Multi-omics Analysis Research Articles

Multi-omics in MECP2 duplication syndrome patients and carriers.

MECP2 duplication syndrome (MDS) is an X-linked neurodevelopmental disorder caused by the gain of dose of at least the genes MECP2 and IRAK1 and is characterised by intellectual disability (ID), developmental delay, hypotonia, epilepsy and recurrent infections. It mainly affects males, and females can be affected or asymptomatic carriers. Rett syndrome (RTT) is mainly triggered by loss of function mutations in MECP2 and is a well described syndrome that presents ID, epilepsy, lack of purposeful hand use and impaired speech, among others. As a result of implementing omics technology, altered biological pathways in human RTT samples have been reported, but such molecular characterisation has not been performed in patients with MDS. We gathered human skin fibroblasts from 17 patients with MDS, 10 MECP2 duplication carrier mothers and 21 patients with RTT, and performed multi-omics (RNAseq and proteomics) analysis. Here, we provide a thorough description and compare the shared and specific dysregulated biological processes between the cohorts. We also highlight the genes TMOD2, SRGAP1, COPS2, CNPY2, IGF2BP1, MOB2, VASP, FZD7, ECSIT and KIF3B as biomarker and therapeutic target candidates due to their implication in neuronal functions. Defining the RNA and protein profiles has shown that our four cohorts are less alike than expected by their shared phenotypes.

Trauma patients with type O blood exhibit unique multi-omics signature with decreased lectin pathway of complement levels.

Patients with type O blood may have an increased risk of hemorrhagic complications due to lower baseline levels of von Willebrand Factor (vWF) and factor VIII, but the transition to a mortality difference in trauma is less clear. We hypothesized that type O trauma patients will have differential proteomic and metabolomic signatures in response to trauma beyond vWF and FVIII alone. Patients meeting the highest level of trauma activation criteria were prospectively enrolled. Blood samples were collected upon arrival to the emergency department. Proteomic and metabolomic (multi-omics) analyses of these samples were performed using liquid chromatography-mass spectrometry. Demographic, clinical, and multi-omics data were compared between patients with type O blood versus all other patients. There were 288 patients with multi-omics data; 146 (51%) had type O blood. Demographics, injury patterns, and initial vital signs and laboratory measurements were not different between groups. Type O patients had increased lengths of stay (7 vs. 6 days, p = 0.041) and a trend towards decreased mortality secondary to traumatic brain injury compared to other causes (TBI, 44.4 % vs. 87.5%, p = 0.055). Type O patients had decreased levels of mannose-binding lectin (MBL) and MBL associated serine proteases 1 and 2 which are required for the initiation of the lectin pathway of complement activation. Type O patients also had metabolite differences signifying energy metabolism and mitochondrial dysfunction. Blood type O patients have a unique multi-omics signature, including decreased levels of proteins required to activate the lectin complement pathway. This may lead to overall decreased levels of complement activation and decreased systemic inflammation in the acute phase possibly leading to a survival advantage, especially in TBI. However, this may later impair healing. Future work will need to confirm these associations, and animal studies are needed to test therapeutic targets. Retrospective Comparative Study, Level IV.

MSphere of Influence: Retreading old ground-the beauty in multi-omic data sets.

Ethan L. Morgan works on human papillomaviruses (HPVs), with a specific interest in identifying how HPV induces tumor formation. In this mSphere of Influence article, he reflects on how three papers influenced him. "Comprehensive genomic characterization of head and neck squamous cell carcinomas" (The Cancer Genome Atlas Network, Nature 517:576-582, 2015, https://doi.org/10.1038/nature14129) and "Integrated genomic and molecular characterization of cervical cancer" (The Cancer Genome Atlas Network, Nature 543: 378-384, 2017, https://doi.org/10.1038/nature21386) showed him the power behind comprehensive multi-omic analyses to understand disease biology, while "Human papillomavirus E7 oncoprotein targets RNF168 to hijack the host DNA damage response" (J. Sitz et al., Proc Natl Acad Sci U S A 116:19552-19562, 2019, https://doi.org/10.1073/pnas.1906102116) reinforced how this can be used to undercover potential new drug targets in HPV-associated disease.

Machine Learning-Based Integrated Multiomics Characterization of Colorectal Cancer Reveals Distinctive Metabolic Signatures.

The metabolic signature identification of colorectal cancer is critical for its early diagnosis and therapeutic approaches that will significantly block cancer progression and improve patient survival. Here, we combined an untargeted metabolic analysis strategy based on internal extractive electrospray ionization mass spectrometry and the machine learning approach to analyze metabolites in 173 pairs of cancer samples and matched normal tissue samples to build robust metabolic signature models for diagnostic purposes. Screening and independent validation of metabolic signatures from colorectal cancers via machine learning methods (Logistic Regression_L1 for feature selection and eXtreme Gradient Boosting for classification) was performed to generate a panel of seven signatures with good diagnostic performance (the accuracy of 87.74%, sensitivity of 85.82%, and specificity of 89.66%). Moreover, seven signatures were evaluated according to their ability to distinguish between cancer and normal tissues, with the metabolic molecule PC (30:0) showing good diagnostic performance. In addition, genes associated with PC (30:0) were identified by multiomics analysis (combining metabolic data with transcriptomic data analysis) and our results showed that PC (30:0) could promote the proliferation of colorectal cancer cell SW480, revealing the correlation between genetic changes and metabolic dysregulation in cancer. Overall, our results reveal potential determinants affecting metabolite dysregulation, paving the way for a mechanistic understanding of altered tissue metabolites in colorectal cancer and design interventions for manipulating the levels of circulating metabolites.

Multi-omics technologies and analyses provide the biological insights and therapeutic strategies for rare tumors

Multi-omics technologies and analyses provide the biological insights and therapeutic strategies for rare tumors

Valine induces inflammation and enhanced adipogenesis in lean mice by multi-omics analysis

IntroductionThe branched-chain amino acids (BCAAs) are essential to mammalian growth and development but aberrantly elevated in obesity and diabetes. Each BCAA has an independent and specific physio-biochemical effect on the host. However, the exact molecular mechanism of the detrimental effect of valine on metabolic health remains largely unknown.Methods and resultsThis study showed that for lean mice treated with valine, the hepatic lipid metabolism and adipogenesis were enhanced, and the villus height and crypt depth of the ileum were significantly increased. Transcriptome profiling on white and brown adipose tissues revealed that valine disturbed multiple signaling pathways (e.g., inflammation and fatty acid metabolism). Integrative cecal metagenome and metabolome analyses found that abundances of Bacteroidetes decreased, but Proteobacteria and Helicobacter increased, respectively; and 87 differential metabolites were enriched in several molecular pathways (e.g., inflammation and lipid and bile acid metabolism). Furthermore, abundances of two metabolites (stercobilin and 3-IAA), proteins (AMPK/pAMPK and SCD1), and inflammation and adipogenesis-related genes were validated.DiscussionValine treatment affects the intestinal microbiota and metabolite compositions, induces gut inflammation, and aggravates hepatic lipid deposition and adipogenesis. Our findings provide novel insights into and resources for further exploring the molecular mechanism and biological function of valine on lipid metabolism.

Examining the Effects of Nutrient Supplementation on Metabolic Pathways via Mitochondrial Ferredoxin in Aging Ovaries

As women age, oocytes are susceptible to a myriad of dysfunctions, including mitochondrial dysfunction, impaired DNA repair mechanisms, epigenetic alterations, and metabolic disturbances, culminating in reduced fertility rates among older individuals. Ferredoxin (FDX) represents a highly conserved iron–sulfur (Fe–S) protein essential for electron transport across multiple metabolic pathways. Mammalian mitochondria house two distinct ferredoxins, FDX1 and FDX2, which share structural similarities and yet perform unique functions. In our investigation into the regulatory mechanisms governing ovarian aging, we employed a comprehensive multi-omics analysis approach, integrating spatial transcriptomics, single-cell RNA sequencing, human ovarian pathology, and clinical biopsy data. Previous studies have highlighted intricate interactions involving excessive lipid peroxide accumulation, redox-induced metal ion buildup, and alterations in cellular energy metabolism observed in aging cells. Through a multi-omics analysis, we observed a notable decline in the expression of the critical gene FDX1 as ovarian age progressed. This observation prompted speculation regarding FDX1’s potential as a promising biomarker for ovarian aging. Following this, we initiated a clinical trial involving 70 patients with aging ovaries. These patients were administered oral nutritional supplements consisting of DHEA, ubiquinol CoQ10, and Cleo-20 T3 for a period of two months to evaluate alterations in energy metabolism regulated by FDX1. Our results demonstrated a significant elevation in FDX1 levels among participants receiving nutritional supplementation. We hypothesize that these nutrients potentiate mitochondrial tricarboxylic acid cycle (TCA) activity or electron transport chain (ETC) efficiency, thereby augmenting FDX1 expression, an essential electron carrier in metabolic pathways, while concurrently mitigating lipid peroxide accumulation and cellular apoptosis. In summary, our findings underscore the potential of nutritional intervention to enhance in vitro fertilization outcomes in senescent cells by bolstering electron transport proteins, thus optimizing energy metabolism and improving oocyte quality in aging women.

Transcriptomic and metabolomic correlation analysis: effect of initial SO2 addition on higher alcohol synthesis in Saccharomyces cerevisiae and identification of key regulatory genes

IntroductionHigher alcohols are volatile compounds produced during alcoholic fermentation that affect the quality and safety of the final product. This study used a correlation analysis of transcriptomics and metabolomics to study the impact of the initial addition of SO2 (30, 60, and 90 mg/L) on the synthesis of higher alcohols in Saccharomyces cerevisiae EC1118a and to identify key genes and metabolic pathways involved in their metabolism.MethodsTranscriptomics and metabolomics correlation analyses were performed and differentially expressed genes (DEGs) and differential metabolites were identified. Single-gene knockouts for targeting genes of important pathways were generated to study the roles of key genes involved in the regulation of higher alcohol production.ResultsWe found that, as the SO2 concentration increased, the production of total higher alcohols showed an overall trend of first increasing and then decreasing. Multi-omics correlation analysis revealed that the addition of SO2 affected carbon metabolism (ko01200), pyruvate metabolism (ko00620), glycolysis/gluconeogenesis (ko00010), the pentose phosphate pathway (ko00030), and other metabolic pathways, thereby changing the precursor substances. The availability of SO2 indirectly affects the formation of higher alcohols. In addition, excessive SO2 affected the growth of the strain, leading to the emergence of a lag phase. We screened the ten most likely genes and constructed recombinant strains to evaluate the impact of each gene on the formation of higher alcohols. The results showed that ADH4, SER33, and GDH2 are important genes of alcohol metabolism in S. cerevisiae. The isoamyl alcohol content of the EC1118a-ADH4 strain decreased by 21.003%; The isobutanol content of the EC1118a-SER33 strain was reduced by 71.346%; and the 2-phenylethanol content of EC1118a-GDH2 strain was reduced by 25.198%.ConclusionThis study lays a theoretical foundation for investigating the mechanism of initial addition of SO2 in the synthesis of higher alcohols in S. cerevisiae, uncovering DEGs and key metabolic pathways related to the synthesis of higher alcohols, and provides guidance for regulating these mechanisms.

Integrative Multi-Omics Analysis for Etiology Classification and Biomarker Discovery in Stroke: Advancing towards Precision Medicine

Recent advancements in high-throughput omics technologies have opened new avenues for investigating stroke at the molecular level and elucidating the intricate interactions among various molecular components. We present a novel approach for multi-omics data integration on knowledge graphs and have applied it to a stroke etiology classification task of 30 stroke patients through the integrative analysis of DNA methylation and mRNA, miRNA, and circRNA. This approach has demonstrated promising performance as compared to other existing single technology approaches.

Context-dependent role of trisomy 6 in myelodysplastic neoplasms and acute myeloid leukemia: a multi-omics analysis.

Context-dependent role of trisomy 6 in myelodysplastic neoplasms and acute myeloid leukemia: a multi-omics analysis.

CsMIEL1 effectively inhibits the accumulation of anthocyanins under low temperatures in tea plants (Camelliasinensis)

Tea is one of the most prevalent non-alcoholic beverages. The leaves of tea plants hyperaccumulate anthocyanins under cold stress, resulting in enhanced bitterness. Previously, we determined that the RING-type E3 ubiquitin ligase CsMIEL1 from the tea plant (Camellia sinensis (L.) O. Kuntze) is involved in the response to stress conditions. This study aimed to determine the role of CsMIEL1 in anthocyanin accumulation at the post-translational modification level. The results showed that the heterologous expression of CsMIEL1 led to an 86% decrease in anthocyanin levels, resulting in a significant decrease in the mRNA levels of related genes in Arabidopsis at low temperatures but no significant differences in other phenotypes. Furthermore, multi-omics analysis and yeast two-hybrid library screening were performed to identify potential downstream targets of CsMIEL1. The results showed that the overexpression of CsMIEL1 resulted in 45% (448) of proteins being differentially expressed, of which 8% (36) were downregulated in A.thaliana, and most of these differentially expressed proteins (DEPs) were clustered in the plant growth and secondary metabolic pathways. Among the 71 potential targets that may interact with CsMIEL1, CsMYB90 and CsGSTa, which are related to anthocyanin accumulation, were selected. In subsequent analyses, these two proteins were verified to interact with CsMIEL1 via yeast two-hybrid (Y2H) and pull-down analyses in vitro. In summary, we explored the potential mechanism by which the E3 ligase relieves anthocyanin hyperaccumulation at low temperatures in tea plants. These results provide a new perspective on the mechanisms of anthocyanin regulation and the molecular breeding of tea plants.

Graph machine learning for integrated multi-omics analysis.

Multi-omics experiments at bulk or single-cell resolution facilitate the discovery of hypothesis-generating biomarkers for predicting response to therapy, as well as aid in uncovering mechanistic insights into cellular and microenvironmental processes. Many methods for data integration have been developed for the identification of key elements that explain or predict disease risk or other biological outcomes. The heterogeneous graph representation of multi-omics data provides an advantage for discerning patterns suitable for predictive/exploratory analysis, thus permitting the modeling of complex relationships. Graph-based approaches-including graph neural networks-potentially offer a reliable methodological toolset that can provide a tangible alternative to scientists and clinicians that seek ideas and implementation strategies in the integrated analysis of their omics sets for biomedical research. Graph-based workflows continue to push the limits of the technological envelope, and this perspective provides a focused literature review of research articles in which graph machine learning is utilized for integrated multi-omics data analyses, with several examples that demonstrate the effectiveness of graph-based approaches.

Integrated multi-omics approach reveals the role of striated muscle preferentially expressed protein kinase in skeletal muscle including its relationship with myospryn complex.

Autosomal-recessive mutations in SPEG (striated muscle preferentially expressed protein kinase) have been linked to centronuclear myopathy with or without dilated cardiomyopathy (CNM5). Loss of SPEG is associated with defective triad formation, abnormal excitation-contraction coupling, calcium mishandling and disruption of the focal adhesion complex in skeletal muscles. To elucidate the underlying molecular pathways, we have utilized multi-omics tools and analysis to obtain a comprehensive view of the complex biological processes and molecular functions. Skeletal muscles from 2-month-old SPEG-deficient (Speg-CKO) and wild-type (WT) mice were used for RNA sequencing (n=4 per genotype) to profile transcriptomics and mass spectrometry (n=4 for WT; n=3 for Speg-CKO mice) to profile proteomics and phosphoproteomics. In addition, interactomics was performed using the SPEG antibody on pooled muscle lysates (quadriceps, gastrocnemius and triceps) from WT and Speg-CKO mice. Based on the multi-omics results, we performed quantitative real-time PCR, co-immunoprecipitation and immunoblot to verify the findings. We identified that SPEG interacts with myospryn complex proteins CMYA5, FSD2 and RyR1, which are critical for triad formation, and that SPEG deficiency results in myospryn complex abnormalities (protein levels decreased to 22±3% for CMYA5 [P<0.05] and 18±3% for FSD2 [P<0.01]). Furthermore, SPEG phosphorylates RyR1 at S2902 (phosphorylation level decreased to 55±15% at S2902 in Speg-CKO mice; P<0.05), and its loss affects JPH2 phosphorylation at multiple sites (increased phosphorylation at T161 [1.90±0.24-fold], S162 [1.61±0.37-fold] and S165 [1.66±0.13-fold]; decreased phosphorylation at S228 and S231 [39±6%], S234 [50±12%], S593 [48±3%] and S613 [66±10%]; P<0.05 for S162 and P<0.01 for other sites). On analysing the transcriptome, the most dysregulated pathways affected by SPEG deficiency included extracellular matrix-receptor interaction (P<1e-15) and peroxisome proliferator-activated receptor signalling (P<9e-14). We have elucidated the critical role of SPEG in the triad as it works closely with myospryn complex proteins (CMYA5, FSD2 and RyR1), it regulates phosphorylation levels of various residues in JPH2 and S2902 in RyR1, and its deficiency is associated with dysregulation of several pathways. The study identifies unique SPEG-interacting proteins and their phosphorylation functions and emphasizes the importance of using a multi-omics approach to comprehensively evaluate the molecular function of proteins involved in various genetic disorders.

Functional divergence in orthologous transcription factors: insights from AtCBF2/3/1 and OsDREB1C.

Despite traditional beliefs of orthologous genes maintaining similar functions across species, growing evidence points to their potential for functional divergence. C-repeat binding factors/dehydration-responsive element binding protein 1s (CBFs/DREB1s) are critical in cold acclimation, with their overexpression enhancing stress tolerance but often constraining plant growth. In contrast, a recent study unveiled a distinctive role of rice OsDREB1C in elevating nitrogen use efficiency (NUE), photosynthesis, and grain yield, implying functional divergence within the CBF/DREB1 orthologs across species. Here, we delve into divergent molecular mechanisms of OsDREB1C and AtCBF2/3/1 by exploring their evolutionary trajectories across rice and Arabidopsis genomes, regulatomes, and transcriptomes. Evolutionary scrutiny shows discrete clades for OsDREB1C and AtCBF2/3/1, with the Poaceae-specific DREB1C clade mediated by a transposon event. Genome-wide binding profiles highlight OsDREB1C's preference for GCCGAC compared to AtCBF2/3/1's preference for A/GCCGAC, a distinction determined by R12 in the OsDREB1C AP2/ERF domain. Cross-species multi-omic analyses reveal shared gene orthogroups (OGs) and underscore numerous specific OGs uniquely bound and regulated by OsDREB1C, implicated in NUE, photosynthesis, and early flowering, or by AtCBF2/3/1, engaged in hormone and stress responses. This divergence arises from gene gains/losses (∼16.7‒25.6%) and expression reprogramming (∼62.3‒66.2%) of OsDREB1C- and AtCBF2/3/1-regulated OGs during the extensive evolution following the rice-Arabidopsis split. Our findings illustrate the regulatory evolution of OsDREB1C and AtCBF2/3/1 at a genomic scale, providing insights on the functional divergence of orthologous transcription factors following gene duplications across species.

Unlocking Nutritional Potential: Multi-OMICS Strategies for Enhancing Millet Nutritional Traits

Millet grains have long been recognized for their nutritional significance, serving as staple foods for millions around the world. However, unlocking their full nutritional potential remains a crucial challenge. In this study, we explore the application of multi-OMICS (genomics, transcriptomics, proteomics, metabolomics, and phenomics) strategies to enhance the nutritional traits of millet grains. By integrating comprehensive molecular datasets, we aim to elucidate the genetic and biochemical pathways governing key nutritional attributes such as protein content, amino acid composition, micronutrient density, and antioxidant capacity in millets. Through targeted breeding and biotechnological interventions informed by multi-OMICS analyses, we seek to develop improved millet varieties with enhanced nutritional profiles and agronomic performance. This interdisciplinary approach holds great promise for addressing malnutrition and promoting food security, particularly in regions where millets are dietary staples. By harnessing the power of multi-OMICS technologies, we aim to unleash the full nutritional potential of millets, contributing to the development of sustainable and resilient food systems for future generations.

An integrative multi-omic analysis defines gut microbiota, mycobiota, and metabolic fingerprints in ulcerative colitis patients

BackgroundUlcerative colitis (UC) is a multifactorial chronic inflammatory bowel disease (IBD) that affects the large intestine with superficial mucosal inflammation. A dysbiotic gut microbial profile has been associated with UC. Our study aimed to characterize the UC gut bacterial, fungal, and metabolic fingerprints by omic approaches.MethodsThe 16S rRNA- and ITS2-based metataxonomics and gas chromatography–mass spectrometry/solid phase microextraction (GC–MS/SPME) metabolomic analysis were performed on stool samples of 53 UC patients and 37 healthy subjects (CTRL). Univariate and multivariate approaches were applied to separated and integrated omic data, to define microbiota, mycobiota, and metabolic signatures in UC. The interaction between gut bacteria and fungi was investigated by network analysis.ResultsIn the UC cohort, we reported the increase of Streptococcus, Bifidobacterium, Enterobacteriaceae, TM7-3, Granulicatella, Peptostreptococcus, Lactobacillus, Veillonella, Enterococcus, Peptoniphilus, Gemellaceae, and phenylethyl alcohol; and we also reported the decrease of Akkermansia; Ruminococcaceae; Ruminococcus; Gemmiger; Methanobrevibacter; Oscillospira; Coprococus; Christensenellaceae; Clavispora; Vishniacozyma; Quambalaria; hexadecane; cyclopentadecane; 5-hepten-2-ol, 6 methyl; 3-carene; caryophyllene; p-Cresol; 2-butenal; indole, 3-methyl-; 6-methyl-3,5-heptadiene-2-one; 5-octadecene; and 5-hepten-2-one, 6 methyl. The integration of the multi-omic data confirmed the presence of a distinctive bacterial, fungal, and metabolic fingerprint in UC gut microbiota. Moreover, the network analysis highlighted bacterial and fungal synergistic and/or divergent interkingdom interactions.ConclusionIn this study, we identified intestinal bacterial, fungal, and metabolic UC-associated biomarkers. Furthermore, evidence on the relationships between bacterial and fungal ecosystems provides a comprehensive perspective on intestinal dysbiosis and ecological interactions between microorganisms in the framework of UC.

Multi-omics analysis of human tendon adhesion reveals that ACKR1-regulated macrophage migration is involved in regeneration

Tendon adhesion is a common complication after tendon injury with the development of accumulated fibrotic tissues without effective anti-fibrotic therapies, resulting in severe disability. Macrophages are widely recognized as a fibrotic trigger during peritendinous adhesion formation. However, different clusters of macrophages have various functions and receive multiple regulation, which are both still unknown. In our current study, multi-omics analysis including single-cell RNA sequencing and proteomics was performed on both human and mouse tendon adhesion tissue at different stages after tendon injury. The transcriptomes of over 74 000 human single cells were profiled. As results, we found that SPP1+ macrophages, RGCC+ endothelial cells, ACKR1+ endothelial cells and ADAM12+ fibroblasts participated in tendon adhesion formation. Interestingly, despite specific fibrotic clusters in tendon adhesion, FOLR2+ macrophages were identified as an antifibrotic cluster by in vitro experiments using human cells. Furthermore, ACKR1 was verified to regulate FOLR2+ macrophages migration at the injured peritendinous site by transplantation of bone marrow from Lysm-Cre;R26RtdTomato mice to lethally irradiated Ackr1−/− mice (Ackr1−/− chimeras; deficient in ACKR1) and control mice (WT chimeras). Compared with WT chimeras, the decline of FOLR2+ macrophages was also observed, indicating that ACKR1 was specifically involved in FOLR2+ macrophages migration. Taken together, our study not only characterized the fibrosis microenvironment landscape of tendon adhesion by multi-omics analysis, but also uncovered a novel antifibrotic cluster of macrophages and their origin. These results provide potential therapeutic targets against human tendon adhesion.

Multilayer regulatory landscape and new regulators identification for bud dormancy release and bud break in Populus.

For trees originating from boreal and temperate regions, the dormancy-to-active transition, also known as bud dormancy release and bud break, are crucial processes that allow trees to reactive growth in the spring. The molecular mechanisms underlying these two processes remain poorly understood. Here, through integrative multiomics analysis of the transcriptome, DNA methylome, and proteome, we gained insights into the reprogrammed cellular processes associated with bud dormancy release and bud break. Our findings revealed multilayer regulatory landscapes governing bud dormancy release and bud break regulation, providing a valuable reference framework for future functional studies. Based on the multiomics analysis, we have determined a novel long intergenic noncoding RNAnamed Phenology Responsive Intergenic lncRNA 1 (PRIR1) plays a role in the activation of bud break. that the molecular mechanism of PRIR1 has been preliminary explored, and it may partially promote bud break by activating its neighbouring gene, EXORDIUM LIKE 5 (PtEXL5), which has also been genetically confirmed as an activator for bud break. This study has revealed a lncRNA-mediated regulatory mechanism for the control of bud break in Populus, operating independently of known regulatory pathways.

Multiomics analysis identifies oxidative phosphorylation as a cancer vulnerability arising from myristoylation inhibition

BackgroundIn humans, two ubiquitously expressed N-myristoyltransferases, NMT1 and NMT2, catalyze myristate transfer to proteins to facilitate membrane targeting and signaling. We investigated the expression of NMTs in numerous cancers and found that NMT2 levels are dysregulated by epigenetic suppression, particularly so in hematologic malignancies. This suggests that pharmacological inhibition of the remaining NMT1 could allow for the selective killing of these cells, sparing normal cells with both NMTs.Methods and resultsTranscriptomic analysis of 1200 NMT inhibitor (NMTI)-treated cancer cell lines revealed that NMTI sensitivity relates not only to NMT2 loss or NMT1 dependency, but also correlates with a myristoylation inhibition sensitivity signature comprising 54 genes (MISS-54) enriched in hematologic cancers as well as testis, brain, lung, ovary, and colon cancers. Because non-myristoylated proteins are degraded by a glycine-specific N-degron, differential proteomics revealed the major impact of abrogating NMT1 genetically using CRISPR/Cas9 in cancer cells was surprisingly to reduce mitochondrial respiratory complex I proteins rather than cell signaling proteins, some of which were also reduced, albeit to a lesser extent. Cancer cell treatments with the first-in-class NMTI PCLX-001 (zelenirstat), which is undergoing human phase 1/2a trials in advanced lymphoma and solid tumors, recapitulated these effects. The most downregulated myristoylated mitochondrial protein was NDUFAF4, a complex I assembly factor. Knockout of NDUFAF4 or in vitro cell treatment with zelenirstat resulted in loss of complex I, oxidative phosphorylation and respiration, which impacted metabolomes.ConclusionsTargeting of both, oxidative phosphorylation and cell signaling partly explains the lethal effects of zelenirstat in select cancer types. While the prognostic value of the sensitivity score MISS-54 remains to be validated in patients, our findings continue to warrant the clinical development of zelenirstat as cancer treatment.

Multi-omics analysis revealed that the protein kinase MoKin1 affected the cellular response to endoplasmic reticulum stress in the rice blast fungus, Magnaporthe oryzae

BackgroundPrevious studies have shown that protein kinase MoKin1 played an important role in the growth, conidiation, germination and pathogenicity in rice blast fungus, Magnaporthe oryzae. ΔMokin1 mutant showed significant phenotypic defects and significantly reduced pathogenicity. However, the internal mechanism of how MoKin1 affected the development of physiology and biochemistry remained unclear in M. oryzae.ResultThis study adopted a multi-omics approach to comprehensively analyze MoKin1 function, and the results showed that MoKin1 affected the cellular response to endoplasmic reticulum stress (ER stress). Proteomic analysis revealed that the downregulated proteins in ΔMokin1 mutant were enriched mainly in the response to ER stress triggered by the unfolded protein. Loss of MoKin1 prevented the ER stress signal from reaching the nucleus. Therefore, the phosphorylation of various proteins regulating the transcription of ER stress-related genes and mRNA translation was significantly downregulated. The insensitivity to ER stress led to metabolic disorders, resulting in a significant shortage of carbohydrates and a low energy supply, which also resulted in severe phenotypic defects in ΔMokin1 mutant. Analysis of MoKin1-interacting proteins indicated that MoKin1 really took participate in the response to ER stress.ConclusionOur results showed the important role of protein kinase MoKin1 in regulating cellular response to ER stress, providing a new research direction to reveal the mechanism of MoKin1 affecting pathogenic formation, and to provide theoretical support for the new biological target sites searching and bio-pesticides developing.