Enhanced microbiota profiling in patients with quiescent Crohn's disease through comparison with paired healthy first-degree relatives.

Prior studies indicate no correlation between the gut microbes of healthy first-degree relatives (HFDRs) of patients with Crohn's disease (CD) and the development of CD. Here, we utilize HFDRs as controls to examine the microbiota and metabolome in individuals with active (CD-A) and quiescent (CD-R) CD, thereby minimizing the influence of genetic and environmental factors. When compared to non-relative controls, the use of HFDR controls identifies fewer differential taxa. Faecalibacterium, Dorea, and Fusicatenibacter are decreased in CD-R, independent of inflammation, and correlated with fecal short-chain fatty acids (SCFAs). Validation with a large multi-center cohort confirms decreased Faecalibacterium and other SCFA-producing genera in CD-R. Classification models based on these genera distinguish CD from healthy individuals and demonstrate superior diagnostic power than models constructed with markers identified using unrelated controls. Furthermore, these markers exhibited limited discriminatory capabilities for other diseases. Finally, our results are validated across multiple cohorts, underscoring their robustness and potential for diagnostic and therapeutic applications.

Identification and validation of microbial biomarkers from cross-cohort datasets using xMarkerFinder.

Microbial signatures have emerged as promising biomarkers for disease diagnostics and prognostics, yet their variability across different studies calls for a standardized approach to biomarker research. Therefore, we introduce xMarkerFinder, a four-stage computational framework for microbial biomarker identification with comprehensive validations from cross-cohort datasets, including differential signature identification, model construction, model validation and biomarker interpretation. xMarkerFinder enables the identification and validation of reproducible biomarkers for cross-cohort studies, along with the establishment of classification models and potential microbiome-induced mechanisms. Originally developed for gut microbiome research, xMarkerFinder's adaptable design makes it applicable to various microbial habitats and data types. Distinct from existing biomarker research tools that typically concentrate on a singular aspect, xMarkerFinder uniquely incorporates a sophisticated feature selection process, specifically designed to address the heterogeneity between different cohorts, extensive internal and external validations, and detailed specificity assessments. Execution time varies depending on the sample size, selected algorithm and computational resource. Accessible via GitHub ( https://github.com/tjcadd2020/xMarkerFinder ), xMarkerFinder supports users with diverse expertise levels through different execution options, including step-to-step scripts with detailed tutorials and frequently asked questions, a single-command execution script, a ready-to-use Docker image and a user-friendly web server ( https://www.biosino.org/xmarkerfinder ).

Superconductivity in Ca-intercalated bilayer graphene: C2CaC2.

The deposition and intercalation of metal atoms can induce superconductivity in monolayer and bilayer graphenes. For example, it has been experimentally proved that Li-deposited graphene is a superconductor with critical temperature Tc of 5.9 K, Ca-intercalated bilayer graphene C6CaC6 and K-intercalated epitaxial bilayer graphene C8KC8 are superconductors with Tc of 2-4 K and 3.6 K, respectively. However, the Tc of them are relatively low. To obtain higher Tc in graphene-based superconductors, here we predict a new Ca-intercalated bilayer graphene C2CaC2, which shows higher Ca concentration than the C6CaC6. It is proved to be thermodynamically and dynamically stable. The electronic structure, electron-phonon coupling (EPC) and superconductivity of C2CaC2 are investigated based on first-principles calculations. The EPC of C2CaC2 mainly comes from the coupling between the electrons of C-pz orbital and the high- and low-frequency vibration modes of C atoms. The calculated EPC constant λ of C2CaC2 is 0.75, and the superconducting Tc is 18.9 K, which is much higher than other metal-intercalated bilayer graphenes. By further applying -4% biaxial compressive strain to C2CaC2, the Tc can be boosted to 26.6 K. Thus, the predicted C2CaC2 provides a new platform for realizing superconductivity with the highest Tc in bilayer graphenes.

RNA m6A dynamic modification mediated by nucleus-localized FTO is involved in follicular reserve.

In eukaryotic organisms, the most common internal modification of messenger RNA (mRNA) is N6-methyladenosine (m6A). This modification can be dynamically and reversibly controlled by specific enzymes known as m6A writers and erasers. The fat-mass and obesity-associated protein (FTO) catalyzes RNA demethylation and plays a critical role in various physiological and pathological processes. Our research identified dynamic alterations in both m6A and FTO during the assembly of primordial follicles, with an inverse relationship observed for m6A levels and nuclear-localized FTO expression. Application of Fto small interfering RNA (siRNA) altered the expression of genes related to cell proliferation, hormone regulation, and cell chemotaxis, and affected RNA alternative splicing. Overexpression of the full-length Fto gene led to changes in m6A levels, alternative splicing of Cdk5, cell proliferation, cell cycle progression, and proportion of primordial follicles. Conversely, overexpression of Fto lacking a nuclear localization signal (NLS) did not significantly alter m6A levels or primordial follicle assembly. These findings suggest that FTO, localized in the nucleus but not in the cytoplasm, regulates RNA m6A demethylation and plays a role in cell proliferation, cell cycle progression, and primordial follicle assembly. These results highlight the potential of m6A and its eraser FTO as possible biomarkers and therapeutic targets.

Multi-kingdom microbial signatures in excess body weight colorectal cancer based on global metagenomic analysis.

Excess body weight (EBW) increases the risk of colorectal cancer (CRC) and is linked to lower colonoscopy compliance. Here, we extensively analyzed 981 metagenome samples from multiple cohorts to pinpoint the specific microbial signatures and their potential capability distinguishing EBW patients with CRC. The gut microbiome displayed considerable variations between EBW and lean CRC. We identify 44 and 37 distinct multi-kingdom microbial species differentiating CRC and controls in EBW and lean populations, respectively. Unique bacterial-fungal associations are also observed between EBW-CRC and lean-CRC. Our analysis revealed specific microbial functions in EBW-CRC, including D-Arginine and D-ornithine metabolism, and lipopolysaccharide biosynthesis. The best-performing classifier for EBW-CRC, comprising 12 bacterial and three fungal species, achieved an AUROC of 0.90, which was robustly validated across three independent cohorts (AUROC = 0.96, 0.94, and 0.80). Pathogenic microbial species, Anaerobutyricum hallii, Clostridioides difficile and Fusobacterium nucleatum, are EBW-CRC specific signatures. This work unearths the specific multi-kingdom microbial signatures for EBW-CRC and lean CRC, which may contribute to precision diagnosis and treatment of CRC.

Integrated Transcriptomics and Metabolomics Reveal Changes in Cell Homeostasis and Energy Metabolism in Trachinotus ovatus in Response to Acute Hypoxic Stress.

Trachinotus ovatus is an economically important mariculture fish, and hypoxia has become a critical threat to this hypoxia-sensitive species. However, the molecular adaptation mechanism of T. ovatus liver to hypoxia remains unclear. In this study, we investigated the effects of acute hypoxic stress (1.5 ± 0.1 mg·L-1 for 6 h) and re-oxygenation (5.8 ± 0.3 mg·L-1 for 12 h) in T. ovatus liver at both the transcriptomic and metabolic levels to elucidate hypoxia adaptation mechanism. Integrated transcriptomics and metabolomics analyses identified 36 genes and seven metabolites as key molecules that were highly related to signal transduction, cell growth and death, carbohydrate metabolism, amino acid metabolism, and lipid metabolism, and all played key roles in hypoxia adaptation. Of these, the hub genes FOS and JUN were pivotal hypoxia adaptation biomarkers for regulating cell growth and death. During hypoxia, up-regulation of GADD45B and CDKN1A genes induced cell cycle arrest. Enhancing intrinsic and extrinsic pathways in combination with glutathione metabolism triggered apoptosis; meanwhile, anti-apoptosis mechanism was activated after hypoxia. Expression of genes related to glycolysis, gluconeogenesis, amino acid metabolism, fat mobilization, and fatty acid biosynthesis were up-regulated after acute hypoxic stress, promoting energy supply. After re-oxygenation for 12 h, continuous apoptosis favored cellular function and tissue repair. Shifting from anaerobic metabolism (glycolysis) during hypoxia to aerobic metabolism (fatty acid ß-oxidation and TCA cycle) after re-oxygenation was an important energy metabolism adaptation mechanism. Hypoxia 6 h was a critical period for metabolism alteration and cellular homeostasis, and re-oxygenation intervention should be implemented in a timely way. This study thoroughly examined the molecular response mechanism of T. ovatus under acute hypoxic stress, which contributes to the molecular breeding of hypoxia-tolerant cultivars.

Host-microbiota interactions contributing to the heterogeneous tumor microenvironment in colorectal cancer.

Colorectal cancer (CRC) exhibits pronounced heterogeneity and is categorized into four widely accepted consensus molecular subtypes (CMSs) with unique tumor microenvironments (TMEs). However, the intricate landscape of the microbiota and host-microbiota interactions within these TMEs remains elusive. Using RNA-sequencing data from The Cancer Genome Atlas, we analyzed the host transcriptomes and intratumoral microbiome profiles of CRC samples. Distinct host genes and microbial genera were identified among the CMSs. Immune microenvironments were evaluated using CIBERSORTx and ESTIMATE, and microbial coabundance patterns were assessed with FastSpar. Through LASSO penalized regression, we explored host-microbiota associations for each CMS. Our analysis revealed distinct host gene signatures within the CMSs, which encompassed ferroptosis-related genes and specific immune microenvironments. Moreover, we identified 293, 153, 66, and 109 intratumoral microbial genera with differential abundance, and host-microbiota associations contributed to distinct TMEs, characterized by 829, 1,270, 634, and 1,882 robust gene-microbe associations for each CMS in CMS1-CMS4, respectively. CMS1 featured inflammation-related HSF1 activation and gene interactions within the endothelin pathway and Flammeovirga. Integrin-related genes displayed positive correlations with Sutterella in CMS2, whereas CMS3 spotlighted microbial associations with biosynthetic and metabolic pathways. In CMS4, genes involved in collagen biosynthesis showed positive associations with Sutterella, contributing to disruptions in homeostasis. Notably, immune-rich subtypes exhibited pronounced ferroptosis dysregulation, potentially linked to tissue microbial colonization. This comprehensive investigation delineates the diverse landscapes of the TME within each CMS, incorporating host genes, intratumoral microbiota, and their complex interactions. These findings shed light on previously uncharted mechanisms underpinning CRC heterogeneity and suggest potential therapeutic targets.NEW & NOTEWORTHY This study determined the following: 1) providing a comprehensive landscape of consensus molecular subtype (CMS)-specific tumor microenvironments (TMEs); 2) constructing CMS-specific networks, including host genes, intratumoral microbiota, and enriched pathways, analyzing their associations to uncover unique patterns that demonstrate the intricate interplay within the TME; and 3) revealing a connection between immune-rich subtypes and ferroptosis activation, suggesting a potential regulatory role of the microbiota in ferroptosis dysregulation of the colorectal cancer TME.

NAFLDkb: A Knowledge Base and Platform for Drug Development against Nonalcoholic Fatty Liver Disease.

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease with a broad spectrum of histologic manifestations. The rapidly growing prevalence and the complex pathologic mechanisms of NAFLD pose great challenges for treatment development. Despite tremendous efforts devoted to drug development, there are no FDA-approved medicines yet. Here, we present NAFLDkb, a specialized knowledge base and platform for computer-aided drug design against NAFLD. With multiperspective information curated from diverse source materials and public databases, NAFLDkb presents the associations of drug-related entities as individual knowledge graphs. Practical drug discovery tools that facilitate the utilization and expansion of NAFLDkb have also been implemented in the web interface, including chemical structure search, drug-likeness screening, knowledge-based repositioning, and research article annotation. Moreover, case studies of a knowledge graph repositioning model and a generative neural network model are presented herein, where three repositioning drug candidates and 137 novel lead-like compounds were newly established as NAFLD pharmacotherapy options reusing data records and machine learning tools in NAFLDkb, suggesting its clinical reliability and great potential in identifying novel drug-disease associations of NAFLD and generating new insights to accelerate NAFLD drug development. NAFLDkb is freely accessible at https://www.biosino.org/nafldkb and will be updated periodically with the latest findings.

First-principles prediction of superconducting properties of monolayer 1T'-WS2 under biaxial tensile strain.

High-purity 1T'-WS2 film has been experimentally synthesized [Nature Materials, 20, 1113-1120 (2021)] and theoretically predicted to be a two-dimensional (2D) superconducting material with Dirac cones [arXiv:2301.11425]. In the present work, we further study the superconducting properties of monolayer 1T'-WS2 by applying biaxial tensile strain. It is shown that the superconducting critical temperature Tc firstly increases and then decreases with respect to tensile strains, with the highest superconducting critical temperature Tc of 7.25 K under the biaxial tensile strain of 3%. In particular, we find that Dirac cones also exist in several tensile strained cases. Our studies show that monolayer 1T'-WS2 may provide a good platform for understanding the superconductivity of 2D Dirac materials.

Multimodal metagenomic analysis reveals microbial single nucleotide variants as superior biomarkers for early detection of colorectal cancer.

Microbial signatures show remarkable potentials in predicting colorectal cancer (CRC). This study aimed to evaluate the diagnostic powers of multimodal microbial signatures, multi-kingdom species, genes, and single-nucleotide variants (SNVs) for detecting precancerous adenomas. We performed cross-cohort analyses on whole metagenome sequencing data of 750 samples via xMarkerFinder to identify adenoma-associated microbial multimodal signatures. Our data revealed that fungal species outperformed species from other kingdoms with an area under the ROC curve (AUC) of 0.71 in distinguishing adenomas from controls. The microbial SNVs, including dark SNVs with synonymous mutations, displayed the strongest diagnostic capability with an AUC value of 0.89, sensitivity of 0.79, specificity of 0.85, and Matthews correlation coefficient (MCC) of 0.74. SNV biomarkers also exhibited outstanding performances in three independent validation cohorts (AUCs = 0.83, 0.82, 0.76; sensitivity = 1.0, 0.72, 0.93; specificity = 0.67, 0.81, 0.67, MCCs = 0.69, 0.83, 0.72) with high disease specificity for adenoma. In further support of the above results, functional analyses revealed more frequent inter-kingdom associations between bacteria and fungi, and abnormalities in quorum sensing, purine and butanoate metabolism in adenoma, which were validated in a newly recruited cohort via qRT-PCR. Therefore, these data extend our understanding of adenoma-associated multimodal alterations in the gut microbiome and provide a rationale of microbial SNVs for the early detection of CRC.

Hydrogenation induced high-temperature superconductivity in two-dimensional W2C3.

The discovery of highly crystalline two-dimensional (2D) superconductors provides a new alluring branch for exploring the fundamental significances. Based on first-principles calculations, we predict a new kind of 2D stable material W2C3, which is a semimetal but not a superconductor because of the weak electron-phonon coupling (EPC) strength. After hydrogenation, W2C3H2 possesses the intrinsic metallic properties with a large density of states (DOS) at the Fermi energy (EF). More interestingly, the EPC strength is greatly enhanced after hydrogenation and the calculated critical temperature (Tc) is 40.5 K. Furthermore, the compressive strain can obviously soften the low-frequency phonons and enhance the EPC strength. Then, the Tc of W2C3H2 can be increased from 40.5 K to 49.1 K with -4% compressive strain. This work paves the way for providing a new platform for 2D superconductivity.

Microbial genes outperform species and SNVs as diagnostic markers for Crohn's disease on multicohort fecal metagenomes empowered by artificial intelligence.

Dysbiosis of gut microbial community is associated with the pathogenesis of CD and may serve as a promising noninvasive diagnostic tool. We aimed to compare the performances of the microbial markers of different biological levels by conducting a multidimensional analysis on the microbial metagenomes of CD. We collected fecal metagenomic datasets generated from eight cohorts that altogether include 870 CD patients and 548 healthy controls. Microbial alterations in CD patients were assessed at multidimensional levels including species, gene, and SNV level, and then diagnostic models were constructed using artificial intelligence algorithm. A total of 227 species, 1047 microbial genes, and 21,877 microbial SNVs were identified that differed between CD and controls. The species, gene, and SNV models achieved an average AUC of 0.97, 0.95, and 0.77, respectively. Notably, the gene model exhibited superior diagnostic capability, achieving an average AUC of 0.89 and 0.91 for internal and external validations, respectively. Moreover, the gene model was specific for CD against other microbiome-related diseases. Furthermore, we found that phosphotransferase system (PTS) contributed substantially to the diagnostic capability of the gene model. The outstanding performance of PTS was mainly explained by genes celB and manY, which demonstrated high predictabilities for CD with metagenomic datasets and was validated in an independent cohort by qRT-PCR analysis. Our global metagenomic analysis unravels the multidimensional alterations of the microbial communities in CD and identifies microbial genes as robust diagnostic biomarkers across geographically and culturally distinct cohorts.

Engineering fluorescent protein chromophores with an internal reference for high-fidelity ratiometric G4 imaging in living cells.

G-quadruplexes (G4s) are significant nucleic acid secondary structures formed by guanine-rich sequences. Many single-emission G4 fluorescent probes that are lit up by inhibiting intramolecular rotation have been reported. However, they are non-fluorescent unless structurally rigidified, making them sensitive to other intracellular crowding and confinement environments in the cell, like viscosity. Ratiometric measurements provide built-in self-calibration for signal correction, enabling more sensitive and reliable detection. Herein, we structurally modulate green fluorescent protein (GFP)-like chromophores by integrating the imidazolidinone scaffold of the GFP chromophore and coumarin 6H, obtaining a G4 responsive dual-emission chromophore, called NHCouI. The red emission signal of NHCouI can specifically respond to parallel G4s, while its green emission signal is inert and acts as an internal reference signal. NHCouI-G4 complexes feature high fluorescence quantum yield and excellent anti-photobleaching properties. NHCouI can self-calibrate the signal and avoid viscosity disturbances within the range of major subcellular organelles during G4 imaging in living cells. It is also applied to reflect the difference between apoptosis and ferroptosis via tracking G4s. To the best of our knowledge, NHCouI is the first small molecule G4 probe enabled by internal reference correction capability, opening up new avenues for dual-emission chromophore development and high-fidelity and reliable analysis in G4 imaging research.

Systematic Microbiome Dysbiosis Is Associated with IgA Nephropathy.

IgA nephropathy (IgAN) is reportedly associated with microbial dysbiosis. However, the microbiome dysregulation of IgAN patients across multiple niches remains unclear. To gain a systematic understanding of microbial dysbiosis, we conducted large-scale 16S rRNA gene sequencing in IgAN patients and healthy volunteers across 1,732 oral, pharynx, gut, and urine samples. We observed a niche-specific increase of several opportunistic pathogens, including Bergeyella and Capnocytophaga in the oral and pharynx, whereas some beneficial commensals decreased in IgAN patients. Similar alterations were also observed in the early versus advanced stage of chronic kidney disease (CKD) progression. Moreover, Bergeyella, Capnocytophaga, and Comamonas in the oral and pharynx were positively associated with creatinine and urea, indicating renal lesions. Random forest classifiers were developed by using the microbial abundance to predict IgAN, achieving an optimal accuracy of 0.879 in the discovery phase and 0.780 in the validation phase. IMPORTANCE This study provides microbial profiles of IgAN across multiple niches and underlines the potential of these biomarkers as promising, noninvasive tools with which to differentiate IgAN patients for clinical applications.

Integrative multi-omics deciphers the spatial characteristics of host-gut microbiota interactions in Crohn's disease.

Dysregulated host-microbial interactions play critical roles in initiation and perpetuation of gut inflammation in Crohn's disease (CD). However, the spatial distribution and interaction network across the intestine and its accessory tissues are still elusive. Here, we profile the host proteins and tissue microbes in 540 samples from the intestinal mucosa, submucosa-muscularis-serosa, mesenteric adipose tissues, mesentery, and mesenteric lymph nodes of 30 CD patients and spatially decipher the host-microbial interactions. We observe aberrant antimicrobial immunity and metabolic processes across multi-tissues during CD and determine bacterial transmission along with altered microbial communities and ecological patterns. Moreover, we identify several candidate interaction pairs between host proteins and microbes associated with perpetuation of gut inflammation and bacterial transmigration across multi-tissues in CD. Signature alterations in host proteins (e.g., SAA2 and GOLM1) and microbes (e.g., Alistipes and Streptococcus) are further imprinted in serum and fecal samples as potential diagnostic biomarkers, thus providing a rationale for precision diagnosis.

Co-expression and interaction network analysis reveals dysregulated neutrophil and T-cell activation as the core mechanism associated with septic shock.

Septic shock as a subset of sepsis, has a much higher mortality, while the mechanism is still elusive. This study was aimed at identifying core mechanisms associated with septic shock and its high mortality by investigating transcriptome data. We screened 72 septic-shock-associated genes (SSAGs) with differential expression between septic shock and sepsis in the discovery dataset. Further gene set enrichment analysis identified upregulated neutrophil activation and impaired T-cell activation in septic shock. Co-expression analysis revealed nine co-expressed gene modules. In addition, we determined twenty-one prognostic SSAGs using cox regression analysis in an independent dataset. Moreover, protein-protein interaction (PPI) network revealed two clusters. Among these neutrophil activation was enriched in the most positively-related modules and the cluster2 PPI network, while T-cell activation was enriched in both the most negatively-related module and one of the most positively-related modules as well as the cluster1 PPI network. ELANE, LCN2 and IFI44 were identified as hub genes with CytoHubba methods and semantic similarity analysis. Notably, ELANE was the only prognostic gene and was further validated in an external dataset. Blood neutrophil count was demonstrated to increase in septic shock and be a risky factor of prognosis based on clinical data. In conclusions, septic shock is associated with upregulated neutrophil activation and dysregulated T-cell activation. Three hub genes might have potentials as sensitive markers for the further translational research and ELANE could be a robust prognostic biomarker and effective therapeutic target.