RESUMEN

Microorganisms are closely associated with human diseases and health. Understanding the composition and function of microbial communities requires extensive research. Metaproteomics has recently become an important method for throughout and in-depth study of microorganisms. However, major challenges in terms of sample processing, mass spectrometric data acquisition, and data analysis limit the development of metaproteomics owing to the complexity and high heterogeneity of microbial community samples. In metaproteomic analysis, optimizing the preprocessing method for different types of samples and adopting different microbial isolation, enrichment, extraction, and lysis schemes are often necessary. Similar to those for single-species proteomics, the mass spectrometric data acquisition modes for metaproteomics include data-dependent acquisition (DDA) and data-independent acquisition (DIA). DIA can collect comprehensive peptide information from a sample and holds great potential for future development. However, data analysis for DIA is challenged by the complexity of metaproteome samples, which hinders the deeper coverage of metaproteomes. The most important step in data analysis is the construction of a protein sequence database. The size and completeness of the database strongly influence not only the number of identifications, but also analyses at the species and functional levels. The current gold standard for metaproteome database construction is the metagenomic sequencing-based protein sequence database. A public database-filtering method based on an iterative database search has been proven to have strong practical value. The peptide-centric DIA data analysis method is a mainstream data analysis strategy. The development of deep learning and artificial intelligence will greatly promote the accuracy, coverage, and speed of metaproteomic analysis. In terms of downstream bioinformatics analysis, a series of annotation tools that can perform species annotation at the protein, peptide, and gene levels has been developed in recent years to determine the composition of microbial communities. The functional analysis of microbial communities is a unique feature of metaproteomics compared with other omics approaches. Metaproteomics has become an important component of the multi-omics analysis of microbial communities, and has great development potential in terms of depth of coverage, sensitivity of detection, and completeness of data analysis.

Asunto(s)

RESUMEN

BACKGROUND: Maternal exposure to metals may pose a risk to the health of newborns, however, the underlying mechanisms remain ambiguous. Herein, we aimed to investigate the influence of metals exposure on birth outcomes and reveal the importance of metabolites in the exposure-outcomes association by using metabolomics methods. METHODS: In our study, 292 mother-pairs were included who were recruited from the affiliated hospitals of Nanjing Medical University between 2006 and 2011. We measured fifteen metals (mercury, lead, vanadium, arsenic, zinc, cadmium, rubidium, copper, cobalt, iron, molybdenum, strontium, thallium, magnesium and calcium) and metabolites in maternal second trimester serums by using inductively coupled plasma mass spectrometry and ultra-high performance liquid chromatography high resolution accurate mass spectrometry, respectively. A multi-step statistical analysis strategy including exposome-wide association study (ExWAS) model, variable selection models and multiple-exposure models were performed to systematically appraise the associations of individual and mixed metals exposure with birth outcomes. Furthermore, differential metabolites that associated with metals exposure and birth outcomes were identified using linear regression models. RESULTS: Metal's levels in maternal serums ranged from 0.05 µg/L to 1864.76 µg/L. In the ExWAS model, maternal exposure to arsenic was negatively associated with birth weight (ß = 188.83; 95% CI: -368.27, -9.39), while maternal mercury exposure showed a positive association (ß = 533.65; 95%CI: 179.40, 887.90) with birth weight. Moreover, each unit increase in mercury (1 ng/mL-log transformed) was associated with a 1.82 week-increase (95%CI: 0.85, 2.79) in gestational age. These findings were subsequently validated by variable selection models and multiple exposure models. Metabolomic analysis further revealed the significant role of 3-methyladenine in the relationship between arsenic exposure and birth weight. CONCLUSION: This study provides new epidemiological evidence indicating the associations of metals exposure and neonatal birth outcomes, and emphasizes the potential role of metabolite biomarkers and their importance in monitoring adverse birth outcomes.

Asunto(s)

RESUMEN

Introduction: Phellodendri Chinensis Cortex is a necessary part of healthcare for its significant clinical efficacy. Raw and processed Phellodendri Chinensis Cortex is both documented in the Chinese Pharmacopoeia (2015). After processing, the therapeutic effects are believed to differ according to traditional Chinese medicine theories. However, the chemical mechanism responsible for this processing, according to traditional Chinese medicine theories, is still not clear. Methods: In this study, the therapeutic effects of various ions were examined based on traditional Chinese medicine theories by ultra-high performance liquid chromatography-hybrid quadrupole-Orbitrap mass spectrometry (UHPLC-Q-Orbitrap MS) coupled with multivariate statistical analysis, such as principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA), to comprehensively compare the differences between raw and processed Phellodendri Chinensis Cortex for the first time. Results: A total of 48 compounds were screened, out and 10 of them simultaneously transformed with significant variation in processed products compared with raw materials. It was illustrated that the contents of berberine, palmatine, jatrorrhizine, magnoflorine, menisperine, phellodendrine, tetrahydrojatrorrhizine, and tetrahydropalmatine decreased, while the compounds of berberrubine and fernloylquinic acid methyl ester newly appeared in processed herbs. This is likely to be related to the conversion of ingredients during processing. Discussion: Altogether, the fact that quality markers have been successfully identified to differentiate processed Phellodendri Chinensis Cortex from raw materials suggests that this approach could be used for the investigation of chemical transformation mechanisms involved in the processing of herbal medicine.

RESUMEN

Accurately and high-thoroughly screening illegal additives in health-care foods continues to be a challenging task in routine analysis for the ultrahigh performance liquid chromatography-high resolution mass spectrometry based techniques. In this work, we proposed a new strategy to identify additives in complex food matrices, which consists of both experimental design and advanced chemometric data analysis. At first, reliable features in the analyzed samples were screened based on a simple but efficient sample weighting design, and those related to illegal additives were screened with robust statistical analysis. After the MS1 in-source fragment ion identification, both MS1 and MS/MS spectra were constructed for each underlying compound, based on which illegal additives can be precisely identified. The performance of the developed strategy was demonstrated by using mixture and synthetic sample datasets, indicating an improvement of data analysis efficiency up to 70.3 %. Finally, the developed strategy was applied for the screening of unknown additives in 21 batches of commercially available health-care foods. Results indicated that at least 80 % of false-positive results can be reduced and 4 additives were screened and confirmed.

Asunto(s)

RESUMEN

Compound Kushen injection (CKI) is a kind of sterilised water-soluble traditional Chinese medicine preparation that has been used for the clinical treatment of a variety of cancers (hepatocellular carcinoma, lung cancer, etc.) for 19 years. However, to date, the metabolism-related study on CKI in vivo has not been conducted.An integrated analytical strategy was established to investigate the metabolic profile of alkaloids of CKI in rat plasma, urine, and faeces based on ultra-high performance liquid chromatography-electrospray quadrupole time-of-flight mass spectrometry in MSE mode (UHPLC-ESI-QTOF/MSE).Nineteen prototype alkaloids (including 12 matrine-type alkaloids, 2 cytisine-type alkaloids, 3 lupinine-type alkaloids, and 2 aloperine-type alkaloids) of CKI were identified in vivo. Furthermore, 71 metabolites of alkaloids (including 11 of lupanine-related metabolites, 14 of sophoridine-related metabolites, 14 of lamprolobine-related metabolites, and 32 of baptifoline-related metabolites) were tentatively characterised. Metabolic pathways involved in the metabolism of phase I (include oxidation, reduction, hydrolysis, and desaturation), phase II (mainly include glucuronidation, acetylcysteine or cysteine conjugation, methylation, acetylation, and sulphation), and associated combination reactions.The integrated analytical strategy was successfully used to characterise the prototype alkaloids and their metabolites of CKI in vivo, and the results laying a foundation for further study its pharmacodynamic substances.

Asunto(s)

RESUMEN

Amplicon sequencing of bacterial or fungal marker sequences is currently the main method for the study of endophytic microorganisms in plants. However, it cannot obtain all types of microorganisms, including bacteria, fungi, protozoa, etc., in samples, nor compare the relative content between endophytic microorganisms and plants and between different types of endophytes. Therefore, it is necessary to develop a better analysis strategy for endophytic microorganism investigation. In this study, a new analysis strategy was developed to obtain endophytic microbiome information from plant transcriptome data. Results showed that the new strategy can obtain the composition of microbial communities and the relative content between plants and endophytic microorganisms, and between different types of endophytic microorganisms from the plant transcriptome data. Compared with the amplicon sequencing method, more endophytic microorganisms and relative content information can be obtained with the new strategy, which can greatly broaden the research scope and save the experimental cost. Furthermore, the advantages and effectiveness of the new strategy were verified with different analysis of the microbial composition, correlation analysis, inoculant content test, and repeatability test.

Asunto(s)

RESUMEN

Flower and fruit colors are important agronomic traits. To date, there is no forward genetic evidence that the glutathione S-transferase (GST) gene is responsible for the white flower color in peach (Prunus persica). In this study, genetic analysis indicated that the white-flower trait is monogenetic, is recessive to the non-white allele, and shows pleiotropic effects with non-white-flowered types. The genetic locus underpinning this trait was mapped onto chromosome 3 between 0.421951 and 3.227115 Mb by using bulked segregant analysis in conjunction with whole-genome sequencing, and was further mapped between 0 and 1.178149 Mb by using the backcross 1 (BC1 ) population. Finally, the locus was fine-mapped within 535.974- and 552.027-kb intervals by using 151 F2 individuals and 75 individuals from a BC1 self-pollinated (BC1 S1 ) population, respectively. Pp3G013600, encoding a GST that is known to transport anthocyanin, was identified within the mapping interval. The analysis of genome sequence data showed Pp3G013600 in white flowers has a 2-bp insertion or a 5-bp deletion in the third exon. These variants likely render the GST non-functional because of early stop codons that reduce the protein length from 215 amino acids to 167 and 175 amino acids, respectively. Genetic markers based on these variants validated a complete correlation between the GST loss-of-function alleles and white flower in 128 peach accessions. This correlation was further confirmed by silencing of Pp3G013600 using virus-induced gene silencing technology, which reduced anthocyanin accumulation in peach fruit. The new knowledge from this study is useful for designing peach breeding programs to generate cultivars with white flower and fruit skin.

Asunto(s)

RESUMEN

Traditional Chinese medicines (TCMs) have attracted more attentions in the treatment of depression. Xiaoyaosan (XYS), a classic anti-depression TCM prescription, contains eight herbs. However, the compatibility effects of XYS in modern pharmacology need to be investigated in depth. In this study, the chronic unpredictable mild stress (CUMS) depression-like model was constructed. Afterwards, XYS was divided into the Shugan and the Jianpi groups according to the research strategy ofefficacy groups. Meanwhile, a proton nuclear magnetic resonance spectrometry (1H NMR) based serum metabolomics was applied. XYS and its efficacy groups significantly regulated the abnormal levels of differential metabolites related to depression, but to different degrees. Metabolic profiling by orthogonal partial least squares discriminant analysis showed that XYS at high dose (XH) exhibited the strongest effects than other treatment groups. Ten metabolites related to depression were identified as differential metabolites. Besides, relative distance (Rd) was calculated to quantitatively evaluate the effects. We found that XH group had the highest Rd value. Moreover, among the five metabolic pathways of depression, XYS and Jianpi groups significantly regulated all pathways while Shugan group regulated four pathways. These findings lay a solid foundation for comprehensively and deeply understanding the compatibility effects of XYS against depression.

Asunto(s)

RESUMEN

BACKGROUND: Vitexin is a natural flavonoid compound with multiple pharmacological activities and is extracted from the leaves and seeds of Vitex negundo L. var. cannabifolia (Sieb. et Zucc.) Hand.-Mazz. However, the metabolite characterization of this component remains insufficient. OBJECTIVE: To establish a rapid profiling and identification method for vitexin metabolites in rat urine, plasma and faeces after oral administration using a UHPLC-Q-Exactive orbitrap mass spectrometer were coupled with multiple data-mining methods. METHODS: In this study a simple and rapid systematic strategy for the detection and identification of constituents was proposed based on UHPLC-Q-Exactive Orbitrap mass spectrometry in parallel reaction monitoring mode combining diagnostic fragment ion filtering techniques. RESULTS: A total of 49 metabolites were fully or partially characterized based on their accurate mass, characteristic fragment ions, retention times, corresponding ClogP values, and so on. It is obvious that C-glycosyl flavonoids often display an [M+H-120]+ ion that represents the loss of C4H8O4. As a result, these metabolites were presumed to be generated through glucuronidation, sulfation, deglucosylation, dehydrogenation, methylation, hydrogenation, hydroxylation, ring cleavage and their composite reactions. Moreover, the characteristic fragmentation pathways of flavonoids, chalcones and dihydrochalcones were summarized for the subsequent metabolite identification. CONCLUSION: The current study provided an overall metabolic profile of vitexin which will be of great help in predicting the in vivo pharmacokinetic profiles and understanding the action mechanism of this active ingredient.

Asunto(s)

RESUMEN

Surface-Enhanced Raman Scattering (SERS) is a powerful technology that provides abundant chemical fingerprint information with advantages of high sensitivity and time-saving. Advancements in SERS substrates fabrication allow Ag nanorods (AgNRs) possess superior sensitivity, high uniformity, and excellent reproducibility. To further promote AgNRs as a promising SERS substrate candidate to a broader application scope, oxides are integrated with AgNRs by virtue of their unique properties which endow the AgNRs-oxide hybrid with high stability and recyclability. Aside from SERS substrates fabrication, significant developments in quantitative analysis strategies offer enormous approaches to minimize influences resulted from variations of measuring conditions and to provide the reasonable data analysis. In this review, we discuss various fabrication approaches for AgNRs and AgNRs-oxide hybrids to achieve efficient SERS platforms. Then, we introduce three types of strategies which are commonly employed in chemical quantitative analysis to reach a reliable result. Further, we highlight SERS applications including food safety, environment safety, biosensing, and vapor sensing, demonstrating the potential of SERS as a powerful and promising technique. Finally, we conclude with the current challenges and future prospects toward efficient SERS manipulations for broader real-world applications.

RESUMEN

In this study, a novel analysis strategy for progressively targeted screening and characterization of drug ingredients from in vitro to in vivo was proposed based on ultra-high performance liquid chromatography-tandem mass spectrometry for comprehensive characterization of in vivo metabolic profile of Polygalae radix (PR). First, an in vitro chemical profile of PR was described with the assistance of UNIFI™ software. The characteristic neutral small molecule losses were summarized to distinguish different chemical structures in the PR extract. Second, the in vitro intestinal microflora metabolism model was applied to describe an in vitro metabolic profile of the main ingredients of PR. The metabolic rule and metabolites were integrated for subsequent targeted screening of metabolites in vivo. Finally, an integrated strategy was established and applied to screen and characterize the major absorbed components in vivo, including blood, urine, brain, feces, and liver, based on the prototypes and metabolic rules obtained in vitro. As a result, in vitro and in vivo metabolic profiles of PR were effectively depicted. A total of 136 compounds were isolated and identified from the crude extract in vitro, and 12 compounds were reported for the first time based on the proposed fragmentations. A total of 13, 32, and 3 compounds were identified and characterized in the dosed plasma, liver, and brain, respectively. A total of 40 and 73 compounds were identified in urine and feces, respectively. This strategy not only provided a comprehensive insight into the chemical and metabolic profiles of PR but also presented a new perspective for the discovery of new drugs for medicinal application.

Asunto(s)

RESUMEN

Recent developments in genomics and proteomics enable the discovery of biomarkers that allow identification of subgroups of patients responding well to a treatment. One currently used clinical trial design incorporating a predictive biomarker is the so-called biomarker strategy design (or marker-based strategy design). Conventionally, the results from this design are analysed by comparing the mean of the biomarker-led arm with the mean of the randomised arm. Several problems regarding the analysis of the data obtained from this design have been identified in the literature. In this paper, we show how these problems can be resolved if the sample sizes in the subgroups fulfil the specified orthogonality condition. We also propose a different analysis strategy that allows definition of test statistics for the biomarker-by-treatment interaction effect as well as for the classical treatment effect and the biomarker effect. We derive equations for the sample size calculation for the case of perfect and imperfect biomarker assays. We also show that the often used 1:1 randomisation does not necessarily lead to the smallest sample size. In addition, we provide point estimators and confidence intervals for the treatment effects in the subgroups. Application of our method is illustrated using a real data example.

Asunto(s)

RESUMEN

The technique of reverse sequence-specific oligonucleotide probes (SSOPs) is commonly used in human leukocyte antigen (HLA) typing. In the conventional method for data analysis (exact pattern matching, EPM), the larger is the number of mismatched probes, the longer the time for final typing assignment. A novel strategy, filtering and scoring (FnS), has been developed to easily assign the best-fit allele pair. In the FnS method, candidate alleles and allele pairs were filtered based on (1) subject's ethnicity, and (2) the measured partial reaction pattern with only definitely negative or positive probes. Then, the complete reaction pattern for all probes (CRPoAPs) were compared between the raw sample and expected residual allele pairs to obtain mismatch scores. To compare the FnS and EPM methods, each analysis time (minutes:seconds) for reverse SSOP HLA typing with intermediate resolution (n = 507) was measured. The analysis time with FnS method was shorter than that of the EPM method [00:21 (00:08-01:47) and 01:04 (00:15-23:45), respectively, P < .05]. In addition, the analysis time of the FnS method was relatively constant, regardless of the number of mismatched probes. The alternative approach of filtering based only on definite probes (neglecting ethnicity) took a long time for analysis. However, this approach did not compromise the accuracy. The FnS method showed improved accuracy and efficiency of HLA typing in a comprehensive and quantitative comparison between measured and expected CRPoAPs of candidate allele pairs. Therefore, this analysis strategy might be useful in a clinical setting.

Asunto(s)

RESUMEN

Annual prevalence of the use of common illicit drugs and new psychoactive substances (NPS) is high, despite the often limited knowledge on the health risks of these substances. Recently, cortical cultures grown on multi-well microelectrode arrays (mwMEAs) have been used for neurotoxicity screening of chemicals, pharmaceuticals, and toxins with a high sensitivity and specificity. However, the use of mwMEAs to investigate the effects of illicit drugs on neuronal activity is largely unexplored. We therefore first characterised the cortical cultures using immunocytochemistry and show the presence of astrocytes, glutamatergic and GABAergic neurons. Neuronal activity is concentration-dependently affected following exposure to six neurotransmitters (glutamate, GABA, serotonin, dopamine, acetylcholine and nicotine). Most neurotransmitters inhibit neuronal activity, although glutamate and acetylcholine transiently increase activity at specific concentrations. These transient effects are not detected when activity is determined during the entire 30min exposure window, potentially resulting in false-negative results. As expected, exposure to the GABAA-receptor antagonist bicuculline increases neuronal activity. Exposure to a positive allosteric modulator of the GABAA-receptor (diazepam) or to glutamate receptor antagonists (CNQX and MK-801) reduces neuronal activity. Further, we demonstrate that exposure to common drugs (3,4-methylenedioxymethamphetamine (MDMA) and amphetamine) and NPS (1-(3-chlorophenyl)piperazine (mCPP), 4-fluoroamphetamine (4-FA) and methoxetamine (MXE)) decreases neuronal activity. MXE most potently inhibits neuronal activity with an IC50 of 0.5µM, whereas 4-FA is least potent with an IC50 of 113µM. Our data demonstrate the importance of analysing neuronal activity within different time windows during exposure to prevent false-negative results. We also show that cortical cultures grown on mwMEAs can successfully be applied to investigate the effects of different (illicit) drugs on neuronal activity. Compared to investigating multiple single endpoints for neurotoxicity or neuromodulation, such as receptor activation or calcium channel function, mwMEAs can provide information on integrated aspects of drug-induced neurotoxicity more rapidly. Therefore, this approach could contribute to a faster insight in possible health risks and shorten the regulation process.

Asunto(s)

RESUMEN

INTRODUCTION: Powder-like extract of Ricinus communis seeds contain a toxic protein, ricin, which has a history of military, criminal and terroristic use. As the detection of ricin in this "terrorist powder" is difficult and time-consuming, related low mass metabolites have been suggested to be useful for screening as biomarkers of ricin. OBJECTIVE: To apply a comprehensive NMR-based analysis strategy for annotation, isolation and structure elucidation of low molecular weight plant metabolites of Ricinus communis seeds. METHODOLOGY: The seed extract was prepared with a well-known acetone extraction approach. The common metabolites were annotated from seed extract dissolved in acidic solution using (1)H NMR spectroscopy with spectrum library comparison and standard addition, whereas unconfirmed metabolites were identified using multi-step off-line HPLC-DAD-NMR approach. RESULTS: In addition to the common plant metabolites, two previously unreported compounds, 1,3-digalactoinositol and ricinyl-alanine, were identified with support of MS analyses. CONCLUSION: The applied comprehensive NMR-based analysis strategy provided identification of the prominent low molecular weight metabolites with high confidence.

Asunto(s)

RESUMEN

This review briefly summarises some of the definitive studies of articular cartilage by microscopic MRI (µMRI) that were conducted with the highest spatial resolutions. The article has four major sections. The first section introduces the cartilage tissue, MRI and µMRI, and the concept of image contrast in MRI. The second section describes the characteristic profiles of three relaxation times (T1, T2 and T1ρ) and self-diffusion in healthy articular cartilage. The third section discusses several factors that can influence the visualisation of articular cartilage and the detection of cartilage lesion by MRI and µMRI. These factors include image resolution, image analysis strategies, visualisation of the total tissue, topographical variations of the tissue properties, surface fibril ambiguity, deformation of the articular cartilage, and cartilage lesion. The final section justifies the values of multidisciplinary imaging that correlates MRI with other technical modalities, such as optical imaging. Rather than an exhaustive review to capture all activities in the literature, the studies cited in this review are merely illustrative.

RESUMEN

Objective To study the cerebral infarction patients with psychological problems,so that patients maintain the best psychological state,actively cooperate with the treatment of disease and recover early. Methods 90 eases of cerebral infarction patients by age group is divided into youth and old age group. From the perspective of their care from clinical data,looking for different age groups of patients with psychological problems,for different psychological problems,with psychological support,psychological counseling and active listening to the method of kneading and the patients with psychological support. Results The psychological state of patients with cerebral infarction and age are closely related. Conclusion According to different ages for different psychological care to patients with cerebral infarction implementation of the measures can effectively reduce the complications and sequel someway, improving the quality of life earlier.