Enriching the gene set analysis of genome-wide data by incorporating directionality of gene expression and combining statistical hypotheses and methods

A cocktail of histidine, carnosine, cysteine and serine reduces adiposity and improves metabolic health and adipose tissue immunometabolic function in ovariectomized rats

Many women have sought alternative therapies to address menopause. Recently, a multi-ingredient supplement (MIS) containing L-histidine, L-carnosine, L-serine, and L-cysteine has been shown to be effective at ameliorating hepatic steatosis (HS) in ovariectomized (OVX) rats, a postmenopausal oestrogen deficiency model. Considering that HS frequently accompanies obesity, which often occurs during menopause, we aimed to investigate the effects of this MIS for 8 weeks in OVX rats. Twenty OVX rats were orally supplemented with either MIS (OVX-MIS) or vehicle (OVX). Ten OVX rats received vehicle orally along with subcutaneous injections of 17β-oestradiol (OVX-E2), whereas 10 rats underwent a sham operation and received oral and injected vehicles (control group). MIS consumption partly counteracted the fat mass accretion observed in OVX animals, leading to decreased total fat mass, adiposity index and retroperitoneal white adipose tissue (RWAT) adipocyte hypertrophy. OVX-MIS rats also displayed increased lean mass and lean/fat ratio, suggesting a healthier body composition, similar to the results reported for OVX-E2 animals. MIS consumption decreased the circulating levels of the proinflammatory marker CRP, the total cholesterol-to-HDL-cholesterol ratio and the leptin-to-adiponectin ratio, a biomarker of diabetes risk and metabolic syndrome. RWAT transcriptomics indicated that MIS favourably regulated genes involved in adipocyte structure and morphology, cell fate determination and differentiation, glucose/insulin homeostasis, inflammation, response to stress and oxidative phosphorylation, which may be mechanisms underlying the beneficial effects described for OVX-MIS rats. Our results pave the way for using this MIS formulation to improve the body composition and immunometabolic health of menopausal women.

Holistic transcriptional responses of Cordyceps militaris to different culture temperatures

Cordyceps militaris is a medicinal entomopathogenic fungus containing valuable biometabolites for pharmaceutical applications. Its genetic inheritance and environmental factors play a crucial role in the production of biomass enriched with cordycepin. While temperature is a crucial controlled parameter for fungal cultivation, its impacts on growth and metabolite biosynthesis remains poorly characterized. This study aimed to investigate the metabolic responses and cordycepin production of C. militaris strain TBRC6039 under various temperature conditions through transcriptome analysis. Among 9599 expressed genes, 576 genes were significantly differentially expressed at culture temperatures of 15 and 25 °C. The changes in the transcriptional responses induced by these temperatures were found in several metabolisms involved in nutrient assimilation and energy source, including amino acids metabolism (e.g., glycine, serine and threonine metabolism) and lipid metabolism (e.g., biosynthesis of unsaturated fatty acids and steroid biosynthesis). At the lower temperature (15 °C), the biosynthetic pathways of lipids, specifically ergosterol and squalene, were the target for maintaining membrane function by transcriptional upregulation. Our study revealed the responsive mechanisms of C. militaris in acclimatization to temperature conditions that provide an insight on physiological manipulation for the production of metabolites by C. militaris.

Multi-omics analysis of aggregative multicellularity

All organisms have to carefully regulate their gene expression, not least during development. mRNA levels are often used as proxy for protein output; however, this approach ignores post-transcriptional effects. In particular, mRNA-protein correlation remains elusive for organisms that exhibit aggregative rather than clonal multicellularity. We addressed this issue by generating a paired transcriptomics and proteomics time series during the transition from uni-to multicellular stage in the social ameba Dictyostelium discoideum. Our data reveals that mRNA and protein levels correlate highly during unicellular growth, but decrease when multicellular development is initiated. This accentuates that transcripts alone cannot accurately predict protein levels. The dataset provides a useful resource to study gene expression during aggregative multicellular development. Additionally, our study provides an example of how to analyze and visualize mRNA and protein levels, which should be broadly applicable to other organisms and conditions.

Signature Search Polestar: a comprehensive drug repurposing method evaluation assistant for customized oncogenic signature

SUMMARY

The burgeoning high-throughput technologies have led to a significant surge in the scale of pharmacotranscriptomic datasets, especially for oncology. Signature search methods (SSMs), utilizing oncogenic signatures formed by differentially expressed genes through sequencing, have been instrumental in anti-cancer drug screening and identifying mechanisms of action without relying on prior knowledge. However, various studies have found that different SSMs exhibit varying performance across pharmacotranscriptomic datasets. In addition, the size of the oncogenic signature can also significantly impact the result of drug repurposing. Therefore, finding the optimal SSMs and customized oncogenic signature for a specific disease remains a challenge. To address this, we introduce Signature Search Polestar (SSP), a webserver integrating the largest pharmacotranscriptomic datasets of anti-cancer drugs from LINCS L1000 with five state-of-the-art SSMs (XSum, CMap, GSEA, ZhangScore, XCos). SSP provides three main modules: Benchmark, Robustness, and Application. Benchmark uses two indices, Area Under the Curve and Enrichment Score, based on drug annotations to evaluate SSMs at different oncogenic signature sizes. Robustness, applicable when drug annotations are insufficient, uses a performance score based on drug self-retrieval for evaluation. Application provides three screening strategies, single method, SS_all, and SS_cross, allowing users to freely utilize optimal SSMs with tailored oncogenic signature for drug repurposing.

AVAILABILITY AND IMPLEMENTATION

SSP is free at https://web.biotcm.net/SSP/. The current version of SSP is archived in https://doi.org/10.6084/m9.figshare.26524741.v1, allowing users to directly use or customize their own SSP webserver.

Unbiased discovery of cancer pathways and therapeutics using Pathway Ensemble Tool and Benchmark

Correctly identifying perturbed biological pathways is a critical step in uncovering basic disease mechanisms and developing much-needed therapeutic strategies. However, whether current tools are optimal for unbiased discovery of relevant pathways remains unclear. Here, we create "Benchmark" to critically evaluate existing tools and find that most function sub-optimally. We thus develop the "Pathway Ensemble Tool" (PET), which outperforms existing methods. Deploying PET, we identify prognostic pathways across 12 cancer types. PET-identified prognostic pathways offer additional insights, with genes within these pathways serving as reliable biomarkers for clinical outcomes. Additionally, normalizing these pathways using drug repurposing strategies represents therapeutic opportunities. For example, the top predicted repurposed drug for bladder cancer, a CDK2/9 inhibitor, represses cell growth in vitro and in vivo. We anticipate that using Benchmark and PET for unbiased pathway discovery will offer additional insights into disease mechanisms across a spectrum of diseases, enabling biomarker discovery and therapeutic strategies.

Assessing the impact of transcriptomics data analysis pipelines on downstream functional enrichment results

Transcriptomics is widely used to assess the state of biological systems. There are many tools for the different steps, such as normalization, differential expression, and enrichment. While numerous studies have examined the impact of method choices on differential expression results, little attention has been paid to their effects on further downstream functional analysis, which typically provides the basis for interpretation and follow-up experiments. To address this, we introduce FLOP, a comprehensive nextflow-based workflow combining methods to perform end-to-end analyses of transcriptomics data. We illustrate FLOP on datasets ranging from end-stage heart failure patients to cancer cell lines. We discovered effects not noticeable at the gene-level, and observed that not filtering the data had the highest impact on the correlation between pipelines in the gene set space. Moreover, we performed three benchmarks to evaluate the 12 pipelines included in FLOP, and confirmed that filtering is essential in scenarios of expected moderate-to-low biological signal. Overall, our results underscore the impact of carefully evaluating the consequences of the choice of preprocessing methods on downstream enrichment analyses. We envision FLOP as a valuable tool to measure the robustness of functional analyses, ultimately leading to more reliable and conclusive biological findings.

Targeted rescue of synaptic plasticity improves cognitive decline in sepsis-associated encephalopathy

Sepsis-associated encephalopathy (SAE) is a frequent complication of severe systemic infection resulting in delirium, premature death, and long-term cognitive impairment. We closely mimicked SAE in a murine peritoneal contamination and infection (PCI) model. We found long-lasting synaptic pathology in the hippocampus including defective long-term synaptic plasticity, reduction of mature neuronal dendritic spines, and severely affected excitatory neurotransmission. Genes related to synaptic signaling, including the gene for activity-regulated cytoskeleton-associated protein (Arc/Arg3.1) and members of the transcription-regulatory EGR gene family, were downregulated. At the protein level, ARC expression and mitogen-activated protein kinase signaling in the brain were affected. For targeted rescue we used adeno-associated virus-mediated overexpression of ARC in the hippocampus in vivo. This recovered defective synaptic plasticity and improved memory dysfunction. Using the enriched environment paradigm as a non-invasive rescue intervention, we found improvement of defective long-term potentiation, memory, and anxiety. The beneficial effects of an enriched environment were accompanied by an increase in brain-derived neurotrophic factor (BDNF) and ARC expression in the hippocampus, suggesting that activation of the BDNF-TrkB pathway leads to restoration of the PCI-induced reduction of ARC. Collectively, our findings identify synaptic pathomechanisms underlying SAE and provide a conceptual approach to target SAE-induced synaptic dysfunction with potential therapeutic applications to patients with SAE.

Differential Reshaping of Skin and Intestinal Microbiota by Stocking Density and Oxygen Availability in Farmed Gilthead Sea Bream (Sparus aurata): A Behavioral and Network-Based Integrative Approach

Fish were kept for six weeks at three different initial stocking densities and water O2 concentrations (low-LD, 8.5 kg/m3 and 95-70% O2 saturation; medium-MD, 17 kg/m3 and 55-75% O2 saturation; high-HD, 25 kg/m3 and 60-45% O2 saturation), with water temperature increasing from 19 °C to 26-27 °C. The improvement in growth performance with the decrease in stocking density was related to changes in skin and intestinal mucosal microbiomes. Changes in microbiome composition were higher in skin, with an increased abundance of Alteromonas and Massilia in HD fish. However, these bacteria genera were mutually exclusive, and Alteromonas abundance was related to a reactive behavior and systemic growth regulation via the liver Gh/Igf system, while Massilia was correlated to a proactive behavior and a growth regulatory transition towards muscle rather than liver. At the intestinal level, microbial abundance showed an opposite trend for two bacteria taxa, rendering in a low abundance of Reyranella and a high abundance of Prauserella in HD fish. This trend was correlated with up-regulated host gene expression, affecting the immune response, epithelial cell turnover, and abiotic stress response. Most of the observed responses are adaptive in nature, and they would serve to infer new welfare indicators for increased stress resilience.

Comparison of transcriptomic profiles between HFPO-DA and prototypical PPARα, PPARγ, and cytotoxic agents in wild-type and PPARα knockout mouse hepatocytes

Recent in vitro transcriptomic analyses for the short-chain polyfluoroalkyl substance, HFPO-DA (ammonium, 2,3,3,3-tetrafluoro-2-(heptafluoropropoxy)-propanoate), support conclusions from in vivo data that HFPO-DA-mediated liver effects in mice are part of the early key events of the peroxisome proliferator-activated receptor alpha (PPARα) activator-induced rodent hepatocarcinogenesis mode of action (MOA). Transcriptomic responses in HFPO-DA-treated rodent hepatocytes have high concordance with those treated with a PPARα agonist and lack concordance with those treated with PPARγ agonists or cytotoxic agents. To elucidate whether HFPO-DA-mediated transcriptomic responses in mouse liver are PPARα-dependent, additional transcriptomic analyses were conducted on samples from primary PPARα knockout (KO) and wild-type (WT) mouse hepatocytes exposed for 12, 24, or 72 h with various concentrations of HFPO-DA, or well-established agonists of PPARα (GW7647) and PPARγ (rosiglitazone), or cytotoxic agents (acetaminophen or d-galactosamine). Pathway and predicted upstream regulator-level responses were highly concordant between HFPO-DA and GW7647 in WT hepatocytes. A similar pattern was observed in PPARα KO hepatocytes, albeit with a distinct temporal and concentration-dependent delay potentially mediated by compensatory responses. This delay was not observed in PPARα KO hepatocytes exposed to rosiglitazone, acetaminophen, d-galactosamine. The similarity in transcriptomic signaling between HFPO-DA and GW7647 in both the presence and absence of PPARα in vitro indicates these compounds share a common MOA.

Comparison of transcriptomic profiles between HFPO-DA and prototypical PPARα, PPARγ, and cytotoxic agents in mouse, rat, and pooled human hepatocytes

Like many per- or polyfluorinated alkyl substances (PFAS), toxicity studies with HFPO-DA (ammonium, 2,3,3,3-tetrafluoro-2-(heptafluoropropoxy)-propanoate), a short-chain PFAS used in the manufacture of some types of fluorinated polymers, indicate that the liver is the primary target of toxicity in rodents following oral exposure. Although the current weight of evidence supports the PPARα mode of action (MOA) for liver effects in HFPO-DA-exposed mice, alternate MOAs have also been hypothesized including PPARγ or cytotoxicity. To further evaluate the MOA for HFPO-DA in rodent liver, transcriptomic analyses were conducted on samples from primary mouse, rat, and pooled human hepatocytes treated for 12, 24, or 72 h with various concentrations of HFPO-DA, or agonists of PPARα (GW7647), PPARγ (rosiglitazone), or cytotoxic agents (ie, acetaminophen or d-galactosamine). Concordance analyses of enriched pathways across chemicals within each species demonstrated the greatest concordance between HFPO-DA and PPARα agonist GW7647-treated hepatocytes compared with the other chemicals evaluated. These findings were supported by benchmark concentration modeling and predicted upstream regulator results. In addition, transcriptomic analyses across species demonstrated a greater transcriptomic response in rodent hepatocytes treated with HFPO-DA or agonists of PPARα or PPARγ, indicating rodent hepatocytes are more sensitive to HFPO-DA or PPARα/γ agonist treatment. These results are consistent with previously published transcriptomic analyses and further support that liver effects in HFPO-DA-exposed rodents are mediated through rodent-specific PPARα signaling mechanisms as part of the MOA for PPARα activator-induced rodent hepatocarcinogenesis. Thus, effects observed in mouse liver are not appropriate endpoints for toxicity value development for HFPO-DA in human health risk assessment.

Integration of Epigenome and Lactylome Reveals the Regulation of Lipid Production in Nannochloropsis oceanica

Lysine lactylation (Kla) is a kind of novel post-translational modification (PTM) that participates in gene expression and various metabolic processes. Nannochloropsis has a remarkable capacity for triacylglycerol (TAG) production under nitrogen stress. To elucidate the involvement of lactylation in lipid synthesis, we conducted chromatin immunoprecipitation sequencing (ChIP-seq) and mRNA-seq analyses to monitor lactylation modifications and transcriptome alterations in Nannochloropsis oceanica. In all, 2057 genes showed considerable variation between nitrogen deprivation (ND) and nitrogen repletion (NR) conditions. Moreover, a total of 5375 differential Kla peaks were identified, including 5331 gain peaks and 44 loss peaks under ND vs NR. The differential Kla peaks were primarily distributed in the promoter (≤1 kb) (71.07%), 5'UTR (22.64%), and exon (4.25%). Integrative analysis of ChIP-seq, transcriptome, and previous proteome and lactylome data elucidates the potential mechanism by which lactylation promotes lipid accumulation under ND. Lactylation facilitates autophagy and protein degradation, leading to the recycling of carbon into the tricarboxylic acid (TCA) cycle, thereby providing carbon precursors for lipid synthesis. Additionally, lactylation induces the redirection of carbon from membrane lipids to TAG by upregulating lipases and enhancing the TCA cycle and β-oxidation pathways. This research offers a new perspective for the investigation of lipid biosynthesis in Nannochloropsis.

Transcriptomic Profiling of Sugarcane White Leaf (SCWL) Canes during Maturation Phase

Sugarcane white leaf (SCWL) disease, caused by Candidatus Phytoplasma sacchari, results in the most damage to sugarcane plantations. Some SCWL canes can grow unnoticed through the maturation phase, subsequently resulting in an overall low sugar yield, or they can be used accidentally as seed canes. In this work, 12-month-old SCWL and asymptomatic canes growing in the same field were investigated. An abundance of phytoplasma in SCWL canes affected growth and sugar content as well as alterations of transcriptomic profiles corresponding to several pathways that responded to the infection. Suppression of photosynthesis, porphyrin and chlorophyll metabolism, coupled with an increase in the expression of chlorophyllase, contributed to the reduction in chlorophyll levels and photosynthesis. Blockage of sucrose transport plausibly occurred due to the expression of sugar transporters in leaves but suppression in stalks, resulting in low sugar content in canes. Increased expression of genes associated with MAPK cascades, plant hormone signaling transduction, callose plug formation, the phenylpropanoid pathway, and calcium cascades positively promoted defense mechanisms against phytoplasma colonization by an accumulation of lignin and calcium in response to plant immunity. Significant downregulation of CPK plausibly results in a reduction in antioxidant enzymes and likely facilitates pathogen invasion, while expression of sesquiterpene biosynthesis possibly attracts the insect vectors for transmission, thereby enabling the spread of phytoplasma. Moreover, downregulation of flavonoid biosynthesis potentially intensifies the symptoms of SCWL upon challenge by phytoplasma. These SCWL sugarcane transcriptomic profiles describe the first comprehensive sugarcane-phytoplasma interaction during the harvesting stage. Understanding molecular mechanisms will allow for sustainable management and the prevention of SCWL disease-a crucial benefit to the sugar industry.

Implications of Ocular Confounding Factors for Aqueous Humor Proteomic and Metabolomic Analyses in Retinal Diseases

Purpose

To assess the impact of ocular confounding factors on aqueous humor (AH) proteomic and metabolomic analyses for retinal disease characterization.

Methods

This study recruited 138 subjects (eyes): 102 with neovascular age-related macular degeneration (nAMD), 18 with diabetic macular edema (DME), and 18 with cataract (control group). AH samples underwent analysis using Olink Target 96 proteomics and Metabolon's metabolomics platform Data analysis included correlation, differential abundance, and gene-set analysis.

Results

In total, 756 proteins and 408 metabolites were quantified in AH. Total AH protein concentration was notably higher in nAMD (3.2-fold) and DME (4.1-fold) compared to controls. Pseudophakic eyes showed higher total AH protein concentrations than phakic eyes (e.g., 1.6-fold in nAMD) and a specific protein signature indicative of matrix remodeling. Unexpectedly, pupil-dilating drugs containing phenylephrine/tropicamide increased several AH proteins, notably interleukin-6 (5.4-fold in nAMD). Correcting for these factors revealed functionally relevant protein correlation clusters and disease-relevant, differentially abundant proteins across the groups. Metabolomics analysis, for which the relevance of confounder adjustment was less apparent, suggested insufficiently controlled diabetes and chronic hyperglycemia in the DME group.

Conclusions

AH protein concentration, pseudophakia, and pupil dilation with phenylephrine/tropicamide are important confounding factors for AH protein analyses. When these factors are considered, AH analyses can more clearly reveal disease-relevant factors.

Translational Relevance

Considering AH protein concentration, lens status, and phenylephrine/tropicamide administration as confounders is crucial for accurate interpretation of AH protein data.

Dual role of GRHL3 in bladder carcinogenesis depending on histological subtypes

The effect of grainyhead-like transcription factor 3 (GRHL3) on cancer development depends on the cancer subtypes as shown in tumor entities such as colorectal or oral squamous cell carcinomas. Here, we analyzed the subtype-specific role of GRHL3 in bladder carcinogenesis, comparing common urothelial carcinoma (UC) with squamous bladder cancer (sq-BLCA). We examined GRHL3 mRNA and protein expression in cohorts of patient samples, its prognostic role and its functional impact on tumorigeneses in different molecular and histopathological subtypes of bladder cancer. We showed for GRHL3 a reverse expression in squamous and urothelial bladder cancer subtypes. Stably GRHL3-overexpressing EJ28, J82, and SCaBER in vitro models revealed a tumor-suppressive function in squamous and an oncogenic role in the urothelial cancer cells affecting cell and colony growth, and migratory and invasive capacities. Transcriptomic profiling demonstrated highly subtype-specific GRHL3-regulated expression networks coined by the enrichment of genes involved in integrin-mediated pathways. In SCaBER, loss of ras homolog family member A (RHOA) GTPase activity was demonstrated to be associated with co-regulation of eukaryotic translation initiation factor 4E family member 3 (EIF4E3), a potential tumor suppressor gene. Thus, our data provide for the first time a detailed insight into the role of the transcription factor GRHL3 in different histopathological subtypes of bladder cancer.

ER stress-induced transcriptional response reveals tolerance genes in yeast

Saccharomyces cerevisiae is important for protein secretion studies, yet the complexities of protein synthesis and secretion under endoplasmic reticulum (ER) stress conditions remain not fully understood. ER stress, triggered by alterations in the ER protein folding environment, poses substantial challenges to cells, especially during heterologous protein production. In this study, we used RNA-seq to analyze the transcriptional responses of yeast strains to ER stress induced by reagents such as tunicamycin (Tm) or dithiothreitol (DTT). Our gene expression analysis revealed several crucial genes, such as HMO1 and BIO5, that are involved in ER-stress tolerance. Through metabolic engineering, the best engineered strain R23 with HMO1 overexpression and BIO5 deletion, showed enhanced ER stress tolerance and improved protein folding efficiency, leading to a 2.14-fold increase in α-amylase production under Tm treatment and a 2.04-fold increase in cell density under DTT treatment. Our findings contribute to the understanding of cellular responses to ER stress and provide a basis for further investigations into the mechanisms of ER stress at the cellular level.

Expression and secretion of galectin-12 in the context of neutrophilic differentiation of human promyeloblastic HL-60 cells

Galectin-12 is a tissue-specific galectin that has been largely defined by its role in the regulation of adipocyte differentiation and lipogenesis. This study aimed to evaluate the role of galectin-12 in the differentiation and polarization of neutrophils within a model of acute myeloid leukemia HL-60 cells. All-trans retinoic acid and dimethyl sulfoxide were used to induce differentiation of HL-60 cells which led to the generation of two phenotypes of neutrophil-like cells with opposite changes in galectin-12 gene (LGALS12) expression and different functional responses to N-formyl- l-methionyl- l-leucyl- l-phenylalanine. These phenotypes showed significant differences of differentially expressed genes on a global scale based on bioinformatics analysis of available Gene Expression Omnibus (GEO) data sets. We also demonstrated that HL-60 cells could secrete and accumulate galectin-12 in cell culture medium under normal growth conditions. This secretion was found to be entirely inhibited upon neutrophilic differentiation and was accompanied by an increase in intracellular lipid droplet content and significant enrichment of 22 lipid gene ontology terms related to lipid metabolism in differentiated cells. These findings suggest that galectin-12 could serve as a marker of neutrophilic plasticity or polarization into different phenotypes and that galectin-12 secretion may be influenced by lipid droplet biogenesis.

Saccharomyces cerevisiae strains performing similarly during fermentation of lignocellulosic hydrolysates show pronounced differences in transcriptional stress responses

Improving our understanding of the transcriptional changes of Saccharomyces cerevisiae during fermentation of lignocellulosic hydrolysates is crucial for the creation of more efficient strains to be used in biorefineries. We performed RNA sequencing of a CEN.PK laboratory strain, two industrial strains (KE6-12 and Ethanol Red), and two wild-type isolates of the LBCM collection when cultivated anaerobically in wheat straw hydrolysate. Many of the differently expressed genes identified among the strains have previously been reported to be important for tolerance to lignocellulosic hydrolysates or inhibitors therein. Our study demonstrates that stress responses typically identified during aerobic conditions such as glutathione metabolism, osmotolerance, and detoxification processes also are important for anaerobic processes. Overall, the transcriptomic responses were largely strain dependent, and we focused our study on similarities and differences in the transcriptomes of the LBCM strains. The expression of sugar transporter-encoding genes was higher in LBCM31 compared with LBCM109 that showed high expression of genes involved in iron metabolism and genes promoting the accumulation of sphingolipids, phospholipids, and ergosterol. These results highlight different evolutionary adaptations enabling S. cerevisiae to strive in lignocellulosic hydrolysates and suggest novel gene targets for improving fermentation performance and robustness.

IMPORTANCE

The need for sustainable alternatives to oil-based production of biochemicals and biofuels is undisputable. Saccharomyces cerevisiae is the most commonly used industrial fermentation workhorse. The fermentation of lignocellulosic hydrolysates, second-generation biomass unsuited for food and feed, is still hampered by lowered productivities as the raw material is inhibitory for the cells. In order to map the genetic responses of different S. cerevisiae strains, we performed RNA sequencing of a CEN.PK laboratory strain, two industrial strains (KE6-12 and Ethanol Red), and two wild-type isolates of the LBCM collection when cultivated anaerobically in wheat straw hydrolysate. While the response to inhibitors of S. cerevisiae has been studied earlier, this has in previous studies been done in aerobic conditions. The transcriptomic analysis highlights different evolutionary adaptations among the different S. cerevisiae strains and suggests novel gene targets for improving fermentation performance and robustness.

Systemic metabolic depletion of gut microbiome undermines responsiveness to melanoma immunotherapy

Immunotherapy has proven to be a boon for patients battling metastatic melanoma, significantly improving their clinical condition and overall quality of life. A compelling link between the composition of the gut microbiome and the efficacy of immunotherapy has been established in both animal models and human patients. However, the precise biological mechanisms by which gut microbes influence treatment outcomes remain poorly understood. Using a robust dataset of 680 fecal metagenomes from melanoma patients, a detailed catalog of metagenome-assembled genomes (MAGs) was constructed to explore the compositional and functional properties of the gut microbiome. Our study uncovered significant findings that deepen the understanding of the intricate relationship between gut microbes and the efficacy of melanoma immunotherapy. In particular, we discovered the specific metagenomic profile of patients with favorable treatment outcomes, characterized by a prevalence of MAGs with increased overall metabolic potential and proficiency in polysaccharide utilization, along with those responsible for cobalamin and amino acid production. Furthermore, our investigation of the biosynthetic pathways of short-chain fatty acids, known for their immunomodulatory role, revealed a differential abundance of these pathways among the specific MAGs. Among others, the cobalamin-dependent Wood-Ljungdahl pathway of acetate synthesis was directly associated with responsiveness to melanoma immunotherapy.

A patient-based iPSC-derived hepatocyte model of alcohol-associated cirrhosis reveals bioenergetic insights into disease pathogenesis

Only ~20% of heavy drinkers develop alcohol cirrhosis (AC). While differences in metabolism, inflammation, signaling, microbiome signatures and genetic variations have been tied to the pathogenesis of AC, the key underlying mechanisms for this interindividual variability, remain to be fully elucidated. Induced pluripotent stem cell-derived hepatocytes (iHLCs) from patients with AC and healthy controls differ transcriptomically, bioenergetically and histologically. They include a greater number of lipid droplets (LDs) and LD-associated mitochondria compared to control cells. These pre-pathologic indicators are effectively reversed by Aramchol, an inhibitor of stearoyl-CoA desaturase. Bioenergetically, AC iHLCs have lower spare capacity, slower ATP production and their mitochondrial fuel flexibility towards fatty acids and glutamate is weakened. MARC1 and PNPLA3, genes implicated by GWAS in alcohol cirrhosis, show to correlate with lipid droplet-associated and mitochondria-mediated oxidative damage in AC iHLCs. Knockdown of PNPLA3 expression exacerbates mitochondrial deficits and leads to lipid droplets alterations. These findings suggest that differences in mitochondrial bioenergetics and lipid droplet formation are intrinsic to AC hepatocytes and can play a role in its pathogenesis.

Unraveling the Etiology of Dilated Cardiomyopathy through Differential miRNA-mRNA Interactome

Dilated cardiomyopathy (DCM) encompasses various acquired or genetic diseases sharing a common phenotype. The understanding of pathogenetic mechanisms and the determination of the functional effects of each etiology may allow for tailoring different therapeutic strategies. MicroRNAs (miRNAs) have emerged as key regulators in cardiovascular diseases, including DCM. However, their specific roles in different DCM etiologies remain elusive. Here, we applied mRNA-seq and miRNA-seq to identify the gene and miRNA signature from myocardial biopsies from four patients with DCM caused by volume overload (VCM) and four with ischemic DCM (ICM). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were used for differentially expressed genes (DEGs). The miRNA-mRNA interactions were identified by Pearson correlation analysis and miRNA target-prediction programs. mRNA-seq and miRNA-seq were validated by qRT-PCR and miRNA-mRNA interactions were validated by luciferase assays. We found 112 mRNAs and five miRNAs dysregulated in VCM vs. ICM. DEGs were positively enriched for pathways related to the extracellular matrix (ECM), mitochondrial respiration, cardiac muscle contraction, and fatty acid metabolism in VCM vs. ICM and negatively enriched for immune-response-related pathways, JAK-STAT, and NF-kappa B signaling. We identified four pairs of negatively correlated miRNA-mRNA: miR-218-5p-DDX6, miR-218-5p-TTC39C, miR-218-5p-SEMA4A, and miR-494-3p-SGMS2. Our study revealed novel miRNA-mRNA interaction networks and signaling pathways for VCM and ICM, providing novel insights into the development of these DCM etiologies.

Dissecting Holistic Metabolic Acclimatization of Mucor circinelloides WJ11 Defective in Carotenoid Biosynthesis

Mucor circinelloides WJ11 is a lipid-producing strain with industrial potential. A holistic approach using gene manipulation and bioprocessing development has improved lipid production and the strain's economic viability. However, the systematic regulation of lipid accumulation and carotenoid biosynthesis in M. circinelloides remains unknown. To dissect the metabolic mechanism underlying lipid and carotenoid biosynthesis, transcriptome analysis and reporter metabolites identification were implemented between the wild-type (WJ11) and ΔcarRP WJ11 strains of M. circinelloides. As a result, transcriptome analysis revealed 10,287 expressed genes, with 657 differentially expressed genes (DEGs) primarily involved in amino acid, carbohydrate, and energy metabolism. Integration with a genome-scale metabolic model (GSMM) identified reporter metabolites in the ΔcarRP WJ11 strain, highlighting metabolic pathways crucial for amino acid, energy, and nitrogen metabolism. Notably, the downregulation of genes associated with carotenoid biosynthesis and acetyl-CoA generation suggests a coordinated relationship between the carotenoid and fatty acid biosynthesis pathways. Despite disruptions in the carotenoid pathway, lipid production remains stagnant due to reduced acetyl-CoA availability, emphasizing the intricate metabolic interplay. These findings provide insights into the coordinated relationship between carotenoid and fatty acid biosynthesis in M. circinelloides that are valuable in applied research to design optimized strains for producing desired bioproducts through emerging technology.

Biosynthesis of Hesperetin, Homoeriodictyol, and Homohesperetin in a Transcriptomics-Driven Engineered Strain of Streptomyces albidoflavus

Flavonoids exhibit various bioactivities including anti-oxidant, anti-tumor, anti-inflammatory, and anti-viral properties. Methylated flavonoids are particularly significant due to their enhanced oral bioavailability, improved intestinal absorption, and greater stability. The heterologous production of plant flavonoids in bacterial factories involves the need for enough biosynthetic precursors to allow for high production levels. These biosynthetic precursors are malonyl-CoA and l-tyrosine. In this work, to enhance flavonoid biosynthesis in Streptomyces albidoflavus, we conducted a transcriptomics study for the identification of candidate genes involved in l-tyrosine catabolism. The hypothesis was that the bacterial metabolic machinery would detect an excess of this amino acid if supplemented with the conventional culture medium and would activate the genes involved in its catabolism towards energy production. Then, by inactivating those overexpressed genes (under an excess of l-tyrosine), it would be possible to increase the intracellular pools of this precursor amino acid and eventually the final flavonoid titers in this bacterial factory. The RNAseq data analysis in the S. albidoflavus wild-type strain highlighted the hppD gene encoding 4-hydroxyphenylpyruvate dioxygenase as a promising target for knock-out, exhibiting a 23.2-fold change (FC) in expression upon l-tyrosine supplementation in comparison to control cultivation conditions. The subsequent knock-out of the hppD gene in S. albidoflavus resulted in a 1.66-fold increase in the naringenin titer, indicating enhanced flavonoid biosynthesis. Leveraging the improved strain of S. albidoflavus, we successfully synthesized the methylated flavanones hesperetin, homoeriodictyol, and homohesperetin, achieving titers of 2.52 mg/L, 1.34 mg/L, and 0.43 mg/L, respectively. In addition, the dimethoxy flavanone homohesperetin was produced as a byproduct of the endogenous metabolism of S. albidoflavus. To our knowledge, this is the first time that hppD deletion was utilized as a strategy to augment the biosynthesis of flavonoids. Furthermore, this is the first report where hesperetin and homoeriodictyol have been synthesized from l-tyrosine as a precursor. Therefore, transcriptomics is, in this case, a successful approach for the identification of catabolism reactions affecting key precursors during flavonoid biosynthesis, allowing the generation of enhanced production strains.

Parechovirus infection in human brain organoids: host innate inflammatory response and not neuro-infectivity correlates to neurologic disease

Picornaviruses are a leading cause of central nervous system (CNS) infections. While genotypes such as parechovirus A3 (PeV-A3) and echovirus 11 (E11) can elicit severe neurological disease, the highly prevalent PeV-A1 is not associated with CNS disease. Here, we expand our current understanding of these differences in PeV-A CNS disease using human brain organoids and clinical isolates of the two PeV-A genotypes. Our data indicate that PeV-A1 and A3 specific differences in neurological disease are not due to infectivity of CNS cells as both viruses productively infect brain organoids with a similar cell tropism. Proteomic analysis shows that PeV-A infection significantly alters the host cell metabolism. The inflammatory response following PeV-A3 (and E11 infection) is significantly more potent than that upon PeV-A1 infection. Collectively, our findings align with clinical observations and suggest a role for neuroinflammation, rather than viral replication, in PeV-A3 (and E11) infection.

Single-cell Transcriptome Analysis Identifies Senescent Osteocytes as Contributors to Bone Destruction in Breast Cancer Metastasis

Breast cancer bone metastases increase fracture risk and are a major cause of morbidity and mortality among women. Upon colonization by tumor cells, the bone microenvironment undergoes profound reprogramming to support cancer progression that disrupts the balance between osteoclasts and osteoblasts, leading to bone lesions. Whether such reprogramming affects matrix-embedded osteocytes remains poorly understood. Here, we demonstrate that osteocytes in breast cancer bone metastasis develop premature senescence and a distinctive senescence-associated secretory phenotype (SASP) that favors bone destruction. Single-cell RNA sequencing identified osteocytes from mice with breast cancer bone metastasis enriched in senescence and SASP markers and pro-osteoclastogenic genes. Using multiplex in situ hybridization and AI-assisted analysis, we detected osteocytes with senescence-associated distension of satellites, telomere dysfunction, and p16Ink4a expression in mice and patients with breast cancer bone metastasis. In vitro and ex vivo organ cultures showed that breast cancer cells promote osteocyte senescence and enhance their osteoclastogenic potential. Clearance of senescent cells with senolytics suppressed bone resorption and preserved bone mass in mice with breast cancer bone metastasis. These results demonstrate that osteocytes undergo pathological reprogramming by breast cancer cells and identify osteocyte senescence as an initiating event triggering bone destruction in breast cancer metastases.

Metabolic re-programming of keratinocytes in response to contact allergens

BACKGROUND

Allergic contact dermatitis (ACD) is a common skin disease caused by the recognition of haptens by the immune system. Keratinocytes play an important role in the initiation and facilitation of inflammatory responses in ACD. Immune responses are associated with major changes in metabolism. However, metabolic re-programming is not well studied in ACD; specifically, knowledge of metabolic alterations in structural cells is lacking.

METHODS

Metabolic re-programming in ACD was studied using publicly available transcriptome datasets. Primary pooled keratinocytes and a keratinocyte cell line (HaCaT) were stimulated with contact allergens, and inflammatory responses and expression of metabolic markers were measured by qPCR and flow cytometry, respectively.

RESULTS

ACD is characterized by metabolic re-programming with a metabolic profile similar to atopic dermatitis. Exposure to contact allergens causes a wide array of metabolic alterations. Stimulation of keratinocytes with contact allergens induced inflammatory responses typical for ACD and was associated with an up-regulation of proteins representative for glucose uptake, fatty acid metabolism, oxidative phosphorylation and to some extent arginine biosynthesis. Changes in these metabolic pathways were also observed when comparing lesional with non-lesional contact dermatitis skin.

CONCLUSIONS

ACD is, similarly to other inflammatory skin diseases, characterized by metabolic re-programming. Contact allergen exposure induces expression of a wide array of metabolic pathways, which is at least in part mediated through metabolic re-programming of keratinocytes.

Integrating single-cell multi-omics and prior biological knowledge for a functional characterization of the immune system

The immune system comprises diverse specialized cell types that cooperate to defend the host against a wide range of pathogenic threats. Recent advancements in single-cell and spatial multi-omics technologies provide rich information about the molecular state of immune cells. Here, we review how the integration of single-cell and spatial multi-omics data with prior knowledge-gathered from decades of detailed biochemical studies-allows us to obtain functional insights, focusing on gene regulatory processes and cell-cell interactions. We present diverse applications in immunology and critically assess underlying assumptions and limitations. Finally, we offer a perspective on the ongoing technological and algorithmic developments that promise to get us closer to a systemic mechanistic understanding of the immune system.

Evaluation of enzyme-constrained genome-scale model through metabolic engineering of anaerobic co-production of 2,3-butanediol and glycerol by Saccharomyces cerevisiae

Enzyme-constrained genome-scale models (ecGEMs) have potential to predict phenotypes in a variety of conditions, such as growth rates or carbon sources. This study investigated if ecGEMs can guide metabolic engineering efforts to swap anaerobic redox-neutral ATP-providing pathways in yeast from alcoholic fermentation to equimolar co-production of 2,3-butanediol and glycerol. With proven pathways and low product toxicity, the ecGEM solution space aligned well with observed phenotypes. Since this catabolic pathway provides only one-third of the ATP of alcoholic fermentation (2/3 versus 2 ATP per glucose), the ecGEM predicted a growth decrease from 0.36 h-1 in the reference to 0.175 h-1 in the engineered strain. However, this <3-fold decrease would require the specific glucose consumption rate to increase. Surprisingly, after the pathway swap the engineered strain immediately grew at 0.15 h-1 with a glucose consumption rate of 29 mmol (g CDW)-1 h-1, which was indeed higher than reference (23 mmol (g CDW)-1 h-1) and one of the highest reported for S. cerevisiae. The accompanying 2,3-butanediol- (15.8 mmol (g CDW)-1 h-1) and glycerol (19.6 mmol (g CDW)-1 h-1) production rates were close to predicted values. Proteomics confirmed that this increased consumption rate was facilitated by enzyme reallocation from especially ribosomes (from 25.5 to 18.5 %) towards glycolysis (from 28.7 to 43.5 %). Subsequently, 200 generations of sequential transfer did not improve growth of the engineered strain, showing the use of ecGEMs in predicting opportunity space for laboratory evolution. The observations in this study illustrate both the current potential, as well as future improvements, of ecGEMs as a tool for both metabolic engineering and laboratory evolution.

Light-Exposed Metabolic Responses of Cordyceps militaris through Transcriptome-Integrated Genome-Scale Modeling

The genome-scale metabolic model (GSMM) of Cordyceps militaris provides a comprehensive basis of carbon assimilation for cell growth and metabolite production. However, the model with a simple mass balance concept shows limited capability to probe the metabolic responses of C. militaris under light exposure. This study, therefore, employed the transcriptome-integrated GSMM approach to extend the investigation of C. militaris's metabolism under light conditions. Through the gene inactivity moderated by metabolism and expression (GIMME) framework, the iPS1474-tiGSMM model was furnished with the transcriptome data, thus providing a simulation that described reasonably well the metabolic responses underlying the phenotypic observation of C. militaris under the particular light conditions. The iPS1474-tiGSMM obviously showed an improved prediction of metabolic fluxes in correlation with the expressed genes involved in the cordycepin and carotenoid biosynthetic pathways under the sucrose culturing conditions. Further analysis of reporter metabolites suggested that the central carbon, purine, and fatty acid metabolisms towards carotenoid biosynthesis were the predominant metabolic processes responsible in light conditions. This finding highlights the key responsive processes enabling the acclimatization of C. militaris metabolism in varying light conditions. This study provides a valuable perspective on manipulating metabolic genes and fluxes towards the target metabolite production of C. militaris.

Shared and Distinct Renal Transcriptome Signatures in 3 Standard Mouse Models of Chronic Kidney Disease

INTRODUCTION

Several mouse models with diverse disease etiologies are used in preclinical research for chronic kidney disease (CKD). Here, we performed a head-to-head comparison of renal transcriptome signatures in standard mouse models of CKD to assess shared and distinct molecular changes in three mouse models commonly employed in preclinical CKD research and drug discovery.

METHODS

All experiments were conducted on male C57BL/6J mice. Mice underwent sham, unilateral ureter obstruction (UUO), or unilateral ischemic-reperfusion injury (uIRI) surgery and were terminated two- and 6-weeks post-surgery, respectively. The adenine-supplemented diet-induced (ADI) model of CKD was established by feeding with adenine diet for 6 weeks and compared to control diet feeding. For all models, endpoints included plasma biochemistry, kidney histology, and RNA sequencing.

RESULTS

All models displayed increased macrophage infiltration (F4/80 IHC) and fibrosis (collagen 1a1 IHC). Compared to corresponding controls, all models were characterized by an extensive number of renal differentially expressed genes (≥11,000), with a notable overlap in transcriptomic signatures across models. Gene expression markers of fibrosis, inflammation, and kidney injury supported histological findings. Interestingly, model-specific transcriptome signatures included several genes representing current drug targets for CKD, emphasizing advantages and limitations of the three CKD models in preclinical target and drug discovery.

CONCLUSION

The UUO, uIRI, and ADI mouse models of CKD have significant commonalities in their renal global transcriptome profile. Model-specific renal transcriptional signatures should be considered when selecting the specific model in preclinical target and drug discovery.

Multiplex single-cell chemical genomics reveals the kinase dependence of the response to targeted therapy

Chemical genetic screens are a powerful tool for exploring how cancer cells' response to drugs is shaped by their mutations, yet they lack a molecular view of the contribution of individual genes to the response to exposure. Here, we present sci-Plex-Gene-by-Environment (sci-Plex-GxE), a platform for combined single-cell genetic and chemical screening at scale. We highlight the advantages of large-scale, unbiased screening by defining the contribution of each of 522 human kinases to the response of glioblastoma to different drugs designed to abrogate signaling from the receptor tyrosine kinase pathway. In total, we probed 14,121 gene-by-environment combinations across 1,052,205 single-cell transcriptomes. We identify an expression signature characteristic of compensatory adaptive signaling regulated in a MEK/MAPK-dependent manner. Further analyses aimed at preventing adaptation revealed promising combination therapies, including dual MEK and CDC7/CDK9 or nuclear factor κB (NF-κB) inhibitors, as potent means of preventing transcriptional adaptation of glioblastoma to targeted therapy.

Identification of a gene network driving the attenuated response to lipopolysaccharide of monocytes from hypertensive coronary artery disease patients

Introduction

The impact of cardiovascular disease (CVD) risk factors, encompassing various biological determinants and unhealthy lifestyles, on the functional dynamics of circulating monocytes-a pivotal cell type in CVD pathophysiology remains elusive. In this study, we aimed to elucidate the influence of CVD risk factors on monocyte transcriptional responses to an infectious stimulus.

Methods

We conducted a comparative analysis of monocyte gene expression profiles from the CTMM - CIRCULATING CELLS Cohort of coronary artery disease (CAD) patients, at baseline and after lipopolysaccharide (LPS) stimulation. Gene co-expression analysis was used to identify gene modules and their correlations with CVD risk factors, while pivotal transcription factors controlling the hub genes in these modules were identified by regulatory network analyses. The identified gene module was subjected to a drug repurposing screen, utilizing the LINCS L1000 database.

Results

Monocyte responsiveness to LPS showed a highly significant, negative correlation with blood pressure levels (ρ< -0.4; P<10-80). We identified a ZNF12/ZBTB43-driven gene module closely linked to diastolic blood pressure, suggesting that monocyte responses to infectious stimuli, such as LPS, are attenuated in CAD patients with elevated diastolic blood pressure. This attenuation appears associated with a dampening of the LPS-induced suppression of oxidative phosphorylation. Finally, we identified the serine-threonine inhibitor MW-STK33-97 as a drug candidate capable of reversing this aberrant LPS response.

Conclusions

Monocyte responses to infectious stimuli may be hampered in CAD patients with high diastolic blood pressure and this attenuated inflammatory response may be reversed by the serine-threonine inhibitor MW-STK33-97. Whether the identified gene module is a mere indicator of, or causal factor in diastolic blood pressure and the associated dampened LPS responses remains to be determined.

Remodeling of the human skeletal muscle proteome found after long-term endurance training but not after strength training

Exercise training has tremendous systemic tissue-specific health benefits, but the molecular adaptations to long-term exercise training are not completely understood. We investigated the skeletal muscle proteome of highly endurance-trained, strength-trained, and untrained individuals and performed exercise- and sex-specific analyses. Of the 6,000+ proteins identified, >650 were differentially expressed in endurance-trained individuals compared with controls. Strikingly, 92% of the shared proteins with higher expression in both the male and female endurance groups were known mitochondrial. In contrast to the findings in endurance-trained individuals, minimal differences were found in strength-trained individuals and between females and males. Lastly, a co-expression network and comparative literature analysis revealed key proteins and pathways related to the health benefits of exercise, which were primarily related to differences in mitochondrial proteins. This network is available as an interactive database resource where investigators can correlate clinical data with global gene and protein expression data for hypothesis generation.

Gene expression signature predicts radiation sensitivity in cell lines using the integral of dose-response curve

BACKGROUND

Although substantial efforts have been made to build molecular biomarkers to predict radiation sensitivity, the ability to accurately stratify the patients is still limited. In this study, we aim to leverage large-scale radiogenomics datasets to build genomic predictors of radiation response using the integral of the radiation dose-response curve.

METHODS

Two radiogenomics datasets consisting of 511 and 60 cancer cell lines were utilized to develop genomic predictors of radiation sensitivity. The intrinsic radiation sensitivity, defined as the integral of the dose-response curve (AUC) was used as the radioresponse variable. The biological determinants driving AUC and SF2 were compared using pathway analysis. To build the predictive model, the largest and smallest datasets consisting of 511 and 60 cancer cell lines were used as the discovery and validation cohorts, respectively, with AUC as the response variable.

RESULTS

Utilizing a compendium of three pathway databases, we illustrated that integral of the radiobiological model provides a more comprehensive characterization of molecular processes underpinning radioresponse compared to SF2. Furthermore, more pathways were found to be unique to AUC than SF2-30, 288 and 38 in KEGG, REACTOME and WIKIPATHWAYS, respectively. Also, the leading-edge genes driving the biological pathways using AUC were unique and different compared to SF2. With regards to radiation sensitivity gene signature, we obtained a concordance index of 0.65 and 0.61 on the discovery and validation cohorts, respectively.

CONCLUSION

We developed an integrated framework that quantifies the impact of physical radiation dose and the biological effect of radiation therapy in interventional pre-clinical model systems. With the availability of more data in the future, the clinical potential of this signature can be assessed, which will eventually provide a framework to integrate genomics into biologically-driven precision radiation oncology.

Data processing solutions to render metabolomics more quantitative: case studies in food and clinical metabolomics using Metabox 2.0

In classic semiquantitative metabolomics, metabolite intensities are affected by biological factors and other unwanted variations. A systematic evaluation of the data processing methods is crucial to identify adequate processing procedures for a given experimental setup. Current comparative studies are mostly focused on peak area data but not on absolute concentrations. In this study, we evaluated data processing methods to produce outputs that were most similar to the corresponding absolute quantified data. We examined the data distribution characteristics, fold difference patterns between 2 metabolites, and sample variance. We used 2 metabolomic datasets from a retail milk study and a lupus nephritis cohort as test cases. When studying the impact of data normalization, transformation, scaling, and combinations of these methods, we found that the cross-contribution compensating multiple standard normalization (ccmn) method, followed by square root data transformation, was most appropriate for a well-controlled study such as the milk study dataset. Regarding the lupus nephritis cohort study, only ccmn normalization could slightly improve the data quality of the noisy cohort. Since the assessment accounted for the resemblance between processed data and the corresponding absolute quantified data, our results denote a helpful guideline for processing metabolomic datasets within a similar context (food and clinical metabolomics). Finally, we introduce Metabox 2.0, which enables thorough analysis of metabolomic data, including data processing, biomarker analysis, integrative analysis, and data interpretation. It was successfully used to process and analyze the data in this study. An online web version is available at http://metsysbio.com/metabox.

Tuning of CHO secretional machinery improve activity of secreted therapeutic sulfatase 150-fold

Rare diseases are, despite their name, collectively common and millions of people are affected daily of conditions where treatment often is unavailable. Sulfatases are a large family of activating enzymes related to several of these diseases. Heritable genetic variations in sulfatases may lead to impaired activity and a reduced macromolecular breakdown within the lysosome, with several severe and lethal conditions as a consequence. While therapeutic options are scarce, treatment for some sulfatase deficiencies by recombinant enzyme replacement are available. The recombinant production of such sulfatases suffers greatly from both low product activity and yield, further limiting accessibility for patient groups. To mitigate the low product activity, we have investigated cellular properties through computational evaluation of cultures with varying media conditions and comparison of two CHO clones with different levels of one active sulfatase variant. Transcriptome analysis identified 18 genes in secretory pathways correlating with increased sulfatase production. Experimental validation by upregulation of a set of three key genes improved the specific enzymatic activity at varying degree up to 150-fold in another sulfatase variant, broadcasting general production benefits. We also identified a correlation between product mRNA levels and sulfatase activity that generated an increase in sulfatase activity when expressed with a weaker promoter. Furthermore, we suggest that our proposed workflow for resolving bottlenecks in cellular machineries, to be useful for improvements of cell factories for other biologics as well.

Rural and urban exposures shape early life immune development in South African children with atopic dermatitis and nonallergic children

BACKGROUND

Immunological traits and functions have been consistently associated with environmental exposures and are thought to shape allergic disease susceptibility and protection. In particular, specific exposures in early life may have more significant effects on the developing immune system, with potentially long-term impacts.

METHODS

We performed RNA-Seq on peripheral blood mononuclear cells (PBMCs) from 150 children with atopic dermatitis and healthy nonallergic children in rural and urban settings from the same ethnolinguistic AmaXhosa background in South Africa. We measured environmental exposures using questionnaires.

RESULTS

A distinct PBMC gene expression pattern was observed in those children with atopic dermatitis (132 differentially expressed genes [DEGs]). However, the predominant influences on the immune cell transcriptome were related to early life exposures including animals, time outdoors, and types of cooking and heating fuels. Sample clustering revealed two rural groups (Rural_1 and Rural_2) that separated from the urban group (3413 and 2647 DEGs, respectively). The most significantly regulated pathways in Rural_1 children were related to innate activation of the immune system (e.g., TLR and cytokine signaling), changes in lymphocyte polarization (e.g., TH17 cells), and immune cell metabolism (i.e., oxidative phosphorylation). The Rural_2 group displayed evidence for ongoing lymphocyte activation (e.g., T cell receptor signaling), with changes in immune cell survival and proliferation (e.g., mTOR signaling, insulin signaling).

CONCLUSIONS

This study highlights the importance of the exposome on immune development in early life and identifies potentially protective (e.g., animal) exposures and potentially detrimental (e.g., pollutant) exposures that impact key immunological pathways.

Functional alterations and predictive capacity of gut microbiome in type 2 diabetes

The gut microbiome plays a significant role in the development of Type 2 Diabetes Mellitus (T2DM), but the functional mechanisms behind this association merit deeper investigation. Here, we used the nanopore sequencing technology for metagenomic analyses to compare the gut microbiome of individuals with T2DM from the United Arab Emirates (n = 40) with that of control (n = 44). DMM enterotyping of the cohort resulted concordantly with previous results, in three dominant groups Bacteroides (K1), Firmicutes (K2), and Prevotella (K3) lineages. The diversity analysis revealed a high level of diversity in the Firmicutes group (K2) both in terms of species richness and evenness (Wilcoxon rank-sum test, p value < 0.05 vs. K1 and K3 groups), consistent with the Ruminococcus enterotype described in Western populations. Additionally, functional enrichment analyses of KEGG modules showed significant differences in abundance between individuals with T2DM and controls (FDR < 0.05). These differences include modules associated with the degradation of amino acids, such as arginine, the degradation of urea as well as those associated with homoacetogenesis. Prediction analysis with the Predomics approach suggested potential biomarkers for T2DM, including a balance between a depletion of Enterococcus faecium and Blautia lineages with an enrichment of Absiella spp or Eubacterium limosum in T2DM individuals, highlighting the potential of metagenomic analysis in predicting predisposition to diabetic cardiomyopathy in T2DM patients.

Epigenetic Regulation in Response to CO2 Fluctuation in Marine Microalga Nannochloropsis oceanica

Microalgae often undergo different CO2 experiment in their habitat. To adapt to low CO2, carbon concentrating mechanism (CCM) could be launched in majority of microalgae and CCM are regulated at RNA level are well known. However, epigenetic modifications and their potential regulation of the transcription of masked genes at the genome level in response to CO2 fluctuation remain unclear. Here epigenetic regulation in response to CO2 fluctuation and epigenome-association with phenotypic plasticity of CCM are firstly uncovered in marine microalga Nannochloropsis oceanica IMET1. The result showed that lysine butyrylation (Kbu) and histone H3K9m2 modifications were present in N. oceanica IMET1. Moreover, Kbu modification positively regulated gene expression. In response to CO2 fluctuation, there were 5,438 and 1,106 genes regulated by Kbu and H3K9m2 in Nannochloropsis, respectively. Gained or lost histone methylations were closely associated with activating or repressing gene expressions. Differential modifications were mainly enriched in carbon fixation, photorespiration, photosynthesis, and lipid metabolism etc. Massive genome-wide epigenetic reprogramming was observed after N. oceanica cells shifted from high CO2 to low CO2. Particularly, we firstly noted that the transcription of the key low CO2 responsive carbonic anhydrase (CA5), a key component involved in CCM stress signaling, was potentially regulated by bivalent Kbu-H3K9m2 modifications in microalgae. This study provides novel insights into the relationship between gene transcription and epigenetic modification in Nannochloropsis, which will lay foundation on genetic improvement of CCM at epigenetic level.

Integrated small RNA, mRNA and protein omics reveal a miRNA network orchestrating metabolic maturation of the developing human heart

BACKGROUND

As the fetal heart develops, cardiomyocyte proliferation potential decreases while fatty acid oxidative capacity increases in a highly regulated transition known as cardiac maturation. Small noncoding RNAs, such as microRNAs (miRNAs), contribute to the establishment and control of tissue-specific transcriptional programs. However, small RNA expression dynamics and genome-wide miRNA regulatory networks controlling maturation of the human fetal heart remain poorly understood.

RESULTS

Transcriptome profiling of small RNAs revealed the temporal expression patterns of miRNA, piRNA, circRNA, snoRNA, snRNA and tRNA in the developing human heart between 8 and 19 weeks of gestation. Our analysis demonstrated that miRNAs were the most dynamically expressed small RNA species throughout mid-gestation. Cross-referencing differentially expressed miRNAs and mRNAs predicted 6200 mRNA targets, 2134 of which were upregulated and 4066 downregulated as gestation progressed. Moreover, we found that downregulated targets of upregulated miRNAs, including hsa-let-7b, miR-1-3p, miR-133a-3p, miR-143-3p, miR-499a-5p, and miR-30a-5p predominantly control cell cycle progression. In contrast, upregulated targets of downregulated miRNAs, including hsa-miR-1276, miR-183-5p, miR-1229-3p, miR-615-3p, miR-421, miR-200b-3p and miR-18a-3p, are linked to energy sensing and oxidative metabolism. Furthermore, integrating miRNA and mRNA profiles with proteomes and reporter metabolites revealed that proteins encoded in mRNA targets and their associated metabolites mediate fatty acid oxidation and are enriched as the heart develops.

CONCLUSIONS

This study presents the first comprehensive analysis of the small RNAome of the maturing human fetal heart. Our findings suggest that coordinated activation and repression of miRNA expression throughout mid-gestation is essential to establish a dynamic miRNA-mRNA-protein network that decreases cardiomyocyte proliferation potential while increasing the oxidative capacity of the maturing human fetal heart. Our results provide novel insights into the molecular control of metabolic maturation of the human fetal heart.

Host adaptation and specialization in Tetranychidae mites

Composite generalist herbivores are comprised of host-adapted populations that retain the ability to shift hosts. The degree and overlap of mechanisms used by host-adapted generalist and specialist herbivores to overcome the same host plant defenses are largely unknown. Tetranychidae mites are exceptionally suited to address the relationship between host adaptation and specialization in herbivores as this group harbors closely related species with remarkably different host ranges-an extreme generalist the two-spotted spider mite (Tetranychus urticae Koch [Tu]) and the Solanaceous specialist Tetranychus evansi (Te). Here, we used tomato-adapted two-spotted spider mite (Tu-A) and Te populations to compare mechanisms underlying their host adaptation and specialization. We show that both mites attenuate induced tomato defenses, including protease inhibitors (PIs) that target mite cathepsin L digestive proteases. While Te solely relies on transcriptional attenuation of PI induction, Tu and Tu-A have elevated constitutive activity of cathepsin L proteases, making them less susceptible to plant anti-digestive proteins. Tu-A and Te also rely on detoxification of tomato constitutive defenses. Te uses esterase and P450 activities, while Tu-A depends on the activity of all major detoxification enzymatic classes to disarm tomato defensive compounds to a lesser extent. Thus, even though both Tu-A and Te use similar mechanisms to counteract tomato defenses, Te can better cope with them. This finding is congruent with the ecological and evolutionary times required to establish mite adaptation and specialization states, respectively.

A prognostic model for ovarian neoplasms established by an integrated analysis of 1580 transcriptomic profiles

Even after debulking surgery combined with chemotherapy or new adjuvant chemotherapy paired with internal surgery, the average year of disease free survival in advanced ovarian cancer was approximately 1.7 years1. The development of a molecular predictor of early recurrence would allow for the identification of ovarian cancer (OC) patients with high risk of relapse. The Ovarian Cancer Disease Free Survival Predictor (ODFSP), a predictive model constructed from a special set of 1580 OC tumors in which gene expression was assessed using both microarray and sequencing platforms, was created by our team. To construct gene expression barcodes that were resistant to biases caused by disparate profiling platforms and batch effects, we employed a meta-analysis methodology that was based on the binary gene pair technique. We demonstrate that ODFSP is a reliable single-sample predictor of early recurrence (1 year or less) using the largest pool of OC transcriptome data sets available to date. The ODFSP model showed significantly high prognostic value for binary recurrence prediction unaffected by clinicopathologic factors, with a meta-estimate of the area under the receiver operating curve of 0.64 (P  =  4.6E-05) and a D-index (robust hazard ratio) of 1.67 (P  =  9.2E-06), respectively. GO analysis of ODFSP's 2040 gene pairs (collapsed to 886 distinct genes) revealed the involvement in small molecular catabolic process, sulfur compound metabolic process, organic acid catabolic process, sulfur compound biosynthetic process, glycosaminoglycan metabolic process and aminometabolic process. Kyoto encyclopedia of genes and genomes pathway analysis of ODFSP's signature genes identified prominent pathways that included cAMP signaling pathway and FoxO signaling pathway. By identifying individuals who might benefit from a more aggressive treatment plan or enrolment in a clinical trial but who will not benefit from standard surgery or chemotherapy, ODFSP could help with treatment decisions.

A novel in vitro prognostic model of bladder cancer based on urine-derived living tumor cells

Bladder cancer (BLCA) remains a difficult malignancy to manage because of its high recurrence, intense follow-up, and invasive diagnostic and treatment techniques. Immune checkpoint inhibitors (ICIs) have forged a new direction for the treatment of BLCA, but it is currently challenging to predict whether an individual patient will be sensitive to ICIs. We collected 43 urine/tumor samples from BLCA patients for primary bladder cancer cells (BCCs) culturing using our previously reported BCC culture platform. We used flow cytometry (FCM) to measure the expression levels of Programmed Death-Ligand 1 (PD-L1) on BCCs before and after interferon-gamma (IFN-γ) treatment and found that PD-L1 expression and the sensitivities to IFN-γ varied among patients. RNA-sequencing, western blotting, and programmed death-1 (PD-1) binding assays confirmed that the BCC FCM-based PD-L1 detection platform (BC-PD-L1) was reliable and was not hindered by the  glycosylation of PD-L1. In the subsequent retrospective study, we found that IFN-γ-stimulated PD-L1 (sPD-L1) expression on BCCs detected by BC-PD-L1 could predict the prognosis of BLCA patients. Importantly, the prognostic value was similar or even better in urine-derived BC-PD-L1 (UBC-PD-L1). Transcriptome analysis showed that BCCs with high sPD-L1 tended to enrich genes associated with the collagen-containing extracellular matrix, cell-cell adhesion, and positive regulation of the immune system. In addition, the UBC-PD-L1 also exhibited predictive value for ICI response in BLCA patients. In conclusion, as a novel personalized urine-detection method, UBC-PD-L1 may provide a rapid, accurate, and non-invasive tool for monitoring tumor progression, predicting therapeutic responses, and helping improve BLCA clinical treatment in future.

Genetic background influences the 5XFAD Alzheimer's disease mouse model brain proteome

There is an urgent need to improve the translational validity of Alzheimer's disease (AD) mouse models. Introducing genetic background diversity in AD mouse models has been proposed as a way to increase validity and enable the discovery of previously uncharacterized genetic contributions to AD susceptibility or resilience. However, the extent to which genetic background influences the mouse brain proteome and its perturbation in AD mouse models is unknown. In this study, we crossed the 5XFAD AD mouse model on a C57BL/6J (B6) inbred background with the DBA/2J (D2) inbred background and analyzed the effects of genetic background variation on the brain proteome in F1 progeny. Both genetic background and 5XFAD transgene insertion strongly affected protein variance in the hippocampus and cortex (n = 3,368 proteins). Protein co-expression network analysis identified 16 modules of highly co-expressed proteins common across the hippocampus and cortex in 5XFAD and non-transgenic mice. Among the modules strongly influenced by genetic background were those related to small molecule metabolism and ion transport. Modules strongly influenced by the 5XFAD transgene were related to lysosome/stress responses and neuronal synapse/signaling. The modules with the strongest relationship to human disease-neuronal synapse/signaling and lysosome/stress response-were not significantly influenced by genetic background. However, other modules in 5XFAD that were related to human disease, such as GABA synaptic signaling and mitochondrial membrane modules, were influenced by genetic background. Most disease-related modules were more strongly correlated with AD genotype in the hippocampus compared with the cortex. Our findings suggest that the genetic diversity introduced by crossing B6 and D2 inbred backgrounds influences proteomic changes related to disease in the 5XFAD model, and that proteomic analysis of other genetic backgrounds in transgenic and knock-in AD mouse models is warranted to capture the full range of molecular heterogeneity in genetically diverse models of AD.

Transcriptomics age acceleration in prolonged treated HIV infection

Biological aging in people with HIV (PWH) with prolonged successful antiretroviral therapy (ART) is convoluted and poorly defined. Here, we aimed to investigate the transcriptomics age estimator (TAE) in a cohort of 178 PWH on prolonged successful ART with immune reconstitution and viral suppression from the Copenhagen Comorbidity (COCOMO) cohort. We also used 143 clinical, demographical, and lifestyle factors to identify the confounders potentially responsible or associated with age acceleration. Among the PWH, 43% had an accelerated aging process (AAP), and 21% had decelerated aging process (DAP). DAP is linked with older age, European ancestry, and higher use of tenofovir disoproxil/alafenamide fumarate. A directionally class-based gene set enrichment analysis identified the upregulation of inflammatory pathways (e.g., cytokine and Retinoic acid-inducible gene I (RIG-I)-like receptor signaling pathways) and immune response like T-cell receptor signaling, antigen processing, and presentation in AAP and the downregulation of metabolic processes like oxidative phosphorylation, pyruvate metabolism.

Data-driven transcriptomics analysis identifies PCSK9 as a novel key regulator in liver aging

The liver, as a crucial metabolic organ, undergoes significant pathological changes during the aging process, which can have a profound impact on overall health. To gain a comprehensive understanding of these alterations, we employed data-driven approaches, along with biochemical methods, histology, and immunohistochemistry techniques, to systematically investigate the effects of aging on the liver. Our study utilized a well-established rat aging model provided by the National Institute of Aging. Systems biology approaches were used to analyze genome-wide transcriptomics data from liver samples obtained from young (4-5 months old) and aging (20-21 months old) Fischer 344 rats. Our findings revealed pathological changes occurring in various essential biological processes in aging livers. These included mitochondrial dysfunction, increased oxidative/nitrative stress, decreased NAD + content, impaired amino acid and protein synthesis, heightened inflammation, disrupted lipid metabolism, enhanced apoptosis, senescence, and fibrosis. These results were validated using independent datasets from both human and rat aging studies. Furthermore, by employing co-expression network analysis, we identified novel driver genes responsible for liver aging, confirmed our findings in human aging subjects, and pointed out the cellular localization of the driver genes using single-cell RNA-sequencing human data. Our study led to the discovery and validation of a liver-specific gene, proprotein convertase subtilisin/kexin type 9 (PCSK9), as a potential therapeutic target for mitigating the pathological processes associated with aging in the liver. This finding envisions new possibilities for developing interventions aimed to improve liver health during the aging process.

Extracellular vesicles from retinal pigment epithelial cells expressing R345W-Fibulin-3 induce epithelial-mesenchymal transition in recipient cells

We have shown previously that expression of R345W-Fibulin-3 induces epithelial-mesenchymal transition (EMT) in retinal pigment epithelial (RPE) cells. The purpose of the current study was to determine if extracellular vesicles (EVs) derived from RPE cells expressing R345W-Fibulin-3 mutation are sufficient to induce EMT in recipient cells. ARPE-19 cells were infected with luciferase-tagged wild-type (WT)- Fibulin-3 or luciferase-tagged R345W-Fibulin-3 (R345W) using lentiviruses. EVs were isolated from the media by ultracentrifugation or density gradient ultracentrifugation. Transmission electron microscopy and cryogenic electron microscopy were performed to study the morphology of the EVs. The size distribution of EVs were determined by nanoparticle tracking analysis (NTA). EV cargo was analysed using LC-MS/MS based proteomics. EV-associated transforming growth factor beta 1 (TGFβ1) protein was measured by enzyme-linked immunosorbent assay. The capacity of EVs to stimulate RPE migration was evaluated by treating recipient cells with WT- or R345W-EVs. The role of EV-bound TGFβ was determined by pre-incubation of EVs with a pan-TGFβ blocking antibody or IgG control. EM imaging revealed spherical vesicles with two subpopulations of EVs: a group with diameters around 30 nm and a group with diameters over 100 nm, confirmed by NTA analysis. Pathway analysis revealed that members of the sonic hedgehog pathway were less abundant in R345W- EVs, while EMT drivers were enriched. Additionally, R345W-EVs had higher concentrations of TGFβ1 compared to control. Critically, treatment with R345W-EVs was sufficient to increase EMT marker expression, as well as cell migration in recipient cells. This EV-increased cell migration was significantly inhibited by pre-incubation of EVs with pan-TGFβ-neutralising antibody. In conclusion, the expression of R345W-Fibulin-3 alters the size and cargo of EVs, which are sufficient to enhance the rate of cell migration in a TGFβ dependent manner. These results suggest that EV-bound TGFβ plays a critical role in the induction of EMT in RPE cells.

MAVEN: compound mechanism of action analysis and visualisation using transcriptomics and compound structure data in R/Shiny

BACKGROUND

Understanding the Mechanism of Action (MoA) of a compound is an often challenging but equally crucial aspect of drug discovery that can help improve both its efficacy and safety. Computational methods to aid MoA elucidation usually either aim to predict direct drug targets, or attempt to understand modulated downstream pathways or signalling proteins. Such methods usually require extensive coding experience and results are often optimised for further computational processing, making them difficult for wet-lab scientists to perform, interpret and draw hypotheses from.

RESULTS

To address this issue, we in this work present MAVEN (Mechanism of Action Visualisation and Enrichment), an R/Shiny app which allows for GUI-based prediction of drug targets based on chemical structure, combined with causal reasoning based on causal protein-protein interactions and transcriptomic perturbation signatures. The app computes a systems-level view of the mechanism of action of the input compound. This is visualised as a sub-network linking predicted or known targets to modulated transcription factors via inferred signalling proteins. The tool includes a selection of MSigDB gene set collections to perform pathway enrichment on the resulting network, and also allows for custom gene sets to be uploaded by the researcher. MAVEN is hence a user-friendly, flexible tool for researchers without extensive bioinformatics or cheminformatics knowledge to generate interpretable hypotheses of compound Mechanism of Action.

CONCLUSIONS

MAVEN is available as a fully open-source tool at https://github.com/laylagerami/MAVEN with options to install in a Docker or Singularity container. Full documentation, including a tutorial on example data, is available at https://laylagerami.github.io/MAVEN .

Systems-level temporal immune-metabolic profile in Crimean-Congo hemorrhagic fever virus infection

Crimean-Congo hemorrhagic fever (CCHF) caused by CCHF virus (CCHFV) is one of the epidemic-prone diseases prioritized by the World Health Organisation as public health emergency with an urgent need for accelerated research. The trajectory of host response against CCHFV is multifarious and remains unknown. Here, we reported the temporal spectrum of pathogenesis following the CCHFV infection using genome-wide blood transcriptomics analysis followed by advanced systems biology analysis, temporal immune-pathogenic alterations, and context-specific progressive and postinfection genome-scale metabolic models (GSMM) on samples collected during the acute (T0), early convalescent (T1), and convalescent-phase (T2). The interplay between the retinoic acid-inducible gene-I-like/nucleotide-binding oligomerization domain-like receptor and tumor necrosis factor signaling governed the trajectory of antiviral immune responses. The rearrangement of intracellular metabolic fluxes toward the amino acid metabolism and metabolic shift toward oxidative phosphorylation and fatty acid oxidation during acute CCHFV infection determine the pathogenicity. The upregulation of the tricarboxylic acid cycle during CCHFV infection, compared to the noninfected healthy control and between the severity groups, indicated an increased energy demand and cellular stress. The upregulation of glycolysis and pyruvate metabolism potentiated energy generation through alternative pathways associated with the severity of the infection. The downregulation of metabolic processes at the convalescent phase identified by blood cell transcriptomics and single-cell type proteomics of five immune cells (CD4+ and CD8+ T cells, CD14+ monocytes, B cells, and NK cells) potentially leads to metabolic rewiring through the recovery due to hyperactivity during the acute phase leading to post-viral fatigue syndrome.

Mercury intoxication disrupts tonic signaling in B cells, and may promote autoimmunity due to abnormal phosphorylation of STIM-1 and other autoimmunity risk associated phosphoproteins involved in BCR signaling

Epidemiological studies link exposure to mercury with autoimmune disease. Unfortunately, in spite of considerable effort, no generally accepted mechanistic understanding of how mercury functions with respect to the etiology of autoimmune disease is currently available. Nevertheless, autoimmune disease often arises because of defective B cell signaling. Because B cell signaling is dependent on phosphorylation cascades, in this report, we have focused on how mercury intoxication alters phosphorylation of B cell proteins in antigen-non stimulated (tonic) mouse (BALB/c) splenic B cells. Specifically, we utilized mass spectrometric techniques to conduct a comprehensive unbiased global analysis of the effect of inorganic mercury (Hg2+) on the entire B cell phosphoproteome. We found that the effects were pleotropic in the sense that large numbers of pathways were impacted. However, confirming our earlier work, we found that the B cell signaling pathway stood out from the rest, in that phosphoproteins which had sites which were affected by Hg2+, exhibited a much higher degree of connectivity, than components of other pathways. Further analysis showed that many of these BCR pathway proteins had been previously linked to autoimmune disease. Finally, dose response analysis of these BCR pathway proteins showed STIM1_S575, and NFAT2_S259 are the two most Hg2+ sensitive of these sites. Because STIM1_S575 controls the ability of STIM1 to regulate internal Ca2+, we speculate that STIM1 may be the initial point of disruption, where Hg2+ interferes with B cell signaling leading to systemic autoimmunity, with the molecular effects pleiotropically propagated throughout the cell by virtue of Ca2+ dysregulation.

Acclimation strategies of the green alga Chlorella vulgaris to different light regimes revealed by physiological and comparative proteomic analyses

Acclimation to different light regimes is at the basis of survival for photosynthetic organisms, regardless of their evolutionary origin. Previous research efforts largely focused on acclimation events occurring at the level of the photosynthetic apparatus and often highlighted species-specific mechanisms. Here, we investigated the consequences of acclimation to different irradiances in Chlorella vulgaris, a green alga that is one of the most promising species for industrial application, focusing on both photosynthetic and mitochondrial activities. Moreover, proteomic analysis of cells acclimated to high light (HL) or low light (LL) allowed identification of the main targets of acclimation in terms of differentially expressed proteins. The results obtained demonstrate photosynthetic adaptation to HL versus LL that was only partially consistent with previous findings in Chlamydomonas reinhardtii, a model organism for green algae, but in many cases similar to vascular plant acclimation events. Increased mitochondrial respiration measured in HL-acclimated cells mainly relied on alternative oxidative pathway dissipating the excessive reducing power produced due to enhanced carbon flow. Finally, proteins involved in cell metabolism, intracellular transport, gene expression, and signaling-including a heliorhodopsin homolog-were identified as strongly differentially expressed in HL versus LL, suggesting their key roles in acclimation to different light regimes.