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The emerging class of multi-functional proteins known as moonlighters challenges the one protein, one function mentality by demonstrating crosstalk between biological pathways that were previously thought to be functionally discrete. Here, we present new links between amino acid metabolism and chromatin regulation, two biological pathways that are critical for cellular and organismal homeostasis. We discovered that the threonine biosynthetic pathway is required for the transcriptional silencing of ribosomal DNA (rDNA) in Saccharomyces cerevisiae. The enzymes in the pathway promote rDNA silencing through distinct mechanisms as a subset of silencing phenotypes was rescued with exogenous threonine. In addition, we found that a key pathway enzyme, homoserine dehydrogenase, promotes DNA repair through a mechanism involving the MRX complex, a major player in DNA double strand break repair. These data further the understanding of enzymes with non-canonical roles, here demonstrated within the threonine biosynthetic pathway, and provide insight into their roles as potential anti-fungal pharmaceutical targets.

In vitro and in vivo studies have established the organic anion transporters OAT1 (SLC22A6, NKT) and OAT3 (SLC22A8) among the main multi-specific "drug" transporters. They also transport numerous endogenous metabolites, raising the possibility of drug-metabolite interactions (DMI). To help understand the role of these drug transporters on metabolism across scales ranging from organ systems to organelles, a formal multi-scale analysis was performed. Metabolic network reconstructions of the omics-alterations resulting from Oat1 and Oat3 gene knockouts revealed links between the microbiome and human metabolism including reactions involving small organic molecules such as dihydroxyacetone, alanine, xanthine, and p-cresol-key metabolites in independent pathways. Interestingly, pairwise organ-organ interactions were also disrupted in the two Oat knockouts, with altered liver, intestine, microbiome, and skin-related metabolism. Compared to older models focused on the "one transporter-one organ" concept, these more sophisticated reconstructions, combined with integration of a multi-microbial model and more comprehensive metabolomics data for the two transporters, provide a considerably more complex picture of how renal "drug" transporters regulate metabolism across the organelle (e.g. endoplasmic reticulum, Golgi, peroxisome), cellular, organ, inter-organ, and inter-organismal scales. The results suggest that drugs interacting with OAT1 and OAT3 can have far reaching consequences on metabolism in organs (e.g. skin) beyond the kidney. Consistent with the Remote Sensing and Signaling Theory (RSST), the analysis demonstrates how transporter-dependent metabolic signals mediate organ crosstalk (e.g., gut-liver-kidney) and inter-organismal communication (e.g., gut microbiome-host).

Obstructive sleep apnea (OSA) is a common disorder associated with increased risk of cardiovascular disease and mortality. Iron and heme metabolism, implicated in ventilatory control and OSA comorbidities, was associated with OSA phenotypes in recent admixture mapping and gene enrichment analyses. However, its causal contribution was unclear. In this study, we performed pathway-level transcriptional Mendelian randomization (MR) analysis to investigate the causal relationships between iron and heme related pathways and OSA. In primary analysis, we examined the expression level of four iron/heme Reactome pathways as exposures and four OSA traits as outcomes using cross-tissue cis-eQTLs from the Genotype-Tissue Expression portal and published genome-wide summary statistics of OSA. We identify a significant putative causal association between up-regulated heme biosynthesis pathway with higher sleep time percentage of hypoxemia (p = 6.14 × 10-3). This association is supported by consistency of point estimates in one-sample MR in the Multi-Ethnic Study of Atherosclerosis using high coverage DNA and RNA sequencing data generated by the Trans-Omics for Precision Medicine project. Secondary analysis for 37 additional iron/heme Gene Ontology pathways did not reveal any significant causal associations. This study suggests a causal association between increased heme biosynthesis and OSA severity.

It is unknown whether indoles, metabolites of tryptophan that are derived entirely from bacterial metabolism in the gut, are associated with symptoms of depression and anxiety. Serum samples (baseline, 12 weeks) were drawn from participants (n = 196) randomized to treatment with cognitive behavioral therapy (CBT), escitalopram, or duloxetine for major depressive disorder. Baseline indoxyl sulfate abundance was positively correlated with severity of psychic anxiety and total anxiety and with resting state functional connectivity to a network that processes aversive stimuli (which includes the subcallosal cingulate cortex (SCC-FC), bilateral anterior insula, right anterior midcingulate cortex, and the right premotor areas). The relation between indoxyl sulfate and psychic anxiety was mediated only through the metabolite's effect on the SCC-FC with the premotor area. Baseline indole abundances were unrelated to post-treatment outcome measures, and changes in symptoms were not correlated with changes in indole concentrations. These results suggest that CBT and antidepressant medications relieve anxiety via mechanisms unrelated to modulation of indoles derived from gut microbiota; it remains possible that treatment-related improvement stems from their impact on other aspects of the gut microbiome. A peripheral gut microbiome-derived metabolite was associated with altered neural processing and with psychiatric symptom (anxiety) in humans, which provides further evidence that gut microbiome disruption can contribute to neuropsychiatric disorders that may require different therapeutic approaches. Given the exploratory nature of this study, findings should be replicated in confirmatory studies.Clinical trial NCT00360399 "Predictors of Antidepressant Treatment Response: The Emory CIDAR" https://clinicaltrials.gov/ct2/show/NCT00360399 .

Malachite green is a common environmental pollutant that poses a great threat to non-target organisms, including humans. This study reports the characterization of a bacterial strain, Pseudomonas veronii JW3-6, which was isolated from a malachite green enrichment culture. This strain degraded malachite green efficiently in a wide range of temperature and pH levels. Under optimal degradation conditions (32.4 °C, pH 7.1, and inoculum amount of 2.5 × 107 cfu/mL), P. veronii JW3-6 could degrade 93.5% of 50 mg/L malachite green within seven days. Five intermediate products from the degradation of malachite green were identified: leucomalachite green, 4-(dimethylamino) benzophenone, 4-dimethylaminophenol, benzaldehyde, and hydroquinone. We propose a possible degradation pathway based on these findings. The present study is the first to report the degradation of malachite green by P. veronii and the identification of hydroquinone as a metabolite in the degradation pathway.

Perennial grasses will account for approximately 16 billion gallons of renewable fuels by the year 2022, contributing significantly to carbon and nitrogen sequestration. However, perennial grasses productivity can be limited by severe freezing conditions in some geographical areas, although these risks could decrease with the advance of climate warming, the possibility of unpredictable early cold events cannot be discarded. We conducted a study on the model perennial grass Brachypodium sylvaticum to investigate the molecular mechanisms that contribute to cold and freezing adaption. The study was performed on two different B. sylvaticum accessions, Ain1 and Osl1, typical to warm and cold climates, respectively. Both accessions were grown under controlled conditions with subsequent cold acclimation followed by freezing stress. For each treatment a set of morphological parameters, transcription, metabolite, and lipid profiles were measured. State-of-the-art algorithms were employed to analyze cross-component relationships. Phenotypic analysis revealed higher adaption of Osl1 to freezing stress. Our analysis highlighted the differential regulation of the TCA cycle and the GABA shunt between Ain1 and Osl1. Osl1 adapted to freezing stress by repressing the GABA shunt activity, avoiding the detrimental reduction in fatty acid biosynthesis and the concomitant detrimental effects on membrane integrity.

We investigate diffusive search on planar networks, motivated by tubular organelle networks in cell biology that contain molecules searching for reaction partners and binding sites. Exact calculation of the diffusive mean first-passage time on a spatial network is used to characterize the typical search time as a function of network connectivity. We find that global structural properties - the total edge length and number of loops - are sufficient to largely determine network exploration times for a variety of both synthetic planar networks and organelle morphologies extracted from living cells. For synthetic networks on a lattice, we predict the search time dependence on these global structural parameters by connecting with percolation theory, providing a bridge from irregular real-world networks to a simpler physical model. The dependence of search time on global network structural properties suggests that network architecture can be designed for efficient search without controlling the precise arrangement of connections. Specifically, increasing the number of loops substantially decreases search times, pointing to a potential physical mechanism for regulating reaction rates within organelle network structures.

Corals and sponges harbor diverse microbial communities that are integral to the functioning of the host. While the taxonomic diversity of their microbiomes has been well-established for corals and sponges, their functional roles are less well-understood. It is unclear if the similarities of symbiosis in an invertebrate host would result in functionally similar microbiomes, or if differences in host phylogeny and environmentally driven microhabitats within each host would shape functionally distinct communities. Here we addressed this question, using metatranscriptomic and 16S rRNA gene profiling techniques to compare the microbiomes of two host organisms from different phyla. Our results indicate functional similarity in carbon, nitrogen, and sulfur assimilation, and aerobic nitrogen cycling. Additionally, there were few statistical differences in pathway coverage or abundance between the two hosts. For example, we observed higher coverage of phosphonate and siderophore metabolic pathways in the star coral, Montastraea cavernosa, while there was higher coverage of chloroalkane metabolism in the giant barrel sponge, Xestospongia muta. Higher abundance of genes associated with carbon fixation pathways was also observed in M. cavernosa, while in X. muta there was higher abundance of fatty acid metabolic pathways. Metagenomic predictions based on 16S rRNA gene profiling analysis were similar, and there was high correlation between the metatranscriptome and metagenome predictions for both hosts. Our results highlight several metabolic pathways that exhibit functional similarity in these coral and sponge microbiomes despite the taxonomic differences between the two microbiomes, as well as potential specialization of some microbially based metabolism within each host.

Tomato fruit are especially susceptible to chilling injury (CI) when continuously exposed to temperatures below 12 °C. In this study, integrative comparative analyses of transcriptomics and metabolomics data were performed to uncover the regulatory network in CI tomato fruit. Metabolite profiling analysis found that 7 amino acids, 27 organic acids, 16 of sugars and 22 other compounds had a significantly different content while transcriptomics data showed 1735 differentially expressed genes (DEGs) were down-regulated and 1369 were up-regulated in cold-stored fruit. We found that the contents of citrate, cis-aconitate and succinate were increased, which were consistent with the expression of ATP-citrate synthase (ACS) and isocitrate dehydrogenase (IDH) genes in cold-treated tomato fruit. Cold stress promotes the expression of ACS and IDH which may increase the synthesis of citrate, cis-aconitate and succinate. Alanine and leucine had increased contents, which may result from alanine aminotransferase (ALT) and branched-chain amino acid aminotransferase (BcAT)'s high expression levels, respectively. Overall the transcriptomics and metabolomics data in our study explain the molecular mechanisms of the chilling injury and expands our understanding of the complex regulatory mechanisms of a metabolic network in response to chilling injury in tomato fruit.

Plant organs consist of multiple cell types that do not operate in isolation, but communicate with each other to maintain proper functions. Here, we extract models specific to three developmental stages of eight root cell types or tissue layers in Arabidopsis thaliana based on a state-of-the-art constraint-based modeling approach with all publicly available transcriptomics and metabolomics data from this system to date. We integrate these models into a multi-cell root model which we investigate with respect to network structure, distribution of fluxes, and concordance to transcriptomics and proteomics data. From a methodological point, we show that the coupling of tissue-specific models in a multi-tissue model yields a higher specificity of the interconnected models with respect to network structure and flux distributions. We use the extracted models to predict and investigate the flux of the growth hormone indole-3-actetate and its antagonist, trans-Zeatin, through the root. While some of predictions are in line with experimental evidence, constraints other than those coming from the metabolic level may be necessary to replicate the flow of indole-3-actetate from other simulation studies. Therefore, our work provides the means for data-driven multi-tissue metabolic model extraction of other Arabidopsis organs in the constraint-based modeling framework.

Light-emitting diodes (LEDs) are an artificial light source used in closed-type plant factories and provide a promising solution for a year-round supply of green leafy vegetables, such as lettuce (Lactuca sativa L.). Obtaining high-quality seedlings using controlled irradiation from LEDs is critical, as the seedling health affects the growth and yield of leaf lettuce after transplantation. Because key molecular pathways underlying plant responses to a specific light quality and intensity remain poorly characterised, we used a multi-omics-based approach to evaluate the metabolic and transcriptional reprogramming of leaf lettuce seedlings grown under narrow-band LED lighting. Four types of monochromatic LEDs (one blue, two green and one red) and white fluorescent light (control) were used at low and high intensities (100 and 300 μmol·m-2·s-1, respectively). Multi-platform mass spectrometry-based metabolomics and RNA-Seq were used to determine changes in the metabolome and transcriptome of lettuce plants in response to different light qualities and intensities. Metabolic pathway analysis revealed distinct regulatory mechanisms involved in flavonoid and phenylpropanoid biosynthetic pathways under blue and green wavelengths. Taken together, these data suggest that the energy transmitted by green light is effective in creating a balance between biomass production and the production of secondary metabolites involved in plant defence.

We investigated the long-term effects of prenatal nutrition on pre-slaughter Nelore bulls using integrative transcriptome and metabolome analyses of liver tissue. Three prenatal nutritional treatments were administered to 126 cows: NP (control, mineral supplementation only), PP (protein-energy supplementation in the third trimester), and FP (protein-energy supplementation throughout pregnancy). Liver samples from 22.5 ± 1-month-old bulls underwent RNA-Seq and targeted metabolomics. Weighted correlation network analysis (WGCNA) identified treatment-associated gene and metabolite co-expression modules, further analyzed using MetaboAnalyst 6.0 (metabolite over-representation analysis and transcriptome-metabolome integrative analysis) and Enrichr (gene over-representation analysis). We identified several significant gene and metabolite modules, as well as hub components associated with energy, protein and oxidative metabolism, regulatory mechanisms, epigenetics, and immune function. The NP transcriptome-metabolome analysis identified key pathways (aminoacyl t-RNA biosynthesis, gluconeogenesis, and PPAR signaling) and hub components (glutamic acid, SLC6A14). PP highlighted pathways (arginine and proline metabolism, TGF-beta signaling, glyoxylate and dicarboxylate metabolism) with arginine and ODC1 as hub components. This study highlights the significant impact of prenatal nutrition on the liver tissue of Nelore bulls, shedding light on critical metabolic pathways and hub components related to energy and protein metabolism, as well as immune system and epigenetics., Competing Interests: Declarations Consent for publication Not applicable. Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

This study assessed the impacts of wheat straw as a cosubstrate on coal biocoverion into methane and the associated mechanism within methane metabolic pathways. Co-digestion of coal with varying wheat straw concentrations resulted in a remarkable (1246.05%) increase in methane yield compared to that of the control (CK). Moreover, microbial analysis revealed a uniform distribution of Methanosarcinaceae (51.14%) and Methanobacteriaceae (39.90%) in the co-digestion of coal and wheat straw (CWS1) at a ratio of 3:1 (w/w) compared to other treatments such as coal and wheat straw (CWS2) at a ratio of 3:0.5. In addition, Hungatieclostridiaceae and Rhodobacteriaceae were abundant in both co-digesters, whereas the bacterial communities in the CK group were significantly different and more abundant than those in the Peptostreptococcaceae and Enterobacteriaceae groups. The key enzymes related to methanogenic metabolic pathways, including EC: 1.2.99.5 and EC: 2.1.1.86 (facilitating the conversion of CO 2 into methane), and EC:1.12.98.1 exhibited significant abundance within CWS1. Aromatic compounds such as 4-(2-chloroanilino)-4-oxobutanoic acid and phthalic acid were substantially more abundant in CWS1 and CWS2 than in CK, indicating the increased bioavailability of coal to microbial activities. This novel approach demonstrates that wheat straw co-digestion with coal during anaerobic digestion modulates microbial communities and their metabolic pathways to enhance methane production from complex substrates such as coal., (© 2024. The Author(s).)

Magnesium (Mg) plays a pivotal role as an essential component of plant chlorophyll and functions as a critical coenzyme. However, research exploring the regulatory mechanisms of magnesium ions on the synthesis of secondary metabolites is still in its early stages. Sophora tonkinensis is a widely utilized medicinal plant in China, recognized for its diverse secondary metabolites with active properties. This study investigates variations in these ingredients in tissue-cultured seedlings under varying magnesium concentrations. Simultaneously, an omics data analysis was conducted on tissue-cultured seedlings subjected to treatments with magnesium and low magnesium. These comprehensive omics analyses aimed to elucidate the mechanisms through which magnesium influences active components, growth, and development. Magnesium exerts a pervasive influence on various metabolic pathways, forming an intricate network. Research findings indicate that magnesium impacts diverse metabolic processes, including the absorption of potassium and calcium, as well as photosynthetic activity. Consequently, these influences lead to discernible changes in the levels of pharmacologically active compounds and the growth and developmental status.This study is the first to employ a multi-omics data analysis in S. tonkinensis. This methodology allows us to uncover the overarching impact of metabolic networks on the levels of various active ingredients and specific phenotypes., (© 2024. The Author(s).)

Akebia trifoliata is a medicinal plant with high oil content and broad pharmacological effects. To investigate the regulatory mechanisms of key metabolic pathways during seed development, we conducted an integrated multi-omics analysis, including transcriptomics, proteomics, and metabolomics, exploring the dynamic changes in carbon and lipid metabolism. Metabolomics analysis revealded that glucose and sucrose levels decreased, while glycolytic intermediate phosphoenolpyruvate and fatty acids increased with seed development, indicating a shift in carbon flux towards fatty acid synthesis. Integrated transcriptomic and proteomic analyses showed that 70 days after flowering, the expression levels of genes and proteins associated with carbon and fatty acid metabolism were upregulated, suggesting an increased energy demand. Additionally, LEC2, LEC1, WRI1, FUS3, and ABI3 were identified as vital regulators of lipid synthesis. By constructing a multi-omics co-expression network, we identified hub genes such as aroE, GAPDH, KCS, TPS, and hub proteins like PGM, PDH, ENO, PFK, PK, ACCase, SAD, PLC, and OGDH that play critical regulatory roles in seed lipid synthesis. This study provides new ideas for the molecular basis of lipid synthesis in Akebia trifoliata seeds and can facilitate future research on the genetic improvement through molecular-assisted breeding., (© 2024. The Author(s).)

To elucidate the lipidomic and metabolomic alterations associated with hypertrophic cardiomyopathy (HCM) pathogenesis, we utilized cmybpc3-/- zebrafish model. Fatty acid profiling revealed variability of 10 fatty acids profiles, with heterozygous (HT) and homozygous (HM) groups exhibiting distinct patterns. Hierarchical cluster analysis and multivariate analyses demonstrated a clear separation of HM from HT and control (CO) groups related to cardiac remodeling. Lipidomic profiling identified 257 annotated lipids, with two significantly dysregulated between CO and HT, and 59 between HM and CO. Acylcarnitines and phosphatidylcholines were identified as key contributors to group differentiation, suggesting a shift in energy source. Untargeted metabolomics revealed 110 and 53 significantly dysregulated metabolites. Pathway enrichment analysis highlighted perturbations in multiple metabolic pathways in the HM group, including nicotinate, nicotinamide, purine, glyoxylate, dicarboxylate, glycerophospholipid, pyrimidine, and amino acid metabolism. Our study provides comprehensive insights into the lipidomic and metabolomic unique signatures associated with cmybpc3-/- induced HCM in zebrafish. The identified biomarkers and dysregulated pathways shed light on the metabolic perturbations underlying HCM pathology, offering potential targets for further investigation and potential new therapeutic interventions., (© 2024. The Author(s).)

Microbial electrosynthesis is a renewable energy and chemical production platform that relies on microbial cells to capture electrons from a cathode and fix carbon. Yet despite the promise of this technology, the metabolic capacity of the microbes that inhabit the electrode surface and catalyze electron transfer in these systems remains largely unknown. We assembled thirteen draft genomes from a microbial electrosynthesis system producing primarily acetate from carbon dioxide, and their transcriptional activity was mapped to genomes from cells on the electrode surface and in the supernatant. This allowed us to create a metabolic model of the predominant community members belonging to Acetobacterium, Sulfurospirillum, and Desulfovibrio. According to the model, the Acetobacterium was the primary carbon fixer, and a keystone member of the community. Transcripts of soluble hydrogenases and ferredoxins from Acetobacterium and hydrogenases, formate dehydrogenase, and cytochromes of Desulfovibrio were found in high abundance near the electrode surface. Cytochrome c oxidases of facultative members of the community were highly expressed in the supernatant despite completely sealed reactors and constant flushing with anaerobic gases. These molecular discoveries and metabolic modeling now serve as a foundation for future examination and development of electrosynthetic microbial communities.

The increasing availability of metabolomics data necessitates novel methods for deeper data analysis and interpretation. We present a flux balance analysis method that allows for the computation of dynamic intracellular metabolic changes at the cellular scale through integration of time-course absolute quantitative metabolomics. This approach, termed "unsteady-state flux balance analysis" (uFBA), is applied to four cellular systems: three dynamic and one steady-state as a negative control. uFBA and FBA predictions are contrasted, and uFBA is found to be more accurate in predicting dynamic metabolic flux states for red blood cells, platelets, and Saccharomyces cerevisiae. Notably, only uFBA predicts that stored red blood cells metabolize TCA intermediates to regenerate important cofactors, such as ATP, NADH, and NADPH. These pathway usage predictions were subsequently validated through 13C isotopic labeling and metabolic flux analysis in stored red blood cells. Utilizing time-course metabolomics data, uFBA provides an accurate method to predict metabolic physiology at the cellular scale for dynamic systems.

The mevalonate (MEV) cascade is responsible for cholesterol biosynthesis and the formation of the intermediate metabolites geranylgeranylpyrophosphate (GGPP) and farnesylpyrophosphate (FPP) used in the prenylation of proteins. Here we show that the MEV cascade inhibitor simvastatin induced significant cell death in a wide range of human tumor cell lines, including glioblastoma, astrocytoma, neuroblastoma, lung adenocarcinoma, and breast cancer. Simvastatin induced apoptotic cell death via the intrinsic apoptotic pathway. In all cancer cell types tested, simvastatin-induced cell death was not rescued by cholesterol, but was dependent on GGPP- and FPP-depletion. We confirmed that simvastatin caused the translocation of the small Rho GTPases RhoA, Cdc42, and Rac1/2/3 from cell membranes to the cytosol in U251 (glioblastoma), A549 (lung adenocarcinoma) and MDA-MB-231(breast cancer). Simvastatin-induced Rho-GTP loading significantly increased in U251 cells which were reversed with MEV, FPP, GGPP. In contrast, simvastatin did not change Rho-GTP loading in A549 and MDA-MB-231. Inhibition of geranylgeranyltransferase I by GGTi-298, but not farnesyltransferase by FTi-277, induced significant cell death in U251, A549, and MDA-MB-231. These results indicate that MEV cascade inhibition by simvastatin induced the intrinsic apoptosis pathway via inhibition of Rho family prenylation and depletion of GGPP, in a variety of different human cancer cell lines.

Malignant transformation is often accompanied by significant metabolic changes. To identify drivers underlying these changes, we calculated metabolic flux states for the NCI60 cell line collection and correlated the variance between metabolic states of these lines with their other properties. The analysis revealed a remarkably consistent structure underlying high flux metabolism. The three primary uptake pathways, glucose, glutamine and serine, are each characterized by three features: (1) metabolite uptake sufficient for the stoichiometric requirement to sustain observed growth, (2) overflow metabolism, which scales with excess nutrient uptake over the basal growth requirement, and (3) redox production, which also scales with nutrient uptake but greatly exceeds the requirement for growth. We discovered that resistance to chemotherapeutic drugs in these lines broadly correlates with the amount of glucose uptake. These results support an interpretation of the Warburg effect and glutamine addiction as features of a growth state that provides resistance to metabolic stress through excess redox and energy production. Furthermore, overflow metabolism observed may indicate that mitochondrial catabolic capacity is a key constraint setting an upper limit on the rate of cofactor production possible. These results provide a greater context within which the metabolic alterations in cancer can be understood.

Biogenesis of lysosome-related organelles complex-1 (BLOC-1) is a protein complex involved in the formation of endosomal tubular structures that mediates the sorting of protein cargoes to specialised compartments. In this study, we present insights into the metabolic consequences caused by BLOC-1 deficiency in pallid mice, which carry a null mutation in the Bloc1s6 gene encoding an essential component of this complex. The metabolome of the hippocampus of pallid mice was analysed using an untargeted, liquid chromatography-coupled mass spectrometric approach. After data pre-treatment, statistical analysis and pathway enrichment, we have identified 28 metabolites that showed statistically significant changes between pallid and wild-type control. These metabolites included amino acids, nucleobase-containing compounds and lysophospholipids. Interestingly, pallid mice displayed increased hippocampal levels of the neurotransmitters glutamate and N-acetyl-aspartyl-glutamic acid (NAAG) and their precursor glutamine. Expression of the sodium-coupled neutral amino acid transporter 1 (SNAT1), which transports glutamine into neurons, was also upregulated. Conversely, levels of the neurotransmitter precursors phenylalanine and tryptophan were decreased. Interestingly, many of these changes could be mapped to overlapping metabolic pathways. The observed metabolic alterations are likely to affect neurotransmission and neuronal homeostasis and in turn could mediate the memory and behavioural impairments observed in BLOC-1-deficient mice.

Application of stable isotopically labelled (SIL) molecules in Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) over a series of time points allows the temporal and spatial dynamics of biochemical reactions to be tracked in a biological system. However, these large kinetic MSI datasets and the inherent variability of biological replicates presents significant challenges to the rapid analysis of the data. In addition, manual annotation of downstream SIL metabolites involves human input to carefully analyse the data based on prior knowledge and personal expertise. To overcome these challenges to the analysis of spatiotemporal MALDI-MSI data and improve the efficiency of SIL metabolite identification, a bioinformatics pipeline has been developed and demonstrated by analysing normal bovine lens glucose metabolism as a model system. The pipeline consists of spatial alignment to mitigate the impact of sample variability and ensure spatial comparability of the temporal data, dimensionality reduction to rapidly map regional metabolic distinctions within the tissue, and metabolite annotation coupled with pathway enrichment modules to summarise and display the metabolic pathways induced by the treatment. This pipeline will be valuable for the spatial metabolomics community to analyse kinetic MALDI-MSI datasets, enabling rapid characterisation of spatio-temporal metabolic patterns from tissues of interest., (© 2024. The Author(s).)

The analysis of the differences in metabolic profiles between naturally Ophiocordyceps sinensis (NO) and cultivated Ophiocordyceps sinensis (CO) is an essential process for the medicinal value mining of Ophiocordyceps sinensis. Non-targeted metabolomics was used to compare the differences in metabolite composition and abundance between NO and CO. Total metabolite composition found that NO is rich in organic acids and derivatives, and CO is rich in lipids and lipid-like molecules. HCA found that organooxygen compounds, cinchona alkaloid, and fatty acyls had different abundances in NO and CO. The variable importance in projection value and quantitative analysis of metabolites found that NO was rich in l-iditol, malate, linoleic acid, and oleic acid; CO is rich in sucrose, perseitol, hydroquinidine, nonanoic acid, 1-hydroxy-2-naphthoic acid, hymol-β-d-glucoside, and gly-his-lys. these compounds have the potential to be biomarkers of NO and CO. KEGG enrichment analysis showed that ascorbate and aldarate metabolism, carbon metabolism, pyrimidine metabolism, and fatty acid biosynthesis were the most different metabolic pathways between NO and CO. Therefore, the analysis of the characteristics of NO and CO metabolites has reference value for finding their different medicinal functions., (© 2024. The Author(s).)

Securing complete control of complex systems comprised of tens of thousands of interconnected nodes holds immense significance across various fields, spanning from cell biology and brain science to human-engineered systems. However, depending on specific functional requirements, it can be more practical and efficient to focus on a pre-defined subset of nodes for control, a concept known as target control. While some methods have been proposed to find the smallest driver node set for target control, they either rely on heuristic approaches based on k-walk theory, lacking a guarantee of optimal solutions, or they are overly complex and challenging to implement in real-world networks. To address this challenge, we introduce a simple and elegant algorithm, inspired by the path cover problem, which efficiently identifies the nodes required to control a target node set within polynomial time. To practically apply the algorithm in real-world systems, we have selected several networks in which a specific set of nodes with functional significance can be designated as a target control set. The analysed systems include the complete connectome of the nematode worm C. elegans, the recently disclosed connectome of the Drosophila larval brain, as well as dozens of genome-wide metabolic networks spanning major plant lineages. The target control analysis shed light on distinctions between neural systems in nematode worms and larval brain insects, particularly concerning the number of nodes necessary to regulate specific functional systems. Furthermore, our analysis uncovers evolutionary trends within plant lineages, notably when examining the proportion of nodes required to control functional pathways., (© 2024. The Author(s).)

Selective drugs with a relatively narrow spectrum can reduce the side effects of treatments compared to broad-spectrum antibiotics by specifically targeting the pathogens responsible for infection. Furthermore, combating an infectious pathogen, especially a drug-resistant microorganism, is more efficient by attacking multiple targets. Here, we combined synthetic lethality with selective drug targeting to identify multi-target and organism-specific potential drug candidates by systematically analyzing the genome-scale metabolic models of six different microorganisms. By considering microorganisms as targeted or conserved in groups ranging from one to six members, we designed 665 individual case studies. For each case, we identified single essential reactions as well as double, triple, and quadruple synthetic lethal reaction sets that are lethal for targeted microorganisms and neutral for conserved ones. As expected, the number of obtained solutions for each case depends on the genomic similarity between the studied microorganisms. Mapping the identified potential drug targets to their corresponding pathways highlighted the importance of key subsystems such as cell envelope biosynthesis, glycerophospholipid metabolism, membrane lipid metabolism, and the nucleotide salvage pathway. To assist in the validation and further investigation of our proposed potential drug targets, we introduced two sets of targets that can theoretically address a substantial portion of the 665 cases. We expect that the obtained solutions provide valuable insights into designing narrow-spectrum drugs that selectively cause system-wide damage only to the target microorganisms., (© 2024. The Author(s).)

The clinical diagnosis of biliary atresia (BA) poses challenges, particularly in distinguishing it from cholestasis (CS). Moreover, the prognosis for BA is unfavorable and there is a dearth of effective non-invasive diagnostic models for detection. Therefore, the aim of this study is to elucidate the metabolic disparities among children with BA, CS, and normal controls (NC) without any hepatic abnormalities through comprehensive metabolomics analysis. Additionally, our objective is to develop an advanced diagnostic model that enables identification of BA. The plasma samples from 90 children with BA, 48 children with CS, and 47 NC without any liver abnormalities children were subjected to metabolomics analysis, revealing significant differences in metabolite profiles among the 3 groups, particularly between BA and CS. A total of 238 differential metabolites were identified in the positive mode, while 89 differential metabolites were detected in the negative mode. Enrichment analysis revealed 10 distinct metabolic pathways that differed, such as lysine degradation, bile acid biosynthesis. A total of 18 biomarkers were identified through biomarker analysis, and in combination with the exploration of 3 additional biomarkers (LysoPC(18:2(9Z,12Z)), PC (22:5(7Z,10Z,13Z,16Z,19Z)/14:0), and Biliverdin-IX-α), a diagnostic model for BA was constructed using logistic regression analysis. The resulting ROC area under the curve was determined to be 0.968. This study presents an innovative and pioneering approach that utilizes metabolomics analysis to develop a diagnostic model for BA, thereby reducing the need for unnecessary invasive examinations and contributing to advancements in diagnosis and prognosis for patients with BA., (© 2024. The Author(s).)

Postoperative cognitive dysfunction (POCD) has become the popular critical post-operative consequences, especially cardiopulmonary bypass surgery, leading to an increased risk of mortality. However, no therapeutic effect about POCD. Probiotics are beneficial bacteria living in the gut and help to reduce the risk of POCD. However, the detailed mechanism is still not entirely known. Therefore, our research aims to uncover the effect and mechanism of probiotics in relieving POCD and to figure out the possible relationship between kynurenine metabolic pathway. 36 rats were grouped into three groups: sham operated group (S group, n = 12), Cardiopulmonary bypass group (CPB group, n = 12), and probiotics+CPB (P group, n = 12). After CPB model preparation, water maze test and Garcia score scale was performed to identify the neurological function. Immunofluorescence and Hematoxylin and eosin staining has been used for hippocampal neurons detection. Brain injury related proteins, oxidative stress factors, and inflammatory factors were detected using enzyme-linked immunosorbent assays (ELISA). Neuronal apoptosis was detected by TdT-mediated dUTP nick end-labeling (TUNEL) staining and western blot. High-performance liquid chromatography/mass spectrometry (HPLC/MS) was performed to detect the key factors of the kynurenine metabolic pathway. Our results demonstrated that probiotics improved neurological function of post-CPB rats. The administration of probiotics ameliorated memory and learning in spatial terms CPB rats (P < 0.05). Hematoxylin and eosin (H&E) staining data, S-100β and neuron-specific enolase (NSE) data convinced that probiotics agonists reduced brain damage in CPB rats (P < 0.05). Moreover, probiotics regulated inflammatory factors, meanwhile attenuated hippocampal neuronal apoptosis. Probiotics alleviated POCD in rats with CPB through regulation of kynurenine metabolic signaling pathway., (© 2024. The Author(s).)

Microorganisms almost always exist as mixed communities in nature. While the significance of microbial community activities is well appreciated, a thorough understanding about how microbial communities respond to environmental perturbations has not yet been achieved. Here we have used a combination of metagenomic, genome binning, and stimulus-induced metatranscriptomic approaches to estimate the metabolic network and stimuli-induced metabolic switches existing in a complex microbial biofilm that was producing electrical current via extracellular electron transfer (EET) to a solid electrode surface. Two stimuli were employed: to increase EET and to stop EET. An analysis of cell activity marker genes after stimuli exposure revealed that only two strains within eleven binned genomes had strong transcriptional responses to increased EET rates, with one responding positively and the other responding negatively. Potential metabolic switches between eleven dominant members were mainly observed for acetate, hydrogen, and ethanol metabolisms. These results have enabled the estimation of a multi-species metabolic network and the associated short-term responses to EET stimuli that induce changes to metabolic flow and cooperative or competitive microbial interactions. This systematic meta-omics approach represents a next step towards understanding complex microbial roles within a community and how community members respond to specific environmental stimuli.

Chronic kidney disease (CKD) is a major public health problem worldwide. Rhubarb has been shown to have nephroprotective and anti-fibrotic activities in patients with CKD. However, bioactive fractions and biochemical mechanism of anti-fibrotic properties of rhubarb remain unclear. Here we applied ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry together with univariate and multivariate statistical analyses to investigate the urinary metabolite profile in rats with adenine-induced CKD treated with the petroleum ether (PE)-, ethyl acetate (EA)- and n-butanol (BU)- extracts of rhubarb. Significant differences in renal function, kidney histopathology as well as metabolic profiles were observed between CKD and control rats. Changes in these parameters reflected characteristic phenotypes of CKD rats. We further identified a series of differential urinary metabolites for CKD rats, suggesting metabolic dysfunction in pathway of amino acid, purine, taurine, and choline metabolisms. Treatment with EA, BU and PE extracts of rhubarb improved renal function and histopathological abnormalities including interstitial fibrosis and inflammation, and either fully or partially reversed the abnormalities of the urinary metabolites. Among them, the nephroprotective effect of EA extract was stronger than BU and PE extracts. This work provides important mechanistic insights into the CKD and nephroprotective effects of different rhubarb extract against tubulo-interstitial fibrosis.

Cellular interactions can be modeled as complex dynamical systems represented by weighted graphs. The functionality of such networks, including measures of robustness, reliability, performance, and efficiency, are intrinsically tied to the topology and geometry of the underlying graph. Utilizing recently proposed geometric notions of curvature on weighted graphs, we investigate the features of gene co-expression networks derived from large-scale genomic studies of cancer. We find that the curvature of these networks reliably distinguishes between cancer and normal samples, with cancer networks exhibiting higher curvature than their normal counterparts. We establish a quantitative relationship between our findings and prior investigations of network entropy. Furthermore, we demonstrate how our approach yields additional, non-trivial pair-wise (i.e. gene-gene) interactions which may be disrupted in cancer samples. The mathematical formulation of our approach yields an exact solution to calculating pair-wise changes in curvature which was computationally infeasible using prior methods. As such, our findings lay the foundation for an analytical approach to studying complex biological networks.

Nicotinic acid (NA, a.k.a. vitamin B3 or niacin) can reduce blood cholesterol and low-density lipoproteins whereas increase high-density lipoproteins. However, when NA is used to treat dyslipidemias, it causes a strong side effect of cutaneous vasodilation, commonly called flushing. A recent study showed that NA may cause flushing by lowering activation threshold temperature of the heat-sensitive capsaicin receptor TRPV1 ion channel, leading to its activation at body temperature. The finding calls into question whether NA might also interact with the homologous heat-sensitive TRPV2-4 channels, particularly given that TRPV3 and TRPV4 are abundantly expressed in keratinocytes of the skin where much of the flushing response occurs. We found that NA indeed potentiated TRPV3 while inhibited TRPV2 and TRPV4. Consistent with these gating effects, NA lowered the heat-activation threshold of TRPV3 but elevated that of TRPV4. We further found that activity of TRPV1 was substantially prolonged by extracellular NA, which may further enhance the direct activation effect. Consistent with the broad gating effect on TRPV1-4 channels, evidence from the present study hints that NA may share the same activation pathway as 2-aminoethoxydiphenyl borate (2-APB), a common agonist for these TRPV channels. These findings shed new light on the molecular mechanism underlying NA regulation of TRPV channels.

Human diets differ from those of non-human primates. Among few obvious differences, humans consume more meat than most non-human primates and regularly cook their food. It is hypothesized that a dietary shift during human evolution has been accompanied by molecular adaptations in metabolic pathways. Consistent with this notion, comparative studies of gene expression levels in primates have found that the regulation of genes with metabolic functions tend to evolve rapidly in the human lineage. The metabolic consequences of these regulatory differences, however, remained unknown. To address this gap, we performed a comparative study using a combination of gene expression and metabolomic profiling in livers from humans, chimpanzees, and rhesus macaques. We show that dietary differences between species have a strong effect on metabolic concentrations. In addition, we found that differences in metabolic concentration across species are correlated with inter-species differences in the expression of the corresponding enzymes, which control the same metabolic reaction. We identified a number of metabolic compounds with lineage-specific profiles, including examples of human-species metabolic differences that may be directly related to dietary differences.

High-altitude cerebral edema (HACE) is a severe neurological condition that can occur at high altitudes. It is characterized by the accumulation of fluid in the brain, leading to a range of symptoms, including severe headache, confusion, loss of coordination, and even coma and death. Exosomes play a crucial role in intercellular communication, and their contents have been found to change in various diseases. This study analyzed the metabolomic characteristics of blood exosomes from HACE patients compared to those from healthy controls (HCs) with the aim of identifying specific metabolites or metabolic pathways associated with the development of HACE conditions. A total of 21 HACE patients and 21 healthy controls were recruited for this study. Comprehensive metabolomic profiling of the serum exosome samples was conducted using ultraperformance liquid chromatography-tandem mass spectrometry (UPLC‒MS/MS). Additionally, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed to identify the metabolic pathways affected in HACE patients. Twenty-six metabolites, including ( +)-camphoric acid, choline, adenosine, adenosine 5'-monophosphate, deoxyguanosine 5'-monophosphate, guanosine, and hypoxanthine-9-β-D-arabinofuranoside, among others, exhibited significant changes in expression in HACE patients compared to HCs. Additionally, these differentially abundant metabolites were confirmed to be potential biomarkers for HACE. KEGG pathway enrichment analysis revealed several pathways that significantly affect energy metabolism regulation (such as purine metabolism, thermogenesis, and nucleotide metabolism), estrogen-related pathways (the estrogen signaling pathway, GnRH signaling pathway, and GnRH pathway), cyclic nucleotide signaling pathways (the cGMP-PKG signaling pathway and cAMP signaling pathway), and hormone synthesis and secretion pathways (renin secretion, parathyroid hormone synthesis, secretion and action, and aldosterone synthesis and secretion). In patients with HACE, adenosine, guanosine, and hypoxanthine-9-β-D-arabinofuranoside were negatively correlated with height. Deoxyguanosine 5'-monophosphate is negatively correlated with weight and BMI. Additionally, LPE (18:2/0:0) and pregnanetriol were positively correlated with age. This study identified potential biomarkers for HACE and provided valuable insights into the underlying metabolic mechanisms of this disease. These findings may lead to potential targets for early diagnosis and therapeutic intervention in HACE patients., (© 2024. The Author(s).)

Depression is a serious psychiatric illness that causes great inconvenience to the lives of elderly individuals. However, the diagnosis of depression is somewhat subjective. Nontargeted gas chromatography (GC)/liquid chromatography (LC)-mass spectrometry (MS) was used to study the plasma metabolic profile and identify objective markers for depression and metabolic pathway variation. We recruited 379 Chinese community-dwelling individuals aged ≥ 65. Plasma samples were collected and detected by GC/LC‒MS. Orthogonal partial least squares discriminant analysis and a heatmap were utilized to distinguish the metabolites. Receiver operating characteristic curves were constructed to evaluate the diagnostic value of these differential metabolites. Additionally, metabolic pathway enrichment was performed to reveal metabolic pathway variation. According to our standard, 49 people were included in the depression cohort (DC), and 49 people age- and sex-matched individuals were included in the non-depression cohort (NDC). 64 metabolites identified via GC‒MS and 73 metabolites identified via LC‒MS had significant contributions to the differentiation between the DC and NDC, with VIP values > 1 and p values < 0.05. Three substances were detected by both methods: hypoxanthine, phytosphingosine, and xanthine. Furthermore, 1-(sn-glycero-3-phospho)-1D-myo-inositol had the largest area under the curve (AUC) value (AUC = 0.842). The purine metabolic pathway is the most important change in metabolic pathways. These findings show that there were differences in plasma metabolites between the depression cohort and the non-depression cohort. These identified differential metabolites may be markers of depression and can be used to study the changes in depression metabolic pathways., (© 2024. The Author(s).)

Traditional alcoholic beverages have played a significant role in the cultural, social, and culinary fabric of societies worldwide for centuries. Studying the microbial community structure and their metabolic potential in such beverages is necessary to define product quality, safety, and consistency, as well as to explore associated biotechnological applications. In the present investigation, Illumina-based (MiSeq system) whole-genome shotgun sequencing was utilized to characterize the microbial diversity and conduct predictive gene function analysis of keem, a starter culture employed by the Jaunsari tribal community in India for producing various traditional alcoholic beverages. A total of 8,665,213 sequences, with an average base length of 151 bps, were analyzed using MG-RAST. The analysis revealed the dominance of bacteria (95.81%), followed by eukaryotes (4.11%), archaea (0.05%), and viruses (0.03%). At the phylum level, Actinobacteria (81.18%) was the most abundant, followed by Firmicutes (10.56%), Proteobacteria (4.00%), and Ascomycota (3.02%). The most predominant genera were Saccharopolyspora (36.31%), followed by Brevibacterium (15.49%), Streptomyces (9.52%), Staphylococcus (8.75%), Bacillus (4.59%), and Brachybacterium (3.42%). At the species level, the bacterial, fungal, and viral populations of the keem sample could be categorized into 3347, 57, and 106 species, respectively. Various functional attributes to the sequenced data were assigned using Cluster of Orthologous Groups (COG), Non-supervised Orthologous Groups (NOG), subsystem, and KEGG Orthology (KO) annotations. The most prevalent metabolic pathways included carbohydrate, lipid, and amino acid metabolism, as well as the biosynthesis of glycans, secondary metabolites, and xenobiotic biodegradation. Given the rich microbial diversity and its associated metabolic potential, investigating the transition of keem from a traditional starter culture to an industrial one presents a compelling avenue for future research., (© 2024. The Author(s).)

Tomato (Solanum lycopersicum) is among the most important commercial horticultural crops worldwide. The crop quality and production is largely hampered due to the fungal pathogen Alternaria solani causing necrotrophic foliage early blight disease. Crop plants usually respond to the biotic challenges with altered metabolic composition and physiological perturbations. We have deciphered altered metabolite composition, modulated metabolic pathways and identified metabolite biomarkers in A. solani-challenged susceptible tomato variety Kashi Aman using Liquid Chromatography-Mass Spectrometry (LC-MS) based metabolomics. Alteration in the metabolite feature composition of pathogen-challenged (m/z 9405) and non-challenged (m/z 9667) plant leaves including 8487 infection-exclusive and 8742 non-infection exclusive features was observed. Functional annotation revealed putatively annotated metabolites and pathway mapping indicated their enrichment in metabolic pathways, biosynthesis of secondary metabolites, ubiquinone and terpenoid-quinones, brassinosteroids, steroids, terpenoids, phenylpropanoids, carotenoids, oxy/sphingolipids and metabolism of biotin and porphyrin. PCA, multivariate PLS-DA and OPLS-DA analysis showed sample discrimination. Significantly up regulated 481 and down regulated 548 metabolite features were identified based on the fold change (threshold ≥ 2.0). OPLS-DA model based on variable importance in projection (VIP scores) and FC threshold (> 2.0) revealed 41 up regulated discriminant metabolite features annotated as sphingosine, fecosterol, melatonin, serotonin, glucose 6-phosphate, zeatin, dihydrozeatin and zeatin-β-D-glucoside. Similarly, 23 down regulated discriminant metabolites included histidinol, 4-aminobutyraldehyde, propanoate, tyramine and linalool. Melatonin and serotonin in the leaves were the two indoleamines being reported for the first time in tomato in response to the early blight pathogen. Receiver operating characteristic (ROC)-based biomarker analysis identified apigenin-7-glucoside, uridine, adenosyl-homocysteine, cGMP, tyrosine, pantothenic acid, riboflavin (as up regulated) and adenosine, homocyctine and azmaline (as down regulated) biomarkers. These results could aid in the development of metabolite-quantitative trait loci (mQTL). Furthermore, stress-induced biosynthetic pathways may be the potential targets for modifications through breeding programs or genetic engineering for improving crop performance in the fields., (© 2023. The Author(s).)

Deoxycytidine analogues (dCas) are widely used for the treatment of malignant diseases. They are commonly inactivated by cytidine deaminase (CDD), or by deoxycytidine monophosphate deaminase (dCMP deaminase). Additional metabolic pathways, such as phosphorylation, can substantially contribute to their (in)activation. Here, a new technique for the analysis of these pathways in cells is described. It is based on the use of 5-ethynyl 2'-deoxycytidine (EdC) and its conversion to 5-ethynyl 2'-deoxyuridine (EdU). Its use was tested for the estimation of the role of CDD and dCMP deaminase in five cancer and four non-cancer cell lines. The technique provides the possibility to address the aggregated impact of cytidine transporters, CDD, dCMP deaminase, and deoxycytidine kinase on EdC metabolism. Using this technique, we developed a quick and cheap method for the identification of cell lines exhibiting a lack of CDD activity. The data showed that in contrast to the cancer cells, all the non-cancer cells used in the study exhibited low, if any, CDD content and their cytidine deaminase activity can be exclusively attributed to dCMP deaminase. The technique also confirmed the importance of deoxycytidine kinase for dCas metabolism and indicated that dCMP deaminase can be fundamental in dCas deamination as well as CDD. Moreover, the described technique provides the possibility to perform the simultaneous testing of cytotoxicity and DNA replication activity., (© 2023. The Author(s).)

Advanced head and neck squamous cell carcinoma (HNSCC) patients have been treated with cisplatin (CDDP) chemoradiation, and the variability of treatment effects has been attributed to single nucleotide variants (SNVs) in genes of metabolic pathways. This study investigated the roles of GSTM1, GSTT1, GSTP1 c.313A>G, XPC c.2815A>C, XPD c.934G>A and c.2251A>C, XPF c.2505T>C, ERCC1 c.354C>T, MLH1 c.93G>A, MSH2 c.211+9C>G, MSH3 c.3133G>A, EXO1 c.1765G>A, TP53 c.215G>C, CASP3 c.-1191A>G and c.-182-247G>T, FAS c.-1378G>A and c.-671A>G and FASL c.-844C>T SNVs in outcome of 109 patients treated with CDDP chemoradiation. Genotypes were identified in genomic DNA by PCR-based methods. Conventional criteria and tests analyzed response and survival. Patients with XPC c.2815AC or CC had 3.43 times more chances of presenting partial response or stable disease. Patients with FAS c.-671GG, GSTM1 present plus XPC c.2815AA, or plus XPD c.934GG, or plus XPD c.2251AA, or plus TP53 c.215GC or CC, and XPD c.2251AA plus XPF c.2505TT had up to 2.70 and 2.37 times more chances of presenting tumor progression and evolving to death, respectively. Our data indicate, for the first time, preliminary evidence that combined SNVs of CDDP metabolism act as independent prognostic factors and can be used to select patients for distinct treatments., (© 2023. Springer Nature Limited.)

Exploiting synthetic lethality is a promising strategy for developing targeted cancer therapies. However, identifying clinically significant synthetic lethal (SL) interactions among a large number of gene combinations is a challenging computational task. In this study, we developed the SL-scan pipeline based on metabolic network modeling to discover SL interaction. The SL-scan pipeline identifies the association between simulated Flux Balance Analysis knockout scores and mutation data across cancer cell lines and predicts putative SL interactions. We assessed the concordance of the SL pairs predicted by SL-scan with those of obtained from analysis of the CRISPR, shRNA, and PRISM datasets. Our results demonstrate that the SL-scan pipeline outperformed existing SL prediction approaches based on metabolic networks in identifying SL pairs in various cancers. This study emphasizes the importance of integrating multiple data sources, particularly mutation data, when identifying SL pairs for targeted cancer therapies. The findings of this study may lead to the development of novel targeted cancer therapies., (© 2023. Springer Nature Limited.)

Gloeocapsopsis dulcis strain AAB1 is an extremely xerotolerant cyanobacterium isolated from the Atacama Desert (i.e., the driest and oldest desert on Earth) that holds astrobiological significance due to its ability to biosynthesize compatible solutes at ultra-low water activities. We sequenced and assembled the G. dulcis genome de novo using a combination of long- and short-read sequencing, which resulted in high-quality consensus sequences of the chromosome and two plasmids. We leveraged the G. dulcis genome to generate a genome-scale metabolic model (iGd895) to simulate growth in silico. iGd895 represents, to our knowledge, the first genome-scale metabolic reconstruction developed for an extremely xerotolerant cyanobacterium. The model's predictive capability was assessed by comparing the in silico growth rate with in vitro growth rates of G. dulcis, in addition to the synthesis of trehalose. iGd895 allowed us to explore simulations of key metabolic processes such as essential pathways for water-stress tolerance, and significant alterations to reaction flux distribution and metabolic network reorganization resulting from water limitation. Our study provides insights into the potential metabolic strategies employed by G. dulcis, emphasizing the crucial roles of compatible solutes, metabolic water, energy conservation, and the precise regulation of reaction rates in their adaptation to water stress., (© 2023. Springer Nature Limited.)

The ocular surface (OS) enzymes are of great interest due to their potential for novel ocular drug development. We aimed first to profile and classify the enzymes of the OS to describe major biological processes and pathways that are involved in the maintenance of homeostasis. Second, we aimed to compare the enzymatic profiles between the two most common tear collection methods, capillary tubes (CT) and Schirmer strips (ScS). A comprehensive tear proteomic dataset was generated by pooling all enzymes identified from nine tear proteomic analyses of healthy subjects using mass spectrometry. In these studies, tear fluid was collected using CT (n = 4), ScS (n = 4) or both collection methods (n = 1). Classification and functional analysis of the enzymes was performed using a combination of bioinformatic tools. The dataset generated identified 1010 enzymes. The most representative classes were hydrolases (EC 3) and transferases (EC 2). Phosphotransferases, esterases and peptidases were the most represented subclasses. A large portion of the identified enzymes was common to both collection methods (n = 499). More enzymes were specifically detected in the ScS-extracted proteome. The major pathways in which the identified enzymes participate are related to the immune system and protein, carbohydrate and lipid metabolism. Metabolic processes for nucleosides, cellular amides, sugars and sulfur compounds constituted the most enriched biological processes. Knowledge of these molecules highly susceptible to pharmacological manipulation might help to predict the metabolism of ophthalmic medications and develop novel prodrug strategies as well as new drug delivery systems. Combining such extensive knowledge of the OS enzymes with new analytical approaches and techniques might create new prospects for understanding, predicting and manipulating the metabolism of ocular pharmaceuticals. Our study reports new, essential data on OS enzymes while also comparing the enzyme profiles obtained via the two most popular methods of tear collection, capillary tubes and Schirmer strips., (© 2023. Springer Nature Limited.)