Analysis Of Fragmentation Patterns Research Articles

Pheno- and Genotypic Epidemiological Characterization of Vancomycin-Resistant Enterococcus faecium Isolates from Intensive Care Unit Patients in Central Türkiye.

Vancomycin-resistant Enterococcus faecium (VRE) has been detected in Türkiye. Only limited information is available on its dissemination in the central regions of the country. This study describes the first epidemiological characterization of VRE clinical isolates detected in patients in a hospital in the province of Aksaray. In this one-year study conducted between 2021 and 2022, stool samples from intensive care unit patients were screened for VRE using the phenotypic E-test method, and the antibiotic sensitivity test was analyzed by using the VITEK® 2 system. A molecular assay for confirmation of species level was carried out by 16S rRNA gene-based sequencing and testing for antibiotic resistance (vanA or vanB) and virulence factor-encoding genes (esp, asa1, and hyl). Further, genotypic characterization was determined by macro-restriction fragment pattern analysis (MRFPA) of genomic DNA digested with SmaI restriction enzyme. Of the total 350 Enterococcus positive patients from different hospital intensive care units, 22 (6.3%) were positive for VRE using the phenotypic E-test method. All isolates showed resistance to ampicillin, ciprofloxacin, vancomycin, and teicoplanin and positive amplification for the vanA gene. However, none of the isolates was positive for the vanB gene. The most prevalent virulence gene was esp. The results indicate that the isolates are persistent in the hospital environment and subsequently transmitted to hospitalized patients, thus representing challenges to an outbreak and infection control. These study results would also help formulate more effective strategies to reduce the transmission and propagation of VRE contamination in various hospital settings.

Isolation and characterization of Thymus serpyllum L. essential oil and mass fragmentation analysis of major constituents

ABSTRACT The essential oils were isolated from Thymus serpyllum L. leaves, stem, flowers and whole plant using hydrodistillation technique and % yield was determined. The chemical constituents were studied using Gas Chromatography-Mass Spectrometry and Gas Chromatography-Flame Ionisation Detection. The analysis revealed the presence of 38 compounds in the essential oils obtained from different plant parts. Identification of compounds was achieved by detailed analysis of mass spectrum and retention indices. The major constituents of essential oil from the whole plant were thymol (35.25%), p-cymene (27.57%), thymol acetate (8.03%) and γ-terpinene (6.92%). In leaves they were thymol (45.59%), p-cymene (24.26%), thymol acetate (6.41%), and β-bisabolene (5.91%); whereas in flowers these were thymol (68.74%) and thymol acetate (7.40%) and in the stem, these were thymol (55.15%) and thymol acetate (8.01%). Specifically, it is the first report wherein essential oil constituents of T. serpyllum L. whole plant, leaves, flowers, and stems have been analyzed separately. Further, fundamental analysis of complex mass fragmentation patterns of terpenes and terpenoids using EI-MS has been achieved and the logical reason for the fragmentation pattern has been elaborated. Detailed elaboration of the mass fragmentation pattern may strengthen the EI-MS-based compound identification of terpenes and terpenoids from essential oils.

FinaleToolkit: Accelerating Cell-Free DNA Fragmentation Analysis with a High-Speed Computational Toolkit.

Cell-free DNA (cfDNA) fragmentation pattern represents a promising non-invasive biomarker for disease diagnosis and prognosis. Numerous fragmentation features, such as end motif and window protection score (WPS), have been characterized in cfDNA genomic sequencing. However, the analytical tools developed in these studies are often not released to the liquid biopsy community or are inefficient for genome-wide analysis in large datasets. To address this gap, we have developed FinaleToolkit, a fast and memory efficient Python package designed to generate comprehensive fragmentation features from large cfDNA genomic sequencing data. For instance, FinaleToolkit can generate genome-wide WPS features from a ~100X cfDNA whole-genome sequencing (WGS) dataset in 1.2 hours using 16 CPU cores, offering up to a ~50-fold increase in processing speed compared to original implementations in the same dataset. We have benchmarked FinaleToolkit against original studies or implementations where possible, confirming its efficacy. Furthermore, FinaleToolkit enabled the genome-wide analysis of fragmentation patterns over arbitrary genomic intervals, significantly boosting the performance for cancer early detection. FinaleToolkit is open source and thoroughly documented with both command line interface and Python application programming interface (API) to facilitate its widespread adoption and use within the research community: https://github.com/epifluidlab/FinaleToolkit.

Assessment of plasma cell-free DNA fragmentation for multi-cancer early detection: An independent clinical validation study.

e15037 Background: Cell-free DNA (cfDNA) in the circulation has gained significant attention due to its potential applications for non-invasive early cancer detection. Fragmentomics of cfDNA is emerging as a promising field of biomarker research, exhibiting the capability to sensitively detect multiple cancer types. In previous retrospective research, we developed an approach called PatternWGS for comprehensive analysis of cfDNA fragmentation patterns and presented a multi-cancer detection model. In this study, we aim to evaluate the performance of PatternWGS in an independent validation cohort including lung, breast, colorectal, liver, and gastric cancers from a new clinical center. Methods: Participants with confirmed diagnosis of lung, breast, colorectal or liver cancer were enrolled in the cancer group. Non-cancer participants without known presence of malignancies were recruited from the same clinical center. Plasma samples from patients with lung (n=47), breast (n=19), colorectal (n=14), liver (n=8) and gastric (n=6) cancers, along with 101 non-cancer individuals were collected in this study. cfDNA was isolated from plasma and stored within a month prior to the whole genome sequencing. The characteristics of cfDNA fragmentation integrating fragment size profiles, motif patterns, genomic coverage distributions were utilized to evaluate the performance for cancer signal detection. In addition, the performance of estimated cfDNA tumor fraction, using copy number aberrations (ichorCNA), was compared with our approach. Results: 94 patients with one of five types of cancers and 101 non-cancer controls were prospectively enrolled between July 2023 and November 2023. Among the cancer group, 64% were at early stages (Stage I: 48%, Stage II: 16%). A significantly higher proportion of shorter fragments was observed in cancer group, and the degree increased with increasing cancer stage. Overall sensitivity across cancer types and stages was 72.3%, and the specificity for non-cancer controls was 80%. As expected, the sensitivity of cancer detection is higher in late-stage patients compared to those in the early-stages (61% in stage I, 80% in stage II, 84.6% in stage III, and 91.7% in stage IV). The sensitivity of detecting lung (72% had stage I cancer), breast, colorectal, liver, and gastric cancers reached 57.4%, 84.2%, 85.7%, 87.5% and 100% respectively. The detection performance using cfDNA tumor fraction by ichorCNA demonstrated a relatively low overall sensitivity of 28.7% (24.6% for stage I-II, 44% for stage III-IV). Conclusions: This independent clinical validation study, which focused on exploring plasma cfDNA fragmentation, demonstrated ideal performance in early-stage cancer detection. The cfDNA fragmentation-based approach exhibited a superior sensitivity in detecting early cancer signals compared with copy number aberrations-based approach.

Abstract PS06-09: Fragmentomic analysis of a circulating tumor DNA targeted cancer gene panel discriminates ER status in metastatic breast cancer liquid biopsies

Abstract Background: Circulating tumor DNA (ctDNA) isolated from the peripheral blood of patients with cancer is now routinely used in the clinic to detect tumor somatic mutations, with multiple ctDNA-targeted sequencing panels commercially available for Food and Drug Administration (FDA)-approved biomarker indications to guide targeted therapy options. More recently, it has been appreciated that ctDNA fragmentation patterns are influenced by the chromatin structure of the cell of origin, with greater diversity in fragment size in areas with open chromatin and less diversity in fragment size in areas with closed chromatin. In consequence, multiple studies have found that ctDNA fragmentation patterns can be used to accurately infer epigenomic and transcriptomic phenotypes from their tumor cells of origin. However, these analyses have previously relied on whole-genome sequencing (WGS), and it is not feasible to identify FDA-approved biomarker indications in a cost-effective manner with WGS. Methods: Peripheral blood was collected from a cohort of 90 patients with metastatic HER2-negative breast cancer (ER-positive n=71, ER-negative n=19). Cell-free DNA was extracted from plasma and sequenced using a custom 822 gene pan-cancer targeted sequencing panel (IDT). Shannon entropy of first coding exon fragment sizes (E1SE) was used to quantify fragmentation patterns. Higher diversity of fragment sizes, leading to a higher E1SE, are expected in ctDNA derived from areas of the genome with more open chromatin. A machine learning model utilizing the E1SE metric across all genes in the targeted panel was developed to distinguish between ER-positive and ER-negative disease. Results: Training cross-validated accuracy of the machine learning model was 87.8% with AUC of 0.91 to distinguish between ER-positive and ER-negative disease, despite a median ctDNA fraction of only 0.02. E1SE metrics for ESR1 and CCND1 were significantly higher in ER-positive than ER-negative samples, while E1SE metrics for EGFR, c-Kit and members of the MAP kinase family were significantly higher in ER-negative than ER-positive samples, consistent with anticipated differences in gene expression between ER-positive and ER-negative triple negative breast cancers. In contrast, HER2 E1SE was similar between groups, as expected in this clinically HER2-negative cohort. Conclusions: We have shown for the first time that sequencing from standard targeted ctDNA panels can be utilized to infer phenotypic information through analysis of ctDNA fragmentation patterns in patients with metastatic breast cancer. This expands the depth of potential biologic data that can be extracted from targeted ctDNA sequencing panels in addition to DNA mutation status in a cost-effective manner. In the future, this approach can be exploited to expand ctDNA-based biomarker development beyond DNA mutation status. Citation Format: Kyle Helzer, Jamie Sperger, Yue Shi, Viridiana Carreno, Hannah Krause, Katherine Kaufmann, Leilani Mora-Rodriguez, Matthew Bootsma, Mark Burkard, Ruth O'Regan, Kari Wisinski, Joshua Lang, Shuang (George) Zhao, Malinda West, Marina Sharifi. Fragmentomic analysis of a circulating tumor DNA targeted cancer gene panel discriminates ER status in metastatic breast cancer liquid biopsies [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS06-09.

Abstract 3674: Blood-based differentiation of malignant and benign pancreatic lesions using analysis of fragmentation patterns in cell-free DNA

Abstract Pancreatic ductal adenocarcinoma (PDAC) remains lethal, with a five-year survival rate of less than 10%. For patients with pancreatic cystic lesions (PCL), analysis of DNA from cyst fluid has shown promise in determining the risk of malignant transformation. However, obtaining cyst fluid requires an invasive procedure. We recently developed an approach for blood-based cancer detection by analyzing fragmentation characteristics in plasma cell-free DNA (cfDNA). In this study, we evaluate the performance of this method in differentiating between patients with malignant and benign pancreatic lesions. We collected plasma samples from 81 patients at the time of endoscopic evaluation or surgical resection of a PCL. We simultaneously obtained plasma samples from 209 PDAC patients and 56 healthy individuals. Using plasma cfDNA whole genome sequencing data from patients with PDAC and healthy individuals, we trained and cross-validated an ensemble machine learning model based on 10 genomic features capturing plasma cfDNA fragmentation patterns. This model was applied to sequencing data from patients with PCL for independent evaluation of diagnostic performance. In training and cross-validation, the model demonstrated an area under the receiver operating characteristic curve (AUROC) of 0.90 for differentiating PDAC samples from healthy individuals. Of the 81 PCL patients, ten patients (12.3%) were found to have a malignant PCL, with either high-grade dysplasia or invasive carcinoma. The trained model showed an AUROC of 0.78 for differentiating malignant from benign lesions, achieving 50% sensitivity and 62.5% positive predictive value at 95% specificity. Our results are a novel demonstration that a peripheral blood test based on plasma cfDNA analysis can enable differentiation between malignant and benign pancreatic lesions. This approach may improve risk-stratification and clinical decision-making regarding the necessity for surgical resection. Larger studies and clinical trials to validate these results and evaluate their impact on outcomes are warranted. Citation Format: Clayton T. Marcinak, Michelle D. Stephens, Bradon R. McDonald, Nabeel Merali, Stephanie M. McGregor, Sharon M. Weber, Adam E. Frampton, Shivan Sivakumar, Rebecca M. Minter, Muhammed Murtaza. Blood-based differentiation of malignant and benign pancreatic lesions using analysis of fragmentation patterns in cell-free DNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3674.

Targeted Offline Two-Dimensional HPLC and UHPLC-Orbitrap-MS Combined with Molecular Networking Reveal the Effect of Processing on Chemical Constituents of Xuetong (the Stem of Kadsura heteroclita)

Xuetong, the dried stem of Kadsura heteroclita (Roxb.) Craib, is a traditional Tujia medicine extensively used to treat rheumatoid arthritis (RA). All traditional Chinese medicines (TCMs) necessitate a processing stage called “Paozhi” before clinical application. However, there is a dearth of research concerning the processing methods employed for Xuetong. To investigate the impact of vinegar and wine processing on the chemical constituents of Xuetong, this study devised a targeted offline two-dimensional (2D) high-performance liquid chromatography (HPLC) and ultra-high-performance liquid chromatography-orbitrap mass spectrometry (UHPLC-orbitrap-MS) method. By incorporating various MS data-processing techniques, such as molecular networking technology, fragment-ion similarity searching (FISh), online and offline database matching, and fragmentation pattern analysis, a total of 158 components were identified in Xuetong. Among them, 14 were verified by comparison with the reference standards. Notably, aside from triterpenoids and lignans, catechin derivatives were found to be the predominant constituents of Xuetong, and their levels exhibited a significant decrease following processing. This method significantly improved peak capacity and resolution, overcoming the limitations of 1D LC in simultaneously analyzing highly polar catechin derivatives and less polar triterpenoids and lignans. Moreover, the developed method shows promise for Xuetong’s quality control.

Structure analysis of depsides, dibenzofuran and sugar derivatives from Cladia aggregata (SW) Nyl using ultra-performance liquid chromatography-tandem mass spectrometry.

Cladia aggregate (SW) Nyl is a lichenized fungi in the family Cladoniaceae producing characteristic secondary metabolites of interest. There are only limited chemical studies relating to the genus Cladia. A chemical study of the lichen C. aggregata was conducted and their chemical constituents were elucidated by ultra-performance liquid chromatography-electrospray ionization/triple-quadrupole tandem-mass spectrometry analysis. It is the first time report of structure analysis of its metabolite by liquid chromatography-mass spectrometry/mass spectrometry. The molecular masses for 20 compounds were detected from different fractions. Seven compounds were elucidated with mass spectrometry/mass spectrometry fragmentation pattern analysis. Barbatic acid (12) was identified as the major compound being common to all fractions. The identified compounds belong to depsides (2, 11, 12 and 20), dibenzofurans (13, 18) and sugar derivatives (1) which are usually distributed in lichens.

Seasonal and Root-Specific Metabolomic Profiles of Panax Ginseng Meyer by Ultra-High Performance Liquid Chromatography-Quadrupole-Time-of-Flight-Mass Spectrometry (UPLC-QTOF-MS) and Partial Least Squares-Discriminant Analysis (PLS-DA)

The chemical composition of ginseng varies by several factors such as age, harvest season, and region. Each part of fresh ginseng contains certain valuable bioactive compounds; however, chemical studies of ginseng have focused on the ginsenoside content. In this study, we examine the chemical composition of Panax ginseng Meyer as related to harvest season and specific root parts via untargeted metabolomics using ultra-high performance liquid chromatography-quadrupole-time-of-flight-mass spectrometry (UPLC-QTOF-MS). Multivariate statistical analysis such as partial least squares discriminant analysis (PLS-DA) was used to select significant metabolites distinguishing ginseng harvested in different seasons and various ginseng parts. The selected thirteen metabolites were identified as amino acids, ginsenosides, and fatty acid amides through MS fragment pattern analysis. Additional chemometric analysis revealed chemical consistency between main and fine roots regardless of harvest time, indicating a stable chemical composition in P. ginseng among seasons. Furthermore, most ginsenosides among the thirteen selected metabolites had higher abundance in fine roots than in main roots, while primary metabolites were more abundant in main roots, highlighting a unique chemical composition dependent on the specific root parts.

Structural Identification of Zotarolimus (ABT-578) Metabolites Generated by Human Liver Microsomes Using Ion-Trap and High-Resolution Time-of-Flight Mass Spectrometry in Combination with the Analysis of Fragmentation Patterns.

Zotarolimus (ABT-578) is a sirolimus derivative that, like sirolimus and everolimus, is an inhibitor of cell growth via inhibition of the mechanistic target of rapamycin (mTOR). Zotarolimus was developed for coating coronary stents to prevent smooth muscle cell proliferation and restenosis. Albeit zotarolimus-eluting cardiovascular devices have been on the market for years, details of zotarolimus drug metabolism in humans are still unknown. Hence, it was the goal of the present study to identify zotarolimus metabolites generated by incubation with human liver microsomes. Metabolite structures were identified using high-resolution mass spectrometry, MS/ion-trap (MSn), and comparison of fragmentation patterns of the metabolites with those of zotarolimus and other known sirolimus derivatives. Kinetic parameters such as incubation time, human liver microsomal protein concentrations, and drug concentrations were optimized before scaling up the metabolism experiments. Human liver microsomes mainly hydroxylated and/or demethylated zotarolimus. The structures of the following metabolites were identified: O-demethylated metabolites: 39-O-desmethyl, 16-O-desmethyl, and 27-O-desmethyl zotarolimus; hydroxylated metabolites: hydroxy piperidine zotarolimus, 11-hydroxy, 12-hydroxy, 14-hydroxy, 23-hydroxy, 24-hydroxy, 25-hydroxy, 45/46-hydroxy, and 49-hydroxy zotarolimus; demethylated-hydroxylated metabolites: 16-O-desmethyl, 23/24-hydroxy; 39-O-desmethyl, 23/24-hydroxy; 39-O-desmethyl, 25-hydroxy zotarolimus; 39-O-desmethyl, 11-hydroxy zotarolimus; 39-O-desmethyl, hydroxy-piperidine zotarolimus; 27-O-desmethyl, 45/46-hydroxy zotarolimus; didemethylated metabolites: 16,39-O-didesmethyl zotarolimus; 16,27-O-didesmethyl zotarolimus; 27,39-O-didesmethyl zotarolimus; and dihydroxylated metabolites: 11,24-dihydroxy zotarolimus, 12,24-dihydroxy zotarolimus, and 11,47/48-dihydroxy zotarolimus. It is concluded that zotarolimus is extensively metabolized by human liver microsomes. Twenty-four of these metabolites could be structurally identified using a combination of ion-trap MSn and high-resolution mass spectrometry.

Atlantic Salmon Gill Epithelial Cell Line (ASG-10) as a Suitable Model for Xenobiotic Biotransformation.

Fish are exposed to xenobiotics in the water. Uptake occurs mainly through the gills, which function as an exchange point with the environment. The gills' ability to detoxify harmful compounds by biotransformation is an essential protection mechanism. The enormous numbers of waterborne xenobiotics requiring ecotoxicological assessment makes it necessary to replace in vivo fish studies with predictive in vitro models. Here, we have characterized the metabolic capacity of the ASG-10 gill epithelial cell line from Atlantic salmon. Inducible CYP1A expression was confirmed by enzymatic assays and immunoblotting. The activities of important cytochrome P450 (CYP) and uridine 5'-diphospho-glucuronosyltransferase (UGT) enzymes were established using specific substrates and metabolite analysis by liquid chromatography (LC) triple quadrupole mass spectrometry (TQMS). Metabolism of the fish anesthetic benzocaine (BZ) in ASG-10 confirmed esterase and acetyl transferase activities through the production of N-acetylbenzocaine (AcBZ), p-aminobenzoic acid (PABA) and p-acetaminobenzoic acid (AcPABA). Moreover, we were able to determine hydroxylamine benzocaine (BZOH), benzocaine glucuronide (BZGlcA) and hydroxylamine benzocaine glucuronide (BZ(O)GlcA) by LC high-resolution tandem mass spectrometry (HRMS/MS) fragment pattern analysis for the first time. Comparison to metabolite profiles in hepatic fractions, and in plasma of BZ-euthanized salmon, confirmed the suitability of the ASG-10 cell line for investigating biotransformation in gills.

Comprehensive characterization of Dactylorhin and loroglossin in Dactylorhiza hatagirea D. DON using ultra-performance liquid chromatography-mass spectrometry

Dactylorhiza hatagirea D. Don is acclaimed for different medicinal properties but a little is known about its secondary-metabolites. The purpose of this study was to reveal the components of D. hatagirea by UPLC−ESI/TQ-MS approach. Metabolite profiling of D.hatagirea is reported for the first time for rapid identification of bioactive components. Molecular mass of twelve compounds were determined from LC-MS analysis of the different fractions and structures of five compounds were elucidated with MS/MS fragmentation pattern analysis. Dactylorhin C (2), B (3), A (5), and Loroglossin (4) were derivatives of 2,3-dihydroxy-2-(2-methylpropyl)butanedioic acid and 2-hydroxy-2-(2-methylpropyl)butanedioic acid. In addition, Sucrose (1) was also identified. The obtained results confirmed the presence of Dactylorhins, Loroglossin and Sucrose which have already been isolated from the plant.

Liquid biopsy in hematological malignancies: current and future applications.

The assessment of the cancer mutational profile is crucial for patient management, stratification, and therapeutic decisions. At present, in hematological malignancies with a solid mass, such as lymphomas, tumor genomic profiling is generally performed on the tissue biopsy, but the tumor may harbor genetic lesions that are unique to other anatomical compartments. The analysis of circulating tumor DNA (ctDNA) on the liquid biopsy is an emerging approach that allows genotyping and monitoring of the disease during therapy and follow-up. This review presents the different methods for ctDNA analysis and describes the application of liquid biopsy in different hematological malignancies. In diffuse large B-cell lymphoma (DLBCL) and Hodgkin lymphoma (HL), ctDNA analysis on the liquid biopsy recapitulates the mutational profile of the tissue biopsy and can identify mutations otherwise absent on the tissue biopsy. In addition, changes in the ctDNA amount after one or two courses of chemotherapy significantly predict patient outcomes. ctDNA analysis has also been tested in myeloid neoplasms with promising results. In addition to mutational analysis, liquid biopsy also carries potential future applications of ctDNA, including the analysis of ctDNA fragmentation and epigenetic patterns. On these grounds, several clinical trials aiming at incorporating ctDNA analysis for treatment tailoring are currently ongoing in hematological malignancies.

Leaf cuticular waxes of wild-type Welsh onion (Allium fistulosum L.) and a wax-deficient mutant: Compounds with terminal and mid-chain functionalities

Plant cuticles cover aerial organs to limit non-stomatal water loss and protect against insects and pathogens. Cuticles contain complex mixtures of fatty acid-derived waxes, with various chain lengths and diverse functional groups. To further our understanding of the chemical diversity and biosynthesis of these compounds, this study investigated leaf cuticular waxes of Welsh onion (Allium fistulosum L.) wild type and a wax-deficient mutant. Leaf waxes were extracted with chloroform, separated using thin layer chromatography (TLC), and analyzed using gas chromatography-mass spectrometry (GC-MS). The extracts contained typical wax compound classes found in nearly all plant lineages but also two uncommon compound classes. Analyses of characteristic MS fragmentation patterns followed by comparisons with synthetic standards identified the latter as very-long-chain ketones and primary ketols. The ketols were minor compounds, with chain lengths ranging from C28 to C32 and carbonyls mainly on C-18 and C-20 in wild type wax, and a C28 chain with C-16 carbonyl in the mutant. The ketones made up 70% of total wax in the wild type, consisting mainly of C31 isomers with carbonyl group on C-14 or C-16. In contrast, the mutant wax comprised only 4% ketones, with chain lengths C27 and C29 and carbonyls predominantly on C-12 and C-14, respectively. A two-carbon homolog shift between wild type and mutant was also observed in the primary alcohols (a major wax compound class), whilst alkanes exhibited a four-carbon shift. Overall, the compositional data shed light on possible biosynthetic pathways to wax ketones that can be tested in future studies.

One toolkit to bring them all, and in silico analyze them.

One toolkit to bring them all, and in silico analyze them.

Analysis of cell-free DNA concentration, fragmentation patterns and TP53 gene expression in mammary tumor-bearing dogs: A pilot study.

Liquid biopsy based on the analysis of circulating cell-free DNA (cfDNA), as well as on detection of point mutations by digital droplet PCR (ddPCR), has revolutionized the research in oncology. In recent years, this technique has been pioneering in veterinary medicine since it is a minimally invasive approach with very promising results for characterization of tumors. The aim of this study was, firstly, to analyze the concentration and the fragmentation pattern of cfDNA of dogs with mammary tumors (n = 36) and healthy dogs (n = 5) and its correlation with clinicopathological data. Secondly, analysis of TP53 gene expression and the point mutation in the codon 245 were performed in cfDNA and in tumor tissues to assess their potential as plasma biomarkers. Our results highlighted that those dogs with worse clinicopathological characteristics (simple or undifferentiated carcinomas, higher histological grade and presence of peritumoral inflammation) shown higher cfDNA concentration and higher concentrations of short-fragments (<190 bp) than healthy dogs. In addition, although no detection of the point mutation in codon 245 of TP53 gene could be detected neither in plasma nor tumor tissue, an increased TP53 expression was detected in animals with tumors bearing malignant characteristics. Finally, a high concordance with TP53 gene expression in plasma and tumor tissue and cfDNA concentration was also found. The results derived from this work confirm the valuable potential of cfDNA and its fragments, as well as the analysis of TP53 expression in plasma as useful liquid biomarkers for clinical application in veterinary oncology.

A Nitrate-Transforming Bacterial Community Dominates in the Miscanthus Rhizosphere on Nitrogen-Deficient Volcanic Deposits of Miyake-jima.

The perennial gramineous grass Miscanthus condensatus functions as a major pioneer plant in colonizing acidic volcanic deposits on Miyake-jima, Japan, despite a lack of nitrogen nutrients. The nitrogen cycle in the rhizosphere is important for the vigorous growth of M. condensatus in this unfavorable environment. In the present study, we identified the nitrogen-cycling bacterial community in the M. condensatus rhizosphere on these volcanic deposits using a combination of metagenomics and culture-based analyses. Our results showed a large number of functional genes related to denitrification and dissimilatory nitrate reduction to ammonium (DNRA) in the rhizosphere, indicating that nitrate-transforming bacteria dominated the rhizosphere biome. Furthermore, nitrite reductase genes (i.e., nirK and nirS) related to the denitrification and those genes related to DNRA (i.e., nirB and nrfA) were mainly annotated to the classes Alpha-proteobacteria, Beta-proteobacteria, and Gamma-proteobacteria. A total of 304 nitrate-succinate-stimulated isolates were obtained from the M. condensatus rhizosphere and were classified into 34 operational taxonomic units according to amplified 16S rRNA gene restriction fragment pattern analysis. Additionally, two strains belonging to the genus Cupriavidus in the class Beta-proteobacteria showed a high in vitro denitrifying activity; however, metagenomic results indicated that the DNRA-related rhizobacteria appeared to take a major role in the nitrogen cycle of the M. condensatus rhizosphere in recent Miyake-jima volcanic deposits. This study elucidates the association between the Miscanthus rhizosphere and the nitrate-reducing bacterial community on newly placed volcanic deposits, which furthers our understanding of the transformation of nitrogen nutrition involved in the early development of vegetation.

DNA methylation analysis explores the molecular basis of plasma cell-free DNA fragmentation

Plasma cell-free DNA (cfDNA) are small molecules generated through a non-random fragmentation procedure. Despite commendable translational values in cancer liquid biopsy, however, the biology of cfDNA, especially the principles of cfDNA fragmentation, remains largely elusive. Through orientation-aware analyses of cfDNA fragmentation patterns against the nucleosome structure and integration with multidimensional functional genomics data, here we report a DNA methylation – nuclease preference – cutting end – size distribution axis, demonstrating the role of DNA methylation as a functional molecular regulator of cfDNA fragmentation. Hence, low-level DNA methylation could increase nucleosome accessibility and alter the cutting activities of nucleases during DNA fragmentation, which further leads to variation in cutting sites and size distribution of cfDNA. We further develop a cfDNA ending preference-based metric for cancer diagnosis, whose performance has been validated by multiple pan-cancer datasets. Our work sheds light on the molecular basis of cfDNA fragmentation towards broader applications in cancer liquid biopsy.

Single-cell metabolome profiling for phenotyping parasitic diseases in phytoplankton

Bloom-forming phytoplankton are key players in aquatic ecosystems, fixing carbon dioxide and forming the base of the marine food web. Diverse stresses, such as nutrient depletion, temperature increase, and pathogen emergence can influence the health and dynamics of algal populations. While population responses to these stressors are well-documented in the aquatic ecosystems, little is known about the individual cellular adaptations. These are however the key to an in-depth physiological understanding of microbiome dynamics in the plankton. Finding solutions to disease control in aquaculture also depends on knowledge of infection dynamics and physiology in algae. Single-cell metabolomics can give insight into infection processes by providing a snapshot of small molecules within a biological system. We used a single-cell metabolome profiling workflow to track metabolic changes of diatoms and dinoflagellates subjected to parasite infection caused by the oomycete Lagenisma coscinodisci and the alveolate Parvilucifera spp. We accurately classified the healthy phenotype of bloom-forming phytoplankton, including the diatoms Coscinodiscus granii and Coscinodiscus radiatus, and the toxic dinoflagellate Alexandrium minutum. We discriminated the infection of the toxic dinoflagellate A. minutum with the alveolate parasitoids Parvilucifera infectans and P. rostrata down to the single-cell resolution. Strain and species-specific responses of the diatom hosts Coscinodiscus spp. Infected with the oomycete pathogen Lagenisma coscinodisci could be recognized. LC-HRMS and fragmentation pattern analysis enabled the structure elucidation of metabolic predictors of infection (guanine, xanthine, DMSP, and pheophorbide). The purine salvage pathway and DMSP lysis could be assigned as regulated processes during host invasion. The findings establish single-cell metabolome profiling with LDI-HRMS coupled with classification analysis as a reliable diagnostic tool to track metabolic changes in algae.

Steroidal glycoside profile differences among primary roots system and adventitious roots in Solanum dulcamara

Main conclusionSolanum dulcamara primary and adventitious roots showed qualitative and quantitative differences in their steroidal glycosides profile. This opened new venues to evaluate the bioactivity of these molecules in belowground ecosystems.The Solanum genus is characterized by the presence of steroidal glycosides (SGs) that confer herbivore resistance and serve as drug precursors in the pharmaceutical industry. Solanum dulcamara is a self-compatible, sexually reproducing species that produces seeds after buzz-pollination. In addition, primordia on the stem facilitate clonal propagation via adventitious root (AR) formation. ARs contain aerenchyma being developmentally and morphologically different from primary roots (PRs). Therefore, we hypothesized that ARs and PRs have different SG profiles. Aiming to assess differences in SGs profiles in S. dulcamara roots in relation to their origins and morphologies, we used liquid chromatography coupled to electron spray ionization quadruple time of flight mass spectrometry (LC-ESI-qToF-MS) to profile SGs from PRs and ARs of seven S. dulcamara individuals. Mass fragmentation pattern analysis indicated the presence of 31 SG-type structures, including those with spirostans and furostans moieties. We assigned the 31 structures to 9 classes of steroidal aglycons (SAgls) that differ in hydroxylation and degree of unsaturation. We found that SAgls were conjugated with di-, tri- and tetra saccharides whereby one compound contained a malonylated sugar. Principle component analysis showed that SG profiles of PRs and ARs separated on the first principal component, supporting our hypothesis. Specifically, PRs contain higher number of SGs than ARs with some compounds exclusively present in PRs. Our results reveal a high level of novel chemodiversity in PRs and ARs of Solanum dulcamara. The knowledge gained will deepen our understanding of SGs biosynthesis and their functional role in plant-environment interactions.