Advances in Nanomaterials for Sustainable Gas Separation and Storage: Focus on Clathrate Hydrates.

ConspectusClathrate hydrates, also known as gas hydrates, are a type of inclusion compound formed in highly developed nanoporous lattice spaces created by water molecules, where gas molecules such as CO2, H2, CH4, and other low-molecular-weight liquid molecules are trapped. The nanoporous cage formed by water molecules serves as the "host", while the trapped gas or low-molecular-weight liquid molecules such as tetrahydrofuran act as "guests". Early on, clathrate hydrates drew attention as a potential replacement for conventional natural gas due to their natural gas hydrate form, which contains natural gases as guests and exists in permafrost or sea floors. Recently, based on the unique physicochemical properties of clathrate hydrates, efforts are being made to utilize synthetic clathrate hydrates in various separation processes such as post- and pre-combustion CO2 capture, H2 storage, natural gas storage and transportation, wastewater desalination, and more. While it is undeniable that clathrate hydrates are based on principles that are beneficial for the separation and storage of gas molecules, there are several challenges that must be addressed for their practical application. These challenges include (i) the limitation of gas storage capacity due to the confined size of nanoporous cages, (ii) the relatively high-pressure and low-temperature thermodynamic storage conditions typically required for clathrate hydrate formation, and (iii) slow formation kinetics and low gas hydrate conversion, which are also essential issues that need to be resolved for the meaningful implementation of clathrate hydrates. In this Account, we aim to introduce recent noteworthy research findings, including those from our research team, focusing on addressing these challenges. We explored the untapped potential of clathrate hydrates by bridging the gap between macroscopic and microscopic properties. This has led to breakthroughs in sustainable gas separation and storage applications. By revealing the hidden nature of these hydrates, we have effectively mitigated their inherent limitations, setting the stage for more feasible and efficient H2 storage solutions through the introduction of hydrogen-natural gas blends to clathrate hydrates. Additionally, we have demonstrated the tuning effect on all naturally formed hydrate structures, offering new insights into their underlying properties and macroscopic behavior. Furthermore, our research has proposed a highly efficient hydrate-based pre-combustion CO2 capture approach that leverages porous media with appropriate wettability and considers the implications of microstructure properties. This emphasizes the crucial connection between nano-structure and macroscopic properties, underscoring the significance of understanding their interplay for economic feasibility. We believe that our efforts to unveil the hidden nature of gas hydrates provide strategies to address challenges and lay the groundwork for practical applications.

Towards multi-omics characterization of tumor heterogeneity: a comprehensive review of statistical and machine learning approaches.

The multi-omics molecular characterization of cancer opened a new horizon for our understanding of cancer biology and therapeutic strategies. However, a tumor biopsy comprises diverse types of cells limited not only to cancerous cells but also to tumor microenvironmental cells and adjacent normal cells. This heterogeneity is a major confounding factor that hampers a robust and reproducible bioinformatic analysis for biomarker identification using multi-omics profiles. Besides, the heterogeneity itself has been recognized over the years for its significant prognostic values in some cancer types, thus offering another promising avenue for therapeutic intervention. A number of computational approaches to unravel such heterogeneity from high-throughput molecular profiles of a tumor sample have been proposed, but most of them rely on the data from an individual omics layer. Since the heterogeneity of cells is widely distributed across multi-omics layers, methods based on an individual layer can only partially characterize the heterogeneous admixture of cells. To help facilitate further development of the methodologies that synchronously account for several multi-omics profiles, we wrote a comprehensive review of diverse approaches to characterize tumor heterogeneity based on three different omics layers: genome, epigenome and transcriptome. As a result, this review can be useful for the analysis of multi-omics profiles produced by many large-scale consortia. Contact:sunkim.bioinfo@snu.ac.kr.

MIDAS: Mining differentially activated subpaths of KEGG pathways from multi-class RNA-seq data.

Pathway based analysis of high throughput transcriptome data is a widely used approach to investigate biological mechanisms. Since a pathway consists of multiple functions, the recent approach is to determine condition specific sub-pathways or subpaths. However, there are several challenges. First, few existing methods utilize explicit gene expression information from RNA-seq. More importantly, subpath activity is usually an average of statistical scores, e.g., correlations, of edges in a candidate subpath, which fails to reflect gene expression quantity information. In addition, none of existing methods can handle multiple phenotypes. To address these technical problems, we designed and implemented an algorithm, MIDAS, that determines condition specific subpaths, each of which has different activities across multiple phenotypes. MIDAS utilizes gene expression quantity information fully and the network centrality information to determine condition specific subpaths. To test performance of our tool, we used TCGA breast cancer RNA-seq gene expression profiles with five molecular subtypes. 36 differentially activate subpaths were determined. The utility of our method, MIDAS, was demonstrated in four ways. All 36 subpaths are well supported by the literature information. Subsequently, we showed that these subpaths had a good discriminant power for five cancer subtype classification and also had a prognostic power in terms of survival analysis. Finally, in a performance comparison of MIDAS to a recent subpath prediction method, PATHOME, our method identified more subpaths and much more genes that are well supported by the literature information. AVAILABILITY: http://biohealth.snu.ac.kr/software/MIDAS/.

Measuring intratumor heterogeneity by network entropy using RNA-seq data.

Intratumor heterogeneity (ITH) is observed at different stages of tumor progression, metastasis and reouccurence, which can be important for clinical applications. We used RNA-sequencing data from tumor samples, and measured the level of ITH in terms of biological network states. To model complex relationships among genes, we used a protein interaction network to consider gene-gene dependency. ITH was measured by using an entropy-based distance metric between two networks, nJSD, with Jensen-Shannon Divergence (JSD). With nJSD, we defined transcriptome-based ITH (tITH). The effectiveness of tITH was extensively tested for the issues related with ITH using real biological data sets. Human cancer cell line data and single-cell sequencing data were investigated to verify our approach. Then, we analyzed TCGA pan-cancer 6,320 patients. Our result was in agreement with widely used genome-based ITH inference methods, while showed better performance at survival analysis. Analysis of mouse clonal evolution data further confirmed that our transcriptome-based ITH was consistent with genetic heterogeneity at different clonal evolution stages. Additionally, we found that cell cycle related pathways have significant contribution to increasing heterogeneity on the network during clonal evolution. We believe that the proposed transcriptome-based ITH is useful to characterize heterogeneity of a tumor sample at RNA level.

Sequestering carbon dioxide into complex structures of naturally occurring gas hydrates.

Large amounts of CH4 in the form of solid hydrates are stored on continental margins and in permafrost regions. If these CH4 hydrates could be converted into CO2 hydrates, they would serve double duty as CH4 sources and CO2 storage sites. We explore here the swapping phenomenon occurring in structure I (sI) and structure II (sII) CH4 hydrate deposits through spectroscopic analyses and its potential application to CO2 sequestration at the preliminary phase. The present 85% CH4 recovery rate in sI CH4 hydrate achieved by the direct use of binary N2+CO2 guests is surprising when compared with the rate of 64% for a pure CO2 guest attained in the previous approach. The direct use of a mixture of N2+CO2 eliminates the requirement of a CO2 separation/purification process. In addition, the simultaneously occurring dual mechanism of CO2 sequestration and CH4 recovery is expected to provide the physicochemical background required for developing a promising large-scale approach with economic feasibility. In the case of sII CH4 hydrates, we observe a spontaneous structure transition of sII to sI during the replacement and a cage-specific distribution of guest molecules. A significant change of the lattice dimension caused by structure transformation induces a relative number of small cage sites to reduce, resulting in the considerable increase of CH4 recovery rate. The mutually interactive pattern of targeted guest-cage conjugates possesses important implications for the diverse hydrate-based inclusion phenomena as illustrated in the swapping process between CO2 stream and complex CH4 hydrate structure.

Effects of oleamide on choline acetyltransferase and cognitive activities.

We screened 50 Korean traditional natural plants to measure the activation effect on choline acetyltransferase and attenuation of scopolamine-induced amnesia. The methanolic extracts from Zizyphus jujuba among the tested 50 plants, showed the highest activatory effect (34.1%) on choline acetyltransferase in vitro. By sequential fractionation of Zizyphus jujuba, the active component was finally identified as cis-9-octadecenoamide (oleamide). After isolation, oleamide showed a 65% activation effect. Administration of oleamide (0.32%) to mice significantly reversed the scopolamine-induced memory and/or cognitive impairment in the passive avoidance test and Y-maze test. Injection of scopolamine to mice impaired performance on the passive avoidance test (31% decrease in step-through latency), and on the Y-maze test (16% decrease in alternation behavior). In contrast, mice treated with oleamide before scopolamine injection were protected from these changes (12-25% decrease in step-through latency; 1-10% decrease in alternation behavior). These results suggest that oleamide should be a useful chemo-preventive agent against Alzheimer's disease.