Search

Abstract Ulcerative colitis (UC) is a significant inflammatory bowel disease caused by an abnormal immune response to gut microbes. However, there are still gaps in our understanding of how immune and metabolic changes specifically contribute to this disease. Our research aims to address this gap by examining mouse colons after inducing ulcerative colitis-like symptoms. Employing single-cell RNA-seq and 16 s rRNA amplicon sequencing to analyze distinct cell clusters and microbiomes in the mouse colon at different time points after induction with dextran sodium sulfate. We observe a significant reduction in epithelial populations during acute colitis, indicating tissue damage, with a partial recovery observed in chronic inflammation. Analyses of cell-cell interactions demonstrate shifts in networking patterns among different cell types during disease progression. Notably, macrophage phenotypes exhibit diversity, with a pronounced polarization towards the pro-inflammatory M1 phenotype in chronic conditions, suggesting the role of macrophage heterogeneity in disease severity. Increased expression of Nampt and NOX2 complex subunits in chronic UC macrophages contributes to the inflammatory processes. The chronic UC microbiome exhibits reduced taxonomic diversity compared to healthy conditions and acute UC. The study also highlights the role of T cell differentiation in the context of dysbiosis and its implications in colitis progression, emphasizing the need for targeted interventions to modulate the inflammatory response and immune balance in colitis.

Cell type identification is a key step toward downstream analysis of single cell RNA-seq experiments. Although the primary objective is to identify known cell populations, good identifiers should also recognize unknown clusters which may represent a previously unidentified subpopulation of a known cell type or tumor cells of an unknown phenotype. Herein, we present MarkerCount, which utilizes the number of expressed markers, regardless of their expression level. MarkerCount works in both reference- and marker-based mode, where the latter utilizes existing lists of markers, while the former uses a pre-annotated dataset to find markers to be used for cell type identification. In both modes, MarkerCount first utilizes the “marker count” to identify cell populations and, after rejecting uncertain cells, reassigns cell type and/or makes corrections in cluster-basis. The performance of MarkerCount was evaluated and compared with existing identifiers, both marker- and reference-based, that can be customized using publicly available datasets and marker databases. The results show that MarkerCount performs better in the identification of known populations as well as of unknown ones, when compared to other reference- and marker-based cell type identifiers for most of the datasets analyzed.

Abstract Integration of distinct materials to form heterostructures enables the proposal of new functional devices based on emergent physical phenomena beyond the properties of the constituent materials. The optical responses and electrical transport characteristics of heterostructures depend on the charge and exciton transfer (CT and ET) at the interfaces, determined by the interfacial energy level alignment. In this work, heterostructures consisting of aggregates of fluorescent molecules (DY1) and 2D semiconductor MoS2 monolayers are fabricated. Photoluminescence spectra of DY1/MoS2 show quenching of the DY1 emission and enhancement of the MoS2 emission, indicating a strong electronic interaction between these two materials. Nanoscopic mappings of the light‐induced contact potential difference changes rule out the CT process at the interface. Using femtosecond transient absorption spectroscopy, the rapid interfacial ET process from DY1 aggregates to MoS2 and a fourfold extension of the exciton lifetime in MoS2 are elucidated. These results suggest that the integration of 2D inorganic semiconductors with fluorescent molecules can provide versatile approaches to engineer the physical characteristics of materials for both fundamental studies and novel optoelectronic device applications.

Nicotinamide phosphoribosyl transferase (NAMPT) is required to maintain the NAD+ pool, among which extracellular (e) NAMPT is associated with inflammation, mainly mediated by macrophages. However, the role of (e) NAMPT in inflammatory macrophages in ulcerative colitis is insufficiently understood. Here our analyses of single-cell RNA-seq data revealed that the levels of NAMPT and CYBB/NOX2 in macrophages were elevated in patients with colitis and in mouse models of acute and chronic colitis. These findings indicate the clinical significance of NAMPT and CYBB in colitis. Further, we found that eNAMPT directly binds the extracellular domains of CYBB and TLR4 in activated NLRP3 inflammasomes. Moreover, we developed a recombinant 12-residue TK peptide designated colon-targeted (CT)-conjugated multifunctional NAMPT (rCT-NAMPT), comprising CT as the colon-targeting moiety, which harbors the minimal essential residues required for CYBB/TLR4 binding. rCT-NAMPT effectively suppressed the severity of disease in DSS-induced acute and chronic colitis models through targeting the colon and inhibiting the interaction of NAMPT with CYBB or TLR4. Together, our data show that rCT-NAMPT may serve as an effective novel candidate therapeutic for colitis by modulating the NLRP3 inflammasome-mediated immune signaling system.

Abstract Background The challenges when developing a good de novo transcriptome assembler include how to deal with read errors and sequence repeats. Almost all de novo assemblers utilize a de Bruijn graph, with which complexity grows linearly with data size while suffering from errors and repeats. Although one can correct the errors by inspecting the topological structure of the graph, this is not an easy task when there are too many branches. Two research directions are to improve either the graph reliability or the path search precision, and in this study, we focused on the former. Results We present TraRECo, a greedy approach to de novo assembly employing error-aware graph construction. In the proposed approach, we built contigs by direct read alignment within a distance margin and performed a junction search to construct splicing graphs. While doing so, a contig of length l was represented by a 4 × l matrix (called a consensus matrix), in which each element was the base count of the aligned reads so far. A representative sequence was obtained by taking the majority in each column of the consensus matrix to be used for further read alignment. Once the splicing graphs had been obtained, we used IsoLasso to find paths with a noticeable read depth. The experiments using real and simulated reads show that the method provided considerable improvement in sensitivity and moderately better performance when comparing sensitivity and precision. This was achieved by the error-aware graph construction using the consensus matrix, with which the reads having errors were made usable for the graph construction (otherwise, they might have been eventually discarded). This improved the quality of the coverage depth information used in the subsequent path search step and finally the reliability of the graph. Conclusions De novo assembly is mainly used to explore undiscovered isoforms and must be able to represent as many reads as possible in an efficient way. In this sense, TraRECo provides us with a potential alternative for improving graph reliability even though the computational burden is much higher than the single k-mer in the de Bruijn graph approach.

Surface enhanced Raman spectroscopy (SERS) has been intensively investigated during the past decades for its enormous electromagnetic field enhancement near the nanoscale metallic surfaces. Chemical enhancement of SERS, however, remains rather elusive despite intensive research efforts, mainly due to the relatively complex enhancing factors and inconsistent experimental results. To study details of chemical enhancement mechanism, we prepared various low dimensional semiconductor substrates such as ZnO and GaN that were fabricated via metal organic chemical vapor deposition process. We used three kinds of molecules (4-MPY, 4-MBA, 4-ATP) as analytes to measure SERS spectra under non-plasmonic conditions to understand charge transfer mechanisms between a substrate and analyte molecules leading to chemical enhancement. We observed that there is a preferential route for charge transfer responsible for chemical enhancement, that is, there exists a dominant enhancement process in non-plasmonic SERS. To further confirm our idea of charge transfer mechanism, we used a combination of 2-dimensional transition metal dichalcogenide substrates and analyte molecules. We also observed significant enhancement of Raman signal from molecules adsorbed on 2-dimensional transition metal dichalcogenide surface that is completely consistent with our previous results. We also discuss crucial factors for increasing enhancement factors for chemical enhancement without involving plasmonic resonance.

Vertically-oriented two-dimensional (2D) tungsten disulfide (WS2) nanosheets were successfully grown on a Si substrate at a temperature range between and 550 °C via the direct chemical reaction between WCl6 and S in the gas phase. The growth process was carefully optimized by adjusting temperature, the locations of reactants and substrate, and carrier gas flow. Additionally, vertically-oriented 2D WS2 nanosheets with a few layers were tested as a surface-enhanced Raman scattering substrate for detecting rhodamine 6G (R6G) molecules where enhancement occurs from chemical enhancement by charge transfer transition from semiconductor). Raman spectra of R6G molecules adsorbed on vertically-oriented 2D WS2 nanosheets exhibited strong Raman enhancement effects up to 9.2 times greater than that on the exfoliated WS2 monolayer flake sample. From our results, we suggest that the WS2 nanosheets can be an effective surface-enhanced Raman scattering substrate for detecting target molecules.