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Stefania Mondello,1 Firas H Kobeissy,2 Yehia Mechref,2 Jingfu Zhao,3 Samer El Hayek,4 Kazem Zibara,5 Monica Moresco,6,7 Giuseppe Plazzi,6 Filomena II Cosentino,8 Raffaele Ferri8 1Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy; 2Faculty of Medicine, American University of Beirut Medical Center, Beirut, Lebanon; 3Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, TX, 79409, USA; 4Department of Psychiatry, American University of Beirut, Beirut, Lebanon; 5Department of Biology, Faculty of Sciences-I, PRASE, DSST, Lebanese University, Beirut, Lebanon; 6Department of Biomedical and Neuromotor Sciences, Alma Mater Studiorum, University of Bologna, Bologna, Italy; 7IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy; 8Sleep Research Centre, Oasi Research Institute - IRCCS, Troina, ItalyCorrespondence: Raffaele FerriSleep Research Centre, Oasi Research Institute - IRCCS, Troina, 94018, ItalyTel +39 0935 936111Fax +39 0935 936231Email rferri@oasi.en.itPurpose: We performed comparative proteomic analyses of blood of patients with RLS and healthy individuals aiming to identify potential biomarker and therapeutic target candidate for RLS.Patients and Methods: Blood serum samples from 12 patients with a clinical diagnosis of RLS (8 females and 4 males, with a mean age of 68.52 years) and 10 healthy controls (5 females and 5 males, with a mean age of 67.61 years) underwent proteomic profiling by liquid chromatography coupled with tandem mass spectrometry. Pathway analysis incorporating protein–protein interaction networks was carried out to identify pathological processes linked to the differentially expressed proteins.Results: We quantified 272 proteins in patients with RLS and healthy controls, of which 243 were shared. Five proteins – apolipoprotein C-II, leucine-rich alpha-2-glycoprotein 1, FLJ92374, extracellular matrix protein 1, and FLJ93143 – were substantially increased in RLS patients, whereas nine proteins – vitamin D-binding protein, FLJ78071, alpha-1-antitrypsin, CD5 antigen-like, haptoglobin, fibrinogen alpha chain, complement factor H-related protein 1, platelet factor 4, and plasma protease C1 inhibitor – were decreased. Bioinformatics analyses revealed that these proteins were linked to 1) inflammatory and immune response, and complement activation, 2) brain-related development, cell aging, and memory disorders, 3) pregnancy and associated complications, 4) myocardial infarction, and 5) reactive oxygen species generation and subsequent diabetes mellitus.Conclusion: Our findings shed light on the multifactorial nature of RLS and identified a set of circulating proteins that may have clinical importance as biomarkers and therapeutic targets.Keywords: idiopathic restless legs syndrome, biomarkers, LC-MS/MS, proteome, interactome

Introduction: The identification and characterization of glycopeptides through LC-MS/MS and advanced enrichment techniques are crucial for advancing clinical glycoproteomics, significantly impacting the discovery of disease biomarkers and therapeutic targets. Despite progress in enrichment methods like Lectin Affinity Chromatography (LAC), Hydrophilic Interaction Liquid Chromatography (HILIC), and Electrostatic Repulsion Hydrophilic Interaction Chromatography (ERLIC), issues with specificity, efficiency, and scalability remain, impeding thorough analysis of complex glycosylation patterns crucial for disease understanding., Areas Covered: This review explores the current challenges and innovative solutions in glycopeptide enrichment and mass spectrometry analysis, highlighting the importance of novel materials and computational advances for improving sensitivity and specificity. It outlines the potential future directions of these technologies in clinical glycoproteomics, emphasizing their transformative impact on medical diagnostics and therapeutic strategies., Expert Opinion: The application of innovative materials such as Metal-Organic Frameworks (MOFs), Covalent Organic Frameworks (COFs), functional nanomaterials, and online enrichment shows promise in addressing challenges associated with glycoproteomics analysis by providing more selective and robust enrichment platforms. Moreover, the integration of artificial intelligence and machine learning is revolutionizing glycoproteomics by enhancing the processing and interpretation of extensive data from LC-MS/MS, boosting biomarker discovery, and improving predictive accuracy, thus supporting personalized medicine.

The peanut seed coat acts as a physical and biochemical barrier against Aspergillus flavus infection; however, the nature of the inhibitory chemicals in the peanut seed coat in general is not known. This study identified and characterized peanut seed coat metabolites that inhibit A. flavus growth and aflatoxin contamination. Selected peanut accessions grown under well-watered and water-deficit conditions were assayed for A. flavus resistance, and seed coats were metabolically profiled using liquid chromatography mass spectrometry. Kyoto Encyclopedia of Genes and Genome phenylpropanoid pathway reference analysis resulted in the identification of several seed coat metabolic compounds, and ten selected metabolites were tested for inhibition of A. flavus growth and aflatoxin contamination. Radial growth bioassay demonstrated that 2,5-dihydroxybenzaldehyde inhibited A. flavus growth (98.7%) and reduced the aflatoxin contamination estimate from 994 to 1 μg/kg. Scanning electron micrographs showed distorted hyphae and conidiophores in cultures of 2,5-dihydroxybenzaldehyde-treated A. flavus , indicating its potential use for field application as well as seed coat metabolic engineering.

Gangliosides are glycosphingolipids composed of a sialylated glycan head group and a ceramide backbone. These anionic lipids form lipid rafts and play crucial roles in regulating various proteins involved in signal transduction, adhesion, and cell-cell recognition. Neuroblastoma, a pediatric cancer of the sympathetic nervous system, is treated with intensive chemotherapy, radiation, and an antibody targeting the GD2 ganglioside. Gangliosides are critical in neuroblastoma development and serve as therapeutic targets, making it essential to establish a reliable, rapid, and cost-effective method for profiling gangliosides, particularly one capable of isomeric separation of intact species. In this study, liquid chromatography-mass spectrometry (LC-MS) was optimized using standard gangliosides, followed by the optimization of sphingolipid extraction methods from cell lines by comparing Folch and absolute methanol extraction techniques. Percent recovery and the number of identified sphingolipids were used to evaluate the analytical merits of these methods. A standard gangliosides calibration curve demonstrated excellent linearity (R 2 = 0.9961-0.9975). The ZIC-HILIC column provided the best separation of ganglioside GD1 isomers with a 25 min runtime. GD1a elutes before GD1b on the ZIC-HILIC column. Absolute methanol yielded better percent recovery (96 ± 7) and identified 121 different sphingolipids, the highest number between the two extraction methods. The optimized method was applied to profile gangliosides in neuroblastoma (COG-N-683), pancreatic cancer (PSN1), breast cancer (MDA-MB-231BR), and brain tumor (CRL-1620) cell lines. The ganglioside profile of the neuroblastoma cell line COG-N-683 showed an inverse relationship between GD1 and GD2. Ceramide, Hex1Cer, GM1, and GM3 were highly abundant in CRL-1620, PSN1, and MDA-MB-231BR, respectively. These results suggest that our method provides a sensitive, reliable, and high-throughput workflow for ganglioside profiling across different cell types.

Mild cognitive impairment (MCI) is an early stage of memory loss that affects cognitive abilities with the aging of individuals, such as language or visual/spatial comprehension. MCI is considered a prodromal phase of more complicated neurodegenerative diseases such as Alzheimer's. Therefore, accurate diagnosis and better understanding of the disease prognosis will facilitate prevention of neurodegeneration. However, the existing diagnostic methods fail to provide precise and well-timed diagnoses, and the pathophysiology of MCI is not fully understood. Alterations of the serum N-glycoproteome expression could represent an essential contributor to the overall pathophysiology of neurodegenerative diseases and be used as a potential marker to assess MCI diagnosis using less invasive procedures. In this approach, we identified N-glycopeptides with different expressions between healthy and MCI patients from serum glycoproteins. Seven of the N-glycopeptides showed outstanding AUC values, among them the antithrombin-III Asn224 + 4-5-0-2 with an AUC value of 1.00 and a p value of 0.0004. According to proteomics and ingenuity pathway analysis (IPA), our data is in line with recent publications, and the glycoproteins carrying the identified N-sites play an important role in neurodegeneration., (© 2024 Wiley‐VCH GmbH.)

Prostate cancer remains a significant health challenge, being the most prevalent non-cutaneous cancer in men worldwide. This review discusses the critical advancements in biomarker discovery using single-omics and multi-omics approaches. Multi-omics, integrating genomic, transcriptomic, proteomic, metabolomic, and epigenomic data, offers a comprehensive understanding of the molecular heterogeneity of prostate cancer, leading to the identification of novel biomarkers and therapeutic targets. This holistic approach not only enhances the specificity and sensitivity of prostate cancer detection but also supports the development of personalized treatment strategies. Key studies highlighted include the identification of novel genes, genetic mutations, peptides, metabolites, and potential biomarkers through multi-omics analyses, which have shown promise in improving prostate cancer management. The integration of multi-omics in clinical practice can potentially revolutionize prostate cancer prognosis and treatment, paving the way for precision medicine. This review underscores the importance of continued research and the application of multi-omics to overcome current challenges in prostate cancer diagnosis and therapy.

Human epidermal growth factor receptor 2 (HER2) is a major driver of disease progression, treatment resistance, and worse survival for patients with various types of cancers, including prostate cancer. However, key bench studies and clinical trials have failed to evaluate the role of HER2 in prostate cancer using racially diverse experimental designs and protocols. This lack of diversity represents what has been the status quo of cancer research in the United States for decades. In the case of prostate cancer, homogenic study designs are problematic as Black men are much more likely to be diagnosed and die from aggressive and incurable forms of the disease. Therefore, the strategic inclusion of biospecimens collected from Black patients as well as the recruitment and enrollment of Black men into prostate cancer clinical trials is necessary to comprehensively evaluate genetic and molecular factors that contribute to variable outcomes in this high-risk population. Additionally, a higher prevalence of HER2 expression in Black men was recently reported in a small cohort of prostate cancer patients and may contribute to worsened prognosis. In this review, we carefully consider the role of HER2 in prostate cancer while, for the first time, taking into account the influences of race and genetic ancestry.

Mass spectrometry (MS) has revolutionized analytical chemistry, enabling precise identification and quantification of chemical species, which is pivotal for biomarker discovery and understanding complex biological systems. Despite its versatility, the presence of background ions in MS analysis hinders the sensitive detection of low-abundance analytes. Therefore, studies aimed at lowering background ion levels have become increasingly important. Here, we utilized the commercially available Active Background Ion Reduction Device (ABIRD) to suppress background ions and assess its effect on the liquid chromatography-electrospray ionization (LC-ESI)-MS analyses of N-glycans on the Q Exactive HF mass spectrometer. We also investigated the effect of different solvent vapors in the ESI source on N-glycan analysis by MS. ABIRD generally had no effect on high-mannose and neutral structures but reduced the intensity of some structures that contained sialic acid, fucose, or both when methanol vapor filled the ESI source. Based on our findings on the highest number of identified N-glycans from human serum, methanol vapor in the ion source compartment may enhance N-glycan LC-ESI-MS analyses by improving the desolvation of droplets formed during the ESI process due to its high volatility. This protocol may be further validated and extended to advanced bottom-up proteomic/glycoproteomic studies for the analysis of peptide/glycopeptide ions by MS., (© 2024 Wiley‐VCH GmbH.)

Alterations in glycoprotein abundance and glycan structures are closely linked to numerous diseases. The quantitative exploration of glycoproteomics is pivotal for biomarker discovery, but comprehensive analysis within biological samples remains challenging due to low abundance, complexity, and lack of universal technology. We developed a multiplex glycoproteomic approach using an LC-ESI-MS platform for direct comparison of glycoproteomic quantitation. Glycopeptides were isotopically labeled during cell culture, achieving high labeling efficiency (≥ 95 %) for both glycans and peptides. Quantitation was validated by mixing the same cell line in a 1:1:1:1 ratio, with mathematical correction applied to deconvolute the ratios. This method proved reliable and was applied to a comparative glycoproteomic study of three breast cancer cell lines (HTB22, MDA-MB-231, MDA-MB-231BR) and one brain cancer cell line (CRL-1620), quantifying glycopeptides from three replicates. The expression of glycopeptides was relatively quantified, and up/down-regulation between cell lines was investigated. This approach provided insights into glycosylation microheterogeneity, crucial for breast cancer brain metastasis research. Benefits include eliminating fluctuations from nano electrospray ionization and reducing analysis time, enabling up to 4-plex profiling in a single injection. Metabolic labeling introduced mass differences at the MS1 level, ensuring increased sensitivity and higher resolution for accurate quantitation. SIGNIFICANCE: Alternations in glycoprotein abundance, changes in glycosylation levels, and variations in glycan structures are closely linked to numerous diseases. The quantitative exploration of glycoproteomics has emerged as a popular area of research for biomarker discovery. However, conducting a comprehensive quantitative analysis of the glycoproteome within biological samples remains challenging due to low abundance, inherent complexities, and the absence of universal quantitative technology. Here, we developed a multiplex glycoproteomic approach using an LC-ESI-MS platform to facilitate direct comparison of glycoproteomic quantitation and enhance throughput. This approach offers benefits such as eliminating quantitative fluctuations arising from nano electrospray ionization (ESI) and reducing analysis time, enabling up to 4-plex glycoproteomic profiling in a single injection. Glycopeptides were stable isotopic labeled during cell culture procedure, attaching to monosaccharides, amino acids, or both. We achieved a high labeling efficiency (≥ 95 %) for both glycans and peptides. Quantitation validation was tested on glycopeptides by mixing the same cell line with 1:1:1:1 ratio. Due to the overlapped isotopes, a mathematical correction was applied to deconvolute the ratio of 4-plex glycopeptides. This method demonstrated quantitative reliability and was successfully applied to a comparative glycoproteomic study of three breast cancer cells (HTB22, MDA-MB-231, and MDA-MB-231BR) and one brain cancer cell (CRL-1620), identifying a total of 264 glycopeptides from three replicates. The expression of glycopeptides among these four cells was relatively quantified and up/down-regulation between two cell lines was investigated. The exploration of glycosylation microheterogeneity through glycopeptide quantification may offer valuable insights for further investigation into breast cancer brain metastasis. Conclusion: The primary advantage of our presented work lies in the multiplexing offered by combining two established labeling techniques, SILAC and IDAWG, both of which have been effectively used and widely cited in the scientific community. This combination enhances the applicability and accuracy of our method, as demonstrated by the extensive citations and successful use of these techniques independently. We believe that this multiplexing approach significantly advances the field, despite the method's current limitation to cell systems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Glyphosate, the active ingredient in many herbicides, has been widely used in agriculture since the 1970s. Despite initial beliefs in its safety for humans and animals due to the absence of the shikimate pathway, recent studies have raised concerns about its potential health effects. This study aimed to identify glycomic changes indicative of glyphosate-induced toxicity. Specifically, the study focused on profiling N -glycosylation, a protein post-translational modification increasingly recognized for its involvement in various disorders, including neurological conditions. A comprehensive analysis of rat serum N -glycomics following chronic exposure to glyphosate-based herbicides (GBH) was conducted using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The results revealed significant changes in the N -glycan profile, particularly in sialylated and sialofucosylated N -glycans. The analysis of N -glycans across gender subgroups provided insights into gender-specific responses to GBH exposure, with the male rats exhibiting a higher susceptibility to these N -glycan changes compared to females. The validation of significantly altered N -glycans using parallel reaction monitoring (PRM) confirmed their expression patterns. This study provides novel insights into the impact of chronic GBH exposure on serum N -glycan composition, with implications for assessing glyphosate toxicity and its potential neurological implications.

Introduction: Glyphosate-based herbicides (GBHs) have been shown to have significant neurotoxic effects, affecting both the structure and function of the brain, and potentially contributing to the development of neurodegenerative disorders. Despite the known importance of glycosylation in disease progression, the glycome profile of systems exposed to GBH has not been thoroughly investigated., Methods: In this study, we conducted a comprehensive glycomic profiling using LC-MS/MS, on the hippocampus and prefrontal cortex (PFC) of juvenile rats exposed to GBH orally, aiming to identify glyco-signature aberrations after herbicide exposure., Results: We observed changes in the glycome profile, particularly in fucosylated, high mannose, and sialofucosylated N-glycans, which may be triggered by GBH exposure. Moreover, we found major significant differences in the N-glycan profiles between the GBH-exposed group and the control group when analyzing each gender independently, in contrast to the analysis that included both genders. Notably, gender differences in the behavioral test of object recognition showed a decreased performance in female animals exposed to GBH compared to controls ( p  < 0.05), while normal behavior was recorded in GBH-exposed male rats ( p  > 0.05)., Conclusion: These findings suggest that glycans may play a role in the neurotoxic effect caused by GBH. The result suggests that gender variation may influence the response to GBH exposure, with potential implications for disease progression and specifically the neurotoxic effects of GBHs. Understanding these gender-specific responses could enhance knowledge of the mechanisms underlying GBH-induced toxicity and its impact on brain health. Overall, our study represents the first detailed analysis of N-glycome profiles in the hippocampus and PFC of rats chronically exposed to GBH. The observed alterations in the expression of N-glycan structures suggest a potential neurotoxic effect associated with chronic GBH exposure, highlighting the importance of further research in this area., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Solomon, Gutierrez-Reyes, Chávez-Reyes, Onigbinde, Marichal-Cancino, López-Lariz, Beck and Mechref.)

Background: The study of glycopeptides is associated with challenges regarding the microheterogeneity of different isomeric glycans occupying the same glycosylation sites in glycoproteins. It is immensely valuable to perform both qualitative and quantitative site-specific glycosylation analysis of glycopeptide isomers due to their link to several diseases. Achieving isomeric separation of glycopeptides is particularly challenging due to the low abundance of glycopeptides as well as inefficient ionization. Although some methods have demonstrated the isomeric separation of glycopeptides, a more efficient nanoflow-based stationary phase is needed for the isomeric separation of both N- and O-glycopeptides., Results: In this study, the separation of N- and O-glycopeptide isomers at 75 °C was achieved with an in-house packed 1 cm long mesoporous graphitized carbon (MGC) column. Different gradient compositions of the optimized mobile phase for separating permethylated glycans on MGC column were tested, and we observed efficient separation of N- and O-glycopeptide isomers at a gradient elution time of 120 min. After achieving the isomeric separation of sialylated glycopeptides from model glycoproteins derived from bovine fetuin, the separation of isomeric glycopeptides derived from asialofetuin, α-1 glycoprotein and human blood serum were also demonstrated. Furthermore, the developed method for the separation of isomeric N- and O-glycopeptide on MGC column showed high reproducibility over three months. We observed an average retention time shift of 1 min and consistent resolution of separated peaks throughout three months., Significance and Novelty: MGC column can serve as an efficient tool for obtaining the isomeric separation of N- and O-glycopeptide from complex biological samples in future studies. This will enable a more profound understanding of the roles played by isomeric N- and O-glycopeptide in important biological processes and their correlations to various disease progressions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

The neurological condition known as narcolepsy type 1 (NT1) is an uncommon condition marked by extreme daytime sleepiness, cataplexy, sleep paralysis, hallucinations, disrupted nocturnal sleep, and low or undetectable levels of orexin in the CSF fluid. NT1 has been hypothesized to be an immunological disorder; its treatment is currently only symptomatic, and misdiagnosis is not uncommon. This study compares the N -glycome of NT1 patients with healthy controls in search of potential glycan biomarkers using LC-MS/MS. A total of 121 candidate N -glycans were identified, 55 of which were isomeric N -glycan structures and 65 were not. Seventeen N -glycan biomarker candidates showed significant differences between the NT1 and control cohorts. All of the candidate glycan biomarkers were isomeric except HexNAc 6 Hex 7 Fuc 0 NeuAc 1 (6701) and HexNAc 6 Hex 7 Fuc 1 NeuAc 2 (6712). Therefore, with isomeric and nonisomeric structures, a total of 20 candidate N -glycan biomarkers are reported in this study, and interestingly, all are either sialylated or sialylated-fucosylated and upregulated in NT1 relative to the control. The distribution levels of all the identified N -glycans show that the sialylated glycan type is the most abundant in NT1 and is majorly disialylated, although the trisialylated subtype is three-fold higher in NT1 compared to the healthy control. The first isomers of HexNAc 5 Hex 6 Fuc 0 NeuAc 3 (5603), HexNAc 6 Hex 7 Fuc 0 NeuAc 2 (6702), and HexNAc 6 Hex 7 Fuc 1 NeuAc 4 (6714) expressed a high level of fold changes (FC) of 1.62, 2.19, and 2.98, respectively. These results suggest a different N -glycome profile of NT1 and a relationship between sialylated glycan isomers in NT1 disease development or progression. The revelation of N -glycan expression alterations in this study may improve NT1 diagnostic methods, understanding of NT1 pathology, and the development of new targeted therapeutics., Competing Interests: The authors declare no competing financial interest., (© 2024 The Authors. Published by American Chemical Society.)

The study of glycoproteomics presents a set of unique challenges, primarily due to the low abundance of glycopeptides and their intricate heterogeneity, which is specific to each site. Glycoproteins play a crucial role in numerous biological functions, including cell signaling, adhesion, and intercellular communication, and are increasingly recognized as vital markers in the diagnosis and study of various diseases. Consequently, a quantitative approach to glycopeptide research is essential. One effective strategy to address this need is the use of multiplex glycopeptide labeling. By harnessing the synergies of 15 N metabolic labeling via the isotopic detection of amino sugars with glutamine (IDAWG) technique for glycan parts and tandem mass tag (TMT)pro labeling for peptide backbones, we have developed a method that allows for the accurate quantification and comparison of multiple samples simultaneously. The adoption of the liquid chromatography-synchronous precursor selection (LC-SPS-MS3) technique minimizes fragmentation interference, enhancing data reliability, as shown by a 97% TMT labeling efficiency. This method allows for detailed, high-throughput analysis of 32 diverse samples from 231BR cell lines, using both 14 N and 15 N glycopeptides at a 1:1 ratio. A key component of our methodology was the precise correction for isotope and TMTpro distortions, significantly improving quantification accuracy to less than 5% distortion. This breakthrough enhances the efficiency and accuracy of glycoproteomic studies, increasing our understanding of glycoproteins in health and disease. Its applicability to various cancer cell types sets a new standard in quantitative glycoproteomics, enabling deeper investigation into glycopeptide profiles., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature.)

Traditional methodologies often fall short in addressing the complexity of biological systems. In this regard, system biology omics have brought invaluable tools for conducting comprehensive analysis. Current sequencing capabilities have revolutionized genetics and genomics studies, as well as the characterization of transcriptional profiling and dynamics of several species and sample types. Biological systems experience complex biochemical processes involving thousands of molecules. These processes occur at different levels that can be studied using mass spectrometry-based (MS-based) analysis, enabling high-throughput proteomics, glycoproteomics, glycomics, metabolomics, and lipidomics analysis. Here, we present the most up-to-date techniques utilized in the completion of omics analysis. Additionally, we include some interesting examples of the applicability of multi omics to a variety of biological systems.

Many powerful methods have been employed to elucidate the global transcriptomic, proteomic, or metabolic responses to pathogen-infected host cells. However, the host glycome responses to bacterial infection remain largely unexplored, and hence, our understanding of the molecular mechanisms by which bacterial pathogens manipulate the host glycome to favor infection remains incomplete. Here, we address this gap by performing a systematic analysis of the host glycome during infection by the bacterial pathogen Brucella spp. that cause brucellosis. We discover, surprisingly, that a Brucella effector protein (EP) Rhg1 induces global reprogramming of the host cell N-glycome by interacting with components of the oligosaccharide transferase complex that controls N-linked protein glycosylation, and Rhg1 regulates Brucella replication and tissue colonization in a mouse model of brucellosis, demonstrating that Brucella exploits the EP Rhg1 to reprogram the host N-glycome and promote bacterial intracellular parasitism, thereby providing a paradigm for bacterial control of host cell infection., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Breast cancer is the second leading cause of cancer-related death among women and a major source of brain metastases. Despite the increasing incidence of brain metastasis from breast cancer, the underlying mechanisms remain poorly understood. Altered glycosylation is known to play a role in various diseases including cancer metastasis. However, profiling studies of O -glycans and their isomers in breast cancer brain metastasis (BCBM) are scarce. This study analyzed the expression of O -glycans and their isomers in human breast cancer cell lines (MDA-MB-231, MDA-MB-361, HTB131, and HTB22), a brain cancer cell line (CRL-1620), and a brain metastatic breast cancer cell line (MDA-MB-231BR) using nanoLC-MS/MS, identifying 27 O -glycan compositions. We observed significant upregulation in the expression of HexNAc 1 Hex 1 NeuAc 2 and HexNAc 2 Hex 3 , whereas the expression of HexNAc 1 Hex 1 NeuAc 1 was downregulated in MDA-MB-231BR compared to other cell lines. In our isomeric analysis, we observed notable alterations in the isomeric forms of the O -glycan structure HexNAc 1 Hex 1 NeuAc 1 in a comparison of different cell lines. Our analysis of O -glycans and their isomers in cancer cells demonstrated that changes in their distribution can be related to the metastatic process. We believe that our investigation will contribute to an enhanced comprehension of the significance of O -glycans and their isomers in BCBM.

Glyphosate-based herbicides (GBHs) have gained extensive popularity in recent decades. For many years, glyphosate has been regarded as harmless or minimally toxic to mammals due to the absence of its primary target, the shikimic acid pathway in humans. Nonetheless, mounting evidence suggests that glyphosate may cause adverse health effects in humans via other mechanisms. In this study, we described the metabolomic changes in the serum of experimental rats exposed to chronic GBH using the highly sensitive LC-MS/MS technique. We investigated the possible relationship between chronic exposure to GBH and neurological disorders. Our findings suggest that chronic exposure to GBH can alter spatial learning memory and the expression of some important metabolites that are linked to neurophysiological disorders in young rats, with the female rats showing higher susceptibility compared to the males. This indicates that female rats are more likely to show early symptoms of the disorder on exposure to chronic GBH compared to male rats. We observed that four important metabolites (paraxanthine, epinephrine, L-(+)-arginine, and D-arginine) showed significant changes and involvement in neurological changes as suggested by ingenuity pathway analysis. In conclusion, our results indicate that chronic exposure to GBH can increase the risk of developing neurological disorders.

MS-target analyses are frequently utilized to analyze and validate structural changes of biomolecules across diverse fields of study such as proteomics, glycoproteomics, glycomics, lipidomics, and metabolomics. Targeted studies are commonly conducted using multiple reaction monitoring (MRM) and parallel reaction monitoring (PRM) techniques. A reliable glycoproteomics analysis in intricate biological matrices is possible with these techniques, which streamline the analytical workflow, lower background interference, and enhance selectivity and specificity., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)