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Thrombus Metabolism-Based Molecular Subtyping for Prognostic Risk Stratification in Acute Ischemic Stroke: A Preliminary Study.

AIMS: To preliminarily characterize metabolic molecular subtypes of cerebral thromboemboli and evaluate their clinical significance in anterior circulation acute ischemic stroke due to large vessel occlusion (AIS-LVO). METHODS: Untargeted metabolomics was performed on thromboemboli retrieved from 36 patients with anterior circulation AIS-LVO using ultra-performance coupled liquid chromatography with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). Unsupervised hierarchical clustering was employed to identify distinct metabolic molecular subtypes, and their associations with stroke etiology, radiographic severity, and functional outcomes were analyzed. RESULTS: Two distinct thrombus metabolic molecular subtypes (C1 and C2) were identified based on 12 metabolites significantly associated with both short-term (7-day ∆NIHSS) and long-term (90-day mRS) functional outcomes. The C1 subtype, predominantly cardioembolic, exhibited enhanced lipid metabolism, whereas the C2 subtype, primarily atherothrombotic, demonstrated increased folate metabolism. Patients with C1 thromboemboli presented more severe admission ischemic lesions (as indicated by ASPECTS) and experienced poorer short-term and long-term outcomes. A six-metabolite signature derived from LASSO regression was identified for exploratory discrimination of thrombus metabolic subtypes, etiological subtypes, and 90-day outcomes. CONCLUSION: This preliminary exploratory study identifies two metabolically distinct thrombus molecular subtypes with clinical implications in anterior circulation AIS-LVO, providing a novel basis for risk stratification and personalized secondary prevention and warrants further investigation.

Humans

Proteomic characterization of the acquired enamel pellicle under acidic challenges at early and mature formation stages.

OBJECTIVES: This study aimed to characterize acquired enamel pellicle (AEP) proteomic changes after exposure to citric acid (CA) and hydrochloric acid (HCl) under different pellicle formation times (3 and 120&#x202f;min) in the same volunteers. DESIGN: Nine healthy volunteers participated in this randomized crossover in vivo study. The AEP was allowed to form for 3 or 120&#x202f;min and subsequently exposed for 10&#x202f;s to deionized water (control), 1% CA (pH 2.5), or 0.01&#x202f;M HCl (pH 2.0). Pellicle samples were collected, followed by protein extraction, tryptic digestion, and analysis by nanoliquid chromatography (nanoLC) coupled to mass spectrometry (MS) with MSE (data-independent acquisition; nanoLC-MS&#x1d31;). Label-free quantitative proteomics were performed for relative quantification using t-test (p&#x202f;<&#x202f;0.05). RESULTS: At 120&#x202f;min, CA exposure markedly reduced several typical AEP proteins, especially acidic proline-rich proteins (PRPs). Conversely, basic PRPs were upregulated, suggesting acid-resistance protein signature. At 3&#x202f;min, basal-layer proteins (PRPs, cystatins, histatins and mucins) were more abundant. Hemoglobins increased 6-8-fold (up to 150-fold in 3&#x202f;min control), suggesting association with early pellicle formation and an acid-resistant protein signature. CA exposures for 120&#x202f;min also upregulated typical AEP proteins (PRPs, mucins, cystatins, immunoglobulins), while HCl exposure depleted albumins and lactotransferrin. CONCLUSION: Intrinsic and extrinsic acids induce distinct proteomic signatures in the AEP. Hemoglobin and PRPs appear consistently enriched in the early pellicle layer, reflecting an initial acid-resistant protein signature. These findings provide new insights into the molecular remodeling of the AEP following intrinsic and extrinsic acid exposure, highlighting proteins potentially involved in early-stage pellicle formation.

Humans

Towards microplastic bioremediation: Fungal degradation of pristine and pretreated high-density polyethylene and polystyrene.

Microplastic (MP) contamination has become a significant ecological issue because of its enduring existence in the ecosystem and its possible negative impacts. Therefore, using degrading strategies to eliminate these stubborn polymers has been a subject of scientific research. However, the currently used degradation methods are relatively inefficient. Given the pervasiveness of High-Density Polyethylene (HDPE) and Polystyrene (PS) and their resistance to biodegradability, disposal strategies are critical and must be addressed. This manuscript examines the biodegradation of pristine and UV-treated HDPE and PS MPs by Aspergillus flavus species in minimal growth media over 70 days. The maximum weight loss observed at 70 days for pristine HDPE and PS in sole carbon source (SCS) media was (29.33 &#xb1; 0.28) % and (17.67 &#xb1; 0.35) %, respectively. Whereas, for UV-treated HDPE and PS MPs, the % weight reduction was (33 &#xb1; 0.21) % and (25 &#xb1; 0.19) %, respectively. UV-treated MPs exhibited greater weight reduction, as UV induced oxygenated functional groups enhance polymer susceptibility to enzymes, thereby promoting biodegradation. HDPE MPs typically show a higher proportion of particles in the lower size range compared to PS MPs. This assertion was based on the weight loss, particle size distribution, and SEM analysis. Furthermore, chemical changes were evaluated using Fourier transform Infrared Spectroscopy (FTIR) analysis, which also displayed chemical oxidation occurring during biodegradation. Liquid Chromatography-Mass Spectrometry (LC-MS) results indicate that UV pretreatment enhances biodegradability by promoting chain scission. These findings further suggest that this fungus's natural and ubiquitous occurrence in terrestrial and marine environments may actively contribute to MP biodegradation while requiring few nutrients.

Microplastics

Identification and formation pathways of oxidation products of chlorinated paraffins during ozonation in municipal wastewater.

Chlorinated paraffins (CPs) cannot be efficiently removed by conventional water treatment processes and are continually discharged into the aqueous environment. Ozonation can effectively remove lipophilic and persistent pollutants. However, the degradation behaviors of short-chain CPs (SCCPs), medium-chain CPs (MCCPs), and long-chain CPs (LCCPs) in wastewater during the ozonation process remained unknown. In this study, ozonation treatment achieved removal efficiencies of 61 % for SCCPs, 66 % for MCCPs, and 51 % for LCCPs from wastewater within 30 min. Approximately 147 oxidative products of SCCPs, MCCPs, and LCCPs were non-targeted identified through Ph4PCl-enhanced ionization with ultra-high performance liquid chromatography-Orbitrap mass spectrometry. These oxidation products were structurally classified into three categories: carbon chain breakage (53 products), HCl-elimination (27 products), and hydroxylation (67 products). Twenty-three di-hydroxylated CPs were newly identified among the products. Hydroxylation was the predominant pathway for SCCPs, producing di-hydroxylated SCCPs ((OH)&#x2082;-SCCPs) with a higher generation rate constant (KG = 22.28 &#xd7; 10&#x207b;&#xb2; min&#x207b;&#xb9;) compared to other products. MCCPs and LCCPs mainly underwent carbon chain breakage and hydroxylation, generating shorter carbon chain congeners, (OH)2-SCCPs, and di-hydroxylated MCCPs ((OH)2-MCCPs). The KG values of (OH)2-SCCPs (10.56 &#xd7; 10-2 min-1) and (OH)2-MCCPs (12.05 &#xd7; 10-2 min-1) generated from the MCCPs were the highest, and the KG values of MCCPs (6.49 &#xd7; 10-2 min-1), SCCPs (6.27 &#xd7; 10-2 min-1), and (OH)2-SCCPs (4.74 &#xd7; 10-2 min-1) generated from the LCCPs were higher than those of other products. These results comprehensively clarify the oxidation efficiencies and pathways of CPs during ozonation. Future studies must explore the potential risks associated with the oxidation products.

Water Pollutants, Chemical

Integrated phytochemical and bioactivity profiling of Xanthium strumarium fruits from Korea and China: Implications for origin-specific quality specification.

BACKGROUND: Geographic origin influences the phytochemical composition and biological activities of medicinal plant resources. Xanthium strumarium L. (XS) fruit is widely used in East Asian traditional medicine. However, current pharmacopeial standards primarily recognize Chinese-derived material, despite the availability and traditional use of XS in Korea. To address this gap and support origin-informed quality specification, we compared fruits from Korea (XS-K) and China (XS-C) using chloroplast genome sequencing, targeted phytochemical profiling (high-performance liquid chromatography (HPLC) for selected phenolics and gas chromatography-flame ionization detection (GC-FID) for fatty acids and phytosterols, and multivariate chemometric analysis. RESULTS: Chloroplast genome analysis revealed high overall similarity but localized divergence around the rpoC2 locus and a greater mutation burden in XS-C, supporting origin-associated genomic differentiation. Phytochemical profiling revealed distinct origin-dependent metabolic signatures. XS-K showed higher levels of phytosterols, chlorogenic acid, 4,5-dicaffeoylquinic acid (4,5-DCQ), and xanthatin was detected only in XS-K, whereas XS-C exhibited greater abundance of total fatty acids, particularly oleic acid. Unsupervised clustering and log2 fold-change ranking confirmed clear compositional separation, and variable importance in projection (VIP) analysis identified chlorogenic acid, &#x3b2;-sitosterol, oleic acid, 4,5-DCQ, and xanthatin as major discriminators between origins. Bioactivity assays demonstrated that XS-K exerted stronger antioxidant effects in ABTS, DPPH and FRAP assays, stronger skin-related enzyme inhibition, and greater antibacterial activity against Staphylococcus aureus, consistent with its enriched phenolic and sterol profile. CONCLUSION: Together, chloroplast sequence variation, targeted metabolite quantification, and screening bioassays consistently distinguished XS-K from XS-C. These findings support the use of candidate markers for the origin-based authentication and quality control of XS fruit-derived ingredients. &#xa9; 2026 The Author(s). Journal of the Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Fruit

Selective monitoring of trace-level catechin and myricetin in herbal and aqueous matrices using magnetic MIP-DSPME: Optimization via design of experiments.

A novel dispersive solid-phase microextraction approach utilizing a magnetic molecularly imprinted polymer (MMIP) integrated with HPLC-UV detection was developed for the concurrent quantification of catechin and myricetin in herbal extracts and aqueous samples. The sorbent was engineered as a core-shell nanocomposite, consisting of a selective polymer layer deposited onto Fe3O4@SiO2-APTMS magnetic nanoparticles. Dual-template imprinting using catechin and myricetin generated complementary binding cavities within the polymer framework. Experimental variables influencing extraction were systematically screened and subsequently optimized. A Plackett-Burman design was first applied to identify the most influential factors, with pH and sorption time identified as the dominant variables. These parameters were subsequently fine-tuned using a central composite design, and the optimization process was completed in only 30 experimental runs. The sorption characteristics of the imprinted sorbent (MMIP) were compared with those of its non-imprinted counterpart (MNIP). The MMIP demonstrated markedly higher maximum binding capacities (Qmax), reaching 119.3&#xa0;mg&#xa0;g-1 for myricetin and 112.1&#xa0;mg&#xa0;g-1 for catechin, whereas the corresponding values for the MNIP were 32.55 and 32.08&#xa0;mg&#xa0;g-1, respectively. Moreover, the affinity constants (KL&#xa0;=&#xa0;0.760-0.950&#xa0;L&#xa0;mg-1) were approximately 2.3-fold higher for the MMIP, confirming its stronger and more selective interactions with the target analytes. The selectivity coefficients for the targeted flavonoids relative to structurally related compounds, including ferulic acid, p-coumaric acid, melatonin, and curcumin, exceeded 3.5 for the MMIP, whereas the corresponding values for the MNIP were close to 1.1, demonstrating the high molecular recognition capability of the imprinted sorbent. Method validation demonstrated limits of detection (LODs) of 0.33-0.59&#xa0;ng&#xa0;mL-1 and limits of quantification (LOQs) of 1.10-1.96&#xa0;ng&#xa0;mL-1, and excellent linearity over the concentration range of 5.0-5500&#xa0;ng&#xa0;mL-1 (R2&#xa0;>&#xa0;0.998). The method achieved recoveries of 93.96% to 105.69% with RSDs below 5.5%, while the preconcentration factors ranged from 209 to 229. Furthermore, the sorbent retained more than 95% of its extraction efficiency after four consecutive reuse cycles and more than 80% after six cycles, demonstrating excellent stability and reusability. The proposed method was successfully applied to the analysis of six medicinal plant extracts and water samples, showing negligible matrix interference and superior sensitivity, selectivity, and operational simplicity compared with conventional solid-phase extraction methods.

Flavonoids

Community-driven advances in computational mass spectrometry: The perspective of EuBIC-MS members.

Advances in data acquisition, artificial intelligence, and integrative bioinformatics are driving the rapid evolution of computational mass spectrometry, and in turn, transforming modern proteomics, metabolomics, and lipidomics. These developments have greatly increased the scale and complexity of mass spectrometry data, underscoring the importance of evolving accurate, transparent, efficient and reproducible data processing workflows. Addressing these challenges requires collaborative innovation that brings together expertise in software engineering, statistics, and biology. The European Bioinformatics Community for Mass Spectrometry (EuBIC-MS), an initiative of the European Proteomics Association (EuPA), fosters a culture of open, community-driven development through its biennial Developers Meetings and Winter Schools. This commentary summarizes the scientific background and outcomes of the EuBIC-MS Developers Meeting 2025, which took place in Novacella, Italy. Three keynote presentations highlighted major frontiers in the field: deep proteome and phosphoproteome profiling, text mining for protein-protein interaction extraction, and scalable proteomics for AI-driven drug discovery. Seven community-selected hackathons addressed emerging challenges such as single-cell proteomics data analysis, FAIR metadata extraction, deep learning frameworks, R-Python interoperability, and DIA validation. Together, these efforts demonstrate the potential for scientific and technical innovation to arise from open collaboration, and highlight how community-driven initiatives can accelerate progress in computational mass spectrometry. SIGNIFICANCE: Modern proteomics increasingly depends on computational advances to translate complex, high-dimensional data into biological knowledge. The EuBIC-MS Developers Meeting 2025 exemplifies how community-driven collaboration can directly accelerate this process by bringing together experts from bioinformatics, statistics, and experimental proteomics to co-develop open, interoperable, and reproducible analytical tools. By fostering shared software frameworks, transparent benchmarking, and collaborative problem solving, the EuBIC-MS community helps ensure that technological innovation translates into reliable biological insights. This collaborative model strengthens the foundation for quantitative, system-level understanding of proteomes and establishes a sustainable path for integrating artificial intelligence and next-generation data acquisition into routine biological discovery. This commentary shows some current highlights in the field of computational mass spectrometry and community-based approaches undertaken during the most recent Developers Meeting to solve these challenges. The approaches discussed and initiated during the meeting - ranging from deep proteome profiling and phosphosite mapping to text mining, single-cell data analysis, and FAIR metadata extraction - address key bottlenecks that currently limit the biological interpretability and comparability of proteomics data.

Mass Spectrometry

LC-IMS-MS profiling of avocado acetogenins reveals tissue-dependent distribution and cultivar-specific metabolic signatures.

This study presents a comprehensive characterisation of acetogenin-related metabolites in avocado using an LC-IMS-MS workflow. A total of 26 metabolites were semi-quantified across peel, pulp and seed tissues from three cultivars (Hass, Bacon and Fuerte). The integration of ion mobility spectrometry enabled the generation of the first experimental database of collision cross section (CCS) values for avocado acetogenins, improving confidence in metabolite annotation. Results revealed a pronounced tissue-dependent distribution, with seeds and pulp as the primary reservoir of several acetogenins, whereas the peel consistently exhibited lower concentrations. In contrast, acetogenin levels remained largely stable throughout ripening. Clear cultivar-dependent differences were observed, with Hass displaying a distinct metabolic profile compared to Bacon and Fuerte. Multivariate analysis confirmed these findings, showing tissue-dependent cultivar differentiation. This study provides new insights into avocado chemical diversity and highlights the potential of avocado by-products as consistent and promising sources of bioactive acetogenins.

Persea

Natural deep eutectic solvent in situ formation-based extraction method coupled to high-performance anion-exchange chromatography with pulsed amperometric detection for multiclass carbohydrates in hot pot bases.

A novel method was developed for the simultaneous extraction of fourteen multiclass carbohydrates from high-fat foods via the in situ formation of deep eutectic adducts from analytes and acetate ions. Different natural deep eutectic solvents (NADESs) composed of fructose and organic acids were tested as extraction solvents. A model NADES formulated with sodium acetate and fructose was characterized using Fourier transform infrared (FTIR) spectroscopy and hydrogen nuclear magnetic resonance (1H-NMR) spectroscopy. The critical extraction parameters were systematically optimized using multi-response surface methodology (MRSM) with a central composite design (CCD). The extract was analyzed using high-performance anion-exchange chromatography coupled with pulsed amperometric detection (HPAEC-PAD) using a sodium hydroxide-sodium acetate eluent, which did not require organic solvents. This approach exhibited good linearity over the concentration range of 0.02-10 mg L-1, with correlation coefficients (r) ranging from 0.9994 to 0.9999. The limits of detection and quantification were in the ranges of 0.06-0.42 mg kg-1 and 0.19-1.3 mg kg-1, respectively, which were significantly lower than those of liquid chromatography (LC). The protocol was successfully applied to the determination of fourteen carbohydrates in forty-five hotpot seasoning samples. The recoveries ranged from 86.3% to 104.1%, with relative standard deviations (RSDs) of 0.9-7.1%. By integrating multiple techniques, this strategy simplifies operations, shortens extraction time, and achieves baseline separation of three carbohydrate classes that exhibit poor resolution using a conventional LC method. This study describes an efficient procedure for the simultaneous determination of multiple trace-level carbohydrates in complex samples using HPAEC-PAD.

Journal Article

First insights into the role of evolutionary history in shaping venom composition of Vipera ammodytes.

Understanding intraspecific venom variation requires distinguishing the contributions of neutral population history from natural selection. This study aims to determine whether venom variation in Vipera ammodytes species complex is structured across eight phylogenetic groups. Despite a complex evolutionary history, venom composition did not differ among phylogenetic groups within the analytical framework used, suggesting that shared ancestry alone does not explain venom variation. Whether local adaptation to environmental conditions explains the observed variation remains an open question for future studies.

Animals

Degradation of a graphene-reinforced polyamide by fungi: When culture conditions matter.

The large-scale production, marketing and disposal of polymer-based graphene products can lead to the dispersal of graphene-enriched plastic particles into terrestrial ecosystems, where they might accumulate if not degraded by organisms. The objective of this work is to test the degradability and compatibility of one polyamide-6 polymer reinforced with reduced graphene-oxide (PA6-rGO) and its base constituents (polyamide-6, PA6; reduced graphene oxide, rGO) using mono- and co-cultures of two lignin-degrading fungi (Bjerkandera adusta and Morchella esculenta) grown under different nutrient conditions. Fungal (co-)cultures were exposed to pure rGO or abraded powders of PA6 and PA6-rGO in two different liquid media, and monitored over time for biomass growth, H2O2 production, and activity of two lignolytic enzymes (i.e., Laccase, Lac, and Lignin peroxidase, LiP). The changes in polyamide structure were evaluated by proton nuclear magnetic resonance and mass spectrometry, and changes in rGO were evaluated by Raman spectroscopy. The materials had no effect on fungal growth. PA6 increased Lac secretion only in low nutrient medium, while PA6-rGO slightly suppressed LiP activity. Only M. esculenta promoted polyamides oxidation when cultured in a low nutrient medium, as evidenced by a change in mass distribution values (m/z: 400-420) and the appearance of a new resonance peak (at 5.37 ppm). Lignolytic exudates in co-cultures low in nutrients caused a greater change in rGO, as shown by the increase in the ID/IG ratio. The degradation of rGO, PA6 and PA6-rGO depended on culture conditions.

Graphite

Influence of nicotine on protein expression around hydrophilic osseointegrated implants: A proteomic study in male rats.

OBJECTIVE: To ensure the success of dental implant treatment, various factors must be considered, including osseointegration and systemic conditions. There is evidence in the literature that smokers may exhibit alterations in tissue healing, which can compromise the success of implant rehabilitation. Therefore, this study aimed to investigate the influence of nicotine on the protein profile of bone tissue around hydrophilic implants during the osseointegration process in rats. DESIGN: Bone tissue samples from the control and nicotine groups (n&#x202f;=&#x202f;3 per group) were subjected to protein extraction, mass spectrometry, and bioinformatic analyses. Protein identification was performed using Proteome Discoverer 2.1 software and the SEQUEST algorithm, and the protein data were compared with those of a protein database of Rattus norvegicus obtained from UniProt. RESULTS: A total of 740 proteins were detected in both the control group and the nicotine-exposed group. Among them, the proteins biglycan, periostin and histone H4 were highlighted because of their higher abundance in the healthy implant group, while they were reduced in the nicotine-exposed group. CONCLUSIONS: Nicotine has the potential to alter the protein profile of bone tissue around hydrophilic implants during osseointegration, which may impair tissue remodeling and healing.

Animals

Occupationally relevant vibrations and the brain: frequency-dependent proteomics signatures in a rat model.

INTRODUCTION: Occupational exposure to whole-body vibration (WBV), particularly in agricultural environments, has been associated with adverse cognitive and physiological effects. This study examined the neurophysiological impact of WBV in a rat model at 4&#x202f;Hz and 30&#x202f;Hz, frequencies representative of off-road and on-road vehicle operation. METHODOLOGY: Forty-four Sprague-Dawley rats were assigned to control (0&#x202f;Hz), low-frequency (4&#x202f;Hz), or high-frequency (30&#x202f;Hz) vibration conditions. After three days of exposure, brain tissues were collected and analyzed using mass spectrometry-based proteomics to identify differentially expressed proteins. RESULTS: Proteomic profiling revealed distinct, frequency-dependent alterations in brain protein expression. Compared with controls, 32 cognition-related proteins were differentially regulated at 4&#x202f;Hz and 29 at 30&#x202f;Hz, with 13 differing between the two vibration conditions. Principal component analysis showed clear separation among groups, indicating unique proteomic signatures for each exposure frequency. Functional enrichment and protein-protein interaction analyses demonstrated involvement of synaptic plasticity, cytoskeletal organization, calcium regulation, and neurotransmitter release. Exposure to 4 Hz was associated with the upregulation of proteins involved in calcium homeostasis and synaptic integrity, suggesting potential disruption of cognitive processes. In contrast, 30 Hz increased the expression of proteins related to axonal guidance and neuroprotection, indicating a less clearly adverse response that may reflect adaptive or potentially beneficial effects. DISCUSSION: These findings provide new insight into biological mechanisms underlying WBV-induced cognitive changes and underscore the importance of vibration frequency in shaping neurophysiological outcomes. They also establish a foundation for future studies integrating proteomics with behavioural assessments in animals and humans.

Animals

Proteomics in environmental pollution research: Advances, challenges, and future directions.

Environmental proteomics has emerged as a powerful approach for elucidating the molecular mechanisms underlying pollutant-induced biological effects. Although this field has developed rapidly, the systematic review of recent proteomics applications in environmental pollution research remains limited. This review explored the emerging roles of toxicoproteomics in biomarker discovery and mechanistic elucidation, as well as ecotoxicoproteomics in ecological risk assessment and bioremediation strategies. Here, we review the field, highlighting recent trends such as the integration of proteomics with genomics, transcriptomics, and metabolomics to provide a comprehensive view of biological responses to environmental stressors. We further discuss the growing application of artificial intelligence in improving proteomics data interpretation and accelerating biomarker discovery. In addition, recent technological advances in environmental proteomics are highlighted, including next-generation tissue microarray proteomics, nanoscale proteomics, single-cell proteomics, and spatial proteomics. Despite its potential, proteomics faces challenges, such as high operational costs, computational complexity in analysis, and technical limitations in low-abundance protein detection. We propose that the convergence of proteomics with artificial intelligence and multi-omics approaches offers promising solutions to these challenges, enhancing the practical application of proteomics in environmental monitoring and risk assessment.

Proteomics

Routine methods misidentify Serratia spp.: Limitations of MALDI-TOF MS revealed by whole-genome sequencing.

Accurate species-level identification within the genus Serratia remains challenging due to extensive phenotypic overlap and high genomic relatedness among closely related and recently described taxa. This study presents an evaluation of routine and genome-based identification approaches applied to clinical Serratia isolates, integrating phenotypic assays, MALDI-TOF MS (Bruker Daltonics), 16S rRNA gene sequencing, and Whole-Genome Sequencing (WGS). A total of 103 isolates collected from a teaching hospital were analyzed. WGS was performed on a subset of isolates. Conventional biochemical methods classified all isolates as Serratia marcescens, whereas MALDI-TOF MS identified 60.1% as S. marcescens, 11.6% as S. ureilytica, and 28.1% just at the genus level. Peak analysis from MALDI-TOF MS revealed specific peaks associated with S. marcescens and S. ureilytica, but limited discriminatory power. WGS of six isolates initially identified as S. ureilytica by MALDI-TOF MS revealed reclassification as Serratia sarumanii (n = 5) and Serratia montpellierensis (n = 1), supported by Average Nucleotide Identity (ANI), Average Amino Acid Identity (AAI), and Digital DNA-DNA Hybridization (dDDH) thresholds. In contrast, 16S rRNA analysis showed limited species-level resolution. Phylogenomic and SNP-based analyses confirmed these classifications with strong support. Overall, this study underscores the critical role of high-resolution genomic approaches for precise species identification and highlights the need for continuous expansion and curation of MALDI-TOF MS reference databases to support reliable clinical diagnostics and epidemiological surveillance of emerging Serratia species.

Spectrometry, Mass, Matrix-Assisted Laser Desorpti

Metabolomics and genomics reveal high diversity and concentrations of cyanopeptides during a Microcystis bloom.

Cyanobacterial blooms are an immense global problem that release complex mixtures of poorly characterized biologically active cyanopeptides into freshwater. In this study, metabolomics and genomics were used to assess the diversity and concentrations of cyanopeptides during a dense Microcystis bloom during the late summer of 2023 in Lake Champlain, a large transboundary lake situated between Canada and the United States. Despite the relatively low genetic diversity of the bloom determined by 16S rRNA metabarcoding, 151 cyanopeptides were detected by non-targeted metabolomics. This represents the most recorded cyanopeptides from a single lake plankton bloom event to date. Fifty-two cyanopeptides were previously reported and 99 represent putative new structures. Standards from the microcystin, cyanopeptolin, microginin, and anabaenopeptin groups were used to either quantify or approximate respective cyanopeptide concentrations over the sampling period. Cyanopeptolins were the most diverse (n&#x202f;=&#x202f;68) cyanopeptides and the second most abundant, reaching 12,892&#x202f;&#x3bc;g/L. Microginins were the second most diverse (n&#x202f;=&#x202f;24) and reached the highest concentrations (18,262&#x202f;&#x3bc;g/L). Anabaenopeptins were the third most diverse (n&#x202f;=&#x202f;17) cyanopeptides, reaching 4,818&#x202f;&#x3bc;g/L. Only 8 microcystins were detected, reaching 4,935&#x202f;&#x3bc;g/L, where MC-LR was the dominant congener. Target cyanopeptide biosynthesis genes for microcystins (mcyE), cyanopeptolins (mcnC), anabaenopeptins (apnD), microviridins (mdnC), and aeruginosins (aerA) were also quantified using digital droplet PCR (ddPCR). The gene copy numbers for mcyE, mcnC, and apnD were highly correlated with their corresponding cyanopeptide concentrations. Overall, the studied Microcystis bloom produced a very diverse cyanopeptide mixture with high cyanopeptide concentrations including non-microcystin groups.

Microcystis

Evaluation of three Aspergillus antibody assays for screening of chronic pulmonary aspergillosis: prospective diagnostic accuracy study.

OBJECTIVES: Chronic pulmonary aspergillosis (CPA) is a frequent complication of pulmonary tuberculosis (PTB), particularly in high-burden settings where access to reliable serological diagnostics remains limited. We evaluated the diagnostic performance of two immunochromatographic technology (ICT) lateral flow assays (LFAs) and an ELISA for CPA screening among patients with active or previously treated PTB. METHODS: In this two-year prospective multicentre diagnostic evaluation, serum from adults with prior or active PTB was tested using the Era Biology Aspergillus IgG ICT LFA, LDBio Aspergillus IgG/IgM ICT LFA, and Bordier Aspergillus fumigatus IgG ELISA. CPA diagnosis was established using a consensus composite reference standard incorporating clinical, immunological, radiological, and microbiological criteria. The Bordier ELISA was used as part of the immunological component of the consensus CPA diagnosis, with a cutoff optical density of &#x2265;1.0. Diagnostic accuracy, agreement statistics, receiver operating characteristic analysis, and latent class analysis (LCA) were performed. RESULTS: Among 340 participants, 24 (7.06%) had CPA. Proportion of participants with positive antibody tests among all tested individuals were 6.76% for LDBio ICT LFA, 20.0% for Era Biology ICT LFA, and 11.47% for Bordier ELISA. Against consensus CPA diagnosis, Bordier ELISA showed 87.50% sensitivity and 94.30% specificity, LDBio ICT LFA 58.33% sensitivity and 97.15% specificity, and Era Biology LFA 66.67% sensitivity and 83.54% specificity. LCA estimated CPA prevalence at 7.72%. LCA-derived sensitivities and specificities were 86.58% and 99.92% for LDBio ICT LFA, 83.39% and 85.31% for Era Biology LFA, and 79.10% and 94.19% for Bordier ELISA. CONCLUSIONS: The Bordier ELISA showed high sensitivity and specificity, while the LDBio ICT LFA demonstrated very high specificity with strong LCA-derived performance. These findings support the use of ELISA for laboratory diagnosis and ICT as a point-of-care screening tool for CPA in resource-limited settings. Era Biology Aspergillus IgG LFA demonstrated moderate sensitivity and acceptable diagnostic performance, indicating its potential utility as a supplementary screening assay for CPA in settings where rapid, point-of-care testing is required.

Humans

Comparative evaluation of molecular technologies for the identification of prevalent non-tuberculous mycobacteria in pulmonary infections: a systematic review and meta-analysis.

BACKGROUND: The increasing prevalence of non-tuberculous mycobacteria pulmonary disease (NTM PD) is a burden to public health. Successful management of NTM PD critically depends on accurate species identification and reliable drug susceptibility testing to guide appropriate antibiotic therapy. Emerging molecular technologies offer rapid diagnostic solutions compared to conventional methods, but their performance varies. This study aims to provide a comprehensive evaluation of current molecular techniques for NTM identification and to present a global antibiotic resistance profile. METHODS: A systematic literature search was conducted in PubMed and Web of Science for studies published between 2005 and 2024. Studies applying molecular methods for NTM identification and resistance detection in humans were included. Data on study characteristics, diagnostic methods, sample types, sample sizes, identification sensitivity, and drug susceptibility results were extracted. Meta-analysis was performed using R with the meta4diag package. The quality of included studies was assessed using the QUADAS-2 tool. RESULTS: The analysis included 49 studies on NTM identification and 33 studies on antibiotic resistance. For species identification, all evaluated molecular technologies (MALDI-TOF MS, PCR-based methods, Sequencing, DNA chip, and DNA strip) demonstrated high pooled sensitivities (>0.92). Subgroup analysis revealed that sample type significantly affected performance for MALDI-TOF MS. Preliminary analysis of antibiotic resistance rates revealed varying patterns. For slowly growing mycobacteria, a significantly high Ethambutol resistance rate was observed in M. avium (69.20%). Among rapidly growing mycobacteria, resistance to Imipenem was notable (54.22%), and Clarithromycin resistance varied significantly within the Mycobacterium abscessus complex. CONCLUSION: Emerging molecular technologies have revolutionized the methodology for NTM identification with excellent performance. However, their performance can be influenced by sample type, particularly for MALDI-TOF MS. The alarming and heterogeneous antibiotic resistance patterns also highlight the critical need for rapid and accurate species identification and drug susceptibility testing to inform effective therapeutic strategies. Key messagesMolecular technologies demonstrate high accuracy for NTM identification.Antibiotic resistance is a serious concern with variations among NTM species and subspecies.Rapid and accurate species identification and drug susceptibility testing are crucial for guiding effective clinical management of NTM PD.

Humans