneling.

Direct Analysis of Incorporation of an Anticancer Drug into DNA at Single-Molecule Resolution.

Identifying positions at which anticancer drug molecules incorporate into DNA is essential to define mechanisms underlying their activity, but current methodologies cannot yet achieve this. The thymidine fluorine substitution product trifluridine (FTD) is a DNA-damaging anticancer agent thought to incorporate into thymine positions in DNA. This mechanism, however, has not been directly confirmed. Here, we report a means to detect FTD in a single-stranded oligonucleotide using a method to distinguish single molecules by differences in electrical conductance. Entire sequences of 21-base single-stranded DNAs with and without incorporated drug were determined based on single-molecule conductances of the drug and four deoxynucleosides, the first direct observation of its kind. This methodology may foster rapid development of more effective anticancer drugs.

Quantitative analysis of DNA with single-molecule sequencing.

Cancer can be diagnosed by identifying DNA and microRNA base sequences that have the same base length yet differ in a few base sequences, if the abundance ratios of these slightly deviant base sequences can be determined. However, such quantitative analyses cannot be performed using the current DNA sequencers. Here we determine entire base sequences of four types of DNA corresponding to the let-7 microRNA, which is a 22-base cancer marker. We record the single-molecule conductances of the base molecules using current-tunneling measurements. In addition, we count the numbers of molecules in a solution to determine the abundance ratios of two DNA strands that differ by a single base sequence.