Short-chain fatty acids reprogram metabolic profiles with the induction of reactive oxygen species production in human colorectal adenocarcinoma cells.

Short-chain fatty acids (SCFAs) exhibit anticancer activity in cellular and animal models of colon cancer. Acetate, propionate, and butyrate are the three major SCFAs produced from dietary fiber by gut microbiota fermentation and have beneficial effects on human health. Most previous studies on the antitumor mechanisms of SCFAs have focused on specific metabolites or genes involved in antitumor pathways, such as reactive oxygen species (ROS) biosynthesis. In this study, we performed a systematic and unbiased analysis of the effects of acetate, propionate, and butyrate on ROS levels and metabolic and transcriptomic signatures at physiological concentrations in human colorectal adenocarcinoma cells. We observed significantly elevated levels of ROS in the treated cells. Furthermore, significantly regulated signatures were involved in overlapping pathways at metabolic and transcriptomic levels, including ROS response and metabolism, fatty acid transport and metabolism, glucose response and metabolism, mitochondrial transport and respiratory chain complex, one-carbon metabolism, amino acid transport and metabolism, and glutaminolysis, which are directly or indirectly linked to ROS production. Additionally, metabolic and transcriptomic regulation occurred in a SCFAs types-dependent manner, with an increasing degree from acetate to propionate and then to butyrate. This study provides a comprehensive analysis of how SCFAs induce ROS production and modulate metabolic and transcriptomic levels in colon cancer cells, which is vital for understanding the mechanisms of the effects of SCFAs on antitumor activity in colon cancer.

Transcriptomic landscapes of effective and failed liver regeneration in humans.

Background & Aims: Although extensive experimental evidence on the process of liver regeneration exists, in humans, validation is largely missing. However, liver regeneration is critically affected by underlying liver disease. Within this project, we aimed to systematically assess early transcriptional changes during liver regeneration in humans and further assess how these processes differ in people with dysfunctional liver regeneration. Methods: Blood samples of 154 patients and intraoperative tissue samples of 46 patients undergoing liver resection were collected and classified with regard to dysfunctional postoperative liver regeneration. Of those, a matched cohort of 21 patients were used for RNA sequencing. Samples were assessed for circulating cytokines, gene expression dynamics, intrahepatic neutrophil accumulation, and spatial transcriptomics. Results: Individuals with dysfunctional liver regeneration demonstrated an aggravated transcriptional inflammatory response with higher intracellular adhesion molecule-1 induction. Increased induction of this critical leukocyte adhesion molecule was associated with increased intrahepatic neutrophil accumulation and activation upon induction of liver regeneration in individuals with dysfunctional liver regeneration. Comparing baseline gene expression profiles in individuals with and without dysfunctional liver regeneration, we found that dual-specificity phosphatase 4 (DUSP4) expression, a known critical regulator of intracellular adhesion molecule-1 expression in endothelial cells, was markedly reduced in patients with dysfunctional liver regeneration. Mimicking clinical risk factors for dysfunctional liver regeneration, we found liver sinusoidal endothelial cells of two liver disease models to have significantly reduced baseline levels of DUSP4. Conclusions: Exploring the landscape of early transcriptional changes of human liver regeneration, we observed that people with dysfunctional regeneration experience overwhelming intrahepatic inflammation. Subclinical liver disease might account for DUSP4 reduction in liver sinusoidal endothelial cells, which ultimately primes the liver for an aggravated inflammatory response. Impact and implications: Using a unique human biorepository, focused on liver regeneration (LR), we explored the landscape of circulating and tissue-level alterations associated with both functional and dysfunctional LR. In contrast to experimental animal models, people with dysfunctional LR demonstrated an aggravated transcriptional inflammatory response, higher intracellular adhesion molecule-1 (ICAM-1) induction, intrahepatic neutrophil accumulation and activation upon induction of LR. Although inflammatory responses appear rapidly after liver resection, people with dysfunctional LR have exaggerated inflammatory responses that appear to be related to decreased levels of LSEC DUSP4, challenging existing concepts of post-resectional LR.

Radiogenomics study to predict the nuclear grade of renal clear cell carcinoma.

Purpose: To develop models based on radiomics and genomics for predicting the histopathologic nuclear grade with localized clear cell renal cell carcinoma (ccRCC) and to assess whether macro-radiomics models can predict the microscopic pathological changes. Method: In this multi-institutional retrospective study, a computerized tomography (CT) radiomic model for nuclear grade prediction was developed. Utilizing a genomics analysis cohort, nuclear grade-associated gene modules were identified, and a gene model was constructed based on top 30 hub mRNA to predict the nuclear grade. Using a radiogenomic development cohort, biological pathways were enriched by hub genes and a radiogenomic map was created. Results: The four-features-based SVM model predicted nuclear grade with an area under the curve (AUC) score of 0.94 in validation sets, while a five-gene-based model predicted nuclear grade with an AUC of 0.73 in the genomics analysis cohort. A total of five gene modules were identified to be associated with the nuclear grade. Radiomic features were only associated with 271 out of 603 genes in five gene modules and eight top 30 hub genes. Differences existed in the enrichment pathway between associated and un-associated with radiomic features, which were associated with two genes of five-gene signatures in the mRNA model. Conclusion: The CT radiomics models exhibited higher predictive performance than mRNA models. The association between radiomic features and mRNA related to nuclear grade is not universal.

MAPKAPK2-centric transcriptome profiling reveals its major role in governing molecular crosstalk of IGFBP2, MUC4, and PRKAR2B during HNSCC pathogenesis.

Transcriptome analysis of head and neck squamous cell carcinoma (HNSCC) has been pivotal to comprehending the convoluted biology of HNSCC tumors. MAPKAPK2 or MK2 is a critical modulator of the mRNA turnover of crucial genes involved in HNSCC progression. However, MK2-centric transcriptome profiles of tumors are not well known. This study delves into HNSCC progression with MK2 at the nexus to delineate the biological relevance and intricate crosstalk of MK2 in the tumor milieu. We performed next-generation sequencing-based transcriptome profiling of HNSCC cells and xenograft tumors to ascertain mRNA expression profiles in MK2-wild type and MK2-knockdown conditions. The findings were validated using gene expression assays, immunohistochemistry, and transcript turnover studies. Here, we identified a pool of crucial MK2-regulated candidate genes by annotation and differential gene expression analyses. Regulatory network and pathway enrichment revealed their significance and involvement in the HNSCC pathogenesis. Additionally, 3'-UTR-based filtering recognized important MK2-regulated downstream target genes and validated them by nCounter gene expression assays. Finally, immunohistochemistry and transcript stability studies revealed the putative role of MK2 in regulating the transcript turnover of IGFBP2, MUC4, and PRKAR2B in HNSCC. Conclusively, MK2-regulated candidate genes were identified in this study, and their plausible involvement in HNSCC pathogenesis was elucidated. These genes possess investigative values as targets for diagnosis and therapeutic interventions for HNSCC.

Impact of broad-spectrum antibiotics on the gut-microbiota-spleen-brain axis.

The spleen is a key immune-related organ that plays a role in communication between the brain and the immune system through the brain-spleen axis and brain-gut-microbiota axis. However, how the gut microbiota affects spleen and brain function remains unclear. Here, we investigated whether microbiome depletion induced by administration of an antibiotic cocktail (ABX) affects spleen and brain function. Treatment with ABX for 14 days resulted in a significant decrease in spleen weight and significant alterations in splenic functions, including the percentage of neutrophils, NK cells, macrophages, and CD8+ T cells. Furthermore, ABX treatment resulted in the depletion of a large portion of the gut microbiota. Untargeted metabolomics analysis showed that ABX treatment caused alterations in the levels of certain compounds in the plasma, spleen, and brain. Moreover, ABX treatment decreased the expression of microglia marker Iba1 in the cerebral cortex. Interestingly, correlations were found between the abundance of different microbiome components and metabolites in various tissues, as well as splenic cell populations and spleen weight. These findings suggest that ABX-induced microbiome depletion and altered metabolite levels may affect spleen and brain function through the gut-microbiota-spleen-brain axis.

Pharmacometabolomic study of drug response to antihypertensive medications for hypertension marker identification in Han Chinese individuals in Taiwan.

Various groups of antihypertensive drugs targeting different pathways have been developed; however, the pharmacometabolic responses to these drugs have rarely been compared to elucidate the common pathway of blood pressure regulation. Here, we performed a comparative multi-dimensional pharmacometabolic study on the four major lines of antihypertensive drugs, namely angiotensin-converting enzyme inhibitors (ACEis), angiotensin receptor blockers (ARBs), calcium channel blockers (CCBs), and diuretics (DIURs), through ultra-performance liquid chromatography coupled to quantum time-of-flight mass spectrometry. Two hundred fifty patients with young-onset hypertension, who were equally divided among five study groups: non-medicated, ACEi, ARB, CCB, and DIUR groups, were recruited. In a metabolome-wide association study conducted through analysis of covariance, 37 molecular features significantly associated with pharmacometabolic responses to antihypertensive drugs were identified. One-third of these features were shared by multiple medications. ACEis, ARBs, and DIURs shared more features than CCB, partially reflecting that ACEis, ARBs, and DIURs affect the renin-angiotensin-aldosterone system. Thirteen molecular features were consistently identified by all four models of the analysis of covariance. A tandem mass spectrometry (or MS/MS) experiment was performed to decipher the chemical structure of these 13 molecular features, including ARB-associated lysophosphatidylcholine (P4135), CCB-associated diacylglycerol(15:0/18:2) (P1175), and DIUR-associated oleamide (P1516). In addition, diacylglycerol(15:0/14:2) (P408) was significantly associated with the pharmacometabolic response to all four antihypertensive drugs. The identified metabolites provide insights into the mechanisms of blood pressure regulation and potential predictive markers of pharmacometabolic responses to antihypertensive drugs.

Proteomics reveals the potential mechanism of Tanshinone IIA in promoting the Ex Vivo expansion of human bone marrow mesenchymal stem cells.

Introduction: Bone marrow mesenchymal stem cells (BMSCs) are a promising cell type for tissue engineering, however, the application of BMSCs is largely hampered by the limited number harvested from bone marrow cells. The methods or strategies that focused on promoting the capacity of BMSCs expansion ex vivo become more and more important. Tanshinone IIA (Tan IIA), the main active components of Danshen, has been found to promote BMSCs proliferation, but the underlying mechanism is still unclear. The aim of this study is to explore the effect and underlying mechanism of Tan IIA on the expansion capacity of hBMSCs ex vivo. Methods: In this present study, the effect of Tan IIA on the expansion capacity of BMSCs from human was investigated, and quantitative proteome analysis was applied furtherly to identify the differentially expressed proteins (DEPs) and the molecular signaling pathways in Tan IIA-treated hBMSCs. Finally, molecular biology skills were employed to verify the proposed mechanism of Tan IIA in promoting hBMSCs expansion. Results: The results showed that a total of 84 DEPs were identified, of which 51 proteins were upregulated and 33 proteins were downregulated. Besides, Tan IIA could promote hBMSCs proliferation by regulating the progression of S phase via increasing the release of fibroblast growth factor 2 (FGF2), FGF-mediated PI3K/AKT signaling pathways may play an important role in Tan IIA's effect on hBMSCs expansion. Conclusions: This study employed molecular biology skills combined with quantitative proteome analysis, to some extent, clarified the mechanism of Tan IIA's effect on promoting hBMSCs proliferation, and will give a hint that Tan IIA may have the potential to be used for BMSCs applications in cell therapies in the future.

Nonlinear EEG signatures of mind wandering during breath focus meditation.

In meditation practices that involve focused attention to a specific object, novice practitioners often experience moments of distraction (i.e., mind wandering). Previous studies have investigated the neural correlates of mind wandering during meditation practice through Electroencephalography (EEG) using linear metrics (e.g., oscillatory power). However, their results are not fully consistent. Since the brain is known to be a chaotic/nonlinear system, it is possible that linear metrics cannot fully capture complex dynamics present in the EEG signal. In this study, we assess whether nonlinear EEG signatures can be used to characterize mind wandering during breath focus meditation in novice practitioners. For that purpose, we adopted an experience sampling paradigm in which 25 participants were iteratively interrupted during meditation practice to report whether they were focusing on the breath or thinking about something else. We compared the complexity of EEG signals during mind wandering and breath focus states using three different algorithms: Higuchi's fractal dimension (HFD), Lempel-Ziv complexity (LZC), and Sample entropy (SampEn). Our results showed that EEG complexity was generally reduced during mind wandering relative to breath focus states. We conclude that EEG complexity metrics are appropriate to disentangle mind wandering from breath focus states in novice meditation practitioners, and therefore, they could be used in future EEG neurofeedback protocols to facilitate meditation practice.

Case study: Targeted RNA-sequencing of aged formalin-fixed paraffin-embedded samples for understanding chemical mode of action.

Formalin-fixed paraffin-embedded (FFPE) samples are the only remaining biological archive for many toxicological and clinical studies, yet their use in genomics has been limited due to nucleic acid damage from formalin fixation. Older FFPE samples with highly degraded RNA pose a particularly difficult technical challenge. Probe-based targeted sequencing technologies show promise in addressing this issue but have not been directly compared to standard whole-genome RNA-Sequencing (RNA-Seq) methods. In this study, we evaluated dose-dependent transcriptional changes from paired frozen (FROZ) and FFPE liver samples stored for over 20 years using targeted resequencing (TempO-Seq) and whole-genome RNA-Seq methods. Samples were originally collected from male mice exposed to a reference chemical (dichloroacetic acid, DCA) at 0, 198, 313, and 427 mg/kg-day (n = 6/dose) by drinking water for 6 days. TempO-Seq showed high overlap in differentially expressed genes (DEGs) between matched FFPE and FROZ samples and high concordance in fold-change values across the two highest dose levels of DCA vs. control (R2 ≥ 0.94). Similarly, high concordance in fold-change values was observed between TempO-Seq FFPE and RNA-Seq FROZ results (R2 ≥ 0.92). In contrast, RNA-Seq FFPE samples showed few overlapping DEGs compared to FROZ RNA-Seq (≤5 for all dose groups). Modeling of DCA-dependent changes in gene sets identified benchmark doses from TempO-Seq FROZ and FFPE samples within 1.4-fold of RNA-Seq FROZ samples (93.9 mg/kg-d), whereas RNA-Seq FFPE samples were 3.3-fold higher (310.3 mg/kg-d). This work demonstrates that targeted sequencing may provide a more robust method for quantifying gene expression profiles from aged archival FFPE samples.

Integrated gut microbiome and metabolome analyses identified fecal biomarkers for bowel movement regulation by Bifidobacterium longum BB536 supplementation: A RCT.

Background: Bifidobacterium longum BB536 supplementation can be used to regulate bowel movements in various people, including healthy subjects and patients with irritable bowel syndrome (IBS); however, individuals vary in their responses to B. longum BB536 treatment. One putative factor is the gut microbiota; recent studies have reported that the gut microbiota mediates the effects of diet or drugs on the host. Here, we investigated intestinal features, such as the microbiome and metabolome, related to B. longum BB536 effectiveness in increasing bowel movement frequency. Results: A randomized, double-blind controlled crossover trial was conducted with 24 adults who mainly tended to be constipated. The subjects received a two-week dietary intervention consisting of B. longum BB536 in acid-resistant seamless capsules or similarly encapsulated starch powder as the placebo control. Bowel movement frequency was recorded daily, and fecal samples were collected at several time points, and analyzed by metabologenomic approach that consists of an integrated analysis of metabolome data obtained using mass spectrometry and microbiome data obtained using high-throughput sequencing. There were differences among subjects in B. longum intake-induced bowel movement frequency. The responders were predicted by machine learning based on the microbiome and metabolome features of the fecal samples collected before B. longum intake. The abundances of eight bacterial genera were significantly different between responders and nonresponders. Conclusions: Intestinal microbiome and metabolome profiles might be utilized as potential markers of improved bowel movement after B. longum BB536 supplementation. These findings have implications for the development of personalized probiotic treatments.

nudt7 gene depletion causes transcriptomic change in early development of zebrafish.

The Nudt family has been identified as enzymes performing Coenzyme A to 3'5'-ADP + 4'-phospho pantetheine catalysis. The members of this family have been shown to be particularly involved in lipid metabolism, while their involvement in gene regulation through regulating transcription or mRNA metabolism has also been suggested. Here, we focused on peroxisomal NUDT7, possessing enzymatic activity similar to that of its paralog, peroxisomal NUDT19, which is involved in mRNA degradation. No reports have been published about the Nudt family in zebrafish. Our transcriptomic data showed that the Nudt family members are highly expressed around zygotic gene activation (ZGA) in developing zebrafish embryos. Therefore, we confirmed the computational prediction that the products of the nudt7 gene in zebrafish were localized in the peroxisome and highly expressed in early embryogenesis. The depletion of nudt7 genes by the CRISPR/Cas9 system did not affect development; however, it decreased the rate of transcription in ZGA. In addition, H3K27ac ChIP-seq analysis demonstrated that this decrease in transcription was correlated with the genome-wide decrease of H3K27ac level. This study suggests that peroxisomal Nudt7 functions in regulating transcription in ZGA via formation of the H3K27ac domain in active chromatin.

Association of Inner Retinal Thickness with Prevalent Dementia and Brain Atrophy in a General Older Population: The Hisayama Study.

Purpose: To assess the association of inner retinal thickness with prevalent dementia and regional brain atrophy in a general older population of Japanese. Design: Population-based, cross-sectional study. Participants: A total of 1078 residents aged 65 years or older who participated in an eye examination, a comprehensive survey of dementia, and brain magnetic resonance imaging scanning in 2017. Methods: The thicknesses of the inner retinal layers, namely, the ganglion cell-inner plexiform layer (GC-IPL) and retinal nerve fiber layer (RNFL)-were measured by swept-source OCT (SS-OCT). The association of these retinal thicknesses with the risk of the presence of dementia was estimated using restricted cubic splines and logistic regression models. Regional brain volumes were estimated separately by applying 2 different methods: voxel-based morphometry (VBM) and analysis by FreeSurfer software. The associations of GC-IPL and RNFL thickness with each brain regional volume were analyzed using multiple regression analysis. Main Outcome Measure: Prevalent dementia and regional brain atrophy. Results: Among the study participants, 61 participants (5.7%) were diagnosed with dementia. The likelihood of the presence of dementia significantly increased with lower GC-IPL thickness after adjusting for potential confounders (odds ratio, 1.62 [95% confidence interval, 1.30-2.01] per 1 standard deviation decrement in the GC-IPL thickness), but no significant association was observed with RNFL thickness. In the VBM analyses with the multivariable adjustment, lower GC-IPL thickness was significantly associated with lower volume of known brain regions related to cognitive functions (i.e., the hippocampus, amygdala, entorhinal area, and parahippocampal gyrus) and visual functions (i.e., the cuneus, lingual gyrus, and thalamus). Meanwhile, the volume of the thalamus significantly decreased with lower RNFL thickness, but none of the brain regions related to cognitive function exhibited a volume change in association with RNFL thickness. The sensitivity analysis using FreeSurfer analysis also showed that lower GC-IPL thickness was significantly associated with lower regional brain volume/intracranial volume of the hippocampus, amygdala, cuneus, lingual gyrus, and thalamus. Conclusions: Our findings suggest that the measurement of GC-IPL thickness by SS-OCT, which is a noninvasive, convenient, and reproducible method, might be useful for identifying high-risk individuals with dementia.

Monocytosis in the acute phase of SARS-CoV-2 infection predicts the presence of anosognosia for cognitive deficits in the chronic phase.

Reduced awareness of neuropsychological disorders (i.e., anosognosia) is a striking symptom of post-COVID-19 condition. Some leukocyte markers in the acute phase may predict the presence of anosognosia in the chronic phase, but they have not yet been identified. This study aimed to determine whether patients with anosognosia for their memory deficits in the chronic phase presented specific leukocyte distribution in the acute phase, and if so, whether these leukocyte levels might be predictive of anosognosia. First, we compared the acute immunological data (i.e., white blood cell differentiation count) of 20 patients who displayed anosognosia 6-9 months after being infected with SARS-CoV-2 (230.25 ± 46.65 days) versus 41 patients infected with SARS-Cov-2 who did not develop anosognosia. Second, we performed an ROC analysis to evaluate the predictive value of the leukocyte markers that emerged from this comparison. Blood circulating monocytes (%) in the acute phase of SARS-CoV-2 infection were associated with long-term post-COVID-19 anosognosia. A monocyte percentage of 7.35% of the total number of leukocytes at admission seemed to predict the presence of chronic anosognosia 6-9 months after infection.

DenovoProfiling: A webserver for de novo generated molecule library profiling.

Various deep learning-based architectures for molecular generation have been proposed for de novo drug design. The flourish of the de novo molecular generation methods and applications has created a great demand for the visualization and functional profiling for the de novo generated molecules. An increasing number of publicly available chemogenomic databases sets good foundations and creates good opportunities for comprehensive profiling of the de novo library. In this paper, we present DenovoProfiling, a webserver dedicated to de novo library visualization and functional profiling. Currently, DenovoProfiling contains six modules: (1) identification & visualization module for chemical structure visualization and identify the reported structures, (2) chemical space module for chemical space exploration using similarity maps, principal components analysis (PCA), drug-like properties distribution, and scaffold-based clustering, (3) ADMET prediction module for predicting the ADMET properties of the de novo molecules, (4) molecular alignment module for three dimensional molecular shape analysis, (5) drugs mapping module for identifying structural similar drugs, and (6) target & pathway module for identifying the reported targets and corresponding functional pathways. DenovoProfiling could provide structural identification, chemical space exploration, drug mapping, and target & pathway information. The comprehensive annotated information could give users a clear picture of their de novo library and could guide the further selection of candidates for chemical synthesis and biological confirmation. DenovoProfiling is freely available at http://denovoprofiling.xielab.net.

FunOMIC: Pipeline with built-in fungal taxonomic and functional databases for human mycobiome profiling.

While analysis of the bacterial microbiome has become routine, that of the fungal microbiome is still hampered by the lack of robust databases and bioinformatic pipelines. Here, we present FunOMIC, a pipeline with built-in taxonomic (1.6 million marker genes) and functional (3.4 million non-redundant fungal proteins) databases for the identification of fungi. Applied to more than 2,600 human metagenomic samples, the tool revealed fungal species associated with geography, body sites, and diseases. Correlation network analysis provided new insights into inter-kingdom interactions. With this pipeline and two of the most comprehensive fungal databases, we foresee a fast-growing resource for mycobiome studies.

Comprehensive analysis of gene expression profiles to identify differential prognostic factors of primary and metastatic breast cancer.

Breast cancer accounts for nearly half of all cancer-related deaths in women worldwide. However, the molecular mechanisms that lead to tumour development and progression remain poorly understood and there is a need to identify candidate genes associated with primary and metastatic breast cancer progression and prognosis. In this study, candidate genes associated with prognosis of primary and metastatic breast cancer were explored through a novel bioinformatics approach. Primary and metastatic breast cancer tissues and adjacent normal breast tissues were evaluated to identify biomarkers characteristic of primary and metastatic breast cancer. The Cancer Genome Atlas-breast invasive carcinoma (TCGA-BRCA) dataset (ID: HS-01619) was downloaded using the mRNASeq platform. Genevestigator 8.3.2 was used to analyse TCGA-BRCA gene expression profiles between the sample groups and identify the differentially-expressed genes (DEGs) in each group. For each group, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were used to determine the function of DEGs. Networks of protein-protein interactions were constructed to identify the top hub genes with the highest degree of interaction. Additionally, the top hub genes were validated based on overall survival and immunohistochemistry using The Human Protein Atlas. Of the top 20 hub genes identified, four (KRT14, KIT, RAD51, and TTK) were considered as prognostic risk factors based on overall survival. KRT14 and KIT expression levels were upregulated while those of RAD51 and TTK were downregulated in patients with breast cancer. The four proposed candidate hub genes might aid in further understanding the molecular changes that distinguish primary breast tumours from metastatic tumours as well as help in developing novel therapeutics. Furthermore, they may serve as effective prognostic risk markers based on the strong correlation between their expression and patient overall survival.

Exploring the zinc-related transcriptional landscape in Alzheimer's disease.

Alzheimer's disease (AD) is a progressive neurological disorder, and increasing evidence suggests AD pathology is driven by metabolic dysfunction in the brain. Zinc is the second most abundant trace element found in the human body and is required by all living organisms. Zinc is used extensively in many biological processes, and alterations in zinc levels are implicated in the pathogenesis of numerous diseases, including AD. Since small fluctuations in brain zinc levels appear to effect AD progression, we investigated the zinc-related transcriptional responses in an AD versus non-AD state using microarray and RNA-sequencing (RNA-seq) datasets from cultured cells, mice, and humans. We identified 582 zinc-related differentially expressed genes (DEG) in human dorsolateral prefrontal cortex samples of late-onset AD (LOAD) versus non-AD controls, 146 zinc-related DEG in 5XFAD versus wild-type mice, and 95 zinc-related DEG in lipopolysaccharide (LPS)-stimulated N9 microglia versus unstimulated control cells, with 19 zinc-related DEG common to all three datasets. Of the 19 common DEG, functional enrichment and network analyses identified several biological processes and molecular functions, such as mRNA destabilization and nucleic acid binding, which may be important in neuroinflammation and AD development. Furthermore, therapeutic drugs targeting zinc-related DEG in the human dataset were identified. Taken together, these data provide insights into zinc utilization for gene transcription during AD progression which may further our understanding of AD pathogenesis and could identify new targets for therapeutic strategies targeted towards AD.

Master Transcription Regulators and Transcription Factors Regulate Immune-Associated Differences Between Patients of African and European Ancestry With Colorectal Cancer.

Background and Aims: Individuals of African (AFR) ancestry have a higher incidence of colorectal cancer (CRC) than those of European (EUR) ancestry and exhibit significant health disparities. Previous studies have noted differences in the tumor microenvironment between AFR and EUR patients with CRC. However, the molecular regulatory processes that underpin these immune differences remain largely unknown. Methods: Multiomics analysis was carried out for 55 AFR and 456 EUR patients with microsatellite-stable CRC using The Cancer Genome Atlas. We evaluated the tumor microenvironment by using gene expression and methylation data, transcription factor, and master transcriptional regulator analysis to identify the cell signaling pathways mediating the observed phenotypic differences. Results: We demonstrate that downregulated genes in AFR patients with CRC showed enrichment for canonical pathways, including chemokine signaling. Moreover, evaluation of the tumor microenvironment showed that cytotoxic lymphocytes and neutrophil cell populations are significantly decreased in AFR compared with EUR patients, suggesting AFR patients have an attenuated immune response. We further demonstrate that molecules called "master transcriptional regulators" (MTRs) play a critical role in regulating the expression of genes impacting key immune processes through an intricate signal transduction network mediated by disease-associated transcription factors (TFs). Furthermore, a core set of these MTRs and TFs showed a positive correlation with levels of cytotoxic lymphocytes and neutrophils across both AFR and EUR patients with CRC, thus suggesting their role in driving the immune infiltrate differences between the two ancestral groups. Conclusion: Our study provides an insight into the intricate regulatory landscape of MTRs and TFs that orchestrate the differences in the tumor microenvironment between patients with CRC of AFR and EUR ancestry.

Detecting differentially expressed circular RNAs from multiple quantification methods using a generalized linear mixed model.

Finding differentially expressed circular RNAs (circRNAs) is instrumental to understanding the molecular basis of phenotypic variation between conditions linked to circRNA-involving mechanisms. To date, several methods have been developed to identify circRNAs, and combining multiple tools is becoming an established approach to improve the detection rate and robustness of results in circRNA studies. However, when using a consensus strategy, it is unclear how circRNA expression estimates should be considered and integrated into downstream analysis, such as differential expression assessment. This work presents a novel solution to test circRNA differential expression using quantifications of multiple algorithms simultaneously. Our approach analyzes multiple tools' circRNA abundance count data within a single framework by leveraging generalized linear mixed models (GLMM), which account for the sample correlation structure within and between the quantification tools. We compared the GLMM approach with three widely used differential expression models, showing its higher sensitivity in detecting and efficiently ranking significant differentially expressed circRNAs. Our strategy is the first to consider combined estimates of multiple circRNA quantification methods, and we propose it as a powerful model to improve circRNA differential expression analysis.

Metabolomic studies in the inborn error of metabolism alkaptonuria reveal new biotransformations in tyrosine metabolism.

Alkaptonuria (AKU) is an inherited disorder of tyrosine metabolism caused by lack of active enzyme homogentisate 1,2-dioxygenase (HGD). The primary consequence of HGD deficiency is increased circulating homogentisic acid (HGA), the main agent in the pathology of AKU disease. Here we report the first metabolomic analysis of AKU homozygous Hgd knockout (Hgd -/-) mice to model the wider metabolic effects of Hgd deletion and the implication for AKU in humans. Untargeted metabolic profiling was performed on urine from Hgd -/- AKU (n = 15) and Hgd +/- non-AKU control (n = 14) mice by liquid chromatography high-resolution time-of-flight mass spectrometry (Experiment 1). The metabolites showing alteration in Hgd -/- were further investigated in AKU mice (n = 18) and patients from the UK National AKU Centre (n = 25) at baseline and after treatment with the HGA-lowering agent nitisinone (Experiment 2). A metabolic flux experiment was carried out after administration of 13C-labelled HGA to Hgd -/-(n = 4) and Hgd +/-(n = 4) mice (Experiment 3) to confirm direct association with HGA. Hgd -/- mice showed the expected increase in HGA, together with unexpected alterations in tyrosine, purine and TCA-cycle pathways. Metabolites with the greatest abundance increases in Hgd -/- were HGA and previously unreported sulfate and glucuronide HGA conjugates, these were decreased in mice and patients on nitisinone and shown to be products from HGA by the 13C-labelled HGA tracer. Our findings reveal that increased HGA in AKU undergoes further metabolism by mainly phase II biotransformations. The data advance our understanding of overall tyrosine metabolism, demonstrating how specific metabolic conditions can elucidate hitherto undiscovered pathways in biochemistry and metabolism.