Dimethylsulfoniopropionate (DMSP): From Biochemistry to Global Ecological Significance.

Dimethylsulfoniopropionate (DMSP) is one of Earth's most abundant organosulfur compounds with important roles in stress tolerance, chemotaxis, global carbon and sulfur cycling, and climate-active gas production. Diverse marine prokaryotes and eukaryotes produce DMSP via three known pathways (methylation, transamination, and decarboxylation) and metabolize DMSP via three further pathways (demethylation, cleavage, and oxidation). Over 20 key enzymes from these pathways have been identified to inform on the biodiversity and importance of DMSP cycling. The last dozen years have seen significant changes in our understanding of the enzymology and molecular mechanisms of these DMSP cycling enzymes through the application of biochemistry and structural biology. This has yielded more than 10 crystal structures and, in many cases, detailed explanations as to how and why organisms synthesis and metabolize DMSP. In this review, we describe recent progress in biochemical and mechanistic understandings of DMSP synthesis and metabolism, highlighting the important knowledge gleaned and current challenges that warrant further exploration.

BRCA1 and ELK-1 regulate neural progenitor cell fate in the optic tectum in response to visual experience in Xenopus laevis tadpoles.

In developing Xenopus tadpoles, the optic tectum begins to receive patterned visual input while visuomotor circuits are still undergoing neurogenesis and circuit assembly. This visual input regulates neural progenitor cell fate decisions such that maintaining tadpoles in the dark increases proliferation, expanding the progenitor pool, while visual stimulation promotes neuronal differentiation. To identify regulators of activity-dependent neural progenitor cell fate, we profiled the transcriptomes of proliferating neural progenitor cells and newly differentiated neurons using RNA-Seq. We used advanced bioinformatic analysis of 1,130 differentially expressed transcripts to identify six differentially regulated transcriptional regulators, including Breast Cancer 1 (BRCA1) and the ETS-family transcription factor, ELK-1, which are predicted to regulate the majority of the other differentially expressed transcripts. BRCA1 is known for its role in cancers, but relatively little is known about its potential role in regulating neural progenitor cell fate. ELK-1 is a multifunctional transcription factor which regulates immediate early gene expression. We investigated the potential functions of BRCA1 and ELK-1 in activity-regulated neurogenesis in the tadpole visual system using in vivo time-lapse imaging to monitor the fate of GFP-expressing SOX2+ neural progenitor cells in the optic tectum. Our longitudinal in vivo imaging analysis showed that knockdown of either BRCA1 or ELK-1 altered the fates of neural progenitor cells and furthermore that the effects of visual experience on neurogenesis depend on BRCA1 and ELK-1 expression. These studies provide insight into the potential mechanisms by which neural activity affects neural progenitor cell fate.

BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets.

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enable generalizable benchmarking. Together with image quality features, we pooled the data in an interactive web application that enables users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and tracing data, and benchmarking of automatic tracing algorithms in user-defined data subsets. The image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. We observed that diverse algorithms can provide complementary information to obtain accurate results and developed a method to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings.

Neuronal membrane proteasomes regulate neuronal circuit activity in vivo and are required for learning-induced behavioral plasticity.

Protein degradation is critical for brain function through processes that remain incompletely understood. Here, we investigated the in vivo function of the 20S neuronal membrane proteasome (NMP) in the brain of Xenopus laevis tadpoles. With biochemistry, immunohistochemistry, and electron microscopy, we demonstrated that NMPs are conserved in the tadpole brain and preferentially degrade neuronal activity-induced newly synthesized proteins in vivo. Using in vivo calcium imaging in the optic tectum, we showed that acute NMP inhibition rapidly increased spontaneous neuronal activity, resulting in hypersynchronization across tectal neurons. At the circuit level, inhibiting NMPs abolished learning-dependent improvement in visuomotor behavior in live animals and caused a significant deterioration in basal behavioral performance following visual training with enhanced visual experience. Our data provide in vivo characterization of NMP functions in the vertebrate nervous system and suggest that NMP-mediated degradation of activity-induced nascent proteins may serve as a homeostatic modulatory mechanism in neurons that is critical for regulating neuronal activity and experience-dependent circuit plasticity.

Molecular interactions of the chaperone CcmS and carboxysome shell protein CcmK1 that mediate ß-carboxysome assembly.

The carboxysome is a natural proteinaceous organelle for carbon fixation in cyanobacteria and chemoautotrophs. It comprises hundreds of protein homologs that self-assemble to form a polyhedral shell structure to sequester cargo enzymes, ribulose 1,5-bisphosphate carboxylase/oxygenase (Rubisco) and carbonic anhydrases. How these protein components assemble to construct a functional carboxysome is a central question in not only understanding carboxysome structure and function but also synthetic engineering of carboxysomes for biotechnological applications. Here, we determined the structure of the chaperone protein CcmS, which has recently been identified to be involved in ß-carboxysome assembly, and its interactions with ß-carboxysome proteins. The crystal structure at 1.99 Å resolution reveals CcmS from Nostoc sp. PCC 7120 forms a homodimer, and each CcmS monomer consists of five α-helices and four ß-sheets. Biochemical assays indicate that CcmS specifically interacts with the C-terminal extension of the carboxysome shell protein CcmK1, but not the shell protein homolog CcmK2 or the carboxysome scaffolding protein CcmM. Moreover, we solved the structure of a stable complex of CcmS and the C-terminus of CcmK1 at 1.67 Å resolution and unveiled how the CcmS dimer interacts with the C-terminus of CcmK1. These findings allowed us to propose a model to illustrate CcmS-mediated ß-carboxysome assembly by interacting with CcmK1 at the outer shell surface. Collectively, our study provides detailed insights into the accessory factors that drive and regulate carboxysome assembly, thereby improving our knowledge of carboxysome structure, function, and bioengineering.

ZFHX3 variants cause childhood partial epilepsy and infantile spasms with favourable outcomes.

BACKGROUND: The ZFHX3 gene plays vital roles in embryonic development, cell proliferation, neuronal differentiation and neuronal death. This study aims to explore the relationship between ZFHX3 variants and epilepsy. METHODS: Whole-exome sequencing was performed in a cohort of 378 patients with partial (focal) epilepsy. A Drosophila Zfh2 knockdown model was used to validate the association between ZFHX3 and epilepsy. RESULTS: Compound heterozygous ZFHX3 variants were identified in eight unrelated cases. The burden of ZFHX3 variants was significantly higher in the case cohort, shown by multiple/specific statistical analyses. In Zfh2 knockdown flies, the incidence and duration of seizure-like behaviour were significantly greater than those in the controls. The Zfh2 knockdown flies exhibited more firing in excitatory neurons. All patients presented partial seizures. The five patients with variants in the C-terminus/N-terminus presented mild partial epilepsy. The other three patients included one who experienced frequent non-convulsive status epilepticus and two who had early spasms. These three patients had also neurodevelopmental abnormalities and were diagnosed as developmental epileptic encephalopathy (DEE), but achieved seizure-free after antiepileptic-drug treatment without adrenocorticotropic-hormone/steroids. The analyses of temporal expression (genetic dependent stages) indicated that ZFHX3 orthologous were highly expressed in the embryonic stage and decreased dramatically after birth. CONCLUSION: ZFHX3 is a novel causative gene of childhood partial epilepsy and DEE. The patients of infantile spasms achieved seizure-free after treatment without adrenocorticotropic-hormone/steroids implies a significance of genetic diagnosis in precise treatment. The genetic dependent stage provided an insight into the underlying mechanism of the evolutional course of illness.

An Ultrasensitive and Efficient microRNA Nanosensor Empowered by the CRISPR/Cas Confined in a Nanopore.

This work presents a clustered regularly interspaced short palindromic repeat (CRISPR)/Cas-nanopipette nano-electrochemistry (Cas = CRISPR-associated proteins) capable of ultrasensitive microRNA detection. Nanoconfinement of the CRISPR/Cas13a within a nanopipette leads to a high catalytic efficacy of ca. 169 times higher than that in bulk electrolyte, contributing to the amplified electrochemical responses. CRISPR/Cas13a-enabled detection of representative microRNA-25 achieves a low limit of detection down to 10 aM. Practical application of this method is further demonstrated for single-cell and real human serum detection. Its general applicability is validated by addressing microRNA-141 and the SARS-CoV-2 RNA gene fragment. This work introduces a new CRISPR/Cas-empowered nanotechnology for ultrasensitive nano-electrochemistry and bioanalysis.

Accurate Cancer Screening and Prediction of PD-L1-Guided Immunotherapy Efficacy Using Quantum Dot Nanosphere Self-Assembly and Machine Learning.

Accurate quantification of exosomal PD-L1 protein in tumors is closely linked to the response to immunotherapy, but robust methods to achieve high-precision quantitative detection of PD-L1 expression on the surface of circulating exosomes are still lacking. In this work, we developed a signal amplification approach based on aptamer recognition and DNA scaffold hybridization-triggered assembly of quantum dot nanospheres, which enables bicolor phenotyping of exosomes to accurately screen for cancers and predict PD-L1-guided immunotherapeutic effects through machine learning. Through DNA-mediated assembly, we utilized two aptamers for simultaneous ultrasensitive detection of exosomal antigens, which have synergistic roles in tumor diagnosis and treatment prediction, and thus, we achieved better sample classification and prediction through machine-learning algorithms. With a drop of blood, we can distinguish between different cancer patients and healthy individuals and predict the outcome of immunotherapy. This approach provides valuable insights into the development of personalized diagnostics and precision medicine.

A novel class of xylanases specifically degrade marine red algal ß1,3/1,4-mixed-linkage xylan.

Xylans are polysaccharides composed of xylose and include ß1,4-xylan, ß1,3-xylan, and ß1,3/1,4-mixed-linkage xylan (MLX). MLX is widely present in marine red algae and constitutes a significant organic carbon in the ocean. Xylanases are hydrolase enzymes that play an important role in xylan degradation. While a variety of ß1,4-xylanases and ß1,3-xylanases involved in the degradation of ß1,4-xylan and ß1,3-xylan have been reported, no specific enzyme has yet been identified that degrades MLX. Herein, we report the characterization of a new MLX-specific xylanase from the marine bacterium Polaribacter sp. Q13 which utilizes MLX for growth. The bacterium secretes xylanases to degrade MLX, among which is Xyn26A, an MLX-specific xylanase that shows low sequence similarities (<27%) to ß1,3-xylanases in the glycoside hydrolase family 26 (GH26). We show that Xyn26A attacks MLX precisely at ß1,4-linkages, following a ß1,3-linkage toward the reducing end. We confirm that Xyn26A and its homologs have the same specificity and mode of action on MLX, and thus represent a new xylanase group which we term as MLXases. We further solved the structure of a representative MLXase, AlXyn26A. Structural and biochemical analyses revealed that the specificity of MLXases depends critically on a precisely positioned ß1,3-linkage at the -2/-1 subsite. Compared to the GH26 ß1,3-xylanases, we found MLXases have evolved a tunnel-shaped cavity that is fine-tuned to specifically recognize and hydrolyze MLX. Overall, this study offers a foremost insight into MLXases, shedding light on the biochemical mechanism of bacterial degradation of MLX.

Structural and molecular basis for urea recognition by Prochlorococcus.

Nitrogen (N) is an essential element for microbial growth and metabolism. The growth and reproduction of microorganisms in more than 75% of areas of the ocean are limited by N. Prochlorococcus is numerically the most abundant photosynthetic organism on the planet. Urea is an important and efficient N source for Prochlorococcus. However, how Prochlorococcus recognizes and absorbs urea still remains unclear. Prochlorococcus marinus MIT 9313, a typical Cyanobacteria, contains an ABC-type transporter, UrtABCDE, which may account for the transport of urea. Here, we heterologously expressed and purified UrtA, the substrate-binding protein of UrtABCDE, detected its binding affinity toward urea, and further determined the crystal structure of the UrtA/urea complex. Molecular dynamics simulations indicated that UrtA can alternate between "open" and "closed" states for urea binding. Based on structural and biochemical analyses, the molecular mechanism for urea recognition and binding was proposed. When a urea molecule is bound, UrtA undergoes a state change from open to closed surrounding the urea molecule, and the urea molecule is further stabilized by the hydrogen bonds supported by the conserved residues around it. Moreover, bioinformatics analysis showed that ABC-type urea transporters are widespread in bacteria and probably share similar urea recognition and binding mechanisms as UrtA from P. marinus MIT 9313. Our study provides a better understanding of urea absorption and utilization in marine bacteria.

Targeting EFHD2 inhibits interferon-γ signaling and ameliorates non-alcoholic steatohepatitis.

BACKGROUND & AIMS: The precise pathomechanisms underlying the development of non-alcoholic steatohepatitis (NASH, also known as metabolic dysfunction-associated steatohepatitis [MASH]) remain incompletely understood. In this study, we investigated the potential role of EF-hand domain family member D2 (EFHD2), a novel molecule specific to immune cells, in the pathogenesis of NASH. METHODS: Hepatic EFHD2 expression was characterized in patients with NASH and two diet-induced NASH mouse models. Single-cell RNA sequencing (scRNA-seq) and double-immunohistochemistry were employed to explore EFHD2 expression patterns in NASH livers. The effects of global and myeloid-specific EFHD2 deletion on NASH and NASH-related hepatocellular carcinoma were assessed. Molecular mechanisms underlying EFHD2 function were investigated, while chemical and genetic investigations were performed to assess its potential as a therapeutic target. RESULTS: EFHD2 expression was significantly elevated in hepatic macrophages/monocytes in both patients with NASH and mice. Deletion of EFHD2, either globally or specifically in myeloid cells, improved hepatic steatosis, reduced immune cell infiltration, inhibited lipid peroxidation-induced ferroptosis, and attenuated fibrosis in NASH. Additionally, it hindered the development of NASH-related hepatocellular carcinoma. Specifically, deletion of myeloid EFHD2 prevented the replacement of TIM4+ resident Kupffer cells by infiltrated monocytes and reversed the decreases in patrolling monocytes and CD4+/CD8+ T cell ratio in NASH. Mechanistically, our investigation revealed that EFHD2 in myeloid cells interacts with cytosolic YWHAZ (14-3-3ζ), facilitating the translocation of IFNγR2 (interferon-γ receptor-2) onto the plasma membrane. This interaction mediates interferon-γ signaling, which triggers immune and inflammatory responses in macrophages during NASH. Finally, a novel stapled α-helical peptide targeting EFHD2 was shown to be effective in protecting against NASH pathology in mice. CONCLUSION: Our study reveals a pivotal immunomodulatory and inflammatory role of EFHD2 in NASH, underscoring EFHD2 as a promising druggable target for NASH treatment. IMPACT AND IMPLICATIONS: Non-alcoholic steatohepatitis (NASH) represents an advanced stage of non-alcoholic fatty liver disease (NAFLD); however, not all patients with NAFLD progress to NASH. A key challenge is identifying the factors that trigger inflammation, which propels the transition from simple fatty liver to NASH. Our research pinpointed EFHD2 as a pivotal driver of NASH, orchestrating the over-activation of interferon-γ signaling within the liver during NASH progression. A stapled peptide designed to target EFHD2 exhibited therapeutic promise in NASH mice. These findings support the potential of EFHD2 as a therapeutic target in NASH.

Outcomes Related to New Persistent Opioid Use after Surgery or Trauma: A population-based Cohort Study.

OBJECTIVES: To evaluate the impact of persistent opioid use (POU) following surgery or trauma on health outcomes using linked data. SUMMARY BACKGROUND DATA: Surgery and trauma can lead to POU, characterised by continuous opioid consumption following hospital discharge. Outside the US, there is a lack of population-based studies on POU outcomes in opioid-naïve patients following these events. METHOD: We included opioid-naïve patients who were dispensed opioids after being discharged following admission for surgery or trauma to any New Zealand (NZ) hospital from 2007-2019. Differences in outcomes between individuals with and without POU were assessed between 180-360 days after discharge. The primary outcome was all-cause mortality, the secondary outcomes were all-cause and opioid-related hospitalisation, and Days Alive and Out of Hospital (DAOH). Cox and quantile multivariable regression models were used to examine the association between POU and outcomes. RESULTS: Overall, 298,928 surgical and 206,663 trauma patients were included in the final analyses, and 17,779 (5.9%) surgical and 17,867 (8.6%) trauma patients developed POU. POU was significantly associated with increased risk of all-cause mortality (surgical, aHR=6.59; 95% CI 5.82-7.46; trauma, aHR=2.77; 95% CI 2.47-3.11), all-cause hospitalisation (surgical, aHR=2.02; 95% CI 1.95-2.08; trauma, aHR=1.57; 95% CI 1.52-1.62), opioid-related hospitalisation (surgical, aHR=2.49; 95% CI 2.24-2.76; trauma, aHR=1.89; 95% CI 1.73-2.05) and reduced DAOH. CONCLUSIONS: Among opioid-naive patients who received opioids after surgery or trauma, POU was associated with worse outcomes, including increased mortality. Further investigation is warranted to understand the reasons for continued opioid use beyond 90 days and mechanisms associated with harm.

Tumor microenvironment characteristics association with clinical outcome in patients with resected intestinal-type gastric cancer.

BACKGROUND: Tumor microenvironment (TME) characteristics including tumor stroma ratio (TSR), tumor budding (TB), and tumor-infiltrating lymphocytes (TILs) were examined in resected gastric cancer. These TME features have been shown to indicate metastatic potential in colon cancer, and intestinal-type gastric cancer (IGC) has pathological similarities with that malignancy. METHODS: TSR, TB, and TILs were quantified in routine histological sections from 493 patients with IGC who underwent radical resection at 2 university hospitals in China from 2010 to 2016. TME variables were dichotomized as follows: TSR (50%), TILs (median), TB per international guidelines (4 buds/0.785mm2), and platelet-lymphocyte ratio (PLR) per survival ROC. Association of TME features with patient clinicopathological characteristics, time-to-recurrence (TTR), and cancer-specific-survival (CSS) were examined using univariate and multivariate analysis, including a relative contribution analysis by Cox regression. RESULTS: Patients whose tumors showed high TSR or high TB or low TILs were each significantly associated with increased T and N stage, higher histological grade, and poorer TTR and CSS at 5 years. Only TSR and N stage were independently associated with TTR and CSS after adjustment for covariates. PLR was only independently associated with TTR after adjustment for covariates. Among the variables examined, only TSR was significantly associated with both TTR (HR 1.72, 95% CI, 1.14-2.60, P = .01) and CSS (HR 1.62, 95% CI, 1.05-2.51, P = .03) multivariately. Relative contribution to TTR revealed that the top 3 contributors were N stage (45.1%), TSR (22.5%), and PLR (12.9%), while the top 3 contributors to CSS were N stage (59.9%), TSR (14.7%), and PLR (10.9%). CONCLUSIONS: Among the examined TME features, TSR was the most robust for prognostication and was significantly associated with both TTR and CSS. Furthermore, the relative contribution of TSR to patient TTR and CSS was second only to nodal status.

An Orthogonal CRISPR/dCas12a System for RNA Imaging in Live Cells.

CRISPR/Cas technology has made great progress in the field of live-cell imaging beyond genome editing. However, effective and easy-to-use CRISPR systems for labeling multiple RNAs of interest are still needed. Here, we engineered a CRISPR/dCas12a system that enables the specific recognition of the target RNA under the guidance of a PAM-presenting oligonucleotide (PAMmer) to mimic the PAM recognition mechanism for DNA substrates. We demonstrated the feasibility and specificity of this system for specifically visualizing endogenous mRNA. By leveraging dCas12a-mediated precursor CRISPR RNA (pre-crRNA) processing and the orthogonality of dCas12a from different bacteria, we further demonstrated the proposed system as a simple and versatile molecular toolkit for multiplexed imaging of different types of RNA transcripts in live cells with high specificity. This programmable dCas12a system not only broadens the RNA imaging toolbox but also facilitates diverse applications for RNA manipulation.

Electrochemiluminescence-Based Single-Particle Tracking of the Biomolecules Moving along Intercellular Membrane Nanotubes between Live Cells.

Electrochemiluminescence (ECL) imaging, a rapidly evolving technology, has attracted significant attention in the field of cellular imaging. However, its primary limitation lies in its inability to analyze the motion behaviors of individual particles in live cellular environments. In this study, we leveraged the exceptional ECL properties of quantum dots (QDs) and the excellent electrochemical properties of carbon dots (CDs) to develop a high-brightness ECL nanoprobe (CDs-QDs) for real-time ECL imaging between living cells. This nanoprobe has excellent signal-to-noise ratio imaging capabilities for the single-particle tracking (SPT) of biomolecules. Our finding elucidated the enhanced ECL mechanism of CDs-QDs in the presence of reactive oxygen species through photoluminescence, electrochemistry, and ECL techniques. We further tracked the movement of single particles on membrane nanotubes between live cells and confirmed that the ECL-based SPT technique using CD-QD nanoparticles is an effective approach for monitoring the transport behaviors of biomolecules on membrane nanotubes between live cells. This opens a promising avenue for the advancement of ECL-based single-particle detection and the dynamic quantitative imaging of biomolecules.

In Situ Quantitative Imaging of Plasma Membrane Stiffness in Live Cells Using a Genetically Encoded FRET Sensor.

Cell membrane stiffness is critical for cellular function, with cholesterol and sphingomyelin as pivot contributors. Current methods for measuring membrane stiffness are often invasive, ex situ, and slow in process, prompting the need for innovative techniques. Here, we present a fluorescence resonance energy transfer (FRET)-based protein sensor designed to address these challenges. The sensor consists of two fluorescent units targeting sphingomyelin and cholesterol, connected by a linker that responds to the proximity of these lipids. In rigid membranes, cholesterol and sphingomyelin are in close proximity, leading to an increased FRET signal. We utilized this sensor in combination with confocal microscopy to explore changes in plasma membrane stiffness under various conditions, including differences in osmotic pressure, the presence of reactive oxygen species (ROS) and variations in substrate stiffness. Furthermore, we explored the impact of SARS-CoV-2 on membrane stiffness and the distribution of ACE2 after attachment to the cell membrane. This tool offers substantial potential for future investigations in the field of mechanobiology.

Chemistry-Enabled Intercellular Enzymatic Labeling for Monitoring the Immune Effects of Cytotoxic T Lymphocytes In Vivo.

Monitoring the effector function of cytotoxic T lymphocytes (CTLs) in vivo remains a great challenge. Here, we develop a chemistry-enabled enzymatic labeling approach to evaluate the tumor-specific immune response of CTLs by precisely monitoring the interaction between CTLs and tumor cells. Staphylococcus aureus sortase A (SrtA) is linked to the CTL surface through bioconjugate chemistry and then catalyzes the transfer of fluorescent-labeled substrate, 5-Tamra-LPETG, to CTLs. Meanwhile, the tumor cells are specifically decorated with N-terminal glycine residues (G5 peptide) through the inherent glycolmetabolism of cathepsin B-specific cleavable triacetylated N-azidoacetyl-d-mannosamine (CB-Ac3ManNAz) and click chemistry. After the infiltration of engineered CTLs into the tumor tissues, the immune-synapse-mediated specific interaction of CTLs and tumor cells leads to the accurate fluorescent labeling of tumor cells through the SrtA-catalyzed 5-Tamra-LPETG transfer. Therefore, the immune effect of CTLs as well as the performance of immune drugs can be determined, providing a novel strategy for pushing ahead immunotherapy.

AntDAS-GCMS: A New Comprehensive Data Analysis Platform for GC-MS-Based Untargeted Metabolomics with the Advantage of Addressing the Time Shift Problem.

Over the years, a number of state-of-the-art data analysis tools have been developed to provide a comprehensive analysis of data collected from gas chromatography-mass spectrometry (GC-MS). Unfortunately, the time shift problem remains unsolved in these tools. Here, we developed a novel comprehensive data analysis strategy for GC-MS-based untargeted metabolomics (AntDAS-GCMS) to perform total ion chromatogram peak detection, peak resolution, time shift correction, component registration, statistical analysis, and compound identification. Time shift correction was specifically optimized in this work. The information on mass spectra and elution profiles of compounds was used to search for inherent landmarks within analyzed samples to resolve the time shift problem across samples efficiently and accurately. The performance of our AntDAS-GCMS was comprehensively investigated by using four complex GC-MS data sets with various types of time shift problems. Meanwhile, AntDAS-GCMS was compared with advanced GC-MS data analysis tools and classic time shift correction methods. Results indicated that AntDAS-GCMS could achieve the best performance compared to the other methods.

Single-cell analysis of Crohn's disease: Unveiling heterogeneity and evaluating ustekinumab outcomes.

BACKGROUND: The present study aimed to dissect the cellular complexity of Crohn's disease (CD) using single-cell RNA sequencing, focusing on identifying key cell populations and their transcriptional profiles in inflamed tissue. METHODS: We applied scRNA-sequencing to compare the cellular composition of CD patients with healthy controls, utilizing Seurat for clustering and annotation. Differential gene expression analysis and protein-protein interaction networks were constructed to identify crucial genes and pathways. RESULTS: Our study identified eight distinct cell types in CD, highlighting crucial fibroblast and T cell interactions. The analysis revealed key cellular communications and identified significant genes and pathways involved in the disease's pathology. The role of fibroblasts was underscored by elevated expression in diseased samples, offering insights into disease mechanisms and potential therapeutic targets, including responses to ustekinumab treatment, thus enriching our understanding of CD at a molecular level. CONCLUSIONS: Our findings highlight the complex cellular and molecular interplay in CD, suggesting new biomarkers and therapeutic targets, offering insights into disease mechanisms and treatment implications.

Correlation of distribution characteristics and dynamic changes of gut microbiota with the efficacy of immunotherapy in EGFR-mutated non-small cell lung cancer.

BACKGROUND: The effects of gut microbiota and metabolites on the responses to immune checkpoint inhibitors (ICIs) in advanced epidermal growth factor receptor (EGFR) wild-type non-small cell lung cancer (NSCLC) have been studied. However, their effects on EGFR-mutated (EGFR +) NSCLC remain unknown. METHODS: We prospectively recorded the clinicopathological characteristics of patients with advanced EGFR + NSCLC and assessed potential associations between the use of antibiotics or probiotics and immunotherapy efficacy. Fecal samples were collected at baseline, early on-treatment, response and progression status and were subjected to metagenomic next-generation sequencing and ultra-high-performance liquid chromatography-mass spectrometry analyses to assess the effects of gut microbiota and metabolites on immunotherapy efficacy. RESULTS: The clinical data of 74 advanced EGFR + NSCLC patients were complete and 18 patients' fecal samples were dynamically collected. Patients that used antibiotics had shorter progression-free survival (PFS) (mPFS, 4.8 vs. 6.7 months; P = 0.037); probiotics had no impact on PFS. Two dynamic types of gut microbiota during immunotherapy were identified: one type showed the lowest relative abundance at the response time point, whereas the other type showed the highest abundance at the response time point. Metabolomics revealed significant differences in metabolites distribution between responders and non-responders. Deoxycholic acid, glycerol, and quinolinic acid were enriched in responders, whereas L-citrulline was enriched in non-responders. There was a significant correlation between gut microbiota and metabolites. CONCLUSIONS: The use of antibiotics weakens immunotherapy efficacy in patients with advanced EGFR + NSCLC. The distribution characteristics and dynamic changes of gut microbiota and metabolites may indicate the efficacy of immunotherapy in advanced EGFR + NSCLC.