Comparison of methods for cancer stem cell detection in prognosis of early stages NSCLC.

BACKGROUND: Despite advances in diagnosis and treatment in lung cancer, therapies still fail to improve patient management due to resistance mechanisms and relapses. As Cancer stem cells (CSCs) directly contribute to tumor growth and therapeutic resistance, their clinical detection represents a major challenge. However specific and additional CSC markers lack. Thus, our aim was to achieve selective detection of CSCs with specific glycan patterns and assess the CSCs burden to predict the risk of relapse in NSCLC tumors. METHODS: The lung CSCs detection and sorting with a lectin MIX were assessed and compared to CD133 in vitro. Then, its putative role as CSC biomarker was evaluated in vivo and its clinical significance on 221 NSCLC patients. RESULTS: We showed a significant CSCs enrichment in the MIX+ sorted fraction compared to CD133+ cells and confirmed its high tumorigenic capacity. The MIX prognostic value on the overall survival from early stages patients was validated suggesting its potential for detecting CSCs directly linked to tumor aggressiveness. CONCLUSION: The MIX could be more relevant for detecting and sorting CSCs than CD133. Moreover, its prognosis value could enable clinicians to better classify early-stage patients at high risk of relapse in order to tailor therapeutic decisions.

Untargeted metabolomic insights into plastisphere communities in European rivers.

Every year, rivers introduce a staggering amount of hundred kilotons of plastic into the Oceans. This plastic is inhabited by microorganisms known as the plastisphere, which can be transferred between different ecosystems through the transport of microplastics. Here, we simulated the microbial colonization of polyethylene-based plastic pellets that are classically used to manufacture large-scale plastic products. The pellets were immersed for 1 month in four to five sampling stations along the river-to-sea continuum of nine of the major European rivers. This study presents the first untargeted metabolomics analysis of the plastisphere, by using ultra high-performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-HRMS). The plastisphere metabolomes were similar in the Rhine and Rhone rivers, while being different from the Tiber and Loire rivers, which showed greater similarity to the Thames and Seine rivers. Interestingly, we found a clear distinction between plastisphere metabolomes from freshwater and marine water in most of the river-to-sea continuum, thus suggesting a complete segregation in plastisphere metabolites that is not consistent with a major transfer of microorganisms between the two contrasted ecosystems. Putative annotations of 189 discriminating metabolites suggested that lipid metabolism was significantly modulated. These results enlightened the relevance of using environmental metabolomic as complementary analysis to the current OMICs analysis.

Metabolomic prediction of breast cancer treatment induced neurological and metabolic toxicities.

BACKGROUND: Long-term treatment-related toxicities, such as neurological and metabolic toxicities, are major issues in breast cancer. We investigated the interest of metabolomic profiling to predict toxicities. METHODS: Untargeted high-resolution metabolomic profiles of 992 patients with ER+/HER2- breast cancer from the prospective CANTO cohort were acquired (n=1935 metabolites). A residual-based modeling strategy with a discovery and validation cohort was used to benchmark machine learning algorithms, taking into account confounding variables. RESULTS: Adaptive LASSO has a good predictive performance, has limited optimism bias, and allows the selection of metabolites of interest for future translational research. The addition of low-frequency metabolites and non-annotated metabolites increases the predictive power. Metabolomics adds extra performance to clinical variables to predict various neurological and metabolic toxicity profiles. CONCLUSIONS: Untargeted high-resolution metabolomics allows better toxicity prediction by considering environmental exposure, metabolites linked to microbiota, and low-frequency metabolites.

Extracellular vesicles from type-2 macrophages increase the survival of chronic lymphocytic leukemia cells ex vivo.

The resistance of Chronic Lymphocytic Leukemia (CLL) B-cells to cell death is mainly attributed to interactions within their microenvironment, where they interact with various types of cells. Within this microenvironment, CLL-B-cells produce and bind cytokines, growth factors, and extracellular vesicles (EVs). In the present study, EVs purified from nurse-like cells and M2-polarized THP1 cell (M2-THP1) cultures were added to CLL-B-cells cultures. EVs were rapidly internalized by B-cells, leading to a decrease in apoptosis (P = 0.0162 and 0.0469, respectively) and an increased proliferation (P = 0.0335 and 0.0109). Additionally, they induced an increase in the resistance of CLL-B-cells to Ibrutinib, the Bruton kinase inhibitor in vitro (P = 0.0344). A transcriptomic analysis showed an increase in the expression of anti-apoptotic gene BCL-2 (P = 0.0286) but not MCL-1 and an increase in the expression of proliferation-inducing gene APRIL (P = 0.0286) following treatment with EVs. Meanwhile, an analysis of apoptotic protein markers revealed increased amounts of IGFBP-2 (P = 0.0338), CD40 (P = 0.0338), p53 (P = 0.0219) and BCL-2 (P = 0.0338). Finally, exploration of EVs protein content by mass spectrometry revealed they carry various proteins involved in known oncogenic pathways and the RNAseq analysis of CLL-B-cells treated or not with NLCs EVs show various differentially expressed genes.

A vaccine targeting antigen-presenting cells through CD40 induces protective immunity against Nipah disease.

Nipah virus (NiV) has been recently ranked by the World Health Organization as being among the top eight emerging pathogens likely to cause major epidemics, whereas no therapeutics or vaccines have yet been approved. We report a method to deliver immunogenic epitopes from NiV through the targeting of the CD40 receptor of antigen-presenting cells by fusing a selected humanized anti-CD40 monoclonal antibody to the Nipah glycoprotein with conserved NiV fusion and nucleocapsid peptides. In the African green monkey model, CD40.NiV induces specific immunoglobulin A (IgA) and IgG as well as cross-neutralizing responses against circulating NiV strains and Hendra virus and T cell responses. Challenge experiments using a NiV-B strain demonstrate the high protective efficacy of the vaccine, with all vaccinated animals surviving and showing no significant clinical signs or virus replication, suggesting that the CD40.NiV vaccine conferred sterilizing immunity. Overall, results obtained with the CD40.NiV vaccine are highly promising in terms of the breadth and efficacy against NiV.

Change of deep subduction seismicity after a large megathrust earthquake.

Subduction zones are home to the world's largest and deepest earthquakes. Recently, large-scale interactions between shallow (0-60 km) and intermediate (80-150 km) seismicity have been evidenced during the interseismic period but also before and after megathrust earthquakes along with large-scale changes in surface motion. Large-scale deformation transients following major earthquakes have also been observed possibly due to a post-seismic change in slab pull or to a bending/unbending of the plates, which suggests the existence of interactions between the deep and shallow parts of the slab. In this study, we analyze the spatio-temporal variations of the declustered seismicity in Japan from 2000 to 2011/3/11 and from 2011/3/11 to 2013/3/11. We observe that the background rate of the intermediate to deep (150-450 km) seismicity underwent a deceleration of 55% south of the rupture zone and an acceleration of 30% north of it after the Tohoku-oki earthquake, consistent with the GPS surface displacements. This shows how a megathrust earthquake can affect the stress state of the slab over a 2500 km lateral range and a large depth range, demonstrating that earthquakes interact at a much greater scale than the surrounding rupture zone usually considered.

Transcriptomic monitoring of Douglas-fir heartwood formation.

OBJECTIVES: Molecular cues linked to heartwood formation open new (complementary) perspectives to genetic breeding programs of Douglas-fir, a tree species largely cultivated in Europe for the natural durability and civil engineering properties of its wood. DATA DESCRIPTION: RNAs from a single genotype of Douglas-fir, extracted from three distinct wood zones (outer sapwood, inner sapwood and transition zone) at four vegetative seasons to generate an extensive RNA-seq dataset used to apprehend the in-wood dynamic and seasonality of heartwood formation in this hardwood model species. Previously published data collected on somatic embryos of the same genotype could be merged with the present dataset to upgrade grade the Douglas-fir reference transcriptome.

SCEP1 and SCEP2 are two new components of the synaptonemal complex central element.

The synaptonemal complex (SC) is a proteinaceous structure that forms between homologous chromosomes during meiosis prophase. The SC is widely conserved across species, but its structure and roles during meiotic recombination are still debated. While the SC central region is made up of transverse filaments and central element proteins in mammals and fungi, few central element proteins have been identified in other species. Here we report the identification of two coiled-coil proteins, SCEP1 and SCEP2, that form a complex and localize at the centre of the Arabidopsis thaliana SC. In scep1 and scep2 mutants, chromosomes are aligned but not synapsed (the ZYP1 transverse filament protein is not loaded), crossovers are increased compared with the wild type, interference is lost and heterochiasmy is strongly reduced. We thus report the identification of two plant SC central elements, and homologues of these are found in all major angiosperm clades.

HEIP1 is required for efficient meiotic crossover implementation and is conserved from plants to humans.

Crossovers (CO) shuffle genetic information and physically connect homologous chromosomal pairs, ensuring their balanced segregation during meiosis. COs arising from the major class I pathway require the activity of the well-conserved group of ZMM proteins, which, in conjunction with MLH1, facilitate the maturation of DNA recombination intermediates specifically into COs. The HEI10 Interacting Protein 1 (HEIP1) was identified in rice and proposed to be a new, plant-specific member of the ZMM group. Here, we establish and decipher the function of the Arabidopsis thaliana HEIP1 homolog in meiotic crossover formation and report its wide conservation in eukaryotes. We show that the loss of Arabidopsis HEIP1 elicits a marked reduction in meiotic COs and their redistribution toward chromosome ends. Epistasis analysis showed that AtHEIP1 acts specifically in the class I CO pathway. Further, we show that HEIP1 acts both prior to crossover designation, as the number of MLH1 foci is reduced in heip1, and at the maturation step of MLH1-marked sites into COs. Despite the HEIP1 protein being predicted to be primarily unstructured and very divergent at the sequence level, we identified homologs of HEIP1 in an extensive range of eukaryotes, including mammals.

Clinical management of molecular alterations identified by high throughput sequencing in patients with advanced solid tumors in treatment failure: Real-world data from a French hospital.

Background: In the context of personalized medicine, screening patients to identify targetable molecular alterations is essential for therapeutic decisions such as inclusion in clinical trials, early access to therapies, or compassionate treatment. The objective of this study was to determine the real-world impact of routine incorporation of FoundationOne analysis in cancers with a poor prognosis and limited treatment options, or in those progressing after at least one course of standard therapy. Methods: A FoundationOneCDx panel for solid tumor or liquid biopsy samples was offered to 204 eligible patients. Results: Samples from 150 patients were processed for genomic testing, with a data acquisition success rate of 93%. The analysis identified 2419 gene alterations, with a median of 11 alterations per tumor (range, 0-86). The most common or likely pathogenic variants were on TP53, TERT, PI3KCA, CDKN2A/B, KRAS, CCDN1, FGF19, FGF3, and SMAD4. The median tumor mutation burden was three mutations/Mb (range, 0-117) in 143 patients with available data. Of 150 patients with known or likely pathogenic actionable alterations, 13 (8.6%) received matched targeted therapy. Sixty-nine patients underwent Molecular Tumor Board, which resulted in recommendations in 60 cases. Treatment with genotype-directed therapy had no impact on overall survival (13 months vs. 14 months; p = 0.95; hazard ratio = 1.04 (95% confidence interval, 0.48-2.26)]. Conclusions: This study highlights that an organized center with a Multidisciplinary Molecular Tumor Board and an NGS screening system can obtain satisfactory results comparable with those of large centers for including patients in clinical trials.

Comparative analysis of histopathological parameters, genome-wide copy number alterations, and variants in genes involved in cell cycle regulation in chordomas of the skull base and sacrum.

Chordomas are rare tumors of the axial skeleton that are refractory to conventional therapy. Few studies have compared the morphological and molecular characteristics of chordomas according to the skull base and sacral locations. Histopathological data and changes revealed by array comparative genomic hybridization (CGH) and next-generation sequencing (NGS) of cell cycle regulation genes were analyzed for 28 skull base (SBCs) and 15 sacral (SC) chordomas. All cases were conventional chordomas. SBCs were significantly more frequent in patients aged <40 years and SCs predominated in patients aged >60 years. Mitotic indices ≥2 mitoses/10 high-power fields were correlated with high degrees of nuclear atypia and Ki67 labeling indices ≥6%. We identified 321 genomic positions, and copy number variation losses were more frequent than gain. Moreover, we report a panel of 85 genetic variants of cell cycle genes and the presence of molecular clusters for chordoma as well in CGH as in NGS. These new data strengthen the view that the chordoma should not be considered as a single molecular entity.

Charcot-Marie-Tooth-1A and sciatic nerve crush rat models: insights from proteomics.

The sensorimotor and histological aspects of peripheral neuropathies were already studied by our team in two rat models: the sciatic nerve crush and the Charcot-Marie-Tooth-1A disease. In this study, we sought to highlight and compare the protein signature of these two pathological situations. Indeed, the identification of protein profiles in diseases can play an important role in the development of pharmacological targets. In fact, Charcot-Marie-Tooth-1A rats develop motor impairments that are more severe in the hind limbs. Therefore, for the first time, protein expression in sciatic nerve of Charcot-Marie-Tooth-1A rats was examined. First, distal sciatic nerves were collected from Charcot-Marie-Tooth-1A and uninjured wild-type rats aged 3 months. After protein extraction, sequential window acquisition of all theoretical fragment ion spectra liquid chromatography and mass spectrometry was employed. 445 proteins mapped to Swiss-Prot or trEMBL Uniprot databases were identified and quantified. Of these, 153 proteins showed statistically significant differences between Charcot-Marie-Tooth-1A and wild-type groups. The majority of these proteins were overexpressed in Charcot-Marie-Tooth-1A. Hierarchical clustering and functional enrichment using Gene Ontology were used to group these proteins based on their biological effects concerning Charcot-Marie-Tooth-1A pathophysiology. Second, proteomic characterization of wild-type rats subjected to sciatic nerve crush was performed sequential window acquisition of all theoretical fragment ion spectra liquid chromatography and mass spectrometry. One month after injury, distal sciatic nerves were collected and analyzed as described above. Out of 459 identified proteins, 92 showed significant differences between sciatic nerve crush and the uninjured wild-type rats used in the first study. The results suggest that young adult Charcot-Marie-Tooth-1A rats (3 months old) develop compensatory mechanisms at the level of redox balance, protein folding, myelination, and axonogenesis. These mechanisms seem insufficient to hurdle the progress of the disease. Notably, response to oxidative stress appears to be a significant feature of Charcot-Marie-Tooth-1A, potentially playing a role in the pathological process. In contrast to the first experiment, the majority of the proteins that differed from wild-type were downregulated in the sciatic nerve crush group. Functional enrichment suggested that neurogenesis, response to axon injury, and oxidative stress were important biological processes. Protein analysis revealed an imperfect repair at this time point after injury and identified several distinguishable proteins. In conclusion, we suggest that peripheral neuropathies, whether of a genetic or traumatic cause, share some common pathological pathways. This study may provide directions for better characterization of these models and/or identifying new specific therapeutic targets.

Untargeted metabolomics confirms the association between plasma branched chain amino acids and residual feed intake in beef heifers.

This study explored plasma biomarkers and metabolic pathways underlying feed efficiency measured as residual feed intake (RFI) in Charolais heifers. A total of 48 RFI extreme individuals (High-RFI, n = 24; Low-RFI, n = 24) were selected from a population of 142 heifers for classical plasma metabolite and hormone quantification and plasma metabolomic profiling through untargeted LC-MS. Most efficient heifers (Low-RFI) had greater (P = 0.03) plasma concentrations of IGF-1 and tended to have (P = 0.06) a lower back fat depth compared to least efficient heifers. However, no changes were noted (P ≥ 0.10) for plasma concentrations of glucose, insulin, non-esterified fatty acids, ß-hydroxybutyrate and urea. The plasma metabolomic dataset comprised 3,457 ions with none significantly differing between RFI classes after false discovery rate correction (FDR > 0.10). Among the 101 ions having a raw P < 0.05 for the RFI effect, 13 were putatively annotated by using internal databases and 6 compounds were further confirmed with standards. Metabolic pathway analysis from these 6 confirmed compounds revealed that the branched chain amino acid metabolism was significantly (FDR < 0.05) impacted by the RFI classes. Our results confirmed for the first time in beef heifers previous findings obtained in male beef cattle and pointing to changes in branched-chain amino acids metabolism along with that of body composition as biological mechanisms related to RFI. Further studies are warranted to ascertain whether there is a cause-and-effect relationship between these mechanisms and RFI.

Joint control of meiotic crossover patterning by the synaptonemal complex and HEI10 dosage.

Meiotic crossovers are limited in number and are prevented from occurring close to each other by crossover interference. In many species, crossover number is subject to sexual dimorphism, and a lower crossover number is associated with shorter chromosome axes lengths. How this patterning is imposed remains poorly understood. Here, we show that overexpression of the Arabidopsis pro-crossover protein HEI10 increases crossovers but maintains some interference and sexual dimorphism. Disrupting the synaptonemal complex by mutating ZYP1 also leads to an increase in crossovers but, in contrast, abolishes interference and disrupts the link between chromosome axis length and crossovers. Crucially, combining HEI10 overexpression and zyp1 mutation leads to a massive and unprecedented increase in crossovers. These observations support and can be predicted by, a recently proposed model in which HEI10 diffusion along the synaptonemal complex drives a coarsening process leading to well-spaced crossover-promoting foci, providing a mechanism for crossover patterning.

Detection of Glycosylated Markers From Cancer Stem Cells With ColoSTEM Dx Kit for Earlier Prediction of Colon Cancer Aggressiveness.

Nowadays, colon cancer prognosis still difficult to predict, especially in the early stages. Recurrences remain elevated, even in the early stages after curative surgery. Carcidiag Biotechnologies has developed an immunohistochemistry (IHC) kit called ColoSTEM Dx, based on a MIX of biotinylated plant lectins that specifically detects colon cancer stem cells (CSCs) through glycan patterns that they specifically (over)express. A retrospective clinical study was carried out on tumor tissues from 208 non-chemotherapeutic-treated and 21 chemotherapeutic-treated patients with colon cancer, which were stained by IHC with the MIX. Clinical performances of the kit were determined, and prognostic and predictive values were evaluated. With 78.3% and 70.6% of diagnostic sensitivity and specificity respectively, our kit shows great clinical performances. Moreover, patient prognosis is significantly poorer when the MIX staining is "High" compared to "Low", especially at 5-years of overall survival and for early stages. The ColoSTEM Dx kit allows an earlier and a more precise determination of patients' outcome. Thus, it affords an innovating clinical tool for predicting tumor aggressiveness earlier and determining prognosis value regarding therapeutic response in colon cancer patients.

The megabase-scale crossover landscape is largely independent of sequence divergence.

Meiotic recombination frequency varies along chromosomes and strongly correlates with sequence divergence. However, the causal relationship between recombination landscapes and polymorphisms is unclear. Here, we characterize the genome-wide recombination landscape in the quasi-absence of polymorphisms, using Arabidopsis thaliana homozygous inbred lines in which a few hundred genetic markers were introduced through mutagenesis. We find that megabase-scale recombination landscapes in inbred lines are strikingly similar to the recombination landscapes in hybrids, with the notable exception of heterozygous large rearrangements where recombination is prevented locally. In addition, the megabase-scale recombination landscape can be largely explained by chromatin features. Our results show that polymorphisms are not a major determinant of the shape of the megabase-scale recombination landscape but rather favour alternative models in which recombination and chromatin shape sequence divergence across the genome.

APOK3, a pollen killer antidote in Arabidopsis thaliana.

The principles of heredity state that the two alleles carried by a heterozygote are equally transmitted to the progeny. However, genomic regions that escape this rule have been reported in many organisms. It is notably the case of genetic loci referred to as gamete killers, where one allele enhances its transmission by causing the death of the gametes that do not carry it. Gamete killers are of great interest, particularly to understand mechanisms of evolution and speciation. Although being common in plants, only a few, all in rice, have so far been deciphered to the causal genes. Here, we studied a pollen killer found in hybrids between two accessions of Arabidopsis thaliana. Exploring natural variation, we observed this pollen killer in many crosses within the species. Genetic analyses revealed that three genetically linked elements are necessary for pollen killer activity. Using mutants, we showed that this pollen killer works according to a poison-antidote model, where the poison kills pollen grains not producing the antidote. We identified the gene encoding the antidote, a chimeric protein addressed to mitochondria. De novo genomic sequencing in 12 natural variants with different behaviors regarding the pollen killer revealed a hyper variable locus, with important structural variations particularly in killer genotypes, where the antidote gene recently underwent duplications. Our results strongly suggest that the gene has newly evolved within A. thaliana. Finally, we identified in the protein sequence polymorphisms related to its antidote activity.

PeakForest: a multi-platform digital infrastructure for interoperable metabolite spectral data and metadata management.

INTRODUCTION: Accuracy of feature annotation and metabolite identification in biological samples is a key element in metabolomics research. However, the annotation process is often hampered by the lack of spectral reference data in experimental conditions, as well as logistical difficulties in the spectral data management and exchange of annotations between laboratories. OBJECTIVES: To design an open-source infrastructure allowing hosting both nuclear magnetic resonance (NMR) and mass spectra (MS), with an ergonomic Web interface and Web services to support metabolite annotation and laboratory data management. METHODS: We developed the PeakForest infrastructure, an open-source Java tool with automatic programming interfaces that can be deployed locally to organize spectral data for metabolome annotation in laboratories. Standardized operating procedures and formats were included to ensure data quality and interoperability, in line with international recommendations and FAIR principles. RESULTS: PeakForest is able to capture and store experimental spectral MS and NMR metadata as well as collect and display signal annotations. This modular system provides a structured database with inbuilt tools to curate information, browse and reuse spectral information in data treatment. PeakForest offers data formalization and centralization at the laboratory level, facilitating shared spectral data across laboratories and integration into public databases. CONCLUSION: PeakForest is a comprehensive resource which addresses a technical bottleneck, namely large-scale spectral data annotation and metabolite identification for metabolomics laboratories with multiple instruments. PeakForest databases can be used in conjunction with bespoke data analysis pipelines in the Galaxy environment, offering the opportunity to meet the evolving needs of metabolomics research. Developed and tested by the French metabolomics community, PeakForest is freely-available at https://github.com/peakforest .

Quantitative analysis of the formation of nucleoprotein complexes between HIV-1 Gag protein and genomic RNA using transmission electron microscopy.

In HIV, the polyprotein precursor Gag orchestrates the formation of the viral capsid. In the current view of this viral assembly, Gag forms low-order oligomers that bind to the viral genomic RNA triggering the formation of high-ordered ribonucleoprotein complexes. However, this assembly model was established using biochemical or imaging methods that do not describe the cellular location hosting Gag-gRNA complex nor distinguish gRNA packaging in single particles. Here, we studied the intracellular localization of these complexes by electron microscopy and monitored the distances between the two partners by morphometric analysis of gold beads specifically labeling Gag and gRNA. We found that formation of these viral clusters occurred shortly after the nuclear export of the gRNA. During their transport to the plasma membrane, the distance between Gag and gRNA decreases together with an increase of gRNA packaging. Point mutations in the zinc finger patterns of the nucleocapsid domain of Gag caused an increase in the distance between Gag and gRNA as well as a sharp decrease of gRNA packaged into virions. Finally, we show that removal of stem loop 1 of the 5'-untranslated region does not interfere with gRNA packaging, whereas combined with the removal of stem loop 3 is sufficient to decrease but not abolish Gag-gRNA cluster formation and gRNA packaging. In conclusion, this morphometric analysis of Gag-gRNA cluster formation sheds new light on HIV-1 assembly that can be used to describe at nanoscale resolution other viral assembly steps involving RNA or protein-protein interactions.

Milk metabolome reveals variations on enteric methane emissions from dairy cows fed a specific inhibitor of the methanogenesis pathway.

Metabolome profiling in biological fluids is an interesting approach for exploring markers of methane emissions in ruminants. In this study, a multiplatform metabolomics approach was used for investigating changes in milk metabolic profiles related to methanogenesis in dairy cows. For this purpose, 25 primiparous Holstein cows at similar lactation stage were fed the same diet supplemented with (treated, n = 12) or without (control, n = 13) a specific antimethanogenic additive that reduced enteric methane production by 23% with no changes in intake, milk production, and health status. The study lasted 6 wk, with sampling and measures performed in wk 5 and 6. Milk samples were analyzed using 4 complementary analytical methods, including 2 untargeted (nuclear magnetic resonance and liquid chromatography coupled to a quadrupole-time-of-flight mass spectrometer) and 2 targeted (liquid chromatography-tandem mass spectrometry and gas chromatography coupled to a flame ionization detector) approaches. After filtration, variable selection and normalization data from each analytical platform were then analyzed using multivariate orthogonal partial least square discriminant analysis. All 4 analytical methods were able to differentiate cows from treated and control groups. Overall, 38 discriminant metabolites were identified, which affected 10 metabolic pathways including methane metabolism. Some of these metabolites such as dimethylsulfoxide, dimethylsulfone, and citramalic acid, detected by nuclear magnetic resonance or liquid chromatography-mass spectrometry methods, originated from the rumen microbiota or had a microbial-host animal co-metabolism that could be associated with methanogenesis. Also, discriminant milk fatty acids detected by targeted gas chromatography were mostly of ruminal microbial origin. Other metabolites and metabolic pathways significantly affected were associated with AA metabolism. These findings provide new insight on the potential role of milk metabolites as indicators of enteric methane modifications in dairy cows.